68 resultados para driver comprehension


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With the advent of object-oriented languages and the portability of Java, the development and use of class libraries has become widespread. Effective class reuse depends on class reliability which in turn depends on thorough testing. This paper describes a class testing approach based on modeling each test case with a tuple and then generating large numbers of tuples to thoroughly cover an input space with many interesting combinations of values. The testing approach is supported by the Roast framework for the testing of Java classes. Roast provides automated tuple generation based on boundary values, unit operations that support driver standardization, and test case templates used for code generation. Roast produces thorough, compact test drivers with low development and maintenance cost. The framework and tool support are illustrated on a number of non-trivial classes, including a graphical user interface policy manager. Quantitative results are presented to substantiate the practicality and effectiveness of the approach. Copyright (C) 2002 John Wiley Sons, Ltd.

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Two experiments tested predictions from a theory in which processing load depends on relational complexity (RC), the number of variables related in a single decision. Tasks from six domains (transitivity, hierarchical classification, class inclusion, cardinality, relative-clause sentence comprehension, and hypothesis testing) were administered to children aged 3-8 years. Complexity analyses indicated that the domains entailed ternary relations (three variables). Simpler binary-relation (two variables) items were included for each domain. Thus RC was manipulated with other factors tightly controlled. Results indicated that (i) ternary-relation items were more difficult than comparable binary-relation items, (ii) the RC manipulation was sensitive to age-related changes, (iii) ternary relations were processed at a median age of 5 years, (iv) cross-task correlations were positive, with all tasks loading on a single factor (RC), (v) RC factor scores accounted for 80% (88%) of age-related variance in fluid intelligence (compositionality of sets), (vi) binary- and ternary-relation items formed separate complexity classes, and (vii) the RC approach to defining cognitive complexity is applicable to different content domains. (C) 2002 Elsevier Science (USA). All rights reserved.

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With evidence of increasing accident risk due to age-related declines in health and cognition affecting driver performance, there is a need for research promoting safe mobility of older people. The present study aimed to identify transport options and licensing issues for a group of older people in an Australian community. Ninety-five participants aged 75 and over were interviewed about their driving status and accident record and tested for cognitive ability. After stratification on cognitive level and driver status (current, ex-driver or non-driver), 30 were selected for further in-depth interviews concerning demographics, licence status and impact of change, travel options available and used, and travel characteristics. Considerable reliance on the motor vehicle as the mode of transport and the decision to cease driving were major quality-of-life issues. There was little evidence of planning and support in making the decision to stop driving. Some differences in transport decisions on the basis of cognitive level were evident; however, people with severely compromised cognitive ability (and, therefore, unable to give informed consent) had been excluded. The study suggested the need for resources to assist older people/carers/health professionals to plan for the transition from driver to non-driver and to manage alternative transport options more effectively

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Design: Randomised controlled trial of psychological debriefing. Setting: A British teaching hospital (the Radcliffe Hospital, Oxford). Patients: 66 men and 40 women, aged 17–69 years, admitted to hospital after a motor vehicle accident. Most had been the driver of a car. Median admission duration was four days for the 52 control patients and eight days for the 54 who underwent the intervention. Interventions: A debriefing of about one hour on Day 2 of admission, encouraging patients to describe the accident and express their emotions, followed by a cognitive appraisal which included describing common reactions to traumatic experiences and suggesting a range of people who might be able to assist in the future, including the patient's general practitioner. 91 patients were assessed at four months and 61 were assessed at three years. Control patients had no debriefing or counselling. Main outcome measures: Impact of Event Scale (IES, which focuses on intrusive thoughts and avoidance of similar situations to the event); Brief Symptom Inventory (BSI, a measure of 53 symptoms); and other questions related to physical pain and functional activities. Main results: At four months there was still considerable psychological morbidity among the patients who were followed up. There was a significant difference (P < 0.05) in changes of IES between the 42 who received the intervention, in whom it increased from 15 (standard deviation [SD], 15) to 16 (SD, 15), and the 49 controls, in whom it fell from 15 (SD, 12) to 13 (SD, 14). Similarly, two subscales of the BSI score changed significantly between the intervention group, among whom it deteriorated from 0.5 (SD, 0.5) to 0.6 (SD, 0.8), and the control s, in whom it hardly changed from 0.4 (SD, 0.3) to 0.4 (SD, 0.4). Among the 61 patients followed for three years, the 30 randomised to receive the intervention were significantly worse, by self-report, both psychologically and physically. Their mean IES score deteriorated from a baseline of 15 (SD, 14) to 16 (SD, 18). In comparison, scores for the 31 control patients improved from 16 (SD, 12) to 13 (SD, 17). The difference in change was significant (P < 0.05). Among all patients with high initial scores, these decreased among the controls but not among those receiving the intervention. Conclusion: Psychological counselling should only be used in the context of trials rather than routine care.

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Input-driven models provide an explicit and readily testable account of language learning. Although we share Ellis's view that the statistical structure of the linguistic environment is a crucial and, until recently, relatively neglected variable in language learning, we also recognize that the approach makes three assumptions about cognition and language learning that are not universally shared. The three assumptions concern (a) the language learner as an intuitive statistician, (b) the constraints on what constitute relevant surface cues, and (c) the redescription problem faced by any system that seeks to derive abstract grammatical relations from the frequency of co-occurring surface forms and functions. These are significant assumptions that must be established if input-driven models are to gain wider acceptance. We comment on these issues and briefly describe a distributed, instance-based approach that retains the key features of the input-driven account advocated by Ellis but that also addresses shortcomings of the current approaches.

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Concurrent programs are hard to test due to the inherent nondeterminism. This paper presents a method and tool support for testing concurrent Java components. Too[ support is offered through ConAn (Concurrency Analyser), a too] for generating drivers for unit testing Java classes that are used in a multithreaded context. To obtain adequate controllability over the interactions between Java threads, the generated driver contains threads that are synchronized by a clock. The driver automatically executes the calls in the test sequence in the prescribed order and compares the outputs against the expected outputs specified in the test sequence. The method and tool are illustrated in detail on an asymmetric producer-consumer monitor. Their application to testing over 20 concurrent components, a number of which are sourced from industry and were found to contain faults, is presented and discussed.

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Lifter use in dryers improves mass transfer by increasing the amount of surface area available for transfer and also by increasing the velocity of gas over the particle surface. An even cross-sectional distribution of particles in a dryer improves the efficiency of operation by ensuring that evaporation from falling particles is taking place for the maximum fraction of the rotation period of the drier. Studies on lifter design to improve the cross-sectional particle distribution were performed on angled lifters. A single lifter was used and the mass-transfer rate examined as a function of angular lifter displacement. Analysis of the mass transfer characteristics of single lifters allowed performance comparisons and recommendations for lifter design.