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共 398 条记录，以下是381-390 订阅

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Federated clouds for biomedical research: Integrating OpenStack for ICTBioMed

Federated clouds for biomedical research: Integrating OpenSt...

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IEEE international conference on Cloud Networking (CLOUDNET)

作者： Cezary Mazurek Juliusz Pukacki Michal Kosiedowski Szymon Trocha Michael Sullivan Hemant Darbari Amit Saxena Rajendra Joshi Devdatt Dubhashi Subazini Thankaswamy Paul Brenner Sandra Gesing Jarek Nabrzyski Anil Srivastava PSNC Poznan Poland C-DAC Pune India CRC Notre Dame USA Internet2 Washington D.C USA Chalmers Gothenburg Sweden Open Health Systems Laboratory Rockville USA

Increasingly complex biomedical data from diverse sources demands large storage, efficient software and high performance computing for the data's computationally intensive analysis. Cloud technology provides flexible storage and data processing capacity to aggregate and analyze complex data; facilitating knowledge sharing and integration from different disciplines in a collaborative research environment. The ICTBioMed collaborative is a team of internationally renowned academic and medical research institutions committed to advancing discovery in biomedicine. In this work we describe the cloud framework design, development, and associated software platform and tools we are working to develop, federate and deploy in a coordinated and evolving manner to accelerate research developments in the biomedical field. Further, we highlight some of the essential considerations and challenges to deploying a complex open architecture cloud-based research infrastructure with numerous software components, internationally distributed infrastructure and a diverse user base.

关键词： Collaboration Biological system modeling Bioinformatics Data visualization Cloud computing Cancer

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Application and Research of Deep Mining of Health Medical Big Data Based on internet of Things 2021

Application and Research of Deep Mining of Health Medical Bi...

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2021 3rd international conference on Artificial Intelligence and Advanced Manufacture

作者： Youshen Chi Human resources and social security information center China

ISBN: (纸本)9781450385046

Traditional data mining algorithms are mostly difficult to handle large data sets, but need to manage big data and discover hidden knowledge. Therefore, the combination of data mining algorithms and IoT technology is the development trend of data processing in the future, but because of the difficulty, not all algorithms can be implemented on the cloud platform, so the research results are not enough. The core idea of cloud computing is architecture. All data mining algorithm improvement strategies need to be designed according to the characteristics of the architecture, and each part must implement specific functions. It is difficult or impossible to implement an algorithm that cannot be decomposed into the above form in the architecture. With the widespread application of IoT technology, a large number of unstructured, distributed and even data mining requirements in mobile devices pose serious challenges to existing data mining technologies. How to use cloud computing technology to achieve large-scale distributed data collection, transmission and mining has become an important research direction. This paper investigates some health care big data, combines the internet of Things cloud data platform, and introduces the traditional association rules algorithm and its interest level in mining technology. On this basis, the improved algorithm is improved and compared with other traditional algorithms. Establish a simulation platform to implement algorithms and mine training data. It proves that the improved algorithm has lower spatial complexity and faster processing rate in data mining, and analyzes the data mining technology in health medical data.

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Study of Next-Generation Infrastructure: InfiniBand HPC Grid computing for Telecommunications Data Center

Study of Next-Generation Infrastructure: InfiniBand HPC Grid...

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2010 3rd IEEE international conference on Computer Science and Information technology—ICCSIT 2010

作者： Gyankamal Chhajed Santosh Shinde Rahul Jagtap Venkatesh Raskotwar Professor of Computer department Vidya Pratishthan's College of Engineering Baramati Pune University Student of Computer Department Vidya Pratishthan's College of EngineeringBaramati Pune University

Grid computing is increasingly being viewed as the next phase of distributed computing. Built on pervasive internet standards, grid computing enables organizations to share computing and information resources across department and organizational boundaries in a secure, highly efficient manner. Grid computing originates in e-Science and its early development was driven to a large extent by the requirements of large-scale computing and efficient sharing of huge datasets. e-Business requirements led to the adoption of emerging Web services technologies-initially developed for distributed business application integration. Therefore grid computing can be applied to enterprise computing within and across organizations and pave the way for utility computing. This paper propose an all InfiniBand grid computing proof of concept （PoC） to deploy "Database-as-a-Service" for mission-critical Oracle deployments in high-end transactional situations. This shows that performance of grid architecture-leveraging blade servers as well as InfiniBand networking and Storage is capable of achieving results equivalent to traditional, high-end SMP systems at significantly lower cost and power consumption levels.

关键词： InfiniBand Grid Architecture OGSA

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E-Learning System Architecture for Cloud computing – A review

E-Learning System Architecture for Cloud Computing – A revi...

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international conference on Contemporary computing and Informatics (IC3I)

作者： Zahoor Ahmad Lone Priyanka Chawla Ajay Rana School of Computer Science & Engineering Lovely Professional University Jalandhar India School of Computer Science & Engineering Amity University Noida

ISBN: (数字)9781538668948

ISBN: (纸本)9781538668955

The recent past has witnessed the e-learning systems gaining more popularity in view of the technological development in support of e-learning and the number of heterogeneous devices connected with such systems. The field of education has already been affected by the infiltration of digital technology connected with the forecast of internet of Things (IoT) foreseeing approximately fifty billion heterogeneous smart devices to be active by 2020. Cloud computing has a tremendous potential and has attracted educational sector for delivery of educational contents in an economical, secure and reliable way. Today's cloud architecture is composed of distributed computing, grid computing, virtualization technologies and its architecture makes available a flexible execution environments in which different resources can be linked to application and platform components. The continuity of architecture is its capability make alterations in itself and at the same time to retain the strength of objectives and this feature of a cloud system has an impact on the economic withstanding. This ability of cloud systems help in maintaining the technical sustainability. The introduction of Fog computing adds value to this scenario. The interconnection of such a huge number of smart electronic devices is expected to generate large amount of data which sometimes be analyzed in real time. This adds new type of big data and could be called as educational big data. The data generated by different sources such as study material, tests etc. needs well defined mining and analysis techniques in order to get time bound accurate information. The present paper reviews the current state of cloud based e-learning systems, compares the available cloud based e-learning architecture with the aim to enhancing the ability of cloud based e-learning architecture in view of present technologies like internet of Things (IoT), Fog computing(FC) and Big Data Streams.

关键词： Cloud computing Big Data Electronic learning Computer architecture internet of Things Edge computing Hardware

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Research on Employee Innovative Behavior Feedback System Based on Web-based ID3 Algorithm

Research on Employee Innovative Behavior Feedback System Bas...

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Data Analytics, computing and Artificial Intelligence (ICDACAI), international conference on

作者： Hongchi Luo School of Management Shanghai University Shanghai China

ISBN: (数字)9798331519032

ISBN: (纸本)9798331519049

In the internet era, the rapid development of technology has had a profound impact on the development of enterprises. With the rapid changes in the global economy, enterprises are faced with the serious challenges brought about by the uncertainty of market structure and demand. In this case, the innovative behaviour of employees has become a key factor to promote the development of enterprises, which is an important part of their innovative capacity. The study used the questionnaire star platform and offline distribution of questionnaires for enterprise employees with different gender, age, nature of the enterprise, job level and other attributes, and successfully distributed and returned 206 valid questionnaires, using SPSS 27, AMOS 25 and other analytical software to analyse the data for reliability analysis, validity analysis and correlation test, and using machine learning decision tree algorithm -ID3 algorithm to construct the decision tree model. This study can effectively help enterprises to recruit employees, through the comprehensive analysis of the attributes and innovative behaviour of employees, to achieve the accurate identification of employee potential, and then screen out high-quality talents with innovative ability for enterprises.

关键词： Technological innovation Machine learning algorithms Uncertainty Software algorithms Stars Software Software reliability Decision trees Problem-solving Recruitment

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Multi-agent Reinforcement Learning for Live Video Streaming in Vehicular Networks

Multi-agent Reinforcement Learning for Live Video Streaming ...

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Digital Society and Intelligent Systems (DSInS), international conference on

作者： Meiting Wu Kangli Zhao Xiaowei Lei Penglin Dai School of Computing and Artificial Intelligence Southwest Jiaotong University Chengdu China College of Computer Science and Technology Aba Teachers University Sichuan China Chongqing Prescholl Education College Chongqing China

Live Video Streaming (LVS) services are critical in supporting real-time applications in internet of Vehicles (IoV) by transmitting real-time generated video content from streaming server to mobile vehicles. However, due to restricted spectrum resources and high mobility of vehicles, LVS suffers from notable performance degradation. Accordingly, our paper investigates the problem of LVS-IoV by synthesizing multicasting and Scalable Video Coding (SVC)-based encoding techniques with the goal of maximizing Quality of Experience (QoE). We resolve the LVS-IoV by decoupling it into three sub-problems: vehicle grouping, quality selection, and resource allocation. Firstly, we propose a K-means-based mechanism for vehicle grouping that considers the geographical distribution and dynamic channels of vehicles. Secondly, we develop the Value Decomposition Network for quality selection which obtains the optimal reward with fast convergence via global value function decomposition and centralized training followed by distributed execution. Lastly, we propose a sub-gradient algorithm to achieve optimal resource allocation within a few iteration steps. We build simulation model and perform extensive evaluation, which demonstrates its superiority compared to other competitive methods.

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Electronic mail-based adaptive social graph for the conference

Electronic mail-based adaptive social graph for the conferen...

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international Workshop on Soft computing Applications (SOFA)

作者： Gabor Tolnai Department of Automation and Applied Informatics Budapest University슠of슠Technology슠and슠Economics Budapest Hungary

In the last few years many Web sites were created to build social networks. These sites have common behavior, for example they need their users to search and mark their friends, so those are the users who build the graph themselves. This graph is fixed from a certain point of view: the connections are binary connections and the graph consists of only the explicit data given by the users. In this paper we define a social network based on e-mails which is distributed and asymmetric. The key differences between this type of network and usual networks are that using this network we do not need to register to a specific Web site and we do not need to mark our friends. The social graph can be built automatically based on the mass of e-mails and the address book belonging to us. By analyzing this huge amount of data we can reveal the connections between our contacts and build a weighted graph. Besides this we can create a graph from the e-mails using the same data to improve the search results when looking for a specific e-mail or contact. These weighted graphs can be considered as neural networks. We can create an adaptive method to modify the connections in the graphs with implicit data gathered from the behavior of the user. Moreover, we can define a search algorithm on this type of graph based on the activation model of the neural networks. In this paper we show a way to build this kind of networks and we define an algorithm which finds similar elements to a specific item.

关键词： Electronic mail Social network services Books Neural networks Automation Informatics IP networks internet Protocols Message service

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An innovative Federated Learning paradigm for safeguarding privacy in IoT through a synergistic SDN-CLOUD Structure

An innovative Federated Learning paradigm for safeguarding p...

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Embedded Systems and Artificial Intelligence (ESAI), international conference on

作者： Harchi Anas Hicham Toumi Mohamed Talea Information Processing Laboratory Faculty of Sciences Ben M’sik University Hassan II Casablanca Morocco Higher School of Technology-Sidi Bennour Chouaïb Doukkali University El Jadida Morocco

ISBN: (数字)9798331522056

ISBN: (纸本)9798331522063

As global society increasingly transitions towards a comprehensive dependence on computational systems and digitization, the formulation of secure environments and connections emerges as one of the foremost challenges of this decade. The proliferation of threats confronting both individuals and organizations is escalating at an exponential rate, attributable to the burgeoning intricacy of contemporary networks and the ascendance of the internet of Things. Insufficient collaboration engenders a scenario wherein identical attacks are executed against disparate organizations in rapid succession. The dissemination of cyber threat intelligence is frequently proposed as a remedy to this predicament; however, it introduces distinct constraints pertaining to Data Safeguarding, traceability, and Integrity. To address this issue, a novel distributed architecture is put forth to augment the protective measures within the IoT landscape. This solution is predicated on federated learning algorithms aimed at constructing a distributed, self-governing system able to Identify intrusion and breaches through a synergistic SDNCloud Structure. This structural paradigm leverages the potential of SDN and cloud computing for IoT endpoints to enable effective and adaptable data analysis while concurrently maintaining user confidentiality. The adoption of federated learning simplifies a non-centralized model learning workflow, reducing data exposure and infringements by keeping private information confined to the IoT endpoints. Consequently, this methodology not only bolsters security but also promotes interdevice cooperation to confront the challenges in an exponentially interconnected.

关键词： Cloud computing Privacy Embedded systems Data analysis Federated learning Intrusion detection Organizations Data models Security internet of Things

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Access Control Mechanism in internet of Things using Blockchain technology: A Review

Access Control Mechanism in Internet of Things using Blockch...

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international conference on Intelligent Sustainable Systems (ICISS)

作者： Avani J. Dadhania Hiren B. Patel LDRP Institute of Technology and Research Gandhinagar India Vidush Somani Institute of Technology and Research Kadi India

ISBN: (数字)9781728170893

ISBN: (纸本)9781728170909

As the number and variety of connected objects continue to grow and the devices themselves become smarter, IoT has demonstrated to be the foremost rising innovation where millions of gadgets can interface to the web which makes the life attainable with no human intercession. However, the security and privacy of this IoT environment face some issues that must be overcome to meet the novel solution for IoT applications with no margin for error. Hence, secure architecture for centralized servers is necessitating maintaining the authenticity and protection of information. However, centralized architecture suffers from some challenges viz. reduction in performance, single point of failure and prone to attacks which could be addressed through decentralized or distributed architecture. Blockchain, being decentralized in nature, immutable in function, transparent in-process and reliable without a trusted third party, could be efficient attention for addressing IoT security challenges. In this research work the security concerns like access control mechanisms for IoT applications like smart city, smart healthcare system through Blockchain innovation is addressed. Blockchain being a distributed ledger provides an approach to securely store the data cryptographically. Specifically, proposed work intend to cover different access control methods for the protection of information and IoT security. This paper makes an exhaustive review of how decentralized architecture using Blockchain might potentially improve IoT access control.

关键词： Access control Blockchain internet of Things Security Computer architecture Authorization Peer-to-peer computing

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Design of distributed Task Scheduling in East China Power Market Trading System

Design of Distributed Task Scheduling in East China Power Ma...

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China international Electrical and Energy conference (CIEEC)

作者： XiaRgang Li Ping Shao Lin Cheng Min Wu Yuanrui Hong East China Branch Of State Grid Corporation Of China Shanghai China China Electric Power Research Institute Beijing China

ISBN: (数字)9781728116754

ISBN: (纸本)9781728116761

With the advancement of power reform, the scale of inter-provincial power trading in the East China region has been increasing, the scale of transactions has been expanding. More and more parameters are being considered, and the calculation processing logic is more and more complicated. In order to cope with the situation that the market rules change too fast and the complexity is too high, the East China Power Trading System will introduce a distributed technology architecture based on cloud computing and microservices. However, this process from the single-element architecture to the distributed architecture puts higher demands on the multi-task scheduling processing mechanism of the system. Based on the analysis of East China Power Market Trading Business and East China Power Market Trading System, this paper proposes a task scheduling solution based on distributed control strategy with reference to the solution ideas of the internet industry. It solves the scheduling problem of mutual exclusion tasks by using the improved Leader election method and effectively avoids the brain crack problem of the Leader election. Based on this distributed task processing strategy, this paper further elaborates the corresponding engineering solutions. It includes the specific implementation contents of task management interface, task scheduling center, task scheduling client and abnormal monitoring function in East China Power Market Trading System, so as to facilitate the practical application of system design and development personnel in system construction. In addition, the program also proved the feasibility of the program through stress testing and application practice.

关键词： power market trading system task scheduling distributed system TASK SCHEDULING power markets distributed Systems Mechanical systems

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