• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.2042-2047
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• 2005

Many service robots which is interacting with human at home and in buildings have been developed. Few of them are shown in of the United States and of Japan. These robots are supposed to have a powerful indoor navigation performance in places where human beings live and work. The overall capability of service robots to move around in this environment is called environment correspondence, in which localization problem to find the accurate position and orientation is the most critical problem. While users set up a proper or a best environment for industrial robots, but for services robots at home and in buildings, it is very difficult to change the environment for robots. The expanded workspace due to mobility is difficult to be covered by means of those used for industrial robots because the cost increases and human beings do not want their environment to be changed for robots. This fact has made many researchers study efficient and effective environment correspondence problems. Among these problems, localization is the most difficult. Goal of localization study includes (1) Accurate detection of position and orientation (2) Minimum cost of the additional devices (3) Minimum change of human environment. In this study, as a solution of the above, we propose "Artificial Stars" which are attached on room ceiling as landmarks. In addition, we solve an adoption problem raised when a robot is delivered to a customer site and before it can perform its full navigation capability. We call this as "Initialization Problem" of service robots. We solve the initialization problem for both cases of environment with the map and without map. The proposed system is experimented and has shown how well it handles the initialization problem.

• 제어로봇시스템학회논문지
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• 제13권8호
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• pp.804-809
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• 2007

Initialization problem is defined for indoor mobile robot as a whole process from arrival to normal operation in a new environment. The unstructured environment make the process much more difficult compared to industrial robot in structured environments. We propose a simple and efficient initialization process based on artificial stars on ceiling. Important task points and paths connecting task points are defined based on the corresponding artificial stars. This approach can be used for all kinds of indoor mobile robots with landmarks used for indoor localization.

• 한국지능시스템학회논문지
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• 제22권5호
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• pp.540-548
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• 2012

무기할당 문제(Weapon Target Allocation : WTA)는 전형적인 NP-Complete 문제로 공중에서 위협하는 표적에 대해 아군의 무기를 적절히 할당하는 문제이다. 이러한 NP-Complete 문제들은 주로 휴리스틱 알고리즘을 이용하여 최적해를 찾는다. 유전자 알고리즘은 대표적인 휴리스틱 알고리즘으로 다양한 도메인에서 우수한 성능을 보여주는 휴리스틱 알고리즘이다. 유전자 알고리즘의 단계 중에 population 초기화는 최초 염색체를 결정하는 문제로 유전자 알고리즘의 해의 질을 높일 수 있고, 탐색성능을 높일 수 있으나 많은 연구가 이루어지고 있지 않는 분야이다. 따라서 본 논문에서는 WTA 문제를 해결하기 위해 유전자 알고리즘의 성능을 향상시키기 위한 population 초기화 알고리즘을 제안하고자 한다. 제안하는 알고리즘은 초기화할 때 WTA 문제 도메인의 특성을 반영하고, 우성유전자를 상속받는다. 또한, 문제 공간에서의 탐색 공간을 넓게 선정하여 질이 좋은 해를 효율적으로 찾을 수 있도록 하였다. 본 논문에서는 제안하는 알고리즘과 다른 알고리즘과의 다양한 속성의 비교분석 및 실험을 통해 성능을 분석하여 제안하는 알고리즘의 우수성을 검증하였다. 실험 결과 제안하는 알고리즘이 WTA 문제 해결에서 다른 방법들에 비해 좋은 성능을 보였다. 특히, 제안하는 알고리즘은 문제 상황에 따라 RMI 수치를 조정하여 적응성 있게 적용할 수 있기 때문에, 문제의 상황이 다양한 WTA 문제 도메인에 적용하기 적합한 알고리즘이다.

• Journal of Communications and Networks
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• 제5권2호
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• pp.157-166
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• 2003

This paper deals with the problem of channel identification for Single Input Multiple Output (SIMO) slow fading channels using clustering algorithms. Due to the intrinsic memory of the discrete-time model of the channel, over short observation periods, the received data vectors of the SIMO model are spread in clusters because of the AWGN noise. Each cluster is practically centered around the ideal channel output labels without noise and the noisy received vectors are distributed according to a multivariate Gaussian distribution. Starting from the Markov SIMO channel model, simultaneous maximum ikelihood estimation of the input vector and the channel coefficients reduce to one of obtaining the values of this pair that minimizes the sum of the Euclidean norms between the received and the estimated output vectors. Viterbi algorithm can be used for this purpose provided the trellis diagram of the Markov model can be labeled with the noiseless channel outputs. The problem of identification of the ideal channel outputs, which is the focus of this paper, is then equivalent to designing a Vector Quantizer (VQ) from a training set corresponding to the observed noisy channel outputs. The Linde-Buzo-Gray (LBG)-type clustering algorithms [1] could be used to obtain the noiseless channel output labels from the noisy received vectors. One problem with the use of such algorithms for blind time-varying channel identification is the codebook initialization. This paper looks at two critical issues with regards to the use of VQ for channel identification. The first has to deal with the applicability of this technique in general; we present theoretical results for the conditions under which the technique may be applicable. The second aims at overcoming the codebook initialization problem by proposing a novel approach which attempts to make the first phase of the channel estimation faster than the classical codebook initialization methods. Sample simulation results are provided confirming the effectiveness of the proposed initialization technique.

• International journal of advanced smart convergence
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• 제8권2호
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• pp.132-139
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• 2019

We address the problem about forecasting the direction of stock price movement in the Korea market. Recently, the deep neural network is popularly applied in this area of research. In deep neural network systems, proper parameter initialization reduces training time and improves the performance of the model. Therefore, in our study, we propose a novel parameter initialization technique and apply this technique for the stock price movement prediction model. Specifically, we design a framework which consists of two models: a base model and a main prediction model. The base model constructed with LSTM is trained by using the large data which is generated by a large amount of the stock data to achieve optimal parameters. The main prediction model with the same architecture as the base model uses the optimal parameter initialization. Thus, the main prediction model is trained by only using the data of the given stock. Moreover, the stock price movements can be affected by other related information in the stock market. For this reason, we conducted our research with two types of inputs. The first type is the stock features, and the second type is a combination of the stock features and the Korea Composite Stock Price Index (KOSPI) features. Empirical results conducted on the top five stocks in the KOSPI list in terms of market capitalization indicate that our approaches achieve better predictive accuracy and F1-score comparing to other baseline models.

• 한국정보통신학회논문지
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• 제10권3호
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• pp.622-627
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• 2006

TSP(Traveling Salesman Problem)는 N개의 도시가 주어질 때 어떠한 임의의 도시에서 출발하여 모든 도시를 단 한번만 방문하여 다시 출발지로 되돌아오는 여려 경로들 중 가장 짧은 거 리를 구하는 문제이다. 방문 도시수가 증가함에 따라 계산량이 기하급수적으로 증가하게 되는 문제로 인해 NP-Hard문제로 분류되며 유전자 알고리즘이 대표적으로 이용된다. TSP문제에 있어서 보다 우수한 결과를 얻기 위해 현재까지 다양한 연산자들이 개발되고 연구되어 왔다. 본 논문에서는 새로운 집단 초기화 방법과 순차변환 방법을 제안하여 기존의 방법들과 비교를 통해 성능 향상을 입증하였다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1998년도 하계종합학술대회논문집
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• pp.887-890
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• 1998

We present a method for initialization of asynchronous circuits using binary decision space representation. From state transition graph(STG) which is given as a specification a circuit, the BDD is generated to solve the state space explosion problem which is caused by concurrecy of STG. We first step, we construct the necessary informaton as a form of K-map from BDD, then find an initial state on the K-map by assignment of don't care assignment.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.752-757
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• 2003

Recently, 3D structure recovery through self-calibration of camera has been actively researched. Traditional calibration algorithm requires known 3D coordinates of the control points while self-calibration only requires the corresponding points of images, thus it has more flexibility in real application. In general, self-calibration algorithm results in the nonlinear optimization problem using constraints from the intrinsic parameters of the camera. Thus, it requires initial value for the nonlinear minimization. Traditional approaches get the initial values assuming they have the same intrinsic parameters while they are dealing with the situation where the intrinsic parameters of the camera may change. In this paper, we propose new initialization method using the minimum 2 images. Proposed method is based on the assumption that the least violation of the camera’s intrinsic parameter gives more stable initial value. Synthetic and real experiment shows this result.

• ETRI Journal
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• 제26권2호
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• pp.92-100
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• 2004

In this paper, we propose an efficient method to broadcast digital television signals using single frequency networks (SFNs) within the Advanced Television Systems Committee (ATSC) transmission systems. In implementing the SFNs of an 8-vestigial side band (8-VSB) Digital Television (DTV) system, the ambiguity problem of the trellis coder is unavoidable in a conventional ATSC transmission system. We propose a memory initialization of the trellis coder to resolve this ambiguity problem. Since the proposed scheme to synchronize multiple transmitters minimizes the changes from the conventional ATSC system, the hardware complexity for these changes is very low. Our simulation results show that the proposed scheme makes a less than 0.1 dB degradation at the threshold of visibility with a bit error rate of $3{\times}10^{-6}$ in the additive white Gaussian noise (AWGN) channel. It is possible to reduce the performance degradation by increasing the initialization period of the proposed scheme.

• 스마트미디어저널
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• 제11권11호
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• pp.84-91
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• 2022

베이스보드 매니지먼트 컨트롤러(BMC, Baseboard Management Controller)는 다양한 통신 인터페이스를 사용하여 서버 모니터링, 유지보수, 제어 기능을 지원한다. 그러나, 디바이스 드라이버 초기화 과정에서 예기치 못한 문제가 발생할 경우 BMC가 정상적으로 동작하지 않을 수 있기 때문에 디바이스 드라이버 초기화 과정을 정확하게 분석하고, 분석 결과를 확인할 수 있는 기능을 제공하는 부팅 과정 프로파일링 도구는 필수적이다. 기존 부팅 과정 프로파일링 도구들은 BMC 부팅 과정 분석에 필요한 디바이스 드라이버 초기화 과정과 결과를 구체적으로 제공하지 않아 개발자가 필요에 따라 여러 도구를 조합하여 사용해야 하는 불편함이 있다. 본 논문에서는 BMC의 부팅 과정 프로파일링 도구를 제안한다. 제안하는 도구는 디바이스 드라이버 초기화 과정분석, CPU 및 메모리 사용률 분석, 커널 버전 관리 기능을 제공한다. 제안하는 도구를 사용하여 부팅 과정을 쉽게 분석할 수 있으며, 분석 결과는 부팅 시간 단축에 사용될 수 있다. 또한 제안한 도구를 Linux 기반의 BMC에 구현하고, 제안한 도구가 기존 프로파일링 도구에 비해 효율적임을 보인다.