• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.33-42
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• 2022

One of the most pressing socioeconomic problems confronting humanity on a worldwide scale is food security, particularly in light of the expanding population and declining land productivity. These causes have increased the number of people in the world who are at risk of starving and have caused the natural ecosystems to degrade at previously unheard-of speeds. Happily, the Internet of Things (IoT) development provides a glimmer of light for those worried about food security through smart agriculture-a development that is particularly relevant to automating food production operations in order to reduce labor expenses. When compared to conventional farming techniques, smart agriculture has the benefit of maximizing resource use through precise chemical input application and regulation of environmental factors like temperature and humidity. Farmers may make data-driven choices about the possibility of insect invasion, natural disasters, anticipated yields, and even prospective market shifts with the use of smart farming tools. The technical foundation of smart agriculture serves as a potential response to worries about food security. It is made up of wireless sensor networks and integrated cloud computing modules inside IoT.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.330-330
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• 2022

우리나라에서 발생하는 기상 재해 현상은 주로 태풍, 집중호우, 장마 등 인명 및 경제적인 피해가 크며, 단기간에 국지적으로 나타난다. 현재 재해 감시 및 예보는 주로 종관기상관측체계를 이용하고 있다. 하지만, 우리나라의 복잡한 지형, 인구 밀집 지형, 관측 시기가 일정하지 않은 지형과 같은 조건에서 미계측 자료 및 지역이 다수 존재 때문에 강수의 공간 분포와 강도에 대한 정밀한 정보를 제공하지 못하는 실정이다. 최근 광범위한 관측영역과 공간 분해능의 개선, 자료추출 알고리즘의 개발로 전세계적으로 위성영상 기반 기상관측 자료의 활용성이 증대되고 있다. 본 연구에서는 한반도 지역의 지상 관측데이터와 전지구 격자형 위성 강우자료를 비교하여 한반도의 적용성을 분석하고자 한다. 다양한 위성영상 기반 기상자료인 Climate Hazards Groups InfraRed Precipitation with Station (CHIRPS), Precipitation Estimation From Remotely Sensed Information Using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR), Global Precipitation Climatology Centre (GPCC), Precipitation Estimation From Remotely Sensed Information Using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS) 4개의 강우위성영상을 수집하여, 1991년부터 2020년까지 30년 데이터를 활용하였다. 강수량 변동성 비교를 위하여 기상청의 종관기상관측장비 (Automated Synoptic Observation System, ASOS), 자동기상관측시설 (Automatic Weather System, AWS) 데이터와 상관 분석을 수행하고, 강우위성영상의 국내 적합성을 판단하고자 한다.

• Journal of Biosystems Engineering
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• v.43 no.2
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• pp.148-159
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• 2018

Purpose: Unmanned air vehicle (UAV) remote sensing was applied to test various vegetation indices and make prediction models of protein content of rice for monitoring grain quality and proper management practice. Methods: Image acquisition was carried out by using NIR (Green, Red, NIR), RGB and RE (Blue, Green, Red-edge) camera mounted on UAV. Sampling was done synchronously at the geo-referenced points and GPS locations were recorded. Paddy samples were air-dried to 15% moisture content, and then dehulled and milled to 92% milling yield and measured the protein content by near-infrared spectroscopy. Results: Artificial neural network showed the better performance with $R^2$ (coefficient of determination) of 0.740, NSE (Nash-Sutcliffe model efficiency coefficient) of 0.733 and RMSE (root mean square error) of 0.187% considering all 54 samples than the models developed by PR (polynomial regression), SLR (simple linear regression), and PLSR (partial least square regression). PLSR calibration models showed almost similar result with PR as 0.663 ($R^2$) and 0.169% (RMSE) for cloud-free samples and 0.491 ($R^2$) and 0.217% (RMSE) for cloud-shadowed samples. However, the validation models performed poorly. This study revealed that there is a highly significant correlation between NDVI (normalized difference vegetation index) and protein content in rice. For the cloud-free samples, the SLR models showed $R^2=0.553$ and RMSE = 0.210%, and for cloud-shadowed samples showed 0.479 as $R^2$ and 0.225% as RMSE respectively. Conclusion: There is a significant correlation between spectral bands and grain protein content. Artificial neural networks have the strong advantages to fit the nonlinear problem when a sigmoid activation function is used in the hidden layer. Quantitatively, the neural network model obtained a higher precision result with a mean absolute relative error (MARE) of 2.18% and root mean square error (RMSE) of 0.187%.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.6
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• pp.379-386
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• 2014

Recently, middleboxes play a key role in many network settings such as firewalls, VPN gateways, proxies, intrusion detection and prevention systems, and WAN optimizers. However, achieving the performance and security benefits that middleboxes offer is highly complex, and therefore it is essential to manage middleboxes efficiently and dynamically. In this respect, Software-Defined Networking (SDN) offers a promising solution for middlebox policy enforcement by using logically centralized management, decoupling the data and control planes, and providing the ability to programmatically configure forwarding rules. Also, cloud computing and distributed Network Function Virtualization (NFV) can enable to manage middleboxes more easily. We introduce SDN-based middlebox management framework in integrated wired and wireless networks and discuss the further issues.

• Electronics and Telecommunications Trends
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• v.35 no.6
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• pp.56-67
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• 2020

The core technologies of the 4th Industrial Revolution, such as artificial intelligence, the Internet of Things, the cloud, big data, and mobile networks, are inspiring major changes and innovations in the defense sector worldwide. The United States, China, and Russia are pursuing defense research and development strategies that seek to maintain their leadership on the battlefield in the future through the overwhelming superiority of defense science technology. Defense science and technology concentrate on the development of challenging new disruptive technologies to efficiently respond to future battlefield environments, where the immediate process of determining the outcome of a war will lead to combat power. In this paper, we first look at the development strategies of the 4th Industrial Revolution in major countries and describe the latest trends in defense science and technology accordingly.

• Journal of Korea Multimedia Society
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• v.19 no.5
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• pp.918-923
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• 2016

IoT should be considered security risk environments such as various platforms and services including smart devices that can be mounted on household electric appliances, healthcare, car, and heterogeneous networks that are connected to the Internet, cloud services and mobile Apps.. In this paper, we provide analysis of new security threats, caused by open-platform of IoT and sensors via the Internet. Also, we present the key recovery mechanism that is applied to IoT. It results to have compatibility with given research, reduces network overhead, and performs key recovery without depending on key escrow agencies or authorized party.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.781-782
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• 2015

As growth engines such as cloud, social networks, big data that can affect the security market have been grown, the information security industry has has also rapidly evolved. Reviewing information security policies carried out in USA, UK and Japan, this paper examines trends on the IoT-related information protection law and regulations that are at issue around the major developed countries. Through this research, we can get the implication that measures be taken as soon as possible to apply the existing data protection laws in the Internet of Things.

• Journal of Information Processing Systems
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• v.16 no.3
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• pp.523-529
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• 2020

Future information and communication technology (ICT) is constantly evolving and converging in diverse fields depending on the wireless environment, and the trend is being further developed to increase the speed of wireless networks. Future ICT is needed in many areas such as active senior & solo-economy, hyper-connected society, intelligent machine, industrial boundary collapse, secured self, and the sharing economy. However, a lot of research is needed to solve problems such as machine learning, security, prediction, unmanned technology, etc. Therefore, this paper describes some technologies developed in the areas of blockchain, fault diagnosis, security, agricultural ICT, cloud, life safety and care, and climate monitoring in order to provide insights into the future paradigm.

• Annual Conference of KIPS
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• 2019.10a
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• pp.168-171
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• 2019

센서 네트워크는 스마트 시티와 같은 4차 산업혁명 분야의 핵심기술로 다양한 분야에 활용되고 있다. 기존의 센서 네트워크는 여러개의 센서 노드가 한 개의 싱크 노드를 통해 인터넷으로 데이터를 전달하였다. 그러나 과도한 트래픽 또는 외부적인 요인으로 인해 싱크 노드가 중지될 경우 그 싱크노드와 연결된 센서 노드로부터 데이터를 수집하지 못하는 단점을 가지고 있다. 제안하는 시스템은 도커를 사용하여 싱크노드를 컨테이너화 하고 쿠버네티스를 통해 중지된 컨테이너를 자동으로 재시작하여 시스템의 안정성을 높일 수 있다.

• Electronics and Telecommunications Trends
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• v.34 no.1
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• pp.23-35
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• 2019

In the upcoming post-app era, real-time, intelligent and immersive services such as autonomous vehicles, virtual secretaries, virtual reality, and augmented reality are expected to dominate. However, there is a growing demand for new networking and computing infrastructure capabilities because existing physical connection-oriented networks and centralized cloud-based service environments have inherent limitations to effectively accommodate these services. To this end, research on intelligent edge network computing technology is underway to analyze the contextual situation of human and things and to configure the service environment on the network edge so that the application services can be performed optimally. In this article, we describe the technology issues for edge network intelligence and introduce related research trends.