Technology strategies in the process of student retention and efficiency of academic management

This article discusses the application of Information and Communication Technologies and strategies for best practices in order to capture and maintain faculty students' attention. It is based on a case study of ten years, using a complete information system. This system, in addition to be considered an ERP, to support the activities of academic management, also has a strong component of SRM that provides support to academic and administrative activities. It describes the extent to which the presented system facilitates the interaction and communication between members of the academic community, using the Internet, with services available on the Web complementing them with email, SMS and CTI. Through a perception, backed by empirical analysis and results of investigations, it demonstrates how this type of practice may raise the level of satisfaction of the community. In particular, it is possible to combat failure at school, avoid that students leave their course before its completion and also that they recommend them to potential students. In addition, such a strategy also allows strong economies in the management of the institution, increasing its value. As future work, we present the new phase of the project towards implementation of Business Intelligence to optimize the management process, making it proactive. The technological vision that guides new developments to a construction based on Web services and procedural languages is also presented.

Histogram-based DNA analysis for the visualization of chromosome, genome and species information

We describe a novel approach to explore DNA nucleotide sequence data, aiming to produce high-level categorical and structural information about the underlying chromosomes, genomes and species. The article starts by analyzing chromosomal data through histograms using fixed length DNA sequences. After creating the DNA-related histograms, a correlation between pairs of histograms is computed, producing a global correlation matrix. These data are then used as input to several data processing methods for information extraction and tabular/graphical output generation. A set of 18 species is processed and the extensive results reveal that the proposed method is able to generate significant and diversified outputs, in good accordance with current scientific knowledge in domains such as genomics and phylogenetics.