The reliability of video based time motion analysis

Time motion analysis is extensively used to assess the demands of team sports. At present there is only limited information on the reliability of measurements using this analysis tool. The aim of this study was to establish the reliability of an individual observer's time motion analysis of rugby union. Ten elite level rugby players were individually tracked in Southern Hemisphere Super 12 matches using a digital video camera. The video footage was subsequently analysed by a single researcher on two occasions one month apart. The test-retest reliability was quantified as the typical error of measurement (TEM) and rated as either good (10% TEM). The total time spent in the individual movements of walking, jogging, striding, sprinting, static exertion and being stationary had moderate to poor reliability (5.8-11.1% TEM). The frequency of individual movements had good to poor reliability (4.3-13.6% TEM), while the mean duration of individual movements had moderate reliability (7.1-9.3% TEM). For the individual observer in the present investigation, time motion analysis was shown to be moderately reliable as an evaluation tool for examining the movement patterns of players in competitive rugby. These reliability values should be considered when assessing the movement patterns of rugby players within competition.

Reproducibility of a laboratory-based 40-km cycle time-trial on a stationary wind-trainer in highly trained cyclists

The purpose of the present study was to examine the reproducibility of laboratory-based 40-km cycle time-trial performance on a stationary wind-trainer. Each week, for three consecutive weeks, and on different days, forty-three highly trained male cyclists ((x) over bar +/- SD; age = 25 +/- 6 y; mass = 75 +/- 7 kg; peak oxygen uptake [(V) over dot O-2 peak] = 64.8 +/- 5.2 ml x kg(-1) x min(-1)) performed: 1) a (V) over dot O-2 peak test, and 2) a 40-km time-trial on their own racing bicycle mounted to a stationary wind-trainer (Cateye - Cyclosimulator). Data from all tests were compared using a one-way analysis of variance. Performance on the second and third 40-km time-trials were highly related (r = 0.96; p < 0.001), not significantly different (57:21 +/- 2:57 vs. 57:12 +/- 3:14 min:s), and displayed a low coefficient of variation (CV) = 0.9 +/- 0.7%. Although the first 40-km time-trial (58:43 +/- 3:17min:s) was not significantly different from the second and third tests (p = 0.06), inclusion of the first test in the assessment of reliability increased within-subject CV to 3.0 +/- 2.9%. 40-km time-trial speed (km x h(-1)) was significantly (p < 0.001) related to peak power output (W; r = 0.75), (V) over dot O-2 peak (1 x min(-1); r = 0.53), and the second ventilatory turnpoint (1 x min(-1); r = 0.68) measured during the progressive exercise tests. These data demonstrate that the assessment of 40-km cycle time-trial performance in well-trained endurance cyclists on a stationary wind-trainer is reproducible, provided the athletes perform a familiarization trial.

Clinical aspects of gestational trophoblastic disease: A review based partly on 25-year experience of a statewide registry

Background: Gestational trophoblastic disease is a fascinating group of pregnancy disorders characterised by abnormal proliferation of trophoblast, ranging from benign to malignant. Because the disease is uncommon, there is a need to formulate management with the assistance of collective information. Methodology: A review of available information from English written literature was undertaken especially data reported by registries around the world (Charing Cross Hospital in England, the North-western University and the New England area in the USA as well as our own experience in Queensland, Australia). Where possible, collated data from relevant studies were analysed to answer some of the questions posed in clinical practice, with reference to metastatic disease to liver and brain, twinning of molar gestation and coexisting fetus, and placental-site tumour. Results: We found that molar gestation can be classified according to its clinical presentation which influences the time taken to reach human chorionic gonadotropin (HCG) 'negativity' and the risk of persisting disease. Categorisation of risk is the basis for choice of chemotherapy to achieve good outcomes. Metastases to liver and brain remain problems in management; the development of 'new' metastases during chemotherapy is a very poor prognostic factor. In the variant of twinning with molar gestation and coexisting fetus, it is important to elucidate the fetal karyotype in planning management: a 69XXX fetus is not salvageable but a normal 46XX or 46XY fetus faces the prospect of early preterm delivery. The placental-site tumour is very rare; localised disease is curable by surgery; chemotherapy is less effective in disseminated disease. From collated worldwide data, the recurrence rate after one mole is 1.3% and after two or more is 20%. Reproductive outcome in subsequent pregnancies, even after multidrug chemotherapy, is not different from the general population. Because of the increased risk long-term of second tumours after multidrug chemotherapy a closer surveillance of these patients is necessary Conclusion: In general, the disease in its persisting or malignant form is 'a cancer model par excellence' because of an identifiable precursor condition, a reliable HCG marker, and sensitivity of the disease to cytotoxic drugs. With current management, retention of fertility is possible and normal reproductive outcome assured.

Real-time 3D interactive segmentation of echocardiographic data through user-based deformation of B-spline explicit active surfaces

Image segmentation is an ubiquitous task in medical image analysis, which is required to estimate morphological or functional properties of given anatomical targets. While automatic processing is highly desirable, image segmentation remains to date a supervised process in daily clinical practice. Indeed, challenging data often requires user interaction to capture the required level of anatomical detail. To optimize the analysis of 3D images, the user should be able to efficiently interact with the result of any segmentation algorithm to correct any possible disagreement. Building on a previously developed real-time 3D segmentation algorithm, we propose in the present work an extension towards an interactive application where user information can be used online to steer the segmentation result. This enables a synergistic collaboration between the operator and the underlying segmentation algorithm, thus contributing to higher segmentation accuracy, while keeping total analysis time competitive. To this end, we formalize the user interaction paradigm using a geometrical approach, where the user input is mapped to a non-cartesian space while this information is used to drive the boundary towards the position provided by the user. Additionally, we propose a shape regularization term which improves the interaction with the segmented surface, thereby making the interactive segmentation process less cumbersome. The resulting algorithm offers competitive performance both in terms of segmentation accuracy, as well as in terms of total analysis time. This contributes to a more efficient use of the existing segmentation tools in daily clinical practice. Furthermore, it compares favorably to state-of-the-art interactive segmentation software based on a 3D livewire-based algorithm.

Concepção e implementação do time-driven activity based costing numa PME industrial: evidência de um estudo empírico

Dissertação para obtenção do Grau de Mestre em Contabilidade e Finanças Orientador: Mestre Paulino Manuel Leite da Silva

Real-time energy resources scheduling considering intensive wind penetration

The use of distributed energy resources, based on natural intermittent power sources, like wind generation, in power systems imposes the development of new adequate operation management and control methodologies. A short-term Energy Resource Management (ERM) methodology performed in two phases is proposed in this paper. The first one addresses the day-ahead ERM scheduling and the second one deals with the five-minute ahead ERM scheduling. The ERM scheduling is a complex optimization problem due to the high quantity of variables and constraints. In this paper the main goal is to minimize the operation costs from the point of view of a virtual power player that manages the network and the existing resources. The optimization problem is solved by a deterministic mixedinteger non-linear programming approach. A case study considering a distribution network with 33 bus, 66 distributed generation, 32 loads with demand response contracts and 7 storage units and 1000 electric vehicles has been implemented in a simulator developed in the field of the presented work, in order to validate the proposed short-term ERM methodology considering the dynamic power system behavior.

Virtual power players demand response programs management based on locational marginal prices

Power systems have been suffering huge changes mainly due to the substantial increase of distributed generation and to the operation in competitive environments. Virtual power players can aggregate a diversity of players, namely generators and consumers, and a diversity of energy resources, including electricity generation based on several technologies, storage and demand response. Resource management gains an increasing relevance in this competitive context, while demand side active role provides managers with increased demand elasticity. This makes demand response use more interesting and flexible, giving rise to a wide range of new opportunities.This paper proposes a methodology for managing demand response programs in the scope of virtual power players. The proposed method is based on the calculation of locational marginal prices (LMP). The evaluation of the impact of using demand response specific programs on the LMP value supports the manager decision concerning demand response use. The proposed method has been computationally implemented and its application is illustrated in this paper using a 32 bus network with intensive use of distributed generation.

Hydro energy systems management in Portugal: Profit-based evaluation of a mixed-integer nonlinear approach

In this paper, a novel mixed-integer nonlinear approach is proposed to solve the short-term hydro scheduling problem in the day-ahead electricity market, considering not only head-dependency, but also start/stop of units, discontinuous operating regions and discharge ramping constraints. Results from a case study based on one of the main Portuguese cascaded hydro energy systems are presented, showing that the proposedmixed-integer nonlinear approach is proficient. Conclusions are duly drawn. (C) 2010 Elsevier Ltd. All rights reserved.

A multi-agent based approach for intelligent smart grid management

The spread and globalization of distributed generation (DG) in recent years has should highly influence the changes that occur in Electricity Markets (EMs). DG has brought a large number of new players to take action in the EMs, therefore increasing the complexity of these markets. Simulation based on multi-agent systems appears as a good way of analyzing players’ behavior and interactions, especially in a coalition perspective, and the effects these players have on the markets. MASCEM – Multi-Agent System for Competitive Electricity Markets was created to permit the study of the market operation with several different players and market mechanisms. MASGriP – Multi-Agent Smart Grid Platform is being developed to facilitate the simulation of micro grid (MG) and smart grid (SG) concepts with multiple different scenarios. This paper presents an intelligent management method for MG and SG. The simulation of different methods of control provides an advantage in comparing different possible approaches to respond to market events. Players utilize electric vehicles’ batteries and participate in Demand Response (DR) contracts, taking advantage on the best opportunities brought by the use of all resources, to improve their actions in response to MG and/or SG requests.

Real-time energy resources scheduling considering short-term and very short-term wind forecast

This paper proposes an energy resources management methodology based on three distinct time horizons: day-ahead scheduling, hour-ahead scheduling, and real-time scheduling. In each scheduling process it is necessary the update of generation and consumption operation and of the storage and electric vehicles storage status. Besides the new operation condition, it is important more accurate forecast values of wind generation and of consumption using results of in short-term and very short-term methods. A case study considering a distribution network with intensive use of distributed generation and electric vehicles is presented.

Decision support system with incomplete and domain incoherent information management

Many of the most common human functions such as temporal and non-monotonic reasoning have not yet been fully mapped in developed systems, even though some theoretical breakthroughs have already been accomplished. This is mainly due to the inherent computational complexity of the theoretical approaches. In the particular area of fault diagnosis in power systems however, some systems which tried to solve the problem, have been deployed using methodologies such as production rule based expert systems, neural networks, recognition of chronicles, fuzzy expert systems, etc. SPARSE (from the Portuguese acronym, which means expert system for incident analysis and restoration support) was one of the developed systems and, in the sequence of its development, came the need to cope with incomplete and/or incorrect information as well as the traditional problems for power systems fault diagnosis based on SCADA (supervisory control and data acquisition) information retrieval, namely real-time operation, huge amounts of information, etc. This paper presents an architecture for a decision support system, which can solve the presented problems, using a symbiosis of the event calculus and the default reasoning rule based system paradigms, insuring soft real-time operation with incomplete, incorrect or domain incoherent information handling ability. A prototype implementation of this system is already at work in the control centre of the Portuguese Transmission Network.

LMP triggered real time demand response events

Recent changes in power systems mainly due to the substantial increase of distributed generation and to the operation in competitive environments has created new challenges to operation and planning. In this context, Virtual Power Players (VPP) can aggregate a diversity of players, namely generators and consumers, and a diversity of energy resources, including electricity generation based on several technologies, storage and demand response. Demand response market implementation has been done in recent years. Several implementation models have been considered. An important characteristic of a demand response program is the trigger criterion. A program for which the event trigger depends on the Locational Marginal Price (LMP) used by the New England Independent System operator (ISO-NE) inspired the present paper. This paper proposes a methodology to support VPP demand response programs management. The proposed method has been computationally implemented and its application is illustrated using a 32 bus network with intensive use of distributed generation. Results concerning the evaluation of the impact of using demand response events are also presented.

Contexts-management strategy in considering the security in urban computing based on urban design

Urban Computing (UrC) provides users with the situation-proper information by considering context of users, devices, and social and physical environment in urban life. With social network services, UrC makes it possible for people with common interests to organize a virtual-society through exchange of context information among them. In these cases, people and personal devices are vulnerable to fake and misleading context information which is transferred from unauthorized and unauthenticated servers by attackers. So called smart devices which run automatically on some context events are more vulnerable if they are not prepared for attacks. In this paper, we illustrate some UrC service scenarios, and show important context information, possible threats, protection method, and secure context management for people.

Demand response in electrical energy supply: an optimal real time pricing approach

In competitive electricity markets with deep concerns for the efficiency level, demand response programs gain considerable significance. As demand response levels have decreased after the introduction of competition in the power industry, new approaches are required to take full advantage of demand response opportunities. This paper presents DemSi, a demand response simulator that allows studying demand response actions and schemes in distribution networks. It undertakes the technical validation of the solution using realistic network simulation based on PSCAD. The use of DemSi by a retailer in a situation of energy shortage, is presented. Load reduction is obtained using a consumer based price elasticity approach supported by real time pricing. Non-linear programming is used to maximize the retailer’s profit, determining the optimal solution for each envisaged load reduction. The solution determines the price variations considering two different approaches, price variations determined for each individual consumer or for each consumer type, allowing to prove that the approach used does not significantly influence the retailer’s profit. The paper presents a case study in a 33 bus distribution network with 5 distinct consumer types. The obtained results and conclusions show the adequacy of the used methodology and its importance for supporting retailers’ decision making.

Linking better shiftwork arrangements with safety and health management systems

OBJECTIVE: Various support measures useful for promoting joint change approaches to the improvement of both shiftworking arrangements and safety and health management systems were reviewed. A particular focus was placed on enterprise-level risk reduction measures linking working hours and management systems. METHODS: Voluntary industry-based guidelines on night and shift work for department stores and the chemical, automobile and electrical equipment industries were examined. Survey results that had led to the compilation of practicable measures to be included in these guidelines were also examined. The common support measures were then compared with ergonomic checkpoints for plant maintenance work involving irregular nightshifts. On the basis of this analysis, a new night and shift work checklist was designed. RESULTS: Both the guidelines and the plant maintenance work checkpoints were found to commonly cover multiple issues including work schedules and various job-related risks. This close link between shiftwork arrangements and risk management was important as shiftworkers in these industries considered teamwork and welfare services to be essential for managing risks associated with night and shift work. Four areas found suitable for participatory improvement by managers and workers were work schedules, ergonomic work tasks, work environment and training. The checklist designed to facilitate participatory change processes covered all these areas. CONCLUSIONS: The checklist developed to describe feasible workplace actions was suitable for integration with comprehensive safety and health management systems and offered valuable opportunities for improving working time arrangements and job content together.