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8th international conference on Electronic information technology and Computer Engineering, EITCE 2024

作者： Huang, Chao Wang, Xiaogang Yang, Zhihe Xiao, Dun School of Electronic and Information Shanghai Dianji University Shanghai China

ISBN: (纸本)9798400710094

In modern cloud computing environments, accurate prediction of resource demand is critical to optimize resource allocation and reduce costs. Existing methods are often inadequate in dealing with variable workloads. In this research, we introduce an innovative combined multiple machine learning prediction approach to enhance prediction accuracy and stability. First, a comprehensive dataset is built by segmenting historical resource utilization and extracting feature vectors using dynamic variable windows. The variable window automatically adjusts its size according to the volatility, thus saving resources. Second, a number of different algorithms are used for forecasting, and the optimal method is selected to capture resource utilisation patterns and improve forecasting accuracy. Finally, the system calls the optimal algorithm from the adaptive selector for prediction based on the feature vectors. The experimental results show that the method performs well under various workloads and scenarios and significantly outperforms the traditional method, providing a theoretical basis and practical guidance for improving the efficiency and performance of cloud computing resource management. © 2024 Copyright held by the owner/author(s).

关键词： Cloud platforms

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Building a safe and secure metaverse 2nd

Building a safe and secure metaverse

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2nd international conference on Next-Generation computing and information Systems, ICNGCIS 2023

作者： Gupta, Ankur Model Institute of Engineering and Technology Jammu India

ISBN: (纸本)9781032738659

The metaverse is an exciting domain representing an amalgamation of advances in computing and communications along with immersive technologies (AR/VR/XR). It is therefore intuitive for large corporations, research organizations and businesses cutting across industry verticals to adopt a metaverse-centric approach and explore diverse use-cases catering to business/individual needs. However, the transition from traditional applications to metaverse-native applications is not expected to be seamless. Privacy, safety and security concerns exist in the early versions of the metaverse with several flaws endangering individual user safety being highlighted. Plus, there is increased scrutiny on the illeffects of social media, gaming and immersive environments by Governments and regulatory agencies. Thus, it is increasingly clear that the final iteration of the metaverse will need to address the concerns of individual users while navigating a complex legal and regulatory landscape. This keynote examines the different aspects and challenges which the future metaverse will need to address. A set of "first principles" are put forth towards building an inclusive, safe and secure metaverse. © 2025 The Author(s).

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Deep learning based multiple regression analysis approach for designing medical image recognition system 2nd

Deep learning based multiple regression analysis approach fo...

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2nd international conference on Next-Generation computing and information Systems, ICNGCIS 2023

作者： Singh, Shweta Jagadish, A.N. Vyas, Bhuman Wasim Bhatt, Mohammed Sameen, Aws Zuhair Degadwala, Sheshang Electronics and Communication Department IES College of Technology Bhopal India Department of Computer Science Bapuji Institute of Engineering and Technology Karnataka Davanagere India Credit Acceptance Canton United States Model Institute of Engineering and Technology J&K Jammu India College of Medical Techniques Al-Farahidi University Baghdad Iraq Department of Computer Engineering Sigma University Gujarat Vadodara India

ISBN: (纸本)9781032738659

Machine learning models are optimization models that make it possible to gather data, evaluate it, and provide the experts and management with the reports they need to make the best decisions. This study uses quantitative research, as it seeks to gather information and analyse it with statistical models such as regression analysis and analysis of variance. Researchers want to use statistical techniques such as descriptive analysis, regression analysis, and ANOVA (analysis of variance) to analyse the hypothesis. The purposive sample technique is used by the authors to choose respondents who work in the healthcare sector. A non-probability sampling technique called purpose sampling is used. The R squared value is 0.744, or 74.4 percent, according to the analysis. According to the investigation, there is a strong correlation between improved picture quality and ML-based techniques in digital image recognition. © 2025 The Author(s).

关键词： Regression analysis

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Identification and Classification of Medicinal Plants using Machine Learning Algorithms 3

Identification and Classification of Medicinal Plants using ...

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3rd international conference on Electronics and Renewable Systems, ICEARS 2025

作者： Bhargavi, G. Jayaraman, Venkatesh Jabez, J. Deepa, R. Surendran, R. Srm Institute of Science and Technology Department of Computing Technologies Chennai India Chennai Institute of Technology Department of Computer Science and Engineering Chennai600069 India Sathyabama Institute of Science and Technology School of Computing Department of Computer Science and Engineering Chennai India Srm Institute of Science and Technology School of Computing Department of Computing Technologies Kattankulathur Tamilnadu Chennai603203 India Saveetha Institute of Medical and Technical Sciences Saveetha School of Engineering Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798331509675

The increaing significance of plant life and botanical expertise extends beyond mere visual appreciation. With the growing interest in sustainable living and alternative remedies, there is a pressing demand for easily accessible and credible information on plant categorization, particularly focusing on medicinal plants. This innovative project synergizes machine learning capabilities, botanical proficiency, and user-friendly technology to give users the insights required to harness the benefits of medicinal plants responsibly and sustainably. The platform facilitates precise categorization and a comprehensive understanding of the therapeutic attributes of plants. © 2025 IEEE.

关键词： Medicinal chemistry

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A computing Power Method Based on EVPN-VXLAN Extension in Data Center Networks 24

A Computing Power Method Based on EVPN-VXLAN Extension in Da...

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5th international conference on Computer Science and Management technology, ICCSMT 2024

作者： Wu, Nan Dong, Guozhen Xing, Wenjuan Ji, Siwei Zhang, Yue China Telecom Corporation Limited Research Institute Beijing China

ISBN: (纸本)9798400709999

Data center networks need to deliver various cloud services to large number of users, necessitating efficient and flexible management of network resources. However, the widely utilized EVPN-VXLAN (Ethernet Virtual Private Network - Virtual Extensible Local Area Network) technology for network virtualization currently lacks support for computing power resource scheduling within the overlay network. While computing power services can conserve network bandwidth and reduce latency for high-demand applications, they encounter challenges related to end-to-end delivery, path selection, and resource allocation in the EVPN-VXLAN data center *** paper proposes a novel computing power scheduling method based on EVPN-VXLAN that defines a new EVPN routing type to facilitate the delivery of multi-resource information, which is then utilized for computing power routing selection and forwarding. The proposed method enhances the performance and efficiency of computing power services within the data center EVPN-VXLAN network at the overlay layer while maintaining compatibility with existing EVPN-VXLAN technology. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Resource allocation

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A Novel Hybrid Approach-Based on Heartbeat and Accelerometer Signals for Enhanced Security in WBSNs

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IEEE Sensors Journal 2025年第6期25卷 10295-10308页

作者： Yan, Guixiang Zhang, Guanghe Liu, Fanghua Williams Samuel, Oluwarotimi Aborokbah, Majed Guo, Jiquan Zhu, Liqing Wei, Sikang Jiangxi Normal University School of Computer and Information Engineering Nanchang330022 China University of Derby School of Computing and Data Science Research Centre DerbyDE22 3AW United Kingdom INTI International University Faculty of Data Science and Information Technology Nilai71800 Malaysia University of Tabuk Faculty of Computers and Information Technology Tabuk71491 Saudi Arabia Jiangxi Normal University School of Digital Industry Shangrao334000 China

In wireless body sensor networks (WBSNs), ensuring secure and efficient key distribution is critical, particularly given the limited computational and energy resources of the sensors. Existing methods often struggle to balance security with these resource constraints, especially in environments involving physiological data such as acceleration (ACC) and electrocardiogram (ECG) signals. For the first time, this study proposes a novel hybrid approach that integrates fuzzy commitment with ACC signal noise and ECG features for efficient key generation and distribution in WBSNs. By employing a low-pass filter to process ACC signal noise, we generated highly random binary sequences (BSs), leveraging the inherent randomness of the signal for secure key generation. Concurrently, an optimized coding scheme was built for ECG feature construction to ensure secure key distribution between devices. Extensive experiments, including entropy analysis and National Institute of Standards and technology (NIST) statistical tests, confirm the robustness and security of our method. The proposed scheme achieves a false acceptance rate (FAR) of 5.23%, demonstrating superior performance across multiple databases in comparison to benchmark approaches. This novel dual-key generation strategy that combines the unpredictability of ACC noise with the individual-specific traits of ECG signals can significantly enhance the security, applicability, and versatility of WBSNs. © 2001-2012 IEEE.

关键词： Acceptance tests

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Adoption of Blockchain technology in Digital Knowledge to Increase Transparency in Transactions using Library Resources 6

Adoption of Blockchain Technology in Digital Knowledge to In...

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6th international conference on Mobile computing and Sustainable Informatics, ICMCSI 2025

作者： Inayatulloh Information Systems Department School of Information system Bina Nusantara University Jakarta11480 Indonesia

ISBN: (数字)9798331522667

ISBN: (纸本)9798331522667

Digital libraries are an important part of educational institutions because of their function as a medium for increasing knowledge. Digital libraries also serve as a liaison between publishers and library users, such as students and researchers. Researchers conducting certain types of research require the use of original references. The use of fake references in research can lead to research products that breach both the code of ethics and the law. Currently, the digital library system only stores information on publishers, users, and types of library resources. The digital library system does not have the capability to provide information to publishers, students, or researchers who utilize its products, which means it cannot prevent researchers from using fake references. Thus, the purpose of this research is to build a blockchain technology adoption model in digital libraries that can monitor the use of library resources. The research employs a qualitative approach, utilizing a literature review, to examine the phenomenon of library resource use and the issue of using fake references in research. The study also employs a literature review to explore the application of blockchain technology in digital libraries. The research output is a blockchain technology adoption model for digital libraries and simulations with the Hyperledger framework. © 2025 IEEE.

关键词： Blockchain

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Healthcare CAD model for hierarchical processing of surgical navigation system 2nd

Healthcare CAD model for hierarchical processing of surgical...

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2nd international conference on Next-Generation computing and information Systems, ICNGCIS 2023

作者： Maiti, Niladri Maurya, Arun Kumar Manerkar, Shri Ganesh V. Shabaz, Mohammad Degadwala, Sheshang Varma, Raj A. School of Dentistry Central Asian University Tashkent Uzbekistan Bit College of Pharmacy Dehradun India Department of Information Technology Goa College of Engineering Goa. South Goa Farmagudi Ponda India Model Institute of Engineering and Technology J&K Jammu India Department of Computer Engineering Sigma University Gujarat Vadodara India Vimannagar Maharashtra Pune India

ISBN: (纸本)9781032738659

To avoid the "feeling out of control" caused by the redundant information of the human-computer interface to the doctor, based on the cognitive model of the doctor during the operation, the human-machine interaction criterion in the augmented reality surgical navigation system is proposed. Aiming at the multi-sensory information fusion problem of AR navigation interface, a human-computer interaction paradigm based on eGOMS model is proposed. To objectively evaluate the human-computer interaction usability of the AR navigation system, the analytic hierarchy process was used to construct the human-computer interaction usability evaluation index system, and the fuzzy theory was used to comprehensively assess the human-computer interaction usability of the AR navigation system. The evaluation result of the system is good, and it can be applied in practice. © 2025 The Author(s).

关键词： Navigation systems

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Analyzing the Effects of coding and Compression on Network Performance 5th

Analyzing the Effects of Coding and Compression on Network P...

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5th international conference on Data Science, Machine Learning and Applications, ICDSMLA 2023

作者： Agarwal, Ankita Kumar, Deepak Singh, Alka Preethi, D. Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Department of Mathematics Vivekananda Global University Jaipur India Department of Master of Computer Application Noida Institute of Engineering and Technology Uttar Pradesh Greater Noida India Karnataka Bengaluru India

ISBN: (纸本)9789819780426

This paper objectives to research the consequences of coding and compression on network performance. Network coding is the technique of encoding information before it is despatched over a network and has become an outstanding method to enhance community overall performance. Compression then again is used to reduce the size of the data before transmission, ensuing in quicker transmission time. This observe evaluates the effect those techniques have on network overall performance by measuring the bandwidth utilization, throughput, latency, and packet losses. A test becomes conducted to have a look at how the strategies have an effect on one of kind mixtures of information speeds, packet sizes, and facts loading. Results display that both strategies had a fine impact at the community overall performance, with network coding and compression having an extra effect on networks with higher facts hundreds. Moreover, the effects show that community coding had a greater impact on networks with larger packets, while compression had a more effect on networks with smaller packets. This studies gives insight into how community coding and compression can be used to enhance network overall performance. coding and compression are important components of network performance that have been studied and tested to have a full-size influence on network pace, scalability, and reliability. coding is used to reduce the amount of data that is sent over a community, by way of reducing the quantity of records frames that need to be sent and growing the performance of the records transfer technique. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Network coding

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Optimized deep learning models based-sentiment analysis approach for identifying healthcare rumors over social media 2nd

Optimized deep learning models based-sentiment analysis appr...

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2nd international conference on Next-Generation computing and information Systems, ICNGCIS 2023

作者： Kumar, Pramod Vashishtha, Ela Alghayadh, Faisal Yousef Wasim Bhatt, Mohammed Bala, Suchitra Sreejitha, T.S. Computer Science and Technology Ganga Institute of Technology and Management Haryana Kablana Jhajjar India Lead Analytics Texas Health Resources TX United States Computer Science and Information Systems Department College of Applied Sciences AlMaarefa University Riyadh Saudi Arabia Model Institute of Engineering and Technology J&K Jammu India ICT & Cognitive Systems Sri Krishna Arts and Science College India St. Marys College Thrissur India

ISBN: (纸本)9781032738659

Research the mechanism of fake news refuting rumors in the real social network environment. Propose methods to evaluate the effect of rumor refuting and explore the factors that affect the impact of rumor refuting. Based on the current research results and assumptions, eight factors that affect the effect of rumor refuting are summed up, such as the proportion of the original fake news content. Experiments were conducted based on the rumor-refuting Weibo data. The experimental analysis showed that the proportion of the original fake news in the rumor-refuting information was negatively correlated with the rumor-refuting effect, and the explanation was positively correlated with the rumor-refuting effect suggestions for refuting rumors, including explaining why the original fake news is wrong to guiding social network fake news denying rumors. © 2025 The Author(s).

关键词： Sentiment analysis

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