• Title/Summary/Keyword: Simultaneous optimization

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2D Pose Nodes Sampling Heuristic for Fast Loop Closing (빠른 루프 클로징을 위한 2D 포즈 노드 샘플링 휴리스틱)

  • Lee, Jae-Jun;Ryu, Jee-Hwan
    • Journal of Institute of Control, Robotics and Systems
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    • v.22 no.12
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    • pp.1021-1026
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    • 2016
  • The graph-based SLAM (Simultaneous Localization and Mapping) approach has been gaining much attention in SLAM research recently thanks to its ability to provide better maps and full trajectory estimations when compared to the filtering-based SLAM approach. Even though graph-based SLAM requires batch processing causing it to be computationally heavy, recent advancements in optimization and computing power enable it to run fast enough to be used in real-time. However, data association problems still require large amount of computation when building a pose graph. For example, to find loop closures it is necessary to consider the whole history of the robot trajectory and sensor data within the confident range. As a pose graph grows, the number of candidates to be searched also grows. It makes searching the loop closures a bottleneck when solving the SLAM problem. Our approach to alleviate this bottleneck is to sample a limited number of pose nodes in which loop closures are searched. We propose a heuristic for sampling pose nodes that are most advantageous to closing loops by providing a way of ranking pose nodes in order of usefulness for closing loops.

Whole learning algorithm of the neural network for modeling nonlinear and dynamic behavior of RC members

  • Satoh, Kayo;Yoshikawa, Nobuhiro;Nakano, Yoshiaki;Yang, Won-Jik
    • Structural Engineering and Mechanics
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    • v.12 no.5
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    • pp.527-540
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    • 2001
  • A new sort of learning algorithm named whole learning algorithm is proposed to simulate the nonlinear and dynamic behavior of RC members for the estimation of structural integrity. A mathematical technique to solve the multi-objective optimization problem is applied for the learning of the feedforward neural network, which is formulated so as to minimize the Euclidean norm of the error vector defined as the difference between the outputs and the target values for all the learning data sets. The change of the outputs is approximated in the first-order with respect to the amount of weight modification of the network. The governing equation for weight modification to make the error vector null is constituted with the consideration of the approximated outputs for all the learning data sets. The solution is neatly determined by means of the Moore-Penrose generalized inverse after summarization of the governing equation into the linear simultaneous equations with a rectangular matrix of coefficients. The learning efficiency of the proposed algorithm from the viewpoint of computational cost is verified in three types of problems to learn the truth table for exclusive or, the stress-strain relationship described by the Ramberg-Osgood model and the nonlinear and dynamic behavior of RC members observed under an earthquake.

Magnetoencephalography Source Localization using Improved Downhill Simplex Method in Frequency Domain (개선된 다운힐 심플렉스 법을 이용한 주파수 영역에서의 뇌자도 신호원 추정)

  • Kim, Byeong-Jun;An, Kwang-Ok;Lee, Chany;Jung, Hyun-Kyo
    • Journal of Biomedical Engineering Research
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    • v.29 no.3
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    • pp.231-238
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    • 2008
  • Nelder-Mead downhill simplex method (DSM), a kind of deterministic optimization algorithms, has been used extensively for magnetoencephalography(MEG) dipolar source localization problems because it dose not require any functional differentiation. Like many other deterministic algorithms, however, it is very sensitive to the choice of initial positions and it can be easily trapped in local optima when being applied to complex inverse problems with multiple simultaneous sources. In this paper, some modifications have been made to make up for DSM's limitations and improve the accuracy of DSM. First of all, initial point determination method for DSM using magnetic fields on the sensor surface was proposed. Secondly, Univariant-DSM combined DSM with univariant method was proposed. To verify the performance of the proposed method, it was applied to simulated MEG data and practical MEG measurements.

Image Restoration and Object Removal Using Prioritized Adaptive Patch-Based Inpainting in a Wavelet Domain

  • Borole, Rajesh P.;Bonde, Sanjiv V.
    • Journal of Information Processing Systems
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    • v.13 no.5
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    • pp.1183-1202
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    • 2017
  • Image restoration has been carried out by texture synthesis mostly for large regions and inpainting algorithms for small cracks in images. In this paper, we propose a new approach that allows for the simultaneous fill-in of different structures and textures by processing in a wavelet domain. A combination of structure inpainting and patch-based texture synthesis is carried out, which is known as patch-based inpainting, for filling and updating the target region. The wavelet transform is used for its very good multiresolution capabilities. The proposed algorithm uses the wavelet domain subbands to resolve the structure and texture components in smooth approximation and high frequency structural details. The subbands are processed separately by the prioritized patch-based inpainting with isophote energy driven texture synthesis at the core. The algorithm automatically estimates the wavelet coefficients of the target regions of various subbands using optimized patches from the surrounding DWT coefficients. The suggested performance improvement drastically improves execution speed over the existing algorithm. The proposed patch optimization strategy improves the quality of the fill. The fill-in is done with higher priority to structures and isophotes arriving at target boundaries. The effectiveness of the algorithm is demonstrated with natural and textured images with varying textural complexions.

Simultaneous Estimation of Spatial Frequency and Phase Based on an Improved Component Cross-Correlation Algorithm for Structured Illumination Microscopy

  • Zhang, Yinxin;Deng, Jiajun;Liu, Guoxuan;Fei, Jianyang;Yang, Huaidong
    • Current Optics and Photonics
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    • v.4 no.4
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    • pp.317-325
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    • 2020
  • Accurate estimation of spatial frequencies and phases for illumination patterns are essential to reconstructing super-resolution images in structured illumination microscopy (SIM). In this manuscript, we propose the improved component cross-correlation (ICC) algorithm, which is based on optimization of the cross-correlation values of the overlapping information between various spectral components. Compared to other algorithms for spatial-frequency and phase determination, the results calculated by the ICC algorithm are more accurate when the modulation depths of the illumination patterns are low. Moreover, the ICC algorithm is able to calculate the spatial frequencies and phases simultaneously. Simulation results indicate that even if the modulation depth is lower than 0.1, the ICC algorithm still estimates the parameters precisely; the images reconstructed by the ICC algorithm are much clearer than those reconstructed by other algorithms. In experiments, our home-built SIM system was used to image bovine pulmonary artery endothelial (BPAE) cells. Drawing support from the ICC algorithm, super-resolution images were reconstructed without artifacts.

DiLO: Direct light detection and ranging odometry based on spherical range images for autonomous driving

  • Han, Seung-Jun;Kang, Jungyu;Min, Kyoung-Wook;Choi, Jungdan
    • ETRI Journal
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    • v.43 no.4
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    • pp.603-616
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    • 2021
  • Over the last few years, autonomous vehicles have progressed very rapidly. The odometry technique that estimates displacement from consecutive sensor inputs is an essential technique for autonomous driving. In this article, we propose a fast, robust, and accurate odometry technique. The proposed technique is light detection and ranging (LiDAR)-based direct odometry, which uses a spherical range image (SRI) that projects a three-dimensional point cloud onto a two-dimensional spherical image plane. Direct odometry is developed in a vision-based method, and a fast execution speed can be expected. However, applying LiDAR data is difficult because of the sparsity. To solve this problem, we propose an SRI generation method and mathematical analysis, two key point sampling methods using SRI to increase precision and robustness, and a fast optimization method. The proposed technique was tested with the KITTI dataset and real environments. Evaluation results yielded a translation error of 0.69%, a rotation error of 0.0031°/m in the KITTI training dataset, and an execution time of 17 ms. The results demonstrated high precision comparable with state-of-the-art and remarkably higher speed than conventional techniques.

An optimization technique for simultaneous reduction of PAPR and out-of-band power in NC-OFDM-based cognitive radio systems

  • Kaliki, Sravan Kumar;Golla, Shiva Prasad;Kurukundu, Rama Naidu
    • ETRI Journal
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    • v.43 no.1
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    • pp.7-16
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    • 2021
  • Noncontiguous orthogonal frequency division multiplexing (NC-OFDM)-based cognitive radio (CR) systems achieve highly efficient spectrum utilization by transmitting unlicensed users' data on subcarriers of licensed users' data when they are free. However, there are two disadvantages to the NC-OFDM system: out-of-band power (OBP) and a high peak-to-average power ratio (PAPR). OBP arises due to side lobes of an NC-OFDM signal in the frequency domain, and it interferes with the spectrum for unlicensed users. A high PAPR occurs due to the inverse fast Fourier transform (IFFT) block used in an NC-OFDM system, and it induces nonlinear effects in power amplifiers. In this study, we propose an algorithm called "Alternative Projections onto Convex and Non-Convex Sets" that reduces the OBP and PAPR simultaneously. The alternate projections are performed onto these sets to form an iteration, and it converges to the specified limits of in-band-power, peak amplitude, and OBP. Furthermore, simulations show that the bit error rate performance is not degraded while reducing OBP and PAPR.

A method for purifying reprocessed uranium from even isotopes under conditions of multiple recycle

  • Smirnov, A.Yu.;Palkin, V.A.;Chistov, A.V.;Sulaberidze, G.A.
    • Nuclear Engineering and Technology
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    • v.54 no.10
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    • pp.3650-3659
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    • 2022
  • We proposed a modification of a double cascade scheme to enrich reprocessed uranium. Such a cascade scheme represents a combination of one cascade with "broadening" of the flow and an ordinary three-flow cascade. A calculation and optimization method has been developed for the proposed scheme according to various efficiency criteria. It is shown that the proposed scheme makes it possible to obtain low-enriched uranium of commercial quality using reprocessed uranium of different initial compositions. For example, the enrichment of reprocessed uranium, which had gone through five consequent recycles, was considered. The proposed scheme allowed to enrich it with simultaneous fulfillment of restrictions on isotopes 232U, 234U, and 236U. Such results indicate the scheme's applicability under conditions of multiple recycling of uranium in reactor fuel. Computational experiments have shown that in the proposed modification, a noticeable saving of natural uranium in the cycle (~18%) can be achieved, provided that the additional consumption of separative work does not exceed 10%, compared with the case of enrichment of natural uranium to obtain LEU of equivalent quality.

Optimization of HPLC Method and Clean-up Process for Simultaneous and Systematic Analysis of Synthetic Color Additives in Foods (식품 중 타르색소의 동시분석 및 계통분석을 위한 HPLC 분석조건 및 정제과정 확립)

  • Park, Sung-Kwan;Hong, Yeun;Jung, Yong-Hyun;Lee, Chang-Hee;Yoon, Hae-Jung;Kim, So-Hee;Lee, Jong-Ok
    • Korean Journal of Food Science and Technology
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    • v.33 no.1
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    • pp.33-39
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    • 2001
  • To develop a method for separation process using Sep-pak $C_18$, simultaneous and systematic analysis of 8 permitted and 11 non-permitted synthetic food colors in Korea, optimization of analysis conditions for reverse phase ion-pair high performance liquid chromatography was carried out. For the best result of Sep-pak $C_18$ separation the pH of color standard mixture solution was $5{\sim}6$ and 0.1% HCl-methanol solution were set as eluent. The colors eluated from Sep-pak $C_18$ cartridge were determined and confirmed by high performance liquid chromatography with a photodiode array detector at 420 nm for yellow colors type, at 520 nm for red colors type, at 600 nm for blue and green colors type and at 254 nm for mixed colors. Conditions for HPLC analysis were as follows: column, Symmetry $C_18$ (5 m, 3.9 mm $i.d.{\times}150\;mm$); mobile phase, 0.025 M ammonium acetate (containing 0.01 M tetrabutylammonium bromide) : acetonitrile : methanol (65 : 25 : 10) and 0.025 M ammonium acetate(containing 0.01 M tetrabutylammonium bromide) : acetonitrile : methanol (40 : 50 : 10); flow rate, 1 mL/min. It takes 35 minutes for simultaneaus analysis and 18 minutes for systematic analysis. The detection limits range of each colors were $0.01{\sim}0.05\;{\mu}g/g$.

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Optimization and Applicability Verification of Simultaneous Chlorogenic acid and Caffeine Analysis in Health Functional Foods using HPLC-UVD (HPLC-UVD를 이용한 건강기능식품에서 클로로겐산과 카페인 동시분석법 최적화 및 적용성 검증)

  • Hee-Sun Jeong;Se-Yun Lee;Kyu-Heon Kim;Mi-Young Lee;Jung-Ho Choi;Jeong-Sun Ahn;Jae-Myoung Oh;Kwang-Il Kwon;Hye-Young Lee
    • Journal of Food Hygiene and Safety
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    • v.39 no.2
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    • pp.61-71
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    • 2024
  • In this study, we analyzed chlorogenic acid indicator components in preparation for the additional listing of green coffee bean extract in the Health Functional Food Code and optimized caffeine for simultaneous analysis. We extracted chlorogenic acid and caffeine using 30% methanol, phosphoric acid solution, and acetonitrile-containing phosphoric acid and analyzed them at 330 and 280 nm, respectively, using liquid chromatography. Our analysis validation results yielded a correlation coefficient (R2) revealing a significance level of at least 0.999 within the linear quantitative range. The chlorogenic acid and caffeine detection and quantification limits were 0.5 and 0.2 ㎍/mL and 1.4, and 0.4 ㎍/mL, respectively. We confirmed that the precision and accuracy results were suitable using the AOAC validation guidelines. Finally, we developed a simultaneous chlorogenic acid and caffeine analysis approach. In addition, we confirmed that our analysis approach could simultaneously quantify chlorogenic acid and caffeine by examining the applicability of each formulation through prototypes and distribution products. In conclusion, the results of this study demonstrated that the standardized analysis would expectably increase chlorogenic acidcontaining health functional food quality control reliability.