• Journal of the Korean Statistical Society
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• v.27 no.1
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• pp.113-132
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• 1998

In this paper, we consider a minimum distance (M.D.) estimation based on kernels for U-statistics. We use Cramer-von Mises type distance function which measures the discrepancy between U-empirical distribution function(d.f.) and modeled d.f. of kernel. In the distance function, we allow various integrating measures, which can be finite, $\sigma$-finite or discrete. Then we derive the asymptotic normality and study the qualitative robustness of M. D. estimates.

• Journal of Information Processing Systems
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• v.2 no.1
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• pp.44-47
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• 2006

One of the critical issues in a sensor network concerns the detection of changes in data streams. Recently presented change detection schemes primarily use a sliding window model to detect changes. In such a model, a distance function is used to compare two sliding windows. Therefore, the performance of the change detection scheme is greatly influenced by the distance function. With regard to sensor nodes, however, energy consumption constitutes a critical design concern because the change detection scheme is implemented in a sensor node, which is a small battery-powered device. In this paper, we present a comparative study of various distance functions in terms of execution time, energy consumption, and detecting accuracy through simulation of speech signal data. The simulation result demonstrates that the Euclidean distance function has the highest performance while consuming a low amount of power. We believe our work is the first attempt to undertake a comparative study of distance functions in terms of execution time, energy consumption, and accuracy detection.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.1
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• pp.4-9
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• 2009

Fuzzy entropy is designed for non convex fuzzy membership function using well known Hamming distance measure. Design procedure of convex fuzzy membership function is represented through distance measure, furthermore characteristic analysis for non convex function are also illustrated. Proof of proposed fuzzy entropy is discussed, and entropy computation is illustrated.

• Korean Journal of Applied Biomechanics
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• v.22 no.1
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• pp.9-16
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• 2012

The purpose of this study was to compare and analyze muscle function and EMG of the trunk and the lower extremity in short and long distance athletes and in order to determine difference in peak torque per unit weight, muscle power per unit weight, endurance ratio, and %MVIC classified by muscle. For that purpose, isokinetic muscle function tests for waist, knee, and ankle joints and EMG measurements for the trunk and the lower extremity muscle with running motion were conducted for 7 short and long distance high school athletes respectively. The study over muscle function of waist, knee, and ankle joints indicates that peak torque per unit weight of short distance athletes is higher than that of long distance athletes in extension and flexion of waist joint, plantar flexion of right ankle joint, and dorsi flexion of left ankle joint. In case of the muscle power per unit weight of short distance athletes is also higher than long distance athletes in waist, knee, and ankle joints. No difference in endurance ratio of waist, knee, and ankle joints between the two groups was founded. The results of the test over EMG of the trunk and the lower extremity show that %MVIC of erector spinae, rectus femoris, vastus medialis, vastus lateralis, and tibialis anterior is higher than that of long distance athletes in support phase. The above results proved to be the same in flight phase except for %MVIC of medial gastrocnemius. In other words, %MVIC of medial gastrocnemius for short distance athletes turned out to be higher than that of long distance athletes in flight phase.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1427-1430
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• 2005

In this paper, the range finder system using a PSD sensor suitable for low-cost localization sensor of a mobile robot. Because the distance-voltage output of a PSD sensor has a non-linear property, the linearizing function is proposed through the experimental characteristics of the sensor. And the characteristics are tested and the distance-voltage data are measured in various colors and materials of object. For a known environment, a mobile robot scans the surroundings using a PSD sensor that can rotate $360^{\circ}$. Finally, the performance and accuracy of the developed system are verified according to the comparison the distance by proposed function with real distance

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.7 no.1
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• pp.9-21
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• 1998

This paper a new solution approach to moving obstacle avoidance problem of a mobile robot. A new concept avoidability measure (AVM) is defined to describe the state of a pair of a robot and an obstacle regarding the collision between them. As an AVM, virtual distance function (VDF), is derived as a function of the distance from the obstacle to the robot and outward speed of the obstacle relative to the robot. By keeping the virtual distance above some positive limit value, the robot avoids the obstacle. In terms of the VDF ,an artificial potential field is constructed to repel the robot away from the obstacle and to attract the robot toward a goal location. At every sampling time, the artificial potential field is updated and the force driving the robot is derived from the gradient of the artificial potential field. The suggested algorithm drives the robot to avoid moving obstacles in real time. Since the algorithm considers the mobility of the obstacle as well as the distance, it is effective for moving obstacle avoidance. Some simulation studies show the effectiveness of the proposed approach.

• Journal of the Korean Statistical Society
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• v.27 no.4
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• pp.507-514
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• 1998

The minimum distance estimation based on the L$_2$ distance between a model density and a density estimator is studied from M-estimation point of view. We will show that how a model density and a density estimator are incorporated in order to create an M-estimation function. This method enables us to create an M-estimating function reflecting the natures of both an assumed model density and a given set of data. Some new types of M-estimation functions for estimating a location and scale parameters are introduced.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.11a
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• pp.199-202
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• 2007

The similarity measure is constructed for non-convex fuzzy membership function using well known Hamming distance measure. Comparison with convex fuzzy membership function is carried out, furthermore characteristic analysis for non-convex function are also illustrated. Proposed similarity measure is proved and the usefulness is verified through example. In example, usefulness of proposed similarity is pointed out.

• The KIPS Transactions:PartD
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• v.18D no.5
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• pp.323-328
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• 2011

For content-based image retrieval, the earth mover's distance and the optimal color composition distance are proposed to measure the dissimilarity. Although providing good retrieval results, both methods are too time-consuming to be used in a large image database. To solve the problem, we propose a new distance function that calculates an approximate earth mover's distance in linear time. To calculate the dissimilarity in linear time, the proposed approach employs the space-filling curve. We have performed extensive experiments to show the effectiveness and efficiency of the proposed approach. The results reveal that our approach achieves almost the same results with the EMD in linear time.

• School Mathematics
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• v.19 no.4
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• pp.639-661
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• 2017

The purpose of this study is to investigate the relationship between the distance function average speed and the speed function. Particularly, in this study, we investigate the process of constructing the speed function in the distance function (irrational function, exponential function) which is difficult to weaken the argument in the denominator. In this process, students showed various anxieties and expressions about the procedural knowledge that they constructed first. In particular, if student B can not explain all the knowledge he already knows in this process, he showed his reflection on the process of calculating the differential coefficient. This study adds an understanding of the calculation method of students in differential coefficient learning. In addition, it is meaningful that the students who construct procedural knowledge at the time of calculating the differential coefficient have thought about how to provide opportunities to reflect on the procedure they constructed.