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A spatial-spectral classification framework for multispectral LiDAR

地球空间信息科学学报（英文版） 2024年第5期27卷中插4,1460-1474页

作者： Shuo Shi Biwu Chen Sifu Bi Junkai Li Wei Gong Jia Sun Bowen Chen Lin Du Jian Yang Qian Xu Fei Wang Shalei Song State Key Laboratory of Information Engineering in Surveying Mapping and Remote SensingWuhan UniversityWuhanChina Scientific Laboratory Shanghai Radio Equipment Research InstituteShanghaiChina Industry Development and Planning Institute NFGABeijingChina State Key Laboratory of Information Engineering in Surveying Mapping and Remote SensingWuhan UniversityWuhanChina Electronic Information School Wuhan UniversityWuhanChina Faculty of Information Engineering China University of GeosciencesWuhanChina Faculty of Information Engineering and Automation Kunming University of Science and TechnologyKunmingChina Innovation Academy for Precision Measurement Science and Technology Chinese Academy of SciencesWuhanChina

Precise classification of Light Detection and Ranging(LiDAR)point cloud is a fundamental process in various applications,such as land cover mapping,forestry management,and autonomous *** to the lack of spectral information,the existing research on single wavelength LiDAR classification is *** information from images could address this limitation,but data fusion suffers from varying illumination conditions and the registration problem.A novel multi-spectral LiDAR successfully obtains spatial and spectral information as a brand-new data type,namely,multispectral point cloud,thereby improving classification ***,spa-tial and spectral information of multispectral LiDAR has been processed separately in previous studies,thereby possibly limiting the classification performance of multispectral *** explore the potential of this new data type,the current spatial-spectral classification framework for multispectral LiDAR that includes four steps:(1)neighborhood selection,(2)feature extraction and selection,(3)classification,and(4)label *** novel highlights were proposed in this spatial-spectral classification framework.(1)We improved the popular eigen entropy-based neighborhood selection by spectral angle match to extract a more precise neighborhood.(2)We evaluated the importance of geometric and spectral features to compare their contributions and selected the most important features to reduce feature redundancy.(3)We conducted spatial label smoothing by a conditional random field,accounting for the spatial and spectral informa-tion of the neighborhood *** proposed method demonstrated by a multispectral LiDAR with three channels:466 nm(blue),527 nm(green),and 628 nm(red).Experimental results demonstrate the effectiveness of the proposed spatial-spectral classification ***,this research takes advantages of the complementation of spatial and spectral infor-mation,which could benefit more precise neighbor

关键词： multispectral Light Detection and Ranging(LiDAR) point cloud classification neighborhood selection feature selection condition random field

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Using analytic hierarchy process to evaluate deep learning for infrared target recognition

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Multimedia Tools and Applications 2024年第38期83卷 86229-86245页

作者： Xu, Laixiang Cao, Bingxu Wei, Xinhong Li, Bei Su, Jingfeng Ning, Shiyuan Zhao, Junmin School of Computer and Data Science Henan University of Urban Construction Pingdingshan467036 China School of Information Engineering Luohe Vocational Technology College Henan University of Technology Luohe Institute of Technology Luohe462000 China School of Computer and Data Science Innovation Laboratory of Smart Traffic and Big Data Development of Hainan Province Pingdingshan467036 China School of Computer and Data Science Research Center of Smart City and Big Data Engineering of Henan Province Henan University of Urban Construction Pingdingshan467036 China Department of Software Information China Electronics Technology Group Corporation 36-th Research Institute Jiaxing314033 China School of Computer and Data Science Research Center of Smart City and Big Data Engineering of Henan Province Research Center of Intelligent Campus Application Engineering of Henan Province Innovation Laboratory of Smart Traffic and Big Data Development of Hainan Province Henan University of Urban Construction Pingdingshan467036 China

In order to promote the evaluation performance of deep learning infrared automatic target recognition (ATR) algorithms in the complex environment of air-to-air missile research, we proposed an analytic hierarchy process (AHP) evaluation system consisting of the target recognition ability, the generalization recognition ability, the anti-interference ability, the background suppression ability, and the cost metrics ability. According to detailed quantitative analysis and experimental results, we establish probability evaluation models and get their probability values. Compared with traditional evaluation systems, our proposed method implementation is showing high reliability. Similar superior performances are also achieved, such as quick, comprehensive, and scientific. Through the above research, the key technology of deep learning performance evaluation in automatic target recognition has been broken through, which provides some basis and guidance for the analysis of infrared imaging-guided weapon systems. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Infrared imaging

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Secure Key Management in 5G Networks Using Elliptic Curve Integrated Encryption Scheme (ECIES) for Low-Power IoT Devices 4

Secure Key Management in 5G Networks Using Elliptic Curve In...

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4th IEEE International Conference on Mobile Networks and Wireless Communications, ICMNWC 2024

作者： Chitra Kiran, N. Maindola, Meenakshi Kumara, Bharath Kaliappan, S. Bhatt, Pooja Maranan, Ramya Alliance University Department of Electronics and Communication Engineering Bengaluru India Graphic Era Deemed to be University Department of Computer Science & Engineering Dehradun India Ramaiah University of Applied Science Department of Electronics and Communication Engineering Bengaluru India Lovely Professional University Division of Research and Development Phagwara India Parul institute of Engineering and Technology Parul University Faculty of Engineering and Technology Department of Computer Science and Engineering Post Limda India Saveetha School of Engineering Simats Department of Research and Innovation Chennai India

ISBN: (纸本)9798350352931

The rapid proliferation of the Internet of Things (IoT) has led to a surge in cyber threats, demanding the development of robust security frameworks. This paper introduces an advanced threat detection model, leveraging Artificial Intelligence (AI) and Cyber Twin Technologies for enhanced IoT security. The proposed framework integrates a Cyber Twin-a digital replica of physical IoT devices-with real-time data analytics to detect, predict, and respond to sophisticated cyber-attacks. The Cyber Twin continuously monitors IoT networks, identifying abnormal behaviors and enabling the implementation of dynamic security measures through AI-driven intrusion detection systems (IDS). A hybrid deep learning approach combining Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN) is utilized to enhance anomaly detection and threat classification accuracy. The system's ability to simulate various attack scenarios within a digital environment facilitates the development of effective countermeasures while minimizing the impact on actual IoT operations. Experimental results demonstrate significant improvements in detection accuracy, reduced false positives, and enhanced system resilience. The proposed AI and Cyber Twin-based threat detection model sets a new benchmark in safeguarding IoT infrastructures against emerging cyber threats. © 2024 IEEE.

关键词： Network intrusion

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Catalytic conversion of asphaltenes to BTXN using metal-loaded modified HZSM-5

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Chinese Journal of Chemical engineering 2022年第9期35卷 253-264页

作者： Linyang Wang Qiang Wang Yongqi Liu Qiuxiang Yao Ming Sun Xiaoxun Ma School of Chemical Engineering Northwest UniversityInternational Science&Technology Cooperation Base of MOST for Clean Utilization of Hydrocarbon ResourcesChemical Engineering Research Center of the Ministry of Education for Advanced Use Technology of Shanbei EnergyShaanxi Research Center of Engineering Technology for Clean Coal ConversionCollaborative Innovation Center for Development of Energy and Chemical Industry in NorthernXi’an 710069China School of Science Xijing UniversityXi’an 710123China

HZSM-5 zeolites with Si/Al ratios of 20,35,50 and 65 were prepared by the directing crystallization process of silicalite-1 *** influence of Si/Al ratios on the production of benzene,toluene,xylene and naphthalene(BTXN)originated from asphaltenes catalytic pyrolysis was explored by adopting Py-GC/*** Z5-50 zeolites were prepared by various metal ions(Ni^(2+),Mo^(6+),Fe^(3+),and Co^(2+))with different loading rates(3%(mass),5%(mass),7%(mass),and 9%(mass))and the physical and chemical properties of these zeolites were characterized by XRD,SEM,ICP-OES,XPS,NH_(3)-TPD,FTIR,Py-IR and N_(2)adsorption-desorption *** addition,they were employed to catalyze the conversion of asphaltenes pyrolysis production to BTXN using Py-GC/*** show that the highest relative content of aromatics has been obtained over HZSM-5 with Si/Al ratio of 50(Z5-50),reaching 61.87%.Besides,the loading of Ni,Mo,Fe,and Co on Z5-50 leads to an increase of acid strength and provides new active *** relative content of BTXN increases by 3.17%over 3Ni-Z5,which may be ascribed to that Ni promoted the conversion of polycyclic aromatic hydrocarbons(PAHs)to monocyclic aromatics due to the cracking of aliphatic side chains of PAHs and the decrease of phenolic activation *** under the catalysis of 5Mo-Z5,the relative content of aromatics and BTXN augmented by 5.75%and 4.02%,*** addition,the highest relative content of aromatics reaches 70.09%when the loading rate of Fe was 7%(mass),and the relative content of BTXN increases from 25.87%to 29.42%.The results demonstrate that the active sites provided by different metal species expressed diverse effects on *** the Bronsted/Lewis acid ratios of HZSM-5 modified by metal decreased,the acid strength and the relative content of BTXN both increased,which illustrated that there is a synergistic catalysis with the Bronsted acid sites and Lewis acid sites provided by metal *** general,the performance of

关键词： Coal tar Asphaltenes HZSM-5 Pyrolysis Metal-modification BTXN

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Reinforced HDPE with optimized biochar content for material extrusion additive manufacturing:morphological,rheological,electrical,and thermomechanical insights

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Biochar 2024年第1期6卷 655-675页

作者： Nectarios Vidakis Markos Petousis Dimitrios Kalderis Nikolaos Michailidis Emmanuel Maravelakis Vassilios Saltas Nikolaos Bolanakis Vassilis Papadakis Mariza Spiridaki Apostolos Argyros Department of Mechanical Engineering Hellenic Mediterranean University71410 HeraklionGreece. Department of Electronic Engineering Hellenic Mediterranean University73133 ChaniaGreece. Physical Metallurgy Laboratory Mechanical Engineering DepartmentSchool of EngineeringAristotle University of Thessaloniki54124 ThessalonikiGreece. Centre for Research and Development of Advanced Materials(CERDAM) Center for Interdisciplinary Research and InnovationBalkan CentreBuilding B’10th Km Thessaloniki-Thermi Road57001 ThessalonikiGreece. Department of Industrial Design and Production Engineering University of West Attica12243 AthensGreece. Institute of Electronic Structure and Laser Foundation for Research and Technology-HellasN.Plastira 100M70013 HeraklionGreece.

The development of efficient and sustainable composites remains a primary objective of both research and *** this study,the use of biochar,an eco-friendly reinforcing material,in additive manufacturing(AM)is investigated.A high-density Polyethylene(HDPE)thermoplastic was used as the matrix,and the material extrusion(MEX)technique was applied for composite *** was produced from olive tree prunings via conventional pyrolysis at 500°*** samples were created using biochar loadings in the range of 2.0-10.0 wt.%.The 3D-printed samples were mechanically tested in accordance with international *** analysis(TGA)and Raman spectroscopy were used to evaluate the thermal and structural properties of the *** electron microscopy was used to examine the fractographic and morphological characteristics of the *** electrical/dielectric properties of HDPE/biochar composites were studied over a broad frequency range(10-2 Hz-4 MHz)at room ***,a laborious effort with 12 different tests was implemented to fully characterize the developed composites and investigate the correlations between the different *** investigation demonstrated that biochar in the MEX process can be a satisfactory reinforcement ***,compared to the control samples of pure HDPE,biochar increased the tensile strength by over 20%and flexural strength by 35.9%when added at a loading of 4.0 wt.%.The impact strength and microhardness were also significantly ***,the Direct current(DC)conductivity of insulating HDPE increased by five orders of magnitude at 8.0 wt.%of biochar content,suggesting a percolation *** results highlight the potential of C-based composites for the use in additive manufacturing to further exploit their applicability by providing parts with improved mechanical performance and eco-friendly profiles.

关键词： High-density polyethylene Biochar Material extrusion 3D printing Additive manufacturing

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Advanced Spatio-Temporal Froth Analysis Using Smart Soft Sensors in Mineral Processing

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SN Computer science 2024年第4期5卷 363页

作者： Bendaouia, Ahmed Abdelwahed, El Hassan Qassimi, Sara Boussetta, Abdelmalek Benzakour, Intissar Amar, Oumkeltoum Chekroun, Mohamed Hasidi, Oussama Lachihab, Oussama Computer Systems Engineering Laboratory (LISI) Cadi Ayyad University Marrakech Morocco SEIA Department Moroccan Foundation for Advanced Science Innovation and Research (MAScIR) Rabat Morocco R & amp D and Engineering Center Reminex Managem Group Marrakech Morocco Computer and Systems Engineering Laboratory (L2IS) Cadi Ayyad University Marrakech Morocco

In the transformative field of mineral processing, the need for innovative technologies to overcome inherent difficulties and a critical shortage of high-quality data is an acute challenge. This study addresses these pressing issues by leveraging advanced spatio-temporal deep learning techniques, specifically Convolutional Long Short-Term Memory (ConvLSTM). Focused on the Zinc flotation circuit at CMG Managem Group in Morocco, our comprehensive approach encompasses meticulous data collection from a real-world industrial setting, rigorous spatial and temporal analyses, practical and accurate data augmentation, and the development of a ConvLSTM model for precise prediction of mineral grades. By capturing the temporal intricacies of froth behavior through video data, we gain insights into mineral concentration fluctuations, a critical aspect of traditional analysis. By offering a comprehensive solution that combines cutting-edge technology, meticulous data analysis, and practical augmentation methods, we aim to elevate not only mineral processing efficiency but also a broader spectrum of resource utilization and sustainable practices. This study offers a promising solution to elevate mineral processing efficiency and accuracy in the face of data limitations. It underscores the potential for transformative impacts on mineral processing operations, paving the way for more effective resource utilization and sustainable practices. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd 2024.

关键词： Data augmentation Industrial data analysis Machine learning Mineral processing

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Multifunction integration within magnetic CNT-bridged MXene/CoNi based phase change materials

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escience 2024年第6期4卷 108-117页

作者： Yan Gao Xiao Chen Xu Jin Chenjun Zhang Xi Zhang Xiaodan Liu Yinhui Li Yang Li Jinjie Lin Hongyi Gao Ge Wang Beijing Advanced Innovation Center for Materials Genome Engineering Beijing Key Laboratory of Function Materials for Molecule&Structure ConstructionSchool of Materials Science and EngineeringUniversity of Science and Technology BeijingBeijing 100083China School of Physics and Astronomy Beijing Normal UniversityBeijing 100875China Research Institute of Petroleum Exploration&Development PetroChinaBeijing 100083China Micro-Nano System Research Center College of Information and Optical EngineeringTaiyuan University of TechnologyTaiyuanShanxi 030024China Shunde Graduate School University of Science and Technology BeijingShunde 528399China

Developing advanced nanocomposite phase change materials(PCMs)integrating zero-energy thermal management,microwave absorption,photothermal therapy and electrical signal detection can promote the leapfrog development of flexible wearable electronic *** this goal,we propose a multidimensional collaborative strategy combining two-dimensional(2D)MXene nanosheets with metal-organic framework-derived onedimensional(1D)carbon nanotubes(CNTs)and zero-dimensional(0D)metal *** encapsulating paraffin wax(PW)in three-dimensional(3D)networked multidimensional MXene/CoNi-C,the resulting composite PCMs exhibit excellent thermal energy storage capacity and long-term thermally reliable *** from the synergistically enhanced photothermal effects of CNTs,Co/Ni nanoparticles and MXene,PW@MXene/CoNi-C can capture photons efficiently and transfer phonons quickly,yielding an ultrahigh photothermal conversion and storage efficiency of 97.5%.Additionally,PW@MXene/CoNi-C composite PCMs exhibit high microwave absorption with a minimum reflection loss of -49.3 dB at 8.03 GHz in heat-related electronic application *** attractively,the corresponding flexible phase change film can simultaneously achieve thermal management and electromagnetic shielding of electronic devices,as well as photothermal therapy and electrical signal detection for *** functional integration design provides an important reference for developing advanced flexible multifunctional wearable materials and devices.

关键词： Phase change materials Metal-organic frameworks Two-dimensional MXene Photothermal conversion Thermal energy storage Microwave absorption

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AT-Spherical Neutrosophic Fuzzy DEMATEL-ANP Approach to Problematiques of Blockchain Technology in Smart Cities 14

AT-Spherical Neutrosophic Fuzzy DEMATEL-ANP Approach to Prob...

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14th International Conference on Software, Knowledge, Information Management and Applications, SKIMA 2022

作者： Promentilla, Michael Angelo B. Kuok, Fidero Gokongwei College of Engineering Center for Engineering and Sustainable Development Research De la Salle University Department of Chemical Engineering Manila Philippines National Institute of Science Technology and Innovation Ministry of Industry Science Technology & Innovation Phnom Penh Cambodia

ISBN: (纸本)9781665493345

As Information and Communication Technologies (ICT) advances, blockchain can be an enabling technology with potential applications in smart cities to improve their service in waste management and resource efficiency, among others. However, it is imperative to identify the potential barriers to blockchain adoption in smart cities and how they are interrelated to each other. This paper thus proposes a novel T-spherical Neutrosophic Fuzzy Decision Making Trial and Evaluation Laboratory (DEMATEL)-Analytic Network Process (ANP) to analyze the interdependencies and rank of these barriers while capturing the ambiguity and impreciseness of human judgment. An illustrative case study is presented to explore the barriers to blockchain technology adoption to waste management in future smart cities of Cambodia. Findings from such a problematique approach could provide insights for policymakers and accelerate the blockchain implementation in convergence to the creation of smart cities. © 2022 IEEE.

关键词： Decision making

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Evaluating Organization's Portfolio of Long-horizon Strategic Action Plans: An Integrated Delphi-DEMATEL-ANP Approach 14

Evaluating Organization's Portfolio of Long-horizon Strategi...

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14th International Conference on Software, Knowledge, Information Management and Applications, SKIMA 2022

作者： Kuok, Fidero Bong, Angkeara Promentilla, Michael Angelo B. National Institute of Science Technology and Innovation Ministry of Industry Science Technology & Innovation Phnom Penh Cambodia Gokongwei College of Engineering Center for Engineering and Sustainable Development Research De la Salle University Department of Chemical Engineering Manila Philippines

ISBN: (纸本)9781665493345

Strategic foresight allows the organization to adapt and cope with the challenges of the next decade and beyond by revealing internal mental models, encouraging reflection and understanding complexity further on the boundaries of organizational knowledge. This paper thus demonstrates a novel method to facilitate collaborative planning using long-range foresight for an organization. Using the Delphi technique, the proposed method involves the identification of key products, periods of products realization, products dependency and ranking, and the formation of a portfolio of long-horizon strategic action plans that are perceived as achievable within the time horizon of 2030. The prioritization of these actions is then investigated using an integrated Decision Making Trial and Evaluation Laboratory (DEMATEL)-Analytic Network Process (ANP) approach. © 2022 IEEE.

关键词： Decision making

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RuCo alloy nanoparticles embedded within N-doped porous two-dimensional carbon nanosheets:a high-performance hydrogen evolution reaction catalyst

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Tungsten 2024年第1期6卷 114-123页

作者： Jin-Hui Wang Shao-Wei Yang Fu-Bin Ma Yi-Ke Zhao Shi-Nuo Zhao Zheng-Yu Xiong Dong Cai Hai-Dong Shen Kai Zhu Qiu-Yu Zhang Yue-Ling Cao Tian-Shuai Wang He-Peng Zhang Research and Development Institute of Northwestern Polytechnical University in Shenzhen Shenzhen 518057China Xi’an Key Laboratory of Functional Organic Porous Materials School of Chemistry and Chemical EngineeringNorthwestern Polytechnical UniversityXi’an 710129China School of Power and Energy Northwestern Polytechnical UniversityXi’an 710129China Chongqing Science and Technology Innovation Center of Northwestern Polytechnical University Chongqing 401135China

Developing cost-effective electrocatalysts with high activity and stability especially at high current density is of great significance for the large-scale commercial application of electrochemical water splitting to hydrogen production but still remains ***,we report an effective confinement pyrolysis strategy to fabricate embedded ruthenium-cobalt nanoclusters supported on N-doped porous two-dimensional carbon nanosheets(RuCo@CN).Markedly,the embedded structure can effectively prevent the migration,agglomeration,and leaching of nanoparticles,thus endowing the RuCo@CN catalyst with high *** be exact,high stability with up to 650 h can be achieved at high current density(-500 and-1000 mA·cm^(-2)).Besides,the RuCo@CN catalysts also exhibit highly reactive with low overpotentials of only 11mV at-10 mA·cm^(-2).Density functional theory calculations reveal that the introduction of cobalt reduces the decomposition barrier of H_(2)O for RuCo@CN alloy,thus promoting hydrogen evolution reaction.

关键词： Hydrogen evolution reaction Confinement pyrolysis strategy Mosaic structure Stability

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