Search results

Indoor air quality monitoring is extremely important in urban, industrial areas. Considering the devastating effect of declining quality of air in major part of the countries like India and China, it is highly recommended to monitor the quality of air which can help people with respiratory diseases, children and elderly people to take necessary precautions and stay safe at their homes. The purpose of this study is to detect air quality and perform predictions which could be part of smart home automation with the use of newer technology.

This study proposes an Internet-of-Things (IoT)-based air quality measurement, warning and prediction system for ambient assisted living. The proposed ambient assisted living system consists of low-cost air quality sensors and ESP32 controller with new generation embedded system architecture. It can detect Indoor Air Quality parameters like CO, PM2.5, NO2, O3, NH3, temperature, pressure, humidity, etc. The low cost sensor data are calibrated using machine learning techniques for performance improvement. The system has a novel prediction model, multiheaded convolutional neural networks-gated recurrent unit which can detect next hour pollution concentration. The model uses a transfer learning (TL) approach for prediction when the system is new and less data available for prediction. Any neighboring site data can be used to transfer knowledge for early predictions for the new system. It can have a mobile-based application which can send warning notifications to users if the Indoor Air Quality parameters exceed the specified threshold values. This is all required to take necessary measures against bad air quality.

The IoT-based system has implemented the TL framework, and the results of this study showed that the system works efficiently with performance improvement of 55.42% in RMSE scores for prediction at new target system with insufficient data.

This study demonstrates the implementation of an IoT system which uses low-cost sensors and deep learning model for predicting pollution concentration. The system is tackling the issues of the low-cost sensors for better performance. The novel approach of pretrained models and TL work very well at the new system having data insufficiency issues. This study contributes significantly with the usage of low-cost sensors, open-source advanced technology and performance improvement in prediction ability at new systems. Experimental results and findings are disclosed in this study. This will help install multiple new cost-effective monitoring stations in smart city for pollution forecasting.

Material extrusion (MEX) 3D printers suffer from an intrinsic limitation of small size of the prints due to its restricted bed dimension. On the other hand, friction stir spot welding (FSSW) is gaining wide interest from automobile, airplane, off-road equipment manufacturers and even consumer electronics. This paper aims to explore the possibility of FSSW on Acrylonitrile Butadiene Styrene/Polylactic acid 3D-printed components to overcome the bed size limitation of MEX 3D printers.

Four different tool geometries (tapered cylindrical pin with/without concavity, pinless with/without concavity) were used to produce the joints. Three critical process parameters related to FSSW (tool rotational speed, plunge depth and dwell time) and two related to 3D printing (material combination and infill percentages) were investigated and optimized using the Taguchi L27 design of experiments. The influence of each welding parameter on the shear strength was evaluated by analysis of variance.

Results revealed that the infill percentage, a 3D printing parameter, had the maximum effect on the joint strength. The joints displayed pull nugget, cross nugget and substrate failure morphologies. The outcome resulted in the joint efficiency reaching up to 100.3%, better than that obtained by other competitive processes for 3D-printed thermoplastics. The results, when applied to weld a UAV wing, showed good strength and integrity. Further, grafting the joints with nylon micro-particles was also investigated, resulting in a detrimental effect on the strength.

To the best of the authors’ knowledge, this is the first study to demonstrate that the welding of dissimilar 3D-printed thermoplastics with/without microparticles is possible by FSSW, whilst the process parameters have a considerable consequence on the bond strength.

This paper aims to focus on the application of multi-attribute decision-making methods (MADMs) to ascertain the optimal machining parameters while turning Ti-6Al-4V alloy under minimum quantity lubrication (MQL) conditions using Jatropha-curcas oil (JCO) bio-based lubricant.

The experiments were designed and performed using Taguchi L27 design of experiments methodology. A total of 27 experiments were performed under MQL conditions using textured carbide cutting tools on which different MADMs like Analytic hierarchy process (AHP), Technique for order preference by similarity to ideal solution (TOPSIS) and Simple additive weighting (SAW) were implemented in an empirical manner to extract optimize machining parameters for turning of Ti-6Al-4V alloy under set of constrained conditions.

The results evaluated through MADMs exhibit the optimized set of machining parameters (cutting speed V_c = 80 m/min, feed rate f = 0.05 mm/rev. and depth of cut a_p = 0.10 mm) for minimizing the average surface roughness (Ra), maximum flank wear (Vbmax), tangential cutting force (Fc) and cutting temperature (T). Further, analysis of variance (ANOVA) and traditional desirability function approach was applied and results of TOPSIS and SAW methods having optimal setting of parameters were compared as well as confirmation experiments were conducted to verify the results. A SEM analysis at lowest and highest cutting speeds was performed to investigate the tool wear patterns. At the highest speed, large cutting temperature generated, thereby resulted in chipping as well as notching and fracturing of the textured insert.

The research paper attempted in exploring the optimized machining parameters during turning of difficult-to-cut titanium alloy (Ti-6AL-4V) with textured carbide cutting tool under MQL environment through combined approach of MADMs techniques. Ti-6Al-4V alloy has been extensively used in important aerospace components like fuselage, hydraulic tubing, bulk head, wing spar, landing gear, as well as bio-medical applications.

This study aims to explore the effect of mental health in terms of depression, anxiety, stress, fear of COVID-19 and quality of life (QoL) on the reluctance to be vaccinated in a population of Palestinian adults living in occupied Palestinian territories and Israel.

The authors recruited 1,122 Palestinian adults who consented to participate in the study; 722 were females, and the mean age of the sample was 40.83 (SD 8.8). Depression, anxiety, and stress scale (DASS), World Health Organization QoL-BREF, FCov-19 and reluctance to the vaccine scale were administered; hierarchical regression analysis was applied to test vaccine reluctance as a dependent variable, and mental health, fear of COVID-19 and QoL as independent variables. This study hypothesized influence of such variables on the vaccine choice with differences due to the participants’ geographical locations.

Findings showed an effect of mental health, particularly depression, QoL and fear of COVID on vaccine reluctance, with depression and fear of COVID in the West Bank and Gaza, while in Israel, QoL played a role in vaccination choices.

The future needs to be comprehended more thoroughly to discover mutations and fluctuations over time in vaccine hesitancy and the increasing role of psychological distress, diminished QoL and fear of Covid-19. Online recruitment might not have allowed the study to include the most disadvantaged strips of the Palestinian population.

Human rights perspectives must be considered in public health and public mental health policies to ensure the QoL and well-being for the Palestinian population during and following the pandemic.

The crumbling of the Palestinian health-care system exacerbated the sense of dread among the population and made them less likely to vaccinate. The pandemic-like spread of Covid-19 prompts a plea for the global community to actively advocate for the urgent re-establishment of equity, autonomy and durability of the medical infrastructure in the occupied territories and equal entitlements for the Palestinians in Israel.

The results demonstrated the importance for public mental health to consider the multiple levels implied in the vaccine refusal in Palestine and Israel among the Palestinian population.