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International Conference on Computing and Networking Technology (ICCNT)

作者： Mohan Garg S Senthurya Jagtej Singh Anila Bajpai Nakul S. Sharma K. Yuvaraj Centre of Research Impact and Outcome Chitkara University Rajpura Punjab India Department of Computer Science and Engineering Prince Shri Venkateshwara Padmavathy Engineering College Chennai India Chitkara Centre for Research and Development Chitkara University Himachal Pradesh India School of Mangement – UG Management JAIN (Deemed to be University) Bangalore Karnataka India Department of Artificial Intelligence & Data Science Vishwakarma Institute of Technology Pune India Department of Computer Science Karpagam Academy of Higher Education Coimbatore India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

Digital personal Networks have been increasingly utilized in ATM networks for ease of communication. This paper studies the use of VPNs over ATM networks, providing a synopsis of their features and advantages and discussing bible safety threats. The paper also explains VPNs, their sub-types, and how they may be implemented in ATM surroundings; observing takes place once they provide additional protection capabilities while used on ATM networks; we also talk about the fate of VPNs throughout ATM networks, precisely due to the risk posed by using Internet-based providers. These novel results are encouraging and indicate that VPNs may also offer a solution for securing ATM transactions and protecting network data from threat actors.

关键词： Telecommunication traffic Network security Virtual private networks Cryptography Protection

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Fuzzy-Deep Learning-Based Artificial Intelligence for Edge Computing and Real-Time Decision-Making in Uncertain IoT Environments

Fuzzy-Deep Learning-Based Artificial Intelligence for Edge C...

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Advances in computer science, Electrical, Electronics, and Communication technologies (CE2CT), International Conference on

作者： B.P. Joshi Akhilesh Singh Nagendra Kumar Siddharth Rautela Department of Mathematics Department of Computer Science & Engineering Graphic Era Hill University India Department of Electrical Engineering VMSB UTU Campus Pithoragarh India Department of Electrical & Electronics Engineering GL Bajaj Institute of Technology & Management Greater Noida India Department of Mathematics Central Board of Secondary Education Bhimtal Uttarakhand India

ISBN: (数字)9798331518578

ISBN: (纸本)9798331518585

Owing to the Internet of Vehicles (IoV) quick growth, both academics and the sector have paid close emphasis to vehicular edge computation (VEC). Nevertheless, because of the unbalanced congestion and the strict delay requirements, task offloading in various junction situations continues to struggle from inefficient resource allocated and poor operation implementation standards. This study proposes a task-offloading technique using a fuzzy decision-making method to deal with ambiguity and uncertainties to solve these problems. Roadside Utilities (RSUs) placed alongside remote roadways typically have limited energy resources, thus they must offer energy-effective planning assistance with the distribution of duties to VEC. However, planning decisions for regional task execution incur computational costs, and assigning duties to edge automobiles incurs transmission costs, making energy usage management difficult. Task data transmission to edge automobiles results in increased RSU power usage even while task offloading lowers response delay. To meet task schedule and supply restrictions, this study proposes an energy-effective automobile planning issue for offloading functions to mobile edge units. This study develops a planning technique depending on on-policy deep reinforcement learning (DRL) and a fuzzy-based DRL to address the extremely complex problem brought on by a rise in the number of automobiles under RSU service. When contrasted to the Q-learning method, this FRL not only speeds up the learning procedure but also enhances long-term payoff.

关键词： Schedules Uncertainty Q-learning Decision making Deep reinforcement learning Real-time systems Delays Automobiles Standards Edge computing

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Bridging Automated Reasoning and Machine Learning for Information Analysis

Bridging Automated Reasoning and Machine Learning for Inform...

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International Conference on Futuristic technologies (INCOFT)

作者： Sarita Joshi R Murugan N.V. Balaji P. Chandrakala Gopal B. Deshmukh Mala Mathur Maharishi School of Business Management Maharishi University of Information Technology Uttar Pradesh India Department of Computer Science and Information Technology Jain (Deemed to be University) Bangalore Karnataka India Department of Computer Science Karpagam Academy of Higher Education Coimbatore Department of Electrical and Electronics Engineering Prince Shri Venkateshwara Padmavathy Engineering College Chennai Department of Computer Engineering Vishwakarma Institute of Information Technology Pune India Department of Civil Engineering Vivekananda Global University Jaipur India

Recent advances in automated reasoning and system studying have appreciably impacted the automation of statistics evaluation. These technologies facilitate understanding the increasingly more complicated volumes of facts in a ramification of approaches. Automatic reasoning helps decide valid solutions based on structured good judgment, while machines can pick out patterns and developments in massive datasets. Bridging those two technologies improves accuracy and efficiency in automated facts evaluation. This paper will overview present-day research on bridging automated reasoning and device-gaining knowledge for such purposes and gift novel approaches to combining the two technologies for more effective data evaluation. Discussion subjects will encompass integrating neural networks and reasoning engines, methods for addressing records incompleteness and uncertainty, and enhancement of reasoning-driven context-conscious systems. Furthermore, the paper will discover the capacity benefits that can be performed via leveraging the strengths of each automated reasoning and gadget gaining knowledge of to optimize answers for a selection of software scenarios.

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An eco-friendly multi-generation system integrating geothermal-driven power and cooling cycles with LNG regasification and hydrogen production: a thermo-economic optimization

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Applied Thermal Engineering 2025年 277卷

作者： Almadhor, Ahmad Samad, Sarminah Shaban, Mohamed Abed, Azher M. Alhomayani, Fahad M. Abduvalieva, Dilsora Knani, Salah Alruwaili, Amani Alturise, Fahad Alkhalaf, Salem Department of Computer Engineering and Networks College of Computer and Information Sciences Jouf University Saudi Arabia Department of Management College of Business Administration Princess Nourah bint Abdulrahman University Riyadh11671 Saudi Arabia Department of Physics Faculty of Science Islamic University of Madinah Madinah42351 Saudi Arabia Air Conditioning and Refrigeration Techniques Engineering Department College of Engineering and Technologies Al-Mustaqbal University Babylon51001 Iraq Al - Mustaqbal Center for Energy Research Al-Mustaqbal University Babylon51001 Iraq College of Computers and Information Technology Taif University Saudi Arabia Applied College Taif University Saudi Arabia Department of Mathematics and Information Technologies Tashkent State Pedagogical University Bunyodkor Avenue 27 Tashkent100070 Uzbekistan Center for Scientific Research and Entrepreneurship Northern Border University Arar73213 Saudi Arabia Department of Cybersecurity College of Computer Qassim University Buraydah Saudi Arabia Department of Computer Engineering College of Computer Qassim University Buraydah Saudi Arabia Department of Physics College of Science Northern Border University Arar Saudi Arabia

This study develops a multi-generation framework utilizing geothermal energy to produce electricity, hydrogen, and cooling with high efficiency. The system integrates a Kalina cycle (KC) and an organic Rankine cycle (ORC), supported by a thermoelectric generator (TEG) for waste heat recovery and a proton exchange membrane electrolyzer (PEME) for hydrogen production. Geothermal energy is leveraged to optimize resource utilization, while waste heat is repurposed for LNG regasification, achieving full vaporization and additional power generation. Unlike previous works, this study introduces a fully integrated and cascade-utilized configuration that combines multiple thermal subsystems, each optimized in synergy. This approach enhances energy recovery and reduces system-level exergy destruction, representing a unique advancement in geothermal-based multi-generation design. The results reveal that geothermal fluid temperature (TGF) is the most critical parameter influencing the system's performance. Increasing TGF significantly enhances electricity, chilled water, and hydrogen production, improves exergy efficiency, and reduces levelized costs of electricity (LCOE) and hydrogen (LCOH). In contrast, a higher pinch point temperature difference (PPTD) at the KC evaporator reduces power and hydrogen output but increases chilled water production, revealing key trade-offs between thermal efficiency and operational outputs. Moreover, the LNG stream accounts for 40 % of the system's total exergy loss, followed by the KC (20 %) and ORC (18 %), identifying areas for targeted efficiency improvements. Optimization results show that a turbine inlet pressure of 5900 kPa achieves the highest system efficiency at 22.74 %, while genetic algorithm (GA) optimization enhances second-law efficiency to 25.11 % with an operational cost rate of 137.54 $/h. These findings demonstrate the system's ability to maximize energy recovery and improve overall cost-effectiveness, providing valuable insig

关键词： Waste heat utilization

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A Time-Aware Dynamic Service Quality Prediction Approach for Services

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Tsinghua science and Technology 2020年第2期25卷 227-238页

作者： Ying Jin Weiguang Guo Yiwen Zhang Department of Management Hefei UniversityHefei 230601China School of Computer Science and Technology and also with the Key Laboratory of Intelligent Computing and Signal ProcessingMinistry of EducationAnhui UniversityHefei 230601China

Dynamic Quality of Service(QoS)prediction for services is currently a hot topic and a challenge for research in the fields of service recommendation and *** paper addresses the problem with a Time-aWare service Quality Prediction method(named TWQP),a two-phase approach with one phase based on historical time slices and one on the current time *** the first phase,if the user had invoked the service in a previous time slice,the QoS value for the user calling the service on the next time slice is predicted on the basis of the historical QoS data;if the user had not invoked the service in a previous time slice,then the Covering Algorithm(CA)is applied to predict the missing *** the second phase,we predict the missing values for the current time slice according to the results of the previous phase.A large number of experiments on a real-world dataset,WS-Dream,show that,when compared with the classical QoS prediction algorithms,our proposed method greatly improves the prediction accuracy.

关键词： dynamic Quality of Service(QoS)prediction time-aware service recommendation

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An Investigation of Multicast Protocols over ATM Networks

An Investigation of Multicast Protocols over ATM Networks

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International Conference on Computing and Networking Technology (ICCNT)

作者： Diptonil Banerjee Kambam Vedantan Priyanka More S. Hemelatha Amit Kumar T. Vanaja College of Engineering Teerthanker Mahaveer University Moradabad Uttar Pradesh India School of Mangement - PG Management JAIN (Deemed to be University) Bangalore Karnataka India Computer Engineering Vishwakarma Institute of InformationTechnology Pune India Department of Computer Science Engineering Karpagam Academy of Higher Education Coimbatore India Centre for Interdisciplinary Research for Business and Technology Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Department of Computer Science and Engineering Prince Shri Venkateshwara Padmavathy Engineering College Chennai India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

The paper investigates the impact of the multicast method used over an asynchronous transfer mode (ATM) network in comparison to factor-to-factor solutions. The paper investigated mechanisms, multicast, and point-to-point (P2P) and in comparison their overall performance in phrases of throughput, total delay, and packet loss charge when beneath various community conditions. It turned into located that multicast had benefits in terms of total throughput and postpone while compared to P2P in phrases of cost of bandwidth for larger variety of receivers. Further, the multicast method had a lower packet loss charge than P2P in all situations. This paper concluded that no matter the complexity related multicast, because of its inherent blessings, is taken into consideration a better answer for multimedia programs that require a large number of receivers. Average, its miles counseled that multicast is the era of desire over ATM networks when the number of receivers growth.

关键词： Multicast algorithms Unicast Packet loss Receivers Throughput Multicast protocols Routing Delays Reliability Asynchronous transfer mode

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Machine Learning Based Sentiment Analysis and Swarm Intelligence

Machine Learning Based Sentiment Analysis and Swarm Intellig...

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Integrated Circuits and Communication Systems (ICICACS), IEEE International Conference on

作者： Raj Kumar Patra Bassamma Patil T. Sathish Kumar Gandla Shivakanth Manjula B M Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaadeswaram India Department of Electronics & Communication Engg H. K. E. Society's S. L. N. College of Engineering Raichur India Department of Computer Science and Engineering Hyderabad Institute of Technology and Management Telangana India Department of Computer Science & Engineering K L University Vadeeshwaram Vijayawada India Department of Electronics and Communication Engineering Nitte Meenakshi Institute of Technology Bengaluru India

Social networking platforms, online news outlets, and weblog hosting services continue to expand, and with them come an increasing number of user-generated content contributions such product evaluations, comments on recent articles, and more. Products, movies, shopping sites, and review sites are common areas for customer feedback. The sheer volume and rate of growth of material that expresses opinions is becoming a burden on manufacturers who must manually categorise this data. Also, the perspective on entities at the level of aspects is expected by the public. It is for this reason that an automated sentiment analyzer must be built, one that can detect the bipolar and multipolar sentiment polarity of documents and/or aspects. People's ability to voice their opinions openly in public has greatly increased with the advent of various social networking apps. As a result, this helps to further the field of automated emotional analysis by providing a wealth of data on which to base analyses of people's feelings. User review categorization and analysis has emerged as an important part of sentiment analysis in recent years. Opinion mining is used to determine the degree of positivity or negativity in each user review posted on a social network. Numbers, star ratings, and descriptive text are the three polarity indications in a review. The sentiments of the public have been analysed using a wide variety of machine learning methods, but these methods often fall short in key areas such as classification accuracy, precision, recall, and F-measure due to pre-existing classification problems such as the two-class problem, overfitting, and parallel processing. The primary goal of the study is to create a fully automated system that can analyse a massive dataset of movie reviews using aspect-based SA or OM. We use natural language processing to tally up the good, bad, and ugly reviews. The research enhances advertising efforts and guides customers to the most suitable products. I

关键词： Sentiment analysis Sensitivity Social networking (online) Simulation User-generated content Stars Machine learning

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IoT-Driven Genomic Ecology: Exploring Genetic Adaptation in Changing Environments using CNN Model

IoT-Driven Genomic Ecology: Exploring Genetic Adaptation in ...

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Electrical, Electronics, Information and Communication technologies (ICEEICT), International Conference on

作者： Chitra Sabapathy Ranganathan Arshadh Ariff Mohamed Abuthahir Riazulhameed Santosh Kumar Sahoo V. Sumathi G. Sudhakar Anantha Raman Rathinam Mphasis Corporation Chennai Tamil Nadu India Blackstraw Technologies Pvt Ltd Chennai Tamil Nadu India Department of Engineering and Technology VIT University Bhopal Madhya Pradesh India Department of Mathematics Sri Sairam Engineering College Chennai Tamil Nadu India Department of Computer Science and Engineering Sri Sai Ranganathan Engineering College Coimbatore Tamil Nadu India Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vijayawada India

ISBN: (数字)9798350369083

ISBN: (纸本)9798350369090

The Internet of Things (IoT) technology and Convolutional Neural Networks (CNNs) catalyzes this investigation, which dives into the complex relationship between genomes and the surrounding environment. It monitors various environmental factors in real-time using a distributed network of Internet of Things sensors installed across various natural and urban locations. While doing this, this system collects genomic data from creatures that live in or interact with these habitats. This allows us to explore the intriguing dynamics of genetic adaptation in response to environmental changes. The research sheds light on the genetic factors responsible for an organism's capacity to flourish in constantly changing environments. The system can shed light on patterns of genetic mutations, disease prevalence, and variations in biodiversity by integrating environmental data collected from the Internet of Things with genomic information. These realizations contribute to our comprehension of the mechanisms that drive evolution; help create conservation plans for species at risk of extinction, inform disease epidemiology, and assist sustainable farming practices. The article "IoT-Driven Genomic Ecology" demonstrates a multidisciplinary approach to converging genomics, environmental science, and IoT technology. Its purpose is to shed light on the underlying principles that control life's adaptability to a world that is always changing.

关键词： Temperature sensors Genomics Water quality Sensors Internet of Things Convolutional neural networks Bioinformatics Environmental management Monitoring Diseases

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Innovations in Social Informatic: A Patent Landscape Review 7

Innovations in Social Informatic: A Patent Landscape Review

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7th Information Systems International Conference, ISICO 2023

作者： Afia, Nur Purnomo, Agung Maulana, Fairuz Iqbal Prasetyo, Yogi Tri Gumasing, Ma Janice J. Rosyidah, Elsa Persada, Satria Fadil Institute for Research and Community Services Universitas Nahdlatul Ulama Sidoarjo Sidoarjo61234 Indonesia English Language Education Universitas Nahdlatul Ulama Sidoarjo Sidoarjo61234 Indonesia Entrepreneurship Department BINUS Business School Undergraduate Program Bina Nusantara University Jakarta11480 Indonesia Computer Science Department Bina Nusantara University Jakarta11480 Indonesia School of Industrial Engineering and Engineering Management Mapúa University Manila1002 Philippines International Bachelor Program in Engineering Yuan Ze University Taoyuan32003 Taiwan

Patent intellectual property in social informatics with entrepreneurship support creates greater opportunities to improve human life. It has the potential to open enormous innovation opportunities in various fields, such as technology, health, services, and society. This research was conducted to review the patent landscape and the main trends of patents on social informatics in all countries. Researchers applied a patent landscape analysis using data on 487 patent documents over 16 years from the *** database. The study results show yearly patented development patterns related to social informatics. There is a royalty-free opportunity by using 15 patent discontinued. Patent related to social informatics was dominated by company ownership and inventors from the United States. The patent physics (G) section overwhelmed patents related to social informatics. There were 334 simple family patents on social informatics in nine jurisdictions;the United States was the highest. © 2023 The Authors. Published by Elsevier B.V.

关键词： Patents and inventions

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A Weather-Informed Traffic Forecasting System Constructed Using the SAE Method

A Weather-Informed Traffic Forecasting System Constructed Us...

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Communications and Information technologies (GCCIT), Global Conference on

作者： Vivek Deshpande V.J. Vijayalakshmi Siddharth Sriram S. Sathya Tusha Manita D Shah Department of Computer Engineering Vishwakarma Institute of Technology Pune Maharashtra India Department of Electrical and Electronics Engineering Karpagam Academy of Higher Education Coimbatore Centre of Research Impact and Outcome Chitkara University Rajpura Punjab India Department of Computer Science and Engineering Prince Shri Venkateshwara Padmavathy Engineering College Chennai Quantum University Research Center Quantum University Roorkee Uttarakhand India School of Management – Management JAIN (Deemed to be University) Bangalore Karnataka

ISBN: (数字)9798350388916

ISBN: (纸本)9798350388923

Access to accurate traffic data is critical for drivers to effectively plan routes and reduce congestion. Traffic patterns, including vehicle speeds and volumes, may be analysed with the use of monitors set up along roads. The vast majority of currently available traffic prediction systems make use of historical traffic data. But, there are two issues with people: (1) they just used traffic statistics to make forecasts, and (2) they didn't consider the volume of data or the time it would take to analyses it. Yet, the weather has a significant effect in predicting how busy the roads will be. In this research, we provide a WTPS, or weather-based traffic predictive model, which uses both traffic and weather information to make accurate predictions. The experimental findings demonstrate that WTPS beats the state-of-the-art methods in terms of prediction accuracy in both dry and wet conditions. In order to handle high volumes of traffic, WTPS was developed using big data concepts.

关键词： Accuracy Roads Urban areas Weather forecasting Traffic control Predictive models Prediction algorithms Forecasting Monitoring Vehicles

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