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Your search keyword '"Liao, Yuan"' showing total 186 results
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186 results on '"Liao, Yuan"'

7. Taiwanese Across Taiwan Corpus And Its Applications

Author

Liao, Yuan-Fu, primary, Tsay, Jane S., additional, Kang, Peter, additional, Khoo, Hui-Lu, additional, Tan, Le-Kun, additional, Chang, Li-Chen, additional, Iunn, Un-Gian, additional, Su, Huang-Lan, additional, Thiann, Tsun-Guan, additional, Tiun, Hak-Khiam, additional, and Liao, Su-Lian, additional

Published
2022
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14. Energy and Age Pareto Optimal Trajectories in UAV-Assisted Wireless Data Collection.

Author

Liao, Yuan and Friderikos, Vasilis

Subjects
*MIXED integer linear programming, *PARETO optimum, *ENERGY consumption, *INFORMATION society
Abstract

This paper studiesan unmanned aerial vehicle (UAV)-assisted wireless network, where a UAV is dispatched to gather information from ground sensor nodes (SN) and transfer the collected data to a depot. The information freshness is captured by the age of information (AoI) metric, whilst the energy consumption of the UAV is seen as another performance criterion. Most importantly, the AoI and energy efficiency are inherently competing metrics, since decreasing the AoI requires the UAV returning to the depot more frequently, leading to a higher energy consumption. To this end, we design UAV paths that optimize these two competing metrics jointly and reveal the Pareto frontier. To formulate this problem, a multi-objective mixed integer linear programming (MILP) is proposed with a flow-based constraint set and we apply Bender’s decomposition on the proposed formulation. Numerical results show that the proposed method allows deriving non-dominated solutions among two competing metrics when designing the UAV path. [ABSTRACT FROM AUTHOR]

Published
2022
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16. Scattered Image Reconstruction at Near-Infrared Based on Spatial Modulation Instability.

Author

Liao, Yuan, Li, Lin, Wang, Zhaolu, Huang, Nan, and Liu, Hongjun

Abstract

We present a method of near-infrared image reconstruction based on spatial modulation instability in a photorefractive strontium barium niobate crystal. The conditions that lead to the formation of modulation instability at near-infrared are discussed depending on the theory of modulation instability gain. Experimental results of scattered image reconstruction at the 1064 nm wavelength show the maximum cross-correlation coefficient and cross-correlation gain are 0.57 and 2.09 respectively. This method is expected to be an aid for near-infrared imaging technologies. [ABSTRACT FROM AUTHOR]

Published
2022
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39. Welding in Break and Make Operations for CuMo and CuW Contact Materials in DC200–500V and Different Surrounding Gases

Author

Zhang Lige, Liao Yuan, Zhu Qingcheng, Makoto Hasegawa, and Li Zhenbiao

Subjects
010302 applied physics, Materials science, Condensed matter physics, 020208 electrical & electronic engineering, 02 engineering and technology, Welding, 01 natural sciences, law.invention, law, 0103 physical sciences, 0202 electrical engineering, electronic engineering, information engineering, Cold welding, Contactor, Voltage
Abstract

Hermetically sealed electromagnetic relays or contactors w ith high DC switching capacity, smaller size and longer lifespan are getting more and more important nowadays due to rapid developments of renewable energy installations and electrical vehicles. However, reports on contact welding resistances, arc durations and other related characteristics in DC200–1000VDC load ranges are quite few. In this paper, experiments were conducted with CuW70 and CuMo85 contacts in the following conditions: DC power voltage 200 to 500V, load current 40 to 150A, surrounding gases of air, $\text{N}_{\mathbf {2}} {, \mathbf {CO}} _{\mathbf {2}}$, Ar, $\text{O}_{\mathbf {2}}$, and mixtures of CO$_{\mathbf {2}}$ and Ar. Contact welding in both breaking and making operations was detected and analyzed. Percentages of welding in making operations were in general higher than those in breaking operations. Welding percentages of CuW in breaking operations were much lower than those of CuMo. Contact welding tendency in air is the least, but in the mixture of CO$_{\mathbf {2}}$/80% and Ar/20% is the most. Higher current levels generally caused more welding occurrences than higher voltage levels.

Published
2018

40. Development of Efficient and Robust Methods for Estimation of Transmission Line Parameters Using Synchronized PMU Data

Author

Lahmar Mustafa and Liao Yuan

Subjects
Electric power system, Electric power transmission, Computer science, Control theory, Robustness (computer science), 020209 energy, Transmission line parameters, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, Series impedance, Estimation methods, Electrical impedance, Linear methods
Abstract

Accurate transmission line parameters are important inputs for power system analysis, operation and planning, and protection and control system design, and are thus essential for safety and reliability of power system networks. The line parameters are affected by several factors and usually change when operating conditions vary. There are a variety of estimation methods, and each estimation method has certain restrictions and advantages. This paper proposes a new online linear method to estimate the positive-sequence line parameters using synchronized PMU data. The series impedance and shunt admittance are linearly estimated using the developed algorithm that is more computationally efficient than non-linear methods. The case study results demonstrate the robustness and effectiveness of the proposed algorithm, and the estimation method is applicable to both long and short transmission lines.

Published
2018

42. Exploring IEEE C37.246-2017 Guide for Protection Systems of Transmission-to-Generation Interconnections

Author

Deronja, Alla, primary, Houser, Keith, additional, Bapary, Abu, additional, Barsch, Jeffrey, additional, Cunico, Randy, additional, Fontana, Dominic, additional, Holt, Craig, additional, Jensen, Mike, additional, Liao, Yuan, additional, Midence, Rene, additional, Nagpal, Mukesh, additional, Patel, Manish, additional, Tualla, Ian, additional, and Ward, Solveig, additional

Published
2019
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49. A Hierarchical K-Means-Assisted Scenario-Aware Reconfigurable Convolutional Neural Network.

Author

Chen, Kun-Chih, Huang, Ya-Wei, Liu, Geng-Ming, Liang, Jing-Wen, Yang, Yueh-Chi, and Liao, Yuan-Hao

Subjects
CONVOLUTIONAL neural networks, SIGNAL convolution, GATE array circuits, REMOTE sensing
Abstract

The superiority of convolutional neural network (CNN) has been proven in various object recognition tasks and has received much attention. However, the modern CNN approaches usually that assume the testing data and the training data belong to an identical category. Therefore, the current CNN approaches are not efficient for some applications with multisource data (i.e., the input data come from different sources), such as remote sensing scene. To increase the adaptability of the involved CNN approach, we first propose a $K$ -means-assisted scenario-aware reconfigurable convolutional neural network (KASR-CNN) mechanism. The KASR-CNN is composed of a fully convolutional autoencoder-based $K$ -means clustering (FCA-KC) and a reconfigurable convolutional neural network (RCNN), which are used to perform the coarse-grained classification and fine-grained classification to the input data, respectively. Furthermore, a Lego-like architecture design methodology is proposed to reduce the design complexity and improve computing flexibility. To show the adaptability, the KASR-CNN mechanism has been applied to different CNN models. In addition, the KASR-CNN has been verified on the Xilinx Zynq-ZC706 field-programmable gate array (FPGA) and implemented with TSMC 40-nm technology. Compared with the conventional approaches, the proposed KASR-CNN can help the involved CNN model to improve 3.73%–36.65% classification accuracy with only 0.38%–0.74% area overhead. [ABSTRACT FROM AUTHOR]

Published
2021
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50. Temperature Tracking and Management With Number-Limited Thermal Sensors for Thermal-Aware NoC Systems.

Author

Chen, Kun-Chih, Tang, Hsueh-Wen, Liao, Yuan-Hao, and Yang, Yueh-Chi

Abstract

As the complexity of multicore system grows with respect to the technology development, the Network-on-Chip (NoC) provides flexible and scalable interconnection for the multicore systems. However, as the complexity of the network increases, the large workload diversity and the time-varying workload distribution result in large power density, which leads to severer thermal problems and makes the temperature distribution of the system become time-varying. To prevent the multicore systems from overheating, in a practical way, many thermal sensors are embedded in the system. However, due to the manufacturing cost constraints, it is not a viable option to involve a massive number of embedded thermal sensors. Therefore, searching for the appropriate locations in offline design phase to allocate the number-limited thermal sensors, which will be used to sense the time-varying system temperature behavior at runtime, is a design challenge. On the other hand, full-chip temperature distribution tracking based on the restricted temperature sensing information affects the efficiency of the involved temperature management. In this paper, we first present a novel thermal sensor allocation methodology by considering the time-varying temperature behavior on the chip according to different applications. Besides, a linear-regression-based reconstruction algorithm is proposed to estimate the full-chip temperature distribution according to the number-limited thermal sensing results. At last, a framework of temperature management with restricted temperature sensing information is introduced. Compared with the conventional methods, the proposed approach can reduce 28% to 92% average error of full-chip temperature estimation, which helps to improve the average system throughput by 60% to 70%. [ABSTRACT FROM AUTHOR]

Published
2020
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