• Journal of Digital Contents Society
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• v.19 no.1
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• pp.149-155
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• 2018

In this paper we propose an algorithm for generating role-performer bipartite matrix for analyzing BPM-based human resource affiliations. Firstly, the proposed algorithm conducts the extraction of role-performer affiliation relationships from ICN(Infromation Contorl Net) based business process models. Then, the role-performer bipartite matrix is constructed in the final step of the algorithm. Conclusively, the bipartite matrix generated through the proposed algorithm ought to be used as the fundamental data structure for discovering the role-performer affiliation networking knowledge, and by using a variety of social network analysis techniques it enables us to acquire valuable analysis results about BPM-based human resource affiliations.

• Proceedings of the Korean Printing Society Conference
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• 2002.05a
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• pp.10-18
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• 2002

On the process of cross-media color reproduction, a key feature is the use of gamut mapping techniques to adjust the different color gamuts between displays and printers. Even though a number of GMAs have been published, but there are no method satisfactory enough for more exect color reproduction. In this paper, the gamut mapping methods of nearest point clipping(NPC), centroid clipping (SLIN), straight clipping and cusp clipping(CUSP) were tested and analyzed with color difference, and a new gamut mapping algorithm based on variable anchor point method was proposed.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.1
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• pp.23-31
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• 2023

Research and interest in sustainable printing are increasing in the packaging printing industry. Currently, predicting the amount of ink required for each work is based on the experience and intuition of field workers. Suppose the amount of ink produced is more than necessary. In this case, the rest of the ink cannot be reused and is discarded, adversely affecting the company's productivity and environment. Nowadays, machine learning models can be used to figure out this problem. This study compares the ink usage prediction machine learning models. A simple linear regression model, Multiple Regression Analysis, cannot reflect the nonlinear relationship between the variables required for packaging printing, so there is a limit to accurately predicting the amount of ink needed. This study has established various prediction models which are based on CART (Classification and Regression Tree), such as Decision Tree, Random Forest, Gradient Boosting Machine, and XGBoost. The accuracy of the models is determined by the K-fold cross-validation. Error metrics such as root mean squared error, mean absolute error, and R-squared are employed to evaluate estimation models' correctness. Among these models, XGBoost model has the highest prediction accuracy and can reduce 2134 (g) of wasted ink for each work. Thus, this study motivates machine learning's potential to help advance productivity and protect the environment.

• Journal of the Korean Society of Clothing and Textiles
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• v.41 no.5
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• pp.825-839
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• 2017

Generative Art (also called as the art of the algorithm) creates unexpected results, moving autonomously according to rules or algorithms. The evolution of digital media in art, which tries to seek novelty, increases the possibility of new artistic fields; subsequently, this study establishes the basis for new design approaches by analyzing visual cases of Generative Art that have emerged since the 20th century and characteristics expressed on fashion. For the methodology, the study analyzes fashion designs that have emerged since 2000, based on theoretical research that includes literature and research papers relating to Generative Art. According to the study, expression characteristics shown in fashion, based on visual properties of Generative Art, are as follows. First, abstract randomness is expressed with unexpected coincidental forms using movements of a creator and properties of materials as variables in accordance to rules or algorithms. Second, endlessly repeated pattern imitation expresses an emergent shape by endless repetition created by a modular system using rules or 3D printing using a computer algorithm. Third, the systematic variability expresses constantly changing images with a combination of system and digital media by a wearing method. It is expected that design by algorithm becomes a significant method in producing other creative ideas and expressions in modern fashion.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.8
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• pp.793-798
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• 2009

In this paper, the simulation and optimization of SRH (Surface Relief Hologram) masks for printing LCD gate patterns using TIR (Total Internal Reflection) holographic lithography was investigated. A simulation and optimization algorithm based on SDTA (Scalar Diffraction Theory Analysis) method was developed. The accuracy of the algorithm was compared to that of the RCWA (Rigorous Coupled Wave Analysis) method for estimating the Fresnel diffraction pattern of Cr amplitude masks for the given system geometry. In addition, the results from the optimization algorithm were validated experimentally. It was found that one to the most important conditions for the fabrication of SRH masks is to avoid nonlinear shape distortions of the resulting grating. These distortions can be avoided by designing SRH masks with recorded gratings having small aspect ratios of width versus depth. The optimum gap size between the Cr and SRH masks was found using the optimization algorithm. A printed LCD gate pattern with a minimum line width of $1.5{\mu}m$ exposed using the optimized SRH mask was experimentally demonstrated.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.1
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• pp.55-64
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• 2013

Due to the popularization of digital high-performance capturing equipments and the emergence of powerful image-editing softwares, it is easy for anyone to make a high-quality counterfeit money. However, the probability of detecting a counterfeit money to the general public is extremely low. In this paper, we propose a counterfeit money detection algorithm using a general purpose scanner. This algorithm determines counterfeit money based on the different features in the printing process. After the non-local mean value is used to analyze the noises from each money, we extract statistical features from these noises by calculating a gray level co-occurrence matrix. Then, these features are applied to train and test the support vector machine classifier for identifying either original or counterfeit money. In the experiment, we use total 324 images of original money and counterfeit money. Also, we compare with noise features from previous researches using wiener filter and discrete wavelet transform. The accuracy of the algorithm for identifying counterfeit money was over 94%. Also, the accuracy for identifying the printing source was over 93%. The presented algorithm performs better than previous researches.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.3
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• pp.247-257
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• 2001

New methods are proposed for printing a full resolution image on a limited output device. The proposed algorithm uses a dot-pattern database that models overlapping phenomena among neighbor printing dots. To solve the problem of dot-overlap, the gray levels of dot-pattern sets were calculated using a circular dot-overlap model and then measured by a spectrometer. Thereafter, in order to improve the visual quality of the color dithering, the contrast sensitivity function of the human visual system was used. As a result, the optimal dot-pattern can be selected from the database. Consequently, the proposed algorithm can produce high quality images while using low-cost color devices.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.10
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• pp.1447-1452
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• 2022

Seoul Special City, one of the world's top 10 cities and Metro City, has traditional urban manufacturing industries such as printing, sewing, and mechanical metals. Small business owners in these manufacturing clusters have developed in the form of mutual assistance. Due to the nature of the agglomeration site, each process is handled by an individual company. It is difficult for relatively small business owners to prepare order processing services that provide real-time logistics movement information between processes. This paper collects and analyzes existing logistics data for smooth order and delivery of small business owners in package manufacturing and special printing fields We design an artificial intelligence Fulfillment Service Platform system with CRNN, k-NN, and ID3 Decision Tree Algorithm. Through this study, it is expected that it will greatly contribute to increasing sales and improving capabilities by allowing small business owners in integrated areas to use individual orders and delivery customized services through the Cloud network.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.219-221
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• 2022

Seoul Metropolitan City, the world's top 10 cities and Metro City, has traditional urban manufacturing industries such as printing, sewing, and mechanical metals. These manufacturing industries have developed in the form of mutual assistance by forming small business clusters according to detailed industries and processes. Due to the nature of the cluster, logistics between companies for each process in the cluster are being carried out quickly, but it is difficult for relatively small small business owners to prepare order processing services for consumers of finished products. Therefore, it is urgent to introduce an integrated order fulfillment service platform for collective business owners for smooth order and delivery processing. In this paper, we collect and analyze the existing Fulfillment Service data of small business owners in the printing industry among traditional urban industries, and design an artificial intelligence Fulfillment Service Platform system applying CRNN, k-NN, and ID3 Decision Tree algorithm. Through this study, it is expected to greatly contribute to the increase in sales and capacity of small business owners by enabling the use of individual orders and customized delivery services that can be used by any small business owner in the cluster.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.3 s.180
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• pp.102-109
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• 2006

Several methods for PCB pattern inspection have been tried to detect fine detects in pad contours, but their low detection accuracy results from pattern variations originating from etching, printing and handling processes. The adaptive inspection algorithm has been newly proposed to extract minute defects based on movable segments. With gerber master images of PCB, vertex extractions of a pad boundary are made and then a lot of segments are constructed in master data. The pad boundary is composed of segment units. The proposed method moves these segments to optimal directions of a pad boundary and so adaptively matches segments to pad contours of inspected images, irrespectively of various pattern variations. It makes a fast, accurate and reliable inspection of PCB patterns. Its performances are also evaluated with several images.