Comput. Informatics最新文献

New Simulation Software Technologies at the LHCb Experiment at CERN 欧洲核子研究中心LHCb实验的新模拟软件技术

Comput. Informatics Pub Date : 2021-12-09 DOI: 10.31577/cai_2021_4_815

M. Mazurek, G. Corti, D. Müller

{"title":"New Simulation Software Technologies at the LHCb Experiment at CERN","authors":"M. Mazurek, G. Corti, D. Müller","doi":"10.31577/cai_2021_4_815","DOIUrl":"https://doi.org/10.31577/cai_2021_4_815","url":null,"abstract":". The LHCb experiment at the Large Hadron Collider (LHC) at CERN has successfully performed a large number of physics measurements during Runs 1 and 2 of the LHC. Monte Carlo simulation is the key to the interpretation of these and future measurements. The LHCb experiment is currently undergoing a major detector upgrade for Run 3 of the LHC to process events with five times higher luminosity. New simulation software technologies have to be introduced to produce simulated data samples of sufficient size within the computing resources allocated for the next few years. Therefore, the LHCb collaboration is currently preparing an upgraded version of its Gauss simulation framework. The new version provides the LHCb specific functionality while its generic simulation infrastructure has been encapsulated in an experiment independent framework, Gaussino . The latter combines the Gaudi core software framework and the Geant4 simulation toolkit and fully exploits their multi-threading capabilities. A prototype of a fast simulation interface to the simulation toolkit is being developed as the latest addition to Gaussino to provide an extensive palette of fast simulation models, including new deep learning-based options. of ring-imaging Cherenkov detectors, upstream downstream of the RICH2).","PeriodicalId":345268,"journal":{"name":"Comput. Informatics","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123913281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Privacy Issue: From Static to Dynamic Online Social Networks 隐私问题:从静态到动态的在线社交网络

Comput. Informatics Pub Date : 2021-10-19 DOI: 10.21203/RS.3.RS-991879/V1

M. Alanezi, Basim Mahmood

引用次数: 4

Effect of Term Weighting on Keyword Extraction in Hierarchical Category Structure 分级分类结构中词权对关键词提取的影响

Comput. Informatics Pub Date : 2021-08-03 DOI: 10.31577/cai_2021_1_57

Boonthida Chiraratanasopha, Salin Boonbrahm, T. Theeramunkong

{"title":"Effect of Term Weighting on Keyword Extraction in Hierarchical Category Structure","authors":"Boonthida Chiraratanasopha, Salin Boonbrahm, T. Theeramunkong","doi":"10.31577/cai_2021_1_57","DOIUrl":"https://doi.org/10.31577/cai_2021_1_57","url":null,"abstract":"While there have been several studies related to the effect of term weighting on classification accuracy, relatively few works have been conducted on how term weighting affects the quality of keywords extracted for characterizing a document or a category (i.e., document collection). Moreover, many tasks require more complicated category structure, such as hierarchical and network category structure, rather than a flat category structure. This paper presents a qualitative and quantitative study on how term weighting affects keyword extraction in the hierarchical category structure, in comparison to the flat category structure. A hierarchical structure triggers special characteristic in assigning a set of keywords or tags to represent a document or a document collection, with support of statistics in a hierarchy, including category itself, its parent category, its child categories, and sibling categories. An enhancement of term weighting is proposed particularly in the form of a series of modified TFIDF's, for improving keyword extraction. A text collection of public-hearing opinions is used to evaluate variant TFs and IDFs to identify which types of information in hierarchical category structure are useful. By experiments, we found that the most effective IDF family, namely TF-IDFr, is identity>sibling>child>parent in order. The TF-IDFr outperforms the vanilla version of TFIDF with a centroid-based classifier.","PeriodicalId":345268,"journal":{"name":"Comput. Informatics","volume":"s3-32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130135594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Credit Risk Assessment of Banks' Loan Enterprise Customer Based on State-Constraint 基于状态约束的银行贷款企业客户信用风险评估

Comput. Informatics Pub Date : 2021-08-03 DOI: 10.31577/cai_2021_1_145

Ren-jing Liu, Xuming Yang, Xiangmin Dong, Boyang Sun

引用次数: 2

Automating Test Case Identification in Java Open Source Projects on GitHub 在GitHub上的Java开源项目中自动化测试用例识别

Comput. Informatics Pub Date : 2021-02-23 DOI: 10.31577/cai_2021_3_575

Matej Madeja, J. Porubän, M. Bačíková, Matúš Sulír, Ján Juhár, Sergej Chodarev, Filip Gurbáľ

{"title":"Automating Test Case Identification in Java Open Source Projects on GitHub","authors":"Matej Madeja, J. Porubän, M. Bačíková, Matúš Sulír, Ján Juhár, Sergej Chodarev, Filip Gurbáľ","doi":"10.31577/cai_2021_3_575","DOIUrl":"https://doi.org/10.31577/cai_2021_3_575","url":null,"abstract":"Software testing is one of the very important Quality Assurance (QA) components. A lot of researchers deal with the testing process in terms of tester motivation and how tests should or should not be written. However, it is not known from the recommendations how the tests are written in real projects. In this paper, the following was investigated: (i) the denotation of the word\"test\"in different natural languages; (ii) whether the number of occurrences of the word\"test\"correlates with the number of test cases; and (iii) what testing frameworks are mostly used. The analysis was performed on 38 GitHub open source repositories thoroughly selected from the set of 4.3M GitHub projects. We analyzed 20,340 test cases in 803 classes manually and 170k classes using an automated approach. The results show that: (i) there exists a weak correlation (r = 0.655) between the number of occurrences of the word\"test\"and the number of test cases in a class; (ii) the proposed algorithm using static file analysis correctly detected 97% of test cases; (iii) 15% of the analyzed classes used main() function whose represent regular Java programs that test the production code without using any third-party framework. The identification of such tests is very complex due to implementation diversity. The results may be leveraged to more quickly identify and locate test cases in a repository, to understand practices in customized testing solutions, and to mine tests to improve program comprehension in the future.","PeriodicalId":345268,"journal":{"name":"Comput. Informatics","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132038243","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Analysis and Application of Min-Cost Transition Systems to Business Process Management 最小成本转换系统在业务流程管理中的分析与应用

Comput. Informatics Pub Date : 2020-02-29 DOI: 10.31577/cai_2020_1-2_213

Xiwen Feng, Dong Han, Yinhua Tian

引用次数: 2

A Time-Sensitive Collaborative Filtering Algorithm with Feature Stability 一种具有特征稳定性的时间敏感协同过滤算法

Comput. Informatics Pub Date : 2020-02-29 DOI: 10.31577/cai_2020_1-2_141

Shanchen Pang, Shihang Yu, Guiling Li, Sibo Qiao, Min Wang

引用次数: 2

Optimizing Data Placement for Cost Effective and High Available Multi-Cloud Storage 优化数据放置的成本效益和高可用的多云存储

Comput. Informatics Pub Date : 2020-02-29 DOI: 10.31577/cai_2020_1-2_51

P. Wang, Caihui Zhao, Wenqiang Liu, Zhen Chen, Zhaohui Zhang

{"title":"Optimizing Data Placement for Cost Effective and High Available Multi-Cloud Storage","authors":"P. Wang, Caihui Zhao, Wenqiang Liu, Zhen Chen, Zhaohui Zhang","doi":"10.31577/cai_2020_1-2_51","DOIUrl":"https://doi.org/10.31577/cai_2020_1-2_51","url":null,"abstract":"With the advent of big data age, data volume has been changed from trillionbyte to petabyte with incredible speed. Owing to the fact that cloud storage offers the vision of a virtually infinite pool of storage resources, data can be stored and accessed with high scalability and availability. But a single cloud-based data storage has risks like vendor lock-in, privacy leakage, and unavailability. Multi-cloud storage can mitigate these risks with geographically located cloud storage providers. In this storage scheme, one important challenge is how to place a user's data cost-effectively with high availability. In this paper, an architecture for multi-cloud storage is presented. Next, a multi-objective optimization problem is defined to minimize total cost and maximize data availability simultaneously, which can be solved by an approach based on the non-dominated sorting genetic algorithm II (NSGA-II) and obtain a set of non-dominated solutions called the Pareto-optimal set. Then, a method is proposed which is based on the entropy method to determine the most suitable solution for users who cannot choose one from the Pareto-optimal set directly. Finally, the performance of the proposed algorithm is validated by extensive experiments based on real-world multiple cloud storage scenarios.","PeriodicalId":345268,"journal":{"name":"Comput. Informatics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129264802","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 19

A Multi-Dimensional Recommendation Scheme for Social Networks Considering a User Relationship Strength Perspective 基于用户关系强度视角的社交网络多维推荐方案

Comput. Informatics Pub Date : 2020-02-29 DOI: 10.31577/cai_2020_1-2_105

Bo Zhang, Ya Zhang, Yanhong Bai, Jie Lian, Meizi Li

{"title":"A Multi-Dimensional Recommendation Scheme for Social Networks Considering a User Relationship Strength Perspective","authors":"Bo Zhang, Ya Zhang, Yanhong Bai, Jie Lian, Meizi Li","doi":"10.31577/cai_2020_1-2_105","DOIUrl":"https://doi.org/10.31577/cai_2020_1-2_105","url":null,"abstract":"Developing a computational method based on user relationship strength for multi-dimensional recommendation is a significant challenge. The traditional recommendation methods have relatively low accuracy because they lack considering information from the perspective of user relationship strength into the recommendation algorithm. User relationship strength reflects the degree of closeness between two users, which can make the recommendation system more efficient between users in pairs. This paper proposes a multi-dimensional comprehensive recommendation method based on user relationship strength. We take three main factors into consideration, including the strength of user relationship, the similarity of entities, and the degree of user interest. First, we introduce a novel method to generate a user candidate set and an entity candidate set by calculating the relationship strength between two users and the similarity between two entities. Then, the algorithm will calculate the user interest degree of each user in the user candidate set to each entity in the entity candidate set, if the user interest degree is larger than or equal to a threshold, this particular entity will be recommended to this user. The performance of the proposed method was verified based on the real-world social network dataset and the e-commerce website dataset, and the experimental result suggests that this method can improve the recommendation accuracy.","PeriodicalId":345268,"journal":{"name":"Comput. Informatics","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133778248","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Deep Convolution and Correlated Manifold Embedded Distribution Alignment for Forest Fire Smoke Prediction 森林火灾烟雾预测的深度卷积和相关流形嵌入分布对齐

Comput. Informatics Pub Date : 2020-02-29 DOI: 10.31577/cai_2020_1-2_318

Yaoli Wang, Xiaohui Liu, Maozhen Li, Wenxia Di, Lipo Wang

{"title":"Deep Convolution and Correlated Manifold Embedded Distribution Alignment for Forest Fire Smoke Prediction","authors":"Yaoli Wang, Xiaohui Liu, Maozhen Li, Wenxia Di, Lipo Wang","doi":"10.31577/cai_2020_1-2_318","DOIUrl":"https://doi.org/10.31577/cai_2020_1-2_318","url":null,"abstract":"This paper proposes the deep convolution and correlated manifold embedded distribution alignment (DC-CMEDA) model, which is able to realize the transfer learning classification between and among various small datasets, and greatly shorten the training time. First, pre-trained Resnet50 network is used for feature transfer to extract smoke features because of the difficulty in training small dataset of forest fire smoke; second, a correlated manifold embedded distribution alignment (CMEDA) is proposed to register the smoke features in order to align the input feature distributions of the source and target domains; and finally, a trainable network model is constructed. This model is evaluated in the paper based on satellite remote sensing image and video image datasets. Compared with the deep convolutional integrated long short-term memory (DC-ILSTM) network, DC-CMEDA has increased the accuracy of video images by 1.50 %, and the accuracy of satellite remote sensing images by 4.00 %. Compared the CMEDA algorithm with the ILSTM algorithm, the number of iterations of the former has decreased to 10 times or less, and the algorithm complexity of CMEDA is lower than that of ILSTM. DC-CMEDA has a great advantage in terms of convergence speed. The experimental results show that DC-CMEDA can solve the problem of small sample smoke dataset detection and recognition.","PeriodicalId":345268,"journal":{"name":"Comput. Informatics","volume":"101 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120906642","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6