• Cement Symposium
• /
• no.29
• /
• pp.245-252
• /
• 2002

소성 영역(Sintering zone)에서 클링커(Clinker)의 형상 형성은 시멘트 생산 공정에서 가장 중요한 생산 공정중의 하나이다. 소성공정의 진단 및 최적 제어의 핵심은 써모그래프(Thermo graph), 즉 적외선 카메라를 이용한 온도 분포의 측정이다. 여기에서 다룰 ''PIT Indicator'' 시스템은 분진이 많은 열악한 산업 현장의 연소 시스템에 적용할 수 있도록 특별히 설계한 공냉식의 2개 채널을 가진 광학 장비에 기초하고 있다. 비디오 영상과 써모그래프 이미지 그리고 다양한 연소 특성이 카메라를 통하여 얻어지고 자기 학습 기능을 가진 소프트웨어에서 기록되고 분석된다. 이때 얻은 데이터는 수학적 모델에서 온라인으로 Free Lime 함유율을 예측하는데 이용된다. 열분포의 써모그래프 표시와 공정상의 다양한 운전 특성을 분석하여 주는 ''PIT Indicator'' 소프트웨어를 통하여 다른 공정 제어 시스템과 연결이 가능하다. 이와 같은 하드웨어와 소프트웨어를 이용하여 최적화가 필요한 여러요소들의 최적화를 동시에 그리고 온라인으로 수행할 수가 있다. Free Lime 함유율의 연속적인 온라인 연산을 통해 생산 설비 및 공정에 맞는 최소한의 에너지를 Kiln 에 공급함으로써 근본적으로 1차 연료의 절감이 가능하고 NOx와 같은 유해 가스의 배출량도 제어할 수 있다. 또한 별도로 NOx에 대한 모델을 개발하여 NOx를 정확하게 예측하는 것도 가능하다.

• Journal of Radiation Protection and Research
• /
• v.24 no.3
• /
• pp.161-170
• /
• 1999

System performances in terms of image quality between an amorphous silicon DR system and a conventional film-screen system were evaluated. Various aspects of image quality MTF (modulation transfer function), NPS (noise power spectrum), SNR(signal-to-noise ratio) and contrast were measured and calculated. The MTF of the DR system was comparable to the film-screen systems. The noise was mainly dominated by the quantum mottle in both systems and the electronic noise was found in the DR system. The contrast of the DR system was better than the film-screen systems by virtue of high sensitivity and image processing. Compared to the film-screen systems in general radiography, the DR system had similar resolution and showed better contrast with the same exposure condition after contrast manipulation. The results of this study provide some useful information about the performance of the DR system in connection with medical applications.

• Journal of Digital Contents Society
• /
• v.10 no.2
• /
• pp.327-332
• /
• 2009

In this paper, we propose the diagnosis system that can predict pet's state of health for pet lovers lacking a technical knowledge of dog-diseases. The proposed system deduces diseases of dogs from input symptoms by our database constructed with 105 kinds of diseases and symptoms. First, a disease is clustered by ART2, the self-learning method in neural network and secondly, the result values, outputs and the weight values clustered by the algorithm are stored to database. Finally, our system diagnoses the state of health by means of comparing the learned information of diseases with the input vectors of each symptom and the related results of questions on diseases. The correct information of diseases and symptom diagnosing is important to predict the state of health of dogs. Therefore, in this paper, the proposed system can manage symptoms and diseases efficiently by database and ART2. We ask veterinary specialist with the efficiency of our system. As a result, we could confirm the possibility as the auxiliary diagnosis system for dog diseases.

• The KIPS Transactions:PartB
• /
• v.9B no.6
• /
• pp.853-862
• /
• 2002

Face Detection can be defined as follows : Given a digitalized arbitrary or image sequence, the goal of face detection is to determine whether or not there is any human face in the image, and if present, return its location, direction, size, and so on. This technique is based on many applications such face recognition facial expression, head gesture and so on, and is one of important qualify factors. But face in an given image is considerably difficult because facial expression, pose, facial size, light conditions and so on change the overall appearance of faces, thereby making it difficult to detect them rapidly and exactly. Therefore, this paper proposes fast and exact face detection which overcomes some restrictions by using neural network. The proposed system can be face detection irrelevant to facial expression, background and pose rapidily. For this. face detection is performed by neural network and detection response time is shortened by reducing search region and decreasing calculation time of neural network. Reduced search region is accomplished by using skin color segment and frame difference. And neural network calculation time is decreased by reducing input vector sire of neural network. Principle Component Analysis (PCA) can reduce the dimension of data. Also, pose estimates in extracted facial image and eye region is located. This result enables to us more informations about face. The experiment measured success rate and process time using the Squared Mahalanobis distance. Both of still images and sequence images was experimented and in case of skin color segment, the result shows different success rate whether or not camera setting. Pose estimation experiments was carried out under same conditions and existence or nonexistence glasses shows different result in eye region detection. The experiment results show satisfactory detection rate and process time for real time system.

• 제어로봇시스템학회:학술대회논문집
• /
• 1997.10a
• /
• pp.504-507
• /
• 1997

It is well known that Variable Structure Controller(VSC) is robust to parameters variation and disturbance but its performance depends on the design parameters such as switching gain and slope of sliding surface. This paper proposes a more robust VSC that is composed of local VSC's. Each local VSC considers the local system dynamics with narrow parameter variation and disturbance. First we optimize the local VSC's by use of Evolution Strategy, and next we use Artificial Neural Network to generalize the local VSC's and construct the overall VSC in order to cover the whole range of parameter variation and disturbance. Simulation on BLDC motor current control shows that the proposed VSC is superior to the conventional VSC.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2014.04a
• /
• pp.226-229
• /
• 2014

편측무시는 뇌졸중 환자에게서 나타나는 지각 손상중의 하나로 말초 운동 및 감각 신경의 손상과 상관없이 손상된 대뇌반구의 반대편의 공간과 신체의 지각이 감소된 상태로 양방향에서 동시에 주어지는 자극에 대해서 한쪽 자극만을 지각하며 뇌손상 반대편의 신체 움직임의 인식 부족과, 무시된 공간쪽으로의 적은 눈 움직임을 보인다. 이와 같은 편측무시를 측정하는 기존 방법으로는 Albert Test, Line bisection Test, Star Cancellation Test 등이 있다. 하지만, 기존 편측무시 평가 방식에는 여러 가지 단점들이 발생한다. 항상 새로운 평가용지가 필요, 검사시간이 오래 소모되고, 모든 작업을 수작업으로 진행, 종이로 데이터를 관리, 수작업이므로 인력낭비 발생한다. 따라서 본 논문에서는 이러한 아날로그 방식에서 나오는 문제점들을 누구나 사용하고 있는 스마트 디바이스를 이용해 디지털방식으로 전환하여 기존의 비효율적이던 방식을 개선시키고자 평가시스템을 개발하고자 한다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2018.06a
• /
• pp.178-179
• /
• 2018

증강현실 환경에서 현실 세계의 물체를 포착하여 디지털화 시키는 것은 몰입감 향상에 있어 매우 중요한 기술이다. Faster R - CNN 은 영상에서 여러 물체를 인식하는 기술 중 하나이며, 지금껏 많은 응용 기술의 개발과 함께 많은 연구가 진행되고 있다. 본 논문은 증강현실 환경에서 평면물체의 2D 변환관계를 설명하는 Homography 와 Faster R - CNN 을 활용하여 여러 개의 비콘에 대한 6 자유도(6DOF) 를 추정하는 방법을 제안한다. 또한 증강현실에서 주로 사용되는 마커 기술에 존재하는 단점들을 극복할 수 있는 비콘 구조를 소개하고 여러 개의 비콘을 용이하게 관리하는 시스템을 제안한다.

• Journal of the Korea Society of Computer and Information
• /
• v.19 no.12
• /
• pp.11-19
• /
• 2014

In this paper, we design an intelligent agent system with the data mining module and information fusion module as the core components of the system and investigate the possibility for the medical expert system. In the data mining module, fuzzy neural network, OFUN-NET analyzes multi-view data and produces fuzzy cluster knowledge base. In the information fusion module and application module, they serve the diagnosis result with possibility degree and useful information for diagnosis, such as uncertainty decision status or detection of asymmetry. We also present the experiment results on the BI-RADS-based feature data set selected form DDSM benchmark database. They show higher classification accuracy than conventional methods and the feasibility of the system as a computer aided diagnosis system.

• Journal of the Korea Computer Industry Society
• /
• v.7 no.4
• /
• pp.437-446
• /
• 2006

Mobilecomputer offers more fundamental role than role assistance enemy of modern technology equipment and new Information <중략> These main weakness puts in structural relation between elements that compose system. Therefore, dynamics research that time urea of systematic adjustment has selected method code Tuesday nerve dynamics enemy who groping of approach that become analysis point is proper and do with recycling bioelectricity signal. Nature model of do living body signal digital analysis chapter as research result could be developed and scientific foundation groping could apply HSS (Hardware-software system) by rehalibitation purpose. Special quality that is done radish form Tuesday of bioelectricity signal formation furthermore studied, and by the result, fundamental process of bodysignal in do structure circuit form of analog - digital water supply height modelling do can.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.46 no.6
• /
• pp.73-79
• /
• 2009

For the shake of control for movement object, control theory like neural network, nonlinear model predictive control(NMPC) is realized on digital high speed computer. Predictor of flight control system(FCS) based nonlinear model predictive control has to be satisfied with response for hard real-time to perform applications on each module in the FCS. Simultaneously, It gives a serious consideration accuracy to give full play to FCS's performance. Error of mathematical aspect affects realization of whole algorithm. But factors of bring mathematical error is not considered to calculate final accuracy on parameter of predictor. In this paper, Predictor was made using load control model on the digital computer for design FCS at hard real-time and is shown response time on realization algorithm. And is shown realization algorithm of high effective predictor over the accuracy. The predictor was realized on the load control model using Euler method, Heun method, Runge-Kutta and Taylor method.