Adapted Control Methods for Cerebral Palsy Users of an Intelligent Wheelchair

The development of an intelligent wheelchair (IW) platform that may be easily adapted to any commercial electric powered wheelchair and aid any person with special mobility needs is the main objective of this project. To be able to achieve this main objective, three distinct control methods were implemented in the IW: manual, shared and automatic. Several algorithms were developed for each of these control methods. This paper presents three of the most significant of those algorithms with emphasis on the shared control method. Experiments were performed by users suffering from cerebral palsy, using a realistic simulator, in order to validate the approach. The experiments revealed the importance of using shared (aided) controls for users with severe disabilities. The patients still felt having complete control over the wheelchair movement when using a shared control at a 50% level and thus this control type was very well accepted. Thus it may be used in intelligent wheelchairs since it is able to correct the direction in case of involuntary movements of the user but still gives him a sense of complete control over the IW movement.

Analysis of Forest Fires by means of Pseudo Phase Plane and Multidimensional Scaling Methods

Forest fires dynamics is often characterized by the absence of a characteristic length-scale, long range correlations in space and time, and long memory, which are features also associated with fractional order systems. In this paper a public domain forest fires catalogue, containing information of events for Portugal, covering the period from 1980 up to 2012, is tackled. The events are modelled as time series of Dirac impulses with amplitude proportional to the burnt area. The time series are viewed as the system output and are interpreted as a manifestation of the system dynamics. In the first phase we use the pseudo phase plane (PPP) technique to describe forest fires dynamics. In the second phase we use multidimensional scaling (MDS) visualization tools. The PPP allows the representation of forest fires dynamics in two-dimensional space, by taking time series representative of the phenomena. The MDS approach generates maps where objects that are perceived to be similar to each other are placed on the map forming clusters. The results are analysed in order to extract relationships among the data and to better understand forest fires behaviour.

Using Baseline Methods to Identify Non-technical Losses in the Context of Smart Grids

Demand response has gained increasing importance in the context of competitive electricity markets and smart grid environments. In addition to the importance that has been given to the development of business models for integrating demand response, several methods have been developed to evaluate the consumers’ performance after the participation in a demand response event. The present paper uses those performance evaluation methods, namely customer baseline load calculation methods, to determine the expected consumption in each period of the consumer historic data. In the cases in which there is a certain difference between the actual consumption and the estimated consumption, the consumer is identified as a potential cause of non-technical losses. A case study demonstrates the application of the proposed method to real consumption data.

Consumers Performance Evaluation of the Participation in Demand Response Programs Using Baseline Methods

Demand response has gain increasing importance in the context of competitive electricity markets environment. The use of demand resources is also advantageous in the context of smart grid operation. In addition to the need of new business models for integrating demand response, adequate methods are necessary for an accurate determination of the consumers’ performance evaluation after the participation in a demand response event. The present paper makes a comparison between some of the existing baseline methods related to the consumers’ performance evaluation, comparing the results obtained with these methods and also with a method proposed by the authors of the paper. A case study demonstrates the application of the referred methods to real consumption data belonging to a consumer connected to a distribution network.

Contextual Intelligent Load Management Considering Real-Time Pricing in a Smart Grid Environment

The use of demand response programs enables the adequate use of resources of small and medium players, bringing high benefits to the smart grid, and increasing its efficiency. One of the difficulties to proceed with this paradigm is the lack of intelligence in the management of small and medium size players. In order to make demand response programs a feasible solution, it is essential that small and medium players have an efficient energy management and a fair optimization mechanism to decrease the consumption without heavy loss of comfort, making it acceptable for the users. This paper addresses the application of real-time pricing in a house that uses an intelligent optimization module involving artificial neural networks.

Real Time Pricing Approaches to Deal With Unexpected Wind Power Variations

The use of renewables have been increased I several countries around the world, namely in Europe. The wind power is generally the larger renewable resource with very specific characteristics in what concerns its variability and the inherent impacts in the power systems and electricity markets operation. This paper focuses on the Portuguese context of renewables use, including wind power. The work here presented includes the use of a real time pricing methodology developed by the authors aiming the reduction of electricity consumption in the moments of unexpected low wind power. A more specific example of application of real time pricing is demonstrated for the minimization of the operation costs in a distribution network. When facing lower wind power generation than expected from day ahead forecast, demand response is used in order to minimize the impacts of such wind availability change. In this way, consumers actively participate in regulation up and spinning reserve ancillary services through demand response programs.

Analysis of Consumption Data to Detect Commercial Losses Using Performance Evaluation Methods in a Smart Grid

Electric power networks, namely distribution networks, have been suffering several changes during the last years due to changes in the power systems operation, towards the implementation of smart grids. Several approaches to the operation of the resources have been introduced, as the case of demand response, making use of the new capabilities of the smart grids. In the initial levels of the smart grids implementation reduced amounts of data are generated, namely consumption data. The methodology proposed in the present paper makes use of demand response consumers’ performance evaluation methods to determine the expected consumption for a given consumer. Then, potential commercial losses are identified using monthly historic consumption data. Real consumption data is used in the case study to demonstrate the application of the proposed method.

Real-Time Simulation of Real-Time Pricing Demand Response to Meet Wind Variations

Recent changes of paradigm in power systems opened the opportunity to the active participation of new players. The small and medium players gain new opportunities while participating in demand response programs. This paper explores the optimal resources scheduling in two distinct levels. First, the network operator facing large wind power variations makes use of real time pricing to induce consumers to meet wind power variations. Then, at the consumer level, each load is managed according to the consumer preferences. The two-level resources schedule has been implemented in a real-time simulation platform, which uses hardware for consumer’ loads control. The illustrative example includes a situation of large lack of wind power and focuses on a consumer with 18 loads.

Comparison of different methods for work accidents investigation in hospitals: A Portuguese case study

BACKGROUND: The hospital environment has many occupational health risks that predispose healthcare workers to various kinds of work accidents. OBJECTIVE: This study aims to compare different methods for work accidents investigation and to verify their suitability in hospital environment. METHODS: For this purpose, we selected three types of accidents that were related with needle stick, worker fall and inadequate effort/movement during the mobilization of patients. A total of thirty accidents were analysed with six different work accidents investigation methods. RESULTS: The results showed that organizational factors were the group of causes which had the greatest impact in the three types of work accidents. CONCLUSIONS: The methods selected to be compared in this paper are applicable and appropriate for the work accidents investigation in hospitals. However, the Registration, Research and Analysis of Work Accidents method (RIAAT) showed to be an optimal technique to use in this context.

Emerging (Bio)Sensing Technology for Assessing and Monitoring Freshwater Contamination – Methods and Applications

Ecological Water Quality - Water Treatment and Reuse

Combining sparse and dense methods in 6D Visual Odometry

13th International Conference on Autonomous Robot Systems (Robotica), 2013, Lisboa

Reliability of Two Methods for Identifying the Postural Phase of Gait Initiation in Healthy and Post-stroke Subjects

This study aims to compare two methods of assessing the postural phase of gait initiation as to intrasession reliability, in healthy and post-stroke subjects. As a secondary aim, this study aims to analyse anticipatory postural adjustments during gait initiation based on the centre of pressure (CoP) displacements in post-stroke participants. The CoP signal was acquired during gait initiation in fifteen post-stroke subjects and twenty-three healthy controls. Postural phase was identified through a baseline-based method and a maximal displacement based method. In both healthy and post-stroke participants higher intra-class correlation coefficient and lower coefficient of variation values were obtained with the baseline-based method when compared to the maximal displacement based method. Post-stroke participants presented decreased CoP displacement backward and toward the first swing limb compared to controls when the baseline-based method was used. With the maximal displacement based method, there were differences between groups only regarding backward CoP displacement. Postural phase duration in medial-lateral direction was also increased in post-stroke participants when using the maximal displacement based method. The findings obtained indicate that the baseline-based method is more reliable detecting the onset of gait initiation in both groups, while the maximal displacement based method presents greater sensitivity for post-stroke participants.

Knowledge repository framework for crowdsourcing innovation intermediary: a proposal

A crowdsourcing innovation intermediary performs mediation activities between companies that have a problem to solve or that seek a business opportunity, and a group of people motivated to present ideas based on their knowledge, experience and wisdom, taking advantage of technology sharing and collaboration emerging from Web2.0. As far as we know, most of the present intermediaries don´t have, yet, an integrated vision that combines the creation of value through community development, brokering and technology transfer. In this paper we present a proposal of a knowledge repository framework for crowdsourcing innovation that enables effective support and integration of the activities developed in the process of value creation (community building, brokering and technology transfer), modeled using ontology engineering methods.

Modelos Teóricos de Difusão Dérmica: abordagens matemáticas e computacionais para terapias transdérmicas da Obesidade

É de senso comum que os nutrientes são fundamentais à vida e que a subnutrição leva à acumulação de gorduras que pode chegar a casos de obesidade, tendo como consequência inúmeras complicações de saúde. Diferentes estruturas neuroanatómicas do cérebro têm um papel essencial no comportamento digestivo. A ação de várias moléculas de sinalização (hormonas, neurotransmissores e neuropéptidos) resulta na regulação da ingestão de alimentos, sendo que, por exemplo, algumas hormonas podem aumentar a sensação de saciedade podendo diminuir o apetite e a ingestão calórica. A descoberta de hormonas envolvidas no balanço energético proporcionou novas oportunidades para desenvolver meios para o tratamento da obesidade. A transferência de medicação antiobesidade por via tópica ou transdérmica é um desafio pois a pele funciona como uma barreira natural e protetora. Sendo uma barreira com uma grande área de superfície e de fácil acessibilidade, a pele tem potencial interesse na libertação de fármacos específicos a cada terapia. Vários métodos têm sido estudados de modo a permitir um aumento da permeabilidade de moléculas terapêuticas para o interior da pele e através da pele. As biotecnologias transdérmicas são um campo de interesse cada vez maior, devido as aplicações dérmicas e farmacêuticas que lhes estão subjacentes. Existem vários modelos computacionais e matemáticos em uso que permite uma visão mais abrangente de puros dados experimentais e até mesmo permite a extrapolação prática de novas metodologias de difusão dérmica. Contudo, eles compreendem uma complexa variedade de teorias e suposições que atribuem a sua utilização para situações específicas. Este trabalho, primeiramente analisa, de forma extensiva, as várias metodologias teóricas para o estudo da difusão dérmica e sistematiza as suas características, realizando depois a fase prévia duma nova abordagem computacional para o estudo da difusão dérmica, que determina características microscópicas de moléculas capazes de provocar a perda de peso, tais como a Leptina e/ou os seus agonistas.