A communication and information technology infrastructure for real time monitoring and management of type 1 diabetes patients

This paper is focused on the integration of state-of-the-art technologies in the fields of telecommunications, simulation algorithms, and data mining in order to develop a Type 1 diabetes patient's semi to fully-automated monitoring and management system. The main components of the system are a glucose measurement device, an insulin delivery system (insulin injection or insulin pumps), a mobile phone for the GPRS network, and a PDA or laptop for the Internet. In the medical environment, appropriate infrastructure for storage, analysis and visualizing of patients' data has been implemented to facilitate treatment design by health care experts.

Entrepreneurship in a Hub-and-Spoke Industrial District: Firm Survey Evidence from Seattle's Technology Industry

Mayer H. Entrepreneurship in a hub-and-spoke industrial district: firm survey evidence from Seattle's technology industry, Regional Studies. The paper investigates entrepreneurial dynamics in a hub-and-spoke industrial district. Using data on the genealogy of high-technology firms in Seattle, Washington State, the study examines the ways in which entrepreneurial firms relate to their parent firms and the role of agglomeration economies. The results illustrate that entrepreneurship is an important vehicle for the diversification of such a district. When compared, hub-related spinoffs such as those founded by former Microsoft employees do not differ much from other start-ups. The differences between Microsoft spinoffs and start-ups are very limited; both diversify the regional economy by entering new markets when compared with their parents.

Iowa State Daily (April 5, 2012)

ContentsEnjoy a caveman's dietFair focuses on science, technology, math fieldsStudents present research at CapitolRacism finds its sociological roots Track and field looks to future of conference

Progress Report on Iowa State University Burroughs Endowment Activities

Faculty in the Department of Animal Science initiated soliciting of funds in 1987 to establish a permanent endowment to recognize the distinguished career and major contributions of Dr. Wise Burroughs, a distinguished professor in animal science at Iowa State University. The endowment was established in the Iowa State University Foundation in 1991. The purpose of the fund is to support research and graduate education in the areas of fundamental factors regulating growth in food-producing animals, with emphasis on ruminants; to enhance growth of animals with the goal of improving the competitive position of ruminants as food-producing animals; and to develop innovative approaches to ruminant nutrition and/or growth enhancement as a means to improve desirability of meat produced by food animals. Dr. Burroughs’ research resulted in important and significant developments in technology for modern production systems for beef cattle. He was widely known for his ability to communicate complex ideas and research results for use by those involved in the animal industry. The current Burroughs Team has established three research projects: 1) Ghrelin--How does ghrelin affect blood and body composition in rats?; 2) Use of 25- hydroxyvitamin D3 to improve tenderness of beef; 3) Redesigning beef cattle to have a more healthful fatty acid composition.

Iowa State University ADVANCE Program, Annual Report, Year 1: June 2007

The goal of the ISU ADVANCE program is to investigate the effectiveness of a multilevel collaborative effort to produce institutional transformation that results in the full participation of women faculty in science, technology, engineering and math fields in the university. Our approach focuses on transforming departmental cultures (views, attitudes, norms and shared beliefs), practices (what people say and do), and structures (physical and social arrangements), as well as university policies, through active participation of individuals at all levels of the university.

The New Concept of Universal Service in a Digital Networked Communications Environment

Digitization, sophisticated fiber-optic networks and the resultant convergence of the media, communications and information technology industries have completely transformed the communications ecosystem in the last couple of decades. New contingent business and social models were created that have been mirrored in the amended communications regimes. Yet, despite an overhaul of the communications regulation paradigm, the status of and the rules on universal service have remained surprisingly intact, both during and after the liberalization exercise. The present paper looks into this paradox and examines the sustainability of the existing concept of universal service. It suggests that there is a need for a novel concept of universal service in the digital networked communications environment, whose objectives go beyond the conventional internalizing and redistributional rationales and concentrate on communication and information networks as a public good, where not only access to infrastructure but also access to content may be essential.

State-of-the-art aortic imaging: part I - fundamentals and perspectives of CT and MRI

Over the last two decades, imaging of the aorta has undergone a clinically relevant change. As part of the change non-invasive imaging techniques have replaced invasive intra-arterial digital subtraction angiography as the former imaging gold standard for aortic diseases. Computed tomography (CT) and magnetic resonance imaging (MRI) constitute the backbone of pre- and postoperative aortic imaging because they allow for imaging of the entire aorta and its branches. The first part of this review article describes the imaging principles of CT and MRI with regard to aortic disease, shows how both technologies can be applied in every day clinical practice, offering exciting perspectives. Recent CT scanner generations deliver excellent image quality with a high spatial and temporal resolution. Technical developments have resulted in CT scan performed within a few seconds for the entire aorta. Therefore, CT angiography (CTA) is the imaging technology of choice for evaluating acute aortic syndromes, for diagnosis of most aortic pathologies, preoperative planning and postoperative follow-up after endovascular aortic repair. However, radiation dose and the risk of contrast induced nephropathy are major downsides of CTA. Optimisation of scan protocols and contrast media administration can help to reduce the required radiation dose and contrast media. MR angiography (MRA) is an excellent alternative to CTA for both diagnosis of aortic pathologies and postoperative follow-up. The lack of radiation is particularly beneficial for younger patients. A potential side effect of gadolinium contrast agents is nephrogenic systemic fibrosis (NSF). In patients with high risk of NSF unenhanced MRA can be performed with both ECG- and breath-gating techniques. Additionally, MRI provides the possibility to visualise and measure both dynamic and flow information.

The Evolution of Routines under flexible Information Technology

Many technological developments of the past two decades come with the promise of greater IT flexi-bility, i.e. greater capacity to adapt IT. These technologies are increasingly used to improve organiza-tional routines that are not affected by large, hard-to-change IT such as ERP. Yet, most findings on the interaction of routines and IT stem from contexts where IT is hard to change. Our research ex-plores how routines and IT co-evolve when IT is flexible. We review the literatures on routines to sug-gest that IT may act as a boundary object that mediates the learning process unfolding between the ostensive and the performative aspect of the routine. Although prior work has concluded from such conceptualizations that IT stabilizes routines, we qualify that flexible IT can also stimulate change because it enables learning in short feedback cycles. We suggest that, however, such change might not always materialize because it is contingent on governance choices and technical knowledge. We de-scribe the case-study method to explore how routines and flexible IT co-evolve and how governance and technical knowledge influence this process. We expect to contribute towards stronger theory of routines and to develop recommendations for the effective implementation of flexible IT in loosely coupled routines.

Evaluation of Three State-of-the-Art Classifiers for Recognition of Activities of Daily Living from Smart Home Ambient Data

Smart homes for the aging population have recently started attracting the attention of the research community. The "health state" of smart homes is comprised of many different levels; starting with the physical health of citizens, it also includes longer-term health norms and outcomes, as well as the arena of positive behavior changes. One of the problems of interest is to monitor the activities of daily living (ADL) of the elderly, aiming at their protection and well-being. For this purpose, we installed passive infrared (PIR) sensors to detect motion in a specific area inside a smart apartment and used them to collect a set of ADL. In a novel approach, we describe a technology that allows the ground truth collected in one smart home to train activity recognition systems for other smart homes. We asked the users to label all instances of all ADL only once and subsequently applied data mining techniques to cluster in-home sensor firings. Each cluster would therefore represent the instances of the same activity. Once the clusters were associated to their corresponding activities, our system was able to recognize future activities. To improve the activity recognition accuracy, our system preprocessed raw sensor data by identifying overlapping activities. To evaluate the recognition performance from a 200-day dataset, we implemented three different active learning classification algorithms and compared their performance: naive Bayesian (NB), support vector machine (SVM) and random forest (RF). Based on our results, the RF classifier recognized activities with an average specificity of 96.53%, a sensitivity of 68.49%, a precision of 74.41% and an F-measure of 71.33%, outperforming both the NB and SVM classifiers. Further clustering markedly improved the results of the RF classifier. An activity recognition system based on PIR sensors in conjunction with a clustering classification approach was able to detect ADL from datasets collected from different homes. Thus, our PIR-based smart home technology could improve care and provide valuable information to better understand the functioning of our societies, as well as to inform both individual and collective action in a smart city scenario.

Using small area estimation and geographic information systems technology to target health services for the uninsured

The three articles that comprise this dissertation describe how small area estimation and geographic information systems (GIS) technologies can be integrated to provide useful information about the number of uninsured and where they are located. Comprehensive data about the numbers and characteristics of the uninsured are typically only available from surveys. Utilization and administrative data are poor proxies from which to develop this information. Those who cannot access services are unlikely to be fully captured, either by health care provider utilization data or by state and local administrative data. In the absence of direct measures, a well-developed estimation of the local uninsured count or rate can prove valuable when assessing the unmet health service needs of this population. However, the fact that these are “estimates” increases the chances that results will be rejected or, at best, treated with suspicion. The visual impact and spatial analysis capabilities afforded by geographic information systems (GIS) technology can strengthen the likelihood of acceptance of area estimates by those most likely to benefit from the information, including health planners and policy makers. ^ The first article describes how uninsured estimates are currently being performed in the Houston metropolitan region. It details the synthetic model used to calculate numbers and percentages of uninsured, and how the resulting estimates are integrated into a GIS. The second article compares the estimation method of the first article with one currently used by the Texas State Data Center to estimate numbers of uninsured for all Texas counties. Estimates are developed for census tracts in Harris County, using both models with the same data sets. The results are statistically compared. The third article describes a new, revised synthetic method that is being tested to provide uninsured estimates at sub-county levels for eight counties in the Houston metropolitan area. It is being designed to replicate the same categorical results provided by a current U.S. Census Bureau estimation method. The estimates calculated by this revised model are compared to the most recent U.S. Census Bureau estimates, using the same areas and population categories. ^