• Journal of Korea Multimedia Society
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• v.16 no.7
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• pp.810-819
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• 2013

FCM (Fuzzy C-Means) clustering algorithm, a typical split-based clustering algorithm, has been successfully applied to the various fields. Nonetheless, the FCM clustering algorithm has some problems, such as high sensitivity to noise and local data, the different clustering result from the intuitive grasp, and the setting of initial round and the number of clusters. To address these problems, in this paper, we determine fuzzy numbers which project the FCM clustering result on the axis with the specific attribute. And we propose a model that the fuzzy numbers apply to FDT (Fuzzy Decision Tree). This model improves the two problems of FCM clustering algorithm such as elevated sensitivity to data, and the difference of the clustering result from the intuitional decision. And also, this paper compares the effect of the proposed model and the result of FCM clustering algorithm through the experiment using real traffic and rainfall data. The experimental results indicate that the proposed model provides more reliable results by the sensitivity relief for data. And we can see that it has improved on the concordance of FCM clustering result with the intuitive expectation.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.9
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• pp.615-620
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• 2013

With the development of smartphones, the number of applications for smartphone increases sharply. As a result, users need to try several times to find their favorite apps. In order to solve this problem, we propose a recommendation system to provide an appropriate app list based on the user's log information including time stamp, location, application list, and so on. The proposed approach learns three recommendation models including Naive-Bayesian model, SVM model, and Most-Frequent Usage model using temporal and spatial attributes. In order to figure out the best model, we compared the performance of these models with variant features, and suggest an hybrid method to improve the performance of single models.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.29 no.1
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• pp.47-72
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• 2018

The quality of records determines the value of records as assets in the digital age. It depends on how consistently record requirements can be applied during the records production and utilization processes using mostly IT systems. Therefore, the importance of effective records management (RM) governance applied for all organizational areas cannot be emphasized enough. The purpose of this paper is to propose a new framework of RM governance in order to produce and manage more valuable records, and the way to implement it in an organizational context. For the purpose, this paper discusses the necessity of a governance framework to formulate and operate consistent policies and procedures for overall processes of production, distribution, utilization and protection of records based on the values of evidence and information. Next, it proposes an integrated model by linking the management framework of the Information Governance Reference Model (IGRM) and the Management System for Records standards (ISO 30300 series; MSR) for the effective RM governance to be implemented in an organizational context.

• The Journal of Bigdata
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• v.5 no.1
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• pp.197-208
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• 2020

Lexical ambiguity means that a word can be interpreted as two or more meanings, such as homonym and polysemy, and there are many cases of word sense ambiguation in words expressing emotions. In terms of projecting human psychology, these words convey specific and rich contexts, resulting in lexical ambiguity. In this study, we propose an emotional classification model that disambiguate word sense using bidirectional LSTM. It is based on the assumption that if the information of the surrounding context is fully reflected, the problem of lexical ambiguity can be solved and the emotions that the sentence wants to express can be expressed as one. Bidirectional LSTM is an algorithm that is frequently used in the field of natural language processing research requiring contextual information and is also intended to be used in this study to learn context. GloVe embedding is used as the embedding layer of this research model, and the performance of this model was verified compared to the model applied with LSTM and RNN algorithms. Such a framework could contribute to various fields, including marketing, which could connect the emotions of SNS users to their desire for consumption.

• Journal of Korea Technology Innovation Society
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• v.12 no.1
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• pp.113-136
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• 2009

The purpose of this study is to develop meta evaluating indicators for Defense R&D Programs in Korea. At first, the four components of this meta evaluation model were designed, which are evaluation context, evaluation input, evaluation process, evaluation output. And fifty two indicators were developed for this meta evaluation. Basic model of meta evaluation was derived from the literature review and brain storming. And this meta evaluation model was determined by adapting the result of experts who performed evaluations for Defense R&D Programs in recent years. Factor Analysis method was used to verify the validity of meta evaluation model. The survey of fifty three members turned out that Cronbach' ${\alpha}$ was over 0.6 in evaluation components and items. And the reliability of evaluation context was 0.877, that of evaluation input was 0.755, that of evaluation process was 0.755, that of evaluation output was 0.755 respectively. Analytic Hierarchy Process (AHP) method was used in assigning the evaluation weight. The survey of twenty two members showed that the Consistency Ratio was 0.09 in evaluation components and items.

• International Journal of Computer Science & Network Security
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• v.21 no.12
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• pp.309-315
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• 2021

The purpose of the article is to analyze the functioning of economic systems in the context of the development of their potential in a circular economy. It is determined that the functioning of economic systems to ensure their sustainability should meet modern challenges and provide for the formation of competitive institutional architecture, the introduction of structural and regulatory innovations, the transition to an innovative model of development. The specific principles of functioning of economic systems include openness, nonlinearity, multivectority, dynamism, emergence, uncertainty about the development of economic processes. It is substantiated that the linear nature of development and equilibrium are not dominant in the functioning of economic systems, and increasing the level of economic efficiency should go hand in hand with minimizing the activities of enterprises, which necessitates the use of circular economy. The main prerequisites for the transition to a circular economy are analyzed. It is determined that the basic concept of the circular economy involves the development of a system of production and consumption, which is based on processing, reuse, repair, product sharing, change of consumption patterns and new business models and systems. The main elements of the circular economy include: a closed cycle, the use of renewable energy sources, systems thinking. The correlation of the principles of sustainable development and the peculiarities of the application of the circular economy is analyzed. It is determined that the circular economy contrasts with the traditional linear economic model, which is based on the model of "take-do-consume-throw away". The advantages and disadvantages due to the use of the principles of circular economy are given. Based on the study, steps are identified to accelerate the transition from a linear economy to a circular economy.

• Korean Journal of Computational Design and Engineering
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• v.16 no.4
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• pp.268-276
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• 2011

The product-level carbon footprint (PCF) is a comprehensive and widely accepted metric for sustainable product development. However, since a full PCF study in general is time and cost intensive, it is not feasible for the product development team to synchronize the activity to the main product development process. In addition, the current dedicated life cycle assessment (LCA) tools for calculating PCF, separated from the main product data management systems, have limitations to provide timely PCF information for design decision makings and collaborations between design and environment engineers. This paper examines the possibility of the extension of the current product data model that can support the PCF calculation with PDM (Product Data Management) databases. The product data model can represent not only the content of products but also context or system information of the products. The product data model can be implemented as a PDM database that can satisfy the needs for handy and timely PCF calculations from the consistent product data for dynamic design decision makings and engineering collaborations.

• 시스템엔지니어링워크숍
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• s.4
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• pp.151-154
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• 2004

This paper presents the general system theory and its applications to the safety analysis method that is a recent trend over the traditional event-driven model. This new model is known as STAMP(Systems Theory Accident Modeling and Process)proposed by Nancy G. Leveson in MIT. The new model has benefits of systemic approaches concerning the system safety as a whole including the context it is in, its stimulants and outcomes, and its parts as well as the relationships among them in a holistic manner. The method consists of a hierarchical control structure, a process model, and the safety constraints governing the control. This paper demonstrates an example the contrasts the differences between the approaches of STAMP and the traditional safety models.

• Communications for Statistical Applications and Methods
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• v.27 no.1
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• pp.37-46
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• 2020

Recurrent event data frequently occur in clinical studies, demography, engineering reliability and so on (Cook and Lawless, The Statistical Analysis of Recurrent Events, Springer, 2007). Sometimes, two or more different but related type of recurrent events may occur simultaneously. In this study, our interest is to estimate the covariate effect on bivariate recurrent event times with zero inflations. Such zero inflation can be related with susceptibility. In the context of bivariate recurrent event data, furthermore, such susceptibilities may be different according to the type of event. We propose a joint model including both two intensity functions and two cure rate functions. Bivariate frailty effects are adopted to model the correlation between recurrent events. Parameter estimates are obtained by maximizing the likelihood derived under a piecewise constant hazard assumption. According to simulation results, the proposed method brings unbiased estimates while the model ignoring cure rate models gives underestimated covariate effects and overestimated variance estimates. We apply the proposed method to a set of bivariate recurrent infection data in a study of child patients with leukemia.

• Transactions of Materials Processing
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• v.19 no.8
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• pp.468-473
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• 2010

Shape memory alloys (SMAs) have the ability to recover their original shape upon thermo-mechanical loading even after large inelastic deformation. The unique feature is known as pseudoelasticity and shape memory effect caused by the crystalline structural transformation between two solid-state phases called austenite and martensite. To support the engineering application, a number of constitutive models, which can be formally classified into either micromechanics-based or phenomenological model, have been developed. Most of the constitutive models include a kinetic law governing the crystallographic transformation. The present work presents a one-dimensional, phenomenological constitutive model for SMAs in the context of the unified viscoplasticity theory. The proposed model does not incorporate the complex mechanisms of phase transformation. Instead, the effects induced by the transformation are depicted through the growth law for the back stress that is an internal state variable of the model.