• Journal of the Korean Society for Library and Information Science
• /
• v.56 no.4
• /
• pp.431-453
• /
• 2022

Hate is a collective expression of exclusivity toward others and it is fostered and reproduced through false public perception. This study aims to explore the objects and issues of hate discussed in our society using text mining techniques. To this end, we collected 17,867 news data published from 1990 to 2020 and constructed a co-word network and cluster analysis. In order to derive an explicit co-word network highly related to hate, we carried out sentence split and extracted a total of 52,520 sentences containing the words 'hate', 'prejudice' and 'discrimination' in the preprocessing phase. As a result of analyzing the frequency of words in the collected news data, the subjects that appeared most frequently in relation to hate in our society were women, race, and sexual minorities, and the related issues were related laws and crimes. As a result of cluster analysis based on the co-word network, we found a total of six hate-related clusters. The largest cluster was 'genderphobic', accounting for 41.4% of the total, followed by 'sexual minority hatred' at 28.7%, 'racial hatred' at 15.1%, 'selective hatred' at 8.5%, 'political hatred' accounted for 5.7% and 'environmental hatred' accounted for 0.3%. In the discussion, we comprehensively extracted all specific hate target names from the collected news data, which were not specifically revealed as a result of the cluster analysis.

• Journal of the Korean Geotechnical Society
• /
• v.22 no.4
• /
• pp.41-49
• /
• 2006

This paper demonstrates the feasibility of using shallow S-wave, high-resolution seismic reflection surveys to characterize geological structure and stratigraphy of basement rocks for civil engineering purposes. S-wave seismic reflections from depths less than 20 m were recorded along the top of steep readout slopes. Seismic reflection data were recorded using a standard CDP acquisition method with a 24-channel seismograph and a sledge-hammer SH-wave source. The data were acquired using a split-spread source-receiver geometry with a 2 m shot-and-receiver interval, and then were processed to enhance S/N ratio of the data, to improve resolvable power of the seismic section, and to get velocity information of the basement rock. The final seismic reflection profiles using the CDP technique has imaged surfaces as shallow as less than 1m and resolved beds as thin as 1m. The migrated reflection sections possess sufficient quality to correlate the prominent reflection events to the bedding planes and faults identified on the readout outcrops. Similar S-wave reflection surveys could also be used to produce the necessary details of a geological structure of shallow bedrocks to pinpoint optimum locations for monitor wells of civil engineering purposes.

• Korean Chemical Engineering Research
• /
• v.61 no.4
• /
• pp.542-549
• /
• 2023

Since the growing interest in surrogate modeling, there has been continuous research aimed at simulating nonlinear chemical processes using data-driven machine learning. However, the opaque nature of machine learning models, which limits their interpretability, poses a challenge for their practical application in industry. Therefore, this study aims to analyze chemical processes using Explainable Artificial Intelligence (XAI), a concept that improves interpretability while ensuring model accuracy. While conventional sensitivity analysis of chemical processes has been limited to calculating and ranking the sensitivity indices of variables, we propose a methodology that utilizes XAI to not only perform global and local sensitivity analysis, but also examine the interactions among variables to gain physical insights from the data. For the ammonia synthesis process, which is the target process of the case study, we set the temperature of the preheater leading to the first reactor and the split ratio of the cold shot to the three reactors as process variables. By integrating Matlab and Aspen Plus, we obtained data on ammonia production and the maximum temperatures of the three reactors while systematically varying the process variables. We then trained tree-based models and performed sensitivity analysis using the SHAP technique, one of the XAI methods, on the most accurate model. The global sensitivity analysis showed that the preheater temperature had the greatest effect, and the local sensitivity analysis provided insights for defining the ranges of process variables to improve productivity and prevent overheating. By constructing alternative models for chemical processes and using XAI for sensitivity analysis, this work contributes to providing both quantitative and qualitative feedback for process optimization.

• Tuberculosis and Respiratory Diseases
• /
• v.42 no.1
• /
• pp.84-92
• /
• 1995

Background: Nasal applied continuous positive airway pressure(CPAP) is a highly effective method of treatment for obstructive sleep apnea syndrome. More than a decade of accumulated experience with this treatment modality confirmed that it is unquestionably the medical treatment of choice for patients with obstructive sleep apnea syndrome. However it takes long time to reach optimal CPAP pressure. To save the time to reach optimal pressure, it is necessary to clarify the time to reach optimal pressure for treatment of obstructive sleep apnea syndrome. Method: CPAP pressure is titrated during an overnight study according to a standardized protocol. Just before the presleep bio-calibration procedures, the technician applies the nasal mask and switches on the clinical CPAP unit. Initial positive for pressure is typically 3.0 centimeters of water pressure. After sleep onset, the technician gradually increases the pressure until sleep-disordered breathing events disappear or become minimal. The pressure must maintain maximal airway patency during both NREM and REM sleep to be considered effective. Before recommending a final pressure setting, sleep recording and oximetry data are reviewed by an American Board of Sleep Medicine certified Sleep Specialist and a Registrered Polysomnographic Technologist. Results: We examined the time required to reach optimal pressure during routine CPAP titration in 127 consecutively evaluated individuals diagnosed with sleep-disordered breathing. Results indicate that 33% of patients required more than four hours to attain satisfactory titration. This indicates that a four-hour session is marginally enough time, at best, to determine a proper CPAP pressure setting. Moreover, 60 of 127 patients required further adjustment after optimal pressure was reached. These additional pressure trials were needed to confirm that higher pressures were not superior for eliminating sleep-disordered breathing events. Conclusions: The data presented underscore the logistical difficulty of titrating CPAP during split-night studies without modifying the titration procedure. Futhermore, the time needed to reach optimal pressure makes it improbable that proper CPAP titration can be performed during a 2-3 hour nap study.

• Korean Journal of Psychosomatic Medicine
• /
• v.8 no.2
• /
• pp.212-227
• /
• 2000

This study was designed to testify the reliability and validation on the Korean version of the Social Adaptation Self-rating Scale(SASS) which was developed from Bose et al. for the evaluation of social motivation and behavior of depressed patients in 1997. Interests for the social world, those of social functioning, of patients were involved in the addition of new measure of disturbance. And those were distinct from abnormalities of thought, mood and symptoms of patients with major depression. As the previous reports there were several evidences that treatments may be less likely to be effective if the system they act on is dysfunctional. Thus, a better social situation favoured better outcome. As a matter of fact, however, those reports were developed in the course of the evaluation of interpersonal therapy(IPT) and cognitive therapy. Accordingly the conversed question -whether pharmacological therapy with antidepressants can impact on social functioning in addition to addressing the core features of illness- has been addressed. To date, anyhow, it is accepted that enhancement of social functioning may be a therapeutic principle in its own right and illness rarely divorced from social context. In terms of those concepts the introduction of an assessment of social functioning into pharmacotherapeutic studies of depression has been welcomed and might be a potent instrument for evaluating the relative pharmacoeconomic benefits of different treatments. Despite of many scales which were applied for the evaluation of symptoms in the patients with depression, however, the scale for the evaluation of social functiong has not been introduced in Korea yet. Thus, this study was designed to introduce the concepts of social functioning in the patients with depression and to testify the reliability and validation on Korean version of SASS. This Korean version of SASS was submitted to a reliability and validation procedure based on the data from healthy general population survey in 291 individuals and 40 patients with major depression. Cronbach a was 0.790 in total subjects group and the correlation of test-retest was statistically significant(y=0.653, p<0.0l). Thus, the Korean version of SASS might be shown to be valid and reliable. The results of multivariate analyses allowed the identification of 3 principle factors(factor 1 = intersts in social activities, factor 2 = active interpersonal relationship, factor 3 = selfesteem) in normal group, however, it could be counted as only one factor in the depression group because nearly total items of SASS were involved in factor 1. In the view of these results, the Korean version of SASS may be useful additional tool for the evaluation of social functioning in depression.

• Journal of Intelligence and Information Systems
• /
• v.27 no.1
• /
• pp.65-82
• /
• 2021

Stock market investors are generally split into foreign investors, institutional investors, and individual investors. Compared to individual investor groups, professional investor groups such as foreign investors have an advantage in information and financial power and, as a result, foreign investors are known to show good investment performance among market participants. The purpose of this study is to propose an investment strategy that combines investor-specific transaction information and machine learning, and to analyze the portfolio investment performance of the proposed model using actual stock price and investor-specific transaction data. The Korea Exchange offers daily information on the volume of purchase and sale of each investor to securities firms. We developed a data collection program in C# programming language using an API provided by Daishin Securities Cybosplus, and collected 151 out of 200 KOSPI stocks with daily opening price, closing price and investor-specific net purchase data from January 2, 2007 to July 31, 2017. The self-organizing map model is an artificial neural network that performs clustering by unsupervised learning and has been introduced by Teuvo Kohonen since 1984. We implement competition among intra-surface artificial neurons, and all connections are non-recursive artificial neural networks that go from bottom to top. It can also be expanded to multiple layers, although many fault layers are commonly used. Linear functions are used by active functions of artificial nerve cells, and learning rules use Instar rules as well as general competitive learning. The core of the backpropagation model is the model that performs classification by supervised learning as an artificial neural network. We grouped and transformed investor-specific transaction volume data to learn backpropagation models through the self-organizing map model of artificial neural networks. As a result of the estimation of verification data through training, the portfolios were rebalanced monthly. For performance analysis, a passive portfolio was designated and the KOSPI 200 and KOSPI index returns for proxies on market returns were also obtained. Performance analysis was conducted using the equally-weighted portfolio return, compound interest rate, annual return, Maximum Draw Down, standard deviation, and Sharpe Ratio. Buy and hold returns of the top 10 market capitalization stocks are designated as a benchmark. Buy and hold strategy is the best strategy under the efficient market hypothesis. The prediction rate of learning data using backpropagation model was significantly high at 96.61%, while the prediction rate of verification data was also relatively high in the results of the 57.1% verification data. The performance evaluation of self-organizing map grouping can be determined as a result of a backpropagation model. This is because if the grouping results of the self-organizing map model had been poor, the learning results of the backpropagation model would have been poor. In this way, the performance assessment of machine learning is judged to be better learned than previous studies. Our portfolio doubled the return on the benchmark and performed better than the market returns on the KOSPI and KOSPI 200 indexes. In contrast to the benchmark, the MDD and standard deviation for portfolio risk indicators also showed better results. The Sharpe Ratio performed higher than benchmarks and stock market indexes. Through this, we presented the direction of portfolio composition program using machine learning and investor-specific transaction information and showed that it can be used to develop programs for real stock investment. The return is the result of monthly portfolio composition and asset rebalancing to the same proportion. Better outcomes are predicted when forming a monthly portfolio if the system is enforced by rebalancing the suggested stocks continuously without selling and re-buying it. Therefore, real transactions appear to be relevant.

• Journal of Korean Society of Steel Construction
• /
• v.16 no.3 s.70
• /
• pp.305-314
• /
• 2004

Many residential buildings and mixed-use (i.e., residential and commercial) buildings that are currently under construction in the country mainly consist of building clusters rather than single structures. Recent trends show single buildings that actually consist of two houses. The lower part of the building consists of a single dwelling space. However, the upper part of the building is split into two dwellings, considering the aspects of commercialism and appearance, such as ventilation and lighting. These tall and complex buildings not only have low mass and damping. They also depend on wind loads for their structural stability and serviceability, due to the interaction between the building groups and the wind. In architectural design, however, the interaction effects among neighboring houses within a building group have yet to be identified. In addition, it is difficult to predict these interaction effects. In this regard, this thesis aims to model patterns of architecture, which consist of two houses that are existing or under construction. Current structures are investigated by comparing their wind-reduced response interaction effects, based on the measured distance between two buildings, and the acceleration response through the wind tunnel test. The results of this study are expected to provide basic data for wind-induced response interaction effects of building groups. Furthermore, the outcomes are also intended to be used as data for more rational and economical structure design.

• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.60 no.3
• /
• pp.343-348
• /
• 2015

Soybean is one of the important food crop around the world. Especially in East Asia, it is the main ingredient for traditional food like soy sauce and soy paste. The double cropping system including soybean following onion, Chinese cabbage, and potato is widely adopted in Southern region of Korea. In this system, sowing date of second crop (soybean) can be delayed depending on first crops' growth period and weather condition. When planting date is delayed it is known that soybean yield is declined because of shorter vegetative growth period and earlier flowering induced by warm temperature and changes in photoperiod. The objective of this study was to determine soybean growth and yield responses as plant populations at late planting date. Field experiment was conducted at Department of Functional Crop, National Institute of Crop Science, RDA located in Miryang, Gyeongsangnam-Do for two years ('13-'14) in upland field with mid-late maturity cultivar Daewon. A split-plot block design was used with three replications. Main plots were three sowing dates from June 20 to July 20 with 15 days intervals, and subplots were 4 levels of planting densities. Data of maturity (R8) was recorded, yield components and yield were examined after harvesting. Experimental data were analyzed by using PROC GLM, and DMRT were used for mean comparison. Optimum planting population for maximizing soybean yield in late planting which compared with standard population. In mid-June planting, higher planting density causes increased plant height and decreased diameter which lead to higher risk of lodging, however, reduced growth period due to late planting alleviated this problem. Therefore higher seeding rates can provide protection against low seedling emergence caused by late planting in this region.

• Toxicological Research
• /
• v.24 no.1
• /
• pp.37-44
• /
• 2008

The in vitro cell transformation assays (CTA) were performed using BALB/3T3 murine fibroblasts and HaCaT human keratinocytes in order to evaluate concordance between both in vitro CTAs and carcinogenicity with compounds differing in their genotoxic and carcinogenic potential. Six test articles were evaluated, two each from three classes of compounds: genotoxic carcinogens (2-amino-5-nitrophenol and 4-nitroquinoline-N-oxide), genotoxic noncarcinogens (8-hydroxyquinoline and benzyl alcohol), and nongenotoxic carcinogens (methyl carbamate and N-nitrosodiphenylamine). Any foci of size $\geq$2 mm regardless of invasiveness and piling was scored as positive in CTA with BALB/3T3. As expected, four carcinogens regardless of their genotoxicity had positive outcomes in two-stage CTA using BALB/3T3 cells. However, of the two genotoxic noncarcinogens, benzyl alcohol was positive CTA finding. We concluded that, of the 6 chemicals tested, the sensitivity for BALB/3T3 system was reasonably high, being 100%. The respective specificity for BALB/3T3 assay was 50%. We also investigated the correlation between results of BALB/3T3 assay and results from HaCaT assay in order to develop a reliable human cell transformation assay. However, evaluation of staining at later time points beyond the confluency stage did not yield further assessable data because most of HaCaT cells were detached after $2{\sim}3$ days of confluency. Thus, after test article treatment, HaCaT cells were split before massive cell death began. In this modified protocol for this HaCaT system, growing attached colonies were counted instead of transformed foci 3 weeks since last subculture. Compared to BALB/3T3 assay, HaCaT assay showed moderate low sensitivity and high specificity. Despite these differences in specificity and sensitivity, both cell systems did exhibit same good concordance between in vitro CTA and rodent carcinogenicity findings (overall 83% concordant results). At present the major weakness of these in vitro CTA is lack of validation for regulatory acceptance and use. Thus, more controlled studies will be needed in order to be better able to assess and quantitatively estimate in vitro CTA data.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.10
• /
• pp.94-105
• /
• 2020

Recently, most studies of 3D printing in construction have focused on the development of 3D printers and materials suitable for construction 3D printers. In comparison, there has been little research on design support tools that enable representative BIM data of building modeling tools to be applied to 3D printing. In addition, existing 3D printing slicing programs are commercialized around manufacturing, showing that they are unsuitable for construction 3D printing. Therefore, this research aims to develop a design support tool for 3D printing for buildings. The developed design support tool was validated based on arbitrary BIM data. Verification showed that wall pattern generation was modeled accurately without errors, and a calculation of the construction period showed that the formula presented in this study was valid. Furthermore, the maximum length of the mesh split was set to 100mm to minimize errors when converting to STL files.