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Leveraging Instruction-based Learning for Effective UAV Traffic Management in Dynamic Environment

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Leveraging Instruction-based Learning for Effective UAV Traf...

Multi-Agent Systems for Collaborative Intelligence (ICMSCI), International Conference on

作者： R.S. Ramya Keren Lois Daniel S. Rajkumar Sruthi S Madhavan Akshya. J Mani Deepak Choudhry Department of Computer Science and Engineering Sri Ramakrishna Engineering College Coimbatore Department of Computer Science and Business Systems KGiSL Institute of Technology Coimbatore Department of Information Technology Sona College of Technology Salem Department of Artificial Intelligence and Data Science Nehru Institute of Engineering and Technology Coimbatore Department of Computational Intelligence SRM Institute of Science and Technology Chennai Department of Computing Technologies SRM Institute of Science and Technology Chennai

ISBN: (数字)9798331509828

ISBN: (纸本)9798331509835

With the popularization of UAVs (Unmanned Aerial Vehicles) in surveillance, delivery services, environmental monitoring, and increasingly other operational aspects, besides the need to take off and land, efficient traffic management becomes integral for assuring and securing further development and exploitation. Most of the existing traffic management systems for UAVs depend on traditional rule-based algorithms or simpler machine learning techniques, such as DQN or PPO. However, these systems also have enormous challenges: dynamic environments, high-density traffic, and robust decision-making over unpredictable weather and network conditions. In addition, the above traditional models usually experience difficulties in balancing exploration and exploitation, leading to suboptimal routing and enlarged collision risks in complicated urban airspaces. These challenges have driven us to develop a new proposal: a UA V traffic management framework based on Double Deep Q-Network (DDQN) combined with Instruction-Based Learning. In this approach, advanced learning for DDQN optimizes processes at decision-making points for UAVs. The model proposed herein, along with comprehensive simulations and quantitative analyses, demonstrated higher performance in terms of leadership and cumulative rewards while keeping lower training loss compared to the classical algorithms such as DQN, A3C, and PPO. At the same time, the DDQN model presented a better success rate (95%), as also reflected in the balanced precision-recall curve showing an area under the curve of 0.90, over others in the on-point prediction of UAVstate and safety margin of collision. Our experimental results demonstrate that the proposed DDQN-based framework significantly enhances UA V traffic management by optimizing energy consumption in complex airspaces and reducing the risk of collision.

关键词： Training Analytical models Adaptation models Statistical analysis Atmospheric modeling computational modeling Decision making Predictive models Autonomous aerial vehicles Safety

A BROKEN HARDY INEQUALITY ON FINITE ELEMENT SPACE AND APPLICATION TO STRAIN GRADIENT ELASTICITY

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arXiv 2025年

作者： Liao, Yulei Ming, Pingbing Department of Mathematics Faculty of Science National University of Singapore 10 Lower Kent Ridge Road Singapore119076 Singapore LSEC Institute of Computational Mathematics and Scientific/Engineering Computing AMSS Chinese Academy of Sciences Beijing100190 China School of Mathematical Sciences University of Chinese Academy of Sciences Beijing100049 China

We illustrate a broken Hardy inequality on discontinuous finite element spaces, blowing up with a logarithmic factor with respect to the meshes size. This is motivated by numerical analysis for the strain gradient elasticity with natural boundary conditions. A mixed finite element pair is employed to solve this model with nearly incompressible materials. This pair is quasi-stable with a logarithmic factor, which is not significant in the approximation error, and converges robustly in the incompressible limit and uniformly in the microscopic material parameter. Numerical results back up that the theoretical predictions are nearly optimal. Moreover, the regularity estimates for the model over a smooth domain have been proved with the aid of the Agmon-Douglis-Nirenberg theory. Copyright © 2025, The Authors. All rights reserved.

关键词： Set theory

A Comunication Framework for Compositional Generation

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arXiv 2025年

作者： Elberg, Rafael Petrache, Mircea Parra, Denis Department of Computer Science PUC Chile Centro Nacional de Inteligencia Artificial CenIA Chile Department of Mathematics PUC Chile Institute for Mathematical and Computational Engineering PUC Chile

Compositionality and compositional generalization—the ability to understand novel combinations of known concepts—are central characteristics of human language and are hypothesized to be essential for human cognition. In machine learning, the emergence of this property has been studied in a communication game setting, where independent agents (a sender and a receiver) converge to a shared encoding policy from a set of states to a space of discrete messages, where the receiver can correctly reconstruct the states observed by the sender using only the sender’s messages. The use of communication games in generation tasks is still largely unexplored, with recent methods for compositional generation focusing mainly on the use of supervised guidance (either through class labels or text). In this work, we take the first steps to fill this gap, and we present a self-supervised generative communication game-based framework for creating compositional encodings in learned representations from pre-trained encoder-decoder models. In an Iterated Learning (IL) protocol involving a sender and a receiver, we apply alternating pressures for compression and diversity of encoded discrete messages, so that the protocol converges to an efficient but unambiguous encoding. Approximate message entropy regularization is used to favor compositional encodings. Our framework is based on rigorous justifications and proofs of defining and balancing the concepts of Eficiency, Unambiguity and Non-Holisticity in encoding. We test our method on the compositional image dataset Shapes3D, demonstrating robust performance in both reconstruction and compositionality metrics, surpassing other tested discrete message frameworks. © 2025, CC BY.

关键词： Encoding (symbols)

Joint Design of Radar Receive Filter and Unimodular ISAC Waveform with Sidelobe Level Control

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arXiv 2025年

作者： Zhang, Kecheng Liu, Ya-Feng Wang, Zhongbin Yuan, Weijie Keskin, Musa Furkan Wymeersch, Henk Xia, Shuqiang School of System Design and Intelligent Manufacturing The Shenzhen Key Laboratory of Robotics and Computer Vision Southern University of Science and Technology Shenzhen518055 China State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China Department of Electrical Engineering Chalmers University of Technology Gothenburg41296 Sweden ZTE Corporation The State Key Laboratory of Mobile Network and Mobile Multimedia Technology Shenzhen518055 China

Integrated sensing and communication (ISAC) has been considered a key feature of next-generation wireless networks. This paper investigates the joint design of the radar receive filter and dual-functional transmit waveform for the multiple-input multiple-output (MIMO) ISAC system. While optimizing the mean square error (MSE) of the radar receive spatial response and maximizing the achievable rate at the communication receiver, besides the constraints of full-power radar receiving filter and unimodular transmit sequence, we control the maximum range sidelobe level, which is often overlooked in existing ISAC waveform design literature, for better radar imaging performance. To solve the formulated optimization problem with convex and nonconvex constraints, we propose an inexact augmented Lagrangian method (ALM) algorithm. For each subproblem in the proposed inexact ALM algorithm, we custom-design a block successive upper-bound minimization (BSUM) scheme with closed-form solutions for all blocks of variable to enhance the computational efficiency. Convergence analysis shows that the proposed algorithm is guaranteed to provide a stationary and feasible solution. Extensive simulations are performed to investigate the impact of different system parameters on communication and radar imaging performance. Comparison with the existing works shows the superiority of the proposed algorithm. © 2025, CC BY-NC-SA.

关键词： Mean square error

Augmented reality for area measurement reasoning of elementary students

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Educational Technology Research and Development 2025年 1-35页

作者： Flavin, Eunhye Chung, Moon Hwang, Sunghwan Flavin, Matthew T. Center for Education Integrating Science Mathematics and Computing Georgia Institute of Technology 505 10th St NW Atlanta 30332 GA United States Department of Education Studies Stonehill College 320 Washington Street North Easton 02322 MA United States Department of Mathematics Education Chuncheon National University of Education 126 Gongji-ro Gangwon-do Chuncheon-si South Korea School of Electrical and Computer Engineering Georgia Institute of Technology 777 Atlantic Dr NW Atlanta 30309 GA United States

Area measurement is a foundational component across STEM fields. The area formula offers limited insight for children trying to develop their area measurement reasoning skills, particularly when dealing with composite shapes. Spatial structuring, where children explore structural units of a 2D space, is an alternative approach. However, poor manipulation of physical units can reinforce misconceptions about area measurement. To address this issue, we developed MeoGeo, an augmented reality (AR) smartphone application. MeoGeo allows children to readily create virtual structural arrays with units of varying sizes, superimposing them on their surroundings in real-time. We conducted an exploratory multiple-case study over a 7-week program to examine the effect of AR activities. Data included written responses from three elementary students on paper-and-pencil tests, along with in situ videos recordings. Our findings indicate that engagement in AR activities facilitated reasoning skills in area measurement for both basic and composite shapes. Furthermore, students maintained their reasoning skills beyond the intervention period. Our study underscores the importance of developing AR systems that align explicitly with the developmental progression of each child, and it highlights the critical role of the instructor in effective execution of AR activities. © The Author(s) 2025.

关键词： Area measurement Augmented reality Elementary education Intelligent system mathematics education mathematics reasoning

Detection and Cancellation of Multiplicative FDI Attack on Bilateral Encrypted Control System in Variable Periodic Motion

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Detection and Cancellation of Multiplicative FDI Attack on B...

2025 IEEE/SICE International Symposium on System Integration, SII 2025

作者： Kosha, Katsumasa Miyazaki, Tetsuro Teranishi, Kaoru Kogiso, Kiminao Kawashima, Kenji The University of Tokyo Department of Information Physics and Computing 7-3-1 Hongo Bunkyo-ku Tokyo113-8656 Japan The University of Texas at Austin Oden Institute for Computational Engineering and Sciences AustinTX United States Japan Society for the Promotion of Science Tokyo Japan The University of Electro-Communications Department of Mechanical and Intelligent Systems Engineering 1-5-1 ChofugaokaChofu-shi Tokyo182-8585 Japan

ISBN: (纸本)9798331531614

Teleoperation of remote assist robots has recently advanced owing to the development of communication technology. However, anonymous malicious attacks may intercept or falsify the network control system. Therefore, it is necessary to improve the security against cyber-attacks. As a countermeasure, an encrypted control method has been applied to prevent intercepting and detect the falsification of control parameters, as well as control signals by performing control operations with encrypted signals and parameters. Furthermore, we have proposed the algorithm to detect and restore the attack exploiting a vulnerability of encryption, which falsifies the plaintext by multiplying a constant factor. However, the algorithm is only effective for periodic motions with a fixed operating frequency and amplitude. If the frequency or amplitude of the motion is smaller than those of the base motion, the algorithm cannot detect the attack. To solve the problem, we propose an improved algorithm to detect and restore the attack in periodic motion with variable operating frequency and amplitude. In the proposed method, the operating frequency and amplitude are obtained through the position frequency analysis. They contribute to update the base energy, which is the average energy of corresponding periodic motion. We verified the proposed method for the bilateral control system using ElGamal encryption and experimentally confirmed its effectiveness against the FDI attack in various periodic motion. © 2025 IEEE.

关键词： Cyber attacks

CONSENSUS BASED STOCHASTIC CONTROL

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arXiv 2025年

作者： Lyu, Liyao Chen, Jingrun Department of Computational Mathematics Science & Engineering Michigan State University MI48824 United States School of Mathematical Sciences Suzhou Institute for Advanced Research University of Science and Technology of China Suzhou215127 China

We propose a gradient-free deep reinforcement learning algorithm to solve high-dimensional, finite-horizon stochastic control problems. Although the recently developed deep reinforcement learning framework has achieved great success in solving these problems, direct estimation of policy gradients from Monte Carlo sampling often suffers from high variance. To address this, we introduce the Momentum Consensus-Based Optimization (M-CBO) and Adaptive Momentum Consensus-Based Optimization (Adam-CBO) frameworks. These methods optimize policies using Monte Carlo estimates of the value function, rather than its gradients. Adjustable Gaussian noise supports efficient exploration, helping the algorithm converge to optimal policies in complex, nonconvex environments. Numerical results confirm the accuracy and scalability of our approach across various problem dimensions and show the potential for extension to mean-field control problems. Theoretically, we prove that M-CBO can converge to the optimal policy under some assumptions. © 2025, CC BY-NC-SA.

关键词： Deep reinforcement learning

Are there type-III multiferroics?

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arXiv 2025年

作者： Wang, Haojin Liu, Haitao Ye, Meng Li, Yuanchang Advanced Research Institute of Multidisciplinary Science Beijing Institute of Technology Beijing100081 China Institute of Applied Physics and Computational Mathematics Beijing100088 China National Key Laboratory of Computational Physics Beijing100088 China Graduate School of China Academy of Engineering Physics Beijing100193 China

Multiferroics are known to be classified into two types. However, type-I lacks sufficient magnetoelectric coupling and type-II lacks sufficient electric polarization, making both practically difficult. In this work, we explore the possibility of type-III multiferroics, where the origins of ferroelectricity and magnetism are highly intertwined but not causally related, with a combination of strong magnetoelectric coupling and large polarization. Our first-principles calculations predict that monolayer TiCdO4 is such a type-III ferroelectric-ferromagnetic multiferroics with both electronic and magnetic orders originating from competing electron populations on oxygen atoms. It shows an electric polarization of 50 µC/m2 while the maximum linear and quadratic magnetoelectric response are as high as 35000 ps/m and 1.59 × 10−14 s/A, respectively. Our study opens up new perspectives for the discovery and design of much-anticipated multiferroics that can be used for cross-modulation. © 2025, CC BY.

关键词： Ferroelectricity

Permissioned Blockchain Security Pqfabric from Quantum and Classical Attacks

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Permissioned Blockchain Security Pqfabric from Quantum and C...

Advances in Computer science, Electrical, Electronics, and Communication Technologies (CE2CT), International Conference on

作者： C. Tamilarasi K Bhavadrarani Thiagarajan Kittappa N. Subashini V. Anitha Vimalraj E Department of Computer Science and Engineering B.S.Abdur Rahman Crescent Institute of Science & Technology Chennai Department of Computer Science and Engineering V.S.B. Engineering College Karur. Department of Mathematics Rajalakshmi Institute of Technology Chennai Department of Mathematics Sathyabama Institute of Science and Technology Chennai Department of CSE Panimalar Engineering College Poonamallee Chennai School of Computing Mohan Babu University Tirupati Andhra Pradesh

ISBN: (数字)9798331518578

ISBN: (纸本)9798331518585

Old style cryptographic techniques are genuinely compromised by the development of quantum computing, which requires the formation of safety ideal models that are impervious to quantum mistakes. A new permissioned blockchain security system called PqFabric is intended to oppose both traditional and quantum attacks. PqFabric ensures the validness, mystery, and respectability of exchanges in a quantum-empowered future by including post-quantum cryptographic techniques like hash-based and grid based marks. As opposed to ordinary blockchains, PqFabric utilizes a half breed agreement process that gets information trades and members characters by melding Byzantine Fault Tolerance (BFT) with quantum-safe encryption. The system gives protection against calculation based attacks by Shor and Grover, tending to huge imperfections in existing blockchain structures. Besides, when quantum-safe guidelines advance, its secluded plan empowers smooth enhancements. With this procedure, PqFabric is situated as a ground breaking answer for organizations and areas wishing to safeguard their blockchain networks from new cryptographic risks.

关键词： Production systems Technological innovation Quantum computing Supply chains Standards organizations Oral communication Throughput Fabrics Blockchains Encryption