• 방송공학회논문지
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• 제16권2호
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• pp.258-273
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• 2011

본 논문에서는 기존 비디오 재생 시스템보다 고속으로 동작하는 다시점 3차원 비디오 재생 시스템을 설계하여 구현하였다. 대용량의 다시점 영상 데이터를 고속으로 처리하기 위해 구성 모듈들을 병렬화하여 다중코어 프로세서 환경에서 최적의 속도를 얻을 수 있는 구조를 제안하였다. 병목지점의 병행성을 활용하기 위하여 복호화, 영상합성, 렌더링 모듈을 파이프라인 구조로 설계하였다. 부하 균형을 위하여 복호화 모듈을 시점 단위로 분할하고, 영상합성 모듈을 합성영상을 기준으로 기하적으로 데이터 분할하였다. 실험결과로서, 다시점 영상이 올바르게 합성되어 무안경식 다시점 입체디스플레이 상에서 시청 시 입체감을 느낄 수 있었으며, 제안하는 응용프로그램의 처리구조는 다중코어 프로세서를 최대 활용하여 대용량의 다시점 영상데이터를 고속으로 처리할 수 있었다.

• 한국해양공학회지
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• 제28권5호
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• pp.404-410
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• 2014

The purpose of this study was to find the optimal arrangement of FPSO equipment in a module while considering the economic value and fire risk. We estimated the economic value using the pipe connections and pump installation cost in an HP (high pressure) gas compression module. The equipment risks were also analyzed using fire scenarios based on historical data. To consider the wind effect during a fire accident, fuzzy modeling was applied to improve the accuracy of the analysis. The objective functions consisted of the economic value and fire risk, and the constraints were the equipment maintenance and weight balance of the module. We generated a Pareto-optimal front group using a multi-objective GA (genetic algorithm) and suggested an equipment arrangement method that included the opinions of the designer.

• 전자공학회논문지
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• 제54권6호
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• pp.55-64
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• 2017

대용량 고화질의 영상 응용분야에서는 많은 양의 데이터를 고속으로 처리하는 기술이 필요하며, 이를 위해 고속화된 병렬처리 시스템이 요구된다. 2004년 park은 병렬처리 메모리의 충돌 없이 여러 처리기에 데이터를 접속할 수 있는 방법을 제안하였다. 제안된 MAMS(Multi-Access Memory System) 는 이후 MAMS-PP16 및 MAMS-PP64 등으로 추가적인 연구가 이루어졌다. MAMS는 병렬처리를 위한 메모리 아키텍처로써 One-chip으로 구성되어야하기 때문에 기존 MAMS와 동일한 기능을 수행하면서 아키텍처의 최소화 하는 방법의 연구가 필요하다. 주소 계산 (ACR : Address Calculation and Routing) circuit과 MMS(Memory Module Selection)circuit의 아키텍처는 메모리에 있는 데이터를 병렬처리기(Prossing Elements)들에게 전달한다. 본 논문에서는 MMS circuit을 사용하지 않고 ACR circuit 내부에 1개의 쉬프트와 메모리 모듈의 개수만큼의 조건문으로 구성하는 방법을 통해 아키텍처를 최소화 하는 방법을 제안한다. 구현한 아키텍처의 검증을 위해 Image correlation 실험을 하였다. 실험을 통하여 제안된 MAMS-PP64의 처리시간을 측정 하였으며, 그 결과 Ratio가 평균 1.05향상 된 결과를 확인 할 수 있었다.

• 한국레이저가공학회지
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• 제11권2호
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• pp.33-38
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• 2008

Laser micromachining has increasingly been adopted in various advanced industries where the high-precision machining of large-area, high-density and multi-layered components is in a strong demand. To effectively meet the requirements, the laser micromachining process must be carefully monitored. In order to facilitate the development of a new laser micromachining process and/or a new system, we have fabricated a UV laser micromachining platform that is equipped with optical modules for monitoring the process online. They include a laser power stabilizing module, a module for laser-induced breakdown spectroscopy, and an auto-focusing module.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 하계학술대회 논문집 A
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• pp.193-195
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• 2002

In this paper, a communication module is proposed to be applied to communication between over current relay (OCR) agents in multi agent protection system. A multi agent system can achieve a global goal beyond the ability of each individual agent by working together, in which it is the prerequisite for each agent to be able to exchange or share information or processing status with other agent. The proposed communication module is purposed to enable not only each agent to bring about its own goal, but also the whole protective system to provide much improved coordinated protection. It is applied to a self adaptive protection system for a distribution network using multi agent concept to show its effectiveness.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권1호
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• pp.1-14
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• 2024

Time-series forecasting is extensively used in the actual world. Recent research has shown that Transformers with a self-attention mechanism at their core exhibit better performance when dealing with such problems. However, most of the existing Transformer models used for time series prediction use the traditional encoder-decoder architecture, which is complex and leads to low model processing efficiency, thus limiting the ability to mine deep time dependencies by increasing model depth. Secondly, the secondary computational complexity of the self-attention mechanism also increases computational overhead and reduces processing efficiency. To address these issues, the paper designs an efficient multi-layer attention-based time-series forecasting model. This model has the following characteristics: (i) It abandons the traditional encoder-decoder based Transformer architecture and constructs a time series prediction model based on multi-layer attention mechanism, improving the model's ability to mine deep time dependencies. (ii) A cross attention module based on cross attention mechanism was designed to enhance information exchange between historical and predictive sequences. (iii) Applying a recently proposed sparse attention mechanism to our model reduces computational overhead and improves processing efficiency. Experiments on multiple datasets have shown that our model can significantly increase the performance of current advanced Transformer methods in time series forecasting, including LogTrans, Reformer, and Informer.

• 대한임베디드공학회논문지
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• 제5권2호
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• pp.93-102
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• 2010

The FMCW(Frequency Modulation Continuous Wave) radar possesses range-velocity ambiguity to identify the correct combination of beat frequencies for each target in the multi-target situation. It can lead to ghost targets and missing targets, and it can reduce the detection probability. In this pap er, we propose an effective identification algorithm for the correct pairs of beat frequencies and the signal processing hardware architecture to effectively support the algorithm. First, using the correlation of the detected up- and down-beat frequencies and Doppler frequencies, the possible combinations are determined. Then, final pairing algorithm is completed with the power spectrum density of the correlated up- and down-beat frequencies. The proposed hardware processor has the basic architecture consisting of beat-frequency registers, pairing table memory, and decision unit. This method will be useful to improve the radar detection probability and reduce the false alarm rate.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1996년도 추계학술대회 논문집
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• pp.434-438
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• 1996

In this paper we present the multi-agent robot system and the vision system developed for participating in micro robot soccer tournament. The multi-agent robot system consists of micro robot, a vision system, a host computer and a communication module. Micro robot are equipped with two mini DC motors witf encoders and gearboxes, a R/F receiver, a CPU and infrared sensors for obstacle detection. A vision system is used to recognize the position of the ball and opponent robots, position and orientation of our robots. The vision system is composed of a color CCD camera and a vision processing unit(AISI vision computer). The vision algorithm is based on morphological method. And it takes about 90 msec to detect ball and 3-our robots and 3-opponent robots with reasonable accuracy

• E2M - 전기 전자와 첨단 소재
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• 제8권6호
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• pp.774-779
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• 1995

Process optimization experiments based on the Taguchi method were performed in order to set up the optimal process conditions for the contact oxide etching process module which was built in order to be attached to the cluster system of multi-processing purpose. In order to compare with Taguchi method, the contact oxide etching process carried out with different process parameters(CHF$_{3}$/CF$_{4}$ gas flow rate, chamber pressure, RF power and magnetic field intensity). Optimal etching characteristics were evaluated in terms of etch rate, selectivity, uniformity and etched profile. In this paper, as a final analysis of experimental results the optimal etching characteristics were obtained at the process conditions of CHF3/CF4 gas flow rate = 72/8 sccm, chamber pressure = 50 mTorr, RF power = 500 watts, and magnetic field intensity = 90 gauss.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권12호
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• pp.4420-4438
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• 2021

Image dehazing is an ill-posed problem which is far from being solved. Traditional image dehazing methods often yield mediocre effects and possess substandard processing speed, while modern deep learning methods perform best only in certain datasets. The haze removal effect when processed by said methods is unsatisfactory, meaning the generalization performance fails to meet the requirements. Concurrently, due to the limited processing speed, most dehazing algorithms cannot be employed in the industry. To alleviate said problems, a lightweight fast dehazing network based on a multiple scale-patch framework (MSP) is proposed in the present paper. Firstly, the multi-scale structure is employed as the backbone network and the multi-patch structure as the supplementary network. Dehazing through a single network causes problems, such as loss of object details and color in some image areas, the multi-patch structure was employed for MSP as an information supplement. In the algorithm image processing module, the image is segmented up and down for processed separately. Secondly, MSP generates a clear dehazing effect and significant robustness when targeting real-world homogeneous and nonhomogeneous hazy maps and different datasets. Compared with existing dehazing methods, MSP demonstrated a fast inference speed and the feasibility of real-time processing. The overall size and model parameters of the entire dehazing model are 20.75M and 6.8M, and the processing time for the single image is 0.026s. Experiments on NTIRE 2018 and NTIRE 2020 demonstrate that MSP can achieve superior performance among the state-of-the-art methods, such as PSNR, SSIM, LPIPS, and individual subjective evaluation.