Work domain analysis for training-system definition and acquisition

Training-needs analysis is critical for defining and procuring effective training systems. However, traditional approaches to training-needs analysis are not suitable for capturing the demands of highly automated and computerized work domains. In this article, we propose that work domain analysis can identify the functional structure of a work domain that must be captured in a training system, so that workers can be trained to deal with unpredictable contingencies that cannot be handled by computer systems. To illustrate this argument, we outline a work domain analysis of a fighter aircraft that defines its functional structure in terms of its training objectives, measures of performance, basic training functions, physical functionality, and physical context. The functional structure or training needs identified by work domain analysis can then be used as a basis for developing functional specifications for training systems, specifically its design objectives, data collection capabilities, scenario generation capabilities, physical functionality, and physical attributes. Finally, work domain analysis also provides a useful framework for evaluating whether a tendered solution fulfills the training needs of a work domain.

ICICLE: A semantic-based retrieval system for WWW images

In this paper, we present ICICLE (Image ChainNet and Incremental Clustering Engine), a prototype system that we have developed to efficiently and effectively retrieve WWW images based on image semantics. ICICLE has two distinguishing features. First, it employs a novel image representation model called Weight ChainNet to capture the semantics of the image content. A new formula, called list space model, for computing semantic similarities is also introduced. Second, to speed up retrieval, ICICLE employs an incremental clustering mechanism, ICC (Incremental Clustering on ChainNet), to cluster images with similar semantics into the same partition. Each cluster has a summary representative and all clusters' representatives are further summarized into a balanced and full binary tree structure. We conducted an extensive performance study to evaluate ICICLE. Compared with some recently proposed methods, our results show that ICICLE provides better recall and precision. Our clustering technique ICC facilitates speedy retrieval of images without sacrificing recall and precision significantly.

A comparison of computer-based methods for the determination of onset of muscle contraction using electromyography

Little consensus exists in the literature regarding methods for determination of the onset of electromyographic (EMG) activity. The aim of this study was to compare the relative accuracy of a range of computer-based techniques with respect to EMG onset determined visually by an experienced examiner. Twenty-seven methods were compared which varied in terms of EMG processing (low pass filtering at 10, 50 and 500 Hz), threshold value (1, 2 and 3 SD beyond mean of baseline activity) and the number of samples for which the mean must exceed the defined threshold (20, 50 and 100 ms). Three hundred randomly selected trials of a postural task were evaluated using each technique. The visual determination of EMG onset was found to be highly repeatable between days. Linear regression equations were calculated for the values selected by each computer method which indicated that the onset values selected by the majority of the parameter combinations deviated significantly from the visually derived onset values. Several methods accurately selected the time of onset of EMG activity and are recommended for future use. Copyright (C) 1996 Elsevier Science Ireland Ltd.

A coupled knowledge-based expert system for design of liquid-retaining structures

This paper describes a coupled knowledge-based system (KBS) for the design of liquid-retaining structures, which can handle both the symbolic knowledge processing based on engineering heuristics in the preliminary synthesis stage and the extensive numerical crunching involved in the detailed analysis stage. The prototype system is developed by employing blackboard architecture and a commercial shell VISUAL RULE STUDIO. Its present scope covers design of three types of liquid-retaining structures, namely, a rectangular shape with one compartment, a rectangular shape with two compartments and a circular shape. Through custom-built interactive graphical user interfaces, the user is directed throughout the design process, which includes preliminary design, load specification, model generation, finite element analysis, code compliance checking and member sizing optimization. It is also integrated with various relational databases that provide the system with sectional properties, moment and shear coefficients and final member details. This system can act as a consultant to assist novice designers in the design of liquid-retaining structures with increase in efficiency and optimization of design output and automated record keeping. The design of a typical example of the liquid-retaining structure is also illustrated. (C) 2003 Elsevier B.V All rights reserved.

Hydrogen storage of magnesium-based nanocomposites system

Hydrogen storage in traditional metallic hydrides can deliver about 1.5 to 2.0 wt pct hydrogen but magnesium hydrides can achieve more than 7 wt pct. However, these systems suffer from high temperature release drawback and chemical instability problems. Recently, big improvements of reducing temperature and increasing kinetics of hydrogenation have been made in nanostructured Mg-based composites. This paper aims to provide an overview of the science and engineering of Mg materials and their nanosized composites with nanostructured carbon for hydrogen storage. The needs in research including preparation of the materials, processing and characterisation and basic mechanisms will be explored. The preliminary experimental results indicated a promising future for chemically stable hydrogen storage using carbon nanotubes modified metal hydrides under lower temperatures.

An Internet-based telerehabilitation system for the assessment of motor speech disorders: A pilot study

Purpose: This pilot study explored the feasibility and effectiveness of an Internet-based telerehabilitation application for the assessment of motor speech disorders in adults with acquired neurological impairment. Method: Using a counterbalanced, repeated measures research design, 2 speech-language pathologists assessed 19 speakers with dysarthria on a battery of perceptual assessments. The assessments included a 19-item version of the Frenchay Dysarthria Assessment (FDA; P. Enderby, 1983), the Assessment of Intelligibility of Dysarthric Speech (K. M. Yorkston & D. R. Beukelman, 1981), perceptual analysis of a speech sample, and an overall rating of severity of the dysarthria. One assessment was conducted in the traditional face-to-face manner, whereas the other assessment was conducted using an online, custom-built telerehabilitation application. This application enabled real-time videoconferencing at 128 kb/s and the transfer of store-and-forward audio and video data between the speaker and speech-language pathologist sites. The assessment methods were compared using the J.M.Bland and D.G.Altman (1986, 1999) limits-of-agreement method and percentage level of agreement between the 2 methods. Results: Measurements of severity of dysarthria, percentage intelligibility in sentences, and most perceptual ratings made in the telerehabilitation environment were found to fall within the clinically acceptable criteria. However, several ratings on the FDA were not comparable between the environments, and explanations for these results were explored. Conclusions: The online assessment of motor speech disorders using an Internet-based telerehabilitation system is feasible. This study suggests that with additional refinement of the technology and assessment protocols, reliable assessment of motor speech disorders over the Internet is possible. Future research methods are outlined.

An analysis of the images attached to referral messages in an e-mail based telemedicine system for developing countries

Little is known about the quality of the images transmitted in email telemedicine systems. The present study was designed to survey the quality of images transmitted in the Swinfen Charitable Trust email referral system. Telemedicine cases were examined for a 3 month period in 2002 and a 3 month period in 2006. The number of cases with images attached increased from 8 (38%) to 37 (53%). There were four types of images (clinical photographs, microscope pictures, notes and X-ray images) and the proportion of radiology images increased from 27 to 48%. The cases in 2002 came from four different hospitals and were associated with seven different clinical specialties. In 2006, the cases came from 19 different hospitals and 20 different specialties. The 46 cases (from both study periods) had a total of 159 attached images. The quality of the images was assessed by awarding each image a score in four categories: focus, anatomical perspective, composition and lighting. The images were scored on a five-point scale (1 = very poor to 5 =very good) by a qualified medical photographer. In comparing image quality between the two study periods, there was some evidence that the quality had reduced, although the average size of the attached images had increased. The median score for all images in 2002 was 16 (interquartile range 14-19) and the median score in 2006 was 15 (13-16). The difference was significant (P < 0.001, Mann-Whitney test).

Successes and failures in assessing acquired language disorders using an Internet-based telerehabilitation system

We have used a telerehabilitation system (eREHAB) to remotely assess acquired language disorders via the Internet. The system was used to establish a 128 kbit/s videoconference between two sites and allowed a remote language assessment to be conducted using the standardized Boston Diagnostic Aphasia Examination (BDAE). The system had the capacity to display text and images, and could play pre-recorded instructions to the participant via various built-in tools. A touch screen allowed tasks involving picture identification to be completed easily. Eighteen participants with a diagnosis of an acquired language disorder were simultaneously assessed using the eREHAB system, and in the traditional face-to-face manner by two speech pathologists. There was very high agreement between the two assessors, with weighted kappa scores of 0.8–1.0 for 88% of the sub-tests of the BDAE. There was also high agreement (80–100%) and high kappa scores (0.67–0.90) between assessors on the six rating scales relating to language characteristics. The agreement between the two assessors for the diagnosis of the type of aphasia was 83%. Limitations of the system related mainly to problems inherent in IP videoconferencing. The inability to maintain the preferred speed of 128 kbit/s for the duration of the videoconference and the resultant increase in video and audio breakup and latency affected the clinician’s ability to administer the BDAE with the same ease and accuracy as in face-to-face administration. These difficulties were exacerbated when participants presented with a moderate to severe language disorder, auditory comprehension deficits or significant hearing loss. Despite these limitations, a valid assessment of language disorder was found to be feasible via this telerehabilitation application.

Intelligent agent supported personalization for virtual learning environments

Virtual learning environments (VLEs) are computer-based online learning environments, which provide opportunities for online learners to learn at the time and location of their choosing, whilst allowing interactions and encounters with other online learners, as well as affording access to a wide range of resources. They have the capability of reaching learners in remote areas around the country or across country boundaries at very low cost. Personalized VLEs are those VLEs that provide a set of personalization functionalities, such as personalizing learning plans, learning materials, tests, and are capable of initializing the interaction with learners by providing advice, necessary instant messages, etc., to online learners. One of the major challenges involved in developing personalized VLEs is to achieve effective personalization functionalities, such as personalized content management, learner model, learner plan and adaptive instant interaction. Autonomous intelligent agents provide an important technology for accomplishing personalization in VLEs. A number of agents work collaboratively to enable personalization by recognizing an individual's eLeaming pace and reacting correspondingly. In this research, a personalization model has been developed that demonstrates dynamic eLearning processes; secondly, this study proposes an architecture for PVLE by using intelligent decision-making agents' autonomous, pre-active and proactive behaviors. A prototype system has been developed to demonstrate the implementation of this architecture. Furthemore, a field experiment has been conducted to investigate the performance of the prototype by comparing PVLE eLearning effectiveness with a non-personalized VLE. Data regarding participants' final exam scores were collected and analyzed. The results indicate that intelligent agent technology can be employed to achieve personalization in VLEs, and as a consequence to improve eLeaming effectiveness dramatically.