检索结果-内蒙古大学图书馆

Optimized Data Storage Algorithm of IoT Based on Cloud Computing in Distributed System

Optimized Data Storage Algorithm of IoT Based on Cloud Compu...

2024 OPJU International Technology Conference on Smart Computing for Innovation and Advancement in Industry 4.0, OTCON 2024

作者： Deepthi, K.Jaya Balakrishnan, T.Suresh Krishnan, Prabhakar Ebenezar, U.Samson Nageshwari Mohan Babu University Department of Aiml AP Tirupati India Saveetha Institute of Medical and Technical Sciences Saveetha University Saveetha School of Engineering Department of Computer Science and Engineering Chennai India Amrita Vishwa Vidyapeetham Center for Cyber Security Systems and Networks Amritapuri-campus India Saveetha Institute of Medical and Technical Sciences Saveetha University Saveetha School of Engineering Department of Computer Science and Engineering Tamil Nadu Chennai India Care College of Engineering Department of Computer Science and Engineering Tamil Nadu Trichy620009 India

ISBN: (纸本)9798350373783

IoT and cloud technology are vital for large systems. An improved data storage technique for IoT applications and cloud distribution is described in this research. Scalability, reliability, latency, and resource usage are internal and external to the algorithm. The approach above scales well with work portion or dataset size. The first experiment shows the algorithm scaling perfectly even as IoT devices generate additional data. Experiment 2 proves linear scalability works for 100,000 IoT devices, while Experiment 3 efficiently organizes 1 million data points. It proved the algorithm by tolerating manufactured faults. To ensure data service availability, Experiment 1 tests the system's operational dependability on node failures and network disturbances. With 0.1% downtime even under challenging conditions, experiment 2 showed the algorithm's incredible robustness in real-world applications. To improve data organization, this experiment exhibits data consistency when nodes fail. Lower and constant time improves operation safety and reliability. Algorithm 1 shows how the algorithm can quickly answer data queries and keep up with the massive amount of data transfers, supporting low-latency IoT applications. Average data retrieval latency of experiment 2 is 10 ms, which is real-time for vital information. Trial 3 processes data online with a latency © 2024 IEEE.

关键词： Cloud storage

来源：评论

学校读者我要写书评

暂无评论

Machine Learning-Enhanced Analysis of Genomic Data for Precision Medicine

Machine Learning-Enhanced Analysis of Genomic Data for Preci...

引用

2024 OPJU International Technology Conference on Smart Computing for Innovation and Advancement in Industry 4.0, OTCON 2024

作者： Sasikala, R. Deepthi, K. Jaya Balakrishnan, T. Suresh Krishnan, Prabhakar Ebenezar, U. Samson Care College of Engineering Department of Computer Science and Engineering Tamil Nadu Trichy620009 India Mohan Babu University Department of Aiml Ap Tirupati India Saveetha Institute of Medical and Technical Sciences Saveetha University Saveetha School of Engineering Department of Computer Science and Engineering Chennai India Amrita Vishwa Vidyapeetham Center for Cyber Security Systems and Networks Amritapuri-Campus India Saveetha Institute of Medical and Technical Sciences Saveetha University Saveetha School of Engineering Department of Computer Science and Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350373783

Precision medicine employs genetic data, which is enhanced with machine learning algorithms, to determine the most relevant treatment method per patient's genotype. We have zoned in on the area of a machine learning-guided genetic information analysis in this study to assist in clinical decisionmaking of precision medicine while improvising. Genetic information for 500 cancer patients cases taken from the public database and cleaned to lean out the desired features were furnished. Different machine learning algorithms were trained, including SVM, random forest, gradient boost, deep learning (CNN) and ensemble (ensemble method). Their performance was investigated for predicting cancer subtypes. The ensemble model reached the top accuracy level (88%), the best sensitivity (85%), ever specificity (91%) and AUC score (0.95). By comparison a group had better result than an individual algorithm could across all metrics. In further, deep learning methods were reported to attain more accuracy and F1 scores which is more than traditional machine learning methods. These findings hence prequalify the usefulness of ML in investigating genotype data in precision medicine, and enable physicians with useful information to select treatment options, make prognosis, and indicate the medical care. © 2024 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Wavelength-division-multiplexed Transmission and Dispersion Compensation Enabled by Soliton Microcombs and Cascaded Microrings

Wavelength-division-multiplexed Transmission and Dispersion ...

引用

CLEO: science and Innovations in CLEO 2024, CLEO: S and I 2024 - Part of Conference on Lasers and Electro-Optics

作者： Liu, Yuanbin Zhang, Hongyi Liu, Jiacheng Lu, Liangjun Du, Jiangbing Li, Yu He, Zuyuan Chen, Jianping Zhou, Linjie Poon, Andrew W. State Key Laboratory of Advanced Optical Communication Systems and Networks Shanghai Key Lab of Navigation and Location Services Shanghai Institute for Advanced Communication and Data Science Department of Electronic Engineering Shanghai Jiao Tong University Shanghai200240 China SJTU-Pinghu Institute of Intelligent Optoelectronics Pinghu314200 China Photonic Device Laboratory Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Clear Water Bay Hong Kong

We demonstrate wavelength-division-multiplexed data transmission and dispersion compensation of 25 Gb/s × 9 on-off-keying signals over a 20-km singlemode fiber using an integrated single-soliton microcomb and a cascaded microring resonator-based reconfigurable dispersion compensator. © Optica Publishing Group 2024

关键词： Dispersion compensation

来源：评论

学校读者我要写书评

暂无评论

Wavelength-division-multiplexed Transmission and Dispersion Compensation Enabled by Soliton Microcombs and Cascaded Microrings

Wavelength-division-multiplexed Transmission and Dispersion ...

引用

2024 Conference on Lasers and Electro-Optics, CLEO 2024

ISBN: (纸本)9781957171395

关键词： Optical fibers

来源：评论

学校读者我要写书评

暂无评论

Visual Measurement of Foam Thickness in Flotation Process Based on Depth Stereo Matching

Visual Measurement of Foam Thickness in Flotation Process Ba...

引用

2024 International Conference on Automation in Manufacturing, Transportation and Logistics, ICaMaL 2024

作者： Zheng, Xiuguang Li, Xiaorui Yuan, Zhaolin Ban, Xiaojuan School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China Institute of Artificial Intelligence University of Science and Technology Beijing Beijing China Hong Kong Polytechnic University Department of Industrial and Systems Engineering Hong Kong Hong Kong

ISBN: (纸本)9798350378658

In the process of copper flotation, the traditional detection method has some defects in accurately detecting the depth of foam layer in the flotation cell, especially for the identification of foam information of highly reflective and attenuation materials in the flotation foam system. We aim to introduce a new synthetic dataset, specifically for the flotation foam system, and pay special attention to the foam information of high reflection and high attenuation materials, so as to promote it to the actual flotation foam system and improve the accuracy of liquid level detection. We combine the newly synthesized dataset with binocular ranging methods and propose a soft strategy method for depth estimation of flotation cell thickness using binocular stereo matching based on IoT technology. The experimental results show that our method has achieved remarkable results in the flotation foam system, can accurately measure the depth of the flotation cell, and provides reliable technical support for the control and optimization of the flotation process. Therefore, this binocular stereo matching depth estimation method based on IoT technology provides an effective way to solve the limitations of traditional flotation depth detection methods. It not only effectively monitors the current efficiency of the flotation cell but also automatically identifies instances of flotation cell froth overflowing, offering automated inspection and diagnostics. © 2024 IEEE.

关键词： Stereocenters

来源：评论

学校读者我要写书评

暂无评论

Method for preserving privacy in wearable IoT devices by extending security using fog computing

Method for preserving privacy in wearable IoT devices by ext...

引用

2024 OPJU International Technology Conference on Smart Computing for Innovation and Advancement in Industry 4.0, OTCON 2024

作者： Sathyaraj, P. Singh, Mukesh Umaeswari, P. Mahesh Kumar, A.S. Vekariya, Vipul Maranan, Ramya R.M.K. College of Engineering and Technology Department of Electronics and Communication Engineering Puduvoyal601206 India Graphic Era Deemed to Be University Department of Computer Science & Engineering Uttarakhand Dehradun248002 India R.M.K Engineering College Department of Computer Science and Business Systems Thiruvallur Tamil Nadu Kavaraipettai India Pes College of Engineering Department of Electronics and Communication Engineering Karnataka Mandya571401 India Parul Institute of Engineering and Technology Parul University Department of Computer Science and Engineering Gujarat India Simats Saveetha School of Engineering Department of Research and Innovation Tamil Nadu Chennai602105 India

ISBN: (纸本)9798350373783

The overarching objective has been achieved through the development of a method enabling the extension of Fog Computing (FC) to facilitate the transport and encryption of sensitive data from wearable devices. The study presents a method leveraging Fog Computing (FC) to transport and encrypt sensitive data from wearable devices, effectively mitigating privacy risks. Through comprehensive tests, NFC emerges as the optimal technology for data transport, while the DHEC algorithm is identified as the best encryption method for securing data between FC and the cloud. Real-world simulations validate the proposed approach, demonstrating its feasibility and effectiveness. The MyNFC app facilitates secure data transmission to AWS, with ServerNFC successfully decrypting data. The AES algorithm exhibited an average CPU usage of 31.8375, with low energy consumption and an average execution time of 26.404 seconds. For the RSA algorithm, the average CPU usage was 33.5875, also with low energy consumption, and an average execution time of 27.8 seconds. The DHEC algorithm showed an average CPU usage of 33.25, with low energy consumption, and an average execution time of 26.711 seconds. Lastly, the HJP algorithm displayed an average CPU usage of 32.375, with low energy consumption, and an average execution time of 30.163 seconds. Overall, the study highlights the ability of FC to safeguard information against interception, endorsing the proposed method's security and scalability. © 2024 IEEE.

关键词： Fog computing

来源：评论

学校读者我要写书评

暂无评论

Edge Computing in Micro Data Centers for Firefighting in Residential Areas of Future Smart Cities

Edge Computing in Micro Data Centers for Firefighting in Res...

引用

2022 International Conference on Electrical, computer, communications and Mechatronics Engineering, ICECCME 2022

作者： Gudepu, Venkateswarlu Pappu, Bhavani Javvadi, Tejasri Bassoli, Riccardo Fitzek, Frank H.P. Valcarenghi, Luca Devi, D.V.N. Kondepu, Koteswararao IIT Dharwad Department of Computer Science and Engineering Dharwad India RGUKT-Srikakulam Department of Computer Science and Engineering Srikakulam India RGUKT-Srikakulam Department of Electronics Communication Engineering Srikakulam India Technische Universitat Dresden Deutsche Telekom of Communication Networks Dresden Germany Telecommunications. Computer Engineering and Photonics Institute Scuola Superiore sant'Anna Pisa Italy RGUKT Nuzvid Department of Computer Science and Engineering Nuzvid India

ISBN: (数字)9781665470957

ISBN: (纸本)9781665470957

5G standardization is going to reach its end, so research on 6G has started, driven by the scientific and industrial communities. 5G and especially 6G, are going to provide resources to enhance every aspect of human life via communication networks and computing. Among the different verticals, emergency services are one of the most important parts of making smart cities of the future a reality. In this context, firefighting is highly important for security and safety. However, firefighting requires ultra-reliable and low-latency communications since firefighters can be provided with advanced guidance during fire control with the employment of distributed sensors, robots, etc. Also, the use of machine learning algorithms is important for firefighters to analyze and make decisions based on the audiovisual and possibly tactile information they collect. Such a scenario cannot leverage the current cloud computing paradigm, which has significant latency issues. That is why it is important to study and design edge computing paradigms to address the goals of these scenarios and use cases since they can be capable of fulfilling latency and reliability requirements. In this situation, this work looks into how computing at Edge Micro Data Centers (EMDC) can be used to improve how fires are predicted and managed. We propose a novel three-stage architecture. The initial stage focuses on prediction and classification of the fire occurrence based on available sensor data at the EMDC, whereas the second stage deals with the fire occurrence confirmation using a convolutional neural network (CNN) classification model. After the fire occurrence has been confirmed, the final stage notifies the tenants and streams 360-degree monitoring video to the nearby fire station after processing at EMDC. The results showed that the proposed architecture can realize firefighting services with low latency. to the best of the authors' knowledge, this is the first work studying and experimentally evalu

关键词： Network architecture

来源：评论

学校读者我要写书评

暂无评论

Design and Development of an Ontology Driven Search Engine for a Mobile Cloud Asynchronous Remote Learning Platform 13

Design and Development of an Ontology Driven Search Engine f...

引用

13th Annual IEEE Global Humanitarian Technology Conference, GHTC 2023

作者： Cruz, X.M. Honrado, J.L. Coronel, A. Libatique, N.J. Tangonan, G. Ateneo de Manila University Ateneo Innovation Center Quezon City Philippines Ateneo de Manila University Department of Information Systems and Computer Science Quezon City Philippines Ateneo de Manila University Department of Electronics Computer and Communication Engineering Department Quezon City Philippines

ISBN: (纸本)9798350321326

In the face of a global pandemic, the digital divide has become apparent especially in bandwidth-constrained countries. As contactless remote services have become increasingly necessary in the face of limited human mobility, remote learning has become the norm. To support remote learning, the research team developed a resilient asynchronous remote learning and content distribution platform as a digital library. Collaborating with corresponding stakeholders, the scope of content for the initial iterations of the platform was curated to accommodate resources for STEM educational *** the initial feedback for the prototype, there is a need for a consolidated means of retrieving information and resources across content channels while adhering to the prescribed Philippine K-12 curriculum. As such, the researcher proposes an implementation of an ontology-driven search engine deployed on the remote learning platform. The search engine will use an ontology encompassing the K-12 curriculum and an index of curated content across the educational content-hosting services within the digital library. This study develops a system to reliably retrieve and recommend contextually relevant results with the use of semantic web annotations and semantic information retrieval techniques to improve upon classical information retrieval. © 2023 IEEE.

关键词： COVID-19

来源：评论

学校读者我要写书评

暂无评论

Mathematically Modified Adaptive Neuro-Fuzzy Inference System for an Intelligent Cyber Security System

引用

SN computer science 2023年第5期4卷 453页

作者： Marimuthu, Divyapushpalakshmi Rao, Ganga Rama Koteswara Mehbodniya, Abolfazl Mohanasundaram, Dhavamani Sundaram, Chandru Kavindapadi Maria, Anto Bennet Mani, Devi Department of Computer Science and Engineering GITAM University Bangalore 561203 India Department of Computer Science and Information Technology Koneru Lakshmaiah Education Foundation Andhra Pradesh Vaddeswaram 52002 India Department of Electronics and Communication Engineering Kuwait College of Science and Technology Kuwait City Kuwait Department of Mathematics Kongu Engineering College Tamil Nadu Perundurai 638060 India Department of Computer Science and Business Systems Bannari Amman Institute of Technology Tamil Nadu Sathyamangalam 638401 India Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Tamil Nadu Chennai 600062 India Department of Computer Science College of Science and Arts (Female) Sarat Abidah Campus King Khalid University Kingdom of Saudi Arabia Abha Saudi Arabia

Cybersecurity is defending sensitive information and crucial systems against Internet attacks. Cyber-Physical systems (CPS) and the Internet of Things (IoT) are becoming increasingly significant in critical infrastructure, government, and daily life. Using persons, processes, technology, and policies to protect businesses, their sensitive data, and critical systems from Internet threats. Several researchers developed and analyzed the security system for protecting confidential information. The existing security system lacks sufficient accuracy, which results in cyber-attacks. A Mathematically Modified Adaptive Neuro-Fuzzy Inference System (MMANFIS) is used to attain efficiency and handle complex data. The proposed MMANFIS is effective in attaining an accuracy of 96% by retrieving significant features where the MMANFIS classifier accomplishes the classification. To demonstrate the proposed MMANFIS, the output classifier is compared with the results of the current methodologies. Two fuzzy inference-based rules are taken into consideration to clarify this MMANFIS model. The current and proposed optimum feature selection algorithms have examined the classifiers’ effectiveness using full and best features. The proposed MMANFIS approach outperforms in terms of accuracy, which attains 95% accuracy, and the accuracy rate is higher than the existing techniques. The processing time for the attack diagnosis has significantly reduced from 12.220 to 3.079 s while using optimal features of MM as inputs compared to using Gaussian Algorithm (GA) features. © 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： Classification Cyber-attacks Fuzzy Mathematical model Membership Neural network Optimal feature

来源：评论

学校读者我要写书评

暂无评论

Performance Improvements of Vehicular PKI Protocol for the Security of V2X communications 46

Performance Improvements of Vehicular PKI Protocol for the S...

引用

46th International Conference on Telecommunications and Signal Processing, TSP 2023

作者： Farran, Hassan Khoury, David Budapest University of Technology and Economics Faculty of Electrical Engineering and Informatics Department of Networked Systems and Services BudapestH-1111 Hungary American University of Science and Technology Department of Computer Science and Information and Communication Technology Beirut Lebanon

ISBN: (纸本)9798350303964

Vehicle-to-Everything (V2X) technology allows vehicles to communicate with numerous transportation system components. To provide safe communication between vehicles and other entities, V2X depends on Public Key Infrastructure (PKI). However, the present PKI employed in V2X has certain drawbacks, including scalability and high computational cost. This article offers an enhancement to the current PKI in V2X that tackles these constraints by managing and distributing keys using blockchain technology. The suggested Public Key Infrastructure enhancement is intended to be secure, efficient, and scalable, providing a more solid and trustworthy foundation for V2Xcommunication. The article explains the suggested PKI enhancement and examines its advantages and disadvantages. Overall, the suggested Public Key Infrastructure enhancement has the potential to increase the security and dependability of Vehicle-to-Everything communication, allowing for a secure and more effective transportation system. © 2023 IEEE.

关键词： Vehicle to Everything

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：