• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.172-175
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• 2016

본 논문은 손목에 부착된 단일 3축 가속도 센서를 이용하여 사용자 움직임 기반의 휴식, 걷기, 달리기(느린속도, 빠른속도)를 분류하는 방법에 관한 연구이다. 초당 32회 표본 값의 가속도 정보에서 특징 신호인 평균, 표준편차를 산출하고 사용자의 행동상태를 4가지 상태로 분류한다. 분류 기준이 모호한 상태전이 신호에 대해 6가지 상태로 분류하여 구해진 총 10개의 행동상태 정보를 2차원 평면에 사영하고 최종적으로 K-means 군집화 기법을 적용하여 사용자의 행동상태를 4가지 상태로 분류한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.313-314
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• 2021

최근 개인 정보 보호를 위해 주목 받고 있는 동형암호 알고리즘은 암호화된 상태로 덧셈과 곱셈 연산이 가능하여, 연산을 위한 복호화 과정 없이 데이터에 대한 가공이 가능하다. 따라서 이러한 동형암호 알고리즘이 개인 정보 보호를 위한 방법으로 떠오르고 있으며, 특히 완전동형암호 알고리즘의 경우 덧셈과 곱셈 연산을 모두 지원하며, 유효 연산 횟수에도 제한이 없어 응용 분야에서 널리 활용될 것으로 예상된다. 그러나, 완전동형암호 알고리즘의 경우 암호문의 크기가 평문대비 크게 증가하고, 다항식으로 구성된 암호문의 덧셈 및 곱셈 연산도 복잡하여 이에 대한 가속이 필요한 실정이다. 이에 FPGA 기반의 동형암호 가속기 개발이 많이 연구되고 있으며, 이를 통해 동형암호 연산의 특징을 이해하고 가속기 연구 동향을 알아보려 한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.11a
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• pp.13-16
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• 2008

본 논문은 가중퍼지소속함수 기반신경망(neural network with weighted fuzzy membership functions, NEWFM)기반의 자동 특징 추출기법을 사용하여 인체의 세 방향에서 발생하는 가속도 값으로부터 낙상을 탐지하는 방안을 제시하고 있다. 10명의 피검자로부터 8가지 시나리오로 낙상/비낙상 데이터 800개를 수집하고 웨이블릿 변환(wavelet transform, WT)을 통해 추출한 계수중 비중복면적 분산법에 의해 중요도가 가장 낮은 특징입력을 하나씩 제거하면서 최소의 특징 입력을 선택하였다. 특징입력으로는 가속도 값을 웨이블릿 변환한 11개의 d4계수들 중 비중복면적 분산법에 의해서 중요도가 가장 높은 5개의 계수가 사용되었고, 이들 특징입력을 통해 93%의 전체 분류율을 나타내었다.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.3
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• pp.216-220
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• 2009

In this paper we propose a motion recognition method for handheld controller 3-D acceleration signals, generated by 3 axis accelerometer in the controller, are transmitted to the computer by Bluetooth communication. We extract motion segments from continuous acceleration signals and apply to each motion model, which is trained in training phase. Hidden Markov Model was used to model each motion. We applied proposed method to three motion sets, the recognition result was good enough to practical use.

• Proceedings of the Korea Contents Association Conference
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• 2007.11a
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• pp.543-546
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• 2007

Flow visualization is one of visualization techniques and it means a visual expression of vector data using 2D or 3D graphics. It aims for human to easily find and understand a special feature of the vector data. The Image Based Flow Visualization (IBFV) is one of the fastest technique in the dense integration based flow visualization techniques. In this paper, IBFV is accelerated and implemented using commodity GPU. Especially, mesh advection is accelerated at the vertex program.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.6
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• pp.1477-1484
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• 2015

With the growth of financial industry with smartphone, interest on user authentication using smartphone has been arisen in these days. There are various type of biometric user authentication techniques, but gait recognition using accelerometer sensor in smartphone does not seem to develop remarkably. This paper suggests the method of user authentication using accelerometer sensor embedded in smartphone. Specifically, calibrate the sensor data from smartphone with 3D-transformation, extract features from transformed data and do principle component analysis, and learn model with using gaussian mixture model. Next, authenticate user data with confidence interval of GMM model. As result, proposed method is capable of user authentication with accelerometer sensor on smartphone as a high degree of accuracy(about 96%) even in the situation that environment control and limitation are minimum on the research.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.30 no.3
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• pp.249-254
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• 2017

The paper presents a new short-term dynamic displacement estimation method based on an acceleration and a geophone sensor. The proposed method combines acceleration and velocity measurements through a real time data fusion algorithm based on Kalman filter. The proposed method can estimate the displacement of a structure without displacement sensors, which is typically difficult to be applied to earthquake or fire sites due to their requirement of a fixed rigid support. The proposed method double-integrates the acceleration measurement recursively, and corrects an accumulated integration error based on the velocity measurement, The performance of the proposed method was verified by a lab-scale test, in which displacement estimated by the proposed method are compared to a reference displacement measured by laser doppler vibrometer (LDV).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.4
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• pp.813-820
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• 2009

This paper describes the realization of ubiquitous healthcare monitoring system using wearable pulse oximeter based on a wireless sensor network. In order to obtain information of oxygen saturation from a patient, a small size and low power consumption wearable pulse oximeter was designed. Information of oxygen saturation collected by wireless sensor node was transmitted wirelessly to a base-station for storage and display purposes via wireless sensor network. Wireless sensor nodes were programmed by TinyOS application to perform data acquisition and transmission. Lab VIEW server program was designed to monitor information of oxygen saturation and process the measured PPG (photo plethysmogram) signals to APG(Accelerated plethysmogram) signals by appling second order derivatives. PPG signals are simple and cost effective technique to measure blood volume change.

• Journal of the Korea institute for structural maintenance and inspection
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• v.13 no.2 s.54
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• pp.115-121
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• 2009

The paper presents a signal-based damage detection algorithm of ARX model using dynamic acceleration data. An ARX model correlates acceleration data measured at two locations in a structure by considering those two sets of data as input and output signals. For detecting damage, the error between the measured data and the predicted response from the defined ARX model is computed in time and used for a statistical evaluation. A normal distribution function from the error in time is constructed and its statistical characteristic values are used for the evaluation of damage. By comparing the normal distribution functions before and after damage, three different types of damage indices are proposed. The efficiency and limitation of the proposed algorithm with the statistical evaluation of damage indices have been examined and discussed through laboratory experiments.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.1A
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• pp.135-146
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• 2008

In this paper, a hybrid damage monitoring scheme for prestressed concrete (PSC) girder bridges by using sequential acceleration and impedance signatures is newly proposed. Damage types of interest include prestress-loss in tendon and flexural stiffness-loss in a concrete girder. The hybrid scheme mainly consists of three sequential phases: damage alarming, damage classification, and damage estimation. In the first phase, the global occurrence of damage is alarmed by monitoring changes in acceleration features. In the second phase, the type of damage is classified into either prestress-loss or flexural stiffness-loss by recognizing patterns of impedance features. In the third phase, the location and the extent of damage are estimated by using two different ways: a mode shape-based damage detection to detect flexural stiffness-loss and a natural frequency-based prestress prediction to identify prestress-loss. The feasibility of the proposed scheme is evaluated on a laboratory-scaled PSC girder model for which hybrid vibration-impedance signatures were measured for several damage scenarios of prestress-loss and flexural stiffness-loss.