• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.942-947
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• 2003

An important signal processing problem in PVDF sensor is the restoration of surface information from electric sensing signals. The objectives of this research are to design a new texture sensing system and to develop a new signal processing algorithm for signals from the sensor to be tangibly displayed by tangible interface systems. The texture sensing system is designed to get surface information with high resolution and dynamic range. First, a PVDF sensor is made of piezoelectric polymer (polyvinylidene fluoride) strips molded in a silicon rubber and attached in a rigid cylinder body. The sensor is mounted to a scanning system for dynamic sensing. Secondly, a new signal processing algorithm is developed to restore surface information. The algorithm consists of the two-dimensional modeling of the sensor using an identification method and inverse filtering from sensing signals into estimated surface information. Finally the two-dimensional surface information can be experimentally reconstructed from sensing signals using the developed signal processing algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.7
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• pp.3465-3479
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• 2017

Information-Centric Vehicular Ad Hoc Network (IC-VANET) is a promising network architecture for the future intelligent transport system. Video streaming applications over IC-VANET not only enrich infotainment services, but also provide the drivers and pedestrians real-time visual information to make proper decisions. However, due to the characteristics of wireless link and frequent change of the network topology, the packet loss seriously affects the quality of video streaming applications. In this paper, we propose a REceiver-Driven loss reCOvery Mechanism (REDCOM) to enhance video dissemination over IC-VANET. A Markov chain based estimation model is introduced to capture the real-time network condition. Based on the estimation result, the proposed REDCOM recovers the lost packets by requesting additional forward error correction packets. The REDCOM follows the receiver-driven model of IC-VANET and does not require the infrastructure support to efficiently overcome packet losses. Experimental results demonstrate that the proposed REDCOM improves video quality under various network conditions.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.15 no.6
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• pp.20-26
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• 2001

In this paper, we design tunnel inner section displacement measurement system which is composed of potentiometer-type displacement sensors, microcontroller-based intelligent sensing head and host computer for the management system and acquisition data. Multiple node communication bus connects the intelligent sensing heads with the host computer. For safe and re1iab1e network operation we use daisy-chain configuration, termination resistor, fail-safe biasing circuit. For tole enhancement of system utilization, we use modbus protocol. The acquisition data are transmitted to host computer and managed by database. Several data request conditions and sorting conditions are provided by management software. The utilization of designed system is confirmed by experiment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.3
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• pp.980-998
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• 2023

In Low Earth Orbit (LEO) satellite networks, satellites operate fast and the inter-satellite link change period is short. In order to sense the spectrum state in LEO satellite networks in real-time, a space-based satellite network intelligent spectrum sensing algorithm based on artificial neural network (ANN) is proposed, while Geosynchronous Earth Orbit (GEO) satellites are introduced to make fast and effective judgments on the spectrum state of LEO satellites by using their stronger arithmetic power. Firstly, the visibility constraints between LEO satellites and GEO satellites are analyzed to derive the inter-satellite link building matrix and complete the inter-satellite link situational awareness. Secondly, an ANN-based energy detection (ANN-ED) algorithm is proposed based on the traditional energy detection algorithm and artificial neural network. The ANN module is used to determine the spectrum state and optimize the traditional energy detection algorithm. GEO satellites are used to fuse the information sensed by LEO satellites and then give the spectrum decision, thereby realizing the inter-satellite spectrum state sensing. Finally, the sensing quality is evaluated by the analysis of sensing delay and sensing energy consumption. The simulation results show that our proposed algorithm has lower complexity, the sensing delay and sensing energy consumption compared with the traditional energy detection method.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.6
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• pp.110-120
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• 2008

Cognitive Radio (CR) technology is proposed for using the unused spectrum band efficiently because of the spectrum scarcity problems. Spectrum sensing technology is one of the key challenge issues in cognitive radio technologies, which enables unlicensed users to identify and utilize vacant spectrum resource allocated to primary users. In this paper, the cooperative spectrum sensing technologies apply the ITS(Intelligent Transport System) and performance of signal detection analyzes. Then, we utilize the OR-rule and AND-rule for the cooperative signal detection. These data fusion rules improve the performance and reliability of the signal detection.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.1
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• pp.19-26
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• 2010

In this paper, we propose an efficient decision rule in order to get better chance to detect the unused spectrum assigned to a licensed user and improve reliability of spectrum sensing performance. Each secondary user receives the signals from the licensed user. And the resulting signals input to an energy detector. Then, each sensing result is combined and used to make a decision whether the primary user is present at the licensed spectrum band or not. In order to make the reliable decision, we apply an efficient decision rule that is called as a majority rule in this paper. The simulation results show that spectrum sensing performance with the proposed decision rule is more reasonable and efficient than that with conventional decision rules.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.4
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• pp.2038-2057
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• 2017

Gaussian learning is a new technology in the computational intelligence area. However, this technology weakens the learning ability of a particle swarm and achieves a lack of diversity. Thus, this paper proposes a vector Gaussian learning strategy and presents an effective approach, named particle swarm optimization based on vector Gaussian learning. The experiments show that the algorithm is more close to the optimal solution and the better search efficiency after we use vector Gaussian learning strategy. The strategy adopts vector Gaussian learning to generate the Gaussian solution of a swarm's optimal location, increases the learning ability of the swarm's optimal location, and maintains the diversity of the swarm. The method divides the states into normal and premature states by analyzing the state threshold of the swarm. If the swarm is in the premature category, the algorithm adopts an inertia weight strategy that decreases linearly in addition to vector Gaussian learning; otherwise, it uses a fixed inertia weight strategy. Experiments are conducted on eight well-known benchmark functions to verify the performance of the new approach. The results demonstrate promising performance of the new method in terms of convergence velocity and precision, with an improved ability to escape from a local optimum.

• International Journal of Automotive Technology
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• v.7 no.5
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• pp.609-618
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• 2006

This paper presents the lateral control of an autonomous vehicle by using a look-ahead sensing system. In look-ahead sensing by an absolute positioning system, a reference lane, constructed by straight lanes or circular lanes, was switched by a segment switching algorithm. To cope with sensor noise and modeling uncertainty, a robust LMI-based $H_{\infty}$ lateral controller was designed by the feedback of lateral offset and yaw angle error at the vehicle look-ahead. In order to verify the safety and the performance of lateral control, a scaled-down vehicle was developed and the location of the vehicle was detected by using an ultrasonic local positioning system. In the mechatronic scaled-down vehicle, the lateral model and parameters are verified and estimated by a J-turn test. For the lane change and reference lane tracking, the lateral controllers are used experimentally. The experimental results show that the $H_{\infty}$ controller is robust and has better performance compared with look-down sensing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.4
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• pp.1555-1570
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• 2016

For monitoring forest fires, a real-time system to prevent fires in wider areas should be supported consistently. However, there has still been a lack of the support for real-time system related to forest fire monitoring. In addition, the 'real-time' processing in a forest fire detection system can lead to excessive consumption of energy. To solve these problems, the intelligent data acquisition of sensing nodes is required, and the maximum energy savings as well as rapid and accurate detection by flame sensors need to be done. In this regard, this paper proposes a node built-in filter algorithm for intelligent data collection of sensing nodes for the rapid detection of forest fires with focus on reducing the power consumption of the remote sensing nodes and providing efficient wireless sensor network-based forest environment monitoring in terms of data transmission, network stability and data acquisition. The experimental result showed that battery life can be extended through the intelligent sampling of remote sensing nodes, and the average accuracy of the measurement of flame detection based on the distance is 44%.

• 한국ITS학회:학술대회논문집
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• 2010.05a
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• pp.48-52
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• 2010