Simulation-Based Traceability Analysis of RFID Authentication Protocols

Nowadays low-cost RFID systems have moved from obscurity into mainstream applications which cause growing security and privacy concerns. The lightweight cryptographic primitives and authentication protocols are indispensable requirements for these devices to grow pervasive. In recent years, there has been an increasing interest in intuitive analysis of RFID protocols. This concept has recently been challenged by formal privacy models. This paper investigates how to analyse and solve privacy problems in formal model. First, we highlight some vague drawbacks especially in forward and backward traceability analysis and extend it in the simulation-based privacy model family. Then, the privacy weaknesses of three new-found RFID authentication protocols are analysed in formal privacy models and three improved protocols are proposed to prevent the aforementioned attacks.     

A Low Complexity Suboptimal Energy-Based Detection Method for SISO/MIMO Channels

In this paper, we propose an actually novel and simple method for detection of transmitted symbols in MIMO channels. This method is based on the energy level of the received signals. At the receiver, we assume the knowledge of channel state information which can be estimated by different methods, e.g. by sending pilots. So, we can determine all possible levels of energy. This computation of energy levels is done only once for the quasi-static channels. Energy of the received signals is a criterion by which we can estimate the transmitted symbols. Detection of transmitted signal is made based on the nearest energy level and the points which lie on it. In other words, we have restricted our search space to a new smaller space with different levels of energy. Simulation results confirm approximately the same performance between the maximum-likelihood detector and the proposed approach especially in high signal-to-noise ratios with a remarkable reduction in the computational complexity.     

A Comprehensive Framework for Counterfeit Defect Coverage Analysis and Detection Assessment

The increasing threat of counterfeit electronic components has created specialized service of testing, detection, and avoidance of such components. However, various types of counterfeit components – recycled, remarked, overproduced, defective, cloned, forged documentation, and tampered – pose serious threats to supply chain. Over the past few years, standards and programs have been put in place throughout the supply chain that outline testing, documenting, and reporting procedures. However, there is little uniformity in the test results among the various entities. Currently, there are no metrics for evaluating these counterfeit detection methods. In this paper, we have developed a detailed taxonomy of defects present in counterfeit components. Based on this taxonomy, a comprehensive framework has been developed to find an optimum set of detection methods considering test time, test cost, and application risks. We have also performed an assessment of all the detection methods based on the newly introduced metrics – counterfeit defect coverage, under-covered defects, and not-covered defects.     

Dynamic analysis of carbon nanotubes under electrostatic actuation using modified couple stress theory

Modified couple stress theory is a size-dependent theorem capturing the micro/nanoscale effects influencing the mechanical behaviors of the micro- and nanostructures. In this paper, it is applied to investigate the nonlinear vibration of carbon nanotubes under step DC voltage. The vibration, natural frequencies and dynamic pull-in characteristics of the carbon nanotubes are studied in detail. Moreover, the effects of various boundary conditions and geometries are scrutinized on the dynamic characteristics. The results reveal that application of this theory leads to the higher values of the natural frequencies and dynamic pull-in voltages.     

Controlling foam morphology of polystyrene via surface chemistry,size and concentration of nanosilica particles

Controlling cell morphologies of polymeric foams is an important part of controlling foam properties. In this study, the effects of particle size, particle content, and particle surface chemistry on cell nucleation in nanosilica/polystyrene (PS) composites are investigated. A theoretical hypothesis on the effect of nanoparticle size on cell nucleation in PS matrix foam was examined. The surface chemistry of nanosilica particles was studied by modifying them with Vinyltriethoxysilane (VTES) silane coupling agent. The microcellular porous materials of neat and composite PS were prepared by batch foaming technique (pressure quench) using supercritical carbon dioxide (ScCO₂) as a blowing agent. It was found that the size of the pores decreases and the cell density increases with the decrease in nanosilica size and the increase of silica loading. It was also observed that the surface treatment of the nanosilica particles have substantial effect on the decrease of the cell size and the increase of the cell density.     

Preparation,characterization, viscosity,and thermal conductivity of nitrogen-doped graphene aqueous nanofluids

Nanofluids perform a crucial role in the development of newer technologies ideal for industrial purposes. In this study, Nitrogen-doped graphene (NDG) nanofluids, with varying concentrations of nanoparticles (0.01, 0.02, 0.04, and 0.06 wt%) were prepared using the two-step method in a 0.025 wt% Triton X-100 (as a surfactant) aqueous solution as a base. Stability, zeta potential, thermal conductivity, viscosity, specific heat, and electrical conductivity of nanofluids containing NDG particles were studied. The stability of the nanofluids was investigated by UV–vis over a time span of 6 months and concentrations remain relatively constant while the maximum relative concentration reduction was 20 %. The thermal conductivity of nanofluids was increased with the particle concentration and temperature, while the maximum enhancement was about 36.78 % for a nanoparticle loading of 0.06 wt%. These experimental results compared with some theoretical models including Maxwell and Nan’s models and observed a good agreement between Nan’s model and the experimental results. Study of the rheological properties of NDG nanofluids reveals that it followed the Newtonian behaviors, where viscosity decreased linearly with the rise of temperature. It has been observed that the specific heat of NDG nanofluid reduced gradually with the increase of concentration of nanoparticles and temperature. The electrical conductivity of the NDG nanofluids enhanced significantly due to the dispersion of NDG in the base fluid. This novel type of fluids demonstrates an outstanding potential for use as innovative heat transfer fluids in medium-temperature systems such as solar collectors.     

Anionic clay intercalated by multi-walled carbon nanotubes as an efficient 3D nanofiller for the preparation of high-performance l-alanine amino acid containing poly(amide-imide) nanocomposites

In this study, three-dimensional (3D) nanohybrids with excellent properties were prepared by the simple combination of 1D carbon nanotubes (CNTs) and 2D MgAl-layered double hydroxides (LDHs). An optically active amino acid containing poly(amide-imide) was prepared by direct polycondensation reaction of N-trimellitylimido-l-alanine and 4,4′-diaminodiphenyl methane under green condition in molten tetra-n-butylammonium bromide. PAI/LDH-CNT nanocomposites containing 2, 4, and 8 wt% LDH-CNT were prepared via a simple and an effective ultrasonic method. The presence of CNT in the interlayer space of LDH was confirmed by thermogravimetry analysis, Fourier transformed infrared spectroscopy, and X-ray diffraction techniques. The homogeneous dispersion of nanofillers in the PAI matrix was observed by field emission scanning electron microscopy and transmission electron microscopy. The obtained results revealed the coexistence of exfoliated and intercalated modified LDH-CNT in the polymer matrix.     

Comparison of sintering behavior and piezoelectric properties of (K,Na)NbO3-based ceramics sintered in conventional and microwave furnace

In this study (1 − x) K_0.48Na_0.48Li_0.04Nb_0.96Ta_0.04O₃ − xSrTiO₃ (0.0 ≤ x ≤ 0.10) ceramics were fabricated by sintering in microwave furnace for first time as well as in conventional furnace (either via single step or two-step procedures). Sintering behavior and piezoelectric properties of sintered samples were studied and compared. It was found that two-step sintering decreases sintering temperature effectively and enhances densification compared to single step sintering. Microstructure analysis revealed that, two-step sintering suppresses grain growth and promotes densification. On the other hand, microwave sintering enhanced densification more effectively and reduced sintering time and temperature. The maximum piezoelectric constants of ceramics were measured for those sintered in microwave furnace. Piezoelectric constant of the sample containing 1 mol% SrTiO₃ which was sintered in microwave furnace was measured 310 pC N⁻¹ while by sintering in conventional furnace via single and two-step sintering it was obtained 208 and 278 pC N⁻¹, respectively.     

A New Model for the Thermal Conductivity of Molten Salts

A new model based on rough hard-sphere theory is proposed for the thermal conductivity of molten salts. The model incorporates a smooth hard-sphere contribution using the properties of argon, as well as characteristic parameters based on the melting point of the molten salt. It is demonstrated that it is possible to correlate the thermal conductivity of monovalent and multivalent molten salts within experimental error using this approach. Furthermore, in salts with a common anion, the single adjustable parameter in the model exhibits regular behavior with the molecular weight of the salt. It is also shown that the thermal conductivity of several molten-salt mixtures can be predicted without any mixture parameters.     

An efficient memetic algorithm for 3D shape matching problems

Shape representation plays a vital role in any shape optimization exercise. The ability to identify a shape with good functional properties is dependent on the underlying shape representation scheme, the morphing mechanism and the efficiency of the optimization algorithm. This article presents a novel and efficient methodology for morphing 3D shapes via smart repair of control points. The repaired sequence of control points are subsequently used to define the 3D object using a B-spline surface representation. The control points are evolved within the framework of a memetic algorithm for greater efficiency. While the authors have already proposed an approach for 2D shape matching, this article extends it further to deal with 3D shape matching problems. Three 3D examples and a real customized 3D earplug design have been used as examples to illustrate the performance of the proposed approach and the effectiveness of the repair scheme. Complete details of the problems are presented for future work in this direction.