On the basis of fast Multi-Agent System (MAS) application development with Agent Pattern Language (APL), this paper proposed a framework of process-oriented enterprise application integration. According to the general characteristics of business process, the framework adopted a hierarchy structure for the business process to separate business logic and implementation. Then some local changes of sub-process had less influence on the execution of global business process. Besides, roles and structured activities were adopted in the framework. The business process can be divided into sub-process with roles to form the hierarchy structure. The structured activities were used to describe complex business process. With the framework, the enterprise application integration can be implemented in an effective way, and the implementation will be more flexible.

A framework of semantic Web service composition based on abstract template was proposed, and analysis of the template retrieval, data pre-processing and template adaptation modules of this framework were introduced in detail. In order to improve the accuracy of the template retrieval, the framework adopted the feature matching and graph matching methods in the similarity computation between the abstract template and the user’s request. Besides, it constructed the service dependency graph through the data pre-processing, deleted the useless services and verified the satisfiability of the user’s request. According to the service dependency graph, it implemented the automatic template adaptation, by using the Heuristic Plan Adaptation Algorithm (HPAA), and improved the adaptability and scalability of HPAA by providing the function of the flexible configuration of the heuristic strategies. Finally, the experiments on the different heuristic strategies show the effectiveness and reliability of HPAA when dealing with the large-scale problems.

Due to the difficulty of factoring multivariate polynomials, a new implementation of high performance named HPFMF was proposed based on NTL and the existence of factorization algorithms. The NTL was introduced and how to apply the library to implement the algorithms of number theory and computer algebra was discussed. The factoring multivariate polynomials was successfully designed and implemented. Experimental results show that the method is more efficient than factor in Maple 11 for multivariate polynomials.

The Shin's signcryption scheme with public verifiability of Shin et al.and the proxy signcryption scheme of Jung et al. were cryptoanalyzed and improved. By studying the confidentiality of Shin's scheme and Jung's scheme, and the proxy authority of Jung's scheme, the fact is that the confidentiality of Shin's scheme and Jung's scheme was lost, and the proxy authority of Jung's scheme was not controlled. Then a modification based on Shin's scheme was presented. The modification was a security proxy signcryption scheme with public verifiability and controllable authority. Based on some cryptographic assumptions, the security of the scheme was also proved.

Construction， mining， exploration and other industries have mandatory regulations on helmet wearing in production. The helmet wearing detection algorithms have been widely used in the above industries， but the existing algorithms have problems such as too many parameters， high complexity and poor real-time performance. Therefore， a lightweight safety helmet wearing detection algorithm YOLO v8-s-LE was proposed on the basis of YOLO v8 （You Only Look Once v8）. Firstly， the LAD （Light Adaptive-weight Downsampling） method was designed，so that compared with the original YOLO v8 algorithm， the proposed algorithm reduced floating-point computation significantly. Then， the efficient multi-scale convolution C2f_EMC （C2f_Efficient Multi-Scale Conv） method was used to extract multi-scale feature information， which increased the depth of the network effectively， made the neural network take into account both shallow and deep semantic information， and further improved the expression ability of the algorithm for feature information. Experimental results show that compared with YOLO v8-s algorithm on the public dataset SHWD （Safety Helmet Wearing Dataset）， the proposed algorithm has the parameters reduced by 77%， the floating-point computation reduced by 73%， and the precision reached 92.6%， verifying that the algorithm takes into account the requirements of accuracy and real-time performance， and is more suitable for the deployment and application in actual production environments.