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2024 International Applied Computational Electromagnetics Society Symposium, ACES-China 2024

作者： Cui, Jiaqian Zhu, Lei University of Macau Faculty of Science and Technology Department of Electrical and Computer Engineering Macau China

ISBN: (纸本)9798350355581

This paper presents a method to control the out-ofband performance of absorptive filters in both narrowband and wideband cases. To verify the method, a narrowband absorptive filter is designed with wideband matching, and a wideband one is proposed to achieve an infinite low-reflection range. Finally, the narrowband filter is implemented in microstrip-line platform, not only attaining symmetrical geometry but also improving impedance-matching performance. © 2024 IEEE.

关键词： Wiener filtering

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RobustFace: a novel image restoration technique for face adversarial robustness improvement

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Multimedia Tools and Applications 2025年第11期84卷 8965-8993页

作者： Sadu, Chiranjeevi Das, Pradip K. Yannam, V Ramanjaneyulu Nayyar, Anand Department of Computer Science and Engineering RGUKT Nuzvid Andhra Pradesh Nuzvid India Department of Computer Science and Engineering IIT Guwahati Assam Guwahati India School of Technology Woxsen University Telangana Hyderabad India Graduate School Faculty of Information Technology Duy Tan University Da Nang550000 Viet Nam

Machine Learning (ML) models, particularly Deep Learning (DL), have made rapid progress and achieved significant milestones across various applications, including numerous safety-critical contexts. However, these models have recently been discovered to be susceptible to adversarial attacks, which are well-crafted input images. The primary objective of this paper is to propose a novel methodology titled "RobustFace", which is based on deep image restoration networks, that significantly improves the facial adversarial robustness of various image-classification models. Adversarial images are created using the Private Fast Gradient Sign Method (P-FGSM), StyleGAN and Fast Landmark Manipulation (FLM) methods. The adversarial images are then enhanced using deep image restoration networks to bring back them into the original space. The encoded weighted local magnitude patterns (WLMP) are extracted and provided to different types of classifiers to detect facial adversarial images from the clean images. The effectiveness of RobustFace has been demonstrated on two real-world datasets and experimental outcomes show that it significantly improves facial adversarial robustness on all evaluating classifiers. It improves the highest classification accuracy from 98.75% to 99.00% on P-FGSM attacks, from 77.94% to 85.25% on adversarial attacks generated by StyleGAN and from 65.52% to 69.50% for FLM attacks. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Image reconstruction

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Energy Preserving Techniques for CPS in Smart Healthcare System 13

Energy Preserving Techniques for CPS in Smart Healthcare Sys...

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13th International Conference on System Modeling and Advancement in Research Trends, SMART 2024

作者： Srivastava, Jyoti Routray, Sidheswar School of Engineering Indrashil University Department of Computer Science and Engineering Gujarat Rajpur Mehsana India Ganpat University Faculty of Engineering and Technology Department of Computer Engineering Gujarat Kherwa Mehsana India School of Technology Pandit Deendayal Energy University Department of Computer Science and Engineering Gandhinagar382007 India

ISBN: (纸本)9798350380583

Cyber Physical System (CPS) enhances the functionality of various cyber and physical equipment of Smart Healthcare System (SHS) and provides automation in the healthcare sector using Artificial Intelligence (AI) techniques. SHS collects medical data with the help of sensors or actuators equipped with smart medical devices that act as the physical component of CPS, then processes and analyzes these medical data with the help of cyber components of CPS to provide automation in health monitoring, doctor consultancy, medical prescriptions, medicine delivery and various other perspectives of the healthcare sector. These advancements in the healthcare sector result in great assistance for healthcare individuals like doctors, patients, nursing staff, etc, but at the same time deal with very sensitive parameters like time, efficiency, reliability, security, etc, that need to be managed with utmost accuracy for preserving each life in this global smart healthcare environment. There can be various efficiency parameters in CPS enabled SHS namely the number of hops, average energy consumption, resource utilization, etc, This work elaborately defines various characteristics of CPS in SHS, efficiency parameters, and major challenges for the successful implementation of CPS enabled SHS. © 2024 IEEE.

关键词： Electronic health record

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Neutrosophic Price Indices with an Applied Study on Pesticide Prices

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Neutrosophic Sets and Systems 2023年 58卷 603-610页

作者： Alhabib, Rafif Alhabib, Amani Salama, A.A. Department of Mathematics Faculty of Science Hama University Hama Syria Faculty of Agricultural Engineering Albaath University Homs Syria Department of Mathematics and Computer Science Faculty of Science Port Said University Port Said Egypt

An index is a tool for comparing a phenomenon or several phenomena dating back to different periods to know the amount of change in the phenomena or the difference between them. For example, we compare the price of a commodity in a particular year with its price in a given year, compare the prices of a group of commodities in one year with their prices in another year, or compare the price of a commodity in two different places. For example, we compare the price of a commodity in one city with its price in another city. This paper presents a study of these Indices from a neutrosophic point of view. Which allows us to study Indices with uncertain or non-welldefined price data. In addition, access to results that determine the extent of the change in prices as accurately as possible, and thus the optimal planning for the next stage and the development of appropriate solutions. An applied example was presented to study the change in the prices of pesticides used to combat the "vine stem borer" insect using the neutrosophic Indices. © (2023). All Rights Reserved.

关键词： Pesticides

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Improvement of myopia using brain vision training with variable focal length VR

Improvement of myopia using brain vision training with varia...

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2024 International Conference on Advanced Mechatronic Systems, ICAMechS 2024

作者： Shindou, Kazuma Taguchi, Akira Bao, Yue Tokyo City University Faculty of Information Engineering Department of Computer Science Tokyo Japan

ISBN: (纸本)9798350366204

There is growing interest in vision improvement methods because poor vision impairs quality of life and causes a variety of problems in daily living and cognitive function. However, many existing vision improvement methods are invasive, expensive, and require large training spaces and long training *** this study, we focused on the positive effects of HMD use on visual acuity and devised a noninvasive visual acuity training method using an HMD with variable focal distance and Gabor stimuli to enhance its effectiveness. In this training method, the image formation distance during training is adjusted according to the subject's visual acuity, providing training at the optimal difficulty level for each subject. It also aims to efficiently enhance visual function through perceptual learning using Gabor *** results of this study showed that this training method improved visual acuity by an average of 35% in 1/8th the training time of the conventional method. This indicates that the proposed method is an effective way to improve visual acuity in a short period of time without the need for expensive equipment or a large training space. © 2024 IEEE.

关键词： Vision aids

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Spatial Attention Integrated EfficientNet Architecture for Breast Cancer Classification with Explainable AI

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computers, Materials & Continua 2024年第9期80卷 5029-5045页

作者： Sannasi Chakravarthy Bharanidharan Nagarajan Surbhi Bhatia Khan Vinoth Kumar Venkatesan Mahesh Thyluru Ramakrishna Ahlam AlMusharraf Khursheed Aurungzeb Department of Electronics and Communication Engineering Bannari Amman Institute of TechnologySathyamangalam638402India School of Computer Science Engineering and Information Systems(SCORE) Vellore Institute of TechnologyVellore632014India School of Science Engineering and EnvironmentUniversity of SalfordManchesterM54WTUK Department of Computer Science&Engineering Faculty of Engineering and TechnologyJAIN(Deemed-to-be University)Bengaluru562112India Department of Management College of Business AdministrationPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Adjunct Research Faculty Centre for Research Impact&OutcomeChitkara UniversityRajpura140401India

Breast cancer is a type of cancer responsible for higher mortality rates among *** cruelty of breast cancer always requires a promising approach for its earlier *** light of this,the proposed research leverages the representation ability of pretrained EfficientNet-B0 model and the classification ability of the XGBoost model for the binary classification of breast *** addition,the above transfer learning model is modified in such a way that it will focus more on tumor cells in the input ***,the work proposed an EfficientNet-B0 having a Spatial Attention Layer with XGBoost(ESA-XGBNet)for binary classification of *** this,the work is trained,tested,and validated using original and augmented mammogram images of three public datasets namely CBIS-DDSM,INbreast,and MIAS *** accuracy of 97.585%(CBISDDSM),98.255%(INbreast),and 98.91%(MIAS)is obtained using the proposed ESA-XGBNet architecture as compared with the existing ***,the decision-making of the proposed ESA-XGBNet architecture is visualized and validated using the Attention Guided GradCAM-based Explainable AI technique.

关键词： EfficientNet mammograms breast cancer Explainable AI deep-learning transfer learning

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Hybrid Reptile-Snake Optimizer Based Channel Selection for Enhancing Alzheimer’s Disease Detection

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Journal of Bionic engineering 2025年第2期22卷 884-900页

作者： Digambar Puri Pramod Kachare Smith Khare Ibrahim Al-Shourbaji Abdoh Jabbari Abdalla Alameen Department of Electronics and Telecommunication Ramrao Adik Institute of TechnologyD.Y.Patil CampusNavi-MumbaiMaharashtra400706India Maersk Mc-Kinney Moller Institute Faculty of EngineeringUniversity of Southern DenmarkOdenseDenmark Department of Electrical and Electronics Engineering Jazan UniversityJazan45142Saudi Arabia Department of Computer Science University of HertfordshireHatfieldUK Department of Computer Engineering and Information College of Engineering in Wadi AlddawasirPrince Sattam Bin Abdulaziz UniversityWadi Alddawasir11991Saudi Arabia

The global incidence of Alzheimer's Disease(AD)is on a swift *** Electroencephalogram(EEG)signals is an effective tool for the identification of AD and its initial Mild Cognitive Impairment(MCI)stage using machine learning *** of AD using EEG involves multi-channel ***,the use of multiple channels may impact the classification performance due to data redundancy and *** this work,a hybrid EEG channel selection is proposed using a combination of Reptile Search Algorithm and Snake Optimizer(RSO)for AD and MCI detection based on decomposition *** Mode Decomposition(EMD),Low-Complexity Orthogonal Wavelet Filter Banks(LCOWFB),Variational Mode Decomposition,and discrete-wavelet transform decomposition techniques have been employed for subbands-based EEG *** extracted thirty-four features from each subband of EEG ***,a hybrid RSO optimizer is compared with five individual metaheuristic algorithms for effective channel *** effectiveness of this model is assessed by two publicly accessible AD EEG *** accuracy of 99.22% was achieved for binary classification from RSO with EMD using 4(out of 16)EEG ***,the RSO with LCOWFBs obtained 89.68%the average accuracy for three-class classification using 7(out of 19)*** performance reveals that RSO performs better than individual Metaheuristic algorithms with 60%fewer channels and improved accuracy of 4%than existing AD detection techniques.

关键词： Alzheimer's Disease Brain disorder Electroencephalogram Reptile Search Algorithm Snake Optimizer Optimization

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Deep Learning-Based Web Application for Real-Time Apple Leaf Disease Detection and Classification 2

Deep Learning-Based Web Application for Real-Time Apple Leaf...

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2nd International Conference on Advancements in Smart, Secure and Intelligent Computing, ASSIC 2024

作者： Kumar, Satish Kumar, Rakesh Gupta, Meenu Obaid, Ahmed J. Chandigarh University Department of Computer Science and Engineering Punjab India University of Kufa Faculty of Computer Science and Mathematics Najaf Iraq Technical Engineering College Al-Ayen University Department of Computer Technical Engineering Thi-Qar Iraq

ISBN: (纸本)9798350370188

Agriculture is the most significant industry in the economy of India. Various kinds of diseases affect the leaves of plants and influence the productivity of crops. Apple farmers are also constantly facing challenges in boosting their yield and protecting apple trees from diseases. The prevalence of diseases and pests significantly hampers apple production, leading to substantial financial losses for the industry each year. Farmers may not have expertise in leaf disease prediction. Detecting Apple Leaf Diseases (ALD) swiftly and accurately is crucial for effectively handling and curbing these issues within orchards. Specifically, advancements in computer vision methods utilizing Deep Learning (DL) have opened up avenues for identifying and understanding these diseases at an early stage directly on the leaves. Web application based on the DL model is proposed to address this issue, which can predict Healthy and Alternaria, Leaf Spot, Marssonina Blotch, and Powdery mildew disease of the affected leaf. © 2024 IEEE.

关键词： Forecasting

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Securing Cloud-Encrypted Data:Detecting Ransomware-as-a-Service(RaaS)Attacks through Deep Learning Ensemble

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computers, Materials & Continua 2024年第4期79卷 857-873页

作者： Amardeep Singh Hamad Ali Abosaq Saad Arif Zohaib Mushtaq Muhammad Irfan Ghulam Abbas Arshad Ali Alanoud Al Mazroa School of Computer Information Sciences University of CumberlandsWilliamsburgKentucky40769USA Computer Science Department College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Department of Mechanical Engineering College of EngineeringKing Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Electrical Electronics and Computer SystemsCollege of Engineering and TechnologyUniversity of SargodhaSargodha40100Pakistan Electrical Engineering Department College of EngineeringNajran UniversityNajran61441Saudi Arabia Department of Electrical Engineering The University of LahoreLahore54000Pakistan Faculty of Computer and Information Systems Islamic University of MadinahMadinah42351Saudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

Data security assurance is crucial due to the increasing prevalence of cloud computing and its widespread use across different industries,especially in light of the growing number of cybersecurity threats.A major and everpresent threat is Ransomware-as-a-Service(RaaS)assaults,which enable even individuals with minimal technical knowledge to conduct ransomware *** study provides a new approach for RaaS attack detection which uses an ensemble of deep learning *** this purpose,the network intrusion detection dataset“UNSWNB15”from the Intelligent Security Group of the University of New South Wales,Australia is *** the initial phase,the rectified linear unit-,scaled exponential linear unit-,and exponential linear unit-based three separate Multi-Layer Perceptron(MLP)models are ***,using the combined predictive power of these three MLPs,the RansoDetect Fusion ensemble model is introduced in the suggested *** proposed ensemble technique outperforms previous studieswith impressive performance metrics results,including 98.79%accuracy and recall,98.85%precision,and 98.80%*** empirical results of this study validate the ensemble model’s ability to improve cybersecurity defenses by showing that it outperforms individual *** expanding the field of cybersecurity strategy,this research highlights the significance of combined deep learning models in strengthening intrusion detection systems against sophisticated cyber threats.

关键词： Cloud encryption RaaS ensemble threat detection deep learning cybersecurity

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Computational Investigation of Multiband EMNZ Metamaterial Absorber for Terahertz Applications

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computers, Materials & Continua 2022年第5期71卷 3905-3920页

作者： Ismail Hossain Md Samsuzzaman Mohd Hafiz Baharuddin Norsuzlin Binti Mohd Sahar Mandeep Singh Jit Singh Mohammad Tariqul Islam Space Science Center Universiti Kebangsaan Malaysia43600UKM BangiSelangorMalaysia Department of Computer and Communication Engineering Faculty of Computer Science and EngineeringPatuakhali Science and Technology UniversityBangladesh Department of Electrical Electronic and Systems EngineeringFaculty of Engineering and Built EnvironmentUniversiti Kebangsaan MalaysiaMalaysia

This study presents an Epsilon Mu near-zero(EMNZ)nanostructured metamaterial absorber(NMMA)for visible regime *** resonator and dielectric layers are made of tungsten(W)and quartz(fused),where the working band is expanded by changing the resonator layer’s *** to perfect impedance matching with plasmonic resonance characteristics,the proposed NMMA structure is achieved an excellent absorption of 99.99%at 571 THz,99.50%at 488.26 THz,and 99.32%at 598 THz *** absorption mechanism is demonstrated by the theory of impedance,electric field,and power loss density distributions,*** geometric parameters are explored and analyzed to show the structure’s performance,and a near-field pattern is used to explain the absorption mechanism at the resonance frequency *** numerical analysis method describes that the proposed structure exhibited more than 80%absorbability between 550 and 900 *** computer Simulation Technology(CST Microwave Studio 2019)software is used to design the proposed ***,CSTHFSS interference is validated by the simulation data with the help of the finite element method(FEM).The proposed NMMA structure is also exhibits glucose concentration sensing capability as *** the proposed broadband absorber may have a potential application in THz sensing,imaging(MRI,thermal,color),solar energy harvesting,light modulators,and optoelectronic devices.

关键词： Metamaterial absorber terahertz applications multiband EM near zero nanostructured visible regime applications

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