Advanced generative adversarial network for optimizing layout of wireless sensor networks.

The best layout design related to the sensor node distribution represents one among the major research questions in Wireless Sensor Networks (WSNs). It has a direct impact on WSNs' cost, detection capabilities, and monitoring quality. The optimization of several conflicting objectives, including as load balancing, coverage, cost, lifetime, connection, and energy consumption of sensor nodes, is necessary for layout optimization.

Hybrid quantum enhanced federated learning for cyber attack detection.

Cyber-attack brings significant threat and become a critical issue in the digital world network security. The conventional procedures developed to detects are centralized and often struggles with concerns like data privacy and communication overheads. Due to this, conventional methods are unable to adapt quickly for different threats.

Sparse attention with residual pyramidal depthwise separable convolutional based malware detection with optimization mechanism.

Recent developments indicate that malware programs present a significant risk in the security and privacy of cloud systems. Existing research in malware detection encounters numerous significant challenges due to the constantly changing and advanced characteristics of malware. Malware detection systems frequently experience high rates of false positives and false negatives, where legitimate applications are incorrectly identified as malware or actual malware remains undetected, which results in operational inefficiencies.

Design of modified long short-term memory-based zebra optimization algorithm for limiting the issue of SHEPWM in multi-level inverter.

This research work proposes unique MLSTM-ZOA to quickly measure SAs for an MLI. Within a certain MI range, the suggested method may calculate a greater count of SAs with various solutions. Here, the main objective lies in minimizing the THD with consideration of three parameters such as MI, number of pulses per quarter cycle, and duty cycle.

Tracking perishable foods in the supply chain using chain of things technology.

Modern food supply chains are intrinsically sophisticated due to their multi-participant and multi-echelon structure, which are challenging to handle high turbulent business environment. The development of Perishable Food Supply Chains (PFSC) has to be strong enough to manage any type of disruptions in the food industry. At the same time, the food processing industry must also take responsibility for the social and environmental consequences of their deeds.

A novel development of hybrid maximum power point tracking controller for solar pv systems with wide voltage gain DC-DC converter.

Now, the present power generation and distribution companies are working on renewable energy systems because their features are low-level atmospheric pollution, producing less greenhouse pollutants, more reliability, good static performance, and high robustness. In this work, the sunlight Photovoltaic (PV) system is selected because of its advantages are easily available in the atmosphere, high flexibility, zero carbon footprint, easy to maintain, and less transportation cost. However, solar networks produce nonlinear I-V characteristics.

A hybrid deep learning approach to solve optimal power flow problem in hybrid renewable energy systems.

The reliable operation of power systems while integrating renewable energy systems depends on Optimal Power Flow (OPF). Power systems meet the operational demands by efficiently managing the OPF. Identifying the optimal solution for the OPF problem is essential to ensure voltage stability, and minimize power loss and fuel cost when the power system is integrated with renewable energy resources.

An experimental investigation on copper square electrode wear in electric discharge machining of Hastelloy B2.

Hastelloy B2 is a high-performance nickel-molybdenum alloy and has been used in micro reactor, pump, pipe, and corrosion-resistant equipment. Square holes are required in the above application components. Although square holes are easily produced by spending more electrodes wear in Electrical Discharge Machining (EDM).

Human monkeypox disease prediction using novel modified restricted Boltzmann machine-based equilibrium optimizer.

While the globe continues to struggle to recover from the devastation brought on by the COVID-19 virus's extensive distribution, the recent worrying rise in human monkeypox outbreaks in several nations raises the possibility of a novel worldwide pandemic. The symptoms of human monkeypox resemble those of chickenpox and traditional measles, with a few subtle variations like the various kinds of skin blisters. A range of deep learning techniques have demonstrated encouraging results in image-oriented tumor cell, Covid-19 diagnosis, and skin disease prediction tasks.

An effective video inpainting technique using morphological Haar wavelet transform with krill herd based criminisi algorithm.

In recent times, video inpainting techniques have intended to fill the missing areas or gaps in a video by utilizing known pixels. The variety in brightness or difference of the patches causes the state-of-the-art video inpainting techniques to exhibit high computation complexity and create seams in the target areas. To resolve these issues, this paper introduces a novel video inpainting technique that employs the Morphological Haar Wavelet Transform combined with the Krill Herd based Criminisi algorithm (MHWT-KHCA) to address the challenges of high computational demand and visible seam artifacts in current inpainting practices.

A comprehensive performance analysis of advanced hybrid MPPT controllers for fuel cell systems.

The present power generation corporations are working on Renewable Power Systems (RPS) for supplying electrical power to the automotive power industries. There are several categories of RPSs available in the atmosphere. Among all of the RPSs, the most general power network used for Electric Vehicles (EVs) is hydrogen fuel which is available in nature.

Experimental design and analysis of advanced three phase converter for PV application with WCO-P&O MPPT controller.

Photovoltaic (PV)-based power generation systems are becoming increasingly popular as a due to its high performance and cleanliness. Several factors influence the performance of a PV system, including shadowing effects. PV systems employ MPPT methodologies to obtain the power from PV array.

Design and analysis of solitary AC-AC converter using reduced components for efficient power generation system.

Considering different applications that require varied power and voltage conversion levels between AC grids and AC loads, AC-AC power conversion between AC grids has become an inevitable technology of energy management systems. An isolated converter for performing AC-to-AC transmission is proposed with minimal components for reduced losses and enhanced system efficiency. Single-phase direct buck-boost AC to AC converter with minimum components constituted with two dual IGBT control units (IGBT 1-IGBT 4), inductor (L), and capacitor (C) is proposed in this work.

Development of grey wolf optimization based modified fast terminal sliding mode controller for three phase interleaved boost converter fed PV system.

The conventional MPPT method has drawbacks, such as that under partial shading conditions, several peaks occur and identifying the global peak is difficult. It may converge to a local peak and lead to poor conversion efficiency and tracking efficiency. Implementation of a hybrid algorithm by integrating P&O and metaheuristic algorithms can perform better under partial shading conditions.

Performance optimization of interleaved boost converter with ANN supported adaptable stepped-scaled P&O based MPPT for solar powered applications.

Solar energy is the most promising among many renewable energy sources to meet the increasing demand. Photovoltaic (PV) based power generating solutions are expected to gain popularity as a power source for different applications, including independent and grid connected loads, due to their cleanliness, high performance, and high dependability. The efficacy of photovoltaic systems is impacted by several elements, including geographical location, positioning, shadowing effects, and local climate conditions.

A quad DC source switched three-phase multilevel DC-link inverter topology.

The concept of an isolated DC source cascaded multilevel inverter finds good solutions for generating quality output voltage for low-medium power applications. It shapes the output voltage from three levels into a number of steps closer to a sinusoidal shape using small DC sources or batteries. Several advantages have been sighted like lower voltage stress and bearing noise, and lesser THD.

Shrimp classification for white spot syndrome detection through enhanced gated recurrent unit-based wild geese migration optimization algorithm.

The major dangerous viral infection for cultivated shrimps is WSSV. The virus is extremely dangerous, spreads swiftly, and may result in up to 100% mortality in 3-10 days. The vast wrapped double stranded DNA virus known as WSSV describes a member of the Nimaviridae viral family's species Whispovirus.

Green synthesis of MnO nanoparticles from Psidium guajava leaf extract: Morphological characterization, photocatalytic and DNA/BSA interaction studies.

In this work, a simple, efficient and eco-friendly green synthesis of manganese dioxide nanoparticles (MnONPs) by Psidium guajava leaf extract was described. Fourier-Transform infrared spectra results revealed that involvement of the plant extract functional groups in the formation of MnONPs. The UV-vis absorption spectra of the synthesized MnONPs exhibited absorption peaks at 374 nm, which were attributed to the band gap of the MnONPs.

Optimization of Double-Gate Carbon Nanotube FET Characteristics for Short Channel Devices.

Introduction: Transistors are the fundamental electronic component integrated into electronic devices' chips Carbon Nano Tube (CNT) based field.

Methods: Effect Transistor (FET) is a promising component for next-generation transistor technologies; as it has high carrier mobility, device stability, and mechanical flexibility. Nevertheless, some shortcomings in the CNT FET's design prevent it from providing the best performance while preserving thermal stability.

Spectroscopic and theoretical approach of DNA interaction and anticancer studies of bio-pharmaceutically active pyrimidine derived Cu(II) and Zn(II) complexes.

New metal(II) complexes (CuL and ZnL) with pyrimidine appended Schiff base ligand (HL) were synthesized and characterized by diverse spectroscopic methods, reveals the proposed structure of metal(II) complexes possess square planar geometry. DNA interaction ability of isolated compounds was studied by UV-Visible, fluorescence, viscometric and electrochemical methods and the results showed that isolated compounds intercalated with calf thymus DNA (CT-DNA). In addition, anticancer activities of HL, CuL and ZnL have been evaluated by MTT assay, signifying moderate cytotoxic activity on selected cancer cell lines and less toxicity on NHDF normal cell line due to the specific targeting of pyrimidine analogues.

DNA/BSA interaction, anticancer, antimicrobial and catalytic applications of synthesis of nitro substituted pyrimidine-based Schiff base ligand capped nickel nanoparticles.

The objective of this research was to create stable nickel nanoparticles using nickel chloride salt and a Schiff base ligand called DPMN. The synthesis process involved a two-step phase transfer procedure. Spectroscopic techniques such as UV-Visible and FT-IR were used to confirm the formation of ligand-stabilized nickel nanoparticles (DPMN-NiNPs).

Reduction of pollutant emissions from a heat treatment furnace.

This paper addresses a preliminary study on the emission control of pollutants from an industrial furnace. The stack sampling technique was implemented in this study, and the quantity of pollutants released from the furnace smoke was monitored. The transverse points required to collect the data were selected based on the upstream and downstream disturbances.

Reshaping healthcare supply chain using chain-of-things technology and key lessons experienced from COVID-19 pandemic.

The COVID-19 (Corona virus disease 2019) pandemic continues to slash through the entire humanity on the earth causing an international health crisis and financial uncertainty. The pandemic has formed a colossal disruption in supply chain networks. It has caused piling higher mortality in patients with comorbidities and generated a surging demand for critical care equipment, vaccines, pharmaceuticals, and cutting-edge technologies.