• Earthquakes and Structures
• /
• v.15 no.1
• /
• pp.45-65
• /
• 2018

Over the last three decades, Performance-based Earthquake Engineering (PBEE) has been mainly developed for high seismicity regions. Although information is abundant for PBEE throughout the world, the application of PBEE to lower-seismicity regions, such as those where the magnitude of the maximum considered earthquake (MCE) is less than 6.5, is not always straightforward because some portions of PBEE may not be appropriate for such regions due to geological differences between high- and low-seismicity regions. This paper presents a brief review of state-of-art PBEE methodologies and introduces the seismic hazard of lower-seismicity regions, including those of the Korean Peninsula, with their unique characteristics. With this seismic hazard, representative low-rise RC MRF structures and high-rise RC wall residential structures are evaluated using PBEE. Also, the range of the forces and deformations of the representative building structures under the design earthquake (DE) and the MCE of South Korea are presented. These reviews are used to propose some ideas to improve the practice of state-of-art PBEE in lower-seismicity regions.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2002.10a
• /
• pp.467-474
• /
• 2002

Semiactive control systems have received considerable attention for protecting structures against natural hazards such as strong earthquakes and high winds, because they not only offer the reliability of passive control systems but also maintain the versatility and adaptability of fully active control systems. Among the many semiactive control devices, magnetorheological (MR) fluid dampers comprise one particularly promising class. In the field of civil engineering, much research and development on MR fluid damper-based control systems has been conducted since B. F. Spencer first introduced this unique semiactive device to civil engineering applications in mid 1990s. In 2001, MR fluid dampers were applied to the full-scale in-service civil engineering structures for the first time. This state-of-the-art paper includes a detailed literature review of control algorithms considering the characteristics of fm fluid dampers. This review provides references to semiactive control systems using MR fluid dampers. The MR fluid damper-based semiactive control systems are shown to have the potential for mitigating the responses of full-scale civil engineering structures under natural hazards.

• Journal of Electrical Engineering and Technology
• /
• v.11 no.2
• /
• pp.529-536
• /
• 2016

In this paper we proposed an unsupervised algorithm to estimate the reverberation time (RT) directly from the reverberant speech signal. For estimation process we use maximum likelihood estimation (MLE) which is a very well-known and state of the art method for estimation in the field of signal processing. All existing RT estimation methods are based on the decay rate distribution. The decay rate can be obtained either from the energy envelop decay curve analysis of noise source when it is switch off or from decay curve of impulse response of an enclosure. The analysis of a pre-existing method of reverberation time estimation is the foundation of the proposed method. In one of the state of the art method, the reverberation decay is modeled as a Laplacian distribution. In this paper, the proposed method models the reverberation decay as a Gamma distribution along with the unification of an effective technique for spotting free decay in reverberant speech. Maximum likelihood estimation technique is then used to estimate the RT from the free decays. The method was motivated by our observation that the RT of a reverberant signal when falls in specific range, then the decay rate of the signal follows Gamma distribution. Experiments are carried out on different reverberant speech signal to measure the accuracy of the suggested method. The experimental results reveal that the proposed method performs better and the accuracy is high in comparison to the state of the art method.

• The Bulletin of The Korean Astronomical Society
• /
• v.40 no.1
• /
• pp.53.3-54
• /
• 2015

We are developing large arrays of X-ray microcalorimeters for applications in X-ray astronomy. X-ray microcalorimeters can detect the energy of X-rays with extremely high resolution. High-resolution Imaging spectroscopy enabled by these arrays will allow us to study the hot and energetic nature of the Universe through the detection of X-rays from astronomical objects such as neutron stars or black holes. I will introduce the state-of-the-art X-ray microcalorimeters being developed at NASA/GSFC and the future X-ray observatory missions based on microcalorimeters.

• Journal of the Korean Society for Precision Engineering
• /
• v.12 no.12
• /
• pp.120-129
• /
• 1995

This study introduces a tool wear monitoring technology in face milling operation comprised of an unsupervised neural network. The monitoring system employs two types of sensor signal such as cutting force and acceleration in sensory detection state. The RMS value and band frequency energy of the sensor signals are calculated for te input patterns of neural network. ART2 neural network, which is capable of self organizing without supervised learning, is used for clustering of tool wear states. The experimental results show that tool wear can be effectively detected under various cutting conditions without prior knowledge of cutting processes.

• Journal of Information Technology Applications and Management
• /
• v.30 no.1
• /
• pp.115-126
• /
• 2023

In various fields such as art, design, music, film, sports, games, and fashion, NFTs (Non-Fungible Tokens) are creating new economic value through trading platforms dedicated to NFT art and content. In this article, I analyze the current state of blockchain technology and NFT art content in the context of an expanding market for blockchain-based NFT art content in the metaverse. I also propose several tasks based on the economic and industrial logic of technological innovation. The first task proposed is to integrate cultural arts on blockchain, metaverse, and NFT platforms through digital innovation, instead of separating or distinguishing between creative production and consumption. Before the COVID-19 pandemic, there was a clear separation between creators and consumers. However, with the rise of Web 3.0 platforms, any user can now create and own their own content. Therefore, it is important to promote a collaborative and integrated approach to cultural arts production and consumption in the blockchain and metaverse ecosystem. The second task proposed is to align the legal framework with blockchain-based technological innovation. The enactment and revision of relevant laws should focus on promoting the development of the NFT trading platform ecosystem, rather than merely regulating it for user protection. As blockchain-based technology continues to evolve, it is important that legal systems adapt to support and promote innovation in the space. This shift in focus can help create a more conducive environment for the growth of blockchain-based NFT platforms. The third task proposed is to integrate education on digital arts, including metaverse and NFT art contents, into the current curriculum. This education should focus on convergence and consilience, rather than merely mixing together humanities, technology, and arts. By integrating digital arts education into the curriculum, students can gain a more comprehensive understanding of the potential of blockchain-based technologies and NFT art. This article examines the digital technological innovation such as blockchain, metaverse, and NFT from an economic and industrial point of view. As a limitation of this research, the critical mind such as philosophical thinking or social criticism on technological innovation is left as a future task.

• ETRI Journal
• /
• v.37 no.2
• /
• pp.251-261
• /
• 2015

We present a novel method for real-time automatic license plate detection in high-resolution videos. Although there have been extensive studies of license plate detection since the 1970s, the suggested approaches resulting from such studies have difficulties in processing high-resolution imagery in real-time. Herein, we propose a novel cascade structure, the fastest classifier available, by rejecting false positives most efficiently. Furthermore, we train the classifier using the core patterns of various types of license plates, improving both the computation load and the accuracy of license plate detection. To show its superiority, our approach is compared with other state-of-the-art approaches. In addition, we collected 20,000 images including license plates from real traffic scenes for comprehensive experiments. The results show that our proposed approach significantly reduces the computational load in comparison to the other state-of-the-art approaches, with comparable performance accuracy.

• Advances in Energy Research
• /
• v.6 no.2
• /
• pp.103-129
• /
• 2019

While global demand for energy increases annually, at the same time the demand for carbon-free, sulphur-free and NO_x-free energy sources grows considerably. This state poses a challenge in the research for newer sources like biomass and shale gas as well as renewable energy resources such as solar, wind, geothermal and hydraulic energy. Although wave energy also is a form of renewable energy it has not fully been exploited technically and economically so far. This study tries to explain those reasons in which it is beyond doubt that the demand for wave energy will soon increase as fossil energy resources are depleted and environmental concerns gain more importance. The electrical energy supplied to the grid shall be produced from wave energy whose conversion devices can basically work according to three different systems. i. Systems that exploit the motions or shape deformations of their mechanisms involved, being driven by the energy of passing waves. ii. Systems that exploit the weight of the seawater stored in a reservoir or the changes of water pressure by the oscillations of wave height, iii. Systems that convert the wave motions into air flow. One of the aims of this study is to present the classification deficits of the wave energy converters (WECs) of the "wave developers" prepared by the European Marine Energy Center, which were to be reclassified. Furthermore, a new classification of all WECs listed by the European Marine Energy Center was arranged independently. The other aim of the study is to assess the technological state of the art of these WECs designed and/or produced, to obtain an overview on them.

• IEIE Transactions on Smart Processing and Computing
• /
• v.4 no.1
• /
• pp.35-43
• /
• 2015

Over the past couple of years, tremendous progress has been made in applying deep learning (DL) techniques to computer vision. Especially, deep convolutional neural networks (DCNNs) have achieved state-of-the-art performance on standard recognition datasets and tasks such as ImageNet Large-Scale Visual Recognition Challenge (ILSVRC). Among them, GoogLeNet network which is a radically redesigned DCNN based on the Hebbian principle and scale invariance set the new state of the art for classification and detection in the ILSVRC 2014. Since there exist various deep learning techniques, this review paper is focusing on techniques directly related to DCNNs, especially those needed to understand the architecture and techniques employed in GoogLeNet network.

• Journal of Radiation Protection and Research
• /
• v.47 no.4
• /
• pp.181-194
• /
• 2022

Internal dosimetry is a discipline which brings together a set of knowledge, tools and procedures for calculating the dose received after incorporation of radionuclides into the body. Several steps are necessary to calculate the committed effective dose (CED) for workers or members of the public. Each step uses the best available knowledge in the field of radionuclide biokinetics, energy deposition in organs and tissues, the efficiency of radiation to cause a stochastic effect, or in the contributions of individual organs and tissues to overall detriment from radiation. In all these fields, knowledge is abundant and supported by many works initiated several decades ago. That makes the CED a very robust quantity, representing exposure for reference persons in reference situation of exposure and to be used for optimization and assessment of compliance with dose limits. However, the CED suffers from certain limitations, accepted by the International Commission on Radiological Protection (ICRP) for reasons of simplification. Some of its limitations deserve to be overcome and the ICRP is continuously working on this. Beyond the efforts to make the CED an even more reliable and precise tool, there is an increasing demand for personalized dosimetry, particularly in the medical field. To respond to this demand, currently available tools in dosimetry can be adjusted. However, this would require coupling these efforts with a better assessment of the individual risk, which would then have to consider the physiology of the persons concerned but also their lifestyle and medical history. Dosimetry and risk assessment are closely linked and can only be developed in parallel. This paper presents the state of the art of internal dosimetry knowledge and the limitations to be overcome both to make the CED more precise and to develop other dosimetric quantities, which would make it possible to better approximate the individual dose.