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.     

Simulation of Propane Dehydrogenation to Propylene in a Radial‐Flow Reactor over Pt‐Sn/Al2O3 as the Catalyst

Catalytic paraffin dehydrogenation for manufacturing olefins is considered to be one of the most significant production routes in the petrochemical industries. A reactor kinetic model for the dehydrogenation of propane to propylene in a radial‐flow reactor over Pt‐Sn/Al₂O₃ as the catalyst was investigated here. The model showed that the catalyst activity was highly time dependent. In addition, the component concentrations and the temperature varied along the reactor radius owing to the occurring endothermic reaction. Moreover, a similar trend was noticed for the propane conversion as for the propylene selectivity, with both of them decreasing over the time period studied. Furthermore, a reversal of this trend was also revealed when the feed temperature was enhanced or when argon was added into the feed as an inert gas.     

Evolving Fuzzy Min–Max Neural Network Based Decision Trees for Data Stream Classification

Learning from data streams is a challenging task which demands a learning algorithm with several high quality features. In addition to space complexity and speed requirements needed for processing the huge volume of data which arrives at high speed, the learning algorithm must have a good balance between stability and plasticity. This paper presents a new approach to induce incremental decision trees on streaming data. In this approach, the internal nodes contain trainable split tests. In contrast with traditional decision trees in which a single attribute is selected as the split test, each internal node of the proposed approach contains a trainable function based on multiple attributes, which not only provides the flexibility needed in the stream context, but also improves stability. Based on this approach, we propose evolving fuzzy min–max decision tree (EFMMDT) learning algorithm in which each internal node of the decision tree contains an evolving fuzzy min–max neural network. EFMMDT splits the instance space non-linearly based on multiple attributes which results in much smaller and shallower decision trees. The extensive experiments reveal that the proposed algorithm achieves much better precision in comparison with the state-of-the-art decision tree learning algorithms on the benchmark data streams, especially in the presence of concept drift.     

Full-state neural network observer-based hybrid quantum diagonal recurrent neural network adaptive tracking control

Neural Computing and Applications - This study introduces a neural network (NN) adaptive tracking controller-based reinforcement learning (RL) scheme for unknown nonlinear systems. First, an...     

Oxidase-Peroxidase sequential polymerization for removal of a dye from contaminated water by horseradish peroxidase (HRP)/glucose oxidase (GOx)/polyurethane hybrid catalyst

Horseradish peroxidase (HRP) and glucose oxidase (GOx) were co-immobilized on polyurethane, and the resulting HRP/GOx/polyurethane biocatalyst was characterized using scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDAX) mapping techniques. The prepared biocatalyst was used for removal of acid orange 7 as model azo dye. The required H₂O₂ for activation of HRP was in-situ produced using GOx to prevent deactivation of HRP in the presence of excess chemical H₂O₂. Central composite design (CCD) was applied for modeling and optimization of parameters affecting the activity of prepared biocatalyst. Under the optimum conditions, removal efficiency of the azo dye was predicted to be 87.47%, which was in good agreement with the experimental value (89.69%). In addition, the performance of the prepared biocatalyst for removal of two other dyes with different structure was investigated at the optimum conditions, and a removal efficiency of 91.56% and 95.25% was obtained for removal of methylene blue and malachite green, respectively. The results demonstrated that the resultant HRP/GOx/Polyurethane biocatalyst was able to decrease the chemical oxygen demand (COD) of a textile effluent from 740mg/L to 96mg/L, indicating that the prepared biocatalyst is an effective enzymatic system for treatment of real wastewater.     

An automated composite table algorithm considering zero liquid discharge possibility in water regeneration–recycle network

In this study, a novel Automated Composite Table Algorithm (ACTA) is developed for targeting the water regeneration–recycle network of single contaminant problem. The ACTA is based on Pinch Analysis, but is automated by taking into consideration the possibility of zero liquid discharge (ZLD) for the water network. In the existing literature, the targeting procedure for ZLD network is based on the graphical tool of Limiting Composite Curve (LCC). However, identification of key parameters (i.e. freshwater, wastewater, regenerated water flowrates, along with pre-regeneration concentrations) is very tedious for highly integrated water network system. The magnification around the turning point of LCC is required to identify the correct pinch points and targeting procedure is done iteratively until the reliable network targets can be determined. These limitations are now overcome by the ACTA, which is an improved version of Composite Table Algorithm that is capable of identifying key parameters algebraically for a given post-regeneration concentration. The newly developed ACTA is capable of handling a wide range of problems including ZLD and non-ZLD network, for both fixed load and fixed flowrate problems.     

Removal of Diazinon from aqueous solution by electrocoagulation process using aluminum electrodes

Electrocoagulation (EC) is an electrochemical method to treat polluted wastewaters and aqueous solutions. In this paper, the removal of Diazinon was studied by EC on aluminum electrode. The effect of several parameters such as initial concentration of Diazinon, current density, solution conductivity, effect of pH, and electrolysis time were investigated on EC performance. The obtained results showed that the removal efficiency of EC depends on the current density, initial concentration of Diazinon and electrolysis time. The optimum pH is 3 and also the solution conductivity has no significant effect on removal efficiency.     

On Plate Identification of Coexisting Polyoxyethylene (20) Stearyl Ether,Cetyl Pyridinium Chloride,Tetradecyl Trimethyl Ammonium Bromide and Polyoxyethylene (9.5) Octyl Phenyl Ether Surfactants with Preliminary Separation by Planar Chromatography

Separation studies of four surfactants (nonionic and cationic) were performed on silica high-performance thin-layer chromatographic plates with various solvent systems. The most useful chromatographic system for the mutual separation of coexisting polyoxyethylene (20) stearyl ether (C18EO20), cetylpyridinium chloride (CPC), tetradecyl trimethyl ammonium bromide (TTAB) and polyoxyethylene (9.5), octyl phenyl ether (OPEO9.5) was formamide + 1 M formic acid (50:50 v/v). The nature of ‘H’ and ‘H⁺’ of formic acid (H–COO⁻H⁺) on the mobility of these surfactants was studied. The interference due to the presence of metal cations as impurities on the resolution of mixture of C18EO20, CPC, TTAB and OPEO9.5 was also examined. The limits of detection of C18EO20, CPC, TTAB and OPEO9.5 estimated were 0.0620, 0.0310, 0.0625 and 0.0312 μg/zone, respectively. The practical applicability of the proposed method was tested for the identification of four coexisting surfactants after their separation from the spiked aqueous systems.     

Environmental Hazard Analysis - a Variant of Preliminary Hazard Analysis for Autonomous Mobile Robots

Robot manufacturers will be required to demonstrate objectively that all reasonably foreseeable hazards have been identified in any robotic product design that is to be marketed commercially. This is problematic for autonomous mobile robots because conventional methods, which have been developed for automatic systems do not assist safety analysts in identifying non-mission interactions with environmental features that are not directly associated with the robot’s design mission, and which may comprise the majority of the required tasks of autonomous robots. In this paper we develop a new variant of preliminary hazard analysis that is explicitly aimed at identifying non-mission interactions by means of new sets of guidewords not normally found in existing variants. We develop the required features of the method and describe its application to several small trials conducted at Bristol Robotics Laboratory in the 2011–2012 period.     

Strength and Microstructure of Silicon Nitride Ceramics Brazed with Nickel-Chromium-Silicon Alloys

Joining of sintered Si₃N₄ was performed using a high-temperature brazing technique. Ni-based brazing alloys having the same Ni:Cr ratio as AWS BNi-5 (Ni·18Cr·19Si (at. %)) but different Si content were used as the brazing filler metals. Joining experiments were performed at 1220°C under a N₂ partial pressure of 15 Pa for different times between 5 to 15 min. The highest room-temperature four-point bend strength of the joints was 115 MPa, whereas 220 MPa was achieved when the joints were tested at 900°C. The high strength of the experimental joints was attributed to the reduction in residual stresses and formation of a CrN reaction layer at the ceramic/filler metal interface.