• Journal of Korean Neurosurgical Society
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• v.66 no.1
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• pp.90-94
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• 2023

Objective : Cubital tunnel syndrome, the most common ulnar nerve entrapment neuropathy, is usually managed by simple decompression or anterior transposition. One of the concerns in transposition is damage to the nerve branches around the elbow. In this study, the location of ulnar nerve branches to the flexor carpi ulnaris (FCU) was assessed during operations for cubital tunnel syndrome to provide information to reduce operation-related complications. Methods : A personal series (HJY) of cases operated for cubital tunnel syndrome was reviewed. Cases managed by transposition and location of branches to the FCU were selected for analysis. The function of the branches was confirmed by intraoperative nerve stimulation and the location of the branches was assessed by the distance from the center of medial epicondyle. Results : There was a total of 61 cases of cubital tunnel syndrome, among which 31 were treated by transposition. Twenty-one cases with information on the location of branches were analyzed. The average number of ulnar nerve branches around the elbow was 1.8 (0 to 3), only one case showed no branches. Most of the cases had one branch to the medial head, and one other to the lateral head of the FCU. There were two cases having branches without FCU responses (one branch in one case, three branches in another). The location of the branches to the medial head was 16.3±8.6 mm distal to the medial epicondyle (16 branches; range, 0 to 35 mm), to the lateral head was 19.5±9.5 mm distal to the medial epicondyle (19 branches; range, -5 to 30 mm). Branches without FCU responses were found from 20 mm proximal to the medial condyle to 15 mm distal to the medial epicondyle (five branches). Most of the branches to the medial head were 15 to 20 mm (50% of cases), and most to the lateral head were 15 to 25 mm (58% of cases). There were no cases of discernable weakness of the FCU after operation. Conclusion : In most cases of cubital tunnel syndrome, there are ulnar nerve branches around the elbow. Although there might be some cases with branches without FCU responses, most branches are to the FCU, and are to be saved. The operator should be watchful for branches about 15 to 25 mm distal to the medial epicondyle, where most branches come out.

• Journal of the Economic Geographical Society of Korea
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• v.25 no.4
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• pp.641-656
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• 2022

This article investigates how Baedal Minjok(BaeMin) has grown to be a dominant mobility platform operator in food delivery sector in South Korea and what roles its brand and branding have played in the process, drawing on the idea of origination. For the purpose, BaeMin is considered as a typical platformized mobility service provider and origination is framed to be an appropriate analytical lens for the business sector. For the origination conception, unlike mainstream neoclassical theory and concepts, is able to deal fairly well with the issues of imperfect competition, imperfect information, and monopolistic brand rent, which are apparent in today's platformized mobility services. Drawing evidence from textual data, empirical analysis pays particular attention to discursive and symbolic dimensions of BaeMin's socio-spatial biography. It is found that national origination underpinning ethnicity comprises an important pillar of BaeMin's brand and branding. Another form of place-based origination is also observed to matter, especially in the varied relation between the mobility service brand's owner and consumers. However, this configuration of BaeMin's brand origination has yet to be fully stabilized, as it has faced with serious challenges including brand vandalism and anti-brand movement especially since its merger to German food delivery platform giant Delivery Hero in 2020. This origination crisis moment appears to be associated with a series of contractions intrinsic to so-called 'platform capitalism'.

• Nuclear Engineering and Technology
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• v.26 no.1
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• pp.41-53
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• 1994

A SGTR accident postulated at Kori unit 1 is simulated with Mihama unit experience, which occurred on February 1991, to evaluate the capability of plant to cope with the transient. The system design and plant conditions of Kori Unit 1 are much similar with those of Mihama Unit 2. Therefore, special concern has been given to evaluate the sequence and the resulting consequence of the postulated SGTR accident at the Kori unit 1 An analysis is peformed as realistically as possible, with following the EOP of Kori unit 1. The result indicates that the leak through tube break terminates within about forty minutes, and the Kori unit 1 may be sufficient to cope with SGTR accident with same type of sequence. However, the reconsideration may be required for the design of Kori unit 1 which disconnects non-safety AC power from off-site power on SI signal generation. It may be pointed out that the content of EOP for SGTR accident is not enough to require operator's proper judgements. An analysis of SGTR accident tested in the LSTF which simulated the SGTR accident at the Mihama Unit 2 is peformed using the RELAP5/MOD3. The results indicates that the code yields in general good agreement with the test, except the break flowrate at the early stage of the event.

• Nuclear Engineering and Technology
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• v.27 no.6
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• pp.877-887
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• 1995

YGN 3 is the first nuclear power plant to use the Core Protection Calculator (CPC) as the core protection system and the Core Operating Limit Supervisory System (COLSS) as the core monitor-ing system in Korea. The CPC is designed to provide on-line calculations of Departure from Nucleate Boiling Ratio (DNBR) and Local Power Density (LPD) and to initiate reactor trip if the core conditions exceed the DNBR or LPD design limit. The COLSS is designed to assist the operator in implementing the Limiting Conditions for Operation (LCOs) in Technical Specifications for DNBR/Linear Heat Rate (LHR) margin, azimuthal tilt, and axial shape index and to provide alarm when the LCOs are reached. During YGN 3 initial startup testing, extensive CPC/COLSS related tests ore peformed to ver-ify the CPC/COLSS performance and to obtain optimum CPC/COLSS calibration constants at var, -ious core conditions. Most of test results met their specific acceptance criteria. In the case of missing the acceptance criteria, the test results ore analyzed, evaluated, and justified. Through the analysis and evaluation of each of the CPC/COLSS related test results, it can be concluded that the CPC/COLSS are successfully Implemented as designed at YGN 3.

• Journal of the Korea Society of Computer and Information
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• v.14 no.1
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• pp.217-228
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• 2009

Data analysis applications typically aggregate data across many dimensions looking for unusual patterns in data. Even though such applications are usually possible with standard structured query language (SQL) queries, the queries may become very complex. A complex query may result in many scans of the base table, leading to poor performance. Because online analytical processing (OLAP) queries are usually complex, it is desired to define a new operator for aggregation, called the data cube or simply cube. Data cube supports OLAP tasks like aggregation and sub-totals. Many aggregate functions can be used to construct a data cube. Those functions can be classified into three categories, the distributive, the algebraic, and the holistic. It has been thought that the distributive functions such as SUM, COUNT, MAX, and MIN can be used to construct a data cube, and also the algebraic function such as AVG can be used if the function is replaced to an intermediate function. It is believed that even though AVG is not distributive, but the intermediate function (SUM, COUNT) is distributive, and AVG can certainly be computed from (SUM, COUNT). In this paper, however, it is found that the intermediate function (SUM COUNT) cannot be applied to OLAP cubes, and consequently the function leads to erroneous conclusions and decisions. The objective of this study is to identify some problems in applying aggregate function AVG to OLAP cubes, and to design a process for solving these problems.

• The Korean Journal of Franchise Management
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• v.3 no.2
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• pp.20-38
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• 2012

After being introduced into franchises industry, franchise has made a phenomenal growth in a short time and a substantial contribution to job creation and economic revitalization. Nevertheless, franchise business operators failed a business or low profit because of a lack of information and indiscriminate foundation. Therefore the first object of this study is characteristics of franchise's factors on disclosure agreement in franchise associate website. second is examinations about casual relationship between factor and franchise performance with using Excel and SPSS 18.0 versions. The findings of present study were as follows. First, franchises manage small business mostly(financial data, scale so on) and franchise's type focused the food service industry. Specially, a business district select unprotected contract. Second, in franchise's factors, we could find statistically significant effect on annual average sales and annual average net profit. However growth rate of franchise don't have statistically significant effect. Third, we could find statistically significant difference on analysis both franchises' factors and financial data. In conclusion, we must consider of franchise industry environment and success effect on performance in starting one's business. Furthermore franchises plan ways for their sustained growth and protection of rights and interests. Finally business operator draw up their information and upgrade continuously for franchises industry growth. Discussion and theoretical and managerial implications of the results were described along with future franchise research suggestions.

• Tuberculosis and Respiratory Diseases
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• v.86 no.3
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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.

• The Journal of Bigdata
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• v.7 no.2
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• pp.153-172
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• 2022

Online shopping has transformed and rapidly grown the entire market at the forefront of wholesale and retail services as an effective solution to issues such as digital transformation and social distancing policy (COVID-19 pandemic). Small business owners, who form the majority at the center of the online shopping industry, are constantly collecting policy changes and market trend information to overcome these problems and use them for marketing and other sales activities in order to overcome these problems and continue to grow. Objective and refined information that is more closely related to the business is also needed. Therefore, in this paper, through the collection and analysis of big data information, which is the core technology of digital transformation, key variables are set in product classification, sales trends, consumer preferences, and review information of online shopping malls, and a method of using them for competitor comparison analysis and business sustainability evaluation has been prepared and we would like to propose it as a service. If small and medium-sized businesses can benchmark competitors or excellent businesses based on big data and identify market trends and consumer tendencies, they will clearly recognize their level and position in business and voluntarily strive to secure higher competitiveness. In addition, if the sustainable growth of the online shopping mall operator can be confirmed as an indicator, more efficient policy establishment and risk management can be expected because it has an improved measurement method.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.1D
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• pp.107-117
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• 2008

Private financing is playing an increasing role in public infrastructure construction projects worldwide. However, private investors/operators are exposed to the financial risk of low profitability due to the inaccurate estimation of facility demand, operation income, maintenance costs, etc. From the operator's perspective, a sound and thorough financial feasibility study is required to establish the appropriate capital structure of a project. Operators tend to reduce the equity amount to minimize the level of risk exposure, while creditors persist to raise it, in an attempt to secure a sufficient level of financial involvement from the operators. Therefore, it is important for creditors and operators to reach an agreement for a balanced capital structure that synthetically considers both profitability and repayment capacity. This paper presents an optimal capital structure model for successful private infrastructure investment. This model finds the optimized point where the profitability is balanced with the repayment capacity, with the use of the concept of utility function and multi-objective GA (Generic Algorithm)-based optimization. A case study is presented to show the validity of the model and its verification. The research conclusions provide a proper capital structure for privately-financed infrastructure projects through a proposed multi-objective model.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4D
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• pp.687-693
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• 2006

Image co-registration is the process of overlaying two images of the same scene, one of which represents a reference image, while the other is geometrically transformed to the one. In order to improve efficiency and effectiveness of the co-registration approach, the author proposed a pre-qualified area matching algorithm which is composed of feature extraction with canny operator and area matching algorithm with cross correlation coefficient. For refining matching points, outlier detection using studentized residual was used and iteratively removes outliers at the level of three standard deviation. Throughout the pre-qualification and the refining processes, the computation time was significantly improved and the registration accuracy is enhanced. A prototype of the proposed algorithm was implemented and the performance test of 3 Landsat images of Korea. showed: (1) average RMSE error of the approach was 0.435 pixel; (2) the average number of matching points was over 25,573; (3) the average processing time was 4.2 min per image with a regular workstation equipped with a 3 GHz Intel Pentium 4 CPU and 1 Gbytes Ram. The proposed approach achieved robustness, full automation, and time efficiency.