839 resultados para family systems approach


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The increasing scarcity of water in the world, along with rapid population increase in urban areas, gives reason for concern and highlights the need for integrating water and wastewater management practices. The uncontrolled growth in urban areas has made planning, management and expansion of water and wastewater infrastructure systems very difficult and expensive. In order to achieve sustainable wastewater treatment and promote the conservation of water and nutrient resources, this chapter advocates the need for a closed-loop treatment system approach, and the transformation of the traditional linear treatment systems into integrated cyclical treatment systems. The recent increased understanding of integrated resource management and a shift towards sustainable management and planning of water and wastewater infrastructure are also discussed.

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Station track allocation is the critical component in the overall railway timetabling. Because of its intrinsic complexity and lack of modeling on station track layouts and train movement within station, analytical approach to attain optimal solution is not feasible. This study investigates the possibilities of applying a heuristic approach and identifies possible difficulties in practice. It is the first and important step to resolve one of the burning issues in the mainline railway operation in China.

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With the recent regulatory reforms in a number of countries, railways resources are no longer managed by a single party but are distributed among different stakeholders. To facilitate the operation of train services, a train service provider (SP) has to negotiate with the infrastructure provider (IP) for a train schedule and the associated track access charge. This paper models the SP and IP as software agents and the negotiation as a prioritized fuzzy constraint satisfaction (PFCS) problem. Computer simulations have been conducted to demonstrate the effects on the train schedule when the SP has different optimization criteria. The results show that by assigning different priorities on the fuzzy constraints, agents can represent SPs with different operational objectives.

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Streaming SIMD Extensions (SSE) is a unique feature embedded in the Pentium III class of microprocessors. By fully exploiting SSE, parallel algorithms can be implemented on a standard personal computer and a theoretical speedup of four can be achieved. In this paper, we demonstrate the implementation of a parallel LU matrix decomposition algorithm for solving power systems network equations with SSE and discuss advantages and disadvantages of this approach.

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Streaming SIMD Extensions (SSE) is a unique feature embedded in the Pentium III and IV classes of microprocessors. By fully exploiting SSE, parallel algorithms can be implemented on a standard personal computer and a theoretical speedup of four can be achieved. In this paper, we demonstrate the implementation of a parallel LU matrix decomposition algorithm for solving linear systems with SSE and discuss advantages and disadvantages of this approach based on our experimental study.

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A high peak power demand at substations will result under Moving Block Signalling (MBS) when a dense queue of trains begins to start from a complete stop at the same time in an electrified railway system. This may cause the power supply interruption and in turn affect the train service substantially. In a recent study, measures of Starting Time Delay (STD) and Acceleration Rate Limit (ARL) are the possible approaches to reduce the peak power demand on the supply system under MBS. Nevertheless, there is no well-defined relationship between the two measures and peak power demand reduction (PDR). In order to attain a lower peak demand at substations on different traffic conditions and system requirements, an expert system is one of the possible approaches to procure the appropriate use of peak demand reduction measures. The main objective of this paper is to study the effect of the train re-starting strategies on the power demand at substations and the time delay suffered by the trains with the aid of computer simulation. An expert system is a useful tool to select various adoptions of STD and ARL under different operational conditions and system requirements.

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This correspondence paper addresses the problem of output feedback stabilization of control systems in networked environments with quality-of-service (QoS) constraints. The problem is investigated in discrete-time state space using Lyapunov’s stability theory and the linear inequality matrix technique. A new discrete-time modeling approach is developed to describe a networked control system (NCS) with parameter uncertainties and nonideal network QoS. It integrates a network-induced delay, packet dropout, and other network behaviors into a unified framework. With this modeling, an improved stability condition, which is dependent on the lower and upper bounds of the equivalent network-induced delay, is established for the NCS with norm-bounded parameter uncertainties. It is further extended for the output feedback stabilization of the NCS with nonideal QoS. Numerical examples are given to demonstrate the main results of the theoretical development.

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Abstract Computer simulation is a versatile and commonly used tool for the design and evaluation of systems with different degrees of complexity. Power distribution systems and electric railway network are areas for which computer simulations are being heavily applied. A dominant factor in evaluating the performance of a software simulator is its processing time, especially in the cases of real-time simulation. Parallel processing provides a viable mean to reduce the computing time and is therefore suitable for building real-time simulators. In this paper, we present different issues related to solving the power distribution system with parallel computing based on a multiple-CPU server and we will concentrate, in particular, on the speedup performance of such an approach.

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Gibson and Tarrant discuss the range of inter-dependant factors needed to manage organisational resilience. Over the last few years there has been considerable interest in the idea of resilience across all areas of society. Like any new area or field this has produced a vast array of definitions, processes, management systems and measurement tools which together have clouded the concept of resilience. Many of us have forgotten that ultimately resilience is not just about ‘bouncing back from adversity’ but is more broadly concerned with adaptive capacity and how we better understand and address uncertainty in our internal and external environments. The basis of organisational resilience is a fundamental understanding and treatment of risk, particularly non-routine or disruption related risk. This paper presents a number of conceptual models of organisational resilience that we have developed to demonstrate the range of inter-dependant factors that need to be considered in the management of such risk. These conceptual models illustrate that effective resilience is built upon a range of different strategies that enhance both ‘hard’ and ‘soft’ organisational capabilities . They emphasise the concept that there is no quick fix, no single process, management system or software application that will create resilience.

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In recent years, cities have shown increasing signs of environmental problems due to the negative impacts of urban activities. The degradation and depletion of natural resources, climate change, and development pressure on green areas have become major concerns for cities. In response to these problems, urban planning policies have shifted to a sustainable focus and authorities have begun to develop new strategies for improving the quality of urban ecosystems. An extremely important function of an urban ecosystem is to provide healthy and sustainable environments for both natural systems and communities. Therefore, ecological planning is a functional requirement in the establishment of sustainable built environment. With ecological planning, human needs are supplied while natural resources are used in the most effective and sustainable manner and ecological balance is sustained. Protecting human and environmental health, having healthy ecosystems, reducing environmental pollution and providing green spaces are just a few of the many benefits of ecological planning. In this context, this chapter briefly presents a short overview of the importance of the implementation of ecological planning into sustainable urban development. Furthermore, it presents a conceptual framework for a new methodology for developing sustainable urban ecosystems through ecological planning approach.

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This abstract explores the possibility of a grass roots approach to engaging people in community change initiatives by designing simple interactive exploratory prototypes for use by communities over time that support shared action. The prototype is gradually evolved in response to community use, fragments of data gathered through the prototype, and participant feedback with the goal of building participation in community change initiatives. A case study of a system to support ridesharing is discussed. The approach is compared and contrasted to a traditional IT systems procurement approach.

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In this chapter we present a case study set in Beloi, a fishing village located on Ataúro Island, 30 km across the sea from Díli, capital of Timor-Leste (East-Timor). We explore the tension between tourism development, food security and marine conservation in a developing country context. In order to better understand the relationships between the social, ecological and economic issues that arise in tourism planning we use an approach and associated methodology based on storytelling, complexity theory and concept mapping. Through testing scenarios with this methodology we hope to evaluate which trade-offs are acceptable to local people in return for the hoped-for economic boost from increased tourist visitation and associated developments.

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Recently, the numerical modelling and simulation for fractional partial differential equations (FPDE), which have been found with widely applications in modern engineering and sciences, are attracting increased attentions. The current dominant numerical method for modelling of FPDE is the explicit Finite Difference Method (FDM), which is based on a pre-defined grid leading to inherited issues or shortcomings. This paper aims to develop an implicit meshless approach based on the radial basis functions (RBF) for numerical simulation of time fractional diffusion equations. The discrete system of equations is obtained by using the RBF meshless shape functions and the strong-forms. The stability and convergence of this meshless approach are then discussed and theoretically proven. Several numerical examples with different problem domains are used to validate and investigate accuracy and efficiency of the newly developed meshless formulation. The results obtained by the meshless formations are also compared with those obtained by FDM in terms of their accuracy and efficiency. It is concluded that the present meshless formulation is very effective for the modelling and simulation for FPDE.

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This paper presents a multiscale study using the coupled Meshless technique/Molecular Dynamics (M2) for exploring the deformation mechanism of mono-crystalline metal (focus on copper) under uniaxial tension. In M2, an advanced transition algorithm using transition particles is employed to ensure the compatibility of both displacements and their gradients, and an effective local quasi-continuum approach is also applied to obtain the equivalent continuum strain energy density based on the atomistic poentials and Cauchy-Born rule. The key parameters used in M2 are firstly investigated using a benchmark problem. Then M2 is applied to the multiscale simulation for a mono-crystalline copper bar. It has found that the mono-crystalline copper has very good elongation property, and the ultimate strength and Young's modulus are much higher than those obtained in macro-scale.

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In this paper, we present a control strategy design technique for an autonomous underwater vehicle based on solutions to the motion planning problem derived from differential geometric methods. The motion planning problem is motivated by the practical application of surveying the hull of a ship for implications of harbor and port security. In recent years, engineers and researchers have been collaborating on automating ship hull inspections by employing autonomous vehicles. Despite the progresses made, human intervention is still necessary at this stage. To increase the functionality of these autonomous systems, we focus on developing model-based control strategies for the survey missions around challenging regions, such as the bulbous bow region of a ship. Recent advances in differential geometry have given rise to the field of geometric control theory. This has proven to be an effective framework for control strategy design for mechanical systems, and has recently been extended to applications for underwater vehicles. Advantages of geometric control theory include the exploitation of symmetries and nonlinearities inherent to the system. Here, we examine the posed inspection problem from a path planning viewpoint, applying recently developed techniques from the field of differential geometric control theory to design the control strategies that steer the vehicle along the prescribed path. Three potential scenarios for surveying a ship?s bulbous bow region are motivated for path planning applications. For each scenario, we compute the control strategy and implement it onto a test-bed vehicle. Experimental results are analyzed and compared with theoretical predictions.