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  • Öğe
    L-HSAB: A Levantine Twitter Dataset for Hate Speech and Abusive Language
    (Assoc Computational Linguistics-Acl, 2019) Mulki, Hala; Haddad, Hatem; Ali, Chedi Bechikh; Alshabani, Halima
    Hate speech and abusive language have become a common phenomenon on Arabic social media. Automatic hate speech and abusive detection systems can facilitate the prohibition of toxic textual contents. The complexity, informality and ambiguity of the Arabic dialects hindered the provision of the needed resources for Arabic abusive/hate speech detection research. In this paper, we introduce the first publicly-available Levantine Hate Speech and Abusive (L-HSAB) Twitter dataset with the objective to be a benchmark dataset for automatic detection of online Levantine toxic contents. We, further, provide a detailed review of the data collection steps and how we design the annotation guidelines such that a reliable dataset annotation is guaranteed. This has been later emphasized through the comprehensive evaluation of the annotations as the annotation agreement metrics of Cohen's Kappa (k) and Krippendorff's alpha (alpha) indicated the consistency of the annotations.
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    Modeling of Induction Fluid Heater via Transformer Equivalent Circuit
    (Institute of Electrical and Electronics Engineers Inc., 2023) Kelesoğlu, Alper; Ünver, Halil Murat; Ünver, Ümit
    In air conditioning systems where electrical energy is used as input, resistance and infrared heating systems are effectively used today. Due to its advantages, induction heating systems are a technology in the development stage as an alternative to these two technologies. In this study, the electromagnetic performance of an induction gas heater operating at grid frequency is investigated experimentally and theoretically. A mathematical method is developed to determine the conversion efficiency of electrical power to heat on conductive material. The results obtained are compared with experimental findings. © 2023 University of Split, FESB.
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    Flower Pollination Algorithm-Optimized Deep CNN Features for Almond(Prunus dulcis) Classification
    (Institute of Electrical and Electronics Engineers Inc., 2024) Yurdakul, Mustafa; Atabaş, İrfan; Taşdemir, Şakir
    Almond is a nut rich in essential nutrients. In addition to being a food, it is also used in cosmetics and the pharmaceutical industry. The market value of almonds is determined according to the quality of the almonds. Manually determining the quality of almonds by humans is a prone to error, time-consuming, and tiring process. In this study, For this reasons, well-known twelve pre-trained CNNs were used to classify almonds as normal and damaged. Then, the most successful model was used as a feature extractor, and the features were classified with various machine learning algorithms. In addition to all these, features were selected by using the FPA algorithm, and the classification process was carried out. Experimental results showed that the use of CNNs as feature extractors and classification with machine learning algorithms can provide better results than the classical softmax structure. In addition, the proposed FPA-based feature extraction increases the classification performance. © 2024 IEEE.
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    Chestnut(Castanea Sativa) Varieties Classification with Harris Hawks Optimization based Selected Features and SVM
    (Institute of Electrical and Electronics Engineers Inc., 2024) Yurdakul, Mustafa; Atabaş, İrfan; Taşdemir, Şakir
    Chestnut(Castanea sativa) is a nutritious food with a hard outer shell. It is also used in different sectors for various purposes. Chestnut is a commercial product that is in demand worldwide due to its multi-purpose use. In order to determine the market value of chestnuts, it is necessary to classify it according to its types. With classical methods, people classify it manually. However, this method is tiring and error prone. In this study, for classifying chestnut varieties, features were extracted from chestnut images using various feature extraction methods. The extracted features were combined and classified with Linear, Poly and Radial Basis Function(RBF) kernels of Support Vector Machine(SVM). The combined handcrafted features and RBF kernel achieved an accuracy of 94.28%, precision of 93.83%, recall of 93.98%, F1-Score of 93.84%, and AUC of 99.25%. Furthermore, the most relevant features were selected using Arithmetic Optimization, Harris Hawks and Sooty Tern algorithms. The Harris Hawks Optimization selected features and RBF kernel showed the best classification performance with an accuracy of 95.84%, precision of 95.56%, recall of 95.51%, F1-score of 95.46% and AUC of 99.45%. © 2024 IEEE.
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    An Application of Tree Seed Algorithm for Optimization of 50 and 100 Dimensional Numerical Functions
    (Institute of Electrical and Electronics Engineers Inc., 2021) Güngör, İmral; Emiroğlu, Bülent Gürsel; Uymaz, Sait Ali; Kıran, Mustafa Servet
    The Tree-Seed Algorithm is an optimization algorithm created by observing the process of growing and becoming a new tree, the seeds scattering around trees in natural life. In this study, TSA is applied to optimize high-dimensional functions. In previous studies, the performance of the tree seed algorithm applied for the optimization of low-dimensional functions has been proven. Thus, in addition to running the algorithm on 30-dimensional functions before, it has also been applied to solve 50-and 100-dimensional numerical functions. This improvement, called the tree seed algorithm, is based on the use of more solution update mechanisms instead of one mechanism. In the experiments, CEC2015 benchmarking functions are used and the developed tree seed algorithm is compared with the base state of TSA, artificial bee colony, particle swarm optimization and some variants of the differential evolution algorithm. Experimental results are obtained as mean, max, min solutions and standard deviation of 30 different runs. As a result, it is observed by the studies that the developed algorithm gives successful results. © 2021 IEEE.
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    Affecting Factors of Efficiency in Photovoltaic Energy Systems and Productivity-Enhancing Suggestions
    (Institute of Electrical and Electronics Engineers Inc., 2022) Ay, İlker; Kademli, Murat; Karabulut, Şener; Savaş, Serkan
    In recent years, hazardous gases emission from fossil fuels has attracted public concerns due to its worse effects on the ecosystem and living conditions not only mankind but also all creatures living on earth. That's why solar energy has a vital role in alternative energy resources. Solar energy sources will gain more importance in the future. As it is known, the most needed type of energy today is electrical energy. Thus, in this study, the necessary conditions for the photovoltaic (PV) systems used in solar energy production to operate at maximum performance and which parameters are required to control these conditions are examined. The results show that four parameters that we need to measure. These are: maximum operating current of a panel/cell (Impp), maximum operating voltage of a panel/cell (Vmpp), panel surface temperature and light intensity falling on the panel. Except for the panel surface temperature, the rest of the parameters can be measured directly. However, affecting the panel surface temperature; we must not ignore parameters such as ambient temperature, wind speed, humidity and light intensity. Therefore, while determining the panel surface temperature, these parameters should also be measured and a surface temperature should be determined accordingly. © 2022 IEEE.
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    Vision Transformer-based Automatic Detection of COVID-19 in Chest X-ray Images
    (Institute of Electrical and Electronics Engineers Inc., 2023) Yurdakul, Mustafa; Taşdemir, Şakir
    The COVID-19 virus, which first emerged in the city of Wuhan in China, rapidly spread across the globe due to its high contagiousness. Detecting the virus early is crucial to stop its spread and to provide timely treatment to affected individuals. Chest X-ray (CXR) images are a quick, cost- effective, and non-invasive method commonly used for the diagnosis of COVID-19. CXR images are manually inspected by experts for diagnosis. However manually detection is not only time-consuming but also prone to errors due to human fatigue. For these reasons, there is an urgent need for a system that can detect COVID-19 from CXR images. In this study, the Vision Transformer (ViT) model was used to classify Normal, Pneumonia, and COVID-19 from CXR images. Experimental results show that the Vision Transformer (ViT) possesses a robust and high generalization capability, with an accuracy rate of 97%, indicating its significant potential in medical image analysis. © 2023 IEEE.
  • Öğe
    Analysis Of Interoperability In Cloud Computing
    (Assoc Computing Machinery, 2019) Bulent, Emiroglu; Tarek, Alshiply
    Today most of traditional forms of education are not suitable for requirements of educational development and can't keep up with changes in learning demand over time, but Computer networks have provided many opportunities for it. By Cloud Computing software and files are imported into cloud, so word processing, presentations, databases, and more can be accessed from a web browsers. Educational institutions can take advantage of cloud applications to provide students and teachers with free or cost-effective alternatives instead of expensive proprietary productivity tools. In this paper we use semantic models in cloud computing to provide platform-independent data presentation and improve the description of the service. We analyze and discuss how cloud computing can affect boundaries of educational resources in background of semantic web by providing a technological solution using experimental and semantic platforms and numerically cloud services.
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    The Android Malware Static Analysis: Techniques, Limitations, and Open Challenges
    (Ieee, 2018) Bakour, Khaled; Unver, H. Murat; Ghanem, Razan
    This paper aims to explain static analysis techniques in detail, and to highlight the weaknesses and challenges which face it. To this end, more than 80 static analysis based framework have been studied, and in their light, the process of detecting malicious applications has been divided into four phases that were explained in a schematic manner. Also, the features that is used in static analysis were discussed in detail by dividing it into four categories namely, Manifest-based features, code-based features, semantic features and app's metadata-based features. Also, the challenges facing methods based on static analysis were discussed in detail. Finally, a case study was conducted to test the strength of some known commercial antivirus and one of the stat-of-art academic static analysis frameworks against obfuscation techniques used by developers of malicious applications. The results showed a significant impact on the performance of the most tested antiviruses and frameworks, which is reflecting the urgent need for more accurately tools.
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    Open Source Slurm Computer Cluster System Design and a Sample Application
    (Ieee, 2017) Azginoglu, Nuh; Atasever, Mehmet Umt; Aydin, Zafer; Celik, Mete; Erbay, Hasan
    Cluster computing combines the resources of multiple computers as they act like a single high-performance computer. In this study, a computer cluster consisting of Lustre distributed file system with one cluster server based on Slurm resource management system and thirteen calculation nodes were built by using available and inert computers that have different processors. Different bioinformatics algorithms were run using different data sets in the cluster, and the performance of the clusters was evaluated with the amount of time the computing cluster spent to finish the jobs.
  • Öğe
    An Intrusion Detection System Based on a Hybrid Tabu-Genetic Algorithm
    (Ieee, 2017) Bakour, Khaled; Das, Gulesin Sena; Unver, H. Murat
    In this paper, we proposed a framework for detecting network's intrusions using Genetic Algorithm (GA) with multiple criteria. First of all, we build an intrusion detection system (IDS) using a pure GA with multiple selection methods. Then, we proposed one of the few hybrid algorithms in the literature, which is hybridized using a GA and a Tabu search (TS) algorithm. The proposed hybrid algorithm and the pure GA were tested to detect malicious traffic using DARPA dataset. The test results revealed that the proposed hybrid algorithm gives a higher Detection Rate (DR) and Detection Accuracy (AC) compared to the pure GA.
  • Öğe
    Automatic Landmark Detection through Circular Hough Transform in Cephalometric X-rays
    (Ieee, 2017) Duman, Elvan; Kokver, Yunus; Unver, Halil Murat; Erdem, Osman Ayhan
    In this paper, a knowledge based framework is proposed to detect automatically cephalometric landmarks: Porion (Po), Sella (S), Menton (Me), Pogonion (Pg) and Gnathion (Gn). In this way anomalies can be diagnosed easily by orthodontists. Our framework comprise of two main steps: (1) Adaptive Histogram Equalisation (AHE) is applied to clarify the image which is used to determine the method of treatment in orthodontics and obtained from the plain X-ray. (2) Circular Hough Transform method is used to locate the cephalometric landmarks automatically on the processed image, the method was tested on 7 cephalometric images and our framework accurately and automatically locates these 5 cephalometric landmarks.
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    Forming a cloud computing based lifelong learning platform: integration of basic computer courses as mass open online courses to university
    (Iclel Conferences, 2016) Kor, Hakan; Erbay, Hasan; Aksoy, Hamit
    Today's formal educational institutions remain incapable of keeping people's knowledge up to date. Updating information in fields like general culture, information technology, language education and vocational education is needed. Online learning settings, certificate trainings, in service trainings and social network settings greatly contribute to updating information. The learning function is a lifelong process besides formal educational institutions. Lifelong learning can be defined as individual's whole collaboration of events which aims to develop their knowledge, skills and talents individually, vocationally or socially in order to manage their lives. It can be said that a web based learning settings has contributed to the learning processes the most these days. In this regard, people and especially universities grants free access to supply of information they have through Mass Open Online Courses (MOOC). In order for users to access MOOC, having an internet browser is enough. MOOC is also able to develop lifelong learning skills and brings the participants ways of self-learning and information gathering. Strong hardware and software substructure is needed for an MOOC system which will be accessed by thousands. Rapid developments in information technology have decreased hardware costs significantly. By decreasing the costs, developed software and hardware platforms are formed and brought into mutual use of people. Bringing the hardware and software components (storage, data base, mail services and some private software) into people's mutual use form the basis of cloud computing. Cloud computing systems provide great advantages in terms of cost and workforce. Also, through cloud, many subunits can be managed at one origin. In this study, processes of forming a cloud computing based MOOC platform where basic computer technology subjects are included are given place. Through the formed platform, individuals learn new information in the information technology field or keep their knowledge up to date. This will ease people's learning interest and provide lifelong learning opportunity.
  • Öğe
    Latent Semantic Analysis via Truncated ULV Decomposition
    (Ieee, 2016) Varcin, Fatih; Erbay, Hasan; Horasan, Fahrettin
    Latent semantic analysis (LSA) usually uses the singular value decomposition (SVD) of the term-document matrix for discovering the latent relationships within the document collection. With the SVD, by disregarding the smaller singular values of the term-document matrix a vector space cleaned from noises that distort the meaning is obtained. The latent semantic structure of the terms and documents is obtained by examining the relationship of representative vectors in the vector space. However, the computational time of re-computing or updating the SVD of the term-document is high when adding new terms and/or documents to pre-existing document collection. Thus, the need a method not only has low computational complexity but also creates the correct semantic structure when updating the latent semantic structure is arisen. This study shows that the truncated ULV decomposition is a good alternative to the SVD in LSA modelling about cost and producing the correct semantic structure.
  • Öğe
    Design and Implementation of a Basic Microcomputer for Educational Purpose
    (Ieee, 2016) Bakacak, Mehmet; Topal, Taner
    Today, most of electronic equipments includes at least one microcomputer. Microcomputers control the operation of electronic devices and to provide the required operations. The microcomputer has a constantly developing and changing structure according to the needs. To gain necessary information and skill on the structure and operation of the microcomputer is theoretically difficult. In the educational environment, the microcomputer need to embody to give a better understanding. The purpose of this study is design and implement a basic microcomputer by simplifying. Thus, facilitate understanding in education. The microcomputer which was the subject of this study is defined in the fifth section of Morris Mano's computer system architecture book [1] (third edition). Is a Single cycle and has 16 bit data bus, a 12 bit address bus and a memory size of 8 kilobytes. This microcomputer is designed on VHDL and reviewed the implementation on FPGA.
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    A Modelling Study of Renewable and Stored Energy Sharing and Pricing Management System Developed for Multi-Apartment Complexes
    (Ieee, 2014) Kıray, Vedat; Topal, Taner; Sağbansua, Lütfü; Atacak, İsmail
    A unique system that will enable the efficient and shared usage of PV panels in multi-apartment complexes and sharing of energy is developed in this study along with a modeling scheme. Efficient and shared usage of the panels which is suggested as the solution requires sharing and pricing the energy in the apartment complex. In this modeling study which is conducted in Matlab and Simulink environment, the available energy is initially allocated for all the apartments and has them use it for free. The modeled system is applied to a three-apartment complex and the simulation results are obtained based on the electricity pricing tariff in Turkey. The amounts reflected in the electricity bill in the cases where the solar energy used and not used are calculated separately and compared later in the experimental results. It is demonstrated that the shared energy of the apartment complex can be allocated in an efficient and fair way. Moreover, it is proved that the budget generated by using the cheap energy can pay off the fix costs such as battery charge and renewal costs.
  • Öğe
    Comparison of the Proficiency Level of the Course Materials (Animations, Videos, Simulations, E-Books) Used In Distance Education
    (Elsevier Science Bv, 2014) Kor, Hakan; Aksoy, Hamit; Erbay, Hasan
    Activities in the field of distance education have shown a significant improvement in the world and Turkey in parallel with the technology. Activities in this field started through newspapers and letters and they were improved by using printed material, radio, television and internet. Recently, as well as the use of computer and internet have become widespread in the world, web-based distance education systems have been used more than the other teaching tools. In Turkey, departments of distance education attached to the Council of Higher Education were opened in large number and they are still continued to be opened. In this paper, in terms of quality and interactivity it is aimed to evaluate the course materials used by the institutions of distance education. Through the surveys applied to the institutions of distance education determined by choosing from the different regions of Turkey, it was aimed to find out the faults and defects of the course materials in terms of quality and interactivity. By sharing the obtained outputs with related institutions, formation of more efficient distance learning materials will be possible. (C) 2014 The Authors. Published by Elsevier Ltd.
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    Comparison of Principal Component Analysis and Radial Basis Function Network for Diagnosis of Hypertension
    (Turgut Ozal Univ, 2012) Turk, Fuat; Barisci, Necaattin; Ciftci, Aydin; Ekmekci, Yakup
    In this study, from 150 individuals over the age of 30 taken no drugs, sex, age, height, weight, HDL, LDL, Triglyceride, smoking and uric acid were measured. 65 of them are normal but 85 consist of the patients. Data obtained of each patient was applied Artificial Neural Network (ANN) models. The results obtained will be classified as either normal or the patient. Using Principal Component Analysis (PCA), 89% of patient individuals and 88% of normal individuals were classified correctly. Using Radial Basis Function Networks (RBFN), 89% of the patient individuals and 84% of normal individuals were classified correctly.
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    An efficient algorithm for rank and subspace tracking
    (Pergamon-Elsevier Science Ltd, 2006) Erbay, Hasan
    Traditionally, the singular value decomposition (SVD) has been used in rank and subspace tracking methods. However, the SVD is computationally costly, especially when the problem is recursive in nature and the size of the matrix is large. The truncated ULV decomposition (TULV) is an alternative to the SVD. It provides a good approximation to subspaces for the data matrix and can be modified quickly to reflect changes in the data. It also reveals the rank of the matrix. This paper presents a TULV updating algorithm. The algorithm is most efficient when the matrix is of low rank. Numerical results are presented that illustrate the accuracy of the algorithm. (c) 2006 Elsevier Ltd. All rights reserved.
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    Updating TULV decomposition
    (Vsp Bv-C/O Brill Acad Publ, 2005) Erbay, Hasan
    A truncated ULV decomposition (TULVD) of an m x n matrix A of rank k is a decomposition of the form A = U1LV1T + E, where U-1 and V-1 are left orthogonal matrices, L is a lower triangular matrix and E is an error matrix. We present an updating algorithm of order O (nk) that reveals the rank correctly and produces good approximation to the subspaces of the matrix A.