• Transactions of the Korean Society of Automotive Engineers
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• v.23 no.6
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• pp.615-622
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• 2015

Recently Digital-TachoGraph(DTG) was mounted mandatorily in commercial vehicles(Taxi, Bus, etc.). DTG records accurate and detailed information of the running state of vehicles related to traffic accident, such as Time, Distance, Velocity, RPM, Brake ON/OFF, GPS, Azimuth, Acceleration. Thus those standardized data can play an important role in traffic accident investigation and reconstruction. To develope the accurate and objective method using the DTG data for the reconstruction of traffic accident, we had conducted several tests such as driving test, high speed circuit test, braking test, slalom test at Korea Automobile Testing & Research Institute(KATRI), and collision test at Korea Automobile insurance repair Research and Training center(KART) with the vehicle equipped with several DTG. Development of the program which enables the reading and analysis of the DTG data was followed. In the experiments, we have found velocity error, RPM error, brake signal error and azimuth error in several products, and also non-continuous event data. The cause of these errors was deduced to be related to the correction factor, the durability of electronic parts and the algorithm.

• Journal of Auto-vehicle Safety Association
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• v.13 no.4
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• pp.66-72
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• 2021

This study was initiated to improve of the defect investigation method using event data recorders (EDR) and suggested a solution through the regulation and system analysis of EDR. The EDR data has been used for various purposes such as the vehicle defect investigation and the traffic accident investigation. However the EDR regulation has not been updated since the implementation in 2012. "Trigger Threshold" can be used to analyze a single accident such as the frontal crash, the side crash, and the rollover. In the case of a complex accident in which a rollover accident and a crash accident occur simultaneously, it is difficult to analyze a complex accident due to current "Trigger Threshold". This study proposed the method of separating the "Trigger Threshold" into a crash accident and a rollover accident so that accidents can be analyzed using the EDR data even when a complex accident occurs. In addition, it proposed the improvement method to quickly use the data of EDR in accident reconstruction software.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.12A
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• pp.1188-1197
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• 2010

A most important thing in a connected dominating set(CDS)-based routing in a wireless ad-hoc network is to select a minimum number of dominating nodes and then build a backbone network which is made of them. Node failure in a CDS is an event of non-negligible probability. For applications where fault tolerance is critical, a traditional dominating-set based routing may not be a desirable form of clustering. It is necessary to minimize the frequency of reconstruction of a CDS to reduce message overhead due to message flooding. The idea is that by finding alternative nodes within a restricted range and locally reconstructing a CDS to include them, instead of totally reconstructing a new CDS. With the proposed algorithm, the resulting number of dominating nodes after partial reconstruction of CDS is not changed and also its execution time is faster than well-known algorithm of construction of CDS by 20~40%. In the case of high mobility situation, the proposed algorithm gives better results for the performance metrics, packet receive ratio and energy consumption.

• Journal of Auto-vehicle Safety Association
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• v.12 no.3
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• pp.52-60
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• 2020

Usage of EDR(Event Data Recorder) report for traffic accident analysis is currently increasing due to government regulation of EDR data release. Nevertheless, a lot of investigators simply adopt by comparing the number of ignition cycles(crash) at event to the number of ignition cycles(download) without an exact judgment whether event data occurred by this accident or not. In the EDR report, besides ignition cycles, there are many factors such as event record type, algorithm active(rear/rollover/side/frontal), time between events, event severity status(rollover/rear/right side/reft side/frontal), belt switch circuit status, driver/passenger pretensioner/air-bag deployment, PDOF(Principal Direction of Force) by ΔV to be able to decide whether or not to adopt. also the event data is considered enough to vehicle damaged state, accident situation at the scene of the accident. and there is described in "all data should be examined in conjunction with other available physical evidence from the vehicle and scene" in the CDR(Crash Data Retrieval) report. Therefore many investigators have to decide whether or not to adopt after they consider sufficiently to above factors when they are the traffic accident analysis and investigate the causes of a accident on the adopted event data. In this paper, we report to traffic accident investigators notable points and analysis methods on the basis of thousands of cases and the results of one's own experiment in NFS(National Forensic Service).

• Nuclear Engineering and Technology
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• v.54 no.5
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• pp.1747-1753
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• 2022

Compton imaging is the main method for locating radioactive hot spots emitting high-energy gamma-ray photons. In particular, this imaging method is crucial when the photon energy is too high for coded-mask aperture imaging methods to be effective or when a large field of view is required. Reconstruction of the photon source requires advanced Compton event processing algorithms to determine the exact position of the source. In this study, we introduce a novel method based on a Deep Learning algorithm with a Convolutional Neural Network (CNN) to perform Compton imaging. This algorithm is trained on simulated data and tested on real data acquired with Caliste, a single planar CdTe pixelated detector. We show that performance in terms of source location accuracy is equivalent to state-of-the-art algorithms, while computation time is significantly reduced and sensitivity is improved by a factor of ~5 in the Caliste configuration.

• Nuclear Engineering and Technology
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• v.56 no.7
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• pp.2799-2805
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• 2024

Energy-resolved neutron imaging is an effective way to investigate the internal structure and residual stress of materials. Different sample sizes have varying requirements for the detector's imaging field of view (FOV) and spatial resolution. Therefore, a dual-mode energy-resolved neutron imaging detector was developed, which mainly consisted of a neutron scintillator screen, a mirror, imaging lenses, and a time-stamping optical fast camera. This detector could operate in a large FOV mode or a high spatial resolution mode. To evaluate the performance of the detector, the neutron wavelength spectra and the multiple spatial resolution tests were conducted at CSNS. The results demonstrated that the detector accurately measured the neutron wavelength spectra selected by a bandwidth chopper. The best spatial resolution was about 20 ㎛ in high spatial resolution mode after event reconstruction, and a FOV of 45.0 mm × 45.0 mm was obtained in large FOV mode. The feasibility was validated to change the spatial resolution and FOV by replacing the scintillator screen and adjusting the lens magnification.