• Title/Summary/Keyword: data-driver

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An Analysis of Driving Pattern and Transportation Efficiency of Commercial Vehicle using On-board Truck scale (자중계 적용을 통한 화물차량 운행패턴 및 운송효율성 분석)

  • Kim, Jong Woo;Jung, Young Woo;Jho, Youn Beom
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.18 no.6
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    • pp.76-95
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    • 2019
  • An on-board truck scale is an essential technical solution for preventing overload, which makes the driver aware of the commercial vehicle weight. This study analyzed the effects of the driving pattern and transportation efficiency by the IoT Platform service for an on-board truck scale. A comparison of before and after installation using the long-term monitored data confirmed the reduction effects both of the overload ratio and overweight value, and their effects on increasing the transportation efficiency. In addition, the analysis result of the driving route showed that the installation of an on-board truck scale could be a more effective way of preventing overload than increasing the weighing checkpoints.

A Case Study of Exposure to Elemental Carbon (EC) in an Underground Copper Ore Mine (구리원석광산에서의 Elemental Carbon (EC) 노출에 관한 사례연구)

  • Lee, Su-Gil;Kim, Jung-Hee;Kim, Seong-Soo
    • Journal of Environmental Science International
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    • v.26 no.9
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    • pp.1013-1021
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    • 2017
  • Exposure to Diesel Particulate Matter (DPM) potentially causes adverse health effects (e.g. respiratory symptoms, lung cancer). Due to a lack of data on Elemental Carbon (EC) exposure levels in underground copper ore mining (unlike other underground mining industries such as non-metallic and coal mining), this case study aims to provide individual miners' EC exposure levels, and information on their work practices including use of personal protective equipment. EC measurement was carried out during different work activities (i.e. drilling, driving a loader, plant fitting, plant operation, driving a Specialized Mining Vehicle (SMV)) as per NIOSH Method 5040. The copper miners were working 10 h/day and 5 days/week. This study found that the most significant exposures to EC were reported from driving a loader (range $0.02-0.42mg/m^3$). Even though there were control systems (i.e. water tanks and DPM filters) on the diesel vehicles, around 49.5% of the results were over the adjusted recommendable exposure limit ($0.078mg/m^3$). This was probably due to: (1) driver's frequently getting in and out of the diesel vehicles and opening the windows of the diesel vehicles, and (2) inappropriate maintenance of the diesel vehicles and the DPM control systems. The use of the P2 type respirator provided was less than 19.2%. However, there was no significant difference between the day shift results and the night shift results. In order to prevent or minimize exposure to EC in the copper ore mine, it is recommended that the miners are educated in the need to wear the appropriate respirator provided during their work shifts, and to maintain the diesel engine and emission control systems on a regular basis. Consideration should be given to a specific examination of the diesel vehicles' air-conditioning filters and the air ventilation system to control excessive airborne contaminants in the underground copper mine.

Design and Applications of Graphics Interface on Personal Computer (개인용 컴퓨터상의 그래픽스 인터페이스 설계와 응용)

  • Kim, Jin-Han;Kyung, Chong-Min
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.26 no.1
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    • pp.113-121
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    • 1989
  • A software interface called CGI-K including device driver routines and graphics primitives for the grphic board "K" was designed, implemented in the Design Automation Laboratory of KAIST and installed on IBM PC/AT, using assembly and C language supported by TMS 34010 grphics processor. Several algorithms generating the graphics primitives such as box, circle, pie chord are proposed. The drawing speed of CGI-K on the graphic board K was found out to be three to ten times faster than that of the EGA for several examples. A 2-D graphics editor called GRIM (graphics input and modification) and a 3-dimensional graphics renderer called IPCHE which can draw 3-D objects were developed as two major application programs running on CGI-K. The graphics primitives supported in GRIM include polygon, box, circle, and ace. The IPCHE receives a 3-D objects data file and displays the 3-D object on the screen with hidden surface removal, shading, and perspective scaling.

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Study on the Remote Controllability of Vision Based Unmanned Vehicle Using Virtual Unmanned Vehicle Driving Simulator (가상 무인 차량 시뮬레이터를 이용한 영상 기반 무인 차량의 원격 조종성 연구)

  • Kim, Sunwoo;Han, Jong-Boo;Kim, Sung-Soo
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.40 no.5
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    • pp.525-530
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    • 2016
  • In this paper, we proposed an image shaking index to evaluate the remote controllability of vision based unmanned vehicles. To analyze the usefulness of the proposed image-shaking index, we perform subjective tests using a virtual unmanned vehicle driving simulator. The developed driving simulator consists of a real-time multibody dynamic software of the unmanned vehicle, a motion simulator, and a driver console. We perform dynamic simulations to obtain the motion of the unmanned vehicle running on the various road surfaces such as ISO roughness level A~E roads. The motion of the vehicle body is reflected in the motion simulator. Then, to enable remote control operation, we offer to operators the image data that was measured using the camera sensor on the simulator. We verify the usefulness of the proposed image-shaking index compared with subjective index provided by operators.

Large Eddy Simulation of Flow around a Bluff Body of Vehicle Shape

  • Jang, Dong-Sik;Lee, Yeon-Won;Doh, Deug-Hee;Toshio Kobayashi;Kang, Chang-Soo
    • Journal of Mechanical Science and Technology
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    • v.15 no.12
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    • pp.1835-1844
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    • 2001
  • The turbulent flow with wake, reattachment and recirculation is a very important problem that is related to vehicle dynamics and aerodynamics. The Smagorinsky Model (SM), the Dynamics Subgrid Scale Model (DSM), and the Lagrangian Dynamic Subgrid Scale Model (LDSM) are used to predict the three-dimensional flow field around a bluff body model. The Reynolds number used is 45,000 based on the bulk velocity and the height of the bluff body. The fully developed turbulent flow, which is generated by the driver part, is used for the inlet boundary condition. The Convective boundary condition is imposed on the outlet boundary condition, and the Spalding wall function is used for the wall boundary condition. We compare the results of each model with the results of the PIV measurement. First of all, the LES predicts flow behavior better than the k-$\xi$ turbulence model. When ew compare various LES models, the DSM and the LDSM agree with the PIV experimental data better than the SM in the complex flow, with the separation and the reattachment at the upper front part of th bluff body. But in the rear part of the bluff body, the SM agrees with the PIV experimental results better than them. In this case, the SM predicts overall flow behavior better than the DSM nd the LDSM.

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Distribution and Determinants of Out-of-pocket Healthcare Expenditures in Bangladesh

  • Mahumud, Rashidul Alam;Sarker, Abdur Razzaque;Sultana, Marufa;Islam, Ziaul;Khan, Jahangir;Morton, Alec
    • Journal of Preventive Medicine and Public Health
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    • v.50 no.2
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    • pp.91-99
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    • 2017
  • Objectives: As in many low-income and middle-income countries, out-of-pocket (OOP) payments by patients or their families are a key healthcare financing mechanism in Bangladesh that leads to economic burdens for households. The objective of this study was to identify whether and to what extent socioeconomic, demographic, and behavioral factors of the population had an impact on OOP expenditures in Bangladesh. Methods: A total of 12 400 patients who had paid to receive any type of healthcare services within the previous 30 days were analyzed from the Bangladesh Household Income and Expenditure Survey data, 2010. We employed regression analysis for identify factors influencing OOP health expenditures using the ordinary least square method. Results: The mean total OOP healthcare expenditures was US dollar (USD) 27.66; while, the cost of medicines (USD 16.98) was the highest cost driver (61% of total OOP healthcare expenditure). In addition, this study identified age, sex, marital status, place of residence, and family wealth as significant factors associated with higher OOP healthcare expenditures. In contrary, unemployment and not receiving financial social benefits were inversely associated with OOP expenditures. Conclusions: The findings of this study can help decision-makers by clarifying the determinants of OOP, discussing the mechanisms driving these determinants, and there by underscoring the need to develop policy options for building stronger financial protection mechanisms. The government should consider devoting more resources to providing free or subsidized care. In parallel with government action, the development of other prudential and sustainable risk-pooling mechanisms may help attract enthusiastic subscribers to community-based health insurance schemes.

Driving Pattern Recognition System Using Smartphone sensor stream (스마트폰 센서스트림을 이용한 운전 패턴 인식 시스템)

  • Song, Chung-Won;Nam, Kwang-Woo;Lee, Chang-Woo
    • Journal of Korea Society of Industrial Information Systems
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    • v.17 no.3
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    • pp.35-42
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    • 2012
  • The database for driving patterns can be utilized in various system such as automatic driving system, driver safety system, and it can be helpful to monitor driving style. Therefore, we propose a driving pattern recognition system in which the sensor streams from a smartphone are recorded and used for recognizing driving events. In this paper we focus on the driving pattern recognition that is an essential and preliminary step of driving style recognition. We divide input sensor streams into 7 driving patterns such as, Left-turn(L), U-turn(U), Right-turn(R), Rapid-Braking(RB), Quick-Start(QS), Rapid-Acceleration (RA), Speed-Bump(SB). To classify driving patterns, first, a preprocessing step for data smoothing is followed by an event detection step. Last the detected events are classified by DTW(Dynamic Time Warping) algorithm. For assisting drivers we provide the classified pattern with the corresponding video stream which is recorded with its sensor stream. The proposed system will play an essential role in the safety driving system or driving monitoring system.

A Study on Eye Point and Field of View of Older Drivers (고령운전자의 Eye Point와 전방 시계 특성에 관한 연구)

  • Lee, Seong-Il;Choi, Ji-Ho;Hwang, In-Jun;Song, Kyo-Hyun
    • Journal of the Ergonomics Society of Korea
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    • v.29 no.1
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    • pp.67-71
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    • 2010
  • This study examined the field of view of older drivers based on their eye points. The subjects were 25 people whose age was over 65 years and 10 contrasting subjects on their 20s. For the experiment, we expanded the width of the A-pillar of a test vehicle. With a measuring apparatus designed for the study, we analyzed 3 axes of coordinates from glabella to a fixed point of the vehicle that would be used as CAD data of vehicle design. Result shows that average eye point of the older subjects was located significantly farther from the seat than that of the 20s approximately by 31.62mm(p=0.05). It was also found that the Binocular FOV was not significantly different between the older subjects and the 20s(p=0.85), and the effect of the width of the A-pillar on the FOV could not be found. We also measured the left and right side of the Ambinocular FOV of the older subjects. It was found that the older subjects had much wider visual angle than the 20s by 2.84 degree (F=4.78, p=0.01) on the left side, while the 20s showed significantly wider average angle than the older subjects by about 4.88 degree (F=4.78, p<0.05) on the right side. The results of this study can be used to improve the FOV based on the optimal eye points when designing a vehicle for older drivers.

Construction and Comparison of Sound Quality Index for the Vehicle HVAC System Using Regression Model and Neural Network Model (회귀모형과 신경망모형을 이용한 차량공조시스템의 음질 인덱스 구축 및 비교)

  • Park, Sang-Gil;Lee, Hae-Jin;Sim, Hyun-Jin;Lee, You-Yub;Oh, Jae-Eung
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.16 no.9 s.114
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    • pp.897-903
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    • 2006
  • The reduction of the vehicle interior noise has been the main interest of noise and vibration harshness (NVH) engineers. The driver's perception on the vehicle noise is affected largely by psychoacoustic characteristic of the noise as well as the SPL. In particular, the heating, ventilation and air conditioning (HVAC) system sound among the vehicle interior noise has been reflected sensitively in psychoacoustics view point. Even though the HVAC noise is not louder than overall noise level, it clearly affects subjective perception to drivers in the way of making to be nervous or annoyed. Therefore, these days a vehicle engineer takes aim at developing sound quality as well as reduction of noise. In this paper, we acquired noises in the HVAC from many vehicles. Through the objective and subjective sound quality (SQ) evaluation with acquiring noises recorded by the vehicle HVAC system, the simple and multiple regression models were obtained for the subjective evaluation 'Pleasant' using the semantic differential method (SDM). The regression procedure also allows you to produce diagnostic statistics to evaluate the regression estimates including appropriation and accuracy. Furthermore, the neural network (NN) model were obtained using three inputs(loudness, sharpness and roughness) of the SQ metrics and one output(subjective 'Pleasant'). Because human's perception is very complex and hard to estimate their pattern, we used NN model. The estimated models were compared with correlations between output indexes of SQ and hearing test results for verification data 'Pleasant'. As a result of application of the SQ indexes, the NN model was shown with the largest correlation of SQ indexes and we found possibilities to predict the SQ metrics.

A Development of The Road Surface Decision Algorithm Using SVM(Support Vector Machine) Clustering Methods (SVM(Support Vector Machine) 기법을 활용한 노면상태 판별 알고리즘 개발)

  • Kim, Jong Hoon;Won, Jae Moo
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.12 no.5
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    • pp.1-12
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    • 2013
  • Road's accidents caused by Ice, snow, Wet of roads surface conditions and weather conditions situations that are constantly occurring. That is, driver's negligence and safe driving ability of individuals due to lack of awareness, and Road management main agent(the government and the public, etc.) due to road conditions, if there is insufficient information. So Related research needs is a trend that is required. In this study, gather Camera(Stereo camera)'s image data, and analysis polarization coefficients and wavelet transform. And unlike traditional single-dimensional classification algorithms as multi-dimensional analysis by using SVM classification techniques, develop an algorithm to determine road conditions. Four on the road conditions (dry, wet, snow, ice) recognition success rate for the detection and analysis of experiments.