Estimativa dos parâmetros de compactação de solos usando técnicas de data mining

Dissertação de mestrado integrado em Engenharia Civil

Plataforma de apoio à decisão nos cuidados de ginecologia e obstetrícia

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

Antibiofilm strategies in the food industry

Biofilms in food processing plants represent not only a problem to human health but also cause economic losses by technical failure in several systems. In fact, many foodborne outbreaks have been found to be associated with biofilms. Biofilms may be prevented by regular cleaning and disinfection, but this does not completely prevent biofilm formation. Besides, due to their diversity and to the development of specialized phenotypes, it is well known that biofilms are more resistant to cleaning and disinfection than planktonic microorganisms. In recent years, a considerable effort has been made in the prevention of microbial adhesion and biofilm formation on food processing surfaces and novel technologies have been introduced. In this context, this chapter discusses the main conventional and emergent strategies that have been employed to prevent bacterial adhesion to food processing surfaces and thus to efficiently maintain good hygiene throughout the food industries.

Introduction [to Food Safety in the Seafood Industry: A practical guide for ISO 22000 and FSSC 22000 implementation]

The prelims comprise: * Half-Title Page * Dedication Page * Title Page * Copyright Page * Table of Contents * Foreword * Acknowledgements * Disclaimer * Introduction

Pervasive decision support to predict football corners and goals by means of data mining

Football is considered nowadays one of the most popular sports. In the betting world, it has acquired an outstanding position, which moves millions of euros during the period of a single football match. The lack of profitability of football betting users has been stressed as a problem. This lack gave origin to this research proposal, which it is going to analyse the possibility of existing a way to support the users to increase their profits on their bets. Data mining models were induced with the purpose of supporting the gamblers to increase their profits in the medium/long term. Being conscience that the models can fail, the results achieved by four of the seven targets in the models are encouraging and suggest that the system can help to increase the profits. All defined targets have two possible classes to predict, for example, if there are more or less than 7.5 corners in a single game. The data mining models of the targets, more or less than 7.5 corners, 8.5 corners, 1.5 goals and 3.5 goals achieved the pre-defined thresholds. The models were implemented in a prototype, which it is a pervasive decision support system. This system was developed with the purpose to be an interface for any user, both for an expert user as to a user who has no knowledge in football games.

Towards a pervasive data mining engine: architecture overview

Current data mining engines are difficult to use, requiring optimizations by data mining experts in order to provide optimal results. To solve this problem a new concept was devised, by maintaining the functionality of current data mining tools and adding pervasive characteristics such as invisibility and ubiquity which focus on their users, providing better ease of use and usefulness, by providing autonomous and intelligent data mining processes. This article introduces an architecture to implement a data mining engine, composed by four major components: database; Middleware (control); Middleware (processing); and interface. These components are interlinked but provide independent scaling, allowing for a system that adapts to the user’s needs. A prototype has been developed in order to test the architecture. The results are very promising and showed their functionality and the need for further improvements.

Predicting triage waiting time in maternity emergency care by means of data mining

Healthcare organizations often benefit from information technologies as well as embedded decision support systems, which improve the quality of services and help preventing complications and adverse events. In Centro Materno Infantil do Norte (CMIN), the maternal and perinatal care unit of Centro Hospitalar of Oporto (CHP), an intelligent pre-triage system is implemented, aiming to prioritize patients in need of gynaecology and obstetrics care in two classes: urgent and consultation. The system is designed to evade emergency problems such as incorrect triage outcomes and extensive triage waiting times. The current study intends to improve the triage system, and therefore, optimize the patient workflow through the emergency room, by predicting the triage waiting time comprised between the patient triage and their medical admission. For this purpose, data mining (DM) techniques are induced in selected information provided by the information technologies implemented in CMIN. The DM models achieved accuracy values of approximately 94% with a five range target distribution, which not only allow obtaining confident prediction models, but also identify the variables that stand as direct inducers to the triage waiting times.

Predicting pre-triage waiting time in a maternity emergency room through data mining

An unsuitable patient flow as well as prolonged waiting lists in the emergency room of a maternity unit, regarding gynecology and obstetrics care, can affect the mother and child’s health, leading to adverse events and consequences regarding their safety and satisfaction. Predicting the patients’ waiting time in the emergency room is a means to avoid this problem. This study aims to predict the pre-triage waiting time in the emergency care of gynecology and obstetrics of Centro Materno Infantil do Norte (CMIN), the maternal and perinatal care unit of Centro Hospitalar of Oporto, situated in the north of Portugal. Data mining techniques were induced using information collected from the information systems and technologies available in CMIN. The models developed presented good results reaching accuracy and specificity values of approximately 74% and 94%, respectively. Additionally, the number of patients and triage professionals working in the emergency room, as well as some temporal variables were identified as direct enhancers to the pre-triage waiting time. The imp lementation of the attained knowledge in the decision support system and business intelligence platform, deployed in CMIN, leads to the optimization of the patient flow through the emergency room and improving the quality of services.

Real-Time decision support using data mining to predict blood pressure critical events in intensive medicine patients

Patient blood pressure is an important vital signal to the physicians take a decision and to better understand the patient condition. In Intensive Care Units is possible monitoring the blood pressure due the fact of the patient being in continuous monitoring through bedside monitors and the use of sensors. The intensivist only have access to vital signs values when they look to the monitor or consult the values hourly collected. Most important is the sequence of the values collected, i.e., a set of highest or lowest values can signify a critical event and bring future complications to a patient as is Hypotension or Hypertension. This complications can leverage a set of dangerous diseases and side-effects. The main goal of this work is to predict the probability of a patient has a blood pressure critical event in the next hours by combining a set of patient data collected in real-time and using Data Mining classification techniques. As output the models indicate the probability (%) of a patient has a Blood Pressure Critical Event in the next hour. The achieved results showed to be very promising, presenting sensitivity around of 95%.

How does banking industry influence economic growth in Latin American countries?

Mestrado em Finanças

Impact of wind power generation on the electricity supply industry

The objective of this dissertation is to investigate the effect wind energy has on the Electricity Supply Industry in Ireland. Wind power generation is a source of renewable energy that is in abundant supply in Ireland and is fast becoming a resource that Ireland is depending on as a diverse and secure of supply of energy. However, wind is an intermittent resource and coupled with a variable demand, there are integration issues with balancing demand and supply effectively. To maintain a secure supply of electricity to customers, it is necessary that wind power has an operational reserve to ensure appropriate backup for situations where there is low wind but high demand. This dissertation examines the affect of this integration by comparing wind generation to that of conventional generation in the national grid. This is done to ascertain the cost benefits of wind power generation against a scenario with no wind generation. Then, the analysis examines to see if wind power can meet the pillars of sustainability. This entails looking at wind in a practical scenario to observe how it meets these pillars under the criteria of environmental responsibility, displacement of conventional fuel, cost competitiveness and security of supply.

A comparison of environmental licensing systems in operation in the wood panel manufacturing industry in the Northern Hemisphere

The objective of this thesis is to compare and contrast environmental licensing systems, for the wood panel industry, in a number of countries in order to determine which system is the best from an environmental and economic point of view. The thesis also examines the impact which government can have on industry and the type of licensing system in operation in a country. Initially, the thesis investigates the origins of the various environmental licensing systems which are in operation in Ireland, Scotland, Wales, France, USA and Canada. It then examines the Environmental Agencies which control and supervise industry in these countries. The impact which the type of government (i.e. unitary or federal) in charge in any particular country has on industry and the Regulatory Agency in that country is then described. Most of the mills in the thesis make a product called OSB (Oriented Strand Board) and the manufacturing process is briefly described in order to understand where the various emissions are generated. The main body of the thesis examines a number of environmental parameters which have emission limit values in the licenses examined, although not all of these parameters have emission limit values in all of the licenses. All of these parameters are used as indicators of the potential impact which the mill can have on the environment. They have been set at specific levels by the Environmental Agencies in the individual countries to control the impact of the mill. Following on from this, the two main types of air pollution control equipment (WESPs and RTOs) are described in regard to their function and capabilities. The mill licenses are then presented in the form of results tables which compare air results and water results separately. This is due to the fact that the most significant emission from this type of industry is to air. A matrix system is used to compare the licenses so that the comparison can be as objective as possible. The discussion examines all of the elements previously described and from this it was concluded that the IPC licensing system is the best from an environmental and economic point of view. It is a much more expensive system to operate than the other systems examined, but it is much more comprehensive and looks at the mill as a whole rather than fragmenting it. It was also seen that the type of environmental licensing system which is in place in a country can play a role in the locating of an industry as certain systems were seen to have more stringent standards attached to them. The type of standard in place in a country is in turn influenced by the type of government which is in place in that country.

Green furniture: sustainable design guidelines for the Irish furniture and wood products industry.

This thesis presents the research and development of sustainable design guidelines for the furniture and wood products industry, suitable for sustainably enhancing design, manufacturing and associated activities. This sustainable guideline is based on secondary research conducted on subject areas such as ‘eco’ design, ‘green’ branding and ‘green’ consumerism, as well as an examination of existing certifications and sustainable tools techniques and methodologies, national and international drivers for sustainable development and an overview of sustainability in the Irish furniture manufacturing context. The guideline was further developed through primary research. This consisted of a focus group attended by leading Irish designers, manufacturers and academics in the area of furniture and wood products. This group explored the question of ‘green branding’ saturation in the market and the viability of investing in sustainability just yet. Participants stated that they felt the market for ‘green’ products is evolving very slowly and that there is no metric or legal framework present to audit whether or not companies are producing products that really embody sustainability. All the participants believed that developing and introducing a new certification process to incorporate a sustainable design process was a viable and necessary solution to protecting Irish furniture and wood manufacturers going forward. For the purposes of the case study, the author investigated a ‘sustainable’ design process for Team woodcraft, Ltd., through the design and development of a ‘sustainable’ children’s furniture range. The case study followed a typical design and development process; detailing customer design specifications, concept development and refinement and cumulating in final prototype, as well as associated engineering drawings. Based on this primary and secondary research, seven fundamental core principles for this sustainable guideline have been identified by the author. The author then used these core principles to expand into guidelines for the basis of proposed new Irish sustainable design guidelines for the furniture and wood products industry, the concept of which the author has named ‘Green Dot’. The author suggests that the ‘Green Dot’ brand or logo could be used to market an umbrella network of Irish furniture designers and manufactures who implement the recommended sustainable techniques.