scholarly journals MOVING: A User-Centric Platform for Online Literacy Training and Learning

2021 ◽  
pp. 77-97
Author(s):  
Aitor Apaolaza ◽  
Tobias Backes ◽  
Sabine Barthold ◽  
Irina Bienia ◽  
Till Blume ◽  
...  
Keyword(s):  
Machine Learning ◽  
Web Application ◽  
Large Scale ◽  
Learning Technologies ◽  
Public Administrators ◽  
Scientific Publications ◽  
Front End ◽  
Main Components ◽  
Young Researchers ◽  
The Web

AbstractIn this paper, we present an overview of the MOVING platform, a user-driven approach that enables young researchers, decision makers, and public administrators to use machine learning and data mining tools to search, organize, and manage large-scale information sources on the web such as scientific publications, videos of research talks, and social media. In order to provide a concise overview of the platform, we focus on its front end, which is the MOVING web application. By presenting the main components of the web application, we illustrate what functionalities and capabilities the platform offer its end-users, rather than delving into the data analysis and machine learning technologies that make these functionalities possible.

scholarly journals Detecting Anti Ad-blockers in the Wild

2017 ◽  
Vol 2017 (3) ◽  
pp. 130-146 ◽  
Author(s):  
Muhammad Haris Mughees ◽  
Zhiyun Qian ◽  
Zubair Shafiq
Keyword(s):  
Machine Learning ◽  
Large Scale ◽  
Online Advertising ◽  
Arms Race ◽  
Third Party ◽  
Measurement Study ◽  
Economic Threat ◽  
In The Wild ◽  
Automated Machine Learning ◽  
The Web

Abstract The rise of ad-blockers is viewed as an economic threat by online publishers who primarily rely on online advertising to monetize their services. To address this threat, publishers have started to retaliate by employing anti ad-blockers, which scout for ad-block users and react to them by pushing users to whitelist the website or disable ad-blockers altogether. The clash between ad-blockers and anti ad-blockers has resulted in a new arms race on the Web. In this paper, we present an automated machine learning based approach to identify anti ad-blockers that detect and react to ad-block users. The approach is promising with precision of 94.8% and recall of 93.1%. Our automated approach allows us to conduct a large-scale measurement study of anti ad-blockers on Alexa top-100K websites. We identify 686 websites that make visible changes to their page content in response to ad-block detection. We characterize the spectrum of different strategies used by anti ad-blockers. We find that a majority of publishers use fairly simple first-party anti ad-block scripts. However, we also note the use of third-party anti ad-block services that use more sophisticated tactics to detect and respond to ad-blockers.

scholarly journals The role of e-learning in the modern high education

2021 ◽  
Vol 10 (4) ◽  
pp. 4243-4251
Author(s):  
V. V. Filatov ◽  
A. V. Gobysh
Keyword(s):  
Large Scale ◽  
Learning Technologies ◽  
Educational Process ◽  
Scientific Publications ◽  
Distant Learning ◽  
Force Majeure ◽  
E Learning ◽  
Mathematical Discipline ◽  
Additional Education

The article is devoted to the problem of establishing the frames to use distant learning in higher education. The topic relevance is related to emerging a force majeure situation associated with a pandemic, which made it possible to carry out a unique experiment on such large-scale training applying. The paper analyzes some aspects of this problem concerning the mathematical discipline learning at the technical university junior courses. The study is based on the analysis of scientific publications by domestic and foreign authors devoted to the problems of mixed learning, distant learning, and peculiarities of teaching mathematical disciplines in universities. The author conclude that the main problems of introducing e-learning and distant learning technologies into the educational process is insufficient motivation of students pronounced especially in junior courses. They note that the effectiveness of using distant educational technologies in additional education is largely due to the good motivation of people who want to improve their professional level. The paper discusses results obtained during the forced transition to distant learning (March-July 2020), in particular, gives the rationale for a certain model of mixed learning. It emphasizes that, as the threat of the pandemic situation repetition, as well as the need for a new transition to e-learning are not excluded, the problem of motivating students should be given special attention at all educational process levels.

scholarly journals A Study on Comparison of Network Location Efficiency of Web Application Firewall

2018 ◽  
Vol 7 (3.33) ◽  
pp. 183
Author(s):  
Sung-Ho Cho ◽  
Sung-Uk Choi ◽  
. .
Keyword(s):  
Web Services ◽  
Web Application ◽  
Large Scale ◽  
Service Providers ◽  
Web Security ◽  
Small Scale ◽  
Internet Service ◽  
Large Scale Networks ◽  
The Web ◽  
Line Type

This paper proposes a method to optimize the performance of web application firewalls according to their positions in large scale networks. Since ports for web services are always open and vulnerable in security, the introduction of web application firewalls is essential. Methods to configure web application firewalls in existing networks are largely divided into two types. There is an in-line type where a web application firewall is located between the network and the web server to be protected. This is mostly used in small scale single networks and is vulnerable to the physical obstruction of web application firewalls. The port redirection type configured with the help of peripheral network equipment such as routers or L4 switches can maintain web services even when physical obstruction of the web application firewall occurs and is suitable for large scale networks where several web services are mixed. In this study, port redirection type web application firewalls were configured in large-scale networks and there was a problem in that the performance of routers was degraded due to the IP-based VLAN when a policy was set for the ports on the routers for web security. In order to solve this problem, only those agencies and enterprises that provide web services of networks were separated and in-line type web application firewalls were configured for them. Internet service providers (ISPs) or central line-concentration agencies can apply the foregoing to configure systems for web security for unit small enterprises or small scale agencies at low costs.  

scholarly journals Analysis of the Productive, Structural, and Dynamic Development of Augmented Reality in Higher Education Research on the Web of Science

2019 ◽  
Vol 9 (24) ◽  
pp. 5306 ◽  
Author(s):  
Jesús López Belmonte ◽  
Antonio-José Moreno-Guerrero ◽  
Juan Antonio López Núñez ◽  
Santiago Pozo Sánchez
Keyword(s):  
Higher Education ◽  
Augmented Reality ◽  
Virtual Environments ◽  
Web Of Science ◽  
Learning Technologies ◽  
Scientific Publications ◽  
The Status ◽  
Meta Analyses ◽  
Education And Development ◽  
The Web

Augmented reality is an emerging technology that has gained great relevance thanks to the benefits of its use in learning spaces. The present study focuses on determining the performance and scientific production of augmented reality in higher education (ARHE). A bibliometric methodology for scientific mapping has been used, based on processes of estimation, quantification, analytical tracking, and evaluation of scientific research, taking as its reference the analysis protocols included in the Preferred Reporting Items for Systematic reviews and Meta-analyses for Protocols (PRISMA-P) matrix. A total of 552 scientific publications on the Web of Science (WoS) have been analyzed. Our results show that scientific productions on ARHE are not abundant, tracing its beginnings to the year 1997, with its most productive period beginning in 2015. The most abundant studies are communications and articles (generally in English), with a wide thematic variety in which the bibliometric indicators “virtual environments” and “higher education” stand out. The main sources of origin are International Technology, Education and Development Conference (INTED) Proceedings and Education and New Learning Technologies (EDULEARN) Proceedings, although Spanish institutions are the most prolific. In conclusion, studies related to ARHE in the WoS have become increasingly abundant since ARHE’s research inception in 1997 (and especially since 2009), dealing with a wide thematic variety focused on “virtual environments” and “higher education”; abundant manuscripts are written in English (communications and articles) and originate from Spanish institutions. The main limitation of the study is that the results only reveal the status of this issue in the WoS database.

Gamification and Its Application in the Social Environment

2020 ◽  
Vol 13 (3) ◽  
pp. 58-79
Author(s):  
Staling Cordero-Brito ◽  
Juanjo Mena
Keyword(s):  
Social Environment ◽  
Web Of Science ◽  
The United States ◽  
Scientific Publications ◽  
Scientific Databases ◽  
The Social ◽  
Motivation And Engagement ◽  
Main Components ◽  
Over Time ◽  
The Web

This study sets out to conduct a systematic review of the emergence and evolution of gamification in the social environment, its main components, and its application as a learning tool through the motivation and engagement it generates in people. The results were obtained by consulting two major scientific databases, namely, Scopus and the Web of Science, which provided 136 articles published on the social environment from 2011 through to mid-2016 using the term gamification. The results of this study reveal how over time gamification has been gaining importance in the social environment through the use of its components. The highest number of scientific publications come from the United States and Spain. In addition, the use of gaming components increases motivation and engagement. It shows how gamification uses (individual or group) rewards according to the context to achieve the proposed objectives, being successfully implemented in education, health, services, and social learning.

scholarly journals IOT based Advanced Medicine Dispenser Integrated with an Interactive Web Application

2018 ◽  
Vol 7 (4.10) ◽  
pp. 46
Author(s):  
Nanda Kishor Panda ◽  
Shubham Bhardwaj ◽  
H. Bharadwaj ◽  
Rohil Singhvi
Keyword(s):  
Machine Learning ◽  
Web Application ◽  
The Internet ◽  
Human Machine Interaction ◽  
Everyday Objects ◽  
Front End ◽  
Healthcare Monitoring ◽  
User Friendly ◽  
Machine Interaction ◽  
Interactive User

Internet of Things (IOT) is a development of the internet which plays a  major role in integrating human-machine interaction by allowing everyday objects to send and receive data in a variety of applications. Using IOT in healthcare monitoring provides an avenue for doctors and patients to interact and to track the dosage of medication administered. The paper presents an interactive, user friendly network integrated with an automated medicine dispenser which uses IOT, cloud computing and machine learning. The network was built on a python tornado framework with a front end developed using materialise CSS. The feasibility of this approach was validated by building a prototype and conducting a survey.  

scholarly journals Evidence of Open Access of scientific publications in Google Scholar: a large-scale analysis

2018 ◽  
Author(s):  
Alberto Martín-Martín ◽  
Rodrigo Costas ◽  
Thed van Leeuwen ◽  
Emilio Delgado López-Cózar
Keyword(s):  
Open Access ◽  
Large Scale ◽  
Web Of Science ◽  
Google Scholar ◽  
Scale Analysis ◽  
Scientific Publications ◽  
Large Scale Analysis ◽  
Citation Indexes ◽  
Legal Forms ◽  
The Web

This article uses Google Scholar (GS) as a source of data to analyse Open Access (OA) levels across all countries and fields of research. All articles and reviews with a DOI and published in 2009 or 2014 and covered by the three main citation indexes in the Web of Science (2,269,022 documents) were selected for study. The links to freely available versions of these documents displayed in GS were collected. To differentiate between more reliable (sustainable and legal) forms of access and less reliable ones, the data extracted from GS was combined with information available in DOAJ, CrossRef, OpenDOAR, and ROAR. This allowed us to distinguish the percentage of documents in our sample that are made OA by the publisher (23.1%, including Gold, Hybrid, Delayed, and Bronze OA) from those available as Green OA (17.6%), and those available from other sources (40.6%, mainly due to ResearchGate). The data shows an overall free availability of 54.6%, with important differences at the country and subject category levels. The data extracted from GS yielded very similar results to those found by other studies that analysed similar samples of documents, but employed different methods to find evidence of OA, thus suggesting a relative consistency among methods.

Predictive analytics for crystalline materials: bulk modulus

RSC Advances ◽  
2016 ◽  
Vol 6 (97) ◽  
pp. 95246-95251 ◽  
Author(s):  
Al'ona Furmanchuk ◽  
Ankit Agrawal ◽  
Alok Choudhary
Keyword(s):  
Machine Learning ◽  
Bulk Modulus ◽  
Predictive Model ◽  
Web Application ◽  
Predictive Analytics ◽  
Generalized Model ◽  
Crystalline Materials ◽  
The Web

The machine learning-based generalized model developed for forecasting bulk moduli of various types of stoichiometric and non-stoichiometric crystalline materials. The web application (ThermoEl) deploying the developed predictive model is available for public use.

Abstract 135: Towards Automated Incidence Rate Reporting: Leveraging Machine Learning Technologies to Assist Stroke Adjudication in a Large-scale Epidemiological Study

Stroke ◽  
2017 ◽  
Vol 48 (suppl_1) ◽  
Author(s):  
Yizhao Ni ◽  
Kathleen Alwell ◽  
Charles J Moomaw ◽  
Daniel Woo ◽  
Opeolu Adeoye ◽  
...  
Keyword(s):  
Machine Learning ◽  
Large Scale ◽  
International Classification Of Diseases ◽  
Epidemiological Studies ◽  
Incidence Rates ◽  
Learning Technologies ◽  
Prediction Intervals ◽  
Administrative Databases ◽  
Sensitivity Specificity ◽  
Improved Accuracy

Introduction: Epidemiological studies utilizing administrative databases typically use International Classification of Diseases (ICD) codes to identify stroke cases and estimate incidence rates. However, they are limited by sensitivity/specificity across study designs and stroke types. Few studies utilize physician chart review of patient records to confirm cases for improved accuracy, as this is labor intensive. We sought to develop a machine learning (ML) approach that could adjudicate potential stroke events. Methods: We utilized 8081 hospitalized stroke events in the Greater Cincinnati/Northern Kentucky Stroke Study. The study coordinators identified events with stroke-related diagnoses (ICD9 codes 430-438) from 17 regional hospitals in 2005 and 2010 and performed detailed chart abstraction. The information (e.g. diagnostic tests) was abstracted from patients’ medical records for each event, followed by physician case adjudication. Utilizing all clinical variables, a ML algorithm (logistic regression) was used to predict stroke cases and subtypes (ischemic, hemorrhagic, TIA, and non-strokes). Linear regression (LR) was applied to calibrate ML outputs and estimate prediction intervals based on gold-standard physician adjudication. The ML and LR models were trained on one year of data and tested on the other year. The model results were compared with using ICD-9 (ischemic: 434/436; hemorrhagic: 430-432; TIA: 435; non-stroke: other codes) calibrated by LR analysis. Results: Prediction intervals generated by ML covered the majority of true numbers of stroke events (Table). Compared with ICD9 codes, the ML algorithm achieved better sensitivity/specificity and more “hits” with narrower prediction intervals. Conclusions: The ML algorithm showed promise in matching physician adjudication and subtyping stroke cases. Future work is required to refine the methods to automate stroke epidemiology with improved accuracy and granularity.

scholarly journals Connected Bike-smart IoT-based Cycling Training Solution

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1473 ◽  
Author(s):  
George Catargiu ◽  
Eva-H. Dulf ◽  
Liviu C. Miclea
Keyword(s):  
Web Application ◽  
Alternative Solution ◽  
Software Components ◽  
Android Application ◽  
Front End ◽  
Cycling Training ◽  
The Web

The Connected Bike project combines several technologies, both hardware and software, to provide cycling enthusiasts with a modern alternative solution for training. Therefore, a trainer can monitor online through a Web Application some of the important parameters for training, more specifically the speed, cadence and power generated by the cyclist. Also, the trainer can see at every moment where the rider is with the aid of a GPS module. The system is built out of both hardware and software components. The hardware is in charge of collecting, scaling, converting and sending data from sensors. On the software side, there is the server, which consists of the Back-End and the MQTT (Message Queues Telemetry Transport) Broker, as well as the Front-End of the Web Application that displays and manages data as well as collaboration between cyclists and trainers. Finally, there is the Android Application that acts like a remote command for the hardware module on the bike, giving the rider control over how and when the ride is monitored.

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