• Title/Summary/Keyword: extrema

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A Spiking Neural Network for Autonomous Search and Contour Tracking Inspired by C. elegans Chemotaxis and the Lévy Walk

  • Chen, Mohan;Feng, Dazheng;Su, Hongtao
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.9
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    • pp.2846-2866
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    • 2022
  • Caenorhabditis elegans exhibits sophisticated chemotaxis behavior through two parallel strategies, klinokinesis and klinotaxis, executed entirely by a small nervous circuit. It is therefore suitable for inspiring fast and energy-efficient solutions for autonomous navigation. As a random search strategy, the Lévy walk is optimal for diverse animals when foraging without external chemical cues. In this study, by combining these biological strategies for the first time, we propose a spiking neural network model for search and contour tracking of specific concentrations of environmental variables. Specifically, we first design a klinotaxis module using spiking neurons. This module works in conjunction with a klinokinesis module, allowing rapid searches for the concentration setpoint and subsequent contour tracking with small deviations. Second, we build a random exploration module. It generates a Lévy walk in the absence of concentration gradients, increasing the chance of encountering gradients. Third, considering local extrema traps, we develop a termination module combined with an escape module to initiate or terminate the escape in a timely manner. Experimental results demonstrate that the proposed model integrating these modules can switch strategies autonomously according to the information from a single sensor and control steering through output spikes, enabling the model worm to efficiently navigate across various scenarios.

An autonomous synchronized switch damping on inductance and negative capacitance for piezoelectric broadband vibration suppression

  • Qureshi, Ehtesham Mustafa;Shen, Xing;Chang, Lulu
    • International Journal of Aeronautical and Space Sciences
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    • v.17 no.4
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    • pp.501-517
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    • 2016
  • Synchronized switch damping (SSD) is a structural vibration control technique in which a piezoelectric patch attached to or embedded into the structure is connected to or disconnected from the shunt circuit in order to dissipate the vibration energy of the host structure. The switching process is performed by a digital signal processor (DSP) which detects the displacement extrema and generates a command to operate the switch in synchronous with the structure motion. Recently, autonomous SSD techniques have emerged in which the work of DSP is taken up by a low pass filter, thus making the whole system autonomous or self-powered. The control performance of the previous autonomous SSD techniques heavily relied on the electrical quality factor of the shunt circuit which limited their damping performance. Thus in order to reduce the influence of the electrical quality factor on the damping performance, a new autonomous SSD technique is proposed in this paper in which a negative capacitor is used along with the inductor in the shunt circuit. Only a negative capacitor could also be used instead of inductor but it caused saturation of negative capacitor in the absence of an inductor due to high current generated during the switching process. The presence of inductor in the shunt circuit of negative capacitor limits the amount of current supplied by the negative capacitance, thus improving the damping performance. In order to judge the control performance of proposed autonomous SSDNCI, a comparison is made between the autonomous SSDI, autonomous SSDNC and autonomous SSDNCI techniques for the control of an aluminum cantilever beam subjected to both single mode and multimode excitation. A value of negative capacitance slightly greater than the piezoelectric patch capacitance gave the optimum damping results. Experiment results confirmed the effectiveness of the proposed autonomous SSDNCI technique as compared to the previous techniques. Some limitations and drawbacks of the proposed technique are also discussed.

Genetic Algorithm based B-spline Fitting for Contour Extraction from a Sequence of Images (연속 영상에서의 경계추출을 위한 유전자 알고리즘 기반의 B-spline 적합)

  • Heo Hoon;Lee JeongHeon;Chae OkSam
    • Journal of KIISE:Software and Applications
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    • v.32 no.5
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    • pp.357-365
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    • 2005
  • We present a B-spline fitting method based on genetic algorithm for the extraction of object contours from the complex image sequence, where objects with similar shape and intensity are adjacent each other. The proposed algorithm solves common malfitting problem of the existing B-spline fitting methods including snakes. Classical snake algorithms have not been successful in such an image sequence due to the difficulty in initialization and existence of multiple extrema. We propose a B-spline fitting method using a genetic algorithm with a new initial population generation and fitting function, that are designed to take advantage of the contour of the previous slice. The test results show that the proposed method extracts contour of individual object successfully from the complex image sequence. We validate the algorithm by false-positive/negative errors and relative amounts of agreements.

Extreme value modeling of structural load effects with non-identical distribution using clustering

  • Zhou, Junyong;Ruan, Xin;Shi, Xuefei;Pan, Chudong
    • Structural Engineering and Mechanics
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    • v.74 no.1
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    • pp.55-67
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    • 2020
  • The common practice to predict the characteristic structural load effects (LEs) in long reference periods is to employ the extreme value theory (EVT) for building limit distributions. However, most applications ignore that LEs are driven by multiple loading events and thus do not have the identical distribution, a prerequisite for EVT. In this study, we propose the composite extreme value modeling approach using clustering to (a) cluster initial blended samples into finite identical distributed subsamples using the finite mixture model, expectation-maximization algorithm, and the Akaike information criterion; (b) combine limit distributions of subsamples into a composite prediction equation using the generalized Pareto distribution based on a joint threshold. The proposed approach was validated both through numerical examples with known solutions and engineering applications of bridge traffic LEs on a long-span bridge. The results indicate that a joint threshold largely benefits the composite extreme value modeling, many appropriate tail approaching models can be used, and the equation form is simply the sum of the weighted models. In numerical examples, the proposed approach using clustering generated accurate extrema prediction of any reference period compared with the known solutions, whereas the common practice of employing EVT without clustering on the mixture data showed large deviations. Real-world bridge traffic LEs are driven by multi-events and present multipeak distributions, and the proposed approach is more capable of capturing the tendency of tailed LEs than the conventional approach. The proposed approach is expected to have wide applications to general problems such as samples that are driven by multiple events and that do not have the identical distribution.

No-reference objective quality assessment of image using blur and blocking metric (블러링과 블록킹 수치를 이용한 영상의 무기준법 객관적 화질 평가)

  • Jeong, Tae-Uk;Kim, Young-Hie;Lee, Chul-Hee
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.46 no.3
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    • pp.96-104
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    • 2009
  • In this paper, we propose a no-reference objective Quality assessment metrics of image. The blockiness and blurring of edge areas which are sensitive to the human visual system are modeled as step functions. Blocking and blur metrics are obtained by estimating local visibility of blockiness and edge width, For the blocking metric, horizontal and vertical blocking lines are first determined by accumulating weighted differences of adjacent pixels and then the local visibility of blockiness at the intersection of blocking lines is obtained from the total difference of amplitudes of the 2-D step function which is modelled as a blocking region. The blurred input image is first re-blurred by a Gaussian blur kernel and an edge mask image is generated. In edge blocks, the local edge width is calculated from four directional projections (horizontal, vertical and two diagonal directions) using local extrema positions. In addition, the kurtosis and SSIM are used to compute the blur metric. The final no-reference objective metric is computed after those values are combined using an appropriate function. Experimental results show that the proposed objective metrics are highly correlated to the subjective data.

Parameter Analysis for Time Reduction in Extracting SIFT Keypoints in the Aspect of Image Stitching (영상 스티칭 관점에서 SIFT 특징점 추출시간 감소를 위한 파라미터 분석)

  • Moon, Won-Jun;Seo, Young-Ho;Kim, Dong-Wook
    • Journal of Broadcast Engineering
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    • v.23 no.4
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    • pp.559-573
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    • 2018
  • Recently, one of the most actively applied image media in the most fields such as virtual reality (VR) is omni-directional or panorama image. This image is generated by stitching images obtained by various methods. In this process, it takes the most time to extract keypoints necessary for stitching. In this paper, we analyze the parameters involved in the extraction of SIFT keypoints with the aim of reducing the computation time for extracting the most widely used SIFT keypoints. The parameters considered in this paper are the initial standard deviation of the Gaussian kernel used for Gaussian filtering, the number of gaussian difference image sets for extracting local extrema, and the number of octaves. As the SIFT algorithm, the Lowe scheme, the originally proposed one, and the Hess scheme which is a convolution cascade scheme, are considered. First, the effect of each parameter value on the computation time is analyzed, and the effect of each parameter on the stitching performance is analyzed by performing actual stitching experiments. Finally, based on the results of the two analyses, we extract parameter value set that minimize computation time without degrading.

Coordinative movement of articulators in bilabial stop /p/

  • Son, Minjung
    • Phonetics and Speech Sciences
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    • v.10 no.4
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    • pp.77-89
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    • 2018
  • Speech articulators are coordinated for the purpose of segmental constriction in terms of a task. In particular, vertical jaw movements repeatedly contribute to consonantal as well as vocalic constriction. The current study explores vertical jaw movements in conjunction with bilabial constriction in bilabial stop /p/ in the context /a/-to-/a/. Revisiting kinematic data of /p/ collected using the electromagenetic midsagittal articulometer (EMMA) method from seven (four female and three male) speakers of Seoul Korean, we examined maximum vertical jaw position, its relative timing with respect to the upper and lower lips, and lip aperture minima. The results of those dependent variables are recapitulated in terms of linguistic (different word boundaries) and paralinguistic (different speech rates) factors as follows. Firstly, maximum jaw height was lower in the across-word boundary condition (across-word < within-word), but it did not differ as a function of different speech rates (comfortable = fast). Secondly, more reduction in the lip aperture (LA) gesture occurred in fast rate, while word-boundary effects were absent. Thirdly, jaw raising was still in progress after the lips' positional extrema were achieved in the within-word condition, while the former was completed before the latter in the across-word condition. Lastly, relative temporal lags between the jaw and the lips (UL and LL) were more synchronous in fast rate, compared to comfortable rate. When these results are considered together, it is possible to posit that speakers are not tolerant of lenition to the extent that it is potentially realized as a labial approximant in either word-boundary condition while jaw height still manifested lower jaw position in the across-word boundary condition. Early termination of vertical jaw maxima before vertical lower lip maxima across-word condition may be partly responsible for the spatial reduction of jaw raising movements. This may come about as a consequence of an excessive number of factors (e.g., upper lip height (UH), lower lip height (LH), jaw angle (JA)) for the representation of a vector with two degrees of freedom (x, y) engaged in a gesture-based task (e.g., lip aperture (LA)). In the task-dynamic application toolkit, the jaw angle parameter can be assigned numerical values for greater weight in the across-word boundary condition, which in turn gives rise to lower jaw position. Speech rate-dependent spatial reduction in lip aperture may be able to be resolved by means of manipulating activation time of an active tract variable in the gestural score level.