bluuebunny/crossref_metadata_2025_split huggingface dataset:
An IoT Based Approach to Monitor and Replace Batteries for Battery Operated Vehicle
Authors: Kaushal Rajesh Kumar , Panda Surya Narayan , Kumar Naveen 
Published: December 2020

AbstractIn today's world of constant connectivity, instant gratification and customer-driven market, immediate availability of battery supply warehouses and replacement are the vast array of challenges faced by the vehicles such as e-rickshaws. Eelectric vehicles, as a new generation of vehicles, are increasingly favoured by the automotive research field because of their incomparable advantages in energy saving and emission reduction and reduction of human dependence on traditional fossil resources. Especially in the issue of safe operation and supervision of electric vehicles, it has received special attention. Therefore, remote monitoring and management of electric vehicles and remote monitoring of battery replacement stations have become an important part of the safe operation of electric vehicles. In the traditional approach, the recharging pattern of batteries of the e-rickshaw drivers is their own household sockets but the proposed system can immediately provide charged batteries and replace the used batteries by tracking the battery life along with storing the necessary data in the cloud so that it can be accessed from anywhere.
Vision Tracking and Optical Character Recognition for Augmented Reality based Attendance System
Authors: Kaur D P , Mantri A 
Published: December 2020

Abstract
This paper presents a system for smart portable electronic device which is based on computer vision-based techniques for scanning the manually entered data by the user for automatic update on a central database and augmented reality is used for automatic display of updated data to the user. The developed application is in the form of an Android app which is installed in compatible smart portable electronic device. The system for providing an interactive augmented reality-based attendance uses image processing for optical character recognition to identify the characters in the register marked as X’ for absence and any numeric data for presence of the student. For capturing the images, an AR enabled device can be used which is connected to a central database through the internet and the user is made to visualize the augmented information in the form of overlaid virtual content on the real scene.
Modelling and Analysis of Foldable Motorcycle Helmet for Human Comfort
Authors: Palanivendhan M , Vengatesan S , Naresh G , Jain Prathik , Aakash Vinu 
Published: December 2020

Abstract
Riding a motorcycle gives rider the freedom of the open road. However, there are some serious dangers involved in it. Thus, motorcyclists need to take extra precautionary measures to protect their body. The foremost place to start out is by protecting the top. The head and brain are the most susceptible to injury during a motorcycle accident than any other body part. Wearing a helmet increases the chance of survival significantly over non-helmet wearers. From 2008 to 2010, there have been 14,283 motorcyclist fatalities and 6,057 of them involved the rider not wear a helmet. Also, in India, it’s absolutely compulsory for motorcycle riders to wear helmets under the Section 129 of the automobiles Act, 1988. The rule also states that a standard safety helmet should have a thickness of 20-25 mm, with quality foam to absorb the impacts. The most frequent reasons for not using a helmet were weight of the helmet (77%), discomfort due to the heat, pain within the neck and inconvenience to carry it due to its bulky nature. Our project aims at easing the neighbourhood of carrying the helmet by making it collapsible when not in use making it portable and convenient. The new helmet design will have a similar design to a normal motorcycle helmet but will have collapsible/foldable mechanism that reduces the volume of the helmet by 20% and thus making it less bulky. The new mechanism is such that it doesn’t compromise on the protection of the rider. This therefore increases the convenience of usage and also the portability aspect of the helmet. The main goal of the project is to develop a collapsible helmet design that features a considerably reduced space occupied by 20% while retaining all the characteristics of a standard helmet that’s available in the market. This will therefore encourage the riders to use helmets more often and hence decrease the number of deaths caused by road accidents.
Fabrication and Characteristization of Bagasse Ash Particle (BAP) Reinforced Magnesium (AZ91E) Alloy Composite by Vacuum Stir Casting
Authors: Thirugnanasambandham T , Chandradass J 
Published: December 2020

Abstract
The present study is to fabricate AZ91E alloy matrix composite by varying the Bagasse ash particle (50μm) content (0, 5, 7.5, and 10wt%) via vacuum stir casting technique. The samples were characterized for its mechanical and microstructure properties. The mechanical properties of BAP reinforced composites were evaluated as per the ASTM standard and compared to unreinforced AZ91E alloy. The effect of reinforcement and distribution of BAP has been examined through a scanning electron microscope. The results of AZ91E magnesium alloy with 10wt% of BAP have found to have maximum tensile strength. The impact strength and hardness shows a marginal increase with increasing bagasse ash particle.
Optimization of cutting parameters of hybrid metal matrix composite AA6061/ZrB2 and ZrC during dry turning
Authors: Rajesh Ruban S , David Raja Selvam J , Leo Dev Wins K , Kandavalli Sumanth Ratna 
Published: December 2020

Abstract
The predominant aim of the research has been meant to evaluate cutting characteristic features of machining on AA6061/ZrB2-ZrC hybrid composite metal matrix with polycrystalline diamond tool. Though researchers understand, Taguchi would be used for dry turning operations to find the optimal cutting parameters. We have used the Taguchi L16 orthogonal array in the current investigation to evaluate the cutting characteristics. Through this work it’s analyzed that the optimal cutting as well as main cutting parameters actually affects the cutting performance. In order to understand the effectiveness of investigational optimization, confirmatory tests have been carried out hybrid composites fabrication composite has proved that it has better machining characterization. Hence, the fabricated composite can be recommended for applications especially hypersonic flight and rocket propulsion systems and because of the presence of hard ceramic material it is used commercially for the manufacture of cutting tools inserts.
Experimental Study and Determination of the Effect of Drilling EDM Parameters for Incoloy 800 Alloy
Authors: Arunbharathi R , Ashoka Varthanan P , Jayasurya R , Kavin SV , Jayasuriya S 
Published: December 2020

Abstract
This work involves the experimental study of drilling EDM parameters for Incoloy 800 alloy. Material erosion rate and tool wear rate has been considered as the response characteristics. Design of experimental runs were framed using CCD based response surface methodology. The experiments are performed in random manner with different combination of pulse current, spark duration, voltage and pulse interval and the results obtained are analyzed using Analysis of Variance (ANOVA). Various 3D plots are generated by using Design Expert software in this work. Discharge current and spark duration were found as the dominant variables for MRR and EWR and the effect is high on these two responses relative to other variables.
Electric Power Train design for FSAE Electric Car and Study of that Performance Parameters
Authors: Palanivendhan M , Kiran S , Boopathi D , Dhingra Dhruv , Madhuritha R 
Published: December 2020

Abstract
The aim of this work is to develop the power train of an FSAE electric car by modelling the vehicle on MATLAB/Simulink and then estimating the performance parameters such as acceleration (longitudinal and lateral), velocity (longitudinal and lateral), force (longitudinal and lateral), energy consumption (mechanical and electrical), power (mechanical and electrical), voltage drop and many more. These parameters are used to define endurance and acceleration capabilities of the vehicle as well as cornering properties. The future goal of this work is to estimate the different vehicle parameters and use these parameters to generate algorithms and design Electronic Differentials for the upcoming generations of FSAE vehicles.
Design and Development of Variable overhang chassis mechanism
Authors: Yokeshwaran S , Palanivendhan M , Sharma Chitransh , Sharma Rahul , Bindal Parth 
Published: December 2020

Abstract
This mechanism is designed in such some way that the vehicle can have safe, simple and stable mobility even at the higher speeds. To confirm that the overhang is safe and secure while expansion and retraction positions. This mechanism will be powered by hydraulics and electronics by functionality. As this mechanism only be used for electric vehicles, it brings a modern approach for utilizing the massive existing space in the electric vehicle and proving additional safety to the vehicle This concept of the variable overhang mechanism also provides a new approach in designing the vehicle of future as the frontal crumple zone will be expanded and retracted in accordance to the speed variation. This system will be acting as an active safety system providing different configurations in adjustment to the road conditions and speed variations. Among the major road crashes which occurs in our day to day lives, most of those crashes are notes as head on collision. The current safety systems such as seatbelts and airbags perform a good job in safeguarding a person from upcoming injuries but despite of them we still require an additional system which will further improve the current safety conditions. This design will function by variable overhang mechanism which will further be helpful in crash reduction and will support vehicle as an added safety. In addition to this, it will support vehicle as a safety component by the introduction of honeycomb bumper, which will further sustain the impact and would be a great tool of utility. The honeycomb bumper will help sustaining the initial impact of the vehicle over crashes. This will result in drastic impact reduction at cabin area and improvising the safety conditions for the vehicle and certainly limit the impact transfer to the passenger cabin area. This safety feature will work on the principle of crumple zone, where the front mechanism of the vehicle will act as the frontal crumple zone to the vehicle by its self-breakdown tendency.
Preparation of Graphene based Hydroxyapatite by Freeze Drying Method
Authors: Gopi Krishnan R , Suganthan R , Prabhakaran V 
Published: December 2020

Abstract
Hydroxyapatite (HA) is one of the major compounds that play a major role in bone restoration. The skeletal bone of our body contains about 80% hydroxyapatite. Low stiffness and strong stiffness are a major problem for HA, after a lot of research and researchers have come to the conclusion that Hydroxyapatite is a bad thing it can't build a proper structure so adding graphene oxide and hydroxyapatite will improve the strength and durability of the material so that the flaws can be fixed, at last we have added a few other natural biomaterials which are used to increase cellular contact and are said to be an effective treatment for osteoporosis. Graphene oxide is a carbon-based material that provides a good durable for any other material used. In this article, we propose a unique method of preparing Graphene based Hydroxyapatite by Freeze Drying Method. This method is most promising for preparing for Hydroxyapatite in a very simple and elegant manner. After the entire preparation process the so formed HAP is characterized with FTIR analysis to confirm the molecular presence of the HAP.
Preparation of Graphene Oxide Based Hydrogel for Diabetics Foot Ulcer
Authors: Karthikeyan R , Fazil M , Prabhakaran V 
Published: December 2020

Abstract
Diabetes is a condition that impairs the body’s ability to process glucose otherwise known as blood sugar. High levels of blood glucose caused by diabetes can over time affect the nerves and lead to poor blood circulation making it hard for the blood needed for skin repair to reach areas of the body affected by wounds. In this paper we produce a component material which heals the wound for diabetic patients in a short period of time. Normally, wound is healed in slow process therefore we designed a hydrogel for fast recovery in diabetic patient. In this work the Graphene oxide (GO) is synthesized using popular chemical method and the particle size is characterized using FTIR analysis. This Graphene Oxide (GO) as hydrogel can make the process of healing is faster method for diabetic patients. Graphene oxide (GO) have been incorporated into hydrogels to improve the properties of conventional hydrogel and healing property.
Effect of Debonding on Stiffness and Long-term Creep of Sandwich panels IOP: Conference Series
Authors: Siva Kishore I. , Mallika Chowdary Ch. , Ranga Rao V. 
Published: December 2020

Abstract
The main objective of this study was to analyze the effect of debonding on the stiffness and long-term creep of sandwich panel. Sandwich panel is made of thermoplastic core which is viscoelastic in nature and debonding is the major failure mode of the sandwich panel. Sandwich beams were made of different types of materials and the different materials have different properties. Numerical modeling of sandwich beam with aluminium face sheet and polypropylene core is done. Analysis was performed by using ANSYS software and the element used in the modeling is SHELL181. Four-point load configuration was created for the model with loading of 60 % of core shear strength according to McCallum (2012) and the model were subjected to static deflection. Static deflection results were compared with experimental and theoretical results and stiffness of deboned sandwich beam was evaluated. Primary and Secondary creep was evaluated in ANSYS by using Time hardening and the Norton equations to the propylene core and Burger model was used to fit with the secondary creep of the bonded sandwich beam. The primary and the secondary creep of bonded and the deboned sandwich beams were compared and long-term creep of deboned sandwich beam was determined.
Thermal conductivity of a thick 3D textile composite using an RVE model with specialized thermal periodic boundary conditions
Authors: Kim Hye-gyu , Ji Wooseok 
Published: December 2020

Abstract
Finite element analysis is performed to virtually measure homogenized thermal conductivity of a thick 3D woven textile composite (T3DWC). Temperature-dependent thermal and mechanical properties of constituents are considered for the measurements over a wide range of temperature. A two-step homogenization approach is adopted here to simplify the analysis at the microscopic level without losing heterogeneity of the material at the macroscopic scale. First-step homogenization is carried out at a tow level using an analytical homogenization scheme. Fiber tows are homogenized and assigned with effective elastic and thermal properties. The solid tows are then implemented into a representative volume element considering the unique in-plane periodic fiber architecture of the thick composite material. Due to the unique in-plane periodicity, conventional periodic boundary conditions for thermal and mechanical loading conditions are reformulated. Anisotropic thermal conductivity of T3DWC is obtained from the second-step homogenization based on virtual thermal tests performed at ambient to elevated temperatures.
Blasting induced dynamic response analysis in a rock tunnel based on combined inversion of Laplace transform with elasto-plastic cellular automaton
Authors: Mei Wanquan , Li Mei , Pan Peng-Zhi , Pan Junfeng , Liu Kunlun 
Published: December 2020

SUMMARY
The dynamic disturbance from explosion, earthquakes and stress impact may induce rock mass damage around the deep-buried tunnel. Here, we show the dynamic responses triggered by blasting load disturbance. In this paper, the theoretical formulae are first derived to evaluate the time-domain dynamic responses based on the wave function expansion method and the inversion of Laplace transform and then a self-developed numerical code, that is, elasto-plastic cellular automaton (EPCA), a module of CASRock, is subsequently employed to simulate the blasting induced elasto-plastic dynamic responses. It can be found from the analytical solutions that tensile stress concentration at two sidewalls occurs, while compressive counterpart at the roof and floor appears. Moreover, the radial velocity vibrations generate concentration at the two sidewalls, while the circumferential counterparts appear at the roof and floor. The numerical simulations indicate that compression-shear and tensile failure are the major mechanism for the rock mass damage around the rock tunnel. The analytical and numerical results help to understand the velocity vibrations and the major mechanism of rock mass damage and provide theoretical basis for the support of rock tunnel.
A robust mathematical model of adaxial–abaxial patterning
Authors: Andrejek Luke , Chou Ching-Shan , Husbands Aman Y 
Published: December 2020

AbstractBiological development results from intricate and dynamic interactions between members of gene regulatory networks. This is exemplified by the production of flat leaf architecture. Leaves flatten by driving growth along the boundary between their adaxial (top) and abaxial (bottom) domains. These domains are generated by interactions between a complex network of transcription factors and small RNAs. Despite its complexity, flat leaf production is robust to genetic and environmental noise. To identify factors contributing to this robustness, we mathematically modelled the determinants and interactions that pattern the adaxial–abaxial axis in leaves of Arabidopsis thaliana. Model parameters were estimated almost exclusively using experimental data. Our model recapitulates observations of adaxial–abaxial patterning and small RNA-target interactions. Positioning of the adaxial–abaxial boundary is stable across a wide range of small RNA source values and is highly robust to noise in the model. The successful application of our one-dimensional spatial model will enable higher-dimension modelling of the complex and mechanistically challenging process of flat leaf production.
Framework for identifying drug repurposing candidates from observational healthcare data
Authors: Ozery-Flato Michal , Goldschmidt Yaara , Shaham Oded , Ravid Sivan , Yanover Chen 
Published: December 2020

AbstractObjectiveObservational medical databases, such as electronic health records and insurance claims, track the healthcare trajectory of millions of individuals. These databases provide real-world longitudinal information on large cohorts of patients and their medication prescription history. We present an easy-to-customize framework that systematically analyzes such databases to identify new indications for on-market prescription drugs.Materials and MethodsOur framework provides an interface for defining study design parameters and extracting patient cohorts, disease-related outcomes, and potential confounders in observational databases. It then applies causal inference methodology to emulate hundreds of randomized controlled trials (RCTs) for prescribed drugs, while adjusting for confounding and selection biases. After correcting for multiple testing, it outputs the estimated effects and their statistical significance in each database.ResultsWe demonstrate the utility of the framework in a case study of Parkinson’s disease (PD) and evaluate the effect of 259 drugs on various PD progression measures in two observational medical databases, covering more than 150 million patients. The results of these emulated trials reveal remarkable agreement between the two databases for the most promising candidates.DiscussionEstimating drug effects from observational data is challenging due to data biases and noise. To tackle this challenge, we integrate causal inference methodology with domain knowledge and compare the estimated effects in two separate databases.ConclusionOur framework enables systematic search for drug repurposing candidates by emulating RCTs using observational data. The high level of agreement between separate databases strongly supports the identified effects.
Modeling physician variability to prioritize relevant medical record information
Authors: Tajgardoon Mohammadamin , Cooper Gregory F , King Andrew J , Clermont Gilles , Hochheiser Harry , Hauskrecht Milos , Sittig Dean F , Visweswaran Shyam 
Published: December 2020

Abstract

Objective
Patient information can be retrieved more efficiently in electronic medical record (EMR) systems by using machine learning models that predict which information a physician will seek in a clinical context. However, information-seeking behavior varies across EMR users. To explicitly account for this variability, we derived hierarchical models and compared their performance to nonhierarchical models in identifying relevant patient information in intensive care unit (ICU) cases.

Materials and methods
Critical care physicians reviewed ICU patient cases and selected data items relevant for presenting at morning rounds. Using patient EMR data as predictors, we derived hierarchical logistic regression (HLR) and standard logistic regression (LR) models to predict their relevance.

Results
In 73 pairs of HLR and LR models, the HLR models achieved an area under the receiver operating characteristic curve of 0.81, 95% confidence interval (CI) [0.80–0.82], which was statistically significantly higher than that of LR models (0.75, 95% CI [0.74–0.76]). Further, the HLR models achieved statistically significantly lower expected calibration error (0.07, 95% CI [0.06–0.08]) than LR models (0.16, 95% CI [0.14–0.17]).

Discussion
The physician reviewers demonstrated variability in selecting relevant data. Our results show that HLR models perform significantly better than LR models with respect to both discrimination and calibration. This is likely due to explicitly modeling physician-related variability.

Conclusion
Hierarchical models can yield better performance when there is physician-related variability as in the case of identifying relevant information in the EMR.