Alternate uses of epoxy asphalt on bridge decks and roadways. Simulation of Mesofracture Process of Asphalt Mixture using Digital Image Processing and Extended Finite Element Method. Renewable and Sustainable Energy Reviews. Potentials of Piezoelectric and Thermoelectric Technologies for Harvesting Energy from Pavements. Construction and Building Materials, Vol. Optimization of Hard Modified Asphalt Formula for Gussasphalt Based on Uniform Experimental Design. Laboratory Investigation and Numerical Simulation of the Rutting Performance of Double-Layer Surfacing Structure for Steel Bridge Decks. Fatigue Behavior of Epoxy Asphalt Concrete and Its Moisture Susceptibility from Flexural Stiffness and Phase Angle.
The Effects of Neighborhood Characteristics and the Built Environment on Pedestrian Injury Severity: A Random Parameters Generalized Ordered Probability Model with Heterogeneity in Means and Variances, Analytic Methods in Accident Research, Volume 16, pp. Modeling a New Energy Harvesting Pavement System with Experimental Verification, Applied Energy, Volume 208, pp.1071-1082, 2017. The graduate courses she has taught are mainly security-related, including computer network security (ECE4490/6490), malware reverse engineering (ECE8830), and distributed denial-of-service (DDoS) attacks (ECE8860). She has taught System Programming Concepts (ECE2220) and Communications systems (ECE4270). Yu has taught both undergraduate and graduate courses. In particular, her previous work includes privacy-preserving probabilistic counting, and negative surveys. True user privacy is only possible when no personally identifiable information (PII) is ever collected. Yu’s research focuses on privacy-preserving data collection approaches. Privacy-preserving data techniques look at techniques that useful statistics from user data without disclosing any private user information. Privacy-preserving data mining techniques are critical to protect user privacy in the era of big data. The application of the LWM algorithm includes clinical trials, transparency and accountability of agriculture supply chain, and digital forensics, etc. This allows consensus to be achieved with minimal computational overhead.
#Dr yu lu free
Unlike most existing mining algorithms (e.g., Proof-of-Work (PoW), Proof-of-Stake (PoS)) that are devised for cryptocurrency applications, LWM is completely free of monetary qualities.
The lightweight mining (LWM) consensus algorithm guarantees a c as long as there is one good miner. A reliable, efficient and secure consensus algorithm is critical to the blockchain technology. Her previous research includes botnet detection (e.g., domain name generation (DGA)), distributed denial-of-service (DDoS) attacks detection and mitigation, and Markov decision processes (MDP), etc.īlockchain is a distributed digital ledger storing provenance metadata.
She is currently engaged in research in privacy-preserving data mining, blockchain technology, and anonymity network. Yu’s research interests mainly focus on cybersecurity. 2004, Xi’an Jiaotong University Information Engineering Contact Information Office: 300B Riggs Hall Office Phone: 864.656.5916 Email: Dr. 2007, Xi’an Jiaotong University Control Theory and Control Engineering B.S. 2012, Clemson University Electrical Engineering B.S. Research Assistant Professor of Electrical and Computer Engineering
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