• Title/Summary/Keyword: 선형보간법

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An Adaptive Temporal Suppression for Reducing Network Traffic in Wireless Sensor Networks (무선 센서 네트워크에서 통신량 감소를 위한 적응적 데이터 제한 기법)

  • Min, Joonki;Kwon, Youngmi
    • Journal of the Institute of Electronics and Information Engineers
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    • v.49 no.10
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    • pp.60-68
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    • 2012
  • Current wireless sensor networks are considered to support more complex operations ranging from military to health care which require energy-efficient and timely transmission of large amounts of data. In this paper, we propose an adaptive temporal suppression algorithm which exploits a temporal correlation among sensor readings. The proposed scheme can significantly reduce the number of transmitted sensor readings by sensor node, and consequently decrease the energy consumption and delay. Instead of transmitting all sensor readings from sensor node to sink node, the proposed scheme is to selectively transmit some elements of sensor readings using the adaptive temporal suppression, and the sink node is able to reconstruct the original data without deteriorating data quality by linear interpolation. In our proposed scheme, sensing data stream at sensor node is divided into many small sensing windows and the transmission ratio in each window is decided by the window complexity. It is defined as the number of a fluctuation point which has greater absolute gradient than threshold value. We have been able to achieve up about 90% communication reduction while maintaining a minimal distortion ratio 6.5% in 3 samples among 4 ones.

Eyelid Detection Algorithm Based on Parabolic Hough Transform for Iris Recognition (홍채 인식을 위한 포물 허프 변환 기반 눈꺼풀 영역 검출 알고리즘)

  • Jang, Young-Kyoon;Kang, Byung-Jun;Park, Kang-Ryoung
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.44 no.1
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    • pp.94-104
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    • 2007
  • Iris recognition is biometric technology which uses a unique iris pattern of user in order to identify person. In the captured iris image by conventional iris recognition camera, it is often the case with eyelid occlusion, which covers iris information. The eyelids are unnecessary information that causes bad recognition performance, so this paper proposes robust algorithm in order to detect eyelid. This research has following three advantages compared to previous works. First, we remove the detected eyelash and specular reflection by linear interpolation method because they act as noise factors when locating eyelid. Second, we detect the candidate points of eyelid by using mask in limited eyelid searching area, which is determined by searching the cross position of eyelid and the outer boundary of iris. And our proposed algorithm detects eyelid by using parabolic hough transform based on the detected candidate points. Third, there have been many researches to detect eyelid, but they did not consider the rotation of eyelid in an iris image. Whereas, we consider the rotation factor in parabolic hough transform to overcome such problem. We tested our algorithm with CASIA Database. As the experimental results, the detection accuracy were 90.82% and 96.47% in case of detecting upper and lower eyelid, respectively.

An Electric Load Forecasting Scheme with High Time Resolution Based on Artificial Neural Network (인공 신경망 기반의 고시간 해상도를 갖는 전력수요 예측기법)

  • Park, Jinwoong;Moon, Jihoon;Hwang, Eenjun
    • KIPS Transactions on Software and Data Engineering
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    • v.6 no.11
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    • pp.527-536
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    • 2017
  • With the recent development of smart grid industry, the necessity for efficient EMS(Energy Management System) has been increased. In particular, in order to reduce electric load and energy cost, sophisticated electric load forecasting and efficient smart grid operation strategy are required. In this paper, for more accurate electric load forecasting, we extend the data collected at demand time into high time resolution and construct an artificial neural network-based forecasting model appropriate for the high time resolution data. Furthermore, to improve the accuracy of electric load forecasting, time series data of sequence form are transformed into continuous data of two-dimensional space to solve that problem that machine learning methods cannot reflect the periodicity of time series data. In addition, to consider external factors such as temperature and humidity in accordance with the time resolution, we estimate their value at the time resolution using linear interpolation method. Finally, we apply the PCA(Principal Component Analysis) algorithm to the feature vector composed of external factors to remove data which have little correlation with the power data. Finally, we perform the evaluation of our model through 5-fold cross-validation. The results show that forecasting based on higher time resolution improve the accuracy and the best error rate of 3.71% was achieved at the 3-min resolution.

A Non-consecutive Cloth Draping Simulation Algorithm using Conjugate Harmonic Functions (켤레조화함수를 이용한 비순차적 의류 주름 모사 알고리즘)

  • Kang Moon Koo
    • Journal of KIISE:Software and Applications
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    • v.32 no.3
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    • pp.181-191
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    • 2005
  • This article describes a simplified mathematical model and the relevant numerical algorithm to simulate the draped cloth on virtual human body. The proposed algorithm incorporates an elliptical, or non-consecutive, method to simulate the cloth wrinkles on moving bodies without resorting to the result of the past time-steps of drape simulation. A global-local analysis technique was employed to decompose the drape of cloths into the global deformation and the local wrinkles that will be superposed linearly The global deformation is determined directly by the rotation and the translation of body parts to generate a wrinkle-free yet globally deformed shape of cloth. The local wrinkles are calculated by solving simple elliptical equations based on the orthogonality between conjugate harmonic functions representing the wrinkle amplitude and the direction of wrinkles. The proposed method requires no interpolative time frames even for discontinuous body postures. Standing away from the incremental approach of time integration in conventional methods, the proposed method yields a remarkable reduction of CPU time and an enhanced stability. Also, the transient motion of cloth could be achieved by interpolating between the deformations corresponding to each static posture.

Uniform Posture Map Algorithm to Generate Natural Motion Transitions in Real-time (자연스러운 실시간 동작 전이 생성을 위한 균등 자세 지도 알고리즘)

  • Lee, Bum-Ro;Chung, Chin-Hyun
    • Journal of KIISE:Computing Practices and Letters
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    • v.7 no.6
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    • pp.549-558
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    • 2001
  • It is important to reuse existing motion capture data for reduction of the animation producing cost as well as efficiency of producing process. Because its motion curve has no control point, however, it is difficult to modify the captured data interactively. The motion transition is a useful method to reuse the existing motion data. It generates a seamless intermediate motion with two short motion sequences. In this paper, Uniform Posture Map (UPM) algorithm is proposed to perform the motion transition. Since the UPM is organized through quantization of various postures with an unsupervised learning algorithm, it places the output neurons with similar posture in adjacent position. Using this property, an intermediate posture of two active postures is generated; the generating posture is used as a key-frame to make an interpolating motion. The UPM algorithm needs much less computational cost, in comparison with other motion transition algorithms. It provides a control parameter; an animator could control the motion simply by adjusting the parameter. These merits of the UPM make an animator to produce the animation interactively. The UPM algorithm prevents from generating an unreal posture in learning phase. It not only makes more realistic motion curves, but also contributes to making more natural motions. The motion transition algorithm proposed in this paper could be applied to the various fields such as real time 3D games, virtual reality applications, web 3D applications, and etc.

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Adaptive Block Recovery Based on Subband Energy and DC Value in Wavelet Domain (웨이블릿 부대역의 에너지와 DC 값에 근거한 적응적 블록 복구)

  • Hyun, Seung-Hwa;Eom, Il-Kyu;Kim, Yoo-Shin
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.42 no.5 s.305
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    • pp.95-102
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    • 2005
  • When images compressed with block-based compression techniques are transmitted over a noisy channel, unexpected block losses occur. In this paper, we present a post-processing-based block recovery scheme using Haar wavelet features. No consideration of the edge-direction, when recover the lost blocks, can cause block-blurring effects. The proposed directional recovery method in this paper is effective for the strong edge because exploit the varying neighboring blocks adaptively according to the edges and the directional information in the image. First, the adaptive selection of neighbor blocks is performed based on the energy of wavelet subbands (EWS) and difference of DC values (DDC). The lost blocks are recovered by the linear interpolation in the spatial domain using selected blocks. The method using only EWS performs well for horizontal and vertical edges, but not as well for diagonal edges. Conversely, only using DDC performs well diagonal edges with the exception of line- or roof-type edge profiles. Therefore, we combined EWS and DDC for better results. The proposed methods out performed the previous methods using fixed blocks.

Oil Spill Visualization and Particle Matching Algorithm (유출유 이동 가시화 및 입자 매칭 알고리즘)

  • Lee, Hyeon-Chang;Kim, Yong-Hyuk
    • Journal of the Korea Convergence Society
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    • v.11 no.3
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    • pp.53-59
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    • 2020
  • Initial response is important in marine oil spills, such as the Hebei Spirit oil spill, but it is very difficult to predict the movement of oil out of the ocean, where there are many variables. In order to solve this problem, the forecasting of oil spill has been carried out by expanding the particle prediction, which is an existing study that studies the movement of floats on the sea using the data of the float. In the ocean data format HDF5, the current and wind velocity data at a specific location were extracted using bilinear interpolation, and then the movement of numerous points was predicted by particles and the results were visualized using polygons and heat maps. In addition, we propose a spill oil particle matching algorithm to compensate for the lack of data and the difference between the spilled oil and movement. The spilled oil particle matching algorithm is an algorithm that tracks the movement of particles by granulating the appearance of surface oil spilled oil. The problem was segmented using principal component analysis and matched using genetic algorithm to the point where the variance of travel distance of effluent oil is minimized. As a result of verifying the effluent oil visualization data, it was confirmed that the particle matching algorithm using principal component analysis and genetic algorithm showed the best performance, and the mean data error was 3.2%.

Advanced Neighbor Embedding based on Support Vector Regression (SVR에 기반한 개선된 네이버 임베딩)

  • Eum, Kyoung-Bae;Jeon, Chang-Woo;Choi, Young-Hee;Nam, Seung-Tae;Lee, Jong-Chan
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2014.10a
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    • pp.733-735
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    • 2014
  • Example based Super Resolution(SR) is using the correspondence between the low and high resolution image from a database. This method uses only one image to estimate a high resolution image and can get the larger image than 2 times. Example based SR is proposed to solve the problem of classical SR. Neighbor embedding(NE) has been inspired by manifold learning method, particularly locally linear embedding. However, the poor generalization of NE decreases the performance of such algorithm. The sizes of local training sets are always too small to improve the performance of NE. We propose the advanced NE baesd on SVR having an excellent generalization ability to solve this problem. Given a low resolution image, we estimate a pixel in its high resolution version by using SVR based NE. Through experimental results, we quantitatively and qualitatively confirm the improved results of the proposed algorithm when comparing with conventional interpolation methods and NE.

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Experimental Study on the Adsorption Characteristics of Methane Gas Considering Coalbed Depth in Coalbed Methane Reservoirs (석탄층 메탄가스 저류층에서 탄층 심도를 고려한 메탄가스의 흡착 특성에 관한 실험 연구)

  • Chayoung Song;Dongjin Lee;Jeonghwan Lee
    • Journal of the Korean Institute of Gas
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    • v.27 no.2
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    • pp.39-48
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    • 2023
  • This study presents the experimental results to measure the adsorption amount of methane gas by coal according to the conditions of a coalbed methane (CBM) reservoir. Adsorbed gas to coal seam particles was measured under reservoir conditions (normal pressure ~ 1,200 psi pressure range, temperature range15 ~ 45℃) using coal samples obtained from random mines in Kalimantan Island, North Indonesia. The obtained amount of absolute adsorbed gas was applied to triangular with linear interpolation to calculate the maximum amount of adsorbed gas according to temperature and pressure change, at which no experiment was performed. As a result, it was revealed that the amount of adsorbed gas to coal particles increased as the pressure increased and temperature decreased, but the increase of the amount of adsorbed gas decreased at more than an appropriate depth(1,000 ft). In the cleat permeability and cleat porosity for each depth of the coal bed considering the effective stress, the cleat permeability was 28.86 ~ 46.81 md, and the cleat porosity was 0.83 ~ 0.98%. This means that the gas productivity varies significantly with the depth because the reduction of the permeability according to the depth in the coal seam is significant. Therefore, a coalbed depth should be considered essential when designing the spacing of production wells in a coalbed methane reservoir in further study.