bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of Magnus Force on Flow over Cylinder and Heat Transfer Investigation: A Computational Fluid Dynamics Approach
Authors: Goyal Shubham , Gupta Sanjeev Kumar , Kukreja Nitin , Verma Harshita , Yadav Neha , Yadav Harsh 
Published: May 2021

Abstract
This computational study deals with the forced convection through horizontal cylinder which is performed in the CFD Lab, Department, Mechanical Engineering, GLA University, Mathura. The convective heat transfer coefficient is measured for two different cases stationary cylinder and rotating cylinder. The computational analysis was performed by using commercial CFD package ANSYS-Fluent. This analysis is done because we can’t get the pressure and velocity values in the full domain by using the governing equations. The contours of pressure, velocity and temperature are determined to capture the behaviour of flow throughout the region. Computationally determined values of local heat transfer coefficient are compared with the theoretical values obtained by using governing equations. The effect of the Magnus force is measured on the computational value in such way whether there is any increment in heat transfer coefficient or not. The nondimensional numbers as Nusselt number (Nu), Reynolds number (Re) and Prandtl number (Pr) are used to find the results of heat transfer. It is found that heat transfer is more efficient in case of rotating cylinder in comparison with stationary cylinder. The computationally determined results are found in well agreement with the analytical result.
Exhaust system of commercial vehicle: a review
Authors: Yadav Pawankumar , Kothmire Pramod 
Published: May 2021

Abstract
In Automobiles like Truck, Bus, Car, and other commercial vehicles, various exhaust emission norms like Euro IV and Euro VI are considered for a non-polluted environment. This paper focuses on increasing engine and vehicle performance of commercial vehicle by reducing back-pressure and noise due to after treatment systems, considering exhaust emission norms. Back-pressure in exhaust systems is calculated with advanced Computational Fluid Dynamics (CFD) technologies like ANSYS Fluent, GT Power. Backpressure in the exhaust pipe is reduced by varying length, diameter, number of bends, exhaust mass flow rate and bending angle of exhaust pipe. Narrow band noise in vehicles is predicted by Large Eddy Simulation (LES). Selective Catalytic Reduction (SCR) converts harmful NOx to harmless N2. SCR non-linearities are calculated by CFD code CONVERGE and TRIZ method. SCR urea deposit is minimized by proper nozzle position of urea spray. Diesel and gasoline particulate filter is used to filter particulate matter in diesel and gasoline engine respectively. This research focuses on the optimization of commercial vehicle exhaust systems.
Optimization of Heat Transfer Coefficient through Micro channel using CFD
Authors: Kukreja Nitin , Gupta Sanjeev Kumar 
Published: May 2021

Abstract
This paper provides a computational examination of the 3D (three-dimensional) heat flow and heat transfer moving in a rectangular smaller scale channel and utilizing water as a cooling liquid. The miniaturized scale channel utilized is having a width of 57 μm, profundity of 180 μm and length of 10000 μm. The work is engaged to build the heat transfer rate in a smaller scale channel utilizing expanded surfaces called blades and the examination is done at various Reynolds number. Computationally work is approved through the expectation and correlation with the current work. The augmented estimation of Reynolds number shows the decrement in the heat transfer. The examination of coefficient of heat transfer has been completed over the miniaturized scale channels, which demonstrate the surmised variety of temperature along the course of stream. Exact presumptions introduced in the balance technique give a brief look at genuine circumstance and the whole work is anticipating another thought of blade on the channel to build the heat transfer rate. In addition, other blade structures examination over the channel demonstrated the variety of heat transfer and the last work is engaged to discover the best effective approach to expand the heat transfer rate.
Simulation and Analysis of P-P-N 10T SRAM cell for IoT based devices
Authors: Bansal Saloni , Tomar V.K 
Published: May 2021

Abstract
Ultra low power integrated circuits got the major attention due to its lower power dissipation in the era of Internet of Things (IoT) based smarter devices. In this context, a P-P-N based 10T SRAM cell has been designed and simulated on cadence virtuoso tool with GPDK 45nm technology node at supply voltage ranges from 0.6V to 1V. The various parameters such as static noise margin, read/write power, read/write delay of the 10T SRAM cell are determined out and compared with other considered topologies. It is interesting to notice that 10T SRAM cell shows commendable improvement in read static noise margin (RSNM) i.e. 36% and 46% as compared to conventional 6T and differential 8T SRAM cells respectively. The 10T SRAM cell also has reduction in read power of 38.52% and 38% as compared to conventional 6T and differential 8T SRAM cells respectively. The read delay of P-P-N based 10T SRAM cell is improved by 40% with compared to conventional 6T SRAM cell.
A Survey on Image Encoders and Language Models for Image Captioning
Authors: Sharma Himanshu 
Published: May 2021

Abstract
Generating a natural language explanation for a given image is known as image captioning. An image captioning method aims to determine the significant objects present in an image together with the relationship between these objects. Also, the model has the capability to describe an image by a syntactically and semantically correct sentence. For image encoding, convolutional neural network {CNN] is applied and for producing natural language descriptions for a given image, language models (RNN & LSTM etc.) are employed. In this paper, the image encoders and language models used by the state-of-the-art image captioning models is discussed.
Design and simulation of a Mine Proof Mechanism
Authors: Chaubey V K , Rawat M K 
Published: May 2021

Abstract
The issue of security is very paramount in every organization. The traditional mine proof vehicles with a solid plate hull provide protection against very small IED (improvised explosive devices) & MINES. This led to lives being lost more due to physical injuries by shock produced and a large change in momentum in very small time, that made organs over pressured and fatality. The present analysis deals with the application of a mechanism filled with Nitrogen gas to provide the cushioning effect of damper and using that pressure and Kinetic energy of gases to be utilized in acting against the mechanism forcing the compressed gases to break the safety valve and move into a reserve container which has various attachments and the pipes of steel take that heavily pressurized air into the compartment. The compartment having an inserted airbag type structure will be filled with air and it will make the compartment a big air stuffed structure to damp shockwaves. The designing and the strength analysis of the structure is done with the help of CATIA & ANSYS. The result was not very different except we achieved a reduced chance of physical and secondary deaths. The flat hull was then replaced by a V shaped hull which shown a reduction in 66% of pressure concentration on the vehicle hull. By using the combination of damping container system and a V monocoque hull the blast force was mainly diverted and the overall casualties can be reduced.
Artificial intelligence based Parameter Optimization Technique for selection of Optimal Real-Time Scheduling Algorithm
Authors: Kumar Ajitesh , Kumari Mona 
Published: May 2021

Abstract
In Modern days, real time system plays an important role in our modern and digital society. The success of any real time application is totally depending upon the selection of optimal scheduling algorithm. In real time application every task should have the nature of deadlines and time when they arrived, on the basis of these parameters we observe the response time of different scheduling algorithm then we select the optimal algorithm for a particular application. So in this paper our aim is to reduce the complexity of real time system researcher for selection of scheduling algorithm for a particular application. This artificial intelligence based approach is an extent the state of any real time system in the area of scheduling. This approach works in any uni-processor system. Introduction
Rating of Various Indian Airlines on various parameters using Twitter Data
Authors: Garg Hitendra 
Published: May 2021

Abstract
In today’s world, e-commerce markets runs on the sentiments of the customers as they provides real feedback of the products or services. In such scenario, the companies tries to collect data from different social media platform like instagram, Facebook, twitter, and other sites where customers places their reviews and feedback about their experience on various parameters. These organizations analyze these data as per their requirements for market analysis, recommendation systems, feedback of the product/service, sentimental analysis etc. In this proposed work, feedback/reviews of various Indian airlines like Air-India, Indigo, Go-Air, Jet airways, Spice-Jet.is collected from twitter to rate the airlines services on various parameters like food quality, staff, delay in time, turbulence, aircraft condition and value for money parameters.
Simulating and Analysing delay in Indian Railways
Authors: Pradhan Rahul , Kumar Ashutosh , Kumar Mayank , Sharma Bhakti 
Published: May 2021

Abstract
Delay is one of the serious issue all over the world in railways, however it becomes more important to country like India having the top four biggest railway network all over the world and where the majority of the population depends on railways for making their journey’s in different parts of our country. Categorically most of the train in Indian railway not able to run on its schedule time which in turn affects the passenger to reach their destination timely. So we have make a small step in order to learn and analyze these problems and its factor we have used a real world dataset from internet and perform simulation on the data using regression to predict the total delay take place while planning a particular journey from a provided date by a passenger and our approach accuracy is promising.
An Analytical Study of Aadhar based Information System via Big Data’s MapReduce Framework
Authors: Shankhdhar Ashutosh , Singh Akhilesh Kumar 
Published: May 2021

Abstract
Aadhaar is a 12-digit identification number provided to every Indian individual which also includes children and infants. This is used to identify every Indian individual uniquely. This is issued by UIDAI (The unique Identification Authority of India) for free of cost. This unique identification number carries many wonderful advantages. Firstly, it provides a unique identity to every individual whom everybody can trust, no matter in which state they are, in whole country. This unique number can be used to avail different schemes like Pradhan mantri ujjwala yojna and gas subsidy, to open bank accounts and for other government transactions or benefits. This paper shows the use of Aadhaar data set to answer several queries which can be very useful for the government or the concerned authority in various scenarios. Since the Aadhaar data set of all citizens of Indian is a huge data set, big data with its different methods such as Map and Reduce algorithm is very useful in fetching the required query’s answer in a more efficient and faster way.
Modeling of Acoustic emotion recognition using Artificial Intelligence and Machine Learning
Authors: Rathor Sandeep , Khandelwal Diksha , Nigam Himanshu , Tomar Sahil 
Published: May 2021

Abstract
The emotion is a kind of language that can be understand by speech. If a machine can understand the emotions by its intelligence, then it refers as artificial intelligent. Therefore, in this paper we proposed an artificial intelligence technique for recognizing acoustic emotions. In this paper, the modeling of acoustic emotion is done by the fusion of classifiers such as MLP, SVM, KNN, Random forest and voting classifier. The voting can be ‘Soft’ and ‘Hard’. In hard voting the output is proportional to the highly voted or favorable class where as in soft voting the output is proportional to average voting. The best combination that we found with the fusion of MLP, SVM, Random Forest classifiers. The voting in this case was soft voting with the accuracy of 88.09%. It is higher than any of the single classifier. The proposed model is executed on the standard datasets i.e. Ravdess dataset.
Application of Monte-Carlo Simulations in Estimation of Pi
Authors: Sharma Rajkumar , Singhal Piyush , Agrawal Manoj Kumar 
Published: May 2021

Abstract
The term Pi can be defined as the share of the boundary of any circle to the diameter of that circle. Despite the circle’s dimension, this ratio is the same for all circles. Sometimes it is approximated as 22/7. In decimal form, the value of Pi is approximately 3.14. These approximations result in an error during precise calculations because actually, it is an irrational number. Its decimal representation is non-repeating & non-terminating. In this paper, an effort has been made to estimate the value of Pi using Monte Carlo Simulations.
Implementation of UART Design for RF Modules Using Different FPGA Technologies
Authors: Kumar Vivek , Rastogi Aksh , Tomar V.K. 
Published: May 2021

Abstract
This paper is focused on the designing of UART (Universal Asynchronous Receiver Transmitter) for RF based modules, which is a type of serial communication protocol, mainly used for short-distance, low speed and low-cost data transmission between two embedded systems or computer peripherals. These days RF-Microcontroller modules widely uses UART protocol for the interface with other hardware. A reduced FSM (Finite State Machine) UART design has been implemented on different FPGAs. The maximum achievable speed and their corresponding power consumption are calculated using these FPGAs. The proposed design is implemented using Verilog HDL and for simulation purpose, Xilinx ISE 12.1, 14.7, Xilinx Vivado 2018 and Intel Quartus Prime 19.1 are used. The smallest value of maximum power consumption i.e. 20.67mW at 105.47MHz frequency with 180nm technology node is achieved by Intel Max V among all the Intel and Xilinx devices. Furthermore, the maximum achievable frequency i. e. 769.48 Hz has been found in Virtex 4 FPGA device. Xilinx Virtex UltraScale+ devices occupy the minimum area which provides 16-nm FinFET Technology node.
Diabetes Prediction using Machine learning and Data Mining Methods
Authors: Ram Anant , Vishwakarma Honey 
Published: May 2021

Abstract
Diabetes mellitus, commonly known as diabetes, is a metabolic disease. It is an extremely regular disease to the humankind from young to oldster. A persistent disease appears when blood glucose level is too high. Hence, to reduce the increasing rate of diabetes, diagnosing diabetes is very important. Data Analytics is a methodical procedure of examining and recognizing the concealed pattern from huge measure of information to reach conclusions. In medical science, this methodical procedure is implemented by using different machine learning algorithms to analyze the medical data like K-Nearest Neighbors, Support Vector Classifier, Logistic Regression, Gaussian Naive Bayes, and Random Forest. The objective of this research is to utilize significant features rather than using all the features. Therefore, we performed the data cleaning along with the potential feature selection and then used the Logistic Regression. Proposed approach outperform with some existing approaches that are using the machine learning algorithms.
Thermal and Structural Analysis of Disk Brake using Finite Element Analysis
Authors: Pachauri Saurabh , Gupta Naveen Kr. , Singh Nagendra 
Published: May 2021

Abstract
The present paper discusses and examine a comparative study of the materials of the carbon ceramic matrix and the gray cast iron disk. This disk brake research is used to develop the braking mechanism of passenger cars. The Ansys package used to determine the distribution of temperature, induced heat flux, equivalent stress and deformation due to heat through the disk brake. To analyze the temperature distribution across the disk using axis-symmetric components, steady state thermal analysis was performed. Further structural analysis is often performed through thermal coupling analysis. Competitive analysis of disk brake material that yields less deformation and equal stress (von mises stress) at low temperature around the disk is feasible. For better validity, both outcomes are compared. Therefore, both findings provide a better understanding of the thermal characteristics of the disk brake rotor and enable the automotive industry to create an optimal and reliable disk brake rotor.
Efficacy of Volume of Fluid Method in Computational Simulation of Sloshing Phenomenon
Authors: Joshi Aditya Y. , Saikia Pranaynil , Rakshit Dibakar 
Published: May 2021

Abstract
The present study deals with the analysis of stochastic transient pressure variations and wall impacts for scaled down models of LNG carriers by using the VOF technique for interface characterization. Numerical simulation of sloshing under sway using multiphase liquid-gas condition has been carried out. Use of VOF method for multiphase numerical simulation is compared with the results of previously performed SPH study and established sloshing experiments. The efficacies of the VOF interface capturing technique is established by comparison with high-resolution images taken during sloshing experiments performed under the same external excitation frequency, amplitude and fill level. The pressure data from experiments when compared with respective simulations involving SPH and VOF methods helps to capture the fluid flow behaviour and intricacies they can handle.
Analysis of Elliptical Wing Type Bird Inspired Device
Authors: Kumar M H , Dorlikar P 
Published: May 2021

Abstract
Technology advancements have made the use of Unmanned Aerial Vehicles (UAV) in many applications. This paper aims at performing stress analysis of elliptical wing type birds using ABAQUS. The wings considered for investigation are elliptical wings of two birds having low aspect ratio. Aerodynamic forces like lift and drag are calculated and applied on proposed wing design CAD models to obtain results of stresses and structural deformation at different altitude. The material used for wing structure is carbon fiber for its various advantages over other materials. Further, shape optimization of wing structure has performed to reduce the stresses at critical regions and to reduce volume of material. This wing design analysis helps designers to build UAV in optimizing manner. In addition to above investigation, various flapping wing mechanisms 2D in SAM and 3D in ADAMS have made based on curves that are obtained by tracing the tip of wings of selected birds in TRACKER.
Generalized system of relaxed cocoercive variational inequalities governed by nonexpansive mappings
Authors: Gupta Sanjeev 
Published: May 2021

AbstractThe objective of this paper is to study the generalized systems of relaxed cocoercive variational inequalities associated with six nonlinear operators. We proposed three steps explicit iterative methods involving projection operators and give the equivalent fixed point problem of the generalized systems of relaxed cocoercive variational inequalities. This fixed point problem suggests to us the three steps explicit iterative algorithms to obtain an approximate solution of the system under consideration. Strong convergence results are obtained.
A Experimental and Numerical Approach to Evaluate Thermal characteristics a of Heat Pipe
Authors: Rawat M K , Gupta N K 
Published: May 2021

Abstract
Nanofluid as working fluid for the improvement of thermal performance, in case of heat pipe, is the newly emerging area of research. Superior thermal characteristics of nanofluids attracted the researchers towards the application of nanofluid in heat pipes. In present study, a 2D analysis is applied to evaluate the thermal performance of heat pipe having CeO2/H2O nanofluid. The heat transfer analysis of heat pipe having nanofluid (0.5, 1.0, &1.5 wt. % concentration) at operating temperature of 60, 80, 100,& 120°C has been done numerically through CFD simulation and results was compared with the experimental results. The results predicted by numerical analysis show that the application CeO2/H2O nanofluid diminishes the temperature of surface wall and thermal resistance of heat pipe as compared to that of water. The efficiency as well as effective thermal conductivity of the heat pipe increased with the use of CeO2/H2O nanofluid as compared to that of water heat pipe. A good agreement has been observed between experimental and numerical results. The present study concludes that heat pipe using CeO2/H2O nanofluid as working fluid has better heat transfer characteristics than the water.
Automated Detection of Coronary Artery Disease using Machine Learning Algorithm
Authors: Sinha Dibakar , Sharma Ashish 
Published: May 2021

Abstract
Data mining, an excellent development technology for discovering and gathering essential knowledge from vast data collection that can help analyze and draw up trends for decision-making in the industry. Talking about the medical sphere, data mining can be used to uncover and withdraw useful data and trends that can be helpful in clinical diagnostic results. The research focuses on the diagnosis of heart disease, taking past evidence and information into account. To achieve this SHDP, non-linear SVC with RBF kernel algorithms is designed to perfect this SHDP (Smart Heart Disease Prediction). The final is a useful algorithm to look for the right combination of hyper parameters to increase the precision of the algorithm (C, α). The requisite data was arranged in a structured way. The following features are derived from medical profiles for the estimation of the risks of heart failure in a patient: BP, age, sex, cholesterol, blood sugar, etc. The collected characteristics serve as an input to the Navies Bayesian heart disease prediction classification. The data collection used is divided into two parts, 80% of the data are used for preparation, and 20% are used for research. The method suggested includes data collection, user authentication, and log in (based on application), classification through Navies Bayesian, prediction, and safe data transmission via the AES application (Advanced Encryption Standard). An average accuracy, specificity, sensitivity, precision, 93.53% f-score, 89.22%, 91.24% and 86.98%, respectively. This method is also possible in clinical settings to help clinicians predict cardiac arrest.