In this paper, a dual notch Ultra Wideband (UWB) monopole antenna with compact dimensions of 37.8 × 27.1 × 1.6 mm 3 is presented. Octagon patch with a defected ground structure is used to attain the wide frequency range of 3.17 GHz-11.61 GHz with ultra-wide impedance bandwidth of 8.33 GHz. The band notch characteristics in WiMAX (3.2 GHz-3.67 GHz) and WLAN (4.32 GHz-5.81 GHz) bands are achieved using inverted pi-slot in the radiating element and a pair of double split ring resonators (DSRRs) on either sides of the feed, respectively. Reconfigurability in the bands is obtained by using BAR64-03W pin diodes switching at the appropriate placement in the antenna structure. The proposed antenna exhibits efficiency of 88% in operating and 20% in nonoperating frequencies. The proposed antenna is designed, simulated, and optimized using HFSS 19 electromagnetic tool. The measured results are tested using combinational analyzer in a chamber with antenna measurement setup for validation and found in good matching with simulation.

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In(Ga)As/GaAs-based quantum dot infrared photodetectors (QDIPs) have emerged as one of the most suitable devices for infrared detection. However, quantum dot devices suffer from lower efficiencies due to a low fill-factor (∼20%–25%) of dots. Here, we report a post-growth technique for improving the QDIP performance using low energy light ion (H−) implantation. At high bias, there is evidence of suppression in the field-assisted tunneling component of the dark current. Enhancement in peak detectivity (D*), a measure of the signal-to-noise ratio, by more than one order, from ∼109 to 2.44 × 1010 cm Hz1/2/W was obtained from the implanted devices.

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The folded tandem ion accelerator (FOTIA) facility set up at BARC has become operational. At present, it is used for elemental analysis studies using the Rutherford backscattering technique. The beams of 1 H, 7 Li, 12 C, 16 O and 19 F have been accelerated up to terminal voltages of about 3 MV and are available for experiments. The terminal voltage is stable within ¦2 kV. In this paper, present status of the FOTIA and future plans are discussed.

Tuberculosis (TB) is an infectious disease that primarily affects the lungs. If the TB is left undiagnosed in its early stage, it may affect other body parts leading to sudden death. A posterior anterior chest radiographs are used to diagnose pulmonary TB. This work presents a novel automatic system for the early detection of pulmonary TB. Initially, the Chan-Vese active contour model is generated to segment the lung region from the preprocessed chest x-rays. Different textural, statistical, and morphological features are extracted from the segmented lungs. Finally, the pertinent feature vector is considered for the classification of chest x-rays using the Naïve Bayes classifier (NBC). The NBC is trained using 10-fold cross validation technique. The proposed method achieves an average accuracy, the area under the curve, specificity, and sensitivity as 95.5%, 98%, 93.3%, and 94.6% respectively, when tested on different available datasets. Comparison results reveals that the Naïve Bayes classifier outperforms than the multinomial Naïve Bayes classifier and Bernoulli's Naïve Bayes classifier in classifying the chest x-rays into healthy and TB.

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