• 한국조사연구학회:학술대회논문집
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• 한국조사연구학회 2001년도 춘계학술대회
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• pp.109.1-127
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• 2001

이 글에서는 사회 조직이나 집단에 참여하는 개인들의 사회인구학적 특성을 통해 이들 조직의 생태지위를 측정하는 방법을 인터넷사이트와 자원조직이라는 두 가지 사례를 통해 제시하였다. 구체적으로 인터넷사이트의 생태지위는 사이트 방문자들의 연령과 교육연수로, 자원조직은 참여자들의 연령, 교육연수, 직업위신을 바탕으로 측정하였다. 결과적으로 이 글에서는 참여자들의 사회인구학적 특성을 바탕으로 각 조직들의 생태지위의 범위 뿐 아니라, 생태지위간의 중복 정도를 통하여 조직들간의 잠재적 경쟁 및 공생의 가능성을 분석할 수 있다는 것을 제시하였다. 이는 조직의 성과에 대한 조직 환경의 영향을 생태학적으로 분석하는 것을 가능하게 한다. 결론적으로, 이 글에서는 생태지위의 분포를 참여하는 개인들의 사회인구학적 특성의 분포를 측정함으로써 조직이 사회적인 진공 상태에서 무작위로 만들어지는 것이 아니라, 조직을 구성하는 개인들의 연령, 교육, 직업위신과 같은 사회인구학적 변수들의 분포의 영향을 받는다는 것을 보여주고자 하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권10호
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• pp.4214-4230
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• 2020

This paper introduces a pilot allocation scheme for massive MIMO systems based on deep convolutional neural network (CNN) learning. This work is an extension of a prior work on the basic deep learning framework of the pilot assignment problem, the application of which to a high-user density nature is difficult owing to the factorial increase in both input features and output layers. To solve this problem, by adopting the advantages of CNN in learning image data, we design input features that represent users' locations in all the cells as image data with a two-dimensional fixed-size matrix. Furthermore, using a sorting mechanism for applying proper rule, we construct output layers with a linear space complexity according to the number of users. We also develop a theoretical framework for the network capacity model of the massive MIMO systems and apply it to the training process. Finally, we implement the proposed deep CNN-based pilot assignment scheme using a commercial vanilla CNN, which takes into account shift invariant characteristics. Through extensive simulation, we demonstrate that the proposed work realizes about a 98% theoretical upper-bound performance and an elapsed time of 0.842 ms with low complexity in the case of a high-user-density condition.

• Journal of Power Electronics
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• 제13권3호
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• pp.419-428
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• 2013

The modular multilevel cascade converter (MMCC) is a new family of multilevel power converters with modular realization and a cascaded pattern for submodules. The MMCC family can be classified by basic configurations and submodule types. One member of this family, the Hexverter, is configured as Double-Delta Full-Bridge (DDFB). It is a novel multilevel AC/AC converter with direct power conversion and comparatively fewer required components. It is appropriate for connecting two three-phase systems with different frequencies and driving an AC motor directly from a utility grid. This paper presents the dq model of a Hexverter with both of its AC systems by state-space representation, which then simplifies the continuous time-varying model into a periodic discrete time-invariant one. Then a generalized multivariable optimal control strategy for regulating the Hexverter's independent currents is developed. The resulting control structure can be adapted to other MMCCs and is flexible enough to include other control criterion while guaranteeing the original controller performance. The modeling method and control design are verified by simulation results.

• International Journal of Computer Science & Network Security
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• 제22권3호
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• pp.252-258
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• 2022

Globalization, development of the information society, intensification of migration processes, and internationalization of education in recent years have significantly affected the international labour market and increased competition between professionals in various fields. Academic, research and teaching staff are currently facing rapid changes and growing demand for quality educational services. Under such conditions, educational institutions around the world pay particular attention to improving the quality of the educational process in order for their graduates to be able to compete in the international labour market. The study of the experience of teachers' professional training in advanced countries opens new opportunities for improving the system of pedagogical training in Ukraine in order to adapt it to the requirements of the European educational space. The progressive achievements of countries demonstrating a high level of teachers' professional training in accordance with international standards, having rich historical educational traditions are of considerable scientific interest; consequently, this contributes to their leadership in science and education at the regional and global levels. The purpose of the present academic paper lies in analysing the latest trends in exploring teaching experience in the European countries and performance review of passing by students and teachers of the program on studying of pedagogical practice and experience of teaching in the countries of Europe. Methodology. Analytical and empirical (questionnaire) methods were used in the research process. Results. According to the obtained results of the research, the advantages, the most common areas of educational programs and the wishes of the participants regarding the practical implementation of the experience were identified.

• 한국경제지리학회지
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• 제24권1호
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• pp.14-28
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• 2021

관광은 일상의 대척점으로 간주되어 왔다. 일상은 매일 반복되는 시간에 일상적 공간에서 행해지는 평범한 경험이고, 관광은 한시적 시간에 비일상적 공간에서 행해지는 색다른 경험으로 인식되었다. 본고는 관광과 일상을 바라보는 이분법적 사고를 뛰어넘어 각각의 경계를 초월한 결합에 초점을 두고 있다. 이를 위해 관광공간에서 나타나는 일상의 평범함을 분석하고, 역으로 일상공간에서 표출되는 관광적인 색다름을 파악했다. 분석 결과 일상생활의 루틴은 관광 실천에 영향을 주고, 수행을 통한 가족여행은 관광공간을 일상화시키며. 현지 주민의 평범한 일상을 경험하기 위한 비전형적 관광공간이 글로벌 도시의 근린에서 나타난다는 점을 도출했다. 이를 통해 일상생활은 더욱 관광화되고, 관광은 보다 일상화된다는 점을 파악했으며, 궁극적으로 일상과 관광 간의 결합을 도모할 수 있었다.

• Smart Structures and Systems
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• 제26권3호
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• pp.345-360
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• 2020

Modern swarm intelligence heuristic search methods are widely applied in the field of structural health monitoring due to their advantages of excellent global search capacity, loose requirement of initial guess and ease of computational implementation etc. To this end, a hybrid strategy is proposed based on butterfly optimization algorithm (BOA) and differential evolution (DE) with purpose of effective combination of their merits. In the proposed identification strategy, two improvements including mutation and crossover operations of DE, and dynamic adaptive operators are introduced into original BOA to reduce the risk to be trapped in local optimum and increase global search capability. The performance of the proposed algorithm, hybrid butterfly optimization and differential evolution algorithm (HBODEA) is evaluated by two numerical examples of a simply supported beam and a 37-bar truss structure, as well as an experimental test of 8-story shear-type steel frame structure in the laboratory. Compared with BOA and DE, the numerical and experimental results show that the proposed HBODEA is more robust to detect the reduction of stiffness with limited sensors and contaminated measurements. In addition, the effect of search space, two dynamic operators, population size on identification accuracy and efficiency of the proposed identification strategy are further investigated.

• 디지털융복합연구
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• 제11권8호
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• pp.213-218
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• 2013

본 논문은 자동차 점검이 이루어질 때 작업현장, 교육현장, 기타 시공간에서 현재 상황에 따라 지능화 및 개인화에 근거해 추천함으로써 생산성 향상, 비용절감, 성과향상 등을 이루고자 한다. 이에 본 연구는 태스크 온톨로지를 이용한 자동차 점검 추천시스템 개발 방법을 설계하였다. 추천 방법은 추상개념을 기반으로 각 추상개념에 연결되는 부품들을 가중치 값 순서로 보여줄 수 있도록 하고, 부품이 다른 추상개념과 연결될 경우 부품들을 확장하여 보여 주도록 하였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.19-24
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• 2003

A new method for designing critical control systems is proposed in this paper. The controller structure is chosen as a Davison type integral controller with an observer. The proposed method consists of two steps. First, the state feedback critical control system is designed using a quadratic performance index with tunable parameters. Second, the observer gain matrix is determined by the formal LTR procedure using a Riccati equation. Consequently, the search space can be reduced considerably compared with the conventional approach. Although the proposed method sacrifices a large freedom for the choice of controller structure provided by the principle of matching, the controller structure used in this paper is not excessively complex and can be used for most applications. An illustrative design example is presented.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권7호
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• pp.1815-1830
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• 2012

Existing R-tree that is based on a variety of outdoor-based techniques to manage moving objects have been investigated. Due to the different characteristics of the indoor and outdoor, it is difficult to management of moving object using existed methods in indoor setting. We propose a new index structure called ACII(adaptive Cell-based index for Indoor moving objects) for Indoor moving objects. ACII is Cell-based access structure adopting an overlapping technique. The ACII refines cells adaptively to handle indoor regional data, which may change its locations over time. The ACII consumed at most 30% of the space required by R-tree based methods, and achieved higher query performance compared with r-tree based methods.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -2
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• pp.1094-1097
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• 2002

Realtime applications like VoIP(Voice over IP) in All-IP networks need smooth handoffs in order to minimize or eliminate packet loss as a Mobile Host(MH) transitions between network links. In this paper, we design a new dynamic buffering(DB) mechanism for IPv6 by which an MH can request that the router on its current subnet buffers packets on its behalf while the MH completes registration procedures with the router of a new subnet. Performance results show that our proposed buffering scheme with a dynamic buffer space allocation is quite appropriate for mobile Internet, or the All-IP environment in terms of the datagram loss rate.