Articles — Thesis

Research about recommendation systems has increased due to the amount of information that it is available to individuals. In the music context these systems help the individual to filter and discover new songs according the individual's taste. Most of the business music companies use a recommendation system, based on the characteristics of a song listened by an individual, but a group recommendation system is still underexplored. For a shared environment when there is music, the songs selection will be more efficient if a group recommendation system is used. The goal of this project is to develop a music recommendation for a group that, is sharing the same environment, taking into consideration the context. For this reason, in this work we will employ the Spotify API to recover the data of playlists that were listened by an individual, collecting its preferences and adding them to the others individuals playlists.

Bachelor thesis on Upscaling the extracellular glucose oxidase production in Aspergillus niger var tubingensis strain Ed8 Grade: ~95% Abbreviation system included.

Chapters 1-3 of my PhD dissertation.

This master thesis aims to investigate and to assess the fatigue life of a component that undergoes cyclic thermal loads. This study will consider different approaches through the use of different material models, providing a final comparison of the assessed fatigue life. The case study is a cylindrical copper mold used for continuous casting of steel; in order to work at high temperature the mold is properly cooled, but nevertheless high stresses arise due to the huge thermal flux and its uneven distribution. The beginning of this work is focused on understanding theories and models available in literature in order to implement data in a finite element software. A comparison of two software (Ansys and Marc Mentat) is carried out, with the purpose of verifying experimental data coming from another work [3]. Subsequently we use Marc Mentat to define a coupled thermal-mechanical analysis, and we perform it using a combined model. A huge computational time is required to get the solution, so other models were exploited in order to save time, and the variation of the obtained solution was evaluated. Several simulations are performed for reaching stabilized conditions, from where strain data will be used to define fatigue life through the number of cycles to failure. The subsequent chapter takes care of this last concept, giving a brief explanation of fatigue and using data coming from previous simulations for assessing fatigue life. A final comparison is provided with the purpose of finding a trade off between the solution’s reliability and the time employed. In the appendix the macro used for the computed simulations are attached.

There are several voice communication systems that are used nowadays which are capable of maintain voice calls between two users in real time. Telephones are widely used all around the world in an unlimited kind of situations. All of these situations expose the microphone (or microphones) of the phones to different and unpredictable noises, as street noise, sea noise, rain noise, wind noise, unwanted voices, car motors, etc. As microphones capture all the sounds around it, including the wanted voice and the unwanted noises, it is necessary to implement digital real time filters capable of attenuate as much as possible all the surrounding noises. It exists a large quantity of noise reduction methods that have been used in the calling algorithms of phones. Even if these methods have had, in general, a good performance, there is still a research being done in this area in order to improve the current results. Because of this, the multichannel methods were created (using multiple microphones) as well as new algorithms that pretend to have a better noise reduction than the single channel methods. Most of these methods require a speech presence probability (SPP) method to achieve the noise reduction. The following document presents a research about different SPP methods as well as a comparison between these. This includes an explanation on how theses algorithm work, a Matlab implementation using real voice and noise recordings and objective tests of the filter.

The purpose of this work is to outline the first steps taken towards the building of an automatic interpretation and hypothesis generation machine. The contents of this thesis describe the framework built to parse and manipulate the knowl- edge assemblies encoded in BEL, which enables BEL to act as a semantic inte- gration layer for heterogeneous data and knowledge sources, the development of a framework for automatic integration of relevant knowledge from structured sources, and the development of schema-free analytical techniques to generate data-driven hypothesis.

The usage of software has grown as computers become popular. There have emerged, both in academia and in the market, technological solutions for several areas, among them education. On the other hand, classroom teaching and learning continues to suffer from classical educational problems such as lack of student and teacher motivation and lack of clear educational goals. And although software supports learning across a range of disciplines and ages, children's audiences, especially in mathematics, have been little contemplated with the benefits that technological solutions can bring. Therefore, the use of pedagogical approaches, such as Bloom's Taxonomy and Formative Assessments, together with gamification techniques, such as Octalysis, can be used to develop a technological solution that contemplates this public. The present work aims to propose the development of a software to assist the teaching and learning of mathematics for children in the classroom.

In Email Analytics, our main focus on criminal and civil investigation from large email dataset. It is very difficult to deal with challenging task for investigator due to large size of email dataset. This paper offer an interactive email analytics various to current and manually intensive technique is used for search evidence from large email dataset. In investigation process, many emails are irrelevant to the investigation so it will force investigator to search carefully through email in order to find relevant emails manually. This process is very costly in terms of money and times. To help to investigation process. We combine Elasticsearch, Logstash and Kibana for data storing, data preprocessing, data visualization and data analytics and displaying results. In this process reduce the number of email which are irrelevant for investigation. It shows the relationship between them and also analyzing the email corpus based on topic relation using text mining.

General Game Playing (GGP) is the playing of a wide variety games you may have never seen before, by being told nothing but the rules of the game at run time. This sets it apart from traditional specific game players, like the famous chess player Deep Blue. Deep Blue can beat the world chess champion at chess however, it has absolutely no idea how to play checkers. It is designed for one particular game and cannot adapt to rule changes, and certainly cannot play entirely different games. The goal of this project is to create a program that will play a wide variety of 2d games given descriptions of their rules without the creator of the program having ever known of the games. This report will cover the design and implementation of this project, as well as the background research performed and reflections on the outcome of the project.