• 한국정보통신학회논문지
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• 제9권5호
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• pp.1142-1148
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• 2005

본 논문에서는 클라이언트들의 작업부하를 분산하기 위한 측정 알고리즘을 제안하였다. 이 알고리즘은 작업들이 재배치되는 것을 허용할 때, 송신자가 수신자에게 요청한 처리량만큼 적절하게 전송하여야 한다. 이 양은 송신자와 수신자의 협상 과정에서 동적으로 결정된다. 전송하여야 할 작업량을 결정할 때 전송 노드는 수신하는 다른 노드들의 처리 속도를 포함하여 송신 노드와 수신 노드의 현재 부하상태, 재배치하기에 적절한 작업의 처리 요구량 등의 요소들을 고려하여야 한다. 이러한 분석에 근거하여 이기종 분산 웹서버 시스템에 적합한 새로운 알고리즘을 제안하고, 기존 알고리즘과의 성능을 비교하였다. 시뮬레이션을 통하여 본 논문에서 제안한 알고리즘이 CPU 이용율과 응답시간에서 성능의 개선을 보였다.

• 유통과학연구
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• 제15권7호
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• pp.35-41
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• 2017

Purpose - A product bundling is a marketing approach where multiple products or components are packaged together into one bundle solution. This paper aims to introduce an optimal bundle search problem (hereinafter called "OBSP") which may be embedded with online recommendation system to provide an optimized service considering pairwise discount and delivery cost. Research design, data, and methodology - Online retailers have their own discount policy and it is time consuming for online shoppers to find an optimal bundle. Unlike an online system recommending one item for each search, the OBSP considers multiple items for each search. We propose a mathematical formulation with numerical example for the OBSP and analyzed the complexity of the problem. Results - We provide two results from the complexity analysis. In general case, the OBSP belongs to strongly NP-Hard which means the difficulty of the problem while the special case of OBSP can be solved within polynomial time by transforming the OBSP into the minimum weighted perfect matching problem. Conclusions - In this paper, we propose the OBSP to provide a customized service considering bundling price and delivery cost. The results of research will be embedded with an online recommendation system to help customers for easy and smart online shopping.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 1999년도 추계학술대회 논문집 - 한국공작기계학회
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• pp.162-169
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• 1999

In this paper, it is presented a new scheme of adaptive-neuro control system to implement real-time control of robot manipulator using digital Signal Processors. Digital signal processors DSPs. are micro-processors that are particularly developed for variables. Digital version of most advanced control algorithms can be defined as sums and products of measured variables, thus it can be programmed and executed through DSPs. In addition, DSPs are as fast in computation as most 32-bit micro-processors and yet at a fraction of their prices. These features make DSPs a biable computatinal tool in digital implementation of sophisticated controllers. Unlike the well-established theory for the adaptive control of linear systems, there exists relatively little general theory for the adaptive control of nonlinear systems. Adaptive control technique is essential for providing a stable and robust performance for application of robot control. The proposed neuro control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method. The proposed adaptive-neuro control scheme is illustrated to be a efficient control scheme for implementation of real-time control of robot system by the simulation and experiment.

• 전기학회논문지
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• 제66권9호
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• pp.1402-1408
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• 2017

Recently, services for personal biometric data analysis based on real-time monitoring systems has been increasing and many of them have focused on recognition of emotions. In this paper, we propose a classification model to classify anxiety emotion using biometric data actually collected from people. We propose to deploy the support vector machine to build a classification model. In order to improve the classification accuracy, we propose two data pre-processing procedures, which are normalization and data deletion. The proposed algorithms are actually implemented based on Real-time Traffic Flow Measurement structure, which consists of data collection module, data preprocessing module, and creating classification model module. Our experiment results show that the proposed classification model can infers anxiety emotions of people with the accuracy of 65.18%. Moreover, the proposed model with the proposed pre-processing techniques shows the improved accuracy, which is 78.77%. Therefore, we can conclude that the proposed classification model based on the pre-processing process can improve the classification accuracy with lower computation complexity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권7호
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• pp.3369-3385
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• 2019

There are various research challenges in vehicular ad hoc networks (VANETs) that need to be focused until an extensive deployment of it becomes conceivable. Design and development of a scalable routing algorithm for VANETs is one of the critical issue due to frequent path disruptions caused by the vehicle's mobility. This study aims to provide a novel road-aware routing protocol for vehicular networks named as Two-level hierarchical Hybrid Road-Aware (THERA) routing for vehicular ad hoc networks. The proposed protocol is designed explicitly for inter-vehicle communication. In THERA, roads are distributed into non-overlapping road segments to reduce the routing overhead. Unlike other protocols, discovery process does not flood the network with packet broadcasts. Instead, THERA uses the concept of Gateway Vehicles (GV) for the discovery process. In addition, a route between source and destination is flexible to changing topology, as THERA only requires road segment ID and destination ID for the communication. Furthermore, Road-Aware routing reduces the traffic congestion, bypasses the single point of failure, and facilitates the network management. Finally yet importantly, this paper also proposes a probabilistical model to estimate a path duration for each road segment using the highway mobility model. The flexibility of the proposed protocol is evaluated by performing extensive simulations in NS3. We have used SUMO simulator to generate real time vehicular traffic on the roads of Gangnam, South Korea. Comparative analysis of the results confirm that routing overhead for maintaining the network topology is smaller than few previously proposed routing algorithms.

• 한국콘텐츠학회논문지
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• 제7권5호
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• pp.1-9
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• 2007

토폴로지 정보는 망에서 계층적으로 구성될 수 있으며, 토폴로지 정보를 요약하는 과정을 토폴로지 요약이라 한다. 이는 라우팅과 네트워크의 확장성에 매우 중요한 요소이다. 특히, 사설망 인터페이스에서 라우팅 알고리즘과 토폴로지 요약 알고리즘은 네트워크의 성능에 중요한 변수가 된다. 따라서 본 논문에서는 사설망 인터페이스에서 토폴로지 요약을 위한 라우팅 시뮬레이터를 설계 및 구현하였다. 그리고 구현된 시뮬레이터를 사용하여 기존 토폴로지 요약 알고리즘의 성능을 분석하였다. 구현된 사설망 인터페이스 시뮬레이터는 토폴로지 요약 알고리즘 개발에 유용하게 사용될 수 있다.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제51권3호
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• pp.116-124
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• 2002

Design and analysis of disturbance observer-based deadbeat control fur single-phase inverter applications are comprehensively presented in this paper. Load current can be estimated by disturbance observer, which is basically structured with the first order equation in this case and is regarded as a relatively simple method in comparison with conventional full-order Luenberger observer. Also, an inherent one-step delay problem appeared in the deadbeat control method is overcome by a simple prediction technique proposed. Output voltage dip is reduced by the feedforward control with the change rate of the estimated load current involved in the deadbeat current control loop. The proposed algorithms are verified by the respective simulation and experiment results.

• 한국콘텐츠학회논문지
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• 제9권12호
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• pp.877-885
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• 2009

본 논문은 그리드 컴퓨팅을 이용한 고성능 과학기술지식처리 프레임워크인 SINDI-Grid의 개발에 관련된 연구이다. SINDI-Grid 프레임워크는 대용량의 데이터 저장소 및 고속의 컴퓨팅 파워를 제공하는 그리드 컴퓨팅의 장점을 이용하여 분산 데이터 분석과 과학기술지식처리를 위한 다양한 그리드 서비스들을 제공한다. 그리고 SINDI-Workflow 도구는 이러한 서비스들을 이용하여 다양한 지식처리 알고리즘을 통합하는 복잡한 과학기술지식처리 애플리케이션을 설계하고 실행하는 역할을 수행한다.

• 한국음향학회지
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• 제22권1호
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• pp.54-60
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• 2003

구형 배플상의 피스톤 음원에 대하여 방사임피던스 특성을 2차원 축대칭 유한요소법과 하이브리드형 무한요소법을 사용하여 수치 해석하였다. 강체 배플에 있어서 피스톤 음원의 방사면 크기에 따른 자기방사임피던스 변화와 피스톤 음원간의 상호방사임피던스 변화를 계산한 결과는 알려진 해석해와 잘 일치하였다. 또한 비강체 배플의 적용에 따른 자기방사임피던스 및 상호방사임피던스의 변화를 규명함으로서 음향변환기의 설계 및 방사특성 해석에 응용되어질 것으로 기대된다.

• International Journal of CAD/CAM
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• 제5권1호
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• pp.19-27
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• 2005

As three-dimensional range scanners make large point clouds a more common initial representation of real world objects, a need arises for algorithms that can efficiently process point sets. In this paper, we present a method for extracting smooth surfaces from dense point clouds. Given an unorganized set of points in space as input, our algorithm first uses principal component analysis to estimate the surface variation at each point. After defining conditions for determining the geometric compatibility of a point and a surface, we examine the points in order of increasing surface variation to find points whose neighborhoods can be closely approximated by a single surface. These neighborhoods become seed regions for region growing. The region growing step clusters points that are geometrically compatible with the approximating surface and refines the surface as the region grows to obtain the best approximation of the largest number of points. When no more points can be added to a region, the algorithm stores the extracted surface. Our algorithm works quickly with little user interaction and requires a fraction of the memory needed for a standard mesh data structure. To demonstrate its usefulness, we show results on large point clouds acquired from real-world objects.