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A Novel Explainable CNN Model for Screening COVID-19 on X-ray Images

computer Systems science & engineering 2023年第8期46卷 1789-1809页

作者： Hicham Moujahid Bouchaib Cherradi Oussama El Gannour Wamda Nagmeldin Abdelzahir Abdelmaboud Mohammed Al-Sarem Lhoussain Bahatti Faisal Saeed Mohammed Hadwan EEIS Laboratory ENSET of MohammediaHassan II University of CasablancaMohammedia28820Morocco STIE Team CRMEF Casablanca-SettatThe Provincial Section of El JadidaEl Jadida24000Morocco Department of Information Systems College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia Department of Information Systems King Khalid UniversityMuhayel Aseer61913Saudi Arabia College of Computer Science and Engineering Taibah UniversityMedina42353Saudi Arabia Department of Computer Science University of Sheba RegionMarib14400Yemen DAAI Research Group Department of Computing and Data ScienceSchool of Computing and Digital TechnologyBirmingham City UniversityBirminghamB47XGUK Department of Information Technology College of ComputerQassim UniversityBuraydah 51452Saudi Arabia Department of Computer Science College of Applied SciencesTaiz UniversityTaiz6803Yemen

Due to the rapid propagation characteristic of the Coronavirus(COVID-19)disease,manual diagnostic methods cannot handle the large number of infected individuals to prevent the spread of ***,new automated diagnostic methods have been brought on board,particularly methods based on artificial intelligence using different medical data such as X-ray *** imaging,for example,produces several image types that can be processed and analyzed by machine and deep learning methods.X-ray imaging materials widely exist in most hospitals and health institutes since they are affordable compared to other imaging *** this paper,we propose a novel Convolutional Neural Network(CNN)model(COV2Net)that can detect COVID-19 virus by analyzing the X-ray images of suspected *** model is trained on a dataset containing thousands of X-ray images collected from different *** model was tested and evaluated on an independent *** order to approve the performance of the proposed model,three CNN models namely Mobile-Net,Residential Energy Services Network(Res-Net),and Visual Geometry group 16(VGG-16)have been implemented using transfer learning *** experiment consists of a multi-label classification task based on X-ray images for normal patients,patients infected by COVID-19 virus and other patients infected with *** proposed model is empowered with Gradient-weighted Class Activation Mapping(Grad-CAM)and Grad-Cam++techniques for a visual explanation and methodology debugging *** finding results show that the proposed model COV2Net outperforms the state-of-the-art methods.

关键词： Artificial intelligence intelligent diagnostic systems decisionmaking COVID-19 convolutional neural network

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software Complexity Measurement for Flight software

Software Complexity Measurement for Flight Software

引用

Space, Aerospace and Defence Conference (SPACE), IEEE

作者： Savitha A Pushpavathi T. P. Yogesh Prasad Prasanna Kumar Reliability and Quality Assurance Software Group URSC ISRO Bengalure Department of Computer Science M.S Ramaiah University of Applied Sciences Bengalure Communication systems Group URSC ISRO Bangalore

ISBN: (数字)9798350367386

ISBN: (纸本)9798350367393

The usage of software, which is used in variety of missions like Loe, Geo and interplanetary missions is increasing from mission to mission. The flight software size is increasing to take care of safety and security parameters, autonomy features and also to handle contingencies like failure detection, isolation and recovery. The growth rate of software will increase for future missions as new functionally gets added in software rather than hardware. This paper mainly concentrates on the software complexity metrics based on the static analysis carried out. This analysis helps to address the risks associated with development in size and complexity of flight software.

关键词： Space vehicles Databases Thermistors Aerospace electronics Extraterrestrial measurements software Complexity theory

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Development Anonymous Authentication Maria et al.’s Scheme of VANETs Using Blockchain and Fog Computing with QR Code Technique

Development Anonymous Authentication Maria et al.’s Scheme ...

引用

International Conference on Control, Decision and Information Technologies (CoDIT)

作者： Zahraa Sh. Alzaidi Ali A. Yassin Zaid Ameen Abduljabbar Vincent Omollo Nyangaresi Department of Computer Science College of Education for Pure Sciences University of Basrah Basrah Iraq Department of Computer Science and Software Engineering Jaramogi Oginga Odinga University of Science and Technology Bando Kenya Department of Applied Electronics Saveetha School of Engineering SIMATS Chennai Tamilnadu India

ISBN: (数字)9798350373974

ISBN: (纸本)9798350373981

The evolution of intelligent transport systems (ITS) has significantly enhanced driving experiences in vehicular ad-hoc networks (VANET), crucial for improving road safety and traffic efficiency. Despite these advancements, challenges persist. Trust management solutions often assume user legitimacy without verification. Moreover, the need for reauthentication as vehicles move between RSUs adds computational complexity. VANET is relatively vulnerable to security threats from multiple parties given its highly dynamic topology and its wireless and heterogeneous communication mode. We have expanded upon Maria et al.’s schema by specifically targeting and resolving significant shortcomings in their research. More precisely, we improve the features related to confirming the identity of users, preventing vehicles from being used without authorization, and continuously monitoring their current location in order to strengthen the security of vehicles and increase user involvement. We suggest implementing a schema that utilizes QR code verification to authenticate vehicle users, specifically targeting these difficulties. In VANETs, blockchain has been adopted with the authentication process for fog computing. The result is that there is no need for trusted authority (TA) while achieving privacy within the blockchain network and ensuring of the vehicle user authentication and the integrity of messages. Several key benefits have been achieved, such as blocking malicious entities and the potential damage they cause, enabling the revocation of malicious vehicles by conditional anonymization, as well as simplifying conflict resolution. Likewise, the proposed work was characterized by achieving an effective balance between effectiveness and complexity, protecting privacy, conditional tracking, ensuring integrity, and anonymous authentication.

关键词： Wireless communication Privacy Authentication Vehicular ad hoc networks QR codes Blockchains Security Vehicle dynamics Trust management Edge computing

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IoHT System Authentication Through the Blockchain Technology: A Review

IoHT System Authentication Through the Blockchain Technology...

引用

International Conference on Control, Decision and Information Technologies (CoDIT)

作者： Muwafaq Jawad Ali A. Yassin Hamid Ali Abed Al-Asadi Zaid Ameen Abduljabbar Vincent Omollo Nyangaresi Department of Computer Science College of Education for Pure Sciences University of Basrah Basrah Iraq Department of Computer Science and Software Engineering Jaramogi Oginga Odinga University of Science and Technology Bando Kenya Department of Applied Electronics Saveetha School of Engineering SIMATS Chennai Tamilnadu India

ISBN: (数字)9798350373974

ISBN: (纸本)9798350373981

The growing adoption of the Internet of Things (IoT) terminology in recent years in several domains, including healthcare, has yielded multiple benefits. One of the roles is to support professionals in delivering outstanding and suitable healthcare for patients, while also empowering patients to independently track their health state. However, this wide growth is accompanied by many significant security concerns and cyber risks, including unauthorized access, data leakage, information modification, and data erasure. This article outlines the advantages of employing groundbreaking blockchain technology to provide robust and verified authentication methods for different systems. Additionally, it imparts a foundational comprehension of the technologies employed in the procedure of constructing and advancing blockchain-based platforms. In addition, we explore tools like Scythe and Avispa that are employed to assess the system’s resilience against different types of attacks.

关键词： Terminology Reviews Instruments Authentication Medical services Throughput Blockchains Internet of Things Information technology Resilience

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Modeling of Sensor Enabled IrrigationManagement for Intelligent Agriculture Using Hybrid Deep Belief Network

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computer Systems science & engineering 2023年第8期46卷 2319-2335页

作者： Saud Yonbawi Sultan Alahmari B.R.S.S.Raju Chukka Hari Govinda Rao Mohamad Khairi Ishak Hend Khalid Alkahtani JoséVarela-Aldás Samih M.Mostafa Department of Software Engineering College of Computer Science and EngineeringUniversity of JeddahJeddahSaudi Arabia King Abdul Aziz City for Science and Technology RiyadhKingdom of Saudi Arabia Aditya Engineering College Affiliated to JNTUK(Kakinada) SurampalemIndia Department of MBA Vignan’s Institute of Information and Technology(A)DuvvadaVisakhapatnamAP530049India School of Electrical and Electronic Engineering Engineering CampusUniversiti Sains Malaysia(USM)Nibong TebalPenang14300Malaysia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11564Saudi Arabia SISAu Research Group Universidad Tecnológica IndoaméricaAmbato180103Ecuador Faculty of Computers and Information South Valley UniversityQena83523Egypt

Artificial intelligence(AI)technologies and sensors have recently received significant interest in intellectual *** the application of AI technologies and agriculture sensors in intellectual agriculture is urgently required for the growth of modern agriculture and will help promote smart *** irrigation scheduling systems were highly required in the agricultural field due to their capability to manage and save water deficit irrigation *** learning systems devise an alternative to conventional irrigation management through the automatic elaboration of predictions related to the learning of an *** this motivation,this study develops a modified black widow optimization with a deep belief network-based smart irrigation system(MBWODBN-SIS)for intelligent *** MBWODBN-SIS algorithm primarily enables the Internet of Things(IoT)based sensors to collect data forwarded to the cloud server for examination ***,the MBWODBN-SIS technique applies the deep belief network(DBN)model for different types of irrigation classification:average,high needed,highly not needed,and not *** MBWO algorithm is used for the hyperparameter tuning process.A wideranging experiment was conducted,and the comparison study stated the enhanced outcomes of the MBWODBN-SIS approach to other DL models with maximum accuracy of 95.73%.

关键词： Agriculture smart farming hyperparameter tuning artificial intelligence irrigation management sensors deep learning

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Multimodal Attention-Enhanced Feature Fusion-based Weekly Supervised Anomaly Violence Detection

arXiv

引用

arXiv 2024年

作者： Kaneko, Yuta Musa Miah, Abu Saleh Hassan, Najmul Lee, Hyoun-Sup Jang, Si-Woong Shin, Jungpil School of Computer Science and Engineering The University of Aizu Aizuwakamatsu Japan Department of Applied Software Engineering Dongeui University Busanjin-Gu Busan47340 Korea Republic of Department of Computer Engineering Dongeui University Busan47340 Korea Republic of

Weakly supervised video anomaly detection (WS-VAD) is a crucial area in computer vision for developing intelligent surveillance systems. Researchers are actively working on WS-VAD systems by assessing anomaly scores, but challenges persist due to ineffective feature extraction from unimodal approaches. Additionally, limited research on multimodal datasets has led to unsatisfactory performance accuracy. To address the challenges, We propose a multimodal attention-enhanced feature fusion-based system for weakly supervised anomaly detection. This system uses three feature streams: RGB video, optical flow, and audio signals, where each stream extracts complementary spatial and temporal features using an enhanced attention module to improve detection accuracy and robustness. In the first stream, we employed an attention-based, multi-stage feature enhancement approach to improve spatial and temporal features from the RGB video where the first stage consists of a ViT-based CLIP module, with top-k features concatenated in parallel with I3D and Temporal Contextual Aggregation (TCA) based rich spatiotemporal features. The second stage effectively captures temporal dependencies using the Uncertainty-Regulated Dual Memory Units (UR-DMU) model, which learns representations of normal and abnormal data simultaneously, and the third stage is employed to select the most relevant spatiotemporal features. The second stream extracted enhanced attention-based spatiotemporal features from the flow data modality-based feature by taking advantage of the integration of the deep learning and attention module. The audio stream captures auditory cues using an attention module integrated with the VGGish model, aiming to detect anomalies based on sound patterns. These streams enrich the model by incorporating motion and audio signals often indicative of abnormal events undetectable through visual analysis alone. The concatenation of the multimodal fusion leverages the strengths of each modality,

关键词： Audio streaming

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Impact Assessment and Mitigation Strategies for Plug-in Electric Vehicles on Distribution Networks: A Probabilistic Approach

Impact Assessment and Mitigation Strategies for Plug-in Elec...

引用

International Conference on Contemporary Computing and Informatics (IC3I)

作者： Vijilius Helena Raj M Siva Swetha Reddy H Pal Thethi G Ramesh Q. Mohammad Munugapati Bhavana Department of Applied Sciences New Horizon College of Engineering Bangalore Computer Science Software Engineering Institute of Aeronautical Engineering Hyderabad Telangana Lovely Professional University Phagwara India Department of Computer Science and Engineering GRIET Bachupally Hyderabad India Hilla University College Babylon Iraq Department of Computer Science and Engineering MLR Institute of Technology Hyderabad Telangana India

ISBN: (数字)9798350350067

ISBN: (纸本)9798350350074

The rapid depletion of fossil fuel reserves coupled with the ever-increasing demand for electrical power has prompted the search for new energy sources. Electric vehicles (EVs) are one potential answer because of the technology that allows for more efficient transportation while simultaneously reducing fossil fuel usage and emissions of greenhouse chemicals. Depending on the power system’s capability, structure, and architecture, several studies have shown that the distribution network may be negatively affected by the widespread interconnection of electric vehicles. Consequently, it is important to determine the effects of this additional load on the network so that measures can be taken to prevent threats to the system’s stability, dependability, and security, especially because the Indian federal and state governments have introduced incentives to increase sales of this type of vehicle.

关键词： Semantic Web Prevention and mitigation Transportation Distribution networks Power system stability Transformers Probabilistic logic Fossil fuels Security Protection

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A Proposed Approach for Risk Planning and Management

A Proposed Approach for Risk Planning and Management

引用

Information Technology (ACIT)

作者： Mohammed N. Al Refai Yazan Al-Smadi Adai Al-Momani Zeyad M. Jamhawi Ahmed Ali Otoom Issa Atoum Ahid Yaseen Jafar Ababneh Mohammad Kanan Software Engineering Dep. Zarqa University Zarqa Jordan Department of Computer Science Zarqa University Zarqa Jordan Department of Computer Science Applied Science Private University Amman Jordan Department of Cyber Security Applied Science Private University Amman Jordan Software Engineering Department Faculty of Information Technology Philadelphia University Jordan Department of Cyber Security Zarqa University Zarqa Jordan Dep. of Industry Engineering University of Business and Technelogy Jeddah Saudi Arabia

ISBN: (数字)9798331540012

ISBN: (纸本)9798331540029

Project Risk management is the process of identifying, evaluating, avoiding, or reducing risks. Where there is no software project without risks existence are natural in the context of project planning and management. This study focuses on proposing an enhanced risk management approach where testing phases were added to make the risk management process more effective by proposing solutions to many mistakes and challenges that occur through dealing with risks. The proposed approach focuses on dealing with risks that cannot be easily defined, more accurate risk evaluation, planning, and managing risk coordinated with a contingency plan.

关键词： Technological innovation Accuracy Contingency management Process control software Planning Risk management Information technology Testing

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Drive-Charge Dilemma in Electric Mobility: Price of Anarchy and Data Analytics Standpoint 5

Drive-Charge Dilemma in Electric Mobility: Price of Anarchy ...

引用

5th International Conference on Advanced Communication Technologies and Networking, CommNet 2022

作者： Mahrez, Zineb Sabir, Fssaid Saad, Walid Badidi, Elarbi Hassan Ii University of Casablanca Nest Research Group Lri Lab Ensem Morocco University of Quebec at Montreal Departrment of Computer Science MontrealQCH2L 2C4 Canada Wireless VT Department of Computer Science and Software Engineering Virginia Tech VA United States College of Information Technology Uae University Department of Computer Science and Software Engineering United Arab Emirates

ISBN: (数字)9781665450546

ISBN: (纸本)9781665450546

The advent of electric mobility has created new costs that are closely linked to and influenced by the actions and behaviors of electric vehicle (EV) drivers. These include time-, energy-, and risk-related costs that each driver seeks to reduce by adjusting his or her strategy. In this paper, an electric vehicle charging dilemma using a non-cooperative routing game with selfish players is formulated. We assume that an electric vehicle plans a trip from one place to another and, in the process, must choose a specific route, stop at a roadside station, decide on the charging station, and charge its battery by a certain amount. The strategy of EVs to drive or stop depends on factors related to battery level, waiting status at charging stations, availability of charging types, and traffic load both on roads and at stations. The research problem aims to solve the EV driver's dilemma and determine the route that the EV driver must take to optimize his travel cost.' To solve the dilemma, we propose to build a simulation model based on input data obtained from historical records of U.S. government sources, as described in the paper. © 2022 IEEE.

关键词： Data Analytics

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Towards Classifying File Segments in Memory Using Machine-Learning

Towards Classifying File Segments in Memory Using Machine-Le...

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HCT Information Technology Trends (ITT)

作者： Mohammed I. Al-Saleh Akram Alkouz Abdulsalam Alarabeyyat Majed Bouchahma Computer Science Department Jordan University of Science and Technology Computer Information System Higher Colleges of Technology Jordan-Salt Software Engineering Department Al-Balqa’ Applied University

Digital media triage is a main challenge that faces a digital investigator. Knowing what might be useful during crime investigation could greatly save the investigator’s time and enhance outcomes. Memory investigation can get potential benefit from the triage process because of its scattered and diverse contents. The Operating System’s paging scheme might map the contents of a file into non-consecutive page frames in the physical memory, making the file-type classification and identification process harder. This paper tackles the memory content triage problem at the page level using a machine-learning methodology.

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