• Korean Journal of Culture and Social Issue
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• v.29 no.1
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• pp.1-23
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• 2023

The purpose of this study was to validate the Suicidal Ideation Attributes Scale(SIDAS) which can measure the severity of suicidal ideation in a sample of 399 Korean adults. For this purpose, an online survey was conducted for two weeks from July 2020 to August 2020. First, there were differences in SIDAS scores among groups divided by gender, residence status, depression and anxiety symptoms, suicidal ideation, suicidal plan, suicidal preparation, and suicidal attempt. Second, correlations between SIDAS, C-SSRS suicidal ideation intensity question(3 items), and the Rosenberg Self-efficacy (RSE) were examined to confirm the validity of SIDAS. As a result, correlations between the SIDAS and suicidal ideation intesity items of C-SSRS were significant in all items, while correlations between the SIDAS and RSE items were negative or insignificant. Third, as a result of the confirmatory factor analysis of SIDAS on all respondents and respondents with suicidal ideation, a single factor structure was appropriate for both groups. Internal consistency of SIDAS was also good. Lastly, as a result of identifying the variables affecting the suicidal plan over the past year, controllability and age were identified as significant predictive variables. SIDAS which was designed to be administered through web, can be appropriately used in Korea. It was confirmed that SIDAS is a reliable and valid suicidal ideation scale which is applicable to adults in Korea.

• Journal of The Korean Society of Clinical Toxicology
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• v.20 no.2
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• pp.58-65
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• 2022

Purpose: Alcohol is one of the most commonly co-ingested agents in deliberate self-poisoning (DSP) cases presenting at the emergency department (ED). The increased impulsivity, aggressiveness, and disinhibition caused by alcohol ingestion may have different clinical features and outcomes in cases of DSP. This study investigates whether alcohol co-ingestion affects the clinical features and outcomes of DSP patients in the ED. Methods: This was a single-center retrospective study. We investigated DSP cases who visited our ED from January 2010 to December 2016. Patients were classified into two groups: with (ALC+) or without (ALC-) alcohol co-ingestion. The clinical features of DSP were compared by considering the co-ingestion of alcohol, and the factors related to discharge against medical advice (AMA) of DSP were analyzed. Results: A total of 689 patients were included in the study, with 272 (39.5%) in the ALC+ group. Majority of the ALC+ group patients were middle-aged males (45-54 years old) and arrived at the ED at night. The rate of discharge AMA from ED was significantly higher in the ALC+ group (130; 47.8%) compared to the ALC- group (p=0.001). No significant differences were obtained in the poisoning severity scores between the two groups (p=0.223). Multivariate analysis revealed that alcohol co-ingestion (odds ratio [OR]=1.42; 95% confidence interval [CI], 1.01-1.98), alert mental status (OR=1.65; 95% CI, 1.17-2.32), past psychiatric history (OR=0.04; 95% CI, 0.01-0.28), age >65 years (OR=0.42; 95% CI, 0.23-0.78), and time from event to ED arrival >6 hrs (OR=0.57; 95% CI, 0.37-0.88) were independent predictive factors of discharge AMA (p=0.043, p=0.004, p=0.001, p=0.006, and p=0.010, respectively). Conclusion: Our results determined a high association between alcohol co-ingestion and the outcome of discharge AMA in DSP patients. Emergency physicians should, therefore, be aware that DSP patients who have co-ingested alcohol may be uncooperative and at high risk of discharge AMA.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.2
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• pp.59-76
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• 2023

Since the COVID-19 era, the rise in apartment prices has been unconventional. In this uncertain real estate market, price prediction research is very important. In this paper, a model is created to predict the actual transaction price of future apartments after building a vast data set of 870,000 from 2015 to 2020 through data collection and crawling on various real estate sites and collecting as many variables as possible. This study first solved the multicollinearity problem by removing and combining variables. After that, a total of five variable selection algorithms were used to extract meaningful independent variables, such as Forward Selection, Backward Elimination, Stepwise Selection, L1 Regulation, and Principal Component Analysis(PCA). In addition, a total of four machine learning and deep learning algorithms were used for deep neural network(DNN), XGBoost, CatBoost, and Linear Regression to learn the model after hyperparameter optimization and compare predictive power between models. In the additional experiment, the experiment was conducted while changing the number of nodes and layers of the DNN to find the most appropriate number of nodes and layers. In conclusion, as a model with the best performance, the actual transaction price of apartments in 2021 was predicted and compared with the actual data in 2021. Through this, I am confident that machine learning and deep learning will help investors make the right decisions when purchasing homes in various economic situations.

• Resources Recycling
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• v.31 no.6
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• pp.81-91
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• 2022

The use of lithium-ion batteries increases significantly with the rapid spread of electronic devices and electric vehicle and thereby an increase in the amount of waste batteries is expected in the near future. Therefore, studies are continuously being conducted to recover various resources of cathode active material (Ni, Co, Mn, Li) from waste battery. In order to recover the cathode active material, black mass is generally recovered from waste battery. The general process of recovering black mass is a waste battery collection - discharge - dismantling - crushing - classification process. This study focus on the crushing/classification process among the processes. Specifically, the particle size distribution of various samples at each crushing/classification step were evaluated, and the particle shape of each particle fraction was analyzed with a microscope and SEM (Scanning Electron Microscopy)-EDS(Energy Dispersive Spectrometer). As a result, among the black mass particle, fine particle less than 74 ㎛ was the mixture of cathode and anode active material which are properly liberated from the current metals. However, coarse particle larger than 100 ㎛ was present in a form in which the current metal and active material were combined. In addition, this study developed a PBM(Population Balance Model) system that can simulate two-species mixture sample with two different crushing properties. Using developed model, the breakage parameters of two species was derived and predictive performance of breakage distribution was verified.

• Journal of the Korean Geotechnical Society
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• v.22 no.6
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• pp.15-26
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• 2006

Although numerous investigations have been performed over the years to predict the behavior and bearing capacity of piles, the mechanisms are not yet entirely understood. The prediction of bearing capacity is a difficult task, because large numbers of factors affect the capacity and also have complex relationship one another. Therefore, it is extremely difficult to search the essential factors among many factors, which are related with ground condition, pile type, driving condition and others, and then appropriately consider complicated relationship among the searched factors. The present paper describes the application of Artificial Neural Network (ANN) in predicting the capacity including its components at the tip and along the shaft from dynamic load test of the driven piles. Firstly, the effect of each factor on the value of bearing capacity is investigated on the basis of sensitivity analysis using ANN modeling. Secondly, the authors use the design methodology composed of ANN and genetic algorithm (GA) to find optimal neural network model to predict the bearing capacity. The authors allow this methodology to find the appropriate combination of input parameters, the number of hidden units and the transfer structure among the input, the hidden and the out layers. The results of this study indicate that the neural network model serves as a reliable and simple predictive tool for the bearing capacity of driven piles.

• Journal of The Korean Society of Grassland and Forage Science
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• v.42 no.1
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• pp.1-9
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• 2022

This study was carried out to compare the DMY (dry matter yield) of IRG (Italian ryegrass) in the southern coastal regions of Korea due to seasonal climate scenarios such as the Kaul-Changma (late monsoon) in autumn, extreme winter cold, and drought in the next spring. The IRG data (n = 203) were collected from various Reports for Collaborative Research Program to Develop New Cultivars of Summer Crops in Jeju, 203 Namwon, and Yeungam from the Rural Development Administration - (en DASH). In order to define the seasonal climate scenarios, climate variables including temperature, humidity, wind, sunshine were used by collected from the Korean Meteorological Administration. The discriminant analysis based on 5% significance level was performed to distinguish normal and abnormal climate scenarios. Furthermore, the DMY comparison was simulated based on the information of sample distribution of IRG. As a result, in the southern coastal regions, only the impact of next spring drought on DMY of IRG was critical. Although the severe winter cold was clearly classified from the normal, there was no difference in DMY. Thus, the DMY comparison was simulated only for the next spring drought. Under the yield comparison simulation, DMY (kg/ha) in the normal and drought was 14,743.83 and 12,707.97 respectively. It implies that the expected damage caused by the spring drought was about 2,000 kg/ha. Furthermore, the predicted DMY of spring drought was wider and slower than that of normal, indicating on high variability. This study is meaningful in confirming the predictive DMY damage and its possibility by spring drought for IRG via statistical simulation considering seasonal climate scenarios.

• Journal of the Korea Convergence Society
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• v.13 no.1
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• pp.399-408
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• 2022

The purpose of this study was to compare the usefulness of the lipid ratio indicators for the diagnosis of metabolic syndrome in the elderly aged 65 years or older. From January 2018 to December 2020, 1,464 people aged 65 years or older who underwent a health checkup at a general hospital in Seoul were included. Lipid ratio indicators were measured through blood tests. The prevalence of metabolic syndrome according to the quartiles of the lipid ratio index was confirmed by logistic regression analysis. In addition, the metabolic syndrome predictive ability and cutoff value of the lipid ratio indices were estimated with the receiver operating characteristic(ROC) curve. The correlation between atherogenic index of plasma(AIP) and waist circumference was the highest in both men and women(r=0.278, p<0.001 vs r=0.252, p<0.001). As for the lipid ratio indices, the incidence of metabolic syndrome was higher in the fourth quartile than in the first quartile. The area under the ROC curve(AUC) value of AIP was higher at 0.826(95% CI=0.799-0.850) and 0.852(95% CI=0.820-0.881) for men and women, respectively, compared to other lipid ratio indicators, and the optimal cutoff values for both men and women was 0.44(p<0.001). Therefore, the AIP among the lipid ratio indicators was found to be the most useful index for diagnosing metabolic syndrome in the elderly aged 65 years or older.

• Journal of Cadastre & Land InformatiX
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• v.52 no.2
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• pp.211-231
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• 2022

This study attempted to identify the effects of macroeconomic variables such as the All Industry Production Index, Consumer Price Index, CD Interest Rate, and KOSPI on apartment lease prices divided into nationwide, Seoul, metropolitan, and region, and to present a methodological prediction model of apartment lease prices by region using Long Short Term Memory (LSTM). According to VAR analysis results, the nationwide apartment lease price index and consumer price index in Lag1 and 2 had a significant effect on the nationwide apartment lease price, and likewise, the Seoul apartment lease price index, the consumer price index, and the CD interest rate in Lag1 and 2 affect the apartment lease price in Seoul. In addition, it was confirmed that the wide-area apartment jeonse price index and the consumer price index had a significant effect on Lag1, and the local apartment jeonse price index and the consumer price index had a significant effect on Lag1. As a result of the establishment of the LSTM prediction model, the predictive power was the highest with RMSE 0.008, MAE 0.006, and R-Suared values of 0.999 for the local apartment lease price prediction model. In the future, it is expected that more meaningful results can be obtained by applying an advanced model based on deep learning, including major policy variables

• Journal of the Korean Applied Science and Technology
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• v.40 no.2
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• pp.199-209
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• 2023

This study is a descriptive research to identify the factors that influence blood donation intentions of the middle-aged firefighters and prison officer based on Ajzen's (1991) planned behavior theory. The subjects of the study were 223 middle-aged firefighters and prison officer at a fire station and prison located in G City and District B. The Data were analyzed by descriptive statistics and t-test, one-way ANOVA, Pearson's correlation coefficient, Turkey, and multiple regression with the SPSS 21.0 program. There were statistically significant differences in blood donation intention according to the blood donation experience, attempted blood donation within a year, participate plan in blood donation within 3 months. The blood donation intention of middle aged showed significant positive correlations with attitude, subjective norms, and perceived behavioral control towards blood donation. Multiple regression analysis for blood donation intention revealed that the significant predictors were participate plan in blood donation within 3 months, perceived behavior control, subjective norms, attitude towards blood donation, and attempted blood donation within a year. These factors explained 69% of the variance. In order to enhance the middle aged's intention to blood donation, we need a program that can improve middle aged's attitude, subjective norms, perceived behavior control.

• Journal of the Korean Orthopaedic Association
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• v.52 no.1
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• pp.73-82
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• 2017

Purpose: To assess the chronological changes of disease-related kyphosis after chemotherapy alone. Materials and Methods: A total of 101 children aged 2 to 15 years with spinal tuberculosis, accompanied by various stages of disease processes were enrolled for analysis. By utilizing the images in them, the growth plate condition and chronological changes of kyphosis after chemotherapy were analyzed at two points in time; the first assessment was at post-chemotherapy one-year and second at the final discharge. Results: Complete disc destruction in the cervical, dorsal and lumbosacral spines was observed in 2 out of 40 children (5.0%), 8 out of 30 children (26.7%), and 6 out of 31 children (19.4%), respectively. In those cases, the residual kyphosis inevitably developed. In the remaining children, the discs were intact or partially damaged. Among the 101 children kyphotic deformity was maintained without change in 20 children (19.8%). Kyphosis decreased in 14 children (13.9%), while it increased in 67 children (66.3%) with non-recoverably damaged growth plate. Conclusion: Although it is tentatively possible to predict the deformity progress or non-progress and spontaneous correction at the time of the initial treatment, its predictive accuracy is low. Therefore, assessment of the chronological changes should be performed at the end of chemotherapy. In children with progressive curve change, assessment of deformity should be continued until maturity.