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5th International IEEE Novel Intelligent and Leading Emerging Sciences Conference, NILES 2023

作者： Abdelrahman, Amany A. El-Kassas, Wafaa S. Mohamed, Hoda K. Ain Shams University Faculty of Engineering Department of Computer and Systems Engineering Cairo Egypt Faculty of Computers and Information Technology Giza Egypt

ISBN: (纸本)9798350381030

Automatic Text Summarization (ATS) for long documents is a very challenging task. A long document includes more than one topic, so it is required to construct a summary that covers the most important contextual information from the different topics in the input document. There are many ATS techniques, but the produced summaries are much less accurate than the human summaries. This paper proposes a supervised extractive Neural-based summarization model that focuses on long documents summarization by integrating both the local and global contexts of the document. The proposed system employs two bidirectional Gated Recurrent Units (GRUs) as word and sentence encoders, respectively, and uses Word2Vec embeddings as word representation. Two ensembles are proposed by applying the average ensemble method to the proposed system with two other Neural-based systems. The proposed system uses the PubMed dataset to evaluate the two ensembles using the ROUGE evaluation metrics. The results of the evaluation show that there are promising and remarkable improvements of 0.14% and 0.97% for ROUGE-1, 0.33% and 1.12% for ROUGE-2, and 0.25% for ROUGE-L. © 2023 IEEE.

关键词： Signal encoding

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Fractal Measurement of Images Human Brain from MRI

Fractal Measurement of Images Human Brain from MRI

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2024 Cognitive Models and Artificial Intelligence Conference, AICCONF 2024

作者： Anarova, Shahzoda Jabbarov, Jamoliddin Uralova, Iroda Tashkent University of Information Technologies Department of Convergence of digital technologies Computer Engineering Faculty Tashkent Uzbekistan Department of Computer science and technology Intelligent systems and computer technologies Faculty Samarkand State University Samarkand Uzbekistan

ISBN: (纸本)9798400716928

This article is devoted to the determination of the fractal size of the damaged part of the human brain on the basis of images obtained from MRI (magnetic resonance imaging). There are various mathematical methods for determining the size of fractal structures, this article uses two variants of the cell counting method and describes the analysis of errors in determining the fractal size of the damaged part of the human brain. The article shows that the damaged part of the human brain has a fractal structure and that it has a fractal dimension. Fractal measurement has also been used to determine the size of the damaged part of the human brain, unlike common methods. In determining the fractal scale, cases of changes in human body organs were not taken into account. In the article, the determination of the size of the damaged part of the human brain is studied on the basis of mathematical formulas. Two different variants of the special cell counting method were used to calculate the fractal measurements, as well as the corresponding number of experimental results. In addition, these measurements were used to assess the extent to which patients suffered brain damage and to provide information on the practical application of these fractal measurements. © 2024 ACM.

关键词： Magnetic resonance imaging

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Intelligent optimisation in smart and sustainable compressed air systems: Towards support for decision-making under faulty conditions 31

Intelligent optimisation in smart and sustainable compressed...

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31st CIRP Conference on Life Cycle engineering, LCE 2024

作者： Mallia, Jasmine Francalanza, Emmanuel Xuereb, Peter Baldacchino, Daniel Refalo, Paul Department of Industrial and Manufacturing Engineering Faculty of Engineering University of Malta MsidaMSD2080 Malta Department of Computer Information Systems Faculty of Information & Communication Technology University of Malta MsidaMSD2080 Malta

The monitoring of complex industrial systems through the implementation of smart approaches provides unique opportunities, such as the characterisation of their real-time performance. Within this scope, there exists the need to support decision-making during maintenance processes, due to the presence of a multitude of faults in real-world systems and the difficulty of identifying the appropriate mitigating solutions. The proposed solution uses intelligent optimisation techniques to identify the ideal control solution within these complex systems when faults arise. This paper presents a framework based on an intelligent optimisation approach, which provides a workflow process for the support of decision-making during faulty situations. It is adapted and implemented to the demand-side of a Compressed Air System (CAS), thus providing a holistic approach in automating fault mitigation during real-time system operation. In implementing this framework, multiple intelligent optimisation techniques such as the Genetic Algorithm and the Particle Swarm Optimisation algorithms were adopted and implemented. Both algorithms were successful in providing the ideal control solution under fault conditions. For a typical production case study, the proposed optimisation approach results in a reduction of 40% in its air consumption, which directly improves its environmental performance and energy costs. This result demonstrates that this approach contributes a suitable control strategy for CAS when experiencing a pneumatic fault, which has a direct positive effect on the operational energy performance and costs. © 2024 The Author(s).

关键词： Decision making

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Building an interoperable space for smart agriculture

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Digital Communications and Networks 2023年第1期9卷 183-193页

作者： Ioanna Roussaki Kevin Doolin Antonio Skarmeta George Routis Juan Antonio Lopez-Morales Ethel Claffey Manuel Mora Juan Antonio Martinez Institute of Communications and Computer Systems AthensGreece Walton Institute WaterfordIreland Department of Information and Communications Engineering University of MurciaMurciaSpain School of Business Waterford Institute of TechnologyWaterfordIreland R&D Department Odin SolutionsMurciaSpain

The digital transformation in agriculture introduces new challenges in terms of data,knowledge and technology adoption due to critical interoperability issues,and also challenges regarding the identification of the most suitable data sources to be exploited and the information models that must be ***(Building an Interoperable,Data-Driven,Innovative and Sustainable European Agri-Food Sector)addresses these challenges by providing an overarching solution that integrates various heterogeneous hardware and software resources(e.g.,devices,networks,platforms)and enables the seamless sharing of data and knowledge throughout the agri-food *** paper introduces the main concepts of DEMETER and its reference architecture to address the data sharing and interoperability needs of farmers,which is validated via two rounds of 20 large-scale pilots along the DEMETER *** paper elaborates on the two pilots carried out in region of Murcia in Spain,which target the arable crops sector and demonstrate the benefits of the deployed DEMETER reference architecture.

关键词： Smart agriculture Internet of things(IoT) DEMETER Reference architecture Interoperability Agricultural information model(AIM) Pilot validation

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Model for Recognition of Sign Language and Hand Gesture by Hard Hearing People

Model for Recognition of Sign Language and Hand Gesture by H...

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2023 International Conference on Sustainable Communication Networks and Application, ICSCNA 2023

作者： Manjula, R. Jagadeesan, S. Ramalingam, Venkadeshan Vetriselvi, T. Johnpeter, T. Srm Institute of Science and Technology College of Engineering and Technology Department of Computing Technologies Chennai India Vellore Institute of Technology School of Computer Science Engineering and Information Systems Department of Software and Systems Engineering Tamilnadu Vellore India Information Technology Department University of Technology and Applied Sciences-Shinas Branch Sultanate of Oman Oman Vellore Institute of Technology School of Computer Science and Engineering Department of Iot Tamilnadu Vellore India K.Ramakrishnan College of Engineering Department of Computer Science and Engineering Trichy India

ISBN: (纸本)9798350313987

Hard hearing and deaf people are communicating with other people using the sign language. This is the only way of communication of such people to convey Since this is the only means by which these individuals can communicate, it is imperative that others be able to understand their language. Sign language recognition by computer begins with the acquisition of sign gestures and ends with recognition and conversion to text or voice. Static and dynamic are the two ways of sign gestures used. This study aims at focusing on the dynamic gesture recognition and the steps for recognizing sign language are discussed. The collected data are preprocessed and feature are extracted for classification. Finally the results are all investigated and developed for single user. © 2023 IEEE.

关键词： Gesture analysis Hand gesture recognition Hand tracking Sign language

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Secure and fast mobility handover scheme for IoMT in 5 G and future 6 G networks

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Alexandria engineering Journal 2025年 128卷 127-143页

作者： Islam, Shayla Topazal, S.M. Hasan, Mohammad Kamrul Kolandaisamy, Raenu AL Abbas, Huda Saleh Vo, Nguyen Thakkar, Rahul Khan, Muhammad Attique Gupta, Deepak AlHammadi, Dina Abdulaziz Institute of Computer Science and Digital Innovation UCSI University Kuala Lumpur56000 Malaysia Center for Cyber Security Faculty of Information Science and Technology the National University of Malaysia Selangor Bangi43600 Malaysia Department of computer science College of Computer Science and Engineering Taibah University Madina Saudi Arabia Victorian Institute of Technology Melbourne Australia Center of AI College of Computer Engineering and Science Prince Mohammad Bin Fahd University Al-Khobar Saudi Arabia Maharaja Agrasen Institute of Technology Delhi India Department of Information Systems College of Computer and Information Sciences Princess Nourah bint Abdulrahman University P.O.Box 84428 Riyadh11671 Saudi Arabia

The emergence of 5 G and 6 G networks promises significant advancements in the Internet of Medical Things (IoMT) by enabling real-time medical data transmission and continuous connectivity for mobile healthcare devices. However, traditional Handover (HO) mechanisms face latency, security, energy consumption, and scalability challenges when supporting fast-moving and dense IoMT environments. This paper presents a secure and fast mobility handover scheme for IoMT in 5 G and future 6 G networks, incorporating a predictive algorithm, Blockchain-Based (BC-B) decentralized authentication mechanism, and AI-driven anomaly detection. The predictive algorithm anticipates device movement and pre-allocates resources at the target Base Station (BS), reducing HO latency by 20–30 % in 5 G and up to 40 % in 6 G. Meanwhile, blockchain-based authentication ensures tamper-proof and decentralized security, reducing vulnerability to cyberattacks by 90 % compared to traditional methods. Additionally, the energy consumption during HO events is reduced by 20–35 %, dropping from 15 mJ in traditional schemes to 12 mJ in 5 G and further to 10 mJ in 6 G. The scheme also incorporates AI-driven anomaly detection, achieving an accuracy of 96.7 %, ensuring proactive identification and mitigation of potential security threats. The analyzed scheme maintains consistent throughput with less than 5 % reduction and scales effectively for up to 300 devices per cell. The simulation results demonstrate significant improvements across key performance metrics, including latency, security, energy efficiency, and scalability, making this approach highly suitable for critical IoMT applications such as telesurgery, remote patient monitoring, and innovative healthcare environments. These advancements position the analyzed framework as a cornerstone for next-generation (NG) healthcare networks. © 2025 The Authors

关键词： Remote patient monitoring

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EsECC_SDN:Attack Detection and Classification Model for MANET

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computers, Materials & Continua 2023年第3期74卷 6665-6688页

作者： Veera Ankalu Vuyyuru Youseef Alotaibi Neenavath Veeraiah Saleh Alghamdi Korimilli Sirisha Department of Computer Science and Engineering Koneru Lakshmaiah Education FoundationVaddeswaram522502A.PIndia Department of Computer Science College of Computers and Information SystemsUmm Al-Qura UniversityMakkah21955Saudi Arabia Department of Electronics and Communications DVR&DHS MIC Engineering CollegeKanchikacharla521180A.PIndia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Electronics and Communications BVC Institute of Technology&ScienceAmalapuram533221A.PIndia

Mobile Ad Hoc Networks(MANET)is the framework for social networking with a realistic *** theMANETenvironment,based on the query,information is transmitted between the sender and *** the MANET network,the nodes within the communication range are involved in data *** the nodes that lie outside of the communication range are involved in the transmission of relay ***,due to the openness and frequent mobility of nodes,they are subjected to the vast range of security threats ***,it is necessary to develop an appropriate security mechanism for the dataMANET environment for data *** paper proposed a security framework for the MANET network signature escrow *** proposed framework uses the centralised Software Defined Network(SDN)with an ECC cryptographic *** developed security framework is stated as Escrow Elliptical Curve Cryptography SDN(EsECC_SDN)for attack detection and *** developed EsECC-SDN was adopted in two stages for attack classification and detection:(1)to perform secure data transmission between nodes SDN performs encryption and decryption of the data;and(2)to detect and classifies the attack in theMANET hyper alert based HiddenMarkovModel Transductive Deep ***,the EsECC_SDN is involved in the assignment of labels in the transmitted data in the database(DB).The escrow handles these processes,and attacks are evaluated using the hyper *** labels are assigned based on the k-medoids attack clustering through label assignment through a transductive deep learning *** proposed model uses the CICIDS dataset for attack detection and *** developed framework EsECC_SDN’s performance is compared to that of other classifiers such as AdaBoost,Regression,and Decision *** performance of the proposed EsECC_SDN exhibits∼3%improved performance compared with conventional techniques.

关键词： MANET security classifier cryptography attack escrow ECC

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When LoRa meets distributed machine learning to optimize the network connectivity for green and intelligent transportation system

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Green Energy and Intelligent Transportation 2024年第3期3卷 24-41页

作者： Malak Abid Ali Khan Hongbin Ma Arshad Farhad Asad Mujeeb Imran Khan Mirani Muhammad Hamza National Key Lab of Autonomous Intelligent Unmanned Systems School of AutomationBeijing Institute of TechnologyBeijing 100081China Department of Computer Science Namal UniversityPakistan Department of Electrical Engineering Tsinghua UniversityBeijing 100084China Faculty of Information Technology Beijing University of TechnologyBeijing 100124China School of Mechanical Engineering Beijing Institute of TechnologyBeijing 100081China

LoRa technology contributes to green energy by enabling efficient,long-range communication for the Internet of Things(IoT).This paper addresses the challenges related to coverage range in outdoor monitoring systems utilizing LoRa,where the network performance is affected by the density of gateways(GWs)and end devices(EDs),as well as environmental *** mitigate interference,data throughput losses,and high-power consumption,the proposed spreading factor(SF)and hybrid(data rate|SF)models dynamically adjust the transmission *** orchestration of concurrent data modifications within the network server(NS)is crucial for uninterrupted communication between GWs and EDs,especially in monitoring electric vehicle(EV)stations to reduce traffic congestion and *** K-means and density-based spatial clustering of applications with noise(DBSCAN)algorithms optimizes ED allocation,averts data congestion,and improves the signal-tointerference noise ratio(SINR).These methods ensure seamless information reception by meticulously allocated EDs across various GW *** estimate the free-space losses(FSL),a log-distance path loss model(log-PL)is *** various bandwidths(BWs),bidirectional communications,and duty cycles(DCs)helps to prevent saturation,thus prolonging the operational lifespan of *** findings reveal a notable packet rejection rate(PRR)of 0%for the DBSCAN(hybrid model).In contrast,the K-means exhibits a PRR ranging from 5%(hybrid model)to 35.29%(SF model)for the ten GWs ***,the network saturation is reduced to 10.185%and 9.503%,respectively,highlighting an improvement in the average efficiency of slotted ALOHA(91.1%)and pure ALOHA(90.7%).These enhancements increase the lifespan of EDs to 15,465.27 days.

关键词： DBSCAN Green transportation Hybrid model Intelligent transportation K-means

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Cardiac Arrhythmia Disease Classifier Model Based on a Fuzzy Fusion Approach

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computers, Materials & Continua 2023年第5期75卷 4485-4499页

作者： Fatma Taher Hamoud Alshammari Lobna Osman Mohamed Elhoseny Abdulaziz Shehab Eman Elayat College of Technological Innovation Zayed UniversityDubaiUAE Department of Information Systems College of Computer and Information SciencesJouf UniversitySakakaSaudi Arabia Department of Electronics and Communications Engineering Delta Higher Institute for Engineering&TechnologyMansouraEgypt College of Computing and Informatics University of SharjahSharjahUnited Arab Emirates Department of Information Systems Mansoura UniversityMansoura35516Egypt Department of Teacher Preparation Faculty of Specific EducationMansoura UniversityMansouraEgypt

Cardiac diseases are one of the greatest global health *** to the high annual mortality rates,cardiac diseases have attracted the attention of numerous researchers in recent *** article proposes a hybrid fuzzy fusion classification model for cardiac arrhythmia *** fusion model is utilized to optimally select the highest-ranked features generated by a variety of well-known feature-selection *** ensemble of classifiers is then applied to the fusion’s *** proposed model classifies the arrhythmia dataset from the University of California,Irvine into normal/abnormal classes as well as 16 classes of ***,at the preprocessing steps,for the miss-valued attributes,we used the average value in the linear attributes group by the same class and the most frequent value for nominal ***,in order to ensure the model optimality,we eliminated all attributes which have zero or constant values that might bias the results of utilized *** preprocessing step led to 161 out of 279 attributes(features).Thereafter,a fuzzy-based feature-selection fusion method is applied to fuse high-ranked features obtained from different heuristic feature-selection *** short,our study comprises three main blocks:(1)sensing data and preprocessing;(2)feature queuing,selection,and extraction;and(3)the predictive *** proposed method improves classification performance in terms of accuracy,F1measure,recall,and precision when compared to state-of-the-art *** achieves 98.5%accuracy for binary class mode and 98.9%accuracy for categorized class mode.

关键词： Cardiac arrhythmia preprocessing missing values classification model fusion

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A Web-Based Vaccine Distribution System for Covid-19 Using Vaxallot 4th

A Web-Based Vaccine Distribution System for Covid-19 Using V...

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4th EAI International Conference on Cognitive Computing and Cyber Physical systems, IC4S 2023

作者： Valarmathi, B. Srinivasa Gupta, N. Prakash, G. BarathyKolappan, A. Padmavathy, N. Department of Software and Systems Engineering School of Computer Science Engineering and Information Systems Vellore Institute of Technology Tamil Nadu Vellore India Department of Manufacturing Engineering School of Mechanical Engineering Vellore Institute of Technology Tamil Nadu Vellore India Department of Database Systems School of Computer Science and Engineering Vellore Institute of Technology Tamil Nadu Vellore India Systems Engineer Tata Consultancy Services Tamil Nadu Chennai India Department of Electronics and Communication Engineering Vishnu Institute of Technology Andhra Pradesh Bhimavaram India

ISBN: (纸本)9783031488900

Vaxallot seeks to implement a system to distribute vaccines across high-risk groups accounting for various parameters and prove to be superior to what conventional systems are capable of today. It is a Python flask-based tool backed by infrastructure and data resources from the Covid India central repository;all it needs is a single channel input and a single parameter of the value produced, and the algorithm will take care of the rest. Since it’s Python-based and has an active integration with google sheets, live value updating could be possible for the real-time output of the distribution. The novelty of the proposed mechanism is the unique priority index, a score that accounts for an array of factors associated with the pandemic and is computed for regions in question here;this makes way for better distribution of vaccines. The application has an exclusive segment centered on handling excess units, if any. Moreover, since the application is developed to suit the needs of dynamic demographics, any region can roll out this application for purposes they desire to serve the masses. Since it isn’t bound by a coronavirus, it can be used by the healthcare industry as they deem fit. © 2024, ICST Institute for computer Sciences, Social Informatics and Telecommunications engineering.

关键词： Coronavirus

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