• Journal of Korean Institute of Industrial Engineers
• /
• v.41 no.6
• /
• pp.572-578
• /
• 2015

Yield prediction is one of the most important issues in semiconductor manufacturing. Especially, for a fast-changing environment of the semiconductor industry, accurate and reliable prediction techniques are required. In this study, we propose a prediction model to predict wafer yield based on virtual metrology process parameters in semiconductor manufacturing. The proposed prediction model addresses imbalance problems frequently encountered in semiconductor processes so as to construct reliable prediction model. The effectiveness and applicability of the proposed procedure was demonstrated through a real data from a leading semiconductor industry in South Korea.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.15 no.4
• /
• pp.131-136
• /
• 2019

As the NCS(National Competency Standards) classification system continued to be developed and supplemented, NCS became widespread. Qualifications were redesigned to actively reflect industry demands, reduce the burden of redundant acquisition of unnecessary qualifications, and to evaluate objective capacities of the workforce. In addition to the learning modules to be developed in the future, previously developed NCS-based learning modules and lectures should be reorganized based on the new qualification design. In this paper, the Java programming subject designed based on NCS was redesigned according to SW new qualification design. Since the redesigned Java programming subjects consider the qualification design direction or qualification roadmap, not only can they be recognized as a test subject in qualification assessment through course evaluation, but also can be used as individual qualification data.

• Food Science and Industry
• /
• v.50 no.4
• /
• pp.50-64
• /
• 2017

Applications of the second generation of electronic nose in various field such as new food product development, slight rancidity during induction period, classification of similar products, discovery of odor, and odor reduction were reviewed. The possibilities of using electronic noses in areas that are difficult to analyze so far would be done in the future. It is believed that the utility value is expanded not only in the food industry but also in other areas.

• Journal of Dairy Science and Biotechnology
• /
• v.38 no.4
• /
• pp.230-236
• /
• 2020

Heat treatment is a fundamental processing technology in the dairy industry. The main purpose of heat treatment is to destroy pathogenic and spoilage promoting microorganisms to ensure milk safety and shelf life. Despite the development of alternative technologies, such as high-pressure processing and pulse field technology for microbial destruction, heat treatment is widely used in the dairy industry and in other food processes to destroy microorganisms. Heat treatment has contributed greatly to the success of food preservation since Pasteur's early discovery that heat treatment of wine and beer could prevent their deterioration, and since the introduction of milk pasteurization in the 1890s. In Korea, food labeling standards do not stratify heat treatments into low temperature, high temperature, and ultra-high temperature methods. Most milk is produced in Korea by pasteurization, with extended shelf life (ESL : 125--140℃ / 1-10 s). Classification based on temperature (i.e. low, high, and ultra-high), is meaningless.

• Journal of Information Technology Applications and Management
• /
• v.28 no.1
• /
• pp.63-81
• /
• 2021

The advent of the convergence era led to the convergence of industries while increasing the uncertainty of R&D. R&D uncertainty can be addressed by identifying and addressing industrial innovation patterns, which Neo-Schumpeterian suggested can be identified through the process of identifying the technical characteristics of a particular industry, which can be embodied in the concept of technology trajectory. Thus, this study considered and proposed a method to track the technology trajectory of the convergence industry through topic modeling and patent citation network analysis, and applied it to the micro medical robot industry, which is a representative convergence industry, to track the technology trajectory of active catheter. In particular, it is intended to identify the unique characteristics of the industry by identifying the industry before the promotion of the national-led medical robot industry support policy. Therefore, we tried to understand the innovation pattern of the industry by tracking the technology trajectory of the industry before 2017, the time of full-scale support for the medical robot industry in the United States. Through tracking technology trajectories, the role of each technology classification, the development path, and the knowledge flow between applicants were analyzed empirically. The results of this study are expected to contribute to resolving the remaining uncertainties in the process of establishing an active catheter R&D strategy, one of the leading convergence industries, and furthermore, it is expected to be available for tracking technology trajectories in other industries.

• Asian Pacific Journal of Cancer Prevention
• /
• v.17 no.5
• /
• pp.2375-2382
• /
• 2016

Cancer is a major health problem in Oman. It is reported that cancer incidence in Oman is the second highest after Saudi Arabia among Gulf Cooperation Council countries. Based on GLOBOCAN estimates, Oman is predicted to face an almost two-fold increase in cancer incidence in the period 2008-2020. However, cancer research in Oman is still in its infancy. This is due to the fact that medical institutions and infrastructure that play central roles in data collection and analysis are relatively new developments in Oman. We believe the country requires an organized plan and efforts to promote local cancer research. In this paper, we discuss current research progress in cancer diagnosis using machine learning techniques to optimize computer aided cancer detection and classification (CAD). We specifically discuss CAD using two major medical data, i.e., medical imaging and microarray gene expression profiling, because medical imaging like mammography, MRI, and PET have been widely used in Oman for assisting radiologists in early cancer diagnosis and microarray data have been proven to be a reliable source for differential diagnosis. We also discuss future cancer research directions and benefits to Oman economy for entering the cancer research and treatment business as it is a multi-billion dollar industry worldwide.

• Journal of the Korean Society of Safety
• /
• v.20 no.2 s.70
• /
• pp.127-132
• /
• 2005

The purpose of this study is to compare representative posture classification schemes of OWAS, RULA and REBA in terms of correctness for postural load. The comparison was based on the evaluation results by the three methods for 224 working postures sampled from steel, electronics, automotive, and chemical industries. The results showed that OWAS and REBA generally underestimated postural stress than RULA irrespective of industry type, work performed and whether or not leg posture is balanced. While about $71\%\;and\;73\%$ of the 224 posture were evaluated with the action category/level 1 or 2 by OWAS and REBA respectively, about $60\%$ of the postures were classified into the action level of 3 or 4 by RULA. The coincidence rate of postural stress category between OWAS and RULA was just $33.5\%$, while the rate between RULA and REBA was $46.0\%$. It is concluded from the findings of this study and the previous research that compared to OWAS and REBA, RULA more precisely evaluates postural stress.

• Journal of Institute of Control, Robotics and Systems
• /
• v.2 no.4
• /
• pp.337-343
• /
• 1996

In this paper, we investigate the defect detection by making use of pre-made reference image data and classify the defects by using the artificial neural network. The approach is composed of three main parts. The first step consists of a proper generation of two reference image data by using a low level morphological technique. The second step proceeds by performing three times logical bit operations between two ready-made reference images and just captured image to be tested. This results in defects image only. In the third step, by extracting four features from each detected defect, followed by assigning them into the input nodes of an already trained artificial neural network we can obtain a defect class corresponding to the features. All of the image data are formed in a bit level for the reduction of data size as well as time saving. Experimental results show that proposed algorithms are found to be effective for flexible defect detection, robust classification, and high speed process by adopting a simple logic operation.

• Journal of the Korea Computer Industry Society
• /
• v.2 no.8
• /
• pp.1045-1054
• /
• 2001

To improve classification accuracy in this paper, we proposed an algorithm for the chromosome image reconstruction in the image preprocessing part and also proposed the pattern classification method using the hierarchical multilayer neural network(HMNN) to classify the chromosome karyotype. It reconstructed chromosome images for twenty normal human chromosome by the image reconstruction algorithm. The four morphological and ten density feature parameters were extracted from the 920 reconstructed chromosome images. The each combined feature parameters of ten human chromosome images were used to learn HMNN and the rest of them were used to classify the chromosome images. The experimental results in this paper were composed to optimized HMNN and also obtained about 98.26％ to recognition ratio.

• Journal of the Korea Computer Industry Society
• /
• v.3 no.5
• /
• pp.605-610
• /
• 2002

In this paper, we propose a Internet filtering tool which allows parents to manage their children's Internet access, block access to Internet sites they deem inappropriate. The other filtering tools which like Cyber Patrol, NCA Patrol, Argus, Netfilter are oriented only URL filtering or keyword detection methods. Thease methods are used on limited fields application. But our approach is focus on image color space model. First we convert RGB color space to HLS(Hue Luminance Saturation). Next, this HLS histogram learned by our classification method tools which include cohesion factor, naive baysian, N-nearest neighbor. Then we use voting for result from various classification methods. Using 2,000 picture, we prove that 2-layer voting result have better accuracy than other methods.