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Articles 331 - 360 of 3006
Full-Text Articles in Engineering
An Efficient Deep Learning Based Fog Removal Model For Multimedia Applications, Gaurav Saxena, Sarita Singh Bhadauria
An Efficient Deep Learning Based Fog Removal Model For Multimedia Applications, Gaurav Saxena, Sarita Singh Bhadauria
Turkish Journal of Electrical Engineering and Computer Sciences
In the present era of technology, several applications such as surveillances systems, security and object recognitions mainly depend on the contents of an image. In this context, the hazy/foggy environment and/or other adverse climatic conditions degrade the image contents that severely influences the result of related applications. The effective haze removal from a single image decides the reliability of these systems. The convolutional neural network (CNN) based techniques are widely used among the available image dehazing methods. However, in CNN based image dehazing techniques, the robustness and accuracy of the learning models are based on the improvement of transmission estimation …
A Topological Overview Of Microgrids: From Maturity To The Future, Ayşe Kübra Erenoğlu, Semanur Sancar, Ozan Erdi̇nç, Mustafa Bağriyanik
A Topological Overview Of Microgrids: From Maturity To The Future, Ayşe Kübra Erenoğlu, Semanur Sancar, Ozan Erdi̇nç, Mustafa Bağriyanik
Turkish Journal of Electrical Engineering and Computer Sciences
The concept of microgrid (MG) has attracted great attention from the system operators for increasing operational effectiveness as well as providing more reliable, sustainable and economic power system. In this paper, a comprehensive investigation is presented to shine new light on evaluating changes in MG operation from maturity to the future. A great deal of literature studies consisting of the traditional MG architecture, encountered challenges and proposed solutions for overcoming them are all examined in detail. Also, the impact of highly integrated renewable-based energy sources into the power system is analysed by current studies. Moreover, modern MG architecture is extensively …
Model-Based Control For Second-Order Piezo Actuator System With Hysteresis Intime-Delay Environment, Saikat Kumar Shome, Sandip Jana, Arpita Mukherjee, Partha Bhattacharjee
Model-Based Control For Second-Order Piezo Actuator System With Hysteresis Intime-Delay Environment, Saikat Kumar Shome, Sandip Jana, Arpita Mukherjee, Partha Bhattacharjee
Turkish Journal of Electrical Engineering and Computer Sciences
Piezo actuated systems are promising solutions for precision positioning applications. In this paper, a piezoelectric actuator is modeled as a second-order system using the Dahl hysteresis model and the system parameters have been identified from experimental data. The modified internal model control (M-IMC) approach is presented, which not only improves control performance but also reduces associated controller hardware resources. System dead time is approximated using first-order Padé expansion and the proposed Smith predictor-based M-IMC for piezoelectric actuators is seen to offer satisfactory stable control response even for plants with large dead time. The control performance of the M-IMC has been …
Chaos In Metaheuristic Based Artificial Intelligence Algorithms:A Short Review, Gökhan Atali, İhsan Pehli̇van, Bi̇lal Gürevi̇n, Hali̇l İbrahi̇m Şeker
Chaos In Metaheuristic Based Artificial Intelligence Algorithms:A Short Review, Gökhan Atali, İhsan Pehli̇van, Bi̇lal Gürevi̇n, Hali̇l İbrahi̇m Şeker
Turkish Journal of Electrical Engineering and Computer Sciences
Metaheuristic based artificial intelligence algorithms are commonly used in the solution of optimization problems. Another area -besides engineering systems- where chaos theory is widely employed is optimization problems. Being applied easily and not trapping in local optima, chaos-based search algorithms have attracted great attention. For example, it has been reported that when random number sequences generated from different chaotic systems are replaced with parameter values in bioinspired and swarm intelligence algorithms, an increase in the performance of metaheuristic algorithms is observed. Many scientific studies on developing hybrid algorithms in which metaheuristic algorithms and chaos theory are used together are already …
Determining And Evaluating New Store Locations Using Remote Sensing Andmachine Learning, Berkan Höke, Zeynep Zerri̇n Turgay, Cem Ünsalan, Hande Küçükaydin
Determining And Evaluating New Store Locations Using Remote Sensing Andmachine Learning, Berkan Höke, Zeynep Zerri̇n Turgay, Cem Ünsalan, Hande Küçükaydin
Turkish Journal of Electrical Engineering and Computer Sciences
Decision making for store locations is crucial for retail companies as the profit depends on the location. The key point for correct store location is profit approximation, which is highly dependent on population of the corresponding region, and hence, the volume of the residential area. Thus, estimating building volumes provides insight about the revenue if a new store is about to be opened there. Remote sensing through stereo/tri-stereo satellite images provides wide area coverage as well as adequate resolution for three dimensional reconstruction for volume estimation. We reconstruct 3D map of corresponding region with the help of semiglobal matching and …
An Improved Version Of Multi-View K-Nearest Neighbors (Mvknn) For Multipleview Learning, Eli̇fe Öztürk Kiyak, Derya Bi̇rant, Kökten Ulaş Bi̇rant
An Improved Version Of Multi-View K-Nearest Neighbors (Mvknn) For Multipleview Learning, Eli̇fe Öztürk Kiyak, Derya Bi̇rant, Kökten Ulaş Bi̇rant
Turkish Journal of Electrical Engineering and Computer Sciences
Multi-view learning (MVL) is a special type of machine learning that utilizes more than one views, where views include various descriptions of a given sample. Traditionally, classification algorithms such as k-nearest neighbors (KNN) are designed for learning from single-view data. However, many real-world applications involve datasets with multiple views and each view may contain different and partly independent information, which makes the traditional single-view classification approaches ineffective. Therefore, this article proposes an improved MVL algorithm, called multi-view k-nearest neighbors (MVKNN), based on the existing KNN algorithm. The experimental results conducted in this research show that a significant improvement is achieved …
Analysis Of Optical Gyroscopes With Vertically Stacked Ring Resonators, Dooyoung Hah
Analysis Of Optical Gyroscopes With Vertically Stacked Ring Resonators, Dooyoung Hah
Turkish Journal of Electrical Engineering and Computer Sciences
Without any moving part, optical gyroscopes exhibit superior reliability and accuracy in comparison to mechanical sensors. Microring-resonator-based optical gyroscopes emerged as alternatives for bulky conventional Sagnac interferometer sensors, especially attractive for applications with limited footprints. Previously, it has been reported that planar incorporation of multiple resonators does not bring about improvement in sensitivity for a given area because the increase in Sagnac phase accumulation does not outrun the increase of area. Therefore, it was naturally suggested to consider vertical stacking of ring resonators because then, the resonators can share the same footprint. In this work, sensitivity performances of such configurations …
Determining Overfitting And Underfitting In Generative Adversarial Networksusing Fréchet Distance, Enes Eken
Determining Overfitting And Underfitting In Generative Adversarial Networksusing Fréchet Distance, Enes Eken
Turkish Journal of Electrical Engineering and Computer Sciences
Generative adversarial networks (GANs) can be used in a wide range of applications where drawing samples from a data probability distribution without explicitly representing it is essential. Unlike the deep convolutional neural networks (CNNs) trained for mapping an input to one of the multiple outputs, monitoring the overfitting and underfitting in GANs is not trivial since they are not classifying but generating a data. While training set and validation set accuracy give a direct sense of success in terms of overfitting and underfitting for CNNs during the training process, evaluating the GANs mainly depends on the visual inspection of the …
A Fuzzy Expert System For Predicting The Mortality Of Covid'19, Monika Mangla, Nonita Sharma, Poonam Mittal
A Fuzzy Expert System For Predicting The Mortality Of Covid'19, Monika Mangla, Nonita Sharma, Poonam Mittal
Turkish Journal of Electrical Engineering and Computer Sciences
The COVID-19 pandemic has had a widespread impact on health and economy across the globe. It is leading to a huge number of deaths per day. Few researchers have been attracted to analyzing the mortality rate of COVID-19 from various perspectives. During the research, it has become evident that these fatalities are not only caused by COVID19, but they are also affected by some other factors. The authors of this paper aim to encompass three important types of factors viz. risk factors, clinical factors, and miscellaneous factors that influence the mortality of COVID-19. This manuscript presents a rule-based model under …
Joint Optimization Of Target Wake Time Mechanism And Scheduling For Ieee802.11ax, Mehmet Karaca
Joint Optimization Of Target Wake Time Mechanism And Scheduling For Ieee802.11ax, Mehmet Karaca
Turkish Journal of Electrical Engineering and Computer Sciences
IEEE 802.11ax as the newest wireless local area networks (WLANs) standard brings enormous improvements in network throughput, coverage and energy efficiency in densely populated areas. Unlike previous IEEE 802.11 WLAN standards where power saving mechanisms have a limited capability and flexibility, 802.11ax comes with a different mechanism called target wake time (TWT) where stations (STAs) wake up only after each TWT interval and different STAs can wake up at different time instance depending on their application requirements. As an example, for a periodic data arrival occurring in IoT applications, STA can wake up by following the data period and go …
Obround Trees: Sparsity Enhanced Feedback Motion Planning Of Differential Driverobotic Systems, Mustafa Mert Ankarali
Obround Trees: Sparsity Enhanced Feedback Motion Planning Of Differential Driverobotic Systems, Mustafa Mert Ankarali
Turkish Journal of Electrical Engineering and Computer Sciences
Robot motion planning & control is one of the most critical and prevalent problems in the robotics community. Even though original motion planning algorithms had relied on "open-loop" strategies and policies, researchers and engineers have been focusing on feedback motion planning and control algorithms due to the uncertainties, such as process and sensor noise of autonomous robotic applications. Recently, several studies proposed some robust feedback motion planning strategies based on sparsely connected safe zones. In this class of planning and control policies, local control policy inside a single zone computes and feeds the control actions that can drive the robot …
Information Retrieval-Based Bug Localization Approach With Adaptive Attributeweighting, Mustafa Erşahi̇n, Semi̇h Utku, Deni̇z Kilinç, Buket Erşahi̇n
Information Retrieval-Based Bug Localization Approach With Adaptive Attributeweighting, Mustafa Erşahi̇n, Semi̇h Utku, Deni̇z Kilinç, Buket Erşahi̇n
Turkish Journal of Electrical Engineering and Computer Sciences
Software quality assurance is one of the crucial factors for the success of software projects. Bug fixing has an essential role in software quality assurance, and bug localization (BL) is the first step of this process. BL is difficult and time-consuming since the developers should understand the flow, coding structure, and the logic of the program. Information retrieval-based bug localization (IRBL) uses the information of bug reports and source code to locate the section of code in which the bug occurs. It is difficult to apply other tools because of the diversity of software development languages, design patterns, and development …
In Depth Study Of Two Solutions For Common Mode Current Reduction In Six-Phasemachine Drive Inverters, Iman Abdoli, Alireza Lahooti Eshkevari, Ali Mosallanejad
In Depth Study Of Two Solutions For Common Mode Current Reduction In Six-Phasemachine Drive Inverters, Iman Abdoli, Alireza Lahooti Eshkevari, Ali Mosallanejad
Turkish Journal of Electrical Engineering and Computer Sciences
Common mode current (CMC) destroy machine bearings in the long run and increase electromagnetic interference. According to standards, the RMS value of CMC must be lower than 0.3A. Theories show that CMC is originated by applying zero states to the inverter. In this paper, the performance of two solutions in reducing CMC for six-phase machines is investigated. In the first solution, the traditional six-phase inverter is modified by adding two serial power switches on its input terminal. This method is an extended version of a method that has been presented for three-phase inverters, reduces CMC by optimizing the circuit structure. …
Novel Ofdm Transmission Scheme Using Generalized Prefix With Subcarrierindex Modulation, Yusuf Acar
Novel Ofdm Transmission Scheme Using Generalized Prefix With Subcarrierindex Modulation, Yusuf Acar
Turkish Journal of Electrical Engineering and Computer Sciences
The cyclic prefix (CP) is a prefix technique widely used in orthogonal frequency division multiplexing (OFDM) systems in order to eliminate the intersymbol interference (ISI) caused by the dispersion of wireless channels. However, CP reduces the number of symbols that can be transmitted in one OFDM symbol. Therefore, CP is one of the bottlenecks of OFDM systems limiting their spectral efficiency (SE). This limitation on the SE of the classical CP-based OFDM system is the main motivation for this work to introduce a novel method. In this paper, the design of a new CP structure, which is based on the …
Power-Based Modelling And Control: Experimental Results On A Cart-Pole Doubleinverted Pendulum, Tuğçe Yaren, Selçuk Ki̇zi̇r
Power-Based Modelling And Control: Experimental Results On A Cart-Pole Doubleinverted Pendulum, Tuğçe Yaren, Selçuk Ki̇zi̇r
Turkish Journal of Electrical Engineering and Computer Sciences
This paper is concerned with the modeling framework based on power and control for a mechanical system that has nonlinear, unstable, and under-actuated characteristic features, based on an analogy, which is developed by using the Brayton and Moser's (BM) equations between mechanical and electrical systems. The analogy is based on a mixed-potential function generalized for BM. The mixed-potential function for a cart - pole double inverted pendulum (CPDIP) system is used as a new building block for modeling, analysis, and controller design. The analogy allows for the exact transfer of results from electrical circuit synthesis and analysis to the mechanical …
Adaptation Of Metaheuristic Algorithms To Improve Training Performance Of Aneszsl Model, Şi̇fa Özsari, Mehmet Serdar Güzel, Gazi̇ Erkan Bostanci, Ayhan Aydin
Adaptation Of Metaheuristic Algorithms To Improve Training Performance Of Aneszsl Model, Şi̇fa Özsari, Mehmet Serdar Güzel, Gazi̇ Erkan Bostanci, Ayhan Aydin
Turkish Journal of Electrical Engineering and Computer Sciences
Zero-shot learning (ZSL) is a recent promising learning approach that is similar to human vision systems. ZSL essentially allows machines to categorize objects without requiring labeled training data. In principle, ZSL proposes a novel recognition model by specifying merely the attributes of the category. Recently, several sophisticated approaches have been introduced to address the challenges regarding this problem. Embarrassingly simple approach to zeroshot learning (ESZSL) is one of the critical of those approaches that basically proposes a simple but efficient linear code solution. However, the performance of the ESZSL model mainly depends on parameter selection. Metaheuristic algorithms are considered as …
A New Approach: Semisupervised Ordinal Classification, Ferda Ünal, Derya Bi̇rant, Özlem Şeker
A New Approach: Semisupervised Ordinal Classification, Ferda Ünal, Derya Bi̇rant, Özlem Şeker
Turkish Journal of Electrical Engineering and Computer Sciences
Semisupervised learning is a type of machine learning technique that constructs a classifier by learning from a small collection of labeled samples and a large collection of unlabeled ones. Although some progress has been made in this research area, the existing semisupervised methods provide a nominal classification task. However, semisupervised learning for ordinal classification is yet to be explored. To bridge the gap, this study combines two concepts ?semisupervised learning? and "ordinal classification" for the categorical class labels for the first time and introduces a new concept of "semisupervised ordinal classification". This paper proposes a new algorithm for semisupervised learning …
A Case Study On Player Selection And Team Formation In Football With Machinelearning, Di̇dem Abi̇di̇n
A Case Study On Player Selection And Team Formation In Football With Machinelearning, Di̇dem Abi̇di̇n
Turkish Journal of Electrical Engineering and Computer Sciences
Machine learning has been widely used in different domains to extract information from raw data. Sports is one of the popular domains for researchers to work on recently. Although score prediction for matches is the most preferred application area for artificial intelligence, player selection, and team formation is also an application area worth working on. There are some studies in the literature about player selection and team formation which are examined in this study. The study has two important contributions: First one is to apply seven different machine learning algorithms on our dataset to find the best player combination for …
Analysis And Simulation Of Efficiency Optimized Ipm Drives In Constant Torqueregion With Reduced Computational Burden, Mi̇kai̇l Koç, Selçuk Emi̇roğlu, Bünyami̇n Tamyürek
Analysis And Simulation Of Efficiency Optimized Ipm Drives In Constant Torqueregion With Reduced Computational Burden, Mi̇kai̇l Koç, Selçuk Emi̇roğlu, Bünyami̇n Tamyürek
Turkish Journal of Electrical Engineering and Computer Sciences
Moving from internal combustion engine based towards electric based transportation is crucial for wide societies as they facilitate the use of green energy technologies such as wind and solar. Interior mounted permanent magnet (IPM) machines, also known as salient brushless alternating current (AC) machines, are commonly employed in traction applications as they have superior features, such as high efficiency operation, high torque, and power densities. The efficiency optimization in IPM drives is achieved by obtaining and operating at accurate and unique current angle for a certain electromagnetic torque demand. In conventional drives, the optimum current angle is obtained by online …
Control Synthesis For Parametric Timed Automata Under Reachability, Ebru Aydin Göl
Control Synthesis For Parametric Timed Automata Under Reachability, Ebru Aydin Göl
Turkish Journal of Electrical Engineering and Computer Sciences
Timed automata is a fundamental modeling formalism for real-time systems. During the design of such real-time systems, often the system information is incomplete, and design choices can vary. These uncertainties can be integrated to the model via parameters and labelled transitions. Then, the design can be completed by tuning the parameters and restricting the transitions via controller synthesis. These problems, namely parameter synthesis and controller synthesis, are studied separately in the literature. Herein, these are combined to generate an automaton satisfying the given specification by both parameter tuning and controller synthesis, thus exploring all design choices. First, it is shown …
New Hyperchaotic System With Single Nonlinearity, Its Electronic Circuit Andencryption Design Based On Current Conveyor, Anitha Karthikeyan, Serdar Çi̇çek, Karthikeyan Rajagopal, Prakash Duraisamy, Ashokkumar Srinivasan
New Hyperchaotic System With Single Nonlinearity, Its Electronic Circuit Andencryption Design Based On Current Conveyor, Anitha Karthikeyan, Serdar Çi̇çek, Karthikeyan Rajagopal, Prakash Duraisamy, Ashokkumar Srinivasan
Turkish Journal of Electrical Engineering and Computer Sciences
Nowadays, hyperchaotic system (HCSs) have been started to be used in engineering applications because they have complex dynamics, randomness, and high sensitivity. For this purpose, HCSs with different features have been introduced in the literature. In this work, a new HCS with a single discontinuous nonlinearity is introduced and analyzed. The proposed system has one saddle focus equilibrium. When the dynamic properties and bifurcation graphics of the system are analyzed, it is determined that the proposed system exhibits the complex phenomenon of multistability. Moreover, analog electronic circuit design of the proposed system is performed with positive second-generation current conveyor. In …
A Novel Hybrid Global Optimization Algorithm Having Training Strategy: Hybridtaguchi-Vortex Search Algorithm, Mustafa Saka, Meli̇h Çoban, İbrahi̇m Eke, Suleyman Sungur Tezcan, Müslüm Cengi̇z Taplamacioğlu
A Novel Hybrid Global Optimization Algorithm Having Training Strategy: Hybridtaguchi-Vortex Search Algorithm, Mustafa Saka, Meli̇h Çoban, İbrahi̇m Eke, Suleyman Sungur Tezcan, Müslüm Cengi̇z Taplamacioğlu
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, a novel hybrid Taguchi-vortex search algorithm (HTVS) is proposed for solving global optimization problems. Taguchi orthogonal approximation and vortex search algorithm (VS) are hybridized in presenting method. In HTVS, orthogonal arrays in the Taguchi method are trained and obtained better solutions are used to find global optima in VS. Thus, HTVS has better relation between exploration and exploitation, and it exhibits more powerful approximation to find global optimum value. Proposed HTVS algorithm is applied to sixteen well-known benchmark optimization test functions with different dimensions. The results are compared with the Taguchi orthogonal array approximation (TOAA), vortex search …
A Novel Approach For Intrusion Detection Systems: V-Ids, Kenan İnce
A Novel Approach For Intrusion Detection Systems: V-Ids, Kenan İnce
Turkish Journal of Electrical Engineering and Computer Sciences
An intrusion detection system (IDS) is a security mechanism that detects abnormal activities in a network. An ideal IDS must detect intrusion attempts and maybe categorize them for further research and keep false-positive analysis at a very low level. IDSs are used in the analysis of network traffic data at all sizes. Studies on this subject focused on machine learning techniques. Even though the performance rates are high, it is seen that processes such as data understanding, preprocessing, and consistency tests are time-consuming and laborious. For this reason, the use of deep learning (DL) models that automatically perform the mentioned …
Performance Improvement Speed Control Of Ipmsm Drive Based On Nonlinearcurrent Control, Muhammad Usama, Jaehong Kim
Performance Improvement Speed Control Of Ipmsm Drive Based On Nonlinearcurrent Control, Muhammad Usama, Jaehong Kim
Turkish Journal of Electrical Engineering and Computer Sciences
Recently model predictive control (MPC) scheme emerges as an efficient current control technique for dynamic performance of motor drives. For excellent dynamic performance, maximum torque per ampere (MTPA) control technique is utilized to achieve maximum torque while using minimum current constrain in contrast to conventional qaxis current control. Model predictive current control (MPCC) scheme alongside MTPA control is employed to replace the traditional constant gain proportional-integral (PI) current control and a nonlinear hysteresis current (HC) control schemes. The PI and hysteresis current controller offers satisfactory performance at ideal conditions but, with variable speed and load conditions, these control schemes cause …
Area-Delay Efficient Radix-4 8×8 Booth Multiplier For Dsp Applications, Subodh Singhal, Sujit Patel, Anurag Mahajan, Gaurav Saxena
Area-Delay Efficient Radix-4 8×8 Booth Multiplier For Dsp Applications, Subodh Singhal, Sujit Patel, Anurag Mahajan, Gaurav Saxena
Turkish Journal of Electrical Engineering and Computer Sciences
Booth multiplier is the key component in portable very large-scale integration (VSLI) systems enabled with signal and image processing applications. The area, delay, and energy are the major constraints in these systems. Therefore, in this paper, a detailed analysis of the state-of-the-art Booth multiplier architecture and its various internal units are presented to find the scope of optimization. Based on the finding of analysis, optimized new binary to 2's complement (B2C), Booth encoder-cum-selector type-1 and type-2, and partial product addition units are proposed. Furthermore, using these optimized units, an efficient parallel radix-4 8×8 Booth multiplier architecture is proposed. The simulation …
Image Forgery Detection Based On Fusion Of Lightweight Deep Learning Models, Amit Doegar, Srinidhi Hiriyannaiah, Siddesh Gaddadevara Matt, Srinivasa Krishnarajanagar Gopaliyengar, Maitreyee Dutta
Image Forgery Detection Based On Fusion Of Lightweight Deep Learning Models, Amit Doegar, Srinidhi Hiriyannaiah, Siddesh Gaddadevara Matt, Srinivasa Krishnarajanagar Gopaliyengar, Maitreyee Dutta
Turkish Journal of Electrical Engineering and Computer Sciences
Image forgery detection is one of the key challenges in various real time applications, social media and online information platforms. The conventional methods of detection based on the traces of image manipulations are limited to the scope of predefined assumptions like hand-crafted features, size and contrast. In this paper, we propose a fusion based decision approach for image forgery detection. The fusion of decision is based on the lightweight deep learning models namely SqueezeNet, MobileNetV2 and ShuffleNet. The fusion decision system is implemented in two phases. First, the pretrained weights of the lightweight deep learning models are used to evaluate …
Zero Knowledge Based Data Deduplication Using In-Line Block Matching Protocolfor Secure Cloud Storage, Vivekrabinson Kanagamani, Muneeswaran Karuppiah
Zero Knowledge Based Data Deduplication Using In-Line Block Matching Protocolfor Secure Cloud Storage, Vivekrabinson Kanagamani, Muneeswaran Karuppiah
Turkish Journal of Electrical Engineering and Computer Sciences
In the area of cloud computing, data deduplication enables the cloud server to store a single copy of data by eliminating redundant files to improve storage and network efficiency. Proof-of-ownership (PoW) is a cryptographic function that verifies the user who really owns the data. Most of the existing schemes have tried to solve the deduplication problem by providing the same encryption key for identical data. However, these schemes suffer from dynamic changes in ownership management. In this paper, we propose an in-line block matching (IBM) protocol based on zero-knowledge proof for deduplication with dynamic ownership management, which eliminates the unauthorized …
Legendre-Wavelet Embedded Neurofuzzy Feedback Linearization Based Controlscheme For Phevs Charging Station In A Microgrid, Muhammad Awais, Laiq Khan, Saghir Ahmad, Sidra Mumtaz, Rabiah Badar, Shafaat Ullah
Legendre-Wavelet Embedded Neurofuzzy Feedback Linearization Based Controlscheme For Phevs Charging Station In A Microgrid, Muhammad Awais, Laiq Khan, Saghir Ahmad, Sidra Mumtaz, Rabiah Badar, Shafaat Ullah
Turkish Journal of Electrical Engineering and Computer Sciences
The immense emergence of plug-in hybrid electric vehicles (PHEVs) is envisioned in the future. The rapid proliferation of PHEVs and their charging triggers intense surges in the load during load peak hours. A sophisticated controlled charging station is developed for PHEVs to alleviate grid load during peak demand hours. A novel feedback linearization embedded full recurrent adaptive NeuroFuzzy Legendre wavelet control (FBL-FRANF-Leg-WC) technique is employed to control the charging of PHEVs. The antecedent part of the NeuroFuzzy framework is based on recurrent Gaussian membership function while the consequent part comprises of recurrent Legendre wavelet. The charging station is integrated into …
Visual Object Detection For Autonomous Transport Vehicles In Smart Factories, Nazlican Gengeç, Onur Eker, Hakan Çevi̇kalp, Ahmet Yazici, Hasan Serhan Yavuz
Visual Object Detection For Autonomous Transport Vehicles In Smart Factories, Nazlican Gengeç, Onur Eker, Hakan Çevi̇kalp, Ahmet Yazici, Hasan Serhan Yavuz
Turkish Journal of Electrical Engineering and Computer Sciences
Autonomous transport vehicles (ATVs) are one of the most substantial components of smart factories of Industry 4.0. They are primarily considered to transfer the goods or perform some certain navigation tasks in the factory with self driving. The recent developments on computer vision studies allow the vehicles to visually perceive the environment and the objects in the environment. There are numerous applications especially for smart traffic networks in outdoor environments but there is lack of application and databases for autonomous transport vehicles in indoor industrial environments. There exist some essential safety and direction signs in smart factories and these signs …
A Linear Programming Approach To Multiple Instance Learning, Emel Şeyma Küçükaşci, Mustafa Gökçe Baydoğan, Zeki̇ Caner Taşkin
A Linear Programming Approach To Multiple Instance Learning, Emel Şeyma Küçükaşci, Mustafa Gökçe Baydoğan, Zeki̇ Caner Taşkin
Turkish Journal of Electrical Engineering and Computer Sciences
Multiple instance learning (MIL) aims to classify objects with complex structures and covers a wide range of real-world data mining applications. In MIL, objects are represented by a bag of instances instead of a single instance, and class labels are provided only for the bags. Some of the earlier MIL methods focus on solving MIL problem under the standard MIL assumption, which requires at least one positive instance in positive bags and all remaining instances are negative. This study proposes a linear programming framework to learn instance level contributions to bag label without emposing the standart assumption. Each instance of …