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An Approach of Fog Computing and Edge Computing for Computing Resources Optimization Strategies

An Approach of Fog Computing and Edge Computing for Computin...

引用

Pioneering Developments in computer science & Digital Technologies (IC2SDT), International Conference on

作者： Deepak Upadhyay Abhay Upadhyay Mridul Gupta Kunj Bihari Sharma Devansh Yadav Dept. of Computer Science and Engineering Graphic Era Hill University Dehradun India Dept. of Computer Science and Engineering Graphic Era deemed to be University Dehradun India Dept. of Electronics and Communication Engineering Graphic Era deemed to be University Dehradun India

ISBN: (数字)9798350365016

ISBN: (纸本)9798350365023

This paper investigates optimization strategies for fog and edge computing systems, focusing on the key challenges of resource allocation, load balancing, latency minimization, and power efficiency. We analyze the results of the simulation study to determine the impact and potential of our strategies and find that the improvements achieved are small to moderate, varying between 1.75% and 2.95%. This knowledge demonstrates that system optimization requires small, gradual increments and that fog and edge computing are dynamic systems. Our results suggest that optimization based on integration and adaptability can produce a significant difference in the performance and reliability of distributed systems.

关键词： System performance Focusing Minimization Load management Reliability Resource management Dynamical systems Distributed computing Optimization Edge computing

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Online Transit Entanglement Routing in Quantum Networks: Architecture Design and Optimization

Online Transit Entanglement Routing in Quantum Networks: Arc...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Wan-Ting Ho Shing-Yan Fang Wei-Chia Hsieh Li-Feng Cheni Jian-Jhih Kuo Ming-Jer Tsai Dept. of Computer Science National Tsing Hua University Hsinchu Taiwan Dept. of Computer Science and Information Engineering National Chung Cheng University Chiayi Taiwan

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

Quantum networks (QNs) gradually gain significant attention due to their higher security compared with classical networks. Conventional approaches in QN routing often aggregate multiple requests into a batch before determining their routing paths. However, this approach may overlook the limited lifetime of qubits, resulting in critical decoherence. In this paper, we present a new online entanglement routing architecture with an online optimization problem and propose a novel [1, O(log |V|)]-competitive algorithm supporting online requests with admission control, aiming to maximize the number of admitted requests. Finally, extensive simulation results show that our algorithm can outperform the existing approaches by up to 98%.

关键词： Simulation Data security Aggregates Qubit Decision making Focusing Routing Quantum networks Global communication Optimization

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Age and Gender Detection using Deep Learning 1

Age and Gender Detection using Deep Learning

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1st International Conference on Technological Innovations and Advance Computing, TIACOMP 2024

作者： Ansari, Mo Ateeb Singh, Vineeta Aeri, Manisha Chaudhary, Sumit Joshi, Kapil Anandaram, Harishchander Uttaranchal University Uttaranchal Institute of Technology Departement of Cse Dehradun India Department of Computer Science and Engineering Uttar Pradesh Kanpur Kalyanpur208024 India Graphic Era Hill University Graphic Era Deemed to Be University Dept. Computer Science and Engineering Dehradun India Amrita Vishwa Vidyapeetham Amrita School of Artificial Intelligance Coimbatore India

ISBN: (纸本)9798350392111

The goal of computer vision, a subfield of computer science is to give computers the ability to perceive recognize and process data in a manner similar to how humans see and process data. The process is analogous to teaching a computer to think and act like a person. Techniques for obtaining processing analysing and comprehending visual media are all a part of it. Not only is seeing important, but processing and providing actionable results from observations is of utmost importance. The proliferation of social media and platforms has increased the number of uses where age and gender categorization are important. Current methods performance on real-world images is still substantially inadequate when contrasted with the recently announced enormous gains in performance for the associated task of face recognition. Details on how to use Deep Learning Models and Transfer Learning to determine a person's age and gender are presented in this study. © 2024 IEEE.

关键词： Contrastive Learning

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Yoga Posture Image Classification Using Big Transfer(BiT)

Yoga Posture Image Classification Using Big Transfer(BiT)

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2024 IEEE International Conference on Computing, Applications and Systems, COMPAS 2024

作者： Rahman Fuad, K.M Nafiur Rozario, Uland Shoaib, Hashibul Ahsan Moushumi Khatun, Mst. Islam, Md Raisul Mridha, M.F. Shin, Jungpil Bangladesh University of Business and Technology Dept. of Computer Science and Engineering Dhaka Bangladesh Information Technology St. Francis College BrooklynNY11201 United States Western Illinois University IL United States American International University - Bangladesh Dhaka Bangladesh The University of Aizu School of Computer Science and Engineering Aizuwakamatsu Japan

ISBN: (纸本)9798331529765

Yoga, celebrated for its holistic well-being approach, has become widely popular, providing both physical and mental benefits. Integrating technology, particularly deep learning models for yoga posture classification, has introduced innovative avenues for improved learning experiences. This paper explores the application of the cutting-edge Big Transfer model to classify yoga posture images. BiT, recognized for its exceptional performance in visual recognition tasks, leverages pre-trained representations to achieve high accuracy, even with limited data. This study involves an extensive dataset encompassing diverse yoga postures and *** research uses fine-tuned BiT model on this dataset and rigorously evaluate its performance. The results underscore BiT's effectiveness in accurately identifying yoga postures, making it a valuable tool for automating posture assessment and providing real-time feedback during yoga sessions. Furthermore, the potential transformative applications of this technology in remote yoga instruction and telehealth is discussed. Automatic classification of yoga postures enhances personalized guidance and broadens access to yoga instruction. In conclusion, this paper presents a novel approach to yoga posture image classification using Big Transfer Model, with great results of 80.00% & 98.83% training accuracy & 69.14% & 95.69% validation accuracy in provided datasets *** has the potential to revolutionize how practitioners learn and instructors teach yoga in the digital age. This research bridges the gap between technology and tradition, enhancing the practice of this ancient art. © 2024 IEEE.

关键词： Image classification

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Cyber Complaint Automation System

Cyber Complaint Automation System

引用

Advanced Computing and Communication Technologies for High Performance Applications

作者： Anand V Prabhu MJ Jefiya Joel Denny Joseph Tisa Sunny Cerene Mariam Abraham Computer Science and Engineering dept. of Artificial Intelligence and Data Science

Due to the Internet's quick spread and the digitali-sation of commercial activity, cybercrime has risen dramatically. computers or data are the intended victim of cybercrime. This paper is about “Cyber Complaint Automation System”. The current cyber cell of Kerala police has a time comsuming approach. Complaint can be given in two ways. A written complaint can be given to cyber police station. Second option is to use cyber crime reporting portal. In this portal user has to undergo four different steps to sucessfully register the complaint. These complaints are stored in a database and manually classified into respective departments. This methodology of a cyber complaint takes a great deal of effort and time. The time wasted on current system helps the criminal in covering his track. As a result, the victim's time and money are squandered, and police receive criticism. We are working to create a software that will drastically shorten the time it takes to handle a complaint in an effort to remedy this scenario. Our system automates the classification process and prioritize emergency complaints. Thus helps the police to apprehend the criminal faster.

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Alpha-x Framework for Assessing Network Robustness in Nakagami-m Fading and Co-Channel Interference Environments

Alpha-x Framework for Assessing Network Robustness in Nakaga...

引用

Delhi Section Conference (DELCON), IEEE

作者： Deepak Upadhyay Karan Siwach Shiv Ashish Dhondiyal Abhay Upadhyay Mridul Gupta Kunj Bihari Sharma Dept. of Computer Science and Engineering Graphic Era Hill University Dehradun India Dept. of Computer Science and Engineering G.L. Bajaj Institute of Technology and Management Greater Noida India Dept. of Computer Science and Engineering Graphic Era deemed to be University Dehradun India Dept. of Electronics and Communication Engineering Graphic Era deemed to be University Dehradun India

ISBN: (数字)9798331518592

ISBN: (纸本)9798331518608

This article explores how the Alpha-x framework can improve network robustness under Nakagami-m fading and co-channel interference (CI), The study evaluates network performance using key metrics such as outage probability, spectral efficiency, and capacity degradation. The simulations show a 50% reduction in outage probability, a 20% boost in spectral efficiency, and a 33.3% lower capacity degradation compared to traditional models. These results demonstrate how the Alpha-x framework enhances network performance by adapting to various fading conditions and interference levels in wireless communication systems. The framework not only improves reliability and efficiency but also shows practical relevance in network planning and management. This can potentially lead to better user experiences and increased operational resilience. Future research could focus on optimizing the underlying algorithms and testing their performance on a larger scale in real-world environments. As telecommunications systems evolve, frameworks like Alpha-x could play a crucial role in ensuring reliable and efficient wireless networks.

关键词： Fading channels Degradation Adaptation models Spectral efficiency Probability Robustness Power system reliability Telecommunication network reliability Interchannel interference Capacity planning

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Advancements in Distributed Deep Learning: Federated Learning, AutoML Integration, and Beyond

Advancements in Distributed Deep Learning: Federated Learnin...

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Innovation and Novelty in engineering and Technology (INNOVA), International Conference on

作者： T. Kavitha Manikandan S P Bhimaraya Patil Anita Patil Dept. of Computer Science and Engineering New Horizon College of engineering Bangalore India School of Engineering & Technology(SoET) CMR University Bengaluru India Dept. of Computer Science Engineering New Horizon College of Engg Bangalore India Dept. of Information Science and Engg City Engineering College Bengaluru India

ISBN: (数字)9798331505134

ISBN: (纸本)9798331505141

This paper present advancements in distributed deep learning, focusing on federated learning, AutoML integration, and beyond. Leveraging the latest developments in machine learning (ML) and artificial intelligence (AI), our research explores novel approaches to enhance the efficiency, scalability, and security of distributed deep learning systems. This paper introduces federated learning techniques to enable collaborative model training across decentralized edge devices, thereby minimizing data privacy concerns and reducing communication over-head. Additionally, Proposed work investigate the integration of automated machine learning (AutoML) capabilities into distributed training pipelines, streamlining the model selection and hyperparameter tuning processes. Furthermore, Paper also explores cutting-edge advancements beyond traditional deep learning paradigms, such as generative adversarial networks (GANs) and reinforcement learning (RL), to unlock new opportunities in distributed AI. Through experimental evaluations and case studies, Paper demonstrate the effectiveness and potential impact of our proposed advancements, paving the way for future breakthroughs in distributed deep learning research.

关键词： Deep learning Training Technological innovation Federated learning Scalability Reinforcement learning Automated machine learning Generative adversarial networks Security Tuning

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Cyber-Physical Robustness Assessment of Stormwater Controls with Real-Time Mechanism for Smart and Sustainable Urban Water Resources Management

Cyber-Physical Robustness Assessment of Stormwater Controls ...

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World Environmental and Water Resources Congress 2022: Adaptive Planning and Design in an Age of Risk and Uncertainty

作者： Reddy Bathi, Prachotan Ellis, Riley Liang, Yu Bathi, Jejal Dept. of Computer Science and Engineering Manipal Institute of Technology Manipal India Dept. of Civil and Chemical Engineering Univ. of Tennessee At Chattanooga ChattanoogaTN United States

ISBN: (数字)9780784484258

ISBN: (纸本)9780784484258

Technological advancement has opened up new opportunities for smart water networks (SWNs), including real-time management of stormwater runoff such as Open Storm, an open-source end-to-end platform for real-time monitoring and controlling stormwater. With the increasing popularity of SWNs, they also become increasingly complex with a wide range of components. Such complexity leads to inadvertent points of compromise in terms of both cyber and physical safety. We assessed the robustness of the Open Storm framework for an upgrade to stormwater controls with real-time mechanisms for the management of innovative and sustainable urban water resources. Based on the components in our planning project and the literature review, we identified various points of failure ranging over four layers of the cyber-physical system (CPS). In addition, we investigated the levels of risk and possible workarounds comprehensively to help researchers and developers strengthen future smart water projects in urban ecosystems. © ASCE.

关键词： Storms

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Securing Against Deception: Exploring Phishing Emails Through ChatGPT and Sentiment Analysis 22

Securing Against Deception: Exploring Phishing Emails Throug...

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22nd IEEE/ACIS International Conference on Software engineering Research, Management and Applications, SERA 2024

作者： Sayyafzadeh, Shahrzad Weatherspoon, Mark Yan, Jie Chi, Hongmei Florida A and M University Dept. of Comp. & Info Sciences TallahasseeFL32307-5100 United States FAMU-FSU College of Engineering TallahasseeFL32301 United States Bowie State University Dept. of Computer Science BowieMD United States

ISBN: (纸本)9798350391343

The origin of large language models (LLMs) has left an indelible mark on various domains, most notably in natural language processing and artificial intelligence. While extensive research has delved into LLMs like ChatGPT 4 for tasks such as code generation and text synthesis, their application in identifying malicious web content, particularly phishing web sites, still needs to be explored. To confront the growing wave of automated cyber threats facilitated by LLMs, automating the detection of malicious email content. This paper investigates the utilization of Natural Language Processing (NLP) techniques, including VADER (valence aware dictionary and sentiment Reasoner) sentiment analysis and Large Language Models (LLMs) to strengthen the detection of phishing emails, offering enhanced defense mechanisms against cyber threats by analyzing the diverse attributes of phishing emails, including sender details, URLs, textual content, and linguistic characteristics. In this study, we leverage the power of ChatGPT's 4 state-of-the-art language models and employ Natural Language Processing (NLP) techniques. We develop an intelligent system that identifies and flags potential phishing attempts in spam emails and URLs. Our experiments using GPT-4 on our dataset demonstrated promising results, achieving an accuracy of 92%. These findings underscore LLMs' potential, including VADER sentiment analysis, to detect rapidly and accurately phishing emails, safeguarding cybersecurity challenges and protecting users from online fraud and phishing attempts. © 2024 IEEE.

关键词： Phishing

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Beyond the Blink: IoT's Next-Gen Drowsiness Detection System for Drivers

Beyond the Blink: IoT's Next-Gen Drowsiness Detection System...

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Industrial Electronics: Developments & Applications (ICIDeA), IEEE International Conference on-

作者： Sidheswar Routray Nachiket Patel Dhruv Patel Jyoti Srivastava Rudra Narayan Dash Dept. of Computer Science & Engg. Pandit Deendayal Energy University Gandhinagar India Dept. of Computer Science & Engg. Indrashil University Mehsana India Dept. of Computer Engineering Ganpat University Mehsana India School of Electrical Engineering KIIT University Bhubaneswar India

ISBN: (数字)9798331533205

ISBN: (纸本)9798331533212

Drowsiness during driving includes high risks for the driver, the co-passengers, and the other people on the road. Advance Driver Assistance Systems (ADAS) have been proposed to reduce these risks. This work introduces a new Internet of Things (IoT) seizure detection system to improve driver safety using Raspberry Pi, which is equipped with various sensors and utilizes machine learning for real-time monitoring and analysis. Using sensor fusion technology, including monitoring yawning and eye-closing patterns, the system aims to detect early signs of driver sleepiness. Being a low-cost, versatile, and tiny device, it becomes an ideal core processor for integration into an in-car environment. Additionally, the simplicity enables seamless communication with various sensors and facilitates effective data collection. Extensive tests and simulations were conducted to evaluate the effectiveness and reliability of the proposed system for real-world driving situations. The result outcomes prove the system's accuracy and efficiency in detecting early signs of driver fatigue to enhance driver safety. The integration of Raspberry Pi and sensor fusion technology makes it economical as well as scalable approaches supporting multiple platforms.

关键词： Sleep Roads Sensor fusion Sensor systems Real-time systems Sensors Safety Internet of Things Reliability Vehicles

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