Modern Web Browsers Research Articles

A Review of Probabilistic Techniques Used for Web browsers’ Caching

Cache memory plays a central role in improving the performance of web servers, especially for big data transmission, which response time is constrained. It is necessary to use an effective method, such as web cache. Browsers' cache has a significant role according to less bandwidth use, response time and traffic load as well as beneficial if the internet connection is slow. Due to the space limitations, modern browsers companies attempt to use a method to store a great number of web objects and to advance the effectiveness of web browsers. Many scientists have been working to discover and recommend various techniques for this purpose. This study consequently reviews the recent likelihood probabilistic methods, to figure out how browsers store web objects in their caches, and which methods are used to load more speedily and to store a great number of web objects. The comparison between numerous browsers performed to pick and recommend the utmost one for usage. The result has shown that each browser using RI (Ratio Improvement) has powerful performance; to be discussed later. It has proposed using Google Chrome browser because web objects are placed in its cache through the RI technique that correlated with browsers' effectiveness.

Review of Probabilistic Techniques Used for Web browsers’ Caching

Cache memory plays a central role in improving the performance of web servers, especially for big data transmission, which response time is constrained. It is necessary to use an effective method, such as web cache. Browsers' cache has a significant role according to less bandwidth use, response time and traffic load as well as beneficial if the internet connection is slow. Due to the space limitations, modern browsers companies attempt to use a method to store a great number of web objects and to advance the effectiveness of web browsers. Many scientists have been working to discover and recommend various techniques for this purpose. This study consequently reviews the recent likelihood probabilistic methods, to figure out how browsers store web objects in their caches, and which methods are used to load more speedily and to store a great number of web objects. The comparison between numerous browsers performed to pick and recommend the utmost one for usage. The result has shown that each browser using RI (Ratio Improvement) has powerful performance; to be discussed later. It has proposed using Google Chrome browser because web objects are placed in its cache through the RI technique that correlated with browsers' effectiveness.

Efficient deep learning techniques for the detection of phishing websites

Phishing is a fraudulent practice and a form of cyber-attack designed and executed with the sole purpose of gathering sensitive information by masquerading the genuine websites. Phishers fool users by replicating the original and genuine contents to reveal personal information such as security number, credit card number, password, etc. There are many anti-phishing techniques such as blacklist- or whitelist-, heuristic-feature- and visual-similarity-based methods proposed as of today. Modern browsers adapt to reduce the chances of users getting trapped into a vicious agenda, but still users fall as prey to phishers and end up revealing their secret information. In a previous work, the authors proposed a machine learning approach based on heuristic features for phishing website detection and achieved an accuracy of 99.5% using 18 features. In this paper, we have proposed novel phishing URL detection models using (a) Deep Neural Network (DNN), (b) Long Short-Term Memory (LSTM) and (c) Convolution Neural Network (CNN) using only 10 features of our earlier work. The proposed technique achieves an accuracy of 99.52% for DNN, 99.57% for LSTM and 99.43% for CNN. The proposed techniques utilize only one third-party service feature, thus making it more robust to failure and increases the speed of phishing detection.

Information systems for creating e-learning resources for realization of resource-based learning aimed at students majoring in Economics

The authors have examined and analysed information systems (Constructor Electronic books 1.1.3, SunRav, Webnode, Google Classroom) in terms of functionality, which will allow creating electronic educational resources for introduction of the resource-based learning for students in higher school. It has been proven that Constructor Electronic books 1.1.3 and SunRav provide the creation of online tutorials that are run using an exe-file. Webnode Website Designer enables the creation of open-source electronic educational resources that are freely available on the World Wide Web (teacher's personal sites, discipline study site, e-learning teaching / learning support of disciplines, etc.). These electronic educational resources effectively and fully function in any modern browser: Google Chrome, Opera, Mozilla Firefox, Internet Explorer, etc., and also provide the opportunity to work online with students. Using Google Classroom is appropriate when you need to organise full-time online (virtual) online distance learning. For the resource-based learning of the students majoring in Economics, the authors have developed and presented an electronic manual "Higher Mathematics for Economists" in the Designer of Electronic Textbooks (N. Kononets); an educational and methodological complex of the discipline "Economic Informatics" in the environment of SunRav IS (N. Kononets); a site of study studio "Digital Technologies in the Economist's Work", created at Webnode (V. Baliuk); a Virtual Classroom "Educational practice in information systems and technologies in Economics" in Google Classroom (N. Kononets and V. Baliuk).

Libsbmljs—Enabling web-based SBML tools

The SBML standard is used in a number of online repositories for storing systems biology models, yet there is currently no Web-capable JavaScript library that can read and write the SBML format. This is a severe limitation since the Web has become a universal means of software distribution, and the graphical capabilities of modern web browsers offer a powerful means for building rich, interactive applications. Also, there is a growing developer population specialized in web technologies that is poised to take advantage of the universality of the web to build the next generation of tools in systems biology and other fields. However, current solutions require server-side processing in order to support existing standards in modeling. We present libsbmljs, a JavaScript/WebAssembly library for Node.js and the Web with full support for all SBML extensions. Our library is an enabling technology for online SBML editors, model-building tools, and web-based simulators, and runs entirely in the browser without the need for any dedicated server resources. We provide NPM packages, an extensive set of examples, JavaScript API documentation, and an online demo that allows users to read and validate the SBML content of any model in the BioModels and BiGG databases. We also provide instructions and scripts to allow users to build a copy of libsbmljs against any libSBML version. Although our library supports all existing SBML extensions, we cover how to add additional extensions to the wrapper, should any arise in the future. To demonstrate the utility of this implementation, we also provide a demo at https://libsbmljsdemo.github.io/ with a proof-of-concept SBML simulator that supports ODE and stochastic simulations for SBML core models. Our project is hosted at https://libsbmljs.github.io/, which contains links to examples, API documentation, and all source code files and build scripts used to create libsbmljs. Our source code is licensed under the Apache 2.0 open source license.

An Emulator Software Tool for Improving Learning of DC-DC Converters

Power electronics disciplines involve different fundamental topics and technologies. The use of the Internet facilitates and supports the transmission of the theoretical concepts of the teacher to the student and improve the sequence of activities within the available time. The main goal of this work is to develop an emulator software tool to facilitate the usage of control loop fundamentals when applied to DC-to-DC converters. This emulator is a very solid tool for the educational community, and it allows students to analyze and design control circuits in a very flexible way. This resource is available online without time restrictions, allowing users to choose where and when they can learn and interact with the tool which offers a variety of different DC-DC converters, compensation networks and feedback topologies. Once the selection has been made and the different values of the components have been established, a frequency response analysis is shown. The development of the software tool can be operated using any modern browser under any platform and device. The effectiveness of the presented emulator software tool was assessed with the feedback obtained for the students and the results obtained therefor.

GlycoGlyph: a glycan visualizing, drawing and naming application.

Glycan structures are commonly represented using symbols or linear nomenclature such as that from the Consortium for Functional Glycomics (also known as modified IUPAC-condensed nomenclature). No current tool allows for writing the name in such format using a graphical user interface (GUI); thus, names are prone to errors or non-standardized representations. Here we present GlycoGlyph, a web application built using JavaScript, which is capable of drawing glycan structures using a GUI and providing the linear nomenclature as an output or using it as an input in a dynamic manner. GlycoGlyph also allows users to save the structures as an SVG vector graphic, and allows users to export the structure as condensed GlycoCT. The application can be used at: https://glycotoolkit.com/Tools/GlycoGlyph/. The application is tested to work in modern web browsers such as Firefox or Chrome. aymehta@bidmc.harvard.edu or rcummin1@bidmc.harvard.edu.

EpiMetal: an open-source graphical web browser tool for easy statistical analyses in epidemiology and metabolomics.

MotivationAn intuitive graphical interface that allows statistical analyses and visualizations of extensive data without any knowledge of dedicated statistical software or programming. ImplementationEpiMetal is a single-page web application written in JavaScript, to be used via a modern desktop web browser.General featuresStandard epidemiological analyses and self-organizing maps for data-driven metabolic profiling are included. Multiple extensive datasets with an arbitrary number of continuous and category variables can be integrated with the software. Any snapshot of the analyses can be saved and shared with others via a www-link. We demonstrate the usage of EpiMetal using pilot data with over 500 quantitative molecular measures for each sample as well as in two large-scale epidemiological cohorts (N >10 000).AvailabilityThe software usage exemplar and the pilot data are open access online at [http://EpiMetal.computationalmedicine.fi]. MIT licensed source code is available at the Github repository at [https://github.com/amergin/epimetal].

Can Doctors Be App Developers? Our Experience As Medical Educators

Introduction: Smartphone and mobile apps have become an indispensable companion in our modern-day living and working environment. In the medical field, web browsers and medical apps have transformed the medical practice as the most current knowledge, best practices, medical references, and calculators are available instantaneously at our fingertips. However, these functionality and usage are limited by the creativity and imagination of the app developers. To overcome these limitations, doctors should think out-of-the-box and educate themselves to be appdevelopers to create functional and useful apps in their field. Our aim was to create medical apps from ground-up independently without formal software development training. Material and method: Hybrid app technology is a popular method for creating apps for newbies due to the familiarity with web browsers. We explore the Ionic© Framework which is a free and open-source front-end with good resources and documentation. This programming technology assumes that everyone has experience with web browsers and the modern browsers essentially run on three technology stacks which are Hypertext Markup Language (HTML), JavaScript and Cascading Style Sheets (CSS). The HTML is a standard markup language for web browser while JavaScript is a scripting language for running commands and functions. The CSS is used for describing how HTML elements should be displayed. Results: We successfully published three apps on the Apple AppStore and Google Play, namely, OrthoBoard©, OpList and OOLH. Based on our experience of designing, coding, testing and deploying the apps, it is not impossible for medical doctors to achieve this goal and utilizing the app-development skills as an armamentarium for teaching, learning, and medical practice tools. Conclusions: App development is an essential skill especially for medical educators to leverage the technological advancement in their teaching and learning as well as medical practice in tandem with our nations’ aspiration towards Education 4.0.

BAlaS: fast, interactive and accessible computational alanine-scanning using BudeAlaScan.

In experimental protein engineering, alanine-scanning mutagenesis involves the replacement of selected residues with alanine to determine the energetic contribution of each side chain to forming an interaction. For example, it is often used to study protein-protein interactions. However, such experiments can be time-consuming and costly, which has led to the development of programmes for performing computational alanine-scanning mutagenesis (CASM) to guide experiments. While programmes are available for this, there is a need for a real-time web application that is accessible to non-expert users. Here, we present BAlaS, an interactive web application for performing CASM via BudeAlaScan and visualizing its results. BAlaS is interactive and intuitive to use. Results are displayed directly in the browser for the structure being interrogated enabling their rapid inspection. BAlaS has broad applications in areas, such as drug discovery and protein-interface design. BAlaS works on all modern browsers and is available through the following website: https://balas.app. The project is open source, distributed using an MIT license and is available on GitHub (https://github.com/wells-wood-research/balas).

Visualization and Analysis of Protein Structures with LiteMol Suite.

LiteMol suite is an innovative solution that enables near-instant delivery of model and experimental biomacromolecular structural data, providing users with an interactive and responsive experience in all modern web browsers and mobile devices. LiteMol suite is a combination of data delivery services (CoordinateServer and DensityServer), compression format (BinaryCIF), and a molecular viewer (LiteMol Viewer). The LiteMol suite is integrated into Protein Data Bank in Europe (PDBe) and other life science web applications (e.g., UniProt, Ensemble, SIB, and CNRS services), it is freely available at https://litemol.org , and its source code is available via GitHub. LiteMol suite provides advanced functionality (annotations and their visualization, powerful selection features), and this chapter will describe their use for visual inspection of protein structures.

Rapid multispectral data sampling using Google Earth Engine

The advent of cloud-based GIS tools has enabled the rapid exploration and processing of geospatial datasets. The Google Earth Engine (GEE) platform provides a library of algorithms and a powerful application programming interface (API) to produce flexible cloud-based applications that leverage Google’s computing infrastructure for geospatial analysis. We introduce ”Spectral Point”, a new GUI tool developed in GEE that allows users to explore, process and extract multispectral data rapidly within a single browser window. The ability to access and measure spectral signals from surface deposits using the entire available Landsat and Sentinel 2 archive is of tremendous benefit to geomorphic research, removing the need to download and process terabytes worth of imagery. Spectral values from composite imagery collected in GEE that relate to changes in surface mineral composition agree with corresponding point values using conventional desktop Landsat processing. The ”Spectral Point” tool makes it fast and simple to extract quantitative, contrast-corrected brightness data from multispectral imagery compared conventional desktop-based approaches. At the same time, the user needs no experience developing code, proprietary third-party software or dedicated high-performance computing and only a modern web browser. The ”Spectral Point” tool has many potential applications in the remote study of Earth’s surface; for example, we explore a case study from the western United States that demonstrates how the tool can be used for mapping, geochronology, and estimating weathering rates for Quaternary landforms. With increasing numbers of satellites, we are now faced with a growing deluge of geospatial data. Cloud-based solutions to mapping, field reconnaissance and image processing will be increasingly necessary to handle this valuable but untapped satellite image resource. ”Spectral Point” is an example of a new generation of web-based remote sensing tools available for Earth scientists, leveraging the revolution in cloud-based processing power and access to entire satellite image archives.

ViDis: A Platform for Constructing and Sharing of Medical Algorithms.

The literature and the Internet provide different sources, in which medical community as well as patients can browse through medical algorithms. These algorithms are dispersed and use different formats of presentation. We present visualized diagnosis (ViDis), a web platform aimed to construction and sharing of graphical representations of medical algorithms in a single place and in a unified format. ViDis is accessible as a web application, which can run on an arbitrary platform with a modern web browser. The platform's user friendly interfaces allow the users with different backgrounds to construct, share, and browse through medical algorithms. Visualization of the algorithms can be created using a flowchart diagram notation that is commonly applied in the design of computer software and is very intuitive to use and understand. Algorithms can be viewed in two different formats, that is, in the format of flowchart diagrams or in the format of sequential steps that guide the user from the beginning to the end of a medical procedure in dependence on his or her decisions made in each step of the process. ViDis enables registered users to create, edit, and share visualized medical algorithms and guest users to view these visualizations. To the best of our knowledge, this is the first platform for efficient sharing of medical algorithms with the community. We believe that ViDis provides an excellent platform for sharing medical knowledge and information among diagnosticians, clinicians, researchers, and patients.

Auditing Deployed Software Licenses on Cloud using a Secure Loopback Protocol

The rapidly growing cloud-centric focuses among organizations and enterprises have thrown into sharp relief the pressing need to progressively upgrade security within a cloud infrastructure. While a significant portion of threat perception emanates from malicious software that can infiltrate a cloud computing infrastructure, the risk of unlicensed software deployments in infrastructure-as-a-service model can expose an affected cloud service provider to a host of legal and statutory issues. The task of managing software licenses and conducting license validation checks can be an intense activity. The onus of tracking and managing licenses of software that have been deployed on an infrastructure-as-a-service cloud model is on both cloud service provider as well as its customers. However, the business of effectively managing software licenses is contingent upon the ease and use of an effective license auditing management tool to which auditors can connect through a secure conduit. In this paper, we propose a model that would allow cloud service providers to securely track software deployments and tally corresponding usage of appropriate licenses within an infrastructure-as-a-service model. Using the proposed model a cloud service provider can match all software licenses that have been deployed by a customer within the IaaS cloud space allotted. Further, a license auditor can securely connect to cloud service provider’s console and generate reports on license usage and software deployments from any modern browser. At the core of our model, lies a secure loopback connection framework that prevents access to any other web site once a secure connection to the primary console for monitoring and tracking software deployments has been established.

PPSB: An Open and Flexible Platform for Privacy-Preserving Safe Browsing

Safe Browsing (SB) is an important security feature in modern web browsers to help detect new unsafe websites. Although useful, recent studies have pointed out that the widely adopted SB services, such as Google Safe Browsing and Microsoft SmartScreen, can raise privacy concerns since users’ browsing history might be subject to unauthorized leakage to service providers. In this paper, we present a Privacy-Preserving Safe Browsing (PPSB) platform. It bridges the browser that uses the service and the third-party blacklist providers who provide unsafe URLs, with the guaranteed privacy of users and blacklist providers. Particularly, in PPSB, the actual URL to be checked, as well as its associated hashes or hash prefixes, never leave the browser in cleartext. This protects the user’s browsing history from being directly leaked or indirectly inferred. Moreover, these lists of unsafe URLs, the most valuable asset for the blacklist providers, are always encrypted and kept private within our platform. Extensive evaluations using real datasets (with over 1 million unsafe URLs) demonstrate that our prototype can function as intended without sacrificing normal user experience, and block unsafe URLs at the millisecond level. All resources, including Chrome extension, Docker image, and source code, are available for public use.

Summit: Scaling Deep Learning Interpretability by Visualizing Activation and Attribution Summarizations.

Deep learning is increasingly used in decision-making tasks. However, understanding how neural networks produce final predictions remains a fundamental challenge. Existing work on interpreting neural network predictions for images often focuses on explaining predictions for single images or neurons. As predictions are often computed from millions of weights that are optimized over millions of images, such explanations can easily miss a bigger picture. We present Summit, an interactive system that scalably and systematically summarizes and visualizes what features a deep learning model has learned and how those features interact to make predictions. Summit introduces two new scalable summarization techniques: (1) activation aggregation discovers important neurons, and (2) neuron-influence aggregation identifies relationships among such neurons. Summit combines these techniques to create the novel attribution graph that reveals and summarizes crucial neuron associations and substructures that contribute to a model's outcomes. Summit scales to large data, such as the ImageNet dataset with 1.2M images, and leverages neural network feature visualization and dataset examples to help users distill large, complex neural network models into compact, interactive visualizations. We present neural network exploration scenarios where Summit helps us discover multiple surprising insights into a prevalent, large-scale image classifier's learned representations and informs future neural network architecture design. The Summit visualization runs in modern web browsers and is open-sourced.

Interactive Browser-Based Genomics Data Visualization Tools for Translational and Clinical Laboratory Applications

Visualization-driven data exploration is a highly effective modality for interpreting and discovering insights from high-throughput genomics data sets; however, it is vastly underutilized in routine workflows in clinical and translation settings. We have developed three open-source, browser-based, interactive genomics data visualization widgets that can be used as intuitive stand-alone applications or integrated with existing web-based laboratory information solutions. The widgets were developed in JavaScript using the D3.js library. These widgets run in any modern web browser across desktop and mobile devices for easy accessibility but are designed for client-side data processing to address data privacy concerns. jsProteinMapper plots the location of a variant of interest relative to the protein domains and multiple variant databases, assisting with clinical interpretation of sequence variants. jsComut generates a highly interactive and customizable comutation plot for visual exploration of genomic data sets with clinicopathologic annotations to reveal unique molecular profiles and clinical correlates. jsCodonWheel is an interactive version of the ubiquitous circular codon-to-amino acid translation table, which lets users quickly map nucleotide changes onto resulting amino acid differences. These open-source visualization tools may improve some of the key laboratory workflows that involve the review of large-scale genomics data sets in a high-volume setting. The intuitive and responsive user interface, highly customizable visualizations, and easy integration with existing web-based laboratory software are significant highlights of these tools.

A Portal Offering Standard Visualization and Analysis on top of an Open Data Cube for Sub-National Regions: The Catalan Data Cube Example

The amount of data that Sentinel fleet is generating over a territory such as Catalonia makes it virtually impossible to manually download and organize as files. The Open Data Cube (ODC) offers a solution for storing big data products in an efficient way with a modest hardware and avoiding cloud expenses. The approach will still be useful up to the next decade. Yet, ODC requires a level of expertise that most people who could benefit from the information do not have. This paper presents a web map browser that gives access to the data and goes beyond a simple visualization by combining the OGC WMS standard with modern web browser capabilities to incorporate time series analytics. This paper shows how we have applied this tool to analyze the spatial distribution of the availability of Sentinel 2 data over Catalonia and revealing differences in the number of useful scenes depending on the geographical area that ranges from one or two images per month to more than one image per week. The paper also demonstrates the usefulness of the same approach in giving access to remote sensing information to a set of protected areas around Europe participating in the H2020 ECOPotential project.

PAMAM: Power analysis in multiancestry admixture mapping.

Admixed populations arise when two or more previously isolated populations interbreed. Admixture mapping (AM) methods are used for tracing the ancestral origin of disease-susceptibility genetic loci in the admixed population such as African American and Latinos. AM is different from genome-wide association studies in that ancestry rather than genotypes are tracked in the association process. The power and sample size of AM primarily depend on proportion of admixture and differences in the risk allele frequencies among the ancestral populations. Ensuring sufficient power to detect the effect of ancestry on disease susceptibility is critical for interpretability and reliability of studies using AM approach. However, there is no power and sample size analysis tool existing for AM studies in admixed population. In this study, we developed power analysis of multiancestry AM (PAMAM) to estimate power and sample size for two-way and three-way population admixtures. PAMAM is the first web-based bioinformatics tool developed to calculate power and sample size in admixed population under a variety of genetic and disease phenotype models. It is a valuable resource for investigators to design a cost-efficient study and develop grant application to pursue AM studies. PAMAM is built on JavaScript back-end with HTML front-end. It is accessible through any modern web browser such as Firefox, Internet Explorer, and Google Chrome regardless of operating system. It is a user-friendly tool containing links for support information including user manual and examples, and freely available at https://research.cchmc.org/mershalab/PAMAM/login.html.

What-If Analysis of Page Load Time in Web Browsers Using Causal Profiling

Web browsers have become one of the most commonly used applications for desktop and mobile users. Despite recent advances in network speeds and several techniques to speed up web page loading such as speculative loading, smart caching, and multi-threading, browsers still suffer from relatively long page load time (PLT). As web applications are receiving widespread attention owing to their cross-platform support and comparatively straightforward development process, they need to have higher performance to compete with native applications. Recent studies have investigated the bottleneck of the modern web browser's performance and conclude that network connection is not the browser's bottleneck anymore. Even though there is still no consensus on this claim, no subsequent analysis has been conducted to inspect which parts of the browser's computation contribute to the performance overhead. In this paper, we apply comprehensive and quantitative what-if analysis on the web browser's page loading process. Unlike conventional profiling methods, we applycausal profiling to precisely determine the impact of each computation stage such as HTML parsing and Layout on PLT. For this purpose, we develop COZ+, a high-performance causal profiler capable of analyzing large software systems such as the Chromium browser. COZ+ highlights the most influential spots for further optimization, which can be leveraged by browser developers and/or website designers. For instance, COZ+ shows that optimizing JavaScript by 40% is expected to improve the Chromium desktop browser's page loading performance by more than 8.5% under typical network conditions.