Relinquishing and Governing the Volatile: The Many Afghanistans and Critical Research Agendas of NATO's Governance

This article invites academics and policy analysts to examine the mechanisms and legacy of NATO's security and development governance of Afghan social spaces by using critical theory concepts. It argues that such scholarly endeavors are growing in importance as the United States and NATO gradually pull their troops out of Afghanistan. Thus, the article suggests a broad twofold research agenda. First, it points out that researching social spaces such as towns, villages, marketplaces, and neighborhoods beyond the realm of intergovernmental politics can lead to thick descriptions of how such places have been governed from within by agents external to them. Second, the study argues for a multifaceted examination of instruments, strategies, and institutions of security governance, its conduct and social effects by deploying critical and Foucauldian concepts such as the rationality and apparatuses of power relations. Thereby, it proposes an inquiry into Provincial Reconstruction Teams and Afghan National Security Forces as spatially and temporally specific apparatuses of surveillance and security

Jefferson Digital Commons quarterly report: April-June 2019

This quarterly report includes: Articles CREATE Day Presentations Dissertations From the Archives Grand Rounds and Lectures House Staff Quality Improvement and Patient Safety Posters JCIPE Student Hotspotting Posters Journals and Newsletters MPH Capstone Presentations Posters Sigma Xi Research Day What People are Saying About the Jefferson Digital Common

Medical data processing and analysis for remote health and activities monitoring

Recent developments in sensor technology, wearable computing, Internet of Things (IoT), and wireless communication have given rise to research in ubiquitous healthcare and remote monitoring of human\u2019s health and activities. Health monitoring systems involve processing and analysis of data retrieved from smartphones, smart watches, smart bracelets, as well as various sensors and wearable devices. Such systems enable continuous monitoring of patients psychological and health conditions by sensing and transmitting measurements such as heart rate, electrocardiogram, body temperature, respiratory rate, chest sounds, or blood pressure. Pervasive healthcare, as a relevant application domain in this context, aims at revolutionizing the delivery of medical services through a medical assistive environment and facilitates the independent living of patients. In this chapter, we discuss (1) data collection, fusion, ownership and privacy issues; (2) models, technologies and solutions for medical data processing and analysis; (3) big medical data analytics for remote health monitoring; (4) research challenges and opportunities in medical data analytics; (5) examples of case studies and practical solutions

Protected Health Information filter (Philter): accurately and securely de-identifying free-text clinical notes.

There is a great and growing need to ascertain what exactly is the state of a patient, in terms of disease progression, actual care practices, pathology, adverse events, and much more, beyond the paucity of data available in structured medical record data. Ascertaining these harder-to-reach data elements is now critical for the accurate phenotyping of complex traits, detection of adverse outcomes, efficacy of off-label drug use, and longitudinal patient surveillance. Clinical notes often contain the most detailed and relevant digital information about individual patients, the nuances of their diseases, the treatment strategies selected by physicians, and the resulting outcomes. However, notes remain largely unused for research because they contain Protected Health Information (PHI), which is synonymous with individually identifying data. Previous clinical note de-identification approaches have been rigid and still too inaccurate to see any substantial real-world use, primarily because they have been trained with too small medical text corpora. To build a new de-identification tool, we created the largest manually annotated clinical note corpus for PHI and develop a customizable open-source de-identification software called Philter ("Protected Health Information filter"). Here we describe the design and evaluation of Philter, and show how it offers substantial real-world improvements over prior methods

Big data analytics in healthcare: promise and potential

Objective To describe the promise and potential of big data analytics in healthcare. Methods The paper describes the nascent field of big data analytics in healthcare, discusses the benefits, outlines an architectural framework and methodology, describes examples reported in the literature, briefly discusses the challenges, and offers conclusions. Results The paper provides a broad overview of big data analytics for healthcare researchers and practitioners. Conclusions Big data analytics in healthcare is evolving into a promising field for providing insight from very large data sets and improving outcomes while reducing costs. Its potential is great; however there remain challenges to overcome

Design against crime european exchange tool. Guidance for designing against crime across Europe

This guidance—a key output of the European Commission's AGIS 2006 project led by the University of Salford—aims to help local authorities, planners, police, academics, design professionals and developers identify methods of addressing crime prevention through design and planning, tailoring the approach to the European context. Guidance on addressing fear of crime and insecurity is also provided. The guidance is divided into the following sections: ๏ Design-led Crime Prevention Approaches ๏ Advice for European countries ๏ Further information and reference