• Title/Summary/Keyword: 상황 이력

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An Automatic Pattern Recognition Algorithm for Identifying the Spatio-temporal Congestion Evolution Patterns in Freeway Historic Data (고속도로 이력데이터에 포함된 정체 시공간 전개 패턴 자동인식 알고리즘 개발)

  • Park, Eun Mi;Oh, Hyun Sun
    • Journal of Korean Society of Transportation
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    • v.32 no.5
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    • pp.522-530
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    • 2014
  • Spatio-temporal congestion evolution pattern can be reproduced using the VDS(Vehicle Detection System) historic speed dataset in the TMC(Traffic Management Center)s. Such dataset provides a pool of spatio-temporally experienced traffic conditions. Traffic flow pattern is known as spatio-temporally recurred, and even non-recurrent congestion caused by incidents has patterns according to the incident conditions. These imply that the information should be useful for traffic prediction and traffic management. Traffic flow predictions are generally performed using black-box approaches such as neural network, genetic algorithm, and etc. Black-box approaches are not designed to provide an explanation of their modeling and reasoning process and not to estimate the benefits and the risks of the implementation of such a solution. TMCs are reluctant to employ the black-box approaches even though there are numerous valuable articles. This research proposes a more readily understandable and intuitively appealing data-driven approach and developes an algorithm for identifying congestion patterns for recurrent and non-recurrent congestion management and information provision.

Association Service Mining using Level Cross Tree (레벨 교차 트리를 이용한 연관 서비스 탐사)

  • Hwang, Jeong Hee
    • Journal of Digital Contents Society
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    • v.15 no.5
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    • pp.569-577
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    • 2014
  • The various services are required to user in time and space. It is important to provide suitable service to user according to user's circumstance. Therefore it is need to provide services to user through mining by latest information of user activity and service history. In this paper we propose a mining method to search association rule using service history based on spatiotemporal information and service ontology. In this method, we find the associative service pattern using level-cross tree on service ontology. The proposed method is to be a basic research to find the service pattern to provide high quality service to user according to season, location and age under the same context.

A Study on the Prediction of Traffic Volume on Highway by the Reference Day of Archived Data (이력자료 참조일수에 따른 고속도로 교통량 예측에 관한 연구)

  • Lee, So-Yeon;Jung, So-Yeon
    • Journal of the Society of Disaster Information
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    • v.14 no.2
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    • pp.230-237
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    • 2018
  • Purpose: In Korea, traffic information is collected in real time as part of Intelligent Transportation System to enhance efficiency of road operation. However, traffic information based on real-time data is different from the traffic situation the driver will experience. Method: In this study, forecasts were made for future highway traffic by day and time period by adjusting the Archived data reference days to 3, 5 and 10 days based on existing traffic Archived data. Results: Fewer days of reference in the past showed smaller errors. The prediction of Monday based on five past histories showed greater errors than the 10 past histories, as the traffic flow on the sixth Monday of 2016 was somewhat different from the usual holiday. Conclution: This study shows that less of the reference days of the past history when estimating traffic volume, the more accurate the data of the traffic history of the event can be used on special days.

Design and Implementation of the Taxi Telematics Driving History Data Visualization System using Google Earth (Google Earth를 이용한 택시 텔레매틱스 운행 이력 데이터 가시화 시스템의 설계 및 구현)

  • Choi, Jin-Woo;Yang, Young-Kyu
    • Korean Journal of Remote Sensing
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    • v.25 no.1
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    • pp.61-69
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    • 2009
  • This paper presents design and implementation of a system for effective visualizing driving history data of the Jeju taxi telematics system using Google Earth. It is possible to review the situation of all taxies or extract the trace of any taxi or search taxies driven through a region of interest.

Seismic Design of Long Span Structures Based on Hysteric Energy Absorption Mechanism(1) (이력에너지흡수 원리를 이용한 대경간 구조물의 내진설계(1) -이선형 탄소성 이력거동에 의안 에너지 소산원리를 이용하는 방법-)

  • Cheong, Myung-Chae;Won, Sung-Dae
    • Journal of Korean Association for Spatial Structures
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    • v.10 no.1
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    • pp.85-93
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    • 2010
  • This paper suggests a vibration control method long span structures with trussed roof. Basic concept of this method is based on the energy absorption through hysteresis loop of an elasto-plastic element. This element is attached on the top of the column supporting the roof. Two different types of roofs and three of earthquake waves are used in the investigation. It shows that this is very efficient method to reduce the seismic energy of roof member transferred from the column.

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A Smart Home-Based Elderly Emergency Detection and Response System (스마트 홈 기반 노약자 응급상황 탐지 및 대응 시스템)

  • Byeong-Sun Park;Do-Yeong Shin;Su-A-Yun;Chae-Won-Park;Min-Ho-Bae
    • Annual Conference of KIPS
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    • 2023.11a
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    • pp.998-999
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    • 2023
  • 본 논문에서는 스마트 홈 기반 노약자 응급상황 탐지 및 대응 시스템을 설계하였다. 2 개의 레이다 센서를 활용하여 센서 데이터를 분석하고 분류하며, 사용자의 상태를 취침, 외출, 응급상황 총 3 가지 경우로 식별한다. AWS 서버의 데이터베이스를 통해 응급상황 및 낙상 감지 이력을 축적하여 맞춤형 서비스를 제공한다. 어플리케이션을 통해 응급상황 자동 신고 접수와 센서 오작동시 자동 신고 접수 수동 취소 기능을 제공하는 응급상황 탐지 및 대응 시스템을 소개한다.

Speed Prediction of Urban Freeway Using LSTM and CNN-LSTM Neural Network (LSTM 및 CNN-LSTM 신경망을 활용한 도시부 간선도로 속도 예측)

  • Park, Boogi;Bae, Sang hoon;Jung, Bokyung
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.20 no.1
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    • pp.86-99
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    • 2021
  • One of the methods to alleviate traffic congestion is to increase the efficiency of the roads by providing traffic condition information on road user and distributing the traffic. For this, reliability must be guaranteed, and quantitative real-time traffic speed prediction is essential. In this study, and based on analysis of traffic speed related to traffic conditions, historical data correlated with traffic flow were used as input. We developed an LSTM model that predicts speed in response to normal traffic conditions, along with a CNN-LSTM model that predicts speed in response to incidents. Through these models, we try to predict traffic speeds during the hour in five-minute intervals. As a result, predictions had an average error rate of 7.43km/h for normal traffic flows, and an error rate of 7.66km/h for traffic incident flows when there was an incident.

Design and Implementation of RFID Processing Systems for Agricultural Products Traceability (농산물 이력 추적 관리를 위한 RFID 처리 시스템 설계 및 구현)

  • Yeon Dong-Hee;Lee Sang-Jo;Cho Tae-Beom;Min Byung-Hun;Jung Hoe-Kyung
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2006.05a
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    • pp.931-934
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    • 2006
  • Recently, as the problems related to agricultural product's safety occur continuously, the system with traceability that can quickly trace back the agricultural products with problems occurred and enable the analysis of causes and prohibition of distribution is required. Therefore, the recording of distribution data is important for this system and for this purpose, the RFID technology that can perceive tags from remote place through radio frequency can be effectively used. But, since the RFID is a technology that is being watched recently, the system that processes RFID tags and distribution data is trifling. Hereby, this thesis designed and implemented the RFID processing system that enables the career trace by analyzing and managing the data on recorded RFID tags and career data based on the standard of traceability.

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A Mining System based on ECA Rule in Ubiquitous Environment (유비쿼터스 환경의 ECA 규칙기반 마이닝 시스템)

  • Hwang, Jeong Hee
    • Annual Conference of KIPS
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    • 2010.11a
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    • pp.14-15
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    • 2010
  • 유비쿼터스 환경에서 사용자에게 최적의 서비스를 제공하기 위해서는 사용자 행동 및 서비스 이력을 기반으로 사용자의 상황에 적합한 새로운 서비스 규칙을 발견하는 것이 중요하다. 이 논문에서는 사용자의 상황을 고려하기 위한 컨텍스트 온톨로지를 기반으로 사용자의 행동 및 서비스 패턴을 능동적으로 마이닝할 수 있는 ECA규칙 기반의 시스템 구조를 제안한다.

A Context-Aware Lecture Rooms Management System (상황인식 강의실 관리 시스템)

  • Park, Kyuhuen;Baek, Sunjae;Lee, Daesung;Yoon, Sungpil;Moon, Mikyeong
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2009.10a
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    • pp.231-234
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    • 2009
  • 일반적으로 사용자의 작업과 관련 있는 적절한 정보 또는 서비스를 제공하는 과정에서 '상황'을 사용하는 경우 이를 상황인식 시스템으로 정의한다. 상황인식 컴퓨팅 기술이 내장된 기기나 컴퓨터는 상황을 감지하여 적절하고 유용한 서비스를 제공하는 능력을 갖게 된다. 이러한 기술은 교육, 의료, 사무실 환경 등 다양한 분야에 걸쳐 활용된다. 특히 현대화된 강의실 환경은 각종 매체의 설치로 인해 전력소모가 심해지며, 매체들과 강의 환경의 효율적인 관리가 어려워지는 문제를 발생시키므로 상황인식 컴퓨팅 기술이 적용될 필요가 있다. 본 논문에서는 상황인식 기술을 이용한 강의실 관리 시스템을 제안한다. 이 관리 시스템은 다양한 센서 (온도, 조도, $CO_2$, 인체감지) 로부터 획득되는 저수준의 데이터를 사용자가 식별할 수 있는 추상화된 고수준의 정보로 변환하여 사용자에게 알려준다. 이 시스템을 구축함으로써 관리자는 강의실 내부에 설치된 매체들과 환경요소에 대한 상황을 쉽게 인식 할 수 있고, 강의실 내부의 상황변화에 대해 능동적으로 관리 할 수 있게 된다. 또한 강의실에 대한 과거의 이력정보를 검색 할 수 있음으로써 사전관리가 가능해짐에 따라 수동적인 관리로 인한 전력소비에 비해 전력절감 효과가 있고 쾌적한 강의실 환경을 학생들에게 제공 해 줄 수 있게 된다.

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