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IEEE 18th international conference on E-Science (E-Science)

作者： Ejarque, Jorge Andrio, Pau Hospital, Adam Conejero, Javier Lezzi, Daniele Gelpi, Josep Ll Badia, Rosa M. Barcelona Supercomp Ctr BSC CNS Barcelona Spain Inst Res Biomed IRB Barcelona Spain Univ Barcelona Dept Biochem & Mol Biomed Barcelona Spain

ISBN: (数字)9781665461245

ISBN: (纸本)9781665461245

Developing complex biomolecular workflows is not always straightforward. It requires tedious developments to enable the interoperability between the different biomolecular simulation and analysis tools. Moreover, the need to execute the pipelines on distributed systems increases the complexity of these developments. To address these issues, we propose a methodology to simplify the implementation of these workflows on HPC infrastructures. It combines a library, the BioExcel Building Blocks (BioBBs), that allows scientists to implement biomolecular pipelines as Python scripts, and the PyCOMPSs programming framework which allows to easily convert Python scripts into task-based parallel workflows executed in distributed computing systems such as HPC clusters, clouds, containerized platforms, etc. Using this methodology, we have implemented a set of computational molecular workflows and we have performed several experiments to validate its portability, scalability, reliability and malleability.

关键词： data analysis Runtime Biological system modeling Scalability Pipelines Libraries Reliability

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Power quality and modeling analysis of a university campus electrical distribution system

Power quality and modeling analysis of a university campus e...

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2022 IEEE international conference on Electrical, Computer, and Energy Technologies, ICECET 2022

作者： Ferrolho, Cesar Barata, Filipe Gamboa, Paulo Lisboa Portugal INESC-ID Lisboa Portugal

ISBN: (数字)9781665470872

ISBN: (纸本)9781665470872

For a few years now, electrical power quality has been a topic of interest and discussion, mainly due to issues regarding costs, continuity of service and electrical installation energy efficiency. The lack in electrical power quality can reveal itself in different ways, in reactive power costs, in frequent tripping of protections, in overheating and overloads of equipment and cables, in the significant shortening of capacitor lifespans, and, on power grid resonance events. This paper makes an electrical power quality analysis on Instituto Superior de Engenharia de Lisboa (ISEL) school campus, more precisely, two transformer substations and several building electrical distribution boards that make up the campus' electrical power grid. The acquired data enabled the graphical display of several electrical parameters, and their subsequent quantitative and qualitative analysis, regarding legislation and standards, namely, NP EN 50160;IEC 61000-2-3 and IEEE Std 1159-2019. In the paper, a Matlab/Simulink model of ISEL campus' electrical power grid was developed, so that, when anomalies are identified, it will be possible to analyze and verify, through simulation, the effect that different solutions produce to mitigate them. © 2022 IEEE.

关键词： Energy efficiency

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Research on Parallel Attribute Exploration Algorithm Based on Unrelated Attribute and Intent Sets 13th

Research on Parallel Attribute Exploration Algorithm Based o...

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13th European-Alliance-for-Innovation (EAI) international conference on simulation Tools and Techniques (EAI SIMUtools)

作者： Han, Daojun Chen, Wan Zuo, Xianyu Henan Univ Henan Key Lab Big Data Anal & Proc Kaifeng Henan Peoples R China Henan Univ Sch Comp & Informat Engn Kaifeng Henan Peoples R China

ISBN: (纸本)9783030971243;9783030971236

The attribute exploration algorithm is an important knowledge discovery tool for obtaining the stem basis and intent of a given formal context in formal concept analysis. However, when the scale of the formal context is large, the traditional attribute exploration algorithm and the improved attribute exploration algorithm still traverse the attribute sets in the lexicographical order, which leads to the calculation process of the algorithm is too time-consuming. It seriously hinders the promotion and application of the current big data era. The time-consuming bottleneck mainly exists in the link of "traversing attribute sets in the lexicographic order". To solve this problem, first, we construct a prefix dictionary tree in the inverse linear order of the attribute sets in the inter-layer cardinality order and use the irrelevant definition. Second, we propose and prove three theorems by the above definition and formal concept analysis. Third, according to these theorems, we put forward a new parallel attribute exploration algorithm based on attribute and intent sets. In the process of calculating intent and pseudo-intent sets, the algorithm skips the computing process of attribute sets which are intent sets and neither intent nor pseudo-intent sets with the help of these proposed theorems and reduces search space of the algorithm and the scale of implication calculation, so as to reduce the time complexity. Experimental results show that the worst time complexity of the algorithm is Op(M-2 x max(P, G)) . Compared with the improved algorithm, this algorithm has obvious time performance advantages.

关键词： Formal concept analysis Stem base Intent Parallel attribute exploration Lexicographic order Knowledge discovery

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Fault Diagnosis of Hydraulic System of Aircraft Landing Gear Based on CNN-SVM

Fault Diagnosis of Hydraulic System of Aircraft Landing Gear...

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2022 international conference on Intelligent Transportation, big data and Smart City, ICITBS 2022

作者： Feng, Dongyang Jiang, Chunying Lu, Mowu Li, Shengyu Ye, Changlong Shenyang Aerospace University The School of Mechanical and Electrical Engineering Shenyang110136 China Shenyang Aerospace University The School of Computer Science Shenyang110136 China

ISBN: (纸本)9781665497213

Aiming at the difficulty of extracting fault features on the aircraft landing gear hydraulic system, traditional feature extraction methods rely heavily on expert knowledge, and the accuracy of fault diagnosis is difficult to guarantee. This paper combined convolutional neural network (CNN) and support vector machine classification algorithm (SVM) to propose a fault diagnosis model suitable for aircraft landing gear hydraulic system. The diagnosis model adopted the one-dimensional multi-channel CNN network structure, took the original pressure signal of multiple nodes as input, adaptively extracts the feature value of the pressure signal through CNN, and built a multi-feature fusion layer to realize the feature fusion of the pressure signal of each node. Finally, input the fused features into the SVM classifier to complete the fault classification. In order to verify the proposed fault diagnosis model, a typical aircraft landing gear hydraulic system simulation model was built based on AMESim, and several typical fault types such as hydraulic pump leakage, actuator leakage, selector valve clogging and accumulator failure were simulated, and corresponding Fault type data set, and use overlapping sample segmentation for data enhancement. Experiments show that the diagnosis accuracy of the proposed fault diagnosis algorithm can reach 99.25%, which can realize the adaptive extraction of the fault features of the aircraft landing gear hydraulic system, and the features after multi-dimensional fusion have better discrimination, compared with traditional feature extraction methods more effective and more accurate. © 2022 IEEE.

关键词： Failure analysis

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A Personalized Recommendation Strategy Based on Emotional analysis and Forgetting Rule

A Personalized Recommendation Strategy Based on Emotional An...

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2022 international conference on Computer, Artificial Intelligence, and Control Engineering, CAICE 2022

作者： Lu, Zhubing Ma, Xiaoqin Wu, Wenjuan College of Economy Management Southwest University Chongqing400715 China College of Big Data and Artificial Intelligence Chi Zhou University Anhui 247000 China Central library of Southwest University Chongqing400715 China

ISBN: (纸本)9781510655942

In traditional collaborative filtering recommendation system, drawbacks such as interest drift and data sparseness always exist, which has weakened performance of the system. In this paper, a novel approach from the perspective of emotion analysis and forgotten rules was proposed to offset the influence on recommendation accuracy caused by interest migration. Firstly, user online comment has been analyzed to extract emotional words and the rated object using optimized DP algorithm. Secondly, the emotional words about the rated object have been appropriate quantified so that we can take advantage of the user emotional tendency to generate interest model. Thirdly, the Ebbinghaus forgetting curve is also introduced into the recommendation process to overcome the problem that caused by the change of user interest, which can effectively increase the accuracy and offer user better service when interest move. The simulation experiment shows that the strategy could greatly reduce MAE and effectively improve coverage. © 2022 SPIE.

关键词： Recommender systems

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Household Structure Projection Using Monte-Carlo simulation and Its Effectiveness analysis in an Infectious Disease Transmission Model 1

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12th international conference on simulation and modeling Methodologies, Technologies and Applications, SIMULTECH 2022

作者： Chang, Hung-Jui Goh, Wei-Ping Tsai, Shu-Chen Lin, Ting-Yu Chang, Chien-Chi Pan, Mei-Lien Wang, Da-Wei Hsu, Tsan-sheng Department of Computer Science and Information Engineering National Dong Hwa University Taiwan Institute of Information Science Academia Sinica Taiwan Information Technology Service Center National Yang Ming Chiao Tung University Taiwan

ISBN: (数字)9783031438240

ISBN: (纸本)9783031438233

The high quality of simulation systems depends on precise input parameters. The underlying population model is crucial for an agent-based simulation system that studies the spread of infectious diseases. To build the population model, the system requires a household structure (HSD) of the simulated area, including a household list with recorded age information for each member. Previous research has shown that changes in household structure significantly impact disease-spreading patterns. However, with the increasing frequency of severe infectious diseases like SARS (the year 2002), H1N1 (the year 2009), and COVID-19 (the year 2019), using outdated HSD data is inappropriate. This paper proposes a Monte-Carlo-based approach to approximate the HSD for a given year using aggregated information from a range of years. The validation of our algorithm shows good matches with different diseases. As a result, we obtained an HSD for 2020 to study the spread of new COVID-19 variants and future outbreaks. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： COVID-19

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Automatic Gaussian Bandwidth Selection for Kernel Principal Component analysis 1

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16th international conference on Knowledge Science, Engineering and Management (KSEM)

作者： Shen, Kai Wang, Haoyu Chaudhuri, Arin Asgharzadeh, Zohreh SAS Inst Inc Cary NC 27513 USA

ISBN: (数字)9783031402838

ISBN: (纸本)9783031402821;9783031402838

Kernel principal component analysis (KPCA) has been proved to be useful in many applications as a dimension reduction technique. Compared with PCA, KPCA better exploits the complicated spatial structure of high-dimensional features. Because of the high computational cost of exact KPCA, however, research has focused on the fast computation of KPCA, through techniques such as matrix sketching, the Nystrom method, and random Fourier features. There has been little discussion of the selection of kernel bandwidth, which is critical in practice. In this paper, we propose a new data-driven bandwidth selection method, called the criterion of the maximum sum of eigenvalues (CMSE) method and a scalable variation (SCMSE) to handle big data. Both feature high time efficiency and achieve performance better than or comparable to that of the existing methods. We conduct both simulation study and real-world data analyses to support our conclusions.

关键词： Kernel PCA Gramian matrix Pre-image problem Reconstruction error Gaussian kernel bandwidth selection

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Design and analysis of Two Efficient Socialist Millionaires’ Protocols for Privacy Protection 1

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7th international conference on Smart Computing and Communication, SmartCom 2022

作者： Liu, Xin Liu, Xiaomeng Tu, Xiaofen Xiong, Neal School of Information Engineering Inner Mongolia University of Science and Technology Inner Mongolia Baotou014010 China National Engineering Research Center for E-Learning Central China Normal University Wuhan430079 China Department of Computer Science and Mathematics Sul Ross State University AlpineTX79830 United States

ISBN: (数字)9783031281242

ISBN: (纸本)9783031281235

Yao's Millionaires’ problem has led to the emergence of secure multi-party computation. As an important tool for privacy protection in cryptography, secure multi-party computation has attracted more and more scholars to study it. The socialist millionaires’ problem is the basic module of the secure multiparty computing protocol. Designing secure and efficient solutions for the socialist millionaires’ problem can be effectively applied to the secret ballot, electronic auction, and so on. Based on the vector encoding method, the Paillier encryption scheme, and the Goldwasser-Micali encryption scheme, two efficient socialist millionaires’ protocols are proposed and the protocols are analyzed. The correctness analysis, security proof, performance analysis, and experimental simulation show that the efficiency of the two protocols is superior to the existing schemes. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Cryptography

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Application of Uncertainty analysis in Evaluation of Marine Engine Simulator 3

Application of Uncertainty Analysis in Evaluation of Marine ...

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3rd international conference on modeling, simulation, Optimization and Algorithm, ICMSOA 2021

作者： Shen, Henglong Cao, Hui Liang, Shiyuan Marine Engineering College Dalian Maritime University Liaoning Dalian China

Aiming at the problem of fuzziness and randomness in the evaluation process of marine engine simulator, a comprehensive evaluation model based on subjective and objective combination weighting method and cloud model method is established on the basis of single subjective and objective combination weighting method. Firstly, the combined weighting method is used to determine the comprehensive weight;Then, the standard cloud model is generated by using the cloud model method, and the digital characteristics of the evaluation cloud are obtained through the sample data and cloud computing rules. The digital characteristics of the evaluation cloud are obtained by the backward cloud generator and comprehensive weight;Finally, the similarity between the generated evaluation cloud and the standard cloud model is calculated, so as to evaluate the operation of the student marine engine simulator. The example analysis shows that the evaluation method can scientifically and reasonably evaluate the crew's operation ability, and is feasible and effective. © Published under licence by IOP Publishing Ltd.

关键词： Uncertainty analysis

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THE ROLE OF modeling UNCERTAINTIES IN SEISMIC analysis OF CONCRETE DAMS

World Conference on Earthquake Engineering proceedings

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World conference on Earthquake Engineering proceedings 2024年 2024卷

作者： Hariri-Ardebili, M.A. Salamon, J.W. University of Maryland College Park United States US Bureau of Reclamation Denver United States

Despite the significant advances in nonlinear dynamic analysis of engineering structures, concerns still exist regarding the level of confidence in modeling and the accuracy of analysis outcomes. While verification and validation of computational processes are primary tools used to quantify the accuracy of solutions and to build confidence in the analysis results, they cannot fully eliminate sources of uncertainties during performance evaluation. In particular, uncertainties in the dynamic analysis of dam-water-rock coupled systems can be attributed to both epistemic and aleatory sources of uncertainties. This paper focuses on the importance of addressing epistemic uncertainties in the seismic analysis of a gravity dam through careful data collection from the 15th ICOLD’s Benchmark Workshop organized in Milan, Italy in 2019. In the case study formulation, the geometry of the model, mechanical properties of materials, and loads were precisely defined, and participants were asked to analyze the defined cases selecting the best practice in modeling and simulation of concrete dams. Significant variability was observed in contributions, particularly in the application of the far-field boundary conditions and the non-linear material models selected for concrete damage modeling. This paper elaborates further on the sources of various variabilities and attempts to quantify the amount of uncertainty in modeling and simulation for such well-defined benchmark problems. The results of this study emphasize the need for establishing a systematic approach to modeling and analyzing seismic hazards in dam engineering to improve the accuracy and consistency of predictions. A better understanding of the sources and magnitudes of modeling uncertainties can help improve the reliability of dam analyses, contribute to the development of more effective risk assessment and mitigation strategies, and build confidence in the analysis results. © 2024, international Association for Earthquake E

关键词： Concrete dams

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