• Title/Summary/Keyword: solution accuracy

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An Observation-based Movement Control for Educational Coding Robots (코딩 학습용 로봇 제어를 위한 관찰 기반 움직임 제어)

  • Park, Kyeongbok;Cho, Sung Hyun;Seo, Beomjoo
    • Journal of Korea Game Society
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    • v.16 no.6
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    • pp.131-142
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    • 2016
  • Recently, a variety of methodologies based on the use of educational coding robots have been proposed and experimented in newly emerging korean educational coding markets. Due to imprecise movement accuracy of the existing coding robots, however, such robots are mainly used as a toy. Inspired by these observations, we developed a simple adjustment method during robot movements, which is based on the observation results of 6 line-tracking sensors: 3 sensors in the center of a robot and other 3 sensors at the front. These sensors help to determine whether the robot is in the right location and whether it rotates as expected. Through the well-designed experiments, we report the effectiveness of our proposed solution: the average distance error of 1.57cm and the average degree error of 2.38 degree before and after complex movements. In near future, we hope our method to be popularly used in various educational coding robot platforms.

On B-spline Approximation for Representing Scattered Multivariate Data (비정렬 다변수 데이터의 B-스플라인 근사화 기법)

  • Park, Sang-Kun
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.35 no.8
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    • pp.921-931
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    • 2011
  • This paper presents a data-fitting technique in which a B-spline hypervolume is used to approximate a given data set of scattered data samples. We describe the implementation of the data structure of a B-spline hypervolume, and we measure its memory size to show that the representation is compact. The proposed technique includes two algorithms. One is for the determination of the knot vectors of a B-spline hypervolume. The other is for the control points, which are determined by solving a linear least-squares minimization problem where the solution is independent of the data-set complexity. The proposed approach is demonstrated with various data-set configurations to reveal its performance in terms of approximation accuracy, memory use, and running time. In addition, we compare our approach with existing methods and present unconstrained optimization examples to show the potential for various applications.

Comparative Study on DAE Solution Methods for Effective Multi-Body Dynamics Analysis of Unmanned Military Robot Based on Subsystem Synthesis Method (무인 국방 로봇의 효과적인 다물체 동역학 해석을 위한 부분시스템 합성방법 기반 DAE 해석 기법 비교 연구)

  • Kim, Myoung Ho;Kim, Sung-Soo;Yun, Hong-Seon
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.37 no.9
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    • pp.1069-1075
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    • 2013
  • An effective method is necessary for the real-time analysis of an unmanned military robot. To achieve highly efficient simulations, a subsystem synthesis method has been developed. The subsystem synthesis method separately generates equations of motion for the base body and for the subsystem. The equations of motion are expressed by DAE, which consist of differential equations and algebraic equations. To increase the accuracy and efficiency of solutions, DAE solvers such as the Direct, CS (Constraint Stabilization), and GCP (Generalized Coordinate Partitioning) method are employed. In this study, the subsystem synthesis method is applied for effective multi-body dynamics analysis of an unmanned military robot, and a comparative study of three different DAE solvers is carried out.

DOProC-based reliability analysis of structures

  • Janas, Petr;Krejsa, Martin;Sejnoha, Jiri;Krejsa, Vlastimil
    • Structural Engineering and Mechanics
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    • v.64 no.4
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    • pp.413-426
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    • 2017
  • Probabilistic methods are used in engineering where a computational model contains random variables. The proposed method under development: Direct Optimized Probabilistic Calculation (DOProC) is highly efficient in terms of computation time and solution accuracy and is mostly faster than in case of other standard probabilistic methods. The novelty of the DOProC lies in an optimized numerical integration that easily handles both correlated and statistically independent random variables and does not require any simulation or approximation technique. DOProC is demonstrated by a collection of deliberately selected simple examples (i) to illustrate the efficiency of individual optimization levels and (ii) to verify it against other highly regarded probabilistic methods (e.g., Monte Carlo). Efficiency and other benefits of the proposed method are grounded on a comparative case study carried out using both the DOProC and MC techniques. The algorithm has been implemented in mentioned software applications, and has been used effectively several times in solving probabilistic tasks and in probabilistic reliability assessment of structures. The article summarizes the principles of this method and demonstrates its basic possibilities on simple examples. The paper presents unpublished details of probabilistic computations based on this method, including a reliability assessment, which provides the user with the probability of failure affected by statistically dependent input random variables. The study also mentions the potential of the optimization procedures under development, including an analysis of their effectiveness on the example of the reliability assessment of a slender column.

A novel hyperbolic plate theory including stretching effect for free vibration analysis of advanced composite plates in thermal environments

  • Elmascri, Setti;Bessaim, Aicha;Taleb, Ouahiba;Houari, Mohammed Sid Ahmed;Mohamed, Sekkal;Bernard, Fabrice;Tounsi, Abdelouahed
    • Structural Engineering and Mechanics
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    • v.75 no.2
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    • pp.193-209
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    • 2020
  • This paper presents a new hyperbolic shear deformation plate theory including the stretching effect for free vibration of the simply supported functionally graded plates in thermal environments. The theory accounts for parabolic distribution of the transverse shear strains and satisfies the zero traction boundary conditions on the surfaces of the plate without using shear correction factors. This theory has only five unknowns, which is even less than the other shear and normal deformation theories. The present one has a new displacement field which introduces undetermined integral variables. Material properties are assumed to be temperature-dependent, and graded in the thickness direction according to a simple power law distribution in terms of the volume power laws of the constituents. The equation of motion of the vibrated plate obtained via the classical Hamilton's principle and solved using Navier's steps. The accuracy of the proposed solution is checked by comparing the present results with those available in existing literature. The effects of the temperature field, volume fraction index of functionally graded material, side-to-thickness ratio on free vibration responses of the functionally graded plates are investigated. It can be concluded that the present theory is not only accurate but also simple in predicting the natural frequencies of functionally graded plates with stretching effect in thermal environments.

Past Block Matching Motion Estimation based on Multiple Local Search Using Spatial Temporal Correlation (시공간적 상관성을 이용한 국소 다중 탐색기반 고속 블록정합 움직임 추정)

  • 조영창;남혜영;이태홍
    • Journal of Korea Multimedia Society
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    • v.3 no.4
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    • pp.356-364
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    • 2000
  • Block based fast motion estimation algorithm use the fixed search pattern to reduce the search point, and are based on the assumption that the error in the mean absolute error space monotonically decreases to the global minimum. Therefore, in case of many local minima in a search region we are likely to find local minima instead of the global minimum and highly rely on the initial search points. This situation is evident in the motion boundary. In this paper we define the candidate regions within the search region using the motion information of the neighbor blocks and we propose the multiple local search method (MLSM) which search for the solution throughout the candidate regions to reduce the possibilities of isolation to the local minima. In the MLSM we mark the candidate region in the search point map and we avoid to search the candidate regions already visited to reduce the calculation. In the simulation results the proposed method shows more excellent results than that of other gradient based method especially in the search of motion boundary. Especially, in PSNR the proposed method obtains similar estimate accuracy with the significant reduction of search points to that of full search.

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Precise Orbit Estimation of GPS using GIPSY-OASIS (GIPSY-OASIS기반 GPS 정밀 궤도 추정)

  • Ha, Jihyun;Chun, Sebum;Park, Kwan-Dong
    • Journal of Advanced Navigation Technology
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    • v.23 no.6
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    • pp.535-541
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    • 2019
  • In this paper, scripts for estimating the reference orbits of navigation satellites were developed and their performance was analyzed as a preliminary study for the development of the Korean GPS precise orbit determination technology. The JPL Flinn AC's data processing strategy was applied and Linux-based scripts were developed using GIPSY-OASIS. For the analysis of the accuracy of the estimated reference orbit, the precise orbit provided by the international GNSS data center was used as the truth. As a result, estimated satellite coordinates showed almost exactly same patterns and trends with the reference precise orbits, and their differences are in the range of ±2 cm. The average error between the two orbits was less than 1 cm in the 3D direction, while the standard deviation was also at 1 cm. From these, we found that the developed scripts have excellent performance in precise orbit determination.

Graph Construction Based on Fast Low-Rank Representation in Graph-Based Semi-Supervised Learning (그래프 기반 준지도 학습에서 빠른 낮은 계수 표현 기반 그래프 구축)

  • Oh, Byonghwa;Yang, Jihoon
    • Journal of KIISE
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    • v.45 no.1
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    • pp.15-21
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    • 2018
  • Low-Rank Representation (LRR) based methods are widely used in many practical applications, such as face clustering and object detection, because they can guarantee high prediction accuracy when used to constructing graphs in graph - based semi-supervised learning. However, in order to solve the LRR problem, it is necessary to perform singular value decomposition on the square matrix of the number of data points for each iteration of the algorithm; hence the calculation is inefficient. To solve this problem, we propose an improved and faster LRR method based on the recently published Fast LRR (FaLRR) and suggests ways to introduce and optimize additional constraints on the underlying optimization goals in order to address the fact that the FaLRR is fast but actually poor in classification problems. Our experiments confirm that the proposed method finds a better solution than LRR does. We also propose Fast MLRR (FaMLRR), which shows better results when the goal of minimizing is added.

Effects of Latin hypercube sampling on surrogate modeling and optimization

  • Afzal, Arshad;Kim, Kwang-Yong;Seo, Jae-won
    • International Journal of Fluid Machinery and Systems
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    • v.10 no.3
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    • pp.240-253
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    • 2017
  • Latin hypercube sampling is widely used design-of-experiment technique to select design points for simulation which are then used to construct a surrogate model. The exploration/exploitation properties of surrogate models depend on the size and distribution of design points in the chosen design space. The present study aimed at evaluating the performance characteristics of various surrogate models depending on the Latin hypercube sampling (LHS) procedure (sample size and spatial distribution) for a diverse set of optimization problems. The analysis was carried out for two types of problems: (1) thermal-fluid design problems (optimizations of convergent-divergent micromixer coupled with pulsatile flow and boot-shaped ribs), and (2) analytical test functions (six-hump camel back, Branin-Hoo, Hartman 3, and Hartman 6 functions). The three surrogate models, namely, response surface approximation, Kriging, and radial basis neural networks were tested. The important findings are illustrated using Box-plots. The surrogate models were analyzed in terms of global exploration (accuracy over the domain space) and local exploitation (ease of finding the global optimum point). Radial basis neural networks showed the best overall performance in global exploration characteristics as well as tendency to find the approximate optimal solution for the majority of tested problems. To build a surrogate model, it is recommended to use an initial sample size equal to 15 times the number of design variables. The study will provide useful guidelines on the effect of initial sample size and distribution on surrogate construction and subsequent optimization using LHS sampling plan.

Low-pass Filters for Removing Numerical Noises of Boussinesq Equation Model (Boussinesq 방정식 모델의 수치잡음 제거를 위한 저파수 통과 필터에 대한 고찰)

  • Chun, In-Sik;Sim, Jae-Seol
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.19 no.5
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    • pp.418-428
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    • 2007
  • In the calculation of wave propagation by Boussinesq equation model, it is very common to experience numerical noises generated from nonlinear interaction and breaking wave occurrence, and the numerical solution is rapidly diverged unless the noises are properly controlled. A comparative study was here undertaken for the characteristics of three different lowpass filters (FFT filter, Gaussian filter and Shapiro filter) which are all designed to be applied to the interim results of numerical calculation. The numerical results obtained with application of respective filter techniques were compared with the results of an existing hydraulic experiment for the aspects of noise suppression, conservation of main signal and altering time. The results show that the Shapiro filter can be best applied with optimal choices of its element number, pass number and filtering tune interval. The combination of the number of filter element off, pass number of 50 or less, and application interval of 100 to 200 time steps generally showed good performance in both accuracy and efficiency of the numerical calculation.