Improving selective collection of urban waste using a business intelligence system

Today recovering urban waste requires effective management services, which usually imply sophisticated monitoring and analysis mechanisms. This is essential for the smooth running of the entire recycling process as well as for planning and control urban waste recovering. In this paper we present a business intelligence system especially designed and im- plemented to support regular decision-making tasks on urban waste management processes. The system provides a set of domain-oriented analytical tools for studying and characterizing poten- tial scenarios of collection processes of urban waste, as well as for supporting waste manage- ment in urban areas, allowing for the organization and optimization of collection services. In or- der to clarify the way the system was developed and the how it operates, particularly in process visualization and data analysis, we also present the organization model of the system, the ser- vices it disposes, and the interface platforms for exploring data.

Step towards of a homemade business intelligence solution: A case study in textile industry

Nowadays, organizations are increasingly looking to invest in business intelligence solutions, mainly private companies in order to get advantage over its competitors, however they do not know what is necessary. Business intelligence allows an analysis of consolidated information in order to obtain more specific outlets and certain indications in order to support the decision making process. You can take the right decision based on the data collected from different information systems present in the organization and outside of them. The textile sector is a sector where concept of Business Intelligence it is not many explored yet. Actually there are few textile companies that have a BI platform. Thus, the article objective is present an architecture and show all the steps by which companies need to spend to implement a successful free homemade Business Intelligence system. As result the proposed approach it was validated using real data aiming assess the steps defined.

Pervasive business intelligence platform to improve the quality of decision process in primary and secondary education – A Portuguese case study

Business Intelligence (BI) can be seen as a method that gathers information and data from information systems in order to help companies to be more accurate in their decision-making process. Traditionally BI systems were associated with the use of Data Warehouses (DW). The prime purpose of DW is to serve as a repository that stores all the relevant information required for making the correct decision. The necessity to integrate streaming data became crucial with the need to improve the efficiency and effectiveness of the decision process. In primary and secondary education, there is a lack of BI solutions. Due to the schools reality the main purpose of this study is to provide a Pervasive BI solution able to monitoring the schools and student data anywhere and anytime in real-time as well as disseminating the information through ubiquitous devices. The first task consisted in gathering data regarding the different choices made by the student since his enrolment in a certain school year until the end of it. Thereafter a dimensional model was developed in order to be possible building a BI platform. This paper presents the dimensional model, a set of pre-defined indicators, the Pervasive Business Intelligence characteristics and the prototype designed. The main contribution of this study was to offer to the schools a tool that could help them to make accurate decisions in real-time. Data dissemination was achieved through a localized application that can be accessed anywhere and anytime.

Intra and inter-individual differences in social intelligence of Portuguese students

Social intelligence is a favorable condition for career decision-making and development. The social intelligence indices of Portuguese students in school years prior to a career transition are characterized and intra and interindividual differences are analyzed. Participants were 1095 students (552, 50.4% women) with a mean age of 14.78 years (SD = 1.86), in the 8th (542, 49.5%), 10th (295, 26.9%) and 11th (258, 23.6%) grades. The Cognitive Test of Social Intelligence (PCIS) was administered at two moments, six months apart. Results indicate that the 8th grade obtained higher average scores in Problem Solving, Motivation and Self-confidence (time 1), while the 10th grade obtained better results in Problem Solving, Motivation and Familiarity (time 2). Between the assessment moments, all school years register an increase in Problem Solving and Self-confidence in social situations. These results constitute favorable psychological conditions for the promotion of ethical questioning in career guidance interventions.

Poker learner: modelação de jogadores através de data mining

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação

Corporate Performance Management através da integração de Business Intelligence e Business Process Management

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação

Business intelligence no suporte às autarquias locais e à sua gestão orçamental

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação

Exploração de dados para soluções de retalho em business intelligence

Dissertação de mestrado integrado em Engenharia de Gestão e Sistemas de Informação

Pervasive business intelligence: a marketing intelligence framework proposal

Doctoral Thesis in Information Systems and Technologies Area of Information Systems and Technology

Plataforma de suporte à decisão médica para transplante de órgãos baseada em Business Intelligence

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Informática Médica)

Automated network resilience optimization using computational intelligence methods

This paper presents an automated optimization framework able to provide network administrators with resilient routing configurations for link-state protocols, such as OSPF or IS-IS. In order to deal with the formulated NP-hard optimization problems, the devised framework is underpinned by the use of computational intelligence optimization engines, such as Multi-objective Evolutionary Algorithms (MOEAs). With the objective of demonstrating the framework capabilities, two illustrative Traffic Engineering methods are described, allowing to attain routing configurations robust to changes in the traffic demands and maintaining the network stable even in the presence of link failure events. The presented illustrative results clearly corroborate the usefulness of the proposed automated framework along with the devised optimization methods.

Step towards to improve the voluntary interruption of pregnancy by means of business intelligence

With the implementation of Information and Communication Technologies in the health sector, it became possible the existence of an electronic record of information for patients, enabling the storage and the availability of their information in databases. However, without the implementation of a Business Intelligence (BI) system, this information has no value. Thus, the major motivation of this paper is to create a decision support system that allows the transformation of information into knowledge, giving usability to the stored data. The particular case addressed in this chapter is the Centro Materno Infantil do Norte, in particular the Voluntary Interruption of Pregnancy unit. With the creation of a BI system for this module, it is possible to design an interoperable, pervasive and real-time platform to support the decision-making process of health professionals, based on cases that occurred. Furthermore, this platform enables the automation of the process for obtaining key performance indicators that are presented annually by this health institution. In this chapter, the BI system implemented in the VIP unity in CMIN, some of the KPIs evaluated as well as the benefits of this implementation are presented.

Body Mass Index: A Scientific Evidence-Based Inquiry

OBJECTVE: To objectively and critically assess body mass index and to propose alternatives for relating body weight and height that are evidence-based and that eliminate or reduce the limitations of the body mass index. METHODS: To analyze the relations involving weight and height, we used 2 databases as follows: 1) children and adolescents from Brazil, the United States, and Switzerland; and 2) 538 university students. We performed mathematical simulations with height data ranging from 115 to 190 cm and weight data ranging from 25 to 105 kg. We selected 3 methods to analyze the relation of weight and height as follows: body mass index - weight (kg)/height (m²); reciprocal of the ponderal index - height (cm)/weight1/3 (kg); and ectomorphy. Using the normal range from 20 to 25 kg/m² for the body mass index in the reference height of 170 cm, we identified the corresponding ranges of 41 to 44 cm/kg1/3 for the reciprocal of the ponderal index, and of 1.45 to 3.60 for ectomorphy. RESULTS: The mathematical simulations showed a strong association among the 3 methods with an absolute concordance to a height of 170 cm, but with a tendency towards discrepancy in the normal ranges, which had already been observed for the heights of 165 and 175 cm. This made the direct convertibility between the indices unfeasible. The reciprocal of the ponderal index and ectomorphy with their cut points comprised a larger age range in children and adolescents and a wider and more central range in the university students, both for the reported (current) and desired weights. CONCLUSION: The reciprocal of the ponderal index and ectomorphy are stronger and are more mathematically logical than body mass index; in addition, they may be applied with the same cut points for normal from the age of 5 ½ years on.

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