Security enhancements against UMTS–GSM interworking attacks

In this paper we first present three new attacks on Universal Mobile Telecommunication System (UMTS) in access domain. We exploit the interoperation of UMTS network with its predecessor, Global System for Mobile communications (GSMs). Two attacks result in the interception of the entire traffic of the victim UMTS subscriber in the GSM access area of UMTS network. These attacks are applicable, regardless of the strength of the selected GSM encryption algorithm. The third attack is an impersonation attack and allows the attacker to impersonate a genuine UMTS subscriber to a UMTS network and fool the network to provide services at the expense of the victim subscriber. Then, we propose some countermeasures to strengthen the UMTS network against the mentioned attacks with emphasis on the practicality in present networks. The proposed solutions require limited change of the network elements or protocols, insignificant additional computational load on the network elements and negligible additional bandwidth consumption on the network links.     

An electrochemical sensor based on V2O5 nanoparticles for the detection of ciprofloxacin

This research constructed and utilized a screen-printed electrode (SPE) modified with V₂O₅ nanoparticles (NPs) (V₂O₅/SPE) employed in order to sensitively and selectively quantify ciprofloxacin with exceptional accuracy in the phosphate buffer solution (PBS) with the use of differential pulse voltammetry (DPV). Moreover, electrochemical properties of this new V₂O₅/SPE sensor have been examined using diverse characterization procedures. Very good V₂O₅/SPE electrochemical features offered sensitive ciprofloxacin voltammetric determination with the reduced limit of detection (LOD?=?0.01 µM) toward electrocatalytic oxidation of ciprofloxacin in comparison with the bare SPE. Finally, this new disposable sensor exhibited higher sensitivity and thus has been efficiently utilized to determine ciprofloxacin in the real samples.

     

Evaluation of ‘green’ synthesis and biological activity of gold nanoparticles using Tragopogon dubius leaf extract as an antibacterial agent

Currently, the use of ‘green’ synthesised nanoparticles with environmentally friendly properties is considered a novel therapeutic approach in medicine. Here, the authors evaluated gold nanoparticles (AuNPs) conjugated with Tragopogon dubius leaf extract and their antibacterial activity in vitro and in vivo. Colour changes from yellow to dark brown and a peak at 560 nm on ultraviolet–visible spectroscopy confirmed the formation of nanoparticles. Additionally, transmission electron microscopy, X‐ray diffraction, and Fourier transform infrared spectroscopy analyses were performed to determine particle sizes and functional groups involved in gold reduction. Moreover, using standard micro‐dilution and disc‐diffusion assays against Klebsiella pneumoniae, Bacillus cereus, Escherichia coli, and Staphylococcus aureus, the antimicrobial properties of synthesised AuNPs were investigated. To confirm antibacterial activity, synthesised AuNPs were applied in a rat model on burn wounds infected with S. aureus, and the nanoparticles were as effective as tetracycline in bacterial reduction and wound healing. In conclusion, the synthesis of AuNPs with aqueous T. dubius extract was rapid, simple, and inexpensive, and the synthesised nanoparticles had significant antibacterial activity in vitro and in vivo.Inspec keywords: transmission electron microscopy, wounds, nanoparticles, ultraviolet spectra, reduction (chemical), particle size, nanofabrication, gold, X‐ray diffraction, antibacterial activity, microorganisms, visible spectra, nanomedicine, biomedical materials, Fourier transform infrared spectraOther keywords: biological activity, gold nanoparticles, antibacterial agent, therapeutic approach, colour changes, ultraviolet–visible spectroscopy, transmission electron microscopy, gold reduction, antimicrobial properties, Fourier transform infrared spectroscopy analyses, disc‐diffusion assay, green synthesis, Tragopogon dubius leaf, in vitro antibacterial activity, in vivo antibacterial activity, X‐ray diffraction, particle sizes, functional groups, standard microdilution assay, burn wounds, S. aureus, tetracycline, bacterial reduction, wound healing, wavelength 560.0 nm     

Interconnection-based performance analysis for a class of decentralized controllers

This paper is concerned with decentralized controller design for large-scale interconnected systems of pseudo-hierarchical structure. Given such a system, one can use existing techniques to design a decentralized controller for the reference hierarchical model, obtained by eliminating certain weak interconnections of the original system. Although this indirect controller design is appealing as far as the computational complexity is concerned, it does not necessarily result in satisfactory performance for the original pseudo-hierarchical system. An LQ cost function is defined in order to evaluate the performance discrepancy between the pseudo-hierarchical system and its reference hierarchical model under the designed decentralized controller. A discrete Lyapunov equation is then solved to compute this performance index. However, due to the large-scale nature of the system, this equation cannot be handled efficiently in many real-world systems. Thus, attaining an upper bound on this cost function can be more desirable than finding its exact value, in practice. For this purpose, a novel technique is proposed which only requires solving a simple LMI optimization problem with three variables. The problem is then reduced to a scalar optimization problem, for which an explicit solution is provided. It is also shown that when the original model is exactly hierarchical, then the upper bounds obtained from the LMI and scalar optimization problems will both be equal to zero.     

PREDICTIVE MODELS OF THE SPRING-BACK IN THE BENDING PROCESS

Spring-back is one of the most sensitive features of sheet metal forming processes because the elastic recovery during unloading leads to some geometric changes in the product. Three parameters that are most influential on spring-back in the V-die bending process are sheet thickness, sheet orientation, and punch tip radius. In this research, radial basis function (RBF) neural network and back propagation (BP) neural network approaches are used to predict the spring-back using the data generated from experimental observations. The performances of the models in training and testing sets are compared with those observations. Furthermore, output obtained through regression analysis is used to compare with the two developed model outputs. The results indicate that both networks can be applied successfully for prediction of spring-back against the input parameters of the V-die bending process. Also, the BP model shows better performance for prediction of spring-back with respect to the RBF model.     

Synthesis,recognition and evaluation of molecularly imprinted polymer nanoparticle using miniemulsion polymerization for controlled release and analysis of risperidone in human plasma samples

We prepared high selective imprinted nanoparticle polymers by a miniemulsion polymerization technique, using risperidone as the template, MAA as the functional monomers, and TRIM as the cross-linker in acetonitrile as solvent. The morphology of the nanoparticles determined by scanning electron microscopy (SEM) images and drug release, binding properties and dynamic light scattering (DLS) of molecularly imprinted polymers (MIPs) were studied. Controlled release of risperidone from nanoparticles was investigated through in 1% wt sodium dodecyl sulfate aqueous solution and by measuring the absorbance by HPLC-UV. The results showed that the imprinted nanoparticles exhibited a higher binding level and slower release rate than non-imprinted nanoparticles, which contributed to interaction of risperidone with imprinted cavities within nanoparticles. Furthermore, the results from HPLC showed good precision (5% for 50.0 μg L^?1) and recoveries (between 86–91) using MIP from human plasma samples.     

Performance assessment of an electrochemical hydrogen production and storage system for solar hydrogen refueling station

This paper investigates the performance of a hydrogen refueling system that consists of a polymer electrolyte membrane electrolyzer integrated with photovoltaic arrays, and an electrochemical compressor to increase the hydrogen pressure. The energetic and exergetic performance of the hydrogen refueling station is analyzed at different working conditions. The exergy cost of hydrogen production is studied in three different case scenarios; that consist of i) off-grid station with the photovoltaic system and a battery bank to supply the required electric power, ii) on-grid station but the required power is supplied by the electric grid only when solar energy is not available and iii) on-grid station without energy storage. The efficiency of the station significantly increases when the electric grid empowers the system. The maximum energy and exergy efficiencies of the photovoltaic system at solar irradiation of 850 W m-2 are 13.57% and 14.51%, respectively. The exergy cost of hydrogen production in the on-grid station with energy storage is almost 30% higher than the off-grid station. Moreover, the exergy cost of hydrogen in the on-grid station without energy storage is almost 4 times higher than the off-grid station and the energy and exergy efficiencies are considerably higher.     

Evaluating knowledge management failure factors using intuitionistic fuzzy FMEA approach

The twenty-first century organizations are characterized by an emphasis on knowledge and information. Today’s organizations also require the acquisition, management, and exploitation of knowledge and information in order to improve their own performance. In the current economy, the foundations of organizational competitiveness have turned former tangible and intangible resources into knowledge and the focus of information systems has also changed from information management to knowledge management. Besides, the most important step in the implementation of knowledge management is to examine the significant factors in this regard and to identify the causes of failure. Therefore, the present study evaluated knowledge management failure factors in an intuitionistic fuzzy environment as a case study in Khuzestan Oil and Gas Company. For this purpose, a series of failure factors affecting knowledge management in organizations were identified based on a review of the related literature and similar studies. Then, 16 failure factors in the implementation of knowledge management in the given organization were determined on the basis of interviews with company experts. According to the specified factors as well as the integration of multiple criteria decision-making techniques in an intuitionistic fuzzy environment, knowledge management failure factors in Khuzestan Oil and Gas Company were investigated. The results indicated that lack of management commitment and leadership was the most important factor affecting the failure of knowledge management in the given company.