• Journal of the Korean Society of Marine Environment & Safety
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• v.23 no.3
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• pp.294-300
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• 2017

In this study, a survey was conducted among students who received ARPA/radar simulation training in order to verify the effect of training. An effective training method based on the analysis results was also proposed. Furthermore, this study analyzed full mission simulation conducted over one semester, and found that training effect increased as time passed. The survey showed improvement in skills related to radar/ARPA utilization, ARPA decoding, ship handling, and overall skill. Students responded practical skills improved more than theoretical knowledge, and also analysis showed that ship handling skills had a larger effect than radar decoding skills on improving overall skill, therefore proposed that theoretical education regarding the functions of radar and ARPA should be reinforced in ARPA/radar simulation training.

• Journal of Industrial Technology
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• v.31 no.A
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• pp.63-69
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• 2011

A home-based rehabilitation system for patients with uncomfortable hands or arms was developed. By using this system, patients can save time and money of going to the hospital. The system's interface is easy to manipulate. In this paper, we discuss a rehabilitation system using video recognition; the focus is on designing a convenient user interface and rehabilitation training methods. The system consists of two screens: one for recording user's information and the other for training. A first-time user inputs his/her information. The system chooses the training method based on the information and records the training process automatically using video recognition. On the training screen, video clips of the training method and help messages are displayed for the user.

• PNF and Movement
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• v.11 no.1
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• pp.17-25
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• 2013

Purpose : To identify importance of coordinative locomotor training, we reviewed the coordinative locomotor training using sprinter & skater with respect to motor control theory. Methods : We reviewed literatures related with sprinter & skater and coordination.. Results : The coordinative locomotor training is useful tool to improve interlimb coordination. A problem of interlimb coordination ability is to minimize the degree of freedoms during walking and to solve with context-condition variability and how to make a interlimb coordinative structures. A way of solving method is coordinative locomotor training using sprinter & skater in PNF. The coordinative locomotor training set to fit the gait steps can be applied with gait tasks and can be extended by applying the irradiation of the PNF. Conclusion : The coordinative locomotor training using sprinter & skater in PNF is a useful way method to improve interlimb coordination during walking.

• Journal of the Society of Disaster Information
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• v.15 no.3
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• pp.347-357
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• 2019

Purpose: The purpose of this paper is to present a method for effectively conducting discussion-based training in disaster response safety training. Method: To this end, we analyzed the disaster response training of developed countries and suggested the training scenarios by applying the war-game process that is currently applied in the operation planning of our military. Result: In one disaster situation, several contingencies could be identified, and supplementary requirements for the manual could be derived. Conclusion: Therefore, in conclusion, if the military war-game process is applied to the discussion-based training in disaster response safety training, effective training can be carried out.

• ETRI Journal
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• v.41 no.2
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• pp.242-253
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• 2019

We devise a layer-wise hint training method to improve the existing hint-based knowledge distillation (KD) training approach, which is employed for knowledge transfer in a teacher-student framework using a residual network (ResNet). To achieve this objective, the proposed method first iteratively trains the student ResNet and incrementally employs hint-based information extracted from the pretrained teacher ResNet containing several hint and guided layers. Next, typical softening factor-based KD training is performed using the previously estimated hint-based information. We compare the recognition accuracy of the proposed approach with that of KD training without hints, hint-based KD training, and ResNet-based layer-wise pretraining using reliable datasets, including CIFAR-10, CIFAR-100, and MNIST. When using the selected multiple hint-based information items and their layer-wise transfer in the proposed method, the trained student ResNet more accurately reflects the pretrained teacher ResNet's rich information than the baseline training methods, for all the benchmark datasets we consider in this study.

• Journal of The Korean Society of Integrative Medicine
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• v.4 no.2
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• pp.77-88
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• 2016

Purpose : The purpose of this study was to explore an effect exerted to non-affected hand and affected hand of patients by performing training of chopsticks and grasp strength that are helpful to dexterity and grasp strength of hand together with training method of joint exercise, muscle strength build-up training, delicate hand function training. Method : By targeting 30 normal adult male/females engaged in K university, Busan for one month on April, 2015, 10 persons of hand function build-up training group, that of dexterity training group and 10 persons of control group were randomly selected. For hand function build-up training group, chopsticks training in parallel with total 20 times of grasp strength training for 4 weeks including 5 minutes of dominant hand grasp strength training, 5 minutes of non-dominant hand grasp strength training, 15 minutes of chopsticks training was performed based on 25 minutes/one time, 5 times a week. Result : First, In a comparison of dexterity of both hands by each group depending on training period, hand function build-up group and dexterity training group were represented to be effective compared with control group. Secondly, In a comparison of manipulatory ability of both hands by each group depending on training period, hand function build-up group and dexterity training group were represented to be effective compared with control group. Conclusion : It is considered that diversified and broad research covering patients with musculoskeletal disease and nervous system-related disease would be performed by securing far more test subjects after comparing a correlation between dexterity training and hand function training.

• The Journal of Industrial Distribution & Business
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• v.15 no.8
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• pp.13-20
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• 2024

Purpose: The purpose of this study is to analyse the effectiveness of training and development on the performance of employees in Zimbabwe's banks using FBC Bank as a case study. Research design, data and methodology: The study adopted a mixed research method to collect and analyse data from ten key informants and fifty FBC Bank employees drawn from its branches in Harare. The data collection method used were survey and interviews. Results: The study revealed that effective training and development is significant to FBC Bank because it has a positive effect on the performance of employees, which consequently result in improved organisational performance. Conclusion: The study concluded that knowledge on how to conduct effective training and development programs in FBC Bank is not optimum. Recommendations: The study recommended that management should acknowledge that training and development is a systematic process and therefore conduct training needs analysis, design training plans, implement training programs effectively and evaluate them in order to ensure well-coordinated and effective training and development programs. It also suggested that adequate budget allocation should be availed to finance the implementation of training and development programs in organisations.

• The Journal of the Acoustical Society of Korea
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• v.16 no.2
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• pp.58-65
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• 1997

A new automatic classification method with high and stable accuracy for time-series image data is presented in this paper. This method is based on prior condition that a classified map of the target area already exists, or at least one of the time-series image data had been classified. The classified map is used as a reference map to specify training areas of classification categories. The new automatic classification method consists of five steps, i.e., extraction of training data using reference map, detection of changed pixels based upon the homogeneity of training data, clustering of changed pixels, reconstruction of training data, and classification as like maximum likelihood classifier. In order to evaluate the performance of this method qualitatively, four time-series Landsat TM image data were classified by using this method and a conventional method which needs a skilled operator. As a results, we could get classified maps with high reliability and fast throughput, without a skilled operator.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2001.10a
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• pp.59-64
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• 2001

The objectives of the thesis are to propose a pattern classification method for remote sensing data using artificial neural network. First, we apply the error back propagation algorithm to classify the remote sensing data. In this case, the classification performance depends on a training data set. Using the training data set and the error back propagation algorithm, a layered neural network is trained such that the training pattern are classified with a specified accuracy. After training the neural network, some pixels are deleted from the original training data set if they are incorrectly classified and a new training data set is built up. Once training is complete, a testing data set is classified by using the trained neural network. The classification results of Landsat TM data show that this approach produces excellent results which are more realistic and noiseless compared with a conventional Bayesian method.

• Journal of KIISE:Software and Applications
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• v.31 no.7
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• pp.859-868
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• 2004

We propose a method of selecting initial training examples for active learning so that it can reach high accuracy faster with fewer further queries. Our method is based on the assumption that an active learner can reach higher performance when given an initial training set consisting of diverse and typical examples rather than similar and special ones. To obtain a good initial training set, we first cluster examples by using k-means clustering algorithm to find groups of similar examples. Then, a representative example, which is the closest example to the cluster's centroid, is selected from each cluster. After these representative examples are labeled by querying to the user for their categories, they can be used as initial training examples. We also suggest a method of using the centroids as initial training examples by labeling them with categories of corresponding representative examples. Experiments with various text data sets have shown that the active learner starting from the initial training set selected by our method reaches higher accuracy faster than that starting from randomly generated initial training set.