• KDI Journal of Economic Policy
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• v.30 no.2
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• pp.129-155
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• 2008

The rate of antibiotics prescription for an acute airway infection significantly varies depending upon the diagnosis type, specialty, and the location of the hospital along with many other related factors. The objective of this study is to empirically investigate the possible relationship between the antibiotics prescription rates for an acute airway infection and the degree of competition in the hospital market regions of mainly the providers of primary medical care services such as clinics, internal medicines, pediatrics and otorhinolaryngology department. Using the data from Health Insurance Review and Assessment Service (HIRA) regarding the hospitals' antibiotics prescription rates for the acute airway infection and controlling for selected variables of demand and supply sectors, this study tries to figure out that the degree of competition in the hospital market, regardless of what type of competition indexes we employed, has a statistically significant effect on the variations of antibiotics prescription rate of the clinics in local areas. This result implies that as an economic consideration itself, the change in the degree of competition in the hospital market can play a crucial role influencing the treatment behaviors of the medical doctors. More specifically, this study reveals that as the degree of competition increases the antibiotics prescription rate goes up. This result means that if the market becomes more competitive in a specific region so that it might cause a reduction in doctor's income, doctors with rational decision-making process, recognize that the benefit created from inducing patients' seemingly unnecessary demand for medical care (income effect) would be higher than the costs associated with sustaining their targeted income (substitution effect). It is because that the doctors are more likely to prescribe antibiotics which create relatively higher margins than other medical care services in order to sustain their targeted income when the hospital market competition becomes tighter. Even though this study empirically confirms that antibiotics prescription can be affected by the economic incentives, it still raises following issues as limitations of the study: first issue is about the representativeness of the hospital regions segregated for this study, which might be weak in explaining whether these regions are mutually exclusive in reality. Patients actually consider the quality of services, transportation cost, time costs, and any other related factors choosing the doctors or hospitals, and in that sense, this study rules out 'border-crossing' in using the medical care services. Second issue arises in capturing the data of antibiotics prescription rate. Since we use the average rate for each medical institution, we cannot figure out the average rate for each patient so that we are not able to control for the variation of patients' medical conditions. It is because of the unavailability of data regarding each patient's medical condition from HIRA. Thirdly, since this study mainly analyzes the medical institutions providing primary care such as clinics, internal medicines, pediatrics, and otorhinolaryngology department, it is skeptical of whether those institutions can represent the hospital market in respective regions and truly reflect the degree of competition. It needs to extend the study areas and disease types as well as any micro data for future studies.

• Economic Analysis
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• v.26 no.1
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• pp.1-33
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• 2020

Recent discussions about a minimum wage increase (MWI) and its influence on the economy have mainly focused on the quantitative aspects, such as labor costs and employment. However, concerning the qualitative aspects, an MWI could have positive effects by enhancing firm productivity and crowding out marginal firms from the market. These positive effects of an MWI can offset, to some extent, its potential negative effects - increasing labor costs and decreasing employment, among others. In this regard we empirically examine the impact of an MWI on firm productivity (total factor productivity). Using firm level panel data from the manufacturing industry in Korea, we calculate the influence rates of a minimum wage by sector and by firm size (number of workers), and analyze its effects on firm productivity. In particular, the production functions of the firms are estimated by taking into account endogeneity among the input factors, in order to resolve the drawbacks of existing studies - underestimating the capital factor coefficient and overestimating the labor factor coefficient. This study finds that the influences of an MWI on wages, employment, and productivity are substantially different across sectors and firm sizes. While an MWI has shown to have positive influences on productivity growth in the manufacturing industry as a whole, each sector demonstrates a different direction of effect, and the degree of productivity change also varies by sector. The impacts of an MWI on firm productivity are generally estimated to be more negative for smaller firms, but in some sectors the effects are found to be positive. In addition, the wage increases resulting from an MWI seem to cause a productivity enhancement across all sectors in the manufacturing industry. The policy implications of this study are as follows. Considering the empirical findings that an MWI causes an increase in productivity in many sectors of the manufacturing industry, it would be desirable to take into consideration not only the negative side effects but also the positive effects of an MWI when designing any future minimum wage policy. Moreover, in spite of there being a uniform minimum wage, this study finds that the diverse influence rates of a minimum wage across firms have different impacts on wages, employment, and productivity across sectors or firm size. This finding could be conducive to discussions about differentiation among minimum wage schemes by sector or firm size.

• The Transactions of the Korea Information Processing Society
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• v.5 no.10
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• pp.2575-2583
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• 1998

The productionof the highly relible softwae systems and theirs performance evaluation hae become important interests in the software industry. The software evaluation has been mainly carried out in ternns of both reliability and performance of software system. Software reliability is the probability that no software error occurs for a fixed time interval during software testing phase. These theoretical software reliability models are sometimes unsuitable for the practical testing phase in which a software error at a certain testing stage occurs by causes of the imperfect debugging, abnornal software correction, and so on. Such a certatin software testing stage needs to be considered as an outlying stage. And we can assume that the software reliability does not improve by means of muisance factor in this outlying testing stage. In this paper, we discuss Bavesian software reliability growth modeling and estimation procedure in the presence of an imidentitied outlying software testing stage by the modification of Jehnski Moranda. Also we derive the Bayes estimaters of the software reliability panmeters by the assumption of prior information under the squared error los function. In addition, we evaluate the proposed software reliability growth model with an unidentified outlying stage in an exchangeable model according to the values of nuisance paramether using the accuracy, bias, trend, noise metries as the quantilative evaluation criteria through the compater simulation.

• Journal of Korean Society of Environmental Engineers
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• v.33 no.1
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• pp.25-31
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• 2011

In this study, model-based $NH_4-N$ predictive control algorithm by using influent pattern was developed and evaluated for effective control application in $A^2/O$ process. A pilot-scale $A^2/O$process at S wastewater treatment plant in B city was selected. The behaviors of organic, nitrogen and phosphorous in the biological reactors were described by using the modified ASM3+Bio-P model. A one-dimensional double exponential function model was selected for modeling of the secondary settlers. The effluent $NH_4-N$ concentration on the next day was predicted according to model-based simulation by using influent pattern. After the objective effluent quality and simulation result were compared, the optimal operational condition which able to meet the objective effluent quality was deduced through repetitive simulation. Next the effluent $NH_4-N$ control schedule was generated by using the optimal operational condition and this control schedule on the next day was applied in pilot-scale $A^2/O$ process. DO concentration in aerobic reactor in predictive control algorithm was selected as the manipulated variable. Without control case and with control case were compared to confirm the control applicability and the study of the applied $NH_4-N$control schedule in summer and winter was performed to confirm the seasonal effect. In this result, the effluent $NH_4-N$concentration without control case was exceeded the objective effluent quality. However the effluent $NH_4-N$ concentration with control case was not exceeded the objective effluent quality both summer and winter season. As compared in case of without predictive control algorithm, in case of application of predictive control algorithm, the RPM of air blower was increased about 9.1%, however the effluent $NH_4-N$ concentration was decreased about 45.2%. Therefore it was concluded that the developed predictive control algorithm to the effluent $NH_4-N$ in this study was properly applied in a full-scale wastewater treatment process and was more efficient in aspect to stable effluent.

• The Mathematical Education
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• v.62 no.3
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• pp.435-455
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• 2023

This study primarily focused on the development of an Explainable Artificial Intelligence (XAI) model to discern and analyze papers with significant impact in the field of mathematics education. To achieve this, meta-information from 29 domestic and international mathematics education journals was utilized to construct a comprehensive academic research network in mathematics education. This academic network was built by integrating five sub-networks: 'paper and its citation network', 'paper and author network', 'paper and journal network', 'co-authorship network', and 'author and affiliation network'. The Random Forest machine learning model was employed to evaluate the impact of individual papers within the mathematics education research network. The SHAP, an XAI model, was used to analyze the reasons behind the AI's assessment of impactful papers. Key features identified for determining impactful papers in the field of mathematics education through the XAI included 'paper network PageRank', 'changes in citations per paper', 'total citations', 'changes in the author's h-index', and 'citations per paper of the journal'. It became evident that papers, authors, and journals play significant roles when evaluating individual papers. When analyzing and comparing domestic and international mathematics education research, variations in these discernment patterns were observed. Notably, the significance of 'co-authorship network PageRank' was emphasized in domestic mathematics education research. The XAI model proposed in this study serves as a tool for determining the impact of papers using AI, providing researchers with strategic direction when writing papers. For instance, expanding the paper network, presenting at academic conferences, and activating the author network through co-authorship were identified as major elements enhancing the impact of a paper. Based on these findings, researchers can have a clear understanding of how their work is perceived and evaluated in academia and identify the key factors influencing these evaluations. This study offers a novel approach to evaluating the impact of mathematics education papers using an explainable AI model, traditionally a process that consumed significant time and resources. This approach not only presents a new paradigm that can be applied to evaluations in various academic fields beyond mathematics education but also is expected to substantially enhance the efficiency and effectiveness of research activities.

• Journal of Korea Spatial Information System Society
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• v.6 no.1 s.11
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• pp.73-85
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• 2004

Recently, as the growth of the wireless Internet, PDA and HPC, the focus of research and development related with GIS(Geographic Information System) has been changed to the Real-Time Mobile GIS to service LBS. To offer LBS efficiently, there must be the Real-Time GIS platform that can deal with dynamic status of moving objects and a location index which can deal with the characteristics of location data. Location data can use the same data type(e.g., point) of GIS, but the management of location data is very different. Therefore, in this paper, we studied the Real-Time Mobile GIS using the HBR-tree to manage mass of location data efficiently. The Real-Time Mobile GIS which is developed in this paper consists of the HBR-tree and the Real-Time GIS Platform HBR-tree. we proposed in this paper, is a combined index type of the R-tree and the spatial hash Although location data are updated frequently, update operations are done within the same hash table in the HBR-tree, so it costs less than other tree-based indexes Since the HBR-tree uses the same search mechanism of the R-tree, it is possible to search location data quickly. The Real-Time GIS platform consists of a Real-Time GIS engine that is extended from a main memory database system. a middleware which can transfer spatial, aspatial data to clients and receive location data from clients, and a mobile client which operates on the mobile devices. Especially, this paper described the performance evaluation conducted with practical tests if the HBR-tree and the Real-Time GIS engine respectively.

• Journal of the Institute of Convergence Signal Processing
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• v.9 no.1
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• pp.31-38
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• 2008

Ad-Hoc network is a network architecture which has no backbone network and is deployed temporarily and rapidly in emergency or war without fixed mobile infrastructures. All communications between network entities are carried in ad-hoc networks over the wireless medium. Due to the radio communications being extremely vulnerable to propagation impairments, connectivity between network nodes is not guaranteed. Therefore, many new algorithms have been studied recently. This study proposes the secondary header approach to the cluster based routing protocol (CBRP). The primary header becomes abnormal status so that the primary header can not participate in the communications between network entities, the secondary header immediately replaces the primary header without selecting process of the new primary header. This improves the routing interruption problem that occurs when a header is moving out from a cluster or in the abnormal status. The performances of proposed algorithm ACBRP(Advanced Cluster Based Routing Protocol) are compared with CBRP. The cost of the primary header reelection of ACBRP is simulated. And results are presented in order to show the effectiveness of the algorithm.

• Food Science and Preservation
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• v.17 no.3
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• pp.418-424
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• 2010

Although the wine industry continues to grow, little empirical research on consumer preferences has been conducted. Thus, our objective was to analyze consumer views on wine attributes. A choice experiment (CE) was designed to detect a marginal willingness to pay for particular characteristics of wine (balance, flavor, color, clarity, and value-for-money). A questionnaire was administered and 286 responses were received. A multinomial logit model was estimated using the maximum likelihood method. The results indicated that balance, flavor, color, clarity, and price were all important to consumers. The CE data revealed that estimates of marginal willingness to pay were 31,899 won/bottle for balance, 23,088 won/bottle for flavor, 3,230 won/bottle for color, and 25,936 won/bottle for clarity. The balance of a wine was most important, and the flavor, clarity, and color were also significant. The results of this work will be of assistance in promoting the domestic wine industry.

• Journal of Korean Society of Transportation
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• v.34 no.1
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• pp.43-54
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• 2016

Although there are continuous demands for activating BSSs(Bicycle Sharing Systems) due to the convenience and positive health effects, it is difficult to make a decision to support the existing systems and build more systems because of the deficit resulting from the operation of BSSs. Consequently, this study estimated the economic effects(WTP; Willingness to Pay) of BSS and analyzed the impact factors of WTP to support the above decision making in Daejeon. For this, we conducted a survey and collected 668 samples from the users and non-users of TASHU that is the BSS operated in Daejeon. Also, we used CVM(Contingent Valuation Method) for the estimation of WTP. The results show that the number of bicycle uses is a determinant factor having a positive relationship with WTP and car ownership and age are also determinant factors having a negative relationship with WTP. On the other hand, income and sex have no significant statistical relationship with WTP. Also, the economic benefit of TASHU was estimated as much as 49.9 billion KRW to 63.6 billion KRW. Considering the operation cost of 2.5 billion KRW, it is quite big benefit. Based on the results, it needs to support TASHU from a user perspective for the efficient operation of the system.

• Journal of Digital Convergence
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• v.10 no.10
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• pp.221-227
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• 2012

In Korea, ocean dumping has been widely used as the ultimate disposal of sewage sludge. However, ocean dumping of food wasted and sewage sludge from 2013 is expected to legally restricted as London convention on marine pollution prevention has been effective in 2009. This research aims to examine the effect of HEAS in treating the environmental pollution load caused by organic high concentrated sludge. Thus, onsite laboratory scale treatability test using HEAS was adopted to treat the high concentrated organic sludge from sewage and industrial wastewater treatment plant. The research results showed that the HEAS is useful to reduce the environmental pollution caused by organic high concentrated sludge. Specific results are as follows. 1. The organic removal after the sludge digestion using the high efficiency aeration system was 55.2-85.8%. Although these results were lower than those from the general sewage treatment, the high efficiency aeration system could be evaluated as efficient, considering the object sludge contained the industrial waster water. 2. The average removal efficiency was about 25.2%. 3. It was revealed that sludge digestion by the high efficiency aeration system could effectively contribute to the sludge treatment cost. Especially, the high efficiency aeration system is more applicable to the onsite treatment of small sewage and wastewater treatment plant that contains high solid content sludge, industrial wastewater sludge, high fixed solid sludge.