• 디지털융복합연구
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• 제13권2호
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• pp.135-140
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• 2015

일반적인 CHMM 어휘 인식 시스템은 어휘 인식에 대한 모델들의 관측 확률 인식률이 낮고, 일부 단위 음소 모델에만 적용되어 제한적으로 사용되는 문제점이 있다. 또한, 어휘 탐색에서 어휘의 의미가 다양하여 탐색된 어휘가 사용자의 요구에 부합되지 않는 문제점을 가진다. 이러한 문제를 개선하기 위해 GMM(Gaussian Mixture Model)을 이용한 음소인식을 수행하고, 개선된 k-means 알고리즘을 이용하여 어휘 특성에 따른 제한적인 탐색 문제점을 해결하였다. 성능 실험은 기존의 시스템과 비교하여 정확도와 재현율로 대변되는 효과성을 측정하였으며, 성능 실험 결과 정확도는 83%, 재현율은 67%로 나타났다.

• International Journal of Knowledge Content Development & Technology
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• 제7권1호
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• pp.101-120
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• 2017

Healthcare professionals have edited many health questions (HQs) and their answers for healthcare consumers on the Internet. The HQs provide both readable and reliable health information, and hence retrieval of those HQs that are relevant to a given question is essential for health education and promotion through the Internet. However, retrieval of relevant HQs needs to be based on the recognition of the intention of each HQ, which is difficult to be done by predefining syntactic and semantic rules. We thus model the intention recognition problem as a text classification problem, and develop two techniques to improve a learning-based text classifier for the problem. The two techniques improve the classifier by location-based and area-based feature weightings, respectively. Experimental results show that, the two techniques can work together to significantly improve a Support Vector Machine classifier in both the recognition of HQ intentions and the retrieval of relevant HQs.

• 한국과학교육학회지
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• 제37권2호
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• pp.273-290
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• 2017

본 연구의 목적은 과학 교실 탐구공동체 관점에서 접근한 학생의 과학 수업에 대한 인식 조사 도구 개발과, 개발된 도구를 사용하여 과학 교실 탐구공동체 관점에서 과학 수업에 대한 학생의 인식을 조사하는 것이다. 본 연구는 총 417명의 초등학교 6학년 학생들을 대상으로 수행되었다. 연구결과, (a) 6개의 요인('문제인식I: 불일치 인식', '문제인식II: 흥미', '문제원인설명I: 가설설정 및 검증', '문제원인설명II: 협력적 검토', '문제해결I: 대상관계/개념 변화 반추', '문제해결II: 공동체관계/탐구자 변화 반추')으로 구성된 총 42개 문항의 '탐구수행 과정' 관련 조사 도구와, (b) 3개의 요인('탐구실행 의지', '탐구수행 태도', '의사소통 구조')으로 구성된 총 17개 문항의 '탐구수행 토대' 관련 조사 도구를 개발하였다. 또, 개발된 도구를 사용하여 초등학생들의 인식을 조사한 결과, 학생들은 과학 수업에 대해 과학 교실 탐구공동체 관점에서 대체로 보통 이상의 긍정적 인식을 하고 있었지만, 불일치에 기반 한 문제인식, 탐구자의 변화 및 공동체와의 관계 변화 반추를 동반하는 문제해결, 엄격성과 오류가능성 견지에 기반 한 탐구수행 태도 등 일부 요인에 대해서는 상대적으로 덜 긍정적인 인식을 하고 있었다. 이러한 결과를 바탕으로 탐구 중심의 과학 교육을 위한 몇 가지 시사점에 대해 논의하였다.

• International journal of advanced smart convergence
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• 제6권3호
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• pp.29-37
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• 2017

The current behavior recognition system don't match data formats between sensor data measured by user's sensor module or device. Therefore, it is necessary to support data processing, sharing and collaboration services between users and behavior recognition system in order to process sensor data of a large capacity, which is another formats. It is also necessary for real time interaction with users and behavior recognition system. To solve this problem, we propose fog cloud based behavior recognition system for human body sensor data processing. Fog cloud based behavior recognition system solve data standard formats in DbaaS (Database as a System) cloud by servicing fog cloud to solve heterogeneity of sensor data measured in user's sensor module or device. In addition, by placing fog cloud between users and cloud, proximity between users and servers is increased, allowing for real time interaction. Based on this, we propose behavior recognition system for user's behavior recognition and service to observers in collaborative environment. Based on the proposed system, it solves the problem of servers overload due to large sensor data and the inability of real time interaction due to non-proximity between users and servers. This shows the process of delivering behavior recognition services that are consistent and capable of real time interaction.

• IEIE Transactions on Smart Processing and Computing
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• 제4권4호
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• pp.281-290
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• 2015

Human action recognition from a video scene has remained a challenging problem in the area of computer vision and pattern recognition. The development of the low-cost RGB depth camera (RGB-D) allows new opportunities to solve the problem of human action recognition. In this paper, we present a comprehensive review of recent approaches to human action recognition based on depth maps, skeleton joints, and other hybrid approaches. In particular, we focus on the advantages and limitations of the existing approaches and on future directions.

• International Journal of Advanced Culture Technology
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• 제7권4호
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• pp.229-235
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• 2019

Due to the development of video and optical technology today, video equipments are being used in a variety of fields such as identification, security maintenance, and factory automation systems that generate products. In this paper, we investigate an algorithm that effectively recognizes an experimental object in an input image with a partial problem due to the mechanical problem of the input imaging device. The object recognition algorithm proposed in this paper moves and rotates the vertices constituting the outline of the experimental object to the positions of the respective vertices constituting the outline of the DB model. Then, the discordance values between the moved and rotated experimental object and the corresponding DB model are calculated, and the minimum discordance value is selected. This minimum value is the final discordance value between the experimental object and the corresponding DB model, and the DB model with the minimum discordance value is selected as the recognition result for the experimental object. The proposed object recognition method obtains satisfactory recognition results using only partial information of the experimental object.

• 로봇학회논문지
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• 제17권3호
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• pp.334-338
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• 2022

In visual simultaneous localization and mapping (vSLAM), the correct recognition of a place benefits in relocalization and improved map accuracy. However, its performance is significantly affected by the environmental conditions such as variation in light, viewpoints, seasons, and presence of dynamic objects. This research addresses the problem of feature occlusion caused by interference of dynamic objects leading to the poor performance of visual place recognition algorithm. To overcome the aforementioned problem, this research analyzes the role of scene semantics in correct detection of a place in challenging environments and presents a semantics aided visual place recognition method. Semantics being invariant to viewpoint changes and dynamic environment can improve the overall performance of the place matching method. The proposed method is evaluated on the two benchmark datasets with dynamic environment and seasonal changes. Experimental results show the improved performance of the visual place recognition method for vSLAM.

• 수산해양교육연구
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• 제27권5호
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• pp.1424-1435
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• 2015

The purpose of this study was to investigate the recognition about 'problem solving and invention' unit in technology and home-economics subject. The study was carried out through questionnaire survey method. The sample of this study was 397 8th middle school students. The data was collected using questionnaires and analyzed by the descriptive statistics, t-test and one-way ANOVA. The result of this study was as follows: First, middle school students presented positive preferences toward 'problem solving and invention' unit. Second, middle school students recognized the necessity of this unit. Third, the level of difficulty for this unit of students was intermediate. Fifth, middle school students recognized that learning 'problem solving and invention' unit made them have more interest than before learning it.

• Journal of Multimedia Information System
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• 제4권4호
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• pp.219-224
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• 2017

This paper is to introduce an application of face recognition algorithm in parallel. We have experiments of 25 images with different motions and simulated the image recognitions; grouping of the image vectors, image normalization, calculating average image vectors, etc. We also discuss an analysis of the related eigen-image vectors and a parallel algorithm. To develop the parallel algorithm, we propose a new type of initial matrices for eigenvalue problem. If A is a symmetric matrix, initial matrices for eigen value problem are investigated: the "optimal" one, which minimize ${\parallel}C-A{\parallel}_F$ and the "super optimal", which minimize ${\parallel}I-C^{-1}A{\parallel}_F$. In this paper, we present a general new approach to the design of an initial matrices to solving eigenvalue problem based on the new optimal investigating C with preserving the characteristic of the given matrix A. Fast all resulting can be inverted via fast transform algorithms with O(N log N) operations.

• 제어로봇시스템학회논문지
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• 제21권2호
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• pp.121-129
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• 2015

This paper presents a multiple vehicle recognition algorithm based on radar and vision sensor fusion for lane change assistance. To determine whether the lane change is possible, it is necessary to recognize not only a primary vehicle which is located in-lane, but also other adjacent vehicles in the left and/or right lanes. With the given sensor configuration, two challenging problems are considered. One is that the guardrail detected by the front radar might be recognized as a left or right vehicle due to its genetic characteristics. This problem can be solved by a guardrail recognition algorithm based on motion and shape attributes. The other problem is that the recognition of rear vehicles in the left or right lanes might be wrong, especially on curved roads due to the low accuracy of the lateral position measured by rear radars, as well as due to a lack of knowledge of road curvature in the backward direction. In order to solve this problem, it is proposed that the road curvature measured by the front vision sensor is used to derive the road curvature toward the rear direction. Finally, the proposed algorithm for multiple vehicle recognition is validated via field test data on real roads.