Given that analysis on the vulnerability of functions is helpful to the detection and improvement of software security, this paper aims to propose an efficient methods to identify the vulnerable nodes (ITVN) in differ...
Given that analysis on the vulnerability of functions is helpful to the detection and improvement of software security, this paper aims to propose an efficient methods to identify the vulnerable nodes (ITVN) in different software by the interdependence of functions. First, the dynamic software execution process was constructed as Software Execution Dependency Network (SEDN) based on Complex network theory. Second, by analyzing the dependency relationship among functions, the algorithm calVulAndScoOfNodes (CVSN) was designed to compute the vulnerability and the affected scope of each node for further analysis. Third, in order to measure the functions vulnerability in the whole software network, the algorithm calVulDegreeOfNodes (CVDN) was put forward to calculate the vulnerable degree of each node. Finally, the Vulnerable Nodes in different software were obtained by ITVN. Experimental results show that the vulnerable nodes selected as important nodes are well-reasoned in software network by testing different software, and the measures are effective for evaluating nodes vulnerability.
With the research of influence maximization algorithm, many researchers have found that the existing algorithm has the problem of overlapping influence of seed nodes. In order to solve the problem of overlapping influ...
With the research of influence maximization algorithm, many researchers have found that the existing algorithm has the problem of overlapping influence of seed nodes. In order to solve the problem of overlapping influence of seed nodes, this paper proposes an IMCS algorithm based on community structure. Firstly, we divide the community through the central node, and the quality of community division is ensured by defining community fitness and node contribution. Then through the analysis of the community division results, the seed node selects the one with the largest degree. Since most of the nodes activated by seed nodes of different communities also belong to different communities, this method solves the problem of overlapping influence to a certain extent. The experimental results show that the effectiveness of the IMCS algorithm is verified under the real network, cooperative network and artificial network, and the IMCS algorithm has a better effect than IEIR and Degree algorithms in most networks under the IC model.
In order to maximize the influence of commodity profits in e-commerce platforms, designing and improving the K-shell algorithm to select the more influential seed node sets in this paper. The new algorithm improves th...
In order to maximize the influence of commodity profits in e-commerce platforms, designing and improving the K-shell algorithm to select the more influential seed node sets in this paper. The new algorithm improves the number of active nodes by setting node threshold and edge weight attributes. To obtain more commodity profits, a strategy IRDSN (Strategy for Improving Repeat Degree of Seed Nodes) is proposed to select initial seed nodes and improve the repeat degree of seed nodes. The profit maximization based on linear threshold model is realized by setting different propagation modes. The improved algorithm and strategy IRDSN are analysed and verified in real data set and e-commerce platform. The results show that the algorithm effectively improves the profit of commodities.
Friend recommendation is a fundamental service for both social networks and practical applications. The majority of existing friend-recommendation methods utilize user profiles, social relationships, or static post co...
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The form of books is constantly developing with the upgrading of carrying media, and the emergence of electronic books has greatly shaken the traditional paper books. In recent years, with the combination of artificia...
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ISBN:
(纸本)9781538684986;9781538684979
The form of books is constantly developing with the upgrading of carrying media, and the emergence of electronic books has greatly shaken the traditional paper books. In recent years, with the combination of artificial intelligence, virtual reality, high-speed network and digital reading, the concept of "VR" has been applied to more and more industries. The introduction of VReading multi-sensory reading platform will bring new ideas to digital reading industry.
Cloud storage is one of the key services in cloud computing. In order to appeal more users to the cloud storage, free cloud experience is provided to potential users. A registration server is set specially for intenti...
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SYVR is a real-time simulation graphic engine focusing on equipment manufacturing. It is based on decades of research works of physics simulations, is able to provide services like real-time simulation for key parts o...
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ISBN:
(纸本)9781538684986;9781538684979
SYVR is a real-time simulation graphic engine focusing on equipment manufacturing. It is based on decades of research works of physics simulations, is able to provide services like real-time simulation for key parts of devices, large-scale com-plicated situation simulation, virtual experiment, operational training, visualization of concept design and etc., which con-sist of the whole process of virtual manufacturing and simulation. SYVR can provide comprehensive technology support for industrial 3-dimensional data, accelerate applications of VR to all aspects of industry, cut down development costs of equipment manufacturing significantly, highly increase effi-ciency of equipment design, and promote development of equipment manufacturing.
Background: An artificial intelligence system of Faster Region-based Convolutional Neural Network (Faster R-CNN) is newly developed for the diagnosis of metastatic lymph node (LN) in rectal cancer patients. The primar...
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Background: An artificial intelligence system of Faster Region-based Convolutional Neural Network (Faster R-CNN) is newly developed for the diagnosis of metastatic lymph node (LN) in rectal cancer patients. The primary objective of this study was to comprehensively verify its accuracy in clinical use. Methods: Four hundred fourteen patients with rectal cancer discharged between January 2013 and March 2015 were collected from 6 clinical centers, and the magnetic resonance imaging data for pelvic metastatic LNs of each patient was identified by Faster R-CNN. Faster R-CNN based diagnoses were compared with radiologist based diagnoses and pathologist based diagnoses for methodological verification, using correlation analyses and consistency check. For clinical verification, the patients were retrospectively followed up by telephone for 36 months, with post-operative recurrence of rectal cancer as a clinical outcome;recurrence-free survivals of the patients were compared among different diagnostic groups, by methods of Kaplan-Meier and Cox hazards regression model. Results: Significant correlations were observed between any 2 factors among the numbers of metastatic LNs separately diagnosed by radiologists, Faster R-CNN and pathologists, as evidenced by rradiologist-Faster R-CNN of 0.912, rPathologist-radiologist of 0.134, and rPathologist-Faster R-CNN of 0.448 respectively. The value of kappa coefficient in N staging between Faster R-CNN and pathologists was 0.573, and this value between radiologists and pathologists was 0.473. The 3 groups of Faster R-CNN, radiologists and pathologists showed no significant differences in the recurrence-free survival time for stage N0 and N1 patients, but significant differences were found for stage N2 patients. Conclusion: Faster R-CNN surpasses radiologists in the evaluation of pelvic metastatic LNs of rectal cancer, but is not on par with pathologists.
The existing robust collaborative recommendation algorithms have low robustness against PIA and Ao P attacks. Aiming at the problem, we propose a robust recommendation method based on shilling attack detection and mat...
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The existing robust collaborative recommendation algorithms have low robustness against PIA and Ao P attacks. Aiming at the problem, we propose a robust recommendation method based on shilling attack detection and matrix factorization model. Firstly, the type of shilling attack is identified based on statistical characteristics of attack profiles. Secondly, we devise corresponding unsupervised detection algorithms for standard attack, Ao P and PIA, and the suspicious users and items are flagged. Finally, we devise a robust recommendation algorithm by combining the proposed shilling attack detection algorithm with matrix factorization model, and conduct experiments on the Movie Lens dataset to demonstrate its effectiveness. Experimental results show that the proposed method exhibits good recommendation precision and excellent robustness for shilling attacks of multiple types.
Guiding assembly system based on AR is to apply the technol-ogy of Augmented Reality to guide mechanical assembly op-eration and teach or train freshmen. By the means of adapting AR glasses(HoloLens, Magic Leap One et...
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ISBN:
(纸本)9781538684986;9781538684979
Guiding assembly system based on AR is to apply the technol-ogy of Augmented Reality to guide mechanical assembly op-eration and teach or train freshmen. By the means of adapting AR glasses(HoloLens, Magic Leap One etc.), we use virtual information to guide operating real mechanic. AR operation can achieve better effect than traditional reality training, and make industrial assembly process easier for costumers to un-derstand. It can also decrease losses caused by operational error, therefore increases efficiency safety and productivity.
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