• Journal of the Korean Data and Information Science Society
• /
• v.16 no.4
• /
• pp.1017-1026
• /
• 2005

We consider the problem of modeling count data where the observation period is determined by the survival time of the individual under study. We assume random effects or frailty model to allow for a possible association between the death times and the counts. We assume that, given a random effect, the death times follow a Weibull distribution with a rate that depends on some covariates. For the counts, given the random effect, a Poisson process is assumed with the intensity depending on time and the covariates. A gamma model is assumed for the random effect. Maximum likelihood estimators of the model parameters are obtained. The model is applied to data set of patients with breast cancer who received a bone marrow transplant. A model for the time to death and the number of supportive transfusions a patient received is constructed and consequences of the model are examined.

• Proceedings of the IEEK Conference
• /
• 2001.06a
• /
• pp.173-176
• /
• 2001

Several dielectric as well as conducting cylinders buried in the lossy half space are reconstructed from the scattered fields measured along the interface between the air and the lossy ground. Iterative inversion method by using the hybrid optimization algorithm combining the genetic and the Levenberg-Marquardt algorithm enables us to find the positions, the sizes, and the medium parameters such as the permittivities and the conductivities of the buried cylinders as well as those of the background lossy half space. Illposedness of the inversion caused by the errors in the measured scattered fields are regularized by filtering the evanescent modes of the scattered fields out.

• Proceedings of the KIEE Conference
• /
• 2006.04a
• /
• pp.105-107
• /
• 2006

As internet streaming data increase, transport protocol such as TCP, TGP-Friendly is important to study control transmission rate and share of Internet bandwidth. In this paper, we propose a TCP-Friendly protocol using Neural Network for media delivery over wired Internet which has various traffic size(PTFRC). PTFRC can effectively send streaming data when occur congestion and predict one-step ahead round trip time and packet loss rate. A multi-layer perceptron structure is used as the prediction model, and the Levenberg-Marquardt algorithm is used as a traning algorithm. The performance of the PTFRC was evaluated by the share of Bandwidth and packet loss rate with various protocols.

• The Microorganisms and Industry
• /
• v.19 no.4
• /
• pp.39-43
• /
• 1993

최초의 압착 빵효모는 1781년경에 Holland에서 Dutch process로 생산되었으며, 이때에 원료에 대한 4-6%의 압착효모만을 생산하였다. 1846년 비엔나에서 효모발효중에 생성된 거품을 계속하여 수집하여 효모를 회수하는 방법인 Vienna process가 Mautner에 의해 개발되었다. 압착효모 생산 수율은 약 14%로 증가되었고, 알코올은 30%이었다. 1879년 Marquardt가 맥주용 당액에 공기를 공급하면서 발효한 결과를 발표한 후, 빵효모제조에도 공기공급 방법을 사용하게 되었으며, 이것은 압착효모의 생산수율은 50-60%로 높아졌으나, Ethanol의 생산 수율은 20%로 떨어지게 되었다. 그후 1919년 Sak(덴마크)와 Hayduck(독일)은 동시에 incremental-feeding과 fed-batch process의 기초가 된 zulauf 방법을 개발하여 발표하였고, 같은 시기에 1차 세계 대전으로 인한 식량부족은 원료인 곡류를 당밀로 대체하게 되었으며, 이와 같은 제조기술의 계속적인 발달과 원료의 수율은 이론수율에 도달하게 되었고, 수요의 증가로 인하여 양조산업과 분리, 독립되어 빵효모공업이 발전되었다.

• Journal of the Korean Society for Precision Engineering
• /
• v.18 no.11
• /
• pp.124-131
• /
• 2001

Fault diagnosis of an assembled small motor relies usually on human experts hearing ability. The quality of diagnosis depends, however, heavily on physical conditions of the human experts. A fault diagnosis system for assembled small motors is developed using artificial neural network (ANN) in this paper. It is consisted of sound sampling device and fault diagnosis software package. Six parameters are defined to characterize the sampled sound waves. The Levenberg-Marquardt Backpropagation (LMBP) Algorithm is used to diagnose the fault of assembled small motors. Experimental results for more than two hundred small motors verify the performance of the developed system.

• Journal of Sensor Science and Technology
• /
• v.13 no.6
• /
• pp.454-461
• /
• 2004

We have designed a portable electronic nose (e-nose) system using an array of commercial gas sensors and personal digital assistants (PDA) for the recognition and analysis of volatile organic compounds (VOC) in the field. Field screening of pollutants has been a target of instrumental development during the past years. A portable e-nose system was advantageous to localize the special extent of a pollution or to find pollutants source. The employment of PDA improved the user-interface and data transfer by Internet from on-site to remote computer. We adapted the Lavenberg-Marquardt algorithm based on the back-propagation and proposed the method that could predict the concentration levels of VOC gases after classification by separating neural network into two parts.

• Journal of Advanced Marine Engineering and Technology
• /
• v.23 no.5
• /
• pp.637-653
• /
• 1999

In this study well-known burned rate expressions of Weibe function and double Wiebe function have been adopted for the combustion analysis of large two stroke marine diesel engine. A cycle simulation program was also developed to predict the performance and pressure waves in pipes using validated burned rate function,. Levenberg-Marquardt iteration method was applied to cali-brate the shape coefficients included in double Wiebe function for the performance prediction of two-stroke marine diesel engine. As a result the performance prediction using double Wiebe func-tion is well correlated withexperimental dta with the accuracy of 5% and pressure waves in intake and transport pipe are well predicted. From the results of this study it can be confirmed that the shape coefficients of burned rate function should be modified using the numerical method suggested for the accurated prediction and double Wiebe function is more suitable than Wiebe func-tion for combustion analysis of large two stroke marine engine.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.5 no.4
• /
• pp.297-301
• /
• 2005

In this paper, we propose a method to estimate camera motion parameter based on invariant point features. Typically, feature information of image has drawbacks, it is variable to camera viewpoint, and therefore information quantity increases after time. The LM(Levenberg-Marquardt) method using nonlinear minimum square evaluation for camera extrinsic parameter estimation also has a weak point, which has different iteration number for approaching the minimal point according to the initial values and convergence time increases if the process run into a local minimum. In order to complement these shortfalls, we, first propose constructing feature models using invariant vector of geometry. Secondly, we propose a two-stage calculation method to improve accuracy and convergence by using homography and LM method. In the experiment, we compare and analyze the proposed method with existing method to demonstrate the superiority of the proposed algorithms.

• Proceedings of the KIPE Conference
• /
• 2013.07a
• /
• pp.514-515
• /
• 2013

본 논문은 해상풍력단지와 같은 대용량 신재생에너지를 송전하는데 적합한 전압형 HVDC(High Voltage DC) 중에서, 최근 실용화되어 많은 연구가 이루어지고 있는 Modular Multi-level Converter HVDC(MMC HVDC)에 대한 새로운 토폴로지를 제안한 내용이다. 대표적인 MMC HVDC는 독일의 R. Marquardt 교수가 제안한 Half-Bridge 모듈을 적용하여 MMC를 구현하는 방식으로 이는 계통에 DC 지락 사고가 발생할 경우 컨버터를 구성하는 모듈에 큰 고장 전류가 흐르게 되고 결국 모듈의 주요 구성품인 IGBT가 소손 될 수 있는 약점을 지니고 있다. 이를 보완하기 위해 각 모듈에 Thyristor를 삽입하거나 새로운 모듈을 적용하는 방식이 제안되었다. 본 논문에서는 DC 지락 고장시 큰 고장 전류를 차단할 수 있는 새로운 모듈 구성을 제안하였다. 또한 제안된 토폴로지에 대한 기본 동작을 설명하고 시뮬레이션을 통해 제안한 방식과 기존의 방식을 비교 분석 하였다.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
• /
• v.13 no.12
• /
• pp.1288-1296
• /
• 2001

A scheme for on-line fault detection and diagnosis of an air-handling unit is presented. The fault detection scheme uses residuals which are generated by comparing each measurement with analytical redundancies computed from the reference models. In this paper, artificial neural networks (ANNs) are used to estimate analytical redundancy and to classify faults. The Lebenburg-Marquardt algorithm is used to train feed forward ANNs that provide estimates of continuous states and diagnosis results. The simulation result demonstrated that the ANNs can effectively detect and diagnose faults in the highly non-linear and complex HVAC systems.