• Smart Structures and Systems
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• v.30 no.6
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• pp.661-671
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• 2022

Stayed cables are the key components for transmitting loads in cable-stayed bridges. Therefore, it is very important to evaluate the cable force condition to ensure bridge safety. An online condition assessment and anomaly localization method is proposed for cables based on the spatiotemporal correlation of grouped cable forces. First, an anomaly sensitive feature index is obtained based on the distribution characteristics of grouped cable forces. Second, an adaptive anomaly detection method based on the k-nearest neighbor rule is used to perform dissimilarity measurements on the extracted feature index, and such a method can effectively remove the interference of environment factors and vehicle loads on online condition assessment of the grouped cable forces. Furthermore, an online anomaly isolation and localization method for stay cables is established, and the complete decomposition contributions method is used to decompose the feature matrix of the grouped cable forces and build an anomaly isolation index. Finally, case studies were carried out to validate the proposed method using an in-service cable-stayed bridge equipped with a structural health monitoring system. The results show that the proposed approach is sensitive to the abnormal distribution of grouped cable forces and is robust to the influence of interference factors. In addition, the proposed approach can also localize the cables with abnormal cable forces online, which can be successfully applied to the field monitoring of cables for cable-stayed bridges.

• Journal of Advanced Navigation Technology
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• v.6 no.3
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• pp.223-230
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• 2002

In this paper, we induced that the noise powers and bit error rate of direct detection receiver taking account of ISI (intersymbol interference) in the 2,000 km optical transmission system. And we evaluated the sensitivity in the vrious bit rate system. We verified that the proposed calculation method is applicable to the exact optical system. And we confirmed that the signal distortion due to both chromatic dispersion and nonlinear effects compensated by using of MSSI (Mid-Span Spectral Inversion) method, and yet the sensitivity of a higher bit rate system is reduced, because of the increase of ISI and then the decrease of the average receiving power, compared with a the lower bit rate system.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.4
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• pp.1-10
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• 2013

This study was conducted to investigate that bus information was used as an information of travel speed. To determine the travel speed on the road, bus information and the information collected from the point detector and the interval detection installed were compared. If bus information has the function of traffic information detector, can provide the travel speed information to road users. To this end, the model of recognizing the traffic patterns is necessary. This study used simple moving-average method, simple exponential smoothing method, Double moving average method, Double exponential smoothing method, ARIMA(Autoregressive integrated moving average model) as the existing methods rather than new approach methods. This study suggested the possibility to replace bus information system into other information collection system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.8
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• pp.1825-1830
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• 2015

In some cases, despite the pedestrian jaywalking pedestrian traffic lights to red, or even wait for the walk signal to stand down in the driveway. If this is the case may be liable to lead to a traffic accident. Thus, using an infrared sensor wateuna adopted the approach that the warning announcement when a pedestrian enters the driveway, curved pedestrian crossing the intersection in this case, it is difficult to install. In this paper, we propose a Fitness referral system utilizes a built-in sensor of the Android mobile devices. For this purpose, the sensor is a proximity sensor using an acceleration sensor. The proximity sensor has a number of disadvantages compared to the high precision battery power, the acceleration sensor accuracy, fast response time, on the other hand, the disadvantage is the lower. Close to reduce battery consumption of the sensor, BMI of the user sensor control mechanism and increase the accuracy of the acceleration sensor (Body Mass Index) obtained after the index was applied to the recommendation algorithm, which like the movement mechanism.

• Journal of KIISE:Information Networking
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• v.28 no.4
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• pp.517-526
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• 2001

In order to reduce the increasing packet loss rates caused by an exponential increase in network traffic, the IETF(Internet Engineering Task Force) is considering the deployment of active queue management techniques such as RED(Random Early Detection). While active queue management in routers and gateways can potentially reduce total packet loss rates in the Internet, this paper has demonstrated the inherent weakness of current techniques and shows that they are ineffective in preventing high loss rates. The inherent problem with these queue management algorithms is that they all use queue lengths as the indicator of the severity of congestion. In this paper, in order to solve this problem, a new active queue management algorithm called MRED(Modified Random Early Detection) is proposed. MRED computes the packet drop probability based on our heuristic method rather than the simple method used in RED. Using simulation, MRED is shown to perform better than existing queue management schemes. To analyze the performance, we also measure throughput of traffics under the FIFO control, and compared the performance with that of this MRED system.

• Journal of the Korea Convergence Society
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• v.9 no.6
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• pp.33-38
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• 2018

In this study, we try to detect new attacks for vehicle by learning only one class. We use Car-Hacking dataset, an intrusion detection dataset, which is used to evaluate classification performance. The dataset are created by logging CAN (Controller Area Network) traffic through OBD-II port from a real vehicle. The dataset have four attack types. One class classification is one of unsupervised learning methods that classifies attack class by learning only normal class. When using unsupervised learning, it difficult to achieve high efficiency because it does not use negative instances for learning. However, unsupervised learning has the advantage for classifying unlabeled data, which are new attacks. In this study, we use one class classifier to detect new attacks that are difficult to detect using signature-based rules on network intrusion detection system. The proposed method suggests a combination of parameters that detect all new attacks and show efficient classification performance for normal dataset.

• Journal of Satellite, Information and Communications
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• v.6 no.2
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• pp.72-77
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• 2011

Spectrum sensing is a critical functionality of CR network; it allow secondary user to detect spectral holes and to opportunistically use under-utilized frequency bands without causing harmful interference to primary use. Recently, wideband service has been increase for processing abundance of data traffic. So CR network needs a realizable implementation design of spectrum sensing for wideband. To get high resolution performance of wideband sensing must precede algorithm processing for reliability signal detection. By the way, the performance of spectrum sensing can be degraded due to fading and shadowing. In order to overcome this problem, we propose system model of wideband sensing scheme on energy detected collaborative technique. we divide wideband into narrowbands and use narrowbands to detect signal excepting some narrowbands including bad channel through the CSI. And we simulate and analyze in terms of detection probability with various SNR.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.816-819
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• 2011

The image recognition system using CCTV camera has been introduced to minimize not only loss of life and property but also traffic jam in the tunnel. In this paper, multi-object detection algorithm is proposed to track multi vehicles. The proposed algorithm is to detect multi cars based on Adaboost and to track multi vehicles to use template matching. As results of simulations, it is shown that proposed algorithm is useful for tracking multi vehicles.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.29 no.4
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• pp.37-44
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• 2021

In case of South Korea, the airspace which airlines can operate is extremely limited due to the military operational area located within the Incheon flight information region. As a result, safety problems such as mid-air collision between aircraft or Traffic alert and Collision Avoidance System Resolution Advisory (TCAS RA) may occur with higher probability than in wider airspace. In order to prevent such safety problems, an mid-air collision risk detection model based on Detect-And-Avoid (DAA) well clear metrics is investigated. The model calculates the risk of mid-air collision between aircraft using aircraft trajectory data. In this paper, the practical use of DAA well clear metrics based model has been validated. Aviation safety data such as aviation safety mandatory report and Automatic Dependent Surveillance Broadcast is used to measure the performance of the model. The attributes of individual aircraft track data is analyzed to correct the threshold of each parameter of the model.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3D
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• pp.349-352
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• 2006

To cope with traffic congestion, traffic accidents and lack of parking facilities, caused by dramatic increase in total vehicle number, vigorous researches on managing vehicles efficiently are done, both domestically and internationally. The vehicle license plate recognition makes effective management of traffic possible, with its wide application in many fields, covering from speed enforcement, collecting toll, stolen vehicle detection to parking management. The vehicle license plate recognition system causes high cost for collecting training data. Many researches are done by using the virtual sample method, which can be effective for utilizing limited number of training data by generating virtual sample. This paper investigates techniques to improve the performance of vehicle license plate recognition by using the training data's annexation. Also, popular methods for virtual sample creation used for text recognition algorithm are analyzed and their effectiveness is verified.