• 한국생활과학회지
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• 제18권3호
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• pp.769-773
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• 2009

The purpose of this study is to examine the food consumption behavior, the attitudes to food sanitation and the HACCP(?) knowledge of college students. Questionnaires were collected from 130 students in Daejeon University. The subjects mainly purchased their food at big discount stores and thought of expiration date as a most important factor considered. When purchasing the grocery, female students seldom took the convenience cooking into consideration, however, 10.3% of male students concerned it(p<0.05). In subjects' knowledge of food hygiene, the average score was 16.21 and in their performance(p<0.05)of it, the average score was 11.14. Especially in their knowledge of separate food storage, the average point was 5.03 and in their performance of it(p<0.05), the average point was 2.84. 72% of respondents had ever experienced food sanitation education. Of students who answered that food sanitation education was very helpful, the number of students living in university dormitory or boarding houses was as much again as that of students living in their own places. 82.2% of students did not know about HACCP system. They wanted to know 'the meaning(43%)', 'the necessity' (19.6%), 'the advantage(9.3%)' of HACCP and 'the kinds of food products adopting HACCP(28%)'.

• 대한간호학회지
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• 제41권5호
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• pp.715-723
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• 2011

Purpose: This study was done to evaluated the effects of Human Papillomavirus (HPV) vaccination education on college women's knowledge of HPV, health beliefs (perceived severity and perceived susceptibility), and preventive behavior intention. Methods: A nonequivalent control group pretest-posttest design with repeated measures was used. Participants were 125 female college students in one university, assigned to an experimental group (72 students) and control group (53 students). Results: Two weeks after the intervention, the experimental group reported higher scores of knowledge, perceived severity, perceived susceptibility, and preventive behavior intention than the control group. All follow-up scores except intention measured at 5 weeks after the intervention from the experimental group remained still higher than those from the control group. Conclusion: The results suggest that the variable of preventive behavior intention which is believed to be the closest predictor of real vaccination rate could be affected by the education, but did not remain at the same level at 5 weeks. Therefore, additional interventions may need to be provided before the educational effect on preventive behavior intention is greatly diminished.

• 한국정보과학회 언어공학연구회:학술대회논문집(한글 및 한국어 정보처리)
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• 한국정보과학회언어공학연구회 2007년도 제19회 한글 및 한국어 정보처리 학술대회
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• pp.128-133
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• 2007

Focused crawling은 검색시스템의 구축을 위한 웹 문서 수집단계에서, 미리 정의된 토픽 집합들과 관련성을 가지는 웹 문서를 수집하기 위하여 제안되었다. 이러한 focused crawling 연구에서 보다 효과적인 웹 문서 수집을 위해 주어진 토픽에 대한 양질의 배경지식을 제공할 수 있도록 온톨로지가 활발히 활용되어왔다. 그러나 기존의 온톨로지 기반 focused crawling 연구는 토픽과 웹 문서 간의 관련성 측정을 위하여, 주어진 토픽과 관련있는 온톨로지 내 각 개념들에 직관에 의존한 가중치를 부여하여 활용하였다. 하지만 이러한 직관에 의존한 가중치부여 기법은 안정된 수집결과를 도출할 수 있는 최적화된 가중치 값을 얻기가 힘든 한계가 있다. 따라서 본 논문에서는 이러한 개념에 대한 가중치가 학습에 의하여 자동으로 결정되도록, 인공신경망을 적용한 온톨로지 기반 focused crawling 기법을 제안한다. 웹 상에서 제안된 시스템의 성능을 실험한 결과 기존의 온톨로지 기반 수집 기법에 비하여 보다 향상된 결과를 보임을 알 수 있었다.

• 한국정보과학회 언어공학연구회:학술대회논문집(한글 및 한국어 정보처리)
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• 한국정보과학회언어공학연구회 2004년도 제16회 한글.언어.인지 한술대회
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• pp.159-166
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• 2004

본 논문에서는 질의응답 시스템에서 질문의 주제와 개념적으로 일치하는 단락으로부터 정보를 추출할 경우에 보다 정확한 정답을 추출할 수 있다는 가정 하에 문장 주제를 활용한 의미적 단락 생성 및 검색 기법을 제안한다. 문장주제란 백과사전 문서 집합에서 공통으로 기술하는 내용이나 자주 언급하고 있는 사건 혹은 개념들의 집합을 의미하는 것으로, 주제별로 응집된 문장들로 재구성된 단락을 의미적 단락이라고 정의한다. 제안된 방법의 성능을 평가하기 위해 의미적 단락의 신뢰도를 파악하고, 백과사전 본문을 3문장 단위로 잘라서 고정길이 단락을 만든 후 의미적 단락의 검색결과와 비교하였다. 평가척도로는 TREC의 역순위평균(MRR : Mean Reciprocal Rank)과 상위 5개 단락 안에 정답유무를 측정하는 사용자 정답만족도를 사용하였다. ETRI 평가셋을 대상으로 한 실험 결과, 주제를 이용한 의미적 단락 검색 성능이 고정길이 단락 검색보다 우수함을 알 수 있었다.

• 한국정보과학회 언어공학연구회:학술대회논문집(한글 및 한국어 정보처리)
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• 한국정보과학회언어공학연구회 2015년도 제27회 한글 및 한국어 정보처리 학술대회
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• pp.174-177
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• 2015

자가 지식 학습 프레임워크는 자연어 텍스트에서 지식 트리플을 생성하기 위한 방법 중 하나로, 문장의 의존 관계 트리 상에서 주어 개체와 목적어 개체 사이의 관계를 패턴으로 학습해 이 패턴을 바탕으로 새로운 지식 트리플을 생성한다. 그러나 이 방법은 의존 관계 트리를 생성하는 도구의 성능에 영향을 받을 뿐만 아니라 생성된 지식 트리플을 반복적으로 사용하는 자가 지식 학습의 특성상 오류가 누적될 가능성이 있다. 이러한 문제점을 해결하기 위해서 본 논문에서는 자가 지식 학습 프레임워크에서 생성된 지식 트리플을 TransR 신뢰도 함수를 사용해 신뢰도 값을 측정하여 그 값에 따라 지식 트리플을 필터링하는 방법을 제안한다. 실험 결과에 따르면 필터링 된 지식 트리플들이 그렇지 않은 지식 트리플들에 비하여 더 높은 정확률을 보여주어, 제안한 방법이 자가 지식 학습 프레임워크의 정확률 향상에 효과적임을 증명하였다.

• The Journal of Asian Finance, Economics and Business
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• 제8권3호
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• pp.1153-1162
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• 2021

The innovation of enterprises allowed firms to promote technological innovation as an important choice to improve sustainable competitiveness. This study aims to investigate the relationship between absorptive capacity and innovation performance of Chinese high-tech enterprises and focuses on the mediating role of innovation culture in high-tech enterprises. Data came from surveying high-tech enterprises in China, and the reliability analysis, factor analysis, and correlation analysis, path analysis (SEM) were analyzed using SPSS23, AMOS. The results show that intellectual capital composed of human capital, structural capital, and relational has a significant impact on acquisition performance; intellectual capital is composed of human capital; structural capital has a significant influence on innovation performance; and absorptive capital has a significant impact on innovation performance. In addition, innovative culture plays a partial mediating role between absorptive capacity and innovation performance. The findings of this study suggest that, to ensure the better absorption and operation of knowledge, high-tech enterprises can accumulate more knowledge, promote the transformation of knowledge into technology, and strengthen the capability of knowledge absorptive capacity, and at the same time, create an innovation culture atmosphere and encourage employees to develop new products to achieve enterprise goals in order to promote the improvement of innovation performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권10호
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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.

• 한국식생활문화학회지
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• 제29권6호
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• pp.648-658
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• 2014

The aim of this study was to investigate the relationships between eating habits and health among adolescents in Shanghai and Heze, China. A cross-sectional study was conducted in 2013 on 2,089 adolescents; 1,089 students were from Shanghai and 999 students from Heze region. Eating habits, weight, height, and nutritional knowledge were assessed using a self-administered questionnaire. Eating habits score was classified into two categories: healthy eating habits and unhealthy eating habits, based on "Korean Youth Risk Behavior Web-based Survey", for statistical data analysis. Associations between eating habits, BMI, and nutritional knowledge were examined using a general linear model with adjustment of potential confounding factors such as region, gender, age, parents' education level, and pocket money. Statistical analyses were performed using the SAS (version 9.3) program. Proportions of healthy eating habits group were 90.0% for breakfast (3-7 times/wk), 29.1% for fruit (${\geq}once/d$), 12.5% for vegetable (${\geq}3times/d$), 7.3% for milk (${\geq}2times/d$), 90.0% for fast food (<3 times/wk) consumption, respectively. The average BMI score was 20.1 (Shanghai 20.5 Heze 19.6), which is in the range of normal weight. Rates of obesity and overweight were 16.5% and 8.3% in Shanghai and Heze, respectively. There were significant negative correlations between intake frequencies of breakfast, fast food, biscuits, sugar, chocolate, and BMI score. Eating habits and nutritional knowledge score showed a significant positive correlation. These results showed better eating habits regarding eating regularity and consumption of fruits and soft drinks in Chinese adolescents compared with Korean adolescents, although cultural differences were not fully considered. This study demonstrated significant associations of BMI and nutritional knowledge with dietary behavior in Chinese adolescents in two regions of China. Further studies on Chinese adolescents from other regions in China should be considered.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.49.2-49
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• 2002

This paper describes the configuration of a multi-agent system that can recognize human intentions. This system constructs ontologies of human intentions and enables knowledge acquisition and sharing between intelligent agents operating in different environments. This is achieved by using a bi-directional associative memory network. The process of intention recognition is based on fuzzy association inferences. This paper shows the process of information sharing by using ontologies. The purpose of this research is to create human-centered systems that can provide a natural interface in their interaction with people.

• 제어로봇시스템학회논문지
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• 제5권1호
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• pp.54-61
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• 1999

Objective of the research is to put the vast and complex fault tracking knowledge of human experts in semiconductor production line into the knowledge base of computer system. We mined the fault tracking knowledge of domain experts(engineers of production line) for the construction of knowledge base of the expert system. Object oriented fact models which increase the extensibility and reusability have been built. The rules are designed to perform the fault diagnosis of the items in production device. We have exploited the evidence accumulation method to assign check priority in rules. The major contribution is in the overall design and implementation of the nile base and related facts of the expert system in object oriented paradigm for the application of the system in fault diagnosis in semiconductor production line.