Presenting a Multi-level Superstructure Optimization Approach for Mechatronic System Design

DEFF Research Database (Denmark)

Pedersen, Henrik C.; Andersen, Torben Ole; Bech, Michael Møller

2010-01-01

Synergism and integration in the design process is what sets apart a Mechatronic System from a traditional, multidisciplinary system. However the typical design approach has been to divide the design problem into sub problems for each technology area (mechanics, electronics and control) and descr......Synergism and integration in the design process is what sets apart a Mechatronic System from a traditional, multidisciplinary system. However the typical design approach has been to divide the design problem into sub problems for each technology area (mechanics, electronics and control......) and describe the interface between the technologies, whereas the lack of well-established, systematic engineering methods to form the basic set-off in analysis and design of complete mechatronic systems has been obvious. The focus of the current paper is therefore to present an integrated design approach...... for mechatronic system design, utilizing a multi-level superstructure optimization based approach. Finally two design examples are presented and the possibilities and limitations of the approach are outlined....

A multi-attribute approach to choosing adaptation strategies: Application to sea-level rise

International Nuclear Information System (INIS)

Smith, A.E.; Chu, H.Q.

1994-01-01

Selecting good adaptation strategies in anticipation of climate change is gaining increasing attention as it becomes increasingly clear that much of the likely change is already committed, and could not be avoided even with aggressive and immediate emissions reductions. Adaptation decision making will place special requirements on regional and local planners in the US and other countries, especially developing countries. Approaches, tools, and guidance will be useful to assist in an effective response to the challenge. This paper describes the value of using a multi-attribute approach for evaluating adaptation strategies and its implementation as a decision-support software tool to help planners understand and execute this approach. The multi-attribute approach described here explicitly addresses the fact that many aspects of the decision cannot be easily quantified, that future conditions are highly uncertain, and that there are issues of equity, flexibility, and coordination that may be as important to the decision as costs and benefits. The approach suggested also avoids trying to collapse information on all of the attributes to a single metric. Such metrics can obliterate insights about the nature of the trade-offs that must be made in choosing among very dissimilar types of responses to the anticipated threat of climate change. Implementation of such an approach requires management of much information, and an ability to easily manipulate its presentation while seeking acceptable trade-offs. The Adaptation Strategy Evaluator (ASE) was developed under funding from the US Environmental Protection Agency to provide user-friendly, PC-based guidance through the major steps of a multi-attribute evaluation. The initial application of ASE, and the focus of this paper, is adaptation to sea level rise. However, the approach can be easily adapted to any multi-attribute choice problem, including the range of other adaptation planning needs

Evaluation Considerations for Secondary Uses of Clinical Data: Principles for an Evidence-based Approach to Policy and Implementation of Secondary Analysis.

Science.gov (United States)

Scott, P J; Rigby, M; Ammenwerth, E; McNair, J Brender; Georgiou, A; Hyppönen, H; de Keizer, N; Magrabi, F; Nykänen, P; Gude, W T; Hackl, W

2017-08-01

Objectives: To set the scientific context and then suggest principles for an evidence-based approach to secondary uses of clinical data, covering both evaluation of the secondary uses of data and evaluation of health systems and services based upon secondary uses of data. Method: Working Group review of selected literature and policy approaches. Results: We present important considerations in the evaluation of secondary uses of clinical data from the angles of governance and trust, theory, semantics, and policy. We make the case for a multi-level and multi-factorial approach to the evaluation of secondary uses of clinical data and describe a methodological framework for best practice. We emphasise the importance of evaluating the governance of secondary uses of health data in maintaining trust, which is essential for such uses. We also offer examples of the re-use of routine health data to demonstrate how it can support evaluation of clinical performance and optimize health IT system design. Conclusions: Great expectations are resting upon "Big Data" and innovative analytics. However, to build and maintain public trust, improve data reliability, and assure the validity of analytic inferences, there must be independent and transparent evaluation. A mature and evidence-based approach needs not merely data science, but must be guided by the broader concerns of applied health informatics. Georg Thieme Verlag KG Stuttgart.

A Multi-level Examination of how the Organizational Context Relates to Readiness to Implement Prevention and Evidence-Based Programming in Community Settings

Science.gov (United States)

Chilenski, Sarah M.; Olson, Jonathan R.; Schulte, Jill A.; Perkins, Daniel F.; Spoth, Richard

2015-01-01

Prior theoretical and empirical research suggests that multiple aspects of an organization’s context are likely related to a number of factors, from their interest and ability to adopt new programming, to client outcomes. A limited amount of the prior research has taken a more community-wide perspective by examining factors that associate with community readiness for change, leaving how these findings generalize to community organizations that conduct prevention or positive youth development programs unknown. Thus for the current study, we examined how the organizational context of the Cooperative Extension System (CES) associates with current attitudes and practices regarding prevention and evidence-based programming. Attitudes and practices have been found in the empirical literature to be key indicators of an organization’s readiness to adopt prevention and evidence-based programming. Based on multi-level mixed models, results indicate that organizational management practices distinct from program delivery may affect an organization’s readiness to adopt and implement new prevention and evidence-based youth programs, thereby limiting the potential public health impact of evidence-based programs. Openness to change, openness of leadership, and communication were the strongest predictors identified within this study. An organization’s morale was also found to be a strong predictor of an organization’s readiness. The findings of the current study are discussed in terms of implications for prevention and intervention. PMID:25463014

Empirically Examining the Performance of Approaches to Multi-Level Matching to Study the Effect of School-Level Interventions

Science.gov (United States)

Hallberg, Kelly; Cook, Thomas D.; Figlio, David

2013-01-01

The goal of this paper is to provide guidance for applied education researchers in using multi-level data to study the effects of interventions implemented at the school level. Two primary approaches are currently employed in observational studies of the effect of school-level interventions. One approach employs intact school matching: matching…

Tree-Based Ecosystem Approaches (TBEAs as Multi-Functional Land Management Strategies—Evidence from Rwanda

Directory of Open Access Journals (Sweden)

Miyuki Iiyama

2018-04-01

Full Text Available Densely populated rural areas in the East African Highlands have faced significant intensification challenges under extreme population pressure on their land and ecosystems. Sustainable agricultural intensification, in the context of increasing cropping intensities, is a prerequisite for deliberate land management strategies that deliver multiple ecosystem goods (food, energy, income sources, etc. and services (especially improving soil conditions on the same land, as well as system resilience, if adopted at scale. Tree based ecosystem approaches (TBEAs are among such multi-functional land management strategies. Knowledge on the multi-functionality of TBEAs and on their scaling up, however, remains severely limited due to several methodological challenges. This study aims at offering an analytical perspective to view multi-functional TBEAs as an integral part of sustainable agricultural intensification. The study proposes a conceptual framework to guide the analysis of socio-economic data and applies it to cross-site analysis of TBEAs in extremely densely populated Rwanda. Heterogeneous TBEAs were identified across Rwanda’s different agro-ecological zones to meet locally-specific smallholders’ needs for a set of ecosystem goods and services on the same land. The sustained adoption of TBEAs would be guaranteed if farmers subjectively recognize their compatibility and synergy with sustainable intensification of existing farming systems, supported by favorable institutional conditions.

Multi-level and hybrid modelling approaches for systems biology.

Science.gov (United States)

Bardini, R; Politano, G; Benso, A; Di Carlo, S

2017-01-01

During the last decades, high-throughput techniques allowed for the extraction of a huge amount of data from biological systems, unveiling more of their underling complexity. Biological systems encompass a wide range of space and time scales, functioning according to flexible hierarchies of mechanisms making an intertwined and dynamic interplay of regulations. This becomes particularly evident in processes such as ontogenesis, where regulative assets change according to process context and timing, making structural phenotype and architectural complexities emerge from a single cell, through local interactions. The information collected from biological systems are naturally organized according to the functional levels composing the system itself. In systems biology, biological information often comes from overlapping but different scientific domains, each one having its own way of representing phenomena under study. That is, the different parts of the system to be modelled may be described with different formalisms. For a model to have improved accuracy and capability for making a good knowledge base, it is good to comprise different system levels, suitably handling the relative formalisms. Models which are both multi-level and hybrid satisfy both these requirements, making a very useful tool in computational systems biology. This paper reviews some of the main contributions in this field.

Coupling biomechanics to a cellular level model: an approach to patient-specific image driven multi-scale and multi-physics tumor simulation.

Science.gov (United States)

May, Christian P; Kolokotroni, Eleni; Stamatakos, Georgios S; Büchler, Philippe

2011-10-01

Modeling of tumor growth has been performed according to various approaches addressing different biocomplexity levels and spatiotemporal scales. Mathematical treatments range from partial differential equation based diffusion models to rule-based cellular level simulators, aiming at both improving our quantitative understanding of the underlying biological processes and, in the mid- and long term, constructing reliable multi-scale predictive platforms to support patient-individualized treatment planning and optimization. The aim of this paper is to establish a multi-scale and multi-physics approach to tumor modeling taking into account both the cellular and the macroscopic mechanical level. Therefore, an already developed biomodel of clinical tumor growth and response to treatment is self-consistently coupled with a biomechanical model. Results are presented for the free growth case of the imageable component of an initially point-like glioblastoma multiforme tumor. The composite model leads to significant tumor shape corrections that are achieved through the utilization of environmental pressure information and the application of biomechanical principles. Using the ratio of smallest to largest moment of inertia of the tumor material to quantify the effect of our coupled approach, we have found a tumor shape correction of 20% by coupling biomechanics to the cellular simulator as compared to a cellular simulation without preferred growth directions. We conclude that the integration of the two models provides additional morphological insight into realistic tumor growth behavior. Therefore, it might be used for the development of an advanced oncosimulator focusing on tumor types for which morphology plays an important role in surgical and/or radio-therapeutic treatment planning. Copyright © 2011 Elsevier Ltd. All rights reserved.

Enhancing evidence informed policymaking in complex health systems: lessons from multi-site collaborative approaches.

Science.gov (United States)

Langlois, Etienne V; Becerril Montekio, Victor; Young, Taryn; Song, Kayla; Alcalde-Rabanal, Jacqueline; Tran, Nhan

2016-03-17

There is an increasing interest worldwide to ensure evidence-informed health policymaking as a means to improve health systems performance. There is a need to engage policymakers in collaborative approaches to generate and use knowledge in real world settings. To address this gap, we implemented two interventions based on iterative exchanges between researchers and policymakers/implementers. This article aims to reflect on the implementation and impact of these multi-site evidence-to-policy approaches implemented in low-resource settings. The first approach was implemented in Mexico and Nicaragua and focused on implementation research facilitated by communities of practice (CoP) among maternal health stakeholders. We conducted a process evaluation of the CoPs and assessed the professionals' abilities to acquire, analyse, adapt and apply research. The second approach, called the Policy BUilding Demand for evidence in Decision making through Interaction and Enhancing Skills (Policy BUDDIES), was implemented in South Africa and Cameroon. The intervention put forth a 'buddying' process to enhance demand and use of systematic reviews by sub-national policymakers. The Policy BUDDIES initiative was assessed using a mixed-methods realist evaluation design. In Mexico, the implementation research supported by CoPs triggered monitoring by local health organizations of the quality of maternal healthcare programs. Health programme personnel involved in CoPs in Mexico and Nicaragua reported improved capacities to identify and use evidence in solving implementation problems. In South Africa, Policy BUDDIES informed a policy framework for medication adherence for chronic diseases, including both HIV and non-communicable diseases. Policymakers engaged in the buddying process reported an enhanced recognition of the value of research, and greater demand for policy-relevant knowledge. The collaborative evidence-to-policy approaches underline the importance of iterations and continuity

A Multi-step and Multi-level approach for Computer Aided Molecular Design

DEFF Research Database (Denmark)

. The problem formulation step incorporates a knowledge base for the identification and setup of the design criteria. Candidate compounds are identified using a multi-level generate and test CAMD solution algorithm capable of designing molecules having a high level of molecular detail. A post solution step...... using an Integrated Computer Aided System (ICAS) for result analysis and verification is included in the methodology. Keywords: CAMD, separation processes, knowledge base, molecular design, solvent selection, substitution, group contribution, property prediction, ICAS Introduction The use of Computer...... Aided Molecular Design (CAMD) for the identification of compounds having specific physic...

Analytic hierarchy process-based approach for selecting a Pareto-optimal solution of a multi-objective, multi-site supply-chain planning problem

Science.gov (United States)

Ayadi, Omar; Felfel, Houssem; Masmoudi, Faouzi

2017-07-01

The current manufacturing environment has changed from traditional single-plant to multi-site supply chain where multiple plants are serving customer demands. In this article, a tactical multi-objective, multi-period, multi-product, multi-site supply-chain planning problem is proposed. A corresponding optimization model aiming to simultaneously minimize the total cost, maximize product quality and maximize the customer satisfaction demand level is developed. The proposed solution approach yields to a front of Pareto-optimal solutions that represents the trade-offs among the different objectives. Subsequently, the analytic hierarchy process method is applied to select the best Pareto-optimal solution according to the preferences of the decision maker. The robustness of the solutions and the proposed approach are discussed based on a sensitivity analysis and an application to a real case from the textile and apparel industry.

Bayesian Mixed Hidden Markov Models: A Multi-Level Approach to Modeling Categorical Outcomes with Differential Misclassification

Science.gov (United States)

Zhang, Yue; Berhane, Kiros

2014-01-01

Questionnaire-based health status outcomes are often prone to misclassification. When studying the effect of risk factors on such outcomes, ignoring any potential misclassification may lead to biased effect estimates. Analytical challenges posed by these misclassified outcomes are further complicated when simultaneously exploring factors for both the misclassification and health processes in a multi-level setting. To address these challenges, we propose a fully Bayesian Mixed Hidden Markov Model (BMHMM) for handling differential misclassification in categorical outcomes in a multi-level setting. The BMHMM generalizes the traditional Hidden Markov Model (HMM) by introducing random effects into three sets of HMM parameters for joint estimation of the prevalence, transition and misclassification probabilities. This formulation not only allows joint estimation of all three sets of parameters, but also accounts for cluster level heterogeneity based on a multi-level model structure. Using this novel approach, both the true health status prevalence and the transition probabilities between the health states during follow-up are modeled as functions of covariates. The observed, possibly misclassified, health states are related to the true, but unobserved, health states and covariates. Results from simulation studies are presented to validate the estimation procedure, to show the computational efficiency due to the Bayesian approach and also to illustrate the gains from the proposed method compared to existing methods that ignore outcome misclassification and cluster level heterogeneity. We apply the proposed method to examine the risk factors for both asthma transition and misclassification in the Southern California Children's Health Study (CHS). PMID:24254432

Optimized swimmer tracking system based on a novel multi-related-targets approach

Science.gov (United States)

Benarab, D.; Napoléon, T.; Alfalou, A.; Verney, A.; Hellard, P.

2017-02-01

Robust tracking is a crucial step in automatic swimmer evaluation from video sequences. We designed a robust swimmer tracking system using a new multi-related-targets approach. The main idea is to consider the swimmer as a bloc of connected subtargets that advance at the same speed. If one of the subtargets is partially or totally occluded, it can be localized by knowing the position of the others. In this paper, we first introduce the two-dimensional direct linear transformation technique that we used to calibrate the videos. Then, we present the classical tracking approach based on dynamic fusion. Next, we highlight the main contribution of our work, which is the multi-related-targets tracking approach. This approach, the classical head-only approach and the ground truth are then compared, through testing on a database of high-level swimmers in training, national and international competitions (French National Championships, Limoges 2015, and World Championships, Kazan 2015). Tracking percentage and the accuracy of the instantaneous speed are evaluated and the findings show that our new appraoach is significantly more accurate than the classical approach.

Assessment of multi-version NPP I and C systems safety. Metric-based approach, technique and tool

International Nuclear Information System (INIS)

Kharchenko, Vyacheslav; Volkovoy, Andrey; Bakhmach, Eugenii; Siora, Alexander; Duzhyi, Vyacheslav

2011-01-01

The challenges related to problem of assessment of actual diversity level and evaluation of diversity-oriented NPP I and C systems safety are analyzed. There are risks of inaccurate assessment and problems of insufficient decreasing probability of CCFs. CCF probability of safety-critical systems may be essentially decreased due to application of several different types of diversity (multi-diversity). Different diversity types of FPGA-based NPP I and C systems, general approach and stages of diversity and safety assessment as a whole are described. Objectives of the report are: (a) analysis of the challenges caused by use of diversity approach in NPP I and C systems in context of FPGA and other modern technologies application; (b) development of multi-version NPP I and C systems assessment technique and tool based on check-list and metric-oriented approach; (c) case-study of the technique: assessment of multi-version FPGA-based NPP I and C developed by use of Radiy TM Platform. (author)

Mainstreaming Multi-Risk Approaches into Policy

Directory of Open Access Journals (Sweden)

Anna Scolobig

2017-12-01

Full Text Available Multi-risk environments are characterized by domino effects that often amplify the overall risk. Those include chains of hazardous events and increasing vulnerability, among other types of correlations within the risk process. The recently developed methods for multi-hazard and risk assessment integrate interactions between different risks by using harmonized procedures based on common metrics. While the products of these assessments, such as multi-hazard and -risk indexes, maps, cascade scenarios, or warning systems provide innovative and effective information, they also pose specific challenges to policy makers and practitioners due to their novel cross-disciplinary aspects. In this paper we discuss the institutional barriers to the adoption of multi-risk approaches, summarizing the results of the fieldwork conducted in Italy and Guadeloupe and of workshops with disaster risk reduction practitioners from eleven European countries. Results show the need for a clear identification of responsibilities for the implementation of multi-risk approaches, as institutional frameworks for risk reduction remain to this day primarily single-risk centered. Authorities are rarely officially responsible for the management of domino effects between e.g., tsunamis and industrial accidents, earthquake and landslides, floods and electricity network failures. Other barriers for the implementation of multi-risk approaches include the limited measures to reduce exposure at the household level, inadequate financial capacities at the local level and limited public-private partnerships, especially in case of interactions between natural and industrial risks. Adapting the scale of institutions to that of multi-risk environments remains a major challenge to better mainstream multi-risk approaches into policy. To address it, we propose a multi-risk governance framework, which includes the phases of observation, social and institutional context analysis, generation of

MULTI-LEVEL SAMPLING APPROACH FOR CONTINOUS LOSS DETECTION USING ITERATIVE WINDOW AND STATISTICAL MODEL

OpenAIRE

Mohd Fo'ad Rohani; Mohd Aizaini Maarof; Ali Selamat; Houssain Kettani

2010-01-01

This paper proposes a Multi-Level Sampling (MLS) approach for continuous Loss of Self-Similarity (LoSS) detection using iterative window. The method defines LoSS based on Second Order Self-Similarity (SOSS) statistical model. The Optimization Method (OM) is used to estimate self-similarity parameter since it is fast and more accurate in comparison with other estimation methods known in the literature. Probability of LoSS detection is introduced to measure continuous LoSS detection performance...

Multi-Level Wavelet Shannon Entropy-Based Method for Single-Sensor Fault Location

Directory of Open Access Journals (Sweden)

Qiaoning Yang

2015-10-01

Full Text Available In actual application, sensors are prone to failure because of harsh environments, battery drain, and sensor aging. Sensor fault location is an important step for follow-up sensor fault detection. In this paper, two new multi-level wavelet Shannon entropies (multi-level wavelet time Shannon entropy and multi-level wavelet time-energy Shannon entropy are defined. They take full advantage of sensor fault frequency distribution and energy distribution across multi-subband in wavelet domain. Based on the multi-level wavelet Shannon entropy, a method is proposed for single sensor fault location. The method firstly uses a criterion of maximum energy-to-Shannon entropy ratio to select the appropriate wavelet base for signal analysis. Then multi-level wavelet time Shannon entropy and multi-level wavelet time-energy Shannon entropy are used to locate the fault. The method is validated using practical chemical gas concentration data from a gas sensor array. Compared with wavelet time Shannon entropy and wavelet energy Shannon entropy, the experimental results demonstrate that the proposed method can achieve accurate location of a single sensor fault and has good anti-noise ability. The proposed method is feasible and effective for single-sensor fault location.

A multi-level surface rebalancing approach for efficient convergence acceleration of 3D full core multi-group fine grid nodal diffusion iterations

International Nuclear Information System (INIS)

Geemert, René van

2014-01-01

Highlights: • New type of multi-level rebalancing approach for nodal transport. • Generally improved and more mesh-independent convergence behavior. • Importance for intended regime of 3D pin-by-pin core computations. - Abstract: A new multi-level surface rebalancing (MLSR) approach has been developed, aimed at enabling an improved non-linear acceleration of nodal flux iteration convergence in 3D steady-state and transient reactor simulation. This development is meant specifically for anticipating computational needs for solving envisaged multi-group diffusion-like SP N calculations with enhanced mesh resolution (i.e. 3D multi-box up to 3D pin-by-pin grid). For the latter grid refinement regime, the previously available multi-level coarse mesh rebalancing (MLCMR) strategy has been observed to become increasingly inefficient with increasing 3D mesh resolution. Furthermore, for very fine 3D grids that feature a very fine axial mesh as well, non-convergence phenomena have been observed to emerge. In the verifications pursued up to now, these problems have been resolved by the new approach. The novelty arises from taking the interface current balance equations defined over all Cartesian box edges, instead of the nodal volume-integrated process-rate balance equation, as an appropriate restriction basis for setting up multi-level acceleration of fine grid interface current iterations. The new restriction strategy calls for the use of a newly derived set of adjoint spectral equations that are needed for computing a limited set of spectral response vectors per node. This enables a straightforward determination of group-condensed interface current spectral coupling operators that are of crucial relevance in the new rebalancing setup. Another novelty in the approach is a new variational method for computing the neutronic eigenvalue. Within this context, the latter is treated as a control parameter for driving another, newly defined and numerically more fundamental

ML-Space: Hybrid Spatial Gillespie and Particle Simulation of Multi-Level Rule-Based Models in Cell Biology.

Science.gov (United States)

Bittig, Arne T; Uhrmacher, Adelinde M

2017-01-01

Spatio-temporal dynamics of cellular processes can be simulated at different levels of detail, from (deterministic) partial differential equations via the spatial Stochastic Simulation algorithm to tracking Brownian trajectories of individual particles. We present a spatial simulation approach for multi-level rule-based models, which includes dynamically hierarchically nested cellular compartments and entities. Our approach ML-Space combines discrete compartmental dynamics, stochastic spatial approaches in discrete space, and particles moving in continuous space. The rule-based specification language of ML-Space supports concise and compact descriptions of models and to adapt the spatial resolution of models easily.

Mathematical model comparing of the multi-level economics systems

Science.gov (United States)

Brykalov, S. M.; Kryanev, A. V.

2017-12-01

The mathematical model (scheme) of a multi-level comparison of the economic system, characterized by the system of indices, is worked out. In the mathematical model of the multi-level comparison of the economic systems, the indicators of peer review and forecasting of the economic system under consideration can be used. The model can take into account the uncertainty in the estimated values of the parameters or expert estimations. The model uses the multi-criteria approach based on the Pareto solutions.

A variational approach to multi-phase motion of gas, liquid and solid based on the level set method

Science.gov (United States)

Yokoi, Kensuke

2009-07-01

We propose a simple and robust numerical algorithm to deal with multi-phase motion of gas, liquid and solid based on the level set method [S. Osher, J.A. Sethian, Front propagating with curvature-dependent speed: Algorithms based on Hamilton-Jacobi formulation, J. Comput. Phys. 79 (1988) 12; M. Sussman, P. Smereka, S. Osher, A level set approach for capturing solution to incompressible two-phase flow, J. Comput. Phys. 114 (1994) 146; J.A. Sethian, Level Set Methods and Fast Marching Methods, Cambridge University Press, 1999; S. Osher, R. Fedkiw, Level Set Methods and Dynamics Implicit Surface, Applied Mathematical Sciences, vol. 153, Springer, 2003]. In Eulerian framework, to simulate interaction between a moving solid object and an interfacial flow, we need to define at least two functions (level set functions) to distinguish three materials. In such simulations, in general two functions overlap and/or disagree due to numerical errors such as numerical diffusion. In this paper, we resolved the problem using the idea of the active contour model [M. Kass, A. Witkin, D. Terzopoulos, Snakes: active contour models, International Journal of Computer Vision 1 (1988) 321; V. Caselles, R. Kimmel, G. Sapiro, Geodesic active contours, International Journal of Computer Vision 22 (1997) 61; G. Sapiro, Geometric Partial Differential Equations and Image Analysis, Cambridge University Press, 2001; R. Kimmel, Numerical Geometry of Images: Theory, Algorithms, and Applications, Springer-Verlag, 2003] introduced in the field of image processing.

Interteaching: An Evidence-Based Approach to Instruction

Science.gov (United States)

Brown, Thomas Wade; Killingsworth, Kenneth; Alavosius, Mark P.

2014-01-01

This paper describes "interteaching" as an evidence-based method of instruction. Instructors often rely on more traditional approaches, such as lectures, as means to deliver instruction. Despite high usage, these methods are ineffective at achieving desirable academic outcomes. We discuss an innovative approach to delivering instruction…

A multi-objective constraint-based approach for modeling genome-scale microbial ecosystems.

Science.gov (United States)

Budinich, Marko; Bourdon, Jérémie; Larhlimi, Abdelhalim; Eveillard, Damien

2017-01-01

Interplay within microbial communities impacts ecosystems on several scales, and elucidation of the consequent effects is a difficult task in ecology. In particular, the integration of genome-scale data within quantitative models of microbial ecosystems remains elusive. This study advocates the use of constraint-based modeling to build predictive models from recent high-resolution -omics datasets. Following recent studies that have demonstrated the accuracy of constraint-based models (CBMs) for simulating single-strain metabolic networks, we sought to study microbial ecosystems as a combination of single-strain metabolic networks that exchange nutrients. This study presents two multi-objective extensions of CBMs for modeling communities: multi-objective flux balance analysis (MO-FBA) and multi-objective flux variability analysis (MO-FVA). Both methods were applied to a hot spring mat model ecosystem. As a result, multiple trade-offs between nutrients and growth rates, as well as thermodynamically favorable relative abundances at community level, were emphasized. We expect this approach to be used for integrating genomic information in microbial ecosystems. Following models will provide insights about behaviors (including diversity) that take place at the ecosystem scale.

A multi-level approach of evaluating crew resource management training: a laboratory-based study examining communication skills as a function of team congruence.

Science.gov (United States)

Sauer, J; Darioly, A; Mast, M Schmid; Schmid, P C; Bischof, N

2010-11-01

The article proposes a multi-level approach for evaluating communication skills training (CST) as an important element of crew resource management (CRM) training. Within this methodological framework, the present work examined the effectiveness of CST in matching or mismatching team compositions with regard to hierarchical status and competence. There is little experimental research that evaluated the effectiveness of CRM training at multiple levels (i.e. reaction, learning, behaviour) and in teams composed of members of different status and competence. An experiment with a two (CST: with vs. without) by two (competence/hierarchical status: congruent vs. incongruent) design was carried out. A total of 64 participants were trained for 2.5 h on a simulated process control environment, with the experimental group being given 45 min of training on receptiveness and influencing skills. Prior to the 1-h experimental session, participants were assigned to two-person teams. The results showed overall support for the use of such a multi-level approach of training evaluation. Stronger positive effects of CST were found for subjective measures than for objective performance measures. STATEMENT OF RELEVANCE: This work provides some guidance for the use of a multi-level evaluation of CRM training. It also emphasises the need to collect objective performance data for training evaluation in addition to subjective measures with a view to gain a more accurate picture of the benefits of such training approaches.

Multi-atlas and label fusion approach for patient-specific MRI based skull estimation.

Science.gov (United States)

Torrado-Carvajal, Angel; Herraiz, Joaquin L; Hernandez-Tamames, Juan A; San Jose-Estepar, Raul; Eryaman, Yigitcan; Rozenholc, Yves; Adalsteinsson, Elfar; Wald, Lawrence L; Malpica, Norberto

2016-04-01

MRI-based skull segmentation is a useful procedure for many imaging applications. This study describes a methodology for automatic segmentation of the complete skull from a single T1-weighted volume. The skull is estimated using a multi-atlas segmentation approach. Using a whole head computed tomography (CT) scan database, the skull in a new MRI volume is detected by nonrigid image registration of the volume to every CT, and combination of the individual segmentations by label-fusion. We have compared Majority Voting, Simultaneous Truth and Performance Level Estimation (STAPLE), Shape Based Averaging (SBA), and the Selective and Iterative Method for Performance Level Estimation (SIMPLE) algorithms. The pipeline has been evaluated quantitatively using images from the Retrospective Image Registration Evaluation database (reaching an overlap of 72.46 ± 6.99%), a clinical CT-MR dataset (maximum overlap of 78.31 ± 6.97%), and a whole head CT-MRI pair (maximum overlap 78.68%). A qualitative evaluation has also been performed on MRI acquisition of volunteers. It is possible to automatically segment the complete skull from MRI data using a multi-atlas and label fusion approach. This will allow the creation of complete MRI-based tissue models that can be used in electromagnetic dosimetry applications and attenuation correction in PET/MR. © 2015 Wiley Periodicals, Inc.

A multi-objective constraint-based approach for modeling genome-scale microbial ecosystems.

Directory of Open Access Journals (Sweden)

Marko Budinich

Full Text Available Interplay within microbial communities impacts ecosystems on several scales, and elucidation of the consequent effects is a difficult task in ecology. In particular, the integration of genome-scale data within quantitative models of microbial ecosystems remains elusive. This study advocates the use of constraint-based modeling to build predictive models from recent high-resolution -omics datasets. Following recent studies that have demonstrated the accuracy of constraint-based models (CBMs for simulating single-strain metabolic networks, we sought to study microbial ecosystems as a combination of single-strain metabolic networks that exchange nutrients. This study presents two multi-objective extensions of CBMs for modeling communities: multi-objective flux balance analysis (MO-FBA and multi-objective flux variability analysis (MO-FVA. Both methods were applied to a hot spring mat model ecosystem. As a result, multiple trade-offs between nutrients and growth rates, as well as thermodynamically favorable relative abundances at community level, were emphasized. We expect this approach to be used for integrating genomic information in microbial ecosystems. Following models will provide insights about behaviors (including diversity that take place at the ecosystem scale.

Multi-Sensor Building Fire Alarm System with Information Fusion Technology Based on D-S Evidence Theory

Directory of Open Access Journals (Sweden)

Qian Ding

2014-10-01

Full Text Available Multi-sensor and information fusion technology based on Dempster-Shafer evidence theory is applied in the system of a building fire alarm to realize early detecting and alarming. By using a multi-sensor to monitor the parameters of the fire process, such as light, smoke, temperature, gas and moisture, the range of fire monitoring in space and time is expanded compared with a single-sensor system. Then, the D-S evidence theory is applied to fuse the information from the multi-sensor with the specific fire model, and the fire alarm is more accurate and timely. The proposed method can avoid the failure of the monitoring data effectively, deal with the conflicting evidence from the multi-sensor robustly and improve the reliability of fire warning significantly.

Taxonomy of multi-focal nematode image stacks by a CNN based image fusion approach.

Science.gov (United States)

Liu, Min; Wang, Xueping; Zhang, Hongzhong

2018-03-01

In the biomedical field, digital multi-focal images are very important for documentation and communication of specimen data, because the morphological information for a transparent specimen can be captured in form of a stack of high-quality images. Given biomedical image stacks containing multi-focal images, how to efficiently extract effective features from all layers to classify the image stacks is still an open question. We present to use a deep convolutional neural network (CNN) image fusion based multilinear approach for the taxonomy of multi-focal image stacks. A deep CNN based image fusion technique is used to combine relevant information of multi-focal images within a given image stack into a single image, which is more informative and complete than any single image in the given stack. Besides, multi-focal images within a stack are fused along 3 orthogonal directions, and multiple features extracted from the fused images along different directions are combined by canonical correlation analysis (CCA). Because multi-focal image stacks represent the effect of different factors - texture, shape, different instances within the same class and different classes of objects, we embed the deep CNN based image fusion method within a multilinear framework to propose an image fusion based multilinear classifier. The experimental results on nematode multi-focal image stacks demonstrated that the deep CNN image fusion based multilinear classifier can reach a higher classification rate (95.7%) than that by the previous multilinear based approach (88.7%), even we only use the texture feature instead of the combination of texture and shape features as in the previous work. The proposed deep CNN image fusion based multilinear approach shows great potential in building an automated nematode taxonomy system for nematologists. It is effective to classify multi-focal image stacks. Copyright © 2018 Elsevier B.V. All rights reserved.

The Evidence-Based Approach to Adult-Onset Idiopathic Nephrotic Syndrome.

Science.gov (United States)

Canetta, Pietro A A; Radhakrishnan, Jai

2015-01-01

Adult-onset nephrotic syndrome (NS) differs from its pediatric counterpart in several important ways. Most importantly, NS in adults is more etiologically heterogeneous compared to children, and thus treatment approaches rely heavily on the histological diagnosis provided by renal biopsy. The evidence-based approach to treatment of adult NS has been critically examined by the Kidney Disease Improving Global Outcomes (KDIGO) guidelines in glomerulonephritis, published in 2012. Here, we examine the strengths and limits of those guidelines and review recent work that expands the evidence-based approach.

LEADING CHANGES IN ASSESSMENT USING AN EVIDENCE BASED APPROACH

Directory of Open Access Journals (Sweden)

J. O. Macaulay

2015-08-01

Full Text Available Introduction and objectivesIt is has been widely accepted that assessment of learning is a critical component of education and that assessment drives/guides student learning through shaping study habits and student approaches to learning. However, although most academics would agree that assessment is a critical aspect of their roles as teachers it is often an aspect of teaching that is regarded more as an additional task rather than an integral component of the teaching/learning continuum. An additional impediment to high quality assessment is the non-evidence based-approach to the decision making process. The overall aim of this project was to improve the quality of assessment in Biochemistry and Molecular Biology undergraduate education by promoting high quality assessment.Materials and methodsTo do this we developed and trialled an audit tool for mapping assessment practices. The audit tool was designed to gather data on current assessment practices and identify areas of good practice in which assessment aligned with the learning objectives and areas in need of improvement. This evidence base will then be used to drive change in assessment.Results and conclusionsUsing the assessment mapping tool we have mapped the assessment regime in a Biochemistry and Molecular Biology major at Monash University. Criteria used included: assessment type, format, timing, assessors, provision of feedback, level of learning (Bloom’s, approaches taken to planning assessment. We have mapped assessment of content and the systematic development of higher order learning and skills progression throughout the program of study. The data has enabled us to examine the assessment at unit (course level as well as the vertical development across the major. This information is now being used to inform a review of the units and the major.

The evidence-based approach to adult-onset idiopathic nephrotic syndrome

Directory of Open Access Journals (Sweden)

Pietro A. Canetta

2015-09-01

Full Text Available Adult-onset nephrotic syndrome differs from its pediatric counterpart in several important ways. Most importantly, nephrotic syndrome in adults is more etiologically heterogeneous compared to children, and thus treatment approaches rely heavily on the histologic diagnosis provided by renal biopsy. The evidence-based approach to treatment of adult nephrotic syndrome has been critically examined by the Kidney Disease Improving Global Outcomes (KDIGO guidelines in glomerulonephritis, published in 2012. Here, we examine the strengths and limits of those guidelines and review recent work that expands the evidence-based approach.

Multi-floor cascading ferroelectric nanostructures: multiple data writing-based multi-level non-volatile memory devices

Science.gov (United States)

Hyun, Seung; Kwon, Owoong; Lee, Bom-Yi; Seol, Daehee; Park, Beomjin; Lee, Jae Yong; Lee, Ju Hyun; Kim, Yunseok; Kim, Jin Kon

2016-01-01

Multiple data writing-based multi-level non-volatile memory has gained strong attention for next-generation memory devices to quickly accommodate an extremely large number of data bits because it is capable of storing multiple data bits in a single memory cell at once. However, all previously reported devices have failed to store a large number of data bits due to the macroscale cell size and have not allowed fast access to the stored data due to slow single data writing. Here, we introduce a novel three-dimensional multi-floor cascading polymeric ferroelectric nanostructure, successfully operating as an individual cell. In one cell, each floor has its own piezoresponse and the piezoresponse of one floor can be modulated by the bias voltage applied to the other floor, which means simultaneously written data bits in both floors can be identified. This could achieve multi-level memory through a multiple data writing process.Multiple data writing-based multi-level non-volatile memory has gained strong attention for next-generation memory devices to quickly accommodate an extremely large number of data bits because it is capable of storing multiple data bits in a single memory cell at once. However, all previously reported devices have failed to store a large number of data bits due to the macroscale cell size and have not allowed fast access to the stored data due to slow single data writing. Here, we introduce a novel three-dimensional multi-floor cascading polymeric ferroelectric nanostructure, successfully operating as an individual cell. In one cell, each floor has its own piezoresponse and the piezoresponse of one floor can be modulated by the bias voltage applied to the other floor, which means simultaneously written data bits in both floors can be identified. This could achieve multi-level memory through a multiple data writing process. Electronic supplementary information (ESI) available. See DOI: 10.1039/c5nr07377d

Ensuring a proactive, evidence-based, patient safety approach to patient assessment.

Science.gov (United States)

Considine, Julie; Currey, Judy

2015-01-01

To argue that if all nurses were to adopt the primary survey approach (assessment of airway, breathing, circulation and disability) as the first element of patient assessment, they would be more focused on active detection of clinical deterioration rather than passive collection of patient data. Nurses are the professional group that carry the highest level of responsibility for patient assessment, accurate data collection and interpretation. The timely recognition of, and response to deteriorating patients, is dependent on the measurement and interpretation of pertinent physiological data by nurses. Discursive paper. Traditionally taught and commonly used approaches to patient assessment such as 'vital signs' and 'body systems' are not evidence-based nor framed in patient safety. The primary survey approach as the first element in patient assessment has three major advantages: (1) data are collected according to clinical importance; (2) data are collected using the same framework as most organisation's rapid response system activation criteria; and (3) the primary survey acts as a patient safety checklist, thereby decreasing the risk of failure to recognise, and therefore respond to, deteriorating patients. The vital signs and body systems approaches to patient assessment have significant limitations in identifying clinical deterioration. The primary survey approach provides nurses with a consistent, evidence-based and sequenced approach to patient assessment in every clinical setting. All nurses should use a primary survey approach as the first element of patient assessment in every patient encounter as a patient safety strategy. © 2014 John Wiley & Sons Ltd.

Roadmap-Based Level Clearing of Buildings

KAUST Repository

Rodriguez, Samuel

2011-01-01

In this paper we describe a roadmap-based approach for a multi-agent search strategy to clear a building or multi-story environment. This approach utilizes an encoding of the environment in the form of a graph (roadmap) that is used to encode feasible paths through the environment. The roadmap is partitioned into regions, e.g., one per level, and we design region-based search strategies to cover and clear the environment. We can provide certain guarantees within this roadmap-based framework on coverage and the number of agents needed. Our approach can handle complex and realistic environments where many approaches are restricted to simple 2D environments. © 2011 Springer-Verlag.

Microcontroller based multi-channel ultrasonic level monitoring system

International Nuclear Information System (INIS)

Ambastha, K.P.; Chaudhari, Y.V.; Singh, Inder Jeet; Chadda, V.K.

2004-01-01

Microcontroller based Multi-channel Ultrasonic Level Monitoring System developed by Computer Division is based on echo ranging techniques to monitor level. The transmitter directs an ultrasonic burst towards the liquid, which gets reflected from the top of the liquid surface. The time taken for ultrasound to travel from the transmitter to the top of liquid surface is measured and used to calculate the liquid level. The system provides for temperature compensation for accurate measurement as the ultrasound velocity depends on the ambient temperature. It can measure liquid level up to 5 meters. A single monitor can be used to measure level in 6 tanks. PC connectivity has been provided via RS 232 and RS 485 for remote operation and data logging of level. A GUI program developed using LABVIEW package displays level on PC monitor. The program provides for pictorial as well as numerical display for level and temperature in the front panel on the PC monitor. A user can monitor level for any or all tanks from the PC. One unit is installed at CIRUS for measuring level in Acid/ Alkali tanks and one is installed at APSARA for measuring water level in the reactor pool. (author)

Creative teaching an evidence-based approach

CERN Document Server

Sale, Dennis

2015-01-01

This book contains an evidence-based pedagogic guide to enable any motivated teaching/training professional to be able to teach effectively and creatively. It firstly summarises the extensive research field on human psychological functioning relating to learning and how this can be fully utilised in the design and facilitation of quality learning experiences. It then demonstrates what creativity actually 'looks like' in terms of teaching practices, modelling the underpinning processes of creative learning design and how to apply these in lesson planning. The book, having established an evidence-based and pedagogically driven approach to creative learning design, extensively focuses on key challenges facing teaching professionals today. These include utilising information technologies in blended learning formats, differentiating instruction, and developing self-directed learners who can think well. The main purpose of the book is to demystify what it means to teach creatively, explicitly demonstrating the pr...

Evidence-based practice beliefs and behaviors of nurses providing cancer pain management: a mixed-methods approach.

Science.gov (United States)

Eaton, Linda H; Meins, Alexa R; Mitchell, Pamela H; Voss, Joachim; Doorenbos, Ardith Z

2015-03-01

To describe evidence-based practice (EBP) beliefs and behaviors of nurses who provide cancer pain management. Descriptive, cross-sectional with a mixed-methods approach. Two inpatient oncology units in the Pacific Northwest. 40 RNs.
 Data collected by interviews and web-based surveys. EBP beliefs, EBP implementation, evidence-based pain management. Nurses agreed with the positive aspects of EBP and their implementation ability, although implementation level was low. They were satisfied with their pain management practices. Oncology nursing certification was associated with innovativeness, and innovativeness was associated with EBP beliefs. Themes identified were (a) limited definition of EBP, (b) varied evidence-based pain management decision making, (c) limited identification of evidence-based pain management practices, and (d) integration of nonpharmacologic interventions into patient care. Nurses' low level of EBP implementation in the context of pain management was explained by their trust that standards of care and medical orders were evidence-based. Nurses' EBP beliefs and behaviors should be considered when developing strategies for sustaining evidence-based pain management practices. Implementation of the EBP process by nurses may not be realistic in the inpatient setting; therefore, hospital pain management policies need to be evidence-based and reinforced with nurses.

[Evidence-based medicine: an approach without any weakness?].

Science.gov (United States)

Junod, A F

2000-04-06

Evidence-based medicine is a methodological approach giving access to the best information derived from clinical research for an individual patient. It requires the formulation of a question, a strategy to search for the best information, the selection of the latter, its critical appraisal and its application to the patient. The qualities, but also the limitations of this approach are discussed.

A Multi-Model Approach for System Diagnosis

DEFF Research Database (Denmark)

Niemann, Hans Henrik; Poulsen, Niels Kjølstad; Bækgaard, Mikkel Ask Buur

2007-01-01

A multi-model approach for system diagnosis is presented in this paper. The relation with fault diagnosis as well as performance validation is considered. The approach is based on testing a number of pre-described models and find which one is the best. It is based on an active approach......,i.e. an auxiliary input to the system is applied. The multi-model approach is applied on a wind turbine system....

A Character Level Based and Word Level Based Approach for Chinese-Vietnamese Machine Translation

Directory of Open Access Journals (Sweden)

Phuoc Tran

2016-01-01

Full Text Available Chinese and Vietnamese have the same isolated language; that is, the words are not delimited by spaces. In machine translation, word segmentation is often done first when translating from Chinese or Vietnamese into different languages (typically English and vice versa. However, it is a matter for consideration that words may or may not be segmented when translating between two languages in which spaces are not used between words, such as Chinese and Vietnamese. Since Chinese-Vietnamese is a low-resource language pair, the sparse data problem is evident in the translation system of this language pair. Therefore, while translating, whether it should be segmented or not becomes more important. In this paper, we propose a new method for translating Chinese to Vietnamese based on a combination of the advantages of character level and word level translation. In addition, a hybrid approach that combines statistics and rules is used to translate on the word level. And at the character level, a statistical translation is used. The experimental results showed that our method improved the performance of machine translation over that of character or word level translation.

A Character Level Based and Word Level Based Approach for Chinese-Vietnamese Machine Translation.

Science.gov (United States)

Tran, Phuoc; Dinh, Dien; Nguyen, Hien T

2016-01-01

Chinese and Vietnamese have the same isolated language; that is, the words are not delimited by spaces. In machine translation, word segmentation is often done first when translating from Chinese or Vietnamese into different languages (typically English) and vice versa. However, it is a matter for consideration that words may or may not be segmented when translating between two languages in which spaces are not used between words, such as Chinese and Vietnamese. Since Chinese-Vietnamese is a low-resource language pair, the sparse data problem is evident in the translation system of this language pair. Therefore, while translating, whether it should be segmented or not becomes more important. In this paper, we propose a new method for translating Chinese to Vietnamese based on a combination of the advantages of character level and word level translation. In addition, a hybrid approach that combines statistics and rules is used to translate on the word level. And at the character level, a statistical translation is used. The experimental results showed that our method improved the performance of machine translation over that of character or word level translation.

Low level laser therapy and hair regrowth: an evidence-based review.

Science.gov (United States)

Zarei, Mina; Wikramanayake, Tongyu C; Falto-Aizpurua, Leyre; Schachner, Lawrence A; Jimenez, Joaquin J

2016-02-01

Despite the current treatment options for different types of alopecia, there is a need for more effective management options. Recently, low-level laser therapy (LLLT) was evaluated for stimulating hair growth. Here, we reviewed the current evidence on the LLLT effects with an evidence-based approach, focusing more on randomized controlled studies by critically evaluating them. In order to investigate whether in individuals presenting with hair loss (male pattern hair loss (MPHL), female pattern hair loss (FPHL), alopecia areata (AA), and chemotherapy-induced alopecia (CIA)) LLLT is effective for hair regrowth, several databases including PubMed, Google Scholar, Medline, Embase, and Cochrane Database were searched using the following keywords: Alopecia, Hair loss, Hair growth, Low level laser therapy, Low level light therapy, Low energy laser irradiation, and Photobiomodulation. From the searches, 21 relevant studies were summarized in this review including 2 in vitro, 7 animal, and 12 clinical studies. Among clinical studies, only five were randomized controlled trials (RCTs), which evaluated LLLT effect on male and female pattern hair loss. The RCTs were critically appraised using the created checklist according to the Critical Appraisal for Therapy Articles Worksheet created by the Center of Evidence-Based Medicine, Oxford. The results demonstrated that all the performed RCTs have moderate to high quality of evidence. However, only one out of five studies performed intention-to-treat analysis, and only another study reported the method of randomization and subsequent concealment of allocation clearly; all other studies did not include this very important information in their reports. None of these studies reported the treatment effect of factors such as number needed to treat. Based on this review on all the available evidence about effect of LLLT in alopecia, we found that the FDA-cleared LLLT devices are both safe and effective in patients with MPHL and FPHL

Multi-stage decoding for multi-level block modulation codes

Science.gov (United States)

Lin, Shu

1991-01-01

In this paper, we investigate various types of multi-stage decoding for multi-level block modulation codes, in which the decoding of a component code at each stage can be either soft-decision or hard-decision, maximum likelihood or bounded-distance. Error performance of codes is analyzed for a memoryless additive channel based on various types of multi-stage decoding, and upper bounds on the probability of an incorrect decoding are derived. Based on our study and computation results, we find that, if component codes of a multi-level modulation code and types of decoding at various stages are chosen properly, high spectral efficiency and large coding gain can be achieved with reduced decoding complexity. In particular, we find that the difference in performance between the suboptimum multi-stage soft-decision maximum likelihood decoding of a modulation code and the single-stage optimum decoding of the overall code is very small: only a fraction of dB loss in SNR at the probability of an incorrect decoding for a block of 10(exp -6). Multi-stage decoding of multi-level modulation codes really offers a way to achieve the best of three worlds, bandwidth efficiency, coding gain, and decoding complexity.

Material properties identification using ultrasonic waves and laser Doppler vibrometer measurements: a multi-input multi-output approach

International Nuclear Information System (INIS)

Longo, R; Vanlanduit, S; Guillaume, P

2013-01-01

In this paper a multi-input multi-output approach able to determine the material properties of homogeneous materials is presented. To do so, an experimental set-up which combines the use of multi harmonic signals with interleaved frequencies and laser Doppler vibrometer measurements has been developed. A modeling technique, based on transmission and reflection measurements, allowed the simultaneous determination of longitudinal wave velocity, density and thickness of the materials under test with high levels of precision and accuracy. (paper)

Bridging Ayurveda with evidence-based scientific approaches in medicine.

Science.gov (United States)

Patwardhan, Bhushan

2014-01-01

This article reviews contemporary approaches for bridging Ayurveda with evidence-based medicine. In doing so, the author presents a pragmatic assessment of quality, methodology and extent of scientific research in Ayurvedic medicine. The article discusses the meaning of evidence and indicates the need to adopt epistemologically sensitive methods and rigorous experimentation using modern science. The author critically analyzes the status of Ayurvedic medicine based on personal observations, peer interactions and published research. This review article concludes that traditional knowledge systems like Ayurveda and modern scientific evidence-based medicine should be integrated. The author advocates that Ayurvedic researchers should develop strategic collaborations with innovative initiatives like 'Horizon 2020' involving predictive, preventive and personalized medicine (PPPM).

A case for multi-model and multi-approach based event attribution: The 2015 European drought

Science.gov (United States)

Hauser, Mathias; Gudmundsson, Lukas; Orth, René; Jézéquel, Aglaé; Haustein, Karsten; Seneviratne, Sonia Isabelle

2017-04-01

Science on the role of anthropogenic influence on extreme weather events such as heat waves or droughts has evolved rapidly over the past years. The approach of "event attribution" compares the occurrence probability of an event in the present, factual world with the probability of the same event in a hypothetical, counterfactual world without human-induced climate change. Every such analysis necessarily faces multiple methodological choices including, but not limited to: the event definition, climate model configuration, and the design of the counterfactual world. Here, we explore the role of such choices for an attribution analysis of the 2015 European summer drought (Hauser et al., in preparation). While some GCMs suggest that anthropogenic forcing made the 2015 drought more likely, others suggest no impact, or even a decrease in the event probability. These results additionally differ for single GCMs, depending on the reference used for the counterfactual world. Observational results do not suggest a historical tendency towards more drying, but the record may be too short to provide robust assessments because of the large interannual variability of drought occurrence. These results highlight the need for a multi-model and multi-approach framework in event attribution research. This is especially important for events with low signal to noise ratio and high model dependency such as regional droughts. Hauser, M., L. Gudmundsson, R. Orth, A. Jézéquel, K. Haustein, S.I. Seneviratne, in preparation. A case for multi-model and multi-approach based event attribution: The 2015 European drought.

The design of multi-core DSP parallel model based on message passing and multi-level pipeline

Science.gov (United States)

Niu, Jingyu; Hu, Jian; He, Wenjing; Meng, Fanrong; Li, Chuanrong

2017-10-01

Currently, the design of embedded signal processing system is often based on a specific application, but this idea is not conducive to the rapid development of signal processing technology. In this paper, a parallel processing model architecture based on multi-core DSP platform is designed, and it is mainly suitable for the complex algorithms which are composed of different modules. This model combines the ideas of multi-level pipeline parallelism and message passing, and summarizes the advantages of the mainstream model of multi-core DSP (the Master-Slave model and the Data Flow model), so that it has better performance. This paper uses three-dimensional image generation algorithm to validate the efficiency of the proposed model by comparing with the effectiveness of the Master-Slave and the Data Flow model.

Integration of Evidence Base into a Probabilistic Risk Assessment

Science.gov (United States)

Saile, Lyn; Lopez, Vilma; Bickham, Grandin; Kerstman, Eric; FreiredeCarvalho, Mary; Byrne, Vicky; Butler, Douglas; Myers, Jerry; Walton, Marlei

2011-01-01

INTRODUCTION: A probabilistic decision support model such as the Integrated Medical Model (IMM) utilizes an immense amount of input data that necessitates a systematic, integrated approach for data collection, and management. As a result of this approach, IMM is able to forecasts medical events, resource utilization and crew health during space flight. METHODS: Inflight data is the most desirable input for the Integrated Medical Model. Non-attributable inflight data is collected from the Lifetime Surveillance for Astronaut Health study as well as the engineers, flight surgeons, and astronauts themselves. When inflight data is unavailable cohort studies, other models and Bayesian analyses are used, in addition to subject matters experts input on occasion. To determine the quality of evidence of a medical condition, the data source is categorized and assigned a level of evidence from 1-5; the highest level is one. The collected data reside and are managed in a relational SQL database with a web-based interface for data entry and review. The database is also capable of interfacing with outside applications which expands capabilities within the database itself. Via the public interface, customers can access a formatted Clinical Findings Form (CLiFF) that outlines the model input and evidence base for each medical condition. Changes to the database are tracked using a documented Configuration Management process. DISSCUSSION: This strategic approach provides a comprehensive data management plan for IMM. The IMM Database s structure and architecture has proven to support additional usages. As seen by the resources utilization across medical conditions analysis. In addition, the IMM Database s web-based interface provides a user-friendly format for customers to browse and download the clinical information for medical conditions. It is this type of functionality that will provide Exploratory Medicine Capabilities the evidence base for their medical condition list

Evidence-based policymaking is not like evidence-based medicine, so how far should you go to bridge the divide between evidence and policy?

Science.gov (United States)

Cairney, Paul; Oliver, Kathryn

2017-04-26

There is extensive health and public health literature on the 'evidence-policy gap', exploring the frustrating experiences of scientists trying to secure a response to the problems and solutions they raise and identifying the need for better evidence to reduce policymaker uncertainty. We offer a new perspective by using policy theory to propose research with greater impact, identifying the need to use persuasion to reduce ambiguity, and to adapt to multi-level policymaking systems.We identify insights from secondary data, namely systematic reviews, critical analysis and policy theories relevant to evidence-based policymaking. The studies are drawn primarily from countries such as the United States, United Kingdom, Canada, Australia and New Zealand. We combine empirical and normative elements to identify the ways in which scientists can, do and could influence policy.We identify two important dilemmas, for scientists and researchers, that arise from our initial advice. First, effective actors combine evidence with manipulative emotional appeals to influence the policy agenda - should scientists do the same, or would the reputational costs outweigh the policy benefits? Second, when adapting to multi-level policymaking, should scientists prioritise 'evidence-based' policymaking above other factors? The latter includes governance principles such the 'co-production' of policy between local public bodies, interest groups and service users. This process may be based primarily on values and involve actors with no commitment to a hierarchy of evidence.We conclude that successful engagement in 'evidence-based policymaking' requires pragmatism, combining scientific evidence with governance principles, and persuasion to translate complex evidence into simple stories. To maximise the use of scientific evidence in health and public health policy, researchers should recognise the tendency of policymakers to base judgements on their beliefs, and shortcuts based on their emotions

Extended feature-fusion guidelines to improve image-based multi-modal biometrics

CSIR Research Space (South Africa)

Brown, Dane

2016-09-01

Full Text Available The feature-level, unlike the match score-level, lacks multi-modal fusion guidelines. This work demonstrates a practical approach for improved image-based biometric feature-fusion. The approach extracts and combines the face, fingerprint...

Multi-level predictive maintenance for multi-component systems

International Nuclear Information System (INIS)

Nguyen, Kim-Anh; Do, Phuc; Grall, Antoine

2015-01-01

In this paper, a novel predictive maintenance policy with multi-level decision-making is proposed for multi-component system with complex structure. The main idea is to propose a decision-making process considered on two levels: system level and component one. The goal of the decision rules at the system level is to address if preventive maintenance actions are needed regarding the predictive reliability of the system. At component level the decision rules aim at identifying optimally a group of several components to be preventively maintained when preventive maintenance is trigged due to the system level decision. Selecting optimal components is based on a cost-based group improvement factor taking into account the predictive reliability of the components, the economic dependencies as well as the location of the components in the system. Moreover, a cost model is developed to find the optimal maintenance decision variables. A 14-component system is finally introduced to illustrate the use and the performance of the proposed predictive maintenance policy. Different sensitivity analysis are also investigated and discussed. Indeed, the proposed policy provides more flexibility in maintenance decision-making for complex structure systems, hence leading to significant profits in terms of maintenance cost when compared with existing policies. - Highlights: • A predictive maintenance policy for complex structure systems is proposed. • Multi-level decision process based on prognostic results is proposed. • A cost-based group importance measure is introduced for decision-making. • Both positive and negative dependencies between components are investigated. • A cost model and Monte Carlo simulation are developed for optimization process.

A multi-scale, multi-disciplinary approach for assessing the technological, economic and environmental performance of bio-based chemicals.

Science.gov (United States)

Herrgård, Markus; Sukumara, Sumesh; Campodonico, Miguel; Zhuang, Kai

2015-12-01

In recent years, bio-based chemicals have gained interest as a renewable alternative to petrochemicals. However, there is a significant need to assess the technological, biological, economic and environmental feasibility of bio-based chemicals, particularly during the early research phase. Recently, the Multi-scale framework for Sustainable Industrial Chemicals (MuSIC) was introduced to address this issue by integrating modelling approaches at different scales ranging from cellular to ecological scales. This framework can be further extended by incorporating modelling of the petrochemical value chain and the de novo prediction of metabolic pathways connecting existing host metabolism to desirable chemical products. This multi-scale, multi-disciplinary framework for quantitative assessment of bio-based chemicals will play a vital role in supporting engineering, strategy and policy decisions as we progress towards a sustainable chemical industry. © 2015 Authors; published by Portland Press Limited.

Power magnetic devices a multi-objective design approach

CERN Document Server

Sudhoff, Scott D

2014-01-01

Presents a multi-objective design approach to the many power magnetic devices in use today Power Magnetic Devices: A Multi-Objective Design Approach addresses the design of power magnetic devices-including inductors, transformers, electromagnets, and rotating electric machinery-using a structured design approach based on formal single- and multi-objective optimization. The book opens with a discussion of evolutionary-computing-based optimization. Magnetic analysis techniques useful to the design of all the devices considered in the book are then set forth. This material is then used for ind

A mixed-methods study of system-level sustainability of evidence-based practices in 12 large-scale implementation initiatives.

Science.gov (United States)

Scudder, Ashley T; Taber-Thomas, Sarah M; Schaffner, Kristen; Pemberton, Joy R; Hunter, Leah; Herschell, Amy D

2017-12-07

In recent decades, evidence-based practices (EBPs) have been broadly promoted in community behavioural health systems in the United States of America, yet reported EBP penetration rates remain low. Determining how to systematically sustain EBPs in complex, multi-level service systems has important implications for public health. This study examined factors impacting the sustainability of parent-child interaction therapy (PCIT) in large-scale initiatives in order to identify potential predictors of sustainment. A mixed-methods approach to data collection was used. Qualitative interviews and quantitative surveys examining sustainability processes and outcomes were completed by participants from 12 large-scale initiatives. Sustainment strategies fell into nine categories, including infrastructure, training, marketing, integration and building partnerships. Strategies involving integration of PCIT into existing practices and quality monitoring predicted sustainment, while financing also emerged as a key factor. The reported factors and strategies impacting sustainability varied across initiatives; however, integration into existing practices, monitoring quality and financing appear central to high levels of sustainability of PCIT in community-based systems. More detailed examination of the progression of specific activities related to these strategies may aide in identifying priorities to include in strategic planning of future large-scale initiatives. ClinicalTrials.gov ID NCT02543359 ; Protocol number PRO12060529.

Multi-criteria objective based climate change impact assessment for multi-purpose multi-reservoir systems

Science.gov (United States)

Müller, Ruben; Schütze, Niels

2014-05-01

Water resources systems with reservoirs are expected to be sensitive to climate change. Assessment studies that analyze the impact of climate change on the performance of reservoirs can be divided in two groups: (1) Studies that simulate the operation under projected inflows with the current set of operational rules. Due to non adapted operational rules the future performance of these reservoirs can be underestimated and the impact overestimated. (2) Studies that optimize the operational rules for best adaption of the system to the projected conditions before the assessment of the impact. The latter allows for estimating more realistically future performance and adaption strategies based on new operation rules are available if required. Multi-purpose reservoirs serve various, often conflicting functions. If all functions cannot be served simultaneously at a maximum level, an effective compromise between multiple objectives of the reservoir operation has to be provided. Yet under climate change the historically preferenced compromise may no longer be the most suitable compromise in the future. Therefore a multi-objective based climate change impact assessment approach for multi-purpose multi-reservoir systems is proposed in the study. Projected inflows are provided in a first step using a physically based rainfall-runoff model. In a second step, a time series model is applied to generate long-term inflow time series. Finally, the long-term inflow series are used as driving variables for a simulation-based multi-objective optimization of the reservoir system in order to derive optimal operation rules. As a result, the adapted Pareto-optimal set of diverse best compromise solutions can be presented to the decision maker in order to assist him in assessing climate change adaption measures with respect to the future performance of the multi-purpose reservoir system. The approach is tested on a multi-purpose multi-reservoir system in a mountainous catchment in Germany. A

Tuneable resolution as a systems biology approach for multi-scale, multi-compartment computational models.

Science.gov (United States)

Kirschner, Denise E; Hunt, C Anthony; Marino, Simeone; Fallahi-Sichani, Mohammad; Linderman, Jennifer J

2014-01-01

The use of multi-scale mathematical and computational models to study complex biological processes is becoming increasingly productive. Multi-scale models span a range of spatial and/or temporal scales and can encompass multi-compartment (e.g., multi-organ) models. Modeling advances are enabling virtual experiments to explore and answer questions that are problematic to address in the wet-lab. Wet-lab experimental technologies now allow scientists to observe, measure, record, and analyze experiments focusing on different system aspects at a variety of biological scales. We need the technical ability to mirror that same flexibility in virtual experiments using multi-scale models. Here we present a new approach, tuneable resolution, which can begin providing that flexibility. Tuneable resolution involves fine- or coarse-graining existing multi-scale models at the user's discretion, allowing adjustment of the level of resolution specific to a question, an experiment, or a scale of interest. Tuneable resolution expands options for revising and validating mechanistic multi-scale models, can extend the longevity of multi-scale models, and may increase computational efficiency. The tuneable resolution approach can be applied to many model types, including differential equation, agent-based, and hybrid models. We demonstrate our tuneable resolution ideas with examples relevant to infectious disease modeling, illustrating key principles at work. © 2014 The Authors. WIREs Systems Biology and Medicine published by Wiley Periodicals, Inc.

Customized binary and multi-level HfO2-x-based memristors tuned by oxidation conditions.

Science.gov (United States)

He, Weifan; Sun, Huajun; Zhou, Yaxiong; Lu, Ke; Xue, Kanhao; Miao, Xiangshui

2017-08-30

The memristor is a promising candidate for the next generation non-volatile memory, especially based on HfO 2-x , given its compatibility with advanced CMOS technologies. Although various resistive transitions were reported independently, customized binary and multi-level memristors in unified HfO 2-x material have not been studied. Here we report Pt/HfO 2-x /Ti memristors with double memristive modes, forming-free and low operation voltage, which were tuned by oxidation conditions of HfO 2-x films. As O/Hf ratios of HfO 2-x films increase, the forming voltages, SET voltages, and R off /R on windows increase regularly while their resistive transitions undergo from gradually to sharply in I/V sweep. Two memristors with typical resistive transitions were studied to customize binary and multi-level memristive modes, respectively. For binary mode, high-speed switching with 10 3 pulses (10 ns) and retention test at 85 °C (>10 4 s) were achieved. For multi-level mode, the 12-levels stable resistance states were confirmed by ongoing multi-window switching (ranging from 10 ns to 1 μs and completing 10 cycles of each pulse). Our customized binary and multi-level HfO 2-x -based memristors show high-speed switching, multi-level storage and excellent stability, which can be separately applied to logic computing and neuromorphic computing, further suitable for in-memory computing chip when deposition atmosphere may be fine-tuned.

A GIS-based multi-source and multi-box modeling approach (GMSMB) for air pollution assessment--a North American case study.

Science.gov (United States)

Wang, Bao-Zhen; Chen, Zhi

2013-01-01

This article presents a GIS-based multi-source and multi-box modeling approach (GMSMB) to predict the spatial concentration distributions of airborne pollutant on local and regional scales. In this method, an extended multi-box model combined with a multi-source and multi-grid Gaussian model are developed within the GIS framework to examine the contributions from both point- and area-source emissions. By using GIS, a large amount of data including emission sources, air quality monitoring, meteorological data, and spatial location information required for air quality modeling are brought into an integrated modeling environment. It helps more details of spatial variation in source distribution and meteorological condition to be quantitatively analyzed. The developed modeling approach has been examined to predict the spatial concentration distribution of four air pollutants (CO, NO(2), SO(2) and PM(2.5)) for the State of California. The modeling results are compared with the monitoring data. Good agreement is acquired which demonstrated that the developed modeling approach could deliver an effective air pollution assessment on both regional and local scales to support air pollution control and management planning.

A Learning Object Approach To Evidence based learning

OpenAIRE

Zabin Visram; Bruce Elson; Patricia Reynolds

2005-01-01

This paper describes the philosophy, development and framework of the body of elements formulated to provide an approach to evidence-based learning sustained by Learning Objects and web based technology Due to the demands for continuous improvement in the delivery of healthcare and in the continuous endeavour to improve the quality of life, there is a continuous need for practitioner's to update their knowledge by accomplishing accredited courses. The rapid advances in medical science has mea...

OBJECT-ORIENTED CHANGE DETECTION BASED ON MULTI-SCALE APPROACH

Directory of Open Access Journals (Sweden)

Y. Jia

2016-06-01

Full Text Available The change detection of remote sensing images means analysing the change information quantitatively and recognizing the change types of the surface coverage data in different time phases. With the appearance of high resolution remote sensing image, object-oriented change detection method arises at this historic moment. In this paper, we research multi-scale approach for high resolution images, which includes multi-scale segmentation, multi-scale feature selection and multi-scale classification. Experimental results show that this method has a stronger advantage than the traditional single-scale method of high resolution remote sensing image change detection.

Analysis of cell adhesion during early stages of colon cancer based on an extended multi-valued logic approach.

Science.gov (United States)

Guebel, Daniel V; Schmitz, Ulf; Wolkenhauer, Olaf; Vera, Julio

2012-04-01

Cell adhesion in the normal colon is typically associated with differentiated cells, whereas in cancerous colon it is associated with advanced tumors. For advanced tumors growing evidence supports the existence of stem-like cells that have originated from transdifferentiation. Because stem cells can also be transformed in their own niche, at the base of the Lieberkühn's crypts, we conjectured that cell adhesion can also be critical in early tumorigenesis. To assess this hypothesis we built an annotated, multi-valued logic model addressing cell adhesion of normal and tumorigenic stem cells in the human colon. The model accounts for (i) events involving intercellular adhesion structures, (ii) interactions involving cytoskeleton-related structures, (iii) compartmental distribution of α/β/γ/δ-catenins, and (iv) variations in critical cell adhesion regulators (e.g., ILK, FAK, IQGAP, SNAIL, Caveolin). We developed a method that can deal with graded multiple inhibitions, something which is not possible with conventional logical approaches. The model comprises 315 species (including 26 genes), interconnected by 269 reactions. Simulations of the model covered six scenarios, which considered two types of colonic cells (stem vs. differentiated cells), under three conditions (normal, stressed and tumor). Each condition results from the combination of 92 inputs. We compared our multi-valued logic approach with the conventional Boolean approach for one specific example and validated the predictions against published data. Our analysis suggests that stem cells in their niche synthesize high levels of cytoplasmatic E-cadherin and CdhEP(Ser684,686,692), even under normal-mitogenic stimulus or tumorigenic conditions. Under these conditions, E-cadherin would be incorporated into the plasmatic membrane, but only as a non-adhesive CdhE_β-catenin_IQGAP complex. Under stress conditions, however, this complex could be displaced, yielding adhesive Cdh

Emitter signal separation method based on multi-level digital channelization

Science.gov (United States)

Han, Xun; Ping, Yifan; Wang, Sujun; Feng, Ying; Kuang, Yin; Yang, Xinquan

2018-02-01

To solve the problem of emitter separation under complex electromagnetic environment, a signal separation method based on multi-level digital channelization is proposed in this paper. A two-level structure which can divide signal into different channel is designed first, after that, the peaks of different channels are tracked using the track filter and the coincident signals in time domain are separated in time-frequency domain. Finally, the time domain waveforms of different signals are acquired by reverse transformation. The validness of the proposed method is proved by experiment.

Proposal of a Holistic Model to Support Local-Level Evidence-Based Practice

Directory of Open Access Journals (Sweden)

Said Shahtahmasebi

2010-01-01

Full Text Available In response to a central drive for evidence-based practice, there have been many research support schemes, setups, and other practices concentrating on facilitating access to external research, such as the Centre for Evidence Based Healthcare Aotearoa, the Cochrane Collaboration, and the York Centre for Reviews and Dissemination. Very little attention has been paid to supporting internal research in terms of local evidence and internal research capabilities. The whole evidence-based practice movement has alienated internal decision makers and, thus, very little progress has been made in the context of evidence informing local policy formation. Health and social policies are made centrally based on dubious claims and often evidence is sought after implementation. For example, on record, most health care practitioners appear to agree with the causal link between depression and mental illness (sometimes qualified with other social factors with suicide; off the record, even some psychiatrists doubt that such a link is applicable to the population as a whole. Therefore, be it through misplaced loyalty or a lack of support for internal researchers/decision makers, local evidence informing local decision making may have been ignored in favour of external evidence. In this paper, we present a practical holistic model to support local evidence-based decision making. This approach is more relevant in light of a new approach to primary health care of “local knowledge” complementing external evidence. One possible outcome would be to network with other regional programmes around the world to share information and identify “best” practices, such as the “Stop Youth Suicide Campaign”(www.stopyouthsuicide.com.

Waste management project’s alternatives: A risk-based multi-criteria assessment (RBMCA) approach

International Nuclear Information System (INIS)

Karmperis, Athanasios C.; Sotirchos, Anastasios; Aravossis, Konstantinos; Tatsiopoulos, Ilias P.

2012-01-01

Highlights: ► We examine the evaluation of a waste management project’s alternatives. ► We present a novel risk-based multi-criteria assessment (RBMCA) approach. ► In the RBMCA the evaluation criteria are based on the quantitative risk analysis of the project’s alternatives. ► Correlation between the criteria weight values and the decision makers’ risk preferences is examined. ► Preference to the multi-criteria against the one-criterion evaluation process is discussed. - Abstract: This paper examines the evaluation of a waste management project’s alternatives through a quantitative risk analysis. Cost benefit analysis is a widely used method, in which the investments are mainly assessed through the calculation of their evaluation indicators, namely benefit/cost (B/C) ratios, as well as the quantification of their financial, technical, environmental and social risks. Herein, a novel approach in the form of risk-based multi-criteria assessment (RBMCA) is introduced, which can be used by decision makers, in order to select the optimum alternative of a waste management project. Specifically, decision makers use multiple criteria, which are based on the cumulative probability distribution functions of the alternatives’ B/C ratios. The RBMCA system is used for the evaluation of a waste incineration project’s alternatives, where the correlation between the criteria weight values and the decision makers’ risk preferences is analyzed and useful conclusions are discussed.

A Market-Based Approach to Multi-factory Scheduling

Science.gov (United States)

Vytelingum, Perukrishnen; Rogers, Alex; MacBeth, Douglas K.; Dutta, Partha; Stranjak, Armin; Jennings, Nicholas R.

In this paper, we report on the design of a novel market-based approach for decentralised scheduling across multiple factories. Specifically, because of the limitations of scheduling in a centralised manner - which requires a center to have complete and perfect information for optimality and the truthful revelation of potentially commercially private preferences to that center - we advocate an informationally decentralised approach that is both agile and dynamic. In particular, this work adopts a market-based approach for decentralised scheduling by considering the different stakeholders representing different factories as self-interested, profit-motivated economic agents that trade resources for the scheduling of jobs. The overall schedule of these jobs is then an emergent behaviour of the strategic interaction of these trading agents bidding for resources in a market based on limited information and their own preferences. Using a simple (zero-intelligence) bidding strategy, we empirically demonstrate that our market-based approach achieves a lower bound efficiency of 84%. This represents a trade-off between a reasonable level of efficiency (compared to a centralised approach) and the desirable benefits of a decentralised solution.

Enhancing evidence-based diabetes and chronic disease control among local health departments: a multi-phase dissemination study with a stepped-wedge cluster randomized trial component.

Science.gov (United States)

Parks, Renee G; Tabak, Rachel G; Allen, Peg; Baker, Elizabeth A; Stamatakis, Katherine A; Poehler, Allison R; Yan, Yan; Chin, Marshall H; Harris, Jenine K; Dobbins, Maureen; Brownson, Ross C

2017-10-18

The rates of diabetes and prediabetes in the USA are growing, significantly impacting the quality and length of life of those diagnosed and financially burdening society. Premature death and disability can be prevented through implementation of evidence-based programs and policies (EBPPs). Local health departments (LHDs) are uniquely positioned to implement diabetes control EBPPs because of their knowledge of, and focus on, community-level needs, contexts, and resources. There is a significant gap, however, between known diabetes control EBPPs and actual diabetes control activities conducted by LHDs. The purpose of this study is to determine how best to support the use of evidence-based public health for diabetes (and related chronic diseases) control among local-level public health practitioners. This paper describes the methods for a two-phase study with a stepped-wedge cluster randomized trial that will evaluate dissemination strategies to increase the uptake of public health knowledge and EBPPs for diabetes control among LHDs. Phase 1 includes development of measures to assess practitioner views on and organizational supports for evidence-based public health, data collection using a national online survey of LHD chronic disease practitioners, and a needs assessment of factors influencing the uptake of diabetes control EBPPs among LHDs within one state in the USA. Phase 2 involves conducting a stepped-wedge cluster randomized trial to assess effectiveness of dissemination strategies with local-level practitioners at LHDs to enhance capacity and organizational support for evidence-based diabetes prevention and control. Twelve LHDs will be selected and randomly assigned to one of the three groups that cross over from usual practice to receive the intervention (dissemination) strategies at 8-month intervals; the intervention duration for groups ranges from 8 to 24 months. Intervention (dissemination) strategies may include multi-day in-person workshops, electronic

A Learning Object Approach To Evidence based learning

Directory of Open Access Journals (Sweden)

Zabin Visram

2005-06-01

Full Text Available This paper describes the philosophy, development and framework of the body of elements formulated to provide an approach to evidence-based learning sustained by Learning Objects and web based technology Due to the demands for continuous improvement in the delivery of healthcare and in the continuous endeavour to improve the quality of life, there is a continuous need for practitioner's to update their knowledge by accomplishing accredited courses. The rapid advances in medical science has meant increasingly, there is a desperate need to adopt wireless schemes, whereby bespoke courses can be developed to help practitioners keep up with expanding knowledge base. Evidently, without current best evidence, practice risks becoming rapidly out of date, to the detriment of the patient. There is a need to provide a tactical, operational and effective environment, which allows professional to update their education, and complete specialised training, just-in-time, in their own time and location. Following this demand in the marketplace the information engineering group, in combination with several medical and dental schools, set out to develop and design a conceptual framework which form the basis of pioneering research, which at last, enables practitioner's to adopt a philosophy of life long learning. The body and structure of this framework is subsumed under the term Object oriented approach to Evidence Based learning, Just-in-time, via Internet sustained by Reusable Learning Objects (The OEBJIRLO Progression. The technical pillars which permit this concept of life long learning are pivoted by the foundations of object oriented technology, Learning objects, Just-in-time education, Data Mining, intelligent Agent technology, Flash interconnectivity and remote wireless technology, which allow practitioners to update their professional skills, complete specialised training which leads to accredited qualifications. This paper sets out to develop and

A stochastic multicriteria model for evidence-based decision making in drug benefit-risk analysis.

Science.gov (United States)

Tervonen, Tommi; van Valkenhoef, Gert; Buskens, Erik; Hillege, Hans L; Postmus, Douwe

2011-05-30

Drug benefit-risk (BR) analysis is based on firm clinical evidence regarding various safety and efficacy outcomes. In this paper, we propose a new and more formal approach for constructing a supporting multi-criteria model that fully takes into account the evidence on efficacy and adverse drug reactions. Our approach is based on the stochastic multi-criteria acceptability analysis methodology, which allows us to compute the typical value judgments that support a decision, to quantify decision uncertainty, and to compute a comprehensive BR profile. We construct a multi-criteria model for the therapeutic group of second-generation antidepressants. We assess fluoxetine and venlafaxine together with placebo according to incidence of treatment response and three common adverse drug reactions by using data from a published study. Our model shows that there are clear trade-offs among the treatment alternatives. Copyright © 2011 John Wiley & Sons, Ltd.

Reliability-oriented multi-objective optimal decision-making approach for uncertainty-based watershed load reduction

International Nuclear Information System (INIS)

Dong, Feifei; Liu, Yong; Su, Han; Zou, Rui; Guo, Huaicheng

2015-01-01

Water quality management and load reduction are subject to inherent uncertainties in watershed systems and competing decision objectives. Therefore, optimal decision-making modeling in watershed load reduction is suffering due to the following challenges: (a) it is difficult to obtain absolutely “optimal” solutions, and (b) decision schemes may be vulnerable to failure. The probability that solutions are feasible under uncertainties is defined as reliability. A reliability-oriented multi-objective (ROMO) decision-making approach was proposed in this study for optimal decision making with stochastic parameters and multiple decision reliability objectives. Lake Dianchi, one of the three most eutrophic lakes in China, was examined as a case study for optimal watershed nutrient load reduction to restore lake water quality. This study aimed to maximize reliability levels from considerations of cost and load reductions. The Pareto solutions of the ROMO optimization model were generated with the multi-objective evolutionary algorithm, demonstrating schemes representing different biases towards reliability. The Pareto fronts of six maximum allowable emission (MAE) scenarios were obtained, which indicated that decisions may be unreliable under unpractical load reduction requirements. A decision scheme identification process was conducted using the back propagation neural network (BPNN) method to provide a shortcut for identifying schemes at specific reliability levels for decision makers. The model results indicated that the ROMO approach can offer decision makers great insights into reliability tradeoffs and can thus help them to avoid ineffective decisions. - Highlights: • Reliability-oriented multi-objective (ROMO) optimal decision approach was proposed. • The approach can avoid specifying reliability levels prior to optimization modeling. • Multiple reliability objectives can be systematically balanced using Pareto fronts. • Neural network model was used to

Reliability-oriented multi-objective optimal decision-making approach for uncertainty-based watershed load reduction

Energy Technology Data Exchange (ETDEWEB)

Dong, Feifei [College of Environmental Science and Engineering, Key Laboratory of Water and Sediment Sciences (MOE), Peking University, Beijing 100871 (China); Liu, Yong, E-mail: yongliu@pku.edu.cn [College of Environmental Science and Engineering, Key Laboratory of Water and Sediment Sciences (MOE), Peking University, Beijing 100871 (China); Institute of Water Sciences, Peking University, Beijing 100871 (China); Su, Han [College of Environmental Science and Engineering, Key Laboratory of Water and Sediment Sciences (MOE), Peking University, Beijing 100871 (China); Zou, Rui [Tetra Tech, Inc., 10306 Eaton Place, Ste 340, Fairfax, VA 22030 (United States); Yunnan Key Laboratory of Pollution Process and Management of Plateau Lake-Watershed, Kunming 650034 (China); Guo, Huaicheng [College of Environmental Science and Engineering, Key Laboratory of Water and Sediment Sciences (MOE), Peking University, Beijing 100871 (China)

2015-05-15

Water quality management and load reduction are subject to inherent uncertainties in watershed systems and competing decision objectives. Therefore, optimal decision-making modeling in watershed load reduction is suffering due to the following challenges: (a) it is difficult to obtain absolutely “optimal” solutions, and (b) decision schemes may be vulnerable to failure. The probability that solutions are feasible under uncertainties is defined as reliability. A reliability-oriented multi-objective (ROMO) decision-making approach was proposed in this study for optimal decision making with stochastic parameters and multiple decision reliability objectives. Lake Dianchi, one of the three most eutrophic lakes in China, was examined as a case study for optimal watershed nutrient load reduction to restore lake water quality. This study aimed to maximize reliability levels from considerations of cost and load reductions. The Pareto solutions of the ROMO optimization model were generated with the multi-objective evolutionary algorithm, demonstrating schemes representing different biases towards reliability. The Pareto fronts of six maximum allowable emission (MAE) scenarios were obtained, which indicated that decisions may be unreliable under unpractical load reduction requirements. A decision scheme identification process was conducted using the back propagation neural network (BPNN) method to provide a shortcut for identifying schemes at specific reliability levels for decision makers. The model results indicated that the ROMO approach can offer decision makers great insights into reliability tradeoffs and can thus help them to avoid ineffective decisions. - Highlights: • Reliability-oriented multi-objective (ROMO) optimal decision approach was proposed. • The approach can avoid specifying reliability levels prior to optimization modeling. • Multiple reliability objectives can be systematically balanced using Pareto fronts. • Neural network model was used to

Toward Simulating Realistic Pursuit-Evasion Using a Roadmap-Based Approach

KAUST Repository

Rodriguez, Samuel

2010-01-01

In this work, we describe an approach for modeling and simulating group behaviors for pursuit-evasion that uses a graph-based representation of the environment and integrates multi-agent simulation with roadmap-based path planning. We demonstrate the utility of this approach for a variety of scenarios including pursuit-evasion on terrains, in multi-level buildings, and in crowds. © 2010 Springer-Verlag Berlin Heidelberg.

Multi-person and multi-attribute design evaluations using evidential reasoning based on subjective safety and cost analyses

International Nuclear Information System (INIS)

Wang, J.; Yang, J.B.; Sen, P.

1996-01-01

This paper presents an approach for ranking proposed design options based on subjective safety and cost analyses. Hierarchical system safety analysis is carried out using fuzzy sets and evidential reasoning. This involves safety modelling by fuzzy sets at the bottom level of a hierarchy and safety synthesis by evidential reasoning at higher levels. Fuzzy sets are also used to model the cost incurred for each design option. An evidential reasoning approach is then employed to synthesise the estimates of safety and cost, which are made by multiple designers. The developed approach is capable of dealing with problems of multiple designers, multiple attributes and multiple design options to select the best design. Finally, a practical engineering example is presented to demonstrate the proposed multi-person and multi-attribute design selection approach

Multi-criteria clinical decision support: A primer on the use of multiple criteria decision making methods to promote evidence-based, patient-centered healthcare.

Science.gov (United States)

Dolan, James G

2010-01-01

Current models of healthcare quality recommend that patient management decisions be evidence-based and patient-centered. Evidence-based decisions require a thorough understanding of current information regarding the natural history of disease and the anticipated outcomes of different management options. Patient-centered decisions incorporate patient preferences, values, and unique personal circumstances into the decision making process and actively involve both patients along with health care providers as much as possible. Fundamentally, therefore, evidence-based, patient-centered decisions are multi-dimensional and typically involve multiple decision makers.Advances in the decision sciences have led to the development of a number of multiple criteria decision making methods. These multi-criteria methods are designed to help people make better choices when faced with complex decisions involving several dimensions. They are especially helpful when there is a need to combine "hard data" with subjective preferences, to make trade-offs between desired outcomes, and to involve multiple decision makers. Evidence-based, patient-centered clinical decision making has all of these characteristics. This close match suggests that clinical decision support systems based on multi-criteria decision making techniques have the potential to enable patients and providers to carry out the tasks required to implement evidence-based, patient-centered care effectively and efficiently in clinical settings.The goal of this paper is to give readers a general introduction to the range of multi-criteria methods available and show how they could be used to support clinical decision-making. Methods discussed include the balance sheet, the even swap method, ordinal ranking methods, direct weighting methods, multi-attribute decision analysis, and the analytic hierarchy process (AHP).

Usability Methods for Ensuring Health Information Technology Safety: Evidence-Based Approaches. Contribution of the IMIA Working Group Health Informatics for Patient Safety.

Science.gov (United States)

Borycki, E; Kushniruk, A; Nohr, C; Takeda, H; Kuwata, S; Carvalho, C; Bainbridge, M; Kannry, J

2013-01-01

Issues related to lack of system usability and potential safety hazards continue to be reported in the health information technology (HIT) literature. Usability engineering methods are increasingly used to ensure improved system usability and they are also beginning to be applied more widely for ensuring the safety of HIT applications. These methods are being used in the design and implementation of many HIT systems. In this paper we describe evidence-based approaches to applying usability engineering methods. A multi-phased approach to ensuring system usability and safety in healthcare is described. Usability inspection methods are first described including the development of evidence-based safety heuristics for HIT. Laboratory-based usability testing is then conducted under artificial conditions to test if a system has any base level usability problems that need to be corrected. Usability problems that are detected are corrected and then a new phase is initiated where the system is tested under more realistic conditions using clinical simulations. This phase may involve testing the system with simulated patients. Finally, an additional phase may be conducted, involving a naturalistic study of system use under real-world clinical conditions. The methods described have been employed in the analysis of the usability and safety of a wide range of HIT applications, including electronic health record systems, decision support systems and consumer health applications. It has been found that at least usability inspection and usability testing should be applied prior to the widespread release of HIT. However, wherever possible, additional layers of testing involving clinical simulations and a naturalistic evaluation will likely detect usability and safety issues that may not otherwise be detected prior to widespread system release. The framework presented in the paper can be applied in order to develop more usable and safer HIT, based on multiple layers of evidence.

Evidence-based management of otitis media: a 5S model approach.

Science.gov (United States)

Wasson, J D; Yung, M W

2015-02-01

The 5S model proposes five hierarchical levels (systems, summaries, synopses, syntheses and studies) of pre-appraised evidence to guide evidence-based practice. This review aimed to identify and summarise pre-appraised evidence at the highest available 5S level for the management of different subsets of otitis media: acute otitis media, otitis media with effusion, chronic suppurative otitis media and cholesteatoma in both adults and children. Data sources were pre-appraised evidence resources. Evidence freely available from sources at the highest available level of the 5S model were summarised for this review. System level evidence exists for acute otitis media and otitis media with effusion. Summary level evidence exists for recurrent acute otitis media and medical management of chronic suppurative otitis media. There is an absence of randomised controlled trials to prove the efficacy of surgical management of chronic suppurative otitis media and cholesteatoma. Until randomised controlled trial data are generated, consensus publications on the surgical management of chronic suppurative otitis media and cholesteatoma should be used to guide best practice.

Evidence-based radiology: why and how?

International Nuclear Information System (INIS)

Sardanelli, Francesco; Di Leo, Giovanni; Hunink, Myriam G.; Gilbert, Fiona J.; Krestin, Gabriel P.

2010-01-01

To provide an overview of evidence-based medicine (EBM) in relation to radiology and to define a policy for adoption of this principle in the European radiological community. Starting from Sackett's definition of EBM we illustrate the top-down and bottom-up approaches to EBM as well as EBM's limitations. Delayed diffusion and peculiar features of evidence-based radiology (EBR) are defined with emphasis on the need to shift from the demonstration of the increasing ability to see more and better, to the demonstration of a significant change in treatment planning or, at best, of a significant gain in patient outcome. The ''as low as reasonably achievable'' (ALARA) principle is thought as a dimension of EBR while EBR is proposed as part of the core curriculum of radiology residency. Moreover, we describe the process of health technology assessment in radiology with reference to the six-level scale of hierarchy of studies on diagnostic tests, the main sources of bias in studies on diagnostic performance, and levels of evidence and degrees of recommendations according to the Centre for Evidence-Based Medicine (Oxford, UK) as well as the approach proposed by the GRADE working group. Problems and opportunities offered by evidence-based guidelines in radiology are considered. Finally, we suggest nine points to be actioned by the ESR in order to promote EBR. Radiology will benefit greatly from the improvement in practice that will result from adopting this more rigorous approach to all aspects of our work. (orig.)

An Evidence-Based Approach to Detection by DASI-ELISA and RT-PCR in Dormant Period

Directory of Open Access Journals (Sweden)

Antonio Olmos

2008-01-01

Full Text Available An evidence-based approach, such as those developed in clinical and veterinary medicine, was applied to the detection of Plum pox virus (PPV during the dormant period. A standardized methodology was used for the calculation of parameters of the operational capacity of DASI-ELISA and RT-PCR in wintertime. These methods are routinely handled to test the sanitary status of plants in national or international trading and in those cases concerning export-import of plant materials. Diagnosis often has to be performed during the dormant period, when plant material is commercialized. Some guidelines to interpret diagnostic results of wintertime are provided in an attempt to minimize risks associated with the methods and over-reliance on the binary outcome of a single assay. In order to evaluate if a complementary test increased the confidence of PPV diagnosis when discordant results between DASI-ELISA and RT-PCR are obtained, NASBA-FH also was included. Likelihood ratios of each method were estimated based on the sensitivity and specificity obtained in wintertime. Subsequently, a Bayesian approach was performed to calculate post-test probability of PPV infection in spring. Results of evidence-based approach show that different PPV prevalences require different screening tests. Thus, at very low PPV prevalence levels DASI-ELISA should be used as the election method, whilst at the highest PPV prevalence levels RT-PCR should be performed. NASBA-FH could be used at medium prevalences to clarify discordances between DASI-ELISA and RT-PCR.

Single-step reinitialization and extending algorithms for level-set based multi-phase flow simulations

Science.gov (United States)

Fu, Lin; Hu, Xiangyu Y.; Adams, Nikolaus A.

2017-12-01

We propose efficient single-step formulations for reinitialization and extending algorithms, which are critical components of level-set based interface-tracking methods. The level-set field is reinitialized with a single-step (non iterative) "forward tracing" algorithm. A minimum set of cells is defined that describes the interface, and reinitialization employs only data from these cells. Fluid states are extrapolated or extended across the interface by a single-step "backward tracing" algorithm. Both algorithms, which are motivated by analogy to ray-tracing, avoid multiple block-boundary data exchanges that are inevitable for iterative reinitialization and extending approaches within a parallel-computing environment. The single-step algorithms are combined with a multi-resolution conservative sharp-interface method and validated by a wide range of benchmark test cases. We demonstrate that the proposed reinitialization method achieves second-order accuracy in conserving the volume of each phase. The interface location is invariant to reapplication of the single-step reinitialization. Generally, we observe smaller absolute errors than for standard iterative reinitialization on the same grid. The computational efficiency is higher than for the standard and typical high-order iterative reinitialization methods. We observe a 2- to 6-times efficiency improvement over the standard method for serial execution. The proposed single-step extending algorithm, which is commonly employed for assigning data to ghost cells with ghost-fluid or conservative interface interaction methods, shows about 10-times efficiency improvement over the standard method while maintaining same accuracy. Despite their simplicity, the proposed algorithms offer an efficient and robust alternative to iterative reinitialization and extending methods for level-set based multi-phase simulations.

Multi-level decision making models, methods and applications

CERN Document Server

Zhang, Guangquan; Gao, Ya

2015-01-01

This monograph presents new developments in multi-level decision-making theory, technique and method in both modeling and solution issues. It especially presents how a decision support system can support managers in reaching a solution to a multi-level decision problem in practice. This monograph combines decision theories, methods, algorithms and applications effectively. It discusses in detail the models and solution algorithms of each issue of bi-level and tri-level decision-making, such as multi-leaders, multi-followers, multi-objectives, rule-set-based, and fuzzy parameters. Potential readers include organizational managers and practicing professionals, who can use the methods and software provided to solve their real decision problems; PhD students and researchers in the areas of bi-level and multi-level decision-making and decision support systems; students at an advanced undergraduate, master’s level in information systems, business administration, or the application of computer science.  

A Novel Approach to Selecting Contractor in Agent-based Multi-sensor Battlefield Reconnaissance Simulation

Directory of Open Access Journals (Sweden)

Xiong Li

2012-11-01

Full Text Available This paper presents a novel approach towards showing how contractor in agent-based simulation for complex warfare system such as multi-sensor battlefield reconnaissance system can be selected in Contract Net Protocol (CNP with high efficiency. We first analyze agent and agent-based simulation framework, CNP and collaborators, and present agents interaction chain used to actualize CNP and establish agents trust network. We then obtain contractor's importance weight and dynamic trust by presenting fuzzy similarity-based algorithm and trust modifying algorithm, thus we propose contractor selecting approach based on maximum dynamic integrative trust. We validate the feasibility and capability of this approach by implementing simulation, analyzing compared results and checking the model.

Agent-based model with multi-level herding for complex financial systems

Science.gov (United States)

Chen, Jun-Jie; Tan, Lei; Zheng, Bo

2015-02-01

In complex financial systems, the sector structure and volatility clustering are respectively important features of the spatial and temporal correlations. However, the microscopic generation mechanism of the sector structure is not yet understood. Especially, how to produce these two features in one model remains challenging. We introduce a novel interaction mechanism, i.e., the multi-level herding, in constructing an agent-based model to investigate the sector structure combined with volatility clustering. According to the previous market performance, agents trade in groups, and their herding behavior comprises the herding at stock, sector and market levels. Further, we propose methods to determine the key model parameters from historical market data, rather than from statistical fitting of the results. From the simulation, we obtain the sector structure and volatility clustering, as well as the eigenvalue distribution of the cross-correlation matrix, for the New York and Hong Kong stock exchanges. These properties are in agreement with the empirical ones. Our results quantitatively reveal that the multi-level herding is the microscopic generation mechanism of the sector structure, and provide new insight into the spatio-temporal interactions in financial systems at the microscopic level.

Mapping and navigating transitions - The multi-level perspective compared with arenas of development

DEFF Research Database (Denmark)

Jørgensen, Ulrik

2012-01-01

actors to navigate. The second concern builds on the observation that actors engage at all levels in society including visions, institutions, and innovations. The third concern addresses the role of academic theories and advice regarding governance of transition processes in which they function......Transitions of socio-technical systems imply the reconfiguration of institutions and politics making made evident the need to understand and intervene in existing patterns of growth and socio-technical practices in more sustainable directions. In recent decades, theories of transitions have been...... introduced, which include the multi-level approach indicating ways to govern transitions through understanding the interactions between niches, regimes and landscapes. An alternative approach is suggested, which takes its outset in arenas of development and increased awareness of actors and their way...

A Two-Stage Multi-Agent Based Assessment Approach to Enhance Students' Learning Motivation through Negotiated Skills Assessment

Science.gov (United States)

Chadli, Abdelhafid; Bendella, Fatima; Tranvouez, Erwan

2015-01-01

In this paper we present an Agent-based evaluation approach in a context of Multi-agent simulation learning systems. Our evaluation model is based on a two stage assessment approach: (1) a Distributed skill evaluation combining agents and fuzzy sets theory; and (2) a Negotiation based evaluation of students' performance during a training…

Toward realistic pursuit-evasion using a roadmap-based approach

KAUST Repository

Rodriguez, Samuel

2011-05-01

In this work, we describe an approach for modeling and simulating group behaviors for pursuit-evasion that uses a graph-based representation of the environment and integrates multi-agent simulation with roadmap-based path planning. Our approach can be applied to more realistic scenarios than are typically studied in most previous work, including agents moving in 3D environments such as terrains, multi-story buildings, and dynamic environments. We also support more realistic three-dimensional visibility computations that allow evading agents to hide in crowds or behind hills. We demonstrate the utility of this approach on mobile robots and in simulation for a variety of scenarios including pursuit-evasion and tag on terrains, in multi-level buildings, and in crowds. © 2011 IEEE.

A diagnosis method for physical systems using a multi-modeling approach

International Nuclear Information System (INIS)

Thetiot, R.

2000-01-01

In this thesis we propose a method for diagnosis problem solving. This method is based on a multi-modeling approach describing both normal and abnormal behavior of a system. This modeling approach allows to represent a system at different abstraction levels (behavioral, functional and teleological. Fundamental knowledge is described according to a bond-graph representation. We show that bond-graph representation can be exploited in order to generate (completely or partially) the functional models. The different models of the multi-modeling approach allows to define the functional state of a system at different abstraction levels. We exploit this property to exonerate sub-systems for which the expected behavior is observed. The behavioral and functional descriptions of the remaining sub-systems are exploited hierarchically in a two steps process. In a first step, the abnormal behaviors explaining some observations are identified. In a second step, the remaining unexplained observations are used to generate conflict sets and thus the consistency based diagnoses. The modeling method and the diagnosis process have been applied to a Reactor Coolant Pump Sets. This application illustrates the concepts described in this thesis and shows its potentialities. (authors)

An approach for setting evidence-based and stakeholder-informed research priorities in low- and middle-income countries.

Science.gov (United States)

Rehfuess, Eva A; Durão, Solange; Kyamanywa, Patrick; Meerpohl, Joerg J; Young, Taryn; Rohwer, Anke

2016-04-01

To derive evidence-based and stakeholder-informed research priorities for implementation in African settings, the international research consortium Collaboration for Evidence-Based Healthcare and Public Health in Africa (CEBHA+) developed and applied a pragmatic approach. First, an online survey and face-to-face consultation between CEBHA+ partners and policy-makers generated priority research areas. Second, evidence maps for these priority research areas identified gaps and related priority research questions. Finally, study protocols were developed for inclusion within a grant proposal. Policy and practice representatives were involved throughout the process. Tuberculosis, diabetes, hypertension and road traffic injuries were selected as priority research areas. Evidence maps covered screening and models of care for diabetes and hypertension, population-level prevention of diabetes and hypertension and their risk factors, and prevention and management of road traffic injuries. Analysis of these maps yielded three priority research questions on hypertension and diabetes and one on road traffic injuries. The four resulting study protocols employ a broad range of primary and secondary research methods; a fifth promotes an integrated methodological approach across all research activities. The CEBHA+ approach, in particular evidence mapping, helped to formulate research questions and study protocols that would be owned by African partners, fill gaps in the evidence base, address policy and practice needs and be feasible given the existing research infrastructure and expertise. The consortium believes that the continuous involvement of decision-makers throughout the research process is an important means of ensuring that studies are relevant to the African context and that findings are rapidly implemented.

Evidence-based management - healthcare manager viewpoints.

Science.gov (United States)

Janati, Ali; Hasanpoor, Edris; Hajebrahimi, Sakineh; Sadeghi-Bazargani, Homayoun

2018-06-11

Purpose Hospital manager decisions can have a significant impact on service effectiveness and hospital success, so using an evidence-based approach can improve hospital management. The purpose of this paper is to identify evidence-based management (EBMgt) components and challenges. Consequently, the authors provide an improving evidence-based decision-making framework. Design/methodology/approach A total of 45 semi-structured interviews were conducted in 2016. The authors also established three focus group discussions with health service managers. Data analysis followed deductive qualitative analysis guidelines. Findings Four basic themes emerged from the interviews, including EBMgt evidence sources (including sub-themes: scientific and research evidence, facts and information, political-social development plans, managers' professional expertise and ethical-moral evidence); predictors (sub-themes: stakeholder values and expectations, functional behavior, knowledge, key competencies and skill, evidence sources, evidence levels, uses and benefits and government programs); EBMgt barriers (sub-themes: managers' personal characteristics, decision-making environment, training and research system and organizational issues); and evidence-based hospital management processes (sub-themes: asking, acquiring, appraising, aggregating, applying and assessing). Originality/value Findings suggest that most participants have positive EBMgt attitudes. A full evidence-based hospital manager is a person who uses all evidence sources in a six-step decision-making process. EBMgt frameworks are a good tool to manage healthcare organizations. The authors found factors affecting hospital EBMgt and identified six evidence sources that healthcare managers can use in evidence-based decision-making processes.

Multi-level molecular modelling for plasma medicine

International Nuclear Information System (INIS)

Bogaerts, Annemie; Khosravian, Narjes; Van der Paal, Jonas; Verlackt, Christof C W; Yusupov, Maksudbek; Kamaraj, Balu; Neyts, Erik C

2016-01-01

Modelling at the molecular or atomic scale can be very useful for obtaining a better insight in plasma medicine. This paper gives an overview of different atomic/molecular scale modelling approaches that can be used to study the direct interaction of plasma species with biomolecules or the consequences of these interactions for the biomolecules on a somewhat longer time-scale. These approaches include density functional theory (DFT), density functional based tight binding (DFTB), classical reactive and non-reactive molecular dynamics (MD) and united-atom or coarse-grained MD, as well as hybrid quantum mechanics/molecular mechanics (QM/MM) methods. Specific examples will be given for three important types of biomolecules, present in human cells, i.e. proteins, DNA and phospholipids found in the cell membrane. The results show that each of these modelling approaches has its specific strengths and limitations, and is particularly useful for certain applications. A multi-level approach is therefore most suitable for obtaining a global picture of the plasma–biomolecule interactions. (paper)

Evidence-based approach for continuous improvement of occupational health.

Science.gov (United States)

Manzoli, Lamberto; Sotgiu, Giovanni; Magnavita, Nicola; Durando, Paolo

2015-01-01

It was recognized early on that an Evidence-Based Medicine (EBM) approach could be applied to Public Health (PH), including the area of Occupational Health (OH). The aim of Evidence-Based Occupational Health (EBOH) is to ensure safety, health, and well-being in the workplace. Currently, high-quality research is necessary in order to provide arguments and scientific evidence upon which effective, efficient, and sustainable preventive measures and policies are to be developed in the workplace in Western countries. Occupational physicians need to integrate available scientific evidence and existing recommendations with a framework of national employment laws and regulations. This paper addresses the state of the art of scientific evidence available in the field (i.e., efficacy of interventions, usefulness of education and training of workers, and need of a multidisciplinary strategy integrated within the national PH programs) and the main critical issues for their implementation. Promoting good health is a fundamental part of the smart, inclusive growth objectives of Europe 2020 - Europe's growth strategy: keeping people healthy and active for longer has a positive impact on productivity and competitiveness. It appears clear that health quality and safety in the workplace play a key role for smart, sustainable, and inclusive growth in Western countries.

A Multi-organisational Approach to Service Delivery

Science.gov (United States)

Purchase, Valerie; Mills, John; Parry, Glenn

Who is involved in delivering a service? There has been growing recognition in a wide variety of contexts that service is increasingly being delivered by multi-rather than single-organisational entities. Such recognition is evident not only in our experience but in a number of areas of literature including strategy development, core competence analysis, operations and supply chain management, and is reflected in and further facilitated by ICT developments. Customers have always been involved in some degree in the process of value delivery and such involvement is increasing to include complex co-creation of value. Such interactions are challenging when they involve individual customers, however, this becomes ever more challenging when the 'customer' is another organisation or when there are multiple 'customers'. Within this chapter we will consider some of the key drivers for a multi-organisational approach to service delivery; examine the ways in which the parties involved in service co-creation have expanded to include multiple service providers and customers; and finally, identify some of the challenges created by a multi-organisational approach to service delivery.

Multi-Objective Particle Swarm Optimization Approach for Cost-Based Feature Selection in Classification.

Science.gov (United States)

Zhang, Yong; Gong, Dun-Wei; Cheng, Jian

2017-01-01

Feature selection is an important data-preprocessing technique in classification problems such as bioinformatics and signal processing. Generally, there are some situations where a user is interested in not only maximizing the classification performance but also minimizing the cost that may be associated with features. This kind of problem is called cost-based feature selection. However, most existing feature selection approaches treat this task as a single-objective optimization problem. This paper presents the first study of multi-objective particle swarm optimization (PSO) for cost-based feature selection problems. The task of this paper is to generate a Pareto front of nondominated solutions, that is, feature subsets, to meet different requirements of decision-makers in real-world applications. In order to enhance the search capability of the proposed algorithm, a probability-based encoding technology and an effective hybrid operator, together with the ideas of the crowding distance, the external archive, and the Pareto domination relationship, are applied to PSO. The proposed PSO-based multi-objective feature selection algorithm is compared with several multi-objective feature selection algorithms on five benchmark datasets. Experimental results show that the proposed algorithm can automatically evolve a set of nondominated solutions, and it is a highly competitive feature selection method for solving cost-based feature selection problems.

Predicting the functions and specificity of triterpenoid synthases: a mechanism-based multi-intermediate docking approach.

Directory of Open Access Journals (Sweden)

Bo-Xue Tian

2014-10-01

Full Text Available Terpenoid synthases construct the carbon skeletons of tens of thousands of natural products. To predict functions and specificity of triterpenoid synthases, a mechanism-based, multi-intermediate docking approach is proposed. In addition to enzyme function prediction, other potential applications of the current approach, such as enzyme mechanistic studies and enzyme redesign by mutagenesis, are discussed.

Paper Prototyping: The Surplus Merit of a Multi-Method Approach

Directory of Open Access Journals (Sweden)

Stephanie Bettina Linek

2015-07-01

Full Text Available This article describes a multi-method approach for usability testing. The approach combines paper prototyping and think-aloud with two supplemental methods: advanced scribbling and a handicraft task. The method of advanced scribbling instructs the participants to use different colors for marking important, unnecessary and confusing elements in a paper prototype. In the handicraft task the participants have to tinker a paper prototype of their wish version. Both methods deliver additional information on the needs and expectations of the potential users and provide helpful indicators for clarifying complex or contradictory findings. The multi-method approach and its surplus benefit are illustrated by a pilot study on the redesign of the homepage of a library 2.0. The findings provide positive evidence for the applicability of the advanced scribbling and the handicraft task as well as for the surplus merit of the multi-method approach. The article closes with a discussion and outlook. URN: http://nbn-resolving.de/urn:nbn:de:0114-fqs150379

Evidence-based approach to HIV/AIDS policy and research prioritization in the Islamic Republic of Iran.

Science.gov (United States)

Feizzadeh, A; Nedjat, S; Asghari, S; Keshtkar, A; Heshmat, R; Setayesh, H; Majdzadeh, R

2010-03-01

In formulating the second national strategic plan for prevention of HIV/AIDS in the Islamic Republic of Iran a more evidence-based approach was needed. This paper reports on a systematic review of the local evidence about the determinants of HIV/AIDS transmission in 3 categories: poor knowledge and negative attitudes about HIV transmission; injection drug use; and sexual promiscuity. Of 93 reports reviewed, 53 met the inclusion criteria. Information about the prevalence and magnitude of effect for the 3 risk determinants at the national and regional level was scarce. Heterogeneity between studies, even in the same sub-population, was significant. An improved research base and better sharing of information are needed within countries of the Eastern Mediterranean Region.

Extended multi-configuration quasi-degenerate perturbation theory: the new approach to multi-state multi-reference perturbation theory.

Science.gov (United States)

Granovsky, Alexander A

2011-06-07

The distinctive desirable features, both mathematically and physically meaningful, for all partially contracted multi-state multi-reference perturbation theories (MS-MR-PT) are explicitly formulated. The original approach to MS-MR-PT theory, called extended multi-configuration quasi-degenerate perturbation theory (XMCQDPT), having most, if not all, of the desirable properties is introduced. The new method is applied at the second order of perturbation theory (XMCQDPT2) to the 1(1)A(')-2(1)A(') conical intersection in allene molecule, the avoided crossing in LiF molecule, and the 1(1)A(1) to 2(1)A(1) electronic transition in cis-1,3-butadiene. The new theory has several advantages compared to those of well-established approaches, such as second order multi-configuration quasi-degenerate perturbation theory and multi-state-second order complete active space perturbation theory. The analysis of the prevalent approaches to the MS-MR-PT theory performed within the framework of the XMCQDPT theory unveils the origin of their common inherent problems. We describe the efficient implementation strategy that makes XMCQDPT2 an especially useful general-purpose tool in the high-level modeling of small to large molecular systems. © 2011 American Institute of Physics

Probabilistic Approaches for Multi-Hazard Risk Assessment of Structures and Systems

Science.gov (United States)

Kwag, Shinyoung

Performance assessment of structures, systems, and components for multi-hazard scenarios has received significant attention in recent years. However, the concept of multi-hazard analysis is quite broad in nature and the focus of existing literature varies across a wide range of problems. In some cases, such studies focus on hazards that either occur simultaneously or are closely correlated with each other. For example, seismically induced flooding or seismically induced fires. In other cases, multi-hazard studies relate to hazards that are not dependent or correlated but have strong likelihood of occurrence at different times during the lifetime of a structure. The current approaches for risk assessment need enhancement to account for multi-hazard risks. It must be able to account for uncertainty propagation in a systems-level analysis, consider correlation among events or failure modes, and allow integration of newly available information from continually evolving simulation models, experimental observations, and field measurements. This dissertation presents a detailed study that proposes enhancements by incorporating Bayesian networks and Bayesian updating within a performance-based probabilistic framework. The performance-based framework allows propagation of risk as well as uncertainties in the risk estimates within a systems analysis. Unlike conventional risk assessment techniques such as a fault-tree analysis, a Bayesian network can account for statistical dependencies and correlations among events/hazards. The proposed approach is extended to develop a risk-informed framework for quantitative validation and verification of high fidelity system-level simulation tools. Validation of such simulations can be quite formidable within the context of a multi-hazard risk assessment in nuclear power plants. The efficiency of this approach lies in identification of critical events, components, and systems that contribute to the overall risk. Validation of any event or

Progress and challenges in the development and qualification of multi-level multi-physics coupled methodologies for reactor analysis

International Nuclear Information System (INIS)

Ivanov, K.; Avramova, M.

2007-01-01

Current trends in nuclear power generation and regulation as well as the design of next generation reactor concepts along with the continuing computer technology progress stimulate the development, qualification and application of multi-physics multi-scale coupled code systems. The efforts have been focused on extending the analysis capabilities by coupling models, which simulate different phenomena or system components, as well as on refining the scale and level of detail of the coupling. This paper reviews the progress made in this area and outlines the remaining challenges. The discussion is illustrated with examples based on neutronics/thermohydraulics coupling in the reactor core modeling. In both fields recent advances and developments are towards more physics-based high-fidelity simulations, which require implementation of improved and flexible coupling methodologies. First, the progresses in coupling of different physics codes along with the advances in multi-level techniques for coupled code simulations are discussed. Second, the issues related to the consistent qualification of coupled multi-physics and multi-scale code systems for design and safety evaluation are presented. The increased importance of uncertainty and sensitivity analysis are discussed along with approaches to propagate the uncertainty quantification between the codes. The incoming OECD LWR Uncertainty Analysis in Modeling (UAM) benchmark is the first international activity to address this issue and it is described in the paper. Finally, the remaining challenges with multi-physics coupling are outlined. (authors)

Progress and challenges in the development and qualification of multi-level multi-physics coupled methodologies for reactor analysis

Energy Technology Data Exchange (ETDEWEB)

Ivanov, K.; Avramova, M. [Pennsylvania State Univ., University Park, PA (United States)

2007-07-01

Current trends in nuclear power generation and regulation as well as the design of next generation reactor concepts along with the continuing computer technology progress stimulate the development, qualification and application of multi-physics multi-scale coupled code systems. The efforts have been focused on extending the analysis capabilities by coupling models, which simulate different phenomena or system components, as well as on refining the scale and level of detail of the coupling. This paper reviews the progress made in this area and outlines the remaining challenges. The discussion is illustrated with examples based on neutronics/thermohydraulics coupling in the reactor core modeling. In both fields recent advances and developments are towards more physics-based high-fidelity simulations, which require implementation of improved and flexible coupling methodologies. First, the progresses in coupling of different physics codes along with the advances in multi-level techniques for coupled code simulations are discussed. Second, the issues related to the consistent qualification of coupled multi-physics and multi-scale code systems for design and safety evaluation are presented. The increased importance of uncertainty and sensitivity analysis are discussed along with approaches to propagate the uncertainty quantification between the codes. The incoming OECD LWR Uncertainty Analysis in Modeling (UAM) benchmark is the first international activity to address this issue and it is described in the paper. Finally, the remaining challenges with multi-physics coupling are outlined. (authors)

A multi-level approach to understanding the impact of cyber crime on the financial sector

OpenAIRE

Monica Lagazio; Nazneen Sherif; Mike Cushman

2014-01-01

This paper puts forward a multi-level model, based on system dynamics methodology, to understand the impact of cyber crime on the financial sector. Consistent with recent findings, our results show that strong dynamic relationships, amongst tangible and intangible factors, affect cyber crime cost and occur at different levels of society and value network. Specifically, shifts in financial companies’ strategic priorities, having the protection of customer trust and loyalty as a key objective, ...

The ethical approach to evidence-based medicine

African Journals Online (AJOL)

research findings as the basis for clinical decisions”.2 The practice ... paper will explore the role of evidence-based medicine in ethical practice of health care professionals. ... based medicine is used for “evidence-based purchasing”, it will.

Building the Evidence Base for Population-Level Interventions: Barriers and Opportunities

Science.gov (United States)

Lifsey, Sarah; Cash, Amanda; Anthony, Jodi; Mathis, Sheryl; Silva, Sandra

2015-01-01

Population-level interventions focused on policy, systems, and environmental change strategies are increasingly being used to affect and improve the health of populations. At the same time, emphasis on implementing evidence-based public health practices and programming is increasing, particularly at the federal level. Valuing strategies in the…

Profile of Students’ Mental Model Change on Law Concepts Archimedes as Impact of Multi-Representation Approach

Science.gov (United States)

Taher, M.; Hamidah, I.; Suwarma, I. R.

2017-09-01

This paper outlined the results of an experimental study on the effects of multi-representation approach in learning Archimedes Law on students’ mental model improvement. The multi-representation techniques implemented in the study were verbal, pictorial, mathematical, and graphical representations. Students’ mental model was classified into three levels, i.e. scientific, synthetic, and initial levels, based on the students’ level of understanding. The present study employed the pre-experimental methodology, using one group pretest-posttest design. The subject of the study was 32 eleventh grade students in a Public Senior High School in Riau Province. The research instrument included model mental test on hydrostatic pressure concept, in the form of essay test judged by experts. The findings showed that there was positive change in students’ mental model, indicating that multi-representation approach was effective to improve students’ mental model.

MetricForensics: A Multi-Level Approach for Mining Volatile Graphs

Energy Technology Data Exchange (ETDEWEB)

Henderson, Keith [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Eliassi-Rad, Tina [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Faloutsos, Christos [Carnegie Mellon Univ., Pittsburgh, PA (United States); Akoglu, Leman [Carnegie Mellon Univ., Pittsburgh, PA (United States); Li, Lei [Carnegie Mellon Univ., Pittsburgh, PA (United States); Maruhashi, Koji [Fujitsu Laboratories Ltd., Kanagawa (Japan); Prakash, B. Aditya [Carnegie Mellon Univ., Pittsburgh, PA (United States); Tong, H [Carnegie Mellon Univ., Pittsburgh, PA (United States)

2010-02-08

Advances in data collection and storage capacity have made it increasingly possible to collect highly volatile graph data for analysis. Existing graph analysis techniques are not appropriate for such data, especially in cases where streaming or near-real-time results are required. An example that has drawn significant research interest is the cyber-security domain, where internet communication traces are collected and real-time discovery of events, behaviors, patterns and anomalies is desired. We propose MetricForensics, a scalable framework for analysis of volatile graphs. MetricForensics combines a multi-level “drill down" approach, a collection of user-selected graph metrics and a collection of analysis techniques. At each successive level, more sophisticated metrics are computed and the graph is viewed at a finer temporal resolution. In this way, MetricForensics scales to highly volatile graphs by only allocating resources for computationally expensive analysis when an interesting event is discovered at a coarser resolution first. We test MetricForensics on three real-world graphs: an enterprise IP trace, a trace of legitimate and malicious network traffic from a research institution, and the MIT Reality Mining proximity sensor data. Our largest graph has »3M vertices and »32M edges, spanning 4:5 days. The results demonstrate the scalability and capability of MetricForensics in analyzing volatile graphs; and highlight four novel phenomena in such graphs: elbows, broken correlations, prolonged spikes, and strange stars.

Modeling Multi-Level Systems

CERN Document Server

Iordache, Octavian

2011-01-01

This book is devoted to modeling of multi-level complex systems, a challenging domain for engineers, researchers and entrepreneurs, confronted with the transition from learning and adaptability to evolvability and autonomy for technologies, devices and problem solving methods. Chapter 1 introduces the multi-scale and multi-level systems and highlights their presence in different domains of science and technology. Methodologies as, random systems, non-Archimedean analysis, category theory and specific techniques as model categorification and integrative closure, are presented in chapter 2. Chapters 3 and 4 describe polystochastic models, PSM, and their developments. Categorical formulation of integrative closure offers the general PSM framework which serves as a flexible guideline for a large variety of multi-level modeling problems. Focusing on chemical engineering, pharmaceutical and environmental case studies, the chapters 5 to 8 analyze mixing, turbulent dispersion and entropy production for multi-scale sy...

Detecting bots using multi-level traffic analysis

DEFF Research Database (Denmark)

Stevanovic, Matija; Pedersen, Jens Myrup

2016-01-01

introduces a novel multi-level botnet detection approach that performs network traffic analysis of three protocols widely considered as the main carriers of botnet Command and Control (C&C) and attack traffic, i.e. TCP, UDP and DNS. The proposed method relies on supervised machine learning for identifying...

Systematic implementation of evidence-based practice in a clinical nursing setting: a participatory action research project.

Science.gov (United States)

Friesen-Storms, Jolanda H H M; Moser, Albine; van der Loo, Sandra; Beurskens, Anna J H M; Bours, Gerrie J J W

2015-01-01

To describe the process of implementing evidence-based practice in a clinical nursing setting. Evidence-based practice has become a major issue in nursing, it is insufficiently integrated into daily practice and its implementation is complex. Participatory action research. The main participants were nurses working in a lung unit of a rural hospital. A multi-method process of data collection was used during the observing, reflecting, planning and acting phases. Data were continuously gathered during a 24-month period from 2010 to 2012, and analysed using an interpretive constant comparative approach. Patients were consulted to incorporate their perspective. A best-practice mode of working was prevalent on the ward. The main barriers to the implementation of evidence-based practice were that nurses had little knowledge of evidence-based practice and a rather negative attitude towards it, and that their English reading proficiency was poor. The main facilitators were that nurses wanted to deliver high-quality care and were enthusiastic and open to innovation. Implementation strategies included a tailored interactive outreach training and the development and implementation of an evidence-based discharge protocol. The academic model of evidence-based practice was adapted. Nurses worked according to the evidence-based practice discharge protocol but barely recorded their activities. Nurses favourably evaluated the participatory action research process. Action research provides an opportunity to empower nurses and to tailor evidence-based practice to the practice context. Applying and implementing evidence-based practice is difficult for front-line nurses with limited evidence-based practice competencies. Adaptation of the academic model of evidence-based practice to a more pragmatic approach seems necessary to introduce evidence-based practice into clinical practice. The use of scientific evidence can be facilitated by using pre-appraised evidence. For clinical practice

Contributions of dopamine-related genes and environmental factors to highly sensitive personality: a multi-step neuronal system-level approach.

Directory of Open Access Journals (Sweden)

Chunhui Chen

Full Text Available Traditional behavioral genetic studies (e.g., twin, adoption studies have shown that human personality has moderate to high heritability, but recent molecular behavioral genetic studies have failed to identify quantitative trait loci (QTL with consistent effects. The current study adopted a multi-step approach (ANOVA followed by multiple regression and permutation to assess the cumulative effects of multiple QTLs. Using a system-level (dopamine system genetic approach, we investigated a personality trait deeply rooted in the nervous system (the Highly Sensitive Personality, HSP. 480 healthy Chinese college students were given the HSP scale and genotyped for 98 representative polymorphisms in all major dopamine neurotransmitter genes. In addition, two environment factors (stressful life events and parental warmth that have been implicated for their contributions to personality development were included to investigate their relative contributions as compared to genetic factors. In Step 1, using ANOVA, we identified 10 polymorphisms that made statistically significant contributions to HSP. In Step 2, these polymorphism's main effects and interactions were assessed using multiple regression. This model accounted for 15% of the variance of HSP (p<0.001. Recent stressful life events accounted for an additional 2% of the variance. Finally, permutation analyses ascertained the probability of obtaining these findings by chance to be very low, p ranging from 0.001 to 0.006. Dividing these loci by the subsystems of dopamine synthesis, degradation/transport, receptor and modulation, we found that the modulation and receptor subsystems made the most significant contribution to HSP. The results of this study demonstrate the utility of a multi-step neuronal system-level approach in assessing genetic contributions to individual differences in human behavior. It can potentially bridge the gap between the high heritability estimates based on traditional

An Example-Based Multi-Atlas Approach to Automatic Labeling of White Matter Tracts.

Science.gov (United States)

Yoo, Sang Wook; Guevara, Pamela; Jeong, Yong; Yoo, Kwangsun; Shin, Joseph S; Mangin, Jean-Francois; Seong, Joon-Kyung

2015-01-01

We present an example-based multi-atlas approach for classifying white matter (WM) tracts into anatomic bundles. Our approach exploits expert-provided example data to automatically classify the WM tracts of a subject. Multiple atlases are constructed to model the example data from multiple subjects in order to reflect the individual variability of bundle shapes and trajectories over subjects. For each example subject, an atlas is maintained to allow the example data of a subject to be added or deleted flexibly. A voting scheme is proposed to facilitate the multi-atlas exploitation of example data. For conceptual simplicity, we adopt the same metrics in both example data construction and WM tract labeling. Due to the huge number of WM tracts in a subject, it is time-consuming to label each WM tract individually. Thus, the WM tracts are grouped according to their shape similarity, and WM tracts within each group are labeled simultaneously. To further enhance the computational efficiency, we implemented our approach on the graphics processing unit (GPU). Through nested cross-validation we demonstrated that our approach yielded high classification performance. The average sensitivities for bundles in the left and right hemispheres were 89.5% and 91.0%, respectively, and their average false discovery rates were 14.9% and 14.2%, respectively.

Reported Systems Changes and Sustainability Perceptions of Three State Departments of Health Implementing Multi-Faceted Evidence-Based Fall Prevention Efforts

Directory of Open Access Journals (Sweden)

Matthew Lee Smith

2017-06-01

Full Text Available Although the concepts of systems change and sustainability are not new, little is known about the factors associated with systems change sustaining multi-state, multi-level fall prevention efforts. This exploratory study focuses on three State Departments of Health (DOH that were awarded 5-year funding from the Centers for Disease Control and Prevention to simultaneously implement four separate yet related evidence-based fall prevention initiatives at the clinical, community, and policy level. The purpose of this study was to examine changes in partnerships and collaborative activities that occurred to accomplish project goals (examining changes in the context of “before funding” and “after funding was received”. Additionally, this study explored changes in State DOH perceptions about action related to sustainability indicators in the context of “during funding” and “after funding ends.” Findings from this study document the partnership and activity changes necessary to achieve defined fall prevention goals after funding is received, and that the importance of sustainability indicator documentation is seen as relevant during funding, but less so after the funding ends. Findings from this study have practice and research implications that can inform future funded efforts in terms of sector and stakeholder engagement necessary for initiating, implementing, and sustaining community- and clinical-based fall prevention interventions.

The construct validity of the Spanish version of the ABQ using a multi-trait/multi-method approach

Directory of Open Access Journals (Sweden)

Thomas D. Raedeke

2013-10-01

Full Text Available This study was designed to evaluate construct validity evidence associated with the Spanish version of the Athlete Burnout Questionnaire (ABQ using a multi-trait/multi-method (MTMM approach. The ABQ was administered to a sample of 302 Spanish athletes, along with two other questionnaires including the Maslach Burnout Inventory-General Survey (MBI-GS and the Depression, Anxiety, Stress Scale (DASS-21, which respectively measure burnout in organizational settings and indicators of ill being including depression, anxiety and stress. A structural equation modeling approach to a MTMM analysis was used. Results revealed by comparative analysis of four models that the Spanish version of ABQ has convergent and internal discriminant validity evident by high correlations between matching burnout subscales across two measures and lower correlations between non-matching dimensions. In addition, the burnout measures exhibited external discriminant validity as the correlations between burnout dimensions were higher than those seen between conceptually related, but unique, constructs.

PMHT Approach for Multi-Target Multi-Sensor Sonar Tracking in Clutter.

Science.gov (United States)

Li, Xiaohua; Li, Yaan; Yu, Jing; Chen, Xiao; Dai, Miao

2015-11-06

Multi-sensor sonar tracking has many advantages, such as the potential to reduce the overall measurement uncertainty and the possibility to hide the receiver. However, the use of multi-target multi-sensor sonar tracking is challenging because of the complexity of the underwater environment, especially the low target detection probability and extremely large number of false alarms caused by reverberation. In this work, to solve the problem of multi-target multi-sensor sonar tracking in the presence of clutter, a novel probabilistic multi-hypothesis tracker (PMHT) approach based on the extended Kalman filter (EKF) and unscented Kalman filter (UKF) is proposed. The PMHT can efficiently handle the unknown measurements-to-targets and measurements-to-transmitters data association ambiguity. The EKF and UKF are used to deal with the high degree of nonlinearity in the measurement model. The simulation results show that the proposed algorithm can improve the target tracking performance in a cluttered environment greatly, and its computational load is low.

Estimation of winter wheat canopy nitrogen density at different growth stages based on Multi-LUT approach

Science.gov (United States)

Li, Zhenhai; Li, Na; Li, Zhenhong; Wang, Jianwen; Liu, Chang

2017-10-01

Rapid real-time monitoring of wheat nitrogen (N) status is crucial for precision N management during wheat growth. In this study, Multi Lookup Table (Multi-LUT) approach based on the N-PROSAIL model parameters setting at different growth stages was constructed to estimating canopy N density (CND) in winter wheat. The results showed that the estimated CND was in line with with measured CND, with the determination coefficient (R2) and the corresponding root mean square error (RMSE) values of 0.80 and 1.16 g m-2, respectively. Time-consuming of one sample estimation was only 6 ms under the test machine with CPU configuration of Intel(R) Core(TM) i5-2430 @2.40GHz quad-core. These results confirmed the potential of using Multi-LUT approach for CND retrieval in winter wheat at different growth stages and under variables climatic conditions.

Bayesian Multi-Energy Computed Tomography reconstruction approaches based on decomposition models

International Nuclear Information System (INIS)

Cai, Caifang

2013-01-01

Multi-Energy Computed Tomography (MECT) makes it possible to get multiple fractions of basis materials without segmentation. In medical application, one is the soft-tissue equivalent water fraction and the other is the hard-matter equivalent bone fraction. Practical MECT measurements are usually obtained with polychromatic X-ray beams. Existing reconstruction approaches based on linear forward models without counting the beam poly-chromaticity fail to estimate the correct decomposition fractions and result in Beam-Hardening Artifacts (BHA). The existing BHA correction approaches either need to refer to calibration measurements or suffer from the noise amplification caused by the negative-log pre-processing and the water and bone separation problem. To overcome these problems, statistical DECT reconstruction approaches based on non-linear forward models counting the beam poly-chromaticity show great potential for giving accurate fraction images.This work proposes a full-spectral Bayesian reconstruction approach which allows the reconstruction of high quality fraction images from ordinary polychromatic measurements. This approach is based on a Gaussian noise model with unknown variance assigned directly to the projections without taking negative-log. Referring to Bayesian inferences, the decomposition fractions and observation variance are estimated by using the joint Maximum A Posteriori (MAP) estimation method. Subject to an adaptive prior model assigned to the variance, the joint estimation problem is then simplified into a single estimation problem. It transforms the joint MAP estimation problem into a minimization problem with a non-quadratic cost function. To solve it, the use of a monotone Conjugate Gradient (CG) algorithm with suboptimal descent steps is proposed.The performances of the proposed approach are analyzed with both simulated and experimental data. The results show that the proposed Bayesian approach is robust to noise and materials. It is also

An integrated multi-sensor fusion-based deep feature learning approach for rotating machinery diagnosis

Science.gov (United States)

Liu, Jie; Hu, Youmin; Wang, Yan; Wu, Bo; Fan, Jikai; Hu, Zhongxu

2018-05-01

The diagnosis of complicated fault severity problems in rotating machinery systems is an important issue that affects the productivity and quality of manufacturing processes and industrial applications. However, it usually suffers from several deficiencies. (1) A considerable degree of prior knowledge and expertise is required to not only extract and select specific features from raw sensor signals, and but also choose a suitable fusion for sensor information. (2) Traditional artificial neural networks with shallow architectures are usually adopted and they have a limited ability to learn the complex and variable operating conditions. In multi-sensor-based diagnosis applications in particular, massive high-dimensional and high-volume raw sensor signals need to be processed. In this paper, an integrated multi-sensor fusion-based deep feature learning (IMSFDFL) approach is developed to identify the fault severity in rotating machinery processes. First, traditional statistics and energy spectrum features are extracted from multiple sensors with multiple channels and combined. Then, a fused feature vector is constructed from all of the acquisition channels. Further, deep feature learning with stacked auto-encoders is used to obtain the deep features. Finally, the traditional softmax model is applied to identify the fault severity. The effectiveness of the proposed IMSFDFL approach is primarily verified by a one-stage gearbox experimental platform that uses several accelerometers under different operating conditions. This approach can identify fault severity more effectively than the traditional approaches.

A practical approach for active camera coordination based on a fusion-driven multi-agent system

Science.gov (United States)

Bustamante, Alvaro Luis; Molina, José M.; Patricio, Miguel A.

2014-04-01

In this paper, we propose a multi-agent system architecture to manage spatially distributed active (or pan-tilt-zoom) cameras. Traditional video surveillance algorithms are of no use for active cameras, and we have to look at different approaches. Such multi-sensor surveillance systems have to be designed to solve two related problems: data fusion and coordinated sensor-task management. Generally, architectures proposed for the coordinated operation of multiple cameras are based on the centralisation of management decisions at the fusion centre. However, the existence of intelligent sensors capable of decision making brings with it the possibility of conceiving alternative decentralised architectures. This problem is approached by means of a MAS, integrating data fusion as an integral part of the architecture for distributed coordination purposes. This paper presents the MAS architecture and system agents.

A novel multi-scale adaptive sampling-based approach for energy saving in leak detection for WSN-based water pipelines

Science.gov (United States)

Saqib, Najam us; Faizan Mysorewala, Muhammad; Cheded, Lahouari

2017-12-01

In this paper, we propose a novel monitoring strategy for a wireless sensor networks (WSNs)-based water pipeline network. Our strategy uses a multi-pronged approach to reduce energy consumption based on the use of two types of vibration sensors and pressure sensors, all having different energy levels, and a hierarchical adaptive sampling mechanism to determine the sampling frequency. The sampling rate of the sensors is adjusted according to the bandwidth of the vibration signal being monitored by using a wavelet-based adaptive thresholding scheme that calculates the new sampling frequency for the following cycle. In this multimodal sensing scheme, the duty-cycling approach is used for all sensors to reduce the sampling instances, such that the high-energy, high-precision (HE-HP) vibration sensors have low duty cycles, and the low-energy, low-precision (LE-LP) vibration sensors have high duty cycles. The low duty-cycling (HE-HP) vibration sensor adjusts the sampling frequency of the high duty-cycling (LE-LP) vibration sensor. The simulated test bed considered here consists of a water pipeline network which uses pressure and vibration sensors, with the latter having different energy consumptions and precision levels, at various locations in the network. This is all the more useful for energy conservation for extended monitoring. It is shown that by using the novel features of our proposed scheme, a significant reduction in energy consumption is achieved and the leak is effectively detected by the sensor node that is closest to it. Finally, both the total energy consumed by monitoring as well as the time to detect the leak by a WSN node are computed, and show the superiority of our proposed hierarchical adaptive sampling algorithm over a non-adaptive sampling approach.

Development of a Multi-Disciplinary Intervention for the Treatment of Childhood Obesity Based on Cognitive Behavioral Therapy

Science.gov (United States)

Bathrellou, Eirini; Yannakoulia, Mary; Papanikolaou, Katerina; Pehlivanidis, Artemios; Pervanidou, Panagiota; Kanaka-Gantenbein, Christina; Tsiantis, John; Chrousos, George P.; Sidossis, Labros S.

2010-01-01

Along the lines of the evidence-based recommendations, we developed a multi-disciplinary intervention for overweight children 7- to 12-years-old, primarily aiming at helping children to adopt healthier eating habits and a physically active lifestyle. The program combined nutrition intervention, based on a non-dieting approach, with physical…

Roadmap-Based Level Clearing of Buildings

KAUST Repository

Rodriguez, Samuel; Amato, Nancy M.

2011-01-01

In this paper we describe a roadmap-based approach for a multi-agent search strategy to clear a building or multi-story environment. This approach utilizes an encoding of the environment in the form of a graph (roadmap) that is used to encode

Automatic approach to stabilization and control for multi robot teams by multilayer network operator

Directory of Open Access Journals (Sweden)

Diveev Askhat

2016-01-01

Full Text Available The paper describes a novel methodology for synthesis a high-level control of autonomous multi robot teams. The approach is based on multilayer network operator method that belongs to a symbolic regression class. Synthesis is accomplished in three steps: stabilizing robots about some given position in a state space, finding optimal trajectories of robots’ motion as sets of stabilizing points and then approximating all the points of optimal trajectories by some multi-dimensional function of state variables. The feasibility and effectiveness of the proposed approach is verified on simulations of the task of control synthesis for three mobile robots parking in the constrained space.

Multi-criteria multi-stakeholder decision analysis using a fuzzy-stochastic approach for hydrosystem management

Science.gov (United States)

Subagadis, Y. H.; Schütze, N.; Grundmann, J.

2014-09-01

The conventional methods used to solve multi-criteria multi-stakeholder problems are less strongly formulated, as they normally incorporate only homogeneous information at a time and suggest aggregating objectives of different decision-makers avoiding water-society interactions. In this contribution, Multi-Criteria Group Decision Analysis (MCGDA) using a fuzzy-stochastic approach has been proposed to rank a set of alternatives in water management decisions incorporating heterogeneous information under uncertainty. The decision making framework takes hydrologically, environmentally, and socio-economically motivated conflicting objectives into consideration. The criteria related to the performance of the physical system are optimized using multi-criteria simulation-based optimization, and fuzzy linguistic quantifiers have been used to evaluate subjective criteria and to assess stakeholders' degree of optimism. The proposed methodology is applied to find effective and robust intervention strategies for the management of a coastal hydrosystem affected by saltwater intrusion due to excessive groundwater extraction for irrigated agriculture and municipal use. Preliminary results show that the MCGDA based on a fuzzy-stochastic approach gives useful support for robust decision-making and is sensitive to the decision makers' degree of optimism.

An Evidence-Based Approach to Plum Pox Virus Detection by DASI-ELISA and RT-PCR in Dormant Period

Directory of Open Access Journals (Sweden)

Antonio Olmos

2008-01-01

Full Text Available An evidence-based approach, such as those developed in clinical and veterinary medicine, was applied to the detection of Plum pox virus (PPV during the dormant period. A standardized methodology was used for the calculation of parameters of the operational capacity of DASI-ELISA and RT-PCR in wintertime. These methods are routinely handled to test the sanitary status of plants in national or international trading and in those cases concerning export-import of plant materials. Diagnosis often has to be performed during the dormant period, when plant material is commercialized. Some guidelines to interpret diagnostic results of wintertime are provided in an attempt to minimize risks associated with the methods and over-reliance on the binary outcome of a single assay. In order to evaluate if a complementary test increased the confidence of PPV diagnosis when discordant results between DASI-ELISA and RT-PCR are obtained, NASBA-FH also was included. Likelihood ratios of each method were estimated based on the sensitivity and specificity obtained in wintertime. Subsequently, a Bayesian approach was performed to calculate post-test probability of PPV infection in spring. Results of evidence-based approach show that different PPV prevalences require different screening tests. Thus, at very low PPV prevalence levels DASI-ELISA should be used as the election method, whilst at the highest PPV prevalence levels RT-PCR should be performed. NASBA-FH could be used at medium prevalences to clarify discordances between DASIELISA and RT-PCR.

A Formal Model of Trust Chain based on Multi-level Security Policy

OpenAIRE

Kong Xiangying

2013-01-01

Trust chain is the core technology of trusted computing. A formal model of trust chain based on finite state automata theory is proposed. We use communicating sequential processes to describe the system state transition in trust chain and by combining with multi-level security strategy give the definition of trust system and trust decision theorem of trust chain transfer which is proved meantime. Finally, a prototype system is given to show the efficiency of the model.

Consumer engagement and the development, evaluation and dissemination of evidence-based parenting programs

Science.gov (United States)

Sanders, Matthew R.; Kirby, James N.

2013-01-01

A consumer perspective can contribute much to enhancing the “ecological fit” of population level parenting interventions so they meet the needs of parents. This approach involves building relationships with consumer groups and soliciting consumer input into the relevance and acceptability of interventions, clarifying the enablers and barriers to engagement and involvement of parents, and clarifying variables that influence a parent’s program completion. The adoption of a more collaborative approach to working with consumers is important if meaningful population level change in the prevalence of serious social, emotional and behavioral problems in children and young people is to be achieved. Parents seeking assistance for their children’s behavior come from a diverse range of socioeconomic backgrounds, educational levels, cultures and languages. This paper examines consumer engagement strategies that can be employed throughout the process of program development, evaluation, training and dissemination and in “scaling up” the intervention. We argue that a multi-level public health approach to parenting intervention requires a strong consumer perspective to enable interventions to be more responsive to the preferences and needs of families and to ensure improved population reach of interventions. Examples from large scale dissemination trials are used to illustrate how consumer input can result in an increasingly differentiated suite of evidence-based parenting programs. PMID:22440062

Multi-stage decoding of multi-level modulation codes

Science.gov (United States)

Lin, Shu; Kasami, Tadao; Costello, Daniel J., Jr.

1991-01-01

Various types of multi-stage decoding for multi-level modulation codes are investigated. It is shown that if the component codes of a multi-level modulation code and types of decoding at various stages are chosen properly, high spectral efficiency and large coding gain can be achieved with reduced decoding complexity. Particularly, it is shown that the difference in performance between the suboptimum multi-stage soft-decision maximum likelihood decoding of a modulation code and the single-stage optimum soft-decision decoding of the code is very small, only a fraction of dB loss in signal to noise ratio at a bit error rate (BER) of 10(exp -6).

Modular Multi-level converter based HVDC System for Grid Connection of Offshore Wind Power Plant

DEFF Research Database (Denmark)

Gnanarathna, U.N.; Chaudhary, Sanjay Kumar; Gole, A.M.

2010-01-01

This paper explores the application of modular multi-level converters (MMC) as a means for harnessing the power from off-shore wind power plants. The MMC consists of a large number of simple voltage sourced converter (VSC) submodules that can be easily assembled into a converter for high......-voltage and high power. The paper shows that the MMC converter has a fast response and low harmonic content in comparison with a two-level VSC option. The paper discusses the modeling approach used, including a solution to the modeling challenge imposed by the very large number of switching devices in the MMC....

Optimizing survivability of multi-state systems with multi-level protection by multi-processor genetic algorithm

International Nuclear Information System (INIS)

Levitin, Gregory; Dai Yuanshun; Xie Min; Leng Poh, Kim

2003-01-01

In this paper we consider vulnerable systems which can have different states corresponding to different combinations of available elements composing the system. Each state can be characterized by a performance rate, which is the quantitative measure of a system's ability to perform its task. Both the impact of external factors (stress) and internal causes (failures) affect system survivability, which is determined as probability of meeting a given demand. In order to increase the survivability of the system, a multi-level protection is applied to its subsystems. This means that a subsystem and its inner level of protection are in their turn protected by the protection of an outer level. This double-protected subsystem has its outer protection and so forth. In such systems, the protected subsystems can be destroyed only if all of the levels of their protection are destroyed. Each level of protection can be destroyed only if all of the outer levels of protection are destroyed. We formulate the problem of finding the structure of series-parallel multi-state system (including choice of system elements, choice of structure of multi-level protection and choice of protection methods) in order to achieve a desired level of system survivability by the minimal cost. An algorithm based on the universal generating function method is used for determination of the system survivability. A multi-processor version of genetic algorithm is used as optimization tool in order to solve the structure optimization problem. An application example is presented to illustrate the procedure presented in this paper

Interconnected Levels of Multi-Stage Marketing

DEFF Research Database (Denmark)

Vedel, Mette; Geersbro, Jens; Ritter, Thomas

2012-01-01

different levels of multi-stage marketing and illustrates these stages with a case study. In addition, a triadic perspective is introduced as an analytical tool for multi-stage marketing research. The results from the case study indicate that multi-stage marketing exists on different levels. Thus, managers...... must not only decide in general on the merits of multi-stage marketing for their firm, but must also decide on which level they will engage in multi-stage marketing. The triadic perspective enables a rich and multi-dimensional understanding of how different business relationships influence each other...... in a multi-stage marketing context. This understanding assists managers in assessing and balancing different aspects of multi- stage marketing. The triadic perspective also offers avenues for further research....

Evidence-Based Toxicology.

Science.gov (United States)

Hoffmann, Sebastian; Hartung, Thomas; Stephens, Martin

Evidence-based toxicology (EBT) was introduced independently by two groups in 2005, in the context of toxicological risk assessment and causation as well as based on parallels between the evaluation of test methods in toxicology and evidence-based assessment of diagnostics tests in medicine. The role model of evidence-based medicine (EBM) motivated both proposals and guided the evolution of EBT, whereas especially systematic reviews and evidence quality assessment attract considerable attention in toxicology.Regarding test assessment, in the search of solutions for various problems related to validation, such as the imperfectness of the reference standard or the challenge to comprehensively evaluate tests, the field of Diagnostic Test Assessment (DTA) was identified as a potential resource. DTA being an EBM discipline, test method assessment/validation therefore became one of the main drivers spurring the development of EBT.In the context of pathway-based toxicology, EBT approaches, given their objectivity, transparency and consistency, have been proposed to be used for carrying out a (retrospective) mechanistic validation.In summary, implementation of more evidence-based approaches may provide the tools necessary to adapt the assessment/validation of toxicological test methods and testing strategies to face the challenges of toxicology in the twenty first century.

Multi-level trellis coded modulation and multi-stage decoding

Science.gov (United States)

Costello, Daniel J., Jr.; Wu, Jiantian; Lin, Shu

1990-01-01

Several constructions for multi-level trellis codes are presented and many codes with better performance than previously known codes are found. These codes provide a flexible trade-off between coding gain, decoding complexity, and decoding delay. New multi-level trellis coded modulation schemes using generalized set partitioning methods are developed for Quadrature Amplitude Modulation (QAM) and Phase Shift Keying (PSK) signal sets. New rotationally invariant multi-level trellis codes which can be combined with differential encoding to resolve phase ambiguity are presented.

A New Approach to Site Demand-Based Level Inventory Optimization

Science.gov (United States)

2016-06-01

Note: If probability distributions are estimated based on mean and variance , use ˆ qix  and 2ˆ( )qi to generate these. q in , number of...TO SITE DEMAND-BASED LEVEL INVENTORY OPTIMIZATION by Tacettin Ersoz June 2016 Thesis Advisor: Javier Salmeron Second Reader: Emily...DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE A NEW APPROACH TO SITE DEMAND-BASED LEVEL INVENTORY OPTIMIZATION 5. FUNDING NUMBERS 6

A simulation-based optimization approach for free distributed repairable multi-state availability-redundancy allocation problems

International Nuclear Information System (INIS)

Attar, Ahmad; Raissi, Sadigh; Khalili-Damghani, Kaveh

2017-01-01

A simulation-based optimization (SBO) method is proposed to handle multi-objective joint availability-redundancy allocation problem (JARAP). Here, there is no emphasis on probability distributions of time to failures and repair times for multi-state multi-component series-parallel configuration under active, cold and hot standby strategies. Under such conditions, estimation of availability is not a trivial task. First, an efficient computer simulation model is proposed to estimate the availability of the aforementioned system. Then, the estimated availability values are used in a repetitive manner as parameter of a two-objective joint availability-redundancy allocation optimization model through SBO mechanism. The optimization model is then solved using two well-known multi-objective evolutionary computation algorithms, i.e., non-dominated sorting genetic algorithm (NSGA-II), and Strength Pareto Evolutionary Algorithm (SPEA2). The proposed SBO approach is tested using non-exponential numerical example with multi-state repairable components. The results are presented and discussed through different demand scenarios under cold and hot standby strategies. Furthermore, performance of NSGA-II and SPEA2 are statistically compared regarding multi-objective accuracy, and diversity metrics. - Highlights: • A Simulation-Based Optimization (SBO) procedure is introduced for JARAP. • The proposed SBO works for any given failure and repair times. • An efficient simulation procedure is developed to estimate availability. • Customized NSGA-II and SPEA2 are proposed to solve the bi-objective JARAP. • Statistical analysis is employed to test the performance of optimization methods.

Biodiversity conservation in Swedish forests: ways forward for a 30-year-old multi-scaled approach.

Science.gov (United States)

Gustafsson, Lena; Perhans, Karin

2010-12-01

A multi-scaled model for biodiversity conservation in forests was introduced in Sweden 30 years ago, which makes it a pioneer example of an integrated ecosystem approach. Trees are set aside for biodiversity purposes at multiple scale levels varying from individual trees to areas of thousands of hectares, with landowner responsibility at the lowest level and with increasing state involvement at higher levels. Ecological theory supports the multi-scaled approach, and retention efforts at every harvest occasion stimulate landowners' interest in conservation. We argue that the model has large advantages but that in a future with intensified forestry and global warming, development based on more progressive thinking is necessary to maintain and increase biodiversity. Suggestions for the future include joint planning for several forest owners, consideration of cost-effectiveness, accepting opportunistic work models, adjusting retention levels to stand and landscape composition, introduction of temporary reserves, creation of "receiver habitats" for species escaping climate change, and protection of young forests.

Multi-level restricted maximum likelihood covariance estimation and kriging for large non-gridded spatial datasets

KAUST Repository

Castrillon, Julio

2015-11-10

We develop a multi-level restricted Gaussian maximum likelihood method for estimating the covariance function parameters and computing the best unbiased predictor. Our approach produces a new set of multi-level contrasts where the deterministic parameters of the model are filtered out thus enabling the estimation of the covariance parameters to be decoupled from the deterministic component. Moreover, the multi-level covariance matrix of the contrasts exhibit fast decay that is dependent on the smoothness of the covariance function. Due to the fast decay of the multi-level covariance matrix coefficients only a small set is computed with a level dependent criterion. We demonstrate our approach on problems of up to 512,000 observations with a Matérn covariance function and highly irregular placements of the observations. In addition, these problems are numerically unstable and hard to solve with traditional methods.

A Dynamic Fuzzy Approach Based on the EDAS Method for Multi-Criteria Subcontractor Evaluation

Directory of Open Access Journals (Sweden)

Mehdi Keshavarz-Ghorabaee

2018-03-01

Full Text Available Selection of appropriate subcontractors for outsourcing is very important for the success of construction projects. This can improve the overall quality of projects and promote the qualification and reputation of the main contractors. The evaluation of subcontractors can be made by some experts or decision-makers with respect to some criteria. If this process is done in different time periods, it can be defined as a dynamic multi-criteria group decision-making (MCGDM problem. In this study, we propose a new fuzzy dynamic MCGDM approach based on the EDAS (Evaluation based on Distance from Average Solution method for subcontractor evaluation. In the procedure of the proposed approach, the sets of alternatives, criteria and decision-makers can be changed at different time periods. Also, the proposed approach gives more weight to newer decision information for aggregating the overall performance of alternatives. A numerical example is used to illustrate the proposed approach and show the application of it in subcontractor evaluation. The results demonstrate that the proposed approach is efficient and useful in real-world decision-making problems.

Multi-level Bayesian analyses for single- and multi-vehicle freeway crashes.

Science.gov (United States)

Yu, Rongjie; Abdel-Aty, Mohamed

2013-09-01

This study presents multi-level analyses for single- and multi-vehicle crashes on a mountainous freeway. Data from a 15-mile mountainous freeway section on I-70 were investigated. Both aggregate and disaggregate models for the two crash conditions were developed. Five years of crash data were used in the aggregate investigation, while the disaggregate models utilized one year of crash data along with real-time traffic and weather data. For the aggregate analyses, safety performance functions were developed for the purpose of revealing the contributing factors for each crash type. Two methodologies, a Bayesian bivariate Poisson-lognormal model and a Bayesian hierarchical Poisson model with correlated random effects, were estimated to simultaneously analyze the two crash conditions with consideration of possible correlations. Except for the factors related to geometric characteristics, two exposure parameters (annual average daily traffic and segment length) were included. Two different sets of significant explanatory and exposure variables were identified for the single-vehicle (SV) and multi-vehicle (MV) crashes. It was found that the Bayesian bivariate Poisson-lognormal model is superior to the Bayesian hierarchical Poisson model, the former with a substantially lower DIC and more significant variables. In addition to the aggregate analyses, microscopic real-time crash risk evaluation models were developed for the two crash conditions. Multi-level Bayesian logistic regression models were estimated with the random parameters accounting for seasonal variations, crash-unit-level diversity and segment-level random effects capturing unobserved heterogeneity caused by the geometric characteristics. The model results indicate that the effects of the selected variables on crash occurrence vary across seasons and crash units; and that geometric characteristic variables contribute to the segment variations: the more unobserved heterogeneity have been accounted, the better

A multi-institutional study of the perceived barriers and facilitators to implementing evidence-based practice.

Science.gov (United States)

Duncombe, Daphne C

2018-03-01

To examine perceived barriers and facilitators to implementing evidence-based practice among nurses working in psychiatric, geriatric, hospital and community settings in The Bahamas. It is evident from previous studies that a number of factors exist which either obstruct or promote the utilisation of research evidence in nursing practice. Identifying these factors is vital to the successful uptake of evidence-based practice in nursing. Descriptive, comparative study. Data were collected using self-administered questionnaires. A stratified random sample (n = 100) of registered nurses participated; 5-point Likert-like scales were used to examine nurses' perceptions of barriers and facilitators of evidence-based practice. Descriptive statistics were used to describe demographic characteristics and to compare responses of nurses. Participants were predominantly female (98.4%), in the 25 to implement evidence-based practice previously. The greatest barriers identified were as follows: "Inadequate resources for implementing research findings" (85.2%; n = 52) and "Inadequate training in research methods" (83.6%; n = 51). The top facilitators identified were as follows: "Training in research methods" (88.5%; n = 54) and "Organisational policies and protocols that are evidence-based" (86.9%; n = 53). Nurses generally expressed that they required additional training in research and evidence-based practice concepts. Although some nurses had a desire to implement evidence-based practice to provide quality care and improve patient outcomes, many expressed that they lacked the required resources. The study draws attention to the need for prioritisation of evidence-based practice both at institutional and governmental levels. Successful adoption of evidence-based practice implies combined efforts of nurses, healthcare providers and policymakers. Further research is needed to determine the best method for successfully incorporating evidence-based practice into nursing

Perturbational treatment of spin-orbit coupling for generally applicable high-level multi-reference methods

International Nuclear Information System (INIS)

Mai, Sebastian; Marquetand, Philipp; González, Leticia; Müller, Thomas; Plasser, Felix; Lischka, Hans

2014-01-01

An efficient perturbational treatment of spin-orbit coupling within the framework of high-level multi-reference techniques has been implemented in the most recent version of the COLUMBUS quantum chemistry package, extending the existing fully variational two-component (2c) multi-reference configuration interaction singles and doubles (MRCISD) method. The proposed scheme follows related implementations of quasi-degenerate perturbation theory (QDPT) model space techniques. Our model space is built either from uncontracted, large-scale scalar relativistic MRCISD wavefunctions or based on the scalar-relativistic solutions of the linear-response-theory-based multi-configurational averaged quadratic coupled cluster method (LRT-MRAQCC). The latter approach allows for a consistent, approximatively size-consistent and size-extensive treatment of spin-orbit coupling. The approach is described in detail and compared to a number of related techniques. The inherent accuracy of the QDPT approach is validated by comparing cuts of the potential energy surfaces of acrolein and its S, Se, and Te analoga with the corresponding data obtained from matching fully variational spin-orbit MRCISD calculations. The conceptual availability of approximate analytic gradients with respect to geometrical displacements is an attractive feature of the 2c-QDPT-MRCISD and 2c-QDPT-LRT-MRAQCC methods for structure optimization and ab inito molecular dynamics simulations

Perturbational treatment of spin-orbit coupling for generally applicable high-level multi-reference methods

Energy Technology Data Exchange (ETDEWEB)

Mai, Sebastian; Marquetand, Philipp; González, Leticia [Institute of Theoretical Chemistry, University of Vienna, Währinger Str. 17, 1090 Vienna (Austria); Müller, Thomas, E-mail: th.mueller@fz-juelich.de [Institute for Advanced Simulation, Jülich Supercomputing Centre, Forschungszentrum Jülich, 52425 Jülich (Germany); Plasser, Felix [Interdisciplinary Center for Scientific Computing, University of Heidelberg, Im Neuenheimer Feld 368, 69120 Heidelberg (Germany); Lischka, Hans [Institute of Theoretical Chemistry, University of Vienna, Währinger Str. 17, 1090 Vienna (Austria); Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, Texas 79409-1061 (United States)

2014-08-21

An efficient perturbational treatment of spin-orbit coupling within the framework of high-level multi-reference techniques has been implemented in the most recent version of the COLUMBUS quantum chemistry package, extending the existing fully variational two-component (2c) multi-reference configuration interaction singles and doubles (MRCISD) method. The proposed scheme follows related implementations of quasi-degenerate perturbation theory (QDPT) model space techniques. Our model space is built either from uncontracted, large-scale scalar relativistic MRCISD wavefunctions or based on the scalar-relativistic solutions of the linear-response-theory-based multi-configurational averaged quadratic coupled cluster method (LRT-MRAQCC). The latter approach allows for a consistent, approximatively size-consistent and size-extensive treatment of spin-orbit coupling. The approach is described in detail and compared to a number of related techniques. The inherent accuracy of the QDPT approach is validated by comparing cuts of the potential energy surfaces of acrolein and its S, Se, and Te analoga with the corresponding data obtained from matching fully variational spin-orbit MRCISD calculations. The conceptual availability of approximate analytic gradients with respect to geometrical displacements is an attractive feature of the 2c-QDPT-MRCISD and 2c-QDPT-LRT-MRAQCC methods for structure optimization and ab inito molecular dynamics simulations.

Multi-level restricted maximum likelihood covariance estimation and kriging for large non-gridded spatial datasets

KAUST Repository

Castrillon, Julio; Genton, Marc G.; Yokota, Rio

2015-01-01

We develop a multi-level restricted Gaussian maximum likelihood method for estimating the covariance function parameters and computing the best unbiased predictor. Our approach produces a new set of multi-level contrasts where the deterministic

Multi-criteria multi-stakeholder decision analysis using a fuzzy-stochastic approach for hydrosystem management

Directory of Open Access Journals (Sweden)

Y. H. Subagadis

2014-09-01

Full Text Available The conventional methods used to solve multi-criteria multi-stakeholder problems are less strongly formulated, as they normally incorporate only homogeneous information at a time and suggest aggregating objectives of different decision-makers avoiding water–society interactions. In this contribution, Multi-Criteria Group Decision Analysis (MCGDA using a fuzzy-stochastic approach has been proposed to rank a set of alternatives in water management decisions incorporating heterogeneous information under uncertainty. The decision making framework takes hydrologically, environmentally, and socio-economically motivated conflicting objectives into consideration. The criteria related to the performance of the physical system are optimized using multi-criteria simulation-based optimization, and fuzzy linguistic quantifiers have been used to evaluate subjective criteria and to assess stakeholders' degree of optimism. The proposed methodology is applied to find effective and robust intervention strategies for the management of a coastal hydrosystem affected by saltwater intrusion due to excessive groundwater extraction for irrigated agriculture and municipal use. Preliminary results show that the MCGDA based on a fuzzy-stochastic approach gives useful support for robust decision-making and is sensitive to the decision makers' degree of optimism.

Generating multi-double-scroll attractors via nonautonomous approach.

Science.gov (United States)

Hong, Qinghui; Xie, Qingguo; Shen, Yi; Wang, Xiaoping

2016-08-01

It is a common phenomenon that multi-scroll attractors are realized by introducing the various nonlinear functions with multiple breakpoints in double scroll chaotic systems. Differently, we present a nonautonomous approach for generating multi-double-scroll attractors (MDSA) without changing the original nonlinear functions. By using the multi-level-logic pulse excitation technique in double scroll chaotic systems, MDSA can be generated. A Chua's circuit, a Jerk circuit, and a modified Lorenz system are given as designed example and the Matlab simulation results are presented. Furthermore, the corresponding realization circuits are designed. The Pspice results are in agreement with numerical simulation results, which verify the availability and feasibility of this method.

Project Based Learning in Multi-Grade Class

Science.gov (United States)

Ciftci, Sabahattin; Baykan, Ayse Aysun

2013-01-01

The purpose of this study is to evaluate project based learning in multi-grade classes. This study, based on a student-centered learning approach, aims to analyze students' and parents' interpretations. The study was done in a primary village school belonging to the Centre of Batman, already adapting multi-grade classes in their education system,…

Using the Dynamic Model to develop an evidence-based and theory-driven approach to school improvement

NARCIS (Netherlands)

Creemers, B.P.M.; Kyriakides, L.

2010-01-01

This paper refers to a dynamic perspective of educational effectiveness and improvement stressing the importance of using an evidence-based and theory-driven approach. Specifically, an approach to school improvement based on the dynamic model of educational effectiveness is offered. The recommended

Multi-objective Search-based Mobile Testing

OpenAIRE

Mao, K.

2017-01-01

Despite the tremendous popularity of mobile applications, mobile testing still relies heavily on manual testing. This thesis presents mobile test automation approaches based on multi-objective search. We introduce three approaches: Sapienz (for native Android app testing), Octopuz (for hybrid/web JavaScript app testing) and Polariz (for using crowdsourcing to support search-based mobile testing). These three approaches represent the primary scientific and technical contributions of the thesis...

Biomarker responses to environmental contamination in estuaries: A comparative multi-taxa approach.

Science.gov (United States)

Duarte, Irina A; Reis-Santos, Patrick; França, Susana; Cabral, Henrique; Fonseca, Vanessa F

2017-08-01

Estuaries are highly productive ecosystems subjected to numerous anthropogenic pressures with consequent environmental quality degradation. In this study, multiple biomarker responses [superoxide dismutase (SOD), catalase (CAT), ethoxyresorufin O-deethylase (EROD) and glutathione S-transferase (GST) activities, as well as lipid peroxidation (LPO) and DNA damage (DNAd)] were determined in two fish (Dicentrarchus labrax and Pomatoschistus microps) and four macroinvertebrate species (Carcinus maenas, Crangon crangon, Hediste diversicolor and Scrobicularia plana) from the Ria de Aveiro and Tejo estuaries over distinct months. Two sites per estuarine system were selected based on anthropogenic pressures and magnitude of environmental contamination. Antioxidant enzyme activities in fish species suggested a ubiquitous response to oxidative stress, while biotransformation and effect biomarkers exhibited higher spatial and temporal variation. In invertebrate species, biotransformation enzyme activity was clearly less variable than in fish evidencing lower xenobiotic transformation capability. Overall, largest biomarker responses were found in the most contaminated sites (Tejo), yet species-specific patterns were evident. These should be factored in multi-taxa approaches, considering that the differential functional traits of species, such as habitat use, life-stage, feeding or physiology can influence exposure routes and biomarker responses. The Integrated Biomarker Response index highlighted patterns in biomarker responses which were not immediately evident when analyzing biomarkers individually. Overall, results provided insights into the complexity of species responses to contamination in naturally varying estuarine environments. Ultimately, multi-taxa and multi-biomarker approaches provide a comprehensive and complementary view of ecosystem health, encompassing diverse forms of biological integration and exposure routes, and allow the validation of results among markers

A multi-band, multi-level, multi-electron model for efficient FDTD simulations of electromagnetic interactions with semiconductor quantum wells

Science.gov (United States)

Ravi, Koustuban; Wang, Qian; Ho, Seng-Tiong

2015-08-01

We report a new computational model for simulations of electromagnetic interactions with semiconductor quantum well(s) (SQW) in complex electromagnetic geometries using the finite-difference time-domain method. The presented model is based on an approach of spanning a large number of electron transverse momentum states in each SQW sub-band (multi-band) with a small number of discrete multi-electron states (multi-level, multi-electron). This enables accurate and efficient two-dimensional (2-D) and three-dimensional (3-D) simulations of nanophotonic devices with SQW active media. The model includes the following features: (1) Optically induced interband transitions between various SQW conduction and heavy-hole or light-hole sub-bands are considered. (2) Novel intra sub-band and inter sub-band transition terms are derived to thermalize the electron and hole occupational distributions to the correct Fermi-Dirac distributions. (3) The terms in (2) result in an explicit update scheme which circumvents numerically cumbersome iterative procedures. This significantly augments computational efficiency. (4) Explicit update terms to account for carrier leakage to unconfined states are derived, which thermalize the bulk and SQW populations to a common quasi-equilibrium Fermi-Dirac distribution. (5) Auger recombination and intervalence band absorption are included. The model is validated by comparisons to analytic band-filling calculations, simulations of SQW optical gain spectra, and photonic crystal lasers.

Increasing the public health impact of evidence-based interventions in behavioral medicine: new approaches and future directions.

Science.gov (United States)

Buscemi, Joanna; Janke, E Amy; Kugler, Kari C; Duffecy, Jenna; Mielenz, Thelma J; St George, Sara M; Sheinfeld Gorin, Sherri N

2017-02-01

The dissemination and implementation of evidence-based behavioral medicine interventions into real world practice has been limited. The purpose of this paper is to discuss specific limitations of current behavioral medicine research within the context of the RE-AIM framework, and potential opportunities to increase public health impact by applying novel intervention designs and data collection approaches. The MOST framework has recently emerged as an alternative approach to development and evaluation that aims to optimize multicomponent behavioral and bio-behavioral interventions. SMART designs, imbedded within the MOST framework, are an approach to optimize adaptive interventions. In addition to innovative design strategies, novel data collection approaches that have the potential to improve the public-health dissemination include mHealth approaches and considering environment as a potential data source. Finally, becoming involved in advocacy via policy related work may help to improve the impact of evidence-based behavioral interventions. Innovative methods, if increasingly implemented, may have the ability to increase the public health impact of evidence-based behavioral interventions to prevent disease.

Predicting multi-level drug response with gene expression profile in multiple myeloma using hierarchical ordinal regression.

Science.gov (United States)

Zhang, Xinyan; Li, Bingzong; Han, Huiying; Song, Sha; Xu, Hongxia; Hong, Yating; Yi, Nengjun; Zhuang, Wenzhuo

2018-05-10

Multiple myeloma (MM), like other cancers, is caused by the accumulation of genetic abnormalities. Heterogeneity exists in the patients' response to treatments, for example, bortezomib. This urges efforts to identify biomarkers from numerous molecular features and build predictive models for identifying patients that can benefit from a certain treatment scheme. However, previous studies treated the multi-level ordinal drug response as a binary response where only responsive and non-responsive groups are considered. It is desirable to directly analyze the multi-level drug response, rather than combining the response to two groups. In this study, we present a novel method to identify significantly associated biomarkers and then develop ordinal genomic classifier using the hierarchical ordinal logistic model. The proposed hierarchical ordinal logistic model employs the heavy-tailed Cauchy prior on the coefficients and is fitted by an efficient quasi-Newton algorithm. We apply our hierarchical ordinal regression approach to analyze two publicly available datasets for MM with five-level drug response and numerous gene expression measures. Our results show that our method is able to identify genes associated with the multi-level drug response and to generate powerful predictive models for predicting the multi-level response. The proposed method allows us to jointly fit numerous correlated predictors and thus build efficient models for predicting the multi-level drug response. The predictive model for the multi-level drug response can be more informative than the previous approaches. Thus, the proposed approach provides a powerful tool for predicting multi-level drug response and has important impact on cancer studies.

Multi level configuration of ETO products

DEFF Research Database (Denmark)

Petersen, Thomas Ditlev; Jørgensen, Kaj Asbjørn; Hvolby, Hans-Henrik

2007-01-01

The paper introduces and defines central concepts related to multi level configuration and analyzes which challenges an engineer to order company must deal with to be able to realize a multi level configuration system. It is argued that high flexibility can be achieved and focus can be directed...... in certain business processes if a multi level configuration system is realized....

Multi-level Strategy for Identifying Proteasome-Catalyzed Spliced Epitopes Targeted by CD8(+) T Cells during Bacterial Infection

NARCIS (Netherlands)

Platteel, Anouk C M|info:eu-repo/dai/nl/375805613; Liepe, Juliane; Textoris-Taube, Kathrin; Keller, Christin; Henklein, Petra; Schalkwijk, Hanna H; Cardoso, Rebeca; Kloetzel, Peter M; Mishto, Michele; Sijts, Alice J A M|info:eu-repo/dai/nl/115553843

2017-01-01

Proteasome-catalyzed peptide splicing (PCPS) generates peptides that are presented by MHC class I molecules, but because their identification is challenging, the immunological relevance of spliced peptides remains unclear. Here, we developed a reverse immunology-based multi-level approach to

Fuzzy Multi-objective Linear Programming Approach

Directory of Open Access Journals (Sweden)

Amna Rehmat

2007-07-01

Full Text Available Traveling salesman problem (TSP is one of the challenging real-life problems, attracting researchers of many fields including Artificial Intelligence, Operations Research, and Algorithm Design and Analysis. The problem has been well studied till now under different headings and has been solved with different approaches including genetic algorithms and linear programming. Conventional linear programming is designed to deal with crisp parameters, but information about real life systems is often available in the form of vague descriptions. Fuzzy methods are designed to handle vague terms, and are most suited to finding optimal solutions to problems with vague parameters. Fuzzy multi-objective linear programming, an amalgamation of fuzzy logic and multi-objective linear programming, deals with flexible aspiration levels or goals and fuzzy constraints with acceptable deviations. In this paper, a methodology, for solving a TSP with imprecise parameters, is deployed using fuzzy multi-objective linear programming. An example of TSP with multiple objectives and vague parameters is discussed.

Life cycle assessment of greenhouse gas emissions and water-energy optimization for shale gas supply chain planning based on multi-level approach: Case study in Barnett, Marcellus, Fayetteville, and Haynesville shales

International Nuclear Information System (INIS)

Chen, Yizhong; He, Li; Guan, Yanlong; Lu, Hongwei; Li, Jing

2017-01-01

Highlights: • Detailed model developed for the shale gas supply chain system in the US. • Dynamic integration of multi-level programming and life cycle assessment. • Analysis of the objectives with environmental, economic and energy concerns. • Identification of GHG emissions and water-energy consumption at life cycle stages. • Comparison of management performances obtained from the MLP, MOP, and BLP methods. - Abstract: This study develops a multi-level programming model from a life cycle perspective for performing shale-gas supply chain system. A set of leader-follower-interactive objectives with emphases of environmental, economic and energy concerns are incorporated into the synergistic optimization process, named MGU-MEM-MWL model. The upper-level model quantitatively investigates the life-cycle greenhouse gas (GHG) emissions as controlled by the environmental sector. The middle-level one focuses exclusively on system benefits as determined by the energy sector. The lower-level one aims to recycle water to minimize the life-cycle water supply as required by the enterprises. The capabilities and effectiveness of the developed model are illustrated through real-world case studies of the Barnett, Marcellus, Fayetteville, and Haynesville Shales in the US. An improved multi-level interactive solution algorithm based on satisfactory degree is then presented to improve computational efficiency. Results indicate that: (a) the end-use phase (i.e., gas utilization for electricity generation) would not only dominate the life-cycle GHG emissions, but also account for 76.1% of the life-cycle system profits; (b) operations associated with well hydraulic fracturing would be the largest contributor to the life-cycle freshwater consumption when gas use is not considered, and a majority of freshwater withdrawal would be supplied by surface water; (c) nearly 95% of flowback water would be recycled for hydraulic fracturing activities and only about 5% of flowback water

Automatic evidence quality prediction to support evidence-based decision making.

Science.gov (United States)

Sarker, Abeed; Mollá, Diego; Paris, Cécile

2015-06-01

Evidence-based medicine practice requires practitioners to obtain the best available medical evidence, and appraise the quality of the evidence when making clinical decisions. Primarily due to the plethora of electronically available data from the medical literature, the manual appraisal of the quality of evidence is a time-consuming process. We present a fully automatic approach for predicting the quality of medical evidence in order to aid practitioners at point-of-care. Our approach extracts relevant information from medical article abstracts and utilises data from a specialised corpus to apply supervised machine learning for the prediction of the quality grades. Following an in-depth analysis of the usefulness of features (e.g., publication types of articles), they are extracted from the text via rule-based approaches and from the meta-data associated with the articles, and then applied in the supervised classification model. We propose the use of a highly scalable and portable approach using a sequence of high precision classifiers, and introduce a simple evaluation metric called average error distance (AED) that simplifies the comparison of systems. We also perform elaborate human evaluations to compare the performance of our system against human judgments. We test and evaluate our approaches on a publicly available, specialised, annotated corpus containing 1132 evidence-based recommendations. Our rule-based approach performs exceptionally well at the automatic extraction of publication types of articles, with F-scores of up to 0.99 for high-quality publication types. For evidence quality classification, our approach obtains an accuracy of 63.84% and an AED of 0.271. The human evaluations show that the performance of our system, in terms of AED and accuracy, is comparable to the performance of humans on the same data. The experiments suggest that our structured text classification framework achieves evaluation results comparable to those of human performance

Generating multi-double-scroll attractors via nonautonomous approach

Energy Technology Data Exchange (ETDEWEB)

Hong, Qinghui; Xie, Qingguo, E-mail: qgxie@mail.hust.edu.cn [Wuhan National Laboratory for Optoelectronics, Wuhan 430074 (China); Shen, Yi; Wang, Xiaoping [School of Automation, Huazhong University of Science and Technology, Wuhan 430074 (China)

2016-08-15

It is a common phenomenon that multi-scroll attractors are realized by introducing the various nonlinear functions with multiple breakpoints in double scroll chaotic systems. Differently, we present a nonautonomous approach for generating multi-double-scroll attractors (MDSA) without changing the original nonlinear functions. By using the multi-level-logic pulse excitation technique in double scroll chaotic systems, MDSA can be generated. A Chua's circuit, a Jerk circuit, and a modified Lorenz system are given as designed example and the Matlab simulation results are presented. Furthermore, the corresponding realization circuits are designed. The Pspice results are in agreement with numerical simulation results, which verify the availability and feasibility of this method.

Multi-Level Secure Local Area Network

OpenAIRE

Naval Postgraduate School (U.S.); Center for Information Systems Studies Security and Research (CISR)

2011-01-01

Multi-Level Secure Local Area Network is a cost effective, multi-level, easy to use office environment leveraging existing high assurance technology. The Department of Defense and U.S. Government have an identified need to securely share information classified at differing security levels. Because there exist no commercial solutions to this problem, NPS is developing a MLS LAN. The MLS LAN extends high assurance capabilities of an evaluated multi-level secure system to commercial personal com...

An adaptive multi-agent-based approach to smart grids control and optimization

Energy Technology Data Exchange (ETDEWEB)

Carvalho, Marco [Florida Institute of Technology, Melbourne, FL (United States); Perez, Carlos; Granados, Adrian [Institute for Human and Machine Cognition, Ocala, FL (United States)

2012-03-15

In this paper, we describe a reinforcement learning-based approach to power management in smart grids. The scenarios we consider are smart grid settings where renewable power sources (e.g. Photovoltaic panels) have unpredictable variations in power output due, for example, to weather or cloud transient effects. Our approach builds on a multi-agent system (MAS)-based infrastructure for the monitoring and coordination of smart grid environments with renewable power sources and configurable energy storage devices (battery banks). Software agents are responsible for tracking and reporting power flow variations at different points in the grid, and to optimally coordinate the engagement of battery banks (i.e. charge/idle/discharge modes) to maintain energy requirements to end-users. Agents are able to share information and coordinate control actions through a parallel communications infrastructure, and are also capable of learning, from experience, how to improve their response strategies for different operational conditions. In this paper we describe our approach and address some of the challenges associated with the communications infrastructure for distributed coordination. We also present some preliminary results of our first simulations using the GridLAB-D simulation environment, created by the US Department of Energy (DoE) at Pacific Northwest National Laboratory (PNNL). (orig.)

Adopting a blended learning approach to teaching evidence based medicine: a mixed methods study

OpenAIRE

Ilic, Dragan; Hart, William; Fiddes, Patrick; Misso, Marie; Villanueva, Elmer

2013-01-01

Background Evidence Based Medicine (EBM) is a core unit delivered across many medical schools. Few studies have investigated the most effective method of teaching a course in EBM to medical students. The objective of this study was to identify whether a blended-learning approach to teaching EBM is more effective a didactic-based approach at increasing medical student competency in EBM. Methods A mixed-methods study was conducted consisting of a controlled trial and focus groups with second ye...

Developing evidence-based maternity care in Iran: a quality improvement study

Directory of Open Access Journals (Sweden)

Mohammad Kazem

2008-06-01

Full Text Available Abstract Background Current Iranian perinatal statistics indicate that maternity care continues to need improvement. In response, we implemented a multi-faceted intervention to improve the quality of maternity care at an Iranian Social Security Hospital. Using a before-and-after design our aim was to improve the uptake of selected evidence based practices and more closely attend to identified women's needs and preferences. Methods The major steps of the study were to (1 identify women's needs, values and preferences via interviews, (2 select through a process of professional consensus the top evidence-based clinical recommendations requiring local implementation (3 redesign care based on the selected evidence-based recommendations and women's views, and (4 implement the new care model. We measured the impact of the new care model on maternal satisfaction and caesarean birth rates utilising maternal surveys and medical record audit before and after implementation of the new care model. Results Twenty women's needs and requirements as well as ten evidence-based clinical recommendations were selected as a basis for improving care. Following the introduction of the new model of care, women's satisfaction levels improved significantly on 16 of 20 items (p Conclusion The introduction of a quality improvement care model improved compliance with evidence-based guidelines and was associated with an improvement in women's satisfaction levels and a reduction in rates of caesarean birth.

A hybrid solution approach for a multi-objective closed-loop logistics network under uncertainty

Science.gov (United States)

Mehrbod, Mehrdad; Tu, Nan; Miao, Lixin

2015-06-01

The design of closed-loop logistics (forward and reverse logistics) has attracted growing attention with the stringent pressures of customer expectations, environmental concerns and economic factors. This paper considers a multi-product, multi-period and multi-objective closed-loop logistics network model with regard to facility expansion as a facility location-allocation problem, which more closely approximates real-world conditions. A multi-objective mixed integer nonlinear programming formulation is linearized by defining new variables and adding new constraints to the model. By considering the aforementioned model under uncertainty, this paper develops a hybrid solution approach by combining an interactive fuzzy goal programming approach and robust counterpart optimization based on three well-known robust counterpart optimization formulations. Finally, this paper compares the results of the three formulations using different test scenarios and parameter-sensitive analysis in terms of the quality of the final solution, CPU time, the level of conservatism, the degree of closeness to the ideal solution, the degree of balance involved in developing a compromise solution, and satisfaction degree.

A Guide to Visual Multi-Level Interface Design From Synthesis of Empirical Study Evidence

CERN Document Server

Lam, Heidi

2010-01-01

Displaying multiple levels of data visually has been proposed to address the challenge of limited screen space. Although many previous empirical studies have addressed different aspects of this question, the information visualization research community does not currently have a clearly articulated consensus on how, when, or even if displaying data at multiple levels is effective. To shed more light on this complex topic, we conducted a systematic review of 22 existing multi-level interface studies to extract high-level design guidelines. To facilitate discussion, we cast our analysis findings

A Probabilistic Approach for the System-Level Design of Multi-ASIP Platforms

DEFF Research Database (Denmark)

Micconi, Laura

introduce a system-level Design Space Exploration (DSE) for the very early phases of the design that automatizes part of the multi-ASIP design flow. Our DSE is responsible for assigning the tasks to the different ASIPs exploring different platform alternatives. We perform a schedulability analysis for each...

Multi-Level Formation of Complex Software Systems

Directory of Open Access Journals (Sweden)

Hui Li

2016-05-01

Full Text Available We present a multi-level formation model for complex software systems. The previous works extract the software systems to software networks for further studies, but usually investigate the software networks at the class level. In contrast to these works, our treatment of software systems as multi-level networks is more realistic. In particular, the software networks are organized by three levels of granularity, which represents the modularity and hierarchy in the formation process of real-world software systems. More importantly, simulations based on this model have generated more realistic structural properties of software networks, such as power-law, clustering and modularization. On the basis of this model, how the structure of software systems effects software design principles is then explored, and it could be helpful for understanding software evolution and software engineering practices.

MULTI-TEMPORAL REMOTE SENSING IMAGE CLASSIFICATION - A MULTI-VIEW APPROACH

Data.gov (United States)

National Aeronautics and Space Administration — MULTI-TEMPORAL REMOTE SENSING IMAGE CLASSIFICATION - A MULTI-VIEW APPROACH VARUN CHANDOLA AND RANGA RAJU VATSAVAI Abstract. Multispectral remote sensing images have...

Multi-Level Marketing as a business model

Directory of Open Access Journals (Sweden)

Bogdan Gregor

2013-03-01

Full Text Available Multi Level Marketing is a very popular business model in the Western countries. It is a kind of hybrid of the method of distribution of goods and the method of building a sales network. It is one of the safest (carries a very low risk ways of conducting a business activity. The knowledge about functioning of this business model, both among theoreticians (scanty literature on the subject and practitioners, is still insufficient in Poland. Thus, the presented paper has been prepared as — in the Authors' opinion — it, at least infinitesimally, bridges the gap in the recognition of Multi Level Marketing issues. The aim of the study was, first of all, to describe Multi Level Marketing, to indicate practical benefits of this business model as well as to present basic systems of calculating a commission, which are used in marketing plans of companies. The discussion was based on the study of literature and the knowledge gained in the course of free-form interviews with the leaders of the sector.

Regression-based approach for testing the association between multi-region haplotype configuration and complex trait

Directory of Open Access Journals (Sweden)

Zhao Hongbo

2009-09-01

Full Text Available Abstract Background It is quite common that the genetic architecture of complex traits involves many genes and their interactions. Therefore, dealing with multiple unlinked genomic regions simultaneously is desirable. Results In this paper we develop a regression-based approach to assess the interactions of haplotypes that belong to different unlinked regions, and we use score statistics to test the null hypothesis of non-genetic association. Additionally, multiple marker combinations at each unlinked region are considered. The multiple tests are settled via the minP approach. The P value of the "best" multi-region multi-marker configuration is corrected via Monte-Carlo simulations. Through simulation studies, we assess the performance of the proposed approach and demonstrate its validity and power in testing for haplotype interaction association. Conclusion Our simulations showed that, for binary trait without covariates, our proposed methods prove to be equal and even more powerful than htr and hapcc which are part of the FAMHAP program. Additionally, our model can be applied to a wider variety of traits and allow adjustment for other covariates. To test the validity, our methods are applied to analyze the association between four unlinked candidate genes and pig meat quality.

A diagnosis method for physical systems using a multi-modeling approach; Utilisation de l'approche multi-modeles pour l'aide au diagnostic d'installations industrielles

Energy Technology Data Exchange (ETDEWEB)

Thetiot, R

2000-07-01

In this thesis we propose a method for diagnosis problem solving. This method is based on a multi-modeling approach describing both normal and abnormal behavior of a system. This modeling approach allows to represent a system at different abstraction levels (behavioral, functional and teleological). Fundamental knowledge is described according to a bond-graph representation. We show that bond-graph representation can be exploited in order to generate (completely or partially) the functional models. The different models of the multi-modeling approach allows to define the functional state of a system at different abstraction levels. We exploit this property to exonerate sub-systems for which the expected behavior is observed. The behavioral and functional descriptions of the remaining sub-systems are exploited hierarchically in a two steps process. In a first step, the abnormal behaviors explaining some observations are identified. In a second step, the remaining unexplained observations are used to generate conflict sets and thus the consistency based diagnoses. The modeling method and the diagnosis process have been applied to a Reactor Coolant Pump Sets. This application illustrates the concepts described in this thesis and shows its potentialities. (authors)

Leveling up? An inter-neighborhood experiment on parochialism and the efficiency of multi-level public goods provision

OpenAIRE

Gallier, Carlo; Goeschl, Timo; Kesternich, Martin; Lohse, Johannes; Reif, Christiane; Römer, Daniel

2017-01-01

Many public goods can be provided at different spatial levels. Evidence from social identity theory and in-group favoritism raises the possibility that where higher-level provision is more efficient, subjects’ narrow concern for local outcomes (parochialism) could harm efficiency. Building on the experimental paradigm of multi-level public good games and the ‘neighborhood attachment’ concept, we conduct an artefactual field experiment with 600 participants in a setting conducive to parochial...

Implementing evidence-based medicine in general practice: a focus group based study

Directory of Open Access Journals (Sweden)

Aertgeerts Bert

2005-09-01

Full Text Available Abstract Background Over the past years concerns are rising about the use of Evidence-Based Medicine (EBM in health care. The calls for an increase in the practice of EBM, seem to be obstructed by many barriers preventing the implementation of evidence-based thinking and acting in general practice. This study aims to explore the barriers of Flemish GPs (General Practitioners to the implementation of EBM in routine clinical work and to identify possible strategies for integrating EBM in daily work. Methods We used a qualitative research strategy to gather and analyse data. We organised focus groups between September 2002 and April 2003. The focus group data were analysed using a combined strategy of 'between-case' analysis and 'grounded theory approach'. Thirty-one general practitioners participated in four focus groups. Purposeful sampling was used to recruit participants. Results A basic classification model documents the influencing factors and actors on a micro-, meso- as well as macro-level. Patients, colleagues, competences, logistics and time were identified on the micro-level (the GPs' individual practice, commercial and consumer organisations on the meso-level (institutions, organisations and health care policy, media and specific characteristics of evidence on the macro-level (policy level and international scientific community. Existing barriers and possible strategies to overcome these barriers were described. Conclusion In order to implement EBM in routine general practice, an integrated approach on different levels needs to be developed.

An Ontological-Fuzzy Approach to Advance Reservation in Multi-Cluster Grids

International Nuclear Information System (INIS)

Ferreira, D J; Dantas, M A R; Bauer, Michael A

2010-01-01

Advance reservation is an important mechanism for a successful utilization of available resources in distributed multi-cluster environments. This mechanism allows, for example, a user to provide parameters aiming to satisfy requirements related to applications' execution time and temporal dependence. This predictability can lead the system to reach higher levels of QoS. However, the support for advance reservation has been restricted due to the complexity of large scale configurations and also dynamic changes verified in these systems. In this research work it is proposed an advance reservation method, based on a ontology-fuzzy approach. It allows a user to reserve a wide variety of resources and enable large jobs to be reserved among different nodes. In addition, it dynamically verifies the possibility of reservation with the local RMS, avoiding future allocation conflicts. Experimental results of the proposal, through simulation, indicate that the proposed mechanism reached a successful level of flexibility for large jobs and more appropriated distribution of resources in a distributed multi-cluster configuration.

An Ontological-Fuzzy Approach to Advance Reservation in Multi-Cluster Grids

Energy Technology Data Exchange (ETDEWEB)

Ferreira, D J; Dantas, M A R; Bauer, Michael A, E-mail: ded@inf.ufsc.br, E-mail: mario@inf.ufsc.br, E-mail: bauer@csd.uwo.ca

2010-11-01

Advance reservation is an important mechanism for a successful utilization of available resources in distributed multi-cluster environments. This mechanism allows, for example, a user to provide parameters aiming to satisfy requirements related to applications' execution time and temporal dependence. This predictability can lead the system to reach higher levels of QoS. However, the support for advance reservation has been restricted due to the complexity of large scale configurations and also dynamic changes verified in these systems. In this research work it is proposed an advance reservation method, based on a ontology-fuzzy approach. It allows a user to reserve a wide variety of resources and enable large jobs to be reserved among different nodes. In addition, it dynamically verifies the possibility of reservation with the local RMS, avoiding future allocation conflicts. Experimental results of the proposal, through simulation, indicate that the proposed mechanism reached a successful level of flexibility for large jobs and more appropriated distribution of resources in a distributed multi-cluster configuration.

Using pedagogical approaches to influence evidence-based practice integration - processes and recommendations: findings from a grounded theory study.

Science.gov (United States)

Malik, Gulzar; McKenna, Lisa; Griffiths, Debra

2017-04-01

The study aimed to explore the processes undertaken by nurse academics when integrating evidence-based practice (EBP) into their teaching and learning practices. This article focuses on pedagogical approaches employed by academics to influence evidence-based practice integration into undergraduate programs across Australian universities. Nursing academics are challenged to incorporate a variety of teaching and learning strategies to teach evidence-based practice and determine their effectiveness. However, literature suggests that there are limited studies available focusing on pedagogical approaches in evidence-based practice education. A constructivist grounded theory methodology, informed by Charmaz was used for this study. Data were collected during 2014 from 23 nurse academics across Australian universities through semi-structured interviews. Additionally, nine were observed during teaching of undergraduate students. Twenty subject outlines were also analysed following Charmaz's approach of data analysis. 'Influencing EBP integration' describes the pedagogical approaches employed by academics to incorporate EBP knowledge and skills into undergraduate curricula. With the use of various teaching and learning strategies, academics attempted to contextualize EBP by engaging students with activities aiming to link evidence to practice and with the EBP process. Although, some strategies appeared to be engaging, others were traditional and seemed to be disengaging for students due to the challenges experienced by participants that impeded the use of the most effective teaching methods. Study findings offer valuable insights into the teaching practices and identify some key challenges that require the adoption of appropriate strategies to ensure future nurses are well prepared in the paradigm of evidence-based practice. © 2016 John Wiley & Sons Ltd.

An examination of cross-cultural systems implementing evidence-based assessment and intervention approaches

Directory of Open Access Journals (Sweden)

Murray Laura K

2006-01-01

Full Text Available Implementation of evidence-based assessment and intervention approaches for youth with behavioral and/or emotional problems is rising to recognition worldwide. Feasibility research is critical to examine what characteristics of systems allow for success or barriers to the implementation of evidence-based practices into real-world settings, especially when working cross-culturally. This paper briefly reviews the experience of 4 international sites to understand how the overall structure and specific site variables directed the implementation of the World Health Organization and the World Psychiatry Association project. Discussion includes a thematic summary of the successes and challenges experienced by the sites, and future directions of feasibility studies.

Statin Selection in Qatar Based on Multi-indication Pharmacotherapeutic Multi-criteria Scoring Model, and Clinician Preference.

Science.gov (United States)

Al-Badriyeh, Daoud; Fahey, Michael; Alabbadi, Ibrahim; Al-Khal, Abdullatif; Zaidan, Manal

2015-12-01

Statin selection for the largest hospital formulary in Qatar is not systematic, not comparative, and does not consider the multi-indication nature of statins. There are no reports in the literature of multi-indication-based comparative scoring models of statins or of statin selection criteria weights that are based primarily on local clinicians' preferences and experiences. This study sought to comparatively evaluate statins for first-line therapy in Qatar, and to quantify the economic impact of this. An evidence-based, multi-indication, multi-criteria pharmacotherapeutic model was developed for the scoring of statins from the perspective of the main health care provider in Qatar. The literature and an expert panel informed the selection criteria of statins. Relative weighting of selection criteria was based on the input of the relevant local clinician population. Statins were comparatively scored based on literature evidence, with those exceeding a defined scoring threshold being recommended for use. With 95% CI and 5% margin of error, the scoring model was successfully developed. Selection criteria comprised 28 subcriteria under the following main criteria: clinical efficacy, best publish evidence and experience, adverse effects, drug interaction, dosing time, and fixed dose combination availability. Outcome measures for multiple indications were related to effects on LDL cholesterol, HDL cholesterol, triglyceride, total cholesterol, and C-reactive protein. Atorvastatin, pravastatin, and rosuvastatin exceeded defined pharmacotherapeutic thresholds. Atorvastatin and pravastatin were recommended as first-line use and rosuvastatin as a nonformulary alternative. It was estimated that this would produce a 17.6% cost savings in statins expenditure. Sensitivity analyses confirmed the robustness of the evaluation's outcomes against input uncertainties. Incorporating a comparative evaluation of statins in Qatari practices based on a locally developed, transparent, multi

A Transformational Approach to VHDL and CDFG Based High-Level Synthesis: a Case Study

NARCIS (Netherlands)

Middelhoek, Peter F.A.; Middelhoek, P.F.A.; Mekenkamp, G.E.; Molenkamp, Egbert; Krol, Th.

1995-01-01

In this paper, a novel multi-target design methodology based on the concepts of transformational design, and its application to the interlaced-to-progressive scan conversion (IPSC) problem, are discussed. Starting from a single high-level behavioral specification in VHDL a direction detector used in

Multi-model approach to characterize human handwriting motion.

Science.gov (United States)

Chihi, I; Abdelkrim, A; Benrejeb, M

2016-02-01

This paper deals with characterization and modelling of human handwriting motion from two forearm muscle activity signals, called electromyography signals (EMG). In this work, an experimental approach was used to record the coordinates of a pen tip moving on the (x, y) plane and EMG signals during the handwriting act. The main purpose is to design a new mathematical model which characterizes this biological process. Based on a multi-model approach, this system was originally developed to generate letters and geometric forms written by different writers. A Recursive Least Squares algorithm is used to estimate the parameters of each sub-model of the multi-model basis. Simulations show good agreement between predicted results and the recorded data.

A Multi-Scalar Approach to Theorizing Socio-Ecological Dynamics of Urban Residential Landscapes

Directory of Open Access Journals (Sweden)

Rinku Roy Chowdhury

2011-01-01

Full Text Available Urban residential expansion increasingly drives land use, land cover and ecological changes worldwide, yet social science theories explaining such change remain under-developed. Existing theories often focus on processes occurring at one scale, while ignoring other scales. Emerging evidence from four linked U.S. research sites suggests it is essential to examine processes at multiple scales simultaneously when explaining the evolution of urban residential landscapes. Additionally, focusing on urbanization dynamics across multiple sites with a shared research design may yield fruitful comparative insights. The following processes and social-hierarchical scales significantly influence the spatial configurations of residential landscapes: household-level characteristics and environmental attitudes; formal and informal institutions at the neighborhood scale; and municipal-scale land-use governance. While adopting a multi-scale and multi-site approach produces research challenges, doing so is critical to advancing understanding of coupled socio-ecological systems and associated vulnerabilities in a dynamic and environmentally important setting: residential landscapes.

Multi-level significance of vulnerability indicators. Case study: Eastern Romania

Science.gov (United States)

Stanga, I. C.; Grozavu, A.

2012-04-01

logistic regression, varimax rotation, multiple-criteria decision analysis, weight of evidence, multi-criteria evaluation method etc. The approach started from the local level which allows a functional and structural analysis and was progressively translated to an upper level and to a spatial analysis. The model shows that changing the level of analysis diminishes the functional significance of some indicators and increases the capacity of discretization in the case of others, highlighting the spatial and functional complexity of vulnerability.

Multi-Level Anomaly Detection on Time-Varying Graph Data

Energy Technology Data Exchange (ETDEWEB)

Bridges, Robert A [ORNL; Collins, John P [ORNL; Ferragut, Erik M [ORNL; Laska, Jason A [ORNL; Sullivan, Blair D [ORNL

2015-01-01

This work presents a novel modeling and analysis framework for graph sequences which addresses the challenge of detecting and contextualizing anomalies in labelled, streaming graph data. We introduce a generalization of the BTER model of Seshadhri et al. by adding flexibility to community structure, and use this model to perform multi-scale graph anomaly detection. Specifically, probability models describing coarse subgraphs are built by aggregating probabilities at finer levels, and these closely related hierarchical models simultaneously detect deviations from expectation. This technique provides insight into a graph's structure and internal context that may shed light on a detected event. Additionally, this multi-scale analysis facilitates intuitive visualizations by allowing users to narrow focus from an anomalous graph to particular subgraphs or nodes causing the anomaly. For evaluation, two hierarchical anomaly detectors are tested against a baseline Gaussian method on a series of sampled graphs. We demonstrate that our graph statistics-based approach outperforms both a distribution-based detector and the baseline in a labeled setting with community structure, and it accurately detects anomalies in synthetic and real-world datasets at the node, subgraph, and graph levels. To illustrate the accessibility of information made possible via this technique, the anomaly detector and an associated interactive visualization tool are tested on NCAA football data, where teams and conferences that moved within the league are identified with perfect recall, and precision greater than 0.786.

Assessment of Material Solutions of Multi-level Garage Structure Within Integrated Life Cycle Design Process

Science.gov (United States)

Wałach, Daniel; Sagan, Joanna; Gicala, Magdalena

2017-10-01

The paper presents an environmental and economic analysis of the material solutions of multi-level garage. The construction project approach considered reinforced concrete structure under conditions of use of ordinary concrete and high-performance concrete (HPC). Using of HPC allowed to significant reduction of reinforcement steel, mainly in compression elements (columns) in the construction of the object. The analysis includes elements of the methodology of integrated lice cycle design (ILCD). By making multi-criteria analysis based on established weight of the economic and environmental parameters, three solutions have been evaluated and compared within phase of material production (information modules A1-A3).

Exploring Wellness Interventions in Progressive Multiple Sclerosis: an Evidence-Based Review.

Science.gov (United States)

Venasse, Myriam; Edwards, Thomas; Pilutti, Lara A

2018-04-10

There has been recent interest in the role of lifestyle and wellness-based approaches in the treatment and management of multiple sclerosis (MS). These approaches may be particularly relevant for patients with progressive MS, considering limited therapeutic options currently available. The purpose of this review is to examine the role of wellness-based interventions including exercise training, emotional well-being therapies, and dietary modification in patients with progressive MS. We conducted a literature search on the efficacy of wellness-based interventions in patients with progressive MS published between 1985 and July 2017. The level of evidence for each trial was evaluated using the American Academy of Neurology criteria. Overall, 21 articles reporting on 16 wellness-based interventions were identified: ten trials involved exercise training, three involved emotional wellness therapies, two involved dietary modification, and one was a combined wellness intervention. There is level C evidence (possibly effective; one class II study) for the efficacy of aerobic exercise training on cardiorespiratory fitness in patients with progressive MS. There is level B evidence (probably effective; one class I study) for the efficacy of mindfulness training on psychological distress, depression, anxiety, pain, and quality of life in patients with progressive MS. There is inadequate evidence (level U) for efficacy of dietary modification (one class III study and one class IV study) and combined wellness interventions involving exercise training, meditation, and dietary modification (one class IV study). High-quality research is needed to provide evidence-based recommendations for wellness behaviors and lifestyle change in patients with progressive MS.

Multi person detection and tracking based on hierarchical level-set method

Science.gov (United States)

Khraief, Chadia; Benzarti, Faouzi; Amiri, Hamid

2018-04-01

In this paper, we propose an efficient unsupervised method for mutli-person tracking based on hierarchical level-set approach. The proposed method uses both edge and region information in order to effectively detect objects. The persons are tracked on each frame of the sequence by minimizing an energy functional that combines color, texture and shape information. These features are enrolled in covariance matrix as region descriptor. The present method is fully automated without the need to manually specify the initial contour of Level-set. It is based on combined person detection and background subtraction methods. The edge-based is employed to maintain a stable evolution, guide the segmentation towards apparent boundaries and inhibit regions fusion. The computational cost of level-set is reduced by using narrow band technique. Many experimental results are performed on challenging video sequences and show the effectiveness of the proposed method.

SYMPOSIUM REPORT: An Evidence-Based Approach to IBS and CIC: Applying New Advances to Daily Practice

Science.gov (United States)

Chey, William D.

2017-01-01

Many nonpharmacologic and pharmacologic therapies are available to manage irritable bowel syndrome (IBS) and chronic idiopathic constipation (CIC). The American College of Gastroenterology (ACG) regularly publishes reviews on IBS and CIC therapies. The most recent of these reviews was published by the ACG Task Force on the Management of Functional Bowel Disorders in 2014. The key objective of this review was to evaluate the efficacy of therapies for IBS or CIC compared with placebo or no treatment in randomized controlled trials. Evidence-based approaches to managing diarrhea-predominant IBS include dietary measures, such as a diet low in gluten and fermentable oligo-, di-, and monosaccharides and polyols (FODMAPs); loperamide; antispasmodics; peppermint oil; probiotics; tricyclic antidepressants; alosetron; eluxadoline, and rifaximin. Evidence-based approaches to managing constipation-predominant IBS and CIC include fiber, stimulant laxatives, polyethylene glycol, selective serotonin reuptake inhibitors, lubiprostone, and guanylate cyclase agonists. With the growing evidence base for IBS and CIC therapies, it has become increasingly important for clinicians to assess the quality of evidence and understand how to apply it to the care of individual patients. PMID:28729815

A desirability-based multi objective approach for the virtual screening discovery of broad-spectrum anti-gastric cancer agents.

Directory of Open Access Journals (Sweden)

Yunierkis Perez-Castillo

Full Text Available Gastric cancer is the third leading cause of cancer-related mortality worldwide and despite advances in prevention, diagnosis and therapy, it is still regarded as a global health concern. The efficacy of the therapies for gastric cancer is limited by a poor response to currently available therapeutic regimens. One of the reasons that may explain these poor clinical outcomes is the highly heterogeneous nature of this disease. In this sense, it is essential to discover new molecular agents capable of targeting various gastric cancer subtypes simultaneously. Here, we present a multi-objective approach for the ligand-based virtual screening discovery of chemical compounds simultaneously active against the gastric cancer cell lines AGS, NCI-N87 and SNU-1. The proposed approach relays in a novel methodology based on the development of ensemble models for the bioactivity prediction against each individual gastric cancer cell line. The methodology includes the aggregation of one ensemble per cell line using a desirability-based algorithm into virtual screening protocols. Our research leads to the proposal of a multi-targeted virtual screening protocol able to achieve high enrichment of known chemicals with anti-gastric cancer activity. Specifically, our results indicate that, using the proposed protocol, it is possible to retrieve almost 20 more times multi-targeted compounds in the first 1% of the ranked list than what is expected from a uniform distribution of the active ones in the virtual screening database. More importantly, the proposed protocol attains an outstanding initial enrichment of known multi-targeted anti-gastric cancer agents.

Community and evidence-based approaches to healthcare ...

International Development Research Centre (IDRC) Digital Library (Canada)

2016-04-29

Apr 29, 2016 ... This project developed community connections, shared cross-cultural teaching experiences, and fostered local community partnerships. Participants in the course were encouraged to continue providing evidence-based care throughout their careers. UniLúrio now plans to include the community-based ...

Stakeholder conceptualisation of multi-level HIV and AIDS determinants in a Black epicentre.

Science.gov (United States)

Brawner, Bridgette M; Reason, Janaiya L; Hanlon, Kelsey; Guthrie, Barbara; Schensul, Jean J

2017-09-01

HIV has reached epidemic proportions among African Americans in the USA but certain urban contexts appear to experience a disproportionate disease burden. Geographic information systems mapping in Philadelphia indicates increased HIV incidence and prevalence in predominantly Black census tracts, with major differences across adjacent communities. What factors shape these geographic HIV disparities among Black Philadelphians? This descriptive study was designed to refine and validate a conceptual model developed to better understand multi-level determinants of HIV-related risk among Black Philadelphians. We used an expanded ecological approach to elicit reflective perceptions from administrators, direct service providers and community members about individual, social and structural factors that interact to protect against or increase the risk for acquiring HIV within their community. Gender equity, social capital and positive cultural mores (e.g., monogamy, abstinence) were seen as the main protective factors. Historical negative contributory influences of racial residential segregation, poverty and incarceration were among the most salient risk factors. This study was a critical next step toward initiating theory-based, multi-level community-based HIV prevention initiatives.

Three essays on multi-level optimization models and applications

Science.gov (United States)

Rahdar, Mohammad

The general form of a multi-level mathematical programming problem is a set of nested optimization problems, in which each level controls a series of decision variables independently. However, the value of decision variables may also impact the objective function of other levels. A two-level model is called a bilevel model and can be considered as a Stackelberg game with a leader and a follower. The leader anticipates the response of the follower and optimizes its objective function, and then the follower reacts to the leader's action. The multi-level decision-making model has many real-world applications such as government decisions, energy policies, market economy, network design, etc. However, there is a lack of capable algorithms to solve medium and large scale these types of problems. The dissertation is devoted to both theoretical research and applications of multi-level mathematical programming models, which consists of three parts, each in a paper format. The first part studies the renewable energy portfolio under two major renewable energy policies. The potential competition for biomass for the growth of the renewable energy portfolio in the United States and other interactions between two policies over the next twenty years are investigated. This problem mainly has two levels of decision makers: the government/policy makers and biofuel producers/electricity generators/farmers. We focus on the lower-level problem to predict the amount of capacity expansions, fuel production, and power generation. In the second part, we address uncertainty over demand and lead time in a multi-stage mathematical programming problem. We propose a two-stage tri-level optimization model in the concept of rolling horizon approach to reducing the dimensionality of the multi-stage problem. In the third part of the dissertation, we introduce a new branch and bound algorithm to solve bilevel linear programming problems. The total time is reduced by solving a smaller relaxation

Settings for Physical Activity – Developing a Site-specific Physical Activity Behavior Model based on Multi-level Intervention Studies

DEFF Research Database (Denmark)

Troelsen, Jens; Klinker, Charlotte Demant; Breum, Lars

Settings for Physical Activity – Developing a Site-specific Physical Activity Behavior Model based on Multi-level Intervention Studies Introduction: Ecological models of health behavior have potential as theoretical framework to comprehend the multiple levels of factors influencing physical...... to be taken into consideration. A theoretical implication of this finding is to develop a site-specific physical activity behavior model adding a layered structure to the ecological model representing the determinants related to the specific site. Support: This study was supported by TrygFonden, Realdania...... activity (PA). The potential is shown by the fact that there has been a dramatic increase in application of ecological models in research and practice. One proposed core principle is that an ecological model is most powerful if the model is behavior-specific. However, based on multi-level interventions...

Enhancing the Teaching of Introductory Economics with a Team-Based, Multi-Section Competition

Science.gov (United States)

Beaudin, Laura; Berdiev, Aziz N.; Kaminaga, Allison Shwachman; Mirmirani, Sam; Tebaldi, Edinaldo

2017-01-01

The authors describe a unique approach to enhancing student learning at the introductory economics level that utilizes a multi-section, team-based competition. The competition is structured to supplement learning throughout the entire introductory course. Student teams are presented with current economic issues, trends, or events, and use economic…

Development of evidence-based clinical practice guidelines (CPGs: comparing approaches

Directory of Open Access Journals (Sweden)

Harris Claire

2008-10-01

Full Text Available Abstract Background While the potential of clinical practice guidelines (CPGs to support implementation of evidence has been demonstrated, it is not currently being achieved. CPGs are both poorly developed and ineffectively implemented. To improve clinical practice and health outcomes, both well-developed CPGs and effective methods of CPG implementation are needed. We sought to establish whether there is agreement on the fundamental characteristics of an evidence-based CPG development process and to explore whether the level of guidance provided in CPG development handbooks is sufficient for people using these handbooks to be able to apply it. Methods CPG development handbooks were identified through a broad search of published and grey literature. Documents published in English produced by national or international organisations purporting to support development of evidence-based CPGs were included. A list of 14 key elements of a CPG development process was developed. Two authors read each handbook. For each handbook a judgement was made as to how it addressed each element; assigned as: 'mentioned and clear guidance provided', 'mentioned but limited practical detail provided ', or 'not mentioned'. Results Six CPG development handbooks were included. These were produced by the Council of Europe, the National Health and Medical Research Council of Australia, the National Institute for Health and Clinical Excellence in the UK, the New Zealand Guidelines Group, the Scottish Intercollegiate Guideline Network, and the World Health Organization (WHO. There was strong concordance between the handbooks on the key elements of an evidence-based CPG development process. All six of the handbooks require and provide guidance on establishment of a multidisciplinary guideline development group, involvement of consumers, identification of clinical questions or problems, systematic searches for and appraisal of research evidence, a process for drafting

How Evidence-Based Teaching Practices Are Challenged by a Deweyan Approach to Education

Science.gov (United States)

Webster, R. Scott

2009-01-01

The claim is made in this paper that the discourse of education offers a challenge to evidence-based practices because this latter approach is embedded in the discourse of management. Although claiming the status of being "scientific", this latter development is drawn upon problematically by policy makers to provide the warrant for stipulating…

Morphing Wing Weight Predictors and Their Application in a Template-Based Morphing Aircraft Sizing Environment II. Part 2; Morphing Aircraft Sizing via Multi-level Optimization

Science.gov (United States)

Skillen, Michael D.; Crossley, William A.

2008-01-01

This report presents an approach for sizing of a morphing aircraft based upon a multi-level design optimization approach. For this effort, a morphing wing is one whose planform can make significant shape changes in flight - increasing wing area by 50% or more from the lowest possible area, changing sweep 30 or more, and/or increasing aspect ratio by as much as 200% from the lowest possible value. The top-level optimization problem seeks to minimize the gross weight of the aircraft by determining a set of "baseline" variables - these are common aircraft sizing variables, along with a set of "morphing limit" variables - these describe the maximum shape change for a particular morphing strategy. The sub-level optimization problems represent each segment in the morphing aircraft's design mission; here, each sub-level optimizer minimizes fuel consumed during each mission segment by changing the wing planform within the bounds set by the baseline and morphing limit variables from the top-level problem.

Intervention planning for a digital intervention for self-management of hypertension: a theory-, evidence- and person-based approach.

Science.gov (United States)

Band, Rebecca; Bradbury, Katherine; Morton, Katherine; May, Carl; Michie, Susan; Mair, Frances S; Murray, Elizabeth; McManus, Richard J; Little, Paul; Yardley, Lucy

2017-02-23

This paper describes the intervention planning process for the Home and Online Management and Evaluation of Blood Pressure (HOME BP), a digital intervention to promote hypertension self-management. It illustrates how a Person-Based Approach can be integrated with theory- and evidence-based approaches. The Person-Based Approach to intervention development emphasises the use of qualitative research to ensure that the intervention is acceptable, persuasive, engaging and easy to implement. Our intervention planning process comprised two parallel, integrated work streams, which combined theory-, evidence- and person-based elements. The first work stream involved collating evidence from a mixed methods feasibility study, a systematic review and a synthesis of qualitative research. This evidence was analysed to identify likely barriers and facilitators to uptake and implementation as well as design features that should be incorporated in the HOME BP intervention. The second work stream used three complementary approaches to theoretical modelling: developing brief guiding principles for intervention design, causal modelling to map behaviour change techniques in the intervention onto the Behaviour Change Wheel and Normalisation Process Theory frameworks, and developing a logic model. The different elements of our integrated approach to intervention planning yielded important, complementary insights into how to design the intervention to maximise acceptability and ease of implementation by both patients and health professionals. From the primary and secondary evidence, we identified key barriers to overcome (such as patient and health professional concerns about side effects of escalating medication) and effective intervention ingredients (such as providing in-person support for making healthy behaviour changes). Our guiding principles highlighted unique design features that could address these issues (such as online reassurance and procedures for managing concerns). Causal

Multi-Level Model

Directory of Open Access Journals (Sweden)

Constanta Nicoleta BODEA

2008-01-01

Full Text Available Is an original paper, which contains a hierarchical model with three levels, for determining the linearized non-homogeneous and homogeneous credibility premiums at company level, at sector level and at contract level, founded on the relevant covariance relations between the risk premium, the observations and the weighted averages. We give a rather explicit description of the input data for the multi- level hierarchical model used, only to show that in practical situations, there will always be enough data to apply credibility theory to a real insurance portfolio.

Integrated approach for fusion multi-physics coupled analyses based on hybrid CAD and mesh geometries

Energy Technology Data Exchange (ETDEWEB)

Qiu, Yuefeng, E-mail: yuefeng.qiu@kit.edu; Lu, Lei; Fischer, Ulrich

2015-10-15

Highlights: • Integrated approach for neutronics, thermal and structural analyses was developed. • MCNP5/6, TRIPOLI-4 were coupled with CFX, Fluent and ANSYS Workbench. • A novel meshing approach has been proposed for describing MC geometry. - Abstract: Coupled multi-physics analyses on fusion reactor devices require high-fidelity neutronic models, and flexible, accurate data exchanging between various calculation codes. An integrated coupling approach has been developed to enable the conversion of CAD, mesh, or hybrid geometries for Monte Carlo (MC) codes MCNP5/6, TRIPOLI-4, and translation of nuclear heating data for CFD codes Fluent, CFX and structural mechanical software ANSYS Workbench. The coupling approach has been implemented based on SALOME platform with CAD modeling, mesh generation and data visualization capabilities. A novel meshing approach has been developed for generating suitable meshes for MC geometry descriptions. The coupling approach has been concluded to be reliable and efficient after verification calculations of several application cases.

Modeling Performance in C4ISR Sustained Operations: A Multi-Level Approach (Briefing Charts)

National Research Council Canada - National Science Library

Barnes, Christopher; Miller, James C; Elliott, Linda; Coovert, Michael

2003-01-01

This briefing discusses methodology and preliminary findings focused on the application of multi-level modeling techniques to distinguish effects of sleep loss and task demands on individual and team...

Changing ‘Multi-Problem Families’ – Developing a Multi-Contextual Systemic Approach

Directory of Open Access Journals (Sweden)

2007-05-01

Full Text Available Over the past 30 years the Marlborough Family Service in London has pioneered multi-family work with marginalized families presenting simultaneously with abuse and neglect, family violence, substance misuse, educational failure and mental illness. The approach is based on a systemic multi-contextual mode and this chapter describes the evolving work, including the establishment of the first permanent multiple family day setting, specifically designed for and solely dedicated to the work with seemingly ‘hopeless’ families. The ingredients of ‘therapeutic assessments’ of parents and families are outlined and the importance of initial network meetings with professionals and family members is emphasized.

Improving the evidence for ecosystem-based adaptation

Energy Technology Data Exchange (ETDEWEB)

Reid, Hannah

2011-11-15

Ecosystem-based approaches to adaptation (EBA) integrate the use of biodiversity and ecosystem services into an overall strategy for helping people adapt to climate change. The body of scientific evidence that indicates how effective they are is in some cases lacking but in other cases is dispersed across a range of related fields, such as natural resource management, disaster risk reduction and agroecology, from which it needs to be synthesised. Without presenting and strengthening this evidence in a consolidated way, EBA cannot secure the policy traction at local, national and international levels that it merits.

Analysis of the Usage of Magnetic Force-directed Approach and Visual Techniques for Interactive Context-based Drawing of Multi-attributed Graphs

Directory of Open Access Journals (Sweden)

Zabiniako Vitaly

2014-12-01

Full Text Available In this article, the authors perform an analysis in order to assess adaptation of magnetic force-directed algorithms for context-based information extraction from multi-attributed graphs during visualization sessions. Theoretic standings behind magnetic force-directed approach are stated together with review on how particular features of respective algorithms in combination with appropriate visual techniques are especially suitable for improved processing and presenting of knowledge that is captured in form of graphs. The complexity of retrieving multi-attributed information within the proposed approach is handled with dedicated tools, such as selective attraction of nodes to MFE (Magnetic Force Emitter based on search criteria, localization of POI (Point of Interest regions, graph node anchoring, etc. Implicit compatibility of aforementioned tools with interactive nature of data exploration is distinguished. Description of case study, based on bibliometric network analysis is given, which is followed by the review of existing related works in this field. Conclusions are made and further studies in the field of visualization of multi-attributed graphs are defined.

Multi-level governance of forest resources (Editorial to the special feature

Directory of Open Access Journals (Sweden)

Esther Mwangi

2012-08-01

Full Text Available A major challenge for many researchers and practitioners relates to how to recognize and address cross-scale dynamics in space and over time in order to design and implement effective governance arrangements. This editorial provides an overview of the concept of multi-level governance (MLG. In particular we highlight definitional issues, why the concept matters as well as more practical concerns related to the processes and structure of multi-level governance. It is increasingly clear that multi-level governance of forest resources involves complex interactions of state, private and civil society actors at various levels, and institutions linking higher levels of social and political organization. Local communities are increasingly connected to global networks and influences. This creates new opportunities to learn and address problems but may also introduce new pressures and risks. We conclude by stressing the need for a much complex approach to the varieties of MLG to better understand how policies work as instruments of governance and to organize communities within systems of power and authority.

A new cut-based algorithm for the multi-state flow network reliability problem

International Nuclear Information System (INIS)

Yeh, Wei-Chang; Bae, Changseok; Huang, Chia-Ling

2015-01-01

Many real-world systems can be modeled as multi-state network systems in which reliability can be derived in terms of the lower bound points of level d, called d-minimal cuts (d-MCs). This study proposes a new method to find and verify obtained d-MCs with simple and useful found properties for the multi-state flow network reliability problem. The proposed algorithm runs in O(mσp) time, which represents a significant improvement over the previous O(mp 2 σ) time bound based on max-flow/min-cut, where p, σ and m denote the number of MCs, d-MC candidates and edges, respectively. The proposed algorithm also conquers the weakness of some existing methods, which failed to remove duplicate d-MCs in special cases. A step-by-step example is given to demonstrate how the proposed algorithm locates and verifies all d-MC candidates. As evidence of the utility of the proposed approach, we present extensive computational results on 20 benchmark networks in another example. The computational results compare favorably with a previously developed algorithm in the literature. - Highlights: • A new method is proposed to find all d-MCs for the multi-state flow networks. • The proposed method can prevent the generation of d-MC duplicates. • The proposed method is simpler and more efficient than the best-known algorithms

Historical perspectives on evidence-based nursing.

Science.gov (United States)

Beyea, Suzanne C; Slattery, Mary Jo

2013-04-01

The authors of this article offer a review and historical perspective on research utilization and evidence-based practice in nursing. They present the evolution of research utilization to the more contemporary framework of evidence-based nursing practice. The authors address the role of qualitative research in the context of evidence-based practice. Finally, some approaches and resources for learning more about the fundamentals of evidence-based healthcare are provided.

Multi-level iteration optimization for diffusive critical calculation

International Nuclear Information System (INIS)

Li Yunzhao; Wu Hongchun; Cao Liangzhi; Zheng Youqi

2013-01-01

In nuclear reactor core neutron diffusion calculation, there are usually at least three levels of iterations, namely the fission source iteration, the multi-group scattering source iteration and the within-group iteration. Unnecessary calculations occur if the inner iterations are converged extremely tight. But the convergence of the outer iteration may be affected if the inner ones are converged insufficiently tight. Thus, a common scheme suit for most of the problems was proposed in this work to automatically find the optimized settings. The basic idea is to optimize the relative error tolerance of the inner iteration based on the corresponding convergence rate of the outer iteration. Numerical results of a typical thermal neutron reactor core problem and a fast neutron reactor core problem demonstrate the effectiveness of this algorithm in the variational nodal method code NODAL with the Gauss-Seidel left preconditioned multi-group GMRES algorithm. The multi-level iteration optimization scheme reduces the number of multi-group and within-group iterations respectively by a factor of about 1-2 and 5-21. (authors)

Intelligent wear mode identification system for marine diesel engines based on multi-level belief rule base methodology

Science.gov (United States)

Yan, Xinping; Xu, Xiaojian; Sheng, Chenxing; Yuan, Chengqing; Li, Zhixiong

2018-01-01

Wear faults are among the chief causes of main-engine damage, significantly influencing the secure and economical operation of ships. It is difficult for engineers to utilize multi-source information to identify wear modes, so an intelligent wear mode identification model needs to be developed to assist engineers in diagnosing wear faults in diesel engines. For this purpose, a multi-level belief rule base (BBRB) system is proposed in this paper. The BBRB system consists of two-level belief rule bases, and the 2D and 3D characteristics of wear particles are used as antecedent attributes on each level. Quantitative and qualitative wear information with uncertainties can be processed simultaneously by the BBRB system. In order to enhance the efficiency of the BBRB, the silhouette value is adopted to determine referential points and the fuzzy c-means clustering algorithm is used to transform input wear information into belief degrees. In addition, the initial parameters of the BBRB system are constructed on the basis of expert-domain knowledge and then optimized by the genetic algorithm to ensure the robustness of the system. To verify the validity of the BBRB system, experimental data acquired from real-world diesel engines are analyzed. Five-fold cross-validation is conducted on the experimental data and the BBRB is compared with the other four models in the cross-validation. In addition, a verification dataset containing different wear particles is used to highlight the effectiveness of the BBRB system in wear mode identification. The verification results demonstrate that the proposed BBRB is effective and efficient for wear mode identification with better performance and stability than competing systems.

Evidence-based management: a literature review.

Science.gov (United States)

Young, Sam K

2002-05-01

This paper presents a review of evidence-based management (EBM), exploring whether management activities within healthcare have been, or can be, subject to the same scientific framework as clinical practice. The evidence-based approach was initially examined, noting the hierarchy of evidence ranging from randomized control trials to clinical anecdote. The literature varied in its degree of criticism of this approach; the most common concern referring to the assumed superiority of positivism. However, evidence-based practice was generally accepted as the best way forward. Stewart (1998) offered the only detailed exposition of EBM, outlining a necessary 'attitude of mind' both for EBM and for the creation of a research culture. However, the term 'clinical effectiveness' emerged as a possible replacement buzz-word for EBM (McClarey 1998). The term appears to encompass the sentiments of the evidence-based approach, but with a concomitant concern for economic factors. In this paper the author has examined the divide between those who viewed EBM as an activity for managers to make their own practice accountable and those who believed it to be a facilitative practice to help clinicians with evidence-based practice. Most papers acknowledged the limited research base for management activities within the health service and offered some explanation such as government policy constraints and lack of time. Nevertheless, the overall emphasis is that ideally there should be a management culture firmly based in evidence.

An Evidence-Based Medicine Approach to Antihyperglycemic Therapy in Diabetes Mellitus to Overcome Overtreatment.

Science.gov (United States)

Makam, Anil N; Nguyen, Oanh K

2017-01-10

Overtreatment is pervasive in medicine and leads to potential patient harms and excessive costs in health care. Although evidence-based medicine is often derided as practice by rote algorithmic medicine, the appropriate application of key evidence-based medicine principles in clinical decision making is fundamental to preventing overtreatment and promoting high-value, individualized patient-centered care. Specifically, this article discusses the importance of (1) using absolute rather than relative estimates of benefits to inform treatment decisions; (2) considering the time horizon to benefit of treatments; (3) balancing potential harms and benefits; and (4) using shared decision making by physicians to incorporate the patient's values and preferences into treatment decisions. Here, we illustrate the application of these principles to considering the decision of whether or not to recommend intensive glycemic control to patients to minimize microvascular and cardiovascular complications in type 2 diabetes mellitus. Through this lens, this example will illustrate how an evidence-based medicine approach can be used to individualize glycemic goals and prevent overtreatment, and can serve as a template for applying evidence-based medicine to inform treatment decisions for other conditions to optimize health and individualize patient care. © 2017 American Heart Association, Inc.

A simple network agreement-based approach for combining evidences in a heterogeneous sensor network

Directory of Open Access Journals (Sweden)

Raúl Eusebio-Grande

2015-12-01

Full Text Available In this research we investigate how the evidences provided by both static and mobile nodes that are part of a heterogenous sensor network can be combined to have trustworthy results. A solution relying on a network agreement-based approach was implemented and tested.

The Evidence-Based Manifesto for School Librarians

Science.gov (United States)

Todd, Ross

2008-01-01

School Library Journal's 2007 Leadership Summit, "Where's the Evidence? Understanding the Impact of School Libraries," focused on the topic of evidence-based practice. Evidence-based school librarianship is a systematic approach that engages research-derived evidence, school librarian-observed evidence, and user-reported evidence in the processes…

A multi-level biological approach to evaluate impacts of a major municipal effluent in wild St. Lawrence River yellow perch (Perca flavescens)

Energy Technology Data Exchange (ETDEWEB)

Houde, Magali, E-mail: magali.houde@ec.gc.ca [Centre Saint-Laurent, Environment Canada, 105 McGill Street, Montreal, QC H2Y 2E7 (Canada); Giraudo, Maeva, E-mail: maeva.giraudo@ec.gc.ca [Centre Saint-Laurent, Environment Canada, 105 McGill Street, Montreal, QC H2Y 2E7 (Canada); Douville, Mélanie, E-mail: melanie.douville@ec.gc.ca [Centre Saint-Laurent, Environment Canada, 105 McGill Street, Montreal, QC H2Y 2E7 (Canada); Bougas, Bérénice, E-mail: berenice.bougas.1@ulaval.ca [Institut de biologie intégrative et des systèmes, Université Laval, 1030, avenue de la Médecine, Québec, QC G1V 0A6 (Canada); Institut National de la Recherche Scientifique, Centre Eau Terre Environnement, 490 de la Couronne, Québec, QC G1K 9A9 (Canada); Couture, Patrice, E-mail: patrice.couture@ete.inrs.ca [Institut National de la Recherche Scientifique, Centre Eau Terre Environnement, 490 de la Couronne, Québec, QC G1K 9A9 (Canada); De Silva, Amila O., E-mail: amila.desilva@ec.gc.ca [Canada Centre for Inland Waters, Environment Canada, 867 Lakeshore Road, P.O. Box 5050, Burlington, ON L7R 4A6 (Canada); Spencer, Christine, E-mail: christine.spencer@ec.gc.ca [Canada Centre for Inland Waters, Environment Canada, 867 Lakeshore Road, P.O. Box 5050, Burlington, ON L7R 4A6 (Canada); Lair, Stéphane, E-mail: stephane.lair@umontreal.ca [Centre québécois sur la santé des animaux sauvages, Université de Montréal, C.P. 5000, St-Hyacinthe, QC J2S 7C6 (Canada); and others

2014-11-01

The development of integrated ecotoxicological approaches is of great interest in the investigation of global concerns such as impacts of municipal wastewater effluents on aquatic ecosystems. The objective of this study was to investigate the effects of a major wastewater municipal effluent on fish using a multi-level biological approach, from gene transcription and enzyme activities to histological changes. Yellow perch (Perca flavescens) were selected based on their wide distribution, their commercial and recreational importance, and the availability of a customized microarray. Yellow perch were sampled upstream of a major municipal wastewater treatment plant (WWTP) and 4 km and 10 km downstream from its point of discharge in the St. Lawrence River (Quebec, Canada). Concentrations of perfluoroalkyl substances (PFASs), polybrominated diphenyl ethers (PBDEs) and metals/trace elements in whole body homogenates were comparable to those from other industrialized regions of the world. Genomic results indicated that the transcription level of 177 genes was significantly different (p < 0.024) between exposed and non-exposed fish. Among these genes, 38 were found to be differentially transcribed at both downstream sites. Impacted genes were associated with biological processes and molecular functions such as immunity, detoxification, lipid metabolism/energy homeostasis (e.g., peroxisome proliferation), and retinol metabolism suggesting impact of WWTP on these systems. Moreover, antioxidant enzyme activities were more elevated in perch collected at the 4 km site. Biomarkers of lipid metabolism, biosynthetic activity, and aerobic capacities were significantly lower (p < 0.05) in fish residing near the outfall of the effluent. Histological examination of the liver indicated no differences between sites. Correlations between PFAS, PBDE, and metal/trace element tissue concentrations and markers of peroxisomal proliferation, oxidative stress, and retinoid metabolism were found

Interestingness measures and strategies for mining multi-ontology multi-level association rules from gene ontology annotations for the discovery of new GO relationships.

Science.gov (United States)

Manda, Prashanti; McCarthy, Fiona; Bridges, Susan M

2013-10-01

The Gene Ontology (GO), a set of three sub-ontologies, is one of the most popular bio-ontologies used for describing gene product characteristics. GO annotation data containing terms from multiple sub-ontologies and at different levels in the ontologies is an important source of implicit relationships between terms from the three sub-ontologies. Data mining techniques such as association rule mining that are tailored to mine from multiple ontologies at multiple levels of abstraction are required for effective knowledge discovery from GO annotation data. We present a data mining approach, Multi-ontology data mining at All Levels (MOAL) that uses the structure and relationships of the GO to mine multi-ontology multi-level association rules. We introduce two interestingness measures: Multi-ontology Support (MOSupport) and Multi-ontology Confidence (MOConfidence) customized to evaluate multi-ontology multi-level association rules. We also describe a variety of post-processing strategies for pruning uninteresting rules. We use publicly available GO annotation data to demonstrate our methods with respect to two applications (1) the discovery of co-annotation suggestions and (2) the discovery of new cross-ontology relationships. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

Generalist solutions to complex problems: generating practice-based evidence - the example of managing multi-morbidity

NARCIS (Netherlands)

Reeve, J.; Blakeman, T.; Freeman, G.K.; Green, L.A.; James, P.A.; Lucassen, P.L.; Martin, C.M.; Sturmberg, J.P.; Weel, C. van

2013-01-01

BACKGROUND: A growing proportion of people are living with long term conditions. The majority have more than one. Dealing with multi-morbidity is a complex problem for health systems: for those designing and implementing healthcare as well as for those providing the evidence informing practice. Yet

Governance and the Commons in a Multi-Level World

Directory of Open Access Journals (Sweden)

Derek Armitage

2007-11-01

Full Text Available Multi-level governance may facilitate learning and adaptation in complex social-ecological circumstances. Such arrangements should connect community-based management with regional/national government-level management, link scientific management and traditional management systems, encourage the sharing of knowledge and information, and promote collaboration and dialogue around goals and outcomes. Governance innovations of this type can thus build capacity to adapt to change and manage for resilience. However, critical reflection on the emergence of adaptive, multi-level governance for the commons is warranted. Drawing on examples from the North and South, the purpose of this review is to connect three complementary bodies of scholarship with insights for commons governance in a multi-level world: common property theory, resilience thinking and political ecology. From the commons and resilience literature, normative principles of adaptive, multi-level governance are synthesized (e.g., participation, accountability, leadership, knowledge pluralism, learning and trust. Political ecological interpretations, however, help to reveal the challenge of actualizing these principles and the contextual forces that make entrenched, top-down management systems resilient to change. These forces include the role of power, scale and levels of organization, knowledge valuation, the positioning of social actors and social constructions of nature. Also addressed are the policy narratives that shape governance, and the dialectic relationship among ecological systems and social change. tekst

Mass lesions in chronic pancreatitis: benign or malignant? An "evidence-based practice" approach.

LENUS (Irish Health Repository)

Gerstenmaier, Jan F

2012-02-01

The diagnosis of a pancreatic mass lesion in the presence of chronic pancreatitis can be extremely challenging. At the same time, a high level of certainty about the diagnosis is necessary for appropriate management planning. The aim of this study was to establish current best evidence about which imaging methods reliably differentiate a benign from a malignant lesion, and show how that evidence is best applied. A diagnostic algorithm based on Bayesian analysis is proposed.

Integrating physically based simulators with Event Detection Systems: Multi-site detection approach.

Science.gov (United States)

Housh, Mashor; Ohar, Ziv

2017-03-01

The Fault Detection (FD) Problem in control theory concerns of monitoring a system to identify when a fault has occurred. Two approaches can be distinguished for the FD: Signal processing based FD and Model-based FD. The former concerns of developing algorithms to directly infer faults from sensors' readings, while the latter uses a simulation model of the real-system to analyze the discrepancy between sensors' readings and expected values from the simulation model. Most contamination Event Detection Systems (EDSs) for water distribution systems have followed the signal processing based FD, which relies on analyzing the signals from monitoring stations independently of each other, rather than evaluating all stations simultaneously within an integrated network. In this study, we show that a model-based EDS which utilizes a physically based water quality and hydraulics simulation models, can outperform the signal processing based EDS. We also show that the model-based EDS can facilitate the development of a Multi-Site EDS (MSEDS), which analyzes the data from all the monitoring stations simultaneously within an integrated network. The advantage of the joint analysis in the MSEDS is expressed by increased detection accuracy (higher true positive alarms and fewer false alarms) and shorter detection time. Copyright © 2016 Elsevier Ltd. All rights reserved.

MATT: Multi Agents Testing Tool Based Nets within Nets

Directory of Open Access Journals (Sweden)

Sara Kerraoui

2016-12-01

As part of this effort, we propose a model based testing approach for multi agent systems based on such a model called Reference net, where a tool, which aims to providing a uniform and automated approach is developed. The feasibility and the advantage of the proposed approach are shown through a short case study.

A diagnosis method for physical systems using a multi-modeling approach; Utilisation de l'approche multi-modeles pour l'aide au diagnostic d'installations industrielles

Energy Technology Data Exchange (ETDEWEB)

Thetiot, R

2000-07-01

In this thesis we propose a method for diagnosis problem solving. This method is based on a multi-modeling approach describing both normal and abnormal behavior of a system. This modeling approach allows to represent a system at different abstraction levels (behavioral, functional and teleological). Fundamental knowledge is described according to a bond-graph representation. We show that bond-graph representation can be exploited in order to generate (completely or partially) the functional models. The different models of the multi-modeling approach allows to define the functional state of a system at different abstraction levels. We exploit this property to exonerate sub-systems for which the expected behavior is observed. The behavioral and functional descriptions of the remaining sub-systems are exploited hierarchically in a two steps process. In a first step, the abnormal behaviors explaining some observations are identified. In a second step, the remaining unexplained observations are used to generate conflict sets and thus the consistency based diagnoses. The modeling method and the diagnosis process have been applied to a Reactor Coolant Pump Sets. This application illustrates the concepts described in this thesis and shows its potentialities. (authors)

Just how multi-level is leadership research? : A document co-citation analysis 1980–2013 on leadership constructs and outcomes

NARCIS (Netherlands)

Batistic, S.; Cerne, Matej; Vogel, Bernd

2017-01-01

The use of multi-level theories and methodologies in leadership has gained momentum in recent years. However, the leadership field still suffers from a fragmented and unclear evolution and practice of multi-level approaches. The questions of how and to what extent multi-level research has evolved in

Experimental researches and comparison on aerodynamic parameters and cleaning efficiency of multi-level multi-channel cyclone

Directory of Open Access Journals (Sweden)

Aleksandras Chlebnikovas

2015-10-01

Full Text Available Multi-level multi-channel cyclone – the lately designed air cleaning device that can remove ultra-fine 20 μm particulatematter (PM from dusted air and reach over 95% of the overall cleaning efficiency. Multi-channel cyclone technology is based on centrifugal forces and has the resulting additional filtering process operation. Multi-level structure of cyclone allows to achieve higher air flow cleaning capacity at the same dimensions of the device, thus saving installation space required for the job, production and operating costs. Studies have examined the air flow parameters change in one–, two– and three–levels multichannel cyclone. These constructions differ according to the productivity of cleaned air under the constant peripheral and transitional (50/50 case air flow relations. Accordance with the results of air flow dynamics – velocity distribution of multi-channel cyclone, aerodynamic resistance and efficiency can be judged on the flow turbulence, the flow channel cross-section and select the most appropriate application. Cleaning efficiency studies were carried out using fine granite and wood ashes PM. The maximum cleaning efficiency was 93.3%, at an average of 4.5 g/m3, the aerodynamic resistance was equal to 1525 Pa.

An integrated approach for multi-level sample size determination

International Nuclear Information System (INIS)

Lu, M.S.; Teichmann, T.; Sanborn, J.B.

1997-01-01

Inspection procedures involving the sampling of items in a population often require steps of increasingly sensitive measurements, with correspondingly smaller sample sizes; these are referred to as multilevel sampling schemes. In the case of nuclear safeguards inspections verifying that there has been no diversion of Special Nuclear Material (SNM), these procedures have been examined often and increasingly complex algorithms have been developed to implement them. The aim in this paper is to provide an integrated approach, and, in so doing, to describe a systematic, consistent method that proceeds logically from level to level with increasing accuracy. The authors emphasize that the methods discussed are generally consistent with those presented in the references mentioned, and yield comparable results when the error models are the same. However, because of its systematic, integrated approach the proposed method elucidates the conceptual understanding of what goes on, and, in many cases, simplifies the calculations. In nuclear safeguards inspections, an important aspect of verifying nuclear items to detect any possible diversion of nuclear fissile materials is the sampling of such items at various levels of sensitivity. The first step usually is sampling by ''attributes'' involving measurements of relatively low accuracy, followed by further levels of sampling involving greater accuracy. This process is discussed in some detail in the references given; also, the nomenclature is described. Here, the authors outline a coordinated step-by-step procedure for achieving such multilevel sampling, and they develop the relationships between the accuracy of measurement and the sample size required at each stage, i.e., at the various levels. The logic of the underlying procedures is carefully elucidated; the calculations involved and their implications, are clearly described, and the process is put in a form that allows systematic generalization

A new integrated approach to demonstrate the safe disposal of high-level radioactive waste and spent nuclear fuel in a geological repository

International Nuclear Information System (INIS)

Mueller-Hoeppe, N.; Krone, J.; Niehues, N.; Raitz von Frentz, R.

2000-01-01

Multi-barrier systems are accepted as the basic approach for long term environmental safe isolation of radioactive waste in geological repositories. Assessing the performance of natural and engineered barriers is one of the major difficulties in producing evidence of environmental safety for any radioactive waste disposal facility, due to the enormous complexity of scenarios and uncertainties to be considered. This paper outlines a new methodological approach originally developed basically for a repository in salt, but that can be transferred with minor modifications to any other host rock formation. The approach is based on the integration of following elements: (1) Implementation of a simple method and efficient criteria to assess and prove the tightness of geological and engineered barriers; (2) Using the method of Partial Safety Factors in order to assess barrier performance at certain reasonable level of confidence; (3) Integration of a diverse geochemical barrier in the near field of waste emplacement limiting systematically the radiological consequences from any radionuclide release in safety investigations and (4) Risk based approach for the assessment of radionuclide releases. Indicative calculations performed with extremely conservative assumptions allowed to exclude any radiological health consequences from a HLW repository in salt to a reference person with a safety level of 99,9999% per year. (author)

Feature-Fusion Guidelines for Image-Based Multi-Modal Biometric Fusion

Directory of Open Access Journals (Sweden)

Dane Brown

2017-07-01

Full Text Available The feature level, unlike the match score level, lacks multi-modal fusion guidelines. This work demonstrates a new approach for improved image-based biometric feature-fusion. The approach extracts and combines the face, fingerprint and palmprint at the feature level for improved human identification accuracy. Feature-fusion guidelines, proposed in our recent work, are extended by adding a new face segmentation method and the support vector machine classifier. The new face segmentation method improves the face identification equal error rate (EER by 10%. The support vector machine classifier combined with the new feature selection approach, proposed in our recent work, outperforms other classifiers when using a single training sample. Feature-fusion guidelines take the form of strengths and weaknesses as observed in the applied feature processing modules during preliminary experiments. The guidelines are used to implement an effective biometric fusion system at the feature level, using a novel feature-fusion methodology, reducing the EER of two groups of three datasets namely: SDUMLA face, SDUMLA fingerprint and IITD palmprint; MUCT Face, MCYT Fingerprint and CASIA Palmprint.

Establishing a multi-proxy approach to alpine blockfield evolution in south-central Norway

Directory of Open Access Journals (Sweden)

Philipp Marr

2017-11-01

Full Text Available Blockfields in high latitude mountain areas are a wide spread proxy for glaciation history. Their origin is debated since decades, especially in south-central Norway, where glaciation had a major global climate implication. Some authors explain old blockfield features by protection of cold-based ice, others claim they persisted as nunataks during the LGM (~20 kyr, or were formed throughout the Holocene. In order to clarify the origin of alpine blockfields we established a multi-method approach to combining lichenometry, stratigraphy, granulometry, and geochemistry (XRD, XRF. Our lichenometric dating results in conjunction with our factors indicate landscape stability for at least ~12.5 kyr. Frequent climatic shifts are evident in our profiles by varying color, LOI content and grain sizes. On the basis of geochemical analyses we were able to identify a long-term (chemical weathering history and in situ blockfield formation. The field evidences and the climatic setting of the study area leave the possibility that our location was not covered by cold-based ice during the Late-Quaternary.

Development of a multi-epitope peptide vaccine inducing robust T cell responses against brucellosis using immunoinformatics based approaches.

Science.gov (United States)

Saadi, Mahdiye; Karkhah, Ahmad; Nouri, Hamid Reza

2017-07-01

Current investigations have demonstrated that a multi-epitope peptide vaccine targeting multiple antigens could be considered as an ideal approach for prevention and treatment of brucellosis. According to the latest findings, the most effective immunogenic antigens of brucella to induce immune responses are included Omp31, BP26, BLS, DnaK and L7-L12. Therefore, in the present study, an in silico approach was used to design a novel multi-epitope vaccine to elicit a desirable immune response against brucellosis. First, five novel T-cell epitopes were selected from Omp31, BP26, BLS, DnaK and L7-L12 proteins using different servers. In addition, helper epitopes selected from Tetanus toxin fragment C (TTFrC) were applied to induce CD4+ helper T lymphocytes (HTLs) responses. Selected epitopes were fused together by GPGPG linkers to facilitate the immune processing and epitope presentation. Moreover, cholera toxin B (CTB) was linked to N terminal of vaccine construct as an adjuvant by using EAAAK linker. A multi-epitope vaccine was designed based on predicted epitopes which was 377 amino acid residues in length. Then, the physico-chemical properties, secondary and tertiary structures, stability, intrinsic protein disorder, solubility and allergenicity of this multi-epitope vaccine were assessed using immunoinformatics tools and servers. Based on obtained results, a soluble, and non-allergic protein with 40.59kDa molecular weight was constructed. Expasy ProtParam classified this chimeric protein as a stable protein and also 89.8% residues of constructed vaccine were located in favored regions of the Ramachandran plot. Furthermore, this multi-epitope peptide vaccine was able to strongly induce T cell and B-cell mediated immune responses. In conclusion, immunoinformatics analysis indicated that this multi-epitope peptide vaccine can be effectively expressed and potentially be used for prophylactic or therapeutic usages against brucellosis. Copyright © 2017 Elsevier B.V. All

An Internet of Things Based Multi-Level Privacy-Preserving Access Control for Smart Living

Directory of Open Access Journals (Sweden)

Usama Salama

2018-05-01

Full Text Available The presence of the Internet of Things (IoT in healthcare through the use of mobile medical applications and wearable devices allows patients to capture their healthcare data and enables healthcare professionals to be up-to-date with a patient’s status. Ambient Assisted Living (AAL, which is considered as one of the major applications of IoT, is a home environment augmented with embedded ambient sensors to help improve an individual’s quality of life. This domain faces major challenges in providing safety and security when accessing sensitive health data. This paper presents an access control framework for AAL which considers multi-level access and privacy preservation. We focus on two major points: (1 how to use the data collected from ambient sensors and biometric sensors to perform the high-level task of activity recognition; and (2 how to secure the collected private healthcare data via effective access control. We achieve multi-level access control by extending Public Key Infrastructure (PKI for secure authentication and utilizing Attribute-Based Access Control (ABAC for authorization. The proposed access control system regulates access to healthcare data by defining policy attributes over healthcare professional groups and data classes classifications. We provide guidelines to classify the data classes and healthcare professional groups and describe security policies to control access to the data classes.

An improved AE detection method of rail defect based on multi-level ANC with VSS-LMS

Science.gov (United States)

Zhang, Xin; Cui, Yiming; Wang, Yan; Sun, Mingjian; Hu, Hengshan

2018-01-01

In order to ensure the safety and reliability of railway system, Acoustic Emission (AE) method is employed to investigate rail defect detection. However, little attention has been paid to the defect detection at high speed, especially for noise interference suppression. Based on AE technology, this paper presents an improved rail defect detection method by multi-level ANC with VSS-LMS. Multi-level noise cancellation based on SANC and ANC is utilized to eliminate complex noises at high speed, and tongue-shaped curve with index adjustment factor is proposed to enhance the performance of variable step-size algorithm. Defect signals and reference signals are acquired by the rail-wheel test rig. The features of noise signals and defect signals are analyzed for effective detection. The effectiveness of the proposed method is demonstrated by comparing with the previous study, and different filter lengths are investigated to obtain a better noise suppression performance. Meanwhile, the detection ability of the proposed method is verified at the top speed of the test rig. The results clearly illustrate that the proposed method is effective in detecting rail defects at high speed, especially for noise interference suppression.

Implementing health promotion activities using community-engaged approaches in Asian American faith-based organizations in New York City and New Jersey.

Science.gov (United States)

Kwon, S C; Patel, S; Choy, C; Zanowiak, J; Rideout, C; Yi, S; Wyatt, L; Taher, M D; Garcia-Dia, M J; Kim, S S; Denholm, T K; Kavathe, R; Islam, N S

2017-09-01

Faith-based organizations (FBOs) (e.g., churches, mosques, and gurdwaras) can play a vital role in health promotion. The Racial and Ethnic Approaches to Community Health for Asian Americans (REACH FAR) Project is implementing a multi-level and evidence-based health promotion and hypertension (HTN) control program in faith-based organizations serving Asian American (AA) communities (Bangladeshi, Filipino, Korean, Asian Indian) across multiple denominations (Christian, Muslim, and Sikh) in New York/New Jersey (NY/NJ). This paper presents baseline results and describes the cultural adaptation and implementation process of the REACH FAR program across diverse FBOs and religious denominations serving AA subgroups. Working with 12 FBOs, informed by implementation research and guided by a cultural adaptation framework and community-engaged approaches, REACH FAR strategies included (1) implementing healthy food policies for communal meals and (2) delivering a culturally-linguistically adapted HTN management coaching program. Using the Ecological Validity Model (EVM), the program was culturally adapted across congregation and faith settings. Baseline measures include (i) Congregant surveys assessing social norms and diet (n = 946), (ii) HTN participant program surveys (n = 725), (iii) FBO environmental strategy checklists (n = 13), and (iv) community partner in-depth interviews assessing project feasibility (n = 5). We describe the adaptation process and baseline assessments of FBOs. In year 1, we reached 3790 (nutritional strategies) and 725 (HTN program) via AA FBO sites. Most AA FBOs lack nutrition policies and present prime opportunities for evidence-based multi-level interventions. REACH FAR presents a promising health promotion implementation program that may result in significant community reach.

Evidence-based monitoring and evaluation of the faith-based ...

African Journals Online (AJOL)

Background: The Islamic Medical Association of Uganda, has been implementing the faith-based approach to HIV prevention without baseline data on expected positive outcomes. Objectives: To establish evidence-based baseline data on expected positive outcomes of the faith-based approach to HIV prevention. Methods: ...

Physical Layer Multi-Core Prototyping A Dataflow-Based Approach for LTE eNodeB

CERN Document Server

Pelcat, Maxime; Piat, Jonathan; Nezan, Jean-François

2013-01-01

Base stations developed according to the 3GPP Long Term Evolution (LTE) standard require unprecedented processing power. 3GPP LTE enables data rates beyond hundreds of Mbits/s by using advanced technologies, necessitating a highly complex LTE physical layer. The operating power of base stations is a significant cost for operators, and is currently optimized using state-of-the-art hardware solutions, such as heterogeneous distributed systems. The traditional system design method of porting algorithms to heterogeneous distributed systems based on test-and-refine methods is a manual, thus time-expensive, task.   Physical Layer Multi-Core Prototyping: A Dataflow-Based Approach for LTE eNodeB provides a clear introduction to the 3GPP LTE physical layer and to dataflow-based prototyping and programming. The difficulties in the process of 3GPP LTE physical layer porting are outlined, with particular focus on automatic partitioning and scheduling, load balancing and computation latency reduction, specifically in sys...

Risk Evaluation of Railway Coal Transportation Network Based on Multi Level Grey Evaluation Model

Science.gov (United States)

Niu, Wei; Wang, Xifu

2018-01-01

The railway transport mode is currently the most important way of coal transportation, and now China’s railway coal transportation network has become increasingly perfect, but there is still insufficient capacity, some lines close to saturation and other issues. In this paper, the theory and method of risk assessment, analytic hierarchy process and multi-level gray evaluation model are applied to the risk evaluation of coal railway transportation network in China. Based on the example analysis of Shanxi railway coal transportation network, to improve the internal structure and the competitiveness of the market.

Multi-Cohort Stand Structural Classification: Ground- and LiDAR-based Approaches for Boreal Mixedwood and Black Spruce Forest Types of Northeastern Ontario

Science.gov (United States)

Kuttner, Benjamin George

Natural fire return intervals are relatively long in eastern Canadian boreal forests and often allow for the development of stands with multiple, successive cohorts of trees. Multi-cohort forest management (MCM) provides a strategy to maintain such multi-cohort stands that focuses on three broad phases of increasingly complex, post-fire stand development, termed "cohorts", and recommends different silvicultural approaches be applied to emulate different cohort types. Previous research on structural cohort typing has relied upon primarily subjective classification methods; in this thesis, I develop more comprehensive and objective methods for three common boreal mixedwood and black spruce forest types in northeastern Ontario. Additionally, I examine relationships between cohort types and stand age, productivity, and disturbance history and the utility of airborne LiDAR to retrieve ground-based classifications and to extend structural cohort typing from plot- to stand-levels. In both mixedwood and black spruce forest types, stand age and age-related deadwood features varied systematically with cohort classes in support of an age-based interpretation of increasing cohort complexity. However, correlations of stand age with cohort classes were surprisingly weak. Differences in site productivity had a significant effect on the accrual of increasingly complex multi-cohort stand structure in both forest types, especially in black spruce stands. The effects of past harvesting in predictive models of class membership were only significant when considered in isolation of age. As an age-emulation strategy, the three cohort model appeared to be poorly suited to black spruce forests where the accrual of structural complexity appeared to be more a function of site productivity than age. Airborne LiDAR data appear to be particularly useful in recovering plot-based cohort types and extending them to the stand-level. The main gradients of structural variability detected using Li

Multi-level damage identification with response reconstruction

Science.gov (United States)

Zhang, Chao-Dong; Xu, You-Lin

2017-10-01

Damage identification through finite element (FE) model updating usually forms an inverse problem. Solving the inverse identification problem for complex civil structures is very challenging since the dimension of potential damage parameters in a complex civil structure is often very large. Aside from enormous computation efforts needed in iterative updating, the ill-condition and non-global identifiability features of the inverse problem probably hinder the realization of model updating based damage identification for large civil structures. Following a divide-and-conquer strategy, a multi-level damage identification method is proposed in this paper. The entire structure is decomposed into several manageable substructures and each substructure is further condensed as a macro element using the component mode synthesis (CMS) technique. The damage identification is performed at two levels: the first is at macro element level to locate the potentially damaged region and the second is over the suspicious substructures to further locate as well as quantify the damage severity. In each level's identification, the damage searching space over which model updating is performed is notably narrowed down, not only reducing the computation amount but also increasing the damage identifiability. Besides, the Kalman filter-based response reconstruction is performed at the second level to reconstruct the response of the suspicious substructure for exact damage quantification. Numerical studies and laboratory tests are both conducted on a simply supported overhanging steel beam for conceptual verification. The results demonstrate that the proposed multi-level damage identification via response reconstruction does improve the identification accuracy of damage localization and quantization considerably.

Exploring Multi-Scale Spatiotemporal Twitter User Mobility Patterns with a Visual-Analytics Approach

Directory of Open Access Journals (Sweden)

Junjun Yin

2016-10-01

Full Text Available Understanding human mobility patterns is of great importance for urban planning, traffic management, and even marketing campaign. However, the capability of capturing detailed human movements with fine-grained spatial and temporal granularity is still limited. In this study, we extracted high-resolution mobility data from a collection of over 1.3 billion geo-located Twitter messages. Regarding the concerns of infringement on individual privacy, such as the mobile phone call records with restricted access, the dataset is collected from publicly accessible Twitter data streams. In this paper, we employed a visual-analytics approach to studying multi-scale spatiotemporal Twitter user mobility patterns in the contiguous United States during the year 2014. Our approach included a scalable visual-analytics framework to deliver efficiency and scalability in filtering large volume of geo-located tweets, modeling and extracting Twitter user movements, generating space-time user trajectories, and summarizing multi-scale spatiotemporal user mobility patterns. We performed a set of statistical analysis to understand Twitter user mobility patterns across multi-level spatial scales and temporal ranges. In particular, Twitter user mobility patterns measured by the displacements and radius of gyrations of individuals revealed multi-scale or multi-modal Twitter user mobility patterns. By further studying such mobility patterns in different temporal ranges, we identified both consistency and seasonal fluctuations regarding the distance decay effects in the corresponding mobility patterns. At the same time, our approach provides a geo-visualization unit with an interactive 3D virtual globe web mapping interface for exploratory geo-visual analytics of the multi-level spatiotemporal Twitter user movements.

Evidence-based approach to the treatment of hidradenitis suppurativa/acne inversa, based on the European guidelines for hidradenitis suppurativa

NARCIS (Netherlands)

W.P. Gulliver (Wayne P.); C.C. Zouboulis (Christos C.); E.P. Prens (Errol); G.B.E. Jemec (Gregor); T. Tzellos (Thrasivoulos)

2016-01-01

textabstractHidradenitis suppurativa/acne inversa (HS) is a chronic inflammatory skin disease characterized by painful, recurrent nodules and abscesses that rupture and lead to sinus tracts and scarring. To date, an evidence-based therapeutic approach has not been the standard of care and this is

Multi-label literature classification based on the Gene Ontology graph

Directory of Open Access Journals (Sweden)

Lu Xinghua

2008-12-01

Full Text Available Abstract Background The Gene Ontology is a controlled vocabulary for representing knowledge related to genes and proteins in a computable form. The current effort of manually annotating proteins with the Gene Ontology is outpaced by the rate of accumulation of biomedical knowledge in literature, which urges the development of text mining approaches to facilitate the process by automatically extracting the Gene Ontology annotation from literature. The task is usually cast as a text classification problem, and contemporary methods are confronted with unbalanced training data and the difficulties associated with multi-label classification. Results In this research, we investigated the methods of enhancing automatic multi-label classification of biomedical literature by utilizing the structure of the Gene Ontology graph. We have studied three graph-based multi-label classification algorithms, including a novel stochastic algorithm and two top-down hierarchical classification methods for multi-label literature classification. We systematically evaluated and compared these graph-based classification algorithms to a conventional flat multi-label algorithm. The results indicate that, through utilizing the information from the structure of the Gene Ontology graph, the graph-based multi-label classification methods can significantly improve predictions of the Gene Ontology terms implied by the analyzed text. Furthermore, the graph-based multi-label classifiers are capable of suggesting Gene Ontology annotations (to curators that are closely related to the true annotations even if they fail to predict the true ones directly. A software package implementing the studied algorithms is available for the research community. Conclusion Through utilizing the information from the structure of the Gene Ontology graph, the graph-based multi-label classification methods have better potential than the conventional flat multi-label classification approach to facilitate

An Evidence Based Approach to Designing Medical Support for Long Duration, Interplanetary Missions

Science.gov (United States)

Watkins, S. D.; McGrath, T. L.; Bauman, D. K.; Wu, J. H.; Barsten, K. N.; Barr, Y. R.; Kerstman, E. L.

2011-01-01

The Exploration Medical Capability (ExMC) element is one of six elements under NASA's Human Research Program (HRP). The goal of the ExMC element is to address the risk of the "inability to adequately recognize or treat an ill or injured crewmember." This poster highlights the evidence-based approach that the ExMC element has taken to address this goal, and the ExMC element's current areas of interest.

Multi-scale Modeling Approach for Design and Optimization of Oleochemical Processes

DEFF Research Database (Denmark)

Jones, Mark Nicholas; Forero-Hernandez, Hector Alexander; Sarup, Bent

2017-01-01

The primary goal of this work is to present a systematic methodology and software frameworkfor a multi-level approach ranging from process synthesis and modeling throughproperty prediction, to sensitivity analysis, property parameter tuning and optimization.This framework is applied to the follow...

Integrating remote sensing with GIS-based multi-criteria evaluation approach for Karst rocky desertification assessment in Southwest of China

International Nuclear Information System (INIS)

Zhang, Z; Xu, W; Zhou, W; Zhang, L; Xiao, Y; Ouyang, Z; Ou, X

2014-01-01

The increasing exploitation of Karst resources is leading to severe environmental impacts, as Karst frequently occurs in the most fragile and vulnerable environments. This paper presents a multi-criteria evaluation (MCE) approach in a spatial context to support Karst rocky desertification (KRD) assessment by integrating remote sensing data with GIS. The study area is located in Wenshan Prefecture, Yunnan Province, Southwest of China. Criteria and impact factors for KRD first were identified and weighted through pairwise comparison method. A GIS fuzzy set membership function was then used to generate gradient effects of each criterion, and a clustering method based on K-mean algorithms was used to classify KRD into several descending rank zones (or levels). Both ROC and error matrix assessments indicated that the MCE approach is better than the NDVI approach. In addition, we found it is useful to integrate the topographic and human disturbance factors into KRD mapping and assessment, compared with most of the previous KRD assessment studies mainly focused on developing vegetation or land cover information in karst regions by using remote sensing alone. Furthermore, the integrated MCE approach is robust, flexible, and easy to be implemented. It also explicitly includes the quantitative and qualitative information, for instance, opinions of decision makers and experts as well as characteristics of the landscape

Component- and system-level degradation modeling of digital Instrumentation and Control systems based on a Multi-State Physics Modeling Approach

International Nuclear Information System (INIS)

Wang, Wei; Di Maio, Francesco; Zio, Enrico

2016-01-01

Highlights: • A Multi-State Physics Modeling (MSPM) framework for reliability assessment is proposed. • Monte Carlo (MC) simulation is utilized to estimate the degradation state probability. • Due account is given to stochastic uncertainty and deterministic degradation progression. • The MSPM framework is applied to the reliability assessment of a digital I&C system. • Results are compared with the results obtained with a Markov Chain Model (MCM). - Abstract: A system-level degradation modeling is proposed for the reliability assessment of digital Instrumentation and Control (I&C) systems in Nuclear Power Plants (NPPs). At the component level, we focus on the reliability assessment of a Resistance Temperature Detector (RTD), which is an important digital I&C component used to guarantee the safe operation of NPPs. A Multi-State Physics Model (MSPM) is built to describe this component degradation progression towards failure and Monte Carlo (MC) simulation is used to estimate the probability of sojourn in any of the previously defined degradation states, by accounting for both stochastic and deterministic processes that affect the degradation progression. The MC simulation relies on an integrated modeling of stochastic processes with deterministic aging of components that results to be fundamental for estimating the joint cumulative probability distribution of finding the component in any of the possible degradation states. The results of the application of the proposed degradation model to a digital I&C system of literature are compared with the results obtained by a Markov Chain Model (MCM). The integrated stochastic-deterministic process here proposed to drive the MC simulation is viable to integrate component-level models into a system-level model that would consider inter-system or/and inter-component dependencies and uncertainties.

History of evidence-based medicine

Directory of Open Access Journals (Sweden)

Roger L Sur

2011-01-01

Full Text Available This essay reviews the historical circumstances surrounding the introduction and evolution of evidence-based medicine. Criticisms of the approach are also considered. Weaknesses of existing standards of clinical practice and efforts to bring more certainty to clinical decision making were the foundation for evidence-based medicine, which integrates epidemiology and medical research. Because of its utility in designing randomized clinical trials, assessing the quality of the literature, and applying medical research at the bedside, evidence-based medicine will continue to have a strong influence on everyday clinical practice.

Evidence-based approach to the treatment of hidradenitis suppurativa/acne inversa, based on the European guidelines for hidradenitis suppurativa

DEFF Research Database (Denmark)

Gulliver, Wayne; Zouboulis, Christos C.; Prens, Errol

2016-01-01

Hidradenitis suppurativa/acne inversa (HS) is a chronic inflammatory skin disease characterized by painful, recurrent nodules and abscesses that rupture and lead to sinus tracts and scarring. To date, an evidence-based therapeutic approach has not been the standard of care and this is likely due...

Multi-objective approach in thermoenvironomic optimization of a benchmark cogeneration system

International Nuclear Information System (INIS)

Sayyaadi, Hoseyn

2009-01-01

Multi-objective optimization for designing of a benchmark cogeneration system known as CGAM cogeneration system has been performed. In optimization approach, the exergetic, economic and environmental aspects have been considered, simultaneously. The thermodynamic modeling has been implemented comprehensively while economic analysis conducted in accordance with the total revenue requirement (TRR) method. The results for the single objective thermoeconomic optimization have been compared with the previous studies in optimization of CGAM problem. In multi-objective optimization of the CGAM problem, the three objective functions including the exergetic efficiency, total levelized cost rate of the system product and the cost rate of environmental impact have been considered. The environmental impact objective function has been defined and expressed in cost terms. This objective has been integrated with the thermoeconomic objective to form a new unique objective function known as a thermoenvironomic objective function. The thermoenvironomic objective has been minimized while the exergetic objective has been maximized. One of the most suitable optimization techniques developed using a particular class of search algorithms known as multi-objective evolutionary algorithms (MOEAs) has been considered here. This approach which is developed based on the genetic algorithm has been applied to find the set of Pareto optimal solutions with respect to the aforementioned objective functions. An example of decision-making has been presented and a final optimal solution has been introduced. The sensitivity of the solutions to the interest rate and the fuel cost has been studied

Evidence-based librarianship: an overview.

Science.gov (United States)

Eldredge, J D

2000-10-01

To demonstrate how the core characteristics of both evidence-based medicine (EBM) and evidence-based health care (EBHC) can be adapted to health sciences librarianship. Narrative review essay involving development of a conceptual framework. The author describes the central features of EBM and EBHC. Following each description of a central feature, the author then suggests ways that this feature applies to health sciences librarianship. First, the decision-making processes of EBM and EBHC are compatible with health sciences librarianship. Second, the EBM and EBHC values of favoring rigorously produced scientific evidence in decision making are congruent with the core values of librarianship. Third, the hierarchical levels of evidence can be applied to librarianship with some modifications. Library researchers currently favor descriptive-survey and case-study methods over systematic reviews, randomized controlled trials, or other higher levels of evidence. The library literature nevertheless contains diverse examples of randomized controlled trials, controlled-comparison studies, and cohort studies conducted by health sciences librarians. Health sciences librarians are confronted with making many practical decisions. Evidence-based librarianship offers a decision-making framework, which integrates the best available research evidence. By employing this framework and the higher levels of research evidence it promotes, health sciences librarians can lay the foundation for more collaborative and scientific endeavors.

An Evidence-Based Approach to Reducing Cardiac Telemetry Alarm Fatigue.

Science.gov (United States)

Srinivasa, Ekta; Mankoo, Jaspreet; Kerr, Charles

2017-08-01

It is estimated that between 80% and 99% of alarms in the clinical areas are in actionable alarms (Gross, Dahl, & Nielson). Alarm management is one of the Joint Commission's National Patient Safety Goals (2014) because sentinel events have directly been linked to the devices generating these alarms. At an acute care facility in Boston, a multidisciplinary team consisting of Nursing, Biomedical Engineers, Patient Safety and Providers was formed to conduct a pilot study on the state of telemetry alarms on a surgical floor. An evidence-based approach was taken utilizing Philips Real-time data exporter alarms tracking software to capture all telemetry alarms during a 43-day time span. Likewise, noise meters were placed near telemetry alarm speakers to track decibel levels within the aforementioned timeframe for 21 days. Analysis of the data showed that clinically insignificant Premature Ventricular Contractions (PVC) alarms accounted for more than 40% of all alarms in the unit within the time span, while also contributing to an average noise level of 58.49 dB. In response to the data, the interdisciplinary team approved to permanently default the settings for PAIR PVC, MULTIFORM PVC, and RUN PVC alarms to off. The results showed a 54% decrease in the rate of alarms per bed per day, and an average noise reduction of 2.3 dB between the two selected noise measurement areas. Organizing a multidisciplinary team provides an effective framework toward analyzing and addressing cardiac telemetry alarm fatigue. Looking at quantitative datasets for clinical care areas through various lenses helps identify opportunities for improvement in regards to highlighting alarms that are not actionable. Pilot changes to alarm parameters can be tested for their environmental impact in the care area. © 2017 Sigma Theta Tau International.

Modeling crowd behavior based on the discrete-event multiagent approach

OpenAIRE

Лановой, Алексей Феликсович; Лановой, Артем Алексеевич

2014-01-01

The crowd is a temporary, relatively unorganized group of people, who are in close physical contact with each other. Individual behavior of human outside the crowd is determined by many factors, associated with his intellectual activities, but inside the crowd the man loses his identity and begins to obey more simple laws of behavior.One of approaches to the construction of multi-level model of the crowd using discrete-event multiagent approach was described in the paper.Based on this analysi...

Efficacy of a modern neuroscience approach versus usual care evidence-based physiotherapy on pain, disability and brain characteristics in chronic spinal pain patients: protocol of a randomized clinical trial

Science.gov (United States)

2014-01-01

Background Among the multiple conservative modalities, physiotherapy is a commonly utilized treatment modality in managing chronic non-specific spinal pain. Despite the scientific progresses with regard to pain and motor control neuroscience, treatment of chronic spinal pain (CSP) often tends to stick to a peripheral biomechanical model, without targeting brain mechanisms. With a view to enhance clinical efficacy of existing physiotherapeutic treatments for CSP, the development of clinical strategies targeted at ‘training the brain’ is to be pursued. Promising proof-of-principle results have been reported for the effectiveness of a modern neuroscience approach to CSP when compared to usual care, but confirmation is required in a larger, multi-center trial with appropriate evidence-based control intervention and long-term follow-up. The aim of this study is to assess the effectiveness of a modern neuroscience approach, compared to usual care evidence-based physiotherapy, for reducing pain and improving functioning in patients with CSP. A secondary objective entails examining the effectiveness of the modern neuroscience approach versus usual care physiotherapy for normalizing brain gray matter in patients with CSP. Methods/Design The study is a multi-center, triple-blind, two-arm (1:1) randomized clinical trial with 1-year follow-up. 120 CSP patients will be randomly allocated to either the experimental (receiving pain neuroscience education followed by cognition-targeted motor control training) or the control group (receiving usual care physiotherapy), each comprising of 3 months treatment. The main outcome measures are pain (including symptoms and indices of central sensitization) and self-reported disability. Secondary outcome measures include brain gray matter structure, motor control, muscle properties, and psychosocial correlates. Clinical assessment and brain imaging will be performed at baseline, post-treatment and at 1-year follow-up. Web-based

A Multi-scale, Multi-disciplinary Approach for Assessing the Technological, Economic, and Environmental Performance of Bio-based Chemicals

DEFF Research Database (Denmark)

Herrgard, Markus; Sukumara, Sumesh; Campodonico Alt, Miguel Angel

2015-01-01

, the Multi-scale framework for Sustainable Industrial Chemicals (MuSIC) was introduced to address this issue by integrating modelling approaches at different scales ranging from cellular to ecological scales. This framework can be further extended by incorporating modelling of the petrochemical value chain...... towards a sustainable chemical industry....

Multi-level gene/MiRNA feature selection using deep belief nets and active learning.

Science.gov (United States)

Ibrahim, Rania; Yousri, Noha A; Ismail, Mohamed A; El-Makky, Nagwa M

2014-01-01

Selecting the most discriminative genes/miRNAs has been raised as an important task in bioinformatics to enhance disease classifiers and to mitigate the dimensionality curse problem. Original feature selection methods choose genes/miRNAs based on their individual features regardless of how they perform together. Considering group features instead of individual ones provides a better view for selecting the most informative genes/miRNAs. Recently, deep learning has proven its ability in representing the data in multiple levels of abstraction, allowing for better discrimination between different classes. However, the idea of using deep learning for feature selection is not widely used in the bioinformatics field yet. In this paper, a novel multi-level feature selection approach named MLFS is proposed for selecting genes/miRNAs based on expression profiles. The approach is based on both deep and active learning. Moreover, an extension to use the technique for miRNAs is presented by considering the biological relation between miRNAs and genes. Experimental results show that the approach was able to outperform classical feature selection methods in hepatocellular carcinoma (HCC) by 9%, lung cancer by 6% and breast cancer by around 10% in F1-measure. Results also show the enhancement in F1-measure of our approach over recently related work in [1] and [2].

Testing multi-alternative decision models with non-stationary evidence.

Science.gov (United States)

Tsetsos, Konstantinos; Usher, Marius; McClelland, James L

2011-01-01

Recent research has investigated the process of integrating perceptual evidence toward a decision, converging on a number of sequential sampling choice models, such as variants of race and diffusion models and the non-linear leaky competing accumulator (LCA) model. Here we study extensions of these models to multi-alternative choice, considering how well they can account for data from a psychophysical experiment in which the evidence supporting each of the alternatives changes dynamically during the trial, in a way that creates temporal correlations. We find that participants exhibit a tendency to choose an alternative whose evidence profile is temporally anti-correlated with (or dissimilar from) that of other alternatives. This advantage of the anti-correlated alternative is well accounted for in the LCA, and provides constraints that challenge several other models of multi-alternative choice.

A practical and applied approach to assessing the cross cutting nature of child injury prevention as a basis for policy making at the local level

Directory of Open Access Journals (Sweden)

Beatrice Scholtes

2015-12-01

Full Text Available Aim: Risk factors for child injury are multi-faceted. Social, environmental and economic factors place responsibility for prevention upon many stakeholders across traditional sectors such as health, justice, environment and education. Multi-sectoral collaboration for injury prevention is thus essential. In addition, co-benefits due to injury prevention initiatives exist. However, multi-sectoral collaboration is often difficult to establish and maintain. We present an applied approach for practitioners and policy makers at the local level to use to explore and address the multi-sectoral nature of child injury. Methods: We combined elements of the Haddon Matrix and the Lens and Telescope model, to develop a new approach for practitioners and policy makers at the local level. Results: The approach offers the opportunity for diverse sectors at the local level to work together to identify their role in child injury prevention. Based on ecological injury prevention and life-course epidemiology it encourages multi-disciplinary team building from the outset. The process has three phases: first, visualising the multi-sectoral responsibilities for child injury prevention in the local area; second,  demonstrating the need for multi-sectoral collaboration and helping plan prevention activities together; and third, visualising potential co-benefits to other sectors and age groups that may arise from child injury prevention initiatives. Conclusion: The approach and process encourages inter-sectoral collaboration for child injury prevention at the local level. It is a useful addition for child injury  prevention at the local level, however testing the practicality of the approach in a real-world setting, and refinement of the process would improve it further.

Isocyanide based multi component reactions in combinatorial chemistry.

NARCIS (Netherlands)

Dömling, A.

1998-01-01

Although usually regarded as a recent development, the combinatorial approach to the synthesis of libraries of new drug candidates was first described as early as 1961 using the isocyanide-based one-pot multicomponent Ugi reaction. Isocyanide-based multi component reactions (MCR's) markedly differ

Biphasic DC measurement approach for enhanced measurement stability and multi-channel sampling of self-sensing multi-functional structural materials doped with carbon-based additives

Science.gov (United States)

Downey, Austin; D'Alessandro, Antonella; Ubertini, Filippo; Laflamme, Simon; Geiger, Randall

2017-06-01

Investigation of multi-functional carbon-based self-sensing structural materials for structural health monitoring applications is a topic of growing interest. These materials are self-sensing in the sense that they can provide measurable electrical outputs corresponding to physical changes such as strain or induced damage. Nevertheless, the development of an appropriate measurement technique for such materials is yet to be achieved, as many results in the literature suggest that these materials exhibit a drift in their output when measured with direct current (DC) methods. In most of the cases, the electrical output is a resistance and the reported drift is an increase in resistance from the time the measurement starts due to material polarization. Alternating current methods seem more appropriate at eliminating the time drift. However, published results show they are not immune to drift. Moreover, the use of multiple impedance measurement devices (LCR meters) does not allow for the simultaneous multi-channel sampling of multi-sectioned self-sensing materials due to signal crosstalk. The capability to simultaneously monitor multiple sections of self-sensing structural materials is needed to deploy these multi-functional materials for structural health monitoring. Here, a biphasic DC measurement approach with a periodic measure/discharge cycle in the form of a square wave sensing current is used to provide consistent, stable resistance measurements for self-sensing structural materials. DC measurements are made during the measurement region of the square wave while material depolarization is obtained during the discharge region of the periodic signal. The proposed technique is experimentally shown to remove the signal drift in a carbon-based self-sensing cementitious material while providing simultaneous multi-channel measurements of a multi-sectioned self-sensing material. The application of the proposed electrical measurement technique appears promising for real

A Mission Planning Approach for Precision Farming Systems Based on Multi-Objective Optimization

Directory of Open Access Journals (Sweden)

Zhaoyu Zhai

2018-06-01

Full Text Available As the demand for food grows continuously, intelligent agriculture has drawn much attention due to its capability of producing great quantities of food efficiently. The main purpose of intelligent agriculture is to plan agricultural missions properly and use limited resources reasonably with minor human intervention. This paper proposes a Precision Farming System (PFS as a Multi-Agent System (MAS. Components of PFS are treated as agents with different functionalities. These agents could form several coalitions to complete the complex agricultural missions cooperatively. In PFS, mission planning should consider several criteria, like expected benefit, energy consumption or equipment loss. Hence, mission planning could be treated as a Multi-objective Optimization Problem (MOP. In order to solve MOP, an improved algorithm, MP-PSOGA, is proposed, taking advantages of the Genetic Algorithms and Particle Swarm Optimization. A simulation, called precise pesticide spraying mission, is performed to verify the feasibility of the proposed approach. Simulation results illustrate that the proposed approach works properly. This approach enables the PFS to plan missions and allocate scarce resources efficiently. The theoretical analysis and simulation is a good foundation for the future study. Once the proposed approach is applied to a real scenario, it is expected to bring significant economic improvement.

A Practice Approach of Multi-source Geospatial Data Integration for Web-based Geoinformation Services

Science.gov (United States)

Huang, W.; Jiang, J.; Zha, Z.; Zhang, H.; Wang, C.; Zhang, J.

2014-04-01

Geospatial data resources are the foundation of the construction of geo portal which is designed to provide online geoinformation services for the government, enterprise and public. It is vital to keep geospatial data fresh, accurate and comprehensive in order to satisfy the requirements of application and development of geographic location, route navigation, geo search and so on. One of the major problems we are facing is data acquisition. For us, integrating multi-sources geospatial data is the mainly means of data acquisition. This paper introduced a practice integration approach of multi-source geospatial data with different data model, structure and format, which provided the construction of National Geospatial Information Service Platform of China (NGISP) with effective technical supports. NGISP is the China's official geo portal which provides online geoinformation services based on internet, e-government network and classified network. Within the NGISP architecture, there are three kinds of nodes: national, provincial and municipal. Therefore, the geospatial data is from these nodes and the different datasets are heterogeneous. According to the results of analysis of the heterogeneous datasets, the first thing we do is to define the basic principles of data fusion, including following aspects: 1. location precision; 2.geometric representation; 3. up-to-date state; 4. attribute values; and 5. spatial relationship. Then the technical procedure is researched and the method that used to process different categories of features such as road, railway, boundary, river, settlement and building is proposed based on the principles. A case study in Jiangsu province demonstrated the applicability of the principle, procedure and method of multi-source geospatial data integration.

Integrated Systems-Based Approach for Reaching Acceptable End Points for Groundwater - 13629

International Nuclear Information System (INIS)

Lee, M. Hope; Wellman, Dawn; Truex, Mike; Freshley, Mark D.; Sorenson, Kent S. Jr.; Wymore, Ryan

2013-01-01

The sheer mass and nature of contaminated materials at DOE and DoD sites, makes it impractical to completely restore these sites to pre-disposal conditions. DOE faces long-term challenges, particularly with developing monitoring and end state approaches for clean-up that are protective of the environment, technically based and documented, sustainable, and most importantly cost effective. Integrated systems-based monitoring approaches (e.g., tools for characterization and monitoring, multi-component strategies, geophysical modeling) could provide novel approaches and a framework to (a) define risk-informed endpoints and/or conditions that constitute completion of cleanup and (b) provide the understanding for implementation of advanced scientific approaches to meet cleanup goals. Multi-component strategies which combine site conceptual models, biological, chemical, and physical remediation strategies, as well as iterative review and optimization have proven successful at several DOE sites. Novel tools such as enzyme probes and quantitative PCR for DNA and RNA, and innovative modeling approaches for complex subsurface environments, have been successful at facilitating the reduced operation or shutdown of pump and treat facilities and transition of clean-up activities into monitored natural attenuation remedies. Integrating novel tools with site conceptual models and other lines of evidence to characterize, optimize, and monitor long term remedial approaches for complex contaminant plumes are critical for transitioning active remediation into cost effective, yet technically defensible endpoint strategies. (authors)

Adopting a blended learning approach to teaching evidence based medicine: a mixed methods study

Science.gov (United States)

2013-01-01

Background Evidence Based Medicine (EBM) is a core unit delivered across many medical schools. Few studies have investigated the most effective method of teaching a course in EBM to medical students. The objective of this study was to identify whether a blended-learning approach to teaching EBM is more effective a didactic-based approach at increasing medical student competency in EBM. Methods A mixed-methods study was conducted consisting of a controlled trial and focus groups with second year graduate medical students. Students received the EBM course delivered using either a didactic approach (DID) to learning EBM or a blended-learning approach (BL). Student competency in EBM was assessed using the Berlin tool and a criterion-based assessment task, with student perceptions on the interventions assessed qualitatively. Results A total of 61 students (85.9%) participated in the study. Competency in EBM did not differ between the groups when assessed using the Berlin tool (p = 0.29). Students using the BL approach performed significantly better in one of the criterion-based assessment tasks (p = 0.01) and reported significantly higher self-perceived competence in critical appraisal skills. Qualitative analysis identified that students had a preference for the EBM course to be delivered using the BL approach. Conclusions Implementing a blended-learning approach to EBM teaching promotes greater student appreciation of EBM principles within the clinical setting. Integrating a variety of teaching modalities and approaches can increase student self-confidence and assist in bridging the gap between the theory and practice of EBM. PMID:24341502

Adopting a blended learning approach to teaching evidence based medicine: a mixed methods study.

Science.gov (United States)

Ilic, Dragan; Hart, William; Fiddes, Patrick; Misso, Marie; Villanueva, Elmer

2013-12-17

Evidence Based Medicine (EBM) is a core unit delivered across many medical schools. Few studies have investigated the most effective method of teaching a course in EBM to medical students. The objective of this study was to identify whether a blended-learning approach to teaching EBM is more effective a didactic-based approach at increasing medical student competency in EBM. A mixed-methods study was conducted consisting of a controlled trial and focus groups with second year graduate medical students. Students received the EBM course delivered using either a didactic approach (DID) to learning EBM or a blended-learning approach (BL). Student competency in EBM was assessed using the Berlin tool and a criterion-based assessment task, with student perceptions on the interventions assessed qualitatively. A total of 61 students (85.9%) participated in the study. Competency in EBM did not differ between the groups when assessed using the Berlin tool (p = 0.29). Students using the BL approach performed significantly better in one of the criterion-based assessment tasks (p = 0.01) and reported significantly higher self-perceived competence in critical appraisal skills. Qualitative analysis identified that students had a preference for the EBM course to be delivered using the BL approach. Implementing a blended-learning approach to EBM teaching promotes greater student appreciation of EBM principles within the clinical setting. Integrating a variety of teaching modalities and approaches can increase student self-confidence and assist in bridging the gap between the theory and practice of EBM.

Adapting Evidence-Based Mental Health Treatments in Community Settings: Preliminary Results from a Partnership Approach

Science.gov (United States)

Southam-Gerow, Michael A.; Hourigan, Shannon E.; Allin, Robert B., Jr.

2009-01-01

This article describes the application of a university-community partnership model to the problem of adapting evidence-based treatment approaches in a community mental health setting. Background on partnership research is presented, with consideration of methodological and practical issues related to this kind of research. Then, a rationale for…

Multi-level Discourse Analysis in a Physics Teaching Methods Course from the Psychological Perspective of Activity Theory

Science.gov (United States)

Vieira, Rodrigo Drumond; Kelly, Gregory J.

2014-11-01

In this paper, we present and apply a multi-level method for discourse analysis in science classrooms. This method is based on the structure of human activity (activity, actions, and operations) and it was applied to study a pre-service physics teacher methods course. We argue that such an approach, based on a cultural psychological perspective, affords opportunities for analysts to perform a theoretically based detailed analysis of discourse events. Along with the presentation of analysis, we show and discuss how the articulation of different levels offers interpretative criteria for analyzing instructional conversations. We synthesize the results into a model for a teacher's practice and discuss the implications and possibilities of this approach for the field of discourse analysis in science classrooms. Finally, we reflect on how the development of teachers' understanding of their activity structures can contribute to forms of progressive discourse of science education.

Multi-Level and Multi-Scale Feature Aggregation Using Pretrained Convolutional Neural Networks for Music Auto-Tagging

Science.gov (United States)

Lee, Jongpil; Nam, Juhan

2017-08-01

Music auto-tagging is often handled in a similar manner to image classification by regarding the 2D audio spectrogram as image data. However, music auto-tagging is distinguished from image classification in that the tags are highly diverse and have different levels of abstractions. Considering this issue, we propose a convolutional neural networks (CNN)-based architecture that embraces multi-level and multi-scaled features. The architecture is trained in three steps. First, we conduct supervised feature learning to capture local audio features using a set of CNNs with different input sizes. Second, we extract audio features from each layer of the pre-trained convolutional networks separately and aggregate them altogether given a long audio clip. Finally, we put them into fully-connected networks and make final predictions of the tags. Our experiments show that using the combination of multi-level and multi-scale features is highly effective in music auto-tagging and the proposed method outperforms previous state-of-the-arts on the MagnaTagATune dataset and the Million Song Dataset. We further show that the proposed architecture is useful in transfer learning.

Evidence-Based Psychotherapy: Advantages and Challenges.

Science.gov (United States)

Cook, Sarah C; Schwartz, Ann C; Kaslow, Nadine J

2017-07-01

Evidence-based psychotherapies have been shown to be efficacious and cost-effective for a wide range of psychiatric conditions. Psychiatric disorders are prevalent worldwide and associated with high rates of disease burden, as well as elevated rates of co-occurrence with medical disorders, which has led to an increased focus on the need for evidence-based psychotherapies. This chapter focuses on the current state of evidence-based psychotherapy. The strengths and challenges of evidence-based psychotherapy are discussed, as well as misperceptions regarding the approach that may discourage and limit its use. In addition, we review various factors associated with the optimal implementation and application of evidence-based psychotherapies. Lastly, suggestions are provided on ways to advance the evidence-based psychotherapy movement to become truly integrated into practice.

Multi-hazard national-level risk assessment in Africa using global approaches

Science.gov (United States)

Fraser, Stuart; Jongman, Brenden; Simpson, Alanna; Murnane, Richard

2016-04-01

In recent years Sub-Saharan Africa has been characterized by unprecedented opportunity for transformation and sustained growth. However, natural disasters such as droughts, floods, cyclones, earthquakes, landslides, volcanic eruptions and extreme temperatures cause significant economic and human losses, and major development challenges. Quantitative disaster risk assessments are an important basis for governments to understand disaster risk in their country, and to develop effective risk management and risk financing solutions. However, the data-scarce nature of many Sub-Saharan African countries as well as a lack of financing for risk assessments has long prevented detailed analytics. Recent advances in globally applicable disaster risk modelling practices and data availability offer new opportunities. In December 2013 the European Union approved a € 60 million contribution to support the development of an analytical basis for risk financing and to accelerate the effective implementation of a comprehensive disaster risk reduction. The World Bank's Global Facility for Disaster Reduction and Recovery (GFDRR) was selected as the implementing partner of the Program for Result Area 5: the "Africa Disaster Risk Assessment and Financing Program." As part of this effort, the GFDRR is overseeing the production of national-level multi-hazard risk profiles for a range of countries in Sub-Saharan Africa, using a combination of national and global datasets and state-of-the-art hazard and risk assessment methodologies. In this presentation, we will highlight the analytical approach behind these assessments, and show results for the first five countries for which the assessment has been completed (Kenya, Uganda, Senegal, Niger and Ethiopia). The presentation will also demonstrate the visualization of the risk assessments into understandable and visually attractive risk profile documents.

Data Hiding and Security for XML Database: A TRBAC- Based Approach

Institute of Scientific and Technical Information of China (English)

ZHANG Wan-song; SUN Wei; LIU Da-xin

2005-01-01

In order to cope with varying protection granularity levels of XML (eXtensible Markup Language) documents, we propose a TXAC (Two-level XML Access Control) framework, in which an extended TRBAC (Temporal Role-Based Access Control) approach is proposed to deal with the dynamic XML data. With different system components,TXAC algorithm evaluates access requests efficiently by appropriate access control policy in dynamic web environment.The method is a flexible and powerful security system offering a multi-level access control solution.

It's the parameters, stupid! Moving beyond multi-model and multi-physics approaches to characterize and reduce predictive uncertainty in process-based hydrological models

Science.gov (United States)

Clark, Martyn; Samaniego, Luis; Freer, Jim

2014-05-01

Multi-model and multi-physics approaches are a popular tool in environmental modelling, with many studies focusing on optimally combining output from multiple model simulations to reduce predictive errors and better characterize predictive uncertainty. However, a careful and systematic analysis of different hydrological models reveals that individual models are simply small permutations of a master modeling template, and inter-model differences are overwhelmed by uncertainty in the choice of the parameter values in the model equations. Furthermore, inter-model differences do not explicitly represent the uncertainty in modeling a given process, leading to many situations where different models provide the wrong results for the same reasons. In other cases, the available morphological data does not support the very fine spatial discretization of the landscape that typifies many modern applications of process-based models. To make the uncertainty characterization problem worse, the uncertain parameter values in process-based models are often fixed (hard-coded), and the models lack the agility necessary to represent the tremendous heterogeneity in natural systems. This presentation summarizes results from a systematic analysis of uncertainty in process-based hydrological models, where we explicitly analyze the myriad of subjective decisions made throughout both the model development and parameter estimation process. Results show that much of the uncertainty is aleatory in nature - given a "complete" representation of dominant hydrologic processes, uncertainty in process parameterizations can be represented using an ensemble of model parameters. Epistemic uncertainty associated with process interactions and scaling behavior is still important, and these uncertainties can be represented using an ensemble of different spatial configurations. Finally, uncertainty in forcing data can be represented using ensemble methods for spatial meteorological analysis. Our systematic

Fuzzy multinomial logistic regression analysis: A multi-objective programming approach

Science.gov (United States)

Abdalla, Hesham A.; El-Sayed, Amany A.; Hamed, Ramadan

2017-05-01

Parameter estimation for multinomial logistic regression is usually based on maximizing the likelihood function. For large well-balanced datasets, Maximum Likelihood (ML) estimation is a satisfactory approach. Unfortunately, ML can fail completely or at least produce poor results in terms of estimated probabilities and confidence intervals of parameters, specially for small datasets. In this study, a new approach based on fuzzy concepts is proposed to estimate parameters of the multinomial logistic regression. The study assumes that the parameters of multinomial logistic regression are fuzzy. Based on the extension principle stated by Zadeh and Bárdossy's proposition, a multi-objective programming approach is suggested to estimate these fuzzy parameters. A simulation study is used to evaluate the performance of the new approach versus Maximum likelihood (ML) approach. Results show that the new proposed model outperforms ML in cases of small datasets.

A multi-criteria decision approach to sorting actions for promoting energy efficiency

International Nuclear Information System (INIS)

Pires Neves, Luis; Gomes Martins, Antonio; Henggeler Antunes, Carlos; Candido Dias, Luis

2008-01-01

This paper proposes a multi-criteria decision approach for sorting energy-efficiency initiatives, promoted by electric utilities, with or without public funds authorized by a regulator, or promoted by an independent energy agency, overcoming the limitations and drawbacks of cost-benefit analysis. The proposed approach is based on the ELECTRE-TRI multi-criteria method and allows the consideration of different kinds of impacts, although avoiding difficult measurements and unit conversions. The decision is based on all the significant effects of the initiative, both positive and negative, including ancillary effects often forgotten in cost-benefit analysis. The ELECTRE-TRI, as most multi-criteria methods, provides to the decision maker the ability of controlling the relevance each impact can have on the final decision in a transparent way. The decision support process encompasses a robustness analysis, which, together with a good documentation of the parameters supplied into the model, should support sound decisions. The models were tested with a set of real-world initiatives and compared with possible decisions based on cost-benefit analysis

CGLXTouch: A multi-user multi-touch approach for ultra-high-resolution collaborative workspaces

KAUST Repository

Ponto, Kevin

2011-06-01

This paper presents an approach for empowering collaborative workspaces through ultra-high resolution tiled display environments concurrently interfaced with multiple multi-touch devices. Multi-touch table devices are supported along with portable multi-touch tablet and phone devices, which can be added to and removed from the system on the fly. Events from these devices are tagged with a device identifier and are synchronized with the distributed display environment, enabling multi-user support. As many portable devices are not equipped to render content directly, a remotely scene is streamed in. The presented approach scales for large numbers of devices, providing access to a multitude of hands-on techniques for collaborative data analysis. © 2011 Elsevier B.V. All rights reserved.

Complementary and alternative medicine approaches to blood pressure reduction: An evidence-based review.

Science.gov (United States)

Nahas, Richard

2008-11-01

ABSTRACTOBJECTIVETo review the evidence supporting complementary and alternative medicine approaches used in the treatment of hypertension.QUALITY OF EVIDENCEMEDLINE and EMBASE were searched from January 1966 to May 2008 combining the key words hypertension or blood pressure with acupuncture, chocolate, cocoa, coenzyme Q10, ubiquinone, melatonin, vitamin D, meditation, and stress reduction. Clinical trials, prospective studies, and relevant references were included.MAIN MESSAGEEvidence from systematic reviews supports the blood pressure-lowering effects of coenzyme Q10, polyphenol-rich dark chocolate, Qigong, slow breathing, and transcendental meditation. Vitamin D deficiency is associated with hypertension and cardiovascular risk; supplementation lowered blood pressure in 2 trials. Acupuncture reduced blood pressure in 3 trials; in 1 of these it was no better than an invasive placebo. Melatonin was effective in 2 small trials, but caution is warranted in patients taking pharmacotherapy.CONCLUSIONSeveral complementary and alternative medicine therapies can be considered as part of an evidence-based approach to the treatment of hypertension. The potential benefit of these interventions warrants further research using cardiovascular outcomes.

Hydro-environmental management of groundwater resources: A fuzzy-based multi-objective compromise approach

Science.gov (United States)

Alizadeh, Mohammad Reza; Nikoo, Mohammad Reza; Rakhshandehroo, Gholam Reza

2017-08-01

Sustainable management of water resources necessitates close attention to social, economic and environmental aspects such as water quality and quantity concerns and potential conflicts. This study presents a new fuzzy-based multi-objective compromise methodology to determine the socio-optimal and sustainable policies for hydro-environmental management of groundwater resources, which simultaneously considers the conflicts and negotiation of involved stakeholders, uncertainties in decision makers' preferences, existing uncertainties in the groundwater parameters and groundwater quality and quantity issues. The fuzzy multi-objective simulation-optimization model is developed based on qualitative and quantitative groundwater simulation model (MODFLOW and MT3D), multi-objective optimization model (NSGA-II), Monte Carlo analysis and Fuzzy Transformation Method (FTM). Best compromise solutions (best management policies) on trade-off curves are determined using four different Fuzzy Social Choice (FSC) methods. Finally, a unanimity fallback bargaining method is utilized to suggest the most preferred FSC method. Kavar-Maharloo aquifer system in Fars, Iran, as a typical multi-stakeholder multi-objective real-world problem is considered to verify the proposed methodology. Results showed an effective performance of the framework for determining the most sustainable allocation policy in groundwater resource management.

Research on the Fusion of Dependent Evidence Based on Rank Correlation Coefficient

Directory of Open Access Journals (Sweden)

Fengjian Shi

2017-10-01

Full Text Available In order to meet the higher accuracy and system reliability requirements, the information fusion for multi-sensor systems is an increasing concern. Dempster–Shafer evidence theory (D–S theory has been investigated for many applications in multi-sensor information fusion due to its flexibility in uncertainty modeling. However, classical evidence theory assumes that the evidence is independent of each other, which is often unrealistic. Ignoring the relationship between the evidence may lead to unreasonable fusion results, and even lead to wrong decisions. This assumption severely prevents D–S evidence theory from practical application and further development. In this paper, an innovative evidence fusion model to deal with dependent evidence based on rank correlation coefficient is proposed. The model first uses rank correlation coefficient to measure the dependence degree between different evidence. Then, total discount coefficient is obtained based on the dependence degree, which also considers the impact of the reliability of evidence. Finally, the discount evidence fusion model is presented. An example is illustrated to show the use and effectiveness of the proposed method.

Research on the Fusion of Dependent Evidence Based on Rank Correlation Coefficient.

Science.gov (United States)

Shi, Fengjian; Su, Xiaoyan; Qian, Hong; Yang, Ning; Han, Wenhua

2017-10-16

In order to meet the higher accuracy and system reliability requirements, the information fusion for multi-sensor systems is an increasing concern. Dempster-Shafer evidence theory (D-S theory) has been investigated for many applications in multi-sensor information fusion due to its flexibility in uncertainty modeling. However, classical evidence theory assumes that the evidence is independent of each other, which is often unrealistic. Ignoring the relationship between the evidence may lead to unreasonable fusion results, and even lead to wrong decisions. This assumption severely prevents D-S evidence theory from practical application and further development. In this paper, an innovative evidence fusion model to deal with dependent evidence based on rank correlation coefficient is proposed. The model first uses rank correlation coefficient to measure the dependence degree between different evidence. Then, total discount coefficient is obtained based on the dependence degree, which also considers the impact of the reliability of evidence. Finally, the discount evidence fusion model is presented. An example is illustrated to show the use and effectiveness of the proposed method.

An approach to multi-attribute utility analysis under parametric uncertainty

International Nuclear Information System (INIS)

Kelly, M.; Thorne, M.C.

2001-01-01

The techniques of cost-benefit analysis and multi-attribute analysis provide a useful basis for informing decisions in situations where a number of potentially conflicting opinions or interests need to be considered, and where there are a number of possible decisions that could be adopted. When the input data to such decision-making processes are uniquely specified, cost-benefit analysis and multi-attribute utility analysis provide unambiguous guidance on the preferred decision option. However, when the data are not uniquely specified, application and interpretation of these techniques is more complex. Herein, an approach to multi-attribute utility analysis (and hence, as a special case, cost-benefit analysis) when input data are subject to parametric uncertainty is presented. The approach is based on the use of a Monte Carlo technique, and has recently been applied to options for the remediation of former uranium mining liabilities in a number of Central and Eastern European States

Hollow optical-fiber based infrared spectroscopy for measurement of blood glucose level by using multi-reflection prism.

Science.gov (United States)

Kino, Saiko; Omori, Suguru; Katagiri, Takashi; Matsuura, Yuji

2016-02-01

A mid-infrared attenuated total reflection (ATR) spectroscopy system employing hollow optical fibers and a trapezoidal multi-reflection ATR prism has been developed to measure blood glucose levels. Using a multi-reflection prism brought about higher sensitivity, and the flat and wide contact surface of the prism resulted in higher measurement reproducibility. An analysis of in vivo measurements of human inner lip mucosa revealed clear signatures of glucose in the difference spectra between ones taken during the fasting state and ones taken after ingestion of glucose solutions. A calibration plot based on the absorption peak at 1155 cm(-1) that originates from the pyranose ring structure of glucose gave measurement errors less than 20%.

A quasiparticle-based multi-reference coupled-cluster method.

Science.gov (United States)

Rolik, Zoltán; Kállay, Mihály

2014-10-07

The purpose of this paper is to introduce a quasiparticle-based multi-reference coupled-cluster (MRCC) approach. The quasiparticles are introduced via a unitary transformation which allows us to represent a complete active space reference function and other elements of an orthonormal multi-reference (MR) basis in a determinant-like form. The quasiparticle creation and annihilation operators satisfy the fermion anti-commutation relations. On the basis of these quasiparticles, a generalization of the normal-ordered operator products for the MR case can be introduced as an alternative to the approach of Mukherjee and Kutzelnigg [Recent Prog. Many-Body Theor. 4, 127 (1995); Mukherjee and Kutzelnigg, J. Chem. Phys. 107, 432 (1997)]. Based on the new normal ordering any quasiparticle-based theory can be formulated using the well-known diagram techniques. Beyond the general quasiparticle framework we also present a possible realization of the unitary transformation. The suggested transformation has an exponential form where the parameters, holding exclusively active indices, are defined in a form similar to the wave operator of the unitary coupled-cluster approach. The definition of our quasiparticle-based MRCC approach strictly follows the form of the single-reference coupled-cluster method and retains several of its beneficial properties. Test results for small systems are presented using a pilot implementation of the new approach and compared to those obtained by other MR methods.

An enhanced unified uncertainty analysis approach based on first order reliability method with single-level optimization

International Nuclear Information System (INIS)

Yao, Wen; Chen, Xiaoqian; Huang, Yiyong; Tooren, Michel van

2013-01-01

In engineering, there exist both aleatory uncertainties due to the inherent variation of the physical system and its operational environment, and epistemic uncertainties due to lack of knowledge and which can be reduced with the collection of more data. To analyze the uncertain distribution of the system performance under both aleatory and epistemic uncertainties, combined probability and evidence theory can be employed to quantify the compound effects of the mixed uncertainties. The existing First Order Reliability Method (FORM) based Unified Uncertainty Analysis (UUA) approach nests the optimization based interval analysis in the improved Hasofer–Lind–Rackwitz–Fiessler (iHLRF) algorithm based Most Probable Point (MPP) searching procedure, which is computationally inhibitive for complex systems and may encounter convergence problem as well. Therefore, in this paper it is proposed to use general optimization solvers to search MPP in the outer loop and then reformulate the double-loop optimization problem into an equivalent single-level optimization (SLO) problem, so as to simplify the uncertainty analysis process, improve the robustness of the algorithm, and alleviate the computational complexity. The effectiveness and efficiency of the proposed method is demonstrated with two numerical examples and one practical satellite conceptual design problem. -- Highlights: ► Uncertainty analysis under mixed aleatory and epistemic uncertainties is studied. ► A unified uncertainty analysis method is proposed with combined probability and evidence theory. ► The traditional nested analysis method is converted to single level optimization for efficiency. ► The effectiveness and efficiency of the proposed method are testified with three examples

Shrub growth and expansion in the Arctic tundra: an assessment of controlling factors using an evidence-based approach

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Martin, Andrew C.; Jeffers, Elizabeth S.; Petrokofsky, Gillian; Myers-Smith, Isla; Macias-Fauria, Marc

2017-08-01

Woody shrubs have increased in biomass and expanded into new areas throughout the Pan-Arctic tundra biome in recent decades, which has been linked to a biome-wide observed increase in productivity. Experimental, observational, and socio-ecological research suggests that air temperature—and to a lesser degree precipitation—trends have been the predominant drivers of this change. However, a progressive decoupling of these drivers from Arctic vegetation productivity has been reported, and since 2010, vegetation productivity has also been declining. We created a protocol to (a) identify the suite of controls that may be operating on shrub growth and expansion, and (b) characterise the evidence base for controls on Arctic shrub growth and expansion. We found evidence for a suite of 23 proximal controls that operate directly on shrub growth and expansion; the evidence base focused predominantly on just four controls (air temperature, soil moisture, herbivory, and snow dynamics). 65% of evidence was generated in the warmest tundra climes, while 24% was from only one of 28 floristic sectors. Temporal limitations beyond 10 years existed for most controls, while the use of space-for-time approaches was high, with 14% of the evidence derived via experimental approaches. The findings suggest the current evidence base is not sufficiently robust or comprehensive at present to answer key questions of Pan-Arctic shrub change. We suggest future directions that could strengthen the evidence, and lead to an understanding of the key mechanisms driving changes in Arctic shrub environments.

Multi-Level Determinants of Parasitic Fly Infection in Forest Passerines

Science.gov (United States)

Manzoli, Darío Ezequiel; Antoniazzi, Leandro Raúl; Saravia, María José; Silvestri, Leonardo; Rorhmann, David; Beldomenico, Pablo Martín

2013-01-01

The study of myiasis is important because they may cause problems to the livestock industry, public health, or wildlife conservation. The ecology of parasitic dipterans that cause myiasis is singular, as they actively seek their hosts over relatively long distances. However, studies that address the determinants of myiasis dynamics are very scarce. The genus Philornis include species that may be excellent models to study myiasis ecology, as they exclusively parasitize bird nestlings, which stay in their nests until they are fully fledged, and larvae remain at the point of entry until the parasitic stage is over, thus allowing the collection of sequential individual-level infection data from virtually all the hosts present at a particular area. Here we offer a stratified multi-level analysis of longitudinal data of Philornis torquans parasitism in replicated forest bird communities of central Argentina. Using Generalized Linear Models and Generalized Linear Mixed Models and an information theory approach for model selection, we conducted four groups of analyses, each with a different study unit, the individual, the brood, the community at a given week, and the community at a given year. The response variable was larval abundance per nestling or mean abundance per nestling. At each level, models included the variables of interest of that particular level, and also potential confounders and effect modifiers of higher levels. We found associations of large magnitude at all levels, but only few variables truly governed the dynamics of this parasite. At the individual level, the infection was determined by the species and the age of the host. The main driver of parasite abundance at the microhabitat level was the average height of the forest, and at the community level, the density of hosts and prior rainfall. This multi-level approach contributed to a better understanding of the ecology of myiasis. PMID:23874408

Evidence based mental healthcare and service innovation: review of concepts and challenges.

Science.gov (United States)

Kouimtsidis, Ch; John-Smith, St; Kemp, P; Ikkos, G

2013-01-01

Health provision systems in the developed western nations are currently facing major financial challenges. In order to meet these challenges, a number of new approaches used to assist the provision of health have been introduced, including the practice of health professionals. These approaches utilize specific methods of data capture and summarization such as: evidence based medicine (EBM) and practice guidelines. Evidence is generated from systematic clinical research as well as reported clinical experience and individually case based empirical evidence. All types of research though (quantitative or qualitative) have limitations. Similarly all types of evidence have advantages and disadvantages and can be complimentary to each other. Evidencebased individual decision (EBID) making is the commonest evidence-based medicine as practiced by the individual clinician in making decisions about the care of the individual patient. It involves integrating individual clinical expertise with the best available external clinical evidence from systematic research. However this sort of evidence-based medicine, focuses excessively on the individual (potentially at the expense of others) in a system with limited budgets. Evidence-based guidelines (EBG) also support the practice of evidence-based medicine but at the organizational or institutional level. The main aim is to identify which interventions, over a range of patients, work best and which is cost-effective in order to guide service development and provision at a strategic level. Doing this effectively is a scientific and statistical skill in itself and the quality of guidelines is based primarily on the quality research evidence. It is important to note that lack of systematic evidence to support an intervention does not automatically mean that an intervention must instantly be abandoned. It is also important that guidelines are understood for what they are, i.e. not rules, or complete statements of knowledge. EBM will

Evidence-based practice of periodontics.

Science.gov (United States)

Cobb, Charles M; MacNeill, Simon R; Satheesh, Keerthana

2010-01-01

Evidence-based practice involves complex and conscientious decision making based not only on the available evidence but also on patient characteristics, situations, and preferences. It recognizes that care is individualized and ever-changing and involves uncertainties and probabilities. The specialty of periodontics has abundant high-level evidence upon which treatment decisions can be determined. This paper offers a brief commentary and overview of the available evidence commonly used in the private practice of periodontics.

Regulated open multi-agent systems (ROMAS) a multi-agent approach for designing normative open systems

CERN Document Server

Garcia, Emilia; Botti, Vicente

2015-01-01

Addressing the open problem of engineering normative open systems using the multi-agent paradigm, normative open systems are explained as systems in which heterogeneous and autonomous entities and institutions coexist in a complex social and legal framework that can evolve to address the different and often conflicting objectives of the many stakeholders involved. Presenting  a software engineering approach which covers both the analysis and design of these kinds of systems, and which deals with the open issues in the area, ROMAS (Regulated Open Multi-Agent Systems) defines a specific multi-agent architecture, meta-model, methodology and CASE tool. This CASE tool is based on Model-Driven technology and integrates the graphical design with the formal verification of some properties of these systems by means of model checking techniques. Utilizing tables to enhance reader insights into the most important requirements for designing normative open multi-agent systems, the book also provides a detailed and easy t...

An evidence-based approach to perioperative nutrition support in the elective surgery patient.

Science.gov (United States)

Miller, Keith R; Wischmeyer, Paul E; Taylor, Beth; McClave, Stephen A

2013-09-01

In surgical practice, great attention is given to the perioperative management of the elective surgical patient with regard to surgical planning, stratification of cardiopulmonary risk, and postoperative assessment for complication. However, growing evidence supports the beneficial role for implementation of a consistent and literature-based approach to perioperative nutrition therapy. Determining nutrition risk should be a routine component of the preoperative evaluation. As with the above issues, this concept begins with the clinician's first visit with the patient as risk is assessed and the severity of the surgical insult considered. If the patient is an appropriate candidate for benefit from preoperative support, a plan for initiation and reassessment should be implemented. Once appropriate nutrition end points have been achieved, special consideration should be given to beneficial practices the immediate day preceding surgery that may better prepare the patient for the intervention from a metabolic standpoint. In the operating room, consideration should be given to the potential placement of enteral access during the index operation as well as judicious and targeted intraoperative resuscitation. Immediately following the intervention, adequate resuscitation and glycemic control are key concepts, as is an evidence-based approach to the early advancement of an enteral/oral diet in the postoperative patient. Through the implementation of perioperative nutrition therapy plans in the elective surgery setting, outcomes can be improved.

Multi-Criteria Approach in Multifunctional Building Design Process

Science.gov (United States)

Gerigk, Mateusz

2017-10-01

The paper presents new approach in multifunctional building design process. Publication defines problems related to the design of complex multifunctional buildings. Currently, contemporary urban areas are characterized by very intensive use of space. Today, buildings are being built bigger and contain more diverse functions to meet the needs of a large number of users in one capacity. The trends show the need for recognition of design objects in an organized structure, which must meet current design criteria. The design process in terms of the complex system is a theoretical model, which is the basis for optimization solutions for the entire life cycle of the building. From the concept phase through exploitation phase to disposal phase multipurpose spaces should guarantee aesthetics, functionality, system efficiency, system safety and environmental protection in the best possible way. The result of the analysis of the design process is presented as a theoretical model of the multifunctional structure. Recognition of multi-criteria model in the form of Cartesian product allows to create a holistic representation of the designed building in the form of a graph model. The proposed network is the theoretical base that can be used in the design process of complex engineering systems. The systematic multi-criteria approach makes possible to maintain control over the entire design process and to provide the best possible performance. With respect to current design requirements, there are no established design rules for multifunctional buildings in relation to their operating phase. Enrichment of the basic criteria with functional flexibility criterion makes it possible to extend the exploitation phase which brings advantages on many levels.

Jansen-MIDAS: A multi-level photomicrograph segmentation software based on isotropic undecimated wavelets.

Science.gov (United States)

de Siqueira, Alexandre Fioravante; Cabrera, Flávio Camargo; Nakasuga, Wagner Massayuki; Pagamisse, Aylton; Job, Aldo Eloizo

2018-01-01

Image segmentation, the process of separating the elements within a picture, is frequently used for obtaining information from photomicrographs. Segmentation methods should be used with reservations, since incorrect results can mislead when interpreting regions of interest (ROI). This decreases the success rate of extra procedures. Multi-Level Starlet Segmentation (MLSS) and Multi-Level Starlet Optimal Segmentation (MLSOS) were developed to be an alternative for general segmentation tools. These methods gave rise to Jansen-MIDAS, an open-source software. A scientist can use it to obtain several segmentations of hers/his photomicrographs. It is a reliable alternative to process different types of photomicrographs: previous versions of Jansen-MIDAS were used to segment ROI in photomicrographs of two different materials, with an accuracy superior to 89%. © 2017 Wiley Periodicals, Inc.

Estimation of effective permeability for magnetoactive composites containing multi-chain-structured particles based on the generalized Mori–Tanaka approach

International Nuclear Information System (INIS)

Zhang, Haiyu; Wang, Xingzhe

2014-01-01

We present an analytic approach to evaluate the effective permeability of multi-chain-structured magnetic particle-filled composites which is formulated by a microstructure-based double-inclusion magnetic model with the generalized Mori–Tanaka theorem. The local magnetic field in a representative volume element (RVE) containing multi-chain-structured particles is derived by using a modified Green’s function. The average fields in the particles, in a matrix coated by particles, and in an effective medium far away from particles are rendered by homogenization of the local magnetic distributions. By means of the relation between the average magnetic field and induction, the effective magnetic permeability of magnetoactive composites is explicitly derived; it exhibits anisotropic and universal behavior. The proposed model has been compared with the available experimental data and other microstructure-based models in the literature; it shows good agreement and gives reliable predictions for magnetic particle-filled composites, especially in terms of capturing the magnetic anisotropic characteristics with respect to the multi-chain-structured particle distribution. (paper)

Integrative Data Analysis of Multi-Platform Cancer Data with a Multimodal Deep Learning Approach.

Science.gov (United States)

Liang, Muxuan; Li, Zhizhong; Chen, Ting; Zeng, Jianyang

2015-01-01

Identification of cancer subtypes plays an important role in revealing useful insights into disease pathogenesis and advancing personalized therapy. The recent development of high-throughput sequencing technologies has enabled the rapid collection of multi-platform genomic data (e.g., gene expression, miRNA expression, and DNA methylation) for the same set of tumor samples. Although numerous integrative clustering approaches have been developed to analyze cancer data, few of them are particularly designed to exploit both deep intrinsic statistical properties of each input modality and complex cross-modality correlations among multi-platform input data. In this paper, we propose a new machine learning model, called multimodal deep belief network (DBN), to cluster cancer patients from multi-platform observation data. In our integrative clustering framework, relationships among inherent features of each single modality are first encoded into multiple layers of hidden variables, and then a joint latent model is employed to fuse common features derived from multiple input modalities. A practical learning algorithm, called contrastive divergence (CD), is applied to infer the parameters of our multimodal DBN model in an unsupervised manner. Tests on two available cancer datasets show that our integrative data analysis approach can effectively extract a unified representation of latent features to capture both intra- and cross-modality correlations, and identify meaningful disease subtypes from multi-platform cancer data. In addition, our approach can identify key genes and miRNAs that may play distinct roles in the pathogenesis of different cancer subtypes. Among those key miRNAs, we found that the expression level of miR-29a is highly correlated with survival time in ovarian cancer patients. These results indicate that our multimodal DBN based data analysis approach may have practical applications in cancer pathogenesis studies and provide useful guidelines for

Provincial prenatal record revision: a multiple case study of evidence-based decision-making at the population-policy level

Directory of Open Access Journals (Sweden)

Olson Joanne

2008-12-01

Full Text Available Abstract Background There is a significant gap in the knowledge translation literature related to how research evidence actually contributes to health care decision-making. Decisions around what care to provide at the population (rather than individual level are particularly complex, involving considerations such as feasibility, cost, and population needs in addition to scientific evidence. One example of decision-making at this "population-policy" level involves what screening questions and intervention guides to include on standardized provincial prenatal records. As mandatory medical reporting forms, prenatal records are potentially powerful vehicles for promoting population-wide evidence-based care. However, the extent to which Canadian prenatal records reflect best-practice recommendations for the assessment of well-known risk factors such as maternal smoking and alcohol consumption varies markedly across Canadian provinces and territories. The goal of this study is to better understand the interaction of contextual factors and research evidence on decision-making at the population-policy level, by examining the processes by which provincial prenatal records are reviewed and revised. Methods Guided by Dobrow et al.'s (2004 conceptual model for context-based evidence-based decision-making, this study will use a multiple case study design with embedded units of analysis to examine contextual factors influencing the prenatal record revision process in different Canadian provinces and territories. Data will be collected using multiple methods to construct detailed case descriptions for each province/territory. Using qualitative data analysis techniques, decision-making processes involving prenatal record content specifically related to maternal smoking and alcohol use will be compared both within and across each case, to identify key contextual factors influencing the uptake and application of research evidence by prenatal record review

Assessing mental health clinicians' intentions to adopt evidence-based treatments: reliability and validity testing of the evidence-based treatment intentions scale.

Science.gov (United States)

Williams, Nathaniel J

2016-05-05

Intentions play a central role in numerous empirically supported theories of behavior and behavior change and have been identified as a potentially important antecedent to successful evidence-based treatment (EBT) implementation. Despite this, few measures of mental health clinicians' EBT intentions exist and available measures have not been subject to thorough psychometric evaluation or testing. This paper evaluates the psychometric properties of the evidence-based treatment intentions (EBTI) scale, a new measure of mental health clinicians' intentions to adopt EBTs. The study evaluates the reliability and validity of inferences made with the EBTI using multi-method, multi-informant criterion variables collected over 12 months from a sample of 197 mental health clinicians delivering services in 13 mental health agencies. Structural, predictive, and discriminant validity evidence is assessed. Findings support the EBTI's factor structure (χ (2) = 3.96, df = 5, p = .556) and internal consistency reliability (α = .80). Predictive validity evidence was provided by robust and significant associations between EBTI scores and clinicians' observer-reported attendance at a voluntary EBT workshop at a 1-month follow-up (OR = 1.92, p adoption at a 12-month follow-up (R (2) = .17, p adopt EBTs. Discussion focuses on research and practice applications.

Adopting an Evidence-Based Lifestyle Physical Activity Program: Dissemination Study Design and Methods.

Science.gov (United States)

Dunn, Andrea L; Buller, David B; Dearing, James W; Cutter, Gary; Guerra, Michele; Wilcox, Sara; Bettinghaus, Erwin P

2012-06-01

BACKGROUND: There is a scarcity of research studies that have examined academic-commercial partnerships to disseminate evidence-based physical activity programs. Understanding this approach to dissemination is essential because academic-commercial partnerships are increasingly common. Private companies have used dissemination channels and strategies to a degree that academicians have not, and declining resources require academicians to explore these partnerships. PURPOSE: This paper describes a retrospective case-control study design including the methods, demographics, organizational decision-making, implementation rates, and marketing strategy for Active Living Every Day (ALED), an evidence-based lifestyle physical activity program that has been commercially available since 2001. Evidence-based public health promotion programs rely on organizations and targeted sectors to disseminate these programs although relatively little is known about organizational-level and sector-level influences that lead to their adoption and implementation. METHODS: Cases (n=154) were eligible if they had signed an ALED license agreement with Human Kinetics (HK), publisher of the program's textbooks and facilitator manuals, between 2001 and 2008. Two types of controls were matched (2:2:1) and stratified by sector and region. Active controls (Control 1; n=319) were organizations that contacted HK to consider adopting ALED. Passive controls (Control 2; n=328) were organizations that received unsolicited marketing materials and did not initiate contact with HK. We used Diffusion of Innovations Theory (DIT) constructs as the basis for developing the survey of cases and controls. RESULTS: Using the multi-method strategy recommended by Dillman, a total of n=801 cases and controls were surveyed. Most organizations were from the fitness sector followed by medical, nongovernmental, governmental, educational, worksite and other sectors with significantly higher response rates from government

A Data-Based Approach to Discovering Multi-Topic Influential Leaders.

Directory of Open Access Journals (Sweden)

Xing Tang

Full Text Available Recently, increasing numbers of users have adopted microblogging services as their main information source. However, most of them find themselves drowning in the millions of posts produced by other users every day. To cope with this, identifying a set of the most influential people is paramount. Moreover, finding a set of related influential users to expand the coverage of one particular topic is required in real world scenarios. Most of the existing algorithms in this area focus on topology-related methods such as PageRank. These methods mine link structures to find the expected influential rank of users. However, because they ignore the interaction data, these methods turn out to be less effective in social networks. In reality, a variety of topics exist within the information diffusing through the network. Because they have different interests, users play different roles in the diffusion of information related to different topics. As a result, distinguishing influential leaders according to different topics is also worthy of research. In this paper, we propose a multi-topic influence diffusion model (MTID based on traces acquired from historic information. We decompose the influential scores of users into two parts: the direct influence determined by information propagation along the link structure and indirect influence that extends beyond the restrictions of direct follower relationships. To model the network from a multi-topical viewpoint, we introduce topic pools, each of which represents a particular topic information source. Then, we extract the topic distributions from the traces of tweets, determining the influence propagation probability and content generation probability. In the network, we adopt multiple ground nodes representing topic pools to connect every user through bidirectional links. Based on this multi-topical view of the network, we further introduce the topic-dependent rank (TD-Rank algorithm to identify the multi

A Data-Based Approach to Discovering Multi-Topic Influential Leaders.

Science.gov (United States)

Tang, Xing; Miao, Qiguang; Yu, Shangshang; Quan, Yining

2016-01-01

Recently, increasing numbers of users have adopted microblogging services as their main information source. However, most of them find themselves drowning in the millions of posts produced by other users every day. To cope with this, identifying a set of the most influential people is paramount. Moreover, finding a set of related influential users to expand the coverage of one particular topic is required in real world scenarios. Most of the existing algorithms in this area focus on topology-related methods such as PageRank. These methods mine link structures to find the expected influential rank of users. However, because they ignore the interaction data, these methods turn out to be less effective in social networks. In reality, a variety of topics exist within the information diffusing through the network. Because they have different interests, users play different roles in the diffusion of information related to different topics. As a result, distinguishing influential leaders according to different topics is also worthy of research. In this paper, we propose a multi-topic influence diffusion model (MTID) based on traces acquired from historic information. We decompose the influential scores of users into two parts: the direct influence determined by information propagation along the link structure and indirect influence that extends beyond the restrictions of direct follower relationships. To model the network from a multi-topical viewpoint, we introduce topic pools, each of which represents a particular topic information source. Then, we extract the topic distributions from the traces of tweets, determining the influence propagation probability and content generation probability. In the network, we adopt multiple ground nodes representing topic pools to connect every user through bidirectional links. Based on this multi-topical view of the network, we further introduce the topic-dependent rank (TD-Rank) algorithm to identify the multi-topic influential users

Distributed model based control of multi unit evaporation systems

International Nuclear Information System (INIS)

Yudi Samyudia

2006-01-01

In this paper, we present a new approach to the analysis and design of distributed control systems for multi-unit plants. The approach is established after treating the effect of recycled dynamics as a gap metric uncertainty from which a distributed controller can be designed sequentially for each unit to tackle the uncertainty. We then use a single effect multi-unit evaporation system to illustrate how the proposed method is used to analyze different control strategies and to systematically achieve a better closed-loop performance using a distributed model-based controller

Fast Multi-Symbol Based Iterative Detectors for UWB Communications

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Lottici Vincenzo

2010-01-01

Full Text Available Ultra-wideband (UWB impulse radios have shown great potential in wireless local area networks for localization, coexistence with other services, and low probability of interception and detection. However, low transmission power and high multipath effect make the detection of UWB signals challenging. Recently, multi-symbol based detection has caught attention for UWB communications because it provides good performance and does not require explicit channel estimation. Most of the existing multi-symbol based methods incur a higher computational cost than can be afforded in the envisioned UWB systems. In this paper, we propose an iterative multi-symbol based method that has low complexity and provides near optimal performance. Our method uses only one initial symbol to start and applies a decision directed approach to iteratively update a filter template and information symbols. Simulations show that our method converges in only a few iterations (less than 5, and that when the number of symbols increases, the performance of our method approaches that of the ideal Rake receiver.

Simultaneous observations of electromagnetically induced transparency (EIT) and absorption (EIA) in a multi-level V-type system of 87Rb and theoretical simulation of the observed spectra using a multi-mode approach.

Science.gov (United States)

Das, Bankim Chandra; Bhattacharyya, Dipankar; Das, Arpita; Chakrabarti, Shrabana; De, Sankar

2016-12-14

We report here simultaneous experimental observation of Electromagnetically Induced Transparency (EIT) and Electromagnetically Induced Absorption (EIA) in a multi-level V-type system in D 2 transition of Rb87, i.e., F=2→F ' with a strong pump and a weak probe beam. We studied the probe spectrum by locking the probe beam to the transition F=2→F ' =2 while the pump is scanned from F=2→F ' . EIA is observed for the open transition (F=2→F ' =2) whereas EIT is observed in the closed transition (F=2→F ' =3). Sub natural line-width is observed for the EIA. To simulate the observed spectra theoretically, Liouville equation for the three-level V-type system is solved analytically with a multi-mode approach for the density matrix elements. We assumed both the pump and the probe beams can couple the excited states. A multi-mode approach for the coherence terms facilitates the study of all the frequency contributions due to the pump and the probe fields. Since the terms contain higher harmonics of the pump and the probe frequencies, we expressed them in Fourier transformed forms. To simulate the probe spectrum, we have solved inhomogeneous difference equations for the coherence terms using the Green's function technique and continued fraction theory. The experimental line-widths of the EIT and the EIA are compared with our theoretical model. Our system can be useful in optical switching applications as it can be precisely tuned to render the medium opaque and transparent simultaneously.

Lot Sizing Based on Stochastic Demand and Service Level Constraint

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hajar shirneshan

2012-06-01

Full Text Available Considering its application, stochastic lot sizing is a significant subject in production planning. Also the concept of service level is more applicable than shortage cost from managers' viewpoint. In this paper, the stochastic multi period multi item capacitated lot sizing problem has been investigated considering service level constraint. First, the single item model has been developed considering service level and with no capacity constraint and then, it has been solved using dynamic programming algorithm and the optimal solution has been derived. Then the model has been generalized to multi item problem with capacity constraint. The stochastic multi period multi item capacitated lot sizing problem is NP-Hard, hence the model could not be solved by exact optimization approaches. Therefore, simulated annealing method has been applied for solving the problem. Finally, in order to evaluate the efficiency of the model, low level criterion has been used .

Rayleigh-based, multi-element coral thermometry: A biomineralization approach to developing climate proxies

Science.gov (United States)

Gaetani, G.A.; Cohen, A.L.; Wang, Z.; Crusius, John

2011-01-01

This study presents a new approach to coral thermometry that deconvolves the influence of water temperature on skeleton composition from that of “vital effects”, and has the potential to provide estimates of growth temperatures that are accurate to within a few tenths of a degree Celsius from both tropical and cold-water corals. Our results provide support for a physico-chemical model of coral biomineralization, and imply that Mg2+ substitutes directly for Ca2+ in biogenic aragonite. Recent studies have identified Rayleigh fractionation as an important influence on the elemental composition of coral skeletons. Daily, seasonal and interannual variations in the amount of aragonite precipitated by corals from each “batch” of calcifying fluid can explain why the temperature dependencies of elemental ratios in coral skeleton differ from those of abiogenic aragonites, and are highly variable among individual corals. On the basis of this new insight into the origin of “vital effects” in coral skeleton, we developed a Rayleigh-based, multi-element approach to coral thermometry. Temperature is resolved from the Rayleigh fractionation signal by combining information from multiple element ratios (e.g., Mg/Ca, Sr/Ca, Ba/Ca) to produce a mathematically over-constrained system of Rayleigh equations. Unlike conventional coral thermometers, this approach does not rely on an initial calibration of coral skeletal composition to an instrumental temperature record. Rather, considering coral skeletogenesis as a biologically mediated, physico-chemical process provides a means to extract temperature information from the skeleton composition using the Rayleigh equation and a set of experimentally determined partition coefficients. Because this approach is based on a quantitative understanding of the mechanism that produces the “vital effect” it should be possible to apply it both across scleractinian species and to corals growing in vastly different environments. Where

MODELING OF INVESTMENT STRATEGIES IN STOCKS MARKETS: AN APPROACH FROM MULTI AGENT BASED SIMULATION AND FUZZY LOGIC

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ALEJANDRO ESCOBAR

2010-01-01

Full Text Available This paper presents a simulation model of a complex system, in this case a financial market, using a MultiAgent Based Simulation approach. Such model takes into account microlevel aspects like the Continuous Double Auction mechanism, which is widely used within stock markets, as well as investor agents reasoning who participate looking for profits. To model such reasoning several variables were considered including general stocks information like profitability and volatility, but also some agent's aspects like their risk tendency. All these variables are incorporated throughout a fuzzy logic approach trying to represent in a faithful manner the kind of reasoning that nonexpert investors have, including a stochastic component in order to model human factors.

A social marketing approach to implementing evidence-based practice in VHA QUERI: the TIDES depression collaborative care model

Science.gov (United States)

2009-01-01

Abstract Collaborative care models for depression in primary care are effective and cost-effective, but difficult to spread to new sites. Translating Initiatives for Depression into Effective Solutions (TIDES) is an initiative to promote evidence-based collaborative care in the U.S. Veterans Health Administration (VHA). Social marketing applies marketing techniques to promote positive behavior change. Described in this paper, TIDES used a social marketing approach to foster national spread of collaborative care models. TIDES social marketing approach The approach relied on a sequential model of behavior change and explicit attention to audience segmentation. Segments included VHA national leadership, Veterans Integrated Service Network (VISN) regional leadership, facility managers, frontline providers, and veterans. TIDES communications, materials and messages targeted each segment, guided by an overall marketing plan. Results Depression collaborative care based on the TIDES model was adopted by VHA as part of the new Primary Care Mental Health Initiative and associated policies. It is currently in use in more than 50 primary care practices across the United States, and continues to spread, suggesting success for its social marketing-based dissemination strategy. Discussion and conclusion Development, execution and evaluation of the TIDES marketing effort shows that social marketing is a promising approach for promoting implementation of evidence-based interventions in integrated healthcare systems. PMID:19785754

Just how multi-level is leadership research? A document co-citation analysis 1980–2013 on leadership constructs and outcomes

OpenAIRE

Batistic, S.; Cerne, M.; Vogel, Bernd

2017-01-01

The use of multi-level theories and methodologies in leadership has gained momentum in recent years. However, the leadership field still suffers from a fragmented and unclear evolution and practice of multi-level approaches. The questions of how and to what extent multi-level research has evolved in both leadership phenomena and leadership outcomes, and which informal research networks drove this evolution, remain vastly unexplored. In this study, the extent of literature published between 19...

A multi-disciplinary approach for the integrated assessment of multiple risks in delta areas.

Science.gov (United States)

Sperotto, Anna; Torresan, Silvia; Critto, Andrea; Marcomini, Antonio

2016-04-01

The assessment of climate change related risks is notoriously difficult due to the complex and uncertain combinations of hazardous events that might happen, the multiplicity of physical processes involved, the continuous changes and interactions of environmental and socio-economic systems. One important challenge lies in predicting and modelling cascades of natural and man -made hazard events which can be triggered by climate change, encompassing different spatial and temporal scales. Another regard the potentially difficult integration of environmental, social and economic disciplines in the multi-risk concept. Finally, the effective interaction between scientists and stakeholders is essential to ensure that multi-risk knowledge is translated into efficient adaptation and management strategies. The assessment is even more complex at the scale of deltaic systems which are particularly vulnerable to global environmental changes, due to the fragile equilibrium between the presence of valuable natural ecosystems and relevant economic activities. Improving our capacity to assess the combined effects of multiple hazards (e.g. sea-level rise, storm surges, reduction in sediment load, local subsidence, saltwater intrusion) is therefore essential to identify timely opportunities for adaptation. A holistic multi-risk approach is here proposed to integrate terminology, metrics and methodologies from different research fields (i.e. environmental, social and economic sciences) thus creating shared knowledge areas to advance multi risk assessment and management in delta regions. A first testing of the approach, including the application of Bayesian network analysis for the assessment of impacts of climate change on key natural systems (e.g. wetlands, protected areas, beaches) and socio-economic activities (e.g. agriculture, tourism), is applied in the Po river delta in Northern Italy. The approach is based on a bottom-up process involving local stakeholders early in different

Multi-level Control Framework for Enhanced Flexibility of Active Distribution Network

DEFF Research Database (Denmark)

Nainar, Karthikeyan; Pokhrel, Basanta Raj; Pillai, Jayakrishnan Radhakrishna

2017-01-01

In this paper, the control objectives of future active distribution networks with high penetration of renewables and flexible loads are analyzed and reviewed. From a state of the art review, the important control objectives seen from the perspective of a distribution system operator are identifie......-ordination and management of the network assets at different voltage levels and geographical locations. The paper finally shows the applicability of the multi-level control architecture to some of the key challenges in the distribution system operation by relevant scenarios....... to be hosting capacity improvement, high reliable operation and cost effective network management. Based on this review and a state of the art review concerning future distribution network control methods, a multi-level control architecture is constructed for an active distribution network, which satisfies...... the selected control objectives and provides enhanced flexibility. The control architecture is supported by generation/load forecasting and distribution state estimation techniques to improve the controllability of the network. The multi-level control architecture consists of three levels of hierarchical...

In the teeth of the evidence: the curious case of evidence-based medicine.

Science.gov (United States)

Davidoff, F

1999-03-01

For a very long time, evidence from research has contributed to clinical decision making. Over the past 50 years, however, the nature of clinical research evidence has drastically changed compared with previous eras: its standards are higher, the tools for assembling and analyzing it are more powerful, and the context in which it is used is less authoritarian. The consequence has been a shift in both the concept and the practice of clinical decision making known as evidence-based medicine. Evidence-based decisions, by definition, use the strongest available evidence, are often more quantitatively informed than decisions made in the traditional fashion; and sometimes run counter to expert opinion. The techniques of evidence-based medicine are also helpful in resolving conflicting opinions. Evidence-based medicine did not simply appear in vacuo; its roots extend back at least as far as the great French Encyclopedia of the 18th century, and the subsequent work of Pierre Louis in Paris in the early 19th century. The power of the evidence-based approach has been enhanced in recent years by the development of the techniques of systematic review and meta-analysis. While this approach has its critics, we would all want the best available evidence used in making decisions about our care if we got sick. It is only fair that the patients under our care receive nothing less.

Hierarchical graphical-based human pose estimation via local multi-resolution convolutional neural network

Science.gov (United States)

Zhu, Aichun; Wang, Tian; Snoussi, Hichem

2018-03-01

This paper addresses the problems of the graphical-based human pose estimation in still images, including the diversity of appearances and confounding background clutter. We present a new architecture for estimating human pose using a Convolutional Neural Network (CNN). Firstly, a Relative Mixture Deformable Model (RMDM) is defined by each pair of connected parts to compute the relative spatial information in the graphical model. Secondly, a Local Multi-Resolution Convolutional Neural Network (LMR-CNN) is proposed to train and learn the multi-scale representation of each body parts by combining different levels of part context. Thirdly, a LMR-CNN based hierarchical model is defined to explore the context information of limb parts. Finally, the experimental results demonstrate the effectiveness of the proposed deep learning approach for human pose estimation.

Hierarchical graphical-based human pose estimation via local multi-resolution convolutional neural network

Directory of Open Access Journals (Sweden)

Aichun Zhu

2018-03-01

Full Text Available This paper addresses the problems of the graphical-based human pose estimation in still images, including the diversity of appearances and confounding background clutter. We present a new architecture for estimating human pose using a Convolutional Neural Network (CNN. Firstly, a Relative Mixture Deformable Model (RMDM is defined by each pair of connected parts to compute the relative spatial information in the graphical model. Secondly, a Local Multi-Resolution Convolutional Neural Network (LMR-CNN is proposed to train and learn the multi-scale representation of each body parts by combining different levels of part context. Thirdly, a LMR-CNN based hierarchical model is defined to explore the context information of limb parts. Finally, the experimental results demonstrate the effectiveness of the proposed deep learning approach for human pose estimation.

Population-based dietary approaches for the prevention of noncommunicable diseases.

Science.gov (United States)

Somasundaram, Noel P; Kalupahana, Nishan Sudheera

2016-04-01

As the incidence of noncommunicable diseases such as diabetes continues to rise at an alarming rate in South-East Asia, it is imperative that urgent and population-wide strategies are adopted. The most important contributors to the rise in noncommunicable disease are a rise in mean caloric intake and a decrease in physical activity. The evidence for population-based dietary approaches to counter these factors is reviewed. Several structural and cohesive interdepartmental coordination efforts are required for effective implementation of prevention strategies. Since low- and middle-income countries may lack the frameworks for effective and integrated multi-stakeholder intervention, implementation of population-based dietary and physical-activity approaches may be delayed and may be too late for effective prevention in current at-risk cohorts. Evidence-based strategies to decrease energy intake and increase physical activity are now well established and their urgent adoption by Member States of the World Health Organization South-East Asia Region is essential. In the context of Sri Lanka, for example, it is recommended that the most effective and easy-to-implement interventions would be media campaigns, restrictions on advertisement of unhealthy foods, taxation of unhealthy foods, subsidies for production of healthy foods, and laws on nutrition labelling that introduce colour coding of packaged foods.

A Pareto-based multi-objective optimization algorithm to design energy-efficient shading devices

International Nuclear Information System (INIS)

Khoroshiltseva, Marina; Slanzi, Debora; Poli, Irene

2016-01-01

Highlights: • We present a multi-objective optimization algorithm for shading design. • We combine Harmony search and Pareto-based procedures. • Thermal and daylighting performances of external shading were considered. • We applied the optimization process to a residential social housing in Madrid. - Abstract: In this paper we address the problem of designing new energy-efficient static daylight devices that will surround the external windows of a residential building in Madrid. Shading devices can in fact largely influence solar gains in a building and improve thermal and lighting comforts by selectively intercepting the solar radiation and by reducing the undesirable glare. A proper shading device can therefore significantly increase the thermal performance of a building by reducing its energy demand in different climate conditions. In order to identify the set of optimal shading devices that allow a low energy consumption of the dwelling while maintaining high levels of thermal and lighting comfort for the inhabitants we derive a multi-objective optimization methodology based on Harmony Search and Pareto front approaches. The results show that the multi-objective approach here proposed is an effective procedure in designing energy efficient shading devices when a large set of conflicting objectives characterizes the performance of the proposed solutions.

A Quasi-Feed-In-Tariff policy formulation in micro-grids: A bi-level multi-period approach

International Nuclear Information System (INIS)

Taha, Ahmad F.; Hachem, Nadim A.; Panchal, Jitesh H.

2014-01-01

A Quasi-Feed-In-Tariff (QFIT) policy formulation is presented for micro-grids that integrates renewable energy generation considering Policy Makers' and Generation Companies' (GENCOs) objectives assuming a bi-level multi-period formulation that integrates physical characteristics of the power-grid. The upper-level problem corresponds to the PM, whereas the lower-level decisions are made by GENCOs. We consider that some GENCOs are green energy producers, while others are black energy producers. Policy makers incentivize green energy producers to generate energy through the payment of optimal time-varying subsidy price. The policy maker's main objective is to maximize an overall social welfare that includes factors such as demand surplus, energy cost, renewable energy subsidy price, and environmental standards. The lower-level problem corresponding to the GENCOs is based on maximizing the players' profits. The proposed QFIT policy differs from the FIT policy in the sense that the subsidy price-based contracts offered to green energy producers dynamically change over time, depending on the physical properties of the grid, demand, and energy price fluctuations. The integrated problem solves for time-varying subsidy price and equilibrium energy quantities that optimize the system welfare under different grid and system conditions. - Highlights: • We present a bi-level optimization problem formulation for Quasi-Feed-In-Tariff (QFIT) policy. • QFIT dictates that subsidy prices dynamically vary over time depending on conditions. • Power grid's physical characteristics affect optimal subsidy prices and energy generation. • To maximize welfare, policy makers ought to increase subsidy prices during the peak-load

Evidence-based toxicology for the 21st century: opportunities and challenges.

Science.gov (United States)

Stephens, Martin L; Andersen, Melvin; Becker, Richard A; Betts, Kellyn; Boekelheide, Kim; Carney, Ed; Chapin, Robert; Devlin, Dennis; Fitzpatrick, Suzanne; Fowle, John R; Harlow, Patricia; Hartung, Thomas; Hoffmann, Sebastian; Holsapple, Michael; Jacobs, Abigail; Judson, Richard; Naidenko, Olga; Pastoor, Tim; Patlewicz, Grace; Rowan, Andrew; Scherer, Roberta; Shaikh, Rashid; Simon, Ted; Wolf, Douglas; Zurlo, Joanne

2013-01-01

The Evidence-based Toxicology Collaboration (EBTC) was established recently to translate evidence-based approaches from medicine and health care to toxicology in an organized and sustained effort. The EBTC held a workshop on "Evidence-based Toxicology for the 21st Century: Opportunities and Challenges" in Research Triangle Park, North Carolina, USA on January 24-25, 2012. The presentations largely reflected two EBTC priorities: to apply evidence-based methods to assessing the performance of emerging pathway-based testing methods consistent with the 2007 National Research Council report on "Toxicity Testing in the 21st Century" as well as to adopt a governance structure and work processes to move that effort forward. The workshop served to clarify evidence-based approaches and to provide food for thought on substantive and administrative activities for the EBTC. Priority activities include conducting pilot studies to demonstrate the value of evidence-based approaches to toxicology, as well as conducting educational outreach on these approaches.

Knowledge-based approach to video content classification

Science.gov (United States)

Chen, Yu; Wong, Edward K.

2001-01-01

A framework for video content classification using a knowledge-based approach is herein proposed. This approach is motivated by the fact that videos are rich in semantic contents, which can best be interpreted and analyzed by human experts. We demonstrate the concept by implementing a prototype video classification system using the rule-based programming language CLIPS 6.05. Knowledge for video classification is encoded as a set of rules in the rule base. The left-hand-sides of rules contain high level and low level features, while the right-hand-sides of rules contain intermediate results or conclusions. Our current implementation includes features computed from motion, color, and text extracted from video frames. Our current rule set allows us to classify input video into one of five classes: news, weather, reporting, commercial, basketball and football. We use MYCIN's inexact reasoning method for combining evidences, and to handle the uncertainties in the features and in the classification results. We obtained good results in a preliminary experiment, and it demonstrated the validity of the proposed approach.

A Multi-Faceted Approach to Inquiry-Based Learning

Science.gov (United States)

Brudzinski, M. R.; Sikorski, J.

2009-12-01

In order to fully attain the benefits of inquiry-based learning, instructors who typically employ the traditional lecture format need to make several adjustments to their approach. This change in styles can be intimidating and logistically difficult to overcome. A stepwise approach to this transformation is likely to be more manageable for individual faculty or departments. In this session, we will describe several features that we are implementing in our introductory geology course with the ultimate goal of converting to an entirely inquiry-based approach. Our project is part of the Miami University initiative in the top 25 enrolled courses to move towards the “student as scholar” model for engaged learning. Some of the features we developed for our course include: student learning outcomes, student development outcomes, out-of-class content quizzes, in-class conceptests, pre-/post-course assessment, reflective knowledge surveys, and daily group activities.

Ship Detection in Optical Remote Sensing Images Based on Wavelet Transform and Multi-Level False Alarm Identification

Directory of Open Access Journals (Sweden)

Fang Xu

2017-09-01

Full Text Available Ship detection by Unmanned Airborne Vehicles (UAVs and satellites plays an important role in a spectrum of related military and civil applications. To improve the detection efficiency, accuracy, and speed, a novel ship detection method from coarse to fine is presented. Ship targets are viewed as uncommon regions in the sea background caused by the differences in colors, textures, shapes, or other factors. Inspired by this fact, a global saliency model is constructed based on high-frequency coefficients of the multi-scale and multi-direction wavelet decomposition, which can characterize different feature information from edge to texture of the input image. To further reduce the false alarms, a new and effective multi-level discrimination method is designed based on the improved entropy and pixel distribution, which is robust against the interferences introduced by islands, coastlines, clouds, and shadows. The experimental results on optical remote sensing images validate that the presented saliency model outperforms the comparative models in terms of the area under the receiver operating characteristic curves core and the accuracy in the images with different sizes. After the target identification, the locations and the number of the ships in various sizes and colors can be detected accurately and fast with high robustness.

Fault-Tolerant Control of ANPC Three-Level Inverter Based on Order-Reduction Optimal Control Strategy under Multi-Device Open-Circuit Fault.

Science.gov (United States)

Xu, Shi-Zhou; Wang, Chun-Jie; Lin, Fang-Li; Li, Shi-Xiang

2017-10-31

The multi-device open-circuit fault is a common fault of ANPC (Active Neutral-Point Clamped) three-level inverter and effect the operation stability of the whole system. To improve the operation stability, this paper summarized the main solutions currently firstly and analyzed all the possible states of multi-device open-circuit fault. Secondly, an order-reduction optimal control strategy was proposed under multi-device open-circuit fault to realize fault-tolerant control based on the topology and control requirement of ANPC three-level inverter and operation stability. This control strategy can solve the faults with different operation states, and can works in order-reduction state under specific open-circuit faults with specific combined devices, which sacrifices the control quality to obtain the stability priority control. Finally, the simulation and experiment proved the effectiveness of the proposed strategy.

Interactive Fuzzy Goal Programming approach in multi-response stratified sample surveys

Directory of Open Access Journals (Sweden)

Gupta Neha

2016-01-01

Full Text Available In this paper, we applied an Interactive Fuzzy Goal Programming (IFGP approach with linear, exponential and hyperbolic membership functions, which focuses on maximizing the minimum membership values to determine the preferred compromise solution for the multi-response stratified surveys problem, formulated as a Multi- Objective Non Linear Programming Problem (MONLPP, and by linearizing the nonlinear objective functions at their individual optimum solution, the problem is approximated to an Integer Linear Programming Problem (ILPP. A numerical example based on real data is given, and comparison with some existing allocations viz. Cochran’s compromise allocation, Chatterjee’s compromise allocation and Khowaja’s compromise allocation is made to demonstrate the utility of the approach.

Mechanical analyses on the digital behaviour of the Tokay gecko (Gekko gecko) based on a multi-level directional adhesion model

OpenAIRE

Wu, Xuan; Wang, Xiaojie; Mei, Tao; Sun, Shaoming

2015-01-01

This paper proposes a multi-level hierarchical model for the Tokay gecko (Gekko gecko) adhesive system and analyses the digital behaviour of the G. gecko under macro/meso-level scale. The model describes the structures of G. gecko's adhesive system from the nano-level spatulae to the sub-millimetre-level lamella. The G. gecko's seta is modelled using inextensible fibril based on Euler's elastica theorem. Considering the side contact of the spatular pads of the seta on the flat and rigid subst...

Tunable complex-valued multi-tap microwave photonic filter based on single silicon-on-insulator microring resonator.

Science.gov (United States)

Lloret, Juan; Sancho, Juan; Pu, Minhao; Gasulla, Ivana; Yvind, Kresten; Sales, Salvador; Capmany, José

2011-06-20

A complex-valued multi-tap tunable microwave photonic filter based on single silicon-on-insulator microring resonator is presented. The degree of tunability of the approach involving two, three and four taps is theoretical and experimentally characterized, respectively. The constraints of exploiting the optical phase transfer function of a microring resonator aiming at implementing complex-valued multi-tap filtering schemes are also reported. The trade-off between the degree of tunability without changing the free spectral range and the number of taps is studied in-depth. Different window based scenarios are evaluated for improving the filter performance in terms of the side-lobe level.

Operational validation of a multi-period and multi-criteria model conditioning approach for the prediction of rainfall-runoff processes in small forest catchments

Science.gov (United States)

Choi, H.; Kim, S.

2012-12-01

Most of hydrologic models have generally been used to describe and represent the spatio-temporal variability of hydrological processes in the watershed scale. Though it is an obvious fact that hydrological responses have the time varying nature, optimal values of model parameters were normally considered as time invariants or constants in most cases. The recent paper of Choi and Beven (2007) presents a multi-period and multi-criteria model conditioning approach. The approach is based on the equifinality thesis within the Generalised Likelihood Uncertainty Estimation (GLUE) framework. In their application, the behavioural TOPMODEL parameter sets are determined by several performance measures for global (annual) and short (30-days) periods, clustered using a Fuzzy C-means algorithm, into 15 types representing different hydrological conditions. Their study shows a good performance on the calibration of a rainfall-runoff model in a forest catchment, and also gives strong indications that it is uncommon to find model realizations that were behavioural over all multi-periods and all performance measures, and multi-period model conditioning approach may become new effective tool for predictions of hydrological processes in ungauged catchments. This study is a follow-up study on the Choi and Beven's (2007) model conditioning approach to test how the approach is effective for the prediction of rainfall-runoff responses in ungauged catchments. To achieve this purpose, 6 small forest catchments are selected among the several hydrological experimental catchments operated by Korea Forest Research Institute. In each catchment, long-term hydrological time series data varying from 10 to 30 years were available. The areas of the selected catchments range from 13.6 to 37.8 ha, and all areas are covered by coniferous or broad-leaves forests. The selected catchments locate in the southern coastal area to the northern part of South Korea. The bed rocks are Granite gneiss, Granite or

Electrically-controlled nonlinear switching and multi-level storage characteristics in WOx film-based memory cells

Science.gov (United States)

Duan, W. J.; Wang, J. B.; Zhong, X. L.

2018-05-01

Resistive switching random access memory (RRAM) is considered as a promising candidate for the next generation memory due to its scalability, high integration density and non-volatile storage characteristics. Here, the multiple electrical characteristics in Pt/WOx/Pt cells are investigated. Both of the nonlinear switching and multi-level storage can be achieved by setting different compliance current in the same cell. The correlations among the current, time and temperature are analyzed by using contours and 3D surfaces. The switching mechanism is explained in terms of the formation and rupture of conductive filament which is related to oxygen vacancies. The experimental results show that the non-stoichiometric WOx film-based device offers a feasible way for the applications of oxide-based RRAMs.

Multi-energy CT based on a prior rank, intensity and sparsity model (PRISM)

International Nuclear Information System (INIS)

Gao, Hao; Osher, Stanley; Yu, Hengyong; Wang, Ge

2011-01-01

We propose a compressive sensing approach for multi-energy computed tomography (CT), namely the prior rank, intensity and sparsity model (PRISM). To further compress the multi-energy image for allowing the reconstruction with fewer CT data and less radiation dose, the PRISM models a multi-energy image as the superposition of a low-rank matrix and a sparse matrix (with row dimension in space and column dimension in energy), where the low-rank matrix corresponds to the stationary background over energy that has a low matrix rank, and the sparse matrix represents the rest of distinct spectral features that are often sparse. Distinct from previous methods, the PRISM utilizes the generalized rank, e.g., the matrix rank of tight-frame transform of a multi-energy image, which offers a way to characterize the multi-level and multi-filtered image coherence across the energy spectrum. Besides, the energy-dependent intensity information can be incorporated into the PRISM in terms of the spectral curves for base materials, with which the restoration of the multi-energy image becomes the reconstruction of the energy-independent material composition matrix. In other words, the PRISM utilizes prior knowledge on the generalized rank and sparsity of a multi-energy image, and intensity/spectral characteristics of base materials. Furthermore, we develop an accurate and fast split Bregman method for the PRISM and demonstrate the superior performance of the PRISM relative to several competing methods in simulations. (papers)

Multi-interface Level Sensors and New Development in Monitoring and Control of Oil Separators

Directory of Open Access Journals (Sweden)

Wuqiang Yang

2006-04-01

Full Text Available In the oil industry, huge saving may be made if suitable multi-interface levelmeasurement systems are employed for effectively monitoring crude oil separators andefficient control of their operation. A number of techniques, e.g. externally mounteddisplacers, differential pressure transmitters and capacitance rod devices, have beendeveloped to measure the separation process with gas, oil, water and other components.Because of the unavailability of suitable multi-interface level measurement systems, oilseparators are currently operated by the trial-and-error approach. In this paper someconventional techniques, which have been used for level measurement in industry, and newdevelopment are discussed.

Teaching evidence-based medicine using a problem-oriented approach.

Science.gov (United States)

Hosny, Somaya; Ghaly, Mona S

2014-04-01

Faculty of Medicine, Suez Canal University is adopting an innovative curriculum. Evidence-based medicine (EBM) has been integrated into problem based learning (PBL) sessions as a responsive innovative paradigm for the practice and teaching of clinical medicine. To integrate EBM in the problem based sessions of the sixth-year students, and to assess students' and tutor satisfaction with this change. EBM training was conducted for sixth-year students (196) including four theoretical, and eight practical sessions. Sixteen EBM educational scenarios (problems) were formulated, according to sixth-year curriculum. Each problem was discussed in two sessions through steps of EBM, namely: formulating PICO questions, searching for and appraising evidence, applying the evidence to the clinical scenario and analysing the practice. Students and tutors satisfaction were evaluated using a 3-point ratings questionnaire. The majority of students and faculty expressed their satisfaction about integrating EBM with PBL and agreed that the problems were more stimulating. However, 33.6% of students indicated that available time was insufficient for searching literatures. Integrating EBM into PBL sessions tends to be more interesting and stimulating than traditional PBL sessions for final year students and helps them to practice and implement EBM in clinical context.

Evidence-based Paradigm In Orthodontics | Ajayi | Nigerian ...

African Journals Online (AJOL)

The need to integrate the accrued scientific evidence into clinical orthodontic practice is amongst the challenges facing orthodontists in the 21st century. The evidence-based health care approach aims to improve patient care based upon informed decision-making. This article therefore highlights the importance and ...

Energetic Variational Approach to Multi-Component Fluid Flows

Science.gov (United States)

Kirshtein, Arkadz; Liu, Chun; Brannick, James

2017-11-01

In this talk I will introduce the systematic energetic variational approach for dissipative systems applied to multi-component fluid flows. These variational approaches are motivated by the seminal works of Rayleigh and Onsager. The advantage of this approach is that we have to postulate only energy law and some kinematic relations based on fundamental physical principles. The method gives a clear, quick and consistent way to derive the PDE system. I will compare different approaches to three-component flows using diffusive interface method and discuss their advantages and disadvantages. The diffusive interface method is an approach for modeling interactions among complex substances. The main idea behind this method is to introduce phase field labeling functions in order to model the contact line by smooth change from one type of material to another. The work of Arkadz Kirshtein and Chun Liu is partially supported by NSF Grants DMS-141200 and DMS-1216938.

Multi-level converter with auxiliary resonant-commutated pole

NARCIS (Netherlands)

Dijkhuizen, F.R.; Duarte, J.L.; Groningen, van W.D.H.

1998-01-01

The family of multi-level power converters offers advantages for high-power, high-voltage systems. A multi-level nested-cell structure has the attractive feature of static and dynamic voltage sharing among the switches. This is achieved by using clamping capacitors (floating capacitors) rather than

Multi-Level Marketing - a Tool of Relationship Marketing

Directory of Open Access Journals (Sweden)

Constantin C.

2009-12-01

Full Text Available This paper aims to analyse the opportunity of using multi-level marketing (MLM as a tool of relationship marketing. The research is firstly based on an analysis regarding the issues about the legality of MLM techniques in the context of EU and US regulation systems. The outcomes of this research stress the main characteristics of legal network marketing and how a person which wants to become independent distributor could avoid the cooperation with an illegal pyramid scheme. The second research is based on a case study at the level of an insurance broker, which emphasizes the benefits that all parties involved in a transaction (broker, distributor and customer could obtain by using an MLM scheme.

Introduction: evidence-based action in humanitarian crises

NARCIS (Netherlands)

Dijkzeul, D.; Hilhorst, D.; Walker, P.

2013-01-01

This introductory paper sets the stage for this special issue of Disasters on evidence-based action in humanitarian crises. It reviews definition(s) of evidence and it examines the different disciplinary and methodological approaches to collecting and analysing evidence. In humanitarian action, the

Treatment for bovine Escherichia coli mastitis - an evidence-based approach.

Science.gov (United States)

Suojala, L; Kaartinen, L; Pyörälä, S

2013-12-01

Bovine mastitis caused by Escherichia coli can range from being a subclinical infection of the mammary gland to a severe systemic disease. Cow-dependent factors such as lactation stage and age affect the severity of coliform mastitis. Evidence for the efficacy of antimicrobial treatment for E. coli mastitis is very limited. Antimicrobial resistance is generally not a limiting factor for treatment, but it should be monitored to detect changes in resistance profiles. The only antimicrobials for which there is some scientific evidence of beneficial effects in the treatment for E. coli mastitis are fluoroquinolones and cephalosporins. Both are critically important drugs, the use of which in animals destined for food should be limited to specific indications and should be based on bacteriological diagnosis. The suggested routine protocol in dairy herds could target the primary antimicrobial treatment for mastitis, specifically infections caused by gram-positive bacteria. In E. coli mastitis with mild to moderate clinical signs, a non-antimicrobial approach (anti-inflammatory treatment, frequent milking and fluid therapy) should be the first option. In cases of severe E. coli mastitis, parenteral administration of fluoroquinolones, or third- or fourth-generation cephalosporins, is recommended due to the risk of unlimited growth of bacteria in the mammary gland and ensuing bacteremia. Evidence for the efficacy of intramammary-administered antimicrobial treatment for E. coli mastitis is so limited that it cannot be recommended. Nonsteroidal anti-inflammatory drugs have documented the efficacy in the treatment for E. coli mastitis and are recommended for supportive treatment for clinical mastitis. © 2013 John Wiley & Sons Ltd.

Big data privacy protection model based on multi-level trusted system

Science.gov (United States)

Zhang, Nan; Liu, Zehua; Han, Hongfeng

2018-05-01

This paper introduces and inherit the multi-level trusted system model that solves the Trojan virus by encrypting the privacy of user data, and achieve the principle: "not to read the high priority hierarchy, not to write the hierarchy with low priority". Thus ensuring that the low-priority data privacy leak does not affect the disclosure of high-priority data privacy. This paper inherits the multi-level trustworthy system model of Trojan horse and divides seven different risk levels. The priority level 1˜7 represent the low to high value of user data privacy, and realize seven kinds of encryption with different execution efficiency Algorithm, the higher the priority, the greater the value of user data privacy, at the expense of efficiency under the premise of choosing a more encrypted encryption algorithm to ensure data security. For enterprises, the price point is determined by the unit equipment users to decide the length of time. The higher the risk sub-group algorithm, the longer the encryption time. The model assumes that users prefer the lower priority encryption algorithm to ensure efficiency. This paper proposes a privacy cost model for each of the seven risk subgroups. Among them, the higher the privacy cost, the higher the priority of the risk sub-group, the higher the price the user needs to pay to ensure the privacy of the data. Furthermore, by introducing the existing pricing model of economics and the human traffic model proposed by this paper and fluctuating with the market demand, this paper improves the price of unit products when the market demand is low. On the other hand, when the market demand increases, the profit of the enterprise will be guaranteed under the guidance of the government by reducing the price per unit of product. Then, this paper introduces the dynamic factors of consumers' mood and age to optimize. At the same time, seven algorithms are selected from symmetric and asymmetric encryption algorithms to define the enterprise

A linear bi-level multi-objective program for optimal allocation of water resources.

Directory of Open Access Journals (Sweden)

Ijaz Ahmad

Full Text Available This paper presents a simple bi-level multi-objective linear program (BLMOLP with a hierarchical structure consisting of reservoir managers and several water use sectors under a multi-objective framework for the optimal allocation of limited water resources. Being the upper level decision makers (i.e., leader in the hierarchy, the reservoir managers control the water allocation system and tend to create a balance among the competing water users thereby maximizing the total benefits to the society. On the other hand, the competing water use sectors, being the lower level decision makers (i.e., followers in the hierarchy, aim only to maximize individual sectoral benefits. This multi-objective bi-level optimization problem can be solved using the simultaneous compromise constraint (SICCON technique which creates a compromise between upper and lower level decision makers (DMs, and transforms the multi-objective function into a single decision-making problem. The bi-level model developed in this study has been applied to the Swat River basin in Pakistan for the optimal allocation of water resources among competing water demand sectors and different scenarios have been developed. The application of the model in this study shows that the SICCON is a simple, applicable and feasible approach to solve the BLMOLP problem. Finally, the comparisons of the model results show that the optimization model is practical and efficient when it is applied to different conditions with priorities assigned to various water users.

Evaluating Partnerships to Enhance Disaster Risk Management using Multi-Criteria Analysis: An Application at the Pan-European Level

Science.gov (United States)

Hochrainer-Stigler, Stefan; Lorant, Anna

2018-01-01

Disaster risk is increasingly recognized as a major development challenge. Recent calls emphasize the need to proactively engage in disaster risk reduction, as well as to establish new partnerships between private and public sector entities in order to decrease current and future risks. Very often such potential partnerships have to meet different objectives reflecting on the priorities of stakeholders involved. Consequently, potential partnerships need to be assessed on multiple criteria to determine weakest links and greatest threats in collaboration. This paper takes a supranational multi-sector partnership perspective, and considers possible ways to enhance disaster risk management in the European Union by better coordination between the European Union Solidarity Fund, risk reduction efforts, and insurance mechanisms. Based on flood risk estimates we employ a risk-layer approach to determine set of options for new partnerships and test them in a high-level workshop via a novel cardinal ranking based multi-criteria approach. Whilst transformative changes receive good overall scores, we also find that the incorporation of risk into budget planning is an essential condition for successful partnerships.

Optimal Multi-Level Lot Sizing for Requirements Planning Systems

OpenAIRE

Earle Steinberg; H. Albert Napier

1980-01-01

The wide spread use of advanced information systems such as Material Requirements Planning (MRP) has significantly altered the practice of dependent demand inventory management. Recent research has focused on development of multi-level lot sizing heuristics for such systems. In this paper, we develop an optimal procedure for the multi-period, multi-product, multi-level lot sizing problem by modeling the system as a constrained generalized network with fixed charge arcs and side constraints. T...

A MultiAir®/MultiFuel Approach to Enhancing Engine System Efficiency

Energy Technology Data Exchange (ETDEWEB)

Reese, Ronald [Chrysler Group LLC., Auburn Hills, MI (United States)

2015-05-20

FCA US LLC (formally known as Chrysler Group LLC, and hereinafter “Chrysler”) was awarded an American Recovery and Reinvestment Act (ARRA) funded project by the Department of Energy (DOE) titled “A MultiAir®/MultiFuel Approach to Enhancing Engine System Efficiency” (hereinafter “project”). This award was issued after Chrysler submitted a proposal for Funding Opportunity Announcement DE-FOA- 0000079, “Systems Level Technology Development, Integration, and Demonstration for Efficient Class 8 Trucks (SuperTruck) and Advanced Technology Powertrains for Light-Duty Vehicles (ATP-LD).” Chrysler started work on this project on June 01, 2010 and completed testing activities on August 30, 2014. Overall objectives of this project were; Demonstrate a 25% improvement in combined Federal Test Procedure (FTP) City and Highway fuel economy over a 2009 Chrysler minivan; Accelerate the development of highly efficient engine and powertrain systems for light-duty vehicles, while meeting future emissions standards; and Create and retain jobs in accordance with the American Recovery and Reinvestment Act of 2009

On multi-level thinking and scientific understanding

Science.gov (United States)

McIntyre, Michael Edgeworth

2017-10-01

Professor Duzheng YE's name has been familiar to me ever since my postdoctoral years at MIT with Professors Jule CHARNEY and Norman PHILLIPS, back in the late 1960s. I had the enormous pleasure of meeting Professor YE personally in 1992 in Beijing. His concern to promote the very best science and to use it well, and his thinking on multi-level orderly human activities, reminds me not only of the communication skills we need as scientists but also of the multi-level nature of science itself. Here I want to say something (a) about what science is; (b) about why multi-level thinking—and taking more than one viewpoint—is so important for scientific as well as for other forms of understanding; and (c) about what is meant, at a deep level, by "scientific understanding" and trying to communicate it, not only with lay persons but also across professional disciplines. I hope that Professor YE would approve.

A Socio-Ecological Approach for Identifying and Contextualising Spatial Ecosystem-Based Adaptation Priorities at the Sub-National Level.

Directory of Open Access Journals (Sweden)

Amanda Bourne

Full Text Available Climate change adds an additional layer of complexity to existing sustainable development and biodiversity conservation challenges. The impacts of global climate change are felt locally, and thus local governance structures will increasingly be responsible for preparedness and local responses. Ecosystem-based adaptation (EbA options are gaining prominence as relevant climate change solutions. Local government officials seldom have an appropriate understanding of the role of ecosystem functioning in sustainable development goals, or access to relevant climate information. Thus the use of ecosystems in helping people adapt to climate change is limited partially by the lack of information on where ecosystems have the highest potential to do so. To begin overcoming this barrier, Conservation South Africa in partnership with local government developed a socio-ecological approach for identifying spatial EbA priorities at the sub-national level. Using GIS-based multi-criteria analysis and vegetation distribution models, the authors have spatially integrated relevant ecological and social information at a scale appropriate to inform local level political, administrative, and operational decision makers. This is the first systematic approach of which we are aware that highlights spatial priority areas for EbA implementation. Nodes of socio-ecological vulnerability are identified, and the inclusion of areas that provide ecosystem services and ecological resilience to future climate change is innovative. The purpose of this paper is to present and demonstrate a methodology for combining complex information into user-friendly spatial products for local level decision making on EbA. The authors focus on illustrating the kinds of products that can be generated from combining information in the suggested ways, and do not discuss the nuance of climate models nor present specific technical details of the model outputs here. Two representative case studies from

A Socio-Ecological Approach for Identifying and Contextualising Spatial Ecosystem-Based Adaptation Priorities at the Sub-National Level

Science.gov (United States)

Bourne, Amanda; Holness, Stephen; Holden, Petra; Scorgie, Sarshen; Donatti, Camila I.; Midgley, Guy

2016-01-01

Climate change adds an additional layer of complexity to existing sustainable development and biodiversity conservation challenges. The impacts of global climate change are felt locally, and thus local governance structures will increasingly be responsible for preparedness and local responses. Ecosystem-based adaptation (EbA) options are gaining prominence as relevant climate change solutions. Local government officials seldom have an appropriate understanding of the role of ecosystem functioning in sustainable development goals, or access to relevant climate information. Thus the use of ecosystems in helping people adapt to climate change is limited partially by the lack of information on where ecosystems have the highest potential to do so. To begin overcoming this barrier, Conservation South Africa in partnership with local government developed a socio-ecological approach for identifying spatial EbA priorities at the sub-national level. Using GIS-based multi-criteria analysis and vegetation distribution models, the authors have spatially integrated relevant ecological and social information at a scale appropriate to inform local level political, administrative, and operational decision makers. This is the first systematic approach of which we are aware that highlights spatial priority areas for EbA implementation. Nodes of socio-ecological vulnerability are identified, and the inclusion of areas that provide ecosystem services and ecological resilience to future climate change is innovative. The purpose of this paper is to present and demonstrate a methodology for combining complex information into user-friendly spatial products for local level decision making on EbA. The authors focus on illustrating the kinds of products that can be generated from combining information in the suggested ways, and do not discuss the nuance of climate models nor present specific technical details of the model outputs here. Two representative case studies from rural South Africa

An audience research study to disseminate evidence about comprehensive state mental health parity legislation to US State policymakers: protocol.

Science.gov (United States)

Purtle, Jonathan; Lê-Scherban, Félice; Shattuck, Paul; Proctor, Enola K; Brownson, Ross C

2017-06-26

A large proportion of the US population has limited access to mental health treatments because insurance providers limit the utilization of mental health services in ways that are more restrictive than for physical health services. Comprehensive state mental health parity legislation (C-SMHPL) is an evidence-based policy intervention that enhances mental health insurance coverage and improves access to care. Implementation of C-SMHPL, however, is limited. State policymakers have the exclusive authority to implement C-SMHPL, but sparse guidance exists to inform the design of strategies to disseminate evidence about C-SMHPL, and more broadly, evidence-based treatments and mental illness, to this audience. The aims of this exploratory audience research study are to (1) characterize US State policymakers' knowledge and attitudes about C-SMHPL and identify individual- and state-level attributes associated with support for C-SMHPL; and (2) integrate quantitative and qualitative data to develop a conceptual framework to disseminate evidence about C-SMHPL, evidence-based treatments, and mental illness to US State policymakers. The study uses a multi-level (policymaker, state), mixed method (QUAN→qual) approach and is guided by Kingdon's Multiple Streams Framework, adapted to incorporate constructs from Aarons' Model of Evidence-Based Implementation in Public Sectors. A multi-modal survey (telephone, post-mail, e-mail) of 600 US State policymakers (500 legislative, 100 administrative) will be conducted and responses will be linked to state-level variables. The survey will span domains such as support for C-SMHPL, knowledge and attitudes about C-SMHPL and evidence-based treatments, mental illness stigma, and research dissemination preferences. State-level variables will measure factors associated with C-SMHPL implementation, such as economic climate and political environment. Multi-level regression will determine the relative strength of individual- and state-level

Effect of evidence-based approach on the customer orientation (Case study: Physicians Health Centers in Isfahan province in 2014)

Science.gov (United States)

Esfahani, NG; Maharati, Y

2015-01-01

Introduction: The purpose of this research was to examine the approach, based on evidence to customer-orientation attending physicians in the region, them being the subject collection. Research method: This is a definitive-analytic and cross-sectional configuration, which was completed in 2014. The statistical community in this research consists of 212 doctors in the healthcare hubs. The working physicians chose 200 patients by means of a simple accidental sampling. The analysis means was the researcher built survey whose efficacy and reliability were verified. In this research, the fundamental equation design and partial least square technique were applied to examine the presumptions and fitness pattern and the structural design was agreed as adequate. Findings: The outcomes showed four cases linked to the character, a behavior which was meant to treat; traditional origins of evidence were employed to retrieve data based on the reliable evidence and the shortage of limitations to the performance of client orientation strategy of evidence-based influences were meaningful. Two ranges of the doctor's information, the absence of restrictions, and the finding of the sign of dimensions about the client orientation approach were according to the evidence that had no meaningful influence. Conclusion: The utilization of evidence-based training not only increased awareness, character, and abilities of the doctors but also allowed them to answer to the requirements of clients in choosing excellent decisions and presenting a better quality of healthcare, by decreasing treatment prices for patients, bringing satisfaction of patients, and finally having a better effectiveness for patients and institutions. PMID:28316691

Exploring complex dynamics in multi agent-based intelligent systems: Theoretical and experimental approaches using the Multi Agent-based Behavioral Economic Landscape (MABEL) model

Science.gov (United States)

Alexandridis, Konstantinos T.

This dissertation adopts a holistic and detailed approach to modeling spatially explicit agent-based artificial intelligent systems, using the Multi Agent-based Behavioral Economic Landscape (MABEL) model. The research questions that addresses stem from the need to understand and analyze the real-world patterns and dynamics of land use change from a coupled human-environmental systems perspective. Describes the systemic, mathematical, statistical, socio-economic and spatial dynamics of the MABEL modeling framework, and provides a wide array of cross-disciplinary modeling applications within the research, decision-making and policy domains. Establishes the symbolic properties of the MABEL model as a Markov decision process, analyzes the decision-theoretic utility and optimization attributes of agents towards comprising statistically and spatially optimal policies and actions, and explores the probabilogic character of the agents' decision-making and inference mechanisms via the use of Bayesian belief and decision networks. Develops and describes a Monte Carlo methodology for experimental replications of agent's decisions regarding complex spatial parcel acquisition and learning. Recognizes the gap on spatially-explicit accuracy assessment techniques for complex spatial models, and proposes an ensemble of statistical tools designed to address this problem. Advanced information assessment techniques such as the Receiver-Operator Characteristic curve, the impurity entropy and Gini functions, and the Bayesian classification functions are proposed. The theoretical foundation for modular Bayesian inference in spatially-explicit multi-agent artificial intelligent systems, and the ensembles of cognitive and scenario assessment modular tools build for the MABEL model are provided. Emphasizes the modularity and robustness as valuable qualitative modeling attributes, and examines the role of robust intelligent modeling as a tool for improving policy-decisions related to land

Together We STRIDE: A quasi-experimental trial testing the effectiveness of a multi-level obesity intervention for Hispanic children in rural communities.

Science.gov (United States)

Ko, Linda K; Rillamas-Sun, Eileen; Bishop, Sonia; Cisneros, Oralia; Holte, Sarah; Thompson, Beti

2018-04-01

Hispanic children are disproportionally overweight and obese compared to their non-Hispanic white counterparts in the US. Community-wide, multi-level interventions have been successful to promote healthier nutrition, increased physical activity (PA), and weight loss. Using community-based participatory approach (CBPR) that engages community members in rural Hispanic communities is a promising way to promote behavior change, and ultimately weight loss among Hispanic children. Led by a community-academic partnership, the Together We STRIDE (Strategizing Together Relevant Interventions for Diet and Exercise) aims to test the effectiveness of a community-wide, multi-level intervention to promote healthier diets, increased PA, and weight loss among Hispanic children. The Together We STRIDE is a parallel quasi-experimental trial with a goal of recruiting 900 children aged 8-12 years nested within two communities (one intervention and one comparison). Children will be recruited from their respective elementary schools. Components of the 2-year multi-level intervention include comic books (individual-level), multi-generational nutrition and PA classes (family-level), teacher-led PA breaks and media literacy education (school-level), family nights, a farmer's market and a community PA event (known as ciclovia) at the community-level. Children from the comparison community will receive two newsletters. Height and weight measures will be collected from children in both communities at three time points (baseline, 6-months, and 18-months). The Together We STRIDE study aims to promote healthier diet and increased PA to produce healthy weight among Hispanic children. The use of CBPR approach and the engagement of the community will springboard strategies for intervention' sustainability. Clinical Trials Registration Number: NCT02982759 Retrospectively registered. Copyright © 2018 Elsevier Inc. All rights reserved.

Thermo-mechanical analysis for multi-level HLW repository concept

International Nuclear Information System (INIS)

Kwon, Sang Ki; Choi, Jong Won

2004-01-01

This work aims to investigate the influence of design parameters for the underground high-level nuclear waste repository with multi-level concept. B. Necessity o In order to construct an HLW repository in deep underground, it is required to select a site, which is far from major discontinuities. To dispose the whole spent fuels generated from the Korean nuclear power plants in a repository, the underground area of about 4km 2 is required. This would be a constraints for selecting an adequate repository site. It is recommended to dispose the two different spent fuels, PWR and CANDU, in different areas at the operation efficiency point of view. It is necessary to investigate the influence of parameters, which can affect the stability of multi-level repository. It is also needed to consider the influence of heat generated from the HLW and the high in situ stress in deep location. Therefore, thermo-mechanical coupling analysis should be carried out and the results should be compared with the results from single-level repository concept. Three-dimensional analysis is required to model the disposal tunnel and deposition hole. It is recommended to use the Korean geological condition and actually measured rock properties in Korea in order to achieve reliable modeling results. A FISH routine developed for effective modeling of Thermal-Mechanical coupling was implemented in the modeling using FLAC3D, which is a commercial three-dimensional FDM code. The thermal and mechanical properties of rock and rock mass achieved from Yusung drilling site, were used for the computer modeling. Different parameters such as level distance, waste type disposed on different levels, and time interval between the operation on different levels, were considered in the three-dimensional analysis. From the analysis, it was possible to derive adequate multi-level repository concept. Results and recommendations for application From the thermal-mechanical analysis for the multi-level repository

A frozen Gaussian approximation-based multi-level particle swarm optimization for seismic inversion

Energy Technology Data Exchange (ETDEWEB)

Li, Jinglai, E-mail: jinglaili@sjtu.edu.cn [Institute of Natural Sciences, Department of Mathematics, and MOE Key Laboratory of Scientific and Engineering Computing, Shanghai Jiao Tong University, Shanghai 200240 (China); Lin, Guang, E-mail: lin491@purdue.edu [Department of Mathematics, School of Mechanical Engineering, Purdue University, West Lafayette, IN 47907 (United States); Computational Sciences and Mathematics Division, Pacific Northwest National Laboratory, Richland, WA 99352 (United States); Yang, Xu, E-mail: xuyang@math.ucsb.edu [Department of Mathematics, University of California, Santa Barbara, CA 93106 (United States)

2015-09-01

In this paper, we propose a frozen Gaussian approximation (FGA)-based multi-level particle swarm optimization (MLPSO) method for seismic inversion of high-frequency wave data. The method addresses two challenges in it: First, the optimization problem is highly non-convex, which makes hard for gradient-based methods to reach global minima. This is tackled by MLPSO which can escape from undesired local minima. Second, the character of high-frequency of seismic waves requires a large number of grid points in direct computational methods, and thus renders an extremely high computational demand on the simulation of each sample in MLPSO. We overcome this difficulty by three steps: First, we use FGA to compute high-frequency wave propagation based on asymptotic analysis on phase plane; Then we design a constrained full waveform inversion problem to prevent the optimization search getting into regions of velocity where FGA is not accurate; Last, we solve the constrained optimization problem by MLPSO that employs FGA solvers with different fidelity. The performance of the proposed method is demonstrated by a two-dimensional full-waveform inversion example of the smoothed Marmousi model.

PELAKSANAAN JUAL BELI MELALUI SISTEM MULTI LEVEL MARKETING PERSPEKTIF HUKUM ISLAM

Directory of Open Access Journals (Sweden)

Ayu Dewi Utami

2016-03-01

Full Text Available Bisnis Multi Level Marketing (MLM cukup berperan dalam menggerakkan roda perekonomian masyarakat. Dalam sejumlah kasus, Multi Level Marketing (MLM kerap dijadikan kedok dari bisnis money game dan mendewakan passive income. Bertolak dari kasus kasus seperti itulah, Majelis Ulama Indonesia (MUI telah menggodok prinsip-prinsip bisnis ini secara syariah termasuk marketing plannya. Tujuannya untuk melindungi pengusaha dan mitra bisnisnya (masyarakat dari praktik bisnis yang haram atau syubhat. Dari prinsip-prinsip yang ditentukan oleh Majelis Ulama Indonesia (MUI, peneliti mengadakan penelitian ini dengan tujuan untuk mengetahui bagaimana mekanisme bisnis Multi Level Marketing (MLM, serta untuk mengetahui bagaimana bisnis Multi Level Marketing (MLM menurut hukum Islam. Metode yang digunakan dalam penelitian ini adalah menggunakan metode pendekatan yuridis normatif, spesifikasi penelitian yang digunakan adalah deskriptif analitis, sedangkan penentuan sampel menggunakan metode Non Random sampling. Alat penelitian meliputi studi kepustakaan dan wawancara. Metode analisis data dilakukan dengan analisis kualitatif. Ada dua aspek untuk menilai apakah bisnis Multi Level Marketing (MLM itu sesuai dengan syariah atau tidak, yaitu aspek produk atau jasa yang dijual dan sistem dari Multi Level Marketing (MLM itu sendiri. Bagaimana sistem pemberian bonus yang terdapat dalam perusahaan Multi Level Marketing (MLM apakah terbebas dari unsus garar maupun maisir. Penelitian ini bertujuan untuk mengkaji lebih dalam tentang Multi Level Marketing (MLM khususnya dalam Hukum Islam. Sisi negatif yang terdapat pada sistem Multi Level Marketing (MLM tidak mewakili keharaman secara keseluruhan terhadap bisnis yang berbasis Multi Level Marketing (MLM lainnya.

Applicability and feasibility of systematic review for performing evidence-based risk assessment in food and feed safety

DEFF Research Database (Denmark)

Aiassa, E.; Higgins, J.P.T.; Frampton, G. K.

2015-01-01

for answering questions in health care, and can be implemented to minimise biases in food and feed safety risk assessment. However, no methodological frameworks exist for refining risk assessment multi-parameter models into questions suitable for systematic review, and use of meta-analysis to estimate all......Food and feed safety risk assessment uses multi-parameter models to evaluate the likelihood of adverse events associated with exposure to hazards in human health, plant health, animal health, animal welfare and the environment. Systematic review and meta-analysis are established methods...... parameters in the risk model. This approach to planning and prioritising systematic review seems to have useful implications for producing evidence-based food and feed safety risk assessment....

Development of Evidence-Based Health Policy Documents in Developing Countries: A Case of Iran

Science.gov (United States)

Imani-Nasab, Mohammad Hasan; Seyedin, Hesam; Majdzadeh, Reza; Yazdizadeh, Bahareh; Salehi, Masoud

2014-01-01

Background: Evidence-based policy documents that are well developed by senior civil servants and are timely available can reduce the barriers to evidence utilization by health policy makers. This study examined the barriers and facilitators in developing evidence-based health policy documents from the perspective of their producers in a developing country. Methods: In a qualitative study with a framework analysis approach, we conducted semi-structured interviews using purposive and snowball sampling. A qualitative analysis software (MAXQDA-10) was used to apply the codes and manage the data. This study was theory-based and the results were compared to exploratory studies about the factors influencing evidence-based health policymaking. Results: 18 codes and three main themes of behavioral, normative, and control beliefs were identified. Factors that influence the development of evidence-based policy documents were identified by the participants: behavioral beliefs included quality of policy documents, use of resources, knowledge and innovation, being time-consuming and contextualization; normative beliefs included policy authorities, policymakers, policy administrators, and co-workers; and control beliefs included recruitment policy, performance management, empowerment, management stability, physical environment, access to evidence, policy making process, and effect of other factors. Conclusion: Most of the cited barriers to the development of evidence-based policy were related to control beliefs, i.e. barriers at the organizational and health system levels. This study identified the factors that influence the development of evidence-based policy documents based on the components of the theory of planned behavior. But in exploratory studies on evidence utilization by health policymakers, the identified factors were only related to control behaviors. This suggests that the theoretical approach may be preferable to the exploratory approach in identifying the barriers

Development of evidence-based health policy documents in developing countries: a case of Iran.

Science.gov (United States)

Imani-Nasab, Mohammad Hasan; Seyedin, Hesam; Majdzadeh, Reza; Yazdizadeh, Bahareh; Salehi, Masoud

2014-02-07

Evidence-based policy documents that are well developed by senior civil servants and are timely available can reduce the barriers to evidence utilization by health policy makers. This study examined the barriers and facilitators in developing evidence-based health policy documents from the perspective of their producers in a developing country. In a qualitative study with a framework analysis approach, we conducted semi-structured interviews using purposive and snowball sampling. A qualitative analysis software (MAXQDA-10) was used to apply the codes and manage the data. This study was theory-based and the results were compared to exploratory studies about the factors influencing evidence-based health policy-making. 18 codes and three main themes of behavioral, normative, and control beliefs were identified. Factors that influence the development of evidence-based policy documents were identified by the participants: behavioral beliefs included quality of policy documents, use of resources, knowledge and innovation, being time-consuming and contextualization; normative beliefs included policy authorities, policymakers, policy administrators, and co-workers; and control beliefs included recruitment policy, performance management, empowerment, management stability, physical environment, access to evidence, policy making process, and effect of other factors. Most of the cited barriers to the development of evidence-based policy were related to control beliefs, i.e. barriers at the organizational and health system levels. This study identified the factors that influence the development of evidence-based policy documents based on the components of the theory of planned behavior. But in exploratory studies on evidence utilization by health policymakers, the identified factors were only related to control behaviors. This suggests that the theoretical approach may be preferable to the exploratory approach in identifying the barriers and facilitators of a behavior.

A New Multi-Agent Approach to Adaptive E-Education

Science.gov (United States)

Chen, Jing; Cheng, Peng

Improving customer satisfaction degree is important in e-Education. This paper describes a new approach to adaptive e-Education taking into account the full spectrum of Web service techniques and activities. It presents a multi-agents architecture based on artificial psychology techniques, which makes the e-Education process both adaptable and dynamic, and hence up-to-date. Knowledge base techniques are used to support the e-Education process, and artificial psychology techniques to deal with user psychology, which makes the e-Education system more effective and satisfying.

Evidence-based tick acaricide resistance intervention strategy in Uganda: Concept and feedback of farmers and stakeholders.

Science.gov (United States)

Vudriko, Patrick; Okwee-Acai, James; Byaruhanga, Joseph; Tayebwa, Dickson Stuart; Omara, Robert; Muhindo, Jeanne Bukeka; Lagu, Charles; Umemiya-Shirafuji, Rika; Xuan, Xuenan; Suzuki, Hiroshi

2018-02-01

The emergence of multi-acaricide resistant ticks has led to unprecedented level of acaricide failure in central and western Uganda. In the absence of a national acaricide resistance management strategy, the country's dairy sector is threatened by upsurge of ticks and tick-borne diseases. In this study, we developed a short-to-medium-term intervention approach called Evidence-Based Acaricide Tick Control (EBATIC): Identify, Test, Intervene and Eradicate (IT-IE). Furthermore, the perception of 199 farmers and extension workers, 12 key informants in four districts and 47 stakeholders in the animal industry in Uganda were assessed using semi-structured questionnaires. We report that the establishment of a specialized laboratory is pivotal in identifying and testing (IT) acaricide resistant ticks for prompt intervention and eradication (IE). The laboratory test results and the farm tick control gaps identified are very important in guiding acaricide resistance management strategies such as evidence-based acaricide rotation, development and dissemination of extension materials, training of farmers and extension workers, and stakeholders' engagement towards finding sustainable solutions. All the 47 stakeholders and 91.0% (181/199) of the farmers and extension workers reported that the EBATIC approach will help in solving the tick acaricide resistance crisis in Uganda. Similarly, all the 12 key informants and 92.5% (184/199) of the farmers and extension workers suggested that the EBATIC approach should be sustained and rolled out to other districts. The EBATIC stakeholders' dialogue generated both short-to-medium and long-term strategies for sustainable management of tick acaricide resistance in the country. Overall, the positive feedback from farmers, district veterinarians and stakeholders in the animal industry suggest that the EBATIC approach is a useful proof-of-concept on scalable intervention pathway against tick acaricide resistance in Uganda with possibility of

On the multi-level solution algorithm for Markov chains

Energy Technology Data Exchange (ETDEWEB)

Horton, G. [Univ. of Erlangen, Nuernberg (Germany)

1996-12-31

We discuss the recently introduced multi-level algorithm for the steady-state solution of Markov chains. The method is based on the aggregation principle, which is well established in the literature. Recursive application of the aggregation yields a multi-level method which has been shown experimentally to give results significantly faster than the methods currently in use. The algorithm can be reformulated as an algebraic multigrid scheme of Galerkin-full approximation type. The uniqueness of the scheme stems from its solution-dependent prolongation operator which permits significant computational savings in the evaluation of certain terms. This paper describes the modeling of computer systems to derive information on performance, measured typically as job throughput or component utilization, and availability, defined as the proportion of time a system is able to perform a certain function in the presence of component failures and possibly also repairs.

Scheduling and resource allocation of non-conventional power systems via multi level approach

Energy Technology Data Exchange (ETDEWEB)

Fahmy, F H [National Research Center, Cairo (Egypt). Electronics Research Inst.

1996-12-31

The objective of article is to propose a design technique wit a new economic dispatch analysis. This analysis are used the combined hierarchical approach and N.L. programming. There are three different energy sources which can be used to feed a remote area in Egypt desert: Wind source, PV and Diesel engine. The two subsources are considered here as: Batteries and water Basin: The load demand is to feed the suitable electric energy need for irrigation and domestic services. The optimization problem is composed of set of goals with set of constraints i.e. a multi objective functions system had been studied as a large scale system. Using the developed technique, the complicated stochastic system can be transformed into a simple deterministic scale system for simplicity. The use of developed technique constitute a more forceful approach to find the minimum cost operating point with maximizing the total electric energy generated form the three energy sources. The method also gives greater flexibility in the selection of constraints, permitting the use of equality constraints as well as inequality one. (author)

Scheduling and resource allocation of non-conventional power systems via multi level approach

Energy Technology Data Exchange (ETDEWEB)

Fahmy, F.H. [National Research Center, Cairo (Egypt). Electronics Research Inst.

1995-12-31

The objective of article is to propose a design technique wit a new economic dispatch analysis. This analysis are used the combined hierarchical approach and N.L. programming. There are three different energy sources which can be used to feed a remote area in Egypt desert: Wind source, PV and Diesel engine. The two subsources are considered here as: Batteries and water Basin: The load demand is to feed the suitable electric energy need for irrigation and domestic services. The optimization problem is composed of set of goals with set of constraints i.e. a multi objective functions system had been studied as a large scale system. Using the developed technique, the complicated stochastic system can be transformed into a simple deterministic scale system for simplicity. The use of developed technique constitute a more forceful approach to find the minimum cost operating point with maximizing the total electric energy generated form the three energy sources. The method also gives greater flexibility in the selection of constraints, permitting the use of equality constraints as well as inequality one. (author)

Scheduling and resource allocation of non-conventional power systems via multi level approach

International Nuclear Information System (INIS)

Fahmy, F.H.

1995-01-01

The objective of article is to propose a design technique wit a new economic dispatch analysis. This analysis are used the combined hierarchical approach and N.L. programming. There are three different energy sources which can be used to feed a remote area in Egypt desert: Wind source, PV and Diesel engine. The two subsources are considered here as: Batteries and water Basin: The load demand is to feed the suitable electric energy need for irrigation and domestic services. The optimization problem is composed of set of goals with set of constraints i.e. a multi objective functions system had been studied as a large scale system. Using the developed technique, the complicated stochastic system can be transformed into a simple deterministic scale system for simplicity. The use of developed technique constitute a more forceful approach to find the minimum cost operating point with maximizing the total electric energy generated form the three energy sources. The method also gives greater flexibility in the selection of constraints, permitting the use of equality constraints as well as inequality one. (author)

Sustainability of evidence-based healthcare: research agenda, methodological advances, and infrastructure support.

Science.gov (United States)

Proctor, Enola; Luke, Douglas; Calhoun, Annaliese; McMillen, Curtis; Brownson, Ross; McCrary, Stacey; Padek, Margaret

2015-06-11

Little is known about how well or under what conditions health innovations are sustained and their gains maintained once they are put into practice. Implementation science typically focuses on uptake by early adopters of one healthcare innovation at a time. The later-stage challenges of scaling up and sustaining evidence-supported interventions receive too little attention. This project identifies the challenges associated with sustainability research and generates recommendations for accelerating and strengthening this work. A multi-method, multi-stage approach, was used: (1) identifying and recruiting experts in sustainability as participants, (2) conducting research on sustainability using concept mapping, (3) action planning during an intensive working conference of sustainability experts to expand the concept mapping quantitative results, and (4) consolidating results into a set of recommendations for research, methodological advances, and infrastructure building to advance understanding of sustainability. Participants comprised researchers, funders, and leaders in health, mental health, and public health with shared interest in the sustainability of evidence-based health care. Prompted to identify important issues for sustainability research, participants generated 91 distinct statements, for which a concept mapping process produced 11 conceptually distinct clusters. During the conference, participants built upon the concept mapping clusters to generate recommendations for sustainability research. The recommendations fell into three domains: (1) pursue high priority research questions as a unified agenda on sustainability; (2) advance methods for sustainability research; (3) advance infrastructure to support sustainability research. Implementation science needs to pursue later-stage translation research questions required for population impact. Priorities include conceptual consistency and operational clarity for measuring sustainability, developing evidence

Peripheral neuropathy in HIV: an analysis of evidence-based approaches.

Science.gov (United States)

Nicholas, Patrice K; Corless, Inge B; Evans, Linda A

2014-01-01

Peripheral neuropathy is a common and vexing symptom for people living with HIV infection (PLWH). Neuropathy occurs in several different syndromes and is identified in the literature as distal sensory polyneuropathy or distal sensory peripheral neuropathy. More recently, the HIV literature has focused on the syndrome as painful HIV-associated sensory neuropathy, addressing the symptom rather than the underlying pathophysiology. Assessment of neuropathy in PLWH is critical and must be incorporated into nursing practice for each visit. Neuropathy has been attributed to the direct effects of HIV, exposure to antiretroviral medications (particularly the nucleoside reverse transcriptase inhibitors), advanced immune suppression, and comorbid tuberculosis infection and exposure to antituberculosis medications. Evidence supports the importance of addressing neuropathy in PLWH with pharmacologic treatment regimens and complementary/alternative approaches. This paper examines the pathophysiology, evidence, and approaches to managing peripheral neuropathy. A case study has been included to illustrate a patient's experience with neuropathy symptoms. Copyright © 2014 Association of Nurses in AIDS Care. Published by Elsevier Inc. All rights reserved.

Using linguistic descriptions with multi-criteria decision aid approaches in urban energy systems

OpenAIRE

Afsordegan, Arayeh; Sánchez Soler, Monica; Agell Jané, Núria; Gamboa Jimenez, Gonzalo; Cremades Oliver, Lázaro Vicente

2015-01-01

Multi-Criteria Decision Aid (MCDA) methods include various collections of mathematical techniques related to decision support systems in non-deterministic environments to support such applications as facility management, disaster management and urban planning. This paper applies MCDA approaches based on qualitative reasoning techniques with linguistic labels assessment. The aim of this method is ranking multi-attribute alternatives in group decision-making with qualitative labels. Finally ...

The Integrated Multi-Level Bilingual Teaching of "Social Research Methods"

Science.gov (United States)

Zhu, Yanhan; Ye, Jian

2012-01-01

"Social Research Methods," as a methodology course, combines theories and practices closely. Based on the synergy theory, this paper tries to establish an integrated multi-level bilingual teaching mode. Starting from the transformation of teaching concepts, we should integrate interactions, experiences, and researches together and focus…

An Agent Based Modelling Approach for Multi-Stakeholder Analysis of City Logistics Solutions

NARCIS (Netherlands)

Anand, N.

2015-01-01

This thesis presents a comprehensive framework for multi-stakeholder analysis of city logistics solutions using agent based modeling. The framework describes different stages for the systematic development of an agent based model for the city logistics domain. The framework includes a

Educating change agents: a qualitative descriptive study of graduates of a Master's program in evidence-based practice.

Science.gov (United States)

Hole, Grete Oline; Brenna, Sissel Johansson; Graverholt, Birgitte; Ciliska, Donna; Nortvedt, Monica Wammen

2016-02-25

Health care professionals are expected to build decisions upon evidence. This implies decisions based on the best available, current, valid and relevant evidence, informed by clinical expertise and patient values. A multi-professional master's program in evidence-based practice was developed and offered. The aims of this study were to explore how students in this program viewed their ability to apply evidence-based practice and their perceptions of what constitute necessary conditions to implement evidence-based practice in health care organizations, one year after graduation. A qualitative descriptive design was chosen to examine the graduates' experiences. All students in the first two cohorts of the program were invited to participate. Six focus-group interviews, with a total of 21 participants, and a telephone interview of one participant were conducted. The data was analyzed thematically, using the themes from the interview guide as the starting point. The graduates reported that an overall necessary condition for evidence-based practice to occur is the existence of a "readiness for change" both at an individual level and at the organizational level. They described that they gained personal knowledge and skills to be "change-agents" with "self-efficacy, "analytic competence" and "tools" to implement evidence based practice in clinical care. An organizational culture of a "learning organization" was also required, where leaders have an "awareness of evidence- based practice", and see the need for creating "evidence-based networks". One year after graduation the participants saw themselves as "change agents" prepared to improve clinical care within a learning organization. The results of this study provides useful information for facilitating the implementation of EBP both from educational and health care organizational perspectives.

A social marketing approach to implementing evidence-based practice in VHA QUERI: the TIDES depression collaborative care model.

Science.gov (United States)

Luck, Jeff; Hagigi, Fred; Parker, Louise E; Yano, Elizabeth M; Rubenstein, Lisa V; Kirchner, JoAnn E

2009-09-28

Collaborative care models for depression in primary care are effective and cost-effective, but difficult to spread to new sites. Translating Initiatives for Depression into Effective Solutions (TIDES) is an initiative to promote evidence-based collaborative care in the U.S. Veterans Health Administration (VHA). Social marketing applies marketing techniques to promote positive behavior change. Described in this paper, TIDES used a social marketing approach to foster national spread of collaborative care models. The approach relied on a sequential model of behavior change and explicit attention to audience segmentation. Segments included VHA national leadership, Veterans Integrated Service Network (VISN) regional leadership, facility managers, frontline providers, and veterans. TIDES communications, materials and messages targeted each segment, guided by an overall marketing plan. Depression collaborative care based on the TIDES model was adopted by VHA as part of the new Primary Care Mental Health Initiative and associated policies. It is currently in use in more than 50 primary care practices across the United States, and continues to spread, suggesting success for its social marketing-based dissemination strategy. Development, execution and evaluation of the TIDES marketing effort shows that social marketing is a promising approach for promoting implementation of evidence-based interventions in integrated healthcare systems.

Simulation and evaluation of urban rail transit network based on multi-agent approach

Directory of Open Access Journals (Sweden)

Xiangming Yao

2013-03-01

Full Text Available Purpose: Urban rail transit is a complex and dynamic system, which is difficult to be described in a global mathematical model for its scale and interaction. In order to analyze the spatial and temporal characteristics of passenger flow distribution and evaluate the effectiveness of transportation strategies, a new and comprehensive method depicted such dynamic system should be given. This study therefore aims at using simulation approach to solve this problem for subway network. Design/methodology/approach: In this thesis a simulation model based on multi-agent approach has been proposed, which is a well suited method to design complex systems. The model includes the specificities of passengers’ travelling behaviors and takes into account of interactions between travelers and trains. Findings: Research limitations/implications: We developed an urban rail transit simulation tool for verification of the validity and accuracy of this model, using real passenger flow data of Beijing subway network to take a case study, results show that our simulation tool can be used to analyze the characteristic of passenger flow distribution and evaluate operation strategies well. Practical implications: The main implications of this work are to provide decision support for traffic management, making train operation plan and dispatching measures in emergency. Originality/value: A new and comprehensive method to analyze and evaluate subway network is presented, accuracy and computational efficiency of the model has been confirmed and meet with the actual needs for large-scale network.

A multi-objective approach to solid waste management

International Nuclear Information System (INIS)

Galante, Giacomo; Aiello, Giuseppe; Enea, Mario; Panascia, Enrico

2010-01-01

The issue addressed in this paper consists in the localization and dimensioning of transfer stations, which constitute a necessary intermediate level in the logistic chain of the solid waste stream, from municipalities to the incinerator. Contextually, the determination of the number and type of vehicles involved is carried out in an integrated optimization approach. The model considers both initial investment and operative costs related to transportation and transfer stations. Two conflicting objectives are evaluated, the minimization of total cost and the minimization of environmental impact, measured by pollution. The design of the integrated waste management system is hence approached in a multi-objective optimization framework. To determine the best means of compromise, goal programming, weighted sum and fuzzy multi-objective techniques have been employed. The proposed analysis highlights how different attitudes of the decision maker towards the logic and structure of the problem result in the employment of different methodologies and the obtaining of different results. The novel aspect of the paper lies in the proposal of an effective decision support system for operative waste management, rather than a further contribution to the transportation problem. The model was applied to the waste management of optimal territorial ambit (OTA) of Palermo (Italy).

A multi-objective approach to solid waste management.

Science.gov (United States)

Galante, Giacomo; Aiello, Giuseppe; Enea, Mario; Panascia, Enrico

2010-01-01

The issue addressed in this paper consists in the localization and dimensioning of transfer stations, which constitute a necessary intermediate level in the logistic chain of the solid waste stream, from municipalities to the incinerator. Contextually, the determination of the number and type of vehicles involved is carried out in an integrated optimization approach. The model considers both initial investment and operative costs related to transportation and transfer stations. Two conflicting objectives are evaluated, the minimization of total cost and the minimization of environmental impact, measured by pollution. The design of the integrated waste management system is hence approached in a multi-objective optimization framework. To determine the best means of compromise, goal programming, weighted sum and fuzzy multi-objective techniques have been employed. The proposed analysis highlights how different attitudes of the decision maker towards the logic and structure of the problem result in the employment of different methodologies and the obtaining of different results. The novel aspect of the paper lies in the proposal of an effective decision support system for operative waste management, rather than a further contribution to the transportation problem. The model was applied to the waste management of optimal territorial ambit (OTA) of Palermo (Italy). 2010 Elsevier Ltd. All rights reserved.

River modeling and multi-level fish health assessment to evaluate impacts from oil sands water releases (Part 2)

International Nuclear Information System (INIS)

Shaw, R.; Swanson, S.M.; Lagimodiere, M.; Gulley, J.

1995-01-01

A multi-level, multi-scale approach was used to assess potential impacts to fish health from oil sands water releases. The method used to arrive at predicted impacts involved assembling experimental data on the effects of chronic exposure to oil sands wastewaters on biochemical, physiological and whole-organism endpoint. This information was used to determine no effect levels (NOELs) and lowest effect levels (LOELs) for the suite of fish health parameters used in laboratory experiments (primarily biochemical and physiological measurement endpoints). LOELs and NOELs were compared to modeled concentrations of wastewater in the Athabasca River for five time snapshots. For each time period, concentrations were predicted based on mean annual flows and 7Q10 flows (low flows). This comparison was used to predict impacts on biochemical/physiological endpoints. Impacts on at the whole-organism and population-level were determined by comparing what the laboratory data would predict with what was observed in the field. This process was used to draw a conclusion regarding the health and sustainability of fish populations

American Pancreatic Association Practice Guidelines in Chronic Pancreatitis: Evidence-Based Report on Diagnostic Guidelines

Science.gov (United States)

Conwell, Darwin L.; Lee, Linda S.; Yadav, Dhiraj; Longnecker, Daniel S.; Miller, Frank H.; Mortele, Koenraad J.; Levy, Michael J.; Kwon, Richard; Lieb, John G.; Stevens, Tyler; Toskes, Philip P.; Gardner, Timothy B.; Gelrud, Andres; Wu, Bechien U.; Forsmark, Christopher E.; Vege, Santhi S.

2016-01-01

The diagnosis of chronic pancreatitis remains challenging in early stages of the disease. This report defines the diagnostic criteria useful in the assessment of patients with suspected and established chronic pancreatitis. All current diagnostic procedures are reviewed and evidence based statements are provided about their utility and limitations. Diagnostic criteria for chronic pancreatitis are classified as definitive, probable or insufficient evidence. A diagnostic (STEP-wise; S-survey, T-tomography, E-endoscopy and P-pancreas function testing) algorithm is proposed that proceeds from a non-invasive to a more invasive approach. This algorithm maximizes specificity (low false positive rate) in subjects with chronic abdominal pain and equivocal imaging changes. Futhermore, a nomenclature is suggested to further characterize patients with established chronic pancreatitis based on TIGAR-O (T-toxic, I-idiopathic, G-genetic, A- autoimmune, R-recurrent and O-obstructive) etiology, gland morphology (Cambridge criteria) and physiologic state (exocrine, endocrine function) for uniformity across future multi-center research collaborations. This guideline will serve as a baseline manuscript that will be modified as new evidence becomes available and our knowledge of chronic pancreatitis improves. PMID:25333398

A diagnostic imaging approach for online characterization of multi-impact in aircraft composite structures based on a scanning spatial-wavenumber filter of guided wave

Science.gov (United States)

Ren, Yuanqiang; Qiu, Lei; Yuan, Shenfang; Su, Zhongqing

2017-06-01

Monitoring of impact and multi-impact in particular in aircraft composite structures has been an intensive research topic in the field of guided-wave-based structural health monitoring (SHM). Compared with the majority of existing methods such as those using signal features in the time-, frequency- or joint time-frequency domain, the approach based on spatial-wavenumber filter of guided wave shows superb advantage in effectively distinguishing particular wave modes and identifying their propagation direction relative to the sensor array. However, there exist two major issues when conducting online characterization of multi-impact event. Firstly, the spatial-wavenumber filter should be realized in the situation that the wavenumber of high spatial resolution of the complicated multi-impact signal cannot be measured or modeled. Secondly, it's difficult to identify the multiple impacts and realize multi-impact localization due to the overlapping of wavenumbers. To address these issues, a scanning spatial-wavenumber filter based diagnostic imaging method for online characterization of multi-impact event is proposed to conduct multi-impact imaging and localization in this paper. The principle of the scanning filter for multi-impact is developed first to conduct spatial-wavenumber filtering and to achieve wavenumber-time imaging of the multiple impacts. Then, a feature identification method of multi-impact based on eigenvalue decomposition and wavenumber searching is presented to estimate the number of impacts and calculate the wavenumber of the multi-impact signal, and an image mapping method is proposed as well to convert the wavenumber-time image to an angle-distance image to distinguish and locate the multiple impacts. A series of multi-impact events are applied to a carbon fiber laminate plate to validate the proposed methods. The validation results show that the localization of the multiple impacts are well achieved.

Radiative characterization of random fibrous media with long cylindrical fibers: Comparison of single- and multi-RTE approaches

Science.gov (United States)

Randrianalisoa, Jaona; Haussener, Sophia; Baillis, Dominique; Lipiński, Wojciech

2017-11-01

Radiative heat transfer is analyzed in participating media consisting of long cylindrical fibers with a diameter in the limit of geometrical optics. The absorption and scattering coefficients and the scattering phase function of the medium are determined based on the discrete-level medium geometry and optical properties of individual fibers. The fibers are assumed to be randomly oriented and positioned inside the medium. Two approaches are employed: a volume-averaged two-intensity approach referred to as multi-RTE approach and a homogenized single-intensity approach referred to as the single-RTE approach. Both approaches require effective properties, determined using direct Monte Carlo ray tracing techniques. The macroscopic radiative transfer equations (for single intensity or two volume-averaged intensities) with the corresponding effective properties are solved using Monte Carlo techniques and allow for the determination of the radiative flux distribution as well as overall transmittance and reflectance of the medium. The results are compared against predictions by the direct Monte Carlo simulation on the exact morphology. The effects of fiber volume fraction and optical properties on the effective radiative properties and the overall slab radiative characteristics are investigated. The single-RTE approach gives accurate predictions for high porosity fibrous media (porosity about 95%). The multi-RTE approach is recommended for isotropic fibrous media with porosity in the range of 79-95%.

Multi-level learning: improving the prediction of protein, domain and residue interactions by allowing information flow between levels

Directory of Open Access Journals (Sweden)

McDermott Drew

2009-08-01

Full Text Available Abstract Background Proteins interact through specific binding interfaces that contain many residues in domains. Protein interactions thus occur on three different levels of a concept hierarchy: whole-proteins, domains, and residues. Each level offers a distinct and complementary set of features for computationally predicting interactions, including functional genomic features of whole proteins, evolutionary features of domain families and physical-chemical features of individual residues. The predictions at each level could benefit from using the features at all three levels. However, it is not trivial as the features are provided at different granularity. Results To link up the predictions at the three levels, we propose a multi-level machine-learning framework that allows for explicit information flow between the levels. We demonstrate, using representative yeast interaction networks, that our algorithm is able to utilize complementary feature sets to make more accurate predictions at the three levels than when the three problems are approached independently. To facilitate application of our multi-level learning framework, we discuss three key aspects of multi-level learning and the corresponding design choices that we have made in the implementation of a concrete learning algorithm. 1 Architecture of information flow: we show the greater flexibility of bidirectional flow over independent levels and unidirectional flow; 2 Coupling mechanism of the different levels: We show how this can be accomplished via augmenting the training sets at each level, and discuss the prevention of error propagation between different levels by means of soft coupling; 3 Sparseness of data: We show that the multi-level framework compounds data sparsity issues, and discuss how this can be dealt with by building local models in information-rich parts of the data. Our proof-of-concept learning algorithm demonstrates the advantage of combining levels, and opens up

Multi-Level Sensor Fusion Algorithm Approach for BMD Interceptor Applications

National Research Council Canada - National Science Library

Allen, Doug

1998-01-01

... through fabrication and testing of advanced sensor hardware concepts and advanced sensor fusion algorithms. Advanced sensor concepts include onboard LADAR in conjunction with a multi-color passive IR sensor...

Building a Unit-Level Mentored Program to Sustain a Culture of Inquiry for Evidence-Based Practice.

Science.gov (United States)

Breckenridge-Sproat, Sara T; Throop, Meryia D; Raju, Dheeraj; Murphy, Deborah A; Loan, Lori A; Patrician, Patricia A

2015-01-01

This study tested the effectiveness of a dynamic educational and mentoring program, facilitated by unit-level mentors, to introduce, promote, and sustain an evidence-based practice (EBP) culture among nurses in a military healthcare setting. The need to identify gaps in practice, apply principles of EBP, and advance scientific applications in the pursuit of quality nursing care is as important to military healthcare as it is in the civilian sector. The Advancing Research through Close Collaboration Model guided the intervention and study. Three instruments were used: the Organizational Readiness for System-wide Integration of Evidence-Based Practice, EBP Beliefs, and EBP Implementation scales. The study took place in 3 military hospitals simultaneously undergoing facility and staff integration. Data were collected from staff nurses in the inpatient nursing units before and after a facilitated education and mentoring intervention. Three hundred sixty nurses (38%) completed baseline, and 325 (31%) completed follow-up surveys. Scores improved on all 3 measures following implementation of the program; however, the differences were statistically significant only for the Organizational Readiness for System-wide Integration of Evidence-Based Practice scale (70.96 vs 77.63, t = -3.95, P culture may diffuse among individuals in an organization, even while experiencing significant change. It also demonstrates that a unit-level mentored EBP program is sustainable despite changes in organizational structure and workforce composition.

Field Trials of the Multi-Source Approach for Resistivity and Induced Polarization Data Acquisition

Science.gov (United States)

LaBrecque, D. J.; Morelli, G.; Fischanger, F.; Lamoureux, P.; Brigham, R.

2013-12-01

Implementing systems of distributed receivers and transmitters for resistivity and induced polarization data is an almost inevitable result of the availability of wireless data communication modules and GPS modules offering precise timing and instrument locations. Such systems have a number of advantages; for example, they can be deployed around obstacles such as rivers, canyons, or mountains which would be difficult with traditional 'hard-wired' systems. However, deploying a system of identical, small, battery powered, transceivers, each capable of injecting a known current and measuring the induced potential has an additional and less obvious advantage in that multiple units can inject current simultaneously. The original purpose for using multiple simultaneous current sources (multi-source) was to increase signal levels. In traditional systems, to double the received signal you inject twice the current which requires you to apply twice the voltage and thus four times the power. Alternatively, one approach to increasing signal levels for large-scale surveys collected using small, battery powered transceivers is it to allow multiple units to transmit in parallel. In theory, using four 400 watt transmitters on separate, parallel dipoles yields roughly the same signal as a single 6400 watt transmitter. Furthermore, implementing the multi-source approach creates the opportunity to apply more complex current flow patterns than simple, parallel dipoles. For a perfect, noise-free system, multi-sources adds no new information to a data set that contains a comprehensive set of data collected using single sources. However, for realistic, noisy systems, it appears that multi-source data can substantially impact survey results. In preliminary model studies, the multi-source data produced such startling improvements in subsurface images that even the authors questioned their veracity. Between December of 2012 and July of 2013, we completed multi-source surveys at five sites

Multi-dimensional information diffusion and balancing market supply: an agent-based approach

NARCIS (Netherlands)

Osinga, S.A.; Kramer, M.R.; Hofstede, G.J.; Beulens, A.J.M.

2013-01-01

This agent-based information management model is designed to explore how multi-dimensional information, spreading through a population of agents (for example farmers) affects market supply. Farmers make quality decisions that must be aligned with available markets. Markets distinguish themselves by

An Emerging Theory for Evidence Based Information Literacy Instruction in School Libraries, Part 1: Building a Foundation

Directory of Open Access Journals (Sweden)

Carol A. Gordon

2009-06-01

Full Text Available Objective – Part I of this paper aims to create a framework for an emerging theory of evidence based information literacy instruction. In order to ground this framework in existing theory, a holistic perspective views inquiry as a learning process that synthesizes information searching and knowledge building. An interdisciplinary approach is taken to relate user-centric information behavior theory and constructivist learning theory that supports this synthesis. The substantive theories that emerge serve as a springboard for emerging theory. A second objective of this paper is to define evidence based information literacy instruction by assessing the suitability of performance based assessment and action research as tools of evidence based practice.Methods – An historical review of research grounded in user-centered information behavior theory and constructivist learning theory establishes a body of existing substantive theory that supports emerging theory for evidence based information literacy instruction within an information-to-knowledge approach. A focused review of the literature presents supporting research for an evidence based pedagogy that is performance assessment based, i.e., information users are immersed in real-world tasks that include formative assessments. An analysis of the meaning of action research in terms of its purpose and methodology establishes its suitability for structuring an evidence based pedagogy. Supporting research tests a training model for school librarians and educators which integrates performance based assessment, as well as action research. Results – Findings of an historical analysis of information behavior theory and constructivist teaching practices, and a literature review that explores teaching models for evidence based information literacy instruction, point to two elements of evidence based information literacy instruction: the micro level of information searching behavior and the macro level of

Improving PERSIANN-CCS rain estimation using probabilistic approach and multi-sensors information

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Karbalaee, N.; Hsu, K. L.; Sorooshian, S.; Kirstetter, P.; Hong, Y.

2016-12-01

This presentation discusses the recent implemented approaches to improve the rainfall estimation from Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network-Cloud Classification System (PERSIANN-CCS). PERSIANN-CCS is an infrared (IR) based algorithm being integrated in the IMERG (Integrated Multi-Satellite Retrievals for the Global Precipitation Mission GPM) to create a precipitation product in 0.1x0.1degree resolution over the chosen domain 50N to 50S every 30 minutes. Although PERSIANN-CCS has a high spatial and temporal resolution, it overestimates or underestimates due to some limitations.PERSIANN-CCS can estimate rainfall based on the extracted information from IR channels at three different temperature threshold levels (220, 235, and 253k). This algorithm relies only on infrared data to estimate rainfall indirectly from this channel which cause missing the rainfall from warm clouds and false estimation for no precipitating cold clouds. In this research the effectiveness of using other channels of GOES satellites such as visible and water vapors has been investigated. By using multi-sensors the precipitation can be estimated based on the extracted information from multiple channels. Also, instead of using the exponential function for estimating rainfall from cloud top temperature, the probabilistic method has been used. Using probability distributions of precipitation rates instead of deterministic values has improved the rainfall estimation for different type of clouds.

4D-CT Lung registration using anatomy-based multi-level multi-resolution optical flow analysis and thin-plate splines.

Science.gov (United States)

Min, Yugang; Neylon, John; Shah, Amish; Meeks, Sanford; Lee, Percy; Kupelian, Patrick; Santhanam, Anand P

2014-09-01

The accuracy of 4D-CT registration is limited by inconsistent Hounsfield unit (HU) values in the 4D-CT data from one respiratory phase to another and lower image contrast for lung substructures. This paper presents an optical flow and thin-plate spline (TPS)-based 4D-CT registration method to account for these limitations. The use of unified HU values on multiple anatomy levels (e.g., the lung contour, blood vessels, and parenchyma) accounts for registration errors by inconsistent landmark HU value. While 3D multi-resolution optical flow analysis registers each anatomical level, TPS is employed for propagating the results from one anatomical level to another ultimately leading to the 4D-CT registration. 4D-CT registration was validated using target registration error (TRE), inverse consistency error (ICE) metrics, and a statistical image comparison using Gamma criteria of 1 % intensity difference in 2 mm(3) window range. Validation results showed that the proposed method was able to register CT lung datasets with TRE and ICE values <3 mm. In addition, the average number of voxel that failed the Gamma criteria was <3 %, which supports the clinical applicability of the propose registration mechanism. The proposed 4D-CT registration computes the volumetric lung deformations within clinically viable accuracy.

The dynamic influence of human resources on evidence-based intervention sustainability and population outcomes: an agent-based modeling approach.

Science.gov (United States)