Conventional methods are difficult to use for machining hard materials. The non-conventional techniques like Abrasive Air Jet Machine (AAJM) are suitable for machining hard materials. The main objective is to evaluate and optimize the machining parameters of Magnesium alloy (AZ91D) / Graphene (MMC) and Glass fiber reinforced polymer (GFRP) using Abrasive air jet machine. In this study, we examined the influence of multiple process parameters on the predominant machining criteria for metal removal rate (MRR), including air pressure, stand-off distance and time. Sic particles were used as an abrasive particle during machining process. In addition to analyzing and optimizing the machining parameters of an abrasive jet machine, Taguchi's L9 is used to determine the Material Removal Rate (MRR) and the kerf taper angle (θ) during the machining process. Based on the experimental results, the machining parameters like pressure and stand of distance influenced the material removal rate.

Advances in medical imaging technology continue to create new possibilities for the collection of medical data that are important in timely and accurate diagnosis, in monitoring progress, and in the treatment of various diseases and in medical research. The capabilities of the new skills arise mainly from the technologies depicted in the vivo interior of the human body. Thus the study of the morphology and function of the various organs and the detection of any pathogens is achieved in a very direct way. The "source imaging data" provided by them is important information, but their large number is constantly growing, but their nature also creates the need for further processing with the help of computers. The primary purpose of processing images is to use denoising that includes the elimination of noise due to technical errors and feature preservation. Following noise reduction, the image segment, i.e. the location or areas of interest in an image, is the central objective of the process. In addition, usually, the complexity of the data in large volumes and charts requires a lot of time to study and a lot of experience to do their interpretation correctly. Therefore, in many cases, its automation using machine learning seeks out the partitioning process, but also categorizes images, i.e. classifying an image or parts of an image into specific categories. In most applications, machine learning performance is better than conventional techniques.

This present paper discusses the preparation and characterization of magnesium based metal matrix composite with reinforcement of graphene particles. Composites are prepared and experiments have been conducted to investigate the impact of addition of 0.5%, 1%, 1.5% graphene particles in magnesium alloy. The magnesium alloy was successfully cast by stir casting. As part of this study, hardness, tensile, impact and compression tests are conducted to assess the mechanical properties of graphene composites. To study the fracture mechanism of tensile testing by using Scanning Electron Microscopy (SEM). As a result, the addition of graphene particles increased the properties of the composite in terms of hardness, tensile strength, impact and ductility. Copyright (c) 2022 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the International Confer-ence on Advanced Materials for Innovation and Sustainability.

The abrasive air machine has been used widely to machine the hard materials and making the complex shapes. The main objective of this work is to evaluate and optimize the machining parameters of the Abrasive air jet machine. The machining parameters are air pressure, abrasive flow rate, and stand off distance. The Silicon carbide particles were used as an abrasive particle. The Taguchi’s L27 used to analyze and optimize the machining parameters of the abrasive jet machine, and used to determine Material Removal Rate (MRR) and kerf taper angle (θ) during the machining process. The experimental results revealed that the material removal rate was influenced by the machining parameters. The machining surfaces were evaluated by the scanning electron microscope.

Rationale: We have devised a score based on screen time exposure, physical activity,energy intake, sleep hours per day and family history of obesity and its relation with BMI,Obesity and Overweight in children.We have also studied early childhood risk factors and its impact on pediatric obesity.

Main focus of this research work is to analyze the impact of mechanical behaviour (hardness) and tribological behaviour (wear properties) of Graphene reinforced Magnesium alloy (AZ91D) consisting of metal matrix compound. During this analysis, 1% reinforcement found in Graphene molecules by weight to the Mg alloy (AZ91D) to generate a compound by applying the technique of bottom poured stir casting. Wear analysis technique (wear and frictional coefficient) has been incorporated on the DUCOM pin and on the setup of disc tribometer, with the utilization of metal matrix composite (MMC). For experimental designs, Taguchi’s optimization technique has been incorporated. To study the wear resistance phenomenon of the MMC, “Smaller the better” criteria have been taken into consideration as an objective model. The operating parameters like applied load (30 N, 40 N, 50 N), disc rotating time (4, 6, 8 min) and disc rotational speed (500, 650, 800 RPM) are optimized through analysis of variance (ANOVA) along with signal to noise ratio analysis. From the statistical study of ANOVA, finally, it is concluded from the observation that tribological behaviour is significantly affected by rotational time and the load applied on the disc.

Registration is a critical step in identifying the morphological disparity between the temporal and bilateral mammograms. Since the object involved is deformable in nature, deformable (non-rigid or physical) registration schemes are preferable to remove the internal geometrical distortions. The basic idea is to mimic the property of the tissue under examination before constructing the regularizer. Elastic, visco-elastic and fluid are the three important physical models found in literature. Elastic model mimics small deformation and hence cannot be applied for problems involving large deformation. Visco-elastic models and fluid models are considered as alternates. These models assume the breast to possess the properties of visco-elastic or fluid, which is contrary to the real property. After a careful and intensive literature analysis, we conclude that model mimicking breast has to be hyper elastic. Hence, we have proposed an idea called hyper-elastic image registration to match 2D mammograms. Experimentally, we tested with 89 pairs of bilateral and temporal 2D mammograms and compared with other models. We have introduced a star rating scheme for validating our results, which along with visual analysis utilizes a quantitative measure too.

Experiments have been carried out on liver and Kidneys to study the age dependent changes in alanine and aspartate aminotranserases and the influence of steroid hormones corticosterone (catabolic). testosterone (anabolic) and vitamin B6 on these changes. The rats used were of the ages between 7 to 73 weeks. It is observed that specific activity of alanine aminotransferase as well as the activity per liver increased with age. The same is true with the kidneys. Corticosterone treatment brings about two and half fold increase in activity in the liver of younger rats. whereas there is only 25% increase in the oldest group. Testosterone and vitamin B610wer this activity. the latter showed more pronounced feffect. In the case of kidneys the Changes are marginal.

BACKGROUND:Thrombotic thrombocytopenic purpura (TTP) is extremely rare. This disease and its prompt diagnosis are important because TTP in pregnancy carries a 90% mortality rate.CASE:A 21-year-old woman underwent suction dilation and curettage for molar pregnancy. Postoperatively the patient developed severe hypertension, microangiopathic anemia, thrombocytopenia and chest pain associated with ischemic cardiac changes. Despite blood and plasma transfusions and steroid therapy, the patient continued to have worsening hemolysis and thrombocytopenia. TTP was diagnosed, and plasmapheresis led to a rapid recovery.CONCLUSION:TTP can occur with molar pregnancy. Making this diagnosis in a timely manner is crucial to ensure that potentially life-saving plasmapheresis is initiated in a timely manner. To our knowledge, this is the first reported case of thrombotic thrombocytopenic purpura with molar pregnancy.

We have investigated the registration of mammograms based on the Tsallis entropy using mutual information measure. Tsallis entropy has one more parameter ‘q’ and the values of ‘q’ decide the quality of the registration. Existing Tsallis entropy based algorithms are not automatic as they claimed to be. In this article, an automatic affine image registration based on Tsallis entropy is proposed and its performance is analyzed for clinically acquired mammograms for globally registering them. The accuracy is compared with traditionally used mutual information and normalized mutual information based on Shannon entropy. Our algorithm shows promising results with increased accuracy with reduction in number of evaluations. Further, the need for pre-registration in mammogram is discussed in detail. Through this experiment, it is found that the proposed algorithm is effective enough to replace Shannon and existing Tsallis entropy based affine registration schemes.

This paper presents a new approach to enhance the contrast of microcalcifications in mammograms using a fuzzy algorithm based on Normalized Tsallis entropy. In phase I, image is fuzzified using Gaussian membership function. In Phase II, using the non-uniformity factor calculated from local information, the contrasts of microcalcifications are enhanced while suppressing the background heavily. Some of the previous works are related to Shannon entropy and Tsallis entropy. This is the first time in literature to propose an enhancement algorithm using Normalized Tsallis entropy. Normalized Tsallis entropy has an extra parameter q. Our proposed work is completely automatic and q values are selected empirically. The proposed approach improves the detection process vastly. Without Normalized Tsallis entropy enhancement, detection of MCs is meager 80.21%Tps with 8.1Fps, whereas after introduction of Normalized Tsallis entropy, the results have surged to 96.25%Tps with 0.803Fps.

This article investigates a novel automatic microcalcification detection method using a type II fuzzy index. The thresholding is performed using the Tsallis entropy characterized by another parameter 'q', which depends on the non-extensiveness of a mammogram. In previous studies, 'q' was calculated using the histogram distribution, which can lead to erroneous results when pectoral muscles are included. In this study, we have used a type II fuzzy index to find the optimal value of 'q'. The proposed approach has been tested on several mammograms. The results suggest that the proposed Tsallis entropy approach outperforms the two-dimensional non-fuzzy approach and the conventional Shannon entropy partition approach. Moreover, our thresholding technique is completely automatic, unlike the methods of previous related works. Without Tsallis entropy enhancement, detection of microcalcifications is meager: 80.21% Tps (true positives) with 8.1 Fps (false positives), whereas upon introduction of the Tsallis entropy, the results surge to 96.55% Tps with 0.4 Fps.

Among the various power quality problems, the voltage sags, are attracting a large amount of attention of researchers from industry. DVR gives the solution to the above mentioned problem. The main function of DVR is to mitigate the voltage sag. It controls voltage applied to the load by injecting voltage of compensating amplitude, frequency and phase angle to the distribution line. The DVR is primarily responsible for restoring the quality of voltage delivered to the end user when the voltage from the source is not appropriate to be used for sensitive loads. Usage of DVR enables consumers to isolate and protect themselves from transients and disturbances caused- by sags. DVR is simulated using Matlab and it is implemented using microcontroller 89C2051. The experimental results are compared with the simulation results.

This paper proposes a new segmentation approach by considering the Non extensive property of mammograms. The novel thresholding technique is performed by Tsallis entropy characterized by one more parameter q, which depends on the nonextensiveness of mammogram. Mammograms are typical examples of image with fractal-type structures (nonextensiveness).The proposed approach has been tested on 388 mammograms, and the results have demonstrated that the proposed Tsallis fuzzy approach outperforms the 2D nonfuzzy approach and traditional Shannon entropy (SE) partition approach. Some typical results are presented to illustrate the influence of the parameter q in the thresholding.

This paper presents a new approach to enhance thecontrast of microcalcifications in mammograms using afuzzy algorithm based on Tsallis entropy. In phase I imageis fuzzified using S membership function. In Phase II usingthe non-uniformity factor calculated from local informationthe contrast of Microcalcifications were enhanced whilesuppressing the background heavily. This is the first time inliterature to propose an enhancement algorithm usingTsallis entropy. Tsallis entropy has an extra parameter q.We assume that grade of mammogram is related with qparameter. The values of q were calculated from thehistogram. The proposed approach can be even suitable fordense mammograms.

This paper presents a new approach to enhance the contrast of microcalcifications in mammograms using a fuzzy algorithm based on Tsallis entropy. In phase I image is fuzzified using S membership function. In Phase II using the non-uniformity factor calculated from local information the contrast of Microcalcifications were enhanced while suppressing the background heavily. This is the first time in literature to propose an enhancement algorithm using Tsallis entropy. Tsallis entropy has an extra parameter q. The proposed approach can be even suitable for dense mammograms.