Novel sensing and joint beam and null steering based resource allocation for cross-tier interference mitigation in cognitive femtocell networks

Wireless Networks - Cognitive radios and femtocell networks are gaining much popularity due to the formers ability to carry out unlicensed transmission in licensed bands and the latter’s...     

An integrated design methodology based on the use of group AHP-DEA approach for measuring lean tools efficiency with undesirable output

The selection of lean tools is one of the crucial factors for decision makers and practitioners in a competitive environment. A few efforts have been made based on problem selection. Conversely, numerical studies have been done on analytical hierarchy process (AHP)–data envelopment analysis (DEA) as well as DEA-undesirable variables separately. Thus, there is a shortage of lean practitioners as well as the methods involved. The present research aims at integrating AHP and DEA with desirable and undesirable factors to evaluate the lean tools and techniques and to rank the aspect of efficacy. We suggest a logical procedure to measure the efficacy of lean tools on leanness and to prioritize them as decision makers. In this extensive research, we apply the integrated multicriteria decision-making approach, including the hybrid groups AHP and DEA models with desirable and undesirable variables, to assess the relative efficiency of lean manufacturing tools and techniques. Case studies are used to demonstrate the lean implementation in companies while being validated by a panel of experts. The integration of these approaches has created synergy and shown to be even more powerful. Thus, the proposed integrated AHP-DEA model can evaluate and rank different alternatives while considering desirable and undesirable variables in the production processes.     

Enhancing differential evolution with role assignment scheme

As one of the most popular evolutionary algorithms, differential evolution (DE) has been used for solving a wide range of real-world problems. The performance of DE highly depends on the chosen mutation strategy and control parameter settings. Although the conventional trial-and-error procedure can be used to elaborately select the proper strategy and to tune the parameter values, this procedure is often very time-consuming and is not suitable for practitioners without a priori experience. To tackle this problem, DE with a novel role assignment (RA) scheme is proposed in this paper. In the RA scheme, both the fitness information and positional information of individuals are utilized to dynamically divide the population into several groups. Each group is considered as a role, which has its own mutation strategy and parameter settings and is expected to play a different role in the evolution process. To verify the performance of our approach, experiments are conducted on 23 well-known benchmark functions. Results show that our approach is better than, or at least comparable to, several state-of-the-art DE variants.     

Ultra trace quantification of chromium(VI) in food and water samples by highly sensitive catalytic adsorptive stripping voltammetry with rubeanic acid

A simple and highly selective and sensitive catalytic adsorptive stripping voltammetric procedure for determination of ultra trace levels of chromium(VI) on hanging mercury drop electrode is reported. The method is based on the adsorptive preconcentration of the Cr(III)–dithiooxamide (rubeanic acid) complex and the utilization of the catalytic reaction in the presence of nitrate. At optimized conditions the calibration graph is linear from 0.01 to 6 ng/ml and detection limit is 0.002 ng/ml for accumulation time of 50 s. The interference of some common ions was studied and this method has been applied to the determination of chromium in food and waste water samples with satisfactory results.     

Design of a traveling wave thermo‐acoustic engine based on genetic algorithm

This paper presents a novel design scheme for traveling wave thermo‐acoustic Stirling engines (TASEs) based on a target frequency using genetic algorithm (GA). First, the effects of engine design parameters on the system performance are studied via root locus method. Accordingly, it is found that the resonator length, the inertance diameter, and the hot gas temperature are the most effective parameters in the engine design procedure. Next, the relation between the closed‐loop poles positions of the thermo‐acoustic system and the effective design variables are described parametrically. Consequently, in order to estimate the optimum values of the effective design parameters as well as the unknown positions of the nondominant poles, an appropriate fitness function based on the desired engine frequency is proposed. Subsequently, a GA is used to achieve the optimal values of design parameters so as to minimize the considered cost function. Finally, the validity of the proposed design technique is verified by comparing the obtained results with the available data of an experimental case study.     

Testing the application of Free Flapping Foils (FFF) as a method to improve adhesion in an electrostatic wall-climbing robot

In this paper, extensive testing on an electrostatic wall-climbing robot is carried out to examine the electrostatic adhesion force when using the Free Flapping Foils (FFF) method. This method is successfully applied to an electrostatic robot to enable it to stick more firmly, by about three times, on walls with different materials, including wood, plaster, granite, glass and climb wall with a continuous movement. The innovation in this paper is that successful tests were carried out, when using thin flexible electrodes made from aluminium foil and free movement of those electrodes. The FFF electrodes are flexible enough to get the shape and roughness of the wall and increases the contact surface. Thus, they increase the adhesion force and would also improve performance of the robot in rough surfaces. The experimental parameters including charging voltage, charging time, number of electrodes, area of electrodes, wall material (permittivity) and surface finishing of wall that affect the electrostatic carrying force were investigated. The robot could cross obstacles with different heights. The final robot was 1.27?Kg and able to convey 14?N extra load when sticking and climbing vertical walls.     

Kinetic-spectrophotometry method for determination of ultra trace amounts of aluminum in food samples

A simple and sensitive kinetic-spectrophotometry method is developed for the determination of trace amounts of aluminum in food samples based on its catalytic effect on the oxidation of Nile Blue A by potassium bromate in sulfuric acid medium. The absorbance is measured at 595.5 nm with the fixed-time method. The optimization of the operating conditions regarding concentrations of the reagents, temperature and interferences are also investigated. The calibration curve is linear over the concentration range 0.07–0.9 μg ml⁻¹ of aluminum with good precision and accuracy and the detection limit was down to 0.034 μg ml⁻¹. The relative standard deviation for a standard solution of 0.4 μg ml⁻¹ of aluminum is 1.73% (n = 10). The proposed method proved highly sensitive, selective and relatively rapid for the assay of aluminum at ultra trace level without any pre-concentration and separation step. The method was applied to the determination of aluminum in food samples (rice, tea and potato). The analytical results of the real samples were in good agreement with the standard method.     

An Android runtime security policy enforcement framework

Today, smart phone’s malwares are deceptive enough to spoof itself as a legal mobile application. The front-end service of Trojans is attractive enough to deceive mobile users. Mobile users download similar malwares without knowing their illegitimate background threat. Unlike other vendors, Android is an open-source mobile operating system, and hence, it lacks a dedicated team to analyze the application code and decide its trustworthiness. We propose an augmented framework for Android that monitors the dynamic behavior of application during its execution. Our proposed architecture called Security Enhanced Android Framework (seaf) validates the behavior of an application through its permissions exercising patterns. Based on the exercised permissions’ combination, the mobile user is intimated about the dangerous behavior of an application. We have implemented the proposed framework within Android software stack and ported it to device. Our initial investigation shows that our solution is practical enough to be used in the consumer market.