AutoDesc: Facilitating Convenient Perusal of Web Data Items for Blind Users

Web data items such as shopping products, classifieds, and job listings are indispensable components of most e-commerce websites. The information on the data items are typically distributed over two or more webpages, e.g., a ‘Query-Results’ page showing the summaries of the items, and ‘Details’ pages containing full information about the items. While this organization of data mitigates information overload and visual cluttering for sighted users, it however increases the interaction overhead and effort for blind users, as back-and-forth navigation between webpages using screen reader assistive technology is tedious and cumbersome. Existing usability-enhancing solutions are unable to provide adequate support in this regard as they predominantly focus on enabling efficient content access within a single webpage, and as such are not tailored for content distributed across multiple webpages. As an initial step towards addressing this issue, we developed AutoDesc, a browser extension that leverages a custom extraction model to automatically detect and pull out additional item descriptions from the ‘details’ pages, and then proactively inject the extracted information into the ‘Query-Results’ page, thereby reducing the amount of back-and-forth screen reader navigation between the two webpages. In a study with 16 blind users, we observed that within the same time duration, the participants were able to peruse significantly more data items on average with AutoDesc, compared to that with their preferred screen readers as well as with a state-of-the-art solution

The VPS ReplaySuite: development and evaluation of a novel, Internet based telepathology tool

The ReplaySuite is a web-based telepathology tool that replicates the doubleheaded microscope environment online, enabling a reviewing pathologist to ‘replay’ an archived virtual slide examination. Examination-tracking data obtained by the Virtual Pathology Slide (VPS) virtual slide viewer is exploited, allowing a remote pathologist to review an examination conducted at a different time and location. This removes temporal and spatial issues associated with double-headed microscopy. In order to conduct a preliminary evaluation of the technology, 9 pathologists used the ReplaySuite to review examination replays and diagnostic data from archived examinations of 10 needlecore breast biopsies. Diagnostically difficult cases were most frequently evaluated, either via diagnostic concordance graphs or examination replays, and all 3 participants who replayed more than 10 examinations stated the ReplaySuite to be of some or great benefit in pathology training and quality assurance. Of those who replayed an examination by another pathologist, 83% (5/6) agreed that replays provided an insight into the examining pathologists diagnosis, and 33% (2/6) reconsidered their own diagnosis for at least one case. Of those who reconsidered their original diagnosis, all reclassified either concordant with group consensus or original glass slide diagnosis. This study demonstrated that the ReplaySuite was of potential benefit in pathology education, however the technology required evaluation in a setting that would facilitate its impact on diagnostic performance. Accordingly, a redeveloped VPS and ReplaySuite were incorporated into the EQUALIS External Quality Assurance (EQA) study in chronic hepatitis staging and grading. During the study, 9 Swedish pathology departments examined and scored digital representations of liver needlecore biopsies during two sessions, with 10 cases per session and two digital slides per case. Between scoring sessions, participants were provided with access to two supplementary electronic resources: the ReplaySuite, and a library of pre-selected reference images. Comparison of concordance with gold standard (KVAST group) scoring before and after electronic resource use facilitated the elucidation of impact on diagnostic performance. Between scoring sessions, participant concordance with KVAST staging increased by 18% (49%-67%), while concordance with KVAST grading increased by 20% (34%-54%). Mean staging un-weighted kappa improved from 0.347 to 0.554 (+0.207), or from ‘fair’ to ‘moderate’ exact agreement with KVAST staging. Linear weighted staging kappa improved from 0.603 to 0.688 (+0.085), indicating close agreement in both sessions. Mean grading unweighted kappa increased from 0.132 to 0.412 (+0.280), or from a ‘poor’ to ‘moderate’ level o f exact agreement with KVAST, while linear weighted kappa improved from 0.328 to 0.624 (+0.295), or from ‘fair’ to ‘good’ level of approximate agreement with KVAST. Subsequent to the EQA scheme, an expert liver pathologist used the ReplaySuite to evaluate study examinations, assessing examination technique and identifying sources of error. Examinations scoring concordant with KVAST were observed to exhibit acceptable examination technique more frequently than discordantly scoring examinations. When grading, 28% (46% - 18%) more concordant than discordant examinations were considered to have viewed sufficient tissue, and at the appropriate magnification. A similar disparity of 24% (59% - 35%) was observed in staging, suggesting that examination technique was important both when determining the degree of necroinflammation within a biopsy, and when ascertaining the extent of fibrosis. In assessing sources of error, the expert pathologist identified a potential source in 50% of grading examinations, with misinterpretation of observed pathology cited in 19%, and missed pathology (oversight) cited in 31% of grading examinations. Of the 41% of staging examinations in which a source was identified, misinterpretation of observed pathology was cited in 20% of examinations, and missed pathology (oversight) in 21% of examinations. This study demonstrated that the use of supplementary electronic resources could result in improvements in diagnostic performance. It also illustrated the significant ‘add on’ value that could be provided by the ReplaySuite in EQA, by providing means to assess not only diagnostic concordance, but also diagnostic technique and identify sources of error. In order to assess Irish trainee pathologist’s perceptions of computer-assisted learning (CAL), a number of commercial systems were utilised to incorporate digital slides into a postgraduate seminar series, and provide subsequent access to seminar digital slides, diagnoses and expert annotations online. All surveyed trainees considered the use of digital slides and expert annotations of benefit in pathology training, and considered the potential implementation of expert examination replays, online self-assessment and the capability to search online for material by organ, diagnosis or pathological feature of benefit. The work described herein illustrates that both expert and trainee pathologists alike consider the use of supplementary electronic resources of benefit in pathology education, and demonstrates that their use can improve diagnostic performance. The ability to evaluate participation in EQA studies via the ReplaySuite provides significant additional value to education schemes, providing a depth of assessment not possible with conventional microscopy

Detecting Deceptive Dark-Pattern Web Advertisements for Blind Screen-Reader Users

Advertisements have become commonplace on modern websites. While ads are typically designed for visual consumption, it is unclear how they affect blind users who interact with the ads using a screen reader. Existing research studies on non-visual web interaction predominantly focus on general web browsing; the specific impact of extraneous ad content on blind users\u27 experience remains largely unexplored. To fill this gap, we conducted an interview study with 18 blind participants; we found that blind users are often deceived by ads that contextually blend in with the surrounding web page content. While ad blockers can address this problem via a blanket filtering operation, many websites are increasingly denying access if an ad blocker is active. Moreover, ad blockers often do not filter out internal ads injected by the websites themselves. Therefore, we devised an algorithm to automatically identify contextually deceptive ads on a web page. Specifically, we built a detection model that leverages a multi-modal combination of handcrafted and automatically extracted features to determine if a particular ad is contextually deceptive. Evaluations of the model on a representative test dataset and \u27in-the-wild\u27 random websites yielded F1 scores of 0.86 and 0.88, respectively

Factors Affecting the Accessibility of IT Artifacts : A Systematic Review

Accessibility awareness and development have improved in the past two decades, but many users still encounter accessibility barriers when using information technology (IT) artifacts (e.g., user interfaces and websites). Current research in information systems and human-computer interaction disciplines explores methods, techniques, and factors affecting the accessibility of IT artifacts for a particular population and provides solutions to address these barriers. However, design realized in one solution should be used to provide accessibility to the widest range of users, which requires an integration of solutions. To identify the factors that cause accessibility barriers and the solutions for users with different needs, a systematic literature review was conducted. This paper contributes to the existing body of knowledge by revealing (1) management- and development-level factors, and (2) user perspective factors affecting accessibility that address different accessibility barriers to different groups of population (based on the International Classification of Functioning by the World Health Organization). Based on these findings, we synthesize and illustrate the factors and solutions that need to be addressed when creating an accessible IT artifact.© 2022 by the Association for Information Systems. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and full citation on the first page. Copyright for components of this work owned by others than the Association for Information Systems must be honored. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers, or to redistribute to lists requires prior specific permission and/or fee. Request permission to publish from: AIS Administrative Office, P.O. Box 2712 Atlanta, GA, 30301-2712 Attn: Reprints are via e-mail from [email protected]=vertaisarvioitu|en=peerReviewed

Factors Affecting the Accessibility of IT Artifacts: A Systematic Review

Accessibility awareness and development have improved in the past two decades, but many users still encounter accessibility barriers when using information technology (IT) artifacts (e.g., user interfaces and websites). Current research in information systems and human-computer interaction disciplines explores methods, techniques, and factors affecting the accessibility of IT artifacts for a particular population and provides solutions to address these barriers. However, design realized in one solution should be used to provide accessibility to the widest range of users, which requires an integration of solutions. To identify the factors that cause accessibility barriers and the solutions for users with different needs, a systematic literature review was conducted. This paper contributes to the existing body of knowledge by revealing (1) management- and development-level factors, and (2) user perspective factors affecting accessibility that address different accessibility barriers to different groups of population (based on the International Classification of Functioning by the World Health Organization). Based on these findings, we synthesize and illustrate the factors and solutions that need to be addressed when creating an accessible IT artifact

A New Web Search Engine with Learning Hierarchy

Most of the existing web search engines (such as Google and Bing) are in the form of keyword-based search. Typically, after the user issues a query with the keywords, the search engine will return a flat list of results. When the query issued by the user is related to a topic, only the keyword matching may not accurately retrieve the whole set of webpages in that topic. On the other hand, there exists another type of search system, particularly in e-Commerce web- sites, where the user can search in the categories of different faceted hierarchies (e.g., product types and price ranges). Is it possible to integrate the two types of search systems and build a web search engine with a topic hierarchy? The main diffculty is how to classify the vast number of webpages on the Internet into the topic hierarchy. In this thesis, we will leverage machine learning techniques to automatically classify webpages into the categories in our hierarchy, and then utilize the classification results to build the new search engine SEE. The experimental results demonstrate that SEE can achieve better search results than the traditional keyword-based search engine in most of the queries, particularly when the query is related to a topic. We also conduct a small-scale usability study which further verifies that SEE is a promising search engine. To further improve SEE, we also propose a new active learning framework with several novel strategies for hierarchical classification

Mapping Nanomedicine Terminology in the Regulatory Landscape

A common terminology is essential in any field of science and technology for a mutual understanding among different communities of experts and regulators, harmonisation of policy actions, standardisation of quality procedures and experimental testing, and the communication to the general public. It also allows effective revision of information for policy making and optimises research fund allocation. In particular, in emerging scientific fields with a high innovation potential, new terms, descriptions and definitions are quickly generated, which are then ambiguously used by stakeholders having diverse interests, coming from different scientific disciplines and/or from various regions. The application of nanotechnology in health -often called nanomedicine- is considered as such emerging and multidisciplinary field with a growing interest of various communities. In order to support a better understanding of terms used in the regulatory domain, the Nanomedicines Working Group of the International Pharmaceutical Regulators Forum (IPRF) has prioritised the need to map, compile and discuss the currently used terminology of regulatory scientists coming from different geographic areas. The JRC has taken the lead to identify and compile frequently used terms in the field by using web crawling and text mining tools as well as the manual extraction of terms. Websites of 13 regulatory authorities and clinical trial registries globally involved in regulating nanomedicines have been crawled. The compilation and analysis of extracted terms demonstrated sectorial and geographical differences in the frequency and type of nanomedicine related terms used in a regulatory context. Finally 31 relevant and most frequently used terms deriving from various agencies have been compiled, discussed and analysed for their similarities and differences. These descriptions will support the development of harmonised use of terminology in the future. The report provides necessary background information to advance the discussion among stakeholders. It will strengthen activities aiming to develop harmonised standards in the field of nanomedicine, which is an essential factor to stimulate innovation and industrial competitiveness.JRC.F.2-Consumer Products Safet

Deep Learning for Phishing Detection: Taxonomy, Current Challenges and Future Directions

This work was supported in part by the Ministry of Higher Education under the Fundamental Research Grant Scheme under Grant FRGS/1/2018/ICT04/UTM/01/1; and in part by the Faculty of Informatics and Management, University of Hradec Kralove, through SPEV project under Grant 2102/2022.Phishing has become an increasing concern and captured the attention of end-users as well as security experts. Existing phishing detection techniques still suffer from the de ciency in performance accuracy and inability to detect unknown attacks despite decades of development and improvement. Motivated to solve these problems, many researchers in the cybersecurity domain have shifted their attention to phishing detection that capitalizes on machine learning techniques. Deep learning has emerged as a branch of machine learning that becomes a promising solution for phishing detection in recent years. As a result, this study proposes a taxonomy of deep learning algorithm for phishing detection by examining 81 selected papers using a systematic literature review approach. The paper rst introduces the concept of phishing and deep learning in the context of cybersecurity. Then, taxonomies of phishing detection and deep learning algorithm are provided to classify the existing literature into various categories. Next, taking the proposed taxonomy as a baseline, this study comprehensively reviews the state-of-the-art deep learning techniques and analyzes their advantages as well as disadvantages. Subsequently, the paper discusses various issues that deep learning faces in phishing detection and proposes future research directions to overcome these challenges. Finally, an empirical analysis is conducted to evaluate the performance of various deep learning techniques in a practical context, and to highlight the related issues that motivate researchers in their future works. The results obtained from the empirical experiment showed that the common issues among most of the state-of-the-art deep learning algorithms are manual parameter-tuning, long training time, and de cient detection accuracy.Ministry of Higher Education under the Fundamental Research Grant Scheme FRGS/1/2018/ICT04/UTM/01/1Faculty of Informatics and Management, University of Hradec Kralove, through SPEV project 2102/202