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检索条件"任意字段=4th International Multi-Conference on Computing in the Global Information Technology"

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A Sustainable and Secure Cloud resource provisioning system in Industrial Internet of things (IIoT) based on Image Encryption 22

A Sustainable and Secure Cloud resource provisioning system ...

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Proceedings of the 4th international conference on information Management & Machine Intelligence

作者： C.T Dora Pravina Mrunalini Upendra Buradkar Md Khalid Jamal Ashish Tiwari Udit Mamodiya Dinesh Goyal Mathematics Vel Tech Rangarajan Dr Sagunthala R&D Institute of Science and Technology India Electronics & Telecommunication Engineering St. Vincent Pallotti College of Engineering & Technology India Computer Application Integral University Lucknow India Computer science and engineering Amity University Lucknow campus India PIET AICTE IDEA LAB Poornima Institute of Engineering and Technology India CSE Poornima Institute of Engineering and Technology India

ISBN: (纸本)9781450399937

An organization can be created through the Industrial Internet of things (IIoT), which can transform an existing bound structure. the Industrial Internet of things (IIoT) and its remote organization requirements for current sensors are very productive. the IIoT's introduced sensors monitor the conditions of contemporary machines and devices. Silicon Cloud demonstrated the advantages of modern distributed computing advancements for intelligent and planning applications. As a result, constant quality and security have emerged as the primary concerns in the IIoT. this presents several distinct and consistently increasing wagers on the advanced system. the research deals with the aim of cutting-edge handheld GPS devices. In a similar vein, recent region-based organizations make use of regional data. there is enough fragile data in the region data provided to these area-based expert communities to warrant overemphasis. As a result, experts are working on finding a solution for safe regional data. Most of the investigation frameworks that were suggested were designed to make them believe that the research objectives are fulfilled rather than precise headings of the client's region.

关键词： information Internet of things (IoT) Cloud Applications Searching Methodology Optimization

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Optimizing Privacy-Accuracy Trade-off in DP-FL via Significant Gradient Perturbation

Optimizing Privacy-Accuracy Trade-off in DP-FL via Significa...

引用

international conference on Mobile Ad-hoc and Sensor Networks, MSN

作者： Benteng Zhang Yingchi Mao Zijian Tu Xiaoming He Ping Ping Jie Wu School of Computer and Information Hohai University Nanjing China Key Laboratory of Water Big Data Technology of Ministry of Water Resources Hohai University Nanjing China Center for Networked Computing Temple University Philadelphia USA

ISBN: (数字)9798350358261

ISBN: (纸本)9798350358278

In federated learning with differential privacy, an obvious phenomenon of local gradient sparsification emerges in some training rounds. When training with low privacy budgets, there is a risk of excessive noise being introduced into the uploaded gradients, leading to a significant decrease in the accuracy of the global model. To tackle the trade-off between privacy protection and model accuracy with low privacy budgets, we propose a differential privacy federated aggregation method based on gradient sparsification (DP-FedAGS), which not only prevents excessive noise addition by protecting only significant gradients, but also accelerates global model convergence by dynamically calculating the weight of the gradient. Experimental results indicate that DP-FedAGS achieves comparable privacy protection to DP-FedAvg and cpSGD, while outperforming DPFedSNLC. Moreover, our approach respectively attains an approximate average test accuracy improvement of $2 .45 \%, 4 . 79$% and $0 . 29$% over the above three methods, rendering DP-FedAGS a promising approach for exploring a balance between privacy protection and model accuracy.

关键词： Training Privacy Differential privacy Accuracy Perturbation methods Noise Rendering (computer graphics)

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Improving the courses of educational programs on information security smart grid 4

Improving the courses of educational programs on information...

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4th All-Russian Scientific and Practical conference with international Participation "Distance Learning Technologies", DLT 2019

作者： Olifirov, Alexander V. Makoveichuk, Krystina A. Petrenko, Sergei A. V.I. Vernadsky Crimean Federal University Simferopol Russia Innopolis University Kazan Russia

global trends directly or indirectly affect the directions of development of the electric power industry in Russia, including the power grid complex. therefore, it is necessary not only to monitor these trends, but also to strive to respond to them in a timely manner. Smart Grids (SGs) represent a new concept in the development of electric power infrastructure in a digital economy. the widespread use of digital technology is a key factor in providing customers with intelligent electricity services. Existing courses, educational programs in such a situation do not always meet the requirements of the new concept and do not allow the formation of the necessary new competencies. this article provides recommendations for improving educational activities based on the risk analysis of the electricity company and compiling a competency map for an educational program for training personnel in the field of security risk management for SG, methodological approaches to teaching courses are discussed. © 2021 CEUR-WS. All rights reserved.

关键词： Risk analysis

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TBIT: Transformer-based Business Prediction Model Integrating Work Order Textual Contextual information 21

TBIT: Transformer-based Business Prediction Model Integratin...

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4th international conference on Big Data Technologies, ICBDT 2021

作者： Yin, Mingli Zhang, Wenbin Guo, Shuangshuang Tang, Linlin Han, Shengya Liu, Yin Shi, Yuliang State Grid Shandong Electric Power Company Information and Communication Company Jinan China State Grid Shandong Electric Power Company Information and Communication Company Jinan China School of Software Shandong University Jinan China Dareway Software Co. Ltd Jinan China

ISBN: (纸本)9781450385091

Accurate business prediction provides a good understanding of individual business trends and has a significant impact on reducing overall operating costs and ensuring a high level of customer service quality. Currently, artificial intelligence and big data technologies have been widely used in various businesses of electric power customer service, but how to effectively use the heterogeneous information in customer service data for business prediction has become a major challenge. To solve this problem, this paper proposes a Transformer-based Business Prediction Model Integrating Work Order Textual Contextual information (TBIT) to perform customer service business prediction. the model first uses one-dimensional convolution and self-attention mechanism to mine the semantic contexts contained in the work order text information. then, the Transformer is used to fuse the customer's dynamic preference information with the work order text context, and to mine the global time sequence dependence of work order data, so as to realize customer service business prediction. the final experiments show that the TBIT model can perform representation learning on work order data more effectively compared to the baseline models, and also show superior performance in the customer service business prediction task. © 2021 ACM.

关键词： Forecasting

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Dynamic Resource Aware Scheduling Schemes for IEEE 802.16 Broadband Wireless Networks 4th

Dynamic Resource Aware Scheduling Schemes for IEEE 802.16 Br...

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4th international conference on Advanced computing and Intelligent Engineering, ICACIE 2019

作者： Deva Priya, M. Christy Jeba Malar, A. Sam Peter, S. Sandhya, G. Vishnu Varthan, L.R. Vignesh, R. Department of Computer Science & Engineering Sri Krishna College of Technology CoimbatoreTamil Nadu India Department of Information Technology Sri Krishna College of Technology CoimbatoreTamil Nadu India

ISBN: (纸本)9789811565830

the scheduling algorithms for IEEE 802.16 standard are designed with the predominant goals of throughput optimization, ensuring fairness and Quality of Service (QoS) provisioning. In this work, enhancements are proposed to the existing Weighted Fair Queuing (WFQ) and Deficit Weighted Round Robin (DWRR) scheduling algorithms to efficiently utilize the unused units. In WFQ, additional units may be assigned to a queue, thus reducing the service rate. Instead in Enhanced WFQ (EWFQ), multiple queues are served in a round by effectively utilizing the unexploited units. In DWRR, a queue is not serviced if the size of the packet at the front of the queue exceeds the available quantum. Enhanced DWRR (EDWRR) checks for packets with sizes less than the Deficit Counter (DC), sorts the queue and services a smaller packet in the current round. Further, if the queue that is currently served becomes empty, the DC is transferred to the ensuing active queue instead of making it zero. this helps in servicing more number of packets in a round. the proposed scheduling schemes are proficient in servicing specific traffic flows. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Scheduling algorithms

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Predicting Electricity Consumption Using Load Profiling Clustering Method

Predicting Electricity Consumption Using Load Profiling Clus...

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Data Analytics for Business and Industry: Way Towards a Sustainable Economy (ICDABI), international conference on

作者： Esra Al-Jowder Sawsan Hilal Riadh Ksantini M.Sc. in Big Data Science & Analytics Collage of Science University of Bahrain Kingdom of Bahrain Department of Mathematics College of Science University of Bahrain Kingdom of Bahrain Department of Computer Science College of Information Technology University of Bahrain Kindgom of Bahrain

ISBN: (数字)9798350369786

ISBN: (纸本)9798350369793

It became crucial to analyze the energy consumption trends from smart meter data to identify potential saving opportunities by the electricity suppliers and authorities since energy consumption is considered one of the essential topics of energy systems which gained high attention after the energy crisis in 1970’s. Despite that smart meter data analytics is relatively recent field, the progress in high performance computing makes it possible to efficiently and effectively extracting more beneficial knowledge and patterns from collected massive data within the smart grid. this research aims at providing a model for predicting load profiling while considering the temporal feature of the smart meter data by deploying a deep clustering algorithm embedded with an autoencoder and compare it with the dynamic autoencoder which can improve the prediction quality while applying dimensionality reduction and evaluate these models based on the performance using the silhouette score. the dynamic autoencoder outperformed the deep embedded clustering (DEC) and improved deep embedded clustering (IDEC) models and achieved a silhouette score of 0.9931 compared to DEC of 0.6128 and IDEC of 0.8829. this shows that positioning a dynamic autoencoder embedded with deep clustering model has worked effectively against the problem of feature drift and feature randomness.

关键词： Energy consumption Data analysis Heuristic algorithms Electricity Clustering algorithms Predictive models Smart meters

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Fuzzy cloud ranking model based on QoS and trust 4

Fuzzy cloud ranking model based on QoS and trust

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4th international conference on IoT in Social, Mobile, Analytics and Cloud, ISMAC 2020

作者： Faiz, Mohammad Daniel, A.K. M.M.M. University of Technology Department of Computer Science and Engineering Gorakhpur India

ISBN: (纸本)9781728154640

Cloud computing is one of the emerging domains of information technology as most of the applications are moving towards Cloud because of its features like availability, performance, security, cost, and maintenance. In recent advancement due to the rapid growth of Cloud computing technology, a vast number of Cloud service providers are available to fulfill the needs of Cloud customers. So, it is quite difficult for a customer to choose a Cloud service provider that will satisfy his needs. this paper has reviewed popular Cloud ranking models to prioritize the ranking of Cloud services based on different parameters of Cloud and proposed a fuzzy trust model for the ranking of different cloud service providers using three basic parameters capacity, cost and performance. © 2020 IEEE.

关键词： Trusted computing

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Two Enhanced-Rate Power Allocation Strategies for Active IRS-Assisted Wireless Network

Two Enhanced-Rate Power Allocation Strategies for Active IRS...

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Computer Communication and Artificial Intelligence (CCAI), international conference on

作者： Qiankun Cheng Rongen Dong Wenlong Cai Ruiqi Liu Feng Shu Jiangzhou Wang Hainan University School of Information and Communication Engineering Haikou China National Key Laboratory of Science and Technology on Aerospace Intelligence Control Beijing Aerospace Automatic Control Institute Beijing China Wireless and Computing Research Institute ZTE Corporation Beijing China University of Kent School of Engineering Canterbury U.K.

ISBN: (数字)9798350362763

ISBN: (纸本)9798350362770

Due to its ability of overcoming the impact of double-fading effect, active intelligent reflecting surface (IRS) has attracted a lot of attention. Unlike passive IRS, active IRS should be supplied by power, thus adjusting power between base station (BS) and IRS having a direct impact on the system rate performance. In this paper, the active IRS-aided network under a total power constraint is modeled with an ability of adjusting power between BS and IRS. Given the transmit beamforming at BS and reflecting beamforming at IRS, the SNR expression is derived to be a function of power allocation (PA) factor, and the optimization of maximizing the SNR is given. Subsequently, two high-performance PA strategies, enhanced multiple random initialization Newton's (EMRIN) and Taylor polynomial approximation (TPA), are proposed. the former is to improve the rate performance of classic Newton's method to avoid involving a local optimal point by using multiple random initializations. To reduce its high computational complexity, the latter provides a closed-form solution by making use of the first-order Taylor polynomial approximation to the original SNR function. Actually, using TPA, the original optimization problem is transformed into a problem of finding a root for a third-order polynomial. Simulation results are as follows: the first-order TPA of SNR fit its exact expression well, the proposed two PA methods performs much better than fixed PA in accordance with rate, and approaches exhaustive search as the number of IRS reflecting elements goes to large-scale.

关键词： Array signal processing Wireless networks Simulation Polynomials Vectors Resource management Newton method

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Expression of Concern for: OIDCBMS: A Novel Neural Network based Intrusion Detection System to Cloud computing based on New Cube Algorithm

Expression of Concern for: OIDCBMS: A Novel Neural Network b...

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international conference on Inventive Research in computing Applications (ICIRCA)

作者： Doddi Srilatha N. thillaiarasu School of Computing and Information Technology REVA University Bengaluru India Department of CSE Sreenidhi Institute of Science and Technology Hyderabad India

ISBN: (数字)9781665497077

ISBN: (纸本)9781665497084

Intrusion Detection System (IDS) is a significant segment for maintaining network security. Likewise, as the cloud stage is rapidly developing and becoming more famous in our daily existence, it is valuable and important to construct an effective IDS for cloud computing. Notwithstanding, present intrusion detection procedures will probably confront difficulties when deployed on the cloud stage. the pre-decided IDS engineering may prompt over-burdening of a piece of the cloud because of the additional discovery overhead. the presented approach, Online Instruction Detection Cloud-Based Management System (OIDCBMS), receives the novel NN (Neural Network) design standards termed as New Cube algorithm. It is the primary sorting-out framework approach that uses the New Cube calculation. the OIDCBMS takes over the hybrid learning aspect of the New Cube algorithm and utilizes such calculation in an online framework by deep-rooted figuring out how to group input while learning the framework. In addition, with the AI capacity with the neural organization, the projected IDS may identify novel kinds of attacks with genuinely precise outcomes. Using zero-day assaults, the framework's precision increases to roughly 096.74 percent depending on the to-be-remembered (TBR) encoding computation.

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Real Time Web Server Aggregator to Collect Fresh information Based on multi-Services

Real Time Web Server Aggregator to Collect Fresh Information...

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international conference on Engineering technology and their Applications (IICETA)

作者： Ammar Hameed Shnain Azham Hussain Wasan Abdulwahab Mohammed Hayder M. A. Ghanimi Sarah Hadi Shaheed Manhal Isam Sabri The Islamic University Najaf Iraq Ministry of transportation of Iraqi state company for private transport School of Computing Universiti Utara Malaysia Changlun Malaysia Ministry of transportation of Iraqi Ministry of Education Baghdad Iraq. College of Engineering University of Warith Al-Anbiyaa Karbala Iraq Ministry of Electricity Baghdad Iraq.

ISBN: (纸本)9781665494625

It is well-known that Internet information has grown substantially where millions of news spread online in a blink of an eye. this causes what so called information overloading that makes browsing important online information daunting and annoying task. thus, this paper seeks to design a complete real-time webserver helps in gathering and distributing essential information based on user’s preferences. A one-stop webserver prototype is developed to serve as an automatic information collector from heterogenous sources and as well it’s evaluated. Evaluation process has shown the server enables users to browse different information from multiple sources on one site easily.

关键词： Prototypes Real-time systems Web servers Internet Task analysis

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