• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.1
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• pp.160-170
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• 2010

This paper proposes a Haar Wavelet Feature Detector (HWFD) based on the Haar wavelet transform and average box filter. By decomposing the original image using the Haar wavelet transform, the proposed detector obtains the variance information of the image, making it possible to extract more distinctive features from the original image. For detection of interest points that represent the regions whose variance is the highest among their neighbor regions, we apply the average box filter to evaluate the local variance information and use the integral image technique for fast computation. Due to utilization of the Haar wavelet transform and the average box filter, the proposed detector is robust to illumination change, scale change, and rotation of the image. Experimental results show that even though the proposed method detects fewer interest points, it achieves higher repeatability, higher efficiency and higher matching accuracy compared with the DoG detector and Harris corner detector.

• Journal of the Korea Society of Computer and Information
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• v.16 no.1
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• pp.53-59
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• 2011

In many face recognition applications such as security systems, it is assumed that upright faces are given to the system. In order for the system to be used in more general environments, the system should be able to deal with the rotated faces properly. It is a generally used approach to rotate the face detection window and apply face detector repeatedly to detect a rotated face in the given image. But such an approach requires a lot of computation time. In this paper, a method of extracting the axis of symmetry for a given set of points is proposed. The axis of symmetry for the edge points in the face detection window is extracted in a way that is fast and accurate, and the face detector is applied only for that direction. It is shown that the mean and standard deviation of the symmetry detection error is $0^{\circ}$ and $3^{\circ}$ respectively, for the database used.

• Journal of Energy Engineering
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• v.7 no.1
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• pp.65-72
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• 1998

This paper presents a fast calculation method for evaluating of voltage stability margin (MW) using the line flow equation in polar form. Here, Line flow equations $(P_{ij},\;Q_{ij}$ are comprised of state variable, $V_i,\;{\Delta}_i,\;V_j$ and ${Delta}_j$, and line parameter, r and x. using the feature of polar coordinate, these becomes one equation with two variables, $V_j,;V_j$. Moreover, if bus j is slack or generator bus, which is specified voltage magnitude in load flow calculation, it becomes one equation with one variable $V_ i $ that is, may be formulated with the second-order equation for $V^2_i$. Therefore, multiple load flow solutions may be obtained with simple computation. The obtained load flow multiple solutions are used for evaluating of voltage stability through sensitivity analysis or its closeness. Also, the method is proposed to calculate for voltage stability margin considering shunt capacitor, which is important element for evaluating of voltage stability. The proposed method was validated to sample systems.

• Journal of the Korea Computer Graphics Society
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• v.23 no.5
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• pp.1-7
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• 2017

We propose a complex crack generation technique which is represented when impact is applied to glass. The crack patterns expressed when external forces are applied to the glass are classified into dense, radial, and concentric cracks, and we use procedural methods to efficiently represent crack patterns. Based on the input external force, we synthesize the crack example and apply the L-system based on this example to model the propagation shape of the crack in real time. Although physics based crack generation can analyze and model accurate cracks, it has a disadvantage of slow computation because of its high computational cost, and procedural methods have a relatively fast rate of continuity, but are not sufficient to capture accurate crack characteristics. We modeled cracks in glass using L-system to achieve both of these advantages. As a result, it realistically represented the microscopic crack patterns of glass in real time.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.43 no.6 s.312
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• pp.1-8
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• 2006

Many researches on path planning and obstacle avoidance for the fundamentals of mobile robot have been done recently. Informations from various sensors can be used to find obstacles and plan feasible path. In spite of many solutions of finding optimal path, each can be applied in only a constrained condition. This means that it is difficult to find university good algorithm. An optimal path with a complicated computation generates a time delay which cannot avoid moving obstacles. In this paper, we propose an algorithm of path planning and obstacle avoidance for mobile robot. We call the proposed method Random Access Sequence(RAS) method. In the proposed method, a small region is set first and numbers are assigned to its neighbors, then the path is selected using these numbers and cumulative numbers. It has an advantage of fast planning time and completeness of path if one exists. This means that new path selection may be possible within short time and that helps a robot to avoid obstacle in dynamic environments. Using the information of the start and destination position, the RAS can be performed for collision-free navigation by reforming feasible paths repeatedly in dynamic environments.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.8
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• pp.18-26
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• 2015

Measuring the heart rate during exercise is important to properly control the amount of exercise. With the recent advent of smart device usage, there is a dramatic increase in interest in devices for the real-time measurement of the heart rate during exercise. During intensive exercise, accurate heart rate estimation from wrist-type photoplethysmography (PPG) signals is a very difficult problem due to motion artifact (MA). In this study, we propose an efficient algorithm for an accurate estimation of the heart rate from wrist-type PPG signals. For the twelve data sets, the proposed algorithm achieves the average absolute error of 1.38 beat per minute (BPM) and the Pearson correlation between the estimates and the ground-truth of heart rate was 0.9922. The proposed algorithm presents the strengths in an accurate estimation together with a fast computation speed, which is attractive in application to wearable devices.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.45 no.2
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• pp.49-54
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• 2008

In cryptosystems based on finite fields, a modular multiplication operation is the most crucial part of finite field arithmetic. Also, in multipliers with resource constrained environments, bit-serial output structures are used in general. This paper proposes two efficient bit-serial output multipliers with the polynomial basis representation for irreducible trinomials. The proposed multipliers have lower time complexity compared to previous bit-serial output multipliers. One of two proposed multipliers requires the time delay of $(m+1){\cdot}MUL+(m+1){\cdot}ADD$ which is more efficient than so-called Interleaved Multiplier with the time delay of $m{\cdot}MUL+2m{\cdot}ADD$. Therefore, in elliptic curve cryptosystems and pairing based cryptosystems with small characteristics, the proposed multipliers can result in faster overall computation. For example, if the characteristic of the finite fields used in cryprosystems is small then the proposed multipliers are approximately two times faster than previous ones.

• Journal of KIISE:Software and Applications
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• v.34 no.10
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• pp.889-899
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• 2007

In proteomics, recent advancements In mass spectrometry technology and in protein extraction and separation technology made high-throughput analysis possible. This leads to thousands to hundreds of thousands of MS/MS spectra per single LC-MS/MS experiment. Such a large amount of data creates significant computational challenges and therefore effective data analysis methods that make efficient use of computational resources and, at the same time, provide more peptide identifications are in great need. Here, SIFTER system is designed to avoid inefficient processing of shotgun proteomic data. SIFTER provides software tools that can improve throughput of mass spectrometry-based peptide identification by filtering out poor-quality tandem mass spectra and estimating a Peptide charge state prior to applying analysis algorithms. SIFTER tools characterize and assess spectral features and thus significantly reduce the computation time and false positive rates by localizing spectra that lead to wrong identification prior to full-blown analysis. SIFTER enables fast and in-depth interpretation of tandem mass spectra.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.12
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• pp.1834-1843
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• 2016

DVRs are the most common recording and displaying devices used for surveillance. Video compression plays a key role in DVRs for saving storage; the video compression standard, H.264/AVC, has recently become the dominant choice for DVRs. DVRs require various display modes, such as fast-forward, backward play, and pause; these are called trick modes. The implementation of precise trick mode play requires a very high decoding capability or a very intelligent scheme in order to handle the high computation complexity. The complexity is increased in many surveillance applications where more than one camera is used to monitor multiple spots or to monitor the same area using various angles. An implementation of a trick mode play and a frame buffer management scheme for the hardware-based H.264/AVC codec for multi-channel is presented in this paper. The experimental results show that exact trick mode play is possible using a standard H.264/AVC video codec with keyframe encoding feature at the expense of bitstream size increase.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.7
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• pp.893-898
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• 2005

Due to the merits that only a small amount of computation is needed for solutions and stochastic policies can be handled explicitly, the actor-critic algorithm, which is a class of reinforcement learning methods, has recently attracted a lot of interests in the area of artificial intelligence. The actor-critic network composes of tile actor network for selecting control inputs and the critic network for estimating value functions, and in its training stage, the actor and critic networks take the strategy, of changing their parameters adaptively in order to select excellent control inputs and yield accurate approximation for value functions as fast as possible. In this paper, we consider a new actor-critic algorithm employing an RLS(Recursive Least Square) method for critic learning, and policy gradients for actor learning. The applicability of the considered algorithm is illustrated with experiments on the two linked robot arm.