• Journal of Microbiology and Biotechnology
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• 제16권6호
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• pp.993-998
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• 2006

We earlier suggested a hierarchical regulatory network using defined modeling symbols and weights in order to improve the flux balance analysis (FBA) with regulatory events that were represented by if-then rules and Boolean logic. In the present study, the simulation results of the models, which were developed and improved from the previou model by incorporating a hierarchical regulatory network into the FBA, were compared with the experimental outcome of an aerobic batch growth of E. coli on glucose and tryptophan. From the experimental result, a diauxic growth curve was observed, reflecting growth resumption, when tryptophan was used as an alternativee after the supply of glucose was exhausted. The model parameters, the initial concentration of substrates (0.92 mM glucose and 1 mM tryptophan), cell density (0.0086 g biomass/1), the maximal uptake rates of substrates (5.4 mmol glucose/g DCW h and 1.32 mmol tryptophan/g DCW h), and lag time (0.32 h) were derived from the experimental data for more accurate prediction. The simulation results agreed with the experimental outcome of the temporal profiles of cell density and glucose, and tryptophan concentrations.

• 정보관리학회지
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• 제29권2호
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• pp.193-204
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• 2012

이 연구에서는 인용 및 동시인용 문헌 네트워크에서의 중심성 지수를 사용한 추론 통계 적용의 첫 번째 단계로써 이들 간 관계의 선형성을 살펴보고자 하였다. 703개의 문헌 동시인용 네트워크를 활용하여 인용 빈도, 연결정도 중심성, 인접 중심성, 매개 중심성 간의 4가지 주요 관계의 패턴을 살펴본 결과, 모든 인용 및 중심성 간 관계가 선형모델보다는 비선형적 모델로 더 잘 설명될 수 있음을 통계적으로 확인되었다. 따라서 이들 간의 인과관계에 대한 다중회귀분석과 같은 추론 통계 분석의 기반이 되는 선형성을 확보하기 위해서는 논리적인 기준에 근거한 데이터 변환이나 실제값을 구간값으로 변환하는 과정이 필요하다고 할 수 있다.

• 사회복지연구
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• 제45권2호
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• pp.375-402
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• 2014

이 연구는 장애와 그에 따른 부가적 실체(낙인, 편견, 차별,, 사회적 제약 등)들로 인해 낮은 삶의 만족도를 나타내는 장애인들의 삶의 만족도 변화양상을 종단적으로 살펴보고, 그에 대한 예측요인으로서 사회자본의 구성개념인 네트워크와 사회참여의 영향력을 파악하는데 목적이 있다. 이를 위해 2차~5차 장애인고용패널조사 자료를 활용해, 3206명을 대상으로 잠재성장모형 분석을 실시하였다. 분석결과, 장애인의 삶의 만족도는 시간이 흐를수록 감소하는 경향을 나타냈으며, 초기 높은 삶의 만족도를 나타낸 장애인의 경우 시간이 흐를수록 완만하게 감소하고, 낮은 삶의 만족도를 나타낸 장애인의 경우 가파르게 감소하는 경향을 보였다. 삶의 만족에 영향을 미치는 네트워크와 사회참여의 영향력을 살펴보면, 네트워크는 삶의 만족도 초기 값에 정적인 영향을, 변화율에는 부적인 영향을 미쳤다. 사회참여는 삶의 만족도 초기 값에 정적인 영향을 미쳤으나, 변화율에는 영향을 미치지 못하였다. 이러한 결과를 바탕으로 실천적 개입방안과 정책적 함의를 제시하였다.

• Investigative Magnetic Resonance Imaging
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• 제25권1호
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• pp.10-22
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• 2021

Purpose: To overcome the difficulty in building a large data set with a high-quality in medical imaging, a concept of 'blended-transfer learning' (BTL) using a combination of both source data and target data is proposed for the target task. Materials and Methods: Source and target tasks were defined as training of the source and target networks to reconstruct cardiac CINE images from undersampled data, respectively. In transfer learning (TL), the entire neural network (NN) or some parts of the NN after conducting a source task using an open data set was adopted in the target network as the initial network to improve the learning speed and the performance of the target task. Using BTL, an NN effectively learned the target data while preserving knowledge from the source data to the maximum extent possible. The ratio of the source data to the target data was reduced stepwise from 1 in the initial stage to 0 in the final stage. Results: NN that performed BTL showed an improved performance compared to those that performed TL or standalone learning (SL). Generalization of NN was also better achieved. The learning curve was evaluated using normalized mean square error (NMSE) of reconstructed images for both target data and source data. BTL reduced the learning time by 1.25 to 100 times and provided better image quality. Its NMSE was 3% to 8% lower than with SL. Conclusion: The NN that performed the proposed BTL showed the best performance in terms of learning speed and learning curve. It also showed the highest reconstructed-image quality with the lowest NMSE for the test data set. Thus, BTL is an effective way of learning for NNs in the medical-imaging domain where both quality and quantity of data are always limited.

• 한국정밀공학회지
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• 제12권6호
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• pp.120-127
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• 1995

A nonlinear empirical state-space model of the Artificial Neural Network(ANN) has been developed. The nonlinear model structure incorporates characteristic, so as to enable identification of the transient response, as well as the steady-state response of a dynamic system. A hybrid feedfoward/feedback neural network, namely a Local Time Delayed Recurrent Multi-layer Perception(RMLP), is the model structure developed in this paper. RMLP is used to identify nonlinear dynamic system in an input/output sense. The feedfoward protion of the network architecture provides with the well-known curve fitting factor, while local recurrent and cross-talk connections provides the dynamics of the system. A dynamic learning algorithm is used to train the proposed network in a supervised manner. The derived dynamic learning algorithm exhibit a computationally desirable characteristic; both network sweep involved in the algorithm are performed forward, enhancing its parallel implementation. RMLP state-space and its associate learning algorithm is demonstrated through a simple examples. The simulation results are very encouraging.

• Agricultural and Biosystems Engineering
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• 제1권1호
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• pp.30-37
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• 2000

Wet porous media representing agronomic soil that contains variable water content with variable electrolyte concentration was measured to study the shape of the curves of the electric double layer capacitance versus frequency (from 10 KHz to 10 MHz. This was done in an attempt to find the lowest practical operating frequency for developing low cost dielectric constant soil moisture probes. Cellulose sponge was used as the porous media. A high frequency electronic bridge circuit was developed for measuring the equivalent network parallel resistance and capacitance of porous media. It appears that the effects of the electric double layer component of the total parallel network capacitance essentially disappear at operating frequencies greater than approximately 25 MHz at low electrolyte concentrations but are still important at 50 MHz at higher concentrations. At these frequencies, the double layer capacitance masks the diffusion region capacitance where true water content capacitance values reside. The general shape of the curve of volumetric water content versus porous media dielectric constant is presented, with an empirical equation representing data for this type of curve. It was concluded that the lowest frequency where dielectric constant values which represent true water content information will most likely be found is between 30 and 50 MHz at low electrolyte concentrations but may be above 50 MHz when the total electrolyte concentration is near the upper level required for most mesophyte plant nutrition.

• 전기학회논문지
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• 제59권10호
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• pp.1741-1747
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• 2010

The development of overload management systems for distribution transformers offers new opportunities for improving the reliability of distribution systems. It allows network planners to optimize the system resource utilization and investment cost. Such an improvement in the flexibility of the distribution network is only possible if the operator has more accurate knowledge of the realtime conditions of distribution transformers. In this paper, we present an improved overload decision system for distribution transformers using realtime monitoring data. Our study can be categorized into two parts: (a) improvement in the criteria for judging the overload conditions of distribution transformers and (b) development of an overload evaluation system using realtime monitoring data. In order to determine the overload criteria, overload experiments are performed on sample transformers; the results of these experiments are used to define the relationship between the transformer overload and the increase in the top-oil temperature. To verify the accuracy of the experimental results, field tests are performed using specially manufactured transformers, the loads and top-oil temperatures of which can be measured. For arriving at online overload decisions, we propose methods whereby the measured load curve can be converted into an overload characteristic curve and the overload time can be calculated for any load condition. The developed system is able to evaluate the overload for individual distribution transformers and calculate the losses using realtime monitoring data.

• Imaging Science in Dentistry
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• 제52권2호
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• pp.187-195
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• 2022

Purpose: This study developed a convolutional neural network (CNN) model to diagnose maxillary sinusitis on panoramic radiographs(PRs) and cone-beam computed tomographic (CBCT) images and evaluated its performance. Materials and Methods: A CNN model, which is an artificial intelligence method, was utilized. The model was trained and tested by applying 5-fold cross-validation to a dataset of 148 healthy and 148 inflamed sinus images. The CNN model was implemented using the PyTorch library of the Python programming language. A receiver operating characteristic curve was plotted, and the area under the curve, accuracy, sensitivity, specificity, positive predictive value, and negative predictive values for both imaging techniques were calculated to evaluate the model. Results: The average accuracy, sensitivity, and specificity of the model in diagnosing sinusitis from PRs were 75.7%, 75.7%, and 75.7%, respectively. The accuracy, sensitivity, and specificity of the deep-learning system in diagnosing sinusitis from CBCT images were 99.7%, 100%, and 99.3%, respectively. Conclusion: The diagnostic performance of the CNN for maxillary sinusitis from PRs was moderately high, whereas it was clearly higher with CBCT images. Three-dimensional images are accepted as the "gold standard" for diagnosis; therefore, this was not an unexpected result. Based on these results, deep-learning systems could be used as an effective guide in assisting with diagnoses, especially for less experienced practitioners.

• 정보처리학회논문지C
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• 제14C권3호
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• pp.285-292
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• 2007

적응형 대역폭 할당 방법에서는 가변 비트율로 저장된 비디오 데이터에 대한 전송 계획을 세우고 네트워크 트래픽을 고려하여 전송하는데, 전송 계획으로 CBA 알고리즘이 사용된다 그러나, CBA 알고리즘에서는 전송률 증가 구간의 크기가 감소 구간의 크기보다 일반적으로 크며, 전송률이 증가될 때에 오버플로우 경계선에서 전송률이 변화되므로 가용 전송률이 작은 경우에는 폐기되는 프레임의 양이 많아지게 된다. 본 논문에서는 이를 개선하기 위하여 언더플로우 경계선과 오버플로우 경계선의 중간에서 전송률이 변화되지만, 전송률의 증가가 필요한 경우에는 증가 양을 최소로 하는 스무딩 알고리즘을 제안한다. 제안 알고리즘과 CBA 알고리즘을 적응형 대역폭 할당 방법의 전송 계획으로 사용하였을 때, 최소 재생률, 평균 재생률, 재생률 변화량, 그리고 폐기되는 프레임 양을 비교하여 제안 알고리즘의 성능이 우수함을 보였다.

• 한국통신학회논문지
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• 제39C권11호
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• pp.1068-1077
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• 2014

본 논문은 무선 센서 네트워크 환경에서 센서노드의 에너지 소모를 최소화하기 위한 효과적인 모바일 싱크노드의 이동경로설정 방법을 제안한다. 싱크노드의 이동경로를 설정하기 위해 Random way point 방식을 사용한 기존의 연구들은 싱크노드의 위치와 경로를 파악하고 데이터 전송을 위한 라우팅 경로설정을 위해 불필요한 에너지 소모와 데이터 전송 지연을 발생시킬 수 있는 단점이 있다. 이를 해결하기 위해 제안하는 방법은 Hilbert curve를 사용하여 최적의 싱크노드 이동경로를 설정한다. 또한, 센서노드의 분포 밀도를 고려한 경로 수정을 통해 데이터 전송 지연을 최소화시킨다. 실험 결과 제안하는 기법은 기존의 TTDD, CBPER에 비해 최대 50배 이상의 에너지 효율을 보여주는 것으로 나타났다.