The paper presents results of numerical calculations and experimental data on the directional pattern of two 38-element parametric arrays composed of ultrasound sources. Two types of antenna arrays are considered, namely with parallel and coaxial connections of ultrasonic transducers (elements). The results of selecting and functional testing of unit elements are described in this paper. It is found that in the coaxial element connection of the antenna array, the level of side lobes is higher than that in the parallel element connection.

Ever rising increase in number of wireless services has prompted the use of spatial multiplexing through null steering.Various algorithms provide electronic control of antenna array pattern. Simulation-driven technique further introduces correction in array factor to account for array geometry. Taguchi method is used here to combat interference in practical antenna arrays of non-isotropic elements, by incorporating the effect of antenna element pattern on array pattern control in the optimization algorithm. 4-element rectangular and bowtie patch antenna arrays are considered to validate the effectiveness of Taguchi optimization. The difference in the computed excitations and accuracy of null steering confirms the dependence of beam pattern on element factor and hence eliminates the need for extra computations performed byconventional algorithms based on array factor correction. Taguchi method employs an orthogonal array and converges rapidly to the desired radiation pattern in 25 iterations, thus signifying it to be computationally cost-effective. A higher gain and a significant reduction in side lobe level (SLL) was obtained for the bowtie array. Further, due to feed along parallel edges of the patch, the radiating edges being slanted to form the bow shape results in a significant reduction in the area as compared with the rectangular patch designed to resonate at the same frequency.

An intelligent security model for the big data environment is presented in this paper. The proposed security framework is data sensitive in nature and the level of security offered is defined on the basis of the data secrecy standard. The application area preferred in this work is the healthcare sector where the amount of data generated through the digitization and aggregation of medical equipment’s readings and reports is huge. The handling and processing of this great amount of data has posed a serious challenge to the researchers. The analytical outcomes of the study of this data are further used for the advancement of the medical prognostics and diagnostics. Security and privacy of this data is also a very important aspect in healthcare sector and has been incorporated in the healthcare act of many countries. However, the security level implemented conventionally is of same level to the complete data which not a smart strategy considering the varying level of sensitivity of data. It is inefficient for the data of high sensitivity and redundant for the data of low sensitivity. An intelligent data sensitive security framework is therefore proposed in this paper which provides the security level best suited for the data of given sensitivity. Fuzzy logic decision making technique is used in this work to determine the security level for a respective sensitivity level. Various patient attributes are used to take the intelligent decision about the security level through fuzzy inference system. The effectiveness and the efficacy of the proposed work is verified through the experimental study.