bluuebunny/crossref_metadata_2025_split huggingface dataset:
Data Driven Cutting Tool Fault Diagnosis System Using Machine Learning Approach: A Review
Authors: Tambake Nagesh R , Deshmukh Bhagyesh B , Patange Abhishek D 
Published: July 2021

Abstract
Every industry is now turning towards industry 4.0. In this era, industry requires smart machine tools. But for small scale and medium scale industries, it is not affordable to buy new smart machineries. Therefore, the fault diagnosis system (FDS) has got unavoidable propensity in the machine of modern huge information and smart manufacturing. Simultaneously, it offers a solid answer for taking care of the mechanical machines & its cutting tools health status. Industry 4.0 and its key advances assume a fundamental part to make mechanical systems independent and along these lines make conceivable the automated data assortment from modern machines/cutting tools. In view of the gathered information, ML algorithms can be applied for automated shortcoming identification and finding. It is difficult to choose relevant machine learning (ML) procedures, kind of data, data size, and hardware to apply ML in mechanical systems. Determination of wrong FDS procedure, dataset, and data size may cause increase in downtime and infeasible for scheduled maintenance. Accordingly, this study aims to present, the brief review of literatures for investigation to find existing methodologies of ML and its applications, Supportability to develop novel system to diagnose faults in CNC hobbing cutter and to choose suitable ML methods for their required FDS.
Application of Meta family Classifiers for monitoring hydraulic brake system using vibration based statistical learning approach
Authors: Wagh Mohit Nikhil , Alamelu Manghai T M , Jegadeeshwaran R , Saravanakumar D , Raghukiran N 
Published: July 2021

Abstract
In the modern days, use of vehicles is increasing rapidly. It is very essential that the vehicle must have a good control mechanism which ensures the safety of the vehicle. The brake system in automobile is one of the important control element which needs to be monitored. The unconditional brake leads to catastrophic failures. Hence, the brake system should be monitored regularly. An experimental study is proposed for the brake system monitoring using vibration signals. The vibration signals are captured under all possible brake conditions. The hidden information in the vibration are extracted as statistical features. We carry out the feature selection. Classification using the selected features is the final step in machine learning (ML). Meta family classifiers are used for the study. Among the considered classifiers, Bagging algorithm produced 80.8 % accuracy for monitoring the brake condition.
Touch-free operated Face shield-cum-mask for multifaceted applications – Vaktram Kavacham
Authors: Sanjana T , Anantha Sunil M , Shekhar G K 
Published: July 2021

Abstract
There are various situations where face shields and mask play an important role such as for doctors in operation theatres, healthcare workers diagnosing/treating patients with infectious disease, traffic police and construction workers working in environments with high levels of dust and air pollution, welders working at high temperatures, bike, bicycle riders and many others. A face shield-cum-mask can be useful to protect from infectious bacteria, virus, parasites, debris, hazardous chemicals, sparks etc. Knowing the potential need and importance of face shield and mask, its usability can be further enhanced by operating them based on sensors. We have built a prototype of 3D printed visor attached with face shield-cum-mask integrated with proximity sensors, battery and circuitry which is used to move the visor above or in front of the face as and when required by movement of hand close to the sensor.
Design of a Fuzzy Based Pid Algorithm for Temperature Control of An Incubator
Authors: Mizanur Rahman Md. , Saiful Islam Md. 
Published: July 2021

Abstract
The incubator is an apparatus that is used to regulate environmental conditions such as temperature, humidity control in an enclosure. To maintain the temperature of the incubator is difficult and challenging. This research paper proposes the design of an incubator temperature control by using fuzzy based PID. The proposed model construct of two fuzzy logic based PID controllers to control the temperature. This paper principally focuses on the designing of new fuzzy self-tuning PID algorithm. The error and changing error rate are inputs of the fuzzy based PID controller. The PID parameters are outputs of the fuzzy based PID controller. A set of fuzzy rules is used to regulate the PID parameters. The simulation result shows that the rising time, settling time & overshoot had reduced compared to PID control.
Compounding hazards and intersecting vulnerabilities: experiences and responses to extreme heat during COVID-19
Authors: Wilhelmi O V , Howe P D , Hayden M H , O’Lenick C R 
Published: July 2021

Abstract
Extreme heat is a major threat to human health worldwide. The COVID-19 pandemic, with its complexity and global reach, created unprecedented challenges for public health and highlighted societal vulnerability to hazardous hot weather. In this study, we used data from a three-wave nationally representative survey of 3036 American adults to examine how the COVID-19 pandemic affected extreme heat vulnerability during the summer of 2020. We used mixed effects models to examine the roles of socio-demographic characteristics and pandemic-related factors in the distribution of negative heat effects and experiences across the United States. The survey findings show that over a quarter of the US population experienced heat-related symptoms during the summer of 2020. Mixed effects models demonstrate that among all socio-economic groups, those who were most vulnerable were women, those in low-income households, unemployed or on furlough, and people who identify as Hispanic or Latino or as other non-white census categories (including Asian, American Indian or Alaska Native, Native Hawaiian or other Pacific Islander, and multi-racial US residents). The study findings indicate that millions of people in the US had difficulty coping with or responding to extreme heat because of the direct and indirect effects of the COVID-19 pandemic. Limited access to cooling as well as COVID-19 related social isolation played a major role in adverse heat health effects. Geographically, the South and the West of the US stood out in terms of self-reported negative heat effects. Overall, the study suggests that the intersection of two health hazards—extreme heat and coronavirus SARS-CoV2—amplified existing systemic vulnerabilities and expanded the demographic range of people vulnerable to heat stress.
A study on magnetic and spin polarized electric transport properties of cation doped LaCaMnO3perovskite ceramic system
Authors: Rajan Sam , Isac Jayakumari 
Published: July 2021

Abstract
Thepoly-crystallineLa0.5Nd0.15Ca0.35MnO3 has been synthesized by a conventional solid reaction method through the cation doping in LaCaMnO3. The analysis of the powder XRD of the composites revealed the formation of an orthorhombic structure in Pbnm space group. The cell parameters of the formed system has obtained and confirmed through Reitveld analysis and it is found to be a=5.4505,b=5.4457,c=7.6876.The lattice parameters and the spin ordering temperature TC of this system are decreasing due to Nd substitution. The ac and dc magnetization studies and resistivity measurements in ZFC and FC mode gives good understanding to the magnetic and electric transport properties of the doped system. The magnetization studies show a paramagnetic to ferromagnetic transition at a temperature below the critical temperature TC.The resistivity measurements reveals semiconducting to metallic transition below the temperature TMS. The temperature dependent transport nature shown in this system is one type of the correlated polaron hopping mechanism and it can be modeled by an adiabatic small polaron hopping(SPH) mechanism.
Effect of polycarboxylate ether-based superplasticizer dosage on fresh and hardened properties of cement concrete
Authors: Paktiawal Ajmal , Alam Mehtab 
Published: July 2021

Abstract
Ready-mix concrete nowadays is available almost everywhere in the country. RMC plants are indispensably using high-range water-reducing admixtures namely, sulfonate naphthalene formaldehyde condensate, and Polyether polycarboxylate, for making standard cement concrete. These admixtures are used to economize the cost of concrete by reducing the quantity of water. Commonly used high range water reducer admixture, the polycarboxylate ether-based (PCE) superplasticizer has been used to investigate its influence on workability and strength of concrete by measuring slump and ultrasonic pulse velocity as well as crushing strength. The cement of grade 43 has been used in this work. This superplasticizer was added to the mix to make concrete of grade M60 by weight of cement with 0.15%, 0.25%, 0.35%, 0.45%, and 0.55% without altering the w/c ratio. Experimental results reveal that the restricted dosage of the superplasticizer provided in Plain and reinforced concrete code of practice in Indian standard, IS456:2000, restricts to 1% is on the higher side. The slump, ultrasonic pulse velocity, and crushing strength of M60 grade standard concrete with water to binder ratio of 0.40 gives the optimum dose 0.45% by weight of cement, which is quite less than the restricted quantity of dosage.
Push system for Aluminium tube by using a stepper motor with the Arduino
Authors: Joshi P P , Jorapur V S 
Published: July 2021

Abstract
The research content of this paper is to design a push system for an Aluminium tube to be cut on the cutting machine. The system consists of one driving pulley, one idler pulley, and a timing belt. The stepper motor will drive the pulley and the stopper attached to a timing belt will push the Aluminium tube further. This paper describes the process of developing a push system using a stepper motor driver, membrane keypad, Nokia LCD, and a microcontroller board. Different types of stepping mode and the formula for the number of pulses to be sent to a stepper motor are derived and tested. The result of the paper shows that a stepper motor along with the electronic components improves accuracy for a push application and can be used.
Generation of Microtextured Characteristics using Maskless Electrochemical Micromachining
Authors: Kunar S. , Kibria G. , Shivakoti I. 
Published: July 2021

Abstract
To minimize and control friction and wear, the manufacture of microtextured characteristics on circular micropatterns is an innovative approach to extend the life of mechanical systems and components and enhance their reliability and performance. The form, size, and surface quality of circular micropatterns developed on stainless steel surfaces using maskless electrochemical micromachining directly affect the service life and function of textured surface. This article presents the experimental study on the generation by electrochemical micromachining of circular micropatterns on stainless steel. The effect of process variables such as inter-electrode gap (IEG), flow velocity and machining time on current density, current efficiency, material removal rate (MRR), surface roughness, and diametric taper angle are examined during the generation of circular micropatterns. The best parameters obtained from the experimental results are 100μm IEG, 4.4 m/s flow velocity and 3 minutes machining time for producing this micropattern. An attempt is also made to analyze the optical and 3D images of circular micropattern from the experimental results.
A Review on Transition-metal Oxalate Based Electrode for Supercapacitors
Authors: Singh Abhijeet Kumar , Jaiswal Piyush , Singh Preetam 
Published: July 2021

Abstract
Transition-metal oxalates have been significantly showing the potential for charge storage in supercapacitor as an energy material. Transition-metal oxalate materials with framework structures, morphology and electrochemical properties offer an opportunity for sustainable energy storage material. Recently, transition metal oxalates, witnessed pseudocapacitive or battery type behaviour when it has been used as electrode for supercapacitor applications. In this review, we mainly address the recent study of transition metal oxalates as potential energy storage materials such as Co, Ni, Mn and Fe based oxalates and composites in the context of supercapacitors with electrochemical performances. Although, electrochemical performances of TMOx electrode can be enhanced through various methodology such as by preparing mixed TMOx structures or preparing nanocomposite with highly conductive secondary materials such as graphene and CNT. The generated idea after reading this paper will help the researchers to explore further usage of transition metal oxalates in the field of electrochemical energy storage devices.
Microwave-assisted extraction of chlorophyll and polyphenol with antioxidant activity from Pandanus amaryllifolius Roxb. in Vietnam
Authors: Nguyen Nguyen Hong Khoi , Diem An Nguyen Thi , Anh Phan Kim , Truc Tran Thanh 
Published: July 2021

Abstract

Pandanus amaryllifolius Roxb., also called as pandan leaf, is distributed mainly in hot and humid climate areas. Pandan leaf, grown very popular in Vietnam, contains many biological value compounds such as chlorophyll and polyphenol with oxidation prevention activity. Microwave-assisted extraction (MAE) has advantages such as reduced extraction time and high extraction efficiency in comprison to other extraction technologies. The aim of this study was to assess the effect of microwave-assisted extraction conditions on chlorophyll and polyphenol content as well as antioxidant activity of pandan leaf. Research results show that acetone solvents of 90°, pandan powder: acetone ratio of 1:30, microwave capacity of 300W, microwave-assisted time of 2 minutes are parameters for the highest extraction efficiency. With these conditions, chlorophyll a, b and total chlorophyll content are respectively 9.4278 μg/mL, 4.2460 μg/mL, 13.6738 μg/mL, polyphenol content is 2.7577 g/L and DPPH radical collection activity 1409.51 μmol/L.
Evaluation of antibacterial properties of some essential oils from Vietnam
Authors: Do D N , Nguyen D P , Tran T T A , Nguyen D Q , Lai N M T , Huynh T H , Do V M , Luu X C , Le X T 
Published: July 2021

Abstract
Natural products have attracted attention from scientists because of their potential to replace antibiotics in the near future. Thanks to Vietnam’s richness in biodiversity, this study aimed at evaluating antibacterial activity of eleven essential oils from various plants. These essential oils were collected from various plants across Vietnam such as corn mint, clove, clove basil, eugenol, tea tree, terpinen-4-ol, kaffir lime, Mexican mint, rosemary, Homalomena occulta, and betel. By chemical reaction and fractional vacuum distillation method, eugenol and terpinen-4-ol was isolated from clove basil and tea tree oils with the content reaching up to 97.0% and 95.8%, respectively. The antibacterial activity against Staphylococcus aureus, Bacillus subtilis, Escherichia coli of essential oils was determined by disk diffusion and broth dilution method. As a result, Mexican mint oil and eugenol exhibited high antibacterial properties with low MICs and MBCs (62.5 to 125 uL/L), whereas other essential oils (clove, clove basil, betel, tea tree, terpinen-4-ol) had higher MIC and MBC values ranged from 125 to 500 uL/L.
Vehicle Recognition using extensions of Pattern Descriptors
Authors: Keerthi Kiran V , Dash Sonali , Parida Priyadarsan 
Published: July 2021

Abstract
Vehicle identification and classification for still images are incredibly useful and can be extended to a range of traffic surveillance operations. Reliable and accurate recognition of vehicles is however a challenging issue due to changes in vehicle appearance and illumination difference in real time scene. In this paper, we present a simple and effective way of vehicle recognition technique based on vehicle’s local texture features extraction and classification. The local features are extracted individually using the Local Binary Pattern (LBP), Median Binary Pattern (MBP), Gradient directional pattern (GDP), and Local Arc Pattern (LAP) descriptors and feed into Support Vector Machine (SVM) for classification. We also focus on vehicle classification using various color spaces like RGB, HSV, YCbCr for the texture descriptors extraction. The primary focus is to observe the effect of colour information on vehicle classification efficiency across different colour spaces. Initially, experiments are conducted for the classification of gray-level vehicle images of five different classes from the CompCars dataset. Then experiments are extended to different color spaces for the same dataset for color texture classification. The integration of different colour details increases the efficiency of vehicle classification, according to the experimental results.
Ab-initio Modeling of Functionalized 2D-Stanene nanostructure in context of FET based Toxic Gas Sensor
Authors: Verma Swati , Kumar Arun , Kumar Hemant , Baghel Rahul , Pinjarkar Latika , Verma Mohan L 
Published: July 2021

Abstract
Detecting toxic gases in the environment cannot be minimized in today’s highly polluted world and the reality of global warming. Carbon monoxide is a highly toxic air pollutant and can cause serious health problems. Sensing materials plays a critical role in the performance of gas sensors. Nanostructure materials exhibit better performance as sensing channels in application for developing novel FET-based sensing devices. In the proposed work, the ab-initio study is performed to explore the performance of 2D-Stanene nano sheet as a sensing substrate for application of field-effect transistors as gas sensor. We explored CO gas-adsorption behaviour on pristine, hole-defective, and Pt-doped Stanene sheet and analyzed structural, charge-density, electronic and transport properties by first principles calculations and exploit its potential for high-performance gas sensing. Here in, to get the measure of sensing properties of Stanene nano sheet after the adsorption of gas molecule, first the molecular model of all the adsorption cases are modelled by considering all possible anchoring sites and optimized, and then calculations were performed based on density functional theory (DFT).
Comparative Analysis of Solution Methods for Swing Equation in Power System for Transient Stability Studies
Authors: Sanitha Michail C 
Published: July 2021

Abstract
In power system swing equation plays a remarkable role in investigating the transient stability. Disturbances in system creates imbalance and it may lead to lose the synchronism. Solution of swing equation will help the operators to analyze the stability of the system during the disturbances and initiate the protective mechanism to save the system. The non linear differential swing equation is complex in nature. Commonly used numerical methods to solve swing equations like Point by Point, Modified Euler’s and Runge Kutta have explained in the paper. Along with numerical methods, two other methods, evolutionary algorithm based Particle Swarm Optimization method and analytical based Maximum Lyapunov Exponent method has also been investigated in this paper.
Dielectric and Magnetic Studies La+3 doped Cobalt Nano Ferrite
Authors: Ragini N. , Ayesha Syeda , P Komal K. , Fatima Tanveer , Harsha G. A , Shilpa S , Abdul Khader S. 
Published: July 2021

Abstract
La3+ substituted cobalt ferrite nano-particles with the chemical composition LaxCoFe2-xO4 (here,x=0, 0.05, 0.1, 0.15 and 0.2) were synthesized using auto-combustion method. Structural and morphological studies were probed using X-ray diffraction (XRD) and Field Emission Scanning Electron Microscopy (FESEM). Formation of rare-earth doped cobalt ferrite was confirmed using the X-ray diffraction studies. Average crystallite size (D) was found to be varying from 43.71nm to 55.37nm with the increase in La3+ concentration. Frequency dependent dielectric properties of synthesized samples were measured from 100 Hz to 1 MHz at room temperature using a precision HIOKI make LCR HI-TESTER. Dielectric dispersion was observed at lower frequencies for the synthesized samples. Magnetic properties were studies using Vibrating Sample Magnetometer (VSM), all the synthesized samples exhibited well defined magnetic hysteresis curves, there by confirming the magnetic behaviour of the sintered samples.
Optimal CRONE controller using meta-heuristic optimization algorithm for shell and tube Heat Exchanger
Authors: Girirajan B. , Rathikarani D. 
Published: July 2021

Abstract
A meta-heuristic optimization algorithm based third generation CRONE controller is proposed for controlling the thermal interfaces in heat exchanger device. The primary aim of this work is to identify suitable optimization technique among the whale optimization Algorithm (WOA) and grey wolf optimization (GWO) algorithms that would improve the robustness of third order crone controller against the parameter variations. A mathematical model of HE is developed to compute non-integer parameters so as to realize the optimal performance of the controller. The objective function is to minimize cost of fluid flow rate and to maximize the heat transfer rate. The optimization of heat exchanger is complicated by number of process plants, area, and method of connection, pressure drop of fluid, and transfer rate. A competitive result is obtained with multi-objective non-linear WOA for wide range of the process variable variations. The simulation is performed in MATLAB software to verify proposed WOA optimized third order CRONE controller and the performance is compared with the GWO optimized CRONE controller.
Churn Prediction in Telecom sector using Deep Neural Network with Flask Application
Authors: Kiruthika J.K. , Neshamoney B.S. , Madhan Kumar L. , Mugunthan V. 
Published: July 2021

Abstract
Agitate Analysis is one of the overall utilized examination on Subscription Oriented Industries to break down client practices to anticipate the clients which are going to leave the help understanding from an organization. It depends on Deep Learning techniques and calculations and become so significant for organizations in the present business conditions as acquiring another client’s expense is more than holding the current ones. The paper audits the significant examinations on Customer Churn Analysis on Telecommunication Industry in writing to introduce general data to perusers about the regularly utilized information mining techniques utilized, results and execution of the strategies and revealing an insight to additional studies. To stay up with the latest, contemplates distributed in most recent five years and basically most recent two years have been incorporated.
Extended micromagnetic model for the detection of superparamagnetic labels using a GMR vortex sensor
Authors: Wetterau Lukas , Abert Claas , Suess Dieter , Albrecht Manfred , Witzigmann Bernd 
Published: July 2021

Abstract
A self-consistent micromagnetic model is proposed for simulating interactions between a superparamagnetic label particle and a low-noise GMR vortex sensor, focusing on most common operations such as label detection and saturation. For this purpose, we evaluate the combined action of vortex stray field and the applied external field.
By solving the Landau–Lifshitz-Gilbert equation we find that a superparamagnetic label with a diameter of 60 nm can be successfully detected by a magnetic vortex structure assisted with an external magnetic field of 100 mT. Subsequently, the self-consistent spin diffusion model is applied to calculate electric response of a standard low-noise GMR vortex sensor to the presence of magnetically-saturated label. It is shown that the stray field of the activated label produces a detectable potential difference in the GMR sensor of 27.1 to 27.8 mV, the magnitude of which depends on location of the label with respect to the sensor surface.