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Articles 6301 - 6330 of 27416
Full-Text Articles in Engineering
On B-Anti-Open Sets: A Formal Definition, Proofs, And Examples, Sudeep Dey, Priyanka Paul, Gautam Chandra Ray
On B-Anti-Open Sets: A Formal Definition, Proofs, And Examples, Sudeep Dey, Priyanka Paul, Gautam Chandra Ray
Neutrosophic Systems with Applications
The concepts of open sets, closed sets, the interior of a set, and the exterior of a set are the most basic concepts in the study of topological spaces in any setting. When we turn our attention to the concept of anti-topological spaces, we encounter analogous fundamental concepts, such as the definition of anti-open sets, anti-closed sets, anti-interior, anti-exterior, etc. These concepts have already been introduced and studied by mathematicians worldwide. In this article, we introduce and study the concepts of b-anti-open set, b-anti-closed set, anti-b-interior, and anti-b-closure in the context of anti-topological spaces and investigate some of their basic …
Superhyperfunction, Superhyperstructure, Neutrosophic Superhyperfunction And Neutrosophic Superhyperstructure: Current Understanding And Future Directions, Florentin Smarandache
Superhyperfunction, Superhyperstructure, Neutrosophic Superhyperfunction And Neutrosophic Superhyperstructure: Current Understanding And Future Directions, Florentin Smarandache
Neutrosophic Systems with Applications
The n-th PowerSet of a Set {or Pn(S)} better describes our real world, because a system S (which may be a company, institution, association, country, society, set of objects/plants/animals/beings, set of concepts/ideas/propositions, etc.) is formed by sub-systems, which in their turn by sub-sub-systems, and so on. We prove that the SuperHyperFunction is a generalization of classical Function, SuperFunction, and HyperFunction. And the SuperHyperAlgebra, SuperHyperGraph are part of the SuperHyperStructure. Almost all structures in our real world are Neutrosophic SuperHyperStructures since they have indeterminate/incomplete/uncertain/conflicting data.
A Review On Ship Recycling Industry In Bangladesh From Global Perspective, Ahammad Abdullah, Zobair Ibn Awal, M Ziauddin Alamgir, Md. Jobayer Mia, Farihatul Mim, Utpal K. Dhar
A Review On Ship Recycling Industry In Bangladesh From Global Perspective, Ahammad Abdullah, Zobair Ibn Awal, M Ziauddin Alamgir, Md. Jobayer Mia, Farihatul Mim, Utpal K. Dhar
Journal of Ocean and Coastal Economics
At present, the global center of the ship breaking and recycling industry is in South Asia, specifically Bangladesh, India, and Pakistan. These three countries account for 70–80 percent of the international recycling market for ocean-going vessels, with China and Turkey covering most of the remaining market. Only about 5 percent of global volume is scrapped outside these five countries. Bangladesh has environmentally beneficial coastal region and affordable labor that make the shipbreaking and recycling business as a potential sector for the country. In addition, ship recycling and its related businesses are helping to solve our nation’s unemployment issues at all …
Strengthening Of Mechanical Properties And Electrical Conductivity Study On 6061 Al Alloy After Ecap Process, Nour Eldeen Megahed, A.M. El-Kassas, Maher Rashad
Strengthening Of Mechanical Properties And Electrical Conductivity Study On 6061 Al Alloy After Ecap Process, Nour Eldeen Megahed, A.M. El-Kassas, Maher Rashad
Mansoura Engineering Journal
The investigation centered around the analysis of enhanced mechanical properties and electrical conductivity in an industrial aluminum alloy that underwent a transformation into an ultra-fine-grained (UFG) state. The aforementioned transformation was successfully accomplished by utilizing a singular iteration of the Equal Channel Angular Pressing (ECAP) method. The study involved conducting evaluations through hardness and compression tests, measuring electrical conductivity, and analyzing microstructures using OM and SEM. After annealing for three hours at a temperature of 4150C, it is experimentally explored how the electrical conductivity and material properties of AA-6061 The mechanical properties of the material are influenced by the level …
Classification Of Kidney Masses Using Convolution Neural Network, Nada M. Yakout, Eman Abdelhalim, Abdalla Abdelhalim, Hossam El-Din Moustafa
Classification Of Kidney Masses Using Convolution Neural Network, Nada M. Yakout, Eman Abdelhalim, Abdalla Abdelhalim, Hossam El-Din Moustafa
Mansoura Engineering Journal
Classification of tumors among kidney masses (KM) through deep neural networks is one of the most important applications for detecting the disease at an early stage. It can increase patient survival rates, prevent mass growth, and prevent complications. Preoperative multi-phase abdominal Contrast Enhancement Computed Tomography (CE-CT) is widely used to detect lesions of kidney masses in order to avoid unneeded biopsy or surgery. However, decisions about treatment are difficult because of inter-observer variability caused by minute variations in the imaging characteristics of mass sub-types. In this study, we offer a comprehensive deep learning model using a Convolutional Neural Networks(CNN) for …
An Image Processing Technique For Studying The Flame Structure Using Single Shots Of Oh-Plif Diagnostics, Hazem M. Al-Bulqini, El-Shafie B. Zeidan, Farouk M. Okasha, Mohy S. Mansour
An Image Processing Technique For Studying The Flame Structure Using Single Shots Of Oh-Plif Diagnostics, Hazem M. Al-Bulqini, El-Shafie B. Zeidan, Farouk M. Okasha, Mohy S. Mansour
Mansoura Engineering Journal
Laser diagnostic techniques have played a crucial role in enhancing our understanding of combustion processes. Among these techniques, Planar Laser-Induced Fluorescence (PLIF) utilizing OH radicals has proven to be a powerful tool for investigating reaction zones, flame curvature, and flame surface density in diverse flame modes including premixed, non-premixed, and partially premixed flames. However, to fully harness the potential of experimental measurements and laser diagnostics in studying combustion processes, a comprehensive grasp of image processing techniques and tools is essential for effectively analyzing captured images and extracting valuable information. In this study, we present a detailed algorithm that facilitates the …
An Efficient Optimal Solution Method For Neutrosophic Transport Models: Analysis, Improvements, And Examples, Maissam Jdid, Florentin Smarandache
An Efficient Optimal Solution Method For Neutrosophic Transport Models: Analysis, Improvements, And Examples, Maissam Jdid, Florentin Smarandache
Neutrosophic Systems with Applications
Transport issues aim to determine the number of units that will be transferred from the production centers to consumption areas so that the cost of transportation is as low as possible, taking into account the conditions of supply and demand. Due to the great importance of these issues and to obtain more accurate results that take into account all circumstances, we conducted two research studies. In the first research, we presented a formulation of neutrosophic transport issues, and in the second research, we presented some ways to find a preliminary solution to these issues, but we do not know whether …
An Efficient Optimal Solution Method For Neutrosophic Transport Models: Analysis, Improvements, And Examples, Maissam Jdid, Florentin Smarandache
An Efficient Optimal Solution Method For Neutrosophic Transport Models: Analysis, Improvements, And Examples, Maissam Jdid, Florentin Smarandache
Neutrosophic Systems with Applications
Transport issues aim to determine the number of units that will be transferred from the production centers to consumption areas so that the cost of transportation is as low as possible, taking into account the conditions of supply and demand. Due to the great importance of these issues and to obtain more accurate results that take into account all circumstances, we conducted two research studies. In the first research, we presented a formulation of neutrosophic transport issues, and in the second research, we presented some ways to find a preliminary solution to these issues, but we do not know whether …
An Exhaustive Review Of Neutrosophic Logic In Addressing Image Processing Issues, Samia Mandour
An Exhaustive Review Of Neutrosophic Logic In Addressing Image Processing Issues, Samia Mandour
Neutrosophic Systems with Applications
Since the importance of images in our lives and the advancements in computer data gathering methods, anyone can collect a large number of images, but most of them cannot be processed manually. Image processing therefore becomes appealing since various types of data may be represented and processed digitally. Image processing has become the most popular processing method, employed in security camera films, healthcare images, images from remote sensors, and naturalistic image/videos because of fast computers and processors. In order to raise cognitive function and speed up decision-making, image processing is crucial to many information access systems. Since ambiguity now permeates …
An Integrated Neutrosophic Approach For The Urban Energy Internet Assessment Under Sustainability Dimensions, Walaa M. Sabry
An Integrated Neutrosophic Approach For The Urban Energy Internet Assessment Under Sustainability Dimensions, Walaa M. Sabry
Neutrosophic Systems with Applications
The urgent issue of climate change has resulted in an increasing preoccupation with the transition to low-carbon energy. The urban energy internet (UEI) enables the efficient utilization of renewable energy via the integration of contemporary energy grids, smart energy services, and cyber-physical systems. Consequently, the assessment of urban energy is vital for the construction of low-carbon cities. This study intends to provide an integrated decision-making approach for addressing assessment challenges related to UEI, with a focus on sustainability. The introduced approach adopts the opinions of three experts to express their opinions through semantic terms in evaluating sustainability factors and evaluating …
Tests Of A Gamma Spectrometer-Neutron Counter Relationship As A Neutron Alarm Metric In Mobile Radiation Search Systems, Jackson N. Wagner, Craig Marianno
Tests Of A Gamma Spectrometer-Neutron Counter Relationship As A Neutron Alarm Metric In Mobile Radiation Search Systems, Jackson N. Wagner, Craig Marianno
International Journal of Nuclear Security
A mobile radiological search system (MRSS) is frequently used in nuclear security to interdict illicit nuclear material. One difficulty an MRSS faces is in characterizing its detectors’ background responses, particularly in its neutron counter(s). This difficulty adds complications to identifying the presence of neutron-emitting radiological materials during an operation. Fortunately, previous work has identified a power law relationship between muons registered by the MRSS’s gamma detectors and background neutrons. This relationship can be applied to estimate the MRSS’s background neutron count rate using that muon count rate. To test the usability of such an estimate, an MRSS was used to …
The Effects Of Silica Sand Particle Size On Drying Using A Vertical Fluid Bed Dryer, Aysun ŞengüL, Soner Celen, Ayşen Haksever
The Effects Of Silica Sand Particle Size On Drying Using A Vertical Fluid Bed Dryer, Aysun ŞengüL, Soner Celen, Ayşen Haksever
The Philippine Agricultural Scientist
The experimental and theoretical relationships of silica sand particle size and drying was compared to predict the minimum fluidization rate in drying at 9.57% moisture. The drying temperature (90°C, 120°C, and 150°C) and particle size (274 ± 0.5 μm, 563 ± 0.5 μm, and 910 ± 0.5 μm) parameters were studied as factors influencing the drying process in the experiment. Upon comparing all the test results, it was found that moisture loss accelerated as drying temperature of the silica sand samples increased. On the other hand, the minimum fluidization rate was found to have varied directly with particle size, in …
Assessing The Effectiveness Of Nuclear Security Training And Education In Ghana, Michael Nii Sanka Ansah, Boris Stepanov Pavlovich, Paul Atta Amoah, David Okoh Kpeglo, Simon Adu, Bright Kwame Afornu
Assessing The Effectiveness Of Nuclear Security Training And Education In Ghana, Michael Nii Sanka Ansah, Boris Stepanov Pavlovich, Paul Atta Amoah, David Okoh Kpeglo, Simon Adu, Bright Kwame Afornu
International Journal of Nuclear Security
Growing attention is being given to nuclear power across several African countries, including in Ghana. The world is depending on nuclear energy as a reliable and efficient means of energy generation. Ghana as a country is developing nuclear energy; thus, equal attention must be directed toward nuclear safety and security. Ghana is gradually developing interest in and is devoting substantial required resources to educating and training on nuclear security to meet the standards required by international bodies. Institutions such as the Nuclear Safety and Security Centre and the School of Nuclear and Allied Sciences of the Ghana Atomic Energy Commission …
Systematic Literature Review On Ontology-Based Indonesian Question Answering System, Fadhila Tangguh Admojo, Adidah Lajis, Haidawati Nasir
Systematic Literature Review On Ontology-Based Indonesian Question Answering System, Fadhila Tangguh Admojo, Adidah Lajis, Haidawati Nasir
Knowledge Engineering and Data Science
Question-Answering (QA) systems at the intersection of natural language processing, information retrieval, and knowledge representation aim to provide efficient responses to natural language queries. These systems have seen extensive development in English and languages like Indonesian present unique challenges and opportunities. This literature review paper delves into the state of ontology-based Indonesian QA systems, highlighting critical challenges. The first challenge lies in sentence understanding, variations, and complexity. Most systems rely on syntactic analysis and struggle to grasp sentence semantics. Complex sentences, especially in Indonesian, pose difficulties in parsing, semantic interpretation, and knowledge extraction. Addressing these linguistic intricacies is pivotal for …
Eeg Classification While Listening To Murottal Al-Quran And Classical Music Using Random Forest Method, Heni Sumarti, Fahira Septiani, Agus Sudarmanto, Wahyu Caesarendra, Rizki Edmi Edison
Eeg Classification While Listening To Murottal Al-Quran And Classical Music Using Random Forest Method, Heni Sumarti, Fahira Septiani, Agus Sudarmanto, Wahyu Caesarendra, Rizki Edmi Edison
Knowledge Engineering and Data Science
This study is aimed to classify the brain activity of adolescents associated with audio stimuli; murottal Al-Quran and classical music. The raw data were filtered using Independent Component Analisys (ICA) and followed by band-pass filter in Python on the Google Colab Extraction was processed with Power Spectral Density (PSD) and the Random Forest Method in Weka Machine Learning was used for classification. The research results showed the same results between the two types of stimulation, namely the order of brain waves from highest to lowest were delta, alpha, theta and beta. The average brain waves of teenagers when given murottal …
Deep Learning Approaches With Optimum Alpha For Energy Usage Forecasting, Aji Prasetya Wibawa, Agung Bella Putra Utama, Ade Kurnia Ganesh Akbari, Akhmad Fanny Fadhilla, Alfiansyah Putra Pertama Triono, Andien Khansa’A Iffat Paramarta, Faradini Usha Setyaputri, Leonel Hernandez
Deep Learning Approaches With Optimum Alpha For Energy Usage Forecasting, Aji Prasetya Wibawa, Agung Bella Putra Utama, Ade Kurnia Ganesh Akbari, Akhmad Fanny Fadhilla, Alfiansyah Putra Pertama Triono, Andien Khansa’A Iffat Paramarta, Faradini Usha Setyaputri, Leonel Hernandez
Knowledge Engineering and Data Science
Energy use is an essential aspect of many human activities, from individual to industrial scale. However, increasing global energy demand and the challenges posed by environmental change make understanding energy use patterns crucial. Accurate predictions of future energy consumption can greatly influence decision-making, supply-demand stability and energy efficiency. Energy use data often exhibits time-series patterns, which creates complexity in forecasting. To address this complexity, this research utilizes Deep Learning (DL), Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Long Short-term Memory (LSTM), Bidirectional LSTM (Bi-LSTM), and Gated Recurrent Unit (GRU) models. The main objective is to improve the accuracy of …
The Effect Of The Number Of Hidden Layers On The Performance Of Deep Q-Network For Traveling Salesman Problem, Benzfica Hanif, Aisyah Larasati, Rudi Nurdiansyah, Trung Le
The Effect Of The Number Of Hidden Layers On The Performance Of Deep Q-Network For Traveling Salesman Problem, Benzfica Hanif, Aisyah Larasati, Rudi Nurdiansyah, Trung Le
Knowledge Engineering and Data Science
The Traveling Salesman Problem (TSP) effectively represents the complex distribution issues encountered by couriers, who must carefully plan a route that includes all customer addresses while minimizing the distance traveled. As the magnitude of deliveries and the range of destinations expand, the courier's responsibility becomes progressively challenging. In this particular context, the objective of our research is to expand the existing knowledge and explore the complete capabilities of Deep Q-Network (DQN) models in order to achieve the most efficient route determination. This endeavor can potentially bring about significant changes in the courier and delivery service sector. The foundation of our …
Stacked Lstm-Gru Long-Term Forecasting Model For Indonesian Islamic Banks, Yayat Sujatna, Adhitio Satyo Bayangkari Karno, Widi Hastomo, Nia Yuningsih, Dody Arif, Sri Setya Handayani, Aqwam Rosadi Kardian, Ire Puspa Wardhani, L.M Rasdi Rere
Stacked Lstm-Gru Long-Term Forecasting Model For Indonesian Islamic Banks, Yayat Sujatna, Adhitio Satyo Bayangkari Karno, Widi Hastomo, Nia Yuningsih, Dody Arif, Sri Setya Handayani, Aqwam Rosadi Kardian, Ire Puspa Wardhani, L.M Rasdi Rere
Knowledge Engineering and Data Science
The development of the Islamic banking industry in Indonesia has become a significant concern in recent years, with rapid growth in the number of banks operating based on Sharia principles. To face emerging challenges and opportunities, a deep understanding of the long-term financial behavior of Islamic banks is becoming increasingly important. This study aims to predict the share price of PT Bank Syariah Indonesia Tbk, over 28 days using the LSTM-GRU stack. The observation stage includes importing the dataset, data separation, model variations, the training process, output, and evaluation. Observations were conducted using 10 model variations from 4 stacks of …
Comparison Of Machine Learning Algorithms For Species Family Classification Using Dna Barcode, Lala Septem Riza, M Ammar Fadhlur Rahman, Yudi Prasetyo, Muhammad Iqbal Zain, Herbert Siregar, Topik Hidayat, Khyrina Airin Fariza Abu Samah, Miftahurrahma Rosyda
Comparison Of Machine Learning Algorithms For Species Family Classification Using Dna Barcode, Lala Septem Riza, M Ammar Fadhlur Rahman, Yudi Prasetyo, Muhammad Iqbal Zain, Herbert Siregar, Topik Hidayat, Khyrina Airin Fariza Abu Samah, Miftahurrahma Rosyda
Knowledge Engineering and Data Science
Classifying plant species within the Liliaceae and Amaryllidaceae families presents inherent challenges due to the complex genetic diversity and overlapping morphological traits among species. This study explores the difficulties in accurate classification by comparing 11 supervised learning algorithms applied to DNA barcode data, aiming to enhance the precision of species family classification in these taxonomically intricate plant families. The ribulose-1,5-bisphosphate carboxylase-oxygenase large sub-unit (rbcL) gene, selected as a DNA barcode locus for plants, is used to represent species within the Amaryllidaceae and Liliaceae families. The experimental results demonstrate that nearly all tested models achieve accurate species classification into the appropriate …
Multivariate Analysis Approach To Factor-Affected Tuberculosis Disease, Zuli Agustina Gultom, Farid Akbar Siregar, Mahardika Abdi Prawira Tanjung, Al-Hamidy Hazidar
Multivariate Analysis Approach To Factor-Affected Tuberculosis Disease, Zuli Agustina Gultom, Farid Akbar Siregar, Mahardika Abdi Prawira Tanjung, Al-Hamidy Hazidar
Knowledge Engineering and Data Science
Tuberculosis is a disease caused by infection with the mycobacterium tuberculosis complex. Tuberculosis attack organ besides the lung, such as the pleura, lining of the brain, lining of the heart, lymph gland, bones, joint, skin, intestines, kidney, urinary tract, and genital. This disease is found in densely populated settlements with poor sanitation, lack of ventilation and sunlight and lack of rest. Moreover, the factors that will be analyzed in this research are Population Density (X1), Number of HIV/AIDS (X2), number of toddlers who experience nutrition (X3), Number of toddlers who experience BCG immunization (X4), number of toddlers who get exclusive …
Evidence Of Students’ Academic Performance At The Federal College Of Education Asaba Nigeria: Mining Education Data, Arnold Adimabua Ojugo, Christopher Chukwufunaya Odiakaose, Frances Emordi, Rita Erhovwo Ako, Winifred Adigwe, Kizito Eluemonor Anazia, Victor Geteloma
Evidence Of Students’ Academic Performance At The Federal College Of Education Asaba Nigeria: Mining Education Data, Arnold Adimabua Ojugo, Christopher Chukwufunaya Odiakaose, Frances Emordi, Rita Erhovwo Ako, Winifred Adigwe, Kizito Eluemonor Anazia, Victor Geteloma
Knowledge Engineering and Data Science
One main objective of higher education is to provide quality education to its students. One way to achieve the highest level of quality in the higher education system is by discovering knowledge for prediction regarding enrolment of students in a particular course, alienation of traditional classroom teaching model, detection of unfair means used in online examination, detection of abnormal values in the result sheets of the students, and prediction about students’ performance. The knowledge is hidden among the educational data set and is extractable through data mining techniques. The present paper is designed to justify the capabilities of data mining …
Recurrent Session Approach To Generative Association Rule Based Recommendation, Tubagus Arief Armanda, Ire Puspa Wardhani, Tubagus M. Akhriza, Tubagus M. Adrie Admira
Recurrent Session Approach To Generative Association Rule Based Recommendation, Tubagus Arief Armanda, Ire Puspa Wardhani, Tubagus M. Akhriza, Tubagus M. Adrie Admira
Knowledge Engineering and Data Science
This article introduces a generative association rule (AR)-based recommendation system (RS) using a recurrent neural network approach implemented when a user searches for an item in a browsing session. It is proposed to overcome the limitations of the traditional AR-based RS which implements query-based sessions that are not adaptive to input series, thus failing to generate recommendations. The dataset used is accurate retail transaction data from online stores in Europe. The contribution of the proposed method is a next-item prediction model using LSTM, but what is trained to develop the model is an associative rule string, not a string of …
An Integrated Neutrosophic Approach For The Urban Energy Internet Assessment Under Sustainability Dimensions, Walaa M. Sabry
An Integrated Neutrosophic Approach For The Urban Energy Internet Assessment Under Sustainability Dimensions, Walaa M. Sabry
Neutrosophic Systems with Applications
The urgent issue of climate change has resulted in an increasing preoccupation with the transition to low-carbon energy. The urban energy internet (UEI) enables the efficient utilization of renewable energy via the integration of contemporary energy grids, smart energy services, and cyber-physical systems. Consequently, the assessment of urban energy is vital for the construction of low-carbon cities. This study intends to provide an integrated decision-making approach for addressing assessment challenges related to UEI, with a focus on sustainability. The introduced approach adopts the opinions of three experts to express their opinions through semantic terms in evaluating sustainability factors and evaluating …
An Exhaustive Review Of Neutrosophic Logic In Addressing Image Processing Issues, Samia Mandour
An Exhaustive Review Of Neutrosophic Logic In Addressing Image Processing Issues, Samia Mandour
Neutrosophic Systems with Applications
Since the importance of images in our lives and the advancements in computer data gathering methods, anyone can collect a large number of images, but most of them cannot be processed manually. Image processing therefore becomes appealing since various types of data may be represented and processed digitally. Image processing has become the most popular processing method, employed in security camera films, healthcare images, images from remote sensors, and naturalistic image/videos because of fast computers and processors. In order to raise cognitive function and speed up decision-making, image processing is crucial to many information access systems. Since ambiguity now permeates …
Application Of Virtual-Real Simulation In Military Field, Ziquan Mao, Jialong Gao, Jianxing Gong, Quan Liu
Application Of Virtual-Real Simulation In Military Field, Ziquan Mao, Jialong Gao, Jianxing Gong, Quan Liu
Journal of System Simulation
Abstract: The definition and content of the virtual-real simulation are presented. According to different technical ideas, the development status and existing problems of virtual-real simulation are summarized from three aspects of digital twin, live-virtual-constructive (LVC) simulation, and parallel system. The similarities and differences, as well as the advantages and disadvantages of the three methods are analyzed and compared, and their main application fields are discussed. In order to deal with difficulties encountered in military training, operational tests, equipment development, and equipment maintenance, a solution based on virtual-real simulation is proposed by means of theoretical guidance, case comparison, and transfer and …
Charge Transfer Evaluation In Solid Insulating Materials Encapsulating The Gaseous Voids Of Submillimeter Dimensions Using Transmission Line Method, Amin Shamsi, Alireza Ganjovi, Amir Abas Shayegani Akmal
Charge Transfer Evaluation In Solid Insulating Materials Encapsulating The Gaseous Voids Of Submillimeter Dimensions Using Transmission Line Method, Amin Shamsi, Alireza Ganjovi, Amir Abas Shayegani Akmal
Turkish Journal of Electrical Engineering and Computer Sciences
In this work, using a lumped RC circuit model which is based on transmission line modeling (TLM) method, the charge transfer in a solid insulating system encapsulating a gaseous void of submillimeter dimensions is evaluated. Here, both the dielectric material and gaseous void are considered simultaneously as a transmission line. The transmission line includes the capacitive and resistance elements and, the obtained circuit equations were coupled with the continuity and kinetic energy equations for charged species along with Poisson's equation. These equations are solved via 4th order Runge-Kutta method and, the electric field and potential, density of all the charged …
A Practical Low-Dimensional Feature Vector Generation Method Based On Wavelet Transform For Psychophysiological Signals, Erdem Erkan, Yasemi̇n Erkan
A Practical Low-Dimensional Feature Vector Generation Method Based On Wavelet Transform For Psychophysiological Signals, Erdem Erkan, Yasemi̇n Erkan
Turkish Journal of Electrical Engineering and Computer Sciences
High-dimensional feature vectors entail computational cost and computational complexity. However, a successful classification can be obtained with an optimally sized feature vector consisting of distinctive features. With the widespread use of the internet and mobile devices, the need for systems with low computational costs is increasing day by day. In this study, starting from the idea that each motor imagery is represented as a subject-specific pattern in the brain, we propose a new and practical method that can generate a low-dimensional feature vector based on wavelet transform. The feature vector is obtained from the correlation between each trial and each …
Lsav: Lightweight Source Address Validation In Sdn To Counteract Ip Spoofing-Based Ddos Attacks, Ali̇ Karakoç, Fati̇h Alagöz
Lsav: Lightweight Source Address Validation In Sdn To Counteract Ip Spoofing-Based Ddos Attacks, Ali̇ Karakoç, Fati̇h Alagöz
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, we propose a design to detect and prevent IP spoofing-based distributed denial of service (DDoS) attacks on software-defined networks (SDNs). DDoS attacks are still one of the significant problems for internet service providers (ISPs) and individual users. These attacks can disrupt customer services by targeting the availability of the system, and in some cases, they can completely shut down the target infrastructure. Protecting the system against DDoS attacks is therefore crucial for ensuring the reliability and availability of internet services. To address this problem, we propose a lightweight source address validation (LSAV) framework that leverages the flexibility …
Exploring The Impact Of Training Datasets On Turkish Stance Detection, Muhammed Sai̇d Zengi̇n, Berk Utku Yeni̇sey, Mücahi̇d Kutlu
Exploring The Impact Of Training Datasets On Turkish Stance Detection, Muhammed Sai̇d Zengi̇n, Berk Utku Yeni̇sey, Mücahi̇d Kutlu
Turkish Journal of Electrical Engineering and Computer Sciences
Stance detection has garnered considerable attention from researchers due to its broad range of applications, including fact-checking and social computing. While state-of-the-art stance detection models are usually based on supervised machine learning methods, their effectiveness is heavily reliant on the quality of training data. This problem is more prevalent in stance detection task because the stance of a text is intimately tied to the target under consideration. While numerous datasets exist for stance detection, determining their suitability for a specific target can be challenging. In this work, we focus on Turkish stance detection and explore the impact of training data …
A Comparative Study Of Blind Source Separation Methods, Burak Baysal, Mehmet Önder Efe
A Comparative Study Of Blind Source Separation Methods, Burak Baysal, Mehmet Önder Efe
Turkish Journal of Electrical Engineering and Computer Sciences
Blind source separation is a popular research topic used for decomposing mixed signals, particularly in the field of music. In addition to exploring machine learning-based approaches, this study aims to examine the performance of classical algorithms in separating audio signal sources. The evaluation of different genres is a significant aspect of this study as the performance of the methods may vary across various musical genres and different audio components. This consideration provides a novel perspective and contributes to a comprehensive analysis of the algorithms. Using the MusDB-HQ dataset, we conducted experimental studies comparing classical algorithms, including FastICA, NMF, and DUET, …