• Journal of Sensor Science and Technology
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• v.31 no.2
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• pp.79-84
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• 2022

Self-powered sensors play an important role in everyday life, and they cover a wide range of topics. These sensors are meant to measure the amount of relevant motion and transform the biomechanical activities into electrical signals using triboelectric nanogenerators (TENGs) since they are sensitive to external stimuli such as pressure, temperature, wetness, and motion. The present advancement of TENGs-based self-powered wearable, implantable, and patchable sensors for healthcare monitoring, human body motion, and medication delivery systems was carefully emphasized in this study. The use of TENG technology to generate electrical energy in real-time using self-powered sensors has been the topic of considerable research among various leading scholars. TENGs have been used in a variety of applications, including biomedical and healthcare physical sensors, wearable devices, biomedical, human-machine interface, chemical and environmental monitoring, smart traffic, smart cities, robotics, and fiber and fabric sensors, among others, as efficient mechanical-to-electric energy conversion technologies. In this evaluation, the progress accomplished by TENG in several areas is extensively reviewed. There will be a discussion on the future of self-powered sensors.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.3
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• pp.221-229
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• 2013

In this paper, the image formation by the motion compensation technique for Synthetic Aperture Radar system(SAR) were realized through the computer simulation. The motion compensation technique performed image data with the range compression, the compensation procedure, the azimuth compensation and the noise elimination procedure. The range compression procedure transform the SAR raw data into the frequency domain and correlate with the range reference function and then inversely transform into the time domain. The compensation procedure contain the aircraft fluctuations compensation and the radar image degrading effect elimination procedure which was caused by image formation algorithm itself. The aircraft fluctuations compensation procedure perform the first stage which correct the phase angle and the second stage which calculate the Doppler frequency and determine the coordinate of the received signal. The radar image degrading effect elimination procedure also perform range migration compensation and the image defocussing effect compensation. The azimuth compression procedure transform the compensation data to the frequency domain and correlate with the azimuth reference function. The azimuth correlated data are inversely transformed to the time domain which is called SAR image data. When the above procedure were completed, the image data contains the received signals mixed with noise. The threshold technique was applied to elimination the noise from the mixed image data.

• Research in Mathematical Education
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• v.14 no.3
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• pp.195-209
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• 2010

Utilizing a structure of operations known as Dissection-Motion-Operations (DMO), a set of mathematics propositions or area-formulas in school mathematics will be introduced through shape-to-shape transforms. The underlying theme for DMO is problem-solving through visual reasoning and proving manipulatively or electronically vs. rote learning and memorization. Visual reasoning is the focus here where two operations that constitute DMO are utilized. One operation is known as Dissection (or Decomposition) operation that operates on a given region in 2D or 3D and dissects it into a number of subregions. The second operation is known as Motion (or Composition) operation applied on the resultant sub-regions to form a distinct area (or volume)-equivalent region. In 2D for example, DMO can transform a given polygon into a variety of new and distinct polygons each of which is area-equivalent to the original polygon (cf [Rahim, M. H. & Sawada, D. (1986). Revitalizing school geometry through Dissection-Motion Operations. Sch. Sci. Math. 86(3), 235-246] and [Rahim, M. H. & Sawada, D. (1990). The duality of qualitative and quantitative knowing in school geometry, International Journal of Mathematical Education in Science and Technology 21(2), 303-308]).

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.1
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• pp.14-19
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• 2010

In this paper, an efficient algorithm is developed to perform target rotational motion compensation to achieve the clear inverse synthetic aperture radar(ISAR) image. The algorithm is based on a time-frequency technique. This algorithm provides an efficient method to resolve the blurring image caused by the time-varying behavior of the target scattering centers and leads to a well-focused ISAR image. Results demonstrate that the time-frequency techniques can improve the blurring ISAR image when an aircraft is in complex motion, such as maneuvering, rotation and acceleration.

• Journal of Broadcast Engineering
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• v.8 no.3
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• pp.297-305
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• 2003

In this paper, we propose a wavelet based fast motion estimation algorithm for video sequence encoding with very low bit-rate. By using one of properties oi wavelet transform, multi-resolution analysis(MRA) property and spatial Interpolation of an image, we are able to reduce both prediction error and computational complexity at the same time. Especially, by defining a significant block(SB) based on the differential information of wavelet coefficients between successive frames, the proposed algorithm makes up a defect of multi-resolution motion estimation(MRME) algorithm of increasing the number of motion vectors. As experimental results. we can reduce the computational load up to 70% but also improve PSNR up to about 0.1 ∼ 1.2 dB comparing with the MRME algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.8
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• pp.961-968
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• 1999

In this paper we handle a system that transform sensor data to sensor information. Sensor informations from redundant accelerometers are manipulated to represent the configuration of objects carrying sensors. Basic sensor unit of the proposed systme is composed of 3 accelerometers that are aligned along x-y-z coordination axes of motion. To refine the sensor information, at first the sensor data are fused by geometrical optimization to reduce the variance of sensor information. To overcome the error caused from inexact alignment of each sensor to the coordination system, we propose a calibration technique that identifies the transformation between the coordinate axes and real sensor axes. The calibration technique make the sensor information approach real value. Also, we propose a technique that decomposes the accelerometer data into motion acceleration component and gravity acceleration component so that we can get more exact configuration of objects than in the case of raw sensor data. A set of experimental results are given to show the usefulness of the proposed method as well as the experiments in which the proposed techniques are applied to human body motion capture.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.14 no.11
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• pp.1156-1160
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• 2003

Many time-frequency analysis techniques have been used for motion compensated ISAR(Inverse Synthetic Aperture Radar) imaging. In this work, a novel time-frequency(T-F) analysis called evolutionary adaptive wavelet transform (EAWT) and evolutionary adaptive joint time-frequency(EAJTF) procedure are used for the motion compensated ISAR image. To show the validity of our algorism, we use simulated MIG-25 and Boeing 727(B-727) ISAR data. From the constructed ISAR image using EAWT and EAJTF, we show that our algorithm can obtain a clear motion compensated ISAR image such as other time-frequency analysis techniques.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.3
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• pp.80-92
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• 2008

Many predominant video coding tools in terms of coding efficiency were adopted in the latest video coding standard, H.264/AVC. Regardless of development of these predominant video coding tools such as the variable block-size motion estimation/compensation, intra prediction based on various directions, and so on, the discrete cosine transform has been continuously used starting from the early video coding standards. Generally, the correlation coefficient of the residual signal is usually less than 0.5 when this residual signal is actually encoded. In this interval of correlation coefficient, the discrete cosine transform does not show the optimal coding gain, and the discrete sine transform which is a sub-optimal transform when the correlation coefficient is in the interval from -0.5 to 0.5 can be used in conjunction with the discrete cosine transform in the video coding. In this paper, an alternative transform that alternatively uses the discrete sine transform and integer cosine transform in H.264/AVC by using rate-distortion optimization is proposed. The proposed method achieves a BD-PSNR gain of up to 0.71 dB compared to H.264/AVC JM 10.2 at relatively high bitrates.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.9
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• pp.3782-3796
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• 2020

A three-dimensional (3D) reconstruction is an important research area in computer vision. The ability to detect and match features across multiple views of a scene is a critical initial step. The tracking matrix W obtained from a 3D reconstruction can be applied to structure from motion (SFM) algorithms for 3D modeling. We often fail to generate an acceptable number of features when processing face or medical images because such images typically contain large homogeneous regions with minimal variation in intensity. In this study, we seek to locate sufficient matching points not only in general images but also in face and medical images, where it is difficult to determine the feature points. The algorithm is implemented on an adaptive threshold value, a scale invariant feature transform (SIFT), affine SIFT, speeded up robust features (SURF), and affine SURF. By applying the algorithm to face and general images and studying the geometric errors, we can achieve quasi-dense matching points that satisfy well-functioning geometric constraints. We also demonstrate a 3D reconstruction with a respectable performance by applying a column space fitting algorithm, which is an SFM algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.5
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• pp.1199-1206
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• 2015

This paper introduces an algorithm for computing similarity between two poses in the motion capture data with different scale of skeleton, different number of joints and different joint names. The proposed algorithm first performs the topological analysis on the skeleton hierarchy for classifying the joints into more meaningful groups. The global joints positions of each joint group then are aggregated into a point cloud. The number of joints and their positions are automatically adjusted in this process. Once we have two point clouds, the algorithm finds an optimal 2D transform matrix that transforms one point cloud to the other as closely as possible. Then, the similarity can be obtained by summing up all distance values between two points clouds after applying the 2D transform matrix. After some experiment, we found that the proposed algorithm is able to compute the similarity between two poses regardless of their scale, joint name and the number of joints.