• Korean Business Review
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• v.5
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• pp.161-183
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• 1992

This paper has an aim to look into whether it is possible for us to make an approach the budgeting control with the theory of human relation. This is only a traditional method and also it is open to criticism. I think modem budgetion control should be debeloped by the contingency theory. As the environment is changing continuously, the budgeting control system which can be adapted for this change should be built up. This paper consists of management control, human relation model method and changes of budgeting control.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.10
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• pp.3230-3255
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• 2022

Causality mining in NLP is a significant area of interest, which benefits in many daily life applications, including decision making, business risk management, question answering, future event prediction, scenario generation, and information retrieval. Mining those causalities was a challenging and open problem for the prior non-statistical and statistical techniques using web sources that required hand-crafted linguistics patterns for feature engineering, which were subject to domain knowledge and required much human effort. Those studies overlooked implicit, ambiguous, and heterogeneous causality and focused on explicit causality mining. In contrast to statistical and non-statistical approaches, we present Bidirectional Encoder Representations from Transformers (BERT) integrated with Multi-level Feature Networks (MFN) for causality recognition, called BERT+MFN for causality recognition in noisy and informal web datasets without human-designed features. In our model, MFN consists of a three-column knowledge-oriented network (TC-KN), bi-LSTM, and Relation Network (RN) that mine causality information at the segment level. BERT captures semantic features at the word level. We perform experiments on Alternative Lexicalization (AltLexes) datasets. The experimental outcomes show that our model outperforms baseline causality and text mining techniques.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1525-1530
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• 2003

In this paper, a model of adaptive individual life support system is proposed from the viewpoint of cybernetics. This model is derived based on the relation between human behavior and human action, static and dynamic in processing speed, and abstract/concrete. In applications, task and information of human which includes in this system analyzed by paying attention to cybernetics. This paper shows a few actual example of modeling by fundamental adaptive individual life support model such as medical diagnosis, health care and education support. Finally as an example, design and implementation are concretely carried out for health care support system. This is also a method to design a information support system which is involved in human.

• Proceedings of the Safety Management and Science Conference
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• 2007.04a
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• pp.113-123
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• 2007

Through so that accident of semiconductor industry deduces unsafe factor of the person center on unsafe behaviour that incident history and questionnaire and I made starting point that extract very important factor. It served as a momentum that make up base that analyzes factors that happen based on factor that extract factor cause classification for the first factor, the second factor and the third factor and presents model of human error. Factor for whole defines factor component for human factor and to cause analysis 1 stage in human factor and step that wish to do access of problem and it do analysis cause of data of 1 step. Also, see significant difference that analyzes interrelation between leading persons about human mistake in semiconductor industry and connect interrelation of mistake by this. Continuously, dictionary road map to human error theoretical background to basis traditional accidental cause model and modern accident cause model and leading persons. I wish to present model and new model in semiconductor industry by backbone that leading persons of existing scholars who present model of existent human error deduce relation. Finally, I wish to deduce backbone of model of pre-suppression about accident leading person of the person center.

• Fashion & Textile Research Journal
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• v.3 no.5
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• pp.415-422
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• 2001

Focusing on working with fashion show as fashion model in South Korea, this study was develop a fashion model typology based on specific model characteristics related demographics and body, job satisfaction/dissatisfaction factors. The survey was done through questionnaire and 194 fashion models were used in the data analysis. The statistical analysis used in this study were frequency, ${\chi}^2$-test, cluster Analysis, MANOVA. ANOVA and Duncan multiple range test. The results of this study were as follows: 1) The majority of sample were as follows: unmarried, college graduate and undergraduate, resident in the Seoul, 20 to 24 yrs old female with 175-177 cm, 52-54 kg, B-W-H (33-24-35 inch). 2) The types of fashion model were classified into 4 types: showing type, lack of professionalism type, matured professionalism type, dissatisfaction with job-environment type. The model segments were profiled on levels of various job related attitude factors, job satisfaction/dissatisfaction, model education, working condition, human relation, regulation discrimination, fashion show stage level, the job of model, body & clothing, and promising job. 3) There were significant differences found between their sex, academic background, guarantee, and in all factors in their job related attitude factors, job satisfaction/dissatisfaction, model education, working condition, human relation, regulation discrimination, fashion show stage level, the job of model, body & clothing, style promising job.

• Annual Conference on Human and Language Technology
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• 2020.10a
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• pp.9-13
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• 2020

관계 추출은 주어진 문장이나 문서에 존재하는 개체들 간의 의미적 관계를 찾아내는 작업을 말한다. 최근 문서 수준 관계 추출 말뭉치인 DocRED가 공개되면서 문서 수준 관계 추출에 대한 연구가 활발히 진행되고 있다. 또한 사전 학습된 Masked Language Model(MLM)이 자연어처리 분야 전체에 영향력을 보이면서 관계 추출에서도 MLM을 사용하는 연구가 진행되고 있다. 그러나 문서 수준의 관계 추출은 문서의 단위가 길기 때문에 Self-attention을 기반으로 하는 MLM을 사용하면 모델의 계산량이 증가하는 문제가 있다. 본 논문은 이 점을 보완하기 위해 관계 추출에 필요한 문장을 선별하는 간단한 전처리 방법을 제안한다. 또한 문서의 길이에 상관없이 관계 추출에 필요한 어휘 정보를 자동으로 습득 할 수 있는 Relation-Context Co-attention 방법을 제안한다. 제안 모델은 DocRED 말뭉치에서 Dev F1 62.01%, Test F1 59.90%로 높은 성능을 보였다.

• Journal of Environmental Health Sciences
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• v.19 no.3
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• pp.46-51
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• 1993

In order to survery the risk of air-borne lead to human, the relation between air-borne lead level and blood lead level was examined by using of the kinetic model and statistical model. The results of this survey were as follows: 1. The pathways of lead intake were food and water, mainly. 2. Though blood lead level of Korean urbanire was higher than that of American or Japanese, it was not so severe as to influence human health. 3. The lead content in food and water was high, and so it is needed to confirm the cause of high content was whether second contamination by air pollution or not.

• Journal of the Korean Home Economics Association
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• v.37 no.12 s.142
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• pp.179-192
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• 1999

Thesedays, Home Economic in Korea is faced with the danger of a discord caused by the outer pressure of reorganization in the process educational reformation. The first purpose of this study was to examine the characteristics of the informatized society and the changes of families lived in the informatized society. The second was to assert to strengthen Home Economics in the informatized society. Ultimately we suggested an integrative and interdisciplinary model about Home Economics from the ecological and informative perspective. This model consist with three parts: Human development(Child studies, Gerontology, & Adolescent studies) and family studies division(Family relation studies, family resource management studies, & Consumer studies) Environmental division(Clothing and Textiles, Food and Nutrition, & Housing) and HEIS(Home Economics Information System). This classification is correspond with the one Human-Behavioral Environment and Human-Constructed Environment of Ecological theory.

• The Journal of Korea Robotics Society
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• v.3 no.1
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• pp.9-15
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• 2008

Unlike robotic systems, humans excel at a variety of tasks by utilizing their intrinsic impedance, force sensation, and tactile contact clues. By examining human strategy in arm impedance control, we may be able to teach robotic manipulators human''s superior motor skills in contact tasks. This paper develops a novel method for estimating and predicting the human joint impedance using the electromyogram(EMG) signals and limb position measurements. The EMG signal is the summation of MUAPs (motor unit action potentials). Determination of the relationship between the EMG signals and joint stiffness is difficult, due to irregularities and uncertainties of the EMG signals. In this research, an artificial neural network(ANN) model was developed to model the relation between the EMG and joint stiffness. The proposed method estimates and predicts the multi joint stiffness without complex calculation and specialized apparatus. The feasibility of the developed model was confirmed by experiments and simulations.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.553-558
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• 1994

In this paper, we present a new approach for the automation of deburring process. An algorithm for teaching skills of a human expert to a robot manipulator is developed. This approach makes use of TSK fuzzy model that can express a highly nonlinear functional relation with small number of rules. Burr features such as height, width, area, cutting area are extracted from image processing by use of the vision system. Cutting depth, repeative number and normal cutting force are chosen as control signals representing actions of the human expert. It is verified that our processed fuzzy model can accurately express the skills of human experts for the deburring process.