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Chinese Chemical Letters 2011年第9期22卷 1115-1118页

作者： Ling Ling Bai Yong Hao Zhou Xiu Li wang si Guo Yuan xian Li Wu School of Chemical Engineering and Energy Zhengzhou University Zhengzhou 450001 China

A combination of photochlorination ofp-xylene and succedent Friedel-Crafts alkylation polymerization was firstly used in the preparation of the hypercrosslinked adsorptive resin. The data of GC-MS and GC showed that a series of chlorizates were produced when p-xylene was photochlorinated. Hypercrosslinked resins could be synthesized by copolymerization, self-polymerization of chlorizates or post crosslinking reaction. The chemical structure and micromorphology of the porous resins were characterized by BET, FF-IR, SEM and elementary analysis （EA）. The results showed that the novel adsorptive resins possess high BET surface near to 1038 m^2/g and large pore volumes range from 0.5 to 1.2 cm^3/g.

关键词： Hypercrosslinked resin Synthesis p-Xylene Photochlorination Polymerization

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矿山斜井箕斗安全性能检验方法的研究

世界有色金属 2024年第12期 64-67页

作者：杨玮林王四现李勇吴剑雄长沙矿山研究院有限责任公司湖南长沙410012 金属矿山安全技术国家重点实验室湖南长沙410012 昆明高金金马机电设备有限公司云南昆明651701

本文深入探讨了针对矿山斜井箕斗这一关键运输设备的安全性能检验的科学方法与技术规范。论文紧密围绕矿山安全这一核心问题,详细分析了斜井箕斗在复杂矿山环境下的运行特性和潜在安全隐患,并在此基础上研究设计了一套全面、严谨且符合... 详细信息

本文深入探讨了针对矿山斜井箕斗这一关键运输设备的安全性能检验的科学方法与技术规范。论文紧密围绕矿山安全这一核心问题,详细分析了斜井箕斗在复杂矿山环境下的运行特性和潜在安全隐患,并在此基础上研究设计了一套全面、严谨且符合实际作业条件的斜井箕斗安全性能检验体系。该研究通过对斜井箕斗的关键部件、结构强度、运行稳定性、制动效能等多方面进行系统性检验与评估,旨在提高其整体安全性能水平,有效预防因设备故障引发的各类安全事故。同时,结合国内外现行的相关标准和技术规范,论文还对斜井箕斗的安全性能检验方法进行了标准化和规范化建设,力求为我国矿山斜井箕斗的安全管理和定期检验提供理论依据和技术支持,从而有力地推动我国矿山安全生产技术水平的整体提升。

关键词：矿山安全斜井箕斗安全性能检验方法技术规范

Medical Image Compression by Applying 3D DWT in PACS

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Wuhan University Journal of Natural Sciences 1999年第3期4卷 313-318页

作者： wang si-xian Li Fei-peng Zeng Fa-long Liao Meng-yang Li Hui Wuhan Univ Wuhan China

The process of image compression in a practical Picture Archiving and Communication System (PACS) was discussed with detail. To fully reduce the inter-slice correlation existing in the volumetric image sets generated by CT and MR, 3D Discrete Wavelet Transformation (DWT) was introduced in our application. Instead of using a fixed quantizer of lossless low frequency and distinct loss of high frequency, an adaptive quantizer was devised taking MSE as the performance index. In the low frequency subband, DPCM was replaced withS+P transform to facilitate coding computation. Compared with JPEG or 2D DWT, our method is 20%–50% more efficient. Furthermore, preliminary tests showed that 33 dB may be the maximal distortion threshold for CT images.

关键词： PACS 3D DWT S+P transformation optimal bit allocation maximal distortion threshold

New meroterpenoid compounds from the culture of mushroom Panus lecomtei

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Chinese Journal of Natural Medicines 2020年第4期18卷 268-272页

作者： wang si-xian ZHAO Rui-Lin GUO Cui CHEN Bao-Song DAI Huan-Qin LIU Gao-Qiang LIU Hong-Wei Hunan Provincial Key Laboratory of Forestry Biotechnology&International Cooperation Base of Science and Technology Innovation on Forest Resource Biotechnology Central South University of Forestry&TechnologyChangsha 410004China State Key Laboratory of Mycology Institute of MicrobiologyChinese Academy of SciencesBeijing 100101China Savaid Medicine School University of Chinese Academy of SciencesBeijing 100049China

Two new meroterpenoid compounds(1 and 2) together with five known meroterpenoid derivatives(3–7) were isolated from solid culture of mushroom Panus lecomtei. The structures of new compounds were confirmed by the analysis of NMR and HREsi-MS spectroscopic data. The biosynthetic pathway of 1–7 was postulated. All isolated compounds were evaluated for antibacterial activities against Staphylococcus aureus, Escherichia coli, Bacillus subtilis, Pseudomonas aeruginosa and Bacillus Calmette–Gué*** 3 exhibited weak antibacterial activity against Bacillus Calmette–Guérin with the inhibition rate of 83.6% at 100 μmol·*** compounds showed no antibacterial activities against all tested pathogens at 100 μmol·L-1.

关键词： Panus lecomtei Meroterpenoid Antibacterial Biosynthetic pathway

Track correlation algorithm based on CNN-LSTM for swarm targets

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Journal of Systems Engineering and Electronics 2024年第2期35卷 417-429页

作者： CHEN Jinyang wang Xuhua CHEN xian Research Institute for National Defense Engineering Academy of Military SciencesLuoyang 471023China Information Engineering University Zhengzhou 450001China School of Computer Science and Technology Xidian UniversityXi’an 710071China

The rapid development of unmanned aerial vehicle(UAV) swarm, a new type of aerial threat target, has brought great pressure to the air defense early warning system. At present, most of the track correlation algorithms only use part of the target location, speed, and other information for *** this paper, the artificial neural network method is used to establish the corresponding intelligent track correlation model and method according to the characteristics of swarm ***, a route correlation method based on convolutional neural networks (CNN) and long short-term memory (LSTM)Neural network is designed. In this model, the CNN is used to extract the formation characteristics of UAV swarm and the spatial position characteristics of single UAV track in the formation,while the LSTM is used to extract the time characteristics of UAV swarm. Experimental results show that compared with the traditional algorithms, the algorithm based on CNN-LSTM neural network can make full use of multiple feature information of the target, and has better robustness and accuracy for swarm targets.

关键词： track correlation correlation accuracy rate swarm target convolutional neural network(CNN) long short-term memory(LSTM)neural network

Recent advances in graphene-based phase change composites for thermal energy storage and management

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Nano Materials Science 2024年第2期6卷 115-138页

作者： Qiang Zhu Pin Jin Ong si Hui Angela Goh Reuben J.Yeo Suxi wang Zhiyuan Liu xian Jun Loh Institute of Materials Research and Engineering A*STAR(Agency for ScienceTechnology and Research)2 Fusionopolis WayInnovis#08-03138634Singapore Institute of Sustainability for Chemicals Energy and EnvironmentA*STAR(Agency for ScienceTechnology and Research)1 Pesek RoadJurong Island627833Singapore School of Chemistry Chemical Engineering and BiotechnologyNanyang Technological University21 Nanyang Link637371Singapore Shenzhen Institutes of Advanced Technology(siAT) Chinese Academy of Sciences(CAS)1068 Xueyuan AvenueShenzhen518055China Department of Material Science and Engineering National University of Singapore9 Engineering Drive 1#03-09 EA117575Singapore

Energy storage and conservation are receiving increased attention due to rising global energy ***,the development of energy storage materials is *** energy storage(TES)systems based on phase change materials(PCMs)have increased in prominence over the past two decades,not only because of their outstanding heat storage capacities but also their superior thermal energy regulation ***,issues such as leakage and low thermal conductivity limit their applicability in a variety of ***-based materials such as graphene and its derivatives can be utilized to surmount these *** study examines the recent advancements in graphene-based phase change composites(PCCs),where graphene-based nanostructures such as graphene,graphene oxide(GO),functionalized graphene/GO,and graphene aerogel(GA)are incorporated into PCMs to substantially enhance their shape stability and thermal conductivity that could be translated to better storage capacity,durability,and temperature response,thus boosting their attractiveness for TES *** addition,the applications of these graphene-based PCCs in various TES disciplines,such as energy conservation in buildings,solar utilization,and battery thermal management,are discussed and summarized.

关键词： Phase change material Nanocomposites Solar energy Sustainable energy Thermo-regulation

Full-domain collaborative deployment method of multiple interference sources and evaluation of its deployment effect

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Defence Technology（防务技术） 2024年第2期32卷 572-595页

作者： Yue wang Fuping Sun xian wang Jinming Hao Kai Xiao School of Geospatial Information The PLA Information Engineering UniversityZhengzhou 450001HenanChina

This paper realizes the full-domain collaborative deployment of multiple interference sources of the global satellite navigation system(GNSS)and evaluates the deployment effect to enhance the ability to disturb the attacker and the capability to defend the GNSS during navigation *** evaluation indicators for the jamming effect of GNSS suppressive and deceptive jamming sources are first created,their evaluation models are built,and their detection procedures are sorted out,as the basis for determining the deployment *** principles for collaboratively deploying multi-jamming sources are developed to obtain the deployment structures(including the required number,structures in demand,and corresponding positions)of three single interference sources required by collaboratively ***,simulation and hardware-in-loop testing results are presented to determine a rational configuration of the collaborative deployment of multi-jamming sources in the set situation and further realize the full-domain deployment of an interference network from ground,air to *** evaluation indices for the deployment effect are finally developed to evaluate the deployment effect of the proposed configuration and further verify its reliability and rationality.

关键词： Jamming effect Multiple interference sources Collaborative deployment Effect evaluation Defense capability

An improved high-fidelity adaptive model for integrated inlet-engine-nozzle based on mechanismdata fusion

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Chinese Journal of Aeronautics 2024年第8期37卷 190-207页

作者： Chen wang Ziyang YU xian DU Ximing SUN School of Control Science and Engineering Dalian University of TechnologyDalian 116024China Key Laboratory of Intelligent Control and Optimization for Industrial Equipment Ministry of EducationDalian University of TechnologyDalian 116024China

Nowadays,there has been an increasing focus on integrated flight propulsion control and the inlet-exhaust design for the aero-propulsion *** component-level models are inadequate due to installed performance deviations and mismatches between the real engine and the model,failing to meet the accuracy requirements of supersonic *** paper establishes a quasi-one-dimensional model for the inlet-exhaust system and conducts experimental ***,a mechanism-data fusion adaptive modeling scheme using an Extreme Learning Machine based on the Salp Swarm Algorithm(SSA-ELM)is *** study reveals the inlet model’s efficacy in reflecting installed performance,flow matching,and mitigating pressure distortion,while the nozzle model accurately predicts flow coefficients and thrust coefficients,and identifies various operational *** model’s output closely aligns with typical experimental *** combining offline optimization and online adaptive correction,the mechanismdata fusion adaptive model substantially reduces output errors during regular flights and varying levels of degradation,and effectively handles gradual degradation within a single flight ***,the mechanism-data fusion adaptive model holistically addresses total pressure errors within the inlet-exhaust system and normal shock location *** approach significantly curbs performance deviations in supersonic *** example,at Ma=2.0,the system error impressively drops from 34.17%to merely 6.54%,while errors for other flight conditions consistently stay below the 2.95%*** findings underscore the clear superiority of the proposed method.

关键词： Aero-propulsion system Integrated inlet-enginenozzle Component-level model On-board adaptive model Mechanism-data fusion Extreme learning machine

An adaptive 3D reconstruction method for asymmetric dual-angle multispectral stereo imaging system on UAV platform

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Science China(Information Sciences) 2024年第8期67卷 285-299页

作者： Chen wang xian LI Yanfeng GU Zixu wang School of Electronics and Information Engineering Harbin Institute of Technology Beijing Institute of Control and Electronic Technology

A multispectral imaging system often cannot capture 3D spatial information owing to hardware limitations, which diminishes the effectiveness across various domains. To address this problem, we have developed a multispectral stereo imaging system along with an adaptive 3D reconstruction algorithm. Unlike existing unmanned aerial vehicle stereo imaging systems, our multispectral stereo imaging system uses two multispectral cameras with asymmetric spectral bands positioned at different angles. This design enables the acquisition of a higher number of bands and lateral spatial information while maintaining a lightweight structure. This system introduces challenges such as large geometric distortions and intensity differences between multiple bands. To accurately recover 3D spatial information, we propose an adaptive 3D reconstruction method. This method employs a position and orientation system-assisted projection transformation and a normalized threshold adjustment strategy. Finally, mutual information is used to reconstruct the multispectral images densely, effectively addressing nonlinear differences and generating a comprehensive multispectral point cloud. Our stereo system was used for two real data collections in different regions, and the efficacy of the proposed 3D reconstruction method was validated by comparing it with existing methods and commercial software.

关键词： multispectral images 3D reconstruction stereo imaging system unmanned aerial vehicle feature extraction

A New Industrial Intrusion Detection Method Based on CNN-BiLSTM

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Computers, Materials & Continua 2024年第6期79卷 4297-4318页

作者： Jun wang Changfu si Zhen wang Qiang Fu College of Computer Science and Technology Shenyang University of Chemical TechnologyShenyang110142China

Nowadays,with the rapid development of industrial Internet technology,on the one hand,advanced industrial control systems(ICS)have improved industrial production ***,there are more and more cyber-attacks targeting industrial control *** ensure the security of industrial networks,intrusion detection systems have been widely used in industrial control systems,and deep neural networks have always been an effective method for identifying cyber *** intrusion detection methods still suffer from low accuracy and a high false alarm ***,it is important to build a more efficient intrusion detection *** paper proposes a hybrid deep learning intrusion detection method based on convolutional neural networks and bidirectional long short-term memory neural networks(CNN-BiLSTM).To address the issue of imbalanced data within the dataset and improve the model’s detection capabilities,the Synthetic Minority Over-sampling Technique-Edited Nearest Neighbors(SMOTE-ENN)algorithm is applied in the preprocessing *** algorithm is employed to generate synthetic instances for the minority class,simultaneously mitigating the impact of noise in the majority *** approach aims to create a more equitable distribution of classes,thereby enhancing the model’s ability to effectively identify patterns in both minority and majority *** the experimental phase,the detection performance of the method is verified using two data *** results show that the accuracy rate on the CICIDS-2017 data set reaches 97.7%.On the natural gas pipeline dataset collected by Lan Turnipseed from Mississippi State University in the United States,the accuracy rate also reaches 85.5%.

关键词： Intrusion detection convolutional neural network bidirectional long short-term memory neural network multi-head self-attention mechanism