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检索条件"任意字段=2019 International Conference on Modeling, Simulation and Big Data Analysis（MSBDA 2019）"

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Exploring the research landscape of data warehousing and mining based on DaWaK conference full-text articles

Exploring the research landscape of data warehousing and min...

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作者： Timakum, Tatsawan Lee, Soobin Song, Min Department of Information Sciences Chiang Mai Rajabhat University Chiang Mai Thailand Department of Library and Information Science Yonsei University Seoul Korea Republic of

The international conference on data Warehousing and Knowledge Discovery (DaWaK) has become a pivotal place to exchange experiences and knowledge among researchers and practitioners in big data analytics. The conference has been essential to data warehousing and data analytics for the last 21 years (1999–2019). This study explored the knowledge structure embedded in the DaWaK conference papers and examined the research trends over time. It also analyzed the performance of published papers, authors, and their affiliations and countries and visualized a collaboration network in DaWaK. We applied several text mining techniques, including co-word analysis, topic modeling, co-author network analysis, and network visualization. The study's findings indicate that the core topics are data mining techniques, algorithm performance, and information systems. The popular topic trends are associated with database encryption, whereas the topics related to online analytical processing (OLAP) technology are in decline. The research metrics results demonstrate that the DaWaK papers were cited 6,262 times, with an h-index of 34 for the 722 DaWaK papers. The article titled "Outlier Detection Using Replicator Neural Networks" reached the most citations (177), and the most productive author was Bellatreche, Ladjel (15 papers). Nanyang Technological University is the most frequently mentioned as the author's affiliation, the United States is the country with the largest number of authors, and the National Science Foundation was the largest funding agency that supported the DaWaK researchers. Moreover, the authorship network of Bellatreche, Ladjel is the largest collaboration network in the DaWaK scholar community. The outcomes of this study would be beneficial for comprehending the knowledge in data warehousing and the relevant cross-disciplinary areas of research and collaboration networks in this field. © 2021 Elsevier B.V.

关键词： data warehouses

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3rd international conference on Wireless Communications and Applications,ICWCA 2019

3rd International Conference on Wireless Communications and ...

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3rd international conference on Wireless Communications and Applications,ICWCA 2019

ISBN: (纸本)9789811556968

The proceedings contain 28 papers. The special focus in this conference is on Wireless Communications and Applications. The topics include: Application of the Several Common Algorithms for Corner Detection to Sonar Image Registration;performance analysis of Interleaver for Polar Coding in Bit-Interleaved Coded Modulation System;research on Technology of Wireless Sensor Network;characteristics of Scholte Wave for Target Detection;visible and Infrared Image Fusion Based on Online Convolutional Dictionary Learning with Sparse Matrix Computation;optimization of Maintenance Force Dispatch of Artillery Command Information System Based on Mission Success;application of an Improved Genetic Algorithm in Tourism Route Planning;classification of Medical Symptoms Based on Social Sensors;research on Method and Technology of Emergency Logistics Intelligent System Engineering;research on Radio Base Station Distribution Technology in Transrapid System Communication;a Technical Survey on Approaches for Detecting Rogue Access Points;A Matching Algorithm Based on the Fusion of SAD and Census;evaluation Method of Vehicle Technology Status Based on big data analysis Technology;bay Number Recognition Based on Deep Convolutional Recurrent Neural Network;Deep Reinforcement Learning-Based Resource Allocation for Smart Grid in RAN Network Slice;identification of e-Nose Wine Varieties Based on Feature Extraction and Classification modeling;comparison of Contrast Enhancement Methods for Underwater Target Sonar Images;region Contraction-Based Sparse Approach for Magnetocardiography Current Source Imaging;the Differential Properties of the Metric Projector Over a Class of Closed Convex Cones;a Novel Node Scheduling Algorithm for Solar-Powered Wireless Sensor Networks;A USRP-Based Testbed of Multi-agent Reinforcement Learning for Dynamic Spectrum Anti-Jamming.

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Security analysis of Power System User Behavior in big data Based on Comparative of Neural Network Methods 5

Security Analysis of Power System User Behavior in Big Data ...

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5th IEEE international conference on big data Analytics (ICBDA)

作者： Guan, Ti Liu, Yong Wang, Hao Liang, Ye Jin, Xueqi State Grid Shandong Elect Power Co Jinan Peoples R China State Grid Elect Power Res Inst Beijing Peoples R China State Grid Zhejiang Elect Power CO LTD Hangzhou Peoples R China

ISBN: (纸本)9781728141114

In the context of exponential growth of data information, a large amount of data needs to be effectively processed in the power system intranet to analyze and obtain valuable information. Among them, user behavior is especially important for the security of the entire power system. With the development of large data technology and the wide application of machine learning technology, useful information can be extracted and processed from a large amount of unprocessed data. At the same time, in order to reasonably expand the data set of the relevant samples, traditional mathematical modeling can preprocess the data and integrate the classified output into the sample data set. Finally, this paper selects SSH data as the training set and Local data as the test set, and compares the accuracy of the four machine learning methods in predicting user behavior categories. The ultimate goal is to predict the level of risk of user behavior through the characteristics of user behavior.

关键词： User Behavior big data Mathematical modeling Machine Learning

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Graphical Model and Model Search for Medical data analysis 2nd

Graphical Model and Model Search for Medical Data Analysis

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2nd international conference on Power Engineering, Computing and Control, PECCON 2019

作者： Mehta, Naimish P. Menaka, R. Prasad, Arathy S. Aarthy, Thanga Vellore Institute of Technology Chennai India

ISBN: (纸本)9789811572401

Learning the electrophysiological activities inside the human mind is a significant step toward studying the human brain. Systems, such as electroencephalography, are significant instruments for considering the neurophysiologic activities, in view of their high value of temporal and spatial resolution. In the biomedical research, identifying brain abnormalities such as autism spectrum disorder through electroencephalography (EEG) signals is an extremely exhausting issue for specialists and human services experts. The high volume of data available with EEG will be a useful biomarker for the classification of autism and typical children. Traditional techniques face challenges to deal with such big data. So we present a strategy for autism identification by analyzing the EEG signal through mathematical model. One such modeling using graph theory is applied in this work. The EEG signals are acquired from 3 autism and 3 typical children. The functional connectivity among the neuron regions are plotted through small world networks. From this graphical models using a software tool Gephi, the graphical parameters as betweenness centrality, degree, weighted degree, closeness centrality, modularity, and clustering coefficient are calculated. There is significant difference among these parameters between autistic and typical children. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Electroencephalography

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simulation-Based analysis of COVID-19 Spread Through Classroom Transmission on a University Campus

Simulation-Based Analysis of COVID-19 Spread Through Classro...

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IEEE international conference on Communications (ICC)

作者： Hekmati, Arvin Luhar, Mitul Krishnamachari, Bhaskar Mataric, Maja Univ Southern Calif Dept Comp Sci Los Angeles CA 90007 USA Univ Southern Calif Dept Elect & Comp Engn Los Angeles CA 90007 USA Univ Southern Calif Dept Aerosp & Mech Engn Los Angeles CA 90007 USA

ISBN: (纸本)9781728194417

Airborne transmission is now believed to be the primary way that COVID-19 spreads. We study the airborne transmission risk associated with holding in-person classes on university campuses. We utilize a model for airborne transmission risk in an enclosed room that considers the air change rate for the room, mask efficiency, initial infection probability of the occupants, and also the activity level of the occupants. We introduce, and use for our evaluations, a metric R-0(eff) that represents the ratio of new infections that occur over a week due to classroom interactions to the number of infected individuals at the beginning of the week. This can be seen as a surrogate for the well-known R-0 reproductive number metric, but limited in scope to classroom interactions and calculated on a weekly basis. The simulations take into account the possibility of repeated in-classroom interactions between students throughout the week. We presented model predictions were generated using Fall 2019 and Fall 2020 course registration data at a large US university, allowing us to evaluate the difference in transmission risk between in-person and hybrid programs. We quantify the impact of parameters such as reduced occupancy levels and mask efficacy. Our simulations indicate that universal mask usage results in an approximately 3.6x reduction in new infections through classroom interactions. Moving 90% of the classes online leads to about 18x reduction in new cases. Reducing class occupancy to 20%, by having hybrid classes, results in an approximately 2.15 - 2.3x further reduction in new infections.

关键词： COVID-19 Epidemic modeling

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Performance analysis of VLC Indoor Positioning and Demonstration 2nd

Performance Analysis of VLC Indoor Positioning and Demonstra...

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2nd EAI international conference on big data Innovation for Sustainable Cognitive Computing, BDCC 2019

作者： Rishi Nandan, S. Kumar, Navin Department of Electronic and Communication Engineering Amrita School of Engineering Bengaluru Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9783030475598

Precise indoor positioning is a widely researched topic currently. Many existing or new radio devices and standards are being explored for this purpose. Existing infrastructure or technology is always advantageous as it might reduce the cost and at the same time can be used for other purposes. The emerging visible light communication (VLC) is another technology being researched for precise positioning, especially in the indoor environment. VLC can be designed on existing infrastructure or slightly modified systems, and positioning using VLC would find usage in real-life scenarios. In this positioning system, an object whose location needs to be determined must have a VLC receiver. In this work, a comparative study is performed for popular algorithms through simulation as well as hardware demonstration. Thorough analysis and simulation are performed for circular lateration, hyperbolic lateration, differential detection, and angulation;the hardware implementation and demonstration as a proof of concept (POC) is completed for circular lateration and differential detection. Both these models use received signal strength (RSS) to calculate distances. We use a single photodetector for implementing circular lateration whereas two photodetectors for demonstrating differential technique. We observe that the differential detection performs relatively better compared to circular lateration, that is, the error is reduced in differential detection. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Indoor positioning systems

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modeling of covid-19 in Indonesia using vector autoregressive integrated moving average 10

Modeling of covid-19 in Indonesia using vector autoregressiv...

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10th international conference and Workshop on High Dimensional data analysis, ICW-HDDA 2020

作者： Meimela, A. Lestari, S.S.S. Mahdy, I.F. Toharudin, T. Ruchjana, B.N. Department of Statistics Universitas Padjadjaran Jl. Raya Bandung Sumedang km 21 Jatinangor Sumedang45363 Indonesia BPS-Statistics of Sumatera Utara Province Jl. Asrama No 179 Medan20123 Indonesia Department of Mathematics Universitas Padjadjaran Jl. Raya Bandung Sumedang km 21 Jatinangor Sumedang45363 Indonesia

A phenomenon of coronavirus became a big deal around the world at the end of December 2019. To find out how deadly the disease is, we can use the Case Fatality Rate (CFR), which provides the ratio number of deaths due to covid-19 between founded cases number of covid-19. However, studies to see the relationship between the number of cases and the number of deaths caused by covid-19 in Indonesia rarely done. Time Series analysis that can see how the relationship between the number of cases and the number of deaths due to covid-19 in Indonesia is Vector Autoregressive Integrated Moving Average analysis (VARIMA). data used in this model must be qualified the stationary. For that reason, the transformation using differencing and logarithm on data must be performed to resolve non-stationary. The result shows the model that fulfilled all assumptions and had the smallest AICC value is VARIMA (1,1,1). The model shows the number of cases influenced by the number of cases and the number of deaths in the previous period. The same condition applies to the number of deaths affected by the number of deaths and the number of cases from the preceding period. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Time series analysis

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Design and Research of Cloud Virtual simulation Experiment Teaching Case in the Period of COVID-19 4

Design and Research of Cloud Virtual Simulation Experiment T...

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4th international conference on Education Technology Management, ICETM 2021

作者： Lu, He-Jun Liu, Juan The School of Big Data and Artificial Intelligence Anhui Xinhua University China College of Computing and Information Technologies National University Philippines

ISBN: (纸本)9781450385800

This paper uses VMware virtual machine and ghost technology to design virtual simulation experiment teaching case. In the Vmware virtual machine environment, the approach of project-led and task-driven is used to carry out for related experiments such as computer system construction, BIOS system application and security, hard disk management, operating system installation, system backup and restoration, image and cloning of partition and disk and so on. With OBE as the experimental teaching concept, a comprehensive virtual simulation experimental teaching case is designed. The teaching case design implements CDIO thinking, emphasizes process education, and cultivates the ability to analyze and solve problems. In the teaching process, the ideas of case conception, case design, case implementation, case operation and result analysis and summary are implemented. This virtual simulation experiment teaching case relies on the private cloud server platform in the school, adopts B / S architecture, and is shared and opened through internet, which can facilitate the implementation of online and offline experimental teaching, as well as experimental exercises and assessments. During the COVID-19 epidemic, it provides online experimental teaching environment and student training environment for relevant experimental teaching in courses such as "Computer System Security", "Information Security", "Computer System Maintenance", "Operating System and Application", "Computer Assembly and Maintenance"and other courses. It effectively solves the problems of inconvenience to carry out relevant experimental teaching through physical machine and the inability to carry out experimental teaching and conducting experiments online. It helps to improve the quality and effect of experimental teaching, increase the rate of experimentation and save experimental cost. © 2021 ACM.

关键词： COVID-19

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Development of the GIS Software Technology in the big data Era 9th

Development of the GIS Software Technology in the Big Data E...

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9th international conference on Frontier Computing, FC 2019

作者： Zhao, Fang College of Environment and Planning Henan University KaifengHenan475000 China

ISBN: (纸本)9789811532498

In the era of the big data, GIS faces the following challenges and opportunities: the efficient management of very large-scale data, including the data management system and architecture, the real-time processing and analysis of the stream data, and the efficient query and analysis of the historical data and patterns. Under the big data environment, GIS is in the environment of the large volume of the data, the rapid expansion of the data, the diverse data sources, the inaccurate data and the low value density of the data. This paper describes the salient features of the GIS data in the big data environment, discusses the challenges of the GIS technology in the data acquisition, storage, analysis and processing under the big data environment, and looks forward to the development trend of the storage de-structuring, the computing memory, the analysis de-modeling and the map holography in the face of these challenges. © 2020, Springer Nature Singapore Pte Ltd.

关键词： big data

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Verification and analysis of mobile communication network simulation method based on reverse coverage test 2

Verification and analysis of mobile communication network si...

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2019 2nd international Symposium on big data and Applied Statistics, ISBDAS 2019

作者： Liu, Yunyu Yu, Ming Tianjin University of Technology and Education No.1310 Dagu South Road Hexi District Tianjin300222 China Tianjin Sino-German University of Applied Sciences No.2 Yashen Road Tianjin Haihe Education Park Tianjin300350 China China Mobile Comm Tianjin Branch Tianjin300000 China

The common mobile communication network simulation method is to use the terminal to measure the downlink data of the base station and carry out the coverage simulation analysis of the mobile communication network. The test workload is large, the labor cost is high, and the accuracy deviation is *** distributed base station is used to test the uplink data of the terminal, and the wireless link algorithm is used to carry out the coverage simulation analysis of the mobile communication network, so as to collect big data and high precision. Combined with the high-speed distribution processing capacity of the new generation of mobile communication network, the network test, simulation and analysis can be *** verification and comparison, this method has many data sampling points, good real-time performance and high accuracy, and provides technical support for future automatic network planning and intelligent network optimization. © Published under licence by IOP Publishing Ltd.

关键词： Base stations

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