• Nutritional Sciences
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• v.9 no.2
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• pp.131-138
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• 2006

The primary purpose of this study was to investigate the job characteristics and competencies of a head-cook in contracted foodservice management company, identify the knowledge, abilities, skills and other characteristics (KASO) required to perform the duties of a head-cook, and provide training content and develop training program for job of head-cook in contract foodservice management company (CFMC). A survey instrument including identified KASO was used in the study. The questionnaire was delivered by using e-mail to 165 head-cooks employed by CFMC. The factor analysis resulted in a three-factor structure of the instrument such as 'basic foodservice operation duties' 'personal characteristics' 'managing of expanded duties-menu, customer and business'. This result suggested the education and training program for head-cook in CFMC should be composed of 'basic foodservice operation duties' on 'bulk preparation', 'procurement, inventory management', 'facility and equipment management', and 'sanitation and safety management', 'personal characteristics' on 'personality management' and 'moral duties', and 'managing of expanded duties-menu, customer and business' on 'menu management', 'customer service management', 'cost management', and 'administrative ability'. Therefore, it will be expected that the management of human resources in the contract foodservice industry would be developed by the application of recommended education and training program.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.9B
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• pp.1775-1784
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• 1999

This paper proposes a method of removing unnecessary hidden nodes by a new cost function that evaluates the variance and the mean of hidden node outputs during training. The proposed cost function makes necessary hidden nodes be activated and unnecessary hidden nodes be constants. We can remove the constant hidden nodes without performance degradation. Using the CEDAR handwritten digit recognition, we have shown that the proposed method can remove the number of hidden nodes up to 37.2%, with higher recognition rate and shorter learning time.

• Journal of Korean Academy of Nursing
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• v.34 no.6
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• pp.1117-1128
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• 2004

Purpose: This study was carried out to substantiate the application process of activity-based costing on the current cost of hospital home care (HHC) service. The study materials were documents, 120 client charts, health insurance demand bills, salary of 215 HHC nurses, operating expense, 6 HHC agencies, and 31 HHC nurses. Method: The research was carried out by analyzing the HHC activities and then collecting labor and operating expenses. For resource drivers, HHC activity performance time and workload were studied. For activity drivers, the number of HHC activity performances and the activity number of visits were studied. Result: The HHC activities were classified into 70 activities. In resource, the labor cost was 245￦per minute, operating cost was 9,570￦ per visit and traffic expense was an average of 12,750￦. In resource drivers, education and training had the longest time of 67 minutes. Average length of performance for activities was 13.7 minutes. The workload was applied as a relative value. The average cost of HHC was 62,741￦ and the cost ranged from 55,560￦ to 74,016￦. Conclusion: The fixed base rate for a visit in the current HHC medical fee should be increased. Exclusion from the current fee structure or flexible operation of traveling expenses should be reviewed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.1
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• pp.141-156
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• 2011

In this paper we develop a link cost function for data delivery in sensor network. Usually most conventional methods determine the optimal coefficients in the cost function without considering the surrounding environment of the node such as the wireless propagation environment or the topological environment. Due to this reason, there are limitations to improve the quality of data delivery such as data delivery ratio and delay of data delivery. To solve this problem, we derive a new cost function using the concept of Partially Connected Neural Network (PCNN) which is modeled according to the input types whether inputs are correlated or uncorrelated. The correlated inputs are connected to the hidden layer of the PCNN in a coupled fashion but the uncoupled inputs are in an uncoupled fashion. We also propose the training technique for finding an optimal weight vector in the link cost function. The link cost function is trained to the direction that the packet transmission success ratio of each node maximizes. In the experimental section, we show that our method outperforms other conventional methods in terms of the quality of data delivery and the energy efficiency.

• Communications for Statistical Applications and Methods
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• v.10 no.2
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• pp.595-601
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• 2003

In this paper we propose an on line training method for classification based on least squares support vector machine. Proposed method enables the computation cost to be reduced and the training to be peformed incrementally, With the incremental formulation of an inverse matrix in optimization problem, current information and new input data can be used for building the new inverse matrix for the estimation of the optimal bias and Lagrange multipliers, so the large scale matrix inversion operation can be avoided. Numerical examples are included which indicate the performance of proposed algorithm.

• Proceedings of the KWS Conference
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• 2002.10a
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• pp.430-432
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• 2002

Some confusion in the terminology concerning the weld quality and its assurance seems caused by the different practises currently in use around the world. Qualified welding personnel are not automatically certified personnel. Education and training are the tools to obtain qualification. Flexibility in training and education seems logical and the most cost-effective way to obtain qualified personnel. A third party seems essential for issuing recognised Certificates. Manufacturers of welded products continue to face increased demands and concerns regarding weld quality. The following are the main conditions influencing weld quality: $\bigcirc$ Establishing reliable productions procedures and tests that meet the requirements of established codes and standards. $\bigcirc$ Finding qualified welding personnel capable of reliably carrying out established welding procedures. The issue of hiring and keeping skilled welding personnel has been a crucial consideration for manufacturers worldwide for the past few decades. It will continue to be a concern for decades to come.

• The Korean Journal of Applied Statistics
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• v.17 no.3
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• pp.445-457
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• 2004

Given class-imbalanced data in two-class classification problem, we often do over-sampling and/or under-sampling of training data to make it balanced. We investigate the validity of such practice. Also we study the effect of such sampling practice on boosting of classification trees. Through experiments on twelve real datasets it is observed that keeping the natural distribution of training data is the best way if you plan to apply boosting methods to class-imbalanced data.

• Archives of Reconstructive Microsurgery
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• v.18 no.2
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• pp.75-78
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• 2009

Purpose: Microsurgery is an essential technique in plastic and reconstructive surgery. However, microsurgical suturing and handling of the instrument are difficult for beginners, and who requires a steep learning curve. Therefore, methods for improving the technical skill are needed. The authors describe the value of a small stereoscopic microscope as a training tool. Materials and Methods: A small stereoscopic microscope was used to help improve the microsurgical skill. Monofilament 10-0 Nylon and a surgical rubber globe were used as a suture material and education material, respectively Result: Stereoscopic view of the operation field was obtained and basic microsurgical suture was possible. Conclusion: The stereoscopic microscope is an effective training tool for beginners of microsurgery with benefits in cost and usefulness in small place.

• IE interfaces
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• v.20 no.1
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• pp.41-48
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• 2007

The main purpose of this paper is cost reduction in absurd pilot positive expense and human accident prevention which is caused by in the pilot selection process. We use classification models such as logistic regression, decision tree, and neural network based on aptitude test results of 505 ROK Air Force applicants in 2001~2004. First, we determine the reliability and propriety against the aptitude test system which has been improved. Based on this conference flight simulator test item was compared to the new aptitude test item in order to make additional yes or no decision from different models in terms of classification accuracy, ROC and Response Threshold side. Decision tree was selected as the most efficient for each sequential flight training result and the last flight training results predict excellent. Therefore, we propose that the standard of pilot selection be adopted by the decision tree and it presents in the aptitude test item which is new a conference flight simulator test.

• Journal of Korean Neurosurgical Society
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• v.65 no.4
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• pp.489-498
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• 2022

Spatial insight into intracranial pathology and structure is important for neurosurgeons to perform safe and successful surgeries. Three-dimensional (3D) printing technology in the medical field has made it possible to produce intuitive models that can help with spatial perception. Recent advances in 3D-printed disease models have removed barriers to entering the clinical field and medical market, such as precision and texture reality, speed of production, and cost. The 3D-printed disease model is now ready to be actively applied to daily clinical practice in neurosurgical planning, simulation, and training. In this review, the development of 3D-printed neurosurgical disease models and their application are summarized and discussed.