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检索条件"任意字段=2nd International Conference on Computational Modeling, Simulation and Data Analysis, CMSDA 2022"

共 201 条记录，以下是111-120 订阅

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Research on the application of virtual simulation technology in law experiment teaching under the background of educational informatization

Research on the application of virtual simulation technology...

引用

Information Science and Education (ICISE-IE), international conference on

作者： Guohui Cai Science and Technology College Gannan Normal University Ganzhou China

ISBN: (纸本)9781665438308

Virtual simulation system law teaching system usually adopts multi-level technology and modular technology, which makes the teaching system have good scalability, allows users to carry out practical a operation in actual law teaching, and adds new experimental teaching modules at the same time. The goal of establishing law laboratory is to create a diversified and systematic teaching environment. Based on computer technology, make full use of virtual simulation technology to establish three- dimensional legal model and construct virtual simulation legal experiment system. It can further realize the data analysis of virtual simulation technology and law teaching. The laboratory system has a complete data protection mechanism. All data confidence in the system will be backed up by the system, using incremental backup and stage overall backup model. It can better preserve the data information and operation process generated in the process of law experiment teaching, and Hitler can quickly restore even if data loss occurs.

关键词： Solid modeling Technological innovation Information science Systematics Law computational modeling Scalability

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PharmaLab: A Tool to Study the Drug Action on the Mouse Ventricular Myocyte 2

PharmaLab: A Tool to Study the Drug Action on the Mouse Vent...

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2021 2nd international Symposium on Automation, Information and Computing, ISAIC 2021

作者： Camargo, M.L.A. Goroso, D.G. Bissaco, M.A.S. Silva, R.R. Research and Technology Center University of Mogi das Cruzes SP Mogi das Cruzes Brazil Human Motor Skill Analysis Laboratory FACDEF/National University of Tucumán Tucumán Argentina LabNECC Center for Biomedical Engineering University of Campinas SP Campinas Brazil

Mathematical and computational modeling has been a great ally in the development of new drugs. It helps by providing preliminary results that ultimately guide the path that the tests should take. Thus, the objective of this work was to develop the PharmaLab computational tool, which simulates the pharmacological action in the mouse ventricular myocyte using the mathematical model of Mullins & Bondarenko (2013). Having as one of the main differentials the integration with a model for the force of contraction, at PharmaLab it is possible to perform pharmacological tests by changing parameters of the mathematical model and registering drugs to be used in the simulations. The computational tool has its own interface for plotting results and support material for educational use. As a demonstration of the tool, a validation was performed, comparing simulations with experimental data for the drug Niferidil and two "in silico"tests: SS-68 correcting the "Catecholaminergic Polymorphic Ventricular Tachycardia"(CPVT) and Niferidil correcting the Short QT Syndrome (SQTS). The drugs showed good results in the correction of arrhythmias. Finally, it can be concluded that the PharmaLab computational tool has resources for use in both research and teaching. © Published under licence by IOP Publishing Ltd.

关键词： computational methods

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Multiscale modeling of Mechanotransduction Processes in Flow-Induced Platelet Activation

Multiscale Modeling of Mechanotransduction Processes in Flow...

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IEEE international conference on Big data Security on Cloud (BigdataSecurity), High Performance and Smart Computing (HPSC) and Intelligent data and Security (IDS)

作者： Chao Gao Peng Zhang Danny Bluestein Department of Biomedical Engineering Stony Brook University Stony Brook NY

Shear induced platelet activation is the major cause of thrombus formation in cardiovascular diseases and prosthetic devices. A novel multiscale modeling approach based on discrete particle methods permits the investigation of such complex phenomena by coupling the macroscopic flow conditions with the cellular and molecular effects of platelet activation. However, such a modeling approach poses a major computational challenge, where a typical simulation involves the computation and communication of millions of particles. The large computational requirement was fulfilled with the assistance of the state of the art high performance computing facilities. In this paper, we first present our multiscale model of shear-induced platelet activation, where the blood plasma and platelet were modeled by dissipative particle dynamics (DPD), and coarse grained molecular dynamics (CGMD), respectively. We then employ the blood plasma-platelet interaction model to study the platelet flipping dynamics and mechanotransduction process of platelet activation. To achieve the best performance of our model on supercomputers, we conduct the performance analysis by scaling our blood plasma model with 20 million particles to 10, 000 CPU cores on Sunway bluelight system. The simulation results suggest that our multiscale model of shear-induced platelet activation can fully achieve fluid-platelet interaction across micro-and nano-scales, and can achieve good strong scalability running on the system with large number of processors.

关键词： Fluids computational modeling Stress Mathematical model Fluid flow Blood Heart

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Research on Influence Factors of Prevention and Control Measures on Economy-based on Netlogo simulation and Big data Computation

Research on Influence Factors of Prevention and Control Meas...

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Social Sciences and Intelligent Management (SSIM), IEEE international conference on

作者： Yanling Zhou Xiaoxuan Shen Jing Cao Yunxiang Zhang Artificial Intelligence and Big Data College Hefei University Hefei China

ISBN: (纸本)9781665498319

Emergencies have a significant impact on the economy. Thus, effective prevention and control measures can reduce economic losses to the greatest extent. Taking the novel coronavirus outbreak as the starting point, we proposed the SEEIR-E model, an optimization model of the SEIR. The model compares two different prevention and control modes, “fence mode” and “free-range mode” Combined with the big data of the epidemic, systematic simulation and analysis were carried out in the Netlogo simulation environment. When environmental factors are the same, the “fence model” can control the spread of the disease more quickly, and the economic impact is less. At the same time, the impact of various environmental factors on economic recovery was simulated and analyzed. The result provides a basic understanding in economic recovery after the epidemic.

关键词： Economics COVID-19 Epidemics Analytical models computational modeling Sociology data models

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Topic modeling on Customer Feedback from an Online Ticketing System using Latent Dirichlet Allocation and BERTopic

Topic Modeling on Customer Feedback from an Online Ticketing...

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Information and Computing Research (iCORE), international conference in

作者： Charmaine S. Ponay College of Information and Computing Sciences University of Santo Tomas College of Computing and Information Technologies National University Manila Philippines

This project aims to use Topic modeling on Customer Feedback from an Online Ticketing System using Latent Dirichlet Allocation and BERTopic. The experiment started with analysis of the Topics generated from a base LDA model and computing its coherence score and fine-tuning the LDA model and comparing the coherence score with the base Model. It was found that the fine-tuned LDA model increased the cohesion score by 8.33%. This project also explored the use of BERTopic, using the multilingual model and found that it was able to extract Tagalog words from the data composed of English and Tagalog. As such, BERTopic can be further experimented on using data with more relevant Tagalog words. Also, using human judgements or “eye-balling” techniques, it was able to evaluate that the topic distribution generated by both the LDA and BERTopic model was able to capture the information needed by the organization.

关键词： Analytical models computational modeling Coherence Organizations data models Resource management data mining

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The Method of Processing Abnormal Values for Flight Test data Based on Wavelet Transform

The Method of Processing Abnormal Values for Flight Test Dat...

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Electronic Information Engineering and Computer Technology (EIECT), international conference on

作者： Jingxiang Xu Lei Zuo Zheng Zhao National Laboratory of Radar Signal Processing Xidian University Xi’an China State Key Laboratory of Experimental Physics and Computational Mathematics Beijing China

In the flight test data, there usually are abnormal values due to uncertainties in acquisition, storage and transmission. Processing the abnormal values is essential to ensure the accuracy of subsequent test data analysis. In this paper, we propose an abnormal value processing method based on wavelet transform for flight test data. We use the summation of high- frequency wavelet details as the characteristic quantity for abnormal value detection. Moreover, the detection threshold is constructed based on the idea of constant false alarm detection to locate and process the abnormal values. simulation results show that the method can detect and process the abnormal values in the time-series flight test data fast and accurately.

关键词： Wavelet transforms Uncertainty data analysis simulation Feature extraction Robustness High frequency

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A new optimal cost model of queue systems with Heavy-Tailed distribution

A new optimal cost model of queue systems with Heavy-Tailed ...

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international conference on Information Science and Engineering (ICISE)

作者： Sen Qin School of Science Hangzhou Dianzi University Hangzhou China

ISBN: (纸本)9781424476169

The heavy-tailed characteristic has been emerged in the distributions of Internet flow sizes, web pages and computer files. So the M/Heavy-Tailed/K queue system is the highlight of the research of queue systems. In this paper, it is firstly proved that the efficiency of multiple servers is equal to the single server when all of servers work with full load. Then, with the cost objective function, the optimal number of servers for the queue systems is presented with three heavy tailed distributions, which are the bimodal distribution, bounded Pareto distribution and power-law distribution. An event-driven simulator for queuing systems is proposed to the simulation of the M/HT/K queue systems. According to theoretical analysis and numerical simulation, the optimal number of servers for the M/HT/K system with cost objective function is less than that of system with the average response time as its objective function. It implies that the latter model emphasizes the optimization of the response time, not the optimal cost which is the key of the former system.

关键词： Servers Time factors Load modeling data models computational modeling Biological system modeling Optimization

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K-Means Clustering Algorithm with Refined Initial Center

K-Means Clustering Algorithm with Refined Initial Center

引用

international conference on BioMedical Engineering and Informatics (BMEI)

作者： Xuhui Chen Yong Xu School of Computer and Communication Lanzhou University of Technology Lanzhou China

ISBN: (纸本)9781424441327

K-means algorithm is a popular method in clustering analysis. After reviewing the traditional K-means algorithm, we proposed an improved K-means algorithm. At first we select the Euclidean distance or Manhattan distance as distance measure in our algorithm through calculating the rule of distance measure. Different initial centroids lead to different results. So the next step we will select the initial centroids which are consistent with the distribution of data. According to simulation, the improved K-means algorithm has can achieve higher accuracy and stability than the traditional ones.

关键词： Clustering algorithms Partitioning algorithms Euclidean distance Algorithm design and analysis computational modeling Stability data mining Pattern recognition Image segmentation NP-hard problem

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Privacy protection beyond encryption for cloud big data

Privacy protection beyond encryption for cloud big data

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international conference on Information Technology and Electronic Commerce

作者： Hongbing Cheng Weihong Wang Chunming Rong College of Computer Science Zhejiang University of Technology Hangzhou China Department of Computer Science University of Stavanger Stavanger Norway

ISBN: (纸本)9781479953004

As the paradigm of future information technology architecture, cloud computing has been a hot issue since it emerged. However, data privacy protection is perceived as the most important challenge that cloud tenants concern, and conventional protection technology sometimes can not be applied to cloud data efficiently. In this paper, a scheme is proposed to protect the tenants' data privacy in cloud computing beyond encryption. In the scheme, in order to protect the data privacy which will be stored in the cloud, tenants only need to do some hash operations on privacy data rather than encryption. analysis and simulation experiment results show that the proposed scheme can protect the tenants' data privacy efficiently.

关键词： Cloud computing Big data data privacy Security computational modeling data models Computer architecture

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Intelligent electricity consumption forecasting and electricity-theft analysis method based on deep learning

Intelligent electricity consumption forecasting and electric...

引用

Electronic Information Engineering and Computer Technology (EIECT), international conference on

作者： Shimao Yu Chunhe Song Pengpei Gao Haiyang Zheng Key Laboratory of Networked Control Systems Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China

Residential electricity consumption data have great mining value for electricity-theft analysis and electricity consumption forecasting. This paper designs an intelligent electricity consumption forecasting and electricity-theft analysis method based on deep learning. Firstly, the power consumption data of a single user is converted into multi-period data through preprocessing, and the data forecasting is realized by designing a deep neural network model. The electricity-theft data are first amplified through user’s power data and electricity-theft labels. And then the time series are converted into two-dimensional tensors for classification and recognition by deep CNN. The classification accuracy of electricity-theft reaches 92.2% compared with RNN method.

关键词： Deep learning Training Analytical models Power demand Tensors computational modeling Time series analysis

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