Moulding process

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Shanmuga Raj

special moulding process

Engineering

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The objective is to design and develop an application that will help to imp rove the efficiency and effectiveness of the police security measures in keeping criminal records. ABSTRACT The victims can file the FIR through the website under various sections. The user can send photo evidence if any online. There will be an 'SOS 'capability in which, the user can press a button and his/her location will be sent to the nearest Police station. There will be a separate component for the accident victims so that FIR can be registered fast and treatment can be started as soon as possible. In this current system, user's information will be kept confidential and only users complain will be forwarded to its nearest police station. Users complain number will be forwarded from the server side automatically. For identifying location and authentic person, concept of cookies and IP addressing has been used. To eliminate the location conflicts between police station, server will play a vital role. It will search the address table using IP address and forward message to that police location from where the message has been received. We intend to create a project which will help bridge the gap between the police department and the common man. 'Online FIR Registration and SOS system' project will have an app from where the users can file FIR against the offender under the various sections. The main site will be maintained by the admin (from the police) who will then notify the user if the FIR has been registered and the necessary action has been taken.

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In this short lecture, I explain the fundamentals of electromagnetic compatibility (EMC), the basic coupling model and coupling paths via cables, electric fields, magnetic fields and wave fields. We also look at electric vehicles as an example of systems with many conducted EMC problems due to power electronic devices such as rectifiers and inverters with non-linear components such as diodes and fast switching components such as MOSFETs or IGBTs. After a brief review of circuit analysis fundamentals and an experimental investigation of the frequency-dependent impedance of resistors, capacitors and inductors, we look at a simple low-pass filter. The transfer function is derived and measured.

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We investigated the applicability and efficiency of the MLMC approach to the Henry-like problem with uncertain porosity, permeability and recharge. These uncertain parameters were modelled by random fields with three independent random variables. Permeability is a function of porosity. Both functions are time-dependent, have multi-scale behaviour and are defined for two layers. The numerical solution for each random realisation was obtained using the well-known ug4 parallel multigrid solver. The number of random samples required at each level was estimated by calculating the decay of the variances and the computational cost for each level. The MLMC method was used to compute the expected value and variance of several QoIs, such as the solution at a few preselected points $(t,\bx)$, the solution integrated over a small subdomain, and the time evolution of the freshwater integral. We have found that some QoIs require only 2-3 mesh levels and samples from finer meshes would not significantly improve the result. Other QoIs require more grid levels.

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According to the World Health Organization (WHO), seventy million individuals worldwide suffer from epilepsy, a neurological disorder. While electroencephalography (EEG) is crucial for diagnosing epilepsy and monitoring the brain activity of epilepsy patients, it requires a specialist to examine all EEG recordings to find epileptic behavior. This procedure needs an experienced doctor, and a precise epilepsy diagnosis is crucial for appropriate treatment. To identify epileptic seizures, this study employed a convolutional neural network (CNN) based on raw scalp EEG signals to discriminate between preictal, ictal, postictal, and interictal segments. The possibility of these characteristics is explored by examining how well timedomain signals work in the detection of epileptic signals using intracranial Freiburg Hospital (FH), scalp Children's Hospital Boston-Massachusetts Institute of Technology (CHB-MIT) databases, and Temple University Hospital (TUH) EEG. To test the viability of this approach, two types of experiments were carried out. Firstly, binary class classification (preictal, ictal, postictal each versus interictal) and four-class classification (interictal versus preictal versus ictal versus postictal). The average accuracy for stage detection using CHB-MIT database was 84.4%, while the Freiburg database's time-domain signals had an accuracy of 79.7% and the highest accuracy of 94.02% for classification in the TUH EEG database when comparing interictal stage to preictal stage.

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