• Journal of Information Processing Systems
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• v.4 no.2
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• pp.41-52
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• 2008

In this paper, we discuss a novel reservation-based, asynchronous MAC protocol called 'Multi-rate Multi-hop MAC Protocol' (MMMP) for multi-hop ad hoc networks that provides QoS guarantees for multimedia traffic. MMMP achieves this by providing service differentiation for multirate real-time traffic (both constant and variable bit rate traffic) and guaranteeing a bounded end-to-end delay for the same while still catering to the throughput requirements of non real time traffic. In addition, it administers bandwidth preservation via a feature called 'Smart Drop' and implements efficient bandwidth usage through a mechanism called 'Release Bandwidth'. Simulation results on the QualNet simulator indicate that MMMP outperforms IEEE 802.11 on all performance metrics and can efficiently handle a large range of traffic intensity. It also outperforms other similar state-of-the-art MAC protocols.

• Journal of Korean Society of Transportation
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• v.14 no.2
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• pp.89-118
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• 1996

The development and implementation of a real-time, traffic adaptive control scheme based on fuzzy logic through Video Image Detector systems (VIDs) is presented. Through VIDs based image processing, fuzzy logic can be used for a real-time traffic adaptive signal control scheme. Fuzzy control logic allows linguistic and inexact traffic data to be manipulated as a useful tool in designing signal timing plans. The fuzzy logic has the ability to comprehend linguistic instructions and to generate control strategy based on a priori verbal communication. The implementation of fuzzy logic controller for a traffic network is introduced. Comparisons are made between implementations of the fuzzy logic controller and the actuated controller in an isolated intersection. The results obtained from the application of the fuzzy logic controller are also compared with those corresponding to a pretimed controller for the coordinated intersections. Simulation results from the comparisons indicate the performance of the system is between under the fuzzy logic controller. Integration of the aforementioned schemes into and ATMS framework will lead to real-time adjustment of the traffic control signals, resulting in significant reduction in traffic congestion.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.3
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• pp.6-13
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• 2002

In this paper, we propose an image processing based method to measure red-time and green-time backward moving shockwave speed automatically at signalized intersections. Shockwave means the discontinuous boundary line between different vehicle traffic flows, and its moving speed is called shockwave speed which is obtain from the slope of boundary line. In this paper, we compose distance-time diagram for measuring shockwave speed automatically. By global vehicle tracking, we draw all of the vehicle moving path on distance-time diagram. We analyze the slope change pattern of curved moving path line, and compute red-time and green-time backward moving shockwave speed. We obtain the measurement result of shockwave speed, when applying above mentioned proposed method to experiment at signalized intersections, Once we can measure the shockwave speed, we could apply the result to highway ramp metering and automatic signal control at intersections effectively since we know the situation of frontal congestion easily.

• Journal of Information Processing Systems
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• v.2 no.1
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• pp.39-43
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• 2006

In this paper, we proposed TASL-MAC, a medium-access control (MAC) protocol for wireless sensor networks. In wireless sensor networks, sensor nodes are usually deployed in a special environment, are assigned with long-term work, and are supported by a limited battery. As such, reducing the energy consumption becomes the primary concern with regard to wireless sensor networks. At the same time, reducing the latency in multi-hop data transmission is also very important. In the existing research, sensor nodes are expected to be switched to the sleep mode in order to reduce energy consumption. However, the existing proposals tended to assign the sensors with a fixed Sleep/Listening schedule, which causes unnecessary idle listening problems and conspicuous transmission latency due to the diversity of the traffic-load in the network. TASL-MAC is designed to dynamically adjust the duty listening time based on traffic load. This protocol enables the node with a proper data transfer rate to satisfy the application's requirements. Meanwhile, it can lead to much greater power efficiency by prolonging the nodes' sleeping time when the traffic. We evaluate our implementation of TASL-MAC in NS-2. The evaluation result indicates that our proposal could explicitly reduce packet delivery latency, and that it could also significantly prolong the lifetime of the entire network when traffic is low.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.4
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• pp.237-250
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• 2015

This paper describes a hardware-oriented algorithm and its conceptual implementation in a real-time speed limit traffic sign detection system on an automotive-oriented field-programmable gate array (FPGA). It solves the training and color dependence problems found in other research, which saw reduced recognition accuracy under unlearned conditions when color has changed. The algorithm is applicable to various platforms, such as color or grayscale cameras, high-resolution (4K) or low-resolution (VGA) cameras, and high-end or low-end FPGAs. It is also robust under various conditions, such as daytime, night time, and on rainy nights, and is adaptable to various countries' speed limit traffic sign systems. The speed limit traffic sign candidates on each grayscale video frame are detected through two simple computational stages using global luminosity and local pixel direction. Pipeline implementation using results-sharing on overlap, application of a RAM-based shift register, and optimization of scan window sizes results in a small but high-performance implementation. The proposed system matches the processing speed requirement for a 60 fps system. The speed limit traffic sign recognition system achieves better than 98% accuracy in detection and recognition, even under difficult conditions such as rainy nights, and is implementable on the low-end, low-cost Xilinx Zynq automotive Z7020 FPGA.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.6
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• pp.430-439
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• 2016

Estimation and analysis of traffic jams plays a vital role in an intelligent transportation system and advances safety in the transportation system as well as mobility and optimization of environmental impact. For these reasons, many researchers currently mainly focus on the brilliant machine learning-based prediction approaches for traffic prediction systems. This paper primarily addresses the analysis and comparison of prediction accuracy between two machine learning algorithms: Naïve Bayes and K-Nearest Neighbor (K-NN). Based on the fact that optimized estimation accuracy of these methods mainly depends on a large amount of recounted data and that they require much time to compute the same function heuristically for each action, we propose an approach that applies multi-threading to these heuristic methods. It is obvious that the greater the amount of historical data, the more processing time is necessary. For a real-time system, operational response time is vital, and the proposed system also focuses on the time complexity cost as well as computational complexity. It is experimentally confirmed that K-NN does much better than Naïve Bayes, not only in prediction accuracy but also in processing time. Multi-threading-based K-NN could compute four times faster than classical K-NN, whereas multi-threading-based Naïve Bayes could process only twice as fast as classical Bayes.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.35.4-35
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• 2001

Image detection system for road traffic data analysis is a real time detection system using image processing techniques to get the real-time traffic information which is used for traffic control and analysis. One of the most important functions in this system is to match the coordinates of real world and that of image on video camera. When there in no way to know the exact position of camera and it´s height from the object. If some points on the road of real world are known it is possible to calculate the coordinates of real world from image.

• Journal of Information Processing Systems
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• v.10 no.1
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• pp.119-131
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• 2014

In recent literature on traffic scheduling, the combination of the two-dimensional discrete-time Markov chain (DTMC) and the Markov modulated Poisson process (MMPP) is used to analyze the capacity of VoIP traffic in the cognitive radio system. The performance of the cognitive radio system solely depends on the accuracy of spectrum sensing techniques, the minimization of false alarms, and the scheduling of traffic channels. In this paper, we only emphasize the scheduling of traffic channels (i.e., traffic handling techniques for the primary user [PU] and the secondary user [SU]). We consider the following three different traffic models: the cross-layer analytical model, M/G/1(m) traffic, and the IEEE 802.16e/m scheduling approach to evaluate the performance of the VoIP services of the cognitive radio system from the context of blocking probability and throughput.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.6
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• pp.697-702
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• 2018

Recently, the number of private cars has increased sharply due to the increase in national income. The sudden increase in the number of vehicles in limited territory has caused serious traffic congestion and the traffic congestion cost wasted on the road due to such traffic congestion is increasing every year. To solve this problem, we propose a traffic signal control system using image processing. In this paper, we use the camera installed at the intersection to measure the amount of traffic flowing in and out of each road simultaneously. We propose a traffic signal control system that can prevent traffic congestion before it happens. In the case of applying the traffic signal control system proposed in this paper to the daytime, the traffic volume could be measured accurately. However, the result of the experiment with the night-time general camera and the headlight with the infrared camera at the night-time of 72.8% was 86.6%.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.10A
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• pp.930-937
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• 2005

In this paper, a processing time and traffic capacity analysis algorithm for RFID system using LBT-serial searching scheme is proposed. Service time, carrier sensing time, additional delay time required for contiguous frequency channel occupancy, and additional delay time required for the contiguous using the same frequency channel are considered and the processing delay and frequency channel capacity are analyzed for the steady state operation of the system. The simulation results showing maximum capacity of the system and explaining the accuracy of the algorithm are provided.