Table of contents

It is our immense pleasure to virtually organize the conference on Future of Engineering systems and Technologies (FEST) during December 18-19, 2020 by 'Fusion and Integration of Science and Technology (FIST), New Delhi' in association with 'Noida Institute of Engineering and Technology, Greater Noida, India'. The conference was organized in association with the dedicated faculty members from Amity University India, I.K. Gujral Punjab Technical University Jalandhar; National Institute of Technology Srinagar; Manipal University India and many other national/International reputed Institutes/Universities.

The conference FEST 2020 aimed to provide a platform for scientists and engineers to share their research results, exchange ideas on engineering systems, theories, technologies and applications; and dissemination of knowledge among engineers, researchers, scientists and entrepreneurs. FEST 2020 also aimed to establish research relations and to find global partners for future collaboration. The conference had covered all the emerging research areas of engineering and technologies.

List of Organizing Team (FEST 2020), COMMITTEE NAMES and this titles are available in this pdf.

All papers published in this volume of Journal of Physics: Conference Series have been peer reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing.

• Type of peer review: Single-blind / Double-blind / Triple-blind / Open / Other (please describe)

Double Blind

• Conference submission management system: Easy chair and email

• Number of submissions received: 123

• Number of submissions sent for review: 95

• Number of submissions accepted: 56

• Acceptance Rate (Number of Submissions Accepted / Number of Submissions Received X 100): 45%

• Average number of reviews per paper: 2.5

• Total number of reviewers involved: 37

• Any additional info on review process:

• Contact person for queries (please include: name, affiliation, institutional email address)

Dr. Vikas Kumar

Department of Mechanical engineering

Amity University, Noida

viksmied@gmail.com

vkumar20@amity.edu

fest@fistinternational.com

The requirement of lightweight components for interplanetary missions explore the possibilities of the application of composite materials. Carbon Fibre Reinforced polymers (CFRP) are most practical and widely used in space industries. Enhancement of mechanical, thermal, and electrical properties by reinforcing CFRP with Carbon Nanotubes (CNTs) is advantageous, considering the potential applications of such a modified CFRP material in space payload. CNT composites for space use opens new horizons to improve specific stiffness and electrical conductivity of the CFRP components without degrading the performance index. Composite characterization and space qualification are critical and essential, which demonstrate the capability of fulfilling functional as well as specific requirements for space. CNT Composites have to undergo severe environmental tests without degradation. This paper addresses the synthesis of CNT-CFRP composites, its Characterisation and Space Qualification aspects. Synthesis of CNT-CFRP sample with single-walled CNT (Ø1.6µm & L>5µm) 0.5%wt by solution mixing method is attempted. The characterization in terms of measurement of tensile strength, electrical resistivity, shielding effectiveness, thermal conductivity, Co-efficient of thermal expansion (CTE) is carried out. Limited Space qualification on samples and electroplated coupons has been carried out by conducting various environmental tests. The results indicate that CNT reinforced CFRP composites are a promising potential candidate for use in the space domain.

Stochastic differential equations (SDEs) were developed at the beginning of the twentieth century to quantify all aspects of stochastic processes. This study focusses to evaluate the applicability and efficiency of the SDEs for modeling tree diameter over bark at any particular height and total stem volume for birch tree species in the boreal forests of Lithuania. Newly developed models of the stem taper development are based on well-defined diffusion processes, such as the symmetric Vasicek type diffusion process, and asymmetric geometric type diffusion process. The stem taper models with the fixed- and mixed-effect parameters are examined. The fixed- and mixed-effect parameters of the SDEs stem are evaluated using maximum likelihood procedure. Results are illustrated using birch trees longitudinal measurements. These models are compared with traditionally used regression type stem taper models using statistical measures and residual analysis. Overall, the best goodness-of-fit statistics for tree diameter and volume predictions produced the SDEs stem taper models. All results are implemented in the Maple software.

Performance of small scale wind turbine (SSWT) and miniature aerial vehicles (MAV) is always effected with Laminar separation bubble. The problem of a laminar separation bubble on the upper surface of an E216 airfoil operated at low Reynolds number (Re=100000) is investigated numerically. Incompressible steady two-dimensional simulation is carried out with Transition γ − Re_θ turbulence model on the airfoil with a boundary layer trip (BLT). The performance of two different types of trips, namely, isosceles triangular (IT) and right-angled triangular (RA) is compared with that of the airfoil with a rectangular (RT) trip. The trip locations used are, 17% of the chord for location-1 and 10% of the chord for location-2 from the leading edge of the airfoil, while the trip heights selected are 0.3 mm, 0.5 mm, 0.7 mm, and 1 mm. Results showed that the boundary layer trip significantly affected the laminar separation and improved the aerodynamic performance of the airfoil. Maximum improvement in drag by 17.41% and corresponding lift to drag ratio by 10.86% are obtained for the isosceles trip at location-2 for the angle of attack of 6°. There is no observable advantage for isosceles and right-angled triangular trips over rectangular trips. Considering the geometrical complexity in fabrication, the rectangular trip is recommended.

India has a population of 1.3 billion people and one of largest growing economies in the world. Therefore, there is a strong demand of energy. Till date, the main source of energy is coal which is non renewable and harmful to the environment. Therefore, it is important and necessary to find an alternative source of energy. This indirectly drives us to focus on Renewable Energy Source, which has several advantages. The Ministry of National Renewable Energy (MNRE) has launched many schemes to encourage the domestic and commercial sector to use renewable energy sources. In India the state of Rajasthan is occupying 5^th position in the production of electric power generation from Renewable Energy Sources like Solar, Wind and Biomass etc. Therefore this paper discusses the potential and opportunities of electric power generation through renewable energy in the state of Rajasthan.

The present paper investigates the effect of time delay in a particular type of single degree-of-freedom self-excited oscillator. The self-excited vibration is generated in the system by using linear velocity feedback (to destabilize the static equilibrium of the system) with a nonlinear Rayleigh type feedback (to limit the growth of the instability into a stable limit cycle). The general method of describing function is employed to study the dynamics with the presence of time delay. Also, the analytical results are verified with the simulation result. Without time delay, the control law can generate a stable limit cycle with the proper choice of control parameters. However, the presence of time delay introduces a globally unstable limit cycle in the system with a stable one. Though the amplitude of the stable limit cycle dies down with the increase of time delay and finally vanishes by stabilizing the static equilibrium of the system. The effect of control parameters is also studied.

There are a lot of studies on semiconductors and in semiconductors also appear many dynamic effects, from the research results that have many applications in science and technology. Conductivity tensor is a familiar concept in physics in general and semiconductors in particular, but research on scattering on ionized impurities is still limited. This paper presents the influence of laser field and electromagnetic waves on conductivity tensor for the case of scattering on ionized impurities in semiconductor. The particle system is placed in an electromagnetic wave field and a laser field. Using quantum kinetic equations for electrons in semiconductor under the action of an electromagnetic wave field, a laser field, the conductivity tensor is calculated with case of scattering on ionized impurities. Conductivity tensor depends on the frequency of the laser field, the laser field amplitude, the electromagnetic wave frequency and typical parameters for semiconductor system. With different frequency bands, the dependence of tensor conductivity on the frequency is different, and the special conductivity tensor is strongly dependent on the amplitude of the laser field but depends very little on its frequency. The results will be plotted and discussed with GaAs semiconductor case and compared with studies for different scattering cases.

Intuitionistic fuzzy set is very important topic for study as it open door to many applications of Science and Technology. Intuitionistic fuzzy set is developed to express uncertain, imprecise, incomplete and inconsistent information. Intuitionistic fuzzy set is expressed to handle uncertainty by using truth membership function and falsity membership function. In various practical problems intuitionistic fuzzy set shows more rational results. Intuitionistic fuzzy set shows inconsistent information and can deal with real-life problem. By observing these we are forwarded to do our work in almost topological group on the basis of Intuitionistic fuzzy set. Since the concept of almost topological group is very new by observing this, in this paper we introduce the notion of intuitionistic fuzzy almost topological group. We have defined some new concepts and investigated properties of intuitionistic fuzzy almost topological group.

Zinc oxide (ZnO) nanoparticles were prepared by sol-gel method and deposited on the substrates (glass gliders and platinum electrodes) by a rotation coating at 2000 rpm. The coated substrate was calcined at 500, 550 and 600 ° C 1hour: The films were determined by XRD and UV, where the results showed their compatibility with the global measurements, and through the results of the test of sensitivity to the membranes of the stomach, we obtained that the film is heat at a temperature of 550 high sensitivity, depending on the surface area of the surface. The Zno thin films were exposed to NH₃ gas with a different concentration of 50 ppm–4000 ppm and the resulting resistance transient was recorded at different operating temperatures (500,550, 600 ) °C.

An ambulance tracking system (ATS) is the need of the hour due to the recent pandemic situation going on around us. It is necessary that patients carrying vehicles such as ambulances must be equipped with the ATS technology. The ATS technology helps the hospital administration to carry out the necessary steps before the patient arrives at the hospital premises. In this technology, Global systems for Mobile communication (GSM) and Global Positioning System (GPS) are used for the efficient working of this device. In this system, a low-cost microcontroller-based electronic device Arduino is used to control the GPS and GSM modules. In this system, modem and display device such as liquid crystal display (LCD) is used at the user end which is also called as Base Station. Information regarding the location of the ambulance is provided by the GPS module. GSM module is used for communicating with the base station. The hospital administration can get the information of the arrival of the ambulance well in time and can increase the chance of survival of the patient as the time required for setting up basic components is done well in advance. This system can also be used for various other vehicles used in emergency situations.

In this work, we have investigated the liquid lithium silicate by the method of molecular dynamics simulation (MD) using the Born-Mayer pairwise potentials under compression. The simulations have been carried out by systems including various pressure values from 5 to 30 GPa. The microstructure of lithium silicate was clarified through the thorough analysis of short-range order (SRO) and intermediate range order (IRO). The short-range order was investigated through factors such as pair radial distribution functions (PRDFs), coordination distributions, angular distributions. The results show that the structure of the system has a transformation from low-coordination to high-coordination under the influence of compression. Besides, the analysis of intermediate range order shows that the structure network in model consists of SiOx and LiOx units connected to others via an Oxygen atom. In the case for the intermediate range order, the fraction of OTy bond calculated under compression shows that their bonding angle and bond length are very little dependent on the pressure changes. Furthermore, the dynamics of liquid lithium silicates calculated through the diffusion coefficients of the atoms shows that there is a dependence of atomic mobility on pressure. The obtained results of simulations are in good agreement with previous experimental and simulated data.

In current scenario the sustainability principles has to be adopted to tackle the challenges facing in the various industrial sectors. As the machining processes consumes natural resources to a great extent, it has become mandatory for manufacturers to go for sustainable management practices. The sustainability in manufacturing processes can be achieved by integrating all small factors and thus achieving sustainable machining conditions. Machining plays a vital role in the industrial economy and it contributes more than 5% to the country's economy. The machining processes have gone through significant changes in the last decades. Competition has increased drastically to gain more profit. Machining processes are been widely used and attempts have been made to minimize the machining cost and the energy consumption. The machining parameters like speed, feed, depth of cut and the coolants used play an important role in machining economy. Main focus in this work is to enhance the surface integrity and the tool life by utilizing least resources and to reduce the energy consumption. P20 steel have wide application in the moulds for plastic injection cavities and tooling. Also, it is used in the die casting of dies for zinc. Thus, the surface roughness plays an important role in the machining of the P20 steel. In this paper, the experiments have carried out on P20 steel on CNC milling process by adopting Taguchi Analysis to optimize surface roughness and tool life. Besides, analysis of cutting forces by using fuzzy logic is studied to evaluate the energy consumption.

Accomplished and accurate object detection has been an important topic in the progress of computer vision systems. With the arrival of deep learning techniques, the purity for object detection has increased drastically. The paper aims to inclusive state of the art technique for the object detection with the goal of obtain high accuracy with a real time performance. A major challenge in many of the object detection system is the docility on other computer vision techniques for helping the deep learning-based perspective, which leads to slow and minimal performance. In this paper, I use a completely deep learning-based approach to solve the problems of object detection in an end to end fashion using wireless sensor network. Even if, many techniques have been developed, but I have discussed some famous and basic idea of object detection using deep learning. In the end i have also given their general applications and results.

Energy plays an important role in the monetary and social expansion of any country. However, there used to be a general deficiency of rural energy development policies that focuses on agriculture. Agriculture has a dual role, i.e. it acts as an energy user in crops as well as an energy supplier in solar electricity generation. Rajasthan, the largest state of India, is blessed with the highest solar insolation. However, solar energy has not been fulfilled yet, predominantly in the field of the agricultural sector, where irrigation is still being done by outdated conventional methods. This paper focuses on the development of strategies to enhance solar energy use in the agriculture sector of Rajasthan state India. An intensive survey was being conducted among scientists, academicians, farmers, and government officials regarding the know-how of present policies and schemes for the different applications of solar energy in Rajasthan state India. The survey reveals that not only the farmers and rural persons but the intellectual world is also unaware of the different policies of solar program prevailing in the state. Based on the survey, various strategies have been suggested to accelerate the solar program among the rural and agriculture sectors of Rajasthan state India.

An Electrical vehicle can utilize a force move framework to charge the on-board Rechargeable Energy Storage System (RESS the battery) or to give the capacity to the electric engine. It is additionally conceivable to utilize remote force move to charge the batteries while fixed, using charging pads. Both of these arrangements are satisfactory for assessing at home or in-vehicle parking, yet at the same time, require the vehicle to stop in a proper area to charge the battery. We propose an eco-friendly wireless charging system for electric vehicles, which enables wireless charging of the vehicle while running on the highways. The proposed approach is also used for the charging of cars in the shopping malls and other parking places. Moreover, the proposed charging system may require electrical energy from the solar PV systems and wind turbines, installed along the highways. The solar PV system and wind turbines are connected to form a Microgrid system and feed generated electrical energy to the wireless charging system. The surplus electrical energy may be either fed back to the primary grid or used for highway illumination. The wireless charging system also consists of an air-core transformer with its primary winding below the highway surface and secondary mounted on the vehicle. The ac power from secondary passes through a rectifier and dc-dc conversion stage to produce suitable dc voltage and current for the charging of the battery unit.

With the increase in utilization of Continuously Variable Transmission, more research has been done in areas pertaining to improving the efficiency of the Continuously Variable Transmission. While it provides a continuous gear ratio for the vehicle to work in, the overall efficiency is lesser than in a Manual or Automatic Transmission. The decrease in the efficiency is mainly due to the variator and the hydraulic losses. While hydraulic losses can be reduced by using electro-hydraulic control systems, the variator losses are primarily caused by the high camping forces required for the transfer of the engine torque. Controlling the clamping forces can improve the efficiency of the Continuously Variable Transmission and reduce the slip experienced by the system. Analysis of control strategies to reduce the clamping forces and improve the slip characteristics are the primary objectives of this paper. The study looks into the change in the transmission efficiency with respect to the change in slip percentage experienced by the belt. A mathematical model is designed in SIMULINK based on the equations governing the functioning of a Continuously Variable Transmission. The results of the theoretical belt slip and the belt slip due to change in dynamics is compared and the effects of the change in torque and clamping forces are also discussed. Using this, a control strategy is developed to improve the power transmission efficiency of the model.

This work presents an optimal recharging strategy for Electric vehicles (EVs) using Quadratic Programming (QP) to flatten the peak power demand on the utility. The increase in penetration of EVs in distribution systems causes a significant increase in peak power demand due to synchronization between the peak load hours and EV charging period. The optimization technique aims to assess the effects of optimal scheduling considering the initial State-of-charge (SOC) level, Demand Side Management (DSM) functionalities that meet both the grid and EV owners' requirements. The feasibility of the scheme is verified with two case studies using different aggregator units and the effect on the system is analyzed by determining the load demands from local utilities and EVs. The aggregator units collect data from EV users with common interests such as EV battery specification, Battery SOC, recharging period and mediate with utility operators such as Transmission system operator (TSO), Distribution system operator (DSO). Further, other parameters such as peak power reduction, peak-to-average ratio (PAR), standard deviation, and peak-to-valley differences are also compared to test the effectiveness of the implemented optimization technique. The outcomes of the study show that using load demand profile and optimal rescheduling using aggregated EVs can flatten the load curve for the utility and lower the demand charges for the end-users.

In this paper, a Numerical investigation of developing laminar flows with forced convection through a compact circular pipe has been done using water-Al₂O₃ nano-fluid. Uniform heat flux (UHF) and the steady-state has been maintained at the wall in each model. Throughout the numerical experiments, Nano-fluid models were made by Alumina volume fraction and were processed under the Re=1050. A single-phase fluid model was determined by nano-fluid thermal and physical properties calculation, whereas the Two-phase model, i.e., granular mixture model was defined in 100nm diameter. The results show that the Al₂O₃ volume fraction increases, the heat transfer rate and Nusselt number increases. All the numerical simulations were developed in ANSYS FLUENT. The result displays the rise of thermal transfer from the volume fraction concentration.

To avoid spread of novel corona virus, in the second week of March, state government advised to close schools & colleges till further announcement. There was no certainty about reopening. This was a decisive time for the education sector to switch from physical classroom teaching to online classroom teaching. The primary objective of our institute was continuous learning and facilitates teaching-learning process through online teaching. It is an observation that few courses are found to be difficult for students even in physical classrooms and teacher need to employ different active learning strategies to make class active & engaged. Thus same issue was found in online teaching. Therefore we employed micro learning strategy for the course Theory of computation at S.Y. B.Tech.(Computer Science & Engineering). "Micro learning is a holistic approach for skill based learning and education which deals with relatively small learning units.[1]" In this approach, micro level activities were designed, each activity containing a series of short videos, quiz & assignments. Thus we have designed 25 micro level activities for 2 units covering 25% curriculum. Flipped classroom is used as instructional strategy while implementing micro learning. These activities helped to engage students and keep active even in online environment. Tests conducted at the end of topic and perception survey showed that students enjoyed while learning.

The process of Teaching-Learning has evolved tremendously within the last 5-10 years. The mode of teaching is changed from normal blackboard classroom teaching to technological teaching. Due to the COVID-19 outbreak, the education system has been disrupted especially; it affects more for Higher Educational Institutes where students have come from various regions. The immediate lockdown in the country made the outside students reach their homes without any prior knowledge of its effects. Most of the education sector has switched to distance learning. Our institute has also adopted Virtual Learning. Various virtual platforms are available as the Learning Management System. We have adopted the use of ICT in education for the last 3-4 years. This helped us to handle the Teaching-Learning during a pandemic outbreak. We have used Moodle Learning Management System for Virtual Learning. Learners Centric MOOCs (LCM) model is implemented through LMS and the effectiveness is improved by adding Feedback and Assessment to it. The LCM model consists of structural elements: Learning Dialogs (LeD) in the form of short 10 to 12 minutes Videos, Learning by Doing (LbD) in the form of an assignment question or activity to do, Learning Experience Interactions (LxI) in the form reflection spot and discussion on the video provided and Learning Extension Trajectories (LxT) in the form of a small quiz on the video and resources. The major challenge for Virtual Learning is learner's engagement. We have added feedback to improve the teaching-learning process. The model is effectively applied for Third Year Computer Science and Engineering class. The course of Compiler Construction is taken in to account for the implementation. A total of 73 students were involved in this activity. The results of feedback from students are satisfactory. More than 83% of the learners have given positive feedback towards this technological change of teaching. Learner's engagement has improved to 30%.

Power Quality is major issue that has led to large amount of research by the industry and academic experts. The increased uses of the electronics in electrical utilities have created a need of monitoring the power quality and provide the mitigation to enhance the performance of the electrical equipment. With advancement in technologies and availability of various online monitoring tools, it is very important to assess and review these technologies. The increased rate of research in this field is proven to be beneficial to the consumers. Customers are now able to request for better quality of service and making the Power Quality issue more important. This paper provide an inclusive review of various application of signal processing on power quality events, analysis of artificial intelligent techniques to classify the signals and optimization techniques for decision making. The paper also explores the upcoming opportunities for power quality classification and further improvement in terms of higher performance of the electrical equipment.

Today's health information management system collects a huge quantity of healthcare data and information, that hold complex information related to patients and their medical conditions. In data mining, there has been an increase in the use of techniques on medical to determine usage patterns that are used in the analysis. Nowadays human disease is the main reason for human death, one person may suffer from more than one disease. This work is to predict disease by adding symptoms related to patients' condition and behavior. In this developed system we enter symptoms, as per patients' condition, the system analyzes symptoms and predicts diseases using data mining algorithm. The number of symptoms can be added in the search engine as per symptoms disease can be changed. This proposed work is developed to analyze the symptoms given by the user or patient for checking health condition, knowing their health conditions it predicts the disease without the need of a doctor, this work is implemented to save the time of patients'. This proposed system will not only predict the diseases also recommend the appropriate doctors from the doctor list based on a particular disease. In the existing system heart, kidney disease is predicted, whether the patient's heart, kidney are healthy, or not using the K-Nearest Neighbors algorithm. This system is developed for predicting the disease based on the patient's symptoms by using a data mining algorithm.

The use of hybrid composites now a days has been very attractive due to their light weight, low cost along with high strength to weight ratio. Lot of research is going on to develop the newer composites with improved mechanical, tribological and thermal properties. From the last two decades, Aluminium alloys have gained lot of attention owing to their practical usage and the ease of processing. Aluminium matrix composites are most versatile materials which has applications in advanced structure, aviation, marine and defence application due to their excellent properties. It is a known fact that stir casting is one of the economical method of fabrication of the metal matrix composite, moreover it is also easy to fabricate the composites by stir casting rather than other processes of fabrication. But, the quality of metal matrix composites being cast through stir casting route are highly dependent on the process parameters and achieving the homogenous distribution of reinforcement is a big challenge. In the present investigation, AA2024/SiC/Gr/flyash hybrid composites were fabricated with the stir casting technique (having reinforcement weight composition of SiC 10%, Graphite 5%, and fly ash 5%). The morphological characteristics of the developed Metal matrix composite (MMC) have been investigated using X-ray diffraction (XRD), scanning electron microscopy (SEM). The uniform distribution of the reinforcement particles clearly depicts the development of homogeneous composite.

In recent years, there is a remarkable rise in the use of electronic appliances in many homes and corporate offices. Such appliances include Air Conditioners, Smart Lights, Refrigerators, and CCTV Cameras, etc. To keep such appliances in a proper working condition, functional working of appliances needs to be checked. Changing the place of appliance, improper settings, cleaning of rooms, etc. lead appliances to failure. In proposed system sensors are used to track the functional working of appliances in real time or when there is a need arises to check working of the appliances before and after the maintenance is done. This sensor data is collected in database server. At database server, preprocessing of data is done to get accurate results. Then preprocessed sensor data are compared with the manufacturer's data (sensor data when the appliance is in ideal working conditions). For comparison of sensor data with the manufacturer's data, a Change Detection algorithm is used in the proposed system. The results of the Change Detection algorithm are shown in the form of graphs on the user interface at the server. This is accessed and analyzed using a mobile application in smartphones and a web browser in a desktop PC with, authorized login credentials provided to owners and technicians of appliances. This helps technician or the owner of appliance to identify the basic cause of appliance failure and do necessary repair whenever needed.

Face recognition is the most advanced way of authentication and authorization and it has been developed a lot since the last decade and such systems are now popular in fields such as security and commerce. This work revolves around facial recognition based automated user management system with active learning features the proposed work uses a combination of a couple of technologies to build such a system for user keeping which is foolproof and secure it also adds active learning to counter the problem of changing faces in youngsters. The system is recommended for schools, universities, corporate offices, and prisons.

Content-based advertising is a method by which we advertise on a video media based on a relevant topic assigned to the video. In digital advertising, the advertisements shown to a user is based on the user's behaviour on the internet. Streaming platforms are then used to target audience based on parameters like user's geo-location, interests, watch history, age, etc. In most cases, the advertisements shown are not relevant; an undesired impact is created. Content-based advertising helps to convey the message with increased efficiency and simultaneously optimizes its conversion rate. In this proposed system we take the video metadata as input and apply the NLP techniques for text classification which categories the video and assigns a relevant advertisement to it. The second module takes the video as an input. Thereafter the video is converted into N individual frames to tackle the video classification as an image classification problem. In this proposed system we train a Convolutional Neural Network to identify the topic of the video on an image dataset and compare its performance with a pre-trained model. We create the image dataset by downloading images from the internet. We also create a video advertisement's dataset by web scrapping. This proposed system makes sure that the user is shown the advertisement in reference to the video. This increases probability of the user visiting the client's website.

Ionosphere scintillation causes rapid and abrupt fluctuations in the intensity and phase of the signal due to the ionosphere irregularities. It is proved to be detrimental to the effective functioning of navigation systems. The reliability and integrity of GNSS system is dependent on the performance of signal tracking loops of the GNSS receivers which are adversely affected during scintillation. The study presents the analysis of the impact of scintillation on the receiver performance particularly carrier tracking loops which may provide cues of handling scintillation signals and overcome its drastic influence on the receiver functioning. The performance of the carrier tracking loop under scintillation is analysed and evaluated in terms of signal locking ability, correlator power, carrier to noise ratio and tracking error. The methodology involves generating simulated scintillation signals based on statistical model and modulating the real NavIC L5 signals with simulated scintillations to generate scintillated signal to test the performance of the software implemented carrier tracking loop. The study concludes with possible strategies such as adaptable loop bandwidth and extending integration time to subdue scintillation effects on receiver performance.

The C band microwave signals are widely used for Earth observation in the field of remote sensing by using synthetic aperture radar sensor. The coverage of Indian regions by Sentinel 1A SAR sensor in interoferometric wide swath mode, provide an opportunity to research and conduct studies in remote sensing areas from urban planning to disaster management applications. The sensor acquired images undergo calibration test to confirm the quality requirements. The foremost significant step to ensure the availability of the signal of Sentinel 1A on the ground surface is by designing a antenna system which tracks and monitor the signal strength. In this context, the following stages are significant in signal monitoring system: satellite downlink budget calculation to ensure minimum signal strength, designing and configuring antenna system to receive the signals and measurement system such as spectrum analyser to monitor the signal strength. The paper presents the mathematical analysis of designing a down link for receiving Sentinel-1A SAR signals. An antenna subsystem is implemented which includes the design of the parabola antenna with horn feed and the simulation of the same using Matlab platform to confirm antenna parameters such as gain, directivity, VSWR and beam-width which meets the practical requirements

The world is going through the biggest change in modern world, the climate change. And this is majorly due to our utmost reliance over fossil fuels. Researchers, industrialists and scientists around the globe are trying to figure out the alternate energy sources or at least the ones with the least poisonous emissions. To design an automobile machinery with such parameters that they would cause possibly the least pollution, a huge sum of money is spent on majorly executing experimentations repeatedly. The paper has shown the objective of testing of such emissions and with the help of known machine learning algorithms, predicting those harmful emissions. In other words, using statistical modelling to predict the engine emissions which is traditionally measured by an exhaust gas analyser. In this research, data of real-time engine emissions produced by burning of Bio-Diesel fuel is recorded and fed into machine learning algorithms for their training. Three machine learning emission models were built up to illustrate their emission ranges. Out of the three, results showed that Decision Tree based engine emission model showed the best results.

The decrease in the physical dimensions of the devices have sought the attention of research community due to quick response, high sensitivity and sturdiness of the devices. These devices in the form of nano resonators have been extensively used as sensors to detect the entity at submicron level as well as to identify the properties of matter at submicron level. With the process like chemical vapour deposition, lithography technique as well as mechanical exfoliation techniques, it has become possible to produce materials which are 2D in nature. The excellent mechanical and electrical properties of graphene as well as its complete plain geometry advocate it as an ideal material for the development of sensors used for identifying the object at nano level. Here an attempt is made to analyse the vibration characterization of graphene resonator in the form of membrane to understand the shift in the frequency by adsorbing the mass and change in the temperature. The tobacco mosaic virus is considered as a mass adsorbed onto the graphene nano ribbon based membrane. Along with the adsorption of the mass, the effect of variation in temperature is also introduced to observe the shift in the natural frequency of the graphene membrane based resonator.

The Plasma Electrolytic Method of Oxidation (PEMO ) is proved powerful for producing the wear and corrosion-resistant coating of the oxide layer for exclusive applications. This technique is having a better capability for industrial use for growing proactive coatings on material like Aluminium, Magnesium, Titanium for diverse application of lightweight and high temperature requirements applications. The paper consists of review of papers primarily based on the surface modification amendment method of plasma arc oxidation of aluminium and its alloy. Because the process characterized by the discharge generated by electrode, electrolyte composition and oxide coating morphology which might be crucial component for effectiveness of the technique. The purpose of the paper is to write the systematic review for electrodes, electrolyte compositions, and its effect in improving the characteristics of aluminium alloys. There is a large scope for enhancing the method and monitoring the electric parameters of PEMO for massive applications in regions of automotive wherein the modification in surfaces can replace the components by the lightweight aluminium alloy material. The attempt is made to pick the key elements inside the technique. The scope of designing numerous optimization algorithms and analytical modelling is a key area for further research which can help to screen the technique extra precisely to get an optimized coating microstructure.

A high performance digital system is the need of an hour, in the current scenario not only the area but the leakage power holds the key for the future devices. The development of handheld devices often gets restricted due to the limited power resources available in these devices. The conventional structure performs badly for these devices hence multiple design schemes like domino have surface for recent devices. The Domino logic circuits provide high speed operations in comparison to conventional structure. The problem of charge sharing, charge leakage in domino circuits results in improper output level which can be eliminated using Keeper and Pre-charge internal node technique. For achieving very low power all PMOS and NMOS transistors are conducted in sub threshold region. This paper has implemented ultra-low power Domino AND gate. Simulations has been done using Tanner 13 using 18u CMOS technology. A comparison has been carried out with different approaches available in literature and keeper circuit-based domino logic reveals least power consumption which makes it is suitable for ultra-low power devices.

This paper studies the performance of classical and quantum machine learning models for sentiment analysis task. Here, popular machine learning algorithms viz support vector machine (SVM), gradient boosting (GB) and random forest (RF) are compared with variational quantum classifier (VQC) using two sets of parameterized circuits viz EfficientSU2 and RealAmplitudes. For experimenting with VQC, IBM Quantum Experience and IBM Qiskit were used while for classical machine learning models, scikit-learn was used. It was found that the performance of the VQC was slightly better than popular machine learning algorithms. For our experiments, we have used popular restaurant sentiment analysis dataset. The extracted features from this dataset and then after applying PCA reduced the feature set into 5 features. Quantum ML models were trained using 100 epochs and 150 epochs. Overall, four Quantum ML models were trained and three Classical ML models were trained. The performance of the trained models was evaluated using standard evaluation measures viz, Accuracy, Precision, Recall, F-Score etc. In all the cases EfficientSU2 based model with 100 Epochs performed better than all other models. Efficient SU2 model with 100 epochs produced an accuracy of 74.5% and an F-Score of 0.7605 which were highest across all the trained models.

Heavy vehicle drivers in the Indian road transport industry are generally exposed to whole-body vibration (WBV) and shock loading resulting in musculoskeletal disorders (MSDs) in their different body parts. Not much work has been done in identifying the contribution of driver's personal and vehicle/road-related factors in the enhancement of vibration and shock exposure. This study has been conducted on 10 bus and 10 truck drivers from Northern India to investigate the role of these factors. Based on previous studies, the factors or predictor variables included were driver's age, body mass index (BMI), driving experience, age of vehicle, mileage, age of tyres, and seat pad thickness. 8-hours vector sum acceleration, i.e., (A(8)_s) and vibration dose value, i.e., ( VDV(8)_s) of 25% of the drivers were found to be more than upper limit values of ISO 2631-1. The WBV exposure magnitudes of acceleration and vibration dose value were much higher along the vertical z-axis than along the longitudinal x-axis and lateral y-axis. The results of univariate linear regression analysis found both vibrations and shocks to be related to the driver's age, body mass index (BMI), driving experience, vehicle speed, and road roughness. Similar types of results were observed from multiple regression analyses with the only exception that no association was found between BMI and WBV exposure in this case. The results of the study may help the authorities in minimising the risks associated with the driver's profession.

From Generations, Security methods have always been improvised on the basis of modernisation of Technology. Now a day's using man power for security have become less reliable as Humans can be manipulated using social/emotional hacking. Today most of the family members are employed and only the old aged members or toddlers of the family are left alone at home unattended and unguided. One of the best solutions to these problems is to use the things that are reliable and can't be socially hacked. The primary aim that is achieved by this technology is to look after the unattended and other important activities. Problems like this can be handled by using IOT which involves Surveillance System, remote access, automated security systems, Cloud Computing and many more. Vast variety of problems can be solved by this technology. This can be used at personal level, organisational level or national level. This paper basically describes how Internet of things (i.e. Connecting multiple uncommon devices using internet and giving them instructions remotely as per required) can be used to achieve reliable high level security and can be used to make working simple and easy in some other important fields. IOT has limitless potential; it has the capacity to replace some previous technologies.

Maximum power point tracking System (MPPT) is so important in PV systems to increase the efficiency of solar cells. So many methods are proposed to generate the maximum voltage from PV modules under different weather conditions. This paper proposed an intelligent method for maximum power point tracking using the P & O algorithm. The model contains a PV module connected to DC to DC boost converter. The PV System is tested under disturbance in the solar irradiation and temperature level. The simulation results show the maximum power tracker could track the maximum power accurately and successfully in all conditions tested. Comparison of various working parameters such as: tracking efficiency and response time of the system shows that the proposed method gives higher efficiency and better performance than the conventional perturbation and observation method. The voltage, current, and power of the Module can be measured through the P&O Method. The Fuzzy logic based Mppt controller is proposed in this method to increase the voltage Pv module. The proposed method used the fuzzy logic-based controlled (FLC) to initiate the control command to the output buck-boost converter as there is a change in the voltage and current across the PV panel. The modeling of the FLC-based MPPT controller is done for the PV module with the help of MATLAB/SIMULINK.

PyPSA is a Python-based open-source tool used for load flow analysis in the power system. PyPSA (Python for load flow analysis) is a leading tool, which is convenient for simulation and optimization of the power system network. It is a free software which regulates parametric valuation along with multi-temporal analysis in the power system. The Modern power system is the integration of various devices like Generators, Transformers, Bus bar, lines Protecting devices and load connected through it. Load flow analysis is used to determine the different types of parameters in the power system i.e. Voltage Magnitude, Phase angle, Power injected, power output and losses through the power system etc. Various kind of devices is utilised in modern power system analysis. Conventionally many techniques are adopted for power System analysis i.e. Mathematical modelling of the system and then calculation. These techniques consume very much time for the calculation. But, due to the advantage of Science and Technology, different types of new methods are developed. PyPSA is one of them. These methods are accurate, fast and reliable for power system analysis. In this study, PyPSA tool is used to analyse the IEEE 12 bus system for determining the voltage magnitude across each bus.

In this study, Bi₂O₃couple system sample materials were synthesized using solid state reaction method sintering each of them. Structural and electrical properties of these electrolyte samples for solid oxide fuel cells (SOFCs) have been evaluated by means of XRD, TG / DTA, SEM and four-probe method. In this work, (Bi₂O₃)1-x-y(Dy₂O₃)x(Ho₂O₃)y tenary systems have been investigated. As a result of XRD measurements, δ (cubic)-phase samples were obtained with a stable structure. As a results of electrical conductivity measurements, (Bi₂O₃)1-x-y(Dy₂O₃)_x(Ho₂O₃)_y tenary system, increase Dy₂O₃ molar ratio corresponds to a fixed molar ratio of Ho₂O₃ conductivity value falls was obtained.

Depleting sources of fossil fuels and environmental issues like air pollution and harmful toxic emissions from the combustion of these fossil fuels have made the search for their potential substitutes essential. Biodiesel is found to be one such widely accepted viable option as seen from literature. In this work, Pongamia oil biodiesel, Bioethanol and Biobutanol have been selected for blending with diesel. The analysis of exergy and energy of varying proportions of Pongamia-Ethanol-Butanol blends and diesel as fuels for a 4-stroke, single-cylinder CI engine has been carried out. Further, based on the formed equations, a computer program has been written to obtain the final output characteristics. Four blends namely, D100 (neat diesel), P50E50 (50:50 Pongamia-Ethanol blend), P45E45Bu10 (45:45:10 Pongamia–Ethanol-Butanol blend), P40E40Bu20 (40:40:20 Pongamia-Ethanol-Butanol blend) have been considered for the analysis. P50E50 blend shows a significant decrease in heat loss due to exhaust gases, net energy loss, destructive availability, and increase in energy efficiency, exhaust availability, and available efficiency output characteristics as compared to neat diesel. Hence, it is concluded to be the best potential replacement for diesel fuel from all the considered blends.

In this work framework request picture square size and tumultuous capacity control as a piece of information. Here this builds the adaptability and mix of a secret phrase. As the quality of a secret key relies upon number bits or characters. So proposed work store entire square as the mystery key of the client. For creating an alternate arrangement of pictures proposed work utilize tumultuous capacity where an alternate arrangement of muddling is feasible for a similar picture. The proposed plan will be usable anyplace and whenever with a low mistake rate just as a quicker outcome confirmation. This exposition work primarily centered around the snap-based methodology and mix with the proposed algorithmic disorderly approach. A test was done on a genuine arrangement of pictures and results that that proposed work has high join rate, low execution time when contrasted with past secret word creation calculation.

Gaussian noise has been the bane of any and every denoising process under the sun. Being a very corrosive noise with huge disruptive potential, this has received much attention form the image restoration community. Building on the premise, a novel framework is proposed to leverage multi-level image denoising that iteratively removes gaussian noise while recovering details lost during processing. This framework uses existing deep learning based CNN systems whilst enhancing the same by the addition of method denoising to the process. This framework is habile in competing with state-of-the-art technologies and outperforming them in some cases.

The Library Automation System is gaining more importance as the number of its users is increasing. Automation of libraries reduces the duplication of work, saves time, and brings accuracy and speed. It also increases efficiency in library services and boosts the quality of work. One such effective system is the Smart Library Automation System using Face Recognition. The Proposed system uses face recognition for entering and getting the details of an end user. Through this application, the book gets issued to the end-user by identifying the user with the help of face recognition and identifying the book using barcode capture. In our system, we are using dlib face recognition, which is 99.38% accurate. We have provided the validations on the user registration form so that we get the right information. The registration process captures the face of the user and book issue, and the book return process checks the details of the user. End-users of the application will be librarians, students, and teachers. Our project aims at making the tasks of the library easy and to make the book issuing and returning process more interactive and effortless for the user. Also, our system is responsible for preserving the details of book issue and return and paperless report generation.

String matching and searching problems are one of the classical hitches to the domain of computer engineering. There exist numerous variants of such algorithms, which can be categorized into dual classes; i.e. an approximate match and exact match algorithms. This paper engrossed on comparing prevalent algorithms of exact matching category in terms of their functionality and complexity along with critical opinions for a better understanding of the differences among them. The application of string matching is used in various fields like for intrusion detection in the networks, DNA matching in the field of bioinformatics, plagiarism checking for fraud detection, in the field of information security, pattern recognition, text mining, web searching, recommendation system, the document comprising, authentication system and web scraping. The uses are not only restricted to the fields termed above but also the notion has copious advantages for ongoing and forthcoming research work.

Image acquisitions are increasing day by day due to progress in social networking and digital technologies. Nowadays, with the evolution of various image capturing devices, an enormous quantity of complex images is being produced.content-primarily based image Retrieval (CBIR) is the answer to access images without difficulty wherein proper indexing and association are required. It makes CBIR a distinguished field in computer vision research. There are several uses of CBIR systems in day to day life for example medical, internet, scientific research and various other communication media. In the CBIR system, the user gives a query to obtain images from large datasets having a large number of images. In information transfer via electronic media using particular formats of data, images play an essential role. The extraction of information from communicated images is necessary with extra processing. In this paper, a comparative survey has been carried out on different content-based image retrieval implementation. These methods are determined by several authors for the feature extraction process of images and classification. This will help to plan the strategy for optimizing the CBIR system.

Hybrid metal matrix composite (MMC) reinforced with silicon carbide (SiC_p), alumina (Al₂O_3p) and graphite (Gr_p) are being preferred for industrial applications due to their lightweight, and lower densities of these combined materials and high strength at the molecular level. These developed hybrid composite materials have been utilized in the wide range of applications in automotive and aerospace industries. The manufacturing industries that are utilizing the hybrid Mg-MMC also go through the machining turning operations for application products. Therefore, it is very important for machining the hybrid Mg-MMC for the desired dimensional accuracy. The present experimental research was therefore aimed at investigating the average surface roughness height R_a while turning the hybrid Mg-MMC using the CCMT 09 T3 08 WF 1525 tungsten carbide insert. The machining parameters includes the cutting speed was 40 m/min, 80 m/min and 120 m/min, the feed rate was 0.08 mm/rev, 0.2 mm/rev, 0.4 mm/rev and the depth of cut was 0.2 mm, 0.5 mm and 0.75 mm. The average surface roughness height R_a was measured using surfcom 130A (profilometer). Experimental investigation found that the average surface roughness height R_a was lower at a high cutting speed and at a lower feed rate. In addition, the built-up edges were formed at a lower feed rate with all cutting speed values.

Shortages are quite common in command economics and inflation is a regular increment in the price of services and goods in an economy over a span of time. In this paper we established an EPQ model with life-time items with multivariate demand with markdown policy under shortages and inflation. We also discover an inventory model that gives the best markdown time with shortages and inflation and at the same time maximize annual profit. An inventory model by using mathematical tools is developed. The numerical experiments together with sensitivity analysis for relevant parameter is provided to show the behaviour of model.

Artificial intelligence and Deep learning techniques propose and provide effective mechanism for classification among several commodities like gender classification on basis of ridge count, spam mail classification and detection etc. Here we have proposed a hybrid module on basis of available AI and ML techniques by which we can achieve more than 90% accuracy for any provided test dataset. We have included over 50423 samples, out of which we use 66 percentage of data for training purpose of our model and 34% remaining sample we use as test dataset, with 8 fold we have achieve approximately 96% accuracy. For collection of dataset and processing of dataset we gone through several phases which include extraction of feature (EoF) using feature extraction technique, for cleaning of dataset we have use dimension reduction technique factor analysis(FA). In next phase for classification of flowers we have used classification techniques in which we found the accuracy score of j48 classifier is higher than Naïve Bayes and Jrip algorithm. Hence the choice of j48 classifier for classification is right.

The human voices are very flexible and contains a mess of sentiments or emotions. Feeling or emotions in speech incorporates extra vision about human activities. Recognition of various emotions from the human speech signal is very stretching ingredient in human computer interaction. Through in addition analysis, we can higher recognize the rationale of human beings or people, whether they are not happy with the service clients, happy customers, encouraging folks or inspiring fans. Deep Learning strategies have been as of lately proposed as an option in contrast to conventional techniques in Speech Emotion Recognition (SER). The Emotion of a speaker can be easily govern by the humans because it the human nature to understand the complexion of a person by just guessing the flow of speech, but the domain of emotion or sentiment recognition in the course of machine learning is an open circle of research. In this intended project, we perform speech information evaluation on speaker discriminated speech signals to hitupon the warmth of the person speakers involved inside the verbal exchange. we're analyzing exceptional techniques to perform speaker discrimination and speech evaluation to locate efficient algorithms to carry out this task.

In modern science there is a rapid development of artificial intelligence, image processing has gradually fascinated and inspired the attention of many researchers in the field of artificial intelligence and has become an interesting and demanding task. The main idea of Image caption is to automatically generate natural language descriptions according to the information observed in an image, this is an important portion of scene understanding, which combines all the knowledge and information available of computer vision and natural language processing. The use of image caption is broad and noteworthy, for example, the understanding of human-computer collaboration. This paper reviews the related methods and focuses on the attention mechanism, which plays a vital role in computer vision and is broadly used in image caption generation tasks. Furthermore, the advantages and the shortcomings of these methods are discussed, providing the commonly used datasets and evaluation criteria in this field. Finally, this paper proposes some open challenges in the image caption task.

This paper is designed to lay emphasis on a regenerative form of power generation. A conventional leaf spring is taken and its plates are replaced with piezoelectric plates in order to convert vibrational energy obtained from unevenness and bumps on the road into electrical energy to feed the battery. The plates are replaced alternatively to ensure that the overall structural integrity of the model is not affected negatively. The model is created in SolidWorks and static evaluation is carried out in ANSYS. The stress acting on each piezoelectric leaf is obtained. The stress so obtained is used to calculate input AC voltage for each plate and this voltage is used to estimate DC voltage and DC current using NI MULTISUM software. The procedure is repeated with varying the basic parameters like the thickness of plates and the number of plates to find the optimal case in which maximum voltage generation is observed. Further, the time required to charge the on-board lead battery and the auxiliary battery is calculated. The project aims to find out the optimal case for an Indian road scenario, which will be able to feed the on-board battery of an E-rickshaw to enhance its average running time.