2018 7th International Conference On Software Process Improvement (CIMPS)最新文献

Maturity Model for the Risk Analysis of Information Assets based on Methodologies MAGERIT, OCTAVE y MEHARI; focused on Shipping Companies 基于MAGERIT、OCTAVE和MEHARI方法的信息资产风险分析成熟度模型专注于航运公司

2018 7th International Conference On Software Process Improvement (CIMPS) Pub Date : 2018-10-01 DOI: 10.1109/CIMPS.2018.8625848

Fresia Yanina Holguín García, Lohana Mariella Lema Moreta

引用次数: 3

Digital Analog Conversion with SPI Protocol for Gas Sensors 数字模拟转换与SPI协议气体传感器

2018 7th International Conference On Software Process Improvement (CIMPS) Pub Date : 2018-10-01 DOI: 10.1109/CIMPS.2018.8625626

S. G. Briceño-Muro, R. Chaparro-Sánchez, J. Romero-González

引用次数: 0

CIMPS 2018 Preface

2018 7th International Conference On Software Process Improvement (CIMPS) Pub Date : 2018-10-01 DOI: 10.1109/cimps.2018.8625616

引用次数: 0

Evolution of Virtual Reality’s Interaction Devices 虚拟现实交互设备的演变

2018 7th International Conference On Software Process Improvement (CIMPS) Pub Date : 2018-10-01 DOI: 10.1109/CIMPS.2018.8625634

Alexis Santana, A. Lira, Graciela Lara, Adriana Peña

引用次数: 2

Support tool for software quality assurance in software development 软件开发中软件质量保证的支持工具

2018 7th International Conference On Software Process Improvement (CIMPS) Pub Date : 2018-10-01 DOI: 10.1109/CIMPS.2018.8625617

Saul Ibarra, M. Muñoz

引用次数: 6

CIMPS 2018 Committees CIMPS 2018委员会

2018 7th International Conference On Software Process Improvement (CIMPS) Pub Date : 2018-10-01 DOI: 10.1109/cimps.2018.8625622

引用次数: 0

Measuring data privacy preserving and machine learning 测量数据隐私保护和机器学习

2018 7th International Conference On Software Process Improvement (CIMPS) Pub Date : 2018-10-01 DOI: 10.1109/CIMPS.2018.8625613

Luis Gustavo Esquivel-Quirós, E. G. Barrantes, Fernando Esponda Darlington

{"title":"Measuring data privacy preserving and machine learning","authors":"Luis Gustavo Esquivel-Quirós, E. G. Barrantes, Fernando Esponda Darlington","doi":"10.1109/CIMPS.2018.8625613","DOIUrl":"https://doi.org/10.1109/CIMPS.2018.8625613","url":null,"abstract":"The increasing publication of large amounts of data, theoretically anonymous, can lead to a number of attacks on the privacy of people. The publication of sensitive data without exposing the data owners is generally not part of the software developers concerns. The regulations for the data privacy-preserving create an appropriate scenario to focus on privacy from the perspective of the use or data exploration that takes place in an organization. The increasing number of sanctions for privacy violations motivates the systematic comparison of three known machine learning algorithms in order to measure the usefulness of the data privacy preserving. The scope of the evaluation is extended by comparing them with a known privacy preservation metric. Different parameter scenarios and privacy levels are used. The use of publicly available implementations, the presentation of the methodology, explanation of the experiments and the analysis allow providing a framework of work on the problem of the preservation of privacy. Problems are shown in the measurement of the usefulness of the data and its relationship with the privacy preserving. The findings motivate the need to create optimized metrics on the privacy preferences of the owners of the data since the risks of predicting sensitive attributes by means of machine learning techniques are not usually eliminated. In addition, it is shown that there may be a hundred percent, but it cannot be measured. As well as ensuring adequate performance of machine learning models that are of interest to the organization that data publisher.","PeriodicalId":159915,"journal":{"name":"2018 7th International Conference On Software Process Improvement (CIMPS)","volume":"107 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115813658","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

Correlation Analysis and Residual Error between Re-Analysis Data of the CFSR Model and Meteorological Stations CFSR模式再分析资料与气象站的相关分析及残差

2018 7th International Conference On Software Process Improvement (CIMPS) Pub Date : 2018-10-01 DOI: 10.1109/CIMPS.2018.8626060

F. Barrera, W. Rojas

{"title":"Correlation Analysis and Residual Error between Re-Analysis Data of the CFSR Model and Meteorological Stations","authors":"F. Barrera, W. Rojas","doi":"10.1109/CIMPS.2018.8626060","DOIUrl":"https://doi.org/10.1109/CIMPS.2018.8626060","url":null,"abstract":"The article describes a work of analysis of correlations between Re-Analysis Data (RAD) of the climate-forecasting model known worldwide as CFSR (Climate Forecast System Reanalysis), and those provided by local Meteorological Stations (MS), installed in the geographical area study. We also seek to quantify and characterize the residual error in order to validate the RAD as a source of alternative information to the data of the MS (DMS). The study area that encompasses the work corresponds to the northern region of Chile Tarapacá region, adjacent to border areas with Peru, Bolivia and Argentina. There is evidence that MS Data in the Tarapacá region present quality problems to calculate the Climatic Extremes Indices (CEI). For this reason, this work performs the indicated analysis, through the use of Data Mining (DM) techniques, which include the correlation coefficients of Pearson, Spearman and Kendall. In addition, descriptive statistics are used, considering temperature and precipitation data, provided by 82 MS for the period 1983–2012. The study concludes that there are severe residual errors, and it is not recommended to use the RAD as an alternative information source to calculate the CEI, since these can be affected. However, the RAD manage to reproduce the behavior of the meteorological variables, which is why they can be used for qualitative studies of these).","PeriodicalId":159915,"journal":{"name":"2018 7th International Conference On Software Process Improvement (CIMPS)","volume":"189 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133898044","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: 0

Use of Graph Database for the Integration of Heterogeneous Data about Ecuadorian Historical Personages 利用图形数据库整合厄瓜多尔历史人物异构数据

2018 7th International Conference On Software Process Improvement (CIMPS) Pub Date : 2018-10-01 DOI: 10.1109/CIMPS.2018.8625618

Jean Mosquera, Nelson Piedra

引用次数: 3

Requirements Engineering to Design a Brain-Computer Interface for Cognitive Training 认知训练脑机接口设计需求工程

2018 7th International Conference On Software Process Improvement (CIMPS) Pub Date : 2018-10-01 DOI: 10.1109/CIMPS.2018.8625612

D. Ramírez, José-Antonio Cervantes, Jahaziel Molina, Sonia López

引用次数: 0