In recent years, many context-sensitive approaches have been established to offer physiological information about the wellness of each person. While the patient's health is being monitored, there are delays in the cloud data transfer. To overcome these delays, a Deep Convolutional Spike Neural Network (DCSNN) with a Woodpecker Mating Algorithm (WMA) is proposed in this manuscript for monitoring the healthcare data in the Internet of Things (IoT)-based context-aware architecture (DCSNN-WMA-HCM-IoT-CAA). Here, the input data are amassed from real-time datasets. Then the data are supplied to the pre-processing. The pre-processing data involve the assortment phase, data storage phase, and data redundancy phase. In the redundancy phase, the Kernel co-relation method is employed to remove the repeated data. The pre-processing output is given to the feature extraction. The feature is extracted under the fast discrete Curvelet transform method. After that, the extracted features are given to DCSNN optimized with WMA to classify regular, irregular, and critical conditions of the patient. The proposed DCSNN-WMA-HCM-IoT-CAA method is activated in OMNeT++. The proposed DCSNN-WMA-HCM-IoT-CAA approach attains 4.08%, 8.17%, 9.32%, and 5.17% high accuracy, 14.3%, 15.4%, 19.51%, and 27.81% lower computation Time and 12.29%, 15.36%, 11.55%, and 13.91% higher AUC compared with existing methods.

The healthcare sector is being swiftly transformed by IoT thanks to the proliferation of innovative models in health care industry. We have proposed V-Doctor module which monitors patient health by various sensors. We used arduino and sensors for monitoring pulse and temperature to identify various disorders in human health. This IoT gadget could check the temperature and read the heart rate. It updates the ambient temperature and pulse rate to an IoT platform on an ongoing basis, Proposed V-doctor module effectively identifies human disorders based on pulse and temperature.

In this article, a novel technique has been developed to measure the flank wear in turning nickel based super alloy Nimonic C263. The MSER (maximally stable extremal regions) and deep pattern network (DPN) has been applied on the worn out insert for the measurement of flank wear. The combination of MSER algorithm along with DPN is termed out as FlankNet in this article. The flank wear measured by tool maker’s microscope was compared with the values measured by FlankNet and the average percentage error of 3.03% was noted. As the Nimonic C263 is highly difficult-to-machine materials owing to high work hardening tendency and lower thermal conductivity, rapid tool wear was found and it would affect the dimensional and geometrical accuracy of machined parts. Therefore, the influences of the machining parameters on tool wear were also studied. The experimental trails were conducted based on L9 orthogonal array.

In this paper, a hybrid method is proposed to achieve an effective control of the speed of the BLDC motor with the established specifications. The proposed hybrid system is the joined execution of Radial Basis Function Neural Network (RBFNN) and Student psychology optimization algorithm (SPOA) and hence it is named as RBFNN-SPOA strategy. The RBFNN is trained and processed first, then that output is given to the SPOA approach, which drives the BLDC motor. The proposed RBFNN-SPOA approach is tune the parameter of PID controller, through which the speed regulation process of motor is achieved. Based on the load variation and the variation of input, the proposed approach is analyzed. The best gain parameter of the PID controller is utilized to control the speed of the motor. The proposed approach is considering the constraints, which are utilized to obtain the objective of the system. The factors like rise time, peak time, peak overshoot, settling time and steady-state error is assessed using the proposed approach. By then, the performance of the proposed method is executed on MATLAB platform and compared with existing methods. The proposed method Peak overshoot, Peak undershoot value becomes 9.67 rpm and 2.05 rpm. The settling time of proposed approach is 0.009 s. The steady state error at speed and steady state error percentage of proposed approach is 0.25 rpm, 0.008 rpm; it is less than the existing approach under no load condition.

When driving at night, especially when traveling long distances, being drowsy is a major cause of accidents in vehicles. Sleep deprivation affects persons who work in the transportation industry, such as taxi drivers, bus drivers, truck drivers, and people who travel great distances. To avoid this, driving when feeling drowsy becomes quite difficult. According to several studies, weariness contributes to approximately 20% of all traffic accidents, with the figure reaching up to 50% on some highways. The drowsiness detection system was proposed to detect the drowsiness of the driver and to alert the human by alarming the driver as well as send alert messages to their respective people (e.g., family members, car owner, manager of a specific travel company) about the presence of drowsiness is demonstrated in this work. The blinking behavior of the eyes is the essential visual indicator for identifying tiredness because it reflects the driver’s condition the most accurately. The device performs satisfactorily in natural lighting situations, regardless of whether the driver is using driving accouterments such as glasses, hearing aids, or a cap. This idea was developed in response to a high number of traffic incidents involving drivers who had fallen asleep at the wheel. It is intended to avoid these mishaps by using a rigid system that is convenient and does not require the purchase of specialized gadgets. The approach is successful in detecting drowsiness in 93.37 percent of cases. Our team used a camera with Open CV (computer vision) techniques to determine and observe the driver’s blinking habit. Computer vision techniques have been used to construct a non-intrusive driver sleepiness monitoring system, which is included in the proposed method. Drowsiness will be detected by the system within two to three seconds, depending on the system configuration.

The composite technology is a gate way of invention of new materials with desirable properties. Synthesize of Copper Metal Matrix Composite (CMMC) is focused in this paper. The copper is reinforced with tungsten carbide and groundnut shell ash. The composite matrix of 80% of copper powder (Cu), 15% Tungsten Carbide Powder (WC) and 5% of Ash of Groundnut shell (GSA) preferred in which copper is matrix material. The composite manufactured by powder metallurgy technology. The proposed composite investigated by microscopy analysis, corrosive analysis and hardness analysis. The reinforcement of proposed proportion of 15% Tungsten Carbide Powder and 5% of Ash of Groundnut shell, improved hardness and reduced corrosion rate (increased corrosive resistance). The Scanning Electron Microscopy image ensures uniform distribution of reinforced particles in the matrix material. The control specimen made with only copper powder by same method of manufacturing and testing also to expose the effects of reinforcement.

Axial Flow pumps are elected based on the system requirements. Conventional design process takes a lot of time of the designer in calculations. Only experienced designers can do the design process successfully and produce required drawings accurately. In this competitive world, frequent changes in design are needed and also tailored according to customer requirements. The time taken for the design process should be reduced. This is very difficult to achieve in case of manual calculation process. The present work attempts to automate the design process of axial flow pump using computer aided design. The computer aided design tool was based on a Visual Basic program for hydraulic design calculations. The Hydraulic design of the impeller blade is based on Aerodynamic method. Mechanical design of the shaft was done and the diameter was found out using static analysis. The 3D model of the impeller was generated in Solidworks and imported into ANSYS environment with a view to do dynamic analysis. The 3D model of shaft and supporting elements such as bearing, coupling and hub was generated in ANSYS and dynamic analysis on this model was carried out for the design speed and stress values are found out at various sections of impeller. The analysis was also carried out for various speeds of the shaft and is finalized when the stress concentrations are minimum at all the sections. A procedure was developed starting with hydraulic design and completing with mechanical design of pump elements. Also a comparative study was carried out for various materials of the impeller such as brass, bronze and steel.

Manufacturing and utilizing biodiesel for transportation is one approach for sustainable energy future for the world. The opportunity to take place of cleaner burning biodiesel fuels for automotive service has drawn increasing attention during the last decade. A biodiesel fuel contributes lesser global climate change. In a dual fuel engine a main fuel that is generally gaseous fuel is mixed with air, compressed and ignited by a small quantity of pilot spray of diesel as in a diesel engine. Dual fuel engines are capable of generating as much power when running with a gaseous fuel as a primary fuel as when operating liquid fuel only. LPG (Liquefied Petroleum Gas) has been widely used as an alternative fuel for petrol and diesel vehicles in light of clean fuel and multiplicity of energy resources. The phenomenon of knock in a dual-fuel engine is the nature of auto ignition of gaseous mixture in the neighbourhood of injected spray. In this paper, using of liquefied petroleum gas (LPG) as a primary fuel with diethyl ether (DEE) as an ignition enhancer in a direct injection diesel engine. The performance and emission characteristics of the LPG– diesel dual-fuel engine performance, emission characteristics are studied and the dual fuel diesel engine results are compared and analysed.

In global scenario rapid advancements in engineering and technology reflects in core mechanical engineering and automotive sector viz automobile and aeronautical engineering. Various researchers are working on smart materials, nano materials and composites materials for aeromechanical applications through sustainable manufacturing. Now a day’s light weight high strength, functional materials are manufactured using micro and nano-machining through computer integrated manufacturing. Advancements of computer interfaced tool are quite common in day to day life in the field of design, simulation and analysis. In the area of computational study, the governing equations are used in FEM and FEA to determine the feasibility of CAE model. For optimizing the combustion chamber geometries, CAE provides the most suitable tool. This research paper encompasses the simulation technique in different combustion chamber geometries with three different cavities on the piston land. The appropriate boundary conditions were constrained in the corresponding numeric model and the combustion simulations were solved using 3D Navier-Stokes equation. The NS solver discretized the FE model into FVM, coupled with species transport equations. The engine combustion parameters peak cylinder pressure of 110 bar, maximum temperature of 1075 K, emission particulates 12.4 PPM NOx and 0.000335 % CO were predicted in the elliptical bowl type of piston using Finite Element Method.

In the biotic world for human life next to basic needs, water plays a vital role for human survival and sustainability. Water is available in plenty, in our earth which covers 70 percent of the surface area. In that, nearly 98 percent of water in ocean, seas and rivers only. Less than 2 percent of water is used for all sort of human needs. Many rivers originated from the mountains crosses various types of terrains and finally reaching the sea. Between the start and end, the water stream possesses huge level of potential and kinetic energy. Many of our power engineers was not attracted towards these natural penstock in form of water streams which can be able to operate mini and micro hydro power plants. In north and north-eastern areas of India, particularly in Himalayan range more than 6000 water streams are available, where large scale of hydro power project are not feasible. But the mini and micro level hydro power plants are possible. The success of any project is incorporated with the cost, in the way the hydraulic turbine cost also too high. In this perception this research paper an ordinary centrifugal pump was modified into the hydraulic turbine. This Pump-as-turbine (PAT) was studied experimentally and the numerical model was simulated and compared. The efficacy of PAT was 33.52% with the head and discharge of 40 m and 45.40 Kg/s respectively. For the same head the PAT numerical model predicts the efficacy of 44.87%.