[An editorial to] Recent Advances on Knowledge Discovery and Business Intelligence

Special issue guest editorial, June, 2015.

Business intelligence in banking: A literature analysis from 2002 to 2013 using Text Mining and latent Dirichlet allocation

telligence applications for the banking industry. Searches were performed in relevant journals resulting in 219 articles published between 2002 and 2013. To analyze such a large number of manuscripts, text mining techniques were used in pursuit for relevant terms on both business intelligence and banking domains. Moreover, the latent Dirichlet allocation modeling was used in or- der to group articles in several relevant topics. The analysis was conducted using a dictionary of terms belonging to both banking and business intelli- gence domains. Such procedure allowed for the identification of relationships between terms and topics grouping articles, enabling to emerge hypotheses regarding research directions. To confirm such hypotheses, relevant articles were collected and scrutinized, allowing to validate the text mining proce- dure. The results show that credit in banking is clearly the main application trend, particularly predicting risk and thus supporting credit approval or de- nial. There is also a relevant interest in bankruptcy and fraud prediction. Customer retention seems to be associated, although weakly, with targeting, justifying bank offers to reduce churn. In addition, a large number of ar- ticles focused more on business intelligence techniques and its applications, using the banking industry just for evaluation, thus, not clearly acclaiming for benefits in the banking business. By identifying these current research topics, this study also highlights opportunities for future research.

Evaluating ubiquitous computing environments using 3D simulation

Human activity is very dynamic and subtle, and most physical environments are also highly dynamic and support a vast range of social practices that do not map directly into any immediate ubiquitous computing functionally. Identifying what is valuable to people is very hard and obviously leads to great uncertainty regarding the type of support needed and the type of resources needed to create such support. We have addressed the issues of system development through the adoption of a Crowdsourced software development model [13]. We have designed and developed Anywhere places, an open and flexible system support infrastructure for Ubiquitous Computing that is based on a balanced combination between global services and applications and situated devices. Evaluation, however, is still an open problem. The characteristics of ubiquitous computing environments make their evaluation very complex: there are no globally accepted metrics and it is very difficult to evaluate large-scale and long-term environments in real contexts. In this paper, we describe a first proposal of an hybrid 3D simulated prototype of Anywhere places that combines simulated and real components to generate a mixed reality which can be used to assess the envisaged ubiquitous computing environments [17].

From a NoSQL data source to a business intelligence solution: An experiment

We are living in the era of Big Data. A time which is characterized by the continuous creation of vast amounts of data, originated from different sources, and with different formats. First, with the rise of the social networks and, more recently, with the advent of the Internet of Things (IoT), in which everyone and (eventually) everything is linked to the Internet, data with enormous potential for organizations is being continuously generated. In order to be more competitive, organizations want to access and explore all the richness that is present in those data. Indeed, Big Data is only as valuable as the insights organizations gather from it to make better decisions, which is the main goal of Business Intelligence. In this paper we describe an experiment in which data obtained from a NoSQL data source (database technology explicitly developed to deal with the specificities of Big Data) is used to feed a Business Intelligence solution.

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.

Nutritional status and specific leaf area of mahogany and tonka bean under two light environments

Studies on nutritional status and leaf traits were carried out in two tropical tree species Swietenia macrophylla King (mahogany) and Dipetryx odorata Aubl. Willd. (tonka bean) planted under contrasting light environments in Presidente Figueiredo-AM, Brazil. Leaves of S. macrophylla and D. odorata were collected in three year-old trees grown under full sunlight (about 2000 µmol m-2 s-1) and natural shade under a closed canopy of Balsa-wood plantation (Ochroma pyramidale Cav. Ex. Lam.Urb) about 260 µmol m-2 s-1. The parameters analysed were leaf area (LA), leaf dry mass (LDM), specific leaf area (SLA) and leaf nutrient contents. It was observed that, S. macrophylla leaves grown under full sunlight showed LA 35% lower than those grown under shade. In D. odorata leaves these differences in LA were not observed. In addition, it was observed that S. macrophylla shade leaves, for LDM, were 50% smaller than sun leaves, while in D. odorata, there differences were not observed. SLA in S. macrophylla presented that sun leaves were three times smaller than those grown under shade. In D. odorata, no differences were observed. Nutrient contents in S. macrophylla, regardless of their light environments, showed higher contents for P and Ca than those found in D. odorata. The N, K, Fe and Mn contents in S. macrophylla leaves decreased under shade. Finally, we suggest that the decreasing in leaf nutrient contents may have a negative influence on leaf growth. The results demonstrated that the tested hypothesis is true for leaf traits, which D. odorata, late-successional species, showed lower plasticity for leaf traits than Swietenia macrophylla, mid-successional species.

Plataforma para suporte ao ciclo de vida de organizações virtuais e seleção dinâmica de parceiros e fornecedores

Tese de Doutoramento em Engenharia Industrial e de Sistemas

Distance perception in immersive environments: the role of photorealism

Immersive environments (IE) are being increasingly used in order to perform psychophysical experiments. The versatility in terms of stimuli presentation and control and the less time-consuming procedures are their greatest strengths. However, to ensure that IE results can be generalized to real world scenarios we must first provide evidence that performance in IE is quantitatively indistinguishable from performance in real-world. Our goal was to perceptually validate distance perception for CAVE-like IEs. Participants performed a Frontal Matching Distance Task (Durgin & Li, 2011) in three different conditions: real-world scenario (RWS); photorealistic IE (IEPH) and non-photorealistic IE (IENPH). Underestimation of distance was found across all the conditions, with a significant difference between the three conditions (Wilks’ Lambda = .38, F(2,134)= 110.8, p<.01, significant pairwise differences with p<.01). We found a mean error of 2.3 meters for the RWS, 5 meters for the IEPH, and of 6 meters for the IENPH in a pooled data set of 5 participants. Results indicate that while having a photorealistic IE with perspective and stereoscopic depth cues might not be enough to elicit a real-world performance in distance judgment tasks, nevertheless this type of environment minimizes the discrepancy between simulation and real-world when compared with non-photorealistic IEs.

Using students’ learning style to create effective learning groups in MCSCL environments

Students have different ways for learning and processing information. Some students prefer learning through seeing while others prefer learning through listening; some students prefer doing activities while other prefer reflecting.Some students reason logically, while others reason intuitively, etc. Identifying the learning style of each student, and providing learning content based on these styles represents a good method to enhance the learning quality. However, there are no efforts onhow to detect the students’ learning styles in mobile computer supported collaborative learning (MCSCL) environments. We present in this paper new ways for automatically detecting the learning styles of students in MCSCL environments based on the learning style model of Felder-Silverman. The identified learning styles of students could be then stored and used at anytime toassign each one of them to his/her appropriate learning group.

High levels of Mercury and Lead detected by hair analysis in two Venezuelan environments

Mercury and Lead concentrations obtained by ICP-OAS analysis of human hair from riverside communities along the Orinoco river in the Amazon state (Venezuela) were compared with those from Caracas, Venezuela. Taking into account the characteristics of these two environments and the values of the average concentrations of Mercury and Lead, baselines were established suggesting that gold mining activity near the Orinoco river is responsible for the high levels of Mercury in hair from the Amazon state, whereas automobile activity is responsible for high levels of Lead in hair in Caracas.

Indoor biological agents: evaluation of primary schools environments

Dissertação de mestrado em Human Engineering

Protected environments and substrates for production of genipap seedlings

Genipap (Genipa americana L., Rubiaceae ) is a native Brazilian species and can be used in the recovery of degraded forest areas or for food supply. In order for the species to reach its potential, production of high quality seedlings is essential. The objective of this study was to evaluate genipap seedlings in protected environments and different substrates. The environments tested were: (1) a greenhouse with polyethylene film in the top, with aluminized screen (Aliminet®) of 50%-shading under this film, and lateral sides covered with 50%-shading nylon net (Sombrite®), (2) a shaded hut, all sides covered with 50%-shading nylon net (Sombrite®), and (3) a nursery shelter, with all lateral sides uncovered and the roof covered with leaves of buriti (Mauritia flexuosa). In these environments the following substrates were tested: 50% cattle manure + 50% cassava foliage, 50% cattle manure + 50% Vida Verde®, 50% cattle manure + 50% vermiculite, and 25% cattle manure + 25% vermiculite + 25% of cassava foliage + 25% Vida Verde®. Because there was no repetition of the growth environment, the effect of environment was examined using statistical procedures for analysis of combined experiments. Within environments a completely randomized design was used with five replications. All substrates are suitable for the formation of genipap seedlings, where the recommended substrates are: 50% cattle manure + 50% cassava foliage and 50% cattle manure + 50% Vida Verde® for the greenhouse and the substrates composed of 50% cattle manure + 50% vermiculite and 25% cattle manure + 25% cassava foliage + 25% Vida Verde®+ 25% vermiculite for the shaded hut. The buriti shelter is not recommended for production of genipap seedlings.

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