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Articles 2311 - 2340 of 8897

Full-Text Articles in Physical Sciences and Mathematics

Refugees' Social Media Activities In Turkey: A Computational Analysis And Demonstration Method, Muhammed Abdullah Bülbül, Salah Haj Ismail Jan 2019

Refugees' Social Media Activities In Turkey: A Computational Analysis And Demonstration Method, Muhammed Abdullah Bülbül, Salah Haj Ismail

Turkish Journal of Electrical Engineering and Computer Sciences

This study performs a data analysis on refugees in Turkey based on their social media activities. In order to achieve this, we first propose a method to find their relevant public accounts and collect their activities generating a dataset. Then, we perform spatial and temporal analysis over this dataset to shed light on the most important topics and events discussed in social networks. We present the results graphically for ease of understanding and comparison. Our results indicate that we can reveal the most shared topics over a specific time and place as well as the change of pattern in refugees' …

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Measurement Of Network-Based And Random Meetings In Social Networks, Pranav Nerurkar, Madhav Chandane, Sunil Bhirud Jan 2019

Measurement Of Network-Based And Random Meetings In Social Networks, Pranav Nerurkar, Madhav Chandane, Sunil Bhirud

Turkish Journal of Electrical Engineering and Computer Sciences

Social networks are created by the underlying behavior of the actors involved in them. Each actor has interactions with other actors in the network and these interactions decide whether a social relationship should develop between them. Such interactions may occur due to meeting processes such as chance-based meetings or network-based (choice) meetings. Depending upon which of these two types of interactions plays a greater role in creation of links, a social network shall evolve accordingly. This evolution shall result in the social network obtaining a suitable structure and certain unique features. The aim of this work is to determine the …

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Cache Pressure-Aware Caching Scheme For Content-Centric Networking, Xi Luo, Ying An Jan 2019

Cache Pressure-Aware Caching Scheme For Content-Centric Networking, Xi Luo, Ying An

Turkish Journal of Electrical Engineering and Computer Sciences

Content centric networking (CCN) is a new networking paradigm to meet the growing demand for content access in the future. Because of its important role in accelerating content retrieval and reducing network transmission load, in-network caching has become one of the core technologies in CCN and has attracted wide attention. The existing caching schemes often lack sufficient consideration of node cache status and the temporal validity of user requests, and thus the cache efficiency of the network is greatly reduced. In this paper, a cache pressure-aware caching scheme is proposed, which comprehensively takes into account various factors such as content …

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A Novel Adaptive Hysteresis Dc-Dc Buck Converter For Portable Devices, Sung Sik Park, Ju Sang Lee, Sang Dae Yu Jan 2019

A Novel Adaptive Hysteresis Dc-Dc Buck Converter For Portable Devices, Sung Sik Park, Ju Sang Lee, Sang Dae Yu

Turkish Journal of Electrical Engineering and Computer Sciences

This paper presents a new technique that adjusts the hysteresis window depending on the variations in load current caused by a voltage-mode circuit to reduce the voltage and current ripples. Moreover, a compact current-sensing circuit is used to provide an accurate sensing signal for achieving fast hysteresis window adjustment. In addition, a zero-current detection circuit is also proposed to eliminate the reverse current at light loads. As a result, this technique reduces the voltage ripple below 8.08 mV$_{\rm pp}$ and the current ripple below 93.98 mA$_{\rm pp}$ for a load current of 500 mA. Circuit simulation is performed using 0.18 …

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A Novel Design Of An Electromagnetically Levitated Vibrational Viscometer For Biomedical And Clinical Applications, Ali̇ Akpek Jan 2019

A Novel Design Of An Electromagnetically Levitated Vibrational Viscometer For Biomedical And Clinical Applications, Ali̇ Akpek

Turkish Journal of Electrical Engineering and Computer Sciences

Accurate determination of the viscosity behavior of fluids is extremely important, especially for biomedical and clinical applications. For example, blood viscosity is used to detect cardiovascular diseases in patients. Like blood, all body fluids and biochemical solvents used in biomedical studies are very limited resources. Therefore, a viscometer that is especially focused for biomedical and clinical applications should have the ability to obtain viscosity results from a reservoir as small as possible, in a range as wide as possible and in a period of time as short as possible. The measurements must be accurate even when the fluid temperatures shift …

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Classification Of Generic System Dynamics Model Outputs Via Supervised Time Series Pattern Discovery, Mert Edali, Mustafa Gökçe Baydoğan, Gönenç Yücel Jan 2019

Classification Of Generic System Dynamics Model Outputs Via Supervised Time Series Pattern Discovery, Mert Edali, Mustafa Gökçe Baydoğan, Gönenç Yücel

Turkish Journal of Electrical Engineering and Computer Sciences

System dynamics (SD) is a simulation-based approach for analyzing feedback-rich systems. An ideal SD modeling cycle requires evaluating the qualitative pattern characteristics of a large set of time series model output for testing, validation, scenario analysis, and policy analysis purposes. This traditionally requires expert judgement, which limits the extent of experimentation due to time constraints. Although time series recognition approaches can help to automate such an evaluation, utilization of them has been limited to a hidden Markov model classifier, namely the Indirect Structure Testing Software (ISTS) algorithm. Despite being used within several automated model-analysis tools, ISTS has several shortcomings. In …

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Fitting A Recurrent Dynamical Neural Network To Neural Spiking Data: Tackling The Sigmoidal Gain Function Issues, Reşat Özgür Doruk Jan 2019

Fitting A Recurrent Dynamical Neural Network To Neural Spiking Data: Tackling The Sigmoidal Gain Function Issues, Reşat Özgür Doruk

Turkish Journal of Electrical Engineering and Computer Sciences

This is a continuation of a recent study (Doruk RO, Zhang K. Fitting of dynamic recurrent neural network models to sensory stimulus-response data. J Biol Phys 2018; 44: 449-469), where a continuous time dynamical recurrent neural network is fitted to neural spiking data. In this research, we address the issues arising from the inclusion of sigmoidal gain function parameters to the estimation algorithm. The neural spiking data will be obtained from the same model as that of Doruk and Zhang, but we propose a different model for identification. This will also be a continuous time recurrent neural network, but with …

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Hybrid Control Of Five-Phase Permanent Magnet Synchronous Machine Using Space Vector Modulation, Djamel Difi, Khaled Halbaoui, Djamel Boukhetala Jan 2019

Hybrid Control Of Five-Phase Permanent Magnet Synchronous Machine Using Space Vector Modulation, Djamel Difi, Khaled Halbaoui, Djamel Boukhetala

Turkish Journal of Electrical Engineering and Computer Sciences

This paper aims to study the hybrid control of a five-phase permanent-magnet synchronous machine improved by the space vector modulation (SVM) technique. The torque ripples and currents will therefore be reduced. This control is based on the theory of hybrid dynamic systems (HDS), its discrete component is the voltage inverter which has a finite number of states controlling the continuous component that represents the machine. The results of the simulation made on MATLAB/Simulink are presented and discussed in order to check the performance of the strategy of the studied control. They show, in particular, the main advantages of this control …

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Characterization Of A High-Speed Radio-Frequency Sampling And Demultiplexing Circuit Based On The Cascade Connection Of Pin Photodiodes, Carlos Villa Angulo, Ivan O. Hernandez-Fuentes, Ricardo Morales-Carbajal, Rafael Villa-Angulo, Jose R. Villa-Angulo Jan 2019

Characterization Of A High-Speed Radio-Frequency Sampling And Demultiplexing Circuit Based On The Cascade Connection Of Pin Photodiodes, Carlos Villa Angulo, Ivan O. Hernandez-Fuentes, Ricardo Morales-Carbajal, Rafael Villa-Angulo, Jose R. Villa-Angulo

Turkish Journal of Electrical Engineering and Computer Sciences

Herein, we apply theoretical models to characterize the transfer function and frequency response of a complex optoelectronic circuit that comprises a primary ultrafast sampling circuit followed by a cascade connection of \textsl{N} demultiplexing stages. The successive radio-frequency optoelectronic samplers were based on the cascade connection of positive-intrinsic-negative-photodiodes (PIN-PDs). We developed a procedure to calculate the principal design parameters that allows us to use optical power for each sampling and demultiplexing stage, such that the circuit can be designed based on the application requirements. The results obtained from the theoretical models were compared with the measurements obtained from the 2.5 GS …

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Design And Development Of A Stewart Platform Assisted And Navigated Transsphenoidal Surgery, Selçuk Ki̇zi̇r, Zafer Bi̇ngül Jan 2019

Design And Development Of A Stewart Platform Assisted And Navigated Transsphenoidal Surgery, Selçuk Ki̇zi̇r, Zafer Bi̇ngül

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, technical details of a Stewart platform (SP) based robotic system as an endoscope positioner and holder for endoscopic transsphenoidal surgery are presented. Inverse and forward kinematics, full dynamics, and the Jacobian matrix of the robotic system are derived and simulated in MATLAB/Simulink. The required control structure for the trajectory and position control of the SP is developed and verified by several experiments. The robotic system can be navigated using a six degrees of freedom (DOF) joystick and a haptic device with force feedback. Position and trajectory control of the SP in the joint space is achieved using …

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Multi-Objective Design Optimization Of A Permanent Magnet Axial Flux Eddy Current Brake, Rasul Tarvirdilu Asl, Hüseyi̇n Murat Yüksel, Ozan Keysan Jan 2019

Multi-Objective Design Optimization Of A Permanent Magnet Axial Flux Eddy Current Brake, Rasul Tarvirdilu Asl, Hüseyi̇n Murat Yüksel, Ozan Keysan

Turkish Journal of Electrical Engineering and Computer Sciences

The main aim of this study is to optimize an axial flux eddy current damper to be used in a specific aviation application. Eddy current dampers are more advantageous compared to conventional mechanical dampers as they are maintenance-free due to contactless structure and have higher reliability, which is very desirable in aerospace applications. An initial eddy current brake prototype is manufactured and the test results are used to verify the 3-D finite element simulations. The effect of temperature on the brake performance is investigated. Finally, a multiobjective genetic algorithm optimization is applied to find the optimum pole number and geometric …

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A Study On Application Container Resource Efficiency, Özmen Emre Demi̇rkol, Cemi̇l Öz, Aşkin Demi̇rkol Jan 2019

A Study On Application Container Resource Efficiency, Özmen Emre Demi̇rkol, Cemi̇l Öz, Aşkin Demi̇rkol

Turkish Journal of Electrical Engineering and Computer Sciences

Nowadays, the IT service environment develops in a dynamic, rapid, and unpredictable way. Microservices and application containers in this process have a significant impact on new generation IT service models. The fact that they have important capabilities such as modelability, presentability as service, and restructurability, are reasons for preferring them in many areas. Moreover, microservices can meet various needs of IT personnel. As it is known, all server system components, such as CPU, network, hard-drive I/O, affect energy consumption. At this point, microservices also play an important mediator role in resource management. Energy consumption of microservice-based applications is lower than …

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A Comparative Study Of Author Gender Identification, Tuğba Yildiz Jan 2019

A Comparative Study Of Author Gender Identification, Tuğba Yildiz

Turkish Journal of Electrical Engineering and Computer Sciences

In recent years, author gender identification has gained considerable attention in the fields of information retrieval and computational linguistics. In this paper, we employ and evaluate different learning approaches based on machine learning (ML) and neural network language models to address the problem of author gender identification. First, several ML classifiers are applied to the features obtained by bag-of-words. Secondly, datasets are represented by a low-dimensional real-valued vector using Word2vec, GloVe, and Doc2vec, which are on par with ML classifiers in terms of accuracy. Lastly, neural networks architectures, the convolution neural network and recurrent neural network, are trained and their …

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The Biobjective Multiarmed Bandit: Learning Approximate Lexicographic Optimal Allocations, Cem Teki̇n Jan 2019

The Biobjective Multiarmed Bandit: Learning Approximate Lexicographic Optimal Allocations, Cem Teki̇n

Turkish Journal of Electrical Engineering and Computer Sciences

We consider a biobjective sequential decision-making problem where an allocation (arm) is called $\epsilon$ lexicographic optimal if its expected reward in the first objective is at most $\epsilon$ smaller than the highest expected reward, and its expected reward in the second objective is at least the expected reward of a lexicographic optimal arm. The goal of the learner is to select arms that are $\epsilon$ lexicographic optimal as much as possible without knowing the arm reward distributions beforehand. For this problem, we first show that the learner's goal is equivalent to minimizing the $\epsilon$ lexicographic regret, and then, propose a …

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Multiscanning Mode Laser Scanning Confocal Microscopy System, Mert Aktürk, Gökhan Gümüş, Baykal Sarioğlu, Yi̇ği̇t Dağhan Gökdel Jan 2019

Multiscanning Mode Laser Scanning Confocal Microscopy System, Mert Aktürk, Gökhan Gümüş, Baykal Sarioğlu, Yi̇ği̇t Dağhan Gökdel

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, a table-top, reflective mode, laser scanning confocal microscopy system that is capable of scanning the target specimen alternately through various scanning devices and methods is proposed. We have developed a laser scanning confocal microscopy system to utilize combinations of various scanning devices and methods and to be able to characterize the optical performance of different scanners and micromirrors that are frequently used in scanning microscopy systems such as multiphoton microscopy, optical coherence tomography, or confocal microscopy. By integrating the scanner to be characterized on the same optical path with a galvanometric scan mirror, which is the conventional …

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Prediction Of Preference And Effect Of Music On Preference: A Preliminary Study On Electroencephalography From Young Women, Bülent Yilmaz, Cengi̇z Gazeloğlu, Fati̇h Altindi̇ş Jan 2019

Prediction Of Preference And Effect Of Music On Preference: A Preliminary Study On Electroencephalography From Young Women, Bülent Yilmaz, Cengi̇z Gazeloğlu, Fati̇h Altindi̇ş

Turkish Journal of Electrical Engineering and Computer Sciences

Neuromarketing is the application of the neuroscientific approaches to analyze and understand economically relevant behavior. In this study, the effect of loud and rhythmic music in a sample neuromarketing setup is investigated. The second aim was to develop an approach in the prediction of preference using only brain signals. In this work, 19-channel EEG signals were recorded and two experimental paradigms were implemented: no music/silence and rhythmic, loud music using a headphone, while viewing women shoes. For each 10-sec epoch, normalized power spectral density (PSD) of EEG data for six frequency bands was estimated using the Burg method. The effect …

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A New Spectral Estimation-Based Feature Extraction Method For Vehicle Classification In Distributed Sensor Networks, Erdem Köse, Ali̇ Köksal Hocaoğlu Jan 2019

A New Spectral Estimation-Based Feature Extraction Method For Vehicle Classification In Distributed Sensor Networks, Erdem Köse, Ali̇ Köksal Hocaoğlu

Turkish Journal of Electrical Engineering and Computer Sciences

Ground vehicle detection and classification with distributed sensor networks is of growing interest for border security. Different sensing modalities including electro-optical, seismic, and acoustic were evaluated individually and in combination to develop a more efficient system. Despite previous works that mostly studied frequency-domain features and acoustic sensors, in this work we analyzed the classification performance for both frequency and time-domain features and seismic and acoustic modalities. Despite their infrequent use, we show that when fused with frequency-domain features, time-domain features improve the classification performance and reduce the false positive rate, especially for seismic signals. We investigated the performance of seismic …

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Hybrid Self-Controlled Precharge-Free Cam Design For Low Power And High Performance, V V Satyanarayana Satti, Sridevi Sriadibhatla Jan 2019

Hybrid Self-Controlled Precharge-Free Cam Design For Low Power And High Performance, V V Satyanarayana Satti, Sridevi Sriadibhatla

Turkish Journal of Electrical Engineering and Computer Sciences

Content-addressable memory (CAM) is a prominent hardware for high-speed lookup search, but consumes larger power. Traditional NOR and NAND match-line (ML) architectures suffer from a short circuit current path sharing and charge sharing respectively during precharge. The recently proposed precharge-free CAM suffers from high search delay and the subsequently proposed self-controlled precharge-free CAM suffers from high power consumption. This paper presents a hybrid self-controlled precharge-free (HSCPF) CAM architecture, which uses a novel charge control circuitry to reduce search delay as well as power consumption. The proposed and existing CAM ML architectures were developed using CMOS 45nm technology node with a …

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Structure Tensor Adaptive Total Variation For Image Restoration, Surya Prasath, Dang Nh Thanh Jan 2019

Structure Tensor Adaptive Total Variation For Image Restoration, Surya Prasath, Dang Nh Thanh

Turkish Journal of Electrical Engineering and Computer Sciences

Image denoising and restoration is one of the basic requirements in many digital image processing systems. Variational regularization methods are widely used for removing noise without destroying edges that are important visual cues. This paper provides an adaptive version of the total variation regularization model that incorporates structure tensor eigenvalues for better edge preservation without creating blocky artifacts associated with gradient-based approaches. Experimental results on a variety of noisy images indicate that the proposed structure tensor adaptive total variation obtains promising results and compared with other methods, gets better structure preservation and robust noise removal.

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Polyhedral Conic Kernel-Like Functions For Svms, Gürkan Öztürk, Emre Çi̇men Jan 2019

Polyhedral Conic Kernel-Like Functions For Svms, Gürkan Öztürk, Emre Çi̇men

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, we propose a new approach that can be used as a kernel-like function for support vector machines (SVMs) in order to get nonlinear classification surfaces. We combined polyhedral conic functions (PCFs) with the SVM method. To get nonlinear classification surfaces, kernel functions are used with SVMs. However, the parameter selection of the kernel function affects the classification accuracy. Generally, in order to get successful classifiers which can predict unknown data accurately, best parameters are explored with the grid search method which is computationally expensive. We solved this problem with the proposed method. There is no need to …

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Power Quality Improvement Of Smart Microgrids Using Ems-Based Fuzzy Controlled Upqc, Ahmed A. Hossam-Eldin, Ahmed A. Mansour, Mohammed El-Gamal, Karim H. Youssef Jan 2019

Power Quality Improvement Of Smart Microgrids Using Ems-Based Fuzzy Controlled Upqc, Ahmed A. Hossam-Eldin, Ahmed A. Mansour, Mohammed El-Gamal, Karim H. Youssef

Turkish Journal of Electrical Engineering and Computer Sciences

The prevalent power quality problems in smart microgrids and power distribution systems are voltage sag, voltage swell, and harmonic distortion. The achievement of pure sinusoidal waveform with proper magnitude and phase is currently a great research and development concern. The aim of this paper is to evaluate and mitigate the smart microgrid harmonics, voltage sag, and voltage swell throughout a 24-h cycle, taking into consideration the variation in solar power generation due to changes in irradiation received by photovoltaic cells, the variation in wind power generation due to changes in wind speed, and the variation of linear and nonlinear load …

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A Fast And Memory-Efficient Two-Pass Connected-Component Labeling Algorithm For Binary Images, Bilal Bataineh Jan 2019

A Fast And Memory-Efficient Two-Pass Connected-Component Labeling Algorithm For Binary Images, Bilal Bataineh

Turkish Journal of Electrical Engineering and Computer Sciences

Connected-component labeling is an important process in image analysis and pattern recognition. It aims to deduct the connected components by giving a unique label value for each individual component. Many algorithms have been proposed, but they still face several problems such as slow execution time, falling in the pipeline, requiring a huge amount of memory with high resolution, being noisy, and giving irregular images. In this work, a fast and memory-efficient connected-component labeling algorithm for binary images is proposed. The proposed algorithm is based on a new run-base tracing method with a new resolving process to find the final equivalent …

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A Novel Accuracy Assessment Model For Video Stabilization Approaches Based On Background Motion, Md Alamgir Hossain, Tien-Dung Nguyen, Eui Nam Huh Jan 2019

A Novel Accuracy Assessment Model For Video Stabilization Approaches Based On Background Motion, Md Alamgir Hossain, Tien-Dung Nguyen, Eui Nam Huh

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we propose a new accuracy measurement model for the video stabilization method based on background motion that can accurately measure the performance of the video stabilization algorithm. Undesired residual motion present in the video can quantitatively be measured by the pixel by pixel background motion displacement between two consecutive background frames. First of all, foregrounds are removed from a stabilized video, and then we find the two-dimensional flow vectors for each pixel separately between two consecutive background frames. After that, we calculate a Euclidean distance between these two flow vectors for each pixel one by one, which …

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A Polarity Calculation Approach For Lexicon-Based Turkish Sentiment Analysis, Gökhan Yurtalan, Murat Koyuncu, Çi̇ğdem Turhan Jan 2019

A Polarity Calculation Approach For Lexicon-Based Turkish Sentiment Analysis, Gökhan Yurtalan, Murat Koyuncu, Çi̇ğdem Turhan

Turkish Journal of Electrical Engineering and Computer Sciences

Sentiment analysis attempts to resolve the senses or emotions that a writer or speaker intends to send across to the people about an object or event. It generally uses natural language processing and/or artificial intelligence techniques for processing electronic documents and mining the opinion specified in the content. In recent years, researchers have conducted many successful sentiment analysis studies for the English language which consider many words and word groups that set emotion polarities arising from the English grammar structure, and then use datasets to test their performance. However, there are only a limited number of studies for the Turkish …

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Robust Compressed Domain Watermarking Algorithm For Video Protection And Authentication In Noisy Channels, Naveen Cheggoju, Vishal Satpute Jan 2019

Robust Compressed Domain Watermarking Algorithm For Video Protection And Authentication In Noisy Channels, Naveen Cheggoju, Vishal Satpute

Turkish Journal of Electrical Engineering and Computer Sciences

This paper introduces a robust and noise-resilient compressed domain video watermarking technique for data authentication and copyright protection. In recent years, watermarking has emerged as an essential technique to be equipped with data transmission. The main challenge pertaining to transmission is to protect the watermark from noise introduced by the channel. Here, we address this issue by watermark replication and by using the independent pass coding (INPAC) algorithm for compression. A replicated watermark is embedded into the video by the proposed blind video watermarking algorithm and then the watermarked video is compressed by the INPAC algorithm. The compressed video is …

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Speech Enhancement Using Adaptive Thresholding Based On Gamma Distribution Of Teager Energy Operated Intrinsic Mode Functions, Özkan Arslan, Erkan Zeki̇ Engi̇n Jan 2019

Speech Enhancement Using Adaptive Thresholding Based On Gamma Distribution Of Teager Energy Operated Intrinsic Mode Functions, Özkan Arslan, Erkan Zeki̇ Engi̇n

Turkish Journal of Electrical Engineering and Computer Sciences

This paper introduces a new speech enhancement algorithm based on the adaptive threshold of intrinsic mode functions (IMFs) of noisy signal frames extracted by empirical mode decomposition. Adaptive threshold values are estimated by using the gamma statistical model of Teager energy operated IMFs of noisy speech and estimated noise based on symmetric Kullback--Leibler divergence. The enhanced speech signal is obtained by a semisoft thresholding function, which is utilized by threshold IMF coefficients of noisy speech. The method is tested on the NOIZEUS speech database and the proposed method is compared with wavelet-shrinkage and EMD-shrinkage methods in terms of segmental SNR …

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Improving Undersampling-Based Ensemble With Rotation Forest For Imbalanced Problem, Huaping Guo, Xiaoyu Diao, Hongbing Liu Jan 2019

Improving Undersampling-Based Ensemble With Rotation Forest For Imbalanced Problem, Huaping Guo, Xiaoyu Diao, Hongbing Liu

Turkish Journal of Electrical Engineering and Computer Sciences

As one of the most challenging and attractive issues in pattern recognition and machine learning, the imbalanced problem has attracted increasing attention. For two-class data, imbalanced data are characterized by the size of one class (majority class) being much larger than that of the other class (minority class), which makes the constructed models focus more on the majority class and ignore or even misclassify the examples of the minority class. The undersampling-based ensemble, which learns individual classifiers from undersampled balanced data, is an effective method to cope with the class-imbalance data. The problem in this method is that the size …

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Online Network Coding-Based Multicast Routing In Multichannel Multiradio Wireless Mesh Networks, Leili Farzinvash Jan 2019

Online Network Coding-Based Multicast Routing In Multichannel Multiradio Wireless Mesh Networks, Leili Farzinvash

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we consider the problem of online multicast routing in multichannel multiradio wireless mesh networks (WMNs). We propose an efficient online algorithm, namely zone-based multicast routing (ZBMR), which exploits network coding and wireless broadcast advantage. In the proposed algorithm, to investigate the acceptance of an arrived session in polynomial time, the WMN is divided into some zones. The derived zones are processed sequentially, where the zone processing is defined as connecting the receivers in a given zone to the session. The main challenge in this scheme is to enable data transmission to the receivers in each zone. If …

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An Improved Form Of The Ant Lion Optimization Algorithm For Image Clustering Problems, Meti̇n Toz Jan 2019

An Improved Form Of The Ant Lion Optimization Algorithm For Image Clustering Problems, Meti̇n Toz

Turkish Journal of Electrical Engineering and Computer Sciences

This paper proposes an improved form of the ant lion optimization algorithm (IALO) to solve image clustering problem. The improvement of the algorithm was made using a new boundary decreasing procedure. Moreover, a recently proposed objective function for image clustering in the literature was also improved to obtain well-separated clusters while minimizing the intracluster distances. In order to accurately demonstrate the performances of the proposed methods, firstly, twenty-three benchmark functions were solved with IALO and the results were compared with the ALO and a chaos-based ALO algorithm from the literature. Secondly, four benchmark images were clustered by IALO and the …

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A Hybrid Model For The Prediction Of Aluminum Foil Output Thickness In Cold Rolling Process, Ali̇ Öztürk, Ri̇fat Şeherli̇ Jan 2019

A Hybrid Model For The Prediction Of Aluminum Foil Output Thickness In Cold Rolling Process, Ali̇ Öztürk, Ri̇fat Şeherli̇

Turkish Journal of Electrical Engineering and Computer Sciences

This study proposes a hybrid model composed of multiple prediction algorithms and an autoregressive moving average (ARMA) module for the thickness prediction. In order to attain higher accuracy, the prediction algorithms were globally combined by simple voting to reduce the effect of the inductive bias imposed by each algorithm on the dataset. The global multiexpert combination (GMEC) system included the multilayer perceptron neural network (MLPNN), radial basis function network (RBFN), multiple linear regression (MLR), and support vector machines (SVM) algorithms. The proposed hybrid model extends the GMEC system by integrating an ARMA module for the output. On the test dataset, …

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