bluuebunny/crossref_metadata_2025_split huggingface dataset:
Use of Non-vitamin K Antagonist Oral Anticoagulants for Stroke Prevention across the Stroke Spectrum: Progress and Prospects
Authors: Camm A. John , Atar Dan 
Published: January 2021

AbstractMultiple randomized controlled trials and many real-world evidence studies have consistently shown that non-vitamin K antagonist oral anticoagulants (NOACs) are preferable to vitamin K antagonists for thromboembolic stroke prevention in the majority of patients with atrial fibrillation (AF). However, their role in the management of patients with AF and comorbidities, as well as in other patient populations with a high risk of stroke, such as patients with prior embolic stroke of undetermined source (ESUS) and those with atherosclerosis, is less clear. There is now increasing evidence suggesting that NOACs have a beneficial effect in the prevention of stroke in patients with AF and comorbidities, such as renal impairment and diabetes. In addition, while studies investigating the efficacy and safety of NOACs for the prevention of secondary stroke in patients with a history of ESUS demonstrated neutral results, subanalyses suggested potential benefits in certain subgroups of patients with ESUS. One NOAC, rivaroxaban, has also recently been found to be effective in reducing the risk of stroke in patients with chronic cardiovascular disease including coronary artery disease and peripheral artery disease, further broadening the patient groups that may benefit from NOACs. In this article, we will review recent evidence for the use of NOACs across the stroke spectrum in detail, and discuss the progress and future prospects in the different stroke areas.
Variable Presentation and Reduced Penetrance in Autosomal Dominant Acute Necrotizing Encephalopathy Related to RANBP2 Variant
Authors: Carvalho Daniel R. , Speck-Martins Carlos E. , Martins Bernardo J. A. F. , Izumi Ana Paula , La Rocque-Ferreira Alessandra 
Published: January 2021

AbstractAcute necrotizing encephalopathy (ANE) is clinically characterized by fever, acute alteration of consciousness, seizures, and rapid progression to coma within days of onset of a viral illness occurring in healthy children without evidence of central nervous system infection. Brain magnetic resonance imaging (MRI) shows multiple symmetrical lesions affecting primarily the thalami but also brain stem, putamina, periventricular white matter, and cerebellum. Most cases of ANE are sporadic and nonrecurrent. However, a missense variant in RANBP2 has been identified in some families with recurrent ANE (OMIM # 608033), also named autosomal dominant ANE (ADANE). Clinical manifestation, clinical course, and brain MRI imaging findings of six affected members of two distinct families with ADANE were described. Sequencing revealed heterozygous c.1754C > T variant in RANBP2 (p.Thr585Met) in affected and asymptomatic family members. Only few ADANE families have been reported and it is the first description in South America. Differential diagnosis of Leigh disease and acute disseminated encephalomyelitis is discussed. Our report reinforces incomplete penetrance of ADANE and intrafamilial phenotypic variability of outcome.
Reliability and Maintainability Investigation of Generator in Steam Turbine Power Plant using RAMD analysis
Authors: Gupta Nivedita , Kumar Ashish , Saini Monika 
Published: January 2021

Abstract
Generator is key unit of steam turbine power plant which is used to convert mechanical energy into electrical energy. This energy is further used for completing the requirement generated by various sectors of country. Generator is one of the most important component of steam turbine power plant configured with seven subsystems in series configuration. So, it is necessary to ensure its smooth functioning which is attain by the proper functioning of its subcomponents. It is important to increase operational availability of subsystem. Hence, present study is proposed to investigate various reliability measures of generator used in STP through RAMD approach at component level. For this purpose, mathematical models using Markovian birth death process have been developed for all subsystems of generator. These models are very helpful in reliability, maintainability, and availability analysis of generators. RAMD analysis will play significant role in this direction. This will help to find critical component of system so that proper maintenance strategies can be proposed. It is assumed that all failure and repair rates associated with each component followed exponential distribution and adequate repair facility always remains available with system. Various system performance measures like reliability function, maintainability function, dependability function and steady state availability for different components as well as system have been evaluated. The numerical results have been derived to highlight the importance of study.
Fingerprint Based Authentication Architecture for Accessing Multiple Cloud Computing Services using Single User Credential in IOT Environments
Authors: Alemu Biniyam , Kumar Rajesh , Sinwar Deepak , Raghuwanshi Ghanshyam 
Published: January 2021

Abstract
Cloud computing technology provides access to the pool of configurable resources including storage space, application, services and on demand network. Involvement of Cloud with the organization minimizes organization efforts toward fulfilling its customer’s needs. One of the major advantages of cloud computing is the Single Sign On (SSO) technique that allows the user to access multiple application services using a single user credential. In cloud computing, there are many issues, and challenges to be discussed. However, prevention from security attacks is much more difficult in preserving privacy of user agents. This paper has proposed SSO-based bio-metric authentication architecture for cloud computing services to overcome the security and privacy attacks. Bio-metric authentication is effective for resources controlled by end devices at the time of accessing the cloud services since these devices are computationally inefficient for user information processing during authentication. Accordingly, security attack in the cloud computing gets minimized using the proposed architecture. The proposed architecture also includes a novel approach in which there exist one to one relationship between user agent and the service provider. In this user agents can use their fingerprint while requesting for registration and accessing different cloud application services at cloud. Based on comparative study with several existing architectures, the highlights of the proposed architecture have been presented.
Structuring Learning Analytics through Visual Media and Online Classrooms on Social Cognition during COVID-19 Pandemic
Authors: Latheef Afeefa , Liyakath Ali Mohdhoom Fathima , Bhardwaj Aradhana Balodi , Shukla Vinod Kumar 
Published: January 2021

Abstract
Media as the core source of information and knowledge disperse in the society, its effect on the learning, understanding and analysing about the society in the human minds and cognition is certainly impacted. In focal to the visual media such as advertisement, movies, video etc., it enunciates and indicates a high level of learning process and social learning. Media has a huge impact on the different aspects of cognition in the population, especially on the age category of teenagers and young adults. With the current situation of covid 19, there has been a paradigm shift within the educational sector, forcing visual media as the key source of education and learning, with many countries utilizing remote learning or digital learning to cope with the current educational crisis. This study therefore aims to investigate and understand the impact of the visual media and different video learning platforms in improvement of the social cognition and learning among student. Questionnaire survey method was employed as a tool to collect data from the sample of 250 students between the age group of 16 – 25 and a sample of 155 teachers with the experience of 1 -10 + years in the field of education across UAE and India. The result indicates that the student population showcase a keen interest and participation on the information and knowledge dispersed through screens such as movies and presentation rather than the content published such as newspaper and books. It helps students foster self-awareness, cultural value, cognitive skills and moral wellbeing with the help of visual media.
Hybrid Learning Model for Metal Artifact Reduction
Authors: Bedi Pradeep , Goyal S B , Yadav Dileep Kumar , Kumar Sunil , Sharma Monika 
Published: January 2021

Abstract
In today’s healthcare, the human brain imaging is done for finding the tumors and other disorders of the brain. The Magnetic Resonance Imaging (MRI) plays a significant role throughout the complete clinical procedure starting from diagnostics and treatment planning to surgical processes and follow up studies. The MRI of brain allows the clinical expert for the earliest detection and treatment of brain abnormality or any neurological diseases, which is the most treatable stage that gives patients the greatest chance of survival. An artifact is a feature appearing in an image which is not present in the original imaged object. The types of artifacts are herringbone artifact, zipper artifact, motion artifact, aliasing artifact, chemical shift artifact, magnetic susceptibility artifact, central point artifact, Gibbs ringing artifact and intensity inhomogeneity artifact. After segmentation, the features are extracted using Gray level co-occurrence matrix (GLCM) and an CNN, Deep belief network, Proposed hybrid model (Based on CNN and Deep belief network (DBN)) and Morphological Technique with Segmentation Techniques is implemented to classify the brain MRI images as either normal (without tumor) or abnormal (with tumor). Proposed hybrid model for metal artifact reduction and represent though the experiment our proposed model very effective to existing one. Results in Accuracy (in %) Before artifact removal(92.12%), After artifact removal (95.77%)
Machine Learning Based Predictive Model for Coronavirus Pandemic
Authors: Singh Supreet , Sharma Lavanya , Kumar Birender 
Published: January 2021

AbstractTechnological advancements have a rapid effect on each domain of day today life, whether it is medical domain or any other domain. Artificial intelligence has shown promising outcomes in emergency department through its decision making by investigating the data. COVID-19 has affected many countries across the globe in a matter of no time. Citizens all over the world are susceptible to its consequences in future.Covid-19 being a contagious disease needs a program that will make it easier for the tracking, the spread and preventing the future cases. Proposed algorithm that can predict on-going Covid-19 positive cases in India. For experimental analysis machine learning algorithm has been coded to make future predictions.
Survey on Internet of Things and its Application in Agriculture
Authors: Mishra Kanderp Narayan , Kumar Shishir , Patel Nileshkumar R. 
Published: January 2021

Abstract
The Internet of Things (IoT) is empowering the field of agriculture. The IoT application helps the farmer and makes him aware about all the latest information which is related to agriculture. In this study, authors have found that the implementation of IoT is very important in the field of agriculture that makes farming smarter. IoT applications make farmers smarter with the latest information about the crop and weather. By using the IoT application the farmer can prepare a plan for next season’s crop. With the help of IoT based agriculture application the farmers already know the information about the weather, soil, wind speed and direction, relative humidity, and temperature. The farmers know about the disease of crops and then consult the expert and get an appropriate solution to the disease. The experts may advise the farmer how farmers can protect the crop from the disease. The IoT agriculture application helps to increase the production of crops and reduce the loss of crops from the disease. The IoT based agriculture application is like a friend of a farmer because the IoT based agriculture applications are helping the farmer at every moment of agriculture activities. India has set a food grain production target of 298.3 million tonnes for the current fiscal year 2020-21 which is 2.5% higher compared to previous fiscal year’s targets. Agriculture sector contribution to Indian economy is 17%. To empower Indian farmers and in turn to empower Indian economy, IoT based agriculture applications are essential for the farmers.
Segmenting e-Commerce Customer through Data Mining Techniques
Authors: Punhani Ritu , Arora V.P.S , Sai Sabitha A. , Shukla Vinod Kumar 
Published: January 2021

Abstract
Business-to-business e-commerce is in much attention nowadays, mainly due to its growing use. In today’s world, it has become imperative for companies to segment their customers and thereby take required measures to survive against other companies. Since there exist a lot, each company must fulfil the demands of their users or they might lose them to other alternatives that exist. This report aims to analyse the customer data from two years: 2018 and 2019 of the company: Autofurnish.com and thereby recommend methods to increase customer influx and give suggestions on what mistakes should not be repeated by the company in future for better performance and sales. To analyse the database, RapidMiner tool has been used. RapidMiner is an open source predictive analytic software that gives support regarding data mining. It lets the user to build models based on their needs and gives solutions quickly. For this analysis, K- means algorithm clustering will be used. Clustering is dividing groups based on similarities and K means is one of the very commonly used methods to do so. In the software, data has been imported having information about customers which is then analysed to prove different results draw a contrast between two years as told before keeping customer segmentation in mind based on various attributes given in the dataset. Relationships between the features are identified as assess to company’s performance.
Three-layer Authentication in Keystroke Dynamics using Time based Tool
Authors: Bhasin Namisha , Tarar Sandhya 
Published: January 2021

Abstract
Having a secure and sound system is the most important need of the end-user. Confidential and authentic information about the system must be available to the genuine user when required. This paper presents a generalized Keystroke Dynamics Technique for identification of genuine users. The method works for the authentication of the user while user is entering the password to using the system. It is a three-layer approach which first check the typing pattern while entering the password then it also monitors the system while user is using the system. Different users have different typing pattern which could be used to recognize a user. For identification of the user a time-based tool is used to collect data pertaining to the typing time of each user for words of different lengths. This is a very easy and cost-effective way of collecting data for differentiating between a genuine user and imposter. At first layer elbow method is used to know unknown targets depending upon different word combinations. For the second layer principal component analysis (PCA) is used to find suitable factors where user typing pattern is making users indistinguishable. For the third step Long-Short Term Memory (LSTM) technique is used to forecast whether the user is a genuine user or an imposter.
Solution of Einstein’s Field Equations for the Static Fluid Sphere
Authors: Singh Abhishek Kumar 
Published: January 2021

Abstract
In this paper we deals about some exact static spherical solution of Einstein’s field equations with Λ = 0 (cosmological constant) and p = ρ (taking suitable choice of g11 and g44). We have eψ = km5 4 and e−χ = l, which help to investigate the value of eχ. Here some previously known solutions are contained as a particular case. The explicit expressions for rotation, shear scalar of expansion and fluid velocity have also investigated. We get some previously known solution for distinct values of n. Here Λ = 0, this implies that Einstein element would degenerate into a line element of special relativity for flat space time. It also helpful to investigates solution for the perfect fluid core.
Evaluating Artificial Intelligence in Education for Next Generation
Authors: Joshi Shubham , Rambola Radha Krishna , Churi Prathamesh 
Published: January 2021

Abstract
The use of Artificial Intelligence (AI) is now observed in almost all areas of our lives. Artificial intelligence is a thriving technology to transform all aspects of our social interaction. In education, AI will now develop new teaching and learning solutions that will be tested in different situations. Educational goals can be better achieved and managed by new educational technologies. First, this paper analyses how AI can use to improve outcomes in teaching, providing examples of how technology AI can help educators use data to enhance fairness and rank of education in developing countries. This study aims to examine teacher’s and student’s perceptions of the use and effectiveness of AI in education. Its curse and perceived as a good education system and human knowledge. The optimistic use of AI in class is strongly recommended by teachers and students. But every teacher is more adapted to new technological changes than students. Further research on generational and geographical diversity on perceptions of teachers and students can contribute to the more effective implementation of AI in Education (AIED).
Students’ perceptions towards IoTs adoption: A case study
Authors: Singh Upasana G , Msibi Andile 
Published: January 2021

Abstract
The Internet of Things (IoT) is expanding the interdependence of people, objects and systems. It has enforced the idea of a global infrastructure of “things” networked to enable unlimited connectivity, communication and collaboration across physical, biological and digital spheres. The ever-present internet is the foundation of this phenomenon (IoT) and continues to facilitate innovation in this field. Over the past decade, many forms of IoT have been widely adopted in manufacturing and enterprise spaces, which has led to dramatic changes in production processes and the supply chain. Despite the convenience, real-time monitoring and reporting capabilities offered by IoT adoption amongst individual consumers is unclear. The purpose of this paper is to understand the factors that determine the adoption of IoT devices and/or applications by individuals whether for education, job, security or health purposes. The study uses mixed methods research to examine the factors of IoT adoption by individuals in their daily lives. Qualitative and Quantitative analysis using the Technology Acceptance Model (TAM) reveals how perceptions of users affect the intention to use Information Technology (IT) and actual adoption. One hundred students from the University of KwaZulu-Natal (UKZN) participated in the study. The findings of the study revealed that positive attitude towards usefulness, ease of use, user satisfaction had a positive influence on the adoption of IoT devices and/or applications. It also revealed that affordability, basic knowledge, tech savvy attitude, security and internet access influence the behaviour of users and non-users of IoT technologies.
Assessing Impact of Climate Change on Rainfall Patterns of Vadodara District, Gujarat, India
Authors: Shah N V , Patel Y S , DBhangaonkar P 
Published: January 2021

Abstract
Due to climate change, variable rainfall pattern and rapid urbanization during last two decades, Vadodara district is frequently facing problems related to flooding. In present research paper frequency Analysis is carried from the available hydrometeorologicalhistorical rainfall data series of past four decades for Vadodara District, Gujarat. Rainbow software is used to carry out the analysis. Homogeneity of data is checked and Goodness-of-fit is tested. A logarithm transformation is selected to plot magnitude of event and corresponding probabilities of exceedance. The mixed Global probability distribution is used to explore the re-occurrence of rainfall events with certain return period. Analysis revealed that the rainfall events causing extreme flooding conditions in Vadodara District has frequency of re-occurrence as 25 years.
Study of Echo Cancellation approach by using Least Mean Square (LMS) Algorithm
Authors: PavanKalyan I. , Jaya Santosh G. , Prasad K.H.K. , Nandan Durgesh 
Published: January 2021

Abstract
Sound is the origin of communication. We are using sound channel for interaction. The acoustic signal introduces echo signal properties which lead the original signal as error signal. In most of applications the adaptive filters implemented in time domain works quite efficiently. However, the complication of the adaptive filter increases as the impulsive reaction becomes quite large hence it cannot be implemented efficiently in time domain. Acoustic echo cancellation is one example where this can happen. In this paper we will explain about to acoustic cancellation and different methods that are adopted to overcome the interference of noise by using various levels of algorithms and apply it to an error signal and makes solution for the problem, verifies the performance, describe the best and suitable technique which gives most effective results.
Research on EFI multi-point synchronous initiation technology based on mems process
Authors: Su Q , Chu E Y , Xie R Zh , Liu W , Han K H 
Published: January 2021

Abstract
In order to solve the problems of the warhead initiation system due to the low safety of conventional detonator arrays and the poor synchronization of the explosion logic network, as well as the MEMS batch integration requirements, a research on EFI multi-point synchronous initiation technology based on MEMS technology was carried out. Explosive foil was prepared by magnetron sputtering and photolithography. SU-8 photoresist flying sheet layer and acceleration chamber were prepared on the bridge foil by UV thick glue technology, and single-point, two-point parallel and three-point parallel were realized. The two batches of two and a total of four points and three strings of three and a total of nine points explosion foil initiators were batch-integrated and tested for the synchronism of the flying sheet effect. The test results show that the average time between two points, three points, and four points is less than 80ns, and the synchronization time is small; the average time at nine points is less than 200ns, and the synchronization time is large.
Study on the explosion field temperature and gas products of FOX-7 / RDX based aluminized explosives
Authors: Yang X , Tian X , Zhao K , Dong J , Huang Y F , Feng B , Wang X F 
Published: January 2021

Abstract
To investigate the effect of RDX on the explosion reaction mechanism of FOX-7 based aluminized explosives in vacuum environment, the explosion field temperature of FOX-7 based aluminized explosives and RDX/FOX-7 based aluminized explosives were measured in an isolated explosion chamber. The results show that adding RDX would increase the equilibrium temperature of explosion field of FOX-7-based aluminized explosives. The equilibrium temperature of FOX-7-based aluminized explosives and RDX/FOX-7-based aluminized explosives increases first and then decreases with the increasing of Al content, which shows the highest equilibrium temperature as the Al content is 30%. When the Al content is less than 25%, the explosion peak temperature of FOX-7-based aluminized explosives would increased by adding RDX, and when the aluminium content is more than 30%, the explosion peak temperature of FOX-7-based aluminized explosives can be reduced by adding RDX.