• Journal of radiological science and technology
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• v.43 no.5
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• pp.397-404
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• 2020

Coronavirus disease(COVID-19) is highly infectious disease that directly affects the lungs. To observe the clinical findings from these lungs, the Chest Radiography(CXR) can be used in a fast manner. However, the diagnostic performance via CXR needs to be improved, since the identifying these findings are highly time-consuming and prone to human error. Therefore, Artificial Intelligence(AI) based tool may be useful to aid the diagnosis of COVID-19 via CXR. In this study, we explored various Deep learning(DL) approach to classify COVID-19, other viral pneumonia and normal. For the original dataset and lung-segmented dataset, the pre-trained AlexNet, SqueezeNet, ResNet18, DenseNet201 were transfer-trained and validated for 3 class - COVID-19, viral pneumonia, normal. In the results, AlexNet showed the highest mean accuracy of 99.15±2.69% and fastest training time of 1.61±0.56 min among 4 pre-trained neural networks. In this study, we demonstrated the performance of 4 pre-trained neural networks in COVID-19 diagnosis with CXR images. Further, we plotted the class activation map(CAM) of each network and demonstrated that the lung-segmentation pre-processing improve the performance of COVID-19 classifier with CXR images by excluding background features.

• Journal of Korean Society for Geospatial Information Science
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• v.1 no.2 s.2
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• pp.143-152
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• 1993

A long-term water quality study has been initiated by the Korean Ministry of Environment(MOE) - The G-7 Project--in cooperation with two national research institutes, an University research tn and a consulting firm. This study includes the development of computer software for total water quality management system, so called ISWQM (Integrated System of Water Quality Management). ISWQM includes four major components: a GIS database; two artificial intelligence (AI) based expert systems to estimate pollutant loadings and to provide cost-effective wastewater treatment system for small and medium size urban areas; and computer programs to integrate the database and expert systems. ISWQM is to provide user-friendly Decision Support System (DSS) for water quality planners. A GIS was used to create spatial database which stores all the necessary data to n DSS. GIS was also used to integrate the four components of ISWQM from data creation to decision making through Graphic User Interface (GUI). The results from the first phase of this study showed that GIS would provide an effective tool to build DSS using expert system.

• Journal of the Korea Society of Computer and Information
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• v.25 no.8
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• pp.73-79
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• 2020

Since the start of the 4th industrial revolution, technologies have been developed in the Internet of Things (IoT), artificial intelligence (AI), virtual reality (VR), and 5G. Compared to other technologies IoT is currently being commercialized more than other technologies where the numbers of connected things are increases every year. The IoT has a huge advantage to provide convenience and lots of information to users, but security cannot keep up with the speed of development. IoT services continue to provide services for related devices, but at present, more and more types of new services are being combined with other technologies by utilizing the services of devices. This paper reviews and analyzes research on security issues and services related to the Internet of Things to explore how security trends and service delivery will develop in the future.

• Journal of Digital Convergence
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• v.14 no.8
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• pp.177-183
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• 2016

Augmented Reality(AR) has been further developed through connectivity with Artificial Intelligence (AI), Big Data, the Internet of Things(IoT). The interest of AR in the advertising is on the increase. However, it needs to explore the use of AR technology in advertising based on user experience rather than the technical aspects. This study is very significant in that it is the exploratory study which provides guidelines in the field of utilizing AR, particularly based on direct user experience. In addition, through a quantitative survey, it checks the validity of the present study to verify the impact of utilitarian, experiential value of AR ad on brand attitude as consumer attitude. The characteristics of AR ad based on user experience through this study will provide guidance to utilize AR ad, utilizing AR technology in various fields, such as education and exhibitions in developing convergence contents that can provide practical value.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.4
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• pp.91-96
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• 2018

Recently, as artificial intelligence technology becomes popular, demand for wireless traffic is rapidly increasing. In order to provide services in response to the increase in demand for wireless traffic, telecommunication companies are generalizing the installation of public APs. In order to provide convenience of using wireless APs between communication companies, it is necessary to share the use of APs in public places to efficiently use wireless resources in a public place, to pre-authenticate between wireless APs in a mobile communication service, So as to increase the convenience of the user. In this paper, we propose to share APs in public places through handoff between APs and pre-authentication between carriers in mobile communication services. The simulation results show that the handoff latency is improved by 35.1% and the bandwidth used by the AP selected by the pre-authentication method can utilize more bandwidth than the method of automatically selecting the AP.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.1
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• pp.157-167
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• 2020

The big data and artificial intelligence technology, which has provided the foundation for the recent 4th industrial revolution, has become a major driving force in business innovation across industries. In the field of information security, we are trying to develop and improve an intelligent security system by applying these techniques to large-scale log data, which has been difficult to find effective utilization methods before. The quality of security log big data, which is the basis of information security AI learning, is an important input factor that determines the performance of intelligent security system. However, the difference and complexity of log data by various product has a problem that requires excessive time and effort in preprocessing big data with poor data quality. In this study, we research and analyze the cases related to log data collection of various firewall. By proposing firewall log data collection format standard, we hope to contribute to the development of intelligent security systems based on security log big data.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.213-216
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• 2018

As the advantages of smart devices based on artificial intelligence and voice recognition become more prominent, Virtual Assistant is gaining popularity. Virtual Assistant provides a user experience through smart speakers and is valued as the most user friendly IoT device by consumers. The purpose of this study is to investigate whether there are differences in people's perception of the key virtual assistant brand voice recognition. We collected tweets that included six keyword form three companies that provide Virtual Assistant services. The authors conducted semantic network analysis for the collected datasets and analyzed the feelings of people through sentiment analysis. The result shows that many people have a different perception and mainly about the functions and services provided by the Virtual Assistant and the expectation and usability of the services. Also, people responded positively to most keywords.

• Journal of the Semiconductor & Display Technology
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• v.18 no.3
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• pp.122-126
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• 2019

These-days technology related to IoT (Internet of Thing) is widely used and there are many types of smart system based IoT like smart health, smart building and so on. In smart health system, it is possible to check someone's health by analyzing data from wearable IoT device like smart watch. Smart building system aims to collect data from sensor such as humidity, temperature, human counter like that and control the building for energy efficiency, security, safety and so forth. Furthermore, smart city system can comprise several smart systems like smart building, smart health, smart mobility, smart energy and etc. In this paper, we propose multimedia IoT based intelligent emergency alarm system for smart city. In existing IoT based smart system, it communicates lightweight data like text data. In the past, due to network's limitations lightweight IoT protocol was proposed for communicating data between things but now network technology develops, problem which is to communicate heavy data is solving. The proposed system obtains video from IP cameras/CCTVs, analyses the video by exploiting AI algorithm for detecting emergencies and prevents them which cause damage or death. If emergency is detected, the proposed system sends warning message that emergency may occur to people or agencies. We built prototype of the intelligent emergency alarm system based on MQTT and assured that the system detected dangerous situation and sent alarm messages. From the test results, it is expected that the system can prevent damages of people, nature and save human life from emergency.

• The Journal of Bigdata
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• v.5 no.1
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• pp.139-145
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• 2020

In the era of the 4th Industrial Revolution, the use of information based on AI APIs has a great influence on industry and life. In particular, the use of artificial intelligence data in the medical field will have many changes and effects on society. This paper is to study the necessary components to implement the "Cognitive Health Advisor model (CHA model)" and to implement the "CHA model using chatbot" based on this. It uses the open Cognitive chatbot to analyze and analyze the health status of users changing in their daily lives. The user's health information analyzed by the biometric sensor and chatbot consultation delivers the information to the user through the chatbot. And it implements a cognitive health advisor model that provides educational information for users' health promotion. Through this implementation, it intends to confirm the possibility of future use and to suggest research directions.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.123-123
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• 2018

가뭄은 홍수와 달리 진행속도가 비교적 느리기 때문에 초기에 감지한다면 피해를 최소화 할 수 있다. 국내에서는 가뭄전망을 위해 물리적 기반의 기상-수문연계해석 시스템을 구축하여 월 내지 계절전망을 수행하고 있다. 물리적 기반의 가뭄전망은 수치예보모델의 불확실성을 가지고 있으므로 예보 정확도 개선의 측면에서는 통계적 모델을 같이 활용하는 것이 바람직하다. 최근 국외에서는 통계적 방법인 AI (Artificial Intelligence) 기술을 사용하여 가뭄을 전망하는 연구가 활발히 진행 중이나, 아직까지 국내에서는 관련연구가 미흡한 실정이다. 이에 본 연구에서는 ANFIS (Adaptive Neuro-Fuzzy Inference System) 기반의 댐 유입량 예측 모델을 구축하고 SRI (Standardized Runoff Index)를 활용하여 수문학적 가뭄전망을 수행하였다. 대상유역은 국내 주요 다목적댐이 위치한 충주댐 유역과 소양강댐 유역을 선정하였다. 수문 및 기상자료는 국토 교통부 및 기상청의 관측 댐 유입량, 관측 강수량, 관측 기온 및 장기기상예보 자료를 사용하였다. ANFIS 모델 구축을 위한 훈련 및 보정기간과 검정기간은 각각 1987~2010년과 2011~2016년을 선정하였다. 수문학적 가뭄전망은 지속기간 3개월의 1개월 전망 SRI3를 활용하였으며, SRI3는 관측유입량과 예측유입량을 결합하여 산정하였다. 댐 예측유입량 및 수문학적 가뭄전망의 정확도 평가를 위해 상관계수, 평균제곱근오차를 활용하였다. 댐 예측유입량 평가 결과 예측값과 관측값의 상관계수가 높게 나타났으며, 평균제곱근오차는 낮아 예측성이 뛰어났다. SRI3의 경우 관측값과 예측값의 가뭄발생시기가 유사하여 가뭄을 적절하게 반영하는 것으로 나타났다. 본 연구의 결과는 통계적 기반의 수문학적 가뭄전망기법을 개발하였다는 측면에서 의의가 있으며, 향후 물리적 기반의 가뭄전망정보와 결합한다면 보다 실효성이 향상될 것으로 기대된다.