50 resultados para Electric capacity.
Resumo:
To counteract and prevent the deleterious effect of free radicals the living organisms have developed complex endogenous and exogenous antioxidant systems. Several analytical methodologies have been proposed in order to quantify antioxidants in food, beverages and biological fluids. This paper revises the electroanalytical approaches developed for the assessment of the total or individual antioxidant capacity. Four electrochemical sensing approaches have been identified, based on the direct electrochemical detection of antioxidant at bare or chemically modified electrodes, and using enzymatic and DNA-based biosensors.
Resumo:
The purpose of the present work is to determine the antioxidant capacity (AC) of 27 commercial beers. The AC indicates the degree of protection of a certain organism against oxidative damage provoked by reactive oxygen and nitrogen species. Assays were carried out by the following methods: (i) total radical trapping antioxidant parameter (TRAP); (ii) trolox equivalent antioxidant capacity (TEAC); (iii) trolox equivalent antioxidant capacity (DPPH); (iv) ferric-ion reducing antioxidant parameter (FRAP); (v) cupric reducing antioxidant capacity (CUPRAC); (vi) oxygen radical absorbance capacity (ORAC). Ascorbic acid (AA), gallic acid (GA) and trolox (TR) were used as standards. All beers showed antioxidant power, but a wide range of ACs was observed. The effect of several factors upon these differences was studied. Statistical differences were found between ACs of beers of different colours. ORAC method provided always higher experimental ACs, of significant statistical differences to other assays.
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A dynamic scheduler that supports the coexistence of guaranteed and non-guaranteed bandwidth servers is proposed. Overloads are handled by an efficient reclaiming of residual capacities originated by early completions as well as by allowing reserved capacity stealing of non-guaranteed bandwidth servers. The proposed dynamic budget accounting mechanism ensures that at a particular time the currently executing server is using a residual capacity, its own capacity or is stealing some reserved capacity, eliminating the need of additional server states or unbounded queues. The server to which the budget accounting is going to be performed is dynamically determined at the time instant when a capacity is needed. This paper describes and evaluates the proposed scheduling algorithm, showing that it can efficiently reduce the mean tardiness of periodic jobs. The achieved results become even more significant when tasks’ computation times have a large variance.
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Firms located within a cluster have access to tacit, complex and specific local knowledge which allow them to develop competitive advantage. However, firms have no equal ability to access and to apply that knowledge, meaning that not all have a similar knowledge absorptive capacity. Using a sample of the largest Portuguese firms within a footwear cluster, this paper examine whether there are significant differences in firm’s absorptive capacity and whether such differences within a cluster are related to firms’ specific characteristics. The results suggest that absorptive capacity is significantly associated with the firms’ characteristics, namely size, export intensity and position within the cluster.
Resumo:
The economical and environment impacts of fossil energies increased the interest for hybrid, battery and fuel-cell electric vehicles. Several demanding engineering challenges must be faced, motivated by different physical domains integration. This paper aims to present an overview on hybrid (HEV) and electric vehicles (EV) basic structures and features. In addition, it will try to point out some of the most relevant challenges to overcome for HEV and EV may be a solid option for the mobility issue. New developments in energy storage devices and energy management systems (EMS) are crucial to achieve this goal.
Resumo:
This paper focuses on the scheduling of tasks with hard and soft real-time constraints in open and dynamic real-time systems. It starts by presenting a capacity sharing and stealing (CSS) strategy that supports the coexistence of guaranteed and non-guaranteed bandwidth servers to efficiently handle soft-tasks’ overloads by making additional capacity available from two sources: (i) reclaiming unused reserved capacity when jobs complete in less than their budgeted execution time and (ii) stealing reserved capacity from inactive non-isolated servers used to schedule best-effort jobs. CSS is then combined with the concept of bandwidth inheritance to efficiently exchange reserved bandwidth among sets of inter-dependent tasks which share resources and exhibit precedence constraints, assuming no previous information on critical sections and computation times is available. The proposed Capacity Exchange Protocol (CXP) has a better performance and a lower overhead when compared against other available solutions and introduces a novel approach to integrate precedence constraints among tasks of open real-time systems.
Resumo:
Modeling the fundamental performance limits of Wireless Sensor Networks (WSNs) is of paramount importance to understand their behavior under worst-case conditions and to make the appropriate design choices. In that direction this paper contributes with an analytical methodology for modeling cluster-tree WSNs where the data sink can either be static or mobile. We assess the validity and pessimism of analytical model by comparing the worst-case results with the values measured through an experimental test-bed based on Commercial-Off- The-Shelf (COTS) technologies, namely TelosB motes running TinyOS.
Resumo:
This paper proposes a dynamic scheduler that supports the coexistence of guaranteed and non-guaranteed bandwidth servers to efficiently handle soft-tasks’ overloads by making additional capacity available from two sources: (i) residual capacity allocated but unused when jobs complete in less than their budgeted execution time; (ii) stealing capacity from inactive non-isolated servers used to schedule best-effort jobs. The effectiveness of the proposed approach in reducing the mean tardiness of periodic jobs is demonstrated through extensive simulations. The achieved results become even more significant when tasks’ computation times have a large variance.
Resumo:
This paper proposes a new strategy to integrate shared resources and precedence constraints among real-time tasks, assuming no precise information on critical sections and computation times is available. The concept of bandwidth inheritance is combined with a capacity sharing and stealing mechanism to efficiently exchange bandwidth among tasks to minimise the degree of deviation from the ideal system’s behaviour caused by inter-application blocking. The proposed Capacity Exchange Protocol (CXP) is simpler than other proposed solutions for sharing resources in open real-time systems since it does not attempt to return the inherited capacity in the same exact amount to blocked servers. This loss of optimality is worth the reduced complexity as the protocol’s behaviour nevertheless tends to be fair and outperforms the previous solutions in highly dynamic scenarios as demonstrated by extensive simulations. A formal analysis of CXP is presented and the conditions under which it is possible to guarantee hard real-time tasks are discussed.
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The recent update of the R-Fieldbus testbed to the new Flexible Manufacturing Field Trial – FMFT – brought up the need for a complete revision of its electric schematic.This document comes as a sort of appendix to the Technical Report “Flexible Manufacturing Field Trial”, providing a reliable source of information about the FMFT electric schematic for further developments and/or maintenances.
Resumo:
This paper proposes a new strategy to integrate shared resources and precedence constraints among real-time tasks, assuming no precise information on critical sections and computation times is available. The concept of bandwidth inheritance is combined with a greedy capacity sharing and stealing policy to efficiently exchange bandwidth among tasks, minimising the degree of deviation from the ideal system's behaviour caused by inter-application blocking. The proposed capacity exchange protocol (CXP) focus on exchanging extra capacities as early, and not necessarily as fairly, as possible. This loss of optimality is worth the reduced complexity as the protocol's behaviour nevertheless tends to be fair in the long run and outperforms other solutions in highly dynamic scenarios, as demonstrated by extensive simulations.
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The use of fiber reinforced plastics has increased in the last decades due to their unique properties. Advantages of their use are related with low weight, high strength and stiffness. Drilling of composite plates can be carried out in conventional machinery with some adaptations. However, the presence of typical defects like delamination can affect mechanical properties of produced parts. In this paper delamination influence in bearing stress of drilled hybrid carbon+glass/epoxy quasi-isotropic plates is studied by using image processing and analysis techniques. Results from bearing test show that damage minimization is an important mean to improve mechanical properties of the joint area of the plate. The appropriateness of the image processing and analysis techniques used in the measurement of the damaged area is demonstrated.
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This paper presents the system developed to promote the rational use of electric energy among consumers and, thus, increase the energy efficiency. The goal is to provide energy consumers with an application that displays the energy consumption/production profiles, sets up consuming ceilings, defines automatic alerts and alarms, compares anonymously consumers with identical energy usage profiles by region and predicts, in the case of non-residential installations, the expected consumption/production values. The resulting distributed system is organized in two main blocks: front-end and back-end. The front-end includes user interface applications for Android mobile devices and Web browsers. The back-end provides data storage and processing functionalities and is installed in a cloud computing platform - the Google App Engine - which provides a standard Web service interface. This option ensures interoperability, scalability and robustness to the system.
Resumo:
The energy resource scheduling is becoming increasingly important, as the use of distributed resources is intensified and massive gridable vehicle (V2G) use is envisaged. This paper presents a methodology for day-ahead energy resource scheduling for smart grids considering the intensive use of distributed generation and V2G. The main focus is the comparison of different EV management approaches in the day-ahead energy resources management, namely uncontrolled charging, smart charging, V2G and Demand Response (DR) programs i n the V2G approach. Three different DR programs are designed and tested (trip reduce, shifting reduce and reduce+shifting). Othe r important contribution of the paper is the comparison between deterministic and computational intelligence techniques to reduce the execution time. The proposed scheduling is solved with a modified particle swarm optimization. Mixed integer non-linear programming is also used for comparison purposes. Full ac power flow calculation is included to allow taking into account the network constraints. A case study with a 33-bus distribution network and 2000 V2G resources is used to illustrate the performance of the proposed method.
Resumo:
The massification of electric vehicles (EVs) can have a significant impact on the power system, requiring a new approach for the energy resource management. The energy resource management has the objective to obtain the optimal scheduling of the available resources considering distributed generators, storage units, demand response and EVs. The large number of resources causes more complexity in the energy resource management, taking several hours to reach the optimal solution which requires a quick solution for the next day. Therefore, it is necessary to use adequate optimization techniques to determine the best solution in a reasonable amount of time. This paper presents a hybrid artificial intelligence technique to solve a complex energy resource management problem with a large number of resources, including EVs, connected to the electric network. The hybrid approach combines simulated annealing (SA) and ant colony optimization (ACO) techniques. The case study concerns different EVs penetration levels. Comparisons with a previous SA approach and a deterministic technique are also presented. For 2000 EVs scenario, the proposed hybrid approach found a solution better than the previous SA version, resulting in a cost reduction of 1.94%. For this scenario, the proposed approach is approximately 94 times faster than the deterministic approach.