• 컴퓨터교육학회논문지
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• 제14권4호
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• pp.63-70
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• 2011

인터넷 상에서 사용자 흥미에 부합하는 항목을 예측하여 추천해 주는 추천 시스템은 e-commerce가 발달함에 따라 다양한 분야에서 적용되어 왔다. 추천 시스템의 주요 방법인 협력 필터링은 사용자가 선호했던 항목들과 유사한 항목을 추천하거나 또는 유사한 기호의 다른 사용자가 선호했던 항목을 추천하는 것이다. 따라서 유사도의 정확한 측정과 추천한 항목의 실제 평가등급 예측은 협력 필터링의 성능을 결정하는 두가지 중요한 문제이다. 본 연구에서는 후자의 문제를 다룬다. 기존 연구에서는 평가 등급의 평균값을 기반으로 하여 실제 평가등급을 예측하였으나, 본 연구에서는 평가 등급 범위 기반의 방법을 제시하고 실험을 통해 성능을 조사하였다. 실험 결과 기존 방법에 비해 제안 방법은 평균 절대 오차에 있어서 성능이 크게 향상됨을 입증하였다.

• 한국콘텐츠학회논문지
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• 제8권9호
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• pp.139-149
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• 2008

특정직 공무원은 별도의 인사법규를 근거로 일반직과 다른 개별 인사행정을 시행하고 있다. 조직과 임무가 특수한 만큼 일반직에 대한 인사행정을 적용하는 것은 여러 면에서 문제점이 야기될 수 있다. 경찰공무원 역시 특정직으로 타 공직과는 상이한 형태의 인사행정을 시행하고 있다. 그런데 이러한 개별적 인사행정은 많은 장점을 가질 수 있으나 그에 못지않은 단점도 발생할 수 있다. 본 연구에서는 타 공직과 상이하게 운영되고 있는 경찰 근무성적평정 제도의 바람직한 운영을 도모하기 위해 평정결과에 대한 검증절차의 도입을 제안하였다. 다만, 제도시행 초기에는 검증대상을 최종 평정권자로 한정하는 것이 바람직할 것이다.

• 국제학술발표논문집
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• The 3th International Conference on Construction Engineering and Project Management
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• pp.550-557
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• 2009

The concepts of 'sustainable development', 'sustainable construction' and 'green building' have been elevated to priority levels in all types and phases of construction project development worldwide. Consultants and contractors are now required to seriously consider the impact of their operations on the natural environment and the society, and consequently adopt sustainable construction practices in the development process to minimize and mitigate the negative impacts of their activities. However, existing sustainability rating tools apply to the design, post-construction and operation phases of a building; no tool exists for the rating of the performance of the contractor or the project team at the construction phase. This study aimed to develop a model for evaluating the sustainability of construction operations, drawing on the global best practice standards on sustainability. Practical applications of the model were carried out through case studies to evaluate the performances of fifteen construction firms in New Zealand. The developed model and the outcomes of the case studies were presented, including potential areas of weaknesses, strengths, constraints to achievement or adoption of sustainable construction practices and areas for improvement in the operations of the firms. The successful application of the developed model in practice shows its usefulness and ease of application. It is therefore recommended for adoption as a simple but effective system for measuring and reporting on sustainability performance or sustainability of construction operations of firms in New Zealand and elsewhere.

• 공업화학
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• 제32권4호
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• pp.423-430
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• 2021

본 연구는 건자재용 목재의 화재위험성 및 화재위험성 등급을 평가하기 위하여 Chung's equations-III, -IV에 의한 화재성능지수-III (FPI-III), 화재성장지수-III (FGI-III), 화재위험성지수-IV (FRI-IV)를 중심으로 조사하였다. 시험편은 적삼목, 전나무, 물푸레나무, 단풍나무를 사용하였다. 화재 특성은 시험편에 대하여 콘칼로리미터(ISO 5660-1) 장비를 이용하여 조사하였다. 연소반응 후 측정된 FPI-III는 polymethylmetacrylate (PMMA) 기준으로 0.86~12.77로 나타났다. FGI-III는 PMMA를 기준으로 0.63~5.26으로 나타났다. 화재위험성 등급 지수인 FRI-IV에 의한 화재 등급은 0.05~6.12였으며 적삼목이 단풍나무와 비교하여 122.4배 높았다. FRI-IV에 의한 화재위험성 등급은 단풍나무, 물푸레나무, 전나무, PMMA, 적삼목 순서로 증가하였다. 모든 시편의 CO 피크농도는 103~162 ppm으로 측정되었으며 미국직업안전위생관리국(occupational safety and health administration)의 허용기준(permissible exposure limits)인 50 ppm보다 2.1~3.2배 높게 나타났다. 적삼목과 같이 체적밀도가 작고 휘발성 유기물질을 다량 함유한 소재는 FPI-III가 낮고 FGI-III가 높으므로 화재위험성 등급이 높은 것으로 나타났다.

• 한국컴퓨터정보학회논문지
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• 제23권8호
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• pp.123-131
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• 2018

The purpose of this study is to investigate the clinical nursing competence and self-efficacy of 4th and 2nd semester nursing college students who completed most of the performance-based nursing education curriculum. It was attempted to develop competency evaluation and competency-based curriculum. The collected data were analyzed using descriptive statistics, t-test, one-way ANOVA, $scheff{\bar{e}}$ test, Pearson's correlation coefficients and Stepwise multiple regression in SPSS WIN 24.0 program. The findings of this study were as follows. 1) The knowledge level of essential basic nursing skills received a score of 88.95. The overall average score of clinical performance was 3.15 out of 5. The mean score of self-efficacy was $4.14{\pm}0.57$ points on 6 points 2) Among the general characteristics of subjects, 'motivation of major selection' and 'satisfaction of practice time' differed in the knowledge of essential basic nursing skills, 'religion' and 'health status' differed in clinical performance ability and 'interpersonal relationship', 'motivation of major selection', 'major satisfaction', 'satisfaction of practice time', 'nursing satisfaction', 'desired working period' and 'average rating' differed in self-efficacy. 3) The self-efficacy showed a significant positive correlation with the clinical nursing competency including the knowledge of essential basic nursing skills and clinical performance ability. The nursing satisfaction, clinical performance ability, the knowledge of essential basic nursing skills, interpersonal relationship and average rating influenced significantly and explained 23.7% of the subjects' self-efficacy.

• 지질공학
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• 제29권4호
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• pp.393-403
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• 2019

취수보의 저류성능은 유량과 수심의 관계로 평가될 수 있다. 돌망태 취수보의 유량과 수심의 관계는 채움재의 물리적 특성에 따라 달라진다. 본 연구에서는 인공함양 원수확보를 위한 돌망태 취수보의 저류성능을 평가하는데 활용할 기존의 방류량 산출식들을 검토하였다. 채움재의 물리적 특성을 실험변수들과 관계식으로 표현한 기존의 방류량 산출식은 유량과 수심의 관계를 잘 표현하였다. 또한 채움재의 평균입경은 수심확보와 간접취수에 영향을 미치기 때문에 저류성능 뿐 아니라 취수성능에도 중요한 인자임을 알 수 있었다.

• 한국정보시스템학회지:정보시스템연구
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• 제29권1호
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• pp.241-265
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• 2020

Purpose Various machine learning techniques are used to implement for predicting corporate credit. However, previous research doesn't utilize time series input features and has a limited prediction timing. Furthermore, in the case of corporate bond credit rating forecast, corporate sample is limited because only large companies are selected for corporate bond credit rating. To address limitations of prior research, this study attempts to implement a predictive model with more sample companies, which can adjust the forecasting point at the present time by using the credit score information and corporate information in time series. Design/methodology/approach To implement this forecasting model, this study uses the sample of 2,191 companies with KIS credit scores for 18 years from 2000 to 2017. For improving the performance of the predictive model, various financial and non-financial features are applied as input variables in a time series through a sliding window technique. In addition, this research also tests various machine learning techniques that were traditionally used to increase the validity of analysis results, and the deep learning technique that is being actively researched of late. Findings RNN-based stateful LSTM model shows good performance in credit rating prediction. By extending the forecasting time point, we find how the performance of the predictive model changes over time and evaluate the feature groups in the short and long terms. In comparison with other studies, the results of 5 classification prediction through label reclassification show good performance relatively. In addition, about 90% accuracy is found in the bad credit forecasts.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권11호
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• pp.5321-5334
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• 2019

Data mining technology is frequently used in identifying the intention of users over a variety of information contexts. Since relevant terms are mainly hidden in text data, it is necessary to extract them. Quantification is required in order to interpret user preference in association with other structured data. This paper proposes rating and comments mining to identify user priority and obtain improved ratings. Structured data (location and rating) and unstructured data (comments) are collected and priority is derived by analyzing statistics and employing TF-IDF. In addition, the improved ratings are generated by applying priority categories based on materialized ratings through Sentiment-Oriented Point-wise Mutual Information (SO-PMI)-based emotion analysis. In this paper, an experiment was carried out by collecting ratings and comments on "place" and by applying them. We confirmed that the proposed mining method is 1.2 times better than the conventional methods that do not reflect priorities and that the performance is improved to almost 2 times when the number to be predicted is small.

• Journal of Multimedia Information System
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• 제3권4호
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• pp.155-160
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• 2016

The Pulse Coupled Neural Network (PCNN) is a kind of neural network models that consists of spiking neurons and local connections. The PCNN was originally proposed as a model that can reproduce the synchronous phenomena of the neurons in the cat visual cortex. Recently, the PCNN has been applied to the various image processing applications, e.g., image segmentation, edge detection, pattern recognition, and so on. The method for the image matching using the PCNN had been proposed as one of the valuable applications of the PCNN. In this method, the Genetic Algorithm is applied to the PCNN parameter learning for the image matching. In this study, we propose the method of the similar image rating using the PCNN. In our method, the Genetic Algorithm based method is applied to the parameter learning of the PCNN. We show the performance of our method by simulations. From the simulation results, we evaluate the efficiency and the general versatility of our parameter learning method.

• 대한설비공학회:학술대회논문집
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• 대한설비공학회 2009년도 하계학술발표대회 논문집
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• pp.706-711
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• 2009

Energy shortage and environmental pollution caused by fossil fuels are very serious problem. Especially buildings have consumed more and more energy, and buildings are spend up to 25% of total energy consumption. So we should prepare alternatives to save energy in buildings. In apartment houses, The efficiency of thermal insulators and window glasses is very important to curtail heating energy. In this study, the energy rating of Apartment building is evaluated by applying various thermal insulators and window glasses.