Hybrid salp swarm maximum power point tracking algorithm for photovoltaic systems in highly fluctuating environmental conditions.

The maximum power delivered by a photovoltaic system is greatly influenced by atmospheric conditions such as irradiation and temperature and by surrounding objects like trees, raindrops, tall buildings, animal droppings, and clouds. The partial shading caused by these surrounding objects and the rapidly changing atmospheric parameters make maximum power point tracking (MPPT) challenging. This paper proposes a hybrid MPPT algorithm that combines the benefits of the salp swarm algorithm (SSA) and hill climbing (HC) techniques.

Hybridization of synergistic swarm and differential evolution with graph convolutional network for distributed denial of service detection and mitigation in IoT environment.

Enhanced technologies of the future are gradually improving the digital landscape. Internet of Things (IoT) technology is an advanced technique that is quickly increasing owing to the development of a network of organized online devices. In today's digital era, the IoT is considered one of the most robust technologies.

Secure cloud computing: leveraging GNN and leader K-means for intrusion detection optimization.

Over the past two decades, cloud computing has experienced exponential growth, becoming a critical resource for organizations and individuals alike. However, this rapid adoption has introduced significant security challenges, particularly in intrusion detection, where traditional systems often struggle with low detection accuracy and high processing times. To address these limitations, this research proposes an optimized Intrusion Detection System (IDS) that leverages Graph Neural Networks and the Leader K-means clustering algorithm.

Augmenting cybersecurity through attention based stacked autoencoder with optimization algorithm for detection and mitigation of attacks on IoT assisted networks.

The Internet of Things (IoT) network is a fast-growing technology, which is efficiently used in various applications. In an IoT network, the massive amount of connecting nodes is the existence of day-to-day communication challenges. The platform of IoT uses a cloud service as a backend for processing information and maintaining remote control.

A novel energy efficient 4-bit vedic multiplier using modified GDI approach at 32 nm technology.

Multipliers are essential components within digital signal processing, arithmetic operations, and various computational tasks, making their design and optimization crucial for improving the efficiency and performance of integrated circuits. Among multiplier architectures, Vedic multipliers stand out due to their inherent efficiency and speed, derived from ancient Indian mathematical principles. This study presents a comprehensive analysis and comparison of 4-bit Vedic multiplier designs utilizing Gate Diffusion Input (GDI), Complementary Metal-Oxide-Semiconductor (CMOS), and Transmission Gate (TG) technologies, utilizing different adder architectures such as Ripple Carry Adder (RCA), and Carry Lookahead Adder (CLA), Carry Skip Adder (CSA).

EDSSR: a secure and power-aware opportunistic routing scheme for WSNs.

Motivated by the pivotal role of routing in Wireless Sensor Networks (WSNs) and the prevalent security vulnerabilities arising from existing protocols, this research tackles the inherent challenges of securing WSNs. Many current WSN routing protocols prioritize computational efficiency but lack robust security measures, making them susceptible to exploitation by malicious actors. The prevalence of reactive protocols, chosen for their lower bandwidth consumption, exacerbates security concerns, as proactive alternatives require more resources for maintaining network routes.

A wavelet and local binary pattern-based feature descriptor for the detection of chronic infection through thoracic X-ray images.

This investigation attempts to propose a novel Wavelet and Local Binary Pattern-based Xception feature Descriptor (WLBPXD) framework, which uses a deep-learning model for classifying chronic infection amongst other infections. Chronic infection (COVID-19 in this study) is identified via RT-PCR test, which is time-consuming and requires a dedicated laboratory (materials, equipment, etc.) to complete the clinical results.

Enhancing distribution system performance by optimizing electric vehicle charging station integration in smart grids using the honey badger algorithm.

The global surge in electric vehicle (EV) adoption has driven significant research into electric vehicle charging stations (EVCS) due to their environmentally friendly attributes, including low CO₂ emissions. However, integrating EVCS into existing distribution grids presents challenges such as power losses and voltage instability, especially with the increasing incorporation of renewable distributed generation (RDG) sources and battery energy storage systems (BESS). This study introduces a novel honey badger optimization algorithm (HBOA), designed to enhance solution convergence and optimize multi-objective criteria efficiently.

Impact of plastic waste fiber and treated construction demolition waste on the durability and sustainability of concrete.

This study explores the mechanical and durability properties of Plastic-Fibre Reinforced Concrete, incorporating hand-shredded plastic fibers sourced from polyethylene bags and PET bottles. Evaluations, including compressive and split tensile strength tests, were conducted on M40 grade mixes containing plastic fibers and 100% treated Construction and Demolition Waste (CDW), comparing them with conventional concrete. The results demonstrate a significant enhancement in strength properties with the addition of 0.

Design, Synthesis of Flurbiprofen Based 1,3,4-Oxadiazoles and Constrained Anticancer, Antioxidant Agents: In silico Docking Analysis.

Flurbiprofen, a primary component of a nonsteroidal anti-inflammatory drug (NSAID) used to relieve symptoms of arthritis, and is a considerable interest in medicinal chemistry due to its demonstrated potential as an effective agent in various therapeutic applications. In consideration of the 1,3,4-oxadiazole therapeutic potential and anticancer activity, a new series of flurbiprofen scaffolds have been prepared through a straightforward reaction between 5-(1-(2-fluoro-[1,1'-biphenyl]-4-yl)ethyl)-1,3,4-oxadiazole-2-thiol (4) and various organic active 2-chloro-N-phenyl acetamides (5). The synthesized series (6a-6k) was characterized using a combination of spectroscopic techniques, including FT-IR, mass, H-NMR, and C NMR, followed by physical data.

An efficient brain tumor detection and classification using pre-trained convolutional neural network models.

In cases of brain tumors, some brain cells experience abnormal and rapid growth, leading to the development of tumors. Brain tumors represent a significant source of illness affecting the brain. Magnetic Resonance Imaging (MRI) stands as a well-established and coherent diagnostic method for brain cancer detection.

Recent advances in sustainable biopolymer-based nanocomposites for smart food packaging: A review.

The main goal of emerging food-packaging technologies is to address environmental issues and minimize their impact, while also guaranteeing food quality and safety for consumers. Bio-based polymers have drawn significant interest as a means to reduce the usage and environmental impact of petroleum-derived polymeric products. Therefore, this current review highlights on the biopolymer blends, various biodegradable bio-nanocomposites materials, and their synthesis and characterization techniques recently used in the smart food packaging industry.

Optimal design of hybrid green energy powered reduced switch converter based shunt active power filter using horse herd algorithm.

Renewable energy sources are playing a leading role in today's world. However, integrating these sources into the distribution network through power electronic devices can lead to power quality (PQ) challenges. This work addresses PQ issues by utilizing a shunt active power filter in combination with an Energy Storage System (ESS), a Wind Energy Generation System (WEGS), and a Solar Energy System.

Transformer-less high gain DC-DC converter design and analysis for fuel cell vehicles.

High-power converters with significant gains represent established configurations that hold appeal for applications in the industrial and commercial sectors, such as fuel cell electric vehicles (FCEV), energy backup systems, and automotive headlamps. Existing literature predominantly features topologies employing a single-duty ratio. However, this singular approach may not be dependable for operations with high-duty cycles, necessitating the incorporation of additional components to enhance voltage gain.

Harnessing probiotic foods: managing cancer through gut health.

Unlabelled: One of the greatest threats to global health is cancer. Probiotic foods have been shown to have therapeutic promise in the management of cancer, even though traditional treatments such as radiation therapy, chemotherapy, and surgery are still essential. The generation of anticarcinogenic compounds, immune system stimulation, and gut microbiota regulation are a few ways that probiotics when taken in sufficient quantities, might help health.

A Review of Digital Twinning for Rotating Machinery.

This review focuses on the definitions, modalities, applications, and performance of various aspects of digital twins (DTs) in the context of transmission and industrial machinery. In this regard, the context around Industry 4.0 and even aspirations for Industry 5.

Modeling of scour hole characteristics under turbulent wall jets using machine learning.

The novelty of the present study is to investigate the parameters that depict the scour hole characteristics caused by turbulent wall jets and develop new mathematical relationships for them. Four significant parameters i.e.

EEG-based motor imagery channel selection and classification using hybrid optimization and two-tier deep learning.

Brain-computer interface (BCI) technology holds promise for individuals with profound motor impairments, offering the potential for communication and control. Motor imagery (MI)-based BCI systems are particularly relevant in this context. Despite their potential, achieving accurate and robust classification of MI tasks using electroencephalography (EEG) data remains a significant challenge.

An analytical characterization study on biofuel obtained from pyrolysis of Madhuca longifolia residues.

The current study focuses on examining the characteristics of biofuel obtained from the pyrolysis of Madhuca longifolia residues, since the selected forest residue was primarily motivated by its greater volatile matter content. The study used several analytical techniques to describe pyrolysis oil, char, and gas obtained from slow pyrolysis process conducted between 350 and 600 °C in a fixed-bed reactor. Initially, the effect of process temperature on product distribution was assessed to motivate maximum pyrolysis oil yield and found to be 44.

Gd substitution induced incommensurate antiferromagnetism in B20 noncentrosymmetric CoSi.

Rare-earth element Gd doped CoSi, Co1-xGdSi (= 0.01), is investigated using x-ray diffraction and magnetization. It crystallizes in B20 cubic structure with lattice parameter of= 4.

Spin-disorder intervened avoidance of quantum criticality in B20 cubic Mn1-xVxSi.

The effect of negative chemical pressure with the substitution of transition metal V in an itinerant helimagnetically ordered MnSi, Mn1-xVSi with= 0-0.1, is explored using dc and ac-susceptibilities. With increasing, the manifestations are unaffected crystal structure with increasing unit cell volume, suppression of long-range magnetic order, weakening of itinerant character and reduced spin-cooperative phenomenon.

A comparative assessment of biomethane potential of fresh fecal matter and fecal sludge and its correlation with malodor.

Comprehensive and proper management of fecal sludge (FS) is an ongoing concern in many nations. Decentralized fecal sludge treatment plants (FSTPs) are effective in this regard; however, many have experienced strong public opposition based partly on suspicion of malodor. Fecal sludge and freshly generated fecal matter (FM) samples from various FSTPs were collected, characterized, and investigated for biomethane potential.