• Journal of Korean Society for Quality Management
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• v.47 no.2
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• pp.381-395
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• 2019

Purpose: This study aims to conduct a systematic literature review to suitably identify wide and specific issues and topics on service quality in supply chain. Methods: This study is to investigate service quality in supply chain research using a systematic literature review methodology. In order to extract influential journals and papers, we used the SJR impact factor provided by the SCOPUS database. The collected 169 papers were analyzed using bibliometric analysis, citation analysis as well as keywords network. Results: We conducted a bibliometric analysis to identify top authors contributing to service quality in supply chain and their issues, and further examined important keywords and new emerging keywords. In addition, we extracted five influential papers by PageRank to clarify critical issues and divided into five clusters to identify topics of service quality in supply chain by using network-based approach. In order to examine comprehensive issues and topics of service quality in supply chain, we constructed a keyword network to observe difference in the classification of important keywords across network centrality measures. Conclusion: Our study reviewed literature on service quality in supply chain and explored the future directions and trends of service quality in supply chain.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.15 no.4
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• pp.485-494
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• 2008

Purpose: In this study, relationships between symptom experience and quality of life in a cross-sectional sample of patients with Atrial Fibrillation (AF) were investigated. Methods: This descriptive study involved a convenience sample of AF patients from S university hospital, C city. One hundred and two AF patients completed psychometric validated measures of AF related symptoms and quality of life. Descriptive statistics and Pearson correlation coefficients with SPSS WIN 14.0 were used for data analysis. Results: Of 16 atrial arrhythmia-related symptoms, the patients reported 'tiredness' as the most frequent and 'shortness of breath' as the most severe. The level of overall quality of life for patients with AF was 53.92. There were significant differences in symptom frequency according to religion, New York Heart Association (NYHA) classification and left ventricular ejection fraction ; symptom severity according to monthly income and stroke ; quality of life according to age, job, alcohol intake, NYHA class and stroke. Quality of life for these patients was positively correlated with symptom frequency and symptom severity. Conclusions: This study demonstrated that patients with more frequent and severe symptoms perceive poorer quality of life than patients with less frequent and less severe symptoms. Symptom experience should be assessed early to improve quality of life for patients.

• Journal of Korean Academy of Nursing
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• v.39 no.3
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• pp.409-421
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• 2009

Purpose: In this research multi-level analysis was done to identify factors related to quality of services. Patient characteristics and organizational factors were considered. Methods: The data were collected from the Health Insurance Review and Assessment Service(HIRA) data base. The sample was selected from 17,234 patients who had been admitted between January 2007 and May 2008 to one of 253 long-term care hospitals located in Seoul, six other metropolitan cities or nine provinces The data were analyzed with SAS 9.1 using multi-level analysis. Results: The results indicated that individual level variables related to quality of service were age, cognitive ability, patient classification, and initial quality scores. The organizational level variables related to quality of service were ownership, number of beds, and turnover rate. The explanatory power of variables related to organizational level variances in quality of service was 23.72%. Conclusion: The results of this study indicate that differences in the quality of services were related to organizational factors. It is necessary to consider not only individual factors but also higher-level organizational factors such as nurse' welfare and facility standards if quality of service in long term care hospitals is to be improved.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.10a
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• pp.363-366
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• 2001

The present process of grading leather quality by the rare eyes is not reliable. Because inconsistency of grading due to eyes strain for long time can cause incorrect result of grading. Therefore it is necessary to automate the process of grading quality of leather based on objective standard for it. In this paper, leather automatic classification system consists of the process obtaining the information of leather and the process grading the quality of leather from the information. Leather is graded by its information such as texture density, types and distribution of defects. This paper proposes the algorithm which sorts out leather information like texture density and defects from the gray-level images obtained by digital camera. The density information is sorted out by the distribution value of Fourier spectrum which comes out after original image is converted to the image in frequency domain. And the defect information is obtained by the statistics of pixels which is relevant to Window using searching Window after sort out boundary lines from preprocessed images. The information for entire leather is used as standard of grading leather quality, and the proposed algorithm is practically applied to machine vision system.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.2
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• pp.230-235
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• 2008

Recently, LG chemical corporation developed new material called HYPERIER, which has an excellent barrier characteristic. It has many layers which are made of nano-composite within LDPE(Low-Density Poly Ethylene). In order to guarantee the quality of the final product from the production line, a certain test equipment is required to investigate the existence of layers inside the HYPERIER. In this work, ultrasonic sensor based test equipment for investigating the existence of inner layers is proposed. However, it is a tedious job for human operators to check the existence by just looking at the resounding waveform from ultrasonic sensor. Therefore, to enhance the performance of the ultrasonic test equipment, Fast Fourier Transform(FFT) and Principle Components Analysis(PCA) and Back-Propagation Neural Network(BPNN) are utilized which is used for classification of Quality. To verily the feasibility of the proposed scheme, some experiments are executed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.10
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• pp.1301-1308
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• 2016

Internet traffic identification is an essential preliminary step for stable service provision and efficient network management. The payload signature-based-classification is considered as a reliable method for Internet traffic identification. But its performance is highly dependent on the number and the structure of signatures. If the numbers and structural complexity of signatures are not proper, the performance of payload signature-based-classification easily deteriorates. Therefore, in order to improve the performance of the identification system, it is necessary to regulate the numbers of the signature. In this paper, we propose a novel signature quality evaluation method to decide which signature is highly efficient for Internet traffic identification. We newly define the signature quality evaluation criteria and find the highly efficient signature through the method. Quality evaluation is performed in three different perspectives and the weight of each signature is computed through those perspectives values. And we construct the signature map(S-MAP) to find the highly efficient signature. The proposed method achieved an approximately fourfold increased efficiency in application traffic identification.

• Journal of Biomedical Engineering Research
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• v.43 no.6
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• pp.390-398
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• 2022

Ultrasound examination using ultrasound equipment is an ultrasound device that images human organs using sound waves and is used in various areas such as diagnosis, follow-up, and treatment of diseases. However, if the quality of ultrasound equipment is not guaranteed, the possibility of misdiagnosis increases, and the diagnosis rate decreases. Accordingly, The Korean Society of Radiology and Korea society of Ultrasound in Medicine presented guidelines for quality management of ultrasound equipment using ATS-539 phantom. The DenseNet201 classification algorithm shows 99.25% accuracy and 5.17% loss in the Dead Zone, 97.52% loss in Axial/Lateral Resolution, 96.98% accuracy and 20.64% loss in Sensitivity, 93.44% accuracy and 22.07% loss in the Gray scale and Dynamic Range. As a result, it is the best and is judged to be an algorithm that can be used for quantitative evaluation. Through this study, it can be seen that if quantitative evaluation using artificial intelligence is conducted in the qualitative evaluation item of ultrasonic equipment, the reliability of ultrasonic equipment can be increased with high accuracy.

• Korean Journal of Remote Sensing
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• v.38 no.6_4
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• pp.1945-1953
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• 2022

Korea Aerospace Research Institute produces mosaic images of the Korean Peninsula every year to promote the use of satellite images and provides them to users in the public sector. However, since the pan-sharpening and color balancing methodologies are applied during the mosaic image processing, the original spectral information is distorted. In addition, there is a limit to analyze using mosaic images as mosaic images provide only Red, Green and Blue bands excluding Near Infrared (NIR) band. Therefore, in order to compensate for these limitations, this study applied the Principal Component Analysis (PCA) technique and indices extracted from R, G, B bands together for image classification and compared the classification results. As a result of the analysis, the accuracy of the mosaic image classification result was about 67.51%, while the accuracy of the image classification result using both PCA and RGB indices was about 75.86%, confirming that the accuracy of the image classification result can be improved. As a result of comparing the PCA and the RGB indices, the accuracy of the image classification result was about 64.10% and 74.05% respectively. Through this, it was confirmed that the classification accuracy using the RGB indices was higher among the two techniques, and implications were derived that it was important to use high quality reference or supplementary data. In the future, additional indices and techniques are needed to improve the classification and analysis results of mosaic images, and related research is expected to increase the utilization of images that provide only R, G, B or limited spectral information.

• Journal of Animal Science and Technology
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• v.56 no.4
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• pp.15.1-15.10
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• 2014

Background: Morphologically classifying embryos is important for numerous laboratory techniques, which range from basic methods to methods for assisted reproduction. However, the standard method currently used for classification is subjective and depends on an embryologist's prior training. Thus, our work was aimed at developing software to classify morphological quality for blastocysts based on digital images. Methods: The developed methodology is suitable for the assistance of the embryologist on the task of analyzing blastocysts. The software uses artificial neural network techniques as a machine learning technique. These networks analyze both visual variables extracted from an image and biological features for an embryo. Results: After the training process the final accuracy of the system using this method was 95%. To aid the end-users in operating this system, we developed a graphical user interface that can be used to produce a quality assessment based on a previously trained artificial neural network. Conclusions: This process has a high potential for applicability because it can be adapted to additional species with greater economic appeal (human beings and cattle). Based on an objective assessment (without personal bias from the embryologist) and with high reproducibility between samples or different clinics and laboratories, this method will facilitate such classification in the future as an alternative practice for assessing embryo morphologies.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.12
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• pp.635-640
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• 2016

It is important factors for a production system to get a profitable result in quality and reliability process. For this reason, there's are various type of research papers in a certain type of data acquisition and application to reliability and quality of the level of M2M devices. In general, a classification problem of slightly different signal such as sensing data is difficult to do with classical statistical methods. There's required real-time and instantaneous calculation properties in machine process. Especially a type of injection molding machine which has a property to be decided in accordance with short-term cycle process needs a solution that can be done a certain type of decision like as good or bad quality immediately. This paper presents a simple application of Kalman Filtering by single sensing data to injection molding process in order to get a correct answer from the real time sensing data.