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3rd International Conference on Emerging Electronics and Automation, E2A 2023

作者： Dhar, Prasenjit Singh, Mohit Kumar Ahmed, Tanveer Suganya, Devi K. Medical Imaging Laboratory Computer Science and Engineering Department National Institute of Technology Silchar Assam India

ISBN: (纸本)9789819768011

Red blood cells (RBCs) also known as erythrocytes are an essential component of the human body that play several important roles. RBCs transport oxygen (O2) from the lungs to the body’s tissues, remove carbon dioxide (CO2), regulate pH balance, support the immune system, and provide diagnostic information. The abnormal shapes of RBCs (signified as poikilocytosis) are unable to carry O2 and CO2, leading to decreased O2 delivery to the tissues and an increased workload on the heart and lungs. Anemia, thalassemia, and other blood-related illnesses affect the body for insufficient replenishment (oxygen, protein, nutrients). Hematologists take more time to examine RBC shapes manually using a microscope. In this study ensemble deep learning technique was introduced to examine poikilocytosis abnormality accurately and efficiently. The proposed ensemble model outperforms state-of-the-art approaches with an excellent accuracy and F1-score of 98.77%. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Deep learning

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Effective skin cancer prediction using hybrid Xception and XGBoost approach tuned by honey badger optimization

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Multimedia Tools and Applications 2024年第36期83卷 83889-83916页

作者： Naveena, T. Jerine, S. Department of Computer Science Noorul Islam Centre for Higher Education Tamil Nadu Kumaracoil629180 India Department of Software Engineering Noorul Islam Centre for Higher Education Tamil Nadu Kumaracoil629180 India

One of the several malignancies that can afflict humans and spread the fastest is skin cancer. The most and most serious kind of skin cancer, melanoma typically starts out on the skin's surface before spreading deeper into the skin layers. But melanoma patients have a 96% survival rate with straightforward and affordable treatments if they are discovered at an early stage. Expert dermatologists, equipment, and biopsies are employed in the traditional technique of melanoma diagnosis. Deep learning has shown to offer cutting edge solutions for skin cancer identification at an early stage with high accuracy, helping dermatologists prevent the costly diagnosis and assisting patients. Hybrid Xception-XGBoost classifier tuned by HBA is developed in this paper for effective skin cancer prediction. Raw skin image is given as an input for the proposed method. Dingo Optimized Texture based Histogram Equalization strategy is employed to enhance the raw input image. Then pre-processed image is split into different regions using U-net based segmentation approach. This segmented image is then given as an input for the Hybrid Xception-XGBoost approach which was tuned by Honey Badger Optimization for final prediction of skin cancer. In this classifier, the fully connected layers of Xception network is replayed with XGBoost classifier. HBA is utilized to choose best tunable variables of XGBoost. The evaluation outcomes show that the proposed approach achieves 98% accuracy, 97% precision and 113 s of training time. Thus, proposed hybrid classifier is the best choice for predicting skin cancer effectively. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Diagnosis

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Faithful geometric measures for genuine tripartite entanglement

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Physical Review A 2024年第1期110卷 L010402-L010402页

作者： Xiaozhen Ge Lijun Liu Yong Wang Yu Xiang Guofeng Zhang Li Li Shuming Cheng Department of Control Science and Engineering Department of Applied Mathematics The Department of Mathematics and Computer Science State Key Laboratory for Mesoscopic Physics School of Physics Frontiers Science Center for Nano-optoelectronics and Collaborative Innovation Center of Quantum Matter Shanghai Institute of Intelligent Science and Technology Institute for Advanced Study

We present a faithful geometric picture for genuine tripartite entanglement of discrete, continuous, and hybrid quantum systems. We first find that the triangle relation Ei|jkα≤Ej|ikα+Ek|ijα holds for all subadditive bipartite entanglement measure E, all permutations under parties i,j,k, all α∈[0,1], and all pure tripartite states. Then, we rigorously prove that the nonobtuse triangle area, enclosed by side Eα with 0<α≤1/2, is a measure for genuine tripartite entanglement. Finally, it is significantly strengthened for qubits that given a set of subadditive and nonsubadditive measures, some state is always found to violate the triangle relation for any α>1, and the triangle area is not a measure for any α>1/2. Our results pave the way to study discrete and continuous multipartite entanglement within a unified framework.

关键词： Entanglement measures Quantum correlations in quantum information Quantum correlations, foundations & formalism Resource theories

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Incentive-Driven Approach for Misbehavior Avoidance in Vehicular Networks

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computers, Materials & Continua 2022年第3期70卷 6089-6106页

作者： Shahid Sultan Qaisar Javaid Eid Rehman Ahmad Aziz Alahmadi Nasim Ullah Wakeel Khan Department of Computer Science and Software Engineering International Islamic UniversityIslamabad44000Pakistan Department of Software Engineering Foundation University Islamabad44000Pakistan Department of Electrical Engineering Taif University KSA Taif21944Saudi Arabia Department of Electrical Engineering Foundation University Islamabad44000Pakistan

For efficient and robust information exchange in the vehicular adhoc network,a secure and trusted incentive reward is needed to avoid and reduce the intensity of misbehaving nodes and congestion especially in the case where the periodic beacons exploit the *** addition,we cannot be sure that all vehicular nodes eagerly share their communication assets to the system for message dissemination without any ***,there may be some misbehaving nodes and due to their selfish and greedy approach,these nodes may not help others on the *** deal with this challenge,trust-based misbehavior avoidance schemes are generally reflected as the capable *** this paper,we employed a fair incentive mechanism for cooperation aware vehicular communication *** order to deploy a comprehensive credit based rewarding scheme,the proposed rewardbased scheme fully depends on secure and reliable cryptographic *** order to achieve the security goals,we used the cryptographic scheme to generate a certified public key for the authenticity of every message exchange over the *** evaluated the friction of misbehaving vehicles and the effect of rewarding schemes in context with honest messages dissemination over the network.

关键词： VANET misbehavior reputation rewards congestion avoidance certified public key

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DFU_XAI: A Deep Learning-Based Approach to Diabetic Foot Ulcer Detection Using Feature Explainability

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Biomedical Materials and Devices 2024年第2期2卷 1225-1245页

作者： Biswas, Shuvo Mostafiz, Rafid Paul, Bikash Kumar Uddin, Khandaker Mohammad Mohi Hadi, Md. Abdul Khanom, Fahmida Department of Information and Communication Technology Mawlana Bhashani Science and Technology University Institute of Information Technology Noakhali Science and Technology University Department of Software Engineering Daffodil International University Department of Computer Science and Engineering Dhaka International University Department of Computer Science: Information Technology University of Nebraska Omaha Department of Mathematics American International University – Bangladesh

Diabetic foot ulcer (DFU) is a potentially fatal complication of diabetes. Traditional techniques of DFU analysis and therapy are more time-consuming and costly. Artificial intelligence (AI), particularly deep neural networks, has demonstrated remarkable effectiveness in medical applications. Despite this, the lack of explainability of deep learning models is currently viewed as a key hurdle to using these approaches in actual clinical settings. In this research, we present the DFU_XAI framework for assessing the interpretability of explainable-driven deep learning (DL) models. DFU_XAI evaluates five DL models (Xception, DenseNet121, ResNet50, InceptionV3, and MobileNetV2) to establish a transparent DL framework using three state-of-the-art explanation methods: Shapley additive explanation (SHAP), local interpretable model-agnostic explanations (LIME), and gradient-weighted class activation mapping (Grad-CAM). ResNet50 outperformed the other four models with remarkable results: 98.75% accuracy, 99.2% precision, 97.6% recall, 98.4% F1-score, and 98.5% AUC. For the most part, it can locate diabetic foot ulcers precisely on a diabetic foot and discriminate between diabetic foot ulcers and healthy feet in the DFU dataset. A heat map will indicate the precise location of the ulcer that needs care. © The Author(s), under exclusive licence to Springer science+Business Media, LLC 2024.

关键词： Convolutional neural networks Deep learning Diabetic foot ulcers Explainable AI

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An Approach for Early Detection of Schizophrenia 15

An Approach for Early Detection of Schizophrenia

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Paranagama, Sachin Uditha, Isiwara Daundasekara, Pamodya Hettiarachchi, Shehani Weerasinghe, Lokesha Kasthurirathna, Dharshana Sri Lanka Institue Of Information Technology Faculty Of Computing Department of Computer Science and Software Engineering Malabe Sri Lanka

ISBN: (纸本)9798350370249

Schizophrenia is a chronic mental disorder with distorted thinking, hallucinations, and social difficulties. Early diagnosis is vital, but current methods are limited. This research proposes a web-based application integrating machine learning, emotion recognition, and game-based elements to track symptoms and aid in early diagnosis. Interactive exercises focus on specific symptoms like cognitive evaluation, emotional analysis, and memory assessment. By combining computer science, psychology, and machine learning, the project aims to improve early detection and ultimately enhance the quality of life for affected individuals. Key components include using Deep Convolutional Neural Network (DCNN) architecture for recognizing facial and physical expressions associated with schizophrenia with an 87% accuracy rate, and utilizing Vector Regressor (SVR) with a 93% accuracy rate, along with Vision Transformer (ViT) and Custom CNN models for cognitive assessment, achieving accuracy rates of 99% and 98%, respectively. © 2024 IEEE.

关键词： Convolutional neural networks

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Improving Power Response of Single-Controllable VSG-Based Active Distribution Network

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CSEE Journal of Power and Energy Systems 2025年第1期11卷 102-114页

作者： Shah Fahad Arman Goudarzi Pierluigi Siano Ji Xiang Department of Electrical and Computer Engineering Missouri University of Science and TechnologyUSA University of Victoria Canada Department of Management&Innovation Systems University of SalernoItaly Department of Electrical and Electronic Engineering Science University of JohannesburgJohannesburg2006South Africa National Laboratory of Industrial Control Technology College of Electrical EngineeringZhejiang UniversityHangzhou310058China

Controlling an active distribution network(ADN)from a single PCC has been advantageous for improving the performance of coordinated Intermittent RESs(IRESs).Recent studies have proposed a constant PQ regulation approach at the PCC of ADNs using coordination of non-MPPT based ***,due to the intermittent nature of DGs coupled with PCC through uni-directional broadcast communication,the PCC becomes vulnerable to transient *** address this challenge,this study first presents a detailed mathematical model of an ADN from the perspective of PCC regulation to realize rigidness of PCC against ***,an H_(∞)controller is formulated and employed to achieve optimal performance against disturbances,consequently,ensuring the least oscillations during transients at ***,an eigenvalue analysis is presented to analyze convergence speed limitations of the newly derived system ***,simulation results show the proposed method offers superior performance as compared to the state-of-the-art methods.

关键词： Cooperative control of DGs hierarchical control system high penetration of intermittent RESs H_(∞)control optimal control in power systems single-controllable active distribution networks

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A survey on security analysis of Amazon echo devices

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High-Confidence Computing 2022年第4期2卷 28-36页

作者： Surendra Pathak Sheikh Ariful Islam Honglu Jiang Lei Xu Emmett Tomai Department of Computer Science The University of Texas Rio Grande ValleyUSA Department of Computer Science and Software Engineering Miami UniversityUSA Department of Computer Science Kent State UniversityUSA

Since its launch in 2014,Amazon Echo family of devices has seen a considerable increase in adaptation in consumer homes and *** a market worth millions of dollars,Echo is used for diverse tasks such as accessing online information,making phone calls,purchasing items,and controlling the smart *** offers user-friendly voice interaction to automate everyday tasks making it a massive *** many people view Amazon Echo as a helpful assistant at home or office,few know its underlying security and privacy *** this paper,we present the findings of our research on Amazon Echo’s security and privacy *** findings are divided into different categories by vulnerability or *** proposed mitigation(s)to the vulnerabilities are also presented in the *** conclude that though numerous privacy concerns and security vulnerabilities associated with the device are mitigated,many vulnerabilities still need to be addressed.

关键词： Amazon echo Privacy Security Intelligent virtual assistants

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A Comparative Analysis of Goal-Oriented Requirements engineering and Model-Based Systems engineering Frameworks for Managing Requirements of Systems of Systems 25

A Comparative Analysis of Goal-Oriented Requirements Enginee...

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25th International Arab Conference on Information Technology, ACIT 2024

作者： Alhajhassan, Suhair Murrar, Samer Samhan, Ahmad Odeh, Mohammed Elrashidi, Ali Applied Science Private University Software Engineering Department Amman Jordan Applied Science Private University Computer Science Department Amman Jordan Zarqa University Software Engineering Department Zarqa Jordan Global Academy for Digital Health Bristol United Kingdom University of Business and Technology Department of Electrical Engineering Jeddah Saudi Arabia

ISBN: (纸本)9798331540012

Goal-oriented requirements engineering (GORE) for Systems of Systems (SoS) includes combining individual operational systems local goals to achieve higher-level goals. GORE offers a structured approach to managing complex requirements, ensuring that strategic goals are translated into operational tasks. This paper provides a review of GORE frameworks, including those incorporating Model-Based Systems engineering (MBSE), that could be used in the management of complex Systems of Systems. The paper analyzes recent GORE frameworks such as CGS4Adaptation which combines Goals and SysML for managing adaptive Socio-Cyber-Physical Systems (SCPSs);GORE-based approach to Energy Management Systems (EnMS);Model-Based and Goal-Oriented Approach for the conceptual design of smart grid services;GORE and reference architecture approach for microgrid systems;and Adaptation-Oriented Requirement Modeling approach (ADORE). A comparative analysis is conducted to assess the extent of effectiveness these frameworks provide for improving SoS traceability, adaptability, and system design integrity. The paper concludes with key findings on the strengths and limitations of the considered frameworks, on the basis of which, major conclusions on how GORE combined with MBSE can be used for managing SoS requirements in Smart Grid (SG) and socio-cyber-physical systems could be drawn. This review paper also contributes to the requirements engineering domain by outlining effective strategies for designing and managing complex, adaptive Systems of Systems. © 2024 IEEE.

关键词： Conceptual design

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Mathematical Methods for Reducing the Search Space for Solutions in 'Big Data' Analysis and Management 14

Mathematical Methods for Reducing the Search Space for Solut...

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14th International Conference on Advanced computer Information Technologies, ACIT 2024

作者： Syrotkina, Olena Kobti, Ziad Aleksieiev, Mykhailo Moroz, Dmytro Udovyk, Iryna Martynenko, Andrii University of Windsor School of Computer Science Windsor Canada Dnipro University of Technology Department of Software Engineering Dnipro Ukraine

ISBN: (纸本)9798350350036

This paper addresses mathematical methods to reduce or segment the search space for big data solutions into distinct subspaces with partial solutions. It is achieved by using a data organization structure of 'm-tuples based on ordered sets of arbitrary cardinality.' We provide a mathematical description of this structure and review contemporary methodologies to address similar problems. The study highlights how these properties can significantly reduce the analyzed state space and includes graphs that demonstrate changes in data volume within these subspaces. Additionally, we analyze how variations in four specific arguments affect data volume changes and provide an overview of the efficiency gains in resource use from applying the mathematical methods discussed. © 2024 IEEE.

关键词： Data structures

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