• Journal of Technology Innovation
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• v.29 no.3
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• pp.33-62
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• 2021

This study compares and analyzes the efficiency of R&D activities of technology-innovative small and medium-sized enterprises(SMEs) between industries and proposes ways to improve efficiency. The research samples are 6,708 technology-innovative SMEs, which have received a guarantee by the KIBO from 2008 to 2011. Input variables are the level of R&D personnel, R&D investment, and output variables are patent applications, prototype. Efficiency is measured by the DEA model, and indirect comparisons that are individually measured by industry are performed. As a result of the analysis, the CCR for determining the optimal returns to scale is 0.19, the BCC for determining the optimal input distribution is 0.70, and the SE for determining the optimal output is 0.30. By industry type, the medium and low-tech industries have high CCR and BCC, while the high-end and high-tech industries have high SE. R&D activities need to be operated on an optimal scale through managing R&D performance because there is the inefficiency of scale across the industry. The contribution of the study is to analyze the R&D efficiency of each industry of technology-innovative SMEs by the technology evaluation data of the KIBO.

• Korean Journal of Remote Sensing
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• v.37 no.5_2
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• pp.1307-1315
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• 2021

The Changjiang Diluted Water (CDW) spreads over the East China Sea every summer and significantly affects the sea surface salinity changes in the seas around Jeju Island and the southern coast of Korea peninsula. Sometimes its effect extends to the eastern coast of Korea peninsula through the Korea Strait. Specifically, the CDW has a significant impact on marine physics and ecology and causes damage to fisheries and aquaculture. However, due to the limited field surveys, continuous observation of the CDW in the East China Sea is practically difficult. Many studies have been conducted using satellite measurements to monitor CDW distribution in near-real time. In this study, an algorithm for estimating Sea Surface Salinity (SSS) in the East China Sea was developed using the Geostationary Ocean Color Imager (GOCI). The Multilayer Perceptron Neural Network (MPNN) method was employed for developing an algorithm, and Soil Moisture Active Passive (SMAP) SSS data was selected for the output. In the previous study, an algorithm for estimating SSS using GOCI was trained by 2016 observation data. By comparison, the train data period was extended from 2015 to 2020 to improve the algorithm performance. The validation results with the National Institute of Fisheries Science (NIFS) serial oceanographic observation data from 2011 to 2019 show 0.61 of coefficient of determination (R²) and 1.08 psu of Root Mean Square Errors (RMSE). This study was carried out to develop an algorithm for monitoring the surface salinity of the East China Sea using GOCI and is expected to contribute to the development of the algorithm for estimating SSS by using GOCI-II.

• The Journal of the Korea Contents Association
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• v.19 no.1
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• pp.141-151
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• 2019

A network of graph data structure is used in many applications to represent interactions between entities. Recently, as the size of the network to be processed due to the development of the big data technology is getting larger, it becomes more difficult to handle it in one server, and thus the necessity of distributed processing is also increasing. In this paper, we propose a distributed processing system for efficiently performing subgraph and stores. To reduce unnecessary searches, we use statistical information of the data to determine the search order through probabilistic scoring. Since the relationship between the vertex and the degree of the graph network may show different characteristics depending on the type of data, the search order is determined by calculating a score to reduce unnecessary search through a different scoring method for a graph having various distribution characteristics. The graph is sequentially searched in the distributed servers according to the determined order. In order to demonstrate the superiority of the proposed method, performance comparison with the existing method was performed. As a result, the search time is improved by about 3 ~ 10% compared with the existing method.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.7
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• pp.939-944
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• 2018

Clean fire extinguishing agents refer to chemical that can replace Halon 1211 and Halon 1310 according to the Montreal Protocol fermented to protect the Earth's ozone layer. In Korea and abroad, system standardization and performance evaluation of clean fire extinguishing agents are being carried out. This paper proposes an optimal nozzle shape by modeling and numerical analysis of various nozzle shapes based on general clean fire extinguishing system. The ejection speed of the nozzle can be improved by studying three - dimensional modeling of the nozzle for two shapes, Type A and B. Flow analysis was performed on the two types of nozzles and the gas velocity and pressure distribution were measured with different nozzle diameters. It was confirmed that the jetting speed was changed at the nozzle outlet according to the number and diameter of the nozzle holes. The flow rate increased with increasing the pressure regardless of the nozzle hole diameter. Based on the results obtained from the experiment, the K-factor value was deduced. Finally, a nozzle with a 12-hole structure with a 5-mm nozzle hole was proposed.

• Journal of Climate Change Research
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• v.8 no.4
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• pp.415-424
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• 2017

This study was conducted to estimate carbon stocks of Pinus densiflora with drawing volume of trees in each tree height and DBH applying the suitable stem taper equation and tree specific carbon emission factors, using collected growth data from all over the country. Information on distribution area, tree age, tree number per hectare, tree volume and volume stocks were obtained from the $5^{th}$ National Forest Inventory (2006~2010) and Statistical yearbook of forest (2016), and method provided in IPCC GPG was applied to estimate carbon stock and uptake. Performance in predicting stem diameter at a specific point along a stem in Pinus densiflora by applying Kozak's model, $d=a_{1}DBH^{a_2}a_3^{DBH}X^{b_{1}Z^2+b_2ln(Z+0.001)+b_3\sqrt{Z}+b_4e^z+b_5(\frac{DBH}{H})}$, which is well known equation in stem taper estimation, was evaluated with validations statistics, Fitness Index, Bias and Standard Error of Bias. Consequently, Kozak's model turned out to be suitable in all validations statistics. Stem volume table of P. densiflora was derived by applying Kozak's model and carbon stock tables in each tree height and DBH were developed with country-specific carbon emission factors ($WD=0.445t/m^3$, BEF = 1.445, R = 0.255) of P. densiflora. As the results of analysis in carbon uptake for each province, the values were high with Gangwon-do $9.4tCO_2/ha/yr$, Gyeongsandnam-do and Gyeonggi-do $8.7tCO_2/ha/yr$, Chungcheongnam-do $7.9tCO_2/ha/yr$ and Gyeongsangbuk-do $7.8tCO_2/ha/yr$ in order, and Jeju-do was the lowest with $6.8tC/ha/yr$. Total carbon stocks of P. densiflora were 127,677 thousands tC which is 25.5% compared with total percentage of forest and carbon stock per hectare (ha) was $84.5tC/ha/yr$ and $7.8tCO_2/ha/yr$, respectively.

• Journal of Climate Change Research
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• v.1 no.3
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• pp.205-210
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• 2010

LED light has various advantages such as an energy saving effect of over 80% compared to existing lighting and environmentally friendly characteristics; however, there has been no affordable market for LED lighting because of its expensive price. This study discussed the validity of the expansion of distribution of LED lighting through an assessment of economic efficiency concerning LED lightening in order to analyze its efficiency in terms of energy savings and maintenance and repair, which will be generated as a result of the change from existing incandescent bulbs to LED lighting in the public sector. As to the target of analysis, the paper reviewed the validity of change to LED lighting as a result of the elimination of existing incandescent bulbs, by referring to 'the current incandescent bulb use and elimination performance' published by the Ministry of Knowledge Economy based on the "Elimination management system" executed by Korea Energy Management Corporation. The paper considered expenses for change, annual power savings amount and electric charges savings amount, repair and maintenance cost, $CO_2$ reduction volume, and the profit from the sale of CER (certified emission reduction). As a result of analyzing economic efficiency, when the discount rate during the change of existing incandescent bulb lighting to LED lighting is 3.26%, the profit was 8,648,400,000 won. Accordingly, NPV was analyzed to have a 'positive (+)' value, which means that this change is profitable.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.11
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• pp.435-442
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• 2018

Outlier detection means to detect data samples that deviate significantly from the distribution of normal data. Most outlier detection methods calculate an outlier score that indicates the extent to which a data sample is out of normal state and determine it to be an outlier when its outlier score is above a given threshold. However, since the range of an outlier score is different for each data and the outliers exist at a smaller ratio than the normal data, it is very difficult to determine the threshold value for an outlier score. Further, in an actual situation, it is not easy to acquire data including a sufficient amount of outliers available for learning. In this paper, we propose a clustering-based outlier detection method by constructing a model representing a normal data region using only normal data and performing binary classification of outliers and normal data for new data samples. Then, by dividing the given normal data into chunks, and constructing a clustering model for each chunk, we expand it to the ensemble method combining the decision by the models and apply it to the streaming data with dynamic changes. Experimental results using real data and artificial data show high performance of the proposed method.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.17 no.3
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• pp.321-328
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• 2019

The detection performances of the NaI(Tl), $LaBr_3$(Ce) and $CeBr_3$ scintillation detectors, which can be used to rapidly evaluate the major artificial radionuclides deposited on the soil surface in a nuclear accident or radiological emergency, were compared. Detection performance was assessed by calculating the minimum detectable activity (MDA). The detection efficiency of each detector for artificial radionuclides was semi-empirically determined using mathematical modelling and point-like sources having certified radioactivity. The background gamma-ray energy spectrum for MDA evaluation was obtained from relatively wide and flat grassland, and the MDA values of each detector for the major artificial radionuclides that could be released in nuclear accidents were calculated. As a result, the relative MDA values of each detector regarding surface deposition distribution at normal environmental radiation level were evaluated as high in the order of the NaI(Tl), $LaBr_3$(Ce), and $CeBr_3$ detectors. These results were compared based on each detector's intrinsic and measurement environment background, detection efficiency, and energy resolution for the gamma-ray energy region of the radionuclide of interest.

• Management & Information Systems Review
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• v.37 no.4
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• pp.219-236
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• 2018

The purpose of this study is to investigate the effect of image of brand origin on brand related variables in the formation of attitude or loyalty of global brand, We tried to identify more influential relationships through sub-variables such as brand familiarity, brand identification, and brand attitude. This study presents the following results and implications. It is shown that the manufacturing ability image has no direct effect on brand identification, but the general image has a direct positive effect on brand identification. In addition, the manufacturing capability image and general image of brand origin have indirect effects on brand familiarity through brand identification without directly affecting brand familiarity. In addition, consumers are more likely to be more familiar with brands that they think are consistent with their own images, maintain a good attitude, and be more likely to be loyal to brands. Brand familiarity had a positive effect on brand attitude but not on brand loyalty. Familiarity showed a positive attitude, but it did not necessarily lead to strong repeat purchase or purchase.

• Journal of the Microelectronics and Packaging Society
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• v.26 no.1
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• pp.29-33
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• 2019

With shrinking form factor and improving performance of electronic packages, high input/output (I/O) density is considered as an important factor. Fan out wafer-level packaging (FO-WLP) has been paid great attention as an alternative. However, FO-WLP is vulnerable to warpage during its manufacturing process. Minimizing warpage is essential for controlling production yield, and in turn, package reliability. While many studies investigated the effect of process and design parameters on warpage using finite element analysis, they did not take uncertainty into consideration. As parameters, including material properties, chip positions, have uncertainty from the point of manufacturing view, the uncertainty should be considered to reduce the gap between the results from the field and the finite element analysis. This paper focuses on the effect of uncertainty of Young's modulus of chip on fan-out wafer level packaging warpage using finite element analysis. It is assumed that Young's modulus of each chip follows the normal distribution. Simulation results show that the uncertainty of Young's modulus affects the maximum von Mises stress. As a result, it is necessary to control the uncertainty of Young's modulus of silicon chip since the maximum von Mises stress is a parameter related to the package reliability.