• The Journal of the Korea institute of electronic communication sciences
• /
• v.9 no.11
• /
• pp.1227-1232
• /
• 2014

This paper relates 10% shrink from $0.13{\mu}m$ design for core devices as well as input and output (I/O) devices different from previous poly length shrink size only. We analyzed body effect with different channel length and doping profile simulation. After fixing the gate oxide module process, LDD implant conditions were optimized such as decoupled plasma nitridation of gate oxide, TEOS oxide $100{\AA}$ before LDD implant and 22o tilt-angle(45o twist-angle) LDD implant respectively to match the spice DC parameters of pre-shrink and finally matched them within 5%.

• Journal of Korea Society of Industrial Information Systems
• /
• v.13 no.1
• /
• pp.22-29
• /
• 2008

This paper describes the developed results of vision system for the recognition of material management characters, which was included in the billet image. The material management characters, which was marked at the surface of billet, should be recognized before billet moves to the next process. Our vision system for the character recognition includes that CCD camera system which acquire billet image, optical transmission system which transmit captured image to the long distance, input and output system for the interface with existing system and software for the character recognition. We have installed our vision system at the wire rod line of steel & iron plant and tested. Also, we have performed inspection of durability, reliability and recognition rate. Through the testing, we have confirmed that our system have high recognition rate, 98.6%.

• Proceedings of the Korean Information Science Society Conference
• /
• 2007.10b
• /
• pp.1-6
• /
• 2007

서열을 분석하고, 기능을 예측하는 서열 주해는 생명 현상 규명을 위한 필수 과정이다. 서열 주해는 다수 응용 프로그램간 상호 연계를 통한 복잡한 처리 과정을 거쳐 이루어진다. 현재 사용자는 다양한 응용 프로그램들 중 적합한 응용 프로그램을 선택한 후, 운영환경에 맞도록 설치하고, 사용법을 익혀야 한다. 또한 각 프로그램들의 연계를 위해 입출력 데이터 형식을 변환해야 하는 불편함이 있다. 이를 위해 자동화된 솔루션들이 개발되고 있지만, 각 단계별 프로그램들이 강결합(tightly coupled)되어 있어 유연성(flexibility)이 떨어지고, 기능의 확장 및 변경에 어려움이 있다. 본 논문에서는 기존 시스템들의 한계를 극복하기 위하여 SOA (Service Oriented Architecture) 기반의 서열 주해 시스템인 SeqWeB을 제안한다. SeqWeB은 서열 주해에 필요한 7개의 응용 프로그램(Phred, cross_match, RepeatMasker, ICAtools, Phrap, CAP3, Blast)들을 웹 서비스 기술을 통해 단위 서비스로 개발하고, BPM 기법을 이용하여 통합하였다. SeqWeB은 각 응용 프로그램간 상호 운용성을 높이기 위하여 XML 형식의 입/출력 데이터를 사용하며, SOA 기반의 시스템 통합으로 각 응용 프로그램들을 약결합(loosely coupled)하여 시스템의 확장 및 변경이 용이하다. 또한 웹을 기반으로 하는 다양한 조합의 서열 주해 솔루션 제공이 가능한 특징이 있다.

• Microbiology and Biotechnology Letters
• /
• v.31 no.2
• /
• pp.182-190
• /
• 2003

As DNA microarrays are widely used recently, the amount of microarray data is exponentially increasing. Until now, however, no domestic system is available for the efficient management of such data. Because the number of experimental data in a specific laboratory is limited, it is necessary to avoid redundant experiments and to accumulate the results using a shared data management system for microarrays. In this paper, a system named WEMA (WEb management of Micro Arrays) was designed and implemented to manage and process the microarray data. WEMA system was designed to include the basic feature of MIAME (Minimal Information About a Microarray Experiment), and general data units were also defined in the system in order to systematically manage the data. The WEMA system has three main features: efficient management of microarray data, integration of input/ouput data, and metafile processing. The system was tested with actual microarray data produced by a molecular biology laboratory, and we found that the biologists could systematically manage and easily analyze the microarray data. As a consequence, the researchers could reduce the cost of data exchange and communication.

• Proceedings of the Korean Society for Agricultural Machinery Conference
• /
• 2017.04a
• /
• pp.166-166
• /
• 2017

모돈의 건강 상태를 정량 지수화 하기 위한 연구를 수행 중이다. 지제이상, 섭식 불량, 수면 패턴 등의 운동 특성 분석을 위하여 복수의 초음파 센서를 이용하였다. 시계열 계측 신호를 분석하여 정량 지수화를 수행하는 과정에서 주파수 도메인 분석을 시도하였다. 이 과정에서 주파수 도메인의 분해능에 따른 편차 극복을 위한 비선형 모델링을 수행하였다. 또한 인접한 시계열 데이터 구간 간의 상관성 분석이 가능하면 대용량 데이터의 실시간 처리로 인한 지연 시간 극복 및 기대되는 예후에 대한 조기 진단이 가능할 것이다. 본 연구에서는 구글에서 제공하는 Tensorflow와 NVIDIA에서 제공하는 CUDA 엔진을 동시 적용한 심층 학습 시스템을 이용하였다. 전 처리를 위하여 주파수 분해능 (2분, 3분, 5분, 7분, 11분, 13분, 17분, 19분)에 따른 데이터 집합을 1단계로 두고, 상위 10 순위 안에 드는 파워 스펙트럼 밀도의 크기를 2단계로 하여, 총 2~10개의 입력 노드를 순차적으로 선정하였고, 동일한 방식으로 인접한 시계열의 파워 스펙터럼 밀도를 순위를 변화시켜 지정하였다. 대표적인 심층학습 모델인 Softmax regression with a multilayer convolutional network를 이용하여 Recursive feature selection 경우의 수를 $8{\times}9{\times}9$로 총 648 가지 선정하고, Epoch는 10,000회로 지정하였다. Calibration 모델링의 경우 Cost function이 10% 이하인 경우 해당 경우의 학습을 중단하였으며, 모델 간 상호 교차 검증을 수행하기 위하여 $_8C_2{\times}_8C_2{\times}_8C_2$ 경우의 수에 대한 Verification test를 수행하였다. Calibration 과정 상 모든 경우에 대하여 10% 이하의 Cost function 값을 보였으나, 검증 테스트 과정에서 모든 경우에 대하여 $r^2$ < 0.5 인 결정 계수 값이 나타났다. 단적으로 심층학습 모델의 과도한 적합(Over fitting) 방식의 한계를 보인 것이라 판단할 수 있다. 적합한 Feature selection 및 심층 학습 모델에 대한 지속적이고 추가적인 고려를 통해 과도적합을 해소함과 동시에 실효적이고 활용 가능한 Classification을 위한 입, 출력 노드 단의 전후 Indexing, Quantization에 대한 고려가 필요할 것이다. 이를 통해 모돈 생체 정보 정량화를 위한 지능형 현장 진단 기술 연구를 지속할 것이다.

• Journal of the Institute of Convergence Signal Processing
• /
• v.9 no.4
• /
• pp.261-271
• /
• 2008

Holographic volume grating couplers (VGCs) are become increasingly attractive device for the application of optical interconnects because of their higher preferential coupling, dry fabrication processing, compact, and low cost. In this paper, the analysis, design, and implementation of the waveguide-imbedded input-output VGC with $45^{\circ}$ grating slant angle using holographic photopolymer(Dupont HRF600-20) for guided-wave optical interconnection applications, are presented. To show the usefulness of the proposed VGC, we fabricated the VGCs operating at 632.8nm and 1550nm wavelengths and its results are presented. The measured input coupling efficiency of the single VGC with $0.5{\mu}m$ grating period at 632.8nm wavelength is above 86.6% for TE-polarization. The input coupling efficiency of the $1\times2$ VGC with $0.73068{\mu}m$ grating period at 1550nm wavelength is about 90.8%.

• The KIPS Transactions:PartD
• /
• v.9D no.5
• /
• pp.745-754
• /
• 2002

The Google search site (http://www.google.com), which was introduced in 1998, implemented the PageRank algorithm for the first time. PageRank is a ranking method based on the link structure of the Web pages. Even though PageRank has been implemented and being used in various commercial search engines, implementation details did not get documented well, primarily due to business reasons. Implementation techniques introduced in [4,8] are not sufficient to produce PageRank values of Web pages. This paper explains the techniques[4,8], and suggests major data structure and four implementation techniques in order to apply the PageRank algorithm. The paper helps understand the methods of applying PageRank algorithm by means of showing a real system that produces PageRank values of Web pages.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.37 no.5
• /
• pp.1-12
• /
• 2000

In this paper we propose a design method of the adaptive fuzzy controller for autonomous navigation of mobile robots based on the fuzzy theory. We present two improvements. First, unnecessary rules in the fuzzy inference process make data processing time increase. We reduce this data processing time by generating suitable fuzzy inference rules and membership functions according to the current state of a mobile robot. It is implemented with the clustering method using input and output data pairs, and then it is possible for a mobile robot to navigate in shorter processing time with less fuzzy inference rules. Second, existing algorithms used fixed membership functions of input and output variables, hence converged slowly. We improve convergence time via scaling membership functions generated by the clustering method. To evaluate and compare the performance of the proposed method with the existing fuzzy navigation controller, computer simulations and navigation experiments of a mobile robot are Presented.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.16 no.5
• /
• pp.1095-1101
• /
• 2012

This paper presents a design of a BLDC servo motor control system for the auto process of assembly and supply using DSP(Digital Signal Processor) controller and IGBT driver. The assembly and supply auto processing system needs torque, speed, position control of servo motor for variable action. This paper implements those servo control with vector control and space vector PWM(Pulse Width Modulation) technique. As CPU of controller, TMS320F240 DSP was adopted because it has PWM waveform generator, A/D converter, SPI(Serial Peripheral Interface) port and many input/output port etc. This control system consists of 3-level hierarchy structure that main host PC manages three sub DSP system which transfer downward command and are monitoring the states of end servo controllers. Each sub DSP system operates eight BLDC servo controllers which control BLDC motor using DSP and IPM. Between host system and sub DSP communicate with RS-422, between main processor and controller communicate with SPI port.

• The Transactions of the Korea Information Processing Society
• /
• v.4 no.8
• /
• pp.2070-2079
• /
• 1997

In this paper, we proposed the FNCAC (fuzzy neural call admission control) scheme of the ATM networks which used the benefits of fuzzy logic controller and the learning abilities of the neural network to solve the call admission control problems. The new call in ATM networks is connected if QoS(quality of service) of the current calls is not affected due to the connection of a new call. The neural network CAC(call admission control) system is predictable system because the neural network is able to learn by the input/output pattern. We applied the fuzzy inference on the learning rate and momentum constant for improving the learning speed of the fuzzy neural network. The excellence of the proposed algorithm was verified using measurement of learning numbers in the traditional neural network method and fuzzy neural network method by simulation. We found that the learning speed of the FNCAC based on the fuzzy learning rules is 5 times faster than that of the CAC method based on the traditional neural network theory.