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2023 International Symposium on Networks, computers and Communications, ISNCC 2023

作者： Ghosh, Aviroop Kunz, Thomas Yousefi, Saleh Carleton University Department of Systems and Computer Engineering Ottawa Canada Urmia University Department of Computer Engineering Urmia Iran

ISBN: (纸本)9798350335590

Industry 4.0 applications require communication networks with deterministic and bounded latency. Ethernet, augmented with the IEEE Time-Sensitive Networking (TSN) standards, can meet these requirements. One of the TSN standards, Time Aware Shaper (TAS) is ideal for periodic time-sensitive traffic in wired TSN networks. However, it relies on network-wide synchronization to a common reference time. Existing solutions for developing TAS schedules assume perfect synchronization or consider a worst-case error. This study highlights the need for using network-derived time synchronization parameters and errors to optimize TAS schedules. It raises the importance of accurate time synchronization information and proposes a novel methodology for efficient band-width utilization while ensuring deadline requirements are met for time-sensitive traffic in realistic networks. The effectiveness of the proposed framework is validated by simulating a TSN network in OMNeT++ and comparing the devised TAS schedules with schedules which use existing assumptions. © 2023 IEEE.

关键词： Ethernet

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Fuzzy Decision-Based Clustering for Efficient Data Aggregation in Mobile UWSNs

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computers, Materials & Continua 2025年第4期83卷 259-279页

作者： Aadil Mushtaq Pandith Manni Kumar Naveen Kumar Nitin Goyal Sachin Ahuja Yonis Gulzar Rashi Rastogi Rupesh Gupta Department of Computer Science and Engineering Lovely Professional UniversityJalandhar144402PunjabIndia Department of Computer Science and Engineering Chandigarh UniversityMohali140413PunjabIndia Salesforce Inc. DallasTX 75201USA Department of Computer Science and Engineering School of Engineering and TechnologyCentral University of HaryanaMahendragarh123031HaryanaIndia Department of Management Information Systems College of Business AdministrationKing Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Computer Application Sir Chhotu Ram Institute of Engineering and TechnologyCh.Charan Singh UniversityMeerut250001Uttar PradeshIndia Chitkara University Institute of Engineering and Technology Chitkara UniversityRajpura140401PunjabIndia

Underwater wireless sensor networks(UWSNs)rely on data aggregation to streamline routing operations by merging information at intermediate nodes before transmitting it to the ***,many existing data aggregation techniques are designed exclusively for static networks and fail to reflect the dynamic nature of underwater ***,conventional multi-hop data gathering techniques often lead to energy depletion problems near the sink,commonly known as the energy hole ***,cluster-based aggregation methods face significant challenges such as cluster head(CH)failures and collisions within clusters that degrade overall network *** address these limitations,this paper introduces an innovative framework,the Cluster-based Data Aggregation using Fuzzy Decision Model(CDAFDM),tailored for mobile *** proposed method has four main phases:clustering,CH selection,data aggregation,and *** CH selection,a fuzzy decision model is utilized to ensure efficient cluster head selection based on parameters such as residual energy,distance to the sink,and data delivery likelihood,enhancing network stability and energy *** the aggregation phase,CHs transmit a single,consolidated set of non-redundant data to the base station(BS),thereby reducing data duplication and saving *** adapt to the changing network topology,the re-clustering phase periodically updates cluster formations and reselects *** results show that CDAFDM outperforms current protocols such as CAPTAIN(Collection Algorithm for underwater oPTical-AcoustIc sensor Networks),EDDG(Event-Driven Data Gathering),and DCBMEC(Data Collection Based on Mobile Edge Computing)with a packet delivery ratio increase of up to 4%,an energy consumption reduction of 18%,and a data collection latency reduction of 52%.These findings highlight the framework’s potential for reliable and energy-efficient data aggregation mobile UWSNs.

关键词： Clustering data aggregation data collection fuzzy model monitoring UWSN

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Xtractor: A Two-Step Tweet Extractor for Sentiment Analysis 5

Xtractor: A Two-Step Tweet Extractor for Sentiment Analysis

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5th International Conference on Advancements in Computational Sciences, ICACS 2024

作者： Alvi, Muhammad Bux Mahoto, Naeem Ahmed Unar, Mukhtiar Ali Shaikh, Muhammad Akram The Islamia University of Bahawalpur Computer Systems Engineering Bahawalpur Pakistan Mehran Uet Software Engineering Department Jamshoro Pakistan Mehran Uet Computer Systems Engineering Department Jamshoro Pakistan Pastic Pakistan Science Foundation Islamabad Pakistan

ISBN: (纸本)9798350394764

Twitter (now X) has been gaining popularity with each passing day since its inception in 2006. People have been using Twitter as an instant repository to collect data and gain insight into folks' minds on trending issues. Although Twitter allows access to its data through streaming and rest APIs, extracting the required data is difficult. The data (tweet) returned by Twitter is in json format, having at least 26 fields. Each field is bundled in the dictionary form data structure. tweet metadata such as tweet 'likes' and 'retweets' increase the volume and complexity of a tweet, making data extraction in a cleaner format more difficult. This work aims to develop an effective two-step tweet extractor (Xtractor: an online-offline keyword-based Twitter data extractor). In the first step, Xtractor collects publicly available topical tweets using keywords, hashtags, or their list on the fly, parses all the tweet fields, and filters them to retain potential field contents without additional payload. The second step of the Xtractor evicts partially matching tweets using the regular expression method to acquire the targeted domain-specific tweets. Using the proposed two-step Twitter data extraction method, datasets concerning the people of Pakistan have been collected, which can be leveraged to get insight for decision-making, specially in the context of sentiment analysis. We found this method efficient, capacitive, and productive. © 2024 IEEE.

关键词： Python

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Transaction transmission model for blockchain channels based on non-cooperative games

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Science China(Information Sciences) 2023年第1期66卷 97-114页

作者： Peiyun ZHANG Chenxi LI Mengchu ZHOU Wenjun HUANG Abdullah ABUSORRAH Omaimah O.BAMASAG Engineering Research Center of Digital Forensics of Ministry of Education School of Computer and SoftwareNanjing University of Information Science and Technology School of Computer and Information Anhui Normal University Department of Electrical and Computer Engineering New Jersey Institute of Technology Center of Research Excellence in Renewable Energy and Power Systems Department of Electrical and Computer Engineering Faculty of Engineering and K.A.CARE Energy Research and Innovation CenterKing Abdulaziz University Department of Computer Science Faculty of Computing and Information Technology Center of Excellence in Smart Environment Research King Abdulaziz University

In blockchain networks, transactions can be transmitted through channels. The existing transmission methods depend on their routing information. If a node randomly chooses a channel to transmit a transaction, the transmission may be aborted due to insufficient funds(also called balance) or a low transmission rate. To increase the success rate and reduce transmission delay across all transactions, this work proposes a transaction transmission model for blockchain channels based on non-cooperative game *** balance, channel states, and transmission probability are fully considered. This work then presents an optimized channel transaction transmission algorithm. First, channel balances are analyzed and suitable channels are selected if their balance is sufficient. Second, a Nash equilibrium point is found by using an iterative sub-gradient method and its related channels are then used to transmit transactions. The proposed method is compared with two state-of-the-art approaches: Silent Whispers and Speedy Murmurs. Experimental results show that the proposed method improves transmission success rate, reduces transmission delay,and effectively decreases transmission overhead in comparison with its two competitive peers.

关键词： Blockchain channel transaction transmission channel balance channel state channel transmission probability non-cooperative game

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Enhancing Renewable Energy Integration:A Gaussian-Bare-Bones Levy Cheetah Optimization Approach to Optimal Power Flow in Electrical Networks

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computer Modeling in engineering & Sciences 2024年第8期140卷 1339-1370页

作者： Ali S.Alghamdi Mohamed A.Zohdy Saad Aldoihi Department of Electrical Engineering College of EngineeringMajmaah UniversityAl-Majmaah11952Saudi Arabia Electrical and Computer Engineering Department Oakland UniversityRochesterMI48309USA Institute of Earth and Space Science King Abdulaziz City for Science and Technology(KACST)Riyadh11442Saudi Arabia Computer Science and Systems Engineering Institute Polytechnique de ParisPalaiseau CedexFrance

In the contemporary era,the global expansion of electrical grids is propelled by various renewable energy sources(RESs).Efficient integration of stochastic RESs and optimal power flow(OPF)management are critical for network *** study introduces an innovative solution,the Gaussian Bare-Bones Levy Cheetah Optimizer(GBBLCO),addressing OPF challenges in power generation systems with stochastic *** primary objective is to minimize the total operating costs of RESs,considering four functions:overall operating costs,voltage deviation management,emissions reduction,voltage stability index(VSI)and power loss ***,a carbon tax is included in the objective function to reduce carbon *** scrutiny,using modified IEEE 30-bus and IEEE 118-bus systems,validates GBBLCO’s superior performance in achieving optimal *** results demonstrate GBBLCO’s efficacy in six optimization scenarios:total cost with valve point effects,total cost with emission and carbon tax,total cost with prohibited operating zones,active power loss optimization,voltage deviation optimization and enhancing voltage stability index(VSI).GBBLCO outperforms conventional techniques in each scenario,showcasing rapid convergence and superior solution ***,GBBLCO navigates complexities introduced by valve point effects,adapts to environmental constraints,optimizes costs while considering prohibited operating zones,minimizes active power losses,and optimizes voltage deviation by enhancing the voltage stability index(VSI)*** research significantly contributes to advancing OPF,emphasizing GBBLCO’s improved global search capabilities and ability to address challenges related to local *** emerges as a versatile and robust optimization tool for diverse challenges in power systems,offering a promising solution for the evolving needs of renewable energy-integrated power grids.

关键词： Renewable energy integration optimal power flow stochastic renewable energy sources gaussian-bare-bones levy cheetah optimizer electrical network optimization carbon tax optimization

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AI Based Automated Gym Trainer Using Machine Learning 10

AI Based Automated Gym Trainer Using Machine Learning

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10th International Conference on Advanced Computing and Communication systems, ICACCS 2024

作者： Cholaraja, K. Gururaj, M. Swasthika, V. Gnanasambandam, S.R. Sri Eshwar College of Engineering Department of Computer Science and Business Systems Coimbatore India

ISBN: (数字)9798350384369

ISBN: (纸本)9798350384369

The 'Smart Exercise Counter using computer Vision' is a groundbreaking system that blends cutting-edge computer vision technology with exercise monitoring. In an age where fitness and health are paramount, this innovative solution addresses the limitations of conventional fitness tracking methods by offering real-time, accurate feedback and comprehensive data analysis. By utilizing computer vision algorithms, this system tracks and analyzes the movements of individuals during their exercise routines, enhancing exercise counting, form assessment, and overall workout efficacy. Key components of the system include strategically positioned cameras, real-time image processing, machine learning models for exercise recognition, and biomechanically-informed form analysis. The system not only counts repetitions but also evaluates posture and technique, providing immediate feedback and corrections. Users can access their exercise data and progress through an intuitive mobile app or web dashboard, making it accessible and user-friendly. The applications of this technology extend beyond personal fitness, encompassing healthcare, sports training, and gym facilities. Healthcare professionals can employ it for rehabilitation and therapy, while athletes and coaches can refine training regimens. Gyms can enhance member experiences by offering advanced exercise monitoring. The 'Smart Exercise Counter using computer Vision' embodies the future of exercise monitoring, where technology aligns with health and fitness goals, offering a promising path towards more accurate, effective, and enjoyable workouts. This abstract encapsulates the transformative potential of computer vision in shaping the way we approach physical exercise and well-being. © 2024 IEEE.

关键词： Training computer vision Accuracy Tracking Medical treatment Machine learning Real-time systems Mobile applications Monitoring Sports

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Advanced Auditing Solutions Through the Blockchain Cutting Edge Technology 10

Advanced Auditing Solutions Through the Blockchain Cutting E...

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10th International Conference on Advanced Computing and Communication systems, ICACCS 2024

作者： Siva, K.P. Sudhakar, S. Sahaya Gurus Raja, M. Kanishka, G. Niranjan, V. Sri Eshwar College of Engineering Department of Computer Science and Business Systems Coimbatore India

ISBN: (数字)9798350384369

ISBN: (纸本)9798350384369

In the modern business landscape, organizations seek technology-driven auditing solutions. This Abstract empowers auditors by reducing their workload and providing precise questionnaires to extract detailed financial information for a comprehensive examination process, ensuring accuracy and efficiency. The scourge of manual data entry is relegated to history, as this system seamlessly connects to bank accounts for effortless data import or accommodates the upload of data in universally accepted document formats. At its core, an advanced algorithm works tirelessly to analyze extensive transaction data, swiftly pinpointing potential fraud or suspicious activities and expediting the investigative process. After analysis, this system meticulously compiles transaction data, associates them with the relevant parties, and diligently flags anomalies, facilitating the identification of stolen assets and the methodologies employed in the transgressions. Security is paramount through the implementation of blockchain technology, ensuring data integrity, while the project fosters collaboration by facilitating discussions with senior auditors and aligning with established audit standards. The culmination of these features streamlines the creation of auditable, court-ready reports, simplifying the transformation of findings into comprehensive documents fit for legal *** represents a revolutionary paradigm shift, poised to redefine auditing by harmonizing technology, efficiency, security, and adherence to professional principles. Overall, your abstract is comprehensive and well-structured, conveying the significance of your auditing initiative effectively. © 2024 IEEE.

关键词： Efficiency

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Customer Churn Predictive Analytics: Understanding Customer Segments for Enhanced Business Strategies 10

Customer Churn Predictive Analytics: Understanding Customer ...

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10th International Conference on Advanced Computing and Communication systems, ICACCS 2024

作者： Priyanka, G. Sowmiya, M. Vinuja, M. Shree, S.S. Dhanu Shalini, S. Sri Eshwar College of Engineering Department of Computer Science and Business Systems Coimbatore India

ISBN: (纸本)9798350384369

Getting new clients and keeping current ones are the highest priority goals in modern business world. The subscriber base is growing as each industry's market grows swiftly. As a result, companies increasingly recognize how important it is to retain their current customers. In order to maintain their ability to turn a profit, service providers must now significantly reduce their churn rates. Churn prediction enables the identification of clients who are most likely to shop elsewhere. The purpose of this work is to provide broad guidelines on churn prediction using supervised machine learning techniques as a benchmark in conjunction with widely used data sampling techniques on publicly available datasets. A priori selection of the best sampling technique and classification model is challenging since it heavily depends on the inherent properties of the data. In this research, we investigate the performance of seven sampling methodologies, eleven supervised and semi-supervised learning methods, and sixteen different and openly accessible churn-like datasets. © 2024 IEEE.

关键词： Predictive analytics

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Crop Productivity Enhancement Through Data Analytics and IOT 10

Crop Productivity Enhancement Through Data Analytics and IOT

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10th International Conference on Advanced Computing and Communication systems, ICACCS 2024

作者： Siva, K.P. Shri Suriya, P. Praveen, R. Nimesh Rajan, D. Santhosh Kumar, G. Sri Eshwar College of Engineering Department of Computer Science and Business Systems Coimbatore India

ISBN: (数字)9798350384369

ISBN: (纸本)9798350384369

The goal of this project is to create a web-based application for smart farming that makes use of IoT technology to enable real-time monitoring, data analysis, and remote control for improving crop productivity. The solution connects numerous IoT sensors, offers data visualization, applies machine learning for predictive analytics, and assures data security. A sustainable and fruitful future for agriculture is made possible by the application, which equips farmers with useful knowledge. The MQTT protocol collects the data from a variety of IoT sensors, including temperature, humidity, soil moisture, and weather sensors. Using the HTTPS and TLS protocols, data transfer and communication are done using a security-focused approach. An efficient alert and notification system is built up utilizing Twilio for SMS and email services to inform farmers of important occurrences. The project's accomplishments demonstrate the value of incorporating contemporary technology into agriculture and pave the way for more research and development in the area of smart farming. Future improvements may involve extending the selection of IoT sensors that are supported, including drone technology for aerial monitoring, and working with agricultural specialists to adapt the program for various crop kinds and geographical locations. © 2024 IEEE.

关键词： Smart agriculture

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Fitness Certificate Validation Using Automatic Number Plate Recognition 10

Fitness Certificate Validation Using Automatic Number Plate ...

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10th International Conference on Advanced Computing and Communication systems, ICACCS 2024

作者： Ramya, D. Sakthi Maheswari, S. Balaji, S. Shri Kishore, J.C. Deepanchakaravarthy, K. Sri Eshwar College of Engineering Department of Computer Science and Business Systems Coimbatore India

ISBN: (数字)9798350384369

ISBN: (纸本)9798350384369

As traffic congestion escalates, the need for precise and prompt vehicle regulation becomes increasingly critical. Ensuring vehicles comply with fitness certificate requirements is pivotal for road safety and legal conformity. However, traditional manual methods of verifying fitness certificates are prone to errors and time-consuming. This paper introduces an innovative solution: an Automated Number Plate Recognition (ANPR) system seamlessly integrated with a backend database for efficient and reliable verification of vehicle fitness certificates. Our proposed ANPR system utilizes computer vision to capture and analyze number plates, matching them with fitness certificate status stored in the database. This technology not only expedites the verification process but also significantly enhances accuracy compared to manual approaches. By merging ANPR technology with fitness certificate databases, this project has the potential to modernize vehicle regulation practices. This paper offers a detailed exploration of the system's design and functionality, showcasing its ability to revolutionize regulatory procedures and promote road safety. The project places a strong emphasis on data security, ensuring the safe storage and retrieval of sensitive vehicle information. Through this project, we aim to contribute to discussions surrounding intelligent transportation systems and their role in optimizing regulatory processes. By reducing errors, minimizing manual intervention, and enhancing overall efficiency, the ANPR-based approach offers a path towards safer roads and more streamlined regulation. This abstract provides an overview of the methodology, system architecture, implementation details, results, and conclusions, offering a comprehensive perspective on the proposed solution's effectiveness in automating fitness certificate verification. © 2024 IEEE.

关键词： Traffic congestion

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