A proactive intelligent decision support system for predicting the popularity of online news

"Lecture notes in computer science series, ISSN 0302-9743, vol. 9273"

Intelligent decision support to predict patient barotrauma risk in intensive care units

The occurrence of Barotrauma is identified as a major concern for health professionals, since it can be fatal for patients. In order to support the decision process and to predict the risk of occurring barotrauma Data Mining models were induced. Based on this principle, the present study addresses the Data Mining process aiming to provide hourly probability of a patient has Barotrauma. The process of discovering implicit knowledge in data collected from Intensive Care Units patientswas achieved through the standard process Cross Industry Standard Process for Data Mining. With the goal of making predictions according to the classification approach they several DM techniques were selected: Decision Trees, Naive Bayes and Support Vector Machine. The study was focused on identifying the validity and viability to predict a composite variable. To predict the Barotrauma two classes were created: “risk” and “no risk”. Such target come from combining two variables: Plateau Pressure and PCO2. The best models presented a sensitivity between 96.19% and 100%. In terms of accuracy the values varied between 87.5% and 100%. This study and the achieved results demonstrated the feasibility of predicting the risk of a patient having Barotrauma by presenting the probability associated.

Development of an intelligent bio-based packaging system

[Extrat] Currently there is a growing interest in the development of eco-efficient bio-based packaging, being active, smart and intelligent packaging the most highlighted among various innovations. Intelligent packaging has the ability to detect and mark, in real time, changes that might occur within the package/in the food product. Their main purpose is to help the consumer decide whether to buy a certain food product, ensuring that when it is bought it has not suffered significant changes influencing its quality and safety. (...)

Degradation of all-inkjet-printed organic thin-film transistors with TIPS-pentacene under processes applied in textile manufacturing

Printed electronics represent an alternative solution for the manufacturing of low-temperature and large area flexible electronics. The use of inkjet printing is showing major advantages when compared to other established printing technologies such as, gravure, screen or offset printing, allowing the reduction of manufacturing costs due to its efficient material usage and the direct-writing approach without requirement of any masks. However, several technological restrictions for printed electronics can hinder its application potential, e.g. the device stability under atmospheric or even more stringent conditions. Here, we study the influence of specific mechanical, chemical, and temperature treatments usually appearing in manufacturing processes for textiles on the electrical performance of all-inkjet-printed organic thin-film transistors (OTFTs). Therefore, OTFTs where manufactured with silver electrodes, a UV curable dielectric, and 6,13-bis(triisopropylsilylethynyl) pentance (TIPS-pentacene) as the active semiconductor layer. All the layers were deposited using inkjet printing. After electrical characterization of the printed OTFTs, a simple encapsulation method was applied followed by the degradation study allowing a comparison of the electrical performance of treated and not treated OTFTs. Industrial calendering, dyeing, washing and stentering were selected as typical textile processes and treatment methods for the printed OTFTs. It is shown that the all-inkjet-printed OTFTs fabricated in this work are functional after their submission to the textiles processes but with degradation in the electrical performance, exhibiting higher degradation in the OTFTs with shorter channel lengths (L=10 μm).

Inkjet printing technology for flexible pressure sensors

Tese de Doutoramento Ciência e Engenharia de Polímeros e Compósitos.

The role of automatic shape and position recognitionin streamlining manufacturing

The main features of most components consist of simple basic functional geometries: planes, cylinders, spheres and cones. Shape and position recognition of these geometries is essential for dimensional characterization of components, and represent an important contribution in the life cycle of the product, concerning in particular the manufacturing and inspection processes of the final product. This work aims to establish an algorithm to automatically recognize such geometries, without operator intervention. Using differential geometry large volumes of data can be treated and the basic functional geometries to be dealt recognized. The original data can be obtained by rapid acquisition methods, such as 3D survey or photography, and then converted into Cartesian coordinates. The satisfaction of intrinsic decision conditions allows different geometries to be fast identified, without operator intervention. Since inspection is generally a time consuming task, this method reduces operator intervention in the process. The algorithm was first tested using geometric data generated in MATLAB and then through a set of data points acquired by measuring with a coordinate measuring machine and a 3D scan on real physical surfaces. Comparison time spent in measuring is presented to show the advantage of the method. The results validated the suitability and potential of the algorithm hereby proposed

Aplicação de princípios e técnicas de Lean Manufacturing para melhoria do desempenho de linhas de montagem

Dissertação de mestrado integrado em Engenharia e Gestão Industrial

Development of procedures for the design, optimization and manufacturing of customized orthopaedic and trauma implants: Geometrical/anatomical modelling from 3D medical imaging

Tese de Doutoramento (Programa Doutoral em Engenharia Biomédica)

Development of an intelligent earthwork optimization system

Tese de Doutoramento em Engenharia Civil.

A Real-Time intelligent system for tracking patient condition

Hospitals have multiple data sources, such as embedded systems, monitors and sensors. The number of data available is increasing and the information are used not only to care the patient but also to assist the decision processes. The introduction of intelligent environments in health care institutions has been adopted due their ability to provide useful information for health professionals, either in helping to identify prognosis or also to understand patient condition. Behind of this concept arises this Intelligent System to track patient condition (e.g. critic events) in health care. This system has the great advantage of being adaptable to the environment and user needs. The system is focused in identifying critic events from data streaming (e.g. vital signs and ventilation) which is particularly valuable for understanding the patient’s condition. This work aims to demonstrate the process of creating an intelligent system capable of operating in a real environment using streaming data provided by ventilators and vital signs monitors. Its development is important to the physician because becomes possible crossing multiple variables in real-time by analyzing if a value is critic or not and if their variation has or not clinical importance.

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.

Motivating techniques within Irish and American manufacturing and service companies in the Northwest of Ireland

In today’s world, many companies are concentrating on both their technology and human resources to provide them with their competitive advantage. Hence, understanding what motivates people is particularly important for managers in order to develop and sustain a competitive edge. As a result, numerous theories have been advanced to help our understanding of the subject matter and from these theories many motivational methods have evolved to enhance motivation within the workplace. In addition, research has been conducted on the various types of motivational techniques utilised by companies within Ireland. However, very little research has been completed within specific geographical regions in Ireland concerning the types of motivational techniques implemented at different job levels and their impact on employees work performance. Thus the objective of this research was to identify the motivational techniques utilised at different job levels within large manufacturing and service companies in the Northwest of Ireland and examine how these techniques influence the performance levels of employees. Furthermore, the study examined if these companies have changed from traditional ways of motivating employees to newer techniques. The research methodologies used to undertake the research included interviews with the HR managers and questionnaires completed by different employees at various job levels within the participating companies. Overall the conclusions were varied. Many different types of motivation techniques were found within the study’s participating companies. Irish companies are improving their motivational techniques, however most of these techniques are only used within higher job levels. In contrast to their American counterparts, a variety of motivational techniques are utilised and implemented at all job levels. On a more positive note, the majority of these motivational techniques do increase performance levels at all job levels. From the extensive primary and secondary research conducted, the thesis concludes by offering a number of recommendations to assist companies in further development of their motivational techniques for all job levels. These recommendations hope to augment the success of companies through an enhanced motivated workforce.

Application of multivariate statistical process control to fuel cell manufacturing

Univariate statistical control charts, such as the Shewhart chart, do not satisfy the requirements for process monitoring on a high volume automated fuel cell manufacturing line. This is because of the number of variables that require monitoring. The risk of elevated false alarms, due to the nature of the process being high volume, can present problems if univariate methods are used. Multivariate statistical methods are discussed as an alternative for process monitoring and control. The research presented is conducted on a manufacturing line which evaluates the performance of a fuel cell. It has three stages of production assembly that contribute to the final end product performance. The product performance is assessed by power and energy measurements, taken at various time points throughout the discharge testing of the fuel cell. The literature review performed on these multivariate techniques are evaluated using individual and batch observations. Modern techniques using multivariate control charts on Hotellings T2 are compared to other multivariate methods, such as Principal Components Analysis (PCA). The latter, PCA, was identified as the most suitable method. Control charts such as, scores, T2 and DModX charts, are constructed from the PCA model. Diagnostic procedures, using Contribution plots, for out of control points that are detected using these control charts, are also discussed. These plots enable the investigator to perform root cause analysis. Multivariate batch techniques are compared to individual observations typically seen on continuous processes. Recommendations, for the introduction of multivariate techniques that would be appropriate for most high volume processes, are also covered.

Forearm surface EMG signals recognition and muscoloskeletal system dynamics identification using intelligent computational methods

Biosignals processing, Biological Nonlinear and time-varying systems identification, Electomyograph signals recognition, Pattern classification, Fuzzy logic and neural networks methods

The Determinants of Entry are not Independent of Start-up Size: Some evidence from Spanish manufacturing

In this paper we explore the determinants of firm start-up size of Spanish manufacturing industries. The industries' barriers to entry affect the ability of potential entrants to enter the markets and the size range at which they decide to enter. In order to examine the relationships between barriers to entry and size we applied the quantile regression techniques. Our results indicate that the variables that characterize the structure of the market, the variables that are related to the behaviour of the incumbent firms and the rate of growth of the industries generate different barriers depending on the initial size of the entrants. Keywords: Entry, regression quantiles, start-up size. JEL classification: L110, L600