bluuebunny/crossref_metadata_2025_split huggingface dataset:
Inter-Disciplinary Approach to Suborbital Reusable Spaceplane Composite Wing Design
Authors: Ashikhmina E R , Prosuntsov P V , Reznik S V 
Published: February 2021

Abstract
The development of the wing of suborbital reusable spaceplane is a complex task due to conflicting requirements that are sufficient for its structure. They include high mass and cost efficiency, sustainability, low g-forces, effective heat protection under the consideration of technological restraints. To satisfy outlined requirements in the design of the composite wing the inter-disciplinary approach is presented relying on advanced methods of mathematical modelling. The approach starts with wing shape optimization enabling to get good aerodynamic performance. Subsequent optimal re-entry trajectory planning which use both angle-of-attack and angle-of-bank changes to control the re-entry provides a set level of g-forces and heat flux. Then based on the obtained trajectory the aerodynamic loads for the wing are gained. To acquire composite materials properties of the wing the analysis/test approach is applied that comprises multilevel modelling of mechanical and thermal material properties by commercial software. The results of modelling are validated by experiment. In addition, to enhancing mass efficiency of the wing structure the topology optimization of its wing box and structural optimization of the wing skin is conducted which uses both angles of orientations and thicknesses of composite monolayers as the variables with constraints on the strength and stiffness of wing skin. Furthermore, the approach includes thermal design due to high aerodynamic heating taking place during re-entry. Thermal loads are analysed by modelling the thermal state of the structure. The analysis showed that the wing skin needs thermal protection. As the thermal protection coating, the material based on glass microspheres was chosen. Its thickness through wing is obtained in the result of parameter optimization. As the result, the interdisciplinary approach to the design of the spaceplane composite wing is developed that allows feeding back mass, economic, aerodynamic, heat and strength impact into the spaceplane wing design synthesis.
Increasing the Wear Resistance of the Friction Surfaces of Rotating Parts Made of Bearing Steels Through Hardening Processing Methods
Authors: Tkachuk A , Zabolotnyi O , Chetverzhuk T , Svirzhevskyi K , Kononenko A 
Published: February 2021

Abstract
During the study, it was found that the basic technological processes of forming cylindrical working surfaces of friction pairs do not fully provide a rational combination of micro geometric characteristics and physical and mechanical properties of the surface layer. Therefore, we proposed to evaluate the wear resistance of the working surfaces of parts to use a complex indicator that takes into account the influence of technological factors on the properties of the material and the performance characteristics of the surface layer for the running-in and continuous operation modes. Plots of distribution of equivalent stresses by indentors of different geometric configurations are constructed and the optimal shape and material of the deforming element are established. A model of the dynamics of the deformation of the workpiece with a single-axis elastic tool has been developed, which can be used to calculate the radial force in the contact zone. The calculation scheme corresponds to the scheme of the axial cam mechanism. Based on the analysis of the influence of the geometric characteristics of the deforming element on the parameters of the deformation process, a barrel-type indenter was developed for fixing which a slider-type holder was developed with the ability to adjust the stiffness of the dynamic system.
Study of toxic gas adsorption on silicon substrate integrated with piezoelectric material for sensing application using COMSOL Multiphysics
Authors: Akshya S , Vimala Juliet A 
Published: February 2021

Abstract
This paper aims to study the analytical response of micro cantilever based gas sensor for the quantification of NOx gas molecules, simultaneously discussing the possibility of a different measurement technique. Numerous packed and digital gas sensors are available in the market, but each with its own limits. MEMS sensors provide smart working, portable, save space, and reusable. Hence the micro cantilever beam deposited with an active material such as palladium, reduced graphene oxide to monitor and obtain the concentration of NOx was identified in terms of deflection for deposited mass. The physics and study provided by COMSOL Multiphysics will be exploited for the current usage. Various materials such as silicon and diamond as a substrate were simulated and compared. This paper discussed about the different micro cantilever beam structures for the gas sensing mechanism and selects the better structure based on their deformation in structure due to applied mass. The excellent trapping substrate material for NOx is chosen. A new measurement technique using piezoelectric material will be discussed. The proposed method will be discussed based on their pros and cons by compared with other sensors. The drawbacks of the proposed technique are also highlighted. Overcoming the drawback of conventional measurement methodology and devising a novel sensor to make it compatible for gas sensing.
Performance and Shelf-Life of Electrospun Ag-doped WO3 Nanofiber-Based SERS Substrates
Authors: Juntaracena Komkrit , Yuangkaew Tienthong , Horpratum Mati , Triroj Napat , Jaroenapibal Papot 
Published: February 2021

Abstract
Recent advances in Ag-doped WO3 nanofibers have provided an opportunity to fabricate high quality and low-cost surface-enhanced Raman scattering (SERS) substrates. This work studied the performance and shelf-life of Ag-doped WO3 nanofiber-based substrates. Methylene blue (MB) molecules were used as analytical references. The prepared substrates were stored in ambient air at room temperature for the duration of 12 months. The Raman enhancement factor (EF) of freshly prepared sample was calculated to be 6.2 × 105. In the first 6 months, a small decrease in EF was observed. The EF was found to significantly decrease after samples were stored for 12 months. After 12 months, the relative standard deviations (RSD) of Raman signals changed from 10.35% to 50.29%, indicating non-uniform Raman enhancements at different locations of the sample. These suggested agglomerations of Ag nanoparticles, which deteriorated the Raman enhancement effect, after samples were stored for a prolonged period.
A novel to control defects of P-N semiconductor device by SRFE process
Authors: Sangwaranatee N , Srithanachai I , Niemcharoen S 
Published: February 2021

Abstract
This paper present the results from soft radiation flash exposure (SRFE) process. In principle of semiconductor device always has defect in structure from fabrication process and impact from usage environment. Although, device have control process but still has unexpected defects. Then, I would like to share results of SRFE process to control defects in P-N semiconductor device by exposed on device for few second with optimize radiation energy. The defects has disappear after passed SRFE process. The optimize of exposure energy and time will cure or remove defect in devices structure.
Synthesis and electrochemical performance of cobalt oxide deposited on nickel-foam for energy storage devices
Authors: Jangu S , Debnath N K , Acharya V 
Published: February 2021

Abstract
Efficient and flexible energy storage materials are the future of energy technology. Among the various energy storage devices supercapacitor which stores electrochemical energy with higher power density than battery and higher energy density than capacitor is a potential device. In the supercapacitor, electrode active material plays very important role for storage and transportation of electrolytic ions. Herein, we have synthesized substrate free cobalt oxide deposited nickel-foam with the help of microwave-assisted hydrothermal technique, which is novel and faster synthesis process than conventional synthesis processes. Morphological characterization of as-synthesized samples was investigated with FESEM. Electrochemical performance with specific capacitance (Cs) value of 98.31 F g1 at 0.25 A g1 current density and 93.59 F g1 at 1 mV s1 scan rate obtained from galvanostatic charge/discharge and cyclic voltammetry curves.
Thermovision study on Alumina’s Ra v/s Ts for AIDHVACS to control COVID-19
Authors: Arora Ashutosh , Singh Prithvi , Arora CM , Bansal Sanjay Kumar , Dixit Ambesh 
Published: February 2021

Abstract
The current study is the authors’ next work from the thermo vision perspective of real time single sun solar field performance infrared thermography (IRT) on commercial grade Alumina solar absorber surface coatings (SASCs) to recognize surface roughness (Ra) as one of the important production process parameters. In a previous study, it was investigated with IRT, and found that Ra<1.8 is favorable and hard anodized Alumina (HAAO) coatings exhibits better surface temperature (Ts) gain as compared to organic dyed non-HAAO coatings on Aluminum substrate, and are more stable in solar field for many years in open air environment without degrading their performance. It may be useful in better optimization of SASCs specifically for personal protective equipments (PPEs) sanitization and artificial intelligence (AI) driven heating ventilation air conditioning (HVAC) systems (AIDHVACS) design to control Covid-19 in current situations.The influence of Ra of few microns ∼ <15 µm on Alumina SASCs’ Ts gain is examined. The presented study shows that more than 1.05 mm thickness of substrate flat is necessary to develop good quality of alumina coating; Ra<1.8 µm is favorably expected to the extent of Ra value approaching as close as to nanoscale ∼ 5-500 nm; local surface temperature gained is depending upon local Ra profile as well as upon surface morphology in addition to the anodizing process parameters and other environmental factors. It suggests that the optimal surface profile should be designed as an integral to the production line processes. The substrate surface chemical composition may also change while processing due to surface contact with the processing tools, which may also result in altered solar field performance due to substrate altered material composition prior to hard anodizing process, as examined with X-ray fluorescence spectrometry (XRF) and ultraviolet–visible spectrophotometry (UV-VIS). The novelty is that other studies of surface roughness parameter is focused upon convective heat transfer inside tunnel or duct solar heat absorbers e.g. air heaters, whereas the authors have focused upon surface roughness of solar radiation receiving outer surface as an important commercial production process variable having effect upon conductive heat transfer in solar thermal power systems. The AIDHVACS needs machine learning and big data analysis as the need of the hour.
Radioactive decay of thorium and uranium in the liquid lead and molten salt
Authors: Tien Tran Minh , Khanh Nguyen Kim , Ngan Nguyen Kim , Nhi Nguyen Thi Tuyet 
Published: February 2021

Abstract
The accelerator driven subcritical reactor (ADSR) is very interested in the recent years. One of the researches is about the fuel, fuel should be thorium or uranium; the coolant is liquid lead or molten salt. This paper presents the results of research on the radioactive spectrum of thorium in molten salt, uranium in molten salt, and liquid lead. These research results include energy spectrums of alpha, beta, gamma, neutrino particles; the energy spectrums of the daughter nucleus.
Vibration mitigation of high-rise buildings via tuned mass damper subjected to dynamic loads
Authors: Miah Mohammad Shamim 
Published: February 2021

Abstract
Vibration mitigation and control problems in structural engineering are complex to deal with due to many reasons such as overall size of the structures (high-rise or low-rise), controlling systems (passive, active, semi-active, hybrid), and unknown input excitations. This study focuses into the vibration mitigation of high-rise buildings via the use of tuned-mass-damper (TMD). To do this end, a 15-storied structure is considered and the investigations are performed by employing MATLAB and SIMULINK. Even though the functionality of TMD is simple as the main controlling parameters are mass ratio, stiffness, and damping of the TMD. However, the tuning process of TMD parameters (e.g. manual tuning) gets complicated when the structures get taller and larger. Therefore, to deal with the aforementioned issues, the sensitivity of the TMD parameters have been performed. And the optimization is carried out by employing an unconstrained multi-variable function using derivative-free method and those (e.g. optimized) parameters are incorporated to perform the final simulations. Herein the performance of the TMD is compared with an uncontrolled system where no damper was used. In a nutshell, the outcome of this study shows that the vibration mitigation of high-rise buildings are possible effectively with optimized (optimal) parameters of the TMD.
Modeling compressive, split tensile strength and chloride ion penetration of concrete incorporating marble powder
Authors: Gehlot Tarun , Sankhla Suresh Singh , Parihar Sangeeta 
Published: February 2021

Abstract
The use of recycle materials as concrete ingredients has gained popularity because of increasingly stringent environmental legislation. This research paper check the possibility of replacement of sand (Fine aggregate) by marble powder recovered from marble slurry waste of marble processing units from 0% to 20 %, in production of concrete. This Research paper explore the mathematical modeling of compression strength of concrete cube specimens cured at 7 & 28 days, Split Tensile Strength at 28 days and Chloride penetration resistance of cylindrical concrete specimens cured at 28 days incorporating Marble Powder. Experimental investigation done on various concrete specimens to acknowledge compressive, split tensile strength and chloride penetration. Ordinary Portland cement (OPC) has been substituted with 0%, 10%, 15% and 20% by Marble Powder than after Concrete Cubes & cylindrical specimens prepared accordingly. Compressive strength test, Split Tensile Strength Test has been done concrete specimens and Rapid chloride permeability test (RCPT) has been done on cylindrical specimens. Three predictive regression models has been developed, one for compression strength (CS) of concrete cubes at 7, 28 days and second one for split tensile strength (STS) of concrete samples at 28 days age and last model for RCPT value i.e. charge passed Q@28days in cylindrical concrete specimens. Chloride penetration predictive Model Q @ 28 Days has value of 0.93, 0.69, 200.11 and 0.022 for R Square, Adjusted R Square, Standard Error, and P value. All predictive math models has been confirmed by data in complete range and has superior precision, correlation with experimental data and results.
Analysis of Seismic data using Machine Learning Algorithms
Authors: Sruthi A A V L , Bhargavi R , Gospati Vineesha Reddy 
Published: February 2021

Abstract
Earthquakes result in a gigantic loss of lives and properties to people because of its powerful, devastating and deep action. Over the years, a lot of research is going on to forecast the likelihood of occurrence of an earthquake to minimize the loss. In this study, a data mining technique i.e., classification analysis has been applied to estimate the most accurate earthquake model. Previous seismic data were collected and classified by applying k-NN (k-nearest neighbors algorithm) and Random forest algorithms. k-NN is a supervised machine learning algorithm used for bigger datasets (generally for statistical estimation) to determine the accuracy of the model. Random forest algorithm is also a supervised algorithm which is used for both classification and regression. By using this algorithm, multiple decision trees can be created over the datasets as well as predicting and offering a solution. Analysis and visualization of the data has been done and subsequently a comparative analysis of these two algorithms were done and tested to obtain the efficiency in predicting the accuracy of the earthquake model in terms of earthquake magnitude and depth
An intensive online survey of climate change due to development of roads and bridges on the highway road at Coimbatore – an evidence
Authors: Thenmozhi G , Cherian Mary , Nirmala M , Lalitha R 
Published: February 2021

Abstract
Climate change plays a major role in global warming. Coimbatore is a city with equal distribution of industrial and agricultural development and is fully surrounded with greenery in the past. Due to the increase in population and development of industries, development of infrastructural facilities for transportation becomes necessary. When compared to other districts, most of the human population make use of their own vehicles. The net result of industrialization in Coimbatore is the growth in infrastructure, ease in access to different places at reduced time with loss in trees. In this study, it was found that more trees were cut down in the past five years of period which causes reduced rainfall, increased air and soil temperature, increased pollutant gases. Because of these changes, there exists a decrease in underground water level and the quality of the air becomes poor. Hence, an online survey was conducted to validate the results obtained through meteorological data to obtain the actual outcome. Opinion poll was conducted in person and through online at Coimbatore to get the actual feedback from the public audience to mitigate the change in climate.
Evaluation of time series methods for distribution system state forecasting.
Authors: Thasnimol C M , Rajathy R 
Published: February 2021

Abstract
High proliferation of DERs in the distribution system necessitates forecasting ability for state estimator. A dynamic state estimation is a fundamental tool for realizing distribution system automation. Selection of appropriate methodological framework is an essential step before implementing dynamic state estimation. We applied Vector Error Correction Model (VECM), Random Forest and Long Short Term Memory Network (LSTM) time series models to dynamic power system state estimation problem and found out that the LSTM model outperforms the other two in prediction accuracy.
Collaborative artificial bee colony k-mean clustering algorithm for mixed data set
Authors: Nalini C , Sudeeptha J , Charulatha B S , Valarmathi P 
Published: February 2021

Abstract
Data mining techniques are used to extract useful patterns from a large data set. k-mean algorithm is one of the most famous partitioning clustering algorithm. But, Euclidean distance is sensitive to outliers and is suitable to only numeric values. Real time datasets have mixed attribute values, missing values and measurements are not in the standard format.The proposed algorithm extends the ability of the kmean algorithm to use a mixed simil arity measure to find the similarity between data objects for clustering mixed datasets.For imp uting missing values, correlation based data imputation is used.In addition, k-mean output depends on the initial cluster centre and local optima suffers from the number of clusters(k). In order to improve the efficiency of the k-mean algorithm, Artificial Bee Colony Optimization (ABC) based clustering algorithm is suggested. ABC is successful at exploring the search space, but endures in leveraging the search space. Collaborative search is used to amplify the search quality of bees to amplify the search quality of bees employees. To determine the number of clusters for the given data set, the Elbow method is used. In order to evaluate the outcome of the proposed algorithm, real time datasets are used. The results showed that the proposed method performs well compared to comparative algorithms.
Split and rule algorithm for documents clustering in big data of research articles on Google scholar
Authors: Thirumaran S , Nagarajan R 
Published: February 2021

Abstract
Big data of digital documents must be ranked in online repositories as a result of the exponential rise in digital information and the user’s needs. The ranking process plays an important role in online repositories as it helps users to identify the document, what they want exactly. Various ranking techniques have been suggested on the basis of various measures, such as the number of citations of the journal article, the impact factor of the publication platform, the quality of the article, the published year of the article, bookmarks, etc. However, the current ranking algorithms often offer meaningless results due to some limitations, which suggest the potential for further development of ranking mechanisms. This paper proposes an efficient split and rule algorithm that uses both static and dynamic ranking of documents in Google scholar. The proposed algorithm uses paper citations, user input, and the clustering mechanism for document ranking. The optimized solution obtained from the proposed split and rule algorithm offers a cluster-shaped filtered search result list against the user query.
Feature concatenation for scene classification of VHR images based on canonical correlation analysis.
Authors: Thirumaladevi S , Veera Swamy K , Sailaja M 
Published: February 2021

Abstract
The recent advancements of technology in remote sensing enable us to get very high-resolution images (VHR). To do scene classification in these images turned significant and become a challenging problem due to the lack of availability of adequate labelled data. We get over fitting problems by training a limited amount of labelled data. Considering the features obtained by deep learning convolutional nets as inputs we address this issue. Here we utilize the existing VGG16, Alex Net frameworks as a feature extractor to extricate informative features from the authentic VHR Images. Succeeding, discuss feature concatenation and classification framework based on Canonical Correlation Analysis (CCA). This strategy uses the correspondence of two feature vectors of discriminant information and eradicates redundant information within the features. This permits a more effective approach than conventional extraction techniques exclusively. The experimental results demonstrate that the feature concatenation strategy based on the CCA technique produces good informative features and accomplishes a higher accuracy with much dimension reduction than exclusively using the raw deep features. We use a 0.3 sub-meter resolution UC MERCED data set to explore our approach.
Miniaturization of asymmetrical gaussian profiled corrugated horn
Authors: Sachaniya Prashant D , Rathod Jagdishkumar M 
Published: February 2021

Abstract
In this paper, miniaturization of the asymmetrical profiled corrugated horn with low sidelobes, low cross-polarization, and good beam symmetry is presented. The miniaturized corrugated horn is designed at 2.48 GHz and optimizes the result between the frequency sweeps of 2 GHz to 4 GHz. At design frequency, the result of the S11 Parameter is -30.2966 dB, and the S11 Parameter remains below -20 dB between 2 GHz to 4 GHz. The asymmetrical profiled corrugated horn comprises the Gaussian Profiled Corrugation part and the most widely used Variable Depth Slot Mode Converter. The purpose of the mode converter is to generate hybrid mode in the corrugated horn antenna. The length of the asymmetrical profiled corrugated horn antenna after applying the miniaturization technique is only 3.5λ long. The designed horn full-fill the number of S-Band applications such as Satellite communication, Radio astronomy, Weather Radar, Surface ship radar.