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arXiv 2025年

作者： Manas, Kumar Schlauch, Christian Paschke, Adrian Wirth, Christian Klein, Nadja Department of Mathematics and Computer Science Freie Universität Berlin Germany Continental Automotive Technologies GmbH AI Lab Berlin Germany Karlsruhe Institute of Technology Scientific Computing Center Germany Fraunhofer Institute for Open Communication Systems Berlin Germany

Deep learning-based trajectory prediction models have demonstrated promising capabilities in capturing complex interactions. However, their out-of-distribution generalization remains a significant challenge, particularly due to unbalanced data and a lack of enough data and diversity to ensure robustness and calibration. To address this, we propose SHIFT (Spectral Heteroscedastic Informed Forecasting for Trajectories), a novel framework that uniquely combines well-calibrated uncertainty modeling with informative priors derived through automated rule extraction. SHIFT reformulates trajectory prediction as a classification task and employs heteroscedastic spectral-normalized Gaussian processes to effectively disentangle epistemic and aleatoric uncertainties. We learn informative priors from training labels, which are automatically generated from natural language driving rules, such as stop rules and drivability constraints, using a retrieval-augmented generation framework powered by a large language model. Extensive evaluations over the nuScenes dataset, including challenging low-data and cross-location scenarios, demonstrate that SHIFT outperforms state-of-the-art methods, achieving substantial gains in uncertainty calibration and displacement metrics. In particular, our model excels in complex scenarios, such as intersections, where uncertainty is inherently higher. Project page: https://***/SHIFT/. © 2025, CC BY.

关键词： Deep learning

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A New Construction Structure on Coded Caching with Linear Subpacketization: Non-Half-Sum Disjoint Packing

arXiv

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arXiv 2025年

作者： Cheng, Minquan Wei, Huimei Wan, Kai Caire, Giuseppe Guangxi Key Lab of Multi-source Information Mining & Security Guangxi Normal University Guilin541004 China the School of Electronic Information and Communications Huazhong University of Science and Technology Wuhan430074 China the Electrical Engineering and Computer Science Department Technische Universität Berlin Berlin10587 Germany

Coded caching is a promising technique to effectively reduce peak traffic by using local caches and the multicast gains generated by these local caches. Coded caching schemes have been widely investigated following the seminal work of Maddah-Ali and Niesen. Explicit coding constructions have been proposed for a variety of network topologies with information-theoretically optimal or near-optimal transmission load R. An important parameter in these constructions is the subpacketization F, i.e., the number of subpackets that each content file needs to be divided into. In particular, the original scheme of Maddah-Ali and Niesen as well as several other variants require F to grow exponentially with the number of users K. In practice, files have finite size and too large F yields impractically small subpackets. Therefore, it is important to design coded caching schemes with F and R as small as possible. At present, the few known schemes with subpacketization linear in K achieve large load. In this paper, we consider the linear scaling regime F = O(K) and design schemes with unprecedented transmission load R. Specifically, we first introduce a new combinatorial structure called non-half-sum disjoint packing (NHSDP) which can be used to generate a coded caching scheme with K = O(F). A class of new schemes is then obtained by constructing NHSDP. Theoretical and numerical analyses demonstrate that (i) in comparison to existing schemes with linear subpacketization, the proposed scheme achieves a lower load;(ii) the proposed scheme also attains a lower load than some existing schemes with polynomial subpacketization in some cases;and (iii) the proposed scheme achieves load values comparable to those of existing schemes with exponential subpacketization in some cases. Furthermore, the newly introduced concept of NHSDP is closely related to classical combinatorial structures, including cyclic difference packings (CDP), non-three-term arithmetic progressions (NTAP), and perfect ha

关键词： Combinatorial mathematics

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IntelliChain: An Integrated Framework for Enhanced Socratic Method Dialogue with LLMs and Knowledge Graphs ∗

arXiv

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arXiv 2025年

作者： Qi, Changyong Jia, Linzhao Wei, Yuang Jiang, Yuan-Hao Gu, Xiaoqing Lab of Artificial Intelligence for Education East China Normal University China Shanghai Institute of Artificial Intelligence for Education East China Normal University China School of Computer Science and Technology East China Normal University China Department of Educational Information Technology East China Normal University China

With the continuous advancement of educational technology, the demand for Large Language Models (LLMs) as intelligent educational agents in providing personalized learning experiences is rapidly increasing. This study aims to explore how to optimize the design and collaboration of a multi-agent system tailored for Socratic teaching through the integration of LLMs and knowledge graphs in a chain-of-thought dialogue approach, thereby enhancing the accuracy and reliability of educational applications. By incorporating knowledge graphs, this research has bolstered the capability of LLMs to handle specific educational content, ensuring the accuracy and relevance of the information provided. Concurrently, we have focused on developing an effective multi-agent collaboration mechanism to facilitate efficient information exchange and chain dialogues among intelligent agents, significantly improving the quality of educational interaction and learning outcomes. In empirical research within the domain of mathematics education, this framework has demonstrated notable advantages in enhancing the accuracy and credibility of educational interactions. This study not only showcases the potential application of LLMs and knowledge graphs in mathematics teaching but also provides valuable insights and methodologies for the development of future AI-driven educational solutions. Copyright © 2025, The Authors. All rights reserved.

关键词： Knowledge graph

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High-Quality Novel View Synthesis of Robotic Surgical Scenes using Gaussian Splatting with Depth Prior

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computer Methods and Programs in Biomedicine 2025年 268卷 108856-108856页

作者： Song, Changshun Peng, Jun Chen, Qi Qin, Zhibao Tai, Yonghang Yunnan Key Lab Optoelectronic Information Technology Yunnan Normal University Kunming650500 China Department of Thoracic Surgery Institute of The First People's Hospital of Yunnan Province Kunming650032 China School of Mathematics and Computer Science Yunnan Minzu University Kunming650031 China Yunnan Province Photoelectric Detection and Perception Technology Engineering Research Center China

Background and Objective: Robot-assisted surgery has revolutionized modern medical procedures by enhancing precision, reducing invasiveness, and providing a clearer, more controlled environment. However, it still faces challenges in fully visualizing the target tissue, particularly from multiple perspectives. This limitation is most evident in minimally invasive surgeries, Therefore, the ability to synthesize new views of the surgical scene is becoming increasingly critical. By generating multi-view visualizations, surgeons can gain a more comprehensive understanding of the target tissue, improving spatial awareness and decision-making during surgery. Methods: This article proposes an innovative novel view synthesis method for robotic surgical scenarios, which utilizes pre-trained depth estimation model to obtain global depth information and solves the scale ambiguity problem encountered in the transition region of the Gaussian distribution in the 3D Gaussian model. In addition, we introduce a multi-scale loss optimization strategy that captures features of various scales through a multi-scale loss function to regularize the Gaussian parameters while maintaining the 3D consistency of the splatting. Results: Our method is evaluated against current scene novel view synthesis techniques using our robotic surgery scene dataset, along with the Hamlyn and Stereo MIS public datasets. The proposed approach achieved an average PSNR of 33.45, SSIM of 0.939, LPIPS of 0.153, and an RMSE of 0.022 across the three datasets. Conclusions: Our approach helps to enhance the visualization capabilities of robotic surgical systems by synthesizing novel views of surgical scenes. A deeper understanding of the target tissue will enhance patient safety during surgery and support surgeon training. These advancements will contribute to the improvement of robot-assisted surgery, making it more adaptable to diverse clinical scenarios. © 2025 Elsevier B.V.

关键词： Robotic surgery

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Mitosis detection and classification for breast cancer diagnosis: What we know and what is next

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computers in Biology and Medicine 2025年 191卷 110057-110057页

作者： Khalil, Rafi Ullah Sajjad, Muhammad Dhahbi, Sami Bourouis, Sami Hijji, Mohammad Muhammad, Khan Digital Image Processing Lab Department of Computer Science Islamia College Peshawar Peshawar25000 Pakistan Applied College of Mahail Aseer King Khalid University Muhayil Aseer62529 Saudi Arabia Department of Information Technology College of Computers and Information Technology Taif University Taif21944 Saudi Arabia Faculty of Computers and Information Technology University of Tabuk Tabuk71491 Saudi Arabia Department of Applied AI School of Convergence College of Computing and Informatics Sungkyunkwan University Seoul03063 Korea Republic of

Breast cancer is the second most deadly malignancy in women, behind lung cancer. Despite significant improvements in medical research, breast cancer is still accurately diagnosed with histological analysis. During this procedure, pathologists examine a physical sample for the presence of mitotic cells, or dividing cells. However, the high resolution of histopathology images and the difficulty of manually detecting tiny mitotic nuclei make it particularly challenging to differentiate mitotic cells from other types of cells. Numerous studies have addressed the detection and classification of mitosis, owing to increasing capacity and developments in automated approaches. The combination of machine learning and deep learning techniques has greatly revolutionized the process of identifying mitotic cells by offering automated, precise, and efficient solutions. In the last ten years, several pioneering methods have been presented, advancing towards practical applications in clinical settings. Unlike other forms of cancer, breast cancer and gliomas are categorized according to the number of mitotic divisions. Numerous papers have been published on techniques for identifying mitosis due to easy access to datasets and open competitions. Convolutional neural networks and other deep learning architectures can precisely identify mitotic cells, significantly decreasing the amount of labor that pathologists must perform. This article examines the techniques used over the past decade to identify and classify mitotic cells in histologically stained breast cancer hematoxylin and eosin images. Furthermore, we examine the benefits of current research techniques and predict forthcoming developments in the investigation of breast cancer mitosis, specifically highlighting machine learning and deep learning. © 2025 Elsevier Ltd

关键词： Lung cancer

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Topology Rewiring Strategies to construct robust scale-free medical Internet of Things Networks

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Simulation Modelling Practice and Theory 2025年 142卷

作者： Khan, Muhammad Awais Javaid, Nadeem Alrajeh, Nabil Bouk, Safdar Hussain Department of Electrical and Computer Engineering COMSATS University Islamabad Islamabad44000 Pakistan ComSens Lab International Graduate School of Artificial Intelligence National Yunlin University of Science and Technology Yunlin64002 Taiwan Department of Biomedical Technology College of Applied Medical Sciences King Saud University Riyadh11633 Saudi Arabia Old Dominion University 5115 Hampton Blvd NorfolkVA23529 United States

The Internet of Things (IoT) network topologies are now most commonly impacted by cyberattacks. The scale-free network topologies have demonstrated great robustness against random attacks by preserving the connectedness of the nodes. The scale-free network topologies’ susceptibility to malicious attacks, however, is a significant worry. It is due to the significance of the scale-free networks in different fields of life like medical, transportation, education, agriculture, etc. Also, high-degree node removal diminishes the network's resiliency and compromises the connection of the majority of nodes. In this study, we offer several rewiring techniques for building scale-free, reliable Medical Internet of Things (MIoT) networks that can withstand malicious attacks. Initially, the scale-free MIoT network's performance optimization is ensured using a heuristic algorithm known as the Great Deluge Algorithm (GDA). Then, four rewiring strategies are formulated. The initial approach is degree dissortativity, which rewires the network if all nodes have high maximum connectivity to other neighbors with a similar degree. For the second strategy, we introduced a degree difference operation based on degree dissortativity to ensure that the edges that are connected possess low dissortativity and degree difference. Meanwhile, the remaining two strategies take into account the node load bound and enhanced GDA to increase network robustness. The performance of the proposed rewiring strategies is validated through simulations. The results prove that the proposed strategies increase network robustness by up to 25% compared to Hill Climbing (HC) and Simulated Annealing (SA). Additionally, the strategies show great success in improving network connectivity and graph density. However, their computational time is higher compared to HC and SA. © 2025 Elsevier B.V.

关键词： Network topology

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Towards Understanding Interactive Sonic Gastronomy with Chefs and Diners 25

Towards Understanding Interactive Sonic Gastronomy with Chef...

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Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems

作者： Hongyue Wang Jialin Deng Linjia He Nathalie Overdevest Ryan Wee Yan Wang Phoebe O. Toups Dugas Don Samitha Elvitigala Florian Floyd Mueller Exertion Games Lab Department of Human-Centred Computing Monash University Melbourne Australia Exertion Games Lab Department of Human-Centred Computing Monash University Melbourne Australia and Diverse-ability Interaction Lab School of Computer Science Bristol United Kingdom Exertion Games Lab Department of Human-Centred Computing Monash University Melbourne Australia and Faculty of Engineering and Information Technology University of Technology Sydney Sydney Australia Exertion Games Lab Department of Human-Centred Computing Monash University Melbourne Australia and Mineral Resources Commonwealth Scientific and Industrial Research Organisation Melbourne Australia

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Practical security analysis and attack strategies on permutation functions used in IoT supply chain systems

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Scientific Reports 2025年第1期15卷 1-15页

作者： Mokhtari, Narges Safari, Amirhossein Sadeghi, Sadegh Bagheri, Nasour Rostampour, Samad Bendavid, Ygal CPS2 Lab Department of Communication Faculty of Electrical Engineering Shahid Rajaee Teacher Training University Tehran 16788-15811 Iran Department of Computer Science and Information Technology Institute for Advanced Studies in Basic Sciences (IASBS) Zanjan 45137-66731 Iran Department of Mathematics Institute for Advanced Studies in Basic Sciences (IASBS) Zanjan 45137-66731 Iran School of Computer Science Institute for Research in Fundamental Sciences (IPM) Tehran 19538-33511 Iran Department of Computer Science Vanier College Montreal Canada Department of Analytics Operations and Technology School of Management Université du Québec à Montréal (UQAM) Montreal Canada

The widespread adoption of IoT devices has made the production of low-cost systems a priority. Since construction costs are generally directly related to the complexity of security methods, researchers are exploring methods that provide acceptable security with minimal hardware complexity. One such method is the use of permutation functions in ultra-lightweight authentication protocols that employ simple operators such as XOR and Shift. This paper demonstrates the critical importance of the internal structure of a permutation function in ensuring system security. This implies that even if a protocol is designed securely and efficiently, structural weaknesses in the function can render the protocol vulnerable. To illustrate this, we examine a recently published protocol named ULBRAP for supply chain management systems and reveal its security flaws, including secret disclosure and traceability attacks. We also demonstrate the attack step-by-step on Raspberry Pi devices, publishing the details on GitHub and presenting them in a video. The attack method requires 1,710,947 hash calculations, which takes approximately 5 min in our experiments. Finally, we propose a solution to address the issues associated with these functions. © The Author(s) 2025.

关键词： 5G mobile edge computing RFID authentication protocol Security analysis Supply chain management Ultra-lightweight blockchain

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Synthesized Acoustic Vortex-Frequency Comb via Rotational Doppler Effect

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Physical Review Letters 2025年第13期134卷 137001-137001页

作者： Yurou Jia Xuan Zhang Suying Zhang Guoqiang Xu Taoyu Chen Hongtao Zhou Yechao Bai Ying Cheng Dajian Wu Department of Physics MOE Key Laboratory of Modern Acoustics Collaborative Innovation Center of Advanced Microstructures Jiangsu Physical Science Research Center Nanjing University Nanjing 210093 China Department of Electrical and Computer Engineering National University of Singapore Singapore Department of Mechanics School of Mechanical Engineering Tianjin University Tianjin 300350 China School of Electronic Science and Engineering Nanjing University Nanjing 210023 China Jiangsu Key Lab on Opto-Electronic Technology School of Physics and Technology Nanjing Normal University Nanjing 210023 China

The synergistic control of light’s frequency and orbital angular momentum (OAM) via integrated nonlinear ring microresonators is crucial for creating spatiotemporal optical waveforms and advancing optical metrology. A direct analog of this capability in acoustics is challenging due to the nonlinearity-based mechanisms’ dependence on external driving and limited frequency conversion efficiency. Here, we present an acoustic synthesized comb structure derived from spatiotemporal metasurfaces, concurrently controlling frequency and OAM characteristics with high conversion efficiency and removing the constraints of critical driving frequency and power level in nonlinear mechanisms. By optimizing comb structures, energy distributions among OAM modes are adjusted to different frequency lines. We finally propose spatiotemporal metalens devices based on vortex-frequency combs, enabling synchronously multiple-order spatial differential operations for parallel data processing. This Letter is groundbreaking in integrating spectral- and spatial-domain acoustic waves, promising multifunctional imaging and advantages in spatiotemporal beams.

关键词： Vortex flow

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Circular LPDA Array Design for Efficient Microwave Treatment of Palm Weevil Infestation

Circular LPDA Array Design for Efficient Microwave Treatment...

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Microwave, Antennas & Circuits (ICMAC), International Conference on

作者： Asad Masood Muhammad Ali Zubair Mehmood Zunair Ahmad Faizan Ramzan Rifaqat Hussain Muhammad Qasim Mehmood Department of Electrical Engineering MicroNano Lab Information Technology University (ITU) Lahore Pakistan Department of Electrical Engineering Hafiz Hayat Campus University of Gujrat (UOG) Gujrat Pakistan Antenna and Electromagnetics Research Group School of Electronic Engineering and Computer Science Queen Mary University of London London UK

ISBN: (数字)9798331518424

ISBN: (纸本)9798331518431

The Red Palm Weevil (RPW) is one of the most harmful pests to palms globally. Various strategies have been used to killing this pest which includes Phyto sanitation, chemical pesticides, pheromone traps, and biological management, however the use of microwave energy for heat disinfestation appears to be a potential alternative. This article describes the method to develop a microwave antenna system that uses a circular array of Log-Periodic Dipole Antennas (LPDAs) to disinfect date palms. The simulation results are performed in FDTD solver. The proposed antenna covers a wide frequency range spanning 1.3 GHz − 3 GHz. The reflection coefficient is well below to −10 dB over the whole resonant frequency band, having a peak gain of 9.5 dBi for a single antenna. A circular LPDA antenna array is proposed to perform the thermal analysis for particular area of the palm tree to mitigate the RPW.

关键词： Electromagnetic heating Microwave integrated circuits Dipole antennas Resonant frequency Microwave theory and techniques Microwave circuits Microwave antenna arrays Thermal analysis Reflection coefficient Time-domain analysis

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