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Articles 1771 - 1800 of 10319
Full-Text Articles in Physical Sciences and Mathematics
Automated Classification Of Bi-Rads In Textual Mammography Reports, Mostafa Boroumandzadeh, Elham Parvinnia
Automated Classification Of Bi-Rads In Textual Mammography Reports, Mostafa Boroumandzadeh, Elham Parvinnia
Turkish Journal of Electrical Engineering and Computer Sciences
The main purpose of this paper is to process key information in medical text records and also classifypatients, per different levels of breast imaging-reporting and data system (BI-RADS). The BI-RADS is a scheme for thestandardization of breast imaging reports. Therefore, medical text mining is employed to classify mammography reportssupported BI-RADS. In this research, a new method is proposed for automated BI-RADS classifications extraction fromtextual reports and improves the therapeutic procedures. At first, a mammography lexicon is employed for choosingkeywords from medical text reports. Word2vec and term frequency inverse document frequency (TFIDF) techniques areused for extracting features, finally, they are combined …
Improvements Of Torque Ripple Reduction In Dtc Im Drive Witharbitrary Number Of Voltage Intensities And Automatic Algorithm Modification, Marko Rosic, Sanja Antic, Milan Bebic
Improvements Of Torque Ripple Reduction In Dtc Im Drive Witharbitrary Number Of Voltage Intensities And Automatic Algorithm Modification, Marko Rosic, Sanja Antic, Milan Bebic
Turkish Journal of Electrical Engineering and Computer Sciences
Techniques of direct torque control (DTC) are very common in high-performance electric motor drives.Retaining the good features of the conventional DTC and reducing torque ripple have been the subject of many years ofresearch work on improving these algorithms. This paper presents the DTC algorithm with discretized voltage vectorsbased on the use of conventional switching table (ST-DTC). This algorithm enables a significant torque ripple reductionby defining the corresponding number of the given voltage intensity while retaining calculation simplicity and fast torqueresponse typical of the ST-DTC algorithms. The proposed algorithm has the ability for its automatic modificationdepending on the defined number of …
An Adversarial Framework For Open-Set Human Action Recognition Usingskeleton Data, Özge Özti̇mur Karadağ
An Adversarial Framework For Open-Set Human Action Recognition Usingskeleton Data, Özge Özti̇mur Karadağ
Turkish Journal of Electrical Engineering and Computer Sciences
Human action recognition is a fundamental problem which is applied in various domains, and it is widelystudied in the literature. Majority of the studies model action recognition as a closed-set problem. However, in real-life applications it usually arises as an open-set problem where a set of actions are not available during training butare introduced to the system during testing. In this study, we propose an open-set action recognition system, humanaction recognition and novel action detection system (HARNAD), which consists of two stages and uses only 3D skeletoninformation. In the first stage, HARNAD recognizes a given action and in the second …
A Multiple Sensor Fusion Based Drift Compensation Algorithm For Mecanumwheeled Mobile Robots, Abdurrahman Halabi̇, Mert Ezi̇m, Kansu Oğuz Canbek, Abdurrahman Eray Baran
A Multiple Sensor Fusion Based Drift Compensation Algorithm For Mecanumwheeled Mobile Robots, Abdurrahman Halabi̇, Mert Ezi̇m, Kansu Oğuz Canbek, Abdurrahman Eray Baran
Turkish Journal of Electrical Engineering and Computer Sciences
This paper investigates a multiple sensor fusion based drift compensation technique for a mecanum wheeledmobile robot platform. The mobile robot is equipped with high-precision encoders integrated to the wheels and fouraccelerometers placed on its chassis. The proposed algorithm combines the information from the encoders and theacceleration sensors to estimate the total drift in the acceleration dimension. The inner loop controller is designedutilizing a disturbance-observer-based acceleration control structure which is blind against the slipping motion of thewheels. The estimated drift acceleration from the sensor fusion is then mapped back to the joint space of the robot andused as additional compensation over …
Energy-Efficient Virtual Infrastructure Based Geo-Nested Routing Protocol Forwireless Sensor Networks, Baranidharan Varadharajan, Sivaradje Gopalakrishnan, Kiruthiga Varadharajan, Karthikeyan Mani, Sathishkumar Kutralingam
Energy-Efficient Virtual Infrastructure Based Geo-Nested Routing Protocol Forwireless Sensor Networks, Baranidharan Varadharajan, Sivaradje Gopalakrishnan, Kiruthiga Varadharajan, Karthikeyan Mani, Sathishkumar Kutralingam
Turkish Journal of Electrical Engineering and Computer Sciences
The wireless sensor networks (WSN) are comprised of hundreds to thousands of compact and battery-operated sensor nodes. The deployed sensor nodes are widely used to sense the physical changes in the environment,which collect, aggregate, and transmit the information as data packets or static sink or monitoring station. Thedata transmission is very challenging under some extreme environments and applications. The efficient way of datatransmission is achieved by designing an energy-efficient routing protocol. The position of the sink nodes is broadcasted periodically to all other sensor nodes to forward the sensed data to the monitoring system or sink. The frequentbroadcasting of the …
Multidirectional Power Flow In Three-Port Isolated Dc-Dc Converter For Multiplebattery Stacks, Chandra Sekhar Nalamati, Niranjan Kumar, Rajesh Gupta
Multidirectional Power Flow In Three-Port Isolated Dc-Dc Converter For Multiplebattery Stacks, Chandra Sekhar Nalamati, Niranjan Kumar, Rajesh Gupta
Turkish Journal of Electrical Engineering and Computer Sciences
The advances in the field of power electronics have created a superior platform for interfacing clean renewableresources with the ever-growing energy storage technology. In this paper, a multidirectional power flow operation in thethree-port isolated DC-DC converter (TBDC) topology has been demonstrated for interfacing different battery energystorage sections to increase the system reliability. Comparison of multiple battery integration with dual active bridge andTBDC has been presented. Converter analysis has been conducted using the Fourier series harmonic model and converterloss calculation is also presented. Power flow controller has been proposed for closed-loop control of the TBDC. Theperformance of the converter has been …
Optimal Planning Dg And Bes Units In Distribution System Consideringuncertainty Of Power Generation And Time-Varying Load, Mansur Khasanov, Salah Kamel, Ayman Awad, Francisco Jurado
Optimal Planning Dg And Bes Units In Distribution System Consideringuncertainty Of Power Generation And Time-Varying Load, Mansur Khasanov, Salah Kamel, Ayman Awad, Francisco Jurado
Turkish Journal of Electrical Engineering and Computer Sciences
Global environmental problems associated with traditional energy generation have led to a rapid increasein the use of renewable energy sources (RES) in power systems. The integration of renewable energy technologiesis commercially available nowadays, and the most common of such RES technology is photovoltaic (PV). This paperproposes an application of hybrid teaching-learning and artificial bee colony (TLABC) technique for determining theoptimal allocation of PV based distributed generation (DG) and battery energy storage (BES) units in the distributionsystem (DS) with the aim of minimizing the total power losses. Besides, some potential nodes identified by the powerloss sensitivity factor (PLSF). Thereupon TLABC is …
Dynamic Issue Queue Capping For Simultaneous Multithreaded Processors, Merve Güney, Büşra Kuru, Sercan Sari, İsa Ahmet Güney, Gürhan Küçük
Dynamic Issue Queue Capping For Simultaneous Multithreaded Processors, Merve Güney, Büşra Kuru, Sercan Sari, İsa Ahmet Güney, Gürhan Küçük
Turkish Journal of Electrical Engineering and Computer Sciences
A simultaneous multithreaded (SMT) processor mixes multiple instruction streams in its superscalar out-of-order execution core for higher throughput. To achieve this, a superscalar processor is modified in such a way that someof its resources are duplicated and the rest is shared among multiple threads. The issue queue (IQ), which holds allwaiting instructions until they become ready and scheduled for execution, is among these shared resources. A baselineunmanaged IQ can give an unexpectedly low performance since a hungry thread can tie up most of the IQ entries.This type of scenario is also worse in terms of the fairness metric since some …
An Evolutionary-Based Image Classification Approach Through Facial Attributes, Seli̇m Yilmaz, Cemi̇l Zalluhoğlu
An Evolutionary-Based Image Classification Approach Through Facial Attributes, Seli̇m Yilmaz, Cemi̇l Zalluhoğlu
Turkish Journal of Electrical Engineering and Computer Sciences
With the recent developments in technology, there has been a significant increase in the studies on analysisof human faces. Through automatic analysis of faces, it is possible to know the gender, emotional state, and even theidentity of people from an image. Of them, identity or face recognition has became the most important task whichhas been studied for a long time now as it is crucial to take measurements for public security, credit card verification,criminal identification, and the like. In this study, we have proposed an evolutionary-based framework that relies ongenetic programming algorithm to evolve a binary- and multilabel image classifier …
Swft: Subbands Wavelet For Local Features Transform Descriptor For Cornealdiseases Diagnosis, Samer Al-Salihi, Sezgi̇n Aydin, Nebras Hussein
Swft: Subbands Wavelet For Local Features Transform Descriptor For Cornealdiseases Diagnosis, Samer Al-Salihi, Sezgi̇n Aydin, Nebras Hussein
Turkish Journal of Electrical Engineering and Computer Sciences
Human cornea is the front see-through shield of the eye. It refracts light onto the retina to induce vision.Therefore, any defect in the cornea may lead to vision disturbance. This deficiency is estimated by sets of topographicalimages measured, and assessed by an ophthalmologist. Consequently, an important priority is the early and accuratediagnosis of diseases that may affect corneal integrity through the use of machine learning algorithms. Images producedby a Pentacam device can be subjected to rotation or some distortion during acquisition; therefore, accurate diagnosisrequires the use of local features in the image. Accordingly, a new algorithm called subbands wavelet for …
Heuristic Based Binary Grasshopper Optimization Algorithm To Solve Unitcommitment Problem, Muhammad Shahid, Tahir Nadeem Malik, Ahsan Said
Heuristic Based Binary Grasshopper Optimization Algorithm To Solve Unitcommitment Problem, Muhammad Shahid, Tahir Nadeem Malik, Ahsan Said
Turkish Journal of Electrical Engineering and Computer Sciences
The unit commitment problem in power system is a highly nonlinear, nonconvex, multiconstrained, complex,highly dimensional, mixed integer and combinatorial generation selection problem. The phenomenon of committing anddecommitting represents a discrete problem that requires binary/discrete optimization techniques to tackle with unitcommitment optimization problem. The key functions of the unit commitment optimization problem involve decidingwhich units to commit and then to decide their optimum power (economic dispatch). This paper confers a binarygrasshopper optimization algorithm to solve the unit commitment optimization problem under multiple constraints.The grasshopper optimization algorithm is a metaheuristic, multiple solutions-based algorithm inspired by the naturalswarming behavior of grasshopper towards food. …
A Novel Pulse Plethysmograph Signal Analysis Method For Identification Of Myocardial Infarction, Dilated Cardiomyopathy, And Hypertension, Muhammad Umar Khan, Sumair Aziz
A Novel Pulse Plethysmograph Signal Analysis Method For Identification Of Myocardial Infarction, Dilated Cardiomyopathy, And Hypertension, Muhammad Umar Khan, Sumair Aziz
Turkish Journal of Electrical Engineering and Computer Sciences
Cardiac diseases (CDs) are one of the leading causes of the growing global mortality rate. Early detectionof CDs is necessary to avoid a high increase in the mortality rate. Machine learning-based computer-aided diagnosisof CDs using various physiological signals has recently been used by researchers. Since pulse plethysmograph (PuPG)signal contains a wealth of information about cardiac pathologies, therefore, this paper presents an expert system designfor the automatic diagnosis of cardiac disorders like hypertension, dilated cardiomyopathy and myocardial infarctionusing a novel fingertip PuPG signal analysis. The proposed system first performs signal denoising of raw PuPG sensordata using discrete wavelet transform (DWT). After …
A Step-Down Isolated Three-Phase Igbt Boost Pfc Rectifier Using A Novel Controlalgorithm With A Novel Start-Up Method, Hüseyi̇n Köse, Mehmet Ti̇mur Aydemi̇r
A Step-Down Isolated Three-Phase Igbt Boost Pfc Rectifier Using A Novel Controlalgorithm With A Novel Start-Up Method, Hüseyi̇n Köse, Mehmet Ti̇mur Aydemi̇r
Turkish Journal of Electrical Engineering and Computer Sciences
For some industrial converter applications such as battery chargers, a DC/DC converter is needed to stepdown the high DC (direct current) voltages generated by PWM (pulse with modulated) rectifiers to lower voltage levelssuch as 110V/220V. These both complicate the design and decrease the efficiency. In this paper, a novel topology thatincludes a step-down transformer and a novel control algorithm is proposed. The proposed current, which is synchronized,look-up table based, sinusoidal PWM control method (CS-LUT-SPWM method) using switching frequency-orientedsynchronization (SWFOS) results in a very fast PWM generation and stable operation. Finally, a new thyristor-basedstart-up circuit providing safe operation when there is …
Neural Relation Extraction: A Review, Mehmet Aydar, Özge Bozal, Furkan Özbay
Neural Relation Extraction: A Review, Mehmet Aydar, Özge Bozal, Furkan Özbay
Turkish Journal of Electrical Engineering and Computer Sciences
Neural relation extraction discovers semantic relations between entities from unstructured text using deeplearning methods. In this study, we make a clear categorization of the existing relation extraction methods in termsof data expressiveness and data supervision, and present a comprehensive and comparative review. We describe theevaluation methodologies and the datasets used for model assessment. We explicitly state the common challenges inrelation extraction task and point out the potential of the pretrained models to solve them. Accordingly, we investigateadditional research directions and improvement ideas in this field.
A Novel Approach Of Order Diminution Using Time Moment Concept With Routharray And Salp Swarm Algorithm, Nafees Ahamad, Afzal Sikander
A Novel Approach Of Order Diminution Using Time Moment Concept With Routharray And Salp Swarm Algorithm, Nafees Ahamad, Afzal Sikander
Turkish Journal of Electrical Engineering and Computer Sciences
In control engineering, there may be two systems that have the same input-output characteristic with differentdegrees of complexity. This concept leads to order diminution(OD) of a large scale system. In this article, the authorspropose a new hybrid order diminution technique based on the time moment matching method with the Routh arrayconcept and a recently developed fast and accurate salp swarm optimization (SSO) technique. The proposed methodcombines the advantages of both the classical method of OD and the optimization technique. The unknown coe?icient ofthe divisor of the reduced system is obtained by exploring the time moment matching methodology with the Routh …
Pfecc: A Precise Feedback-Based Explicit Congestion Control Algorithm In Nameddata Networking, Hui Li
Pfecc: A Precise Feedback-Based Explicit Congestion Control Algorithm In Nameddata Networking, Hui Li
Turkish Journal of Electrical Engineering and Computer Sciences
Named data networking (NDN), as a future Internet architecture that is a promising alternative to TCP/IPnetworks, has the new features of connectionless, in-network cache, and hop-by-hop forwarding, which makes thecongestion control algorithms of traditional TCP/IP networks unable to be directly applied to NDN. In addition, sincethe optimal size of the sending window cannot be determined, the existing window-based congestion control algorithmsgenerally use the AIMD-like window adjustment algorithm, which cannot achieve the optimal throughput. In thispaper, we propose a precise feedback-based, multipath-aware congestion control algorithm PFECC, which is inspiredby Accel-Brake Control algorithm. PFECC considers the influence of Interest flows, uses a …
On The Outage Performance Of Swipt-Noma-Crs With Imperfect Sic And Csi, Ferdi̇ Kara
On The Outage Performance Of Swipt-Noma-Crs With Imperfect Sic And Csi, Ferdi̇ Kara
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, a nonorthogonal multiple access based cooperative relaying system (NOMA-CRS) is consideredto increase spectral efficiency. Besides, the simultaneous wireless information and power transfer (SWIPT) is proposedfor the relay in NOMA-CRS. In SWIPT-NOMA-CRS, three different energy harvesting (EH) protocols, power sharing(PS), time sharing (TS) and ideal protocols are implemented. The outage performances of the SWIPT-NOMA-CRSare studied for all three EH protocols. In the analysis, to represent practical/reasonable scenarios, imperfect successiveinterference canceler (SIC) and imperfect channel state information (CSI) are taken into consideration. The derivedoutage probability (OP) expressions are validated via computer simulations. Besides, the OP for the benchmark scheme,NOMA-CRS …
Subjective Analysis Of Social Distance Monitoring Using Yolo V3 Architecture Andcrowd Tracking System, Muhammed Murat Özbek, Mustafa Syed, İlkay Öksüz
Subjective Analysis Of Social Distance Monitoring Using Yolo V3 Architecture Andcrowd Tracking System, Muhammed Murat Özbek, Mustafa Syed, İlkay Öksüz
Turkish Journal of Electrical Engineering and Computer Sciences
The lethal infection, World Health Organization (WHO) reported coronavirus (COVID-19) as a pandemic.Lack of proper vaccine, low levels of immunity against COVID-19 has led to vulnerability of the human beings. Due tolack of efficient vaccine treatment, the only options left to fight against this pandemic are lockdown and social distance.This work offers an autonomous monitoring system on social distancing using deep learning techniques. The proposedarchitecture tracks the humans on roads and calculates their distance between each other. This surveillance detects thefurore violation of social distance utilizing CCTV cameras. The proposed framework uses YOLO v3 object-detectionmodel built on COCO dataset and …
An Adaptive Element Division Algorithm For Accurate Evaluation Of Singular Andnear Singular Integrals In 3d, Hakan Bayindir, Besi̇m Baranoğlu, Ali̇ Yazici
An Adaptive Element Division Algorithm For Accurate Evaluation Of Singular Andnear Singular Integrals In 3d, Hakan Bayindir, Besi̇m Baranoğlu, Ali̇ Yazici
Turkish Journal of Electrical Engineering and Computer Sciences
An adaptive algorithm for evaluation of singular and near singular integrals in 3D is presented. The algorithmis based on successive adaptive/selective subdivisions of the element until a prescribed error criteria is met. For evaluatingthe integrals in each subdivision, Gauss quadrature is applied. The method is computationally simple, memory efficientand can be applied for both triangular and quadrilateral elements, including the elements with nonplanar and/or curvedsurfaces. To assess the method, several examples are discussed. It has shown that the algorithm performs well forsingular and near-singular integral examples presented in the paper and evaluates the integrals with very high accuracy.
A Deep Neural Network Classifier For P300 Bci Speller Based On Cohen's Classtime-Frequency Distribution, Hamed Ghazikhani, Modjtaba Rouhani
A Deep Neural Network Classifier For P300 Bci Speller Based On Cohen's Classtime-Frequency Distribution, Hamed Ghazikhani, Modjtaba Rouhani
Turkish Journal of Electrical Engineering and Computer Sciences
This paper presents a new method of predicting the P300 component of an electroencephalography (EEG)signal to recognize the characters in a P300 brain-computer interface (BCI) speller accurately. This method consistsof a deep learning model and the nonlinear time-frequency features. It is believed that the combination of the deepmodel network and extracting the nonlinear features of the EEG led this research to a better prediction of the P300and, therefore, character recognition. Cohen's class distribution is used in order to extract the nonlinear features of theEEG. Evaluating all of the kernels, Butterworth found to be more informative and it produced better results. …
Relational-Grid-World: A Novel Relational Reasoning Environment And An Agentmodel For Relational Information Extraction, Faruk Küçüksubaşi, Eli̇f Sürer
Relational-Grid-World: A Novel Relational Reasoning Environment And An Agentmodel For Relational Information Extraction, Faruk Küçüksubaşi, Eli̇f Sürer
Turkish Journal of Electrical Engineering and Computer Sciences
Reinforcement learning (RL) agents are often designed specifically for a particular problem and they generallyhave uninterpretable working processes. Statistical methods-based agent algorithms can be improved in terms ofgeneralizability and interpretability using symbolic artificial intelligence (AI) tools such as logic programming. Inthis study, we present a model-free RL architecture that is supported with explicit relational representations of theenvironmental objects. For the first time, we use the PrediNet network architecture in a dynamic decision-making problemrather than image-based tasks, and multi-head dot-product attention network (MHDPA) as a baseline for performancecomparisons. We tested two networks in two environments -i.e., the baseline box-world environment and …
Sliding Mode Pll-Pdm Controller For Induction Heating System, Harun Özbay, Aki̇f Karafi̇l, Seli̇m Öncü
Sliding Mode Pll-Pdm Controller For Induction Heating System, Harun Özbay, Aki̇f Karafi̇l, Seli̇m Öncü
Turkish Journal of Electrical Engineering and Computer Sciences
In this study, a sliding mode controlled phase locked loop (SMC-PLL) was developed for induction heating(IH) applications with a resonant inverter. PLL applications are widely used in induction heating applications to achievezero voltage switching and zero current switching. In many PLL applications, the frequency tracking is too slow andunreliable. Therefore, a sliding mode controller was developed to provide robust and fast PLL. Furthermore, a pulsedensity modulation (PDM) control strategy was developed to work at the resonant frequency for all power levels. ThePDM power control is a good solution for the design of high-frequency inverters because of a great reduction of …
Efficient Power Macromodeling Approach For An Ip-Based Soc System Usingdiscrete Water Cycle Algorithm, Faisal Siddiq, Yaseer Arafat Durrani
Efficient Power Macromodeling Approach For An Ip-Based Soc System Usingdiscrete Water Cycle Algorithm, Faisal Siddiq, Yaseer Arafat Durrani
Turkish Journal of Electrical Engineering and Computer Sciences
Low-power consumption is becoming a crucial concern that cannot be neglected in system-on-chip (SoC) designs. Low-power solutions help designers to provide a powerful methodology to analyze, estimate, and optimize today's power concerns. Early estimation of power at a high level reduces the redesign cycle and turn-around time. Power dissipation is a function of input patterns and their characteristics. This paper describes a power estimation technique by using predefined statistical characteristics-based input patterns, which gives the average power dissipation of individual intellectual property (IP) blocks and interconnects/buses in an SoC system design. During the power estimation phase, the discrete water cycle …
The Effect Of Demand Response Control On Stability Delay Margins Of Loadfrequency Control Systems With Communication Time-Delays, Deni̇z Kati̇poğlu, Şahi̇n Sönmez, Saffet Ayasun, Ausnain Naveed
The Effect Of Demand Response Control On Stability Delay Margins Of Loadfrequency Control Systems With Communication Time-Delays, Deni̇z Kati̇poğlu, Şahi̇n Sönmez, Saffet Ayasun, Ausnain Naveed
Turkish Journal of Electrical Engineering and Computer Sciences
This paper studies the effect of dynamic demand response (DR) control on stability delay margins of load frequency control (LFC) systems including communication time-delays. A DR control loop is included in each control area, called as LFC-DR system and Rekasius substitution is utilized to identify stability margins for various proportionalintegral (PI) gains and participation ratios of the secondary and DR control loops. The purpose of Rekasius substitution technique is to obtain purely complex roots on the imaginary axis of the time-delayed LFC-DR system. This substitution first converts the characteristic equation of the LFC-DR system including delay-dependent exponential terms into an …
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 …
Using Eeg To Detect Driving Fatigue Based On Common Spatial Pattern Andsupport Vector Machine, Li Wang, David Johnson, Yingzi Lin
Using Eeg To Detect Driving Fatigue Based On Common Spatial Pattern Andsupport Vector Machine, Li Wang, David Johnson, Yingzi Lin
Turkish Journal of Electrical Engineering and Computer Sciences
To investigate the correlation between electroencephalogram (EEG) and driving fatigue states, this study used machine learning algorithms to detect driving fatigue based on EEG. 14 channels of EEG data were collected from thirty-four healthy subjects in this research at Northeastern University. Each subject participated in two scenarios (baseline and fatigue scenarios). Subjective ratings of fatigue levels were also obtained from the subjects using the NASA-Task Load Index (TLX). The common spatial pattern (CSP) algorithm was used to extract features from the raw EEG data. The support vector machine (SVM) was used as the classifier in the design of the machine …
A Geodesic Deployment And Radial Shaped Clustering (Rsc) Algorithm Withstatistical Aggregation In Sensor Networks, Lalitha Krishnasamy, Thangarajan Ramasamy, Rajesh Kumar Dhanaraj, Poongodi Chinnasamy
A Geodesic Deployment And Radial Shaped Clustering (Rsc) Algorithm Withstatistical Aggregation In Sensor Networks, Lalitha Krishnasamy, Thangarajan Ramasamy, Rajesh Kumar Dhanaraj, Poongodi Chinnasamy
Turkish Journal of Electrical Engineering and Computer Sciences
Wireless sensor networks (WSN) comprise a large number of connected tiny or small sensor devices to sense physical phenomenon. In WSN, prolonging the network's lifetime is a biggest challenge due to absence of power harvesting facility and irreplaceable batteries of the sensor devices. Clustering is one of the widely accepted and standard technique to solve the energy issues faced in WSN. In addition to clustering, the shape of the deployment area also plays the major role especially for large scale sensor deployment. This paper proposes a radial shaped clustering (RSC) algorithm with angular inclination routing. The radial shaped deployed area …
A Cross-Space Cascading Failure Hazard Assessment Method Consideringbetweenness Centrality And Power Loss, Ruzhi Xu, Dawei Chen, Qizhuo Zong, Jia Luo
A Cross-Space Cascading Failure Hazard Assessment Method Consideringbetweenness Centrality And Power Loss, Ruzhi Xu, Dawei Chen, Qizhuo Zong, Jia Luo
Turkish Journal of Electrical Engineering and Computer Sciences
In order to accurately assess the hazard caused by cross-space cascading failure in the cyber-physical power system, we propose a quantitative assessment method. This method builds a comprehensive framework of assessment that takes into account the betweenness centrality of attack graph and the consequences of failure. The betweenness centrality of each node in the attack graph is used to characterize the frequency of failure. By calculating the number of all nodes on each attack path, the frequency of a certain fault is calculated. The power loss of physical node caused by each cross-space cascading failure is used to characterize the …
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 …
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 …