Feature Selection(FS)is an important data management technique that aims to minimize redundant information in a *** work proposes DENGO,an improved version of the Northern Goshawk Optimization(NGO),to address the FS *...
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Feature Selection(FS)is an important data management technique that aims to minimize redundant information in a *** work proposes DENGO,an improved version of the Northern Goshawk Optimization(NGO),to address the FS *** NGO is an efficient swarm-based algorithm that takes its inspiration from the predatory actions of the northern *** order to overcome the disadvantages that NGO is prone to local optimum trap,slow convergence speed and low convergence accuracy,two strategies are introduced in the original NGO to boost the effectiveness of ***,a learning strategy is proposed where search members learn by learning from the information gaps of other members of the population to enhance the algorithm's global search ability while improving the population ***,a hybrid differential strategy is proposed to improve the capability of the algorithm to escape from the trap of the local optimum by perturbing the individuals to improve convergence accuracy and *** prove the effectiveness of the suggested DENGO,it is measured against eleven advanced algorithms on the CEC2015 and CEC2017 benchmark functions,and the obtained results demonstrate that the DENGO has a stronger global exploration capability with higher convergence performance and ***,the proposed DENGO is used for FS,and the 29 benchmark datasets from the UCL database prove that the DENGO-based FS method equipped with higher classification accuracy and stability compared with eight other popular FS methods,and therefore,DENGO is considered to be one of the most prospective FS ***'s code can be obtained at https://***/matlabcentral/fileexchange/158811-project1.
Wheat is the most widely grown crop in the world,and its yield is closely related to global food *** number of ears is important for wheat breeding and yield ***,automated wheat ear counting techniques are essential f...
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Wheat is the most widely grown crop in the world,and its yield is closely related to global food *** number of ears is important for wheat breeding and yield ***,automated wheat ear counting techniques are essential for breeding high-yield varieties and increasing grain ***,all existing methods require position-level annotation for training,implying that a large amount of labor is required for annotation,limiting the application and development of deep learning technology in the agricultural *** address this problem,we propose a count-supervised multiscale perceptive wheat counting network(CSNet,count-supervised network),which aims to achieve accurate counting of wheat ears using quantity *** particular,in the absence of location information,CSNet adopts MLP-Mixer to construct a multiscale perception module with a global receptive field that implements the learning of small target attention maps between wheat ear *** conduct comparative experiments on a publicly available global wheat head detection dataset,showing that the proposed count-supervised strategy outperforms existing position-supervised methods in terms of mean absolute error(MAE)and root mean square error(RMSE).This superior performance indicates that the proposed approach has a positive impact on improving ear counts and reducing labeling costs,demonstrating its great potential for agricultural counting *** code is available at .
Question Generation(QG)is the task of generating questions according to the given *** of the existing methods are based on Recurrent Neural Networks(RNNs)for generating questions with passage-level input for providing...
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Question Generation(QG)is the task of generating questions according to the given *** of the existing methods are based on Recurrent Neural Networks(RNNs)for generating questions with passage-level input for providing more details,which seriously suffer from such problems as gradient vanishing and ineffective information *** fact,reasonably extracting useful information from a given context is more in line with our actual needs during questioning especially in the education *** that end,in this paper,we propose a novel Hierarchical Answer-Aware and Context-Aware Network(HACAN)to construct a high-quality passage representation and judge the balance between the sentences and the whole ***,a Hierarchical Passage Encoder(HPE)is proposed to construct an answer-aware and context-aware passage representation,with a strategy of utilizing multi-hop ***,we draw inspiration from the actual human questioning process and design a Hierarchical Passage-aware Decoder(HPD)which determines when to utilize the passage *** conduct extensive experiments on the SQuAD dataset,where the results verify the effectivenesss of our model in comparison with several baselines.
Inner Product Functional Encryption (IPFE) offers strong privacy protection for smart devices by outputting only the results of function computations, minimizing data leakage. This makes it well-suited for privacy-pre...
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With the widespread use of machine learning(ML)technology,the operational efficiency and responsiveness of power grids have been significantly enhanced,allowing smart grids to achieve high levels of automation and ***...
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With the widespread use of machine learning(ML)technology,the operational efficiency and responsiveness of power grids have been significantly enhanced,allowing smart grids to achieve high levels of automation and ***,tree ensemble models commonly used in smart grids are vulnerable to adversarial attacks,making it urgent to enhance their *** address this,we propose a robustness enhancement method that incorporates physical constraints into the node-splitting decisions of tree *** algorithm improves robustness by developing a dataset of adversarial examples that comply with physical laws,ensuring training data accurately reflects possible attack scenarios while adhering to physical *** our experiments,the proposed method increased robustness against adversarial attacks by 100%when applied to real grid data under physical *** results highlight the advantages of our method in maintaining efficient and secure operation of smart grids under adversarial conditions.
Dialogue-based relation extraction(DialogRE) aims to predict relationships between two entities in dialogue. Current approaches to dialogue relationship extraction grapple with long-distance entity relationships in di...
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Dialogue-based relation extraction(DialogRE) aims to predict relationships between two entities in dialogue. Current approaches to dialogue relationship extraction grapple with long-distance entity relationships in dialogue data as well as complex entity relationships, such as a single entity with multiple types of connections. To address these issues, this paper presents a novel approach for dialogue relationship extraction termed the hypergraphs and heterogeneous graphs model(HG2G). This model introduces a two-tiered structure, comprising dialogue hypergraphs and dialogue heterogeneous graphs, to address the shortcomings of existing methods. The dialogue hypergraph establishes connections between similar nodes using hyper-edges and utilizes hypergraph convolution to capture multi-level features. Simultaneously, the dialogue heterogeneous graph connects nodes and edges of different types, employing heterogeneous graph convolution to aggregate cross-sentence information. Ultimately, the integrated nodes from both graphs capture the semantic nuances inherent in dialogue. Experimental results on the DialogRE dataset demonstrate that the HG2G model outperforms existing state-of-the-art methods.
Association in-between features has been demonstrated to improve the representation ability of data. However, the original association data reconstruction method may face two issues: the dimension of reconstructed dat...
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Association in-between features has been demonstrated to improve the representation ability of data. However, the original association data reconstruction method may face two issues: the dimension of reconstructed data is undoubtedly higher than that of original data, and adopted association measure method does not well balance effectiveness and efficiency. To address above two issues, this paper proposes a novel association-based representation improvement method, named as AssoRep. AssoRep first obtains the association between features via distance correlation method that has some advantages than Pearson’s correlation coefficient. Then an improved matrix is formed via stacking the association value of any two features. Next, an improved feature representation is obtained by aggregating the original feature with the enhancement matrix. Finally, the improved feature representation is mapped to a low-dimensional space via principal component analysis. The effectiveness of AssoRep is validated on 120 datasets and the fruits further prefect our previous work on the association data reconstruction.
Traditional blockchain key management schemes store private keys in the same location,which can easily lead to security issues such as a single point of ***,decentralized threshold key management schemes have become a...
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Traditional blockchain key management schemes store private keys in the same location,which can easily lead to security issues such as a single point of ***,decentralized threshold key management schemes have become a research focus for blockchain private key *** security of private keys for blockchain user wallet is highly related to user identity authentication and digital asset *** threshold blockchain private key management schemes based on verifiable secret sharing have made some progress,but these schemes do not consider participants’self-interested behavior,and require trusted nodes to keep private key fragments,resulting in a narrow application scope and low deployment efficiency,which cannot meet the needs of personal wallet private key escrow and recovery in public *** design a private key management scheme based on rational secret sharing that considers the self-interest of participants in secret sharing protocols,and constrains the behavior of rational participants through reasonable mechanism design,making it more suitable in distributed scenarios such as the public *** proposed scheme achieves the escrow and recovery of personal wallet private keys without the participation of trusted nodes,and simulate its implementation on smart *** to other existing threshold wallet solutions and keymanagement schemes based on password-protected secret sharing(PPSS),the proposed scheme has a wide range of applications,verifiable private key recovery,low communication overhead,higher computational efficiency when users perform one-time multi-key escrow,no need for trusted nodes,and personal rational constraints and anti-collusion attack capabilities.
Cloud computing, as a promising service platform, has gained significant popularity in addressing emerging data privacy issues in applications such as machine learning and data mining. Researchers have proposed the ve...
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This paper aims to investigate the problem of gaze object prediction in single images. We propose an application-friendly network based on CLIP for gaze object prediction. To avoid domain bias, we utilize a shallow fe...
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