• 대한수학회논문집
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• 제18권1호
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• pp.133-149
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• 2003

Local stability of steady states of an epidemic model is considered. An age structured S-I-R epidemic model with separable inter-cohort force of infection with external force is considered. Stability result for the nontrivial steady states is obtained.

• 한국산업정보학회논문지
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• 제24권2호
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• pp.1-14
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• 2019

웹, XML, 오피스 어플리케이션에 사용되는 대부분의 문서들은 트리 구조로 구성되어 있으며 특히 다중 사용자 환경에서의 트리 구조의 문서의 차이 발견, 합병, 버전 제어 등의 연구가 활발하다. 그러나 이들의 기초가 되는 편집스크립트에 대한 연구는 초보적인 상태에 있다. 본 논문에서는 편집연산들의 실행 시 트리구조의 문서의 변화를 이해하기 위한 문서 모델을 제시하고 편집연산들의 실행 효과의 분석을 통해 트리 구조 문서에 대한 인접한 편집연산들의 순서 교환 방법을 제안한다. 트리 구조 문서에 대한 변화탐지의 결과로 생성되는 편집스크립트들은 대부분 기본연산들(갱신, 삽입, 삭제)만으로 구성된다. 그러나 이동, 복사연산을 포함하는 경우, 이들의 복합연산의 특성으로 인해 주로 2단계 패스의 실행을 전제로 하는 편집스크립트를 생성한다. 본 논문에서는 제안한 편집 연산들의 순서 교환 방법을 통해 2단계 패스의 실행을 전제로 하는 X-treeESgen의 편집스크립트를 단일 패스로 변환하는 알고리즘을 제시한다.

• 한국콘텐츠학회논문지
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• 제19권1호
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• pp.1-15
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• 2019

직업훈련 교육 현장에서 느끼는 가장 큰 어려움 중 하나는 중도탈락 문제이다. 훈련과정마다 많은 수의 학생들이 중도탈락을 하게 되어 국가 예산 낭비 및 청년 취업률 개선에 장애 요인이 되고 있다. 본 연구에서는 중도탈락의 원인을 주로 분석한 기존 연구들과 달리, 각종 수강생 정보를 활용하여 사전에 중도탈락을 예측할 수 있는 기계학습 기반 모형을 제안하고자 한다. 특히 본 연구의 제안모형은 수강생 관련 정형 데이터 뿐 아니라 비정형 데이터인 강사의 상담일지 정보까지 동시에 고려하여 모형의 예측정확도를 제고하고자 하였다. 이 때 비정형 데이터에 대한 분석은 최근 주목받고 있는 텍스트 분석 기술인 Word2vec과 합성곱 신경망을 이용해 수행하였다. 국내 한 직업훈련기관의 실제 데이터에 제안모형을 적용해 본 결과, 정형데이터만을 사용하여 중도탈락을 예측할 때보다 비정형 데이터를 함께 고려했을 때 예측의 정확도가 최대 20%까지 향상됨을 확인할 수 있었다. 아울러, Support Vector Machine을 기반으로 정형 데이터와 비정형 데이터를 결합해 분석했을 때, 검증용 데이터셋 기준으로 90% 후반대의 높은 예측 정확도를 나타냄을 확인하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권5호
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• pp.2346-2362
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• 2016

As one of the most important issues in computer vision and image processing, online object tracking plays a key role in numerous areas of research and in many real applications. In this study, we present a novel tracking method based on the proposed structured sparse representation model, in which the tracked object is assumed to be sparsely represented by a set of object and background templates. The contributions of this work are threefold. First, the structure information of all the candidate samples is utilized by a joint sparse representation model, where the representation coefficients of these candidates are promoted to share the same sparse patterns. This representation model can be effectively solved by the simultaneous orthogonal matching pursuit method. In addition, we develop a tracking algorithm based on the proposed representation model, a discriminative candidate selection scheme, and a simple model updating method. Finally, we conduct numerous experiments on several challenging video clips to evaluate the proposed tracker in comparison with various state-of-the-art tracking algorithms. Both qualitative and quantitative evaluations on a number of challenging video clips show that our tracker achieves better performance than the other state-of-the-art methods.

• 한국신뢰성학회지:신뢰성응용연구
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• 제17권4호
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• pp.332-342
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• 2017

Purpose: In this study, the lifetime distribution of a k-out-of-n system with heterogeneous components is suggested as Markov model, and the time-to-failure (TTF) distribution of each component is considered as phase-type distribution (PHD). Furthermore, based on the model, a redundancy allocation problem with a mix of components (RAPMC) is proposed. Methods: The lifetime distribution model for the system is formulated by the structured Markov chain. From the model, the various information on the system lifetime can be ascertained by the matrix-analytic (or-geometric) method. Conclusion: By the generalization of TTF distribution (PHD) and the consideration of heterogeneous components, the lifetime distribution model can delineate many real systems and be exploited for developing system operation policies such as preventive maintenance, warranty. Moreover, the effectiveness of the proposed RAPMC is verified by numerical experiments. That is, under the equivalent design conditions, it presented a system with higher reliability than RAP without component mixing (RAPCM).

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권12호
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• pp.4706-4724
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• 2020

With various structured data, such as the company size, loan balance, and savings accounts, the voice of customer (VOC), which is text data containing contact history and counseling details was analyzed in this study. To analyze unstructured data, the term frequency-inverse document frequency (TF-IDF) analysis, semantic network analysis, sentiment analysis, and a convolutional neural network (CNN) were implemented. A performance comparison of the models revealed that the predictive model using the CNN provided the best performance with regard to predictive power, followed by the model using the TF-IDF, and then the model using semantic network analysis. In particular, a character-level CNN and a word-level CNN were developed separately, and the character-level CNN exhibited better performance, according to an analysis for the Korean language. Moreover, a systematic selection model for optimal text mining techniques was proposed, suggesting which analytical technique is appropriate for analyzing text data depending on the context. This study also provides evidence that the results of previous studies, indicating that individual customers leave when their loyalty and switching cost are low, are also applicable to corporate customers and suggests that VOC data indicating customers' needs are very effective for predicting their behavior.

• 대한조선학회논문집
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• 제58권3호
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• pp.182-190
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• 2021

Computational simulations of turbulent flows around a model ship have been performed to investigate an influence of TVD schemes on the accuracy of advective terms associated with ship resistances. Several TVD schemes including upwind, second-order upwind, vanLeer, and QUICK as well as a nonTVD linear scheme were studied by examining temporal and spatial characteristics of accuracy transition in adjacent cells to the hull. Even though vanLeer scheme was the most accurate among TVD schemes in both structured and unstructured grid systems, the ratio of accuracy switch from 2^nd order to 1^st order in vanLeer scheme was considerable compared with the 2^nd order linear scheme. Also, the accuracy transition was observed to be overally scattered in the unstructured grid while the accuracy transition in the structured grid appeared relatively clustered. It concluded that TVD schemes had to be carefully used in computational simulations of turbulent flows around a model ship due to the loss of accuracy despite its attraction of numerical stability.

• Nuclear Engineering and Technology
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• 제55권10호
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• pp.3709-3715
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• 2023

It is an important work to measure the dimensions of underwater spent fuel assemblies in the nuclear power industry during the overhaul, to judging whether the spent fuel assemblies can continue to be used. In this paper, a three dimensional reconstruction method for underwater spent fuel assemblies of nuclear reactor based on linear structured light is proposed, and the topography and size measurement was carried out based on the reconstructed 3D model. Multiple linear structured light sensors are used to obtain contour size data, and the shape data of the whole spent fuel assembly can be collected by one-dimensional scanning motion. In this paper, we also presented a corrected model to correct the measurement error introduced by lead-glass and water is corrected. Then, we set up an underwater measurement system for spent fuel assembly based on this method. Finally, an underwater measurement experiment is carried out to verify the 3D reconstruction ability and measurement ability of the system, and the measurement error is less than ±0.05 mm.

• 한국정밀공학회지
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• 제20권2호
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• pp.176-183
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• 2003

The paper presents a feature recognition and segmentation method for surface approximation in reverse engineering. Efficient digitizing plays an important role in constructing a computational surface model from a physical part-surface without its CAD model on hand. Depending on its measuring source (e.g., touch probe or structured light), each digitizing method has its own strengths and weaknesses in terms of speed and accuracy. The final goal of the research focuses on an integration of two different digitizing methods: measuring by the structured light and that by the touch probe. Gathering bulk of digitized points (j.e., cloud-of-points) by use of a laser scanning system, we construct a coarse surface model directly from the cloud-of-points, followed by the segmentation process where we utilize the z-map filleting & differencing to trace out feature boundary curves. The feature boundary curves and the approximate surface model could be inputs to further digitizing by a scanning touch probe. Finally, more accurate measuring points within the boundary curves can be obtained to construct a finer surface model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권11호
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• pp.3507-3522
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• 2022

Model pruning methods have attracted huge attention owing to the increasing demand of deploying models on low-resource devices recently. Most existing methods use the weight norm of filters to represent their importance, and discard the ones with small value directly to achieve the pruning target, which ignores the contribution of the small norm filters. This is not only results in filter contribution waste, but also gives comparable performance to training with the random initialized weights [1]. In this paper, we point out that the small norm filters can harm the performance of the pruned model greatly, if they are discarded directly. Therefore, we propose a novel filter contribution recycle (FCR) method for structured model pruning to resolve the fore-mentioned problem. FCR collects and reassembles contribution from the small norm filters to obtain a mixed contribution collector, and then assigns the reassembled contribution to other filters with higher probability to be preserved. To achieve the target FLOPs, FCR also adopts a weight decay strategy for the small norm filters. To explore the effectiveness of our approach, extensive experiments are conducted on ImageNet2012 and CIFAR-10 datasets, and superior results are reported when comparing with other methods under the same or even more FLOPs reduction. In addition, our method is flexible to be combined with other different pruning criterions.