Gated Recurrent Unit Based Demand Response For Preventing Voltage Collapse In A Distribution System,
2020
TÜBİTAK
Gated Recurrent Unit Based Demand Response For Preventing Voltage Collapse In A Distribution System, Venkateswarlu Gundu, Sishaj Pulikottil Simon, Kinattingal Sundareswaran, Srinivasa Rao Nayak Panugothu
Turkish Journal of Electrical Engineering and Computer Sciences
This paper presents the application of deep learning algorithms towards demand response management. Demand limit violation and voltage stability are the major problems associated with a secondary distribution system. These problems are solved using demand response models by day ahead scheduling loads at every 15 min interval through linear integer programming and based on short term forecasting of load (kW). A new architecture for short term load forecasting is presented namely gated recurrent unit in which statistical analysis is carried out to get the optimal architecture of the neural network model. Reliability indices such as loss of load probability (LOLP) …
Quantum Key Distribution Over Free Space Optic (Fso) Channel Using Higher Order Gaussian Beam Spatial Modes,
2020
TÜBİTAK
Quantum Key Distribution Over Free Space Optic (Fso) Channel Using Higher Order Gaussian Beam Spatial Modes, Muhammad Kamran, Dr. Muhammad Mubashir Khan, Tahir Malik, Asad Arfeen
Turkish Journal of Electrical Engineering and Computer Sciences
Quantum key distribution(QKD) has emerged as a secure solution of secret key distribution utilizing the well established theories of modern physics. Since its introduction in 1984, many interesting and innovative ideas have been proposed for QKD in order to improve the security and efficiency of the scheme keeping in view of its applications and practicalimplementation. High error rate QKD scheme for long distance communication-theso-called KMB09 protocol is one such scheme which was designed to achieve longer communication distance in QKD, without compromising its security,by allowing the utilisation of higher dimensional photon states which is not possible with standard BB84 scheme. …
Improving Coverage Method Of Autonomous Drones For Environmental Monitoring,
2020
TÜBİTAK
Improving Coverage Method Of Autonomous Drones For Environmental Monitoring, Ömür Yildirim, Revna Acar Vural, Klaus Diepold
Turkish Journal of Electrical Engineering and Computer Sciences
With the rapid developments of unmanned aerial vehicles (UAVs), usage of UAVs is increasing to bring autonomy for complicated processes such as environmental monitoring. Because of the complexity of the problem, environmental monitoring tasks are highly demanding in terms of time and resources. To reduce expensive costs of operations, improvements on autonomous observation capabilities has a key role. In this work, we offer coverage improvements for our autonomous environmental monitoring system. We compared different path planning approaches to find out the optimum path planning solution. Simulation results showed that required task execution time and required resources are decreased by usage …
A Regular Expression Generator Based On Css Selectors For Efficient Extraction From Html Pages,
2020
TÜBİTAK
A Regular Expression Generator Based On Css Selectors For Efficient Extraction From Html Pages, Erdi̇nç Uzun
Turkish Journal of Electrical Engineering and Computer Sciences
Cascading style sheets (CSS) selectors are patterns used to select HTML elements. They are often preferred in web data extraction because they are easy to prepare and have short expressions. In order to be able to extract data from web pages by using these patterns, a document object model (DOM) tree is constructed by an HTML parser for a webpage. The construction process of this tree and the extraction process using this tree increase time and memory costs depending on the number of HTML elements and their hierarchies. For reducing these costs, regular expressions can be considered as a solution. …
Binary Multicriteria Collaborative Filtering,
2020
TÜBİTAK
Binary Multicriteria Collaborative Filtering, Emre Yalçin, Alper Bi̇lge
Turkish Journal of Electrical Engineering and Computer Sciences
Collaborative filtering is specialized in suggesting appropriate products and services to the users concerning personal characteristics and past preferences without requiring any effort of users. It might be more efficient to collect preferences of users based on multiple subcriteria of products and services. For this purpose, researchers propose multicriteria recommender systems that are convenient for more accurate and useful evaluation of items. Insuchsystems, it might be preferable tocollect binary ratings instead of numerical ones due to the large number of subcriteria. However, there is a gap in the literature to satisfy a binary preferences-based multicriteria recommender system. In this study, …
A New Configuration For Four-Switch Three-Phase Inverters Based On A Switched-Capacitor Step-Up Cell For Electric Vehicles Application, Alireza Lahooti Eshkevari, Ali Mosallanejad, Mohammad Sadegh Sepasian
Turkish Journal of Electrical Engineering and Computer Sciences
This paper proposes a new configuration for four-switch three-phase inverters based on a step-up switchedcapacitor cell, which is called switched-capacitor four-switch three-phase inverter (SCFSTPI). This converter includes eight power switches and two DC-link capacitors. Voltage step-up feature, high efficiency, integrated structure, and bidirectional power flow are the main contribution of this new configuration. A modified space vector modulation (SVM) strategy is presented to generate appropriate pulses for the converter. This modulation method also eliminates the effect of capacitors voltage imbalance problem on the inverter output voltage and current. Simulation and experimental results are presented and investigated to confirm the performance …
A New Grid Partitioning Technology For Location Privacy Protection,
2020
TÜBİTAK
A New Grid Partitioning Technology For Location Privacy Protection, Yue Sun, Lei Zhang, Jing Li, Zhen Zhang
Turkish Journal of Electrical Engineering and Computer Sciences
Nowadays, the location-based service (LBS) has become an essential part of convenient service in people's daily life. However, the untrusted LBS servers can store lots of information about the user, such as the user's identity, location, and destination. Then the information can be used as background knowledge and combined with the query frequency of the user to launch the inference attack to obtain user's privacy. In most of the existing schemes, the author considers the algorithm of virtual location selection from the historical location of the user. However, the LBS server can infer the user's location information on the historical …
Energy Efficiency In Cmos Power Amplifier Designs For Ultralow Power Mobile Wireless Communication Systems,
2020
TÜBİTAK
Energy Efficiency In Cmos Power Amplifier Designs For Ultralow Power Mobile Wireless Communication Systems, Selvakumar Mariappan, Jagadheswaran Rajendran, Norlaili Mohd Noh, Harikrishnan Ramiah, Asrulnizam Abd Manaf
Turkish Journal of Electrical Engineering and Computer Sciences
Wireless communication standards keep evolving so that the requirement for high data rate operation can be fulfilled. This leads to the efforts in designing high linearity and low power consumption radio frequency power amplifier (RFPA) to support high data rate signal transmission and preserving battery life. The percentage of the DC power of the transceiver utilized by the power amplifier (PA) depends on the efficiency of the PA, user data rate, propagation conditions, signal modulations, and communication protocols. For example, the PA of a WLAN transceiver consumes 49 % of the overall efficiency from the transmitter. Hence, operating the PA …
A Review On Embedded Field Programmable Gate Array Architectures And Configuration Tools,
2020
TÜBİTAK
A Review On Embedded Field Programmable Gate Array Architectures And Configuration Tools, Khouloud Bouaziz, Abdulfattah M. Obeid, Sonda Chtourou, Mohamed Abid
Turkish Journal of Electrical Engineering and Computer Sciences
Nowadays, systems-on-chip have reached a level where nonrecurring engineering costs have become a great challenge due to the increase of design complexity and postfabrication errors. Embedded field programmable gate arrays (eFPGAs) represent a viable alternative to overcome these issues since they provide postmanufacturing flexibility that can reduce the number of chip redesigns and amortize chip fabrication cost. In this paper, we present an overview on eFPGAs and their architectures, computer aided design (CAD) tools, and design challenges. An eFPGA must be well-designed and accompanied by an optimized CAD tool suite to respond to target application's requirements in terms of power …
Design Of A High Performance Narrowband Low Noise Amplifier Using An On-Chip Orthogonal Series Stacked Differential Fractal Inductor For 5g Applications, Sunil Kumar Tumma, Bheemarao Nistala
Turkish Journal of Electrical Engineering and Computer Sciences
Inductors play a crucial role in the design of radio frequency integrated circuits (RFICs) and they typically consume a considerably large area and have a low-quality factor at high frequencies. The employment of fractal structure in on-chip inductors helps in improving the quality factor and also reduces the overall area besides improving the inductance value. In this paper, an orthogonal series stacked differential fractal inductor is proposed and the same is used to design a low noise amplifier (LNA) for 5G band (27--30 GHz) applications. The proposed inductor is fabricated on a multilayer printed circuit board and the measurement results …
A Novel Semisupervised Classification Method Via Membership And Polyhedral Conic Functions,
2020
TÜBİTAK
A Novel Semisupervised Classification Method Via Membership And Polyhedral Conic Functions, Nur Uylaş Sati
Turkish Journal of Electrical Engineering and Computer Sciences
In real-world problems, finding sufficient labeled data for defining classification rules is very difficult. This paper suggests a new semisupervised multiclass classification method. In the initialization, new membership functions are defined by utilizing the labeled data?Äôs medoids and means. Then the unlabeled points are labeled with the class of the highest membership value. In the supervised learning phase, separation via the polyhedral conic functions (PCFs) approach is improved by using defined membership values in the linear programming problem. The suggested algorithm is tested on real-world datasets and compared with the state-of-the-art semisupervised methods. The results obtained indicate that the suggested …
Integrated Topic Modeling And Sentiment Analysis: A Review Rating Prediction Approach For Recommender Systems,
2020
TÜBİTAK
Integrated Topic Modeling And Sentiment Analysis: A Review Rating Prediction Approach For Recommender Systems, Anbazhagan Mahadevan, Michael Arock
Turkish Journal of Electrical Engineering and Computer Sciences
Recommender systems (RSs) are running behind E-commerce websites to recommend items that are likely to be bought by users. Most of the existing RSs are relying on mere star ratings while making recommendations. However, ratings alone cannot help RSs make accurate recommendations, as they cannot properly capture sentiments expressed towards various aspects of the items. The other rich and expressive source of information available that can help make accurate recommendations is user reviews. Because of their voluminous nature, reviews lead to the information overloading problem. Hence, drawing out the user opinion from reviews is a decisive job. Therefore, this paper …
Retinal Vessel Segmentation Using Modified Symmetrical Local Threshold,
2020
TÜBİTAK
Retinal Vessel Segmentation Using Modified Symmetrical Local Threshold, Umar Özgünalp
Turkish Journal of Electrical Engineering and Computer Sciences
Retinal vessel segmentation is important for the identification of many diseases including glaucoma, hypertensive retinopathy, diabetes, and hypertension. Moreover, retinal vessel diameter is associated with cardiovascular mortality. Accurate detection of blood vessels improves the detection of exudates in color fundus images, as well as detection of the retinal nerve, optic disc, or fovea. A retinal vessel is a darker stripe on a lighter background. Thus, the objective is very similar to the lane detection task for intelligent vehicles. A lane on a road is a light stripe on a darker background (i.e. asphalt). For lane detection, the symmetrical local threshold …
Detailed Modeling Of A Thermoelectric Generator For Maximum Power Point Tracking,
2020
TÜBİTAK
Detailed Modeling Of A Thermoelectric Generator For Maximum Power Point Tracking, Hayati̇ Mamur, Yusuf Çoban
Turkish Journal of Electrical Engineering and Computer Sciences
Thermoelectric generators (TEGs) are used in small power applications to generate electrical energy from waste heats. Maximum power is obtained when the connected load to the ends of TEGs matches their internal resistance. However, impedance matching cannot always be ensured. Therefore, TEGs operate at lower efficiency. For this reason, maximum power point tracking (MPPT) algorithms are utilized. In this study, both TEGs and a boost converter with MPPT were modeled together. Detailed modeling, simulation, and verification of TEGs depending on the Seebeck coefficient, the hot/cold side temperatures, and the number of modules in MATLAB/Simulink were carried out. In addition, a …
Fuzzy C-Means Directional Clustering (Fcmdc) Algorithm Using Trigonometric Approximation,
2020
TÜBİTAK
Fuzzy C-Means Directional Clustering (Fcmdc) Algorithm Using Trigonometric Approximation, Orhan Kesemen, Özge Tezel, Eda Özkul, Buğra Kaan Ti̇ryaki̇
Turkish Journal of Electrical Engineering and Computer Sciences
Cluster analysis is widely used in data analysis. Statistical data analysis is generally performed on the linear data. If the data has directional structure, classical statistical methods cannot be applied directly to it. This study aims to improve a new directional clustering algorithm which is based on trigonometric approximation. The trigonometric approximation is used for both descriptive statistics and clustering of directional data. In this paper, the fuzzy clustering algorithms (FCD and FCM4DD) improved for directional data and the proposed method are carried out on some numerical and real data examples, and the simulation results are presented. Consequently, these results …
Consumer Loans' First Payment Default Detection: A Predictive Model,
2020
TÜBİTAK
Consumer Loans' First Payment Default Detection: A Predictive Model, Utku Koç, Türkan Sevgi̇li̇
Turkish Journal of Electrical Engineering and Computer Sciences
A default loan (also called nonperforming loan) occurs when there is a failure to meet bank conditions and repayment cannot be made in accordance with the terms of the loan which has reached its maturity. In this study, we provide a predictive analysis of the consumer behavior concerning a loan?Äôs first payment default (FPD) using a real dataset of consumer loans with approximately 600,000 records from a bank. We use logistic regression, naive Bayes, support vector machine, and random forest on oversampled and undersampled data to build eight different models to predict FPD loans. A two-class random forest using undersampling …
Applying Deep Learning Models To Structural Mri For Stage Prediction Of Alzheimer's Disease,
2020
TÜBİTAK
Applying Deep Learning Models To Structural Mri For Stage Prediction Of Alzheimer's Disease, Altuğ Yi̇ği̇t, Zerri̇n Işik
Turkish Journal of Electrical Engineering and Computer Sciences
Alzheimer's disease is a brain disease that causes impaired cognitive abilities in memory, concentration, planning, and speaking. Alzheimer's disease is defined as the most common cause of dementia and changes different parts of the brain. Neuroimaging, cerebrospinal fluid, and some protein abnormalities are commonly used as clinical diagnostic biomarkers. In this study, neuroimaging biomarkers were applied for the diagnosis of Alzheimer's disease and dementia as a noninvasive method. Structural magnetic resonance (MR) brain images were used as input of the predictive model. T1 weighted volumetric MR images were reduced to two-dimensional space by several preprocessing methods for three different projections. …
An Index-Based Joint Multilingual/Cross-Lingual Text Categorization Using Topic Expansion Via Babelnet,
2020
TÜBİTAK
An Index-Based Joint Multilingual/Cross-Lingual Text Categorization Using Topic Expansion Via Babelnet, Eniafe Festus Ayetiran
Turkish Journal of Electrical Engineering and Computer Sciences
The majority of the state-of-the-art text categorization algorithms are supervised and therefore require prior training. Besides the rigor involved in developing training datasets and the requirement for repetition of training for different texts, working with multilingual texts poses additional unique challenges. One of these challenges is that the developer is required to have many different languages involved. Term expansion such as query expansion has been applied in numerous applications; however, a major drawback of most of these applications is that the actual meaning of terms is not usually taken into consideration. Considering the semantics of terms is necessary because of …
A New Biometric Identity Recognition System Based On A Combination Of Superior Features In Finger Knuckle Print Images,
2020
TÜBİTAK
A New Biometric Identity Recognition System Based On A Combination Of Superior Features In Finger Knuckle Print Images, Hadis Heidari, Abdolah Chalechale
Turkish Journal of Electrical Engineering and Computer Sciences
Biometric methods are among the safest and most secure solutions for identity recognition and verification. One of the biometric features with sufficient uniqueness for identity recognition is the finger knuckle print (FKP). This paper presents a new method of identity recognition and verification based on FKP features, where feature extraction is combined with an entropy-based pattern histogram and a set of statistical texture features. The genetic algorithm (GA) is then used to find the superior features among those extracted. After extracting superior features, a support vector machine-based feedback scheme is used to improve the performance of the biometric system. Two …
Fast Texture Classification Of Denoised Sar Image Patches Using Glcm On Spark,
2020
TÜBİTAK
Fast Texture Classification Of Denoised Sar Image Patches Using Glcm On Spark, Caner Özcan, Kadri̇ Okan Ersoy, İskender Ülgen Oğul
Turkish Journal of Electrical Engineering and Computer Sciences
Classification of a synthetic aperture radar (SAR) image is an essential process for SAR image analysis and interpretation. Recent advances in imaging technologies have allowed data sizes to grow, and a large number of applications in many areas have been generated. However, analysis of high-resolution SAR images, such as classification, is a time-consuming process and high-speed algorithms are needed. In this study, classification of high-speed denoised SAR image patches by using Apache Spark clustering framework is presented. Spark is preferred due to its powerful open-source cluster-computing framework with fast, easy-to-use, and in-memory analytics. Classification of SAR images is realized on …
