• 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 the Korean Society of Radiology
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• v.12 no.7
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• pp.845-852
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• 2018

This study aimed to investigate the difference of X-ray exposure by comparing and analyzing absorbed dose according to changes in the number of frames in coronary angiography, also depending whether the zoom mode is FOV enlargement or Zoom Live. Moreover, for appropriate frame selection measures for examination, including the effect of frame change on the image quality, were sought by measuring the noise strength expressed by the standard deviation (SD), the signal to noise ratio (SNR) and contrast to noise ratio (CNR). The study was conducted with an anthropomorphic phantom on an angio-system. The linear relationship between the frame rate and the radiation dose was evident. On the contrary, the indices of image quality (SD, SNR, and CNR) were almost constant irrespective of the number of frames. The difference depending on the zoom mode was not statistically significant for DAP, air kerma, and SD (p > 0.05). However, SNR and CNR were statistically different between FOV enlargement and Zoom Live. In conclusion, since the image quality was not degraded significantly with the decreasing frame rate from 30, 15, to 7.5 f/s and the radiation dose evidently decreases in almost exactly linear proportion to the decreasing frame rate, the number of frames per second needs to be maintained as low as reasonably achievable. As for the dependence on the zooming mode, the Live Zoom mode showed statistically significant improvement in the image quality indices of SNR and CNR and it justifies active use of the Live Zoom mode which enables real-time image enlargment without additional radiation dose.

• 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.725-735
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• 2022

Currently, disasters occurring in Korea are characterized by unpredictability and complexity. Due to these features, property damage and human casualties are increasing. Since the initial response process of these disasters is directly related to the scale and the spread of damage, optimal decision-making is essential, and information of the site must be obtained through timely applicable sensors. However, it is difficult to make appropriate decisions because indiscriminate information is collected rather than necessary information in the currently operated Disaster and Safety Situation Office. In order to improve the current situation, this study proposed a framework that quickly collects various disaster image information, extracts information required to support decision-making, and utilizes it. To this end, a web-based display system and a smartphone application were proposed. Data were collected close to real time, and various analysis results were shared. Moreover, the capability of supporting decision-making was reviewed based on images of actual disaster sites acquired through CCTV, smartphones, and UAVs. In addition to the reviewed capability, it is expected that effective disaster management can be contributed if institutional mitigation of the acquisition and sharing of disaster-related data can be achieved together.

• Journal of Internet Computing and Services
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• v.23 no.3
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• pp.87-95
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• 2022

Recently, with the development of smart technology, in medical information platform, patient's biometric data is measured in real time and accumulated into database, and it is possible to determine the patient's emergency situations. Medical staff can easily access patient information after simple authentication using a mobile terminal. However, in accessing medical information using the mobile terminal, it is necessary to study authentication in consideration of the patient situations and mobile terminal. In this paper, we studied on medical information platforms based on big data processing and edge computing for supporting automatic authentication in emergency situations. The automatic authentication system that we had studied is an authentication system that simultaneously performs user authentication and mobile terminal authentication in emergency situations, and grants upper-level access rights to certified medical staff and mobile terminal. Big data processing and analysis techniques were applied to the proposed platform in order to determine emergency situations in consideration of patient conditions such as high blood pressure and diabetes. To quickly determine the patient's emergency situations, edge computing was placed in front of the medical information server so that the edge computing determine patient's situations instead of the medical information server. The medical information server derived emergency situation decision values using the input patient's information and accumulated biometric data, and transmit them to the edge computing to determine patient-customized emergency situation. In conclusion, the proposed medical information platform considers the patient's conditions and determine quick emergency situations through big data processing and edge computing, and enables rapid authentication in emergency situations through automatic authentication, and protects patient's information by granting access rights according to the patient situations and the role of the medical staff.

• Journal of the Korea Society of Computer and Information
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• v.25 no.9
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• pp.37-44
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• 2020

AI technology has developed in the form of decision support technology in law, patent, finance and national defense and is applied to disease diagnosis and legal judgment. To search real-time information with Deep Learning, Big data Analysis and Deep Learning Algorithm are required. In this paper, we try to predict the entrance rate to high-ranking universities using a Deep Learning model, RNN(Recurrent Neural Network). First, we analyzed the current status of private academies in administrative districts and the number of students by age in administrative districts, and established a socially accepted hypothesis that students residing in areas with a high educational fever have a high rate of enrollment in high-ranking universities. This is to verify based on the data analyzed using the predicted hypothesis and the government's public data. The predictive model uses data from 2015 to 2017 to learn to predict the top enrollment rate, and the trained model predicts the top enrollment rate in 2018. A prediction experiment was performed using RNN, a Deep Learning model, for the high-ranking enrollment rate in the special education zone. In this paper, we define the correlation between the high-ranking enrollment rate by analyzing the household income and the participation rate of private education about the current status of private institutes in regions with high education fever and the effect on the number of students by age.

• Archives of design research
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• v.18 no.2 s.60
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• pp.219-232
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• 2005

Moderns are living within flood of web contents, animation, reflex data etc. as well as sight, product, environment design. There fore, modern consumer has much options. Designer must provide various result for consumer for this reason. And must invent new sensitivity and propose to consumer. As purpose of this MCC sensitivity palette research takes advantage of the most sensitive color, do. Because applying correct sensitivity more than when design with matter already settled, rid private prejudice, and is thing to convey design intention exactly to user. Excellent culture contents must be able to equip international color design sensitivity. MCC sensitivity palette research studies and carries on the head emotion and sensitivity language that is nationality first, and collect End arranged sensitivity adjective through data analysis and picture data analysis that is the next time research leader Munheonjeok. And distributed collected adjective equally, and arrange distributed adjective by field of each sensitivity and collect system. Do 3 colors, 4 colors color scheme in selected sensitivity adjective and completed Simheom version. Result of beta version research to color specialist and designer last digital palette through question and inquiry compose. Through this process, completed more real and correct digital color sensitivity palette. Completed color scheme is operated in www.mcdri.net on web, and also programs to windows base and developed to software. MCC color scheme palette that research result is made includes sensitivity data database. This database can use directly in industry and continuous development is available. Software can search color scheme in language and idea development through classification search that use 3 attributes of color is available there is cough data of each output device different color error.

• Knowledge Management Research
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• v.19 no.1
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• pp.59-77
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• 2018

The tourism industry is now changing to smart tourism, which maximizes tourists' overall tourism experience with the use of advanced mobile technologies and emphasizes the utilization of tourism information. Despite the quantitative expansion of the tourism industry, there is a lack of academic and practical discussion on tourism safety. Especially, in the context of walking tourism, tourists are more likely to be exposed to natural or social disasters and emergencies. Therefore, it is necessary to build a system that can provide walking tourists with safety information not only on dangerous factors which are anticipated to be confronted during a walking trip in advance but also on specific dangers in real time. Under the circumstances, this study seeks to identify the types of tourism safety information that can be offered by using publicly available open data, drawing on the safety information framework on the walking tourism that is presented in Choi et al. (2017)'s study. More specifically, this study focuses on the use of open data which is provided by the Korean government. Furthermore, this study verifies the types of safety information that are most urgently needed in walking travel situations. Specifically, this study aims to derive the importance and priority of each type of safety information for a walking trip by applying the analytic hierarchy process (AHP) analysis. For this, we collected 35 questionnaires from walking tour operators (practitioners) and walking tourists. The main results are as follows. First, natural disaster information is the most important factor in the top-level factor of safety information for walking tourists, followed by social disaster, life safety, and exhibition (security crisis) information. Second, information on natural disasters, environmental pollution, and weather is considered to be important at the sub-level factor. Lastly, the noteworthy result of this study is that the importance of each type of safety information varies depending on the walking tour operators (practitioners) and the walking tourists. That is, there is a recognition difference between the operator (practitioner) and the user in the importance and priority of the safety information of the walking trip. Therefore, it is necessary to develop policies and services reflecting the opinions of potential users when providing safety information so that the most importantly recognized information can be provided first.

• Development and Reproduction
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• v.20 no.4
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• pp.297-304
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• 2016

Lectins belong to the pattern-recognition receptors (PRRs) class and play important roles in the recognition and elimination of pathogens via the innate immune system. Recently, it was reported that lily-type lectin-1 is involved when a pathogen attacks in the early immune response of fish. However, this study is limited to information that the lectin is involved in the innate immune response against viral infection. In the present study, the lily-type lectin-2 and -3 of Oplegnathus fasciatus (OfLTL-2 and 3) have been presented to be included B-lectin domain and two D-mannose binding sites in the amino acid sequence that an important feature for the fundamental structure. To investigate the functional properties of OfLTLs, the tissue distribution in the healthy rock bream and temporal expression during early developmental stage analysis are performed using quantitative real-time PCR. OfLTL-2 and 3 are predominantly expressed in the liver and skin, but rarely expressed in other organ. Also, the transcripts of OfLTLs are not expressed during the early developmental stage but its transcripts are increased after immune-related organs which are fully formed. In the challenge experiment with RBIV (rock bream iridovirus), the expression of OfLTLs was increased much more strongly in the late response than the early, unlike previously known. These results suggest that OfLTLs are specifically expressed in the immune-related tissues when those organs are fully formed and it can be inferred that the more intensively involved in the second half to the virus infection.

• 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.