Ant Colony Optimization for Requirement selection in Incremental Software development

This proposal shows that ACO systems can be applied to problems of requirements selection in software incremental development, with the idea of obtaining better results of those produced by expert judgment alone. The evaluation of the ACO systems should be done through a compared analysis with greedy and simulated annealing algorithms, performing experiments with some problems instance

An Exploratory Study on the Strategic Use of Information Technology in the Source Selection Decision-Making Process

The strategic use of Information Technology in the acquisition field can be very useful in the decision making process of evaluating alternative solutions during a Government source selection. Current implementation of information technology provides a more tactical approach to systems development. The use of Electronic Commerce/Electronic Data Interchange and the internet to electronically transfer information is only the beginning of the shift towards a more strategic design process for information systems within Government procurement agencies. A schematic model was designed to demonstrate how information technology, such as Decision Support Systems, Expert Systems, and Shared Data Warehousing could assist the SSA in selecting the optimal, or best value solution. In addition, three source selection evaluation models using management science techniques were designed and developed using Microsoft Excel software. The Sealed Bidding, FAR Part 14, and Competitive Proposal, FAR Part 15 models implemented Integer Linear Programming through Microsoft Excel\u27s SOLVER option. The AFFARS Appendix AA/BB model implemented the use of the multi-criteria Analytical Hierarchy Process

Solving multiple-criteria R&D project selection problems with a data-driven evidential reasoning rule

In this paper, a likelihood based evidence acquisition approach is proposed to acquire evidence from experts'assessments as recorded in historical datasets. Then a data-driven evidential reasoning rule based model is introduced to R&D project selection process by combining multiple pieces of evidence with different weights and reliabilities. As a result, the total belief degrees and the overall performance can be generated for ranking and selecting projects. Finally, a case study on the R&D project selection for the National Science Foundation of China is conducted to show the effectiveness of the proposed model. The data-driven evidential reasoning rule based model for project evaluation and selection (1) utilizes experimental data to represent experts' assessments by using belief distributions over the set of final funding outcomes, and through this historic statistics it helps experts and applicants to understand the funding probability to a given assessment grade, (2) implies the mapping relationships between the evaluation grades and the final funding outcomes by using historical data, and (3) provides a way to make fair decisions by taking experts' reliabilities into account. In the data-driven evidential reasoning rule based model, experts play different roles in accordance with their reliabilities which are determined by their previous review track records, and the selection process is made interpretable and fairer. The newly proposed model reduces the time-consuming panel review work for both managers and experts, and significantly improves the efficiency and quality of project selection process. Although the model is demonstrated for project selection in the NSFC, it can be generalized to other funding agencies or industries.Comment: 20 pages, forthcoming in International Journal of Project Management (2019

Expert System for Crop Disease based on Graph Pattern Matching: A proposal

Para la agroindustria, las enfermedades en cultivos constituyen uno de los problemas más frecuentes que generan grandes pérdidas económicas y baja calidad en la producción. Por otro lado, desde las ciencias de la computación, han surgido diferentes herramientas cuya finalidad es mejorar la prevención y el tratamiento de estas enfermedades. En este sentido, investigaciones recientes proponen el desarrollo de sistemas expertos para resolver este problema haciendo uso de técnicas de minería de datos e inteligencia artificial, como inferencia basada en reglas, árboles de decisión, redes bayesianas, entre otras. Además, los grafos pueden ser usados para el almacenamiento de los diferentes tipos de variables que se encuentran presentes en un ambiente de cultivos, permitiendo la aplicación de técnicas de minería de datos en grafos, como el emparejamiento de patrones en los mismos. En este artículo presentamos una visión general de las temáticas mencionadas y una propuesta de un sistema experto para enfermedades en cultivos, basado en emparejamiento de patrones en grafos.For agroindustry, crop diseases constitute one of the most common problems that generate large economic losses and low production quality. On the other hand, from computer science, several tools have emerged in order to improve the prevention and treatment of these diseases. In this sense, recent research proposes the development of expert systems to solve this problem, making use of data mining and artificial intelligence techniques like rule-based inference, decision trees, Bayesian network, among others. Furthermore, graphs can be used for storage of different types of variables that are present in an environment of crops, allowing the application of graph data mining techniques like graph pattern matching. Therefore, in this paper we present an overview of the above issues and a proposal of an expert system for crop disease based on graph pattern matching

Fostering the reduction of assortative mixing or homophily into the class

Human societies from the outset have been associated according to race, beliefs, religion, social level, and the like. These behaviors continue even today in the classroom at primary, middle, and superior levels. However, the growth of ICT offers educational researchers new ways to explore methods of team formation that have been proven to be efficient in the field of serious games through the use of computer networks. The selection process of team members in serious games through the use of computer networks is carried out according to their performance in the area of the game without distinction of social variables. The use of serious games in education has been discussed in multiple research studies which state that its application in teaching and learning processes are changing the way of teaching. This article presents an exploratory analysis of the team formation process based on collaboration through the use of ICT tools of collective intelligence called TBT (The best team). The process and its ICT tool combine the paradigms of creativity in swarming, collective intelligence, serious games, and social computing in order to capture the participants’ emotions and evaluate contributions. Based on the results, we consider that the use of new forms of teaching and learning based on the emerging paradigms is necessary. Therefore, TBT is a tool that could become an effective way to encourage the formation of work groups by evaluating objective variable of performance of its members in collaborative works.Postprint (published version

Narratives of an outsourced information systems failure in a small enterprise

In this study we investigate a case of an outsourced information systems (IS) failure (OISF) within the collaborative partnership among asymmetric partners. A small and medium-sized enterprise (SME) is dealing with an independent software vendor (ISV) conducting a project of implementing an IS that fails. We used a narrative research methodology for our enquiry. In the construction of our narrative we followed the OISF framework as a theoretical touchstone. As a major conclusion we found that asymmetric collaborations with partners with inadequate managerial and technical IT capabilities are extremely prone to OISF’s. We showed that an outcome-based and fixed price contract is not an adequate instrument to conduct such a partnership and to avoid a failure