3,103 research outputs found
Submission of content to a digital object repository using a configurable workflow system
The prototype of a workflow system for the submission of content to a digital
object repository is here presented. It is based entirely on open-source
standard components and features a service-oriented architecture. The front-end
consists of Java Business Process Management (jBPM), Java Server Faces (JSF),
and Java Server Pages (JSP). A Fedora Repository and a mySQL data base
management system serve as a back-end. The communication between front-end and
back-end uses a SOAP minimal binding stub. We describe the design principles
and the construction of the prototype and discuss the possibilities and
limitations of work ow creation by administrators. The code of the prototype is
open-source and can be retrieved in the project escipub at
http://sourceforge.ne
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
Dual-FOV Raman and Doppler lidar studies of aerosol-cloud interactions : Simultaneous profiling of aerosols, warm-cloud properties, and vertical wind
Date of Acceptance: 24/04/2014 This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are madeFor the first time, colocated dual-field of view (dual-FOV) Raman lidar and Doppler lidar observations (case studies) of aerosol and cloud optical and microphysical properties below and within thin layered liquid water clouds are presented together with an updraft and downdraft characterization at cloud base. The goal of this work is to investigate the relationship between aerosol load close to cloud base and cloud characteristics of warm (purely liquid) clouds and the study of the influence of vertical motions and turbulent mixing on this relationship. We further use this opportunity to illustrate the applicability of the novel dual-FOV Raman lidar in this field of research. The dual-FOV lidar combines the well-established multiwavelength Raman lidar technique for aerosol retrievals and the multiple-scattering Raman lidar technique for profiling of the single-scattering extinction coefficient, effective radius, number concentration of the cloud droplets, and liquid water content. Key findings of our 3 year observations are presented in several case studies of optically thin altocumulus layers occurring in the lower free troposphere between 2.5 and 4 km height over Leipzig, Germany, during clean and polluted situations. For the clouds that we observed, the most direct link between aerosol proxy (particle extinction coefficient) and cloud proxy (cloud droplet number concentration) was found at cloud base during updraft periods. Above cloud base, additional processes resulting from turbulent mixing and entrainment of dry air make it difficult to determine the direct impact of aerosols on cloud processes.Peer reviewedFinal Published versio
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
Risk scores for long-term unemployment and the assignment to job search counseling
This paper analyses how risk profiling is used to assign unemployed job seekers to job search counseling in Flanders, Belgium. We compare algorithmic selection to self-selection and selection by job search counselors. We discuss practical challenges for the implementation of risk profiling and highlight avenues for further research. We find that algorithmic assignment is used for only a small fraction of the sample and that job search counselors appear to have valuable private information on job seekers' reemployment prospects beyond what is captured by the algorithmic risk score
Job seekers’ perceptions and employment prospects: heterogeneity, duration dependence, and bias
This paper uses job seekers’elicited beliefs about job finding to disentangle the sources of the decline in job-finding rates by duration of unemployment. We document that beliefs have strong predictive power for job finding, but are not revised downward when remaining unemployed and are subject to optimistic bias, especially for the long-term unemployed. Leveraging the predictive power of beliefs, we find substantial heterogeneity in job finding with the resulting dynamic selection explaining most of the observed negative duration dependence in job finding. Moreover, job seekers’beliefs underreact to heterogeneity in job finding, distorting search behavior and increasing long-term unemployment
Fiscal policy coordination in currency unions (at the zero lower bound)
Within currency unions, according to the pre-crises consensus, countries can rely on fiscal policy to stabilize economic activity locally. Monetary policy's role, in turn, is to stabilize economic activity at the union level. Against this background, we reassess the optimal degree of fiscal stabilization within currency union provided that monetary policy is constrained by the zero lower bound on nominal interest rates. Specifically, we contrast the optimal level of government consumption from an individual country's perspective with the optimal level from the union's perspective and explore the need for coordinating expansionary fiscal policies
Cerebrospinal Fluid Tau Protein Levels and F-18-Fluorodeoxyglucose Positron Emission Tomography in the Differential Diagnosis of Alzheimer's Disease
Aims: In this study, we aimed to compare cerebrospinal fluid (CSF) levels of total tau (t-tau), phosphorylated tau (p-tau(181)) and positron emission tomography with F-18-fluorodeoxyglucose (FDG-PET) in the differential diagnosis of Alzheimer's disease (AD) under clinical conditions. Method: In a cross-sectional, blinded, single-center study, we examined a sample of 75 unselected memory clinic patients with clinical diagnoses of dementia of Alzheimer type (DAT; n = 24), amnestic mild cognitive impairment (MCI; n = 16), other dementias (n = 13) and nondemented controls (n = 22). Discriminative accuracy, sensitivity and specificity were calculated and compared using ROC analyses. Results: p-tau(181) and FDG-PET were comparable in separating DAT from controls (sensitivity: 67 vs. 79%; specificity: 91% for both) and patients with other dementias (sensitivity: 71 vs. 79%; specificity: 100% for both). The sensitivity of p-tau 181 in differentiating MCI patients from controls was significantly (p < 0.05) superior to that of FDG-PET (75 vs. 44%) at a comparably high specificity (82 vs. 91%); t-tau measures were less accurate in all analyses. Conclusions: FDG-PET and CSF p-tau(181) levels are able to discriminate DAT in heterogeneous and unselected samples with a high accuracy. CSF p-tau(181) might be somewhat superior for a sensitive detection of patients with MCI. Copyright (C) 2010 S. Karger AG, Base
Radiation hardness of diamond and silicon sensors compared
The radiation hardness of silicon charged particle sensors is compared with
single crystal and polycrystalline diamond sensors, both experimentally and
theoretically. It is shown that for Si- and C-sensors, the NIEL hypothesis,
which states that the signal loss is proportional to the Non-Ionizing Energy
Loss, is a good approximation to the present data. At incident proton and
neutron energies well above 0.1 GeV the radiation damage is dominated by the
inelastic cross section, while at non-relativistic energies the elastic cross
section prevails. The smaller inelastic nucleon-Carbon cross section and the
light nuclear fragments imply that at high energies diamond is an order of
magnitude more radiation hard than silicon, while at energies below 0.1 GeV the
difference becomes significantly smaller.Comment: 6 pages, 4 figurs, invited talk at the Hasselt Diamond Workshop, Feb.
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