• Journal of the Korean Magnetic Resonance Society
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• v.27 no.4
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• pp.35-41
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• 2023

From a marine sponge Dysidea species, four new furanosesquiterterpenoids were isolated and characterized. Their structural elucidation was achieved through an extensive analysis employing NMR, MS data, and DFT method. Notably, all compounds shared as identical molecular formula. Compound 2 was identified as a derivative of compound 1, while compounds 3 and 4 exhibited an identical planar structure. Determination of the configurations of chiral centers in compounds 1 and 2 involved a comparative analysis between measured and calculated ECD spectra, along with the application of DP4+ probability analysis. Distinctly, the configurations of isomers 3 and 4 were established by scrutinizing proton chemical shifts based on the NOE correlation.

• Journal of Sensor Science and Technology
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• v.28 no.3
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• pp.182-186
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• 2019

When a camera is employed for 3D sensing, accurate camera calibration is vital as it is a prerequisite for the subsequent steps of the sensing process. Camera calibration is usually performed by complex mathematical modeling and geometric analysis. On the other contrary, data learning using an artificial neural network can establish a transformation relation between the 3D space and the 2D camera image without explicit camera modeling. However, a neural network requires a large amount of accurate data for its learning. A significantly large amount of time and work using a precise system setup is needed to collect extensive data accurately in practice. In this study, we propose a two-step neural calibration method that is effective when only a small amount of learning data is available. In the first step, the camera projection transformation matrix is determined using the limited available data. In the second step, the transformation matrix is used for generating a large amount of synthetic data, and the neural network is trained using the generated data. Results of simulation study have shown that the proposed method as valid and effective.

• Journal of Information Technology Services
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• v.22 no.4
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• pp.123-140
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• 2023

In recent times, the global economy has been subject to increasing volatility, which has made it considerably more difficult to accurately predict economic indicators compared to previous periods. In response to this challenge, the present study conducts an exploratory investigation that aims to predict the Business Survey Index (BSI) by leveraging data mining techniques on both structured and unstructured data sources. For the structured data, we have collected information regarding foreign, domestic, and industrial conditions, while the unstructured data consists of content extracted from newspaper articles. By employing an extensive set of 44 distinct data mining techniques, our research strives to enhance the BSI prediction accuracy and provide valuable insights. The results of our analysis demonstrate that the highest predictive power was attained when using data exclusively from the t-1 period. Interestingly, this suggests that previous timeframes play a vital role in forecasting the BSI effectively. The findings of this study hold significant implications for economic decision-makers, as they will not only facilitate better-informed decisions but also serve as a robust foundation for predicting a wide range of other economic indicators. By improving the prediction of crucial economic metrics, this study ultimately aims to contribute to the overall efficacy of economic policy-making and decision processes.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.10
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• pp.6715-6721
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• 2015

Recently, DNA data of missing person, killed person, and missing child continue to increase but most of statistical calculation for paternity confirmation is being done through manual methods or Excel. Therefore, we need development of a software which is able to facilitate both systematic management and effective analysis of Short Tandem Repeat (STR) derived from DNA data. Without extensive testing, through a twenty-month study was developed a web-based system which performs paternity analysis and kinship analysis easily based on the various options. The former uses an existing algorithm for paternity index and the latter does Identity by descent (IBD) formula. Due to our system validated over real datasets in terms of likelihood ratio and probability of paternity, it ensures increased reliability as well as effective management and analysis of DNA data in mass disaster. In addition, it includes advanced features such as an integrated environment, user-centered interface, process automation and so on.

• Journal of KIISE
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• v.44 no.12
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• pp.1333-1337
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• 2017

Recommender systems (RS) that predict a set of items a target user is likely to prefer have been extensively studied in academia and have been aggressively implemented by many companies such as Google, Netflix, eBay, and Amazon. Data imputation alleviates the data sparsity problem occurring in recommender systems by inferring missing ratings and adding them to the original data. In this paper, we point out the drawbacks of existing approaches and make suggestions for data imputation techniques. We also justify our suggestions through extensive experiments.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.468-471
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• 2001

The importance of early project planning is broadly recognized for construction projects. From the planning step, If extensive historical data related with the project is applied effectively, It can be major resource for estimating cost and project scope. However, The accumulation, analysis, and application of historical data is not sufficient in Korea. So useful information of construction project has disappeared. In order to solve the problems, Project Historical Data Management Systems is need to be developed. The purpose of this study is to analyze current problems and to find the method to utilize historical data in similar project.

• The Journal of Industrial Distribution & Business
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• v.12 no.6
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• pp.37-46
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• 2021

Purpose: The international business is affected by significant cultural factors that may impediment the operation and the ultimate performance of a business organization. The current study aims to investigate prior literatures works to find cross-cultural discrepancies such as the cultural distance that impacts international companies' operations and management and develop appropriate strategies for realizing high performance while overcoming these challenges. Research design, data and methodology: To find the required sources, the study employed the use of secondary data. Different search strategies were used to find the necessary materials from various sources. The data composed of an extensive review from multiple peer-reviewed journals and other existing research. Results: Based on literature analysis, the current study suggests novel seven strategies for multinational organizations. As a result, this study provides various pieces of literature to deduce meaningful information on the appropriate business strategies that a company can use to bridge the gap of the limitations of cross-cultural impacts on international businesses. Conclusion: An organization moving into a new cultural environment faces challenges including tastes and preferences, norms, language barriers, and beliefs. Organizations, therefore, have to devise the best strategies to align themselves with the prevailing cultural conditions to reap the benefits of internationalization.

• Economic Analysis
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• v.17 no.1
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• pp.103-130
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• 2011

This paper intends to provide applied economists which study the effects of research and development with valuable information on econometric model selection. It includes extensive discussion on econometric models which have been applied for the study on the relationship between research and development and productivity. In particular, it compares various stochastic production frontier models which have been developed recently. The discussion decomposes them into models with scaling property and the ones with nonscaling property as well as models with monotonic and nonmonotonic relationships between research and development and productivity. Finally, this paper applies the models to two different panel data sets (firm level data and country level data) and compare estimation results from competing econometric models.

• Archives of Craniofacial Surgery
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• v.21 no.5
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• pp.276-282
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• 2020

Background: Orbital fractures are the most common pediatric facial fractures. Treatment is conservative due to the anatomical differences that make children more resilient to severe displacement or orbital volume change than adults. Although rarely, extensive fractures may result in enophthalmos, causing cosmetic problems. We aimed to establish criteria for extensive fractures that may result in enophthalmos. Methods: We retrospectively reviewed the charts of patients aged 0-15 years diagnosed with orbital fractures in our hospital from January 2010 to February 2019. Computed tomography images were used to classify the fractures into linear, trapdoor, and open-door types, and to estimate the defect size. Data on enophthalmos severity (Hertel exophthalmometry results) and fracture pattern and size at the time of injury were obtained from patients who did not undergo surgery during the follow-up and were used to identify the surgical indications for pediatric orbital fractures. Results: A total of 305 pediatric patients with pure orbital fractures were included-257 males (84.3%), 48 females (15.7%); mean age, 12.01±2.99 years. The defect size (p=0.002) and fracture type (p=0.017) were identified as the variables affecting the enophthalmometric difference between the eyes of non-operated patients. In the linear regression analysis, the variable affecting the fracture size was open-door type fracture (p<0.001). Pearson's correlation analysis demonstrated a positive correlation between the enophthalmometric difference and the bony defect size (p=0.003). Using receiver operating characteristic curve analysis, a cutoff value of 1.81 ㎠ was obtained (sensitivity, 0.543; specificity, 0.724; p=0.002). Conclusion: The incidence of enophthalmos in pediatric pure orbital fractures was found to increase with fracture size, with an even higher incidence when open-door type fracture was a cofactor. In clinical settings, pediatric orbital fractures larger than 1.81 ㎠ may be considered as extensive fractures that can result in enophthalmos and consequent cosmetic problems.

• Journal of the Korea Institute of Military Science and Technology
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• v.4 no.2
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• pp.189-201
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• 2001

For a design of multi-layer armor, the extensive full scale or sub-scale penetration test data are required. In generally, the collection of penetration data is in need of time-consuming and expensive processes. However, the application of numerical or analytical method is very limited due to poor understanding about penetration mechanics. In this paper, we have developed a neural network analyzer which can be used as a design tool for a new armor. Calculation results show that the developed neural network analyzer can predict relatively exact penetration depth of a new armor through the effective analysis of the pre-existing penetration database.