• Title/Summary/Keyword: Auto-Management

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Auto-Analysis of Traffic Flow through Semantic Modeling of Moving Objects (움직임 객체의 의미적 모델링을 통한 차량 흐름 자동 분석)

  • Choi, Chang;Cho, Mi-Young;Choi, Jun-Ho;Choi, Dong-Jin;Kim, Pan-Koo
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.8 no.6
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    • pp.36-45
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    • 2009
  • Recently, there are interested in the automatic traffic flowing and accident detection using various low level information from video in the road. In this paper, the automatic traffic flowing and algorithm, and application of traffic accident detection using traffic management systems are studied. To achieve these purposes, the spatio-temporal relation models using topological and directional relations have been made, then a matching of the proposed models with the directional motion verbs proposed by Levin's verbs of inherently directed motion is applied. Finally, the synonym and antonym are inserted by using WordNet. For the similarity measuring between proposed modeling and trajectory of moving object in the video, the objects are extracted, and then compared with the trajectories of moving objects by the proposed modeling. Because of the different features with each proposed modeling, the rules that have been generated will be applied to the similarity measurement by TSR (Tangent Space Representation). Through this research, we can extend our results to the automatic accident detection of vehicle using CCTV.

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An Analysis on the Status of Inappropriate Material Posting and Personal Information Exposure in Elementary Schools' Web Sites (초등학교 홈페이지에서의 불건전 정보 유통 및 개인정보 노출 실태 분석)

  • Kim, Min-Ki
    • Journal of The Korean Association of Information Education
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    • v.8 no.4
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    • pp.489-500
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    • 2004
  • In this paper, an investigation on internet safety of 244 national or public elementary schools' web sites was performed with two points of view : inappropriate material posting and personal information exposure. The investigation results showed that obscene materials and commercial advertisements were uploaded into the bulletin board(67.2%) and students' personal information such as photograph, address, telephone number were exposed(87.3%). Most of the inappropriate materials were posted by auto-register programs. This problem was occurred due to reckless bulletin board opening and inappropriate management. On the contrary, personal information was exposed by teachers and students. They didn't not care about their personal information. It shows the fact that they have not recognized the danger of personal information exposure. Therefore managing real-name membership and enforcing permission to bulletin board were required to construct and use a safe school web site. Teachers have to understand not only negative effects appeared in a school web site but also latent dangerous factors.

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A Study on Classification of Medical Information Documents using Word Correlation (색인어 연관성을 이용한 의료정보문서 분류에 관한 연구)

  • Lim, Hyeong-Geon;Jang, Duk-Sung
    • The KIPS Transactions:PartB
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    • v.8B no.5
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    • pp.469-476
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    • 2001
  • As the service of information through web system increases in modern society, many questions and consultations are going on through Home page and E-mail in the hospital. But there are some burdens for the management and postponements for answering the questions. In this paper, we investigate the document classification methods as a primary research of the auto-answering system. On the basis of 1200 documents which are questions of patients, 66% are used for the learning documents and 34% for test documents. All of are also used for the document classification using NBC (Naive Bayes Classifier), common words and coefficient of correlation. As the result of the experiments, the two methods proposed in this paper, that is, common words and coefficient of correlation are higher as much as 3% and 5% respectively than the basic NBC methods. This result shows that the correlation between indexes and categories is more effective than the word frequency in the document classification.

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Inter-device Mutual Authentication and Formal Verification in Vehicular Security System (자동차 보안시스템에서 장치간 상호인증 및 정형검증)

  • Lee, Sang-Jun;Bae, Woo-Sik
    • Journal of Digital Convergence
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    • v.13 no.4
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    • pp.205-210
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    • 2015
  • The auto industry has significantly evolved to the extent that much attention is paid to M2M (Machine-to-Machine) communication. In M2M communication which was first used in meteorology, environment, logistics, national defense, agriculture and stockbreeding, devices automatically communicate and operate in accordance with varying situations. M2M system is applied to vehicles, specifically to device-to-device communication inside cars, vehicle-to-vehicle communication, communication between vehicles and traffic facilities and that between vehicles and surroundings. However, communication systems are characterized by potential intruders' attacks in transmission sections, which may cause serious safety problems if vehicles' operating system, control system and engine control parts are attacked. Thus, device-to-device secure communication has been actively researched. With a view to secure communication between vehicular devices, the present study drew on hash functions and complex mathematical formulae to design a protocol, which was then tested with Casper/FDR, a tool for formal verification of protocols. In brief, the proposed protocol proved to operate safely against a range of attacks and be effective in practical application.

Short-term Forecasting of Power Demand based on AREA (AREA 활용 전력수요 단기 예측)

  • Kwon, S.H.;Oh, H.S.
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.39 no.1
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    • pp.25-30
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    • 2016
  • It is critical to forecast the maximum daily and monthly demand for power with as little error as possible for our industry and national economy. In general, long-term forecasting of power demand has been studied from both the consumer's perspective and an econometrics model in the form of a generalized linear model with predictors. Time series techniques are used for short-term forecasting with no predictors as predictors must be predicted prior to forecasting response variables and containing estimation errors during this process is inevitable. In previous researches, seasonal exponential smoothing method, SARMA (Seasonal Auto Regressive Moving Average) with consideration to weekly pattern Neuron-Fuzzy model, SVR (Support Vector Regression) model with predictors explored through machine learning, and K-means clustering technique in the various approaches have been applied to short-term power supply forecasting. In this paper, SARMA and intervention model are fitted to forecast the maximum power load daily, weekly, and monthly by using the empirical data from 2011 through 2013. $ARMA(2,\;1,\;2)(1,\;1,\;1)_7$ and $ARMA(0,\;1,\;1)(1,\;1,\;0)_{12}$ are fitted respectively to the daily and monthly power demand, but the weekly power demand is not fitted by AREA because of unit root series. In our fitted intervention model, the factors of long holidays, summer and winter are significant in the form of indicator function. The SARMA with MAPE (Mean Absolute Percentage Error) of 2.45% and intervention model with MAPE of 2.44% are more efficient than the present seasonal exponential smoothing with MAPE of about 4%. Although the dynamic repression model with the predictors of humidity, temperature, and seasonal dummies was applied to foretaste the daily power demand, it lead to a high MAPE of 3.5% even though it has estimation error of predictors.

Improvement Research of BLE-based System for Monitoring the cause of Breakdown of Automatic Doors (자동문의 고장원인을 모니터링하기 위한 BLE 기반의 시스템 개선연구)

  • Kim, Gi-Doo;Won, Seo-Yeon;Kim, Hie-Sik
    • Journal of the Institute of Electronics and Information Engineers
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    • v.54 no.7
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    • pp.93-102
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    • 2017
  • Recently increasing usage of smartphones makes the Internet of Things (IoT) a leading technology that can collect and share data through sensor networks and wireless communication such as low-power Bluetooth (BLE). BLE-based application can provide operators more precise information on Automatic Door system by remotely diagnosing the system faults through wireless sensor networks and sensors around the Automatic Door. In this paper, a smart device with extended BLE module is implemented which can monitor and Control the system states and faults remotely without on-site diagnostic. while maintaining system integrity so that increase efficiency of time and costs for system management. We can use the results of this research as a basis in evaluating reliability of data between devices, extending communication module in Controller of obsolete Door systems, and establishing centralized monitoring systems in near future with multi-channel Door Controls.

The Study on Time Series Analysis of Groundwater Data and Groundwater Recharge in Jeju Island (제주도 수리자료에 대한 시계열 분석 및 지하수 함양률 추정 연구)

  • Choi, Hyun-Mi;Lee, Jin-Yong;Ha, Kyoo-Chul;Kim, Gee-Pyo
    • The Journal of Engineering Geology
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    • v.21 no.4
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    • pp.337-348
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    • 2011
  • We examined temporal variations in and relationships among groundwater level, groundwater temperature, and electric conductivity, and estimated groundwater recharge at Jeju Island. The time lag and regulation time of groundwater level data revealed that monitoring well in Ansung (JM-AS) has the highest auto-correlation. The cross-correlations for electric conductivity-water level, precipitation-water level, and air temperature-water temperature revealed that monitoring well in Seogwi-2 (JR-SG2) (electric conductivity-water level), monitoring well in Hamo (JD-HM) (precipitation-water level), and monitoring well in Wonjongjang-2 (JT-WJJ2) (air temperature-water temperature) had the highest cross-correlations. The average groundwater recharge ratio was 39.61%, and the average groundwater recharge amount was 1,153,490,407 $m^3/yr$, which is consistent with the results of previous studies.

A Development of an Integrated Inventory Managing System for Steel-Plates (강재 통합 관리 시스템 개발)

  • Lee, Seok Hyun;Yu, Ji Hun;Kim, Hyun Chul;Jang, Seok Min;Lim, Rae Soo;Kim, Ho Kyeong;Heo, Joo Ho
    • Journal of the Society of Naval Architects of Korea
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    • v.51 no.2
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    • pp.130-137
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    • 2014
  • As one of the largest shipbuilding company in the world, STX Offshore & Shipbuilding currently developed an inventory managing system for steel-plates, which is applied to their steel stock yard. In a traditional way to manage steel yard, almost every work has been done by manually. The manual steel-plate piling process caused some problems such as process delay due to piling errors and the uncertainty of work plan due to lack of information. To solve these problems, we developed an integrated inventory managing system based on real-time crane tracking system which automatically updates steel-plates' piling status. We built the integrated steel-plate database, developed several programs including steel-plate input program, real-time steel-plate monitoring program and steel-yard management program, and constructed hardware system for tracking magnetic cranes. As a result, a supervisor of steel-yard can manage the inventory of steel-plates efficiently and furthermore plan an efficient piling schedule and crane working schedule.

An Auto-blogging System based Context Model for Micro-blogging Service (마이크로 블로깅 서비스를 지원하기 위한 컨텍스트 모델 기반 자동 블로깅 시스템)

  • Park, Jae-Min;Lee, Sang-Yong
    • Journal of Digital Convergence
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    • v.10 no.4
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    • pp.341-346
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    • 2012
  • Social network service is service that enables the human network to be built up on web. It is important to record users' information simply and establish the network with people based on the information to provide with the social network service effectively. But it is very troublesome work for the user to input his or her own information on the mobile environment. In this paper we suggested a system which classifies users' behavior using context and creates blogging sentences automatically after inferring the destination. For this, users' behavior is classified and the destination is inferred with the sequence matching method using Naive Bayes classification. Then sentences which are suitable for situation is created by arranging the processed context using the structure of 5W1H. The system was evaluated satisfaction degree by comparing the created sentences based on actually collected data with users' intension and got accuracy rate of 88.73%.

A study on analysis of DVR(Dynamic Voltage Restorer) in electric traction network by using the PSCAD/EMTDC (PSCAD/EMTDC를 이용한 전기철도급전계통에 DVR(Dynamic Voltage Restorer)해석에 관한 연구)

  • Choi, J.H.;Kim, J.C.;Park, S.M.;Kim, T.S.;Choo, D.W.;Chung, I.Y.;Park, S.W.
    • Proceedings of the KIEE Conference
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    • 2003.07a
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    • pp.283-286
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    • 2003
  • The electric traction load is quite differ from general power system load which is single-phase, high-speed heavy load receiving power from 3-phase power system and also has variable load characteristics over time and space. Therefore, there are inevitably power quality problems such as steady state or transient voltage drop, voltage imbalance and harmonic distortion. In addition, it is expected that transient voltage sag could affect the safety of feeding system. Thus, in this paper transient analysis and voltage sag compensation of AT(Auto Transformer) feeding system are studied. The fault study of traction network is analysed by using PSCAD/SMTDC simulation tool. In addition, application of DVR in electric traction system is proposed to compensate the voltage sag of traction network which is occurred by the fault of utility source. The results of fault study will be a useful research works for operation and setting of electric traction relay. Also, it can be shown that application of the DVR in electric system is very useful to compensate the voltage sag from the result of related simulated work. The results of study will be a useful research works for management and planning of power quality in electric traction system.

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