• Journal of KIISE
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• v.42 no.9
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• pp.1124-1132
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• 2015

In order to train a supervised machine learning algorithm, it is necessary to have non-biased labels and a sufficient amount of training data. However, it is difficult to collect the required non-biased labels and a sufficient amount of training data to develop an automatic English Composition scoring system. In addition, an English writing assessment is carried out using a multi-faceted evaluation of the overall level of the answer. Therefore, it is difficult to choose an appropriate machine learning algorithm for such work. In this paper, we show that it is possible to alleviate these problems through ensemble learning. The results of the experiment indicate that the ensemble technique exhibited an overall performance that was better than that of other algorithms.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.849-854
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• 2023

The Korea Post is providing postal, savings, and insurance services to the public. Although it has been automated due to the development of the industry, the risk of industrial accidents is high. Safety and health education should be effectively conducted to reduce industrial accidents. In this study, a survey was conducted for postal service workers. As a result, there was a tendency to prefer instructors with technical experience and professional qualifications, and increasing direct participation training through on-site inspection and audio-visual training and hands-on training were found to be helpful. analyzed. Based on this, an efficient safety and health education plan was presented to improve safety and health awareness, and it can be used as a basic data

• 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 Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2007.04a
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• pp.383-387
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• 2007

The improved accuracy of the Land Cover/Land Use Map constructed using Hyperspectal Satellite Image and the possibility of real time classification of Land Use using optimal Band Selective Factor enable the change detection from automatic classification using the existed Land Cover/Land Use Map and the newly acquired Hyperspectral Satellite Image. In this study, the effective analysis techniques for automatic generation of training regions, automatic classification and automatic change detection are proposed to minimize the expert's interpretation for automatic update of the Land Cover/Land Use Map. The proposed algorithms performed successfully the automatic Land Cover/Land Use Map construction, automatic change detection and automatic update on the image which contained the changed region. It would increase applicability in actual services. Also, it would be expected to present the effective methods of constructing national land monitoring system.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.9 s.174
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• pp.93-98
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• 2005

The purposes of this paper are the review and derivation of design characteristics for the new construction of the practical flexible manufacturing system. The basic ideas to analyze the manufacturing system which is the automatically operated are dependant on the various manufacturing procedures in factory. The practical flexible manufacturing systems have various mechanical subsystems appropriated fur the final manufacturing products. Therefore the systems have the various kinds of hardwares as well as softwares. We study the software for the practical flexible manufacturing system designed and developed in the Halla University with the related company. Specially the design concepts and using specifications of all subsystems which are composed of mechanical and electronic movements of the product are analyzed and introduced in this dissertation.

• Proceedings of the KIPE Conference
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• 2008.06a
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• pp.160-163
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• 2008

Currently workmen take charge of the maintenance work of bridges. But the process of sealing cracks in damage bridge is dangerous, costly, and labor-intensive operation Labor turnover and training are increasing problems related to crack sealing crews, and as traffic volumes increase, crack sealing operations become increasingly disruptive to the general public. Automation crack sealing can reduce labor and road user costs, improve work quality and decrease worker exposure to bridge hazards. This research aims to develop an automated damage bridge crack sealing system and developing of algorithms for hybrid controlling.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.50 no.2
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• pp.195-206
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• 2017

Joint time-frequency images of the broadband echo signals of six fish species were obtained using the smoothed pseudo-Wigner-Ville distribution in controlled environments. Affine transformation and principal component analysis were used to obtain eigenimages that provided species-specific acoustic features for each of the six fish species. The echo images of an unknown fish species, acquired in real time and in a fully automated fashion, were identified by finding the smallest Euclidean or Mahalanobis distance between each combination of weight matrices of the test image of the fish species to be identified and of the eigenimage classes of each of six fish species in the training set. The experimental results showed that the Mahalanobis classifier performed better than the Euclidean classifier in identifying both single- and mixed-species groups of all species assessed.

• Journal of Fashion Business
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• v.3 no.3
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• pp.59-67
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• 1999

The results of study can be summarized as follows: 1. Few sewing companies committed their workers to a professional and systematic training course. 2. Brands as Brother, Juki, Yamato, Singer and Nara were being much used. Among them the Brother was most popular. The age of the sewing machines was between one and six years. Most companies were repairing their machines. The manual main sewing machines were more frequently out of order than other machines. The ratio of idle machines was highest in sewing work, compared with cutting or finishing work, primarily due to decreased orders, aging machines or reduced manpower. 3. Most of the sewing companies were feeling necessary for automated sewing machines.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.1
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• pp.147-155
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• 2010

Landcover information of access-denied area was extracted from low-medium and high resolution satellite image. Training for supervised classification was performed to refer visually by landcover map which is made and distributed from The Ministry of Environment. The classification result was compared by relating data of FACC land classification system. As we rasterize digital military map with same pixel size of satellite classification, the accuracy test was performed by image to image method. In vegetation case, ancillary data such as NDVI and image for seasons are going to improve accuracy. FACC code of FDB need to recognize the properties which can be automated.

• Journal of the Korea Society of Computer and Information
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• v.21 no.12
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• pp.125-130
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• 2016

Automatic quality inspection by computer vision can be applied and give a solution to the pharmaceutical industry field. Pharmaceutical capsule can be easily affected by flaws like dents, cracks, holes, etc. In order to solve the quality inspection problem, it is required computationally efficient image processing technique like thresholding, boundary edge detection and segmentation and some automated systems are available but they are very expensive to use. In this paper, we have developed a dented capsule image processing technique using edge-based image segmentation, TLS(Total Least Squares) curve fitting technique and adopted low cost camera module for capsule image capturing. We have tested and evaluated the accuracy, training and testing time of the classification recognition algorithms like PCA(Principal Component Analysis), ICA(Independent Component Analysis) and SVM(Support Vector Machine) to show the performance. With the result, PCA, ICA has low accuracy, but SVM has good accuracy to use for classifying the dented capsule.