Web Browser Research Articles

TREADS: Target Research for Anti-epileptic Drugs Using Data Science

Context: Epilepsy is a common neurological disease and is classified into different types based on features such as the kind of seizure, age of onset, part of brain effected, etc. There are nearly 30 approved anti-epileptic drugs (AEDs) for treating different epilepsies and each drug targets proteins exhibiting a specific molecular mechanism of action. There are many genes, proteins, and microRNAs known to be associated with different epileptic disorders. This rich information on epilepsy-associated data is not available at one single location and is scattered across multiple publicly available repositories. There is a need to have a single platform integrated with the data, as well as tools required for epilepsy research. Methods and Material: Text mining approaches are used to extract data from multiple biological sources. The data is curated and populated within an in-house developed epilepsy database. Machine-learning based models are built in-house to know the probability of a protein being druggable based on the significant protein features. A web interface is provided for the access of the epilepsy database as well as the ML-based tool developed in-house. Results: The epilepsy-associated data is made accessible through a web browser. For a protein of interest, the platform provides all the feature values, and the results generated using different machine learning models are displayed as visualization plots. Conclusions: To meet these objectives, we present TREADS, a platform for epilepsy research community, having both database and an ML-based tool for the study of AED targets. To access TREADS: https://treads-aer.cdacb.in

PellucidAttachment: Protecting Users From Attacks via E-Mail Attachments

Malicious email attachments are a common and successful attack vector on today's Internet. Sophisticated at- tackers can craft highly-targeted attachments, using publicly available information about potential victims to create convincing documents that contain hidden malicious payloads. Users who open these attachments using vulnerable applications are at a high risk of infection. Unfortunately, current mitigations are unreliable, relying either on fallible malware detection techniques or user education. In this work, we propose adopting a default policy of isolated attachment rendering. Emails bearing attachments are transpar- ently rewritten (in a sandboxed virtual machine environment) to contain static renderings of the attachments. Users who wish to obtain the original attachment are explicitly warned of the dan- gers of doing so – akin to TLS warnings as used in web browsers before being allowed to access the requested documents. We implement this technique in a system we call PellucidAttachment. We further report on an extensive user study that measures the usability and effectiveness of PellucidAttachment in shielding users from attacks. Our evaluation shows that adopting email attachment security indicators and an isolation-by-default policy results in a significant increase in user security, while maintaining the usability of email attachments.

Speech to Text Transcription

Abstract: This paper aims to enhance speech recognition and audio processing, converting spoken sentences into text and taking input from various input sources like microphones, audio, and video files. Notably, it offers robust audio conversion capabilities, supporting MP3 to WAV and other formats. To enhance the scalability and user experience, the system is implemented as a Flask-powered web application, providing users with a seamless interface accessible through a Flask-powered web browser serves to facilitate intuitive and user-friendly communication, making the application versatile, different users -and adaptable to features here the first. This comprehensive design meets the needs of users looking for efficient speech recognition and audio processing solutions, especially for web-based applications

“Through the looking glass: envisioning new library technologies” AI and the information interface

Purpose This study aims to inform and guide information professionals in thinking clearly about the challenges and opportunities this technology may create. Design/methodology/approach This column uses the Web browser Arc as a focal point for exploring elements that seem key to understanding how artificial intelligence (AI) may change our relationship with information. Large language model’s were used to help draft or rewrite sentences. That text was then reviewed or revised by the author. Findings The following elements are key to understanding the potential of informational interface software like Arc. The ability to abstract information from the original content. The ability to produce multimedia compelling user experiences. The ability to “read” multimodal forms of information and take action based on that “understanding”. This may impact the value exchange between the user and the underlying information, with implications for libraries. Research limitations/implications Everything about AI the future of AI or any technology is speculative. Practical implications Libraries that wish to continue to be part of adding value to how users interact with information need to pay attention and find ways to adapt. Originality/value As new paradigms are created to ensure information exchange is sustainable for everyone, there may be opportunities for libraries. And even if not, libraries may leverage their expertise or relationships to build something that could not be imagined without them. Yet these are only possible if libraries engage.

Connected Robotics for Intelligent Surveillance: An IOT Approach

Abstract: The robot employs the HTTP Communication protocol, enabling users to access live video streaming from the OV2640 camera through a standard web browser. The web interface includes intuitive directional buttons for seamless control, allowing users to command the robot to move left, right, forward, and backward. The locomotion of the robot is achieved through two DC motors integrated with a Robot chassis and an L293D motor driver module. This paper presents the development and implementation of an innovative IoT-based Surveillance Robot designed for remote control, utilizing a Wi-Fi module and a smartphone interface. The portable espionage robot integrates cutting-edge technology, featuring an AI Thinker ESP32-CAM module with an ESP32-S processor, an OV2640 camera, motor drivers, and a robust chassis with two moving wheels. The ESP32-CAM allows the capture and storage of images on a microSD card, facilitating efficient data management. The real-time video feed is transmitted wirelessly to the user's smartphone over a Wi-Fi infrastructure, providing a livestreaming experience. This wireless surveillance robot finds applications in various scenarios such as war fields, disaster management, and beyond, showcasing its versatility in remote monitoring and reconnaissance tasks.

Browser Security

Web browsers play a crucial role in accessing and interacting with information on the internet. However, they also present significant security challenges due to their complexity and the diverse range of threats they face. This paper provides an overview of web browser security, focusing on the key challenges, vulnerabilities, and defences. It discusses common attack vectors, such as cross-site scripting (XSS) and cross-site request forgery (CSRF), as well as browser security features like sandboxing, secure storage, and Content Security Policy (CSP). Additionally, the paper explores emerging threats and future directions in web browser security, highlighting the importance of ongoing research and collaboration among browser vendors, developers, and security experts to ensure a more secure browsing experience for users.

Recent advances of ECG monitoring and webserver health monitoring applications: A review

In response to recent improvements in mobile technology and cloud computing-based real-time monitoring systems, numerous cloud-based healthcare services and devices have been developed. In the cloud system, it is feasible to collect and distribute medical data immediately from anywhere to medical specialists, and patients can receive network-based feedback. This paper reviews the most recent developments and trends in wearable technology and biomedical equipment (mostly ECG), as well as the development of a cloud-based solution for mobile device and web browser users. The system contains ECG enhancement, ECG quality grading, and ECG parameter extraction methods. A use case was utilized to showcase the system, in which a web server processed ECG data from a mobile phone in real-time. The system has been proved to be functional, accurate, and efficient. We review the primary principles underlying the operation of the ECG and its fundamental operation, as well as the recording and transmission paradigm for ECG signals. Detailed processes were also provided for the system components, their configuration, and the employed technologies. In conclusion, we examine the complete study and the project's future scope.

A randomized controlled educational pilot trial of interictal epileptiform discharge identification for neurology residents.

To assess the effectiveness of an educational program leveraging technology-enhanced learning and retrieval practice to teach trainees how to correctly identify interictal epileptiform discharges (IEDs). This was a bi-institutional prospective randomized controlled educational trial involving junior neurology residents. The intervention consisted of three video tutorials focused on the six IFCN criteria for IED identification and rating 500 candidate IEDs with instant feedback either on a web browser (intervention 1) or an iOS app (intervention 2). The control group underwent no educational intervention ("inactive control"). All residents completed a survey and a test at the onset and offset of the study. Performance metrics were calculated for each participant. Twenty-one residents completed the study: control (n = 8); intervention 1 (n = 6); intervention 2 (n = 7). All but two had no prior EEG experience. Intervention 1 residents improved from baseline (mean) in multiple metrics including AUC (.74; .85; p < .05), sensitivity (.53; .75; p < .05), and level of confidence (LOC) in identifying IEDs/committing patients to therapy (1.33; 2.33; p < .05). Intervention 2 residents improved in multiple metrics including AUC (.81; .86; p < .05) and LOC in identifying IEDs (2.00; 3.14; p < .05) and spike-wave discharges (2.00; 3.14; p < .05). Controls had no significant improvements in any measure. This program led to significant subjective and objective improvements in IED identification. Rating candidate IEDs with instant feedback on a web browser (intervention 1) generated greater objective improvement in comparison to rating candidate IEDs on an iOS app (intervention 2). This program can complement trainee education concerning IED identification.

A New Generation of Collaborative Immersive Analytics on the Web: Open-Source Services to Capture, Process and Inspect Users’ Sessions in 3D Environments

Recording large amounts of users’ sessions performed through 3D applications may provide crucial insights into interaction patterns. Such data can be captured from interactive experiences in public exhibits, remote motion tracking equipment, immersive XR devices, lab installations or online web applications. Immersive analytics (IA) deals with the benefits and challenges of using immersive environments for data analysis and related design solutions to improve the quality and efficiency of the analysis process. Today, web technologies allow us to craft complex applications accessible through common browsers, and APIs like WebXR allow us to interact with and explore virtual 3D environments using immersive devices. These technologies can be used to access rich, immersive spaces but present new challenges related to performance, network bottlenecks and interface design. WebXR IA tools are still quite new in the literature: they present several challenges and leave quite unexplored the possibility of synchronous collaborative inspection. The opportunity to share the virtual space with remote analysts in fact improves sense-making tasks and offers new ways to discuss interaction patterns together, while inspecting captured records or data aggregates. Furthermore, with proper collaborative approaches, analysts are able to share machine learning (ML) pipelines and constructively discuss the outcomes and insights through tailored data visualization, directly inside immersive 3D spaces, using a web browser. Under the H2IOSC project, we present the first results of an open-source pipeline involving tools and services aimed at capturing, processing and inspecting interactive sessions collaboratively in WebXR with other analysts. The modular pipeline can be easily deployed in research infrastructures (RIs), remote dedicated hubs or local scenarios. The developed WebXR immersive analytics tool specifically offers advanced features for volumetric data inspection, query, annotation and discovery, alongside spatial interfaces. We assess the pipeline through users’ sessions captured during two remote public exhibits, by a WebXR application presenting generative AI content to visitors. We deployed the pipeline to assess the different services and to better understand how people interact with generative AI environments. The obtained results can be easily adopted for a multitude of case studies, interactive applications, remote equipment or online applications, to support or accelerate the detection of interaction patterns among remote analysts collaborating in the same 3D space.

Buttery Smooth: Privacy’s Bundling with Attention in Web Browser Performance

Long considered an object of the law, Americans increasingly encounter privacy via the operations and settings of networked technologies. Based on ethnographic fieldwork with privacy engineers and their corporate colleagues, this paper examines how privacy’s manifestation in web technologies opens it to pragmatic linkages with new sensuous qualities and interpretive possibilities. The paper’s primary object is Project Quantum, a company-wide effort initiated by the Mozilla Corporation in 2016 to build a new engine for its Firefox web browser, thus radically improving Firefox’s “performance.” I show that animating Project Quantum was an ideal of smooth, snappy performance that Firefox engineers understood to be keyed to the demands of user attention and attempted to establish for users as meaningful signs of Mozilla’s engineering prowess and paternalistic care. Drawing on the study of “qualia”—phenomenal experiences of abstract qualities—I identify performance engineering as a key site of privacy’s semiotic bundling with attention, through which privacy’s practically available forms are taking on idealized qualities of speed and smoothness. Attending to privacy’s qualia, I propose, provides methodological access to the institutional and global value systems reconfiguring privacy’s political capacities as it becomes an object of technological stewardship and intervention.

Campus Automation Using Cloud Computing

The project, we propose is “Campus automation”, which is considered a website for a college, the main aim of this project is to change college website content dynamically online and provide a user interface application. The above aim can be established by creating a layout Structural module and each module may have a sub-module. This will provide information about the college campus in which staff, students, and HOD can access this information and will be familiar with the college campus. When campus automation technology is integrated with popular web services it can be utilized securely by an even larger audience. By leveraging the power of cloud computing, the system offers scalability, reliability, and accessibility. It allows users to access the platform from anywhere, at any time, using a web browser, thereby facilitating seamless collaboration and communication among stakeholders. Overall, the proposed Campus Automation System aims to modernize campus management processes, streamline administrative tasks, improve communication, and enhance the overall efficiency of educational institutions. By harnessing the capabilities of cloud computing and the MERN stack, the system promises to deliver a robust, scalable, and user-friendly solution tailored to the needs of modern educational institutions. Key Words: Campus automation, cloud computing, MERN stack, web services

ESFuzzer: An Efficient Way to Fuzz WebAssembly Interpreter

WebAssembly code is designed to run in a sandboxed environment, such as a web browser, providing a high level of security and isolation from the underlying operating system and hardware. This enables the execution of untrusted code in a web browser without compromising the security and integrity of the user’s system. This paper discusses the challenges associated with using fuzzing tools to identify vulnerabilities or bugs in WebAssembly interpreters. Our approach, known as ESFuzzer, introduces an efficient method for fuzzing WebAssembly interpreters using an Equivalent-Statement concept and the Stack Repair Algorithm. The samples generated by our approach successfully passed code validation. In addition, we developed effective mutation strategies to enhance the efficacy of our approach. ESFuzzer has demonstrated its ability to generate code that achieves 100% WebAssembly validation testing and achieves code coverage that is more than twice that of libFuzzer. Furthermore, the 24-h experiment results show that ESFuzzer performs ten times more efficiently than libFuzzer.

An Interactive Webcast Portal of Training Placement using SMTP and Database using PHP

The Training and Placement Department plays a crucial role in facilitating students' interactions with various companies and securing placements. By cultivating relationships with esteemed organizations and industrial establishments, the Placement Department assists both undergraduate and postgraduate students in exploring career opportunities. Its mission includes equipping students with knowledge, expertise, and skills to meet industry demands and make well-informed career choices. However, manual management of data pertaining to campus recruitment events poses difficulties, highlighting the need to automate these processes to minimize errors and improve efficiency. This study proposes the creation of a Training and Placement Application to tackle these challenges. The application will be web- based, featuring intuitive interfaces for both students and administrators (Training and Placement Officers, TPOs). To ensure usability across different devices, the application will be compatible with smartphones and web browsers. Leveraging React + Vite as the underlying technologies for design and development, the application aims to provide adaptability, customization, and scalability while retaining essential features for streamlined management of training and placement activities. Students will have the ability to create profiles and complete registrations effortlessly, while administrators can efficiently oversee and manage all operations through the application

Development and Employment of Cyber Security of e201 File Web Application for Data Center College of the Philippines of Laoag City, Inc.

Web-based systems in today's interconnected world play a vital role and need of enhanced cybersecurity measures to protect sensitive information since cybercrimes are increasing rapidly. The focus of the study is on the development of an e201 file web application for the Data Center College of the Philippines which will be accessed through a web browser. The objective study is to evaluate the cybersecurity of the developed application, particularly in handling essential personnel records using confidential data OWASP ZAP security testing tool and its software quality based on ISO 25010 specifically in software functionality, usability, and security to determine if it is ready for live deployment. The study utilizes the Research and Development model as its research design to achieve its purpose. The conceptual framework of the study utilized the used of Input-Process-Output model and the Agile Iterative model in the development. The result of the security testing and suggestions of the OWASP ZAP, cyber security was employed in the web application including Content Security Policy Header, HTTOnly Cookie flags, SameSite attribute, X-Content-Type-Options Header, and Anti-CSRF Token. With an overall mean of 4.41 in the result of Users Acceptance Testing, it implies that the system is a great help for the institution. The positive feedback received from evaluators confirmed that the development of the e201 files web application were successful. This study implies that utilizing the OWASP Zap is a great help in strengthening cybersecurity and ISO 25010 in the software quality assurance of web applications of educational institutions.

Web Real-Time Communication Using Gesture

Gesture recognition has emerged as a promising technology for enhancing human-computer interaction in various domains. In this paper, we propose a novel approach to gesture recognition using WebRTC (Web Real-Time Communication), a powerful web technology that enables real-time communication between web browsers. Our approach leverages the capabilities of WebRTC to capture live video streams from webcams and process them in real-time for gesture recognition. We present a detailed methodology for integrating WebRTC with a custom deep learning techniques. We evaluate the performance of our system using a diverse set of hand gestures and demonstrate its effectiveness in real-world scenarios. Our experimental results show an average recognition accuracy of 90%, outperforming existing methods in terms of both accuracy and computational efficiency. Potential applications of our approach in interactive web applications, gaming, and augmented reality systems. This work contributes the research on gesture recognition and demonstrates the feasibility of using WebRTC for real-time gesture recognition applications. Key Words: gesture recognition, WebRTC , Real-time communication

A novel approach towards web browser using the concept of a complex spherical fuzzy soft information

The modern technology is the practical application of scientific knowledge, whether in industry or daily life, for goals or purposes. More quickly than any other technological advancement in human history, digital technologies have advanced. The technology sector is expanding and provides both new educational opportunities and innovative, exciting products. Right now, one of the most widely used and fascinating technologies is the web browser. This article introduced the novel concepts of complex spherical fuzzy soft relations (CSFSRs) by using the Cartesian Product (CP) of two complex spherical fuzzy soft sets (CSFSSs). Additionally, examples are used to clarify various types of relations. Because it discusses all levels of membership, abstinence, and non-membership with multidimensional variables, the CSFSRs have a detailed structure. The CSFSR-based modelling tools developed in this research, which primarily rely on the score function, can be used to choose the best Web browser. The transaction could be as easy as users sharing records via a functional web browser. Finally, the advantages of this suggested structure are illustrated by contrasting it with alternative structures.

Remote practical instruction using web browsers

&lt;p&gt;This paper introduces a novel approach to remote coaching, specifically targeting the body movements of learners participating remotely. The proposed system employs a smartphone camera to capture the learner’s body and represent it as a 3D avatar. The instructor can then offer guidance and instruction by manipulating the 3D avatar’s shape, which is displayed on a web browser. The main challenge faced by the system is to enable the sharing and editing of 3D objects among users. Since the HTML5 drag-and-drop feature is inadequate for transforming virtual objects consisting of multiple interconnected rigid bodies, the system tracks the pivot point of the manipulated rigid body. It assigns attributes such as pivot points and action points to each object, extending beyond their 2D screen coordinates. To implement the system, an interactive web application framework following the model-view-view-model (MVVM) architecture is utilized, incorporating Vue.js, Three.js, and Google Firebase. The prototype system takes advantage of the data binding capability of the framework and successfully operates within the 3D space of a web browser. Experimental results demonstrate that it can effectively share transformation information with an average delay of 300 ms.&lt;/p&gt;

A cloud‐based solution for trustless indigenous data sovereignty: Protecting Māori biodiversity management data in Aotearoa New Zealand

AbstractIndigenous peoples should be able to govern data about themselves, their territories, resources, and ways of life, collected by themselves or others. However, the progressive use of cloud computing for the geoweb raises data security and privacy concerns. We propose a complete and trustless approach for indigenous geospatial data sovereignty on the cloud by furnishing security functions at the core—the web browser. Geomasking permits sharing an anonymized dataset with less privileged users, while the original is protected and shared with sovereign data owners via public‐key encryption. The encrypted dataset's hash value is notarized on the blockchain for the verification of its authenticity when on the cloud. The application was designed for the protection of Biodiversity Management Areas stewarded by the Māori people in Aotearoa New Zealand. It enables diversified functions of geospatial data protection compared with previous works focusing on the cloud by solving data‐sharing problems without relying on a third party.

PEPesc: A TCP Performance Enhancing Proxy for Non-Terrestrial Networks

Non-terrestrial networks (NTNs) using flying objects such as satellites play key roles in the next-generation wireless system (6 G). The NTN links with long propagation delay and random packet losses pose a great challenge to the performance of Transport Control Protocol (TCP), which many Internet applications rely on. Performance enhancing proxy (PEP) is an easy-to-deploy approach for improving TCP's performance. In this paper, we design and implement a novel PEP called <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">PEPesc</i> which has two distinctive features. First, it features <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">retransmission-free</i> loss recovery, using an adaptive packet-level forward erasure correction method called streaming coding (SC). Second, as packet losses are recovered by SC, the congestion control problem is simplified to rate control and local acknowledgement between entities based on bandwidth estimation. Based on a queueing theoretic analysis of the design, we carefully devise a protocol and implement PEPesc as an open-source application. Extensive evaluations show that PEPesc can achieve much higher <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">and</i> smoother goodput than the canonical TCP variants and than other existing open-source PEPs in applications including <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">iperf</i> and HTTP-based adaptive streaming, and achieves similar performance in web browsing. Finally, we also present a deployment case over a real-world geostationary satellite link.

Music Recommendation System based on Facial Expressions by using CNN

Abstract: In today's world, the integration of emotion detection and personalized music recommendation has become increasingly prevalent across diverse fields. This project endeavors to develop a cutting-edge music recommendation system that tailors playlists to users' emotional states, as discerned from their facial expressions in real-time. Leveraging the Facial Expression Recognition 2013 (FER 2013) dataset, which encompasses a wide array of emotional expressions including happiness, sadness, anger, fear, disgust, neutrality, and surprise, serves as the foundation for training our model. The project employs the Mediapipe algorithm for feature extraction from facial expressions and utilizes a Convolutional Neural Network (CNN) to classify these emotions accurately. For seamless integration and user interaction, streamlit web browser frameworks are harnessed to facilitate music recommendations within an intuitive interface. Furthermore, the proposed system capitalizes on real-time face detection through camera input using OpenCV, ensuring timely and responsive interaction. By automatically generating music playlists based on the user's current emotional state, our system aims to significantly reduce computational time and overall costs compared to existing literature. In essence, this project presents a comprehensive solution that combines real-time facial expression analysis with personalized music recommendation, offering enhanced efficiency and accuracy while minimizing computational overhead.