To overcome the limitations of conventional radar target recognition methods, this paper proposes a novel approach that integrates cyclic spectrum slicing with deep learning techniques. First, the cyclic spectrum of the radar signal is computed using the time smoothing method, enabling a theoretical analysis of the distinguishing features present in the target’s cyclic spectrum slice. The resulting slice spectrum is then fed into an improved Deep Convolutional Generative Adversarial Network (DCGAN) model, which employs a Wasserstein GAN with Gradient Penalty (WGAN-GP) loss function for data augmentation. Subsequently, an enhanced VGGNet architecture—incorporating Global Average Pooling and Parametric Rectified Linear Unit (PReLU) activation functions—is utilized to automatically extract features that capture the target’s cyclic stability. Experimental results on aircraft target recognition demonstrate that the proposed method achieves outstanding average accuracies of 98.46 % and 98.40 % for different cyclic spectrum slices, significantly outperforming traditional methods by more than 3 %. The findings highlight the exceptional capability of the cyclic spectrum in revealing the intrinsic properties of target signals, along with its strong suppression of noise and clutter. Moreover, the integration of deep learning techniques has substantially improved target recognition accuracy, offering an effective solution for automatic target recognition under conditions of limited samples and low signal-to-noise ratios.

This paper presents a method for determining the optimal structural characteristics of a muzzle brake compensator to enhance the firing stability of automatic assault rifles during short bursts. Utilizing the principle of independent force action in mechanics, the rifle is modeled as a multi-body system with rigid bodies and concentrated masses, assuming forces acting on the gun, including the shooter’s visco-elastic coupling, are independent. The method focuses on minimizing muzzle deflection at the moment a bullet exits the barrel by accurately determining the structural characteristics - aT, ay and az - which quantify how the gas reaction force from propellant gases generates compensatory impulses along the axial and lateral axes. Theoretical analysis involves solving nonlinear differential equations based on Lagrange’s formulation and using internal ballistic data to simulate gun motion and optimize device parameters. Experimental validation, conducted with specialized equipment, demonstrates strong correlation between calculated and observed values (with errors below 9.8 %), confirming that a well-designed muzzle device can significantly reduce recoil and enhance the overall stability and accuracy of automatic weapons.

Climate modes can contribute significantly to sea level variability over shorter time scales. The present study examines annual and inter annual Sea Level Anomalies (SLA) in the Bay of Bengal, emphasizing the influences of El Niño /La Niña and the Indian Ocean Dipole (IOD). An Empirical Orthogonal Function (EOF) analysis is employed to discern the spatiotemporal variability within SLA measurements obtained from the satellite altimeter data. The Oceanic Nino Index (ONI) and Dipole Mode Index (DMI) were used to identify the climatic events and to investigate their influence on the SLA variations over the Bay. Results show distinct seasonal SLA patterns in both Western and Eastern Bay, transitioning from positive to negative anomalies and vice versa within a year. The leading mode of EOF explains 25.5 % variance and indicates a contrasting SLA pattern in the Bay. Significant variations in the sea level are observed during the co-occurrences of Positive Indian Ocean Dipole (PIOD) and El Niño, as well as Negative Indian Ocean Dipole (NIOD) and La Niña. Specifically, the co-occurred El Niño and PIOD (La Niña and NIOD) or pure strong PIOD (pure strong NIOD) is associated with increased (decreased) SLA in the western Bay and decreased SLA in the eastern Bay. However, a detailed analysis of individual events reveals that strong IOD events exert a greater influence on the SLA of the Bay of Bengal.

Oceanic eddies are important ocean surface features and play a crucial role in ocean energy transfer, nutrient distribution and biological production in the global ocean. Sub-mesoscale eddies are characterized by their small spatial scales (<100km) and short temporal scales (hours to days). Large mesoscale eddies are detected using satellite altimetry data where as sub-mesoscale eddies are detected using Synthetic Aperture Radar(SAR) images of high resolution. This paper analyses two such eddies captured in a SAR image off the coast of Vizag. The SAR image is despeckled and thresholded to extract the eddy features. The eddy images are analysed and validated using Sea Level Anomaly(SLA) and Chlorophyll-a datasets in order to understand the eddy dynamics and its characteristics.

This study introduces a novel Vertical Sense Mass (VSM) design for MEMS gyroscope sensors, addressing the growing demand for miniaturization and enhanced performance in navigation and industrial applications. Leveraging Deep Reactive Ion Etching (DRIE) technology, the VSM design significantly reduces size while offering superior performance compared to traditional planar configurations. Comprehensive theoretical analysis and comparative evaluations demonstrate the VSM design’s advantages across critical metrics, including sensitivity, bandwidth, noise, and device footprint. This advancement represents a substantial leap in MEMS gyroscope technology, enabling high-performance sensing in compact form factors. Specifically, the VSM design achieves a 30 % reduction in sense mass area, resulting in a 36 % smaller sensor footprint. This size reduction is coupled with a significant improvement in the overall Performance Metric (PM), with the VSM design exhibiting a PM of 1090 mHz/dps2μm2 compared to 70.7 mHz/dps2μm2 for the planar design. These analytical findings are supported by existing literature, further validating the superior performance of the proposed VSM design. The detailed fabrication process flow of the structure is presented, and successful fabrication of thick-proof-mass structures using DRIE confirms the feasibility of this innovative approach. These results highlight the potential of the VSM design for future applications requiring compact, high-performance gyroscope sensors.

Sediment samples collected from 3 shallow water test sites in Idukki reservoir in Kerala are used to estimate the geophysical properties such as porosity, wet bulk density, mean grain size and sediment grain size distribution. The measured geophysical properties are utilised to estimate the geoacoustic parameters, including the compressional speed and compressional attenuation based on effective fluid density model (Biot-Stoll theory), grain and viscous grain shearing model (Buckingham’s theory). The derived geoacoustic parameters are then used for modelling the transmission loss in the sediment layer. TL variation is analysed as a function of source depth in the mid-to-high frequency (5-15 kHz) band. Modelling results supports that the penetration is minimal for low grazing angles and higher penetration occurs only at grazing angles greater than the critical angle.

The choice of the right industrial robot is a crucial step in the development of the manufacturing firm because of its impact on the production rate, output, and income-generating capacity of the firm. In the last decades, people have started using tools from Multi-Criteria Decision Making (MCDM) to help them make better decisions. Nevertheless, many questions remain unanswered in the literature regarding the usability of these methods in industrial robot selection. To enhance the ability to evaluate and select industrial robots, this study introduces two new methods of MCDM, which are named Sum Weighted Information (SWI) and Sum Weighted Information Exponential (SWEI).

The echo signal amplitude received by radar is very low, necessitating signal amplification for effective detection and processing. A Low Noise Amplifier (LNA) has been developed to boost signal amplitude without adding extra noise. This paper presents innovative techniques such as gm-boosting, RC coupling, an L-type matching network, and common source inductive degeneration. These techniques achieve a wide bandwidth of 1.3 GHz (4.7 to 6 GHz) and a low undesired signal level of 0.8 dB. The bias network enhances transconductance, resulting in a gain of 36-40 dB, while the RC coupling network ensures stability from DC to 36 GHz. The LNA achieves an output 1 dB compression point of 9 dBm, an OIP3 of 23.91 dBm, a sensitivity of -137.8 dBm, a linear dynamic range of 108.8 dB, and a spurious free dynamic range of 87.87 dB. This LNA operates well in RF interference environments and demonstrates strong detection capability and linearity. Built on GaAs technology, the MMIC circuit has a compact footprint of 3.5052 mm². This efficient LNA boosts the tracking range from 128 km to 243 km when integrated into larger systems.

The growing demand for high-specific strength, lightweight materials drives research and innovation in manufacturing industries. Composite materials are emerging as viable alternatives to traditional metals and alloys as they address these critical industry requirements effectively. Advancements in additive manufacturing technology have transformed the fabrication of composite materials with tailored mechanical properties. However, there is a limited understanding of the material properties of composites manufactured through three-dimensional (3D) printing technology. This work aims to provide a better understanding of the relationship between the 3D printing process parameters and mechanical properties of the carbon fibre materials. Specifically, the study reports the effect of raster angle and infill pattern on the flexural and impact properties of onyx-reinforced carbon fibre composites. Major findings from this study reveal that there is a significant decrease in flexural strength with an increase in raster angle due to parallel deposition of fibres. In addition, the triangular infill pattern had the highest energy absorption when compared to all other equivalents. The 0° raster angles with solid or rectangular infill patterns and 45⁰ raster angles with triangular or solid patterns are ideal for applications with high flexural strength and impact resistance, respectively.

This study aims to understand whether introducing a steel liner at the rear face of concrete is beneficial compared to reinforced concrete in improving impact resistance when subjected to flat and hemisphere nose-shaped hard missiles. The paper presents the numerical results of penetration, perforation, and ballistic limit of plain and reinforced concrete targets (1200 mm x 1200 mm x 180 mm) with and without steel liner. Numerical simulations are done using LS Dyna. The thickness of the steel liner varied from 2.25 mm to 4.5 mm according to the percentage of flexural reinforcement for 30, 40 & 50MPa unconfined concrete strengths. 12 mm diameter bars are used as flexural reinforcement spaced at a distance of 100 mm c/c. The geometric dimensions of the missile are 300 mm in length and 80 mm in diameter, and the missile’s mass is 11.75 kg. The findings revealed that because of its higher tensile strength, steel reinforcement was shown to decrease penetration depth, whereas steel liners greatly enhance ballistic limits. Plain Concrete with Rear Face Liner PCL2.25 had a 27.7 % higher penetration depth than Single Mat Reinforced Concrete (SMRC) at 100 m/s for 1.75 % reinforcement, while PCL4.5 demonstrated a 22 % higher penetration than Double Mat Reinforced Concrete (DMRC) for 3.5 % reinforcement. PCL4.5 demonstrated a 50 % greater ballistic limit compared to SMRC for a flat nose and a 9 % higher ballistic limit for a hemisphere nose. These results show that steel liners are an alternative for RC in increasing the impact resistance of concrete structures in crucial applications like nuclear and military facilities because of their improved ballistic limits and perforation resistance.