• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.4
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• pp.84-90
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• 2019

Lately, there have been tremendous shifts in the business technology landscape. Advances in cloud technology and mobile applications have enabled businesses and IT users to interact in entirely new ways. One of the most rapidly growing technologies in this sphere is business intelligence, and associated concepts such as big data and data mining. BI is the collection of systems and products that have been implemented in various business practices, but not the information derived from the systems and products. On the other hand, big data has come to mean various things to different people. When comparing big data vs business intelligence, some people use the term big data when referring to the size of data, while others use the term in reference to specific approaches to analytics. As the volume of data grows, businesses will also ask more questions to better understand the data analytics process. As a result, the analysis team will have to keep up with the rising demands on the infrastructure that supports analytics applications brought by these additional requirements. It's also a good way to ascertain if we have built a valuable analysis system. Thus, Business Intelligence and Big Data technology can be adapted to the business' changing requirements, if they prove to be highly valuable to business environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.8
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• pp.3028-3039
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• 2015

Recently, the web index of Korea peaked at the top 10 among the eighty six countries, and Korea became the only Asian country ranked at the top level. Korea also has been on the top in the field of Internet penetration rate, in terms of both high-speed broadband and wireless Internet. However, such achievements did not guarantee the national level for the effective use of information utilizing Internet. According to OECD, the national informatization index of Korea has not been free from the middle of the OECD countries. Despite of the heightened pressure in practically enhancing effective information use utilizing Internet, the previous research interests and efforts to develop the Internet-related framework or to identify Internet capabilities rarely existed. The study aims to propose the framework, named "Internet Information Orientation" that illustrates the relationship between Internet capabilities and national competitiveness on Internet. The research identified the specific Internet capabilities, reclassified the capabilities based on the research issues provided at the 6^th international conference on Internet held in December 2014, and finally described the rigorous research endeavors on the issues. As a result, 16 papers presented and selected as the outstanding papers at the conference handle issues to be brought together, which include: Wireless Network, Internet of Things, Green Computing, Multimedia Processing, Big Data and Text Mining, Database in Cloud Environment, Business Intelligence, Software Engineering, IT Strategy & Policy, and Social Network Services.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.6
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• pp.1035-1043
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• 2022

With the spread of the Internet of Things (IoT), cloud computing, and big data, the need for high-speed encryption for applications is emerging. GPU optimization can be used to validate cryptographic analysis results or reduced versions theoretically obtained by the GPU in a reasonable time. In this paper, PIPO lightweight encryption implemented in various environments was implemented on GPU. Optimally implemented considering the brute force attack on PIPO. In particular, the optimization implementation applying the bit slicing technique and the GPU elements were used as much as possible. As a result, the implementation of the proposed method showed a throughput of about 19.5 billion per second in the RTX 3060 environment, achieving a throughput of about 122 times higher than that of the previous study.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.11a
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• pp.298-299
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• 2022

Digital Transformation in the maritime transportation sector means "by utilizing digital technologies such as artificial intelligence, big data, Internet of Things, block chain, and cloud to create new business models, products, and services for maritime transportation-related companies. It can be defined as a continuous process that adapts to or drives disruptive changes in the market" (Chang, 2021). In a situation where various digital conversion technologies are applied and started to be used in the domestic port logistics field, active acceptance by members can bring about the success of digital conversion. Therefore, in this study, in order to investigate the acceptability of digital transformation in the domestic port logistics sector,

• Journal of Korean Society of Water and Wastewater
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• v.31 no.5
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• pp.383-388
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• 2017

The $4^{th}$ Industry Revolution was advocated by Klaud Schwab who is founder of World Economic Forum at the Davos Forum in 2016, and there are big differences on ICT based $4^{th}$ Industry revolution in the aspects of speed, scope and impact compared with the 3rd Industry revolution. Creating new industries and values through technology such as internet of things, cloud, big data, and artificial intelligence are included in the meaning of The $4^{th}$ industry revolution. In this article, the direction of change to water technology in response to the $4^{th}$ Industry revolution is surveyed. 4G Water Infra should minimize environmental impact under the consideration of sustainable development and advanced technologies. To solve the existing water infra problems, it is common and fundamental that the intake water from nature can be regarded as borrowed from nature and it should be returned to natural state with improved water quality. Government, academic organizations and industries should prepare and collaborate together in order to help our country with outstanding capabilities in infrastructure construction and ICT to lead the 4G water technology development.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.560-563
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• 2016

The changes in the medical and healthcare are started from the digital technology. The new field of digital healthcare has started fused with existing healthcare, medical technology, and digital technology. It can increase the service effect and reduce healthcare costs by applying ICT skills such as ICBM(Internet of Things, Cloud, Big data and Mobile), artificial intelligence, robotics, virtual, augmented reality, and wearable devices to healthcare services including healthcare, disease management. Recently there has been grafted an artificial intelligence technologies such as AlphaGo of Google and Watson of IBM onto the healthcare area. In this study, we analyze the main technology, ecosystem, platforms for digital healthcare, and lastly future changes in health care services and issues of digital healthcare.

• 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.

• Korean System Dynamics Review
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• v.16 no.3
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• pp.97-107
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• 2015

본 논문은 최근 다양한 사회 분야에 있어서 IT 기술이 적용되는 과정을 SD 모델링 방식을 사용하여 연구한 경험과 발견을 서술하고자 한다. 모델의 초기 단계에서 우리는 다양한 사회 분야마다 다른 SD 모델을 만들 것이냐 아니면 기본적으로 유사한 모델 구조를 취할 것이냐를 선택해야 했다. 사회 분야마다 다른 구조의 SD 모델을 만들면, 상호간의 구조와 시뮬레이션 결과를 비교하기 어렵다. 하지만 상호 모델 구조를 유사하게 구축하려고 하니, 서로 다른 모델링 팀들간의 의사소통에 노력과 시간 소비가 지나치게 커져 갔다. 이러한 어려움을 극복하기 위하여 본 연구에서는 시스템 다이내믹스 모델링에도 시스템 사고의 원형적 피드백 루프에서와 같은 원형적 SD 모델을 만들고, 이를 사회 각 분야에 적용하는 방식을 취하고자 하였다. 먼저 최근 IT 기술 발전을 이끌어 가는 핵심적인 요소로서 클라우드 컴퓨팅, 스마트 기기, 사물 인터넷을 선정하고 이들간의 상호 관계성을 표현하는 SD 모델을 만들었다. 이를 원형(archetype)으로 하여, 교육, 의료, 원격 근무 등 사회 각 분야의 IT 확산 과정에 적용하여 모델링을 하고 시뮬레이션을 하여 상호 비교하면서 정책 시사점을 논의할 수 있었다. 본 논문에서는 이 중에서 원격 근무(smart work)에 관한 적용 사례를 제시함으로써, SD 모델링에 있어서 원형적 접근 방법의 가능성을 탐색한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2377-2398
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• 2021

In the recent modernized world, utilization of natural resources (renewable & non-renewable) is increasing drastically due to the sophisticated life style of the people. The over-consumption of non-renewable resources causes pollution which leads to global warming. Consequently, government agencies have been taking several initiatives to control the over-consumption of non-renewable natural resources and encourage the production of renewable energy resources. In this regard, we introduce an IoT powered integrated framework called as green home architecture (GHA) for green score calculation based on the usage of natural resources for household purpose. Green score is a credit point (i.e.,10 pts) of a family which can be calculated once in a month based on the utilization of energy, production of renewable energy and pollution caused. The green score can be improved by reducing the consumption of energy, generation of renewable energy and preventing the pollution. The main objective of GHA is to monitor the day-to-day usage of resources and calculate the green score using the proposed green score algorithm. This algorithm gives positive credits for economic consumption of resources and production of renewable energy and also it gives negative credits for pollution caused. Here, we recommend a green score based tax calculation system which gives tax exemption based on the green score value. This direct beneficiary model will appreciate and encourage the citizens to consume fewer natural resources and prevent pollution. Rather than simply giving subsidy, this proposed system allows monitoring the subsidy scheme periodically and encourages the proper working system with tax exemption rewards. Also, our GHA will be used to monitor all the household appliances, vehicles, wind mills, electricity meter, water re-treatment plant, pollution level to read the consumption/production in appropriate units by using the suitable sensors. These values will be stored in mass storage platform like cloud for the calculation of green score and also employed for billing purpose by the government agencies. This integrated platform can replace the manual billing and directly benefits the government.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.12
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• pp.291-306
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• 2020

Nowadays, Data-Network-AI (DNA)-based intelligent services and applications have become a reality to provide a new dimension of services that improve the quality of life and productivity of businesses. Artificial intelligence (AI) can enhance the value of IoT data (data collected by IoT devices). The internet of things (IoT) promotes the learning and intelligence capability of AI. To extract insights from massive volume IoT data in real-time using deep learning, processing capability needs to happen in the IoT end devices where data is generated. However, deep learning requires a significant number of computational resources that may not be available at the IoT end devices. Such problems have been addressed by transporting bulks of data from the IoT end devices to the cloud datacenters for processing. But transferring IoT big data to the cloud incurs prohibitively high transmission delay and privacy issues which are a major concern. Edge computing, where distributed computing nodes are placed close to the IoT end devices, is a viable solution to meet the high computation and low-latency requirements and to preserve the privacy of users. This paper provides a comprehensive review of the current state of leveraging deep learning within edge computing to unleash the potential of IoT big data generated from IoT end devices. We believe that the revision will have a contribution to the development of DNA-based intelligent services and applications. It describes the different distributed training and inference architectures of deep learning models across multiple nodes of the edge computing platform. It also provides the different privacy-preserving approaches of deep learning on the edge computing environment and the various application domains where deep learning on the network edge can be useful. Finally, it discusses open issues and challenges leveraging deep learning within edge computing.