Training methods used at Harvey Norman

In today’s highly competitive retail world, identifying the experts, striving for performance and prospering skills are essential components needed to succeed. However, many organisations struggle to bring constructive approaches to work. Retail companies’ big or small, depend upon their sales representatives’ knowledge and skills for making or breaking a deal and whether a customer would return or not. The employees of an organisation can be an asset or a liability and because they are also human, they are bound to have good and bad moods, a possibility of forgetting things and making mistakes. This research was conducted to examine the methods used by Harvey Norman (Hamilton) to train their employees and the effects of training on the employee performance and the company’s output. The researcher used qualitative research methods to collect primary data. The manager and Harvey Norman (Hamilton) sales representatives were interviewed to evaluate the importance and need of the training, the training methods used by the organisation and how they affect employee performance and the brand image. The results depict the significance of correct training techniques and their impact on selling skills, and also the knowledge gained from training by the sales representatives of Harvey Norman and its impact on other necessary activities of a retail business. Information was collected from primary sources that tell about the methods of training being used in Harvey Norman. It was found that even though managers are aware of the significance of the employee training, there are certain changes that can be made to make the training programmes better and more efficient. Therefore, recommendations are given for future modifications in training techniques. Such as, it is important that not just the managers, but employees as well, understand the importance of the training and why is it required. Managers need to identify gaps in what is demanded by the job profile, and where the employees really stand, and how they can fill that gap by giving a proper training about knowledge and techniques. The managers need to identify the learning style of each individual in order to use a correct method of training, and let their employees be creative in using that knowledge and ideas to perform better. Most importantly, the training of the employees of Harvey Norman (Hamilton) has to be a steady process as knowledge and growth comes only with continuous effort

Training Support Vector Machines Using Frank-Wolfe Optimization Methods

Training a Support Vector Machine (SVM) requires the solution of a quadratic programming problem (QP) whose computational complexity becomes prohibitively expensive for large scale datasets. Traditional optimization methods cannot be directly applied in these cases, mainly due to memory restrictions. By adopting a slightly different objective function and under mild conditions on the kernel used within the model, efficient algorithms to train SVMs have been devised under the name of Core Vector Machines (CVMs). This framework exploits the equivalence of the resulting learning problem with the task of building a Minimal Enclosing Ball (MEB) problem in a feature space, where data is implicitly embedded by a kernel function. In this paper, we improve on the CVM approach by proposing two novel methods to build SVMs based on the Frank-Wolfe algorithm, recently revisited as a fast method to approximate the solution of a MEB problem. In contrast to CVMs, our algorithms do not require to compute the solutions of a sequence of increasingly complex QPs and are defined by using only analytic optimization steps. Experiments on a large collection of datasets show that our methods scale better than CVMs in most cases, sometimes at the price of a slightly lower accuracy. As CVMs, the proposed methods can be easily extended to machine learning problems other than binary classification. However, effective classifiers are also obtained using kernels which do not satisfy the condition required by CVMs and can thus be used for a wider set of problems

Training Input-Output Recurrent Neural Networks through Spectral Methods

We consider the problem of training input-output recurrent neural networks (RNN) for sequence labeling tasks. We propose a novel spectral approach for learning the network parameters. It is based on decomposition of the cross-moment tensor between the output and a non-linear transformation of the input, based on score functions. We guarantee consistent learning with polynomial sample and computational complexity under transparent conditions such as non-degeneracy of model parameters, polynomial activations for the neurons, and a Markovian evolution of the input sequence. We also extend our results to Bidirectional RNN which uses both previous and future information to output the label at each time point, and is employed in many NLP tasks such as POS tagging

Telemedicine Training in Undergraduate Medical Education: Mixed-Methods Review.

BACKGROUND: Telemedicine has grown exponentially in the United States over the past few decades, and contemporary trends in the health care environment are serving to fuel this growth into the future. Therefore, medical schools are learning to incorporate telemedicine competencies into the undergraduate medical education of future physicians so that they can more effectively leverage telemedicine technologies for improving the quality of care, increasing patient access, and reducing health care expense. This review articulates the efforts of allopathic-degree-granting medical schools in the United States to characterize and systematize the learnings that have been generated thus far in the domain of telemedicine training in undergraduate medical education. OBJECTIVE: The aim of this review was to collect and outline the current experiences and learnings that have been generated as medical schools have sought to implement telemedicine capacity-building into undergraduate medical education. METHODS: We performed a mixed-methods review, starting with a literature review via Scopus, tracking with Excel, and an email outreach effort utilizing telemedicine curriculum data gathered by the Liaison Committee on Medical Education. This outreach included 70 institutions and yielded 7 interviews, 4 peer-reviewed research papers, 6 online documents, and 3 completed survey responses. RESULTS: There is an emerging, rich international body of learning being generated in the field of telemedicine training in undergraduate medical education. The integration of telemedicine-based lessons, ethics case-studies, clinical rotations, and even teleassessments are being found to offer great value for medical schools and their students. Most medical students find such training to be a valuable component of their preclinical and clinical education for a variety of reasons, which include fostering greater familiarity with telemedicine and increased comfort with applying telemedical approaches in their future careers. CONCLUSIONS: These competencies are increasingly important in tackling the challenges facing health care in the 21st century, and further implementation of telemedicine curricula into undergraduate medical education is highly merited

`Modern` learning methods : rhetoric and reality - further to Sadler-Smith et al

Working in the UK, Sadler-Smith, Down and Lean, in their article &ldquo;&lsquo;Modern&rsquo; learning methods: rhetoric and reality&rdquo;, Personnel Review, Vol. 29 No. 4, 2000, pp. 474-90, have shown that distance learning methods are neither favoured nor perceived as effective by enterprises pursuing training that yields a competitive edge. They have suggested that these methods need to be integrated with other more conventional on-job training methods. This paper, based on Australian research, shows a tension between the requirements of flexible training methods based on distance learning methods, and the characteristics that typify learners and their workplaces. That identified tension is used to suggest how an integration of training methods may be effected in workplaces.<br /

Training methods for facial image comparison: a literature review

This literature review was commissioned to explore the psychological literature relating to facial image comparison with a particular emphasis on whether individuals can be trained to improve performance on this task. Surprisingly few studies have addressed this question directly. As a consequence, this review has been extended to cover training of face recognition and training of different kinds of perceptual comparisons where we are of the opinion that the methodologies or findings of such studies are informative. The majority of studies of face processing have examined face recognition, which relies heavily on memory. This may be memory for a face that was learned recently (e.g. minutes or hours previously) or for a face learned longer ago, perhaps after many exposures (e.g. friends, family members, celebrities). Successful face recognition, irrespective of the type of face, relies on the ability to retrieve the to-berecognised face from long-term memory. This memory is then compared to the physically present image to reach a recognition decision. In contrast, in face matching task two physical representations of a face (live, photographs, movies) are compared and so long-term memory is not involved. Because the comparison is between two present stimuli rather than between a present stimulus and a memory, one might expect that face matching, even if not an easy task, would be easier to do and easier to learn than face recognition. In support of this, there is evidence that judgment tasks where a presented stimulus must be judged by a remembered standard are generally more cognitively demanding than judgments that require comparing two presented stimuli Davies &amp; Parasuraman, 1982; Parasuraman &amp; Davies, 1977; Warm and Dember, 1998). Is there enough overlap between face recognition and matching that it is useful to look at the literature recognition? No study has directly compared face recognition and face matching, so we turn to research in which people decided whether two non-face stimuli were the same or different. In these studies, accuracy of comparison is not always better when the comparator is present than when it is remembered. Further, all perceptual factors that were found to affect comparisons of simultaneously presented objects also affected comparisons of successively presented objects in qualitatively the same way. Those studies involved judgments about colour (Newhall, Burnham &amp; Clark, 1957; Romero, Hita &amp; Del Barco, 1986), and shape (Larsen, McIlhagga &amp; Bundesen, 1999; Lawson, Bülthoff &amp; Dumbell, 2003; Quinlan, 1995). Although one must be cautious in generalising from studies of object processing to studies of face processing (see, e.g., section comparing face processing to object processing), from these kinds of studies there is no evidence to suggest that there are qualitative differences in the perceptual aspects of how recognition and matching are done. As a result, this review will include studies of face recognition skill as well as face matching skill. The distinction between face recognition involving memory and face matching not involving memory is clouded in many recognition studies which require observers to decide which of many presented faces matches a remembered face (e.g., eyewitness studies). And of course there are other forensic face-matching tasks that will require comparison to both presented and remembered comparators (e.g., deciding whether any person in a video showing a crowd is the target person). For this reason, too, we choose to include studies of face recognition as well as face matching in our revie

Strenght training methods and the work of Arthur Jones

This article is not available through ChesterRep. It is available at http://www.asep.org/files/Smith.pdfThis paper reviews research evidence relating to the strength training advice offered by Arthur Jones, founder and retired Chairman of Nautilus Sports/Medical Industries and MedX Corporation. Jones advocated that those interested in improving their muscular size, strength, power and/or endurance should perform one set of each exercise to muscular failure (volitional fatigue), train each muscle group no more than once (or, in some cases, twice) per week, perform each exercise in a slow, controlled manner and perform a moderate number of repetitions (for most people, ~8-12). This advice is very different to the strength training guidelines offered by the National Strength and Conditioning Association, the American College of Sports Medicine and most exercise physiology textbooks. However, in contrast to the lack of scientific support for most of the recommendations made by such bodies and in such books, Jones' training advice is strongly supported by the peer-reviewed scientific literature, a statement that has recently been supported by a review of American College of Sports Medicine resistance training guidelines. Therefore, we strongly recommend Jones' methods to athletes and coaches, as they are time-efficient and optimally efficacious, and note that, given his considerable contribution to the field of strength training, academic recognition of this contribution is long overdue