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Articles 2341 - 2370 of 8897
Full-Text Articles in Physical Sciences and Mathematics
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 …
An Approach To Improve The Performance Of Cooperative Unmanned Vehicle Team, Ömer Ci̇han Kivanç
An Approach To Improve The Performance Of Cooperative Unmanned Vehicle Team, Ömer Ci̇han Kivanç
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, a method based on optimal energy management is proposed in order to improve the operational and tactical abilities of collaborative unmanned vehicle teams. Collaborative unmanned systems are used in surveillance, tracking, and military operations. The optimal assignment of these tasks requires cooperation among the vehicles in order to generate a strategy that is efficient with respect to overall mission duration and satisfies all problem constraints. The key motivation behind this paper is to design an unmanned vehicle team that mitigates the disadvantages caused by the structures and characteristics of unmanned ground vehicles (UGVs) and unmanned aerial vehicles …
Hybix: A Novel Encoding Bitmap Index For Space- And Time-Efficient Query Processing, Naphat Keawpibal, Ladda Preechaveerakul, Sirirut Vanichayobon
Hybix: A Novel Encoding Bitmap Index For Space- And Time-Efficient Query Processing, Naphat Keawpibal, Ladda Preechaveerakul, Sirirut Vanichayobon
Turkish Journal of Electrical Engineering and Computer Sciences
A bitmap-based index is an effective and efficient indexing method for answering selective queries in a read-only environment. It offers improved query execution time by applying low-cost Boolean operators on the index directly, before accessing raw data. A drawback of the bitmap index is that index size increases with the cardinality of indexed attributes, which additionally has an impact on a query execution time. This impact is related to an increase of query execution time due to the scanning of bitmap vectors to answer the queries. In this paper, we propose a new encoding bitmap index, called the HyBiX bitmap …
A Novel Hybrid Teaching-Learning-Based Optimization Algorithm For The Classification Of Data By Using Extreme Learning Machines, Ender Sevi̇nç, Tansel Dökeroğlu
A Novel Hybrid Teaching-Learning-Based Optimization Algorithm For The Classification Of Data By Using Extreme Learning Machines, Ender Sevi̇nç, Tansel Dökeroğlu
Turkish Journal of Electrical Engineering and Computer Sciences
Data classification is the process of organizing data by relevant categories. In this way, the data can be understood and used more efficiently by scientists. Numerous studies have been proposed in the literature for the problem of data classification. However, with recently introduced metaheuristics, it has continued to be riveting to revisit this classical problem and investigate the efficiency of new techniques. Teaching-learning-based optimization (TLBO) is a recent metaheuristic that has been reported to be very effective for combinatorial optimization problems. In this study, we propose a novel hybrid TLBO algorithm with extreme learning machines (ELM) for the solution of …
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 …
Invisible Watermarking Framework That Authenticates And Prevents The Visualization Of Anaglyph Images For Copyright Protection, David-Octavio Muñoz-Ramirez, Volodymyr Ponomaryov, Rogelio Reyes-Reyes, Clara Cruz-Ramos, Beatriz-Paulina Garcia-Salgado
Invisible Watermarking Framework That Authenticates And Prevents The Visualization Of Anaglyph Images For Copyright Protection, David-Octavio Muñoz-Ramirez, Volodymyr Ponomaryov, Rogelio Reyes-Reyes, Clara Cruz-Ramos, Beatriz-Paulina Garcia-Salgado
Turkish Journal of Electrical Engineering and Computer Sciences
In this work, a watermarking framework to authenticate and protect the copyright that prevents the visualization of nonauthorized anaglyph images is proposed. Designed scheme embeds a binary watermark and the Blue channel of the anaglyph image into the discrete cosine transform domain of the original image. The proposed method applies the quantization index modulation-dither modulation algorithm and a combination of Bose-Chaudhuri-Hocquenghem with repetition codes, which permit to increase the capability in recovering the watermark. Additionally, Hash algorithm is used to scramble the component where the watermark should be embedding, guaranteeing a higher security performance of the scheme. This new technique …
Efficient Features For Smartphone-Based Iris Recognition, Ritesh Vyas, Tirupathiraju Kanumuri, Gyanendra Sheoran, Pawan Dubey
Efficient Features For Smartphone-Based Iris Recognition, Ritesh Vyas, Tirupathiraju Kanumuri, Gyanendra Sheoran, Pawan Dubey
Turkish Journal of Electrical Engineering and Computer Sciences
Iris recognition has widely been used in personal authentication problems. Recent advances in iris recognition through visible wavelength images have paved the way for the use of this technology in smartphones. Smartphone-based iris recognition can be of significant use in financial transactions and secure storage of sensitive information. This paper presents a hybrid representation scheme for iris recognition in mobile devices. The scheme is called hybrid because it firstly makes use of Gabor wavelets to reveal the texture present in the normalized iris images, and then extracts statistical features from different partitions of Gabor-processed images. The standard mobile-iris database, called …
Plant Disease And Pest Detection Using Deep Learning-Based Features, Muammer Türkoğlu, Davut Hanbay
Plant Disease And Pest Detection Using Deep Learning-Based Features, Muammer Türkoğlu, Davut Hanbay
Turkish Journal of Electrical Engineering and Computer Sciences
The timely and accurate diagnosis of plant diseases plays an important role in preventing the loss of productivity and loss or reduced quantity of agricultural products. In order to solve such problems, methods based on machine learning can be used. In recent years, deep learning, which is especially widely used in image processing, offers many new applications related to precision agriculture. In this study, we evaluated the performance results using different approaches of nine powerful architectures of deep neural networks for plant disease detection. Transfer learning and deep feature extraction methods are used, which adapt these deep learning models to …
A Hybrid Of Tropical-Singular Value Decomposition Method For Salt And Pepper Noise Removal, Achmad Abdurrazzaq, Ismail Mohd, Ahmad Kadri Junoh, Zainab Yahya
A Hybrid Of Tropical-Singular Value Decomposition Method For Salt And Pepper Noise Removal, Achmad Abdurrazzaq, Ismail Mohd, Ahmad Kadri Junoh, Zainab Yahya
Turkish Journal of Electrical Engineering and Computer Sciences
The unknown information contained in an image that causes the change of information in the image is called noise. In this paper, we propose a new method for removing salt and pepper noise by using singular value decomposition and the concept of tropical algebra operations. To determine the performance of the proposed method, 20 test images are used as samples. Then three different image quality assessments are used: peak signal-to-noise ratio (PSNR), structural similarity (SSIM), and image enhancement factor (IEF). In addition, six different filtering methods, i.e. MF, DWMF, PSMF, MDBUTM, NAFSM, and BPDF, are used to compare the performance …
Can Additional Spectral Bands Be Estimated From Aerial Color Images?, Muhammet Ali̇ Dede, Erchan Aptoula, Yakup Genç
Can Additional Spectral Bands Be Estimated From Aerial Color Images?, Muhammet Ali̇ Dede, Erchan Aptoula, Yakup Genç
Turkish Journal of Electrical Engineering and Computer Sciences
Inspired by the surprising performances of deep generative models, in this paper we present the preliminary results of an overly ambitious task: estimating computationally the additional spectral bands of a color aerial image. We have harnessed the expressive power of deep generative models to estimate the distribution of mostly infrared bands of aerial scenes, using only color RGB channels as input. Our approach has been tested from multiple aspects, including the reconstruction error of the additional bands and the effect of estimated bands on scene classification performance, as well as through the transfer potential of the trained network to a …
Optimized Bilevel Classifier For Brain Tumor Type And Grade Discrimination Using Evolutionary Fuzzy Computing, Kavitha Srinivasan, Mohanavalli Subramaniam, Bharathi Bhagavathsingh
Optimized Bilevel Classifier For Brain Tumor Type And Grade Discrimination Using Evolutionary Fuzzy Computing, Kavitha Srinivasan, Mohanavalli Subramaniam, Bharathi Bhagavathsingh
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, an optimized bilevel brain tumor diagnostic system for identifying the tumor type at the first level and grade of the identified tumor at the second level is proposed using genetic algorithm, decision tree, and fuzzy rule-based approach. The dataset is composed of axial MRI of brain tumor types and grades. From the images, various features such as first and second order statistical and textural features are extracted (26 features). In the first level, tumor type classification was done using decision tree constructed with all features. Further evolutionary computing using genetic algorithms (GA) was applied to select the …
Low-Cost Multiple Object Tracking For Embedded Vision Applications, Muhammad Imran Shehzad, Fazal Wahab Karam, Shoaib Azmat
Low-Cost Multiple Object Tracking For Embedded Vision Applications, Muhammad Imran Shehzad, Fazal Wahab Karam, Shoaib Azmat
Turkish Journal of Electrical Engineering and Computer Sciences
This paper presents a low-cost multiple object tracking (MOT) technique by employing a novel appearance update model for object appearance modeling using K-means. The state-of-the-art work has attained a very high accuracy without considering the real-time aspects necessitated by currently trending embedded vision platforms. The major research on multiple object tracking is used to update the appearance model in every frame while discounting its persistent nature. The proposed appearance update model reduces the computational cost of the state-of-the-art MOT 6-fold by exploiting this facet of persistent appearance over the sequence of frames. To ensure accuracy, the proposed model is tested …
An Efficient Retrieval Algorithm Of Encrypted Speech Based On Inverse Fast Fourier Transform And Measurement Matrix, Qiuyu Zhang, Zixian Ge, Liang Zhou, Yongbing Zhang
An Efficient Retrieval Algorithm Of Encrypted Speech Based On Inverse Fast Fourier Transform And Measurement Matrix, Qiuyu Zhang, Zixian Ge, Liang Zhou, Yongbing Zhang
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, we present an efficient retrieval algorithm for encrypted speech based on an inverse fast Fourier transform and measurement matrix. Our approach improves query performance, as well as retrieval efficiency and accuracy, compared to existing content-based encrypted speech retrieval methods. Our proposed algorithm constructs a perceptual hash scheme using perceptual hash sequences from original speech files. By classifying the sequences and applying run-length compression, we decrease the cloud storage required for the hash index. We secure the speech database by encrypting it with Henon chaos scrambling, which offers excellent resistance to attacks. Experimental results show that the robustness, …
Classification Of The Likelihood Of Colon Cancer With Machine Learning Techniques Using Ftir Signals Obtained From Plasma, Suat Toraman, Mustafa Gi̇rgi̇n, Bi̇lal Üstündağ, İbrahi̇m Türkoğlu
Classification Of The Likelihood Of Colon Cancer With Machine Learning Techniques Using Ftir Signals Obtained From Plasma, Suat Toraman, Mustafa Gi̇rgi̇n, Bi̇lal Üstündağ, İbrahi̇m Türkoğlu
Turkish Journal of Electrical Engineering and Computer Sciences
Colon cancer is one of the major causes of human mortality worldwide and the same can be said for Turkey. Various methods are used for the determination of cancer. One of these methods is Fourier transform infrared (FTIR) spectroscopy, which has the ability to reveal biochemical changes. The most common features used to distinguish patients with cancer and healthy subjects are peak densities, peak height ratios, and peak area ratios. The greatest challenge of studies conducted to distinguish cancer patients from healthy subjects using FTIR signals is that the signals of cancer patients and healthy subjects are similar. In the …
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 …
A Hybrid Sentiment Analysis Method For Turkish, Buket Erşahi̇n, Özlem Aktaş, Deni̇z Kilinç, Mustafa Erşahi̇n
A Hybrid Sentiment Analysis Method For Turkish, Buket Erşahi̇n, Özlem Aktaş, Deni̇z Kilinç, Mustafa Erşahi̇n
Turkish Journal of Electrical Engineering and Computer Sciences
This paper presents a hybrid methodology for Turkish sentiment analysis, which combines the lexicon-based and machine learning (ML)-based approaches. On the lexicon-based side, we use a sentiment dictionary that is extended with a synonyms lexicon. Besides this, we tackle the classification problem with three supervised classifiers, naive Bayes, support vector machines, and J48, on the ML side. Our hybrid methodology combines these two approaches by generating a new lexicon-based value according to our feature generation algorithm and feeds it as one of the features to machine learning classifiers. Despite the linguistic challenges caused by the morphological structure of Turkish, the …
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 …
Extending A Sentiment Lexicon With Synonym--Antonym Datasets: Swnettr++, Fati̇h Sağlam, Burkay Genç, Hayri̇ Sever
Extending A Sentiment Lexicon With Synonym--Antonym Datasets: Swnettr++, Fati̇h Sağlam, Burkay Genç, Hayri̇ Sever
Turkish Journal of Electrical Engineering and Computer Sciences
In our previous studies on developing a general-purpose Turkish sentiment lexicon, we constructed SWNetTR-PLUS, a sentiment lexicon of 37K words. In this paper, we show how to use Turkish synonym and antonym word pairs to extend SWNetTR-PLUS by almost 33 % to obtain SWNetTR++, a Turkish sentiment lexicon of 49K words. The extension was done by transferring the problem into the graph domain, where nodes are words, and edges are synonym--antonym relations between words, and propagating the existing tone and polarity scores to the newly added words using an algorithm we have developed. We tested the existing and new lexicons …
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, …
A Process-Tolerant Low-Power Adder Architecture For Image Processing Applications, Bharat Garg, G K. Sharma
A Process-Tolerant Low-Power Adder Architecture For Image Processing Applications, Bharat Garg, G K. Sharma
Turkish Journal of Electrical Engineering and Computer Sciences
The aggressive CMOS technology scaling in the sub-100-nm regime leads to highly challenging VLSI design due to the presence of unreliable components. The delay failures in arithmetic units are increasing rapidly due to the increased effect of process variation (PV) in scaled technology. This paper introduces a novel process-tolerant low-power adder (Prot-LA) architecture for error-tolerant applications. The proposed Prot-LA architecture segments the operands into two parts and computes addition of the upper parts in carry-propagate, whereas it computes the lower parts in a carry-free manner. In the Prot-LA, the number of bits in carry-propagate and carry-free additions can be reconfigured …
Design Of A Portable And Low-Cost Mass-Sensitive Sensor With The Capability Of Measurements On Various Frequency Quartz Tuning Forks, Mehmet Altay Ünal, İsmai̇l Cengi̇z Koçum, Di̇lek Çökeli̇ler Serdaroğlu
Design Of A Portable And Low-Cost Mass-Sensitive Sensor With The Capability Of Measurements On Various Frequency Quartz Tuning Forks, Mehmet Altay Ünal, İsmai̇l Cengi̇z Koçum, Di̇lek Çökeli̇ler Serdaroğlu
Turkish Journal of Electrical Engineering and Computer Sciences
Recently, sensor and biosensor applications have become widespread and are now significant tools in the biomedical field and other areas. Since quartz tuning fork (QTF) resonance frequency depends on the mass adsorbed to its prongs, it is generally used to measure minor mass change and detect target analyte in picogram levels. This study is undertaken to design and fabricate a sensor device for the measurement of QTF transducers. When QTF sensor studies were investigated, it was found that explanations on the details of instrumentation part were limited, and in addition, there was no compact commercial products. In this study, a …
Hybrid Parliamentary Optimization And Big Bang-Big Crunch Algorithm For Global Optimization, Soner Kiziloluk, Ahmet Bedri̇ Özer
Hybrid Parliamentary Optimization And Big Bang-Big Crunch Algorithm For Global Optimization, Soner Kiziloluk, Ahmet Bedri̇ Özer
Turkish Journal of Electrical Engineering and Computer Sciences
Researchers have developed different metaheuristic algorithms to solve various optimization problems. The efficiency of a metaheuristic algorithm depends on the balance between exploration and exploitation. This paper presents the hybrid parliamentary optimization and big bang-big crunch (HPO-BBBC) algorithm, which is a combination of the parliamentary optimization algorithm (POA) and the big bang-big crunch (BB-BC) optimization algorithm. The intragroup competition phase of the POA is a process that searches for potential points in the search space, thereby providing an exploration mechanism. By contrast, the BB-BC algorithm has an effective exploitation mechanism. In the proposed method, steps of the BB-BC algorithm are …
Identifying Preferred Solutions In Multiobjective Combinatorial Optimization Problems, Banu Lokman, Mustafa Murat Köksalan
Identifying Preferred Solutions In Multiobjective Combinatorial Optimization Problems, Banu Lokman, Mustafa Murat Köksalan
Turkish Journal of Electrical Engineering and Computer Sciences
We develop an evolutionary algorithm for multiobjective combinatorial optimization problems. The algorithm aims at converging the preferred solutions of a decision-maker. We test the performance of the algorithm on the multiobjective knapsack and multiobjective spanning tree problems. We generate the true nondominated solutions using an exact algorithm and compare the results with those of the evolutionary algorithm. We observe that the evolutionary algorithm works well in approximating the solutions in the preferred regions.
Performance Comparison Of Optimization Algorithms In Lqr Controller Design For A Nonlinear System, Ümi̇t Önen, Abdullah Çakan, İlhan İlhan
Performance Comparison Of Optimization Algorithms In Lqr Controller Design For A Nonlinear System, Ümi̇t Önen, Abdullah Çakan, İlhan İlhan
Turkish Journal of Electrical Engineering and Computer Sciences
The development and improvement of control techniques has attracted many researchers for many years. Especially in the controller design of complex and nonlinear systems, various methods have been proposed to determine the ideal control parameters. One of the most common and effective of these methods is determining the controller parameters with optimization algorithms.In this study, LQR controller design was implemented for position control of the double inverted pendulum system on a cart. First of all, the equations of motion of the inverted pendulum system were obtained by using Lagrange formulation. These equations were linearized by Taylor series expansion around the …
Investigation On Communication Aspects Of Multiple Swarm Networked Robotics, Shahzad Ali, Zenib Khan, Ahmad Din, Mahmood Ul Hassan
Investigation On Communication Aspects Of Multiple Swarm Networked Robotics, Shahzad Ali, Zenib Khan, Ahmad Din, Mahmood Ul Hassan
Turkish Journal of Electrical Engineering and Computer Sciences
Swarm robotics is an emerging field of robotics and is envisioned to play a vital role in surveillance and search/rescue operations. Most of the existing works on swarm networked robotics address the problem of formation movement or the communication aspects within a swarm. However, none of the existing works consider multiple swarms. Even for the case of single swarms, researchers use unrealistic assumptions with respect to communication, leading to unrealistic results. In this paper, we evaluate the performance of multiple swarms considering realistic assumptions with respect to communication. To the best of our knowledge, it will be the first time …
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 …
Impact Of The Primary User On The Secondary User Blocking Probability In Cognitive Radio Sensor Networks, Mohammad Mehdi Hassani, Reza Berangi
Impact Of The Primary User On The Secondary User Blocking Probability In Cognitive Radio Sensor Networks, Mohammad Mehdi Hassani, Reza Berangi
Turkish Journal of Electrical Engineering and Computer Sciences
With the increasing usage of wireless sensor network technologies, their unlicensed bands become overcrowded. To address this challenge, cognitive radio technology with the dynamic spectrum access policy has merged with Wireless Sensor Network to overcome spectrum underutilization. The Cognitive Radio Sensor Network (CRSN) has emerged as a promising solution to overcome spectrum scarcity in a resource-constrained wireless sensor network. In CRSN, TCP has to cope with a new type of packet loss due to the primary users (PU) arrival, known here as a secondary user (SU) blocking loss. In this paper SU blocking loss is modelled by a discrete-time Markov …
On Parameter Adjustment Of The Fuzzy Neighborhood-Based Clustering Algorithms, Fatma Günseli̇ Yaşar, Gözde Ulutagay, Semi̇h Utku, Efendi̇ Nasi̇boğlu
On Parameter Adjustment Of The Fuzzy Neighborhood-Based Clustering Algorithms, Fatma Günseli̇ Yaşar, Gözde Ulutagay, Semi̇h Utku, Efendi̇ Nasi̇boğlu
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 …
A Distributed Measurement Architecture For Inferring Tcp Round-Trip Times Through Passive Measurements, Fatih Abut
A Distributed Measurement Architecture For Inferring Tcp Round-Trip Times Through Passive Measurements, Fatih Abut
Turkish Journal of Electrical Engineering and Computer Sciences
The round-trip time (RTT), defined as the time elapsed for transmission of a data packet to travel from one endpoint to the other and back again, is an important parameter for Internet quality. This paper proposes an extended version of the well-known SYN/ACK (SA) methodology for passively measuring the RTTs over Transmission Control Protocol (TCP) connections. Differently from the original version of the SA methodology and the rest of studies in the related literature, the proposed passive methodology measures not only the total RTT of an end-to-end connection but also the proportion of the existing connection sections on this entire …