This study examines the effectiveness of artificial intelligence techniques in generating high-quality environmental data for species introductory site selection *** Strengths,Weaknesses,Opportunities,Threats(SWOT)ana...
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This study examines the effectiveness of artificial intelligence techniques in generating high-quality environmental data for species introductory site selection *** Strengths,Weaknesses,Opportunities,Threats(SWOT)analysis data with Variation Autoencoder(VAE)and Generative AdversarialNetwork(GAN)the network framework model(SAE-GAN),is proposed for environmental data *** model combines two popular generative models,GAN and VAE,to generate features conditional on categorical data embedding after SWOT *** model is capable of generating features that resemble real feature distributions and adding sample factors to more accurately track individual sample *** data is used to retain more semantic information to generate *** model was applied to species in Southern California,USA,citing SWOT analysis data to train the *** show that the model is capable of integrating data from more comprehensive analyses than traditional methods and generating high-quality reconstructed data from them,effectively solving the problem of insufficient data collection in development *** model is further validated by the Technique for Order Preference by Similarity to an Ideal Solution(TOPSIS)classification assessment commonly used in the environmental data *** study provides a reliable and rich source of training data for species introduction site selection systems and makes a significant contribution to ecological and sustainable development.
To address the issue of delay-sensitive data collection in wireless sensor networks (WSNs), autonomous aerial vehicles (AAVs) offer a promising solution due to their flexibility and maneuverability. We investigate the...
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The lightest uranium isotope^(214)U has been produced at the Heavy lon Research Facility in Lanzhou,*** a-decay reduced width($2)of^(214)U has been found to be significantly larger than those of other nuclei by a fact...
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The lightest uranium isotope^(214)U has been produced at the Heavy lon Research Facility in Lanzhou,*** a-decay reduced width($2)of^(214)U has been found to be significantly larger than those of other nuclei by a factor of ***,the extraction ofσ^(2)depends on the penetration probability(P)through the barrier,and P is related to the theoretical method of obtaining it and the form of theα-core *** aim of this study is to investigate whether the selections of theα-core potential and the method of calculating P can affect the above *** different phenomenological a-core potentials and two microscopic double-folding potentials,together with the Wentzel-Kramers-Brillouin(WKB)approximation and transfer matrix(TM)approach,are used to obtain *** value of P obtained using the WKB approximation is about 20%-40%smaller than the one obtained using the TM ***,the deduced s2 is *** choice of a-core potential can significantly affect the value ofσ^(2).With the spherical form for theα-core potentials,theσ^(2)of^(214)U obtained with both the WKB and TM approaches are about twice as large as those of the surrounding *** the deformed double-folding potential,the ratio between 32 of^(214)U and that of the surrounding nuclei is observed to be slightly belowσ^(2).The effects of nuclear deformation and theα-core potential should be considered when studying theα-decay reduced width in the NpNn systematics.
Foam concrete has the advantages of energy and shock absorption which can be used as an impact resistant material. This article designed a three-layer concrete gradient structure and analyzed the failure mechanism of ...
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Conventional silicate cement is difficult to use in extremely cold regions. But alkali-activated slag concrete (AASC) can use alkali-activated chemistry to accelerate the production of C-A-S-H cementitious materials, ...
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To establish semantic associations between images and texts, existing Image-Text Retrieval (ITR) methods primarily focus on fixed-scale fragments, which only identify explicit semantic categories. Consequently, semant...
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To reduce key disagreement rate and increase key generation rate, this paper proposes a lightweight and robust shared secret key extraction scheme from atmospheric optical wireless channel. A conception of grouping sa...
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The compression and energy absorption properties of foam geopolymers increase stress wave attenuation under explosion impacts,reducing the vibration effect on the *** tests were conducted using several composite struc...
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The compression and energy absorption properties of foam geopolymers increase stress wave attenuation under explosion impacts,reducing the vibration effect on the *** tests were conducted using several composite structure models,including a concrete lining structure(CLS)without foam geopolymer and six foam geopolymer composite structures(FGCS)with different backfill parameters,to study the dynamic response and wave dissipation mechanisms of FGCS under explosive ***,strain,and vibration responses at different locations were synchronously *** damage modes and dynamic responses of different models were compared,and how wave elimination and energy absorption efficiencies were affected by foam geopolymer backfill parameters was *** results showed that the foam geopolymer absorbed and dissipated the impact energy through continuous compressive deformation under high strain rates and dynamic loading,reducing the strain in the liner structure by 52%and increasing the pressure attenuation rate by 28%.Additionally,the foam geopolymer backfill reduced structural vibration and liner deformation,with the FGCS structure showing 35%less displacement and 70%less acceleration compared to the *** FGCS model with thicker,less dense foam geopolymer backfill,having more pores and higher porosity,demonstrated better compression and energy absorption under dynamic impact,increasing stress wave attenuation *** analyzing the stress wave propagation and the compression characteristics of the porous medium,it was concluded that the stress transfer ratio of FGCS-ρ-579 was 77%lower than that of CLS,and the transmitted wave energy was 90%*** results of this study provide a scientific basis for optimizing underground composite structure interlayer parameters.
With the rapid proliferation of Internet ofThings(IoT)devices,ensuring their communication security has become increasingly *** and smart contract technologies,with their decentralized nature,provide strong security g...
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With the rapid proliferation of Internet ofThings(IoT)devices,ensuring their communication security has become increasingly *** and smart contract technologies,with their decentralized nature,provide strong security guarantees for ***,at the same time,smart contracts themselves face numerous security challenges,among which reentrancy vulnerabilities are particularly *** detection tools for reentrancy vulnerabilities often suffer from high false positive and false negative rates due to their reliance on identifying patterns related to specific transfer *** address these limitations,this paper proposes a novel detection method that combines pattern matching with deep ***,we carefully identify and define three common patterns of reentrancy vulnerabilities in smart ***,we extract key vulnerability features based on these ***,we employ a Graph Attention Neural Network to extract graph embedding features from the contract graph,capturing the complex relationships between different components of the ***,we use an attention mechanism to fuse these two sets of feature information,enhancing the weights of effective information and suppressing irrelevant information,thereby significantly improving the accuracy and robustness of vulnerability *** results demonstrate that our proposed method outperforms existing state-ofthe-art techniques,achieving a 3.88%improvement in accuracy compared to the latest vulnerability detection model AME(Attentive Multi-Encoder Network).This indicates that our method effectively reduces false positives and false negatives,significantly enhancing the security and reliability of smart contracts in the evolving IoT ecosystem.
In high-risk industrial environments like nuclear power plants, precise defect identification and localization are essential for maintaining production stability and safety. However, the complexity of such a harsh env...
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In high-risk industrial environments like nuclear power plants, precise defect identification and localization are essential for maintaining production stability and safety. However, the complexity of such a harsh environment leads to significant variations in the shape and size of the defects. To address this challenge, we propose the multivariate time series segmentation network(MSSN), which adopts a multiscale convolutional network with multi-stage and depth-separable convolutions for efficient feature extraction through variable-length templates. To tackle the classification difficulty caused by structural signal variance, MSSN employs logarithmic normalization to adjust instance distributions. Furthermore, it integrates classification with smoothing loss functions to accurately identify defect segments amid similar structural and defect signal subsequences. Our algorithm evaluated on both the Mackey-Glass dataset and industrial dataset achieves over 95% localization and demonstrates the capture capability on the synthetic dataset. In a nuclear plant's heat transfer tube dataset, it captures 90% of defect instances with75% middle localization F1 score.
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