• Journal of Auto-vehicle Safety Association
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• v.12 no.4
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• pp.23-30
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• 2020

Recently, self-driving research has been actively studied in various institutions. Accurate recognition is important because information about surrounding objects is needed for safe autonomous driving. This study mainly deals with the signal processing of LiDAR among sensors for object recognition. LiDAR is a sensor that is widely used for high recognition accuracy. First, we clustered and tracked objects by predicting relative position and speed of objects. The characteristic points of all objects were extracted using point cloud data of each objects through proposed algorithm. The Classification between vehicle and pedestrians is estimated using number of characteristic points and distances among characteristic points. The algorithm for classifying cars and pedestrians was implemented and verified using test vehicle equipped with LiDAR sensors. The accuracy of proposed object classification algorithm was about 97%. The classification accuracy was improved by about 13.5% compared with deep learning based algorithm.

• Korean Journal of Health Education and Promotion
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• v.26 no.2
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• pp.15-23
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• 2009

Objectives: This study was conducted to investigate the relationship between physical activity function and stages of self-change for exercise in the aged of a farming village. The object of this research was to make with the basic data for the exercise program for the aged of rural area. Methods: This study was a volunteer sample of 612 persons, 60 years and above, who were living at the 2 farming villages, in 2005 July. This instruments were analyzed using frequency analysis and descriptive statistics, multiple regression analysis. Results: The distribution of stages of self-change of the research object person showed that the pre-contemplation stage was most with 57.2%, and the contemplation stage : 8.1%, the preparation stage : 2.2%, the action stage : 22.5%, the maintenance stage : 10.0%. The person who having good physical function state and advanced stages of self-change of exercise were higher in the ratio of the educational level and the income level. Factors for physical function were effected by the aging and the woman negatively. Conclusion: Physical function scores were highly correlated with stages of self-change for exercise. So it will be helpful that the program which designed by one's physical function and stage of self-change for exercise would applied the one.

• Proceedings of the KIEE Conference
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• 1994.11a
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• pp.349-352
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• 1994

An object recognition and restoration using ultrasound sensors and neural networks are presented. The planar arrangement of the sensor is used to reduce the interference effects between sensors. The SOFM(Self-Organizing Feature Map) Neural Network and SCL(Simple Competitive Learning) method are learned with the acquired data. Lab experiments were performed that the object can be recognized ed the resolutions of the object can be enhanced by using the small number of the ultrasound array and neural networks.

• Journal of the Korea Fashion and Costume Design Association
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• v.18 no.2
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• pp.51-64
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• 2016

The object of this study was to find out the influence of juvenile self-consciousness on the importance of unit 'clothing and self-express' in technology home economics curriculum and appearance management behavior. Questionnaires were administered to 244 middle school students living in Deagu metropolitan City. Frequency, factor analysis, reliability analysis, regression analysis, and ${\chi}^2-test$ were used for data analysis. Our findings are as follows. Self-consciousness had factors as privately and socially self-consciousness and social anxiety. The factors of the importance of unit 'Clothing and self-express' were clothing, self-express and excellence in traditional clothing. Appearance management behavior had factors as appearance management, plastic surgery interest, diet importance, health focus and eating habit. Self-consciousness was found to have significant effects on the factors of the importance of unit 'Clothing and self-express', and self-consciousness on factors of appearance management behavior. The differences by gender of middle students was examined in clothing and textile interest, clothing and textile unit interest and knowledge acquisition route.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.70-74
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• 1998

This paper describes a method for recognition of two-dimensional position of an object by use of aerial ultra-sonic sensor and signal processing technique, which would become a help for blind person or self-mobile robot. First, we have developed a method for measuring the time difference between the transmitted and the received burst wave by use of one ultrasonic transmitter and three receivers. Secondly, a new method is developed for measuring the distance to an object by use of M-sequence correlation method. Thirdly, a measurement method to obtain the position of an object is described by use of phase-arrayed ultrasonic sensor, which gives us a wide-range position determination in a short time.

• Proceedings of the Korean Institute of Interior Design Conference
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• 2008.05a
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• pp.46-49
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• 2008

This research does Complexity form, Interior epidermis cell re-organization, Object discovery that have correct numerical value concept by purpose. Research applied by Grid re-organization in form generation, Parameter variation of cell unit (morphor, tweener), Symbol, pattern of variation, self-organization cell substitution order. Representation through 3d digital modeler of polygon, Nurbs and street-sheet program(x,y,z coordinates & Network way of points) etc. of main work. Investigator specified numbers of U profiles*30, V point-20 that is 600 Paramaters individual in volume, and define circle radius of lighting in object, Projection size variously and tried difference. Transposition cell to point and Heightened brightness of color using pointillism of painting. Led lighting cell object is expressed being decoded by digital code.

• Journal of Korean Institute of Industrial Engineers
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• v.19 no.3
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• pp.123-137
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• 1993

In this paper, an integrated approach is proposed to generate gouging-free Cartesian tool paths for machining sculptured surfaces from 3D measurement data. The integrated CAD/CAM system consists of two modules : offset surface module an Carteian tool path module. The offset surface module generates an offset surface of an object from its 3D measurement data, using an offsetting method and a surface fitting method. The offsetting is based on the idea that the envelope of an inversed tool generates an offset surface without self-intersection as the center of the inversed tool moves along on the surface of an object. The surface-fitting is the process of constructing a compact representation to model the surface of an object based on a fairly large number of data points. The resulting offset surtace is a composite Bezier surface without self-intersection. When an appropriate tool-approach direction is selected, the tool path module generates the Cartesian tool paths while the deviation of the tool paths from the surface stays within the user-specified tolerance. The tool path module is a two-step process. The first step adaptively subdivides the offset surface into subpatches until the thickness of each subpatch is small enough to satisfy the user-defined tolerance. The second step generates the Cartesian tool paths by calculating the intersection of the slicing planes and the adaptively subdivided subpatches. This tool path generation approach generates the gouging-free Cartesian CL tool paths, and optimizes the cutter movements by minimizing the number of interpolated points.

• International Journal of Advanced Culture Technology
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• v.10 no.4
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• pp.536-546
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• 2022

A society will lose a lot of something in this field when the forest fire broke out. If a forest fire can be detected in advance, damage caused by the spread of forest fires can be prevented early. So, we studied how to detect forest fires using CCTV currently installed. In this paper, we present a deep learning-based model through efficient image data construction for monitoring forest fire smoke, which is unstructured data, based on the deep learning model YOLOv5. Through this study, we conducted a study to accurately detect forest fire smoke, one of the amorphous objects of various forms, in YOLOv5. In this paper, we introduce a method of self-learning by producing insufficient data on its own to increase accuracy for unstructured object recognition. The method presented in this paper constructs a dataset with a fixed labelling position for images containing objects that can be extracted from the original image, through the original image and a model that learned from it. In addition, by training the deep learning model, the performance(mAP) was improved, and the errors occurred by detecting objects other than the learning object were reduced, compared to the model in which only the original image was learned.

• Journal of Power Electronics
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• v.2 no.4
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• pp.258-267
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• 2002

This paper presents the principal features of the software modules developed to provide an interactive teaching/learning environment in Power Electronics that can be used by educators and students. The software modules utilize an object oriented programming LabVIEW that provides a highly flexible graphical user interface. The paper highlights the principal features the software components and illustrates a number of highly interactive graphical user interfaces of selected Power Electronics circuits and systems.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2330-2332
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• 2000

In this study, 3-D underwater object recognition using ultrasonic sensor fabricated with PZT-Polymer 1-3 type composites and invariant moment vector and SOFM(Self Organizing Feature Map) neural networks are presented. The recognition rates for the training data and the testing data were 99% and 93%, respectively.