Teamwork Optimization with Deep Learning Based Fall Detection for IoT-Enabled Smart Healthcare System

The current advancement in cloud computing,Artificial Intelligence(AI),and the Internet of Things(IoT)transformed the traditional healthcare system into smart healthcare.Healthcare services could be enhanced by incorporating key techniques like AI and IoT.The convergence of AI and IoT provides distinct opportunities in the medical field.Fall is regarded as a primary cause of death or post-traumatic complication for the ageing population.Therefore,earlier detection of older person falls in smart homes is required to improve the survival rate of an individual or provide the necessary support.Lately,the emergence of IoT,AI,smartphones,wearables,and so on making it possible to design fall detection(FD)systems for smart home care.This article introduces a new Teamwork Optimization with Deep Learning based Fall Detection for IoT Enabled Smart Healthcare Systems(TWODLFDSHS).The TWODL-FDSHS technique’s goal is to detect fall events for a smart healthcare system.Initially,the presented TWODL-FDSHS technique exploits IoT devices for the data collection process.Next,the TWODLFDSHS technique applies the TWO with Capsule Network(CapsNet)model for feature extraction.At last,a deep random vector functional link network(DRVFLN)with an Adam optimizer is exploited for fall event detection.A wide range of simulations took place to exhibit the enhanced performance of the presentedTWODL-FDSHS technique.The experimental outcomes stated the enhancements of the TWODL-FDSHS method over other models with increased accuracy of 98.30%on the URFD dataset.

Improved Stiffness Modeling for An Exechon‑Like Parallel Kinematic Machine(PKM)and Its Application

Hole drilling or contour milling for the large and complex workpieces such as automobile panels and aircraft fuselages makes a high combined demand on machining accuracy,stiffness and workspace of machining equipment.Therefore,a 5-DOF(degrees of freedom)parallel kinematic machine(PKM)with redundant constraints is proposed.Based on the kinematics analysis of the parallel mechanism using intermediate variables,the kinematics problems of the PKM are solved through equivalent kinematics model.The structural stiffness matrix method is adopted to model the stiffness of the parallel mechanism of the PKM,where the stiffness of each joint and branch component is obtained by stiffness formula and finite element analysis.And the stiffness model of the parallel mechanism is improved by correction coefficient matrix,each element of which is constructed as a polynomial function of three independent end variables of the parallel mechanism.The terminal stiffness matrices obtained by simulation result are used to determine the coefficients of polynomial function by least square fitting to describe the correction coefficient over the workspace of the parallel mechanism quantitatively.The experiment results prove that the modification method can greatly improve the stiffness model of the parallel mechanism.To enhance the machining accuracy of the PKM,the proposed kinematics model and the improved stiffness model are utilized to optimize the working stiffness of parallel machine by searching the best relative position of parallel machine and workpiece.A plate workpiece taken as example is examined in the case study section,which demonstrates the effectiveness of optimization method.

Effects of working parameters on the performance of cyclone separator for rapeseed combine harvester based on CFD

Existing development for cyclone separation cleaning components of the rapeseed combine harvester,which employs the suspending airflow to separate the rapeseeds from the materials other than grain(MOG),has the challenge to figure out the optimal working parameters,highlighting a need for exploration of the invisible airflow based on Computational Fluid Dynamics(CFD).The airflow status was mainly affected by the air velocities of the inlet,and the outlet for the MOG.The single factor and response surface experiments were carried out.It could be found that the inlet and MOG outlet velocities affected the air velocities through the change in the air quantity.Furthermore,the mathematical model of the relationship between the air velocities inside the cyclone and the working parameters was built,and the optimal combination of working parameters was obtained by multi-objective optimization.The inlet and outlet velocities of the optimal combination were 4.25 m/s and 29.87 m/s,respectively.Under this condition,the cleaning ratio and loss ratio of the cleaning device was 94.62%and 5.39%,respectively,as validated by the field experiment.The findings provide references for the improvement of cleaning systems for rapeseed combine harvesters.

Performance test and process parameter optimization of 9FF type square bale straw crusher

In order to solve the problem of low productivity,unqualified segment length and high energy consumption during the process of crushing square bale straw caused by improper operation parameters,a 9FF square bale straw crusher was developed.In this study,by taking maize straw as the test material,the feeding speed,spindle speed of the crushing device and the state of the crushing device were taken as influence factors,and standard straw length rate,productivity per net working hour(hereinafter referred to as NWH)and energy consumption per ton of product as test indicators,the influence of the factors on the indicators were studied,and tests were carried out on the process of square bale straw crushing.By adopting the single factor test on the effect of the feeding speed,the spindle speed of the crushing device and the state of the crushing device on the test indicators,the suitable range of each factor was determined,respectively.Using the orthogonal test method,range method,variance method and comprehensive balance method,the experiment analyzed the significance of the influence of the three factors on various indicators and the order of priority.The test results showed that:the feeding speed was 5 m/min,spindle speed was 3000 r/min,and the state of the crushing device was a mixing cutter hammer,which was the best parameter combination(A1B1C1)for the processing technology of the square bale forage crusher.The standard straw length rate was 93.7%,and the productivity per NWH was 2.80 t/h,with energy consumption per ton of 4.72 kW·h/t,in which the standard straw length rate and productivity per NWH reached optimal values,and the energy consumption per ton of product was slightly higher than the optimal value in the experiment.The research results can provide a reference for the optimal design of the special crusher for square bale straw.