Authors:Hasanah Putri, Sinta Novanana Pages: 639 - 644 Abstract: The 5G System is being developed and enhanced to provide unparalleled connectivity to connect everyone and everything, everywhere. 5G technology use cases depicts the prospects of 5G network model to revolutionize Industry and Education is not an exception . To catch up with the latest technology in the higher education environment there’s a need to have 5G Lab as a Service (LaaS) in education to simulate the real network experience. The software is the key to this generation as the virtualization, modularity and abstraction become more popular in the implementation and that the cloud computing is nowadays becoming the trend of technology. This paper presents a software selection between free5gc, magma and open5gs program. The 5G lab located in Jakarta Indonesia has the ability where in physical and virtual resources can be accessed and managed from any location in the world. Free5gc opensource software solution is the most suitable software which can be used as LaaS in Higher Education laboratory. With a LaaS, we can configuration, connection, and troubleshoot 5G infrastructure including radio access networks, core networks, and transportation networks. PubDate: 2023-10-28 Issue No:Vol. 69, No. 4 (2023)
Authors:Arkadiusz Zięba, Martin Kollar, Krzysztof Tatarczyk, Jarosław Sadowski Pages: 645 - 654 Abstract: IP scheduled throughput defined according to 3GPP TS 36.314 reflects user throughput regardless of traffic characteristics, and therefore has become one of the most important indicators for monitoring Quality of Service (QoS) of the end user in Evolved Universal Terrestrial Radio Access Network (E-UTRAN). However, networks built on a distributed architecture make the above definition impossible to be applied directly due to the implementation challenges. This paper gives an overview of the classical Long Term Evolution (LTE) architecture as opposed to Dual Connectivity (DC) topology and focuses on a novel method of solving the calculation issue with the IP scheduled throughput measurement in edge computing environment. Experimental results show a good agreement with the real end user perception. PubDate: 2023-10-28 Issue No:Vol. 69, No. 4 (2023)
Authors:Gulzat Ziyatbekova, Aigerim Mazakova, Sholpan Jomartova, Waldemar Wójcik, Talgat Mazakov Pages: 655 - 660 Abstract: The article explores the possibility of automated linearization of nonlinear models. The process of constructing a linearized model for a nonlinear system is quite laborious and is practically unrealizable when the dimension n is greater than 3. Also, when building a linearized model, there is a "human factor" that does not guarantee the correctness of the calculation of arithmetic expressions. In this regard, the task of automating the process of linearization of the original nonlinear model is relevant. On the basis of linearized models, one can further investigate such properties of the original model as stability and controllability. Based on the application of computer algebra, a constructive algorithm for the linearization of a system of nonlinear ordinary differential equations has been developed. Developed software on MatLab. The efficiency of the proposed algorithm has been demonstrated on applied problems. For a mathematical model of the dynamics of an unmanned aerial vehicle, described by a system of ordinary differential equations of the 6th order, a linearized system is automatically constructed. Two procedures have been developed for the mathematical model of a two-link robot. The first procedure allows one to normalize the mathematical model obtained on the basis of the Lagrange equations of the second kind. The second procedure uses the normalized mathematical model to build its linearized copy.The linearized models obtained were further used to investigate the stability of the original models.In order to account for possible inaccuracies in the measurement of model technical parameters arising from wear and tear or variability in temperature operating conditions, the linearized model is assumed to be interval. For the interval linearized model, the procedure of constructing the corresponding interval characteristic polynomial and the corresponding Hurwitz matrix is automated. Based on the analysis of the properties of the main minors of the Hurwitz matrix, the stability of the system under study is analyzed. Keywords— Ordinary differential equation, Computer algebra, Stability, Controllability, MatLab PubDate: 2023-10-28 Issue No:Vol. 69, No. 4 (2023)
Authors:PG Suprith, Mohammed Riyaz Ahmed Pages: 661 - 667 Abstract: The future Internet of Things (IoT) era is anticipated to support computation-intensive and time-critical applications using edge computing for mobile (MEC), which is regarded as promising technique. However, the transmitting uplink performance will be highly impacted by the hostile wireless channel, the low bandwidth, and the low transmission power of IoT devices. Using edge computing for mobile (MEC) to offload tasks becomes a crucial technology to reduce service latency for computation-intensive applications and reduce the computational workloads of mobile devices. Under the restrictions of computation latency and cloud computing capacity, our goal is to reduce the overall energy consumption of all users, including transmission energy and local computation energy. In this article, the Deep Q Network Algorithm (DQNA) to deal with the data rates with respect to the user base in different time slots of 5G NOMA network. The DQNA is optimized by considering more number of cell structures like 2, 4, 6 and 8. Therefore, the DQNA provides the optimal distribution of power among all 3 users in the 5G network, which gives the increased data rates. The existing various power distribution algorithms like frequent pattern (FP), weighted least squares mean error weighted least squares mean error (WLSME), and Random Power and Maximal Power allocation are used to justify the proposed DQNA technique. The proposed technique which gives 81.6% more the data rates when increased the cell structure to 8. Thus 25% more in comparison to other algorithms like FP, WLSME Random Power and Maximal Power allocation. PubDate: 2023-10-28 Issue No:Vol. 69, No. 4 (2023)
Authors:Khazini Mohammed, Damou Mehdi, Souar Zeggai Pages: 669 - 673 Abstract: This Article presented the study of a single pacth antenna and array patch antenna. We will focus on the design based on a small size at a resonant frequency of 30GHz. using the software CST Microwave Studio (FEM method) and ADS software (Moments method) to find internal parameters (S... parameters, bandwidth ,VSWR) and external characteristics (gain, directivity and radiation pattern, efficiencies) . To increase the total gain of the antenna and to have a wider bandwidth band width and taking advantage of the functionality of the radiation overlap of several elements radiating in the same direction, we suggest the second and most important step to design a most important step to design an antenna array grouping patches identical to our first patch antenna proposed in first patch antenna proposed in the first step PubDate: 2023-10-28 Issue No:Vol. 69, No. 4 (2023)
Authors:Anna Witenberg Pages: 675 - 681 Abstract: The paper discusses the phenomena accompanying switching the sinusoidal excitation of an antenna on and off when the antenna is excited by a train of sinusoids containing several to several hundred periods. Transient phenomena are presented against the background of the resonant properties of the antenna. The processes of turning the antenna on and off take place under different conditions and therefore are different. When the antenna is switched on, the transient processes are determined by the antenna properties and the excitation properties. When the antenna is switched off, excitation is no longer present, and the properties of the antenna determine the transient process. We define a new measure of time: the effective light meter. PubDate: 2023-10-28 Issue No:Vol. 69, No. 4 (2023)
Authors:Imelda Uli Vistalina Simanjuntak, Sulistyaningsih Sulistyaningsih, Heryanto Heryanto, Dian Widi Astuti Pages: 683 - 690 Abstract: Research on improving the performance of microstrip antennas is continuously developing the following technology; this is due to its light dimensions, cheap and easy fabrication, and performance that is not inferior to other dimension antennas. Especially in telecommunications, microstrip antennas are constantly being studied to increase bandwidth and gain according to current cellular technology. Based on the problem of antenna performance limitations, optimization research is always carried out to increase the gain to become the antenna standard required by 5G applications. This research aims to increase the gain by designing a 5-element microstrip planar array antenna arrangement at a uniform distance (lamda/2) with edge weights at a frequency of 2.6 GHz, Through the 1x5 antenna design with parasitic patch, without parasitic, and using proximity coupling.This study hypothesizes that by designing an N-element microstrip planar array antenna arrangement at uniform spacing (lamda/2) with edge weights, a multi-beam radiation pattern character will be obtained so that to increase gain, parasitic patches contribute to antenna performance. This research contributes to improving the main lobe to increase the gain performance of the 1x5 planar array antenna. Based on the simulation results of a 1x5 microstrip planar array antenna using a parasitic patch and edge weighting, a gain value of 7.34 dB is obtained; without a parasitic patch, a gain value of 7.03 dB is received, using a parasitic patch and proximity coupling, a gain value of 2.29 dB is obtained. The antenna configuration with the addition of a parasitic patch, even though it is only supplied at the end (edge weighting), is enough to contribute to the parameters impedance, return loss, VSWR, and total gain based on the resulting antenna radiation pattern. The performance of the 1x5 microstrip planar array antenna with parasitic patch and double substrate (proximity coupling), which is expected to contribute even more to the gain side and antenna performance, has yet to be achieved. The 1x5 planar array antenna design meets the 5G gain requirement of 6 dB. Keyword—Microstrip antenna; edge weighting; parasitic patch; proximity coupling; 5G antenna gain. PubDate: 2023-10-28 Issue No:Vol. 69, No. 4 (2023)
Authors:Al-Khowarizmi Al-Khowarizmi, Marah Doly Nasution, Romi Fadillah Rahmat, Arif Ridho Lubis, Muharman Lubis Pages: 691 - 696 Abstract: Faster R-CNN is an algorithm development that continuously starts from CNN then R-CNN and Faster R-CNN. The development of the algorithm is needed to test whether the heuristic algorithm has optimal provisions. Broadly speaking, faster R-CNN is included in algorithms that are able to solve neural network and machine learning problems to detect a moving object. One of the moving objects in the current phenomenon is the use of masks. Where various countries in the world have issued endemic orations after the Covid 19 pandemic occurred. Detection tool has been prepared that has been tested at the mandatory mask door, namely for mask users. In this paper, the role of the Faster R-CNN algorithm has been carried out to detect masks poured on Internet of Thinks (IoT) devices to automatically open doors for standard mask users. From the results received that testing on the detection of moving mask objects when used reaches 100% optimal at a distance of 0.5 to 1 meter and 95% at a distance of 1.5 to 2 meters so that the process of sending detection signals to IoT devices can be carried out at a distance of 1 meter at the position mask users to automatic doors PubDate: 2023-10-28 Issue No:Vol. 69, No. 4 (2023)
Authors:Olena Kryvoruchko, Alona Desyatko, Igor Karpunin, Dmytro Hnatchenko, Myroslav Lakhno, Feruza Malikova, Ayezhan Turdaliev Pages: 697 - 705 Abstract: A mathematical model is proposed that makes it possible to describe in a conceptual and functional aspect the formation and application of a knowledge base (KB) for an intelligent information system (IIS). This IIS is developed to assess the financial condition (FC) of the company. Moreover, for circumstances related to the identification of individual weakly structured factors (signs). The proposed model makes it possible to increase the understanding of the analyzed economic processes related to the company's financial system. An iterative algorithm for IIS has been developed that implements a model of cognitive modeling. The scientific novelty of the proposed approach lies in the fact that, unlike existing solutions, it is possible to adjust the structure of the algorithm depending on the characteristics of a particular company, as well as form the information basis for the process of assessing the company's FC and the parameters of the cognitive model. PubDate: 2023-10-28 Issue No:Vol. 69, No. 4 (2023)
Authors:Valerii Lakhno, Maira Shalabayeva, Olena Kryvoruchko, Alona Desyatko, Vitaliy Chubaievskyi, Zhibek Alibiyeva Pages: 707 - 712 Abstract: A hardware-software system has been implemented to monitor the environmental state (EnvState) at the site of railway (RY) accidents and disasters. The proposed hardware-software system consists of several main components. The first software component, based on the queueing theory (QT), simulates the workload of emergency response units at the RY accident site. It also interacts with a central data processing server and information collection devices. A transmitter for these devices was built on the ATmega328 microcontroller. The hardware part of the environmental monitoring system at the RY accident site is also based on the ATmega328 microcontroller. In the hardware-software system for monitoring the EnvState at the RY accident site, the data processing server receives information via the MQTT protocol from all devices about the state of each sensor and the device's location at the RY accident or disaster site, accompanied by EnvState contamination. All data is periodically recorded in a database on the server in the appropriate format with timestamps. The obtained information can then be used by specialists from the emergency response headquarters. PubDate: 2023-10-28 Issue No:Vol. 69, No. 4 (2023)
Authors:Viktor Mashkov, Andrzej Smolarz, Volodymyr Lytvynenko Pages: 713 - 718 Abstract: The paper deals with alliances and coalitions that can be formed by the agents or entities. Alliance agents are assumed to cooperate and form coalitions for performing the tasks or missions. It is considered that alliance agents are unselfish. That is, they are more interested in achieving the common goal(s) than in getting personal benefits. In the paper, the concept of fuzzy alliance was introduced. A fuzzy alliance is considered as a generalization of a traditional alliance allowing agents to decide on the capabilities that their agents can and want to deliver to the coalition. Coalitions that fuzzy alliance agents can form were considered. The definition of the “best” coalition was explained. The method of how to find the “best” coalition among all possible coalitions was suggested and verified by computer simulation. PubDate: 2023-10-28 Issue No:Vol. 69, No. 4 (2023)
Authors:Xianlei Ge, Xiaoyan Li, Zhipeng Zhang Pages: 719 - 726 Abstract: Acquiring labels in anomaly detection tasks is expensive and challenging. Therefore, as an effective way to improve efficiency, pretraining is widely used in anomaly detection models， which enriches the model's representation capabilities, thereby enhancing both performance and efficiency in anomaly detection. In most pretraining methods, the decoder is typically randomly initialized. Drawing inspiration from the diffusion model, this paper proposed to use denoising as a task to pretrain the decoder in anomaly detection, which is trained to reconstruct the original noise-free input. Denoising requires the model to learn the structure, patterns, and related features of the data, particularly when training samples are limited. This paper explored two approaches on anomaly detection: simultaneous denoising pretraining for encoder and decoder, denoising pretraining for only decoder. Experimental results demonstrate the effectiveness of this method on improving model’s performance. Particularly, when the number of samples is limited, the improvement is more pronounced. PubDate: 2023-10-28 Issue No:Vol. 69, No. 4 (2023)
Authors:Serhii Semendiai, Yuliіa Tkach, Mykhailo Shelest, Oleksandr Korchenko, Ruslana Ziubina, Olga Veselska Pages: 727 - 732 Abstract: The article is devoted to the development of a method for increasing the efficiency of communication channels of unmanned aerial vehicles (UAVs) in the conditions of electronic warfare (EW). The author analyses the threats that may be caused by the use of electronic warfare against autonomous UAVs. A review of some technologies that can be used to create original algorithms for countering electronic warfare and increasing the autonomy of UAVs on the battlefield is carried out. The structure of modern digital communication systems is considered. The requirements of unmanned aerial vehicle manufacturers for onboard electronic equipment are analyzed, and the choice of the hardware platform of the target radio system is justified. The main idea and novelty of the proposed method are highlighted. The creation of a model of a cognitive radio channel for UAVs is considered step by step. The main steps of modeling the spectral activity of electronic warfare equipment are proposed. The main criteria for choosing a free spectral range are determined. The type of neural network for use in the target cognitive radio system is substantiated. The idea of applying adaptive coding in UAV communication channels using multicomponent turbo codes in combination with neural networks, which are simultaneously used for cognitive radio, has been further developed. PubDate: 2023-10-28 Issue No:Vol. 69, No. 4 (2023)
Authors:Luis Carlos Timana-Eraso, Diego Fernando Rueda-Pepinosa, Carlos Rene Suarez-Suarez, Jose Leon-Leon Pages: 733 - 744 Abstract: Long Range Wide Area Network (LoRaWAN) technology has established new concepts for long-range wireless communication, being widely used in the implementation of IoT solutions. Therefore, it is crucial to validate the coverage of the signal and to know the distance at which a LoRAWAN communication system can be connected. This document investigates LoRaWAN technology for cases based on urban environments, so it can be used as a guide for those projects that require predicting the connection distance range of a LoRaWAN link. In addition, it serves as a tool for the reader when it comes to predicting the coverage of Long-Range Wide Area Network (LoRaWAN) technology. Measurements were made in a LoRaWAN network deployed in urban environments, where RSSI measurements were made in the city of Bogotá D.C., Colombia. Experimentally RSSI values were compared with four different propagation models at a frequency of 915 MHz in urban environments. The contribution of this work is an adjustment to widely used prediction models, according to the recommendation of the International Telecommunications Union (ITU) ITU-R P.1546, which allows estimating coverage in scenarios with characteristics similar to Bogotá D.C. This allows to know with precision the coverage before implementing the LoRaWAN communications system at 915 MHz. The results of comparing field measurements with fitted propagation models show that the Okumura model is the best predictor of coverage with a minimum error rate. PubDate: 2023-10-28 Issue No:Vol. 69, No. 4 (2023)
Authors:Doan Perdana, Amirah Amaliah Sakhrul, Bayu Erfianto, Abdul Aziz Marwan Pages: 745 - 749 Abstract: This research proposed a model of Enhanced Distributed Channel Access (EDCA) scheme which is one of the techniques used in reducing collision and usually prioritized due to its contention window to determine the impact of distance change on the IEEE 802.11 ah standard. The proposed model was analyzed using the Markov Chain approach to determine the effect of distance change on collisions levels while the numerical were simulated using MATLAB. Moreover, the Markov chain solution was used to evaluate parameters such as throughput, energy consumption, and delay. The results showed the increment in RAW slot duration and the distance change for each station can reduce the performance on the standard and the scenario when the RAW slot duration was changed by 50 ms performed better than 100 ms and 250 ms. PubDate: 2023-10-28 Issue No:Vol. 69, No. 4 (2023)
Authors:Krzysztof Walkowiak, Daniel Szostak, Adam Włodarczyk, Andrzej Kasprzak Pages: 751 - 762 Abstract: Knowledge about future traffic in backbone optical networks may greatly improve a range of tasks that Communications Service Providers (CSPs) have to face. This work proposes a procedure for long-term traffic forecasting in optical networks. We formulate a long-term traffic forecasting problem as an ordinal classification task. Due to the optical networks’ (and other network technologies’) characteristics, traffic forecasting has been realized by predicting future traffic levels rather than the exact traffic volume. We examine different machine learning (ML) algorithms and compare them with time series algorithms methods. To evaluate the developed ML models, we use a quality metric, which considers the network resource usage. Datasets used during research are based on real traffic patterns presented by Internet Exchange Point in Seattle. Our study shows that ML algorithms employed for long-term traffic forecasting problem obtain high values of quality metrics. Additionally, the final choice of the ML algorithm for the forecasting task should depend on CSPs expectations. PubDate: 2023-10-28 Issue No:Vol. 69, No. 4 (2023)
Authors:Imelda Uli Vistalina Simanjuntak, Junas Haidi, Heryanto Heryanto, Lukman Medriavin Silalahi Pages: 763 - 768 Abstract: The problem of link availability and redundancy of server network devices that need to be on standby 24 hours must be met by banking companies. This problem still needs to be solved by data networks in banking companies that are used as the object of this research. Therefore, this study aims to analyze improving the standby network through simulation to increase network performance using the HSRP (Hot Standby Router Protocol) method as network redundancy to back up the network in the event of a disturbance. From the failover simulation results, when the device is actively down, the backup device succeeds in replacing it and acts as the active device. Network simulations without HSRP are packet loss values of 0%, 189.2 ms delay, 0.19 ms jitter, and 1.6 kbps throughput. In comparison, the implementation results on the network obtained a packet loss value of 0%, 108.6 ms delay, 0.1 ms jitter, and two kbps throughput. The network performance after using HSRP is better based on the simulation and implementation. Process downtime reduces, and network performance increases. Keywords—Link failover; HSRP (Hot Standby Router Protocol), downtime; throughput; jitter; delay. PubDate: 2023-10-28 Issue No:Vol. 69, No. 4 (2023)
Authors:Sharmini Enoch, Ifiok Otung Pages: 769 - 773 Abstract: The Non Line of Sight (NLOS) broadband wireless access provided by Worldwide Interoperability for Microwave Access (WiMAX) operating in 2-11 GHz frequency is susceptible to the effects of multipath propagation, diffraction fading, vegetation attenuation, shadowing loss etc. In order to overcome these effects effective fade mitigation techniques, have to be implemented. The Orthogonal Frequency Division Multiplexing- Multiple Input Multiple Output (OFDM-MIMO) is an efficient method that helps in combatting the fading and providing higher SNR to the WiMAX system. According to the IEEE 802.16 specification, for QPSK modulation, a threshold SNR of 6 dB is required for the link to operate. In the present work the use of OFDM-MIMO achieves a SNR above this operating threshold. PubDate: 2023-10-28 Issue No:Vol. 69, No. 4 (2023)
Authors:Minaxi Doorwar, P Malathi Pages: 775 - 784 Abstract: Multimedia networks utilize low-power scalar nodes to modify wakeup cycles of high-performance multimedia nodes, which assists in optimizing the power-to-performance ratios. A wide variety of machine learning models are proposed by researchers to perform this task, and most of them are either highly complex, or showcase low-levels of efficiency when applied to large-scale networks. To overcome these issues, this text proposes design of a Q-learning based iterative sleep-scheduling and fuses these schedules with an efficient hybrid bioinspired multipath routing model for large-scale multimedia network sets. The proposed model initially uses an iterative Q-Learning technique that analyzes energy consumption patterns of nodes, and incrementally modifies their sleep schedules. These sleep schedules are used by scalar nodes to efficiently wakeup multimedia nodes during adhoc communication requests. These communication requests are processed by a combination of Grey Wolf Optimizer (GWO) & Genetic Algorithm (GA) models, which assist in the identification of optimal paths. These paths are estimated via combined analysis of temporal throughput & packet delivery performance, with node-to-node distance & residual energy metrics. The GWO Model uses instantaneous node & network parameters, while the GA Model analyzes temporal metrics in order to identify optimal routing paths. Both these path sets are fused together via the Q-Learning mechanism, which assists in Iterative Adhoc Path Correction (IAPC), thereby improving the energy efficiency, while reducing communication delay via multipath analysis. Due to a fusion of these models, the proposed Q-Learning based Iterative sleep-scheduling & hybrid Bioinspired Multipath Routing model for Multimedia Networks (QIBMRMN) is able to reduce communication delay by 2.6%, reduce energy consumed during these communications by 14.0%, while improving throughput by 19.6% & packet delivery performance by 8.3% when compared with standard multimedia routing techniques. PubDate: 2023-10-28 Issue No:Vol. 69, No. 4 (2023)
Authors:Kiran V Shanbhag, Dayakshini Sathish Pages: 785 - 791 Abstract: Multicarrier modulation (MCM) based schemes have been a major contributing factor in revolutionizing cellular networks due to their ability to overcome fading. One of the popular scheme orthogonal frequency division multiple access (OFDMA), having been part of 4G, is also adapted as part of 5G enhanced mobile broadband (eMBB). Though it has several advantages, spectral efficiency (SE) and peak to average power ratio (PAPR) have been two major concerns which have attracted lot of attention resulting in proposals of several other MCM schemes. But most of these studies have treated the two issues independently. This paper in particular studies the subcarrier filtering approach to improve the spectral efficiency of MCM scheme and its impact on the overall PAPR of such schemes. The analysis shows that the PAPR improvement is also achieved by such filters meant for spectral confinement and the simulation results validate the same provoking a unified research direction less explored till now. PubDate: 2023-10-28 Issue No:Vol. 69, No. 4 (2023)
Authors:Basavaraj M. Angadi, Mahabaleshwar S. Kakkasageri Pages: 793 - 801 Abstract: Wireless Sensor Networks (WSN) acquired a lot of attention due to their widespread use in monitoring hostile environments, critical surveillance and security applications. In these applications, usage of wireless terminals also has grown significantly. Grouping of Sensor Nodes (SN) is called clustering and these sensor nodes are burdened by the exchange of messages caused due to successive and recurring re-clustering, which results in power loss. Since most of the SNs are fitted with nonrechargeable batteries, currently researchers have been concentrating their efforts on enhancing the longevity of these nodes. For battery constrained WSN concerns, the clustering mechanism has emerged as a desirable subject since it is predominantly good at conserving the resources especially energy for network activities. This proposed work addresses the problem of load balancing and Cluster Head (CH) selection in cluster with minimum energy expenditure. So here, we propose hybrid method in which cluster formation is done using unsupervised machine learning based kmeans algorithm and Fuzzy-logic approach for CH selection. PubDate: 2023-10-28 Issue No:Vol. 69, No. 4 (2023)
Authors:Konrad Kamiński, Wojciech Mazurczyk Pages: 803 - 810 Abstract: This research investigates the intricacies of X.509 certificates within a comprehensive corporate infrastructure. Spanning over two decades, the examined enterprise has heavily depended on its internal certificate authority and Public Key Infrastructure (PKI) to uphold its data and systems security. With the broad application of these certificates, from personal identification on smart cards to device and workstation authentication via Trusted Platform Modules (TPM), our study seeks to address a pertinent question on how prevalent are weak RSA keys within such a vast internal certificate repository. Previous research focused primarily on key sets publicly accessible from TLS and SSH servers or PGP key repositories. On the contrary, our investigation provides insights into the private domain of an enterprise, introducing new dimensions to this problem. Among our considerations are the trustworthiness of hardware and software solutions in generating keys and the consequential implications of identified vulnerabilities on organizational risk management. The obtained results can contribute to enhancing security strategies in enterprises. PubDate: 2023-10-28 Issue No:Vol. 69, No. 4 (2023)
Authors:Harith Hazim Thannoon, Ivan A. Hashim Pages: 811 - 817 Abstract: In this paper, Recursive Least Square (RLS) and Affine Projection (AP) adaptive filters are designed using Xilinx System Generator and implemented on the Spartan6 xc6slx16-2csg324 FPGA platform. FPGA platform utilizes the non-restoring division algorithm and the COordinate Rotation DIgital Computer (CORDIC) division algorithm to perform the division task of the RLS and AP adaptive filters. The Non-restoring division algorithm demonstrates efficient performance in terms of convergence speed and signal-to-noise ratio. In contrast, the CORDIC division algorithm requires 31 cycles for division initialization, whereas the non-restoring algorithm initializes division in just one cycle. To validate the effectiveness of the proposed filters, a set of ten ECG records from the BIT-MIT database is used to test their ability to remove Power Line Interference (PLI) noise from the ECG signal. The proposed adaptive filters are compared with various adaptive algorithms in terms of Signal-to-Noise Ratio (SNR), convergence speed, residual noise, steady-state Mean Square Error (MSE), and complexity. PubDate: 2023-10-28 Issue No:Vol. 69, No. 4 (2023)
Authors:Maksat Kalimoldayev, Waldemar Wójcik, Zhazira Shermantayeva Pages: 819 - 824 Abstract: Абстрактный:В данной статье разработана система мониторинга на основе IoT-технологий электрической системы подстанции в Республике Казахстан. На данный момент работа энергосистем крайне важна для поддержания частоты электрического тока с течением времени. Для приложений управления и мониторинга необходимо учитывать связь в допустимых пределах. Технологии IoT рассматриваются основными функциями в приложениях для мониторинга и управления энергосистемами в режиме реального времени, а также принятия эффективных решений как по техническим, так и по финансовым вопросам системы, для мониторинга основной формы регистрации данных на электрической подстанции в городе Шымкент Республики Казахстан, для последовательного эффективного принятия решений системными операторами. В данной работе была реализована и внедрена система мониторинга на базе интернета вещей для подстанции энергосистемы с использованием специализированного устройства, встроенного в ко... PubDate: 2023-10-28 Issue No:Vol. 69, No. 4 (2023)
Authors:Łukasz Popek, Rafał Perz, Grzegorz Galiński, Artur Abratański Pages: 825 - 831 Abstract: The article presents research on animal detection in thermal images using the YOLOv5 architecture. The goal of the study was to obtain a model with high performance in detecting animals in this type of images, and to see how changes in hyperparameters affect learning curves and final results. This manifested itself in testing different values of learning rate, momentum and optimizer types in relation to the model's learning performance. Two methods of tuning hyperparameters were used in the study: grid search and evolutionary algorithms. The model was trained and tested on an in-house dataset containing images with deer and wild boars. After the experiments, the trained architecture achieved the highest score for Mean Average Precision (mAP) of 83\%. These results are promising and indicate that the YOLO model can be used for automatic animal detection in various applications, such as wildlife monitoring, environmental protection or security systems. PubDate: 2023-10-28 Issue No:Vol. 69, No. 4 (2023)
Authors:Łukasz Krzak, Jan Macheta, Mateusz Kubaszek, Cezary Worek Pages: 833 - 842 Abstract: This article provides a comparison of various wireless data transmission protocols, such as Wireless M-Bus, LoRaWAN, Sigfox, NB-IoT and a newly developed proprietary protocol, studying their performance in the application of battery-powered residential water meters. Key aspects of the comparison include energy consumption, which is analyzed through comparing unitary amount of charge required to conduct a single, bi-directional data transaction between the meter and base station, and maximum coupling loss which effectively defines the range and coverage in the system. For completeness, the study includes also a brief cost analysis and ends with a conclusion, stating when each of the particular standards should be favored. PubDate: 2023-10-28 Issue No:Vol. 69, No. 4 (2023)
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