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1041
Collective Behavior Analysis and Graph Mining in Social Networks 2021
Published 2022-01-01Get full text
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1042
Performance Evaluation of New Joint EDF-RM Scheduling Algorithm for Real Time Distributed System
Published 2014-01-01Get full text
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1043
Secure IoT data dissemination with blockchain and transfer learning techniques
Published 2025-01-01Get full text
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1044
Evaluating Mobile Telecom Apps: An Integrated Fuzzy MCDM Model Using Marketing Mix
Published 2025-01-01“…Typically, telecom providers must invest an amount of company resources to develop and maintain the operations mechanism of information technology platforms (e.g., mobile apps); therefore, it is important to take the issue of marketing effectiveness into account. …”
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Joint Identification and Sensing for Discrete Memoryless Channels
Published 2024-12-01Get full text
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Numerical Analysis on the Effects of Binary Interaction between Typhoons Tembin and Bolaven in 2012
Published 2019-01-01Get full text
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1054
Improved marine predators algorithm for engineering design optimization problems
Published 2024-06-01Get full text
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1055
High-performance directional fuzzing scheme based on deep reinforcement learning
Published 2023-04-01“…With the continuous growth and advancement of the Internet and information technology, continuous growth and advancement of the Internet and information technology.Nevertheless, these applications’ vulnerabilities pose a severe threat to information security and users’ privacy.Fuzzing was widely used as one of the main tools for automatic vulnerability detection due to its ease of vulnerability recurrence and low false positive errors.It generates test cases randomly and executes the application by optimization in terms of coverage or sample generation to detect deeper program paths.However, the mutation operation in fuzzing is blind and tends to make the generated test cases execute the same program path.Consequently, traditional fuzzing tests have problems such as low efficiency, high randomness of inputs generation and limited pertinence of the program structure.To address these problems, a directional fuzzing based on deep reinforcement learning was proposed, which used deep reinforcement learning networks with information obtained by staking program to guide the selection of the inputs.Besides, it enabled fast approximation and inspection of the program paths that may exist vulnerabilities.The experimental results showed that the proposed approach had better performance than the popular fuzzing tools such as AFL and AFLGO in terms of vulnerability detection and recurrence on the LAVA-M dataset and real applications like LibPNG and Binutils.Therefore, the approach can provide support for further vulnerability mining and security research.…”
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1056
Mining Stack Overflow for API class recommendation using DOC2VEC and LDA
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Geometrically Nonlinear Analysis for Elastic Beam Using Point Interpolation Meshless Method
Published 2019-01-01Get full text
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Multiobjectives for Optimal Geographic Routing in IoT Health Care System
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A No-Reference Modular Video Quality Prediction Model for H.265/HEVC and VP9 Codecs on a Mobile Device
Published 2017-01-01Get full text
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