• 한국정보시스템학회지:정보시스템연구
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• 제28권4호
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• pp.155-174
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• 2019

Purpose Social interest in financial statement notes has recently increased. However, contrary to the keen interest in financial statement notes, there is no morphological analyzer for accounting terms, which is why researchers are having considerable difficulty in carrying out research. In this study, we build a morphological analyzer for accounting related text mining techniques. This morphological analyzer can handle accounting terms like financial statements and we expect it to serve as a springboard for growth in the text mining research field. Design/methodology/approach In this study, we build customized korean morphological analyzer to extract proper accounting terms. First, we collect Company's Financial Statement notes, financial information data published by KPFIS(Korea Public Finance Information Service), K-IFRS accounting terms data. Second, we cleaning and tokeninzing and removing stopwords. Third, we customize morphological analyzer using n-gram methodology. Findings Existing morphological analyzer cannot extract accounting terms because it split accounting terms to many nouns. In this study, the new customized morphological analyzer can detect more appropriate accounting terms comparing to the existing morphological analyzer. We found that accounting words that were not detected by existing morphological analyzers were detected in new customized morphological analyzers.

• 한국해양공학회:학술대회논문집
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• 한국해양공학회 2006년 창립20주년기념 정기학술대회 및 국제워크샵
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• pp.315-318
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• 2006

This paper concerns about coupled dynamic analysis of the deep-seabed mining system in launching operation. The dynamic behavior of mining system consisting of lifting pipe, buffer station, flexible conduit and self-propelled miner is simulated in time domain. The launching operation is divided into four critical phases: (1) deployment of miner and flexible conduit, (2) deployment of lifting pipe, flexible conduit and miner, (3) touch-down of miner, (4) final launching. The dynamic responses of sub-systems - miner, flexible conduit, buffer and lifting pipe - are analyzed in each launching phase. According to the changing periods of forced excitation at the top, the dynamic responses of sub-systems are diverse in their characteristics. It has been shown that the total integrated responses of sub-systems are strongly affected by the design parameters. Especially, the principal dimensions of flexible conduit seem to be significant in determining of the global response. Based on the simulation results, safe operation conditions are investigated.

• 디지털콘텐츠학회 논문지
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• 제17권5호
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• pp.359-366
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• 2016

유비쿼터스 환경에서 사용자에게 유용한 서비스를 제공하기 위해서는 시간과 공간을 기반으로 사용자의 행동과 선호 패턴을 고려하여 가장 적합한 데이터를 처리할 수 있는 방법이 필요하다. 실세계에서 사용자의 관심은 시간이 지남에 따라 변화할 수 있다. 그러므로 서비스 관심도의 변화를 중요도에 반영하여 정보를 추출할 수 있는 방법이 필요하다. 이 논문에서는 사용자에게 필요한 서비스 정보를 온톨로지로 설계하고 시간에 따라 동적으로 변화하는 사용자의 서비스 이용 패턴이나 데이터의 중요도를 동적 가중치로 표현하여 빈발 패턴을 찾는 방법을 제안한다. 이 논문에서 제안하는 동적 가중치를 고려하는 빈발 서비스 패턴 마이닝 기법은 시간의 변화에 따라 필요로 하는 사용자의 관심을 서비스의 중요도로 반영하므로 실시간의 최적화된 서비스 제공이 가능하다.

• International Journal of Naval Architecture and Ocean Engineering
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• 제6권3호
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• pp.652-669
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• 2014

This paper concerns the kinematic characteristics of a coupling device in a deep-seabed mining system. This coupling device connects the buffer system and the flexible pipe. The motion of the buffer system, flexible pipe and mining robot are affected by the coupling device. So the coupling device should be considered as a major factor when this device is designed. Therefore, we find a stable kinematic device, and apply it to the design coupling device through this study. The kinematic characteristics of the coupling device are analyzed by multi-body dynamics simulation method, and finite element method. The dynamic analysis model was built in the commercial software DAFUL. The Fluid Structure Interaction (FSI) method is applied to build the deep-seabed environment. Hydrodynamic force and moment are applied in the dynamic model for the FSI method. The loads and deformation of flexible pipe are estimated for analysis results of the kinematic characteristics.

• 한국정보시스템학회지:정보시스템연구
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• 제29권4호
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• pp.171-191
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• 2020

Purpose The study aims to compare the online review writing behavior of users in China and the United States through text mining on online reviews' text content. In particular, existing studies have verified that there are differences in online reviews between different cultures. Therefore, the purpose of this study is to compare the differences between reviews written by Chinese and American tourists by analyzing text contents of online reviews based on cultural theory. Design/methodology/approach This study collected and analyzed online review data for hotels, targeting Chinese and US tourists who visited Korea. Then, we analyzed review data through text mining like sentiment analysis and topic modeling analysis method based on previous research analysis. Findings The results showed that Chinese tourists gave higher ratings and relatively less negative ratings than American tourists. And American tourists have more negative sentiments and emotions in writing online reviews than Chinese tourists. Also, through the analysis results using topic modeling, it was confirmed that Chinese tourists mentioned more topics about the hotel location, room, and price, while American tourists mentioned more topics about hotel service. American tourists also mention more topics about hotels than Chinese tourists, indicating that American tourists tend to provide more information through online reviews.

• 한국정보시스템학회지:정보시스템연구
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• 제30권2호
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• pp.189-214
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• 2021

Purpose This paper aims to effectively utilize user-generated content (UGC) and analyze the market structure of a relatively new market which lacks rich user review information. Specifically, we propose a domain-specific text mining tool for the domestic craft beer market and visualize the market structure by incorporating how individual beer products are positioned in the perceptual map of consumers. Design/methodology/approach We collect user review information from Naver blogs, and extract words that describe beers. We identify semantic relationships between beer products through text mining, and then depending on these semantic relationships, construct a graph representing the market structure of the domestic craft beer market based on the consumer's perceptual map. Findings First, beer products produced in the same brewery are perceived as very similar to consumers. Second, only two products, 'Heukdang Milky Stout' and 'Gompyo', was noticeably distinguishable from other products. Third, even though 'Gyeongbokgung' is from a different brewery, it is located very close to the products of 'Jeju Beer' brewery such as 'Jeju Baeknokdam Ale' and 'Seongsan Ilchulbong Ale', which suggests the influence of 'landmark series.' We successfully show that our methodology effectively describes the market structure of the craft beer market.

• Safety and Health at Work
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• 제13권1호
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• pp.73-77
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• 2022

Background: Whole-body vibration (WBV) exposure of coal mine dumper operators poses numerous health hazards. The case-control study was aimed at assessing the relative musculoskeletal health risk of dumper operators' exposure to WBV with reference to the nonexposed group. Methods: Measurements of WBV exposure were taken at the operator-seat interface using a human vibration analyzer for 110 dumper operators in three coal mines. This vibration measurement was supplemented by a questionnaire survey of 110 dumper operators exposed to WBV and an equal number of workers not exposed to WBV. The relative risk of musculoskeletal disorders (MSDs) has been assessed through the case-control study design. Results: ISO guidelines were used to compare the health risk. It was observed that the prevalence of pain in the lower back was 2.52 times more in the case group compared to the control group. The case group of Mine-2 was 2.0 times more prone to vibration hazards as compared to Mine-3. Conclusion: The case group is more vulnerable to MSDs than the control group. The on-site measurement as well as the response of the dumper operators during the questionnaire survey corroborates this finding.

• 한국의류학회지
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• 제46권1호
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• pp.116-131
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• 2022

This study used text mining to analyze big data to understand consumers' demand for and perceptions of fashion masks. Based on the text-mining analysis results, a survey was conducted with those living in Korea to investigate the influence of consumers' mask selection criteria on mask brand awareness and purchase intention for fashion masks. "Fashion mask" and "functional mask" were used as the keywords in a text-mining analysis, and an online survey of 242 respondents was conducted. The analysis results were as follows: First, the text-mining analysis extracted commonly appearing words that had a high frequency and TF-IDF, such as "COVID-19," "fashion," "celebrity," "antibacterial," and "filter." This confirmed that during the COVID-19 pandemic, consumers have demanded masks that are both functional and fashionable. Second, among consumers' mask selection criteria, trend and design had positive effects on face-mask brand awareness. Third, face-mask brand awareness had a positive effect on the purchase intention for both brand and fashion masks, and the purchase intention for brand masks had a positive effect on the purchase intention for fashion masks.

• Geomechanics and Engineering
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• 제31권5호
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• pp.529-543
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• 2022

The lattice-spring-based synthetic rock mass model (LS-SRM) technique has been extensively employed in large open-pit mining and underground projects in the last decade. Since the LS-SRM requires a complex and time-consuming calibration process, a robust approach was developed using the Response Surface Methodology (RSM) to optimize the calibration procedure. For this purpose, numerical models were designed using the Box-Behnken Design technique, and numerical simulations were performed under uniaxial and triaxial stress states. The model input parameters represented the models' micro-mechanical (lattice) properties and the macro-scale properties, including uniaxial compressive strength (UCS), elastic modulus, cohesion, and friction angle constitute the output parameters of the model. The results from RSM models indicate that the lattice UCS and lattice friction angle are the most influential parameters on the macro-scale UCS of the specimen. Moreover, lattice UCS and elastic modulus mainly control macro-scale cohesion. Lattice friction angle (flat joint fiction angle) and lattice elastic modulus affect the macro-scale friction angle. Model validation was performed using physical laboratory experiment results, ranging from weak to hard rock. The results indicated that the RSM model could be employed to calibrate LS-SRM numerical models without a trial-and-error process.

• Geomechanics and Engineering
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• 제34권3호
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• pp.303-316
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• 2023

With the development and utilization of urban underground space, the artificial ground freezing technology has been widely used in the construction of underground engineering in soft soil areas. The mechanical properties of soft clay changed greatly after freezing and thawing, which affected the seismic performance of underground structures. In this paper, a series of triaxial tests were carried out to study the dynamic response of the freezing-thawing clay under the seismic load considering different dynamic stress amplitudes and different confining pressures. The reduction factor of dynamic shear stress was determined to correct the amplitude of the seismic load. The deformation development mode, the stress-strain relationship and the energy dissipation behavior of the soft clay under the seismic load were analyzed. An empirical model for predicting accumulative plastic strain was proposed and validated considering the loading times, the confining pressures and the dynamic stress amplitudes. The relevant research results can provide a theoretical reference to the seismic design of underground structures in soft clay areas.