Amirkabir University of Technology

About: Amirkabir University of Technology is a education organization based out in Tehran, Iran. It is known for research contribution in the topics: Nonlinear system & Finite element method. The organization has 15254 authors who have published 31165 publications receiving 487551 citations. The organization is also known as: Tehran Polytechnic & Tehran Polytechnic University.

Highly aligned, ultralarge-size reduced graphene oxide/polyurethane nanocomposites: Mechanical properties and moisture permeability

Abstract: Polyurethane (PU) nanocomposite films containing highly-aligned graphene sheets are produced. Aqueous dispersion of ultralarge-size graphene oxide (GO) is in situ reduced in waterborne polyurethane, resulting in fine dispersion and high degree of orientation of graphene sheets, especially at high graphene contents. The PU/reduced GO nanocomposites present remarkable 21- and 9-fold increases in tensile modulus and strength, respectively, with 3 wt.% graphene content. The agreement between the experiments and theoretical predictions for tensile modulus proves that the graphene sheets are indeed dispersed individually on the molecular scale and oriented in the polymer matrix to form a layered structure. The moisture permeability of the nanocomposites presents a systematic decrease with increasing graphene content, clearly indicating the impermeable graphene sheets acting as moisture barrier. The synergy arising from the very high aspect ratio and horizontal alignment of the graphene sheets is responsible for this finding.

Asphalt flocculation and deposition: I. The onset of precipitation

Abstract: Formation of asphalt aggregates and their deposition on the pore surfaces of a porous medium, which alter the structure of the medium and its effective properties, is a critical problem to catalytic and oil recovery and refinery processes. Extensive new experimental data for the amount of precipitated asphalt formed with crude oil and various solvents are presented. Results indicate that, contrary to the previous assumptions, asphalt formation is at best partially reversible. A thermodynamic model based on the Flory–Huggins theory of polymer solutions is used, together with the Soave equation of state, to predict the data. Critical evaluation of the model shows that its predictions do not agree well with our data. As an alternative, we propose a new model that employs a scaling equation, somewhat similar to those encountered in aggregation and gelation phenomena. The scaling function takes on a very simple form, and its predictions are in very good agreement with the data. It also predicts that the onset of precipitation may obey a simple universal equation.

Intrusion detection using fuzzy association rules

Abstract: Vulnerabilities in common security components such as firewalls are inevitable. Intrusion Detection Systems (IDS) are used as another wall to protect computer systems and to identify corresponding vulnerabilities. In this paper, a novel framework based on data mining techniques is proposed for designing an IDS. In this framework, the classification engine, which is actually the core of the IDS, uses Association Based Classification (ABC). The proposed classification algorithm uses fuzzy association rules for building classifiers. Particularly, the fuzzy association rulesets are exploited as descriptive models of different classes. The compatibility of any new sample (which is to be classified) with different class rulesets is assessed by the use of some matching measures and the class corresponding to the best matched ruleset is declared as the label of the sample. A new method is also proposed to speed up the rule induction algorithm via reducing items that may be included in extracted rules. KDD-99 dataset is used to evaluate the proposed framework. Although results on unseen attacks are not so promising, total detection rate and detection rate of known attacks is significant while false positive rate is kept low. Results are compared with some recent works in the literature using the same dataset. Generally, the proposed approach outperforms other methods, specially in terms of false positive rate.