Diagnostic structure of visual robotic inundated systems with fuzzy clustering membership correlation.

The process of using robotic technology to examine underwater systems is still a difficult undertaking because the majority of automated activities lack network connectivity. Therefore, the suggested approach finds the main hole in undersea systems and fills it using robotic automation. In the predicted model, an analytical framework is created to operate the robot within predetermined areas while maximizing communication ranges.

An improved GBSO-TAENN-based EEG signal classification model for epileptic seizure detection.

Detection and classification of epileptic seizures from the EEG signals have gained significant attention in recent decades. Among other signals, EEG signals are extensively used by medical experts for diagnosing purposes. So, most of the existing research works developed automated mechanisms for designing an EEG-based epileptic seizure detection system.

EEG-BCI-based motor imagery classification using double attention convolutional network.

This article aims to improve and diversify signal processing techniques to execute a brain-computer interface (BCI) based on neurological phenomena observed when performing motor tasks using motor imagery (MI). The noise present in the original data, such as intermodulation noise, crosstalk, and other unwanted noise, is removed by Modify Least Mean Square (M-LMS) in the pre-processing stage. Traditional LMSs were unable to extract all the noise from the images.

Optimizing the allocation of renewable DGs, DSTATCOM, and BESS to mitigate the impact of electric vehicle charging stations on radial distribution systems.

The increasing global adoption of Electric Vehicles (EVs) necessitates a greater supply of electricity for charging these cars. The popularity of EVs is also driven by their minimal maintenance requirements, enhanced performance, and eco-friendly nature. However, the expanding usage of EVs poses challenges to the distribution system's efficiency, thereby impacting its reliability.

A study on waste PCB fibres reinforced concrete with and without silica fume made from electronic waste.

This research goal is to appraise the effect of electronic waste on concrete properties by examining the mechanical properties of concrete reinforced with waste printed circuit boards (PCBs). PCB fibres, each 50 mm long, were mixed in varying proportions (1-5% by weight of cement). Silica fume (SF) was used as a 12% weight replacement for cement to conserve the properties of PCB fibre-reinforced concrete while tumbling cement consumption.

An improved energy-efficient cloud-optimized load-balancing for IoT frameworks.

As wireless communication grows, so does the need for smart, simple, affordable solutions. The need prompted academics to develop appropriate network solutions ranging from wireless sensor networks (WSNs) to the Internet of Things (IoT). With the innovations of researchers, the necessity for enhancements in existing researchers has increased.

Deep fit_predic: a novel integrated pyramid dilation EfficientNet-B3 scheme for fitness prediction system.

This study introduces novel deep learning (DL) techniques for effective fitness prediction using a person's health data. Initially, pre-processing is performed in which data cleaning, one-hot encoding and data normalization are performed. The pre-processed data are then fed into the feature selection stage, where the useful features are extracted using the enhanced chameleon swarm (ECham-Sw) optimization technique.

Iodoxybenzoic Acid (IBX) in Organic Synthesis: A Septennial Review.

This study reviews the oxidative applications of 2-iodoxybenzoic acid (IBX) in organic synthesis, focusing on C-H functionalization, hetero-hetero bond formations, ring cleavage reactions, dehydrogenation, heterocyclic ring formations, and some miscellaneous reactions in a comprehensive and critical way. It compiles the literature starting from mid-2015 to date.

Experimental Investigation and Characterization of Friction Stir Spot-Welded Dissimilar Aluminum Copper Metallic Lap Joints.

Due to their contrasting physical properties, joining materials like copper and aluminum has always proven difficult. The disadvantages of traditional joining methods include additional weight, solidification problems, and energy waste. Friction stir spot-welding (FSSW) was utilized for joining copper and aluminum in order to get around these difficulties.

Prediction of DDoS attacks in agriculture 4.0 with the help of prairie dog optimization algorithm with IDSNet.

Integrating cutting-edge technology with conventional farming practices has been dubbed "smart agriculture" or "the agricultural internet of things." Agriculture 4.0, made possible by the merging of Industry 4.

Energy generation from bioelectrochemical techniques: Concepts, reactor configurations and modeling approaches.

The process industries play a significant role in boosting the economy of any nation. However, poor management in several industries has been posing worrisome threats to an environment that was previously immaculate. As a result, the untreated waste and wastewater discarded by many industries contain abundant organic matter and other toxic chemicals.

Efficient data transmission on wireless communication through a privacy-enhanced blockchain process.

In the medical era, wearables often manage and find the specific data points to check important data like resting heart rate, ECG voltage, SPO2, sleep patterns like length, interruptions, and intensity, and physical activity like kind, duration, and levels. These digital biomarkers are created mainly through passive data collection from various sensors. The critical issues with this method are time and sensitivity.

A novel artificial intelligence-based predictive analytics technique to detect skin cancer.

One of the leading causes of death among people around the world is skin cancer. It is critical to identify and classify skin cancer early to assist patients in taking the right course of action. Additionally, melanoma, one of the main skin cancer illnesses, is curable when detected and treated at an early stage.

Power enhanced solar PV array configuration based on calcudoku puzzle pattern for partial shaded PV system.

The power output of solar photovoltaic systems can be affected by environmental factors, such as partial shading. This can lead to a decrease in the power conversion rate of the system. Although existing solutions for this issue are cost-effective and efficient, new solutions could further improve the system's performance by increasing consistency, power generation, and reducing mismatch loss and costs.

Solar photovoltaic converter controller using opposition-based reinforcement learning with butterfly optimization algorithm under partial shading conditions.

The major use of a power point tracking controller is to maximize or enhance the power generation in photovoltaic systems. These systems are steered to operate and maximize the power point. Under partial shading conditions, the power points may vary or fluctuate between global maxima and local maxima.

Experimental investigation and multi-objective optimization of eco-friendly near-dry electrical discharge machining of shape memory alloy using Cu/SiC/Gr composite electrode.

The near-dry electrical discharge machining processes have been conducted using air-mist or gas mist as a dielectric fluid to minimize the environmental impacts. In this article, near-dry electrical discharge machining (NDEDM) experiments have been performed to improve machining performance using an oxygen-mist dielectric fluid, a copper composite electrode, and Cu-Al-Be polycrystalline shape memory alloy (SMA) work materials. The copper composite electrode is made up of 12 wt% silicon carbide and 9 wt% graphite particles.

Are emerging technologies unlocking the potential of sustainable practices in the context of a net-zero economy? An analysis of driving forces.

Increasing globalization and climate change have significantly affected business activities. Government and other stakeholders are creating pressure to have a sustainable business model for efficient resource utilization and minimizing negative environmental impact. Many organizations have started focusing on sustainable and cleaner production through the adoption of net-zero economy (NZE) practices.

N-Doped Carbon Dots and ZnO Conglomerated Electrodes for Optically Responsive Supercapacitor Applications.

The over-dependence of human society on fossil fuels for energy is exhausting the level of such non-renewable energy sources. Alternative energy storage systems have gained more popularity recently to counter this issue. In this context, we report the fabrication of N-doped carbon dot (N-CD)-decorated ZnO-based electrodes for supercapacitor applications.

Thwarting Alzheimer's Disease through Healthy Lifestyle Habits: Hope for the Future.

Alzheimer's disease (AD) is a neurodegenerative disorder that slowly disintegrates memory and thinking skills. Age is known to be the major risk factor in AD, but there are several nonmodifiable and modifiable causes. The nonmodifiable risk factors such as family history, high cholesterol, head injuries, gender, pollution, and genetic aberrations are reported to expediate disease progression.

A novel COVID diagnosis and feature extraction based on discrete wavelet model and classification using X-ray and CT images.

Recently, the Covid-19 pandemic has affected several lives of people globally, and there is a need for a massive number of screening tests to diagnose the existence of coronavirus. For the medical specialist, detecting COVID-19 cases is a difficult task. There is a need for fast, cheap and accurate diagnostic tools.

Unveiling the correlation between structural and magnetic ordering in nano CoNiTeO.

Nanomaterials with unique structures and exotic magnetic phenomena are always intriguing; however, the direct correlation of structural and magnetic ordering up to a few nanometers remains critical. We report structural and magnetic properties of sol-gel grown CoNiTeO ( = 0, 0.5 and 1) nanoparticles.

Deciphering the Nexus Between Oxidative Stress and Spermatogenesis: A Compendious Overview.

Oxidative stress (OS) and reactive oxygen species (ROS) are one of the main reasons for the multifactorial concern - male infertility. ROS are active components of cellular metabolism that are intrinsic to cellular functioning and are present at minimal and unreactive levels in normal cells. They are an integral component of the sperm developmental physiology, capacitation, and function.