Venkateswari Ramesh

The surface roughness of Inconel 718 is predicted using a sequential discharge model for electrical discharge machining (EDM). To begin with, the EDM single pulse discharge machining process was accurately simulated using the finite-element method (FEM). The surface topography under various discharge settings, the size, and the characteristic parameters of a single-pulse crater are simulated. Second, the material defines the discharge position as the minimum gap width between the work piece’s starting surface and the electrode in the removal model. The simulation shows that the magnitude of the single-pulse discharge energy influences the crater’s form and size. A difference in discharge energy causes a divergence in the increasing crater radius, depth, and flanging height trends. On the other hand, the ultimate surface morphology of an EDM machined surface is determined by the distribution of discharge locations around the parts in the workpiece; finally, machined surfaces are inspected using the same discharge parameters. The EDM work piece’s surface morphology matches the material removal. Between simulation and experiment, there is a relative error in surface roughness around 8.26%, and there is a relative error in surface roughness.

Because of the high mortality rate, increased medical costs, and ongoing global growth in the incidence of this malignancy, early detection has become a top priority. Early detection and treatment of melanoma are critically important; the likelihood of a positive outcome rises dramatically. To address this issue, academic researchers plan to develop a prototype image analysis system based on deep learning to determine whether a lesion is malignant or benign based on dermatoscopy image databases. Pretrained convolutional networks with simple architectures were employed in this study to grasp their design better and to train the given dataset more quickly. Using convolutional neural networks as the basis, this research seeks to develop a deep learning system capable of classifying images. To train our model with the pretrained AlexNet, VGG, and ResNet networks, we will use the learning transfer methodology (or transfer learning), whose architecture we will outline so that it may subsequently be adjusted to our data. In this research work, fairly basic pretrained convolutional networks have been used to understand their architecture and efficiently train the given dataset. However, other networks have much more complex structures or even the same networks used, but with many more layers. For possible future work, it is proposed to use, for example, ResNet‐152, Vgg‐19, or other different networks such as DenseNet or Inception.

Hybrid synchronization is one of the most significant aspects of a dynamic system. We achieve nonlinear control unit results to synchronize two comparable 7D structures in this study. Many dynamic systems are directly connected to health care and directly enhance health. We employed linearization and Lyapunov as analytical methods, and since the linearization method does not need updating the Lyapunov function, it is more successful in achieving synchronization phenomena with better outcomes than the Lyapunov method. The two methods were combined, and the result was a striking resemblance to the dynamic system’s mistake. The mathematical system with control and error of the dynamic system was subjected to digital emulation. The digital good outcomes were comparable to the two methods previously stated. We compared the outcomes of three hybrid synchronizations based on Lyapunov and linearization methods. Finally, we used the existing system, presenting it in a new attractor and comparing the findings to those of other similar systems.

Impact of Non-Linear Electronic Circuits and Switch of Chaotic Dynamics

Neuroblastoma is the most common extracranial solid tumor in children. Neuroblastoma presenting with diarrhea as the predominant symptom is rare and can be a diagnostic challenge to the paediatrician. We present a twenty months old child with Retroperitoneal Ganglioneuroblastoma who presented with chronic diarrhea and refractory hypokalemia. Tumor removal resulted in cessation of diarrhea and correction of hypokalemia.

The aim of this paper is to give a systematic development of grill N-topological spaces and discuss a few properties of local function. We build a topology for the corresponding grill by using the local function. Furthermore, we investigate the properties of weak forms of open sets in the grill N-topological spaces and discuss the relationships between them.