bluuebunny/crossref_metadata_2025_split huggingface dataset:
Machine learning approach for categorical document mining
Authors: Sarma P , Deka H 
Published: February 2021

Abstract
The word text mining or document mining means automatic classification of text documents to different categories depending on their content. At present days this area of research is attracting many researchers due to increasing use of electronic documents in everyday life. In this paper authors have proposed a document mining method using Bisecting K-means algorithm, KNN classifier and Decision tree. There are many machine learning classification algorithms used for information retrieval. But most of them have very high computational complexity. So a method Bisecting K – Means clustering algorithm instead of normal K-means algorithm is used here and this approach trivially reduces the number of comparisons compared to others. The researchers also used decision tree at last to obtain the sub categories more accurately. After analysis it is found that the combination of Bisecting K Means and KNN classifier enhance the accuracy of the categorization. Accuracy of this proposed system is shown for each category at Result and discussion section.
Multi agent-based framework for interactive learning system with conversational user interface for visually and speech impaired
Authors: Ilango V , Anand Shankar Raja M , Uma V R 
Published: February 2021

Abstract
The purpose of this research article is to illustrate the role of Conversational User Interface to foster inclusive education among the Speech Impaired People (SIP) and the Visually Impaired People (VIP). The multiagent framework on “Conversational User Interface for interactive learning” will throw light on the role of the host and the learner in communicating and facilitating knowledge with each other. The article has been built after the in-depth exploration of various sources, which were handpicked for the study. This multiagent model can be put into implementation in the education industry. The scope of the study extends only to SIP’s and VIP’s because of their growing numbers across the globe, and yet they are deprived of formal education. The Conversational User interface can be used to bridge the gap, especially with the advancement of technologies such as VUI, MUI, WUI, BOTs, etc., for the VIPs and SIPs.
Analysis and Prediction Of Pima Indian Diabetes Dataset Using SDKNN Classifier Technique
Authors: Patra Radhanath , khuntia Bonomali 
Published: February 2021

Abstract
The newly proposed weighted k nearest neighbour is known as standard deviation K nearest neighbour(SDKNN) classifier technique. It is based on the principle of standard deviation. Standard deviation measures spreading of attribute about mean. Spreading of attribute plays a significant role to improve the classification accuracy of a dataset. Most of our distance calculation method between two points is determined by using euclidean distance process for finding nearest neighbour. Our proposed technique is based on a new distance calculation formula to find nearest neighbour in KNN. We apply here standard deviations of attributes as power for calculating distance between train dataset and test dataset. Distance calculation between two points in k nearest neighbour classifier is modified according to the standard deviation of attribute. In this paper, standard deviation of attributes are used. In first attempt, we have used standard deviation of attributes as power for calculating K Nearest Neighbour to improve classification accuracy and in second attempt, based on mean of standard deviation attributes, distance in K Nearest Neighbour is processed to further improve the classification accuracy. Our concept is implemented on Pima Indian Diabetes Dataset (PIDD). The analysis on Pima Indian Diabetes Dataset (PIDD) is carried out by splitting dataset in to 90% training data and 10% testing data. We have found that, in our proposed technique, average classification accuracy gives result 83.2%, a great improvement as compared to other conventional technique.
Face mask detection for covid_19 pandemic using pytorch in deep learning
Authors: Sen Sneha , Sawant Khushboo 
Published: February 2021

Abstract
The World Health Organization (WHO) has stated that there are two ways in which the spread of COVID 19 virus takes place that are respiratory droplets and physical contact. So, avoiding the spread of this virus need some precautionary steps to be taken that are social distancing and the wearing of masks. Among these two precautions the mask wearing is considered as the important factor for the spread of COVID 19 virus because these droplets can land on any surface. So, to keep track of the people that are wearing mask or not is more important. Here we have presented a mask detection system that is able to detect any type of mask and masks of different shapes from the video streams for following the rules that are applied by the government. Deep learning algorithm is used here and the PyTorch library of python is used for mask detection from the images/video streams. The proposed system is able to detect the mask wearing people and those one who are not wearing the masks.
Area optimized design of tetrad flip-flop using new tetrad value logic gate’s
Authors: Malviya Utsav Kumar , Ramakrishna Vaikuntapu 
Published: February 2021

Abstract
Logic levels in digital systems are predefined voltage and current range and a defined difference in voltage and current value signify binary information’s in digital systems. There are many logic families available to define binary data. In binary logic, there are two logic levels 1 and 0. This paper defines a new tetrad value logic (TVL) which can have four logic levels 0,1,2 and 3. This work presented novel designs of tetrad value logic NOT gate, AND gate and OR gate. With the help of these tetrad logic gates, a tetrad logic Flip-flop has been designed and tested on Tanner Electronic Design Automation (EDA) tool. The proposed tetrad flip-flop is a memory cell of tetrad Value Logic (TVL) which can store Logic 0, Logic 1, Logic 2, and Logic 3 when the input clock is off, and on the positive edge of the input clock, it can change the past stored logic with new input logic. This work discusses the possible application of tetrad logic. Simulation of tetrad logic gates and flip flop performed with help of tanner tool and verifies expected output correctly for all possible test cases. Parameters like Voltage levels, power consumption, noise margin, MOS count, propagation time, fan-out, noise margin, clock frequency, sink, source current, setup and hold time, are analyzed for proposed tetrad logic gates and flip flop. The S-edit 9.0 is used for the schematic design and T-spice 9.0 is used for parameter setting and design technology selection and W-edit 9.0 is used for simulation observation. The obtained results have been compared with other similar work and found better.
Multimodal medical image fusion using laplacian redecomposition
Authors: KoteswaraRao K , Veera Swamy K 
Published: February 2021

Abstract
Fusion of multi-modality images gives more sophisticated and complete information in video surveillance, remote sensing, and medical diagnosis. The present paper delivers a contemporary fusion method using laplacian redecomposition. The area of medical image fusion with different modalities has achieved more progress in medical field. Existing methods suffer from noise, blurring, and color distortion. These complications are addressed in the present method. The authors propose laplacian redecomposition method after enhancement to get redundant and complementary information. The proposed method has two alterations. First, we give the concept of overlap and non-overlap domains. Overlap and non-overlap domains are used for fusing redundant and complementary information respectively. Second, decision graph scheme is presented to get low frequency sub band images, complementary and redundant information. Global decision graph is used for reconstructing HF sub band images. Lastly, by taking inverse laplacian operation fused image is obtained. In the experiments for comparison, a few pairs of medical images have been taken to prove the strength of the suggested technique. The experimental results demonstrate that, the proposed technique accomplish aggressive performance qualitatively and quantitatively.
Impact of interfacial layer thickness on gate stack-based DGTFET: an analog/RF prospective
Authors: Goyal Vibhu , Tayal Shubham , Meena Shweta , Gupta Ravi 
Published: February 2021

Abstract
In this work, influence of interfacial layer thickness on gate-stack based double gate (DG) TFET device concerning analog/RF performance has been studied. Through simulation, it has been found that thicker interfacial layer can be used to mitigate the deprivation inRF/analog performance instigated with high -K gate dielectric. In this article, we have varied the thickness (Ti) of interfacial layer ranging from 0.2 nm to0.7nm and analyzed its effect. The decline in the intrinsic dc gain (δAV = Av(K = 3.9) - Av
(K = 40)), maximum oscillation frequency (δfMAX = fMAX(K = 3.9) - fmax(K = 40)) and the cut -off frequency (AfT = fT(K = 39) - fT(K = 40)) is 27.1 dB, 8 GHz and 6.4 GHz, respectively for TI = 0.2nm and24 dB, 1.7 GHz,&3.5 GHz, respectively in case ofTI = 0.7nm which indicates that if interfacial layer is thick (0.7nm), then, it is advantageous as compared to thickness of 0.2nm. Thus, such a device design not only decreases the surface lattice mismatching effect, but also, is more promising for better analog/RF performance of TFET device.
Recognition of valence using QRS complex in children with Autism Spectrum Disorder (ASD)
Authors: Anandhi B , Jerritta S 
Published: February 2021

Abstract
In children with a diagnosis of autism spectrum disorder (ASD), the absence of emotional inexpressiveness continues to be a consistent issue. This causes them to an unexpected emotional outbursts and meltdowns. This study utilizes the QRS complex derived from the Electrocardiogram (ECG) signals to investigate the positive (“Like”) and negative (“Dislike”) valence using a personalized emotion elicitation protocol using audio- and audio-visual cues in children who have ASD under the ages between 5 and 11 years. The sample size consisted of 15 controls and 15 children who have ASD.The acquired raw ECG signals are cleaned using various digital filters and the useful valence specific features are extracted from the QRS complex and are classified using the K nearest neighbour (KNN) and Ensemble learner. The control children were able to exhibit largely to the valence states, in contrast the children who have ASD did not show much difference in their valence states which was also verified using the Ensemble learner which achieved a maximum mean accuracy of 75.5 % in controls and 70.5% in children who have ASD.
Asymmetric complementary split ring resonator for identification of materials
Authors: Idayachandran G , Oudaya coumar S 
Published: February 2021

Abstract
In this paper, a new microwave sensor for identification of materials is presented. The sensor is composed of an asymmetric complementary split ring resonator etched on the ground side of the microstrip line. The sensor is designed using low cost FR4 substrate. The S21 simulation result shows the unloaded resonator operates at 6.45 GHz. The overall size of the sensor is 100mm×50mm×0.8mm. When the sensor is loaded with sample material, the resonant frequency shift is noticed. This change in frequency shift is used to identify the material type and also the thickness of the material under test. The sensor is tested for different test samples placed on the ground and is correctly able to identify the material under test and its thickness by its resonant frequency variations.
Modelling and performance analysis of hybrid electric vehicle
Authors: Sreeram K , Preetha P K 
Published: February 2021

Abstract
Electric Vehicles (EV) have become an integral part of the automotive industry and will soon replace Internal Combustion Engine (ICE) automobiles. The technological trends in the various components of EV have contributed towards extensive use of EVs. EVs can have a positive impact on ecology and power sector. EVs comprehensively decrease the greenhouse gas emissions created by the transport sector. This paper provides a basic understanding of the need for Electric Vehicles, the recent developments in India and the upcoming trends and research in Electric Vehicles. The modelling of Hybrid Electric Vehicle (HEV) and the performance analysis for various operating stages is detailed in this paper. The paper provides a base for additional studies.
Experimental investigation on CI engine with jatropha biodiesel-hydrogen peroxide blends
Authors: Sanjeevannavar Mallesh B , Banapurmath N R , Ganachari Sharanabasava V , Soudagar Manzoore Elahi M 
Published: February 2021

Abstract
The main objective of this research attempt is to determine implications of applying hydrogen-based additives as diesel and biodiesel oxygenates. Due to the difference in additive polarity, blending of hydrogen-based additives and petroleum diesel-biodiesel fuel mixtures require emulsification process towards achieving a stable mixture. After emulsification, stability test was conducted. experimentations were conducted on a single cylinder diesel engine fuelled with petroleum diesel and jatropha oil methyl ester diesel blends with hydrogen peroxide introduction at different loads and different injection operating pressures. From the experimentations it was observed that Introductions of H2O2 improve the brake thermal efficiency of the engine for D60-B30-A10 blend at 80% load and at 205 bar I.O.P. And also, extreme reduction in C.O. and H.C. emission was observed at all loads. NOx increased relatively with the escalation of hydrogen based additive concentration. It can thus be concluded that introduction of hydrogen can improve the engine performance and emissions. D60-B30-A10 gave the best engine performance and emissions at 205 bar I.O.P., 17.5 CR, 230 bTDC injection timing and 1500rpm.
Effect of retrogression and re-aging on mechanical &wear properties of LM-25 aluminium alloy
Authors: Gopi Mohan Ranjith , Jayasankaran J , Ilangovan S , Shanmugasundaram A 
Published: February 2021

Abstract
Abstract.The effect of retrogression and re-aging on the mechanical and wear properties of LM 25 were studied. The raw material ingot was casted in to cylindrical rods. The samples were solutionized at 530 °C for 2 hours and then artificially aged at 165 °C for 12 hours. The samples were heat treated using retrogression process at temperatures 200 °C, 225 °C, 250 °C, and 275 °C and re-aged at 165 °C for 12 h. The samples were tested for its hardness and tensile strength and found that the 200°C retrogressed and re-aged sample (HT1) was having high hardness (125 HV) and the tensile strength was recorded as highest (182 N/mm2) when compared to other samples. Izod impact test was conducted for all the samples and it remains same for all the samples. Dry sliding wear test results shows that HT1 sample was having least wear rate when compared to other samples.Microstructure of HT1 sample reveals that the silicon precipitates of sleek and finer grain structure, which improves the hardness and tensile strength.
Non-linear vibrations of a simply supported rectangular plate carrying a centric mass
Authors: Hamdani M. , El Kadiri M. , Benamar R. 
Published: February 2021

Abstract
Vibration is something that surrounds us in all areas, from everyday life to advanced industries. Among them, plates are found anywhere, so it has taken a fair share of study and analysis. Often, plates hold one or many point masses which completely changes their vibration frequencies and mode shapes. So, the main objective of this work is to analyze the effect of an added centric mass on the vibration Characteristics of simply supported rectangular plates and in both the linear and non-linear vibration regimes. The theoretical formulation adopted is based on Hamilton’s principle and spectral analysis. The expressions for the kinetic, linear and non-linear strain energies are derived taking into account the effect of the added mass on the kinetic energy and the effect of the membrane forces induced by the non-linearity on the strain energy. The generated equation has been solved numerically via an iterative procedure permitting to obtain the amplitude dependent frequencies and mode shapes. The results presented in this article are expected to be useful, both quantitatively and qualitatively, for a better understanding of the vibration of plates with an added mass.
Mechanics of Bio-tribology in Bionic Joints- Analytical Approach
Authors: Khot Sachin , Guttal Ravi 
Published: February 2021

Abstract
Bionic joints are extraordinary bearings and which are still unexplored. The bio-tribology deals with the study of lubrication methods, and mechanisms involved in natural joints. In the first part of the present work, the review of various lubrication methods is carried out. The anatomical description of knee joint lubrication is explored. The natural joints are found to be not governed by any of the single lubrication methods but all the lubrication methods are necessary to explain the lubrication in natural joints. In other words, one can say that the mixed lubrication method is the best suitable way to explore the bio-tribology of natural joints. The second part deals with the study of mechanics of the bio-tribology of the Knee joint. The Knee condyle’s spherical shape is used to develop the geometrical construction for analytical study. The soft cartilaginous tissue and menisci tissue are treated as an elastic material medium with elastic modulus E, whose surface is covered with synovial fluid film. The effect of applied force on film thickness is found to vary logarithmically. Anyway, the application of a higher magnitude of force will not affect the velocity of indentation. This study is useful to validate the numerical solutions of the bio-tribology study. This also helps in developing the surrogate models of bionic joints to analyse them with the least computational power and provides a platform to study the fluid-structure interactions.
Experimental studies on the wear and mechanical properties of Al7075-B4C-Al2O3 composite
Authors: Balasubramanian T , Ganesh M , Subramanian M , Arunkumar N , Aswin S 
Published: February 2021

Abstract
In order to deal with the demands of current requirements, traditional metals require changes in some properties. The high strength and light weight application of aluminium is well known. In certain instances, its ductility prevents its application in some environments. In the existing research, Al 7075 is reinforced with materials such as boron carbide (B4C) and aluminum oxide (Al2O3) to achieve low mass, low weight, high power, superior malleability, easy machining and excellent corrosion resistance. Thus, hybrid MMC production is being carried out to enhance these mechanical properties. In this study, Al 7075 is cut into small pieces with 90% wt in the form of a bar and placed in a SiC graphite crucible and the metal matrix is formed by melting it and stirring casting metal to add the reinforcement particles. The quantity of B4C & Al2O3 combined to form the new material was taken at 5% each. The samples were prepared according to ASTM specifications and eventually tested for tensile, compression, hardness, wear and effect measurements, and the findings were compared with those of pure aluminium Al 7075. The test results showed improved properties of Al MMC, which is more efficient than Al 7075.
Study of effects of radial load on vibration of bearing using time-Domain statistical parameters
Authors: Jain Prashant H. , Bhosle Santosh P. 
Published: February 2021

Abstract
Rolling element bearings are important parts of rotating machineries. Any defect in their elements causes vibration and damage. Many vibration signal analysis techniques are available for detection and diagnosis of defects in machineries. In time domain vibration analysis techniques, various statistical parameters such as RMS, crest factor, skewness, kurtosis etc. are used for defect detection in bearings. Bearing related parameters like defect type, defect size, shaft speed, radial load etc. affect the bearing vibrations. In this paper, the effects of change in bearing radial load on various time-domain statistical parameters are analyzed. New combination of indicators like Kurtosis × RMS, Kurtosis × Peak, RMS × Peak and new indicators developed by researchers TALAF and THIKAT are analyzed for change in radial load on bearing. Also the effect of outer race defect in bearing on statistical parameters is analyzed. In this paper, the bearing defect data sets with outer and inner race defects provided by Society for Machinery Failure Prevention Technology are used. The results show that these parameters can be used as condition indicators for early fault detection in bearings.
Prioritization of Lean Six Sigma Success Factors using Pareto Analysis
Authors: Patel Anand S , Patel Kaushik M 
Published: February 2021

Abstract
In the era of Globalization and technological intervention, organizations are forced to innovate the product and deliverer at a competitive price in the shortest possible time. Hence the organizations have to adopt drastic and quick changes to improve productivity at optimum resources by adopting emerging strategies. Lean Six Sigma (LSS) has grown as one of the continuous improvement strategies in the recent past, evolving from the merger of Lean philosophy and Six Sigma methodology. Lean aims to reduce waste, whereas Six Sigma mainly focuses to reduce the variation. However, the implementation of LSS and sustenance of it is a massive challenge for the organizations. Therefore, this paper aims to understand and to explore the factors responsible for successful implementation of LSS from the literature. The eleven success factors are prioritized as vital few through Pareto analysis. Top Management commitment and involvement, Training and Education, Cultural change, Project Management skills, and link LSS with the business strategy analyzed as the five most significant factors in implementing LSS. This study will help the academicians, researchers, and professionals explore the factors as a research domain and implement LSS more smoothly.