MINERVA 2003

This inaugural issue of Minerva includes an article on the inauguration of the University of Maine Honors College; a discussion of Honors Living-Learning communities, Colvin and Balentine Halls; and an article on the introduction of the Honors Read tutorial course. Other highlights include an article on Honors travel to Washington D.C. and Chicago

Risk Assessment Framework for Evaluation of Cybersecurity Threats and Vulnerabilities in Medical Devices

Medical devices are vulnerable to cybersecurity exploitation and, while they can provide improvements to clinical care, they can put healthcare organizations and their patients at risk of adverse impacts. Evidence has shown that the proliferation of devices on medical networks present cybersecurity challenges for healthcare organizations due to their lack of built-in cybersecurity controls and the inability for organizations to implement security controls on them. The negative impacts of cybersecurity exploitation in healthcare can include the loss of patient confidentiality, risk to patient safety, negative financial consequences for the organization, and loss of business reputation. Assessing the risk of vulnerabilities and threats to medical devices can inform healthcare organizations toward prioritization of resources to reduce risk most effectively. In this research, we build upon a database-driven approach to risk assessment that is based on the elements of threat, vulnerability, asset, and control (TVA-C). We contribute a novel framework for the cybersecurity risk assessment of medical devices. Using a series of papers, we answer questions related to the risk assessment of networked medical devices. We first conducted a case study empirical analysis that determined the scope of security vulnerabilities in a typical computerized medical environment. We then created a cybersecurity risk framework to identify threats and vulnerabilities to medical devices and produce a quantified risk assessment. These results supported actionable decision making at managerial and operational levels of a typical healthcare organization. Finally, we applied the framework using a data set of medical devices received from a partnering healthcare organization. We compare the assessment results of our framework to a commercial risk assessment vulnerability management system used to analyze the same assets. The study also compares our framework results to the NIST Common Vulnerability Scoring System (CVSS) scores related to identified vulnerabilities reported through the Common Vulnerability and Exposure (CVE) program. As a result of these studies, we recognize several contributions to the area of healthcare cybersecurity. To begin with, we provide the first comprehensive vulnerability assessment of a robotic surgical environment, using a da Vinci surgical robot along with its supporting computing assets. This assessment supports the assertion that networked computer environments are at risk of being compromised in healthcare facilities. Next, our framework, known as MedDevRisk, provides a novel method for risk quantification. In addition, our assessment approach uniquely considers the assets that are of value to a medical organization, going beyond the medical device itself. Finally, our incorporation of risk scenarios into the framework represents a novel approach to medical device risk assessment, which was synthesized from other well-known standards. To our knowledge, our research is the first to apply a quantified assessment framework to the problem area of healthcare cybersecurity and medical networked devices. We would conclude that a reduction in the uncertainty about the riskiness of the cybersecurity status of medical devices can be achieved using this framework

A new design equation for prediction of ultimate bearing capacity of shallow foundation on granular soils

A major concern in design of structures is to provide precise estimations of ultimate bearing capacity of soil beneath their foundations. Direct determination of the bearing capacity of foundations requires performing expensive and time consuming laboratory tests. To cope with this issue, several numerical models have been presented by researchers. This paper presents the development of a new design equation for the prediction of the ultimate bearing capacity of shallow foundations on granular soils using linear genetic programming (LGP) methodology. The ultimate bearing capacity is formulated in terms of width of footing, footing geometry, depth of footing, unit weight of sand, and angle of shearing resistance. The LGP-based design equation is established using the results of several load tests on real sized foundations presented in the literature. Validity of the model is verified using a part of laboratory data that are not involved in the calibration process. The statistical measures of coefficient of determination, root mean squared error and mean absolute error are used to evaluate the performance of the model. Sensitivity and parametric analyses are conducted and discussed. The proposed model accurately characterizes the ultimate bearing capacity resulting in a very good prediction performance. The LGP model reaches a better prediction performance than the well-known prediction equations for the bearing capacity of shallow foundations

Program and Abstracts Celebration of Student Scholarship, 2012

Program and Abstracts from the Celebration of Student Scholarship on April 25, 2012

Teacher Evaluation–Study of Minnesota Secondary School Principals Related to the Amount of Time Necessary to Implement Common Teacher Evaluation Models

The study measured perceptions of select secondary school principals in Minnesota regarding the teacher evaluation model utilized in their schools and the amount of time principals commit to the process of evaluating their teachers. Research questions were answered through analysis of data from a survey including principal demographics, the teacher evaluation model utilized in the principal’s school, the volume of time principals’ report devoting to teacher evaluation and principal perceptions related to the extent to which the teacher evaluation model improves teacher performance. The responses received showed that 60.5% of respondents were using a model based on Charlotte Danielson and 20.2% of respondents were using a Robert Marzano based teacher evaluation model. Another 10.1% of respondents indicated their district had created their own model and 8.4% reported using a Kim Marshall based model. Principals reported spending between 0 and 10 or more hours per week on teacher evaluation with the most common response of 2-4 hours per week provided by 37.0% of respondents. Based on the results of the study, it is recommended that schools in Minnesota examine the teacher evaluation practices in place to assure the time spent by principals is meaningful for teachers and leads to improved teacher performance

Digital technologies for behavioral change in sustainability domains: a systematic mapping review

Sustainability research has emerged as an interdisciplinary area of knowledge about how to achieve sustainable development, while political actions toward the goal are still in their infancy. A sustainable world is mirrored by a healthy environment in which humans can live without jeopardizing the survival of future generations. The main aim of this contribution was to carry out a systematic mapping (SM) of the applications of digital technologies in promoting environmental sustainability. From a rigorous search of different databases, a set of more than 1000 studies was initially retrieved and then, following screening criteria based on the ROSES (RepOrting standards for Systematic Evidence Syntheses) procedure, a total of N = 37 studies that met the eligibility criteria were selected. The studies were coded according to different descriptive variables, such as digital technology used for the intervention, type of sustainable behavior promoted, research design, and population for whom the intervention was applied. Results showed the emergence of three main clusters of Digital Technologies (i.e., virtual/immersive/augmented reality, gamification, and power-metering systems) and two main Sustainable Behaviors (SBs) (i.e., energy and water-saving, and pollution reduction). The need for a clearer knowledge of which digital interventions work and the reasons why they work (or do not work) does not emerge from the outcomes of this set of studies. Future studies on digital interventions should better detail intervention design characteristics, alongside the reasons underlying design choices, both behaviourally and technologically. This should increase the likelihood of the successful adoption of digital interventions promoting behavioral changes in a more sustainable direction