An increasing number of deep learning methods is being applied to quantify the perception of urban environments, study the relationship between urban appearance and resident safety, and improve urban appearance. Most ...
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An increasing number of deep learning methods is being applied to quantify the perception of urban environments, study the relationship between urban appearance and resident safety, and improve urban appearance. Most advanced methods extract image feature representations from street-level images through conventional visual computation algorithms or deep convolutional neural networks and then directly predict the results using features. Unfortunately, these methods take color and texture information together during processing. Color and texture are prime image features, and they affect human perception and judgment differently. We argue that color and texture should be operated differently; therefore, we formulate an end-to-end learning methodology to process input images according to color and texture information before inputting it into the neural network. The processed images and the original image constitute three input streams for the triad attention ranking convolutional neural network(AR-CNN) model proposed in this *** accordance with the aspects of color and texture, an improved attention mechanism in the convolution layer is proposed. Our objective is to obtain the scores of humans on urban appearance in accordance with the prediction results computed from pairwise comparisons generated by the AR-CNN model.
Studies on the lung cancer genome are indispensable for developing a cure for lung ***-genome resequencing,genome-wide association studies,and transcriptome sequencing have greatly improved our understanding of the ca...
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Studies on the lung cancer genome are indispensable for developing a cure for lung ***-genome resequencing,genome-wide association studies,and transcriptome sequencing have greatly improved our understanding of the cancer ***,dysregulation of longrange chromatin interactions in lung cancer remains poorly *** better understand the three-dimensional(3D)genomic interaction features of the lung cancer genome,we used the A549 cell line as a model system and generated high-resolution chromatin interactions associated with RNA polymerase II(RNAPII),CCCTC-binding factor(CTCF),enhancer of zeste homolog 2(EZH2),and histone 3 lysine 27 trimethylation(H3K27me3)using long-read chromatin interaction analysis by paired-end tag sequencing(ChIA-PET).Analysis showed that EZH2/H3K27me3-mediated interactions further repressed target genes,either through loops or domains,and their distributions along the genome were distinct from and complementary to those associated with ***-related genes were highly enriched with chromatin interactions,and chromatin interactions specific to the A549 cell line were associated with oncogenes and tumor suppressor genes,such as additional repressive interactions on FOXO4 and promoter–promoter interactions between NF1 and *** of an anchor associated with chromatin interactions reversed the dysregulation of cancer-related genes,suggesting that chromatin interactions are essential for proper expression of lung cancer-related *** findings demonstrate the 3D landscape and gene regulatory relationships of the lung cancer genome.
Query optimization is a critical task in database systems, focused on determining the most efficient way to execute a query from an enormous set of possible strategies. Traditional approaches rely on heuristic search ...
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Magnesium alloys have gained extensive applications across various industries,including aerospace,transportation,and civil construction,owing to their excellent combinations of high specific strength and stiffness[1]....
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Magnesium alloys have gained extensive applications across various industries,including aerospace,transportation,and civil construction,owing to their excellent combinations of high specific strength and stiffness[1].However,their lim-ited strength due to the lack of effective strengthening phases has hindered their broader industrial applications[2].Never-theless,it has been challenging to achieve significant strength-ening due to the restricted solubility of alloying elements in magnesium[3].Thus,more and more efforts have been made to explore the concept of secondary phase-reinforced magne-sium alloys[2,4,5],where the secondary phase acts as re-inforcing agents within the magnesium matrix,resembling a composite material.
Multi-object tracking (MOT) is garnering more attention due to its widespread application in the area of autonomous driving, human-computer interaction, and intelligent video surveillance. Especially in recent years, ...
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Along with the integrated and miniaturized development of advanced electronic devices,phase change materials(PCMs)simultaneously with efficient thermal management and high electromag-netic interference(EMI)shielding e...
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Along with the integrated and miniaturized development of advanced electronic devices,phase change materials(PCMs)simultaneously with efficient thermal management and high electromag-netic interference(EMI)shielding effectiveness(SE)are ungently ***,the shape-stabilized MXene/Ni-platted melamine sponge/Regenerated cellulose/Graphene nanoplate/Polyethylene glycol(MX/Ni@MS/RCG/PEG)composite PCMs comprising hierarchical Ni@MS/RCG and MXene film were fabricated via a facile encapsulation *** Ni@MS/RCG hybrid aerogel was prepared by electroless plating and sol-gel methods,and MXene film was obtained using vacuum-assisted filtra-tion *** synergistic effect of conductive Ni@MS/RCG networks and tight MXene film endows MX/Ni@MS/RCG/PEG composite PCMs with good shape stability,high cyclic reliability,large latent heat of phase change(154.3 J g^(–1)),excellent thermal conductivity(TC,0.47 W m^(–1)K^(–1))and favorable EMI shield-ing performance(32.7 dB).The TC of acceptable 0.47 W m^(–1)K^(–1)is observed for MX/Ni@MS/RCG-5/PEG at a rather low GNP content of merely 0.39 wt%.In addition,the temperature variation of MX/Ni@MS/RCG-5/PEG is a lot faster than that of pure PEG in the heating/cooling process,revealing the remarkable energy storage and release efficiency for the composite *** investigation has taken an important step to-wards shape-stabilized composite PCMs with both effective thermal management and high EMI SE for promising applications in electronic packaging and advanced energy.
Few-shot knowledge graph completion (FKGC) aims to infer unknown fact triples of a relation using its few-shot reference entity pairs. Recent FKGC studies focus on learning semantic representations of entity pairs by ...
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In the context of the publication of the "Thirteenth Five-Year Plan for Educational Informationization," and China’s entry into the era of education informatization, the integration of information technolog...
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Voter model is an important basic model in statistical *** recent years,it has been more and more used to describe the process of opinion formation in *** real complex systems,the interactive network of individuals is...
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Voter model is an important basic model in statistical *** recent years,it has been more and more used to describe the process of opinion formation in *** real complex systems,the interactive network of individuals is dynamically adjusted,and the evolving network topology and individual behaviors affect each ***,we propose a linking dynamics to describe the coevolution of network topology and individual behaviors in this paper,and study the voter model on the adaptive *** theoretically analyze the properties of the voter model,including consensus probability and *** evolution of opinions on dynamic networks is further analyzed from the perspective of evolutionary ***,a case study of real data is shown to verify the effectiveness of the theory.
Multi-modal entity alignment (MMEA) aims to identify equivalent entities across different multi-modal knowledge graphs. In these graphs, entities are enriched with information from various modalities, such as text, im...
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ISBN:
(数字)9798331508821
ISBN:
(纸本)9798331508838
Multi-modal entity alignment (MMEA) aims to identify equivalent entities across different multi-modal knowledge graphs. In these graphs, entities are enriched with information from various modalities, such as text, images, and numerical data, making the alignment task both challenging and crucial for improving knowledge graph quality. Current MMEA algorithms typically encode entity information separately for each modality using corresponding encoders, and then integrate these representations through various modal fusion strategies. However, these methods often fail to fully exploit the multi-modal information of entities. To address this issue, we propose a feature-enhanced multi-modal entity alignment transformer (FEMEAT). FEMEAT enhances entity attribute information by incorporating modal distribution data, which captures the inherent distribution of different modalities for each entity. This inclusion allows the model to have a richer understanding of entity characteristics across modalities. Additionally, FEMEAT utilizes an Optical Character Recognition (OCR) model to extract and incorporate textual information from images. By integrating this text extracted from images, the model can better utilize the visual modality, enhancing its ability to understand and process multi-modal information. Furthermore, FEMEAT employs a multi-head cross-modal attention (MHCA) mechanism for modal fusion to achieve comprehensive multi-modal entity representation. This mechanism enables the model to attend to different modalities simultaneously and learn a detailed representation of entities by considering the interactions between modalities. The multi-head cross-modal attention mechanism facilitates a nuanced understanding and integration of multi-modal data. Experimental results demonstrate that our model achieves state-of-the-art (SOTA) performance across various training scenarios. The code and datasets used in this study can be accessed at https://***/zewenD/FEMEAT.
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