Open Access. Powered by Scholars. Published by Universities.®

Engineering Commons™

Open Access. Powered by Scholars. Published by Universities.®

2019

Discipline
Institution
Keyword
Publication
Publication Type
File Type

Articles 10171 - 10200 of 10492

Full-Text Articles in Engineering

Approximation Of Planar Curves, Malik Zawwar Hussain, Ayesha Shakeel, Maria Hussain Jan 2019

Approximation Of Planar Curves, Malik Zawwar Hussain, Ayesha Shakeel, Maria Hussain

Turkish Journal of Electrical Engineering and Computer Sciences

In the present article, we have developed the $G^{2}$-approximation scheme for planar curves arising in science, engineering, computer-aided design, computer-aided manufacturing, and many other fields. The obtained results reveal that the proposed method is a significant addition to the approximation of planar curves. The method is illustrated using different numerical examples. The smaller absolute error confirms the applicability and efficiency of the proposed method.

Go to article

On Spectral Analysis Of The Internet Delay Space And Detecting Anomalous Routing Paths, Gonca Gürsun Jan 2019

On Spectral Analysis Of The Internet Delay Space And Detecting Anomalous Routing Paths, Gonca Gürsun

Turkish Journal of Electrical Engineering and Computer Sciences

Latency is one of the most critical performance metrics for a wide range of applications. Therefore, it is important to understand the underlying mechanisms that give rise to the observed latency values and diagnose the ones that are unexpectedly high. In this paper, we study the Internet delay space via robust principal component analysis (RPCA). Using RPCA, we show that the delay space, i.e. the matrix of measured round trip times between end hosts, can be decomposed into two components: the estimated latency between end hosts with respect to the current state of the Internet and the inflation on the …

Go to article

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 …

Go to article

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' …

Go to article

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 …

Go to article

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 …

Go to article

Graph Analysis Of Network Flow Connectivity Behaviors, Hangyu Hu, Xuemeng Zhai, Mingda Wang, Guangmin Hu Jan 2019

Graph Analysis Of Network Flow Connectivity Behaviors, Hangyu Hu, Xuemeng Zhai, Mingda Wang, Guangmin Hu

Turkish Journal of Electrical Engineering and Computer Sciences

Graph-based approaches have been widely employed to facilitate in analyzing network flow connectivity behaviors, which aim to understand the impacts and patterns of network events. However, existing approaches suffer from lack of connectivity-behavior information and loss of network event identification. In this paper, we propose network flow connectivity graphs (NFCGs) to capture network flow behavior for modeling social behaviors from network entities. Given a set of flows, edges of a NFCG are generated by connecting pairwise hosts who communicate with each other. To preserve more information about network flows, we also embed node-ranking values and edge-weight vectors into the original …

Go to article

Design And Fabrication Of A Dual-Polarized, Dual-Band Reflectarray Using Optimal Phase Distribution, Iman Aryanian, Arash Ahmadi, Mehdi Rabbani, Sina Hassibi, Majid Karimipour Jan 2019

Design And Fabrication Of A Dual-Polarized, Dual-Band Reflectarray Using Optimal Phase Distribution, Iman Aryanian, Arash Ahmadi, Mehdi Rabbani, Sina Hassibi, Majid Karimipour

Turkish Journal of Electrical Engineering and Computer Sciences

Two main factors limiting the reflectarray bandwidth are different phase slopes versus the frequency at every point on the aperture and the phase limitation of comprising elements at different frequencies. Considering these two factors, a novel design method is proposed to implement a dual-band, dual-polarized reflectarray antenna in X and Ku bands. An optimization algorithm is adopted to find the optimum phase for each unit cell on the reflectarray aperture. The best geometrical parameters of the phasing elements are suggested based on the phase variation of the element versus frequency and the element position with respect to the antenna feed. …

Go to article

A New Computer-Controlled Platform For Adc-Based True Random Number Generator And Its Applications, Selçuk Coşkun, İhsan Pehli̇van, Aki̇f Akgül, Bi̇lal Gürevi̇n Jan 2019

A New Computer-Controlled Platform For Adc-Based True Random Number Generator And Its Applications, Selçuk Coşkun, İhsan Pehli̇van, Aki̇f Akgül, Bi̇lal Gürevi̇n

Turkish Journal of Electrical Engineering and Computer Sciences

The basis of encryption techniques is random number generators (RNGs). The application areas of cryptology are increasing in number due to continuously developing technology, so the need for RNGs is increasing rapidly, too. RNGs can be divided into two categories as pseudorandom number generator (PRNGs) and true random number generator (TRNGs). TRNGs are systems that use unpredictable and uncontrollable entropy sources and generate random numbers. During the design of TRNGs, while analog signals belonging to the used entropy sources are being converted to digital data, generally comparators, flip-flops, Schmitt triggers, and ADCs are used. In this study, a computer-controlled new …

Go to article

Cost-Effective Telemetry For Energy Network Of An Electricity Distribution Company: Part I, Asim Zaheer Ud Din, Yasar Ayaz, Mian Ilyas Ahmad Ahmad, Momena Hasan, Salman Masaud, Naveed Muhammad Jan 2019

Cost-Effective Telemetry For Energy Network Of An Electricity Distribution Company: Part I, Asim Zaheer Ud Din, Yasar Ayaz, Mian Ilyas Ahmad Ahmad, Momena Hasan, Salman Masaud, Naveed Muhammad

Turkish Journal of Electrical Engineering and Computer Sciences

We present a novel application of radio frequency wireless mesh network and general packet radio service technologies in a telemetry solution to measure power flow in the energy network of an electricity distribution company. The telemetry solution utilizes some selected circuits of grid stations and calculates total power consumed, total power imported, and total power exported by the distribution company. The selection of circuits for sensors installation is the key for reducing solution cost as compared to the case when sensors are installed on all the power output points. The framework involves installation of specially developed energy sensors (smart energy …

Go to article

Prey-Predator Algorithm For Discrete Problems: A Case For Examination Timetabling Problem, Surafel Luleseged Tilahun Jan 2019

Prey-Predator Algorithm For Discrete Problems: A Case For Examination Timetabling Problem, Surafel Luleseged Tilahun

Turkish Journal of Electrical Engineering and Computer Sciences

The prey-predator algorithm is a metaheuristic algorithm inspired by the interaction between a predator and its prey. Initial solutions are put into three categories: the better performing solution as the best prey, the worst performing solution as a predator, and the rest as ordinary prey. The best prey totally focuses on exploiting its neighborhood while the predator explores the search space searching for a promising region in the search space. The ordinary prey will be affected by these two extreme search behaviors of exploration and exploitation. The algorithm has been tested and found to be effective in solving different problems …

Go to article

Optimal Range Of Loading For Operating A Fixed-Speed Wind Turbine Using A Self-Excited Induction Generator, Nassi̇m Iqteit, Gül Kurt, Beki̇r Çakir Jan 2019

Optimal Range Of Loading For Operating A Fixed-Speed Wind Turbine Using A Self-Excited Induction Generator, Nassi̇m Iqteit, Gül Kurt, Beki̇r Çakir

Turkish Journal of Electrical Engineering and Computer Sciences

In the present study, a new strategy of analysis was used to determine the optimal interval of a single-phase resistive load to operate a fixed-speed wind turbine. The essence of this optimal range is to enable the generator to have stable voltages and current balances, large power, and an acceptable frequency range, and also mitigate generator overheating. The generator windings and excitation capacitances were prepared according to the C-2C connection scheme with suitable values of excitation capacitances. The admittance matrix of the system was based on positive and negative sequence generator voltages and was calculated by symmetrical components theory. The …

Go to article

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 …

Go to article

Tapu: Test And Pick Up-Based $K$-Connectivity Restoration Algorithm For Wireless Sensor Networks, Vahi̇d Khali̇lpour Akram, Orhan Dağdevi̇ren Jan 2019

Tapu: Test And Pick Up-Based $K$-Connectivity Restoration Algorithm For Wireless Sensor Networks, Vahi̇d Khali̇lpour Akram, Orhan Dağdevi̇ren

Turkish Journal of Electrical Engineering and Computer Sciences

A $k$-connected wireless sensor network remains connected if any $k$-1 arbitrary nodes stop working. The aim of movement-assisted $k$-connectivity restoration is to preserve the $k$-connectivity of a network by moving the nodes to the necessary positions after possible failures in nodes. This paper proposes an algorithm named TAPU for $k$-connectivity restoration that guarantees the optimal movement cost. Our algorithm improves the time and space complexities of the previous approach (MCCR) in both best and worst cases. In the proposed algorithm, the nodes are classified into safe and unsafe groups. Failures of safe nodes do not change the $k$ value of …

Go to article

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 …

Go to article

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 …

Go to article

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 …

Go to article

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 …

Go to article

Automated Elimination Of Eog Artifacts In Sleep Eeg Using Regression Method, Mehmet Dursun, Seral Özşen, Sali̇h Güneş, Bayram Akdemi̇r, Şebnem Yosunkaya Jan 2019

Automated Elimination Of Eog Artifacts In Sleep Eeg Using Regression Method, Mehmet Dursun, Seral Özşen, Sali̇h Güneş, Bayram Akdemi̇r, Şebnem Yosunkaya

Turkish Journal of Electrical Engineering and Computer Sciences

Sleep electroencephalogram (EEG) signal is an important clinical tool for automatic sleep staging process. Sleep EEG signal is effected by artifacts and other biological signal sources, such as electrooculogram (EOG) and electromyogram (EMG), and since it is effected, its clinical utility reduces. Therefore, eliminating EOG artifacts from sleep EEG signal is a major challenge for automatic sleep staging. We have studied the effects of EOG signals on sleep EEG and tried to remove them from the EEG signals by using regression method. The EEG and EOG recordings of seven subjects were obtained from the Sleep Research Laboratory of Meram Medicine …

Go to article

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 …

Go to article

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 …

Go to article

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 …

Go to article

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 …

Go to article

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.

Go to article

A Generalized Switching Function-Based Discontinuous Space Vector Modulation Technique For Unbalanced Two-Phase Three-Leg Inverters, Watcharin Srirattanawichaikul Jan 2019

A Generalized Switching Function-Based Discontinuous Space Vector Modulation Technique For Unbalanced Two-Phase Three-Leg Inverters, Watcharin Srirattanawichaikul

Turkish Journal of Electrical Engineering and Computer Sciences

This paper presents a discontinuous space vector modulation technique for unbalanced two-phase three-leg inverters. This technique is based on the shift-angle and generalized modulation algorithm obtained for generating the unbalanced two-phase output voltage. Furthermore, the discontinuous switching sequence intends to improve the commutations of power switching devices in each inverter leg that achieves a minimum number of switching state changes in one sampling cycle. Therefore, the switch commutations can be reduced by one-third in one main period. The step-by-step procedure of the modulation algorithm for easy implementation in a digital control platform is discussed. The performance of the developed modulation …

Go to article

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 …

Go to article

A Kalman Filter Application For Rainfall Estimation Using Radar Reflectivity Measurements, Engi̇n Maşazade, Ali̇ Kemal Bakir, Pinar Kirci Jan 2019

A Kalman Filter Application For Rainfall Estimation Using Radar Reflectivity Measurements, Engi̇n Maşazade, Ali̇ Kemal Bakir, Pinar Kirci

Turkish Journal of Electrical Engineering and Computer Sciences

The rainfall amount observed at a given location mostly depend on the cloud density, which can be quantified with the reflectivity values observed by meteorology weather radars. In this study, we aim to estimate the rainfall amount using a Kalman filter with radar reflectivity measurements. We first assume that the amount of rainfall observed at automatic weather observation stations (AWOSs) are elements of an unknown state vector and consider the Kalman filter process model as the true rainfall amounts observed at these AWOSs over time. For the measurement model of the Kalman filter, we use the radar reflectivity values observed …

Go to article

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 …

Go to article

Probabilistic Small-Signal Stability Analysis Of Power System With Solar Farm Integration, Samundra Gurung, Sumate Naetiladdanon, Anawach Sangswang Jan 2019

Probabilistic Small-Signal Stability Analysis Of Power System With Solar Farm Integration, Samundra Gurung, Sumate Naetiladdanon, Anawach Sangswang

Turkish Journal of Electrical Engineering and Computer Sciences

Currently, large-scale solar farms are being rapidly integrated in electrical grids all over the world. However, the photovoltaic (PV) output power is highly intermittent in nature and can also be correlated with other solar farms located at different places. Moreover, the increasing PV penetration also results in large solar forecast error and its impact on power system stability should be estimated. The effects of these quantities on small-signal stability are difficult to quantify using deterministic techniques but can be conveniently estimated using probabilistic methods. For this purpose, the authors have developed a method of probabilistic analysis based on combined cumulant …

Go to article

An Improved Tree Model Based On Ensemble Feature Selection For Classification, Chandralekha M, Shenbagavadivu N Jan 2019

An Improved Tree Model Based On Ensemble Feature Selection For Classification, Chandralekha M, Shenbagavadivu N

Turkish Journal of Electrical Engineering and Computer Sciences

Researchers train and build specific models to classify the presence and absence of a disease and the accuracy of such classification models is continuously improved. The process of building a model and training depends on the medical data utilized. Various machine learning techniques and tools are used to handle different data with respect to disease types and their clinical conditions. Classification is the most widely used technique to classify disease and the accuracy of the classifier largely depends on the attributes. The choice of the attribute largely affects the diagnosis and performance of the classifier. Due to growing large volumes …

Go to article

First Prev Next Last