• Journal of Korea Society of Industrial Information Systems
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• v.23 no.2
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• pp.63-73
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• 2018

Academia and research institutes mainly use qualitative methods that rely on expert judgments to understand and predict research trends and science and technology trends. Since such a technique has the disadvantage of requiring much time and money, in this study, science and technology trends were predicted using keyword network analysis. To that end, 13,618 AI (Artificial Intelligence) patent abstracts were analyzed using keyword network analysis in three separate lots based on the period of the submission of each abstract: analysis period 1 (January 1, 2002 - December 31, 2006), analysis period 2 (January 1, 2007 - December 31, 2011), and analysis period 3 (January 1, 2012 - December 31, 2016). According to the results of frequency analyses, keywords related to methods in the field of AI application appeared more frequently as time passed from analysis period 1 to analysis period 3. In keyword network analyses, the connectivity between keywords related to methods in the field of AI application and other keywords increased over time. In addition, when the connected keywords that showed increasing or decreasing trends during the entire analysis period were analyzed, it could be seen that the connectivity to methods and management in the field of AI application was strengthened while the connectivity to the field of basic science and technology was weakened. According to analysis of keyword connection centrality, the centrality value of the field of AI application increased over time. According to analysis of keyword mediation centrality during analysis period 3, keywords related to methodologies in the field of AI application showed the highest mediation value. Therefore, it is expected that methods in the field of AI application will play the role of powerful intermediaries in AI hereafter. The technique presented in this paper can be employed in the excavation of tasks related to regional innovation or in fields such as social issue visualization.

• Electronics and Telecommunications Trends
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• v.35 no.6
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• pp.78-87
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• 2020

With the evolution of the Internet of Things (IoT), a computing paradigm shift from cloud to edge computing is rapidly taking place to effectively manage the rapidly increasing volume of data generated by various IoT devices. Edge computing is computing that occurs at or near the physical location of a user or data source. Placing computing services closer to these locations allows users to benefit from faster and more reliable services, and enterprises can take advantage of the flexibility of hybrid cloud computing. This paper describes the concept and main benefits of edge computing and presents the trends and future prospects for edge computing technology.

• Knowledge Management Research
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• v.14 no.1
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• pp.121-132
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• 2013

In education, innovative ways of teaching and learning are always under development and keep being proposed with advanced concepts since the ancient times. Student-centered learning, problem-based learning and cooperative learning have been three major trends under development in secondary education research and practice more than a decade or so. Combined with advanced information and communication technologies, these trends will greatly transform the way we teach and learn in classroom environment and may change the classroom environment itself, into a more interactive and self-centered coaching type environment. In this study, a smart environment that utilizes advanced information technology devices and network is conceptualized, accommodating requirements contained and proposed in the recent trendy pedagogies. Pedagogical cases discussed in these trends are analyzed in detail, producing requirements for such a learning and coaching environment. These requirements are modeled using unified modeling language, leading to a proposal of a basic architecture for an information system supporting this environment.

• Atmosphere
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• v.15 no.2
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• pp.119-127
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• 2005

It is challenging work to predict weather and climate conditions of the future in advance. Since ENIAC was developed, weather and climate research areas have been taking advantage of the improvements in computer hardware. High performance computers allows researchers to build high quality models that allow them to make good predictions of what might happen in the future. Statistics on the high performance computers are one of the major interest to not only manufacturers but also the users such as weather and climate researchers. For this reason, the Top500 Supercomputer Sites Report has been being released twice a year since 1993 to provide a reliable basis for tracking and detecting trends in high performance computing. Using the Top500 Report, a short review on the supercomputer trends in weather and climate research areas is provided in this article.

• Journal of Korea Technology Innovation Society
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• v.3 no.2
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• pp.94-110
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• 2000

This article prospects the patterns of technological innovation in the steel industry and suggests the directions of technological innovation in Korean steel industry. Technological innovation patterns can be analysed through technological trends, innovation-inducing mechanism, and innovators' relationships. In the technological trends, direct coupling of manufacturing processes, lasting growth of mini-mill, and the importance of technological integration are prospected. In the innovation-inducing mechanism, while production system will be specialized, the development of new steel materials and environment-friendly technological innovation will be accelerated. In the innovators' relationships, steel industry faces more complex competition and new forms of inter-firm cooperation including M&A, joint venture, and joint R&D. In order to cope with such changes in the technological innovation patterns, Korean steel industry need to establish core competence based on technological innovation through a great leap in R&D investment, the production of high value-added products, the development of new generation steel technologies, strategic joint R&D, comprehensive technological cooperation, and government's active support.

• Electronics and Telecommunications Trends
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• v.33 no.4
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• pp.33-42
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• 2018

Object classification and detection are fundamental technologies in computer vision and its applications. Recently, a deep-learning based approach has shown significant improvement in terms of object classification and detection. This report reviews the progress of deep-learning based object classification and detection in views of the ImageNet Large Scale Visual Recognition Challenge (ILSVRC), and analyzes recent trends of object classification and detection technology and its applications.

• Electronics and Telecommunications Trends
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• v.32 no.6
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• pp.40-47
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• 2017

One of the main technical constraints of a conventional battery is the limited lifetime of electric energy supplied. With self-power generation using an internal radioisotope as an emitter of beta particles, and a PN-junction semiconductor as an absorber of the beta particles, a betavoltaic battery can provide electric energy to electric devices in a semi-permanent manner. Hence, a betavoltaic battery can be adopted as the solution to the power source issue of IoT devices placed in locations that people cannot easily access, such as in the deep sea, a desert, and space, and requiring a long operation time without an electrical charging. This paper covers the current trends in betavoltaic batteries including issues regarding their technology, application, and patents.

• Electronics and Telecommunications Trends
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• v.35 no.2
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• pp.69-78
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• 2020

Small portable devices such as mobile phones and laptops currently display a trend of high power consumption owing to their characteristics of high speed and multifunctionality. Low-power SoC design is one of the important factors that must be considered to increase portable time at limited battery capacities. Popular low power SoC design techniques include clock gating, multi-threshold voltage, power gating, and multi-voltage design. With a decreasing semiconductor process technology size, leakage power can surpass dynamic power in total power consumption; therefore, appropriate low-power SoC design techniques must be combined to reduce power consumption to meet the power specifications. This study examines several low-power SoC design trends that reduce semiconductor SoC dynamic and static power using EDA tools. Low-power SoC design technology can be a competitive advantage, especially in the IoT and AI edge environments, where power usage is typically limited.

• International Journal of Advanced Culture Technology
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• v.7 no.4
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• pp.295-301
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• 2019

Since the third artificial intelligence boom was triggered by deep learning, it has been 10 years. It is time to analyze and discuss the research trends of deep learning for the stable development of AI. In this regard, this study systematically analyzes the trends of research on deep learning over the past 10 years. We collected research literature on deep learning and performed LDA based topic modeling analysis. We analyzed trends by topic over 10 years. We have also identified differences among the major research countries, China, the United States, South Korea, and United Kingdom. The results of this study will provide insights into research direction on deep learning in the future, and provide implications for the stable development strategy of deep learning.

• International Journal of Advanced Culture Technology
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• v.9 no.3
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• pp.86-91
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• 2021

This study starts with the premise that many problematic situations in modern society can seriously damage personal feelings and that this phenomenon can create anxiety in individuals and society. In order to address such anxiety in individuals and society, we would like to propose measures to heal emotions. Accordingly, 270 research trends related to emotions studied from 2005 to 2020 will be analyzed to establish the direction of future research on emotion healing. As a result of analyzing the trends of healing papers, active healing studies have been conducted since 2010, but reading and writing healing through specific academic societies has been the main focus. Theoretical research accounted for a large portion, and emotional research was steadily conducted. Although healing methods are expanding to various topics, they have not been commercialized as specific methods. As a result, we hope that concrete research to heal individual emotions will be expanded and measures to implement a stable future society will be proposed.