Using virtual reality and mood-induction procedures to test products with consumers of ceramic tiles

This work describes a Virtual Reality Environment (VRE), through which users are able to view and test ceramic tile products. Users’ virtual interfacing with the products generated emotional experiences that allowed them to feel “engaged” with the products. Users could choose between different kinds of products and test them out in order to know how they would look in a real-world context. In the VRE several mood-induction Procedures for inducing relaxation were included. The VRE was tested with respect to its ability to induce relaxation and sense of presence in 26 participants. It was also analyzed the level of satisfaction. Measures included the Visual Analogue Scale, the Self-Assessment Manikin, the Presence Self-Assessment Manikin, and a Satisfaction Scale. The results showed that the VRE was effective among participants in inducing relaxation and high sense of presence. In addition, participants’ satisfaction with the experience in the VRE was high. The VRE thus could be a useful tool for showing and testing products and for evoking a positive emotional association while users are interacting.     

A Bayesian support tool for morphological design

Dynamic computer based support tools for the conceptual design phase have provided a long-standing challenge to develop. This is largely due to the ‘fluid’ nature of the conceptual design phase. Design evaluation methods, which form the basis of most computer design support tools, provide poor support for multiple outcomes. This research proposes a stochastic-based support tool that addresses this problem. A Bayesian Belief Network (BBN) is used to represent the causal links between design variables. Included in this research is an efficient method for learning a design domain network from previous design data in the structure of a morphological design chart. This induction algorithm is based on information content. A user interface is proposed to support dynamically searching the conceptual design space, based on a partial design specification. This support tool is empirically compared against a more traditional search process. While no compelling evidence is produced to support the stochastic-based approach, an interesting broader design search behaviour emerges from observations of the use of the stochastic design support tool.     

Beyond WIMP

The WIMP (windows, icons, menus, point-and-click devices) graphical user interface (GUI) is not an ideal interface. Expert users find pure WIMP GUIs frustratingly slow and thus use keyboard shortcuts. In addition, they don't scale well-GUI bloat accompanies feature bloat. The most serious limitation, however, is that WIMP GUIs were designed for keyboard-plus-mouse desktop computing environments-environments that takes advantage only of vision and primitive touch. Our goal should be to design user interfaces that match our human perceptual, cognitive, manipulative and social abilities. We want to interact as naturally with computers and intelligent devices as we communicate and collaborate with each other and as we manipulate our physical environments. Indeed, computers are increasingly being used to facilitate human communication, collaboration and social interaction. Therefore, we should increasingly focus on human-human interaction, not just human-computer interaction. This change in focus reflects not only changes in the mode of computer use but also the increasingly invisible nature of the computer in our environments. New environments must serve as forcing functions to give us far higher expectations for user interfaces than we have had previously. Furthermore, the potential of future interfaces for handicapped people is phenomenal. Thus, despite the technology challenges, the greatest challenge lies in our understanding of human capabilities and how to incorporate that understanding into new design tools, methodologies and user interfaces     

A monitoring tool of workers' activity at Video Display Terminals for investigating VDT-related risk of musculoskeletal disorders

Today the risk factors related to the use of Video Display Terminals (VDT) are assessed by investigating the actual activities at the VDT through subjective questionnaires and/or quantitative measurements. Questionnaire outcomes are quite imprecise and seldom objective. Quantitative measurements (EMG recordings, electrogoniometers, motion analysis systems) mostly prevent subjects from moving freely while working at the VDT. The paper presents an automatic tool for the monitoring of activity at VDTs, using a quantitative, objective approach. The suitability of the proposed tool was fully tested in the laboratory, both in terms of functionalities, accuracy of the tool, and acceptance by the subjects involved. The outcomes show that the tool allows for a detailed analysis of VDT activities and may be used to improve VDT-related risk analysis with high accuracy and good acceptance by workers.     

基于问题框架的行为驱动开发研究

问题框架(Problem Frames,PF)在需求工程研究领域中已经获得了广泛重视和研究。目前,问题框架的相关研究已经取得了较多成果,但如何从需求模型(问题图)平滑过渡到软件设计以及实现仍是一个有待解决的问题。文中对如何将问题图转换到用户场景文本以及通过用户场景来辅助行为驱动开发方法进行软件设计与开发进行了研究,提出了一种问题框架与行为驱动开发相结合的软件开发方法(PFBDD)。该方法能够帮助系统分析员将用户需求 平滑过渡 到软件设计及测试,从而避免软件项目中表达不一致带来的问题。此外,通过实例介绍了如何将此方法应用到一个车管业务排队系统中,并介绍了Gherkin语言和Specflow工具。该方法对于问题框架进一步走向实践具有重要的推动作用。     

Cognitive Analysis of Intraoperative Critical Events: A Problem-Driven Approach to Aiding Clinicians’ Performance*

Human error is responsible for a large proportion of the anaesthesia mishaps that occur annually in the United States. Ventilation-related events (VRE) constitute a significant number of anaesthesia critical incidents. Monitoring equipment and their displays extend anaesthesiologists’ resources during VRE but at the expense of additional cognitive demands. This project is a cognitive analysis of intraoperative (inside the operating room) VRE. Goal–means networks were utilised to build a problem-solving model of clinicians’ management of patients’ ventilation during anaesthesia and to map the demands of VRE. The model was also used to identify challenging VRE that were then simulated using a comprehensive anaesthesia simulator. The response of eight experienced clinicians was captured on videotape and analysed to investigate the effectiveness of medical equipment in supporting clinical decision making during VRE.     

Building virtual cities,inspiring intelligent citizens: Digital games for developing students’ problem solving and learning motivation

This study investigates the effectiveness digital game-based learning (DGBL) on students’ problem solving, learning motivation, and academic achievement. In order to provide substantive empirical evidence, a quasi-experimental design was implemented over the course of a full semester (23 weeks). Two ninth-grade Civics and Society classes, with a total of 44 students (15–16 years old), were randomly assigned to one of two conditions: an experimental group (incorporating DGBL) and a comparison group (taught using traditional instruction). Two-way mixed ANOVA was employed to evaluate changes in problem solving ability and compare the effectiveness the two strategies, while ANCOVA was used to analyze the effects on learning motivation and academic achievement. The results of this study are summarized as follows: (1) The DGBL strategy was clearly effective in promoting students’ problem solving skills, while the control group showed no improvement. Additionally, data from the mid-test and post-test demonstrate that, as a higher order thinking skill, problem-solving requires a full semester to develop. (2). DGBL resulted in better learning motivation for students in the experimental group as compared to learners receiving TI. (3) Contrary to some suggestions that digital games could inhibit academic achievement, no statistically significant difference was found between the two groups. Most importantly, the quantitative improvement in problem-solving and learning motivation suggest that DGBL can be exploited as a useful and productive tool to support students in effective learning while enhancing the classroom atmosphere. Future research in DGBL should emphasize the evaluation of other higher order elements of the cognitive domain in terms of academic achievement outcomes and skills, such as critical and creative thinking.     

Using tangible user interfaces in computer-based training systems for low-functioning autistic children

In this paper, the design of a computer-based training (CBT) system for low-functioning autistic children is addressed. The emphasis is on ease-of-use and learning efficiency of CBT systems with different interaction styles, namely the WIMP (Window Icon Menu Pointing Device) and TUI (Tangible User Interface) interaction styles. Two WIMP-based CBT systems with different pointing devices were involved in the study. The first system applied a standard computer mouse as a pointing device, while the second one employed a touch screen instead. For the TUI-based CBT system, a tabletop setting was adopted. Based on the known characteristics of TUI and children with autism, as well as related cognitive and learning theories, the benefits of TUI for low-functioning autistic children have been investigated. Elementary skill teaching was chosen as a case study for performance evaluation of these CBT systems. Empirical results show that the touch-based and TUI-based systems offered much better ease-of-use performance than that of the mouse-based system. Regarding learning efficacy, experimental results show that the TUI-based system achieved higher skill improvement, as compared with the WIMP-based system and a non-computer training method. Some guidelines and suggestions for the design of a TUI-based system for children with autism are summarized.     

The implications of window type environments for developers of educational software

Schools in the U.K. are beginning to acquire computers which support a Window-Icon-Menu-Pointer (WIMP) user interface. One factor in the rate of uptake will be the availability, or otherwise, of suitable educational software. This paper reports on the technical aspects of software development for a WIMP environment (Microsoft Windows) and is based on experience gained in an educational software development project called “Dancing Windows”.     

Environmental factors and features that influence visual search in a 3D WIMP interface

The challenge of moving past the classic Window Icons Menus Pointer (WIMP) interface, i.e. by turning it ‘3D’, has resulted in much research and development. To evaluate the impact of 3D on the ‘finding a target picture in a folder’ task, we built a 3D WIMP interface that allowed the systematic manipulation of visual depth, visual aides, semantic category distribution of targets versus non-targets; and the detailed measurement of lower-level stimuli features. Across two separate experiments, one large sample web-based experiment, to understand associations, and one controlled lab environment, using eye tracking to understand user focus, we investigated how visual depth, use of visual aides, use of semantic categories, and lower-level stimuli features (i.e. contrast, colour and luminance) impact how successfully participants are able to search for, and detect, the target image. Moreover in the lab-based experiment, we captured pupillometry measurements to allow consideration of the influence of increasing cognitive load as a result of either an increasing number of items on the screen, or due to the inclusion of visual depth.Our findings showed that increasing the visible layers of depth, and inclusion of converging lines, did not impact target detection times, errors, or failure rates. Low-level features, including colour, luminance, and number of edges, did correlate with differences in target detection times, errors, and failure rates. Our results also revealed that semantic sorting algorithms significantly decreased target detection times. Increased semantic contrasts between a target and its neighbours correlated with an increase in detection errors. Finally, pupillometric data did not provide evidence of any correlation between the number of visible layers of depth and pupil size, however, using structural equation modelling, we demonstrated that cognitive load does influence detection failure rates when there is luminance contrasts between the target and its surrounding neighbours. Results suggest that WIMP interaction designers should consider stimulus-driven factors, which were shown to influence the efficiency with which a target icon can be found in a 3D WIMP interface.     

柔性制造系统中CNC机床故障诊断机理研究

为了及时发现处理柔性制造系统数控机床的故障或异常现象,设计了CNC在线故障诊断测试系统。该系统不仅便于查找数控机床故障的一个或多个症结,可以快捷、准确地对CNC故障定位,而且解决了诊断处理与知识应用中的相关问题。为了对CNC设备终端提供可靠的故障排除建议,对伺服控制组件与后台服务关联关系进行深入剖析,并对故障数据库进行描述与测试程序设计,解决了系统维护、扩展与升级操作等问题。     

集成虚拟现实环境在工程设计分析中的应用 *

虚拟现实技术在工程设计与分析上有很大的应用潜力。可是 ,虚拟环境的创建时间长、成本高,极大地限制了虚拟现实技术在工程上的应用。为此 ,提出了虚拟现实脚本生成器的概念,将虚拟现实技术与过程的设计、分析集成化,创造性地提出了一种自上而下的设计方法———VR-IEDA,以便高效、快速地创建虚拟原型,提高计算机虚拟复杂系统工程的性价比。在 VR-IEDA中复杂系统的结构和行为被计算机捕捉并自动生成可执行的 VR仿真代码 ,从而减少了创建虚拟环境的时间,便利了基于仿真的过程分析和设计。最后 ,以武器系统的维修过程为     

Reliability-based design optimization for problems with interval distribution parameters

Traditional reliability-based design optimization (RBDO) generally describes uncertain variables using random distributions, while some crucial distribution parameters in practical engineering problems can only be given intervals rather than precise values due to the limited information. Then, an important probability-interval hybrid reliability problem emerged. For uncertain problems in which interval variables are included in probability distribution functions of the random parameters, this paper establishes a hybrid reliability optimization design model and the corresponding efficient decoupling algorithm, which aims to provide an effective computational tool for reliability design of many complex structures. The reliability of an inner constraint is an interval since the interval distribution parameters are involved; this paper thus establishes the probability constraint using the lower bound of the reliability degree which ensures a safety design of the structure. An approximate reliability analysis method is given to avoid the time-consuming multivariable optimization of the inner hybrid reliability analysis. By using an incremental shifting vector (ISV) technique, the nested optimization problem involved in RBDO is converted into an efficient sequential iterative process of the deterministic design optimization and the hybrid reliability analysis. Three numerical examples are presented to verify the proposed method, which include one simple problem with explicit expression and two complex practical applications.     

Bridging the gap between analysis and design: improving existing driver interfaces with tools from the framework of cognitive work analysis

Two studies of train driving are presented, both within the framework of cognitive work analysis. In the first study, the modelling tool abstraction–decomposition space is adapted to routine conditions, making the analysis more representative for normal procedures. A major contribution to these analyses was the use of the method for ‘collegial verbalisation’. One particular advantage with this method over other verbalisation methods is that it supplies the analysts with data that contain much more information, but not at the expense of being more subjective. On the contrary, this method produces think-aloud protocols from video-recordings that do not have to be interpreted by the researcher. From these analyses, it was possible to distinguish information that is an intrinsic part of the train driver task from information that is dependent on the configuration and design of the current support system. The analyses show that the driver works in three rather separate time intervals with a long-range, a short-term and an immediate sense of perspective. The driver switches between these while travelling between two stations. Based on these behaviour-shaping constraints, a prototype of a planning area of a driver interface was developed, making feed-forward planning possible for the driver. Four design iterations were completed, using a user-centred system design (UCSD) approach. Early tests show that the planning area of the interface supports the feed-forward decision strategy used by drivers who prefer an active driving style. However, the driver group also made substantial changes in the design, indicating that UCSD is an efficient tool in order to capture user competencies, and to bridge the gap between analysis and design.     

Discourse structures in iconic communication

The success of the WIMP interface, the convergence towards multimedia platforms and the growing use of the Internet combine to place new demands on the systems we use to communicate with one another. Proposals for iconic languages are not new but the computer offers the ability to incorporate interactivity and animation into iconic writing and reading systems. One approach to developing computer-based iconic communication systems derives from the visual arts (i.e. graphic design, illustration, film animation, documentary video, etc.). An alternative approach is derived from computational linguistics in that the syntactic or semantic structure of language is retained while iconic images are used in place of words. Differences between the study of natural language and the design of an iconic language are discussed and the components of one particular system, IconText, are described. Of particular interest is the attempt to capture some pragmatic aspects of communication, both in terms of conveying the intentions of the author and concerning the sequential delivery of the message.     

Neural networks for estimating the tool path length in concurrent engineering applications

This paper deals with the development of a neural computing system that can predict the cutting tool path length for milling an arbitrary pocket defined within the domain of a product design, in a computer numerically controlled (CNC) setting. Existing computer aided design and manufacturing systems (CAD/CAM) consume significant amounts of time in terms of data entry pertaining to the geometries and subsequent modifications to them. In the concurrent engineering environment, where even the designer needs information from the CAD/CAM systems, such time-consuming processes can be expensive. To alleviate this problem, a neural network system can be used to estimate machining time by predicting cost-dependent variables such as tool path length for the pocket milling operation. Pockets are characterized and classified into various groups. A randomized design is described so that the training samples that have been chosen represent the domain evenly. An appropriate network was built and trained with the sample pocket geometries. The analysis of the performance of the system in terms of tool path length prediction for new pocket geometries is presented.     

Evolutionary optimization of a geometrically refined truss

Structural optimization is a field of research that has experienced noteworthy growth for many years. Researchers in this area have developed optimization tools to successfully design and model structures, typically minimizing mass while maintaining certain deflection and stress constraints. Numerous optimization studies have been performed to minimize mass, deflection, and stress on a benchmark cantilever truss problem. Predominantly, traditional optimization theory is applied to this problem. The cross-sectional area of each member is optimized to minimize the aforementioned objectives. This paper will present a structural optimization technique that has been previously applied to compliant mechanism design. This technique demonstrates a method that combines topology optimization, geometric refinement, finite element analysis, and two forms of evolutionary computation—genetic algorithms and differential evolution—to successfully optimize a benchmark structural optimization problem. A nontraditional solution to the benchmark problem is presented in this paper, specifically, a geometrically refined topological solution. The design process begins with an alternate control mesh formulation, multilevel geometric smoothing operation, and an elastostatic structural analysis. The design process is wrapped in an evolutionary computing optimization tool set.     

A fast and accurate computational technique for efficient numerical solution of nonlinear singular boundary value problems

This paper is concerned with design and implementation of a computational technique for the efficient solution of a class of singular boundary value problems. The method is based on a modified homotopy analysis method. The method is illustrated by six examples, two of which arise in chemical engineering: the first problem arises in the study of thermal explosions, while the second problem arises in the study of heat and mass transfer within the porous catalyst particles. Numerical results reveal that our method provides better results as compared to some existing methods. Furthermore, it is a powerful tool for dealing with different types of problems with strong nonlinearity.