Proposal for shared services performance management model applied to portugueses public administration

Comunicação apresentada no 8º Congresso Nacional de Administração Pública - Desafios e Soluções, em Carcavelos de 21 a 22 de Novembro de 2011.

Alkaline soluble Trypanosoma cruzi epimastigote antigen (ASEA) applied to dot-ELISA

The alkaline soluble Trypanosoma cruzi epimastigote antigen (ASEA) was assessed in dot-ELISA for the diagnosis of Chagas' disease. Serum samples (355) from chagasic and non-chagasic patients were studied, and IgG antibodies to ASEA were found in all patients with chronic Chagas' disease. In non-chagasic patients 95.6% were negative, except for those with leishmaniasis (visceral and mucocutaneous), and some patients from control group reacted in low titers. The data indicate that dot-ELISA using ASEA is suitable for seroepidemiologic surveys to be employed in endemic areas for Chagas' disease.

Lean applied to logistics: a case study

This project aims to study the implementation of Lean principles and tools in several levels of logistics, from internal logistics to interface with distribution center and suppliers, in an industrial plant. The main focus of all efforts is to create the conditions to approach the continuous flow scenario in the manufacturing processes. The subject of improvement actions is a company whose core activity is car seat production, more specifically the car seat cover production and assembly. This focuses the assembly process, which requires the usage of a considerable variety of components and therefore is an important obstacle to the implementation of continuous flow. The most salient issues are related with inefficient interaction between sections and late supply of components in assembly lines, forcing the operator to abandon his work station and leading to production interruption. As an operational methodology, actions from Lean philosophy and optimization were implemented according to project management principles.

Parametric analog signal amplification applied to nanoscale cmos wireless digital transceivers

Thesis presented in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the subject of Electrical and Computer Engineering by the Universidade Nova de Lisboa,Faculdade de Ciências e Tecnologia

MCDA applied to performance appraisal of short-haul truck drivers: a case study in a portuguese trucking company

Performance appraisal increasingly assumes a more important role in any organizational environment. In the trucking industry, drivers are the company's image and for this reason it is important to develop and increase their performance and commitment to the company's goals. This paper aims to create a performance appraisal model for trucking drivers, based on a multi-criteria decision aid methodology. The PROMETHEE and MMASSI methodologies were adapted using the criteria used for performance appraisal by the trucking company studied. The appraisal involved all the truck drivers, their supervisors and the company's Managing Director. The final output is a ranking of the drivers, based on their performance, for each one of the scenarios used. The results are to be used as a decision-making tool to allocate drivers to the domestic haul service.

Decision support tool for Virtual Power Players: Hybrid Particle Swarm Optimization applied to Day-ahead Vehicle-To-Grid Scheduling

This paper presents a decision support tool methodology to help virtual power players (VPPs) in the Smart Grid (SGs) context to solve the day-ahead energy resource scheduling considering the intensive use of Distributed Generation (DG) and Vehicle-To-Grid (V2G). The main focus is the application of a new hybrid method combing a particle swarm approach and a deterministic technique based on mixedinteger linear programming (MILP) to solve the day-ahead scheduling minimizing total operation costs from the aggregator point of view. A realistic mathematical formulation, considering the electric network constraints and V2G charging and discharging efficiencies is presented. Full AC power flow calculation is included in the hybrid method to allow taking into account the network constraints. A case study with a 33-bus distribution network and 1800 V2G resources is used to illustrate the performance of the proposed method.

Simulated Annealing Approach Applied to the Energy Resource Management Considering Demand Response for Electric Vehicle

The aggregation and management of Distributed Energy Resources (DERs) by an Virtual Power Players (VPP) is an important task in a smart grid context. The Energy Resource Management (ERM) of theses DERs can become a hard and complex optimization problem. The large integration of several DERs, including Electric Vehicles (EVs), may lead to a scenario in which the VPP needs several hours to have a solution for the ERM problem. This is the reason why it is necessary to use metaheuristic methodologies to come up with a good solution with a reasonable amount of time. The presented paper proposes a Simulated Annealing (SA) approach to determine the ERM considering an intensive use of DERs, mainly EVs. In this paper, the possibility to apply Demand Response (DR) programs to the EVs is considered. Moreover, a trip reduce DR program is implemented. The SA methodology is tested on a 32-bus distribution network with 2000 EVs, and the SA results are compared with a deterministic technique and particle swarm optimization results.

Adaptive Learning in Games: Defining Profiles of Competitor Players

Artificial Intelligence has been applied to dynamic games for many years. The ultimate goal is creating responses in virtual entities that display human-like reasoning in the definition of their behaviors. However, virtual entities that can be mistaken for real persons are yet very far from being fully achieved. This paper presents an adaptive learning based methodology for the definition of players’ profiles, with the purpose of supporting decisions of virtual entities. The proposed methodology is based on reinforcement learning algorithms, which are responsible for choosing, along the time, with the gathering of experience, the most appropriate from a set of different learning approaches. These learning approaches have very distinct natures, from mathematical to artificial intelligence and data analysis methodologies, so that the methodology is prepared for very distinct situations. This way it is equipped with a variety of tools that individually can be useful for each encountered situation. The proposed methodology is tested firstly on two simpler computer versus human player games: the rock-paper-scissors game, and a penalty-shootout simulation. Finally, the methodology is applied to the definition of action profiles of electricity market players; players that compete in a dynamic game-wise environment, in which the main goal is the achievement of the highest possible profits in the market.

Algorithms for time series clustering applied to biomedical signals

Thesis submitted in the fulfillment of the requirements for the Degree of Master in Biomedical Engineering

New Strategies on Molecular Biology Applied to Microbial Systematics

Systematics is the study of diversity of the organisms and their relationships comprising classification, nomenclature and identification. The term classification or taxonomy means the arrangement of the organisms in groups (rate) and the nomenclature is the attribution of correct international scientific names to organisms and identification is the inclusion of unknown strains in groups derived from classification. Therefore, classification for a stable nomenclature and a perfect identification are required previously. The beginning of the new bacterial systematics era can be remembered by the introduction and application of new taxonomic concepts and techniques, from the 50’s and 60’s. Important progress were achieved using numerical taxonomy and molecular taxonomy. Molecular taxonomy, brought into effect after the emergence of the Molecular Biology resources, provided knowledge that comprises systematics of bacteria, in which occurs great evolutionary interest, or where is observed the necessity of eliminating any environmental interference. When you study the composition and disposition of nucleotides in certain portions of the genetic material, you study searching their genome, much less susceptible to environmental alterations than proteins, codified based on it. In the molecular taxonomy, you can research both DNA and RNA, and the main techniques that have been used in the systematics comprise the build of restriction maps, DNA-DNA hybridization, DNA-RNA hybridization, sequencing of DNA sequencing of sub-units 16S and 23S of rRNA, RAPD, RFLP, PFGE etc. Techniques such as base sequencing, though they are extremely sensible and greatly precise, are relatively onerous and impracticable to the great majority of the bacterial taxonomy laboratories. Several specialized techniques have been applied to taxonomic studies of microorganisms. In the last years, these have included preliminary electrophoretic analysis of soluble proteins and isoenzymes, and subsequently determination of deoxyribonucleic acid base composition and assessment of base sequence homology by means of DNA-RNA hybrid experiments beside others. These various techniques, as expected, have generally indicated a lack of taxonomic information in microbial systematics. There are numberless techniques and methodologies that make bacteria identification and classification study possible, part of them described here, allowing establish different degrees of subspecific and interspecific similarity through phenetic-genetic polymorphism analysis. However, was pointed out the necessity of using more than one technique for better establish similarity degrees within microorganisms. Obtaining data resulting from application of a sole technique isolatedly may not provide significant information from Bacterial Systematics viewpoint

Health care marketing: the theory of planned behavior applied to patients' choise between private and public providers in the portuguese health care system.

Dissertation submitted in partial fulfillment of the requirements for degree of Master in Statistics and Information Management.

Sol-gel-based biosensing applied to medicinal science

Biosensors have opened new horizons in biomedical analysis, by ensuring increased assay speed and flexibility, and allowing point-of-care applications, multi-target analyses, automation and reduced costs of testing. This has been a result of many studies merging nanotechnology with biochemistry over the years, thereby enabling the creation of more suitable environments to biological receptors and their substitution by synthetic analogue materials. Sol-gel chemistry, among other materials, is deeply involved in this process. Sol-gel processing allows the immobilization of organic molecules, biomacromolecules and cells maintaining their properties and activities, permitting their integration into different transduction devices, of electrochemical or optical nature, for single or multiple analyses. Sol-gel also allows to the production of synthetic materials mimicking the activity of natural receptors, while bringing advantages, mostly in terms of cost and stability. Moreover, the biocompatibility of sol-gel materials structures of biological nature allowed the use of these materials in emerging in vivo applications. In this chapter, biosensors for biomedical applications based on sol-gel derived composites are presented, compared and described, along with current emerging applications in vivo, concerning drug delivery or biomaterials. Sol-gel materials are shown as a promising tool for current, emerging and future medical applications. - See more at: http://www.eurekaselect.com/127191/article#sthash.iPqqyhox.dpuf

Autonomous guided vehicles applied to industrial engineering and management studies

This article presents a framework to an Industrial Engineering and Management Science course from School of Management and Industrial Studies using Autonomous Ground Vehicles (AGV) to supply materials to a production line as an experimental setup for the students to acquire knowledge in the production robotics area. The students must be capable to understand and put into good use several concepts that will be of utmost importance in their professional life such as critical decisions regarding the study, development and implementation of a production line. The main focus is a production line using AGVs, where the students are required to address several topics such as: sensors actuators, controllers and an high level management and optimization software. The presented framework brings to the robotics teaching community methodologies that allow students from different backgrounds, that normally don’t experiment with the robotics concepts in practice due to the big gap between theory and practice, to go straight to ”making” robotics. Our aim was to suppress the minimum start point level thus allowing any student to fully experience robotics with little background knowledge.