• Journal of Information Technology and Architecture
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• v.9 no.1
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• pp.33-42
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• 2012

Present many organizations are introduced to smartwork for reducing the operational cost and getting the labor's flexibility. The smartwork is the future-oriented worker's environment in which they can engage in their task, anytime and anywhere conveniently and efficiently. In spite of many smartwork advantages, the security problems are major issues and prevent to introducing and spreading of smartwork for organizations. Therefore, the success of the organization for smartwork environment is put in place appropriate security control model. This study is about security threats for smartwork security control model. We apply the exploratory method for this research, which are reviewing, analyzing of literature for extracting the security threats and clustering of the extracted security threats. Finally we define the 16's security threats according to the aspect of smartwork service layers.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.3
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• pp.7-14
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• 2003

MPEG-1 audio standard is the algorithm for the compression of high-qualify digital audio signals. The standard dictates the functions of encoder and decoder pair, and includes three different layers as the complexity and the performance of the encoder and decoder. In this paper, we implemented the real-time system of MPEG-1 audio layer III decoder(MP3) with the TMS320C541 fixed point DSP chip. MP3 algorithm uses psycho-acoustic characteristic of human hearing system, and it reduces the amount of data with eliminating the signals hard to be heard to the hearing system of human being. It is difficult to implement MP3 decoder with fixed Point DSP because of it's broad dynamic range. We implemented realtime system with fixed DSP chip by using weighted look-up tables to reduce the amount of calculation and solve the problem of broad dynamic range.

• KIPS Transactions on Computer and Communication Systems
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• v.1 no.1
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• pp.11-20
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• 2012

Stream data shows a sequence of values changing continuously over time. Due to the nature of stream data, its trend is continuously changing according to various time intervals. Therefore the prediction of stream data must be carried out simultaneously with respect to multiple intervals, i.e. Continuous Multiple Prediction(CMP). In this paper, we propose a Continuous Integrated Hierarchical Temporal Memory (CIHTM) network for CMP based on the Hierarchical Temporal Memory (HTM) model which is a neocortex leraning algorithm. To develop the CIHTM network, we created three kinds of new modules: Shift Vector Senor, Spatio-Temporal Classifier and Multiple Integrator. And also we developed learning and inferencing algorithm of CIHTM network.

• Korean Security Journal
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• no.56
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• pp.55-81
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• 2018

The purpose of this study is to find significant activities in human resource management (HRM) to solve growing-pains caused by the rapid external growth in private security business. To this end, we applied the HRM factors suggested by the National Job Capability Standard (NCS) to the private security and investigated the relative importance using the Analytic Hierarchy Process (AHP). The results were as follows. First, the importance of 4 HRM criteria in the private security was ranked in order of recruitment, operation, benefit, and retirement. Particularly, the relative importance of recruitment reached 63.8%. Second, the composite importance was calculated by dividing the 4 HRM criteria into 14 capability sub-criteria and 46 capability alternatives. As a result, personnel planning and hiring at the recruitment turned out as the areas that needed the most improvement. In addition, the operating and planning of education involved in the highest rank, 8th and 10th respectively. Based on these results, we suggested critical HRM factors for developing the private security business as well as proposed research directions and methods for further studies.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.215-215
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• 2015

SWG(Smart Water Grid)는 한정적인 수자원을 효율적으로 이용하고 사용자 입맛에 맞춰 물을 안정적으로 공급하고자 하는 양방향 개념으로 수자원 분야에서 각광받는 실정이다. SWG의 성능을 평가하는 연구사례는 많지 않으며 현재 국내의 경우 실증단지를 구축하고 있는 단계이다. 그러므로 성능평가를 수행하기 위한 실측자료가 부재하므로 성능평가 지표선정에 활용 할 수 있는 자료가 제한적이다. 따라서 미국의 Leed, 영국의 BREEAM, 일본의 CASBEE, 호주의 Green Star의 인증 기준에서 수자원에 대한 항목과 기존의 IWA, World Bank, AWWA, JWWA, OFWAT 같은 해외 상수도 수행능 지표와 상수도 및 정수장 기술진단에서 제시하는 기준을 바탕으로 성능평가지표를 선정 보완하여 Water Facility Index, Smart Index, Optimum System Index로 분류하여 각 세부의 성능평가지표를 선정하였다. 선정된 지표는 AHP기법를 활용하여 1-4단계에 걸쳐 계층화를 실시하고 Bottom-up방식으로 4단계에서부터 1단계로 평가를 진행하도록 구성했다. 4단계에서는 계층 별 쌍대비교 결과를 바탕으로 중요도에 따른 가중치를 부여하고 차등 점수를 적용하며, 이는 3단계에서 필수적으로 만족해야하는 지표들을 설정하고 평가하기 위해 사용된다. 3단계에서는 지표평가 후 "보통" 이상의 점수를 획득해야 2단계로 진행할 수 있고, 2단계에서는 3가지 큰 지표를 설정 후 총점 기준 60%이상의 최소득점 기준을 만족해야 1단계로 진행할 수 있도록 구성했다. 이러한 절차를 바탕으로 마지막 1단계에서는 100점을 만점으로 하는 6단계의 최종성능을 평가하는 결과를 제시할 수 있다. 본 연구에서는 국외 성능평가 사례 중 SWG와 관련된 지표를 구성하여 성능평가를 수행할 수 있는 기법을 제안하였다. 향후 지속적인 연구 진행 결과와 실측자료를 수집하여 수정 및 보완이 수행될 예정이다.

• Journal of Digital Convergence
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• v.19 no.12
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• pp.557-565
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• 2021

This study was attempted to identify differences in self-esteem and grit in adolescents depending on the type of parenting attitude. Among the Korea Children Youth Panel Survey conducted by National Youth Policy Institute, the data of 2,438 first-year middle school students in 2018 year were analyzed. The collected data were analyzed using hierarchical cluster analysis and k-mean cluster analysis. As a result, the adolescent's perceived parenting attitude was classified into four types: 'passive affection acceptance', 'active affection acceptance', 'authoritarian inconsistency', and 'lack of affection rejection'. Also, there were significant differences in self-esteem and the degree of grit among the four clusters of parenting attitudes. Both self-esteem and grit were highest in the "active affection acceptance" group 2. In the future, differentiated parental education is needed for each cluster to improve self-esteem and grit of adolescents, and this study can be used as a basic data for the development of educational programs.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.6
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• pp.631-637
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• 2018

In 5G mobile communication, it is necessary to provide different mobility to user equipments(UE) that do not require mobility management or need limited mobility management. In this paper, we propose a two-layer mobility management system that classifies multiple MTC devices with similar mobility levels into c-MTC and m-MTC groups. In order to improve the energy efficiency and service life by reducing the number of control signals generated when TAU is performed, the group header typically performs a Tracking Area Update(TAU) request and adjusts the periodic TAU update period according to the mobility level. The TAU update period of the m-MTC is set to 54 minutes proposed by the 3GPP standard and the c-MTC is set to 12 minutes. Compared to when the UEs perform TAU individually, it is found that the number of control signals decreases by 33% when the MME is not changed and by 49% when the MME is not changed in the m-MTC or c-MTC group.

• The Mathematical Education
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• v.60 no.2
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• pp.191-207
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• 2021

Recently, the number of multicultural families has significantly increased in Korea, and this trend creates a need to understand how successfully students from multicultural families achieve their mathematics learning. To understand and predict the changes in mathematics learning achievement of these students over time, we conducted in this study a latent growth mixture model analysis. The study findings show that the majority (92%) of the students from multicultural families experience a decrease in their mathematics achievement over time as their grade level goes up. It was found, in particular, that female students are likely to have lower initial achievements and rapid decline over time more than male students and that the decline over time was more severe for female students than their male counterparts. The findings of this study convey several implications on the how to support the students from multicultural families. First, the result of this study was different from the outcomes of previous studies that presented the income of the household and the education level of the students' parents as major factors that determine the academic achievement of the students from multicultural families. Furthermore, the study indicates the need for more research to identify variables related to the mathematical achievements of the students from multicultural families and the need to use these research findings to develop public support plans for the students from multicultural families.

• The Korean Journal of Applied Statistics
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• v.33 no.6
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• pp.833-842
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• 2020

Global platforms such as Netflix, Amazon, and YouTube have developed a precise recommendation system based on various information from large set of customers and many of the items recommended here are leading to actual purchases. In this paper, a cluster analysis was conducted according to the attribute of the content, expecting that there would be a difference in user preferences according to the attribute of the recommended content. Gower distance was used for use regardless of the type of variables. In this paper, using the data of movie rating site 'The Movie Dataset', the users were grouped hierarchically and recommended movies based on genre, director and actor variables. To evaluate the recommended systems proposed, user group was divided into train set and test set to examine the precision. The results showed that proposed algorithms have far higher precision than UBCF.

• Journal of the Korea Society of Computer and Information
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• v.26 no.4
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• pp.47-53
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• 2021

In this paper, we propose a quadtree-based optimization technique that enables fast Super-resolution(SR) computation by efficiently classifying and dividing physics-based simulation data required to calculate SR. The proposed method reduces the time required for quadtree computation by downscaling the smoke simulation data used as input data. By binarizing the density of the smoke in this process, a quadtree is constructed while mitigating the problem of numerical loss of density in the downscaling process. The data used for training is the COCO 2017 Dataset, and the artificial neural network uses a VGG19-based network. In order to prevent data loss when passing through the convolutional layer, similar to the residual method, the output value of the previous layer is added and learned. In the case of smoke, the proposed method achieved a speed improvement of about 15 to 18 times compared to the previous approach.