The Internet of Things(loT)has grown rapidly due to artificial intelligence driven edge *** enabling many new functions,edge computing devices expand the vulnerability surface and have become the target of malware ***...
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The Internet of Things(loT)has grown rapidly due to artificial intelligence driven edge *** enabling many new functions,edge computing devices expand the vulnerability surface and have become the target of malware ***,attackers have used advanced techniques to evade defenses by transforming their malware into functionality-preserving *** systematically analyze such evasion attacks and conduct a large-scale empirical study in this paper to evaluate their impact on *** specifically,we focus on two forms of evasion attacks:obfuscation and adversarial *** the best of our knowledge,this paper is the first to investigate and contrast the two families of evasion attacks *** apply 10 obfuscation attacks and 9 adversarial attacks to 2870 malware *** obtained findings are as follows.(1)Commercial Off-The-Shelf(COTS)malware detectors are vulnerable to evasion attacks.(2)Adversarial attacks affect COTS malware detectors slightly more effectively than obfuscated malware examples.(3)Code similarity detection approaches can be affected by obfuscated examples and are barely affected by adversarial attacks.(4)These attacks can preserve the functionality of original malware examples.
The hot deformation behaviors of sulfur-containing gear steel 20MnCr5 containing three different contents of Nb and B(0,0.021%Nb,and 0.024%Nb-0.0022%B)were *** compression and tenssion tests were carried out by Gleebl...
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The hot deformation behaviors of sulfur-containing gear steel 20MnCr5 containing three different contents of Nb and B(0,0.021%Nb,and 0.024%Nb-0.0022%B)were *** compression and tenssion tests were carried out by Gleeble3800 at the austenite region from 850 to 1150℃and the adverse effects of Nb and B were analyzed by the fracture,microstructure and precipitate *** compression tests showed that the proportions of instable area in hot processing maps of 0.021%Nb and Nb-B steels were higher and the deformability of Nb free steel was *** tensile deformation experiments showed that the reduction areas of Nb free,0.021%Nb and Nb-B steels were 92%-99%,84%-98%and 67%-97%,*** addition of Nb or Nb and B inhibited the dynamic recrystallization during hot deformation,and consequently,more deformed grains were then formed in 0.021%Nb and Nb-B steels thus to obtain the microstructure with worse uniformity and then deteriorate the *** addition,the interaction between inclusions and microalloyed elements was also *** particles of 0.021%Nb and Nb-B steels dynamically precipitated during deformation and precipitated together with MnS thus to worsen the deformability,resulting in the decrease of reduction area.
Due to the small size of the annotated corpora and the sparsity of the event trigger words, the event coreference resolver cannot capture enough event semantics, especially the trigger semantics, to identify coreferen...
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Due to the small size of the annotated corpora and the sparsity of the event trigger words, the event coreference resolver cannot capture enough event semantics, especially the trigger semantics, to identify coreferential event mentions. To address the above issues, this paper proposes a trigger semantics augmentation mechanism to boost event coreference resolution. First, this mechanism performs a trigger-oriented masking strategy to pre-train a BERT (Bidirectional Encoder Representations from Transformers)-based encoder (Trigger-BERT), which is fine-tuned on a large-scale unlabeled dataset Gigaword. Second, it combines the event semantic relations from the Trigger-BERT encoder with the event interactions from the soft-attention mechanism to resolve event coreference. Experimental results on both the KBP2016 and KBP2017 datasets show that our proposed model outperforms several state-of-the-art baselines.
As a complex hot problem in the financial field,stock trend forecasting uses a large amount of data and many related indicators;hence it is difficult to obtain sustainable and effective results only by relying on empi...
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As a complex hot problem in the financial field,stock trend forecasting uses a large amount of data and many related indicators;hence it is difficult to obtain sustainable and effective results only by relying on empirical *** in the field of machine learning have proved that random forest can form better judgements on this kind of problem,and it has an auxiliary role in the prediction of stock *** study uses historical trading data of four listed companies in the USA stock market,and the purpose of this study is to improve the performance of random forest model in medium-and long-term stock trend *** study applies the exponential smoothing method to process the initial data,calculates the relevant technical indicators as the characteristics to be selected,and proposes the D-RF-RS method to optimize random *** the random forest is an ensemble learning model and is closely related to decision tree,D-RF-RS method uses a decision tree to screen the importance of features,and obtains the effective strong feature set of the model as ***,the parameter combination of the model is optimized through random parameter *** experimental results show that the average accuracy of random forest is increased by 0.17 after the above process optimization,which is 0.18 higher than the average accuracy of light gradient boosting machine *** with the performance of the ROC curve and Precision–Recall curve,the stability of the model is also guaranteed,which further demonstrates the advantages of random forest in medium-and long-term trend prediction of the stock market.
Nonprecious-metal-group single-metal-atom catalysts with bifunctional catalytic capabilities toward the oxygen evolution reaction(OER)and oxygen reduction reaction(ORR)are highly sought after in energy-conversion and ...
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Nonprecious-metal-group single-metal-atom catalysts with bifunctional catalytic capabilities toward the oxygen evolution reaction(OER)and oxygen reduction reaction(ORR)are highly sought after in energy-conversion and storage ***,producing renewable and sustainable energy sources remains ***,single-transition metal atoms anchored onπ-πconjugated two-dimensional(2D)graphitic carbon nitride substrates formπ-d conjugated conductive channels that enhance the overall electrocatalytic ***,firstprinciples calculations were carried out to design and demonstrate a novel macropore graphitic carbon nitride(gC_(10)N_(3))as a promising 2D electrocatalyst substrate to support single-transition metal(TM,from Sc to Au).The"donation-acceptance"charge interaction in the TM-N_(2)moiety effectively balances the adsorption strength of oxygenated intermediates in Ni@g-C_(10)N_(3)and Rh@gC_(10)N_3,making them effective bifunctional OER/ORR electrocatalysts with IrO_(2)/Pt-beyond overpotentials being as low as 0.39/0.38 V and 0.54/0.44 V,***,they possess high stability and conductivity and are less susceptible to oxidation and corrosion under working *** guarantees high activity under ambient ***,the origin of the OER/ORR activity of TM@g-C_(10)N_(3) is explained using multilevel descriptors:intrinsic(p,Bader charge,integral crystal orbital Hamilton population(ICOHP),bond length,and d-band center(εd).In particular,for optimal Ni@g-C_(10)N_(3),the clear hybridization between the Ni-d orbital and surface O-p orbital causes the paired electrons to occupy the bonding *** enables OH~*to be adsorbed on the Ni@g-C_(10)N_(3),thereby achieving the highest catalytic performance.
Early studies on discourse rhetorical structure parsing mainly adopt bottom-up approaches,limiting the parsing process to local *** current top-down parsers can better capture global information and have achieved part...
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Early studies on discourse rhetorical structure parsing mainly adopt bottom-up approaches,limiting the parsing process to local *** current top-down parsers can better capture global information and have achieved particular success,the importance of local and global information at various levels of discourse parsing is *** paper argues that combining local and global information for discourse parsing is more *** prove this,we introduce a top-down discourse parser with bidirectional representation learning *** corpora on Rhetorical Structure Theory(RST)are known to be much limited in size,which makes discourse parsing very *** alleviate this problem,we leverage some boundary features and a data augmentation strategy to tap the potential of our *** use two methods for evaluation,and the experiments on the RST-DT corpus show that our parser can pri-marily improve the performance due to the effective combination of local and global *** boundary features and the data augmentation strategy also play a *** on gold standard elementary discourse units(EDUs),our pars-er significantly advances the baseline systems in nuclearity detection,with the results on the other three indicators(span,relation,and full)being *** on automatically segmented EDUs,our parser still outperforms previous state-of-the-artwork.
Current methods for Music Emotion Recognition (MER) face challenges in effectively extracting features sensitive to emotions, especially those rich in temporal detail. Moreover, the narrow scope of music-related modal...
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As urban populations grow, smart home technology has become a key enabler for enhancing energy efficiency, comfort, and convenience in residential environments. However, existing smart home implementations often strug...
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We theoretically investigate coherent scattering of single photons and quantum entanglement of two giant atoms with azimuthal angle differences in a waveguide *** the real-space Hamiltonian,analytical expressions are ...
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We theoretically investigate coherent scattering of single photons and quantum entanglement of two giant atoms with azimuthal angle differences in a waveguide *** the real-space Hamiltonian,analytical expressions are derived for the transport spectra scattered by these two giant atoms with four azimuthal ***-like resonance can be exhibited in the scattering spectra by adjusting the azimuthal angle *** concurrence of the entangled state for two atoms can be implemented in a wide angle-difference range,and the entanglement of the atomic states can be switched on/off by modulating the additional azimuthal angle differences from the giant *** suggests a novel handle to effectively control the single-photon scattering and quantum entanglement.
Gesture recognition has diverse application prospects in the field of human-computer ***,gesture recognition devices based on strain sensors have achieved remarkable results,among which liquid metal materials have con...
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Gesture recognition has diverse application prospects in the field of human-computer ***,gesture recognition devices based on strain sensors have achieved remarkable results,among which liquid metal materials have considerable advantages due to their high tensile strength and *** improve the detection sensitivity of liquid metal strain sensors,a sawtooth-enhanced bending sensor is proposed in this *** with the results from previous studies,the bending sensor shows enhanced resistance *** addition,combined with machine learning algorithms,a gesture recognition glove based on the sawtooth-enhanced bending sensor is also fabricated in this study,and various gestures are accurately *** the fields of human-computer interaction,wearable sensing,and medical health,the sawtooth-enhanced bending sensor shows great potential and can have wide application prospects.
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