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Spectrum and energy efficient multi-antenna spectrum sensing for green UAV communication

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Digital Communications and Networks 2023年第4期9卷 846-855页

作者： junlin zhang Mingqian Liu Nan Zhao Yunfei Chen Qinghai Yang Zhiguo Ding State Key Laboratory of Integrated Service Networks Xidian UniversityShaanxiXi'an710071China School of Information and Communication Engineering Dalian University of TechnologyDalian116024China Department of Engineering University of DurhamDurhamDH13LEUK School of Electrical and Electronic Engineering University of ManchesterManchesterUK

Unmanned Aerial Vehicle(UAV)communication is a promising technology that provides swift and flexible ondemand wireless connectivity for devices without infrastructure *** recent developments in UAVs,spectrum and energy efficient green UAV communication has become *** deal with this issue,Spectrum Sharing Policy(SSP)is introduced to support green UAV *** sensing in SSP must be carefully formulated to control interference to the primary users and ground *** this paper,we propose spectrum sensing for opportunistic spectrum access in green UAV communication to improve the spectrum utilization *** from most existing works,we focus on the problem of spectrum sensing of randomly arriving primary signals in the presence of non-Gaussian noise/*** propose a novel and improved p-norm-based spectrum sensing scheme to improve the spectrum utilization efficiency in green UAV ***,we construct the p-norm decision statistic based on the assumption that the random arrivals of signals follow a Poisson ***,we analyze and derive the approximate analytical expressions of the false-alarm and detection probabilities by utilizing the central limit *** results illustrate the validity and superiority of the proposed scheme when the primary signals are corrupted by additive non-Gaussian noise and arrive randomly during spectrum sensing in the green UAV communication.

关键词： Green communication Multi-antenna spectrum sensing Non-Gaussian noise Unmanned aerial vehicle communication

Thermal studies of novel molecular perovskite energetic material(C_(6)H_(14)N_(2))[NH_(4)(ClO_(4))_(3)]

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Chinese Chemical Letters 2020年第2期31卷 554-558页

作者： Jing Zhou Li Ding Fengqi Zhao Bozhou Wang junlin zhang Xi'an Modern Chemistry Research Institute Xi'an 710065 China Department of Chemistry Technische Universit?t MünchenGarching bei München 85748Germany

(C6H(14)N2)[NH4(ClO4)3] is a newly developed porous hybrid inorganic-organic framework material with easy access and excellent detonation performances,however,its thermal properties is still unclear and severely hampered further *** this study,thermal behaviors and non-isothermal decomposition reaction kinetics of(C6H(14)N2)[NH4(ClO4)3] were investigated systematically by the combination of differential scanning calorimetry(DSC) and simultaneous thermal analysis ***-situ FTIR spectroscopy technology was applied for investigation of the structure changes of(C6H(14)N2) NH4(ClO4)3]and some selected referents for better understanding of interactions between different components during the heating *** results indicated that the novel molecular perovskite structure renders(C6H(14)N2)[NH4(ClO4)3] better thermal stability than most of currently used energetic *** temperature s,the stability of the cage skeleton constructed by NH4^+and ClO4^-ions determined the decomposition process rather than organic moiety confined in the *** simple synthetic method,good detonation performances and excellent thermal properties make(C6H(14)N2)[NH4(ClO4)3] an ideal candidate for the preparation of advanced explosives and propellants.

关键词： Cage skeleton DSC-TG In-situ FTIR Inorganic-organic framework material Thermal behaviors

A New Method to Identify the Maximum Time Interval between Individual Events in Compound Rainstorm and Heatwave Events

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International Journal of Disaster Risk Science 2024年第3期15卷 453-466页

作者： junlin zhang Wei Xu Yu Qiao Xinli Liao Chenna Meng Qinmei Han Key Laboratory of Environmental Change and Natural Disaster of Ministry of Education Faculty of Geographical ScienceBeijing Normal UniversityBeijing100875China Academy of Disaster Reduction and Emergency Management Ministry of Emergency Management and Ministry of EducationBeijing Normal UniversityBeijing100875China State Key Laboratory of Earth Surface Processes and Resource Ecology Beijing Normal UniversityBeijing100875China National Climate Center China Meteorological AdministrationBeijing100081China

Growing evidence indicates that extreme heat and rain may occur in succession within short time periods and cause greater impacts than individual events separated in time and ***,many studies have examined the impacts of compound hazard events on the social-ecological system at various *** definition of compound events is fundamental for such ***,there are no existing studies that support the determination of time interval between individual events of a compound rainstorm and heatwave(CRH)event,which consists of two or more potentially qualifying component heatwave and rainstorm *** address the deficiency in defining what individual events can constitute a CRH event,this study proposed a novel method to determine the maximum time interval for CRH events through the change in CRH event frequency with increasing time interval between individual events,using southern China as a case *** results show that the threshold identified by the proposed method is *** more than 90%of the meteorological stations,the frequency of CRH events has reached a maximum when the time interval is less than or equal to the *** study can aid in time interval selection,which is an important step for subsequent study of CRH events.

关键词： Compound extreme weather event Rainstorm and heatwave Southern China Threshold.Time interval

Relationships Between Evacuation Population Size, Earthquake Emergency Shelter Capacity, and Evacuation Time

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International Journal of Disaster Risk Science 2017年第4期8卷 457-470页

作者： Xiujuan Zhao Wei Xu Yunjia Ma Lianije Qin junlin zhang Ying Wang State Key Laboratory of Earth Surface Processes and Resource Ecology Faculty of Geographical Science Beijing Normal University Key Laboratory of Environmental Change and Natural Disaster of Ministry of Education Beijing Normal University Academy of Disaster Reduction and Emergency Management Ministry of Civil Affairs and Ministry of Education Beijing Normal University

Determining the location of earthquake emergency shelters and the allocation of affected population to them are key issues that face shelter planning and emergency management. To solve this emergency shelter location–allocation problem, evacuation time and the construction cost of shelters—both influenced by the evacuation population size and its spatial distribution—are two important considerations. In this article, a mathematical model with two objectives—to minimize total weighted evacuation time(TWET) and total shelter area(TSA)—is allied with a modified particle swarm optimization algorithm to address the problem. The relationships between evacuation population size, evacuation time, and total shelter area are examined using Jinzhan Town in Chaoyang District of Beijing, China, as a case study. The results show that TWET has a power function relationship with TSA under different population size scenarios, and a linear function applies between evacuation population and TWET under different TSAs. The joint relationships of TSA, TWET, and population size show that TWET increases with population increase and TSA decrease, and compared with TSA, population influences TWET more strongly. Given a reliable projection of population change and spatial planning of a study area, this method can be useful for government decision making on the location of earthquake emergency shelters and on the allocation of evacuees to those shelters.

关键词： China,earthquake shelter location Evacuation population allocation Total shelter area Total weighted evacuation time

A high-quality Actinidia chinensis(kiwifruit)genome

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Horticulture Research 2019年第1期6卷 269-277页

作者： Haolin Wu Tao Ma Minghui Kang Fandi Ai junlin zhang Guanyong Dong Jianquan Liu Key Laboratory of Bio-Resource and Eco-Environment of Ministry of Education and State Key Laboratory of Hydraulics and Mountain River Engineering College of Life SciencesSichuan UniversityChengdu 610065China The Limited Agriculture Company of Xinyuan Sacred Fruit ShifangDeyang 618409 SichuanChina State Key Laboratory of Grassland Agro-Ecosystem Institute of Innovation EcologyLanzhou UniversityLanzhou 730000China

Actinidia chinensis(kiwifruit)is a perennial horticultural crop species of the Actinidiaceae family with high nutritional and economic *** versions of the *** genomes have been previously assembled,based mainly on relatively short ***,we report an improved chromosome-level reference genome of ***(v3.0),based mainly on PacBio long reads and Hi-C *** high-quality assembled genome is 653 Mb long,with 0.76%*** least 43%of the genome consists of repetitive sequences,and the most abundant long terminal repeats were further identified and account for 23.38%of our novel *** has clear improvements in contiguity,accuracy,and gene annotation over the two previous versions and contains 40,464 annotated protein-coding genes,of which 94.41%are functionally ***,further analyses of genetic collinearity revealed that the kiwifruit genome has undergone two whole-genome duplications:one affecting all Ericales families near the K-T extinction event and a recent genus-specific *** reference genome presented here will be highly useful for further molecular elucidation of diverse traits and for the breeding of this horticultural crop,as well as evolutionary studies with related taxa.

关键词： Actinidia breeding high

A Review of the Status and Development Strategies of Computer Science and Technology Under the Background of Big Data

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Journal of Electronic Research and Application 2024年第2期8卷 49-53页

作者： junlin zhang Chengdu Normal University Chengdu 610000Sichuan ProvinceChina

This article discusses the current status and development strategies of computer science and technology in the context of big ***,it explains the relationship between big data and computer science and technology,focusing on analyzing the current application status of computer science and technology in big data,including data storage,data processing,and data ***,it proposes development strategies for big data *** science and technology play a vital role in big data processing by providing strong technical support.

关键词： Big data Computer science and technology Data storage Data processing Data visualization

Research on Fracture Prediction Method Based on Multi-Source Information Fusion

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Journal of Geoscience and Environment Protection 2024年第6期12卷 291-304页

作者： Yu zhang junlin zhang Shengli Xu Lina Yang CNOOC EnerTech-Drilling & Production Co. Tianjin China

Machine learning is a good method for predicting fracture by integrating multi-source information. Post-stack seismic attributes are commonly used to predict medium to large fractures, while pre-stack seismic attributes are proven to be more sensitive to small and micro sized fractures through forward modeling. Using machine learning algorithm to fuse information from different scales to predict fracture can greatly improve the accuracy of fracture prediction. On the basis of In-Situ stress prediction, the paper conducted post-stack seismic attribute analysis and pre-stack seismic attribute analysis, further studied on the sensitivity of seismic attributes to fracture and selected sensitive attributes, used the sensitivity log of well-bore fractures as the target log for learning, ultimately obtained a comprehensive body of fracture. Through blind well verification, the prediction results match well with the we1l data and the prediction results is highly consistent with the production data. The results of fracture prediction are reliable, and the research method has certain reference significance for fracture prediction.

关键词： In-Situ Stress Fracture Prediction Seismic Attribute Machine Learning

New Blind Recognition Method of SCLD and OFDM in Alpha-Stable Noise

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International Journal of Communications, Network and System Sciences 2017年第5期10卷 240-251页

作者： junlin zhang Bin Wang Yang Wang National Digital Switching System Engineering and Technological R&D Centre Zhengzhou China

This paper deals with modulation classification under the alpha-stable noise condition. Our goal is to discriminate orthogonal frequency division multiplexing (OFDM) modulation type from single carrier linear digital (SCLD) modulations in this scenario. Based on the new results concerning the generalized cyclostationarity of these signals in alpha-stable noise which are presented in this paper, we construct new modulation classification features without any priori information of carrier frequency and timing offset of the received signals, and use support vector machine (SVM) as classifier to discriminate OFDM from SCLD. Simulation results show that the recognition accuracy of the proposed algorithm can be up to 95% when the mix signal to noise ratio (MSNR) is up to ?1 dB.

关键词： Modulation Recognition Generalized Second-Order Cyclic Statistics OFDM Alpha-Stable Noise

Research on Multi-Wave Pore Pressure Prediction Method Based on Three Field Velocity Fusion

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Journal of Geoscience and Environment Protection 2024年第6期12卷 269-278页

作者： junlin zhang Huan Wan Yu zhang Yumei He Linlin Dan CNOOC EnerTech-Drilling & Production Co. Tianjin China

The optimization of velocity field is the core issue in reservoir seismic pressure prediction. For a long time, the seismic processing velocity analysis method has been used in the establishment of pressure prediction velocity field, which has a long research period and low resolution and restricts the accuracy of seismic pressure prediction;This paper proposed for the first time the use of machine learning algorithms, based on the feasibility analysis of wellbore logging pressure prediction, to integrate the CVI velocity inversion field, velocity sensitive post stack attribute field, and AVO P-wave and S-wave velocity reflectivity to obtain high-precision seismic P and S wave velocities. On this basis, high-resolution formation pore pressure and other parameters prediction based on multi waves is carried out. The pressure prediction accuracy is improved by more than 50% compared to the P-wave resolution of pore pressure prediction using only root mean square velocity. Practice has proven that the research method has certain reference significance for reservoir pore pressure prediction.

关键词： Velocity Field Resolution Machine Learning AVO Inversion Pore Pressure