Multimodal data-based human motion intention prediction using adaptive hybrid deep learning network for movement challenged person.

Recently, social demands for a good quality of life have increased among the elderly and disabled people. So, biomedical engineers and robotic researchers aimed to fuse these techniques in a novel rehabilitation system. Moreover, these models utilized the biomedical signals acquired from the human body's particular organ, cells, or tissues.

Performance enhancement in hydroponic and soil compound prediction by deep learning techniques.

The soil quality plays a crucial role in providing essential nutrients for crop growth and ensuring a bountiful yield. Identifying the soil composition, which includes sand, silt particles, and the mixture of clay in specific proportions, is vital for making informed decisions about crop selection and managing weed growth. Furthermore, soil pollution from emerging contaminants presents a substantial risk to water resource management and food production.

Deep learning infused SIRVD model for COVID-19 prediction: XGBoost-SIRVD-LSTM approach.

The global impact of the ongoing COVID-19 pandemic, while somewhat contained, remains a critical challenge that has tested the resilience of humanity. Accurate and timely prediction of COVID-19 transmission dynamics and future trends is essential for informed decision-making in public health. Deep learning and mathematical models have emerged as promising tools, yet concerns regarding accuracy persist.

Evaluation of zirconia ceramics fabricated through DLP 3d printing process for dental applications.

Zirconia ceramics are versatile materials with remarkable properties such as a high thermal resistance, high fracture strength, and low thermal conductivity. They are chemically inert and highly wear- and corrosion-resistant, making them ideal for a wide range of applications in the aerospace, automotive, and biomedical fields. In dentistry, zirconia ceramics are used for veneers, crowns, bridges, and implants because of their biocompatibility.

HPA-UNet: A Hybrid Post-Processing Attention U-Net for Tongue Segmentation.

Tongue diagnosis is the kernel method of Traditional Chinese Medicine (TCM), and it has been proved that the condition of the tongue can serve as an indicator of a person's health status. To automatically recognize a person's latent diseases by computer vision technology, getting the tongue segmentation from a picture with high precision has significant importance. However, the precision of tongue segmentation images in most prior methods is not satisfactory, which will inevitably result in misjudging.

A comprehensive review of navigation systems for visually impaired individuals.

Background: This review explores the evolutionary trajectory of navigation assistance tools tailored for the visually impaired, spanning from traditional aids like white canes to contemporary electronic devices. It underlines their pivotal role in fostering safe mobility for visually impaired individuals.

Objectives: The primary aim is to categorize and assess the plethora of navigation assistance solutions available.

Assessment of consolidative multi-criteria decision making (C-MCDM) algorithms for optimal mapping of polymer materials in additive manufacturing: A case study of orthotic application.

Objective: The objectives of this research are twofold. The primary goal is to introduce, investigate, and contrast consolidative multi-criteria decision-making (C-MCDM) approaches. The second objective is the investigation of five alternative additive manufacturing materials.

EEGDepressionNet: A Novel Self Attention-Based Gated DenseNet With Hybrid Heuristic Adopted Mental Depression Detection Model Using EEG Signals.

World Health Organization (WHO) has identified depression as a significant contributor to global disability, creating a complex thread in both public and private health. Electroencephalogram (EEG) can accurately reveal the working condition of the human brain, and it is considered an effective tool for analyzing depression. However, manual depression detection using EEG signals is time-consuming and tedious.

Fault Classification for Cooling System of Hydraulic Machinery Using AI.

Hydraulic systems are used in all kinds of industries. Mills, manufacturing, robotics, and Ports require the use of Hydraulic Equipment. Many industries prefer to use hydraulic systems due to their numerous advantages over electrical and mechanical systems.

Effect of Traverse Speed Variation on Microstructural Properties and Corrosion Behavior of Friction Stir Welded WE43 Mg Alloy Joints.

The growing demand for Magnesium in the automotive and aviation industries has enticed the need to improve its corrosive properties. In this study, the WE43 magnesium alloys were friction stir welded (FSW) by varying the traverse speed. FSW eliminates defects such as liquefication cracking, expulsion, and voids in joints encountered frequently in fusion welding of magnesium alloys.

Material Extrusion of Multi-Polymer Structures Utilizing Design and Shrinkage Behaviors: A Design of Experiment Study.

Material extrusion (ME) is an additive manufacturing technique capable of producing functional parts, and its use in multi-material fabrication requires further exploration and expansion. The effectiveness of material bonding is one of the main challenges in multi-material fabrication using ME due to its processing capabilities. Various procedures for improving the adherence of multi-material ME parts have been explored, such as the use of adhesives or the post-processing of parts.

Modeling Consequences of COVID-19 and Assessing Its Epidemiological Parameters: A System Dynamics Approach.

In 2020, coronavirus (COVID-19) was declared a global pandemic and it remains prevalent today. A necessity to model the transmission of the virus has emerged as a result of COVID-19's exceedingly contagious characteristics and its rapid propagation throughout the world. Assessing the incidence of infection could enable policymakers to identify measures to halt the pandemic and gauge the required capacity of healthcare centers.

Self-Propelled Rotary Tools in Hard Turning: Analysis and Optimization via Finite Element Models.

This study investigates self-propelled rotary tool (SPRT) performance in hard turning using 3D finite element (FE) models. The FE models developed in this study are based on coupled temperature-displacement analysis using an explicit time-integration scheme. The developed FE models can predict chip morphology, cutting forces, tool and workpiece stresses and temperatures.

Parametric Study and Optimization of End-Milling Operation of AISI 1522H Steel Using Definitive Screening Design and Multi-Criteria Decision-Making Approach.

End-milling operation of steel grade material is a challenging task as it is hard-to-cut material. Proper selection of cutting tools, cutting conditions, and cutting process parameters is important to improve productivity, surface quality, and tool life. Therefore, the present study investigated the end-milling operation of AISI 1522H steel grade under minimum-quantity lubrication (MQL) conditions using a novel blend of vegetable oils, namely canola and olive oil.

Tool Wear Prediction When Machining with Self-Propelled Rotary Tools.

The performance of a self-propelled rotary carbide tool when cutting hardened steel is evaluated in this study. Although various models for evaluating tool wear in traditional (fixed) tools have been introduced and deployed, there have been no efforts in the existing literature to predict the progression of tool wear while employing self-propelled rotary tools. The work-tool geometric relationship and the empirical function are used to build a flank wear model for self-propelled rotary cutting tools.

Friction Stir Welding of Thick Plates of 4Y3Gd Mg Alloy: An Investigation of Microstructure and Mechanical Properties.

Applications of non-ferrous light metal alloys are especially popular in the field of aerospace. Hence it is important to investigate their properties in joining processes such as welding. Solid state joining process such as friction stir welding (FSW) is quite efficient for joining non-ferrous alloys, but with thick plates, challenges increase.

Multi-Response Optimization of Processing Parameters for Micro-Pockets on Alumina Bioceramic Using Rotary Ultrasonic Machining.

The machining of ceramic materials is challenging and often impossible to realize with conventional machining tools. In various manufacturing applications, rotary ultrasonic milling (RUM) shows strengths, in particular for the development of high-quality micro-features in ceramic materials. The main variables that influence the performance and price of the product are surface roughness, edge chipping (EC), and material removal rate (MRR) during the processing of ceramics.

Evaluation of Self-Propelled Rotary Tool in the Machining of Hardened Steel Using Finite Element Models.

This paper presents a model for assessing the performance of self-propelled rotary tool during the processing of hardened steel. A finite element (FE) model has been proposed in this analysis to study the hard turning of AISI 51200 hardened steel using a self-propelled rotary cutting tool. The model is developed by utilizing the explicit coupled temperature displacement analysis in the presence of realistic boundary conditions.

On the Effects of Process Parameters and Optimization of Interlaminate Bond Strength in 3D Printed ABS/CF-PLA Composite.

The scope of additive manufacturing, particularly fused deposition modelling (FDM), can indeed be explored with the fabrication of multi-material composite laminates using this technology. Laminar composite structures made up of two distinct materials, namely acrylonitrile butadiene styrene (ABS) and carbon fiber reinforced polylactic acid (CF-PLA), were produced using the FDM process. The current study analyzes the effect of various printing parameters on the interfacial bond strength (IFBS) of the ABS/CF-PLA laminar composite by employing response surface methodology.

Investigation on Effect of Strain Rate and Heat Generation on Traverse Force in FSW of Dissimilar Aerospace Grade Aluminium Alloys.

The emergence of the aerospace sector requires efficient joining of aerospace grade aluminium alloys. For large-scale industrial practices, achievement of optimum friction stir welding (FSW) parameters is chiefly aimed at obtaining maximum strain rate in deforming material with least application of traverse force on the tool pin. Exact computation of strain rate is not possible due to complex and unexposed material flow kinematics.

Preparation of letrozole dispersed pHEMA/AAm-g-LDPE drug release system: In-vitro release kinetics for the treatment of endometriosis.

This paper focuses on the development of a drug delivery system for systemically controlled release of a poorly soluble drug, letrozole. The work meticulously describes the preparation and characterizations of 2-hydroxyethyl methacrylate (HEMA) polymerization onto hydrophilic acrylamide grafted low-density polyethylene (AAm-g-LDPE) surface for targeted drug release system. The surface morphology and thickness measurement of coated pHEMA layer were measured using scanning electron microscopy (SEM).

Advanced Electric Discharge Machining of Stainless Steels: Assessment of the State of the Art, Gaps and Future Prospect.

Electric discharge machining (EDM) is a material removal process that is especially useful for difficult-to-cut materials with complex shapes and is widely used in aerospace, automotive, surgical tools among other fields. EDM is one of the most efficient manufacturing processes and is used to achieve highly accurate production. It is a non-contact thermal energy process used to machine electrically conductive components irrespective of the material's mechanical properties.

A systematic approach to parameter selection for CAD-virtual reality data translation using response surface methodology and MOGA-II.

Advanced graphics capabilities have enabled the use of virtual reality as an efficient design technique. The integration of virtual reality in the design phase still faces impediment because of issues linked to the integration of CAD and virtual reality software. A set of empirical tests using the selected conversion parameters was found to yield properly represented virtual reality models.

Assistive technologies for hearing, and speaking impaired people: a survey.

This study presents a novel method for evaluating the scientific research papers in the field of assistive technologies pertaining to different impairment conditions. The objectives are to understand the technologies used for addressing the needs of PWD by identifying relevant criteria for the assessment, explore the implications of these technologies in their lives and identify the gaps among certain technologies in assisting PWD. In this article, we reviewed around 40 research scientific papers in relation to the technologies used to assist PWD in their daily activities.