• 대한의용생체공학회:의공학회지
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• 제26권4호
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• pp.243-249
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• 2005

The number of people who have lost limbs due to amputation has increased due to various accidents and diseases. Numerous attempts have been made to provide these people with prosthetic devices. These devices are often controlled using myoelectric signals. Although the success of fitting myoelectric signals (EMG) for single device control is apparent, extension of this control to more than one device has been difficult. The lack of success can be attributed to inadequate multifunctional control strategies. Therefore, the objective of this study was to develop multifunctional myoelectric control strategies that can generate a number of output control signals. We demonstrated the feasibility of a neural network classification control method that could generate 12 functions using three EMG channels. The results of evaluating this control strategy suggested that the neural network pattern classification method could be a potential control method to support reliability and convenience in operation. In order to make this artificial neural network control technique a successful control scheme for each amputee who may have different conditions, more investigation of a careful selection of the number of EMG channels, pre-determined contractile motions, and feature values that are estimated from the EMG signals is needed.

• International Journal of Naval Architecture and Ocean Engineering
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• 제11권2호
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• pp.980-992
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• 2019

This paper describes a model test and numerical simulation of a 750-kW-semi-submersible platform wind turbine under several wind and wave conditions for validation of the numerical simulation model. The semi-submersible platform was designed to support the 750-kW-wind turbine class and operate at a water depth of 50 m. The model tests were performed to estimate the performance characteristics of the wind turbine system in the wide tank of the University of Ulsan. Motions and loads of the wind turbine system under the wind and wave conditions were measured and analyzed. The NREL-FAST code was used to simulate the wind turbine system, and the results were compared with those of the test model. The results demonstrate that the numerical simulation captures noticeably the fully coupled floating wind turbine dynamic responses. Also, the model shows a good stability and small responses during waves, wind, and operation of the 750-kW-floating offshore wind turbine.

• 전산구조공학
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• 제11권1호
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• pp.179-190
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• 1998

두개의 케이블요소를 이용한 3차원 케이블망의 정적 비선형 유한요소해석기법을 제시한다. 먼저, 공간 트러스요소와 탄성현수선 케이블요소(elastic catenary cable element)의 접선강도행렬과 질량행렬을 유도하는 과정을 간략히 요약한다. 지점 변위를 일으키고 자중을 받는 케이블망의 초기평형 상태를 결정하기 위하여, Newton-Raphson 반복법에 근거한 하중증분법과 현수케이블요소를 적용하는 경우에 viscous damping을 고려한 dynamic relaxation법을 제시한다. 또한 초기의 정적평형상태를 기준으로 추가하중에 대한 케이블망의 정적 비선형해석을 수행한다. 지점변위와 외력을 받는 케이블 구조에 대하여 비선형해석을 수행하고, 해석결과들을 기존의 문헌의 결과와 비교, 검토하므로써 본 논문에서 제시한 이론 및 해석방법의 타당성을 입증한다.

• 한국해양공학회지
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• 제22권2호
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• pp.20-27
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• 2008

A moon-pool is a vertical well in a floating barge, drilling ship, or offshore support vessel. In this study, numerical simulation of two-dimensional moon-pool flaw coupled with a ship's motion in waves is carried out using a particle method, the so-called MPS method. The particle method, which is recognized as one of the gridless methods, was developed to investigate nonlinear free-surface motions interacting with structures. The method is more feasible and effective than convectional grid methods in order to solve a flaw field with complicated boundary shapes.

• Nuclear Engineering and Technology
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• 제51권3호
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• pp.894-903
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• 2019

An approach for collapse risk assessment is proposed to evaluate the vulnerability of electric cabinet in nuclear power plants. The lognormal approaches, namely maximum likelihood estimation and linear regression, are introduced to establish the fragility curves. These two fragility analyses are applied for the numerical models of cabinets considering various boundary conditions, which are expressed by representing restrained and anchored models at the base. The models have been built and verified using the system identification (SI) technique. The fundamental frequency of the electric cabinet is sensitive because of many attached devices. To bypass this complex problem, the average spectral acceleration $S_{\bar{a}}$ in the range of period that cover the first mode period is chosen as an intensity measure on the fragility function. The nonlinear time history analyses for cabinet are conducted using a suite of 40 ground motions. The obtained curves with different approaches are compared, and the variability of risk assessment is evaluated for restrained and anchored models. The fragility curves obtained for anchored model are found to be closer each other, compared to the fragility curves for restrained model. It is also found that the support boundary conditions played a significant role in acceleration response of cabinet.

• Structural Engineering and Mechanics
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• 제71권4호
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• pp.445-458
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• 2019

This study mainly aims to assess the performance of soil-structure systems designed by direct displacement-based method coupled with strong column-weak beam design concept through various system identification techniques under strong ground motions. To this end, various system identification methods are employed to evaluate the dynamic characteristics of a structure (i.e., modal frequency, system damping, mode shapes, and plastic hinge formation pattern) under a strong seismic excitation considering soil-structure interaction for different site conditions as specified by ASCE 7-10. The scope of the study narrowed down to the code-complying low- to high-rise steel moment resisting frames with various heights (4, 8, 12, 16-story). The comparison of the result of soil-structure systems with fix-based support condition indicates that the modal frequencies of these systems are highly influenced by the structure heights, specifically for the softer soils. This trend is more significant for higher modes of the system which can considerably dominate the response of structures in which the higher modes have more contribution in dynamic response. Amongst all studied modes of the vibration, the damping ratio estimated for the first mode is relatively the closet to the initial assumed damping ratios. Moreover, it was found that fewer plastic hinges are developed in the structure of soil-structure systems with a softer soil which contradicts the general expectation of higher damageability of such structural systems.

• 대한의용생체공학회:의공학회지
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• 제42권4호
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• pp.186-192
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• 2021

In this paper, we evaluated prediction accuracy of Euler angle spectrograph classification method using a convolutional neural networks (CNN) for hand gesture recognition in augmented reality (AR) cognitive rehabilitation system based on Leap Motion Controller (LMC). Hand gesture recognition methods using a conventional support vector machine (SVM) show 91.3% accuracy in multiple motions. In this paper, five hand gestures ("Promise", "Bunny", "Close", "Victory", and "Thumb") are selected and measured 100 times for testing the utility of spectral classification techniques. Validation results for the five hand gestures were able to be correctly predicted 100% of the time, indicating superior recognition accuracy than those of conventional SVM methods. The hand motion recognition using CNN meant to be applied more useful to AR cognitive rehabilitation training systems based on LMC than sign language recognition using SVM.

• 천문학회보
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• 제46권1호
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• pp.56.2-56.2
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• 2021

Constraining the structure and thus the fate of giant molecular clouds (GMCs), the primary sites of star formation in galaxies, is crucial to understand the evolution of galaxies themselves. Exploiting the unprecedented sensitivity and angular resolution of the Atacama Large Millimeter/sub-millimeter Array (ALMA), we have measured the spatially-resolved (~ 20 pc resolution) properties of the GMCs in two nearby late-type galaxies, NGC 5806 (SAB(s)b) and NGC 6753 ((R)SA(r)b), as part of the WISDOM project. Although these results are preliminary, we identified ~ 200 resolved GMCs in NGC 5806 within a radius of 500 pc, most within a nuclear ring structure, and ~ 400 resolved GMCs in NGC 6753 within a radius of 2 kpc, most within a flocculent spiral structure. The GMCs of NGC 5806 have similar sizes but slightly higher linewidths than clouds in the Milky Way disc. Because the GMCs also have higher surface densities, the calculated cloud Virial parameters are nevertheless about unity, suggesting that the GMCs of NGC 5806 are in gravitational equilibrium and thus long lived. This is contrary to other WISDOM results on earlier-type galaxies, where large cloud linewidths are likely due to shear associated with the local (circular) orbital motions (rather than the clouds' self-gravity), and the clouds are either marginally or not gravitationally bound. These results support the notion that spheroids alter the dynamical states of clouds (morphological quenching), that are otherwise (i.e. in galaxy discs) fairly homogenous and similar to those of the Milky Way.

• Geomechanics and Engineering
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• 제37권6호
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• pp.539-554
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• 2024

This study explores development of prediction model for seismic site classification through the integration of machine learning techniques with horizontal-to-vertical spectral ratio (HVSR) methodologies. To improve model accuracy, the research employs outlier detection methods and, synthetic minority over-sampling technique (SMOTE) for data balance, and evaluates using seven machine learning models using seismic data from KiK-net. Notably, light gradient boosting method (LGBM), gradient boosting, and decision tree models exhibit improved performance when coupled with SMOTE, while Multiple linear regression (MLR) and Support vector machine (SVM) models show reduced efficacy. Outlier detection techniques significantly enhance accuracy, particularly for LGBM, gradient boosting, and voting boosting. The ensemble of LGBM with the isolation forest and SMOTE achieves the highest accuracy of 0.91, with LGBM and local outlier factor yielding the highest F1-score of 0.79. Consistently outperforming other models, LGBM proves most efficient for seismic site classification when supported by appropriate preprocessing procedures. These findings show the significance of outlier detection and data balancing for precise seismic soil classification prediction, offering insights and highlighting the potential of machine learning in optimizing site classification accuracy.

• 한국정보과학회논문지:소프트웨어및응용
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• 제32권3호
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• pp.215-226
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• 2005

루프 불변 코드 이동(loop invariant code motion, LICM) 컴파일러 최적화는 비교적 많은 분석 작업을 필요로 하기 때문에 컴파일 시간이 수행 시간의 일부가 되는 자바 적시(Just-In-Time) 컴파일러에는 사용하기 쉽지 않다. "전통적인" LICM 기법에서는 보통 코드를 분석하여 레지스터의 정의-사용체인과 사용-정의 체인을 미리 만든 뒤 이를 바탕으로 코드 이동을 수행하는 데, 본 논문은 자바 가상 머신(Java virtual machine)이 스택 머신 (stack machine)이라서 좀 더 단순한 코드 형태를 생성한다는 특징을 이용하여 정의-사용 체인을 루프 불변 코드에 대해서만 만들고 사용-정의 체인 없이도 정확히 동작하는 알고리즘을 제시한다. 또한 기존의 방식보다 더 많은 루프 불변 코드 이동을 하게 하는 두 가지 방법을 제시한다. 우선, 간단하기 때문에 루프에 경로가 하나인 경우만 LICM을 적용하는 기존의 기법과 달리, 경로가 여러 개인 루프에서도 부분적으로 중복되는 코드에 대해서도 LICM을 안전하게 적용한다. 또한 부분적으로 중복되는 루프 불변 널(null) 포인터 체크 코드도 Itanium의 조건 수행(predication)을 이용하여 이동시키다. 제안된 기법은 Itanium 마이크로프로세서를 위한 인텔의 ORP(Open Runtime Platform) 자바 가상 머신 위의 적시 컴파일러에 구현하였다. SPECjvm98 벤치마크에 대해 실험을 수행한 결과 전체 적시 컴파일 시간을 1.3％ 정도만을 증가시켰지만 전체 수행 시간을 기하 평균으로 2.2％ 향상 시켰다.