2019 XLV Latin American Computing Conference (CLEI)最新文献_第2页

Challenges and Solutions of Project Management in Distributed Software Development 分布式软件开发中项目管理的挑战与解决方案

2019 XLV Latin American Computing Conference (CLEI) Pub Date : 2019-09-01 DOI: 10.1109/CLEI47609.2019.9089043

W. Moreno, Paulo Afonso Parreira Júnior, H. Costa

引用次数: 2

CLEI 2019 Program Committee CLEI 2019项目委员会

2019 XLV Latin American Computing Conference (CLEI) Pub Date : 2019-09-01 DOI: 10.1109/clei47609.2019.9073955

引用次数: 0

Fusion of infrared and visible images using multiscale morphology 基于多尺度形态学的红外与可见光图像融合

2019 XLV Latin American Computing Conference (CLEI) Pub Date : 2019-09-01 DOI: 10.1109/CLEI47609.2019.235085

Cecilia Araceli Saravia, Magali E. Mereles Peralta, Julio César Mello Román, José Luis Vázquez Noguera, H. Legal-Ayala

引用次数: 1

Proposal of a Software Development Process for a Poultry Company in Colombia 为哥伦比亚一家家禽公司提供软件开发流程建议

2019 XLV Latin American Computing Conference (CLEI) Pub Date : 2019-09-01 DOI: 10.1109/CLEI47609.2019.235057

Fabian Danilo Pérez Díaz, F. Giraldo

引用次数: 0

A ranking-based approach for supporting the initial selection of primary studies in a Systematic Literature Review 在系统文献综述中支持初步研究选择的基于排序的方法

2019 XLV Latin American Computing Conference (CLEI) Pub Date : 2019-09-01 DOI: 10.1109/CLEI47609.2019.235079

Santiago Gonzalez-Toral, Renán Freire, R. Gualán, Víctor Saquicela

{"title":"A ranking-based approach for supporting the initial selection of primary studies in a Systematic Literature Review","authors":"Santiago Gonzalez-Toral, Renán Freire, R. Gualán, Víctor Saquicela","doi":"10.1109/CLEI47609.2019.235079","DOIUrl":"https://doi.org/10.1109/CLEI47609.2019.235079","url":null,"abstract":"Traditionally most of the steps involved in a Systematic Literature Review (SLR) process are manually executed, causing inconvenience of time and effort, given the massive amount of primary studies available online. This has motivated a lot of research focused on automating the process. Current state-of-the-art methods combine active learning methods and manual selection of primary studies from a smaller set so they can maximize the finding of relevant papers while at the same time minimizing the number of manually reviewed papers. In this work, we propose a novel strategy to further improve these methods whose early success heavily depends on an effective selection of initial papers to be read by researchers using a PCAbased method which combines different document representation and similarity metric approaches to cluster and rank the content within the corpus related to an enriched representation of research questions within the SLR protocol. Validation was carried out over four publicly available data sets corresponding to SLR studies from the Software Engineering domain. The proposed model proved to be more efficient than a BM25 baseline model as a mechanism to select the initial set of relevant primary studies within the top 100 rank, which makes it a promising method to bootstrap an active learning cycle.","PeriodicalId":216193,"journal":{"name":"2019 XLV Latin American Computing Conference (CLEI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130645351","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: 4

Method for Project Execution Control based on Soft Computing and Machine Learning 基于软计算和机器学习的项目执行控制方法

2019 XLV Latin American Computing Conference (CLEI) Pub Date : 2019-09-01 DOI: 10.1109/CLEI47609.2019.235097

Anié Bermudez Peña, G. F. Castro, D. M. L. Alvarez, I. M. Alcivar, Giselle Lorena Núñez Núñez, Danny Saavedra Cevallos, Jorge Luis Zambrano Santa

{"title":"Method for Project Execution Control based on Soft Computing and Machine Learning","authors":"Anié Bermudez Peña, G. F. Castro, D. M. L. Alvarez, I. M. Alcivar, Giselle Lorena Núñez Núñez, Danny Saavedra Cevallos, Jorge Luis Zambrano Santa","doi":"10.1109/CLEI47609.2019.235097","DOIUrl":"https://doi.org/10.1109/CLEI47609.2019.235097","url":null,"abstract":"To support decision-making, organizations employ dissimilar tools during their projects execution control. However, they are still insufficient in environments with uncertain information and changing conditions in management styles. Deficiencies in systems for controlling the projects execution, affects the quality of their classification in aiding decision-making. An alternative solution is the introduction of soft computing techniques, which provide robustness, efficiency and adaptability at tools. This research proposes a method for project execution control based on soft computing and machine learning, which contributes to improve the project management. The proposed method allows the machine learning and adjusting of fuzzy inference systems to the project evaluation. The results are obtained from the execution of seven algorithms, which are based on space partitioning, neural networks, gradient descent and genetic algorithms. Validation of the proposed system, integrated to a project management tool, ratifies an improvement in the quality of project evaluation. The obtained result provides a contribution to the perfection of tools to support the decision-making in project management organization","PeriodicalId":216193,"journal":{"name":"2019 XLV Latin American Computing Conference (CLEI)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129124409","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

Risk Catalogs in Software Project Management 软件项目管理中的风险目录

2019 XLV Latin American Computing Conference (CLEI) Pub Date : 2019-09-01 DOI: 10.1109/CLEI47609.2019.9089044

V. Machado, Paulo Afonso Parreira Júnior, H. Costa

引用次数: 1

Effectiveness of preprocessing techniques over social media texts for the improvement of machine learning based classifiers 社交媒体文本预处理技术对基于机器学习的分类器改进的有效性

2019 XLV Latin American Computing Conference (CLEI) Pub Date : 2019-09-01 DOI: 10.1109/CLEI47609.2019.235076

L. Esnaola, Juan Pablo Tessore, Hugo Ramón, C. Russo

引用次数: 0

An architectural proposal for the interactive publication of the data classification obtained through a Differentially Private Random Decision Forest 一种基于差分私有随机决策林的数据分类交互式发布的体系结构方案

2019 XLV Latin American Computing Conference (CLEI) Pub Date : 2019-09-01 DOI: 10.1109/CLEI47609.2019.235070

Rosinei Cristiano Pereira, F. Lopes

{"title":"An architectural proposal for the interactive publication of the data classification obtained through a Differentially Private Random Decision Forest","authors":"Rosinei Cristiano Pereira, F. Lopes","doi":"10.1109/CLEI47609.2019.235070","DOIUrl":"https://doi.org/10.1109/CLEI47609.2019.235070","url":null,"abstract":"Data are generated in several contexts, by various devices, and are collected by organizations whose aims to obtain as much information as possible to add value to their business. There are plenty of ethical and non-ethical purposes involved such as identifying consumers' needs and then recommend products and services, developing new business, conducting health-related research in order to reduce medical errors, assessing risk of people developing diseases, so on. The organizations’ concerns about risks associated to potential privacy leaks and their impacts have increased dramatically. Thus, apply data mining in process optimization without compromising sensitive data and provide a strong privacy standard are challenges imposed to data stewards, who use techniques and privacy models during data release process. This study aims to propose a classification decision tree application, developed under the Differential Privacy model definition, whose architecture was designed according to the interactive data release model that deploys a barrier to forbid users to have access data in their raw format. In addition, a self-tuning feature that controls the forest growth was put in place, resulting in a better classification performance if compared to the adoption of a fixed amount of trees in the forest. However, there was an increase in processing time. It also was observed in most of the datasets used in the experiment that beyond a threshold the classification performance is reduced by increasing the number of trees that compose the forest.","PeriodicalId":216193,"journal":{"name":"2019 XLV Latin American Computing Conference (CLEI)","volume":"327 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123509118","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

CLEI 2019 Organizing Committee CLEI 2019组委会

2019 XLV Latin American Computing Conference (CLEI) Pub Date : 2019-09-01 DOI: 10.1109/clei47609.2019.9073824

引用次数: 0