• Title/Summary/Keyword: Position Classification System

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The In/Out Structure : Interpretation of the Korean Architectural Space by Structuralism (안팍구조(構造)-한국건축공간(韓國建築空間)의 구조주의적(構造主義的) 해석(解析))

  • Lee, Hee-Bong
    • Journal of architectural history
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    • v.1 no.2 s.2
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    • pp.172-182
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    • 1992
  • The binary classification, Yin & Yang, can be shown in our culture. Yin & Yang thinking reveals the Up/Down (Principal/Subordinate) relation in space, and Before/After relation in time, and it shows the sequence of Contrast${\to}$Reconciliation & Unification${\to}$Contrast. For example, a follower is Yin against King, while Yang as a father against his son in our trational cognitive structure. With Left/Right, Front/Rear, and Upper/Lower, In/Out division is a basic body-space term to grasp the space position. In the traditional Korean house, when we go out from the deepest 'In', Anbang to Daechung, we may call Anbang 'In' and Daechung 'Out'. When from Daechung to Anmadang reversely, we call Daechung 'In' and Anmadang 'Out'. Namely, Daechung is both 'In' and 'Out'. This is a fallacy logic in view of western basic conception. 'The In/Out Structure, system of a series of inner spaces, is defined as a transformation of cognitive structure of Yin & Yang thinking to the Korean architectural space. The space structure is one of the important deep structure in Korean society.' The concept of the space structure, apperred in east Asia, can make humane space, for it is not a physical 'type' of typepology but related to cognitive structure of human thinking, The structure is applicable to space design in modern society, for the cognitive structure exists in living culture by transformation.

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Performance Evaluation of ECG Compression Algorithms using Classification of Signals based PQSRT Wave Features (PQRST파 특징 기반 신호의 분류를 이용한 심전도 압축 알고리즘 성능 평가)

  • Koo, Jung-Joo;Choi, Goang-Seog
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.37 no.4C
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    • pp.313-320
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    • 2012
  • An ECG(Electrocardiogram) compression can increase the processing speed of system as well as reduce amount of signal transmission and data storage of long-term records. Whereas conventional performance evaluations of loss or lossless compression algorithms measure PRD(Percent RMS Difference) and CR(Compression Ratio) in the viewpoint of engineers, this paper focused on the performance evaluations of compression algorithms in the viewpoint of diagnostician who diagnosis ECG. Generally, for not effecting the diagnosis in the ECG compression, the position, length, amplitude and waveform of the restored signal of PQRST wave should not be damaged. AZTEC, a typical ECG compression algorithm, is validated its effectiveness in conventional performance evaluation. In this paper, we propose novel performance evaluation of AZTEC in the viewpoint of diagnostician.

Agent-based Automatic Camera Placement for Video Surveillance Systems (영상 감시 시스템을 위한 에이전트 기반의 자동화된 카메라 배치)

  • Burn, U-In;Nam, Yun-Young;Cho, We-Duke
    • Journal of Internet Computing and Services
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    • v.11 no.1
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    • pp.103-116
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    • 2010
  • In this paper, we propose an optimal camera placement using agent-based simulation. To derive importance of space and to cover the space efficiently, we accomplished an agent-based simulation based on classification of space and pattern analysis of moving people. We developed an agent-based camera placement method considering camera performance as well as space priority extracted from path finding algorithms. We demonstrate that the method not only determinates the optimal number of cameras, but also coordinates the position and orientation of the cameras with considering the installation costs. To validate the method, we compare simulation results with videos of real materials and show experimental results simulated in a specific space.

ESTIMATION OF THE POWER PEAKING FACTOR IN A NUCLEAR REACTOR USING SUPPORT VECTOR MACHINES AND UNCERTAINTY ANALYSIS

  • Bae, In-Ho;Na, Man-Gyun;Lee, Yoon-Joon;Park, Goon-Cherl
    • Nuclear Engineering and Technology
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    • v.41 no.9
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    • pp.1181-1190
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    • 2009
  • Knowing more about the Local Power Density (LPD) at the hottest part of a nuclear reactor core can provide more important information than knowledge of the LPD at any other position. The LPD at the hottest part needs to be estimated accurately in order to prevent the fuel rod from melting in a nuclear reactor. Support Vector Machines (SVMs) have successfully been applied in classification and regression problems. Therefore, in this paper, the power peaking factor, which is defined as the highest LPD to the average power density in a reactor core, was estimated by SVMs which use numerous measured signals of the reactor coolant system. The SVM models were developed by using a training data set and validated by an independent test data set. The SVM models' uncertainty was analyzed by using 100 sampled training data sets and verification data sets. The prediction intervals were very small, which means that the predicted values were very accurate. The predicted values were then applied to the first fuel cycle of the Yonggwang Nuclear Power Plant Unit 3. The root mean squared error was approximately 0.15%, which is accurate enough for use in LPD monitoring and for core protection that uses LPD estimation.

Machine Learning Based BLE Indoor Positioning Performance Improvement (머신러닝 기반 BLE 실내측위 성능 개선)

  • Moon, Joon;Pak, Sang-Hyon;Hwang, Jae-Jeong
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.10a
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    • pp.467-468
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    • 2021
  • In order to improve the performance of the indoor positioning system using BLE beacons, a receiver that measures the angle of arrival among the direction finding technologies supported by BLE5.1 was manufactured and analyzed by machine learning to measure the optimal position. For the creation and testing of machine learning models, k-nearest neighbor classification and regression, logistic regression, support vector machines, decision tree artificial neural networks, and deep neural networks were used to learn and test. As a result, when the test set 4 produced in the study was used, the accuracy was up to 99%.

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Analysis System for SNS Issues per Country based on Topic Model (토픽 모델 기반의 국가 별 SNS 관심 이슈 분석 시스템)

  • Kim, Seong Hoon;Yoon, Ji Won
    • Journal of KIISE
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    • v.43 no.11
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    • pp.1201-1209
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    • 2016
  • As the use of SNS continues to increase, various related studies have been conducted. According to the effectiveness of the topic model for existing theme extraction, a huge number of related research studies on topic model based analysis have been introduced. In this research, we suggested an automation system to analyze topics of each country and its distribution in twitter by combining world map visualization and issue matching method. The core system components are the following three modules; 1) collection of tweets and classification by nation, 2) extraction of topics and distribution by country based on topic model algorithm, and 3) visualization of topics and distribution based on Google geochart. In experiments with USA and UK, we could find issues of the two nations and how they changed. Based on these results, we could analyze the differences of each nation's position on ISIS problem.

A Study on Elastic Shaft Alignment Using Nonlinear Soaring Elements (비선형 베어링 요소를 이용한 탄성 추진 축계정렬에 관한 고찰)

  • Choung, Joon-Mo;Choe, Ick-Heung;Shin, Sang-Hoon
    • Journal of the Society of Naval Architects of Korea
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    • v.42 no.3
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    • pp.259-267
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    • 2005
  • The effects of hull flexibility on shaft alignment are growing as ship sizes are increased mainly for container carrier and LNG carrier. In order to consider hull flexibility on a propulsion shafting system, standardization of ship service conditions is necessary because hull deformation is continuously variable according to ship service conditions. How to summarize ship service conditions is suggested based on practically applicable four viewpoints : hull, engine, loading and sea status. Effects of the external forces acting on a ship propulsion shafting system are generally commented. Several design criteria regulated by classification societies are pointed at issue which seems to have Insufficient technical background. A qualitative verification is carried out to point out the invalidity of the assumption of effective supporting position. In this work, an elastic nonlinear multi-supporting bearing system is introduced as a key concept of the elastic shaft alignment. Hertz contact theory is proved to be more proper one than projected area method in calculation of the nonlinear elastic stiffness of the bearing, The squeezing and oil film pressure calculations in the long journal bearing like an after stern tube bearing are recognized as a necessary process for elastic shaft alignment design.

Data Acquisition System Using the Second Binary Code (2차원 부호를 이용한 정보 획득 시스템)

  • Kim, In-Kyeom
    • The Journal of Information Technology
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    • v.6 no.1
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    • pp.71-84
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    • 2003
  • In this paper, it is presented the efficient system for data recognition using the proposed binary code images. The proposed algorithm finds the position of binary image. Through the process of the block region classification, it is classified each block with the edge region using the value of gray level only. Each block region is divided horizontal and vertical edge region. If horizontal edge region blocks are classified over six blocks in any region, the proposed algorithm should search the vertical edge region in the start point of the horizontal edge region. If vertical edge region blocks were found over ten blocks in vertical region, the code image would found. Practical code region is acquired from the rate of the total edge region that is computed from the binary image that is processed with the average value. In case of the wrong rate, it is restarted the code search in the point after start point and the total process is followed. It has a short time than the before process time because it had classified block information. The block processing is faster thant the total process. The proposed system acquires the image from the digital camera and makes binary image from the acquired image. Finally, the proposed system extracts various characters from the binary image.

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Classification of Passing Vessels Around the Ieodo Ocean Research Station Using Automatic Identification System (AIS): November 21-30, 2013 (선박자동식별장치(AIS)를 이용한 이어도 종합해양과학기지 주변 통항 선박의 분류: 2013년 11월 21일~30일)

  • Hong, Dan-Bee;Yang, Chan-Su
    • Journal of the Korean Society for Marine Environment & Energy
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    • v.17 no.4
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    • pp.297-305
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    • 2014
  • In this study, we installed the Automatic Identification System (AIS) receiver on the Ieodo Ocean Research Station (IORS) from November 21 to 30, 2013 in order to monitor marine traffic and fishery activity in the jurisdictional sea area. The collected AIS raw data consist of static data report (MMSI, IMO NO., Call Sign, Ship Name, etc.) and position information report (position, speed, course, etc.), and the developed program was applied to classify ships according to ship flag and type information. The nationalities are released from the first three-digit numbers (MID) of MMSI, but in general most of small ships do not send an exact ship flag through Class B type AIS, a simplified and low-power equipment. From AIS data with flag information, ships under the flag of China had the highest frequency and the second was Korean flag, while in ship type cargo and fishing vessels were dominant in sequence. As for the ships without flag information, we compared the tracks with others in order to estimate ship flags. It can be said that fleets of ships with Chinese frequently appear sail together for fisheries over the waters, because the unknown ships followed a similar moving pattern with Chinese fishing vessels.

A Recognition Algorithm of Suspicious Human Behaviors using Hidden Markov Models in an Intelligent Surveillance System (지능형 영상 감시 시스템에서의 은닉 마르코프 모델을 이용한 특이 행동 인식 알고리즘)

  • Jung, Chang-Wook;Kang, Dong-Joong
    • Journal of Korea Multimedia Society
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    • v.11 no.11
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    • pp.1491-1500
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    • 2008
  • This paper proposes an intelligent surveillance system to recognize suspicious patterns of the human behavior by using the Hidden Markov Model. First, the method finds foot area of the human by motion detection algorithm from image sequence of the surveillance camera. Then, these foot locus form observation series of features to learn the HMM. The feature that is position of the human foot is changed to each code that corresponds to a specific label among 16 local partitions of image region. Therefore, specific moving patterns formed by the foot locus are the series of the label numbers. The Baum-Welch algorithm of the HMM learns each suspicious and specific pattern to classify the human behaviors. To recognize the inputted human behavior pattern in a test image, the probabilistic comparison between the learned pattern of the HMM and foot series to be tested decides the categorization of the test pattern. The experimental results show that the method can be applied to detect a suspicious person prowling in corridor.

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