• Nuclear Engineering and Technology
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• v.48 no.4
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• pp.1015-1021
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• 2016

Structures, systems, and components (SSCs) important to safety of nuclear facilities shall be designed, fabricated, erected, and tested to quality standards commensurate with the importance of the safety functions. Although SSC classification guidelines for nuclear power plants have been well established and applied, those for research reactors have been only recently established by the International Atomic Energy Agency (IAEA). Korea has operated a pool-type research reactor (the High Flux Advanced Neutron Application Reactor) and has recently exported another pool-type reactor (Jordan Research and Training Reactor), which is being built in Jordan. Korea also has a plan to build one more pool-type reactor, the Kijang Research Reactor, in Kijang, Busan. The safety classification of SSCs for pool-type research reactors is proposed in this paper based on the IAEA methodology. The proposal recommends that the SSCs of pool-type research reactors be categorized and classified on basis of their safety functions and safety significance. Because the SSCs in pool-type research reactors are not the pressure-retaining components, codes and standards for design of the SSCs following the safety classification can be selected in a graded approach.

• Journal of Multimedia Information System
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• v.8 no.4
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• pp.211-220
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• 2021

The process of inspecting SMDs on the PCB boards improves the product quality, performance and reduces frequent issues in this field. However, undesirable scenarios such as assembly failure and device breakdown can occur sometime during the assembly process and result in costly losses and time-consuming. The detection of these components with a model based on deep learning may be effective to reduce some errors during the inspection in the manufacturing process. In this paper, YOLO models were used due to their high speed and good accuracy in classification and target detection. A SMD detection and classification method using YOLO networks based on robust data preprocessing and augmentation techniques to deal with various types of variation such as illumination and geometric changes is proposed. For 9 different components of data provided from a PCB manufacturer company, the experiment results show that YOLOv4 is better with fast detection and classification than YOLOv3.

• Journal of Korean Society for Quality Management
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• v.17 no.2
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• pp.64-69
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• 1989

This paper aims at analyzing the process capability and at determining an optimal condition by experimental designs using the 2-way classification with repitition in order to maintain lower Nacl content and to refine both of a very small quantity of fatty acid and various magnetic ions in the glycerin to use ion exchange resin treatment process. An optimal condition of each level combination in both of passing temperature of cation exchange resin($A_1$, $A_2$, $A_3$) and of anion exchange resin($B_1$, $B_2$, $B_3$) is $A_3B_3$. The process capability index is improved from 0.63 to 1.40 and is interpreted as a desirable state. This analysis of process capability by experimental designs will contribute to improving productivity and quality of products.

• Journal of Information Technology Services
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• v.7 no.4
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• pp.179-198
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• 2008

It is widely known that usability is a critical quality attribute of IT systems. Many studies have developed various methods for finding out usability problems. Usability professionals have emphasized that usability should be integrated into the development life cycle in order to maximize the usability of systems with minimal cost. To achieve this, it is essential to classify usability problems systematically and connect them into the activities of designing user interfaces and tasks. However, there is a lack of framework or method for these two problems and thus remains a challengeable research issue. As a beginning study, this paper proposes a conceptual framework for addressing the two issues. We firstly summarize usability-related studies so far, including usability factors and evaluation methods. Secondly, we review seven approaches to identifying and classifying usability problems. Based on this review and opinions of usability engineers in real industry as well as the review results, this paper proposes a framework comprising three viewpoints, from which more sound classification scheme of usability problems can be inductively developed.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.767-772
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• 2005

The Internet is a packet switched network which offers best-effort service, but current IP network provide enhanced services such Quality of Services, Virtual Private Network (VPN) services, Distribute Firewall and IP Security Gateways. All such services need packet classification for determining the flow. The problem is performing scalable packet classification at wire speeds even as rule databases increase in size. Therefore, this research offer packet classification algorithm that increase classifier performance when working with enlarge rules database by rearrange rule structure into Bitmap Intersection Lookup (BIL) tables. It will use packet's header field for looking up BIL tables and take the result with intersection operation by logical AND. This approach will use simple algorithm and rule structure, it make classifier have high search speed and fast updates.

• Journal of Korean Society on Water Environment
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• v.27 no.6
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• pp.794-803
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• 2011

Self Organizing Map (SOM) was applied for pattern classification of hydrological and water quality data measured at Jangseong Reservoir on a monthly basis. The primary objective of the present study is to understand better data characteristics and relationship between the data. For the purpose, two SOMs were configured by a methodologically systematic approach with appropriate methods for data transformation, determination of map size and side lengths of the map. The SOMs constructed at the respective measurement stations for water quality data (JSD1 and JSD2) commonly classified the respective datasets into five clusters by Davies-Bouldin Index (DBI). The trained SOMs were fine-tuned by Ward's method of a hierarchical cluster analysis. On the one hand, the patterns with high values of standardized reference vectors for hydrological variables revealed the high possibility of eutrophication by TN or TP in the reservoir, in general. On the other hand, the clusters with low values of standardized reference vectors for hydrological variables showed the patterns with high COD concentration. In particular, Clsuter1 at JSD1 and Cluster5 at JSD2 represented the worst condition of water quality with high reference vectors for rainfall and storage in the reservoir. Consequently, SOM is applicable to identify the patterns of potential eutrophication in reservoirs according to the better understanding of data characteristics and their relationship.

• Journal of Biomedical Engineering Research
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• v.44 no.3
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• pp.182-189
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• 2023

CT is a medical device that acquires medical images based on Attenuation coefficient of human organs related to X-rays. In addition, using this theory, it can acquire sagittal and coronal planes and 3D images of the human body. Then, CT is essential device for universal diagnostic test. But Exposure of CT scan is so high that it is regulated and managed with special medical equipment. As the special medical equipment, CT must implement quality control. In detail of quality control, Spatial resolution of existing phantom imaging tests, Contrast resolution and clinical image evaluation are qualitative tests. These tests are not objective, so the reliability of the CT undermine trust. Therefore, by applying an artificial intelligence classification model, we wanted to confirm the possibility of quantitative evaluation of the qualitative evaluation part of the phantom test. We used intelligence classification models (VGG19, DenseNet201, EfficientNet B2, inception_resnet_v2, ResNet50V2, and Xception). And the fine-tuning process used for learning was additionally performed. As a result, in all classification models, the accuracy of spatial resolution was 0.9562 or higher, the precision was 0.9535, the recall was 1, the loss value was 0.1774, and the learning time was from a maximum of 14 minutes to a minimum of 8 minutes and 10 seconds. Through the experimental results, it was concluded that the artificial intelligence model can be applied to CT implements quality control in spatial resolution and contrast resolution.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.7
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• pp.205-212
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• 2020

Defects are an important factor in the quality of software developments. In order to manage defects, we propose additional information of search and classification. Additional information suggests a systematic classification scheme and method of operation. In this study, we propose additional information at the requirements analysis stage for defect management.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.9
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• pp.2191-2201
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• 2012

Traffic classification seeks to assign packet flows to an appropriate quality of service (QoS) class based on flow statistics without the need to examine packet payloads. Classification proceeds in two steps. Classification rules are first built by analyzing traffic traces, and then the classification rules are evaluated using test data. In this paper, we use self-organizing map and K-means clustering as unsupervised machine learning methods to identify the inherent classes in traffic traces. Three clusters were discovered, corresponding to transactional, bulk data transfer, and interactive applications. The K-nearest neighbor classifier was found to be highly accurate for the traffic data and significantly better compared to a minimum mean distance classifier.

• Journal of Korean Society for Quality Management
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• v.44 no.4
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• pp.713-733
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• 2016

Purpose: The primary objective of this case study is to establish a COQ(Cost of Quality) management system for power generation industries. Key topics of this study include collecting COQ elements, their classifications, COQ computation formula, and determining COQ improvement projects. Results: A comprehensive set of COQ elements have been isolated for electric power generation companies. The COQ elements were classified in such a way that they could be managed according to the PAF model as well as the SIPOC diagram. This study showed that a systematic approach could be established for monitoring the COQ elements and using them in the process of improving quality competitiveness. Methods: The PAF(Prevention-Appraisal-Failure) model has been employed in the process of collecting COQ elements for a power generation company. All the cost of quality elements were first examined through an extensive review of articles and books in the field of quality. The cost elements were then refined and augmented by conducting a comparative study with international standards. The COQ elements have been verified by a group of quality managers and classified according to both the PAF model and the SIPOC diagram for better understanding in the entire organization. An improvement strategy has been also proposed by using a typical COQ level of power generation companies. Conclusion: The conventional PAF model was used in establishing a COQ management system for power generation industries. This case study illustrates the procedure about identification, classification and computation of quality costs, including selection of improvement projects. The system can be used not only for observing the current state of cost elements related to quality, but also for planning an improvement strategy using the ratio of cost classification.