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Traditional federated learning faces challenges such as high communication costs, structural heterogeneity,and insufficient privacy protection. To address these issues, this paper proposes a federated learning evolutionary algorithm that applies sparse evolutionary training algorithm to reduce communication costs and integrates local differential privacy protection for participants’ privacy. Additionally, it utilizes the NSGA-Ⅲ algorithm to optimize the network structure and sparsity of the global federated learning model, adjusting the relationship between data availability and privacy protection. This achieves a balance between the effectiveness, communication costs, and privacy of the global federated learning model. Experimental results under unstable communication environments demonstrate that, on the MNIST and CIFAR-10 datasets, compared to the solution with the lowest error rate using the FNSGA-Ⅲ algorithm, the proposed algorithm improves communication efficiency by 57. 19% and 52. 17%, respectively. The participants also achieved（3. 46, 10-4） and（6. 52, 10-4）-local differential privacy. This algorithm can effectively reduce communication costs and protect participant privacy without significantly compromising the accuracy of the global model. [ABSTRACT FROM AUTHOR]

In view of the problems of data sparsity and the diversity in academic paper recom-mender systems,based on CONVNCF, this paper proposed an algorithm of convolution with word and heterogeneous information network for academic paper recommendation ( WN -APR) . Firstly, WN -APR algorithm learned user and paper' s diverse features from different semantics to alleviate the sparsity problem. Then it designed an outer product fusing way to seamlessly combine user features with paper features. Replacing of 2D CNN, this algorithm applied 3 D convolution to mine the influence of different features on the performance. Finally, it modified the BPR loss function to enhance diversity in recommendations. Experimental results on CiteULike-a and CiteULike-t datasets show that WN-APR improves the performance of accuracy and diversity over the baseline models. [ABSTRACT FROM AUTHOR]

To improve the accuracy of defect detection in bank note sorting and decrease the effects of cracks and scratches of bank note on detecting, a new algorithm based on wavelet decomposition is proposed, in which affine transform and wavelet transform are applied to bank note image registration and the edge information is extracted by Kirsch operator, while the defect feature is extracted from edge intensity differential. The bank note image is divided into several fixed size subzones, in each of which the defect feature is calculated to judge the degree of contamination. The experimental results reveal that the proposed feature extraction method is robust to the gray intensity change in each subbone, and obtains high recognition rate and high stability. This method has already been used in practical bank note sorting system. [ABSTRACT FROM AUTHOR]

Copyright of Journal of East China University of Science & Technology is the property of Journal of East China University of Science & Technology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Computer Engineering & Applications is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Computer Engineering & Applications is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Pulp & Paper is the property of China Pulp & Paper Magazines Publisher and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

To solve the problem of identifying similar questions in examination database, an algorithm for question similarity identification is proposed in this paper. By introducing domain words to the improvement of the word similarity model in HowNet, a model for question similarity identification is proposed to make the same or similar questions be identified and cut off automatically. This method improves the accuracy of identification compared with other methods. By combining merits of the random selection with those of the backtracking method, a new algorithm of generating papers automatically based on question similarity identification is proposed. It can guarantee the quality of papers. Test results show that the accuracy of question similarity identification of this method is 96% , which approaches to that of manual identification. This method can cut off similar questions not only of the same type, but also of different types. Finally, this method has been applied to the on-line examination of C programming language. [ABSTRACT FROM AUTHOR]

In order to solve the problems of the current art circulation information is not transparent and the centralized trading authority is asymmetric, this paper proposed a art blockchain certificate traceability model based on three chains. First, in view of the large amount of data in a single piece of artwork information, this paper proposed a blockchain-based symmetric searchable encryption algorithm, and used the interplanetary file system to securely store artwork circulation records on-chain and off-chain. Secondly, for the characteristics of the increasing effective data of artwork information, this paper proposed a blockchain-based inverted fast query and traceability algorithm to help data users realize fast traceability and positioning. At the same time, this paper proposed for the first time that the false information alliance chain stores false art circulation records to realize the processing of false information. Finally, experiments verify the feasibility of the model for big data security storage and fast query traceability. Experiments show that the model is feasible and the query method is efficient. [ABSTRACT FROM AUTHOR]

In view of the problem of fuzziness of rating and tag in traditional collaborative filtering algorithms,this paper used trapezoidal fuzzy number to describe the mapping relationship between rating and satisfaction.The algorithm considered the impact of sparseness of the rating,constructed a new trapezoidal fuzzy rating model to determine the similarity based on fuzzy rating,analyzed the degree of membership between the tag and the item,and constructed a fuzzy item-tag matrix to measure the similarity based on the degree of tag membership.Finally,it used the improved scoring prediction strategy to estimate the score.The experimental results on the MovieLens dataset show that the proposed algorithm improves the prediction accuracy while suppressing the cold start of the project,alleviating the problems of fuzziness and sparseness,which indicates the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]