• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2009년도 춘계 종합학술대회 논문집
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• pp.737-742
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• 2009

RIA 기술은 사용자의 경험을 강조하는 최근 트렌드에 힘입어 PC를 넘어, 핸드폰, TV 등 다양한 장치의 주요 사용자 인터페이스 및 소프트웨어 운용 플랫폼으로 자리 잡아가고 있다. 특히, RIA 기반 IPTV는 광고, 에듀테인먼트 등의 서비스에서 화려한 애니메이션 및 다양한 입력 장치에 기반한 첨단 상응식 콘텐츠의 개발을 가능하게 한다. 본 논문에서는 방송통신 융합형 감성 콘텐츠의 운용 및 서비스를 위한 프레임워크를 제안한다. IPTV용 플래시 콘텐츠 개발을 위한 확장프로그래밍 인터페이스를 제안하고 이를 지원하는 IPTV 미들웨어 및 플래시 런타임을 개발한다. 특히, 제안된 플래시 런타임은 하드웨어 그래픽 가속을 최대한 활용함으로써 저성능의 미디어 프로세서에서도 고감도 애니메이션을 지원하도록 설계되었다.

• 대한전기학회논문지:시스템및제어부문D
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• 제51권1호
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• pp.32-38
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• 2002

This paper describes a development of a portable physical activity monitoring system using two accelerometers to quantify physical activity. The system hardware consists of two piezoresistive accelerometers, amplifiers with gain of 30, lowpass filters with cut-off frequency of 15Hz, offset control circuits, one-chip microcontroller and flash memory card. In order to evaluate the performance of the system we acquired 3 channel data at 32 sample/sec from body-fixed accelerometers in chest and right upper leg. And then the acquired data were processed by MatLab on personal computer. We tried to distinguish not only fundamental actions which are steady-state activities such as standing, sitting, and lying but also dynamic activities with walking, up a stairway, down a stairway, and running. Five subjects participated the evaluation process which compare the video data with the measured data. As a result, the activity classification rate of 90.6% on average was obtained. Overall results showed that the steady-state activities could be classified from the low component of 3-axis acceleration signal and dynamic activities could be distinguished from frequency analysis using wavelet transform and FFT. Finally, we could find that this system can be applied to acquire and analyze the static and dynamic physical activity data.

• Journal of Mechanical Science and Technology
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• 제15권8호
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• pp.1090-1096
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• 2001

In this paper, new methods for efficiently solving linear acceleration equations of multibody dynamic simulation exploiting sparsity for real-time simulation are presented. The coefficient matrix of the equations tends to have a large number of zero entries according to the relative joint coordinate numbering. By adequate joint coordinate numbering, the matrix has minimum off-diagonal terms and a block pattern of non-zero entries and can be solved efficiently. The proposed methods, using sparse Cholesky method and recursive block mass matrix method, take advantages of both the special structure and the sparsity of the coefficient matrix to reduce computation time. The first method solves the η$\times$η sparse coefficient matrix for the accelerations, where η denotes the number of relative coordinates. In the second method, for vehicle dynamic simulation, simple manipulations bring the original problem of dimension η$\times$η to an equivalent problem of dimension 6$\times$6 to be solved for the accelerations of a vehicle chassis. For vehicle dynamic simulation, the proposed solution methods are proved to be more efficient than the classical approaches using reduced Lagrangian multiplier method. With the methods computation time for real-time vehicle dynamic simulation can be reduced up to 14 per cent compared to the classical approach.

• 전기전자학회논문지
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• 제11권4호
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• pp.137-144
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• 2007

함포의 사격통제장치 성능은 크게 하드웨어(H/W)적인 오차와 소프트웨어(S/W)적인 오차로 구분할 수 있으며, 이중 S/W 오차에 해당하는 표적의 위치, 속도, 가속도 등을 추정하는 추적필터 오차는 탄도계산장치의 성능에 중요한 영향을 미친다. 함포의 정확한 예상탄착점 형성과 사격시 명중률 향상을 위하여 정확한 미래위치의 표적 상태정보가 필요하다. 표적 추적필터 알고리즘은 Single Singer Model, Fixed Gain 필터 알고리즘, IMM, PBIMM등이 있다. 본 논문에서는 최근 국내 함정에 적용예정인 IMM 추적필터를 설계하였다. IMM 추적필터를 위해 CV모델, Song 모델, CTR모델을 사용하여 동역학 모델을 만들었으며, 추적성능을 Monte-Carlo 시뮬레이션을 통해 해석해 보았다.

• 한국해양공학회지
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• 제16권1호
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• pp.64-70
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• 2002

This paper shows the results of the development of a small size of digital type continuous and intermittent welding auto-carriage based on microprocessor (Intel 80196KC) for welding process with long welding line. The developed welding auto-carriage loads welding torch and tracks welding line. It is an automaton largely used for welding process with a lot of long welding lines such as shipbuilding and structure. Most traditional auto-carriages have been developed based on analog circuit for open loop control. So this analog circuit welding auto-carriage cannon control welding speed. Specially welding auto-carriage for intermittent welding condition is so complicated and has the low precision of control performance in welding distance and non-welding distance. The auto-carriage developed in this paper has the following characteristics: It has not only functions of traditional carriage but also functions such as pseudo-welding process of big iron structures, intermittent welding in order to limit heat for welding thin plates, crater treatment of the final step of welding, acceleration at the initial step of welding and deceleration in the final step of welding. The main control board of auto-carriage, power supply system and DC motor drive wee developed and manufactured. The welding speed and the welding distance of the developed auto-carriage are controlled accurately by feedback control using photo-sensor. Hardware and software robust against the heat and noise produced on the welding process are developed.

• Smart Structures and Systems
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• 제5권4호
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• pp.415-426
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• 2009

This study focuses on the concept of multi-scale wireless sensor networks for damage detection in civil infrastructure systems by first over viewing the general network philosophy and attributes in the areas of data acquisition, data reduction, assessment and decision making. The data acquisition aspect includes a scalable wireless sensor network acquiring acceleration and strain data, triggered using a Restricted Input Network Activation scheme (RINAS) that extends network lifetime and reduces the size of the requisite undamaged reference pool. Major emphasis is given in this study to data reduction and assessment aspects that enable a decentralized approach operating within the hardware and power constraints of wireless sensor networks to avoid issues associated with packet loss, synchronization and latency. After over viewing various models for data reduction, the concept of a data-driven Bivariate Regressive Adaptive INdex (BRAIN) for damage detection is presented. Subsequent examples using experimental and simulated data verify two major hypotheses related to the BRAIN concept: (i) data-driven damage metrics are more robust and reliable than their counterparts and (ii) the use of heterogeneous sensing enhances overall detection capability of such data-driven damage metrics.

• Smart Structures and Systems
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• 제6권5_6호
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• pp.661-673
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• 2010

This paper presents recent developments in an extremely compact, wireless impedance sensor node (the WID3, $\underline{W}$ireless $\underline{I}$mpedance $\underline{D}$evice) for use in high-frequency impedance-based structural health monitoring (SHM), sensor diagnostics and validation, and low-frequency (< ~1 kHz) vibration data acquisition. The WID3 is equipped with an impedance chip that can resolve measurements up to 100 kHz, a frequency range ideal for many SHM applications. An integrated set of multiplexers allows the end user to monitor seven piezoelectric sensors from a single sensor node. The WID3 combines on-board processing using a microcontroller, data storage using flash memory, wireless communications capabilities, and a series of internal and external triggering options into a single package to realize a truly comprehensive, self-contained wireless active-sensor node for SHM applications. Furthermore, we recently extended the capability of this device by implementing low-frequency analog-to-digital and digital-to-analog converters so that the same device can measure structural vibration data. The compact sensor node collects relatively low-frequency acceleration measurements to estimate natural frequencies and operational deflection shapes, as well as relatively high-frequency impedance measurements to detect structural damage. Experimental results with application to SHM, sensor diagnostics and low-frequency vibration data acquisition are presented.

• 반도체디스플레이기술학회지
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• 제21권4호
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• pp.121-125
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• 2022

This paper deals with the development of a deep-learning-based robot that recognizes various types of stairs and performs a mission to go up to the target floor. The overall motion sequence of the robot is performed based on the ROS robot operating system, and it is possible to detect the shape of the stairs required to implement the motion sequence through rapid object recognition through YOLOv4 and Cuda acceleration calculations. Using the ROS operating system installed in Jetson Nano, a system was built to support communication between Arduino DUE and OpenCM 9.04 with heterogeneous hardware and to control the movement of the robot by aligning the received sensors and data. In addition, the web server for robot control was manufactured as ROS web server, and flow chart and basic ROS communication were designed to enable control through computer and smartphone through message passing.

• 대한임베디드공학회논문지
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• 제17권4호
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• pp.217-228
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• 2022

Currently, there are increasing demands for applying deep neural networks (DNNs) in the embedded domain such as classification and object detection. The DNN processing in embedded domain often requires custom hardware such as NPU for acceleration due to the constraints in power, performance, and area. Processing DNN models requires a large amount of data, and its seamless transfer to NPU is crucial for performance. In this paper, we developed a cycle-accurate NPU simulator to evaluate diverse NPU microarchitectures. In addition, we propose a novel technique for reducing the number of memory accesses when processing convolutional layers in convolutional neural networks (CNNs) on the NPU. The main idea is to reuse data with memory interleaving, which recycles the overlapping data between previous and current input windows. Data memory interleaving makes it possible to quickly read consecutive data in unaligned locations. We implemented the proposed technique to the cycle-accurate NPU simulator and measured the performance with LeNet-5, VGGNet-16, and ResNet-50. The experiment shows up to 2.08x speedup in processing one convolutional layer, compared to the baseline.

• Smart Structures and Systems
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• 제29권2호
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• pp.287-299
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• 2022

Rather than using smartphones as seismometers with designated locations and orientations, this study proposes to employ crowds' smartphones in buildings to perform fast safety assessment of buildings. The principal advantage of using crowds' smartphones is the potential to monitor the safety of millions of buildings without hardware costs, installation labor, and long-term maintenance. This study's goal is to measure the maximum interstory drift ratios during earthquake excitation using crowds' smartphones. Beacons inside the building are required to provide the location and relevant building information for the smartphones via Bluetooth. Wi-Fi Direct is employed between nearby smartphones to conduct peer-to-peer time synchronization and exchange the acceleration data measured. An algorithm to align the orientation between nearby smartphones is proposed, and the performance of the orientation alignment, interstory drift measurement, and damage level estimation are studied numerically. Finally, the proposed approach's performance is verified using large-scale shaking table tests of a scaled steel building. The results presented in this study illustrate the potential to use crowds' smartphones with the proposed approach to record building motions during earthquakes and use those data to estimate buildings' safety based on the interstory drift ratios measured.