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Today, researchers are exploring natural fillers as alternatives to synthetic options in composite materials, driven by the need for renewability, eco-friendliness, affordability, and safety. This exploration aims to propose novel composite materials reinforced with natural fillers. The principal aim of this investigation was to thoroughly examine the properties of the novel ABSF as a feasible substitute filler for polymer composites, and the experimental findings indicate the feasibility of manufacturing polymer composites with ABSF as a reinforcement. Consequently, in this study, agricultural by-products of alkali-treated baheda seed filler-reinforced polyester composites were manufactured through compression molding, with differing levels of fiber weight between 9% and 18%. The specimens made of ABSF-P material had their mechanical characteristics inspected, revealing optimal characteristics in specimens with a 15 wt. % filler content. Tensile strength (TS), flexural strength (FS), and impact strength (IS) were optimal at approximately 27.4 MPa, 131.11 MPa and 59.33 kJ/m2, respectively. The combined outcomes validate these specimens' applicability for various lightweight tasks. [ABSTRACT FROM AUTHOR]

Cardiovascular disease (CVD) has been one of the main causes of death for people over the past ten years. Patients' chances of being cured of their illness and their impermanence will both rise with early diagnosis. Modern medical practises extensively use machine learning algorithms because they consistently produce reliable findings that save time and potentially lives. Machine learning models are particularly trained using different datasets to improve accuracy. Our main goal in this paper is to introduce the National Health and Nutrition Examination Survey (NHANES) dataset with two important regularization techniques, LASSO (Lease Absolute Shrinkage and Selection Operator) and Elastic Net and compare the results. We use convolutional neural network (CNN) and Multi-Layer Perceptron Classifier as classification models and individually introduce the regularization techniques and analyse the results. Through further analysis, it was found that LASSO performs better than Elastic Net due to LASSO favouring subsets of features with less collinearity. [ABSTRACT FROM AUTHOR]

Electronic currency usage is growing along with the size of the e-commerce industry. The easiest and most practical method of payment is using a credit card. It is simple to operate and minimizes human effort. Yet, certain problemsgo hand in hand with some positives. Many frauds occur during transactional processes, causing several people to lose millions of dollars. Hence, a detection system is required so that consumers can conduct transactions without being concerned about fraud. Several technologies are available now that can be used to create such a system. "Neural Network, Artificial Intelligence, Bayesian Network, Data Mining, Artificial Immune System, K-Nearest Neighbor Algorithm, Decision Tree, Fuzzy Logic Based System, Support Vector Machine, Machine Learning, Genetic Programming, etc." are some examples of technologies. This article will comprise a number of surveys that will be carried out in which individualswill use various ways to create a solid system. The project's secondary goal is to create a robust detection system using python modules such as NumPy, sklearn, and others. By utilizing the problem is solved with a classifier that can discriminate between fraudulent and valid transactions based on the class and time. The dataset comprises 31 columns, of which 28 have the v1, v2, and v3 designations. Time and money are separated into two columns for security reasons. The total number of transactions was 283.806, of which only 492 were fraud cases. There are credit cards available nowadays for people under the age of 18 as well. It is crucial tocreate a system for safety as a result. The money can also be used by scammers for a variety of illicit activities. In this study, the dataset will be tested using a Decision Tree with a Random Forest Classifier. Some cardholders from Europe areincluded in the dataset. [ABSTRACT FROM AUTHOR]

Every year, electrical shock causes hundreds of workers to become handicapped or perhaps die. It is not the voltage but the amount of current flowing through the body that causes damage or death. When electricity becomes snagged, it may cause electric shocks, which can hurt or even kill people. In India, 8% of industry fatalities are attributable to electrocution, while 42% of all fires are electrical in nature. When a body component is brought into contact with conductors or a ground source, a full circuit is made, and electrical shock may occur. Every year, families and businesses suffer property damage worth more than 12,306 crores due to electrical accidents. We have improved the solution to this issue in our project. In the case of an accident or electric shock, the suggested method may protect users. Accidents involving electric shocks are prevalent when it comes to youngsters playing near household electrical outlets. Even though these outlets have appropriate safety features, they don't work during the day since proximity sensors are employed. This kind of motion sensor uses both infrared and ambient light to detect movements. Even if it's quite bright throughout the day, they aren't sensitive enough to distinguish between natural and arti ficial light. For better dependability, avoid using infrared or photoreceptor proximity sensors. The Internet of Things allows for the retrieval of exact location and time data, as well as the storage of electric shock data for future reference. This approach has the potential to save lives by detecting electric shocks and preventing accidents at home or in the office. [ABSTRACT FROM AUTHOR]

In this experimental research, during CNC turning of LDX2205 duplex stainless steel, the functionality of TiC coated tool and uncoated cemented carbide tool is compared, and a detailed search of the surface roughness (SR) obtained from both tools is accomplished. Materials and Methods: Cemented carbide tools with no need for a layer were in the control group and TiC-coated elements were in the experimental group. In this experiment, LDX2205 steel was used as the workpiece. Using factors such as speed of cutting, rate of feed and cut depth, 27 samples machined in a CNC turning machine based on sample size calculation done using G-power calculator. Result: During the comparison of TiC insert with the uncoated insert, the mean surface roughness value of TiC insert was 0.85330 µm and the mean value for uncoated insert was 1.05078 µm. Lower than the desired value of 0.05, the obtained critical level between the control and experimental groups is 0.039. Conclusion: Within the conditions of this experiment, the TiC tool provides a superior surface finish than just uncoated tool once duplex stainless steel is CNC shaped. [ABSTRACT FROM AUTHOR]

We examine the study of chromatic number of J(G). Complement of a line graph L(G) of G is known as jump graph J(G). Chromatic number of J(G) has been the minimum cardinality about colors alloted to J(G) and is denoted by χ(J(G)). Furthermore, we also state a graph theoretic property of χ(J(G)) and provided the right values of χ(J(G)) for some standard graph of G. [ABSTRACT FROM AUTHOR]

Productivity refers to a company's or economy's ability to convert resources into goods efficiently, allowing it to produce more with fewer resources. Daily productivity is an essential activity since it raises the difficulty of generating product demand by ensuring product quality. Total failure mode effects analysis (TFMEA) and flower pollination optimization approaches are suitable for identifying the failure and rectifying it to increase the performance of the production. The work is evaluated in a gloves manufacturing company; the process is monitored with TFMEA goal setting for the reduction of failures that occurred in the manufacturing process. The performance was compared before and after the implementation of the idea on the basis with optimization techniques, and there was a significant improvement in the performance. Glove manufacturing productivity improved as a result of the intervention, and superintendents reported having a better awareness of process concerns. [ABSTRACT FROM AUTHOR]

A solid-state spot-welding technology called Friction Stir Spot Welding (FSSW) can be used as an alternative to Resistance Spot Welding (RSW). RSW has several constraints, including a high electrode wear rate, a high temperature, and a quick cooling rate, resulting in a brittle microstructure. Many industries, such as automotive and shipbuilding, require joints constructed of various metals such as aluminium and steel to reduce weight and enhance strength. Aluminium 3102 and carbon steel 1010 are friction stir spot welded (lap joint) in this project, with the aluminium at the top and the carbon steel at the bottom. The aluminium and carbon steel have 3mm thickness, 100mm length, and 30mm breadth, respectively, and are ready for welding. Consequently, the ideal set of parameters for FSSW of aluminium 3102 and carbon steel 1010 for each material must be identified. The process parameters considered in this welding are the Tool rotation speed (R), Dwell time (T), and Plunge depth (D), and the Tensile Shear Failure Load (TSFL) (in kN) of the weld is determined by a Tensile test. Each of these process variables directly influences the size of the stir zone and the mechanical properties of the weld. In this scenario, the experimental conditions for finishing the weld were developed using Central Composite Design (CCD). The microstructure and Vickers microhardness of the welded sample with the greatest TSFL is achieved, with hardness values of 147.8, 149.9, and 151.5 obtained in the Heat Affected Zone Thermo-Mechanically Affected Zone, and Stir Zone, respectively. A second-order linear regression equation must be created to establish a relationship between the process parameters. ANOVA was utilized to determine the most significant parameter and the sufficiency of the link, both of which were determined statistically. Dwell time (T) had the greatest effect on TSFL of any process component tested, with an F-value of 17.79 at the highest significance level. [ABSTRACT FROM AUTHOR]

The passenger compartment in a car is generally protected by a firewall which prevents vibration, noise and heat generated in the engine. A vehicle firewall consists of two walls. The first wall runs transversely across the vehicle. The second wall extends parallel to the first wall, completing the firewall. The material used for firewall is fiber reinforced polymer composites. In this project the vibration analysis such as modal and harmonic analysis is conducted on the double walled engine firewall. The finite element analysis (using ANSYS software) is used to conduct the analysis. The modal analysis (free vibration) is conducted to know the excitation nodes of the firewall. The harmonic analysis (forced vibration) is conducted to know the maximum amplitude and resonance frequencies. If the firewall has same excitation modes similar to that of the engine or the body of the car, the design of the firewall is changed accordingly such that the excitation modes of the firewall fall away from the excitation modes of other components to avoid the resonance. Therefore, result of the project can be obtained. The simulation is repeated for single walled & double walled firewall and for the different materials. The results are compared. [ABSTRACT FROM AUTHOR]

Development of natural Composites will play an important role for the development of undecayed greenery, which focuses at decreasing environmental threats and biological deficiencies. Natural Fibers which are renewable in nature can absorb carbon-dioxide, which is equal to their production, thus they help in sustainable development without degrading the environment. Natural fibers are the most efficient replacement for synthetic materials because they have versatile properties such as eco-friendly, bio-degradable in nature and mechanical properties such as high specific strength, toughness, light weight, low density, etc. but, the environmental and energy problems are the problems related to the synthetic fiber composites., Natural fibers have employed in many domains such as Automobile, Aircraft,furniture, construction industries etc., Whereas, Synthetic fibers hold good properties such as durability, absorption, strength, superior mechanical, thermal, and tribological properties etc., in order to get the advantages of both fibers, In this paper, decided to use renewable hybrid fiber composite of 3mm thickness modeled using Solid works and tensile strength analysis performed using ANSYS Workbench. [ABSTRACT FROM AUTHOR]

The fiber-reinforced polymer (FRP) composites have more strength to weight ratio, surface finish, less wear, etc. and it becomes a major consideration for making parts in the automotive industry. Laminated composites are known for their ease of manufacturing even as homemade. However, during assembly, when they are subjected to machining processes such as drilling, milling, etc., they usually get delaminated. The delamination may occur which is barely or not visible to our naked eye and once the delamination originates, it keeps growing by absorbing moisture from the workplace atmosphere. This progressive growth leads to the sudden failure of FRP composite parts. Hence it is very important to identify such damages well ahead of time, in order to avoid unexpected shutdowns. In this work, the vibration analysis such as modal and harmonic analysis is conducted on an automobile inlet/exhaust flange gasket which is made of FRP composite material, such as epoxy-glass nylon-glass fiber, etc. Initially, the analysis is started with an intact gasket plate, then it is continued to delaminated plates. The delamination (which is also the location of drilled hole) is made deliberately in the solid model of the gasket plate. The finite element analysis (using ANSYS software) is used to conduct the analysis. The modal analysis (free vibration) is conducted to know the excitation modes of the plates. The harmonic analysis (forced vibration) is conducted to know the maximum amplitude and resonance frequencies. The stress analysis is also conducted. The simulation is repeated for the different assumed locations of delamination and for the different materials. The results are compared between intact and delaminated gasket plates. [ABSTRACT FROM AUTHOR]

Glass Fiber Reinforced Plastics (GFRP) is considered to be an economic substitute to numerous heavy exotic materials and used in a variety of applications from aircraft to machine tools due to their light weight, high modulus, specific strength and high fracture toughness. Machining of FRP composites is a problematic task because of its unique natureand they are made very close to the final shape and any successive milling is inadequate due to surface roughness, delamination, deburring and trimming and to achieve contour shape accuracy. Delamination occurs during milling of GFRP and it's the big headache for the industries. In this paper, the optimized parameters which results in minimum delamination and a smooth surface during milling of GFRP are analyzed. The main purpose of this paper is to estimate the surface roughness and delamination of the Glass Fiber Reinforced Plastics (GFRP) using Python. [ABSTRACT FROM AUTHOR]

The present study is focused on the investigation of tribological, mechanical and microstructural properties of the Electroless Nickel Phosphorus and Cenosphere coating carried out over the shot peened EN 31. The aim of the current study is to reduce the failure and increase the life time of machining parts in terms of improving the surface and frictional properties of materials. Shot peening is a cold working process used to produce a compressive residual stress layer and modify the mechanical properties of metals to improve the fatigue strength and provide the plastic deformation. In this research shot peening process is carried out on the EN31 steel substrate followed by the Electroless NiP/Cenosphere (CN) coating to improve the corrosion and wear resistance. Electroless coating processed under various composition of cenosphere. The pin on disc wear analysis has been demonstrated over the coated specimen for various loading conditions. Vickers Micro hardness results shows that the hardness of the NiP coated specimen with 1.5grams of cenoshpere has doubled compared to the uncoated EN31 specimen. The wear and friction results shows that the substrate with 1.5gms of cenosphere has low coefficient of friction compared to other compositions. The worn surface analysis has been carried out using the optical microscope. [ABSTRACT FROM AUTHOR]

Nitride based coatings are widely used in medical applications considering their wear resistance and mechanical properties. Among these coating, chromium nitride are especially interesting because they have good tribological properties. The wear behavior of nitride coatings over SS 316L steel surface have been studied. Here, the austenitic stainless steel is coated by a thin layer of chromium nitride using Cathodic Arc Deposition (CAD) technique. The various wear mechanism have been analyzed at different process parameters such as load, time, velocity and sliding distance. The microstructure and the worn surface studies validated the incidental wear mechanism of the contact interface. [ABSTRACT FROM AUTHOR]

In the recent times, there has been an increasing demand for efficient strategies in the field of data assimilation about groundwater. Data mining process is a discovery of hiding information that utilizes the prediction efficiently by stochastic sensing concept. This paper proposes an efficient assessment of groundwater level, rainfall, population, food grains and enterprises dataset by adopting stochastic modeling and data mining approaches. Firstly, the novel data assimilation analysis is proposed to predict the groundwater level effectively. Experimental results are done and the various expected ground water level estimations indicate the sternness of the approach. [ABSTRACT FROM AUTHOR]