One of the traditional ways for detecting dynamic communities is to find the communities at each interval through the static community detection ***,it usually leads to high computation *** this paper,a novel algorith...
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ISBN:
(纸本)9781509036202
One of the traditional ways for detecting dynamic communities is to find the communities at each interval through the static community detection ***,it usually leads to high computation *** this paper,a novel algorithm based on the Map Reduce model and the label propagation progress with the strategy of incremental related vertices is proposed,which is called PLPIRV(Parallel Label Propagation and Incremental Related Vertices).Based on the communities found at the previous interval,the new algorithm adjusts the communities the incremental related vertices belong *** clustering of the whole network can be avoided by incrementally analyzing the variation of the networks,so that the time cost can be greatly *** on artificial and real datasets show that the proposed algorithm performs well on dynamic community detection.
Aiming at the problems that complex testing process, incomplete testing and poor reusability of test cases for Android automated testing methods, we propose a generation method of automation test cases based on contro...
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Aiming at the problems that complex testing process, incomplete testing and poor reusability of test cases for Android automated testing methods, we propose a generation method of automation test cases based on control traversal under the guidance of standard path. The method firstly records a test script as a standard path by the tester, then automatically acquires the control in the interface and generates the control relationship graph. Finally, the test case generation method based on the depth-first search was used to traverse the control relationship graph to generate test cases. The test case was used to test the Android mobile App. The results show that the test case generated by this method improves the test coverage and script reusability, simplifies the test operation and proves the feasibility of the method.
作者:
Jiao, GeLi, LangZou, YiCollege of Computer Science and Technology
Hengyang Normal UniversityHunan Provincial Engineering Laboratory for Technology of Traditional Settlements Digitalization Hunan Provincial Key Laboratory of Intelligent Information Processing and Application Hengyang Hunan421002 China
The power attack of the hardware circuit is going through the steps of algorithm writen in FPGA, power consumption, data processing and analysis. In order to solve the problem of the existing power attack experimental...
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Without the aid of licensed channel, deploying long-term evolution (LTE) networks over unlicensed spectrum (named standalone LTE-U networks) faces the difficulty of establishing and maintaining synchronisation between...
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Without the aid of licensed channel, deploying long-term evolution (LTE) networks over unlicensed spectrum (named standalone LTE-U networks) faces the difficulty of establishing and maintaining synchronisation between user equipments and base stations. In this work, considering the two modes of listen-before-talk-based channel access scheme, frame-based equipment (FBE) and load-based equipment (LBE), the authors propose analytical frameworks to study the successful probability of synchronisation and the energy consumption of synchronisation in a standalone LTE-U network. Specifically, for the LBE mode, the authors also propose a Lattice-Poisson algorithmbased approach to derive the distribution of the channel non-occupancy period of a standalone LTE-U network. Furthermore, the authors explore the impact of diverse protocol parameters of both FBE and LBE modes on the two studied performance metrics. Simulation results demonstrate the accuracy of the analysis, and shed some light on the selection of FBE and LBE for standalone LTE-U networks, in terms of synchronisation, energy consumption, and throughput of standalone LTE-U and Wi-Fi networks.
Machine learning is knowledge of learning rules from data through computational models and algorithms. It has been applied in various fields that require mining rules from complex data, and has become one of the most ...
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Machine learning is knowledge of learning rules from data through computational models and algorithms. It has been applied in various fields that require mining rules from complex data, and has become one of the most core technologies in the field of artificial intelligence in the broad sense. In recent years, a variety of deep neural networks have made remarkable achievements in a large number of machine learning problems, forming a new branch of machine learning, deep learning, and also raising a new climax of machine learning theory, method and application research. Software security is a highly concerned issue at present. Vulnerability detection technology is an important measure to improve software security. In order to make software application more secure, it is necessary to discuss the application of deep learning in software security detection.
This paper analyzes the current situation of blockchain application security. Then, makes a concrete analysis on the problems existing in the application safety of blockchain, including the attack of consensus algorit...
This paper analyzes the current situation of blockchain application security. Then, makes a concrete analysis on the problems existing in the application safety of blockchain, including the attack of consensus algorithm, the leakage of privacy, and the programming vulnerability of blockchain and hash collisions. Then it introduces in detail the three key technologies of security protection under the blockchain application environment, P2P network technology, asymmetric encryption technology and consensus mechanism technology. In order to make more relevant people know more about the key technologies of safety protection in the application environment of blockchain.
In order to improve the reliability and life of components, product providers often take the form of redundant backup. The lower the failure rate of the product itself and the more the number of redundant backups, the...
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This paper proposes a new object classification method based on an improved bacterial foraging optimisation algorithm. Firstly, a dynamic step size is used instead of the fixed step size of the chemotaxis. Secondly, t...
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To solve the radio frequency identification problem, an anti-collision algorithm based on the Gray code (BSGC) was developed. The proposed algorithm reduces the effort required to search for tag prefixes in accordance...
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The smart contract is an interdisciplinary concept that concerns business, finance, contract law and informationtechnology. Designing and developing a smart contract may require the close cooperation of many experts ...
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ISBN:
(纸本)9781538626672
The smart contract is an interdisciplinary concept that concerns business, finance, contract law and informationtechnology. Designing and developing a smart contract may require the close cooperation of many experts coming from different fields. How to support such collaborative development is a challenging problem in blockchain-oriented software engineering. This paper proposes SPESC, a specification language for smart contracts, which can define the specification of a smart contract for the purpose of collaborative design. SPESC can specify a smart contract in a similar form to real-world contracts using a natural-language-like grammar, in which the obligations and rights of parties and the transaction rules of cryptocurrencies are clearly defined. The preliminary study results demonstrated that SPESC can be easily learned and understood by both IT and non-IT users and thus has greater potential to facilitate collaborative smart contract development.
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