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2019

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Articles 3751 - 3780 of 3906

Full-Text Articles in Computer Sciences

Importance-Based Signal Detection And Parameter Estimation With Applications To New Particle Search, Hati̇ce Doğan, Nasuf Sönmez, Güleser Kalayci Demi̇r Jan 2019

Importance-Based Signal Detection And Parameter Estimation With Applications To New Particle Search, Hati̇ce Doğan, Nasuf Sönmez, Güleser Kalayci Demi̇r

Turkish Journal of Electrical Engineering and Computer Sciences

One of the hardest challenges in data analysis is perhaps the detection of rare anomalous data buried in a huge normal background. We study this problem by constructing a novel method, which is a combination of the Kullback?Leibler importance estimation procedure based anomaly detection algorithm and linear discriminant classifier. We choose to illustrate it with the example of charged Higgs boson (CHB) search in particle physics. Indeed, the Large Hadron Collider experiments at CERN ensure that CHB signal must be a tiny effect within the irreducible W-boson background. In simulations, different CHB events with different characteristics are produced and judiciously …

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Particle Swarm Optimization Approach To Optimal Design Of An Afpm Tractionmachine For Different Driving Conditions, Naghi Rostami Jan 2019

Particle Swarm Optimization Approach To Optimal Design Of An Afpm Tractionmachine For Different Driving Conditions, Naghi Rostami

Turkish Journal of Electrical Engineering and Computer Sciences

Axial flux permanent magnet (AFPM) machines can be employed as the traction motor of electric vehicles due to their high torque capability, high efficiency, modular and compact construction, and capability of integration with other mechanical components in integrated systems. Besides, the system efficiency can be further improved by optimal design of the selected electric machine. In this paper, an AFPM machine is optimized against two well-known driving cycles called the New European Drive Cycle (NEDC) and US06 and the influence of the driving cycle on the obtained machine parameters is evaluated. US06 is the more demanding driving cycle and thus …

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Towards Wearable Blood Pressure Measurement Systems From Biosignals: A Review, Ümi̇t Şentürk, Kemal Polat, İbrahi̇m Yücedağ Jan 2019

Towards Wearable Blood Pressure Measurement Systems From Biosignals: A Review, Ümi̇t Şentürk, Kemal Polat, İbrahi̇m Yücedağ

Turkish Journal of Electrical Engineering and Computer Sciences

Blood pressure is the pressure by the blood to the vein wall. High blood pressure, which is called silent death, is the cause of nearly 13 % of mortality all over the world. Blood pressure is not only measured in the medical environment, but the blood pressure measurement is also a need for people in their daily life. Blood pressure estimation systems with low error rates have been developed besides the new technologies and algorithms. Blood pressure measurements are differentiated as invasive blood pressure (IBP) measurement and noninvasive blood pressure (NIBP) measurement methods. Although IBP measurement provides the most accurate …

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Sparsity-Based Three-Dimensional Image Reconstruction For Near-Field Mimo Radar Imaging, Fi̇gen S. Oktem Jan 2019

Sparsity-Based Three-Dimensional Image Reconstruction For Near-Field Mimo Radar Imaging, Fi̇gen S. Oktem

Turkish Journal of Electrical Engineering and Computer Sciences

Near-field multiple-input multiple-output (MIMO) radar imaging systems are of interest in diverse fields such as medicine, through-wall imaging, airport security, concealed weapon detection, and surveillance. The successful operation of these radar imaging systems highly depends on the quality of the images reconstructed from radar data. Since the underlying scenes can be typically represented sparsely in some transform domain, sparsity priors can effectively regularize the image formation problem and hence enable high-quality reconstructions. In this paper, we develop an efficient three-dimensional image reconstruction method that exploits sparsity in near-field MIMO radar imaging. Sparsity is enforced using total variation regularization, and the …

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Empirical Single Frequency Network Threshold For Dvb-T2 Based On Laboratory Experiments, Bundit Ruckveratham, Sathaporn Promwong Jan 2019

Empirical Single Frequency Network Threshold For Dvb-T2 Based On Laboratory Experiments, Bundit Ruckveratham, Sathaporn Promwong

Turkish Journal of Electrical Engineering and Computer Sciences

DVB-T2 broadcasting with a single frequency network (SFN) allows an efficient management of frequency utilization and extends the coverage area, which will enable more people to view a broadcast. The SFN mode also increases the concentration of the signal in overlap areas. However, some difference of overlap areas in actual use of SFN networks may have some degradation of the received signal due to the effect of the SFN. In this research, we analyze SFN broadcasting in SISO mode. This paper represents the effects of delays on the SFN signal over different delay times within the guard interval (GI) by …

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A Comprehensive Methodology To Evaluate The Performance Of A Cooperative Wireless Network, Aykut Kalaycioğlu, Ahmet Akbulut, Asim Egemen Yilmaz, Di̇lek Arslan Jan 2019

A Comprehensive Methodology To Evaluate The Performance Of A Cooperative Wireless Network, Aykut Kalaycioğlu, Ahmet Akbulut, Asim Egemen Yilmaz, Di̇lek Arslan

Turkish Journal of Electrical Engineering and Computer Sciences

Performance evaluation of a cooperative wireless communication network depends on several parameters. Many of the studies, in fact, take a limited number of performance metrics individually to reach a conclusion about the performance of a network. Besides, in general, some performance metrics might be in conflict. Thus, ignoring the combined effect of all performance criteria in the network may lead to an incorrect conception of the overall communication performance of the network. Therefore, in this study, a comprehensive evaluation methodology in terms of various metrics is proposed to calculate the performance of a cooperative wireless communication network deployment using a …

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A No-Reference Framework For Evaluating Video Quality Streamed Through Wireless Network, Muhammad Uzair, Robert D. Dony, Mohsin Jamil, Khawaja Bilal Ahmad Mahmood, Muhammad Nasir Khan Jan 2019

A No-Reference Framework For Evaluating Video Quality Streamed Through Wireless Network, Muhammad Uzair, Robert D. Dony, Mohsin Jamil, Khawaja Bilal Ahmad Mahmood, Muhammad Nasir Khan

Turkish Journal of Electrical Engineering and Computer Sciences

In this work, a no-reference framework is proposed for the video quality estimation streamed through the wireless network. The work presents a comprehensive survey of the existing full reference (FR), reduced reference (RR), and no-reference (NR) algorithms. A comparison has been made among existing algorithms, i.e. in terms of subjective correlation and feasibility to use these algorithms in wireless architecture, to describe the necessity of the proposed framework to overcome the limitations of the existing algorithms. A brief summary of our previously published algorithms, i.e. NR blockiness, NR blur, NR network, NR just noticeable distortion, and RR, has also been …

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Performance Improvement Of Multiuser Cognitive Relay Networks With Full-Duplex Cooperative Sensing And Energy Harvesting, Alieh Moradi, Hamid Farrohki Jan 2019

Performance Improvement Of Multiuser Cognitive Relay Networks With Full-Duplex Cooperative Sensing And Energy Harvesting, Alieh Moradi, Hamid Farrohki

Turkish Journal of Electrical Engineering and Computer Sciences

Energy harvesting cognitive radio has been considered as a promising technology in the fifth generation (5G) of wireless networks to solve the lack of spectrum and energy. In this paper, a novel wireless energy harvesting relay network is proposed for a multiuser cognitive radio to obtain the maximum throughput and decrease the false alarm and misdetection probabilities. The secondary user (SU) can harvest energy from solar sources while utilizing the licensed spectrum of the primary user (PU). Cooperative spectrum sensing is applied to improve the performance of the secondary network and decrease collision and sensing time. In this paper, the …

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A Heuristic Algorithm To Find Rupture Degree In Graphs, Rafet Durgut, Tufan Turaci, Hakan Kutucu Jan 2019

A Heuristic Algorithm To Find Rupture Degree In Graphs, Rafet Durgut, Tufan Turaci, Hakan Kutucu

Turkish Journal of Electrical Engineering and Computer Sciences

Since the problem of Konigsberg bridge was released in 1735, there have been many applications of graph theory in mathematics, physics, biology, computer science, and several fields of engineering. In particular, all communication networks can be modeled by graphs. The vulnerability is a concept that represents the reluctance of a network to disruptions in communication after a deterioration of some processors or communication links. Furthermore, the vulnerability values can be computed with many graph theoretical parameters. The rupture degree $r(G)$ of a graph $G=(V,E)$ is an important graph vulnerability parameter and defined as $r(G)=max\{\omega(G-S)- S -m(G-S):\omega(G-S)\geq2, S\subset V \}$, where …

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Global Stabilization Of A Class Of Fractional-Order Delayed Bidirectional Associativememory Neural Networks, Zhanying Yang, Xiaoyun Tang, Jie Zhang Jan 2019

Global Stabilization Of A Class Of Fractional-Order Delayed Bidirectional Associativememory Neural Networks, Zhanying Yang, Xiaoyun Tang, Jie Zhang

Turkish Journal of Electrical Engineering and Computer Sciences

This paper focuses on the stabilization problem of a class of fractional-order bidirectional associative memory neural networks with time delays. Based on feedback control, a sufficient condition is derived to achieve the global stabilization of systems by using the fractional inequality, the Lyapunov stability theory, and the comparison principle. In particular, this kind of control scheme is proved to be robust in the presence of external disturbances when the feedback gains are sufficiently large. In addition, a condition is obtained to achieve the global quasi-stabilization of systems with some external disturbances, and the corresponding error bound is estimated. Finally, some …

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Privacy Issues In Post Dissemination On Facebook, Burcu Sayi̇n Günel, Serap Şahi̇n, Dimitris G. Kogias, Charalampos Z. Patrikakis Jan 2019

Privacy Issues In Post Dissemination On Facebook, Burcu Sayi̇n Günel, Serap Şahi̇n, Dimitris G. Kogias, Charalampos Z. Patrikakis

Turkish Journal of Electrical Engineering and Computer Sciences

With social networks (SNs) being populated by a still increasing numbers of people who take advantage of the communication and collaboration capabilities that they offer, the probability of the exposure of people's personal moments to a wider than expected audience is also increasing. By studying the functionalities and characteristics that modern SNs offer, along with the people's habits and common behaviors in them, it is easy to understand that several privacy risks may exist, many of which people may be unaware of. In this paper, we focus on users' interactions with posts in a social network (SN), using Facebook as …

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Atomic-Shaped Efficient Delay And Data Gathering Routing Protocol For Underwater Wireless Sensor Networks, Wajiha Farooq, Tariq Ali, Ahmad Shaf, Muhammad Umar, Sana Yasin Jan 2019

Atomic-Shaped Efficient Delay And Data Gathering Routing Protocol For Underwater Wireless Sensor Networks, Wajiha Farooq, Tariq Ali, Ahmad Shaf, Muhammad Umar, Sana Yasin

Turkish Journal of Electrical Engineering and Computer Sciences

High end-to-end delay is a major challenge in autonomous underwater vehicle (AUV)-aided routing protocols for underwater monitoring applications. In this paper, a new routing protocol called atomic-shaped efficient delay and data gathering (ASEDG) has been introduced for underwater wireless sensor networks. The ASEDG is divided into two phases; in the first phase, the atomic-shaped trajectory model with horizontal and vertical ellipticals was designed for the movement of the AUV. In the second phase, two types of delay models were considered to make our protocol more delay efficient: member nodes (MNs) to MNs and MNs to gateway nodes (GNs). The MNs-to-MNs …

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Method Of Limiting The Emissivity Of Wsn Networks, Tomasz Marciniak, Slawomir Bujnowski, Beata Marciniak, Zbigniew Lutowski Jan 2019

Method Of Limiting The Emissivity Of Wsn Networks, Tomasz Marciniak, Slawomir Bujnowski, Beata Marciniak, Zbigniew Lutowski

Turkish Journal of Electrical Engineering and Computer Sciences

Wireless sensor networks (WSNs) are a current topic of research that find usage in many applications from environmental monitoring and health protection to military applications. In this paper, analysis of the possibility of reducing the emissivity of radio sensor networks with the assumed transmission probability is discussed. This has a direct influence on power consumption by the nodes and network lifetime. A method based on introducing retransmissions on individual links creating paths between the nodes is presented. Two approaches are used in analyses, the first one being deterministic methods and the second one simulation. Both methods are used to determine …

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An Algorithm For Line Matching In An Image By Mapping Into An $N$-Dimensional Vector Space, Rayi̇mbek Sultanov, Ahmet Atakan, Rita Ismailova Jan 2019

An Algorithm For Line Matching In An Image By Mapping Into An $N$-Dimensional Vector Space, Rayi̇mbek Sultanov, Ahmet Atakan, Rita Ismailova

Turkish Journal of Electrical Engineering and Computer Sciences

This paper proposes a minimal length difference algorithm for construction of a line in an image by solving the problem of optimal contour approximation. In this algorithm, a method for finding interest points is proposed, and the object matching (classification) is done by mapping interest points onto a vector space. In cases where the lines in the representation of the images are not smooth, the algorithm converges rapidly. The results of the experiments showed that for convergence of the contour simplification, there were 5-6 iterations for $n = 13$. To check how close the curve approximation calculated by the algorithm …

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Parallel Brute-Force Algorithm For Deriving Reset Sequences From Deterministic Incomplete Finite Automata, Uraz Cengi̇z Türker Jan 2019

Parallel Brute-Force Algorithm For Deriving Reset Sequences From Deterministic Incomplete Finite Automata, Uraz Cengi̇z Türker

Turkish Journal of Electrical Engineering and Computer Sciences

A reset sequence (RS) for a deterministic finite automaton $\mathscr{A}$ is an input sequence that brings $\mathscr{A}$ to a particular state regardless of the initial state of $\mathscr{A}$. Incomplete finite automata (FA) are strong in modeling reactive systems, but despite their importance, there are no works published for deriving RSs from FA. This paper proposes a massively parallel algorithm to derive short RSs from FA. Experimental results reveal that the proposed parallel algorithm can construct RSs from FA with 16,000,000 states. When multiple GPUs are added to the system the approach can handle larger FA.

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Hgab3c: A New Hybrid Global Optimization Algorithm, Kamaljeet Kaur, Shakti Kumar, Jyoti Saxena Jan 2019

Hgab3c: A New Hybrid Global Optimization Algorithm, Kamaljeet Kaur, Shakti Kumar, Jyoti Saxena

Turkish Journal of Electrical Engineering and Computer Sciences

This paper proposes a new optimization algorithm, namely HGAB3C, and presents its performance on the CEC-2014 test suite. In HGAB3C, simple genetic algorithms (GAs) and big bang-big crunch (BB-BC) are hybridized. The algorithm carries out global searches using a simple GA. In every generation the BB-BC algorithm is used to carry out local searches. The addition of local search has improved the capability of simple GAs significantly. The performance of the proposed algorithm is compared with 17 other optimization algorithms on all 30 functions of the CEC-2014 benchmark suite. It is observed that HGAB3C outperforms all other algorithms on 4 …

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An Improved Imperialist Competitive Algorithm For Global Optimization, Ting You, Yueli Hu, Peijiang Li, Yinggan Tang Jan 2019

An Improved Imperialist Competitive Algorithm For Global Optimization, Ting You, Yueli Hu, Peijiang Li, Yinggan Tang

Turkish Journal of Electrical Engineering and Computer Sciences

The imperialist competitive algorithm (ICA), inspired by sociopolitical behavior in the real world, is a new optimization algorithm. The ICA shows great potential to solve complex optimization problems. In order to improve the ICA's exploration ability and speed up its convergence, two improved schemes are proposed in this paper. The first scheme presents a new possession probability in the imperialistic competition phase. Inspired by geopolitics, not only the power of the empire but also the distance between the imperialists are taken into account in calculating the new possession probability. The second scheme introduces the wavelet mutation operator into the original …

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Test Case Prioritization And Distributed Testing Of Object-Oriented Program, Vipin Kumar K S, Sheena Mathew Jan 2019

Test Case Prioritization And Distributed Testing Of Object-Oriented Program, Vipin Kumar K S, Sheena Mathew

Turkish Journal of Electrical Engineering and Computer Sciences

Software systems have increased in size and complexity. As a result, object-oriented programming (OOP) is increasingly being used in the development of such large and complex systems. Traditional procedural programming requires a design method that follows a sequential flow of control, which is difficult to follow in the case of large systems design. Thinking in terms of real-life objects and their interactions makes design easier in the case of OOP. However, OOP comes with its own set of disadvantages and testing is one of them. Testing of such systems requires much more effort and time. In our approach the program …

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Schedulability Analysis Of Real-Time Multiframe Cosimulations On Multicore Platforms, Muhammad Uzair Ahsan, Mehmet Hali̇t Seyfullah Oğuztüzün Jan 2019

Schedulability Analysis Of Real-Time Multiframe Cosimulations On Multicore Platforms, Muhammad Uzair Ahsan, Mehmet Hali̇t Seyfullah Oğuztüzün

Turkish Journal of Electrical Engineering and Computer Sciences

For real-time simulations, the fidelity of simulation depends not only on the functional accuracy of simulation but also on its timeliness. It is helpful for simulation designers if they can analyze and verify that a simulation will always meet its timing requirements without unnecessarily sacrificing functional accuracy. Abstracting the simulated processes simply as software tasks allows us to transform the problem of verifying timeliness into a schedulability analysis problem where tasks are checked as to whether they are schedulable under the timing constraints or not. In this paper we extend a timed automaton-based framework due to Fersman and Yi for …

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Reusable And Interactive Classes: A New Way Of Object Composition, Saeid Masoumi, Ali Mahjur Jan 2019

Reusable And Interactive Classes: A New Way Of Object Composition, Saeid Masoumi, Ali Mahjur

Turkish Journal of Electrical Engineering and Computer Sciences

Separating object features from base classes is one of the popular ways of software development. Some popular programming approaches like object-oriented programming, feature-oriented programming, and aspect-oriented programming follow this approach. There are four advantages of using features: 1) Instantiability: the ability to create instances of a feature, 2) Reusability: the quality of a feature being reusable in many compositions, 3) Loosely coupled composability: the ability to compose/decompose features easily at object instantiation time (not offering new data types for compositions), and 4) Interactability: the ability of a feature to crosscut (interact with) other features inside the object. Existing approaches do …

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Detection Of Fraud Risks In Retailing Sector Using Mlp And Svm Techniques, Davut Pehli̇vanli, Süleyman Eken, Ebu Beki̇r Ayan Jan 2019

Detection Of Fraud Risks In Retailing Sector Using Mlp And Svm Techniques, Davut Pehli̇vanli, Süleyman Eken, Ebu Beki̇r Ayan

Turkish Journal of Electrical Engineering and Computer Sciences

In today's business conditions, where business activities are spreading over a wide geographical area, fraud auditing processes have crucial importance especially for the retailing sector which has a high branch network. In the retailing sector, especially purchasing processes are subject to high fraud risks. This paper shows that it is possible to detect fraudulent processes by applying data mining techniques on operational data related to purchasing activities. Within this scope, in order to detect the fraudulent purchasing operations, support vector machine (SVM) models with different kernels and artificial neural networks methods have been used and successful results have been achieved. …

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Incremental Author Name Disambiguation Using Author Profile Models And Self-Citations, Ijaz Hussain, Sohail Asghar Jan 2019

Incremental Author Name Disambiguation Using Author Profile Models And Self-Citations, Ijaz Hussain, Sohail Asghar

Turkish Journal of Electrical Engineering and Computer Sciences

Author name ambiguity in bibliographic databases (BDs) such as DBLP is a challenging problem that degrades the information retrieval quality, citation analysis, and proper attribution to the authors. It occurs when several authors have the same name (homonym) or when an author publishes under several name variants (synonym). Traditionally, much research has been conducted to disambiguate whole bibliographic database at once whenever some new citations are added in these BDs. However, it is more time-consuming and discards the manual disambiguation effects (if any). Only a few incremental author name disambiguation methods are proposed but these methods produce fragmented clusters which …

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Biometric Person Authentication Framework Using Polynomial Curve Fitting-Based Ecg Feature Extraction, Şahi̇n Işik, Kemal Özkan, Semi̇h Ergi̇n Jan 2019

Biometric Person Authentication Framework Using Polynomial Curve Fitting-Based Ecg Feature Extraction, Şahi̇n Işik, Kemal Özkan, Semi̇h Ergi̇n

Turkish Journal of Electrical Engineering and Computer Sciences

The applications of modern biometric techniques for person identification systems rapidly increase for meeting the rising security demands. The distinctive physiological characteristics are more correctly measurable and trustworthy since previous measurements are not appropriately made for physiological properties. While a variety of strategies have been enabled for identification, the electrocardiogram (ECG)-based approaches are popular and reliable techniques in the senses of measurability, singularity, and universal awareness of heartbeat signals. This paper presents a new ECG-based feature extraction method for person identification using a huge amount of ECG recordings. First of all, 1800 heartbeats for each of the 36 subjects have …

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Enhancing Face Pose Normalization With Deep Learning, Anil Çeli̇k, Nafi̇z Arica Jan 2019

Enhancing Face Pose Normalization With Deep Learning, Anil Çeli̇k, Nafi̇z Arica

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, we propose a hybrid method for face pose normalization, which combines the 3-D model-based method with stacked denoising autoencoder (SDAE) deep network. Instead of applying a mirroring operation for the invisible face parts of the posed image, SDAE learns how to fill in those regions by a large set of training samples. In the performance evaluation, we compare the proposed method to four different pose normalization methods and investigate their effects on facial emotion recognition and verification problems in addition to visual quality tests. Methods evaluated in the experiments include 2-D alignment, 3-D model-based method, pure SDAE-based …

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I See Ek: A Lightweight Technique To Reveal Exploit Kit Family By Overall Url Patterns Of Infection Chains, Emre Süren, Peli̇n Angin, Nazi̇fe Baykal Jan 2019

I See Ek: A Lightweight Technique To Reveal Exploit Kit Family By Overall Url Patterns Of Infection Chains, Emre Süren, Peli̇n Angin, Nazi̇fe Baykal

Turkish Journal of Electrical Engineering and Computer Sciences

The prevalence and nonstop evolving technical sophistication of exploit kits (EKs) is one of the most challenging shifts in the modern cybercrime landscape. Over the last few years, malware infections via drive-by download attacks have been orchestrated with EK infrastructures. Malicious advertisements and compromised websites redirect victim browsers to web-based EK families that are assembled to exploit client-side vulnerabilities and finally deliver evil payloads. A key observation is that while the webpage contents have drastic differences between distinct intrusions executed through the same EK, the patterns in URL addresses stay similar. This is due to the fact that autogenerated URLs …

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Adaptive Canonical Correlation Analysis For Harmonic Stimulation Frequencies Recognition In Ssvep-Based Bcis, Sahar Sadeghi, Ali Maleki Jan 2019

Adaptive Canonical Correlation Analysis For Harmonic Stimulation Frequencies Recognition In Ssvep-Based Bcis, Sahar Sadeghi, Ali Maleki

Turkish Journal of Electrical Engineering and Computer Sciences

Steady-state visual evoked potential (SSVEP) is the brain's response to quickly repetitive visual stimulus with a certain frequency. To increase the information transfer rate (ITR) in SSVEP-based systems, due to the frequency resolution restriction, we are forced to broaden the frequency range, which causes harmonic frequencies to come into the stimulation frequency range. Conventional canonical correlation analysis (CCA) may be associated with error for SSVEP frequency recognition at stimulation frequencies with harmonic relations. The number of harmonics considered to construct reference signals are determined adaptively; for frequencies whose second harmonic exists in the frequency range, two harmonics are used, and …

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Extracting Accent Information From Urdu Speech For Forensic Speaker Recognition, Falak Tahir, Sajid Saleem, Ayaz Ahmad Jan 2019

Extracting Accent Information From Urdu Speech For Forensic Speaker Recognition, Falak Tahir, Sajid Saleem, Ayaz Ahmad

Turkish Journal of Electrical Engineering and Computer Sciences

This paper presents a new method for extraction of accent information from Urdu speech signals. Accent is used in speaker recognition system especially in forensic cases and plays a vital role in discriminating people of different groups, communities and origins due to their different speaking styles. The proposed method is based on Gaussian mixture model-universal background model (GMM-UBM), mel-frequency cepstral coefficients (MFCC), and a data augmentation (DA) process. The DA process appends features to base MFCC features and improves the accent extraction and forensic speaker recognition performances of GMM-UBM. Experiments are performed on an Urdu forensic speaker corpus. The experimental …

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Sentence Similarity Using Weighted Path And Similarity Matrices, Reza Javadzadeh, Morteza Zahedi, Marziea Rahimi Jan 2019

Sentence Similarity Using Weighted Path And Similarity Matrices, Reza Javadzadeh, Morteza Zahedi, Marziea Rahimi

Turkish Journal of Electrical Engineering and Computer Sciences

Sentence similarity is the task of assessing how similar the two snippets of text are. Similarity techniques are used extensively in clustering, summarization, classification, plagiarism detection etc. Due to a small set of vocabularies, sentence similarity is considered to be a difficult problem in natural language processing. There are two issues in solving this problem: (1) Which similarity techniques to be used for word pair similarity and (2) How to generalize that to sentence pairs. We have used the weighted path, a WordNet-based similarity assessment, and the paraphrase database to obtain word pair similarity values. Thereafter, we extracted maximum values …

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Segmented Character Recognition Using Curvature-Based Global Image Feature, Belaynesh Chekol, Numan Çelebi̇, Tuğrul Taşci Jan 2019

Segmented Character Recognition Using Curvature-Based Global Image Feature, Belaynesh Chekol, Numan Çelebi̇, Tuğrul Taşci

Turkish Journal of Electrical Engineering and Computer Sciences

Character recognition in natural scene images is a fundamental prerequisite for many text-based image analysis tasks. Generally, local image features are employed widely to recognize characters segmented from natural scene images. In this paper, a curvature-based global image feature and description for segmented character recognition is proposed. This feature is entirely dependent on the curvature information of the image pixels. The proposed feature is employed for segmented character recognition using Chars74k dataset and ICDAR 2003 character recognition dataset. From the two datasets, 1068 and 540 images of characters, respectively, are randomly chosen and 573-dimensional feature vector is synthesized per image. …

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A Hybrid Of Fuzzy Theory And Quadratic Function For Estimating And Refining Transmission Map, Jyun-Yu Jhang, Chengjian Lin, Kuu-Young Young, Chin-Teng Lin Jan 2019

A Hybrid Of Fuzzy Theory And Quadratic Function For Estimating And Refining Transmission Map, Jyun-Yu Jhang, Chengjian Lin, Kuu-Young Young, Chin-Teng Lin

Turkish Journal of Electrical Engineering and Computer Sciences

In photographs captured in outdoor environments, particles in the air cause light attenuation and degrade image quality. This effect is especially obvious in hazy environments. In this study, a fuzzy theory is proposed to estimate the transmission map of a single image. To overcome the problem of oversaturation in dehazed images, a quadratic-function-based method is proposed to refine the transmission map. In addition, the color vector of the atmospheric light is estimated using the top 1\% of the brightest light area. Finally, the dehazed image is reconstructed using the transmission map and the estimated atmospheric light. Experimental results demonstrate that …

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