• Journal of the Korean Society for Nondestructive Testing
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• v.35 no.4
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• pp.245-250
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• 2015

To verify the possibility of generating rattling noise from a motor on caliper brake system, a test was conducted using a caliper excited with vibrations similar to that in a vehicle running on actual roads; this test was conducted using a quiet shaker installed in an anechoic room. After several hours of external excitation, the test assembly was loosened, and the frequency of rattling noise generation increased. A microphone was used to record the generated noise. The measured signals were analyzed by conventional spectrum analysis. Since the noise is generated as an impact response, the advantages of employing Prony analysis was discussed, and the results were compared to those obtained using conventional fast Fourier transforms. The accuracy of Prony analysis was through endurance tests on different brake systems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.12
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• pp.2272-2293
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• 2011

Communication technology of future networks is predicted to provide a large variety of services including WiFi service in vehicular network. In this paper, we assume that vehicles are embedded with WiMAX antenna and in-vehicle terminals receive WiMAX traffic through WiFi interface. This assumption will impose severe performance degradation due to interference among mobile BSSs when WiFi access points (APs) are densely located. Existing interference avoidance techniques cannot properly resolve the above problems and do not cope with dynamically moving vehicular scenario since they focus only on the fixed network topology. In this paper, we propose a mobility-aware interference avoidance scheme for WiFi services. The proposed scheme computes the interference duration by exploiting mobility vector and location information of neighboring APs. If the interference duration is not negligible, our scheme searches for another channel in order to avoid interference. However, if the interference duration is negligible, our scheme continues to use the channel to reduce switching overhead. To measure the effectiveness of the proposed scheme against other existing techniques, we evaluated performance by using OPNET simulator. Through the simulation, we obtained about 60% reduction in the maximum interference frequency and about 67% improvement in throughput. Furthermore, our scheme provides fair channel usage.

• International Journal of Highway Engineering
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• v.17 no.5
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• pp.19-24
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• 2015

PURPOSES : The noise, which is typically generated by fast moving vehicles, can be intercepted by installing a noise barrier with a soundproof panel. However, reflections from the panels cause secondary noise, and hence lower the effectiveness of the panels. In this study, the reduction of reflection noise by considering the shape, especially zigzag one, of the soundproof panel have been evaluated. METHODS : The simulation model used in this study was Nord2000, which simulates real-road situations effectively. Based on the simulation results, the joining angle of $133^{\circ}$ with the pattern width (a) equal to 2 m and the projection height (b) equal to 0.5 m was adapted in the zigzag shape as the best profit designing factors. RESULTS: The measuring results at middle height, 15 m showed reduction at all points except the point with average -1.6 dB. At a greater height of 30 m, 2 points showed reduction. A real-sized facility was constructed to investigate the reflected sound from a zigzag shaped panel up to the height of 5 m. CONCLUSIONS: The reduction effects were detected in all the receive points in the range of 2-6 m distances and 1-5 m heights comparing the plane panel. Compared to plane panel, the noises are reduced at an average of 2.4 dBA.

• Journal of Internet Computing and Services
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• v.9 no.4
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• pp.115-131
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• 2008

Small mobile devices have become commonplace in our everyday life, from cellular phones to PDAs. Discovering dense regions for the mobile devices is one of the problems of grate practical importance. It can be used in monitoring movement of vehicles, concentration of troops, etc. In this paper, we propose a novel algorithm on continuously clustering a large set of mobile objects. We assume that a mobile object reports its position only if it is too far away from the expected position and thus the location data received may be imprecise. To compute the location of each individual object could be costly especially when the number of objects is large. To reduce the complexity of the computation, we want to first cluster objects that are in proximity into a group and treat the members in a group indistinguishable. Each individual object will be examined only when the inaccuracy causes ambiguity in the final results. We conduct extensive experiments on various data sets and analyze the sensitivity and scalability of our algorithms.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.3
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• pp.67-74
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• 2011

In recent years, with increasing utilization of mobile devices such as smartphones, the need for PNS(Pedestrian Navigation Systems) that provide guidance for moving pedestrians is increasing. For the navigation services, road network is the most important component when it comes to creating route and guidance information. In particular, pedestrian network requires modeling methods for more detailed and vast space compared to road network. Therefore, more efficient method is needed to establish pedestrian network that was constructed by existing field survey and manual editing process. This research proposed a pedestrian network creation method appropriate for pedestrians, based on CNS(Car Navigation Systems) data that already has been broadly constructed. Pedestrian network was classified into pedestrian link(sidewalk, side street, walking facility) and openspace link depending on characteristics of walking space, and constructed by applying different methodologies in order to create path that similar to the movements of actual pedestrians. The proposed algorithm is expected to become an alternative for reducing the time and cost of pedestrian network creation.

• Journal of the Korean Institute of Telematics and Electronics T
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• v.35T no.1
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• pp.67-74
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• 1998

The primary cause of air pollution by vehicles is imperfect combustion of fuel. One of the most usual causes of this imperfect combustion is the misfire in IC engins. The U.S. EPA(Environment Protection Agency) and the CARB(California air Resources Board) have imposed regulations for the detection of misfiring in automotive engines. The OBD-II regulations require that misfire should be monitored by the engine diagnostic system, and that the goal of OBD-II is to alert the driver to the presence of a malfunction of the emission control system. Several solutions to the misfire detection problem have been proposed for the detection of misfires. However, the performance of these methods in the presence of misfire is not altogether clear. This paper presents a precise method and system for internal combustion engine misfire. Present invention based upon measurements of engine roughness as derived from crankshaft angular velocity measurements with special signal processing method. Crankshaft angular velocity signals are processed by WDPT, so that the more reliable misfire detection than the time domain analysis. Experimental work confirms that it is possible to apply the WDFT for the detection of misfires in no-load idle and road testing.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.5
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• pp.25-34
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• 2008

By comparing two images, which are captured with the same scene at different time, we can detect a set of outliers, such as occluding objects due to moving vehicles. To reduce the influence from the different intensity properties of the images, an intensity compensation scheme, which is based on the polynomial regression model, is employed. For an accurate detection of outliers alleviating the influence from a set of outliers, a simple technique that reruns the regression is employed. In this paper, an algorithm that iteratively reruns the regression is theoretically analyzed by observing the convergence property of the estimates of the noise variance. Using a correction constant for the estimate of the noise variance is proposed. The correction enables the detection algorithm robust to the choice of thresholds for selecting outliers. Numerical analysis using both synthetic and Teal images are also shown in this paper to show the robust performance of the detection algorithm.

• Journal of the Korean Society for Railway
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• v.20 no.4
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• pp.440-447
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• 2017

Spectrum level for the acoustic roughness of wheels and rail surface should be periodically maintained under the limitation of ISO to reduce rolling noise of railway vehicles. Thus, in maintaining railway track, displacement sensor-based measuring devices are broadly used to measure the surface roughness and to perform spectral analysis. However, these measuring devices cause unexpected measuring errors since the displacement sensors are fixed at moving platforms and the main frame produces pitching motion during measurement. To increase the accuracy of the measured values, this paper has investigated the effects of design variables such as wheel base, additional wheels, and elastic deformation of wheels on the surface roughness and acoustic roughness spectrum.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.8
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• pp.544-554
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• 2014

In this paper, we introduce a cyber-physical intersection systems (CPIS) which intimately interconnects roadside units (RSU) located at intersection, on-board units (OBU) of moving vehicles, and smartphone apps. Based on the architecture of CPIS, we also present a green light optimal speed advisory based on the reference mobility models (GLOSA-RMM) to reduce intersection stopping time (IST) and fuel consumption. Based on several reference mobility models, the GLOSA-RMM determines the appropriate speed advisory by taking into account the current mobility and the intersection traffic light status, and then provides screen/voice GLOSA instructions to minimize the driver's distraction. We show that the GLOSA-RMM can reduce both the IST and the fuel consumption through the numerical results obtained from the prototype of the CPIS consisting of the OBU, the RSU and the smartphone app.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.4
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• pp.641-647
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• 2018

Recently, CCTV, which provides video information for multiple purposes, has been transformed into an intelligent, and the range of automation applications increased using the computer vision. A highly reliable detection method must be performed for accurate recognition of pedestrians and vehicles and various methods are being studied for this purpose. In such an object detection system. In this paper, we propose a method to detect a large number of pedestrians by acquiring three characteristic information that features of color information using HSI, motion vector information and shaping information using HOG feature information of a pedestrian in a situation where a large number of pedestrians are moving. The proposed method distinguishes each pedestrian while minimizing the failure or confusion of pedestrian detection and tracking. Also when pedestrians approach or overlap, pedestrians are identified and detected using stored frame feature data.