936 resultados para pacs: word processing equipment for office automation


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In South and Southeast Asia, postharvest loss causes material waste of up to 66% in fruits and vegetables, 30% in oilseeds and pulses, and 49% in roots and tubers. The efficiency of postharvest equipment directly affects industrial-scale food production. To enhance current processing methods and devices, it is essential to analyze the responses of food materials under loading operations. Food materials undergo different types of mechanical loading during postharvest and processing stages. Therefore, it is important to determine the properties of these materials under different types of loads, such as tensile, compression, and indentation. This study presents a comprehensive analysis of the available literature on the tensile properties of different food samples. The aim of this review was to categorize the available methods of tensile testing for agricultural crops and food materials to investigate an appropriate sample size and tensile test method. The results were then applied to perform tensile tests on pumpkin flesh and peel samples, in particular on arc-sided samples at a constant loading rate of 20 mm min-1. The results showed the maximum tensile stress of pumpkin flesh and peel samples to be 0.535 and 1.45 MPa, respectively. The elastic modulus of the flesh and peel samples was 6.82 and 25.2 MPa, respectively, while the failure modulus values were 14.51 and 30.88 MPa, respectively. The results of the tensile tests were also used to develop a finite element model of mechanical peeling of tough-skinned vegetables. However, to study the effects of deformation rate, moisture content, and texture of the tissue on the tensile responses of food materials, more investigation needs to be done in the future.

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Within-building spatial variability of indoor air quality may influence substantially the reliability of human exposure assessments based on single point samples, but have hitherto been little studied. To investigate and understand the within-building spatial variation of air pollutants, field measurements were conducted in a 7 level office building in Brisbane, Australia. The building consists of 3 sections (A side, Meddler and B side).

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Rural communities across Australia are increasingly being asked to shoulder the environmental and social impacts of intensive mining and gas projects. Escalating demand for coal seam gas (CSG) is raising significant environmental justice issues for rural communities. Chief amongst environmental concerns are risks of contamination or depletion of vital underground aquifers as well as treatment and disposal of high-saline water close to high quality agricultural soils. Associated infrastructure such as pipelines, electricity lines, gas processing and port facilities can also adversely affect communities and ecosystems great distances from where the gas is originally extracted. Whilst community submission (and appeal) rights do exist, accessing expert independent information is challenging, legal terminology is complex and submission periods are short, leading ultimately to a lack of procedural justice for landholders and their communities. Since August 2012, Queensland University of Technology (QUT) has worked in partnership with not-for-profit legal centre - Queensland’s Environmental Defenders Office (EDO) - to help better educate communities about mining and CSG assessment processes. The project, now entering its third semester, aims to empower communities to access relevant information and actively engage in legal processes on their own behalf. Students involved in the project so far have helped to research chapters of a comprehensive community guide to mining and CSG law as well as organising multidisciplinary community forums and preparing information on land access and compensation rights for landholders. While environmental justice issues still exist without significant law reform, the project has led to greater awareness amongst the community of the laws relating the CSG. At the same time, it has led to a greater understanding by students and academics of real life environmental justice issues currently faced by rural communities.

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In recent times, Australia has recognised and enacted a range of initiatives at service, system and community levels that seek to embed sustainability into the early childhood sector. This paper explores the impact of a professional development (PD) session that provided opportunities for early childhood educators to learn and share ideas about the theory and practice of sustainability generally and early childhood education for sustainability (ECEfS) specifically. The PD was entitled ‘Living and Learning about Sustainability in the Early Years’ and was offered on three occasions across Tasmania. A total of 99 participants attended the three PD sessions (one 5 hour; two 2 hour). The participants had varying levels of experience and included early childhood teachers, centre based educators and preservice teachers. At the start and end of the PD, participants were invited to complete a questionnaire that contained a series of likert scale questions that explored their content knowledge, level of understanding and confidence in regards to ECEfS. Participants were also asked at the start and end of the PD to ‘list five words you think of when you consider the word sustainability.’ A model of teacher professional growth was used to conceptualise the results related to the changes in knowledge, understanding and confidence (personal domain) as a result of the PD related to ECEfS (external domain). The likert-scale questions on the questionnaire revealed significant positive changes in levels of knowledge, understanding and confidence from the start to the end of the PD. Differences as a function of length of PD, level of experience and role are presented and discussed. The ‘5 words’ question showed that participants widened their understandings of ECEfS from a narrow environmental focus to a broader understanding of the social, political and economic dimensions. The early childhood education and care (ECEC) sector has been characterised as having a pedagogical advantage for EfS suggesting that early childhood educators are well placed to engage with EfS more readily than might educators in other education sectors. This article argues that PD is necessary to develop capability in educators in order to meet the imperatives around sustainability outlined in educational policy and curriculum documents in ECEC.

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Distributed Wireless Smart Camera (DWSC) network is a special type of Wireless Sensor Network (WSN) that processes captured images in a distributed manner. While image processing on DWSCs sees a great potential for growth, with its applications possessing a vast practical application domain such as security surveillance and health care, it suffers from tremendous constraints. In addition to the limitations of conventional WSNs, image processing on DWSCs requires more computational power, bandwidth and energy that presents significant challenges for large scale deployments. This dissertation has developed a number of algorithms that are highly scalable, portable, energy efficient and performance efficient, with considerations of practical constraints imposed by the hardware and the nature of WSN. More specifically, these algorithms tackle the problems of multi-object tracking and localisation in distributed wireless smart camera net- works and optimal camera configuration determination. Addressing the first problem of multi-object tracking and localisation requires solving a large array of sub-problems. The sub-problems that are discussed in this dissertation are calibration of internal parameters, multi-camera calibration for localisation and object handover for tracking. These topics have been covered extensively in computer vision literatures, however new algorithms must be invented to accommodate the various constraints introduced and required by the DWSC platform. A technique has been developed for the automatic calibration of low-cost cameras which are assumed to be restricted in their freedom of movement to either pan or tilt movements. Camera internal parameters, including focal length, principal point, lens distortion parameter and the angle and axis of rotation, can be recovered from a minimum set of two images of the camera, provided that the axis of rotation between the two images goes through the camera's optical centre and is parallel to either the vertical (panning) or horizontal (tilting) axis of the image. For object localisation, a novel approach has been developed for the calibration of a network of non-overlapping DWSCs in terms of their ground plane homographies, which can then be used for localising objects. In the proposed approach, a robot travels through the camera network while updating its position in a global coordinate frame, which it broadcasts to the cameras. The cameras use this, along with the image plane location of the robot, to compute a mapping from their image planes to the global coordinate frame. This is combined with an occupancy map generated by the robot during the mapping process to localised objects moving within the network. In addition, to deal with the problem of object handover between DWSCs of non-overlapping fields of view, a highly-scalable, distributed protocol has been designed. Cameras that follow the proposed protocol transmit object descriptions to a selected set of neighbours that are determined using a predictive forwarding strategy. The received descriptions are then matched at the subsequent camera on the object's path using a probability maximisation process with locally generated descriptions. The second problem of camera placement emerges naturally when these pervasive devices are put into real use. The locations, orientations, lens types etc. of the cameras must be chosen in a way that the utility of the network is maximised (e.g. maximum coverage) while user requirements are met. To deal with this, a statistical formulation of the problem of determining optimal camera configurations has been introduced and a Trans-Dimensional Simulated Annealing (TDSA) algorithm has been proposed to effectively solve the problem.

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This paper presents an innovative and practical approach to controlling heave motion in the presence of acute stochastic atmospheric disturbances during landing operations of an Unmanned Autonomous Helicopter (UAH). A heave motion model of an UAH is constructed for the purpose of capturing dynamic variations of thrust due to horizontal wind gusts. Additionally, through construction of an effective observer to estimate magnitudes of random gusts, a promising and feasible feedback-feedforward PD controller is developed, based on available measurements from onboard equipment. The controller dynamically and synchronously compensates for aerodynamic variations of heave motion resulting from gust influence, to increase the disturbance-attenuation ability of the UAH in a windy environment. Simulation results justify the reliability and efficiency of the suggested gust observer to estimate gust levels when applied to the heave motion model of a small unmanned helicopter, and verify suitability of the recommended control strategy to realistic environmental conditions.

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The problem of estimating pseudobearing rate information of an airborne target based on measurements from a vision sensor is considered. Novel image speed and heading angle estimators are presented that exploit image morphology, hidden Markov model (HMM) filtering, and relative entropy rate (RER) concepts to allow pseudobearing rate information to be determined before (or whilst) the target track is being estimated from vision information.

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Current research into project management offices (PMOs) has stressed the PMOs' potential to act as knowledge brokers between projects, and between project and top management. Nonetheless, the literature does not provide sufficient evidence of the brokering role of PMOs. The research reported here aims to examine PMO's functions from a knowledge sharing perspective and explore whether or not these functions reflect the knowledge sharing needs of project managers (PMs). These issues are investigated through a cross-case analysis of seven organisations. The main contribution is insight into how PMs share knowledge and awareness of the need to structure PMOs to align with PMs' nature, needs and expectations in order to improve knowledge sharing in PBOs. Finally, some practical steps for helping PMOs to better adapt their functions to the needs of PMs and their learning and knowledge sharing style are proposed.

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This research investigated airborne particle characteristics and their dynamics inside and around the envelope of mechanically ventilated office buildings, together with building thermal conditions and energy consumption. Based on these, a comprehensive model was developed to facilitate the optimisation of building heating, ventilation and air conditioning systems, in order to protect the health of their occupants and minimise the energy requirements of these buildings.

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In the movie industry, the extraordinarily successful theatrical performance of certain films is largely attributed to buzz. Despite longstanding commentary about the role of buzz in successful movie marketing and the belief that it accelerates new product diffusion, limited scholarly evidence exists to support these assertions. This is primarily due to the lack of conceptual distinction of buzz from word-of-mouth, which is often used as the main basis for conceptualising buzz. However, word-of-mouth does not fully explain the buzz surrounding films such as 'Gone With The Wind', 'The Dark Knight' and 'Avatar'. Informed by valuable insights from key experts who have launched some of the most successful movies in box office history, as well as a range of moviegoers, this thesis developed a deeper understanding of what buzz is and how it is created. This thesis concludes that buzz is not the same as word-of-mouth.

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Microvessel density (MVD) is a widely used surrogate measure of angiogenesis in pathological specimens and tumour models. Measurement of MVD can be achieved by several methods. Automation of counting methods aims to increase the speed, reliability and reproducibility of these techniques. The image analysis system described here enables MVD measurement to be carried out with minimal expense in any reasonably equipped pathology department or laboratory. It is demonstrated that the system translates easily between tumour types which are suitably stained with minimal calibration. The aim of this paper is to offer this technique to a wider field of researchers in angiogenesis.

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Safety concerns in the operation of autonomous aerial systems require safe-landing protocols be followed during situations where the a mission should be aborted due to mechanical or other failure. On-board cameras provide information that can be used in the determination of potential landing sites, which are continually updated and ranked to prevent injury and minimize damage. Pulse Coupled Neural Networks have been used for the detection of features in images that assist in the classification of vegetation and can be used to minimize damage to the aerial vehicle. However, a significant drawback in the use of PCNNs is that they are computationally expensive and have been more suited to off-line applications on conventional computing architectures. As heterogeneous computing architectures are becoming more common, an OpenCL implementation of a PCNN feature generator is presented and its performance is compared across OpenCL kernels designed for CPU, GPU and FPGA platforms. This comparison examines the compute times required for network convergence under a variety of images obtained during unmanned aerial vehicle trials to determine the plausibility for real-time feature detection.

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Machine vision is emerging as a viable sensing approach for mid-air collision avoidance (particularly for small to medium aircraft such as unmanned aerial vehicles). In this paper, using relative entropy rate concepts, we propose and investigate a new change detection approach that uses hidden Markov model filters to sequentially detect aircraft manoeuvres from morphologically processed image sequences. Experiments using simulated and airborne image sequences illustrate the performance of our proposed algorithm in comparison to other sequential change detection approaches applied to this application.