• 통상정보연구
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• 제10권4호
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• pp.203-219
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• 2008

This study shows the following results. First, the assessment items of the whole exhibition operation, workforce, counselor's ability, facility and environment were important analysis factors for exhibition recognition, quality of human operation and quality of exhibition facility and environment. Second, exhibition recognition was found to be the most significant factor that influenced exhibitor's cognitive achievement, exhibition employee operation and exhibition facility. Third, exhibitors' satisfaction simultaneously increased as exhibition recognition and employee operation quality were raised. However, exhibition facility didn't strongly influence exhibitors' satisfaction. Fourth, high exhibition recognition, employee operation and exhibition facility resulted in high cognitive achievement and exhibitor's loyalty. Fifth, exhibition recognition is a highly influential factor to mediate exhibitor's cognitive achievement and exhibitors' loyalty. It implied that exhibitors' cognitive achievement and satisfaction were significantly related to the exhibition quality factor. Moreover, it indicated the effective and efficient operational method to strengthen promotional strategy, enhance the quality of employee operation, exhibition facility and environment. Thus, the results suggest a new method to evaluate exhibitor's satisfaction in the exhibition industry.

• 한국항공우주학회지
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• 제47권3호
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• pp.212-219
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• 2019

군사 작전 환경에서 무인 항공기의 활용도가 확대됨에 따라 효율적인 무인기 제어 방식에 대한 연구가 활발하다. 특히 신속한 임무 처리가 요구되는 군 환경에서 기존의 버튼 방식이 지닌 조작의 불편함을 해소하려는 목적으로 음성인식을 통한 무인기 제어 방식이 시도되고 있으며, 아직 초기연구 수준에 머물러 있다. 본 연구에서는 음성 기반의 무인기 제어를 위해 효율적인 음성인식 시스템 운용 체계를 제안한다. 특히 지상관제 센터에 의한 무인기 제어보다는 유/무인기 협업 환경에서 유인기 조종사가 무인기를 직접 통제하는데 효율적인 음성인식 시스템 운용 방식을 제안하며, 음성인식 실험을 통해 운용 체계의 효율성을 검증한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권1호
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• pp.413-435
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• 2018

Although the accuracy of handwritten character recognition based on deep networks has been shown to be superior to that of the traditional method, the use of an overly deep network significantly increases time consumption during parameter training. For this reason, this paper took the training time and recognition accuracy into consideration and proposed a novel handwritten character recognition algorithm with newly designed network structure, which is based on an extended nonlinear kernel residual network. This network is a non-extremely deep network, and its main design is as follows:(1) Design of an unsupervised apriori algorithm for intra-class clustering, making the subsequent network training more pertinent; (2) presentation of an intermediate convolution model with a pre-processed width level of 2;(3) presentation of a composite residual structure that designs a multi-level quick link; and (4) addition of a Dropout layer after the parameter optimization. The algorithm shows superior results on MNIST and SVHN dataset, which are two character benchmark recognition datasets, and achieves better recognition accuracy and higher recognition efficiency than other deep structures with the same number of layers.

• 한국멀티미디어학회논문지
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• 제20권5호
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• pp.748-757
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• 2017

In order to recognize the facial expressions, good features that can express the facial expressions are essential. It is also essential to find the characteristic areas where facial expressions appear discriminatively. In this study, we propose a directional LBP feature for facial expression recognition and a method of finding directional LBP operation and feature region for facial expression classification. The proposed directional LBP features to characterize facial fine micro-patterns are defined by LBP operation factors (direction and size of operation mask) and feature regions through AdaBoost learning. The facial expression classifier is implemented as a SVM classifier based on learned discriminant region and directional LBP operation factors. In order to verify the validity of the proposed method, facial expression recognition performance was measured in terms of accuracy, sensitivity, and specificity. Experimental results show that the proposed directional LBP and its learning method are useful for facial expression recognition.

• 한국CDE학회논문집
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• 제4권1호
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• pp.43-51
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• 1999

Producing the relevant information (features) from the CAD models of CAM, called feature recognition or extraction, is the essential stage for the integration of CAD and CAM. Most feature recognition methods, however, have problems in the recognition of intersecting features because they do not handle the intersection geometry properly. In this paper, we propose a machining feature recognition algorithm, which has a solid model consisting of orthogonal primitives as input. The algorithm calculates candidate features and constitutes the Intersection Geometry Matrix which is necessary to represent the spatial relation of candidate features. Finally, it recognizes machining features from the proposed candidate features dividing and growing systems using half space and Boolean operation. The algorithm has the following characteristics: Though the geometry of part is complex due to the intersections of design primitives, it can recognize the necessary machining features. In addition, it creates the Maximal Feature Volumes independent of the machining sequences at the feature recognition stage so that it can easily accommodate the change of decision criteria of machining orders.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권3호
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• pp.1087-1104
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• 2015

An eye location based head posture recognition method is proposed in this paper. First, face is detected using skin color method, and eyebrow and eye areas are located based on gray gradient in face. Next, pupil circles are determined using edge detection circle method. Finally, head postures are recognized based on eye location information. The proposed method has high recognition precision and is robust for facial expressions and different head postures, and can be used in mouse operation. The experimental results reveal the validity of proposed method.

• 전자공학회논문지B
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• 제33B권9호
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• pp.117-123
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• 1996

In this paper, we present a new learning method for the fuzzy ARTMAP which is effective for the noisy input patterns. Conventional fuzzy ARTMAP employs only fuzzy AND operation between input vector and weight vector in learning both top-down and bottom-up weight vectors. This fuzzy AND operation causes excessive update of the weight vector in the noisy input environment. As a result, the number of spurious categories are increased and the recognition ratio is reduced. To solve these problems, we propose a new method in updating the weight vectors: the top-down weight vectors of the fuzzy ART system are updated using weighted average of the input vector and the weight vector itself, and the bottom-up weight vectors are updated using fuzzy AND operation between the updated top-down weitht vector and bottom-up weight vector itself. The weighted average prevents the excessive update of the weight vectors and the fuzzy AND operation renders the learning fast and stble. Simulation results show that the proposed method reduces the generation of spurious categories and increases the recognition ratio in the noisy input environment.

• 한국전자통신학회논문지
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• 제15권1호
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• pp.115-124
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• 2020

본 논문에서는 현대 사회에서 도어락의 보안성 취약으로 인한 범죄사건들에 대해 보완이 필요하다고 생각하여 보안능력을 강화한 3중 보안 시스템 스마트 도어락을 연구하였다. 앱 이클립스 프로그램을 기반으로 제작한 핸드폰 어플을 통해 도어락 ON&OFF시스템과 음성인식기능, 광학식 지문센서를 사용한 지문인식 기능을 최종으로 잠금과 잠금해제가 가능한 삼중 보안 도어락을 실험, 제작하였다. 끝으로, 실험 제작된 3중 도어락에 대한 앱 기반 동작 실험, 음성 인식 동작실험, 실험지문 인식 동작실험에 대한 평가결과를 통해 도어락의 보안성을 강화할 수 있음을 확인할 수 있었다.

• 한국산업융합학회 논문집
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• 제22권2호
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• pp.137-146
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• 2019

This study proposed a new technique to control of mobile robot based on voice command for (Human-Robot Cooperative operation in manufacturing precess). High performance voice recognition and control system was designed In this paper for smart factory. robust voice recognition is essential for a robot to communicate with people. One of the main problems with voice recognition robots is that robots inevitably effects real environment including with noises. The noise is captured with strong power by the microphones, because the noise sources are closed to the microphones. The signal-to-noise ratio of input voice becomes quite low. However, it is possible to estimate the noise by using information on the robot's own motions and postures, because a type of motion/gesture produces almost the same pattern of noise every time it is performed. In this paper, we describe an robust voice recognition system which can robustly recognize voice by adults and students in noisy environments. It is illustrated by experiments the voice recognition performance of mobile robot placed in a real noisy environment.

• 보건의료산업학회지
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• 제5권3호
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• pp.13-23
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• 2011

This paper investigated the operating environment for the representative of each agency and the facility workers on the basis of analytical result of recognition changes of the operating environment changes under the operating the long-term care insurance. It was described plans to take positive effect on the operating as follows. The first, on the result of regression analysis, the service administrative range takes the biggest effect on the general recognition of executing the long-term care insurance off and on. The affirmative recognition of the service administrative range had the general recognition on the system be positive effect. But the operator of facility asserts that the care manager's professionalism related quality of service be strengthened. The second, on the result of regression analysis, in the financial accounting administrative it is revealed the more positive recognition it is, the more positive effects it has. From the difference verification of an operation size from operation subject, the small operation size and personal facility recognize the long term care insurance positively. On the other side the facilities where the operation size is big recognize the system negatively. The long-term care facility should rearrange a support program newly and the government needs to promote the donation activity, because it is needed to reduce the financial burden of facilities.