310 resultados para Semi-Open


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Loss of home is common to all people from a refugee background yet we have little understanding of the diversity of meaning associated with this important concept. A phenomenological approach was used to explore experiences of home amongst Karen and Chin refugees residing in Brisbane. In-depth, semi-structured interviews were conducted with nine participants from Karen and Chin backgrounds. The participants comprised five females and four males (mean age 40 years, median length of time in Australia 1.33 years). Participants described their migration stories, including pre- and post-migration history. Analysis was conducted using interpretative phenomenological analysis. Three superordinate themes, explicating the meaning of home for participants, were identified: home as the experience of a psychological space of safety and retreat; home as the socio-emotional space of relatedness to family; and home as geographical-emotional landscape. Loss of home was experienced as a multidimensional loss associated with emotional and physical disturbances. These findings, based upon a phenomenological paradigm, enhance understanding of the experience of being a refugee and of the suffering engendered by loss of home. They open up the possibility for conceptualizing refugee responses in terms of human suffering and meaning making.

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Background: In the last decade, there has been increasing interest in the health effects of sedentary behavior, which is often assessed using self-report sitting-time questions. The aim of this qualitative study was to document older adults’ understanding of sitting-time questions from the International Physical Activity (PA) Questionnaire (IPAQ) and the PA Scale for the Elderly (PASE). Methods: Australian community-dwelling adults aged 65+ years answered the IPAQ and PASE sitting questions in face-to-face semi-structured interviews. IPAQ uses one open-ended question to assess sitting on a weekday in the last 7 days 'at work, at home, while doing coursework and during leisure time'; PASE uses a three-part closed question about daily leisure-time sitting in the last 7 days. Participants expressed their thoughts out loud while answering each question. They were then probed about their responses. Interviews were recorded, transcribed and coded into themes. Results: Mean age of the 28 male and 27 female participants was 73 years (range 65-89). The most frequently reported activity was watching TV. For both questionnaires, many participants had difficulties understanding what activities to report. Some had difficulty understanding what activities should be classified as ‘leisure-time sitting’. Some assumed they were being asked to only report activities provided as examples. Most reported activities they normally do, rather than those performed on a day in the previous week. Participants used a variety of strategies to select ‘a day’ for which they reported their sitting activities and to calculate sitting time on that day. Therefore, many different ways of estimating sitting time were used. Participants had particular difficulty reporting their daily sitting-time when their schedules were not consistent across days. Some participants declared the IPAQ sitting question too difficult to answer. Conclusion: The accuracy of older adults’ self-reported sitting time is questionable given the challenges they have in answering sitting-time questions. Their responses to sitting-time questions may be more accurate if our recommendations for clarifying the sitting domains, providing examples relevant to older adults and suggesting strategies for formulating responses are incorporated. Future quantitative studies should include objective criterion measures to assess validity and reliability of these questions.

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Scaffolds with open-pore morphologies offer several advantages in cell-based tissue engineering, but their use is limited by a low cell seeding efficiency. We hypothesized that inclusion of a collagen network as filling material within the open-pore architecture of polycaprolactone-tricalcium phosphate (PCL-TCP) scaffolds increases human bone marrow stromal cells (hBMSC) seeding efficiency under perfusion and in vivo osteogenic capacity of the resulting constructs. PCL-TCP scaffolds, rapid prototyped with a honeycomb-like architecture, were filled with a collagen gel and subsequently lyophilized, with or without final crosslinking. Collagen-free scaffolds were used as controls. The seeding efficiency was assessed after overnight perfusion of expanded hBMSC directly through the scaffold pores using a bioreactor system. By seeding and culturing freshly harvested hBMSC under perfusion for 3 weeks, the osteogenic capacity of generated constructs was tested by ectopic implantation in nude mice. The presence of the collagen network, independently of the crosslinking process, significantly increased the cell seeding efficiency (2.5-fold), and reduced the loss of clonogenic cells in the supernatant. Although no implant generated frank bone tissue, possibly due to the mineral distribution within the scaffold polymer phase, the presence of a non crosslinked collagen phase led to in vivo formation of scattered structures of dense osteoids. Our findings verify that the inclusion of a collagen network within open morphology porous scaffolds improves cell retention under perfusion seeding. In the context of cell-based therapies, collagen-filled porous scaffolds are expected to yield superior cell utilization, and could be combined with perfusion-based bioreactor devices to streamline graft manufacture.

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Machine learning has become a valuable tool for detecting and preventing malicious activity. However, as more applications employ machine learning techniques in adversarial decision-making situations, increasingly powerful attacks become possible against machine learning systems. In this paper, we present three broad research directions towards the end of developing truly secure learning. First, we suggest that finding bounds on adversarial influence is important to understand the limits of what an attacker can and cannot do to a learning system. Second, we investigate the value of adversarial capabilities-the success of an attack depends largely on what types of information and influence the attacker has. Finally, we propose directions in technologies for secure learning and suggest lines of investigation into secure techniques for learning in adversarial environments. We intend this paper to foster discussion about the security of machine learning, and we believe that the research directions we propose represent the most important directions to pursue in the quest for secure learning.

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Single particle analysis (SPA) coupled with high-resolution electron cryo-microscopy is emerging as a powerful technique for the structure determination of membrane protein complexes and soluble macromolecular assemblies. Current estimates suggest that ∼104–105 particle projections are required to attain a 3 Å resolution 3D reconstruction (symmetry dependent). Selecting this number of molecular projections differing in size, shape and symmetry is a rate-limiting step for the automation of 3D image reconstruction. Here, we present SwarmPS, a feature rich GUI based software package to manage large scale, semi-automated particle picking projects. The software provides cross-correlation and edge-detection algorithms. Algorithm-specific parameters are transparently and automatically determined through user interaction with the image, rather than by trial and error. Other features include multiple image handling (∼102), local and global particle selection options, interactive image freezing, automatic particle centering, and full manual override to correct false positives and negatives. SwarmPS is user friendly, flexible, extensible, fast, and capable of exporting boxed out projection images, or particle coordinates, compatible with downstream image processing suites.

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Since manually constructing domain-specific sentiment lexicons is extremely time consuming and it may not even be feasible for domains where linguistic expertise is not available. Research on the automatic construction of domain-specific sentiment lexicons has become a hot topic in recent years. The main contribution of this paper is the illustration of a novel semi-supervised learning method which exploits both term-to-term and document-to-term relations hidden in a corpus for the construction of domain specific sentiment lexicons. More specifically, the proposed two-pass pseudo labeling method combines shallow linguistic parsing and corpusbase statistical learning to make domain-specific sentiment extraction scalable with respect to the sheer volume of opinionated documents archived on the Internet these days. Another novelty of the proposed method is that it can utilize the readily available user-contributed labels of opinionated documents (e.g., the user ratings of product reviews) to bootstrap the performance of sentiment lexicon construction. Our experiments show that the proposed method can generate high quality domain-specific sentiment lexicons as directly assessed by human experts. Moreover, the system generated domain-specific sentiment lexicons can improve polarity prediction tasks at the document level by 2:18% when compared to other well-known baseline methods. Our research opens the door to the development of practical and scalable methods for domain-specific sentiment analysis.

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Railway timetabling is an important process in train service provision as it matches the transportation demand with the infrastructure capacity while customer satisfaction is also considered. It is a multi-objective optimisation problem, in which a feasible solution, rather than the optimal one, is usually taken in practice because of the time constraint. The quality of services may suffer as a result. In a railway open market, timetabling usually involves rounds of negotiations among a number of self-interested and independent stakeholders and hence additional objectives and constraints are imposed on the timetabling problem. While the requirements of all stakeholders are taken into consideration simultaneously, the computation demand is inevitably immense. Intelligent solution-searching techniques provide a possible solution. This paper attempts to employ a particle swarm optimisation (PSO) approach to devise a railway timetable in an open market. The suitability and performance of PSO are studied on a multi-agent-based railway open-market negotiation simulation platform.

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Open-source software systems have become a viable alternative to proprietary systems. We collected data on the usage of an open-source workflow management system developed by a university research group, and examined this data with a focus on how three different user cohorts – students, academics and industry professionals – develop behavioral intentions to use the system. Building upon a framework of motivational components, we examined the group differences in extrinsic versus intrinsic motivations on continued usage intentions. Our study provides a detailed understanding of the use of open-source workflow management systems in different user communities. Moreover, it discusses implications for the provision of workflow management systems, the user-specific management of open-source systems and the development of services in the wider user community.

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This paper describes modelling, estimation and control of the horizontal translational motion of an open-source and cost effective quadcopter — the MikroKopter. We determine the dynamics of its roll and pitch attitude controller, system latencies, and the units associated with the values exchanged with the vehicle over its serial port. Using this we create a horizontal-plane velocity estimator that uses data from the built-in inertial sensors and an onboard laser scanner, and implement translational control using a nested control loop architecture. We present experimental results for the model and estimator, as well as closed-loop positioning.

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The Malaysian National Innovation Model blueprint states that there is an urgent need to pursue an innovation-oriented economy to improve the nation’s capacity for knowledge, creativity and innovation. In nurturing a pervasive innovation culture, the Malaysian government has declared the year 2010 as an Innovative Year whereby creativity among its population is highly celebrated. However, while Malaysian citizens are encouraged to be creative and innovative, scientific data and information generated from publicly funded research in Malaysia is locked up because of rigid intellectual property licensing regimes and traditional publishing models. Reflecting on these circumstances, this paper looks at, and argue why, scientific data and information should be made available, accessible and re-useable freely to promote the grassroots level of innovation in Malaysia. Using innovation theory as its platform of argument, this paper calls for an open access policy for publicly funded research output to be adopted and implemented in Malaysia. Simultaneously, a normative analytic approach is used to determine the types of open access policy that ought to be adopted to spur greater innovation among Malaysians.