Machine learning based intrusion detection framework for detecting security attacks in internet of things.

The Internet of Things (IoT) consist of a network of interconnected nodes constantly communicating, exchanging, and transferring data over various network protocols. Intrusion detection systems using deep learning are a common method used for providing security in IoT. However, traditional deep learning IDS systems do not accurately classify the attack and also require high computation time.

Development of a sustainable and disposable modified Bi-CdFeO electrode for electrochemical sensing of lead (II) and Acetaminophen drug molecule.

The study of research proposes a systematic pattern for optimization and fabrication of a sustainable-cost effective electrochemical sensor made by Bi-CdFeO (BCDF) nanoparticle and graphite powder. The structural examinations of synthesized BCDF materials were analyzed by specific spectral techniques viz.; P-XRD, SEM-EDX, TEM, XPS, FT-IR and DRS techniques.

Experimental investigation of a dual mode antenna using characteristic mode analysis with enhanced directivity for GSM/5G applications.

In this article, a dual-mode, dual-polarized antenna designed using characteristic mode analysis (CMA) is described. An elliptical-shaped patch radiator is chosen with double slits on its minor axis. This design is based on mode separation from the circular patch into the elliptical patch.

Human factors engineering simulated analysis in administrative, operational and maintenance loops of nuclear reactor control unit using artificial intelligence and machine learning techniques.

The nuclear reactor control unit employs human factor engineering to ensure efficient operations and prevent any catastrophic incidents. This sector is of utmost importance for public safety. This study focuses on simulated analysis of specific areas of nuclear reactor control, specifically administration, operation, and maintenance, using artificial intelligence software.

Effect of TiO Nanofillers on the Mechanical and Abrasive Wear Properties of Epoxy Reinforced with Carbon Fabric Hybrid Composites.

Recent studies show that nanofillers greatly contribute to the increase in the mechanical and abrasive behaviors of the polymer composite. In the current study, epoxy composites were made by hand lay-up with the reinforcement of carbon fabric and titanium dioxide (TiO) nanoparticles as secondary reinforcement in weight percentages of 0.5, 1.

Multi-objective hybrid split-ring resonator and electromagnetic bandgap structure-based fractal antennas using hybrid metaheuristic framework for wireless applications.

Design closure and parameter optimisation are crucial in creating cutting-edge antennas. Antenna performance can be improved by fine-tuning preliminary designs created using theoretical considerations and rough dimension adjustment via supervised parameter sweeps. This paper introduces a frequency reconfigurable antenna design that can operate at 28/38 GHz frequencies to meet FCC and Ofcom standards for 5G applications and in the 18 GHz frequency band for K-band radar applications.

A novel on design and implementation of hybrid MPPT controllers for solar PV systems under various partial shading conditions.

At present, fossil fuel-based power generation systems are reducing drastically because of their less availability in nature. In addition, it produces hazardous gasses and high environmental pollution. So, in this work, the solar natural source is selected for generating the electricity.

Assessment of the Biosensing Capabilities of SiGe Heterojunction Negative Capacitance-Vertical Tunnel Field-Effect Transistor.

In this study, a comparison of the negative capacitance vertical tunnel field-effect transistor (NC-VTFET) and VTFET for biosensing applications was conducted. Dielectrically modulated TFET demonstrates better sensitivity than the traditional metal oxide field effect transistor as a biosensor in label-free biosensing applications. The TFET biosensor, however, has much room for advancement by enhancing its DC characteristics.

Detection of Alzheimer's Disease Based on Cloud-Based Deep Learning Paradigm.

Deep learning is playing a major role in identifying complicated structure, and it outperforms in term of training and classification tasks in comparison to traditional algorithms. In this work, a local cloud-based solution is developed for classification of Alzheimer's disease (AD) as MRI scans as input modality. The multi-classification is used for AD variety and is classified into four stages.

Has Machine Learning Enhanced the Diagnosis of Autism Spectrum Disorder?

Autism spectrum disorder (ASD) is a complex neurological condition that limits an individual's capacity for communication and learning throughout their life. Although symptoms of Autism can be diagnosed in individuals of different ages, it is labeled as a developmental disorder because symptoms typically start to show up in the initial 2 years of childhood. Autism has no single known cause but multiple factors contribute to its etiology in children.

Contextual Cluster-Based Glow-Worm Swarm Optimization (GSO) Coupled Wireless Sensor Networks for Smart Cities.

The cluster technique involves the creation of clusters and the selection of a cluster head (CH), which connects sensor nodes, known as cluster members (CM), to the CH. The CH receives data from the CM and collects data from sensor nodes, removing unnecessary data to conserve energy. It compresses the data and transmits them to base stations through multi-hop to reduce network load.

Unclonable fluorescence of MgO-ZrO :Tb nanocomposite for versatile applications in data security, dermatoglyphics.

Latent fingerprints (LFPs) are one among the most important types of evidences at crime scenes because of the distinctiveness and tenacity of the friction ridges in fingerprints (FPs). Therefore, it is essential in forensic science to develop a reliable method to detect LFPs. Traditional detection methods still face a number of difficulties, such as limited sensitivity, low contrast, strong background, and complex processing stages.

-graphyne as a promising anode material for Na-ion batteries: a first-principles study.

Lithium-ion batteries (LIBs) have emerged as a technological game-changer. Due to the rising price of lithium and the environmental concerns LIBs pose, their use is no longer viable. Sodium (Na) may be the best contender among the alternatives for replacing lithium.

Hydrothermal synthesis of novel heterostructured Ag/TiO /CuFe O nanocomposite: Characterization, enhanced photocatalytic degradation of methylene blue dye, and efficient antibacterial studies.

In this work, we reported the successful synthesis of novel Ag/TiO /CuFe O ternary nanocomposite by hydrothermal technique by using TiO /CuFe O binary nanocomposite precursor that was also prepared by hydrothermal treatment by using TiO nanoparticles and CuFe O nanoparticles synthesized via sol-gel method. The synthesized nanomaterials were accessed for their morphological, structural, and optical properties. X-ray diffraction (XRD) study reveals the formation of pure Ag/TiO /CuFe O ternary nanocomposite in which the Ag, TiO , and CuFe O are in anatase, spinal, and cubic crystal phases, respectively.

Recent Advances in Green Synthesis, Characterization, and Applications of Bioactive Metallic Nanoparticles.

Nanoparticles (NPs) are elements derived from a cluster of atoms with one or more dimensions in the nanometer scale in the range of 1-100 nm. The bio nanofabrication of metallic NPs is now an important dynamic area of research, with major significance in applied research. Biogenic synthesis of NPs is more desirable than physical and chemical synthesis due to its eco-friendliness, non-toxicity, lower energy consumption, and multifunctional nature.

SARS-CoV 2 spike protein S1 subunit as an ideal target for stable vaccines: A bioinformatic study.

The Covid-19 a pandemic infectious disease and affected life across the world resulting in over 188.65 million confirmed cases across 223 countries, territories and areas with 4.06 million deaths.

ADID-UNET-a segmentation model for COVID-19 infection from lung CT scans.

Currently, the new coronavirus disease (COVID-19) is one of the biggest health crises threatening the world. Automatic detection from computed tomography (CT) scans is a classic method to detect lung infection, but it faces problems such as high variations in intensity, indistinct edges near lung infected region and noise due to data acquisition process. Therefore, this article proposes a new COVID-19 pulmonary infection segmentation depth network referred as the Attention Gate-Dense Network- Improved Dilation Convolution-UNET (ADID-UNET).

Sensing and sensitive visualization of latent fingerprints on various surfaces using a versatile fluorescent aggregation-induced emission-based coumarin derivative.

The marked rise in criminal activity in society has made a difficult task for forensic scientists who aim to track any crime scene effectively, therefore visualization of latent fingerprints (LFPs) plays an increasingly vital role in forensics. In the present report, a highly sensitive solvatochromism, aggregation-induced emission-based 2-(4-nitrophenyl)-3H-benzocoumarin fluorescent dye (CFD) was fabricated using an ultrasonication protocol. The fluorescence properties of the CFD were analyzed using fluorescence spectrophotometer.

An integrated feature frame work for automated segmentation of COVID-19 infection from lung CT images.

The novel coronavirus disease (SARS-CoV-2 or COVID-19) is spreading across the world and is affecting public health and the world economy. Artificial Intelligence (AI) can play a key role in enhancing COVID-19 detection. However, lung infection by COVID-19 is not quantifiable due to a lack of studies and the difficulty involved in the collection of large datasets.

Nipple Localization in Automated Whole Breast Ultrasound Coronal Scans Using Ensemble Learning.

Nipple is a vital landmark in the breast lesion diagnosis. Although there are advanced computer-aided detection (CADe) systems for nipple detection in breast mediolateral oblique (MLO) views of mammogram images, few academic works address the coronal views of breast ultrasound (BUS) images. This paper addresses a novel CADe system to locate the Nipple Shadow Area (NSA) in ultrasound images.

Polyoxotungstate ([PWO]) immobilized on mesoporous polymer for selective liquid-phase oxidation of alcohols using HO.

Selective oxidation of alcohols is an attractive organic transformation and has received tremendous attention from the scientific community over the years. Herein, a mesoporous polymer (MP) was synthesized by a template-free solvothermal approach. The surface of the MP was functionalized with quaternary ammonium groups and polyoxotungstate anion (PWO ) was subsequently supported on the MP as a counter anion to the ammonium cation by a simple ion-exchange procedure.

Low-Field MRI of Stroke: Challenges and Opportunities.

Stroke is a leading cause of death and disability worldwide. The reasons for increased stroke burden in developing countries are inadequately controlled risk factors resulting from poor public awareness and inadequate infrastructure. Computed tomography and MRI are common neuroimaging modalities used to assess stroke with diffusion-weighted MRI, in particular, being the recommended choice for acute stroke imaging.

An RDAU-NET model for lesion segmentation in breast ultrasound images.

Breast cancer is a common gynecological disease that poses a great threat to women health due to its high malignant rate. Breast cancer screening tests are used to find any warning signs or symptoms for early detection and currently, Ultrasound screening is the preferred method for breast cancer diagnosis. The localization and segmentation of the lesions in breast ultrasound (BUS) images are helpful for clinical diagnosis of the disease.

Biofabrication of Zinc Oxide Nanoparticles With Flower Buds Extract and Finding Its Novel Application in Controlling the Growth and Mycotoxins of .

is a leading plant pathogen that causes Fusarium head blight, stalk rot, and Gibberella ear rot diseases in cereals and posing the immense threat to the microbiological safety of the food. Herein, we report the green synthesis of zinc oxide nanoparticles from (SaZnO NPs) flower bud extract by combustion method and investigated their application for controlling of growth and mycotoxins of . Formation of SaZnO NPs was confirmed by spectroscopic methods.