• Advances in aircraft and spacecraft science
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• 제1권1호
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• pp.69-91
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• 2014

Numerical investigations are presented, which show that a back-flow flap can improve the dynamic stall characteristics of oscillating airfoils. The flap was able to weaken the stall vortex and therefore to reduce the peak in the pitching moment. This paper gives a brief insight into the method of function of a back-flow flap. Initial wind tunnel experiments were performed to define the structural requirements for a detailed experimental wind tunnel characterization. A structural integration concept and two different actuation mechanisms of a back-flow flap for a helicopter rotor blade are presented. First a piezoelectric actuation system was investigated, but the analytical model to estimate the performance showed that the displacement generated is too low to enable reliable operation. The seond actuation mechanism is based on magnetic forces to generate an impulse that initiates the opening of the flap. A concept based on two permanent magnets is further detailed and characterized, and this mechanism is shown to generate sufficient impulse for reliable operation in the wind tunnel.

• 전력전자학회논문지
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• 제8권2호
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• pp.107-115
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• 2003

PMSM은 높은 토크 특성과 우수한 전력 밀도, 논은 효율 때문에 산업용 빛 가정용 기기로 널리 사용되고 있다. PMSM의 우수한 제어 수행을 위해서는 회전자 위치의 정확한 정보가 필요하다. 그러나 위치 센서의 가격이 비싸고, 열악한 환경에서 신뢰도가 떨어지기 때문에 최근에는 센서리스 알고리즘에 대한 연구가 많이 진행되고 있다. 본 논문에서는 회전자 위치의 추정을 위해 쇄교 자속의 도함수를 이용한다. 수치적 미분을 행하지 않고 전압 방정식과 측정된 상전류를 이용한 수식적 미분을 통해 쇄교 자속을 구하는 a-$\beta$ 변환과 수식적 미분을 이용한 새로운 센서리스 알고리즘을 제안한다. 제안된 센서리스 속도 제어 알고리즘이 실험을 통해 증명된다.

• 한국자동차공학회논문집
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• 제24권4호
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• pp.408-415
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• 2016

The vehicle attitude and sideslip is critical information to control the vehicle to prevent from unintended motion. Many of estimation strategy use bicycle model or IMU integration, but both of them have limits on application. The main purpose of this paper is development of vehicle orientation estimator which is robust to various vehicle state and road shape. The suggested estimator use 3-axis magnetometer, yaw rate sensor and lateral acceleration sensor to estimate three Euler angles of vehicle. The estimator is composed of two individual observers: First, comparing the known magnetic field and gravity with measured value, the TRIAD algorithm calculates optimal rotational matrix when vehicle is in static or quasi-static condition. Next, merging 3-axis magnetometer with inertial sensors, the extended Kalman filter is used to estimate vehicle orientation under dynamic condition. A validation through simulation tools, Carsim and Simulink, is performed and the results show the feasibility of the suggested estimation method.

• 한국전기전자재료학회논문지
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• 제14권11호
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• pp.912-916
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• 2001

Fluxmeter is a measuring instrument the magnetic flux intensity by means of an integration of the voltage induced to a search coil to unit time. It also is required to a precise integrator since the voltage induced to a search coil has a differential value of the flux ${\Phi}$ to unit time. In this study, a bias current which is a main problem of the integrator in a drift troublesome depending on the temperature of a FET is investigated. We have confirmed that the temperature dependence of both the bias current of a integrator using the FET and the reversal saturated current of the minor carrier in a P-N junction of a semiconductor were the same. The property of a commercial integrator goes rapidly down with increasing temperature. The bias current of a FET is increased twice as much with 10$^{\circ}C$ increment. As a result, the low drift integrator could be developed by setting the lower temperature up with a pottier device.

• Applied Microscopy
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• 제50권
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• pp.25.1-25.11
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• 2020

Scanning acoustic microscopy (SAM) or Acoustic Micro Imaging (AMI) is a powerful, non-destructive technique that can detect hidden defects in elastic and biological samples as well as non-transparent hard materials. By monitoring the internal features of a sample in three-dimensional integration, this technique can efficiently find physical defects such as cracks, voids, and delamination with high sensitivity. In recent years, advanced techniques such as ultrasound impedance microscopy, ultrasound speed microscopy, and scanning acoustic gigahertz microscopy have been developed for applications in industries and in the medical field to provide additional information on the internal stress, viscoelastic, and anisotropic, or nonlinear properties. X-ray, magnetic resonance, and infrared techniques are the other competitive and widely used methods. However, they have their own advantages and limitations owing to their inherent properties such as different light sources and sensors. This paper provides an overview of the principle of SAM and presents a few results to demonstrate the applications of modern acoustic imaging technology. A variety of inspection modes, such as vertical, horizontal, and diagonal cross-sections have been presented by employing the focus pathway and image reconstruction algorithm. Images have been reconstructed from the reflected echoes resulting from the change in the acoustic impedance at the interface of the material layers or defects. The results described in this paper indicate that the novel acoustic technology can expand the scope of SAM as a versatile diagnostic tool requiring less time and having a high efficiency.

• International Journal of Computer Science & Network Security
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• 제24권1호
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• pp.9-16
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• 2024

AI or Artificial Intelligence has been a significant tool used in the organisational backgrounds for an effective improvement in the management methods. The processing of the information and the analysis of the data for the further achievement of heightened efficiency can be performed by AI through its data analytics measures. In the medical field, AI has been integrated for an improvement within the management of the medical services and to note a rise in the levels of customer satisfaction. With the benefits of reasoning and problem solving, AI has been able to initiate a range of benefits for both the consumers and the medical personnel. The main benefits which have been noted in the integration of AI would be integrated into the study. The issues which are noted with the integrated AI usage for the medical sector would also be identified in the study. Medical Image Processing has been seen to integrate 3D image datasets with the medical industry, in terms of Computed Tomography (CT) or Magnetic Resonance Imaging (MRI). The usage of such medical devices have occurred in the diagnosis of the patients, the development of guidance towards medical intervention and an overall increase in the medical efficiency. The study would focus on such different tools, adhered with AI for increased medical improvement.

• Advances in nano research
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• 제16권2호
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• pp.155-164
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• 2024

The rapid evolution of intelligent sports equipment and gadgets has led to the transformation of smartphones into personalized coaching devices. This transformative role is central in today's technologically advanced landscape, addressing the needs of individuals with contemporary lifestyles. The development of intelligent sports gadgets is geared towards elevating overall quality of life by facilitating sports activities, workouts, and promoting health preservation. This categorization yields two primary types of devices: smart sports devices for exercise and smart health control devices, which encompass functionalities such as blood pressure monitoring and muscle volume measurement. Illustrative examples include smart headbands, smart socks, smart wristbands, and smart shoe soles. Significantly, the global market for smart sports devices has garnered substantial popularity among enthusiasts. Moreover, the integration of sensors within these devices has instigated a revolution in group and professional sports, facilitating the calculation of impact intensity and ball speed. The utilization of various types of smart sports equipment has proliferated, encompassing applications in both sports' performance and health monitoring across diverse demographics. This article conducts an assessment of the application of nanotechnology in the continuous modeling of the magnetic electromechanical sensor integrated within smart shoe soles, with a specific emphasis on its implementation in soccer training. The exploration delves into the nuanced intersection of nanotechnology and sports equipment, elucidating the intricate mechanisms that underlie the transformative impact of these advancements.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권8호
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• pp.2082-2102
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• 2024

Accurate segmentation of magnetic resonance (MR) images is crucial for providing doctors with effective quantitative information for diagnosis. However, the presence of weak boundaries, intensity inhomogeneity, and noise in the images poses challenges for segmentation models to achieve optimal results. While deep learning models can offer relatively accurate results, the scarcity of labeled medical imaging data increases the risk of overfitting. To tackle this issue, this paper proposes a novel fuzzy c-means (FCM) model that integrates a deep learning approach. To address the limited accuracy of traditional FCM models, which employ Euclidean distance as a distance measure, we introduce a measurement function based on the skewed normal distribution. This function enables us to capture more precise information about the distribution of the image. Additionally, we construct a regularization term based on the Kullback-Leibler (KL) divergence of high-confidence deep learning results. This regularization term helps enhance the final segmentation accuracy of the model. Moreover, we incorporate orthogonal basis functions to estimate the bias field and integrate it into the improved FCM method. This integration allows our method to simultaneously segment the image and estimate the bias field. The experimental results on both simulated and real brain MR images demonstrate the robustness of our method, highlighting its superiority over other advanced segmentation algorithms.

• Journal of Animal Science and Technology
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• 제64권4호
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• pp.800-811
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• 2022

The integration of metabolomics and transcriptomics may elucidate the correlation between the genotypic and phenotypic patterns in organisms. In equine physiology, various metabolite levels vary during exercise, which may be correlated with a modified gene expression pattern of related genes. Integrated metabolomic and transcriptomic studies in horses have not been conducted to date. The objective of this study was to detect the effect of moderate exercise on the metabolomic and transcriptomic levels in horses. In this study, using nuclear magnetic resonance (NMR) spectroscopy, we analyzed the concentrations of metabolites in muscle and plasma; we also determined the gene expression patterns of branched chain (alpha) keto acid dehydrogenase kinase complex (BCKDK), which encodes the key regulatory enzymes in branched-chain amino acid (BCAA) catabolism, in two breeds of horses, Thoroughbred and Jeju, at different time intervals. The concentrations of metabolites in muscle and plasma were measured by ¹H NMR (nuclear magnetic resonance) spectroscopy, and the relative metabolite levels before and after exercise in the two samples were compared. Subsequently, multivariate data analysis based on the metabolic profiles was performed using orthogonal partial least square discriminant analysis (OPLS-DA), and variable important plots and t-test were used for basic statistical analysis. The stress-induced expression patterns of BCKDK genes in horse muscle-derived cells were examined using quantitative reverse transcription polymerase chain reaction (qPCR) to gain insight into the role of transcript in response to exercise stress. In this study, we found higher concentrations of aspartate, leucine, isoleucine, and lysine in the skeletal muscle of Jeju horses than in Thoroughbred horses. In plasma, compared with Jeju horses, Thoroughbred horses had higher levels of alanine and methionine before exercise; whereas post-exercise, lysine levels were increased. Gene expression analysis revealed a decreased expression level of BCKDK in the post-exercise period in Thoroughbred horses.

• 한국측량학회지
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• 제27권2호
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• pp.225-234
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• 2009

실시간 공중 자료획득 시스템은 긴급상황에서 DEM, 정사영상과 같은 공간정보를 실시간으로 생성하기 위해 빠른 자료 수집을 수행하는 시스템이다. 이러한 시스템에서 GPS와 INS는 플랫폼의 위치와 자세정보를 획득 하는데 중요한 역할을 한다. 그러므로 이번 연구에서는 실시간 공중 자료획득 시스템에 장착될 GPS/MEMS IMU 센서의 성능을 평가하였다. 그리고 시뮬레이션 데이터를 통하여 실시간 자료 수집에 더욱 적절한 GPS/INS 통합 알고리즘을 확인하였다. 정지 상태와 이동 상태에서의 GPS/MEMS IMU 센서 성능 평가 결과 각각 3$\sim$4m, 2$\sim$3m의 위치오차를 확인하였다. 또한 자기장 센서를 사용하는 Aerospace 모드에서 더 높은 정밀도의 자세 결과를 확인하였다. EKF와 UKF의 비교에서는 직선 뿐만 아니라 곡선에서도 많은 차이를 보이지 않았다. 하지만 계산 시간에서 EKF가 UKF에 비하여 약 25배 빠르므로 실시간 공중 자료획득 시스템의 GPS/INS 통합 알고리즘에는 EKF가 더욱 적합한 것으로 판단된다.