scholarly journals Development of a web application for dissemination of educational information

Author(s):  
Maria Anatoliivna Borodin ◽  
Volodymyr Oleksandrovych Mietielov

The problem of sharing of educational information and research of components interaction on load distribution from users is considered. Purpose: to implement software to solve this problem. Design a database and project structure. Role-based access to information should be implemented. A user-friendly interface must be created for the software. Develop tests for the program that should be implemented to check the functionality and performance of the program. Use the developed tests to conduct research on load distribution from users. The developed program consists two parts (server and client). They interact using HTTP requests. The server part processes the data and verifies them. The client part receives and provides data to the server part and implements a user-friendly interface. The solution of this problem is implemented in the environments IntelliJ Idea 2020.1 (Ultimate Edition) and WebStorm 2020.1. Java 11 and JavaScript (ECMAScript 6) programming languages were used for implementation. The novelty of the work lies in the development of a program that makes it possible to use the functions necessary for studying at a higher educational institution. For example, providing students with access to study materials, the ability for all users to view their schedule. Instructors can also view the schedule of the groups they teach in the current semester. Each student can revise the teacher's schedule if he teaches at least one subject. Another important function is the management of the structure of the university (management of information about institutes, departments and study groups). We also conducted research on the performance of the program and investigated the possibility of improving the speed of the program in the event of a significant increase in active users.

2018 ◽  
Vol 7 (3) ◽  
pp. 1415
Author(s):  
Vinayak Hegde ◽  
Lavanya V Rao ◽  
Shivali B S

Examinations are an indispensable part of a student’s life. In the conventional mechanism, the question paper generation is time-consuming work for the faculty members of the educational institution. Every educational institute mandatorily expects exam setters to follow its own typesetting format. We have designed the automated question paper setting software to be user-friendly so that, paper setters can overcome from the typographic problem. Presently in most of the educational institutions question papers are set manually. It is time-consuming work and there may be chances of repetition of the same questions. So, in order to make the question paper generation more convenient to use, the web application is developed using Java Enterprise Edition (JEE) that can be accessed from LAN/Intranet.The application comes with the Admin Module and Teachers Module. The Admin grants access to the users by registering them. The faculty can access the system once they are registered. The faculty can enter questions in the database daily as per their free time. In this way, the question pool can be generated. The questions are approved by the chairperson and substandard questions are discarded. The question paper is then generated by selected course experts. The Fisher-Yates Shuffling algorithm used to choose questions randomly from the pool of questions from the database. Text Mining Algorithm aids in duplicity removal from the paper.  The generated question paper will be in Word Format. In our application, we assure better security, removal of duplicity, cost-effectiveness, and human intervention avoidance. It can be used by small-scale and large-scale institutions.  


2021 ◽  
Vol 4 ◽  
Author(s):  
Jakub Fusiak ◽  
Annemarie Käsbohrer

The lack of a harmonized model exchange formats among modelling tools impedes communication between researchers, since the exchange and usage of existing models in various software environments can be very difficult. The RaDAR model inventory aims to provide a platform to exchange models among professionals utilizing the Food Safety Knowledge Exchange (FSKX) Format (de Alba Aparicio et al. 2018) as a harmonized model exchange format. FSKX defines a framework that encodes all relevant data, metadata, and model scripts in an exchangeable file format. However, the creation of such a file can be a time-consuming and difficult process. To increase the usage of the FSK standard, we developed the RaDAR model inventory web application that targets the process of creating an FSKX file for the end user. Our inventory aims to be a user-friendly tool that allows users to create, read, edit, write, execute and compile FSKX files within the web browser. The possibility of sharing models with the public or a specific group of people facilitates collaboration and the exchange of information. Since the RaDAR model inventory is based on the open-source technology of Project Jupyter (Granger and Perez 2021), it can support nearly all relevant programming languages executed within a reproducible cloud-computing environment. The intuitive nature of the RaDAR model along with its wide range of features reduce the threshold for contribution to a harmonized model exchange format and eases collaboration. The RaDAR model inventory can be accessed at http://ejp-radar.eu.


Author(s):  
Simar Preet Singh ◽  
Rajesh Kumar ◽  
Anju Sharma ◽  
S. Raji Reddy ◽  
Priyanka Vashisht

Background: Fog computing paradigm has recently emerged and gained higher attention in present era of Internet of Things. The growth of large number of devices all around, leads to the situation of flow of packets everywhere on the Internet. To overcome this situation and to provide computations at network edge, fog computing is the need of present time that enhances traffic management and avoids critical situations of jam, congestion etc. Methods: For research purposes, there are many methods to implement the scenarios of fog computing i.e. real-time implementation, implementation using emulators, implementation using simulators etc. The present study aims to describe the various simulation and emulation tools for implementing fog computing scenarios. Results: Review shows that iFogSim is the simulator that most of the researchers use in their research work. Among emulators, EmuFog is being used at higher pace than other available emulators. This might be due to ease of implementation and user-friendly nature of these tools and language these tools are based upon. The use of such tools enhance better research experience and leads to improved quality of service parameters (like bandwidth, network, security etc.). Conclusion: There are many fog computing simulators/emulators based on many different platforms that uses different programming languages. The paper concludes that the two main simulation and emulation tools in the area of fog computing are iFogSim and EmuFog. Accessibility of these simulation/emulation tools enhance better research experience and leads to improved quality of service parameters along with the ease of their usage.


2021 ◽  
Vol 22 (S2) ◽  
Author(s):  
Daniele D’Agostino ◽  
Pietro Liò ◽  
Marco Aldinucci ◽  
Ivan Merelli

Abstract Background High-throughput sequencing Chromosome Conformation Capture (Hi-C) allows the study of DNA interactions and 3D chromosome folding at the genome-wide scale. Usually, these data are represented as matrices describing the binary contacts among the different chromosome regions. On the other hand, a graph-based representation can be advantageous to describe the complex topology achieved by the DNA in the nucleus of eukaryotic cells. Methods Here we discuss the use of a graph database for storing and analysing data achieved by performing Hi-C experiments. The main issue is the size of the produced data and, working with a graph-based representation, the consequent necessity of adequately managing a large number of edges (contacts) connecting nodes (genes), which represents the sources of information. For this, currently available graph visualisation tools and libraries fall short with Hi-C data. The use of graph databases, instead, supports both the analysis and the visualisation of the spatial pattern present in Hi-C data, in particular for comparing different experiments or for re-mapping omics data in a space-aware context efficiently. In particular, the possibility of describing graphs through statistical indicators and, even more, the capability of correlating them through statistical distributions allows highlighting similarities and differences among different Hi-C experiments, in different cell conditions or different cell types. Results These concepts have been implemented in NeoHiC, an open-source and user-friendly web application for the progressive visualisation and analysis of Hi-C networks based on the use of the Neo4j graph database (version 3.5). Conclusion With the accumulation of more experiments, the tool will provide invaluable support to compare neighbours of genes across experiments and conditions, helping in highlighting changes in functional domains and identifying new co-organised genomic compartments.


2021 ◽  
pp. 193229682098557
Author(s):  
Alysha M. De Livera ◽  
Jonathan E. Shaw ◽  
Neale Cohen ◽  
Anne Reutens ◽  
Agus Salim

Motivation: Continuous glucose monitoring (CGM) systems are an essential part of novel technology in diabetes management and care. CGM studies have become increasingly popular among researchers, healthcare professionals, and people with diabetes due to the large amount of useful information that can be collected using CGM systems. The analysis of the data from these studies for research purposes, however, remains a challenge due to the characteristics and large volume of the data. Results: Currently, there are no publicly available interactive software applications that can perform statistical analyses and visualization of data from CGM studies. With the rapidly increasing popularity of CGM studies, such an application is becoming necessary for anyone who works with these large CGM datasets, in particular for those with little background in programming or statistics. CGMStatsAnalyser is a publicly available, user-friendly, web-based application, which can be used to interactively visualize, summarize, and statistically analyze voluminous and complex CGM datasets together with the subject characteristics with ease.


2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Ye Emma Zohner ◽  
Jeffrey S. Morris

Abstract Background The COVID-19 pandemic has caused major health and socio-economic disruptions worldwide. Accurate investigation of emerging data is crucial to inform policy makers as they construct viral mitigation strategies. Complications such as variable testing rates and time lags in counting cases, hospitalizations and deaths make it challenging to accurately track and identify true infectious surges from available data, and requires a multi-modal approach that simultaneously considers testing, incidence, hospitalizations, and deaths. Although many websites and applications report a subset of these data, none of them provide graphical displays capable of comparing different states or countries on all these measures as well as various useful quantities derived from them. Here we introduce a freely available dynamic representation tool, COVID-TRACK, that allows the user to simultaneously assess time trends in these measures and compare various states or countries, equipping them with a tool to investigate the potential effects of the different mitigation strategies and timelines used by various jurisdictions. Findings COVID-TRACK is a Python based web-application that provides a platform for tracking testing, incidence, hospitalizations, and deaths related to COVID-19 along with various derived quantities. Our application makes the comparison across states in the USA and countries in the world easy to explore, with useful transformation options including per capita, log scale, and/or moving averages. We illustrate its use by assessing various viral trends in the USA and Europe. Conclusion The COVID-TRACK web-application is a user-friendly analytical tool to compare data and trends related to the COVID-19 pandemic across areas in the United States and worldwide. Our tracking tool provides a unique platform where trends can be monitored across geographical areas in the coming months to watch how the pandemic waxes and wanes over time at different locations around the USA and the globe.


Author(s):  
Thanh-Nhan Luong ◽  
Hanh-Phuc Nguyen ◽  
Ninh-Thuan Truong

The software security issue is being paid great attention from the software development community as security violations have emerged variously. Developers often use access control techniques to restrict some security breaches to software systems’ resources. The addition of authorization constraints to the role-based access control model increases the ability to express access rules in real-world problems. However, the complexity of combining components, libraries and programming languages during the implementation stage of web systems’ access control policies may arise potential flaws that make applications’ access control policies inconsistent with their specifications. In this paper, we introduce an approach to review the implementation of these models in web applications written by Java EE according to the MVC architecture under the support of the Spring Security framework. The approach can help developers in detecting flaws in the assignment implementation process of the models. First, the approach focuses on extracting the information about users and roles from the database of the web application. We then analyze policy configuration files to establish the access analysis tree of the application. Next, algorithms are introduced to validate the correctness of the implemented user-role and role-permission assignments in the application system. Lastly, we developed a tool called VeRA, to automatically support the verification process. The tool is also experimented with a number of access violation scenarios in the medical record management system.


2016 ◽  
Author(s):  
Stephen G. Gaffney ◽  
Jeffrey P. Townsend

ABSTRACTSummaryPathScore quantifies the level of enrichment of somatic mutations within curated pathways, applying a novel approach that identifies pathways enriched across patients. The application provides several user-friendly, interactive graphic interfaces for data exploration, including tools for comparing pathway effect sizes, significance, gene-set overlap and enrichment differences between projects.Availability and ImplementationWeb application available at pathscore.publichealth.yale.edu. Site implemented in Python and MySQL, with all major browsers supported. Source code available at github.com/sggaffney/pathscore with a GPLv3 [email protected] InformationAdditional documentation can be found at http://pathscore.publichealth.yale.edu/faq.


2020 ◽  
Author(s):  
Stevenn Volant ◽  
Pierre Lechat ◽  
Perrine Woringer ◽  
Laurence Motreff ◽  
Christophe Malabat ◽  
...  

Abstract BackgroundComparing the composition of microbial communities among groups of interest (e.g., patients vs healthy individuals) is a central aspect in microbiome research. It typically involves sequencing, data processing, statistical analysis and graphical representation of the detected signatures. Such an analysis is normally obtained by using a set of different applications that require specific expertise for installation, data processing and in some case, programming skills. ResultsHere, we present SHAMAN, an interactive web application we developed in order to facilitate the use of (i) a bioinformatic workflow for metataxonomic analysis, (ii) a reliable statistical modelling and (iii) to provide among the largest panels of interactive visualizations as compared to the other options that are currently available. SHAMAN is specifically designed for non-expert users who may benefit from using an integrated version of the different analytic steps underlying a proper metagenomic analysis. The application is freely accessible at http://shaman.pasteur.fr/, and may also work as a standalone application with a Docker container (aghozlane/shaman), conda and R. The source code is written in R and is available at https://github.com/aghozlane/shaman. Using two datasets (a mock community sequencing and published 16S rRNA metagenomic data), we illustrate the strengths of SHAMAN in quickly performing a complete metataxonomic analysis. ConclusionsWe aim with SHAMAN to provide the scientific community with a platform that simplifies reproducible quantitative analysis of metagenomic data.


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