• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.5
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• pp.253-263
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• 2021

Traffic data collected using advanced equipment are highly valuable for traffic planning and efficient road operation. However, there is a problem regarding the reliability of the analysis results due to equipment defects, errors in the data aggregation process, and missing data. Unlike other detectors installed for each vehicle lane, radar detectors can yield different error types because they detect all traffic volume in multilane two-way roads via a single installation external to the roadway. For the traffic data of a radar detector to be representative of reliable data, the error factors of the radar detector must be analyzed. This study presents a field survey of variables that may cause errors in traffic volume collection by targeting the points where radar detectors are installed. Video traffic data are used to determine the errors in traffic measured by a radar detector. This study establishes three types of radar detector traffic errors, i.e., artificial, mechanical, and complex errors. Among these types, it is difficult to determine the cause of the errors due to several complex factors. To solve this problem, this study developed a radar detector traffic volume error analysis model using a multiple linear regression model. The results indicate that the characteristics of the detector, road facilities, geometry, and other traffic environment factors affect errors in traffic volume detection.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.5
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• pp.11-20
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• 2014

Due to the importance of vehicle detector which plays an essential role in generating real-life traffic information, maintaining detector data quality is preeminent in advanced traffic management and information systems (ATMIS). To this end, agencies periodically conduct performance tests on detectors. Detector evaluation is generally performed by comparing baseline data with corresponding detector data. Here, two important things need to be addressed; one is errors (or uncertainties) included in baseline data and the other is the confidence interval concept to represent evaluation results of sample data to corresponding ones of population. To resolve these problems, a new detector evaluation scheme is introduced and the scheme is applied to individual level detector evaluations of loop, video image, and radar detectors. The purpose of individual level evaluation is to eliminate the balancing (or cancelling-out) effects of over- and under-counts. As a consequence, the proposed scheme is proven to be effectively applied to real-world detector evaluations.

• Nuclear Engineering and Technology
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• v.56 no.5
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• pp.1733-1737
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• 2024

In order to specify the location of the scintillation pixel that interacted with gamma rays in the positron emission tomography (PET) detector, conventionally, after acquiring a flood image, the location of interaction between the scintillation pixel and gamma ray could be specified through a pixel-segmentation process. In this study, the experimentally acquired signal was specified as the location of the scintillation pixel directly, without any conversion process, through the simulation data and the deep learning algorithm. To evaluate the accuracy of the specification of the scintillation pixel location through deep learning, a comparative analysis with experimental data through pixel segmentation was performed. In the same way as in the experiment, a detector was configured on the simulation, a model was built using the acquired data through deep learning, and the location was specified by applying the experimental data to the built model. Accuracy was calculated through comparative analysis between the specified location and the location obtained through the segmentation process. As a result, it showed excellent accuracy of about 85 %. When this method is applied to a PET detector, the position of the scintillation pixel of the detector can be specified simply and conveniently, without additional work.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2956-2958
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• 2000

This paper describes the design of a real time traffic data acquisition system using loop detector and piezzo sensor. Loop detector is the cheapest method to measure the speed and piezzo is used to detect the vehicle axle information. A ISA slot based I/O board is designed for data acquisition and PC process the raw traffic data and transfer the data to the host system. Simulation kit is designed with toy car kits. simulated loop detector and piezzo sensor. The data acquisition system collects up to 10 lane highway traffic data such as vehicle count. speed. length axle count. distance between the axles. The data is processed to generate traffic count, vehicle classification, which are to be used for ITS. The system architecture and simulation data is included and the system will be tested for field operation.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.612-615
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• 2003

In this paper, a design of radiation detector for gamma column scanner is introduced. Distillation column is important unit in Petro-chemical industries, and its on-line diagnose is very important. To get density profile measured by the radiation transmitted through column is well method for on-line diagnose as gamma scanning. For this purpose radiation detection circuit, radiation source and mechanical system for moving source and detector are required. Conventional radiation detection circuit for this application is sensitive to electric noise because of interface between the radiation circuit and the controller for mechanical system. The radiation detection system introduced here is using loop coil instead of slip ring to remove contact noise. Radiation detection system designed here for gamma scanning consist of BGO detector, high voltage circuit, PHA circuit and FSK modem. The BGO detector is used as radiation sensor, high voltage circuit and peak height analysis circuit is essential to process the signal generated from BGO detector. Micro controller convert measured data into ASCII data. FSK modem transmit ASCII data. Transmitted ASCH data is picked up in antenna coil and processed for combined function with mechanical system. This method gives good result by isolating the controlling circuit of mechanical system from radiation detecting circuit which is sensitive to noise.

• Journal of the Korean Data and Information Science Society
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• v.16 no.2
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• pp.289-300
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• 2005

In this article quick variance change point (VCP) detection problem for time series is considered. For this variance VCP detector equipped with tuning parameters is proposed. A major tool for the detector is moving variance ratio (MVR) which monitors variance change of a given time series. Tuning process of detector is investigated via simulation, which shows that tuning parameters are critical in achieving sensitivity and adaptiveness of detector.

• Journal of the Korean Institute of Telematics and Electronics
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• v.23 no.1
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• pp.101-113
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• 1986

In this paper, a real-time pitch detector LPC vocoder as implemented on a high speed digital signal processor, NEC 7720, is described. The pitch detector was based mainly on the SIFT algorithm. The SIFT pitch detector consists primarily of a digital low pass filter, inverse filter, computation of autocorrelation, a peak picker, interpolation, V/UV defcision and a final pitch smoother. In our approach, modification, mainly on the V/UV decision and a final pitch smoother, was made to estimate more accurate pitches. An 16-bit fixed-point aithmatic was employed for all necessary computation and the simulated results were compared with the eye detected pitches obtained from real speech data. The pitch detector occupies 98.8% of the instruction ROM, 37% of the data ROM, and 94% of internal RAM and takes 15.2ms to estimate a pitch when an analysis frame is consisted of 128 sampled speech data. It is observed that the tested results were well agreed with the computer simulation results.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.5
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• pp.22-35
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• 2013

With the increase in image detectors, concerns about the reliability of traffic information are increasing. In this paper, we propose a method to generate reliable traffic volume using analysis of the point detector data as a representative value. Therefore, targeting expressway, we analyzed the difference in traffic volume collected by loop and image detector, and verified statistically using t-test, and finally analyzed the error rate compare to the real traffic volume. Analysis revealed that there was a statistically difference the traffic date collected by the loop detector and the image detector, in the same period, the same time, respectively. In addition, the difference between the actual traffic volume and traffic that have been collected in a loop detector was the lowest Therefore, creating a traffic volume of representative value, we proposed a method to use loop detector than the average traffic volume collected by each detector. It shows that it is more important to use one high-quality data rather than various low-quality data to produce a representative value.

• Journal of the Korean Data and Information Science Society
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• v.16 no.2
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• pp.173-183
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• 2005

This paper studies quick detection of variance change point for iid data. For development of sensitive and adaptive variance change point detector, moving variance ratio is employed as a variance ratio estimator. It is shown that selection of tuning parameters of detector, (i.e., information and lag tuning parameters) is critical for detector to achieve desirable sensitivity and adaptiveness. Interestingly our simulation result reveals limitations of the commonly used change ratio against the previous day. Our results will provide useful insight when the detector is applied to time series data.

• Communications for Statistical Applications and Methods
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• v.19 no.4
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• pp.579-590
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• 2012

Local linear jump detection in a discontinuous regression function involves the choice of the bandwidth and the performance of a local linear jump detector depends heavily on the choice of the bandwidth. However, little attention has been paid to this important issue. In this paper we propose two fully data adaptive bandwidth selection methods for a local linear jump detector. The performance of the proposed methods are investigated through a simulation study.