• International Journal of Control, Automation, and Systems
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• v.4 no.5
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• pp.575-591
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• 2006

In a previous research, we presented the Grid Method and confirmed it as a systematic and efficient problem formulation method for the task-oriented design of robot kinematics. However, our previous research was limited in two ways. First, it gave only a local optimum due to its use of a local optimization technique. Second, it used constant weights for a cost function chosen by the manual weights tuning algorithm, thereby showing low efficiency in finding an optimal solution. To overcome these two limitations, therefore, this paper presents a global optimization technique and an adaptive weights tuning algorithm to solve a formulated problem using the Grid Method. The efficiencies of the proposed algorithms have been confirmed through the kinematic design examples of various robot manipulators.

• Journal of information and communication convergence engineering
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• v.13 no.2
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• pp.123-131
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• 2015

Training neural networks is a complex task with great importance in the field of supervised learning. In the training process, a set of input-output patterns is repeated to an artificial neural network (ANN). From those patterns weights of all the interconnections between neurons are adjusted until the specified input yields the desired output. In this paper, a new hybrid algorithm is proposed for global optimization of connection weights in an ANN. Dynamic swarms are shown to converge rapidly during the initial stages of a global search, but around the global optimum, the search process becomes very slow. In contrast, the gradient descent method can achieve faster convergence speed around the global optimum, and at the same time, the convergence accuracy can be relatively high. Therefore, the proposed hybrid algorithm combines the dynamic particle swarm optimization (DPSO) algorithm with the backpropagation (BP) algorithm, also referred to as the DPSO-BP algorithm, to train the weights of an ANN. In this paper, we intend to show the superiority (time performance and quality of solution) of the proposed hybrid algorithm (DPSO-BP) over other more standard algorithms in neural network training. The algorithms are compared using two different datasets, and the results are simulated.

• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.6
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• pp.711-717
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• 2014

Global path planning for autonomous driving of unmanned ground vehicle is essential. When setting global path planning, its accuracy and effectiveness is increased if useful information such as terrain type of driving route has been reflected on global path planning. As a method to reflect the terrain type, there is a method to perform global path planning by applying the weight to each terrain type. At this time, how to assign appropriate weights corresponding to the terrain type is more important than anything. In this paper, we proposed a method to determine the weight for terrain type that may affect the results of global path planning. Moreover, we presented effective operation method and design results(GUI) to check the possibility of the use of the proposed method.

• Journal of Korea Water Resources Association
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• v.52 no.1
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• pp.61-70
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• 2019

The modified Kling-Gupta efficiency fusion method to merge actual evapotranspiration was proposed and compared with the simple Taylor skill's score method using Global Land Data Assimilation System (GLDAS), Global Land Evaporation Amsterdam Model (GLEAM), MODIS Global Evapotranspiration Project (MOD16), and the flux tower on three different land cover types over the Korean peninsula and China. In the results of the weights estimated from two actual evapotranspiration merging techniques (i.e., STS and KGF), the weights of reanalysis data (i.e, GLDAS and GLEAM) in cropland and grassland showed similar performance, while the results of weights are different according to the merging techniques in forest. Both two merging techniques showed better results than original dataset in grassland and forest. However, there were no improvement in cropland compared to the other land cover types. The results of the KGF method slightly improved compared to those of the STS in grassland and forest.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.1-11
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• 2016

Entani and Tanaka (2007) presented a new approach for obtaining interval evaluations suitable for handling uncertain data. Above all, their approach is characterized by the normalization of interval data and thus the elimination of redundant bounds. Further, interval global weights in AHP are derived by using such normalized interval data. In this paper, we present a heuristic method for finding extreme points of interval data, which basically extends the method by Entani and Tanaka (2007), and also helps to obtain normalized interval data. In the second part of this paper, we show that the solutions to the linear program for interval global weights can be obtained by a simple inspection. In the meantime, the absolute dominance proposed by the authors is extended to pairwise dominance which makes it possible to identify at least more dominated alternatives under the same information.

• Journal of Preventive Medicine and Public Health
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• v.56 no.4
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• pp.291-302
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• 2023

Objectives: Disability weights require regular updates, as they are influenced by both diseases and societal perceptions. Consequently, it is necessary to develop an up-to-date list of the causes of diseases and establish a survey panel for estimating disability weights. Accordingly, this study was conducted to calculate, assess, modify, and validate disability weights suitable for Korea, accounting for its cultural and social characteristics. Methods: The 380 causes of disease used in the survey were derived from the 2019 Global Burden of Disease Collaborative Network and from 2019 and 2020 Korean studies on disability weights for causes of disease. Disability weights were reanalyzed by integrating the findings of an earlier survey on disability weights in Korea with those of the additional survey conducted in this study. The responses were transformed into paired comparisons and analyzed using probit regression analysis. Coefficients for the causes of disease were converted into predicted probabilities, and disability weights in 2 models (model 1 and 2) were rescaled using a normal distribution and the natural logarithm, respectively. Results: The mean values for the 380 causes of disease in models 1 and 2 were 0.488 and 0.369, respectively. Both models exhibited the same order of disability weights. The disability weights for the 300 causes of disease present in both the current and 2019 studies demonstrated a Pearson correlation coefficient of 0.994 (p=0.001 for both models). This study presents a detailed add-on approach for calculating disability weights. Conclusions: This method can be employed in other countries to obtain timely disability weight estimations.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.1188-1200
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• 2015

A unified numerical method for computing the quadrature weights, integration matrix, and differentiation matrix is newly developed in this study. For this purpose, a spline-like interpolation using piecewise continuous polynomials is converted into a global spline interpolation formula, with which the quadrature formulas can be derived from integration and differentiation of the transformed function in an exact manner. To prove the usefulness of the suggested approach, both the Lagrange and tension spline interpolations are represented in exactly the same form as global spline interpolation. The applicability of the proposed method on arbitrary nodes is illustrated using two different sets of nodes. A series of validations using three test functions is conducted to show the flexibility in selecting computational nodes with the present method.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.1
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• pp.136-143
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• 2009

Typically, local methods for stereo matching are fast but have relatively low degree of accuracy while global ones, though costly, can achieve a higher degree of accuracy in retrieving disparity information. Recently, some local methods like the ones based on segmentation or adaptive weights are suggested which achieve more accuracy than global ones. These newly suggested local methods that can estimate more accurate disparity information cannot be easily used since they require more computational costs which increase in proportion to the window size they use. In this paper, we propose the method by using distance weights and pixel difference weights similar to those of the bilateral filter. Specifically, we present constant time O(1) algorithm for the case the distance weights are equal. The suggested method requires constant time for computation regardless of the used window size. Furthermore, experiments show that the matching performance of our method is as good as the ones of other recent methods.

• The Korean Journal of Food And Nutrition
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• v.30 no.4
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• pp.696-702
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• 2017

Metabolic syndrome, including obesity, glucose intolerance and elevated blood pressure, is related to type 2 diabetes and cardiovascular disease. Previous studies have reported the anti-oxidative, anti-inflammatory and anti-diabetic effects of purple corn extract. We investigated the efficacy of purple corn extract (PC) against high-fat diet (HFD)-induced obesity and glucose intolerance, and examined the underlying mechanisms by analyzing expression of proteins and genes involved in glucose regulation and macrophage infiltration. C57BL/6 mice were fed with normal chow diet (ND), or HFD treated with distilled water (DW, control) or PC, for 10 weeks. Although body weights were similar in the HFD-fed groups, we observed a decrease in the liver and epididymal adipose tissue (EAT) weights, and enhanced glucose tolerance test (GTT) results in the PC group, as compared with DW group. Liver showed increased Akt phosphorylation in the PC-treated mice; however, no changes were observed in the EAT, for all groups. In PC-treated mice, decreased macrophage infiltration was seen in the EAT, with a reduced expression of macrophage marker genes. Finally, proinflammatory cytokine gene expressions were decreased by PC in the EAT, and a modest trend for downregulation was observed in the liver. Hence, we conclude that PC may decrease glucose intolerance by increasing the phosphorylation of Akt and reducing the macrophage infiltration into the EAT.

• The Journal of Korea Robotics Society
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• v.2 no.1
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• pp.29-39
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• 2007

We present an implementation of particle filter algorithm for global localization and kidnap recovery of mobile robot. Firstly, we propose an algorithm for efficient particle initialization using sonar line features. And then, the average likelihood and entropy of normalized weights are used as a quality measure of pose estimation. Finally, we propose an active kidnap recovery by adding new particle set. New and independent particle set can be initialized by monitoring two quality measures. Added particle set can re-estimate the pose of kidnapped robot. Experimental results demonstrate the capability of our global localization and kidnap recovery algorithm.