High sour natural gas dehydration treatment through low temperature technique: Process simulation, modeling and optimization.

Among the various fossil fuels, natural gas is a clean fuel because it has a less adverse impact on the environment compared to other energy sources. Natural gas emits less hazardous gases and less CO upon burning. Water, CO, N, HS, and other contaminants could be present in raw natural gas, depending on its geographic location.

Segmentation and Classification of Encephalon Tumor by Applying Improved Fast and Robust FCM Algorithm with PSO-Based ELM Technique.

Nowadays, so many people are living in world. If so many people are living, then the diseases are also increasing day by day due to adulterated and chemical content food. The people may suffer either from a small disease such as cold and cough or from a big disease such as cancer.

Thermal Aspects in Edge Trimming of Bio-Filled GFRP: Influence of Fiber Orientation and Silica Sand Filler in Heat Generation.

The present work aims to determine the influence of Glass Fiber-Reinforced Polymer (GFRP) laminating configuration in heat generation during the dry edge trimming process. Temperature measurement experiments were conducted on pure epoxy matrix, 15% unidirectional glass fiber reinforced epoxy, and 28% silica sand-filled GFRP specimens through eight type-K thermocouples evenly distributed along the trim plans and connected to a data acquisition system. Infrared thermographic measurements were also conducted to investigate the tool temperature evolution while processing.

Éclaircissement to Understand Consumers' Decision-Making Psyche and Gender Effects, a Fuzzy Set Qualitative Comparative Analysis.

Consumers' decision-making is complex and diverse in terms of gender. Different social, psychological, and economic factors mold the decision-making preferences of consumers. Most researchers used a variance-based approach to explain consumer decision-making that assumes symmetric relationship between variables.

Multi-objective optimization of thermophysical properties of multiwalled carbon nanotubes based nanofluids.

The experimental determination of thermophysical properties of nanofluid (NF) is time-consuming and costly, leading to the use of soft computing methods such as response surface methodology (RSM) and artificial neural network (ANN) to estimate these properties. The present study involves modelling and optimization of thermal conductivity and viscosity of NF, which comprises multi-walled carbon nanotubes (MWCNTs) and thermal oil. The modelling is performed to predict the thermal conductivity and viscosity of NF by using Response Surface Methodology (RSM) and Artificial Neural Network (ANN).

Investigation of Coatings, Corrosion and Wear Characteristics of Machined Biomaterials through Hydroxyapatite Mixed-EDM Process: A Review.

Together, 316L steel, magnesium-alloy, Ni-Ti, titanium-alloy, and cobalt-alloy are commonly employed biomaterials for biomedical applications due to their excellent mechanical characteristics and resistance to corrosion, even though at times they can be incompatible with the body. This is attributed to their poor biofunction, whereby they tend to release contaminants from their attenuated surfaces. Coating of the surface is therefore required to mitigate the release of contaminants.

Predictive Modelling and Multi-Objective Optimization of Surface Integrity Parameters in Sustainable Machining Processes of Magnesium Alloy.

Magnesium alloys are widely used in numerous engineering applications owing to their superior structural characteristics. However, the machining of magnesium alloy is challenging because of its poor machinability characteristics. Therefore, this paper investigates the machining of magnesium alloys under different sustainable cooling conditions.

Future Forecasting of COVID-19: A Supervised Learning Approach.

A little over a year after the official announcement from the WHO, the COVID-19 pandemic has led to dramatic consequences globally. Today, millions of doses of vaccines have already been administered in several countries. However, the positive effect of these vaccines will probably be seen later than expected.

An IoT Framework for Screening of COVID-19 Using Real-Time Data from Wearable Sensors.

Experts have predicted that COVID-19 may prevail for many months or even years before it can be completely eliminated. A major problem in its cure is its early screening and detection, which will decide on its treatment. Due to the fast contactless spreading of the virus, its screening is unusually difficult.

A Pneumonia Diagnosis Scheme Based on Hybrid Features Extracted from Chest Radiographs Using an Ensemble Learning Algorithm.

Pneumonia is a fatal disease responsible for almost one in five child deaths worldwide. Many developing countries have high mortality rates due to pneumonia because of the unavailability of proper and timely diagnostic measures. Using machine learning-based diagnosis methods can help to detect the disease early and in less time and cost.