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AIAA Guidance, Navigation, and Control Conference, 2018

作者： Van Ekeren, Wim Looye, Gertjan Kuchar, Richard Chu, Qiping Van Kampen, Erik-Jan Delft University of Technology P.O. Box 5058 Delft2626HS Netherlands DLR German Aerospace Center Weßling82234 Germany Faculty of Aerospace Engineering Control and Simulation Division Delft University of Technology Netherlands Department of Aircraft Systems Dynamics Institute of System Dynamics and Control German Aerospace Center Germany

ISBN: (纸本)9781624105265

This paper presents the design and implementation of incremental backstepping (IBS) flight control laws for the attitude control and stabilization on a fixed-wing aircraft. The design consists of multiple functionalities such as command-filtered backstepping, angle of attack control and body attitude control, that are based around an incremental control inner loop that tracks the angular rates of the aircraft. The results include flight data of an integrated IBS design that validate simulation results of control laws shown previously in literature. The results show that it is possible to implement robust nonlinear flight control laws that are easy to tune and require only little knowledge about the system dynamics parameters. © 2018, American institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Fixed wings

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Design and flight testing of incremental nonlinear dynamic inversion based control laws for a passenger aircraft

Design and flight testing of incremental nonlinear dynamic i...

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AIAA Guidance, Navigation, and Control Conference, 2018

作者： Grondman, Fabian Looye, Gertjan H. N. Kuchar, Richard O. Chu, Q. Ping van Kampen, Erik-Jan German Aerospace Center DLR Münchener Straße 20 Weßling82234 Germany Delft University of Technology P.O. Box 5058 Delft2626HS Netherlands Faculty of Aerospace Engineering Control and Simulation Division Delft University of Technology Netherlands Department of Aircraft Systems Dynamics Institute of System Dynamics and Control German Aerospace Institute Germany

ISBN: (数字)9781624105265

ISBN: (纸本)9781624105265

This paper describes the design, implementation and flight testing of flight control laws based on Incremental Nonlinear Dynamic Inversion (INDI). The method compares com- manded and measured accelerations to compute increments on the current control de ec- tions. This results in highly robust control solutions with respect to model uncertainties as well as changes in aircraft dynamic characteristics of failure cases during flight. At the same time, the complexity of the algorithms is similar to classical ones. The key for practical implementation is in ensuring synchronization between angular acceleration and control de ection measurements or estimates. This paper describes the design and vali- dation of manual attitude control functions for a Cessna Citation II experimental aircraft, covering control structure design, application of INDI, design optimization, robustness analyses, software implementation, ground and flight testing. For comparison, also control laws based on classical Nonlinear Dynamic Inversion were implemented and flown. The flight tests were highly successful and marked the first successful demonstration of INDI on a CS-25 certified aircraft. The flight test results proved that INDI clearly outperforms NDI and provided valuable lessons-learnt for future applications. © 2018, American institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Attitude control

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Evolution of the European concurrent design tool for space-based system-of-systems studies

Evolution of the European concurrent design tool for space-b...

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AIAA SPACE Conference and Exposition, 2015

作者： Braukhane, Andy Bieler, Torsten De Koning, Hans-Peter Richardson, Ray Schaus, Volker Stoitsev, Todor Institute of Space Systems System Analysis Space Segment Robert-Hooke-Str. 7 Bremen Germany European Space Research and Technology Centre Software and In-Orbit Demonstration Department Keplerlaan 1 Noordwijk Netherlands Daysha Consulting 9 Mount Street Crescent Dublin 2 Ireland Institute of Simulation and Software Technology Software for Space Systems and Interactive Visualization Lilienthalplatz 1 Braunschweig38108 Germany Telespazio-Vega Deutschland Europaplatz 5 Darmstadt64293 Germany

ISBN: (数字)9781624103346

ISBN: (纸本)9781624103346

One major element in Concurrent Design is the central data model. It allows the various disciplines to share the latest information and to make immediate use of them within their domain specific tools and models. As a successor of the Integrated Design Model, in 2014 the European Space Agency (ESA) released the Open Concurrent Design Tool (OCDT), which aims to be the reference and standard model for European entities performing space system studies during early as well as later phases. This tool, including its web-based server and user interface supporting elements (such as MS Excel Add-ins), is developed in a way that it is not only limited to space system and mission design, but can be used also in other fields such as system-of-systems (SoS) architecture definition and evaluation, which is becoming an emerging topic for European and international collaborations. Instead of just looking at the technical aspects of a system, SoS-studies provide an opportunity to analyze how to share resources and assets amongst institutions, organizations or nations more efficiently and how to provide integrated and more advanced services. However, due to the different nature and rules of SoS, the OCDT requires certain adaptations regarding domain specific tool interfaces, dedicated data libraries, as well as a SoS-specific data flow and representations to the users. Several studies were performed on ESA’s side in advance, to prepare an initial set of requirements for such an evolution of the tools and processes which eventually led to a project called "Development and Validation of a Generic systems‐of‐systems Concurrent Engineering Model (CESoS)". It has been established by ESA and awarded to a consortium which has experience in Concurrent Design, software development and system architecture definitions. © 2015, American institute of Aeronautics and Astronautics Inc, AIAA. All Rights Reserved.

关键词： Software design

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Earlier peak photosynthesis timing potentially escalates global wildfires

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National Science Review 2024年第09期11卷 171-180页

作者： Gengke Lai Jialing Li Jun Wang Chaoyang Wu Yongguang Zhang Constantin M.Zohner Josep Pe?uelas Quansheng Ge International Institute for Earth System Sciences Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing University Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural ResourcesSchool of Geography and Ocean Science Nanjing University The Key Laboratory of Land Surface Pattern and Simulation Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Huangshan National Park Ecosystem Field Scientific Observation and Research Station of the Ministry of Education Jiangsu International Joint Carbon Neutrality Laboratory Nanjing University Department of Environmental Systems Science Institute of Integrative BiologyETH Zurich CSIC Global Ecology Unit CREAF-CSIC-UAB CREAF Cerdanyola del Vallès

More intense fire weather due to climate change is implicated as a key driver of recent extreme wildfire events. As fuel stock, the role of vegetation and its phenology changes in wildfire dynamics, however is not fully appreciated. Using long-term satellite-based burned areas and photosynthesis observations, we reveal that an earlier peak photosynthesis timing(PPT) potentially acts to escalate subsequent wildfires, with an increase in the global average burned fraction of 0.021%(～2.20 Mha) for every additional day of PPT advancement. Satellite observations and Earth system modeling consistently show that this fire escalation is likely due to intensified drought conditions and increased fuel availability associated with the climate feedback arising from earlier PPT. Current fire-enabled dynamic global vegetation models can reproduce the observed negative correlation between PPT and burned area but underestimate the strength of the relationship notably. Given the continued PPT advancement owing to climate change, the bioclimatic effects of vegetation phenology change suggest a potentially pervasive upward pressure on future wildfires.

关键词： vegetation photosynthesis phenology wildfire climate feedback Earth system model

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Empirical estimates of regional carbon budgets imply reduced global soil heterotrophic respiration

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National Science Review 2021年第2期8卷 60-73页

作者： Philippe Ciais Yitong Yao Thomas Gasser Alessandro Baccini Yilong Wang Ronny Lauerwald Shushi Peng Ana Bastos Wei Li Peter A.Raymond Josep G.Canadell Glen P.Peters Rob J.Andres Jinfeng Chang Chao Yue A.Johannes Dolman Vanessa Haverd Jens Hartmann Goulven Laruelle Alexandra G.Konings Anthony W.King Yi Liu Sebastiaan Luyssaert Fabienne Maignan Prabir K.Patra Anna Peregon Pierre Regnier Julia Pongratz Benjamin Poulter Anatoly Shvidenko Riccardo Valentini Rong Wang Grégoire Broquet Yi Yin Jakob Zscheischler Bertrand Guenet Daniel S.Goll Ashley-P.Ballantyne Hui Yang Chunjing Qiu Dan Zhu State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau Northwest A&F University CSIRO Oceans and Atmosphere 15. Institute for Geology CEN—Center for Earth System Research and SustainabilityUniversity of Hamburg 16. Department of Earth System ScienceStanford University 17. Department of Earth System ScienceStanford UniversityStanford 18. School of Geographical SciencesNanjing University of Information Science and Technology 19. Department of Ecological SciencesVrije Universiteit Amsterdam 20. Research Institute for Global ChangeJAMSTEC Laboratoire des Sciences du Climat et de l'Environnement CEA-CNRS-UVSQ-UPSACLAY Center for Environmental Remote Sensing Chiba University Institute of Soil Science and Agrochemistry Siberian Branch of the Russian Academy of Sciences (SB RAS) Tuva State University Republic of Tuva Max Planck Institute for Meteorology NASA Goddard Space Flight Center Biospheric Sciences Lab. 26. Department for Innovation in BiologicalAgro-food and Forest systems (DIBAF)University of Tuscia RUDN University Department of Environmental Science and Engineering Shanghai Key Laboratory of Atmospheric Particle Pollution and PreventionInstitute of Atmospheric SciencesFudan University 29. Division of Geological and Planetary SciencesCalifornia Institute of Technology 30. Climate and Environmental Physics and Oeschger Centre for Climate Change ResearchUniversity of Bern 31. Department of Ecosystem and Conservation Sci

Resolving regional carbon budgets is critical for informing land-based mitigation policy. For nine regions covering nearly the whole globe, we collected inventory estimates of carbon-stock changes complemented by satellite estimates of biomass changes where inventory data are missing. The net land–atmospheric carbon exchange(NEE) was calculated by taking the sum of the carbon-stock change and lateral carbon fluxes from crop and wood trade, and riverine-carbon export to the ocean. Summing up NEE from all regions, we obtained a global ‘bottom-up’ NEE for net land anthropogenic CO2uptake of –2.2 ± 0.6 Pg C yr-1consistent with the independent top-down NEE from the global atmospheric carbon budget during 2000–2009. This estimate is so far the most comprehensive global bottom-up carbon budget accounting, which set up an important milestone for global carbon-cycle studies. By decomposing NEE into component fluxes, we found that global soil heterotrophic respiration amounts to a source of CO2of 39 Pg C yr-1with an interquartile of 33–46 Pg C yr-1—a much smaller portion of net primary productivity than previously reported.

关键词： carbon budget human appropriation of ecosystems soil carbon

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Hybrid Dipper Throated and Grey Wolf Optimization for Feature Selection Applied to Life Benchmark Datasets

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Computers, Materials & Continua 2023年第2期74卷 4531-4545页

作者： Doaa Sami Khafaga El-Sayed M.El-kenawy Faten Khalid Karim Mostafa Abotaleb Abdelhameed Ibrahim Abdelaziz A.Abdelhamid D.L.Elsheweikh Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Department of System Programming South Ural State UniversityChelyabinsk454080Russia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Department of Computer Science Faculty of Specific EducationMansoura UniversityEgypt

Selecting the most relevant subset of features from a dataset is a vital step in data mining and machine *** feature in a dataset has 2n possible subsets,making it challenging to select the optimum collection of features using typical *** a result,a new metaheuristicsbased feature selection method based on the dipper-throated and grey-wolf optimization(DTO-GW)algorithms has been developed in this *** can result when the selection of features is subject to metaheuristics,which can lead to a wide range of ***,we adopted hybrid optimization in our method of optimizing,which allowed us to better balance exploration and harvesting chores more *** propose utilizing the binary DTO-GW search approach we previously devised for selecting the optimal subset of *** the proposed method,the number of features selected is minimized,while classification accuracy is *** test the proposed method’s performance against eleven other state-of-theart approaches,eight datasets from the UCI repository were used,such as binary grey wolf search(bGWO),binary hybrid grey wolf,and particle swarm optimization(bGWO-PSO),bPSO,binary stochastic fractal search(bSFS),binary whale optimization algorithm(bWOA),binary modified grey wolf optimization(bMGWO),binary multiverse optimization(bMVO),binary bowerbird optimization(bSBO),binary hysteresis optimization(bHy),and binary hysteresis optimization(bHWO).The suggested method is superior 4532 CMC,2023,vol.74,no.2 and successful in handling the problem of feature selection,according to the results of the experiments.

关键词： Metaheuristics dipper throated optimization grey wolf optimization binary optimizer feature selection

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Using Natural Version Redundancy of FPGA Projects in Area of Critical Applications

Using Natural Version Redundancy of FPGA Projects in Area of...

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IEEE International Conference on Dependable systems, Services and Technologies (DESSERT)

作者： Oleksandr Drozd Vitaliy Romankevich Mykola Kuznietsov Myroslav Drozd Oleksandr Martynyuk Department of Computer Intelligent Systems and Networks Odessa National Polytechnic University Odessa Ukraine System programming and specialized computer systems National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute" Kyiv Ukraine Department of Information Systems Odessa National Polytechnic University Odessa Ukraine

ISBN: (数字)9781728199573

ISBN: (纸本)9781728199580

The paper focuses on the role of version redundancy, which increases with the expansion of critical applications and the tightening of their functional safety requirements. International standards governing these requirements have already fixed the importance of version redundancy to counter common cause failures in safety-related systems. The problem of hidden faults inherent in these systems is equally acute, undermining confidence in the fault tolerance of circuit solutions important for functional safety. We suggest that this problem be seen as a growth problem where the system rises to the level of diversification in modes of operation by dividing them into normal and emergency and checkability circuits, but components continue to be stamped at a lower level of replication. Then the solution to the problem is to raise the components to the level of the system by developing their version redundancy. We demonstrate this development for FPGA components with LUT-oriented architecture and offer a method to improve the FPGA-ready project by natural version redundancy of its program code. The method generates a set of program code versions and selects versions that improve the checkability of circuits with respect to constant faults and the trustworthiness of results, respectively, in normal and emergency mode to reduce a set of hidden faults. The method is illustrated by an iterative array multiplier implemented in an FPGA project. Versions are generated, evaluated, and selected using the program developed for this.

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Data Poisoning: Issues, Challenges, and Needs 7

Data Poisoning: Issues, Challenges, and Needs

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7th IET Smart Cities Symposium, SCS 2023

作者： Aljanabi, Mohammad Omran, Alaa Hamza Mijwil, Maad M. Abotaleb, Mostafa El-Kenawy, El-Sayed M. Mohammed, Sahar Yousif Ibrahim, Abdelhameed Department of computer College of Education Aliarqai university Baghdad Iraq University of information technology and communications Baghdad Iraq Computer Techniques Engineering Department Baghdad College of Economic Sciences University Baghdad Iraq Department of System Programming South Ural State University Chelyabinsk Russia Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Egypt Computer Science Department Computer Science &Information Technology College Anbar University Anbar Iraq Computer Engineering and Control Systems Department Faculty of Engineering Mansoura University Mansoura Egypt

ISBN: (纸本)9781839539831

Data poisoning attacks, where adversaries manipulate training data to degrade model performance, are an emerging threat as machine learning becomes widely deployed in sensitive applications. This paper provides a comprehensive overview of data poisoning including attack techniques, adversary incentives, impacts on security and reliability, detection methods, defenses, and key research gaps. We examine label flipping, instance injection, backdoors, and other attack categories that enable malicious outcomes ranging from IP theft to accidents in autonomous systems. Promising detection approaches include statistical tests, robust learning, and forensics. However, significant challenges remain in translating academic defenses like adversarial training and sanitization into practical tools ready for operational use. With safety and trustworthiness at stake, more research on benchmarking evaluations, adaptive attacks, fundamental tradeoffs, and real-world deployment of defenses is urgently needed. Understanding vulnerabilities and developing resilient machine learning pipelines will only grow in importance as data integrity is fundamental to developing safe artificial intelligence. © The Institution of Engineering & Technology 2023.

关键词： Machine learning

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Network Intrusion Detection Based on Feature Selection and Hybrid Metaheuristic Optimization

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Computers, Materials & Continua 2023年第2期74卷 2677-2693页

作者： Reem Alkanhel El-Sayed M.El-kenawy Abdelaziz A.Abdelhamid Abdelhameed Ibrahim Manal Abdullah Alohali Mostafa Abotaleb Doaa Sami Khafaga Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Information Systems Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of System Programming South Ural State UniversityChelyabinsk454080Russia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

Applications of internet-of-things(IoT)are increasingly being used in many facets of our daily life,which results in an enormous volume of *** computing and fog computing,two of the most common technologies used in IoT applications,have led to major security *** are on the rise as a result of the usage of these technologies since present security measures are *** artificial intelligence(AI)based security solutions,such as intrusion detection systems(IDS),have been proposed in recent *** technologies that require data preprocessing and machine learning algorithm-performance augmentation require the use of feature selection(FS)techniques to increase classification accuracy by minimizing the number of features *** the other hand,metaheuristic optimization algorithms have been widely used in feature selection in recent *** this paper,we proposed a hybrid optimization algorithm for feature selection in *** proposed algorithm is based on grey wolf(GW),and dipper throated optimization(DTO)algorithms and is referred to as *** proposed algorithm has a better balance between the exploration and exploitation steps of the optimization process and thus could achieve better *** the employed IoT-IDS dataset,the performance of the proposed GWDTO algorithm was assessed using a set of evaluation metrics and compared to other optimization approaches in 2678 CMC,2023,vol.74,no.2 the literature to validate its *** addition,a statistical analysis is performed to assess the stability and effectiveness of the proposed *** results confirmed the superiority of the proposed approach in boosting the classification accuracy of the intrusion in IoT-based networks.

关键词： Feature selection grey wolf optimization dipper throated optimization intrusion detection internet-of-things(IoT)

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Hybrid Grey Wolf and Dipper Throated Optimization in Network Intrusion Detection systems

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Computers, Materials & Continua 2023年第2期74卷 2695-2709页

作者： Reem Alkanhel Doaa Sami Khafaga El-Sayed M.El-kenawy Abdelaziz A.Abdelhamid Abdelhameed Ibrahim Rashid Amin Mostafa Abotaleb B.M.El-den Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Computer Science University of Engineering and TechnologyTaxilaPakistan Department of System Programming South Ural State UniversityChelyabinsk454080Russia

The Internet of Things(IoT)is a modern approach that enables connection with a wide variety of devices *** to the resource constraints and open nature of IoT nodes,the routing protocol for low power and lossy(RPL)networks may be vulnerable to several routing ***’s why a network intrusion detection system(NIDS)is needed to guard against routing assaults on RPL-based IoT *** imbalance between the false and valid attacks in the training set degrades the performance of machine learning employed to detect network ***,we propose in this paper a novel approach to balance the dataset classes based on metaheuristic optimization applied to locality-sensitive hashing and synthetic minority oversampling technique(LSH-SMOTE).The proposed optimization approach is based on a new hybrid between the grey wolf and dipper throated optimization *** prove the effectiveness of the proposed approach,a set of experiments were conducted to evaluate the performance of NIDS for three cases,namely,detection without dataset balancing,detection with SMOTE balancing,and detection with the proposed optimized LSHSOMTE *** results showed that the proposed approach outperforms the other approaches and could boost the detection *** addition,a statistical analysis is performed to study the significance and stability of the proposed *** conducted experiments include seven different types of attack cases in the RPL-NIDS17 *** on the 2696 CMC,2023,vol.74,no.2 proposed approach,the achieved accuracy is(98.1%),sensitivity is(97.8%),and specificity is(98.8%).

关键词： Metaheuristics grey wolf optimization dipper throated optimization dataset balancing locality sensitive hashing SMOTE

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