The consensus control problem under a leader-follower formation scenario is investigated in this paper, where the interactive link considered as directed topology. A fixed-time distributed observer (FDO) proposed to estimate states of leader node, whose are supposed be accessible for only partial followers. Furthermore, weighted protocol (WCP) deployed on unmanned aerial vehicles (UAV) attain tracking. convergence FDO proved through Lyapunov theories. comparative simulation conducted with...

Firstly, the static simulation analysis and modal characteristic were carried out on reducer box, parts with weak stiffness easy deformation obtained from results. The important dimensional parameters extracted, model was parameterized. optimal response surface of box established by using space filling design method, sensitivity out. Based results optimization, multi-objective topology optimization based variable density method as a whole. results, reconstructed comparative showed that after...

Unsupervised Graph Domain Adaptation (UGDA) seeks to bridge distribution shifts between domains by transferring knowledge from labeled source graphs given unlabeled target graphs. Existing UGDA methods primarily focus on aligning features in the latent space learned graph neural networks (GNNs) across domains, often overlooking structural shifts, resulting limited effectiveness when addressing structurally complex transfer scenarios. Given sensitivity of GNNs local features, even slight...

Oil tanks are one of the most important targets in remote sensing. tank detection using optical images has been developed recent years, but few methods have studied for oil synthetic aperture radar (SAR) images. Optical suffer incorrect assessments or false alarms when they applied SAR imagery. A method that combines quasi-circular shadows and highlighting arcs is proposed to detect with higher precision lower alarm. In general, a arc caused by double reflection exists exactly at bottom each...

Dense false target jamming can affect radar detection performance severely. A method of dense targets recognition based on time-frequency atomic decomposition theory and support vector machine (SVM) is proposed to solve the difficulty identification. According feature ambiguity function signal, a Gabor sub-dictionary which has adaptive variation with signal designed. The expanded into corresponding dictionary by sparse decomposition. After parameters are extracted as individual vectors, SVM...

The emergence of Graph Neural Networks (GNNs) has greatly advanced the development recommendation systems. Recently, many researchers have leveraged GNN-based models to learn fair representations for users and items. However, current suffer from biased user–item interaction data, which negatively impacts fairness. Although there been several studies employing adversarial learning mitigate this issue in systems, they mostly focus on modifying model training approach with fairness...

The potential of using water-soluble photoluminescent nanoparticles different sizes for latent fingerprint detection has been explored. In this pilot study, green (582 nm) and red (755 CdTe nanocrystals coated with thioglycolic acid were used. Latent fingerprints on aluminum glass surfaces successfully labeled these time periods ranging from 30 min to 24 h. labeling is probably due the amidation reaction between surface carboxylic groups amine biomaterials present in residues. 582 nm...

The potential of using water-soluble photoluminescent nanoparticles different sizes for latent fingerprint detection has been explored. In this pilot study, green (582nm) and red (755 nm) CdTe nanocrystals coated with thioglycolic acid were used. Latent fingerprints on aluminum glass surfaces successfully labeled these time periods ranging from 30 min to 24 h. labeling is probably due the amidation reaction between surface carboxylic groups amine biomaterials present in residues. 582nm...

In a (t, n) threshold secret sharing scheme, any t- out-of-n participants could recover the shared secret, and less than t get nothing about secret. Most of existing schemes are not flexible enough for fixed threshold. this paper, new dynamic scheme was proposed, which is based on bilinear maps. The basic idea as follows: system consisted some dealer. Each participant holds only one permanent private key. dealer responsible to choose construct linear equations by using 'public keys. realized...

Aspect prediction (AP) and sentiment (SP) are representative applications in fine-grained anal- ysis. They can be considered as sequential tasks, where AP identifies mentioned aspects a sentence, SP infers sentiments for these aspects. Recent models perform the aspect-sentiment joint man-ner, but heavily rely on feature interactions of aspect sentiment. One drawback is that they ignore correlation strength varies between features fea- tures across different sentences, employ fixed...

Abstract Sparse representation is a new signal analysis method which receiving increasing attention in recent years. In this article, novel scheme solving high range resolution profile automatic target recognition for ground moving targets proposed. The sparse theory applied to analyzing the components of profiles and coefficients are used describe their features. Numerous experiments with type number ranging from 2 6 have been implemented. Results show that proposed not only provides higher...

Dense video captioning, with the objective of describing a sequence events in video, has received much attention recently. As are highly correlated, leveraging relationships among helps generate coherent captions. To utilize events, existing methods mainly enrich event representations their context, either form vision (i.e., segments) or combining and language captions). However, these do not explicitly exploit correspondence between two modalities. Moreover, video-level context spanning...

This work intends to solve the problem that traditional education system cannot reasonably adjust educational integration of children with arrival labor force in a short time, and support migrant (MC) policy (EP) integrate them into local environment as soon possible. Firstly, this defines surplus MC. Secondly, principles Artificial Intelligence (AI) Deep Learning (DL) are introduced. Thirdly, it analyzes MC relevant policies, data effect collected evaluation model is built. Finally, MC's...

In this article, we explore how the construction of meaning takes place across audio and visual elements, a music video, Man in Mirror by Michael Jackson,1 can be interpreted through mu...

Tipping points occur in many real-world systems, at which the system shifts suddenly from one state to another. The ability predict occurrence of tipping time series data remains an outstanding challenge and a major interest broad range research fields. Particularly, widely used methods based on bifurcation theory are neither reliable prediction accuracy nor applicable for irregularly-sampled commonly observed systems. Here we address this by developing deep learning algorithm predicting...

Despite significant progress in visual decoding with fMRI data, its high cost and low temporal resolution limit widespread applicability. To address these challenges, we introduce RealMind, a novel EEG-based framework that leverages multi-modal models to efficiently interpret semantic information. By integrating geometric consistency learning, RealMind enhances feature alignment, leading improved performance. Our achieves 56.73\% Top-5 accuracy 200-way retrieval task 26.59\% BLEU-1 score...

Unsupervised Graph Domain Adaptation (UGDA) seeks to bridge distribution shifts between domains by transferring knowledge from labeled source graphs given unlabeled target graphs. Existing UGDA methods primarily focus on aligning features in the latent space learned graph neural networks (GNNs) across domains, often overlooking structural shifts, resulting limited effectiveness when addressing structurally complex transfer scenarios. Given sensitivity of GNNs local features, even slight...