Rearrangement and extremal results for Hermitian matrices

AbstractThis paper contains extreme value results for concave and convex symmetric functions of the eigenvalues of B + P∗AP as functions of the partial isometry P. The matrices A and B are Hermitian

Conditions for the generalized numerical range to be real

AbstractNecessary and sufficient conditions are given for the C-numerical range of a matrix A to be a subset of the real axis. In particular, it is shown that both A and C must be translates of hermitian matrices

The Geography of Black Candidate Electoral Success

In this manuscript, we reexamine claims about the geography of electoral success of African American candidates. Barack Obama\u27s historic election in 2008 prompted journalists, partisans, and scholars to review prior notions of where African American candidates can successfully contend for elected office. Although Obama\u27s victory is just an anecdotal national example (albeit an important one), we review the available evidence at the state level to understand what factors might impede African American electoral success. Heretofore, the literature focused on the density of the black population, and the interconnectedness of region and white racial attitudes. This paper shows that these old standbys can no longer explain African American electoral success

A Survey of the Application of Machine Learning in Decision Support Systems

Machine learning is a useful technology for decision support systems and assumes greater importance in research and practice. Whilst much of the work focuses technical implementations and the adaption of machine learning algorithms to application domains, the factors of machine learning design affecting the usefulness of decision support are still understudied. To enhance the understanding of machine learning and its use in decision support systems, we report the results of our content analysis of design-oriented research published between 1994 and 2013 in major Information Systems outlets. The findings suggest that the usefulness of machine learning for supporting decision-makers is dependent on the task, the phase of decision-making, and the applied technologies. We also report about the advantages and limitations of prior research, the applied evaluation methods and implications for future decision support research. Our findings suggest that future decision support research should shed more light on organizational and people-related evaluation criteria

Coordination of Just-in-Time Deliveries with Multi-attribute Auctions

Just-in-time deliveries are crucial for many industries. They are particularly essential when the properties of the delivered resource or the demanding processes are sensitive in time. Rigid, centralized planning tends to fail, especially in dynamic environments with distributed decisions and control. Under the constraints of distributed decisions and control, auctions promise an efficient allocation of resources. However, a dedicated design of auctions for just-in-time deliveries, which can be incorporated into the design of an IT artifact, is still lacking. We contribute a linear and a quadratic multi-attribute scoring rule for an automated execution by software. We evaluate the artifact in a simulation experiment and reveal the effects of the scoring rules for just-in-time deliveries. Our results provide evidence that the artifact effectively coordinates just-in-time deliveries, which also holds when considering one additional side constraint

Development of a parents' short form survey of their children's oral health.

BackgroundParents play an important role in their children's oral health behaviors, provide oral health access, initiate prevention, and coping strategies for health care.AimThis paper develops a short form (SF) to assist parents to evaluate their children's oral health status using Patient-Reported Outcome Measurement Information System (PROMIS) framework that conceptualized health as physical, mental, and social components.DesignSurveys of parents were conducted at dental clinics in Los Angeles County, together with an on-site clinical examination by dentists to determine clinical outcomes, Children's Oral Health Status Index (COHSI), and referral recommendations (RRs). Graded response models in item response theory were used to create the SF. A toolkit including SF, demographic information, and algorithms was developed to predict the COHSI and RRs.ResultsThe final SF questionnaire consists of eight items. The square root mean squared error for the prediction of COHSI is 7.6. The sensitivity and specificity of using SF to predict immediate treatment needs (binary RRs) are 85% and 31%.ConclusionsThe parent SF is an additional component of the oral health evaluation toolkit that can be used for oral health screening, surveillance program, policy planning, and research of school-aged children and adolescents from guardian perspectives

Developing a Mobile Game Environment to Support Disadvantaged Learners

Schmitz, B., Hoffmann, M., Klamma, R., Klemke, R., & Specht, M. (2012). Developing a Mobile Game Environment to Support Disadvantaged Learners. Proceedings of 12th IEEE International Conference on Advanced Learning Technologies (ICALT 2012) (pp. 223-227). July, 4-6, 2012, Rome, Italy: IEEE Computer Society CPS.This paper reports on the development of WeBuild, a mobile learning game designed to engage learners difficult to reach with IT learning. The development is based on a mobile game engine for the Android smart phone that was devised to support the required multiplayer and location based services. We played and tested the mobile learning game in a training facility of the building industry. The results indicate that the learners accepted the game for the low entry barriers and were motivated to use the game in an educational context. This paper describes the WeBuild prototype and the underlying game engine. Eventually, it presents results from the game session that was carried to assess interface and gameplay usability, technical functionality and motivational aspects of the game design

Computerized adaptive testing and short form development for child and adolescent oral health patient-reported outcomes measurement.

ObjectivesTo develop computerized adaptive testing (CAT) and short forms of self-report oral health measures that are predictive of both the children's oral health status index (COHSI) and the children's oral health referral recommendation (COHRR) scales, for children and adolescents, ages 8-17.Material and methodsUsing final item calibration parameters (discrimination and difficulty parameters) from the item response theory analysis, we performed post hoc CAT simulation. Items most frequently administered in the simulation were incorporated for possible inclusion in final oral health assessment toolkits, to select the best performing eight items for COHSI and COHRR.ResultsTwo previously identified unidimensional sets of self-report items consisting of 19 items for the COHSI and 22 items for the COHRR were administered through CAT resulting in eight-item short forms for both the COHSI and COHRR. Correlations between the simulated CAT scores and the full item bank representing the latent trait are r = .94 for COHSI and r = .96 for COHRR, respectively, which demonstrated high reliability of the CAT and short form.ConclusionsUsing established rigorous measurement development standards, the CAT and corresponding eight-item short form items for COHSI and COHRR were developed to assess the oral health status of children and adolescents, ages 8-17. These measures demonstrated good psychometric properties and can have clinical utility in oral health screening and evaluation and clinical referral recommendations