• Geomechanics and Engineering
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• v.18 no.4
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• pp.339-352
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• 2019

Rockmass parameters are used in the design of engineering structures built in rock and soil. One of the most important of these parameters is the rockmass Emass (Emass). Determination of the Emass of rockmass is a long, hard and expensive job. Therefore, empirical formulas developed by different researchers are used. These formulas use the elastic modulus of the material as a parameter. This value is a constant value in the design. However, engineering structures remain under different loads depending on many factors, such as topography, geometry of the structure, rock / soil properties. Time is other important parameter for rock/soil structure. With the start of the excavation, the loads that the structure is exposed to will change and remain constant at one level. In the new proposed method, the use of different Emass calculated from empirical formulas using the different material elastic modulus, which has different values under different loads as time dependent, was investigated in rock/soil structures during design. The performance of the stability analysis using different deformation modules was questioned by numerical modeling method. For this query, a sub-routine which can be integrated into the numerical modeling software has been developed. The integrated sub-routine contains the formula for the Emass, which is calculated from the material elasticity modules under time dependent and different constant loads in the laboratory. As a result of investigations conducted in 12 different field studies, the new proposed method is very sensitive.

• Journal of Service Research and Studies
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• v.12 no.3
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• pp.60-69
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• 2022

In this study, to verify the effectiveness of the persona-type consumer analysis data service, a study was conducted focusing on the consumer analysis service use case of www.ethno-mining.com. The case was targeted at the 'Small Business Design Difficulty Resolving Support Project' of the Gangwon Institute of Design Promotion. The progress of this study was to develop a questionnaire to measure the user satisfaction and effectiveness of the service, study the consumer analysis data of the persona method of the www.ethno-mining.com system, study related theories, compare similar services, and conduct questionnaires; The results were analyzed and tested. In the result of testing the participants in the 'Small Business Design Difficulty Resolving Support Project' of the Gangwon Design Promotion Institute, the persona-style consumer analysis data got a positive response in terms of user satisfaction, and a regression that measures the effectiveness of the service on the company's R&D In the analysis, it was found that there are practical effects for companies by reducing time, reducing costs, smooth communication between developers, securing expertise in consumer analysis, and improving the overall quality of R&D during R&D.

• Journal of the Korean Society of Clothing and Textiles
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• v.46 no.6
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• pp.1142-1160
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• 2022

Text data plays a significant role in understanding and analyzing trends in consumer, business, and social sectors. For text analysis, there must be a corpus that reflects specific domain knowledge. However, in the field of fashion, the professional corpus is insufficient. This study aims to develop a taxonomy and thesaurus that considers the specialty of fashion products. To this end, about 100,000 fashion vocabulary terms were collected by crawling text data from WSGN, Pantone, and online platforms; text subsequently was extracted through preprocessing with Python. The taxonomy was composed of items, silhouettes, details, styles, colors, textiles, and patterns/prints, which are seven attributes of clothes. The corpus was completed through processing synonyms of terms from fashion books such as dictionaries. Finally, 10,294 vocabulary words, including 1,956 standard Korean words, were classified in the taxonomy. All data was then developed into a web dictionary system. Quantitative and qualitative performance tests of the results were conducted through expert reviews. The performance of the thesaurus also was verified by comparing the results of text mining analysis through the previously developed corpus. This study contributes to achieving a text data standard and enables meaningful results of text mining analysis in the fashion field.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.4
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• pp.366-374
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• 2014

This study assessed and analysed a result of a product design experiment through Product Data Analytics (PDA), to find reasons for failure of some projects in the experiment. PDA is a computer-based data analysis that uses Product Data Management (PDM) databases as its operational databases. The study examines 20 product design projects in the experiment, which are prepared to follow same product development process by using an identical PDM system. The design result in the PDM database is assessed and analysed by On-Line Analytical Processing (OLAP) and data mining tools in PDA. The assesment and analysis reveals the lateness in creation of 3D CAD models as the main reason of the failure.

• Structural Engineering and Mechanics
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• v.71 no.5
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• pp.503-513
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• 2019

Genetic Algorithms (GAs) have found the best design for reinforced concrete frames. The design of the optimum beam sections by GAs has been unified. The process of the optimum-design sections has satisfied axial, flexural, shear and torsion necessities based on the designing code. The frames' function has contained the function of both concrete and reinforced steel besides the function of the frames' formwork. The results have revealed that limiting the dimension of frame-beam with the dimension of frame-column have increased the optimum function of the structure, thereby reducing the reanalysis requirement for checking the optimum-designed structures through GAs.

• Journal of Korea Trade
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• v.24 no.8
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• pp.171-188
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• 2020

Purpose - This is an exploratory study that aims to apply text mining techniques, which computationally extracts words from the large-scale text data, to legal documents to quantify trade claim contents and enables statistical analysis. Design/methodology - This is designed to verify the validity of the application of text mining techniques as a quantitative methodology for trade claim studies, that have relied mainly on a qualitative approach. The subjects are 81 cases of arbitration and court judgments from China published on the website of the UNCITRAL where the CISG was applied. Validation is performed by comparing the manually analyzed result with the automatically analyzed result. The manual analysis result is the cluster analysis wherein the researcher reads and codes the case. The automatic analysis result is an analysis applying text mining techniques to the result of the cluster analysis. Topic modeling and semantic network analysis are applied for the statistical approach. Findings - Results show that the results of cluster analysis and text mining results are consistent with each other and the internal validity is confirmed. And the degree centrality of words that play a key role in the topic is high as the between centrality of words that are useful for grasping the topic and the eigenvector centrality of the important words in the topic is high. This indicates that text mining techniques can be applied to research on content analysis of trade claims for statistical analysis. Originality/value - Firstly, the validity of the text mining technique in the study of trade claim cases is confirmed. Prior studies on trade claims have relied on traditional approach. Secondly, this study has an originality in that it is an attempt to quantitatively study the trade claim cases, whereas prior trade claim cases were mainly studied via qualitative methods. Lastly, this study shows that the use of the text mining can lower the barrier for acquiring information from a large amount of digitalized text.

• Safety and Health at Work
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• v.14 no.4
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• pp.457-466
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• 2023

Background: During hot environment work tasks with whole-body enclosed anti-bioaerosol suit, the combined effect of heavy sweating and exhaled hot humid air may cause the N95 medical respirator to saturate with water/sweat (i.e., water-blocking). Methods: 32 young male subjects with different body mass indexes (BMI) in whole-body protection (N95 medical respirator + one-piece protective suit + head covering + protective face screen + gloves + shoe covers) were asked to simulate waste collecting from each isolated room in a seven-story building at 27-28℃, and the weight, inhalation resistance (R_f), and aerosol penetration of the respirator before worn and after water-blocking were analyzed. Results: All subjects reported water-blocking asphyxia of the N95 respirators within 36-67 min of the task. When water-blocking occurred, the R_f and 10-200 nm total aerosol penetration (P_t) of the respirators reached up to 1270-1810 Pa and 17.3-23.3%, respectively, which were 10 and 8 times of that before wearing. The most penetration particle size of the respirators increased from 49-65 nm before worn to 115-154 nm under water-blocking condition, and the corresponding maximum size-dependent aerosol penetration increased from 2.5-3.5% to 20-27%. With the increase of BMI, the water-blocking occurrence time firstly increased then reduced, while the R_f, P_t, and absorbed water all increased significantly. Conclusions: This study reveals respirator water-blocking and its serious negative impacts on respiratory protection. When performing moderate-to-high-load tasks with whole-body protection in a hot environment, it is recommended that respirator be replaced with a new one at least every hour to avoid water-blocking asphyxia.

• Information Systems Review
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• v.21 no.2
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• pp.117-137
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• 2019

In the Big Data era, data science has become popular with the production of numerous data in various domains, and the power of data has become a competitive power. There is a growing interest in unstructured data, which accounts for more than 80% of the world's data. Along with the everyday use of social media, most of the unstructured data is in the form of text data and plays an important role in various areas such as marketing, finance, and distribution. However, text mining using social media is difficult to access and difficult to use compared to data mining using numerical data. Thus, this study aims to develop Korean Natural Language Application (KoALA) as an integrated application for easy and handy social media text mining without relying on programming language or high-level hardware or solution. KoALA is a specialized application for social media text mining. It is an integrated application that can analyze both Korean and English. KoALA handles the entire process from data collection to preprocessing, analysis and visualization. This paper describes the process of designing, implementing, and applying KoALA applications using the design science methodology. Lastly, we will discuss practical use of KoALA through a block-chain business case. Through this paper, we hope to popularize social media text mining and utilize it for practical and academic use in various domains.

• Journal of Distribution Science
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• v.11 no.3
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• pp.5-11
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• 2013

Purpose - Going concern is one of fundamental concepts in accounting and auditing and sometimes the assessment of a company's going concern status that is a tough process. Various going concern prediction models' based on statistical and data mining methods help auditors and stakeholders suggested in the previous literature. Research design - This paper employs a data mining approach to prediction of going concern status of Iranian firms listed in Tehran Stock Exchange using Particle Swarm Optimization. To reach this goal, at the first step, we used the stepwise discriminant analysis it is selected the final variables from among of 42 variables and in the second stage; we applied a grid-search technique using 10-fold cross-validation to find out the optimal model. Results - The empirical tests show that the particle swarm optimization (PSO) model reached 99.92% and 99.28% accuracy rates for training and holdout data. Conclusions - The authors conclude that PSO model is applicable for prediction going concern of Iranian listed companies.

• 연구논문집
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• s.34
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• pp.1-10
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• 2004

Landfill Mining is becoming more widely used in many closed landfill sites in the world. Many of existing landfills will be excavated inevitably owing to building the clean environment with the new structures and developing the cities in cramped country. This paper aimed at the introducing the design technology of the trommel screen and its in-site applied performance of the trommel screen system through experiments , which system is under developing by one of the national project and the analysis results of influencing factors to the environment . The result of the theoretical estimation agrees well with the experimental data, so that the sorting system could be able to be applied with the requirements of the purpose of end-items. As a result of the analysis, any hazardous materials including heavy metals met the limitions of the criteria in this experiment. In geotechnical enngineering, it will. desireable to use the sorted soils mixing with another soils in accordance with the requirements of the usages.