One of the main purposes of machining is to minimize the surface roughness of the workpiece. In this study, the hole turning operation was applied to AL7075 alloy. First, the parts were drilled on a CNC lathe with an HSS drill. Then the holes were turned. The effects of turning parameters on surface roughness were determined by Signal/Noise analysis. As a result of the study, it has been determined that the most important parameter for surface roughness is the cutting speed. It has also been found that the use of a small amount of cutting depth gives a better surface roughness.

The Internet has become one of the significant ways of communication. Sending medical information from one place to another sometimes may cause leakage or interruption in the messages that are being sent. Thus it is necessary to protect the patients medical information being sent through the network. Cryptography, Steganography are some of the various techniques that are being used to protect data from the outside world. Here, the patients information is encrypted using chaotic encryption and the image is compressed by The Absolute Moment Block Truncation Coding (AMBTC) compression method. The chaotic encryption is employed in the system to improve robustness against security vulnerabilities. The compressed image is embedded into the cover image by the histogram modified embedding method. Various keys are used for encrypting and embedding the information into the image. The reverse process is done on the receiver side to retrieve the original image and the patients information without any loss or distortion by using the same key. The Peak Signal to Noise Ratio (PSNR) of this method is obtained above 50dB.

-Library is a vast place which contains increasing number of books. With the growing phase of technology, library needs to be ready for change and should bring the technology in it to retain their students interest in visiting the library. People often find it difficult to search a particular book and library staff handles a tedious task in sorting. To overcome these obstacles, a smart book tracking system based on Radio Frequency Identification Device (RFID) technology has been proposed. Book tracking system aims in developing an application for the user to track the location of the book in the library. RFID module has been used to locate the book and Arduino controller to control the system. The proposed system uses three modules, the corresponding information is read using RFID reader, the information read is stored in the cloud and finally the cloud information is accessed using android based mobile application.

Face recognition failure is one of the challenging hurdles that a machine deals with. As the revolution of technology comes into the picture, the usability of digital security based on facial biometric become most frequent today. The obsolete security system based on the recognition of features is unable to tackle the variations in a dataset. The failure rate in the face recognition system is found to be common in the various digital systems. This paper introduces a robust design to tackle the recognition issues. This paper utilizes a series of robust techniques in order to establish accurate face recognition with the minimum failure rate. In the proposed design, the facial portion of the acquired image is segmented out using the Haar cascading algorithm which deals with the pixel values of the image. The extracted facial portion of the image is normalized using the normalized pixel intensity algorithm to minimize the noise ratio. Then, the feature extraction procedure is applied to the normalized segmented facial portion of an image which is done by local binary patterns histogram algorithm (LBPH). The face recognition is acquired through such extracted features using the AdaBoost algorithm. The proposed design of face recognition is explored against the testing image with the random variations to generate the accuracy which is found to be 96% and it is proven better than other existing algorithms.

- Face recognition can have considerable significance to factual globe requisition (supplication) for instance video scrutiny, personage system evolvement, privacy & security system. A comparatively deep neural network provides better performance results in terms of accuracy & processing time. The introduced system based on a convolutional neural network (CNN) proposes enhanced building blocks by having normalization computation at the layers & it supplies speed-up to the system. The proposed CNN model utilizes to draw-out distinct features of face &ReLU used to classify faces into CNN fully connected layer. The experimental result showed that the proposed system achieved better performance result with enhanced face recognition security.

Life Expectancy (LE) models have vast effects on many countries social and financial structures around the world. Many studies have suggested the essential implications of Life expectancy predictions on social aspects and healthcare system management around the globe. These models provide many ways to improve healthcare and advanced care planning mechanism related to society. However, with time, it was observed that many present determinants were not enough to predict the generic set of populations longevity. Previous models were based upon mortality-based knowledge of the targeted sampling population. With the advancement in forecasting technologies and rigorous work of past individuals has proposed that other than mortality rate, there are still many factors needed to be addressed to deduce the standard Predicated Life expectancy models (PrLE). Due to this, now Life expectancy is being studied with some additional set of interests into educational, health, economic, and social welfare services. Our objective here will be to briefly discuss the previously used machine learning, Ensemble methods and hybrid methods used in building life expectancy prediction models. We will aim to test the potential and accuracy of existing ML techniques and their probabilistic projections to predict the generic Life expectancy of a particular region, state

- Electronic voting machine is an efficient and fast solution that allows people to choose their representative in a systematic manner. It is a simple device that has replaced the conventional ballot papers used to record votes. Also, in large populations, the ballot system failed, whereas EVMs proved to be successful and reliable. This project describes a real-time voting machine that is designed using the microcontroller AT89C51 and the software program used is written in assembly language. It is a real-time operating device that produces lesser errors and is easy to operate. Once the votes are cast, the result can be produced in no time just by pressing the result button.