• Journal of the Computational Structural Engineering Institute of Korea
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• v.21 no.4
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• pp.325-334
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• 2008

The standard prestressed concrete I-girder bridge (PSC I-girder bridge) is one of the most prevalent types for small and medium bridges in Korea. When determining the member forces in a section to assess the safety of girder in this type of bridge, the general practice is to use the simplified practical equations or the live load distribution factors proposed in design standards rather than the precise analysis through the finite element method or so. Meanwhile, the live load distribution factors currently used in Korean design practice are just a reflection of overseas research results or design standards without alterations. Therefore, it is necessary to develop an equation of the live load distribution factors fit for the design conditions of Korea, considering the standardized section of standard PSC I-girder bridges and the design strength of concrete. In this study, to develop an equation of the live load distribution factors, a parametric analysis and sensitivity analysis were carried out on the parameters such as width of bridge, span length, girder spacing, width of traffic lane, etc. As a result, the major variables to determine the size of distribution factors were girder spacing, overhang length and span length in case of external girders. For internal adjacent girders, the determinant factors were girder spacing, overhang length, span length and width of bridge. For internal girders, the factors were girder spacing, width of bridge and span length. Then, an equation of live load distribution factors was developed through the multiple linear regression analysis on the results of parametric analysis. When the actual practice engineers design a bridge with the equation of live load distribution factors developed here, they will determine the design of member forces ensuring the appropriate safety rate more easily. Moreover, in the preliminary design, this model is expected to save much time for the repetitive design to improve the structural efficiency of PSC I-girder bridges.

• Proceedings of the KOR-BRONCHOESO Conference
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• 1981.05a
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• pp.3.2-3
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• 1981

This paper was attemped to analize 55 cases of fiberoptic bronchoscopy during period of 3 years from Feb. 1978 till Feb. 1981 in Chung Ang University hospital. The results were as follow; 1) In age distribution; Most common age group was 5th decade (15 cases, 27.2%) and the other age groups showed relatively even distribution. 2) The ratio of male to female was 3 to 1. 3) The chief complaints were presented in following order; cough (52%), hemoptysis(25%), dyspnea(23.6%), chest pain(18%), chest disomfort(9%). 4) Direct smear of bronchoscopic aspiration material; Not found 33 cases (60%) were most common finding. In the founded bacteria Gram positive cocci 2 cases (3.6%), Gram negative cocci 2 cases (3.6%), Gram positive bacilli 1 cases (1.8%), Gram negativebacilli 2 cases (3.6%), mixed form 15 cases(27.2%) were presented. 5) Bacterial culture of bronchoscopic aspiration material; No growth 28 cases (50.9%) were most common finding. In the bacterial growth, alpha hemolytic streptococci 10 cases (18.2%), Neisseria group 7cases(12.7%), Klebsiella 2 cases (3.6%), Pseudomonas 2 cases (3.6%), mixed culture 6 cases (10.9%) were presented, 6) The diagnosis of bronchoscopic appearance, laboratory exam., and pathologic exam. of biopsed specimen were 21 cases (38.1%) primary carcinoma of bronchus, 8 cases (14.5%) pulmonary tuberculosis, 7 cases (12.7%) bronchitis in orders.

• Korean Journal of Soil Science and Fertilizer
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• v.17 no.2
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• pp.147-154
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• 1984

Two Fe-hydrous oxide A,B and one Al-hydroxide minerals were synthesized precipitating Fe $Cl_3$ and $AlCl_3$ with alkali solution(NaOH) at pH 6.0, 12.0 and 4.5 respectively, for precise understanding of physico-chemical and surface charge characteristics of soils in which these minerals are dominant. Identification of these final products, effect of free and amorphous materials on X-ray diffraction analysis, particle size distribution and surface change characterics of these minerals were performed. Fe-hydroxide A and B were identified as great deal of X-ray amorphous material and as goethite with large amount of X-ray amorphous material, respectively. Dehydration by oven at $105^{\circ}C$ of these minerals exhibited akaganeite peaks with low X-ray amorphous hump and pure goethite peaks for Fe-hydroxide A and B, respectively. Both minerals, however, turned into hematite upon firing at $550^{\circ}C$. On the other hand, Al-hydroxide identified as mixture of gibbsite and bayerite of around 7:3 ratio. Application of sodium dithionite and ammonium oxalate solutions for removal of free or amorphous Fe and Al from these minerals revealed that only peak intensities of Al-hydroxide system were enhanced upon Al-extraction by oxalate solution even though dithionite solution was much powerful to extract Fe from Fe-hydrous oxide systems. Original(wet) Fe-hydrous oxide A has the highest specific surface and surface charge development(negative and positive), and the greatest amount of less than $2{\mu}m$ sized particles. Specific surface and clay sized particles(less than $2{\mu}m$) of Fe-hydrous oxide A, however, were drastically reduced upon dehydration($P_2O_5$ and oven drying) compare to the rest minerals. The Z.P.C. of these synthetic minerals were 8.0-8.5, 7.5-8.0 and 5.5-6.0 for Fe-hydrous oxide A, B and Al-hydroxide, respectively.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.64-80
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• 2018

In Korea, citizens can only know general information about crime. Thus it is difficult to know how much they are exposed to crime. If the police can predict the crime risky area, it will be possible to cope with the crime efficiently even though insufficient police and enforcement resources. However, there is no prediction system in Korea and the related researches are very much poor. From these backgrounds, the final goal of this study is to develop an automated crime prediction system. However, for the first step, we build a big data set which consists of local real crime information and urban physical or non-physical data. Then, we developed a crime prediction model through machine learning method. Finally, we assumed several possible scenarios and calculated the probability of crime and visualized the results in a map so as to increase the people's understanding. Among the factors affecting the crime occurrence revealed in previous and case studies, data was processed in the form of a big data for machine learning: real crime information, weather information (temperature, rainfall, wind speed, humidity, sunshine, insolation, snowfall, cloud cover) and local information (average building coverage, average floor area ratio, average building height, number of buildings, average appraised land value, average area of residential building, average number of ground floor). Among the supervised machine learning algorithms, the decision tree model, the random forest model, and the SVM model, which are known to be powerful and accurate in various fields were utilized to construct crime prevention model. As a result, decision tree model with the lowest RMSE was selected as an optimal prediction model. Based on this model, several scenarios were set for theft and violence cases which are the most frequent in the case city J, and the probability of crime was estimated by $250{\times}250m$ grid. As a result, we could find that the high crime risky area is occurring in three patterns in case city J. The probability of crime was divided into three classes and visualized in map by $250{\times}250m$ grid. Finally, we could develop a crime prediction model using machine learning algorithm and visualized the crime risky areas in a map which can recalculate the model and visualize the result simultaneously as time and urban conditions change.

• Applied Chemistry for Engineering
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• v.22 no.6
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• pp.685-690
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• 2011

In this study, a solvothermal reaction to prepare nanocrystalline titania was carried out using $TiCl_4$ and mixed solvents of alcohol and water. The effects of the type and the composition of alcohol on the crystal structure and agglomeration of final $TiO_2$ products were investigated. The products were characterized by X-ray diffraction (XRD), transmission electron microscopy (TEM) as well as scanning electron microscopy (SEM). In the solvothermal reaction using the n-butanol solutions with different volume ratios of n-butanol/water (100/0, 75/25, 50/50, 25/75, 0/100), the extent of agglomeration of obtained rutile $TiO_2$ was found to change with the volume ratio of n-butanol/water, and the n-butanol/water ratio of 75/25 revealed the best result for the preparation of well-dispersed nanocrystalline $TiO_2$ powders. The crystal phase of $TiO_2$ prepared through the solvothermal reaction changed with the type of alcohol in solvent (alcohol/water = 75/25). $TiO_2$ products obtained with the aqueous solutions of methanol, ethanol and isopropanol have an anatase phase, while that with n-butanol has a rutile phase. The results showed that, in the solvothermal reaction using both $TiCl_4$ as a starting material and the alcohol-water mixed solvents without any other additive, the enhancement of dispersion and control of crystal structure of $TiO_2$ products can be feasible by simply varying the composition and type of alcohol in the mixed solvents.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.33 no.2
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• pp.83-90
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• 2023

The β-Ga₂O₃ has the most thermodynamically stable phase, a wide band gap of 4.8~4.9 eV and a high dielectric breakdown voltage of 8MV/cm. Due to such excellent electrical characteristics, this material as a power device material has been attracted much attention. Furthermore, the β-Ga₂O₃ has easy liquid phase growth method unlike materials such as SiC and GaN. However, since the grown pure β-Ga₂O₃ single crystal requires the intentionally controlled doping due to a low conductivity to be applied to a power device, the research on doping in β-Ga₂O₃ single crystal is definitely important. In this study, various source powders of un-doped, Sn 0.05 mol%, Sn 0.1 mol%, Sn 1.5 mol%, Sn 2 mol%, Sn 3 mol%-doped Ga₂O₃ were prepared by adding different mole ratios of SnO₂ powder to Ga₂O₃ powder, and β-Ga₂O₃ single crystals were grown by using an edge-defined Film-fed Growth (EFG) method. The crystal direction, crystal quality, optical, and electrical properties of the grown β-Ga₂O₃ single crystal were analyzed according to the Sn dopant content, and the property variation of β-Ga₂O₃ single crystal according to the Sn doping were extensively investigated.

• Economic and Environmental Geology
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• v.49 no.5
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• pp.349-360
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• 2016

This study determined mineralogical characteristics and discussed the meaning of mineralogical changes of the lower Choseon Supergrouop in the Weondong area based on the field geological investigation and the drilling core description using X-ray diffraction (XRD) mineral quantification and Scanning Electron Microscopy (SEM) observation. 100 samples with depth were collected from the core (250 m long) at a site in the study area. Especially, to investigate the changes from the upper Daegi Formation to the lower Hwajeol Formation, the samples were collected closely with the interval of about 0.3 m at this section. All samples were made into power using mortar for XRD. Mineral quantitative analysis was executed using Relative Intensity Ratio (RIR) method with corundum as an internal standard phase. Calcite, $2M_1$ illite and quartz are main constituents in most of samples. Dolomite and siderite are significantly observed in the Sesong Formation. As the results of quantitative analysis for the major minerals, the upper Daegi Formation is dominated by calcite with over 80%. The Sesong Formation includes high percentage of dolomite and siderite with the intercalation of thin layers containing high calcite and $2M_1$ illite contents. Hwajeol Formation is characterized by the alternation between thin layers of $2M_1$ illite and quartz-dominated layer (IQDL) and calcite-dominated layer (CDL). IQDL is more frequent in the lower part, whereas CDL is more common in the upper part. The boundary between Daegi Formation and the Sesong Formation is distinct, whereas the boundary between the Sesong Formation and the Hwajeol Formation tends to be changed gradually in mineralogy. The result of SEM observation shows that quartz and $2M_1$ illite are detrital, and a significant amount of calcite also shows detrital form with some recrystallized one, indicating that the repeated influx of terrestrial materials had changed the mineralogy of the shallow sea depositional environment in the early Paleozoic era.

• Korean Journal of Social Welfare Studies
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• v.48 no.3
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• pp.171-208
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• 2017

The purpose of this study is to classify the underlying and parsimonious types of child maltreatment and examine whether the effects of risk factors on child maltreatment recurrence differ by type of maltreatment. We utilized the multiyear national administrative data from the National Child Maltreatment Information System collected by Child Protection Agency in Korea. Of 26,921 child maltreatment victims reported and substantiated on or after January 1, 2012, 1,447 children who had recurrence of child maltreatment until December 31, 2015 were selected as maltreatment recurrence group and 4,580 children who had not experienced maltreatment since first substantiation were assigned as maltreatment non-recurrence group. Latent class analysis(LCA) and latent transition analysis(LTA) were used to group children with similar maltreatment subtypes into discrete classes of child maltreatment recurrence. Logistic regression is employed to examine the association between the child maltreatment predominant types and risk factors for recurrence. Results of LCA and LTA showed four latent classes representing predominant type of child maltreatment: 'physical abuse predominant type', 'emotional abuse predominant type', 'sexual abuse predominant type', and 'neglect type'. Significant differences in the effect of risk factors among latent classes were found in child's age and gender, perpetrator's gender, family poverty, biological parent as the perpetrator, domestic violence toward partner, perpetrator's alcoholic problem, insufficient parenting skills, and out-of-home care service, Based on these findings, results suggested how the typology can be used to guide decision about who to target in prevention and intervention programs, and which features of risk factors to target. Practice and policy implications as well as further research tasks were discussed in the lights of searching for useful and important strategies to prevent recurrence of child maltreatment.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.237-262
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• 2022

There has been a growing interest in IPOs (Initial Public Offerings) due to the profitable returns that IPO stocks can offer to investors. However, IPOs can be speculative investments that may involve substantial risk as well because shares tend to be volatile, and the supply of IPO shares is often highly limited. Therefore, it is crucially important that IPO investors are well informed of the issuing firms and the market before deciding whether to invest or not. Unlike institutional investors, individual investors are at a disadvantage since there are few opportunities for individuals to obtain information on the IPOs. In this regard, the purpose of this study is to provide individual investors with the information they may consider when making an IPO investment decision. This study presents a model that uses machine learning and text analysis to predict whether an IPO stock price would move up or down after the first 5 trading days. Our sample includes 691 Korean IPOs from June 2009 to December 2020. The input variables for the prediction are three tone variables created from IPO prospectuses and quantitative variables that are either firm-specific, issue-specific, or market-specific. The three prospectus tone variables indicate the percentage of positive, neutral, and negative sentences in a prospectus, respectively. We considered only the sentences in the Risk Factors section of a prospectus for the tone analysis in this study. All sentences were classified into 'positive', 'neutral', and 'negative' via text analysis using TF-IDF (Term Frequency - Inverse Document Frequency). Measuring the tone of each sentence was conducted by machine learning instead of a lexicon-based approach due to the lack of sentiment dictionaries suitable for Korean text analysis in the context of finance. For this reason, the training set was created by randomly selecting 10% of the sentences from each prospectus, and the sentence classification task on the training set was performed after reading each sentence in person. Then, based on the training set, a Support Vector Machine model was utilized to predict the tone of sentences in the test set. Finally, the machine learning model calculated the percentages of positive, neutral, and negative sentences in each prospectus. To predict the price movement of an IPO stock, four different machine learning techniques were applied: Logistic Regression, Random Forest, Support Vector Machine, and Artificial Neural Network. According to the results, models that use quantitative variables using technical analysis and prospectus tone variables together show higher accuracy than models that use only quantitative variables. More specifically, the prediction accuracy was improved by 1.45% points in the Random Forest model, 4.34% points in the Artificial Neural Network model, and 5.07% points in the Support Vector Machine model. After testing the performance of these machine learning techniques, the Artificial Neural Network model using both quantitative variables and prospectus tone variables was the model with the highest prediction accuracy rate, which was 61.59%. The results indicate that the tone of a prospectus is a significant factor in predicting the price movement of an IPO stock. In addition, the McNemar test was used to verify the statistically significant difference between the models. The model using only quantitative variables and the model using both the quantitative variables and the prospectus tone variables were compared, and it was confirmed that the predictive performance improved significantly at a 1% significance level.

• Korean Journal of Ecology and Environment
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• v.57 no.1
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• pp.39-50
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• 2024

In ecosystems within limited resources, interspecific competition is inevitable, often leading to the competitive exclusion of inferior species. This study aims to provide foundational information for the conservation and restoration management of Microphysogobio rapidus by evaluating species' ecological response to biological factors within its habitat. To understand this relationship, we collected food web organisms from site where M. rapidus coexist with Microphysogobio yaluensis, a specie ecologically similar to M. rapidus, and evaluated the trophic levels (TL), isotopic niche space (INS), and the overlap of INS among fishes within the habitat using stable isotope analysis. Our analysis revealed that the M. rapidus exhibited a higher TL than M. yaluensis, with TL of 2.6 and 2.4, respectively. M. yaluensis exhibited a broad INS, significantly influencing the feeding characteristics of most fish. Conversely, M. rapidus showed a narrow INS and asymmetric feeding relationships with other species, in habitats with high competition levels. This feeding characteristics of M. rapidus indicate that the increase in competitors sharing the similar resources lead to a decrease in available resources and, consequently, is expected to result in a decrease in their density.