• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.51.1-51.1
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• 2019

At the commissioning phase of KVN from 2009 to 2013, single-dish survey and monitoring observations were performed toward about 1000 evolved stars and about 60 relatively strong SiO and H2O maser sources respectively. Based on these single-dish results and VLBI feasibility test observations at K/Q/W/D bands in 2014, KVN Key Science Project (KSP) has started from 2015 and will be completed in 2019 as KSP phase I. Here we present the overview of observational studies on evolved stars using KVN. In KSP phase I, we have focused on nine KSP sources which show a successful astrometrically registered maps of SiO and H2O masers using the source frequency phase referencing method. We aim at investigating the spatial structure and dynamical effect from 43/42/86/129 GHz SiO to 22 GHz H2O maser regions associated with a stellar pulsation and development of asymmetry in circumstellar envelopes. Using the combined network KaVA (KVN+Japanese VLBI network VERA), KaVA Large Program titled on "Expanded Study on Stellar Masers: ESTEMA Phase I" was performed from 2015 to 2016. Based on ESTEMA Phase I, EAVN Large Program titled on "EAVN Synthesis of Stellar Maser Animations: ESTEMA Phase II" was also performed from 2018. The ESTEMA II project aims to publish composite animations of circumstellar H2O and SiO masers, which taken from up to 6 long-period variable stars with a variety of the pulsation periods (333-1000 days). The animations will exhibit the three-dimensional kinematics of the maser gas clumps with complexity caused by stellar pulsation-driven shock waves and anisotropy of clump ejections from the stellar surface. Adding three EAVN telescopes (Tianma 65m, Nanshan 26m and NRO 45m telescopes) with KaVA always secures the high quality of the maser image frames through the monitoring program.

• Journal of Wetlands Research
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• v.25 no.4
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• pp.306-314
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• 2023

Stream sediments are an important component of water quality management because they are receptors of various pollutants such as heavy metals and organic matters emitted from upland sources and can be secondary pollution sources, adversely affecting water environment. To effectively manage the stream sediments, identification of primary sources of sediment contamination and source-associated control strategies will be required. We evaluated the performance of machine learning models in identifying primary sources of sediment contamination based on the physico-chemical properties of stream sediments. A total of 356 stream sediment data sets of 18 quality parameters including 10 heavy metal species(Cd, Cu, Pb, Ni, As, Zn, Cr, Hg, Li, and Al), 3 soil parameters(clay, silt, and sand fractions), and 5 water quality parameters(water content, loss on ignition, total organic carbon, total nitrogen, and total phosphorous) were collected near abandoned metal mines and industrial complexes across the four major river basins in Korea. Two machine learning algorithms, linear discriminant analysis (LDA) and support vector machine (SVM) classifiers were used to classify the sediments into four cases of different combinations of the sampling period and locations (i.e., mine in dry season, mine in wet season, industrial complex in dry season, and　industrial complex in wet season). Both models showed good performance in the classification, with SVM outperformed LDA; the accuracy values of LDA and SVM were 79.5% and 88.1%, respectively. An SVM ensemble model was used for multi-label classification of the multiple contamination sources inlcuding landuses in the upland areas within 1 km radius from the sampling sites. The results showed that the multi-label classifier was comparable performance with sinlgle-label SVM in classifying mines and industrial complexes, but was less accurate in classifying dominant land uses (50~60%). The poor performance of the multi-label SVM is likely due to the overfitting caused by small data sets compared to the complexity of the model. A larger data set might increase the performance of the machine learning models in identifying contamination sources.

• Journal of Food Hygiene and Safety
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• v.7 no.4
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• pp.165-172
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• 1992

Among the nutrients of biological importance, minerals are of particular interest in human nutrition because the range of adequate intake is so narrow. As the results of a series of interaction experiments between dietary fiber sources and minerals, there are many inconsistencies in the experimental data regarding the effect of dietary fibers on mineral bioavailability. the mechanism by which dietary fiber might influence mineral absorption is related to its physicochemical properties. These properties involve the ability of dietary fiber to (1) act as a weak cation exchanger, (2) decrease transit time, (3) dilute mineral concentration by increasing fecal bulk and (4) resist digestion in the large bowel. Regardless of the large number of human and animal studies available, a carful review of these publications dose not provide the answer as to whether the adverse effect of dietary fibers on mineral absorption is the fiber itself or some associated dietary factors( e.g. phytate, oxalate, ascorbate, citrate and protein, mineral-mineral interaction, etc) that are responsible for this action. As a result of the complexity of interaction that may take place between minerals. dietary fiber, and other component of food ; it becomes very difficult to blame fiber alone as a negative factor of mineral nutrition. We absolutely need more research with advanced tools rather than metabolic balance study.

• Journal of Information Processing Systems
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• v.15 no.2
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• pp.331-343
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• 2019

Dynamic thermal rating of the overhead transmission lines is affected by many uncertain factors. The ambient temperature, wind speed and wind direction are the main sources of uncertainty. Measurement uncertainty is an important parameter to evaluate the reliability of measurement results. This paper presents the uncertainty analysis based on Monte Carlo. On the basis of establishing the mathematical model and setting the probability density function of the input parameter value, the probability density function of the output value is determined by probability distribution random sampling. Through the calculation and analysis of the transient thermal balance equation and the steady- state thermal balance equation, the steady-state current carrying capacity, the transient current carrying capacity, the standard uncertainty and the probability distribution of the minimum and maximum values of the conductor under 95% confidence interval are obtained. The simulation results indicate that Monte Carlo method can decrease the computational complexity, speed up the calculation, and increase the validity and reliability of the uncertainty evaluation.

• Structural Engineering and Mechanics
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• v.81 no.4
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• pp.429-441
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• 2022

A probabilistic assessment of the seismic-excited buildings with a multiple-tuned-mass-damper (MTMD) system is carried out in the presence of uncertainties of the structural model, MTMD system, and the stochastic model of the seismic excitations. A free search optimization procedure of the individual mass, stiffness and, damping parameters of the MTMD system based on the snap-drift cuckoo search (SDCS) optimization algorithm is proposed for the optimal design of the MTMD system. Considering a 10-story structure in three cases equipped with single tuned mass damper (STMS), 5-TMD and 10-TMD, sensitivity analyses are carried out using Sobol' indices based on the Monte Carlo simulation (MCS) method. Considering different seismic performance levels, the reliability analyses are done using MCS and kriging-based MCS methods. The results show the maximum structural responses are more affected by changes in the PGA and the stiffness coefficients of the structural floors and TMDs. The results indicate the kriging-based MCS method can estimate the accurate amount of failure probability by spending less time than the MCS. The results also show the MTMD gives a significant reduction in the structural failure probability. The effect of the MTMD on the reduction of the failure probability is remarkable in the performance levels of life safety and collapse prevention. The maximum drift of floors may be reduced for the nominal structural system by increasing the TMDs, however, the complexity of the MTMD model and increasing its corresponding uncertainty sources can be caused a slight increase in the failure probability of the structure.

• Management & Information Systems Review
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• v.11
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• pp.1-21
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• 2002

Corporate culture is being recognized as essential managerial resources in the future business management and in recently the attempts, though weak, of developing the corporate culture which is corresponded with their own structure and needs are being carried on by some major companies. Then, corporate culture research, drawing attention in nowadays, indicates that it attempts to analyze and search the organization matters in the basical dimension in regard to the assumptions, values and beliefs of organization and provides the solution of organizational negative effects, which have not been settled in the previews research methods of organizational behavior, and that present turbulent management environment demands the whole conversion from the previews hard style to the soft managerial style. For this reason, this study aim at identifying organizational structure and corporate culture in the business group. Futhermore, the influence of organizational structure and organizational culture are examined. The objective of this paper attempts to analyze the ways and results of strong and special culture on the organizational structure and culture. To accomplish this purpose, this study gathers in-depth data form various secondary courses. First, uncertainties in market and technology are the main sources of mimetic isomorphism. Due to the high level of uncertainty is market and technologies. Smallness in size is responsible for the low level of complexity in organizational structure. The rapid changes in market, contents of service, and tastes of customers are responsible for the low level of formalization, which enhances swift decision making and responses.

• Proceedings of the Korea Information Processing Society Conference
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• 2001.10b
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• pp.1355-1358
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• 2001

IP Multicast can efficiently provide enormous bandwidth savings by enabling sources to send a single copy of a message to multiple recipients who explicitly want to receive the information. But due to the complexity of IP multicast and its fundamental differences from unicast, there are not very many tools available fer monitoring and debugging multicast networks, and only a few experts understand the tools that do exist. This thesis proposes a Multicast Routing Debugger (MRD) system that monitor the status of a multicast network. This system is aimed to multicast-related faults detection. In thesis, first, we define the set of information that should be monitored. Second, the method is developed to take out such information from multicast routers. Third, MRD system is prototyped to collect, process information from heterogeneous routers on a multicast network and to display the various status of the network comprehensively. The prototype of MRD system is implemented and deployed. We perform experiments with several scenarios. Experimental results show we can detect various problems as information that we define is monitored. The MRD system is simple to use, web-based and intuitive tool that can monitor the status of a specific multicast network.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.1
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• pp.63-68
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• 2009

As the complexity of the power system becomes higher, tests of the new devices, such as exciter and PCS(Power Conversion System) of the distributed generation sources, in the real operating condition are more important. However tests of the unverified devices in the real power system may cause hazardous malfunction of the system. In order to avoid this problem, power devices may be tested with the real-time simulators instead of the real power system. This paper presents an real-time multi machine power system simulator using PCs(Personal Computer) and Fast Ethernet. Developed real-time simulator performs the electro-mechanical dynamic simulation of multi-machine power system by the network distributed computing technique. Because the simulator consists of usual PCs and Fast Ethernet, it is possible to make up a simulation system very cheaper than the conventional real-time simulator which consists of dedicated expensive hardware devices. The performance of the developed simulator is tested and verified with the scaled model excitation system. The test which adjust the control parameters of the exciter is performed with the well-known New England 10 generator 39 bus sample power system.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.465-474
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• 2020

This study investigates how financial resources and entrepreneurial orientation (EO) may influence the performance of small- and medium-sized enterprises (SMEs) in the United Arab Emirates (UAE). Twenty-seven interviews were conducted and evaluated using the method of GABEK® (A GAnzheitliche BEwältigung von Komplexität - holistic processing of complexity). The research demonstrated that access to financial resources has significantly mediated EO's effect on the SMEs' performance. The study found that financial autonomy, enhanced through both personal financing and availability of external finance sources, plays a central role in supporting the EO dimension of autonomy and enhancing the SMEs' performance. In particular, the other EO dimension of risk-taking is stymied by lack of funds with which to take commercial and market opportunities. However, when an innovation strategy is pursued and adopted, access to finance can be facilitated, either through financial institutions or through other governmental funding programs attracting high potential innovators. Furthermore, financial barriers, difficulties accessing bank financing, and legal issues have a detrimental impact on SMEs' growth. The study has implications for policy-makers in the UAE, specifically in terms of sending a signal for lending institutions to consider strategies that provide access to affordable financial services to satisfy SMEs' needs.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.622-625
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• 2014

As Big data began to produce a variety of values, a database that allows for huge amount of data with varieties became to be needed. Therefore, for the purpose of overcoming the limitations of the complexity and capacity of the existing RDBMS, NoSQL databases were introduced. Among the different types of NoSQL databases, MongoDB is most commonly used and is offered as open sources. The B-Tree index, used in MongoDB, experiences a significant decrease in performance as the amount of data increases. The fractal tree index enables to enhance the performance of B-Tree substantially by improving B-Tree's insertion algorithm. In this paper, the performances of MongoDB when using B-Tree Index and when using Fractal Tree Index are compared.