• Steel and Composite Structures
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• v.37 no.2
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• pp.175-191
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• 2020

In this article, for the first time, the seismic behavior of elliptic-braced moment resisting frame (ELBRF) is assessed through a laboratory program and numerical analyses of FEM specifically focused on the development of global- and local-type failure mechanisms. The ELBRF as a new lateral braced system, when installed in the middle bay of the frames in the facade of a building, not only causes no problem to the opening space of the facade, but also improves the structural behavior. Quantitative and qualitative investigations were pursued to find out how elliptic braces would affect the failure mechanism of ELBRF structures exposed to seismic action as a nonlinear process. To this aim, an experimental test of a ½ scale single-story single-bay ELBRF specimen under cyclic quasi-static loading was run and the results were compared with those for X-bracing, knee-bracing, K-bracing, and diamond-bracing systems in a story base model. Nonlinear FEM analyses were carried out to evaluate failure mechanism, yield order of components, distribution of plasticity, degradation of structural nonlinear stiffness, distribution of internal forces, and energy dissipation capacity. The test results indicated that the yield of elliptic braces would delay the failure mode of adjacent elliptic columns and thus, help tolerate a significant nonlinear deformation to the point of ultimate failure. Symmetrical behavior, high energy absorption, appropriate stiffness, and high ductility in comparison with the conventional systems are some of the advantages of the proposed system.

• Journal of Digital Convergence
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• v.18 no.7
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• pp.215-222
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• 2020

The aim of this study was to develop a mobile application 'Beat Processing Device (BPD)' to record and quantify the data for the performance accuracy of rhythm production. BPD has been developed in three phases. First, we reviewed studies that used rhythm as main intervention strategy to improve cognitive functioning of older adults, and derived four basic rhythm idioms. Second, we developed an iOS-based mobile application, optimized the device, the instrument tone, and the measurement variables through preliminary test. Lastly, we tested the mobile application by comparing the performance data obtained from MIDI and BPD from 60 older adults. The device was shown to be reliable and consistent with other mode of measurement and analysis. Conclusively, BPD can be a useful tool for assessing rhythm production ability in the course of cognitive skills training.

• Journal of radiological science and technology
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• v.44 no.6
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• pp.655-661
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• 2021

Positron emission tomography (PET) images is affected by acquisition time, short acquisition times results in low gamma counts leading to degradation of image quality by statistical noise. Noise2Void(N2V) is self supervised denoising model that is convolutional neural network (CNN) based deep learning. The purpose of this study is to evaluate denoising performance of N2V for PET image with a short acquisition time. The phantom was scanned as a list mode for 10 min using Biograph mCT40 of PET/CT (Siemens Healthcare, Erlangen, Germany). We compared PET images using NEMA image-quality phantom for standard acquisition time (10 min), short acquisition time (2min) and simulated PET image (S2 min). To evaluate performance of N2V, the peak signal to noise ratio (PSNR), normalized root mean square error (NRMSE), structural similarity index (SSIM) and radio-activity recovery coefficient (RC) were used. The PSNR, NRMSE and SSIM for 2 min and S2 min PET images compared to 10min PET image were 30.983, 33.936, 9.954, 7.609 and 0.916, 0.934 respectively. The RC for spheres with S2 min PET image also met European Association of Nuclear Medicine Research Ltd. (EARL) FDG PET accreditation program. We confirmed generated S2 min PET image from N2V deep learning showed improvement results compared to 2 min PET image and The PET images on visual analysis were also comparable between 10 min and S2 min PET images. In conclusion, noisy PET image by means of short acquisition time using N2V denoising network model can be improved image quality without underestimation of radioactivity.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.58 no.2
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• pp.130-140
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• 2022

Recently, wideband acoustic technology has been introduced and started to be used in fisheries acoustic surveys in various waters worldwide. Wideband acoustic data provides high vertical resolution, high signal-to-noise ratio and continuous frequency characteristics over a wide frequency range for species identification. In this study, the main characteristics of wideband acoustic systems were elaborated, and a general methodology for wideband acoustic data analysis was presented using data collected in frequency modulation mode for the first time in Republic of Korea. In particular, this study described the data recording method using the mission planner of the wideband autonomous acoustic system, wideband acoustic data signal processing, calibration and the wideband frequency response graph. Since wideband acoustic systems are currently installed on many training and research vessels, it is expected that the results of this study can be used as basic knowledge for fisheries acoustic research using the state-of-the-art system.

• Smart Structures and Systems
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• v.32 no.5
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• pp.319-338
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• 2023

The study presents a new hybrid data-driven method by combining radial basis functions neural networks (RBF-NN) with the Jaya algorithm (JA) to provide effective structural health monitoring of arch dams. The novelty of this approach lies in that only one user-defined parameter is required and thus can increase its effectiveness and efficiency, as compared to other machine learning techniques that often require processing a large amount of training and testing model parameters and hyper-parameters, with high time-consuming. This approach seeks rapid damage detection in arch dams under dynamic conditions, to prevent potential disasters, by utilizing the RBF-NNN to seamlessly integrate the dynamic elastic modulus (DEM) and modal parameters (such as natural frequency and mode shape) as damage indicators. To determine the dynamic characteristics of the arch dam, the JA sequentially optimizes an objective function rooted in vibration-based data sets. Two case studies of hyperbolic concrete arch dams were carefully designed using finite element simulation to demonstrate the effectiveness of the RBF-NN model, in conjunction with the Jaya algorithm. The testing results demonstrated that the proposed methods could exhibit significant computational time-savings, while effectively detecting damage in arch dam structures with complex nonlinearities. Furthermore, despite training data contaminated with a high level of noise, the RBF-NN and JA fusion remained the robustness, with high accuracy.

• JSTS:Journal of Semiconductor Technology and Science
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• v.15 no.4
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• pp.506-517
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• 2015

This paper presents a 1.248 Gb/s - 2.918 Gb/s low-power receiver MIPI-DigRF M-PHY with a fully digital frequency detection loop. MIPI-DigRF M-PHY should be operated in a very short training time which is $0.01{\mu}s$ the for HS-G2B mode. Because of this short SYNC pattern, clock and data recovery (CDR) should have extremely fast locking time. Thus, the quarter rate CDR with a fully digital frequency detection loop is proposed to implement a fast phase tracking loop. Also, a low power CDR architecture, deserializer and voltage controlled oscillator (VCO) are proposed to meet the low power requirement of MIPI-DigRF M-PHY. This chip is fabricated using a $0.11{\mu}m$ CMOS process, and the die area is $600{\mu}m{\times}250{\mu}m$. The power consumption of the receiver is 16 mW from the supply voltage of 1.1 V. The measured lock time of the CDR is less than 20 ns. The measured rms and peak jitter are $35.24ps_{p-p}$ and $4.25ps_{rms}$ respectively for HS-G2 mode.

• Journal of the HCI Society of Korea
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• v.1 no.1
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• pp.29-36
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• 2006

Tactile displays can provide useful information without disturbing others and are particularly useful for people with visual or auditory impairments. They can also complement other displays. In this paper, we present a new vibrotactile display device for wearable, mobile, and ubiquitous computing environments. The proposed vibrotactile device has a $5{\times}5$ array configuration for displaying complex information such as letters, numbers, and haptic patterns as well as simple directional ques and situation awareness alarms. Commercially available coin-type vibration motors are embedded vertically in flexible mounting pads in order to best localize vibrations on the skin. An embedded microprocessor controls the motors sequentially with an advanced tracing mode to increase recognition rate. User studies with the vibrotactile device on the top of the foot show 86.7% recognition rate for alphabet characters after some training. In addition, applying vibrotactile device to driving situation shows 83.9% recognition rate. We also propose some potentially useful application scenarios including Caller Identification for mobile phones and Navigation Aids for GPS systems while driving.

• Journal of Broadcast Engineering
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• v.24 no.5
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• pp.791-801
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• 2019

The serial arc is one of factors causing electrical fires. Over past decades, various researches have been carried out to detect arc occurrences. Even though frequency analysis, wavelet and statistical features have been used, arc detection performance is degraded due to diverse arc waveforms. Therefore, there is a need to develop a method that could increase the feature dimension, thereby improving the detection performance. In this paper, we use variational mode decomposition (VMD) to obtain multiple decomposed signals and then extract statistical features from them. The features from VMD outperform those from no-VMD in terms of detection performance. Further, artificial neural network is employed as an arc classifier. Experiments validated that the use of VMD improves the classification accuracy by up to 4 percent, based on 14,000 training data.

• The Journal of the Korea Contents Association
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• v.21 no.10
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• pp.476-493
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• 2021

This study is on the simulation conditions of the tentative 'mobilization simulation mode'(MOBSM) and the setting option of major simulation elements. The MOBSM is a training module that practices mobilization of various institutions through a simulation computer similar to actual situations. So far, mobilization exercise(Mob-Ex) is a message simulation method, so it is necessary to convert into a MOBSM because many problems such as fragmentary and practice only by some institutions are raised. Therefore, the theoretical background and previous studies on Mob-Ex and simulation were reviewed to derive the requirements and simulated elements of the MOBSM to meet the purpose of government level exercise and to suggest the critical concepts and the direction of application. The basic requirement is to simulate the main mobilization practices by institution and provide information on the mobilization execution in a nationwide scope. The simulation elements are simulated events and flow charts by mobilization type, simulated range and level by object, simulated contents of material mobilization by institution, key simulated items, DB application, and simulated period, etc. This study will be useful for policy establishment and follow-up research for technology development of MOBSM in the future, and will accelerate the transition to practical mobilization exercise by MOBSM.

• Physical Therapy Korea
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• v.29 no.4
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• pp.262-268
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• 2022

Background: Virtual reality (VR) programs based on motion capture camera are the most convenient and cost-effective approaches for remote rehabilitation. Assessment of physical function is critical for providing optimal VR rehabilitation training; however, direct muscle strength measurement using camera-based kinematic data is impracticable. Therefore, it is necessary to develop a method to indirectly estimate the muscle strength of users from the value obtained using a motion capture camera. Objects: The purpose of this study was to determine whether the pedaling speed converted using the VR engine from the captured foot position data in the VR environment can be used as an indirect way to evaluate knee muscle strength, and to investigate the validity and reliability of a camera-based VR program. Methods: Thirty healthy adults were included in this study. Each subject performed a 15-second maximum pedaling test in the VR and built-in speedometer modes. In the VR speedometer mode, a motion capture camera was used to detect the position of the ankle joints and automatically calculate the pedaling speed. An isokinetic dynamometer was used to assess the isometric and isokinetic peak torques of knee flexion and extension. Results: The pedaling speeds in VR and built-in speedometer modes revealed a significantly high positive correlation (r = 0.922). In addition, the intra-rater reliability of the pedaling speed in the VR speedometer mode was good (ICC [intraclass correlation coefficient] = 0.685). The results of the Pearson correlation analysis revealed a significant moderate positive correlation between the pedaling speed of the VR speedometer and the peak torque of knee isokinetic flexion (r = 0.639) and extension (r = 0.598). Conclusion: This study suggests the potential benefits of measuring the maximum pedaling speed using 3D depth camera in a VR environment as an indirect assessment of muscle strength. However, technological improvements must be followed to obtain more accurate estimation of muscle strength from the VR cycling test.