• Journal of the Korean Society of Industry Convergence
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• v.24 no.6_2
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• pp.729-735
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• 2021

Recently Artificial Intelligence(AI) has been developed and used in various fields. Especially AI recognition technology can perceive and distinguish images so it should plays a significant role in quality inspection process. For stability of autonomous driving technology, semiconductors inside automobiles must be protected from external electromagnetic wave(EM wave). As a shield film, a thin polymeric material with hole shaped micro-patterns created by a laser processing could be used for the protection. The shielding efficiency of the film can be increased by the hole structure with appropriate pitch and size. However, since the sensitivity of micro-machining for some parameters, the shape of every single hole can not be same, even it is possible to make defective patterns during process. And it is absolutely time consuming way to inspect all patterns by just using optical microscope. In this paper, we introduce a AI inspection system which is based on web site AI tool. And we evaluate the usefulness of AI model by calculate Area Under ROC curve(Receiver Operating Characteristics). The AI system can classify the micro-patterns into normal or abnormal ones displaying the text of the result on real-time images and save them as image files respectively. Furthermore, pressing the running button, the Hardware of robot arm with two Arduino motors move the film on the optical microscopy stage in order for raster scanning. So this AI system can inspect the entire micro-patterns of a film automatically. If our system could collect much more identified data, it is believed that this system should be a more precise and accurate process for the efficiency of the AI inspection. Also this one could be applied to image-based inspection process of other products.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.6
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• pp.975-987
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• 2023

With the advancement of Artificial Intelligence (AI) technologies, the provision of data-driven AI services that enable automation and intelligence is increasing across industries, raising concerns about the AI security risks that may arise from the use of AI. Accordingly, Foreign countries recognize the need and importance of AI regulation and are focusing on developing related policies and regulations. This movement is also happening in Korea, and AI regulations have not been specified, so it is necessary to compare and analyze existing policy proposals or guidelines to derive common factors and identify complementary points, and discuss the direction of domestic AI regulation. In this paper, we investigate AI security risks that may arise in the AI life cycle and derive six points to be considered in establishing domestic AI regulations through analysis of each risk. Based on this, we analyze AI policy proposals and recommendations in Korea and validate additional issues. In addition, based on a review of the main content of AI laws in the US and EU and the analysis of this paper, we propose measures to improve domestic guidelines and policies in the field of AI.

• The Korean Journal of Nuclear Medicine Technology
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• v.13 no.3
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• pp.3-9
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• 2009

Purpose: It is well-known that stress-induced stunning and reversible perfusion defect have impact on ejection fraction (EF) when performing myocardial perfusion SPECT. Due to these reasons, gated SPECT is recommended at stress and rest studies. And there was many experiments to analyze between Stress and Rest EF by using $^{99m}Tc$-MIBI. The aim of this study is to analyze between stress EF and rest EF at myocardial perfusion SPECT by using $^{201}Tl$ and define possible predictors of EF variability. Materials and Methods: From 2008 June to 2009 February, we analyzed 144 patients undergoing $^{201}Tl$ gated myocardial perfusion SPECT in ASAN medical center. To analyze the data, we use QGS (Quantitative gated SPECT) software, and derived End-systolic volume (ESV), End-diastolic volume (EDV), EF from the result. In this study, we comparatively analyzed stress/rest EF correlation based on stress/rest EF, EDV, ESV and reversibility of myocardial perfusion defect by using paired t-test, Bland-Altman analysis. Results: Mached pairs of stress EF and rest EF demonstrated excellent correlation (r=0.92) with no statistically significant difference (p=0.11). Bland-Altman analysis demonstrated a mean ${\Delta}EF$ was 0.52% (95% confidential interval[CI], -1.17~0.12%). No statistically significant difference between a mean ${\Delta}EF$ and hypothetic mean of 0 (${\Delta}EF$=0) (p=0.10). In the correlation of ${\Delta}EF$ according to stress/rest EDV and ESV, except rest ESV of <28mL (p<0.05), there was no statistically significant difference. In the correlation of ${\Delta}EF$ according to reversibility of perfusion defect, patients with reversible perfusion defect has statistically significant difference of ${\Delta}EF$ (p<0.05). ${\Delta}EF$ of stress/rest EF showed no statistically significant difference except 55% of rest EF (p<0.05). Conclusion: Like studies with $^{99m}Tc$-MIBI, there was generally no statistically significant difference between stress and rest EF in this study results. However a stress EF of <55%, a rest ESV of <28mL and patients with reversible perfusion defect showed statistically significant difference in ${\Delta}EF$. If performing $^{201}T$ myocardial perfusion SPECT to patients with abnormal cardiac function or reversible perfusion defect, consider this study results and apply it. We expect this study results could be useful predictors of ${\Delta}EF$ variability.

• Clinical and Experimental Pediatrics
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• v.49 no.10
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• pp.1056-1060
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• 2006

Purpose : As hearing ability affects language and cognitive development, early detection and intervention of congenital hearing defects is very important. We analyzed the result of newborn hearing screening using automated auditory brainstem response and estimated the incidence of congenital hearing defects in newborn infants in Korea. Methods : Hearing screening tests were done on 7,218 newborn infants who were delivered at Cheil General Hospital from July 1, 2004 to June 30, 2005. The first screening test was done on the second day of life with automated auditory brainstem response(AABR) using $ALGO{\bigcirc}^{(3)}$ Newborn hearing screener($Natus^{(R)}$ Medical Incorporated, San Carlos, USA) with 35 dB sound level. The newborn infants who did not pass the initial screening test took the second screening AABR test before discharge from the nursery. Infants who did not pass these screenings at the nursery were followed up at the Department of Otorhinolaryngology, Samsung Seoul Hospital. Results : Total 7,218 infants(83.3 percent of total 8,664 live births of the Cheil General Hospital) were screened in the nursery, and 55 of them failed to pass the newborn screening. Among 55 infants who were referred, six were lost during follow-up, and 14 were confirmed as hearing impaired. Six of them(42.8 percent) do not have any risk factors for hearing impairment. We can estimate that the incidence of hearing defects is about 1.9-2.8 per 1,000 live births. Conclusion : Automated auditory brainstem response is an effective tool to screen the hearing of newborn infants. Congenital hearing loss is more frequent than metabolic diseases on which screening tests are available in the newborn period. About 40 percent of infants who have hearing defects do not have any risk factors for hearing impairment. Therefore, universal newborn hearing screening must be recommended to all neonates.

• Journal of Korean Society of Archives and Records Management
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• v.3 no.1
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• pp.69-92
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• 2003

Registration and description of records are important elements of processing which provide with the background information of production of records and business-related information. They also enable to search and use the records. In this paper, I examined the Korean registration and description system defined in the Public Records Management Act which directs the records creating agency to register records in creating offices and directs the "professional archives" to make "basic registrations" and "detailed registrations" of the records. In the analysis and comparison of two different registration and description systems with the known international standards of records and archives management, such as ISO15489 and ISAD(G), I intended to evaluate the Korean records and archives management system and suggested recommendations for the renovation of the Korean recordskeeping system. Despite we have unique office business procedures and the culture of officialdom, and despite we have developed our system based on the established business procedures and office culture, it would be preferable to adopt or follow the international standards and established best practices. After the comparative analysis, I recommended some innovations in the filed of registration and description. For instance, in the basic registration. we would better to install an item of "simple contents summary." We may also need the multiple-level description. The fonds level description and the series level description should be introduced to our archival automated management system. We need to establish a Korean standard of description adopting the rules of the ISAD(G) and ISAAR(CPF). Essential requirements for electronic records management, such as contextual and structural information, should be incorporated in the new standard. Documentation of records disposition also should be reinforced to guarantee the authenticity of records and to ensure control of the records. To implement the recommendations for the standard, we need to amend the Public Records Management Act and its Regulations and Rules. Also it is imperative to redesign the GARS integrated archival automated management system.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.109-125
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• 2020

The Ministry of National Defense is pushing for the Defense Acquisition Program to build strong defense capabilities, and it spends more than 10 trillion won annually on defense improvement. As the Defense Acquisition Program is directly related to the security of the nation as well as the lives and property of the people, it must be carried out very transparently and efficiently by experts. However, the excessive diversification of laws and regulations related to the Defense Acquisition Program has made it challenging for many working-level officials to carry out the Defense Acquisition Program smoothly. It is even known that many people realize that there are related regulations that they were unaware of until they push ahead with their work. In addition, the statutory statements related to the Defense Acquisition Program have the tendency to cause serious issues even if only a single expression is wrong within the sentence. Despite this, efforts to establish a sentence comparison system to correct this issue in real time have been minimal. Therefore, this paper tries to propose a "Comparison System between the Statement of Military Reports and Related Laws" implementation plan that uses the Siamese Network-based artificial neural network, a model in the field of natural language processing (NLP), to observe the similarity between sentences that are likely to appear in the Defense Acquisition Program related documents and those from related statutory provisions to determine and classify the risk of illegality and to make users aware of the consequences. Various artificial neural network models (Bi-LSTM, Self-Attention, D_Bi-LSTM) were studied using 3,442 pairs of "Original Sentence"(described in actual statutes) and "Edited Sentence"(edited sentences derived from "Original Sentence"). Among many Defense Acquisition Program related statutes, DEFENSE ACQUISITION PROGRAM ACT, ENFORCEMENT RULE OF THE DEFENSE ACQUISITION PROGRAM ACT, and ENFORCEMENT DECREE OF THE DEFENSE ACQUISITION PROGRAM ACT were selected. Furthermore, "Original Sentence" has the 83 provisions that actually appear in the Act. "Original Sentence" has the main 83 clauses most accessible to working-level officials in their work. "Edited Sentence" is comprised of 30 to 50 similar sentences that are likely to appear modified in the county report for each clause("Original Sentence"). During the creation of the edited sentences, the original sentences were modified using 12 certain rules, and these sentences were produced in proportion to the number of such rules, as it was the case for the original sentences. After conducting 1 : 1 sentence similarity performance evaluation experiments, it was possible to classify each "Edited Sentence" as legal or illegal with considerable accuracy. In addition, the "Edited Sentence" dataset used to train the neural network models contains a variety of actual statutory statements("Original Sentence"), which are characterized by the 12 rules. On the other hand, the models are not able to effectively classify other sentences, which appear in actual military reports, when only the "Original Sentence" and "Edited Sentence" dataset have been fed to them. The dataset is not ample enough for the model to recognize other incoming new sentences. Hence, the performance of the model was reassessed by writing an additional 120 new sentences that have better resemblance to those in the actual military report and still have association with the original sentences. Thereafter, we were able to check that the models' performances surpassed a certain level even when they were trained merely with "Original Sentence" and "Edited Sentence" data. If sufficient model learning is achieved through the improvement and expansion of the full set of learning data with the addition of the actual report appearance sentences, the models will be able to better classify other sentences coming from military reports as legal or illegal. Based on the experimental results, this study confirms the possibility and value of building "Real-Time Automated Comparison System Between Military Documents and Related Laws". The research conducted in this experiment can verify which specific clause, of several that appear in related law clause is most similar to the sentence that appears in the Defense Acquisition Program-related military reports. This helps determine whether the contents in the military report sentences are at the risk of illegality when they are compared with those in the law clauses.