• Proceedings of the Optical Society of Korea Conference
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• 2003.07a
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• pp.60-61
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• 2003

A new approach to reduce the computation time of genetic algorithm (GA) for making binary phase holograms is described. Synthesized holograms having diffraction efficiency of 75.8% and uniformity of 5.8% are proven in computer simulation and experimentally demonstrated. Recently, computer-generated holograms (CGHs) having high diffraction efficiency and flexibility of design have been widely developed in many applications such as optical information processing, optical computing, optical interconnection, etc. Among proposed optimization methods, GA has become popular due to its capability of reaching nearly global. However, there exits a drawback to consider when we use the genetic algorithm. It is the large amount of computation time to construct desired holograms. One of the major reasons that the GA' s operation may be time intensive results from the expense of computing the cost function that must Fourier transform the parameters encoded on the hologram into the fitness value. In trying to remedy this drawback, Artificial Neural Network (ANN) has been put forward, allowing CGHs to be created easily and quickly (1), but the quality of reconstructed images is not high enough to use in applications of high preciseness. For that, we are in attempt to find a new approach of combiningthe good properties and performance of both the GA and ANN to make CGHs of high diffraction efficiency in a short time. The optimization of CGH using the genetic algorithm is merely a process of iteration, including selection, crossover, and mutation operators [2]. It is worth noting that the evaluation of the cost function with the aim of selecting better holograms plays an important role in the implementation of the GA. However, this evaluation process wastes much time for Fourier transforming the encoded parameters on the hologram into the value to be solved. Depending on the speed of computer, this process can even last up to ten minutes. It will be more effective if instead of merely generating random holograms in the initial process, a set of approximately desired holograms is employed. By doing so, the initial population will contain less trial holograms equivalent to the reduction of the computation time of GA's. Accordingly, a hybrid algorithm that utilizes a trained neural network to initiate the GA's procedure is proposed. Consequently, the initial population contains less random holograms and is compensated by approximately desired holograms. Figure 1 is the flowchart of the hybrid algorithm in comparison with the classical GA. The procedure of synthesizing a hologram on computer is divided into two steps. First the simulation of holograms based on ANN method [1] to acquire approximately desired holograms is carried. With a teaching data set of 9 characters obtained from the classical GA, the number of layer is 3, the number of hidden node is 100, learning rate is 0.3, and momentum is 0.5, the artificial neural network trained enables us to attain the approximately desired holograms, which are fairly good agreement with what we suggested in the theory. The second step, effect of several parameters on the operation of the hybrid algorithm is investigated. In principle, the operation of the hybrid algorithm and GA are the same except the modification of the initial step. Hence, the verified results in Ref [2] of the parameters such as the probability of crossover and mutation, the tournament size, and the crossover block size are remained unchanged, beside of the reduced population size. The reconstructed image of 76.4% diffraction efficiency and 5.4% uniformity is achieved when the population size is 30, the iteration number is 2000, the probability of crossover is 0.75, and the probability of mutation is 0.001. A comparison between the hybrid algorithm and GA in term of diffraction efficiency and computation time is also evaluated as shown in Fig. 2. With a 66.7% reduction in computation time and a 2% increase in diffraction efficiency compared to the GA method, the hybrid algorithm demonstrates its efficient performance. In the optical experiment, the phase holograms were displayed on a programmable phase modulator (model XGA). Figures 3 are pictures of diffracted patterns of the letter "0" from the holograms generated using the hybrid algorithm. Diffraction efficiency of 75.8% and uniformity of 5.8% are measured. We see that the simulation and experiment results are fairly good agreement with each other. In this paper, Genetic Algorithm and Neural Network have been successfully combined in designing CGHs. This method gives a significant reduction in computation time compared to the GA method while still allowing holograms of high diffraction efficiency and uniformity to be achieved. This work was supported by No.mOl-2001-000-00324-0 (2002)) from the Korea Science & Engineering Foundation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.8
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• pp.29-37
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• 2019

Textile quality management targets the physical properties of fabrics and the subjective discriminations of color and fitting. Color is the most representative quality factor that consumers can use to evaluate quality levels without any instruments. For this reason, quantification using a color discrimination device has been used for statistical quality management in the textile industry. However, small and medium-sized domestic textile manufacturers use only visual inspection for color discrimination. As a result, color discrimination is different based on the inspectors' individual tendencies and work procedures. In this research, we want to develop a textile industry-friendly quality management method, evaluating the possibility of rapid color discrimination using a digital imaging device, which is one of the office-automation instruments. The results show that an imaging process-based color discrimination method is highly correlated with conventional color discrimination instruments ($R^2=0.969$), and is also applicable to field discrimination of the manufacturing process, or for different lots. Moreover, it is possible to recognize quality management factors by analyzing color components, ${\Delta}L$, ${\Delta}a$, ${\Delta}b$. We hope that our rapid discrimination method will be a substitute technique for conventional color discrimination instruments via elaboration and optimization.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.1-23
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• 2019

Big data refers to data that is difficult to store, manage, and analyze by existing software. As the lifestyle changes of consumers increase the size and types of needs that consumers desire, they are investing a lot of time and money to understand the needs of consumers. Companies in various industries utilize Big Data to improve their products and services to meet their needs, analyze unstructured data, and respond to real-time responses to products and services. The financial industry operates a decision support system that uses financial data to develop financial products and manage customer risks. The use of big data by financial institutions can effectively create added value of the value chain, and it is possible to develop a more advanced customer relationship management strategy. Financial institutions can utilize the purchase data and unstructured data generated by the credit card, and it becomes possible to confirm and satisfy the customer's desire. CRM has a granular process that can be measured in real time as it grows with information knowledge systems. With the development of information service and CRM, the platform has change and it has become possible to meet consumer needs in various environments. Recently, as the needs of consumers have diversified, more companies are providing systematic marketing services using data mining and advanced CRM (Customer Relationship Management) techniques. KB Kookmin Card, which started as a credit card business in 1980, introduced early stabilization of processes and computer systems, and actively participated in introducing new technologies and systems. In 2011, the bank and credit card companies separated, leading the 'Hye-dam Card' and 'One Card' markets, which were deviated from the existing concept. In 2017, the total use of domestic credit cards and check cards grew by 5.6% year-on-year to 886 trillion won. In 2018, we received a long-term rating of AA + as a result of our credit card evaluation. We confirmed that our credit rating was at the top of the list through effective marketing strategies and services. At present, Kookmin Card emphasizes strategies to meet the individual needs of customers and to maximize the lifetime value of consumers by utilizing payment data of customers. KB Kookmin Card combines internal and external big data and conducts marketing in real time or builds a system for monitoring. KB Kookmin Card has built a marketing system that detects realtime behavior using big data such as visiting the homepage and purchasing history by using the customer card information. It is designed to enable customers to capture action events in real time and execute marketing by utilizing the stores, locations, amounts, usage pattern, etc. of the card transactions. We have created more than 280 different scenarios based on the customer's life cycle and are conducting marketing plans to accommodate various customer groups in real time. We operate a smart offering system, which is a highly efficient marketing management system that detects customers' card usage, customer behavior, and location information in real time, and provides further refinement services by combining with various apps. This study aims to identify the traditional CRM to the current CRM strategy through the process of changing the CRM strategy. Finally, I will confirm the current CRM strategy through KB Kookmin card's big data utilization strategy and marketing activities and propose a marketing plan for KB Kookmin card's future CRM strategy. KB Kookmin Card should invest in securing ICT technology and human resources, which are becoming more sophisticated for the success and continuous growth of smart offering system. It is necessary to establish a strategy for securing profit from a long-term perspective and systematically proceed. Especially, in the current situation where privacy violation and personal information leakage issues are being addressed, efforts should be made to induce customers' recognition of marketing using customer information and to form corporate image emphasizing security.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.143-174
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• 2023

With the development of deep learning technologies, Artificial Intelligence powered Optical Character Recognition (AI-OCR) has evolved to read multiple languages from various forms of images accurately. For the financial industry, where a large number of diverse documents are processed through manpower, the potential for using AI-OCR is great. In this study, we present a configuration and a design of an AI-OCR modality for use in the financial industry and discuss the platform construction with application cases. Since the use of financial domain data is prohibited under the Personal Information Protection Act, we developed a deep learning-based data generation approach and used it to train the AI-OCR models. The AI-OCR models are trained for image preprocessing, text recognition, and language processing and are configured as a microservice architected platform to process a broad variety of documents. We have demonstrated the AI-OCR platform by applying it to financial domain tasks of document sorting, document verification, and typing assistance The demonstrations confirm the increasing work efficiency and conveniences.

• (The) Research of the performance art and culture
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• no.41
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• pp.219-255
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• 2020

This article was triggered by Victor H. Mair's book 'Painting and performance'. The book explained that Buddhist paintings are common in the area where Buddhism was spread, and there are also performances using them. And although it has nothing to do with Buddhism, it has been shown that this form of performance can be global. However, the problem was not 'Korea'. It was because there was no record or transmission of the corresponding performance soon. In this situation, the landing method of Samcheok stable temple was announced in 2018. On the one hand, the academic community is very pleased, but on the other hand, it is troubled. The worries are summed up as 'synchronic and diachronic universality'. Is the landing method inherited from the Samcheok stable temple a unique type of temple? Otherwise, it is a question of whether it has been passed down or is it universal at the national level. However, prior to this essential question, we do not yet know the full picture of the stable landing method. So this article was prepared to show the overall outline of the stable landing method. There is a 'picture' in common throughout the landing method, and understanding how to operate it in various ways is the first step in understanding the landing method. There are five repertoires (which are called main halls) that are considered important, and more than that. What these repertoires have in common is the narrative structure of a Buddhist character. In this narrative, the most important thing is the revised figure, and it was the earthly method to inform the contents of the revised figure in various ways. In the case of Byeonsangdo, which serves as a clue to the narrative, there was a problem that could not be seen in the evening without light, which required special design. It is the way of shadow play and Yeongdeung. In other words, there are three types of performances in the landing method. The first is the method of using reparation, and the second is the method of using shadow. The third is the way of eternity. This method is not a selection based on the contents of the repertoire, but a selection based on the performance environment. If there is light and you can see the picture, use reparation. However, in the evening, it was impossible to see it dark (when there was no electricity in the past). The use of the visual method as a tool in this method is to confirm the transition to a visual culture that is a step further from the level of culture. Moreover, unlike the epic narrative, the power of the implied image provided an opportunity for viewers to experience the mystery of Buddhism through emotional stimulation.

• Journal of the Korea Knowledge Information Technology Society
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• v.13 no.1
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• pp.11-23
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• 2018

This paper empirically investigates the factors that influence the consumer choice of an app market based on the rational choice theory. The app market is the only channel where a consumer can buy smartphone apps, which give various functional convenience and are considered to be a major contributor to the proliferation of smartphones. Analyses of 281 questionnaires show that usability and structural guarantees as benefit factors significantly influence the app market choice. From the cost perspectives, both monetary and non-monetary conversion costs are found to significantly influence the app market choice. On the other hand, customer trust, information quality, and market image were found to have no significant effect on app market selection. In particular, Korean app market platform providers (KT, LG U +) seem to be superior in terms of structural guarantees, such as customer center operation and damage compensation regulations, compared to overseas app market platform operators (Google). However, in the case of the Google App Market, it is pre-installed on all Android phones, so it is not inconvenient to install additional apps to use other app market. This is disadvantageous to domestic app market platform operators, and it is necessary to establish a policy solution point. In terms of operator costs, both monetary and non-monetary conversion costs have a significant impact on app market choice. In particular, non-monetary conversion costs have a negative impact on Korean app market platform operators. It can be explained that the service expectation level of the domestic app market is low and it is recognized that the time cost factor such as membership is large for new users to use. It seems to be necessary to improve the domestic app market business. Meanwhile, extant research on smartphone apps focuses on the purchase of apps themselves, but not on the selection of the app market itself. In order to fill in this gap, this study focuses on the determinants of app market selection, including the characteristics of an app market and the switching costs.

• Proceedings of the Korean Society of Crop Science Conference
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• 2023.04a
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• pp.7-7
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• 2023

Currently, the main technologies of various fourth industries are big data, the Internet of Things, artificial intelligence, blockchain, mixed reality (MR), and drones. In particular, "digital twin," which has recently become a global technological trend, is a concept of a virtual model that is expressed equally in physical objects and computers. By creating and simulating a Digital twin of software-virtualized assets instead of real physical assets, accurate information about the characteristics of real farming (current state, agricultural productivity, agricultural work scenarios, etc.) can be obtained. This study aims to streamline agricultural work through automatic water management, remote growth forecasting, drone control, and pest forecasting through the operation of an integrated control system by constructing digital twin data on the main production area of the nojinot industry and designing and building a smart farm complex. In addition, it aims to distribute digital environmental control agriculture in Korea that can reduce labor and improve crop productivity by minimizing environmental load through the use of appropriate amounts of fertilizers and pesticides through big data analysis. These open-field agricultural technologies can reduce labor through digital farming and cultivation management, optimize water use and prevent soil pollution in preparation for climate change, and quantitative growth management of open-field crops by securing digital data for the national cultivation environment. It is also a way to directly implement carbon-neutral RED++ activities by improving agricultural productivity. The analysis and prediction of growth status through the acquisition of the acquired high-precision and high-definition image-based crop growth data are very effective in digital farming work management. The Southern Crop Department of the National Institute of Food Science conducted research and development on various types of open-field agricultural smart farms such as underground point and underground drainage. In particular, from this year, commercialization is underway in earnest through the establishment of smart farm facilities and technology distribution for agricultural technology complexes across the country. In this study, we would like to describe the case of establishing the agricultural field that combines digital twin technology and open-field agricultural smart farm technology and future utilization plans.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.75-95
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• 2020

With the growth of social networks, various forms of SNS have emerged. Based on various motivations for use such as interactivity, information exchange, and entertainment, SNS users are also on the fast-growing trend. Facebook is the main SNS channel, and companies have started using Facebook pages as a public relations channel. To this end, in the early stages of operation, companies began to secure a number of fans, and as a result, the number of corporate Facebook fans has recently increased to as many as millions. from a corporate perspective, Facebook is attracting attention because it makes it easier for you to meet the customers you want. Facebook provides an efficient advertising platform based on the numerous data it has. Advertising targeting can be conducted using their demographic characteristics, behavior, or contact information. It is optimized for advertisements that can expose information to a desired target, so that results can be obtained more effectively. it rethink and communicate corporate brand image to customers through contents. The study was conducted through Facebook advertising data, and could be of great help to business people working in the online advertising industry. For this reason, the independent variables used in the research were selected based on the characteristics of the content that the actual business is concerned with. Recently, the company's Facebook page operation goal is to go beyond securing the number of fan pages, branding to promote its brand, and further aiming to communicate with major customers. the main figures for this assessment are Facebook's 'OK', 'Attachment', 'Share', and 'Number of Click' which are the dependent variables of this study. in order to measure the outcome of the target, the consumer's response is set as a key measurable key performance indicator (KPI), and a strategy is set and executed to achieve this. Here, KPI uses Facebook's ad numbers 'reach', 'exposure', 'like', 'share', 'comment', 'clicks', and 'CPC' depending on the situation. in order to achieve the corresponding figures, the consideration of content production must be prior, and in this study, the independent variables were organized by dividing into three considerations for content production into three. The effects of content material, content structure, and message styles on Facebook's user behavior were analyzed using regression analysis. Content materials are related to the content's difficulty, company relevance, and daily involvement. According to existing research, it was very important how the content would attract users' interest. Content could be divided into informative content and interesting content. Informational content is content related to the brand, and information exchange with users is important. Interesting content is defined as posts that are not related to brands related to interesting movies or anecdotes. Based on this, this study started with the assumption that the difficulty, company relevance, and daily involvement have an effect on the dependent variable. In addition, previous studies have found that content types affect Facebook user activity. I think it depends on the combination of photos and text used in the content. Based on this study, the actual photos were used and the hashtag and independent variables were also examined. Finally, we focused on the advertising message. In the previous studies, the effect of advertising messages on users was different depending on whether they were narrative or non-narrative, and furthermore, the influence on message intimacy was different. In this study, we conducted research on the behavior that Facebook users' behavior would be different depending on the language and formality. For dependent variables, 'OK' and 'Full Click Count' are set by every user's action on the content. In this study, we defined each independent variable in the existing study literature and analyzed the effect on the dependent variable, and found that 'good' factors such as 'self association', 'actual use', and 'hidden' are important. Could. Material difficulties', 'actual participation' and 'large scale * difficulties'. In addition, variables such as 'Self Connect', 'Actual Engagement' and 'Sexual Sexual Attention' have been shown to have a significant impact on 'Full Click'. It is expected that through research results, it is possible to contribute to the operation and production strategy of company Facebook operators and content creators by presenting a content strategy optimized for the purpose of the content. In this study, we defined each independent variable in the existing research literature and analyzed its effect on the dependent variable, and we could see that factors on 'good' were significant such as 'self-association', 'reality use', 'concernal material difficulty', 'real-life involvement' and 'massive*difficulty'. In addition, variables such as 'self-connection', 'real-life involvement' and 'formative*attention' were shown to have significant effects for 'full-click'. Through the research results, it is expected that by presenting an optimized content strategy for content purposes, it can contribute to the operation and production strategy of corporate Facebook operators and content producers.

• The Korean Journal of Nuclear Medicine Technology
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• v.12 no.3
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• pp.208-213
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• 2008

Purpose: Generally a whole body bone scan has been known as one of the most frequently executed exams in the nuclear medicine fields. Asan medical center, usually use various gamma camera systems - manufactured by PHILIPS (PRECEDENCE, BRIGHTVIEW), SIEMENS (ECAM, ECAM signature, ECAM plus, SYMBIA T2), GE (INFINIA) - to execute whole body scan. But, as we know, each camera's sensitivity is not same so it is hard to consistent diagnosis of patients. So our purpose is when we execute whole body bone scans, we exclude uncontrollable factors and try to correct controllable factors such as inherent sensitivity of gamma camera. In this study, we're going to measure each gamma camera's sensitivity and study about reasonable correction factors of whole body bone scan to follow up patient's condition using different gamma cameras. Materials and Methods: We used the $^{99m}Tc$ flood phantom, it recommend by IAEA recommendation based on general counts rate of a whole body scan and measured counts rates by the use of various gamma cameras - PRECEDENCE, BRIGHTVIEW, ECAM, ECAM signature, ECAM plus, IFINIA - in Asan medical center nuclear medicine department. For measuring sensitivity, all gamma camera equipped LEHR collimator (Low Energy High Resolution multi parallel Collimator) and the $^{99m}Tc$ gamma spectrum was adjusted around 15% window level, the photo peak was set to 140-kev and acquirded for 60 sec and 120 sec in all gamma cameras. In order to verify whether can apply calculated correction factors to whole body bone scan or not, we actually conducted the whole body bone scan to 27 patients and we compared it analyzed that results. Results: After experimenting using $^{99m}Tc$ flood phantom, sensitivity of ECAM plus was highest and other sensitivity order of all gamma camera is ECAM signature, SYMBIA T2, ECAM, BRIGHTVIEW, IFINIA, PRECEDENCE. And yield sensitivity correction factor show each gamma camera's relative sensitivity ratio by yielded based on ECAM's sensitivity. (ECAM plus 1.07, ECAM signature 1.05, SYMBIA T2 1.03, ECAM 1.00, BRIGHTVIEW 0.90, INFINIA 0.83, PRECEDENCE 0.72) When analyzing the correction factor yielded by $^{99m}Tc$ experiment and another correction factor yielded by whole body bone scan, it shows statistically insignificant value (p<0.05) in whole body bone scan diagnosis. Conclusion: In diagnosing the bone metastasis of patients undergoing cancer, whole body bone scan has been conducted as follow up tests due to its good points (high sensitivity, non invasive, easily conducted). But as a follow up study, it's hard to perform whole body bone scan continuously using same gamma camera. If we use same gamma camera to patients, we have to consider effectiveness of equipment's change by time elapsed. So we expect that applying sensitivity correction factor to patients who tested whole body bone scan regularly will add consistence in diagnosis of patients.

• Radiation Oncology Journal
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• v.26 no.2
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• pp.118-125
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• 2008

Purpose: On-line image guided radiation therapy(on-line IGRT) and(kV X-ray images or cone beam CT images) were obtained by an on-board imager(OBI) and cone beam CT(CBCT), respectively. The images were then compared with simulated images to evaluate the patient's setup and correct for deviations. The setup deviations between the simulated images(kV or CBCT images), were computed from 2D/2D match or 3D/3D match programs, respectively. We then investigated the correctness of the calculated deviations. Materials and Methods: After the simulation and treatment planning for the RANDO phantom, the phantom was positioned on the treatment table. The phantom setup process was performed with side wall lasers which standardized treatment setup of the phantom with the simulated images, after the establishment of tolerance limits for laser line thickness. After a known translation or rotation angle was applied to the phantom, the kV X-ray images and CBCT images were obtained. Next, 2D/2D match and 3D/3D match with simulation CT images were taken. Lastly, the results were analyzed for accuracy of positional correction. Results: In the case of the 2D/2D match using kV X-ray and simulation images, a setup correction within $0.06^{\circ}$ for rotation only, 1.8 mm for translation only, and 2.1 mm and $0.3^{\circ}$ for both rotation and translation, respectively, was possible. As for the 3D/3D match using CBCT images, a correction within $0.03^{\circ}$ for rotation only, 0.16 mm for translation only, and 1.5 mm for translation and $0.0^{\circ}$ for rotation, respectively, was possible. Conclusion: The use of OBI or CBCT for the on-line IGRT provides the ability to exactly reproduce the simulated images in the setup of a patient in the treatment room. The fast detection and correction of a patient's positional error is possible in two dimensions via kV X-ray images from OBI and in three dimensions via CBCT with a higher accuracy. Consequently, the on-line IGRT represents a promising and reliable treatment procedure.