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2023 IEEE International conference on Mechatronics and Automation, ICMA 2023

2023 IEEE International Conference on Mechatronics and Autom...

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20th IEEE International conference on Mechatronics and Automation, ICMA 2023

ISBN: (纸本)9798350320831

the proceedings contain 412 papers. the topics discussed include: an improved point cloud segmentation method based on multi-scale fusion strategy;pseudo-label assisted optimization of multi-branch network for cross-domain person re-identification;a gesture recognition and drone control system based on residual neural network;research on adaptive density normalized crowd counting algorithm;fatigue analysis of leg structure of a Natatores-like amphibious robot;ASV finite-time-formation control based on an improved extended state observer and saturation functions;research of combined rudder and fin stabilizer control strategy for ship;fixed-time disturbance observer-based cooperative control for multiple dynamic positioning vessels under directed topologies;multi-agent task planning algorithm based on region parameter sharing;and a research of voxel-based amygdala genetic network based on improved label propagation algorithm.

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E-Go Bicycle Intelligent Speed Adaptation system for Catching the Green Light 20th

E-Go Bicycle Intelligent Speed Adaptation System for Catchin...

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20th EAI International conference on Mobile and Ubiquitous systems - Computing Networking and Services (EAI MobiQuitous)

作者： Ben Fredj, Khalil Pallamreddy, Akhil Reddy Heijenk, Geert Havinga, Paul Huang, Yanqiu Univ Twente Ctr Networked Syst & Intelligence NL-7522 NB Enschede Netherlands

ISBN: (纸本)9783031639883;9783031639890

the expanding growth of electric bikes in recent years underscores their increasing importance as a sustainable and eco-friendly mode of transportation. With zero emissions and the ability to ease urban congestion, e-bikes are becoming a pivotal solution in promoting greener and more efficient commuting habits. However, signalized intersections and frequent stops at traffic lights (TL) are considered uncomfortable for cyclists. this article introduces a personalized and privacy-preserving Intelligent Speed Adaption (ISA) system that helps cyclists adapt to the required speed to catch the green light. In our system design, traffic lights are augmented with Bluetooth Low Energy (BLE) beaconing devices which allow connected e-bikes to get the remaining green light phase duration, estimate the distance to the intersection, and assist the cyclist to catch the green light when necessary. We address the speed adaption problem as a convex optimization problem to ensure smooth and safe acceleration. In addition, a fuzzy logic controller is used to control motor power to reach the recommended speed while considering the human pedal power. We generate different scenarios with various initial velocities, time to red (TTR), slope of the road, and human pedal power to evaluate the system's performance. the results demonstrate that ISA improves the probability of crossing the traffic light by about 77% compared to the absence of speed adaptation.

关键词： Smart e-bikes Intelligent Speed Adaptation Privacy Preserving Fuzzy Logic Control Bluetooth Low Energy RSSI distance estimation SPaT

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Isolation Forest Algorithm Against UAV's GPS Spoofing Attack 17

Isolation Forest Algorithm Against UAV's GPS Spoofing Attack

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IEEE Congress on Cybermatics: 17th IEEE International conference on Internet of things, ithings 2024, 20th IEEE International conference on Green Computing and Communications, GreenCom 2024, 17th IEEE International conference on Cyber, Physical and Social Computing, CPSCom 2024, 10th IEEE International conference on Smart Data, SmartData 2024

作者： Mohammed, Ahmed Burhan Chaari Fourati, Lamia Fakhrudeen, Ahmed M. ENET'Com Sfax University Sfax Tunisia SM@RTS Laboratory Tunisia University of Kirkuk College of Csit Kirkuk Iraq

ISBN: (纸本)9798350351637

Nowadays, Unmanned Aerial Vehicle (UAV) platforms are a valuable source of data for inspection, surveillance, mapping, and 3D modeling issues. Embedded electronic and communication systems within UAVs are based on the integration of the Internet of things (IoT) into UAV systems (commonly called the Internet of Drone things (IoDT)). Nevertheless, the vulnerability of this interconnected environment to malicious activities, such as GPS spoofing, threatens the dependability and security of UAV operations. To countermeasure this challenging issue, this article uses an effective anomaly detection method, the Isolation Forest algorithm, for mitigating GPS spoofing threats. A well-curated dataset specifically targeting the detection of GPS deception in UAVs has been utilized. Extensive experiments were conducted to compare our proposal with its counterparts (Random Forest and Naive Bayes). the experimental outcomes demonstrate the Isolation Forest algorithm's efficiency in anomaly detection, attaining a noteworthy accuracy rate of (95.85%). However, Random Forest and Naive Bayes achieved (93.63%) and (92.38%), respectively. Other performance evaluation metrics show that the Isolation Forest works better than others, which supports its potential as a reliable way for anomaly detection when GPS spoofing happens in UAVs. the insight obtained from this research can provide valuable input for creating proactive security protocols to guarantee the secure implementation and functioning of UAVs. © 2024 IEEE.

关键词： Global positioning system

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Towards the optimization of Speculative PDES Platforms in Shared-Memory Multi-core Machines 20th

Towards the Optimization of Speculative PDES Platforms in...

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Proceedings of the 20th European conference on Multi-Agent systems, EUMAS 2023

作者： Montesano, Federica University of Rome Tor Vergata Rome Italy

ISBN: (纸本)9783031432637

Speculative parallel discrete event simulation on shared-memory machines has become a hot field to study due to its exploitation of massively parallel computing systems. this paper reviews various aspects taken into account during the first two year of the PhD, believing in their relevance also in the context of agent-based simulation. In particular, it first focuses on memory-awareness to improve performance of speculative PDES platforms, it then introduces a new incremental state saving mechanism leveraging operating system’s services and finally it describes a way of collecting a global committed state during run-time execution with minimum delay. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Memory architecture

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Application of the conditional optimization method in the problem of vessel stormy sailing 12

Application of the conditional optimization method in the pr...

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12th International Scientific and Practical conference "Information Control systems and Technologies", ICST 2024

作者： Zinchenko, Serhii Tovstokoryi, Oleh Mateichuk, Vadym Nosov, Pavlo Popovych, Ihor Kyrychenko, Kostiantyn Kherson state maritime academy 20 Ushakova ave. Kherson73000 Ukraine Kherson state university 27 Universytetska str. Kherson73003 Ukraine

Stormy sailing conditions are among the most extreme and dangerous. the rocking of the ship in the roll and trim channels greatly exhausts the crew, which leads to an increase in the number of errors when making management decisions. the situation worsens also due to the fact that during a storm such dangerous phenomena as harmonic and parametric resonances, a decrease in stability on passing waves, broaching, impacts of group waves in the stern, which can lead to the ship's capsizing, hull destruction, overloads of the power plant and occurrence of blackouts. the most radical way to combat such dangers is the automation of control processes. the authors have developed a method of automatic and optimal control of the ship's movement in storm conditions, which allows to avoid the occurrence and development of dangerous phenomena that lead to the capsize of the ship. the obtained result is explained by: the use of an on-board computer in the ship's motion control system;constant measurement of ship movement parameters and waves;finding, at each step of the on-board computer, safe and optimal values of the ship's course and speed by solving the optimization problem;taking into account when solving the optimization problem linear and non-linear constraints of the type of inequalities that define dangerous areas;maintaining safe and optimal movement parameters using the automatic control system. the theoretical significance of the obtained result lies in the development of a method of automatic and optimal control of the ship's movement in conditions of stormy sailing. the practical significance of the obtained results consists in: verification of the developed method by mathematical modeling;the possibility of using the method in the automatic control system, which allows to automate and optimize the processes of controlling a ship in a storm, reduce the influence of the human factor on control processes, crew fatigue, risks of losing the ship and cargo, and generally i

关键词： Broaching

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A Conceptual Framework for Production Process Parameter optimization with Modular Hybrid Simulations

A Conceptual Framework for Production Process Parameter Opt...

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Workshops on AI4EA, F-IDE, CoSim-CPS, CIFMA 2022, Collocated with the 20th International conference on Software Engineering and Formal Methods, SEFM 2022

作者： Olbrych, Sylwia Kemmerling, Marco Zhou, Hans Aoyang Lütticke, Daniel Schmitt, Robert H. RWTH Aachen University Aachen Germany

ISBN: (纸本)9783031262357

Optimizing the parameters of a manufacturing process is a time-consuming task requiring a series of experiments involving different parameter combinations. To alleviate this difficulty, we propose a conceptual framework for data-driven parameter optimization in production processes, which allows for virtual parameter tuning. To provide an insight into the practical application of our general method, we additionally explore its use on the example of lithium-ion battery (LIB) production. Our framework consists of two components: a modular hybrid simulation and an optimization tool. In the first component, the place of traditional process models is taken by a set of machine learning (ML) models which aim to imitate the behaviour of each process step. these individual models are trained on collected process data and connected in a modular simulation framework. While the resulting system already allows for manual exploration of parameter combinations, the introduction of an optimization tool unlocks further benefits. the proposed modular approach is independent of the production process type, therefore it can be applied to various manufacturing fields. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： optimization

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DComFra Project Learning Module M20 "Advanced Spreadsheets" in Mathematical modeling Tasks of Electrical and Computer Engineers Education 20

DComFra Project Learning Module M20 "Advanced Spreadsheets" ...

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20th IEEE International conference on Modern Electrical and Energy systems, MEES 2021

作者： Guchenko, Mykola Sydorenko, Valeriy Belska, Vikroriya Yudina, Anna Liutenko, Mariia Fesenko, Nataliia Kremenchuk Mykhailo Ostrohradskyi National University Department of Computer and Information Systems Kremenchuk Ukraine Kremenchuk Mykhailo Ostrohradskyi National University Kremenchuk Ukraine

ISBN: (纸本)9781665423663

the necessity of wide application of mathematical modeling in the electrical engineers' education is stated. It is shown that a simple and affordable mean of modeling electrical networks, alternative to specialized software packages, is the MS Excel spreadsheet processor. the abilities of the processor at the example of some optimization problems solution in electrical networks are shown. © 2021 IEEE.

关键词： optimization

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A Nonlinear Autonomous Boundary Value Problem for a Non-Degenerate Differential-Algebraic system 20

A Nonlinear Autonomous Boundary Value Problem for a Non-Dege...

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20th International Scientific conference on Dynamical system modeling and Stability Investigation, DSMSI 2023

作者： Khusainov, Denys Chuiko, Sergey Nesmelova, Olga Diachenko, Daria Taras Shevchenko National University of Kyiv Volodymyrska St 60 Kyiv Ukraine Donbass State Pedagogical University Donetsk region Slavyansk st. General Batyuk 19 Slaviansk 84 116 Ukraine Max Planck Institute for Dynamics of Complex Technical Systems Sandtorstrasse 1 Magdeburg39106 Germany Institute of Applied Mathematics and Mechanics of the NAS of Ukraine st. General Batyuk 19 Slaviansk 84 116 Ukraine

We have found the constructive necessary and sufficient conditions for solvability and the scheme for constructing solutions of a nonlinear autonomous boundary value problem for a nondegenerate differential-algebraic system. the nonlinear boundary value problem for the autonomous system significantly differs from similar autonomous boundary value problems by its dependence on an arbitrary continuous vector function. We have also constructed a convergent iterative scheme for finding approximate solutions of the nonlinear autonomous boundary value problem for the nondegenerate differential-algebraic system in critical and noncritical cases. Proposed in this paper scheme for studying the nonlinear autonomous boundary value problem for the nondegenerate system of differential-algebraic equations can be transferred to degenerate systems of differential-algebraic equations in the same way. © 2023 Copyright for this paper by its authors.

关键词： Iterative methods

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Kernel-Based Particle Filtering for Scalable Inference in Partially Observed Boolean Dynamical systems 20

Kernel-Based Particle Filtering for Scalable Inference in Pa...

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20th IFAC Symposium on system Identification (SYSID)

作者： Alali, Mohammad Imani, Mahdi Northeastern Univ Dept Elect & Comp Engn Boston MA 02115 USA

this paper addresses the inference challenges associated with a class of hidden Markov models with binary state variables, known as partially observed Boolean dynamical systems (POBDS). POBDS have demonstrated remarkable success in modeling the ON and OFF dynamics of genes, microbes, and bacteria in systems biology, as well as in network security to represent the propagation of attacks among interconnected elements. Despite existing optimal and approximate inference solutions for POBDS, scalability remains a significant issue due to the computational cost associated with likelihood evaluations and the exploration of extensive parameter spaces. To overcome these challenges, this paper proposes a kernel-based particle filtering approach for large-scale inference of POBDS. Our method employs a Gaussian process (GP) to efficiently represent the expensive-to-evaluate likelihood function across the parameter space. the likelihood evaluation is approximated using a particle filtering technique, enabling the GP to account for various sources of uncertainty, including limited likelihood evaluations. Leveraging the GP's predictive behavior, a Bayesian optimization strategy is derived for effectively seeking parameters yielding the highest likelihood, minimizing the overall computational burden while balancing exploration and exploitation. the proposed method's performance is demonstrated using two biological networks: the mammalian cell-cycle network and the T-cell large granular lymphocyte leukemia network. Copyright (c) 2024 the Authors.

关键词： Inference Bayesian optimization Particle Filters Partially-Observed Boolean Dynamical systems Biological Networks

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Modelling the Transformation of Hydrogen Ecosystems via Geo-Techno-Economic optimization

Modelling the Transformation of Hydrogen Ecosystems via Geo-...

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International conference on European Electricity Market, EEM

作者： Friedrich Mendler Nikolas Müller Christopher Voglstätter Tom Smolinka Christopher Hebling Barbara Koch Chair of Remote Sensing and Landscape Information Systems University of Freiburg Freiburg Germany Division Hydrogen Technologies Fraunhofer Institute for Solar Energy Systems Freiburg Germany

ISBN: (数字)9798350381740

ISBN: (纸本)9798350381757

A newly developed framework for spatially resolved optimization of hydrogen systems is presented. It enables realistic representation of the whole value chain with different electricity sources and transport technologies that are optimized for every location and connection. the nonlinear structure enables realistic physical properties and economies of scale but increases the difficulties in parametrization of the system and optimization algorithm. three scenarios have been modelled to analyze the influence of electricity and hydrogen import options. Using grid electricity to increase electrolyzer full load hours and reduce storage requirements enables significant economic advantageous. Furthermore, for the selected study region, hydrogen transport is cheaper than electricity transmission as trailers can be shared within the region and pipelines installed to supply large demands. therefore, electrolyzers are primarily installed at site of high potential for renewable electricity generation.

关键词： Electric potential Renewable energy sources Costs Sensitivity Electricity Biological system modeling Hydrogen

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