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This paper introduces a technique to reduce the output impedance in the PWM buck converters with voltage-mode control (VMC) without requiring low Equivalent Series Resistance (ESR) output capacitors. Proposed technique uses the infinity norm ( ) to convert the problem into an optimization problem. Obtained optimization problem is solved with the aid of Genetic Algorithm (GA). The proposed technique is applied to a sample buck converter operating in Continuous Conduction Mode (CCM). Simulink simulation is used to test the suggested method. Simulation results showed a considerable decrease in the low frequency region of output impedance. Such a decrease in output impedance is very desired for low voltage high current loads like computer CPU’s.

The most common type of identification system today is RFID. RFID circuits are used as covered with plastic. With the increase in usage areas, it is also used on metal, wood, paper, and plastic product. In this study, the behavior of the same circuit on different surfaces was investigated. The surface impedance and signal reflection coefficients of RFID tag antennas were investigated based on paper, plastic, and textile surfaces. According to the results of the electrical and mechanical tests, the best results in terms of reflectance coefficients and surface impedances of RFID tags are on PET surfaces. The surface impedance and the reflection coefficients were high on paper surfaces. The lowest values were measured on textile surfaces. According to the results, it has been seen that RFID antenna application on plastic, paper, and textile surfaces is possible and usable.

This paper presents a method based on meta-heuristic to solve Dynamic Economic Dispatch (DED) problem in a power system. In this paper, Crow Search Algorithm (CSA), which is one of the heuristic methods is proposed to solve the DED problem in a power system. In this study, line losses, generation limit values of generators, generation-consumption balance, valve-point effect and ramp rate limits of generator are included as constraints. The proposed algorithm was implemented on two different test cases. Finally, the CSA results were compared with the results of well-known heuristics in the literature such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Symbiotic Organism Search (SOS) algorithm, Artificial Bee Colony (ABC) algorithm, Simulated Annealing (SA), Imperial Competitive Algorithm (ICA), Modified Ant Colony Optimization (MACO) algorithm. The results show that the proposed algorithm has a better operating cost. With the results of the algorithm proposed in the test system 1, a profit of $2,056,5931 per day and $751,751,4815 per year is obtained. It is seen that with the results of the algorithm proposed in the test system 2, a daily profit of $12,279,7328 and a yearly profit of $4,482,102,472 are obtained. Test systems are operated by using less fuel with the results of the proposed algorithm and thus the harmful gas emissions released by thermal production units to the environment are also reduced.

The radio frequency identification (RFID) is a configuration of wireless communication that uses radio frequency (RF) waves for following up and recognizing data. The RFID system includes important parts as antenna and integrated circuit (IC) for radiating and storing data, respectively. Hence, high performance antenna and IC circuits must be designed for assembling the energy from the radio waves and feeding the RFID chip. One of the important circuit/block in the IC part is the amplifier where the antenna is sensing the radiated output power. For this case, it is substantially important to design high performance antenna and amplifier where the specifications of these circuits must be optimized in a professional way. In this paper, we collect the recently published optimization methods that are employed for designing antenna and RF/analog-based amplifiers. Any researcher by referring to these algorithms can access and find the solutions for their problems, straightforwardly.

The increase in energy production costs, and the increasing demand for energy have made energy saving necessary. Energy saving in lighting is able to be actualized by providing economically the same level of light without decreasing the illumination quality. A good lighting is possible by directing required amount of light to spaces desired to be lit. For a good lighting, efficiency factor is a significant measure. By adjusting the luminous efficacy in lamps, the electric energy to be consumed by the lamps is able to be minimized. The electric energy consumed for producing luminous energy will be less at the extent of greatness of luminous efficacy. In this study, the luminous efficacy of lamps of different brands were estimated by the use of data regarding voltage rating, power rating, and total luminous rating of lamps. According to the results of the analysis made by the developed ANN model, the luminous efficacy of lamps of different brands were estimated with an accuracy rate of above 98%. Regarding the lighting systems to be developed, the selection of lamps will be made based on their ability to provide economically the same level of light without decreasing the lighting quality, and to provide the required luminous efficacy for increasing the luminous efficacy.

Industrial Internet of things (IIoT) is a paradigm that changes the way people interact with infrastructures by enabling ubiquitous connection to the Internet. It allows to design connected infrastructures in industrial environments, e.g., factories, in order to support innovative services and improve efficiency. While the advantages of IIoT are numerous, it has some fundamental issues such as propagation of signal through metallic obstacles, i.e., walls in industrial environments. To address this issue, we propose a hybrid wired-wireless mesh node and network topology called hybrid mesh network (HMN), enabling the signal to cross over the metallic obstacles in harsh environments. The proposed hybrid mesh node utilizes dualradio feature of IEEE 802.11 Wi-Fi standard to improve the performance of the proposed HMN further considering multihop communications. The effects of the packet size and different fading channels on the performance of the proposed HMN are investigated through various simulations. In addition, the performance of the proposed HMN is compared with that of conventional wireless mesh network (WMN). The results reveal that the proposed HMN outperforms conventional WMN and the proposed topology is promising for the implementation of high performance wireless mesh networks in harsh environments.

Fractional calculus has gained increasing attention from researchers because of providing accurate modelling and flexible controller design in control applications. More research to design controllers for Fractional Order Two-Input Two-Output (FOTITO) systems, which inherently have certain difficulties, is needed when the studies about these control applications are considered. In this study, Coefficient Diagram Method (CDM) based decentralized controllers are designed for FOTITO systems. For this, integer order approximate models of FOTITO systems are obtained and decoupled into two subsystems by using simplified and inverted decoupling configurations. Obtained high-order approximate subsystem transfer functions are reduced by a model reduction method to facilitate CDM-based decentralized controller design. Then, CDM-based decentralized controllers are designed for each subsystem, which enables to obtain the controllers of the FOTITO system. Simulation results for two different FOTITO systems, one of which is a time delay fractional order system, are demonstrated that the proposed approach exhibits successful performance.

Electrical energy consumed in residential has an important value in total consumption. For this reason, monitoring and control of the electricity consumed in the residential offers a significant potential for energy saving. In this study, the power parameters of the linear and nonlinear loads used in the residential have measured, analyzed and controlled in real time. Thanks to real-time monitoring, analysis and control of power parameters ensure efficient use of energy. For this, power parameters of the loads used have transferred to the computer thanks to the data acquisition card. A visual interface has been created with the software designed in the Laboratory Virtual Instrument Engineering Workbench (LabVIEW) program so that the data transferred to the computer can be monitored and controlled instantly.

Ease of driving and flexibility in movements are very important for the developing automobile technology today. The aim of the study is to provide convenience to the driver by trying different modes in the steering system of a vehicle. In this study, an electronic board has been designed for the steering system for the 4 wheels in the vehicle. With the electronic card made, the user is given the opportunity to choose from 3 different modes (standard, circle, crab). The modes that the user chooses according to the situations provide advantages. The 4-wheel steering system improves handling stability and active safety at high speeds. Using 4-wheel steering at low speeds can reduce the turning radius on the steering wheel for more convenient manoeuvres. Positive feedback is received from the users who have tried it, and the system continues to be tested on different vehicles, and if any, vulnerabilities are tried to be detected. It is planned to easily solve the problems and developments that may occur with the electronic card design. The 4WS controller developed has been tested on the vehicle. The results obtained are satisfactory. It shows good response performances also improves ride quality and stability.

The outer rotor brushless direct current motor, which is a highly speed, efficiently, silence and long-life motor, is the most popular motor for drones. Control methods of this type of motor is the most important parameter to be considered. The hall effect sensors, that used in BLDC motor, are not trustable in control applications therefore the back-EMF observer method can be operated for sensorless control. Reducing the production cost of the drive for drone applications is one of the primary goals of manufacturers. Manufacturing cost reduction is often achieved by eliminating driver auxiliary components such as sensors. The use of these sensors, which are important for the detection of rotor position, has been eliminated with sensorless driver designs. This study presents a sensorless outer rotor BLDC motor driver algorithm with back-EMF observer with motor input terminal current and DC bus voltage independent of rotor speed. The sensorless driver model proposed in the study was implemented for a 330W drone motor with a rated voltage of 14.8V. The proposed sensorless control algorithm is proved by MATLAB/SIMULINK results

Wifi based indoor localization gains the interest of researchers for several purposes. Among various techniques, fingerprinting based on Wifi received signal strength indicator (RSSI) is a widely used feature in indoor localization because of its simplicity in implementation and minimal hardware requirement conditions. However, the amount of access points (AP) at which the RSSI is measured from in the network increases the computational load. This paper presents an alternative approach for dimension reduction in RSSI based indoor localization. We focus on recognizing the building and floor of the test user which is a multi-class problem for both cases. In a multiple class problem, inter-class differences are obtained by Manhattan distance in pair-wise manner. From each pair calculation, top-25 and top-50 features with the largest variances are chosen and merged to generate the final feature set. The proposed algorithm is implemented and evaluated on UJIIndoorLoc dataset. According to the outcomes, our method provides 99.1% accuracy for building and 82.8% accuracy for floor estimation

As complexity and the type of electrical applications perpetually expands, monitor and control will require new systems which are based on some features in such feature of self-powered and distantly management. Building management systems (BMSs) are developed as efficient solutions to monitor and control users electrical and mechanical applications. A BMS employs cheap sensors and a real-time module to create prior knowledge about the climate inside the building. As a result, these features give some attractive advantages in taking a precise decision and managing vital operations of electrical applications. In this paper, a Raspberry Pi as minicomputer for collecting information from server room or data centre for detection the existence of human, temperature and humidity sensor and gas sensors to control ventilation systems, Arduino platform is responsible for receiving sensors signal and control actions according to the statues in the server room. While the Xbee protocol has been used to transmit data from the sensing node (Raspberry PI3) to mentors and control nodes (Arduino mega2560). The prototype design has been verified experimentally.

In this study, the Market Clearing Price (MCP) is forecasted with Artificial Neural Networks and the modeling success is examined for different preprocessing strategies. The purpose of the study is to obtain the optimum model with a significant estimation success and to provide the best price prediction. The hour-based electricity generation data of diverse production items are assigned as inputs and the resulting MCP is modeled. The raw data are first cleaned from outliers, then subjected to different normalization processes and 70 different ANNs are trained. Additionally, networks are trained with data classified in seasons and the effect of seasonal patterns on model success is observed. Finally, networks showing the optimum performance are selected. It is noted that the type of the normalization strategy and the hidden layer size are the key factors to make a decent estimation. Then, in order to test the networks with extreme cases, data for the special days (official holidays) are applied to these networks as input. The success of the networks is evaluated by comparing the MCP predictions with the actual values. It is revealed to make a prediction for official holidays, a model which is special to this period of year is required.

In this study, a low-profile, high directive circular microstrip antenna was designed for 5.8 GHz ISM band applications. In the design, the GA / MoM approach based on the Method of Moments (MoM) integrated with the Genetic Algorithm (GA) optimization method was used. The simulations of the best first and second antennas obtained as a result of the optimization process were made using the ANSYS HFSS software program. According to the simulation results, it was determined that the return loss of both antennas was below 10 dB in the ISM band where the antenna was operating and had maximum directivity. It was observed that the radiation characteristics of both antennas obtained with the GA / MoM approach were steady-state in the operating band. It was concluded that asymmetric pixelation used in this method can be used in the design of antennas with different geometries.

In this study, available spectrum parts in GSM900, LTE800, LTE900, GSM1800, LTE1800, UMTS2100 and LTE2600 were determined. The measurement campaigns were performed at 115 different locations in Samsun city center at the most active time of a day using RF Explorer 6G Combo analyzer device. The spectrum utilization rates were determined using energy detection technique (EDT), and average spectrum occupancy technique (ASOT). The thresholds were chosen manually as -40, -45, -50, -55, -60, -65, -70, -75 dBm, and as 10-dB above the noise floor, as recommended by International Telecommunication Union (ITU), and spectrum utilization was evaluated through EDT and ASOT. Obtained results show that at most of the measurement locations spectrum occupancy percentages calculated via EDT and ASOT very close to each other. Based on the results UMTS2100 band showed the highest average spectrum occupancy i.e. 33.91% and the overall average spectrum occupancy rate was found to 22.72%. Additionally, at 50% of the measurement locations occupancy percentage was below 33% for all services. The average occupancy over GSM900 band was between 0,87% - 66.61% according to the predetermined threshold. It was also found that the bands LTE1800 and LTE2600 were mostly occupied for the thresholds below -60 dBm whereas the measured spectrum was mostly vacant for -40 dBm. This led us to infer that there is a great potential for share some of UHF band for cognitive radio applications and future 5G systems.

It is seen that there is an increase in cancer and cancer-related deaths day by day. Early diagnosis is vital for the early treatment of the cancerous area. Computer-aided programs allow for early diagnosis of unhealthy cells that specialist pathologists diagnose as a result of efforts. In this study, kMeans and Fuzzy C Means methods, which are among the global segmentation methods, and SLIC, Quickshift, Felzenszwalb, Watershed and ERS algorithms, which are among the superpixel segmentation methods, were used for automatic cell nucleus detection in high resolution histopathological images with computer aided programs. As a result of the study, the success performances of the segmentation algorithms were analyzed and evaluated. It is seen that better success is obtained in watershed and FCM algorithms in high resolution histopathological images used. Quickshift and SLIC methods gave better results in terms of precision. It is seen that there are k-Means and FCM algorithms that provide the best performance in F measure (F-M) and the true negative rate (TNR) is more successful in Quickshift, k-Means and SLIC methods.

Electrification in urban transportation is becoming more popular, beside it is also becoming a necessity due to climate changes and sustainability issues. Trolleybuses are presenting an alternative for this purpose. Although their technology is a mature technology that has been used for decades, there are still some technical problems that need to be overcome. In this study, a technical method is presented for the conversion of trolleybus auxiliary power units. The electrification conversion demanded by the metropolitan public transportation company operating 22 trolleybuses in the province of Malatya is the replacement of diesel generators, used as auxiliary power units, with battery units capable of meeting the local operational requirements. For this purpose, a method is proposed and followed. At first step of the implementation, real-time data has gathered from a trolleybus and this one round tour data is used to run on a scaled experiment. The setup has prepared as hardware and software to simulate the consumption on a scaled battery pack. Experimental results were interpreted with capacity and voltage restrictions resulting the determination of battery chemistry and casing to be used. Then optimal battery placement was defined as a container loading problem and application was made with the first fit decreasing algorithm considering mass and volume restrictions. It was found that only two packing types out of six combinations is enough to form a battery pack within the mass and volumetric limitations. It is evaluated that the method adopted in this study can be used in conversion applications to be made in the future.

Developing technology and growing population are increasing the need of countries for energy every passing day. Renewable energy resources, which are an environmentally friendly and local solution alternative to fossil fuels, are seen to be a significant source of supply in this matter. Among renewable energy resources, hydroelectric energy is in an advantageous position with its reliable potential and sustainable production. With the purpose of utilizing small flowing waters such as rivers and streams and solving problems of access to interconnected grids in rural areas, micro-type hydroelectric power plants have a significant potential for countries. This study carried out the design and performance analyses of permanent magnet synchronous generators with different numbers of poles for micro hydroelectric power plants. The generators’ flux density values and total voltage harmonic distortions were examined. Additionally, the cogging torque magnitudes have been analyzed. The generators were loaded with nominal loads, and the time-dependent waveforms of phase voltages were obtained. By subjecting the obtained voltages to Fourier analysis, their harmonic spectrum was created. Finally, by considering the amount of active material used for the designs, their costs were compared.

In this study, it was aimed to carry out the design, electromagnetic analysis and noise-vibration analysis of a 3 phase, high efficient surface-mounted permanent magnet motor with a power level of 7.5kW and 1500rpm speed. Using basic analytical formulas initial design geometry of motor was obtained. This first design geometry was investigated in detail by electromagnetic analyzes. In these electromagnetic analyzes, cogging torque, torque ripple, losses and efficiency parameters have been investigated. Then, modal and harmonic analyzes were carried out in order to interpret the effect of radial harmonic forces, obtained from electromagnetic analyzes, on the stator teeth on the noise and vibration parameters of the motor. According to analysis result of initial designed motor, it was aimed to reduce cogging torque, torque ripple, efficiency, noise and vibration parameters. It is thought that the improvement studies to be perform in the cogging torque will also have a positive effect on the torque ripple and vibration on the motor. By optimizing studies performed magnet and lamination geometry, new motor geometry has been obtained. Electromagnetic, modal, harmonic analyzes were made this new motor geometry. Analysis results of the new design and the first design were studied comparatively.

A three-phase T-type converter topology proposes for wind turbine based on doubly fed induction generator (DFIG). The proposed converter consists of only twelve power switches without flying capacitors or any clamping diodes. The proposed system is implemented to grid side converter of wind turbine. Fuzzy logic controllers are more widely used in wind turbines compared to traditional control systems. Fuzzy logic PI controller has been applied to T-type and the conventional neutral-point clamped (NPC) converters control circuits. Total harmonic distortion (THD) value of current of presented system is measured as 1.76%. Also, DC-link voltage utilization can be maintained. Comparisons are conducted with T- type converter and a 3L-NPC) method under same operation conditions. The proposed scheme has been carried out to verify in simulation results.

Permanent magnet synchronous generator is one of the generator types used in electrical energy production. In this study, a 1.5 kW inner rotor, surface located permanent magnet synchronous generator is used as a reference. The computer model of this generator has been prepared using Maxwell Rmxprt software. Rmxprt analysis of the generator has been performed and results were obtained for no-load and nominal load operating conditions. Parameters such as cogging torque which is an important parameter especially for permanent magnet synchronous generators used in wind turbines and efficiency were examined. The effects of changing in magnetic circuit as the permanent magnet pole arc to pole pitch ratio, magnet thickness and magnet material parameters on the generator performance were analyzed comparatively.

This study includes an optimization of the input filter for three-phase matrix converters. An input filter effects on the power factor while improving the Total Harmonic Distortion (THD) of the input current. Unity power factor being one of the most important advantages of matrix converters will be eliminated if this is not taken into consideration. For this reason, an optimization was used by taking both parameters into consideration in this study. A Particle Swarm Optimization (PSO) algorithm was used in order to reduce the THD of the input current about 3% with nearly unit power factor as 0.985. The first of the optimization objective functions is to decrease the THD of the input current, and the second is to increase the power factor. The matrix converter was used for a constant frequency and modulation by using the switching strategy of Venturini Method and feeds an RL load. The optimized input filter was analyzed in detail in MATLAB/SimPowerSystems environment and examined in the results. Additionally, FFT spectra of the input and output waveforms are given in the results. Thus, the most suitable input filter was obtained for this system.

A positive zero in the transfer function of a process causes an initial response in opposite to the final steady-state. This characteristic is known as inverse response and makes the control more challenging. In the literature, usually, well known tree term controllers, that is, Proportional-Integral-Derivative (PID) controllers, are used to control such processes. In this paper, simple analytical expressions have been derived to find optimum tuning parameters of I-PD controllers to control open loop stable processes with time delay and a positive zero. Time weighted versions of Integral of Squared Error (ISE) criterion, namely ISTE, IST2E and IST3E criteria, which have been proved to be resulting in quite satisfactory closed loop responses, have been used to derive optimum tuning rules. Effectiveness of obtained tuning rules has been shown by simulation examples.

In this study, an open source network based three axis motion control system has been designed and implemented to be used within motion control courses at engineering and technical branches for applicational studies. This system has been developed by using open source code and suitable physical structure for engineering studies. This experimental set has been evaluated by 107 students in related courses which are electrical machines and servo systems. Students have conducted various experiments by using single, two and three axes respectively. These students have been subjected to a Learner Satisfaction Survey which focuses on cognitive, affective and psychomotor extend of experimental studies in the laboratory with the designed motion control system. It has been observed from the results of this survey that learner-centered approach with the experimental set contribute in learning process positively.

Among all the control methods developed for Induction Motor (IM) drivers, the hysteresis controller based Direct Torque Control (DTC) method has an important place. This control method does not require other rotor and stator parameters except the stator resistance and does not require position or velocity sensors. However, there are some disadvantages of the DTC method, such as high torque, flux and current ripples. In this study, in order to reduce the high torque ripples occurring in an induction motor that is controlled by the hysteresis controller based conventional DTC method, a simple and effective Sugeno type Neuro-Fuzzy Torque Controller (NFTC) is proposed. This proposed controller is used instead of hysteresis controller. An experimental setup consisting of 1.1 kW induction motor, current and voltage measurement, DS1103 control card and two-level voltage source inverter was installed. To evaluate the performance of the proposed controller structure, various experimental studies were performed. Results obtained from the proposed NFTC based structure and conventional hysteresis controller based DTC structures are given comparatively. By the obtained experimental results, it was confirmed that the proposed NFTC-based controller structure considerably reduced flux and torque ripples in the motor.

This study presents a Dormand-Prince-based hybrid chaotic True Random Number Generator Design (TRNG) that can be used for secure communication and cryptographic applications on Field Programmable Gate Array (FPGA). In this design, a chaotic oscillator unit has been implemented with an FPGA-based Sprott-Jafari chaotic oscillator model suitable with IQ-Math fixed point number and IEEE 754-1985 floating point number standards. Random numbers have been produced with the quantization of the results generated by the chaotic oscillator. XOR has been performed with FPGA-based ring oscillator structure on the post-processing unit so as to enhance the randomness. The differential equation of the chaotic system used in the TRNG design was modelled using Dormand-Prince numerical algorithm method. The design on FPGA has been realized in two separate number formats including 32-bit (16I16Q) IQ-Math fixed point number standard and 32-bit IEEE 754-1985 floating point number standard. The realized design has been coded in VHDL, a hardware description language, and the Xilinx ISE 14.7 program has been used for the system design. The TRNG design has been synthesized and tested for the Virtex6 (XC6VLX240T-1FF1156) FPGA chip. The maximum operating frequencies of the TRNG in 32-bit IQ-Math fixed point number standard and 32-bit IEEE 754-1985 floating point number standard reach 344.585 MHz and 316 MHz, respectively. The throughputs of the TRNG in 32-bit IQ-Math fixed point number standard and 32-bit IEEE 754-1985 floating point number standard have been obtained as 344 Mbit/s and 316 Mbit/s, respectively. 1 Mbit sequence has been generated by using TRNG system. Randomness analysis of the generated numbers has been performed in accordance with the NIST 800-22 tests and the generated numbers have successfully passed all of the tests.

Establishing separated markets for capacity, energy, and ancillary services (AS) is one of the key steps to liberalize electricity sector and realize electricity markets. This study aims at eliciting AS tariffs from unified capacity and energy tariffs through a cost-based approach. In the proposed framework, maintaining annual revenue requirements of the power plants are considered as the main objective while separating the AS tariff from unified tariffs. The conducted study considers two types of unified tariffs, i.e. capacity and energy tariffs, and offers proper AS eliciting scheme for each type of unified tariffs. The main challenges addressed here are: 1) incentivizing\penalizing AS provision more\less than scheduled amount which is tackled through an incentive factor, and 2) preventing overall tariff increment (customer tariff) after eliciting AS tariff which is addressed by applying fixing constraint to the overall tariff at before and after AS tariff eliciting conditions. Last but not the least, AS trade between adjacent utilities and calculating the benefits from this trade are addressed. The effectiveness of the proposed methodology is assured through numerical investigations.

In this study, a test device is developed to measure the capacities and performances of high capacity battery banks and to detect broken cells. Through this test device, the instant capacity of the battery banks is measured. Based on the data obtained, both quantitative information about the health of the battery bank is provided and it is determined whether the battery bank will meet the need according to its intended use. In addition, battery banks can be divided into small groups and their measurements can be made so that broken cells can be detected.

Amyotrophic lateral sclerosis (ALS) disease, also known as motor neuron disease, is a disease resulting from loss of motor nerve cells in the spinal cord and brain stem region at central nervous system. Researchers can’t find the reason of ALS for certain, however there are a wide variety of risk factors in respect of this disease. This disease has more than one risk factor. Researchers believe that it is resulted from a virus which leads to abnormality in immune system, spoils the structure of DNA and functioning of enzyme system, exhibiting neurotoxic properties. The signals coming to a single arm or leg muscle from upper and lower motor neurons are highly determinative in diagnosis of the disease, although there is not a specific test for diagnosing the ALS disease for certain. Doctors still conduct many tests even though the main symptoms of ALS are the signals coming to muscles. The developments related to gait analysis are used an auxiliary factor in diagnosis and analysis of ALS diseases. In this study, gait signals from control individuals and ALS diseases have been recorded by means of sensors sensitive to the strength under the foot. These signals’ time-amplitude, amplitude spectrum, phase spectrum, average value and variance changes have been analysed. As a result of these inspections, differences of ALS signals from control signals have been identified.

Permutation and substitution processes of an image are most widely used in image encryption algorithms as they are thought to increase system security in cryptography. Permutation is the first process that all pixel positions in an image are shuffled in specific order or randomly in order to break strong correlation between pixels. Secondly, substitution is used to change pixel values by mixing a secret key in the permutated image. In an ordinary image, adjacent pixels have close values so they have strong correlation and this correlation needs to be broken effectively before encryption. The degree to which this process is performed, directly affects the overall system security. In this paper, performance evaluations for Group (GRP) and Arnold’s Cat Map (ACM) method are analyzed through some numerical results and their performances are compared to figure out which one is better. Experimental results consist of numerical and visual results determined in Matlab R2015a.

The electromagnetic behavior of the inductors used as passive circuit elements directly affects the electrical and mechanical performance of the power electronics circuits. In general, when using inductor core structures with or without airgap in the classical design process, the dynamic effects of the inductance value are not considered in the design stage. However, the inductance value may change during the operation of the circuit due to electrical and magnetic parameters of the inductor, and this change is called roll-off value of the inductance. In this study, the roll-off value has been measured graphically and numerically based on mechanical parameters (such as air-gap length) and electrical parameters (such as winding turns and DC current amplitude) for an air-gapped ferrite E core designed with FEA software. Thus, not only the inductance value calculated in the design stage but also the roll-off value during the operation of the circuit has been reported with the parametric simulation studies.

In today's energy systems, many equipment operate with Direct Current (DC) voltage. However, it is not always possible to obtain the voltage level required for the operation of these equipment from standard power supplies. For this reason DC-DC converters are used to achieve the desired voltage values for equipment with different DC voltage levels. These converters are divided into three general categories, named Buck, Boost and Buck-Boost. The most preferred converter is the Cuk converter with low output ripple voltage, which can operate in both buck and boost modes. In this study, a detailed analysis of the Cuk converter, which is frequently used in Photovoltaic (PV) Panels was performed and different control methods of the output voltage were proposed. While performing this analysis, the dynamic model of the Cuk converter was created in which, Proportional-Integral (PI) and Fuzzy Logic (FL) are used to control the output voltage of the Cuk converter. The performances of both controllers were compared with respect to performance parameters such as steady state error, settling time and rise time. When the results obtained were evaluated as a whole, it was observed that FLC achieved the desired reference with less rise and settling time. In this study, modeling and controller applications of Cuk converter are realized by using MATLAB / SIMULINK program

Modeling of unmanned aerial vehicle (UAV) with system identification is very important in terms of its model-based effective control. The modeling of UAV is required for aircraft crashes, analyzing autonomous aircrafts, preventing external disturbances, pre-flight analysis. However, since UAV has nonlinear inherent dynamics including inherent chaoticity and fractality, it becomes difficult to obtain a mathematical model under external disturbance. In this study, some of the inherent nonlinear dynamics of UAV are linearized and the model of UAV is obtained by system identification approaches under external disturbance. The linearized lateral dynamics of a fixed wing UAV is used in this study. Further, the flight motion equations applied to fixed wing UAV have been utilized for obtaining the coefficients of lateral model for straight and level flight. The roll angles are calculated using transfer functions for aileron, rudder and deflections inputs. The autoregressive exogenous (ARX), autoregressive moving average with exogenous (ARMAX) and output error (OE) parametric system identification approaches are performed to estimate UAV lateral dynamic system response as using empirical input-output data sets. The accuracy of parametric model estimation and model degrees are compared for different external disturbance effects.

The electrical activity that occurs during the communication of neurons is recorded by a method called electroencephalography. Brain computer interfaces utilize various electrophysiological sources obtained from different regions of the brain. The electrophysiological source used in this study is the electrical activity seen in the occipital lobes as a result of visual stimuli that flicker at certain frequencies, and is called steady-state visual evoked potential. The main goal in this work is not to try to improve the classification performance but to investigate the effects of different digital filtering algorithms on classification performance. The effects of the high pass and low pass filtering on the classification performance in steady-state visual evoked potential based brain computer interfaces are investigated. As a result of this study, no significant change in the classification performances of designs with only high pass filtering, and high and low pass filtering, has been observed. In addition, it has been observed that only the designs include a high-pass filter implementation give better classification performance in many cases. Consequently, it is concluded that low-pass filtering in steady-state visual evoked potential based brain-computer interfaces does not provide the desired contribution to classification performance.

In this study, a six-leg spider robot (hexapod) was designed and controlled for greenhouse, search and rescue operations and military applications. Solidworks design program was used in the design stage and Matlab Simulink program was used in the control stage of the robot. In the study, a motion trajectory was determined by interpolation technique for the robot and it was aimed to move on this trajectory. Proportional-Integral-Differential (PID) controller and Fuzzy Logic Controller (FLC) were used for the trajectory control of the robot. The robot walk movements were applied in both control types with motion on flat ground, motion on inclined ground, motion at different weights and different friction coefficients. In the analysis studies, the total weight of the robot was taken into consideration as 4kg. As a result of the analysis studies, it was observed that this robot, which was designed and analyzed, followed a trajectory defined by a mass of 4 kg with an error value of 1 mm on average. During the trajectory tracking, it was found that the Fuzzy controller performs better than the PID controller at the turning points of the reference trajectory curve of the robot.

While, researchers work to make the systems operate economically and reduce operational cost, in this study, we work to reduce the fuel costs to make the power station running economically as much as possible by utilizing the Economic Power Dispatch (EPD) and the optimization algorithms. The economic power dispatch (EPD) is an integral part of the power system, The major roles and the purpose of its use are for achieving a reliable and efficient operation out of power system generation networks, and this operation should be obtained by minimizing the generator fuel cost. Getting optimal solutions to EPD problem requires efficient optimization algorithms. Novel Bat Algorithm (NBA) is one of the most recent methods and it has already proven its efficiency and reliability for solving the EPD problem. This paper proposes Novel Bat Algorithm (NBA) in order to solve the EPD problem based on the large scale power system. The NBA has proved its efficiency and it gave a perfect performance for small-scale systems compared with the original Bat algorithm (BA), because of considering the Doppler Effect and assumed that bat can move between various habitats. The study of the EPD for large-scale power systems is more important than study it for small ones, because all power systems in countries are considered large networks. This is why all modern studies focus on the study of EPD for large systems. To test the performance of NBA during small and large scale power system, we have applied it to many systems, including 3- thermal units, 6-thermal units, 31-Iraqi thermal units and IEEE 40-thermal units respectively, with transmission losses and generator limits, and we have made a comparison of the obtained results of NBA with other optimization methods. The Iraqi thermal units have been utilized as a new data.

The increasing consumption of energy and the_x000D_ greenhouse-gas emissions are challenges in the transport and_x000D_ building sectors. Compared to the other transportation types_x000D_ public railway transport systems are the most energy efficient_x000D_ regarding carbon footprint. Modern urban railway public_x000D_ transport systems have the significant advantages of large_x000D_ passenger capacity, punctuality, safety, going green in the urban_x000D_ environment and reducing carbon footprint, is a scientific_x000D_ consensus. However, the energy demand for railways are_x000D_ increasing in proportion to passenger load, require implementing_x000D_ innovative solutions for optimizing the energy consumption and_x000D_ reducing carbon emission. Leadership in Energy and_x000D_ Environmental Design (LEED) is a building rating system used_x000D_ worldwide. The credit categories of the LEED consist of seven_x000D_ different topics from the Energy and Atmosphere to Materials_x000D_ and Resources. In this study, the LEED certification application_x000D_ to railway station and facilities will be discussed mainly energy_x000D_ efficiency criteria.

Exhibiting a high economic growth rate inrecent years, energy demand has increased rapidly in Turkey. Despite having agreat potential in terms of renewable energy sources, Turkey has not utilizedthis potential sufficiently to meet this demand. However, among variousrenewable energy sources, solar energy stands out in terms of investments andincentives in Turkey. In this study, progress and outlook of photovoltaicsystems in Turkey are reviewed considering the potential, the incentives andthe investments. In this context, ratio of the Photovoltaic Solar Power Plantswithin both overall installed power and the total generated energy over theyears is investigated geopolitically. Ongoing and planned investments forPhotovoltaic Solar Power Plants and the incentives provided by the governmentare reviewed by taking into consideration the geographical regions of thecountry. It is observed that the installed power capacity of active solarphotovoltaic power plants increases by more than four times compared to theprevious year, as of the end of 2017, owing to incentives and investments.Solar energy power capacity is expected to contribute significantly to thetotal installed power capacity over the next few years.

Lorenz equations are commonly used in chaos education and studies. Simulation programs can be used to produce solutions of Lorenz equations and to examine its chaotic waveforms. However, sometimes a chaotic signal source can be needed. Such a circuit can be made using either analog or digital circuit components. Recently, a microcontroller-based circuit is suggested to obtain chaotic waveforms of Lorenz equations however only simulations are used to show proof of concept. Such circuit needs experimental verification. In this paper, implementation and experimental verification of the microcontroller-based circuit which solves Lorenz equations in real time and produces its chaotic waveforms are presented. Runge-Kutta method is used to solve the equation system. By using Proteus, microcontroller-based chaotic circuit is simulated and designed. Presented design has been implemented using an Arduino Mega 2560 R3 microcontroller. The microcontroller sends the chaotic signals to the outputs of the circuit using digital-to-analog converters. The waveforms acquired experimentally from the implemented circuit matches well with those obtained from Proteus simulations.

This article proposes three novel models of photonic crystal fiber (PCF) based dual liquid sensor. The performances of Z-Model, X-Model and V-Model structures have been evaluated by applying the well-known full vectorial finite element method (FV-FEM) where boundaries are defined with perfectly matched layers (PMLs). The birefringence and the sensitivity levels of proposed sensors have been studied where core holes are filled with water (n=1.33) and ethanol (n= 1.354). Our numerical results have shown that X-Model and Z-Model of A-Type sensor is an ideal structure for water and ethanol sensing, respectively.

To ensure energy continuity in the interconnected power systems, production and consumption amounts should be in balance, and that can be possible by providing constant voltage and frequency. Otherwise, undesirable large dynamic oscillations, voltage collapse may occur, and the quality of the electrical energy deteriorates. In this study, the power system of the Denizli Region in the Western Mediterranean Region is modeled using realistic national data. The simulation study is carried out to obtain the voltages, active and reactive powers of buses in the case of no-fault and fault occurrence. Using FACTS (Flexible Alternating Current Transmission Systems) technology such as SVC and STATCOM, the power systems can be controlled, and the carrying capacities can be improved within specified limits. Facts devices are capable of producing and consuming reactive power depending on immediate needs, safe and operating flexibility, and having a high reaction time in the simulation studies. The maximum load limits are increased, and the control of the power system is facilitated. STATCOM provides 31.09 % more achievement with respect to SVC device at energy production and consumption rates for the modeled pilot region. The reliability of the power system has been increased against a voltage collapse, thanks to the SVC and STATCOM controllers. Furthermore, the voltage stability of the generator is also raised, and correspondingly the capacity of the power system enhances. The results are compared to the existing system, and the obtained improvements may be assessed for the enhancement of the interconnected network grid of Turkey.

Magnetic field has a huge potential of providing non-destructive and highly efficient detection platforms in biosensing field. It provides a low intrinsic background in biological systems since those systems have no comparable biological signal. Hall devices are currently dominating the market of the magnetic sensors due to several advantages such as allowing miniaturization, being compatible with electronics integration, cheaper fabrication and room temperature operation with high linearity. It is important to construct a suitable front-end circuitry in order to be able to achieve a portable and label-free working Hall biosensor. This paper presents the construction of an electronic circuitry that is required for actuating Hall based biosensors and obtaining the output since there are undesired effects which are causing less sensitive or less accurate results. The paper takes a closer look at those effects and presents the solution to the problem by introducing a developed circuitry on a designed printed circuit board along with the promising results it has achieved.

LabVIEW is a software development platform that can be programmed with a graphical interface and so, measurement and instrumentation problems are used to deliver a solution. In the sensor applications, it is very important to calculate the main electronic parameters of the produced samples and it takes a lot of time to calculate these parameters and evaluate results. Therefore, LabVIEW based a software system was developed to minimize the time spent. In this way, it was used to make the analysis as fast as possible. This study aimed to calculate quickly the obtained results from the measurement system. For this purpose, AuPd/n-GaAs Schottky Junction Structure (SJS) was produced by using RF and DC sputtering techniques to investigate on electronic parameters of SJS. The forward and reverse current-voltage (I-V) of SJS at ±3V were measured at room temperature (295 K). By using thermionic emission (TE) theory, Ohm’s law, Cheung and Cheung’s function and modified Norde’s function, the electronics parameters such as the series resistance (Rs), the shunt resistance (Rsh), the barrier height (ΦB0) and the ideality factor (n) were calculated and graphics, which were drawn according to these models, via the developed software platform.

With the increasing energy demand, the growing capacity of renewable energy sources and the impact of developing competition, it is desirable to manage the market with appropriate investments along with the electricity market and optimum load distribution. In line with this demand, supply security and energy quality play an important role day by day. This includes the production capacity and the long-term security of the system, reflecting the system's ability to stand in unexpected events and sudden load changes. The demand side seems to have insufficient support to the market for new capacity planning to ensure this coverage. This problem can be solved by producing additional capacity. Basically, it is aimed to reduce investment risk for production companies and / or investors and to provide higher supply security and lower price fluctuations to consumers. The concern of not investing in electricity generation capacity to meet the maximum load level has led to investments in capacity utilization in the form of capacity mechanisms of developed and developing states. In this study, an academic analysis of the capacity mechanism of the renewable energy resources and the capacity analysis of the capacity mechanism were made and expert opinions were presented, the latest developments in the energy market were examined and the reliability solutions that could be appropriate to the national electricity market were proposed

A noiseless image is desirable for many applications. However, this is not possible. Generally, wavelet-based methods are used to noise reduction. However, due to insufficient performance of wavelet transforms (WT) on images, different multi-resolution analysis methods have been proposed. In this study, one of them is Contourlet Transform (CT) and the Translation-Invariant Contourlet Transform (TICT) which is an improved version of CT is compared using different noises. The fundus images are taken from the DRIVE dataset and benchmark images are used. Peak Signal-to-Noise Ratio (PSNR), Mean Squared Error (MSE), Mean Structural Similarity (MSSIM) and Feature Similarity Index (FSIM) are used as comparison criteria. The results showed that TICT is better in Gaussian noisy images.

Cryogenic electronics has grown in its widespread use for various technological applications. Particularly, CMOS devices and circuits are more frequently used in such systems due to their dominance in the electronics industry. At cryogenic temperatures, characteristics of CMOS devices vary, which should be characterized with measurements. In this paper, the changes in the electronic behavior of a low threshold voltage (VTH) n-channel MOSFET (nMOSFET) are captured experimentally. The results are then compared with the measurements of a regular nMOSFET having the same channel width and length. It is shown that although the VTH increase of both transistors is at the same amount, this value corresponds to a more significant percentage of the nominal threshold voltage for the low VTH nMOSFET.

In this study, a CAD system is recommended for the classification of mammography images as normal-abnormal and benign malignant. The proposed system consists of the feature extraction, determination of the distinguishing capabilities of the features and selection of the features using by dynamic thresholding according to the determined distinguishing capabilities. It uses the contourlet transform to extract features. The distinguishing capabilities of the features are determined by using t-test statistics, and the thresholds are applied to those values to select effective ones. Classification is performed using support vector machine algorithm for every iteration with each thresholding step. Among the results of the iteration performed, the optimum data that have the best performance, which is they have maximum accuracy result with the minimum number of features, is selected as the optimum value. To evaluate the optimal feature set, classification carries out using the feature set applying 5-fold cross-validation. According to the results, the proposed method can be accepted as a successful CAD system.

In this study, the effects of antenna types and output powers on charging times of RF energy harvesting circuit were measured and analyzed in detail. A measurement system which consisting of a signal generator, an RF energy harvesting circuit, antennas and other devices was installed for receiving the measurement samples. According to the measurement results, the shortest charging time was obtained as 0.58 s at a distance of 20 cm, when 6.1 dBi antenna was connected to the RF energy harvesting circuit and the output power of the signal generator was set to 17 dBm. In addition to that, the longest charging time was evaluated as 25.01 s at a distance of 60 cm, when 1 dBi antenna was connected to the RF energy harvesting circuit and the output power of the signal generator was adjust to 14 dBm. As a result, it was determined that increasing of antenna gains and output powers and shortening of distances between signal generator and RF energy harvesting circuit decreased the charging times of the RF energy harvesting circuit in this study.

Solar energy is a clean energy and it is increasingly being used all over the world. In this study, a water pump drive has been designed with a switched reluctance motor (SRM) to be powered by a photovoltaic energy source (PV). A boost converter has been used to increase the voltage of the PV source. The mathematical model of the system has been composed in the Matlab/Simulink and simulation results have been obtained. Output voltage of the boost converter has been controlled by using a PID controller at 50 kHz switching frequency. A centrifugal pump has been used as the water pump. In the control of boost converter, an eight bit PIC16F877A microcontroller has been used. The electrical energy obtained by PV panels has been stored in batteries. Battery charge testers have been used in order to control the battery charge level. The speed and current control of SRM has been done by using DS1103 Ace kit. The value of the current has been perceived by using hall sensors and transferred to the digital signal processor by using an analog to digital converter. The accuracy of simulation results has been proved by experimental results.

The available number of protein sequences rapidly increased with the development of new sequencing techniques. This in turn led to an urgent need for the development of new computational methods utilizing these data for the solution of different biological problems. One of these problems is the comparison of protein sequences from different species to reveal their evolutional relationship. Recently, several alignment-free methods proposed for this purpose. Here in this study, we also proposed an alignment-free method for the same purpose. Different from the existing methods, the proposed method not only allows for a pairwise comparison of two protein sequences, but also it allows for a bulk comparison of multiple protein sequences simultaneously. Computational results performed on gold-standard datasets showed that, bulk comparison of multiple sequences is much faster than its pairwise counterpart and the proposed method achieves a performance which is quite competitive with the state-of-the-art alignment-based method, ClustalW.0000-0003-4810-1970