• Fire Science and Engineering
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• v.13 no.4
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• pp.30-37
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• 1999

In this study, reduced-scale experiments as the alternative to a real-scale fire test were conducted to understand fire properties in atrium space. The scaling laws were derived from $\pi$-parameters which were deduced by dimensional analysis of governing equations (continuity, conservation of momentum and conservation energy). The 1/50 scale experiment simulated the real-scale fire test in SIVANS atrium at Japan were conducted under the scaling laws. And this results were compared with real-scale experiment results. Furthermore these results were visualized by video recording system using laser light sheet.

• Structural Engineering and Mechanics
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• v.77 no.3
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• pp.305-314
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• 2021

In order to reduce enormous cost of real-scale underwater explosion experiments on ships, the mechanical response of the ships have been analyzed by combining scaled-down experiments and Hopkinson's scaling law. However, the Hopkinson's scaling law is applicable only if all variables vary in an identical ratio; for example, thickness of ship, size of explosive, and distance between the explosive and the ship should vary with same ratio. Unfortunately, it is infeasible to meet such uniform scaling requirement because of environmental conditions and limitations in manufacturing scaled model systems. For the facile application of the scaling analysis, we propose a generalized scaling law that is applicable for non-uniform scaling cases in which different parts of the experiments are scaled in different ratios compared to the real-scale experiments. In order to establish such a generalized scaling law, we conducted a parametric study based on numerical simulations, and validated it with experiments and simulations. This study confirms that the initial peak value of response variables in a real-scale experiment can be predicted even when we perform a scaled experiment composed of different scaling ratios for each experimental variable.

• Smart Structures and Systems
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• v.4 no.5
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• pp.667-684
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• 2008

Numerous devices exist for reducing or eliminating seismic damage to structures. These include passive dampers, semi-active dampers, and active control devices. The performance of structural systems with these devices has often been evaluated using numerical simulations. Experiments on structural systems with these devices, particularly at large-scale, are lacking. This paper describes a real-time hybrid testing facility that has been developed at the Lehigh University NEES Equipment Site. The facility enables real-time large-scale experiments to be performed on structural systems with rate-dependent devices, thereby permitting a more complete evaluation of the seismic performance of the devices and their effectiveness in seismic hazard reduction. The hardware and integrated control architecture for hybrid testing developed at the facility are presented. An application involving the use of passive elastomeric dampers in a three story moment resisting frame subjected to earthquake ground motions is presented. The experiment focused on a test structure consisting of the damper and diagonal bracing, which was coupled to a nonlinear analytical model of the remaining part of the structure (i.e., the moment resisting frame). A tracking indictor is used to track the actuator ability to achieve the command displacement during a test, enabling the quality of the test results to be assessed. An extension of the testbed to the real-time hybrid testing of smart structures with semi-active dampers is described.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.10
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• pp.4098-4116
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• 2020

Mobile devices such as smartphones are very attractive targets for augmented reality (AR) services, but their limited resources make it difficult to increase the number of objects to be recognized. When the recognition process is scaled to a large number of objects, it typically requires significant computation time and memory. Therefore, most large-scale mobile AR systems rely on a server to outsource recognition process to a high-performance PC, but this limits the scenarios available in the AR services. As a part of realizing large-scale standalone mobile AR, this paper presents a solution to the problem of accuracy, memory, and speed for large-scale object recognition. To this end, we design our own basic feature and realize spatial locality, selective feature extraction, rough pose estimation, and selective feature matching. Experiments are performed to verify the appropriateness of the proposed method for realizing large-scale standalone mobile AR in terms of efficiency and accuracy.

• Journal of Ocean Engineering and Technology
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• v.12 no.1
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• pp.135-142
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• 1998

In this study, the frequency transfer function of motions are predicted from the result of a full-scale seakeeping trials. Because the real sea has the characteristics of multi-directional waves,we compare the results in the one directional waves with ones in the directional waves. For calculation of the frequency transfer function in the directional waves, Takezawa's inverse estimation method was introduced and the frequency ranges were divided into three parts in order to consider following seas. The full-scale seakeeping trials was executed in the south sea of Korea using the stern trawler. Those results show that analysis method of the multi-directional waves is more reliable than that of one directional waves, and confirm the possibility of applying this method to the full-scale seakeeping trials.

• Water for future
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• v.45 no.5
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• pp.66-73
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• 2012

• Proceedings of the KSR Conference
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• 2008.06a
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• pp.2011-2014
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• 2008

A linear induction motor for urban railway transit is accompanied with the end-effect and large air-gap comparing with a rotary induction motor. These cause amount of difference between simulation results and experiments. In order to figure out the difference, experiments based on a real-scale test bed are indispensable, however building a test-line and a test vehicle is so difficult that authors are going to make a small-scale model and simulate it for comparison. In this paper, A rotary-type small-scale model of a linear induction motor is designed. Thrust and normal force of the model have been analyzed with the variation of frequency and speed by using a Finite Element Method(FEM).

• Fire Science and Engineering
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• v.19 no.4 s.60
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• pp.37-41
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• 2005

The present study describes the cooling performance of two kinds of water mist systems used in fire extinguishment. The cooling is necessary for the prevention of an auto re-ignition of the power transformer. A heat source for such the re-ignition is the accumulated thermal energy in the dielectric oil from the transformer core. Because of the weight of the real core, reduced-scale experiments are carried out. A similarity analysis Is also performed to determine the discharge time of the water mist systems from the experimental results. The discharge time to prevent the re-ignition in the real-scale transformer is estimated about 12 hour from the similarity analysis of the reduced-scale experiments.

• The Korean Journal of Applied Statistics
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• v.21 no.1
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• pp.65-80
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• 2008

Small scale time-course microarray experiments are those which have a small number of time points. They comprise about 80 percent of all time-course microarray experiments conducted up to 2005. Several statistical methods for the small scale time-course microarray experiments have been proposed. In this paper we applied three methods, namely, QR method, maSigPro method and STEM, to a real time-course microarray experiment which had six time points. We compared the performance of these three methods based on a simulation study and concluded that STEM outperformed, in general, in terms of power when the FDR was set to be 5%.

• Journal of Information Processing Systems
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• v.19 no.4
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• pp.427-438
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• 2023

Plenty of works have indicated that single image super-resolution (SISR) models relying on synthetic datasets are difficult to be applied to real scene text image super-resolution (STISR) for its more complex degradation. The up-to-date dataset for realistic STISR is called TextZoom, while the current methods trained on this dataset have not considered the effect of multi-scale features of text images. In this paper, a multi-scale and attention fusion model for realistic STISR is proposed. The multi-scale learning mechanism is introduced to acquire sophisticated feature representations of text images; The spatial and channel attentions are introduced to capture the local information and inter-channel interaction information of text images; At last, this paper designs a multi-scale residual attention module by skillfully fusing multi-scale learning and attention mechanisms. The experiments on TextZoom demonstrate that the model proposed increases scene text recognition's (ASTER) average recognition accuracy by 1.2% compared to text super-resolution network.