• Journal of Digital Contents Society
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• v.18 no.1
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• pp.159-165
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• 2017

In order to solve problems in automatic quality inspection of tablet capsules, computation-efficient image processing technique, appropriate threshold setting, edge detection and segmentation methods are required. And since existing automatic system for quality inspection of tablet capsules is of very high cost, it needs to be reduced through the realization of low-price hardware system. This study suggests a technique that uses low-cost camera module to obtain image and inspects dents on tablet capsules and sorting them by applying TLS curve fitting technique and edge-based image segmentation. In order to assess the performance, the major classifications algorithm of PCA, ICA and SVM are used to evaluate training time, test time and accuracy for capsule image area and curve fitting edge data sets.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.5
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• pp.985-993
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• 2001

Neural networks are shown to be effective in being able to distinguish incomplete penetration-like weld defects by directly analyzing the plasma which is generated on each impingement of the laser on the materials. The performance is similar to that of existing methods based on extracted feature parameters. In each case around 93% of the defects in a database derived from 100 artificially produced defects of known types can be placed into one of two classes: incomplete penetration and bubbling. The present method based on classification using plasma is faster, and the speed is sufficient to allow on-line classification during data collection.

• Journal of Digital Policy
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• v.2 no.3
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• pp.1-7
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• 2023

In this paper, I proposes a method for performing single image super resolution by separating texture-spatial domains and then classifying features based on detailed information. In CNN (Convolutional Neural Network) based super resolution, the complex procedures and generation of redundant feature information in feature estimation process for enhancing details can lead to quality degradation in super resolution. The proposed method reduced procedural complexity and minimizes generation of redundant feature information by splitting input image into two channels: texture and spatial. In texture channel, a feature refinement process with step-wise skip connections is applied for detail restoration, while in spatial channel, a method is introduced to preserve the structural features of the image. Experimental results using proposed method demonstrate improved performance in terms of PSNR and SSIM evaluations compared to existing super resolution methods, confirmed the enhancement in quality.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.577-587
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• 2023

The utilization of crowdsourced spatial data has been actively researched; however, issues stemming from the uncertainty of data quality have been raised. In particular, when low-quality data is mixed into drone imagery datasets, it can degrade the quality of spatial information output. In order to address these problems, the study presents a methodology for automatically validating the geometric quality of crowdsourced imagery. Key quality factors such as spatial resolution, resolution variation, matching point reprojection error, and bundle adjustment results are utilized. To classify imagery suitable for spatial information generation, training and validation datasets are constructed, and machine learning is conducted using a radial basis function (RBF)-based support vector machine (SVM) model. The trained SVM model achieved a classification accuracy of 99.1%. To evaluate the effectiveness of the quality validation model, imagery sets before and after applying the model to drone imagery not used in training and validation are compared by generating orthoimages. The results confirm that the application of the quality validation model reduces various distortions that can be included in orthoimages and enhances object identifiability. The proposed quality validation methodology is expected to increase the utility of crowdsourced data in spatial information generation by automatically selecting high-quality data from the multitude of crowdsourced data with varying qualities.

• Journal of the Korean Society for Nondestructive Testing
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• v.17 no.3
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• pp.162-173
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• 1997

Automatic on-line surface inspection systems have been applied for monitoring a quality of steel strip surfaces. One of the important issues in this application is the performance of on-line defect classifiers. Rule-based classification table methods which are conventionally used for this purpose have been suffered from their low performances. In this work, probabilistic neural networks and the enhanced classification tables which are newly proposed here are applied as alternative on-line classifiers to identify types of surface defects on cold rolled strips. Probabilistic neural networks have shown very excellent performance for classification of surface defects.

• Journal of Service Research and Studies
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• v.6 no.2
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• pp.83-97
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• 2016

Smart car is a vehicle which maximizes convenience, safety, and user experience. The traditional vehicle style will be replaced by a smart car. The objective of this paper is to find essential quality attributes that consumers want. We provide a method to select a best smart car reflecting their preference based on the quality attributes. We derive Kano's quality attributes by an exploratory survey and show an example to implement their decision using the Analytic Hierarchy Process method. As a result, the quality attributes were classified into two groups of attractive quality and indifference quality. The respondents evaluated that the safety of smart cars was more important than the convenience and user experience. However, the smart car was required more functions related to the convenience criteria. These results will provide important implications for smart car design.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.19 no.4
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• pp.91-97
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• 2005

As the developing of industry, the nonlinear equipments as inverter, converter, SMPS(Switching Mode Power Supply) and motor have been increased. But the sensitive electronic loads to the power quality, such as computers and other electronic equipments, have been spreaded out very fast. Thus, the power quality(PQ) problems and the real time power quality monitering(PQM) are one of the important issues in industry and building area for the intelligent control of the systems. One of them, PQM using PLC(Power Line Communication) have good merits that can send and receive the PQ information without any new network line. This paper presents the PQM hardware and software to monitor the PQ information by using PLC that meets the categories of IEEE Std. 1159.

• Korean Journal of Construction Engineering and Management
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• v.5 no.3 s.19
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• pp.137-145
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• 2004

Owing to the growth of Information Technology, some of big general contractors have been interested in the development of Quality Management Information Systems to integrate the information of quality in planning, design, procurement, construction, and maintenance phases, and tried to maximize the usefulness of it. But the trend has confined only to some big general contractors. The purpose of this paper is to put together and analyze the character of Quality Management Information Systems of big general construction companies and classfy them into a result-focused system and a process-focused system in order to provide primary information for both of development and adoption of the systems.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.3B
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• pp.143-152
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• 2007

In order to provide new value-added services such as a policy-based routing and the quality of services in next generation network, the Internet routers need to classify packets into flows for different treatments, and it is called a packet classification. Since the packet classification should be performed in wire-speed for every packet incoming in several hundred giga-bits per second, the packet classification becomes a bottleneck in the Internet routers. Therefore, high speed packet classification algorithms are required. In this paper, we propose an efficient packet classification architecture based on a hierarchical binary search fee. The proposed architecture hierarchically connects the binary search tree which does not have empty nodes, and hence the proposed architecture reduces the memory requirement and improves the search performance.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.4
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• pp.55-67
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• 2018

The objective of this study is to investigate the effect of ERP system quality factors on the system use satisfaction and on personal and organizational performances. For achieving this objective, we investigated the interrelationship among quality factors, use satisfaction and business performance in the companies which operate the ERP system using questionnaires, whereas many previous studies focused on general quality factors such as the relationship between system quality and use satisfaction on organizational performance. The difference between our study and previous studies is that we classified the information system quality into three categories (system quality, information quality, and service quality) before analyzing the respective relationship among three identified variables (use satisfaction, individual performance and organization performance). The result of this study proved that the system quality, information quality, and service quality considered as the ERP system quality factors have a positive effect on user satisfaction level, respectively.