• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• 제26권3호
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• pp.226-235
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• 2015

Objectives : The purpose of this study was to examine the factor structure of the Adolescent Personality Assessment Inventory (PAI-A) in a standardized adolescent sample using exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). Methods : For this purpose, three models about factor structure of the PAI-A were explored with EFA in 490 adolescents and then were evaluated with CFA in 268 young offenders. Results : The results showed that the five factor model was considered to be most appropriate for factor structures of the PAI-A in EFA. However, none of the factor models were appropriate for the factor structures of the PAI-A in CFA. Conclusion : These findings suggest that the "five factor model" is thought to explain the PAI-A the best, but further studies are needed.

• International Journal of Computer Science & Network Security
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• 제23권1호
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• pp.89-95
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• 2023

Analyzing breast cancer patient files is becoming an exciting area of medical information analysis, especially with the increasing number of patient files. In this paper, breast cancer data is collected from Khartoum state hospital, and the dataset is classified into recurrence and no recurrence. The data is imbalanced, meaning that one of the two classes have more sample than the other. Many pre-processing techniques are applied to classify this imbalanced data, resampling, attribute selection, and handling missing values, and then different classifiers models are built. In the first experiment, five classifiers (ANN, REP TREE, SVM, and J48) are used, and in the second experiment, meta-learning algorithms (Bagging, Boosting, and Random subspace). Finally, the ensemble model is used. The best result was obtained from the ensemble model (Boosting with J48) with the highest accuracy 95.2797% among all the algorithms, followed by Bagging with J48(90.559%) and random subspace with J48(84.2657%). The breast cancer imbalanced dataset was classified into recurrence, and no recurrence with different classified algorithms and the best result was obtained from the ensemble model.

• 전기학회논문지
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• 제63권7호
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• pp.956-961
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• 2014

Due to the increasing needs of anti-fall device for elderly, it is required to develop the test rigs for fall simulation. The femoral bone model consists of silicone and steel is used as an effective device to simulate falls. In this work, we propose five different femoral bone models and analyse them by using a commercial FEA tool. It has been shown that two kinds of simplified models exhibit the simulated side falls with an error range of ~1% in the impact load of femoral neck compared with full model. Especially, the upper tissue model is found to provide us with the best efficient test environment, attributable to its simple structure.

• 통합자연과학논문집
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• 제9권1호
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• pp.41-61
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• 2016

Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related mortality worldwide. Phosphoinositide 3-kinases (PI3Ks) play important role in Non-Small Cell Lung Cancer. PI3Ks constitute a lipid kinase family which modulates the function of numerous substrates involved in the regulation of cell survival, cell cycle progression and cellular growth. Herein, we describe the ligand based pharmacophore combined with molecular docking studies methods to identify new potent PI3K inhibitors. Several pharmacophore models were generated and validated by Guner-Henry scoring Method. The best models were utilized as 3D pharmacophore query to screen against ZINC database (Chemical and Natural) and the retrieved hits were further validated by fitness score, Lipinski's rule of five. Finally four compounds were found to have good potential and they may act as novel lead compounds for PI3K inhibitor designing.

• 보건행정학회지
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• 제27권1호
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• pp.18-29
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• 2017

Background: In Korea, the problem of physician workforce imbalances has been a debated issue for a long time. This study aimed to draw key lessons and policy implications to Korea by analyzing projection models of physician demand/supply among five countries. Methods: We adopted theoretical framework and analyzed detail indicators used in projection models of demand/supply comparatively among countries. A systematic literature search was conducted using PubMed and Google Scholar with key search terms and it was complimented with hand searching of grey literature in Korean or English. Results: As a results, Korea has been used a supply-based traditional approach without taking various variables or environmental factors influencing on demand/supply into consideration. The projection models of USA and Netherlands which considered the diversity of variables and political issues is the most closest integrated approach. Based on the consensus of stakeholder, the evolved integrated forecasting approach which best suits our nation is needed to minimize a wasteful debate related to physician demand/supply. Also it is necessary to establish the national level statistics indices and database about physician workforce. In addition, physician workforce planning will be discussed periodically. Conclusion: We expect that this study will pave the way to seek reasonable and developmental strategies of physician workforce planning.

• Computers and Concrete
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• 제9권6호
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• pp.439-455
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• 2012

The interaction of plan geometry and structural configuration, a determinative factor in the earthquake behavior of buildings, has become a serious issue in the building industry in Turkey due to the poor seismic performance of R/C buildings during the latest earthquake. Consequently, designing new buildings without structural irregularities against earthquake loads is proving to be more significant. This study focuses on the effects of plan geometries on earthquake performances of buildings. In that respect, structural irregularities in the plan are investigated in detail based on the Turkish Earthquake Code (TEC 2007). The study is based on five main parametric models and a total of 40 sub-models that are grouped according to their plan geometries with excessive projections such as L-shaped, H-shaped, T-shaped and U-shaped models. In addition to these, a square model without any projections is also generated. All models are designed to have the same storey gross area but with different number of storeys. Changes in the earthquake behavior of buildings were evaluated according to the number of storeys, the projection ratios and the symmetry conditions of each model. The analysis of each structural irregularity resulted in many findings, which were then assessed. The study demonstrates that the square model delivers the best earthquake performance owing to its regular plan geometry.

• STI Policy Review
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• 제6권1호
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• pp.85-110
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• 2015

Science and technology diplomacy has become an important policy agenda because of its diplomatic utility and enhancing of international science networks. However, different countries possess different objectives and governance of S&T diplomacy. In this context, this paper seeks to answer the following questions: what are the similarities and differences of S&T diplomacy in countries and what shapes these characteristics? To answer these questions, this paper conducts a comparative case study with five countries - Switzerland, Germany, Japan, the United Kingdom, and the United States - whose S&T diplomatic programs are highly recognized and benchmarked by other countries. A useful typology is devised to conduct a systematic comparison. For S&T diplomatic objectives, this paper suggests five types by elaborating concepts from the previous literature: access diplomacy, promotion diplomacy, public aid diplomacy, functional diplomacy, and global leadership diplomacy. Also, in terms of a governance model for S&T diplomacy, three models - a sciencecentered model, a science-outsourcing model and a top-down coordinating model - are suggested based on leadership organization. This paper reveals the different characteristics of the selected countries in S&T diplomacy. While the selected countries pursue almost every type of S&T diplomatic objective, the US and the UK tend to conduct influence-based diplomacy more than other countries do. In addition, different countries each have unique governance models for S&T diplomacy. While more research is necessary for vigorously testing the causes of different objectives and their relationship with governance models, this paper suggests more general policy implications throughout. The strength of the country's S&T base is fundamentally important for the success of S&T diplomacy. However, domestic S&T assets need to be transferred to its diplomatic capabilities. In this sense, the appropriate governance that fits best with the country's S&T mission should be established, while S&T communities should increasingly play a leadership role in evolving global S&T networks.

• Tuberculosis and Respiratory Diseases
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• 제86권3호
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• pp.203-215
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• 2023

Background: Surgical resection is the standard treatment for early-stage lung cancer. Since postoperative lung function is related to mortality, predicted postoperative lung function is used to determine the treatment modality. The aim of this study was to evaluate the predictive performance of linear regression and machine learning models. Methods: We extracted data from the Clinical Data Warehouse and developed three sets: set I, the linear regression model; set II, machine learning models omitting the missing data: and set III, machine learning models imputing the missing data. Six machine learning models, the least absolute shrinkage and selection operator (LASSO), Ridge regression, ElasticNet, Random Forest, eXtreme gradient boosting (XGBoost), and the light gradient boosting machine (LightGBM) were implemented. The forced expiratory volume in 1 second measured 6 months after surgery was defined as the outcome. Five-fold cross-validation was performed for hyperparameter tuning of the machine learning models. The dataset was split into training and test datasets at a 70:30 ratio. Implementation was done after dataset splitting in set III. Predictive performance was evaluated by R² and mean squared error (MSE) in the three sets. Results: A total of 1,487 patients were included in sets I and III and 896 patients were included in set II. In set I, the R² value was 0.27 and in set II, LightGBM was the best model with the highest R² value of 0.5 and the lowest MSE of 154.95. In set III, LightGBM was the best model with the highest R² value of 0.56 and the lowest MSE of 174.07. Conclusion: The LightGBM model showed the best performance in predicting postoperative lung function.

• 한국농공학회지
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• 제38권4호
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• pp.110-124
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• 1996

This study was conducted to simulate long seres of synthetic monthly flows by multi-season first order Markov model with selection of best fitting frequency distribution, harmonic synthetic and harmonic regression models and to make a comparison of statistical parameters between observes and synthetic flows of five watersheds in Geum river system. The results obtained through this study can be summarized as follow. 1. Both gamma and two parameter lognormal distributions were found to be suitable ones for monthly flows in all watersheds by Kolmogorov-Smirnov test. 2. It was found that arithmetic mean values of synthetic monthly flows simulated by multi-season first order Markov model with gamma distribution are much closer to the results of the observed data in comparison with those of the other models in the applied watersheds. 3. The coefficients of variation, index of fluctuation for monthly flows simulated by multi-season first order Markov model with gamma distribution are appeared closer to those of the observed data in comparison with those of the other models in Geum river system. 4. Synthetic monthly flows were simulated over 100 years by multi-season first order Markov model with gamma distribution which is acknowledged as a suitable simulation modal in this study.

• 대한임베디드공학회논문지
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• 제18권4호
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• pp.165-172
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• 2023

Heterogeneous computing is a technology that utilizes different types of processors to perform parallel processing. It maximizes task processing and energy efficiency by leveraging various computing resources such as CPUs, GPUs, and FPGAs. On the other hand, edge computing has developed with IoT and 5G technologies. It is a distributed computing that utilizes computing resources close to clients, thereby offloading the central server. It has evolved to intelligent edge computing combined with artificial intelligence. Intelligent edge computing enables total data processing, such as context awareness, prediction, control, and simple processing for the data collected on the edge. If heterogeneous computing can be successfully applied in the edge, it is expected to maximize job processing efficiency while minimizing dependence on the central server. In this paper, experiments were conducted to verify the feasibility of various parallel programming models on high-end and low-end edge devices by using benchmark applications. We analyzed the performance of five parallel programming models on the Raspberry Pi 4 and Jetson Orin Nano as low-end and high-end devices, respectively. In the experiment, OpenACC showed the best performance on the low-end edge device and OpenSYCL on the high-end device due to the stability and optimization of system libraries.