• Title/Summary/Keyword: artificial target

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Characteristics of Wildbirds Habitat of Artificial Green Corridor in Gangseo-gu, Seoul (서울시 강서구 조성녹지축의 야생조류 서식처 특성 연구)

  • Choi, Jin-Woo;Lee, Kyong-Jae
    • Journal of Environmental Science International
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    • v.19 no.1
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    • pp.47-59
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    • 2010
  • This study was to examine the characteristics of wirdbirds habitat for improvement plan in green corridor. The target site, Gangseo-gu artificial green corridor was set up with the structure in which small scale of core green space with Goongsan and Yeomchang neighborhood parks in urbanized city was connected with the artificial green space with Gongamnaru, Hwanggeumnae neighborhood parks with 28~42.5 m in width. Wild birds six~eleven species; Dendrocopos spp, Paradoxornis webbiana, Parus major, Phasianus colchicus, etc. were observed in core green, but wild birds of two~five species: Columba livuia, Passer montanus, Pica pica, Hypsipetes amaurotis, etc. were observed in artificial green space. Thus wild birds of artificial and generalist species only moved in artificial green space. The artificial green space where vegetation structure was consisted of single-layer with poorness chose target species laying stress on generalist species and edge species of Parus major, P. palustris, Paradoxornis webbiana etc. for short-term and interior species of Dendrocopos major, Picus canus, etc. for long-term. The result suggested enhancement methods for target species's habitat in green corridor: to secure at least a corridor 30 meters in artificial corridor, to secure ecological pond, to offer the various shelterer and environment of prey-resources through the multi-layer structure.

Multi-resolution Fusion Network for Human Pose Estimation in Low-resolution Images

  • Kim, Boeun;Choo, YeonSeung;Jeong, Hea In;Kim, Chung-Il;Shin, Saim;Kim, Jungho
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.7
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    • pp.2328-2344
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    • 2022
  • 2D human pose estimation still faces difficulty in low-resolution images. Most existing top-down approaches scale up the target human bonding box images to the large size and insert the scaled image into the network. Due to up-sampling, artifacts occur in the low-resolution target images, and the degraded images adversely affect the accurate estimation of the joint positions. To address this issue, we propose a multi-resolution input feature fusion network for human pose estimation. Specifically, the bounding box image of the target human is rescaled to multiple input images of various sizes, and the features extracted from the multiple images are fused in the network. Moreover, we introduce a guiding channel which induces the multi-resolution input features to alternatively affect the network according to the resolution of the target image. We conduct experiments on MS COCO dataset which is a representative dataset for 2D human pose estimation, where our method achieves superior performance compared to the strong baseline HRNet and the previous state-of-the-art methods.

Autonomous Mobile Robot Navigation using Artificial Immune Networks and Fuzzy Systems (인공 면역망과 퍼지 시스템을 이용한 자율이동로봇 주행)

  • Kim, Yang-Hyeon;Lee, Dong-Je;Lee, Min-Jung;Choe, Yeong-Gyu
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.51 no.9
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    • pp.402-412
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    • 2002
  • The navigation algorithms enable autonomous mobile robots to reach given target points without collision against obstacles. To achieve safe navigations in unknown environments, this paper presents an effective navigation algorithm for the autonomous mobile robots with ultrasonic sensors. The proposed navigation algorithm consists of an obstacle-avoidance behavior, a target-reaching behavior and a fuzzy-based decision maker. In the obstacle-avoidance behavior and the target-reaching behavior, artificial immune networks are used to select a proper steering angle, make the autonomous mobile robot avoid obstacles and approach a given target point. The fuzzy-based decision maker combines the steering angles from the target-reaching behavior and the obstacle-avoidance behavior in order to steer the autonomous mobile robot appropriately. Simulational and experimental results show that the proposed navigation algorithm is very effective in unknown environments.

Effect of PSD Function on Linear Response and Inelastic Response of Single Degree of Freedom System (단자유도 시스템의 선형응답과 비탄성응답에 미치는 PSD함수의 영향)

  • Choi, Dong-Ho;Lee, Sang-Hoon;Kim, Yong-Sik;Koh, Jung-Hoon
    • 한국방재학회:학술대회논문집
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    • 2008.02a
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    • pp.257-259
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    • 2008
  • Acceleration time history (ATH) used in the seismic analysis should envelop a target power spectral density (PSD) function in addition to the design response spectrum in order to have sufficient energy at each frequency for the purpose of ensuring adequate load. Even though design regulations require the ATH used in seismic analysis to meet a target PSD function, the reason that ATHs meet to a target PSD function is not described. Thus, artificial ATHs for high PSD function and artificial ATHs for low PSD function are generated. And then elastic and inelastic single-degree-of-freedom (SDOF) systems are loaded with these artificial time histories as the earthquake load. As a result, linear response and inelastic response of SDOF systems are affected by PSD function.

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New development of artificial record generation by wavelet theory

  • Amiri, G. Ghodrati;Ashtari, P.;Rahami, H.
    • Structural Engineering and Mechanics
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    • v.22 no.2
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    • pp.185-195
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    • 2006
  • Nowadays it is very necessary to generate artificial accelerograms because of lack of adequate earthquake records and vast usage of time-history dynamic analysis to calculate responses of structures. According to the lack of natural records, the best choice is to use proper artificial earthquake records for the specified design zone. These records should be generated in a way that would contain seismic properties of a vast area and therefore could be applied as design records. The main objective of this paper is to present a new method based on wavelet theory to generate more artificial earthquake records, which are compatible with target spectrum. Wavelets are able to decompose time series to several levels that each level covers a specific range of frequencies. If an accelerogram is transformed by Fourier transform to frequency domain, then wavelets are considered as a transform in time-scale domain which frequency has been changed to scale in the recent domain. Since wavelet theory separates each signal, it is able to generate so many artificial records having the same target spectrum.

Artificial Intelligence based Threat Assessment Study of Uncertain Ground Targets (불확실 지상 표적의 인공지능 기반 위협도 평가 연구)

  • Jin, Seung-Hyeon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.6
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    • pp.305-313
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    • 2021
  • The upcoming warfare will be network-centric warfare with the acquiring and sharing of information on the battlefield through the connection of the entire weapon system. Therefore, the amount of information generated increases, but the technology of evaluating the information is insufficient. Threat assessment is a technology that supports a quick decision, but the information has many uncertainties and is difficult to apply to an advanced battlefield. This paper proposes a threat assessment based on artificial intelligence while removing the target uncertainty. The artificial intelligence system used was a fuzzy inference system and a multi-layer perceptron. The target was classified by inputting the unique characteristics of the target into the fuzzy inference system, and the classified target information was input into the multi-layer perceptron to calculate the appropriate threat value. The validity of the proposed technique was verified with the threat value calculated by inputting the uncertain target to the trained artificial neural network.

Application of wavelet multiresolution analysis and artificial intelligence for generation of artificial earthquake accelerograms

  • Amiri, G. Ghodrati;Bagheri, A.
    • Structural Engineering and Mechanics
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    • v.28 no.2
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    • pp.153-166
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    • 2008
  • This paper suggests the use of wavelet multiresolution analysis (WMRA) and neural network for generation of artificial earthquake accelerograms from target spectrum. This procedure uses the learning capabilities of radial basis function (RBF) neural network to expand the knowledge of the inverse mapping from response spectrum to earthquake accelerogram. In the first step, WMRA is used to decompose earthquake accelerograms to several levels that each level covers a special range of frequencies, and then for every level a RBF neural network is trained to learn to relate the response spectrum to wavelet coefficients. Finally the generated accelerogram using inverse discrete wavelet transform is obtained. An example is presented to demonstrate the effectiveness of the method.

Development of a Natural Target-based Edge Analysis Method for NIIRS Estimation (NIIRS 추정을 위한 자연표적 기반의 에지분석기법 개발)

  • Kim, Jae-In;Kim, Tae-Jung
    • Korean Journal of Remote Sensing
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    • v.27 no.5
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    • pp.587-599
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    • 2011
  • As one measure of image interpretability, NIIRS(National Imagery Interpretability Rating Scale) has been used. Unlike MTF(Modulation Transfer Function), SNR(Signal to Noise Ratio), and GSD(Ground Sampling Distance), NIIRS can describe the quality of overall image at user's perspective. NIIRS is observed with human observation directly or estimated by edge analysis. For edge analysis specially manufactured artificial target is used commonly. This target, formed with a tarp of black and white patterns, is deployed on the ground and imaged by the satellite. Due to this, the artificial target-based method needs a big expense and can not be performed often. In this paper, we propose a new edge analysis method that enables to estimate NIIRS accurately. In this method, natural targets available in the image are used and characteristics of the target are considered. For assessment of the algorithm, various experiments were carried out. The results showed that our algorithm can be used as an alternative to the artificial target-based method.

A Navigation Algorithm for Autonomous Mobile Robots using Artificial Immune Networks and Fuzzy Systems

  • Kim, Yang-Hyun;Lee, Dong-Je;Lee, Min-Jung;Choi, Young-Kiu
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.134.6-134
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    • 2001
  • The purpose of navigation algorithm is to reach a given target point without collision with obstacles while an autonomous mobile robot is navigating. To achieve a safe navigation, this paper presents an effective navigation algorithm for the autonomous mobile robot equipped with ultrasonic sensors in unknown environments. The proposed navigation algorithm consists of an obstacle-avoidance behavior, a target-reaching behavior and a fuzzy-based decision maker. In the obstacle-avoidance behavior and the target-reaching behavior, artificial immune networks are used to select a proper steering angle, make the autonomous mobile robot avoid obstacles and approach a given target point. The decision maker using fuzzy inference systems weights the steering angles selected ...

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Application of neural networks and an adapted wavelet packet for generating artificial ground motion

  • Asadi, A.;Fadavi, M.;Bagheri, A.;Ghodrati Amiri, G.
    • Structural Engineering and Mechanics
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    • v.37 no.6
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    • pp.575-592
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    • 2011
  • For seismic resistant design of critical structures, a dynamic analysis, either response spectrum or time history is frequently required. Owing to the lack of recorded data and the randomness of earthquake ground motion that may be experienced by structure in the future, usually it is difficult to obtain recorded data which fit the requirements (site type, epicenteral distance, etc.) well. Therefore, the artificial seismic records are widely used in seismic designs, verification of seismic capacity and seismic assessment of structures. The purpose of this paper is to develop a numerical method using Artificial Neural Network (ANN) and wavelet packet transform in best basis method which is presented for the decomposition of artificial earthquake records consistent with any arbitrarily specified target response spectra requirements. The ground motion has been modeled as a non-stationary process using wavelet packet. This study shows that the procedure using ANN-based models and wavelet packets in best-basis method are applicable to generate artificial earthquakes compatible with any response spectra. Several numerical examples are given to verify the developed model.