• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.36.5-36
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• 2001

Localization is one of the key problems in the navigation of autonomous mobile robots. The probabilistic Markov localization approaches offer a good mathematical framework to deal with the uncertainty of environment and sensor readings but their use for realtime applications is limited by their computational complexity. This paper aims to reduce the high computational cost associated with the probabilistic Markov localization algorithm. We propose a hybrid landmark-based localization method combining triangulation and probabilistic approaches, which can efficiently update position probability grid, while the probabilistic framework allows to make use of any available sensor data to refine robot´s belief about its current location. The simulation results show the effectiveness and robustness of the method.

• Journal of Ocean Engineering and Technology
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• v.31 no.2
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• pp.111-120
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• 2017

It is generally acknowledged that the Steel Catenary Riser (SCR) is the most cost-effective riser type for deep-water offshore fields among various risers, including the SCR, flexible riser, and hybrid riser. However, in West Africa, the SCR type may not be suitable for FPSO systems because the large vertical motion of the floater brings about a considerable riser dynamic response. In this paper, an SCR system is designed for the FPSO in the West African field, where the use of a hybrid riser has been preferred. The proposed SCR configuration fulfills the design criteria of the API, such as the strength check and fatigue life. Moreover, a sensitivity analysis is also carried out to improve the certainty in the SCR design of a deep-water FPSO. The parameters affecting the strength and fatigue performance of the SCR are considered.

• Proceedings of the SAREK Conference
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• 2006.06a
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• pp.885-890
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• 2006

This study presents analysis results for the hybrid system combining solid oxide fuel cell and gas turbine. Two different system layouts(an ambient pressure system and pressurized system) are considered and their design performance are comparatively investigated taking into account critical design factor, the most critical parameter such as turbine inlet temperature, gas turbine pressure ratio, temperature difference at the fuel cell and fuel cell operating temperature are considered as design constraints. Performance variations according to system layout and design parameters are examined in energetic view point.

• Smart Structures and Systems
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• v.23 no.2
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• pp.185-194
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• 2019

The probabilistic tsunami risk assessment of large coastal areas is challenging because the inland propagation of a tsunami wave requires an accurate numerical model that takes into account the interaction between the ground, the infrastructures, and the wave itself. Classic mesh-based methods face many challenges in the propagation of a tsunami wave inland due to their ever-moving boundary conditions. In alternative, mesh-less based methods can be used, but they require too much computational power in the far-field. This study proposes a hybrid approach. A mesh-based method propagates the tsunami wave from the far-field to the near-field, where the influence of the sea floor is negligible, and a mesh-less based method, smooth particle hydrodynamic, propagates the wave onto the coast and inland, and takes into account the wave structure interaction. Nowadays, this can be done because the advent of general purpose GPUs made mesh-less methods computationally affordable. The method is used to simulate the inland propagation of the 2004 Indian Ocean tsunami off the coast of Indonesia.

• Proceedings of the KIPE Conference
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• 2019.07a
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• pp.77-79
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• 2019

Islanding detection is one of the most important issues for the distributed generation (DG) systems connected to the power grid. The conventional passive islanding detection methods inherently have a non-detection zone (NDZ), and active islanding detection methods may deteriorate the power quality of a power system. This paper proposes a novel hybrid islanding detection method based on Digital Lock-In Amplifier with no NDZ by monitoring the harmonics present in the grid. Proposed method detects islanding by passively monitoring the grid voltage harmonics and verify it by injecting small perturbation for only three-line cycles. Unlike FFT for the harmonic extraction, DLA HC have lower computational burden, moreover, DLA can monitor harmonic in real time, whereas, FFT has certain propagation delay. The simulation results are presented to highlight the effectiveness of the proposed technique. In order to prove the performance of the proposed method it is compared with several passive islanding detection methods. The experimental results confirm that the proposed method exhibits outstanding performance as compared to the conventional methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.5685-5700
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• 2018

Cyber intelligence, surveillance, and reconnaissance (ISR) has become more important than traditional military ISR. An agent used in cyber ISR resides in an enemy's networks and continually collects valuable information. Thus, this agent should be able to determine what is, and is not, useful in a short amount of time. Moreover, the agent should maintain a classification rate that is high enough to select useful data from the enemy's network. Traditional feature selection algorithms cannot comply with these requirements. Consequently, in this paper, we propose an effective hybrid feature selection method derived from the filter and wrapper methods. We illustrate the design of the proposed model and the experimental results of the performance comparison between the proposed model and the existing model.

• Journal of Korean Society for Quality Management
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• v.49 no.1
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• pp.1-15
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• 2021

Purpose: The purpose of this study was to propose a sensor fusion algorithm that integrates vehicle motion sensor(VMS) into the hybrid navigation system. Methods: How to evaluate the navigation performance was comparison test with the hybrid navigation system and the sensor fusion method. Results: The results of this study are as follows. It was found that the effects of the sensor fusion method and α value estimation were significant. Applying these greatly improves the navigation performance. Conclusion: For improving the reliability of navigation system, the sensor fusion method shows that the proposed method improves the navigation performance in a combat vehicle.

• Journal of Information Processing Systems
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• v.18 no.1
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• pp.146-158
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• 2022

With the success of the digital economy and the rapid development of its technology, network security has received increasing attention. Intrusion detection technology has always been a focus and hotspot of research. A hybrid model that combines particle swarm optimization (PSO) and kernel extreme learning machine (KELM) is presented in this work. Continuous-valued PSO and binary PSO (BPSO) are adopted together to determine the parameter combination and the feature subset. A fitness function based on the detection rate and the number of selected features is proposed. The results show that the method can simultaneously determine the parameter values and select features. Furthermore, competitive or better accuracy can be obtained using approximately one quarter of the raw input features. Experiments proved that our method is slightly better than the genetic algorithm-based KELM model.

• International Journal of Computer Science & Network Security
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• v.21 no.11
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• pp.312-320
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• 2021

Increase in computational cost and exhaustive search can lead to more complexity and computational energy. Thus, there is need for effective and efficient scheme to reduce the complexity to achieve optimal energy utilization. This will improve the energy efficiency and enhance the proficiency in terms of the resources needed to achieve convergence. This paper primarily focuses on the development of hybrid swarm intelligence scheme for reducing the computational complexity in binary optimization. In order to reduce the complexity, both artificial bee colony (ABC) and particle swarm optimization (PSO) have been employed to effectively minimize the exhaustive search and increase convergence. First, a new approach using ABC and PSO has been proposed and developed to solve the binary optimization problem. Second, the scout for good quality food sources is accomplished through the deployment of PSO in order to optimally search and explore the best source. Extensive experimental simulations conducted have demonstrate that the proposed scheme outperforms the ABC approaches for reducing complexity and energy consumption in terms of convergence, search and error minimization performance measures.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.1
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• pp.67-73
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• 2023

As interest in underwater structures and ocean exploration increases, many researchers are proposing methods for modeling and controlling various remotely operated vehicles (ROVs). Recently, hybrid systems composed of an autonomous underwater vehicle and an ROV capable of remote control and autonomous navigation are being developed. In this study we introduce a method that models Ariari-aROV, an ROV consisting of five thrusters, and performs navigation. The proposed ROV can be controlled manually and by autonomous navigation when given a target point. An extended Kalman filter is utilized for sensor measurement correction for more precise navigation. The proposed method is verified through a simulation.