• Journal of Korea Society of Industrial Information Systems
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• v.28 no.6
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• pp.29-43
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• 2023

Consumers should look at the ingredients of cosmetics or food for their health and purchase them after checking whether they contain allergy-causing ingredients. Therefore, this paper aimed to develop an artificial intelligence-based smartphone application for automatically recognizing the ingredients displayed on a curved container and delivering it to consumers in an easy-to-understand manner. The app needs to allow consumers to immediately comprehend the restricted ingredients by recognizing the ingredients' words in the cropped image. Two major issues should be solved during the development process: First, although there were flat containers for cosmetics or food, most were curved containers. Thus, it was necessary to recognize the ingredient table displayed on the curved containers. Second, since the ingredients' words were displayed on the curved surface, the transformed or line-changed words also needed to be recognized. The proposed new methods were enough to solve the above two problems. The application developed through various tests verified that there was no problem recognizing the ingredients' words contained in a cylindrical curved container.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.201-220
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• 2019

Fake news has emerged as a significant issue over the last few years, igniting discussions and research on how to solve this problem. In particular, studies on automated fact-checking and fake news detection using artificial intelligence and text analysis techniques have drawn attention. Fake news detection research entails a form of document classification; thus, document classification techniques have been widely used in this type of research. However, document summarization techniques have been inconspicuous in this field. At the same time, automatic news summarization services have become popular, and a recent study found that the use of news summarized through abstractive summarization has strengthened the predictive performance of fake news detection models. Therefore, the need to study the integration of document summarization technology in the domestic news data environment has become evident. In order to examine the effect of extractive summarization on the fake news detection model, we first summarized news articles through extractive summarization. Second, we created a summarized news-based detection model. Finally, we compared our model with the full-text-based detection model. The study found that BPN(Back Propagation Neural Network) and SVM(Support Vector Machine) did not exhibit a large difference in performance; however, for DT(Decision Tree), the full-text-based model demonstrated a somewhat better performance. In the case of LR(Logistic Regression), our model exhibited the superior performance. Nonetheless, the results did not show a statistically significant difference between our model and the full-text-based model. Therefore, when the summary is applied, at least the core information of the fake news is preserved, and the LR-based model can confirm the possibility of performance improvement. This study features an experimental application of extractive summarization in fake news detection research by employing various machine-learning algorithms. The study's limitations are, essentially, the relatively small amount of data and the lack of comparison between various summarization technologies. Therefore, an in-depth analysis that applies various analytical techniques to a larger data volume would be helpful in the future.

• Korean Journal of Clinical Laboratory Science
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• v.37 no.2
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• pp.71-77
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• 2005

We experienced the specimen that contains a hemoglobin variant known as interference from HbAS in October 2003. It was the first case of Hb variants since Samsung Medical Center began conducting glycohemoglobin College of American Pathologists surveys in 1997. The purpose of this study is to share our experience with the specimen and promote the understanding of Hb variants & derivatives. We've performed cross checks to examine HbA1c by using two pieces of equipment; the TOSHOH G7 and BIO-RAD VARIANT-T(turbo), and Automatic High Performance Liquid Chromatography(HPLC) as an analytic measurement method. HPLC provides different fractional information of hemoglobin with a two-dimensional graph as well as numeric results. We have been performing a "Systematic Checking Process". Three specimen suspicious of Hb variants & derivatives were found through this process. College of American Pathologists notified that it is important for users to be aware of the limitation of their glycohemoglobin method to avoid reporting incorrect results due to interference from hemoglobin variants or hemoglobin adducts. Therefore, laboratory findings of Hb variants & derivatives are very important. The experience of qualified technicians with professional knowledge in Hb variants is the most important aspect in finding Hb variants. Korea is homogeneous in race and is not in an area with a higher finding rate of Hb variants. While 1,024 cases of Hb variants have been found in Japan, we do not have specific data on how many cases of Hb variants have been found in Korea. Considering Hb variant cases in Japan, which is geographically close to us, it is presumed that there must be various Hb variant cases in Korea. If domestic laboratories set a systemic protocol and build a network to share our experience in Hb variants, I expect the Korean Hb variants could also be listed on the world's Hb variant list.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.6
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• pp.1195-1202
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• 2016

Recently, a lot of studies that applying the big data technology to various fields, are progressing actively. In the maritime domain, the big data is the meaningful information which makes and gathers by the navigation and communication equipment from the many ships on the ocean. Also, importance of the maritime safety is emphasized, because maritime accidents are rising with increasing of maritime traffic. To support prevention of maritime accidents, in this paper, we developed a vessel traffic display and statistic system based on AIS messages from the many vessels of maritime. Also, to verify the developed system, we conducted tests for vessel track display function and vessel traffic statistic function based on two test scenarios. Therefore, we verified the effectiveness of the developed system for vessel tracks display, abnormal navigation patterns, checking failure of AIS equipments and maritime traffic statistic analyses.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.125-140
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• 2018

As one of the processes in the manufacturing industry, quality inspection inspects the intermediate products or final products to separate the good-quality goods that meet the quality management standard and the defective goods that do not. The manual inspection of quality in a mass production system may result in low consistency and efficiency. Therefore, the quality inspection of mass-produced products involves automatic checking and classifying by the machines in many processes. Although there are many preceding studies on improving or optimizing the process using the data generated in the production process, there have been many constraints with regard to actual implementation due to the technical limitations of processing a large volume of data in real time. The recent research studies on big data have improved the data processing technology and enabled collecting, processing, and analyzing process data in real time. This paper aims to propose the process and details of applying big data for quality inspection and examine the applicability of the proposed method to the dairy industry. We review the previous studies and propose a big data analysis procedure that is applicable to the manufacturing sector. To assess the feasibility of the proposed method, we applied two methods to one of the quality inspection processes in the dairy industry: convolutional neural network and random forest. We collected, processed, and analyzed the images of caps and straws in real time, and then determined whether the products were defective or not. The result confirmed that there was a drastic increase in classification accuracy compared to the quality inspection performed in the past.

• Journal of Digital Convergence
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• v.11 no.4
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• pp.221-227
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• 2013

RFID is an automatic identification technology that can control a range of information via IC chips and radio communication. Also known as electronic tags, smart tags or electronic labels, RFID technology enables embedding the overall process from production to sales in an ultra-small IC chip and tracking down such information using radio frequencies. Currently, RFID-based application and development is in progress in such fields as health care, national defense, logistics and security. RFID structure consists of a reader that reads tag information, a tag that provides information and the database that manages data. Yet, the wireless section between the reader and the tag is vulnerable to security issues. To sort out the vulnerability, studies on security protocols have been conducted actively. However, due to difficulties in implementation, most suggestions are concerned with theorem proving, which is prone to vulnerability found by other investigators later on, ending up in many troubles with applicability in practice. To experimentally test the security of the protocol proposed here, the formal verification tool, CasperFDR was used. To sum up, the proposed protocol was found to be secure against diverse attacks. That is, the proposed protocol meets the safety standard against new types of attacks and ensures security when applied to real tags in the future.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.6
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• pp.714-719
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• 2005

The paper attempts to design and implement the system which can remotely check visitors' speech or Image by a mobile phone. This system is designed to recognize who a visitor is through the automatic calling service, not through a short message, via the mobile phone, even when the home owner is outside. In general, door locks are controlled through the home Server, but it is more effective to control door locks by using DTMF signal from a real-time point of view. The technology suggested in this paper makes it possible to communicate between the visiter and the home owner by making a phone call to tile home owner's mobile phone automatically when the visiter visits the house even if the home owner is outside, and if necessary, it allows for the home owner to control the door lock remotely. Thanks to the system, the home owner is not restricted by time or space for checking the visitor's identification and controlling the door lock. In addition, the security system is improved by changing from the existing password form to the combination of password and speaker verification lot the verification procedure required for controlling the door lock and setting the environment under consideration of any disadvantages which may occur when the mobile Phone is lost. Also, any existing problems such as reconnection to tile network for controlling tile door lock are solved by controlling the door lock in real time by use of DTMF signal while on the phone.

• Journal of the Korea Convergence Society
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• v.10 no.12
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• pp.53-61
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• 2019

The risk of project failure has increased recently as ERP systems have been transformed into Web environments and task complexity has increased. Although low-code platform development tools are being used as a way to solve this problem, limitations exist as they are centered on UI. To overcome this, back-end development tools are required that can be developed quickly and easily, not only from the front development but also from a variety of development sources produced from the ERP development process, including back-end business services. In addition, the development tools included within existing ERP products require a lot of learning time from the perspective of beginner and intermediate developers due to high entry barriers. To address these shortcomings, this paper seeks to study ways to overcome the limitations of existing development tools within the ERP by providing customized development tool functions by enhancing the usability of ERP development tools suitable for each developer's skills and roles based on the requirements required by ERP development tools, such as reducing the time required for querying, automatic binding of data for testing for service-based units, and checking of source code quality.

• Journal of the Korean Society of Radiology
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• v.11 no.4
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• pp.183-188
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• 2017

In recent years, the automatic remote control controller of the gamma ray irradiator malfunctions, and radiation workers are continuously exposed to radiation exposure accidents. In the non-destructive testing field, much time and resources are invested in establishing a radioactive source monitoring system in order to prevent potential incidents of radiation. In this study, the gamma-ray response properties of the lead monoxide-based radiation detector were estimated through monte carlo simulation as a previous study for the development of a radioactive source location monitoring system that can be applied universally to various non-destructive testing equipment. As a result of the study, the optimized thickness of the radiation detector varies according to the gamma-ray energy emitted from the radioactive source, and the optimized thickness gradually increases with increasing energy. In conclusion, the optimized thickness of the lead monoxide-based radiation detector was $200{\mu}m$ for the Ir-192, $150{\mu}m$ for the Se-75 and $300{\mu}m$ for the Co-60. Based on these results, the appropriate thickness of lead monoxide-based radiation detector considering secondary-electron equilibrium was evaluated to be $300{\mu}m$ for general application. These results can be used as a basic data for determining the appropriate thickness required in the radiation detector when developing a radiation source location monitoring system for universal application to various non-destructive testing equipment in the future.

• The Journal of Society for e-Business Studies
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• v.14 no.4
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• pp.1-17
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• 2009

E-Catalogs which describe products or services are one of the most important data for the electronic commerce. E-Catalogs are created, updated, and removed in order to keep up-to-date information in e-Catalog database. However, when the number of catalogs increases, information integrity is violated by the several reasons like catalog duplication and abnormal classification. Catalog search, duplication checking, and automatic classification are important functions to utilize e-Catalogs and keep the integrity of e-Catalog database. To implement these functions, probabilistic models that use statistics of index words extracted from e-Catalogs had been suggested and the feasibility of the methods had been shown in several papers. However, even though these functions are used together in the e-Catalog management system, there has not been enough consideration about how to share common data used for each function and how to effectively manage statistics of index words. In this paper, we suggest a method to implement these three functions by using simple SQL supported by relational database management system. In addition, we use materialized views to reduce the load for implementing an application that manages statistics of index words. This brings the efficiency of managing statistics of index words by putting database management systems optimize statistics updating. We showed that our method is feasible to implement three functions and effective to manage statistics of index words with empirical evaluation.