Metapaths with specific complex semantics are critical to learning diverse semantic and structural information of heterogeneous networks(HNs)for most of the existing representation learning ***,any metapaths consistin...
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Metapaths with specific complex semantics are critical to learning diverse semantic and structural information of heterogeneous networks(HNs)for most of the existing representation learning ***,any metapaths consisting of multiple,simple metarelations must be driven by domain *** sensitive,expensive,and limited metapaths severely reduce the flexibility and scalability of the existing models.A metapath-free,scalable representation learning model,called Metarelation2vec,is proposed for HNs with biased joint learning of all metarelations in a bid to address this ***,a metarelation-aware,biased walk strategy is first designed to obtain better training samples by using autogenerating cooperation probabilities for all metarelations rather than using expert-given ***,grouped nodes by the type,a common and shallow skip-gram model is used to separately learn structural proximity for each node ***,grouped links by the type,a novel and shallow model is used to separately learn the semantic proximity for each link ***,supervised by the cooperation probabilities of all meta-words,the biased training samples are thrown into the shallow models to jointly learn the structural and semantic information in the HNs,ensuring the accuracy and scalability of the *** experimental results on three tasks and four open datasets demonstrate the advantages of our proposed model.
The performances of magnesium alloys remain insufficient to further enhance the application potential of ultralight magnesium *** this work,a Mg-8Li-3Y-2Zn alloy was prepared through vacuum melting and subsequent heat ...
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The performances of magnesium alloys remain insufficient to further enhance the application potential of ultralight magnesium *** this work,a Mg-8Li-3Y-2Zn alloy was prepared through vacuum melting and subsequent heat treatment at 300,450,and 500°*** material properties of the resulting samples were assessed through microstructural observation,tensile testing,electrical conductivity measurements,and electromagnetic shielding effectiveness(EMI-SE)*** influence of the Mg-8Li-3Y-2Zn alloy microstructure on its mechanical and electromagnetic shielding properties in different states was *** was found that the as-cast alloy containsα-Mg,β-Li,Mg_(3)Zn_(3)Y_(2),and Mg_(12)ZnY *** heat treatment at 500℃(HT500),the blockα-Mg phase transformedfine needle-shapes,its tensile strength increased to 263.7 MPa,and its elongation reached 45.3%.The mechanical properties of the alloy were significantly improved by the synergistic effects imparted by the needle-shapedα-Mg phase,solid solution strengthening,and precipitation *** addition of Y and Zn improved the EMI-SE of Mg-8Li-1Zn alloy,wherein the HT500 sample exhibits the highest SE,maintaining a value of 106.7–76.9 dB in the frequency range of 30–4500 MHz;this performance has rarely been reported for electromagnetically shielded *** effect was mainly attributed to the multiple reflections of electromagnetic waves caused by the severe impedance mismatch of the abundant phase boundaries,which were in turn provided by the dual-phase(α/β)and secondary ***,the presence of nano-precipitation was also believed to enhance the absorption of electromagnetic waves.
Accurate prediction of the state-of-charge(SOC)of battery energy storage system(BESS)is critical for its safety and lifespan in electric *** overcome the imbalance of existing methods between multi-scale feature fusio...
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Accurate prediction of the state-of-charge(SOC)of battery energy storage system(BESS)is critical for its safety and lifespan in electric *** overcome the imbalance of existing methods between multi-scale feature fusion and global feature extraction,this paper introduces a novel multi-scale fusion(MSF)model based on gated recurrent unit(GRU),which is specifically designed for complex multi-step SOC prediction in practical *** correlation analysis is first employed to identify SOC-related *** parameters are then input into a multi-layer GRU for point-wise feature ***,the parameters undergo patching before entering a dual-stage multi-layer GRU,thus enabling the model to capture nuanced information across varying time ***,by means of adaptive weight fusion and a fully connected network,multi-step SOC predictions are *** extensive validation over multiple days,it is illustrated that the proposed model achieves an absolute error of less than 1.5%in real-time SOC prediction.
Purpose: The rapid spread of COVID-19 has resulted in significant harm and impacted tens of millions of people globally. In order to prevent the transmission of the virus, individuals often wear masks as a protective ...
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This study proposes a malicious code detection model DTL-MD based on deep transfer learning, which aims to improve the detection accuracy of existing methods in complex malicious code and data scarcity. In the feature...
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In this work,a novel microwave absorbing material(MAM)made of a pseudo-binary of Sr_(2)TiMoO_(6)-Al_(2)O_(3)(STM)is proposed *** MAMs labeled as STM X(X=60,70,80 and 100,respectively),in which X is the initial weight ...
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In this work,a novel microwave absorbing material(MAM)made of a pseudo-binary of Sr_(2)TiMoO_(6)-Al_(2)O_(3)(STM)is proposed *** MAMs labeled as STM X(X=60,70,80 and 100,respectively),in which X is the initial weight percent of Sr_(2)TiMoO_(6),were synthesized using the solid-state reaction *** with STM100,some equilibrium phases,including SrTiO_(3),Mo,Sr_(8)(Al1_(2)O_(24))(MoO_(4))_(2)and a few undefined ones,are presented in the composites as evidenced by X-ray diffraction results and scanning electron microscopy due to the chemical reaction between Sr_(2)TiMoO_(6)and Al_(2)O_(3)*** conductance loss,heterogeneous interfaces between various equilibrium phases introduce interfacial polarization,which causes an enhancement of dissipation for the incident electromagnetic *** the synthesized samples,STM80 presents the best microwave absorbing *** has a minimum reflection loss(RLmin)of-26 dB and an effective absorbing bandwidth up to 2.7 GHz when the thickness is only 1 *** indicates that STM80 is a new type of microwave absorbing material with strong absorption and ultrathin thickness.
The use of generative adversarial network(GAN)-based models for the conditional generation of image semantic segmentation has shown promising results in recent ***,there are still some limitations,including limited di...
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The use of generative adversarial network(GAN)-based models for the conditional generation of image semantic segmentation has shown promising results in recent ***,there are still some limitations,including limited diversity of image style,distortion of detailed texture,unbalanced color tone,and lengthy training *** address these issues,we propose an asymmetric pre-training and fine-tuning(APF)-GAN model.
The Nong Han Chaloem Phrakiat Lotus Park is a tourist attraction and a source of learning regarding lotus ***,as a training area,it lacks appeal and learning motivation due to its conventional presentation of informat...
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The Nong Han Chaloem Phrakiat Lotus Park is a tourist attraction and a source of learning regarding lotus ***,as a training area,it lacks appeal and learning motivation due to its conventional presentation of information regarding lotus *** current study introduced the concept of smart learning in this setting to increase interest and motivation for *** neural networks(CNNs)were used for the classification of lotus plant species,for use in the development of a mobile application to display details about each *** scope of the study was to classify 11 species of lotus plants using the proposed CNN model based on different techniques(augmentation,dropout,and L2)and hyper parameters(dropout and epoch number).The expected outcome was to obtain a high-performance CNN model with reduced total parameters compared to using three different pre-trained CNN models(Inception V3,VGG16,and VGG19)as *** performance of the model was presented in terms of accuracy,F1-score,precision,and recall *** results showed that the CNN model with the augmentation,dropout,and L2 techniques at a dropout value of 0.4 and an epoch number of 30 provided the highest testing accuracy of *** best proposed model was more accurate than the pre-trained CNN models,especially compared to Inception *** addition,the number of total parameters was reduced by approximately 1.80–2.19 *** findings demonstrated that the proposed model with a small number of total parameters had a satisfactory degree of classification accuracy.
Handwriting is a unique and significant human feature that distinguishes them from one *** are many researchers have endeavored to develop writing recognition systems utilizing specific signatures or symbols for perso...
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Handwriting is a unique and significant human feature that distinguishes them from one *** are many researchers have endeavored to develop writing recognition systems utilizing specific signatures or symbols for person identification through ***,such systems are susceptible to forgery,posing security *** response to these challenges,we propose an innovative hybrid technique for individual identification based on independent handwriting,eliminating the reliance on specific signatures or *** response to these challenges,we propose an innovative hybrid technique for individual identification based on independent handwriting,eliminating the reliance on specific signatures or *** innovative method is intricately designed,encompassing five distinct phases:data collection,preprocessing,feature extraction,significant feature selection,and *** key advancement lies in the creation of a novel dataset specifically tailored for Bengali handwriting(BHW),setting the foundation for our comprehensive ***-preprocessing,we embarked on an exhaustive feature extraction process,encompassing integration with kinematic,statistical,spatial,and composite *** meticulous amalgamation resulted in a robust set of 91 *** enhance the efficiency of our system,we employed an analysis of variance(ANOVA)F test and mutual information scores approach,meticulously selecting the most pertinent *** the identification phase,we harnessed the power of cutting-edge deep learning models,notably the Convolutional Neural Network(CNN)and Bidirectional Long Short-Term Memory(BiLSTM).These models underwent rigorous training and testing to accurately discern individuals based on their handwriting ***,our methodology introduces a groundbreaking hybrid model that synergizes CNN and BiLSTM,capitalizing on fine motor features for enhanced individual ***,our experimental results unde
The Internet of Medical Things (IoMT) brings advanced patient monitoring and predictive analytics to healthcare but also raises cybersecurity and data privacy issues. This paper introduces a deep-learning model for Io...
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