Development Of Computationally Efficient Biorthogonal Wavelets,
2021
TÜBİTAK
Development Of Computationally Efficient Biorthogonal Wavelets, Mehmet Cemi̇l Kale
Turkish Journal of Electrical Engineering and Computer Sciences
Daubechies 5-tap/3-tap (Daub 5/3) wavelet and Kale 5-tap/3-tap (Kale 5/3) wavelet are computationally efficient wavelets which can be implemented by bitwise shifts and additions in the lifting scheme. In this work, presented is a formulation for computationally efficient wavelet prediction (P) and update (U) filters of two-channel lifting structures. Their subband decomposition scheme counterparts are also given. This research bases itself on the Daub 5/3 and Kale 5/3 wavelets and develops a formula for wavelets (which can be implemented with bitwise shifts and additions) that are derived from these two wavelets. The proposed wavelets are tried on 16 test images …
Engraved Digit Detection Using Hog-Real Adaboost And Deep Neural Network,
2021
TÜBİTAK
Engraved Digit Detection Using Hog-Real Adaboost And Deep Neural Network, Tuan Linh Dang, Thang Cao, Yukinobu Hoshino
Turkish Journal of Electrical Engineering and Computer Sciences
This paper proposes a framework for recognizing sequences of digits engraved on steel plates. These digits are normally blurred, dirty, not clear, tilted, and sometimes overlapped by other digits. Several digits in a string with uneven spacing and different sizes are detected at the same time. The framework consists of two main components called histogram of oriented gradient-real AdaBoost module and deep neural network module. The first component is used to detect digit windows, and the second component is employed to recognize digits inside the detected windows. Experimental results demonstrated that the proposed framework could be a potential solution to …
Characterization Of Different Crowd Behaviors Using Novel Deep Learningframework,
2021
TÜBİTAK
Characterization Of Different Crowd Behaviors Using Novel Deep Learningframework, Abdullah Jaman Alzahrani, Sultan Daud Khan
Turkish Journal of Electrical Engineering and Computer Sciences
Crowd behavior understanding is recognized as a complex problem due to unpredictable behavior of humans and complex interactions of individuals in groups. For crowd managers, it is crucial to understand the crowd dynamics to manage the crowd efficiently and effectively. Current practice of crowd management is based on manual analysis of the scene. Such manual analysis of the scene is a tedious job and usually prone to errors due to limited human capabilities. Therefore, the task of automatizing crowd analysis has received tremendous attention from the research community during the recent years. In this paper, we propose a deep model …
A New Method For Optimal Expansion Planning In Electrical Energy Distributionnetworks With Distributed Generation Resources Considering Uncertainties, Amir Masoud Mohaghegh, S Yaser Derakhshandeh, Abbas Kargar
Turkish Journal of Electrical Engineering and Computer Sciences
The present study aims to introduce a robust model for distribution network expansion planning considering system uncertainties. The proposed method determines optimal size and placement of distributed generation resources, as well as installation and reinforcement of feeders and substations. This model is designed to minimize cost and to determine the best time for the installation of equipment in the expansion planning. In the proposed expansion planning, the fuzzy logic theory is employed to model uncertainties of loads and energy price. Also, since the proposed model is a nonlinear and nonconvex optimization problem, a tri-stage algorithm is developed to solve it. …
Real-Time Measurements And Performance Analysis Of Closed-Loop Mimo Servicefor Mobile Operators,
2021
TÜBİTAK
Real-Time Measurements And Performance Analysis Of Closed-Loop Mimo Servicefor Mobile Operators, Engi̇n Zeydan, Ömer Dedeoğlu, Yekta Türk
Turkish Journal of Electrical Engineering and Computer Sciences
As fifth generation (5G) networks are starting to become commercial, user expectations in terms of new services become high as well. This signifies that mobile communications service providers need to build robust 5G new services as quickly and cost-efficiently as possible. Many new technologies rely on closed-loop (CL) and multiple input multiple output (MIMO) technologies due to emerging cooperation between nodes in next generation networks. In this paper, we first compare different multiantenna transmission modes namely: transmit diversity, open-loop (OL), and CL MIMO spatial multiplexing strategies to provide mobile network operator (MNO) services in terms of their characteristics, ,limitations and …
Deep-Learning-Based Spraying Area Recognition System Forunmanned-Aerial-Vehicle-Based Sprayers,
2021
TÜBİTAK
Deep-Learning-Based Spraying Area Recognition System Forunmanned-Aerial-Vehicle-Based Sprayers, Shahbaz Khan, Muhammad Tufail, Muhammad Tahir Khan, Zubair Ahmed Khan, Shahzad Anwer
Turkish Journal of Electrical Engineering and Computer Sciences
Unmanned aerial vehicle (UAV)-based spraying system employing machine learning techniques is a recent advancement in precision agriculture for precise spraying, promoting saving chemicals (pesticide/herbicide), and enhancing their effectiveness. This study aims to develop an efficient deep learning system for UAV-based sprayers, which has the capability to accurately recognize spraying areas. A deep learning system is proposed and developed incorporating a faster region-based convolutional neural network (R-CNN) for the imagery collected. In order to develop a classifier for identifying spraying areas from nonspraying areas, four different agriculture croplands and orchards were considered. All the experiments were performed in agriculture fields through …
Performance Evaluation Of A Power Allocation Algorithm Based On Dynamicblocklength Estimation For Urllc In The Multicarrier Downlink Noma Systems, Won Jae Ryu, Soo Young Shin
Turkish Journal of Electrical Engineering and Computer Sciences
This study investigates a power allocation algorithm using blocklength estimation by the finite blocklength (FBL) regime in a multicarrier downlink nonorthogonal multiple access (NOMA) system for ultrareliable low latency communication (URLLC) that is one of the services in 5G networks, requiring exceedingly high reliability and low latency. As NOMA systems can boost the capacity and increase the spectrum efficiency, it can be considered as a solution for URLLC. A multicarrier downlink NOMA system using blocklength estimation based on the FBL regime is proposed for effective resource allocation in this study. The FBL is used to derive the equation for dynamic …
Comparison Of Risc-V And Transport Triggered Architectures For A Postquantumcryptography Application,
2021
TÜBİTAK
Comparison Of Risc-V And Transport Triggered Architectures For A Postquantumcryptography Application, Lati̇f Akçay, Siddika Berna Örs Yalçin
Turkish Journal of Electrical Engineering and Computer Sciences
Cryptography is one of the basic phenomena of security systems. However, some of the widely used publickey cryptography algorithms can be broken by using quantum computers. Therefore, many postquantum cryptography algorithms are proposed in recent years to handle this issue. NTRU (Nth degree truncated polynomial ring units) is one of the most important of these quantum-safe algorithms. Besides the importance of cryptography algorithms, the architecture where they are implemented is also essential. In this study, we developed an NTRU public key cryptosystem application and designed several processors to compare them in many aspects. We address two different architectures in this …
Analyzing The Performances Of Evolutionary Multi-Objective Optimizers On Designoptimization Of Robot Gripper Configurations,
2021
TÜBİTAK
Analyzing The Performances Of Evolutionary Multi-Objective Optimizers On Designoptimization Of Robot Gripper Configurations, Murat Dörterler, Ümi̇t Ati̇la, Rafet Durgut, İsmai̇l Şahi̇n
Turkish Journal of Electrical Engineering and Computer Sciences
Robot grippers are widely used in a variety of areas requiring automation, precision, and safety. The performance of the grippers is directly associated with their design. In this study, four different multiobjective metaheuristic algorithms including particle swarm optimization (MOPSO), artificial algae algorithm (MOAAA), grey wolf optimizer (MOGWO) and nondominated sorting genetic algorithm (NSGA-II) were applied to two different configurations of highly nonlinear and multimodal robot gripper design problem including two objective functions and a certain number of constraints. The first objective is to minimize the difference between minimum and maximum forces for the assumed range in which the gripper ends …
A Novel Fibonacci Hash Method For Protein Family Identification By Usingrecurrent Neural Networks,
2021
TÜBİTAK
A Novel Fibonacci Hash Method For Protein Family Identification By Usingrecurrent Neural Networks, Talha Burak Alakuş, İbrahi̇m Türkoğlu
Turkish Journal of Electrical Engineering and Computer Sciences
Identification and classification of protein families are one of the most significant problem in bioinformatics and protein studies. It is essential to specify the family of a protein since proteins are highly used in smart drug therapies, protein functions, and, in some cases, phylogenetic trees. Some sequencing techniques provide researchers to identify the biological similarities of protein families and functions. Yet, determining these families with sequencing applications requires huge amount of time. Thus, a computer and artificial intelligence based classification system is needed to save time and avoid complexity in protein classification process. In order to designate the protein families …
Development Of An Intelligent Controller For Robot-Aided Assessment Andtreatment Guidance In Physical Medicine And Rehabilitation, Mehmet Emi̇n Aktan, Erhan Akdoğan
Turkish Journal of Electrical Engineering and Computer Sciences
In this study, an intelligent controller was developed for a rehabilitation robot called DIAGNOBOT, which can be used for assessment and treatment in the rehabilitation of wrist and forearm. The controller has a decision support system structure strengthened with conventional statistical methods and databases. The controller uses the patient's biomechanical parameters to make an assessment and proposes a treatment in line with this. In accordance with the recommended treatment, it produces the control parameters, torque, and position information for the control of the rehabilitation robot. The system's ability of assessment and treatment was tested with voluntary patients. Through these test …
Neurofuzzy Robust Backstepping Based Mppt Control For Photovoltaic System,
2021
TÜBİTAK
Neurofuzzy Robust Backstepping Based Mppt Control For Photovoltaic System, Kamran Ali, Laiq Khan, Qudrat Khan, Shafaat Ullah, Naghmash Ali
Turkish Journal of Electrical Engineering and Computer Sciences
Linear maximum power point tracking (MPPT) techniques are unable to achieve the desired performance and efficiency under wide variation in atmospheric conditions (temperature and irradiance) and consequently the maximum power point (MPP). Hence, the design and implementation of a nonlinear MPPT controller is essential to address the problems associated with the variations of the MPP. In this research article, a new nonlinear robust backstepping-based MPPT control technique is proposed for a standalone PV array connected to a dynamic load, and its performance comparison with existing backstepping, integral backstepping and conventional proportional integral derivative (PID) and perturb and observe (P&O) based …
Robust Model Reference Adaptive Pi Controller Based Sliding Mode Control Forthree-Phase Grid Connected Photovoltaic Inverter,
2021
TÜBİTAK
Robust Model Reference Adaptive Pi Controller Based Sliding Mode Control Forthree-Phase Grid Connected Photovoltaic Inverter, Mojtaba Moeti, Mehdi Asadi
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, the design of a new robust model reference adaptive PI (MRAC-PI) current controller is proposed for a two-stage grid connected photovoltaic (PV) inverter. Perturb & observe (P&O) algorithm is implemented in the boost part in order to extract the maximum power from the PV array. Firstly, the current dynamics with considering the system uncertainties are written in dq frame and are simplified by employing a decoupling system. Then, the MRAC-PI controller is designed based on a sliding mode control (SMC) to improve the robustness of the controller under system uncertainties. The parameters of PI controller are tuned …
A Counter Based Approach For Reducer Placement With Augmented Hadoop Rackawareness,
2021
TÜBİTAK
A Counter Based Approach For Reducer Placement With Augmented Hadoop Rackawareness, Mir Wajahat Hussain, K Hemant Reddy, Diptendu Sinha Roy
Turkish Journal of Electrical Engineering and Computer Sciences
As the data-driven paradigm for intelligent systems design is gaining prominence, performance requirements have become very stringent, leading to numerous fine-tuned versions of Hadoop and its MapReduce programming model. However, very few researchers have investigated the effect of intelligent reducer placement on Hadoop's performance. This paper delves into this much ignored reducer placement phase for improving Hadoop's performance and proposes to spawn reduce phase of Hadoop tasks in an asynchronous fashion across nodes in a Hadoop cluster. The main contributions of this paper are: (i) to track when map phase of tasks are completed, (ii) to count the number of …
Risk-Averse Optimal Bidding Strategy For A Wind Energy Portfolio Managerincluding Ev Parking Lots For Imbalance Mitigation,
2021
TÜBİTAK
Risk-Averse Optimal Bidding Strategy For A Wind Energy Portfolio Managerincluding Ev Parking Lots For Imbalance Mitigation, Alper Çi̇çek, Ozan Erdi̇nç
Turkish Journal of Electrical Engineering and Computer Sciences
In this study, an optimal bidding strategy for a wind energy portfolio manager (WEPM) including electricvehicle parking lots (EVPLs) that aims to maximize profits by trading in the day-ahead (DA) market and balancingmarket (BM) and through bilateral contracts, taking into account line capacities and risk management is proposed. Thementioned structure is modeled in mixed integer linear programming (MILP) framework, and the uncertainties regardingelectric vehicle (EV) behavior, electricity market data, wind power generation are captured via a stochastic approach. Todemonstrate the effectiveness of the model, several case studies are carried out considering Sweden and Turkey electricitymarket prices with different risk aversion …
Development Of Majority Vote Ensemble Feature Selection Algorithm Augmentedwith Rank Allocation To Enhance Turkish Text Categorization, Emi̇n Borandağ, Akin Özçi̇ft, Yeşi̇m Kaygusuz
Turkish Journal of Electrical Engineering and Computer Sciences
The increase in the number of texts as digital documents from numerous sources such as customer reviews,news, and social media has made text categorization crucial in order to be able to manage the enormous amount ofdata. The high dimensional nature of these texts requires a preliminary feature selection task to reduce the featurespace with a potential increase in the prediction accuracy. In this study, we developed an ensemble feature selectionmethod, namely majority vote rank allocation, was developed for Turkish text categorization purposes. The methoduses a majority voting ensemble strategy in combination with a rank allocation approach to combine weak filters …
Efficient Hybrid Passive Method For The Detection And Localization Of Copy-Moveand Spliced Images,
2021
TÜBİTAK
Efficient Hybrid Passive Method For The Detection And Localization Of Copy-Moveand Spliced Images, Navneet Kaur, Neeru Jindal, Kulbir Singh
Turkish Journal of Electrical Engineering and Computer Sciences
Digital passive image forgery methods are extensively used to verify the authenticity and integrity of images.Splicing and copy-move are the most common types of passive digital image forgeries. Several approaches have beenproposed to detect these forgeries separately, but very few approaches are available that can detect them simultaneously.However, a more e?icient method is still in demand to meet the day-to-day challenges to detect these forgeries at thesame time. So, a passive hybrid approach based on discrete fractional cosine transform (DFrCT) and local binarypattern (LBP) is proposed to detect copy-move and splicing forgeries simultaneously. The extra parameter i.e. fractionalparameter of DFrCT …
Neuro-Adaptive Backstepping Integral Sliding Mode Control Design For Nonlinearwind Energy Conversion System,
2021
TÜBİTAK
Neuro-Adaptive Backstepping Integral Sliding Mode Control Design For Nonlinearwind Energy Conversion System, Imran Ullah Khan, Laiq Khan, Qudrat Khan, Shafaat Ullah, Uzair Khan, Saghir Ahmad
Turkish Journal of Electrical Engineering and Computer Sciences
The electrical power extracted from a wind energy conversion system (WECS) tends to be inconsistentdue to the intermittent nature of the wind. This issue is addressed by formulating a maximum power point tracking(MPPT) control strategy that optimizes the power extraction from the WECS under a wide range of wind speed profiles.This research article focuses on the formulation of a nonlinear neuro-adaptive backstepping integral sliding mode control(NABISMC) based MPPT strategy for a standalone, variable speed, fixed-pitch WECS equipped with a permanentmagnet synchronous generator (PMSG). The proposed paradigm is a hybrid of the conventional backstepping andthe integral sliding mode control (ISMC) based …
Deep Learning Techniques Of Losses In Data Transmitted In Wirelesssensor Networks,
2021
TÜBİTAK
Deep Learning Techniques Of Losses In Data Transmitted In Wirelesssensor Networks, Mevlüt Ersoy, Beki̇r Aksoy
Turkish Journal of Electrical Engineering and Computer Sciences
Wireless sensor network (WSN) systems are frequently used today as a result of rapid technological developments. Wireless sensor networks, which form the basis of the Internet of Things (IoT), have a wide range of use in theworld from education to health, and from military applications to home applications. It enables the data obtained fromthe sensors to be transferred between nodes with the help of end-to-end wireless protocols. In parallel with the increasingnumber of nodes in WSN, data tra?ic density also increases. Due to the limitations of the WSN network, lost packetrates also increase with increasing data tra?ic. In this study, …
Low Communication Parallel Distributed Adaptive Signal Processing (Lc-Pdasp)Architecture For Processing-Inefficient Platforms,
2021
TÜBİTAK
Low Communication Parallel Distributed Adaptive Signal Processing (Lc-Pdasp)Architecture For Processing-Inefficient Platforms, Hasan Raza, Ghalib Hussain, Noor Khan
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, a low communication parallel distributed adaptive signal processing (LC-PDASP) architecturefor a group of computationally incapable and inexpensive small platforms is introduced. The proposed architectureis capable of running computationally high adaptive filtering algorithms parallely with minimally low communicationoverhead. A recursive least square (RLS) adaptive algorithm based on the application of multiple-input multiple-output(MIMO) channel estimation is implemented on the proposed LC-PDASP architecture. Complexity and Communicationburden of proposed LC-PDASP architecture are compared with that of conventional PDASP architecture. The compar-ative analysis shows that the proposed LC-PDASP architecture exhibits low computational complexity and provides animprovement more than of85%reduced communication burden than …
