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VSQ: Enabling efficient and verifiable similarity queries in blockchain databases

Expert Systems with Applications 2025年 285卷

作者： Yin, Bo Liu, Yihu Xu, Binyao School of Computer and Communication Engineering Changsha University of Science and Technology Changsha410114 China School of Control and Computer Engineering North China Electric Power University Beijing102206 China

Blockchain serves as the basis for secure and distributed applications like decentralized finance (DeFi). Light nodes can help reduce the storage and computation burden of full nodes in the blockchain by storing only block headers instead of full blocks. The resource constraint user runs a light node and sends the query request to the full node to find the answer. However, this approach raises security concerns, as query results from the full node may be altered or incomplete. In this paper, we explore verifiable similarity queries, commonly used in text mining, within the context of blockchain networks. The main challenge lies in designing an authenticated data structure (ADS) that enables efficient query processing and verification of query result soundness and completeness. Previous research on blockchain verifiable queries has focused on range queries, keyword queries, and existence queries, which are not applicable to verifiable similarity queries. Our proposed solutions include a baseline approach that uses the Merkle hash tree as the foundational ADS and adds leaf node pointers for query realization. Additionally, we introduce an enhanced solution Baseline+, which improves query efficiency and reduces storage overhead by leveraging minhash. Finally, we present a verifiable similarity query scheme (VSQ) based on the Merkle bucket tree, integrating minhash and locality-sensitive hashing to enhance query and verification efficiency. We conducted extensive experimental evaluation. The experimental results show that the query time and the verification object size of VSQ are reduced by two orders of magnitude compared to the Baseline approach. © 2025

关键词： Query languages

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Transforming stroop task cognitive assessments with multimodal inverse reinforcement learning

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Smart Health 2025年 36卷

作者： Abbasi, Ali Gong, Jiaqi Korivand, Soroush Department of Control and Computer Engineering Polytechnic University of Turin Italy Department of Computer Science The University of Alabama United States Department of Mechanical Engineering Mississippi State University United States

Stroop tasks, recognized for their cognitively demanding nature, hold promise for diagnosing and monitoring neurodegenerative diseases. Understanding how humans allocate attention and resolve interference in the Stroop test remains a challenge;yet addressing this gap could reveal key opportunities for early-stage detection. Traditional approaches overlook the interplay between overt behavior and underlying neural processes, limiting insights into the complex color-word associations at play. To tackle this, we propose a framework that applies Inverse Reinforcement Learning (IRL) to fuse electroencephalography (EEG) signals with eye-tracking data, bridging the gap between neural and behavioral markers of cognition. We designed a Stroop experiment featuring congruent and incongruent conditions to evaluate attention allocation under varying levels of interference. By framing gaze as actions guided by an internally derived reward, IRL uncovers hidden motivations behind scanning patterns, while EEG data — processed with advanced feature extraction — reveals task-specific neural dynamics under high conflict. We validate our approach by measuring Probability Mismatch, Target Fixation Probability-Area Under the Curve, Sequence Score, and MultiMatch metrics. Results show that the IRL-EEG model outperforms an IRL-Image baseline, demonstrating improved alignment with human scanpaths and heightened sensitivity to attentional shifts in incongruent trials. These findings highlight the value of integrating neural data into computational models of cognition and illuminate possibilities for early detection of neurodegenerative disorders, where subclinical deficits may first emerge. Our IRL-based integration of EEG and eye-tracking further supports personalized cognitive assessments and adaptive user interfaces. © 2025 The Authors

关键词： Cognitive assessment EEG Eye-tracking Inverse reinforcement learning Neurodegenerative diseases

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Design and testing of Hybrid Slime Mold Algorithm for Real-Time Adaptive Mobile Robot Path Planning in Dynamic Environments

Design and testing of Hybrid Slime Mold Algorithm for Real-T...

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Advancement in Computation & computer Technologies (InCACCT), International Conference on

作者： Sachin Gupta Shivali Gupta Shaik Mohammed Raith Anand Kumar Salil Bharany Vishnu Kant Ch.Sandeep Department of Robotics and Control Engineering School of Electronics and Control Engineering Lovely Professional University Phagwara India Department of Chemistry School of Chemical Engineering and Physical Sciences Lovely Professional University Phagwara India Department of Computer Science and Engineering Lovely Professional University Phagwara Punjab India Chitkara University Institute of Engineering and Technology Chitkara University Rajpura India School of Computer Science and Artificial Intelligence SR University Warangal Telangana

ISBN: (数字)9798331543891

ISBN: (纸本)9798331543907

Dynamic path planning and collision prevention is one of the key tasks for autonomous vehicles in relation to dynamic movement of obstacles. In this paper, a novel hybrid approach based on integration of Slime Mold Algorithm (SMA), Triangle Inequality Principle (TIP), and Partition Method Strategy (PMS) for solution of this problem statement. The SMA algorithm is very flexible and adaptive by nature due to its biological working mechanism which is associated with TIP and PMS strategies in relation to their optimization and efficient path planning capabilities and robust solutions. This integrated module is tested in virtual environment and the results are compared with other updated algorithms such as A*, Genetic Algorithm (GA), and Particle Swarm Optimization (PSO) for the same static and dynamic environment. It has been observed from the results that this hybrid strategy significantly improves the path planning task several times than other algorithms in terms of multiple aspects. Under testing conditions, the path length was reduced to 25% than other algorithms in a dynamic environment. During this calculation, the computational efficiency of the system has been improved to 60% than conventional methods. The chances of collision have been improved to 34.23% especially in environment where the obstacles are moving. The capability of SMA has been improved due to the synergy between TIP and PMS. The dynamic and adaptive nature of this algorithm is suitable for various applications such as search-and-rescue operations, manufacturing units’ automation and other hazardous environment exploration.

关键词： Navigation Heuristic algorithms Virtual environments Path planning Partitioning algorithms Safety Mobile robots Vehicle dynamics Testing Genetic algorithms

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MKMGCN-DDI: Predicting Drug-Drug Interactions via Magnetic Graph Convolutional Network With Multiple Kernels

IEEE Transactions on Computational Biology and Bioinformatic...

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IEEE Transactions on Computational Biology and Bioinformatics 2025年第2期22卷 469-480页

作者： Ming Chen Yunhan Pan Xiujuan Lei Chunyan Ji Yinglong Dai Yi Pan Department of Artificial Intelligence Hunan Normal University Changsha Hunan China School of Computer Science Shaanxi Normal University Xi’an China Computer Science Department BNU-HKBU United International College Zhuhai China Shenzhen Key Laboratory of Intelligent Bioinformatics Shenzhen Institute of Advanced Technology Shenzhen China Faculty of Computer Science and Control Engineering Shenzhen University of Advanced Technology Shenzhen China

Polypharmacy is a common means of clinical treatments, but detecting drug-drug interactions (DDIs) behind unexpected effects can be costly and faces clinical limitations. Recently, graph neural networks (GNNs) have demonstrated encouraging performance in predicting DDIs. However, most studies overlook the comprehensive aspects of DDIs, such as the coexistence of types of pharmacological changes and the asymmetric roles of drugs. In this article, we define new prediction tasks, taking into account both enhancive or depressive changes and the roles of drugs, and then establish spectral GNNs to predict comprehensive information of DDIs. First, we formally define several tasks, including joint prediction tasks designed to leverage both types and directions. These tasks deduce to sub-tasks in previous studies. Then, we propose a unified framework, the MKMGCN-DDI, via introducing two Magnetic Laplacian matrices to encode comprehension information within DDIs, defining multiple graph filters, and designing multiple-kernel based Magnetic graph convolutional networks (MKMGCN). Experiments across three datasets show that it not only has good adaptability to multiple tasks but also significantly improves results on simple tasks. Case studies on breast neoplasms and lung neoplasms verify its feasibility, as over half of top-10 items are supported.

关键词： Drugs Predictive models Magnetic separation Laplace equations Bioinformatics Sodium Market research Graph convolutional networks computer science Computational modeling

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A Globally Convergent Method for Computing B-stationary Points of Mathematical Programs with Equilibrium Constraints

arXiv

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arXiv 2025年

作者： Nurkanovic, Armin Leyffer, Sven Systems Control and Optimization Laboratory Department of Microsystems Engineering University of Freiburg Germany Mathematics and Computer Science Division Argonne National Laboratory United States

This paper introduces a method that globally converges to Bstationary points of mathematical programs with equilibrium constraints (MPECs) in a finite number of iterations. B-stationarity is necessary for optimality and means that no feasible first-order direction improves the objective. Given a feasible point of an MPEC, B-stationarity can be certified by solving a linear program with equilibrium constraints (LPEC) constructed at this point. The proposed method solves a sequence of LPECs, which either certify B-stationarity or provide an active-set estimate for the complementarity constraints, and nonlinear programs (NLPs) - referred to as branch NLPs (BNLPs) - obtained by fixing the active set in the MPEC. A BNLP is more regular than the MPEC, easier to solve, and with the correct active set, its solution coincides with the solution of the MPEC. The method has two phases: the first phase identifies a feasible BNLP or certifies local infeasibility, and the second phase solves a finite sequence of BNLPs until a B-stationary point of the MPECis found. The paper provides a detailed convergence analysis and discusses implementation details. In addition, extensive numerical experiments and an open-source software implementation are provided. The experiments demonstrate that the proposed method is more robust and faster than relaxation-based methods, while also providing a certificate of B-stationarity without requiring the usual too-restrictive *** Codes 90C30, 90C33, 49M37, 65K10, 90C11 © 2025, CC BY.

关键词： Nonlinear programming

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Correction to: Generalized Robot Vision-Language Model via Linguistic Foreground-Aware Contrast (International Journal of computer Vision, (2025), 10.1007/s11263-024-02340-z)

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International Journal of computer Vision 2025年 1-1页

作者： Liu, Kangcheng Wang, Chaoqun Han, Xiaodong Liu, Yong-Jin Chen, Baoquan Changsha China Pasadena United States The School of Control Science and Engineering Shandong University Jinan China The School of Control Engineering Minjiang University Fuzhou China The Department of Computer Science and Technology Tsinghua University Beijing China The School of Artificial Intelligence Peking University Beijing China

The original version of this article contained inadvertent typos requiring the following revisions. The article title was given as "Generalized Robotic Vision-Language Learning Model via Linguistic Foreground-Aware Contrast" but should have been "Generalized Robot Vision-Language Model via Linguistic Foreground-Aware Contrast". The affiliation details for Author Chaoqun Wang were given as "The Department of computer science and Technology, Tsinghua University, Beijing, China" but should have been "The School of control science and engineering, Shandong University, Jinan, China". The affiliation details for Author Xiaodong Han were given as "The School of control science and engineering, Shandong University, Jinan, China" but should have been "The School of control engineering, Minjiang University, Fuzhou, China". The affiliation details for Author Yong-Jin Liu were given as "The School of control engineering, Minjiang University, Fuzhou, China" but should have been "The Department of computer science and Technology, Tsinghua University, Beijing, China". In this article, the part of the caption to Fig. 3 "Please refer to the colored figures online for detailed information" was inadvertently omitted. The complete caption of Fig. 3 is given here. Figure 3 Visualizations of projected point correlation maps over the indoor ScanNet (1st-4th rows) and the outdoor KITTI (5th-8th rows) with respect to the query points highlighted by yellow crosses. The View 1 and View 2 in each sample show the intra-view and cross-view correlations, respectively. We compare FAC with the state-of-the-art CSC (Hou et al., 2021) on segmentation (rows 1–4) and ProCo (Yin et al., 2022) on detection (rows 5–8). FAC clearly captures better feature correlations within and across views (columns 3–4). Please refer to the colored figures online for detailed information In this article, the footnote "The bold highlights the results of our proposed approaches" to Table 1 was inadvertently omitted. In Tab

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FPGA-based Real-time High-resolution Image Processing for rocket on-board processing

FPGA-based Real-time High-resolution Image Processing for ro...

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International Conference on computer Research and Development (ICCRD)

作者： Hui Zhou Xiaofeng Wang YuJia Xie Yongxiang Cao Yu Tang Yongchun Huo Huan Wen Xiongbo Zhao Chaoran Li Beijing Aerospace Automatic Control Institute National key Laboratory of Science and Technology on Aerospace Intelligent Control Beijing China Computer Science and Engineering Beihang University Beijing China National Superior College for Engineers Beihang University Beijing China

ISBN: (数字)9798331531881

ISBN: (纸本)9798331531898

The structure of the rocket-borne model is inherently complex, with processed images exhibiting high resolution and generating substantial amounts of data and calculations. Achieving robust real-time computing on an embedded platform poses significant challenges due to strictly limited resources, power consumption constraints, and size limitations. Our review of rocket-borne applications reveals considerable variability in the design resources of different devices, indicating a need for expanded design approaches. Upon evaluating existing methods, we identified two primary drawbacks. First, certain operators within the high-resolution target detection model are difficult to parallelize, resulting in significant inference delays that hinder the ability to meet task requirements. Although existing methods have been extended, there remains significant potential for performance enhancement in core scheduling for poor acceleration. This paper proposes an optimized architecture for the target detection algorithm accelerator designed for high-resolution images, along with a novel highly parallel data pre-processing and post-processing module implemented on FPGA to address these issues. Compared to the ARM implementation, this architecture demonstrates an improved performance of 24.64x. Furthermore, to ensure flexible application across various rocket launch scenarios, we introduce an optimization structure for convolution, pooling, and fusion operators and a multi-core expansion optimization method. This approach yields a 1.29x improvement in computing unit utilization compared to state-of-the-art multi-core scaling efforts. Finally, we assessed the accelerator architecture across multiple FPGA platforms, achieving a peak processing element utilization rate of 99.71% for a single core and layer. The overall computing efficiency, excluding the first layer, exceeded 90%. The peak computing power for the four cores reached 1638.4 GOPS, and the end-to-end computation time for

关键词： YOLO Rockets Power demand Convolution Multicore processing Reviews Scalability Accelerator architectures Real-time systems Field programmable gate arrays

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A Survey of fMRI to Image Reconstruction

arXiv

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arXiv 2025年

作者： Guo, Weiyu Sun, Guoying He, Jianxiang Shao, Tong Wang, Shaoguang Chen, Ziyang Hong, Meisheng Sun, Ying Xiong, Hui Thrust of Artificial Intelligence The Hong Kong University of Science and Technology Guangzhou China College of Computer Science and Technology Harbin Institute of Technology Shenzhen China School of Control Science and Engineering Shandong University China

Functional magnetic resonance imaging (fMRI)based image reconstruction plays a pivotal role in decoding human perception, with applications in neuroscience and brain-computer interfaces. While recent advancements in deep learning and large-scale datasets have driven progress, challenges such as data scarcity, cross-subject variability, and low semantic consistency persist. To address these issues, we introduce the concept of fMRI-to-Image Learning (fMRI2Image) and present the first systematic review in this field. This review highlights key challenges, categorizes methodologies such as fMRI signal encoding, feature mapping, and image generator. Finally, promising research directions are proposed to advance this emerging frontier, providing a reference for future studies. © 2025, CC BY.

关键词： Image reconstruction

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A Study on Impact-Aware Aerial Robots Colliding with the Environment at Non-Vanishing Speed

A Study on Impact-Aware Aerial Robots Colliding with the Env...

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Gayatri Indukumar Alessandro Saccon Antonio Franchi Chiara Gabellieri Robotics and Mechatronics Department Electrical Engineering Mathematics and Computer Science (EEMCS) Faculty University of Twente Enschede The Netherlands Department of Mechanical Engineering Eindhoven University of Technology Eindhoven The Netherlands Department of Computer Control and Management Engineering Sapienza University of Rome Rome Italy

ISBN: (数字)9798331513283

ISBN: (纸本)9798331513290

Enabling aerial robots to handle dynamic contacts happening at non-vanishing speeds can enlarge the range of their applications. In this work, we propose an impactaware strategy to allow aerial multirotor robots to recover from impacts. The method leverages a reactive strategy not requiring low-level changes to the motion controller commonly implemented onboard quadrotors, which might be not viable or not desirable for most users. Extensive simulation tests show that the proposed strategy considerably increases the tolerated velocity at impact in tasks in which the robot either picks an object up or collides against an object to clear its way. Preliminary experimental results using Crazyflie UAVs are also presented.

关键词： Trajectory tracking Dynamics Lead Autonomous aerial vehicles Stability analysis Robustness computer crashes Trajectory Robots Quadrotors

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Optimal Sensor Placement for Full-Set TDOA Localization Accounting for Sensor Location Errors

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IEEE Transactions on Aerospace and Electronic Systems 2025年

作者： Zhang, Chengjie Han, Xinyang Kong, He Ho, K.C. Southern University of Science and Technology Shenzhen Key Laboratory of Control Theory and Intelligent Systems Guangdong Provincial Key Laboratory of Fully Actuated System Control Theory and Technology Shenzhen518055 China University of Missouri Electrical Engineering and Computer Science Department ColumbiaMO65211 United States

The positioning accuracy of a signal source is influenced by where the sensors are deployed. Studies in the literature for the optimal sensor placement (OSP) of localization often ignore the presence of sensor position errors. In practice, however, it is impossible to place the sensors precisely at the desired locations. This work designs OSP by accounting for the presence of Gaussian sensor position errors that are independent and identically distributed (IID), with the full set of Time Difference of Arrival measurements corrupted by Gaussian IID noise. The criterion is the A-optimality equal to the trace of the source position Cramer-Rao Bound (CRB). We show that the presence of sensor position errors introduces a multiplication factor to the same criterion for the case without sensor position errors. The latter factor is dependent on the ratio of the sensor position error power to the range difference noise power but independent of the sensor positions, implying that the A-optimality OSP in the presence of sensor position errors is the same as in the absence. To our knowledge, this is the first time such results have been derived. Simulation studies validate the derived OSP, show the minimal OSP performance gap with sensor positioning error and without, and illustrate the better source localization accuracy by OSP. © 1965-2011 IEEE.

关键词： Cramer-Rao bounds

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