• 한국통신학회논문지
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• 제37권5A호
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• pp.325-338
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• 2012

본 논문에서는 무선 인지(Cognitive Radio, CR) 기반의 다중 홉 릴레이 전송 환경에서 링크별 가용 주파수 자원을 할당하는 문제를 다룬다. 경로 탐색, 채널 센싱 및 판단, 자원 할당의 3단계 시나리오를 제시하고 컬러 다중 그래프 모델과 시분할 된 프레임 구조를 토대로 서비스 받는 사용자의 수를 최대화하는 최적화 문제로 수학적 모델링을 한다. 이에 대한 해법으로 단말 선택, 릴레이 및 경로 선택 그리고 각 홉별 주파수 자원 선택의 3단계로 구성되는 부 최적화된 종합적 자원관리 방안을 제시한다. 모의실험에서는 홉-별 시분할 된 프레임 구조를 가지는 셀룰러 기반 2차 시스템을 고려하였으며, 다중 홉 통신과 단일 홉 통신 간의 성능을 비교를 통해 무선인지 시스템에서 다중 홉 통신의 필요성을 보였다. 또한 다중 홉 통신 가운데 가장 우수한 홉 수와 그 환경에 대해 살펴보았다.

• 산업경영시스템학회지
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• 제43권1호
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• pp.1-6
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• 2020

Fast service access involves keeping track of the location of mobile users, while they are moving around the mobile network for a satisfactory level of QoS (Quality of Service) in a cost-effective manner. The location databases are used to keep track of Mobile Terminals (MT) so that incoming calls can be directed to requested mobile terminals at all times. MT reporting cell system used in location management is to designate each cell in the network as a reporting cell or a non-reporting cell. Determination of an optimal number of reporting cells (or reporting cell configuration) for a given network is reporting cell planning (RCP) problem. This is a difficult combinatorial optimization problem which has an exponential complexity. We can see that a cell in a network is either a reporting cell or a non-reporting cell. Hence, for a given network with N cells, the number of possible solutions is 2^N. We propose a biogeography based optimization (BBO) for design of mobile station location management system in wireless communication network. The number and locations of reporting cells should be determined to balance the registration for location update and paging operations for search the mobile stations to minimize the cost of system. Experimental results show that our proposed BBO is a fairly effective and competitive approach with respect to solution quality for optimally designing location management system because BBO is suitable for combinatorial optimization and multi-functional problems.

• 한국시스템다이내믹스학회:학술대회논문집
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• 한국시스템다이내믹스학회 2002년도 춘계학술대회발표논문집
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• pp.19-40
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• 2002

경제 활동의 근간이 되는 에너지 공급원으로서의 원자력 발전소는 그 경제적 성과의 중요성뿐만 아니라 안전성을 확보하는 것도 매우 중요하다. <그림 1>에서 볼 수 있듯이 원전의 안전성은 하드웨어(hardware) 개선을 포함한 공학적 성능과 조직 및 인적 관리 요소에 대한 부분이 상호 작용하는 시스템 구조를 갖음에도 불구하고, 원전의 경제성과 안전성을 확보하기 위한 조직 및 인적 관리분야에 대한 연구는 기술분야에 비해 상대적으로 소홀히 취급된 경향이 있다.(중략)

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권7호
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• pp.1533-1546
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• 2013

Wireless multicast is considered as an effective transmission mode for the future mobile social contact services supported by Long Time Evolution (LTE). Though wireless multicast has an excellent resource efficiency, its performance suffers deterioration from the channel condition and wireless resource availability. Cognitive Radio (CR) and Device to Device (D2D) are two solutions to provide potential resource. However, resource allocation for cognitive wireless multicast based on D2D is still a great challenge for LTE social networks. In this paper, a joint sub-carriers and power allocation model based on D2D for general cognitive radio multicast (CR-D2D-MC) is proposed for Orthogonal Frequency-Division Multiplexing (OFDM) LTE systems. By opportunistically accessing the licensed spectrum, the maximized capacity for multiple cognitive multicast groups is achieved with the condition of the general scenario of imperfect spectrum sensing, the constrains of interference to primary users (PUs) and an upper-bound power of secondary users (SUs) acting as multicast source nodes. Furthermore, the fairness for multicast groups or unicast terminals is guaranteed by setting a lower-bound number of the subcarriers allocated to cognitive multicast groups. Lagrange duality algorithm is adopted to obtain the optimal solution to the proposed CR-D2D-MC model. The simulation results show that the proposed algorithm improves the performance of cognitive multicast groups and achieves a good balance between capacity and fairness.

• Journal of Communications and Networks
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• 제14권6호
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• pp.662-671
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• 2012

Plug-in hybrid electric vehicles (PHEVs) will be widely used in future transportation systems to reduce oil fuel consumption. Therefore, the electrical energy demand will be increased due to the charging of a large number of vehicles. Without intelligent control strategies, the charging process can easily overload the electricity grid at peak hours. In this paper, we consider a smart charging and discharging process for multiple PHEVs in a building's garage to optimize the energy consumption profile of the building. We formulate a centralized optimization problem in which the building controller or planner aims to minimize the square Euclidean distance between the instantaneous energy demand and the average demand of the building by controlling the charging and discharging schedules of PHEVs (or 'users'). The PHEVs' batteries will be charged during low-demand periods and discharged during high-demand periods in order to reduce the peak load of the building. In a decentralized system, we design an energy cost-sharing model and apply a non-cooperative approach to formulate an energy charging and discharging scheduling game, in which the players are the users, their strategies are the battery charging and discharging schedules, and the utility function of each user is defined as the negative total energy payment to the building. Based on the game theory setup, we also propose a distributed algorithm in which each PHEV independently selects its best strategy to maximize the utility function. The PHEVs update the building planner with their energy charging and discharging schedules. We also show that the PHEV owners will have an incentive to participate in the energy charging and discharging game. Simulation results verify that the proposed distributed algorithm will minimize the peak load and the total energy cost simultaneously.

• 한국BIM학회 논문집
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• 제14권3호
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• pp.1-12
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• 2024

Many efforts are being made to enhance user productivity and promote collaboration while ensuring the economic efficiency of office buildings. Analyzing space utilization, indicating how users utilize spaces, has been a crucial factor in these efforts. Appropriate space utilization enhances building maintenance and space layout design, reducing unnecessary energy waste and under-occupied spaces. Recognizing the importance of space utilization, there have been several studies to predict space utilization using information about users, activities, and spaces. These studies suggested an ontology of the information and implemented automated activity-space mapping as part of space utilization prediction. Despite the existing studies, there remains a gap in integrating space utilization prediction with automated space layout design. As a foundational study to bridge this gap, our study proposes a novel methodology that automatically generates office rooms based on space utilization optimization. This methodology consists of three modules: Activity-space mapping, Space utilization calculation, and Room generation. The first two modules use data on space types and user activity types as input to calculate and optimize space utilization through requirement-based activity-space mapping. After optimizing the space utilization value within an appropriate range, the number and area of each space type are determined. The Room generation module then automatically generates rooms with optimized areas and numbers. The practical application of the developed methodology is demonstrated, highlighting its effectiveness in fabricated case scenario. By automatically generating rooms with optimal space utilization, our methodology shows potential for expanding to automated generation of optimized space layout design based on space utilization.

• 한국도로학회논문집
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• 제10권4호
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• pp.117-125
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• 2008

최근 녹색교통수단으로서 자전거의 이용자수는 급격하게 증가하고 있으나 차대 자전거사고 감소와 자전거 이용자의 안전성 향상에 대한 노력은 미비한 설정이다. 따라서 본 연구에서는 최적의 교차로 설계지침 제공 및 자전거 사고유형에 영향을 미치는 요인들을 면밀히 분석하여 교차로에서의 자전거사고 안전성 향상에 그 목적이 있다. 이를 위해 본 연구에서는 2005년도 인천광역시 사지교차로에서 발생한 56건의 자전거사고 자료에 대한 분석과 사고발생 교차로에 대한 현장조사를 실시하였으며, 다항로짓모형을 이용하여 3가지 경우에 대한 자전거 사고유형 분석모형을 개발하였다. 모형분석결과, 사망사고 유무, 부도로 교통섬 유무, 도로위계, 사고당시 날씨, 주도로 버스정류장 유무, 주도로 차로폭, 인적유발요인이 자전거 사고 유형에 중요한 변수로 나타났다.

• Journal of Communications and Networks
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• 제6권1호
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• pp.68-77
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• 2004

In the near future packet networks should support applications which can not predict their traffic requirements in advance, but still have tight quality of service requirements, e.g., guaranteed bandwidth, jitter, and packet loss. These dynamic characteristics mean that the sources can be made to modify their data transfer rates according to network conditions. Depending on the customer&; needs, network operator can differentiate incoming connections and handle those in the buffers and the interfaces in different ways. In this paper, dynamic QoS-aware scheduling algorithm is presented and investigated in the single node case. The purpose of the algorithm is in addition to fair resource sharing to different types of traffic classes with different priorities ?to maximize revenue of the service provider. It is derived from the linear type of revenue target function, and closed form globally optimal formula is presented. The method is computationally inexpensive, while still producing maximal revenue. Due to the simplicity of the algorithm, it can operate in the highly nonstationary environments. In addition, it is nonparametric and deterministic in the sense that it uses only the information about the number of users and their traffic classes, not about call density functions or duration distributions. Also, Call Admission Control (CAC) mechanism is used by hypothesis testing.

• 제어로봇시스템학회논문지
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• 제6권8호
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• pp.623-628
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• 2000

Video-on-demand system in which users can request any video through the network at any time is made possible by rapid increase in network bandwidth and capacity of the media server. However true video-on-demand system cannot support all requests since bandwidth requirement is still too demanding. Therefore efficient bandwidth reduction algorithm is necessary. both the piggybacking method and the batching method are novel solutions that can provide more logical number of streams than the physical system can support. Of course each of them has its pros and cons. hence piggybacking with batching-by-size can take advantage of both the schemes. Some parameters such as the size of batch and the size of the catch-up window should be adjusted and order to maximize the bandwidth reduction for piggybacking with batching-by-size method. One of the most important parameters is decided optimally in this paper. Simulation shows that the optimized parameter can achieve considerable reductionand consequently remarkable enhancement in performance.

• 한국멀티미디어학회논문지
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• 제24권2호
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• pp.274-284
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• 2021

Customized services to a sleep induction for better sleepcare are more effective because of different satisfaction levels to users. The EOG data measured at the frontal lobe when a person blinks his eyes can be used as biometric data because it has different values for each person. The accuracy of measurement is degraded by a noise source, such as toss and turn. Therefore, it is necessary to analyze the noisy data and remove them from normal EOG by filtering. There are low-pass filtering and high-pass filtering as filtering using a frequency band. However, since filtering within a frequency band range is also required for more effective performance, we propose a machine learning model for the filtering of EOG data in this paper as the second filtering method. In addition, optimal values of parameters such as the depth of the hidden layer, the number of nodes of the hidden layer, the activation function, and the dropout were found through experiments, to improve the performance of the machine learning filtering model, and the filtering performance of 95.7% was obtained. Eventually, it is expected that it can be used for effective user identification services by using filtering model for EOG data.