• Journal of Technologic Dentistry
• /
• v.31 no.3
• /
• pp.67-85
• /
• 2009

This study aims to provide the research for dental technician's stress prevention and management with basic materials by understanding dental technician's psychosocial stress level and examining relevant factors. The subject of this study is 255 dental technologists who work mainly in Seoul Gyeonggi district for a month of April of 2009 and I conducted cross-sectional study through self administered survey. The contents of survey include general feature, occupational feature, health behavior feature. I used Karasek's Job Content Questionnaire, JCQ and Psychosocial well-being index, PWI-SF as means of measurement. To compare the level of dental technician's psychosocial stress, I conducted t-test and ANOVA and I measured the factors that are related with psychosocial stress symptom with step by step multiple regressive analysis. According to the result of Cronbach's a value which is yielded to verify the reliability of means of measurement, the reliability of concept is sufficient. The detailed result of this study is as follows. 1. According to the result of analyzing the stress symptom in accordance with general feature and occupational feature, those dental technologists who are older and not married, graduate from junior college, have lower position, work at university hospital or general hospital show lower stress(p<0.05). There is no difference in the level of psychosocial stress with regard to duty related feature, period of service, daily average working hours, monthly average pay. 2. With regard to health behavior feature, those dental technologists who control weight better and have meal more regularly show lower stress(p<0.05). Those dental technicians who smoke, drink liquid and take a suitable sleep show low stress but the difference does not have significance statistically. 3. With regard to the factors of stress in the workplace, those dental technicians who have lower duty related requirement, have higher duty related control ability, have higher social support, have less instability of employment and have less workload and physical burden show lower stress(p<0.05). 4. According to the result of analyzing the factors that influence dental technologist's stress symptom, social support has the most enormous influence on stress symptom. Unstable employment, regular exercise, regular eating, daily average sleeping hours and technological capacity are also important in this order. According to the result of this study, those dental technicians who have higher social support, less instability of employment, do exercise more regularly, take enough sleep more soundly and have higher technological capacity show lower psychosocial stress symptom. Therefore, to adjust appropriately the dental technician's stress and properly maintain and improve the dental technician's mental health, effective management plan that enables dental technicians to maintain smooth human relationships for dental technicians should be sought. In addition, heath education and health management for dental technicians should be given more thoroughly so that they can establish desirable health behavior in daily life.

• Journal of Internet Computing and Services
• /
• v.20 no.4
• /
• pp.21-27
• /
• 2019

Selection of feature pattern gathered from the observation of the RNA sequencing data (RNA-seq) are not all equally informative for identification of differential expressions: some of them may be noisy, correlated or irrelevant because of redundancy in Big-Data sets. Variable selection of feature pattern aims at differential expressed gene set that is significantly relevant for a special task. This issues are complex and important in many domains, for example. In terms of a computational research field of machine learning, selection of feature pattern has been studied such as Random Forest, K-Nearest and Support Vector Machine (SVM). One of most the well-known machine learning algorithms is SVM, which is classical as well as original. The one of a member of SVM-criterion is Support Vector Machine-Recursive Feature Elimination (SVM-RFE), which have been utilized in our research work. We propose a novel algorithm of the SVM-RFE with Q-learning in reinforcement learning for better variable selection of feature pattern. By comparing our proposed algorithm with the well-known SVM-RFE combining Welch' T in published data, our result can show that the criterion from weight vector of SVM-RFE enhanced by Q-learning has been improved by an off-policy by a more exploratory scheme of Q-learning.

• Journal of the Korea Society of Computer and Information
• /
• v.27 no.4
• /
• pp.27-36
• /
• 2022

In this paper, to improve the conditions of the fish processing site, we propose a method to predict the cutting point of fish according to the target weight using AI machine vision. The proposed method performs image-based preprocessing by first photographing the top and front views of the input fish. Then, RANSAC(RANdom SAmple Consensus) is used to extract the fish contour line, and then 3D external information of the fish is obtained using 3D modeling. Next, machine learning is performed on the extracted three-dimensional feature information and measured weight information to generate a neural network model. Subsequently, the fish is cut at the cutting point predicted by the proposed technique, and then the weight of the cut piece is measured. We compared the measured weight with the target weight and evaluated the performance using evaluation methods such as MAE(Mean Absolute Error) and MRE(Mean Relative Error). The obtained results indicate that an average error rate of less than 3% was achieved in comparison to the target weight. The proposed technique is expected to contribute greatly to the development of the fishery industry in the future by being linked to the automation system.

• Proceedings of the KIPE Conference
• /
• 2000.07a
• /
• pp.535-538
• /
• 2000

There are several electricity applied sterilizers such as sterilizer with high frequency sterilizer with ozone sterilizer with high voltage and so on Those sterilizers feature "because there is no chemical process there is no secondly environmental pollution" At the power conversion part ZVS and ZCS methods have been used that it results in reduced switching loss miniaturized size and lightened weight, Besides the current in the device is smaller than that of existing method. Thus it is expected that the cost of sterilization process when quality of the device is measured by power consumption will be reduced.e reduced.

• Nuclear Engineering and Technology
• /
• v.42 no.3
• /
• pp.271-278
• /
• 2010

While the deterministic lattice physics/depletion codes use leakage-corrected critical spectrum (although approximate due to the B1 buckling search employed), Monte Carlo depletion codes currently in use do not have such a feature in spite of their heterogeneity and continuous-energy modeling capability. This paper describes an approach to Monte Carlo depletion with leakage-corrected critical spectrum derived from first principles. This is based on the concept of albedo eigenvalue treated as weight of the reflected neutron in Monte Carlo simulation.

• Proceedings of the Safety Management and Science Conference
• /
• 2006.11a
• /
• pp.85-89
• /
• 2006

The main objective of this study is to propose numerical guideline for the improvement of educational environment about high school girls. In order to analyze feature of the somatotype of the high school girls, analysis of this study was performed about 25 body parts such as height(7 parts), width(4 parts), thickness(4 parts), circumference(5 parts), length(4 parts), and body weight. For the specific comparison on body dementions, Mollison's comparison graph were used.

• Proceedings of the IEEK Conference
• /
• 2001.06e
• /
• pp.237-240
• /
• 2001

There are several electricity applied sterilizers such as sterilizer with high frequency, sterilizer with ozone, sterilizer with high voltage, and so on. Those sterilizers feature “because there is no chemical process, there is no secondly environmental pollution” At the power conversion part, AVS and ZCS methods have been used that it results in reduced switching loss, miniaturized size, and lightened weight. Besides, the current in the device is smaller than that of existing method. Thus, it is expected that the cost of sterilization process, when quality of the device is measured by power consumption, will be reduced.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.57 no.4
• /
• pp.715-717
• /
• 2008

The connectivity weighted Hough transform is a useful method for detecting well-connected short lines without generating false lines yet requires extensive computation. This letter describes a method that reduces the computation of the connectivity weighted Hough transform by removing unnecessary weight calculations using the gradient angles of feature points. In simulations with synthetic images and experiments with liquid crystal display panel images, the proposed method showed significantly improved speed without compromising detectability.

• Journal of Korea Multimedia Society
• /
• v.18 no.9
• /
• pp.1019-1026
• /
• 2015

In this paper, we propose a new method of eye, face, and lip makeup techniques on the target face image from several makeup examples without losing detail features such as eyelids, eyebrows, hair. After detection of the feature layer for the skin, we applied our makeup techniques to the target face by using a blending technique. We used a cartoon rendering using bilateral filter. In order to smoothly makeup the target face, we created two Gaussian Weight maps for natural skin makeup effects. Our method did not need to perform complex operations, so the makeup results are so natural. Our experimental results show good performances in various makeups.

• Journal of KIISE:Databases
• /
• v.37 no.6
• /
• pp.285-291
• /
• 2010

In this paper, we propose a new paradigm of weighting methods for naive Bayesian learning. We propose more fine-grained weighting methods, called value weighting method, in the context of naive Bayesian learning. While the current weighting methods assign a weight to an attribute, we assign a weight to an attribute value. We develop new methods, using Kullback-Leibler function, for both value weighting and feature weighting in the context of naive Bayesian. The performance of the proposed methods has been compared with the attribute weighting method and general naive bayesian. The proposed method shows better performance in most of the cases.