The movement of pedestrians involves temporal continuity, spatial interactivity, and random diversity. As a result, pedestrian trajectory prediction is rather challenging. Most existing methods tend to focus on just one aspect these challenges, ignoring the information making too many assumptions. In this paper, we propose recurrent attention interaction ( RAI ) model predict trajectories. consists module, pooling randomness modeling module. module proposed assign different weights input...

The ability to sense and adapt adverse food conditions is essential for survival across species, but the detailed mechanisms of neuron-digestive crosstalk in sensing adaptation remain poorly understood. This study identifies a novel mechanism by which animals detect unfavorable sources through olfactory neurons initiate systemic response shut down digestion, thus safeguarding against potential harm. Specifically, we demonstrate that NSY-1, expressed AWC neurons, detects Staphylococcus...

The ability to sense and adapt adverse food conditions is essential for survival across species, but the detailed mechanisms of neuron-digestive crosstalk in sensing adaptation remain poorly understood. This study identifies a novel mechanism by which animals detect unfavorable sources through olfactory neurons initiate systemic response shut down digestion, thus safeguarding against potential harm. Specifically, we demonstrate that NSY-1, expressed AWC neurons, detects Staphylococcus...

Text-based person retrieval (TPR) has gained significant attention as a fine-grained and challenging task that closely aligns with practical applications. Tailoring CLIP to domain is now emerging research topic due the abundant knowledge of vision-language pretraining, but challenges still remain during fine-tuning: (i) Previous full-model fine-tuning in TPR computationally expensive prone overfitting.(ii) Existing parameter-efficient transfer learning (PETL) for lacks feature extraction. To...

Abstract Ancient textile images have a variety of styles and themes, the classification different types textiles provides reliable reference for protection restoration cultural relics. Due to low efficiency traditional methods accuracy classification, image takes longer repair effect is poor. Therefore, this paper ancient as research object selects YOLOv4–ViT collaborative identification network (YOLOv4–ViT network) generative adversarial networks (GAN) model from models classify restore...

Text-based Person Retrieval (TPR) aims to retrieve the target person images given a textual query. The primary challenge lies in bridging substantial gap between vision and language modalities, especially when dealing with limited large-scale datasets. In this paper, we introduce CLIP-based Synergistic Knowledge Transfer (CSKT) approach for TPR. Specifically, explore CLIP's knowledge on input side, first propose Bidirectional Prompts Transferring (BPT) module constructed by text-to-image...

Employees contribute to the sustainability of organizations in many ways, yet specific impact employee voice on performance appraisal, as an element organization sustainability, is not clear. Based attribution theory, we present a model investigate relationship between and appraisal. Using PLS (Partial Least Squares) method, test our model’s hypotheses with 273 dyads supervisor-employee questionnaires administered branch state-owned enterprise China. The results show that promotive...

Clothes-invariant feature extraction is critical to the clothes-changing person re-identification (CC-ReID). It can provide discriminative identity features and eliminate negative effects caused by confounder--clothing changes. But we argue that there exists a strong spurious correlation between clothes human identity, restricts common likelihood-based ReID method P(Y|X) extract clothes-irrelevant features. In this paper, propose new Causal Clothes-Invariant Learning (CCIL) achieve...

The multi-modal information fusion for point cloud quality assessment (PCQA) is still understudied in existing work. Previous methods mostly adopt a late-fusion strategy without fully exploiting the advantages of different modalities and integrating them effectively. Considering that there exist both segregated processing intertwined when human visual system (HVS) tackles types information, we propose novel transformer module PCQA (MFT-PCQA). Specifically, block attention between features...

AbstractAbstractIn this work we explored proof schemes used by 41 middle school students when confronted with four mathematical propositions that demanded verification of accuracy statements. The students' perception mathematically complete vs. convincing arguments in different mathematics branches was also elicited. Lastly, considered whether the recognized and identified advantages associated using justification models from their own order to offer a theoretical account for how...

Due to the complexity and clutter of real-world scenes, occlusion becomes a long-lasting difficulty in object tracking. Most existing tracking methods cannot effectively handle occlusion. In this paper, we propose novel framework that combines trajectory prediction multi-cue appearance modeling deal with difficulty. When target is completely occluded by background or other targets, it unable observe position. Therefore, Long Short-Term Memory (LSTM) model merges attention mechanism...

In this study, a conceptual framework of measurement uncertainty was developed and used to guide the development multiple-choice concept test for assessment students' knowledge integration in learning uncertainty. Based on data interview results, students were identified into three levels including novice, intermediate, expertlike. The reasoning pathways at different revealed progression from rudimentary surface level deep understanding that can be mapped framework. This work demonstrates...

Anomaly detection is a crucial topic in network security which refers to automatically mining known and unknown attacks or threats. Many detectors have been proposed the last decade. Nonetheless, practical solution, able provide high True Positive Rate (TPR) with an acceptable False (FPR) without any prior information, still challenging due complexity variability of anomaly pattern. In this article, we propose novel unsupervised system called MSCA applies multiple sketches, K-means++...

In recent years, jointly utilizing local and global features to improve model performance is becoming an important approach for person re-identification. If the relationship between body parts not considered, it easy confuse identity differentiation of different persons with similar attributes in corresponding parts. To solve this problem, we propose a feature fusion-based method re-identification, which contains three core parts: adjacency module, counterfactual attention module difference...