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736 results on '"Zhao, Xingang"'

210. Performance Evaluation of Visual Noise Imposed Stochastic Resonance Effect on Brain-Computer Interface Application: A Comparison Between Motion-Reversing Simple Ring and Complex Checkerboard Patterns

Author

Xie, Jun, primary, Du, Guangjing, additional, Xu, Guanghua, additional, Zhao, Xingang, additional, Fang, Peng, additional, Li, Min, additional, Cao, Guozhi, additional, Li, Guanglin, additional, Xue, Tao, additional, and Zhang, Yanjun, additional

Published
2019
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215. Discovery of New Phases of Bismuth Oxyselenide Semiconductor Bi2OSe2 by Global Structure Search Approach.

Author

Wang, Xueting, Zhao, Xingang, Wang, Xinjiang, Li, Hongdong, He, Xin, and Zhang, Lijun

Abstract

Bi2O2X and Bi2OX2 (X = S, Se, and Te) have shown potential for thermoelectric, optoelectronic, etc. applications. The ground‐state structures of Bi2O2X have been determined experimentally (in space group I4/mmm). However, for Bi2OX2, only Bi2OS2 has been synthesized in the experiment (in space group P4/nmm). In previous theoretical studies, the crystal structures of Bi2OSe2 and Bi2OTe2 are assumed the same as that of Bi2OS2. Whether they can be experimentally synthesized remains an open question. Here, a swarm intelligence‐based structural prediction is employed in combination with first‐principles calculations to predict the crystal structures of Bi2OSe2. Three thermodynamically stable low‐energy phases (P21/m, P4/nmm, and P21/m′) are identified. Importantly, the newly reported P21/m phase, instead of the previously assumed P4/mmm phase, has the lowest energy. The P21/m‐Bi2OSe2 shows marginal stability with respect to decomposition into binary compounds Bi2O3 and Bi2Se3. The predicted phases of Bi2OSe2 have bandgaps of 0.67–1.19 eV and comparable small electron and hole carrier effective mass (less than 0.65 m0). The different phase stability between Bi2OSe2 and Bi2OS2 are explained in terms of different Bi─S and Bi─Se covalent bonding characters. Our work provides theoretical guidance for discovering new phases of Bi2OSe2 and an in‐depth understanding of the structure‐property relationship of Bi─O─S/Se system. [ABSTRACT FROM AUTHOR]

Published
2021
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216. A Closed-Loop Framework for the Inverse Kinematics of the 7 Degrees of Freedom Manipulator.

Author

Song, Guoli, Su, Shun, Li, Yingli, Zhao, Xingang, Du, Huibin, Han, Jianda, and Zhao, Yiwen

Subjects
DEGREES of freedom, KINEMATICS, MATHEMATICAL sequences, ROBOT kinematics, INVERSE problems
Abstract

SUMMARY: The 7 degrees of freedom (DOF) redundant manipulator greatly improves obstacle/singularity avoidance capability and operational flexibility. However, the inverse kinematics problem of this manipulator is very difficult to solve because it has an infinite number of solutions. This paper uses a new numerical sequence processing method with a closed-loop framework to solve the inverse kinematics of the 7-DOF redundant manipulator. Simulation and experiment show that this method has high commonality. No special structure of the robot is required, and this method has improved computational efficiency and reliability. [ABSTRACT FROM AUTHOR]

Published
2021
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217. A wearable fiber-optic sensor for monitoring human elbow and wrist joint motion.

Author

Li, Min, He, Bo, Zhao, Xingang, Xie, Jun, Yao, Wei, and Xu, Guanghua

Subjects
WRIST joint, OPTICAL modulation, DETECTORS, MOTION detectors, LIGHT intensity, ELBOW joint, ARM
Abstract

This article describes a wearable sensor for monitoring the motion of human elbow and wrist joints. The sensor converts the joint motion angle into a displacement, which is monitored using a fiber-optic sensor based on reflective light intensity modulation. A mathematical model is established, and the potential influencing factors of the sensor are investigated. Two prototypes for elbow and wrist joint angle monitoring are fabricated and validated. The experimental results indicate that the proposed sensor has a measurement range of 0–60° (0–120°), with a resolution of 0.338° (3.6°) for monitoring the wrist joint palm flexion (elbow joint flexion). The proposed sensor has the potential to be used for rehabilitation purposes and monitoring of joint angles while performing reaching tasks, which are the most common upper-limb gestures. [ABSTRACT FROM AUTHOR]

Published
2021
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218. Research on the Status Quo and Supervision Mechanism of Food Safety in China

Author

DONG, Shengzhong, XU, Fangxu, TAO, Siyuan, WU, Longkun, and ZHAO, Xingang

Subjects
ComputingMilieux_LEGALASPECTSOFCOMPUTING, Agribusiness, ComputingMilieux_MISCELLANEOUS, Food safety, Supervision mechanism, Regulatory system
Abstract

Food safety supervision mechanism is a strong guarantee to promote the smooth implementation of China's food safety laws and regulations, and it is implemented through legal, administrative, economic, moral and other integrated policy instruments, as well as media publicity, quality traceability, network tracking, information disclosure and other non-administrative means. Along with strengthening supervision and control means, the people's food safety in China is safeguarded, and the healthy development of the food industry is promoted.

Published
2018
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240. An Approach to Minimize Calibration Time for Brain Computer Interface Based on Motion Imagery

Author

Zhao Xingang, Han Jianda, Zou Yijun, and Xu Weiliang

Subjects
Exploit, Computer science, business.industry, Calibration (statistics), Matched filter, 0206 medical engineering, Training time, SIGNAL (programming language), Pattern recognition, 02 engineering and technology, 020601 biomedical engineering, Motion (physics), 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Artificial intelligence, business, Brain–computer interface, Block (data storage)
Abstract

The long training time is a big problem that block the application of brain computer interface. This paper solve this problem using the existing dataset of many subjects. By analyzing the differences in EEG signal among different users, removing these differences as much as possible and exploits the common points of different individual, the proposed method can correct the data in existing dataset to a new dataset close to the target data. Then using the ensemble method, we combine the model of the existing dataset to a final model. The result shows that the proposed method can decrease the training time greatly while the recognize accuracy can also meet the need.

Published
2017

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