Sahil Yadav

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Papers by Sahil Yadav

Predicting the Trends of Quality Oriented Jobs

In this paper, it focusses on studying the job prediction using different deep neural network mod... more In this paper, it focusses on studying the job prediction using different deep neural network models. To predict the future jobs based on Dataset which contains the previous year’s job opportunities, locations, packages, eligibility criteria and sectors. It focuses that in future which Technology place a major role to get the quality jobs in several sectors. And also analyse the required knowledge to get a qualified job based on eligibility. In future how the graduates get jobs based on their skills with the help of the dataset which collects from the different job sites like first Naukri, LinkedIn, Monster etc. The trends of quality-oriented jobs can be analysed and easily predict the future job opportunities by applying machine learning techniques.

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Structural Health Monitoring of Bridges by Using Ultrasonic Sensor

VIVA-Tech International Journal for Research and Innovation, Mar 1, 2021

Bridges are vital components of the Indian surface transportation system and support the growth o... more Bridges are vital components of the Indian surface transportation system and support the growth of this nation's economy. But recent unexpected collapses and near to collapses of bridges underline the need for effective structural monitoring. There are multiple causes: poor technical state of bridges and roads, failure to traffic rules, vehicle built to modern highway traffic regime As the cost for monitoring and repair is much lower than the cost for reconstruction of new structures, monitoring is vital for civil infrastructure facilities, which form the lifeline of our country's economy. Current maintenance operations and integrity checks on a wide array of structures require personnel entry into normally-inaccessible or hazardous areas to perform necessary nondestructive inspections. Recently there has been increase in need for adopting smart sensing technologies to SHM so this review focus on sensing, monitoring and assessment for civil infra-structure. At present, the commonly used crack detection methods include physical and electrochemical methods, but there are shortcomings such as large equipment area, low detection frequency, and complex operation. This research develops and validates an array of Ultrasonic sensors for surface crack detection. It is a non-destructive testing (NDT) with potential applications for locating and up monitoring cracks and flaws during structural health management. This research presents the quantitative crack detection capabilities of the Ultrasonic sensor, its performance in actual structural environments, and the prospects for structural health monitoring applications.

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RescueAlert-an accident detection and rescue mechanism

International Journal of Electrical and Computer Engineering (IJECE), 2021

With the increase of vehicles and cars of different kind and the large movement that occurs every... more With the increase of vehicles and cars of different kind and the large movement that occurs every day on the roads it was natural to observe an increase in traffic accidents, but the real dilemma lies in how to make the rescue process efficient. The problem that we want to solve is the response of ambulances towards accidents and the lengthy registration process of patients in hospitals. In the above two scenarios, the manual process of calling the ambulance leads to delay in rescue of patients from an accident and the delay in registration of patient leads to delay in medication or treatment of the patient. We want to make the process more efficient by automating accident detection for increasing the efficiency of the ambulance rescue process and by sending the details of the patient before the patient reaches the hospitals for faster treatment of patients. Along with this, alert messages will be sent to the family or friends of the patients to notify them as soon as an accident is...

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Study of Behavior of the Masonry Infill Structures Subjected to Lateral Loads

Lecture Notes in Civil Engineering, 2021

The principal aim of this study is to analyze masonry infills subjected to lateral loads using a ... more The principal aim of this study is to analyze masonry infills subjected to lateral loads using a 3D finite element modeling software, "ABAQUS". With the help of Abaqus, a 3D wall is designed with three sides framed and base fixed for ENCASTRE boundary conditions. And the load is being applied to get various results. Firstly, it has been concluded that rigidity increases as Young's Modulus increases. Further to widen the area of research, Area of the wall is being introduced with an opening in the masonry infill wall with 30%, 45%, 50%, and 45% split openings and concluded that First class brick gives optimum results and increase in opening Percentage of wall tends to decrease in rigidity of the wall. Thus, failure will occur due to diagonal compression so, when force is applied on the infill wall section, a brittle failure occurs in a diagonal direction before the yielding of the stirrups, and diagonal compression mode of failure occurs, (out of plane failure occurs) due to Buckling instability. Both the corners of the wall are crushed.

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Research and Analysis of Smart Mirror

The project shows the design of a smart device-Smart Mirror. The smart mirror here is mainly for ... more The project shows the design of a smart device-Smart Mirror. The smart mirror here is mainly for home environment. These smart mirrors are not widely used due to cost or high requirements of hardware. The proposed smart mirror will be operated by Raspberry Pi and will be connected by real world through internet. The smart mirror will consist Raspberry-Pi, LED monitor, speakers, microphone with two-way mirror and acrylic glass. With the help of voice recognition API the mirror will communicate with the user through voice commands and responds them accordingly. The mirror will highlight some basic amenities like time, local news, weather, etc. The mirror will also perform some advance function such as Home Automation using Smart Mirror. This mirror with artificial intelligence will provide an extraordinary experience to the user.

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Abrasive Jet Machining and Optimization of Process Parameters

International Journal of Advanced Research, 2021

Abrasive Jet Machining also known as micro-abrasive blasting or pencil blasting is one of the mec... more Abrasive Jet Machining also known as micro-abrasive blasting or pencil blasting is one of the mechanical energy based economical non-traditional machining process for cutting, deburring, polishing, drilling, etching and cleaning of alloys, brittle metals and non-metallic materials due to its high degree of flexibility and low stress forces with less heat generation.In AJM process, fine abrasive grits (silicon carbides, Aluminium oxides, Sodium bicarbonate, Boron Carbides, Crushed glass and Dolomite etc.) of typically ~0.025 mm are accelerated in a high velocity (150-300 m/s) jet of gas stream or air which is generated by converting pressure energy of carrier gas or air to its Kinetic energy and hence high velocity jet and nozzle directs abrasive jet in a controlled manner towards the work surface. Small fractures are created after impacting abrasive particles on the work surface.

Holistic Approach in Deep Learning and its Applications

IOP Conference Series: Materials Science and Engineering, 2021

Deep learning has become a territory fundamental to scientists in the past barely any years. Conv... more Deep learning has become a territory fundamental to scientists in the past barely any years. Convolutional Neural Organization is a significant learning approach that is thoroughly utilized for managing complex issues. It beats the prerequisites of standard Artificial Insight moves close. Critical learning, a technique with its establishment in fake neural systems, is making beginning late as a remarkable asset for computer based intelligence, promising to reshape the conceivable predetermination of man-made reasoning. Getting data and important encounters from unusual, high-dimensional and heterogeneous biomedical data remains a key test in changing clinical administrations. Moreover we will investigate the difficulties in enormous information assessment.

Ensuring Privacy in Big Data

SSRN Electronic Journal, 2020

Enormous is characterized as a term used for astoundingly enormous enlightening lists that have p... more Enormous is characterized as a term used for astoundingly enormous enlightening lists that have progressively various and composite structure. Further, additional difficulties like taking care of, analyzing and applying further strategies for isolating outcomes come inseparable. It is the term used to depict the route toward investigating a lot of complex information to part with the game examples or recognize concealed relationships. In any case, there is a conspicuous logical inconsistency between the security and different worries in large information. The principal concern and reason for this paper is on detachment and security worries in enormous information. This paper speaks to on investigation and arrangement of different unknown methods for protection conservation like t-proximity, k-obscurity, l-assorted variety and differential security.

DerainGAN: Single image deraining using wasserstein GAN

Multimedia Tools and Applications, 2021

Rainy weather greatly affects the visibility of salient objects and scenes in the captured images... more Rainy weather greatly affects the visibility of salient objects and scenes in the captured images and videos. The object/scene visibility varies with the type of raindrops, i.e. adherent rain droplets, streaks, rain, mist, etc. Moreover, they pose multifaceted challenges to detect and remove the raindrops to reconstruct the rain-free image for higher-level tasks like object detection, road segmentation etc. Recently, both Convolutional Neural Networks (CNN) and Generative Adversarial Network (GAN) based models have been designed to remove rain droplets from a single image by dealing with it as an image to image mapping problem. However, most of them fail to capture the complexities of the task, create blurry output, or are not time efficient. GANs are a prime candidate for solving this problem as they are extremely effective in learning image maps without harsh overfitting. In this paper, we design a simple yet effective ‘DerainGAN’ framework to achieve improved deraining performance over the existing state-of-the-art methods. The learning is based on a Wasserstein GAN and perceptual loss incorporated into the architecture. We empirically analyze the effect of different parameter choices to train the model for better optimization. We also identify the strengths and limitations of various components for single image deraining by performing multiple ablation studies on our model. The robustness of the proposed method is evaluated over two synthetic and one real-world rainy image datasets using Peak Signal to Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM) values. The proposed DerainGAN significantly outperforms almost all state-of-the-art models in Rain100L and Rain700 datasets, both in semantic and visual appearance, achieving SSIM of 0.8201 and PSNR 24.15 in Rain700 and SSIM of 0.8701 and PSNR of 28.30 in Rain100L. This accounts for an average improvement of 10 percent in PSNR and 20 percent in SSIM over benchmarked methods. Moreover, the DerainGAN is one of the fastest methods in terms of time taken to process the image, giving it over 0.1 to 150 seconds of advantage in some cases.

Sahil Yadav

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