425 resultados para DISTRIBUTED GENERATION


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This thesis is a study of Chinese One Child Generation's digital and social sharing. It examines urban youth grassroots communities, including an urban farmers' community and volunteers in educational camps. These case studies explain the emergence of 'sharism' in reaction to the growing risks in China, such as food safety and environmental degradation emanating from China's rapid economic development, and growing urbanism, globalisation, and consumerism. The new forms of 'sharism' are linked to guanxi (social relations) and connected youth communities, which are made possible by increasing accessibility to digital and networked technologies.

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The vision sense of standalone robots is limited by line of sight and onboard camera capabilities, but processing video from remote cameras puts a high computational burden on robots. This paper describes the Distributed Robotic Vision Service, DRVS, which implements an on-demand distributed visual object detection service. Robots specify visual information requirements in terms of regions of interest and object detection algorithms. DRVS dynamically distributes the object detection computation to remote vision systems with processing capabilities, and the robots receive high-level object detection information. DRVS relieves robots of managing sensor discovery and reduces data transmission compared to image sharing models of distributed vision. Navigating a sensorless robot from remote vision systems is demonstrated in simulation as a proof of concept.

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Embryonic development involves diffusion and proliferation of cells, as well as diffusion and reaction of molecules, within growing tissues. Mathematical models of these processes often involve reaction–diffusion equations on growing domains that have been primarily studied using approximate numerical solutions. Recently, we have shown how to obtain an exact solution to a single, uncoupled, linear reaction–diffusion equation on a growing domain, 0 < x < L(t), where L(t) is the domain length. The present work is an extension of our previous study, and we illustrate how to solve a system of coupled reaction–diffusion equations on a growing domain. This system of equations can be used to study the spatial and temporal distributions of different generations of cells within a population that diffuses and proliferates within a growing tissue. The exact solution is obtained by applying an uncoupling transformation, and the uncoupled equations are solved separately before applying the inverse uncoupling transformation to give the coupled solution. We present several example calculations to illustrate different types of behaviour. The first example calculation corresponds to a situation where the initially–confined population diffuses sufficiently slowly that it is unable to reach the moving boundary at x = L(t). In contrast, the second example calculation corresponds to a situation where the initially–confined population is able to overcome the domain growth and reach the moving boundary at x = L(t). In its basic format, the uncoupling transformation at first appears to be restricted to deal only with the case where each generation of cells has a distinct proliferation rate. However, we also demonstrate how the uncoupling transformation can be used when each generation has the same proliferation rate by evaluating the exact solutions as an appropriate limit.

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Large integration of solar Photo Voltaic (PV) in distribution network has resulted in over-voltage problems. Several control techniques are developed to address over-voltage problem using Deterministic Load Flow (DLF). However, intermittent characteristics of PV generation require Probabilistic Load Flow (PLF) to introduce variability in analysis that is ignored in DLF. The traditional PLF techniques are not suitable for distribution systems and suffer from several drawbacks such as computational burden (Monte Carlo, Conventional convolution), sensitive accuracy with the complexity of system (point estimation method), requirement of necessary linearization (multi-linear simulation) and convergence problem (Gram–Charlier expansion, Cornish Fisher expansion). In this research, Latin Hypercube Sampling with Cholesky Decomposition (LHS-CD) is used to quantify the over-voltage issues with and without the voltage control algorithm in the distribution network with active generation. LHS technique is verified with a test network and real system from an Australian distribution network service provider. Accuracy and computational burden of simulated results are also compared with Monte Carlo simulations.

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Recently, second-generation (non-vegetable oil) feedstocks for biodiesel production are receiving significant attention due to the cost and social effects connected with utilising food products for the production of energy products. The Beauty leaf tree (Calophyllum inophyllum) is a potential source of non-edible oil for producing second-generation biodiesel because of its suitability for production in an extensive variety of atmospheric condition, easy cultivation, high fruit production rate, and the high oil content in the seed. In this study, oil was extracted from Beauty leaf tree seeds through three different oil extraction methods. The important physical and chemical properties of these extracted Beauty leaf oils were experimentally analysed and compared with other commercially available vegetable oils. Biodiesel was produced using a two-stage esterification process combining of an acid catalysed pre-esterification process and an alkali catalysed transesterification process. Fatty acid methyl ester (FAME) profiles and important physicochemical properties were experimentally measured and estimated using equations based on the FAME analysis. The quality of Beauty leaf biodiesels was assessed and compared with commercially available biodiesels through multivariate data analysis using PROMETHEE-GAIA software. The results show that mechanical extraction using a screw press produces oil at a low cost, however, results in low oil yields compared with chemical oil extraction. High pressure and temperature in the extraction process increase oil extraction performance. On the contrary, this process increases the free fatty acid content in the oil. A clear difference was found in the physical properties of Beauty leaf oils, which eventually affected the oil to biodiesel conversion process. However, Beauty leaf oils methyl esters (biodiesel) were very consistent physicochemical properties and able to meet almost all indicators of biodiesel standards. Overall this study found that Beauty leaf is a suitable feedstock for producing second-generation biodiesel in commercial scale. Therefore, the findings of this study are expected to serve as the basis for further development of Beauty leaf as a feedstock for industrial scale second-generation biodiesel production.

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By using electric-field-induced optical second-harmonic generation (EFISHG) measurement, we analyzed hysteresis behavior of capacitance-voltage (C-V) characteristics of IZO/polyterpenol (PT)/C₆₀/pentacene/Au diodes, where PT layer is actively working as a hole-transport electron-blocking layer. The EFISHG measurement verified the presence of interface accumulated charges in the diodes, and showed that a space charge electric field from accumulated excess electrons (holes) that remain at the PT/C₆₀ (C₆₀/pentacene) interface is responsible for the hysteresis loop observed in the C-V characteristics.

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Time-resolved electric field induced second harmonic generation technique was used to probe the carrier transients within double-layer pentacene-based MIM devices. Polyterpenol thin films fabricated from non-synthetic environmentally sustainable source were used as a blocking layer to assist in visualisation of single-species carrier transportation during charging and discharging under different bias conditions. Results demonstrated that carrier transients were comprised of charging on electrodes, followed by carrier injection and charging of the interface. Polyterpenol was demonstrated to be a sound blocking material and can therefore be effectively used for probing of double-layer devices using EFISHG.

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In this study, the authors investigated leader generativity as a moderator of the relationships between leader age, leader-member exchange, and three criteria of leadership success (follower perceptions of leader effectiveness, follower satisfaction with leader, and follower extra effort). Data came from 128 university professors paired with one research assistant each. Results showed positive relationships between leader age and leader generativity, and negative relationships between leader age and follower perceptions of leader effectiveness and follower extra effort. Consistent with expectations based on leadership categorization theory, leader generativity moderated the relationships between leader age and all three criteria of leadership success, such that leaders high in generativity were better able to maintain high levels of leadership success at higher ages than leaders low in generativity. Finally, results of mediated moderation analyses showed that leader-member exchange quality mediated these moderating effects. The findings suggest that, in combination, leader age and the age-related construct of generativity importantly influence leadership processes and outcomes. © 2011 American Psychological Association.

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This research studied distributed computing of all-to-all comparison problems with big data sets. The thesis formalised the problem, and developed a high-performance and scalable computing framework with a programming model, data distribution strategies and task scheduling policies to solve the problem. The study considered storage usage, data locality and load balancing for performance improvement in solving the problem. The research outcomes can be applied in bioinformatics, biometrics and data mining and other domains in which all-to-all comparisons are a typical computing pattern.

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The world is facing an energy crisis due to exponential population growth and limited availability of fossil fuels. Over the last 20 years, carbon, one of the most abundant materials found on earth, and its allotrope forms such as fullerenes, carbon nanotubes and graphene have been proposed as sources of energy generation and storage because of their extraordinary properties and ease of production. Various approaches for the synthesis and incorporation of carbon nanomaterials in organic photovoltaics and supercapacitors have been reviewed and discussed in this work, highlighting their benefits as compared to other materials commonly used in these devices. The use of fullerenes, carbon nanotubes and graphene in organic photovoltaics and supercapacitors is described in detail, explaining how their remarkable properties can enhance the efficiency of solar cells and energy storage in supercapacitors. Fullerenes, carbon nanotubes and graphene have all been included in solar cells with interesting results, although a number of problems are still to be overcome in order to achieve high efficiency and stability. However, the flexibility and the low cost of these materials provide the opportunity for many applications such as wearable and disposable electronics or mobile charging. The application of carbon nanotubes and graphene to supercapacitors is also discussed and reviewed in this work. Carbon nanotubes, in combination with graphene, can create a more porous film with extraordinary capacitive performance, paving the way to many practical applications from mobile phones to electric cars. In conclusion, we show that carbon nanomaterials, developed by inexpensive synthesis and process methods such as printing and roll-to-roll techniques, are ideal for the development of flexible devices for energy generation and storage – the key to the portable electronics of the future.

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Salinity gradient power is proposed as a source of renewable energy when two solutions of different salinity are mixed. In particular, Pressure Retarded Osmosis (PRO) coupled with a Reverse Osmosis process (RO) has been previously suggested for power generation, using RO brine as the draw solution. However, integration of PRO with RO may have further value for increasing the extent of water recovery in a desalination process. Consequently, this study was designed to model the impact of various system parameters to better understand how to design and operate practical PRO-RO units. The impact of feed salinity and recovery rate for the RO process on the concentration of draw solution, feed pressure, and membrane area of the PRO process was evaluated. The PRO system was designed to operate at maximum power density of . Model results showed that the PRO power density generated intensified with increasing seawater salinity and RO recovery rate. For an RO process operating at 52% recovery rate and 35 g/L feed salinity, a maximum power density of 24 W/m2 was achieved using 4.5 M NaCl draw solution. When seawater salinity increased to 45 g/L and the RO recovery rate was 46%, the PRO power density increased to 28 W/m2 using 5 M NaCl draw solution. The PRO system was able to increase the recovery rate of the RO by up to 18% depending on seawater salinity and RO recovery rate. This result suggested a potential advantage of coupling PRO process with RO system to increase the recovery rate of the desalination process and reduce brine discharge.

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Robotic vision is limited by line of sight and onboard camera capabilities. Robots can acquire video or images from remote cameras, but processing additional data has a computational burden. This paper applies the Distributed Robotic Vision Service, DRVS, to robot path planning using data outside line-of-sight of the robot. DRVS implements a distributed visual object detection service to distributes the computation to remote camera nodes with processing capabilities. Robots request task-specific object detection from DRVS by specifying a geographic region of interest and object type. The remote camera nodes perform the visual processing and send the high-level object information to the robot. Additionally, DRVS relieves robots of sensor discovery by dynamically distributing object detection requests to remote camera nodes. Tested over two different indoor path planning tasks DRVS showed dramatic reduction in mobile robot compute load and wireless network utilization.

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Background Medication safety is a pressing concern for residential aged care facilities (RACFs). Retrospective studies in RACF settings identify inadequate communication between RACFs, doctors, hospitals and community pharmacies as the major cause of medication errors. Existing literature offers limited insight about the gaps in the existing information exchange process that may lead to medication errors. The aim of this research was to explicate the cognitive distribution that underlies RACF medication ordering and delivery to identify gaps in medication-related information exchange which lead to medication errors in RACFs. Methods The study was undertaken in three RACFs in Sydney, Australia. Data were generated through ethnographic field work over a period of five months (May–September 2011). Triangulated analysis of data primarily focused on examining the transformation and exchange of information between different media across the process. Results The findings of this study highlight the extensive scope and intense nature of information exchange in RACF medication ordering and delivery. Rather than attributing error to individual care providers, the explication of distributed cognition processes enabled the identification of gaps in three information exchange dimensions which potentially contribute to the occurrence of medication errors namely: (1) design of medication charts which complicates order processing and record keeping (2) lack of coordination mechanisms between participants which results in misalignment of local practices (3) reliance on restricted communication bandwidth channels mainly telephone and fax which complicates the information processing requirements. The study demonstrates how the identification of these gaps enhances understanding of medication errors in RACFs. Conclusions Application of the theoretical lens of distributed cognition can assist in enhancing our understanding of medication errors in RACFs through identification of gaps in information exchange. Understanding the dynamics of the cognitive process can inform the design of interventions to manage errors and improve residents’ safety.

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In the last decade, huge breakthroughs in genetics - driven by new technology and different statistical approaches - have resulted in a plethora of new disease genes identified for both common and rare diseases. Massive parallel sequencing, commonly known as next-generation sequencing, is the latest advance in genetics, and has already facilitated the discovery of the molecular cause of many monogenic disorders. This article describes this new technology and reviews how this approach has been used successfully in patients with skeletal dysplasias. Moreover, this article illustrates how the study of rare diseases can inform understanding and therapeutic developments for common diseases such as osteoporosis. © International Osteoporosis Foundation and National Osteoporosis Foundation 2013.

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Multi-agent systems (MAS) advocate an agent-based approach to software engineering based on decomposing problems in terms of decentralized, autonomous agents that can engage in flexible, high-level interactions. This chapter introduces scalable fault tolerant agent grooming environment (SAGE), a second-generation Foundation for Intelligent Physical Agents (FIPA)-compliant multi-agent system developed at NIIT-Comtec, which provides an environment for creating distributed, intelligent, and autonomous entities that are encapsulated as agents. The chapter focuses on the highlight of SAGE, which is its decentralized fault-tolerant architecture that can be used to develop applications in a number of areas such as e-health, e-government, and e-science. In addition, SAGE architecture provides tools for runtime agent management, directory facilitation, monitoring, and editing messages exchange between agents. SAGE also provides a built-in mechanism to program agent behavior and their capabilities with the help of its autonomous agent architecture, which is the other major highlight of this chapter. The authors believe that the market for agent-based applications is growing rapidly, and SAGE can play a crucial role for future intelligent applications development. © 2007, IGI Global.