244,886 research outputs found

    Autonomic computing architecture for SCADA cyber security

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    Cognitive computing relates to intelligent computing platforms that are based on the disciplines of artificial intelligence, machine learning, and other innovative technologies. These technologies can be used to design systems that mimic the human brain to learn about their environment and can autonomously predict an impending anomalous situation. IBM first used the term ‘Autonomic Computing’ in 2001 to combat the looming complexity crisis (Ganek and Corbi, 2003). The concept has been inspired by the human biological autonomic system. An autonomic system is self-healing, self-regulating, self-optimising and self-protecting (Ganek and Corbi, 2003). Therefore, the system should be able to protect itself against both malicious attacks and unintended mistakes by the operator

    Autonomic computing meets SCADA security

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    © 2017 IEEE. National assets such as transportation networks, large manufacturing, business and health facilities, power generation, and distribution networks are critical infrastructures. The cyber threats to these infrastructures have increasingly become more sophisticated, extensive and numerous. Cyber security conventional measures have proved useful in the past but increasing sophistication of attacks dictates the need for newer measures. The autonomic computing paradigm mimics the autonomic nervous system and is promising to meet the latest challenges in the cyber threat landscape. This paper provides a brief review of autonomic computing applications for SCADA systems and proposes architecture for cyber security

    J-Block Triassic Well Performance & Reservoir Heterogeneity

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    Reducing the burden of depression in youth: what are the implications of neuroscience and genetics on policies and programs?

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    Mood disorders are a leading cause of the burden of disease in youth. Three critical lessons emerge from the reviews in this issue that are relevant to our understanding of these common mental disorders: first, that the brain is in a highly dynamic stage of its development during youth; second, that environmental factors interact with genetic factors to influence the probability of risk behaviors and dysphoric states; and third, that shared developmental and genetic factors may account for the bulk of emotional and behavioral outcomes in youth, and that environmental influences may affect the specific expression of the phenotypes associated with these pathways. Although this evidence does not immediately indicate the potential for new interventions, it is consistent with current policy and practice recommendations. Interventions should focus on both improving the early detection and management of depressive disorders as well as preventive strategies that aim to train children and youth to improve cognitive control and manage stress more effectively. Limiting access to harmful risk-taking situations and providing opportunities to engage are less harmful, but equally exciting, alternatives in a pragmatic universal prevention policy option. Key research priorities and paradigms emerge from this evidence, particularly in the context of the grand challenges in global mental health

    Hyper parameters selection for image classification in convolutional neural networks

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    A Transverse Lattice QCD Model for Mesons

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    QCD is analysed with two light-front continuum dimensions and two transverse lattice dimensions. In the limit of large number of colours and strong transverse gauge coupling, the contributions of light-front and transverse directions factorise in the dynamics, and the theory can be analytically solved in a closed form. An integral equation is obtained, describing the properties of mesons, which generalises the 't Hooft equation by including spin degrees of freedom. The meson spectrum, light-front wavefunctions and form factors can be obtained by solving this equation numerically. These results would be a good starting point to model QCD observables which only weakly depend on transverse directions, e.g. deep inelastic scattering structure functions.Comment: Lattice 2003 (theory), 3 page

    Influenza A nucleoprotein binding sites for antivirals: current research and future potential

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    This document is the Accepted Manuscript version of the following article: Andreas Kukol and Hershna Patel, ‘Influenza A nucleoprotein binding sites for antivirals: current research and future potential’, Future Biology, Vol 9(7): 625-627, July 2014. The version of record is available online at doi: 10.2217/fvl.14.45Peer reviewedFinal Accepted Versio

    Optimal Database Search: Waves and Catalysis

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    Grover's database search algorithm, although discovered in the context of quantum computation, can be implemented using any system that allows superposition of states. A physical realization of this algorithm is described using coupled simple harmonic oscillators, which can be exactly solved in both classical and quantum domains. Classical wave algorithms are far more stable against decoherence compared to their quantum counterparts. In addition to providing convenient demonstration models, they may have a role in practical situations, such as catalysis.Comment: 4 pages (v2) 6 pages, RevTeX4. Title changed. Substantially expanded to include stability considerations, quantum domain analysis, application to catalysis. (v3) Version accepted for publication. (v4) Error in Eqs.(10,11) corrected by replacing \omega by \omega^2. No change in implementation and applicatio

    Pediatric Nurse Practitioner Home Visitation is Associated with a Decrease in Home Care and Healthcare Utilization Errors in High Risk Infants

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    The Santa Clara Valley Health and Hospital System’s (SCVHHS) Babies Reaching Improved Development and Growth in their Environment (BRIDGE) program was developed in 2011 to optimize high risk infants\u27 care transition from Neonatal Intensive Care Unit (NICU) to home. In addition to hospital discharge teaching and public health nursing efforts, NICU infants need further in home support given their medical vulnerability after discharge. The objectives of the SCVHHS BRIDGE program are to provide caregiver interventions to minimize home care errors after NICU discharge and to optimize health care access and utilization across the transition of care. SCVHHS NICU infants at risk for developmental delay, who met Department of Health and Human Services (DHHS) California Children’s Services (CCS) High Risk Infant Follow-up (HRIF) criteria, qualified for SCVHHS BRIDGE visits. From April of 2011 to January of 2015 Pediatric Nurse Practitioners (PNPs) met caregivers in the NICU, visited homes a minimum of two times after discharge, identified errors, educated caregivers, coordinated care, and facilitated in the resolution of the errors. Errors were defined as a deviation from prescribed plan of care upon discharge from the NICU or after an ambulatory care visit. Data were collected prospectively and Institutional Review Board (IRB) approved. Chi Square with Yates correction was used to assess for significance. Wilcoxon Rank Sum test was used to assess association between gestational age, length of stay, and birth weight in infants with and without errors. Wilcoxon Signed Rank test was used to assess for significance of error reduction across visits. PNPs monitored, educated and attenuated home care errors between home visits and caregivers over time. Collaborating with caregivers and health care providers in the inpatient, home, and outpatient environments, PNPs have the potential to decrease errors, improve health, reduce health care costs, and optimize growth and development for high risk infants
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