• Steel and Composite Structures
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• v.34 no.5
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• pp.743-767
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• 2020

Due to the impressive flexural performance, enhanced compressive strength and more constrained crack propagation, Fibre-reinforced concrete (FRC) have been widely employed in the construction application. Majority of experimental studies have focused on the seismic behavior of FRC columns. Based on the valid experimental data obtained from the previous studies, the current study has evaluated the seismic response and compressive strength of FRC rectangular columns while following hybrid metaheuristic techniques. Due to the non-linearity of seismic data, Adaptive neuro-fuzzy inference system (ANFIS) has been incorporated with metaheuristic algorithms. 317 different datasets from FRC column tests has been applied as one database in order to determine the most influential factor on the ultimate strengths of FRC rectangular columns subjected to the simulated seismic loading. ANFIS has been used with the incorporation of Particle Swarm Optimization (PSO) and Genetic algorithm (GA). For the analysis of the attained results, Extreme learning machine (ELM) as an authentic prediction method has been concurrently used. The variable selection procedure is to choose the most dominant parameters affecting the ultimate strengths of FRC rectangular columns subjected to simulated seismic loading. Accordingly, the results have shown that ANFIS-PSO has successfully predicted the seismic lateral load with R² = 0.857 and 0.902 for the test and train phase, respectively, nominated as the lateral load prediction estimator. On the other hand, in case of compressive strength prediction, ELM is to predict the compressive strength with R² = 0.657 and 0.862 for test and train phase, respectively. The results have shown that the seismic lateral force trend is more predictable than the compressive strength of FRC rectangular columns, in which the best results belong to the lateral force prediction. Compressive strength prediction has illustrated a significant deviation above 40 Mpa which could be related to the considerable non-linearity and possible empirical shortcomings. Finally, employing ANFIS-GA and ANFIS-PSO techniques to evaluate the seismic response of FRC are a promising reliable approach to be replaced for high cost and time-consuming experimental tests.

• Journal of Communications and Networks
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• v.12 no.4
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• pp.289-307
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• 2010

The problem of model selection arises in a number of contexts, such as subset selection in linear regression, estimation of structures in graphical models, and signal denoising. This paper studies non-asymptotic model selection for the general case of arbitrary (random or deterministic) design matrices and arbitrary nonzero entries of the signal. In this regard, it generalizes the notion of incoherence in the existing literature on model selection and introduces two fundamental measures of coherence-termed as the worst-case coherence and the average coherence-among the columns of a design matrix. It utilizes these two measures of coherence to provide an in-depth analysis of a simple, model-order agnostic one-step thresholding (OST) algorithm for model selection and proves that OST is feasible for exact as well as partial model selection as long as the design matrix obeys an easily verifiable property, which is termed as the coherence property. One of the key insights offered by the ensuing analysis in this regard is that OST can successfully carry out model selection even when methods based on convex optimization such as the lasso fail due to the rank deficiency of the submatrices of the design matrix. In addition, the paper establishes that if the design matrix has reasonably small worst-case and average coherence then OST performs near-optimally when either (i) the energy of any nonzero entry of the signal is close to the average signal energy per nonzero entry or (ii) the signal-to-noise ratio in the measurement system is not too high. Finally, two other key contributions of the paper are that (i) it provides bounds on the average coherence of Gaussian matrices and Gabor frames, and (ii) it extends the results on model selection using OST to low-complexity, model-order agnostic recovery of sparse signals with arbitrary nonzero entries. In particular, this part of the analysis in the paper implies that an Alltop Gabor frame together with OST can successfully carry out model selection and recovery of sparse signals irrespective of the phases of the nonzero entries even if the number of nonzero entries scales almost linearly with the number of rows of the Alltop Gabor frame.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.4
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• pp.438-444
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• 2004

The intelligent robots that will be needed in the near future are human-friendly robots that are able to coexist with humans and support humans effectively. To realize this, robots need to recognize their position and posture in known environment as well as unknown environment. Moreover, it is necessary for their localization to occur naturally. It is desirable for a robot to estimate of his position by solving uncertainty for mobile robot navigation, as one of the best important problems. In this paper, we describe a method for the localization of a mobile robot using image information of a moving object. This method combines the observed position from dead-reckoning sensors and the estimated position from the images captured by a fixed camera to localize a mobile robot. Using the a priori known path of a moving object in the world coordinates and a perspective camera model, we derive the geometric constraint equations which represent the relation between image frame coordinates for a moving object and the estimated robot's position. Since the equations are based or the estimated position, the measurement error may exist all the time. The proposed method utilizes the error between the observed and estimated image coordinates to localize the mobile robot. The Kalman filter scheme is applied for this method. its performance is verified by the computer simulation and the experiment.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.1
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• pp.17-25
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• 2007

In most electronic imaging applications, image with high resolution(HR) are desired. HR means that pixel density within an image is high, and therefore HR image can offer more details that may be critical in various applications. Digital images that are captured by CCD and CMOS cameras usually have a very low resolution, which significantly limits the performance of image recognition systems. Image super-resolution techniques can be applied to overcome the limits of these imaging systems. Super-resolution techniques have been proposed to increase the resolution by combining information from multiple images. To techniques were consisted of the registration algorithm for estimation and shift, the nearest neighbor interpolation using weight of acquired frames and presented frames. In this paper, it is proposed the image interpolation techniques using the wavelet base function. This is applied to embody a correct edge image and natural image when expend part of the still image by applying the wavelet base function coefficient to the conventional Super-Resolution interpolation method. And the proposal algorithm in this paper is confirmed to improve the image applying the nearest neighbor interpolation algorithm, bilinear interpolation algorithm.,bicubic interpolation algorithm through the computer simulation.

• Asian-Australasian Journal of Animal Sciences
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• v.13 no.8
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• pp.1147-1153
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• 2000

A total of 9,540 pigs were evaluated for their growth performance to provide information on the development of different feeding strategies to support maximum rate of protein deposition (PD). Large variations in growth performance and protein deposition rate were found in the population used in this study (ADG from 701 to 974 g/day; ADFI from 1,726 to 2,498 g/day; Feed/gain from 2.10 to 2.90; Backfat thickness from 12.4 to 20.5 mm and PD rate from 103 to 153 g/day). It was found that ADG was positively correlated to PD ($R^2=0.9362$, p<0.0001) while FCR was negatively correlated to PD ($R^2=0.4031$, p<0.0001). Backfat thickness was negatively correlated to PD ($R^2=0.7024$, p<0.0001) and to ADG ($R^2=0.5096$, p<0.0001). The estimated lysine requirement based on PD rate also showed large variation (12.37 to 18.38 g/day true ileal digestible lysine on average between 25 and 100 kg), thus strongly indicated the need of separate feeding strategies for each group of pigs. When pigs were divided into three categories according to estimated whole body PD rate, the group of pigs with the highest PD rate grew faster by 6.3 and 13.9% than pigs with intermediate and low PD rate, respectively. Feed utilization was also more efficient in pigs with a high PD rate. It appeared that pigs with high PD rate maintained higher PD rate especially in the later stage of their life. Pigs with high PD rate require an extra amount of 1.2 and 2.4 g/true digestible lysine per day and 0.4 and 0.8% more lysine in the diet than pigs with intermediate and low PD rate during the growing-finishing period respectively. Results of this study suggest that there is a need for separate feeding strategies for individual group of pigs with different PD rate. It should be noted that average value for each group presented in this report is not the adequate amount for an animals potential for maximum PD rate. With recent development in growth modeling and access to computer technologies to facilitate computation, pork producers can easily estimate pigs protein deposition rate and thus can make their own feeding strategies.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.10C
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• pp.933-941
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• 2006

In this paper, we proposed an efficient coding method for digital hologram (fringe pattern) acquired by a CCD camera or by computer generation using multi-view prediction technique and MPEG video compression standard technique. It proceeds each R, G, or B color component separately. The basic processing unit is a partial image segmented into the size of $N{\times}N$. Each partial image retains the information of the whole object. This method generates an assembled image for a row of the segmented and frequency-transformed partial images, which is the basis of the coding process. That is, a motion estimation and compensation technique of MPEG is applif:d to the reconstructed images from the assembled images with the disparities found during generation of assembled image and the original partial images. Therefore the compressed results are the disparity of eachpartial image to form the assembled image for the corresponding row, assembled image, and the motion vectors and the compensated image for each partial image. The experimental results with the implemented algorithm showed that the proposed method has NC (Normal Correlation) values about 4% higher than the previous method, by which ours has better compression efficiency. Consequently, the Proposed method is expected to be used effectively in the application areas to transmit the digital hologram data. can be identified in comparison with the previous researches and commercial IPs.

• Journal of Korea Water Resources Association
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• v.40 no.6 s.179
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• pp.459-468
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• 2007

To estimate the groundwater recharge, the fully distributed parameter based model, MIKE SHE was applied to the Gyeongan-cheon watershed which is one of the tributaries of Han River Basin, and covers approximately $260km^2$ with about 49 km main stream length. To set up the model, spatial data such as topography, land use, soil, and meteorological data were compiled, and grid size of 200m was applied considering computer ability and reliability of the results. The model was calibrated and validated using a split sample procedure against 4-year daily stream flows at the outlet of the watershed. Statistical criteria for the calibration and validation results indicated a good agreement between the simulated and observed stream flows. The annual recharges calculated from the model were compared with the values from the conventional groundwater recession curve method, and the simulated groundwater levels were compared with the observed values. As a result, it was concluded that the model could reasonably simulate the groundwater level and recharge, and could be a useful tool for estimating spatially/temporally the groundwater recharges, and enhancing the analysis of the watershed water cycle.

• Tunnel and Underground Space
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• v.11 no.3
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• pp.279-288
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• 2001

Jointed rock mass can be analyzed by either continuum model or discontinuum model. Finite element method or finite difference method is mainly used for continuum modelling. Although discontinuum model is very attractive in analyzing the behavior of each block in jointed blocky rock masses, it has shortcomings such that it is difficult to investigate each joint exactly with the present technology and the amount of calculation in computer becomes trio excessive. Moreover, in case of the jointed blocky rock mass which has more than 2 dominant joint sets, it is impossible to model the behavior of each block. Therefore, a model such as ubiquitous joint model theory which assumes the rock mass as a continuum, is required. In the case of tunnels, unlike slopes, it is not easy to obtain safety factor by utilizing analysis method based on limit equilibrium method because it is difficult to assume the shape of failure surface in advance. For this reason, numerical analyses for tunnels have been limited to analyzing stability rather than in calculating the safety factor. In this study, the behavior of a tunnel excavated in jointed rock mass is analyzed numerically by using ubiquitous joint model which can incorporate 2 joint sets and a method to calculate safety factor of the tunnel numerically is presented. To this end, stress reduction technique is adopted.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.8
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• pp.536-546
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• 2006

Painterly animation is a method that expresses painterly images with a hand-painted appearance from a video, and the most crucial element for it is the temporal coherence of brush strokes between frames. A motion map is proposed in this paper as a solution to the issue of maintaining the temporal coherence in the brush strokes between the frames. A motion map is the region that frame-to-frame motions have occurred. Namely, this map refers to the region frame-to-frame edges move by the motion information with the motion occurred edges as a starting point. In this paper, we employ the optical flow method and block-based method to estimate the motion information. The method that yielded the biggest PSNR using the motion information (the directions and magnitudes) acquired by various methods of motion estimation has been chosen as the final motion information to form a motion map. The created motion map determine the part of the frame that should be re-painted. In order to express painterly images with a hand- painted appearance and maintain the temporal coherence of brush strokes, the motion information was applied to only the strong edges that determine the directions of the brush strokes. Also, this paper seek to reduce the flickering phenomenon between the frames by using the multiple exposure method and the difference map created by the difference between images of the source and the canvas. Maintenance of the coherence in the direction of the brush strokes was also attempted by a local gradient interpolation to maintain the structural coherence.

• The Journal of the Acoustical Society of Korea
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• v.24 no.4
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• pp.230-237
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• 2005

The angle-tracking of maneuvering targets is required to the state estimation and classification of targets in underwater acoustic systems. The Problem of angle-tracking multiple closed and crossing targets has been studied by various authors. Sword et al. Proposed a multiple target an91e-tracking algorithm using angular innovations of the targets during a sampling Period are estimated in the least square sense using the most recent estimate of the sensor output covariance matrix. This algorithm has attractive features of simple structure and avoidance of data association problem. Ryu et al. recently Proposed an effective multiple target angle-tracking algorithm which can obtain the angular innovations of the targets from a signal subspace instead of the sensor output covariance matrix. Hwang et al. improved the computational performance of a multiple target angle-tracking algorithm based on the fact that the steering vector and the noise subspace are orthogonal. These algorithms. however. are ineffective when a subset of the incident sources are coherent. In this Paper, we proposed a new multiple target angle-tracking algorithm for coherent and incoherent sources. The proposed algorithm uses the relationship between source steering vectors and the signal eigenvectors which are multiplied noise covariance matrix. The computer simulation results demonstrate the improved Performance of the Proposed algorithm.