Internet security for mobile computing

Mobile devices are now the most dominant computer platform. Every time a mobile web application accesses the internet, the end user’s data is susceptible to malicious attacks. For instance, when paying a bill at a store with NFC mobile payment, navigating through a city operating GPS on a smartphone, or dictating the temperature at a household with a home automation device. These activities seem routine, yet, when vulnerabilities are present they can leave holes for hackers to access bank accounts, pinpoint a user’s recent location, or tell when someone is not at home. The awareness of the end user cannot be trusted. Device vendors and developers must provide safeguards. An ongoing issue is that the present security standards are outdated and were never envisioned with mobile devices in mind. It can be suggested that security is only idling the progress of mobile computing. Still, many application developers and IT professionals do not adopt security standards fast enough to keep up-to-date with known vulnerabilities. The main goals of the next generation of security standards, TLS, will provide developers with greater security efficiency and improved mobile throughput. These proposed capabilities of the TLS protocol will streamline mobile computing into the forefront of security practices. The analysis of this report demonstrates concepts on the direction mobile security, usability, and performance from a development standpoint.Electrical and Computer Engineerin

Predictive Modelling of Bone Age through Classification and Regression of Bone Shapes

Bone age assessment is a task performed daily in hospitals worldwide. This involves a clinician estimating the age of a patient from a radiograph of the non-dominant hand. Our approach to automated bone age assessment is to modularise the algorithm into the following three stages: segment and verify hand outline; segment and verify bones; use the bone outlines to construct models of age. In this paper we address the final question: given outlines of bones, can we learn how to predict the bone age of the patient? We examine two alternative approaches. Firstly, we attempt to train classifiers on individual bones to predict the bone stage categories commonly used in bone ageing. Secondly, we construct regression models to directly predict patient age. We demonstrate that models built on summary features of the bone outline perform better than those built using the one dimensional representation of the outline, and also do at least as well as other automated systems. We show that models constructed on just three bones are as accurate at predicting age as expert human assessors using the standard technique. We also demonstrate the utility of the model by quantifying the importance of ethnicity and sex on age development. Our conclusion is that the feature based system of separating the image processing from the age modelling is the best approach for automated bone ageing, since it offers flexibility and transparency and produces accurate estimate

Health Care Opinion Leaders' Views on Health Care Delivery System Reform

Presents findings of a survey of experts on reforming delivery systems -- organized delivery systems, patient-centered medical homes, and retail clinics -- and recommended policy strategies, such as improving the primary care system

Health Care Opinion Leaders' Views on the Transparency of Health Care Quality and Price Information in the United States

Presents findings from a survey of experts on collecting and reporting public information on the quality and price of healthcare services; the role of transparency in improving quality, efficiency, and cost-effectiveness; and obstacles

Health Care Opinion Leaders' Views on the Quality and Safety of Health Care in the United States

Presents findings from an annual survey of a diverse group of experts on strategies to improve the quality and safety of health care in the United States