Protecting Blind Screen-Reader Users From Deceptive Content

Visually impaired people who want to use a computer rely on screen readers to independently do this. This research focuses on beginning to build a chrome extension in order to help users more safely navigate the internet using a screen reader. to begin collecting the data, a screen reader was used to help determine items in the website that might take the user somewhere they did not mean to go since the link or image was not sufficiently able to be described by the screen reader. Next, those items were tagged with ’data-attribute=”deceptive”’. After, those data-attributes were extracted and tagged with values for various features in it, and a code at the end for if it was a deceptive item. Then six different machine learning models were created in order to predict whether an item on a website is deceptive. Overall, the best model for this data set was the Random Forest Classification from the Scikit-Learn Python Library. Overall, there is much more to be done to improve the accuracy and usability of the models, and then develop the chrome extension, but this is research created a point to begin from for future research.https://digitalcommons.odu.edu/reu2022_computerscience/1002/thumbnail.jp

Occurrence of bronchial anthracofibrosis in respiratory symptomatics with exposure to biomass fuel smoke

  INTRODUCTION: Bronchial anthracofibrosis (BAF), confirmed bronchoscopically, is characterised by bluish-black mucosal pigmentation and distortion/narrowing of the bronchus. We investigated the occurrence of BAF in respiratory symptomatics with biomass fuel smoke exposure and evaluated its clinico-radiological attributes and impact on functional status. MATERIAL AND METHODS: Of the eighty subjects evaluated, 60 consented for fiberoptic bronchoscopy (FOB). All 60 subjects also underwent chest radiography, high resolution computed tomography (HRCT) of the thorax, complete pulmonary function testing including diffusion capacity and six-minute-walk test. Information regarding cardinal respiratory symptoms and duration of biomass fuel smoke exposure was documented. FOB evaluation revealed that 24 patients had BAF (Group 1), 17 had bronchial anthracosis (Group 2) and 19 had normal appearance (Group 3). RESULTS: Group 1 patients had significantly higher biomass fuel smoke exposure (p < 0.0001), lower mean post bronchodilator FEV1/FVC values (P = 0.02) and lower walk distance (p = 0.003) with greater desaturation. On HRCT, segmental collapse and consolidation were significantly higher in Group 1 while fibrotic lesions were the predominantly seen in Groups 2 and 3. A significant inverse correlation in Group 1 was seen between exposure index, six-minute-walk distance and spirometric parameters. In Group 1, the right middle lobe (RML) bronchus was most commonly involved (15/24 [62.5%]). In Group 2, RML and left upper lobe bronchi were affected in 8/17 (47.1%) patients each. CONCLUSIONS: All patients in our study were females. Those with BAF had poorer lung functions and functional status as compared to those with anthracosis only. On imaging, multifocal bronchial narrowing was specific to BAF.    

On Weighted Generalized Residual Information Measure

In this paper, we have proposed the concept of weighted generalized residual entropy of order α and type β, and have shown that the proposed measure characterizes the distribution function uniquely

StreamingHub: Interactive Stream Analysis Workflows

Reusable data/code and reproducible analyses are foundational to quality research. This aspect, however, is often overlooked when designing interactive stream analysis workflows for time-series data (e.g., eye-tracking data). A mechanism to transmit informative metadata alongside data may allow such workflows to intelligently consume data, propagate metadata to downstream tasks, and thereby auto-generate reusable, reproducible analytic outputs with zero supervision. Moreover, a visual programming interface to design, develop, and execute such workflows may allow rapid prototyping for interdisciplinary research. Capitalizing on these ideas, we propose StreamingHub, a framework to build metadata propagating, interactive stream analysis workflows using visual programming. We conduct two case studies to evaluate the generalizability of our framework. Simultaneously, we use two heuristics to evaluate their computational fluidity and data growth. Results show that our framework generalizes to multiple tasks with a minimal performance overhead

Repurposing Visual Input Modalities for Blind Users: A Case Study of Word Processors

Visual \u27point-and-click\u27 interaction artifacts such as mouse and touchpad are tangible input modalities, which are essential for sighted users to conveniently interact with computer applications. In contrast, blind users are unable to leverage these visual input modalities and are thus limited while interacting with computers using a sequentially narrating screen-reader assistive technology that is coupled to keyboards. As a consequence, blind users generally require significantly more time and effort to do even simple application tasks (e.g., applying a style to text in a word processor) using only keyboard, compared to their sighted peers who can effortlessly accomplish the same tasks using a point-and-click mouse. This paper explores the idea of repurposing visual input modalities for non-visual interaction so that blind users too can draw the benefits of simple and efficient access from these modalities. Specifically, with word processing applications as the representative case study, we designed and developed NVMouse as a concrete manifestation of this repurposing idea, in which the spatially distributed word-processor controls are mapped to a virtual hierarchical \u27Feature Menu\u27 that is easily traversable non-visually using simple scroll and click input actions. Furthermore, NVMouse enhances the efficiency of accessing frequently-used application commands by leveraging a data-driven prediction model that can determine what commands the user will most likely access next, given the current \u27local\u27 screen-reader context in the document. A user study with 14 blind participants comparing keyboard-based screen readers with NVMouse, showed that the latter significantly reduced both the task-completion times and user effort (i.e., number of user actions) for different word-processing activities

Comparative study between choices of preoperative and post operative dress wear among orthopedics patients

Background: Clothes are identity of an individual. A monk, a priest, a doctor, a lawyer etc. all can be identified by clothing. But can we identify preoperative and postoperative orthopedics patient simply by difference in clothing? Can we evaluate the reasons for this difference in clothing mainly due to hide surgical scar or may be due to comfort fit or may be due to compensation of gait abnormalities etc. Methods: The study was conducted at Maharaja Agrasen medical college, India with a population of 1000 OPD and indoor patient for a period of 6 months from January 2022 to June 2022, with data collection and compilation for another 3 months. Our study is an observational retrospective study which discovers where pre trauma preference is for skin tight clothing like jeans, t shirt for men and skirt for girls, post trauma post operative preference shifts to loose and formal clothes like full sleeves shirt, formal pant, pajama, lungi, dhoti for men and full length skirt for girl and saree for women. Results: Causes enlisted for such clothing was hiding surgical scar (80%), comfortable fitting (10%), to hide gait abnormalities (7%), limb length discrepancies (2%), miscellaneous (1%). Conclusions: We claim to be first in literature to have thought and research on this wonderful topic. We claim to devise new system of surgical and non-surgical wear in post operative patients with our research. We also bring out reason for such difference in clothing and work closely with our in-house patient for preference in clothing

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

A comparative study to assess the safety and efficacy of etoricoxib versus aceclofenac in osteoarthritis

Background: Osteoarthritis (OA) is most common form of arthritis; also referred as degenerative joint disease or “wear and tear” arthritis. Cyclooxygenase-2 (COX-2) inhibitors are effective for pain and inflammation in OA and gained importance over conventional non-steroidal anti-inflammatory agents (NSAIDs), as causes significantly less toxicity, particularly, in gastrointestinal tract. The objective of the present research was to study the short-term comparative clinical efficacy of aceclofenac and etoricoxib in patients with osteoarthritis and to compare the safety profile of the two drugs i.e. aceclofenac and etoricoxib.Methods: The present study was a prospective, open label, parallel, intention to treat 80 patients out of 102 screened for osteoarthritis in the Department of Orthopaedics, Guru Nanak Dev Hospital attached to the Government Medical College, Amritsar. Patients were randomly divided in two groups with 40 patients each. Group A patients received Tab etoricoxib 60mg once daily and Group B patients received Tab. Aceclofenac 100mg twice daily. Patients were followed up after three weeks and at six weeks for clinical efficacy and safety.Results: Both the groups found to have significant improvement in signs and symptoms of osteoarthritis. However, aceclofenac was superior to etoricoxib in terms of change in visual analogue scale score, osteoarthritic severity index, patients’ and physicians’ global assessment while, etoricoxib was superior in terms of WOMAC osteoarthritic index and safety parameters in terms of ADR.Conclusions: Etoricoxib was better than conventional NSAIDs for the symptomatic management of osteoarthritis in terms of safety profile and clinical efficacy