• Analyses & Alternatives
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• v.8 no.1
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• pp.169-196
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• 2024

In the House of the Parliament of Kazakhstan, which members are re-elected several times, while others are only first-term? Existing studies on the Kazakhstan political elites have mainly discussed the effect of clans on the appointment or replacement of elites. These studies have contributed to explaining the characteristics of Kazakhstan's clientelistic political structure, but the analysis of the relationship between political background and elite appointment or replacement is very poor. The purpose of this study is to analyze what characteristics of members have continuity in the 4th to 8th House of the Parliament of Kazakhstan. As a result, members with activities in Communist Party of the Soviet Union had a higher average seniority than those who did not in the 4th, 6th, and 7th House of the Parliament. And Nur Otan members had a higher average seniority than those who did not in 4th and 5th House of the Parliament. On the other hand, there was no difference in average seniority by local political experience, and the difference by elite type was only partially found in the 6th House of the Parliament. These results reflect the president's strategy for parliamentary control in that the parliament is used as a means of solidifying Kazakhstan's political regime as an authoritarian state. The significance of this study is that for the first time it empirically proved who sustains political survival in the House of the Parliament of Kazakhstan.

• The Journal of the Korean dental association
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• v.52 no.4
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• pp.203-217
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• 2014

Bisphosphonates are widely used in the treatment of many medical conditions, such as osteoporosis, multiple myeloma, Paget's disease, etc. However, side effect has been documented in the published data during the past years, osteonecrosis of the jaw in patients receiving long-term bisphosphonate therapy. Although pathogenesis of BRONJ(bisphophonate-related osteonecrosis of the jaw) is not yet fully understood, it is currently known to be a disease associated with suppressed bone turnover by bisphopbonate. Recent literature has indicated a similar association with nonbisphosphonate drugs used in cancer therapy including monoclonal antibodies denosumab and bevacizumab and multikinase inhibitor sunitinib. Accordingly, many studies have been carried out on the biochemical markers examination to assess the risk for BRONJ. The treatment of BRONI is reported with a review of the relevant literature. However, there is still a controversial discussion about the adequate treatment. It is necessary to accumulate further studies in order to establish more useful biochemical markers and effective treatment for BRONJ.

• Journal of Navigation and Port Research
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• v.39 no.3
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• pp.261-266
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• 2015

Many of previous studies suggested that working capital management is an important component of firm's financial decision and efficient working capital management affects firms' profitability and it's value. Recently, Korean shipping firms have been suffering from financial distress by recession of shipping economy. In this point of view, this study tries to investigate the relationship between working capital management and shipping firm's profitability, using panel data on 46 Korean shipping firms for the period of 2004-2013. As result of panel regression, it proved that average payment period, inventory turnover, cash conversion cycle and operating cycle are significantly associated with firms profitabilities such as profit margin ratio and operating profit ratio, and the manager of shipping firm can increase firms profitability by more efficient working capital management. There are strong positive relationships between average payment period and operating cycle and firm's profitability. These results suggest that managers can create firm's value by increasing average payment period and operating cycle. Otherwise inventory turnover and cash conversion cycle have negative relationships with firm's profitability. It means that managers can increase firm's profitability by reducing these variables.

• Knowledge Management Research
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• v.25 no.2
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• pp.19-47
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• 2024

Organizational ability to analyze and utilize data plays an important role in knowledge management and decision-making. This study aims to investigate the potential application of large language models in corporate data analysis. Focusing on the field of human resources, the research examines the data analysis capabilities of these models. Using the widely studied IBM HR dataset, the study reproduces machine learning-based employee turnover prediction analyses from previous research through ChatGPT and compares its predictive performance. Unlike past research methods that required advanced programming skills, ChatGPT-based machine learning data analysis, conducted through the analyst's natural language requests, offers the advantages of being much easier and faster. Moreover, its prediction accuracy was found to be competitive compared to previous studies. This suggests that large language models could serve as effective and practical alternatives in the field of corporate data analysis, which has traditionally demanded advanced programming capabilities. Furthermore, this approach is expected to contribute to the popularization of data analysis and the spread of data-driven decision-making (DDDM). The prompts used during the data analysis process and the program code generated by ChatGPT are also included in the appendix for verification, providing a foundation for future data analysis research using large language models.

• Journal of the Korean Association of Geographic Information Studies
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• v.12 no.2
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• pp.23-33
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• 2009

Satellite image is very usefully practiced to predict and analyze physical expansion and change of city. Physical expansion and change of city is closely related to the use of land, and continuous growth management focused on the use of land is essential for sustainable city growth. In this research, the change of land cover and land-use were analyzed with basic input data from 1985 to 2000 according to artificial satellite. Moreover, the land-use turnover rate was understood and expansion trend of urban sprawl in Busan metropolitan city and land-use characteristics of the expansion area. The results are, first, the area for urban region was expanded continuously but areas for agriculture area, forest area, and water area had different changes due to administrative district reform of Busan by each year. Second, the urbanization area in Busan was increased by 3.8% from $92.5km^2$ in 1985 to $167.5km^2$ in 2000. Third, the result of analysis on land-use turnover rate showed that agriculture area was turned into urbanized area the most, and forest area was followed by. Fourth, the result of analysis on database and overlay of buildings in Busan established in 2001 showed that agriculture area are had type 1 and 2 neighborhood living facilities (45.63%), apartment house in forest area (18.49%), and factory in water area (31.84%) with high ratio.

• Journal of Korean Clinical Nursing Research
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• v.25 no.3
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• pp.221-236
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• 2019

Purpose: The purpose of this study was to systematically review and identify factors relevant to the positive psychological capital of clinical nurses. Methods: These was no limit on year of publication. Articles related to Korean clinical nurses were retrieved from computerized database using a manual search. A systematic review was conducted based on the PRISMA flow. The total correlational effect size (ESr) for each related factor was calculated from Fisher's Zr. Funnel plots, fail-safe numbers, and Egger regression tests were used to evaluate publication bias in meta-analysis studies. The correlational effect size of 25 studies was analyzed through meta-analysis using Comprehensive Meta-Analysis software 3.0 (CMA). Results: The review included 25 studies. In the systematic review, 14 demographic factors and 46 organizational factors were found to be influential. Eleven factors (6 demographic factors and 5 organizational factors) were appropriate for meta-analysis. The overall effect size was .26. The demographic total correlation effect size of related factors was .20 and the total effect size of organization was .46. Organizational commitment (ESr=.38) and job satisfaction (ESr=.54) were statistically positively related variables. Negative variables were burnout (ESr=-.61), turnover intention (ESr=-.41) and workplace bullying (ESr=-.33). The total effect size of the organizational factors was larger than the demographic total effect size. There was no publication bias except for demographic variables. Conclusion: Organizational factors and adjustable variables have a significant impact on positive psychological capital. The results of this study support the need for development of interventions focusing on organizational factors.

• Management & Information Systems Review
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• v.28 no.3
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• pp.25-44
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• 2009

The purpose of this paper is to examine the determinants which cause a price differential between common and preferred stock. Prior studies have shown that variables like liquidity, size, the number of outstanding shares issued can explain the price differential between common and preferred stock price. Based on year 2006 through year 2008 data, we analyzed the determinants using regression model. Dummy variables representing large/small company and KSE/KOSDAQ respectively are added and analyzed as independent variables. The firm size, trade volume turnover, and the number of preferred shares to total outstanding shares were proved to make influence on the price differential under the 5% significance level. Especially, we have found the number of preferred shares to total outstanding shares provide the most strong relationship with the price differential. This means that a high ratio of preferred stock to total outstanding shares leads to relatively high value of common stock and causes a big price differential.

• The korean journal of orthodontics
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• v.54 no.1
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• pp.26-47
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• 2024

Objective: This systematic review aimed to evaluate the correlation between vitamin D levels and the rate of tooth movement, external apical root resorption, bone biomarker expression, and bone remodeling. Methods: Three databases (PubMed, Scopus, and Web of Science) were systematically searched from inception until 14th March 2023 to identify studies investigating the correlation between orthodontic tooth movement and vitamin D in animals and humans. The quality assessment was made in accordance with the Joanna Briggs Institute Critical Appraisal Checklist. Results: Overall, 519 records were identified, and 19 were selected for the qualitative synthesis. Eleven studies investigated the effect of local administration (injections in the periodontal ligament, to the gingiva distal to the teeth, or submucosae palatal area) and systemic administration (oral supplementation) of vitamin D on tooth movement, external apical root movement, pro-inflammatory cytokines, and bone remodeling factors. The remaining eight studies investigated the correlation between serum vitamin D levels and salivary vitamin D levels on bone turnover markers and tooth movement. Conclusions: The findings of this systematic review support that vitamin D3 local injections might increase the rate of tooth movement via the receptor activator of the nuclear factor-kB/osteoprotegerin axis. However, the non-uniform study designs and the different protocols and outcome methods make it challenging to draw reliable conclusions.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.79-99
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• 2015

The prediction of bankruptcy has been extensively studied in the accounting and finance field. It can have an important impact on lending decisions and the profitability of financial institutions in terms of risk management. Many researchers have focused on constructing a more robust bankruptcy prediction model. Early studies primarily used statistical techniques such as multiple discriminant analysis (MDA) and logit analysis for bankruptcy prediction. However, many studies have demonstrated that artificial intelligence (AI) approaches, such as artificial neural networks (ANN), decision trees, case-based reasoning (CBR), and support vector machine (SVM), have been outperforming statistical techniques since 1990s for business classification problems because statistical methods have some rigid assumptions in their application. In previous studies on corporate bankruptcy, many researchers have focused on developing a bankruptcy prediction model using financial ratios. However, there are few studies that suggest the specific types of bankruptcy. Previous bankruptcy prediction models have generally been interested in predicting whether or not firms will become bankrupt. Most of the studies on bankruptcy types have focused on reviewing the previous literature or performing a case study. Thus, this study develops a model using data mining techniques for predicting the specific types of bankruptcy as well as the occurrence of bankruptcy in Korean small- and medium-sized construction firms in terms of profitability, stability, and activity index. Thus, firms will be able to prevent it from occurring in advance. We propose a hybrid approach using two artificial neural networks (ANNs) for the prediction of bankruptcy types. The first is a back-propagation neural network (BPN) model using supervised learning for bankruptcy prediction and the second is a self-organizing map (SOM) model using unsupervised learning to classify bankruptcy data into several types. Based on the constructed model, we predict the bankruptcy of companies by applying the BPN model to a validation set that was not utilized in the development of the model. This allows for identifying the specific types of bankruptcy by using bankruptcy data predicted by the BPN model. We calculated the average of selected input variables through statistical test for each cluster to interpret characteristics of the derived clusters in the SOM model. Each cluster represents bankruptcy type classified through data of bankruptcy firms, and input variables indicate financial ratios in interpreting the meaning of each cluster. The experimental result shows that each of five bankruptcy types has different characteristics according to financial ratios. Type 1 (severe bankruptcy) has inferior financial statements except for EBITDA (earnings before interest, taxes, depreciation, and amortization) to sales based on the clustering results. Type 2 (lack of stability) has a low quick ratio, low stockholder's equity to total assets, and high total borrowings to total assets. Type 3 (lack of activity) has a slightly low total asset turnover and fixed asset turnover. Type 4 (lack of profitability) has low retained earnings to total assets and EBITDA to sales which represent the indices of profitability. Type 5 (recoverable bankruptcy) includes firms that have a relatively good financial condition as compared to other bankruptcy types even though they are bankrupt. Based on the findings, researchers and practitioners engaged in the credit evaluation field can obtain more useful information about the types of corporate bankruptcy. In this paper, we utilized the financial ratios of firms to classify bankruptcy types. It is important to select the input variables that correctly predict bankruptcy and meaningfully classify the type of bankruptcy. In a further study, we will include non-financial factors such as size, industry, and age of the firms. Thus, we can obtain realistic clustering results for bankruptcy types by combining qualitative factors and reflecting the domain knowledge of experts.

• Journal of muscle and joint health
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• v.21 no.3
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• pp.255-264
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• 2014

Purpose: The purpose of the study were to analyze the research trends of compassion fatigue in Korea nurses and to suggest future research directions. Methods: For this study, RISS, KISTI, KISS, National Assembly Library databases were searched using the key words 'compassion fatigue', 'secondary traumatic stress', 'professional quality of life' that contains compassion fatigue as a sub-element, and 'nurses' for this study. A total of 124 articles published in June 2014 were searched and analyzed 19 articles for the final analysis. Results: The most frequently used study design was descriptive (N=17, 89.5%). High compassion fatigue was reported in this study. Factors affecting compassion fatigue were personal factors (e.g., age, health state, and sleep hours), work-related factors (e.g., experience with traumatized patients), and psychological factors (e.g., job stress, anxiety, excessive empathy, social support, and coping strategy). Finally, Consequence factors of compassion fatigue was reported burnout, silencing response and turnover intention. Conclusion: There was a few studies on compassion fatigue. Further research on compassion fatigue needs to use a variety of study designs instruments suitable for Korean nurses, and to develop management programs on compassion fatigue in nurses.