• Journal of Information Technology Services
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• v.18 no.4
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• pp.67-82
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• 2019

The purpose of this study is to improve the calculation method of the software operation pricing proposed by the software business price calculation guide from 'input manpower method' to 'rate calculation method'. The software operation pricing of the input manpower method is not objectively calculated in the domestic IT outsourcing situation where the statistical data based on the activity based estimating is insufficient and it is decided by agreement between the owner and the client. In addition, there was no standard for adjusting the productivity according to the characteristics of the operation service. In order to improve this, an operational correction factor item that can affect the software operation productivity was selected based on foreign and domestic standards, and it was confirmed through the first questionnaire to IT operation managers. In order to determine the level of difficulty of the fixed operational correction factors, the operational correction factor using AHP technique was confirmed through a second questionnaire for pairwise comparison. The operational difficulty calculation table was developed with reference to COCOMO and ITIL standards. Finally, we propose a new pricing scheme that reflects the operating rate. Regression analysis was carried out by collecting the data of the domestic public institutions on the estimated cost and the actual cost calculated from the new rate method software operation pricing. The results of the regression analysis show that the estimated cost and the actual cost are related to each other. Mean magnitude of relative error(MMRE) and PRED[25] analysis were added for accuracy analysis. MMRE and PRED also showed satisfactory results, confirming the possibility of replacing the rate method software operation pricing.

• Korean Journal of Remote Sensing
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• v.20 no.3
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• pp.175-188
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• 2004

The objectives of this study were to estimate leaf area index (LAI) as a function of image-derived vegetation indices, and to compare measured and estimated LAI to the results of crop model simulation. Soil moisture, crop phenology, and LAI data were obtained several times during the 2001 growing season at monitoring sites established in two central Missouri experimental fields, one planted to com (Zea mays L.) and the other planted to soybean (Glycine max L.). Hyper- and multi-spectral images at varying spatial. and spectral resolutions were acquired from both airborne and satellite platforms, and data were extracted to calculate standard vegetative indices (normalized difference vegetative index, NDVI; ratio vegetative index, RVI; and soil-adjusted vegetative index, SAVI). When comparing these three indices, regressions for measured LAI were of similar quality $(r^2$ =0.59 to 0.61 for com; $r^2$ =0.66 to 0.68 for soybean) in this single-year dataset. CERES(Crop Environment Resource Synthesis)-Maize and CROPGRO-Soybean models were calibrated to measured soil moisture and yield data and used to simulate LAI over the growing season. The CERES-Maize model over-predicted LAI at all corn monitoring sites. Simulated LAI from CROPGRO-Soybean was similar to observed and image-estimated LA! for most soybean monitoring sites. These results suggest crop growth model predictions might be improved by incorporating image-estimated LAI. Greater improvements might be expected with com than with soybean.

• Nuclear Engineering and Technology
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• v.53 no.9
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• pp.3018-3025
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• 2021

The authors developed a volumetric dosimetry detector system using in-house 3D-printable plastic scintillator resins. Three tumor model scintillators (TMSs) were developed using magnetic resonance images of a tumor. The detector system consisted of a TMS, an optical fiber, a photomultiplier tube, and an electrometer. The background signal, including the Cherenkov lights generated in the optical fiber, was subtracted from the output signal. The system showed 2.1% instability when the TMS was reassembled. The system efficiencies in collecting lights for a given absorbed energy were determined by calibration at a secondary standard dosimetry laboratory (k_SSDL) or by calibration using Monte Carlo simulations (k_sim). The TMSs were irradiated in a Gamma Knife® Icon^TM (Elekta AB, Stockholm, Sweden) following a treatment plan. The energies absorbed to the TMSs were measured and compared with a calculated value. While the measured energy determined with k_SSDL was (5.84 ± 3.56) % lower than the calculated value, the energy with k_sim was (2.00 ± 0.76) % higher. Although the TMS detector system worked reasonably well in measuring the absorbed energy to a tumor, further improvements in the calibration procedure and system stability are needed for the system to be accepted as a quality assurance tool.

• Journal of Environmental Science International
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• v.27 no.12
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• pp.1169-1178
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• 2018

Two man-made carbon emissions, fossil fuel emissions and land use emissions, have been perturbing naturally occurring global carbon cycle. These emitted carbons will eventually be deposited into the atmosphere, the terrestrial biosphere, the soil, and the ocean. In this study, Simple Global Carbon Model (SGCM) was used to simulate global carbon cycle and to estimate global carbon budget. For the model input, fossil fuel emissions and land use emissions were taken from the literature. Unlike fossil fuel use, land use emissions were highly uncertain. Therefore land use emission inputs were adjusted within an uncertainty range suggested in the literature. Simulated atmospheric $CO_2$ concentrations were well fitted to observations with a standard error of 0.06 ppm. Moreover, simulated carbon budgets in the ocean and terrestrial biosphere were shown to be reasonable compared to the literature values, which have considerable uncertainties. Simulation results show that with increasing fossil fuel emissions, the ratios of carbon partitioning to the atmosphere and the terrestrial biosphere have increased from 42% and 24% in the year 1958 to 50% and 30% in the year 2016 respectively, while that to the ocean has decreased from 34% in the year 1958 to 20% in the year 2016. This finding indicates that if the current emission trend continues, the atmospheric carbon partitioning ratio might be continuously increasing and thereby the atmospheric $CO_2$ concentrations might be increasing much faster. Among the total emissions of 399 gigatons of carbon (GtC) from fossil fuel use and land use during the simulation period (between 1960 and 2016), 189 GtC were reallocated to the atmosphere (47%), 107 GtC to the terrestrial biosphere (27%), and 103GtC to the ocean (26%). The net terrestrial biospheric carbon accumulation (terrestrial biospheric allocations minus land use emissions) showed positive 46 GtC. In other words, the terrestrial biosphere has been accumulating carbon, although land use emission has been depleting carbon in the terrestrial biosphere.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.33 no.6
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• pp.411-417
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• 2020

To utilize building information modeling (BIM) technology at the bridge maintenance stage, it is necessary to integrate large quantities of bridge inspection and model data for object-oriented information management. This research aims to establish the benefits of utilizing the extended industry foundation class (IFC)-BIM and ontology for bridge inspection information management. The IFC entities were extended to represent the bridge objects, and a method of generating the extended IFC-based information model was proposed. The bridge inspection ontology was also developed by extraction and classification of inspection concepts from the AASHTO standard. The classified concepts and their relationships were mapped to the ontology based on the semantic triples approach. Finally, the extended IFC-based BIM model was integrated with the ontology for bridge inspection data management. The effectiveness of the proposed framework for bridge inspection information management by integration of the extended IFC-BIM and ontology was tested and verified by extracting bridge inspection data via the SPARQL query.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.3
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• pp.384-390
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• 2020

The reverberation effect on the sound when producing movies or VR contents is a very important factor in the realism and liveliness. The reverberation time depending the space is recommended in a standard called RT60(Reverberation Time 60 dB). In this paper, we propose a scene recognition technique for automatic reverberation editing. To this end, we devised a classification model that independently trains color images and predicted depth images in the same model. Indoor scene classification is limited only by training color information because of the similarity of internal structure. Deep learning based depth information extraction technology is used to use spatial depth information. Based on RT60, 10 scene classes were constructed and model training and evaluation were conducted. Finally, the proposed SCR + DNet (Scene Classification for Reverb + Depth Net) classifier achieves higher performance than conventional CNN classifiers with 92.4% accuracy.

• Journal of Information Technology Services
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• v.20 no.1
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• pp.131-143
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• 2021

Commercial transactions, one of the pillars of the capitalist economy, are occurring countless times every day, especially small and medium-sized businesses. However, small and medium-sized enterprises are bound to be the legal underdogs in contracts for commercial transactions and do not receive legal support for contracts for fair and legitimate commercial transactions. When subcontracting contracts are concluded among small and medium-sized enterprises, 58.2% of them do not apply standard contracts and sign contracts that have not undergone legal review. In order to support small and medium-sized enterprises' fair and legitimate contracts, small and medium-sized enterprises can be protected from legal threats if they can reduce the risk of signing contracts by analyzing various risks in the contract and analyzing and informing them of toxic clauses and omitted contracts in advance. We propose a risk prediction model for the machine reading-based legal contract to minimize legal damage to small and medium-sized business owners in the legal blind spots. We have established our own set of legal questions and answers based on the legal data disclosed for the purpose of building a model specialized in legal contracts. Quantitative verification was carried out through indicators such as EM and F1 Score by applying pine tuning and hostile learning to pre-learned machine reading models. The highest F1 score was 87.93, with an EM value of 72.41.

• Journal of Korean Public Health Nursing
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• v.36 no.3
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• pp.361-374
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• 2022

Purpose: This study applies an ecological model to investigate individual and organizational levels to identify factors influencing the HRQOL of industrial employees. Methods: Totally, 133 industrial workers of a vehicle company were enrolled, who understood the purpose and consented to participate in the study. The collected data were analyzed by frequency, percentage, mean, standard deviation, independent t-test, one-way ANOVA, Scheffe Test and hierarchical regression analysis using the SPSS 20.0 program. Results: Hierarchical regression analysis showed that job Stress(β=-.44, p<.001), and hobbies(β=-.21, p=.013) were the major influencing factors of the Physical Component Summary of HRQOL, which had an additional explanatory power of 11.5%. The influencing factors for the Mental Component Summary of HRQOL were job stress(β=-.43, p<.001), and coronary artery disease(β=.17, p=.034) with an additional explanatory power of 13.5%. Conclusion: Results of this study, reveal that a multidimensional approach based on an ecological model is suitable as a health promotion intervention strategy to improve the HRQOL. We further propose developing a multi-dimensional health promotion program that consider the individual and organizational factors such as job stress, activation of in-house clubs, and assessing and managing of the risk of cerebral and cardiovascular diseases.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.1388-1395
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• 2009

In March 2007, Korea's Ministry of Construction & Transportation (MOCT) established "Guidelines on the Computerization and Use of Geotechnical Investigation Results," which took effect as official instructions. The 2007 Geotechnical Information DB Construction Project is underway as a model project for a stable geotechnical information distribution system based on the MOCT guidelines, accompanied by user education on the geotechnical data distribution system. This study introduces a geotechnical data entry system characterized by the standardization of the geotechnical investigation form, the standardization of metadata for creating the geotechnical data to be distributed, and the creation of borehole space data based on the world geodetic system according to the changes in the national coordinate system, to define a unified DB structure and the items for the geotechnical data entry system and to computerize the field geotechnical investigation results using the MOCT guidelines. In addition, the present operating status of the geotechnical data entry system and entry data processing statistics are introduced through an analysis of the model project, and the problems of the project are analyzed to suggest improvements. Education on, and the implementation of, the model project for the geotechnical data entry system, which was developed via the standardization of the geotechnical investigation results form and the metadata for institutions showed that most users can use the system easily. There were problems, however, including those related to the complexity of metadata creation, partial errors in moving to the borehole data window, partial recognition errors in the installation program for different computer operating systems, etc. Especially, the individual standard form usage and the specificity of the person who enters the geotechnical information for the Korea National Housing Corporation, among the institutions under MOCT, required partial improvement of the geotechnical data entry system. The problems surfaced from this study will be promptly addressed in the operation and management of the geotechnical data DB center in 2008.

• Journal of Korea Trade
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• v.27 no.1
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• pp.1-18
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• 2023

Purpose - Using a sample of Korean multinational corporations, we examine whether the relationship between tax risk and the implied cost of capital discriminates between the environmental, social, and corporate governance (ESG) of highly rated firms. Design/methodology - Firms with high tax risks have an increased uncertainty of future cash flows. Therefore, as the volatility of future cash flow increases, information asymmetry and the required return increases. Highly rated ESG firms can reduce information asymmetry, thereby weakening the positive relationship between tax risk and cost of capital. We employ the standard deviation of the cash effective tax rate as proxy of tax risk. We utilize the ESG rating data of the Korea Corporate Governance Service (KCGS). We use a PEG model, MPEG model, and GM model to measure the implied cost of capital. Findings - We find a positive association between the implied cost of capital and tax risk. The positive relationship between tax risk and the implied cost of capital weakens in highly rated ESG firms. Highly rated ESG firms prefer a stable tax position to invest after-tax cash flows into sustainable management. Therefore, the negative effects of tax risk on cost of capital can be reduced. Originality/value - This study provides empirical evidence that ESG activities can mitigate the negative impact of tax risk on the cost of capital for Korean multinational corporations. In a business environment where ESG activities are more important, the empirical results that ESG activities can reduce the corporate risk of Korean FDI companies are expected to provide implications for the ESG activities of multinational corporations.