Performance assessment of VSC-based HVDC system in asynchronous grid interconnection: Offline and real-time validation of control design with symmetric optimum PI tuning.

Asynchronous interconnection is essential for integrating AC networks operating at different frequencies, typically 50 Hz and 60 Hz. This need arises from distributed power generation methods, including offshore renewable sources and diverse regional grid configurations. Advanced strategies are required to overcome these frequency differences and ensure uninterrupted power transfer.

The dopant (n- and p-type)-, band gap-, size- and stress-dependent field electron emission of silicon nanowires.

This study investigates the electron field emission (EFE) of vertical silicon nanowires (Si NWs) fabricated on n-type Si (100) and p-type Si (100) substrates using catalyst-induced etching (CIE). The impact of dopant types (n- and p-types), optical energy gap, crystallite size and stress on EFE parameters has been explored in detail. The surface morphology of grown SiNWs has been characterized by field emission scanning electron microscopy (FESEM), showing vertical, well aligned SiNWs.

Machine learning-based approach for prediction of ion channels and their subclasses.

Ion channels are ion-permeable protein pores that are found in all cell lipid membranes. Distinct ion channels play multiple roles in biological processes. Proteomic data is fast accumulating as a result of the fast growth of mass spectrometry and giving us the chance to comprehensively explore ion channel classes along with their subclasses.

Complex entropy based encryption and decryption technique for securing medical images.

During medical picture transmission, the most pressing concern is security. Medical images must be encrypted since they are extremely sensitive. Watermarking, digital fingerprinting/signature, and encoding are some of the available image security techniques.

Mechanical Properties of PALF/Kevlar-Reinforced Unsaturated Polyester Hybrid Composite Laminates.

Natural and synthetic fibres are in high demand due to their superior properties. Natural fibres are less expensive and lighter as compared to synthetic fibres. Synthetic fibres have drawn much attention, especially for their outstanding properties, such as durability, and stability.

Predicting the impact of the third wave of COVID-19 in India using hybrid statistical machine learning models: A time series forecasting and sentiment analysis approach.

Background: Since January 2020, India has faced two waves of COVID-19; preparation for the upcoming waves is the primary challenge for public health sectors and governments. Therefore, it is important to forecast future cumulative confirmed cases to plan and implement control measures effectively.

Methods: This study proposed a hybrid autoregressive integrated moving average (ARIMA) and Prophet model to predict daily confirmed and cumulative confirmed cases.

TOXGB: Teamwork Optimization Based XGBoost model for early identification of post-traumatic stress disorder.

Post-traumatic stress (PTSD) is considered a clinical issue that influences numerous people from diverse trades all over the world. Numerous research scholars recorded diverse complexities to estimate the severity of the PTSD symptoms in the patients. But diagnosing PTSD and obtaining accurate diagnosing techniques becomes a more complicated task.

In Situ Formation of ZrB and Its Influence on Wear and Mechanical Properties of ADC12 Alloy Mixed Matrix Composites.

In this work, aluminium alloy ADC12 reinforced with various amounts of ZrB (0 wt.%, 3 wt.%, 6 wt.

Physical and Mechanical Properties of Natural Leaf Fiber-Reinforced Epoxy Polyester Composites.

In recent times, demand for light weight and high strength materials fabricated from natural fibres has increased tremendously. The use of natural fibres has rapidly increased due to their high availability, low density, and renewable capability over synthetic fibre. Natural leaf fibres are easy to extract from the plant (retting process is easy), which offers high stiffness, less energy consumption, less health risk, environment friendly, and better insulation property than the synthetic fibre-based composite.

Effect of Variation of SiC Reinforcement on Wear Behaviour of AZ91 Alloy Composites.

In this investigation, the extensive wear behaviour of materials was studied using SiC reinforced magnesium alloy composites fabricated through the stir casting process. The wear properties of AZ91 alloy composites with a small variation (i.e.

Physical and Mechanical Behaviour of Sugarcane Bagasse Fibre-Reinforced Epoxy Bio-Composites.

In this study, experiments are performed to study the physical and mechanical behaviour of chemically-treated sugarcane bagasse fibre-reinforced epoxy composite. The effect of alkali treatment, fibre varieties, and fibre lengths on physical and mechanical properties of the composites is studied. To study the morphology of the fractured composites, scanning electron microscopy is performed over fractured composite surfaces.

Effect of SiC Reinforcement and Its Variation on the Mechanical Characteristics of AZ91 Composites.

In this study, the processing of SiC particulate-strengthened magnesium alloy metal matrix composites via vacuum supported inert atmosphere stir casting process is presented. The effects of small variations in the SiC particulate (average size 20 µm) reinforcement in magnesium alloy AZ91 were examined. It was found that with the addition of SiC particulate reinforcement, the hardness improved considerably, while the ultimate tensile and yield strength improved slightly.

Diligent profiling of preclinical safety of the silk protein sericin.

Background: Sericin is a widely used protein in the pharmaceutical industry derived from the silkworm, , and used for the treatment of various diseases and pathological conditions. It is the main ingredient of the Unani preparation khameera abresham. The study was conducted to evaluate the preclinical toxicity of the silk protein sericin in mice.

Optimization of the proposed hybrid denoising technique to overcome over-filtering issue.

Image denoising has become a crucial task in medical ultrasound (US) imaging due to the presence of speckle or multiplicative noise and additive Gaussian noise. Recently, several denoising techniques such as adaptive wavelet thresholding & joint bilateral (AWT + JB) filter, adaptive fuzzy switching weighted mean (AFSWM) filter and median patch-based locally optimal Wiener (MPBLOW) filter have been proposed to remove the speckle noise. However, these denoising techniques were found to remove noise along with the essential parts of the actual image data which is known as over-filtering.