Computer-simulated environment for training : challenge of efficacy evaluation

Computer-assisted instruction has been around for decades. There has been much speculation about the benefits of computer-mediated learning. Numerous applications have been developed in different domains incorporated with emerging technologies. In recently years, advanced technologies, such as Augmented Reality (AR) and Virtual Reality (VR), have received much attention in their potential of creating interactive learning experience for the users. However, related literature and empirical studies indicated that learning effects in computer-simulated environments or Virtual Environments (VEs) are not systematically tested. Furthermore, the performance and learning in computer-simulated learning environment need to be evaluated through more rigorous methods. This paper suggests that 1) the efficacy of VEs is subject to a close examination, not only in terms of how VE-based training systems are easy of use, but also in terms of how effective learning is; 2) evaluation of learning in computer simulated learning environments is required to be reconsidered in terms of theoretical basis and evaluation methodologies that are relevant to the measurement of training effectiveness in computer-simulated virtual learning environment. This paper explains on how learning can be assessed in VEs through the lens of training evaluation.

Social-spider optimization-based artificial neural networks training and its applications for Parkinson's disease identification

Evolutionary algorithms have been widely used for Artificial Neural Networks (ANN) training, being the idea to update the neurons' weights using social dynamics of living organisms in order to decrease the classification error. In this paper, we have introduced Social-Spider Optimization to improve the training phase of ANN with Multilayer perceptrons, and we validated the proposed approach in the context of Parkinson's Disease recognition. The experimental section has been carried out against with five other well-known meta-heuristics techniques, and it has shown SSO can be a suitable approach for ANN-MLP training step.

Creating Partnerships: Computer Training with Assistive Technology for Senior Adults

Currently, at the SC Commission for the Blind, there is no opportunity for computer training for adults in the Older Blind Program. The Older Blind Program has to look for outside partners to make this service viable again. This project proposes that the OB Program partner with regional senior and recreation centers to establish a community-based training program that is both effective and is of minimal cost to the agency and to the partnering centers.

Transitional employment aspirations for bridging retirement : implications for training and development

Purpose: The aim of this study was to identify the transitional employment aspirations and training and development needs of older and younger workers at risk of early retirement due to limited education and/or employment in blue collar occupations. Design/ Methodology/ Approach: A computer based methodology was used to evaluate the demographic effects of gender, education level and occupation group on aspirations pertaining to transitional employment and training and development in a sample of over 1000 Local Government employees. Findings: Older blue collar, secondary school educated and younger workers were less interested in transitional employment than older workers with higher levels of education or from white collar backgrounds. The early retirement risk factors of blue collar work and secondary school education had a more limited effect on perceived training and development needs for older workers. However for younger workers, these risk factors provided the impetus to undertake training to move into less physically demanding or more challenging roles as their careers progressed. Practical Implications: Via the identification of education level and occupation types groups’ transitional employment aspirations and perceptions of preparatory training and development within younger and older cohorts, long term strategies to develop and retain staff may be formulated. Originality/ Value: Past studies of transitional employment have rarely included younger workers or older workers at risk of early retirement. Preparatory training and development for transitional employment roles has not been considered in the literature.

Video-based road commentary training improves hazard perception of young drivers in a dual task

This study used a video-based hazard perception dual task to compare the hazard perception skills of young drivers with middle aged, more experienced drivers and to determine if these skills can be improved with video-based road commentary training. The primary task required the participants to detect and verbally identify immediate hazard on video-based traffic scenarios while concurrently performing a secondary tracking task, simulating the steering of real driving. The results showed that the young drivers perceived fewer immediate hazards (mean = 75.2%, n = 24, 19 females) than the more experienced drivers (mean = 87.5%, n = 8, all females), and had longer hazard perception times, but performed better in the secondary tracking task. After the road commentary training, the mean percentage of hazards detected and identified by the young drivers improved to the level of the experienced drivers and was significantly higher than that of an age and driving experience matched control group. The results will be discussed in the context of psychological theories of hazard perception and in relation to road commentary as an evidence-based training intervention that seems to improve many aspects of unsafe driving behaviour in young drivers.

Interval training intensity affects energy intake compensation in obese men

Abstract PURPOSE: Compensatory responses may attenuate the effectiveness of exercise training in weight management. The aim of this study was to compare the effect of moderate- and high-intensity interval training on eating behavior compensation. METHODS: Using a crossover design, 10 overweight and obese men participated in 4-week moderate (MIIT) and high (HIIT) intensity interval training. MIIT consisted of 5-min cycling stages at ± 20% of mechanical work at 45%VO(2)peak, and HIIT consisted of alternate 30-s work at 90%VO(2)peak and 30-s rests, for 30 to 45 min. Assessments included a constant-load exercise test at 45%VO(2)peak for 45 min followed by 60-min recovery. Appetite sensations were measured during the exercise test using a Visual Analog Scale. Food preferences (liking and wanting) were assessed using a computer-based paradigm, and this paradigm uses 20 photographic food stimuli varying along two dimensions, fat (high or low) and taste (sweet or nonsweet). An ad libitum test meal was provided after the constant-load exercise test. RESULTS: Exercise-induced hunger and desire to eat decreased after HIIT, and the difference between MIIT and HIIT in desire to eat approached significance (p = .07). Exercise-induced liking for high-fat nonsweet food tended to increase after MIIT and decreased after HIIT (p = .09). Fat intake decreased by 16% after HIIT, and increased by 38% after MIIT, with the difference between MIIT and HIIT approaching significance (p = .07). CONCLUSIONS: This study provides evidence that energy intake compensation differs between MIIT and HIIT.

Cluster based core vector machine

Core Vector Machine(CVM) is suitable for efficient large-scale pattern classification. In this paper, a method for improving the performance of CVM with Gaussian kernel function irrespective of the orderings of patterns belonging to different classes within the data set is proposed. This method employs a selective sampling based training of CVM using a novel kernel based scalable hierarchical clustering algorithm. Empirical studies made on synthetic and real world data sets show that the proposed strategy performs well on large data sets.

A Low-Complexity Algorithm for Intrusion Detection in a PIR-Based Wireless Sensor Network

We present a low-complexity algorithm for intrusion detection in the presence of clutter arising from wind-blown vegetation, using Passive Infra-Red (PIR) sensors in a Wireless Sensor Network (WSN). The algorithm is based on a combination of Haar Transform (HT) and Support-Vector-Machine (SVM) based training and was field tested in a network setting comprising of 15-20 sensing nodes. Also contained in this paper is a closed-form expression for the signal generated by an intruder moving at a constant velocity. It is shown how this expression can be exploited to determine the direction of motion information and the velocity of the intruder from the signals of three well-positioned sensors.

The airEXODUS evacuation model and its application to evacuation certification, crew training and accident investigation.

Computer based mathematical models describing the aircraft evacuation process have a vital role to play in the design and development of safer aircraft, in the implementation of safer and more rigorous certification criteria, cabin crew training and in post mortuum accident investigation. As the risk of personal injury and costs involved in performing large-scale evacuation experiments for the next generation 'Ultra High Capacity Aircraft' (UHCA) are expected to be high, the development and use of these evacuation modelling tools may become essential if these aircraft are to prove a viable reality. In this paper the capabilities and limitations of the airEXODUS evacuation model are described. Its successful application to the prediction of a recent certification trial, prior to the actual trial taking place, is described. Also described is a newly defined parameter known as OPS which can be used as a measure of evacuation trial optimality. In addition, sample evacuation simulations in the presence of fire atmospheres are described. Finally, the data requiremnets of the airEXODUS evacuation model is discussed along with several projects currently underway at the the Univesity of Greenwich designed to obtain this data. Included in this discussion is a description of the AASK - Aircraft Accident Statistics and Knowledge - data base which contains detailed information from aircraft accident survivors.

IT and other training in the always connected era

Abstract Google and YouTube are quickly becoming the training resource of choice for the IT literate, especially in relation to computer based applications. Many businesses are addressing this training issue in a number of ways, some more successful than others. Find out what the IT services at the university are doing to adapt to this change and contribute to the discussion on how the approach could be improved. Before the talk you could have a look at the following; * One service that has been licenced is Lynda http://go.soton.ac.uk/lynda or lynda.com (note you have to enter www.southampton.ac.uk as the organisation if you don’t log in through the go.soton link) * The IT training team publish a portfolio of systems and courses at http://www.southampton.ac.uk/isolutions/computing/training/portfolio/index.php. * More and more internal systems are being supported through online guides such as http://go.soton.ac.uk/bgsg

Home-based resistance training is not sufficient to maintain improved glycemic control following supervised training in older individuals with type 2 diabetes

OBJECTIVE—To examine whether improvements in glycemic control and body composition resulting from 6 months of supervised high-intensity progressive resistance training could be maintained after an additional 6 months of home-based resistance training.

RESEARCH DESIGN AND METHODS—We performed a 12-month randomized controlled trial in 36 sedentary, overweight men and women with type 2 diabetes (aged 60–80 years) who were randomly assigned to moderate weight loss plus high-intensity progressive resistance training (RT&WL group) or moderate weight loss plus a control program (WL group). Supervised gymnasium-based training for 6 months was followed by an additional 6 months of home-based training. Glycemic control (HbA_1c), body composition, muscle strength, and metabolic syndrome abnormalities were assessed at 0, 3, 6, 9, and 12 months.

RESULTS—Compared with the WL group, HbA_1c decreased significantly more in the RT&WL group (–0.8%) during 6 months of supervised gymnasium-based training; however, this effect was not maintained after an additional 6 months of home-based training. In contrast, the greater increase in lean body mass (LBM) observed in the RT&WL group compared with the WL group (0.9 kg, P < 0.05) after the gymnasium-based training tended to be maintained after the home-based training (0.8 kg, P = 0.08). Similarly, the gymnasium-based increases in upper body and lower body muscle strength in the RT&WL group were maintained over the 12 months (P < 0.001). There were no between-group differences for changes in body weight, fat mass, fasting glucose, or insulin at 6 or 12 months.

CONCLUSIONS—In older adults with type 2 diabetes, home-based progressive resistance training was effective for maintaining the gymnasium-based improvements in muscle strength and LBM but not glycemic control. Reductions in adherence and exercise training volume and intensity seem to impede the effectiveness of home-based training for maintaining improved glycemic control.

Haptically enable interactive virtual assembly training system development and evaluation

Virtual training systems are attracting paramount attention from the manufacturing industries due to their potential advantages over the conventional training practices. Significant cost savings can be realized due to the shorter times for the development of different training-scenarios as well as reuse of existing designed engineering (math) models. In addition, use of computer based virtual reality (VR) training systems can shorten the time span from computer aided product design to commercial production due to non-reliance on the hardware parts for training. Within the aforementioned conceptual framework, a haptically enabled interactive and immersive virtual reality (HIVEx) system is presented. Unlike existing VR systems, the presented idea tries to imitate real physical training scenarios by providing comprehensive user interaction, constrained within the physical limitations of the real world. These physical constrains are imposed by the haptics devices in the virtual environment. As a result, in contrast to the existing VR systems that are capable of providing knowledge generally about assembly sequences only, the proposed system helps in cognitive learning and procedural skill development as well, due to its high physically interactive nature.

An interval type-2 fuzzy logic system-based method for prediction interval construction

This paper introduces a new non-parametric method for uncertainty quantification through construction of prediction intervals (PIs). The method takes the left and right end points of the type-reduced set of an interval type-2 fuzzy logic system (IT2FLS) model as the lower and upper bounds of a PI. No assumption is made in regard to the data distribution, behaviour, and patterns when developing intervals. A training method is proposed to link the confidence level (CL) concept of PIs to the intervals generated by IT2FLS models. The new PI-based training algorithm not only ensures that PIs constructed using IT2FLS models satisfy the CL requirements, but also reduces widths of PIs and generates practically informative PIs. Proper adjustment of parameters of IT2FLSs is performed through the minimization of a PI-based objective function. A metaheuristic method is applied for minimization of the non-linear non-differentiable cost function. Performance of the proposed method is examined for seven synthetic and real world benchmark case studies with homogenous and heterogeneous noise. The demonstrated results indicate that the proposed method is capable of generating high quality PIs. Comparative studies also show that the performance of the proposed method is equal to or better than traditional neural network-based methods for construction of PIs in more than 90% of cases. The superiority is more evident for the case of data with a heterogeneous noise. © 2014 Elsevier B.V.

Evaluation of a comprehensive interactive training system for investigative interviewers of children

This article reports on the evaluation of an interactive interviewer training system with a large, heterogeneous sample of investigative interviewers of children. The system, delivered predominantly through computer-assisted learning activities, focused on how to elicit important evidential details from child witnesses in a narrative format. Two studies are reported, each adopting a pre-versus posttraining design. Study 1 examined the effect of the training on trainees' (N = 92) performance, using mock interviews where an actor played the role of the child in a highly controlled manner. Study 2 examined the effect of the training on field interviews (N = 156) conducted prior to and after the training. Five measures were analyzed: (a) proportion of interviewer question types, (b) proportion of desirable interviewer behaviors, (c) adherence to the interview protocol, (d) interview length, and (e) the quality of evidential information sought. Overall, the findings provide clear support for the utility of the training system. Irrespective of the type of interview or measure, adherence to best-practice interviewing increased from pre- to posttraining, with some evidence supporting sustained performance 12 months after there had been no intervening training or supervision. The implication is that there is now an evidence-based alternative to the traditional classroom-based training system for investigative interviewers. Suggestions for future research are also discussed.

Simulation-based cutaneous surgical-skill training on a chicken-skin bench model in a medical undergraduate program

Background: Because of ethical and medico-legal aspects involved in the training of cutaneous surgical skills on living patients, human cadavers and living animals, it is necessary the search for alternative and effective forms of training simulation. Aims: To propose and describe an alternative methodology for teaching and learning the principles of cutaneous surgery in a medical undergraduate program by using a chicken-skin bench model. Materials and Methods: One instructor for every four students, teaching materials on cutaneous surgical skills, chicken trunks, wings, or thighs, a rigid platform support, needled threads, needle holders, surgical blades with scalpel handles, rat-tooth tweezers, scissors, and marking pens were necessary for training simulation. Results: A proposal for simulation-based training on incision, suture, biopsy, and on reconstruction techniques using a chicken-skin bench model distributed in several sessions and with increasing levels of difficultywas structured. Both feedback and objective evaluations always directed to individual students were also outlined. Conclusion: The teaching of a methodology for the principles of cutaneous surgery using a chicken-skin bench model versatile, portable, easy to assemble, and inexpensive is an alternative and complementary option to the armamentarium of methods based on other bench models described. © Indian Journal of Dermatology 2013.