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7 results on '"Yiyuan Ren"'

1. Metastable square Bismuth allotrope oriented by six-fold symmetric mica

Author

Nan Wu, Xiangchen Hu, Yinliang Tang, Congcong Wu, Yu Chen, Yiyuan Ren, Zhuo Zhang, Yi Yu, and Hung-Ta Wang

Subjects
Materials of engineering and construction. Mechanics of materials, TA401-492, Chemistry, QD1-999
Abstract

Abstract Layered bismuth (Bi) has been focused on two Peierls distortion derivatives, i.e., bulk stable β-phase (A7 phase), black phosphorus-like α-phase (A17 phase), and their mutated structures. Metastable structures beyond Peierls distortion system are yet rarely accessible. Here, Bi in square symmetry ( $${C}_{4v}$$ C 4 v ), called s-Bi, was grown via physical vapor deposition. The co-existence of three 120°-associated s-Bi crystal grains was analyzed using transmission electron microscopy. 120°-oriented one-dimensional (1D) nuclei indicate s-Bi heteroepitaxy on six-fold symmetric ( $${C}_{6v}$$ C 6 v ) mica (001). A subsequent nanorod-like nuclei coalescing could promote a morphology evolution, resulting in triangular or hexagonal nanosheets with the unique triple s-Bi structure suitable for later β-Bi growth. Lattice misfit and strain calculations suggest a supercell match between $$4\times 7$$ 4 × 7 s-Bi and $$3\times 3$$ 3 × 3 mica (001). This work demonstrates the metastable s-Bi structure via anisotropic heteroepitaxy of $${C}_{4v}$$ C 4 v s-Bi on $${C}_{6v}$$ C 6 v mica.

Published
2024
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2. Weighted Contrastive Prototype Network for Few-Shot Hyperspectral Image Classification with Noisy Labels

Author

Dan Zhang, Yiyuan Ren, Chun Liu, Zhigang Han, and Jiayao Wang

Subjects
hyperspectral image (HSI), few-shot learning, prototype network, contrastive learning, noisy labels, Science
Abstract

Few-shot hyperspectral image classification aims to develop the ability of classifying image pixels by using relatively few labeled pixels per class. However, due to the inaccuracy of the localization system and the bias of the ground survey, the potential noisy labels in the training data pose a very significant challenge to few-shot hyperspectral image classification. To solve this problem, this paper proposes a weighted contrastive prototype network (WCPN) for few-shot hyperspectral image classification with noisy labels. WCPN first utilizes a similarity metric to generate the weights of the samples from the same classes, and applies them to calibrate the class prototypes of support and query sets. Then the weighted prototype network will minimize the distance between features and prototypes to train the network. WCPN also incorporates a weighted contrastive regularization function that uses the sample weights as gates to filter the fake positive samples whose labels are incorrect to further improve the discriminative power of the prototypes. We conduct experiments on multiple hyperspectral image datasets with artificially generated noisy labels, and the results show that the WCPN has excellent performance that can sufficiently mitigate the impact of noisy labels.

Published
2024
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5. Differential Based Hologram RFID Indoor Localization Method

Author

Yiyuan Ren, Guang Yang, Lanxin Qiu, and Zhangqin Huang

Subjects
Computer science, business.industry, Holography, Phase (waves), Interference (wave propagation), law.invention, Indoor positioning system, law, Radio-frequency identification, Computer vision, Artificial intelligence, Differential (infinitesimal), business, ComputingMethodologies_COMPUTERGRAPHICS
Abstract

Radio Frequency Identification (RFID) has been widely used in many application domains. However, current indoor positioning systems are lack of accuracy due to the interference of multi-path and other factors. In this paper, a differential based hologram localization method has been proposed to improve the indoor positioning system accuracy. A differential hologram is calculated to locate target based on the naive hologram which is generated at first. Several experiments have been conducted to evaluate localization performance. Based on the experimental results, both the naive hologram method and the differential based hologram method are better than enhanced Phase Differential of Arrival (PDOA) based method in terms of accuracy, and the results also reveal that the differential based hologram method is more accurate than the naive hologram method.

Published
2015

6. The Sensor Behavior Description and Algorithm in Ambient Intelligence Environment

Author

Lanxin Qiu, Xiaolong Zeng, Chunhua Xiao, Zhangqin Huang, and Yiyuan Ren

Subjects
Service (systems architecture), Intelligent sensor, Ambient intelligence, Modeling language, Computer science, Distributed computing, Systems architecture, Wireless sensor network, Sketch, Behavioral modeling
Abstract

Ambient intelligence (AmI) environment is a complicated real-time system with perceptive function and implicit wireless communication ability, which provides humanized and intellectualized service. The previous study of AmI characteristics and intelligent sensor network system architecture makes it feasible to establish a system-level behavioral model of sensor network system in AmI environment. By using POOSL modeling language under the SHESim development environment, a further description class model of system behavior was put forward in this study. Moreover, it proposed a model design sketch of various processing classes and explained the clusters described in the top behavioral model in detail, which lays excellent foundation for establishing performance analysis model in the future intelligent sensor network systems.

Published
2014

7. Behavioral analysis and modeling of sensor network system in ambient intelligence environment

Author

Yiyuan Ren, Zhangqin Huang, Sheng Qian, Shuo Wang, Xiaolong Zeng, and Chunhua Xiao

Subjects
Scheme (programming language), Service (systems architecture), Ambient intelligence, Modeling language, business.industry, Computer science, media_common.quotation_subject, Perspective (graphical), Real-time computing, Wireless, business, Function (engineering), computer, Wireless sensor network, computer.programming_language, media_common
Abstract

To explore the behavior description method of sensor network system in ambient intelligence environment, this paper introduced the basic characteristics of ambient intelligence system, analyzed the architecture and basic functions of sensor network system. Moreover, an implementation scheme of the sensor network system is proposed based on the study above. This research indicates that the ambient intelligence is a complicated real-time system with perceptive function and implicit wireless communication ability, which centered on users and targeted at providing humanized and intellectualized service. Based on the behavioral analysis of the ambient intelligence system, a behavior model of perception system is established in system-level perspective by using the system-level modeling language of POOSL, tools included SHESim as well as the modeling method.

Published
2013

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