• 한국멀티미디어학회논문지
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• 제16권12호
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• pp.1439-1445
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• 2013

We present a Taekwondo training system using a hybrid sensing technique of a body sensor and a visual sensor. Using a body sensor (accelerometer), rotational and inertial motion data are captured which are important for Taekwondo motion detection and evaluation. A visual sensor (camera) captures and records the sequential images of the performance. Motion chunk is proposed to structuralize Taekwondo motions and design HMM (Hidden Markov Model) for motion recognition. Trainees can evaluates their trial motions numerically by computing the distance to the standard motion performed by a trainer. For motion training video, the real-time video images captured by a camera is overlayed with a visualized body sensor data so that users can see how the rotational and inertial motion data flow.

• 대한조선학회논문집
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• 제59권2호
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• pp.125-133
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• 2022

This paper proposes a fault detection method for a Unmanned Surface Vehicle (USV) with overactuated system. Current status information for fault detection is expressed as a scalogram image. The scalogram image is obtained by wavelet-transforming the USV's control input and sensor information. The fault detection scheme is based on Convolutional Neural Network (CNN) algorithm. The previously generated scalogram data was transferred learning to GoogLeNet algorithm. The data are generated as scalogram images in real time, and fault is detected through a learning model. The result of fault detection is very robust and highly accurate.

• 한국통신학회논문지
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• 제35권7A호
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• pp.697-705
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• 2010

WSN에서의 커버리지 문제는 센싱 커버리지에 대한 요구조건을 만족시키기 위해 필요한 최소한의 활동 센서(active sensor)의 개수로 공식화될 수 있다. 일반적으로 확률적 기하학을 이용하여 WSN의 커버리지 분석을 수행하기 때문에 센싱 모델이 커버리지 분석의 핵심 요소로 간주된다. 따라서, 커버리지 분석의 정확도는 어떠한 센싱 모델을 가정하였느냐에 따라 달라질 수 있으며 분석에 사용된 센싱 모델이 얼마나 실 센싱 환경에 가깝게 특성화 되었느냐에 따라 달라진다. 본 논문에서는 Boolean 모델, Exponential 모델, Hybrid 모델 등 다양한 형태의 결정적 혹은 확률적 센싱 모델들을 조사하고 각각의 센싱 모델에 따라 일정 영역을 센싱할 수 있는 최소한의 센서 개수를 도출할 수 있는 수리적 분석을 수행하였으며 이를 통해 성능을 비교 평가하였다.

• 센서학회지
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• 제19권4호
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• pp.271-277
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• 2010

Intravenous(IV) drip therapy is extensively used for all kinds of treatments. It works by delivering medicine directly into the vein. When the medicine has been fully dispensed, a dangerous situation occurs since air in the IV drip bag could enter the patient's vein, which is hazardous to the patient’s safety. In this paper, using capacitive sensors to detect the residual quantity of a plastic IV drip pack is proposed. A simulation model of this technology was shown by a finite elements analysis(FEA) program to find out its feasibility and analyze the proper geometrical dimension of a capacitive sensor. According to the FEA simulation, 3 kinds of capacitive sensors were attached to the bottom surface of the plastic IV drip bag to detect the residual quantity in the experiment. Experimental data showed an agreement with the FEA simulation model estimation and confirmed that the sensor works.

• 센서학회지
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• 제30권5호
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• pp.290-294
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• 2021

Experts have designed popular and successful model architectures, which, however, were not the optimal option for different scenarios. Despite the remarkable performances achieved by deep neural networks, manually designed networks for classification tasks are the backbone of object detection. One major challenge is the ImageNet pre-training of the search space representation; moreover, the searched network incurs huge computational cost. Therefore, to overcome the obstacle of the pre-training process, we introduce a network adaptation technique using a pre-trained backbone model tested on ImageNet. The adaptation method can efficiently adapt the manually designed network on ImageNet to the new object-detection task. Neural architecture search (NAS) is adopted to adapt the architecture of the network. The adaptation is conducted on the MobileNetV2 network. The proposed NAS is tested using SSDLite detector. The results demonstrate increased performance compared to existing network architecture in terms of search cost, total number of adder arithmetics (Madds), and mean Average Precision(mAP). The total computational cost of the proposed NAS is much less than that of the State Of The Art (SOTA) NAS method.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 제36회 하계학술대회 논문집 D
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• pp.3019-3021
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• 2005

In this paper we suggest a novel temperature detection method utilized in direct over-temperature protection circuit modeling. The suggested model detects temperature variation using Rds(on) characteristics of MOSFET, while the conventional methods are using extra devices such as a temperature sensor or an over-temperature detection transistor. The temperature-dependant MOSFET model is implemented using Spice ABM(Spice Analog Behavior Model). The direct over-temperature protection circuit was designed including it. We verified effectiveness of the temperature dependant Rds(on) model characteristics and performance of the direct over-temperature protection circuit on PSpice simulation

• Journal of international Conference on Electrical Machines and Systems
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• 제3권3호
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• pp.325-330
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• 2014

Eddy current induction is used in a wide range of electronic devices, for example in detection sensors. Due to the advances in computer hardware and software, the need for 3D computation and system comprehension is a requirement to develop and optimize such devices nowadays. Pure theoretical models are mostly limited to special cases. On the other hand, the classical use of commercial Finite Element (FE) electromagnetic 3D models is not computationally efficient and lacks modeling flexibility or robustness. The proposed approach focuses on: (1) implementing theoretical formulations in 3D (FE) model of a detection device as well as (2) an automatic Volumetric Estimation Method (VEM) developed to selectively model the target finite elements. Due to these two approaches, this model is suitable for parametric studies and optimization of the number, location, shape, and size of PCB receivers in order to get the desired target discrimination information preserving high accuracy with tenfold reduction in computation time compared to commercial FE software.

• 한국산학기술학회논문지
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• 제13권8호
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• pp.3628-3633
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• 2012

본 논문은 산사태 감지 및 붕괴예측을 위하여 USN(Ubiquitous Sensor Network)을 적용한 실시간 모니터링 시스템 모델을 제안하였다. 이 시스템의 성능을 검증하기 위해 기울기 센서를 이용한 USN기반의 모니터링시스템 모델을 제작하고 실험적 평가를 수행하였다. 성능평가는 기울기 센서모듈 동작특성 실험적 평가와 USN의 데이터 수집 전송 효율 실험적 평가, 개발한 상시 감시모니터링 프로그램(S/W) 동작성능 실험적 평가 등을 수행하였다. 모델의 전체 성능검증은 기울기센서를 $0^{\circ}$, $-10^{\circ}$, $-20^{\circ}$ 및 $0{\sim}-30^{\circ}$ 주고 USN 모니터링시스템에서 100[msec] 주기로 샘플링하였을 때, 기울기센서의 각도와 모니터링 표출 그래프의 출력이 잘 일치하였다. 이 실험으로 제안한 모델의 각 기능요소별 성능이 검증되었고, USN 데이터전송도 오류 없이 전송됨이 확인되었다. 따라서 기울기 센서를 이용한 산사태 감지 예측을 위한 USN기반 실시간 모니터링시스템 제안모델이 산사태 위험성 노출지역에 원격 실시간 모니터링 시스템으로 널리 사용될 것으로 사료된다.

• 대한임베디드공학회논문지
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• 제12권5호
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• pp.277-286
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• 2017

This paper introduces mathematical modelling and control algorithm of expendable mine disposal vehicle. This vehicle has two longitudinal thrusters, one vertical thruster and internal mass moving system which can control pitch rate. Also, the vehicle has an optical camera and forward looking sonar for underwater mine detection and classification. The vehicle is controlled via an optical cable connected with operating console on the mother ship. We describe the vehicle's 6DOF dynamic model and controller which can track the desired trajectory for the way-point tracking. These simulation results shows guidance and maneuvering performance which has other sensor data or not.

• Nuclear Engineering and Technology
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• 제55권2호
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• pp.443-451
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• 2023

Machine Learning has introduced many solutions in data science, but its application in IoT faces significant challenges, due to the limitations in memory size and processing capability of constrained devices. In this paper we design an automatic gamma radiation detection and identification embedded system that exploits the power of TinyML in a SiPM micro radiation sensor leveraging the Edge Impulse platform. The model is trained using real gamma source data enhanced by software augmentation algorithms. Tests show high accuracy in real time processing. This design has promising applications in general-purpose radiation detection and identification, nuclear safety, medical diagnosis and it is also amenable for deployment in small satellites.