• School Mathematics
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• v.18 no.4
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• pp.881-901
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• 2016

This study is about investigating students' recognition and expression on relationship of 'time, distance, speed' via teaching experiment. In this process, students showed not only a change in perception of the relationship of 'time, distance, speed' but also recognizing the average speed as a viewpoint of the slope of the line connecting the end points of the interval in the distance function as well as another way of perceiving average speed of a height of a rectangle. In this process, the study shows the scene of expanding the relation of 'distance = time ${\times}$ speed' to 'distance = time ${\times}$ average speed', and also the student who makes the continuous reasoning shows the possibility of constructing a new function that can explain the change of the primitive function by allocating the average rate of change to the interval. Although this study was conducted with a limited number of students, this study suggests some implications through the observation of relationship of 'time, distance, speed' the students'. We hope that these results will be the starting point for various studies for constructing the integral learning model in the future.

• 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.

• 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.

• 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.

• The Mathematical Education
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• v.56 no.4
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• pp.387-405
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• 2017

The purpose of this study is to investigate the change of students 'perception and expression about the motion of object following distance function $={x \atop 3}$ and distance function $y=\frac{x^3}{3}+3$ according to the necessity of research on students' perception and expression about integral constant. In this paper, we present the recognition and the expression of the difference of the constant in the relationship between the distance function and the speed function of the students, while examining the process of constructing the speed function and the inverse process of the distance function. This provides implications for the relationship between the derivative and the indefinite integral corresponding to the inverse process. In particular, in a teaching experiment, a constructive activity was performed to analyze the motion of two distance functions, where the student had a difference of the constant term. At this time, the students used the expression 'starting point' for the constants in the distance function, and the motion was interpreted by using the meaning. This can be seen as a unique 'students' mathematics' in the process of analyzing the motion of objects. These scenes, in introducing the notion of the relation between differential and indefinite integral, it is beyond the comprehension of the integral constant as a computational procedure, so that the learner can understand the meaning of the integral constant in relation to the motion of the object. It is expected that it will be a meaningful basic research on the relationship between differential and integral.

• The Journal of Korea Robotics Society
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• v.14 no.4
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• pp.357-362
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• 2019

This paper proposes a model and train method that can real-time detect objects and distances estimation based on a monocular camera by applying deep learning. It used YOLOv2 model which is applied to autonomous or robot due to the fast image processing speed. We have changed and learned the loss function so that the YOLOv2 model can detect objects and distances at the same time. The YOLOv2 loss function added a term for learning bounding box values x, y, w, h, and distance values z as 클래스ification losses. In addition, the learning was carried out by multiplying the distance term with parameters for the balance of learning. we trained the model location, recognition by camera and distance data measured by lidar so that we enable the model to estimate distance and objects from a monocular camera, even when the vehicle is going up or down hill. To evaluate the performance of object detection and distance estimation, MAP (Mean Average Precision) and Adjust R square were used and performance was compared with previous research papers. In addition, we compared the original YOLOv2 model FPS (Frame Per Second) for speed measurement with FPS of our model.

• Journal of Industrial Technology
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• v.20 no.B
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• pp.219-226
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• 2000

In this paper, we propose a new novel method for similarity search that supports time warping. Our primary goal is to innovate on search performance in large databases without false dismissal. To attain this goal, we devise a new distance function $D_{tw-lb}$ that consistently underestimates the time warping distance and also satisfies the triangular inequality. $D_{tw-lb}$ uses a 4-tuple feature vector extracted from each sequence and is invariant to time warping. For efficient processing, we employ a multidimensional index that uses the 4-tuple feature vector as indexing attributes and $D_{tw-lb}$ as a distance function. We prove that our method does not incur false dismissal. To verify the superiority of our method, we perform extensive experiments. The results reveal that our method achieves significant speedup up to 43 times with real-world S&P 500 stock data.

• Journal of Korean Society of Transportation
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• v.29 no.3
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• pp.83-91
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• 2011

This paper discusses models for estimating dynamic travel times based on probability theory. The dynamic travel time models proposed in the paper are formulated assuming that the travel time of a vehicle depends on the distribution of the traffic stream condition with respect to the location along a road when the subject vehicle enters the starting point of a travel distance or with respect to the time at the starting point of a travel distance. The models also assume that the dynamic traffic flow can be represented as an exponential distribution function among other types of probability density functions.

• The Mathematical Education
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• v.62 no.4
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• pp.473-490
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• 2023

Previous studies from domestic and abroad are accumulating information on how to reason students' continuous changes through teaching experiments. These studies deal with scenes in which students who make 'smooth reasoning' and 'chunky reasoning' construct mathematical results together in teaching experiments. However, in order to analyze their results in more detail, it is necessary to check what kind of results a student reasoning in a specific way constructs for the tasks of previous studies. According to the need for these studies, the researcher conducted a total of 14 teaching experiments on one first-year high school student who was found to make 'chunky reasoning'. In this study, it was possible to observe a scene in which a student who makes 'chunky reasoning' constructs an output similar to 'a mathematical result constructed by students with various reasoning methods(smooth reasnoning or chunky reasoning) in previous studies.' In particular, the student who participated in this study observed a consistent construction method of constructing the function of 'time-speed' from the function of 'time-distance'. The researcher expected that information on this student's distinctive construction methods would be helpful for subsequent studies.

• Proceedings of the Acoustical Society of Korea Conference
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• 1994.06c
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• pp.133-137
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• 1994

In this paper, a method for designing an optimal weight function for the weighted cepstral distance measure is proposed. A conventional weight function or cepstral lifter is obtained eperimentally depending on the spectral components to be emphasized. The proposed method minimizes the error between word reference patterns and the traning data. To compare the proposed optimal weight function with conventional function, speech recognition systems based on Dpynamic Time Warping and Hidden Markov Models were constructed to conduct speaker independent isolated word necogination eperiment. Results show that the proposed method gives better performance than conventional weight functions.