bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abnormality Detection in Musculoskeletal Radiographs
Authors: choudhary Ravi Raj , Choudhary Somesh , Meena Gaurav 
Published: January 2021

Abstract
A radiographic study is a typical procedure utilized to find different kinds of abnormalities, where the identification of Musculoskeletal Abnormalities from the norm stands out as a crucial task. in this paper we suggests some deep learning methods to identify such Musculoskeletal Abnormalities using the MURA dataset which is one of the largest collections of upper extremity radiographs. We make use of DenseNet and VGG deep learning models to try to draw some unprecedented findings and results. In addition, we try to visualize all our results and findings using comparative graph study. We compare our model with models proposed during the Stanford ML Group MURA Competition using Cohen Kappa Statistic. The obtained results show that deep convolutional neural networks can achieve results which are very close and even better compared to current state-of-the-art models. We achieve comparable model performance to state-of-the-art performances in three of seven study types.
Analysis of EC over Gamma Shadowed α-η-µ Fading Channel
Authors: Yadav Poonam , Kumar Sandeep , Kumar Rajesh 
Published: January 2021

Abstract
Composite fading channels are used to characterize the real time wireless communication system, as it can account for multipath fading as well as shadowing effect on the channel. To analyse the performance of the wireless communication systems supporting real time applications effective capacity is a crucial performance measure. In this paper, analysis of effective capacity for the α-η-µ fading channel under the shadowing effect is performed. To model shadowing gamma distribution is used. Moreover, asymptotic expressions are derived in the pursuance of obtaining insight behaviour of the channel.
Fraud Detection in Financial Statements using Text Mining Methods: A Review
Authors: Singh Yadav Ajit Kr. , Sora Marpe 
Published: January 2021

Abstract
In the financial industry, financial fraud is one of the ever-growing hazards with far concerns. Financial statements are the fundamental papers which replicate economic position of a corporation. Users of the financial information like public, creditors etc. are the major foundations of a decision-making process for financing stakeholders. Financial fraud has extremely damaged the sustainable growth of financial markets and enterprises. The amount of financial reporting fraud cases keeps on developing. Each incident is a thick hit to partners, banks, and financial specialists and it costs human progress significantly. One of the serious issues is to recognize the financial reporting fraud by utilizing formation of an active model. The aim of this paper is to identifying frauds using various text mining techniques and guard, the public’s investments. This investigation will benefit auditors and financial governors.
Reinforcing Livelihood by Interdependency of HR Capacity-ICT: Relevance to Multi-cropping practice system in Indian Eastern Himalaya
Authors: Hatiboruah Jyoti , Pant Rajive Mohan , Choudhury Shibabrata 
Published: January 2021

Abstract
The rural economy of Eastern Himalayan region of India is mostly agriculture based, dominated by traditional as well as community knowledge, has been using as source of livelihood since long years back. But with Green evolution and technological advancement, High Yielding variety of cash crop like Large Cardamom (Amomum subulatum Roxb.) and influence of skill-information-technology are emerging in a great extent respectively only to ensure sustainable livelihood. Since it is seen that only through large cardamom cultivation, it is difficult to ensure sustainability, hence concept of Multicropping is very much demanding. Here, this paper highlights the influence and interdependency of Human Resource Capacity and Information and Communication Technology (ICT) on Multicropping as well as on large cardamom cultivation to ensure sustainable livelihood in this particular region.
Evaluation of energy efficiency and moisture diffusivity for convective drying of large cardamom
Authors: Dash Soumya , Dash Kshirod Kumar , Choudhury Shibabrata 
Published: January 2021

Abstract
The drying behavior of freshly harvested large cardamom capsules were studied in a hot air dryer within the temperature range of 50-80°C. The study on drying rate showed that the constant rate drying period was very short, and capsules mostly followed the falling rate drying period. The drying during falling rate drying was followed unsteady state mass transfer and was governed by Fick’s diffusion law. The drying rate was faster initially when the moisture content in the product was high but with a decrease of moisture content, the drying rate was found to be decreased. Nine different drying kinetics models were fitted to find the best suitable model to predict the drying kinetics of large cardamom capsules. The two-term model was the best-suited model out of the nine different models, representing the drying properties of large cardamom with the highest R2 and the lowest RMSE and χ2 values. The maximum effective moisture diffusivity Deff value of 3.898×10−10 was obtained at a drying temperature of 80°C, while the lowest value was 1.949×10−10 at 50°C. The dependency of effective moisture diffusivity with drying temperature was correlated by Arrhenius equation. The activation energy showing the minimum energy needed to extract moisture from a solid matrix of large cardamom capsule was calculated as 32.54 kJ/mol and the pre-exponential factor of Arrhenius equation was calculated at 7.6×10−4 m2/s.
Significance of Renewable Energy for Empowering Cooperative-Farming Sector in Majuli Island of India
Authors: Athira R , Parida A. , Choudhury S. 
Published: January 2021

Abstract
Agriculture is the backbone of the Indian economy and plays a vital role in the overall development of the country. Many studies and practices have proved the importance and benefits of electricity in agriculture throughout the world. However, the fossil fuel-based conventional energy supply to agriculture is always associated with environmental issues. In an attempt to study the significance of renewable energy in the cooperative farming sector particularly in the biodiversity regions, Majuli Island of Assam, India has been selected for the case study. Even though the major income source in the said locality is agricultural farming, they are deprived of getting the optimum benefit from this indigenous income source due to lack of technological intervention. Technological intervention in this sector in the biodiversity region is not imaginable without exploring the feasible intervention of renewable energy at an affordable energy cost. Therefore, in this paper, the significance of renewable energy in agriculture considering the environmental issues has been highlighted in general and in cooperative farming in particular.
Improved Reliability of Voice over Internet Protocol(VoIP) using Machine Learning
Authors: Kumar Vinod , Roy Om Prakash 
Published: January 2021

Abstract
Start Voice over Internet Protocol (VoIP) is the communication means inspired with the revolutionizing wireless internet technology to transfer voice signals. However, VoIP over wireless means faces several challenges in terms of data loss resulting in poor voice quality or communication delay. To deal with the practical aspects of voice communication over Internet Protocol(IP) we proposed a highly secure wireless network. The proposed VoIP as a secure wireless network for VoIP combines the advantage of Artificial Bee Colony (ABC) based network optimization based on node property. This is followed by implementation of two classifiers; Support Vector Machine (SVM) that identifies the affected route and Convolutional Neural Network (CNN) that detects the malicious nodes present in the affected route to offer secure data transmission. The quality of voice communication is evaluated in terms of dropped packets, delay and jitter to offer interactive communication service. The simulation analysis over 50 nodes had proved the effectiveness in achieving reliable quality voice calling service with average throughput of 98.65% with comparatively lower jitter, packet loss and latency of 2.325 ms, 1.35% and 1.616 ms, respectively.
Word Level Language Identification on Code-Mixed English-Bodo Text
Authors: Kalita Nayan Jyoti , Agarwala Ankita Goyal , Das Jayprakash 
Published: January 2021

Abstract
Since social media has become an active part of one’s life, people express their views freely in mixed informal languages on such platforms. So, in a multi-lingual country like India, it becomes really difficult for conventional language detectors to identify such languages. This paper mainly aims to detect the language at word level where the code mixed text can be in English-Bodo-Assamese. The data for the same is collected from some related Facebook pages and various classification algorithms are used to predict and compare the accuracy with which the detection is done.
Object Detection in Live Streaming Video Using Deep Learning Approach
Authors: Raj Jeberson Retna , Srinivasulu Senduru 
Published: January 2021

Abstract
Object detection in a complex scene is of challenge as the image contains numerous features. Object detection is important in surveillance, healthcare, recognition, manufacturing, military and agriculture etc. The traditional approaches are limited in accuracy and mainly focussing on image datasets. With the application of deep learning algorithm, the accuracy can be increased. In this paper, the Convolutional Neural Network (CNN) is introduced to detect the objects in the image frames. The input of video is decomposed into image frame and the particular image frame is considered for processing. The image is preprocessed and the noises are removed for further processing. In the next step, feature extraction process contains edge detection and extracting the meaningful shape and texture in the image. The shape which contains the higher level feature is then feed into convolutional layer. The convolutional layer consist of four parts such as number of filter, filter size, pooling layer and max pooling layer. With the application of activation function Relu, the objects can be identified. Furthermore, the Gradient descent algorithm is applied for optimization to improve the accuracy. The system has been tested with ImageNet and the results are very promising.
Dielectric Material Selection for High Capacitance Ratio and Low Loss in MEMS Capacitive Switch using Ashby’s Methodology
Authors: Kurmendra  , Kumar Rajesh 
Published: January 2021

Abstract
The performance of the RF MEMS capacitive switch is majorly decided on capacitance ratio and loss in the dielectric layer as they decide the isolation (in dBs) in off condition. The capacitances in a MEMS capacitive switch in pull-up and pull-down states are used for deciding the capacitance ratio. In this article, we have presented a method to find out the best dielectric material using Ashby’s methodology for high capacitance ratio and low loss thus high isolation in switch off condition. Firstly, a database of 10 mostly employed dielectric materials have been created, and then, material indices are derived using material properties such as dielectric constant, resistivity, conductivity, and loss tangent which have been used in the selection of dielectric material. Through the study it is observed that to have a high capacitance ratio and low loss in dielectrics, the down capacitance should always be much greater than pull-up capacitance and tangent loss must be kept at possible minimum. This method will be highly useful in the selection of the best dielectric material by switch designers.
Novel design and performance analysis of WSN node using NRF and ATmega328
Authors: Gupta Ashish , Kumar Rajesh 
Published: January 2021

Abstract

Designing an efficient wireless sensing network (WSN) node over a remote location is a challenging task in the heterogeneous environment. The two implementation challenges are – first, large distance with comparatively signal coverage and second, power consumption for devices. It is observed that the use of energy harnessing techniques by the research communityhas proven successfully redemption in power consumption for circuits involving antenna, microcontroller and sensor. In present work, a novel schematic design of a low power wireless sensing node has been discussed which is used for connecting different sensors such as moisture and temperature sensor. The design considered the wireless sensor node with a power module, a NRF, an Atmega-328 microcontroller and a GSM module to upload data over the cloud. NRF facilitates long-range communication up to a range of 1000m by using a maximum current consumption of 15mA. The wireless sensor node are key elements in implementing Internet of Things.

The performance in terms of power consumption is analyzed for long range communication. Experiment has been designed to transmit with an interval of 15 sec and interval of 60 sec. At the receiver end, the central node GSM sim800A module is used to upload data over the cloud platform Thingspeak. In comparative study with different microcontroller development boards & wireless methods it has been found that the designed WSN node is effective in saving power consumption. The node can act as master or slave and can communicate with several other nodes also.
Tribocorrosion behavior of Nb coating deposited by double-glow plasma alloying
Authors: Zhu Xinbin , Dang Bo , Li Fengkun , Wei Dongbo , Zhang Pingze , Li Shuqin 
Published: January 2021

Abstract
Titanium and titanium alloys are considered as good implant materials, but their poor tribocorrosion resistance limits further development. In this study, niobium coating (DG-Nb) was deposited on TA3 pure titanium (Pure Ti) by double-glow plasma alloying aiming to improve the tribocorrosion resistance of Pure Ti. The properties of the samples were characterized by using X-ray diffraction (XRD), scanning electron microscope (SEM). Open circuit potential (OCP) and coefficient of friction (COF) tests were used to examine the tribocorrosion performance. The results showed that DG-Nb can largely enhance the tribocorrosion resistance of Pure Ti in Ringer’s physiological solution.
Preparation and photocatalytic performance of TiO2-RGO-CuO/Fe2O3 ternary composite photocatalyst by solvothermal method
Authors: Li Dayu , Liang Zhongyang , Zhang Wentao , Dai Shuyu , Zhang Chao 
Published: January 2021

Abstract
In this work, an one-step solvothermal synthesis method is used to prepare TiO2-reduced graphene oxide (RGO)-CuO/Fe2O3 ternary composite photocatalysts with TiO2 and CuO/Fe2O3 nanoparticles coated RGO, while the structures and photocatalytic performance of these synthesized ternary composite photocatalysts are studied. It is found that Cu2+ and Fe3+ are substituted for Ti4+ into the crystal lattice of anatase TiO2 in these prepared ternary composite photocatalysts. TiO2 and CuO/Fe2O3 nanoparticles are uniformly coated on the surface of RGO and closely contact with each other. The Cu/Fe doping has obviously improved the absorption ability on the visible light, and the bandgap of the ternary composite can be reduced. Under visible light irradiation, by increasing the Cu/Fe doping amount, the photocatalytic performance can be improved until the Cu and Fe contents reached 0.075 wt.% and 0.1 wt.%, respectively. The prepared products can be reused for eight cycles to degrade the methyl orange solution, and it retains over 93% photocatalytic efficiency.
Kinetics of the thermal reduction process in graphene oxide thin films from in-situ transport measurements
Authors: Świniarski M , Wróblewska A , Dużyńska A , Zdrojek M , Judek J 
Published: January 2021

Abstract
We investigate the influence of the thermal annealing process on the transport properties of thin films made of graphene oxide. Specially developed methodology allows us to demonstrate that the thermal annealing process of graphene oxide thin films can be described as a kinetic process with one activation energy, which equals 0.94 eV ± 0.12 eV. Moreover, we show that the electrical transport mechanism evolves with the annealing temperature (reduction level) of GO thin films. We have noticed that the Variable Range Hopping transport model change from 3D, 2D to Efros-Shklvoskii with a reduction level. Our findings contribute to further understanding of the role of kinetics in thermal reduction processes of thin films made of graphene oxide and could be useful in applications in which electrical parameters need to be tuned.
Fabrication of void-free submillimeter-scale nickel component by bottom-up electrodeposition
Authors: Lim Chee Siong , Niwa Takashi , Watanabe Satoshi , Zhang Chao , Guan Aaron , Mitsuoka Yasuyuki , Sato Hirotaka 
Published: January 2021

AbstractThis study proposed and demonstrated the feasibility of adopting metallization method of bottom-up Damascene process (seed layer over entire patterned surface) in LIGA electrodeposition process to fabricate void-free submilimeter scale metallic components. Single additive (PEG of molecular weight, Mw 10,000) rather than complicated mixture of multiple additives is studied in order to simplify the additives concentration monitoring process. Hydrodynamic flow pattern and concentration distribution of additive in the electrolyte flowing across trenches of various aspect ratio were studied by using fluid kinetics simulation. Simulation results showed the shear flow of the agitated electrolyte across the top surface caused the formation of a concentration gradient of inhibitor (PEG) within the cavity, in which the concentration of inhibitor at the top surface was consistently maintained at a higher level as compared to the bottom part of cavity. The studies on the influence of PEG concentration on electrodeposition profile showed a relatively low concentration of 10 ppm has exhibited a remarkable difference in the electrodeposition rate at the top and inner surfaces of submillimeter cavity (bottom-up electrodeposition) which subsequently eliminated the formation of void/seam-like defects associated with conventional electrodeposition. Underfilling issue was identified and a two-step electrodeposition method was proposed to mitigate the underfilling effect. Nickel component electrodeposited by PEG-added electrolyte shows higher Vickers hardness of approximately 20% as compared to additive-free sample. Flat and thin surface layer that has been electrodeposited using this technique suggested a low risk of parts’ peel-off. This resulted in the simplified process of surface polishing, planarization and demolding. This approach provides an insight into fabrication techniques for void-free multilayer, millimeter-scaled components like watch parts.
CL as a tool for device characterisation: the case of laser diode degradation
Authors: Dadgostar S , Souto J , Jiménez J 
Published: January 2021

Abstract
Cathodoluminescence is a powerful technique for the characterization of semiconductors. Due to its high spatial resolution, it is emerging as a suitable method for the study of semiconductor devices. The reduced dimension of the devices and the multilayer structure of their active parts demand experimental means with high lateral resolution and probe depth tunability for characterising the different layers forming the device structure. Degradation is a crucial technological issue for high power devices. In particular, the failures of laser diodes are due to the formation of defects during the laser operation. Those defects can be imaged by cathodoluminescence; furthermore, its spectroscopic capabilities permit to go beyond the mere observation of the non-luminescent area morphology, allowing a better understanding of the physical mechanisms of degradation. We present herein an overview of the cathodoluminescence analysis of catastrophically degraded high power laser diodes, both single mode and multimode broad emitter lasers. The study of the defects responsible of the degradation is a step forward to establish models of degradation, necessary to improve the laser power and durability.
Literature’s Vexed Democratization
Authors: Grossman Claire , Spahr Juliana , Young Stephanie 
Published: January 2021

Abstract
This article examines the contradictions of the contemporary literary field that appears both increasingly capacious and more exclusionary than in the past. Discussing the expansion of publishing enabled by digital and online technologies, we note that these changes did not reshape the demographics of most published works in the US, which remain overwhelmingly white authored. We then turn to literary prizes as an indicator of who writes prestige literature, narrating the twentieth-century formation of a racially segregated field and its slow changes against the backdrop of publishing overproduction. Combining a history of prestige literary culture with a demographic analysis of prizewinning writers (1918–2019), we discuss how a mostly white, New Critic-dominated field became the much more diverse and wide-ranging scene of the present. While this area has importantly opened up to writers of different backgrounds, our data show that the inequities of earlier prizegiving now take shape as drastic educational barriers to entry. Observing that a great deal of contemporary literature dramatizes the peculiarity of performing racial difference—often under the auspices of white audiences—we argue that the path to “excellence” has never been more narrow for writers who are not white, and Black writers in particular.
Evaluation of CBRN Respirator Protection in Simulated Fire Overhaul Settings
Authors: Staack Shawn D , Griffin Stephanie C , Lee Vivien S T , Lutz Eric A , Burgess Jefferey L 
Published: January 2021

Abstract
Overhaul is the phase of firefighting after flames have been extinguished but when products of combustion are still being released. While positive pressure self-contained breathing apparatus (SCBA) provide the highest level of respiratory protection during overhaul, use of air-purifying respirators (APRs) with suitable filters could potentially provide a lower weight, longer duration option for first responders. The objective of this study was to assess whether an APR with a chemical, biological, radiological, and nuclear (CBRN) canister could be recommended as substitution for SCBA during overhaul. A total of 15 simulated standard overhaul environments were created by burning household materials. Sampling was conducted using mannequin heads fitted with full facepiece respirators with either a CBRN canister or SCBA. In-mask and personal samples were collected for aldehydes, polynuclear aromatic hydrocarbons, inorganic acids, aromatic hydrocarbons, nitrogen dioxide, and particulate matter. An additional six simulated high-exposure overhaul environments were created in a flashover chamber by continuously adding household materials to a smoldering fire. The sampling train was the same for both the standard and high-exposure environments; however, the facepiece was sealed to the mannequin head in the high-exposure environments. In the standard overhaul environment, the CBRN canister effectively reduced the level of exposure for most contaminants, while in the high-exposure overhaul exposure setting in-mask acetaldehyde and formaldehyde were detected. In both exposure settings, the SCBA prevented almost all exposure, and therefore remains the recommended respiratory protection during overhaul.