• Structural Engineering and Mechanics
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• 제72권6호
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• pp.775-783
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• 2019

The present study deals with the numerical analysis of the symmetric contact problem of two bonded layers resting on an elastic half plane compressed with a rigid punch. In this context, Finite Element Method (FEM) based software called ANSYS and ABAQUS are used. It is assumed that the elastic layers have different elastic constants and heights and the external load is applied to the upper elastic layer by means of a rigid stamp. The problem is solved under the assumptions that the contact between two elastic layers, and between the rigid stamp are frictionless, the effect of gravity force is neglected. To validate the constructed model and obtained results a comparison is performed with the analytical results in literature. The numerical results for normal stresses and shear stresses are obtained for various parameters of load, material and geometry and are tabulated and illustrated.

• 한국전자통신학회논문지
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• 제11권2호
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• pp.215-222
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• 2016

걸음 인식과 그 활용에 대하여 연구가 활발하게 진행되고 있다. 본 연구는 보행자의 비정상적인 보행을 인식하는 방안을 제안한다. 기존의 정상적인 걸음을 인식하는 것이 신체활동을 측정하거나, 인증을 위한 것이었다면, 본 연구의 비정상적인 걸음 인지는 보행자의 생활안전 보장을 위한 것이다. 보행자가 스스로 자신의 취약한 상태를 인지하고 도움을 요청하지 못하는 상황이 있기 때문에, 근래의 IoT기술을 도입하여 본인의 인지와 자발적 도움 요청이 없더라도 위험과 어려움을 벗어날 수 있도록 하고자 함이다. 이에 본 연구는 3축 가속도 센서를 활용하여 보행자의 정상적인 걸음을 분석함으로써 정상적인 걸음이 유지되는 상태에 대한 범위를 정하고, 이후 3축 가속도 센서를 활용하여 걸음을 측정하여 그 결과를 정상적인 걸음 범위에 대조하여 정상과 비정상 여부를 판단하도록 한다. 정상적인 걸음을 유지하는 상태를 벗어날 때, 이를 비정상적인 걸음으로 인지하는 방안을 제안한다.

• Smart Structures and Systems
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• 제29권6호
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• pp.757-766
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• 2022

To train deep learning algorithms, a sufficient number of data are required. However, in most engineering systems, the acquisition of fault data is difficult or sometimes not feasible, while normal data are secured. The dearth of data is one of the major challenges to developing deep learning models, and fault diagnosis in particular cannot be made in the absence of fault data. With this context, this paper proposes an anomaly detection methodology for rotating machines using only normal data with self-labeling. Since only normal data are used for anomaly detection, a self-labeling method is used to generate a new labeled dataset. The overall procedure includes the following three steps: (1) transformation of normal data to self-labeled data based on a pretext task, (2) training the convolutional neural networks (CNN), and (3) anomaly detection using defined anomaly score based on the softmax output of the trained CNN. The softmax value of the abnormal sample shows different behavior from the normal softmax values. To verify the proposed method, four case studies were conducted, on the Case Western Reserve University (CWRU) bearing dataset, IEEE PHM 2012 data challenge dataset, PHMAP 2021 data challenge dataset, and laboratory bearing testbed; and the results were compared to those of existing machine learning and deep learning methods. The results showed that the proposed algorithm could detect faults in the bearing testbed and compressor with over 99.7% accuracy. In particular, it was possible to detect not only bearing faults but also structural faults such as unbalance and belt looseness with very high accuracy. Compared with the existing GAN, the autoencoder-based anomaly detection algorithm, the proposed method showed high anomaly detection performance.

• 말소리와 음성과학
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• 제5권4호
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• pp.71-78
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• 2013

The purpose of this study was to compare the acoustic voice outcomes of children with cochlear implant to those of children with normal hearing. Participants were 41 children using unilateral cochlear implant (18 males and 23 females), and children with normal hearing from the same age and sex. Mean age of implantation was approximately 3 years old, mean duration of implant use was 4 years in CI group. Acoustic analyses were performed using MDVP of CSL. Speech samples were 3 sustained vowels, /a, i, u/. 9 parameters (F0, Fhi, Flo, Jitter, Shimmer, vF0, vAm, NHR, and SPI) were analyzed. Children with CI did not show the significant differences in those parameters after the vowel /a/ phonation. Meanwhile, there were significantly different results in F0, Fhi, vF0, and SPI after /i, u/ phonation. These results revealed that differences of voice characteristics in children with CI compare to children with NH persist regarding vowel context. It suggests that high vowels would recommend as speech samples for acoustic evaluation. Futhermore perceptual analysis and speech therapy for phonation control would be necessary for children with CI.

• Smart Structures and Systems
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• 제3권4호
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• pp.423-437
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• 2007

The empirical mode decomposition (EMD) method is well-known for its ability to decompose a multi-component signal into a set of intrinsic mode functions (IMFs). The method uses a sifting process in which local extrema of a signal are identified and followed by a spline fitting approximation for decomposition. This method provides an effective and robust approach for decomposing nonlinear and non-stationary signals. On the other hand, the IMF components do not automatically guarantee a well-defined physical meaning hence it is necessary to validate the IMF components carefully prior to any further processing and interpretation. In this paper, an attempt to use the EMD method to identify properties of nonlinear elastic multi-degree-of-freedom structures is explored. It is first shown that the IMF components of the displacement and velocity responses of a nonlinear elastic structure are numerically close to the nonlinear normal mode (NNM) responses obtained from two-dimensional invariant manifolds. The IMF components can then be used in the context of the NNM method to estimate the properties of the nonlinear elastic structure. A two-degree-of-freedom shear-beam building model is used as an example to illustrate the proposed technique. Numerical results show that combining the EMD and the NNM method provides a possible means for obtaining nonlinear properties in a structure.

• 스마트미디어저널
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• 제4권1호
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• pp.25-32
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• 2015

Powering wireless sensors with energy harvested from the environment is coming of age due to the increasing power densities of both storage and harvesting devices and the electronics performing energy efficient energy conversion. In order to maximize the functionality of the wireless sensor network, minimize missing packets, minimize latency and prevent the waste of energy, problems like congestion and inefficient energy usage must be addressed. Many sleep-awake protocols and efficient message priority techniques have been developed to properly manage the energy of the nodes and to minimize congestion. For a WSN that is operating in a strictly energy constrained environment, an energy-efficient transmission strategy is necessary. In this paper, we present a novel transmission priority decision scheme for a heterogeneous body sensor network composed of normal nodes and an energy harvesting node that acts as a cluster head. The energy harvesting node's decision whether or not to clear a normal node for sending is based on a set of metrics which includes the energy harvesting node's remaining energy, the total harvested energy, the type of message in a normal node's queue and finally, the implementation context of the wireless sensor network.

• 한국컴퓨터정보학회논문지
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• 제8권1호
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• pp.103-113
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• 2003

프로그램 행위 침입 탐지 기법은 데몬 프로그램이나 루트 권한으로 실행되는 프로그램이 발생시키는 시스템 호출들을 분석하고 프로파일을 구축하여 침입을 효과적으로 탐지한다 시스템 호출을 이용한 이상 탐지는 단지 그 프로세스가 이상(anomaly)임을 탐지할 뿐 그 프로세스에 의해 영향을 받는 여러 부분에 대해서는 탐지하지 못하는 문제점을 갖는다. 이러한 문제점을 개선하는 방법이 베이지안 확률값 이용하여 여러 프로세스의 시스템 호출간의 관계를 표현하고, 베이지안 네트워크를 이용한 어플리케이션의 행위 프로파일링에 의해 이상 탐지 정보를 제공한다. 본 논문은 여러 침입 탐지 모델들의 문제점들을 극복하면서 이상 침입 탐지를 효율적으로 수행할 수 있는 베이지안 네트워크를 이용한 침입 탐지 방법을 제안한다 행위의 전후 관계를 이용한 정상 행위를 간결하게 프로파일링하며, 변형되거나 새로운 행위에 대해서도 탐지가 가능하다. 제안한 정상행위 프로파일링 기법을 UNM 데이터를 이용하여 시뮬레이션하였다.

• 대한지역사회영양학회지
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• 제10권5호
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• pp.623-632
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• 2005

This study was intended to collect the baseline information on dietary behavior of adults to develop nutrition education program in the context of healthy weights at community level. Nutrient intakes of 128 housewives were assessed by 24 hour recall method. Also food habits, nutrition knowledge and attitude were investigated by self-administered questionnaires. Subjects were divided to under-weight, normal-weight, over-weight groups by body mass index (BMI). Most under-weight groups evaluated as their current body images were normal. $41\%$ of normal-weight groups judged as their current body images were obese. Energy and fat intakes of over-weight group were significantly higher than that of under-weight and normal weight groups (p<0.05). However, carbohydrate and protein intakes showed no significant differences among the three groups. It appeared that active attitude toward change in nutrition attitude of normal weight group was significantly higher than that of under-weight group (p<0.05). There were no significant differences of food habit score, nutrition knowledge, and obesity habit scores among the three groups. The frequency of eating-out showed significant difference among three groups (p<0.05). Food habit scores were positively related to health-concerned attitude (r=0.174), convenience-concerned attitude (r=0.229) and food enjoyed attitude (0.213) and negatively related to obesity habit score (r=-0.206). Also, positive correlation of body fat mass with frequency of eatingout (r=0.213), instant food (r=0.227) and amount of meal (r=0.187) existed (p<0.05). We concluded that nutrition education programs for housewives should include specific strategies to modify unsound food behaviors and inappropriate perception of body image for a healthy weight.

• 말소리와 음성과학
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• 제2권1호
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• pp.13-21
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• 2010

The purpose of this study was to examine the prosody characteristics of sentence-level utterances which contain homographs with context cues in patients with neurogenic communication disorders. Homographs which may be affected by prosody, especially tonic length features, were used to investigate this matter. The characteristics of tone, duration, pitch, and pitch peak were analyzed to examine the characteristics of prosody in patients with lesions in the left or right hemisphere and normal controls. The whole process was recorded using Praat 4.3.14 and for statistical analyses, three-way ANOVA and multiple comparative analyses, Chi-Square tests, and a one-way ANOVA were carried out using SPSS 12.0 for Windows. The conclusions of this study are as follows. First, the length of syllables and vowels in homographs in Korean was different depending on the meaning and was not significant between groups. Second, it was found that patients with lesions in the right hemisphere had significant difference on pitch. Third, it was found that frequency of pitch peak and tone in 'short' tone syllables were different between groups. The conclusion of this study found that the prosody of homographs between groups absolutely was not differentiated. Accordingly, more detailed studies of acoustic parameters and other parameters which the prosody characteristic between groups could be found are needed in the future.

• 대한수학교육학회지:학교수학
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• 제9권1호
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• pp.29-44
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• 2007

통계 교육의 목표는 통계적 사고를 기르는 것이고, 변이성은 통계적 사고의 기본 요소이다. 이 연구에서는 자료의 변이성에 관한 선행연구를 고찰하고 이를 토대로 변이성 개념을 탐구할 수 있는 상황을 분류하여 Freudenthal의 이론에 근거한 학습 자료를 개발하였다. 이 자료를 토대로 학습하는 학생들의 변이성 개념의 이해 과정을 면밀히 살펴보기 위하여 사례연구를 실시하였다. 변이성의 탐구는 자료의 요약, 그래프로의 표현을 통하여 분포를 볼 수 있도록 하고, 상대도수와 결합하여 확률분포와 정규분포에 이르는 중요한 시발점이 된다. 이 연구에서는 통계 교육의 내용 및 방법을 재고하고, 변이성을 보다 강화한 학습이 어떤 형태로 가능한가에 대한 사례연구를 통해 통계 교육의 내용과 방법 변화를 위한 기초자료를 제공하였다.