• 한국컴퓨터정보학회논문지
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• 제22권12호
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• pp.27-34
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• 2017

Design of an intelligent controller for efficient control in smart building is one of the effective technologies to reduce energy consumption by reducing response time with keeping comfortable level for inhabitants. In this paper, we focus on how to find major parameters in order to enhance the ability of HVAC(heating, ventilation, air conditioning) PID controller. For the purpose of that, we use machine learning technologies for tuning HVAC devices. We show the simulation results to illustrate the behavioral relation of whole system and each control parameter while learning process.

• International journal of advanced smart convergence
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• 제9권2호
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• pp.114-122
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• 2020

When replacing hardware due to obsolescence, discontinuation, and expansion of software-equipped electronic equipment, software changes are required in the past, but if virtualization technology is applied, it can be applied without software changes. In this regard, we studied in order to apply virtualization technology in the development of naval multi-function radar signal processing, we studied hardware and OS independency for Docker and performance comparison between Docker and virtual machine. As a result, it was confirmed that hardware and OS independence exist when using Docker and that high-speed processing is possible compared to the virtual machine.

• International journal of advanced smart convergence
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• 제7권3호
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• pp.15-22
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• 2018

Nowadays multiple control methods are used in robot control systems. A model, predictor or error estimator is often used as feedback controller to control a robot. While robots have become more and more intensive with algorithms capable to acquiring independent knowledge from raw data. This paper represents experimental results of real time machine learning control that does not require explicit knowledge about the plant. The controller can be applied on a broad range of tasks with different dynamic characteristics. We tested our controller on the balancing problem of a single propeller pendulum. Experimental results show that the use of a supervised machine learning algorithm in a single propeller pendulum allows the stable swing of a given angle.

• International journal of advanced smart convergence
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• 제7권3호
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• pp.66-72
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• 2018

In recent years, indoor simulated sports have become widely used, and screen baseball system has emerged that can play baseball in indoor space. In this paper, we propose a virtual pitching system that can improve the realism of screen baseball game. This virtual pitching system is characterized in that it uses a transmissive screen in the form of a pitching machine without a pitching hole and installed on the back of the screen. Therefore, unlike existing systems where pitching holes are formed on the screen, it enhances the immersion feeling of displayed images. Also, in this pitching system, the synchronization algorithm between the pitching machine and the virtual pitcher is used to form a sense of unity between the virtual pitcher and the ball according to various types of virtual pitchers, thereby enhancing the reality of baseball games.

• Smart Structures and Systems
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• 제1권2호
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• pp.121-140
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• 2005

This paper presents a systematic investigation of the effect of sensor location on the data quality and subsequently, on the effectiveness of machine health monitoring. Based on an analysis of the signal propagation process from the defect location to the sensor, numerical simulations using finite element modeling were conducted on a bearing test bed to determine the signal strength at several representative sensor locations. The results showed that placing sensors closely to the machine component being monitored is critical to achieving high signal-to-noise ratio, thus improving the data quality. Using millimeter-sized piezoceramic plates, the obtained results were evaluated experimentally. A comparison with a set of commercial vibration sensors verified the developed structural dynamics-based sensor placement strategy. It further demonstrated that the proposed shock wave-based sensing technique provided an effective alternative to vibration measurement, while requiring less space for sensor installation.

• Smart Structures and Systems
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• 제2권1호
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• pp.47-60
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• 2006

Bi-spectrum is a tool in the signal processing for identification of non-linear dynamic behvaiour in systems, and well-known for stationary system where components are non-linearly interacting. Breathing of a crack during shaft rotation is also exhibits a non-linear behaviour. The crack is known to generate 2X (twice the machine RPM) and higher harmonics in addition to 1X component in the shaft response during its rotation. Misaligned shaft also shows similar such feature as a crack in a shaft. The bi-spectrum method has now been applied on a small rotating rig to observe its features. The bi-spectrum results are found to be encouraging to distinguish these faults based on few experiments conducted on a small rig. The results are presented here.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2016년도 제53차 동계학술대회논문집 24권1호
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• pp.273-274
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• 2016

근래에 스마트폰 단말기 사용의 가속화와 빅 데이터의 사회적인 관심이 급증하고 있다. 빅 데이터 수집효율을 최대화하기 위해서 실외/내부에서 흔히 찾아 볼 수 있는 Vending Machine(이하 자판기)을 채택했다. 그리고 Main 서버에게 여러 종류의 방대한 데이터를 전송하여 빅 데이터 기술을 구현함으로써 자판기 관리자와 사용자에게 편리함과 부가서비스 제공환경에 대하여 제안한다.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2019년도 제59차 동계학술대회논문집 27권1호
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• pp.389-390
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• 2019

최근 블록체인 기반의 어플리케이션이 증가하고 이들을 위한 스마트 컨트랙트가 설계상 오류로 부적절하게 사용될 가능성이 증대되고 있다. 따라서 스마트 컨트랙트의 설계를 보다 안전하게 지원할 수 있는 방안이 필요한 실정이다. 본 논문에서는 State machine을 이용하여 이더리움 스마트 컨트랙트의 기능사용을 보다 안전하게 지원하기 위한 기법을 제안한다. 제안된 기법은 전체 동작의 흐름의 제어하기 위한 Transition Contract와 각각 상태에 대한 스마트 컨트랙트인 State Contract를 이용하여 스마트 컨트랙트의 동작과정을 제어한다.

• Journal of Information Processing Systems
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• 제15권1호
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• pp.116-126
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• 2019

In this paper, an improved one-against-one support vector machine algorithm is used to classify multiple power quality disturbances. To solve the problem of parameter selection, an improved particle swarm optimization algorithm is proposed to optimize the parameters of the support vector machine. By proposing a new inertia weight expression, the particle swarm optimization algorithm can effectively conduct a global search at the outset and effectively search locally later in a study, which improves the overall classification accuracy. The experimental results show that the improved particle swarm optimization method is more accurate than a grid search algorithm optimization and other improved particle swarm optimizations with regard to its classification of multiple power quality disturbances. Furthermore, the number of support vectors is reduced.

• International journal of advanced smart convergence
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• 제9권4호
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• pp.156-166
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• 2020

In this paper, to improve spectral efficiency and mitigate interference in coordinated millimeter-wave systems, we proposes an optimal user group and beam selection scheme. The proposed scheme improves spectral efficiency by mitigating intra- and inter-cell interferences (ICI). By examining the effective channel capacity for all possible user combinations, user combinations and beams with minimized ICI can be selected. However, implementing this in a dense environment of cells and users requires highly complex computational abilities, which we have investigated applying multiclass classifiers based on machine learning. Compared with the conventional scheme, the numerical results show that our proposed scheme can achieve near-optimal performance, making it an attractive option for these systems.