Hand gesture recognition with deep residual network using Semg signal.

Objectives: To design and develop a classifier, named Sewing Driving Training based Optimization-Deep Residual Network (SDTO_DRN) for hand gesture recognition.

Methods: The electrical activity of forearm muscles generates the signals that can be captured with Surface Electromyography (sEMG) sensors and includes meaningful data for decoding both muscle actions and hand movement. This research develops an efficacious scheme for hand gesture recognition using SDTO_DRN.

Printing Parameter Optimization of Additive Manufactured PLA Using Taguchi Design of Experiment.

Three-dimensional printing (3DP), known as additive layer manufacturing (ALM), is a manufacturing process in which a three-dimensional structure is constructed by successive addition of deposited layers. Fused Deposition Modeling (FDM) has evolved as the most frequently utilized ALM process because of its cost-effectiveness and ease of operation. Nevertheless, layer adhesion, delamination, and quality of the finished product remain issues associated with the FDM process parameters.

Performance Prediction of Erosive Wear of Steel for Two-Phase Flow in an Inverse U-Bend.

Erosion of the elbow due to non-Newtonian viscous slurry flows is often observed in hydrocarbon transportation pipelines. This paper intends to study the erosion behavior of double offset U-bends and 180° U-bends for two-phase (liquid-sand) flow. A numerical simulation was conducted using the Discrete Phase Model (DPM) on carbon steel pipe bends with a 40 mm diameter and an R/D ratio of 1.

Multi-Objective Welding-Parameter Optimization Using Overlaid Contour Plots and the Butterfly Optimization Algorithm.

Distortion and residual stress are two unwelcome byproducts of welding. The former diminishes the dimensional accuracy while the latter unfavorably affects the fatigue resistance of the components being joined. The present study is a multi-objective optimization aimed at minimizing both the welding-induced residual stress as well as distortion.

Influence of Elbow Angle on Erosion-Corrosion of 1018 Steel for Gas-Liquid-Solid Three Phase Flow.

Erosive wear due to the fact of sand severely affects hydrocarbon production industries and, consequently, various sectors of the mineral processing industry. In this study, the effect of the elbow geometrical configuration on the erosive wear of carbon steel for silt-water-air flow conditions were investigated using material loss analysis, surface roughness analysis, and microscopic imaging technique. Experiments were performed under the plug flow conditions in a closed flow loop at standard atmospheric pressure.

Development and Characterization of Silver-Doped Multi-Walled Carbon Nanotube Membranes for Water Purification Applications.

A unique approach was utilized to develop multi-walled carbon nanotube (MWCNT) silver (Ag) membranes. MWCNTs were impregnated with 1 wt% Ag loading, which resulted in a homogeneous dispersion of Ag in MWCNTs. MWCNTs impregnated with Ag were then uniaxially compacted at two different pressures of 80 MPa and 120 MPa to form a compact membrane.

The Property Characterization of α-Sialon/Ni Composites Synthesized by Spark Plasma Sintering.

This study investigates the effect of micron-sized nickel particle additions on the microstructural, thermal, and mechanical property changes of α-sialon ceramic composites. The α-sialon/Ni composites were synthesized with an increasing amount of Ni (10-40 wt.%) using the spark plasma sintering technique and nanosized alpha precursors at a relatively low synthesis temperature of 1500 °C with a holding time of 30 min in each case.

Cumulative effective doses from radiologic procedures for pediatric oncology patients.

Objective: Our aim was to estimate the cumulative effective doses (CEDs) from radiologic procedures for a cohort of pediatric oncology patients.

Methods: A retrospective cohort study of the imaging histories of 150 pediatric oncology patients (30 each in 5 subgroups, that is, leukemia, lymphomas, brain tumors, neuroblastomas, and assorted solid tumors) for 5 years after diagnosis was performed. All procedures involving ionizing radiation were recorded, including radiography, computed tomography (CT), nuclear medicine (NM) studies, fluoroscopy, and interventional procedures.

Imaging in pediatric patients: time to think again about surveillance.

Background: Despite concerns regarding ionizing radiation exposures from diagnostic imaging procedures in pediatric patients, many are deemed unavoidable or even mandated by treatment protocols. A prior review at our institution found patients with lymphoma had a higher median cumulative radiation exposure (191 mSv) versus other oncology subgroups (61 mSv).

Purpose: Estimations of cumulative diagnostic radiation exposures were tabulated for 5 years from the first diagnostic scan for 30 consecutive lymphoma patients diagnosed in 2001.

A comparison of methods for assessing penetrating trauma on retrospective multi-center data.

Objective: TraumaSCAN-Web (TSW) is a computerized decision support system for assessing chest and abdominal penetrating trauma which utilizes 3D geometric reasoning and a Bayesian network with subjective probabilities obtained from an expert. The goal of the present study is to determine whether a trauma risk prediction approach using a Bayesian network with a predefined structure and probabilities learned from penetrating trauma data is comparable in diagnostic accuracy to TSW.

Methods: Parameters for two Bayesian networks with expert-defined structures were learned from 637 gunshot and stab wound cases from three hospitals, and diagnostic accuracy was assessed using 10-fold cross-validation.

Knowledge-based method for building patient decision-analytic tools.

Numerous health decision aids (HDAs) have been developed to increase the participation of patients in shared decision-making, but many have limited accessibility and narrow applicability in clinical care. In the Health e-Decision project, we address these limitations in our work on building general HDAs targeted for older adults. Our approach uses a decision-support software architecture that enables principled methods for HDAs.