• Knowledge Management Research
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• v.22 no.1
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• pp.57-84
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• 2021

In this paper, we explore market and environmental factors which affecting organization's priority claim application which is more powerful and prompt strategic method to protect technology from competitors under uncertain and volatile environments. This study empirically examines why organizations strategically choose the priority claim application which is more strong tactics to protect technology as the source of sustainable competitive advantage. We suggest that market and environmental factors, such as exogenous shock, volatility, and uncertainty, may also affect strategic decision that organization take patent application with claiming priority. The results of our analysis of priority claim application in the Korean high-tech electronics industry from 1994 to 2008 showed that these three strategic factors affected the technology protection decision and organization's status also moderate theses effects, as predicted in our hypotheses.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.7
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• pp.4554-4561
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• 2014

In recent years, several paradigms have been identified to simplify the design of fault-tolerant distributed applications in a conventional static system. Leader Election is among the most noticeable, particularly because it is closely related to group communication, which provides a powerful basis for implementing active replications among other uses. On the other hand, despite its usefulness, to our knowledge, no study has focused on this problem in a mobile computing environment. The aim of this paper was to propose an algorithm for the leader election protocol in a fixed station based wireless networks environment. The election algorithm is much more efficient than other election algorithms in terms of the fault tolerance.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.316-321
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• 2003

This paper presents a design method of the wavelet neural network based controller using direct adaptive control method to deal with a stable intelligent control of chaotic systems. The various uncertainties, such as mechanical parametric variation, external disturbance, and unstructured uncertainty influence the control performance. However, the conventional control methods such as optimal control, adaptive control and robust control may not be feasible when an explicit, faithful mathematical model cannot be constructed. Therefore, an intelligent control system that is an on-line trained WNN controller based on direct adaptive control method with adaptive learning rates is proposed to control chaotic nonlinear systems whose mathematical models are not available. The adaptive learning rates are derived in the sense of discrete-type Lyapunov stability theorem, so that the convergence of the tracking error can be guaranteed in the closed-loop system. In the whole design process, the strict constrained conditions and prior knowledge of the controlled plant are not necessary due to the powerful learning ability of the proposed intelligent control system. The gradient-descent method is used for training a wavelet neural network controller of chaotic systems. Finally, the effectiveness and feasibility of the proposed control method is demonstrated with application to the chaotic systems.

• Journal of Korean Academy of Nursing
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• v.25 no.4
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• pp.696-705
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• 1995

The self-efficacy as the mediating variable to connect knowledge to behavior was Identified as the most powerful predictor that determines behavior. The purpose of this study was, first, to develop the slides /tape program based on the self-efficacy theory of Bandura(1977) second, to investigate that the Slides /Tape program would increase self-efficacy and self-care in patients with hypertension. The subjects for this study were 54 hypertensive outpatients and data collection was carried out from January 9, 1995 until March 18, 1995. The design of this study was one-group pretest and posttest design and the results are as follows 1) The slides /tape program was developed to based on performance accomplishment and vicarious experience which are induction modes of efficacy expectation. It composed of 80 slides and 20 minutes long tape. 2) The effectiveness of the slides /tape program “The self-efficacy score after giving the slides /tape program will be higher than one before giving the slides /tape program.” was supported (t=3.67, p=0.001). “The self-care score after giving the slides /tape program will be higher than one before giving the slides /tape program.” was supported(t=5.23. 000), 3) A significant difference was found between the self-care and sex. Also, the significant difference was found between the self-care and job. From these results, the slides /tape program is effective to increase the hypertensive patients' self-care.

• Bulletin of the Korean Chemical Society
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• v.33 no.3
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• pp.855-861
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• 2012

A pioneering version of an on-line management system for high-energy molecules (MS-HEMs) was developed by the ADD and BMDRC in Korea. The current system can manage the physicochemical and explosive properties of virtual and existing HEMs. The on-line MS-HEMs consist of three main routines: management, calculation, and search. The management routine contains a user-friendly interface to store and manage molecular structures and other properties of the new HEMs. The calculation routine automatically calculates a number of compositional and topological molecular descriptors when a new HEM is stored in the MS-HEMs. Physical properties, such as the heat of formation and density, can also be calculated using group additivity methods. In addition, the calculation routine for the impact sensitivity can be used to obtain the safety nature of new HEMs. The impact sensitivity was estimated in a knowledge-based manner using in-house neural network code. The search routine enables general users to find an exact HEM and its properties by sketching a 2D chemical structure, or to retrieve HEMs and their properties by giving a range of properties. These on-line MS-HEMs are expected be powerful tool for deriving novel promising HEMs.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.3
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• pp.222-229
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• 2016

Linked Data is a powerful technology for storing and publishing the structures of data. It is helpful for web applications because of its usefulness through semantic query data. However, using Linked Data is not easy for ordinary users who lack knowledge about the structure of data or the query syntax of Linked Data. For that problem, we propose a translator component that is used for translating RESTful/JSON request messages into SPARQL commands based on ontology - a metadata that describes the structure of data. Clients do not need to worry about the structure of stored data or SPARQL, a kind of query language used for querying linked data that not many people know, when they insert a new instance or query for all instances of any specific class with those complex structure data. In addition, the translator component has the search function that can find a set of data from multiple classes based on finding the shortest paths between the target classes - the original set that user provide, and target classes- the users want to get. This translator component will be applied for any dynamic ontological structure as well as automatically generate a SPARQL command based on users' request message.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.4
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• pp.217-231
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• 2015

A novel fuzzy learning framework that employs fuzzy inference to solve the problem of Multiple Instance Learning (MIL) is presented. The framework introduces a new class of fuzzy inference systems called Multiple Instance Mamdani Fuzzy Inference Systems (MI-Mamdani). In multiple instance problems, the training data is ambiguously labeled. Instances are grouped into bags, labels of bags are known but not those of individual instances. MIL deals with learning a classifier at the bag level. Over the years, many solutions to this problem have been proposed. However, no MIL formulation employing fuzzy inference exists in the literature. Fuzzy logic is powerful at modeling knowledge uncertainty and measurements imprecision. It is one of the best frameworks to model vagueness. However, in addition to uncertainty and imprecision, there is a third vagueness concept that fuzzy logic does not address quiet well, yet. This vagueness concept is due to the ambiguity that arises when the data have multiple forms of expression, this is the case for multiple instance problems. In this paper, we introduce multiple instance fuzzy logic that enables fuzzy reasoning with bags of instances. Accordingly, a MI-Mamdani that extends the standard Mamdani inference system to compute with multiple instances is introduced. The proposed framework is tested and validated using a synthetic dataset suitable for MIL problems. Additionally, we apply the proposed multiple instance inference to fuse the output of multiple discrimination algorithms for the purpose of landmine detection using Ground Penetrating Radar.

• Journal of Korean Elementary Science Education
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• v.28 no.3
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• pp.340-351
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• 2009

The purpose of this study was to investigate the effect of case-based learning program on three elementary students' scientific problem solving and attitudes in science class. For this study, case-based learning program was designed for bridging students' scientific knowledge and their personal experiences in real life through 4 stages: understanding the problem, planning for problem solving, conducting problem solving, and making conclusion. This study was carried out through 17 lessons of 4th grade for 6 weeks. The data was collected through close observation on three students in two groups in a class. The results include that cased-based learning program showed overall positive effects on the elementary students' scientific problem solving and attitudes in class. In particular, it turned out that the continuous emphasis of real world examples in case-based learning had powerful impacts on students' problem solving abtsity, motivation, and participation in classroom activities. The key factors to successful problem solving in school science was discussed.

• BMB Reports
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• v.43 no.2
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• pp.110-114
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• 2010

The yeast three-hybrid system (Y3H), a powerful method for identifying RNA-binding proteins, still suffers from many false positives, due mostly to RNA-independent interactions. In this study, we attempted to efficiently identify false positives by introducing a tetracycline operator (tetO) motif into the RPR1 promoter of an RNA hybrid expression vector. We successfully developed a tight tetracycline-regulatable RPR1 promoter variant containing a single tetO motif between the transcription start site and the A-box sequence of the RPR1 promoter. Expression from this tetracycline-regulatable RPR1 promoter in the presence of tetracycline-response transcription activator (tTA) was positively controlled by doxycycline (Dox), a derivative of tetracycline. This on-off control runs opposite to the general knowledge that Dox negatively regulates tTA. This positively controlled RPR1 promoter system can therefore efficiently eliminate RNA-independent false positives commonly observed in the Y3H system by directly monitoring RNA hybrid expression.

• Journal of the Korean Society of Costume
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• v.59 no.6
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• pp.41-57
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• 2009

Evaluations of fashion products are often influenced by consumers' knowledge of the country where the products were made in. As globalization progresses, country-of-origin information is widely regarded as a powerful cue on consumers' shopping behavior. The purpose of study was to examine the consumer evaluation of apparel products with uni-national or bi-national country of origin. The effect of price level and gender were also investigated. The empirical research design took 2${\times}$2 factorial design with the country-of-origin coincidence (uni-national vs. bi-national) and price (high vs. low) of gender (male vs. female). Consumers' ethnocentrism and country-of-origin interest were taken into account as covariates in the factorial design. The consumers' evaluation of fashion products was measured in terms of brand attitudes and product attitudes. Data from 514 respondents were analyzed with t-test, one-way ANOVA, two-way ANOVA, and ANCOVA. Results of this study affirmed the importance of price information rather than country-of-origin coincidence in brand attitudes and product attitudes. Only for male consumers, interaction effects of price and country-of-origin coincidence had significant eflects on utilitarian attitude. Effects of two covariate variables included in the study were significant for female respondents but not for male respondents.