Dual scale light weight cross attention transformer for skin lesion classification.

Skin cancer is rapidly growing globally. In the past decade, an automated diagnosis system has been developed using image processing and machine learning. The machine learning methods require hand-crafted features, which may affect performance.

EDTNet: A spatial aware attention-based transformer for the pulmonary nodule segmentation.

Accurate segmentation of lung lesions in CT-scan images is essential to diagnose lung cancer. The challenges in lung nodule diagnosis arise due to their small size and diverse nature. We designed a transformer-based model EDTNet (Encoder Decoder Transformer Network) for PNS (Pulmonary Nodule Segmentation).

Boosting piezoelectric properties of PVDF nanofibers via embedded graphene oxide nanosheets.

Tremendous research efforts have been directed toward developing polymer-based piezoelectric nanogenerators (PENG) in a promising step to investigate self-charging powered systems (SCPSs) and consequently, support the need for flexible, intelligent, and ultra-compact wearable electronic devices. In our work, electrospun polyvinylidene fluoride (PVDF) nanofiber mats were investigated while graphene oxide (GO) was added with different concentrations (from 0 to 3 wt.%).

Robot-based solution for helping Alzheimer patients.

Alzheimer's is a progressive and debilitating neurological disorder characterized by cognitive decline, memory loss, and impaired daily functioning. It is an irreversible brain disease that destroys memory, thinking, and the ability to carry out daily activities. It poses significant challenges for patients and healthcare providers.

Advancing Hyperspectral Image Analysis with CTNet: An Approach with the Fusion of Spatial and Spectral Features.

Hyperspectral image classification remains challenging despite its potential due to the high dimensionality of the data and its limited spatial resolution. To address the limited data samples and less spatial resolution issues, this research paper presents a two-scale module-based CTNet (convolutional transformer network) for the enhancement of spatial and spectral features. In the first module, a virtual RGB image is created from the HSI dataset to improve the spatial features using a pre-trained ResNeXt model trained on natural images, whereas in the second module, PCA (principal component analysis) is applied to reduce the dimensions of the HSI data.

Unsupervised Learning-Based WSN Clustering for Efficient Environmental Pollution Monitoring.

Wireless Sensor Networks (WSNs) have been adopted in various environmental pollution monitoring applications. As an important environmental field, water quality monitoring is a vital process to ensure the sustainable, important feeding of and as a life-maintaining source for many living creatures. To conduct this process efficiently, the integration of lightweight machine learning technologies can extend its efficacy and accuracy.

Nano-Chitosan/ Oil/Cellulose Acetate Nanofibers: Manufacturing, Antibacterial and Wound Healing Activities.

Accelerated wound healing in infected skin is still one of the areas where current therapeutic tactics fall short, which highlights the critical necessity for the exploration of new therapeutic approaches. The present study aimed to encapsulate oil in a nano-drug carrier to enhance its antimicrobial activity. Furthermore, in vitro, and in vivo wound healing studies of the novel nano-chitosan/ oil/cellulose acetate electrospun nanofibers were investigated.

Nano-Enriched Self-Powered Wireless Body Area Network for Sustainable Health Monitoring Services.

Advances in nanotechnology have enabled the creation of novel materials with specific electrical and physical characteristics. This leads to a significant development in the industry of electronics that can be applied in various fields. In this paper, we propose a fabrication of nanotechnology-based materials that can be used to design stretchy piezoelectric nanofibers for energy harvesting to power connected bio-nanosensors in a Wireless Body Area Network (WBAN).

Innovative antibacterial electrospun nanofibers mats depending on piezoelectric generation.

This paper introduces a new approach of testing piezoelectric nanofibers as antibacterial mat. In this work, both Polyvinylidene fluoride (PVDF) and PVDF embedded with thermoplastic polyurethane nanofibers are synthesized as nanofibers mat via electrospinning technique. Then, such mat is analyzed as piezoelectric material to generate electric voltage under different mechanical excitations.

Novel Novolac Phenolic Polymeric Network of Chalcones: Synthesis, Characterization, and Thermal-Electrical Conductivity Investigation.

A series of novolac phenolic polymeric networks (NPPN) were prepared via an acid-catalyzed polycondensation reaction of formaldehyde with chalcones possessing a -phenolic OH group. When -hydroxybenzaldehyde was treated with formaldehyde under the same conditions, a phenolic polymer (PP) was obtained. The resulting polymers were isolated in excellent yields (83-98%).

Semantic textual similarity for modern standard and dialectal Arabic using transfer learning.

Semantic Textual Similarity (STS) is the task of identifying the semantic correlation between two sentences of the same or different languages. STS is an important task in natural language processing because it has many applications in different domains such as information retrieval, machine translation, plagiarism detection, document categorization, semantic search, and conversational systems. The availability of STS training and evaluation data resources for some languages such as English has led to good performance systems that achieve above 80% correlation with human judgment.

Stretchable nanofibers of polyvinylidenefluoride (PVDF)/thermoplastic polyurethane (TPU) nanocomposite to support piezoelectric response via mechanical elasticity.

Interest in piezoelectric nanocomposites has been vastly growing in the energy harvesting field. They are applied in wearable electronics, mechanical actuators, and electromechanical membranes. In this research work, nanocomposite membranes of different blend ratios from PVDF and TPU have been synthesized.

Decision tree based ensemble machine learning model for the prediction of Zika virus T-cell epitopes as potential vaccine candidates.

Zika fever is an infectious disease caused by the Zika virus (ZIKV). The disease is claiming millions of lives worldwide, primarily in developing countries. In addition to vector control strategies, the most effective way to prevent the spread of ZIKV infection is vaccination.

IoT-Enabled Framework for Early Detection and Prediction of COVID-19 Suspects by Leveraging Machine Learning in Cloud.

COVID-19 is the repugnant but the most searched word since its outbreak in November 2019 across the globe. The world has to battle with it until an effective solution is developed. Due to the advancement in mobile and sensor technology, it is possible to come up with Internet of things-based healthcare systems.

Biosensor-Assisted Method for Abdominal Syndrome Classification Using Machine Learning Algorithm.

The digestive system is one of the essential systems in human physiology where the stomach has a significant part to play with its accessories like the esophagus, duodenum, small intestines, and large intestinal tract. Many individuals across the globe suffer from gastric dysrhythmia in combination with dyspepsia (improper digestion), unexplained nausea (feeling), vomiting, abdominal discomfort, ulcer of the stomach, and gastroesophageal reflux illnesses. Some of the techniques used to identify anomalies include clinical analysis, endoscopy, electrogastrogram, and imaging.

Zika Virus Prediction Using AI-Driven Technology and Hybrid Optimization Algorithm in Healthcare.

The Zika virus presents an extraordinary public health hazard after spreading from Brazil to the Americas. In the absence of credible forecasts of the outbreak's geographic scope and infection frequency, international public health agencies were unable to plan and allocate surveillance resources efficiently. An RNA test will be done on the subjects if they are found to be infected with Zika virus.

Data Mining in Employee Healthcare Detection Using Intelligence Techniques for Industry Development.

Background: Even in today's environment, when there is a plethora of information accessible, it may be difficult to make appropriate choices for one's well-being. Data mining, machine learning, and computational statistics are among the most popular arenas of training today, and they are all aimed at secondary empowered person in making good decisions that will maximize the outcome of whatever working area they are involved with. Because the degree of rise in the number of patient roles is directly related to the rate of people growth and lifestyle variations, the healthcare sector has a significant need for data processing services.

Blockchain and IPFS Integrated Framework in Bilevel Fog-Cloud Network for Security and Privacy of IoMT Devices.

Internet of Medical Things (IoMT) has emerged as an integral part of the smart health monitoring system in the present world. The smart health monitoring deals with not only for emergency and hospital services but also for maintaining a healthy lifestyle. The industry 5.

Patient Behavioral Analysis with Smart Healthcare and IoT.

Patient behavioral analysis is the key factor for providing treatment to patients who may suffer from various difficulties including neurological disease, head trauma, and mental disease. Analyzing the patient's behavior helps in determining the root cause of the disease. In traditional healthcare, patient behavioral analysis has lots of challenges that were much more difficult.

Elastic Nanofibrous Membranes for Medical and Personal Protection Applications: Manufacturing, Anti-COVID-19, and Anti-Colistin Resistant Bacteria Evaluation.

Herein, in the present work two series of thermoplastic polyurethane (TPU) nanofibers were manufactured using the electrospinning techniques with ZnO and CuO nanoparticles for a potential use as an elastic functional layer in antimicrobial applications. Percentages of 0%, 2 wt%, and 4 wt% of the nanoparticles were used. The morphological characterization of the electrospun TPU and TPU/NPs composites nanofibers were observed by using scanning electron microscopy to show the average fiber diameter and it was in the range of 90-150 nm with a significant impact of the nanoparticle type.

Smartphone-Based mHealth and Internet of Things for Diabetes Control and Self-Management.

In patients with chronic diseases condition, mobile health monitoring facility proves to play a significant role in providing significant assistance toward personal management. This research examined the use of smartphones by diabetes patients and their intentions to apply them for self-care and monitoring as well as management. This cross-sectional survey-based study was conducted in Jul-Aug 2021 with 200 diabetic patients (especially type 2) who were visiting specialized clinics and hospitals of Gujrat state, India.

Biodegradable Nanofibrous Membranes for Medical and Personal Protection Applications: Manufacturing, Anti-COVID-19 and Anti-Multidrug Resistant Bacteria Evaluation.

Biodegradable nanofibrous hybrid membranes of polyvinyl alcohol (PVA) with ZnO and CuO nanoparticles were manufactured and characterized, and their anti-COVID-19 and anti-multidrug resistant bacteria activities were also evaluated. The morphological structures of the prepared PVA composites nanofibers were observed by scanning electron microscope (SEM), which revealed a homogenous pattern of the developed nanofibers, with an average fibrous diameter of 200-250 nm. Moreover, the results of the SEM showed that the fiber size changed with the type and the concentration of the metal oxide.