• STI Policy Review
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• v.2 no.1
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• pp.13-34
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• 2011

This paper investigates the interaction among the paradigm of Low-Carbon Society (LCS) and the megatrends in field of population, environment, geopolitics, and energy. The paradigm of LCS is regarded as a 'social will' trend, distinguished from other 'phenomenal' trends. The qualitative analysis shows that the megatrends and the LCS paradigm have positive/neutral/negative impacts on one another, while some impacts can be reversed to other types of impact with the conditions having ripened. In quantitative analysis, the correlation between the LCS paradigm and the economy is traced with our Integrated Assessment Model, looking into such response options as population control, increase in labor force participation, and productivity enhancement to maintain utility level despite the pursuit of LCS paradigm. The future challenges in national strategy and S&T policy are suggested, based on the interaction analyses.

• International journal of advanced smart convergence
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• v.7 no.4
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• pp.75-83
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• 2018

Predictive IoT Sensor Algorithm is a technique of data science that helps computers learn from existing data to predict future behaviors, outcomes, and trends. This algorithm is a cloud predictive analytics service that makes it possible to quickly create and deploy predictive models as analytics solutions. Sensors and computers collect and analyze data. Using the time series prediction algorithm helps to predict future temperature. The application of this IoT in industrial environments like power plants and factories will allow organizations to process much larger data sets much faster and precisely. This rich source of sensor data can be networked, gathered and analyzed by super smart software which will help to detect problems, work more productively. Using predictive IoT technology - sensors and real-time monitoring - can help organizations exactly where and when equipment needs to be adjusted, replaced or how to act in a given situation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.2
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• pp.333-336
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• 2020

AI-powered robot news is drawing attention as artificial intelligence technology is fully spread in the news distribution field. Robot news still has many technical and ethical problems, but academic research on this is insufficient. This study analyzes the issue of robot writing in artificial intelligent based robot journalism industry using SWOT analysis. As a result, the advantages of big data processes, accurate information gathering, high efficiency and disadvantages such as lack of independent arguments and lack of evidence and opportunities for technical development, government support, academic development, and industrial applications, and threats such as uncritical acceptance and lack of talent have been found. This study suggests three future-oriented directions, such as human-machine collaboration, intelligent news, and chat-bot, through previous studies on the development direction of robot journalism-based article writing.

• Food Science and Industry
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• v.52 no.4
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• pp.346-357
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• 2019

In recent years, starch nanoparticles (SNPs) have been received much attention due to their unique characteristics different from native starch. Also, SNPs have economic and environmental advantages because they are prepared from starch, a cheap and safe natural polymer. It can be used in various industrial applications such as food additives, drug carriers, etc. SNPs have been prepared using different methods and their physiochemical, functional properties and possible industrial applications have been reported. Based on these studies, SNPs are expected to be the promising food materials and expand their utilization in many industries in the future. This review covered the overall researches on SNPs, including preparation, physicochemical and functional properties, and discussed their current and future applications including resistant starch materials.

• Electronics and Telecommunications Trends
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• v.36 no.1
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• pp.12-21
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• 2021

This article presents the future vision and core technologies of the "Life Companion Robot," which is one of the 12 future concepts introduced in the ETRI Technology Roadmap published in November 2020. Assistant robots, care robots, and life support robots were proposed as the development stages of life companion robots. Further, core technologies for each of the ten major roles that must be directly or indirectly performed by life companion robots are introduced. Finally, this article describes in detail three major artificial intelligence technologies for autonomous robots.

• Journal of the Korean Society of Safety
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• v.35 no.6
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• pp.61-77
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• 2020

In order to establish a conceptual basis and future research direction of safety leadership, this study reviewed domestic and foreign research trends related to safety leadership through systematic literature review methods. The literature search was conducted by combining terms related to safety leadership without limiting the period databases. A total of 195 documents were found, of which the final 59 were used for analysis. As a results, the safety leadership study was the most frequent in relations among variables. The most leadership types were based on transactional leadership and transformational leadership. In addition, studies have been conducted to categorize safety leadership as an independent concept. Safety leadership was mainly studied in the fields of safety engineering, disaster prevention, and business administration. Quantitative studies were mainly conducted to research methods. Based on the results, the research trend related to safety leadership was discussed, and suggestions for future research direction was presented.

• Investigative Magnetic Resonance Imaging
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• v.25 no.4
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• pp.266-280
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• 2021

Advances in radiomics and deep learning (DL) hold great potential to be at the forefront of precision medicine for the treatment of patients with brain metastases. Radiomics and DL can aid clinical decision-making by enabling accurate diagnosis, facilitating the identification of molecular markers, providing accurate prognoses, and monitoring treatment response. In this review, we summarize the clinical background, unmet needs, and current state of research of radiomics and DL for the treatment of brain metastases. The promises, pitfalls, and future roadmap of radiomics and DL in brain metastases are addressed as well.

• Journal of Information Processing Systems
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• v.19 no.1
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• pp.118-129
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• 2023

The expansion of smart cities drives the growth of data generated from sensor devices, benefitting citizens with enhanced governance, intelligent decision-making, optimized and sustainable management of available resources. The exposure of user data during its collection from sensors, storage in databases, and processing by artificial intelligence-based solutions presents significant security and privacy challenges. In this paper, we investigate the various threats and attacks affecting the growth of future smart cities and discuss the available countermeasures using artificial intelligence and blockchain-based solutions. Open challenges in existing literature due to the lack of countermeasures against quantum-inspired attacks are discussed, focusing on postquantum security solutions for resource-constrained sensor devices. Additionally, we discuss future research and challenges for the growing smart city environment and suggest possible solutions.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.800-807
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• 2022

This study aims to review the use of graph databases in construction research. Based on the diagnosis of the current research status, a future research direction is proposed. The use of graph databases in construction research has been increasing because of the efficiency in expressing complex relations between entities in construction big data. However, no study has been conducted to review systematically the status quo of graph databases. This study analyzes 42 papers in total that deployed a graph model and graph database in construction research, both quantitatively and qualitatively. A keyword analysis, topic modeling, and qualitative content analysis were conducted. The review identified the research topics, types of data sources that compose a graph, and the graph database application methods and algorithms. Although the current research is still in a nascent stage, the graph database research has great potential to develop into an advanced stage, fused with artificial intelligence (AI) in the future, based on the active usage trends this study revealed.

• Applied Chemistry for Engineering
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• v.34 no.3
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• pp.226-240
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• 2023

This paper provides an overview of the trends and future directions in the development of anode materials for solid oxide fuel cells (SOFCs) using hydrocarbons as fuel, with the aim of enabling a decentralized energy supply. Hydrocarbons (such as natural gas and biogas) offer promising alternatives to traditional energy sources, as their use in SOFCs can help meet the growing demands for energy. We cover several types of materials, including perovskite structures, high-entropy alloys, proton-conducting ceramic materials, anode on-cell catalyst reforming layers, and anode functional layers. In addition, we review the performance and long-term stability of cells based on these anode materials and assess their potential for commercial manufacturing processes. Finally, we present a model for enhancing the applicability of fuel cell-based power generation systems to assist in the realization of the H₂ economy as the best practice for enabling distributed energy. Overall, this study highlights the potential of SOFCs to make significant progress toward a sustainable and efficient energy future.