• 한국해안·해양공학회논문집
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• 제25권5호
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• pp.285-290
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• 2013

선형과 천해 edge wave로 구분되는 이들의 거동을 더 잘 이해하기 위해 비교하였다. 본 연구에서는 변수분리법을 사용하여, Ursell (1952)이 해의 유도과정 없이 제시한, 선형 edge wave의 해를 얻었다. 천해 edge wave는 비록 천해방정식으로부터 유도되지만 분산특성을 갖는다. 완만한 해저경사의 경우, 천해 파형은 선형 파형과 거의 같게 되고 천해 파형은 다루기가 쉬운 장점이 있다. Gaussian 분포형태의 이동체에 의해 생성되는 edge wave를 계산하기 위해 천해 고유파형으로 전개한 해를 구성하였고, 이에 대한 결과를 제시하고 특성을 기술하였다.

• 한국지능시스템학회논문지
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• 제22권6호
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• pp.793-798
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• 2012

In this paper, we explored the new method for extracting feature from the electroencephalography (EEG) signal based on linear regression technique with the orthonormal polynomial bases. At first, EEG signals from electrodes around motor cortex were selected and were filtered in both spatial and temporal filter using band pass filter for alpha and beta rhymic band which considered related to the synchronization and desynchonization of firing neurons population during motor imagery task. Signal from epoch length 1s were fitted into linear regression with Legendre polynomials bases and extract the linear regression weight as final features. We compared our feature to the state of art feature, power band feature in binary classification using support vector machine (SVM) with 5-fold cross validations for comparing the classification accuracy. The result showed that our proposed method improved the classification accuracy 5.44% in average of all subject over power band features in individual subject study and 84.5% of classification accuracy with forward feature selection improvement.

• Journal of information and communication convergence engineering
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• 제22권2호
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• pp.165-171
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• 2024

In this study, we present a novel approach for enhancing chest X-ray image classification (normal, Covid-19, edema, mass nodules, and pneumothorax) by combining contrastive learning and machine learning algorithms. A vast amount of unlabeled data was leveraged to learn representations so that data efficiency is improved as a means of addressing the limited availability of labeled data in X-ray images. Our approach involves training classification algorithms using the extracted features from a linear fine-tuned Momentum Contrast (MoCo) model. The MoCo architecture with a Resnet34, Resnet50, or Resnet101 backbone is trained to learn features from unlabeled data. Instead of only fine-tuning the linear classifier layer on the MoCopretrained model, we propose training nonlinear classifiers as substitutes for softmax in deep networks. The empirical results show that while the linear fine-tuned ImageNet-pretrained models achieved the highest accuracy of only 82.9% and the linear fine-tuned MoCo-pretrained models an increased highest accuracy of 84.8%, our proposed method offered a significant improvement and achieved the highest accuracy of 87.9%.

• 대한지리학회:학술대회논문집
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• 대한지리학회 2005년도 춘계학술대회
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• pp.37-39
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• 2005

• 비파괴검사학회지
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• 제29권6호
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• pp.563-569
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• 2009

In this paper, four different types of pulsed eddy current(PEC) probe are designed and their performance of detecting wall thickness reduction is compared. By using the backward difference method in time and the finite element method in space, PEC signals from various thickness and materials are numerically calculated and three features of the signal are selected. Since PEC signals and features are obtained by various types and sizes of probe, the comparison is made through the normalized features which reflect the sensitivity of the feature to thickness reduction. The normalized features indicate that the shielded reflection probe provides the best sensitivity to wall thickness reduction for all three signal features. Results show that the best sensitivity to thickness reduction can be achieved by the peak value, but also suggest that the time to peak can be a good candidate because of its linear relationship with the thickness variation.

• Journal of Biosystems Engineering
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• 제19권4호
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• pp.380-396
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• 1994

A personal computer based color machine vision system with video camera and fluorescent lighting system was used to generate images of stationary tobacco leaves. Image processing algorithms were developed to extract both the geometric and the color features of tobacco leaves. Geometric features include area, perimeter, centroid, roundness and complex ratio. Color calibration scheme was developed to convert measured pixel values to the standard color unit using both statistics and artificial neural network algorithm. Improved back propagation algorithm showed less sum of square errors than multiple linear regression. Color features provide not only quality evaluation quantities but the accurate color measurement. Those quality features would be useful in grading tobacco automatically. This system would also be useful in measuring visual features of other agricultural products.

• 융합신호처리학회논문지
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• 제13권3호
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• pp.136-141
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• 2012

운전 중 운전자의 졸음은 교통 사망사고를 일으키는 중요한 요인이며 음주운전보다도 더 위험할 수 도 있다. 이러한 이유로 운전자의 졸음을 판별하고 경고하는 시스템 개발이 최근에 매우 중요한 이슈로 떠올랐다. 그중에서도 졸음과 가장 밀접한 관련이 있는 생체 신호인 뇌파 (Electroencephalogram, EEG)와 안구전도 (Electrooculogram, EOG)를 분석하는 연구가 주류를 이루고 있다. 본 논문에서는 실험 프로토콜에 의거하여 측정된 뇌파를 주파수별로 분석하여 운전자의 상태별 뇌파 데이터베이스를 구축하고 선형예측(Linear Predictive coding, LPC) 계수를 특징벡터로 한 신경회로망 기반 운전자 졸음 감지 시스템을 제안한다. 실험결과로 졸음의 뇌파분석에서 알파파가 감소하며 세타파가 증가하는 추세를 보였으며, LPC 계수가 각성, 졸음 및 수면상태의 특징을 잘 반영하였다. 특히 제안한 시스템은 적은 샘플(250ms)을 가지고도 96.5%라는 높은 분류 결과를 얻어 짧은 순간에 일어날 수 있는 운전 시 돌발 상황을 실시간으로 검출 가능성을 확인하였다.

• Journal of applied mathematics & informatics
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• 제10권1_2호
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• pp.17-26
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• 2002

A stability analysis of a non-linear prey-predator system under the influence of one dimensional diffusion has been investigated to determine the nature of the bifurcation point of the system. The non-linear bifurcation analysis determining the steady state solution beyond the critical point enables us to determine characteristic features of the spatial inhomogeneous pattern arising out of the bifurcation of the state of the system.

• Journal of Mechanical Science and Technology
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• 제20권2호
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• pp.205-211
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• 2006

Among other critical conditions in rotor systems the large non-linear vibration excited by bearing non-linearity causes the rotor failure. For reducing this catastrophic failure and predictive detection of this phenomenon the analysis of orthotropic bearing non-linearity in rotor system using higher order frequency response functions (HFRFs) is conducted and is shown to be theoretically feasible as that of non-rotating structures. The complex HFRFs based on the Volterra series are newly developed for the process and investigated their features by using the simple forms of the FRFs associated with the forward and the backward modes.

• Korean Journal of Geomatics
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• 제5권1호
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• pp.7-19
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• 2005

Photogrammetric mapping procedures have gone through major developments due to significant improvements in its underlying technologies. The availability of GPS/INS systems greatly assist in direct geo-referencing of the acquired imagery. Still, photogrammetric datasets taken without the aid of positioning and navigation systems need control information for the purpose of surface reconstruction. Point features were, and still are, the primary source of control for the photogrammetric triangulation although other higher-order features are available and can be used. LIDAR systems supply dense geometric surface information in the form of three dimensional coordinates with respect to certain reference system. Considering the accuracy improvement of LIDAR systems in the recent years, LIDAR data is considered a viable supply of photogrammetric control. To exploit LIDAR data, new challenges are poised concerning the representation and reference system by which both the photogrammetric and LIDAR datasets are described. In this paper, registration methodologies will be devised for the purpose of integrating the LIDAR data into the photogrammetric triangulation. Such registration methodologies have to deal with three issues: registration primitives, transformation parameters, and similarity measures. Two methodologies will be introduced that utilize straight-line and areal features derived from both datasets as the registration primitives. The first methodology directly incorporates the LIDAR lines as control information in the photogrammetric triangulation, while in the second methodology, LIDAR patches are used to produce and align the photogrammetric model. Also, camera self-calibration experiments were conducted on simulated and real data to test the feasibility of using LIDAR patches for this purpose.