• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.153-154
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• 2019

본 논문에서는 사물인터넷(Internet of Things, IoT)에 적용되어 사용될 수 있는 다중 게이트웨이 환경에서 각 게이트웨이의 자원 상황에 따라 종단 노드를 클라우드 단으로 직접 트레이드하여 처리함으로서 게이트웨이의 자원 소모를 줄이고 높은 처리량을 요구하는 종단 노드를 빠르게 처리 가능한 기법을 제안한다. 본 논문에서는 해당 기법의 효율성 입증을 위하여 클라우드 컴퓨팅이라는 대규모 환경을 가정하여 실험을 진행하였으며, 해당 실험의 결과에 따르면 높은 처리량을 요구하는 종단 노드를 클라우드 단에 트레이드하여 직접 처리함으로서 클라우드 단 하부의 다중 게이트웨이의 자원 소모율 감소 및 데이터 처리 속도가 증대 되었음을 확인할 수 있다.

• Journal of Environmental Health Sciences
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• v.48 no.3
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• pp.131-137
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• 2022

Public interest has been increasing the focus on the management of exposure to pollutants and the related health effects. This study reviewed exposure assessment methodologies and addressed future directions. Exposure can be assessed by direct (exposure monitoring) or indirect approaches (exposure modelling). Exposure modelling is a cost-effective tool to assess exposure among individuals, but direct personal monitoring provides more accurate exposure data. There are several population exposure models: stochastic human exposure and dose simulation (SHEDS), air pollutants exposure (APEX), and air pollution exposure distributions within adult urban population in Europe (EXPOLIS). A South Korean population exposure model is needed since the resolution of ambient concentrations and time-activity patterns are country specific. Population exposure models could be useful to find the association between exposure to pollutants and adverse health effects in epidemiologic studies. With the advancement of sensor technology and the internet of things (IoT), exposure assessment could be applied in a real-time surveillance system. In the future, environmental health services will be useful to protect and promote human health from exposure to pollutants.

• Asian Journal of Innovation and Policy
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• v.12 no.1
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• pp.054-074
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• 2023

With the advent of the '4th Industrial Revolution', digitalization using AI (Artificial Intelligence), big data, IoT (Internet of Things), cloud computing and mobile is accelerating across all industries and global companies have fundamentally reorganized customer experiences, business models, and operations centering on digital transformation. Business innovation drives productivity improvement, process simplification, price, competitiveness and sustainable expansion. Whether digital transformation will be necessary for the current industrial environment is no longer important, and how quickly companies achieve digitalization has emerged as the utmost crucial element in industrial continuity. As non-face-to-face and remote technologies have begun in earnest, and accelerated in the pharmaceutical industry. They are looking for ways to provide value, generate profits, improve efficiency, and sustain the future. Compared to other industries, the pharmaceutical-related sectors have shown high interest in digital transformation especially to reduce costs and meet the challenge of delivering products during the pandemic environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1436-1457
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• 2018

Secure routing services in Wireless Sensor Networks (WSNs) are essential, especially in mission critical fields such as the military and in medical applications. Additionally, they play a vital role in the current and future Internet of Things (IoT) services. Lightness and efficiency of a routing protocol are not the only requirements that guarantee success; security assurance also needs to be enforced. This paper proposes a Secure-Fuzzy Energy Aware Routing Protocol (S-FEAR) for WSNs. S-FEAR applies a security model to an existing energy efficient FEAR protocol. As part of this research, the S-FEAR protocol has been analyzed in terms of the communication and processing costs associated with building and applying this model, regardless of the security techniques used. Moreover, the Qualnet network simulator was used to implement both FEAR and S-FEAR after carefully selecting the following security techniques to achieve both authentication and data integrity: the Cipher Block Chaining-Message Authentication Code (CBC-MAC) and the Elliptic Curve Digital Signature Algorithm (ECDSA). The performance of both protocols was assessed in terms of complexity and energy consumption. The results reveal that achieving authentication and data integrity successfully excluded all attackers from the network topology regardless of the percentage of attackers. Consequently, the constructed topology is secure and thus, safe data transmission over the network is ensured. Simulation results show that using CBC-MAC for example, costs 0.00064% of network energy while ECDSA costs about 0.0091%. On the other hand, attacks cost the network about 4.7 times the cost of applying these techniques.

• Journal of Korean Society of Disaster and Security
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• v.9 no.1
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• pp.19-24
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• 2016

In this study, we conducted a study on the development of Internet of Things-based disaster response system. We researched the method of building the network-based disaster prevention system using a client machine that the sensor network and the keeper. Also, we developed the algorithm for optimal evacuation shelter based on spanning tree algorithm. The system is tested actually in Seoul Gaepo station, and we verified the usability of the system.

• Journal of Satellite, Information and Communications
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• v.10 no.1
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• pp.62-66
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• 2015

This paper introduces various applications and contents of digital signage, and analyzes conventional communication techniques to increase communication range. To realize digital signage in long distance, this paper proposes a hybrid modulation scheme and analyzes its performance. To verify its performance in real channel environment, we mapped symbols and experimented data transmission and reception with a visible light communication module with USRP. As a result, we confirmed a data receiving range and power of transmission and reception of the hybrid modulation mode. Also, we showed that the proposed modulation scheme has better performance of communication range and power efficiency than that of the conventional QAM technique.

• Nuclear Engineering and Technology
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• v.52 no.7
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• pp.1436-1442
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• 2020

Nuclear infrastructure systems play an important role in national security. The functions and missions of nuclear infrastructure systems are vital to government, businesses, society and citizen's lives. It is crucial to design nuclear infrastructure for scalability, reliability and robustness. To do this, we can use machine learning, which is a state of the art technology used in various fields ranging from voice recognition, Internet of Things (IoT) device management and autonomous vehicles. In this paper, we propose to design and develop a machine learning algorithm to perform predictive maintenance of nuclear infrastructure. Support vector machine and logistic regression algorithms will be used to perform the prediction. These machine learning techniques have been used to explore and compare rare events that could occur in nuclear infrastructure. As per our literature review, support vector machines provide better performance metrics. In this paper, we have performed parameter optimization for both algorithms mentioned. Existing research has been done in conditions with a great volume of data, but this paper presents a novel approach to correlate nuclear infrastructure data samples where the density of probability is very low. This paper also identifies the respective motivations and distinguishes between benefits and drawbacks of the selected machine learning algorithms.

• The Journal of the Convergence on Culture Technology
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• v.5 no.4
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• pp.51-60
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• 2019

The purpose of this study is to examine the issues that can be expected in the smart intelligent information society led by artificial intelligence and the Internet of Things, and how to resolve the issues in terms of PR.The results were as follows. First, there are three major issues that can be expected Second, in order to resolve the issue, it is necessary to prepare and carry out a public interest campaign to create and participate in a new paradigm for the alienated public. Third, welfare technology can be considered as an alternative to the issues.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.67-72
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• 2020

The fifth generation (5G) mobile communication has an impact on the human life over the whole world, nowadays, through the artificial intelligence (AI) and the internet of things (IoT). The low latency of the 5G new radio (NR) access is implemented by the state-of-the art technologies, such as non-orthogonal multiple access (NOMA). This paper investigates a practical issue that in NOMA, for the practical channel models, such as fading channel environments, the successive interference cancellation (SIC) should be performed on the stronger channel users with low power allocation. Only if the SIC is performed on the user with the stronger channel gain, NOMA performs better than orthogonal multiple access (OMA). Otherwise, NOMA performs worse than OMA. Such the superiority requirement can be easily implemented for the channel being static or slow varying, compared to the block interval time. However, most mobile channels experience fading. And symbol by symbol channel estimations and in turn each symbol time, selections of the SIC-performing user look infeasible in the practical environments. Then practically the block of symbols uses the single channel estimation, which is obtained by the training sequence at the head of the block. In this case, not all the symbol times the SIC is performed on the stronger channel user. Sometimes, we do perform the SIC on the weaker channel user; such cases, NOMA performs worse than OMA. Thus, we can say that by what percent NOMA is better than OMA. This paper calculates analytically the percentage by which NOMA performs better than OMA in the practical mobile communication systems. We show analytically that the percentage for NOMA being better than OMA is only the function of the ratio of the stronger channel gain variance to weaker. In result, not always, but almost time, NOMA could perform better than OMA.

• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.360-374
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• 2016

Since WSNs (Wireless Sensor Networks) applied to their application areas such as smart home, smart factory, environment monitoring, etc., depend on sensor data, the sensor data is the most important among WSN components. The resources of each node consisting of WSN are extremely limited in energy, hardware and so on. Due to these limitation, communication failure probabilities become much higher and the communication failure causes data loss to occur. For this reason, this paper proposes 2MC (Maximum/Minimum Compression) that is a method to compress sensor data by selecting circular queue-based maximum/minimum sensor data values. Our proposed method reduces sensor data losses and value errors when they are recovered. Experimental results of 2MC method show the maximum/minimum 35% reduction efficiency in average sensor data accumulation error rate after the 3 times compression, comparing with CQP (Circular Queue Compression based on Period) after the compressed data recovering.