• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.1
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• pp.117-124
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• 2021

Among growth disorders, 'Short Stature' can be improved through rapid diagnosis and treatment, and for that, it is important to detect early'Short Stature'. It is recommended to measure the height steadily for early detection of 'Short Stature' and checking the kid's growth process, but existing height measurement methods have problems such as time and space limitations, cost occurrence, and difficulty in keeping records. So in this paper, we proposed an 'Development of Kid Height Measurement Application based on Image using computer vision' method using smart phones, a medium that is highly accessible to people. In images taken through a smartphone camera, the kid's height is measured using algorithms from OpenCV, a computer vision library, and the measured heights were printed on the screen through 'a comparison graph with the standard height by gender and age' and 'list by date', made possible to check the kid's growth process. It is expected to measure height anytime, anywhere without time and space limitations and costs through this proposed method, and it is expected to help early detection of 'Short Stature' and other disorder through steady height measurement and confirmation of growth process.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.67-86
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• 2020

Recommender Systems have been huge influence users and business more and more. Recently the importance of E-commerce has been reached rapid growth greatly in world-wide COVID-19 pandemic. Recommender system is the center of E-commerce lively. Top ranked E-commerce managers mentioned that recommender systems have a major influence on customer's purchase such as about 50% of Netflix, Amazon sales from their recommender systems. Most algorithms have been focused on improving accuracy of recommender system regardless of novelty, diversity, serendipity etc. Recommender systems with only high accuracy cannot satisfy business long-term profit because of generating sales polarization. In addition, customers do not experience enjoyment of shopping from only focusing accuracy recommender system because customer's preference is changed constantly. Therefore, recommender systems with various values need to be developed for user's high satisfaction. Reranking is the most useful methodology to realize diversity of recommender system. In this paper, diversity of recommender system is represented through constructing high similarity with users who have different preference using each user's purchased item's category algorithm. It is distinguished from past research approach which is changing the algorithm of recommender system without user's diversity preference level. We tried to discover user's diversity preference level and observed the results how the effect was different according to user's diversity preference level. In addition, graph-based recommender system was used to show diversity through user's network, not collaborative filtering. In this paper, Amazon Grocery and Gourmet Food data was used because the low-involvement product, such as habitual product, foods, low-priced goods etc., had high probability to show customer's diversity. First, a bipartite graph with users and items simultaneously is constructed to make graph-based recommender system. However, each users and items unipartite graph also need to be established to show diversity of recommender system. The weight of each unipartite graph has played crucial role changing Jaccard Distance of item's category. We can observe two important results from the user's unipartite network. First, the user's diversity preference level is observed from the network and second, dissimilar users can be discovered in the user's network. Through the research process, diversity of recommender system is presented highly with small accuracy loss and optimalization for higher accuracy is possible controlling diversity ratio. This paper has three important theoretical points. First, this research expands recommender system research for user's satisfaction with various values. Second, the graph-based recommender system is developed newly. Third, the evaluation indicator of diversity is made for diversity. In addition, recommender systems are useful for corporate profit practically and this paper has contribution on business closely. Above all, business long-term profit can be improved using recommender system with diversity and the recommender system can provide right service according to user's diversity level. Lastly, the corporate selling low-involvement products have great effect based on the results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.709-730
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• 2017

To address the challenge of unprecedented growth in mobile data traffic, ultra-dense network deployment is a cost efficient solution to offload the traffic over some small cells. The overlapped coverage areas of small cells create more than one candidate access points for one mobile user. Signal strength based user association in IEEE 802.11 results in a significantly unbalanced load distribution among access points. However, the effective bandwidth demand of each user actually differs vastly due to their different preferences for mobile applications. In this paper, we formulate a set of non-linear integer programming models for joint user association control and user demand guarantee problem. In this model, we are trying to maximize the system capacity and guarantee the effective bandwidth demand for each user by soft-association control with a software defined network controller. With the fact of NP-hard complexity of non-linear integer programming solver, we propose a Kernighan Lin Algorithm based graph-partitioning method for a large-scale network. Finally, we evaluated the performance of the proposed algorithm for the edge users with heterogeneous bandwidth demands and mobility scenarios. Simulation results show that the proposed adaptive soft-association control can achieve a better performance than the other two and improves the individual quality of user experience with a little price on system throughput.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.4
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• pp.197-212
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• 2022

The study uses the audited financial statements of 26 Vietnamese commercial banks listed on the Ho Chi Minh City Stock Exchange (HOSE) and Hanoi Stock Exchange (HOSE) during the 2008-2018 period to estimate the system GMM model, which provides empirical evidence on the effect of the variables of customer deposit to total assets (DEPO) ratio, loan to assets (LTA) ratio, liquidity of commercial banks (LIQ), credit development (CRD) ratio, external funding (EFD) ratio, and credit loss provision (LLP) ratio on liquidity risk. The study confirms that commercial banks' internal factors play the most important role, and there is no empirical evidence on macro variables that affect liquidity risk. Finally, in accordance with the theoretical framework, the study uses an estimation method with the R language and the bootstrap methodology to give empirical proof of the nonlinear correlation and U-shaped graph between commercial bank size and liquidity risk. The importance of commercial bank size in absorbing and moderating the effects of liquidity shocks is demonstrated, however, excessive growth in commercial bank size would increase liquidity risk in commercial bank operations.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.706-709
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• 2009

The informatization of Korea is accompanied by the great growth of new strategic export industry, as of mobile phone or semiconductor LCD. Speaking to the situation of mobile phone, Motorola swept over the American domestic market in the beginning of 1990s, digital mobile communication as CDMA developed swiftly in Korea. In 1996, the first year's CDMA users of Samsung were merely one million, nevertheless, the world's sales in the first half of this year is up to 92 million. In this p aper I design 3D application based on J2ME and implement a freely removable 3D object which happened in a 3D scen e by receiving the keyboard response of mobile device with WTK (Wireless ToolKit) simulator. It contains benefits of improvement of relative speed and high-level functionality such as scene graph, keyframe animation, etc.

• Journal of Korea Trade
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• v.27 no.3
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• pp.103-118
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• 2023

Purpose - This study aims to examine the dynamic relationship between the variables impacted by the Regional Comprehensive Economic Partnership (RCEP) and the level of intra-industry trade among member states, with the ultimate objective of deducing the short- and long-term effects of RCEP on trade. Design/methodology - This study focuses on tariffs, GDP growth rates, and the proportion of regional FDI to total FDI as research variables, and employs a panel vector autoregression model and GMM-style estimator to investigate the dynamic relationship between RCEP and intra-industry trade among member countries. Findings - The study finds that the level of intra-industry trade between member states is positively impacted by both tariffs and intra-regional FDI. The impulse response graph shows that tariffs and FDI within the region can promote intra-industry trade among member countries, with a quick response. However, the contribution rates of tariffs and intra-regional FDI are not particularly high at approximately 1.5% and 1.4%, respectively. In contrast, the contribution rate of GDP growth can reach around 8.5%. This implies that the influence of economic growth rate on intra-regional trade in industries is not only long-term but also more powerful than that of tariffs and intra-regional FDI. Originality/value - The originality of this study lies in providing a new approach to investigating the potential impact of RCEP while avoiding the limitations associated with the GTAP model. Additionally, this study addresses existing gaps within the research, further contributing to the research merit of the study.

• Journal of Food Hygiene and Safety
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• v.26 no.2
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• pp.120-124
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• 2011

Predictive mathematical models were developed for predicting the kinetics of growth of Listeria monocytogenes in smoked salmon, which is the popular ready-to-eat foods in the world, as a function of temperature (4, 10, 20 and $30^{\circ}C$). At these storage temperature, the primary growth curve fit well ($r^2$=0.989~0.996) to a Gompertz equation to obtain specific growth rate (SGR) and lag time (LT). The Polynomial model for natural logarithm transformation of the SGR and LT as a function of temperature was obtained by nonlinear regression (Prism, version 4.0, GraphPad Software). Results indicate L. monocytogenes growth was affected by temperature mainly, and SGR model equation is $365.3-31.94^*Temperature+0.6661^*Temperature^{\wedge^2}$ and LT model equation is $0.1162-0.01674^*Temperature+0.0009303^*Temperature{\wedge^2}$. As storage temperature decreased $30^{\circ}C$ to $4^{\circ}C$, SGR decreased and LT increased respectively. Polynomial model was identified as appropriate secondary model for SGR and LT on the basis of most statistical indices such as bias factor (1.01 by SGR, 1.55 by LT) and accuracy factor (1.03 by SGR, 1.58 by LT).

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.28 no.8
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• pp.531-538
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• 2015

This study examined the size and shape of the nano-silver particle through the analysis of electrical resistance when synthesizing nano-sized silver by using the chemical liquid reduction. Changes in particle behaviors formed according to the changes in electronic characteristics by electric resistance in each time period in the beginning of reduction reaction in a course of synthesizing the nano-silver particle formation were studied. In addition, analysis was conducted on particle behaviors according to the changes in concentration of $AgNO_3$ and in temperature at the time of reduction and nucleation and growth course when synthesizing the particles based on the particle behaviors were also examined. As the concentration of $AgNO_3$ increased, the same amount of resistance of approximately $5{\Omega}$ was increased in terms of initial electronic resistance. Furthermore, according to the result of formation of nuclear growth graph and estimation of slope based on estimated resistance, slops of $6.25{\times}10^{-3}$, $2.89{\times}10^{-3}$, and $1.85{\times}10^{-3}$ were derived from the concentrations of 0.01 M, 0.05 M, and 0.1 M, respectively. As the concentration of $AgNO_3$ increased, the more it was dominantly influenced by the nuclear growth areas in the initial phase of reduction leading to increase the size and cohesion of particles. At the time of reduction of nano-silver particle, the increases of initial resistance were $4{\Omega}$, $4.2{\Omega}$, $5{\Omega}$, and $5.3{\Omega}$, respectively as the temperature increased. As the temperature was increased into $23^{\circ}C$, $40^{\circ}C$, $60^{\circ}C$, and $80^{\circ}C$, slopes were formed as $4.54{\times}10^{-3}$, $4.65{\times}10^{-3}$, $5.13{\times}10^{-3}$, and $5.42{\times}10^{-3}$ respectively. As the temperature increased, the particles became minute due to the increase of nuclear growth area in the particle in initial period of reduction.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.6
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• pp.764-771
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• 2018

Domestic and foreign agricultural environments nowadays are undergoing various changes such as aging of agricultural population, increase of earned population, rapid climate change, diversification of agricultural product distribution structure, depletion of water resources and limited cultivation area. In order to respond to various environmental changes in recent agriculture, practical use of Smart Greenhouse to easily record, store and manage crop production information such as crop growing information, growth environment and agriculture work log, Interest is growing. In this paper, we propose a system that collects the situation information necessary for growth such as temperature, humidity, solar radiation, CO2 concentration, and monitor the collected data, which can be measured in the rhizosphere of the crop. We have developed a system that collects data such as temperature, humidity, radiation, and growth environment data, which are measured by data obtained from the rhizosphere measuring section of a growing crop and measured by a sensor, and transmitted to a wireless communication gateway of 400 MHz. We developed the integrated SW that can monitor the rhythm environment data and visualize the data by using cloud based data. We can monitor by graph format and data format for visualization of data. The existing smart farm managed crops and facilities using only the data within the farm, and this study suggested the most efficient growth environment by collecting and analyzing the weather and growth environment of the farms nationwide.

• Journal of the Korea institute for structural maintenance and inspection
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• v.10 no.3
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• pp.165-175
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• 2006

To analyze the deformation and failure of slopes, generally, two types of model, Polynomial model and Growth model, are applied. These two models are focused on the behavior of the slope by time. Therefore, this research is more focused on predicting of slope failure than analyzing the slope behavior by time. Generally, Growth model is used to analyze the soil slope, to the contrary, Polynomial model is used for rock slope. However, 3-degree polynomial($y=ax^3+bx^2+cx+d$) is suggested to combine two models in this research. The main trait of this model is having an asymptote. The fields to adopt this model are Gosujae Danyang(soil slope) and Youngduk slope(rock slope), which are the cut-slope near national road. Data from Gosujae are shown the failure traits of soil slope, to the contrary, those of Youngduk slope are shown the traits of rock slope. From the real-time monitoring data of the slope, 3-degree polynomial is proved as excellent system to analyze the failure and behavior of slope. In case of Polynomial model, even if the order of polynomials is increased, the $R^2$ value and shape of the curve-fitted graph is almost the same.