The fame of Wireless Sensor Networks (WSN) has expanded quickly and colossally because of the huge capability of the sensor systems to associate the physical world with the virtual world. Since sensor gadgets depend on battery force and hub vitality and might be set in antagonistic situations, supplanting them turns into a troublesome undertaking. In this way, improving the vitality of these systems, for example, becomes significant. The proposition gives techniques to bunching and group head determination to WSN to improve vitality effectiveness utilizing a fluffy rationale controller. It presents a correlation between the various techniques based on the system lifetime. It contrasts existing ABC streamlining technique and the Gray Wolf Optimizer (GWO) enhancement calculation for various sizes of systems and diverse situations. It furnishes bunch head determination technique with great execution and diminished computational multifaceted nature. The paper proposes GWO as a calculation for grouping of WSN which would bring about improved execution with quicker combination.

Radar systems are used for detection of objects by transmitting the electromagnetic waves in the free space. They operate in environments where there is a high possibility that the desired echo signal interferes with the signals from other sources. These signals include clutters and jammer signals. The jammer is a device that continuously emits the wideband radio signals in the radar environment to saturate the receiver with noise or false information. Thus, the total received signal has three components-returns from target, clutter and jammer combined, i.e., it is a three-dimensional signal. The use of conventional signal processing techniques is not desirable, as they cannot separate the desired echo signal from the other components, because the statistics of these components in the received signal is not known. This problem needs to be accounted for in airborne surveillance radars, as they have to identify and locate the targets in multiple interference environments. The Space-Time Adaptive Processing (STAP) Techniques is a combination of spatial and temporal filtering that can nullify the jammer signal and recognize the slow-moving targets. These techniques filter the signal in the angular and the Doppler domain for suppressing the unwanted signals. The paper presents a theoretical study of space-time adaptive coding techniques and MATLAB implementation of STAP algorithms, namely, SMI, DPCA and ADPCA, to suppress clutter and jammer interference in the received pulse.

The paper studies an AlGaAs-based standard photonic crystal fiber structure for low dispersive nonlinear optics applications. By employing a finite element solver with perfectly matched layer boundary condition, the key propagation characteristics are investigated over a broad wavelength span of 1 mm to 5 mm by taking different air filling fraction values. The proposed work provides an effective fundamental mode area of 7.30 mm2 with nonlinearity in the order of 8.325W-1m-1 at a low absorption wavelength of 1.55 mm and zero-dispersion wavelength close to 3 mm.