Satisfaction of visually disabled users with California educational websites

BACKGROUND: College and university websites in the United States are legally required to meet accessibility standards to promote equal opportunity in education for blind and visually disabled students. Web Content Accessibility Guidelines are the recognized standard for website accessibility. OBJECTIVE: Determine how satisfied blind and visually disabled college and university students are with college and university websites in California, and whether compliance with Web Content Accessibility Guidelines is a good predictor of that satisfaction. METHODS: A random sample of websites from California colleges and universities was evaluated for accessibility compliance. A stratified sample of six websites was taken from the initial sample. Thirty blind or visually disabled students performed a prescribed series of tasks on each of the six websites, then answered a Likert-format survey regarding their satisfaction with each website. RESULTS: Sixty-three percent of websites did not meet the first priority accessibility criteria. Participant responses showed a majority were satisfied with websites, both compliant and non-compliant, and a strong correlation between satisfaction and accessibility compliance. CONCLUSIONS: Despite legal requirements, a majority or large minority of college and university websites in California do not meet accessibility guidelines, indicating a significant opportunity to improve the accessibility of those websites.

Research on Intelligent Trash Can Garbage Classification Scheme Based on Improved YOLOv3 Target Detection Algorithm

In recent studies, YOLOv3, a deep learning-based target detection algorithm, becomes extensively used in object recognition, especially guiding the visually disabled. Current YOLOv3-based assistive technology for the disabled person can now achieve high-precision, real-time object recognition. Even though this algorithm has several flaws, including the failure to estimate distances and the difficulty of accurately recognizing points in fog or haze, it can perform well in waste management. Therefore, this study proposes an Intelligent Garbage Monitoring Scheme based on an improved YOLOv3 Target Detection Algorithm (IGMS-iYTDA) to classify the IoT’sgarbages (IoT) enabled trash can. The performance of the proposed scheme has been evaluated and illustrated for various classification evaluation metrics. The evaluation results show the highest classification accuracy of 99.9% compared to existing models for the proposed scheme.

Changes in Incidences of Chronic and Traumatic Diseases before and after Registration as Visually Disabled

Purpose: To analyze changes in the incidences of chronic and traumatic diseases before and after registration as visually disabled.Methods: The incidence and risk of chronic and traumatic diseases were compared between patients registered as visually disabled from 2005 to 2013 and a control group, selected through 1:1 propensity score matching for age, sex, premium quantile, and residential area distribution. Data from the National Health Insurance Service were used and the observation period was set from 2 years before to 5 years after the time of registration as visually disabled. The incidences (%) of chronic and traumatic diseases at the point of interest were determined as the mean values according to year of registration, and the risk was measured by conditional logistic regression analysis.Results: 131,434 visually disabled patients and the same number of non-visually impaired controls were included. The incidences of chronic disease and fall-related injury were higher in the visually disabled group before registration, but gradually decreased and became similar to the control group after registration. In addition, the risk of developing chronic diseases was higher in the visually disabled group until 2 years after registration, while the risk of fall-related injury remained consistently higher in the visually disabled group during the observation period. The incidence and risk of hip fracture in the visually disabled group increased gradually from approximately 1 year before registration and remained consistently higher than in the control group.Conclusions: People with visual disability have higher incidences of chronic diseases than do non-visually impaired people and are at greater risk of traumatic injuries, such as hip fractures or falls. There is a need to establish community infrastructure and expand welfare services for the prevention and early treatment of comorbidities, both for patients with registered visual disabilities and for patients who have not yet registered.

How the Accessibility in E-Commerce Affects the Inclusion of the Visually Impaired?

This study reviews the public policy effectiveness of website accessibility in Mexico and explains how these regulations may affect the visually impaired. The authors did n=6 semi-structured interviews with key players of the visually disabled community and then evaluated n=366 websites with a web scraping tool, using principal components analysis and non-parametric statistics to compare their accessibility by type of website. The authors found that even if there is a regulation for providing equal access to websites, the state of the law is insufficient and non enforced for private and public institutions, affecting the basic human right for visually impaired internet users.

Nepafenac loaded ophthalmic nanocarriers for treatment of uveitis: A review

Visual impairment (VI), a worldwide worry that is probably going to raise with delayed futures, has gained increasing attention in the domain of eye care. Now a days, new cases of visual impairment occur in older individuals, some children are born with visual impairments resulting from retinopathy of prematurity, a condition associated with premature birth. Other children experience vision loss because of congenital glaucoma or congenital cataracts, Uveitis and some experience vision loss of unknown etiology. Uveitis is an intraocular inflammation involving primarily the uveal tract. Vision is one of our most cherished senses. There are nearly 45 million people worldwide who are blind and a further 135 million people are visually disabled. Uveitis causes 0.6% - 11% of blindness in various studies. The ophthalmic preparations are available as buffered, sterile and isotonic solution. For the ocular delivery of drugs, several types of dosage forms are prepared and marketed. As drops are easier to administer so the most prescribed dosage form is the eye drop solution. Nepafenac is unique among ophthalmic NSAIDs in that it is a prodrug deaminated to amfenac, a highly effective non-selective cyclooxygenase inhibitor. The compiled data presented in this review will act as a good information resource and reference point for further research in the field of ocular drug delivery aiming non-invasive sustained release of drugs in the anterior and posterior segments of the eye.

Machine Learning Based Computer Vision Application for Visually Disabled People

With the easy availability of technology, smartphones are playing an important role in every person’s life. Also, with the advancements in computer vision based research, Automatic Driving cars, Object Recognition, Depth Map Prediction, Object Distance Estimation, have reached commendable levels of intelligence and accuracy. Combining the research and technological advancements, we can be hopeful in creating a computer vision based mobile-application which will help guide visually disabled people in performing their day to day tasks with easily available mobile applications. With our study, the visually disabled can perform simple tasks like outdoor/indoor navigation without encountering obstacles, also they can avoid accidental collisions with objects in their surroundings. Currently, there are very few applications which provide the same assistance to the visually impaired. Using physical tools like sticks is a very common practice when it comes to avoiding obstacles in a visually disabled person’s path. Our study will be focused on object detection and depth estimation techniques- two of the most popular and advanced fields in Intelligent Computer vision studies. We have explored more on the traditional challenges and future hopes of incorporating these techniques on embedded devices.