Abstract -- In this brief, we propose a data scaling technology (DST) for use in a low-error fixed-width Booth multiplier (FWBM) to reduce truncation errors. The proposed DST reduces the number of redundant bits in the multiplicand, yielding more efficient bits in low-error FWBMs. The truncation errors in FWBMs are reduced by adding a circuit in accorporating the proposed DST to them as well as an error-compensation circuit. We found that the signal-to-noise ratio of the proposed DST-FWBM (1 bit) was more than 1.05 dB higher than that of an FWBM without the DST circuit. Long-width DST-FWBMs achieved an accuracy closely approaching the ideal value of a post-truncated multiplier. To verify its performance in a VLSI chip, we implemented the DST-FWBM in a 0.18-μm CMOS process. The proposed DST method was shown to considerably improve the accuracy of FWBMs, rendering this technology suitable for use in digital signal processing techniques. 

Abstract -- Ethics in the academic environment is important in recent times. It helps to pursue integrity, discipline, and honesty among students and instructors. Without ethics, it is difficult to live and the academic environment has been encounter much use of IT (Information Technology). So teachers must demonstrate, guide, and help students who practice safe, legal, and ethical behaviour. An acknowledgment given by Doug Johnson, an expert in educational technology, that technology can be extremely disruptive in the classroom. Here come the biggest ethical issues affecting our academic environment, we can better understand how to address them. While digital tools in the academic environment, the following are the most common legal and ethical issues in the academic environment. Children are imposed with some guidelines like they should vote at 18, drink at 21, and drive at 16. As they are emotionally underdeveloped for these activities and also they are not properly educated and developed about the use of computer and internet. There are further 10 types of plagiarism namely, Clone Plagiarism, Find & Replace Plagiarism, Hybrid Plagiarism, Ctrl + C Plagiarism ,Remix Plagiarism, Recycle Plagiarism , Mashup Plagiarism, ReTreat Plagiarism, Aggregate Plagiarism, 404 Error Plagiarism these should know by the scholars to resist. let's see below in detailed. 

Abstract -- Breast cancer occurs when cells in the breast begin to grow out of control and invade nearby tissues or spread throughout the body. It is one of the leading causes of death in women. Cancer development appears to generate an increase in the temperature on the breast surface. The limitations of mammography as a screening modality, especially in young women with dense breasts, necessitated the development of novel and more effective screening strategies with high sensitivity and specificity. Aim of this system is to evaluate the feasibility of thermal data as a potential tool for the early detection of the breast cancer. This system consists of 8- temperature sensor data collected from 54 individuals consisting of three different kinds of breast conditions: namely, normal, benign and cancerous breast. We have proposed the use of multiple thermal sensors positioned on brassiere cloth covering all four quadrants to provide continuous monitoring of temperature changes on the breasts, can be used as potential cancer diagnosing tool. To test the reliability of the developed device, breast phantom and tumour respectively. Temperature data from the 8 temperature sensors on the surface of the two breasts (eight sensors one side of the breast) are fed as input to PIC microcontroller which is has inbuilt ADC channel and is used to convert analog input as a digital format. This converted digital temperature value is fed to PC which is enabled with LabVIEW software. If temperature value exceeds threshold temperature value, then this system is considered as a benign and cancerous breast. If it is not exceeded the threshold limit, this wearable device shows normal breast. 

Abstract -- A basic boost converter converts a lower DC voltage to a higher DC voltage in one topology. But the voltage boost provided by a conventional boost converter is not enough to meet the current day fast charging applications such as e-vehicles charging. In this presented project a DC-DC Quadrupler high gain boost converter adds additional benefits that reduce the stress on the diodes and other switching components and high voltage transfer gain compared to the other converters along with a quadrupler (i.e., eight) time increase in voltage. The main aim of this project is to satisfy the various battery loads by implementing the automatic Quadrupler boost operation by sensing the voltage source. The new approach has proven accuracy, robustness and efficiency in energy utilization for standalone charging system by knowing the various facts & topologies about converters, batteries and a regulated powers supply (RPS) is used as a source. Unlike a conventional boost converter, the Quadrupler boost converter uses an extra pair of didoes and capacitors during the energy transmission time divided inductor stored energy is stored in one capacitor and another divided inductor stored energy composed by the other capacitor energy store has transferred to the output to attain much higher voltage gain and making the voltage Quadrupler boost converter efficiency is higher by comparing with conventional boost converters.

Abstract -- Today the biggest problem the world is facing above all the natural disasters is the Covid- 19. It's been more than a year but the solution to the issue is still at a far fetch. However, still have few ways to control the outbreak as instructed by the WHO (World Health Organization). A few among them are wearing a mask and maintaining social distance. The objective of the project is to detect face masks in a public gathering or an event. The algorithm used in the project to achieve the objective is Mobile Net V2. An image of a few people wearing a mask and without wearing a mask is used as an input dataset. There are few processes involved in achieving the objective of the project that include preprocessing, data augmentation, training, testing and image segmentation. Here HAAR-CASACADE algorithm is used for image detection. Collating with other existing algorithms, this classifier produces a high recognition rate even with varying expressions, efficient feature selection and low assortment of false positive features. HAAR feature-based cascade classifier system utilizes only 200 features out of 6000 features to yield a recognition rate of 85-95%. According to this motivation we demand mask detection as a unique and public health service system during the global pandemic COVID-19 epidemic. The model is trained by face mask image and nonface mask image.