bluuebunny/crossref_metadata_2025_split huggingface dataset:
Model of weld beads geometry produced on surface temperatures by Wire and Arc Additive Manufacturing (WAAM)
Authors: Manokruang S. , Vignat F. , Museau M. , Linousin M. 
Published: March 2021

Abstract
Wire and Arc Additive Manufacturing (WAAM) is an Additive Manufacturing (AM) technology that knows a strong interest in recent years. With this technology, the combination of an electrical arc welding and a metallic wire feedstock is used to manufacture parts layer by layer. As part geometry depends strongly on deposition conditions, this study is focused on the characterization of single bead walls and their geometrical evolutions according to welding parameters and surface temperatures. Our experiment has consisted of the production of walls manufactured with a 5083Al wire and built from 1 layer up to 10 layers with several surface temperatures (Tsur fixed at 100, 200, 300 and 400°C). Before the deposition of each new layer, we ensure that the substrate is at the correct temperature using a thermometer in order to guarantee constant welding conditions. Those welding parameters have been kept constant with a Wire Feed Speed (WFS) at 5 m/min and a Travel Speed (TS) at 0.6 m/min. Wall bead geometry and dimensions, width (w) and height (h), have been then measured using a 3D scanner. Results are used to feed a predictive model developed with a circular model curve fitting each top layer cross-section of walls. Data form this study, coupled with thermal simulation, will allow us to predict faithfully parts shapes and to control their dimensions.
Ensemble Flower-Pollination Algorithm for Automatic Breast Cancer Classification using Haar Features
Authors: Sannasi Chakravarthy S R , Rajaguru Harikumar 
Published: March 2021

Abstract
Breast cancer is a deadly disease which reports a higher mortality rate, every year. This type of cancer is more common in women of developed countries while compared with the incident rate in developing countries. The objective of this work is to propose a methodology to increase earlier breast cancer detection. The methodology makes use of ensemble-based classifiers namely histogram-based Gradient Boosting Machine (hbGBM), Gradient Boosting with Light GBM (lGBM), and Gradient Boosting with CatBoost (GBCB) algorithms. The paper adopts the Mammogram Image Analysis Society (MIAS) database for testing the effectiveness of the algorithms. Haar wavelet transform is used for feature extraction and Flower-Pollination Algorithm (FPA) is employed for selecting the best features. Thus, a flower-pollination based haar wavelet feature with three different ensemble-based classifiers is proposed for the automatic mammogram classification. The performance results are then compared briefly by using some benchmark metrics such as specificity, sensitivity, precision, accuracy, and precision, F1 score, and Matthews Correlation Coefficient (MCC) analysis. The result reveals that the highest classification accuracy is obtained for ensemble GBCB based FPA algorithm i.e., 91% when comparing with other existing models.
Analysis of EEG Signal for the Estimation of Concentration Level of Humans
Authors: Velnath R. , Prabhu V. , Krishnakumar S. 
Published: March 2021

Abstract
Especially when studying or thinking, focus is an important part of our lives. To understand humans’ concentration mechanism, the brain activity is monitored using EEG signals. Electroencephalogram (EEG) is test used to track and record the brain wave patterns based on the electrical activity of the brain. It is a very versatile tool for the detection of brain activity. Based on concentration and thinking the brain waves will get change due to their change in brain activity. The variations in brain waves are analysed and the features are extracted using various methods. EEG data are collected for different persons under two different age groups of 20 to 23 age and 29 to 31 aged people because the concentration varies with respect to age. The characteristics are extracted from the collected EEG signal using FFT, Mean, Standard Deviation (SD), Median and Mean Root Square. The concentration level is determined by comparing the extracted features for different aged individuals.
Design of Density Clustering In Diabetic Retinopathy Based Eye Fundus Segmentation
Authors: Udaya Kumar Naluguru , Nikitha Thelapolu , Bachu Srinivas 
Published: March 2021

Abstract
In order to prevent further complications, we learned in this paper that earlier diagnosis is critical in Diabetic Retinopathy (DR). The disease can be classified into one of two stages (the early stage of non-proliferative and later stage of proliferative diabetic retinopathy) of Eye Fundus Images (EFI), diagnosed on the basis of the presence and quantities of a complex series of lesions such as microaneurysms, haemorrhages or exudates. Therefore it is important to properly segment regions of potential lesions to demonstrate and classify the lesions and the degree of DR. Density clustering approaches are promising candidates for the isolation of individual lesions, and can be used along with effective methods for vascular tree elimination, extraction and classification. In this article, our approach, findings, tradeoffs and assumptions for segmenting and detecting individual lesions are reported.
Comparison of Paul Viola – Michael Jones algorithm and HOG algorithm for Face Detection
Authors: PNithish Sriman K , Raj Kumar P , Naveen A , Saravana Kumar R 
Published: March 2021

Abstract
The computer technology which helps to find the face of a person in video and image is face detection. It is like a biometric application that finds a person by analyzing and comparing the person’s face patterns. The face detection technique helps for security purposes, and also it has an rising interest in many fields. This technology has received good attention. It has some good applications based on law enforcement. For detecting face in an digital image, we have lot of algorithms. In this, Viola Jones algorithm and histogram of oriented gradients is used to detect the face of a person. The paper is proposed for a comparison between viola jones and Hog. By analyzing this we can find the gender, age and also emotions of the person. Here different type of images were used for detection. The Matlab tool and Jupyter is used for implementing this face detection process.
Wavelet Based CNN for Diagnosis of COVID 19 using Chest X Ray
Authors: Gunasekaran Suresh , Rajan Santhiya , Moses Leeban , Vikram S , Subalakshmi M , Shudhersini B 
Published: March 2021

Abstract
Human race has overcome numerous pandemic and epidemics like Spanish flu, SARS, cholera, plague, etc since ages and COVID 19 pandemic is one among them. COVID 19 being the recent one, is much different than the others due to the contribution of AI in diagnosis and prediction of COVID 19 patients. Among the various use cases, one widely used area is medical diagnosis. AI and deep learning based algorithms are exploited enormously by data scientist to support radiologist in early prediction and detection of corona patients. Subsequently, in this work, we utilize wavelet based Convolutional Neural Networks for detecting and recognizing of COVID 19 cases from chest X ray images. Currently, previous works utilize existing CNN architectures for classification of healthy and affected chest X rays, however these networks process the image in a single resolution and loss the potential features present in other resolutions of the input image. Wavelets are known to decompose the image into different spatial resolutions based on the high pass and low pass frequency components and extract valuable features from the affected portion of lung X ray efficiently. Henceforth, in this article, we utilize a hybrid CNN model of wavelet and CNN to diagnose the lung X rays. The proposed CNN model is trained and validated on open source COVID 19 chest X ray images and performs better than existing state of the art CNN models with an accuracy of 99.25%, ROC-AUC value of 1.00 and very less false negative values. Further, the performance of our model is validated by Gradient Class Activation Map visualization technique. The visualization of feature maps clearly indicates that our proposed network has perfectly extracted features from the corona virus affected portion of the lung.
Deep Learning Based Multilevel Classification of Alzheimer’s Disease using MRI Scans
Authors: Raju Manu , Thirupalani M , Vidhyabharathi S , Thilagavathi S 
Published: March 2021

Abstract
Alzheimer’s disease is one of the most frequently studied diseases of the nervous system although it has no cure or slowing its progression. There are various options for treating the symptoms of Alzheimer’s disease in different stages and as the disease progresses over time, patients in their various stages need different treatment. Diagnosis of Alzheimer’s in the elderly is quietly difficult and requires representation of a discriminatory factor in isolation due to similar brain patterns and pixel strength. Deep learning strategies are able to learn such representations from the data. In this proposed work we perform multilevel classification of Alzheimer’s disease ie; Mild Demented, Moderate Demented, Non Demented and Very Mild Demented using transfer learning with VGG16 using Fastai. This approach results in 99% predictive accuracy which means a significant increase in accuracy compared to previous studies and clearly demonstrates the effectiveness of the proposed methods.
Brain Tumor Detection Using Spatial Filtering Algorithm
Authors: Sritha P , Valarmathi R S , Brundha K , Dhanusri V 
Published: March 2021

Abstract
In recent decades, many people suffered from brain tumor disease because of the living habits and the stress factors, The tumors in brain is detected by the magnetic resonance imaging (MRI) image by means of filtering and segmentation process.In particular of the image processing techniques Medical Image processing technique is applied to identify the tumors in any parts of the body easily and it saves time. A model was proposed in this paper to detect the brain tumor by means of Spatial filtering algorithm. In this algorithm, a new techniques which combines the segmentation and filtering mechanism to detect the growth of cells or tissues in the tumor. The simulation and experimental result has attained about 90.6 % accuracy, 88.6% specificity and 92.56% sensitivity in detection process of tumors.
RETRACTED: Detection and Classification of Breast Cancer Using improved Grey Wolf Algorithm
Authors: Senthil T , Deepika J , Nithya R. 
Published: March 2021

Abstract
Breast Cancer is the hazardous infection among young ladies and most significant reason for developing destruction rate. Physically anticipation of this affliction takes longer hours and structures are to be had in significantly less number, there’s motivation to expand a mechanized forecast machine for early expectation and visualization of malignancy. The sort of considerate and threatening tumor are accomplished the use of type methodologies of device becoming acquainted with wherein the device is found from the past records and predicts the sorts of late sources of info. This paper is an overall report on the execution of models utilizing Logistic Regression, Support Vector Machine (SVM) and Gray wolf algorithm(GWO). The outcomes are assessed with the exactness, accuracy, affectability, explicitness and False Positive Rate boundaries for every calculation and are thought about. These procedures are coded in Java and executed in MATLAB, the Image handling Environment. Our investigations have demonstrated that Gray wolf is the best for prescient examination with an exactness of 92.7%.We surmise from our test results that SVM is the appropriate calculation for expectation and in general Gray wolf has performed well close to SVM.
RETRACTED: Adaptive Beam forming algorithms for wireless Communication using LABVIEW
Authors: Ramya M. , Thamizharasan V. , Parthipan V. 
Published: March 2021

Abstract
Adaptive antenna arrays are being developed to cope with the high capacity requirement of the 5G wireless communications systems. As adaptive antenna arrays focus narrow high gain beams towards the desired users and nulls towards the unwanted interferers, both coverage and capacity of the network can be improved. The capacity of a Wireless network depends on the size of the antenna array, the beam pattern used and the speed with which the beam-former and Direction of Arrival estimator. To achieve the capacity demand required by a growing number of subscribers, smart antenna systems are used in the present cellular systems. In these systems cell-splitting and sectoring techniques are adopted to improve the capacity. The main disadvantage of these techniques is that decrease in trunking efficiency. It has been established that the smart antenna systems will provide a better solution for the capacity problem. Development of smart antenna includes design of antenna array and adjusting the incoming signal by changing the weights of the amplitude as well as phase using efficient Digital Signal processing algorithms using LabVIEW.
VLSI Implementation Of High Speed Low Power Design Using Hybrid Power Gating Technique
Authors: Pousia S , Murugan K 
Published: March 2021

Abstract
Nowadays, low powerhigh speed CMOS design is one among the challenging issues. As the technology is scaling down, the static power consumption has turned into a remarkableconcern. The proposed methodology incorporates the following technique such as sleep technique, stack technique, sleepy stack technique, sleepy keeper technique, leakage control transistor technique (LECTOR) and sleepy keeper leakage control transistor technique (SK-LCT) for leakage power reduction. The proposed power gating techniquelead to low power,high speed CMOS design. The xor gate, xnor gate, half adder & 6T sram cell is outlined using newly proposed power gating technique for a low power high speed design.When compared to the conventional methodology xor gate saves 19.95 % of power & 33.75% of delay, xnor gate saves 12 % of power & 23.29 % of delay, half adder saves 35.29% of power &25.69% of delay and sram cell saves 14.29% of power & 34.37 % of delay. Simulation is done using Tanner EDA tool and the outcomes demonstrate a noteworthy change in leakage power utilization and speed.
Corrosion Detection of an Orifice Plate for Flow Rate Measurement using Heat Transfer Mechanism
Authors: Prabhu V. , Velnath R. , Vairavel K.S. 
Published: March 2021

Abstract
Flow rate measurement is a critical parameter in industries which is measured by various techniques. But among them the most commonly used method of flow rate measurement is using differential pressure. A restriction placed in the path of flow produces a drop in pressure which is measured. The fundemental principle of bernoullis is used to compute the volumetric flow rate. The orifice plate is the primary sensing element widely used in differential pressure based flow measurement. Hence the accuracy of the flow rate depends upon the dimensions of the orifice plate. The reason for this is the flow rate is computed assuming that the dimensions of the primary sensing element is constant. Due to this reason it is important to detect any damges to the orifice plate. Erosion and plugging of contaminants are common problems encountered in this method. Improper values of pressure adversely lead to drop in transmitter accuracy. This paper provides a novel method for detecting damages in an orifice plate without visual confirmation. This technique provides a significant advantage of providing diagnosis information related to an orifice plate which thereby helps to measure the flow rate of fluids using differential pressure method with accuracy. This objective of our work is focused towards process industries where majority of the flow rate is measured using differential pressure method.
Development of Latex Transducer for Rubber Tapping Process
Authors: Arthur Vasanth J. 
Published: March 2021

Abstract
There is a huge demand for rubber in India used in variety of products. Now a day’s people collect the latex from the rubber tree by manual or semi-automatic rubber tapping process. By collecting the latex, the cutting depth is fixing for an approximate value. For each and every tree the depth of the bark is varied and improper tapping damages the cambium layer of the tree. The proposed latex transducer contains two motors, embedded controller, current sensor, distance sensor, LCD display and power supply. One motor is used for drilling and other motor is for driving. The driving motor will drive the drilling motor. For driving, stepper motor is used and drilling operation brushed DC motor is used. The current sensor senses the current of drilling motor. Initially the current sensor sense the distance up to the tree surface, then the embedded controller will give the signal to the driving motor, the driving motor will drive the drilling motor up to the tree surface. Once the drilling motor reach the surface, the embedded controller initialize the distance and runs the drilling motor so the distance sensor sense the distance from the tree surface. To reach the inner wood the drilling motor takes more current, so the embedded controller will stop the drilling operation and give the signal to the LCD display. So easily find the depth of rubber tree up to the cambium layer.
Potentially Affect Of A Vehicle To Grid On The Electricity System
Authors: Thakre Mohan P. , Mahadik Yogesh V. , Yeole Dipak S. 
Published: March 2021

Abstract
As many electric vehicles (EVs) are continuously on the market, Vehicle to Grid (V2G) technology has been successfully taken into consideration. The EV can be used to take part in such a load change in the electricity network as external storage gadgets. This article makes it much easier for researchers to understand the philosophy of V2G and its measurable influence on the electricity system in order that included all of the details for the integration of renewable energy sources. In the field of well-mannered and battery degradation, bi-directional charger and charging stations, a configuration for V2G and the critical aspects involved with V2G become analyzed by means of concentrated battery system management and control throughout this work. The challenges, benefits and technologies related to V2G are also addressed, in addition to the financial revenues and expenses of both EV holder as well as the energy infrastructure. For standardized test systems, the influence of a vehicle on the grid on the electrical grid has been examined in this work.
Performance Evaluation of speed control using Fuzzy dependent Genetic Algorithm in PMSM
Authors: Vijay Amirtha Raj F. , Kamatchi Kannan V. , Ponmurugan P. , Chitra K. , Lakshmanan M. 
Published: March 2021

Abstract
This paper examines the role of the tuning algorithm for speed regulation of the Permanent Magnet Synchronous Motor (PMSM). The picks of the PID regulator normally provide adequate results in the application of a low-force drive, but for high-power application drives, a self PID controller doesn’t provide any acceptable performance. Such applications require high-precision, superior and adaptable speed regulators and effectiveness in the cycle and execution of the plan. High-performance applications need some capacity based on High-speed high-reliability regulators, adaptability with maximum torque coefficient, higher rating capacity with minimum ripple torque. So many speed controlling mechanisms are available in the quick world, and these methods vary from the choice of regulator used in the PMSM to the method of programming/use of equipment. In this paper, generous examination is taken to control the speed of PMSM with three unique specialists, ABC based speed control drive, ANFIS controller of PMSM drive and Genetic algorithm based fuzzy controller. The planned regulators are tried through the mathematical reproductions in the MATLAB Simulink Platform. The examination between the reproduction aftereffects of execution measures are introduced toward the end. Hereditary calculation based Genetic algorithm based fuzzy controller gives some better outcome appropriate for the superior applications.
Power Flow Management in Hybrid Renewable Sources
Authors: Stanley Raja Alex , Vidhyalakshmi R , Sundar S , Suresh V , Suresh M , Maniraj P 
Published: March 2021

Abstract
The aim of this paper is to manage the power flow in hybrid renewable energy sources in efficient manner. In this there will be two renewable energy sources, battery, load and grid. In this system the bidirectional buck boost converter is used for PV source and battery, dual half bridge converter with transformer coupling and inverter for load/grid. In a standalone system, PV and wind source are made to operate in Maximum Power Point mode where the load will take the required power. In case of systems which are connected to the grid, two sources will always be operating at its MPP. If both the sources are not present, the required power will be taken from the grid and is used for charging the battery when the situation arises. MATLAB/Simulink is used to obtain the simulation results and the performance for the management of power flow is determined for various modes of operation
Design and Development of Automatic Quality Domestic Water Distribution and Wastage Reduction Management System
Authors: Ganesh Babu C , Saran G , Balamurugan V , Harirajan G K , Kavinprasanth M 
Published: March 2021

Abstract
The consequence of the project is that it is possible to minimize unnecessary consumption of water and provide water of good quality. This will eliminate additional health conditions. Recent days have raised the availability of polluted water due to the irresponsibility of staff or the collapse of pipes. However to prevent such cases, such automated systems will help to achieve the best water quality. Another big issue that can be minimized once this project is successfully completed is undesirable water pollution. By automatically shutting down the inlet tube once the tank reaches the full volume large amounts of water can be saved. As of now the water is just shut down on time. This can be stopped. The tank can be cleaned periodically via the automated tank cleaning system with echo enzymes, which in most locations is not properly accomplished. Bacteria and other germs can also be killed automatically by adding organic chlorine when needed. This is more effective than human work, since human beings add chlorine. They just add randomly, but this can be avoided when automated. The system of rationing implemented in this project would help people get the same amount of water. And robbery may also be minimized. We can also implement a system to buy water online by means of which people can buy water when they need the excess. All data, such as flow rate, pH, can be obtained from each house with GSM technology. This project will help to build a new, intelligent village and help people to access good quality water. In addition, implementation can be carried out on the basis of the specifications.