Enhancing EAP-TLS authentication protocol for IEEE 802.11i

IEEE 802.11i authentication framework is composed of the 802.1x and an extensible authentication protocol (EAP) mechanism. One of the most applicable techniques in the EAP methods is EAP-transport layer security (EAP-TLS). The EAP-TLS implementation issues are high execution time; high number of data exchanges between two parties and possibility of closing connection as a result of modification in the contents of the handshake messages, which are all addressed in this paper. This research analyses the EAP-TLS in WLANs to improve this method’s efficiency in terms of the security analysis, time and memory usage. Based on the results, this research proposes an enhanced method with a discrete cryptographic mechanisms and a distinct handshake structure, which reduces the number of steps in the handshake protocol. This enhanced method also provides robust security compared to the original EAP-TLS with approximately the same level of memory usage, which reduces execution time significantly.     

Effect of doping on structural and optical properties of ZnO nanoparticles: study of antibacterial properties

Sol-gel method was successfully used for synthesis of ZnO nanoparticles doped with 10 % Mg or Cu. The structure, morphology and optical properties of the prepared nanoparticles were studied as a function of doping content. The synthesized ZnO:(Mg/Cu) samples were characterized using XRD, TEM, FTIR and UV-Vis spectroscopy techniques. The samples show hexagonal wurtzite structure, and the phase segregation takes place for Cu doping. Optical studies revealed that Mg doping increases the energy band gap while Cu incorporation results in decrease of the band gap. The antibacterial activities of the nanoparticles were tested against Escherichia coli (Gram negative bacteria) cultures. It was found that both pure and doped ZnO nanosuspensions show good antibacterial activity which increases with copper doping, and slightly decreases with adding Mg.     

Study on the Hydrogenated Diamond-Like Carbon Films Synthesized by RF-PECVD from n-decane

Using a mixture of n-decane and hydrogen, diamond-like carbon thin films (DLCTFs) with high growth rate of 35?nm/min are deposited by radio frequency plasma enhanced chemical vapor deposition. We show that n-decane can be considered as a promising carbon source in DLCTF deposition. The properties of the deposited films such as structure, hydrogen content, deposition rate and refractive index are studied for 20, 50 and 100?sccm hydrogen flow rates (HFRs). It is shown that the deposition rate has a maximum of 35?nm/min for HFR?=?20?sccm and by increasing hydrogen concentration, deposition rate drops to 19?nm/min for HFR?=?100?sccm. The Raman spectra reveal that the films represent hydrogenated diamond-like carbon features. The photoluminescence background of the Raman spectra is used as a measure for hydrogen content of the films. The hydrogen content varies from 29 to 46% which yields a various amount of sp³ fraction. The results of the spectroscopic ellipsometry indicate that by increasing HFR, refractive index decreases from 2.1 to 1.9 at 632?nm. The aforementioned trends are attributed to the increase of hydrogen content in DLCTFs which is in very good agreement with enhancing of the photoluminescence background of the Raman spectra.     

Dynamical system learning using extreme learning machines with safety and stability guarantees

This article presents a continuous dynamical system model learning methodology that can be used to generate reference trajectories for the autonomous systems to follow, such that these trajectories are invariant to a given closed set and uniformly ultimately bounded with respect to an equilibrium point inside the closed set. The autonomous system dynamics are approximated using extreme learning machines (ELM), the parameters of which are learned subject to the safety constraints expressed using a reciprocal barrier function, and the stability constraints derived using a Lyapunov analysis in the presence of the ELM reconstruction error. This formulation leads to solving a constrained quadratic program (QP) that includes a finite number of decision variables with an infinite number of constraints. Theorems are developed to relax the QP with infinite number of constraints to a QP with a finite number of constraints which can be practically implemented using a QP solver. In addition, an active sampling methodology is developed that further reduced the number of required constraints for the QP by only evaluating the constraints at a smaller subset of points. The proposed method is validated using a motion reproduction task on a seven degree-of-freedom Baxter robot, where the task space position and velocity dynamics are learned using the presented methodology.     

Efficient thermal desalination technologies with renewable energy systems: A state-of-the-art review

Due to the current fossil fuel crisis and associated adverse environmental impacts, renewable energy sources (RES) have drawn interest as alternatives to fossil fuels for powering water desalination systems. Over the last few decades the utility of renewable energy sources such as solar, geothermal, and wind to run desalination processes has been explored. However, the expansion of these technologies to larger scales is hampered by techno-economic and thermo-economic challenges. This paper reviews the state-of-the-art in the field of renewable energy-powered thermal desalination systems (RE-PTD) to compare their productivity and efficiency through thermodynamic, economic, and environmental analyses. We performed a comparative study using published data to classify RE-PTD systems technologies on the basis of the energy collection systems that they use. Among RE-PTD systems, solar energy powered-thermal desalination systems demonstrate high thermo-environ-economic efficiency to produce fresh water to meet various scales of demand.     

A study of the relation of mobile device attributes with the user-perceived quality of Android apps

The number of mobile applications (apps) and mobile devices has increased considerably over the past few years. Online app markets, such as the Google Play Store, use a star-rating mechanism to quantify the user-perceived quality of mobile apps. Users may rate apps on a five point (star) scale where a five star-rating is the highest rating. Having considered the importance of a high star-rating to the success of an app, recent studies continue to explore the relationship between the app attributes, such as User Interface (UI) complexity, and the user-perceived quality. However, the user-perceived quality reflects the users’ experience using an app on a particular mobile device. Hence, the user-perceived quality of an app is not solely determined by app attributes. In this paper, we study the relation of both device attributes and app attributes with the user-perceived quality of Android apps from the Google Play Store. We study 20 device attributes, such as the CPU and the display size, and 13 app attributes, such as code size and UI complexity. Our study is based on data from 30 types of Android mobile devices and 280 Android apps. We use linear mixed effect models to identify the device attributes and app attributes with the strongest relationship with the user-perceived quality. We find that the code size has the strongest relationship with the user-perceived quality. However, some device attributes, such as the CPU, have stronger relationships with the user-perceived quality than some app attributes, such as the number of UI inputs and outputs of an app. Our work helps both device manufacturers and app developers. Manufacturers can focus on the attributes that have significant relationships with the user-perceived quality. Moreover, app developers should be careful about the devices for which they make their apps available because the device attributes have a strong relationship with the ratings that users give to apps.     

Characterization of the Influence of Tool Pin Profile on Microstructural and Mechanical Properties of Friction Stir Welding

In this study, the effect of tool pin profile on mechanical properties, microstructural, material flow, thermal and strain distributions of friction stir welding of AA5083 was investigated. Two different tools with cylindrical and square pin profiles were employed to produce the welds. A numerical model is developed for investigating the effect of tool pin profiles on material flow, thermal and strain distributions based on thermo-mechanically coupled rigid-viscoplastic 3D FEM. Then, optical microscopy was employed to characterize the microstructures features of the weld. Finally, tensile test was carried out to characterize the mechanical properties of the weld. Obtained results showed that square pin profile produced finer grain structure and higher ultimate strength relative to cylindrical one. These results may be related to higher eccentricity, larger stirred zone, and higher temperature in the weld zone of the square pin profile.     

Blur invariants: A novel representation in the wavelet domain

Blur invariants in the wavelet domain are proposed for the first time in this paper. Wavelet domain blur invariants take advantage of several benefits that this domain provides, i.e. different alternatives for wavelet function and analysis in different scales. It is not required to model the blur system in order to extract the invariants. It will be shown how the space domain blur invariants are a special case of the proposed invariants. It will also be explained how the proposed invariants would not have the null space that their special case in the spatial domain have which limits their discriminative power. The performance of these invariants will be demonstrated through experiments, and compared to its counterpart which is defined in the spatial domain.