Abstract
For the project of an Agile/Virtual Enterprise (A/V E) the resources selection is a key factor. The resources systems (output of the selection process) should be prepared to guarantee quality, efficiency and cost-attractiveness, in order to ensure the agility and integrability of the A/V E. This is a difficult matter because it can be a combinatorial and multi-criteria problem. Despite the potential of Value Analysis (VA), none of the resources selection models found in the literature incorporates the evaluation of the resources value. They approach mainly the factors cost and/or time. So, our model constitutes an innovative approach because it gives the highest importance to the value of the resources systems, through the incorporation of VA. The main objective is to quantify the selection process performance with VA integrated into the pre-selection of resources in accordance with the developed model. The paper contribution is the positive confirmation, through the simulation results analysis, of the benefits of VA integration in the resources selection process: greater applicability domain for candidate resources and number of tasks; and reduction of the selection time. In conclusion, the increased efficiency and the superior applicability domain of the model are demonstrated.

Abstract
Assessing physical activity (PA) is a challenging task and many different approaches have been proposed. Direct observation (DO) techniques can objectively code both the behavior and the context in which it occurred, however, they have significant limitations such as the cost and burden associated with collecting and processing data. Therefore, this study evaluated the utility of an automated video analysis system (CAM) designed to record and discriminate the intensity of PA using a subject tracking methodology. The relative utility of the CAM system and DO were compared with criterion data from an objective accelerometry-based device (Actigraph GT3X+). Eight 10 year old children (three girls and five boys) wore the GT3X+ during a standard basketball session. PA was analyzed by two observers using the SOPLAY instrument and by the CAM system. The GT3X+ and the CAM were both set up to collect data at 30 Hz while the DO was performed every two minutes, with 10s of observation for each gender. The GT3X+ was processed using cut points by Evanson and the outcome measure was the percentage of time spent in different intensities of PA. The CAM data were processed similarly using the same speed thresholds as were used in establishing the Evenson cut-off points (light: <2 mph; walking: 2-4 mph; very active: >4 mph). Similar outcomes were computed from the SOPLAY default analyses. A chi-square test was used to test differences in the percentage of time at the three intensity zones (light, walking and very active). The Yates' correction was used to prevent overestimation of statistical significance for small data. When compared with GT3X+, the CAM had better results than the SOPLAY. The chi-square test yielded the following pairwise comparisons: CAM versus GT3x+ was chi(2) (5) = 24.18, p < .001; SOPLAY2 versus GT3x+ was chi(2) (5) = 144.44, p < .001; SOPLAY1 versus GT3x+ was chi(2) (5) = 119.55, p < .001. The differences were smaller between CAM and GT3x+, suggesting that the video tracking system provided better agreement than DO. The small sample size precludes a definitive evaluation but the results show that the CAM video system may have promise for automated coding of physical activity behavior.

Abstract
In the smart grid environment, reserve services (RS) are also expected from the demand side, taking into account the flexibility and availability of loads connected into the grid. This paper proposes a method to calculate the availability of thermal domestic loads for the provision of upward RS, considering some aspects regarding the constructive characteristics of the appliances, as well as the consumer habits and comfort preferences. A case study comprising 500 consumers with three types of domestic thermal loads (electric water heaters, air-conditioners, and refrigerators) will be used to illustrate the method.

Abstract
The combination of top-K network representation of the data stream with community detection is a novel approach to streaming networks sampling. Keeping an always up-to-date sample of the full network, the advantage of this method, compared to previous, is that it preserves larger communities and original network distribution. Empirically, it will also be shown that these techniques, in conjunction with community detection, provide effective ways to perform sampling and analysis of large scale streaming networks with power law distributions.

Abstract

Abstract
A Shopping Centre (SC) is a "shop open to the public", installed in a building, which include parking, several shops, technical, management, and shopping arcade. In the current economic climate, the maintenance of complex buildings, like shopping centres, is performed under a tight budget context, and is essentially based on systems conditions. A maintenance model, to be effective, requires that maintenance service performance, covering the different building systems and components, is measured. This paper presents a methodology to measure the performance of SCs maintenance management through two major performance indicators: the Building Performance Indicator (BPI); and the Maintenance Efficiency Indicator (MEI). The results of its implementation to seven shopping centres, in Portugal, show that the general condition of the facilities is good (overall BPI= 86,45%) but the low MEI values (<0,37) indicates that insufficient resources are allocated to maintenance activities and this can compromise the future condition of the facilities.