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- Classification (10)
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- Feature selection (7)
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- Feature extraction (6)
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- Sentiment analysis (3)
- Social media (3)
- Social networks (3)
- Voltage stability (3)
- Artificial neural networks (2)
Articles 31 - 60 of 335
Full-Text Articles in Physical Sciences and Mathematics
Probabilistic Small-Signal Stability Analysis Of Power System With Solar Farm Integration, Samundra Gurung, Sumate Naetiladdanon, Anawach Sangswang
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 …
An Improved Tree Model Based On Ensemble Feature Selection For Classification, Chandralekha M, Shenbagavadivu N
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 …
Robust Compressed Domain Watermarking Algorithm For Video Protection And Authentication In Noisy Channels, Naveen Cheggoju, Vishal Satpute
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 …
Speech Enhancement Using Adaptive Thresholding Based On Gamma Distribution Of Teager Energy Operated Intrinsic Mode Functions, Özkan Arslan, Erkan Zeki̇ Engi̇n
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 …
Farsi Document Image Recognition System Using Word Layout Signature, Cem Ergün, Sajedeh Norozpour
Farsi Document Image Recognition System Using Word Layout Signature, Cem Ergün, Sajedeh Norozpour
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, a new representation of Farsi words is proposed to present the keyword spotting problems in Farsi document image retrieval. In this regard, we define a signature for each Farsi word based on the word connected component layout. The mentioned signature is shown as boxes, and then, by sketching vertical and horizontal lines, we construct a grid of each word to provide a new descriptor. One of the advantages of this method is that it can be used for both handwritten and machine-printed texts. Finally, to evaluate the performance of our system in comparison to other methods, a …
Dynamic Physarum Solver: A Bio-Inspired Shortest Path Method Of Dynamically Changing Graphs, Hi̇lal Arslan
Dynamic Physarum Solver: A Bio-Inspired Shortest Path Method Of Dynamically Changing Graphs, Hi̇lal Arslan
Turkish Journal of Electrical Engineering and Computer Sciences
In dynamic graphs, edge weights of the graph change with time and solving the shortest path problem in such graphs is an important real-world problem. The studies in the literature require excessive computational time for computing the dynamic shortest path since determining changing edge weights is difficult especially when the graph size becomes large. In this paper, we propose a dynamic bio-inspired algorithm for finding the dynamic shortest path for large graphs based on Physarum Solver, which is a shortest path algorithm for static graphs. The proposed method is evaluated using three different large graph models representing diverse real-life applications. …
Optimal Training And Test Sets Design For Machine Learning, Burkay Genç, Hüseyi̇n Tunç
Optimal Training And Test Sets Design For Machine Learning, Burkay Genç, Hüseyi̇n Tunç
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, we describe histogram matching, a metric for measuring the distance of two datasets with exactly the same features, and embed it into a mixed integer programming formulation to partition a dataset into fixed size training and test subsets. The partition is done such that the pairwise distances between the dataset and the subsets are minimized with respect to histogram matching. We then conduct a numerical study using a well-known machine learning dataset. We demonstrate that the training set constructed with our approach provides feature distributions almost the same as the whole dataset, whereas training sets constructed via …
Triangular Slotted Ground Plane: A Key To Realizing High-Gain, Cross-Polarization-Free Microstrip Antenna With Improved Bandwidth, Abhijyoti Ghosh, Banani Basu
Triangular Slotted Ground Plane: A Key To Realizing High-Gain, Cross-Polarization-Free Microstrip Antenna With Improved Bandwidth, Abhijyoti Ghosh, Banani Basu
Turkish Journal of Electrical Engineering and Computer Sciences
A simple rectangular microstrip antenna with triangular slotted ground plane has been studied both theoretically and experimentally to improve shortcomings like low gain (5 - 6 dBi), narrow bandwidth (3% - 4%), and poor copolarization (CP) to cross-polarization (XP) isolation, i.e. polarization purity (typically 10 - 12 dB), of conventional rectangular microstrip patch antennas. By placing two pairs of triangular shaped slots on the ground plane just below the nonradiating edges of the patch, high gain (around 9 dBi) and more than 22 dB polarization purity over a wide elevation angle has been achieved. The proposed antenna covers almost the …
Domain Adaptation On Graphs By Learning Graph Topologies: Theoretical Analysis And An Algorithm, Eli̇f Vural
Domain Adaptation On Graphs By Learning Graph Topologies: Theoretical Analysis And An Algorithm, Eli̇f Vural
Turkish Journal of Electrical Engineering and Computer Sciences
Traditional machine learning algorithms assume that the training and test data have the same distribution, while this assumption does not necessarily hold in real applications. Domain adaptation methods take into account the deviations in data distribution. In this work, we study the problem of domain adaptation on graphs. We consider a source graph and a target graph constructed with samples drawn from data manifolds. We study the problem of estimating the unknown class labels on the target graph using the label information on the source graph and the similarity between the two graphs. We particularly focus on a setting where …
A Novel Algorithm For Frequency Extraction Of Abs Signals By Using Dtdnns, Mohammad Ali Shafieian, Hamed Banizaman, Shahrzad Sedaghat
A Novel Algorithm For Frequency Extraction Of Abs Signals By Using Dtdnns, Mohammad Ali Shafieian, Hamed Banizaman, Shahrzad Sedaghat
Turkish Journal of Electrical Engineering and Computer Sciences
Intelligent transportations system (ITSs) have emerged to increase safety and convenience of people in vehicles. In an ITS, communication devices in the vehicle or along the streets send the information gathered from the vehicle to information management centers as well as sending processed information to the vehicle. Furthermore, it is necessary to locate the exact location of the vehicle on a digital map in order to navigate the vehicle precisely in control and navigation systems. One of the technologies for this purpose is the antilock brake system (ABS), which can avoid accidents effectively and can also be utilized to determine …
Key Word Extraction For Short Text Via Word2vec, Doc2vec, And Textrank, Jun Li, Guimin Huang, Chunli Fan, Zhenglin Sun, Hongtao Zhu
Key Word Extraction For Short Text Via Word2vec, Doc2vec, And Textrank, Jun Li, Guimin Huang, Chunli Fan, Zhenglin Sun, Hongtao Zhu
Turkish Journal of Electrical Engineering and Computer Sciences
Day by day huge amounts data are produced, and evaluation of these data becomes more difficult. The data obtained should provide meaningful, correct, and accurate information. Therefore, all data must be separated into clusters correctly, and the right information from these clusters must be obtained. Having the correct clusters depends on the clustering algorithm that is used. There are many clustering algorithms. The density-based methods are very important among the groups of clustering methods, as they can find arbitrary shapes. An advanced model of the density-based spatial clustering of applications with noise (DBSCAN) algorithm, called fuzzy neighborhood DBSCAN Gaussian means …
Automatic Landing Of A Low-Cost Quadrotor Using Monocular Vision And Kalman Filter In Gps-Denied Environments, Mohammad Fattahi Sani, Maryam Shoaran, Ghader Karimian
Automatic Landing Of A Low-Cost Quadrotor Using Monocular Vision And Kalman Filter In Gps-Denied Environments, Mohammad Fattahi Sani, Maryam Shoaran, Ghader Karimian
Turkish Journal of Electrical Engineering and Computer Sciences
Unmanned aerial vehicles are becoming an important part of the modern life. Despite some recent advances in GPS-aided navigation of quadrotors, the concern of crash and collision still overshadows their reliability and safety, especially in GPS-denied environments. Therefore, the necessity for developing fully automatic methods for safe, accurate, and independent landing of drones increases over time. This paper investigates the autolanding process by focusing on an accurate and continuous position estimation of the drone using a monocular vision system and the fusion with the inertial measurement unit and ultrasonic sensors' data. An ARUCO marker is used as the landing pad, …
High-Efficiency Design Of A Grid-Connected Pv Inverter Based On Interleaved Flyback Converter Topology, Bünyami̇n Tamyürek, Bi̇lgehan Kirimer
High-Efficiency Design Of A Grid-Connected Pv Inverter Based On Interleaved Flyback Converter Topology, Bünyami̇n Tamyürek, Bi̇lgehan Kirimer
Turkish Journal of Electrical Engineering and Computer Sciences
The importance of efficiency in photovoltaic (PV) inverter applications makes the topology selection as the critical first step. Due to the low efficiency concern, flyback converter is not the preferred topology in kilowatt range in spite of its galvanic isolation, low cost, and small size advantages. Therefore, the objective of this research is to change the perception in favor of flyback converter by designing a flyback-topology-based PV inverter at 2.5 kW with high efficiency. The enhancement in efficiency is achieved mainly by using silicon carbide switching devices, designing ultrahigh-efficiency flyback transformers with extremely low leakage inductance and by implementing a …
Large-Scale Round-Trip Delay Time Analysis Of Ipv4 Hosts Around The Globe, Ali̇ Gezer
Large-Scale Round-Trip Delay Time Analysis Of Ipv4 Hosts Around The Globe, Ali̇ Gezer
Turkish Journal of Electrical Engineering and Computer Sciences
Design and optimization of many network applications, services, protocols, and routing protocols can be improved with delay-related measurement for a better operation over the Internet. Many experimental delay measurements have been performed on predetermined end-to-end connections with a less number of hosts compared to our study. This study aims to investigate up-to-date round-trip delay time measurement results over the Internet through pinging random IPv4 addresses from three vantage points located in the United States, Turkey, and Japan. Considering different time periods in a day and in consecutive 5 years, we performed a large-scale round-trip delay time analysis study by sending …
Novel Node Deployment Scheme And Reliability Quantitative Analysis For An Iot-Based Monitoring System, Yinghua Tong, Liqin Tian, Jing Li
Novel Node Deployment Scheme And Reliability Quantitative Analysis For An Iot-Based Monitoring System, Yinghua Tong, Liqin Tian, Jing Li
Turkish Journal of Electrical Engineering and Computer Sciences
The Internet of things (IoT) is highly suitable for military, environmental, agricultural, and other remote real-time monitoring applications. A reliable topology ensures a stable and dependable monitoring system. Considering the research of an IoT-based air pollution monitoring system for industrial emissions as background, this study proposes a novel dual redundant node deployment scheme. Specifically, hexagonal clustering is proposed for the internal regions. In addition, relationship and quantification formulas for a monitoring area are presented, and the communication range, total number of layers of the topology, and number of cluster headers are determined. Interruptions in a monitoring system may reduce the …
Monotone Data Modeling Using Rational Functions, Zoha Tariq, Farheen Ibraheem, Malik Zawwar Hussain, Muhammad Sarfraz
Monotone Data Modeling Using Rational Functions, Zoha Tariq, Farheen Ibraheem, Malik Zawwar Hussain, Muhammad Sarfraz
Turkish Journal of Electrical Engineering and Computer Sciences
Rational schemes for shape preservation of monotone data both in 2D and 3D setups have been developed. $C^1$ rational cubic and partially blended bicubic functions are employed for this purpose. Monotonicity is achieved by extracting constraints on parameters involved in the description of these rational functions. Monotone curves and surfaces have been obtained, which provide evidence that the algorithm used fits most types of monotone data and produces visually pleasing results.
Ifit: An Unsupervised Discretization Method Based On The Ramer-Douglas-Peucker Algorithm, Alev Mutlu, Furkan Göz, Orhan Akbulut
Ifit: An Unsupervised Discretization Method Based On The Ramer-Douglas-Peucker Algorithm, Alev Mutlu, Furkan Göz, Orhan Akbulut
Turkish Journal of Electrical Engineering and Computer Sciences
Discretization is the process of converting continuous values into discrete values. It is a preprocessing step of several machine learning and data mining algorithms and the quality of discretization may drastically affect the performance of these algorithms. In this study we propose a discretization algorithm, namely line fitting-based discretization (lFIT), based on the Ramer--Douglas--Peucker algorithm. It is a static, univariate, unsupervised, splitting-based, global, and incremental discretization method where intervals are determined based on the Ramer--Douglas--Peucker algorithm and the quality of partitioning is assessed based on the standard error of the estimate. To evaluate the performance of the proposed method, a …
A Computational Study On Aging Effect For Facial Expression Recognition, Elena Sönmez
A Computational Study On Aging Effect For Facial Expression Recognition, Elena Sönmez
Turkish Journal of Electrical Engineering and Computer Sciences
This work uses newly introduced variations of the sparse representation-based classifier (SRC) to challenge the issue of automatic facial expression recognition (FER) with faces belonging to a wide span of ages. Since facial expression is one of the most powerful and immediate ways to disclose individuals? emotions and intentions, the study of emotional traits is an active research topic both in psychology and in engineering fields. To date, automatic FER systems work well with frontal and clean faces, but disturbance factors can dramatically decrease their performance. Aging is a critical disruption element, which is present in any real-world situation and …
Spatial-Aware Global Contrast Representation For Saliency Detection, Dan Xu, Shucheng Huang, Xin Zuo
Spatial-Aware Global Contrast Representation For Saliency Detection, Dan Xu, Shucheng Huang, Xin Zuo
Turkish Journal of Electrical Engineering and Computer Sciences
Deep learning networks have been demonstrated to be helpful when used in salient object detection and achieved superior performance than the methods that are based on low-level hand-crafted features. In this paper, we propose a novel spatial-aware contrast cube-based convolution neural network (CNN) which can further improve the detection performance. From this cube data structure, the contrast of the superpixel is extracted. Meanwhile, the spatial information is preserved during the transformation. The proposed method has two advantages compared to the existing deep learning-based saliency methods. First, instead of feeding the deep learning networks with raw image patches or pixels, we …
A Method For Indoor Wi-Fi Location Based On Improved Back Propagation Neuralnetwork, Jinghui Chen, Chen Dong, Guorong He, Xiaoyu Zhang
A Method For Indoor Wi-Fi Location Based On Improved Back Propagation Neuralnetwork, Jinghui Chen, Chen Dong, Guorong He, Xiaoyu Zhang
Turkish Journal of Electrical Engineering and Computer Sciences
In order to achieve high precision on indoor location, a Wi-Fi indoor location method based on improved back propagation (BP) neural network is proposed. The classical BP neural network is optimized in real time by the ant colony optimization algorithm. Meanwhile, the momentum term is introduced to construct an improved four-layer BP neural network model. The model uses the Wi-Fi signal feature as the input of the BP neural network and succeeds in the area classification under multiple Wi-Fi signal features. The experimental results demonstrate that the improved BP neural network can increase the classification accuracy of the classifier effectively, …
A Hybrid Single-Source Shortest Path Algorithm, Hi̇lal Arslan, Murat Manguoğlu
A Hybrid Single-Source Shortest Path Algorithm, Hi̇lal Arslan, Murat Manguoğlu
Turkish Journal of Electrical Engineering and Computer Sciences
The single-source shortest path problem arises in many applications, such as roads, social applications, and computer networks. Finding the shortest path is challenging, especially for graphs that contain a large number of vertices and edges. In this work, we propose a novel hybrid method that first sparsifies a given graph by removing most edges that cannot form the shortest path tree and then applies a classical shortest path algorithm to the sparser graph. Removing all the edges that cannot form the shortest path tree would be expensive since it is equivalent to solving the original problem. Therefore, we propose an …
Cloud-Supported Machine Learning System For Context-Aware Adaptive M-Learning, Muhammad Adnan, Asad Habib, Jawad Ashraf, Shafaq Mussadiq
Cloud-Supported Machine Learning System For Context-Aware Adaptive M-Learning, Muhammad Adnan, Asad Habib, Jawad Ashraf, Shafaq Mussadiq
Turkish Journal of Electrical Engineering and Computer Sciences
It is a knotty task to amicably identify the sporadically changing real-world context information of a learner during M-learning processes. Contextual information varies greatly during the learning process. Contextual information that affects the learner during a learning process includes background knowledge, learning time, learning location, and environmental situation. The computer programming skills of learners improve rapidly if they are encouraged to solve real-world programming problems. It is important to guide learners based on their contextual information in order to maximize their learning performance. In this paper, we proposed a cloud-supported machine learning system (CSMLS), which assists learners in learning practical …
Robust Power System State Estimation By Appropriate Selection Of Tolerance Forthe Least Measurement Rejected Algorithm, Mohammad Shoaib Shahriar, Ibrahim Omar Habiballah
Robust Power System State Estimation By Appropriate Selection Of Tolerance Forthe Least Measurement Rejected Algorithm, Mohammad Shoaib Shahriar, Ibrahim Omar Habiballah
Turkish Journal of Electrical Engineering and Computer Sciences
Modern power systems are highly complicated and nonlinear in nature. Accurate estimation of the power system states (voltage-magnitude and phase-angle) is required for the secure operation of the power system. The presence of bad-data measurements in meters has made this estimation process challenging. An efficient estimator should detect and eliminate the effect of bad data during the estimation process. Least measurement rejected (LMR) is a robust estimator that has been found successful in dealing with various categories of bad data. The performance of LMR depends upon the proper selection of a tolerance for each measurement. This paper presents a novel …
Wavelet Energy-Based Stable And Unstable Power Swing Detection Scheme Fordistance Relays, Naga Chaitanya Munukutla, Venkata Siva Krishna Rao Gadi, Ramamoorty Mylavarapu
Wavelet Energy-Based Stable And Unstable Power Swing Detection Scheme Fordistance Relays, Naga Chaitanya Munukutla, Venkata Siva Krishna Rao Gadi, Ramamoorty Mylavarapu
Turkish Journal of Electrical Engineering and Computer Sciences
Distance relays are susceptible to maloperation during postfault power oscillations in the system. This unintended operation of relays may lead to power system blackout. It is due to their inability to distinguish a stable from an unstable power swing and to take a tripping decision appropriately. This research paper proposes a fast and wavelet energy-based method to detect stable and unstable power swings for distance relays. The proposed method computes the angular velocity of an equivalent machine developed from the measurements available at a bus. The energy in the low frequency band of the equivalent machine angular velocity will assist …
Real-Time Implementation Of Electronic Power Transformer Based On Intelligentcontroller, Hakan Açikgöz, Ökkeş Fati̇h Keçeci̇oğlu, Mustafa Şekkeli̇
Real-Time Implementation Of Electronic Power Transformer Based On Intelligentcontroller, Hakan Açikgöz, Ökkeş Fati̇h Keçeci̇oğlu, Mustafa Şekkeli̇
Turkish Journal of Electrical Engineering and Computer Sciences
Along with the rapid advances in power electronics and semiconductor technology, electronic power transformers (EPTs), which are expected to replace conventional power transformers in the future, are being developed and designed. This study presents the dynamic performance of the intelligent controller structure in the control of an EPT. The EPT structure, consisting of the input, isolation, and output stages, is designed for experimental and simulation studies. A three-phase pulse width modulation (PWM) rectifier is used to rectify the grid voltages at the input stage of EPT. The DC-bus voltage of the three-phase PWM rectifier is controlled by a neuro-fuzzy controller …
Extraction And Selection Of Statistical Harmonics Features For Electrical Appliancesidentification Using K-Nn Classifier Combined With Voting Rules Method, Fateh Ghazali, Abdenour Hacine-Gharbi, Philippe Ravier, Tayeb Mohamadi
Extraction And Selection Of Statistical Harmonics Features For Electrical Appliancesidentification Using K-Nn Classifier Combined With Voting Rules Method, Fateh Ghazali, Abdenour Hacine-Gharbi, Philippe Ravier, Tayeb Mohamadi
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, we propose a novel framework for electrical appliances identification using statistical harmonic features of current signals and the use of the k-NN classifier combined with a voting rule strategy. Harmonic coefficients are computed over time using short-time Fourier series of the current signals. From these sequences of coefficients, the mean, standard deviation, skewness, and kurtosis are computed, which provide the statistical harmonic features. This framework has three novelties: (i) selecting the best combination of statistical measures in the sense of classification rate (CR); (ii) combining the k-NN classifier with the voting rule method in order to search …
A New Hybrid Gravitational Search-Teaching-Learning-Based Optimization Methodfor The Solution Of Economic Dispatch Of Power Systems, Mehmet Fati̇h Tefek, Harun Uğuz
A New Hybrid Gravitational Search-Teaching-Learning-Based Optimization Methodfor The Solution Of Economic Dispatch Of Power Systems, Mehmet Fati̇h Tefek, Harun Uğuz
Turkish Journal of Electrical Engineering and Computer Sciences
The economic dispatch problem (EDP) is a complex, constrained, and nonlinear optimization problem. In the EDP, the active power bus should operate between the minimum and maximum bus limits to minimize the fuel cost. In this study, a fast, efficient, and reliable hybrid gravitational search algorithm-teaching learning based optimization (GSA-TLBO) method was proposed for the purpose of solving the EDP in power systems. The proposed method separates the search space into two sections as global and local searching. In the first part, searching was carried out by GSA method effectively to form the second search space. In the second part, …
A New Approach For Parameter Estimation Of The Single-Diode Model Forphotovoltaic Cells/Modules, Bi̇lge Kaan Atay, Ulaş Emi̇noğlu
A New Approach For Parameter Estimation Of The Single-Diode Model Forphotovoltaic Cells/Modules, Bi̇lge Kaan Atay, Ulaş Emi̇noğlu
Turkish Journal of Electrical Engineering and Computer Sciences
Solar energy has become a popular renewable energy source, leading to wide use of photovoltaic (PV) cells/modules in energy production. For this reason, realistic modeling of PVs and determining the equivalent circuit parameters is of great importance in terms of planning and operation. Hence, in this study, an analytical model for identifying the single-diode equivalent circuit parameters; series resistance (Rs ), shunt resistance (Rp ), diode ideality factor (a), diode reverse-saturation current (Io ), and photon current (Ipv ) for PV cells/modules is developed without neglecting any term. In order to test the accuracy of the model, a number of …
A Quasi-Z-Source Active Neutral Point Clamped Inverter Topology Employingsymmetrical/Unsymmetrical Boost Modulation Control Scheme For Renewableenergy Resources, Rehan Majeed, Danial Saleem, M. Imtiaz Hussain, Muhammad Talha Gul, Muhammad Rehan Usman, Salman Majeed
A Quasi-Z-Source Active Neutral Point Clamped Inverter Topology Employingsymmetrical/Unsymmetrical Boost Modulation Control Scheme For Renewableenergy Resources, Rehan Majeed, Danial Saleem, M. Imtiaz Hussain, Muhammad Talha Gul, Muhammad Rehan Usman, Salman Majeed
Turkish Journal of Electrical Engineering and Computer Sciences
This paper proposes a bipolar quasi-Z-source active neutral point clamped inverter (QZS-ANPCI) topology. It acts as a buck/boost inverter (3-phase, 3-level) to integrate renewable energy resources under their fluctuating DC voltages. We propose a symmetrical/unsymmetrical boost modulation control technique to mitigate the DC-link unbalance voltage problem in an ANPC inverter. This worthwhile control technique exploits voltage-current closedloops on AC and DC sides to regulate the desired parameters. Moreover, the constant boost control (CBC) modulation has provided a switching sequence that generates a symmetrical/unsymmetrical full shoot-through (FST) state for boosting input DC voltage in the proposed inverter. Detailed loss and efficiency …
Word Sense Disambiguation Using Semantic Kernels With Class-Based Term Values, Ayşe Berna Altinel, Murat Can Gani̇z, Bi̇lge Şi̇pal, Eren Can Erkaya, Onur Can Yücedağ, Muhammed Ali̇ Doğan
Word Sense Disambiguation Using Semantic Kernels With Class-Based Term Values, Ayşe Berna Altinel, Murat Can Gani̇z, Bi̇lge Şi̇pal, Eren Can Erkaya, Onur Can Yücedağ, Muhammed Ali̇ Doğan
Turkish Journal of Electrical Engineering and Computer Sciences
In this study, we propose several semantic kernels for word sense disambiguation (WSD). Our approaches adapt the intuition that class-based term values help in resolving ambiguity of polysemous words in WSD. We evaluate our proposed approaches with experiments, utilizing various sizes of training sets of disambiguated corpora (SensEval). With these experiments we try to answer the following questions: 1.) Do our semantic kernel formulations yield higher classification performance than traditional linear kernel?, 2.) Under which conditions a kernel design performs better than others?, 3.) Does the addition of class labels into standard term-document matrix improve the classification accuracy?, 4.) Is …