A knowledge-based framework to facilitate E-training implementation

Dissertação para obtenção do Grau de Mestre em Engenharia Eletrotécnica e de Computadores

A semi-automatic approach to code smells detection

Eradication of code smells is often pointed out as a way to improve readability, extensibility and design in existing software. However, code smell detection remains time consuming and error-prone, partly due to the inherent subjectivity of the detection processes presently available. In view of mitigating the subjectivity problem, this dissertation presents a tool that automates a technique for the detection and assessment of code smells in Java source code, developed as an Eclipse plugin. The technique is based upon a Binary Logistic Regression model that uses complexity metrics as independent variables and is calibrated by expert‟s knowledge. An overview of the technique is provided, the tool is described and validated by an example case study.

How enterprise 2,0 firms take advantage of emergent social software platforms to manage knowledge

This research aims to provide a better understanding on how firms stimulate knowledge sharing through the utilization of collaboration tools, in particular Emergent Social Software Platforms (ESSPs). It focuses on the distinctive applications of ESSPs and on the initiatives contributing to maximize its advantages. In the first part of the research, I have itemized all types of existing collaboration tools and classify them in different categories according to their capabilities, objectives and according to their faculty for promoting knowledge sharing. In the second part, and based on an exploratory case study at Cisco Systems, I have identified the main applications of an existing enterprise social software platform named Webex Social. By combining a qualitative and quantitative approach, as well as combining data collected from survey’s results and from the analysis of the company’s documents, I am expecting to maximize the outcome of this investigation and reduce the risk of bias. Although effects cannot be universalized based on one single case study, some utilization patterns have been underlined from the data collected and potential trends in managing knowledge have been observed. The results of the research have also enabled identifying most of the constraints experienced by the users of the firm’s social software platform. Utterly, this research should provide a primary framework for firms planning to create or implement a social software platform and for firms willing to increase adoption levels and to promote the overall participation of users. It highlights the common traps that should be avoided by developers when designing a social software platform and the capabilities that it should inherently carry to support an effective knowledge management strategy.

The implementation of an Enterprise Geographical Information System to support Cadastre and Expropriation activities.

The processes of mobilization of land for infrastructures of public and private domain are developed according to proper legal frameworks and systematically confronted with the impoverished national situation as regards the cadastral identification and regularization, which leads to big inefficiencies, sometimes with very negative impact to the overall effectiveness. This project report describes Ferbritas Cadastre Information System (FBSIC) project and tools, which in conjunction with other applications, allow managing the entire life-cycle of Land Acquisition and Cadastre, including support to field activities with the integration of information collected in the field, the development of multi-criteria analysis information, monitoring all information in the exploration stage, and the automated generation of outputs. The benefits are evident at the level of operational efficiency, including tools that enable process integration and standardization of procedures, facilitate analysis and quality control and maximize performance in the acquisition, maintenance and management of registration information and expropriation (expropriation projects). Therefore, the implemented system achieves levels of robustness, comprehensiveness, openness, scalability and reliability suitable for a structural platform. The resultant solution, FBSIC, is a fit-for-purpose cadastre information system rooted in the field of railway infrastructures. FBSIC integrating nature of allows: to accomplish present needs and scale to meet future services; to collect, maintain, manage and share all information in one common platform, and transform it into knowledge; to relate with other platforms; to increase accuracy and productivity of business processes related with land property management.

New visualization model for large scale biosignals analysis

Benefits of long-term monitoring have drawn considerable attention in healthcare. Since the acquired data provides an important source of information to clinicians and researchers, the choice for long-term monitoring studies has become frequent. However, long-term monitoring can result in massive datasets, which makes the analysis of the acquired biosignals a challenge. In this case, visualization, which is a key point in signal analysis, presents several limitations and the annotations handling in which some machine learning algorithms depend on, turn out to be a complex task. In order to overcome these problems a novel web-based application for biosignals visualization and annotation in a fast and user friendly way was developed. This was possible through the study and implementation of a visualization model. The main process of this model, the visualization process, comprised the constitution of the domain problem, the abstraction design, the development of a multilevel visualization and the study and choice of the visualization techniques that better communicate the information carried by the data. In a second process, the visual encoding variables were the study target. Finally, the improved interaction exploration techniques were implemented where the annotation handling stands out. Three case studies are presented and discussed and a usability study supports the reliability of the implemented work.

From Consciousness to Knowledge – The Explanatory Power of Revelation

Epistemology in philosophy of mind is a difficult endeavor. Those who believe that our phenomenal life is different from other domains suggest that self-knowledge about phenomenal properties is certain and therefore privileged. Usually, this so called privileged access is explained by the idea that we have direct access to our phenomenal life. This means, in contrast to perceptual knowledge, self-knowledge is non-inferential. It is widely believed that, this kind of directness involves two different senses: an epistemic sense and a metaphysical sense. Proponents of this view often claim that this is due to the fact that we are acquainted with our current experiences. The acquaintance thesis, therefore, is the backbone in justifying privileged access. Unfortunately the whole approach has a profound flaw. For the thesis to work, acquaintance has to be a genuine explanation. Since it is usually assumed that any knowledge relation between judgments and the corresponding objects are merely causal and contingent (e.g. in perception), the proponent of the privileged access view needs to show that acquaintance can do the job. In this thesis, however, I claim that the latter cannot be done. Based on considerations introduced by Levine, I conclude that this approach involves either the introduction of ontologically independent properties or a rather obscure knowledge relation. A proper explanation, however, cannot employ either of the two options. The acquaintance thesis is, therefore, bound to fail. Since the privileged access intuition seems to be vital to epistemology within the philosophy of mind, I will explore alternative justifications. After discussing a number of options, I will focus on the so called revelation thesis. This approach states that by simply having an experience with phenomenal properties, one is in the position to know the essence of those phenomenal properties. I will argue that, after finding a solution for the controversial essence claim, this thesis is a successful replacement explanation which maintains all the virtues of the acquaintance account without necessarily introducing ontologically independent properties or an obscure knowledge relation. The overall solution consists in qualifying the essence claim in the relevant sense, leaving us with an appropriate ontology for phenomenal properties. On the one hand, this avoids employing mysterious independent properties, since this ontological view is physicalist in nature. On the other hand, this approach has the right kind of structure to explain privileged self-knowledge of our phenomenal life. My final conclusion consists in the claim that the privileged access intuition is in fact veridical. It cannot, however, be justified by the popular acquaintance approach, but rather, is explainable by the controversial revelation thesis.

Reactive hybrid knowledge bases

Hybrid knowledge bases are knowledge bases that combine ontologies with non-monotonic rules, allowing to join the best of both open world ontologies and close world rules. Ontologies shape a good mechanism to share knowledge on theWeb that can be understood by both humans and machines, on the other hand rules can be used, e.g., to encode legal laws or to do a mapping between sources of information. Taking into account the dynamics present today on the Web, it is important for these hybrid knowledge bases to capture all these dynamics and thus adapt themselves. To achieve that, it is necessary to create mechanisms capable of monitoring the information flow present on theWeb. Up to today, there are no such mechanisms that allow for monitoring events and performing modifications of hybrid knowledge bases autonomously. The goal of this thesis is then to create a system that combine these hybrid knowledge bases with reactive rules, aiming to monitor events and perform actions over a knowledge base. To achieve this goal, a reactive system for the SemanticWeb is be developed in a logic-programming based approach accompanied with a language for heterogeneous rule base evolution having as its basis RIF Production Rule Dialect, which is a standard for exchanging rules over theWeb.

Semantic enrichment of knowledge sources supported by domain ontologies

This thesis introduces a novel conceptual framework to support the creation of knowledge representations based on enriched Semantic Vectors, using the classical vector space model approach extended with ontological support. One of the primary research challenges addressed here relates to the process of formalization and representation of document contents, where most existing approaches are limited and only take into account the explicit, word-based information in the document. This research explores how traditional knowledge representations can be enriched through incorporation of implicit information derived from the complex relationships (semantic associations) modelled by domain ontologies with the addition of information presented in documents. The relevant achievements pursued by this thesis are the following: (i) conceptualization of a model that enables the semantic enrichment of knowledge sources supported by domain experts; (ii) development of a method for extending the traditional vector space, using domain ontologies; (iii) development of a method to support ontology learning, based on the discovery of new ontological relations expressed in non-structured information sources; (iv) development of a process to evaluate the semantic enrichment; (v) implementation of a proof-of-concept, named SENSE (Semantic Enrichment kNowledge SourcEs), which enables to validate the ideas established under the scope of this thesis; (vi) publication of several scientific articles and the support to 4 master dissertations carried out by the department of Electrical and Computer Engineering from FCT/UNL. It is worth mentioning that the work developed under the semantic referential covered by this thesis has reused relevant achievements within the scope of research European projects, in order to address approaches which are considered scientifically sound and coherent and avoid “reinventing the wheel”.

Tool for discovering sequential patterns in financial markets

The goal of this thesis is the study of a tool that can help analysts in finding sequential patterns. This tool will have a focus on financial markets. A study will be made on how new and relevant knowledge can be mined from real life information, potentially giving investors, market analysts, and economists new basis to make informed decisions. The Ramex Forum algorithm will be used as a basis for the tool, due to its ability to find sequential patterns in financial data. So that it further adapts to the needs of the thesis, a study of relevant improvements to the algorithm will be made. Another important aspect of this algorithm is the way that it displays the patterns found, even with good results it is difficult to find relevant patterns among all the studied samples without a proper result visualization component. As such, different combinations of parameterizations and ways to visualize data will be evaluated and their influence in the analysis of those patterns will be discussed. In order to properly evaluate the utility of this tool, case studies will be performed as a final test. Real information will be used to produce results and those will be evaluated in regards to their accuracy, interest, and relevance.

Level of behavior and knowledge concerning human papillomavirus among university students of a nursing college

INTRODUCTION: Human pappilomavirus is one of the most common sexually transmitted diseases, and persistent HPV infection is considered the most important cause of cervical cancer. It is detected in more than 98% of this type of cancer. This study aimed to determine the level of knowledge concerning human papillomavirus among nursing college students of a private educational institution located in the City of Bauru, SP, and correlate their knowledge according to the course year. METHODS: A descriptive study with a quantitative approach, performed with a questionnaire that permitted the quantification of data and opinions, thus guaranteeing the precision of the results without distortions in analysis or interpretation. The survey was applied to randomly selected 1st, 2nd, 3rd, and 4th-year nursing college students. Twenty students from each level were selected during August 2009, totaling 80 students of both genders. RESULTS: Observation revealed that 4th-year students had greater knowledge than 1st-year students, reflecting the greater period of study, the lack of knowledge of 1st-year students was due to the low level of information acquired before entering college. CONCLUSIONS: The need for complementary studies which determine the profile and knowledge of a larger number of teenagers in relation to HPV was established. The need for educational programs that can overcome this lack of information is undeniable, especially those aimed at making adolescents less susceptible to HPV and other STDs.

Control system for actuation and sensing in digital microfluidics devices

Digital Microfluidics (DMF) is a second generation technique, derived from the conventional microfluidics that instead of using continuous liquid fluxes, it uses only individual droplets driven by external electric signals. In this thesis a new DMF control/sensing system for visualization, droplet control (movement, dispensing, merging and splitting) and real time impedance measurement have been developed. The software for the proposed system was implemented in MATLAB with a graphical user interface. An Arduino was used as control board and dedicated circuits for voltage switching and contacts were designed and implemented in printed circuit boards. A high resolution camera was integrated for visualization. In our new approach, the DMF chips are driven by a dual-tone signal where the sum of two independent ac signals (one for droplet operations and the other for impedance sensing) is applied to the electrodes, and afterwards independently evaluated by a lock-in amplifier. With this new approach we were able to choose the appropriated amplitudes and frequencies for the different proposes (actuation and sensing). The measurements made were used to evaluate the real time droplet impedance enabling the knowledge of its position and velocity. This new approach opens new possibilities for impedance sensing and feedback control in DMF devices.

WebGIS applied to improve spatial knowledge of high school students

This research seeks to design and implement a WebGIS application allowing high school students to work with information related to the disciplinary competencies of the competency-teaching model, in Mexico. This paradigm assumes knowledge to be acquired through the application of new technologies and to link it with everyday life situations of students. The WebGIS provides access to maps regarding natural risks in Mexico, e.g. volcanism, seismic activities, or hurricanes; the prototype's user interface was designed with special emphasis on scholar needs for high school students.

Analysis and visualization of energy use for university campus

The reduction of greenhouse gas emissions is one of the big global challenges for the next decades due to its severe impact on the atmosphere that leads to a change in the climate and other environmental factors. One of the main sources of greenhouse gas is energy consumption, therefore a number of initiatives and calls for awareness and sustainability in energy use are issued among different types of institutional and organizations. The European Council adopted in 2007 energy and climate change objectives for 20% improvement until 2020. All European countries are required to use energy with more efficiency. Several steps could be conducted for energy reduction: understanding the buildings behavior through time, revealing the factors that influence the consumption, applying the right measurement for reduction and sustainability, visualizing the hidden connection between our daily habits impacts on the natural world and promoting to more sustainable life. Researchers have suggested that feedback visualization can effectively encourage conservation with energy reduction rate of 18%. Furthermore, researchers have contributed to the identification process of a set of factors which are very likely to influence consumption. Such as occupancy level, occupants behavior, environmental conditions, building thermal envelope, climate zones, etc. Nowadays, the amount of energy consumption at the university campuses are huge and it needs great effort to meet the reduction requested by European Council as well as the cost reduction. Thus, the present study was performed on the university buildings as a use case to: a. Investigate the most dynamic influence factors on energy consumption in campus; b. Implement prediction model for electricity consumption using different techniques, such as the traditional regression way and the alternative machine learning techniques; and c. Assist energy management by providing a real time energy feedback and visualization in campus for more awareness and better decision making. This methodology is implemented to the use case of University Jaume I (UJI), located in Castellon, Spain.

Creation of a web application for smart park system and parking prediction study for system integration

In the last few years, we have observed an exponential increasing of the information systems, and parking information is one more example of them. The needs of obtaining reliable and updated information of parking slots availability are very important in the goal of traffic reduction. Also parking slot prediction is a new topic that has already started to be applied. San Francisco in America and Santander in Spain are examples of such projects carried out to obtain this kind of information. The aim of this thesis is the study and evaluation of methodologies for parking slot prediction and the integration in a web application, where all kind of users will be able to know the current parking status and also future status according to parking model predictions. The source of the data is ancillary in this work but it needs to be understood anyway to understand the parking behaviour. Actually, there are many modelling techniques used for this purpose such as time series analysis, decision trees, neural networks and clustering. In this work, the author explains the best techniques at this work, analyzes the result and points out the advantages and disadvantages of each one. The model will learn the periodic and seasonal patterns of the parking status behaviour, and with this knowledge it can predict future status values given a date. The data used comes from the Smart Park Ontinyent and it is about parking occupancy status together with timestamps and it is stored in a database. After data acquisition, data analysis and pre-processing was needed for model implementations. The first test done was with the boosting ensemble classifier, employed over a set of decision trees, created with C5.0 algorithm from a set of training samples, to assign a prediction value to each object. In addition to the predictions, this work has got measurements error that indicates the reliability of the outcome predictions being correct. The second test was done using the function fitting seasonal exponential smoothing tbats model. Finally as the last test, it has been tried a model that is actually a combination of the previous two models, just to see the result of this combination. The results were quite good for all of them, having error averages of 6.2, 6.6 and 5.4 in vacancies predictions for the three models respectively. This means from a parking of 47 places a 10% average error in parking slot predictions. This result could be even better with longer data available. In order to make this kind of information visible and reachable from everyone having a device with internet connection, a web application was made for this purpose. Beside the data displaying, this application also offers different functions to improve the task of searching for parking. The new functions, apart from parking prediction, were: - Park distances from user location. It provides all the distances to user current location to the different parks in the city. - Geocoding. The service for matching a literal description or an address to a concrete location. - Geolocation. The service for positioning the user. - Parking list panel. This is not a service neither a function, is just a better visualization and better handling of the information.

Using social semantic knowledge to improve annotations in personal photo collections

Instituto Politécnico de Lisboa (IPL) e Instituto Superior de Engenharia de Lisboa (ISEL)apoio concedido pela bolsa SPRH/PROTEC/67580/2010, que apoiou parcialmente este trabalho