• 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.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.3112-3112
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• 2001

Near-Infrared Spectroscopy (NIRS) was investigated aiming at the identification of falsified drugs. The identification is based on comparison of the NIR spectrum of a sample with a typical spectra of an authentic drug using multivariate modelling and classification algorithms (PCA/SIMCA). Two spectrophotometers (Brimrose - Luminar 2000 and 2030), based on acoustic-optical filter (AOTF) technology, sharing the same controlling computer, software (Brimrose - Snap 2.03) and the data acquisition electronics, were employed. The Luminar 2000 scans the range 850 1800 nm and was employed for transmitance/absorbance measurements of liquids with a transflectance optical bundle probe with total optical path of 5 mm and a circular area of 0.5 $\textrm{cm}^2$. Model 2030 scans the rage 1100 2400 nm and was employed for reflectance measurement of solids drugs. 300 spectra, acquired in about 20 s, were averaged for each sample. Chemometric treatment of the spectral data, modelling and classification were performed by using the Unscrambler 7.5 software (CAMO Norway). This package provides the Principal Component Analysis (PCA) and SIMCA algorithms, used for modelling and classification, respectively. Initially, NIRS was evaluated for spectrum acquisition of various drugs, selected in order to accomplish the diversity of physico-chemical characteristics found among commercial products. Parameters which could affect the spectra of a given drug (especially if presented as solid tablets) were investigated and the results showed that the first derivative can minimize spectral changes associated with tablet geometry, physical differences in their faces and position in relation to the probe beam. The effect of ambient humidity and temperature were also investigated. The first factor needs to be controlled for model construction because the ambient humidity can cause spectral alterations that should cause the wrong classification of a real drug if the factor is not considered by the model.

• 한국안전학회지
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• 제35권4호
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• pp.64-73
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• 2020

As Korean government and safety-related organizations make continuous efforts to reduce the number of industrial accidents, accident rate has steadily declined since 2010, thereby recording 0.48% in 2017. However, the number of fatalities due to industrial accidents was 1,987 in 2017, which means that more efforts should be made to reduce the number of industrial accidents. As an essential activity for enhancing the system safety, accident analysis can be effectively used for reducing the number of industrial accidents. Accident analysis aims to understand the process of an accident scenario and to identify the plausible causes of the accident. Accident analysis offers useful information for developing measures for preventing the recurrence of an accident or its similar accidents. However, it seems that the current practice of accident analysis in Korean manufacturing companies takes a simplistic accident model, which is based on a linear and deterministic cause-effect relation. Considering the actual complexities underlying accidents, this would be problematic; it could be more significant in the case of human error-related accidents. Accordingly, it is necessary to use a more elaborated accident model for addressing the complexity and nature of human-error related accidents more systematically. Regarding this, HFACS(Human Factors Analysis and Classification System) can be a viable accident analysis method. It is based on the Swiss cheese model and offers a range of causal factors of a human error-related accident, some of which can be judged as the plausible causes of an accident. HFACS has been widely used in several work domains(e.g. aviation and rail industry) and can be effectively used in Korean industries. However, as HFACS was originally developed in aviation industry, the taxonomy of causal factors may not be easily applied to accidents in Korean industries, particularly manufacturing companies. In addition, the typical characteristics of Korean industries need to be reflected as well. With this issue in mind, we developed HFACS-K as a method for analyzing accidents happening in Korean industries. This paper reports the process of developing HFACS-K, the structure and contents of HFACS-K, and a case study for demonstrating its usefulness.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2008년도 International Symposium on Remote Sensing
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• pp.348-357
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• 2008

The classification of the effect of ionospheric disturbances on the radio occultation signal amplitude has been introduced based on an analysis of more than 2000 seances of radio occultation measurements per formed with the help of the CHAMP German satellite. The dependence of the histograms of variations in the radio occultation signal amplitude on the IMF variation index has been revealed. It has been indicated that it is possible to introduce the radio occultation index characterizing the relation between ionospheric disturbances and solar activity. An amplitude radio occultation (RO) method is proposed to study connection between the ionospheric and solar activity on a global scale. Sporadic amplitude scintillation observed in RO experiments contain important information concerning the seasonal, geographical, and temporal distributions of the ionospheric disturbances and depend on solar activity. The probability of strong RO amplitude variations (RO $S_4$ index greater than 0.2) in the CHAMP RO signals diminishes sharply with the weakening of solar activity from 2001 to 2008. The general number of RO events with strong amplitude variations can be used as an indicator of the ionospheric activity. We found that during 2001-2008 the daily globally averaged RO $S_{4a}$ index depends essentially on solar activity. The maximum occurred in January 2002, minimum has been observed in summer 2008. Different temporal behavoir of $S_{4a}$ index has been detected for polar (with latitude greater than $60^{\circ}$) and low latitude (moderate and equatorial) regions. For polar regions $S_{4a}$ index is slowly decreasing with solar activity. In the low latitude areas $S_{4a}$ index is sharply oscillating, depending on the solar ultraviolet emission variations. The different geographical behavoir of $S_{4a}$ index indicates different origin of ionospheric plasma disturbances in polar and low latitude areas. Origin of the plasma disturbances in the polar areas may be connected with influence of solar wind, the ultraviolet emission of the Sun may be the main cause of the ionospheric irregularities in the low latitude zone. Therefore, the $S_{4a}$ index of RO signal is important radio physical indicator of solar activity.

• 대한화학회지
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• 제53권5호
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• pp.570-584
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• 2009

이 연구의 목적은 과학교사에 의해 조성되는 심리적 학습 환경에 대한 고등학생들의 인식과 과학과 관련된 태도 변화를 알아보는 것이었다. 연구를 위하여 S시 공동학군 선지원 일반계 남자 고등학교 1학년 539명을 대상으로 과학교사에 의해 조성되는 심리적 학습 환경에 대한 인식을 조사하여 과학교사의 특성을 분류하고, 과학과 관련된 태도 검사를 1학기 초와 2학기 초에 실시하여 변화를 조사하였다. 그리고 과학과 관련된 태도 변화가 큰 학생을 대상으로 면담을 실시하였다. 연구 결과, 고등학교 1학년 학생들은 남자 과학교사보다 여자 과학교사를 좀 더 긍정적으로 인식하였으며, 학생들이 인식하는 심리적 학습 환경은 과학교사에 따라 통계적으로 유의미한 차이가 있었다. 과학교사에 의해 조성되는 심리적 학습 환경에 대한 고등학교 1학년 학생들의 인식을 바탕으로 분류한 과학교사의 특성에 따른 과학과 관련된 태도 변화는 과학교사가 한 학급만 담당할 경우에만 부정적으로 나타났으나, 대부분통계적으로 유의미한 관련성은 없었다. 과학과 관련된 태도 변화가 큰 고등학생들과의 비구조화된 면담 결과, 과학과 관련된 태도 변화의 주요 원인은 학업성취도로서, 과학교사의 직접적인 영향보다는 간접적인 영향이 과학과 관련된 태도 변화의 원인이었다. 그리고 학생들은 과학교사들이 다양한 수업 행동과 수업 지원적 행동을 가지고 과학수업에 임하기를 원하고 있었다. 따라서 고등학생들의 장래 진로선택에 중요한 역할을 담당하고 있는 과학교사들은 학습자 중심의 교육과정 실현과 고등학생들의 과학과 관련된 태도를 긍정적으로 변화시키도록 노력해야 한다.