Repositório RCAAP

This paper presents an agent-based simulator designed for analyzing agent market strategies based on a complete understanding of buyer and seller behaviours, preference models and pricing algorithms, considering user risk preferences. The system includes agents that are capable of improving their performance with their own experience, by adapting to the market conditions. In the simulated market agents interact in several different ways and may joint together to form coalitions. In this paper we address multi-agent coalitions to analyse Distributed Generation in Electricity Markets

The aim of this study was to compare the magnitude and pattern of lower limb muscular activity during the sit-to-stand (STS) task with and without upper limb immobilization. The activity of six muscles from each lower limb (Rectus Femoris, Vastus Medialis, Biceps Femoris, Tibialis Anterior, Gastrocnemius Medialis and Soleus) were recorded while 19 young healthy participants performed the STS task with and without an arm sling on their dominant side. Myoelectric signals were collected using BioPlux Research device, and two Bertec force platforms were used to determine different phases of the STS task. The peak of muscular activity and muscle onset times were calculated, two general linear models with an alpha of 0.05 were used between the conditions with and without upper limb immobilization. We found no statistically significant differences in the onset of lower limb muscular activity, and we observed decreased peak of muscular activity in the Rectus Femoris at the immobilized side and an increased peak in the Vastus Medialis at the side opposite to the upper limb immobilized compared to the control condition. We did observe differences in the magnitude of ipsilateral Rectus Femoris and contralateral Vastus Medialis as a consequence of upper limb immobilization.

It is extremely difficult to reduce the relations between the several body parts that perform human motion to a simplified set of features. Therefore, the study of the upper-limb functionality is still in development, partly due to the wider range of actions and strategies for motor execution. This, in turn, leads to inconsistent upper-limb movement parameterization. We propose a methodology to assess and quantify the upper-limb motor execution. Extracting key variables from different sources, we intended to quantify healthy upper-limb movement and use these parameters to quantify motor execution during rehabilitation after stroke. In order to do so, we designed an experimental setup defining a workspace for the execution of the action recording kinematic data. Results reveal an effect of object and instruction on the timing of upper-limb movement, indicating that the spatiotemporal analysis of kinematic data can be used as a quantification parameter for motor rehabilitation stages and methods.

On assistive technology targeted for people with activity limitations and participation, usability issues becomes an essential tool to ensure that the product has the appropriate ergonomics characteristics, in other words, ensure that it fits the specific user's needs. The aim of this study was to analyze the usability of an adaptive seating device for children with neuromotor impairments, by using kinematic indicators of the reaching movement. The study sample consisted of 13 children with associated neurologic conditions. The tests were developed by using a wooden bench height adjustable, integrated with the adaptive seating device under study, and a system to capture three-dimensional image, called Qualisys Track Manager. The following reaching kinematics variables were measured: maximum reaching velocity, movement duration, index of curvature, and unit movements. It was found that the use of the adaptive seating device had a positive impact on upper limb function in children with neuromotor impairments. It was also noticed an improvement in the reaching movement kinematics, which was statistical significant for the index of curvature and unit movements. As main conclusions, it is possible to point out some positive effects that the product under study seems to have on users’ movements, such as the improved movement quality of the upper limb, which could mean a better postural adjustments and higher trunk postural control. By identifying new measures of usability in terms of effectiveness and efficiency for the analyzed device, the results obtained may serve also as performance indicators, providing new data that may help to improve the product and eventually modifying it, in order to turn it more compatible with the needs of the considered target population.

The need for new business models to replace existing ones, soon obsolete, is a subject often discussed among researchers in the area. It is essential to find a practical solution that includes the concepts of demand response and distributed generation in the energy markets, these being the future of the electricity grid. It is believed that these resources can bring advantages to the operation of the system, namely increasing technical efficiency. However, one of the problems is the aggregation of small resources as a result of the associated uncertainties. The authors propose a business model with three main phases used in planning: optimal scheduling, aggregation, and remuneration. In this paper, a new phase was added, the classification, with the main purpose of assisting the aggregator of these small resources in operating situations. The focus is on the fair remuneration of participants in the management of the market, in addition to minimizing operating costs. After testing four different remuneration methods, it was proved that the method proposed by the authors obtained better results, proving the viability of the proposed model.

Background: An increasingly aging society and consequently rising number of patients with poststroke-related neurological dysfunctions are forcing the rehabilitation field to adapt to ever-growing demands. Although clinical reasoning within rehabilitation is dependent on patient movement performance analysis, current strategies for monitoring rehabilitation progress are based on subjective time-consuming assessment scales, not often applied. Therefore, a need exists for efficient nonsubjective monitoring methods. Wearable monitoring devices are rapidly becoming a recognized option in rehabilitation for quantitative measures. Developments in sensors, embedded technology, and smart textile are driving rehabilitation to adopt an objective, seamless, efficient, and cost-effective delivery system. This study aims to assist physiotherapists’ clinical reasoning process through the incorporation of accelerometers as part of an electronic data acquisition system. Methods: A simple, low-cost, wearable device for poststroke rehabilitation progress monitoring was developed based on commercially available inertial sensors. Accelerometry data acquisition was performed for 4 first-time poststroke patients during a reach-press-return task. Results: Preliminary studies revealed acceleration profiles of stroke patients through which it is possible to quantitatively assess the functional movement, identify compensatory strategies, and help define proper movement. Conclusion: An inertial data acquisition system was designed and developed as a low-cost option for monitoring rehabilitation. The device seeks to ease the data-gathering process by physiotherapists to complement current practices with accelerometry profiles and aid the development of quantifiable methodologies and protocols.

Smart home devices currently available on the market can be used for remote monitoring and control. Energy management systems can take advantage of this and deploy solutions that can be implemented in our homes. One of the big enablers is smart plugs that allow the control of electrical resources while providing a retrofitting solution, hence avoiding the need for replacing the electrical devices. However, current so-called smart plugs lack the ability to understand the environment they are in, or the electrical appliance/resource they are controlling. This paper applies environment awareness smart plugs (EnAPlugs) able to provide enough data for energy management systems or act on its own, via a multi-agent approach. A case study is presented, which shows the application of the proposed approach in a house where 17 EnAPlugs are deployed. Results show the ability to shared knowledge and perform individual resource optimizations. This paper evidences that by integrating artificial intelligence on devices, energy advantages can be observed and used in favor of users, providing comfort and savings.

Ankylosing Spondylitis(AS) is a chronic inflammatory rheumatic disease characterized by inflammation of the joints of the spine and sacroiliac and to a lesser percentage of the peripheral joints. It is a debilitating condition which reduces quality of life in patients with AS. The practice of physical therapy is recommended as non-pharmacological treatment as well as the treatment and prevention of associated deformities. To collect and summarize the available evidence in scientific databases to realize the effectiveness of home based and group based programs in patients with AS. Systematic review, where articles for the study were collected from scientific database PubMed. We have found 65 articles with publication date between January 1, 2004 and January 31, 2014. Inclusion and exclusion criteria were established to make the selection of articles to include in the study. All investigators provided their agreement in presencial meeting for a final selection, and at a later stage, the articles were read in full by the three investigators. The present systematic review includes eight randomized controlled trials. All articles show functional benefits in patients with As subject to exercise programsin group based and/or home based. From the eight articles, 4 addressed programs conducted in home based context and 4 addressed in group based context programs. There appearsto be evidence that the programs carried out based on group are more effective than those home based conducted in patients with AS. It was concluded also be advantageous to carry out home-based exercise programsthan the absence of any exercise program.

Postural control, which involves stability and intersegmental orientation against gravity, is considered a prerequisite for movement to occur efficiently and in different contexts [1]. After central nervous system damage, individuals tend to demonstrate motor impairments, which can affect their functional ability in different activities, such as standing and walking [2]. These altered motor behaviours restrict voluntary, well-coordinated and effective movements, which in turn limit a person’s ability to perform everyday tasks [2]. Therefore, this study aimed at analysing the correlation between the orientation of the trunk and lower limbs of individuals after stroke during standing.

The imbalance of muscle strength indicators is harmful for elite sport and, in case of significant asymmetries, it increases the probability of muscular injuries or the deterioration of the athletic performance. So it’s essential the evaluation of these imbalances in Handball, Basketball, Soccer and Volleyball athletes’. Objective: The aim of this study was to verify the existence of Isokinetic muscle imbalances in the profile of professional athletes from various modalities and examine their relationship with the sport practiced. Design: Through an observational, analytical and cross study were evaluated 86 athletes (Handball=14; Basketball=27; Football=25; Volleyball=20) using an isokinetic dynamometer Biodex Medical System 4 ®. The evaluated parameters were the Bilateral Differences and Hamstrings/Quadriceps Ratio at angular velocities of 60 °/s (4 repetitions) and 180 °/s (6 repetitions). Results: The Bilateral Differences (found) between the lower limbs are within the respected normal values (<10%). The Hamstrings / Quadriceps Ratio were higher in Football athletes and were lower in Volleyball athletes comparatively to other modalities. Conclusion: However, the motor skills of each sport do not seem to induce to significant muscular imbalances but each sport requires a specific isokinetic profile.

The rising needs for increased energy efficiency and better use of renewable energy sources bring out the necessity for improved energy management and forecasting models. Electricity consumption, in particular, is subject to large variations due to the effect of multiple variables, such as the temperature, luminosity or humidity, and of course, consumers' habits. Current forecasting models are not able to deal adequately with the influence and correlation between the multiple involved variables. Hence, novel, adaptive forecasting models are needed. This paper presents a novel approach based on multiple artificial intelligence-based forecasting algorithms. The considered algorithms are artificial neural networks, support vector machines hybrid fuzzy inference systems, Wang and Mendel's fuzzy rule learning method and a genetic fuzzy system for fuzzy rule learning based on the MOGUL methodology. These algorithms are used to forecast the electricity consumption of a real office building, using multiple input variables and consumption disaggregation.

As Tecnologias da Informação e Comunicação (TIC) permitem novas estratégias de difusão da informação e novos modelos de comunicação, com a proposta de modificar as atitudes e o comportamento humano em relação à Educação. Actualmente a internet é fundamental como meio de comunicação e partilha de informação. Ao ensino será exigido a utilização de TIC, suportadas na internet, para estabelecer a comunicação professor-aluno e aluno-aluno, para divulgação de conteúdos das unidades curriculares, e mesmo como meio de ensino/aprendizagem. O Portal de Ensino e Aprendizagem do Projecto Electrotécnico (PEAPE) pretende ser uma ferramenta de apoio ao ensino/aprendizagem, de unidades curriculares no Âmbito do projecto electrotécnico.

Aging is a natural process of the individual and is associated with a decline in physical and mental function. Given the high prevalence of older adults worldwide, it becomes ppropriated to identify the consequences of this reduction. The falls appear as a consequence more common in this specific population, which triggers the need to identify the different risk factors, in order to prevent them and create intervention programs in that way.

Mental health professionals, as psychologists, have a demanding and emotionally exhausting profession, which makes it susceptible to occupational risks, namely psychosocial risks. Three areas of psychology practice, Clinical and Health Psychology, Work and Organizational Psychology, and Education Psychology are expose to different working contexts. The purpose of this study was to evaluate psychosocial risks factors and their differences between the three psychology specialties. 339 psychologists participated in the study and results suggest significant differences in terms of high demands and work intensity, working hours, work and employment relations, ethical and values conflicts and work characteristics. In conclusion, this study allows a better understanding to provide strategies for preventing and reducing the incidence of psychosocial risks among psychologists.

The increase of variable renewable energy generation has brought several new challenges to power and energy systems. Solutions based on storage systems and consumption flexibility are being proposed to balance the variability from generation sources that depend directly on environmental conditions. The widespread use of electric vehicles is seen as a resource that includes both distributed storage capabilities and the potential for consumption (charging) flexibility. However, to take advantage of the full potential of electric vehicles’ flexibility, it is essential that proper incentives are provided and that the management is performed with the variation of generation. This paper presents a research study on the impact of the variation of the electricity prices on the behavior of electric vehicle’s users. This study compared the benefits when using the variable and fixed charging prices. The variable prices are determined based on the calculation of distribution locational marginal pricing, which are recalculated and adapted continuously accordingly to the users’ trips and behavior. A travel simulation tool was developed for simulating real environments taking into account the behavior of real users. Results show that variable-rate of electricity prices demonstrate to be more advantageous to the users, enabling them to reduce charging costs while contributing to the required flexibility for the system.

The development of control systems to sustain the level of healthcare-associated infections (HAIs) is an emerging issue for healthcare management. This is partly due to the perception that HAI became a serious negative impact factor on the performance of healthcare organizations and on related public health dimensions. Throughout the decade of 1990 a significant number of international programmes were developed to understand and to promote effective HAIs prevention and control systems: Patient Safety and the quality improvement of healthcare organizations became common concepts in healthcare management. However, regardless of advances in infection control systems, the rates of incidence of HAIs remained relatively unchanged in the last decades. The purpose of this study is to point out barriers that recent international literature has identified as factors hindering the successful development of control systems to prevent HAIs. The international debate on possible alternatives to strengthen this common healthcare management issue, benefits form one such update. A literature review was conducted in a 3-month period by two investigators. The BioMed Central, Pubmed, Emerald, and B-on databases were searched for articles published between January 2006 and September 2011. A standard form was created for data extraction. A total of 49 articles met inclusion criteria. Within the analysed articles, 26 were developed in Europe, 15 were developed in North America; 6 were developed in Asia, and 2 in Australia. Thirty (30) different barriers to effective HAIs control systems were identified. The barriers were clustered by dimensions and sub-dimensions. The largest number of barriers clustered, are associated with structures and processes and also barriers associated with healthcare management processes.

Motivated by increasingly strict policies aiming to reduce the pollutants emission that contribute to the greenhouse gases effect and seeking the sustainability of the electricity sector, buildings have great potential to contribute to these goals. For accounting more than a third of the world's energy consumption and combining the growing incentive in Distributed Generation (DG) and the electric vehicle (EV) industry, smart buildings will be a key development in the years to come. In this way, this work presents an introduction to the linear programming (LP) optimization method and review the main works related to the scope of Smart Buildings (SB) energy resources optimization modeled as LP, with the objective to analyze different approaches taken to meet their goals.

An important tool to manage electrical systems is the knowledge of customers' consumption patterns. Data Mining (DM) emerges as an important tool for extracting information about energy consumption in databases and identifying consumption patterns. This paper presents a short review on DM, with a focus on the characterization of electricity customers supported on knowledge discovery in database (KDD) process. The study includes several steps: first, few concepts of the KDD process are presented; following, a short review of clustering algorithms is presented including partitional, hierarchical, fuzzy, evolutionary methods, and Self-Organizing Maps; finally, the main concepts and methods for load classification, based on load shape indices are presented. The main objective of this work is to present a short review of DM techniques applied to identify typical load profiles in electrical systems and new customers' classification.

In many large-scale and time-consuming problems, the application of metaheuristics becomes essential, since these methods enable achieving very close solutions to the exact one in a much shorter time. In this work, we address the problem of portfolio optimization applied to electricity markets negotiation. As in a market environment, decision-making is carried out in very short times, the application of the metaheuristics is necessary. This work proposes a Hybrid model, combining a simplified exact resolution of the method, as a means to obtain the initial solution for a Particle Swarm Optimization (PSO) approach. Results show that the presented approach is able to obtain better results in the metaheuristic search process.

A new era of cleaner distributed generators, like wind and solar, dispersed along the distribution network are gaining great importance and contributing to the environment and political goals. However, the variability and intermittency of those generators pose new complexities and challenges to the network planning. This research paper proposes an innovative stochastic methodology to deal with the expansion planning of large distribution networks in a smart grid context with high penetration of distributed renewable energy sources and considering the seasonal impact. Also, new power lines locations and types, the size and the location of energy storage systems are considered in the optimization. A distribution network with 180 buses located in Portugal considering high distributed generators penetration is used to illustrate the application of the proposed methodology. The results demonstrate the advantage of the stochastic model when compared with a deterministic formulation, avoiding the need for larger investments in new lines and energy storage systems.