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Computer Support (computer + support)

Distribution by Scientific Domains

Engineering	60%

Selected Abstracts

Empirical design of computer support and staffing in concurrent engineering

HUMAN FACTORS AND ERGONOMICS IN MANUFACTURING & SERVICE INDUSTRIES, Issue 2 2006
Joe W. Meredith
Manufacturing environments are characterized by underlying operational approaches and assumptions. One such assumption is that concurrent engineering (CE) is superior to traditional sequential processing. A laboratory experiment was conducted using 180 engineering and building construction students as subjects. The engineering methodology variable was sequential and concurrent engineering. There were large teams, consisting of six students, and small teams, consisting of three students. The computer support variable was using and not using groupware. Each team was given a set of requirements to design a transportation system that moved a payload from one point to another. Each team was asked to (a) develop a design concept, (b) develop a detail design in the form of engineering drawings, (c) manufacture the system based on their design products (e.g., drawings and specifications) using toy plastic LEGOS, and (d) test the system to determine if it met the design requirements. There was no significant difference in performance between concurrent engineering groups and sequential engineering processes. Small groups significantly outperformed large groups in all conditions. Computer support did not significantly improve the performance of large or small groups. Participants in the experiment were equally satisfied with all conditions. An external survey strongly endorsed the superiority of CE as compared to sequential engineering. Results are discussed in terms of why practitioners believe in the effectiveness of CE, yet an empirical test failed to demonstrate better performance. © 2006 Wiley Periodicals, Inc. Hum Factors Man 16: 177,193, 2006. [source]

Simulation of drying process of corn kernels during microwave and convective treatment

ASIA-PACIFIC JOURNAL OF CHEMICAL ENGINEERING, Issue 2 2007
Gábor Bihercz
Abstract Drying is a necessary technology and a very energy-demanding process in the area of meat and vegetable processing; it is a tool for finishing semiprocessed or processed goods. Taking the given conditions into consideration, development of technology is necessary, which serves several aims that are often in disagreement with each other (in terms of improvement of availability value, avoidance of artificial additives, energy optimization, reduction of other cost factors, etc.). Until now, several scientific works have been published serving solutions for one specific problem of practice. The main idiosyncrasy of these works is the difference between their methods and availability; hence these are unsuitable to give a uniform model for products with different physical-biological properties: because, it goes without saying, circumstances of their birth as well as their aims differ so much. Computer support nowadays allows us to build a uniform model based on previous research and auxiliary measurement results, which can simulate the drying process of some of the most important agricultural products. Copyright © 2007 Curtin University of Technology and John Wiley & Sons, Ltd. [source]

Empirical design of computer support and staffing in concurrent engineering

Effectiveness of simulation on health profession students' knowledge, skills, confidence and satisfaction

INTERNATIONAL JOURNAL OF EVIDENCE BASED HEALTHCARE, Issue 3 2008
Susan Laschinger
Abstract Background, Despite the recent wave of interest being shown in high-fidelity simulators, they do not represent a new concept in healthcare education. Simulators have been a part of clinical education since the 1950s. The growth of patient simulation as a core educational tool has been driven by a number of factors. Declining inpatient populations, concerns for patient safety and advances in learning theory are forcing healthcare educators to look for alternatives to the traditional clinical encounter for skill acquisition for students. Objective, The aim of this review was to identify the best available evidence on the effectiveness of using simulated learning experiences in pre-licensure health profession education. Inclusion criteria,Types of studies: This review considered any experimental or quasi-experimental studies that addressed the effectiveness of using simulated learning experiences in pre-licensure health profession practice. In the absence of randomised controlled trials, other research designs were considered for inclusion, such as, but not limited to: non-randomised controlled trials and before-and-after studies. Types of participants: This review included participants who were pre-licensure practitioners in nursing, medicine, and rehabilitation therapy. Types of intervention(s)/phenomena of interest: Studies that evaluated the use of human physical anatomical models with or without computer support, including whole-body or part-body simulators were included. Types of outcome measures, Student outcomes included knowledge acquisition, skill performance, learner satisfaction, critical thinking, self-confidence and role identity. Search strategy, Using a defined search and retrieval method, the following databases were accessed for the period 1995,2006: Medline, CINAHL, Embase, PsycINFO, HealthSTAR, Cochrane Database of Systematic Reviews and ERIC. Methodological quality, Each paper was assessed by two independent reviewers for methodological quality prior to inclusion in the review using the standardised critical appraisal instruments for evidence of effectiveness, developed by the Joanna Briggs Institute. Disagreements were dealt with by consultations with a third reviewer. Data collection, Information was extracted from each paper independently by two reviewers using the standardised data extraction tool from the Joanna Briggs Institute. Disagreements were dealt with by consultation with a third reviewer. Data synthesis, Due to the type of designs and quality of available studies, it was not possible to pool quantitative research study results in statistical meta-analysis. As statistical pooling was not possible, the findings are presented in descriptive narrative form. Results, Twenty-three studies were selected for inclusion in this review including partial task trainers and high-fidelity human patient simulators. The results indicate that there is high learner satisfaction with using simulators to learn clinical skills. The studies demonstrated that human patient simulators which are used for teaching higher level skills, such as airway management, and physiological concepts are useful. While there are short-term gains in knowledge and skill performance, it is evident that performance of skills over time after initial training decline. Conclusion, At best, simulation can be used as an adjunct for clinical practice, not a replacement for everyday practice. Students enjoyed the sessions and using the models purportedly makes learning easier. However, it remains unclear whether the skills learned through a simulation experience transfer into real-world settings. More research is needed to evaluate whether the skills acquired with this teaching methodology transfer to the practice setting such as the impact of simulation training on team function. [source]

A Computer Implementation of the Separate Maintenance Model for Complex-system Reliability

QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, Issue 7 2006
M. Tortorella
Abstract Reliability modeling and quantitative reliability prediction for all but the simplest system architectures demands intensive computer support for the numerical computations required. Many commercial and academic reliability modeling software packages provide support for the Markov-chain state diagram system reliability model. Other system reliability models, such as those offering non-exponential life and/or repair time distributions, transient analysis, or other special handling, may sometimes be desirable. Users have fewer choices for software supporting these options. This paper describes SUPER, a software package developed at Bell Laboratories, which provides computational support for the separate maintenance model as well as for some other useful system reliability descriptions. SUPER is an acronym for System Used for Prediction and Evaluation of Reliability. The paper also includes a brief tutorial to assist practitioners with system reliability model selection, a review of the models contained in SUPER and their theoretical bases, and implementation issues. SUPER has been used in the telecommunications industry for over 15 years. The paper includes an example from this experience. Copyright © 2005 John Wiley & Sons, Ltd. [source]