• IEMEK Journal of Embedded Systems and Applications
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• v.7 no.2
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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.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.6
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• pp.887-892
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• 2019

Many researchers have developed a series of vision-based technologies to monitor construction sites automatically. To achieve high performance of vision-based technologies, it is essential to build a large amount and high quality of training image database (DB). To do that, researchers usually visit construction sites, install cameras at the jobsites, and collect images for training DB. However, such human and site-dependent approach requires a huge amount of time and costs, and it would be difficult to represent a range of characteristics of different construction sites and resources. To address these problems, this paper proposes a framework that automatically constructs a training image DB using web crawling techniques. For the validation, the authors conducted two different experiments with the automatically generated DB: construction work type classification and equipment classification. The results showed that the method could successfully build the training image DB for the two classification problems, and the findings of this study can be used to reduce the time and efforts for developing a vision-based technology on construction sites.

• Proceedings of the KSRS Conference
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• 2004.10a
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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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• v.20 no.2E
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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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• v.34 no.1
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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.

• International conference on construction engineering and project management
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• 2017.10a
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• pp.214-224
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• 2017

This paper focuses on bibliometrics analysis of personnel training in construction management specialty using visualization software CiteSpace from CNKI database. And points out the research situation and development trend of college personnel training on construction management in China. The results show : (1)the research of professional talents in colleges of construction management presents continued activity, and the source journals are widely. There are a lot of researchers pay attention to this issue, but collaborate little with each other; (2)Most of literature fasten on the practical talent training mode, practical teaching reform and course system reformation. Therefore, we should be further strengthened in academic cooperation, be further broadened research scope, be further enriched the insight of the research, and should follow with interest the issue on personnel training on construction management under the background of new engineering disciplines.

• Journal of Distribution Science
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• v.14 no.7
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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.

• Journal of Information Management
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• v.27 no.1
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• pp.40-65
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• 1996

This study is to review information retrieval techniques of VOCED database. The VOCED database contains internationally relevant information on vocational and adult education, training and related subjects. The software used is CDS/ISIS and the records are indexed using the APSDEP Thesaurus. When searching the VOCED database, various types of search techniques can be used. Multiple word, phrase, boolean logic, term truncation, defind field, and proximity searching techniques or a mixture of all of them, make it possible to find exactly what you want in seconds.

• The Journal of the Korea Contents Association
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• v.6 no.11
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• pp.243-248
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• 2006

Recognition of sign has been studied to provide convenience tour information for foreigners and strangers through automatic recognition of sign. The sign image database is essential to training the classifier and to intuitive measurement of performance. In this paper, we described the sign image database collected at Jeonju Hanok Village. As to 45 each other sign image, corresponding 50 images are collected under several condition. This database could be important content to study for the field of pattern recognition.

• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.39-42
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• 2000

A bootstrap and aggregating (bagging) vector quantization (VQ) classifier is proposed for speaker recognition. This method obtains multiple training data sets by resampling the original training data set, and then integrates the corresponding multiple classifiers into a single classifier. Experiments involving a closed set, text-independent and speaker identification system are carried out using the TIMIT database. The proposed bagging VQ classifier shows considerably improved performance over the conventional VQ classifier.