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Research of Low-Carbon computing Network in Integrated Satellite-Ground System

Research of Low-Carbon Computing Network in Integrated Satel...

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IEEE international conference on Software Engineering and Service Sciences (ICSESS)

作者： Rui Huang Jiakang Xu Haitao Xu Liang Li China Telecom Corporation Limited Beijing China Beijing Spaceiot Technology Development Co. LTD. Beijing China University of Science and Technology Beijing Beijing China

In this paper, research on low-carbon computing networks in integrated satellite-ground systems is given. We have reviewed the research works in the satellite-earth convergence network and multi-access edge computing technology in the integrated satellite-earth convergence network. The development trends are also given for edge computing in the integrated satellite-ground system. Key technologies are deeply researched and Future research directions are discussed in detail.

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Adding Common Sense to Robots by Completing the Incomplete Natural Language Instructions 7

Adding Common Sense to Robots by Completing the Incomplete N...

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7th IEEE international conference for convergence in technology, I2CT 2022

作者： De Silva, G.W.M.H.P. Rajapaksha, Samantha Jayawardena, Chandimal Sri Lanka Institute of Information Technology Faculty of Graduate Studies and Research Sri Lanka Sri Lanka Institute of Information Technology Faculty of Computing Sri Lanka

ISBN: (纸本)9781665421683

This system is developed to identify and complete the human's instructions or incomplete sentences given by a user as a command. It would facilitate the interaction between the human and mobile service robots. However, when humans give the instruction, there can be incompleteness or else missing the information related to the environment. That is because humans, generally based on common sense, depending on the environment. Then the human brain can complete all those incomplete sentences by using common sense knowledge. This paper itself introduced a model of a service robot who can compete with the given incomplete instructions, display the related sentences or words, and finally move to the related objects in the environment. First, it will consider and identify the objects in the environment and then consider the given natural language instruction by humans. As a first step of the approach, complete the incomplete sentences. Those sentences are coming as natural language instructions. By parsing it into as the frame can identify the related words by using the created model or can call as language model and here used some identify words from the human common sense also, then the service robot will learn about the commonsense knowledge automatically from the parsing sentences as a speaker. Considering all the parsing sentences, it calculates and measures the accuracy of this service robot model. Simply this is a commonsense reasoning model. The result of the provided solution can enable the robot model that works in a ROS environment to identify and automatically perform the tasks. © 2022 IEEE.

关键词： Mobile robots

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Healthy Heart - Heart Risk Prediction System on Personalized Guidance for Heart Patients 7

Healthy Heart - Heart Risk Prediction System on Personalized...

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7th IEEE international conference for convergence in technology, I2CT 2022

作者： Bandara, K.R.C. Dureksha, D.D.T.D. Pinidiya, S.C Amarasinghe, R.M.G.H. Thelijjagoda, Samantha Kishara, Jenny Sri Lanka Institute of Information Technology Faculty of Computing Sri Lanka Sri Lanka Institute of Information Technology Faculty of Business Sri Lanka

ISBN: (纸本)9781665421683

Human heart is the principal part of the human body. Change in human lifestyle, work related stress and unhealthy food habits contribute to the increase in rate of numerous heart related diseases. In accordance with several research, various heart diseases have been the key reason for deaths in Sri Lanka. According to the 2018 records, stroke affected 31%, coronary heart disease affected 23%, and ischemic heart disease affected 14%. Therefore, there is a need for an automated system which will enhance medical efficiency and to identify such diseases in time for proper treatment. The proposed system takes physical and medical datasets of heart patients as manual input parameters and predicts the patient's risk of having a heart disease. Prediction process grants the patient a risk level according to the heart condition and proposes a personalized daily guidance for the patient to avoid risks associated with, along with a meal planner, exercise scheduler and a stress releaser as well as alert the patient well in advance. The system will present an efficient technique of predicting heart diseases using machine learning approaches to analyze huge complex medical data. Some of the used algorithms are Random Forest, Logistic regression, Decision tree classifier etc... The research mainly aims to prevent the escalation of heart diseases in patients and lead them to a healthy lifestyle. © 2022 IEEE.

关键词： Heart

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Resource-Adaptive Newton’s Method for Distributed Learning 29th

Resource-Adaptive Newton’s Method for Distributed Learning

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29th international computing and Combinatorics conference, COCOON 2023

作者： Chen, Shuzhen Yuan, Yuan Tao, Youming Cai, Zhipeng Yu, Dongxiao School of Computer Science and Technology Shandong University Qingdao266237 China Shandong University Jinan250100 China Department of Computer Science Georgia State University AtlantaGA30303 United States

ISBN: (纸本)9783031491894

By leveraging curvature information for improved performance, Newton’s method offers significant advantages over first-order methods for distributed learning problems. However, the practical applicability of Newton’s method is hindered in large-scale and heterogeneous learning environments due to challenges such as high computation and communication costs associated with the Hessian matrix, sub-model diversity, staleness in training, and data heterogeneity. To address these challenges, this paper introduces a novel and efficient algorithm called Resource-Adaptive Newton Learning (RANL), which overcomes the limitations of Newton’s method by employing a simple Hessian initialization and adaptive assignments of training regions. The algorithm demonstrates impressive convergence properties, which are rigorously analyzed under standard assumptions in stochastic optimization. The theoretical analysis establishes that RANL achieves a linear convergence rate while effectively adapting to available resources and maintaining high efficiency. Moreover, RANL exhibits remarkable independence from the condition number of the problem and eliminates the need for complex parameter tuning. These advantages make RANL a promising approach for distributed learning in practical scenarios. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Optimization

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Optimizing Network Routing: Performance Analysis of OSPF in FABRIC Testbed

Optimizing Network Routing: Performance Analysis of OSPF in ...

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Advancements in Electrical, Electronics, Communication, computing and Automation (ICAECA), international conference on

作者： Cynthia Jayapal Pranava Yohita P Shifana Shirin Shreeja D K Computer Science Engineering Kumaraguru College of Technology Coimbatore India

ISBN: (数字)9798331525439

ISBN: (纸本)9798331525446

Networking research needs testbeds that are flexible, fast, and efficient. FABRIC is a modern platform built for advanced experiments, offering better customization and performance. This paper compares FABRIC and GENI, focusing on how well they handle routing protocols, especially Open Shortest Path First (OSPF), a widely used method for finding the best network paths. The study looks at control overhead, which is the extra data used for routing, and convergence time, which shows how quickly the network adapts to changes. By testing OSPF on FABRIC, we see how it compares to GENI in handling network updates. The results show that FABRIC lowers overhead and speeds up convergence, making it a better choice for research and real-world use. Its flexible design also makes it future-ready, supporting faster and more efficient networking in evolving systems. FABRIC’s ability to adapt to changing network conditions makes it a reliable choice for future innovations.

关键词： Technological innovation Scalability Routing Fabrics Routing protocols Telecommunication computing Virtualization Software defined networking convergence Testing

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Occupational Health Service Platform Architecture based on IoT and Edge computing

Occupational Health Service Platform Architecture based on I...

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international conference on Information and Communication technology convergence (ICTC)

作者： Kyoungjae Sun Sung Hei Kim Hyungho Do ICT Convergence Standards Research Section ETRI Daejeon Korea Rep. of HealthAll Daegu Korea Rep. of

This paper proposes an occupational health service platform architecture based on Internet of Things (IoT) and edge computing. In the proposed architecture, various types of IoT devices are used to collect workers' health status and occupational environment status. The functionalities defined in the platform running in a distributed way between the edge and core clouds are tailored to the characteristics of the workers' physical and mental healthcare system, as well as features for the improvement of the occupation environment. With the proposed idea, it enables to provide comprehensive capabilities for industrial health services, including worker health management, occupational environment enhancement, and human resource management.

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EfficientNet-V2-B3 Transfer Learning for High-Accuracy Indian Bird Species Classification 15

EfficientNet-V2-B3 Transfer Learning for High-Accuracy India...

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15th international conference on computing Communication and Networking Technologies, ICCCNT 2024

作者： Pillai, Rudresh Sharma, Neha Upadhyay, Deepak Devliyal, Swati Kaur, Gurjot Chitkara University Institute of Engineering & Technology Chitkara University Punjab India Graphic Era Hill University Computer Science & Engineering Uttarakhand Dehradun India Graphic Era Deemed to be University Computer Science &engineering Uttarakhand Dehradun India

ISBN: (纸本)9798350370249

This research paper presents a study on classifying images of Indian birds into 25 different types using the EfficientNet-V2-B3 transfer learning model. The research focuses on using deep learning techniques to accurately classify images of Indian birds, which is important for many ecological and conservation efforts. The ' Indian-Birds-Species-Image-Classification' dataset, which contains 37,500 descriptive images of 25 Indian birds, was used in the study. To train and evaluate the model, the data was split into training, validation, and testing sets. The EfficientNet-V2-B3 model was chosen for its efficiency and effectiveness in image classification, especially through transfer learning. During training, the model was trained on 24,000 images in training set and their weights were adjusted to learn the unique characteristics of Indian birds. The validation set contained 6000 images and was used to monitor the performance of the model and prevent overfitting. The pre-trained EfficientNetB3 model was adjusted throughout the training phase using stochastic gradient descent and backpropagation. Measurements like accuracy and loss were monitored throughout several epochs during the training and validation phases to get insight into the model's convergence. A confusion matrix, which provides a thorough perspective of classification accuracy and misclassifications across species, was used to examine the model's performance. The confusion matrix created from the test results provides information on performance standards for each bird species, including several performance metrics. In test phase, the model classified images of Indian birds by species with 97% accuracy. This result highlights the effectiveness of the transfer learning methodology and the EfficientNet-V2-B3 architecture's adaptability for challenging classification problems. The implications for ornithology and biodiversity preservation are profound since this automated technique streamlines the procedures f

关键词： Deep Learning EfficientNet-V2-B3 Fine-Tuning Indian Birds Species Classification Ornithology Transfer Learning

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Research on computing and Network convergence Resource Allocation Based on Stackelberg Game for New Power System

Research on Computing and Network Convergence Resource Alloc...

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IEEE Joint international Information technology and Artificial Intelligence conference (ITAIC)

作者： Zhongping Xu Linghua Miao Changyu Du Yuanyuan Qi Xianzhou Meng Beijing FibrLink Communications Co. Ltd. Beijing China School of Computer Science Beijing University of Posts and Telecommunications Beijing China

With the development of new power system and computing and network convergence technology, the number of intelligent power communication devices is increasing exponentially. On the one hand, the upgrading of microprocessor technology has provided the possibility for devices to handle high energy consumption and fast response applications. On the other hand, the maturity of Device to Device (D2D) technology provides computing and network convergence support for the implementation of short distance, low latency, and low energy data transmission. This article studies on adjusting the price of computing resources for service-oriented users in new power system, while using KM algorithm to match SU and RU, to achieve effective computing resource allocation and improve user experience. Considering that idle devices require energy consumption to provide computing services for RU devices, in order to ensure the efficiency of SU, it is necessary to charge for computing resources and optimize the price of computing resources based on Stackelberg game to improve the efficiency of SU. And we optimize user unloading direction based on KM algorithm at a given price. Simulations show that the proposed strategy has high efficiency of computing resource allocation for new power system.

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Enhancement of Network Security in MANET Using Refined Adaptive Harris Hawks Optimization Algorithm (RAHHO) for IoT Applications 6

Enhancement of Network Security in MANET Using Refined Adapt...

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6th IEEE international conference on Emerging Smart computing and Informatics, ESCI 2024

作者： Satyanarayana, P. Sofi, Umar Bashir Ahmed, Bisma Farooq Naga Saranya, N. Padma Rao, G.V.S. Gokula Krishnan, V. V. R. Siddhartha Engineering College Department of ECE AP Vijayawada India Punjab Technical University Department of CSE Punjab India Sathyabama Institute of Science and Technology Department of Biomedical Engineering Tamil Nadu Chennai India Meenakshi College of Engineering Department of MCA Tamil Nadu Chennai India S.R.K.R. Engineering College Department of ECE AP Bhimavaram India Department of CSE Saveetha School of Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350306613

The proliferation of Internet of Things (IoT) devices in Mobile Ad-Hoc Networks (MANETs) has introduced complex security challenges, demanding innovative solutions to safeguard data integrity and network functionality. This paper proposes a novel approach, the Refined Adaptive Harris Hawks Optimization Algorithm (RAHHO), tailored to fortify network security within MANETs for IoT applications. The RAHHO method integrates the efficient search capabilities of the Harris Hawks Optimization (HHO) algorithm with a dynamic updating mechanism, enhancing convergence speed and accuracy in optimizing security parameters. Leveraging the adaptability of HHO, RAHHO dynamically adjusts hawk positions and updates search strategies, enabling robust exploration of security parameter spaces crucial for MANETs. Moreover, the application of RAHHO in MANETs offers a multifaceted enhancement of security measures. The outcomes reveal varying degrees of susceptibility to attacks, with HHO displaying the highest vulnerability, followed by CHHSO and MU-HHO. RAHHO emerges as notably more resilient, being 73.33% less vulnerable than HHO, 40.5% less vulnerable than CHHSO, and 20% less vulnerable than MU-HHO. Simulation results demonstrate the efficacy of RAHHO in reinforcing network security, showcasing notable improvements in network performance metric such as cost function. The results establish RAHHO as the most secure algorithm in this specific context, showcasing superior performance. The progressive decrease in vulnerability from HHO to RAHHO corresponds to an increase in overall security. © 2024 IEEE.

关键词： CHHSO HHO IoT MANET MU-HHO Network security RAHHO

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A hybrid architecture for resolving Cryptographic issues in internet of things (IoT), Employing Quantum computing supremacy 12

A hybrid architecture for resolving Cryptographic issues in ...

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12th international conference on ICT convergence (ICTC) - Beyond the Pandemic Era with ICT convergence Innovation

作者： Shamshad, Shuhab Riaz, Farina Riaz, Rabia Rizvi, Sanam Shahla Abdulla, Shahab Univ Azad Jammu & Kashmir Fac Sci Dept Comp Sci & Informat Technol CS & IT Muzaffarabad Pakistan Univ Southern Queensland Toowoomba Qld Australia Commonwealth Sci & Ind Res Org CSIRO Data 61 Sydney NSW Australia Raptor Interact Pty Ltd Eco BlvdWitch Hazel Ave ZA-0157 Centurion South Africa English USQ Coll K336Toowoomba Campus Toowoomba Qld Australia

ISBN: (纸本)9781665423830

The Internet of Things (IoT) is shaping the world of every economy and client. By 2023, clients, companies, and governments will be able to install a total of 40 billion IoT devices worldwide. The 2021's challenges simply confirmed the necessity to secure all four elements of the IoT Model: Sensors, Networks, Cloud, and Applications. Therefore, it is important to be pragmatic regarding the extreme threats and high worth of attacks on secrecy in IoT systems. Although the concept of convergence of IoT and Quantum computing is not a standby topic, it had been mentioned in several works of literature and coated by many researchers, however, nothing is getting ready for sensible applications thus far. Quantum computing is not prepared nevertheless, it is so far from preparation on a billboard scale. Quantum computing resolves most of the issues in IoT however it occurs yet below the analysis phase and can take over a couple of years to induce in public obtainable use. During this research, the author will start through a broad introduction to the internet of things and Quantum computing and carry on with issues that can be featured throughout the convergence of Quantum computing and IoT. To solve these integration issues in terms of cryptography this research will also provide the answer. At long last, this research will call attention to the hybrid of both fields to existing IoT network design.

关键词： Internet of Things (IoT) Quantum computing Cryptography Quantum computing Supremacy Quantum Communication

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