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International Journal of Interactive Mobile Technologies 2023年第4期17卷 89-100页

作者： Sangeetha, M. Erna, G. Kannan, S. Rajes Salameh, Anas A. Kishore, Kakarla Hari Department of Data Science and Business Systems SRMIST KattankulathurChennai India Ongole India Computer Science and Engineering Chennai Institute of Technology Chennai India Department of Management Information Systems College of Business Administration Prince Sattam Bin Abdulaziz University Al-Kharj Saudi Arabia Department of Electronics and Communication Engineering Koneru Lakshmaiah Education Foundation Andhra Pradesh India

Mobile Ad-Hoc network is a distributed wireless network that is self-organized and self-maintained and it doesn’t require a fixed framework or central administration. Wireless nodes in a mobile ad hoc network are transient and have a short lifespan. They combine to form a self-configured, infrastructure-free network where routing is a significant difficulty. The wireless nodes in the network must synchronize in order to decide connectivity and routing. Ad hoc network synchronization includes activities including node organization, neighborhood detection, and routing. The predetermined framework resulted in an increase in network control overhead. If a node can link to every other node in the network, it is referred to as a dominating node, and a set of dominating nodes make up the dominating set. The main purpose of this article is to lessen routing overhead in the wireless network with the dominating set based routing (DSBR). In order to discover routes, shorten reroute establishment times, and increase packet delivery rates, this research presents an energy-efficient routing algorithm (EERA) that considerably increases the network performance. The effectiveness of this technique is demonstrated by the simulation analysis of the outcome. © 2023,International Journal of Interactive Mobile Technologies. All Rights Reserved.

关键词： Mobile ad hoc networks

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Analysis of Feature Parameters and Their Time-Transition for Shockable Arrhythmia and Prediction of the Effect of Electrical Defibrillation 3

Analysis of Feature Parameters and Their Time-Transition for...

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3rd IEEE Industrial Electronics Society Annual On-Line Conference, ONCON 2024

作者： Noguchi, Shunta Yoshikawa, Yuta Okai, Takayuki Oya, Hidetoshi Rahman, Md. Masudur Yoshida, Minoru Graduate School of Integrative Science and Engineering Tokyo City University Tokyo Japan Tokyo City University Department of Computer Science Tokyo Japan Noakhali Science and Technology University Department of Information and Communication Engineering Bangladesh Kanagawa University Department of Applied Systems and Mathematics Kanagawa Japan

ISBN: (纸本)9798331540319

In this paper, we propose a prediction system of the effect of electrical defibrillation. In order to develop the proposed system, we firstly analyze from pre-shock (immediately before defibrillation) ECGs (ElectroCardioGrams) by using Gabor Wavelet Transform, Poincaré plot analysis, Spectral entropy, and feature parameters are extracted by those extracted analysis results, we focus on time-transition feature parameter. Next, effective feature parameters are selected based on χ2 -test. Finally, 'Effective' and 'Ineffective' for electrical defibrillation are classified by using SVM (Support Vector Machine) with three kernels (Linear, Gaussian, and Polynomial) and regularization. In this way, we shows the effectiveness of the proposed feature extraction methods and prediction system. © 2024 IEEE.

关键词： Support vector machines

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Accessing the Edge: Delay Evaluation to Distributed Edge Services in a City-Level 5G Network

Accessing the Edge: Delay Evaluation to Distributed Edge Ser...

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IEEE International Conference on Cloud Engineering (IC2E)

作者： Matthias Frei Piotr Karbownik Reinhard German Anatoli Djanatliev Fraunhofer Institute for Integrated Circuits IIS Erlangen Germany Dept. of Computer Science Computer Networks and Communication Systems University of Erlangen-Nürnberg Germany

ISBN: (数字)9798331528690

ISBN: (纸本)9798331528706

Cloud combined with Multi-Access Edge Computing (MEC) empowers service creators and application developers with promising architectural design and communication performance improvements. In fifth generation (5G) and in 6G cellular networks, MEC gains more importance as a service platform to enable new applications. However, as of today, the availability of MEC resources in public networks is still low, thus not much communication performance measurement data exists. In this work, we use our private, city-level 5 G test bed, to evaluate the end-to-end communication performance to different edge and cloud endpoints through realistic outdoor field tests. Multiple topological locations of the edge service are evaluated, the network is operated in stand-alone (SA) and non-standalone (NSA) modes, and two-way as well as one-way latency measurements with multiple traffic patterns are performed. The measurements are executed in different environmental settings: fixed position and drive tests, including 5 G cell hand-overs. The results not only demonstrate the performance benefits gained from MEC resources, but also show the impact of the communication system and user mobility to Quality of Service (QoS) parameters. Especially for different traffic patterns and for the performance during our drive tests, our results show the time overhead required for exchanging data, which may be challenging for service lookups or delay-constrained applications.

关键词： Measurement Cellular networks 6G mobile communication Multi-access edge computing 5G mobile communication Quality of service Traffic control Position measurement Delays

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An Edge Resource Selection Scheme Considering QoS and Computational Parameters

An Edge Resource Selection Scheme Considering QoS and Comput...

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International Conference on computer communications and networks (ICCCN)

作者： Matthias Frei Reinhard German Anatoli Djanatliev Fraunhofer Institute for Integrated Circuits IIS Erlangen Germany Dept. of Computer Science Computer Networks and Communication Systems University of Erlangen-Nürnberg Germany

ISBN: (数字)9798350384611

ISBN: (纸本)9798350348439

Edge computing enhances cloud architectures through the integration of distributed platforms that operate closer to end-users. With dynamically changing network topologies, user mobility, multiple access networks, demand-driven service orchestration, and consequently several distributed service instances that are available, methods for selecting edge resources must adapt to these conditions. This consideration is particularly relevant for edge computing, where target applications often have strict Quality of Service (QoS) constraints. This work proposes an edge resource selection scheme that considers several QoS parameters, computing load, and service usage cost. These metrics are employed to derive a selection score through four distinct algorithms. The overall performance of each algorithm is evaluated by scoring examples, a sensitivity analysis, and in a system-level simulation of a fifth generation (5G) cellular network with user mobility and multiple Multi-Access Edge Computing (MEC) platforms. The results show that all approaches perform well under unambiguous QoS and load conditions, i.e., very good or very poor, but some lose accuracy under moderate, but still acceptable, conditions. For the goal of cost-optimized selection while meeting QoS constraints, one novel method presented is significantly superior to the others. Used in simulation, it generates 12% more computing load on cheaper platforms than its closest competitor, and maintains significantly lower loads on high-cost platforms.

关键词： Measurement Cellular networks Cloud computing Multi-access edge computing Costs Accuracy Sensitivity analysis

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A Conversational Human-computer Interface for Smart Energy System Simulation Environments

A Conversational Human-Computer Interface for Smart Energy S...

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2023 Winter Simulation Conference, WSC 2023

作者： Dengler, Gabriel Bazan, Peter German, Reinhard Lalbakhsh, Pooia Liebmann, Ariel Friedrich-Alexander-Universität Erlangen-Nürnberg Laboratory of Computer Networks and Communication Systems Martensstr. 3 BY Erlangen91058 Germany Monash University Faculty of Information Technology Department of Data Science and Ai ClaytonVIC3168 Australia

ISBN: (纸本)9798350369663

This paper introduces a conversational framework that enhances the usability of smart energy system simulations. This study is centered around OpenAI's Generative Pre-trained Transformer (GPT), a fine-tuned conversational model that allows users to communicate with the system in a natural way. Therefore, users can describe their simulation scenarios in plain language and GPT seamlessly translates these descriptions into Python scripts, used as inputs to the simulation environment, in our case, AnyLogic Simulation Software. Our framework is based on the i7-AnyEnergy core framework to compute distribution flows and relevant statistics. The proposed human-machine interface facilitates and accelerates simulation modeling, as demonstrated through the two scenarios we have provided in this paper. Overall, our conversational framework has the potential to significantly improve the user experience of smart energy system simulation environments. By simplifying the interaction between users and complex simulation models, we enable users to obtain valuable insights rapidly and more easily. © 2023 IEEE.

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Machine Learning for Climate Change Impact Assessment and Adaptation Planning 2

Machine Learning for Climate Change Impact Assessment and Ad...

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2nd IEEE International Conference on Trends in Quantum Computing and Emerging Business Technologies, TQCEBT 2024

作者： Balakrishnan, T. Suresh Krishnan, Prabhakar Ebenezar, U. Samson Mohammed Nizarudeen, M. Kamal, N. Saveetha Institute of Medical and Technical Sciences Saveetha University Saveetha School of Engineering Department of Computer Science and Engineering Chennai India Amrita Vishwa Vidyapeetham Center for Cyber Security Systems and Networks Amritapuri-Campus India Saveetha Institute of Medical and Technical Sciences Saveetha University Saveetha School of Engineering Department of Computer Science and Engineering Tamil Nadu Chennai India Care College of Engineering Department of Computer Science and Engineering Tamil Nadu Trichy India Grt Institute of Engineering and Technology Dept. of Computer Science and Engineering Tamil Nadu Tiruttani India

ISBN: (纸本)9798350384277

The presented research introduces a new advanced data analytics methodology for climate change impact assessment and adaptive planning that utilizes machine learning and deep-learning techniques. Quantitative analysis was performed over several databases such as GHCN, ERA5, National Centers for Environmental Prediction (NCEP) and JRA-55 in addition to CRU for a thorough assessment of the proposed methodology. In climate modeling, the Convolutional Neural networks (CNN) showed better accuracy than ERA5 and JRA-55 which outperformed Global Historical Climatology Network (GHCN) with lower Mean Absolute Error (MAE), Root Mean Squared Error values. The Early Warning System, which was built using the LSTM network algorithm, had a higher accuracy of 0.90 and recall rate of 0.88 especially with JRA-55 proving its effectiveness in early detection for extreme weather events before they occur. The RL-based adaptive planning component performed well across all datasets, with ERA5 reaching the best feedback loop performance score of 94%. The precision agriculture optimization, which was enabled by Random Forest revealed different accuracy and AUC-ROC values across various datasets showing flexibility. Against international climate agreements, the overall alignment score was 0.78 with ERA5 being slightly better at 0.80 using Support Vector Machines (SVM). These quantitative assessments accentuate the practicality, efficacy, and applicability of this methodology in various datasets making it an apt tool for evidence-based decisions on climate resilience strategies at the global level. © 2024 IEEE.

关键词： Adversarial machine learning

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Big Data Architectures in a patient-driven healthcare system: Implications, Scrutiny and Analysis for future prospects 1

Big Data Architectures in a patient-driven healthcare system...

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1st International Conference on Innovative Engineering sciences and Technological Research, ICIESTR 2024

作者： Memon, Kamran Ali Memon, Imran Kumbhar, Farooque Bala, Abu Bakar Iqbal, Naveed Qureshi, Khurram Karim King Fahd University of Petroleum and Minerals Center for Communication Systems and Sensing Dhahran31261 Saudi Arabia Shah Abdul Latif University Department of Computer Science Shahdadkot Campus Pakistan King Fahd University of Petroleum and Minerals Electrical Engineering Department Center for Communication Systems and Sensing Dhahran31261 Saudi Arabia

ISBN: (纸本)9798350348637

The term "big data"describes a significant amount of valuable information. Additionally, a sizable amount of big data related to public health comes from biological research. It is necessary to manage and analyse this data with care to get accurate information. There are several problems with every step of large data management that can only be fixed with sophisticated big data computing solutions. This is the reason health professionals need to be fully equipped with the tools necessary to efficiently collect and analyse big data to deliver appropriate solutions to promote public health. By creating new opportunities for contemporary health, proper big data management, analysis, and interpretation may completely transform the game. For this reason, several industries, including the health industry, are moving quickly to seize this chance to provide improved services and financial gains. Modern healthcare organizations have the potential to transform medical and personal medicine via the effective integration of big data and healthcare services. This article outlines many analytical paths that the patient-driven healthcare system might take, as seen from the viewpoints of different players. We have also examined several big data architectures in terms of their analytical influence, application fields, and underlying data sources and challenges in collecting the big data for healthcare systems. © 2024 IEEE.

关键词： Electronic health record

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Parallel Computations in the Problem of Identification of Interval Discrete Models based on Swarm Intelligence of a Bee Colony 13

Parallel Computations in the Problem of Identification of In...

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13th International Conference on Advanced computer Information Technologies, ACIT 2023

作者： Dyvak, Mykola Kindzerskyi, Oleksandr Dostalek, Libor Stetsko, Mykola Nowak, Joachim West Ukrainian National University Department of Computer Science Ternopil Ukraine Czech Technical University in Prague Computer Networks Research Group Department of Computer Systems Prague Czech Republic West Ukrainian National University Department of Financial Management and Insurance Ternopil Ukraine Catholic University in Ruzomberok Faculty of Theology Ruzomberok Slovakia

The article discusses the problem of parametric identification of interval discrete models of complex objects. A new scheme of parallel computations for solving the problem of parametric identification based on the behavioral model of an artificial bee colony is proposed and justified. The effectiveness of the proposed parallel computing scheme is considered using the example of parametric identification of a mathematical model of the anaerobic microbiological fermentation process in biogas plants. A nonlinear second-order discrete model describes the dynamics of residual organic waste mass in the biogas reactor during fermentation. According to the results of the experiments, a 2-fold acceleration of the algorithm's computational time was achieved. © 2023 IEEE.

关键词： Swarm intelligence

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Using IoT-Based Mobile Application to Build Smart Parking System 9

Using IoT-Based Mobile Application to Build Smart Parking Sy...

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9th IEEE International Conference on Computing, Engineering and Design, ICCED 2023

作者： Attarbashi, Zainab S. Thamodharan, Tharshaan A-L Abuzaraida, Mustafa Ali Iftikhar, Saman Alansari, Noof Abdulaziz Basri, Atikah Balqis Binti Handayani, Dini Oktarina Dwi International Islamic University Malaysia Department of Computer Science Faculty of Information & Communication Technology Selangor Malaysia Universiti Utara Malaysia School of Computing Sintok Malaysia Misurata University Faculty of Information Technology Computer Science Department Libya Arab Open University Faculty of Computer Studies Saudi Arabia International Islamic University Malaysia Faculty of Information & Communication Technology Department of Information Systems Selangor Malaysia

ISBN: (纸本)9798350370126

The idea of using the current technologies to build more sustainable smart cities has gained great popularity. One of attractive fields is Internet of Things applications to control vehicle traffic and parking which reduce energy consumption in smart cities. This paper presents an android mobile application system that allows users to check the availability and location of parking spots by using their smartphones. Main tools used for this project are the Arduino UNO and mobile application running with Android. Sensors were used to sense if the spot is empty, and then send that info to the mobile application. As the empty place is discovered to be vacant it is distinguished utilizing ultrasonic sensors which report it further. The system would not help the user to book parking spot but would show the availability of parking spot to reduce the searching time. This Smart Parking System is a basic prototype which can be improved later for real system by connecting the system to a GPS-based application which will direct the user to the spot itself and it can further be improved by using artificial intelligence to highlight different spots to different users. © 2023 IEEE.

关键词： Internet of things

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Optimal Resource Allocation for NOMA Wireless networks

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computers, Materials & Continua 2023年第2期74卷 3249-3261页

作者： Fahad R.Albogamy M.A.Aiyashi Fazirul Hisyam Hashim Imran Khan Bong Jun Choi Turabah University College Computer Sciences ProgramTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Mathematics Jazan UniversityJazanP.O.Box 218Saudi Arabia Department of Computer and Communication Systems Engineering Faculty of EngineeringUniversiti Putra Malaysia(UPM)43400SerdangMalaysia Department of Electrical Engineering University of Engineering and Technology PeshawarP.O.Box 814Pakistan School of Computer Science and Engineering Soongsil UniversitySeoulKorea

The non-orthogonal multiple access(NOMA)method is a novel multiple access technique that aims to increase spectral efficiency(SE)and accommodate enormous user ***-user signals are superimposed and transmitted in the power domain at the transmitting end by actively implementing controllable interference information,and multi-user detection algorithms,such as successive interference cancellation(SIC),are performed at the receiving end to demodulate the necessary user *** its basic signal waveform,like LTE baseline,could be based on orthogonal frequency division multiple access(OFDMA)or discrete Fourier transform(DFT)-spread OFDM,NOMA superimposes numerous users in the power *** contrast to the orthogonal transmission method,the nonorthogonal method can achieve higher spectrum ***,it will increase the complexity of its *** power allocation techniques will have a direct impact on the system’s *** a result,in order to boost the system capacity,an efficient power allocation mechanism must be *** research developed an efficient technique based on conjugate gradient to solve the problem of downlink power *** major goal is to maximize the users’maximum weighted sum *** suggested algorithm’s most notable feature is that it converges to the global optimal *** compared to existing methods,simulation results reveal that the suggested technique has a better power allocation capability.

关键词： Non-orthogonalmultiple access wireless networks power domain 5G networks

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