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cloudBrain-ReconAI: A cloud computing platform for MRI Reconstruction and Radiologists' Image Quality Evaluation

IEEE TRANSACTIONS ON cloud computing 2024年第4期12卷 1359-1371页

作者： Zhou, Yirong Qian, Chen Li, Jiayu Wang, Zi Hu, Yu Qu, Biao Zhu, Liuhong Zhou, Jianjun Kang, Taishan Lin, Jianzhong Hong, Qing Dong, Jiyang Guo, Di Qu, Xiaobo Xiamen Univ Natl Inst Data Sci Hlth & Med Biomed Intelligent Cloud R&D Ctr Dept Elect SciFujian Prov Key Lab Plasma & Magnet Xiamen 361102 Peoples R China Xiamen Univ Dept Instrumental & Elect Engn Xiamen 361005 Peoples R China Fudan Univ Zhongshan Hosp Xiamen Dept Radiol Xiamen 361015 Peoples R China Xiamen Univ Sch Med Xiamen 361004 Peoples R China Xiamen Univ Zhongshan Hosp Dept Radiol Xiamen 361004 Peoples R China China Mobile Grp Xiamen 361000 Peoples R China Xiamen Univ Technol Sch Comp & Informat Engn Xiamen 361024 Peoples R China

Efficient collaboration between engineers and radiologists is important for image reconstruction algorithm development and image quality evaluation in magnetic resonance imaging (MRI). Here, we develop cloudBrain-ReconAI, an online cloud computing platform, for algorithm deployment, fast and blind reader study. This platform supports online image reconstruction using state-of-the-art artificial intelligence and compressed sensing algorithms with applications for fast imaging (Cartesian and non-Cartesian sampling) and high-resolution diffusion imaging. Through visiting the website, radiologists can easily score and mark images. Then, automatic statistical analysis will be provided.

关键词： cloud computing platform image quality evaluation reader study image reconstruction artificial intelligence magnetic resonance imaging

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Development of personalized mobile information service platform of university library based on multi-core processor and cloud computing platform

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SOFT computing 2023年

作者： Li, Yingxin Shandong Univ Lib Jinan 250100 Shandong Peoples R China

In recent years, depending on information technology, knowledge and skills, university libraries have established a new "user-centered" data service system, which is called personalized information service. Although this service has made some progress in recent years, these systems have only achieved a certain amount of personalized information services. Multi-core processor is the basic process unit of high-performance cloud computing node, which is an important basis to achieve system security, high-performance, low-power consumption and other high-performance requirements. cloud computing node is one of the core components in the high-performance computer system architecture, in addition to the acceleration node, master control unit, communication system, etc., its efficiency has constituted an important basic condition for the realization of the "high efficiency" goal of the system. The emergence of multi-core processors and cloud computing platforms has created conditions for the development of personalized mobile information service platforms in university libraries. Under the technical support of multi-core processors and cloud computing platforms, it is also an important goal of mobile libraries in the future to meet the needs of users to search library data information at any time and provide users with diversified data services. At present, the knowledge service platform of university library can not only actively select and recommend relevant materials for users according to their knowledge preferences, data utilization habits and academic backgrounds, but also enable service users to quickly obtain the borrowing expiration prompt, independent consultation and retrieval and other personalized information functions, and carry out more in-depth personalized intelligent knowledge consulting services. Based on multi-core processor and cloud computing platform, this paper develops personalized mobile information service platform of university library.

关键词： Multi-core processor cloud computing platform University library platform development

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Operation Controllable Index Optimization of Virtual Power Plant with Electric Vehicle Based on 5g Technology and cloud computing platform 5th

Operation Controllable Index Optimization of Virtual Power P...

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5th EAI International Conference on Advanced Hybrid Information Processing (ADHIP)

作者： Qian, Ke-jun Gu, Shui-fu Yang, Yong-biao State Grid Jiangsu Elect Power Co Ltd Suzhou Power Supply Co Suzhou 215000 Peoples R China Southeast Univ Nanjing 210000 Peoples R China

ISBN: (纸本)9783030945541;9783030945534

For the controllable index optimization of virtual power plant with electric vehicles, the traditional optimization method has low environmental benefits due to the reduction of electricity sales and the use of more clean energy. Therefore, this paper proposes the controllable index optimization of virtual power plant with electric vehicles based on 5g technology and cloud computing platform. The cloud computing platform is used to calculate the deviation degree of controllable indexes of power plant operation and decompose the indexes, so as to allocate reasonable resources for the calculation of unit units. Taking the calculation results as the input parameters, an optimization model with power generation cost and environmental benefits as the objective is established. The membership function is used to solve the optimal solution of the model, and the controllable indexes are optimized The experimental results show that: Based on 5g technology and cloud computing platform, the controllable index optimization method of virtual power plant with electric vehicles has low power generation cost and high environmental benefits, which can meet the operation needs of virtual power plant with electric vehicles.

关键词： cloud computing platform Electric vehicle Virtual power plant Index optimization

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Smart grid data security storage strategy based on cloud computing platform 6

Smart grid data security storage strategy based on cloud com...

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6th International Conference on Smart Grid and Electrical Automation (ICSGEA)

作者： Jiang, Xin Yang, Qifan Ji, Wen Chen, Yanshu Cai, Yuxiang Li, Xiaoming State Grid Fujian Elect Power Co Ltd Informat & Commun Branch Fuzhou 350001 Peoples R China

ISBN: (纸本)9781665432634

Aiming at the security problems of traditional smart grid data security storage strategy, this paper proposes a smart grid data security storage strategy based on cloud computing platform. Based on the analysis of cloud computing and cloud storage, the security storage of smart grid data is modeled to improve the security storage performance of power system. The dynamic key mechanism is introduced to obtain the initial key information in the key chain and generate the dynamic secret key. The hyperchaotic system is used to obtain the modified bit plane code in the key chain to form the context and decision of data storage. MQ arithmetic encoder is used for entropy coding to generate the corresponding data storage compressed code stream, and the smart grid data storage key is improved. Combined with encryption processing and decryption processing, the secure storage of smart grid data is realized. The experimental results show that the smart grid data security storage strategy based on cloud computing platform increases the security of smart grid data storage.

关键词： cloud computing platform smart grid grid data secure storage strategy

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Anomaly detection method of power dispatching data based on cloud computing platform

Anomaly detection method of power dispatching data based on ...

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International Conference on Big Data and Artificial Intelligence and Software Engineering (ICBASE)

作者： Jie, Lu Liu Xiangxiang Li Haoxiang State Grid Jiangxi Elect Power Co Ltd Power Supply Serv Management Ctr Nanchang Jiangxi Peoples R China State Grid Jiangxi Elect Power Co Ltd Nanchang Jiangxi Peoples R China

ISBN: (纸本)9781728196190

The traditional power dispatching data anomaly detection method USES the principle of template matching, which not only has large calculation amount and long processing time, but also the accuracy of the detection method is greatly affected by the template. Aiming at the above problems, the anomaly detection method of power dispatching data based on cloud computing platform is studied. The power demand of residents in the grid is analyzed to determine the load response of residential electricity. To process the detected power dispatching data, the cloud computing platform is used to cluster the processed data and the electricity demand response data to complete the detection of abnormal data. Through the comparison experiment with the traditional power dispatching data anomaly detection method, it is verified that the detection method based on the cloud platform saves about 1.3 times of the detection time, and the detection accuracy of abnormal data is higher.

关键词： cloud computing platform Power dispatching Data anomaly Abnormal detection

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WEB Protection Scheme Based on A cloud computing platform 5

WEB Protection Scheme Based on A Cloud Computing Platform

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5th IEEE International Conference on Big Data Analytics (ICBDA)

作者： Liao Rongzhou Xiao Nanfeng South China Univ Technol Sch Comp Sci & Engn Guangzhou 510006 Peoples R China

ISBN: (数字)9781728141114

ISBN: (纸本)9781728141114

The management of the cloud computing platform adopts web interface, the web is open and easy to use, which makes the security problems of the cloud computing platform be increased prominently. The web security problems have a variety of attack forms, the main-stream attack methods include SQL injection, cross-site scripting (XSS), and HTTP header injection attacks, and so on. For solving these security problems, this paper designs a reason-able security protection scheme based on some defense methods. For SQL injection attack and XSS attack, the web protection scheme based on the cloud computing platform is designed and implemented in this paper, and proposes a typical defense method for the SQL injection attacks, designs the SQL injection filters and conducts the verification. For the XSS attacks, design a reasonable and feasible defense scheme to achieve the main defense functions, and study the characteristics of other web attacks, and briefly give the corresponding defense methods. This paper also designs the experimental environments, the experimental results show that the proposed protection schemes are effective to the corresponding attack methods.

关键词： cloud computing platform web security SQL injection XSS attack

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cloud computing platform Design and Machine Learning-Based Fault Location Method in Automatic Dispatching System of Smart Grid 6th

Cloud Computing Platform Design and Machine Learning-Based F...

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6th International Conference on Communications, Signal Processing, and Systems (ICCSPS)

作者： Guo, Ziming Guo, Haibo Mu, Yongzheng Peng, Yuexing Li, Xinpeng Gao, Xin Liu, Yong State Grid Jibei Elect Power Co Ltd Beijing Peoples R China Beijing Univ Posts & Telecommun Minist Educ Key Lab Universal Wireless Commun Beijing Peoples R China State Grid Tangshan Power Supply Co Tangshan Hebei Peoples R China

ISBN: (纸本)9789811065712;9789811065705

In order to improve the effectiveness and efficiency of automatic dispatching of smart grid, fully exploiting the monitoring data and mining the inherent relation among the data are the key to the grid state monitoring, abnormality prediction and fast fault location for automatic dispatching service of the smart grid. With the rapid increase of grid scale and the type and volume of the monitoring data, distributed storage and computing-based cloud computing platform becomes the basic infrastructure of smart grid. In this paper, after the structure and function analysis of the current management and dispatching platform D5000, a cloud computing platform is designed and integrated into the D5000 platform. This cloud computing platform is constructed hierarchically, in which the Hadoop performs distributed data storage and computing via HDFS and MapReduce, while Spark implements data mining with the aid of Spark SQL when frequent data exchange and data computing is required. The data mining task includes modeling the state of the automatic dispatching subsystem, making early warning, and locating faults, for which machine learning-based algorithms are developed. The feasibility of the designed platform and the effectiveness of the proposed methods are verified.

关键词： cloud computing platform Machine learning Smart grid

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Design and Implementation of a Time Prediction Model for LS-DYNA cloud computing platform 2020

Design and Implementation of a Time Prediction Model for LS-...

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Proceedings of the 2020 9th International Conference on computing and Pattern Recognition

作者： Wenqian Zhang Qingzheng Xu Mingjun Zhao Jianhang Zhang Na Wang College of Information and Communication National University of Defense Technology Xi'an China College of Information and Communication National University of Defense Technology Xi'an China and Youth Innovation Team of Shaanxi Universities National University of Defense Technology Xi'an China

ISBN: (纸本)9781450387835

cloud computing can handle huge amounts of data in a very short time, so as to build a powerful network service capability. However, the existing cloud computing platform (e.g. LS-DYNA) cannot predict the calculation time and then provide appropriate reference conditions for users. Furthermore, the relationship between calculation time and hardware configuration are not always negative correlation. In this paper, the design idea of time prediction model is first put forward. Specifically, the correlation between the hardware conditions of the relevant historical model and the calculation time is set as the training set. Following this idea, a more accurate time prediction model is built and further improved. In this paper, regression analysis is adopted and four core steps are generally required to establish the regression equation, including curve estimation, automatic linear modeling, regression analysis and Durbin-Watson test. When compared with the original LS-DYNA, experimental results fully demonstrate the effectiveness of the proposed method for its small prediction error.

关键词： calculation time LS-DYNA cloud computing platform time prediction model

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Research on Management Accounting Information Construction with cloud computing platform as the Core

Research on Management Accounting Information Construction w...

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作者： Zhang Hui Chengdu Agricultural College Economics and Management Branch

the World Civilization Has Experienced Three Industrial Revolutions in Total. cloud computing Technology is the Representative Technology in the Third Industrial Revolution. the Birth and Development of cloud computing Technology Has Changed People's Daily Life and Enterprise Management. cloud computing Technology Can Provide a Better Fusion Place for Information Technology and Management Accounting. in View of This, This Paper Studies and Analyzes the Advantages of the Development of Management Accounting Information, Discusses the Construction of cloud computing Management Accounting platform, and Studies and Analyzes the Points That Need to Be Paid Attention to in the Process of the Integration of cloud computing platform and Management Accounting Information, and Puts Forward Several Optimization Measures and Implementation Strategies on This Basis.

关键词： cloud computing platform Management Accounting Information Construction

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The research of multimedia cloud computing platform data dynamic task scheduling optimization method in multi core environment

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MULTIMEDIA TOOLS AND APPLICATIONS 2017年第16期76卷 17163-17178页

作者： Wu, Qiong Qin, Guihe Huang, Biaobing Jilin Univ Coll Comp Sci & Technol Changchun 130122 Peoples R China Changchun Univ Technol Coll Humanities & Informat Changchun 130122 Peoples R China

In cloud computing platform, current data scheduling algorithm cannot make full use of bandwidth resources of nodes in multi-core environment, resulting in heavy server load and play discontinuity of multimedia files, thus, a multimedia cloud computing platform data dynamic task scheduling method is proposed, on the basis of the related theory of multi-core processor, the system model and multimedia cloud computing platform data dynamic task model are established, multimedia cloud computing platform data dynamic task scheduling strategy is introduced based on the models, and gives assumed conditions of task scheduling strategy design, the priority calculation stage, improved particle swarm task scheduling stage and mapping stage from the task to processor are passed through to complete the analysis of this strategy, the tasks are distributed to the processor in accordance with certain rules, and dynamic task scheduling results are given and optimized. The simulation experimental results show that the proposed method has very high scheduling performance.

关键词： Multi-core environment Multimedia data cloud computing platform

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