Combined Feature Compression Encoding In Image Retrieval,
2019
TÜBİTAK
Combined Feature Compression Encoding In Image Retrieval, Lu Huo, Leijie Zhang
Turkish Journal of Electrical Engineering and Computer Sciences
Recently, features extracted by convolutional neural networks (CNNs) are popularly used for image retrieval. In CNN representation, high-level features are usually chosen to represent the images in coarse-grained datasets, while mid-level features are successfully applied to describe the images for fine-grained datasets. In this paper, we combine these different levels of features as a joint feature to propose a robust representation that is suitable for both coarse-grained and fine-grained image retrieval datasets. In addition, in order to solve the problem that the efficiency of image retrieval is influenced by the dimensionality of indexing, a unified subspace learning model named spectral …
A Hybrid Of Tropical-Singular Value Decomposition Method For Salt And Pepper Noise Removal,
2019
TÜBİTAK
A Hybrid Of Tropical-Singular Value Decomposition Method For Salt And Pepper Noise Removal, Achmad Abdurrazzaq, Ismail Mohd, Ahmad Kadri Junoh, Zainab Yahya
Turkish Journal of Electrical Engineering and Computer Sciences
The unknown information contained in an image that causes the change of information in the image is called noise. In this paper, we propose a new method for removing salt and pepper noise by using singular value decomposition and the concept of tropical algebra operations. To determine the performance of the proposed method, 20 test images are used as samples. Then three different image quality assessments are used: peak signal-to-noise ratio (PSNR), structural similarity (SSIM), and image enhancement factor (IEF). In addition, six different filtering methods, i.e. MF, DWMF, PSMF, MDBUTM, NAFSM, and BPDF, are used to compare the performance …
A Novel Algorithm For Frequency Extraction Of Abs Signals By Using Dtdnns,
2019
TÜBİTAK
A Novel Algorithm For Frequency Extraction Of Abs Signals By Using Dtdnns, Mohammad Ali Shafieian, Hamed Banizaman, Shahrzad Sedaghat
Turkish Journal of Electrical Engineering and Computer Sciences
Intelligent transportations system (ITSs) have emerged to increase safety and convenience of people in vehicles. In an ITS, communication devices in the vehicle or along the streets send the information gathered from the vehicle to information management centers as well as sending processed information to the vehicle. Furthermore, it is necessary to locate the exact location of the vehicle on a digital map in order to navigate the vehicle precisely in control and navigation systems. One of the technologies for this purpose is the antilock brake system (ABS), which can avoid accidents effectively and can also be utilized to determine …
Channel Estimation For Ofdm-Im Systems,
2019
TÜBİTAK
Channel Estimation For Ofdm-Im Systems, Yusuf Acar, Sultan Aldirmaz Çolak, Ertuğrul Başar
Turkish Journal of Electrical Engineering and Computer Sciences
Orthogonal frequency division multiplexing with index modulation (OFDM-IM) has been recently proposed to increase the spectral efficiency and improve the error performance of multicarrier communication systems. However, all the OFDM-IM systems assume that the perfect channel state information is available at the receiver. Nevertheless, channel estimation is a challenging problem in practical wireless communication systems for coherent detection at the receiver. In this paper, a novel method based on the pilot symbol-aided channel estimation technique is proposed and evaluated for OFDM-IM systems. Pilot symbols, which are placed equidistantly, allow the regeneration of the response of the channel so that pilot …
Ingan/Gan Tandem Solar Cell Parameter Estimation: A Comparative Stud,
2019
TÜBİTAK
Ingan/Gan Tandem Solar Cell Parameter Estimation: A Comparative Stud, Abdelmoumene Benayad, Smail Berrah
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, two hybrid estimation approaches, hybrid genetic algorithm (TR-GA) and hybrid particle swarm optimization (TR-PSO), are used to estimate single-diode model InGaN/GaN solar cell parameters from J?V experimental data under AM0 illumination. These parameters are photocurrent density ($J_{ph}$), reverse saturation current density ($J_{s}$), ideality factor ($A$), series resistance ($R_{s}$), and shunt resistance ($R_{sh}$). The trust region (TR) method used in both approaches provides the initial conditions and helps to avoid the problem of premature convergence (due to local minimum). Simulation results based on the minimization of the mean square error between experimental and theoretical J-V characteristics show that …
A New Failure Protection Algorithm For Circuit Breakers Using The Power Loss Of Switching Arc Incidents,
2019
TÜBİTAK
A New Failure Protection Algorithm For Circuit Breakers Using The Power Loss Of Switching Arc Incidents, Behnam Feizifar, Ömer Usta
Turkish Journal of Electrical Engineering and Computer Sciences
The principal function of circuit breakers (CBs) is to isolate a portion of the power network from the rest of it in a timely manner following an opening command. Any failure in the opening operation of CBs, especially following a fault condition, will almost certainly result in a catastrophic event. Therefore, the issue of failure detection of CBs is essential and has a vital role in power system protection. This paper presents a novel power-based algorithm for failure detection of CBs. The power loss of CBs due to an arcing event increases as the arcing time gets longer. The arcing …
On Parameter Adjustment Of The Fuzzy Neighborhood-Based Clustering Algorithms,
2019
TÜBİTAK
On Parameter Adjustment Of The Fuzzy Neighborhood-Based Clustering Algorithms, Fatma Günseli̇ Yaşar, Gözde Ulutagay, Semi̇h Utku, Efendi̇ Nasi̇boğlu
Turkish Journal of Electrical Engineering and Computer Sciences
Day by day huge amounts data are produced, and evaluation of these data becomes more difficult. The data obtained should provide meaningful, correct, and accurate information. Therefore, all data must be separated into clusters correctly, and the right information from these clusters must be obtained. Having the correct clusters depends on the clustering algorithm that is used. There are many clustering algorithms. The density-based methods are very important among the groups of clustering methods, as they can find arbitrary shapes. An advanced model of the density-based spatial clustering of applications with noise (DBSCAN) algorithm, called fuzzy neighborhood DBSCAN Gaussian means …
Evolutionary Approaches For Weight Optimization In Collaborative Filtering-Based Recommender Systems,
2019
TÜBİTAK
Evolutionary Approaches For Weight Optimization In Collaborative Filtering-Based Recommender Systems, Sevgi̇ Yi̇ği̇t Sert, Yilmaz Ar, Gazi̇ Erkan Bostanci
Turkish Journal of Electrical Engineering and Computer Sciences
Collaborative filtering is one of the widely adopted approaches in recommender systems used for e-commerce applications, stating that users having similar tastes will have similar preferences in the future. The literature presents a number of similarity metrics such as the extended Jaccard coefficient to quantify these preference similarities. This paper aims to improve prediction accuracy by optimizing the similarity values computed using these metrics by adopting two biologically inspired approaches, namely artificial bee colony and genetic algorithms, with a bottom-up approach, suggesting that any improvement on a single-user basis will reflect on the overall prediction accuracy. Detailed statistical analysis was …
Particle Swarm Optimization-Based Collision Avoidance,
2019
TÜBİTAK
Particle Swarm Optimization-Based Collision Avoidance, Ti̇mur İnan, Ahmet Fevzi̇ Baba
Turkish Journal of Electrical Engineering and Computer Sciences
Collision risk assessment and collision avoidance of vessels have always been an important topic in ocean engineering. Decision support systems are increasingly becoming the focus of many studies in the maritime industry today as vessel accidents are often caused by human error. This study proposes an anticollision decision support system that can determine surrounding obstacles by using the information received from radar systems, obtain the position and speed of obstacles within a certain time period, and suggest possible routes to prevent collisions. In this study we use a neural network to predict the subsequent positions of surrounding vessels, a fuzzy …
Automatic Fault Isolation And Restoration Of Distribution System Using Jade Based Multi-Agents,
2019
TÜBİTAK
Automatic Fault Isolation And Restoration Of Distribution System Using Jade Based Multi-Agents, Indhumathi Chellaswamy, Joy Vasantha Rani Sp
Turkish Journal of Electrical Engineering and Computer Sciences
This paper proposes a solution for automatic service restoration along with automatic fault location and isolation of the faulty sections in feeder in a power distribution system. A Java agent development environment-based multiagent system (MAS) is proposed to solve the problem of automatic service restoration in smart grid distribution systems. The agent-based solution development is discussed in detail and the MAS application to solve power restoration problem is elaborated in this paper. A study is done on a modified IEEE 33 bus system and the solution is implemented in the Velachery substation of the Tamilnadu electricity board. The results prove …
Assessing Wind Energy Potential Using Finite Mixture Distributions,
2019
TÜBİTAK
Assessing Wind Energy Potential Using Finite Mixture Distributions, Meli̇h Burak Koca, Muhammet Burak Kiliç, Yusuf Şahi̇n
Turkish Journal of Electrical Engineering and Computer Sciences
Wind has become a popular renewable energy resource in the last two decades. Wind speed modeling is a crucial task for investors to estimate the energy potential of a region. The aim of this paper was to compare the popular unimodal wind speed distributions with their two-component mixture forms. Accordingly, Weibull, gamma, normal, lognormal distributions, and their two-component mixture forms; two-component mixture Weibull, two-component mixture gamma, two-component mixture normal, and two-component mixture lognormal distributions were employed to model wind speed datasets obtained from Belen Wind Power Plant and G??k?ßeada Meteorological Station. This paper also provides the comparison of gradient-based and …
Design Of Area-Efficient Iir Filter Using Fppe,
2019
TÜBİTAK
Design Of Area-Efficient Iir Filter Using Fppe, Ramyarani Nallathambi, Subbiah Veerana, Deepa Prabhakaran
Turkish Journal of Electrical Engineering and Computer Sciences
Floating point arithmetic circuits provide wide dynamic range and high precision, and they are widely used in scientific computing and signal processing applications, but the complexity increases in hardware implementations of floating point units. In VLSI design architecture, many applications suffer in size of the components used in logical operations. The aim of reducing architecture is to gain reduction in power loss and also in area, but the reduction in size of the components leads to an increase in delay and memory. Hence, to overcome these limitations and to optimize the area, a novel design of floating point processing element …
Web Personalization Issues In Big Data And Semantic Web: Challenges Andopportunities,
2019
TÜBİTAK
Web Personalization Issues In Big Data And Semantic Web: Challenges Andopportunities, Bujar Raufi, Florije Ismaili, Jaumin Ajdari, Xhemal Zenuni
Turkish Journal of Electrical Engineering and Computer Sciences
Web personalization is a process that utilizes a set of methods, techniques, and actions for adapting the linking structure of an information space or its content or both to user interaction preferences. The aim of personalization is to enhance the user experience by retrieving relevant resources and presenting them in a meaningful fashion. The advent of big data introduced new challenges that locate user modeling and personalization community in a new research setting. In this paper, we introduce the research challenges related to Web personalization analyzed in the context of big data and the Semantic Web. This paper also introduces …
Design Of A Range-Segmented Cmos Current-Mode Exponential Circuit,
2019
TÜBİTAK
Design Of A Range-Segmented Cmos Current-Mode Exponential Circuit, Chih-Jen Cheng, Kuo-Jen Lin, Jwu-E Chen
Turkish Journal of Electrical Engineering and Computer Sciences
A CMOS current-mode exponential circuit is designed by plugging candidate circuits into a Taylor's approximation circuit to make a multiple-segment circuit. The selection of candidate circuits is dependent on a large linearity range in each segment. The proposed range-segmented circuit is different from all segments constructed only by quadratic circuits or only by linear circuits. The proposed circuit was simulated using UMC 0.18~$\mu$m CMOS technology. The output linearity of the circuit is 56.7~dB for gain error less than 0.5~dB, and the --3~dB bandwidth of the circuit is between 69 and 150~MHz for input range from --63 to 198~$\mu$A.
A Light-Weight Solution For Blackhole Attacks In Wireless Sensor Networks,
2019
TÜBİTAK
A Light-Weight Solution For Blackhole Attacks In Wireless Sensor Networks, Bi̇lal Erman Bi̇lgi̇n, Selçuk Baktir
Turkish Journal of Electrical Engineering and Computer Sciences
Wireless sensors, which are smaller and cheaper, have started being used in many different applications. Military applications, health care and industrial monitoring, environmental applications, smart grids, and vehicular ad-hoc networks are some of the best known applications of wireless sensors. In some applications, especially military, environmental, and health care applications, it is required that the communication between sensor nodes be encrypted to achieve privacy and confidentiality. In this work, some modifications have been made to the ad-hoc on-demand distance vector routing protocol, mostly preferred in wireless sensor networks, to make data communications more reliable. The proposed routing protocol is shown …
State-Space Identification Of Switching Linear Discrete Time-Periodic Systems Withknown Scheduling Signals,
2019
TÜBİTAK
State-Space Identification Of Switching Linear Discrete Time-Periodic Systems Withknown Scheduling Signals, İsmai̇l Uyanik, Hasan Hamzaçebi̇, Mustafa Mert Ankarali
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, we propose a novel frequency domain state-space identification method for switching linear discrete time-periodic (LDTP) systems with known scheduling signals. The state-space identification problem of linear time-invariant (LTI) systems has been widely studied both in the time and frequency domains. Indeed, there have been several studies that also concentrated on state-space identification of both continuous and discrete linear time-periodic (LTP) systems. The focus in this study is the family of LDTP systems that switch among a finite set of subsystems triggered by known periodic scheduling signals. We address the state-space identification of such systems in frequency domain …
Cloud-Supported Machine Learning System For Context-Aware Adaptive M-Learning,
2019
TÜBİTAK
Cloud-Supported Machine Learning System For Context-Aware Adaptive M-Learning, Muhammad Adnan, Asad Habib, Jawad Ashraf, Shafaq Mussadiq
Turkish Journal of Electrical Engineering and Computer Sciences
It is a knotty task to amicably identify the sporadically changing real-world context information of a learner during M-learning processes. Contextual information varies greatly during the learning process. Contextual information that affects the learner during a learning process includes background knowledge, learning time, learning location, and environmental situation. The computer programming skills of learners improve rapidly if they are encouraged to solve real-world programming problems. It is important to guide learners based on their contextual information in order to maximize their learning performance. In this paper, we proposed a cloud-supported machine learning system (CSMLS), which assists learners in learning practical …
Patient Comfort Level Prediction During Transport Using Artificial Neural Network,
2019
TÜBİTAK
Patient Comfort Level Prediction During Transport Using Artificial Neural Network, Zeljko Jovanovic, Marija Blagojevic, Dragan Jankovic, Aleksandar Peulic
Turkish Journal of Electrical Engineering and Computer Sciences
Since patient comfort during transport is a matter of paramount importance, this paper aims to determine the possibilities of applying neural networks for its prediction and monitoring. Specific objectives of the research include monitoring and predicting patient transport comfort, with subjective assessment of comfort by medical personnel. An original Android application that collects signals from an accelerometer and a GPS sensor was used with the aim of achieving the research goals. The collected signals were processed and a total of twelve parameters were calculated. A multilayer perceptron was created in the proposed research. The evaluation results indicate acceptable accuracy and …
Real-Time Implementation Of Electronic Power Transformer Based On Intelligentcontroller,
2019
TÜBİTAK
Real-Time Implementation Of Electronic Power Transformer Based On Intelligentcontroller, Hakan Açikgöz, Ökkeş Fati̇h Keçeci̇oğlu, Mustafa Şekkeli̇
Turkish Journal of Electrical Engineering and Computer Sciences
Along with the rapid advances in power electronics and semiconductor technology, electronic power transformers (EPTs), which are expected to replace conventional power transformers in the future, are being developed and designed. This study presents the dynamic performance of the intelligent controller structure in the control of an EPT. The EPT structure, consisting of the input, isolation, and output stages, is designed for experimental and simulation studies. A three-phase pulse width modulation (PWM) rectifier is used to rectify the grid voltages at the input stage of EPT. The DC-bus voltage of the three-phase PWM rectifier is controlled by a neuro-fuzzy controller …
Automatic Generation Control Analysis Of Power System With Nonlinearities Andelectric Vehicle Aggregators With Time-Varying Delay Implementing A Novel Control Strategy, Nimai Charan Patel, Binod Kumar Sahu, Manoj Kumar Debnath
Turkish Journal of Electrical Engineering and Computer Sciences
Automatic generation control (AGC) also known as load frequency control plays a vital role in interconnected power system for frequency regulation. Electric vehicles (EVs) with battery as the storage device can participate in frequency regulation service. In practice, a large number of EVs are aggregated as a single unit called EV aggregator for participation in frequency regulation service in AGC system. Participation of EV aggregators in AGC system for frequency regulation will be encouraged in near future because EVs have less environmental pollution than the conventional vehicles. However, participation of EV aggregators in AGC system may introduce time delay which …
