Authors:Betül HATİPOĞLU ŞAHİN; Ayşegül TERECİ Abstract: Mass housing played an important role in changing the face of the cities. The Municipality Law No.5393 which gave the right to municipalities to build mass housing were factors that have accelerated the mass housing production. The main goal of local administrations is to build houses in the most rapid and economic way for group of people with low income. However, such production has posed problems in terms of quantity and quality. This research has been conducted to measure the satisfaction levels of users from mass housing projects which are implemented under the leadership of the municipality in Konya. The existing residences in the area selected for the project were demolished swiftly and then mass housing was again built swiftly. Determining how the users in the region are affected by this change and their satisfaction with this matter is one of the main goals of this study. A scale was created by scanning the housing satisfaction parameters in the literature for the purpose of this study. In order to find out the satisfaction with the physical space, 5 mass housing areas, which share similarity in terms of settlement texture density and housing typology, were selected as sample study area from the 22 projects built by the district municipality. In the satisfaction and space analysis, user satisfaction in the mass housing projects produced by the municipality was examined together with the demographic findings. This research will serve as a baseline for future research since it will provide ready and comparable data. PubDate: Wed, 01 Sep 2021 00:00:00 +030
Authors:Özge DALMANOĞLU; Mediha ÖRKCÜ Abstract: In the present paper, our purpose is to generalize the Jakimovski-Leviatan-Păltănea operators in the sense of Chlodowsky. After introducing the new operators we first obtain the moments of these operators in order to establish the convergency properties with the help of Korovkin's theorem. After that, we give the local approximation result and the Voronovskaya type theorem. We also examine the convergence properties of the operators in the weighted space of functions. Lastly we determine the rate of convergence of the operators with the aid of the weighted modulus of continuity PubDate: Wed, 01 Sep 2021 00:00:00 +030
Authors:Dilara GÜR; Seden ACUN ÖZGÜNLER Abstract: This paper focuses on producing a natural hydraulic lime (NHL) mortar with metakaolin, expanded perlite and tuff additives for the purpose of repairing historic masonry. The experimental study was based on laboratory tests for determining the mechanical and physical properties of NHL mortars with mineral additives, under standard and water curing conditions at 7, 28 and 90-day testing periods. Following preliminary tests for selecting most favourable materials; flexural strength, compressive strength, adhesion strength, modulus of elasticity and ultrasound tests were conducted for obtaining mechanical performance. Adhesion strength of mortars were determined by applying each mortar to the most common historic masonry materials. Physical performance of the pozzolan added mortars were investigated through; apparent density, bulk density, water permeability, capillary absorption, water vaporpermeability, porosity tests. Regardless of mineral additive type; water cured mortars reached higher physico-mechanical properties in comparison with the ones cured in relative humidity. Overall, water cured natural hydraulic lime mortars with specific amounts of mineral addition are found promising for the repair of historic masonry. PubDate: Wed, 01 Sep 2021 00:00:00 +030
Authors:Serdar SOLAK; Umut ALTINIŞIK Abstract: Throughout the ages, safely preserving and transmitting data that have extraordinary importance for humanity has increased its importance with rapid advances in computer technology. Steganography stores hidden data within the files, which are unnoticed by third parties, so it provides secure transmission of data to the receiver. In this study, a steganography-based GUI design has been carried out, which ensures that the agricultural data is safely stored and communicated to the other party. We used LSB one-bit, two-bit, three-bit substitution and PVD algorithms with GUI for stages of agricultural data hiding and extracting at cover images. We also provided extra security using the embedded key and shifting operations on the hidden data before hiding data the cover image. In short, we confused the hidden data in the cover image so that malicious people can't understand. In experimental studies, performance analysis was evaluated by comparing various criteria as similarity ratio (Structural Similarity Index Measure, SSIM), stego image quality (Peak Signal-to-Noise Ratio, PSNR) and data hiding capacity (Payload). PubDate: Wed, 01 Sep 2021 00:00:00 +030
Authors:Mahmut KABAKULAK; Serdal ARSLAN Abstract: In this study, harvesters, sensors and data acquisition cards were designed and tested to obtain data from transmission lines. In this context; numerical analyses of harvesters with two different core geometries were performed with Ansys Maxwell software. Then the voltage and power harvested by the harvesters at different line currents were measured with pre-tests in the laboratory. Analyses’ results and pre-test’s results were examined and it was determined that the geometric structure (double C) model suitable for use in overhead transmission lines with high current could be used. The field test was carried out on a distribution transformer. In the field test, the harvester mounted on the transformer supply line has charged the battery supplying the sensor circuit with sufficient power to ensure normal operation of the system. A circuit is designed to measure air temperature, humidity, pressure, altitude, air quality and transformer temperature and to transmit them to the remote distance with RF transmitter. Data received on the data collection card can be recorded at certain periods and time-based graphs of the data can be obtained by a computer interface program. The energy of this circuit is to meet the energy harvested from the electromagnetic field. PubDate: Wed, 01 Sep 2021 00:00:00 +030
Authors:Emre ARTUN Abstract: Carbon footprint of a 10-year old university campus is estimated using IPCC Tier 1 Methodology. Key sources and sinks that cause carbon emissions were identified. Electricity, fuel, food and paper consumption were considered as the key items that would increase the emissions. Trees and recycling practices were considered as the key items that would reduce the emissions. Through communication with campus staff and data collection, annual consumption/production data were compiled in a spreadsheet application that uses these data to estimate the amount of carbon that is emitted per year. It was demonstrated that there has been a reduction in the carbon emissions between 2011 and 2017 due to the sustainability initiatives that were launched during that time in the campus. To analyze future years and address the uncertainty in the data, the spreadsheet allows to perform a probabilistic estimation through Monte Carlo simulation and analysis. PubDate: Wed, 01 Sep 2021 00:00:00 +030
Authors:Derya BAL ALTUNTAŞ; Sema ASLAN, Vagif NEVRUZOĞLU Abstract: Here, Turkish human hair fibers were used as a carbon source at the synthesis of human hair-sourced activated carbons (HHC). During the synthesis of HHCs sodium carbonate (Na2CO3) was added to the synthesis process for an elevated activation by calcination at different temperatures. Then obtained HHCs utilized for the modification of carbon paste electrode to evaluate the supercapacitance performance of this activated HHC. Electrochemical investigation of the HHC modified electrodes have been carried out by employing differential pulse voltammetry (DPV), cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) measurements. The pore and surface properties and chemical structure of the HHCs were investigated by scanning electron microscopy (SEM), Brunauer-Emmett and Teller (BET) analysis and Raman spectroscopy. HHCs displayed a Type-IV isotherm, which indicates the existence of micro-mesoporous structure on the surface. Carbonization of the waste hair was performed by calcination to improve the pore facilities at three different temperatures (200-250-300 °C). The sample was named HHC-250 (HHC calcinated at 250°C) exhibited the best charge storage capacity when used at the modification of carbon paste electrode, among other HHCs with a 26.88 F g−1 specific capacitance value (in 6 M KOH at a scan rate of 100 mV s−1). Also, a very attainable supercapacitance stability was achieved from HHC-250 modified electrode after 1000 cycles. The presented electrode system exhibited an energy density of 3.73W h kg−1. This work can serve as a guideline for optimizing the performance of hair like biomass-derived carbons by matching their pore properties and detailed electrochemical performance investigations. PubDate: Wed, 01 Sep 2021 00:00:00 +030
Authors:İlyas Cihan AKSOY; Mehmet Metin MUTLU, Yalçın ALVER Abstract: In this study, an optimization model for road maintenance scheduling is proposed. The proposed model determines a maintenance schedule for a given set of links in an urban road network, that minimizes the total travel time during the maintenance period under a set of assumptions and a particular crew number constraint. It is assumed that all lanes of a road to be repaired are closed to traffic during the maintenance. Ant Colony Optimization (ACO), a suitable algorithm for discrete transportation problems, is employed in the proposed model. The model generates a set of roads to be closed for each maintenance day. The total travel time during the whole maintenance period is calculated using the deterministic user equilibrium assignment model. The proposed model is applied to a test network, and more efficient schedules in terms of total travel time are obtained compared to randomly generated schedules. PubDate: Wed, 01 Sep 2021 00:00:00 +030
Authors:Özge TEZEL; Buğra Kaan TİRYAKİ, Eda ÖZKUL, Orhan KESEMEN Abstract: This paper presents a new goodness-of-fit technique for testing the assumption of univariate distributions which is based on the theoretical distribution function of the hypothesized distribution. The existing methods are examined in two different categories: binning and binning-free. The most widely known binning test is the Chi-square test. The Kolmogorov-Smirnov, the Cramer-von Mises and the Anderson-Darling goodness-of-fit tests come to the forefront as the binning-free tests. When tests are evaluated in terms of distributions, it is examined in two different classes: the not distribution-free tests and the distribution-free tests. The desired goodness-of-fit test method for a researcher should be binning-free, distribution-free, more sensitivity, easy to use and fast. In this study, a test method is proposed which provides almost all the options that a researcher would want. The Monte-Carlo simulation methods are used to demonstrate the success of the proposed method. In these simulations, the normality test was applied for symmetric distributions whereas the lognormality test was applied for non-symmetric distributions. The proposed test method has demonstrated superiority in many aspects compared to other selected test methods on both simulations and three different real-life datasets. PubDate: Wed, 01 Sep 2021 00:00:00 +030
Authors:Oluwaseun MARTİNS; Adefemi Adeyemi ADEKUNLE, Samuel Babatope ADEJUYIGBE, Hezekiah Oluwole ADEYEMİ Abstract: Path planning evaluates and identifies an obstacle free path for a wheeled mobile robot (WMR) to traverse within its workspace. It emphasizes metric like, start and goal coordinate, static or dynamic workspace, static or dynamic obstacles, computational time and local minimum problem. Path planning play a significant role toward WMR effective traverse within it workspace like industrial, military, hospital, school and office. In this workspace, path planning is an optimal method to increase the productivity of WMR to achieve it specific task. Hence, in this paper, we present a review of path planning algorithms (classical algorithms, heuristics and intelligent algorithms, and machine learning algorithm) for mobile robot using statistical method. Regarding our objective, we use this statistical method to evaluate the success of these algorithms base on the following metrics: architecture (hybrid or standalone), algorithm sub-category (global or local or combine), workspace (static or dynamic), obstacle type (static or dynamic), number of obstacle (≤ 2, ≤ 5, > 5) and test workspace (virtual or real-world). Research materials are sourced from recognized databases where relevant research articles are obtained and analyzed. Result shows hybrid of machine learning approach with heuristic and intelligent algorithm has superior performance where they are applied compare to other hybrid. Also, in complex workspace Q-learning algorithm outperforms other algorithms. To conclude future research is discussed to provide reference for hybrid of Q-learning algorithm with Cuckoo Search, Shuffled Frog Leaping and Artificial Bee Colony algorithm to improve its performance in complex workspace. PubDate: Wed, 01 Sep 2021 00:00:00 +030
Authors:Erhan KARAKOÇ; Gülen ÇAĞDAŞ Abstract: Adaptive façades can enhance energy efficiency in buildings while also sustaining user comfort by using performance-driven decision-making strategies. As a sub-category of adaptive façades, advanced and intelligent façades are executed efficiently by means of mechanisms consisting of sensors, processors and actuators that systematically participate in decision-making processes via control systems. However, the conflicts occur in decision-making processes regarding the compensation between energy conservation and user demands, and material fatigue caused by the extensive movement of kinetic façade components. In this article, it is aimed to develop a novel decision-making approach embedded in a prototype named Advanced Intelligent Façade (AIF) module based on statistical data by proposing critical decision and priority algorithm, which is lacking in the case studies of intelligent façades to solve conflicts in boundary conditions. The methodology of the paper is to verify the proposed system consisting of electromechanical module and decision-making algorithms via simulation according to four scenarios that is implemented of the weather data of equinox dates in Mediterranean climate. The proposed system is simulated in the digital medium by comparing the outcomes with the static façade in terms of indoor temperature. According to the simulation, the proposed strategy is determined as an efficient and performative alternative by optimizing the environmental parameters such as heat, light and humidity levels with the user demand for the specific temperature ranges. Thus, the AIF module can be employed in the buildings as a sustainable façade system. PubDate: Wed, 01 Sep 2021 00:00:00 +030
Authors:Gürkan İRSEL Abstract: The purpose of this research is to present the designs required and methodology of prototype production to control electronically a mechanical-controllable system on a case study. The system under consideration is a field crop sprayer. The reason for the investigation of this system is operator exposure to the harmful chemical and inefficiency of flow control. It is necessary to precisely start and end the chemical flow at the requested location, to close a certain part of the spraying line, and to prevent overdosing during the pulverization. An Arduino system was designed to control a precise electronic flow system. In this regard, Mechanical flow-control valves are equipped with 16 bar pressure-resistant and chemical resistant solenoid valves. Designs were produced and prototypes were presented. Low-cost sprayer control systems (SCS) chemical losses were reduced by 6% to 20%. The ergonomic design increased the productivity of the operator. Moreover, this system reduced fuel consumption by 2% to 6%. It is 40% more economical than existing systems. As a result, productive electronic control was achieved in the field crop sprayer. PubDate: Wed, 01 Sep 2021 00:00:00 +030
Authors:Ömür Kaya KALKAN; Tolga COŞGUNER Abstract: This study aimed to determine the importance levels of mathematics lecture achievement, Turkish lecture achievement, Higher Education Admission Exam score, academic self-efficacy, attitude towards vocational education, academic motivation and mother and father education on the academic achievement of vocational schools of higher education students using the artificial neural network method. The data was obtained through 468 students from vocational schools of higher education at two different universities in Turkey. According to the quantitative research methodology, the correlational research design was used. The artificial neural network analysis results revealed that mathematics lecture achievement, Turkish lecture achievement and academic self-efficacy were the most critical variables that predicted the academic achievement of vocational schools of higher education students. These variables were followed by mother education level, father education level, attitude towards vocational education, Higher Education Admission Exam score and academic motivation. The results suggest that the effectiveness of the Higher Education Admission Exam score, which contributes very little to predict the academic achievement of vocational education students, need to be more questioned. PubDate: Wed, 01 Sep 2021 00:00:00 +030
Authors:Merve APSAK; Ahmet AKDEMİR, Fazliye KARABÖRK, Şakir YAZMAN Abstract: In this study, effects of zinc nanoparticles (ZNPs) on the mechanical properties of epoxy coatings and anticorrosion behavior on the stainless steel were investigated. The nanocomposites (NCs) were obtained by adding ZNPs (0.5, 1.0, 1.5 wt%) to epoxy resin. The first stage in this study, bulk samples were prepared for tensile test and DSC, TGA, FTIR, SEM analysis. The test and analysis were performed separately for samples cured at room temperature for 24 h and postcured at 80 °C for 15 h in the oven. The results indicated that both postcuring and adding ZNPs caused an increase in the mechanical properties of the epoxy matrix. Tensile strength increased by 13.2% and 90.2% in the postcured NC (1.0% Zn) and untreated NC (0.5% Zn) respectively. The NCs prepared with the same parameters for the second stage were coated on AISI 304 test panels and the panels were postcured in the oven. The anticorrosive performance of the coatings was studied by an immersion test. According to the corrosion test results, it was observed that the coated steel surface preserves the best rate of 1.0% ZNPs containing epoxy composite. In addition, impact resistance, flexibilities and adhesion properties of the coating were analyzed. PubDate: Wed, 01 Sep 2021 00:00:00 +030
Authors:Sumaiya Tasneem Z; Kalpana G, Thabet ABDELJAWAD Abstract: Through this work, we analyze the structure of extended Gb-metric spaces and show a fundamental lemma for sequence convergence within the same metric. We also propose the new notion of generalized geraghty type Θ-berinde contraction mappings and demonstrate several fixed point theorems for these mappingsin the sense of extended Gb-metric spaces. Eventually, the existence result for solutions of a Fredholm integral equation is furnished to show the efficacy of the technique developed. PubDate: Wed, 01 Sep 2021 00:00:00 +030
Authors:Şaban ÖZTÜRK Abstract: It is very pleasing for human health that medical knowledge has increased and the technological infrastructure improves medical systems. The widespread use of medical imaging devices has been instrumental in saving lives by allowing early diagnosis of many diseases. These medical images are stored in large databases for many purposes. These datasets are used when a suspicious diagnostic case is encountered or to gain experience for inexperienced radiologists. To fulfill these tasks, images similar to one query image are searched from within the large dataset. Accuracy and speed are vital for this process, which is called content-based image retrieval (CBIR). In the literature, the best way to perform a CBIR system is by using hash codes. This study provides an effective hash code generation method based on feature selection-based downsampling of deep features extracted from medical images. Firstly, pre-hash codes of 256-bit length for each image are generated using a pairwise siamese network architecture that works based on the similarity of two images. Having a pre-hash code between -1 and 1 makes it very easy to generate hash code in hashing algorithms. For this reason, all activation functions of the proposed convolutional neural network (CNN) architecture are selected as hyperbolic tanh. Finally, neighborhood component analysis (NCA) feature selection methods are used to convert pre-hash code to binary hash code. This also downsamples the hash code length to 32-bit, 64-bit, or 96-bit levels. The performance of the proposed method is evaluated using NEMA MRI and NEMA CT datasets. PubDate: Wed, 01 Sep 2021 00:00:00 +030
Authors:Yusuf YILDIZ; Merve KOÇYİĞİT Abstract: Today, increasing energy costs and environmental problems make it mandatory to use energy efficiently in buildings. Universities with high energy consumption have become the focus to save energy in the building sector. At the same time, universities with many buildings and infrastructures are like small settlements. Major objective of this study is to compare historical energy consumption of different types of buildings over a ten-year period. Thus, it shows an overall picture of energy consumption in Çağış Campus of Balikesir University. It has been observed that the university hospital is a very large energy consumer compared to other buildings. In addition to this building, the energy consumed in four buildings such as Faculty of Engineering and Architecture, Rectorate, Medico Social Building and Faculty of Science and Letters corresponds to 70% of the total energy used in Çağış Campus between 2008-2019. The results obtained from the study will be beneficial for universities' related staff to manage energy use and to determine the priorities for retrofitting. PubDate: Wed, 01 Sep 2021 00:00:00 +030
Authors:Sandra Lorena GARCÍA BUSTOS; Steven NAVARRETE, Angel CHANCAY, Marcos MENDOZA, Marcela PİNCAY, Miguel TERAN Abstract: This work applied the extreme value theory and Poisson regression considering maximum likelihood estimates to characterize the 5 seismicity zones of Ecuador obtained through cluster analysis. The Gumbel model was optimal in describing maximum magnitudes in these areas. The Poisson regression model was used to estimate the frequency of earthquakes as a function of magnitude (MW) for each zone. Zones 1 (portions of Esmeraldas and Manabí and their respective maritime zones) and 5 (north central of Ecuador) were the most representative in terms of recurrence and seismic magnitudes. PubDate: Wed, 01 Sep 2021 00:00:00 +030
Authors:Saed ALQARALEH Abstract: In this paper, an effective tweet classification system that fully supports the Turkish language has been developed. The proposed system can be used for mining (classifying) the recently published and publicly available tweets to find the crisis’s most related and useful tweets to gain situational awareness, which can help in taking the correct responses in order to prevent or at least decrease the effect of such situations. A deep study was carried out to improve and optimize the proposed system. In more detail, some intensive experiments were performed to investigate the performance of some well-known machine learning algorithms, i.e., K-Nearest Neighbor (KNN), Support Vector Machine (SVM), and Naive Bayes (NB) when used for text (tweets) classification. Then, the performances of the ensemble systems of the studied algorithms and the Random Forest (RF), AdaBoost Classifier (AdaBoost), GradientBoosting Classifier (GBC) ensemble systems have also been observed. As shown in the experimental evaluation and analysis, the proposed approach has stability, robustness, and can achieve quite good performance when processing the Turkish language. The performance of the proposed classifier was also compared with two state-of-the-art text classification approaches, i.e., "Empirical" and “Turkish Deep ". PubDate: Wed, 01 Sep 2021 00:00:00 +030
Authors:Festus OPONE; Blessing IWERUMOR Abstract: This paper presents a new Marshall-Olkin extended family of distributions with bounded support. Some of the Mathematical properties of the proposed distribution were studied and the method of maximum likelihood estimation was employed to estimate the unknown parameters of the proposed distribution. A Monte Carlo simulation study was carried out to examine the asymptotic behaviour of the parameter estimates of the distribution.” Finally, two real data sets defined on a unit interval were used to show the applicability of the proposed distribution in analyzing real data sets. PubDate: Wed, 01 Sep 2021 00:00:00 +030
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