• Journal of Korea Port Economic Association
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• v.39 no.2
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• pp.77-95
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• 2023

The regional infrastructure industries of Gwangyang City, the subject of this study, are Gwangyang Port and Gwangyang Steel Mill. Therefore, it is necessary to analyze the regional economic ripple effects of the port logistics industry in Gwangyang City. In this study, a multi-stage approach using the RW and the LQ methodology using the national input-output tables in 2015 and 2019 is used to prepare the regional interindustry analysis chart in Gwangyang City, and an exogenous demand induction model that reclassified the port logistics industry was applied. Through this, the purpose of this study was to provide policy implications by figuring out the regional economic ripple effects of the port logistics industry quantitatively in Gwangyang City. As a result of the analysis, the industries with high production inducement effect and forward/backward linkage effect of the port logistics industry in Gwangyang City were analyzed as manufacturing, transportation, land and air logistics sectors. And the industries in which the added value inducement effect and the employment inducement effect were analyzed as an industry related to the service industry. Therefore, it is necessary to prepare support measures to foster the port logistics industry as a way to promote these industries and revitalize the local economy of Gwangyang City. To this end, it is desirable to improve policies and systems for the vitalization of the Gwangyang port maritime cluster and provide various policy support for the port logistics industry in Gwangyang City. This study is meaningful in suggesting policy implications for the regional economy of Gwangyang City based on the results of exogenous analysis of the port logistics industry in small and medium-sized cities. However, It seems that further studies related to this will be needed in the future.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.1-10
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• 2023

This paper proposes a method to extend Inter-Carrier Interference (ICI) canceling Orthogonal Frequency Division Multiplexing (OFDM) receivers for 5G mobile systems to spatial multiplexing 2×2 MIMO (Multiple Input Multiple Output) systems to support high-speed ground transportation services by linear motor cars traveling at 500 km/h. In Japan, linear-motor high-speed ground transportation service is scheduled to begin in 2027. To expand the coverage area of base stations, 5G mobile systems in high-speed moving trains will have multiple base station antennas transmitting the same downlink (DL) signal, forming an expanded cell size along the train rails. 5G terminals in a fast-moving train can cause the forward and backward antenna signals to be Doppler-shifted in opposite directions, so the receiver in the train may have trouble estimating the exact channel transfer function (CTF) for demodulation. A receiver in such high-speed train sees the transmission channel which is composed of multiple Doppler-shifted propagation paths. Then, a loss of sub-carrier orthogonality due to Doppler-spread channels causes ICI. The ICI Canceller is realized by the following three steps. First, using the Demodulation Reference Symbol (DMRS) pilot signals, it analyzes three parameters such as attenuation, relative delay, and Doppler-shift of each multi-path component. Secondly, based on the sets of three parameters, Channel Transfer Function (CTF) of sender sub-carrier number n to receiver sub-carrier number l is generated. In case of n≠l, the CTF corresponds to ICI factor. Thirdly, since ICI factor is obtained, by applying ICI reverse operation by Multi-Tap Equalizer, ICI canceling can be realized. ICI canceling performance has been simulated assuming severe channel condition such as 500 km/h, 8 path reverse Doppler Shift for QPSK, 16QAM, 64QAM and 256QAM modulations. In particular, 2×2MIMO QPSK and 16QAM modulation schemes, BER (Bit Error Rate) improvement was observed when the number of taps in the multi-tap equalizer was set to 31 or more taps, at a moving speed of 500 km/h and in an 8-pass reverse doppler shift environment.

• Journal of the Korea Society for Simulation
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• v.32 no.4
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• pp.77-84
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• 2023

In the agricultural sector, power sources are being developed that use alternative energy sources such as electric tractors and hydrogen tractors, away from internal combustion engine tractors. As parts such as engines and transmissions used in conventional internal combustion engine tractors are replaced with motors and batteries, the center of gravity changes, and thus the risk of rollover should be considered. The purpose of this study is to analyze the overturn angle of the main parts of the electric tractor through dynamic simulation to minimize the overturn accident and to derive the optimal arrangement of parts to improve stability. A total of nine dynamics simulations were conducted by designing three components of the PTO motor, drive motor and the battery pack, and three factors of the arrangement method. As a result of the experiment, it was confirmed that Type3 Level3, in which the drive motor and the PTO motor are located at the front and rear of the tractor, and two battery packs are located in the middle of the tractor, has a high rollover angle. As a result of this study, the stability increased as the center of gravity was placed backward and located below. Future research needs to be done to find the optimal location of parts considering their performance and placement efficiency.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.4
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• pp.51-63
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• 2023

The purpose of this study is to develop and implement a secondary teacher training program based on the TPACK model to strengthen the capacity of teachers of youth entrepreneurship education in the context of the increasing importance of entrepreneurship as a future competency, and to provide theoretical and practical implications based on it. To this end, a teacher training program was developed through the process of analysis, design, development, implementation, and evaluation based on the ADDIE model, and 22 secondary school teachers in Gangwon Province were trained and the effectiveness and validity were analyzed. First, the results of the paired sample t-test of TPACK in entrepreneurship education conducted before and after the program showed statistically significant improvements in all sub-competencies. Second, the satisfaction survey of the training program showed that the overall satisfaction was high with M=4.83. Third, the validity of the program was reviewed by three experts, and it was found to be highly valid with a validity of M=5.0, usefulness of M=4.7, and universality of M=5.0. Based on the results, it is suggested that in order to expand entrepreneurship education, opportunities for teachers' holistic capacity building such as TPACK should be expanded, teachers' understanding and practice of backward design should be promoted, and access to various resources that can be utilized in entrepreneurship education should be improved.

• Journal of Industrial Convergence
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• v.22 no.2
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• pp.97-103
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• 2024

The purpose of this study was to examine the impact of balance training on the Inbody and recovery of the balance capability in stroke patient with obesity. The exercise program was to conduct obesity group and normal weight group, 22 subjects were divided equally into experimental(obesity) and controlled group(normal weight), assigned to excercise using the balance training system for 30min a day and 5 days a week. Every pre and post-experimental data of both groups were gathered by Inbody and BSS(Biodex Medical Systems) for 8 weeks. As a result, Comparing the intra-group data measured by Inbody, obesity group showed significant difference in every parameter (p<.05). In the inter-group data, every parameter showed significant difference between both groups (p<.05). Comparing the intra-group data of LOS(Limits Of Stability), obesity group showed significant difference with all parameters, except with 'Backward' and 'Left' (p<.05). In the inter-group data, 'Forward' parameter showed significant difference. Comparing the intra-group data of PS(Postural Stability), obesity group showed significant difference with all parameters (p<.05). The inter-group PS(Postural Stability) results differed significantly only with 'Med/lat'(p=.000). The above results implicate about the following conclusions that the balance training had a big effect on the Inbody and recovery of the balance capability in stroke patient with obesity.

• Korean Journal of Radiology
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• v.23 no.8
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• pp.811-820
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• 2022

Objective: To develop a model incorporating radiomic features and clinical factors to accurately predict acute ischemic stroke (AIS) outcomes. Materials and Methods: Data from 522 AIS patients (382 male [73.2%]; mean age ± standard deviation, 58.9 ± 11.5 years) were randomly divided into the training (n = 311) and validation cohorts (n = 211). According to the modified Rankin Scale (mRS) at 6 months after hospital discharge, prognosis was dichotomized into good (mRS ≤ 2) and poor (mRS > 2); 1310 radiomics features were extracted from diffusion-weighted imaging and apparent diffusion coefficient maps. The minimum redundancy maximum relevance algorithm and the least absolute shrinkage and selection operator logistic regression method were implemented to select the features and establish a radiomics model. Univariable and multivariable logistic regression analyses were performed to identify the clinical factors and construct a clinical model. Ultimately, a multivariable logistic regression analysis incorporating independent clinical factors and radiomics score was implemented to establish the final combined prediction model using a backward step-down selection procedure, and a clinical-radiomics nomogram was developed. The models were evaluated using calibration, receiver operating characteristic (ROC), and decision curve analyses. Results: Age, sex, stroke history, diabetes, baseline mRS, baseline National Institutes of Health Stroke Scale score, and radiomics score were independent predictors of AIS outcomes. The area under the ROC curve of the clinical-radiomics model was 0.868 (95% confidence interval, 0.825-0.910) in the training cohort and 0.890 (0.844-0.936) in the validation cohort, which was significantly larger than that of the clinical or radiomics models. The clinical radiomics nomogram was well calibrated (p > 0.05). The decision curve analysis indicated its clinical usefulness. Conclusion: The clinical-radiomics model outperformed individual clinical or radiomics models and achieved satisfactory performance in predicting AIS outcomes.

• Journal of Dental Rehabilitation and Applied Science
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• v.39 no.4
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• pp.214-221
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• 2023

In order to fabricate stable dentures in patients with severe resorption of residual ridges, various factors must be considered. One of them is the neutral zone, which is defined as the potential region in which the pressure of the tongue outward in the oral cavity and the pressure of the cheeks and lips directed inward from the outside of the oral cavity equalize during functioning. In patients with severe ridge resorption, if the teeth are usually arranged above the residual ridge, the teeth are located on the lingual side rather than the original position. Therefore, the functional space of the tongue is invaded, the tongue is positioned backward, and the sealing of the lingual border is broken, which acts as a factor reducing the maintenance of denture. In addition, it is also important for the stability of dentures to assume an interalveolar crest line connecting the maxillary and mandibular ridge crests, and to arrange the maxillary and mandibular artificial teeth to match the masticatory force to the interalveolar crest line. Therefore, good clinical results were obtained by fabricating dentures for the patient with poor alveolar residual ridge using neutral zone impression and ridge relationship analysis.

• Particle and aerosol research
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• v.19 no.4
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• pp.111-128
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• 2023

Chungcheongnam-do has various emission sources, including large-scale facilities such as power plants, steel and petrochemical industry complexes, which can lead to the severe PM pollution. Here, we measured concentrations of PM₁₀, PM_2.5, and its metallic elements at a suburban site in Taean, Chungcheongnam-do from September 2017 to June 2022. During the measurement period, the average concentrations of PM₁₀ and PM_2.5 were 58.6 ㎍/m³ (9.6~379.0 ㎍/m³) and 35.0 ㎍/m³ (6.1~132.2 ㎍/m³), respectively. The concentration of PM₁₀ and PM_2.5 showed typical seasonal variation, with higher concentration in winter and lower concentration in summer. When high concentrations of PM_2.5 occurred, particulary in winter, the fraction of Zn and Pb components considerably increased, indicating a significant contribution of Zn and Pb to high-PM_2.5 concentration. In addition, Zn and Pb exhibited the highest correlation coefficient among all other metallic elements of PM_2.5. A backward trajectory cluster analysis and CPF model were performed to examine the origin of PM_2.5. The high concentration of PM_2.5 was primarily influenced by emissions from industrial complexes located in the northeast and northwest areas.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.139-157
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• 2016

Bankruptcy involves considerable costs, so it can have significant effects on a country's economy. Thus, bankruptcy prediction is an important issue. Over the past several decades, many researchers have addressed topics associated with bankruptcy prediction. Early research on bankruptcy prediction employed conventional statistical methods such as univariate analysis, discriminant analysis, multiple regression, and logistic regression. Later on, many studies began utilizing artificial intelligence techniques such as inductive learning, neural networks, and case-based reasoning. Currently, ensemble models are being utilized to enhance the accuracy of bankruptcy prediction. Ensemble classification involves combining multiple classifiers to obtain more accurate predictions than those obtained using individual models. Ensemble learning techniques are known to be very useful for improving the generalization ability of the classifier. Base classifiers in the ensemble must be as accurate and diverse as possible in order to enhance the generalization ability of an ensemble model. Commonly used methods for constructing ensemble classifiers include bagging, boosting, and random subspace. The random subspace method selects a random feature subset for each classifier from the original feature space to diversify the base classifiers of an ensemble. Each ensemble member is trained by a randomly chosen feature subspace from the original feature set, and predictions from each ensemble member are combined by an aggregation method. The k-nearest neighbors (KNN) classifier is robust with respect to variations in the dataset but is very sensitive to changes in the feature space. For this reason, KNN is a good classifier for the random subspace method. The KNN random subspace ensemble model has been shown to be very effective for improving an individual KNN model. The k parameter of KNN base classifiers and selected feature subsets for base classifiers play an important role in determining the performance of the KNN ensemble model. However, few studies have focused on optimizing the k parameter and feature subsets of base classifiers in the ensemble. This study proposed a new ensemble method that improves upon the performance KNN ensemble model by optimizing both k parameters and feature subsets of base classifiers. A genetic algorithm was used to optimize the KNN ensemble model and improve the prediction accuracy of the ensemble model. The proposed model was applied to a bankruptcy prediction problem by using a real dataset from Korean companies. The research data included 1800 externally non-audited firms that filed for bankruptcy (900 cases) or non-bankruptcy (900 cases). Initially, the dataset consisted of 134 financial ratios. Prior to the experiments, 75 financial ratios were selected based on an independent sample t-test of each financial ratio as an input variable and bankruptcy or non-bankruptcy as an output variable. Of these, 24 financial ratios were selected by using a logistic regression backward feature selection method. The complete dataset was separated into two parts: training and validation. The training dataset was further divided into two portions: one for the training model and the other to avoid overfitting. The prediction accuracy against this dataset was used to determine the fitness value in order to avoid overfitting. The validation dataset was used to evaluate the effectiveness of the final model. A 10-fold cross-validation was implemented to compare the performances of the proposed model and other models. To evaluate the effectiveness of the proposed model, the classification accuracy of the proposed model was compared with that of other models. The Q-statistic values and average classification accuracies of base classifiers were investigated. The experimental results showed that the proposed model outperformed other models, such as the single model and random subspace ensemble model.

• Journal of agricultural medicine and community health
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• v.39 no.3
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• pp.176-186
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• 2014

Objectives: As a sequel to the former analysis of the quality of life (QoL) among young-old and old-old in Korea, this research was aimed to identify factors related to the quality of life and the gender difference after controlling for the related factors among Korean elderly. Methods: Selected elderly data of 1,339 subjects from the 5th Korea National Health and Nutrition Examination Survey conducted in 2010 was analyzed. In this survey, QoL was measured using Euro Quality of Life (EQ-5D) instrument. Data were analyzed using complex survey data analysis on IBM-SPSS 20.0. The related factors were identified using general linear models with backward elimination. The gender difference was tested also using general linear models. Results: The distributions of educational level, family income level, and presence of cohabitant were different between male and female elderly in both young-old and old-old age group. So were the health behaviors and perceived health, and experience of stress, depression, and suicidal thoughts. QoL and its subscales- mobility, self care, daily living, pain and discomfort, and anxiety and depression- were consistently better among male elderly regardless of age group. Among the variables considered, education, family income level, presence of cohabitant, perceived health, age group and BMI were found to be related to the QoL at p=.05, and presence of chronic diseases at p=.10. The difference in QoL between male and female elderly after controlling for the variables was statistically significant. Conclusion: Improving QoL is particularly important for the elderly. In order to improve QoL of the elderly, age- and gender- differences need to be considered when developing services and programs for the elderly.