Web Access Research Articles

Department of Justice issues final rule regarding web accessibility

On April 24, 2024, the Department of Justice issued its final rule revising Title II of the Americans with Disabilities Act to include specific requirements for web accessibility (https://www.ada.gov/assets/pdfs/web-rule.pdf). Specifically, the rule proposes technical standards for websites and mobile applications managed by state and local governments. The DOJ stated, “It is critical to ensure that individuals with disabilities can access important web content and mobile apps quickly, easily, independently, privately, and equally.”

The Integration of Artificial Intelligence in Web Accessibility: Enhancing Inclusivity

Abstract: As the digital landscape continues to evolve, ensuring web accessibility for all users, including those with disabilities, becomes increasingly imperative. Artificial Intelligence (AI) presents a promising avenue to address accessibility challenges by providing innovative solutions to improve user experiences. This research paper examines the utilization of AI in enhancing web accessibility, exploring its applications, benefits, challenges, and future prospects. Through an extensive review of literature and case studies, this paper demonstrates the significant impact of AI in fostering inclusivity and facilitating seamless access to online content for individuals with disabilities

Ac4C-AFL: A high-precision identification of human mRNA N4-acetylcytidine sites based on adaptive feature representation learning

RNA N4-acetylcytidine (ac4C) is a highly conserved RNA modification that plays a crucial role in controlling mRNA stability, processing, and translation. Consequently, accurate identification of ac4C sites across the genome is critical for understanding gene expression regulation mechanisms. In this study, we have developed ac4C-AFL, a bioinformatics tool that precisely identifies ac4C sites from primary RNA sequences. In ac4C-AFL, we identified the optimal sequence length for model building and implemented an adaptive feature representation strategy that is capable of extracting the most representative features from RNA. To identify the most relevant features, we proposed a novel ensemble feature importance scoring strategy to rank features effectively. We then used this information to conduct the sequential forward search, which individually determine the optimal feature set from the 16 sequence-derived feature descriptors. Utilizing these optimal feature descriptors, we constructed 176 baseline models using 11 popular classifiers. The most efficient baseline models were identified using the two-step feature selection approach, whose predicted scores were integrated and trained with the appropriate classifier to develop the final prediction model. Our rigorous cross-validations and independent tests demonstrate that ac4C-AFL surpasses contemporary tools in predicting ac4C sites. Moreover, we have developed a publicly accessible web server at https://balalab-skku.org/ac4C-AFL/.

AI-Powered Real-time Accessibility Enhancement: A Solution for Web Content Accessibility Issues

The web accessibility landscape is a significant challenge, with 96.3% of home pages displaying issues with Web Content Accessibility Guidelines (WCAG). This paper addresses the primary accessibility issues, such as missing Accessible Rich Internet Applications (ARIA) landmarks, ill-formed headings, low contrast text, and inadequate form labeling. The dynamic nature of modern web and cloud applications presents challenges, such as developers' limited awareness of accessibility implications, potential code bugs, and API failures. To address these issues, an AI-enabled system is proposed to dynamically enhance web accessibility. The system uses machine learning algorithms to identify and rectify accessibility issues in real-time, integrating with existing development workflows. Empirical evaluation and case studies demonstrate the efficacy of this solution in improving web accessibility across diverse scenarios.

REVIEW ON DESKTOP ASSISTANT FOR VISUALLY IMPAIRED: MIME.AI

The study begins by examining the historical evolution of desktop assistants, highlighting key milestones and breakthroughs in assistive technology. It then delves into the core functionalities that make these desktop assistants valuable tools for the visually impaired. These functionalities include speech synthesis, screen reading, voice commands, and tactile feedback mechanisms. The review addresses the challenges and limitations associated with current desktop assistant technologies for the visually impaired. Mime.ai is a model which includes key aspects typically associated with desktop assistants for the visually impaired like Text-to-Speech technology, voice commands, AI and Machine Learning Integration, Web Accessibility and Compatibility with Other Assistive Technologies. It examines factors such as learnability, efficiency, memorability, errors, and user satisfaction, providing insights into the overall usability of the assistant. The review assesses seamless integration of the assistant with screen readers, braille displays, magnification software, and productivity tools. Finally, the review considers the impact of the desktop assistant on the daily lives of visually impaired users. It presents user feedback and testimonials regarding the utility, effectiveness, and overall satisfaction with the assistant, highlighting its potential to improve accessibility and productivity for this user group. Key Words: Natural Language Processing, Neural Network, Voice Commands, Text-to-Speech technology.

Webometrics ranking of Universities: fallacy or reality

In recent years, the utilization of webometrics as a tool for ranking universities has gained significant traction, purportedly offering a comprehensive assessment of institutions' digital presence and impact. However, amidst its growing popularity, questions arise regarding the validity and applicability of webometrics rankings, particularly concerning universities situated in the global south. This paper critically examines the webometrics ranking system, aiming to discern its strengths and weaknesses while scrutinizing its efficacy in evaluating universities, particularly those in regions with diverse socio-economic contexts and digital infrastructures. The analysis begins by delineating the fundamental principles underlying webometrics rankings, highlighting its reliance on web-based indicators such as web presence, visibility, and transparency. While these metrics ostensibly offer insights into universities' global reach and influence, they also engender methodological complexities and biases. Notably, the dominance of older well-endowed institutions in comparison with younger resource-constrained institutions impeding equitable evaluation. Furthermore, the paper investigates the specific challenges faced by universities in the global south within the webometrics framework. Issues of digital divide, limited internet penetration, and disparities in web accessibility compound the difficulties faced by these institutions in attaining favorable rankings. Moreover, the emphasis on quantitative metrics overlooks qualitative aspects of academic excellence, neglecting factors such as research impact, teaching quality, and societal relevance, which are integral to universities' roles in diverse contexts.Through a critical lens, this paper underscores the fallacies inherent in the uncritical adoption of webometrics rankings as a singular measure of university performance. It advocates for a nuanced approach that acknowledges the contextual nuances and challenges faced by universities, particularly in the global south. By fostering a dialogue on the limitations of webometrics and exploring alternative evaluation methodologies, this research aims to contribute to a more inclusive and equitable framework for assessing higher education institutions in an increasingly digitized world.

Assessing usability of University websites in meeting the expectations of students: a survey of literature

University websites are gateways to display resources offered by an institution (Mentes, 2012). As such first impression, attractiveness, controllability, helpfulness, efficiency and learnability as defined by Website analysis and measurement inventory (WAMMI) (Jabar et al., 2013) is critical in the design of websites. Unfortunately, most Universities Websites design are often driven by technology, organizational structure, or institution's objectives, rather than by its usability from the perspective of students (Undu & Akuma, 2018). This reduces chances of converting a prospective student into a current student after failing to get inquiries into enrollment opportunities in the university. To increase the usability of University websites it is necessary to increase the visibility and accessibility of all website related content. This result into the need of evaluating university websites a process that is very vague and a times usually unknown to most developers, which adversely then impacts the student experience when visiting such websites. To address this problem, standard usability metrics need to be considered to examine the university websites to analyze whether these websites are able to meet the requirements of customer number one who is the student. These metrics comprise of ease of use (simplicity), design (layout), navigation, organization, communication and content. Qualitative and quantitative approaches were used by different researchers to evaluate processes involved by analyzing questionnaires responded to by students after browsing several university websites. In addition, various technological innovations aimed at increasing and improving the web presence were used which involved re-designing of websites using the latest state of the art technologies so as to improve its usability as well as use of automated tools like Web Accessibility checker, HERA and WAVE. After reviewing different literature a valuable insight on key Usability, attributes for websites are noted to be of essence in designing website to meet students’ expectations.

PySupercharge: a python algorithm for enabling ABC transporter bacterial secretion of all proteins through amino acid mutation.

The process of producing proteins in bacterial systems and secreting them through ATP-binding cassette (ABC) transporters is an area that has been actively researched and used due to its high protein production capacity and efficiency. However, some proteins are unable to pass through the ABC transporter after synthesis, a phenomenon we previously determined to be caused by an excessive positive charge in certain regions of their amino acid sequence. If such an excessive charge is removed, the secretion of any protein through ABC transporters becomes possible. In this study, we introduce 'linear charge density' as the criteria for possibility of protein secretion through ABC transporters and confirm that this criterion can be applied to various non-secretable proteins, such as SARS-CoV-2 spike proteins, botulinum toxin light chain, and human growth factors. Additionally, we develop a new algorithm, PySupercharge, that enables the secretion of proteins containing regions with high linear charge density. It selectively converts positively charged amino acids into negatively charged or neutral amino acids after linear charge density analysis to enable protein secretion through ABC transporters. PySupercharge, which also minimizes functional/structural stability loss of the pre-mutation proteins through the use of sequence conservation data, is currently being operated on an accessible web server. We verified the efficacy of PySupercharge-driven protein supercharging by secreting various previously non-secretable proteins commonly used in research, and so suggest this tool for use in future research requiring effective protein production.

Building a Vision Transformer-Based Damage Severity Classifier with Ground-Level Imagery of Homes Affected by California Wildfires

The increase in both the frequency and magnitude of natural disasters, coupled with recent advancements in artificial intelligence, has introduced prospects for investigating the potential of new technologies to facilitate disaster response processes. Preliminary Damage Assessment (PDA), a labor-intensive procedure necessitating manual examination of residential structures to ascertain post-disaster damage severity, stands to significantly benefit from the integration of computer vision-based classification algorithms, promising efficiency gains and heightened accuracy. Our paper proposes a Vision Transformer (ViT)-based model for classifying damage severity, achieving an accuracy rate of 95%. Notably, our model, trained on a repository of over 18,000 ground-level images of homes with damage severity annotated by damage assessment professionals during the 2020–2022 California wildfires, represents a novel application of ViT technology within this domain. Furthermore, we have open sourced this dataset—the first of its kind and scale—to be used by the research community. Additionally, we have developed a publicly accessible web application prototype built on this classification algorithm, which we have demonstrated to disaster management practitioners and received feedback on. Hence, our contribution to the literature encompasses the provision of a novel imagery dataset, an applied framework from field professionals, and a damage severity classification model with high accuracy.

Dynamic switching of psychological test questions and design of scalable database: A study of web page data visualization and front-end interaction

As the need for efficient and user-friendly web applications in the field of psychological assessment continues to grow, traditional web development approaches are challenged to provide a dynamic and adaptive user experience. This study focuses on addressing these challenges through a comprehensive study that provides insight into the current state of psychological assessment web development, highlighting the shortcomings of traditional approaches, including the static limitations of Hyper Text Markup Language (HTML) and limited client-side scripting. The result is a user experience that lacks the responsiveness and flexibility that modern users expect. To tackle these problems, the intended solution suggested in this work combines a strong and scalable database design with a dynamic switching mechanism for psychological exam questions. Features-rich, aesthetically pleasing, and functioning client-server Web applications are created using technologies such as Servlets and Java Server Pages (JSP). The research contains practical case studies that demonstrate how Java-based user interface design can be successfully applied in real-world scenarios. The advantages of modularity, code reusability, and maintainability are demonstrated in these case studies. The study examines how selected technologies affect the performance, security, and accessibility of web UI, while also addressing load times, data integrity, and user inclusion issues. To summarize, this investigation underscores the crucial role of dynamic and scalable databases and Java-based technologies in enhancing the design of psychological assessment Web UIs.Developers can create web applications that exceed user expectations and provide superior user experience in the evolving digital landscape by using the proposed frameworks comprehensive toolkit.

College Federation

Abstract: The College Federation app bridges the gap between colleges and students through web and mobile access. It caters to faculty and students by streamlining communication (announcements, etc.), resource sharing, attendance tracking, and file exchange. This one-stop shop aims to both improve education and compete with social media. unlike social media, College Federation prioritizes academics. It omits student-to-student chat, profiles, and updates to minimize distractions. The focus is clear: enhance communication between faculty and students in a focused environment. Recognizing variable connectivity, the app even sends SMS alerts for offline students. by fostering academic engagement and providing essential college features, College Federation strives to be the go-to platform for learning, reducing reliance on mainstream social media for crucial updates.

DIRECTIONS OF FORMING A BARRIER-FREE ENVIRONMENT IN TOURISM FOR PEOPLE WITH DISABILITIES: THEORETICAL ASPECTS

ABSTRACT. In the conditions of military aggression against Ukraine by Russia, Ukrainian society not only did not lose its social orientation, but on the contrary, focused attention on the prospects of a humane, socially oriented society. Providing a barrier-free environment for people with disabilities in tourism is a marker of the social development of society and is related to the prospects of the country's economic development. People with disabilities and their family members, guardians and others are concerned about the problems and tasks faced by Ukrainian society. Solving these problems was limited due to the state's financial problems. In connection with the increase of people with disabilities due to war and environmental problems, progress in the activation of social orientation and the development of inclusiveness of communities, Ukraine's accession to the EU - the question of the possibilities of people with disabilities to lead an active social and productive life is being updated. That is why the issue of creating a barrier-free environment in tourism, as one of the directions of social and physical rehabilitation and ensuring the normal life of people with disabilities, cannot be ignored. Research methodology. To achieve the set goal, research and analysis of Ukrainian and foreign scientific literature, including authors from the countries of the EU, the United States, and Japan, was carried out. The main differences in the definition of concepts have been identified, the information obtained has been summarized and the directions for further research have been identified. The results. In the article, the main approaches to the definition of synonymous concepts «barrier-free tourism» are analyzed. The similarity, but not the identity, of the trmins is determined. The main problems and barriers that people with disabilities face due to the lack of a complex approach to solving an actual problem have been identified. Scientific novelty. On the basis of the study of the definition of the concept of «tourism for people with disabilities», the definition of the concept of «barrier-free tourism» is given. The рractical significance. The presented study offers a complex approach to solving the problem of implementing complex accessibility of a barrier-free tourist environment with an emphasis on web, Internet, and software accessibility for people with disabilities.

Turning manual web accessibility success criteria into automatic: an LLM-based approach

AbstractWeb accessibility evaluation is a costly process that usually requires manual intervention. Currently, large language model (LLM) based systems have gained popularity and shown promising capabilities to perform tasks that seemed impossible or required programming knowledge specific to a given area or were supposed to be impossible to be performed automatically. Our research explores whether an LLM-based system would be able to evaluate web accessibility success criteria that require manual evaluation. Three specific success criteria of the Web Content Accessibility Guidelines (WCAG) that currently require manual checks were tested: 1.1.1 Non-text Content, 2.4.4 Link Purpose (In Context), and 3.1.2 Language of Parts. LLM-based scripts were developed to evaluate the test cases. Results were compared against current web accessibility evaluators. While automated accessibility evaluators were unable to reliably test the three WCAG criteria, often missing or only warning about issues, the LLM-based scripts successfully identified accessibility issues the tools missed, achieving overall 87.18% detection across the test cases. Conclusion The results demonstrate LLMs can augment automated accessibility testing to catch issues that pure software testing misses today. Further research should expand evaluation across more test cases and types of content.

COVID-19 and the Americans with Disabilities Act: Implications for employment and higher education.

The Americans with Disabilities Act (ADA) is a federal law that protects individuals with disabilities from discrimination in all areas of public life. The ADA contributes to equal opportunity across policy areas, including the interconnected domains of higher education and employment. Since the onset of the COVID-19 pandemic in 2020, emerging research has begun to document the disparities in impact on people with disabilities, among other marginalized groups. However, no research to date has reviewed and synthesized literature that addresses disability discrimination related to COVID-19 that has implications for application of the ADA. This rapid evidence review aims to increase understanding about how COVID-19 has resulted in challenges for people with disabilities in the domains of employment and higher education that may be resolved through application of the ADA. Keyword searches were conducted in five electronic databases. Title, abstract, and full text screening was conducted followed by a thematic analysis of key ADA themes. Twelve final articles were included in this review, eight categorized within higher education and four within employment. In relation to the ADA and COVID-19, five studies revealed findings related to web accessibility, eight related to effective communication, and four related to reasonable accommodations. The findings provide a broad overview of the current research on how COVID-19 has affected accessibility, communications and accommodations in employment and higher education and identify gaps in the literature within these policy domains.

Performance of students with different accessibility needs and preferences in "Design for All" MOOCs.

Recent research has shown that Massive Open Online Courses (MOOCs) create barriers for students with disabilities. Not taking into account their needs in the design, production or delivery of MOOCs may be one of the main causes behind this. It leads to poor compliance with suitable learning designs and web accessibility standards, as well as a lack of knowledge about the students' needs. The objective of our research is to analyze the learning performance of the students in MOOCs on topics related to Design for All, offered in an Open edX-based platform. Accessibility support was conceived from the outset, including compliance of both the platform and the learning resources with the WCAG 2.1 accessibility standard, and with a subset of the principles of Universal Design for Learning. Additionally, students were consulted on their accessibility needs and preferences, following publicly available modeling schemes and previous research. From a sample of 765 students, who completed at least one of the graded assessment activities of the course, a multilevel multiple logistic regression model was fitted. Based on that model, the results indicate that: a) users of screen readers and users of captions show a statistically significant positive association with a good performance when compared to students with no preferences, with an odds ratio of, respectively, OR = 13.482 and OR = 13.701; b) students who have low vision or very low vision show a significant negative association with a good performance when compared to users of screen readers and to users of captions, with OR = 26.817 and OR = 27.254, respectively.

Robots still outnumber humans in web archives in 2019, but less than in 2015 and 2012

The significance of the web and the crucial role of web archives in its preservation highlight the necessity of understanding how users, both human and robot, access web archive content, and how best to satisfy this disparate needs of both types of users. To identify robots and humans in web archives and analyze their respective access patterns, we used the Internet Archive’s (IA) Wayback Machine access logs from 2012, 2015, and 2019, as well as Arquivo.pt’s (Portuguese Web Archive) access logs from 2019. We identified user sessions in the access logs and classified those sessions as human or robot based on their browsing behavior. To better understand how users navigate through the web archives, we evaluated these sessions to discover user access patterns. Based on the two archives and between the three years of IA access logs (2012 vs. 2015 vs. 2019), we present a comparison of detected robots vs. humans and their user access patterns and temporal preferences. The total number of robots detected in IA 2012 (91% of requests) and IA 2015 (88% of requests) is greater than in IA 2019 (70% of requests). Robots account for 98% of requests in Arquivo.pt (2019). We found that the robots are almost entirely limited to “Dip” and “Skim” access patterns in IA 2012 and 2015, but exhibit all the patterns and their combinations in IA 2019. Both humans and robots show a preference for web pages archived in the near past.

Evaluating the delivery of physical activity for people with developmental disabilities using an online knowledge translation approach: part 1 – web accessibility

Background: Knowledge-to-action gap exists in delivering physical activity (PA) to people with developmental disabilities via online platforms. Although web-based platforms have great potential in facilitating the delivery of PA for this target group, the lack of knowledge regarding web accessibility poses a challenge in accessing PA-related information online.Objective: This study evaluates the delivery of PA in terms of web accessibility. It also aims to identify barriers and facilitators in delivering PA knowledge to people with developmental disabilities online to improve web accessibility for the target user group.Methods: The study employs a concurrent nested design incorporating both quantitative (web usability questionnaire) and qualitative data (in-depth interviews). Fifteen pairs of individuals consisting of a person with developmental disabilities and a primary caregiver participated in the study, and three web-based platforms were selected for web accessibility tests and in-depth interviews.Results: The nested analysis provides a quantitative comparison of web accessibility and identifies barriers and facilitators of delivering PA for the target user group from the web accessibility perspective. Conclusion: The study findings could inform the development of accessible online platforms that distribute health-related knowledge to populations with developmental disabilities. Additionally, they could help enhance the design of other platforms intended for these populations.

CRISPRals: A Web Database for Assessing the CRISPR Defense System in the Ralstonia solanacearum Species Complex to Avoid Phage Resistance.

Clustered regularly interspaced short palindromic repeats (CRISPR) has been widely characterized as a defense system against phages and other invading elements in bacteria and archaea. A low percentage of Ralstonia solanacearum species complex (RSSC) strains possess the CRISPR array and the CRISPR-associated proteins (Cas) that would confer immunity against various phages. To provide a wide-range screen of the CRISPR presence in the RSSC, we analyzed 378 genomes of RSSC strains to find the CRISPR locus. We found that 20.1, 14.3, and 54.5% of the R. solanacearum, R. pseudosolanacearum, and R. syzygii strains, respectively, possess the CRISPR locus. In addition, we performed further analysis to identify the respective phages that are restricted by the CRISPR arrays. We found 252 different phages infecting different strains of the RSSC, by means of the identification of similarities between the protospacers in phages and spacers in bacteria. We compiled this information in a database with web access called CRISPRals (https://crisprals.yachaytech.edu.ec/). Additionally, we made available a number of tools to detect and identify CRISPR array and Cas genes in genomic sequences that could be uploaded by users. Finally, a matching tool to relate bacteria spacer with phage protospacer sequences is available. CRISPRals is a valuable resource for the scientific community that contributes to the study of bacteria-phage interaction and a starting point that will help to design efficient phage therapy strategies.

Machine Learning–Driven Prognostication in Traumatic Subdural Hematoma: Development of a Predictive Web Application

BACKGROUND AND OBJECTIVES: Our focus was on creating an array of machine learning (ML) models to predict unfavorable in-hospital outcomes after acute traumatic subdural hematoma (atSDH). Our subsequent aim was to deploy these models in an accessible web application, showcasing their practical value. METHODS: Data from the American College of Surgeons Trauma Quality Program database were used to identify patients with atSDH. In-hospital mortality was the primary outcome of interest. Secondary outcomes were (1) nonhome discharges, (2) prolonged length of stay (LOS), (3) prolonged length of stay in the intensive care unit (ICU-LOS), and (4) major complications. Feature selection was performed with least absolute shrinkage and selection operator algorithm. Five ML algorithms, including TabPFN, TabNET, XGBoost, LightGBM, and Random Forest, were used along with the Optuna optimization library for hyperparameter tuning. RESULTS: There were 104 055 patients included in the analysis for the outcome mortality, 82 988 for the outcome nonhome discharges, 104 207 for the outcome prolonged LOS, 62 543 for the outcome prolonged ICU-LOS, and 100 241 for the outcome major complications. The models with the highest area under receiver operating characteristic curve (AUROC) values included TabPFN for mortality and major complications, and LightGBM for nonhome discharges, prolonged LOS, and ICU-LOS. The TabPFN model for the primary outcome of our study, in-hospital mortality, showed an AUROC of 0.934. The models with the highest AUROC values were integrated into an application to predict the outcomes of interest. CONCLUSION: Our findings show that ML tools aid in predicting various outcomes for patients with atSDH. We developed a web application that has the potential to integrate the developed models into clinical practice.

ВЕБ-ОРІЄНТОВАНЕ НАВЧАННЯ ТА УСПІШНІСТЬ СТУДЕНТІВ У НАЦІОНАЛЬНОМУ ВІДКРИТОМУ УНІВЕРСИТЕТІ НІГЕРІЇ

The study examined the impact of Web based learning structures (Moodle, Blackboard, Online Library, Online Course Module/Study Guide, Internet Learning for coach student and Student - Student Connection and Times of Access of Internet Learning Applications) on students' scholarly accomplishment at the National Open University of Nigeria. The descriptive survey research design was used with a population of 100 to 400 students and a sample size of 150 students from the National Open University of Nigeria's schools of law, arts and social science, business and human resources, education, science and technology, and center for continuing education. A questionnaire with 53 questions titled: Experts validated the Online Learning and Learners' Academic Achievement in National Open University of Nigeria Scale (OLLAAS), and Cronbach's alpha yielded a reliability coefficient of 0.76. To test the hypotheses at the 0.05 level of significance, data were analyzed using Multiple Regressions and the Pearson Product Moment Correlation Coefficient. The discoveries of the review uncovered that the Internet learning structures (Moodle, Blackboard, Online Library, Online Course Module/Study Guide, Web based Learning for mentor student and Student - Student Connection and Times of Access of Web based Learning Applications) essentially impacted students' scholarly accomplishment (F (6, 143) = 24.907; R2 = 0.511), and mutually represented 49.1% of its difference. Moodle (r =.206, P0.001), Blackboard (r =.417, P0.001), the Online Library (r =.594, P0.001), the Online Course Module/Study Guide (r =.395, P0.001), online learning for tutor-learner and learner-learner interaction (r =.442, P0.001), and periods of access to online learning applications (r =.625, P0.001) all had positive correlations with students. In light of the discoveries, it was suggested that administration ought to put more in training of this season of computerized age through satisfactory financing to empower schools obtain and introduce ICT foundation. The government and all relevant stakeholders ought to address the problem of incessant power outages. Mechanical gadgets ought to likewise be made accessible to students at sponsored rates to empower everybody partake in remote learning. Web based learning meetings ought to be planned with significant and profoundly captivating and intelligent learning exercises to lessen fatigue among detached students during learning.