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3. Joint waveform design and resource allocation strategy for cognitive radar target situation awareness.

Author

Song, Yuxiao, Tian, Biao, Wang, Rongqing, Xu, Shiyou, and Chen, Zengping

Subjects
*RADAR cross sections, *RADAR signal processing, *RADAR targets, *MULTIPLE target tracking, *SITUATIONAL awareness
Abstract

Traditional radar systems use fixed patterns and constant electromagnetic wave transmission to illuminate targets, but they often do not effectively use prior information about targets and consume significant radar resources. Cognitive radar has emerged as a way to improve resource efficiency and address these shortcomings. A joint waveform design and resource allocation strategy for cognitive radar that incorporates target situational awareness is proposed. This method integrates the interacting multiple model algorithm and the Unscented Kalman Particle Filter to achieve target situation awareness as prior knowledge. By combining the target attitude and the frequency response function of the target radar cross section at different time points in the prior knowledge, a joint beam control and power allocation strategy is formulated and transformed into an optimization problem. In addition, a cognitive pulse‐to‐pulse frequency agile waveform design method is proposed to support multiple target tracking under complex motion models. Simulation experiments demonstrate the effectiveness of this approach in obtaining accurate target situation information, achieving beam control, and optimizing power allocation. The designed waveforms can enhance radar target detection performance and improve low probability of intercept characteristics by adjusting the pulse repetition interval. This method has significant technical value. [ABSTRACT FROM AUTHOR]

Published
2024
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4. Multi-dimensional LSTM: A Model of Network Text Classification

Author

Wu, Weixin, Liu, Xiaotong, Shi, Leyi, Liu, Yihao, Song, Yuxiao, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Liu, Zhe, editor, Wu, Fan, editor, and Das, Sajal K., editor

Published
2021
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6. Charge Dynamics Engineering Sparks Hetero‐Interfacial Polarization for an Ultra‐Efficient Microwave Absorber with Mechanical Robustness (Small 6/2024)

Author

Huan, Xianhua, primary, Li, Hefeng, additional, Song, Yuxiao, additional, Luo, Jintao, additional, Liu, Cong, additional, Xu, Ke, additional, Geng, Hongbo, additional, Guo, Xiaodong, additional, Chen, Chen, additional, Zu, Lei, additional, Jia, Xiaolong, additional, Zhou, Jisheng, additional, Zhang, Haobin, additional, and Yang, Xiaoping, additional

Published
2024
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11. The Raf‐like MAPKKKs STY8, STY17, and STY46 negatively regulate Botrytis cinerea resistance by limiting MKK7 protein accumulation in Arabidopsis.

Author

Chen, Lijuan, Xiao, Jiahui, Li, You, Song, Yuxiao, Liu, Jun, Zhou, Qi, Sun, Ting, Wang, Hong‐Bin, and Liu, Bing

Subjects
BOTRYTIS cinerea, ARABIDOPSIS proteins, PROTEIN-tyrosine kinases, PLANT diseases, DISEASE resistance of plants, CHITIN, SERINE/THREONINE kinases
Abstract

SUMMARY: Plant diseases, which seriously damage crop production, are in most cases caused by fungal pathogens. In this study, we found that the Raf‐like MAPKKKs STY8 (SERINE/THREONINE/TYROSINE KINASE 8), STY17, and STY46 negatively regulate resistance to the fungal pathogen Botrytis cinerea through jasmonate response in Arabidopsis. Moreover, STY8/STY17/STY46 homologs negatively contribute to chitin signaling. We further identified MKK7 as the MAPKK component interacting with STY8/STY17/STY46 homologs. MKK7 positively contributes to resistance to B. cinerea and chitin signaling. Furthermore, we found that STY8/STY17/STY46 homologs negatively affect the accumulation of MKK7, in accordance with the opposite roles of MKK7 and STY8/STY17/STY46 homologs in defense against B. cinerea. These results provide new insights into the mechanisms precisely regulating plant immunity via Raf‐like MAPKKKs. Significance Statement: We found that STY8/STY17/STY46 homologs negatively regulate plant resistance through modulating the MKK7 pathway. [ABSTRACT FROM AUTHOR]

Published
2024
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12. Charge Dynamics Engineering Sparks Hetero‐Interfacial Polarization for an Ultra‐Efficient Microwave Absorber with Mechanical Robustness

Author

Huan, Xianhua, primary, Li, Hefeng, additional, Song, Yuxiao, additional, Luo, Jintao, additional, Liu, Cong, additional, Xu, Ke, additional, Geng, Hongbo, additional, Guo, Xiaodong, additional, Chen, Chen, additional, Zu, Lei, additional, Jia, Xiaolong, additional, Zhou, Jisheng, additional, Zhang, Haobin, additional, and Yang, Xiaoping, additional

Published
2023
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16. Joint Jam Perception and Adaptive Waveform Optimization for Anti-Interrupted Sampling Repeater Jamming

Author

Wei, Song, Fang, Yuyuan, Song, Yuxiao, Wei, Shaopeng, and Zhang, Lei

Abstract

Recently, interrupted sampling repeater jamming (ISRJ) based on digital radio frequency memory (DRFM), which could easily form high-power false targets, has severely impacted radar detection capabilities. Conventional anti-ISRJ techniques ignore the operating characteristics of the jammer. Once the anti-ISRJ algorithm and the features of the jammer are mismatched, undesirable jamming residues or signal loss appear. In order to avoid these unwanted performance losses, an algorithm jointing the jam perception and the adaptive waveform is developed in this article. First, a bidirectional constant false alarm rate detector is introduced to locate and estimate the jamming component in radar echo. An ISRJ feature vector is then built to reconstruct and cancel jamming components for accurate detection under ISRJ. Second, an adaptive anti-ISRJ waveform is developed based on the vector, leading the DRFM to retransmit signals orthogonal to the real detection signal. Besides, the particle swarm optimization algorithm efficiently works out the optimal waveform parameters to improve the suppression performance. As radar switches to the adaptive anti-ISRJ waveform, long-term suppression of ISRJ is achieved without locating, estimating, and suppressing the ISRJ components in each echo. Simulated experiments demonstrate that the suggested algorithm can accurately detect radar targets under ISRJ.

Published
2024
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18. Research on the Spatial Dynamic Evolution of Digital Agriculture—Evidence from China.

Author

Meng, Jiajia, Zhao, Baoyu, Song, Yuxiao, and Lin, Xiaomei

Abstract

Digital agriculture serves as a pivotal means of ushering in innovative agricultural practices and achieving sustainable agricultural development. Although agricultural digitalization has received increasing attention, the unbalanced development and regional disparities of digital agriculture are still key obstacles to sustainable agricultural development. Based on the data of 31 provinces in China from 2013 to 2021, this study evaluates the development level of digital agriculture in China, and further analyzes the distribution pattern, spatial characteristics, and transition probabilities of digital agriculture from a regional perspective. The index system of the digital agriculture development level is constructed from five aspects: infrastructure, talent resources, agricultural informatization, the digitization of agricultural production processes, and agricultural production efficiency. Among these, infrastructure and talent resources reflect the resources needed for the development of digital agriculture; agricultural informatization and the digitization of the agricultural production process indicate the role of digitization in the process of agricultural development; and the agricultural production efficiency is the goal of the digital agriculture development, which is a critical criteria of its evaluation. The weighted analysis method of objective sequential analysis, which combines the dynamic level of indicators and sequential relationships, is used to assign weights to the indicators. In addition, to address the regional disparities in the development level of digital agriculture, kernel density estimation, Moran's index, and (spatial) Markov chain analysis are applied to analyze the spatial dynamic evolution of digital agriculture in China. The findings reveal substantial regional disparities in digital agriculture development within China, particularly in the Western region, where development lags behind. Moreover, this study offers actionable policy recommendations for policymakers to strengthen regional infrastructure and talent cultivation, as well as other aspects of digital agriculture development, to mitigate regional differences and provide reference for other emerging countries. [ABSTRACT FROM AUTHOR]

Published
2024
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19. Petrogenesis of Syn-Collisional Adakitic Granitoids and Their Copper Mineralization Potential in the North Qilian Suture Zone

Author

Song, Yuxiao Chen, Tianqi Zhang, Ying Cui, and Shuguang

Subjects
adakite, porphyry Cu mineralization, zircon Hf isotope, syn-collisional granitoids, north qilian suture zone
Abstract

The petrogenesis of late Ordovician–early Silurian adakitic plutons in the North Qilian suture zone (NQSZ) and their copper mineralization potential remain poorly understood. Here we present a detailed study of the Heishishan (HSS) granodiorite–granite pluton, spatially associated with Cu–Au mineralization in the eastern section of the NQSZ. Zircon U–Pb dating confirms that the granodiorite–granite were formed at ca. 438–435 Ma, in association with a continental collision. Geochemically, the granitoids resemble low-Mg adakitic rocks featured by elevated Sr/Y and (La/Yb)N ratios with depleted MgO, Cr, and Ni concentrations, suggesting minimal mantle contribution. They are sodium rich with K2O/Na2O < 1, and have higher and more varied Sr/Y, but lower La/Yb than those from the continental lower crust. The εHf(t) values of zircon grains are positive and vary in a wide range of +2.0–12.7, indicating a heterogeneous source rather than a single arc basaltic source. They show moderately radiogenic Sr and Nd isotope compositions with initial 87Sr/86Sr ratios of 0.705101–0.706312 and εNd(t) values of +0.5–1.0, most likely a mixed source of the oceanic basaltic crust plus ca. 15–20% overlying sediments. The magmatic oxygen fugacity was relatively low as indicated by zircon Ce(IV)/Ce(III) ratios of 32–156, which is unfavorable for a large copper mineralization.

Published
2023
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21. Dynamic User-Scheduling and Power Allocation for SWIPT Aided Federated Learning: A Deep Learning Approach

Author

Li, Yang, Wu, Yuan, Song, Yuxiao, Qian, Liping, and Jia, Weijia

Abstract

Federated learning (FL) has been considered as a promising paradigm for enabling distributed machine learning (ML) in wireless networks. To address the limited energy capacity of wireless devices, we propose a simultaneous wireless information and power transfer (SWIPT) aided FL, in which one FL server (FLS) co-located at a cellular base station (BS) uses SWIPT to simultaneously broadcast the global model to wireless user-devices (UDs) and provide wireless power transfer to them. The UDs then use the harvested energy to train their local models and further transmit the local models to the FLS for aggregation. To improve the spectrum efficiency, we consider that the UDs form a non-orthogonal multiple access (NOMA) group for simultaneously sending their local models over the same spectrum channel. Taking the UDs’ time-varying available energy and channel conditions into account, we propose a dynamic optimization of the UDs-scheduling, the BS's transmit-power allocation, and the UDs’ power-splitting factors for SWIPT, with the objective of minimizing the long-term energy consumption while ensuring the FL convergence. The optimization problem, however, is challenging to solve since it is a finite-horizon dynamic programming problem but with an unknown stopping time, and moreover, the action space covers both discrete and continuous variables. To address these difficulties, we first execute a series of equivalent transformations to reduce the number of decision variables and then formulate the problem as a stochastic shortest path problem, based on which we propose an actor-critic deep reinforcement learning algorithm with the proximal policy optimization to efficiently learn the policy that dynamically adjusts the UDs-scheduling for FL as well as the BS's transmit-power for SWIPT. Numerical results validate the effectiveness and performance of our proposed algorithm. The results demonstrate that our proposed algorithm can effectively reduce the long-term energy consumption in comparison with two baseline algorithms.

Published
2023
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39. Multi-dimensional LSTM: A Model of Network Text Classification

Author

Liu Yihao, Leyi Shi, Xiaotong Liu, Song Yuxiao, and Weixin Wu

Subjects
Feature fusion, Computer science, business.industry, Classification result, Feature vector, Computation, Big data, Multi dimensional, Pattern recognition, Artificial intelligence, business, Sample (graphics), Expression (mathematics)
Abstract

Focusing on the diversified opinion expression form and the explosive growth of information amount in network environment of big data, we propose a text emotion recognition model based on multi-dimensional LSTM to improve classification accuracy of network information by making full use of additional information of text samples. In this paper, we divide the original sample into two parts: the main information sample and the additional information sample. Then multi-dimensional LSTM model is used to extract their features vectors. Finally, according to the results of the two feature vectors, the classification result is carried out by feature fusion and further computation. The multi-dimensional LSTM model is implemented and tested by TensorFlow. The experimental results show that the emotion recognition classification accuracy has been greatly improved by taking advantage of multi-dimensional LSTM in big data environment.

Published
2021

48. SACT: A New Model of Covert Communication Based on SDN

Author

Zhiyu Xue, Song Yuxiao, Leyi Shi, Honglong Chen, and Liu Yihao

Subjects
Computer science, 02 engineering and technology, lcsh:Chemical technology, Biochemistry, Article, Analytical Chemistry, SDN, 0202 electrical engineering, electronic engineering, information engineering, Forwarding plane, lcsh:TP1-1185, Electrical and Electronic Engineering, Instrumentation, Digital watermarking, security analysis, business.industry, watermarking, covert communication, 020206 networking & telecommunications, 020207 software engineering, Watermark, Atomic and Molecular Physics, and Optics, Scalability, dynamic protection, business, Software-defined networking, Protection mechanism, Communication channel, Computer network
Abstract

Anonymous tracking technology of network watermarking is limited by the deployment of tracking devices in traditional network structure, resulting in poor scalability and reusability. Software Defined Network (SDN) boasts more freedom thanks to its separation of the control plane from the data plane. In this paper, a new anonymous communication tracking model SDN-based Anonymous Communication Tracking (SACT) is proposed, which introduces network watermarking into SDN and combines IP time hidden channel and symbol expansion technology. In addition, we introduce a hopping protection mechanism to improve the anti detection ability of the watermark as well. The experimental results show that in a variety of simulated network environments, SACT achieves excellent detection rate and bit error rate, thus it is sufficient to determine the communication relationship between the two parties. Meanwhile, SACT solves the deployment problem of anonymous tracking and improves the availability and scalability of covert communication.

Published
2020

50. A New Method for Multi-installment Divisible-Load Scheduling

Author

Song Yuxiao, Xiaoli Wang, Zhen Wei, and Yuping Wang

Subjects
Rate-monotonic scheduling, Earliest deadline first scheduling, Least slack time scheduling, Computer science, Heuristic, Processor scheduling, Dynamic priority scheduling, Parallel computing, Round-robin scheduling, Gang scheduling, Fair-share scheduling, Deadline-monotonic scheduling, Multiprocessor scheduling, Scheduling (computing), Fixed-priority pre-emptive scheduling, Two-level scheduling
Abstract

Minimizing the make-span of the entire divisible load is the primary objective of multi-installment scheduling in heterogeneous parallel and distributed systems. This is a significantly difficult problem to address because we have to find the optimal number m of installments, optimal number n of processors taking part in computation, and optimal load partition A = [αij]n m with each element represents the load fraction assigned to each processor in different installment. Therefore, this problem involves 2+n m variables. In this paper, we first find the function expression of the optimal load partition A with respect to the number m of installments and the number n of processors participating in computation, i.e., A = f (n, m), thereby reducing the dimension of the problem down to 2. Then we propose a new heuristic method for finding the optimal numbers of installments and processors. Finally, experimental results show that the make span of the entire divisible load obtained by the proposed method is smaller than those by the existing multi-installment scheduling methods, which implies the effectiveness of the proposed method.

Published
2015

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