906 resultados para Software quality


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In this study cell wall properties; moisture distribution, stiffness, thickness and cell dimension have been taken into consideration. Cell wall stiffness dependent on complex combination of plant cell microstructures, composition and water holding capacity of the cell. In this work, some preliminary steps taken by investing cell wall properties of apple in order to predict change of porosity and shrinkage during drying. Two different types of apple cell wall characteristic were investigated to correlate with porosity and shrinkage after convective drying. A scanning electron microscope (SEM), 2N Intron, a pyncometer and image J software were used in order to measure and analyze cell characteristics, water dynamics, porosity and shrinkage. Cell stiffness of red delicious apple was found higher than granny smith apples. A significant relationship has found between cell wall characteristics and both heat and mass transfer. Consequently, evolution of porosity and shrinkage noticeably influenced during convective drying by the nature of cell wall. This study has brought better understanding of porosity and shrinkage of dried food stuff in microscopic (cell) level and would provide better insight to attain energy effective drying process and quality food stuff.

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Background Chronic psychological stress may pose a serious threat to health, although the mechanisms are not fully understood. This study examines the impact of stress on modifiable lifestyle factors, depressive symptoms, health-related quality of life (HRQOL) and chronic illness in older Australian women. Methods Cross-sectional data were collected from a random sample of 181 older adults aged 60-70 years from rural and urban areas of South-East Queensland, Australia. We used structural equation modelling to examine associations between stress, modifiable lifestyle factors, HRQoL, and chronic illness. Findings Parameter estimates show that older women who reported life stressors where they felt helpless and feared for their life (high magnitude stressors) also reported higher body mass index (p = 0.03) and more chronic illness (p <0.01). In contrast, duration of exposure to life stressors was associated with higher depressive symptom scores (CES-D, p = 0.02) and sleep disturbance scores (p <0.01). Conclusions Our findings support the link between traumatic personal histories (exposure to high magnitude stressors) and unhealthy lifestyle factors. Findings highlight the need for more research on how stress reduction healthy lifestyle and positive coping strategies can be used to reduce the effects of high magnitude stress on health-related quality of life and chronic illness.

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BACKGROUND Expectations held by health professionals and their patients are likely to affect treatment choices in subacute inpatient rehabilitation settings for older adults. There is a scarcity of empirical evidence evaluating whether health professionals expectations of the quality of their patients' future health states are accurate. METHODS A prospective longitudinal cohort investigation was implemented to examine agreement (kappa coefficients, exact agreement, limits-of-agreement, and intraclass-correlation coefficients) between physiotherapists' (n = 23) prediction of patients' discharge health-related quality of life (reported on the EQ-5D-3L) and the actual health-related quality of life self-reported by patients (n = 272) at their discharge assessment (using the EQ-5D-3L). The mini-mental state examination was used as an indicator of patients' cognitive ability. RESULTS Overall, 232 (85%) patients had all assessment data completed and were included in analysis. Kappa coefficients (exact agreement) ranged between 0.37-0.57 (58%-83%) across EQ-5D-3L domains in the lower cognition group and 0.53-0.68 (81%-85%) in the better cognition group. CONCLUSIONS Physiotherapists in this subacute rehabilitation setting predicted their patients' discharge health-related quality of life with substantial accuracy. Physiotherapists are likely able to provide their patients with sound information regarding potential recovery and health-related quality of life on discharge. The prediction accuracy was higher among patients with better cognition than patients with poorer cognition.

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Fire incident in buildings is common, so the fire safety design of the framed structure is imperative, especially for the unprotected or partly protected bare steel frames. However, software for structural fire analysis is not widely available. As a result, the performance-based structural fire design is urged on the basis of using user-friendly and conventional nonlinear computer analysis programs so that engineers do not need to acquire new structural analysis software for structural fire analysis and design. The tool is desired to have the capacity of simulating the different fire scenarios and associated detrimental effects efficiently, which includes second-order P-D and P-d effects and material yielding. Also the nonlinear behaviour of large-scale structure becomes complicated when under fire, and thus its simulation relies on an efficient and effective numerical analysis to cope with intricate nonlinear effects due to fire. To this end, the present fire study utilizes a second order elastic/plastic analysis software NIDA to predict structural behaviour of bare steel framed structures at elevated temperatures. This fire study considers thermal expansion and material degradation due to heating. Degradation of material strength with increasing temperature is included by a set of temperature-stress-strain curves according to BS5950 Part 8 mainly, which implicitly allows for creep deformation. This finite element stiffness formulation of beam-column elements is derived from the fifth-order PEP element which facilitates the computer modeling by one member per element. The Newton-Raphson method is used in the nonlinear solution procedure in order to trace the nonlinear equilibrium path at specified elevated temperatures. Several numerical and experimental verifications of framed structures are presented and compared against solutions in literature. The proposed method permits engineers to adopt the performance-based structural fire analysis and design using typical second-order nonlinear structural analysis software.

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The detection and correction of defects remains among the most time consuming and expensive aspects of software development. Extensive automated testing and code inspections may mitigate their effect, but some code fragments are necessarily more likely to be faulty than others, and automated identification of fault prone modules helps to focus testing and inspections, thus limiting wasted effort and potentially improving detection rates. However, software metrics data is often extremely noisy, with enormous imbalances in the size of the positive and negative classes. In this work, we present a new approach to predictive modelling of fault proneness in software modules, introducing a new feature representation to overcome some of these issues. This rank sum representation offers improved or at worst comparable performance to earlier approaches for standard data sets, and readily allows the user to choose an appropriate trade-off between precision and recall to optimise inspection effort to suit different testing environments. The method is evaluated using the NASA Metrics Data Program (MDP) data sets, and performance is compared with existing studies based on the Support Vector Machine (SVM) and Naïve Bayes (NB) Classifiers, and with our own comprehensive evaluation of these methods.

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This paper presents an illustrative demonstration of the qualitative data analysis tool NVivo (version 2.0), as employed across a multi-method research design as a comprehensive tool in support of overall research management. The paper will be of interest to (a) novice researchers, as a reference in their research design efforts; (b) academics, involved in research training, where this narrative can be used as a rich teaching case and; potentially to (c) vendors, of similar software tools, who may identify potential new tool applications and valuable tool enhancements.

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Background: There is a paucity of research assessing health-related quality of life (HRQoL) and self-efficacy in caregivers of relatives with dementia in mainland China. Aims: To compare the level of HRQoL between caregivers and the general population in mainland China and to assess the role of caregiver self-efficacy in the relationship between caregiver social support and HRQoL. Methods: A cross-sectional study was conducted in Shanghai, China. The caregivers were recruited from the outpatient department of a teaching hospital. A total of 195 participants were interviewed, using a survey package including the Chinese version of the 36-Item Short-Form Health Survey (SF-36), demographic data, the variables associated with the impairments of care recipients, perceived social support and caregiver self-efficacy. The caregivers' SF-36 scores were compared with those of the general population in China. Results: The results indicated that the HRQoL of the caregivers was poorer compared with that of the general population when matched for age and gender. Multiple regression analyses revealed that caregiver self-efficacy is a partial mediator between social support and HRQoL, and a partial mediator between behavioral and psychological symptoms of dementia (BPSD) and caregiver mental health. Conclusion: Assisting with managing BPSD and enhancing caregiver self-efficacy can be considered integral parts of interventions to improve caregiver HRQoL.

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- Considers broad-scale assessment approaches and how they impact on educational opportunity and outcomes. - Brings together internationally recognised scholars providing new insights into assessment for learning improvement and accountability. - Presents different theoretical and methodological perspectives influential in the field of assessment, learning and social change. - Contributes to the theorising of assessment in contexts characterised by heightened accountability requirements and constant change. This book brings together internationally recognised scholars with an interest in how to use the power of assessment to improve student learning and to engage with accountability priorities at both national and global levels. It includes distinguished writers who have worked together for some two decades to shift the assessment paradigm from a dominant focus on assessment as measurement towards assessment as central to efforts to improve learning. These writers have worked with the teaching profession and, in so doing, have researched and generated key insights into different ways of understanding assessment and its relationship to learning. The volume contributes to the theorising of assessment in contexts characterised by heightened accountability requirements and constant change. The book’s structure and content reflect already significant and growing international interest in assessment as contextualised practice, as well as theories of learning and teaching that underpin and drive particular assessment approaches. Learning theories and practices, assessment literacies, teachers’ responsibilities in assessment, the role of leadership, and assessment futures are the organisers within the book’s structure and content. The contributors to this book have in common the view that quality assessment, and quality learning and teaching are integrally related. Another shared view is that the alignment of assessment with curriculum, teaching and learning is linchpin to efforts to improve both learning opportunities and outcomes for all. Essentially, the book presents new perspectives on the enabling power of assessment. In so doing, the writers recognise that validity and reliability - the traditional canons of assessment – remain foundational and therefore necessary. However, they are not of themselves sufficient for quality education. The book argues that assessment needs to be radically reconsidered in the context of unprecedented societal change. Increasingly, communities are segregating more by wealth, with clear signs of social, political, economic and environmental instability. These changes raise important issues relating to ethics and equity, taken to be core dimensions in enabling the power of assessment to contribute to quality learning for all. This book offers readers new knowledge about how assessment can be used to re/engage learners across all phases of education.

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Field robots often rely on laser range finders (LRFs) to detect obstacles and navigate autonomously. Despite recent progress in sensing technology and perception algorithms, adverse environmental conditions, such as the presence of smoke, remain a challenging issue for these robots. In this paper, we investigate the possibility to improve laser-based perception applications by anticipating situations when laser data are affected by smoke, using supervised learning and state-of-the-art visual image quality analysis. We propose to train a k-nearest-neighbour (kNN) classifier to recognise situations where a laser scan is likely to be affected by smoke, based on visual data quality features. This method is evaluated experimentally using a mobile robot equipped with LRFs and a visual camera. The strengths and limitations of the technique are identified and discussed, and we show that the method is beneficial if conservative decisions are the most appropriate.

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This work aims to contribute to the reliability and integrity of perceptual systems of unmanned ground vehicles (UGV). A method is proposed to evaluate the quality of sensor data prior to its use in a perception system by utilising a quality metric applied to heterogeneous sensor data such as visual and infrared camera images. The concept is illustrated specifically with sensor data that is evaluated prior to the use of the data in a standard SIFT feature extraction and matching technique. The method is then evaluated using various experimental data sets that were collected from a UGV in challenging environmental conditions, represented by the presence of airborne dust and smoke. In the first series of experiments, a motionless vehicle is observing a ’reference’ scene, then the method is extended to the case of a moving vehicle by compensating for its motion. This paper shows that it is possible to anticipate degradation of a perception algorithm by evaluating the input data prior to any actual execution of the algorithm.

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This paper proposes an experimental study of quality metrics that can be applied to visual and infrared images acquired from cameras onboard an unmanned ground vehicle (UGV). The relevance of existing metrics in this context is discussed and a novel metric is introduced. Selected metrics are evaluated on data collected by a UGV in clear and challenging environmental conditions, represented in this paper by the presence of airborne dust or smoke. An example of application is given with monocular SLAM estimating the pose of the UGV while smoke is present in the environment. It is shown that the proposed novel quality metric can be used to anticipate situations where the quality of the pose estimate will be significantly degraded due to the input image data. This leads to decisions of advantageously switching between data sources (e.g. using infrared images instead of visual images).

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This paper proposes an experimental study of quality metrics that can be applied to visual and infrared images acquired from cameras onboard an unmanned ground vehicle (UGV). The relevance of existing metrics in this context is discussed and a novel metric is introduced. Selected metrics are evaluated on data collected by a UGV in clear and challenging environmental conditions, represented in this paper by the presence of airborne dust or smoke.

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Energy auditing is an effective but costly approach for reducing the long-term energy consumption of buildings. When well-executed, energy loss can be quickly identified in the building structure and its subsystems. This then presents opportunities for improving energy efficiency. We present a low-cost, portable technology called "HeatWave" which allows non-experts to generate detailed 3D surface temperature models for energy auditing. This handheld 3D thermography system consists of two commercially available imaging sensors and a set of software algorithms which can be run on a laptop. The 3D model can be visualized in real-time by the operator so that they can monitor their degree of coverage as the sensors are used to capture data. In addition, results can be analyzed offline using the proposed "Spectra" multispectral visualization toolbox. The presence of surface temperature data in the generated 3D model enables the operator to easily identify and measure thermal irregularities such as thermal bridges, insulation leaks, moisture build-up and HVAC faults. Moreover, 3D models generated from subsequent audits of the same environment can be automatically compared to detect temporal changes in conditions and energy use over time.

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Importance Approximately one-third of patients with peripheral artery disease experience intermittent claudication, with consequent loss of quality of life. Objective To determine the efficacy of ramipril for improving walking ability, patient-perceived walking performance, and quality of life in patients with claudication. Design, Setting, and Patients Randomized, double-blind, placebo-controlled trial conducted among 212 patients with peripheral artery disease (mean age, 65.5 [SD, 6.2] years), initiated in May 2008 and completed in August 2011 and conducted at 3 hospitals in Australia. Intervention Patients were randomized to receive 10 mg/d of ramipril (n = 106) or matching placebo (n = 106) for 24 weeks. Main Outcome Measures Maximum and pain-free walking times were recorded during a standard treadmill test. The Walking Impairment Questionnaire (WIQ) and Short-Form 36 Health Survey (SF-36) were used to assess walking ability and quality of life, respectively. Results At 6 months, relative to placebo, ramipril was associated with a 75-second (95% CI, 60-89 seconds) increase in mean pain-free walking time (P < .001) and a 255-second (95% CI, 215-295 seconds) increase in maximum walking time (P < .001). Relative to placebo, ramipril improved the WIQ median distance score by 13.8 (Hodges-Lehmann 95% CI, 12.2-15.5), speed score by 13.3 (95% CI, 11.9-15.2), and stair climbing score by 25.2 (95% CI, 25.1-29.4) (P < .001 for all). The overall SF-36 median Physical Component Summary score improved by 8.2 (Hodges-Lehmann 95% CI, 3.6-11.4; P = .02) in the ramipril group relative to placebo. Ramipril did not affect the overall SF-36 median Mental Component Summary score. Conclusions and Relevance Among patients with intermittent claudication, 24-week treatment with ramipril resulted in significant increases in pain-free and maximum treadmill walking times compared with placebo. This was associated with a significant increase in the physical functioning component of the SF-36 score. Trial Registration clinicaltrials.gov Identifier: NCT00681226

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Purpose Patient-reported symptoms and health-related quality of life (QoL) benefits were investigated in a randomized, phase III trial of afatinib or cisplatin/pemetrexed. Patients and Methods Three hundred forty-five patients with advanced epidermal growth factor receptor (EGFR) mutation-positive lung adenocarcinoma were randomly assigned 2:1 to afatinib 40 mg per day or up to six cycles of cisplatin/pemetrexed. Lung cancer symptoms and health-related QoL were assessed every 21 days until progression using the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire C30 and Lung Cancer-13 questionnaires. Analyses of cough, dyspnea, and pain were preplanned, including percentage of patients who improved on therapy, time to deterioration of symptoms, and change in symptoms over time. Results Questionnaire compliance was high. Compared with chemotherapy, afatinib significantly delayed the time to deterioration for cough (hazard ratio [HR], 0.60; 95% CI, 0.41 to 0.87; P = .007) and dyspnea (HR, 0.68; 95% CI, 0.50 to 0.93; P = .015), but not pain (HR, 0.83; 95% CI, 0.62 to 1.10; P = .19). More patients on afatinib (64%) versus chemotherapy (50%) experienced improvements in dyspnea scores (P lt; .010). Differences in mean scores over time significantly favored afatinib over chemotherapy for cough (P lt; .001) and dyspnea (P = .001). Afatinib showed significantly better mean scores over time in global health status/QoL (P = .015) and physical (P = .001), role (P = .004), and cognitive (P lt; .007) functioning compared with chemotherapy. Fatigue and nausea were worse with chemotherapy, whereas diarrhea, dysphagia, and sore mouth were worse with afatinib (all P = .01). Conclusion In patients with lung adenocarcinoma with EGFR mutations, first-line afatinib was associated with better control of cough and dyspnea compared with chemotherapy, although diarrhea, dysphagia, and sore mouth were worse. Global health status/QoL was also improved over time with afatinib compared with chemotherapy.