• 제목/요약/키워드: Traffic fine

검색결과 141건 처리시간 0.026초

딥러닝을 활용한 반도체 제조 물류 시스템 통행량 예측모델 설계 (A Deep Learning-Based Model for Predicting Traffic Congestion in Semiconductor Fabrication)

  • 김종명;김옥현;홍성빈;임대은
    • 산업기술연구
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    • 제39권1호
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    • pp.27-31
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    • 2019
  • Semiconductor logistics systems are facing difficulties in increasing production as production processes become more complicated due to the upgrading of fine processes. Therefore, the purpose of the research is to design predictive models that can predict traffic during the pre-planning stage, identify the risk zones that occur during the production process, and prevent them in advance. As a solution, we build FABs using automode simulation to collect data. Then, the traffic prediction model of the areas of interest is constructed using deep learning techniques (keras - multistory conceptron structure). The design of the predictive model gave an estimate of the traffic in the area of interest with an accuracy of about 87%. The expected effect can be used as an indicator for making decisions by proactively identifying congestion risk areas during the Fab Design or Factory Expansion Planning stage, as the maximum traffic per section is predicted.

One-dimensional CNN Model of Network Traffic Classification based on Transfer Learning

  • Lingyun Yang;Yuning Dong;Zaijian Wang;Feifei Gao
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제18권2호
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    • pp.420-437
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    • 2024
  • There are some problems in network traffic classification (NTC), such as complicated statistical features and insufficient training samples, which may cause poor classification effect. A NTC architecture based on one-dimensional Convolutional Neural Network (CNN) and transfer learning is proposed to tackle these problems and improve the fine-grained classification performance. The key points of the proposed architecture include: (1) Model classification--by extracting normalized rate feature set from original data, plus existing statistical features to optimize the CNN NTC model. (2) To apply transfer learning in the classification to improve NTC performance. We collect two typical network flows data from Youku and YouTube, and verify the proposed method through extensive experiments. The results show that compared with existing methods, our method could improve the classification accuracy by around 3-5%for Youku, and by about 7 to 27% for YouTube.

De-cloaking Malicious Activities in Smartphones Using HTTP Flow Mining

  • Su, Xin;Liu, Xuchong;Lin, Jiuchuang;He, Shiming;Fu, Zhangjie;Li, Wenjia
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제11권6호
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    • pp.3230-3253
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    • 2017
  • Android malware steals users' private information, and embedded unsafe advertisement (ad) libraries, which execute unsafe code causing damage to users. The majority of such traffic is HTTP and is mixed with other normal traffic, which makes the detection of malware and unsafe ad libraries a challenging problem. To address this problem, this work describes a novel HTTP traffic flow mining approach to detect and categorize Android malware and unsafe ad library. This work designed AndroCollector, which can automatically execute the Android application (app) and collect the network traffic traces. From these traces, this work extracts HTTP traffic features along three important dimensions: quantitative, timing, and semantic and use these features for characterizing malware and unsafe ad libraries. Based on these HTTP traffic features, this work describes a supervised classification scheme for detecting malware and unsafe ad libraries. In addition, to help network operators, this work describes a fine-grained categorization method by generating fingerprints from HTTP request methods for each malware family and unsafe ad libraries. This work evaluated the scheme using HTTP traffic traces collected from 10778 Android apps. The experimental results show that the scheme can detect malware with 97% accuracy and unsafe ad libraries with 95% accuracy when tested on the popular third-party Android markets.

항공사진 촬영 왜곡보정기술 개발 및 적용 사례 - Photoshop과 PC-Rect 적용 중심 (Development and Application of Aerial Photographing Distortion Correction Technology - Focused on Photoshop and PC-Rect)

  • 박명철;박종찬;윤용문;김송희
    • 한국안전학회지
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    • 제32권4호
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    • pp.100-106
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    • 2017
  • Outline map is used for the description and reconstruction of the traffic accident. One way to produce the outline map is by adopting detailed measurements from the accident site such as final position of the vehicle and pedestrian, width of the road, and locations of the oil and tire marks. This method consumes large amount of time not to mention that of the production of detailed version as fine as the picture of the site. Aerial recording equipment so called HeliCam can produce an outline map that can substitute that of manual method with even faster production time and higher resolution. However, the produced picture have errors which are resulted by distortion due to the characteristics of camera and direction of the photographing. This paper provides correction of the distortion of oultline map produced by HeliCam using Adobe Photoshop and PC-Rect. The result showed resonable error range less than 6 cm(0.1%) for $60m{\times}30m$ area taken by HeliCam. The presented method develops outline map with small error, which is useful to traffic accident analysis, and traffic accident cases analyzed in this study were also.

토픽모델링을 활용한 교통경찰 민원 분석 (An Analysis of Civil Complaints about Traffic Policing Using the LDA Model)

  • 이상엽
    • 한국ITS학회 논문지
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    • 제20권4호
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    • pp.57-70
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    • 2021
  • 본 연구는 민원데이터를 분석함으로써 교통경찰에 대한 국민의 치안 수요를 탐색하고자 하였다. 이를 위해 교통경찰 관련 국민신문고 민원데이터 2,062건을 대상으로, 토픽모델링 방법 중 하나인 잠재 디리클레 할당(Latent Dirichlet Allocation)을 통해 주요 토픽을 추출하고 높은 비중을 차지한 위반신고에 대해 추가분석을 시도하였다. 이 과정에서 키워드와 대표문서의 일관성과 합치성을 함께 고려하였다. 분석 결과 교통경찰 관련 민원은 시설개선, 신호에 따른 교차로통행방법, 번호판 영치, 개인형 이동장치 등 41개의 토픽으로 분류할 수 있었다. 교차로내 위반과 이륜자동차의 위반에 대한 단속을 강화하고 무인교통단속장비, 횡단보도, 신호등의 설치 및 운영에 대한 선제적인 조치, 최근 개정된 법령과 시행된 정책, 경찰교통민원 사이트, 단속 사후 절차에 대한 더욱 활발한 홍보가 필요한 것으로 판단된다.

서울시 대기중 부유분진의 입도별 돌연변이원성의 월변화 (Monthly Variation in the Salmonella Mutagenicity by Suspended Particulate according to Particle Size in Seoul City)

  • 장재연;김박광;조성준;정용
    • 약학회지
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    • 제32권5호
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    • pp.362-369
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    • 1988
  • Monthly variation of mutagenicity by airborne particulate were studied according to particle size of the particulate. Airborne particulates were collected in Shinchon of Seoul which is commocial and traffic area in 1986. And those were separately collected into two parts such as fine particle (less than $2.5{\mu}m$ aerodynamic diameter) and coarse particle (greater than $2.5{\mu}m$). Extractable organic matters(EOM) were extracted and mutagenicity of the EOM was tested in Salmonella thyphimurium TA 98 by Ames method. While the concentration of coarse particle did not show the seasonal variation, that of fine particle showed great seasonal variation. The contents and mutagenicity of EOM in fine particles were higher than those of coarse particles. So fine particles were expected to contribute to the 90% of mutagenicity in atmosphere by suspended particulates. The content of EOM and mutagenicity by suspended particulates in atmosphere were highest in January all the year around and also higher as much as 6 and 30 times than in July, respectively.

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공간 분석을 통한 부산광역시 대기오염물질의 분포와 이동오염원 간의 관련성 연구 (Analysis of the Association between Air Pollutant Distribution and Mobile Sources in Busan Using Spatial Analysis)

  • 민재희;김병권;주현지;김나영;황용식;이승호;홍영습
    • 한국환경보건학회지
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    • 제50권3호
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    • pp.191-200
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    • 2024
  • Background: Busan is a rapidly industrializing city with many mixed residential and industrial areas. Fine dust emissions from mobile pollution sources such as ships and vehicles are particularly high in Busan. Objectives: This study analyzed the spatial distribution of air pollutants over the past three years and identified the impact of air pollutants through mobile source data in Busan. Methods: We obtained air pollutant data on fine particulate matter (PM10), ultrafine particulate matter (PM2.5), nitrogen dioxide (NO2), sulfurous acid gas (SO2), and ozone (O3) for the last three years (source: airkorea.or.kr) and analyzed the spatial distribution using SAS 9.4 and Surfer 23. For the mobile pollutant data, we used CCTV data from major intersections in Busan to identify truck and car traffic, and visualized traffic density with QGIS. Results: The analysis of the concentration of air pollutants over three years (2020~2022) showed that all were lower than the annual environmental standards with the exception of PM2.5. PM10 and PM2.5 were found to be highly concentrated in the western part of the area, while NO2 was high in the port area of Busan and SO2 was high in the western part of the area and near the new port of Busan. In the case of O3, it was high in the eastern part of the city. The traffic volume of freight vehicles by intersection was concentrated in the West Busan area, and the traffic volume for all cars was also confirmed to be concentrated at "Mandeok Intersection" located in the West Busan area. Conclusions: This study was conducted to determine the relationship between air pollutants emitted from motor vehicles and the distribution of air pollutants in Busan. The spatial distribution of PM10 and PM2.5 correlates with traffic volume, while high concentrations of SO2 and NO2 near the port are associated with ship emissions.

해상교통을 위한 국지정밀 해상풍 예측 (Local Fine Grid Sea Wind Prediction for Maritime Traffic)

  • 박광순;전기천;권재일;허기영
    • 한국항해항만학회:학술대회논문집
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    • 한국항해항만학회 2009년도 공동학술대회
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    • pp.449-451
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    • 2009
  • 지구온난화에 따른 해수면 상승과 태풍 강도의 증가는 연안역에 밀집한 주거 및 산업공간을 위협하는 요소로 최근 그 연구가 활발하게 진행되어 오고 있다. 본 연구에서는 안전한 해상교통 및 폭풍해일과 파랑예측을 위해서 반드시 필요한 해상풍에 대한 연구이다. 해상풍은 연안역에서의 자연재해를 유발하는 여러 요소 중에서 중요한 연구과제이나, 현재 가상수치모델에 의한 해상풍 및 해면기압은 시 공간적으로 불충분하다. 따라서, 중규모 기상 모형인 Weather Research and Forecasting(WRF)을 사용하여 우리나라 주변해역을 모두 포함하며, 약 9km 격자로 매일 두 번씩 72시간을 예보하는 해상풍을 산출하는 시스템을 구축하였다. 이어도 해양과학기지와 황해중부부이에서 실측한 해상풍과 검증한 결과 상당히 유의할 만한 결과를 얻었으며, 자료동화을 이용하여 향후에는 보다 정확한 해상풍을 산출할 계획이다.

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썬큰광장의 교통소음 감쇠 효과 (Traffic Noise Reduction of Sunken Squares)

  • 민장기;장태현;정재만
    • 한국조경학회지
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    • 제32권5호
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    • pp.35-42
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    • 2004
  • This study examines the traffic noise reduction effects of the diverse efficiency features of a sunken square, and investigates the reduction effects and characteristics of noise alterations according to the construction conditions in order to verify its possibility as a new noise reduction facility. The measured data were analyzed. As a result, (1) the traffic noise from the roads around the sunken squares exceeded the regulatory standards; (2) the sunken squares were protected from noise; (3) the sunken spaces yielded a greater reduction by 6∼7dB than the flat ground thanks to the diffraction effect; and (4) there were fine changes to noise according to the conditions of space construction. In short, a sunken square has the potential to afford new applications as a noise reduction facility in a highly concentrated downtown with the existing defects solved. In addition, its use for effective noise control is evident based on the noise characteristics of a space. Future studies need to include efforts to provide clearer quantitative data, as well as research on shape, layout, and materials.