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SRMs have high torque ripples. Modifying the stator and rotor shape of SRMs is one of their methods to remove torque ripples. In this study, new rotor and stator geometries have been proposed for SRM. Performance characteristics are obtained and dynamic analyses are carried out for both novel and classical 6/4 SRMs. FFT analyses of the torque characteristics are also performed for the both SRMs. The changes in performance and the FFT results of torque characteristics are determined for both the current-controlled and uncontrolled operations in both SRMs. 23.60% and 15.20% improvements in torque ripples are achieved for the uncontrolled and current-controlled operations in SRMs respectively. When the FFT analyses are applied to the torque characteristics, the THD values are obtained as 21.19% and 8.31% in the uncontrolled and controlled motor current operations respectively. A 122 W three-phase 6/4 SRM simulation based on the MATLAB–SIMULINK environment is performed to validate the improvement of the torque ripple of the proposed model.

Poly(ethylene oxide) (PEO)-based polymer electrolytes are a promising class of materials for use in lithium-ion batteries due to their high ionic conductivity and flexibility. In this study, the effects of polymer architecture including linear, star, and hyperbranched and salt (lithiumbis(trifluoromethanesulfonyl)imide (LiTFSI)) concentration on the glass transition (Tg), microstructure, phase diagram, free volume, and bulk viscosity, all of which play a significant role in determining the ionic conductivity of the electrolyte, have been systematically studied for PEO-based polymer electrolytes. The branching of PEO widens the liquid phase toward lower salt concentrations, suggesting decreased crystallization and improved ion coordination. At high salt loadings, ion clustering is common for all electrolytes, yet the cluster size and distribution appear to be strongly architecture-dependent. Also, the ionic conductivity is maximized at a salt concentration of [Li/EO ≈ 0.085] for all architectures, and the highly branched polymers displayed as much as three times higher ionic conductivity (with respect to the linear analogue) for the same total molar mass. The architecture-dependent ionic conductivity is attributed to the enhanced free volume measured by positron annihilation lifetime spectroscopy. Interestingly, despite the strong architecture dependence of ionic conductivity, the salt addition in the highly branched architectures results in accelerated yet similar monomeric friction coefficients for these polymers, offering significant potential toward decoupling of conductivity from segmental dynamics of polymer electrolytes, leading to outstanding battery performance.

© 2023 Informa UK Limited, trading as Taylor & Francis Group.Deep learning methods have been successfully applied to remote-sensing problems for several years. Among these methods, CNN-based models have high accuracy in solving the land classification problem using satellite or aerial images. Although these models have high accuracy, this generally comes with large memory size requirements. However, it is desirable to have small-sized models for applications, such as the ones implemented on unmanned aerial vehicles, with low memory space. Unfortunately, small-sized CNN models do not provide as high accuracy as with their large-sized versions. In this study, we propose a novel method to improve the accuracy of CNN models, especially the ones with small size, by injecting traditional features into them. To test the effectiveness of the proposed method, we applied it to the CNN models SqueezeNet, MobileNetV2, ShuffleNetV2, VGG16 and ResNet50V2 having size 0.5 MB to 528 MB. We used the sample mean, grey-level co-occurrence matrix features, Hu moments, local binary patterns, histogram of oriented gradients and colour invariants as traditional features for injection. We tested the proposed method on the EuroSAT dataset to perform land classification. Our experimental results show that the proposed method significantly improves the land classification accuracy especially when applied to small-sized CNN models.

© 2023, The Minerals, Metals & Materials Society.It is becoming crucial to design/fabricate eco-friendly, sustainable electronic and photonic devices to minimize the carbon footprint for future systems. In this study, we have demonstrated a steady photoresponse enhancement of the self-powered GaN ultraviolet photodetector (GaN-UVPD) via sequentially deposited gold nanoparticles (Au NPs) under 254, 302, and 365 nm UV light exposure. The AuNP-deposited GaN-UVPD exhibited excellent responsivity of 0.65 A/W and detectivity of 6.51 × 1012 cm.Hz1/2 W−1 under 302 nm UV light without any external power. Moreover, the sensitivity of the device increased from 1.98 × 106% to 3.32 × 106% following Au nanoparticle deposition. Additionally, the plausible mechanisms for the self-powered and Au nanoparticle-induced photoresponse enhancement have been discussed. In brief, the high-performance photoresponsivity of our self-powered GaN-UVPD could find many useful applications in sustainable energy and eco-friendly optoelectronic devices.

In this study, the average power consumption of an electrode welding machine during the welding process was estimated using the features of the sound emitted during welding. First, the instantaneous values of electrode current and voltage and the sound emitted during the welding process were recorded simultaneously. The minimum, maximum, average, root mean square (RMS), and energy values of the sound data were found and feature extraction was performed, and the instantaneous power and average power values were calculated using the instantaneous current and voltage values. Three Adaptive Neuro-Fuzzy Inference Systems (ANFIS) using the sound features as inputs and average power values as outputs were created, and their results were compared. The average power values consumed during the welding process have been successfully estimated at a rate of 87-95%.

Considering the increasing demand for cloud computing, and the financial and environmental impact of the increasing energy consumption trend of data centers, improving energy efficiency is vital for cloud service providers. In this study, an energy-aware virtual machine scheduling model is proposed which is based on the multi-unit nondiscriminatory combinatorial auction. The model includes a powerful bidding language that allows users to declare their complicated virtual machine requests using logical AND and OR relations along with the time constraints. The study also presents the formal definition of the model and the associated optimization problem for determining the optimum schedule and energy-efficient placement of VMs on physical servers. The optimization problem is formulated using integer linear programming and several heuristic solution methods including the Genetic Algorithm are proposed for this problem. The performances of the model and the proposed heuristics are assessed on a comprehensive test suite. The proposed model is estimated to provide approximately a 37% improvement in revenues, and the solution methods are estimated to provide high-quality solutions within only 5% of the optimum which enable the model to be deployed in large-scale clouds.

Adrenal lesions are usually discovered incidentally during other health screenings and are usually benign. However, it is vital to take precautions when a malignant adrenal lesion is detected. Especially deep learning models developed in the last ten years give successful results on medical images. In this paper, adrenal lesion characterization on T1-weighted magnetic resonance abdomen images was aimed using convolutional neural network (CNN) which is one of the deep learning methods. Firstly, effects of important model parameters are assessed on performance of CNN, so optimum CNN model is obtained for classification of adrenal lesions. For a fixed number of convolution filters determined in the first stage of the study, CNN model implemented by different kernel sizes were trained. According to the best result obtained, this time the kernel size was kept constant, and experiments were made for different filter numbers. Finally, studies were carried out with CNN structures of different depths and the results were compared. As a result of the studies, when filter is selected as [5 20], the best results in the trainings conducted with a single-block CNN structure are obtained 0.97, 0.90, 0.98, 0.90, 0.90, and 0.94, for accuracy, sensitivity, specificity, precision, F1-score, and AUC score, respectively. The study was compared with the studies in the literature, and it was seen that it was superior to them.

Globally, with the rapid growth of the population, the use of cars is also increasing. Although there is an increase in the use of electric vehicles, the vast majority of the vehicles used are internal combustion engine vehicles. Fossil fuel vehicles have disadvantages such as damaging the environment due to their high emission values, using non-renewable energy sources as fuel, high maintenance costs, and complex vehicle structures. Electric vehicles have many advantages such as being sensitive to the environment with a near-zero emission value, simple structures, low maintenance costs, and the use of renewable energy sources as fuel. Today, the reserve ratios of fossil fuels are rapidly depleting. Consumers tend to buy electric vehicles because of the environmental damage caused by fossil fuel vehicles due to the high emissions they emit, and because of the danger of depletion of non-renewable energy sources. The purchase of electric vehicles from the factory is difficult due to the few product varieties and the high prices in the market. It is possible for consumers to have electric vehicles with the features, colors, and models they want at much more affordable prices, by converting internal combustion engine vehicles to electric vehicles. Each country has its own regulations for the conversion process. Transformation operations in our country are carried out in accordance with the Regulations of the Ministry of Science, Industry, and Technology. There are ready-made conversion kits of different brands on the market that contain the components necessary for the conversion of internal combustion engine vehicles to electric vehicles. In this study, the advantages and disadvantages of internal combustion engine vehicles and electric vehicles, why conversion is necessary, and how conversion should be carried out will be discussed. Thanks to the conversion to an internal combustion engine, there will be a decrease in the emission of harmful gases to the environment, an economic contribution will be made to the country, and consumers will be able to have the vehicle they want at affordable prices.

The usage of the cameras in facilities in the energy sector is becoming more and more common. In addition, with the widespread use of SCADA and the increase in automation of camera-based applications, ensuring security in video data communication has become more and more important. In this study, methods that have been successful in providing image security in previous studies in Ref.[1] have been improved to ensure the security of video data communication. These methods use Kurt-Modified Chua’s Circuit (KMCC) as random number generator. Proposed algorithms are efficient for energy sector secure video communication because of using hyperchaotic random number generator and also bit level scrambling, diffusion encryption to each frame of video.

Elektrik güç sistemlerinin en önemli parametrelerinden biri olan gerilim değerinin korunması modern güç sistemleri için hayati önem taşımaktadır. Otomatik gerilim regülatörleri güç sistemlerinde gerilim değerinin istenilen değerde korunmasını sağlarlar. Bu çalışmada otomatik gerilim regülatör sisteminde kontrolör yapısı olarak literatürde en yaygın kullanılan PID kontrolör yapısı kullanılmıştır. Bu çalışmada kontrolör parametre değerlerini ayarlamak için Genetik algoritma tekniği kullanılmıştır. Kullanılan tekniğin başarısı literatürde PID kontrolör kazanç değerlerini ayarlamada en yaygın kullanılan tekniklerden biri olan Ziegler-Nichols yöntemi ile karşılaştırılmıştır. Sunulan tekniğin başarısını göstermek için hem zaman domeni analiz yöntemleri hem de frekans domeni analiz yöntemleri bu çalışmada kullanılmıştır., Voltage level protection, which is one of the most important parameters of electrical power systems, is critical for modern power systems. Automatic voltage regulators make ensure that power systems' desired voltage level is maintained. The automatic voltage regulator system's controller structure in this study is based on the PID controller structure that has been utilized the most extensively in the literature. In this research, the controller parameter values are modified using a genetic algorithm technique. The Ziegler-Nichols approach, one of the most popular methods in the literature for modifying PID controller gain levels, is utilized to compare the effectiveness of the strategy used. Both time domain analysis methods and frequency domain analysis methods are employed in this study to show the effectiveness of the proposed strategy.

This paper presents a novel systemic algorithm based on conservative power pinch analysis principles using a computationally efficient insight-based binary linear programming optimization technique in a model predictive framework for integrated load shifting and shedding in an isolated hybrid energy storage system. In a receding 24-hour predictive horizon, the energy demand and supply are integrated via an adaptive power grand composite curve tool to form a diagonal matrix of predicted hourly minimum and maximum energy constraints. The intgrated energy constraints must be satisfied recursively by the binary optimisation to ensure the energy storage’s state of charge only operates within 30% and 90%. Hence, the control command to shift or shed load is contingent on the energy storage state of the charge violating the operating constraints. The controllable load demand is shifted and/or shed to prevent any violations while ensuring energy supply to the most critical load without sacrificing the consumers' comfort. The proposed approach enhances efficient energy use from renewable energy supply as well as limits the use of the Hydrogen resources by a fuel cell to satisfy controllable load demands which can be shifted to periods in the day with excess renewable energy supply.

Değişken hızlı rüzgar türbini jeneratörleri, sabit hızlı rüzgar türbinlerine göre daha güçlüdür. Ancak kararsız rüzgar hızı, değişken hızlı makinenin gerilim ve frekansında değişmlere neden olmaktadır. Uygun bir kontrol tekniği ile gücün kalitesi iyileştirilir.Sistemde kullanıldığında, dalgalanan rüzgar jeneratörü çıkışının kontrol edilmesi gerekir, bu nedenle kombine rüzgar jeneratörü sisteminin dinamik özelliklerinin incelenmesi gerekir. Daha dinamik performans için daha iyi denetleyici tasarlanabilir. Bu çalışmada, MATLAB/Simulink ortamında rüzgar türbini tasarlanmış ve hatve açısı denetim işlemi gerçekleştirilmiştir. Hatve açısı denetimi için PID ve Bulanık Mantık Denetleyici (BMD) kullanılmıştır. Bu denetim algoritmaları referans güç değerinde salınım miktarı, referans değere ulaşım süreleri ve kanat hatve açısındaki değişimler benzetim çalışmasında incelenmiştir., Generators for wind turbines with variable speeds are more potent than those with set speeds. However, the variable speed machine's voltage and frequency shift as a result of erratic wind speed. A proper control method raises the power's quality. The dynamic properties of the combined wind generator system must be researched in order to regulate the fluctuating wind generator output when it is employed in the system. More dynamic performance can be achieved by designing better controllers. Pitch angle control was carried out in this study's wind turbine design using the MATLAB/Simulink environment Pitch angle control is accomplished using PID and a fuzzy logic controller (FLC). The simulation research looked at these control techniques, the amount of oscillation in the reference power value, the duration to achieve the reference value, and the variations in blade pitch angle.

Today, electrical energy is used extensively worldwide, increasing importance in almost all business sectors. For this reason, how to produce electrical power from earth sources is so important. Renewable energy sources that do not damage the environment and do not cause greenhouse gas emissions are increasingly used in electrical energy production. Solar energy, also renewable energy, is an excellent choice for the world's future because it is durable, abundant, low cost, recycling, and clean. Efficiency in solar energy is essential in terms of reducing resource use. The efficiency of solar PV modules depends on their structure, irradiance, and temperature. The albedo effects are significant in the bifacial modules because of the reflection of direct and diffuse irradiances. In this paper, the Albedo effect, and the surface's reflective power, are analyzed in a 30-kW bifacial PV system making simulations with PVsyst software. With different ground models and albedos, the PV system is simulated under given conditions using the PVsyst software. After results are compared, it is understood that the albedo effect brings about a severe power increase in bifacial PV systems compared to mono facial PV systems.

miRNAs, a subclass of non-coding small RNAs, are about 18-22 nucleotides long. It has been revealed that miRNAs are responsible many diseases such as cancer. Therefore, great efforts have been made recently by researchers to explore possible relationships between miRNAs and diseases. Experimental studies to identify new disease-associated miRNAs are very expensive and at the same time a long process. Therefore, to determine the relationships between miRNA and disease many computational methods have been developed. In this paper, a new method for the identification of miRNA-disease associations based on space projection and label propagation (SPLPMDA) is proposed. The forecast the precision of SPLPMDA was demonstrated using 5-fold cross-validation and LOOCV techniques. Values of 0.9333 in 5-fold cross validation and 0.9441 in LOOCV were obtained. Moreover, case studies on breast neoplasms and lymphoma were performed to further confirm the predictive reliability of SPLPMDA.

Günümüzde hızla artan nüfusun paralelinde yaşamsal ihtiyaçlara bağlı tüketimler için ortaya çıkan teknolojik gelişmeler ve sanayileşme ile enerji ihtiyacı her geçen gün artmaktadır. İlgili enerji ihtiyacı daha çok konvansiyonel kaynaklardan karşılanmakta ancak bu durum çevre kirliliğine sebebiyet vermektedir. Fosil yakıtların en çok tüketildiği ve doğal olarak karbon emisyonuna neden olan alanlardan biri olan ulaşım sektöründe ise ciddi değişimler meydana gelmektedir. Özellikle fosil kaynaklı araçlar yerini Elektrikli Araçlara (EA) bırakmakta ve birçok marka EA modelleri geliştirmeye yönelik önemli adımlar atmaktadır. Ancak EA’ların üretim ve kullanımının artması enerjiye olan ihtiyacı da katlamaktadır. Aynı zamanda bu araçların şarj ihtiyaçları için kurulması gereken şarj istasyonu sayısı ve yatırım gerektiren altyapı hizmetlerinin planlanmasını zorunlu kılmaktadır. Bu çalışmada, Türkiye’de hizmet veren bir dağıtım sistemi operatörlüğünde işletilen ve EA şarj istasyonu kurulması planlanan otopark alanları için DIgSILENT PowerFactory V15.1 programında detaylı analizler gerçekleştirilmiştir. Türkiye’de hizmet veren bir otopark işletmecisi ile ortak çalışılacak alanlarda altyapı hizmetlerinin aksamaması ve olası güç sistemi arızalarının önüne geçebilmek amacıyla güç akışı analiz sonuçları paylaşılmıştır. Hatlardan akan aktif, reaktif güçler ve transformatör yüklenmelerine göre öneriler sunulmuştur., Today, the need for energy is increasing day by day with the technological developments and industrialization that have emerged in order to keep up with the consumption related to the vital needs that increase in parallel with the rapidly increasing population. This emerging energy need is mostly provided by non-renewable resources and also causes environmental pollution. Serious changes are occurring in the transportation sector, which is one of the areas where fossil fuels are consumed the most and naturally causes carbon emissions. In particular, fossil-based vehicles are replaced by Electric Vehicles (EVs), and many brands are taking important steps to develop EV models. However, the increase in the production and use of EVs also increases the need for energy. At the same time, it makes it necessary to plan the number of charging stations and infrastructure services that require investment for the charging needs of these vehicles. In this study, detailed analyzes were carried out in the DIgSILENT PowerFactory V15.1 program for the parking areas operated by a distribution system operator in Turkey and where an EV charging station is planned to be installed. Power flow analysis results were shared in order to prevent disruption of infrastructure services and possible power system failures in areas to be worked in partnership with a parking lot operator serving in Turkey. Suggestions are presented according to the active and reactive powers flowing from the lines and transformer loads.

The assembly line balancing problem is an important issue for every manufacturing company. A balanced assembly line ensures that a product is produced in the optimum time, and as a result of this effect, less machinery, materials and labour are used during this production. In this article, theoretical information about assembly line balancing has been given, and then the data needed for assembly line balancing has been obtained by making a time study of the production of Downlight Luminaire. With these data obtained, assembly line balancing was done and compared by using Hoffman and Comsoal methods. The aim of this study is to investigate the applicability of Hoffman and Comsoal methods, which are one of the heuristic assembly line balancing methods, in the assembly lines of the companies producing in the lighting sector.

Converter systems are applied to manage active/reactive power control of photovoltaic (PV) source during integration with the electric grid system. The control algorithm of the conventional converter system consists of a reference generation unit, a dc-link voltage control loop, two power control loops and a phase lock loop (PLL) system. PLL unit is used to lock in phase angle of the electric grid, and to perform the coordinate transformation for calculations of the active/reactive powers. However, the control algorithm has a slow dynamic response because of utilisation of a PLL structure. In addition, additional complex mathematical computations are required with the use of a PLL algorithm. Furthermore, the interaction of the PLL and the power control loops may lead power oscillation problems under weak grid, and also result in instability of the PV system. In this study, to avoid the aforementioned issues and to enhance the power flow capability of the grid-connected PV panels, a PLL-less control algorithm in pq-theory is studied for the active/reactive power management and the grid synchronization. In addition, the mathematical formulations of the current control algorithm are presented in detail. To show the effectiveness of the PLL-less controller, a PV system model with using real PV panel groups is designed and constructed in a simulation environment. The proposed control method is tested under various operation cases such as dynamic environmental conditions, reactive power support and voltage variations. The proposed method shows efficient performance under applications of the different operation situations.

Enerji sektöründe meydana gelen teknolojik gelişmeler, dünyanın içinde bulunduğu iklim değişikliği sorunu ve enerji maliyetlerinin hızlı bir şekilde artması insanları daha ucuz ve temiz alternatif enerji kaynakları arayışına yönlendirmiştir. Rüzgâr enerjisi, güneş enerjisi, biyokütle enerjisi, biyogaz, jeotermal enerji, dalga enerjisi gibi yenilenebilir enerji kaynakları günümüzde daha fazla tercih edilir olmuştur. Bununla birlikte yenilenebilir enerji kaynaklarından biri olan güneş enerjisi ile fotovoltaik santraller gerek yenilenebilir olması gerek ülkemizdeki yüksek güneş enerji potansiyeli sayesinde giderek yaygınlaşmıştır. Bu çalışma Kahramanmaraş ili Göksun ilçesinde ikamet eden dört kişiden oluşan bir ailenin evde tüketeceği günlük elektrik enerjisi ihtiyacını, ev çatısına kurulumu gerçekleştirilen şebeke bağlantılı fotovoltaik sistem tarafından karşılamayı amaçlamaktadır. Normal şartlar altında dört kişinin kullanacağı yıllık elektrik enerjisi tüketim miktarı hesaplanmış, bu veriye dayanılarak bu ailenin evinde kullandığı ev gereçlerinin tüketeceği elektrik enerjisinin ortalaması belirlenmiş ve evin ihtiyacı olan günlük elektrik enerjisi miktarı belirlenmiştir. Hesaplamalara göre evin elektrik enerjisi gereksinimini karşılayacak Kahramanmaraş ilinin yıllık ortalama güneşlenme süresi ve ışınım değerleri temel alınarak şebeke bağlantılı fotovoltaik santral tasarlanmış ve bu tasarımın PVsyst demo yazılım programıyla simülasyonu gerçekleştirilmiştir. Simülasyon sonucunda elde edilen nümerik sonuçlar detaylı olarak analiz edilmiştir.

Gerilim kaynaklı dönüştürücülere (VSC) dayalı yüksek gerilim-doğru akım (HVDC) güç sistemleri son yıllarda popüler bir konu haline gelmiştir. Bu makale, zayıf bir AC sistemi için çeşitli sistem hataları ve aşırı yükleme koşulları altında vektör kontrol tekniği ile VSC tabanlı bir VSC-HVDC sisteminin bir modelini ve kontrol performansını incelemektedir. VSC-HVDC sisteminin matematiksel modeli, sistem parametrelerini en uygun şekilde ayarlamak için kontrol edilen ve kontrol edilen değişkenlerin bir simülasyon modelini ilişkilendirmemize izin verir. Bu nedenle, DC bara gerilimini korumak amacıyla aktif ve reaktif gücü ayarlamak için uygun bir vektör kontrol tekniği kullanılır. Bu makalede sunulan kontrol sistemi, sistem salınımını verimli bir şekilde söndürebilen ve sistem geçici ve kararlı durum kararlılığını sürdürebilen dış kontrol döngüsü ve iç kontrol döngüsünü içerir. Vektör kontrol yaklaşımı, zayıf bir 6 baralı AC iletim sisteminde test edilmiştir. Modelin verimliliğini ve kontrol yönteminin güç aktarım limitinin iyileştirilmesine uygulanabilirliğini göstermek ve doğrulamak için DIgSILENT PowerFactory 15.0 yazılımında dinamik simülasyonları yapılmıştır.

Şizofreninin (SZ) erken tanısı hastaların daha etkili tedavi görmelerine olanak sağlayarak, yaşam kalitelerini artırır. Ancak, hastalığın karmaşık ve heterojen bulguları erken klinik tanıları sekteye uğratmaktadır. Bu bağlamda elektroansefalogram (EEG), olası SZ için alternatif bir tanı aracı olarak kullanılmaktadır. EEG tekniğinin yüksek temporal çözünürlük sunmasından dolayı, bilişsel ve davranışsal süreçlerin kortikal aktivitelere yansımaları başarılı bir şekilde irdelenebilir. Bu çalışmada, EEG işaretlerinin permütasyon entropi (PE) tabanlı karmaşıklık analizi ile SZ anomalilerin sınıflandırılması ve değerlendirilmesi amaçlanmıştır. PE analizleri, SZ semptomları sergileyen 45 adölesan birey ile 39 sağlıklı katılımcıdan alınan EEG kayıtları üzerinde uygulanmıştır. Özellik çıkarımı için delta, teta, alfa, beta ve gama dalgaları olmak üzere tüm alt bantların PE değerleri hesaplanmıştır. Sınıflandırıcı model olarak ise çok katmanlı perseptron sinir ağları (MLPNN) kullanılmıştır. Sınıflandırma işlemi her bir elektrot için ayrı bir şekilde yürütülmüştür. Böylelikle, SZ tespitinde etkin kanallar belirlenmiş ve bu kanallara ilişkin kapsamlı istatistiksel analizler uygulanmıştır. Bulgular, SZ tespitinin P4 ve T6 elektrot konumlarından etkin bir şekilde yapılabileceğini göstermiştir. Sınıflandırma doğrulukları P4 ve T6 kanalları için sırasıyla %87.2 ve %86.8 olarak elde edilmiştir. Ayrıca, PE dağılımlarının istatistiksel sonuçları, gama aktiviteleri için SZ hastalarında karmaşık nörodavranışsal özelliklerin önemli ölçüde azaldığını göstermiştir., Early diagnosis of schizophrenia (SZ) can improve the quality of life by allowing patients to receive more effective treatment. The complexity and heterogeneity of symptoms related to the disease hinder early clinical diagnosis. In this context, electroencephalogram (EEG) is used as an alternative diagnostic tool for the probable SZ. Due to the high temporal resolution of the EEG technique, the reflections of cognitive and behavioral processes on cortical activities can be successfully investigated. In this study, it is aimed to classify and evaluate SZ anomalies by permutation entropy (PE) based complexity analysis of EEG signals. PE analyzes were performed on EEG recordings from 45 adolescents with symptoms of SZ and 39 healthy participants. For feature extraction, PE values are computed for all sub-bands in the EEG as delta, theta, alpha, beta, and gamma waves. A multilayer perceptron neural network (MLPNN) is used as a classifier model. The classification process was performed separately for each scalp electrode. Thus, comprehensive statistical analyzes of the PE distributions related to the efficient channels were performed. The results demonstrate that SZ can be detected efficiently from the P4 and T6 electrode locations. The classification accuracy of 87.2% and 86.8% is obtained for P4 and T6 channels, respectively. Moreover, statistical results of PE distributions showed that complex neurobehavioral features significantly decrease in the case of SZ patients for gamma activities.

The decrease in fossil-based resources, the pollution of the environment and the threat of sustainability constantly increase the interest in renewable energy sources. Solar energy is one of the leading renewable energy sources due to its large capacity. Today, solar energy appears in many applications. In this study, a photovoltaic-based solar pole design has been realized and a prototype that can be applied almost anywhere in open-air conditions has been produced. The prototype produced was tested and installed at Gümüşhane University's Gümüşhanevi Campus. The prototype mobile phones produced have a fast charging feature with 5V-2A. In future studies, it is planned to provide the solar tracking feature to the photovoltaic (PV) panel in the system, and it is aimed to bring such systems to the campus in general.

In this study, an Adaptive Cruise Control system is designed by using conventional Proportional Integral Controller (PID) and Model Predictive Controller (MPC). In the design, vehicle, acceleration, and deceleration models are constructed in a way to sim-ulate the real-life environment. The design and simulation were carried out through Matlab and Simulink. In order to investigate the effects of gains in the PID controller, several values for Kp, Ki, and Kd is tested. The simulation results illustrated that the gains Kp and Kd have negligible effects on the vehicle acceleration but the gain Ki has a substantial effect on the response of the ego car. The results of PID controller were compared with the results when the controller is replaced by MPC. It has been shown that the PID controller gives better results as compared to the MPC controller inde-pendent from Kp, Ki, and Kd values. Therefore, we can confidently state that the PID controller provides better responses in addition to its accessibility, simpler design, and cost advantages compared to the MPC controller.

Facilitating instantaneous torque and smooth speed of Electric vehicle (EV) largely relies on modulation scheme employed and type of controller used for motor drive system. The DTC-SVM (Space Vector Modulation) approach with two PI controllers has an excellent steady state and transient response. However, there is still a need to reduce stator current and torque ripples in induction motor for application in Electric vehicle. This paper presents a new approach to minimize stator current harmonics, torque ripple of an induction motor drive with appropriate gain value for torque PI controller. Good performance of the induction motor drive is achieved using a single PI controller. Both flux and torque are controlled effectively with less torque ripple. In this study, torque and current ripples are obtained at full, one-half and one-fourth of the rated speeds at rated torque value. This work analyzes the transient operation of the drive for unit step change in command torque at various rotor speeds. Space Vector Pulse Width Modulation (SVPWM) of the drive at constant switching frequency is presented. Modeling and Simulation is performed in the stationary reference frame theory. The performance is observed during steady state and transient operations. The settling time of torque responses and stator currents are obtained during transient conditions. Torque ripples are obtained during steady state. A comparison with DTC-SVM with two PI controllers for the same Torque commands is well understood. Total Harmonic Distortion (THD) in the motor input current at different reference fluxes are tabulated for classical, two PI controllers and a single PI controller. The proposed DTC-SVM scheme with single PI controller is found to be robust with good steady state and transient characteristics with less settling time and is validated with flux vector trajectories.

Generally, two-stage voltage conversion is preferred for low-voltage DC sources such as PV (photovoltaic) modules, fuel cells, batteries, and super-capacitors however it is not suitable for the small power grid-connected system due to the cost and size. This work considers a single-stage, voltage level enhancement technique with a modified existing system. However, due to the clipped waveform, its output contains low-order harmonics. We design and implement an active filter, based on a clamper circuit to eliminate this clipped waveform. This filter has two tasks. First, detect the lower order harmonics then generate and add friendly harmonics. In our terminology, friendly harmonics are opposite in polarity with the low-frequency harmonics and the same polarity with the fundamental frequency. To prove the novelty, a comparative analysis with the existing strategy is also explained here. We also attempt to depict at least a 0.8% addition reduction in total harmonic distortion by comparing it with another methodology.

In the present paper, a forecasting study on the monthly electricity generation of Türkiye from the conventional and renewable resources is performed. The effect of the CoVid-19 pandemic on the sector has been considered. For this aim, the trend before the pandemic has been initially considered and later the post-pandemic situation has been handled. It has been observed that the electricity generation supply/demand mechanism changes drastically compared to the pre- and post-pandemic cases. The rate of the generation from the renewable resources especially shows a sharp variation compared to the rates from the fossil fuels. According to the forecasting scenario, in 2021, the electricity generation shows different attitudes with regard to the resources used. In 2022, especially increasing trends are expected for wind, biogas, natural gas, imported coal and fuel oil, whereas diesel and mineral coal are expected to be decreased in Türkiye.

Şebeke ile beslenen ve Değişken Hız Sürücüsü (DHS) ile beslenen elektrik motorlarının verimini tespit etmek için IEC tarafından yayımlanan standartlarda test ve ölçüm metotları tarif edilmiştir. İlk olarak 2007 yılında yayımlanmış olan ve şebeke ile beslenen elektrik makinelerinin verim tespit metotlarını içeren IEC 60034-2-1 standardı üzerinde hâlihazırda laboratuvarlar, akademisyenler ve üreticiler geniş bir tecrübe kazanmıştır. DHS ile tahrik edilen elektrik motorlarının verim tespiti ve kayıpları ile ilgili literatürde çalışmalar bulunmaktadır. Ancak DHS ile tahrik edilen motorların verim tespiti metotlarını içeren IEC 60034-2-3 standardı 2020 yılında yayımlanmış ve bu metotlarla ilgili olarak IEC 60034-2-1’deki kadar geniş bir birikim bulunmamaktadır. IEC 60034-2-3 testleri için, IEC 60034-2-1’deki temel donanımlara (dinamometre veya yük motoru, tork ve devir sensörü, en az 3 kanallı güç ölçer, sinüzoidal güç kaynağı) ek olarak standartta tanımlanan referans sürücüye ve 6 kanallı bir güç ölçere ihtiyaç vardır. Ölçüm metotları da temelde IEC 60034-2-1 ile benzerlik göstermektedir. Bu nedenle mevcut altyapılar yeni standarda göre modernize edilebilir. DHS ile yapılacak testlerde elektrik motorunun verim tespiti için 4 adet ölçüm metodu belirlenmiş ve bunlardan ikisi standart tarafından “tercih edilen metot" olarak tanımlanmıştır. Bu çalışmada bu metotların uygulamaları üzerinde değerlendirme ve bir örnek hesaplamanın uygulaması yapılmaktadır.

In addition to ensuring the stability of a Linear Time Invariant system with the LQR control approach, the fact that the feedback gain to be applied to the system is achieved by minimizing a quadratic performance criterion makes this control approach capable of shaping the performance expected from a closed-loop system. At this point, it is important in terms of controller performance to create the quadratic performance criterion or cost function to be minimized, over the weight matrices it contains, in accordance with the purpose. Therefore, the optimization of the weight matrices used in the design of the LQR controller should be carried out in line with the multiple performance objectives expected from the controller. This situation creates a multi-objective optimization problem. Although the weight matrices of the quadratic cost function can be adjusted with the help of classical methods such as trial and error, pole assignment, without optimization, this can be tiring and time consuming. In order to overcome this difficulty, it is possible to benefit from various multi-objective optimization techniques.Within the scope of this study, LQR-based optimal DC motor control is aimed. For the LQR controller, the Q and R weight matrix parameters of the square cost function need to be adjusted. Relevant parameters are adjusted with the help of the optimization algorithm known as Non-Dominated Sorted Genetic Algorithm (NSGA-II), which is one of the multi-purpose optimization techniques. By using the optimum parameters obtained, the performance findings of the synthesized LQR controller on the system are presented with simulation results., LQR kontrol yaklaşımıyla, Lineer Zamanla Değişmeyen bir sistemin kararlılığının temin edilmesi yanında, sisteme uygulanacak geri besleme kazancına, karesel bir performans ölçütünün minimizasyonu yoluyla ulaşılıyor olması, bu kontrol yaklaşımını, kapalı çevrim sistemden beklenen performansı şekillendirme kabiliyetine sahip kılmaktadır. Bu noktada, minimize edilecek karesel performans ölçütünün ya da maliyet fonksiyonunun, içerdiği ağırlık matrisleri üzerinden, amaca uygun biçimde oluşturulması kontrolcü performansı bakımından önem arz etmektedir. O yüzden, LQR kontrolcünün tasarımında kullanılan ağırlık matrislerinin optimizasyonu, kontrolcüden beklenen çoklu performans amaçları doğrultusunda gerçekleştirilmelidir. Bu durum çok amaçlı bir optimizasyon problemini doğurmaktadır. Karesel maliyet fonksiyonunun ağırlık matrisleri, optimizasyon yapılmaksızın, deneme yanılma, kutup atama gibi klasik yöntemler yardımıyla ayarlanabilir olsa da bu durum yorucu ve zaman alıcı olabilmektedir. Bu zorluğun üstesinden gelebilmek adına, çeşitli çok amaçlı optimizasyon tekniklerinden istifade edilmesi mümkündür.Yapılan bu çalışma kapsamında, LQR tabanlı optimal DC motor kontrolü amaçlanmıştır. LQR kontrolcü için söz konusu karesel maliyet fonksiyonuna dair Q ve R ağırlık matrisi parametrelerinin ayarlanması gerekmektedir. Çok amaçlı optimizasyon tekniklerinden biri olan ve Non-Dominated Sorted Genetic Algorithm (NSGA-II) olarak bilinen optimizasyon algoritması yardımıyla ilgili parametreler ayarlanmıştır. Elde edilen optimum parametreler kullanılarak sentezlenen LQR kontrolcünün sistem üzerindeki performans bulguları, simülasyon sonuçları ile sunulmuştur.

Elektrik enerjisinin üretim-tüketim dengesinin korunması, değişik yük taleplerinin karşılanması veya sistemde meydana gelebilecek geçici ve kalıcı arızaların elimine edilmesi oldukça önemlidir. Yaşam kalitesini artırmak için geliştirilen yeni cihazların dengesiz güç tüketimleri ve sürekli artan enerji ihtiyacı elektrik güç sistemlerinin enerji kalitesini, şebeke verimini ve enerji verimini düşürmektedir. Giderek karmaşık hale gelen elektrik şebekelerindeki başlıca problemler; aktif-reaktif güç dengesizlikleri, harmonikler, gerilim dengesizlikleri, geçici ve kalıcı arızalar olarak sıralanabilir. Bu çalışmada yaklaşık olarak 20 MW kurulu güce sahip olan bir dal-budak elektrik şebekesi aktif-reaktif güç dengesi ve gerilim kalitesi analiz edilerek şebekede meydana gelen güç dengesizlikleri ve arızalar tespit edilmiştir. Şebekedeki reaktif güç problemini elimine etmek için şebekeye dinamik kontrollü OG ve AG kompanzasyon uygulaması yapılmış ve bu uygulamayla aktif-reaktif güç dengesi, izin verilen yasal sınırlar içinde olacak şekilde ayarlanmıştır. Yapılan dinamik kompanzasyon uygulaması sayesinde şebeke güç oranları belirtilen sınırlar içinde tutulmuş ve gerilimi daha kararlı hale getirilirken güç faktöründe de iyileştirme sağlanmıştır.

Despite the advances in biomedical signal processing in recent years, the need for fast and highly accurate diagnostic systems for the detection of lung disorders continues. In the study, 150 normal and 444 abnormal lung sounds obtained by automatic detection of respiratory cycles from 94 different people by physical examination were used as a database. Then, 12 different feature extraction methods were applied in the time and frequency domain. Features were evaluated using embedded and wrapper feature selection methods. These methods are recursive feature elimination, adaptive structure learning, dependence-guided unsupervised feature selection, unsupervised feature selection with ordinal locality, feature selection via concave minimization, least absolute shrinkage, and selection operator feature selection methods. Features are classified by linear support vector machines, k nearest neighbor, decision trees, and naive Bayes classification methods. As a result, when the number of features is not limited, 97.3% accuracy is obtained when the recursive feature elimination method is used together with the k nearest neighbor classifier. In the case where the number of features is limited to three, the classification accuracy of 91.4% was achieved using the adaptive structure learning feature selection method and the decision trees., Son yıllarda biyomedikal sinyal işleme alanındaki gelişmelere rağmen, akciğer rahatsızlıklarının tespiti üzerine hızlı ve yüksek doğrulukta çalışan teşhis sistemlerine duyulan ihtiyaç artmaktadır. Yapılan çalışmada fiziki muayene ile 94 farklı kişiden, solunum döngülerinin otomatik olarak tespit edilmesiyle elde edilen 150 adet normal ve 444 adet normal olmayan akciğer sesleri veri tabanı olarak kullanılmıştır. Sınıflandırma işleminde öznitelik olarak frekans ve zaman bölgesinde 12 farklı yöntem uygulanmıştır. Tüm veriler %80 eğitim %20 test aşamasında kullanılacak şekilde ikiye bölünmüştür. Elde edilen öznitelikler gömülü ve sarıcı öznitelik seçim yöntemleri kullanılarak değerlendirilmiştir. Bu yöntemler; özyinelemeli öznitelik eliminasyonu, uyarlanabilir yapı öğrenimi ile öznitelik seçimi, bağımlılık kılavuzlu denetimsiz öznitelik seçimi, sıralı yerellik ile denetimsiz öznitelik seçimi, içbükey küçültme yoluyla öznitelik seçimi, en küçük mutlak büzülme ve seçim operatörü öznitelik seçim yöntemleri olarak isimlendirilmektedir. İncelenen bu öznitelikler doğrusal destek vektör makineleri, k en yakın komşuluk, karar ağaçları ve naive bayes yöntemleri ile sınıflandırılmıştır. Sonuç olarak öznitelik sayısının sınırlandırılmadığı durum için, özyinelemeli öznitelik eliminasyonu yönteminin k en yakın komşuluk sınıflandırma ile beraber kullanıldığı durum için %97,3 doğruluk değerindeki başarıma ulaşılmaktadır. Öznitelik sayısının üç ile sınırlandırıldığı durumda ise uyarlanabilir yapı öğrenimi ile öznitelik seçimi yönteminin karar ağaçları yöntemi ile beraber kullanılması ile %91,4 değerinde başarıma ulaşılmıştır.

In this research, the parameter values of the fractional order proportional-integral (FOPI) controller, which ensure the stability of the system, were calculated in a time-delay single area load frequency control (LFC) system with dynamic demand response (DDR). An efficient and simple graphical method had been applied to calculate all FOPI controller gains. For a given time delay, the method calculated all the compensating proportional-integral (PI) controller gains in the (𝐾𝑃, 𝐾𝐼) plane, which creates a stability region in the parameter space of the FOPI controller. This was done by equating the real and imaginary parts of the characteristic equation of the system to zero. Finally, for time-delayed single area LFC-DDR system with FOPI controller, results obtained were verified by using the timedomain simulation studies in Matlab/Simulink., Bu araştırmada, dinamik talep cevabı (DTC) içeren zaman gecikmeli bir bölgeli yük frekans kontrol (YFK) sisteminde kesir dereceli oransal - integral (FOPI) denetleyicinin sistemin kararlılığını garantileyen parametre değerleri hesaplanmıştır. Tüm FOPI kontrolör kazançlarını hesaplamak için etkili ve basit bir grafiksel yöntem uygulanmıştır. Belirli bir zaman gecikmesi için yöntem, FOPI denetleyicinin parametre uzayında bir kararlılık bölgesi oluşturan tüm dengeleyici orantılı-integral (PI) denetleyici kazançlarını (𝐾𝑃, 𝐾𝐼) düzleminde hesaplamaktadır. Bu işlem, sistemin karakteristik denkleminin reel ve sanal kısımları sıfıra eşitlenerek gerçekleştirilmiştir. Son olarak, Matlab/Simulink ortamında yapılan benzetim çalışmaları yardımıyla FOPI denetleyici içeren bir bölgeli YFK-DTC sistemi için elde edilen sonuçlar doğrulanmıştır.

Direct Torque Control (DTC) techniques are widely used in the control of AC machines as an opponent of space vector pulse width modulation (SVPWM) based field-oriented control (FOC). In the literature, hysteresis-based DTC (HB-DTC) is a vast majority of DTC techniques as the technique do not require a position resolver or an encoder. In this study, HB-DTC and FOC techniques are compared in detail by paying particular attention to current distortions, torque ripple and computational burden. In both techniques, the results have been obtained by simulating a 4.1 kW interior mounted permanent magnet synchronous (IPM) motor which has been designed and manufactured for research and development for electric vehicle traction applications. The results validate that although the HBDTC drives, have pros such as having less computational burden on the processor and eliminating the need for a position sensor, they have relatively much current distortions and torque ripple and hence the results are much deteriorated. Since the modern processors can easily deal with higher computational burden and field-oriented control is feasible in real time, it has been validated by extensive simulations that FOC based IPM drives are superior to their HB-DTC counterparts.

In this study, the positions only of linear antenna array (LAA) elements are optimized for the first time in the literature by using Honey Badger Algorithm (HBA) and Chameleon Swarm Algorithm (CSA) methods, one of the new metaheuristic algorithms, for antenna design with the desired radiation pattern. LAAs with 10, 12, 24 and 32 elements are considered in the simulations. While designing the antenna, the half-beam power width (HPBW) of the antenna array is kept at a minimum level and the maximum sidelobe level (MSL) is suppressed as much as possible. In addition, to test the performance and accuracy of the HBA and CSA methods, the results obtained with the swarm-based metaheuristic algorithms Artificial Bee Colony (ABC) and Particular Swarm Algorithm (PSO) methods, which are quite well known in the literature are compared. As a result of these comparisons, the antenna design with high directivity, gain and desired pattern has been successfully obtained with the HBA and CSA optimization methods., Bu çalışmada, istenen ışıma diyagramına sahip anten tasarımı için yeni metasezgisel algoritmalardan biri olan Bal Porsuğu Algoritması (Honey Badger Algorithm-HBA) ve Bukalemun Sürüsü Algoritması (Chameleon Swarm Algorithm-CSA) yöntemleri kullanılarak lineer anten dizi (Linear Antenna Array-LAA) elemanlarının konumları optimize edilmiştir. Simülasyonlarda 10, 12, 24 ve 32 elemanlı Lineer anten dizileri dikkate alınmıştır. Anten tasarımı yapılırken dizinin yarı demet güç genişliği (Half Power Beam Width-HPBW) minimum seviyede tutulmuş ve maksimum yan demet seviyesi mümkün olduğunca bastırılmıştır. Ayrıca HBA ve CSA yöntemlerinin performans ve doğruluğunu test etmek için literatürde oldukça iyi bilinen sürü tabanlı metasezgisel algoritmalar Yapay Arı Kolonisi (ABC) ve Parçacık Sürüsü Optimizasyonu (PSO) yöntemleri ile elde edilen sonuçlar karşılaştırılarak verilmiştir. Bu karşılaştırmalar sonucunda, HBA ve CSA optimizasyon yöntemleri ile yüksek yönlülük, kazanç ve istenilen ışıma diyagramına sahip anten tasarımı başarılı bir şekilde elde edilmiştir.

The new version of the hydro-electro-mechanical system (HEMS) is modeled via 14 serially connected electrical equivalent circuits resulting in an integrated equivalent circuit. The new model accepts a group of variables and even examines the interaction between them. This paper introduces an improved integrated new model of the heart by replacing the monolithic equivalent structures with segmental comprehensive equivalents. Windkessel Model (WM) is a model of the relationships between aorta, aortic valve and left ventricle. Based on WM, the integrated new model was developed and simulated. The model’s main focus is to define the dynamic properties of the system by a set of ordinary differential equations, and solving them using Ode23, a method for the solution of a closed-loop system. Using Matlab based Ode23 method; time-dependency of pressure, volume and flow were obtained. In case, short computation time and high accuracy are needed, then ode23 is used. The model may be used to analyze complex processes in the heart and blood vessels. The new HEMS model has potential use for hemodynamic simulation of diseases, cardiovascular disorders, and special congenital heart diseases; such as ASD, VSD and PDA.

This article aims to assess life cycle analysis of a wind turbine in Turkey regarding production, transport, construction, operation, and disposal processes in terms of energy and environment. In this context, a 2-MW three-bladed horizontal axis wind turbine has been selected. Two different scenarios have been studied which comprises wind turbines using Al-Conductor and Cu-Conductor cables. Although the cost of Al-Conductor cables is low, their joule losses are higher. The life cycle assessment of a wind turbine includes production, transportation, construction, operation and disposal, and the energy has been generated in its operation time (selected as 20 years). Iron, cast iron, steel, copper, aluminum, and oil have been sent to a recycling facility and the composite materials has been sent for incineration at the end of its life. The energy payback period has been calculated as 10 months in both scenarios and the embodied energy is 2858.2 MWh and 2830.3 MWh for wind turbine using Al-Conductor and Cu-Conductor cable during its lifetime, respectively. Air emission and wastewater production have been calculated to assess environmental impacts (global warming, acidification, eutrophication, etc.) whose consequence provides an evaluation of the life cycle assessment of a wind turbine. For example, global warming is 14.44 and 15.24 g CO2 eq./kWh for wind turbine using Al-Conductor and Cu-Conductor cable, respectively. As a result, the life cycle analysis of the wind turbines has been evaluated and compared regarding two different scenarios according to the definition of ISO 14040 standard throughout its life from production to disposal.

In this paper, it was aimed to carry out the design, electromagnetic analysis of a 3 phase and 6 phase, axial flux permanent magnet synchronous motor with power level of 240W and 3000rpm speed. The motors were designed for an automotive ventilation fan of the HVAC system, each with the same outer volume, output power, and core material. Finite element analysis (FEA) was employed to observe the characteristics of each motor The performance of 3-phase 12/10, and a 6-phase 12/10 axial flux permanent magnet motor (AFPM )are analyzed and compared.. Lastly, experiments were done and the results were compared. The main goal of this study is to observe fundamental differences between each motor and give a general guideline on the characteristics of AFPM

Two wheeled Self balancing robots have become more popular in recent times and used in many applications, commonly used in transportation as these balancing robots are faster and apparently stable. Balancing is achieved by using controllers tuned for the system. Inverted pendulum principle is used in these robots. This paper proposes the use of two control methods, namely Proportional-Integral-Derivative (PID) and Extended PID (EPID), for maintaining the balance of two-wheeled and self-balancing robots, even when slightly tilted, thus preventing them from falling. PID control theory generally depends up on transfer functions, this paper extends the theory using EPID. EPID provides a new perspective on the working principle of PID control and its relationship with other control theories, such as tracking control and disturbance observer. This approach is illustrated using the fundamental principle of inverted pendulum technology. The key advantage of these robots over other mobile robots is their increased stability due to zero turning radius, which allows for smoother rotations during changes in direction.

Data Availability Statement: The data presented in this study are available on request from the corresponding author. The data are not publicly available due to the project being ongoing. Copyright © 2023 by the authors. Electric distribution grids are seeing an increased penetration of photovoltaic (PV) generation. High PV generation exceeding the grid load demand results in a reverse active power flow in the grid, which raises the voltage level. This paper presents a reactive power controller to overcome the overvoltage problem in the distribution system. A sequentially coordinated and cooperative volt/var control technique is presented. The proposed controller aims to use as low reactive power as possible while mitigating the voltage issues. Accordingly, it reduces the active power loss associated with reactive power flow and reduces the probability for active power curtailment of the PV system. The controller is developed for each lateral and is replicated for all laterals. The lateral controller coordinates the operation of the smart PV inverters in a sequential manner. Cooperative control is proposed between the laterals’ controllers as well and is engaged when the individual laterals’ controllers are unable to solve their overvoltage issues. The performance of the proposed controller is evaluated by comparing it to two other volt/var controllers, and it demonstrates better performance in terms of reactive power requirement. To conduct the simulation study, a modified version of the unbalanced IEEE 13-bus system is utilized, which includes an additional 44 low-voltage bus. The study involves simulating 720 operating points across daily time series. The results indicate that the proposed controller effectively addresses overvoltage problems that occur during periods of high PV generation. Newton Fund Institutional Links grant number 623801791, under the Newton-Katip Çelebi Fund partnership. The grant was funded by the UK Department for Business, Energy and Industrial Strategy and TUBITAK grant number 120N996 and delivered by the British Council.

In 2019, the world had been attacked with a severe situation by the new version of the SARSCOV- 2 virus, which is later called COVID-19. One can use artificial intelligence techniques to reduce time consumption and find safe solutions that have the ability to handle huge amounts of data. However, in this article, we investigated the classification performance of eight deep transfer learning methodologies involved (GoogleNet, AlexNet, VGG16, MobileNet-V2, ResNet50, DenseNet201, ResNet18, and Xception). For this purpose, we applied two types of radiographs (X-ray and CT scan) datasets with two different classes: non-COVID and COVID-19. The models are assessed by using seven types of evaluation metrics, including accuracy, sensitivity, specificity, negative predictive value (NPV), F1- score, and Matthew\"s correlation coefficient (MCC). The accuracy achieved by the X-ray was 99.3%, and the evaluation metrics that were measured above were (98.8%, 99.6%, 99.6%, 99.0%, 99.2%, and 98.5%), respectively. Meanwhile, the CT scan model classified the images without error. Our results showed a remarkable achievement compared with the most recent papers published in the literature. To conclude, throughout this study, it has been shown that the perfect classification of the radiographic lung images affected by COVID- 19.

Although the egg is a cheap food source, it is one of the valuable nutritional sources for people because of its rich nutritional values. It is also among the most consumed foods in daily nutrition. With the increase in egg production, it is very difficult to collect them with the human power in the egg production farms, to classify them according to their weights and to separate the defective (dirty and broken) eggs. Therefore, the mechanization has become a necessity in large capacity production farms. Cracks and fractures may occur in the egg shell as a result of exposure to external factors such as the transportation of eggs. The cracks or fractures that are formed leave the egg vulnerable to disease-causing micro-organisms. Before the egg sorting and packing, the broken and cracked eggs must be separated. This process is commonly carried out with manpower by which it is very difficult to obtain the necessary efficiency. In this study, the egg crack detection was performed by using Support Vector Machines (SVM) and Artificial Neural Network (ANN). As a result of the application of studied methods, the accuracy values of crack detection process were 0.99 for ANN and 1 for SVM. In addition, a data acquisition and processing program was developed in LABVIEW environment to detect cracks in real time.

The existing value chains of the energy companies are eroding. Trends such as digitization, big data and AI have long since arrived in the energy industry. These demanding framework conditions are increasingly forcing energy companies to introduce new business models. A possible business model lies in smart home applications. This paper analyzes the added value of smart home applications for customer loyalty of energy companies and electricity customers, as well as to identify obstacles in the context of practical implementation. This paper examines smart home applications and the intelligent control and integration of photovoltaic systems. Above all, the avoiding of peak loads will play an important role in the energy grids of the future. The methodology describes the necessary framework conditions existing for the generation of digital innovations. Moreover, it examines the factors leading to increased customer loyalty through the value-added services and offers a load shifting potential to relieve the distribution networks. It is found that the value-added services can offer increased customer loyalty to the energy companies. Even though smart home-based services are highly relevant in a rapidly growing target market, there will only be a broad acceptance of them for the load control, if the user is offered an added value, for example by load-variable electricity tariffs. Energy companies wishing to position themselves as digital service providers must have smart home-based services such as intelligent load control and load-dependent tariff models, which enable users to add a financial value.

As an effective means of providing power to remote and off-grid areas of developing countries, where rural electrification problems are most common, hybrid renewable energy systems are considered. HOMER simulated and configured wind turbine, photovoltaic, battery bank, and converter for the electricity demand of the Mander rural community, which has 37 families with household sizes of 7 members, as a remote village in Northern Iraq in this article. The hypothesis project was also evaluated using the parameters Net Present Value and Simple Payback Period. Daily energy consumption of 173,120 kWh and peak electricity consumption of 32,14 kW were measured for the outcome of the selected site. The proposed system produced 68,458 kWh/yr (13.7 percent) by the wind turbine, PV created 432,354 kWh/yr. (86.3 percent), and 265 operating batteries with a total operating cost (TOC) and costs of energy (COE) of $9,195 and 0.365 $/kWh, respectively. This survey emphasized the role of solar photovoltaic and wind turbine as hybrid renewable energy systems HRESs in the sustainable supply of electricity in rural areas of northern Iraq.

Obtaining energy with high efficiency from solar panels, which are an endless source of energy, is one of the important research topics today. There are many methods applied both in manufacturing and after manufacturing to increase efficiency in solar panels. One of the methods that affect the efficiency of solar panels is the removal of dirt from the panels. The method is preferred since it does not affect the manufacturing cost and is for old panel users. Innovative panel cleaning method affects maintenance costs. This article presents a new approach to improving the efficiency of solar panels versus traditional method cost analysis. In this study, which includes an experimental approach, 10W solar panels with equal parameters were used. The correlation between the gain and the cost of the efficiency increase in the solar panel coated with rain-slip solution, which is a new approach, has been examined. Cost benefit analysis in this study will guide both small-scale and large-scale solar panel users.

The inverters are frequently used in power electronics applications in the industrial area. Research on multi-level inverter circuit designs in power systems interfaces has intensified in recent years. The design type and quality of the inverter circuit topology is very important for the output voltage to be closer to the sinusoidal waveform. In addition, artificial intelligence techniques for the control algorithms of the power switches of the inverter circuit provide useful information in terms of monitoring the estimated the voltage conditions of the inverter output parameters. In this work, an Adaptive-Network Based Fuzzy Inference Systems (ANFIS) model is proposed to estimate the Total Harmonic Distortion (THD) value of the output current of a three-phase three-level inverter circuit. By changing the switching frequency in the control circuit of the inverter, a data set for the THD values of the inverter current is obtained by Fast Fourier Transform (FFT) analysis in MATLAB. This data set is used in a training and testing phase of ANFIS artificial intelligence algorithm, and the THD value of the current is estimated. At the end of the estimation, the mean absolute error (MAE) values for training and testing are obtained as 0.1894% and 0.4009%, respectively, thereby, an ANFIS estimation example for parametric data set analysis in a power electronics circuit run with Matlab-Simulink software, and a parametric simulation study is presented to the literature for power electronics circuit designers.

Self-excited induction generators (SEIGs) have been rigorously investigated in last few decades owing to their suitability for standalone renewable energy applications. Various issues pertaining to their modeling and control are quite aptly addressed in several analytical and experimental studies. However, these analyses are often focused on elaboration of proposed innovations and findings while the important details on modeling and implementation of SEIGs are left to be explored by readers. In this paper, a step by step approach for the mathematical modeling of three-phase self-voltage regulating, short shunt SEIG in stationary reference frame is explained. Subsequently, the developed d-q model of SEIG is implemented in terms of a simulation model. The developed model is then employed to carry out performance analysis of 3-phase, 2.2 kW SEIG supplying R-L load. All the results are verified with good accuracy in a SEIG test-rig whose details are included in the paper. The prime objective of this work is to provide a consolidated source for developing research resources of a self-voltage regulating three phase SEIG.

Core losses of transformers motivate many engineers and scientists to design and implement different transformers for their specific aims. Since there exists a growing interest on high frequency applications in today’s world, design and optimization studies of a magnetic fluid core transformer (MFCT), having an easy and cheap production approach in high frequency applications, are considered in the present paper. The desired design should operate in a more efficient way within a wide frequency band. The MFCT considered here can be a solution to the eddy currents and core losses encountered in the conventional transformers with its low conductivity, oil-based magnetic fluid and super paramagnetic characteristic. The magnetic fluid in the proposed work consists of a combination of ferromagnetic particles made by iron in an averaged diameter of 70 µm with an adjustable magnetism compared to the traditional magnetic fluids and an engine oil, thereby the magnetic permeability of the overall fluid core can be fully adjustable by the variation of mass proportion between the oil and iron powder as an easy process without any chemical process. A COMSOL Multi-Physics design is performed via a finite element package in three dimensions. It is proven that the iron particles exhibit a complicated pattern inside the engine oil and produce a well-defined high frequency output at the secondary windings in a wide range of frequency.

In this study, optimal power management strategy to make optimal operation of the alternative sources has been considered to meet the load demand of heating, ventilations and air conditioning (HVAC) units for public institutions, hospitals, schools, etc. A hybrid power system consisting of wind türbine (WT), photovoltaics (PV) and battery has been proposed. The system is modelled to be used in an optimal demand response application. Moreover, the grid has been added to the hybrid power system due to the intermittent generation characteristics of alternative power sources. The objectives defined by the optimization problem are the operation of the alternative power sources at maximum rate and primarily meeting the HVAC load demand by the relevant sources. The resulting mixed-integer linear programming model is tested in GAMS v.24.1.3 platform using the solver CPLEX v.12., Bu çalışmada, kamu kuruluşları, hastane, okul vb. gibi kurumların iklimlendirme cihazlarının yük talebinin karşılanmasında alternatif enerji kaynaklarından optimal olarak yararlanma stratejisi ele alınmıştır. İklimlendirme yüklerinin karşılanmasında rüzgar türbini (RT), güneş pili (GP) ve batarya (Bat) ile teşkil edilen hibrit güç sistemi önerilmiştir. Hibrit güç sistemi optimal talep cevabı uygulamasında kullanılmasına imkan verecek şekilde modellenmiştir. Ayrıca, hibrit kaynakların kesintili üretim karakteristikleri gereği hibrit güç sistemine şebeke gücü de ilave edilmiştir. Optimizasyon probleminde alternatif enerji kaynaklarının maksimum kapasitede kullanımı ve ilgili kaynakların öncelikli olarak iklimlendirme yüklerinin talebine cevap verecek şekilde kullanımı amaç olarak belirlenmiştir. Elde edilen karışık tamsayı lineer programlama modeli GAMS v.24.1.3 ortamında CPLEX v.12 çözücüsü ile test edilmiştir. Kış ve yaz koşulları dikkate alınarak optimal işletim modelinin benzetim çalışmaları yapılmıştır ve ilgili sonuçlar sunulmuştur.

Faz kilitli döngü (PLL), iletişimde teknolojinin ilerlemesine önemli ölçüde katkıda bulunan bir tekniktir. İlk uyumlu modülasyon sistemleri geliştirildiğinden beri elektronik mühendisliğinde faz ve frekans senkronizasyon sorunları mevcuttur. Bu makale, PLL'nin temel ayrıntılarını vermektedir. Kontrol sistemleri ve dijital iletişim için geçerli olan temel PLL ilkesinin kısa bir özetini sağlar. Ayrıca PLL bileşenlerini ve bunlar arasındaki karşılaştırmayı da bildirir. PLL'ler, doğru zaman esasını kurtarmaktan ve süreçleri senkronize etmekten sorumludur. Uygulama ihtiyaçlarına göre, master-slave en basit ve en çok kullanılan seçim olmak üzere farklı saat dağıtım stratejileri geliştirildi. Senkronizasyon için en aktif senkronizasyon tekniklerinden biri olduğu için PLL teknikleri seçilmiştir. Bu makale, MATLAB'ın Simulink'i, simulasyon yöntemi ve devre tasarımı ve PLL'yi senkronize etmek için matematiksel çözümler içermektedir., Phase-locked loop (PLL) is a technique which has contributed significantly toward the technology advancement in communication. Phase and frequency synchronization problems have been present in electronic engineering since the first coherent modulation systems were developed. This paper gives basic details of PLL. It provides brief summary of the basic PLL principle applicable to control systems and digital communication. It also reports components of PLL and comparison among them. PLLs are responsible for recovering the correct time basis and synchronizing the processes. According to the application needs, different clock distribution strategies were developed, with the master-slave being the simplest and most used choice. PLL techniques is chosen for synchronization, since it is one of the most active synchronization techniques. This article contains Simulink of the MATLAB, simulation method and circuit design and mathematical solutions to synchronize PLL.

As technology scales, transistors become smaller and aggressive power optimization techniques combined with high operation frequencies and performance-enhancing microarchitectural techniques are employed to achieve increasingly higher performance and power efficiencies. Unfortunately, these developments make the modern systems more vulnerable to soft errors, which are becoming a critical issues in both hardware and software domains. Motivated by this observation, in this work, we propose, implement, and evaluate two error propagation metrics in order to characterize error propagation at both software and hardware levels. The first metric aims to measure error propagation on program data structures, whereas the second one measures the fraction of corrupted locations in the cache memory structure for a given period of time. We evaluate our proposed metrics by performing an empirical study of two application programs using both single-threaded and multi-threaded executions, and varying various experimental parameters such as thread count, error rate, location of errors, and architectural parameters. Our extensive experimental analysis reveals that error propagation over program data structures is highly dependent on application behavior.Further, depending on the cache parameters used, propagation of errors on cache can exhibit different patterns. This paper also discusses how our observed error propagation trends in program data structures and data caches are correlated with each other, focusing in particular on the differences in error propagation speeds in application data structures and data caches.

Gelişen teknoloji ve sanayileşme ile birlikte elektrik enerjisi tüketimi her yıl artış göstermektedir. Artan talebe karşı üretilen elektrik enerjisinin de yeni ve yenilenebilir enerji kaynakları arasından olması önem arz etmektedir. Fabrikalar kendi elektrik enerjisini kendi üretme yoluna giderken aynı zamanda bu durumlar enerji kalitesini de olumsuz olarak etkileyebilmektedir. Bu çalışmada bir tekstil fabrikasının öz tüketim modeli ile kurmuş olduğu güneş enerjisi santralinde enerji kalitesi ile ilgili yaşadığı sorunlar detaylı olarak analiz edilmiş ve ölçümler gerçekleştirilmiştir. Ölçüm metodu ve ölçümün nasıl gerçekleştirildiği konuları ile ilgili detaylı bilgiler de paylaşılmıştır. Enerji kalitesindeki sorun güneş enerjisi santralinin üretim performansını da olumsuz olarak etkilemekte ve düşük üretim yapmasına neden olmaktadır. Üretim performansın iyileştirilmesi, enerji kalitesinin düzeltilmesine bağlı olduğu için enerji kalitesinin iyileştirilmesi konusunda da çözüm önerileri sunulmuştur., With the developing technology and industrialization, electrical energy consumption is increasing every year. It is important that the electrical energy produced against the increasing demand is among the new and renewable energy sources. While factories go to produce their own electrical energy, these situations can also negatively affect energy quality. In this study, the problems related to energy quality in the solar power plant that a textile factory built with a self-consumption model were analyzed in detail and measurements were made. Detailed information about the measurement method and how the measurement is carried out is also shared. The problem in energy quality also negatively affects the production performance of the solar power plant and causes low production. Since the improvement of the production performance depends on the improvement of the energy quality, solution suggestions are also presented for the improvement of the energy quality.