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Yin J.-H.,PolyU Shenzhen Research Institute | Yin J.-H.,Hong Kong Polytechnic University
International Journal of Geomechanics | Year: 2015

In this paper, a number of fundamental concepts are presented and explained. These include (1) differences among an instant compression line, a normal consolidation line, and a true instant compression line; (2) the uniqueness of viscoplastic strain rates with a stress-strain state; (3) whether the creep compression is smaller than the instant compression; (4) the separation of the total strain rates; (5) the relation between elastic-plastic models and elastic viscoplastic (EVP) models, etc. The major conclusions are the following: (1) the elastic compression is the true instant compression; (2) the magnitude of a creep-strain rate at a stress-strain state point is unique, independent of the loading path to reach this point; (3) the true instant (elastic) compression is much smaller than the creep compression; (4) it is more appropriate that strain rates of geomaterials are composed of elastic strain rates and viscoplastic strain rates; (5) the one-dimensional (1D) EVP (1D EVP) is a genuine extension of Maxwell's linear rheological model for considering the nonlinear behavior of soils; (6) the EVP model is more general than an elastic-plastic model; (7) the nonlinear functions proposed by the author are good for fitting the creep compression and the compression under high stress of most soft soils in 1D straining; and (8) the three-dimensional EVP model is rigorously derived using the 1D EVP model approach and the modified Cam-Clay model, but further improvements of this model are still needed. At the end, a number of areas are presented for further study. © 2015 American Society of Civil Engineers. Source


Meng B.,Hong Kong Polytechnic University | Fu M.W.,Hong Kong Polytechnic University | Fu M.W.,PolyU Shenzhen Research Institute | Shi S.Q.,Hong Kong Polytechnic University
Materials and Design | Year: 2016

With the increasing demand for meso/micro-scaledmedical products made of biocompatiblematerials, thermalaidedmesoforming is proposed to improvematerial formability and homogenize flow behavior of materials that are difficult to deform at room temperature. However, the unique material deformation behavior and the interactive effects of material microstructure and deformation temperature on forming quality of the fabricated micropart remain unknown. This study thus aims at addressing this issue in thermalmesoforming in terms of deformation load, material flow,microstructural evolution, dimensional accuracy, and defect formation. Accordingly, the fabrication of a titanium dental abutment by one-stroke mesoforming at elevated temperature is conducted and explored. The characteristic and quality of the mesoformed part are extensively examined. The surface grains on the square extrudate undergo severe deformation and generate an equiaxed structure, reflecting that mesoforming at elevated temperature facilitates the homogenization of material flow without coarsening grain size. In addition, the dimensional accuracy, surface quality and the sizes of burr and flash are associated with the initial grain size of pure titanium, and the surface finish is improved by using fine-grained titanium. The fine-grained material is thus desirable for achieving the optimal surface quality in the thermal-aided mesoformed parts. © 2015 Elsevier Ltd. Source


Li W.,City University of Hong Kong | Meng W.,City University of Hong Kong | Meng W.,Institute for Infocomm Research | Luo X.,Hong Kong Polytechnic University | And 2 more authors.
Computers and Security | Year: 2016

Network intrusion detection systems (NIDSs) have been developed for over twenty years and have been widely deployed in computer networks to detect a variety of network attacks. But one of the major limitations is that these systems would generate a large number of alarms, especially false alarms (positives) during the detection. To address this issue, many machine learning approaches have been applied to reduce NIDS false positives. However, we notice that multi-view based approach is often ignored by the literature, which uses one function to model a particular view and jointly optimizes all the functions to optimize and improve the learning performance. In addition, most existing studies have not implemented their algorithms into practical alam systems. In this paper, we thus develop MVPSys, a practical multi-view based false alarm reduction system to reduce false alarms more efficiently, where each view represents a set of features. More specifically, we implement a semi-supervised learning algorithm to construct two-view items and automatically exploit both labeled and unlabeled data. That is, this system can automatically extract and organize features from an incoming alarm into two feature sets: destination feature set and source feature set, where the former contains the features related to the target environment and the latter contains the features about the source environment. In the evaluation, we deploy our system into two real network environments besides using two datasets. Experimental results indicate that our system can achieve a stable filtration accuracy of over 95%, offering a significant improvement as compared with the state-of-the-art algorithms. © 2016 Elsevier Ltd. Source


Liu X.,Hong Kong Polytechnic University | Liu X.,PolyU Shenzhen Research Institute | Xiao B.,Hong Kong Polytechnic University | Xiao B.,PolyU Shenzhen Research Institute | And 2 more authors.
IEEE Transactions on Parallel and Distributed Systems | Year: 2015

Radio-Frequency Identification (RFID) technology brings revolutionary changes to many fields like retail industry. One important research issue in large RFID systems is the identification of unknown tags, i.e., tags that just entered the system but have not been interrogated by reader(s) covering them yet. Unknown tag identification plays a critical role in automatic inventory management and misplaced tag discovery, but it is far from thoroughly investigated. Existing solutions either trivially interrogate all the tags in the system and thus are highly time inefficient due to re-identification of already identified tags, or use probabilistic approaches that cannot guarantee complete identification of all the unknown tags. In this paper, we propose a series of protocols that can identify all of the unknown tags with high time efficiency. We develop several novel techniques to quickly deactivate already identified tags and prevent them from replying during the interrogation of unknown tags, which avoids re-identification of these tags and consequently improves time efficiency. To our knowledge, our protocols are the first non-trivial solutions that guarantee complete identification of all the unknown tags. We illustrate the effectiveness of our protocols through both rigorous theoretical analysis and extensive simulations. Simulation results show that our protocols can save up to 70 percent time when compared with the best existing solutions. © 2015 IEEE. Source


Feng W.Q.,Hong Kong Polytechnic University | Feng W.Q.,PolyU Shenzhen Research Institute | Li Y.L.,Shanghai JiaoTong University | Li Y.L.,Ecole Centrale Nantes | And 4 more authors.
Numerical Methods in Geotechnical Engineering - Proceedings of the 8th European Conference on Numerical Methods in Geotechnical Engineering, NUMGE 2014 | Year: 2014

A considerable progress in theoretical framework of ElasticVisco-Plastic model (EVP) has been achieved in the last decades. In order to extend these models into application, appropriate numerical algorithms for the nonlinear constitutive equations of an EVP are investigated in this study. The EVP model is incorporated into the Plaxis software. The performances of the implicit time-stepping algorithm and explicit time-stepping algorithm are examined in details. In addition, the stability and accuracy of the EVP model are studied with different algorithms are evaluated and the validation of the EVP model is examined by comparing the simulation results with previous experimental results, demonstrating a considerable agreement. © 2014 Taylor & Francis Group. Source

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