• 대한임베디드공학회논문지
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• 제7권2호
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• pp.85-93
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• 2012

In this paper, we proposed Wireless LAN (WLAN) localization method that enhances database construction based on weighting factor and analyse the characteristic of the WLAN received signals. The weighting factor plays a key role as it determines the importance of Received Signal Strength Indication (RSSI) value from number of received signals (frequency). The fingerprint method is the most widely used method in WLAN-based positioning methods because it has high location accuracy compare to other indoor positioning methods. The fingerprint method has different location accuracies which depend on training phase and positioning phase. In training phase, intensity of RSSI is measured under the various. Conventional systems adapt average of RSSI samples in a database construction, which is not quite accurate due to variety of RSSI samples. In this paper, we analyse WLAN RSSI characteristic from anechoic chamber test, and analyze the causes of various distributions of RSSI and its influence on location accuracy in indoor environments. In addition, we proposed enhanced weighting factor algorithm for accurate database construction and compare location accuracy of proposed algorithm with conventional algorithm by computer simulations and tests.

• 대한토목학회논문집
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• 제39권6호
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• pp.887-892
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• 2019

건설현장 영상 자동 모니터링을 목적으로 많은 연구자들이 영상분석기술을 활발히 개발하고 있다. 높은 성능의 영상분석기술을 개발하기 위해서는 다량의 고품질 학습용 이미지 데이터베이스(Database, DB)를 구축해야 한다. 하지만 기존의 학습 DB 구축 방법은 사람이 건설현장을 직접 방문하여 카메라를 설치하고 각각의 목적에 알맞은 영상을 수집하여 DB를 직접 구축하고 있기 때문에 이에 많은 비용과 시간이 요구된다. 뿐만 아니라 이 같은 사람 의존적인 방식은 건설현장의 다양한 특성을 모두 반영한 DB를 구축하는 것에 한계가 있다. 이러한 한계를 극복하기 위해서 본 연구는 웹 크롤링(Web Crawling) 기법을 활용하여 건설현장 영상분석을 위한 학습 이미지 DB를 자동으로 구축하는 프레임워크를 제안한다. 프레임워크 검증을 위해 건설공종과 건설장비에 대한 학습 DB를 구축하여 영상분석모델을 학습 및 평가하는 실험을 진행하였다. 그 결과, 건설현장 모니터링을 위한 학습용 이미지 DB를 자동으로 구축할 수 있었을 뿐만 아니라 이를 토대로 개발한 영상분석모델이 건설공종과 건설장비를 성공적으로 분류하는 것을 확인하였다. 결과적으로 기존의 방식보다 학습 DB를 구축하는 데 필요한 시간과 비용을 최소화할 수 있었다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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• pp.294-297
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• 2004

The purpose of this study was to develop landslide susceptibility analysis techniques using artificial neural networks and then to apply these to the selected study area of Janghung in Korea. We aimed to verify the effect of data selection on training sites. Landslide locations were identified from interpretation of satellite images and field survey data, and a spatial database of the topography, soil, forest, and land use was constructed. Thirteen landslide-related factors were extracted from the spatial database. Using these factors, landslide susceptibility was analyzed using an artificial neural network. The weights of each factor were determined by the back-propagation training method. Five different training datasets were applied to analyze and verify the effect of training. Then, the landslide susceptibility indices were calculated using the trained back-propagation weights and susceptibility maps were constructed from Geographic Information System (GIS) data for the five cases. The results of the landslide susceptibility maps were verified and compared using landslide location data. GIS data were used to efficiently analyze the large volume of data, and the artificial neural network proved to be an effective tool to analyze landslide susceptibility.

• The Journal of the Acoustical Society of Korea
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• 제20권2E호
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• pp.17-24
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• 2001

In this paper, we propose the bootstrap and aggregating (bagging) vector quantization (VQ) classifier to improve the performance of the text-independent speaker recognition system. This method generates multiple training data sets by resampling the original training data set, constructs the corresponding VQ classifiers, and then integrates the multiple VQ classifiers into a single classifier by voting. The bagging method has been proven to greatly improve the performance of unstable classifiers. Through two different experiments, this paper shows that the VQ classifier is unstable. In one of these experiments, the bias and variance of a VQ classifier are computed with a waveform database. The variance of the VQ classifier is compared with that of the classification and regression tree (CART) classifier[1]. The variance of the VQ classifier is shown to be as large as that of the CART classifier. The other experiment involves speaker recognition. The speaker recognition rates vary significantly by the minor changes in the training data set. The speaker recognition experiments involving a closed set, text-independent and speaker identification are performed with the TIMIT database to compare the performance of the bagging VQ classifier with that of the conventional VQ classifier. The bagging VQ classifier yields improved performance over the conventional VQ classifier. It also outperforms the conventional VQ classifier in small training data set problems.

• Journal of Welding and Joining
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• 제34권1호
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• pp.54-58
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• 2016

In this research paper, suggest method of generate same bead as an actual measurement data in virtual welding conditions, exploit morphology information of the bead that acquired through robot welding. It has many multiple risk factors to Beginners welding training, by we make possible to train welding in virtual reality, we can reduce welding training risk and welding material to exploit bead visualization algorithm that we suggest so it will be expected to achieve educational, environmental and economical effect. The proposed method is acquire data to each case performing robot welding by set the voltage, current, working angle, process angle, speed and arc length of welding condition value. As Welding condition value is most important thing in decide bead form, we would selected one of baseline each item and then acquired metal followed another factors change. Welding type is FCAW, SMAW and TIG. When welding trainee perform the training, it's difficult to save all of changed information into database likewise working angle, process angle, speed and arc length. So not saving data into database are applying the method to infer the form of bead using a neural network algorithm. The way of bead's visualization is applying the spline algorithm. To accurately represent Morphological information of the bead, requires much of morphological information, so it can occur problem to save into database that is why we using the spline algorithm. By applying the spline algorithm, it can make simplified data and generate accurate bead shape. Through the research paper, the shape of bead generated by the virtual reality was able to improve the accuracy when compared using the form of bead generated by the robot welding to using the morphological information of the bead generated through the robot welding. By express the accurate shape of bead and so can reduce the difference of the actual welding training and virtual welding, it was confirmed that it can be performed safety and high effective virtual welding education.

• 국제학술발표논문집
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• The 7th International Conference on Construction Engineering and Project Management Summit Forum on Sustainable Construction and Management
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• pp.214-224
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• 2017

本文运用文献计量分析的可视化软件 CiteSpace 对 CNKI 数据库平台上收录的我国高校工程管理人才培养研究相关文献进行分析, 了解我国高校工程管理人才培养研究现状以及研究的发展轨迹。 研究结果显示: 我国高校工程管理人才培养研究持续活跃, 文献数量呈稳步上升趋势, 载文期刊分布广泛, 研究者多, 但各研究机构之间合作少; 研究热点主要集中在应用型工程管理人才培养,实践教学改革和课程体系改革等方面。 为此, 我国高校工程管理人才培养相关研究可加强学术团体间的合作, 拓展研究对象的范围, 丰富研究视角, 并进一步探讨 "新工科" 发展下的工程管理人才培养。

• 유통과학연구
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• 제14권7호
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• pp.71-81
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• 2016

Purpose - Because creativity, which is an intangible resource embedded within the company, can offer a competitive advantage, most companies have an interest in promoting creativity among their employees and division(e.g., marketing organization). Creativity renders a sustainable competitive advantage to a firm because it is a strategic resource that is valuable, flexible, rare, and imperfectly imitable or substitutable. Although most companies broadly recognize the importance of creativity, the methods for developing creativity remain elusive. Therefore, the present study investigates how to structure incentives to motivate employees to be more creative and how to develop tools to facilitate creativity. In detail, the present study aimed to examine the relationship between the regulatory focus of marketing organizations(e.g., promotion focus vs prevention focus) and creativity of marketing organizations. In addition, the present study set out to examine the moderating role of interaction of financial reward and creative training in addition to investigating the direct relationship between creativity and regulatory focus in New Product Development(NPD) context. Research design, data, and methodology - The data used to test the hypotheses are drawn from a survey of full time NPD project members(including project manager, designer, engineer, and marketer). The present study utilized data obtained mainly from a database compiled by the Korea Investors Service-Financial Analysis System which provides comprehensive corporate and financial information on firms listed on the Korea Stock Exchange. A study population comprising 1,000 South Korean firms was obtained from this database. We selected 864 firms from the database, and the firms have experiences of new product development project. We collected a total of 162 responses, for a 18.8% response rate. After we excluded 14 questionnaire because of incomplete responses, a total of 148 questionnaire remained(final response rate: 17.1%). Working with a sample of 148 responses in South Korea, hierarchical moderated regression is employed to test research hypotheses(

The relationship between promotion focus and creativity of marketing organization,

The relationship between prevention focus and creativity of marketing organization,

The moderating effect of joint influences(interaction between financial rewards and creativity training) on the relationship between promotion focus creativity of marketing organization,

The moderating effect of joint influences(interaction between financial rewards and creativity training) on the relationship between prevention focus creativity of marketing organization). SPSS 18.0 and AMOS software were used in the data analysis. Results - The empirical study confirmed that promotion focus of marketing organization is positively related to creativity of marketing organization. Also, prevention focus of marketing organization is positively affected to creativity of marketing organization. In addition, the interaction between financial rewards and creativity training moderated the relationship between regularity focus(e.g.), promotion focus vs prevention focus) and creativity of marketing organization. These results suggest that managers can improve the performances of their creative efforts by providing the use of financial rewards and creativity training in combination. Conclusion - Based on results of this study that examine the effects of regulatory focused creative efforts on creativity of marketing organization, promotion focus is helpful with marketing organizations to enhance their service innovation and performance. Prevention focused organization should allow monetary rewards and creativity training to increase their creativity for innovation of new products.

• 정보관리연구
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• 제27권1호
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• pp.40-65
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• 1996

본고에서는 VOCED 데이터베이스의 정보검색기법을 살펴보았다. VOCED 데이터베이스를 직업 교육 및 훈련, 그러고 성인교육분야와 관련된 국제적인 정보를 수록하고 있다. VOCED는 CDS/ISIS 소프트웨어를 통해 구축되었으며, 레코드는 APSDEP 시소러스를 사용하여 색인되었다. VOCED 데이터베이스의 정보검색시에는 여러가지 검색기법들을 사용할 수 있다. 다수용어, 구문, 불리안 논리, 용어절단, 제한탐색 및 인접탐색기법 등을 통해 원하는 정보에 신속히 접근할 수 있다.

• 한국콘텐츠학회논문지
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• 제6권11호
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• pp.243-248
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• 2006

간판인식은 관광지의 간판을 자동 인식하여 외국인 또는 외지인에게 편리한 관광 정보제공을 목적으로 연구되고 있다. 간판 인식 연구에서는 인식기의 훈련과 객관적인 성능 측정을 위해 간판영상 데이터베이스가 필수적이다. 이 논문은 전주 한옥마을을 대상으로 수집한 간판영상 데이터베이스에 대해 기술한다. 총 45개의 서로 다른 간판에 대해 각각 50개씩 영상을 다양한 조건에서 획득하였다. 이 데이터베이스는 패턴 인식 분야 연구를 위한 중요한 콘텐츠 이다.

• 한국음향학회:학술대회논문집
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• 한국음향학회 2000년도 하계학술발표대회 논문집 제19권 1호
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• pp.39-42
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• 2000

VQ 모델로 구성된 화자인식 시스템의 성능 향상을 위해 Bootstrap 방식을 적용하였다. Bootstrap 및 aggregating방식은 unstable한 모델에서 그 성능이 유효하므로 이의 적용을 위해 먼저 VQ 모델의 bias와 variance를 계산하여 unstable함을 보였다. 화자인식 실험은 TIMIT Database를 사용하여 수행하였고 실험결과 높은 인식율 향상을 확인하였다. 또한 적은 훈련 데이터 환경에서도 좋은 인식율을 갖는 것으로 나타났다.