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Articles 211 - 240 of 8896

Full-Text Articles in Physical Sciences and Mathematics

Lsav: Lightweight Source Address Validation In Sdn To Counteract Ip Spoofing-Based Ddos Attacks, Ali̇ Karakoç, Fati̇h Alagöz Nov 2023

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 …

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Exploring The Impact Of Training Datasets On Turkish Stance Detection, Muhammed Sai̇d Zengi̇n, Berk Utku Yeni̇sey, Mücahi̇d Kutlu Nov 2023

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 …

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A Novel Computing Scheme Based On Pattern Matching For Identification Of Nephron Loss And Chronic Kidney Disease Stage, Rehan Ahmad, Basant Mohanty Nov 2023

A Novel Computing Scheme Based On Pattern Matching For Identification Of Nephron Loss And Chronic Kidney Disease Stage, Rehan Ahmad, Basant Mohanty

Turkish Journal of Electrical Engineering and Computer Sciences

Nephrons are the basic filtering units of the kidneys. Progression of chronic kidney disease (CKD) destroys nephrons permanently. Although there are many computing schemes suggested in recent years to identify CKD stages, no computing method has been suggested for identifying the nephron loss within kidney regions during CKD progression. In this paper, a novel pattern matching-based computation scheme is proposed to detect nephron loss in the kidney regions during CKD progression. We consider image registration (IR) with different transforms and a structural similarity index algorithm (SSIM) to match patterns of ultrasound images of kidney regions to identify the nephron loss. …

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A Comparative Study Of Blind Source Separation Methods, Burak Baysal, Mehmet Önder Efe Nov 2023

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, …

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Preparation And Lithium Storage Properties Of Carbon Confined Li3Vo4 Nano Materials, Jia-Qi Fan, Huan-Qiao Song, Jia-Ying An, Amantai A-Yi-Da-Na, Mo Chen Nov 2023

Preparation And Lithium Storage Properties Of Carbon Confined Li3Vo4 Nano Materials, Jia-Qi Fan, Huan-Qiao Song, Jia-Ying An, Amantai A-Yi-Da-Na, Mo Chen

Journal of Electrochemistry

Li3VO4, as a promising anode material for lithium ion batteries, has been widely studied because of its low and safe voltage, and large capacity. However, its poor electronic conductivity impedes the practical application of Li3VO4 particularly at high rates. In this paper, carbon confined Li3VO4 nano materials (Li3VO4/C) were synthesized by hydrothermal and solid-phase method, and for comparison, the Li3VO4 (N) nano materials without carbon confinement and Li3VO4 (B) materials were also synthesized by pure solid-phase method. The composition, structure, morphology and specific …

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Peg-Water Electrolyte For High-Performance Zinc Iodine Dual-Ion Batteries, Xiao-Feng Qu, Yu-Ting Tang, Xin-Cheng He, Jia-Sheng Zhou, Zi-Heng Tang, Wen-Hua Feng, Jun Liu Nov 2023

Peg-Water Electrolyte For High-Performance Zinc Iodine Dual-Ion Batteries, Xiao-Feng Qu, Yu-Ting Tang, Xin-Cheng He, Jia-Sheng Zhou, Zi-Heng Tang, Wen-Hua Feng, Jun Liu

Journal of Electrochemistry

Thanks to abundant resource and rapid redox reaction kinetics, iodine is regarded as promising positive materials inthe batteries. However, the shuttling effect due to the high solubility of iodine in the electrolyte makes the performance of battery poor. In this paper, polyethylene glycol (PEG400) and potassium iodide were added into zinc-ion aqueous electrolyte. PEG400 could complex with iodine to reduce the dissolution of iodine, therefore alleviating the formation of soluble triiodide (I3–) from iodine and iodide ions. Furthermore, this electrolyte was used in the battery with double carbon cloths as the current collectors, double separators and zinc …

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Constructing Carbon-Encapsulated Nifev-Based Electrocatalysts By Alkoxide-Based Self-Template Method For Oxygen Evolution Reaction, En-Hui Ma, Xu-Po Liu, Tao Shen, De-Li Wang Nov 2023

Constructing Carbon-Encapsulated Nifev-Based Electrocatalysts By Alkoxide-Based Self-Template Method For Oxygen Evolution Reaction, En-Hui Ma, Xu-Po Liu, Tao Shen, De-Li Wang

Journal of Electrochemistry

The development of green and sustainable water-splitting hydrogen production technology is beneficial to reducing the over-reliance on fossil fuels and realizing the strategic goal of "carbon neutral". As one of the half reactions for water splitting, oxygen evolution reaction has suffered the problems of sluggish four-electron transfer process and relatively slow reaction kinetics. Therefore, exploring efficient and stable catalysts for oxygen evolution reaction is of critical importance for water-splitting technology. Metal alkoxides are a series of compounds formed by the coordination function of metal ions with alcohol molecules. Metal alkoxides possess the double advantages of organic materials and inorganic materials, …

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Lif-Sn Composite Modification Layer To Modify Garnet/Lithium Metal Interface, Wu Yang, Xue-Fan Zheng, Yu-Qi Wu, Zheng-Liang Gong Nov 2023

Lif-Sn Composite Modification Layer To Modify Garnet/Lithium Metal Interface, Wu Yang, Xue-Fan Zheng, Yu-Qi Wu, Zheng-Liang Gong

Journal of Electrochemistry

The growing demands for electric vehicles and consumer electronics; as well as the expanding renewable energy storage market; have promoted extensive research on energy storage technologies with low costhigh energy density and safety. Lithium (Li) metal and solid-state electrolytes are considered as important components for next-generation batteries because of their great potential for improvements in energy density and safety performance. Inorganic garnet-type solid electrolytes with high Li-ion conductivity (about 10-3 S·cm-1) and high shear modulus (55 GPa) are considered to be ideal solid-state electrolytes; however; the issue of Li dendrite growth still obstructs their practical application. Herein; …

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Does Green Energy Really Matter For Environment And Economic Sustainability? Validating The Long-Standing Existing Empirics On Pakistan Economy, Syed Kafait Hussain Naqvi Nov 2023

Does Green Energy Really Matter For Environment And Economic Sustainability? Validating The Long-Standing Existing Empirics On Pakistan Economy, Syed Kafait Hussain Naqvi

CBER Conference

The empirical outcomes of the study validate the widespread concern of the literature on the existence of the “growth hypothesis” which supports, that there is a systematic positive causation running from green energy to economic sustainability. The study findings suggest that regulations in the energy sector can encourage the applications of green energy resources, particularly in the real sector of the economy, leading to reduced emissions.

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Food-Water-Energy Nexus In The Perspective Of Green Revolution, Green Energy, Legal And Institutional Framework: A Killian Based Adjusted Bootstrap Approach, Zia Ur Rahman Nov 2023

Food-Water-Energy Nexus In The Perspective Of Green Revolution, Green Energy, Legal And Institutional Framework: A Killian Based Adjusted Bootstrap Approach, Zia Ur Rahman

CBER Conference

Food and water energy is crucial for human well-being, sustainable development, and poverty reduction. The growing global demand driven by population growth, economic development, urbanization, changing diets, technological advancements, and climate change projections indicates a significant increase in the need for these resources. Understanding the intricate interdependencies between food, water, and energy is essential for effectively addressing these challenges and fostering a prosperous and sustainable future. Therefore, this study incorporated statistical data collected from the Pakistan Economic Survey and the World Governance Indicator from 1990 to 2022 to elucidate the complex connection between food, water, and energy.

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Demand Analysis Of Energy Mix In District Kotli Azad Jammu And Kashmir, Pakistan, Syed Kafait Hussain Naqvi Nov 2023

Demand Analysis Of Energy Mix In District Kotli Azad Jammu And Kashmir, Pakistan, Syed Kafait Hussain Naqvi

CBER Conference

This study is an effort to empirically analyze the household’s demand for energy mix (electricity, liquefied petroleum gas (LPG), kerosene, and firewood) in the District Kotli, AJK. The study estimates the demand elasticities (price and expenditure) by employing the Linear Approximate Almost Ideal Demand System (LA-AIDS) to 384 households sampled across District Kotli, AJK in 2017. The empirical estimations are carried out by using the Seemingly Unrelated Regression (SUR), keeping intact the adding-up, homogeneity and symmetry restrictions.

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System-Level Noise Performance Of Coherent Imaging Systems, Derek J. Burrell, Joshua H. Follansbee, Mark F. Spencer, Ronald G. Driggers Nov 2023

System-Level Noise Performance Of Coherent Imaging Systems, Derek J. Burrell, Joshua H. Follansbee, Mark F. Spencer, Ronald G. Driggers

Faculty Publications

We provide an in-depth analysis of noise considerations in coherent imaging, accounting for speckle and scintillation in addition to “conventional” image noise. Specifically, we formulate closed-form expressions for total effective noise in the presence of speckle only, scintillation only, and speckle combined with scintillation. We find analytically that photon shot noise is uncorrelated with both speckle and weak-to-moderate scintillation, despite their shared dependence on the mean signal. Furthermore, unmitigated speckle and scintillation noise tends to dominate coherent-imaging performance due to a squared mean-signal dependence. Strong coupling occurs between speckle and scintillation when both are present, and we characterize this behavior …

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Optimal And Robust Control Problems Of Microalgae Cultivation, Mariana Rodriguez-Jara, Luis A. Ricardez-Sandoval, Carlos E. Ramirez-Castelan, Hector Puebla Nov 2023

Optimal And Robust Control Problems Of Microalgae Cultivation, Mariana Rodriguez-Jara, Luis A. Ricardez-Sandoval, Carlos E. Ramirez-Castelan, Hector Puebla

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

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Motif-Cluster: A Spatial Clustering Package For Repetitive Motif Binding Patterns, Mengyuan Zhou Nov 2023

Motif-Cluster: A Spatial Clustering Package For Repetitive Motif Binding Patterns, Mengyuan Zhou

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Previous efforts in using genome-wide analysis of transcription factor binding sites (TFBSs) have overlooked the importance of ranking potential significant regulatory regions, especially those with repetitive binding within a local region. Identifying these homogenous binding sites is critical because they have the potential to amplify the binding affinity and regulation activity of transcription factors, impacting gene expression and cellular functions. To address this issue, we developed an open-source tool Motif-Cluster that prioritizes and visualizes transcription factor regulatory regions by incorporating the idea of local motif clusters. Motif-Cluster can rank the significant transcription factor regulatory regions without the need for experimental …

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Impact Of Silicon Ion Irradiation On Aluminum Nitride-Transduced Microelectromechanical Resonators, David D. Lynes, Joshua Young, Eric Lang, Hengky Chandrahalim Nov 2023

Impact Of Silicon Ion Irradiation On Aluminum Nitride-Transduced Microelectromechanical Resonators, David D. Lynes, Joshua Young, Eric Lang, Hengky Chandrahalim

Faculty Publications

Microelectromechanical systems (MEMS) resonators use is widespread, from electronic filters and oscillators to physical sensors such as accelerometers and gyroscopes. These devices' ubiquity, small size, and low power consumption make them ideal for use in systems such as CubeSats, micro aerial vehicles, autonomous underwater vehicles, and micro-robots operating in radiation environments. Radiation's interaction with materials manifests as atomic displacement and ionization, resulting in mechanical and electronic property changes, photocurrents, and charge buildup. This study examines silicon (Si) ion irradiation's interaction with piezoelectrically transduced MEMS resonators. Furthermore, the effect of adding a dielectric silicon oxide (SiO2) thin film is …

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Cyberattacks And Security Of Cloud Computing: A Complete Guideline, Muhammad Dawood, Shanshan Tu, Chuangbai Xiao, Hisham Alasmary, Muhammad Waqas, Sadaqat Ur Rehman Nov 2023

Cyberattacks And Security Of Cloud Computing: A Complete Guideline, Muhammad Dawood, Shanshan Tu, Chuangbai Xiao, Hisham Alasmary, Muhammad Waqas, Sadaqat Ur Rehman

Research outputs 2022 to 2026

Cloud computing is an innovative technique that offers shared resources for stock cache and server management. Cloud computing saves time and monitoring costs for any organization and turns technological solutions for large-scale systems into server-to-service frameworks. However, just like any other technology, cloud computing opens up many forms of security threats and problems. In this work, we focus on discussing different cloud models and cloud services, respectively. Next, we discuss the security trends in the cloud models. Taking these security trends into account, we move to security problems, including data breaches, data confidentiality, data access controllability, authentication, inadequate diligence, phishing, …

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Growth Of Germanium Thin Films On Sapphire Using Molecular Beam Epitaxy, Emmanuel Wangila, Peter Lytvyn, Hryhorii Stanchu, Calbi Gunder, Fernando Maia De Oliveira, Samir Saha, Subhashis Das, Niroshi Eldose, Chen Li, Mohammad Zamani-Alavijeh, Mourad Benamara, Yuriy I. Mazur, Shui-Qing Yu, Gregory J. Salamo Nov 2023

Growth Of Germanium Thin Films On Sapphire Using Molecular Beam Epitaxy, Emmanuel Wangila, Peter Lytvyn, Hryhorii Stanchu, Calbi Gunder, Fernando Maia De Oliveira, Samir Saha, Subhashis Das, Niroshi Eldose, Chen Li, Mohammad Zamani-Alavijeh, Mourad Benamara, Yuriy I. Mazur, Shui-Qing Yu, Gregory J. Salamo

Electrical Engineering Faculty Publications and Presentations

Germanium films were grown on c-plane sapphire with a 10 nm AlAs buffer layer using molecular beam epitaxy. The effects of Ge film thickness on the surface morphology and crystal structure were investigated using ex situ characterization techniques. The nucleation of Ge proceeds by forming (111) oriented three-dimensional islands with two rotational twin domains about the growth axis. The boundaries between the twin grains are the origin of the 0.2% strain and tilt grains. The transition to a single-grain orientation reduces the strain and results in a better-quality Ge buffer. Understanding the role of thickness on material quality during the …

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The Algorithm For The Design Of Fine Granular Substances’ Smart-Type Heat And Moisture Converters Based On Their Accuracy And Speed Criteria, Erkin Uljaev, Ali Abduakhatovich Abduraxmanov Oct 2023

The Algorithm For The Design Of Fine Granular Substances’ Smart-Type Heat And Moisture Converters Based On Their Accuracy And Speed Criteria, Erkin Uljaev, Ali Abduakhatovich Abduraxmanov

Chemical Technology, Control and Management

The paper describes a technique and algorithm allowing to perform parametric design of smart-type heat and moisture converters (hereinafter SHMC) of fine-grained dispersive materials based on their criteria of accuracy and speed. The proposed algorithm optimizes the process of design of smart-type switches and ensure optimal performance of the switches. The method of calculation and selection of optimal parameters of smart-type heat and moisture converters intended to be used in the measurement of parameters such as heat and humidity of fine dispersive substances are aimed at boosting two parameters, i.e., the accuracy and speed. Also, the design stages have been …

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Preparation And Electrocatalytic Performance Of Feni-Cop/Nc Bifunctional Catalyst, Si-Miao Liu, Jing-Jiao Zhou, Shi-Jun Ji, Zhong-Sheng Wen Oct 2023

Preparation And Electrocatalytic Performance Of Feni-Cop/Nc Bifunctional Catalyst, Si-Miao Liu, Jing-Jiao Zhou, Shi-Jun Ji, Zhong-Sheng Wen

Journal of Electrochemistry

Rechargeable zinc-air batteries have gradually attracted much attention worldwide due to their high capacity, high energy density and low price. Oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) correspond to the charging and discharging processes in rechargeable zinc-air battery, respectively. At present, commercial Pt/C and IrO2 catalysts hinder the large-scale application of zinc-air batteries due to low reserves, high prices and poor stability. Therefore, exploring high performance, low cost and high stability with dual functional catalysts is important for the development of rechargeable zinc-Air batteries. The metal-organic frameworks (MOFs) have high specific surface area, structural stability, good catalytic …

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Research Progress And Performance Improvement Strategies Of Hard Carbon Anode Materials For Sodium-Ion Batteries, Xiu-Ping Yin, Yu-Feng Zhao, Jiu-Jun Zhang Oct 2023

Research Progress And Performance Improvement Strategies Of Hard Carbon Anode Materials For Sodium-Ion Batteries, Xiu-Ping Yin, Yu-Feng Zhao, Jiu-Jun Zhang

Journal of Electrochemistry

This paper systematically summarizes the research progress of hard carbon anode materials in sodium ion batteries(SIBs) and the development of the corresponding sodium storage mechanism in recent years, and reviews the performance improvement strategies of hard carbon materials from the aspects of structural design and electrolyte regulation. The effects of the selection of precursors, carbonization temperature, pretreatment, pore formers, heteroatom doping, material compounding, electrolyte regulation and pre-sodiumization on the sodium storage performance of hard carbon anode materials are briefly described. This paper provides new insights into the design, synthesis and electrolyte
matching of high-performance and low-cost hard carbon materials, and …

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Surface Modifications Of Lini0.96Co0.02Mn0.02O2 With Tungsten Oxide And Phosphotungstic Acid, Gang Zhao, Zheng-Liang Gong, Yi-Xiao Li, Yong Yang Oct 2023

Surface Modifications Of Lini0.96Co0.02Mn0.02O2 With Tungsten Oxide And Phosphotungstic Acid, Gang Zhao, Zheng-Liang Gong, Yi-Xiao Li, Yong Yang

Journal of Electrochemistry

With the rapid development of electric vehicles, enormous demands are made for higher energy density, better cycling performance and lower cost of lithium-ion batteries (LIBs). As an important high capacity cathode material for LIBs, the high nickel layered oxide material LiNi0.8Co0.1Mn0.1O2(NCM811) can reach an energy density of 760 Wh·kg-1. The ultra-high nickel ternary positive electrode material (LiNi1-x-yCoxMnyO2, x ≥ 0.90) has a specific capacity of more than 210 mAh·g-1, and can realize higher energy density. Besides, an ultra-high nickel material …

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Directional Microwave Emission From Femtosecond-Laser Illuminated Linear Arrays Of Superconducting Rings, Thomas J. Bullard, Kyle Frische, Charlie Ebbing, Stephen J. Hageman, John Morrison, John Bulmer, Enam A. Chowdury, Michael L. Dexter, Timothy J. Haugan, Anil K. Patniak Oct 2023

Directional Microwave Emission From Femtosecond-Laser Illuminated Linear Arrays Of Superconducting Rings, Thomas J. Bullard, Kyle Frische, Charlie Ebbing, Stephen J. Hageman, John Morrison, John Bulmer, Enam A. Chowdury, Michael L. Dexter, Timothy J. Haugan, Anil K. Patniak

Faculty Publications

We examine the electromagnetic emission from two photo-illuminated linear arrays composed of inductively charged superconducting ring elements. The arrays are illuminated by an ultrafast infrared laser that triggers microwave broadband emission detected in the 1–26 GHz range. Based on constructive interference from the arrays a narrowing of the forward radiation lobe is observed with increasing element count and frequency demonstrating directed GHz emission. Results suggest that higher frequencies and a larger number of elements are achievable leading to a unique pulsed array emitter concept that can span frequencies from the microwave to the terahertz (THz) regime.

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Dynamic Mechanism Of Science Based Technological Innovation And Industrial Evolution—Take Semiconductor, Digital Computer And Radio Technologies As Examples, Yi Zhang, Qiang Yan Oct 2023

Dynamic Mechanism Of Science Based Technological Innovation And Industrial Evolution—Take Semiconductor, Digital Computer And Radio Technologies As Examples, Yi Zhang, Qiang Yan

Bulletin of Chinese Academy of Sciences (Chinese Version)

By studying the technological innovation and industrial development process of semiconductor, digital computer and radio, this study analyzes the path, conditions and force of science-based technological innovation and its industrialization, establishes a chain reaction model of large-scale technological innovation and diffusion, and compares it with market-based technological innovation. It is found that the large-scale aggregation of scientific research institutions and industrial laboratories accelerates the speed of technological innovation, and diffuses along two paths of scientific research institutions to enterprises and enterprises to enterprises, forming a chain reaction of large-scale technological innovation. Strategic demand is the basic driving force for the …

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Fortifying Iot Against Crimpling Cyber-Attacks: A Systematic Review, Usman Tariq, Irfan Ahmed, Muhammad Attique Khan, Ali Kashif Bashir Oct 2023

Fortifying Iot Against Crimpling Cyber-Attacks: A Systematic Review, Usman Tariq, Irfan Ahmed, Muhammad Attique Khan, Ali Kashif Bashir

Karbala International Journal of Modern Science

The rapid growth and increasing demand for Internet of Things (IoT) devices in our everyday lives create exciting opportunities for human involvement, data integration, and seamless automation. This fully interconnected ecosystem considerably impacts crucial aspects of our lives, such as transportation, healthcare, energy management, and urban infrastructure. However, alongside the immense benefits, the widespread adoption of IoT also brings a complex web of security threats that can influence society, policy, and infrastructure conditions. IoT devices are particularly vulnerable to security violations, and industrial routines face potentially damaging vulnerabilities. To ensure a trustworthy and robust security framework, it is crucial to …

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Smart Service Function Chain System For Dynamic Traffic Steering Using Reinforcement Learning (Chrl), Ahmed Nadhum, Ahmed Al-Saadi Oct 2023

Smart Service Function Chain System For Dynamic Traffic Steering Using Reinforcement Learning (Chrl), Ahmed Nadhum, Ahmed Al-Saadi

Karbala International Journal of Modern Science

The rapid development of the Internet and network services coupled with the growth of communication infrastructure necessitates the employment of intelligent systems. The complexity of the network is heightened by these systems, as they offer diverse services contingent on traffic type, user needs, and security considerations. In this context, a service function chain offers a toolkit to facilitate the management of intricate network systems. However, various traffic types require dynamic adaptation in the sets of function chains. The problem of optimizing the order of service functions in the chain must be solved using the proposed approach, along with balancing the …

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Enhancing Exploration-Exploitation In Harmony Search For Airborne Hyperspectral Imaging Band Selection (E3hs), Mohammed Abdulmajeed Moharram, Divya Meena Sundaram Oct 2023

Enhancing Exploration-Exploitation In Harmony Search For Airborne Hyperspectral Imaging Band Selection (E3hs), Mohammed Abdulmajeed Moharram, Divya Meena Sundaram

Turkish Journal of Electrical Engineering and Computer Sciences

Hyperspectral imaging has emerged as a prominent area of research in the field of remote sensing science. However, hyperspectral images (HSIs) pose a notable challenge due to the presence of numerous irrelevant and redundant spectral bands exhibiting high correlation. Therefore, it is necessary to enhance the classification performance for HSI processing by selecting the most relevant discriminative spectral bands. To this end, this paper introduces a metaheuristic search method called enhancing exploration-exploitation in harmony search (E3HS). The standard harmony search suffers from many weaknesses, such as premature convergence and falling easily into the local optimum. Consequently, E3HS was proposed to …

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Infrared Imaging Segmentation Employing An Explainable Deep Neural Network, Xinfei Liao, Dan Wang, Zairan Li, Nilanjan Dey, Rs Simon, Fuqian Shi Oct 2023

Infrared Imaging Segmentation Employing An Explainable Deep Neural Network, Xinfei Liao, Dan Wang, Zairan Li, Nilanjan Dey, Rs Simon, Fuqian Shi

Turkish Journal of Electrical Engineering and Computer Sciences

Explainable AI (XAI) improved by a deep neural network (DNN) of a residual neural network (ResNet) and long short-term memory networks (LSTMs), termed XAIRL, is proposed for segmenting foot infrared imaging datasets. First, an infrared sensor imaging dataset is acquired by a foot infrared sensor imaging device and preprocessed. The infrared sensor image features are then defined and extracted with XAIRL being applied to segment the dataset. This paper compares and discusses our results with XAIRL. Evaluation indices are applied to perform various measurements for foot infrared image segmentation including accuracy, precision, recall, F1 score, intersection over union (IoU), Dice …

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Classification Of Chronic Pain Using Fmri Data: Unveiling Brain Activity Patterns For Diagnosis, Rejula V, Anitha J, Belfin Robinson Oct 2023

Classification Of Chronic Pain Using Fmri Data: Unveiling Brain Activity Patterns For Diagnosis, Rejula V, Anitha J, Belfin Robinson

Turkish Journal of Electrical Engineering and Computer Sciences

Millions of people throughout the world suffer from the complicated and crippling condition of chronic pain. It can be brought on by several underlying disorders or injuries and is defined by chronic pain that lasts for a period exceeding three months. To better understand the brain processes behind pain and create prediction models for pain-related outcomes, machine learning is a potent technology that may be applied in Functional magnetic resonance imaging (fMRI) chronic pain research. Data (fMRI and T1-weighted images) from 76 participants has been included (30 chronic pain and 46 healthy controls). The raw data were preprocessed using fMRIprep …

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Yolo And Lsh-Based Video Stream Analytics Landscape For Short-Term Traffic Density Surveillance At Road Networks, Lavanya K, Stuti Tiwari, Rahul Anand, Jude Hemanth Oct 2023

Yolo And Lsh-Based Video Stream Analytics Landscape For Short-Term Traffic Density Surveillance At Road Networks, Lavanya K, Stuti Tiwari, Rahul Anand, Jude Hemanth

Turkish Journal of Electrical Engineering and Computer Sciences

The duty of monitoring traffic during rush hour is difficult due to the fact that modern roadways are getting more crowded every day. The automated solutions that have already been created in this area are ineffective at processing enormous amounts of data in a short amount of time, leading to ineffectiveness and inconsistent results. The YOLO (you only look once) and LSH (locality sensitive hashing) algorithms are combined with the Kafka architecture in this study to create a method for assessing traffic density in real-time scenarios. Our concept, which is specifically designed for vehicular networks, predicts the traffic density in …

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Hybrid Machine Learning Model To Predict Chronic Kidney Diseases Using Handcrafted Features For Early Health Rehabilitation, Amjad Rehman, Tanzila Saba, Haider Ali, Narmine Elhakim, Noor Ayesha Oct 2023

Hybrid Machine Learning Model To Predict Chronic Kidney Diseases Using Handcrafted Features For Early Health Rehabilitation, Amjad Rehman, Tanzila Saba, Haider Ali, Narmine Elhakim, Noor Ayesha

Turkish Journal of Electrical Engineering and Computer Sciences

Chronic kidney diseases proliferate due to hypertension, diabetes, anemia, obesity, smoking etc. Patients with such conditions are sometimes unaware of first symptoms, complicating disease diagnosis. This paper presents chronic kidney disease (CKD) prediction model to classify CKD patients from NCKD (Non-CKD). The proposed study has two main stages. First, we found the odds ratio through logistic regression and comparison test to identify early risk factors from kidneys? MRI and differentiate CKD from NCKD subjects. In stage 2, LR, LDA, MLP classifiers were applied to predict CKD and NCKD by extracting features from MRI. The odds ratio of blood glucose random …

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