• Korean Chemical Engineering Research
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• v.60 no.3
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• pp.334-346
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• 2022

There is a lack of knowledge and information on the understanding and application of the Process Safety Management (PSM) system, recognized as a major cause of industrial accidents in small-and medium-sized workplaces. Hence, it is necessary to prepare a protocol to secure the practical and continuous levels of implementation for PSM and eliminate human errors through tracking management. However, insufficient research has been conducted on this. Therefore, this study investigated and analyzed the various violations in the administrative measures, based on the regulations announced by the Ministry of Employment and Labor, in approximately 200 small-and medium-sized PSM workplaces with fewer than 300 employees across in korea. This study intended to contribute to the prevention of major industrial accidents by developing a facility maintenance web program that removed human errors in small-and medium-sized workplaces. The major results are summarized as follows. First, It accessed the web via a QR code on a smart device to check the equipment's specification search function, cause of failure, and photos for the convenience of accessing the program, which made it possible to make requests for the it inspection and maintenance in real time. Second, it linked the identification of the targets to be changed, risk assessment, worker training, and pre-operation inspection with the program, which allowed the administrator to track all the procedures from start to finish. Third, it made it possible to predict the life of the equipment and verify its reliability based on the data accumulated through the registration of the pictures for improvements, repairs, time required, cost, etc. after the work was completed. It is suggested that these research results will be helpful in the practical and systematic operation of small-and medium-sized PSM workplaces. In addition, it can be utilized in a useful manner for the development and dissemination of a facility maintenance web program when establishing future smart factories in small-and medium-sized PSM workplaces under the direction of the government.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.1
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• pp.163-169
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• 2020

Recently, research on automation and unmanned operation of machines in the industrial field has been conducted with the advent of AI, Big data, and the IoT, which are the core technologies of the Fourth Industrial Revolution. The machines for these automation processes are controlled based on the data collected from the sensors attached to them, and further, the processes are managed. Conventionally, the abnormalities of sensors are periodically checked and managed. However, due to various environmental factors and situations in the industrial field, there are cases where the inspection due to the failure is not missed or failures are not detected to prevent damage due to sensor failure. In addition, even if a failure occurs, it is not immediately detected, which worsens the process loss. Therefore, in order to prevent damage caused by such a sudden sensor failure, it is necessary to identify the failure of the sensor in an embedded system in real-time and to diagnose the failure and determine the type for a quick response. In this paper, a deep neural network-based fault diagnosis system is designed and implemented using Raspberry Pi to classify typical sensor fault types such as erratic fault, hard-over fault, spike fault, and stuck fault. In order to diagnose sensor failure, the network is constructed using Google's proposed Inverted residual block structure of MobilieNetV2. The proposed scheme reduces memory usage and improves the performance of the conventional CNN technique to classify sensor faults.

• The Bulletin of The Korean Astronomical Society
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• v.42 no.2
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• pp.79.2-79.2
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• 2017

To dynamically and chemically understand how filaments, dense cores, and stars form under different environments, we are conducting a systematic mapping survey of nearby molecular clouds using the TRAO 14 m telescope with high ($N_2H^+$ 1-0, $HCO^+$ 1-0, SO 32-21, and $NH_2D$ v=1-0) and low ($^{13}CO$ 1-0, $C^{18}O$ 1-0) density tracers. The goals of this survey are to obtain the velocity distribution of low dense filaments and their dense cores for the study of their origin of the formation, to understand whether the dense cores form from any radial accretion or inward motions toward dense cores from their surrounding filaments, and to study the chemical differentiation of the filaments and the dense cores. Until the 2017A season, the real OTF observation time is ~760 hours. We have almost completed mapping observation with four molecular lines ($^{13}CO$ 1-0, $C^{18}O$ 1-0, $N_2H^+$ 1-0, and $HCO^+$ 1-0) on the six regions of molecular clouds (L1251 of Cepheus, Perseus West, Polaris South, BISTRO region of Serpens, California, and Orion B). The cube data for $^3CO$ and $C^{18}O$ lines were obtained for a total of 6 targets, 57 tiles, 676 maps, and $7.1deg^2$. And $N_2H^+$ and $HCO^+$ data were added for $2.2deg^2$ of dense regions. All OTF data were regridded to a cell size of 44 by 44 arcseconds. The $^{13}CO$ and $C^{18}O$ data show the RMS noise level of about (0.1-0.2) K and $N_2H^+$ and $HCO^+$ data show about (0.07-0.2) K at the velocity resolution of 0.06 km/s. Additional observations will be made on some regions that have not reached the noise level for analysis. To identify filaments, we are using and testing programs (DisPerSE, Dendrogram, FIVE) and visual inspection for 3D image of cube data. A basic analysis of the physical and chemical properties of each filament is underway.

• Composites Research
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• v.24 no.1
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• pp.24-30
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• 2011

Low-velocity impact can cause various damages which are mostly hidden inside the laminates or occur in the opposite side. Thus, these damages cannot be easily detected by visual inspection or conventional NDT systems. And if they occurred between the scheduled NDT periods, the possibilities of extensive damages or structural failure can be higher. Due to these reasons, the built-in NDT systems such as real-time impact monitoring system are required in the near future. In this paper, we studied the impact monitoring system consist of impact location detection and damage assessment techniques for composite flat and stiffened panel. In order to acquire the impact-induced acoustic signals, four multiplexed FBG sensors and high-speed FBG interrogator were used. And for development of the impact and damage occurrence detections, the neural networks and wavelet transforms were adopted. Finally, these algorithms were embodied using MATLAB and LabVIEW software for the user-friendly interface.

• The Journal of the Korea Contents Association
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• v.20 no.3
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• pp.298-308
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• 2020

This study was designed to verify reliability and feasibility by analyzing elderly drivers' ability test tools for older drivers aged 65 or older, which were improved in 2018 and are currently being conducted by the Korea Highway Traffic Authority. Only those aged 65 or older who voluntarily applied to the elderly driving ability evaluation system implemented by the Seoul branch of the Korea Highway Traffic Authority. The research was conducted for about 50 days until Aug. 31, 2018, starting with the registration and inspection of the first study subjects. The analysis performed a correlation analysis with existing tools and cognitive testing tools (MMSE_K) to determine their feasibility and reliability as an improved tool in 2018. As a result, the first, the speed distance, time-space memory, and dispersionism of each sub-component of the old version showed statistically significant static correlation with the sub-factor of the current version. Persistence, on the other hand, was not statistically significant to the current version. The limitations of this study were as follows. Most of the people in the study were highly educated and residents in the metropolitan area. Therefore, it is likely that the results of MSE_K, which checks cognitive and judgment skills, have been upgraded. Also, cognitive tools that are measured by computers are likely to have real measurement errors for generations who are not familiar with computers. Therefore, it is expected that improvement and development of tools for improving the limit points at the site and assessing actual operation capability will be required.

• Journal of the Korean Society of Hazard Mitigation
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• v.5 no.4 s.19
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• pp.9-15
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• 2005

This research developed the RMIS(Risk Management Information System) which focus on works of risk management fields required of apply of a space information, and focus on the DB to establish and apply the space information efficiently with research scope on the LPG refueling station in city. On the basis of the RMIS, this research provides the baseline to lead on an efficiency of safety inspection of LPG refueling station, advance risk assessment, and efficient making decision of an accident correspondence assessment with interlocking the GIS representing risk through the automation of a quantitative risk assessment standardize requirement to control at real-time. The RMIS development process is as follows. firstly, Relational Database(RDB) was developed by using fundamental data both On-site and Off-site relating data as peforming risk assessment on the LPG refueling station in city. Second, the risk management integral database system was developed to monitor and control the risk efficiently for user with using the Visual Basic Program. Third, through interlocking the risk management integral database system and the GIS(Falcon-map) was suggested the decision making method. Represented results through out the RMIS program development are as follows. Firstly, the RMIS was established the mutual information to advance management the risk efficiently for user and inspector with using the risk management data. Second, as this study managed risk for on-site and off-site separately and considered effect for inside and outside of facility, constructed the basis on safety management which can respond to major accident. Third, it was composed the baseline to making decision that on the basis of user interface.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.2
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• pp.397-409
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• 2014

According to the Personal Information Protection Act(PIPA) which is legislated in March 2011, the individual or company that handles personal information, called Personal information processor, should encrypt some kinds of personal information kept in his Database. For convenience sake we call it DB Encryption in this paper. Law enforcement and the implementation agency accordingly are being strengthen the supervision that the status of DB Encryption is being properly applied and implemented as the PIPA. However, the process of DB Encryption is very complicate and difficult as well as there are many factors to consider in reality. For example, there are so many considerations and requirements in the process of DB Encryption like pre-analysis and design, real application and test, etc.. And also there are surely points to be considered in related system components, business process and time and costs. Like this, although there are plenty of factors significantly associated with DB Encryption, yet more concrete and realistic validation entry seems somewhat lacking. In this paper, we propose a realistic DB Encryption Assurance Framework that it is acceptable and resonable in the performance of the PIPA duty (the aspect of the individual or company) and standard direction of inspection and verification of DB Encryption (the aspect of law enforcement).

• The Journal of Society for e-Business Studies
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• v.23 no.3
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• pp.159-171
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• 2018

The imported foods, which are imported and sold domestically, are on the rise every year, and the scale is expected to be larger, including processing the imported raw materials. However, the origin of raw materials is indicated when declaring cargo for finished products of agricultural products, but the standardization of inspection information management system for raw materials is insufficient. In addition, there is a growing concern about the presence of residual pesticides or radioactivity in raw materials or products, and customer want to know production history information when purchasing agrifoods. It manages the hazard analysis of imported agricultural products, but most of them are global issues such as microorganisms, residual pesticides, food additives, and allergy components, etc. Therefore, it is necessary to share among the logistics entities in the entire transportation process the related data. Additionally, to do this, it needs to design an architecture and standardize business model. In this paper, it defines the architecture and the work-flow that occurs between the business process for collecting, processing, and processing information for tracking the status of imported agricultural products by steps, and develops XML message with UBL and the extracted conceptual information model. It will be easy to exchange and share information among the logistics entities through the defined standard model and it will be possible to establish visibility, reliability, safety, and freshness system for transportation of agricultural products requiring real-time management.

• Journal of Korean Library and Information Science Society
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• v.52 no.1
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• pp.155-178
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• 2021

In the era of the 4th industrial revolution, public libraries need a strategy for promoting intelligent library services in order to actively respond to changes in the external environment such as artificial intelligence. Therefore, in this study, based on the concept of artificial intelligence and analysis of domestic and foreign artificial intelligence related trends, policies, and cases, we proposed the future direction of introduction and development of artificial intelligence services in the library. Currently, the library operates a reference information service that automatically provides answers through the introduction of artificial intelligence technologies such as deep learning and natural language processing, and develops a big data-based AI book recommendation and automatic book inspection system to increase business utilization and provide customized services for users. Has been provided. In the field of companies and industries, regardless of domestic and overseas, we are developing and servicing technologies based on autonomous driving using artificial intelligence, personal customization, etc., and providing optimal results by self-learning information using deep learning. It is developed in the form of an equation. Accordingly, in the future, libraries will utilize artificial intelligence to recommend personalized books based on the user's usage records, recommend reading and culture programs, and introduce real-time delivery services through transport methods such as autonomous drones and cars in the case of book delivery service. Service development should be promoted.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.793-810
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• 2022

Synthetic Aperture Radar (SAR) is considered to be suitable for near real-time inundation monitoring. The distinctly different intensity between water and land makes it adequate for waterbody detection, but the intrinsic speckle noise and variable intensity of SAR images decrease the accuracy of waterbody detection. In this study, we suggest two modules, named 'morphology module' and 'edge-enhanced module', which are the combinations of pooling layers and convolutional layers, improving the accuracy of waterbody detection. The morphology module is composed of min-pooling layers and max-pooling layers, which shows the effect of morphological transformation. The edge-enhanced module is composed of convolution layers, which has the fixed weights of the traditional edge detection algorithm. After comparing the accuracy of various versions of each module for U-Net, we found that the optimal combination is the case that the morphology module of min-pooling and successive layers of min-pooling and max-pooling, and the edge-enhanced module of Scharr filter were the inputs of conv9. This morphologic and edge-enhanced U-Net improved the F1-score by 9.81% than the original U-Net. Qualitative inspection showed that our model has capability of detecting small-sized waterbody and detailed edge of water, which are the distinct advancement of the model presented in this research, compared to the original U-Net.