Authors:Sandra Huerta-Moro, Oscar Martínez-Fuentes, Victor Rodolfo Gonzalez-Diaz, Esteban Tlelo-Cuautle First page: 33 Abstract: This work shows the voltage regulation of a DC–DC buck converter by applying sliding mode control using three different cases of sliding surfaces. The DC–DC buck converter is modeled by ordinary differential equations (ODEs) that are solved by applying numerical methods. The ODEs describe two state variables that are associated to the capacitor voltage and the inductor current. The state variable associated to voltage is regulated by applying two well-known sliding surfaces and a third one that is introduced herein to improve the response of the sliding mode control. The stability of the proposed sliding surface is verified by using a Lyapunov theorem to guarantee closed-loop stability. Finally, simulation results show the improvement of voltage regulation when applying the proposed sliding surface compared to already reported approaches. Citation: Technologies PubDate: 2023-02-23 DOI: 10.3390/technologies11020033 Issue No:Vol. 11, No. 2 (2023)
Authors:Ioannis D. Bougas, Maria S. Papadopoulou, Achilles D. Boursianis, Spyridon Nikolaidis, Sotirios K. Goudos First page: 34 Abstract: Radio-frequency (RF) energy harvesting (EH) is emerging as a reliable and constantly available free energy source. The primary factor determining whether this energy can be utilized is how efficiently it can be collected. In this work, an RF EH system is presented. More particularly, we designed a dual-band RF to DC rectifier circuit at sub-6 GHz in the 5G bands, able to supply low-power sensors and microcontrollers used in agriculture, the military, or health services. The system operates at 3.5 GHz and 5 GHz in the 5G cellular network’s frequency band FR1. Numerical results reveal that the system provides maximum power conversion efficiency (PCE) equal to 53% when the output load (sensor or microcontroller) is 1.74 kΩ and the input power is 12 dBm. Citation: Technologies PubDate: 2023-02-24 DOI: 10.3390/technologies11020034 Issue No:Vol. 11, No. 2 (2023)
Authors:Salvatore Brischetto, Domenico Cesare, Roberto Torre First page: 35 Abstract: In this work, a coupled 3D thermo-elastic shell model is presented. The primary variables are the scalar sovra-temperature and the displacement vector. This model allows for the thermal stress analysis of one-layered and sandwich plates and shells embedding Functionally Graded Material (FGM) layers. The 3D equilibrium equations and the 3D Fourier heat conduction equation for spherical shells are put together into a set of four coupled equations. They automatically degenerate in those for simpler geometries thanks to proper considerations about the radii of curvature and the use of orthogonal mixed curvilinear coordinates α, β, and z. The obtained partial differential governing the equations along the thickness direction are solved using the exponential matrix method. The closed form solution is possible assuming simply supported boundary conditions and proper harmonic forms for all the unknowns. The sovra-temperature amplitudes are directly imposed at the outer surfaces for each geometry in steady-state conditions. The effects of the thermal environment are related to the sovra-temperature profiles through the thickness. The static responses are evaluated in terms of displacements and stresses. After a proper and global preliminary validation, new cases are presented for different thickness ratios, geometries, and temperature values at the external surfaces. The considered FGM is metallic at the bottom and ceramic at the top. This FGM layer can be embedded in a sandwich configuration or in a one-layered configuration. This new fully coupled thermo-elastic model provides results that are coincident with the results proposed by the uncoupled thermo-elastic model that separately solves the 3D Fourier heat conduction equation. The differences are always less than 0.5% for each investigated displacement, temperature, and stress component. The differences between the present 3D full coupled model and the the advantages of this new model are clearly shown. Both the thickness layer and material layer effects are directly included in all the conducted coupled thermal stress analyses. Citation: Technologies PubDate: 2023-02-24 DOI: 10.3390/technologies11020035 Issue No:Vol. 11, No. 2 (2023)
Authors:Lukas Paulauskas, Andrius Paulauskas, Tomas Blažauskas, Robertas Damaševičius, Rytis Maskeliūnas First page: 36 Abstract: Because of its benefits in providing an engaging and mobile environment, virtual reality (VR) has recently been rapidly adopted and integrated in education and professional training. Augmented reality (AR) is the integration of VR with the real world, where the real world provides context and the virtual world provides or reconstructs missing information. Mixed reality (MR) is the blending of virtual and physical reality environments allowing users to interact with both digital and physical objects at the same time. In recent years, technology for creating reality-based 3D models has advanced and spread across a diverse range of applications and research fields. The purpose of this paper is to design, develop, and test VR for kinaesthetic distance learning in a museum setting. A VR training program has been developed in which learners can select and perform pre-made scenarios in a virtual environment. The interaction in the program is based on kinaesthetic learning characteristics. Scenarios with VR controls simulate physical interaction with objects in a virtual environment for learners. Learners can grasp and lift objects to complete scenario tasks. There are also simulated devices in the virtual environment that learners can use to perform various actions. The study’s goal was to compare the effectiveness of the developed VR educational program to that of other types of educational material. Our innovation is the development of a system for combining their 3D visuals with rendering capable of providing a mobile VR experience for effective heritage enhancement. Citation: Technologies PubDate: 2023-02-25 DOI: 10.3390/technologies11020036 Issue No:Vol. 11, No. 2 (2023)
Authors:Alireza Khakpour, Ricardo Colomo-Palacios, Antonio Martini, Mary Sánchez-Gordón First page: 37 Abstract: Visual Analytics (VA) is a multidisciplinary field that requires various skills including but not limited to data analytics, visualizations, and the corresponding domain knowledge. Recently, many studies proposed creating and using Domain-Specific Languages (DSLs) for VA in order to abstract complexities and assist designers in developing better VAs for different data domains. However, development methods and types of DSLs vary for different applications and objectives. In this study, we conducted a systematic literature review to overview DSL methods and their intended applications for VA systems. Moreover, the review outlines the benefits and limitations of each of these methods. The aim is to provide decision support for both the research and development communities to choose the most compatible approach for their application. We think the communication of this research delivers a broad figure of previous relevant research and assists with the transfer and adaptation of the results to other domains. Citation: Technologies PubDate: 2023-03-02 DOI: 10.3390/technologies11020037 Issue No:Vol. 11, No. 2 (2023)
Authors: Ma, Yang, Riaz, Wang, Wang First page: 38 Abstract: Electrochemical supercapacitors are a promising type of energy storage device with broad application prospects. Developing an accurate model to reflect their actual working characteristics is of great research significance for rational utilization, performance optimization, and system simulation of supercapacitors. This paper presents the fundamental working principle and applications of supercapacitors, analyzes their aging mechanism, summarizes existing supercapacitor models, and evaluates the characteristics and application scope of each model. By examining the current state and limitations of supercapacitor modeling research, this paper identifies future development trends and research focuses in this area. Citation: Technologies PubDate: 2023-03-03 DOI: 10.3390/technologies11020038 Issue No:Vol. 11, No. 2 (2023)
Authors:Yixuan Chen, Yunlong Luo, Jianhua Ma, Alex Qi, Runhe Huang, Francesco De Paulis, Yihong Qi First page: 39 Abstract: In order to reduce the probability of automobile safety incidents, the in-vehicle occupant monitoring is indispensable. However, occupant monitoring using frequency-modulated continuous wave (FMCW) radar can be challenging due to the interference from passengers’ posture, movement, and the presence of multiple people. This paper proposes an improved method for generating point clouds using FMCW radar. The approach involves point cloud clustering, post-processing operations such as segmentation, merging, and filtering of the clustered point cloud to match the actual in-vehicle environment, and a state machine combination step. Experimental results show that the proposed method can achieve high recognition accuracy in scenarios with multiple passengers who are moving and sitting in a relaxed manner. Citation: Technologies PubDate: 2023-03-13 DOI: 10.3390/technologies11020039 Issue No:Vol. 11, No. 2 (2023)
Authors:Mohammadreza Iman, Hamid Reza Arabnia, Khaled Rasheed First page: 40 Abstract: Deep learning has been the answer to many machine learning problems during the past two decades. However, it comes with two significant constraints: dependency on extensive labeled data and training costs. Transfer learning in deep learning, known as Deep Transfer Learning (DTL), attempts to reduce such reliance and costs by reusing obtained knowledge from a source data/task in training on a target data/task. Most applied DTL techniques are network/model-based approaches. These methods reduce the dependency of deep learning models on extensive training data and drastically decrease training costs. Moreover, the training cost reduction makes DTL viable on edge devices with limited resources. Like any new advancement, DTL methods have their own limitations, and a successful transfer depends on specific adjustments and strategies for different scenarios. This paper reviews the concept, definition, and taxonomy of deep transfer learning and well-known methods. It investigates the DTL approaches by reviewing applied DTL techniques in the past five years and a couple of experimental analyses of DTLs to discover the best practice for using DTL in different scenarios. Moreover, the limitations of DTLs (catastrophic forgetting dilemma and overly biased pre-trained models) are discussed, along with possible solutions and research trends. Citation: Technologies PubDate: 2023-03-14 DOI: 10.3390/technologies11020040 Issue No:Vol. 11, No. 2 (2023)
Authors:Victor Panarin, Eduard Sosnin, Andrey Ryabov, Victor Skakun, Sergey Kudryashov, Dmitry Sorokin First page: 41 Abstract: The comparison of ion concentrations, pH index, and conductivity in distilled and ground water after exposure to low-temperature plasma formed by barrier and bubble discharges is performed. It has been found that in the case of groundwater, the best performance for the production of NO3− anions is provided by the discharge inside the gas bubbles. For distilled water, the barrier discharge in air, followed by saturation of water with plasma products, is the most suitable from this point of view. In both treatments, the maximum energy input into the stock solution is ensured. After 10 min treatment of ground water, the pH index increases and then it decreases. The obtained numerical indicators make it possible to understand in which tasks the indicated treatment modes should be used, their comparative advantages, and disadvantages. From the point of view of energy consumption for obtaining approximately equal (in order of magnitude) amounts of NO3− anions, both types of discharge treatment are suitable. The research results point to a fairly simple way to convert salts (calcium carbonates) from an insoluble form to soluble one. Namely, when interacting with NO3− anions, insoluble carbonates pass into soluble nitrates. Citation: Technologies PubDate: 2023-03-14 DOI: 10.3390/technologies11020041 Issue No:Vol. 11, No. 2 (2023)
Authors:Xiaofei Yu, Ning Ma, Lei Zheng, Licheng Wang, Kai Wang First page: 42 Abstract: With the continuous developments of information technology, advanced computer technology and information technology have been promoted and used in the field of music. As one of the products of the rapid development of information technology, Artificial Intelligence (AI) involves many interdisciplinary subjects, adding new elements to music education. By analyzing the advantages of AI in music education, this paper systematically summarizes the application of AI in music education and discusses the development prospects of AI in music education. With the aid of AI, the combination of intelligent technology and on-site teaching solves the lack of individuation in the traditional mode and enhances students’ interest in learning. Citation: Technologies PubDate: 2023-03-16 DOI: 10.3390/technologies11020042 Issue No:Vol. 11, No. 2 (2023)
Authors:Fabrizio Stasolla, Antonella Lopez, Khalida Akbar, Leonarda Anna Vinci, Maria Cusano First page: 43 Abstract: Neurological populations (NP) commonly experience several impairments. Beside motor and sensorial delays, communication and intellectual disabilities are included. The COVID-19 pandemic has suddenly exacerbated their clinical conditions due to lockdown, quarantine, and social distancing preventive measures. Healthcare services unavailability has negatively impacted NP clinical conditions, partially mitigated by vaccine diffusion. One way to overcome this issue is the use of technology-aided interventions for both assessment and rehabilitative purposes. Assistive technology-based interventions, telerehabilitation, and virtual reality setups have been widely adopted to help individuals with neurological damages or injuries. Nevertheless, to the best of our knowledge, their matching (i.e., combination or integration) has rarely been investigated. The main objectives of the current position paper were (a) to provide the reader with a perspective proposal on the matching of the three aforementioned technological solutions, (b) to outline a concise background on the use of technology-aided solutions, (c) to argue on the effectiveness and the suitability of technology-mediated programs, and (d) to postulate an integrative proposal to support cognitive rehabilitation including assistive technology, telerehabilitation, and virtual reality. Practical implications for both research and practice are critically discussed. Citation: Technologies PubDate: 2023-03-16 DOI: 10.3390/technologies11020043 Issue No:Vol. 11, No. 2 (2023)
Authors:Subhra Mondal, Subhankar Das, Vasiliki G. Vrana First page: 44 Abstract: Generative Artificial Intelligence (GAI) has brought revolutionary changes to the world, enabling businesses to create new experiences by combining virtual and physical worlds. As the use of GAI grows along with the Metaverse, it is explored by academics, researchers, and industry communities for its endless possibilities. From ChatGPT by OpenAI to Bard AI by Google, GAI is a leading technology in physical and virtual business platforms. This paper focuses on GAI’s economic and societal impact and the challenges it poses. Businesses must rethink their operations and strategies to create hybrid physical and virtual experiences using GAI. This study proposes a framework that can help business managers develop effective strategies to enhance their operations. It analyzes the initial applications of GAI in multiple sectors to promote the development of future customer solutions and explores how GAI can help businesses create new value propositions and experiences for their customers, and the possibilities of digital communication and information technology. A research agenda is proposed for developing GAI for business management to enhance organizational efficiency. The results highlight a healthy conversation on the potential of GAI in various business sectors to improve customer experience. Citation: Technologies PubDate: 2023-03-17 DOI: 10.3390/technologies11020044 Issue No:Vol. 11, No. 2 (2023)
Authors:Eileen Becks, Peter Zdankin, Viktor Matkovic, Torben Weis First page: 9 Abstract: Setup and management of smart home systems is a complex task, and thus challenging for technically inexperienced users. We conducted a qualitative user study to evaluate whether an assistance system could empower users to make better and informed decisions regarding the selection of devices, their interoperability, the resulting set of features and their price. A group of 20 participants used our assistance app on a smartphone to configure a smart home while optimizing for features, interoperability, and the price-performance ratio. The results of our user study show that our assistance app can ease the problem of selecting useful devices and at the same time users become aware of new features resulting from the interoperation of selected devices. Furthermore, the assistance app can counteract the inherent interoperability problem between devices of different vendors or platforms. Finally, users are not only interested in individual device prices. They want to learn the cost of a certain feature set, including the cost of all devices necessary to realize this feature. Interestingly, none of the current smart home systems on the market offer a comparable assistance mechanism. Third-party solutions are not available either, because an assistance app requires meta data about features, interoperability, and usage of devices. This meta data is currently not available via APIs in state-of-the-art smart home systems and marketplaces. Therefore, we present a smart home architecture resulting from our research that can, among other benefits, provide the necessary meta data. Our research indicates that commercial smart home systems should invest more effort in user assistance to gain widespread adoption among technically inexperienced users. This in turn requires substantial changes to the meta data management in smart homes, because otherwise these assistance systems cannot be realized. Citation: Technologies PubDate: 2023-01-03 DOI: 10.3390/technologies11010009 Issue No:Vol. 11, No. 1 (2023)
Authors:Maria Vasiliki Sanida, Theodora Sanida, Argyrios Sideris, Minas Dasygenis First page: 10 Abstract: Tomato plants are vulnerable to a broad number of diseases, each of which has the potential to cause significant damage. Diseases that affect crops substantially negatively impact the quantity and quality of agricultural products. Regarding quality crop maintenance, the importance of a timely and accurate diagnosis cannot be overstated. Deep learning (DL) strategies are now a critical research field for crop disease diagnoses. One independent system that can diagnose plant illnesses based on their outward manifestations is an example of an intelligent agriculture solution that could address these problems. This work proposes a robust hybrid convolutional neural network (CNN) diagnostic tool for various disorders that may affect tomato leaf tissue. A CNN and an inception module are the two components that make up this hybrid technique. The dataset employed for this study consists of nine distinct categories of tomato diseases and one healthy category sourced from PlantVillage. The findings are promising on the test set, with 99.17% accuracy, 99.23% recall, 99.13% precision, 99.56% AUC, and 99.17% F1-score, respectively. The proposed methodology offers a solution that boasts high performance for the diagnostics of tomato crops in the actual agricultural setting. Citation: Technologies PubDate: 2023-01-04 DOI: 10.3390/technologies11010010 Issue No:Vol. 11, No. 1 (2023)
Authors:Sergey N. Grigoriev, Marina A. Volosova, Anna A. Okunkova First page: 11 Abstract: SiAlON is one of the problematic and least previously studied but prospective cutting ceramics suitable for most responsible machining tasks, such as cutting sophisticated shapes of aircraft gas turbine engine parts made of chrome–nickel alloys (Inconel 718 type) with increased mechanical and thermal loads (semi-finishing). Industrially produced SiAlON cutting inserts are replete with numerous defects (stress concentrators). When external loads are applied, the wear pattern is difficult to predict. The destruction of the cutting edge, such as the tearing out of entire conglomerates, can occur at any time. The complex approach of additional diamond grinding, lapping, and polishing combined with an advanced double-layer (CrAlSi)N/DLC coating was proposed here for the first time to minimize it. The criterion of failure was chosen to be 0.4 mm. The developed tri-nitride coating sub-layer plays a role of improving the main DLC coating adhesion. The microhardness of the DLC coating was 28 ± 2 GPa, and the average coefficient of friction during high-temperature heating (up to 800 °C) was ~0.4. The average durability of the insert after additional diamond grinding, lapping, polishing, and coating was 12.5 min. That is superior to industrial cutting inserts and those subjected to (CrAlSi)N/DLC coating by 1.8 and 1.25 times, respectively. Citation: Technologies PubDate: 2023-01-12 DOI: 10.3390/technologies11010011 Issue No:Vol. 11, No. 1 (2023)
Authors:Luis H. Manjarrez, Julio C. Ramos-Fernández, Eduardo S. Espinoza, Rogelio Lozano First page: 12 Abstract: An essential aspect to achieving safety with a UAV is that it operates within the limits of its capabilities, the available flight time being a key aspect when planning and executing a mission. The flight time will depend on the relationship between the available energy and the energy required by the UAV to complete the mission. This paper addresses the problem of estimating the energy required to perform a mission, for which a fuzzy Takagi–Sugeno system was implemented, whose premises were developed using fuzzy C-means to estimate the power required in the different stages of the mission. The parameters used in the fuzzy C-means algorithm were optimized using particle swarm optimization. On the other hand, an equivalent circuit model of a battery was used, for which fuzzy modeling was employed to determine the relationship between the open-circuit voltage and the state of charge of the battery, which in conjunction with an extended Kalman filter allows determining the battery charge. In addition, we developed a methodology to determine the minimum allowable battery charge level. From this, it is possible to determine the available flight time at the end of a mission defined as the flight time margin. In order to evaluate the developed methodology, a physical experiment was performed using an hexarotor UAV obtaining a maximum prediction error equivalent to the energy required to operate for 7 s, which corresponds to 2% of the total mission time. Citation: Technologies PubDate: 2023-01-12 DOI: 10.3390/technologies11010012 Issue No:Vol. 11, No. 1 (2023)
Authors:Paolo Veronesi, Alessio Balestri, Elena Colombini First page: 13 Abstract: Grade 37 titanium is widely used in racing applications thanks to its oxidation resistance up to 650 °C, but it suffers from poor wear and fretting resistance, especially at high temperature. In this paper, different surface modification techniques, namely, carburizing, coating by PVD-ZrO2 and a novel microwave plasma oxy-carburizing treatment, are investigated in terms of hardness, wear resistance and scratch hardness, compared to the untreated substrate. Numerical simulation allowed optimization of the design of the microwave plasma source, which operated at 2.45 GHz at atmospheric pressure. The proposed microwave plasma oxy-carburizing treatment is localized and can serve to improve the tribological properties of selected regions of the sample; compared to untreated Grade 37 titanium, the oxy-carburized layer presents a decrease in the wear rate at 450 °C against alumina of 54% and an increase in scratch hardness of more than three times. Citation: Technologies PubDate: 2023-01-12 DOI: 10.3390/technologies11010013 Issue No:Vol. 11, No. 1 (2023)
Authors:Arebu Dejen, Jeevani Jayasinghe, Murad Ridwan, Jaume Anguera First page: 14 Abstract: Antennas with multifunctional capabilities integrated into a single device that demonstrates a high performance are in demand, and microstrip antennas with quadband coverage are very useful for a wide range of mm-wave applications. Antennas and propagation at mm-wave frequencies, on the other hand, poses several challenges which can be overcome by applying performance enhancement techniques to meet design objectives. This article presents the use of a binary-coded genetic algorithm for developing an improved quadband mm-wave microstrip patch antenna. The patch shape was optimized by dividing a conducting surface into 6×6 tiny rectangular blocks. The algorithm generated the solution space by introducing conducting and nonconducting features for each radiating cell on the patch surface and then greedily searched for the best-fitted individual based on the cost function. With the combination of High-Frequency Structure Simulator (HFSS) and MATLAB, candidate antennas were iteratively modeled by applying the suggested algorithm. The optimized antenna resonated at four frequencies centered at 28.3 GHz, 38.1 GHz, 46.6 GHz, and 60.0 GHz. The antenna realized a peak broadside directivity of 7.8 dB, 8.8 dB, 7.3 dB, and 7.1 dB, respectively, with a total operating bandwidth of 11.5 GHz. The research findings were compared with related works presented in the literature and found that the optimized antenna outperformed them in terms of bandwidth, directivity, and efficiency. Citation: Technologies PubDate: 2023-01-16 DOI: 10.3390/technologies11010014 Issue No:Vol. 11, No. 1 (2023)
Authors:Yoshihiro Kai, Yuuki Seki, Riku Suzuki, Atsunori Kogawa, Ryuichi Tanioka, Kyoko Osaka, Yueren Zhao, Tetsuya Tanioka First page: 15 Abstract: With the aging of the population in Japan, the number of bedridden patients who need long-term care is increasing. The Japanese government has been promoting the creation of an environment that enables everyone, including bedridden patients, to enjoy travel, based on the principle of normalization. However, it is difficult for bedridden patients to enjoy the scenery of distant places and to talk with the local people because they need support from helpers to travel to distant places using travel agencies. Therefore, to enhance their quality of life (QOL), we developed a remote-controlled drone system, which involves using only the eyes. We believe that bedridden patients are able to operate the system’s drone in a distant place, to easily view the scenery of the distant place with a camera installed on the drone, and to talk with the local people. However, we have never evaluated whether actual bedridden patients can operate the drone in a distant place, to see the scenery, and to talk with the local people. In this paper, we presented clinical experimental results to verify the effectiveness of this drone system. Findings showed that, not only subjects with relatively high levels of independence in activities of daily living, but also bedridden subjects, could operate the drone at a distant place with only their eyes and communicate with others. Citation: Technologies PubDate: 2023-01-17 DOI: 10.3390/technologies11010015 Issue No:Vol. 11, No. 1 (2023)
Authors:Peng Lin, Zigang Deng, Zhihao Ke, Wuyang Lei, Xuanbo Wang, Kehong Ren First page: 16 Abstract: A novel type of suspension system for maglev vehicles using six permanent magnet electrodynamic wheels (EDW) and conductor plate has been designed. It has the advantages of high speed, environmental protection, and a low turning radius. Differing from existing maglev vehicles, this paper proposes a new maglev vehicle utilizing six EDWs to respectively provide driving force and levitation force. This structure can keep the levitation force at a large constant value and obtain enough driving force at low rotational speeds by adjusting the motor speed. First, the structure of the electrodynamic wheel is given. The accuracy and validity of the FEM results are verified by the experiments. Moreover, based on the finite element method (FEM), the optimal structure of the EDWs is obtained with the objective of maximum levitation force. Then, the simplified electromagnetic force model is obtained by using MATLAB Toolbox. Third, using a co-simulation of Simulink and Adams to design and build a 1:50 maglev vehicle model, this article studies the dynamic response characteristics of the maglev vehicle model from the perspective of dynamics and proposes a feedback control strategy by adjusting the rotational speed to control the maglev vehicle. This paper also proposes a method to realize the car’s pivot steering to reduce the car’s turning radius and help the drivers pass narrow road sections. This article verifies the feasibility of the maglev vehicle with six EDWs and is expected to provide a certain reference for the development of permanent magnet electrodynamic suspension vehicles. Citation: Technologies PubDate: 2023-01-21 DOI: 10.3390/technologies11010016 Issue No:Vol. 11, No. 1 (2023)
Authors:Rahaf Douhan, Kirill Lozovoy, Andrey Kokhanenko, Hazem Deeb, Vladimir Dirko, Kristina Khomyakova First page: 17 Abstract: In this review the latest advances in the field of nanostructured photodetectors are considered, stating the types and materials, and highlighting the features of operation. Special attention is paid to the group-IV material photodetectors, including Ge, Si, Sn, and their solid solutions. Among the various designs, photodetectors with quantum wells, quantum dots, and quantum wires are highlighted. Such nanostructures have a number of unique properties, that made them striking to scientists’ attention and device applications. Since silicon is the dominating semiconductor material in the electronic industry over the past decades, and as germanium and tin nanostructures are very compatible with silicon, the combination of these factors makes them the promising candidate to use in future technologies. Citation: Technologies PubDate: 2023-01-24 DOI: 10.3390/technologies11010017 Issue No:Vol. 11, No. 1 (2023)
Authors:Hamza Reza Pavel, Enamul Karim, Ashish Jaiswal, Sneh Acharya, Gaurav Nale, Michail Theofanidis, Fillia Makedon First page: 18 Abstract: Cognitive Fatigue (CF) is the decline in cognitive abilities due to prolonged exposure to mentally demanding tasks. In this paper, we used gait cycle analysis, a biometric method related to human locomotion to identify cognitive fatigue in individuals. The proposed system in this paper takes two asynchronous videos of the gait of individuals to classify if they are cognitively fatigued or not. We leverage the pose estimation library OpenPose, to extract the body keypoints from the frames in the videos. To capture the spatial and temporal information of the gait cycle, a CNN-based model is used in the system to extract the embedded features which are then used to classify the cognitive fatigue level of individuals. To train and test the model, a gait dataset is built from 21 participants by collecting walking data before and after inducing cognitive fatigue using clinically used games. The proposed model can classify cognitive fatigue from the gait data of an individual with an accuracy of 81%. Citation: Technologies PubDate: 2023-01-26 DOI: 10.3390/technologies11010018 Issue No:Vol. 11, No. 1 (2023)
Authors:Valeri Mladenov First page: 20 Abstract: The design of memristor-based electronic circuits and devices gives researchers opportunities for the engineering of CMOS-memristor-based electronic integrated chips with ultra-high density and various applications. Metal-oxide memristors have good compatibility with the present CMOS integrated circuits technologies. The analysis of new electronic circuits requires suitable software and fast-functioning models. The main purpose of this paper is to propose the application of several modified, simplified, and improved metal-oxide memristor models in electronic devices and provide a comparison of their behavior, basic characteristics, and properties. According to this, LTSPICE is utilized in this paper because it is a free software product with good convergence. Several memristor-based electronic circuits, such as non-volatile passive and hybrid memory crossbars, a neural network, and different reconfigurable devices–filters, an amplifier, and a generator are analyzed in the LTSPICE environment, applying several standards and modified metal-oxide memristor models. After a comparison of the operation of the considered schemes, the main advantages of the modified metal-oxide memristor models, according to their standard analogs, are expressed, including fast operation, good accuracy, respectable convergence, switching properties, and successful applicability in complex electronic circuits. Citation: Technologies PubDate: 2023-01-28 DOI: 10.3390/technologies11010020 Issue No:Vol. 11, No. 1 (2023)
Authors: Hidalgo, Vázquez, Orosco, Huerta-Ávila, Pinto, Estrada First page: 21 Abstract: A zero-ripple input current is known to improve the lifetime of battery sets and fuel cells and to assure maximum power point tracking in PV panels. To perform current ripple elimination in a floating interleaved boost converter (FIBC), one of the typical linear inductors is substituted by a variable inductor, and phases of the converter have complementary duty cycles. This variable inductor is controlled using a switched current-source converter, which adjusts the input current ripple. An equivalent model for the variable inductor is presented, including uncertainties in the component description. To achieve current stabilization, a variable inductor controller was designed using the sliding modes approach via fixed frequency. An experimental prototype is implemented and tested with an output voltage controller to compare with the conventional FIBC. The results demonstrate that the input current ripple of the proposed converter is eliminated without significantly decreasing the efficiency. Citation: Technologies PubDate: 2023-01-28 DOI: 10.3390/technologies11010021 Issue No:Vol. 11, No. 1 (2023)
Authors:Boopathi Dhanasekaran, Jagatheesan Kaliannan, Anand Baskaran, Nilanjan Dey, João Manuel R. S. Tavares First page: 22 Abstract: The performance of load frequency control (LFC) for isolated multiple sources of electric power-generating units with a proportional integral derivative (PID) controller is presented. A thermal, hydro, and gas power-generating unit are integrated into the studied system. The PID controller is proposed as a subordinate controller to stabilize system performance when there is a sudden demand on the power system. The particle swarm optimization (PSO) algorithm is used to obtain optimal gain values of the proposed PID controller. Various cost functions, mainly integral time absolute error (ITAE), integral absolute error (IAE), integral squared error (ISE), and integral time squared error (ITSE) were used to optimize controller gain parameters. Furthermore, the enhancement of the PSO technique is proven by the performance comparison of conventional, differential evolution (DE) algorithm- and genetic algorithm (GA)-based PID controllers for the same system. The results show the PSO-PID controller delivers a faster settled response and the percentage improvement of the proposed technique over the conventional method is 79%, over GA is 55%, and over DE is 24% in an emergency in a power system. Citation: Technologies PubDate: 2023-01-28 DOI: 10.3390/technologies11010022 Issue No:Vol. 11, No. 1 (2023)
Authors:Woo Sik Yoo, Jung Gon Kim, Kitaek Kang, Yeongsik Yoo First page: 23 Abstract: Colorimetric sensing techniques for point(s), linear and areal array(s) were developed using image sensors and novel image processing software for chemical, biological and medical applications. Monitoring and recording of colorimetric information on one or more specimens can be carried out by specially designed image processing software. The colorimetric information on real-time monitoring and recorded images or video clips can be analyzed for point(s), line(s) and area(s) of interest for manual and automatic data collection. Ex situ and in situ colorimetric data can be used as signals for process control, process optimization, safety and security alarms, and inputs for machine learning, including artificial intelligence. As an analytical example, video clips of chromatographic experiments using different colored inks on filter papers dipped in water and randomly blinking light-emitting-diode-based decorative lights were used. The colorimetric information on points, lines and areas, with different sizes from the video clips, were extracted and analyzed as a function of time. The video analysis results were both visualized as time-lapse images and RGB (red, green, blue) color/intensity graphs as a function of time. As a demonstration of the developed colorimetric analysis technique, the colorimetric information was expressed as static and time-series combinations of RGB intensity, HSV (hue, saturation and value) and CIE L*a*b* values. Both static and dynamic colorimetric analysis of photographs and/or video files from image sensors were successfully demonstrated using a novel image processing software. Citation: Technologies PubDate: 2023-01-28 DOI: 10.3390/technologies11010023 Issue No:Vol. 11, No. 1 (2023)
Authors:Mohammad Arifuzzaman, Md. Rakibul Hasan, Tasnia Jahan Toma, Samia Binta Hassan, Anup Kumar Paul First page: 24 Abstract: Deep neural networks (DNNs), the integration of neural networks (NNs) and deep learning (DL), have proven highly efficient in executing numerous complex tasks, such as data and image classification. Because the multilayer in a nonlinearly separable data structure is not transparent, it is critical to develop a specific data classification model from a new and unexpected dataset. In this paper, we propose a novel approach using the concepts of DNN and decision tree (DT) for classifying nonlinear data. We first developed a decision tree-based neural network (DTBNN) model. Next, we extend our model to a decision tree-based deep neural network (DTBDNN), in which the multiple hidden layers in DNN are utilized. Using DNN, the DTBDNN model achieved higher accuracy compared to the related and relevant approaches. Our proposal achieves the optimal trainable weights and bias to build an efficient model for nonlinear data classification by combining the benefits of DT and NN. By conducting in-depth performance evaluations, we demonstrate the effectiveness and feasibility of the proposal by achieving good accuracy over different datasets. Citation: Technologies PubDate: 2023-02-01 DOI: 10.3390/technologies11010024 Issue No:Vol. 11, No. 1 (2023)
Authors:Marcos Aviles, Juvenal Rodríguez-Reséndiz, Juan Pérez-Ospina, Oscar Lara-Mendoza First page: 25 Abstract: This article presents the methodology for developing a control laboratory project that provides practical experience based on the ABET criteria. The project is structured around a portable and cheap ball and beam whose integrated system is made using printed circuit boards as the first task. For the expression of the plant, students are guided to execute the essential stages of the control system design, from system modeling, through the design of the basic or advanced control strategy in the MATLAB and Arduino environment, to the implementation and validation of the closed loop. The proposed methods are clear and direct, greatly fostering the understanding of feedback control techniques and enabling students to gain extensive knowledge in practical implementations of control systems. The methodology is easy to interpret and modify in order to adopt it to any computer, allowing for the implementation of new practical tasks in control courses. Additionally, application examples and student-focused comments are included. This paper describes, in detail, the implementation and development of six laboratory practices for control courses, which have been developed based on ESP32 and other existing equipment. Citation: Technologies PubDate: 2023-02-03 DOI: 10.3390/technologies11010025 Issue No:Vol. 11, No. 1 (2023)
Authors:Nikita Permiakov, Evgeniya Maraeva, Anton Bobkov, Ritsoh Mbwahnche, Vyacheslav Moshnikov First page: 26 Abstract: The use of liquid probes based on indium–gallium eutectic (EGaIn) with the possibility of positioning is an important problem for the study of thin films. This work is centered on the creation of a setup for measuring the current–voltage characteristics with the use of a liquid eutectic electrode. A technique for obtaining a cone-shaped liquid EGaIn electrode, a 3D assembly model and an algorithm for the operation of a probe setup for obtaining the current–voltage characteristics using liquid contacts are presented. Citation: Technologies PubDate: 2023-02-06 DOI: 10.3390/technologies11010026 Issue No:Vol. 11, No. 1 (2023)
Authors:Abdul Rehman, Kamran Ahmad Awan, Ikram Ud Din, Ahmad Almogren, Mohammed Alabdulkareem First page: 27 Abstract: The Internet of Things (IoT) is widely used to reduce human dependence. It is a network of interconnected smart devices with internet connectivity that can send and receive data. However, the rapid growth of IoT devices has raised security and privacy concerns, with the identification and removal of compromised and malicious nodes being a major challenge. To overcome this, a lightweight trust management mechanism called FogTrust is proposed. It has a multi-layer architecture that includes edge nodes, a trusted agent, and a fog layer. The trust agent acts as an intermediary authority, communicating with both IoT nodes and the fog layer for computation. This reduces the burden on nodes and ensures a trustworthy environment. The trust agent calculates the trust degree and transmits it to the fog layer, which uses encryption to maintain integrity. The encrypted value is shared with the trust agent for aggregation to improve the trust degree’s accuracy. The performance of the FogTrust approach was evaluated against various potential attacks, including On-off, Good-mouthing, and Bad-mouthing. The simulation results demonstrate that it effectively assigns low trust degrees to malicious nodes in different scenarios, even with varying percentages of malicious nodes in the network. Citation: Technologies PubDate: 2023-02-07 DOI: 10.3390/technologies11010027 Issue No:Vol. 11, No. 1 (2023)
Authors:Suriya Priya R. Asaithambi, Ramanathan Venkatraman, Sitalakshmi Venkatraman First page: 28 Abstract: Tour planning has become both challenging and time-consuming due to the huge amount of information available online and the variety of options to choose from. This is more so as each traveler has unique set of interests and location preferences in addition to other tour-based constraints such as vaccination status and pandemic travel restrictions. Several travel planning companies and agencies have emerged with more sophisticated online services to capitalize on global tourism effectively by using technology for making suitable recommendations to travel seekers. However, such systems predominantly adopt a destination-based recommendation approach and often come as bundled packages with limited customization options for incorporating each traveler’s preferences. To address these limitations, “thematic travel planning” has emerged as a recent alternative with researchers adopting text-based data mining for achieving value-added online tourism services. Understanding the need for a more holistic theme approach in this domain, our aim is to propose an augmented model to integrate analytics of a variety of big data (both static and dynamic). Our unique inclusive model covers text mining and data mining of destination images, reviews on tourist activities, weather forecasts, and recent events via social media for generating more user-centric and location-based thematic recommendations efficiently. In this paper, we describe an implementation of our proposed inclusive hybrid recommendation model that uses data of multimodal ranking of user preferences. Furthermore, in this study, we present an experimental evaluation of our model’s effectiveness. We present the details of our improvised model that employs various statistical and machine learning techniques on existing data available online, such as travel forums and social media reviews in order to arrive at the most relevant and suitable travel recommendations. Our hybrid recommender built using various Spark models such as naïve Bayes classifier, trigonometric functions, deep learning convolutional neural network (CNN), time series, and NLP with sentiment scores using AFINN (sentiment analysis developed by Finn Årup Nielsen) shows promising results in the directions of benefit for an individual model’s complementary advantages. Overall, our proposed hybrid recommendation algorithm serves as an active learner of user preferences and ranking by collecting explicit information via the system and uses such rich information to make personalized augmented recommendations according to the unique preferences of travelers. Citation: Technologies PubDate: 2023-02-07 DOI: 10.3390/technologies11010028 Issue No:Vol. 11, No. 1 (2023)
Authors:Manolis Adamakis First page: 29 Abstract: Wearable technologies have become powerful tools for health and fitness and are indispensable everyday tools for many individuals; however, significant limitations exist related to the validity of the metrics these monitors purport to measure. Thus, the purpose of the present study was to validate the step count of three wearable monitors (i.e., Yamax 3D Power-Walker, Garmin Vivofit 3 and Medisana Vifit), as well as two Android apps (i.e., Accupedo Pedometer and Pedometer 2.0), in a sample of healthy adults. These monitors and apps were evaluated in a lab-based semi-structured study and a 3-day field study under habitual free-living conditions. A convenience sample of 24 healthy adults (14 males and 10 females; 32.6 ± 2.5 years) participated in both studies. Direct step observation and Actigraph served as the criterion methods and validity was evaluated by comparing each monitor and app with the criterion measure using mean absolute percentage errors (MAPE), Bland–Altman plots, and Intraclass Correlation Coefficients. The results revealed high validity for the three wearable monitors during the semi-structured study, with MAPE values approximately 5% for Yamax and Vifit and well below 5% for Vivofit, while the two apps showed high MAPE values over 20%. In the free-living study all monitors and apps had high MAPE, over 10%. The lowest error was observed for Yamax, Vifit and Pedometer app, while Accupedo app had the highest error, overestimating steps by 32%. The present findings cannot support the value of wearable monitors and apps as acceptable measures of PA and step count in free-living contexts. Wearable monitors and apps that might be valid in one context, might not be valid in different contexts and vice versa, and researchers should be aware of this limitation. Citation: Technologies PubDate: 2023-02-13 DOI: 10.3390/technologies11010029 Issue No:Vol. 11, No. 1 (2023)
Authors:Muhammad Farooq Saleem, Niaz Ali Khan, Muhammad Javid, Ghulam Abbas Ashraf, Yasir A. Haleem, Muhammad Faisal Iqbal, Muhammad Bilal, Peijie Wang, Ma Lei First page: 30 Abstract: Condensation of moisture on the epitaxial graphene on 6H-SiC was observed below room temperature despite continuous nitrogen flow on the graphene surface. Raman peaks associated with ice were observed. A combination of peaks in the frequency range of 500–750 cm−1, along with a broad peak centered at ~1327 cm−1, were also observed and were assigned to airborne contaminants. The latter is more important since its position is in the frequency range where the defect-associated D band of graphene appears. This band can be easily misunderstood to be the D band of graphene, particularly when the Raman spectrum is taken below room temperature. This peak was even observed after the sample was brought back to room temperature due to water stains. This work highlights the importance of careful Raman investigation of graphene below room temperature and its proper insulation against moisture. Citation: Technologies PubDate: 2023-02-13 DOI: 10.3390/technologies11010030 Issue No:Vol. 11, No. 1 (2023)
Authors: Pritika, Bharanidharan Shanmugam, Sami Azam First page: 31 Abstract: The adaptation of the Internet of Medical Things (IoMT) has provided efficient and timely services and has transformed the healthcare industry to a great extent. Monitoring patients remotely and managing hospital records and data have become effortless with the advent of IoMT. However, security and privacy have become a significant concern with the growing number of threats in the cyber world, primarily for personal and sensitive user data. In terms of IoMT devices, risks appearing from them cannot easily fit into an existing risk assessment framework, and while research has been done on this topic, little attention has been paid to the methodologies used for the risk assessment of heterogeneous IoMT devices. This paper elucidates IoT, its applications with reference to in-demand sectors, and risks in terms of their types. By the same token, IoMT and its application area and architecture are explained. We have also discussed the common attacks on IoMT. Existing papers on IoT, IoMT, risk assessment, and frameworks are reviewed. Finally, the paper analyzes the available risk assessment frameworks such as NIST, ISO 27001, TARA, and the IEEE213-2019 (P2413) standard and highlights the need for new approaches to address the heterogeneity of the risks. In our study, we have decided to follow the functions of the NIST and ISO 270001 frameworks. The complete framework is anticipated to deliver a risk-free approach for the risk assessment of heterogeneous IoMT devices benefiting its users. Citation: Technologies PubDate: 2023-02-14 DOI: 10.3390/technologies11010031 Issue No:Vol. 11, No. 1 (2023)
Authors:Kyriaki A. Tychola, Stamatis Chatzistamatis, Eleni Vrochidou, George E. Tsekouras, George A. Papakostas First page: 32 Abstract: The buildings in a city are of great importance. Certain historic buildings are landmarks and indicate the city’s architecture and culture. The buildings over time undergo changes because of various factors, such as structural changes, natural disaster damages, and aesthetic interventions. The form of buildings in each period is perceived and understood by people of each generation, through photography. Nevertheless, each photograph has its own characteristics depending on the camera (analog or digital) used for capturing it. Any photo, even depicting the same object, is impossible to capture in the same way in terms of illumination, viewing angle, and scale. Hence, to study two or more photographs depicting the same object, first they should be identified and then properly matched. Nowadays, computer vision contributes to this process by providing useful tools. In particular, for this purpose, several feature detection and description algorithms of homologous points have been developed. In this study, the identification of historic buildings over time through feature correspondence techniques and methods is investigated. Especially, photographs from landmarks of Drama city, in Greece, on different dates and conditions (weather, light, rotation, scale, etc.), were gathered and experiments on 2D pairs of images, implementing traditional feature detectors and descriptors algorithms, such as SIFT, ORB, and BRISK, were carried out. This study aims to evaluate the feature matching procedure focusing on both the algorithms’ performance (accuracy, efficiency, and robustness) and the identification of the buildings. SIFT and BRISK are the most accurate algorithms while ORB and BRISK are the most efficient. Citation: Technologies PubDate: 2023-02-17 DOI: 10.3390/technologies11010032 Issue No:Vol. 11, No. 1 (2023)
Authors: Ochiai, Koseki, Matsumura First page: 1 Abstract: Paper chromatography is a low-cost and facile analytical method traditionally used to analyze hydrophilic substances. For the application to substances with lower polarity, we prepared a stationary phase based on filter paper modified with phenyl isocyanate (PI-FP), bearing phenyl carbamate moieties for hydrophobic, π-π, and electrostatic interactions. The preparation and chromatographic methods were established by selecting papers, comparing different chemical structures, optimizing the modification procedure, investigating eluents, and quantitatively parameterizing the separation behavior based on the character of the analytes. PI-FP exhibited better separation performance than esterified FPs and enabled chromatographic analysis of various dyes with both positive and negative clogP (calculated water-octanol partition coefficient). We also demonstrated an application of this system for a preparative separation of dyes using thread-like paper modified with PI. Citation: Technologies PubDate: 2022-12-20 DOI: 10.3390/technologies11010001 Issue No:Vol. 11, No. 1 (2022)
Authors:Eshetu Gelan First page: 2 Abstract: The building sector is a key contributor to climate change, accounting for 40% of global energy consumption and 39% of CO2 emissions. Presently, green buildings have been viewed as crucial strategies to reduce the negative effects of the construction sector. Yet green building research is often carried out in developed countries, while relatively little is known in sub-Saharan African countries. Therefore, this study attempts to investigate the extent of adoption of green building concepts and technologies in Ethiopian buildings, with particular reference to the Wegagen Bank Headquarters building. The study employed an interview, which was underpinned by observation. The quantitative data were analyzed through descriptive statistics while the qualitative data were analyzed through content and context analysis. Results revealed that while the building provides convenient access to transportation; it lacks designated open spaces. Based on the findings, the widely used technologies were energy-saving lighting, highly efficient plumbing fixtures, and external solar shading system. Lack of awareness, lack of policy, insufficient professional skills, the perception that green buildings are expensive, and lack of green building materials hindered the adoption of the concepts. Therefore, the study suggests developing green building policy and rating systems, professional capacity building, and awareness creation as important measures. Citation: Technologies PubDate: 2022-12-21 DOI: 10.3390/technologies11010002 Issue No:Vol. 11, No. 1 (2022)
Authors:Yuqing Xiang, Zigang Deng, Hongfu Shi, Kaiwen Li, Ting Cao, Bin Deng, Le Liang, Jun Zheng First page: 3 Abstract: Inspired by the guidance principle in the electromagnetic levitation system, a new permanent magnet electrodynamic suspension (PM EDS) structure with ferromagnetic guidance track is proposed and analyzed in this paper. Considering the lack of effective guidance ability for the PM EDS system, we adopted the ferromagnetic guidance track as being mounted under the conductor plate. The guidance principle is studied and the implementation of the guidance function is also introduced, and the finite element method (FEM) is employed and its accuracy is confirmed via the PM EDS high-speed rotating experimental platform fabricated in our laboratory. The influence of longitudinal speed on the guidance force is taken into account, which shows that the guidance performance is enhanced more obviously at low speeds. Moreover, the influence of the guidance track parameters on the guidance performance is also analyzed, including the geometric parameters, section shape, installation position and material. The equivalent small-scale PM EDS system experimental prototype is carried out to validate the effectiveness of the ferromagnetic guidance. The proposed ferromagnetic guidance structure is demonstrated to improve the guidance performance of the PM EDS system effectively, which will offer a technical reference for the practical engineering application of the PM EDS system. Citation: Technologies PubDate: 2022-12-21 DOI: 10.3390/technologies11010003 Issue No:Vol. 11, No. 1 (2022)
Authors:Tommy Langen, Haytham B. Ali, Kristin Falk First page: 4 Abstract: The industry acknowledges the value of using data and digitalization approaches to improve their systems. However, companies struggle to use data effectively in product development. This paper presents a conceptual framework for Data Sensemaking in Product Development, exemplified through a case study of an Automated Parking System. The work is grounded in systems engineering, human centered-design, and data science theory. The resulting framework applies to practitioners and researchers in the early phase of product development. The framework combines conceptual models and data analytics, facilitating the range from human judgment and decision-making to verifications. The case study and feedback from several industrial actors suggest that the framework is valuable, usable, and feasible for more effective use of data in product development. Citation: Technologies PubDate: 2022-12-22 DOI: 10.3390/technologies11010004 Issue No:Vol. 11, No. 1 (2022)
Authors:Madhuri Hiwale, Vijayakumar Varadarajan, Rahee Walambe, Ketan Kotecha First page: 5 Abstract: A recent development in the Internet of Things (IoT) has accelerated the application of IoT-based solutions in healthcare. Next-Gen networks and IoT, supported by the development of technologies such as Artificial Intelligence (AI) and blockchain, have propelled the growth of e-health applications. However, there are some unique challenges in the widespread acceptance of IoT in healthcare. Safe storage, transfer, authorized access control, and the privacy and security aspects of patient data management are crucial barriers to the widespread adoption of IoT in healthcare. This makes it necessary to identify current issues in the various health data management systems to develop novel healthcare solutions. As a case study, this work considers a scheme launched by the Government of India for tuberculosis care called Nikshay Poshan Yojana (NPY). It is a web-based Direct Benefit Transfer scheme to provide a nutritional incentive of INR 500/- per month to all tuberculosis patients. The main objective of this work is to identify the current implementation challenges of the NPY scheme from patient and healthcare stakeholder perspectives and proposes a blockchain-based architecture called NikshayChain for sharing patient medical reports and bank details among several healthcare stakeholders within or across Indian cities. The proposed architecture accelerates healthcare stakeholder productivity by reducing workload and overall costs while ensuring effective data management. This architecture can significantly improve medical care, incentive transfer, and data verification, propelling the use of e-health applications. Citation: Technologies PubDate: 2022-12-26 DOI: 10.3390/technologies11010005 Issue No:Vol. 11, No. 1 (2022)
Authors:Anna A. Okunkova, Marina A. Volosova, Khaled Hamdy, Khasan I. Gkhashim First page: 6 Abstract: The paper aims to extend the current knowledge on electrical discharge machining of insulating materials, such as cutting ceramics used to produce cutting inserts to machine nickel-based alloys in the aviation and aerospace industries. Aluminum-based ceramics such as Al2O3, AlN, and SiAlON are in the most demand in the industry but present a scientific and technical problem in obtaining sophisticated shapes. One of the existing solutions is electrical discharge machining using assisting techniques. Using assisting Cu-Ag and Cu mono- and multi-layer coatings of 40–120 µm and ZnO powder-mixed deionized water-based medium was proposed for the first time. The developed coatings were subjected to tempering and testing. It was noticed that Ag-adhesive reduced the performance when tempering had a slight effect. The unveiled relationship between the material removal rate, powder concentration, and pulse frequency showed that performance was significantly improved by adding assisting powder up to 0.0032–0.0053 mm3/s for a concentration of 14 g/L and pulse frequency of 2–7 kHz. Further increase in concentration leads to the opposite trend. The most remarkable results corresponded to the pulse duration of 1 µs. The obtained data enlarged the knowledge of texturing insulating cutting ceramics using various powder-mixed deionized water-based mediums. Citation: Technologies PubDate: 2022-12-27 DOI: 10.3390/technologies11010006 Issue No:Vol. 11, No. 1 (2022)
Authors:Haytham B. Ali, Gerrit Muller, Fahim A. Salim, Kristin Falk, Serkan Güldal First page: 7 Abstract: In complex sociotechnical research, companies aim to utilize data and digitalization to increase a system’s reliability and to minimize a system’s failures. This study exemplifies the use of conceptual modeling and data analysis to increase a system’s reliability by studying a case study for a medium-sized company. The company delivers an Automated Parking System (APS). We identified, collected, and analyzed internal and external data within this context. Internal data consist of failure data from maintenance, whereas external data include environmental data, mainly weather data. Data analyses transformed the collected data into information, where conceptual modeling facilitates the understanding of information by transforming it further into knowledge. We find that the combination of conceptual modeling and data analysis aids in exploring and understanding a system’s reliability. This understanding enables a company to enhance its product-development process. Conceptual modeling and data analyses guide and support each other in an iterative and recursive manner, and they both complement each other. Conceptual modeling also facilitates communication and understanding. Citation: Technologies PubDate: 2022-12-28 DOI: 10.3390/technologies11010007 Issue No:Vol. 11, No. 1 (2022)
Authors:Minjeong Kim, Jimin Koo First page: 8 Abstract: Drowsiness on the road is a widespread problem with fatal consequences; thus, a multitude of systems and techniques have been proposed. Among existing methods, Ghoddoosian et al. utilized temporal blinking patterns to detect early signs of drowsiness, but their algorithm was tested only on a powerful desktop computer, which is not practical to apply in a moving vehicle setting. In this paper, we propose an efficient platform to run Ghoddoosian’s algorithm, detail the performance tests we ran to determine this platform, and explain our threshold optimization logic. After considering the Jetson Nano and Beelink (Mini PC), we concluded that the Mini PC is most efficient and practical to run our embedded system in a vehicle. To determine this, we ran communication speed tests and evaluated total processing times for inference operations. Based on our experiments, the average total processing time to run the drowsiness detection model was 94.27 ms for the Jetson Nano and 22.73 ms for the Beelink (Mini PC). Considering the portability and power efficiency of each device, along with the processing time results, the Beelink (Mini PC) was determined to be most suitable. Additionally, we propose a threshold optimization algorithm, which determines whether the driver is drowsy, or alert based on the trade-off between the sensitivity and specificity of the drowsiness detection model. Our study will serve as a crucial next step for drowsiness detection research and its application in vehicles. Through our experiments, we have determined a favorable platform that can run drowsiness detection algorithms in real-time and can be used as a foundation to further advance drowsiness detection research. In doing so, we have bridged the gap between an existing embedded system and its actual implementation in vehicles to bring drowsiness technology a step closer to prevalent real-life implementation. Citation: Technologies PubDate: 2022-12-30 DOI: 10.3390/technologies11010008 Issue No:Vol. 11, No. 1 (2022)
Authors:Randi Karlsen, Anders Andersen First page: 110 Abstract: Nudging provides a way to gently influence people to change behavior towards a desired goal, e.g., by moving towards a healthier or more environmentally friendly lifestyle. Personalized and context-aware digital nudging (named smart nudging) can be a powerful tool for efficient nudging by tailoring nudges to the current situation of each individual user. However, designing smart nudges is challenging, as different users may need different supports to improve their behavior. Determining the next nudge for a specific user must be done based on the user’s current situation, abilities, and potential for improvement. In this paper, we focus on the challenge of designing the next nudge by presenting a novel classification of nudges that distinguishes between (i) nudges that are impossible for the user to follow, (ii) nudges that are unlikely to be followed, and (iii) probable nudges that the user can follow. The classification is tailored to individual users based on user profiles, current situations, and knowledge of previous behaviors. This paper describes steps in the nudge design process and a novel set of principles for designing smart nudges. Citation: Technologies PubDate: 2022-10-22 DOI: 10.3390/technologies10060110 Issue No:Vol. 10, No. 6 (2022)
Authors:Victor A. Kovtunenko First page: 111 Abstract: Degradation of a catalyst layer in polymer electrolyte membrane fuel cells is considered, which is caused by electrochemical reactions of the platinum ion dissolution and oxide coverage. An accelerated stress test is applied, where the electric potential cycling is given by a non-symmetric square profile. Computer simulations of the underlying one-dimensional Holby–Morgan model predict durability of the fuel cell operating. A sensitivity analysis based on the variance quantifies how loss of the platinum mass subjected to the degradation is impacted by the variation of fitting parameters in the model. Citation: Technologies PubDate: 2022-10-28 DOI: 10.3390/technologies10060111 Issue No:Vol. 10, No. 6 (2022)
Authors:Yugo Asakawa, Takeo Oku, Masashi Kido, Atsushi Suzuki, Riku Okumura, Masanobu Okita, Sakiko Fukunishi, Tomoharu Tachikawa, Tomoya Hasegawa First page: 112 Abstract: Perovskite photovoltaic devices added with tin (Sn) dichloride and copper (Cu) bromide were fabricated and characterized. The thin film devices were prepared by an ordinary spin-coating technique using an air blowing method in ambient air. A decaphenylcyclopentasilane layer was coated at the surface of perovskite layer and annealed at a high temperature of 190 °C. Conversion efficiencies and short-circuit current densities were improved for devices added with Sn and Cu compared with the standard devices. The energy gap of the perovskite crystal decreased through the Sn addition, which was also confirmed by first-principles calculations. Citation: Technologies PubDate: 2022-10-28 DOI: 10.3390/technologies10060112 Issue No:Vol. 10, No. 6 (2022)
Authors:Hossam A. Gabbar, Abdalrahman Elshora First page: 113 Abstract: In this paper, a modular multi-input, single output DC/DC converter is proposed to enhance the energy management of a fast-charging station for electric vehicles (EVs). The proposed bidirectional converter can work in different modes of operation with fewer components and a modular design to extend the input power sources and increase the charging power rate. The converter has several merits compared to the conventional converters, such as centralizing the control, reducing power devices, and reducing power conversion stages. By using MATLAB/Simulink, the converter was tested in many operation modes and was used to charge a Nissan Leaf EV’s battery (350 V, 60 Ah) from hybrid sources simultaneously and individually in power up to (17 kW). In addition, it was tested on a hardware scale at a low power rate (100 W) for the validation of the simulation work and the topology concept. In addition, its different losses and efficiency were calculated during the different operation modes. Citation: Technologies PubDate: 2022-11-07 DOI: 10.3390/technologies10060113 Issue No:Vol. 10, No. 6 (2022)
Authors:Nicholas Vandewetering, Koami Soulemane Hayibo, Joshua M. Pearce First page: 114 Abstract: Solar powering the increasing fleet of electrical vehicles (EV) demands more surface area than may be available for photovoltaic (PV)-powered buildings. Parking lot solar canopies can provide the needed area to charge EVs but are substantially costlier than roof- or ground-mounted PV systems. To provide a low-cost PV parking lot canopy to supply EV charging, in this study, we provide a full mechanical and economic analysis of three novel PV canopy systems: (1) an exclusively wood, single-parking-spot spanning system, (2) a wood and aluminum double-parking-spot spanning system, and (3) a wood and aluminum cantilevered system for curbside parking. All three systems can be scaled to any amount of EV parking spots. The complete designs and bill of materials (BOM) of the canopies are provided, along with basic instructions, and are released with an open-source license that will enable anyone to fabricate them. Analysis results indicate that single-span systems provide cost savings of 82–85%, double-span systems save 43–50%, and cantilevered systems save 31–40%. In the first year of operation, PV canopies can provide 157% of the energy needed to charge the least efficient EV currently on the market if it is driven the average driving distance in London, ON, Canada. Citation: Technologies PubDate: 2022-11-07 DOI: 10.3390/technologies10060114 Issue No:Vol. 10, No. 6 (2022)
Authors:Chin-Teng Lin, Hsiu-Yu Fan, Yu-Cheng Chang, Liang Ou, Jia Liu, Yu-Kai Wang, Tzyy-Ping Jung First page: 115 Abstract: The modelling of trust values on agents is broadly considered fundamental for decision-making in human-autonomous teaming (HAT) systems. Compared to the evaluation of trust values for robotic agents, estimating human trust is more challenging due to trust miscalibration issues, including undertrust and overtrust problems. From a subjective perception, human trust could be altered along with dynamic human cognitive states, which makes trust values hard to calibrate properly. Thus, in an attempt to capture the dynamics of human trust, the present study evaluated the dynamic nature of trust for human agents through real-time multievidence measures, including human states of attention, stress and perception abilities. The proposed multievidence human trust model applied an adaptive fusion method based on fuzzy reinforcement learning to fuse multievidence from eye trackers, heart rate monitors and human awareness. In addition, fuzzy reinforcement learning was applied to generate rewards via a fuzzy logic inference process that has tolerance for uncertainty in human physiological signals. The results of robot simulation suggest that the proposed trust model can generate reliable human trust values based on real-time cognitive states in the process of ongoing tasks. Moreover, the human-autonomous team with the proposed trust model improved the system efficiency by over 50% compared to the team with only autonomous agents. These results may demonstrate that the proposed model could provide insight into the real-time adaptation of HAT systems based on human states and, thus, might help develop new ways to enhance future HAT systems better. Citation: Technologies PubDate: 2022-11-08 DOI: 10.3390/technologies10060115 Issue No:Vol. 10, No. 6 (2022)
Authors:Sergey N. Grigoriev, Anna A. Okunkova, Marina A. Volosova, Khaled Hamdy, Alexander S. Metel First page: 116 Abstract: Aluminum-based ceramics are used in industry to produce cutting tools that resist extreme mechanical and thermal load conditions during the machining of Ni-based and high-entropy alloys. There is wide field of application also in the aerospace industry. Microtexturing of cutting ceramics reduces contact loads and wear of cutting tools. However, most of the published works are related to the electrical discharge machining of alumina in hydrocarbons, which creates risks for the personnel and equipment due to the formation of chemically unstable dielectric carbides (methanide Al3C4 and acetylenide Al2(C2)3). An alternative approach for wire electrical discharge machining Al2O3 in the water-based dielectric medium using copper tape of 40 µm thickness and TiO2 powder suspension was proposed for the first time. The performance was evaluated by calculating the material removal rate for various combinations of pulse frequency and TiO2 powder concentration. The obtained kerf of 54.16 ± 0.05 µm in depth demonstrated an increasing efficiency of more than 1.5 times with the closest analogs for the workpiece thickness up to 5 mm in height. The comparison of the performance (0.0083–0.0084 mm3/s) with the closest analogs shows that the results may correlate with the electrical properties of the assisting materials. Citation: Technologies PubDate: 2022-11-11 DOI: 10.3390/technologies10060116 Issue No:Vol. 10, No. 6 (2022)
Authors:Yangyang Zhao, Henrik Jensen First page: 117 Abstract: The importance of learning from experience is incontrovertible; however, little is studied regarding the digitalization of in- and inter-project lessons learned in modern organizational practices. As a critical part of organizational knowledge, lessons learned are known to help organizations adapt to the ever-changing world via the complex systems development projects they use to capitalize on and to develop their competitive advantage. In this paper, we introduce the concept of human-centered digitalization for this unique type of organizational knowledge and explain why this approach to managing lessons learned for complex systems development projects is necessary. Drawing from design thinking and systems thinking theories, we further outline the design principles for guiding actions and provide a case study of their implementation in automated systems projects for maritime industries. Citation: Technologies PubDate: 2022-11-16 DOI: 10.3390/technologies10060117 Issue No:Vol. 10, No. 6 (2022)
Authors:Sergei Tarasov, Alihan Amirov, Andrey Chumaevskiy, Nikolay Savchenko, Valery E. Rubtsov, Aleksey Ivanov, Evgeniy Moskvichev, Evgeny Kolubaev First page: 118 Abstract: Friction stir welding (FSW) of titanium alloy was carried out using liquid cooling of the FSW tool made of heat-resistant nickel superalloy. Cooling of the nickel superalloy tool was performed by means of circulating water inside the tool. The FSW joints were characterized by microstructures and mechanical strength. The mechanical strength of the joints was higher than that of the base metal. Citation: Technologies PubDate: 2022-11-18 DOI: 10.3390/technologies10060118 Issue No:Vol. 10, No. 6 (2022)
Authors:Olamilekan Shobayo, Reza Saatchi, Shammi Ramlakhan First page: 119 Abstract: Paediatric wrist fractures are commonly seen injuries at emergency departments. Around 50% of the X-rays taken to identify these injuries indicate no fracture. The aim of this study was to develop a model using infrared thermal imaging (IRTI) data and multilayer perceptron (MLP) neural networks as a screening tool to assist clinicians in deciding which patients require X-ray imaging to diagnose a fracture. Forty participants with wrist injury (19 with a fracture, 21 without, X-ray confirmed), mean age 10.50 years, were included. IRTI of both wrists was performed with the contralateral as reference. The injured wrist region of interest (ROI) was segmented and represented by the means of cells of 10 × 10 pixels. The fifty largest means were selected, the mean temperature of the contralateral ROI was subtracted, and they were expressed by their standard deviation, kurtosis, and interquartile range for MLP processing. Training and test files were created, consisting of randomly split 2/3 and 1/3 of the participants, respectively. To avoid bias of participant inclusion in the two files, the experiments were repeated 100 times, and the MLP outputs were averaged. The model’s sensitivity and specificity were 84.2% and 71.4%, respectively. Further work involves a larger sample size, adults, and other bone fractures. Citation: Technologies PubDate: 2022-11-22 DOI: 10.3390/technologies10060119 Issue No:Vol. 10, No. 6 (2022)
Authors:Chara Makri, Didem Gürdür Broo, Andy Neely First page: 120 Abstract: In this study, we reviewed aircraft accidents in order to understand how autonomy and safety has been managed in the aviation industry, with the aim of transferring our findings to autonomous cyber-physical systems (CPSs) in general. Through the qualitative analysis of 26 reports of aircraft accidents that took place from 2016 to 2022, we identified the most common contributing factors and the actors involved in aircraft accidents. We found that accidents were rarely the result of a single event or actor, with the most common contributing factor being non-adherence to standard operating procedures (SOPs). Considering that the aviation industry has had decades to perfect their SOPs, it is important for CPSs not only to consider the actors and causes that may contribute to safety-related issues, but also to consider well-defined reporting practices, as well as the different levels of mechanisms checked by diverse stakeholders, in order to minimise the cascading nature of such events to improve safety. In addition to proposing a new definition of safety, in this study we suggest reviewing high-reliability organisations to offer further insights as part of future research on CPS safety. Citation: Technologies PubDate: 2022-11-24 DOI: 10.3390/technologies10060120 Issue No:Vol. 10, No. 6 (2022)
Authors:Mirella Carneiro, Victor Oliveira, Fernanda Oliveira, Marco Teixeira, Milena Pinto First page: 121 Abstract: Electrical signals are generated and transmitted through plants in response to stimuli caused by external environment factors, such as touching, luminosity, and leaf burning. By analyzing a specific plant’s electrical responses, it is possible to interpret the impact of external aspects in the plasma membrane potential and, thus, determine the cause of the electrical signal. Moreover, these signals permit the whole plant structure to be informed almost instantaneously. This work presents a brief discussion of plants electrophysiology theory and low-cost signal conditioning circuits, which are necessary for the acquisition of plants’ electrical signals. Two signal conditioning circuits, which must be chosen depending on the signal to be measured, are explained in detail and electrical simulation results, performed in OrCAD Capture Software are presented. Furthermore, Monte Carlo simulations were performed to evaluate the impact of components variations on the accuracy and efficiency of the signal conditioning circuits. Those simulations showed that, even after possible component variations, the filters’ cut-off frequencies had at most 4% variation from the mean. Citation: Technologies PubDate: 2022-11-25 DOI: 10.3390/technologies10060121 Issue No:Vol. 10, No. 6 (2022)
Authors:Dimitrios Zikos, Nailya DeLellis First page: 122 Abstract: Health analytics frequently involve tasks to predict outcomes of care. A foundational predictor of clinical outcomes is the medical diagnosis (Dx). The most used expression of medical Dx is the International Classification of Diseases (ICD-10-CM). Since ICD-10-CM includes >70,000 codes, it is computationally expensive and slow to train models with. Alternative lower-dimensionality alternatives include clinical classification software (CCS) and diagnosis-related groups (MS-DRGs). This study compared the predictive power of these alternatives against ICD-10-CM for two outcomes of hospital care: inpatient mortality and length of stay (LOS). Naïve Bayes (NB) and Random Forests models were created for each Dx system to examine their predictive performance for inpatient mortality, and Multiple Linear Regression models for the continuous LOS variable. The MS-DRGs performed highest for both outcomes, even outperforming ICD-10-CM. The admitting ICD-10-CM codes were, surprisingly, not underperformed by the primary ICD-10-CM Dxs. The CCS system, although having a much lower dimensionality than ICD-10-CM, has only slightly lower performance while the refined version of CCS only slightly outperformed the old CCS. Random Forests outperformed NB for MS-DRG, and ICD-10-CM, by a large margin. Results can provide insights to understand the compromise from using lower-dimensionality representations in clinical outcome studies. Citation: Technologies PubDate: 2022-11-28 DOI: 10.3390/technologies10060122 Issue No:Vol. 10, No. 6 (2022)
Authors:Yu Liu, Kyoung-Don Kang, Mi Jin Doe First page: 123 Abstract: Depression is a serious mood disorder that is under-recognized and under-treated. Recent advances in mobile/wearable technology and ML (machine learning) have provided opportunities to detect the depressed moods of participants in their daily lives with their consent. To support high-accuracy, ubiquitous detection of depressed mood, we propose HADD, which provides new capabilities. First, HADD supports multimodal data analysis in order to enhance the accuracy of ubiquitous depressed mood detection by analyzing not only objective sensor data, but also subjective EMA (ecological momentary assessment) data collected by using mobile devices. In addition, HADD improves upon the accuracy of state-of-the-art ML algorithms for depressed mood detection via effective feature selection, data augmentation, and two-stage outlier detection. In our evaluation, HADD significantly enhanced the accuracy of a comprehensive set of ML models for depressed mood detection. Citation: Technologies PubDate: 2022-11-29 DOI: 10.3390/technologies10060123 Issue No:Vol. 10, No. 6 (2022)
Authors:Philipp Kolmer, Abhay Shukla, Jian Song First page: 124 Abstract: The development of autonomous vehicles and the integration of new information and communication technologies are making the reliability of electrical systems and components in modern vehicles increasingly important. Electrical connectors are a crucial component in an electrical on-board system. They are exposed to a wide variety of influences by the environment and operating conditions. Thus, the degradation of electrical connectors can occur. Material and surface analysis methods are the tools used to analyze the degradation mechanisms in connectors after lifetime tests, as well as in field operations. Within the framework of this study, a wide variety of methods from the analytical scope are presented and discussed. The connector surfaces degraded by different failure mechanisms are analyzed using various material and surface analysis methods. The quality and the nature of the analyses results obtained from various analysis methods are compared. Also, this study deals with the benefits and limitations, as well as the effort and the specific challenges of different material and surface analytical methods for the evaluation of failure mechanisms from the point of view of a material and surface analyst. Citation: Technologies PubDate: 2022-11-29 DOI: 10.3390/technologies10060124 Issue No:Vol. 10, No. 6 (2022)
Authors:Aso Bozorgpanah, Vicenç Torra, Laya Aliahmadipour First page: 125 Abstract: There is an increasing need to provide explainability for machine learning models. There are different alternatives to provide explainability, for example, local and global methods. One of the approaches is based on Shapley values. Privacy is another critical requirement when dealing with sensitive data. Data-driven machine learning models may lead to disclosure. Data privacy provides several methods for ensuring privacy. In this paper, we study how methods for explainability based on Shapley values are affected by privacy methods. We show that some degree of protection still permits to maintain the information of Shapley values for the four machine learning models studied. Experiments seem to indicate that among the four models, Shapley values of linear models are the most affected ones. Citation: Technologies PubDate: 2022-12-01 DOI: 10.3390/technologies10060125 Issue No:Vol. 10, No. 6 (2022)
Authors:Valeri Mladenov, Vesselin Chobanov, Verzhinia Ivanova First page: 126 Abstract: The legislation at the EU level is decisive in developing the local flexibility market. At the current stage, there are far-from-sufficient regulations on the local flexibility market, which can be perceived as a major barrier. The scope of this article is to explore the operational principles of the European local flexibility market and to assess the regulation of emerging flexible markets in order to help a new policy framework that facilitates the integration of flexible assets in the distribution grid. Although the evaluation primarily focuses on current regulations, numerous modifications are still being made to them, such as those brought about by the implementation of the Clean Energy Package. The possibility of the research material quickly becoming outdated makes this difficult. To reduce this risk, we also examine current debates over potential restrictions; nonetheless, the core of the report mainly applies to laws and policies that were in force prior to the second half of 2022. An examination and analysis of potential flexibility providers’ motives to offer flexibility on a local flexibility market were conducted concurrently with the regulatory assessment. The inquiry was initiated by identifying resources that may be used to improve the flexibility of the electrical system but are underutilized. Underutilized resources refer to assets that are already part of society, such as efficient energy use, support for behavioral changes, heating systems (such as district heating, heat pumps, and thermal inertia), as well as underutilized energy storage capacities that are underutilized in terms of supplying flexibility to the electric grid. Resources were found via conducting interviews and studying scientific literature. The rules and guidelines for the emerging local flexibility markets are examined in this study. The regulations need to be continually improved because they are far from complete. Citation: Technologies PubDate: 2022-12-02 DOI: 10.3390/technologies10060126 Issue No:Vol. 10, No. 6 (2022)
Authors:Martin Mikelj, Marko Nagode, Jernej Klemenc, Domen Šeruga First page: 127 Abstract: Manhole covers must provide adequate strength and durability over the intended service life. In addition to operating loads, the lifespan of cast-iron manhole covers is strongly influenced by the conditions of installation and cover placement after opening or closing. These can include a vertical displacement from the plane of the carriageway during installation or the settlement of the terrain around the cover afterwards. After opening and closing the cover, the lid often only partially touches the support surface due to stones or other impurities caught on the surface or under the cover. These events can significantly affect the lifespan of the cover. In this study, an improved geometry of the cast-iron cover is proposed and analysed from an operational strength point of view. Initially, the geometry and potential critical points were scrutinized, and typical loads on the cover were determined. A numerical model was then set to simulate the behaviour during typical operation. In the simulations, the impact of the critical scenarios was analysed by dividing the impact parameters into individual levels. The simulation results reveal the suitability of the improved cover geometry. Citation: Technologies PubDate: 2022-12-06 DOI: 10.3390/technologies10060127 Issue No:Vol. 10, No. 6 (2022)
Authors:Jiří Hanzl, Jan Pečman, Ladislav Bartuška, Ondrej Stopka, Branislav Šarkan First page: 128 Abstract: The presented article deals with research on the dependence between road vehicle fuel consumption and the longitudinal height profile of the road. The main research goal is to investigate the difference in fuel consumption during acceleration on different longitudinal profiles of the road (i.e., flat surface, downhill) based on the actual investigation. In the first part of the article, important factors influencing fuel consumption during vehicle acceleration are summarized and a review of literature dealing with this issue is carried out. The next part focuses on the very real-world measurement. In addition to fuel consumption, other parameters were recorded that could be detected by a professional measuring laboratory. In the final part of the article, all the recorded data are evaluated, compared with research question and an actual example is given. Based on the evaluation, it could be concluded that approx. 100 L of fuel can be saved in one week thanks to the implemented measures. Thereafter, recommended possibilities for further use of these findings in technical practice are outlined in the conclusion. Citation: Technologies PubDate: 2022-12-09 DOI: 10.3390/technologies10060128 Issue No:Vol. 10, No. 6 (2022)
Authors:Constantin Waubert de Puiseau, Dimitri Tegomo Nanfack, Hasan Tercan, Johannes Löbbert-Plattfaut, Tobias Meisen First page: 129 Abstract: The warehousing industry is faced with increasing customer demands and growing global competition. A major factor in the efficient operation of warehouses is the strategic storage location assignment of arriving goods, termed the dynamic storage location assignment problem (DSLAP). This paper presents a real-world use case of the DSLAP, in which deep reinforcement learning (DRL) is used to derive a suitable storage location assignment strategy to decrease transportation costs within the warehouse. The DRL agent is trained on historic data of storage and retrieval operations gathered over one year of operation. The evaluation of the agent on new data of two months shows a 6.3% decrease in incurring costs compared to the currently utilized storage location assignment strategy which is based on manual ABC-classifications. Hence, DRL proves to be a competitive solution alternative for the DSLAP and related problems in the warehousing industry. Citation: Technologies PubDate: 2022-12-11 DOI: 10.3390/technologies10060129 Issue No:Vol. 10, No. 6 (2022)
Authors:Sergey Grigoriev, Alexander Metel, Marina Volosova, Yury Melnik, Enver Mustafaev First page: 130 Abstract: To improve the quality of a part manufactured by the additive method, it is necessary to eliminate the porosity and high roughness of its surface, as well as to deposit a coating on it. For this purpose, in the present work, we studied the combined processing in a gas discharge plasma of complex shape parts obtained by the additive manufacturing method, which includes explosive ablation of surface protrusions when voltage pulses are applied to the part immersed in the plasma; polishing with a concentrated beam of fast neutral argon atoms at a large angle of incidence on the surface of the part, and magnetron deposition of a coating on it with assistance by fast argon atoms. Combined processing made it possible to completely get rid of porosity and reduce the surface roughness from Ra ~ 5 µm to Ra ~ 0.05 µm. Citation: Technologies PubDate: 2022-12-11 DOI: 10.3390/technologies10060130 Issue No:Vol. 10, No. 6 (2022)
Authors:F. J. Gómez-Uceda, M. Varo-Martínez, J. C. Ramírez-Faz, R. López-Luque, L. M. Fernández-Ahumada First page: 131 Abstract: Renewable energies play an important role as a solution to the challenge of satisfying the growing global energy demand without jeopardizing the achievements in the fight against climate change. Given this panorama, different countries, including Spain, have developed policies to promote renewable energies. One of the technologies that benefit from these policies is photovoltaics. In Spain, the number of grid-connected photovoltaic installations has increased significantly in recent years. It is interesting to analyze the panorama of these facilities and identify the trends in their design criteria. In this line, in this work, the projects of 70 grid-connected photovoltaic installations distributed across Spain were analyzed. For that purpose, benchmarking techniques were applied, facilitating the systematization of information, the intercomparison of plants and the identification of trends and efficient solutions. A set of characteristic indicators of each installation was defined, and a statistical analysis of them was developed. Likewise, a tool was developed that allows the designers of this type of photovoltaic plant to compare the design parameters chosen for their installations with those of the surrounding area. Therefore, this work provides knowledge about the current panorama of photovoltaic implementation applicable to its future advance. Citation: Technologies PubDate: 2022-12-13 DOI: 10.3390/technologies10060131 Issue No:Vol. 10, No. 6 (2022)
Authors:Huiting Zha, Wenjun Shang, Jie Xu, Feng Feng, Hongyun Kong, Enlai Jiang, Yuan Ma, Chao Xu, Pingfa Feng First page: 132 Abstract: Nomex honeycomb composites are used extensively in aerospace, automotive, and other industries due to their superior material properties. However, the tool wear during their machining can compromise the processing accuracy and the stability of the whole machining process, thus studies on the tool wear and strengthening method are urgently needed. This study presents a radial difference calculation method (RDC) to evaluate the tool wear of the disc cutter quantitatively in both conventional cutting and ultrasonic assisted cutting. The morphology of the tool wear process and its characteristics were analyzed. Two different heat treatments (salt bath quenching and vacuum quenching) were carried out to strengthen the tool performance. The research results demonstrated that ultrasonic vibration could significantly reduce the tool wear of the disc cutter, by up to 36%, after the same machining time. Salt bath quenching and vacuum quenching can both strengthen the tool performance. Particularly, after vacuum quenching treatment, the disc cutter’s metallographic grains were refined, and the tool wear could be reduced by 64%, compared to the as-received disc cutter. The findings in this study could be instructive to obtain further understanding of the machining mechanism and to improve methods in ultrasonic assisted cutting of Nomex honeycomb composites. Citation: Technologies PubDate: 2022-12-16 DOI: 10.3390/technologies10060132 Issue No:Vol. 10, No. 6 (2022)
Authors:Panagiotis Stavropoulos First page: 98 Abstract: Zero-defect manufacturing and flexibility in production lines is driven from accurate Digital Twins (DT) which monitor, understand, and predict the behavior of a manufacturing process under different conditions while also adapting to them by deciding the right course of action in time intervals relevant to the captured phenomenon. During the exploration of the alternative approaches for the development of process twins, significant efforts should be made for the selection of acquisition devices and signal-processing techniques to extract meaningful information from the studied process. As such, in Industry 4.0 era, machine tools are equipped with embedded sensors that give feedback related to the process efficiency and machine health, while additional sensors are installed to capture process-related phenomena, feeding simulation tools and decision-making algorithms. Although the maturity level of some process mechanisms facilitates the representation of the physical world with the aid of physics-based models, data-driven models are proposed for complex phenomena and non-mature processes. This paper introduces the components of Digital Twin and gives emphasis on the steps that are required to transform obtained data into meaningful information that will be used in a Digital Twin. The introduced steps are identified in a case study from the milling process. Citation: Technologies PubDate: 2022-08-30 DOI: 10.3390/technologies10050098 Issue No:Vol. 10, No. 5 (2022)
Authors:Christos Papadopoulos, Marios Kourtelesis, Anastasia Maria Moschovi, Konstantinos Miltiadis Sakkas, Iakovos Yakoumis First page: 99 Abstract: Burning fuels with high sulfur content leads to SOx emissions, especially SO2, which leads to various environmental and health problems. The maritime sector is responsible for 13% of the global anthropogenic emissions of SO2. Thus, the International Maritime Organization (IMO) has issued a protocol, known as MARPOL Annex VI, which aims to further limit SO2 emissions derived from ships along with NOx, particulate matter and volatile organic compound emissions. This has led ship owners and operators to choose between more expensive fuels with low sulfur content or to apply a DeSOx solution, which still allows them to use the cheapest heavy fuel oil. The current work reviews the state-of-the-art DeSOx solutions both for the maritime and land-based sector. Next, it proposes an alternative cheaper and environmentally friendly DeSOx solution based on the selective reduction of SO2 to elemental sulfur by utilizing a catalytic converter based on metal oxides, similar to the ones used in the automotive industry. Finally, it reviews the most promising metal oxide catalysts reported in the literature for the selective reduction of SO2 towards elemental sulfur. Citation: Technologies PubDate: 2022-08-30 DOI: 10.3390/technologies10050099 Issue No:Vol. 10, No. 5 (2022)
Authors:Meiwen Guo, Zhenheng Huang, Liang Wu, Cheng Ling Tan, Jianping Peng, Xingcheng Guo, Hong Chen First page: 100 Abstract: Blockchain technology and its applications have recently become a research hotspot. Its three core technologies, distributed ledger, smart contract, and consensus mechanism, provide trust-enhancing features such as tamper-proof records, full traceability, and data decentralization for a wide range of applications. This paper investigates the use of blockchain technology in environmental health. It investigates indicators such as the number of articles published, author collaboration network, research institution network, and keyword co-occurrence in this field between 2014 and 2021. It describes and analyzes the development and connotations of these indicators. Many scholars have conducted in-depth studies on blockchain in various areas. Still, there are few cross-over studies on environmental health and a lack of cross-over studies on technology application in multiple fields. The current study investigates the evolution of research on the application of blockchain technology in environmental health, as well as potential development patterns and research trends, to provide a theoretical foundation for the application and sustainability of blockchain technology in this field. Citation: Technologies PubDate: 2022-09-07 DOI: 10.3390/technologies10050100 Issue No:Vol. 10, No. 5 (2022)
Authors:Fadel Kawtharani, Bruno Serio, Geraldine Guida, Patrice Twardowski, Mohammad Hammoud First page: 101 Abstract: Angular and spectral separations of thermal radiation have become a key challenge in solar concentration or thermal management of sources radiating at extremely high or low temperatures. Reflections obtained from electromagnetic theory in an open cavity geometry increase the emission and absorption compared to a flat surface due to the cavity effect. In this paper, in order to obtain the directional emission of geometric surfaces (V-Grooves) using ray tracing and studying the propagation of light, a new algorithm is developed. The numerical simulations take into account the materials properties of both facets of the V-shape, thus simulating an original asymmetric and a multilayer V-shape and providing a very interesting directive thermal emission behavior. We evaluated the emission behavior from the reflection and emission coefficients of different rays at different angles for different parameters (materials properties, wavelength, and geometry). The simulations of a V-groove showed that due to the different reflections occurring inside an aluminum V-cavity with an aperture angle of 28°, the emissivity was well enhanced by 86% in the normal direction compared to a flat surface made of the same material. Moreover, using the original asymmetric opposite-sided materials (Al and Si) in a V- groove, it was possible to separate and control the emission by focusing the radiation or directing different spectral bands in different directions. Citation: Technologies PubDate: 2022-09-12 DOI: 10.3390/technologies10050101 Issue No:Vol. 10, No. 5 (2022)
Authors:Alexandre Staub, Lucas Brunner, Adriaan B. Spierings, Konrad Wegener First page: 102 Abstract: Additive manufacturing (AM) processes offer a good opportunity to manufacture three- dimensional objects using various materials. However, many of the processes, notably laser Powder bed fusion, face limitations in manufacturing specific geometrical features due to their physical constraints, such as the thermal conductivity of the surrounding medium, the internal stresses, and the warpage or weight of the part being manufactured. This work investigates the opportunity to use machine learning algorithms in order to identify hard-to-manufacture geometrical features. The segmentation of these features from the main body of the part permits the application of different manufacturing strategies to improve the overall manufacturability. After selecting features that are particularly problematic during laser powder bed fusion using stainless steel, an algorithm is trained using simple geometries, which permits the identification of hard-to-manufacture features on new parts with a success rate of 88%, showing the potential of this approach. Citation: Technologies PubDate: 2022-09-16 DOI: 10.3390/technologies10050102 Issue No:Vol. 10, No. 5 (2022)
Authors:Valentina A. Yurova, Gleb Velikoborets, Andrei Vladyko First page: 103 Abstract: The development and manufacture of prosthetic limbs is one of the important tendencies of the development of medical techniques. Taking into account the development of modern electronic technology and automated systems and its mobility and compactness, the actual task is to create a prosthesis that will be close to a fully functioning human limb in its anthropomorphic properties and will be capable of reproducing its basic actions with a high accuracy. The paper analyzes the main directions in the development of a control system for electronic limb prostheses. The description and results of the practical implementation of a prototype of an anthropomorphic prosthetic arm and its control system are presented in the paper. We developed an anthropomorphic multi-finger artificial hand for utilization in robotic research and teaching applications. The designed robotic hand is a low-cost alternative to other known 3D printed robotic hands and has 21 degrees of freedom—4 degrees of freedom for each finger, 3 degrees for the thumb and 2 degrees responsible for the position of the robotic hand in space. The open-source mechanical design of the presented robotic arm has mass-dimensional and motor parameters close to the human hand, with the possibility of autonomous battery operation, the ability to connect different control systems, such as from a computer, an electroencephalograph, a touch glove. Citation: Technologies PubDate: 2022-09-21 DOI: 10.3390/technologies10050103 Issue No:Vol. 10, No. 5 (2022)
Authors:Ji-Eun Yu First page: 104 Abstract: The metaverse has been evolving the internet-based education represented by e-learning. Metaverse technology is currently being developed as a platform centered on content-based information industries. It can be classified into four categories: augmented reality, lifelogging, mirror worlds, and virtual worlds. Although current research finds that the potential of the metaverse is not small in the education world, and metaverse technology is already being used in the sports world, concrete applications have not been investigated. The main aims of this study, which started with this purpose, can be summarized as follows. The metaverse environment is still in its rudimentary stage, and its use related to physical education subjects is only at the game level. In the future, the utilization of the metaverse by physical education subjects will be possible in universities only when more specialized technology is grafted into various sports. Ultimately, this study contributes to expanding the scope and depth of follow-up research by offering basic data showing the direction of metaverse-based physical education. Citation: Technologies PubDate: 2022-09-23 DOI: 10.3390/technologies10050104 Issue No:Vol. 10, No. 5 (2022)
Authors:Mahesh Chavan, Vijayakumar Varadarajan, Shilpa Gite, Ketan Kotecha First page: 105 Abstract: COVID-19 patients require effective diagnostic methods, which are currently in short supply. In this study, we explained how to accurately identify the lung regions on the X-ray scans of such people’s lungs. Images from X-rays or CT scans are critical in the healthcare business. Image data categorization and segmentation algorithms have been developed to help doctors save time and reduce manual errors during the diagnosis. Over time, CNNs have consistently outperformed other image segmentation algorithms. Various architectures are presently based on CNNs such as ResNet, U-Net, VGG-16, etc. This paper merged the U-Net image segmentation and ResNet feature extraction networks to construct the ResUNet++ network. The paper’s novelty lies in the detailed discussion and implementation of the ResUNet++ architecture in lung image segmentation. In this research paper, we compared the ResUNet++ architecture with two other popular segmentation architectures. The ResNet residual block helps us in lowering the feature reduction issues. ResUNet++ performed well compared with the UNet and ResNet architectures by achieving high evaluation scores with the validation dice coefficient (96.36%), validation mean IoU (94.17%), and validation binary accuracy (98.07%). The novelty of this research paper lies in a detailed discussion of the UNet and ResUNet architectures and the implementation of ResUNet++ in lung images. As per our knowledge, until now, the ResUNet++ architecture has not been performed on lung image segmentation. We ran both the UNet and ResNet models for the same amount of epochs and found that the ResUNet++ architecture achieved higher accuracy with fewer epochs. In addition, the ResUNet model gave us higher accuracy (94%) than the UNet model (92%). Citation: Technologies PubDate: 2022-09-30 DOI: 10.3390/technologies10050105 Issue No:Vol. 10, No. 5 (2022)
Authors:Vittoria Biagi, Angela Russo First page: 106 Abstract: Organizations must quickly adapt their processes to understand the dynamic nature of modern business environments. As highlighted in the literature, centralized governance supports decision-making and performance measurement processes in technology companies. For this reason, a reliable decision-making system with an integrated data model that enables the rapid collection and transformation of data stored in heterogeneous and different sources is needed. Therefore, this paper proposes the design of a data model to implement data-driven governance through a literature review of adopted approaches. The lack of a standardized procedure and a disconnection between theoretical frameworks and practical application has emerged. This paper documented the suggested approach following these steps: (i) mapping of monitoring requirements to the data structure, (ii) documentation of ER diagram design, and (iii) reporting dashboards used for monitoring and reporting. The paper helped fill the gaps highlighted in the literature by supporting the design and development of a DWH data model coupled with a BI system. The application prototype shows benefits for top management, particularly those responsible for governance and operations, especially for risk monitoring, audit compliance, communication, knowledge sharing on strategic areas of the company, and identification and implementation of performance improvements and optimizations. Citation: Technologies PubDate: 2022-10-08 DOI: 10.3390/technologies10050106 Issue No:Vol. 10, No. 5 (2022)
Authors:Phuong Thanh Phan, Phong Thanh Nguyen First page: 107 Abstract: In the current market of integration and globalization, the competition between engineering and construction companies is increasing. Construction contractors can improve their competitiveness by evaluating and selecting qualified personnel for the construction engineering manager position for their company’s civil engineering projects. However, most personnel evaluation and selection models in the construction industry rely on qualitative techniques, which leads to unsuitable decisions. To overcome this problem, this paper presents evaluation criteria and proposes a new model for selecting construction managers based on the evaluation based on the distance from the average solution approach (EDASA). The research results showed that EDASA has many strengths, such as solving the problem faster when the number of evaluation criteria or the number of alternatives is increased. Citation: Technologies PubDate: 2022-10-14 DOI: 10.3390/technologies10050107 Issue No:Vol. 10, No. 5 (2022)
Authors:Md Jasim Uddin, Jasmin Hassan, Dennis Douroumis First page: 108 Abstract: Over the last 10 years, inkjet printing technologies have advanced significantly and found several applications in the pharmaceutical and biomedical sector. Thermal inkjet printing is one of the most widely used techniques due to its versatility in the development of bioinks for cell printing or biosensors and the potential to fabricate personalized medications of various forms such as films and tablets. In this review, we provide a comprehensive discussion of the principles of inkjet printing technologies highlighting their advantages and limitations. Furthermore, the review covers a wide range of case studies and applications for precision medicine. Citation: Technologies PubDate: 2022-10-21 DOI: 10.3390/technologies10050108 Issue No:Vol. 10, No. 5 (2022)
Authors:Raquel de M. Barbosa, Amélia M. Silva, Classius F. da Silva, Juliana C. Cardoso, Patricia Severino, Lyghia M. A. Meirelles, Arnobio A. da Silva-Junior, César Viseras, Joel Fonseca, Eliana B. Souto First page: 109 Abstract: This paper presents a comprehensive review of the main types of vaccines approaching production technology, regulatory parameters, and the quality control of vaccines. Bioinformatic tools and computational strategies have been used in the research and development of new pharmaceutical products, reducing the time between supposed pharmaceutical product candidates (R&D steps) and final products (to be marketed). In fact, in the reverse vaccinology field, in silico studies can be very useful in identifying possible vaccine targets from databases. In addition, in some cases (subunit or RNA/ DNA vaccines), the in silico approach permits: (I) the evaluation of protein immunogenicity through the prediction of epitopes, (II) the potential adverse effects of antigens through the projection of similarity to host proteins, (III) toxicity and (IV) allergenicity, contributing to obtaining safe, effective, stable, and economical vaccines for existing and emerging infectious pathogens. Additionally, the rapid growth of emerging infectious diseases in recent years should be considered a driving force for developing and implementing new vaccines and reassessing vaccine schedules in companion animals, food animals, and wildlife disease control. Comprehensive and well-planned vaccination schedules are effective strategies to prevent and treat infectious diseases. Citation: Technologies PubDate: 2022-10-21 DOI: 10.3390/technologies10050109 Issue No:Vol. 10, No. 5 (2022)
Authors:Manoj Gupta First page: 77 Abstract: In the area of Materials Science and Engineering, the tetrahedron comprising of processing, microstructure, properties and performance as four vertex corners is always key to develop new materials and to convert them to a useful shape for end application with the best properties possible [...] Citation: Technologies PubDate: 2022-06-24 DOI: 10.3390/technologies10040077 Issue No:Vol. 10, No. 4 (2022)
Authors:O. M. Gradov First page: 78 Abstract: The interaction of an electromagnetic beam with a sharp boundary of a dense cold semi-limited plasma was considered in the case of a normal wave incidence on the plasma surface. The possibility of the appearance of an electrostatic field outside the plasma was revealed, the intensity of which decreased according to the power law with a distance from the plasma and the center of the beam. It was possible to form cavities with a reduced electron density, being each electromagnetic resonators, which probed deeply into the dense plasma and couldexist in a stable state for a long period. Citation: Technologies PubDate: 2022-06-29 DOI: 10.3390/technologies10040078 Issue No:Vol. 10, No. 4 (2022)
Authors:Francisco Javier Ramírez-Arias, Enrique Efren García-Guerrero, Esteban Tlelo-Cuautle, Juan Miguel Colores-Vargas, Eloisa García-Canseco, Oscar Roberto López-Bonilla, Gilberto Manuel Galindo-Aldana, Everardo Inzunza-González First page: 79 Abstract: In brain–computer interfaces (BCIs), it is crucial to process brain signals to improve the accuracy of the classification of motor movements. Machine learning (ML) algorithms such as artificial neural networks (ANNs), linear discriminant analysis (LDA), decision tree (D.T.), K-nearest neighbor (KNN), naive Bayes (N.B.), and support vector machine (SVM) have made significant progress in classification issues. This paper aims to present a signal processing analysis of electroencephalographic (EEG) signals among different feature extraction techniques to train selected classification algorithms to classify signals related to motor movements. The motor movements considered are related to the left hand, right hand, both fists, feet, and relaxation, making this a multiclass problem. In this study, nine ML algorithms were trained with a dataset created by the feature extraction of EEG signals.The EEG signals of 30 Physionet subjects were used to create a dataset related to movement. We used electrodes C3, C1, CZ, C2, and C4 according to the standard 10-10 placement. Then, we extracted the epochs of the EEG signals and applied tone, amplitude levels, and statistical techniques to obtain the set of features. LabVIEW™2015 version custom applications were used for reading the EEG signals; for channel selection, noise filtering, band selection, and feature extraction operations; and for creating the dataset. MATLAB 2021a was used for training, testing, and evaluating the performance metrics of the ML algorithms. In this study, the model of Medium-ANN achieved the best performance, with an AUC average of 0.9998, Cohen’s Kappa coefficient of 0.9552, a Matthews correlation coefficient of 0.9819, and a loss of 0.0147. These findings suggest the applicability of our approach to different scenarios, such as implementing robotic prostheses, where the use of superficial features is an acceptable option when resources are limited, as in embedded systems or edge computing devices. Citation: Technologies PubDate: 2022-06-30 DOI: 10.3390/technologies10040079 Issue No:Vol. 10, No. 4 (2022)
Authors:Makendran Chandrakasu, Karunanidhi Suthandhiram, Shiferaw Garoma, Bekesha Merea, Balaguru Sethuraman First page: 80 Abstract: In this paper, the self-curing process was considered and found to be a better alternative to the conventional curing process for concrete structures in Ethiopia. It is well known that water plays a significant role in the curing process of preparing concrete in the construction industry. A good quality water is required for the conventional curing process, but that is scarce in Ethiopia. Curing concrete for bridges and roads is difficult in Ethiopia due to the poor quality and scarcity of water. In this study, Polyethylene Glycol (PEG) 600, a self-curing process, is considered as an alternative. Using the M40 Grade mix, four different percentages of PEG-600, 0.0, 0.5, 1.0, and 1.5 of cement weight, were studied, and the specimens were tested. Here, M40 grade stands for “a concrete mix with a characteristic compressive strength of 40 N/mm2, i.e., 40 Newton per square millimeter”. Additionally, the mechanical strengths and properties of both conventional and self-cured processed concretes were calculated and compared. The present investigation concludes that PEG 600 offers significant results for self-curing concrete. The study procedure, results, and recommendations are presented in the text of the paper. Citation: Technologies PubDate: 2022-07-05 DOI: 10.3390/technologies10040080 Issue No:Vol. 10, No. 4 (2022)
Authors:Jiaqi Li, Yun Wang, Ke-Lin Du First page: 81 Abstract: The multivehicle routing problem (MVRP) is a variation of the classical vehicle routing problem (VRP). The MVRP is to find a set of routes by multiple vehicles that serve multiple customers at a minimal total cost while the travelling-time delay due to traffic congestion is tolerated. It is an NP problem and is conventionally solved by metaheuristics such as evolutionary algorithms. For the MVRP in a distribution network, we propose an optimal distribution path optimization method that is composed of a distribution sequence search stage and a distribution path search stage that exploits a divide-and-conquer strategy, inspired by the idea of dynamic programming. Several optimization objectives subject to constraints are defined. The search for the optimal solution of the number of distribution vehicles, distribution sequence, and path is implemented by using an improved genetic algorithm (GA), which is characterized by an operation for preprocessing infeasible solutions, an elitist’s strategy, a sequence-related two-point crossover operator, and a reversion mutation operator. The improved GA outperforms the simple GA in terms of total cost, route topology, and route feasibility. The proposed method can help to reduce costs and increase efficiency for logistics and transportation enterprises and can also be used for flow-shop scheduling by manufacturing enterprises. Citation: Technologies PubDate: 2022-07-05 DOI: 10.3390/technologies10040081 Issue No:Vol. 10, No. 4 (2022)
Authors:Indranil Ghosh, Muhammad Mahbubur Rashid, Pallabi Ghosh, Shukranul Mawa, Rupal Roy, Md Manjurul Ahsan, Kishor Datta Gupta First page: 82 Abstract: In this paper, a numerical study has been undertaken on the susceptible-infected-recovered (SIR) epidemic model that encompasses the mechanisms of the evolution of disease transmission; a prophylactic vaccination strategy in the susceptible populations, depending on the infective individuals. We furnish numerical and graphical simulation combined with explicit series solutions of the proposed model using the New Iterative Method (NIM) and Modified New Iterative Method (MNIM). The analytic-numeric New Iterative Method failed to deliver accurate solution for the large time domain. A new reliable algorithm based on NIM, the coupling of the Laplace transforms, and the New Iterative method is called Modified New Iterative Method (MNIM) which is presented to enhance the validity domain of NIM techniques. The convergence analysis of the MNIM has also been illustrated. The simulation results show that the vaccination strategy can slow down the spread of the epidemic rapidly. Numerical results illustrate the excellent performance of the MNIM and show that the modified method is much more accurate than the NIM. Citation: Technologies PubDate: 2022-07-06 DOI: 10.3390/technologies10040082 Issue No:Vol. 10, No. 4 (2022)
Authors:Hossam A. Gabbar, Yasser Elsayed, Manir Isham, Abdalrahman Elshora, Abu Bakar Siddique, Otavio Lopes Alves Esteves First page: 83 Abstract: In recent years, the foment for sustainable and reliable micro energy grid (MEG) systems has increased significantly, aiming mainly to reduce the dependency on fossil fuels, provide low-cost clean energy, lighten the burden, and increase the stability and reliability of the regional electrical grid by having interconnected and centralized clean energy sources, and ensure energy resilience for the population. A resilient energy system typically consists of a system able to control the energy flow effectively by backing up the intermittent output of renewable sources, reducing the effects of the peak demand on the grid side, considering the impact on dispatch and reliability, and providing resilient features to ensure minimum operation interruptions. This paper aims to demonstrate a real-time simulation of a microgrid capable of predicting and ensuring energy lines run correctly to prevent or shorten outages on the grid when it is subject to different disturbances by using energy management with a fail-safe operation and redundant control. In addition, it presents optimized energy solutions to enhance the situational awareness of energy grid operators based on a graphical and interactive user interface. To expand the MEG’s capability, the setup integrates real implemented hardware components with the emulated components based on real-time simulation using OPAL-RT OP4510. Most hardware components are implemented in the lab to be modular, expandable, and flexible for various test scenarios, including fault imitation. They include but are not limited to the power converter, inverter, battery charger controller, relay drivers, programmable AC and DC loads, PLC, and microcontroller-based controller. In addition, the real-time simulation offers a great variety of power sources and energy storage such as wind turbine emulators and flywheels in addition to the physical sources such as solar panels, supercapacitors, and battery packs. Citation: Technologies PubDate: 2022-07-12 DOI: 10.3390/technologies10040083 Issue No:Vol. 10, No. 4 (2022)
Authors:Ondrej Stopka, Patrik Gross, Jan Pečman, Jiří Hanzl, Mária Stopková, Martin Jurkovič First page: 84 Abstract: This article deals with pick-up and delivery activities in a selected company that focuses on the distribution of products in the gastronomic sector of the market and suggests how to make the present approach more efficient. The introductory part of the article clarifies the meanings of basic concepts related to the issue of optimizing the logistics processes in the company. The crucial goal is to analyze the existing pick-up and delivery technology and then, in the application part of the article, to propose adequate measures in the context of streamlining these activities with their technical and economic evaluation. An analysis of current delivery routes, which are used for the distribution of gastronomic products, is first performed. Thereafter, the routes are optimized with the aim of minimizing the total distance traveled by using the Operations Research methods, namely: the Hungarian method, Vogel approximation method, nearest neighbor method and the Routin route planner which is based on a principle of the Greedy algorithm. At the end of the article, a technical and economical evaluation of the findings is discussed, wherein the individual results of optimization through selected methods are first compared and then, new optimized routes are selected. Citation: Technologies PubDate: 2022-07-14 DOI: 10.3390/technologies10040084 Issue No:Vol. 10, No. 4 (2022)
Authors:Muhammad Usman Hadi, Nik Hazmi Nik Suhaimi, Abdul Basit First page: 85 Abstract: From a single meter that measures the entire home’s electrical demand, energy disaggregation calculates appliance-by-appliance electricity consumption. Non-intrusive load monitoring (NILM), also known as energy disaggregation, tries to decompose aggregated energy consumption data and estimate each appliance’s contribution. Recently, methodologies based on Artificial Intelligence (AI) have been proposed commonly used in these models, which can be expensive to run on a server or prohibitive when the target device has limited capabilities. AI-based models are typically computationally expensive and require a lot of storage. It is not easy to reduce the computing cost and size of a neural network without sacrificing performance. This study proposed an efficient non-parametric supervised machine learning network (ENSML) architecture with a smaller size, and a quick inference time without sacrificing performance. The proposed architecture can maximise energy disaggregation performance and predict new observations based on past ones. The results showed that employing the ENSML model considerably increased the accuracy of energy prediction in 99 percent of cases. Citation: Technologies PubDate: 2022-07-16 DOI: 10.3390/technologies10040085 Issue No:Vol. 10, No. 4 (2022)
Authors:Ignacio Algredo-Badillo, Brenda Sánchez-Juárez, Kelsey A. Ramírez-Gutiérrez, Claudia Feregrino-Uribe, Francisco López-Huerta, Johan J. Estrada-López First page: 86 Abstract: The significant volume of sharing of digital media has recently increased due to the pandemic, raising the number of unauthorized uses of these media, such as emerging unauthorized copies, forgery, the lack of copyright, and electronic fraud, among others. In particular, several applications integrate services or products such as music distribution, content management, audiobooks, streaming, and so on, which require users to demonstrate and guarantee their audio ownership. The use of acoustic fingerprint technology has emerged as a solution that is widely used to secure audio applications. This technique extracts and analyzes certain information that identifies the inherent properties of a partial or complete audio file. In this paper, we introduce two audio fingerprinting hardware architectures with a feature extraction system based on spectrogram saliency maps (SSM) and a brute-force search. The first of these conducts a search in 33 saliency maps of 32 × 32 pixels in size. After analyzing the first algorithm, a second architecture is proposed, in which the saliency map is reduced to 27 × 25 pixels, requiring 75.67% fewer hardware resources, lowering the power consumption by 64.58%, and improving the efficiency by 3.19 times via a throughput reduction of 22.29%. Citation: Technologies PubDate: 2022-07-19 DOI: 10.3390/technologies10040086 Issue No:Vol. 10, No. 4 (2022)
Authors:Spyridon Nikolaidis, Rodrigo Picos First page: 87 Abstract: The International Conference on Modern Circuits and Systems Technologies (MOCAST) was first launched in 2012 inside the framework of a European Project (JEWEL) [...] Citation: Technologies PubDate: 2022-07-20 DOI: 10.3390/technologies10040087 Issue No:Vol. 10, No. 4 (2022)
Authors:Angelos Papavlasopoulos, Agnes Papadopoulou, Andreas Floros, Andreas Giannakoulopoulos First page: 88 Abstract: The aim of this research is to discover the bond of entropy and the experience of video game immersion, using an Interpretative Phenomenological Analysis (IPA) to interpret the immersive experiences of players and how this bond of entropy and immersion could be transferred on other immersive technologies. The experiment was conducted on a selection of low-entropy scenes in three video games belonging to the genre of interactive drama. Six players were selected as the sample group for this research, based on their playthrough experiences of the games Heavy Rain (2010), Until Dawn (2015) and Dark Pictures Anthology: Man of Medan (2019) on the PlayStation platform. By monitoring the levels of entropy and immersion during their playthroughs, this research explores the potential of transferring immersion through the use of entropy from digital games to other immersive technologies. According to the research highlights and through data interpretation, entropy is found to be immensely influential upon achieving and maintaining narrative, physical and emotional immersion, and its effect could be further applied to other immersive technologies sharing a common ground with digital games, which features are further examined in finer detail in the current research. Citation: Technologies PubDate: 2022-07-20 DOI: 10.3390/technologies10040088 Issue No:Vol. 10, No. 4 (2022)
Authors:Taline S. Almeida, Caio A. da Cruz Souza, Mariana B. de Cerqueira e Silva, Fabiana P. R. Batista, Ederlan S. Ferreira, André L. S. Santos, Laura N. Silva, Carlisson R. Melo, Cristiane Bani, M. Lucia Bianconi, Juliana C. Cardoso, Ricardo L. C. de Albuquerque-Júnior, Raquel de Melo Barbosa, Matheus M. Pereira, Eliana B. Souto, Cleide M. F. Soares, Patrícia Severino First page: 89 Abstract: The increased mortality rates associated with antibiotic resistance has become a significant public health problem worldwide. Living beings produce a variety of endogenous compounds to defend themselves against exogenous pathogens. The knowledge of these endogenous compounds may contribute to the development of improved bioactive ingredients with antimicrobial properties, useful against conventional antibiotic resistance. Cowpea is an herbaceous legume of great interest due to its high protein content and high productivity rates. The study of genetic homology of vicillin (7S) from cowpea (Vigna unguiculata L.) with vicilins from soybean and other beans, such as adzuki, in addition to the need for further studies about potential biological activities of this vegetable, led us to seek the isolation of the vicilin fraction from cowpea and to evaluate the potential in vitro inhibitory action of pathogenic microorganisms. The cowpea beta viginin protein was isolated, characterized, and hydrolyzed in silico and in vitro by two enzymes, namely, pepsin and chymotrypsin. The antimicrobial activity of the protein hydrolysate fractions of cowpea flour was evaluated against Staphylococcus aureus and Pseudomonas aeruginosa, confirming the potential use of the peptides as innovative antimicrobial agents. Citation: Technologies PubDate: 2022-07-21 DOI: 10.3390/technologies10040089 Issue No:Vol. 10, No. 4 (2022)
Authors:Giulia Rizzoli, Francesco Barbato, Pietro Zanuttigh First page: 90 Abstract: The perception of the surrounding environment is a key requirement for autonomous driving systems, yet the computation of an accurate semantic representation of the scene starting from RGB information alone is very challenging. In particular, the lack of geometric information and the strong dependence on weather and illumination conditions introduce critical challenges for approaches tackling this task. For this reason, most autonomous cars exploit a variety of sensors, including color, depth or thermal cameras, LiDARs, and RADARs. How to efficiently combine all these sources of information to compute an accurate semantic description of the scene is still an unsolved task, leading to an active research field. In this survey, we start by presenting the most commonly employed acquisition setups and datasets. Then we review several different deep learning architectures for multimodal semantic segmentation. We will discuss the various techniques to combine color, depth, LiDAR, and other modalities of data at different stages of the learning architectures, and we will show how smart fusion strategies allow us to improve performances with respect to the exploitation of a single source of information. Citation: Technologies PubDate: 2022-07-25 DOI: 10.3390/technologies10040090 Issue No:Vol. 10, No. 4 (2022)
Authors:Kaveh Shahverdi, Soheil Hashemi, Sadaf Sarafan, Hung Cao First page: 91 Abstract: Our objective is to design triple-band implantable antennas with wide bandwidths and appropriate sizes for biomedical applications. The targeted design frequencies are 400 MHz, 2.4 GHz, and the new Wi-Fi band of 5.7 GHz. Three triple-band antennas with bandwidth improvements are presented to insure all-time data connection. The proposed triple-band implantable antennas benefit from combining long-distance data transfer at lower frequency bands and a higher effective bandwidth, and high-speed communications at higher frequency bands, which will have flexibility for a variety of applications. A comprehensive explanation of the design procedure to achieve multiple-band implantable antennas is provided. Furthermore, miniaturization techniques are utilized to design antennas in compact sizes suitable for biomedical applications. In this paper, three-layer structures including skin, fat, and muscle are used for the designs, then antennas are placed in the chest, neck, head, and hand of different human voxels to compare antennas’ performance. Additionally, normal and overweight human effects on antenna performance were compared. Antennas have 2 to 6 dBi directivity for telemetry usage, and they are designed to satisfy the absorption limit for the human body to keep the Specific Absorption Rate (SAR) averaged over 1 g of tissue less than 1.6 W/kg and over 10 g of tissue less than 2 W/kg, according to IEEE standard. The antennas include fractal, meandered, and comb types with sizes of 1.4 mm × 10 mm × 10 mm, 3.04 mm × 10 mm × 17.25 mm, and 1.4 mm × 12 mm × 12 mm, respectively. The designed antenna showed an impedance bandwidth of 53 MHz to 120 MHz, 90 MHz to 320 MHz, and 300 MHz to 1200 MHz at the three bands. The meandered antenna was selected for validation of simulations, and its S parameters were measured in the equivalent liquid phantom of body tissues. Citation: Technologies PubDate: 2022-08-04 DOI: 10.3390/technologies10040091 Issue No:Vol. 10, No. 4 (2022)
Authors:Jordina Orcajo Hernández, Pau Fonseca i Casas First page: 92 Abstract: The software selection process in the context of a big company is not an easy task. In the Business Intelligence area, this decision is critical, since the resources needed to implement the tool are huge and imply the participation of all organization actors. We propose to adopt the systemic quality model to perform a neutral comparison between four business intelligence self-service tools. To assess the quality, we consider eight characteristics and eighty-two metrics. We built a methodology to evaluate self-service BI tools, adapting the systemic quality model. As an example, we evaluated four tools that were selected from all business intelligence platforms, following a rigorous methodology. Through the assessment, we obtained two tools with the maximum quality level. To obtain the differences between them, we were more restrictive increasing the level of satisfaction. Finally, we got a unique tool with the maximum quality level, while the other one was rejected according to the rules established in the methodology. The methodology works well for this type of software, helping in the detailed analysis and neutral selection of the final software to be used for the implementation. Citation: Technologies PubDate: 2022-08-10 DOI: 10.3390/technologies10040092 Issue No:Vol. 10, No. 4 (2022)
Authors:Christopher Small First page: 93 Abstract: NASA’s Gateway to Astronaut Photography of Earth contains over 30,000 photos of ~2500 cataloged urban lightscapes (anthropogenic night light) taken from the International Space Station. A subset of over 100 of these multispectral DSLR photos are of sufficient spatial resolution, sharpness and exposure to be potentially useful for broadband spectral characterization of urban lightscapes. Spectral characterization of multiple urban lightscapes can provide a basis for quantifying intra and interurban variability in night light brightness, color and extent, as well as the potential for change analyses. A comparative analysis of simulated atmospheric transmissivity from the MODTRAN radiative transfer model indicates that the spectral slopes of transmissivity spectra are relatively insensitive model atmospheres, with variations in atmospheric path length and aerosol optical depth primarily affecting the bias of the spectrum rather than the slope. A mosaic of 18 intercalibrated, transmissivity-compensated RGB photos renders a spectral feature space bounded by four clearly defined spectral endmembers corresponding to white, yellow and red light sources, with brightness modulated by a dark background endmember. These four spectral endmembers form the basis of a linear spectral mixture model which can be inverted to provide estimates of the areal fraction of each endmember present within every pixel field of view. The resulting spectral feature spaces consistently show two distinct mixing trends extending from the dark endmember to flat spectrum (white–yellow) and warm spectrum (orange) sources. The distribution of illuminated pixels is strongly skewed toward a lower luminance background of warm spectrum street lighting with brighter lights, generally corresponding to point sources and major thoroughfares. Citation: Technologies PubDate: 2022-08-13 DOI: 10.3390/technologies10040093 Issue No:Vol. 10, No. 4 (2022)
Authors:Arash Heidari, Nima Jafari Navimipour, Mehmet Unal First page: 94 Abstract: Persia was the early name for the territory that is currently recognized as Iran. Iran’s proud history starts with the Achaemenid Empire, which began in the 6th century BCE (c. 550). The Iranians provided numerous innovative ideas in breakthroughs and technologies that are often taken for granted today or whose origins are mostly unknown from the Achaemenid Empire’s early days. To recognize the history of computing systems in Iran, we must pay attention to everything that can perform computing. Because of Iran’s historical position in the ancient ages, studying the history of computing in this country is an exciting subject. The history of computing in Iran started very far from the digital systems of the 20th millennium. The Achaemenid Empire can be mentioned as the first recorded sign of using computing systems in Persia. The history of computing in Iran started with the invention of mathematical theories and methods for performing simple calculations. This paper also attempts to shed light on Persia’s computing heritage elements, dating back to 550 BC. We look at both the ancient and current periods of computing. In the ancient section, we will go through the history of computing in the Achaemenid Empire, followed by a description of the tools used for calculations. Additionally, the transition to the Internet era, the formation of a computer-related educational system, the evolution of data networks, the growth of the software and hardware industry, cloud computing, and the Internet of Things (IoT) are all discussed in the modern section. We highlighted the findings in each period that involve vital sparks of computing evolution, such as the gradual growth of computing in Persia from its early stages to the present. The findings indicate that the development of computing and related technologies has been rapidly accelerating recently. Citation: Technologies PubDate: 2022-08-15 DOI: 10.3390/technologies10040094 Issue No:Vol. 10, No. 4 (2022)
Authors:Saeid Saeidi Aminabadi, Atae Jafari-Tabrizi, Dieter Paul Gruber, Gerald Berger-Weber, Walter Friesenbichler First page: 95 Abstract: In the manufacturing of injection-molded plastic parts, it is essential to perform a non-destructive (and, in some applications, contactless) three-dimensional measurement and surface inspection of the injection-molded part to monitor the part quality. The measurement method depends strongly on the shape and the optical properties of the part. In this study, a high-precision (±5 µm) and high-speed system (total of 24 s for a complete part dimensional measurement) was developed to measure the dimensions of a piano-black injection-molded part. This measurement should be done in real time and close to the part’s production time to evaluate the quality of the produced parts for future online, closed-loop, and predictive quality control. Therefore, a novel contactless, three-dimensional measurement system using a multicolor confocal sensor was designed and manufactured, taking into account the nominal curved shape and the glossy black surface properties of the part. This system includes one linear and one cylindrical moving axis, as well as one confocal optical sensor for radial R-direction measurements. A 6 DOF (degrees of freedom) robot handles the part between the injection molding machine and the measurement system. An IPC coordinates the communications and system movements over the OPC UA communication network protocol. For validation, several repeatability tests were performed at various speeds and directions. The results were compared using signal similarity methods, such as MSE, SSID, and RMS difference. The repeatability of the system in all directions was found to be in the range of ±5 µm for the desired speed range (less than 60 mm/s–60 degrees/s). However, the error increases up to ±10 µm due to the fixture and the suction force effect. Citation: Technologies PubDate: 2022-08-17 DOI: 10.3390/technologies10040095 Issue No:Vol. 10, No. 4 (2022)
Authors:Eduardo Guzmán, Armando Maestro First page: 96 Abstract: Synthetic micro/nanomotors (MNMs) are human-made machines characterized by their capacity for undergoing self-propelled motion as a result of the consumption of chemical energy obtained from specific chemical or biochemical reactions, or as a response to an external actuation driven by a physical stimulus. This has fostered the exploitation of MNMs for facing different biomedical challenges, including drug delivery. In fact, MNMs are superior systems for an efficient delivery of drugs, offering several advantages in relation to conventional carriers. For instance, the self-propulsion ability of micro/nanomotors makes possible an easier transport of drugs to specific targets in comparison to the conventional distribution by passive carriers circulating within the blood, which enhances the drug bioavailability in tissues. Despite the promising avenues opened by the use of synthetic micro/nanomotors in drug delivery applications, the development of systems for in vivo uses requires further studies to ensure a suitable biocompatibility and biodegradability of the fabricated engines. This is essential for guaranteeing the safety of synthetic MNMs and patient convenience. This review provides an updated perspective to the potential applications of synthetic micro/nanomotors in drug delivery. Moreover, the most fundamental aspects related to the performance of synthetic MNMs and their biosafety are also discussed. Citation: Technologies PubDate: 2022-08-17 DOI: 10.3390/technologies10040096 Issue No:Vol. 10, No. 4 (2022)
Authors:Fang Ding, Bo Wang, Qianbin Zhang, Aiguo Wang First page: 97 Abstract: To improve the accuracy and real-time performance of vehicle recognition in an advanced driving-assistance system (ADAS), a vehicle recognition method based on radar and camera information fusion is proposed. Firstly, the millimeter-wave radar and camera are calibrated jointly, the radar recognition information is mapped on the camera image, and the region of interest is established. Then, based on operator edge detection, global threshold binarization is performed on the image of the region of interest (ROI) to obtain the contour information of the vehicle in front, and Hough transform is used to fit the vehicle contour edge straight line. Finally, a sliding window is established according to the symmetry characteristics of the fitting line, which can find the vehicle region with the highest symmetry and complete the identification of the vehicle. The experimental results show that compared to the original recognition region of the radar, the mean square error of this algorithm is reduced by 13.4 and the single frame detection time is reduced to 28 ms. It is proven that the algorithm has better accuracy and a faster detection rate, and it can solve the problem of an inaccurate recognition region caused by radar error. Citation: Technologies PubDate: 2022-08-22 DOI: 10.3390/technologies10040097 Issue No:Vol. 10, No. 4 (2022)
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