• Journal of Korean Society for Quality Management
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• v.42 no.2
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• pp.165-177
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• 2014

Purpose: This study analyzes the strategical priority to improve eco-labelling certification system, focused on biodegradable resin. Methods: This study will come up with measures to operate the eco-Label certification system related to biodegradable products more effectively and efficiently by discovering various problems related to the system, using causal loop diagram and AHP analysis. Results: This study shows that the government should play more important role while firms could also serve their roles in the initial and stabilizing stages of the eco-labelling certification system, in order to vitalize the eco-Label certification system more effective. Conclusion: This study addresses strategic eco-labelling policies on governmental and firm's operation and providers guidance to practitioners in addressing strategic decision relating to eco-labelling certification system.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.04a
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• pp.225-230
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• 2004

A cold ＆ hot rolling coil production line of iron nill consists of a kind of coherent automatic process, but an automatic labelling process still had technical difficulties in the automation of its process. The reason for difficulties in building an automatic process is that quantitative data for each rolled coil from every shipping is not easy to receive from the previous process. it is not possible to apply for a general and simple purpose robot that is actually worked through a taught position to the process because the size and direction of the coi1 has differed on every shipping. From these reasons. we introduce a robot vision system to accept an expected variable situation and to ensure the stability and flexibility of the process. This paper examines a study applied for similar cases and finds the position and direction of relied coil using the moment invariant algorithm proposed by Hu. In addition. the camera calibration and position error compensation algorithm is applied by the analysis of the relationship of transition in a space coordinate system. The construction of a robot vision system proposed by this paper is a more intellectual system than that of the automatic labelling system. which is already used to the Daihen steel nill of NEW JAPAN steel mill co. Ltd in Japan, and shows a better independent operation in the field of production.

• Biomedical Science Letters
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• v.8 no.3
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• pp.161-165
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• 2002

Apoptosis can be difficult to detect in routine histological sections. Since extensive DNA fragmentation is an important characteristic of this process, visualization of DNA breaks could greatly facilitate the identification of apoptotic cells. Several techniques for the qualitative and quantitative detection of this process have been established; recently, an in situ nick end-labelling technique based on the detection of DNA fragmentation, which is a molecular characteristic of apoptotic cell death, was described. Applying this method to paraffin sections of rat tissues, sensitivity was observed to be inconsistently low with regard to the expected number of apoptotic cells. I describe a new modified method for formalin-fixed, paraffin-embedded tissue sections, pretense pretreatment to permeate the tissue sections that involves an TUNEL (terminal deoxynucleotidyl transferase-mediated dUTP nick end-labeling) is acknowledged as a method of choice in the rapid identification and quantification of the apoptotic cell fraction in paraffin tissue preparations. TUNEL was performed without apoptosis and with apopotosis samples to each of the three concentrations of proteinase K (10, 25, 40 mg/ml) pretreatments. In this study, I show that chemical pretreatments of the tissue sections in proteinase K (25 mg/ml for 15 min at room temperature) considerably enhances the sensitivity of this nick end labelling technique.

• Fashion & Textile Research Journal
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• v.20 no.3
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• pp.331-342
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• 2018

This paper enables stakeholders involved in textile industry to gain an overview of standards used for care labelling and help establish a common standard that could be used as a universal standard. This study provides a comprehensive and detailed analytical study of care labelling standards adopted by common countries in the textile market. It was found that the development of a universal system for care labeling could enhance the trade of textile articles and assist consumers in caring for textile articles. Universal care label systems could be characterized by two main features of inclusiveness and comprehensiveness. The range of instructions and symbols presented were found different among standards. Insignificant differences in symbols' shapes were found between standards for bleaching, ironing and professional cleaning. The washing process had the widest variety of instructions; in addition, options were provided by stated standards. Different meanings were found for similar shapes in some tumble drying symbols. The study findings show the importance of enhancing text based standards or the development of an understandable format across as many cultures as possible. The unification of symbols and meanings may be needed to provide global consumers consistent guidance. The efficiency of a detailed standard that provides and covers a wide range of instructions is an important aspect. The visibility and practicality of offering variable options/symbols in one standard is an important aspect for developing a universal care label system.

• Journal of Biomedical Engineering Research
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• v.16 no.3
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• pp.337-344
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• 1995

Because of the high energy of the treatment beam, contrast of portal films is very poor. Many image processing techniques have been applied to the portal images but a significant drawback is the loss of definition on the edges of the treatment field. Analysis of this problem shows that it may be remedied by separating the treatment field from the background prior to enhancement and uslng only the pixels within the field boundary in the enhancement procedure. A new edge extraction algorithm for accurate extraction of the radiation field boundary from portal Images has been developed for contrast enhancement of portal images. In this paper, portal image segmentation algorithm based on Sobel filtration, labelling processes and morphological thinning has been presented. This algorithm could automatically search the optimal threshold value which is sensitive to the variation of the type and quality of portal images.

• Journal of Korea Multimedia Society
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• v.20 no.5
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• pp.769-781
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• 2017

Deep learning networks like Convolutional Neural Networks (CNNs) show successful performances in many computer vision applications such as image classification, object detection, and so on. For implementation of deep learning networks in embedded system with limited processing power and memory, deep learning network may need to be simplified. However, simplified deep learning network cannot learn every possible scene. One realistic strategy for embedded deep learning network is to construct a simplified deep learning network model optimized for the scene images of the installation place. Then, automatic training will be necessitated for commercialization. In this paper, as an intermediate step toward automatic training under fisheye camera environments, we study more precise human localization in fisheye images, and propose an accurate human localization method, Automatic Ground-Truth Labelling Method (AGTLM). AGTLM first localizes candidate human object bounding boxes by utilizing GoogLeNet-LSTM approach, and after reassurance process by GoogLeNet-based CNN network, finally refines them more correctly and precisely(tightly) by applying saliency object detection technique. The performance improvement of the proposed human localization method, AGTLM with respect to accuracy and tightness is shown through several experiments.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.222-224
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• 2022

Deep learning-based computer vision applications in the field of object segmentation take a transfer learning method using hyperparameters and models pretrained and distributed by STOA techniques to improve performance. Custom datasets used in this process require a lot of resources, such as time and labeling, in labeling tasks to generate Ground Truth information. In this paper, we present an automatic labeling construction method using object segmentation techniques so that resources such as time and labeling can be used less to build custom datasets used in deep learning neural networks.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.1
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• pp.89-93
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• 1997

This paper describes the automatic testing system developed for powder metallurgy process using the visual inspection, and its some internal algorithms. The system consists of one unit from each of the five types of units; feeding, slot, vision inspection, volumn counter, and inferior good extractor units. Some applications of the system to powder metallurgy process has shown the possibility of reducing the rework and increasing the efficiency of operation.

• Journal of the Semiconductor & Display Technology
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• v.19 no.4
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• pp.121-125
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• 2020

With miniaturization of semiconductor, the manufacturing process become more complex, and undetected small changes in the state of the equipment have unexpectedly changed the process results. Fault detection classification (FDC) system that conducts more active data analysis is feasible to achieve more precise manufacturing process control with advanced machine learning method. However, applying machine learning, especially in supervised learning criteria, requires an arduous data labeling process for the construction of machine learning data. In this paper, we propose a semi-supervised learning to minimize the data labeling work for the data preprocessing. We employed equipment status variable identification (SVID) data and optical emission spectroscopy data (OES) in silicon etch with SF6/O2/Ar gas mixture, and the result shows as high as 95.2% of labeling accuracy with the suggested semi-supervised learning algorithm.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.8
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• pp.4987-4998
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• 2014

Recently, the use of nanotechnology in products is constantly expanding, and the problems on human health hazard has emerged as a major issue. A nanomaterials regulatory policy on the products is urgently required. This study analyzed the introduction of regulatory policies of nanomaterials contained in industrial products. In this study, the AHP (Analytic Hierarchy Process) method was applied and three regulatory policies were evaluated to analyze the validity of the introduction of a nanomaterials regulatory policy. To select the optimal regulatory policy, the policy evaluation criteria were set as enforcement (effectiveness), economics, acceptability, and protection. For the regulatory policies, self-regulation, product labelling, and enforced registration were introduced and evaluated as the regulatory policies, and product labelling was selected as the optimal regulatory policy.