Dynamic Lissajous patterns for real time identification and localization of power quality disturbance.

This study proposes a novel and computationally efficient method for real-time identification and localization of power quality (PQ) disturbances in microgrids using dynamic Lissajous patterns formed by voltage and current waveforms. Each power disturbance-such as sag, swell, harmonic distortion, and transients-induces a unique geometric deformation in the Lissajous figure, which serves as a visual signature of the event. Key geometric and statistical features, including area, skewness, kurtosis, and centroid deviation, are extracted from these dynamic patterns to construct robust indices for classification.

Study and Evaluation of ZnCoFeO Nanocrystalline Spinel Ferrites for Antimicrobial and Anticancer Applications.

Zinc-added cobalt ferrite with a composition of ZnCoFeO was synthesized using the sol-gel method with poly-(vinyl alcohol) as a chelating agent. The structural properties of the as-synthesized ferrite were determined using X-ray diffraction and Fourier transform infrared spectroscopy (FTIR). The measured structural parameters revealed the formation of a single-phase cubic spinel structure in the sample.

Experimental study on the effect of microwave heating power on the drying behavior of onion slices.

Microwave drying has become a highly effective and energy-efficient technique for the processing of agricultural products, mainly onion slices. This method proves to be advantageous over traditional methods of drying like sun drying and hot-air drying, which are often accompanied by longer periods of drying time and quality loss in terms of color, texture, and nutrient content. Microwave drying allows moisture removal through volumetric heating and thus saves energy while preserving essential quality attributes.

Novel and efficient synthesis of 5-chloro-6-methoxy-3-(2-((1-(aryl)-1-1,2,3-triazol-4-yl)methoxy)ethyl)benzo[]isoxazole derivatives as new -glucosidase inhibitors.

A new series of benzisoxazole derivatives () were designed by using molecular hybridization approach and synthesized click-chemistry. All the synthesized compounds were evaluated for their α-glucosidase enzyme inhibition and antibacterial activity. All tested compounds () exhibited a promising α-glucosidase inhibitory activity with IC range of 14.

Histopathological image based breast cancer diagnosis using deep learning and bio inspired optimization.

Breast cancer diagnosis remains a crucial challenge in medical research, necessitating accurate and automated detection methods. This study introduces an advanced deep learning framework for histopathological image classification, integrating AlexNet and Gated Recurrent Unit (GRU) networks, optimized using the Hippopotamus Optimization Algorithm (HOA). Initially, DenseNet-41 extracts intricate spatial features from histopathological images.

Synthesis, characterization, and and α-glucosidase inhibitory evolution of novel '-(2-cyclopentyl-2-phenylacetyl)cinnamohydrazide derivatives.

To discover potential α-glucosidase inhibitory agents, a new series of '-(2-cyclopentyl-2-phenylacetyl)cinnamohydrazide derivatives were designed and synthesized as α-glucosidase inhibitors. The newly synthesized compounds were characterized using H, C NMR, and mass spectroscopy analysis and evaluated for their α-glucosidase inhibitory effects. All the tested compounds displayed significant α-glucosidase inhibitory activity compared to the standard drug acarbose.

An algorithm for heterogeneous wireless network connections for user preferences and services.

Heterogeneous wireless networks (HWNs) present a challenge in selecting the optimal network for user devices due to the overlapping availability of multiple networks. In order to help users choose the best HWN connection, this research is trying to build a decision-making framework that takes user preferences and network performance characteristics into account. Using a multi-attribute decision-making (MADM) method that incorporates fuzzy logic and the Fuzzy Analytic Hierarchy Process (FAHP), our goal is to improve the decision-making process for network selection.

Hardware-Accelerated Non-Contact System for Sleep Disorder Monitoring and Analysis.

This study analyzes human sleep disorders using non-contact approaches. The proposed approach analyzes periodic limb movement disorder (PLMD) under sleep conditions. This was conceptualized as data capture using a non-contact approach with ultrasonic sensors.

Hyaluronic-Acid-Functionalized Tofacitinib Loaded Transethosomes for Targeted Drug Delivery in Rheumatoid Arthritis.

The Janus kinase inhibitor tofacitinib (TOF) is an FDA-approved drug for rheumatoid arthritis (RA) treatment, but its long-term oral use leads to significant systemic side effects. The present research aimed to conquer these challenges by formulating hyaluronic-acid-coated transethosomes (HA-TOF-TE), a novel system for targeted, topical delivery of TOF to reduce systemic toxicity and improve therapeutic efficacy. Transethosomes were synthesized via the cold sonication technique with HA functionalization enabling CD44 receptor-mediated targeting of inflamed synovial tissue.

ANFIS-PSO analysis on axisymmetric tetra hybrid nanofluid flow of Cu-CNT-Graphene-Tio with WEG-Blood under linear thermal radiation and inclined magnetic field: A bio-medicine application.

Background: The development of heat transfer devices used for heat conversion and recovery in several industrial and residential applications has long focused on improving heat transfer between two parallel plates. Numerous articles have examined the relevance of enhancing thermal performance for the system's performance and economics. Heat transport is improved by increasing the Reynolds number as the turbulent effects grow.

A Field-Programmable Gate Array-Based Adaptive Sleep Posture Analysis Accelerator for Real-Time Monitoring.

This research presents a sleep posture monitoring system designed to assist the elderly and patient attendees. Monitoring sleep posture in real time is challenging, and this approach introduces hardware-based edge computation methods. Initially, we detected the postures using minimally optimized sensing modules and fusion techniques.

Optimal placement of renewable distributed generators and electric vehicles using multi-population evolution whale optimization algorithm.

This research takes on a crucial task- exploring the optimal placement of Renewable Distributed Generators such as Solar Photovoltaic, wind turbines and Electric Vehicles into the Radial Distribution System (RDS). This is a strategic move aimed at minimising power loss (P) and improving the voltage profile and stability index. The RDGs are integrated into RDS with and without considering the uncertainty of the different load demands for 24 h.

Comprehensive analysis of faults and diagnosis techniques in cascaded multi-level inverters.

Reliability is a crucial factor to consider for multi-level inverters (MLIs) used in industrial applications. With the increasing number of power semiconductor devices, the potential for defects to significantly degrade the overall system is heightened. A highly effective fault-detection technique is required to minimize the impact of faults.

Adaptive FPGA-Based Accelerators for Human-Robot Interaction in Indoor Environments.

This study addresses the challenges of human-robot interactions in real-time environments with adaptive field-programmable gate array (FPGA)-based accelerators. Predicting human posture in indoor environments in confined areas is a significant challenge for service robots. The proposed approach works on two levels: the estimation of human location and the robot's intention to serve based on the human's location at static and adaptive positions.

Dual-Wide Multi-Band (DWMB) four-port flexible MIMO antenna for on-body multiple wireless applications including high diversity performance.

The single-input-single-output technology experiences loss of data in the communication channel due to the receiving antenna undergoing fading of the signal impinged on it. Today's need is faster data transfer with multiple applications in the single antenna with multiple-identical radiating elements, leading to multiple-input-multiple-outputDWMB (MIMODWMB) technology. The MIMODWMB configuration with multi-band capability is the objective of the proposed work with applications ranging between microwave-millimeterWave bands.

Molecular interaction studies of L-proline in water and ethanol at different temperatures using dielectric relaxation, refractive index and DFT methods.

The complex dielectric permittivity of L-Proline in water and ethanol solutions with molar concentrations ranging from 0.025 M to 0.15 M was measured by open-ended coaxial probe technique.

Forecasting deep learning-based risk assessment of vector-borne diseases using hybrid methodology.

Background: Dengue fever is rapidly becoming Malaysia's most pressing health concern, as the reported cases have nearly doubled over the past decade. Without efficacious antiviral medications, vector control remains the primary strategy for battling dengue, while the recently introduced tetravalent immunization is being evaluated. The most significant and dangerous risk increasing recently is vector-borne illnesses.

Hybrid deep learning and optimized clustering mechanism for load balancing and fault tolerance in cloud computing.

Cloud services are one of the most quickly developing technologies. Furthermore, load balancing is recognized as a fundamental challenge for achieving energy efficiency. The primary function of load balancing is to deliver optimal services by releasing the load over multiple resources.

A Versatile Approach for Adaptive Grid Mapping and Grid Flex-Graph Exploration with a Field-Programmable Gate Array-Based Robot Using Hardware Schemes.

Robotic exploration in dynamic and complex environments requires advanced adaptive mapping strategies to ensure accurate representation of the environments. This paper introduces an innovative grid flex-graph exploration (GFGE) algorithm designed for single-robot mapping. This hardware-scheme-based algorithm leverages a combination of quad-grid and graph structures to enhance the efficiency of both local and global mapping implemented on a field-programmable gate array (FPGA).

Hardware Schemes for Smarter Indoor Robotics to Prevent the Backing Crash Framework Using Field Programmable Gate Array-Based Multi-Robots.

The use of smart indoor robotics services is gradually increasing in real-time scenarios. This paper presents a versatile approach to multi-robot backing crash prevention in indoor environments, using hardware schemes to achieve greater competence. Here, sensor fusion was initially used to analyze the state of multi-robots and their orientation within a static or dynamic scenario.

Morphologically tuned CuO-ZnO-CeO catalyst for CO hydrogenation to methanol.

Morphologically modified composite CuO-ZnO-CeO catalysts were synthesized using a single-step hydrothermal technique. The study highlights the influence of solvent on the structural and physico-chemical properties of the catalysts. Various techniques, such as XRD, FE-SEM, BET, XPS, and H-TPR, were used to analyze the catalyst properties.

An effective Alzheimer's disease segmentation and classification using Deep ResUnet and Efficientnet.

Alzheimer's disease (AD) is a degenerative neurologic condition that results in the deterioration of several brain processes (e.g. memory loss).