• Journal of the Korea Society of Computer and Information
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• v.22 no.3
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• pp.131-138
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• 2017

New drug development is time-consuming and costly. Hence, it is necessary to repurpose old drugs for finding new indication. We suggest the way that repurposing old drug using massive literature data and biological network. We supposed a disease-drug relationship can be available if signal pathways of the relationship include significant genes identified in literature data. This research is composed of three steps-identifying significant gene using co-occurrence in literature; analyzing the shortest path on biological network; and scoring a relationship with comparison between the significant genes and the shortest paths. Based on literatures, we identify significant genes based on the co-occurrence frequency between a gene and disease. With the network that include weight as possibility of interaction between genes, we use shortest paths on the network as signal pathways. We perform comparing genes that identified as significant gene and included on signal pathways, calculating the scores and then identifying the candidate drugs. With this processes, we show the drugs having new possibility of drug repurposing and the use of our method as the new method of drug repurposing.

• Journal of Environmental Health Sciences
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• v.28 no.2
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• pp.99-108
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• 2002

This study was carried out to evaluate the Physicochemical characteristics of mined waste(separated waste and soil) and to predict environmental effect of an old landfill site located at north of Seoul. Municipal solid waster(MSW) had been disposed of at the old landfill site used in this study for about 2 years(1990-1992). The old landfill site selected for this study had accepted mainly municipal solid waste. The landfill-mined waste contained separated waste (40.9%) and soil(59.1%) by wet weight basis. The separated waste consisted of combustible(91.0%) and non-combustible(9.0%). The combustible waste was mainly non-biodegradable plastics. The low heating value of the separated combustible waste, which is calculated by Dulong's equation, was as high as 3,470kcal/kg. According to the Korean Extraction Procedure, separated waste and soil were proved to be not hazardous. The total content of heavy metal in the separated waste and soil met standard of California State, USA. Therefore the separated waste may be relandfilled at a sanitary landfill site and/or burned up at an incinerator, and the separated old soil may be used ad landfill cover-soil at a sanitary landfill site. Water quality of two streams was grade IV, of which water could be used as industrial and agricultural water. The streams near the landfill site might not be contaminated by leachate from the old landfill site. It was estimated that organic matter in the old landfill site would not be actively biodegraded within a short period of time.

• Journal of Power Electronics
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• v.17 no.5
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• pp.1288-1297
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• 2017

The estimation of the remaining useful life (RUL) of lithium-ion (Li-ion) batteries is important for intelligent battery management system (BMS). Data mining technology is becoming increasingly mature, and the RUL estimation of Li-ion batteries based on data-driven prognostics is more accurate with the arrival of the era of big data. However, the support vector machine (SVM), which is applied to predict the RUL of Li-ion batteries, uses the traditional single-radial basis kernel function. This type of classifier has weak generalization ability, and it easily shows the problem of data migration, which results in inaccurate prediction of the RUL of Li-ion batteries. In this study, a novel multi-kernel SVM (MSVM) based on polynomial kernel and radial basis kernel function is proposed. Moreover, the particle swarm optimization algorithm is used to search the kernel parameters, penalty factor, and weight coefficient of the MSVM model. Finally, this paper utilizes the NASA battery dataset to form the observed data sequence for regression prediction. Results show that the improved algorithm not only has better prediction accuracy and stronger generalization ability but also decreases training time and computational complexity.

• Journal of Information Technology Services
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• v.18 no.4
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• pp.135-149
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• 2019

Recently, there are many researches for extracting meaningful information from large amount of text data. Among various applications to extract information from text, topic modeling which express latent topics as a group of keywords is mainly used. Topic modeling presents several topic keywords by term/topic weight and the quality of those keywords are usually evaluated through coherence which implies the similarity of those keywords. However, the topic quality evaluation method based only on the similarity of keywords has its limitations because it is difficult to describe the content of a topic accurately enough with just a set of similar words. In this research, therefore, we propose topic keywords reorganizing method to improve the identifiability of topics. To reorganize topic keywords, each document first needs to be labeled with one representative topic which can be extracted from traditional topic modeling. After that, classification rules for classifying each document into a corresponding label are generated, and new topic keywords are extracted based on the classification rules. To evaluated the performance our method, we performed an experiment on 1,000 news articles. From the experiment, we confirmed that the keywords extracted from our proposed method have better identifiability than traditional topic keywords.

• Safety and Health at Work
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• v.6 no.4
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• pp.279-288
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• 2015

Background: In this study, the measurement of job stress of electric overhead traveling crane operators and quantification of the effects of operator and workplace characteristics on job stress were assessed. Methods: Job stress was measured on five subscales: employee empowerment, role overload, role ambiguity, rule violation, and job hazard. The characteristics of the operators that were studied were age, experience, body weight, and body height. The workplace characteristics considered were hours of exposure, cabin type, cabin feature, and crane height. The proposed methodology included administration of a questionnaire survey to 76 electric overhead traveling crane operators followed by analysis using analysis of variance and a classification and regression tree. Results: The key findings were: (1) the five subscales can be used to measure job stress; (2) employee empowerment was the most significant factor followed by the role overload; (3) workplace characteristics contributed more towards job stress than operator's characteristics; and (4) of the workplace characteristics, crane height was the major contributor. Conclusion: The issues related to crane height and cabin feature can be fixed by providing engineering or foolproof solutions than relying on interventions related to the demographic factors.

• Journal of the Korean Wood Science and Technology
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• v.49 no.3
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• pp.226-233
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• 2021

This article aimed at thermally treating and charactering the Eucalyptus grandis wood under three different temperatures. For this, pristine eucalypt samples were treated by heating in a laboratory oven at 160 ℃, 200 ℃ and 240 ℃, always for 2 h. Treatment parameters (based on weight percentage loss and specific gravity), as well as mechanical (by hardness tests), chemical (by infrared spectroscopy), thermal (by thermogravimetry), and colorimetric (by CIELab method) features were evaluated. Compared to the pristine ones, the treated woods have there was a drop in apparent density at 12 % and consecutively greater thermal stability which is probably related to a previous partial degradation of some major amorphous components (namely cellulose, hemicellulose and lignin), as suggested by the treatment parameters and infrared spectra. Besides of that, the higher the temperature treatment, the higher the loss in surface hardness and the higher the colour darkening.

• The Journal of Economics, Marketing and Management
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• v.9 no.1
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• pp.1-14
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• 2021

Purpose: The article deals with the proposition that consumers' fashion consumption behavior will still follow the consumption behavior of fast fashion, despite recognizing the importance of slow fashion. Research design, data and methodology: The research model to verify this proposition is topic modelling with big data including unstructured textual data. we combined 5,506 news articles posted on Naver news search platform during the 2003-2019 period about fast fashion and slow fashion, high-frequency words have been derived, and topics have been found using LDA model. Based on these, we examined consumers' perception and consumption behavior on slow fashion through the analysis of Topic Network. Results: (1) Looking at the status of annual article collection, consumers' interest in slow fashion mainly began in 2005 and showed a steady increase up to 2019. (2) Term Frequency analysis showed that the keywords for slow fashion are the lowest, with consumers' consumption patterns continuing around 'brand.' (3) Each topic's weight in articles showed that 'social value' - which includes slow fashion - ranked sixth among the 9 topics, low linkage with other topics. (4) Lastly, 'brand' and 'fashion trend' were key topics, and the topic 'social value' accounted for a low proportion. Conclusion: Slow fashion was not a considerable factor of consumption behavior. Consumption patterns in fashion sector are still dominated by general consumption patterns centered on brands and fast fashion.

• Geomechanics and Engineering
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• v.35 no.4
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• pp.425-436
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• 2023

An effective tool for researching actual problems in geotechnical and mining engineering is to conduct physical modeling tests using similar materials. A reliable geometric scaled model test requires selecting similar materials and conducting tests to determine physical properties such as the mixing ratio of the mixed materials. In this paper, a method is proposed to determine similar materials that can reproduce target properties using a polynomial model based on experimental results on modeling materials using a gypsum-sand mixture (GSM) to simulate rocks. To that end, a database is prepared using the unconfined compressive strength, elastic modulus, and density of 459 GSM samples as output parameters and the weight ratio of the mixing materials as input parameters. Further, a model that can predict the physical properties of the GSM using this database and a polynomial approach is proposed. The performance of the developed method is evaluated by comparing the predicted and observed values; the results demonstrate that the proposed polynomial model can predict the physical properties of the GSM with high accuracy. Sensitivity analysis results indicated that the gypsum-water ratio significantly affects the prediction of the physical properties of the GSM. The proposed polynomial model is used as a powerful tool to simplify the process of determining similar materials for rocks and conduct highly reliable experiments in a physical modeling test.

• Advances in nano research
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• v.15 no.4
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• pp.367-384
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• 2023

Natural frequency behavior of graphene platelets reinforced composite (GPL-RC) joined truncated conical-cylindrical- conical shells resting on Winkler-type elastic foundation is presented in this paper for the first time. The rule of mixture and the modified Halpin-Tsai approach are applied to achieve the mechanical properties of the structure. Four different graphene platelets patterns are considered along the thickness of the structure such as GPLA, GPLO, GPLX, GPLUD. Finite element procedure according to Rayleigh-Ritz formulation has been used to solve 2D-axisymmetric elasticity equations. Application of 2D axisymmetric elasticity theory allows thickness stretching unlike simple shell theories, and this gives more accurate results, especially for thick shells. An efficient parametric investigation is also presented to show the effects of various geometric variables, three different boundary conditions, stiffness of elastic foundation, dispersion pattern and weight fraction of GPLs nanofillers on the natural frequencies of the joined shell. Results show that GPLO and BC3 provide the most rigidity that cause the most natural frequencies among different BCs and GPL patterns. Also, by increasing the weigh fraction of nanofillers, the natural frequencies will increase up to 200%.

• Korean Journal of Soil Science and Fertilizer
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• v.36 no.5
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• pp.323-332
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• 2003

This study was carried out to provide information for the present status of soil pollution near abandoned old-zinc mining area through analysis of bound form and 0.1 N-HCl extractable concentrations of heavy metals in soils and plants. Feasibility of endemic plants for phytoremediation was evaluated by the investigation of vegetation in soils. Cd contents of the selected samples near old-zinc mining soils ranged from 0.2 to $42mg\;kg^{-1}$. Nonagricultural soils near the mining area contained great amounts of Zn, Pb, Cd, and Cu than the paddy and upland soils. Some Korean wild plants, Artemisia princeps, Artemisia montana, Erigeron canadensis, and Pueraria thunbergiana, were found to grow vigorously in the studied area. Among them, Artemisia princeps was selected as a possible phytoremediator for cleaning heavy metal contaminated soils. Artemisia princeps contained about 43 and $52mg\;kg^{-1}$ of Cd in their root and shoot as dry weight, respectively. Average contents of Cd in the rhizosphere soil, $15.68mg\;kg^{-1}$, was slightly higher than the soil-root interface soils, $14.1mg\;kg^{-1}$. Sequential extraction of Cd contaminated soils showed that average $2.4mg\;kg^{-1}$ (about 7%) of cadmium existed as exchangeable form and the average amounts increased as follows : adsorbed < organically bound < exchangeable << oxide carbonate << sulfide residual fractions. Amendment of organic by-product fertilizer in metal-contaminated soils promoted the growth of roots significantly as compared with the other treatments containing chemical fertilizer.