• Title/Summary/Keyword: Auto detection

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Development of a driver's emotion detection model using auto-encoder on driving behavior and psychological data

  • Eun-Seo, Jung;Seo-Hee, Kim;Yun-Jung, Hong;In-Beom, Yang;Jiyoung, Woo
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.3
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    • pp.35-43
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    • 2023
  • Emotion recognition while driving is an essential task to prevent accidents. Furthermore, in the era of autonomous driving, automobiles are the subject of mobility, requiring more emotional communication with drivers, and the emotion recognition market is gradually spreading. Accordingly, in this research plan, the driver's emotions are classified into seven categories using psychological and behavioral data, which are relatively easy to collect. The latent vectors extracted through the auto-encoder model were also used as features in this classification model, confirming that this affected performance improvement. Furthermore, it also confirmed that the performance was improved when using the framework presented in this paper compared to when the existing EEG data were included. Finally, 81% of the driver's emotion classification accuracy and 80% of F1-Score were achieved only through psychological, personal information, and behavioral data.

LiDAR Static Obstacle Map based Position Correction Algorithm for Urban Autonomous Driving (도심 자율주행을 위한 라이다 정지 장애물 지도 기반 위치 보정 알고리즘)

  • Noh, Hanseok;Lee, Hyunsung;Yi, Kyongsu
    • Journal of Auto-vehicle Safety Association
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    • v.14 no.2
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    • pp.39-44
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    • 2022
  • This paper presents LiDAR static obstacle map based vehicle position correction algorithm for urban autonomous driving. Real Time Kinematic (RTK) GPS is commonly used in highway automated vehicle systems. For urban automated vehicle systems, RTK GPS have some trouble in shaded area. Therefore, this paper represents a method to estimate the position of the host vehicle using AVM camera, front camera, LiDAR and low-cost GPS based on Extended Kalman Filter (EKF). Static obstacle map (STOM) is constructed only with static object based on Bayesian rule. To run the algorithm, HD map and Static obstacle reference map (STORM) must be prepared in advance. STORM is constructed by accumulating and voxelizing the static obstacle map (STOM). The algorithm consists of three main process. The first process is to acquire sensor data from low-cost GPS, AVM camera, front camera, and LiDAR. Second, low-cost GPS data is used to define initial point. Third, AVM camera, front camera, LiDAR point cloud matching to HD map and STORM is conducted using Normal Distribution Transformation (NDT) method. Third, position of the host vehicle position is corrected based on the Extended Kalman Filter (EKF).The proposed algorithm is implemented in the Linux Robot Operating System (ROS) environment and showed better performance than only lane-detection algorithm. It is expected to be more robust and accurate than raw lidar point cloud matching algorithm in autonomous driving.

AutoML-based Refrigerant Leakage Detection of Air-Conditioning System (머신러닝 기반 실내 냉방기의 냉매누설 검출 방법)

  • Woo, Yeoungju;Kim, Yumin;Ahn, Sohyun;Ko, Seoyeong;Nguyen, Hang Thi Phuong;Shin, Choonsung;Jeong, Hieyong
    • Proceedings of the Korea Information Processing Society Conference
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    • 2021.11a
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    • pp.391-392
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    • 2021
  • 해마다 실내 냉방기 냉매누설 문제가 고질적으로 반복되며 소비자들의 피해도 커져가고 있다. 특히 제조사와 설치 업체가 다른 경우 냉매 누수의 원인이 제품인지, 설치하자인지 책임소재를 두고 갈등을 빚는 경우가 빈번하다. 이에 더 이상 소비자들의 피해를 막기 위해 냉매누설 검출 방안 마련이 필요해 보인다. 본 연구에서는 실내 냉방기 설치 후 냉매누설 검출을 위한 별도의 하드웨어 장치 추가 없이 냉방기의 운영을 위해 설치된 센서들의 값을 이용하여 냉매누설의 유무를 판단할 수 있는 방안을 제안하는 것을 목적으로 한다. 데이터 분석을 위하여 제조사의 제품 출하 전 현장 테스트 단계에서 측정한 온도값, 전류값, 습도값을 취합하여 데이터 셋을 구축하였다. 이때 자동화된 머신러닝(AutoML)을 이용하여 데이터의 80%를 훈련 데이터로 20%를 테스트 데이터로 사용하여 냉매량 80%는 1, 그 이하는 0으로 훈련시켰다. 구축한 데이터 셋을 이용하여 훈련시킨 결과 99% 정확도로 냉매누설 검출을 분별할 수 있었다. 또한 냉매누설과 관련성이 높은 중요 특징 4개를 추출할 수 있었다. 본 연구를 통하여 별도의 하드웨어 장치 추가 없이 소프트웨어적인 접근 방법으로 문제를 해결할 수 있는 feasibility를 확인할 수 있었다.

An Accuracy Evaluation of Algorithm for Shoreline Change by using RTK-GPS (RTK-GPS를 이용한 해안선 변화 자동추출 알고리즘의 정확도 평가)

  • Lee, Jae One;Kim, Yong Suk;Lee, In Su
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.32 no.1D
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    • pp.81-88
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    • 2012
  • This present research was carried out by dividing two parts; field surveying and data processing, in order to analyze changed patterns of a shoreline. Firstly, the shoreline information measured by the precise GPS positioning during long duration was collected. Secondly, the algorithm for detecting an auto boundary with regards to the changed shoreline with multi-image data was developed. Then, a comparative research was conducted. Haeundae beach which is one of the most famous ones in Korea was selected as a test site. RTK-GPS surveying had been performed overall eight times from September 2005 to September 2009. The filed test by aerial Lidar was conducted twice on December 2006 and March 2009 respectively. As a result estimated from both sensors, there is a slight difference. The average length of shoreline analyzed by RTK-GPS is approximately 1,364.6 m, while one from aerial Lidar is about 1,402.5 m. In this investigation, the specific algorithm for detecting the shoreline detection was developed by Visual C++ MFC (Microsoft Foundation Class). The analysis result estimated by aerial photo and satellite image was 1,391.0 m. The level of reliability was 98.1% for auto boundary detection when it compared with real surveying data.

Robust Semi-auto Calibration Method for Various Cameras and Illumination Changes (다양한 카메라와 조명의 변화에 강건한 반자동 카메라 캘리브레이션 방법)

  • Shin, Dong-Won;Ho, Yo-Sung
    • Journal of Broadcast Engineering
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    • v.21 no.1
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    • pp.36-42
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    • 2016
  • Recently, many 3D contents have been produced through the multiview camera system. In this system, since a difference of the viewpoint between color and depth cameras is inevitable, the camera parameter plays the important role to adjust the viewpoint as a preprocessing step. The conventional camera calibration method is inconvenient to users since we need to choose pattern features manually after capturing a planar chessboard with various poses. Therefore, we propose a semi-auto camera calibration method using a circular sampling and an homography estimation. Firstly, The proposed method extracts the candidates of the pattern features from the images by FAST corner detector. Next, we reduce the amount of the candidates by the circular sampling and obtain the complete point cloud by the homography estimation. Lastly, we compute the accurate position having the sub-pixel accuracy of the pattern features by the approximation of the hyper parabola surface. We investigated which factor affects the result of the pattern feature detection at each step. Compared to the conventional method, we found the proposed method released the inconvenience of the manual operation but maintained the accuracy of the camera parameters.

An Analysis of Optimal Sequences for the Detection of Wake-up Signal in Disaster-preventing Broadcast (재난방송용 대기모드 해제신호 검출을 위한 최적 부호 성능 분석)

  • Park, Hae Yong;Jo, Bonggyun;Kim, Heung Mook;Han, Dong Seog
    • Journal of Broadcast Engineering
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    • v.19 no.4
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    • pp.491-501
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    • 2014
  • Recently, the need for disaster-preventing broadcast has increased gradually to cope with natural disaster like earthquake and tsunami causing enormous losses of both life and property. In disaster-preventing broadcast system, the wake-up signal is used to alert user terminal and switch the current state of channel to the emergency channel, which is for the fast and efficient delivery of emergency information. In this paper, we propose the detection method of wake-up signal for disaster-preventing broadcast systems. The wake-up signals for disaster-preventing broadcast should have a good auto-correlation property in low power and narrow-band conditions that does not affect the existing digital television (DTV) system. The suitability of the m-sequence and complementary code (CC) is analyzed for wake-up signals according to signal to noise ratio. A wake-up signal is proposed by combining the direct sequence spread spectrum (DSSS) technique and pseudo noise (PN) sequences such as Barker and Walsh-Hadamard codes. By using the proposed method, a higher detecting performance can be achieved by the spreading gain compared to the single long m-sequence and the Golay code.

GIS 데이터구축 감리와 검수 프로그램

  • 조윤숙;박인만;정필구
    • Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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    • 2002.03b
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    • pp.11-24
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    • 2002
  • Many GIS systems are not to be trusted becuase many GIS project managers often fail to notice importance of GIS data Construction. With this reason, it is a lively discussion on GIS administration system's adaption. The definition of GIS administration system is not clear, but GIS administration system generally is devided information system administration, audit guideline for the data construction of GIS. Audit guideline for the data construction of GIS. GIS data construction's goals are logical and reasonable action policy of GIS data construction in widespread filed, the other goal is creation of product to the purpose exactly. Audit guideline for the data construction of GIS is composed of optimum of GIS data construction's planning, optimum of GIS data construction's activity, optimum of GIS data quality management, optimum of consultations of GIS data construction, GIS data audit. GIS data audit is the phase of detection product's potential error in each level. GIS data audit is composed of filed examination or filed verification, examination with the naked eye, screen verification, program verification, auto verification. GIS information system's efficiency is linked with auto verification system's function variety, accuracy. this paper offer introduction of Audit guideline for the data construction of GIS, efficient auto verification program

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Development of the Algofithm for Gaussian Mixture Models based Traffic Accident Auto-Detection in Freeway (GMM(Gaussian Mixture Model)을 적용한 영상처리기법의 연속류도로 사고 자동검지 알고리즘 개발)

  • O, Ju-Taek;Im, Jae-Geuk;Yeo, Tae-Dong
    • Journal of Korean Society of Transportation
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    • v.28 no.3
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    • pp.169-183
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    • 2010
  • Image-based traffic information collection systems have entered widespread adoption and use in many countries since these systems are not only capable of replacing existing loop-based detectors which have limitations in management and administration, but are also capable of providing and managing a wide variety of traffic related information. In addition, these systems are expanding rapidly in terms of purpose and scope of use. Currently, the utilization of image processing technology in the field of traffic accident management is limited to installing surveillance cameras on locations where traffic accidents are expected to occur and digitalizing of recorded data. Accurately recording the sequence of situations around a traffic accident in a freeway and then objectively and clearly analyzing how such accident occurred is more urgent and important than anything else in resolving a traffic accident. Therefore, in this research, existing technologies, this freeway attribute, velocity changes, volume changes, occupancy changes reflect judge the primary. Furthermore, We pointed out by many past researches while presenting and implementing an active and environmentally adaptive methodology capable of effectively reducing false detection situations which frequently occur even with the Gaussian Mixture model analytical method which has been considered the best among well-known environmental obstacle reduction methods. Therefore, in this way, the accident was the final decision. Also, environmental factors occur frequently, and with the index finger situations, effectively reducing that can actively and environmentally adaptive techniques through accident final judgment. This implementation of the evaluate performance of the experiment road of 12 incidents in simulated and the jang-hang IC's real-time accident experiment. As a result, the do well detection 93.33%, false alarm 6.7% as showed high reliability.

An Experimental Study for Performance Evaluation in Dogs of Preventive Contrast Media Extravasation with a Strain Gage Based Prototype Extravasation Detection Accessory System (잡견에서 조영제 혈관외유출 예방을 위한 스트레인 게이지 기반의 EDA 시스템 성능 평가를 위한 실험적 연구)

  • Kweon, D.C.;Yoo, B.G.;Lee, J.S.;Cho, M.S.;Yang, S.H.
    • Journal of Biomedical Engineering Research
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    • v.29 no.1
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    • pp.66-72
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    • 2008
  • The major risk associated with the use of automated power injectors is the well known complication of contrast material extravasation at the injection site. Automated injection of computed tomography (CT) contrast media can produce the compartment syndrome. The purpose of this study was to assess the ability of this device during clinically important episodes of extravasation. The extravasation detection accessory (EDA) system was composed of a strain gage, an amplifier and a computer based system. A strain gage pliable adhesive patch was applied to the skin aver the intravenous catheter and the catheter was connected to the power injector with a cable to monitor the resolution data. If the programmed monitoring, which was developed with MS Visual C++, at the extravasation occurred, then the injection was interrupted the auto injector. CT was used to demonstrate the clinically important extravasation. This study was a prospective, observational study in which the EDA system was used to monitor the automated mechanical injection of contrast material in 7 dogs. There were two true-positive cases (range of extravasation volumes: $18{\sim}22ml$), twenty three true-negative cases, three false-positive cases and no false-negative cases. The EDA system had a sensitivity of 100% and a specificity of 88% for the detection of clinically important extravasation. The EDA system had good sensitivity for the detection of clinically important extravasation and the EDA system has the clinical potential for the early detection of extravasation of the contrast medium that is administered with power injectors. The EDA system is easy to use safe and accurate for the monitoring extravasation of the intravenous injections, and this system may prove especially useful in CT applications.

Characterizing Multichannel Conduit Signal Properties Using a Ground Penetrating Radar: An FDTD Analysis Approach (FDTD 수치해석을 이용한 다중 관로에 대한 GPR 탐지 신호 특성 분석)

  • Ryu, Hee-Hwan;Bae, Joo-Yeol;Song, Ki-Il;Lee, Sang-Yun
    • Journal of the Korean Geotechnical Society
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    • v.39 no.12
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    • pp.75-91
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    • 2023
  • In this study, we explore the use of ground penetrating radar (GPR) for the nondestructive survey of subsurface conduits, focusing on the challenges posed by multichannel environments. A key concern is the shadow regions created by conduits, which significantly impact survey results. The shadow regions, which are influenced by conduit position and diameter, hinder signal propagation, thereby making detection within these regions challenging. Using finite-difference time-domain numerical analysis, we examined the characteristics of conduit signals, which typically manifest in hyperbolic patterns. Particularly, we investigated three conduit arrangements: horizontal, vertical, and diagonal. Automatic gain control was applied to amplify the signals, enabling the analysis of variations in shadow regions and signal characteristics for each arrangement. In the horizontal arrangement, the proximity of the two conduits resulted in the emergence of a new hyperbolic pattern between the existing conduits. In the vertical arrangement, the lower conduit could be detected using hyperbolic signals on either side, but the detection was challenging when the upper conduit diameter exceeded that of the lower conduit. In the diagonal arrangement, signal characteristics varied based on the position of shadow regions relative to the detection range of the equipment. Asymmetrical signal patterns were observed when the shadow regions fell within the detection range, whereas the signals of the two conduits were minimally impacted when the shadow regions were outside the detection range. This study provides vital insights into accurately detecting and characterizing subsurface multichannel conduits using GPR-a significant contribution to the field of subsurface exploration and management.