A bandwidth enhanced multilayer Electromagnetic Band Gap (EBG) structure to reduce the simultaneous switching noise (SSN) in high frequency operating circuits, which useful for the satellite communication application, is presented in this paper. A proposed stack structure is mathematically analyzed by the dispersion method and transmission matrix method. Simulation results show good mitigation of SSN in scattering parameters and signal integrity in terms of eye diagrams. We have also checked for power integrity analysis using self-impedance. The proposed structure gives a good SSN suppression at -30 dB from 817 MHz to 26.32 GHz, around 25.50 GHz bandwidth and also reduces the cavity mode resonance within the stopband range. The proposed multilayer structure is compared with planar EBG plane and reference board. It is also compared with published results.

Simultaneous switching noise (SSN), often occurs when signals transition rapidly between the ground and power planes, is an important problem in high-speed digital circuits. The Electromagnetic Bandgap Structure (EBG) is a novel technique that can help to solve signal integrity and power integrity problems. In this paper, we present a three dimensional coplanar electromagnetic bandgap (EBG) structure to improve Signal Integrity (SI), validated by eye diagram and Power Integrity (PI) shown by self impedance. This proposed planar EBG structure offers effective SSN suppression for frequency ranges between 2.38 GHz and 22.39 GHz, with an average suppression level of -30 dB.

This paper introduces and validates a compact two-dimensional Electromagnetic Bandgap (EBG) structure for the improvement of signal integrity (SI) and power integrity (PI) by suppressing Simultaneous Switching Noise (SSN). SSN bandwidth can be increased by using the proposed T bridge compact planar structure. The proposed structure is simulated using Ansys HFSS Software. Simulated and measured results by Vector Network Analyzer provide 3.13 GHz to 11.40 GHz frequency bandgap with good mitigation of SSN at -30 dB noise suppression reference. It will almost cover S, C, and X bands from electromagnetic frequency spectrum. This will be useful for satellite and terrestrial communication and radar communication applications. The proposed structure analyzes signal integrity issues using eye diagram in MATLAB and power integrity in HFSS with input impedance respectively. The main purpose of this work is to provide a compact structure to improve signal and power integrity by the suppression of power/ground noise. Comparative study is also performed with the proposed structure and reference board with similar dimensions.

Co-Mart is a daily necessity price comparison application where users can compare the prices of groceries on various E-commerce websites. With the advancement in technology and the growing E-commerce business, the number of E-commerce websites has increased but at the same time, it has become difficult for people to choose the best deals from these websites. This paper focuses on an web application called Co-Mart, where one can compare prices of various products on different E-commerce websites and thus save one's Time, Efforts and Money. The methods that will be used for identifying the best deals will be web crawling and web scraping. The web scraping scripts will be written using python libraries and web crawling works on HTML labels. The framework will be designed using HTML (Hypertext markup language), CSS (Cascading style sheet), and JavaScript as front-end and Python and Django will be used for back-end support with SQLite as the Database Management System.

Today, Artificial intelligence has brought in major developments in the field of technology. The evolution of technology has made it possible to build a fully autonomous driverless vehicle. According to the recent data, a vast majority of road accidents occur due to human errors or spontaneous traffic resulting in a lack of response time. The problem can be solved with the help of automated systems. This paper proposes a working prototype of a self-driving car that is capable of driving in indigenous tracks like curved tracks, straight tracks, or curvilinear tracks. The proposed system uses image processing as well as neural networks for the path planning and identification of road signs according to the regulations; to ease the lives of the drivers and automate the driving process.

In today's world, news information is spreading across all social media platforms rapidly, and most of the pieces of news are fake, and it affects everyday people's lives. Sometimes they may lose their life too due to this. Moreover, many people spread rumors purposely; hence there is a need for a system that can tell the user whether the news is correct and they can trust it or not. Using machine learning and natural language processing, it can be achievable Where a machine learning model can be trained that will be able to predict whether the news is fake or accurate based on the historical data which contains the unique patterns. So using this model system can indicate whether the information is fake or real. Also, natural language processing can be used to improve the performance of the model.

The main aim of the project is to extensively upgrade the automation systems to reduce mishaps or hazards in the industry. To keep a check the sensors are connected to the system to report variations in some parameters for proper action through microcontroller. These sensors like object detector, lightning and rain sensors, gas leak etc. can be utilized in the industry for proper monitoring of the system. Under such conditions the power supply to the entire unit is automatically cut off which would kill the electrical switch immediately. This project is also designed to safeguarding the electrical circuitry by operating a relay circuit. This relay gets activated immediately, whenever the electrical parameters exceed the predefined values.

Street car crashes are a major public health issue as they bring about substantial loss of lives, property, and time. Clinical help given promptly will save many lives. This paper presents a smart mishap detection and caution system that notifies the emergency contacts of the user when a mishap happens by sending a message with the detected location. At the point when the vehicle is in a mishap, the vehicle's sensor distinguishes it promptly and sends an SMS to the crisis contacts. There is a reset button that can be pressed to prevent the alarm from being sent to the crisis contacts in an event where everybody inside the vehicle is safe.

This paper introduces the suppression of Simultaneous Switching Noise (SSN) using compact coplanar Electromagnetic Bandgap (EBG) structure. T-shaped bridge is designed for connection of two adjacent planes i.e. patches of Electromagnetic Band Gap structure. This Planar EBG structure provides good suppression for frequency ranges from 2.87 GHz to 13.56 GHz at -30 dB average suppression level.

In this paper, we have put forward, a unique 3D layer methodology for a crisp and broadband electromagnetic band-gap structure (EBG) to be used in high-speed printed circuit boards (PCBs). In high speed circuits there exists issues of signal integrity and power integrity and is very important to minimize them for efficiently transmitting data at high speeds. Using this technique we have effectively converted one dimensional EBG structure into a vertical 3 dimensional structure, therefore substantially reducing the EBG area and also reducing the space between the unwanted sound origin and the area affected by the same.

In recent years, with the widespread construction, the number of incidences of structural damages and accidents has increased. This has led to fatal casualties and property loss. The most important reason for most of the structural damages and accidents occurring is lack of effective monitoring. The main aim of Structural Health monitoring is to monitor different civil structures like buildings, stadiums and try to improve the health of the structure which in turn will help to improve the lifespan of the civil structures and can also help to maintain the safety of Public [5]. The process of SHM includes detecting and analyzing the damages or weakness that the structure has, due to old age or any other reason and take preventive measure to avoid any fatal consequences [3]. Structural Monitoring is also important helpful for reducing over finance, as we don't always have to take big steps of demolition and rebuilding as sometimes simple repairs can do great effects. The necessity of bridge health monitoring has been drawn more and more attention. This paper introduces a remote bridge health monitoring system. Undergoing regular maintenance procedure on civil structures can help to increase the life span of the structure [7].

In modern integrated circuitry, the need for high-speed printed circuit board design is growing day by day, The high-speed circuits are exposed to noise generated due to fast edge rates, high clock frequency, and low voltage levels. Simultaneous switching noise (SSN) is a major issue in high-speed digital circuits that occurs due to the signal switching at a very fast rate between ground and power plane. The signal integrity issue can be reduced by proposed novel technique of electromagnetic bandgap structure. In this paper, the one-dimensional L-bridge EBG structure is proposed, The L-shaped bridge design not only widen the bandwidth of stop-band, but also enlarge the mutual coupling betwixt adjoining cells also this proposed structure focused on mitigation of noise in high-speed circuits. The simulation result achieves the wide range of band-gap from 2.56 GHz to 13.47 GHz at -30 dB and can obtain ultra-wide band suppression of SSN.

A considerable amount of gap in communication exists amongst the speech and hearing-impaired individuals with the other people; which is of paramount importance to be bridged. The aim is to study various methods for effective intercommunication between Sign language and the English language. Initially, a Hardware glove is implemented which has of flex sensors whose accuracy is proved to be not very high. To further improve the accuracy, a model using a convolutional neural network was trained on an existing data-set. Since the data-sets were not versatile and the scope was narrow, a new diversified data-set was created and the model was further improved. The new model has very high accuracy and it can predict almost every alphabet. Various other gestures having facial features and gestures including both the hands were added to our data-set. This model has a huge potential as it can interpret any gesture of various sign languages if provided in the data-set. The user can also add extra gestures in the data-set, making it highly customized. Further, the data is sent to an application which will convert the received text to speech. To reduce the communication gap, the system is made wholly bidirectional i.e. speech can also be converted to the sign language. Initially, the speech is taken at the input and is converted to the text which acts as the input for the next step in which the converted text is directly taken as the input to be converted to the corresponding gesture according to the convenient sign language. Thus, the input speech is translated into a video consisting of a sequence of gestures of the American sign language which can be extended to other languages as well. Bidirectional Sign Language Translating system consists of a software system. It is named as a bidirectional system as it not only converts the sign language to speech via text conversion but also incorporates a system which translates the speech to the prescribed sign language with text conversion as the mediator. The methodology has been explained in the further sections.

Neuromorphic Engineering is the interdisciplinary branch where various designs are innovate with the use of VLSI technology. This design named as Artificial Neural System that included vision system, head and eye system, auditory system and autonomous robot design. In recent years, neuromorphic computing and VLSI technology merges to used in robotics applications. Biological behavior of neuron is implemented using MOSFET structure which is the part of VLSI technology [1]. One of the key component of neu-romorphic computing is the neural encoder. Comparative study of various neuron models for proposed temporal encoder. Then mathematical implementation of Hodgkin- Huxley (HH) and Leaky Integrate & Fire (LIF) neuron model in the one of the suitable technique of neural encoder. This implementation has performed using an MATLAB software. After implementation this two model encoder comparative study has been performed for selection of better temporal encoder which further used in auditory spiking neuron.

Lip Reading is gaining momentum to be one of the toughest challenges in the Computer Vision society. We have analyzed feature extraction methods for accurately representing the lip contours in terms of feature representations and how these features were trained to give the output in the form of classes - phonemes, words, and sentences. Strong emphasis is given on the challenges that have motivated the creation of different feature extraction methods and neural network models specific to this task and how these challenges were solved by making modifications in the existing algorithms or using alternative algorithms. Feature extraction methods are made robust to variance in illumination, pose, etc. Once, we have these features we have dwelt more into the classification algorithms such as the Random Forest and the Support Vector Machine. Neural network models have been developed which aim to capture the spatial as well as the temporal features in the video datasets. We hope that the reader of this paper will be able to train better models after gaining an insight into how these challenges have been solved in the past.

Radiation pattern is one of the most important characteristics of an antenna. To test any fabricated antenna a measurement system is required. This paper presents an antenna measurement system which measures pattern of antenna using the parameters provided by Vector Network Analyzer with the help of positioning controller. The system is implemented on LabVIEW having user interface to provide parameters and display the antenna radiation pattern. The system frequency measurement varies from 30 KHz to 14 GHz. The performance of system is evaluated by comparing results of proposed system with simulation results in IE3D.