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Fingerprints hold paramount importance in various fields due to their unique characteristics, making them invaluable for identification and verification purposes. This paper presents a state-of-the-art methodology for fingerprint recognition leveraging the Hybrid Deep Learning Model - SpatioTemporalNet (STNet), enhanced by Hybrid GAPSO Optimization for Feature Matching. By fusing Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and advanced optimization techniques, this approach revolutionizes the landscape of fingerprint analysis. STNet integrates both static and dynamic feature analysis, enabling adaptability to diverse conditions encountered in real-world scenarios. The integration of STNet and Hybrid GAPSO Optimization represents a significant advancement in fingerprint recognition technology, offering unparalleled levels of security and reliability. By harnessing the power of deep learning and optimization, the proposed methodology excels in handling various challenges such as partial prints, distortions, and variations in fingerprint impressions. Implemented using Python, the proposed methodology undergoes rigorous experimentation, demonstrating exceptional performance with an accuracy rate of 98.7%. This high level of accuracy underscores the effectiveness and reliability of the approach in accurately identifying individuals based on their unique fingerprint patterns. [ABSTRACT FROM AUTHOR]

The present paper focuses on investigating the cost-effective configuration of an array of wave energy converters (WECs) composed of vertical cylinders situated in front of a vertical seawall in irregular waves. First, the hydrodynamic calculations are performed using a WAMIT commercial code based on linear potential theory, where the influence of the vertical wall is incorporated using the method of image. The viscous damping experienced by the oscillating cylinder is considered through CFD simulations of a free decay test. A variety of parameters, including WEC diameter, number of WECs, and the spacing between them, are considered to determine an economically efficient WEC configuration. The design of the WEC configuration is aided by a cost indicator, defined as the ratio of the total submerged volume of the WEC to overall power capture. The cost-effective configuration of WECs is achieved when WECs are positioned in front of a vertical wall and the distance between them is kept short. It can be explained that the trapped waves formed between adjacent WECs as well as the standing waves in front of a seawall significantly intensify wave fields around WECs and consequently amplify the heave motion of each WEC. A cost-effective design strategy of WEC deployment enhances the wave energy greatly and, consequently, contributes to constructing the wave energy farm. [ABSTRACT FROM AUTHOR]

The Assistive Technology (AT) is a boon for the physically, mentally challenged and aged people. There are various research projects conducted around the world to facilitate the disadvantaged people to lead a normal life. A team of researchers from the University of Technology and Applied Sciences of Salalah campus with the support of the Ministry of Higher Education, Research and Innovation's funding is working on a project on finger movement multimodal assistive system for the smart people (Disadvantaged people). The research team has identified people who have difficulty in speaking and locomotive disability. The team has designed a manual wheelchair with the visual and audio command options for the helper or the nearby people through the finger movement of the disabled people. The main objective is to convey the commands or instructions to others through simple finger movements which are not to be memorized. The machine learning component of this system will make the instruction personalized for the people and it will not be common for all. [ABSTRACT FROM AUTHOR]

The wave energy converter (WEC) system, which extracts electricity through the relative heave motion of two concentric cylinders, comprises an inner cylinder and a torus-type outer cylinder sliding along the inner cylinder. To maximize the relative heave motion between two cylinders, the natural frequencies of the two cylinders must be precisely tuned to resonate and be situated on each side of the peak frequency of the wave spectrum. However, the demerit of this strategy is that it demands a deep draft of each cylinder for tuning, and a large-scale PTO damping device is necessary for mechanical power amplified by resonance. As an alternative to efficient and stable WECs, we adopt a new strategy in which the outer cylinder follows the incoming waves and the motion of the inner one is restricted to be minimal using a heave disk. The viscous damping due to formation of vortices at the disk edge is realized by the drag force in the Morison equation. The developed hydrodynamic model of two-body WEC based on a matched eigenfunction expansion method (MEEM) is applied to irregular waves characterized by significant wave height and peak period. It is found that the present two-body WEC with heave disk produces wave energy stably across a wide range of wave frequencies compared to the previous two-body WECs using resonance. [ABSTRACT FROM AUTHOR]

Introduction: Premature infants undergo a lot of stressful procedures during care and treatment procedure, which may lead to physiological and neurological changes. This study is based on analyzing the neurological deficits in preterm infants with low birth weight born to covid-19 affected mothers. The main purpose of this study was to analyze whether the preterm infants with low birth weight are prone to develop neurological deficits. The aim of this study was to evaluate the neurological effects in preterm infants admitted to the NICU. Materials and Methods: Quasi experimental study design was used in this study; Total 30 Preterm infants admitted to the NICU who met the inclusion criteria were selected. All 30 preterm infants undergone screening for neurological deficits. All the data's were tabulated and statistically analyzed. Results: In very low birth weight infants and risk factors for development delay and neurosensory disability are high. Infants with very early Preterm and extreme low birth weight have a higher risk of attention problems, languages difficulties and intellectual disabilities. Conclusions. It concludes that preterm infants are at risk of developing neurological deficits and also concludes that early the identification in new born helps in early the intervention to the new born. [ABSTRACT FROM AUTHOR]

This paper proposes a low voltage (400 Vdc) distributed renewable energy fed DC microgrid structure for a residential system, which uses DC voltage for the electronic appliances. The distributed energy sources—solar photovoltaic (PV) and wind energy are considered as input sources. The output power from these sources is stochastic in nature. An efficient energy management and switching circuit is designed to control the power flow from the sources with a high gain DC‐DC converter as the main component. The output power regulation is achieved by means of controlling duty ratios of the switches in the proposed high gain converter through PI controller. The control algorithm effectively converts the unregulated DC power from the solar PV and wind into regulated DC for driving a DC load connected in DC‐microgrid. The energy management and switching circuits account for seamless operation of the DC microgrid under various modes when one or all the sources and loads are connected directly at the DC grid link. The designed energy management and switching circuit also ensures the power balancing in the proposed system. The proposed DC microgrid structure is simulated using MATLAB Simulink. The performance of the proposed high gain converter for the DC grid link voltage regulation is analyzed under source power variation and dynamic changes in load for various operating conditions. The proposed DC microgrid structure is validated using simulation results. [ABSTRACT FROM AUTHOR]