• Title/Summary/Keyword: Data Paper

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Analysis of paper map images for acquiring 3D terrain data (3차원 지형 자료 획득을 위한 지도 영상 분석)

  • LEE, JIN SEON
    • Journal of the Korea Computer Graphics Society
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    • v.2 no.1
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    • pp.68-76
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    • 1996
  • One of the major problems in GIS(Geographical Information Systems) involves acquiring 3-D terrain data. Because conventional methods such as land surveying or analysis of aerial photographs are costly, the method of using existing paper maps has been gaining considerable attention. This method demands three processing steps: 1) extraction of contours, 2) assignment of height values to the extracted contours, 3) reconstruction of 3-D terrain data. In this paper we systematically develop a procedure for acquiring 3-D terrain data from contour solutions. For the first two steps, we describe the necessary operations and roughly sketch solutions. For the last step, we propose an efficient raster-based algorithm and present the results of experiments with existing paper map images.

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Global Map Building and Navigation of Mobile Robot Based on Ultrasonic Sensor Data Fusion

  • Kang, Shin-Chul;Jin, Tae-Seok
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.7 no.3
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    • pp.198-204
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    • 2007
  • In mobile robotics, ultrasonic sensors became standard devices for collision avoiding. Moreover, their applicability for map building and navigation has exploited in recent years. In this paper, as the preliminary step for developing a multi-purpose autonomous carrier mobile robot to transport trolleys or heavy goods and serve as robotic nursing assistant in hospital wards. The aim of this paper is to present the use of multi-sensor data fusion such as ultrasonic sensor, IR sensor for mobile robot to navigate, and presents an experimental mobile robot designed to operate autonomously within both indoor and outdoor environments. The global map building based on multi-sensor data fusion is applied for recognition an obstacle free path from a starting position to a known goal region, and simultaneously build a map of straight line segment geometric primitives based on the application of the Hough transform from the actual and noisy sonar data. We will give an explanation for the robot system architecture designed and implemented in this study and a short review of existing techniques, Hough transform, since there exist several recent thorough books and review paper on this paper. Experimental results with a real Pioneer DX2 mobile robot will demonstrate the effectiveness of the discussed methods.

A Study on the Implementation of Crawling Robot using Q-Learning

  • Hyunki KIM;Kyung-A KIM;Myung-Ae CHUNG;Min-Soo KANG
    • Korean Journal of Artificial Intelligence
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    • v.11 no.4
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    • pp.15-20
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    • 2023
  • Machine learning is comprised of supervised learning, unsupervised learning and reinforcement learning as the type of data and processing mechanism. In this paper, as input and output are unclear and it is difficult to apply the concrete modeling mathematically, reinforcement learning method are applied for crawling robot in this paper. Especially, Q-Learning is the most effective learning technique in model free reinforcement learning. This paper presents a method to implement a crawling robot that is operated by finding the most optimal crawling method through trial and error in a dynamic environment using a Q-learning algorithm. The goal is to perform reinforcement learning to find the optimal two motor angle for the best performance, and finally to maintain the most mature and stable motion about EV3 Crawling robot. In this paper, for the production of the crawling robot, it was produced using Lego Mindstorms with two motors, an ultrasonic sensor, a brick and switches, and EV3 Classroom SW are used for this implementation. By repeating 3 times learning, total 60 data are acquired, and two motor angles vs. crawling distance graph are plotted for the more understanding. Applying the Q-learning reinforcement learning algorithm, it was confirmed that the crawling robot found the optimal motor angle and operated with trained learning, and learn to know the direction for the future research.

A Study on Priorities of the Components of Big Data Information Security Service by AHP (AHP 기법을 활용한 Big Data 보안관리 요소들의 우선순위 분석에 관한 연구)

  • Biswas, Subrata;Yoo, Jin Ho;Jung, Chul Yong
    • The Journal of Society for e-Business Studies
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    • v.18 no.4
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    • pp.301-314
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    • 2013
  • The existing computer environment, numerous mobile environments and the internet environment make human life easier through the development of IT technology. With the emergence of the mobile and internet environment, data is getting bigger rapidly. From this environment, we can take advantage of using those data as economic assets for organizations which make dreams come true for the emerging Big Data environment and Big Data security services. Nowadays, Big Data services are increasing. However, these Big Data services about Big Data security is insufficient at present. In terms of Big Data security the number of security by Big Data studies are increasing which creates value for Security by Big Data not Security for Big Data. Accordingly in this paper our research will show how security for Big Data can vitalize Big Data service for organizations. In details, this paper derives the priorities of the components of Big Data Information Security Service by AHP.

On the Aggregation of Multi-dimensional Data using Data Cube and MDX

  • Ahn, Jeong-Yong;Kim, Seok-Ki
    • Journal of the Korean Data and Information Science Society
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    • v.14 no.1
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    • pp.37-44
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    • 2003
  • One of the characteristics of both on-line analytical processing(OLAP) applications and decision support systems is to provide aggregated source data. The purpose of this study is to discuss on the aggregation of multi-dimensional data. In this paper, we (1) examine the SQL aggregate functions and the GROUP BY operator, (2) introduce the Data Cube and MDX, (3) present an example for the practical usage of the Data Cube and MDX using sample data.

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Deep Meta Learning Based Classification Problem Learning Method for Skeletal Maturity Indication (골 성숙도 판별을 위한 심층 메타 학습 기반의 분류 문제 학습 방법)

  • Min, Jeong Won;Kang, Dong Joong
    • Journal of Korea Multimedia Society
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    • v.21 no.2
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    • pp.98-107
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    • 2018
  • In this paper, we propose a method to classify the skeletal maturity with a small amount of hand wrist X-ray image using deep learning-based meta-learning. General deep-learning techniques require large amounts of data, but in many cases, these data sets are not available for practical application. Lack of learning data is usually solved through transfer learning using pre-trained models with large data sets. However, transfer learning performance may be degraded due to over fitting for unknown new task with small data, which results in poor generalization capability. In addition, medical images require high cost resources such as a professional manpower and mcuh time to obtain labeled data. Therefore, in this paper, we use meta-learning that can classify using only a small amount of new data by pre-trained models trained with various learning tasks. First, we train the meta-model by using a separate data set composed of various learning tasks. The network learns to classify the bone maturity using the bone maturity data composed of the radiographs of the wrist. Then, we compare the results of the classification using the conventional learning algorithm with the results of the meta learning by the same number of learning data sets.

Does Big Data Matter to Value Creation? : Based on Oracle Solution Case (Does Big Data Matter to Value Creation? : 오라클(Oracle) 솔루션을 중심으로)

  • Kim, Yonghee;You, Eungjoon;Kang, Miseon;Choi, Jeongil
    • Journal of Information Technology Services
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    • v.11 no.3
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    • pp.39-48
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    • 2012
  • It is essential that firm makes a rational and scientific decision making and creates a news value for the future direction. To do so, many firms attempt to collect meaningful data and find the filtered and refined implication for the better customer relationship and the active market drive through the various analytic tools. Among the possible IT solutions, utilization of 'Big Data' is becoming more attractive and necessary in such a way that it would help firms obtain the systemized and demanding information and facilitate their decision making process to keep up with the market needs. In this paper, it introduces the concepts and development of 'Big Data' recognized as a IT resource and solution under the rapidly changing firm environment. This study also presents the several firm cases using Big Data' and the Oracle's total data management and analytic solutions in order to support the application of 'Big Data'. Finally this paper provides a holistic viewpoint and realistic approach on use of 'Big Data' to create a new value.

Reliability Assessment of Machine Tools Using Failure Mode Analysis Programs (고장모드 분석 프로그램을 통한 공작기계의 신뢰성 평가)

  • Kim Bong-Suk;Lee Soo-Hun;Song Jun-Yeob;Lee Seung-Woo
    • Transactions of the Korean Society of Machine Tool Engineers
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    • v.14 no.1
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    • pp.15-23
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    • 2005
  • For reliability assessment for machine tools, failure mode analyses by two viewpoints were studied in this paper. First, this study developed the reliability data analysis program, which searches f3r optimal failure distribution like failure rate or MTBF(Mean Time Between Failure) using failure data and reliability test data of mechanical parts in the web. Moreover, this data analysis program saves both failure data or reliability data and their failure rate or MTBF for database establishment. Second, this paper conducted failure mode analysis through such performance tests as circular movement test and vibration testing for machine tools when reliability data is not available. A developed web-based analysis program shows correlations between failure mode and performance test result and also accumulates all the data. These kinds of data analysis programs and stored data furnish valuable information for improving the reliability of mechanical system.

Plate Forming Automation System of Steel Plates by Line Heating Method (III) (선상가열법에 의한 강판의 곡가공 자동화 시스템 (III))

  • Lee, Joo-Sung
    • Journal of the Society of Naval Architects of Korea
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    • v.34 no.2
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    • pp.85-89
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    • 1997
  • The development of the algorithm and the computer aided marking data generation system based on it should precede the automation system for plate forming by line heating method. This paper places emphasis on the yard simulation for a real surface model to justify the algorithm and the computer aided marking data generation system which have been already developed. The yard simulation has been carried out according to the generated marking data and the heating condition produced by the developed computer aided system. The practical applicability of the developed computer aided system has been conformed by comparing the results of the computer simulation to the results of the yard simulation. This paper ends with the extension of the developed marking data generation system.

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Dialogic Male Voice Triphone DB Construction (남성 음성 triphone DB 구축에 관한 연구)

  • Kim, Yu-Jin;Baek, Sang-Hoon;Han, Min-Soo;Chung, Jae-Ho
    • The Journal of the Acoustical Society of Korea
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    • v.15 no.2
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    • pp.61-71
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    • 1996
  • In this paper, dialogic triphone data base construction for triphone synthesis system is discussed. Particularly, in this work, dialogic speech data is collected from the broadcast media, and three different transcription steps are taken. Total 10 hours of speech data are collected. Among them, six hours of speech data are used for the triphone data base construction, and the rest four hours of data are reserved. Dialogic speech data base construction is far different from the reciting speech data base construction. This paper describes various steps that necessary for the dialogic triphone data base construction from collecting speech data to triphone unit labeling.

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