Shapley value-based multi-objective data envelopment analysis application for assessing academic efficiency of university departments

NASA Astrophysics Data System (ADS)

Abing, Stephen Lloyd N.; Barton, Mercie Grace L.; Dumdum, Michael Gerard M.; Bongo, Miriam F.; Ocampo, Lanndon A.

2018-02-01

This paper adopts a modified approach of data envelopment analysis (DEA) to measure the academic efficiency of university departments. In real-world case studies, conventional DEA models often identify too many decision-making units (DMUs) as efficient. This occurs when the number of DMUs under evaluation is not large enough compared to the total number of decision variables. To overcome this limitation and reduce the number of decision variables, multi-objective data envelopment analysis (MODEA) approach previously presented in the literature is applied. The MODEA approach applies Shapley value as a cooperative game to determine the appropriate weights and efficiency score of each category of inputs. To illustrate the performance of the adopted approach, a case study is conducted in a university in the Philippines. The input variables are academic staff, non-academic staff, classrooms, laboratories, research grants, and department expenditures, while the output variables are the number of graduates and publications. The results of the case study revealed that all DMUs are inefficient. DMUs with efficiency scores close to the ideal efficiency score may be emulated by other DMUs with least efficiency scores.

Extending multi-tenant architectures: a database model for a multi-target support in SaaS applications

NASA Astrophysics Data System (ADS)

Rico, Antonio; Noguera, Manuel; Garrido, José Luis; Benghazi, Kawtar; Barjis, Joseph

2016-05-01

Multi-tenant architectures (MTAs) are considered a cornerstone in the success of Software as a Service as a new application distribution formula. Multi-tenancy allows multiple customers (i.e. tenants) to be consolidated into the same operational system. This way, tenants run and share the same application instance as well as costs, which are significantly reduced. Functional needs vary from one tenant to another; either companies from different sectors run different types of applications or, although deploying the same functionality, they do differ in the extent of their complexity. In any case, MTA leaves one major concern regarding the companies' data, their privacy and security, which requires special attention to the data layer. In this article, we propose an extended data model that enhances traditional MTAs in respect of this concern. This extension - called multi-target - allows MT applications to host, manage and serve multiple functionalities within the same multi-tenant (MT) environment. The practical deployment of this approach will allow SaaS vendors to target multiple markets or address different levels of functional complexity and yet commercialise just one single MT application. The applicability of the approach is demonstrated via a case study of a real multi-tenancy multi-target (MT2) implementation, called Globalgest.

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

NASA Astrophysics Data System (ADS)

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-Data Source and Multi-Sensor Approach for the 3d Reconstruction and Visualization of a Complex Archaelogical Site: the Case Study of Tolmo de Minateda

NASA Astrophysics Data System (ADS)

Torres-Martínez, J. A.; Seddaiu, M.; Rodríguez-Gonzálvez, P.; Hernández-López, D.; González-Aguilera, D.

2015-02-01

The complexity of archaeological sites hinders to get an integral modelling using the actual Geomatic techniques (i.e. aerial, closerange photogrammetry and terrestrial laser scanner) individually, so a multi-sensor approach is proposed as the best solution to provide a 3D reconstruction and visualization of these complex sites. Sensor registration represents a riveting milestone when automation is required and when aerial and terrestrial dataset must be integrated. To this end, several problems must be solved: coordinate system definition, geo-referencing, co-registration of point clouds, geometric and radiometric homogeneity, etc. Last but not least, safeguarding of tangible archaeological heritage and its associated intangible expressions entails a multi-source data approach in which heterogeneous material (historical documents, drawings, archaeological techniques, habit of living, etc.) should be collected and combined with the resulting hybrid 3D of "Tolmo de Minateda" located models. The proposed multi-data source and multi-sensor approach is applied to the study case of "Tolmo de Minateda" archaeological site. A total extension of 9 ha is reconstructed, with an adapted level of detail, by an ultralight aerial platform (paratrike), an unmanned aerial vehicle, a terrestrial laser scanner and terrestrial photogrammetry. In addition, the own defensive nature of the site (i.e. with the presence of three different defensive walls) together with the considerable stratification of the archaeological site (i.e. with different archaeological surfaces and constructive typologies) require that tangible and intangible archaeological heritage expressions can be integrated with the hybrid 3D models obtained, to analyse, understand and exploit the archaeological site by different experts and heritage stakeholders.

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

PubMed

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.

Beyond the Pink Sand: Case Studies of Experiences of Multi-Tier System of Supports Implementation in the Bermuda Public School System

ERIC Educational Resources Information Center

Francis-Thompson, Nyshawana

2017-01-01

This qualitative study examined how Multi-tier System of Supports (MTSS), a systematic approach to providing academic and behavioral supports to students, was implemented and experienced by macro and micro levels of educators in the Bermuda Public School system. I asked three research questions regarding: (a) how MTSS was being implemented in the…

The "Russian Doll" Approach: Developing Nested Case-Studies to Support International Comparative Research in Education

ERIC Educational Resources Information Center

Chong, Pei Wen; Graham, Linda J.

2013-01-01

International comparison is complicated by the use of different terms, classification methods, policy frameworks and system structures, not to mention different languages and terminology. Multi-case studies can assist in the understanding of the influence wielded by cultural, social, economic, historical and political forces upon educational…

Infusing Technology Driven Design Thinking in Industrial Design Education: A Case Study

ERIC Educational Resources Information Center

Mubin, Omar; Novoa, Mauricio; Al Mahmud, Abdullah

2017-01-01

Purpose: This paper narrates a case study on design thinking-based education work in an industrial design honours program. Student projects were developed in a multi-disciplinary setting across a Computing and Engineering faculty that allowed promoting technologically and user-driven innovation strategies. Design/methodology/approach: A renewed…

Using multi-criteria risk ranking methodology to select case studies for a generic risk assessment framework for exotic disease incursion and spread through Europe.

PubMed

Horigan, V; De Nardi, M; Simons, R R L; Bertolini, S; Crescio, M I; Estrada-Peña, A; Léger, A; Maurella, C; Ru, G; Schuppers, M; Stärk, K D C; Adkin, A

2018-05-01

We present a novel approach of using the multi-criteria pathogen prioritisation methodology as a basis for selecting the most appropriate case studies for a generic risk assessment framework. The approach uses selective criteria to rank exotic animal health pathogens according to the likelihood of introduction and the impact of an outbreak if it occurred in the European Union (EU). Pathogens were evaluated based on their impact on production at the EU level and international trade. A subsequent analysis included criteria of relevance to quantitative risk assessment case study selection, such as the availability of data for parameterisation, the need for further research and the desire for the case studies to cover different routes of transmission. The framework demonstrated is flexible with the ability to adjust both the criteria and their weightings to the user's requirements. A web based tool has been developed using the RStudio shiny apps software, to facilitate this. Crown Copyright © 2018. Published by Elsevier B.V. All rights reserved.

Student Perceptions of Service Quality in a Multi-Campus Higher Education System in Spain

ERIC Educational Resources Information Center

Gallifa, Josep; Batalle, Pere

2010-01-01

Purpose: This paper aims to present an in-depth case study with student perceptions of service quality, discussing the relevance of these perceptions for the important issue of quality improvement in higher education. Design/methodology/approach: The paper presents institutional research carried out in a multi-campus system in Spain made up of…

Strategy and Structure for Online News Production - Case Studies of CNN and NRK

NASA Astrophysics Data System (ADS)

Krumsvik, Arne H.

This cross-national comparative case study of online news production analyzes the strategies of Cable News Network (CNN) and the Norwegian Broadcasting Corporation (NRK), aiming at understanding of the implications of organizational strategy on the role of journalists, explains why traditional media organizations have a tendency to develop a multi-platform approach (distributing content on several platforms, such as television, online, mobile) rather than developing the cross-media (with interplay between media types) or multimedia approach anticipated by both scholars and practitioners.

External Accountability of Collaborative Arrangements; A Case Study of a Multi Academy Trust in England

ERIC Educational Resources Information Center

Ehren, Melanie C. M.; Godfrey, David

2017-01-01

This paper explores the impact of external accountability on four mechanisms of network-internal quality control and the properties of (mandated) inter-organizational networks. An explorative case study approach examines the external accountability of a newly established educational network (MAT) and how schools and the Trust are held accountable…

Parental Involvement in Active Transport to School Initiatives: A Multi-Site Case Study

ERIC Educational Resources Information Center

Eyler, Amy; Baldwin, Julie; Carnoske, Cheryl; Nickelson, Jan; Troped, Philip; Steinman, Lesley; Pluto, Delores; Litt, Jill; Evenson, Kelly; Terpstra, Jennifer; Brownson, Ross; Schmid, Thomas

2008-01-01

Background: Increasing physical activity in youth is a recommended approach to curbing the childhood obesity epidemic. One way to help increase children's daily activity is to promote active transportation to and from school (ATS). Purpose: The purpose of this case study was to explore parental perception of, and participation in, ATS initiatives.…

Diagnosis and treatment of unconsummated marriage in an Iranian couple.

PubMed

Bokaie, Mahshid; Khalesi, Zahra Bostani; Yasini-Ardekani, Seyed Mojtaba

2017-09-01

Unconsummated marriage is a problem among couples who would not be able to perform natural sexual intercourse and vaginal penetration. This disorder is more common in developing countries and sometimes couples would come up with non-technical and non-scientific methods to overcome their problem. Multi-dimensional approach and narrative exposure therapy used in this case. This study would report a case of unconsummated marriage between a couple after 6 years. The main problem of this couple was vaginismus and post-traumatic stress. Treatment with multi-dimensional approach for this couple included methods like narrative exposure therapy, educating the anatomy of female and male reproductive system, correcting misconceptions, educating foreplay, educating body exploring and non-sexual and sexual massage and penetrating the vagina first by women finger and then men's after relaxation. The entire stages of the treatment lasted for four sessions and at the one-month follow-up couple's satisfaction was desirable. Unconsummated marriage is one of the main sexual problems; it is more common in developing countries than developed countries and cultural factors are effective on intensifying this disorder. The use of multi-dimensional approach in this study led to expedite diagnosis and treatment of vaginismus.

The Worst-Case Weighted Multi-Objective Game with an Application to Supply Chain Competitions.

PubMed

Qu, Shaojian; Ji, Ying

2016-01-01

In this paper, we propose a worst-case weighted approach to the multi-objective n-person non-zero sum game model where each player has more than one competing objective. Our "worst-case weighted multi-objective game" model supposes that each player has a set of weights to its objectives and wishes to minimize its maximum weighted sum objectives where the maximization is with respect to the set of weights. This new model gives rise to a new Pareto Nash equilibrium concept, which we call "robust-weighted Nash equilibrium". We prove that the robust-weighted Nash equilibria are guaranteed to exist even when the weight sets are unbounded. For the worst-case weighted multi-objective game with the weight sets of players all given as polytope, we show that a robust-weighted Nash equilibrium can be obtained by solving a mathematical program with equilibrium constraints (MPEC). For an application, we illustrate the usefulness of the worst-case weighted multi-objective game to a supply chain risk management problem under demand uncertainty. By the comparison with the existed weighted approach, we show that our method is more robust and can be more efficiently used for the real-world applications.

Applying the Neurodynamics of Emotional Circular Causalities in Psychosocial and Cognitive Therapy using Multi-Sensory Environments: An ORBDE Case Study Analysis.

PubMed

Ryan, Janice

2017-10-01

This exploratory, evidence-based practice research study focuses on presenting a plausible mesoscopic brain dynamics hypothesis for the benefits of treating clients with psychosocial and cognitive challenges using a mindful therapeutic approach and multi-sensory environments. After an extensive neuroscientific review of the therapeutic benefits of mindfulness, a multi-sensory environment is presented as a window of therapeutic opportunity to more quickly and efficiently facilitate the neurobiological experience of becoming more mindful or conscious of self and environment. The complementary relationship between the default mode network and the executive attention network is offered as a neurobiological hypothesis that could explain positive occupational engagement pattern shifts in a case study video of a hospice client with advanced dementia during multi-sensory environment treatment. Orbital Decomposition is used for a video analysis that shows a significant behavioral pattern shift consistent with dampening of the perceptual system attractors that contribute to negative emotional circular causalities in a variety of client populations. This treatment approach may also prove to be valuable for any person who has developed circular causalities due to feelings of isolation, victimization, or abuse. A case is made for broader applications of this intervention that may positively influence perception during the information transfer and processing of hippocampal learning. Future research is called for to determine if positive affective, interpersonal, and occupational engagement pattern shifts during treatment are related to the improved default mode network-executive attention network synchrony characteristic of increased mindfulness.

How Do University Teachers Combine Different Approaches to Teaching in a Specific Course? A Qualitative Multi-Case Study

ERIC Educational Resources Information Center

Uiboleht, Kaire; Karm, Mari; Postareff, Liisa

2016-01-01

Teaching approaches in higher education are at the general level well researched and have identified not only the two broad categories of content-focused and learning-focused approaches to teaching but also consonance and dissonance between the aspects of teaching. Consonance means that theoretically coherent teaching practices are employed, but…

Cedar Middle School's Response to Intervention Journey: A Systematic, Multi-Tier, Problem-Solving Approach to Program Implementation

ERIC Educational Resources Information Center

Dulaney, Shannon Kay

2010-01-01

The purpose of the present study was to record Cedar Middle School's (CMS) response to intervention implementation journey. It is a qualitative case study that examines one school's efforts to bring school improvements under the response to inventory (RtI) umbrella in order to achieve a more systematic approach to providing high-quality…

A robust multi-objective global supplier selection model under currency fluctuation and price discount

NASA Astrophysics Data System (ADS)

Zarindast, Atousa; Seyed Hosseini, Seyed Mohamad; Pishvaee, Mir Saman

2017-06-01

Robust supplier selection problem, in a scenario-based approach has been proposed, when the demand and exchange rates are subject to uncertainties. First, a deterministic multi-objective mixed integer linear programming is developed; then, the robust counterpart of the proposed mixed integer linear programming is presented using the recent extension in robust optimization theory. We discuss decision variables, respectively, by a two-stage stochastic planning model, a robust stochastic optimization planning model which integrates worst case scenario in modeling approach and finally by equivalent deterministic planning model. The experimental study is carried out to compare the performances of the three models. Robust model resulted in remarkable cost saving and it illustrated that to cope with such uncertainties, we should consider them in advance in our planning. In our case study different supplier were selected due to this uncertainties and since supplier selection is a strategic decision, it is crucial to consider these uncertainties in planning approach.

A study of zero tolerance policies in schools: a multi-integrated systems approach to improve outcomes for adolescents.

PubMed

Teske, Steven C

2011-05-01

School officials throughout the United States have adopted zero tolerance policies to address student discipline, resulting in an increase in out-of-school suspensions and expulsions. The introduction of police on school campuses also increased the referral of students to the juvenile courts. Although school personnel generally view zero tolerance policies as a constructive measure, this approach denies recent research on adolescent brain development that mischief is a foreseeable derivative of adolescence. A case study method examined one juvenile court's innovative multi-integrated systems approach related to the adverse trends associated with zero tolerance policies. A multi-disciplinary protocol resulted in more effective youth assessments that reduced out-of-school suspensions and school referrals; increased graduation rates by 20%; and decreased delinquent felony rates by nearly 50%. The resulting protocol changed how the system responds to disruptive students by significantly reducing out-of-school suspensions and school referrals, and putting into place alternatives as well as providing community resources to address the underlying causes of the behavior. A multi-systems approach that targets the reasons for disruptive behavior improves student educational and behavioral outcomes. © 2011 Wiley Periodicals, Inc.

Absolute order-of-magnitude reasoning applied to a social multi-criteria evaluation framework

NASA Astrophysics Data System (ADS)

Afsordegan, A.; Sánchez, M.; Agell, N.; Aguado, J. C.; Gamboa, G.

2016-03-01

A social multi-criteria evaluation framework for solving a real-case problem of selecting a wind farm location in the regions of Urgell and Conca de Barberá in Catalonia (northeast of Spain) is studied. This paper applies a qualitative multi-criteria decision analysis approach based on linguistic labels assessment able to address uncertainty and deal with different levels of precision. This method is based on qualitative reasoning as an artificial intelligence technique for assessing and ranking multi-attribute alternatives with linguistic labels in order to handle uncertainty. This method is suitable for problems in the social framework such as energy planning which require the construction of a dialogue process among many social actors with high level of complexity and uncertainty. The method is compared with an existing approach, which has been applied previously in the wind farm location problem. This approach, consisting of an outranking method, is based on Condorcet's original method. The results obtained by both approaches are analysed and their performance in the selection of the wind farm location is compared in aggregation procedures. Although results show that both methods conduct to similar alternatives rankings, the study highlights both their advantages and drawbacks.

One-stage Posterior Approach in the Treatment of Consecutive Multi-segment Thoracic Tuberculosis with Kyphosis.

PubMed

Zhong, Nanzhe; Kong, Jinhai; Sun, Zhengwang; Qian, Ming; Liu, Tielong; Xiao, Jianru

2018-01-01

To evaluate the clinical efficacy of the one-stage posterior approach in treating consecutive multiple-segment thoracic tuberculosis with kyphosis. A retrospective study was performed. The data of 22 patients with consecutive multi-level thoracic tuberculosis and kyphosis who underwent the one-stage posterior approach of debridement, bone grafting, drainage and pedicle screws fixation were collected. The kyphotic angle was 61.6°±3.1° pre-operatively. The neurologic status based on American Spinal Injury Association (ASIA) scoring was A in 5 cases, B in 4 cases, C in 9 cases, D in 3 cases and E in 1 case. The average follow-up period was 43.4±5.0 months. The kyphotic angle was 19.8°±0.7° after operation (p < 0.01), and 21.9°±1.2° at the last visit (p < 0.01). No neurological deterioration was observed in any patients after surgery. A significant difference in ASIA score was detected when the state before the operation and at the last visit was compared (p < 0.01). There was no recurrent paravertebral abscess of thoracic tuberculosis in any of these cases. The one-stage posterior approach of debridement and drainage is a feasible surgical option for consecutive multisegment thoracic tuberculosis with kyphosis. It can achieve debridement, decompression, and stabilization simultaneously.

The Worst-Case Weighted Multi-Objective Game with an Application to Supply Chain Competitions

PubMed Central

Qu, Shaojian; Ji, Ying

2016-01-01

In this paper, we propose a worst-case weighted approach to the multi-objective n-person non-zero sum game model where each player has more than one competing objective. Our “worst-case weighted multi-objective game” model supposes that each player has a set of weights to its objectives and wishes to minimize its maximum weighted sum objectives where the maximization is with respect to the set of weights. This new model gives rise to a new Pareto Nash equilibrium concept, which we call “robust-weighted Nash equilibrium”. We prove that the robust-weighted Nash equilibria are guaranteed to exist even when the weight sets are unbounded. For the worst-case weighted multi-objective game with the weight sets of players all given as polytope, we show that a robust-weighted Nash equilibrium can be obtained by solving a mathematical program with equilibrium constraints (MPEC). For an application, we illustrate the usefulness of the worst-case weighted multi-objective game to a supply chain risk management problem under demand uncertainty. By the comparison with the existed weighted approach, we show that our method is more robust and can be more efficiently used for the real-world applications. PMID:26820512

A tuning algorithm for model predictive controllers based on genetic algorithms and fuzzy decision making.

PubMed

van der Lee, J H; Svrcek, W Y; Young, B R

2008-01-01

Model Predictive Control is a valuable tool for the process control engineer in a wide variety of applications. Because of this the structure of an MPC can vary dramatically from application to application. There have been a number of works dedicated to MPC tuning for specific cases. Since MPCs can differ significantly, this means that these tuning methods become inapplicable and a trial and error tuning approach must be used. This can be quite time consuming and can result in non-optimum tuning. In an attempt to resolve this, a generalized automated tuning algorithm for MPCs was developed. This approach is numerically based and combines a genetic algorithm with multi-objective fuzzy decision-making. The key advantages to this approach are that genetic algorithms are not problem specific and only need to be adapted to account for the number and ranges of tuning parameters for a given MPC. As well, multi-objective fuzzy decision-making can handle qualitative statements of what optimum control is, in addition to being able to use multiple inputs to determine tuning parameters that best match the desired results. This is particularly useful for multi-input, multi-output (MIMO) cases where the definition of "optimum" control is subject to the opinion of the control engineer tuning the system. A case study will be presented in order to illustrate the use of the tuning algorithm. This will include how different definitions of "optimum" control can arise, and how they are accounted for in the multi-objective decision making algorithm. The resulting tuning parameters from each of the definition sets will be compared, and in doing so show that the tuning parameters vary in order to meet each definition of optimum control, thus showing the generalized automated tuning algorithm approach for tuning MPCs is feasible.

A novel approach to study effects of asymmetric stiffness on parametric instabilities of multi-rotor-system

NASA Astrophysics Data System (ADS)

Jain, Anuj Kumar; Rastogi, Vikas; Agrawal, Atul Kumar

2018-01-01

The main focus of this paper is to study effects of asymmetric stiffness on parametric instabilities of multi-rotor-system through extended Lagrangian formalism, where symmetries are broken in terms of the rotor stiffness. The complete insight of dynamic behaviour of multi-rotor-system with asymmetries is evaluated through extension of Lagrangian equation with a case study. In this work, a dynamic mathematical model of a multi-rotor-system through a novel approach of extension of Lagrangian mechanics is developed, where the system is having asymmetries due to varying stiffness. The amplitude and the natural frequency of the rotor are obtained analytically through the proposed methodology. The bond graph modeling technique is used for modeling the asymmetric rotor. Symbol-shakti® software is used for the simulation of the model. The effects of the stiffness of multi-rotor-system on amplitude and frequencies are studied using numerical simulation. Simulation results show a considerable agreement with the theoretical results obtained through extended Lagrangian formalism. It is further shown that amplitude of the rotor increases inversely the stiffness of the rotor up to a certain limit, which is also affirmed theoretically.

Importance of multi-modal approaches to effectively identify cataract cases from electronic health records.

PubMed

Peissig, Peggy L; Rasmussen, Luke V; Berg, Richard L; Linneman, James G; McCarty, Catherine A; Waudby, Carol; Chen, Lin; Denny, Joshua C; Wilke, Russell A; Pathak, Jyotishman; Carrell, David; Kho, Abel N; Starren, Justin B

2012-01-01

There is increasing interest in using electronic health records (EHRs) to identify subjects for genomic association studies, due in part to the availability of large amounts of clinical data and the expected cost efficiencies of subject identification. We describe the construction and validation of an EHR-based algorithm to identify subjects with age-related cataracts. We used a multi-modal strategy consisting of structured database querying, natural language processing on free-text documents, and optical character recognition on scanned clinical images to identify cataract subjects and related cataract attributes. Extensive validation on 3657 subjects compared the multi-modal results to manual chart review. The algorithm was also implemented at participating electronic MEdical Records and GEnomics (eMERGE) institutions. An EHR-based cataract phenotyping algorithm was successfully developed and validated, resulting in positive predictive values (PPVs) >95%. The multi-modal approach increased the identification of cataract subject attributes by a factor of three compared to single-mode approaches while maintaining high PPV. Components of the cataract algorithm were successfully deployed at three other institutions with similar accuracy. A multi-modal strategy incorporating optical character recognition and natural language processing may increase the number of cases identified while maintaining similar PPVs. Such algorithms, however, require that the needed information be embedded within clinical documents. We have demonstrated that algorithms to identify and characterize cataracts can be developed utilizing data collected via the EHR. These algorithms provide a high level of accuracy even when implemented across multiple EHRs and institutional boundaries.

Hazard Interactions and Interaction Networks (Cascades) within Multi-Hazard Methodologies

NASA Astrophysics Data System (ADS)

Gill, Joel; Malamud, Bruce D.

2016-04-01

Here we combine research and commentary to reinforce the importance of integrating hazard interactions and interaction networks (cascades) into multi-hazard methodologies. We present a synthesis of the differences between 'multi-layer single hazard' approaches and 'multi-hazard' approaches that integrate such interactions. This synthesis suggests that ignoring interactions could distort management priorities, increase vulnerability to other spatially relevant hazards or underestimate disaster risk. We proceed to present an enhanced multi-hazard framework, through the following steps: (i) describe and define three groups (natural hazards, anthropogenic processes and technological hazards/disasters) as relevant components of a multi-hazard environment; (ii) outline three types of interaction relationship (triggering, increased probability, and catalysis/impedance); and (iii) assess the importance of networks of interactions (cascades) through case-study examples (based on literature, field observations and semi-structured interviews). We further propose visualisation frameworks to represent these networks of interactions. Our approach reinforces the importance of integrating interactions between natural hazards, anthropogenic processes and technological hazards/disasters into enhanced multi-hazard methodologies. Multi-hazard approaches support the holistic assessment of hazard potential, and consequently disaster risk. We conclude by describing three ways by which understanding networks of interactions contributes to the theoretical and practical understanding of hazards, disaster risk reduction and Earth system management. Understanding interactions and interaction networks helps us to better (i) model the observed reality of disaster events, (ii) constrain potential changes in physical and social vulnerability between successive hazards, and (iii) prioritise resource allocation for mitigation and disaster risk reduction.

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

NASA Astrophysics Data System (ADS)

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.

Making Sense of Clinical Practice: Order Set Design Strategies in CPOE

PubMed Central

Novak, Laurie L.

2007-01-01

A case study was conducted during the customization phase of a commercial CPOE system at a multi-hospital, academic health system. The study focused on the development of order sets. Three distinct approaches to order set development were observed: Empirical, Local Consensus and Departmental. The three approaches are first described and then examined using the framework of sensemaking. Different approaches to sensemaking in the context of order set development reflect variations in sources of knowledge related to the standardization of care. PMID:18693900

Ventura County fare integration : a case study : promoting seamless regional fare coordination

DOT National Transportation Integrated Search

2001-09-01

This report details the approach taken in one specific region to plan, operate, and maintain a multi-agency, transit fare collection payment system demonstration utilizing smart card technology as well as other ITS (intelligent transportation systems...

DOE Office of Scientific and Technical Information (OSTI.GOV)

Perdikaris, Paris, E-mail: parisp@mit.edu; Grinberg, Leopold, E-mail: leopoldgrinberg@us.ibm.com; Karniadakis, George Em, E-mail: george-karniadakis@brown.edu

The aim of this work is to present an overview of recent advances in multi-scale modeling of brain blood flow. In particular, we present some approaches that enable the in silico study of multi-scale and multi-physics phenomena in the cerebral vasculature. We discuss the formulation of continuum and atomistic modeling approaches, present a consistent framework for their concurrent coupling, and list some of the challenges that one needs to overcome in achieving a seamless and scalable integration of heterogeneous numerical solvers. The effectiveness of the proposed framework is demonstrated in a realistic case involving modeling the thrombus formation process takingmore » place on the wall of a patient-specific cerebral aneurysm. This highlights the ability of multi-scale algorithms to resolve important biophysical processes that span several spatial and temporal scales, potentially yielding new insight into the key aspects of brain blood flow in health and disease. Finally, we discuss open questions in multi-scale modeling and emerging topics of future research.« less

Multiscale modeling and simulation of brain blood flow

NASA Astrophysics Data System (ADS)

Perdikaris, Paris; Grinberg, Leopold; Karniadakis, George Em

2016-02-01

The aim of this work is to present an overview of recent advances in multi-scale modeling of brain blood flow. In particular, we present some approaches that enable the in silico study of multi-scale and multi-physics phenomena in the cerebral vasculature. We discuss the formulation of continuum and atomistic modeling approaches, present a consistent framework for their concurrent coupling, and list some of the challenges that one needs to overcome in achieving a seamless and scalable integration of heterogeneous numerical solvers. The effectiveness of the proposed framework is demonstrated in a realistic case involving modeling the thrombus formation process taking place on the wall of a patient-specific cerebral aneurysm. This highlights the ability of multi-scale algorithms to resolve important biophysical processes that span several spatial and temporal scales, potentially yielding new insight into the key aspects of brain blood flow in health and disease. Finally, we discuss open questions in multi-scale modeling and emerging topics of future research.

Between Scylla and Charybdis: How Catholic High School Leaders Negotiate the Polarities of Contemporary U.S. Culture within the Catholic Educational Market

ERIC Educational Resources Information Center

Ferdinandt, Kevin William

2009-01-01

This qualitative, comparative case study involves a multi-faceted approach to how lay leaders in four different Catholic high schools brand their schools within a broader Catholic educational marketplace. As compared with the parochial era (1884-1965), the approach of Catholic high school administrators, campus ministers, department chairs, and…

Teacher Conceptions and Approaches Associated with an Immersive Instructional Implementation of Computer-Based Models and Assessment in a Secondary Chemistry Classroom

ERIC Educational Resources Information Center

Waight, Noemi; Liu, Xiufeng; Gregorius, Roberto Ma.; Smith, Erica; Park, Mihwa

2014-01-01

This paper reports on a case study of an immersive and integrated multi-instructional approach (namely computer-based model introduction and connection with content; facilitation of individual student exploration guided by exploratory worksheet; use of associated differentiated labs and use of model-based assessments) in the implementation of…

Feasibility of a novel participatory multi-sector continuous improvement approach to enhance food security in remote Indigenous Australian communities.

PubMed

Brimblecombe, J; Bailie, R; van den Boogaard, C; Wood, B; Liberato, S C; Ferguson, M; Coveney, J; Jaenke, R; Ritchie, J

2017-12-01

Food insecurity underlies and compounds many of the development issues faced by remote Indigenous communities in Australia. Multi-sector approaches offer promise to improve food security. We assessed the feasibility of a novel multi-sector approach to enhance community food security in remote Indigenous Australia. A longitudinal comparative multi-site case study, the Good Food Systems Good Food for All Project, was conducted (2009-2013) with four Aboriginal communities. Continuous improvement meetings were held in each community. Data from project documents and store sales were used to assess feasibility according to engagement, uptake and sustainability of action, and impact on community diet, as well as identifying conditions facilitating or hindering these. Engagement was established where: the community perceived a need for the approach; where trust was developed between the community and facilitators; where there was community stability; and where flexibility was applied in the timing of meetings. The approach enabled stakeholders in each community to collectively appraise the community food system and plan action. Actions that could be directly implemented within available resources resulted from developing collaborative capacity. Actions requiring advocacy, multi-sectoral involvement, commitment or further resources were less frequently used. Positive shifts in community diet were associated with key areas where actions were implemented. A multi-sector participatory approach seeking continuous improvement engaged committed Aboriginal and non-Aboriginal stakeholders and was shown to have potential to shift community diet. Provision of clear mechanisms to link this approach with higher level policy and decision-making structures, clarity of roles and responsibilities, and processes to prioritise and communicate actions across sectors should further strengthen capacity for food security improvement. Integrating this approach enabling local decision-making into community governance structures with adequate resourcing is an imperative.

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

NASA Astrophysics Data System (ADS)

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 component on the critical path is relatively more important in a risk-informed environment. Significance of multi-hazard risk is also illustrated for uncorrelated hazards of earthquakes and high winds which may result in competing design objectives. It is also illustrated that the number of computationally intensive nonlinear simulations needed in performance-based risk assessment for external hazards can be significantly reduced by using the power of Bayesian updating in conjunction with the concept of equivalent limit-state.

Loop-mediated isothermal amplification (LAMP) assay for speedy diagnosis of tubercular lymphadenitis: The multi-targeted 60-minute approach.

PubMed

Sharma, Megha; Sharma, Kusum; Sharma, Aman; Gupta, Nalini; Rajwanshi, Arvind

2016-09-01

Tuberculous lymphadenitis (TBLA), the most common presentation of tuberculosis, poses a significant diagnostic challenge in the developing countries. Timely, accurate and cost-effective diagnosis can decrease the high morbidity associated with TBLA especially in resource-poor high-endemic regions. The loop-mediated isothermal amplification assay (LAMP), using two targets, was evaluated for the diagnosis of TBLA. LAMP assay using 3 sets of primers (each for IS6110 and MPB64) was performed on 170 fine needle aspiration samples (85 confirmed, 35 suspected, 50 control cases of TBLA). Results were compared against IS6110 PCR, cytology, culture and smear. The overall sensitivity and specificity of LAMP assay, using multi-targeted approach, was 90% and 100% respectively in diagnosing TBLA. The sensitivity of multi-targeted LAMP, only MPB64 LAMP, only IS6110 LAMP and IS6110 PCR was 91.7%, 89.4%, 84.7% and 75.2%, respectively among confirmed cases and 85.7%, 77.1%, 68.5% and 60%, respectively among suspected cases of TBLA. Additional 12/120 (10%) cases were detected using multi-targeted method. The multi-targeted LAMP, with its speedy and reliable results, is a potential diagnostic test for TBLA in low-resource countries. Copyright © 2016 Elsevier Ltd. All rights reserved.

Team Learning: Collective Reflection Processes in Teacher Teams

ERIC Educational Resources Information Center

Ohlsson, Jon

2013-01-01

Purpose: The purpose of this paper is to contribute to further studies of theoretical and conceptual understanding of teachers' team learning processes, with a main focus on team work, team atmosphere, and collective reflections. Design/methodology/approach: The empirical study was designed as a multi-case study in a research and development…

Visualising Pareto-optimal trade-offs helps move beyond monetary-only criteria for water management decisions

NASA Astrophysics Data System (ADS)

Hurford, Anthony; Harou, Julien

2014-05-01

Water related eco-system services are important to the livelihoods of the poorest sectors of society in developing countries. Degradation or loss of these services can increase the vulnerability of people decreasing their capacity to support themselves. New approaches to help guide water resources management decisions are needed which account for the non-market value of ecosystem goods and services. In case studies from Brazil and Kenya we demonstrate the capability of many objective Pareto-optimal trade-off analysis to help decision makers balance economic and non-market benefits from the management of existing multi-reservoir systems. A multi-criteria search algorithm is coupled to a water resources management simulator of each basin to generate a set of Pareto-approximate trade-offs representing the best case management decisions. In both cases, volume dependent reservoir release rules are the management decisions being optimised. In the Kenyan case we further assess the impacts of proposed irrigation investments, and how the possibility of new investments impacts the system's trade-offs. During the multi-criteria search (optimisation), performance of different sets of management decisions (policies) is assessed against case-specific objective functions representing provision of water supply and irrigation, hydropower generation and maintenance of ecosystem services. Results are visualised as trade-off surfaces to help decision makers understand the impacts of different policies on a broad range of stakeholders and to assist in decision-making. These case studies show how the approach can reveal unexpected opportunities for win-win solutions, and quantify the trade-offs between investing to increase agricultural revenue and negative impacts on protected ecosystems which support rural livelihoods.

Development of policies for Natura 2000 sites: a multi-criteria approach to support decision makers.

PubMed

Cortina, Carla; Boggia, Antonio

2014-08-01

The aim of this study is to present a methodology to support decision makers in the choice of Natura 2000 sites needing an appropriate management plan to ensure a sustainable socio-economic development. In order to promote sustainable development in the Natura 2000 sites compatible with nature preservation, conservation measures or management plans are necessary. The main issue is to decide when only conservation measures can be applied and when the sites need an appropriate management plan. We present a case study for the Italian Region of Umbria. The methodology is based on a multi-criteria approach to identify the biodiversity index (BI), and on the development of a human activities index (HAI). By crossing the two indexes for each site on a Cartesian plane, four groups of sites were identified. Each group corresponds to a specific need for an appropriate management plan. Sites in the first group with a high level both of biodiversity and human activities have the most urgent need of an appropriate management plan to ensure sustainable development. The proposed methodology and analysis is replicable in other regions or countries by using the data available for each site in the Natura 2000 standard data form. A multi-criteria analysis is especially suitable for supporting decision makers when they deal with a multidimensional decision process. We found the multi-criteria approach particularly sound in this case, due to the concept of biodiversity itself, which is complex and multidimensional, and to the high number of alternatives (Natura 2000 sites) to be assessed. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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 Limestone. The study is progressed based on the followings. Firstly, hydrological time series of each catchment are sampled and clustered into multi-period having distinctly different temporal characteristics, and secondly, behavioural parameter distributions are determined in each multi-period based on the specification of multi-criteria model performance measures. Finally, behavioural parameter sets of each multi-period of single catchment are applied on the corresponding period of other catchments, and the cross-validations are conducted in this manner for all catchments The multi-period model conditioning approach is clearly effective to reduce the width of prediction limits, giving better model performance against the temporal variability of hydrological characteristics, and has enough potential to be the effective prediction tool for ungauged catchments. However, more advanced and continuous studies are needed to expand the application of this approach in prediction of hydrological responses in ungauged catchments,

Advantages of Task-Specific Multi-Objective Optimisation in Evolutionary Robotics.

PubMed

Trianni, Vito; López-Ibáñez, Manuel

2015-01-01

The application of multi-objective optimisation to evolutionary robotics is receiving increasing attention. A survey of the literature reveals the different possibilities it offers to improve the automatic design of efficient and adaptive robotic systems, and points to the successful demonstrations available for both task-specific and task-agnostic approaches (i.e., with or without reference to the specific design problem to be tackled). However, the advantages of multi-objective approaches over single-objective ones have not been clearly spelled out and experimentally demonstrated. This paper fills this gap for task-specific approaches: starting from well-known results in multi-objective optimisation, we discuss how to tackle commonly recognised problems in evolutionary robotics. In particular, we show that multi-objective optimisation (i) allows evolving a more varied set of behaviours by exploring multiple trade-offs of the objectives to optimise, (ii) supports the evolution of the desired behaviour through the introduction of objectives as proxies, (iii) avoids the premature convergence to local optima possibly introduced by multi-component fitness functions, and (iv) solves the bootstrap problem exploiting ancillary objectives to guide evolution in the early phases. We present an experimental demonstration of these benefits in three different case studies: maze navigation in a single robot domain, flocking in a swarm robotics context, and a strictly collaborative task in collective robotics.

Supermodeling With A Global Atmospheric Model

NASA Astrophysics Data System (ADS)

Wiegerinck, Wim; Burgers, Willem; Selten, Frank

2013-04-01

In weather and climate prediction studies it often turns out to be the case that the multi-model ensemble mean prediction has the best prediction skill scores. One possible explanation is that the major part of the model error is random and is averaged out in the ensemble mean. In the standard multi-model ensemble approach, the models are integrated in time independently and the predicted states are combined a posteriori. Recently an alternative ensemble prediction approach has been proposed in which the models exchange information during the simulation and synchronize on a common solution that is closer to the truth than any of the individual model solutions in the standard multi-model ensemble approach or a weighted average of these. This approach is called the super modeling approach (SUMO). The potential of the SUMO approach has been demonstrated in the context of simple, low-order, chaotic dynamical systems. The information exchange takes the form of linear nudging terms in the dynamical equations that nudge the solution of each model to the solution of all other models in the ensemble. With a suitable choice of the connection strengths the models synchronize on a common solution that is indeed closer to the true system than any of the individual model solutions without nudging. This approach is called connected SUMO. An alternative approach is to integrate a weighted averaged model, weighted SUMO. At each time step all models in the ensemble calculate the tendency, these tendencies are weighted averaged and the state is integrated one time step into the future with this weighted averaged tendency. It was shown that in case the connected SUMO synchronizes perfectly, the connected SUMO follows the weighted averaged trajectory and both approaches yield the same solution. In this study we pioneer both approaches in the context of a global, quasi-geostrophic, three-level atmosphere model that is capable of simulating quite realistically the extra-tropical circulation in the Northern Hemisphere winter.

Importance of multi-modal approaches to effectively identify cataract cases from electronic health records

PubMed Central

Rasmussen, Luke V; Berg, Richard L; Linneman, James G; McCarty, Catherine A; Waudby, Carol; Chen, Lin; Denny, Joshua C; Wilke, Russell A; Pathak, Jyotishman; Carrell, David; Kho, Abel N; Starren, Justin B

2012-01-01

Objective There is increasing interest in using electronic health records (EHRs) to identify subjects for genomic association studies, due in part to the availability of large amounts of clinical data and the expected cost efficiencies of subject identification. We describe the construction and validation of an EHR-based algorithm to identify subjects with age-related cataracts. Materials and methods We used a multi-modal strategy consisting of structured database querying, natural language processing on free-text documents, and optical character recognition on scanned clinical images to identify cataract subjects and related cataract attributes. Extensive validation on 3657 subjects compared the multi-modal results to manual chart review. The algorithm was also implemented at participating electronic MEdical Records and GEnomics (eMERGE) institutions. Results An EHR-based cataract phenotyping algorithm was successfully developed and validated, resulting in positive predictive values (PPVs) >95%. The multi-modal approach increased the identification of cataract subject attributes by a factor of three compared to single-mode approaches while maintaining high PPV. Components of the cataract algorithm were successfully deployed at three other institutions with similar accuracy. Discussion A multi-modal strategy incorporating optical character recognition and natural language processing may increase the number of cases identified while maintaining similar PPVs. Such algorithms, however, require that the needed information be embedded within clinical documents. Conclusion We have demonstrated that algorithms to identify and characterize cataracts can be developed utilizing data collected via the EHR. These algorithms provide a high level of accuracy even when implemented across multiple EHRs and institutional boundaries. PMID:22319176

Why we need multi-level health workforce governance: Case studies from nursing and medicine in Germany.

PubMed

Kuhlmann, Ellen; Larsen, Christa

2015-12-01

Health workforce needs have moved up on the reform agendas, but policymaking often remains 'piece-meal work' and does not respond to the complexity of health workforce challenges. This article argues for innovation in healthcare governance as a key to greater sustainability of health human resources. The aim is to develop a multi-level approach that helps to identify gaps in governance and improve policy interventions. Pilot research into nursing and medicine in Germany, carried out between 2013 and 2015 using a qualitative methodology, serves to illustrate systems-based governance weaknesses. Three explorative cases address major responses to health workforce shortages, comprising migration/mobility of nurses, reform of nursing education, and gender-sensitive work management of hospital doctors. The findings illustrate a lack of connections between transnational/EU and organizational governance, between national and local levels, occupational and sector governance, and organizations/hospital management and professional development. Consequently, innovations in the health workforce need a multi-level governance approach to get transformative potential and help closing the existing gaps in governance. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Case study research: training interdisciplinary engineers with context-dependent knowledge

NASA Astrophysics Data System (ADS)

Chanan, Amit; Vigneswaran, Saravanamuth; Kandasamy, Jaya

2012-03-01

It is now widely acknowledged that water management discipline is transforming, from being a public health and flood prevention challenge of the nineteenth century to a multi-dimensional challenge of water security for the twenty-first century. In order to train water engineers to be capable of working with this holistic multi-dimensional approach, a new paradigm in engineering education is required. Adjustments already made to undergraduate coursework are not enough; this new paradigm requires modifications to the PhD in engineering, with greater emphasis on interdisciplinary case study research. Such a change can deliver PhD graduates with both sufficient social and technical knowledge, who can then go on to become the hybrid lecturers crucially needed for training future water engineers.

Multi-state Markov model for disability: A case of Malaysia Social Security (SOCSO)

NASA Astrophysics Data System (ADS)

Samsuddin, Shamshimah; Ismail, Noriszura

2016-06-01

Studies of SOCSO's contributor outcomes like disability are usually restricted to a single outcome. In this respect, the study has focused on the approach of multi-state Markov model for estimating the transition probabilities among SOCSO's contributor in Malaysia between states: work, temporary disability, permanent disability and death at yearly intervals on age, gender, year and disability category; ignoring duration and past disability experience which is not consider of how or when someone arrived in that category. These outcomes represent different states which depend on health status among the workers.

What We Can Learn from the Data: A Multiple-Case Study Examining Behavior Patterns by Students with Different Characteristics in Using a Serious Game

ERIC Educational Resources Information Center

Liu, Min; Lee, Jaejin; Kang, Jina; Liu, Sa

2016-01-01

Using a multi-case approach, we examined students' behavior patterns in interacting with a serious game environment using the emerging technologies of learning analytics and data visualization in order to understand how the patterns may vary according to students' learning characteristics. The results confirmed some preliminary findings from our…

Developing injury prevention policy through a multi-agency partnership approach: a case study of a state-wide sports safety policy in New South Wales, Australia.

PubMed

Poulos, Roslyn G; Donaldson, Alex; McLeod, Brent

2012-01-01

Sports injuries are an important public health issue. A multi-agency key stakeholder partnership was formed to develop a state-wide response to sports injury prevention in New South Wales, Australia. This study evaluated the partnership approach to injury prevention policy development. The partnership approach to policy development was evaluated pre- and post-partnership using semi-structured telephone interviews and questionnaire data gathered from participants. Participants were satisfied with the partnership operation and outcomes. Challenges included: maintaining focus and efficiency; time constraints; sector diversity limiting the likelihood of addressing needs and reaching consensus; and ensuring commitment from all relevant organisations. Potential benefits included: a sense of policy ownership; a broad-based approach across the sector and savings from resource sharing. Policy resulted from a shared understanding of the injury problem, and of an appropriate response. A credible industry leader, investment in partnership management and a consultative approach facilitated the success of the partnership.

The Human Dimension of Energy Conservation and Sustainability: A Case Study of the University of Michigan's Energy Conservation Program

ERIC Educational Resources Information Center

Marans, Robert W.; Edelstein, Jack Y.

2010-01-01

Purpose: The purpose of this paper is to determine the behaviors, attitudes, and levels of understanding among faculty, staff, and students in efforts to design programs aimed at reducing energy use in University of Michigan (UM) buildings. Design/methodology/approach: A multi-method approach is used in five diverse pilot buildings including focus…

Secondary School Socio-Cultural Context Influencing ICT Integration: A Case Study Approach

ERIC Educational Resources Information Center

Divaharan, Shanti; Ping, Lim Cher

2010-01-01

This paper proposes the use of activity theory and multi-level activity systems as a framework to analyse the effectiveness of ICT integration in Singapore secondary school classrooms. Three levels of activity systems are developed to study the effectiveness of ICT integration at the classroom: the classroom activity system, the department…

Leadership and the Design of Data-Driven Professional Networks in Schools

ERIC Educational Resources Information Center

Liou, Yi-Hwa; Grigg, Jeffrey; Halverson, Richard

2014-01-01

Using data from a multi-method comparative case study of two matched schools, this paper adds to the growing body of applications of social network analysis to the study of distributed leadership and accountability. We contrast two approaches to instructional leadership, prescriptive and discretionary, to investigate how leaders design…

Toward an Instructional Approach to Developing Interactive Second Language Listening

ERIC Educational Resources Information Center

Yeldham, Michael; Gruba, Paul

2014-01-01

This study details the development of six second language learners in an English listening course that focused on developing their bottom-up listening skills. The research employed longitudinal multi-case studies to chart the development of these lower proficiency-level Taiwanese university learners, and their progress in the course was analysed…

A Multi-Armed Bandit Approach to Following a Markov Chain

DTIC Science & Technology

2017-06-01

focus on the House to Café transition (p1,4). We develop a Multi-Armed Bandit approach for efficiently following this target, where each state takes the...and longitude (each state corresponding to a physical location and a small set of activities). The searcher would then apply our approach on this...the target’s transition probability and the true probability over time. Further, we seek to provide upper bounds (i.e., worst case bounds) on the

Bargaining Agents in Wireless Contexts: An Alternating-Offers Protocol for Multi-issue Bilateral Negotiation in Mobile Marketplaces

NASA Astrophysics Data System (ADS)

Ragone, Azzurra; Ruta, Michele; di Sciascio, Eugenio; Donini, Francesco M.

We present an approach to multi-issue bilateral negotiation for mobile commerce scenarios. The negotiation mechanism has been integrated in a semantic-based application layer enhancing both RFID and Bluetooth wireless standards. OWL DL has been used to model advertisements and relationships among issues within a shared common ontology. Finally, non standard inference services integrated with utility theory help in finding suitable agreements. We illustrate and motivate the provided theoretical framework in a wireless commerce case study.

Somatic Consequences and Symptomatic Responses to Stress: Directions for Future Research

DTIC Science & Technology

1999-07-01

endeavors, some early work in developing multi- method , multi-source assessment approaches for identifying cases of PTSD; some clinical studies ... research dealing with the entire concept of the cultural shaping of what he calls the illness narrative and the way in which this tends to control the...talk for five to ten minutes about the pattern of the research you’ve been doing and the directions it’s been going in and the directions you think it

A scale-entropy diffusion equation to describe the multi-scale features of turbulent flames near a wall

NASA Astrophysics Data System (ADS)

Queiros-Conde, D.; Foucher, F.; Mounaïm-Rousselle, C.; Kassem, H.; Feidt, M.

2008-12-01

Multi-scale features of turbulent flames near a wall display two kinds of scale-dependent fractal features. In scale-space, an unique fractal dimension cannot be defined and the fractal dimension of the front is scale-dependent. Moreover, when the front approaches the wall, this dependency changes: fractal dimension also depends on the wall-distance. Our aim here is to propose a general geometrical framework that provides the possibility to integrate these two cases, in order to describe the multi-scale structure of turbulent flames interacting with a wall. Based on the scale-entropy quantity, which is simply linked to the roughness of the front, we thus introduce a general scale-entropy diffusion equation. We define the notion of “scale-evolutivity” which characterises the deviation of a multi-scale system from the pure fractal behaviour. The specific case of a constant “scale-evolutivity” over the scale-range is studied. In this case, called “parabolic scaling”, the fractal dimension is a linear function of the logarithm of scale. The case of a constant scale-evolutivity in the wall-distance space implies that the fractal dimension depends linearly on the logarithm of the wall-distance. We then verified experimentally, that parabolic scaling represents a good approximation of the real multi-scale features of turbulent flames near a wall.

Promoting Affordability in Defense Acquisitions: A Multi-Period Portfolio Approach

DTIC Science & Technology

2014-04-30

has evolved out of many areas of research, ranging from economics to modern control theory (Powell, 2011). The general form of a dynamic programming...states 5 School of Aeronautics & Astronautics A Portfolio Approach: Background • Balance expected profit (performance) against risk ( variance ) in...investments (Markowitz 1952) • Efficiency frontier of optimal portfolios given investor risk averseness • Extends to multi-period case with various

[Individual growth modeling of the penshell Atrina maura (Bivalvia: Pinnidae) using a multi model inference approach].

PubMed

Aragón-Noriega, Eugenio Alberto

2013-09-01

Growth models of marine animals, for fisheries and/or aquaculture purposes, are based on the popular von Bertalanffy model. This tool is mostly used because its parameters are used to evaluate other fisheries models, such as yield per recruit; nevertheless, there are other alternatives (such as Gompertz, Logistic, Schnute) not yet used by fishery scientists, that may result useful depending on the studied species. The penshell Atrina maura, has been studied for fisheries or aquaculture supplies, but its individual growth has not yet been studied before. The aim of this study was to model the absolute growth of the penshell A. maura using length-age data. For this, five models were assessed to obtain growth parameters: von Bertalanffy, Gompertz, Logistic, Schnute case 1 and Schnute and Richards. The criterion used to select the best models was the Akaike information criterion, as well as the residual squared sum and R2 adjusted. To get the average asymptotic length, the multi model inference approach was used. According to Akaike information criteria, the Gompertz model better described the absolute growth of A. maura. Following the multi model inference approach the average asymptotic shell length was 218.9 mm (IC 212.3-225.5) of shell length. I concluded that the use of the multi model approach and the Akaike information criteria represented the most robust method for growth parameter estimation of A. maura and the von Bertalanffy growth model should not be selected a priori as the true model to obtain the absolute growth in bivalve mollusks like in the studied species in this paper.

Path synthesis of four-bar mechanisms using synergy of polynomial neural network and Stackelberg game theory

NASA Astrophysics Data System (ADS)

Ahmadi, Bahman; Nariman-zadeh, Nader; Jamali, Ali

2017-06-01

In this article, a novel approach based on game theory is presented for multi-objective optimal synthesis of four-bar mechanisms. The multi-objective optimization problem is modelled as a Stackelberg game. The more important objective function, tracking error, is considered as the leader, and the other objective function, deviation of the transmission angle from 90° (TA), is considered as the follower. In a new approach, a group method of data handling (GMDH)-type neural network is also utilized to construct an approximate model for the rational reaction set (RRS) of the follower. Using the proposed game-theoretic approach, the multi-objective optimal synthesis of a four-bar mechanism is then cast into a single-objective optimal synthesis using the leader variables and the obtained RRS of the follower. The superiority of using the synergy game-theoretic method of Stackelberg with a GMDH-type neural network is demonstrated for two case studies on the synthesis of four-bar mechanisms.

A multi-objective programming model for assessment the GHG emissions in MSW management

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mavrotas, George, E-mail: mavrotas@chemeng.ntua.gr; Skoulaxinou, Sotiria; Gakis, Nikos

2013-09-15

Highlights: • The multi-objective multi-period optimization model. • The solution approach for the generation of the Pareto front with mathematical programming. • The very detailed description of the model (decision variables, parameters, equations). • The use of IPCC 2006 guidelines for landfill emissions (first order decay model) in the mathematical programming formulation. - Abstract: In this study a multi-objective mathematical programming model is developed for taking into account GHG emissions for Municipal Solid Waste (MSW) management. Mathematical programming models are often used for structure, design and operational optimization of various systems (energy, supply chain, processes, etc.). The last twenty yearsmore » they are used all the more often in Municipal Solid Waste (MSW) management in order to provide optimal solutions with the cost objective being the usual driver of the optimization. In our work we consider the GHG emissions as an additional criterion, aiming at a multi-objective approach. The Pareto front (Cost vs. GHG emissions) of the system is generated using an appropriate multi-objective method. This information is essential to the decision maker because he can explore the trade-offs in the Pareto curve and select his most preferred among the Pareto optimal solutions. In the present work a detailed multi-objective, multi-period mathematical programming model is developed in order to describe the waste management problem. Apart from the bi-objective approach, the major innovations of the model are (1) the detailed modeling considering 34 materials and 42 technologies, (2) the detailed calculation of the energy content of the various streams based on the detailed material balances, and (3) the incorporation of the IPCC guidelines for the CH{sub 4} generated in the landfills (first order decay model). The equations of the model are described in full detail. Finally, the whole approach is illustrated with a case study referring to the application of the model in a Greek region.« less

Data fusion of multi-scale representations for structural damage detection

NASA Astrophysics Data System (ADS)

Guo, Tian; Xu, Zili

2018-01-01

Despite extensive researches into structural health monitoring (SHM) in the past decades, there are few methods that can detect multiple slight damage in noisy environments. Here, we introduce a new hybrid method that utilizes multi-scale space theory and data fusion approach for multiple damage detection in beams and plates. A cascade filtering approach provides multi-scale space for noisy mode shapes and filters the fluctuations caused by measurement noise. In multi-scale space, a series of amplification and data fusion algorithms are utilized to search the damage features across all possible scales. We verify the effectiveness of the method by numerical simulation using damaged beams and plates with various types of boundary conditions. Monte Carlo simulations are conducted to illustrate the effectiveness and noise immunity of the proposed method. The applicability is further validated via laboratory cases studies focusing on different damage scenarios. Both results demonstrate that the proposed method has a superior noise tolerant ability, as well as damage sensitivity, without knowing material properties or boundary conditions.

Multi-fidelity Gaussian process regression for prediction of random fields

DOE Office of Scientific and Technical Information (OSTI.GOV)

Parussini, L.; Venturi, D., E-mail: venturi@ucsc.edu; Perdikaris, P.

We propose a new multi-fidelity Gaussian process regression (GPR) approach for prediction of random fields based on observations of surrogate models or hierarchies of surrogate models. Our method builds upon recent work on recursive Bayesian techniques, in particular recursive co-kriging, and extends it to vector-valued fields and various types of covariances, including separable and non-separable ones. The framework we propose is general and can be used to perform uncertainty propagation and quantification in model-based simulations, multi-fidelity data fusion, and surrogate-based optimization. We demonstrate the effectiveness of the proposed recursive GPR techniques through various examples. Specifically, we study the stochastic Burgersmore » equation and the stochastic Oberbeck–Boussinesq equations describing natural convection within a square enclosure. In both cases we find that the standard deviation of the Gaussian predictors as well as the absolute errors relative to benchmark stochastic solutions are very small, suggesting that the proposed multi-fidelity GPR approaches can yield highly accurate results.« less

Hazard interactions and interaction networks (cascades) within multi-hazard methodologies

NASA Astrophysics Data System (ADS)

Gill, Joel C.; Malamud, Bruce D.

2016-08-01

This paper combines research and commentary to reinforce the importance of integrating hazard interactions and interaction networks (cascades) into multi-hazard methodologies. We present a synthesis of the differences between multi-layer single-hazard approaches and multi-hazard approaches that integrate such interactions. This synthesis suggests that ignoring interactions between important environmental and anthropogenic processes could distort management priorities, increase vulnerability to other spatially relevant hazards or underestimate disaster risk. In this paper we proceed to present an enhanced multi-hazard framework through the following steps: (i) description and definition of three groups (natural hazards, anthropogenic processes and technological hazards/disasters) as relevant components of a multi-hazard environment, (ii) outlining of three types of interaction relationship (triggering, increased probability, and catalysis/impedance), and (iii) assessment of the importance of networks of interactions (cascades) through case study examples (based on the literature, field observations and semi-structured interviews). We further propose two visualisation frameworks to represent these networks of interactions: hazard interaction matrices and hazard/process flow diagrams. Our approach reinforces the importance of integrating interactions between different aspects of the Earth system, together with human activity, into enhanced multi-hazard methodologies. Multi-hazard approaches support the holistic assessment of hazard potential and consequently disaster risk. We conclude by describing three ways by which understanding networks of interactions contributes to the theoretical and practical understanding of hazards, disaster risk reduction and Earth system management. Understanding interactions and interaction networks helps us to better (i) model the observed reality of disaster events, (ii) constrain potential changes in physical and social vulnerability between successive hazards, and (iii) prioritise resource allocation for mitigation and disaster risk reduction.

Multi-GPU and multi-CPU accelerated FDTD scheme for vibroacoustic applications

NASA Astrophysics Data System (ADS)

Francés, J.; Otero, B.; Bleda, S.; Gallego, S.; Neipp, C.; Márquez, A.; Beléndez, A.

2015-06-01

The Finite-Difference Time-Domain (FDTD) method is applied to the analysis of vibroacoustic problems and to study the propagation of longitudinal and transversal waves in a stratified media. The potential of the scheme and the relevance of each acceleration strategy for massively computations in FDTD are demonstrated in this work. In this paper, we propose two new specific implementations of the bi-dimensional scheme of the FDTD method using multi-CPU and multi-GPU, respectively. In the first implementation, an open source message passing interface (OMPI) has been included in order to massively exploit the resources of a biprocessor station with two Intel Xeon processors. Moreover, regarding CPU code version, the streaming SIMD extensions (SSE) and also the advanced vectorial extensions (AVX) have been included with shared memory approaches that take advantage of the multi-core platforms. On the other hand, the second implementation called the multi-GPU code version is based on Peer-to-Peer communications available in CUDA on two GPUs (NVIDIA GTX 670). Subsequently, this paper presents an accurate analysis of the influence of the different code versions including shared memory approaches, vector instructions and multi-processors (both CPU and GPU) and compares them in order to delimit the degree of improvement of using distributed solutions based on multi-CPU and multi-GPU. The performance of both approaches was analysed and it has been demonstrated that the addition of shared memory schemes to CPU computing improves substantially the performance of vector instructions enlarging the simulation sizes that use efficiently the cache memory of CPUs. In this case GPU computing is slightly twice times faster than the fine tuned CPU version in both cases one and two nodes. However, for massively computations explicit vector instructions do not worth it since the memory bandwidth is the limiting factor and the performance tends to be the same than the sequential version with auto-vectorisation and also shared memory approach. In this scenario GPU computing is the best option since it provides a homogeneous behaviour. More specifically, the speedup of GPU computing achieves an upper limit of 12 for both one and two GPUs, whereas the performance reaches peak values of 80 GFlops and 146 GFlops for the performance for one GPU and two GPUs respectively. Finally, the method is applied to an earth crust profile in order to demonstrate the potential of our approach and the necessity of applying acceleration strategies in these type of applications.

The effectiveness of simulated robots for supporting the learning of introductory programming: a multi-case case study

NASA Astrophysics Data System (ADS)

Major, Louis; Kyriacou, Theocharis; Brereton, Pearl

2014-07-01

This work investigates the effectiveness of simulated robots as tools to support the learning of programming. After the completion of a systematic review and exploratory research, a multi-case case study was undertaken. A simulator, named Kebot, was developed and used to run four 10-hour programming workshops. Twenty-three student participants (aged 16-18) in addition to 23 pre-service, and 3 in-service, teachers took part. The effectiveness of this intervention was determined by considering opinions, attitudes, and motivation as well as by analysing students' programming performance. Pre- and post-questionnaires, in- and post-workshop exercises, and interviews were used. Participants enjoyed learning using the simulator and believed the approach to be valuable and engaging. The performance of students indicates that the simulator aids learning as most completed tasks to a satisfactory standard. Evidence suggests robot simulators can offer an effective means of introducing programming. Recommendations to support the development of other simulators are provided.

Using kaizen to improve employee well-being: Results from two organizational intervention studies.

PubMed

von Thiele Schwarz, Ulrica; Nielsen, Karina M; Stenfors-Hayes, Terese; Hasson, Henna

2017-08-01

Participatory intervention approaches that are embedded in existing organizational structures may improve the efficiency and effectiveness of organizational interventions, but concrete tools are lacking. In the present article, we use a realist evaluation approach to explore the role of kaizen, a lean tool for participatory continuous improvement, in improving employee well-being in two cluster-randomized, controlled participatory intervention studies. Case 1 is from the Danish Postal Service, where kaizen boards were used to implement action plans. The results of multi-group structural equation modeling showed that kaizen served as a mechanism that increased the level of awareness of and capacity to manage psychosocial issues, which, in turn, predicted increased job satisfaction and mental health. Case 2 is from a regional hospital in Sweden that integrated occupational health processes with a pre-existing kaizen system. Multi-group structural equation modeling revealed that, in the intervention group, kaizen work predicted better integration of organizational and employee objectives after 12 months, which, in turn, predicted increased job satisfaction and decreased discomfort at 24 months. The findings suggest that participatory and structured problem-solving approaches that are familiar and visual to employees can facilitate organizational interventions.

Using kaizen to improve employee well-being: Results from two organizational intervention studies

PubMed Central

von Thiele Schwarz, Ulrica; Nielsen, Karina M; Stenfors-Hayes, Terese; Hasson, Henna

2016-01-01

Participatory intervention approaches that are embedded in existing organizational structures may improve the efficiency and effectiveness of organizational interventions, but concrete tools are lacking. In the present article, we use a realist evaluation approach to explore the role of kaizen, a lean tool for participatory continuous improvement, in improving employee well-being in two cluster-randomized, controlled participatory intervention studies. Case 1 is from the Danish Postal Service, where kaizen boards were used to implement action plans. The results of multi-group structural equation modeling showed that kaizen served as a mechanism that increased the level of awareness of and capacity to manage psychosocial issues, which, in turn, predicted increased job satisfaction and mental health. Case 2 is from a regional hospital in Sweden that integrated occupational health processes with a pre-existing kaizen system. Multi-group structural equation modeling revealed that, in the intervention group, kaizen work predicted better integration of organizational and employee objectives after 12 months, which, in turn, predicted increased job satisfaction and decreased discomfort at 24 months. The findings suggest that participatory and structured problem-solving approaches that are familiar and visual to employees can facilitate organizational interventions. PMID:28736455

Strategic Planning in the Business Enterprise of Christian Colleges and Universities: A Multi-Case Study Approach

ERIC Educational Resources Information Center

Fletcher, Wayne Lewis

2013-01-01

Many tuition-driven private colleges and universities struggled for economic survival in the first decade of this millennium. The current study views higher education from a two-good framework that posits that every college and university provides teaching and service for the societal good while generating revenue from traditional business-like…

Assessing the impacts induced by global climate change through a multi-risk approach: lessons learned from the North Adriatic coast (Italy)

NASA Astrophysics Data System (ADS)

Gallina, Valentina; Torressan, Silvia; Zabeo, Alex; Critto, Andrea; Glade, Thomas; Marcomini, Antonio

2015-04-01

Climate change is expected to pose a wide range of impacts on natural and human systems worldwide, increasing risks from long-term climate trends and disasters triggered by weather extremes. Accordingly, in the future, one region could be potentially affected by interactions, synergies and trade-offs of multiple hazards and impacts. A multi-risk risk approach is needed to effectively address multiple threats posed by climate change across regions and targets supporting decision-makers toward a new paradigm of multi-hazard and risk management. Relevant initiatives have been already developed for the assessment of multiple hazards and risks affecting the same area in a defined timeframe by means of quantitative and semi-quantitative approaches. Most of them are addressing the relations of different natural hazards, however, the effect of future climate change is usually not considered. In order to fill this gap, an advanced multi-risk methodology was developed at the Euro-Mediterranean Centre on Climate Change (CMCC) for estimating cumulative impacts related to climate change at the regional (i.e. sub-national) scale. This methodology was implemented into an assessment tool which allows to scan and classify quickly natural systems and human assets at risk resulting from different interacting hazards. A multi-hazard index is proposed to evaluate the relationships of different climate-related hazards (e.g. sea-level rise, coastal erosion, storm surge) occurring in the same spatial and temporal area, by means of an influence matrix and the disjoint probability function. Future hazard scenarios provided by regional climate models are used as input for this step in order to consider possible effects of future climate change scenarios. Then, the multi-vulnerability of different exposed receptors (e.g. natural systems, beaches, agricultural and urban areas) is estimated through a variety of vulnerability indicators (e.g. vegetation cover, sediment budget, % of urbanization), tailored case by case to different sets of natural hazards and elements at risk. Finally, the multi-risk assessment integrates the multi-hazard with the multi-vulnerability index of exposed receptors, providing a relative ranking of areas and targets potentially affected by multiple risks in the considered region. The methodology was applied to the North Adriatic coast (Italy) producing a range of GIS-based multi-hazard, exposure, multi-vulnerability and multi-risk maps that can be used by policy-makers to define risk management and adaptation strategies. Results show that areas affected by higher multi-hazard scores are located close to the coastline where all the investigated hazards are present. Multi-vulnerability assumes relatively high scores in the whole case study, showing that beaches, wetlands, protected areas and river mouths are the more sensible targets. The final estimate of multi-risk for coastal municipalities provides useful information for local public authorities to set future priorities for adaptation and define future plans for shoreline and coastal management in view of climate change.

Large Margin Multi-Modal Multi-Task Feature Extraction for Image Classification.

PubMed

Yong Luo; Yonggang Wen; Dacheng Tao; Jie Gui; Chao Xu

2016-01-01

The features used in many image analysis-based applications are frequently of very high dimension. Feature extraction offers several advantages in high-dimensional cases, and many recent studies have used multi-task feature extraction approaches, which often outperform single-task feature extraction approaches. However, most of these methods are limited in that they only consider data represented by a single type of feature, even though features usually represent images from multiple modalities. We, therefore, propose a novel large margin multi-modal multi-task feature extraction (LM3FE) framework for handling multi-modal features for image classification. In particular, LM3FE simultaneously learns the feature extraction matrix for each modality and the modality combination coefficients. In this way, LM3FE not only handles correlated and noisy features, but also utilizes the complementarity of different modalities to further help reduce feature redundancy in each modality. The large margin principle employed also helps to extract strongly predictive features, so that they are more suitable for prediction (e.g., classification). An alternating algorithm is developed for problem optimization, and each subproblem can be efficiently solved. Experiments on two challenging real-world image data sets demonstrate the effectiveness and superiority of the proposed method.

Advantages of Task-Specific Multi-Objective Optimisation in Evolutionary Robotics

PubMed Central

Trianni, Vito; López-Ibáñez, Manuel

2015-01-01

The application of multi-objective optimisation to evolutionary robotics is receiving increasing attention. A survey of the literature reveals the different possibilities it offers to improve the automatic design of efficient and adaptive robotic systems, and points to the successful demonstrations available for both task-specific and task-agnostic approaches (i.e., with or without reference to the specific design problem to be tackled). However, the advantages of multi-objective approaches over single-objective ones have not been clearly spelled out and experimentally demonstrated. This paper fills this gap for task-specific approaches: starting from well-known results in multi-objective optimisation, we discuss how to tackle commonly recognised problems in evolutionary robotics. In particular, we show that multi-objective optimisation (i) allows evolving a more varied set of behaviours by exploring multiple trade-offs of the objectives to optimise, (ii) supports the evolution of the desired behaviour through the introduction of objectives as proxies, (iii) avoids the premature convergence to local optima possibly introduced by multi-component fitness functions, and (iv) solves the bootstrap problem exploiting ancillary objectives to guide evolution in the early phases. We present an experimental demonstration of these benefits in three different case studies: maze navigation in a single robot domain, flocking in a swarm robotics context, and a strictly collaborative task in collective robotics. PMID:26295151

Multi-Robot Search for a Moving Target: Integrating World Modeling, Task Assignment and Context

DTIC Science & Technology

2016-12-01

Case Study Our approach to coordination was initially motivated and developed in RoboCup soccer games. In fact, it has been first deployed on a team of...features a rather accurate model of the behavior and capabilities of the humanoid robot in the field. In the soccer case study , our goal is to...on experiments carried out with a team of humanoid robots in a soccer scenario and a team of mobile bases in an office environment. I. INTRODUCTION

Consensus oriented fuzzified decision support for oil spill contingency management.

PubMed

Liu, Xin; Wirtz, Kai W

2006-06-30

Studies on multi-group multi-criteria decision-making problems for oil spill contingency management are in their infancy. This paper presents a second-order fuzzy comprehensive evaluation (FCE) model to resolve decision-making problems in the area of contingency management after environmental disasters such as oil spills. To assess the performance of different oil combat strategies, second-order FCE allows for the utilization of lexical information, the consideration of ecological and socio-economic criteria and the involvement of a variety of stakeholders. On the other hand, the new approach can be validated by using internal and external checks, which refer to sensitivity tests regarding its internal setups and comparisons with other methods, respectively. Through a case study, the Pallas oil spill in the German Bight in 1998, it is demonstrated that this approach can help decision makers who search for an optimal strategy in multi-thread contingency problems and has a wider application potential in the field of integrated coastal zone management.

Integrating Climate Projections into Multi-Level City Planning: A Texas Case Study

NASA Astrophysics Data System (ADS)

Hayhoe, K.; Gelca, R.; Baumer, Z.; Gold, G.

2016-12-01

Climate change impacts on energy and water are a serious concern for many cities across the United States. Regional projections from the National Assessment process, or state-specific efforts as in California and Delaware, are typically used to quantify impacts at the regional scale. However, these are often insufficient to provide information at the scale of decision-making for an individual city. Here, we describe a multi-level approach to developing and integrating usable climate information into planning, using a case study from the City of Austin in Texas, a state where few official climate resources are available. Spearheaded by the Office of Sustainability in collaboration with Austin Water, the first step was to characterize observed trends and future projections of how global climate change might affect Austin's current climate. The City then assembled a team of city experts, consulting engineers, and climate scientists to develop a methodology to assess impacts on regional hydrology as part of its Integrated Water Resource Plan, Austin's 100-year water supply and demand planning effort, an effort which included calculating a range of climate indicators and developing and evaluating a new approach to generating climate inputs - including daily streamflow and evaporation - for existing water availability models. This approach, which brings together a range of public, private, and academic experts to support a stakeholder-initiated planning effort, provides concrete insights into the critical importance of multi-level, long-term engagement for development and application of actionable climate science at the local to regional scale.

Applying the methodology of Design of Experiments to stability studies: a Partial Least Squares approach for evaluation of drug stability.

PubMed

Jordan, Nika; Zakrajšek, Jure; Bohanec, Simona; Roškar, Robert; Grabnar, Iztok

2018-05-01

The aim of the present research is to show that the methodology of Design of Experiments can be applied to stability data evaluation, as they can be seen as multi-factor and multi-level experimental designs. Linear regression analysis is usually an approach for analyzing stability data, but multivariate statistical methods could also be used to assess drug stability during the development phase. Data from a stability study for a pharmaceutical product with hydrochlorothiazide (HCTZ) as an unstable drug substance was used as a case example in this paper. The design space of the stability study was modeled using Umetrics MODDE 10.1 software. We showed that a Partial Least Squares model could be used for a multi-dimensional presentation of all data generated in a stability study and for determination of the relationship among factors that influence drug stability. It might also be used for stability predictions and potentially for the optimization of the extent of stability testing needed to determine shelf life and storage conditions, which would be time and cost-effective for the pharmaceutical industry.

An integrative multi-criteria decision making techniques for supplier evaluation problem with its application

NASA Astrophysics Data System (ADS)

Fatrias, D.; Kamil, I.; Meilani, D.

2018-03-01

Coordinating business operation with suppliers becomes increasingly important to survive and prosper under the dynamic business environment. A good partnership with suppliers not only increase efficiency, but also strengthen corporate competitiveness. Associated with such concern, this study aims to develop a practical approach of multi-criteria supplier evaluation using combined methods of Taguchi loss function (TLF), best-worst method (BWM) and VIse Kriterijumska Optimizacija kompromisno Resenje (VIKOR). A new framework of integrative approach adopting these methods is our main contribution for supplier evaluation in literature. In this integrated approach, a compromised supplier ranking list based on the loss score of suppliers is obtained using efficient steps of a pairwise comparison based decision making process. Implemetation to the case problem with real data from crumb rubber industry shows the usefulness of the proposed approach. Finally, a suitable managerial implication is presented.

A waterborne outbreak of campylobacteriosis in the South Island of New Zealand due to a failure to implement a multi-barrier approach.

PubMed

Bartholomew, Nadia; Brunton, Cheryl; Mitchell, Peter; Williamson, Judy; Gilpin, Brent

2014-09-01

Outbreaks of waterborne gastroenteritis continue to occur in developed countries. Darfield, a rural town in the South Island of New Zealand experienced an outbreak of campylobacteriosis following a transgression of Escherichia coli on 16 August 2012. A descriptive outbreak investigation was performed. As a result, 29 cases had a laboratory-confirmed diagnosis of campylobacteriosis and 138 were identified as probable cases. Heavy rains, contamination of water with animal effluent from nearby paddocks and failures in the treatment of drinking water led to pathogens being distributed through the town's water supply. A multi-barrier approach is advocated to ensure the quality of water and many countries have legislation or programmes to address this. Although legislation for water safety plans based on a multi-barrier approach is in place in New Zealand, at the time of the outbreak it was not a requirement for the Darfield water supply. In addition, despite the awareness of the importance of a multi-barrier approach, competing interests, including those from the agricultural industry and financial restraints on water suppliers, can prevent it from being implemented. Governments need to be more willing to enforce legislation and standards to protect the public from waterborne disease.

Emerging medical informatics with case-based reasoning for aiding clinical decision in multi-agent system.

PubMed

Shen, Ying; Colloc, Joël; Jacquet-Andrieu, Armelle; Lei, Kai

2015-08-01

This research aims to depict the methodological steps and tools about the combined operation of case-based reasoning (CBR) and multi-agent system (MAS) to expose the ontological application in the field of clinical decision support. The multi-agent architecture works for the consideration of the whole cycle of clinical decision-making adaptable to many medical aspects such as the diagnosis, prognosis, treatment, therapeutic monitoring of gastric cancer. In the multi-agent architecture, the ontological agent type employs the domain knowledge to ease the extraction of similar clinical cases and provide treatment suggestions to patients and physicians. Ontological agent is used for the extension of domain hierarchy and the interpretation of input requests. Case-based reasoning memorizes and restores experience data for solving similar problems, with the help of matching approach and defined interfaces of ontologies. A typical case is developed to illustrate the implementation of the knowledge acquisition and restitution of medical experts. Copyright © 2015 Elsevier Inc. All rights reserved.

Multi-disciplinary decision making in general practice.

PubMed

Kirby, Ann; Murphy, Aileen; Bradley, Colin

2018-04-09

Purpose Internationally, healthcare systems are moving towards delivering care in an integrated manner which advocates a multi-disciplinary approach to decision making. Such an approach is formally encouraged in the management of Atrial Fibrillation patients through the European Society of Cardiology guidelines. Since the emergence of new oral anticoagulants switching between oral anticoagulants (OACs) has become prevalent. This case study considers the role of multi-disciplinary decision making, given the complex nature of the agents. The purpose of this paper is to explore Irish General Practitioners' (GPs) experience of switching between all OACs for Arial Fibrillation (AF) patients; prevalence of multi-disciplinary decision making in OAC switching decisions and seeks to determine the GP characteristics that appear to influence the likelihood of multi-disciplinary decision making. Design/methodology/approach A probit model is used to determine the factors influencing multi-disciplinary decision making and a multinomial logit is used to examine the factors influencing who is involved in the multi-disciplinary decisions. Findings Results reveal that while some multi-disciplinary decision-making is occurring (64 per cent), it is not standard practice despite international guidelines on integrated care. Moreover, there is a lack of patient participation in the decision-making process. Female GPs and GPs who have initiated prescriptions for OACs are more likely to engage in multi-disciplinary decision-making surrounding switching OACs amongst AF patients. GPs with training practices were less likely to engage with cardiac consultants and those in urban areas were more likely to engage with other (non-cardiac) consultants. Originality/value For optimal decision making under uncertainty multi-disciplinary decision-making is needed to make a more informed judgement and to improve treatment decisions and reduce the opportunity cost of making the wrong decision.

Automatic seizure detection based on the combination of newborn multi-channel EEG and HRV information

NASA Astrophysics Data System (ADS)

Mesbah, Mostefa; Balakrishnan, Malarvili; Colditz, Paul B.; Boashash, Boualem

2012-12-01

This article proposes a new method for newborn seizure detection that uses information extracted from both multi-channel electroencephalogram (EEG) and a single channel electrocardiogram (ECG). The aim of the study is to assess whether additional information extracted from ECG can improve the performance of seizure detectors based solely on EEG. Two different approaches were used to combine this extracted information. The first approach, known as feature fusion, involves combining features extracted from EEG and heart rate variability (HRV) into a single feature vector prior to feeding it to a classifier. The second approach, called classifier or decision fusion, is achieved by combining the independent decisions of the EEG and the HRV-based classifiers. Tested on recordings obtained from eight newborns with identified EEG seizures, the proposed neonatal seizure detection algorithms achieved 95.20% sensitivity and 88.60% specificity for the feature fusion case and 95.20% sensitivity and 94.30% specificity for the classifier fusion case. These results are considerably better than those involving classifiers using EEG only (80.90%, 86.50%) or HRV only (85.70%, 84.60%).

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

NASA Astrophysics Data System (ADS)

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.

Cross-scale interactions: Quantifying multi-scaled cause–effect relationships in macrosystems

USGS Publications Warehouse

Soranno, Patricia A.; Cheruvelil, Kendra S.; Bissell, Edward G.; Bremigan, Mary T.; Downing, John A.; Fergus, Carol E.; Filstrup, Christopher T.; Henry, Emily N.; Lottig, Noah R.; Stanley, Emily H.; Stow, Craig A.; Tan, Pang-Ning; Wagner, Tyler; Webster, Katherine E.

2014-01-01

Ecologists are increasingly discovering that ecological processes are made up of components that are multi-scaled in space and time. Some of the most complex of these processes are cross-scale interactions (CSIs), which occur when components interact across scales. When undetected, such interactions may cause errors in extrapolation from one region to another. CSIs, particularly those that include a regional scaled component, have not been systematically investigated or even reported because of the challenges of acquiring data at sufficiently broad spatial extents. We present an approach for quantifying CSIs and apply it to a case study investigating one such interaction, between local and regional scaled land-use drivers of lake phosphorus. Ultimately, our approach for investigating CSIs can serve as a basis for efforts to understand a wide variety of multi-scaled problems such as climate change, land-use/land-cover change, and invasive species.

Up-scaling of multi-variable flood loss models from objects to land use units at the meso-scale

NASA Astrophysics Data System (ADS)

Kreibich, Heidi; Schröter, Kai; Merz, Bruno

2016-05-01

Flood risk management increasingly relies on risk analyses, including loss modelling. Most of the flood loss models usually applied in standard practice have in common that complex damaging processes are described by simple approaches like stage-damage functions. Novel multi-variable models significantly improve loss estimation on the micro-scale and may also be advantageous for large-scale applications. However, more input parameters also reveal additional uncertainty, even more in upscaling procedures for meso-scale applications, where the parameters need to be estimated on a regional area-wide basis. To gain more knowledge about challenges associated with the up-scaling of multi-variable flood loss models the following approach is applied: Single- and multi-variable micro-scale flood loss models are up-scaled and applied on the meso-scale, namely on basis of ATKIS land-use units. Application and validation is undertaken in 19 municipalities, which were affected during the 2002 flood by the River Mulde in Saxony, Germany by comparison to official loss data provided by the Saxon Relief Bank (SAB).In the meso-scale case study based model validation, most multi-variable models show smaller errors than the uni-variable stage-damage functions. The results show the suitability of the up-scaling approach, and, in accordance with micro-scale validation studies, that multi-variable models are an improvement in flood loss modelling also on the meso-scale. However, uncertainties remain high, stressing the importance of uncertainty quantification. Thus, the development of probabilistic loss models, like BT-FLEMO used in this study, which inherently provide uncertainty information are the way forward.

Identification of Management Information System (MIS) Strategies Barriers in Higher Education Institutions through Multi-Criteria Decision Making (MCDM) Approach: Case Study of Ferdowsi University of Mashhad

ERIC Educational Resources Information Center

Hosseini, Mirza Hasan; Karimzadegan, Davood; Sazvar, Azam

2012-01-01

Each organization or company, regardless to its restrictions, purposes, and type of the activity, in order to fulfill and manage the duties is in need of various data and pieces of information. The aforesaid cases are generated by managers and employees and used by all the staffs. The manifest issue of current days is that organizations and…

Invasive placental disease: the impact of a multi-disciplinary team approach to management.

PubMed

Smulian, John C; Pascual, Ana-Liza; Hesham, Helai; Qureshey, Emma; Bijoy Thomas, M; Depuy, Amy M; Flicker, Amanda B; Scorza, William E

2017-06-01

To determine the impact of a structured multi-disciplinary management strategy on clinical outcomes in women with invasive placental disease (IPD). This was a retrospective cohort study of consecutive women having peripartum hysterectomies with IPD over seven years. For the most recent three years, a structured multidisciplinary team (MDT) reviewed each suspected case, created a management plan, and implemented that plan. Outcomes were compared between cases delivered prior to and after the MDT process was started. There were 47 pregnancies with IPD, of which 31 (66.0%) were suspected antenatally and 40 (85.1%) had a prior uterine surgery. An MDT approach was performed in 19 (40.4%) cases. In the MDT group, there were longer operative times (260 min versus 181 min, p = 0.0001), less blood loss (1200 mL versus 2500 mL, p = 0.009), less administration of blood products (47.4% versus 85.7%, p = 0.005), and higher intraoperative lowest mean arterial pressures (MAPs) (57 mmHg versus 48 mmHg, p = 0.002, when compared to the No-MDT (n = 28) approach. No differences were found for other outcomes. Clinically meaningful improvements of less blood loss, fewer transfusions, and higher intraoperative MAPs suggest that MDT cases were more stable intraoperatively, which over a larger number of patients, should translate into improved outcomes.

Conducting Molecular Epidemiological Research in the Age of HIPAA: A Multi-Institutional Case-Control Study of Breast Cancer in African-American and European-American Women

PubMed Central

Ambrosone, Christine B.; Ciupak, Gregory L.; Bandera, Elisa V.; Jandorf, Lina; Bovbjerg, Dana H.; Zirpoli, Gary; Pawlish, Karen; Godbold, James; Furberg, Helena; Fatone, Anne; Valdimarsdottir, Heiddis; Yao, Song; Li, Yulin; Hwang, Helena; Davis, Warren; Roberts, Michelle; Sucheston, Lara; Demissie, Kitaw; Amend, Kandace L.; Tartter, Paul; Reilly, James; Pace, Benjamin W.; Rohan, Thomas; Sparano, Joseph; Raptis, George; Castaldi, Maria; Estabrook, Alison; Feldman, Sheldon; Weltz, Christina; Kemeny, Margaret

2009-01-01

Breast cancer in African-American (AA) women occurs at an earlier age than in European-American (EA) women and is more likely to have aggressive features associated with poorer prognosis, such as high-grade and negative estrogen receptor (ER) status. The mechanisms underlying these differences are unknown. To address this, we conducted a case-control study to evaluate risk factors for high-grade ER- disease in both AA and EA women. With the onset of the Health Insurance Portability and Accountability Act of 1996, creative measures were needed to adapt case ascertainment and contact procedures to this new environment of patient privacy. In this paper, we report on our approach to establishing a multicenter study of breast cancer in New York and New Jersey, provide preliminary distributions of demographic and pathologic characteristics among case and control participants by race, and contrast participation rates by approaches to case ascertainment, with discussion of strengths and weaknesses. PMID:19865486

Advances in studies of disease-navigating webs: Sarcoptes scabiei as a case study

PubMed Central

2014-01-01

The discipline of epidemiology is the study of the patterns, causes and effects of health and disease conditions in defined anima populations. It is the key to evidence-based medicine, which is one of the cornerstones of public health. One of the important facets of epidemiology is disease-navigating webs (disease-NW) through which zoonotic and multi-host parasites in general move from one host to another. Epidemiology in this context includes (i) classical epidemiological approaches based on the statistical analysis of disease prevalence and distribution and, more recently, (ii) genetic approaches with approximations of disease-agent population genetics. Both approaches, classical epidemiology and population genetics, are useful for studying disease-NW. However, both have strengths and weaknesses when applied separately, which, unfortunately, is too often current practice. In this paper, we use Sarcoptes scabiei mite epidemiology as a case study to show how important an integrated approach can be in understanding disease-NW and subsequent disease control. PMID:24406101

Object-based classification of global undersea topography and geomorphological features from the SRTM30_PLUS data

NASA Astrophysics Data System (ADS)

Dekavalla, Maria; Argialas, Demetre

2017-07-01

The analysis of undersea topography and geomorphological features provides necessary information to related disciplines and many applications. The development of an automated knowledge-based classification approach of undersea topography and geomorphological features is challenging due to their multi-scale nature. The aim of the study is to develop and evaluate an automated knowledge-based OBIA approach to: i) decompose the global undersea topography to multi-scale regions of distinct morphometric properties, and ii) assign the derived regions to characteristic geomorphological features. First, the global undersea topography was decomposed through the SRTM30_PLUS bathymetry data to the so-called morphometric objects of discrete morphometric properties and spatial scales defined by data-driven methods (local variance graphs and nested means) and multi-scale analysis. The derived morphometric objects were combined with additional relative topographic position information computed with a self-adaptive pattern recognition method (geomorphons), and auxiliary data and were assigned to characteristic undersea geomorphological feature classes through a knowledge base, developed from standard definitions. The decomposition of the SRTM30_PLUS data to morphometric objects was considered successful for the requirements of maximizing intra-object and inter-object heterogeneity, based on the near zero values of the Moran's I and the low values of the weighted variance index. The knowledge-based classification approach was tested for its transferability in six case studies of various tectonic settings and achieved the efficient extraction of 11 undersea geomorphological feature classes. The classification results for the six case studies were compared with the digital global seafloor geomorphic features map (GSFM). The 11 undersea feature classes and their producer's accuracies in respect to the GSFM relevant areas were Basin (95%), Continental Shelf (94.9%), Trough (88.4%), Plateau (78.9%), Continental Slope (76.4%), Trench (71.2%), Abyssal Hill (62.9%), Abyssal Plain (62.4%), Ridge (49.8%), Seamount (48.8%) and Continental Rise (25.4%). The knowledge-based OBIA classification approach was considered transferable since the percentages of spatial and thematic agreement between the most of the classified undersea feature classes and the GSFM exhibited low deviations across the six case studies.

Risk Governance of Multiple Natural Hazards: Centralized versus Decentralized Approach in Europe

NASA Astrophysics Data System (ADS)

Komendantova, Nadejda; Scolobig, Anna; Vinchon, Charlotte

2014-05-01

The multi-risk approach is a relatively new field and its definition includes the need to consider multiple hazards and vulnerabilities in their interdependency (Selva, 2013) and the current multi-hazards disasters, such as the 2011 Tohoku earthquake, tsunami and nuclear catastrophe, showed the need for a multi-risk approach in hazard mitigation and management. Our knowledge about multi-risk assessment, including studies from different scientific disciplines and developed assessment tools, is constantly growing (White et al., 2001). However, the link between scientific knowledge, its implementation and the results in terms of improved governance and decision-making have gained significantly less attention (IRGC, 2005; Kappes et al., 2012), even though the interest to risk governance, in general, has increased significantly during the last years (Verweiy and Thompson, 2006). Therefore, the key research question is how risk assessment is implemented and what is the potential for the implementation of a multi-risk approach in different governance systems across Europe. More precisely, how do the characteristics of risk governance, such as the degree of centralization versus decentralization, influence the implementation of a multi-risk approach. The methodology of this research includes comparative case study analysis of top-down and bottom-up interactions in governance in the city of Naples, (Italy), where the institutional landscape is marked by significant autonomy of Italian regions in decision-making processes for assessing the majority of natural risks, excluding volcanic, and in Guadeloupe, French West Indies, an overseas department of France, where the decision-making process is marked by greater centralization in decision making associated with a well established state governance within regions, delegated to the prefect and decentralised services of central ministries. The research design included documentary analysis and extensive empirical work involving policy makers, private sector actors and practitioners in risk and emergency management. This work was informed by 36 semi-structured interviews, three workshops with over seventy participants from eleven different countries, feedback from questionnaires and focus group discussions (Scolobig et al., 2013). The results show that both governance systems have their own strengths and weaknesses (Komendantova et al., 2013). Elements of the centralized multi-risk governance system could lead to improvements in interagency communication and the creation of an inter-agency environment, where the different departments at the national level can exchange information, identify the communities that are most exposed to multiple risks and set priorities, while providing consistent information about and responses to multi-risk to the relevant stakeholders at the local level. A decentralised multi-risk governance system by contrast can instead favour the creation of local multi-risk commissions to conduct discussions between experts in meteorological, geological and technological risks and practitioners, to elaborate risk and hazard maps, and to develop local capacities which would include educational and training activities. Both governance systems suffer from common deficiencies, the most important being the frequent lack of capacities at the local level, especially financial, but sometimes also technical and institutional ones, as the responsibilities for disaster risk management are often transferred from the national to local levels without sufficient resources for implementation of programs on risk management (UNISDR, 2013). The difficulty in balancing available resources between short-term and medium-term priorities often complicates the issue. Our recommendations are that the implementation of multi-risk approach can be facilitated through knowledge exchange and dialogue between different disciplinary communities, such as geological and meteorological, and between the natural and social sciences. The implementation of a multi-risk approach can be strengthened through the creation of multi-risk platforms and multi-risk commissions, which can liaise between risk management experts and local communities and to unify numerous actions on natural hazard management. However, the multi-risk approach cannot be a subsidiary to a single risk approach, and both have to be pursued. References: IRGC. (2011). Concept note: Improving the management of emerging risks: Risks from new technologies, system interactions, and unforeseen or changing circumstances. International Risk Governance Council (IRGC), Geneva. Kappes, M. S., Keiler, M., Elverfeldt, von K., & Glade, T, (2012). Challenges of analyzing multi-hazard risk: A review. Natural Hazards, 64(2), 1925-1958. doi: 10.1007/s11069-012-0294-2. Komendantova N, Scolobig A, Vinchon C (2013). Multi-risk approach in centralized and decentralized risk governance systems: Case studies of Naples, Italy and Guadeloupe, France. International Relations and Diplomacy, 1(3):224-239 (December 2013) Scolobig, A., Vichon, C., Komendantova, N., Bengoubou-Valerius, M., & Patt, A. (2013). Social and institutional barriers to effective multi-hazard and multi-risk decision-making governance. D6.3 MATRIX project. Selva, J. (2013). Long-term multi-risk assessment: statistical treatment of interaction among risks. Natural Hazards, 67(2),701-722. UNISDR. (2013). Implementing the HYOGO framework for action in Europe: Regional synthesis report 2011-2013. Verweij, M., & Thompson, M. (Eds.). (2006). Clumsy solutions for a complex world: Governance, politics, and plural perceptions. New York: Palgrave Macmillan. White, G., Kates, R., & Burton, I. (2001). Knowing better and losing even more: the use of knowledge in hazards management. Environmental Hazards, 3, 81-92.

Optimization as a Tool for Consistency Maintenance in Multi-Resolution Simulation

NASA Technical Reports Server (NTRS)

Drewry, Darren T; Reynolds, Jr , Paul F; Emanuel, William R

2006-01-01

The need for new approaches to the consistent simulation of related phenomena at multiple levels of resolution is great. While many fields of application would benefit from a complete and approachable solution to this problem, such solutions have proven extremely difficult. We present a multi-resolution simulation methodology that uses numerical optimization as a tool for maintaining external consistency between models of the same phenomena operating at different levels of temporal and/or spatial resolution. Our approach follows from previous work in the disparate fields of inverse modeling and spacetime constraint-based animation. As a case study, our methodology is applied to two environmental models of forest canopy processes that make overlapping predictions under unique sets of operating assumptions, and which execute at different temporal resolutions. Experimental results are presented and future directions are addressed.

A Multi-Dimensional Approach to Gradient Change in Phonological Acquisition: A Case Study of Disordered Speech Development

ERIC Educational Resources Information Center

Glaspey, Amy M.; MacLeod, Andrea A. N.

2010-01-01

The purpose of the current study is to document phonological change from a multidimensional perspective for a 3-year-old boy with phonological disorder by comparing three measures: (1) accuracy of consonant productions, (2) dynamic assessment, and (3) acoustic analysis. The methods included collecting a sample of the targets /s, [image omitted],…

Unpacking the "Value Added" Impact of Continuing Professional Education: A Multi-Method Case Study Approach.

ERIC Educational Resources Information Center

Smith, Jo; Topping, Annie

2001-01-01

A study of 14 nurses who completed a children's neuroscience course found evidence of improved knowledge and increased ability to care for neurology patients. Although the direct impact of continuing education on patient care is difficult to assess, participants' assessment of their learning and its potential to affect patient care is a valid…

Multi-fluid Dynamics for Supersonic Jet-and-Crossflows and Liquid Plug Rupture

NASA Astrophysics Data System (ADS)

Hassan, Ezeldin A.

Multi-fluid dynamics simulations require appropriate numerical treatments based on the main flow characteristics, such as flow speed, turbulence, thermodynamic state, and time and length scales. In this thesis, two distinct problems are investigated: supersonic jet and crossflow interactions; and liquid plug propagation and rupture in an airway. Gaseous non-reactive ethylene jet and air crossflow simulation represents essential physics for fuel injection in SCRAMJET engines. The regime is highly unsteady, involving shocks, turbulent mixing, and large-scale vortical structures. An eddy-viscosity-based multi-scale turbulence model is proposed to resolve turbulent structures consistent with grid resolution and turbulence length scales. Predictions of the time-averaged fuel concentration from the multi-scale model is improved over Reynolds-averaged Navier-Stokes models originally derived from stationary flow. The response to the multi-scale model alone is, however, limited, in cases where the vortical structures are small and scattered thus requiring prohibitively expensive grids in order to resolve the flow field accurately. Statistical information related to turbulent fluctuations is utilized to estimate an effective turbulent Schmidt number, which is shown to be highly varying in space. Accordingly, an adaptive turbulent Schmidt number approach is proposed, by allowing the resolved field to adaptively influence the value of turbulent Schmidt number in the multi-scale turbulence model. The proposed model estimates a time-averaged turbulent Schmidt number adapted to the computed flowfield, instead of the constant value common to the eddy-viscosity-based Navier-Stokes models. This approach is assessed using a grid-refinement study for the normal injection case, and tested with 30 degree injection, showing improved results over the constant turbulent Schmidt model both in mean and variance of fuel concentration predictions. For the incompressible liquid plug propagation and rupture study, numerical simulations are conducted using an Eulerian-Lagrangian approach with a continuous-interface method. A reconstruction scheme is developed to allow topological changes during plug rupture by altering the connectivity information of the interface mesh. Rupture time is shown to be delayed as the initial precursor film thickness increases. During the plug rupture process, a sudden increase of mechanical stresses on the tube wall is recorded, which can cause tissue damage.

Shifting Preservice Teachers' Beliefs and Understandings to Support Pedagogical Change in Mathematics

ERIC Educational Resources Information Center

Letwinsky, Karim Medico; Cavender, Monica

2018-01-01

Many preservice teacher (PST) programs throughout the world are preparing students to implement the Core Standards, which require deeper conceptual understandings of mathematics and an informed approach for teaching. In this qualitative multi-case study, researchers explored the teaching methods for two university instructors and changes in PSTs…

Agroforestry adoption in the Calakmul biosphere reserve, Campeche, Mexico

Treesearch

D. Evan Mercer; Jeremy Haggar; Ann Snook; Mauricio Sosa

2005-01-01

Since farmers engage in a complex, dynamic process of learning-by-doing, evaluating economic incentives, and assessing risks in deciding whether to adopt agroforestry systems, a multi-pronged research approach is required for a complete analysis of adoption potential and to develop effective technological and institutional interventions. A case study is presented for...

A Multi-Modal Approach to Intervention for One Adolescent's Frontal Lisp

ERIC Educational Resources Information Center

Lipetz, Heidi Massel; Bernhardt, B. May

2013-01-01

An adolescent with a persistent frontal lisp participated in a two-part 11-session intervention case study. The first phase used ultrasound imagery and acoustic, phonetic and voice education to provide information about articulatory setting (AS) and general awareness of the speech production process. The second phase used traditional articulation…

Followership at the FDIC: A Case Study

ERIC Educational Resources Information Center

Read, J. Basil, III

2014-01-01

The Federal Deposit Insurance Corporation (FDIC), an independent agency of the U.S. Federal government, has been instructing employees in the tenants of followership since 2009. As part of a multi-pronged approach to create a more empowered workforce and enhance trust in leadership, instruction in followership has helped to raise the FDIC from the…

Generalizing DTW to the multi-dimensional case requires an adaptive approach

PubMed Central

Hu, Bing; Jin, Hongxia; Wang, Jun; Keogh, Eamonn

2017-01-01

In recent years Dynamic Time Warping (DTW) has emerged as the distance measure of choice for virtually all time series data mining applications. For example, virtually all applications that process data from wearable devices use DTW as a core sub-routine. This is the result of significant progress in improving DTW’s efficiency, together with multiple empirical studies showing that DTW-based classifiers at least equal (and generally surpass) the accuracy of all their rivals across dozens of datasets. Thus far, most of the research has considered only the one-dimensional case, with practitioners generalizing to the multi-dimensional case in one of two ways, dependent or independent warping. In general, it appears the community believes either that the two ways are equivalent, or that the choice is irrelevant. In this work, we show that this is not the case. The two most commonly used multi-dimensional DTW methods can produce different classifications, and neither one dominates over the other. This seems to suggest that one should learn the best method for a particular application. However, we will show that this is not necessary; a simple, principled rule can be used on a case-by-case basis to predict which of the two methods we should trust at the time of classification. Our method allows us to ensure that classification results are at least as accurate as the better of the two rival methods, and, in many cases, our method is significantly more accurate. We demonstrate our ideas with the most extensive set of multi-dimensional time series classification experiments ever attempted. PMID:29104448

Shot sequencing based on biological equivalent dose considerations for multiple isocenter Gamma Knife radiosurgery.

PubMed

Ma, Lijun; Lee, Letitia; Barani, Igor; Hwang, Andrew; Fogh, Shannon; Nakamura, Jean; McDermott, Michael; Sneed, Penny; Larson, David A; Sahgal, Arjun

2011-11-21

Rapid delivery of multiple shots or isocenters is one of the hallmarks of Gamma Knife radiosurgery. In this study, we investigated whether the temporal order of shots delivered with Gamma Knife Perfexion would significantly influence the biological equivalent dose for complex multi-isocenter treatments. Twenty single-target cases were selected for analysis. For each case, 3D dose matrices of individual shots were extracted and single-fraction equivalent uniform dose (sEUD) values were determined for all possible shot delivery sequences, corresponding to different patterns of temporal dose delivery within the target. We found significant variations in the sEUD values among these sequences exceeding 15% for certain cases. However, the sequences for the actual treatment delivery were found to agree (<3%) and to correlate (R² = 0.98) excellently with the sequences yielding the maximum sEUD values for all studied cases. This result is applicable for both fast and slow growing tumors with α/β values of 2 to 20 according to the linear-quadratic model. In conclusion, despite large potential variations in different shot sequences for multi-isocenter Gamma Knife treatments, current clinical delivery sequences exhibited consistent biological target dosing that approached that maximally achievable for all studied cases.

Autonomous Motion Learning for Intra-Vehicular Activity Space Robot

NASA Astrophysics Data System (ADS)

Watanabe, Yutaka; Yairi, Takehisa; Machida, Kazuo

Space robots will be needed in the future space missions. So far, many types of space robots have been developed, but in particular, Intra-Vehicular Activity (IVA) space robots that support human activities should be developed to reduce human-risks in space. In this paper, we study the motion learning method of an IVA space robot with the multi-link mechanism. The advantage point is that this space robot moves using reaction force of the multi-link mechanism and contact forces from the wall as space walking of an astronaut, not to use a propulsion. The control approach is determined based on a reinforcement learning with the actor-critic algorithm. We demonstrate to clear effectiveness of this approach using a 5-link space robot model by simulation. First, we simulate that a space robot learn the motion control including contact phase in two dimensional case. Next, we simulate that a space robot learn the motion control changing base attitude in three dimensional case.

The multi temporal/multi-model approach to predictive uncertainty assessment in real-time flood forecasting

NASA Astrophysics Data System (ADS)

Barbetta, Silvia; Coccia, Gabriele; Moramarco, Tommaso; Brocca, Luca; Todini, Ezio

2017-08-01

This work extends the multi-temporal approach of the Model Conditional Processor (MCP-MT) to the multi-model case and to the four Truncated Normal Distributions (TNDs) approach, demonstrating the improvement on the single-temporal one. The study is framed in the context of probabilistic Bayesian decision-making that is appropriate to take rational decisions on uncertain future outcomes. As opposed to the direct use of deterministic forecasts, the probabilistic forecast identifies a predictive probability density function that represents a fundamental knowledge on future occurrences. The added value of MCP-MT is the identification of the probability that a critical situation will happen within the forecast lead-time and when, more likely, it will occur. MCP-MT is thoroughly tested for both single-model and multi-model configurations at a gauged site on the Tiber River, central Italy. The stages forecasted by two operative deterministic models, STAFOM-RCM and MISDc, are considered for the study. The dataset used for the analysis consists of hourly data from 34 flood events selected on a time series of six years. MCP-MT improves over the original models' forecasts: the peak overestimation and the rising limb delayed forecast, characterizing MISDc and STAFOM-RCM respectively, are significantly mitigated, with a reduced mean error on peak stage from 45 to 5 cm and an increased coefficient of persistence from 0.53 up to 0.75. The results show that MCP-MT outperforms the single-temporal approach and is potentially useful for supporting decision-making because the exceedance probability of hydrometric thresholds within a forecast horizon and the most probable flooding time can be estimated.

Multi-Agent Technology for Air Space Deconfliction

DTIC Science & Technology

2008-01-01

previously accepted limit of the runway count is also omitted although in the case study used in the reported research the JFK airport is considered...La Guardia, Republic. Fig. 2.3 depicts the approach zone of JFK airport . In general words, the airport airspace topology is divided into two zones: (i...be omitted when necessary or if the customer believes they are too hard. Fig.2.3. Approach zone of JFK airport 11 4. Development of a realistic

[Cochlear implantation in patients with Waardenburg syndrome type II].

PubMed

Wan, Liangcai; Guo, Menghe; Chen, Shuaijun; Liu, Shuangriu; Chen, Hao; Gong, Jian

2010-05-01

To describe the multi-channel cochlear implantation in patients with Waardenburg syndrome including surgeries, pre and postoperative hearing assessments as well as outcomes of speech recognition. Multi-channel cochlear implantation surgeries have been performed in 12 cases with Waardenburg syndrome type II in our department from 2000 to 2008. All the patients received multi-channel cochlear implantation through transmastoid facial recess approach. The postoperative outcomes of 12 cases were compared with 12 cases with no inner ear malformation as a control group. The electrodes were totally inserted into the cochlear successfully, there was no facial paralysis and cerebrospinal fluid leakage occurred after operation. The hearing threshold in this series were similar to that of the normal cochlear implantation. After more than half a year of speech rehabilitation, the abilities of speech discrimination and spoken language of all the patients were improved compared with that of preoperation. Multi-channel cochlear implantation could be performed in the cases with Waardenburg syndrome, preoperative hearing and images assessments should be done.

Extra-skeletal Ewing's sarcoma in adults: presentation of two cases.

PubMed

Lipski, Samuel M; Cermak, Katia; Shumelinsky, Felix; Gil, Thierry; Gebhart, Michael J

2010-12-01

Extraosseous Ewing's sarcoma represents about 5% of the Ewing family of tumours. Two cases in adult patients are presented, emphasizing the complexity of a multi-modality treatment approach of this tumour. Clinical presentation, chemotherapeutical, surgical and radiotherapeutical approaches are discussed. A thorough literature search was done to correlate our therapeutic attitude with current knowledge of this very rare disease.

77 FR 12598 - Notice Correction; A Multi-Center International Hospital-Based Case-Control Study of Lymphoma in...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-03-01

... DEPARTMENT OF HEALTH AND HUMAN SERVICES National Institutes of Health Notice Correction; A Multi-Center International Hospital-Based Case-Control Study of Lymphoma in Asia (AsiaLymph) (NCI) The Federal... project titled, ``A multi-center international hospital-based case-control study of lymphoma in Asia (Asia...

Targeting community-dwelling urinary incontinence sufferers: a multi-disciplinary community based model for conservative continence services.

PubMed

St John, Winsome; Wallis, Marianne; James, Heather; McKenzie, Shona; Guyatt, Sheridan

2004-10-01

This paper presents an argument that there is a need to provide services that target community-dwelling incontinence sufferers, and presents a demonstration case study of a multi-disciplinary, community-based conservative model of service delivery: The Waterworx Model. Rationale for approaches taken, implementation of the model, evaluation and lessons learned are discussed. In this paper community-dwelling sufferers of urinary incontinence are identified as an underserved group, and useful information is provided for those wishing to establish services for them. The Waterworx Model of continence service delivery incorporates three interrelated approaches. Firstly, client access is achieved by using community-based services via clinic and home visits, creating referral pathways and active promotion of services. Secondly, multi-disciplinary client care is provided by targeting a specific client group, multi-disciplinary assessment, promoting client self-management and developing client knowledge and health literacy. Finally, interdisciplinary collaboration and linkages is facilitated by developing multidisciplinary assessment tools, using interdisciplinary referrals, staff development, multi-disciplinary management and providing professional education. Implementation of the model achieved greater client access, improvement in urinary incontinence and client satisfaction. Our experiences suggest that those suffering urinary incontinence and living in the community are an underserved group and that continence services should be community focussed, multi-disciplinary, generalist in nature.

Based on a multi-agent system for multi-scale simulation and application of household's LUCC: a case study for Mengcha village, Mizhi county, Shaanxi province.

PubMed

Chen, Hai; Liang, Xiaoying; Li, Rui

2013-01-01

Multi-Agent Systems (MAS) offer a conceptual approach to include multi-actor decision making into models of land use change. Through the simulation based on the MAS, this paper tries to show the application of MAS in the micro scale LUCC, and reveal the transformation mechanism of difference scale. This paper starts with a description of the context of MAS research. Then, it adopts the Nested Spatial Choice (NSC) method to construct the multi-scale LUCC decision-making model. And a case study for Mengcha village, Mizhi County, Shaanxi Province is reported. Finally, the potentials and drawbacks of the following approach is discussed and concluded. From our design and implementation of the MAS in multi-scale model, a number of observations and conclusions can be drawn on the implementation and future research directions. (1) The use of the LUCC decision-making and multi-scale transformation framework provides, according to us, a more realistic modeling of multi-scale decision making process. (2) By using continuous function, rather than discrete function, to construct the decision-making of the households is more realistic to reflect the effect. (3) In this paper, attempts have been made to give a quantitative analysis to research the household interaction. And it provides the premise and foundation for researching the communication and learning among the households. (4) The scale transformation architecture constructed in this paper helps to accumulate theory and experience for the interaction research between the micro land use decision-making and the macro land use landscape pattern. Our future research work will focus on: (1) how to rational use risk aversion principle, and put the rule on rotation between household parcels into model. (2) Exploring the methods aiming at researching the household decision-making over a long period, it allows us to find the bridge between the long-term LUCC data and the short-term household decision-making. (3) Researching the quantitative method and model, especially the scenario analysis model which may reflect the interaction among different household types.

Multi Sensor Fusion Using Fitness Adaptive Differential Evolution

NASA Astrophysics Data System (ADS)

Giri, Ritwik; Ghosh, Arnob; Chowdhury, Aritra; Das, Swagatam

The rising popularity of multi-source, multi-sensor networks supports real-life applications calls for an efficient and intelligent approach to information fusion. Traditional optimization techniques often fail to meet the demands. The evolutionary approach provides a valuable alternative due to its inherent parallel nature and its ability to deal with difficult problems. We present a new evolutionary approach based on a modified version of Differential Evolution (DE), called Fitness Adaptive Differential Evolution (FiADE). FiADE treats sensors in the network as distributed intelligent agents with various degrees of autonomy. Existing approaches based on intelligent agents cannot completely answer the question of how their agents could coordinate their decisions in a complex environment. The proposed approach is formulated to produce good result for the problems that are high-dimensional, highly nonlinear, and random. The proposed approach gives better result in case of optimal allocation of sensors. The performance of the proposed approach is compared with an evolutionary algorithm coordination generalized particle model (C-GPM).

International Space Station Logistics Approach: Partnership and Dialog for a Successful Future

NASA Technical Reports Server (NTRS)

Banasik, Natalie

2000-01-01

This article seeks to investigate trends and challenges for establishing a successful partnership in a multi-cultural Logistics environment. The U.S. - Russian relationship in the field of space studies is used as the model for this inquiry. Case studies of culture specific responses to a variety of Logistics situations developed during the initial phase of this cooperation are discussed.

Creating an Effective Educational Environment for Adult Learners: A Qualitative, Multi-Case Study of Off-Campus Center Administrator's Use of Invitational Leadership

ERIC Educational Resources Information Center

McKnight, Carolyn P.; Martin, Barbara N.

2015-01-01

This study was designed to examine off-campus centers and their administrators in creating an effective learning environment for adult learners using a new innovative leadership theory, invitational, which is a holistic approach that nurtures the belief everyone is intrinsically motivated and it is the leaders' responsibility to unleash their true…

Coronary CT angiography using 64 detector rows: methods and design of the multi-centre trial CORE-64.

PubMed

Miller, Julie M; Dewey, Marc; Vavere, Andrea L; Rochitte, Carlos E; Niinuma, Hiroyuki; Arbab-Zadeh, Armin; Paul, Narinder; Hoe, John; de Roos, Albert; Yoshioka, Kunihiro; Lemos, Pedro A; Bush, David E; Lardo, Albert C; Texter, John; Brinker, Jeffery; Cox, Christopher; Clouse, Melvin E; Lima, João A C

2009-04-01

Multislice computed tomography (MSCT) for the noninvasive detection of coronary artery stenoses is a promising candidate for widespread clinical application because of its non-invasive nature and high sensitivity and negative predictive value as found in several previous studies using 16 to 64 simultaneous detector rows. A multi-centre study of CT coronary angiography using 16 simultaneous detector rows has shown that 16-slice CT is limited by a high number of nondiagnostic cases and a high false-positive rate. A recent meta-analysis indicated a significant interaction between the size of the study sample and the diagnostic odds ratios suggestive of small study bias, highlighting the importance of evaluating MSCT using 64 simultaneous detector rows in a multi-centre approach with a larger sample size. In this manuscript we detail the objectives and methods of the prospective "CORE-64" trial ("Coronary Evaluation Using Multidetector Spiral Computed Tomography Angiography using 64 Detectors"). This multi-centre trial was unique in that it assessed the diagnostic performance of 64-slice CT coronary angiography in nine centres worldwide in comparison to conventional coronary angiography. In conclusion, the multi-centre, multi-institutional and multi-continental trial CORE-64 has great potential to ultimately assess the per-patient diagnostic performance of coronary CT angiography using 64 simultaneous detector rows.

Global minimum profile error (GMPE) - a least-squares-based approach for extracting macroscopic rate coefficients for complex gas-phase chemical reactions.

PubMed

Duong, Minh V; Nguyen, Hieu T; Mai, Tam V-T; Huynh, Lam K

2018-01-03

Master equation/Rice-Ramsperger-Kassel-Marcus (ME/RRKM) has shown to be a powerful framework for modeling kinetic and dynamic behaviors of a complex gas-phase chemical system on a complicated multiple-species and multiple-channel potential energy surface (PES) for a wide range of temperatures and pressures. Derived from the ME time-resolved species profiles, the macroscopic or phenomenological rate coefficients are essential for many reaction engineering applications including those in combustion and atmospheric chemistry. Therefore, in this study, a least-squares-based approach named Global Minimum Profile Error (GMPE) was proposed and implemented in the MultiSpecies-MultiChannel (MSMC) code (Int. J. Chem. Kinet., 2015, 47, 564) to extract macroscopic rate coefficients for such a complicated system. The capability and limitations of the new approach were discussed in several well-defined test cases.

Challenges Encountered in Building a University-High School Collaboration: A Case Study

ERIC Educational Resources Information Center

Quebec Fuentes, Sarah; Spice, Loren

2015-01-01

In this paper, we describe the second year of a multi-year project that we developed to foster collaboration between high school teachers and university undergraduates. The project incorporates specific tools that help partners find an approach to collaboration that is right for them, allowing it to offer more flexibility than traditional…

Literacy through Photography: Multimodal and Visual Literacy in a Third Grade Classroom

ERIC Educational Resources Information Center

Wiseman, Angela M.; Mäkinen, Marita; Kupiainen, Reijo

2016-01-01

This article reports findings from a diverse third grade classroom that integrates a literacy through photography (LTP) curriculum as a central component of writing instruction in an urban public school. A case study approach was used in order to provide an in-depth, multi-dimensional consideration of phenomena by drawing on multiple data sources…

A Smart Partnership: Integrating Educational Technology for Underserved Children in India

ERIC Educational Resources Information Center

Charania, Amina; Davis, Niki

2016-01-01

This paper explores the evolution of a large multi-stakeholder partnership that has grown since 2011 to scale deep engagement with learning through technology and decrease the digital divide for thousands of underserved school children in India. Using as its basis a case study of an initiative called integrated approach to technology in education…

Formal Leadership of Department Chairpersons with a Broadening Span of Control in Restructured Community Colleges: A Multi-Case Study

ERIC Educational Resources Information Center

Fattig, Teri L.

2013-01-01

Community college department chairpersons have experienced a broadening span of control due to the restructuring tactics of community colleges and the approaches utilized in order to cope with decreased budgets and increased enrollments. Many community colleges used strategies which involved flattening the middle management section of the…

Optimising Inter-Disciplinary Problem-Based Learning in Postgraduate Environmental and Science Education: Recommendations from a Case Study

ERIC Educational Resources Information Center

Redshaw, Clare H; Frampton, Ian

2014-01-01

As the value of multi-disciplinary working in the business and research worlds is becoming more recognised, the number of inter-disciplinary postgraduate environmental and health sciences courses is also increasing. Equally, the popularity of problem-based learning (PBL) is expected to grow and influence instructional approaches in many…

Sprinters in the Course of a Marathon: Withdrawal from Elite Competitive Sport in Adolescence

ERIC Educational Resources Information Center

Mudrak, Jiri

2010-01-01

This paper attempts to explain, using a multi-case study approach, why some young elite athletes, who have shown extraordinary talent in childhood, leave competitive sport in adolescence. Semi-structured interviews were conducted with five young elite athletes who decided to withdraw from elite sport. Interview data were analyzed using the…

Drug resistant Skeletal Tuberculosis in a tertiary care centre in South India.

PubMed

Arockiaraj, J; Balaji, G S; Cherian, V M; T S, Jepegnanam; Thomas, B P; Michael, Joy S; Poonnoose, P M

2018-03-01

Drug resistant tuberculosis is alarmingly on the rise especially in developing countries. Skeletal tuberculosis accounts up to 10% of all extra pulmonary tuberculosis. World Health Organisation (WHO) has not formulated guidelines for the management of Multi-drug resistant skeletal tuberculosis. A retrospective analysis of patients treated for musculoskeletal tuberculosis was done, to study drug resistance patterns. The outcome was assessed both clinically and radiologically.898 patients were treated for skeletal tuberculosis during the period of 2006-2013 (96 months). 478 (53.2%) patients were treated for tubercular spondylitis and 420 (46.8%) for extra-spinal skeletal tuberculosis. Ninety two patients (10.2%) had documented resistance to the anti-tubercular drugs. There were 42 mono resistant tuberculosis cases (4.7%), 13 poly resistant cases (1.4%), 33 multi-drug resistant cases (MDR TB) (3.7%) and 4 (0.4%) extremely drug resistant tuberculosis cases (XDR). All the patients were treated medically as per drug susceptibility patterns and protocols. Surgery was performed when indicated in 59 (66%) cases. 85% completed their course of treatment and were successfully healed as per pre-set clinical, biochemical and radiological criteria. The remaining were lost to follow up. One patient died as a result of post op respiratory infection. The prevalence of Multi-drug resistant tuberculosis patients in our centre was 3.7% and that of Extremely drug resistant tuberculosis cases was 0.4%. A Multi-disciplinary approach with drug susceptibility tests, sensitive drugs, and surgery if required is essential. Health education is essential to improve awareness among health care professionals about the danger of drug resistance in tuberculosis.

Community engagement to enhance trust between Gypsy/Travellers, and maternity, early years' and child dental health services: protocol for a multi-method exploratory study.

PubMed

McFadden, Alison; Atkin, Karl; Bell, Kerry; Innes, Nicola; Jackson, Cath; Jones, Helen; MacGillivray, Steve; Siebelt, Lindsay

2016-11-14

Gypsy/Travellers have poor health and experience discrimination alongside structural and cultural barriers when accessing health services and consequently may mistrust those services. Our study aims to investigate which approaches to community engagement are most likely to be effective at enhancing trust between Gypsy/Travellers and mainstream health services. This multi-method 30-month study, commenced in June 2015, and comprises four stages. 1. Three related reviews: a) systematic review of Gypsy/Travellers' access to health services; b) systematic review of reviews of how trust has been conceptualised within healthcare; c) realist synthesis of community engagement approaches to enhance trust and increase Gypsy/Travellers' participation in health services. The reviews will consider any economic literature; 2. Online consultation with health and social care practitioners, and civil society organisations on existing engagement activities, including perceptions of barriers and good practice; 3. Four in-depth case studies of different Gypsy/Traveller communities, focusing on maternity, early years and child dental health services. The case studies include the views of 32-48 mothers of pre-school children, 32-40 healthcare providers and 8-12 informants from third sector organisations. 4. Two stakeholder workshops exploring whether policy options are realistic, sustainable and replicable. Case study data will be analysed thematically informed by the evaluative framework derived from the realist synthesis in stage one. The main outputs will be: a) an evaluative framework of Gypsy/Travellers' engagement with health services; b) recommendations for policy and practice; c) evidence on which to base future implementation strategies including estimation of costs. Our novel multi-method study seeks to provide recommendations for policy and practice that have potential to improve uptake and delivery of health services, and to reduce lifetime health inequalities for Gypsy/Travellers. The findings may have wider resonance for other marginalised populations. Strengths and limitations of the study are discussed. Prospero registration for literature reviews: CRD42015021955 and CRD42015021950 UKCRN reference: 20036.

SU-F-R-10: Selecting the Optimal Solution for Multi-Objective Radiomics Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Z; Folkert, M; Wang, J

2016-06-15

Purpose: To develop an evidential reasoning approach for selecting the optimal solution from a Pareto solution set obtained by a multi-objective radiomics model for predicting distant failure in lung SBRT. Methods: In the multi-objective radiomics model, both sensitivity and specificity are considered as the objective functions simultaneously. A Pareto solution set with many feasible solutions will be resulted from the multi-objective optimization. In this work, an optimal solution Selection methodology for Multi-Objective radiomics Learning model using the Evidential Reasoning approach (SMOLER) was proposed to select the optimal solution from the Pareto solution set. The proposed SMOLER method used the evidentialmore » reasoning approach to calculate the utility of each solution based on pre-set optimal solution selection rules. The solution with the highest utility was chosen as the optimal solution. In SMOLER, an optimal learning model coupled with clonal selection algorithm was used to optimize model parameters. In this study, PET, CT image features and clinical parameters were utilized for predicting distant failure in lung SBRT. Results: Total 126 solution sets were generated by adjusting predictive model parameters. Each Pareto set contains 100 feasible solutions. The solution selected by SMOLER within each Pareto set was compared to the manually selected optimal solution. Five-cross-validation was used to evaluate the optimal solution selection accuracy of SMOLER. The selection accuracies for five folds were 80.00%, 69.23%, 84.00%, 84.00%, 80.00%, respectively. Conclusion: An optimal solution selection methodology for multi-objective radiomics learning model using the evidential reasoning approach (SMOLER) was proposed. Experimental results show that the optimal solution can be found in approximately 80% cases.« less

Minimizing impacts of land use change on ecosystem services using multi-criteria heuristic analysis.

PubMed

Keller, Arturo A; Fournier, Eric; Fox, Jessica

2015-06-01

Development of natural landscapes to support human activities impacts the capacity of the landscape to provide ecosystem services. Typically, several ecosystem services are impacted at a single development site and various footprint scenarios are possible, thus a multi-criteria analysis is needed. Restoration potential should also be considered for the area surrounding the permanent impact site. The primary objective of this research was to develop a heuristic approach to analyze multiple criteria (e.g. impacts to various ecosystem services) in a spatial configuration with many potential development sites. The approach was to: (1) quantify the magnitude of terrestrial ecosystem service (biodiversity, carbon sequestration, nutrient and sediment retention, and pollination) impacts associated with a suite of land use change scenarios using the InVEST model; (2) normalize results across categories of ecosystem services to allow cross-service comparison; (3) apply the multi-criteria heuristic algorithm to select sites with the least impact to ecosystem services, including a spatial criterion (separation between sites). As a case study, the multi-criteria impact minimization algorithm was applied to InVEST output to select 25 potential development sites out of 204 possible locations (selected by other criteria) within a 24,000 ha property. This study advanced a generally applicable spatial multi-criteria approach for 1) considering many land use footprint scenarios, 2) balancing impact decisions across a suite of ecosystem services, and 3) determining the restoration potential of ecosystem services after impacts. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Different approaches for centralized and decentralized water system management in multiple decision makers' problems

NASA Astrophysics Data System (ADS)

Anghileri, D.; Giuliani, M.; Castelletti, A.

2012-04-01

There is a general agreement that one of the most challenging issues related to water system management is the presence of many and often conflicting interests as well as the presence of several and independent decision makers. The traditional approach to multi-objective water systems management is a centralized management, in which an ideal central regulator coordinates the operation of the whole system, exploiting all the available information and balancing all the operating objectives. Although this approach allows to obtain Pareto-optimal solutions representing the maximum achievable benefit, it is based on assumptions which strongly limits its application in real world contexts: 1) top-down management, 2) existence of a central regulation institution, 3) complete information exchange within the system, 4) perfect economic efficiency. A bottom-up decentralized approach seems therefore to be more suitable for real case applications since different reservoir operators may maintain their independence. In this work we tested the consequences of a change in the water management approach moving from a centralized toward a decentralized one. In particular we compared three different cases: the centralized management approach, the independent management approach where each reservoir operator takes the daily release decision maximizing (or minimizing) his operating objective independently from each other, and an intermediate approach, leading to the Nash equilibrium of the associated game, where different reservoir operators try to model the behaviours of the other operators. The three approaches are demonstrated using a test case-study composed of two reservoirs regulated for the minimization of flooding in different locations. The operating policies are computed by solving one single multi-objective optimal control problem, in the centralized management approach; multiple single-objective optimization problems, i.e. one for each operator, in the independent case; using techniques related to game theory for the description of the interaction between the two operators, in the last approach. Computational results shows that the Pareto-optimal control policies obtained in the centralized approach dominate the control policies of both the two cases of decentralized management and that the so called price of anarchy increases moving toward the independent management approach. However, the Nash equilibrium solution seems to be the most promising alternative because it represents a good compromise in maximizing management efficiency without limiting the behaviours of the reservoir operators.

CAMELOT: Computational-Analytical Multi-fidElity Low-thrust Optimisation Toolbox

NASA Astrophysics Data System (ADS)

Di Carlo, Marilena; Romero Martin, Juan Manuel; Vasile, Massimiliano

2018-03-01

Computational-Analytical Multi-fidElity Low-thrust Optimisation Toolbox (CAMELOT) is a toolbox for the fast preliminary design and optimisation of low-thrust trajectories. It solves highly complex combinatorial problems to plan multi-target missions characterised by long spirals including different perturbations. To do so, CAMELOT implements a novel multi-fidelity approach combining analytical surrogate modelling and accurate computational estimations of the mission cost. Decisions are then made using two optimisation engines included in the toolbox, a single-objective global optimiser, and a combinatorial optimisation algorithm. CAMELOT has been applied to a variety of case studies: from the design of interplanetary trajectories to the optimal de-orbiting of space debris and from the deployment of constellations to on-orbit servicing. In this paper, the main elements of CAMELOT are described and two examples, solved using the toolbox, are presented.

Increasing the applicability of wind power projects via a multi-criteria approach: methodology and case study

NASA Astrophysics Data System (ADS)

Polatidis, Heracles; Morales, Jan Borràs

2016-11-01

In this paper a methodological framework for increasing the actual applicability of wind farms is developed and applied. The framework is based on multi-criteria decision aid techniques that perform an integrated technical and societal evaluation of a number of potential wind power projects that are a variation of a pre-existing actual proposal that faces implementation difficulties. A number of evaluation criteria are established and assessed via particular related software or are comparatively evaluated among each other on a semi-qualitative basis. The preference of a diverse audience of pertinent stakeholders can be also incorporated in the overall analysis. The result of the process is an identification of a new project that will exhibit increased actual implementation potential compared with the original proposal. The methodology is tested in a case study of a wind farm in the UK and relevant conclusions are drawn.

Multi-category micro-milling tool wear monitoring with continuous hidden Markov models

NASA Astrophysics Data System (ADS)

Zhu, Kunpeng; Wong, Yoke San; Hong, Geok Soon

2009-02-01

In-process monitoring of tool conditions is important in micro-machining due to the high precision requirement and high tool wear rate. Tool condition monitoring in micro-machining poses new challenges compared to conventional machining. In this paper, a multi-category classification approach is proposed for tool flank wear state identification in micro-milling. Continuous Hidden Markov models (HMMs) are adapted for modeling of the tool wear process in micro-milling, and estimation of the tool wear state given the cutting force features. For a noise-robust approach, the HMM outputs are connected via a medium filter to minimize the tool state before entry into the next state due to high noise level. A detailed study on the selection of HMM structures for tool condition monitoring (TCM) is presented. Case studies on the tool state estimation in the micro-milling of pure copper and steel demonstrate the effectiveness and potential of these methods.

Integrating multi-criteria evaluation techniques with geographic information systems for landfill site selection: a case study using ordered weighted average.

PubMed

Gorsevski, Pece V; Donevska, Katerina R; Mitrovski, Cvetko D; Frizado, Joseph P

2012-02-01

This paper presents a GIS-based multi-criteria decision analysis approach for evaluating the suitability for landfill site selection in the Polog Region, Macedonia. The multi-criteria decision framework considers environmental and economic factors which are standardized by fuzzy membership functions and combined by integration of analytical hierarchy process (AHP) and ordered weighted average (OWA) techniques. The AHP is used for the elicitation of attribute weights while the OWA operator function is used to generate a wide range of decision alternatives for addressing uncertainty associated with interaction between multiple criteria. The usefulness of the approach is illustrated by different OWA scenarios that report landfill suitability on a scale between 0 and 1. The OWA scenarios are intended to quantify the level of risk taking (i.e., optimistic, pessimistic, and neutral) and to facilitate a better understanding of patterns that emerge from decision alternatives involved in the decision making process. Copyright © 2011 Elsevier Ltd. All rights reserved.

Design for sustainability of industrial symbiosis based on emergy and multi-objective particle swarm optimization.

PubMed

Ren, Jingzheng; Liang, Hanwei; Dong, Liang; Sun, Lu; Gao, Zhiqiu

2016-08-15

Industrial symbiosis provides novel and practical pathway to the design for the sustainability. Decision support tool for its verification is necessary for practitioners and policy makers, while to date, quantitative research is limited. The objective of this work is to present an innovative approach for supporting decision-making in the design for the sustainability with the implementation of industrial symbiosis in chemical complex. Through incorporating the emergy theory, the model is formulated as a multi-objective approach that can optimize both the economic benefit and sustainable performance of the integrated industrial system. A set of emergy based evaluation index are designed. Multi-objective Particle Swarm Algorithm is proposed to solve the model, and the decision-makers are allowed to choose the suitable solutions form the Pareto solutions. An illustrative case has been studied by the proposed method, a few of compromises between high profitability and high sustainability can be obtained for the decision-makers/stakeholders to make decision. Copyright © 2016 Elsevier B.V. All rights reserved.

Efficient multi-scenario Model Predictive Control for water resources management with ensemble streamflow forecasts

NASA Astrophysics Data System (ADS)

Tian, Xin; Negenborn, Rudy R.; van Overloop, Peter-Jules; María Maestre, José; Sadowska, Anna; van de Giesen, Nick

2017-11-01

Model Predictive Control (MPC) is one of the most advanced real-time control techniques that has been widely applied to Water Resources Management (WRM). MPC can manage the water system in a holistic manner and has a flexible structure to incorporate specific elements, such as setpoints and constraints. Therefore, MPC has shown its versatile performance in many branches of WRM. Nonetheless, with the in-depth understanding of stochastic hydrology in recent studies, MPC also faces the challenge of how to cope with hydrological uncertainty in its decision-making process. A possible way to embed the uncertainty is to generate an Ensemble Forecast (EF) of hydrological variables, rather than a deterministic one. The combination of MPC and EF results in a more comprehensive approach: Multi-scenario MPC (MS-MPC). In this study, we will first assess the model performance of MS-MPC, considering an ensemble streamflow forecast. Noticeably, the computational inefficiency may be a critical obstacle that hinders applicability of MS-MPC. In fact, with more scenarios taken into account, the computational burden of solving an optimization problem in MS-MPC accordingly increases. To deal with this challenge, we propose the Adaptive Control Resolution (ACR) approach as a computationally efficient scheme to practically reduce the number of control variables in MS-MPC. In brief, the ACR approach uses a mixed-resolution control time step from the near future to the distant future. The ACR-MPC approach is tested on a real-world case study: an integrated flood control and navigation problem in the North Sea Canal of the Netherlands. Such an approach reduces the computation time by 18% and up in our case study. At the same time, the model performance of ACR-MPC remains close to that of conventional MPC.

Detection of surface cracking in steel pipes based on vibration data using a multi-class support vector machine classifier

NASA Astrophysics Data System (ADS)

Mustapha, S.; Braytee, A.; Ye, L.

2017-04-01

In this study, we focused at the development and verification of a robust framework for surface crack detection in steel pipes using measured vibration responses; with the presence of multiple progressive damage occurring in different locations within the structure. Feature selection, dimensionality reduction, and multi-class support vector machine were established for this purpose. Nine damage cases, at different locations, orientations and length, were introduced into the pipe structure. The pipe was impacted 300 times using an impact hammer, after each damage case, the vibration data were collected using 3 PZT wafers which were installed on the outer surface of the pipe. At first, damage sensitive features were extracted using the frequency response function approach followed by recursive feature elimination for dimensionality reduction. Then, a multi-class support vector machine learning algorithm was employed to train the data and generate a statistical model. Once the model is established, decision values and distances from the hyper-plane were generated for the new collected data using the trained model. This process was repeated on the data collected from each sensor. Overall, using a single sensor for training and testing led to a very high accuracy reaching 98% in the assessment of the 9 damage cases used in this study.

Post Pareto optimization-A case

NASA Astrophysics Data System (ADS)

Popov, Stoyan; Baeva, Silvia; Marinova, Daniela

2017-12-01

Simulation performance may be evaluated according to multiple quality measures that are in competition and their simultaneous consideration poses a conflict. In the current study we propose a practical framework for investigating such simulation performance criteria, exploring the inherent conflicts amongst them and identifying the best available tradeoffs, based upon multi-objective Pareto optimization. This approach necessitates the rigorous derivation of performance criteria to serve as objective functions and undergo vector optimization. We demonstrate the effectiveness of our proposed approach by applying it with multiple stochastic quality measures. We formulate performance criteria of this use-case, pose an optimization problem, and solve it by means of a simulation-based Pareto approach. Upon attainment of the underlying Pareto Frontier, we analyze it and prescribe preference-dependent configurations for the optimal simulation training.

Shot sequencing based on biological equivalent dose considerations for multiple isocenter Gamma Knife radiosurgery

NASA Astrophysics Data System (ADS)

Ma, Lijun; Lee, Letitia; Barani, Igor; Hwang, Andrew; Fogh, Shannon; Nakamura, Jean; McDermott, Michael; Sneed, Penny; Larson, David A.; Sahgal, Arjun

2011-11-01

Rapid delivery of multiple shots or isocenters is one of the hallmarks of Gamma Knife radiosurgery. In this study, we investigated whether the temporal order of shots delivered with Gamma Knife Perfexion would significantly influence the biological equivalent dose for complex multi-isocenter treatments. Twenty single-target cases were selected for analysis. For each case, 3D dose matrices of individual shots were extracted and single-fraction equivalent uniform dose (sEUD) values were determined for all possible shot delivery sequences, corresponding to different patterns of temporal dose delivery within the target. We found significant variations in the sEUD values among these sequences exceeding 15% for certain cases. However, the sequences for the actual treatment delivery were found to agree (<3%) and to correlate (R2 = 0.98) excellently with the sequences yielding the maximum sEUD values for all studied cases. This result is applicable for both fast and slow growing tumors with α/β values of 2 to 20 according to the linear-quadratic model. In conclusion, despite large potential variations in different shot sequences for multi-isocenter Gamma Knife treatments, current clinical delivery sequences exhibited consistent biological target dosing that approached that maximally achievable for all studied cases.

Multi-phase SPH modelling of violent hydrodynamics on GPUs

NASA Astrophysics Data System (ADS)

Mokos, Athanasios; Rogers, Benedict D.; Stansby, Peter K.; Domínguez, José M.

2015-11-01

This paper presents the acceleration of multi-phase smoothed particle hydrodynamics (SPH) using a graphics processing unit (GPU) enabling large numbers of particles (10-20 million) to be simulated on just a single GPU card. With novel hardware architectures such as a GPU, the optimum approach to implement a multi-phase scheme presents some new challenges. Many more particles must be included in the calculation and there are very different speeds of sound in each phase with the largest speed of sound determining the time step. This requires efficient computation. To take full advantage of the hardware acceleration provided by a single GPU for a multi-phase simulation, four different algorithms are investigated: conditional statements, binary operators, separate particle lists and an intermediate global function. Runtime results show that the optimum approach needs to employ separate cell and neighbour lists for each phase. The profiler shows that this approach leads to a reduction in both memory transactions and arithmetic operations giving significant runtime gains. The four different algorithms are compared to the efficiency of the optimised single-phase GPU code, DualSPHysics, for 2-D and 3-D simulations which indicate that the multi-phase functionality has a significant computational overhead. A comparison with an optimised CPU code shows a speed up of an order of magnitude over an OpenMP simulation with 8 threads and two orders of magnitude over a single thread simulation. A demonstration of the multi-phase SPH GPU code is provided by a 3-D dam break case impacting an obstacle. This shows better agreement with experimental results than an equivalent single-phase code. The multi-phase GPU code enables a convergence study to be undertaken on a single GPU with a large number of particles that otherwise would have required large high performance computing resources.

Multi-Collinearity Based Model Selection for Landslide Susceptibility Mapping: A Case Study from Ulus District of Karabuk, Turkey

NASA Astrophysics Data System (ADS)

Sahin, E. K.; Colkesen, I., , Dr; Kavzoglu, T.

2017-12-01

Identification of localities prone to landslide areas plays an important role for emergency planning, disaster management and recovery planning. Due to its great importance for disaster management, producing accurate and up-to-date landslide susceptibility maps is essential for hazard mitigation purpose and regional planning. The main objective of the present study was to apply multi-collinearity based model selection approach for the production of a landslide susceptibility map of Ulus district of Karabuk, Turkey. It is a fact that data do not contain enough information to describe the problem under consideration when the factors are highly correlated with each other. In such cases, choosing a subset of the original features will often lead to better performance. This paper presents multi-collinearity based model selection approach to deal with the high correlation within the dataset. Two collinearity diagnostic factors (Tolerance (TOL) and the Variance Inflation Factor (VIF)) are commonly used to identify multi-collinearity. Values of VIF that exceed 10.0 and TOL values less than 1.0 are often regarded as indicating multi-collinearity. Five causative factors (slope length, curvature, plan curvature, profile curvature and topographical roughness index) were found highly correlated with each other among 15 factors available for the study area. As a result, the five correlated factors were removed from the model estimation, and performances of the models including the remaining 10 factors (aspect, drainage density, elevation, lithology, land use/land cover, NDVI, slope, sediment transport index, topographical position index and topographical wetness index) were evaluated using logistic regression. The performance of prediction model constructed with 10 factors was compared to that of 15-factor model. The prediction performance of two susceptibility maps was evaluated by overall accuracy and the area under the ROC curve (AUC) values. Results showed that overall accuracy and AUC was calculated as 77.15% and 96.62% respectively for the model with 10 selected factors whilst they were estimated as 73.45% and 89.45% respectively for the model with all factors. It is clear that the multi-collinearity based model outperformed the conventional model in the mapping of landslide susceptibility.

An Unlikely Destination: Meeting the Educational Needs of Immigrant, Migrant and Refugee Children in the Suburbs of Chicago, IL

ERIC Educational Resources Information Center

Israel, Marla; Goldberger, Nancy; Vera, Elizabeth; Heineke, Amy

2017-01-01

Purpose: The purpose of this paper is to describe a university-multi-school district partnership that positively affected the lives of P-12 immigrant, migrant and refugee students and their parents through an iterative collaboration of talent and resources among institutions. Design/methodology/approach: This is a case study describing a…

Comparative Urban Bangladesh Physics Learning Experiences as Described by Students and Alumni

ERIC Educational Resources Information Center

Ali, Tanzeem Iqbal

2013-01-01

A neo-culture of extra-curricular coaching prior to sitting the terminal exam was once the privileged domain of public education systems in the Eastern world, but this is no longer the case. This multi-phase study based on a grounded theory approach considered a diversity of physics learning experiences of students and alumni from two urban…

A Cross-Layer Approach to Multi-Hop Networking with Cognitive Radios

DTIC Science & Technology

2008-11-01

recent investigations. In [2], Behzad and Rubin studied the special case that the same power level are used at each node and found that the maximum...Sep. 2, 2005. [2] A. Behzad and I. Rubin, “Impact of power control on the performance of ad hoc wireless networks,” in Proc. IEEE Infocom, pp. 102–113

Library Subject Guides: A Content Management Case Study at the Open University, UK

ERIC Educational Resources Information Center

Wales, Tim

2005-01-01

Purpose: To share the experiences and challenges faced by the Open University Library (OUL) in developing a content management (CM) system for its subject guides. Design/methodology/approach: A summary of multi-format subject guide production at the OUL is provided to justify the decision to develop a new system for their production using a…

Putting Ourselves in the Big Picture: A Sustainable Approach to Project Management for e-Learning

ERIC Educational Resources Information Center

Buchan, Janet

2010-01-01

In a case study of a large Australian university the metaphor of panarchy is used as a means of describing and understanding the complex interrelationships of multi-scale institutional projects and the influences of a variety factors on the potential success of e-learning initiatives. The concept of para-analysis is introduced as a management…

The Role of the Teaching Experiment: Students' Construction of Transformations in a Multiple Representational Environment.

ERIC Educational Resources Information Center

Borba, Marcelo; Confrey, Jere

Function Probe is a multi-representational software for Apple Macintosh computers. It was designed to allow students to approach problems in different ways and/or use different representations. This case study describes a 16-year-old student as he creates a path among a variety of representations of transformations of functions while using the…

Unintended outcomes evaluation approach: A plausible way to evaluate unintended outcomes of social development programmes.

PubMed

Jabeen, Sumera

2018-06-01

Social development programmes are deliberate attempts to bring about change and unintended outcomes can be considered as inherent to any such intervention. There is now a solid consensus among the international evaluation community regarding the need to consider unintended outcomes as a key aspect in any evaluative study. However, this concern often equates to nothing more than false piety. Exiting evaluation theory suffers from overlap of terminology, inadequate categorisation of unintended outcomes and lack of guidance on how to study them. To advance the knowledge of evaluation theory, methods and practice, the author has developed an evaluation approach to study unintended effects using a theory building, testing and refinement process. A comprehensive classification of unintended outcomes on the basis of knowability, value, distribution and temporality helped specify various type of unintended outcomes for programme evaluation. Corresponding to this classification, a three-step evaluation process was proposed including a) outlining programme intentions b) forecasting likely unintended effects c) mapping the anticipated and understanding unanticipated unintended outcomes. This unintended outcomes evaluation approach (UOEA) was then trialled by undertaking a multi-site and multi-method case study of a poverty alleviation programme in Pakistan and refinements were made to the approach.The case study revealed that this programme was producing a number of unintended effects, mostly negative, affecting those already disadvantaged such as the poorest, women and children. The trialling process demonstrated the effectiveness of the UOEA and suggests that this can serve as a useful guide for future evaluation practice. It also provides the discipline of evaluation with an empirically-based reference point for further theoretical developments in the study of unintended outcomes. Copyright © 2017 Elsevier Ltd. All rights reserved.

An optimized solution of multi-criteria evaluation analysis of landslide susceptibility using fuzzy sets and Kalman filter

NASA Astrophysics Data System (ADS)

Gorsevski, Pece V.; Jankowski, Piotr

2010-08-01

The Kalman recursive algorithm has been very widely used for integrating navigation sensor data to achieve optimal system performances. This paper explores the use of the Kalman filter to extend the aggregation of spatial multi-criteria evaluation (MCE) and to find optimal solutions with respect to a decision strategy space where a possible decision rule falls. The approach was tested in a case study in the Clearwater National Forest in central Idaho, using existing landslide datasets from roaded and roadless areas and terrain attributes. In this approach, fuzzy membership functions were used to standardize terrain attributes and develop criteria, while the aggregation of the criteria was achieved by the use of a Kalman filter. The approach presented here offers advantages over the classical MCE theory because the final solution includes both the aggregated solution and the areas of uncertainty expressed in terms of standard deviation. A comparison of this methodology with similar approaches suggested that this approach is promising for predicting landslide susceptibility and further application as a spatial decision support system.

Foundations of modelling of nonequilibrium low-temperature plasmas

NASA Astrophysics Data System (ADS)

Alves, L. L.; Bogaerts, A.; Guerra, V.; Turner, M. M.

2018-02-01

This work explains the need for plasma models, introduces arguments for choosing the type of model that better fits the purpose of each study, and presents the basics of the most common nonequilibrium low-temperature plasma models and the information available from each one, along with an extensive list of references for complementary in-depth reading. The paper presents the following models, organised according to the level of multi-dimensional description of the plasma: kinetic models, based on either a statistical particle-in-cell/Monte-Carlo approach or the solution to the Boltzmann equation (in the latter case, special focus is given to the description of the electron kinetics); multi-fluid models, based on the solution to the hydrodynamic equations; global (spatially-average) models, based on the solution to the particle and energy rate-balance equations for the main plasma species, usually including a very complete reaction chemistry; mesoscopic models for plasma-surface interaction, adopting either a deterministic approach or a stochastic dynamical Monte-Carlo approach. For each plasma model, the paper puts forward the physics context, introduces the fundamental equations, presents advantages and limitations, also from a numerical perspective, and illustrates its application with some examples. Whenever pertinent, the interconnection between models is also discussed, in view of multi-scale hybrid approaches.

Performance of an Artificial Multi-observer Deep Neural Network for Fully Automated Segmentation of Polycystic Kidneys.

PubMed

Kline, Timothy L; Korfiatis, Panagiotis; Edwards, Marie E; Blais, Jaime D; Czerwiec, Frank S; Harris, Peter C; King, Bernard F; Torres, Vicente E; Erickson, Bradley J

2017-08-01

Deep learning techniques are being rapidly applied to medical imaging tasks-from organ and lesion segmentation to tissue and tumor classification. These techniques are becoming the leading algorithmic approaches to solve inherently difficult image processing tasks. Currently, the most critical requirement for successful implementation lies in the need for relatively large datasets that can be used for training the deep learning networks. Based on our initial studies of MR imaging examinations of the kidneys of patients affected by polycystic kidney disease (PKD), we have generated a unique database of imaging data and corresponding reference standard segmentations of polycystic kidneys. In the study of PKD, segmentation of the kidneys is needed in order to measure total kidney volume (TKV). Automated methods to segment the kidneys and measure TKV are needed to increase measurement throughput and alleviate the inherent variability of human-derived measurements. We hypothesize that deep learning techniques can be leveraged to perform fast, accurate, reproducible, and fully automated segmentation of polycystic kidneys. Here, we describe a fully automated approach for segmenting PKD kidneys within MR images that simulates a multi-observer approach in order to create an accurate and robust method for the task of segmentation and computation of TKV for PKD patients. A total of 2000 cases were used for training and validation, and 400 cases were used for testing. The multi-observer ensemble method had mean ± SD percent volume difference of 0.68 ± 2.2% compared with the reference standard segmentations. The complete framework performs fully automated segmentation at a level comparable with interobserver variability and could be considered as a replacement for the task of segmentation of PKD kidneys by a human.

Prospects for direct social perception: a multi-theoretical integration to further the science of social cognition.

PubMed

Wiltshire, Travis J; Lobato, Emilio J C; McConnell, Daniel S; Fiore, Stephen M

2014-01-01

In this paper we suggest that differing approaches to the science of social cognition mirror the arguments between radical embodied and traditional approaches to cognition. We contrast the use in social cognition of theoretical inference and mental simulation mechanisms with approaches emphasizing a direct perception of others' mental states. We build from a recent integrative framework unifying these divergent perspectives through the use of dual-process theory and supporting social neuroscience research. Our elaboration considers two complementary notions of direct perception: one primarily stemming from ecological psychology and the other from enactive cognition theory. We use this as the foundation from which to offer an account of the informational basis for social information and assert a set of research propositions to further the science of social cognition. In doing so, we point out how perception of the minds of others can be supported in some cases by lawful information, supporting direct perception of social affordances and perhaps, mental states, and in other cases by cues that support indirect perceptual inference. Our goal is to extend accounts of social cognition by integrating advances across disciplines to provide a multi-level and multi-theoretic description that can advance this field and offer a means through which to reconcile radical embodied and traditional approaches to cognitive neuroscience.

An efficient multi-resolution GA approach to dental image alignment

NASA Astrophysics Data System (ADS)

Nassar, Diaa Eldin; Ogirala, Mythili; Adjeroh, Donald; Ammar, Hany

2006-02-01

Automating the process of postmortem identification of individuals using dental records is receiving an increased attention in forensic science, especially with the large volume of victims encountered in mass disasters. Dental radiograph alignment is a key step required for automating the dental identification process. In this paper, we address the problem of dental radiograph alignment using a Multi-Resolution Genetic Algorithm (MR-GA) approach. We use location and orientation information of edge points as features; we assume that affine transformations suffice to restore geometric discrepancies between two images of a tooth, we efficiently search the 6D space of affine parameters using GA progressively across multi-resolution image versions, and we use a Hausdorff distance measure to compute the similarity between a reference tooth and a query tooth subject to a possible alignment transform. Testing results based on 52 teeth-pair images suggest that our algorithm converges to reasonable solutions in more than 85% of the test cases, with most of the error in the remaining cases due to excessive misalignments.

On the identifiability of inertia parameters of planar Multi-Body Space Systems

NASA Astrophysics Data System (ADS)

Nabavi-Chashmi, Seyed Yaser; Malaek, Seyed Mohammad-Bagher

2018-04-01

This work describes a new formulation to study the identifiability characteristics of Serially Linked Multi-body Space Systems (SLMBSS). The process exploits the so called "Lagrange Formulation" to develop a linear form of Equations of Motion w.r.t the system Inertia Parameters (IPs). Having developed a specific form of regressor matrix, we aim to expedite the identification process. The new approach allows analytical as well as numerical identification and identifiability analysis for different SLMBSSs' configurations. Moreover, the explicit forms of SLMBSSs identifiable parameters are derived by analyzing the identifiability characteristics of the robot. We further show that any SLMBSS designed with Variable Configurations Joint allows all IPs to be identifiable through comparing two successive identification outcomes. This feature paves the way to design new class of SLMBSS for which accurate identification of all IPs is at hand. Different case studies reveal that proposed formulation provides fast and accurate results, as required by the space applications. Further studies might be necessary for cases where planar-body assumption becomes inaccurate.

Elucidating complicated assembling systems in biology using size-and-shape analysis of sedimentation velocity data

PubMed Central

Chaton, Catherine T.

2017-01-01

Sedimentation velocity analytical ultracentrifugation (SV-AUC) has seen a resurgence in popularity as a technique for characterizing macromolecules and complexes in solution. SV-AUC is a particularly powerful tool for studying protein conformation, complex stoichiometry, and interacting systems in general. Deconvoluting velocity data to determine a sedimentation coefficient distribution c(s) allows for the study of either individual proteins or multi-component mixtures. The standard c(s) approach estimates molar masses of the sedimenting species based on determination of the frictional ratio (f/f0) from boundary shapes. The frictional ratio in this case is a weight-averaged parameter, which can lead to distortion of mass estimates and loss of information when attempting to analyze mixtures of macromolecules with different shapes. A two-dimensional extension of the c(s) analysis approach provides size-and-shape distributions that describe the data in terms of a sedimentation coefficient and frictional ratio grid. This allows for better resolution of species with very distinct shapes that may co-sediment and provides better molar mass determinations for multi-component mixtures. An example case is illustrated using globular and non-globular proteins of different masses with nearly identical sedimentation coefficients that could only be resolved using the size-and-shape distribution. Other applications of this analytical approach to complex biological systems are presented, focusing on proteins involved in the innate immune response to cytosolic microbial DNA. PMID:26412652

Smart Grid as Multi-layer Interacting System for Complex Decision Makings

NASA Astrophysics Data System (ADS)

Bompard, Ettore; Han, Bei; Masera, Marcelo; Pons, Enrico

This chapter presents an approach to the analysis of Smart Grids based on a multi-layer representation of their technical, cyber, social and decision-making aspects, as well as the related environmental constraints. In the Smart Grid paradigm, self-interested active customers (prosumers), system operators and market players interact among themselves making use of an extensive cyber infrastructure. In addition, policy decision makers define regulations, incentives and constraints to drive the behavior of the competing operators and prosumers, with the objective of ensuring the global desired performance (e.g. system stability, fair prices). For these reasons, the policy decision making is more complicated than in traditional power systems, and needs proper modeling and simulation tools for assessing "in vitro" and ex-ante the possible impacts of the decisions assumed. In this chapter, we consider the smart grids as multi-layered interacting complex systems. The intricacy of the framework, characterized by several interacting layers, cannot be captured by closed-form mathematical models. Therefore, a new approach using Multi Agent Simulation is described. With case studies we provide some indications about how to develop agent-based simulation tools presenting some preliminary examples.

A multi-method approach toward de novo glycan characterization: a Man-5 case study.

PubMed

Prien, Justin M; Prater, Bradley D; Cockrill, Steven L

2010-05-01

Regulatory agencies' expectations for biotherapeutic approval are becoming more stringent with regard to product characterization, where minor species as low as 0.1% of a given profile are typically identified. The mission of this manuscript is to demonstrate a multi-method approach toward de novo glycan characterization and quantitation, including minor species at or approaching the 0.1% benchmark. Recently, unexpected isomers of the Man(5)GlcNAc(2) (M(5)) were reported (Prien JM, Ashline DJ, Lapadula AJ, Zhang H, Reinhold VN. 2009. The high mannose glycans from bovine ribonuclease B isomer characterization by ion trap mass spectrometry (MS). J Am Soc Mass Spectrom. 20:539-556). In the current study, quantitative analysis of these isomers found in commercial M(5) standard demonstrated that they are in low abundance (<1% of the total) and therefore an exemplary "litmus test" for minor species characterization. A simple workflow devised around three core well-established analytical procedures: (1) fluorescence derivatization; (2) online rapid resolution reversed-phase separation coupled with negative-mode sequential mass spectrometry (RRRP-(-)-MS(n)); and (3) permethylation derivatization with nanospray sequential mass spectrometry (NSI-MS(n)) provides comprehensive glycan structural determination. All methods have limitations; however, a multi-method workflow is an at-line stopgap/solution which mitigates each method's individual shortcoming(s) providing greater opportunity for more comprehensive characterization. This manuscript is the first to demonstrate quantitative chromatographic separation of the M(5) isomers and the use of a commercially available stable isotope variant of 2-aminobenzoic acid to detect and chromatographically resolve multiple M(5) isomers in bovine ribonuclease B. With this multi-method approach, we have the capabilities to comprehensively characterize a biotherapeutic's glycan array in a de novo manner, including structural isomers at >/=0.1% of the total chromatographic peak area.

Sampling strategies for improving tree accuracy and phylogenetic analyses: a case study in ciliate protists, with notes on the genus Paramecium.

PubMed

Yi, Zhenzhen; Strüder-Kypke, Michaela; Hu, Xiaozhong; Lin, Xiaofeng; Song, Weibo

2014-02-01

In order to assess how dataset-selection for multi-gene analyses affects the accuracy of inferred phylogenetic trees in ciliates, we chose five genes and the genus Paramecium, one of the most widely used model protist genera, and compared tree topologies of the single- and multi-gene analyses. Our empirical study shows that: (1) Using multiple genes improves phylogenetic accuracy, even when their one-gene topologies are in conflict with each other. (2) The impact of missing data on phylogenetic accuracy is ambiguous: resolution power and topological similarity, but not number of represented taxa, are the most important criteria of a dataset for inclusion in concatenated analyses. (3) As an example, we tested the three classification models of the genus Paramecium with a multi-gene based approach, and only the monophyly of the subgenus Paramecium is supported. Copyright © 2013 Elsevier Inc. All rights reserved.

Reliable design of a closed loop supply chain network under uncertainty: An interval fuzzy possibilistic chance-constrained model

NASA Astrophysics Data System (ADS)

Vahdani, Behnam; Tavakkoli-Moghaddam, Reza; Jolai, Fariborz; Baboli, Arman

2013-06-01

This article seeks to offer a systematic approach to establishing a reliable network of facilities in closed loop supply chains (CLSCs) under uncertainties. Facilities that are located in this article concurrently satisfy both traditional objective functions and reliability considerations in CLSC network designs. To attack this problem, a novel mathematical model is developed that integrates the network design decisions in both forward and reverse supply chain networks. The model also utilizes an effective reliability approach to find a robust network design. In order to make the results of this article more realistic, a CLSC for a case study in the iron and steel industry has been explored. The considered CLSC is multi-echelon, multi-facility, multi-product and multi-supplier. Furthermore, multiple facilities exist in the reverse logistics network leading to high complexities. Since the collection centres play an important role in this network, the reliability concept of these facilities is taken into consideration. To solve the proposed model, a novel interactive hybrid solution methodology is developed by combining a number of efficient solution approaches from the recent literature. The proposed solution methodology is a bi-objective interval fuzzy possibilistic chance-constraint mixed integer linear programming (BOIFPCCMILP). Finally, computational experiments are provided to demonstrate the applicability and suitability of the proposed model in a supply chain environment and to help decision makers facilitate their analyses.

A multi-resolution strategy for a multi-objective deformable image registration framework that accommodates large anatomical differences

NASA Astrophysics Data System (ADS)

Alderliesten, Tanja; Bosman, Peter A. N.; Sonke, Jan-Jakob; Bel, Arjan

2014-03-01

Currently, two major challenges dominate the field of deformable image registration. The first challenge is related to the tuning of the developed methods to specific problems (i.e. how to best combine different objectives such as similarity measure and transformation effort). This is one of the reasons why, despite significant progress, clinical implementation of such techniques has proven to be difficult. The second challenge is to account for large anatomical differences (e.g. large deformations, (dis)appearing structures) that occurred between image acquisitions. In this paper, we study a framework based on multi-objective optimization to improve registration robustness and to simplify tuning for specific applications. Within this framework we specifically consider the use of an advanced model-based evolutionary algorithm for optimization and a dual-dynamic transformation model (i.e. two "non-fixed" grids: one for the source- and one for the target image) to accommodate for large anatomical differences. The framework computes and presents multiple outcomes that represent efficient trade-offs between the different objectives (a so-called Pareto front). In image processing it is common practice, for reasons of robustness and accuracy, to use a multi-resolution strategy. This is, however, only well-established for single-objective registration methods. Here we describe how such a strategy can be realized for our multi-objective approach and compare its results with a single-resolution strategy. For this study we selected the case of prone-supine breast MRI registration. Results show that the well-known advantages of a multi-resolution strategy are successfully transferred to our multi-objective approach, resulting in superior (i.e. Pareto-dominating) outcomes.

Multi-stage 3D-2D registration for correction of anatomical deformation in image-guided spine surgery

NASA Astrophysics Data System (ADS)

Ketcha, M. D.; De Silva, T.; Uneri, A.; Jacobson, M. W.; Goerres, J.; Kleinszig, G.; Vogt, S.; Wolinsky, J.-P.; Siewerdsen, J. H.

2017-06-01

A multi-stage image-based 3D-2D registration method is presented that maps annotations in a 3D image (e.g. point labels annotating individual vertebrae in preoperative CT) to an intraoperative radiograph in which the patient has undergone non-rigid anatomical deformation due to changes in patient positioning or due to the intervention itself. The proposed method (termed msLevelCheck) extends a previous rigid registration solution (LevelCheck) to provide an accurate mapping of vertebral labels in the presence of spinal deformation. The method employs a multi-stage series of rigid 3D-2D registrations performed on sets of automatically determined and increasingly localized sub-images, with the final stage achieving a rigid mapping for each label to yield a locally rigid yet globally deformable solution. The method was evaluated first in a phantom study in which a CT image of the spine was acquired followed by a series of 7 mobile radiographs with increasing degree of deformation applied. Second, the method was validated using a clinical data set of patients exhibiting strong spinal deformation during thoracolumbar spine surgery. Registration accuracy was assessed using projection distance error (PDE) and failure rate (PDE  >  20 mm—i.e. label registered outside vertebra). The msLevelCheck method was able to register all vertebrae accurately for all cases of deformation in the phantom study, improving the maximum PDE of the rigid method from 22.4 mm to 3.9 mm. The clinical study demonstrated the feasibility of the approach in real patient data by accurately registering all vertebral labels in each case, eliminating all instances of failure encountered in the conventional rigid method. The multi-stage approach demonstrated accurate mapping of vertebral labels in the presence of strong spinal deformation. The msLevelCheck method maintains other advantageous aspects of the original LevelCheck method (e.g. compatibility with standard clinical workflow, large capture range, and robustness against mismatch in image content) and extends capability to cases exhibiting strong changes in spinal curvature.

The role of economics in the QUERI program: QUERI Series

PubMed Central

Smith, Mark W; Barnett, Paul G

2008-01-01

Background The United States (U.S.) Department of Veterans Affairs (VA) Quality Enhancement Research Initiative (QUERI) has implemented economic analyses in single-site and multi-site clinical trials. To date, no one has reviewed whether the QUERI Centers are taking an optimal approach to doing so. Consistent with the continuous learning culture of the QUERI Program, this paper provides such a reflection. Methods We present a case study of QUERI as an example of how economic considerations can and should be integrated into implementation research within both single and multi-site studies. We review theoretical and applied cost research in implementation studies outside and within VA. We also present a critique of the use of economic research within the QUERI program. Results Economic evaluation is a key element of implementation research. QUERI has contributed many developments in the field of implementation but has only recently begun multi-site implementation trials across multiple regions within the national VA healthcare system. These trials are unusual in their emphasis on developing detailed costs of implementation, as well as in the use of business case analyses (budget impact analyses). Conclusion Economics appears to play an important role in QUERI implementation studies, only after implementation has reached the stage of multi-site trials. Economic analysis could better inform the choice of which clinical best practices to implement and the choice of implementation interventions to employ. QUERI economics also would benefit from research on costing methods and development of widely accepted international standards for implementation economics. PMID:18430199

The role of economics in the QUERI program: QUERI Series.

PubMed

Smith, Mark W; Barnett, Paul G

2008-04-22

The United States (U.S.) Department of Veterans Affairs (VA) Quality Enhancement Research Initiative (QUERI) has implemented economic analyses in single-site and multi-site clinical trials. To date, no one has reviewed whether the QUERI Centers are taking an optimal approach to doing so. Consistent with the continuous learning culture of the QUERI Program, this paper provides such a reflection. We present a case study of QUERI as an example of how economic considerations can and should be integrated into implementation research within both single and multi-site studies. We review theoretical and applied cost research in implementation studies outside and within VA. We also present a critique of the use of economic research within the QUERI program. Economic evaluation is a key element of implementation research. QUERI has contributed many developments in the field of implementation but has only recently begun multi-site implementation trials across multiple regions within the national VA healthcare system. These trials are unusual in their emphasis on developing detailed costs of implementation, as well as in the use of business case analyses (budget impact analyses). Economics appears to play an important role in QUERI implementation studies, only after implementation has reached the stage of multi-site trials. Economic analysis could better inform the choice of which clinical best practices to implement and the choice of implementation interventions to employ. QUERI economics also would benefit from research on costing methods and development of widely accepted international standards for implementation economics.

Learning and Innovation in Agriculture and Rural Development: The Use of the Concepts of Boundary Work and Boundary Objects

ERIC Educational Resources Information Center

Tisenkopfs, Talis; Kunda, Ilona; šumane, Sandra; Brunori, Gianluca; Klerkx, Laurens; Moschitz, Heidrun

2015-01-01

Purpose: The paper explores the role of boundary work and boundary objects in enhancing learning and innovation processes in hybrid multi-actor networks for sustainable agriculture (LINSA). Design/Methodology/Approach: Boundary work in LINSA is analysed on the basis of six case studies carried out in SOLINSA project under a common methodology. In…

Inverse scattering transform and soliton classification of the coupled modified Korteweg-de Vries equation

NASA Astrophysics Data System (ADS)

Wu, Jianping; Geng, Xianguo

2017-12-01

The inverse scattering transform of the coupled modified Korteweg-de Vries equation is studied by the Riemann-Hilbert approach. In the direct scattering process, the spectral analysis of the Lax pair is performed, from which a Riemann-Hilbert problem is established for the equation. In the inverse scattering process, by solving Riemann-Hilbert problems corresponding to the reflectionless cases, three types of multi-soliton solutions are obtained. The multi-soliton classification is based on the zero structures of the Riemann-Hilbert problem. In addition, some figures are given to illustrate the soliton characteristics of the coupled modified Korteweg-de Vries equation.

Fuzzy Evaluating Customer Satisfaction of Jet Fuel Companies

NASA Astrophysics Data System (ADS)

Cheng, Haiying; Fang, Guoyi

Based on the market characters of jet fuel companies, the paper proposes an evaluation index system of jet fuel company customer satisfaction from five dimensions as time, business, security, fee and service. And a multi-level fuzzy evaluation model composing with the analytic hierarchy process approach and fuzzy evaluation approach is given. Finally a case of one jet fuel company customer satisfaction evaluation is studied and the evaluation results response the feelings of the jet fuel company customers, which shows the fuzzy evaluation model is effective and efficient.

GP leadership in clinical commissioning groups: a qualitative multi-case study approach across England.

PubMed

Marshall, Martin; Holti, Richard; Hartley, Jean; Matharu, Tatum; Storey, John

2018-06-01

Clinical commissioning groups (CCGs) were established in England in 2013 to encourage GPs to exert greater influence over the processes of service improvement and redesign in the NHS. Little is known about the extent and the ways in which GPs have assumed these leadership roles. To explore the nature of clinical leadership of GPs in CCGs, and to examine the enablers and barriers to implementing a policy of clinical leadership in the NHS. A qualitative multi-case study approach in six localities across England. The case studies were purposefully sampled to represent different geographical localities and population demographics, and for their commitment to redesigning specified clinical or service areas. Data were collected from the case study CCGs and their partner organisations using a review of relevant documents, semi-structured individual or group interviews, and observations of key meetings. The data were analysed thematically and informed by relevant theories. GPs prefer a collaborative style of leadership that may be unlikely to produce rapid or radical change. Leadership activities are required at all levels in the system from strategy to frontline delivery, and the leadership behaviours of GPs who are not titular leaders are as important as formal leadership roles. A new alliance is emerging between clinicians and managers that draws on their different skillsets and creates new common interests. The uncertain policy environment in the English NHS is impacting on the willingness and the focus of GP leaders. GPs are making an important contribution as leaders of health service improvement and redesign but there are significant professional and political barriers to them optimising a leadership role. © British Journal of General Practice 2018.

A multi-scale spatial approach to address environmental effects of small hydropower development.

PubMed

McManamay, Ryan A; Samu, Nicole; Kao, Shih-Chieh; Bevelhimer, Mark S; Hetrick, Shelaine C

2015-01-01

Hydropower development continues to grow worldwide in developed and developing countries. While the ecological and physical responses to dam construction have been well documented, translating this information into planning for hydropower development is extremely difficult. Very few studies have conducted environmental assessments to guide site-specific or widespread hydropower development. Herein, we propose a spatial approach for estimating environmental effects of hydropower development at multiple scales, as opposed to individual site-by-site assessments (e.g., environmental impact assessment). Because the complex, process-driven effects of future hydropower development may be uncertain or, at best, limited by available information, we invested considerable effort in describing novel approaches to represent environmental concerns using spatial data and in developing the spatial footprint of hydropower infrastructure. We then use two case studies in the US, one at the scale of the conterminous US and another within two adjoining rivers basins, to examine how environmental concerns can be identified and related to areas of varying energy capacity. We use combinations of reserve-design planning and multi-metric ranking to visualize tradeoffs among environmental concerns and potential energy capacity. Spatial frameworks, like the one presented, are not meant to replace more in-depth environmental assessments, but to identify information gaps and measure the sustainability of multi-development scenarios as to inform policy decisions at the basin or national level. Most importantly, the approach should foster discussions among environmental scientists and stakeholders regarding solutions to optimize energy development and environmental sustainability.

Impact of model complexity and multi-scale data integration on the estimation of hydrogeological parameters in a dual-porosity aquifer

NASA Astrophysics Data System (ADS)

Tamayo-Mas, Elena; Bianchi, Marco; Mansour, Majdi

2018-03-01

This study investigates the impact of model complexity and multi-scale prior hydrogeological data on the interpretation of pumping test data in a dual-porosity aquifer (the Chalk aquifer in England, UK). In order to characterize the hydrogeological properties, different approaches ranging from a traditional analytical solution (Theis approach) to more sophisticated numerical models with automatically calibrated input parameters are applied. Comparisons of results from the different approaches show that neither traditional analytical solutions nor a numerical model assuming a homogenous and isotropic aquifer can adequately explain the observed drawdowns. A better reproduction of the observed drawdowns in all seven monitoring locations is instead achieved when medium and local-scale prior information about the vertical hydraulic conductivity (K) distribution is used to constrain the model calibration process. In particular, the integration of medium-scale vertical K variations based on flowmeter measurements lead to an improvement in the goodness-of-fit of the simulated drawdowns of about 30%. Further improvements (up to 70%) were observed when a simple upscaling approach was used to integrate small-scale K data to constrain the automatic calibration process of the numerical model. Although the analysis focuses on a specific case study, these results provide insights about the representativeness of the estimates of hydrogeological properties based on different interpretations of pumping test data, and promote the integration of multi-scale data for the characterization of heterogeneous aquifers in complex hydrogeological settings.

An adaptive multi-moment FVM approach for incompressible flows

NASA Astrophysics Data System (ADS)

Liu, Cheng; Hu, Changhong

2018-04-01

In this study, a multi-moment finite volume method (FVM) based on block-structured adaptive Cartesian mesh is proposed for simulating incompressible flows. A conservative interpolation scheme following the idea of the constrained interpolation profile (CIP) method is proposed for the prolongation operation of the newly created mesh. A sharp immersed boundary (IB) method is used to model the immersed rigid body. A moving least squares (MLS) interpolation approach is applied for reconstruction of the velocity field around the solid surface. An efficient method for discretization of Laplacian operators on adaptive meshes is proposed. Numerical simulations on several test cases are carried out for validation of the proposed method. For the case of viscous flow past an impulsively started cylinder (Re = 3000 , 9500), the computed surface vorticity coincides with the result of the body-fitted method. For the case of a fast pitching NACA 0015 airfoil at moderate Reynolds numbers (Re = 10000 , 45000), the predicted drag coefficient (CD) and lift coefficient (CL) agree well with other numerical or experimental results. For 2D and 3D simulations of viscous flow past a pitching plate with prescribed motions (Re = 5000 , 40000), the predicted CD, CL and CM (moment coefficient) are in good agreement with those obtained by other numerical methods.

The Case for Diabetes Population Health Improvement: Evidence-Based Programming for Population Outcomes in Diabetes.

PubMed

Golden, Sherita Hill; Maruthur, Nisa; Mathioudakis, Nestoras; Spanakis, Elias; Rubin, Daniel; Zilbermint, Mihail; Hill-Briggs, Felicia

2017-07-01

The goal of this review is to describe diabetes within a population health improvement framework and to review the evidence for a diabetes population health continuum of intervention approaches, including diabetes prevention and chronic and acute diabetes management, to improve clinical and economic outcomes. Recent studies have shown that compared to usual care, lifestyle interventions in prediabetes lower diabetes risk at the population-level and that group-based programs have low incremental medial cost effectiveness ratio for health systems. Effective outpatient interventions that improve diabetes control and process outcomes are multi-level, targeting the patient, provider, and healthcare system simultaneously and integrate community health workers as a liaison between the patient and community-based healthcare resources. A multi-faceted approach to diabetes management is also effective in the inpatient setting. Interventions shown to promote safe and effective glycemic control and use of evidence-based glucose management practices include provider reminder and clinical decision support systems, automated computer order entry, provider education, and organizational change. Future studies should examine the cost-effectiveness of multi-faceted outpatient and inpatient diabetes management programs to determine the best financial models for incorporating them into diabetes population health strategies.

Pedagogical Practices: The Case of Multi-Class Teaching in Fiji Primary School

ERIC Educational Resources Information Center

Lingam, Govinda I.

2007-01-01

Multi-class teaching is a common phenomenon in small schools not only in Fiji, but also in many countries. The aim of the present study was to determine the teaching styles adopted by teachers in the context of multi-class teaching. A qualitative case study research design was adopted. This included a school with multi-class teaching as the norm.…

Undergraduate Psychology Students' Experiences with Creative Drama: A Multi-Case Study

ERIC Educational Resources Information Center

Wilcox, Ruth A.

2015-01-01

This qualitative multi-case study explored undergraduate psychology students' experiences participating in creative drama activities the instructor/researcher developed to teach psychological concepts. The study was conducted in three introductory and developmental courses in a mid-western community college setting. Participants (cases) included…

A big-data model for multi-modal public transportation with application to macroscopic control and optimisation

NASA Astrophysics Data System (ADS)

Faizrahnemoon, Mahsa; Schlote, Arieh; Maggi, Lorenzo; Crisostomi, Emanuele; Shorten, Robert

2015-11-01

This paper describes a Markov-chain-based approach to modelling multi-modal transportation networks. An advantage of the model is the ability to accommodate complex dynamics and handle huge amounts of data. The transition matrix of the Markov chain is built and the model is validated using the data extracted from a traffic simulator. A realistic test-case using multi-modal data from the city of London is given to further support the ability of the proposed methodology to handle big quantities of data. Then, we use the Markov chain as a control tool to improve the overall efficiency of a transportation network, and some practical examples are described to illustrate the potentials of the approach.

The Treatment of Anorexia Nervosa in a General Hospital: A Case Vignette of a Multi-Disciplinary General Hospital-Based Approach.

ERIC Educational Resources Information Center

Kronenberg, J.; And Others

1994-01-01

Describes anorexia nervosa as condition variable in etiology and resistant to treatment, which may lead to mortality in 5% of treated cases. Notes that efforts have been made for treating disorder in nonstigmatizing medical units outside psychiatric hospitals. Describes, through presentation of short case vignette, advantages of treating…

A facilitated approach to family case conferencing for people with advanced dementia living in nursing homes: perceptions of palliative care planning coordinators and other health professionals in the IDEAL study.

PubMed

Luckett, Tim; Chenoweth, Lynnette; Phillips, Jane; Brooks, Deborah; Cook, Janet; Mitchell, Geoffrey; Pond, Dimity; Davidson, Patricia M; Beattie, Elizabeth; Luscombe, Georgina; Goodall, Stephen; Fischer, Thomas; Agar, Meera

2017-10-01

Palliative care for nursing home residents with advanced dementia is often sub-optimal due to poor communication and limited care planning. In a cluster randomized controlled trial, registered nurses (RNs) from 10 nursing homes were trained and funded to work as Palliative Care Planning Coordinators (PCPCs) to organize family case conferences and mentor staff. This qualitative sub-study aimed to explore PCPC and health professional perceptions of the benefits of facilitated case conferencing and identify factors influencing implementation. Semi-structured interviews were conducted with the RNs in the PCPC role, other members of nursing home staff, and physicians who participated in case conferences. Analysis was conducted by two researchers using a thematic framework approach. Interviews were conducted with 11 PCPCs, 18 other nurses, eight allied health workers, and three physicians. Perceived benefits of facilitated case conferencing included better communication between staff and families, greater multi-disciplinary involvement in case conferences and care planning, and improved staff attitudes and capabilities for dementia palliative care. Key factors influencing implementation included: staffing levels and time; support from management, staff and physicians; and positive family feedback. The facilitated approach explored in this study addressed known barriers to case conferencing. However, current business models in the sector make it difficult for case conferencing to receive the required levels of nursing qualification, training, and time. A collaborative nursing home culture and ongoing relationships with health professionals are also prerequisites for success. Further studies should document resident and family perceptions to harness consumer advocacy.

How do strategic decisions and operative practices affect operating room productivity?

PubMed

Peltokorpi, Antti

2011-12-01

Surgical operating rooms are cost-intensive parts of health service production. Managing operating units efficiently is essential when hospitals and healthcare systems aim to maximize health outcomes with limited resources. Previous research about operating room management has focused on studying the effect of management practices and decisions on efficiency by utilizing mainly modeling approach or before-after analysis in single hospital case. The purpose of this research is to analyze the synergic effect of strategic decisions and operative management practices on operating room productivity and to use a multiple case study method enabling statistical hypothesis testing with empirical data. 11 hypotheses that propose connections between the use of strategic and operative practices and productivity were tested in a multi-hospital study that included 26 units. The results indicate that operative practices, such as personnel management, case scheduling and performance measurement, affect productivity more remarkably than do strategic decisions that relate to, e.g., units' size, scope or academic status. Units with different strategic positions should apply different operative practices: Focused hospital units benefit most from sophisticated case scheduling and parallel processing whereas central and ambulatory units should apply flexible working hours, incentives and multi-skilled personnel. Operating units should be more active in applying management practices which are adequate for their strategic orientation.

Accelerating and focusing protein-protein docking correlations using multi-dimensional rotational FFT generating functions.

PubMed

Ritchie, David W; Kozakov, Dima; Vajda, Sandor

2008-09-01

Predicting how proteins interact at the molecular level is a computationally intensive task. Many protein docking algorithms begin by using fast Fourier transform (FFT) correlation techniques to find putative rigid body docking orientations. Most such approaches use 3D Cartesian grids and are therefore limited to computing three dimensional (3D) translational correlations. However, translational FFTs can speed up the calculation in only three of the six rigid body degrees of freedom, and they cannot easily incorporate prior knowledge about a complex to focus and hence further accelerate the calculation. Furthemore, several groups have developed multi-term interaction potentials and others use multi-copy approaches to simulate protein flexibility, which both add to the computational cost of FFT-based docking algorithms. Hence there is a need to develop more powerful and more versatile FFT docking techniques. This article presents a closed-form 6D spherical polar Fourier correlation expression from which arbitrary multi-dimensional multi-property multi-resolution FFT correlations may be generated. The approach is demonstrated by calculating 1D, 3D and 5D rotational correlations of 3D shape and electrostatic expansions up to polynomial order L=30 on a 2 GB personal computer. As expected, 3D correlations are found to be considerably faster than 1D correlations but, surprisingly, 5D correlations are often slower than 3D correlations. Nonetheless, we show that 5D correlations will be advantageous when calculating multi-term knowledge-based interaction potentials. When docking the 84 complexes of the Protein Docking Benchmark, blind 3D shape plus electrostatic correlations take around 30 minutes on a contemporary personal computer and find acceptable solutions within the top 20 in 16 cases. Applying a simple angular constraint to focus the calculation around the receptor binding site produces acceptable solutions within the top 20 in 28 cases. Further constraining the search to the ligand binding site gives up to 48 solutions within the top 20, with calculation times of just a few minutes per complex. Hence the approach described provides a practical and fast tool for rigid body protein-protein docking, especially when prior knowledge about one or both binding sites is available.

Informatics tools to improve clinical research study implementation.

PubMed

Brandt, Cynthia A; Argraves, Stephanie; Money, Roy; Ananth, Gowri; Trocky, Nina M; Nadkarni, Prakash M

2006-04-01

There are numerous potential sources of problems when performing complex clinical research trials. These issues are compounded when studies are multi-site and multiple personnel from different sites are responsible for varying actions from case report form design to primary data collection and data entry. We describe an approach that emphasizes the use of a variety of informatics tools that can facilitate study coordination, training, data checks and early identification and correction of faulty procedures and data problems. The paper focuses on informatics tools that can help in case report form design, procedures and training and data management. Informatics tools can be used to facilitate study coordination and implementation of clinical research trials.

The process of aging: A case study approach implementing an ergonomics evaluation of the built environment for the elderly in Brazil.

PubMed

Paiva, Marie; Ferrer, Nicole; Villarouco, Vilma

2015-01-01

The phenomenon of aging is increasing worldwide. Various problems accompany it since aging makes the elderly undergo a decline in their natural functions. As such, senility can present itself as a barrier for everyday activities. This article presents a research that deals with the study of collective residences for the elderly. It seeks to identify configurations of these homes by seeking shortcomings and/or successful solutions. The Ergonomic Methodology for the Built Environment was applied. The method of the approach is qualitative and consists of multi-case study. Through the methodological approach, conflicts in the environment created by missing or inadequate elements were identified. Also, the opinions and suggestions from the elderly were analyzed, which shows their perception of the environment in use. The situations detected in this study indicate the occurrence of problems, exacerbated by the multiple deficiencies found in the user population of the environments analyzed. Thus it highlights the importance of there being future studies that are better targeted on designing environments for the elderly.

Scalable software architecture for on-line multi-camera video processing

NASA Astrophysics Data System (ADS)

Camplani, Massimo; Salgado, Luis

2011-03-01

In this paper we present a scalable software architecture for on-line multi-camera video processing, that guarantees a good trade off between computational power, scalability and flexibility. The software system is modular and its main blocks are the Processing Units (PUs), and the Central Unit. The Central Unit works as a supervisor of the running PUs and each PU manages the acquisition phase and the processing phase. Furthermore, an approach to easily parallelize the desired processing application has been presented. In this paper, as case study, we apply the proposed software architecture to a multi-camera system in order to efficiently manage multiple 2D object detection modules in a real-time scenario. System performance has been evaluated under different load conditions such as number of cameras and image sizes. The results show that the software architecture scales well with the number of camera and can easily works with different image formats respecting the real time constraints. Moreover, the parallelization approach can be used in order to speed up the processing tasks with a low level of overhead.

Assessment of berberine as a multi-target antimicrobial: a multi-omics study for drug discovery and repositioning.

PubMed

Karaosmanoglu, Kubra; Sayar, Nihat Alpagu; Kurnaz, Isil Aksan; Akbulut, Berna Sariyar

2014-01-01

Postgenomics drug development is undergoing major transformation in the age of multi-omics studies and drug repositioning. Rather than applications solely in personalized medicine, omics science thus additionally offers a better understanding of a broader range of drug targets and drug repositioning. Berberine is an isoquinoline alkaloid found in many medicinal plants. We report here a whole genome microarray study in tandem with proteomics techniques for mining the plethora of targets that are putatively involved in the antimicrobial activity of berberine against Escherichia coli. We found DNA replication/repair and transcription to be triggered by berberine, indicating that nucleic acids, in general, are among its targets. Our combined transcriptomics and proteomics multi-omics findings underscore that, in the presence of berberine, cell wall or cell membrane transport and motility-related functions are also specifically regulated. We further report a general decline in metabolism, as seen by repression of genes in carbohydrate and amino acid metabolism, energy production, and conversion. An involvement of multidrug efflux pumps, as well as reduced membrane permeability for developing resistance against berberine in E. coli was noted. Collectively, these findings offer original and significant leads for omics-guided drug discovery and future repositioning approaches in the postgenomics era, using berberine as a multi-omics case study.

[The actual approaches to the economic analysis of effectiveness of functioning of multi-profile curative preventive medical institution].

PubMed

Gaĭdarov, G M; Alekseeva, N Iu; Latysheva, E A

2010-01-01

The article deals with the technique of economic analysis of effectiveness of functioning of multi-profile curative preventive medical institution in the conditions of transition to the payment according the completed case of treatment. The necessity of the measures targeted to prevent the financial losses under the new form of payment for hospital care is proved.

Case managers for older persons with multi-morbidity and their everyday work – a focused ethnography

PubMed Central

2013-01-01

Background Modern-day health systems are complex, making it difficult to assure continuity of care for older persons with multi-morbidity. One way of intervening in a health system that is leading to fragmented care is by utilising Case Management (CM). CM aims to improve co-ordination of healthcare and social services. To better understand and advance the development of CM, there is a need for additional research that provides rich descriptions of CM in practice. This knowledge is important as there could be unknown mechanisms, contextual or interpersonal, that contribute to the success or failure of a CM intervention. Furthermore, the CM intervention in this study is conducted in the context of the Swedish health system, which prior to this intervention was unfamiliar with this kind of coordinative service. The aim of this study was to explore the everyday work undertaken by case managers within a CM intervention, with a focus on their experiences. Methods The study design was qualitative and inductive, utilising a focused ethnographic approach. Data collection consisted of participant observations with field notes as well as a group interview and individual interviews with nine case managers, conducted in 2012/2013. The interviews were recorded, transcribed verbatim and subjected to thematic analysis. Results An overarching theme emerged from the data: Challenging current professional identity, with three sub-themes. The sub-themes were 1) Adjusting to familiar work in an unfamiliar role; 2) Striving to improve the health system through a new role; 3) Trust is vital to advocacy. Conclusions Findings from this study shed some light on the complexity of CM for older persons with multi-morbidity, as seen from the perspective of case managers. The findings illustrate how their everyday work as case managers represents a challenge to their current professional identity. These findings could help to understand and promote the development of CM models aimed at a population of older persons with complex health needs. PMID:24279695

A multi-temporal analysis approach for land cover mapping in support of nuclear incident response

NASA Astrophysics Data System (ADS)

Sah, Shagan; van Aardt, Jan A. N.; McKeown, Donald M.; Messinger, David W.

2012-06-01

Remote sensing can be used to rapidly generate land use maps for assisting emergency response personnel with resource deployment decisions and impact assessments. In this study we focus on constructing accurate land cover maps to map the impacted area in the case of a nuclear material release. The proposed methodology involves integration of results from two different approaches to increase classification accuracy. The data used included RapidEye scenes over Nine Mile Point Nuclear Power Station (Oswego, NY). The first step was building a coarse-scale land cover map from freely available, high temporal resolution, MODIS data using a time-series approach. In the case of a nuclear accident, high spatial resolution commercial satellites such as RapidEye or IKONOS can acquire images of the affected area. Land use maps from the two image sources were integrated using a probability-based approach. Classification results were obtained for four land classes - forest, urban, water and vegetation - using Euclidean and Mahalanobis distances as metrics. Despite the coarse resolution of MODIS pixels, acceptable accuracies were obtained using time series features. The overall accuracies using the fusion based approach were in the neighborhood of 80%, when compared with GIS data sets from New York State. The classifications were augmented using this fused approach, with few supplementary advantages such as correction for cloud cover and independence from time of year. We concluded that this method would generate highly accurate land maps, using coarse spatial resolution time series satellite imagery and a single date, high spatial resolution, multi-spectral image.

Strategies for waste management in small and medium towns of developing countries: a case study of India.

PubMed

Sundaravadivel, M; Vigneswaran, S

2003-01-01

This paper evaluates the issues of waste management in small and medium towns (SMTs) (with population in the range of 10,000-100,000) of India, and identifies the need for a multi-disciplinary approach encompassing technological, economic and financial aspects of the issues to effect improvements. A comprehensive set of cross-disciplinary strategies is suggested to improve the prevailing conditions with environmentally appropriate, economically efficient and financially self-sustaining waste management services. Based on a case study of four SMTs in the State of Tamil Nadu in India, this paper evaluates the application of the suggested strategies and offers policy recommendations.

Providing Health Sciences Services in a Joint-Use Distributed Learning Library System: An Organizational Case Study.

PubMed

Enslow, Electra; Fricke, Suzanne; Vela, Kathryn

2017-01-01

The purpose of this organizational case study is to describe the complexities librarians face when serving a multi-campus institution that supports both a joint-use library and expanding health sciences academic partnerships. In a system without a centralized health science library administration, liaison librarians are identifying dispersed programs and user groups and collaborating to define their unique service and outreach needs within a larger land-grant university. Using a team-based approach, health sciences librarians are communicating to integrate research and teaching support, systems differences across dispersed campuses, and future needs of a new community-based medical program.

Estimation of corn yield using multi-temporal optical and radar satellite data and artificial neural networks

NASA Astrophysics Data System (ADS)

Fieuzal, R.; Marais Sicre, C.; Baup, F.

2017-05-01

The yield forecasting of corn constitutes a key issue in agricultural management, particularly in the context of demographic pressure and climate change. This study presents two methods to estimate yields using artificial neural networks: a diagnostic approach based on all the satellite data acquired throughout the agricultural season, and a real-time approach, where estimates are updated after each image was acquired in the microwave and optical domains (Formosat-2, Spot-4/5, TerraSAR-X, and Radarsat-2) throughout the crop cycle. The results are based on the Multispectral Crop Monitoring experimental campaign conducted by the CESBIO (Centre d'Études de la BIOsphère) laboratory in 2010 over an agricultural region in southwestern France. Among the tested sensor configurations (multi-frequency, multi-polarization or multi-source data), the best yield estimation performance (using the diagnostic approach) is obtained with reflectance acquired in the red wavelength region, with a coefficient of determination of 0.77 and an RMSE of 6.6 q ha-1. In the real-time approach the combination of red reflectance and CHH backscattering coefficients provides the best compromise between the accuracy and earliness of the yield estimate (more than 3 months before the harvest), with an R2 of 0.69 and an RMSE of 7.0 q ha-1 during the development of the central stem. The two best yield estimates are similar in most cases (for more than 80% of the monitored fields), and the differences are related to discrepancies in the crop growth cycle and/or the consequences of pests.

Designing a capacitated multi-configuration logistics network under disturbances and parameter uncertainty: a real-world case of a drug supply chain

NASA Astrophysics Data System (ADS)

Shishebori, Davood; Babadi, Abolghasem Yousefi

2018-03-01

This study investigates the reliable multi-configuration capacitated logistics network design problem (RMCLNDP) under system disturbances, which relates to locating facilities, establishing transportation links, and also allocating their limited capacities to the customers conducive to provide their demand on the minimum expected total cost (including locating costs, link constructing costs, and also expected costs in normal and disturbance conditions). In addition, two types of risks are considered; (I) uncertain environment, (II) system disturbances. A two-level mathematical model is proposed for formulating of the mentioned problem. Also, because of the uncertain parameters of the model, an efficacious possibilistic robust optimization approach is utilized. To evaluate the model, a drug supply chain design (SCN) is studied. Finally, an extensive sensitivity analysis was done on the critical parameters. The obtained results show that the efficiency of the proposed approach is suitable and is worthwhile for analyzing the real practical problems.

Pareto frontier analyses based decision making tool for transportation of hazardous waste.

PubMed

Das, Arup; Mazumder, T N; Gupta, A K

2012-08-15

Transportation of hazardous wastes through a region poses immense threat on the development along its road network. The risk to the population, exposed to such activities, has been documented in the past. However, a comprehensive framework for routing hazardous wastes has often been overlooked. A regional Hazardous Waste Management scheme should incorporate a comprehensive framework for hazardous waste transportation. This framework would incorporate the various stakeholders involved in decision making. Hence, a multi-objective approach is required to safeguard the interest of all the concerned stakeholders. The objective of this study is to design a methodology for routing of hazardous wastes between the generating units and the disposal facilities through a capacity constrained network. The proposed methodology uses posteriori method with multi-objective approach to find non-dominated solutions for the system consisting of multiple origins and destinations. A case study of transportation of hazardous wastes in Kolkata Metropolitan Area has also been provided to elucidate the methodology. Copyright © 2012 Elsevier B.V. All rights reserved.

Prospects for direct social perception: a multi-theoretical integration to further the science of social cognition

PubMed Central

Wiltshire, Travis J.; Lobato, Emilio J. C.; McConnell, Daniel S.; Fiore, Stephen M.

2015-01-01

In this paper we suggest that differing approaches to the science of social cognition mirror the arguments between radical embodied and traditional approaches to cognition. We contrast the use in social cognition of theoretical inference and mental simulation mechanisms with approaches emphasizing a direct perception of others’ mental states. We build from a recent integrative framework unifying these divergent perspectives through the use of dual-process theory and supporting social neuroscience research. Our elaboration considers two complementary notions of direct perception: one primarily stemming from ecological psychology and the other from enactive cognition theory. We use this as the foundation from which to offer an account of the informational basis for social information and assert a set of research propositions to further the science of social cognition. In doing so, we point out how perception of the minds of others can be supported in some cases by lawful information, supporting direct perception of social affordances and perhaps, mental states, and in other cases by cues that support indirect perceptual inference. Our goal is to extend accounts of social cognition by integrating advances across disciplines to provide a multi-level and multi-theoretic description that can advance this field and offer a means through which to reconcile radical embodied and traditional approaches to cognitive neuroscience. PMID:25709572

Activity recognition from minimal distinguishing subsequence mining

NASA Astrophysics Data System (ADS)

Iqbal, Mohammad; Pao, Hsing-Kuo

2017-08-01

Human activity recognition is one of the most important research topics in the era of Internet of Things. To separate different activities given sensory data, we utilize a Minimal Distinguishing Subsequence (MDS) mining approach to efficiently find distinguishing patterns among different activities. We first transform the sensory data into a series of sensor triggering events and operate the MDS mining procedure afterwards. The gap constraints are also considered in the MDS mining. Given the multi-class nature of most activity recognition tasks, we modify the MDS mining approach from a binary case to a multi-class one to fit the need for multiple activity recognition. We also study how to select the best parameter set including the minimal and the maximal support thresholds in finding the MDSs for effective activity recognition. Overall, the prediction accuracy is 86.59% on the van Kasteren dataset which consists of four different activities for recognition.

Comparison of the application of B-mode and strain elastography ultrasound in the estimation of lymph node metastasis of papillary thyroid carcinoma based on a radiomics approach.

PubMed

Liu, Tongtong; Ge, Xifeng; Yu, Jinhua; Guo, Yi; Wang, Yuanyuan; Wang, Wenping; Cui, Ligang

2018-06-21

B-mode ultrasound (B-US) and strain elastography ultrasound (SE-US) images have a potential to distinguish thyroid tumor with different lymph node (LN) status. The purpose of our study is to investigate whether the application of multi-modality images including B-US and SE-US can improve the discriminability of thyroid tumor with LN metastasis based on a radiomics approach. Ultrasound (US) images including B-US and SE-US images of 75 papillary thyroid carcinoma (PTC) cases were retrospectively collected. A radiomics approach was developed in this study to estimate LNs status of PTC patients. The approach included image segmentation, quantitative feature extraction, feature selection and classification. Three feature sets were extracted from B-US, SE-US, and multi-modality containing B-US and SE-US. They were used to evaluate the contribution of different modalities. A total of 684 radiomics features have been extracted in our study. We used sparse representation coefficient-based feature selection method with 10-bootstrap to reduce the dimension of feature sets. Support vector machine with leave-one-out cross-validation was used to build the model for estimating LN status. Using features extracted from both B-US and SE-US, the radiomics-based model produced an area under the receiver operating characteristic curve (AUC) [Formula: see text] 0.90, accuracy (ACC) [Formula: see text] 0.85, sensitivity (SENS) [Formula: see text] 0.77 and specificity (SPEC) [Formula: see text] 0.88, which was better than using features extracted from B-US or SE-US separately. Multi-modality images provided more information in radiomics study. Combining use of B-US and SE-US could improve the LN metastasis estimation accuracy for PTC patients.

Bottom-Up Analysis of Single-Case Research Designs

ERIC Educational Resources Information Center

Parker, Richard I.; Vannest, Kimberly J.

2012-01-01

This paper defines and promotes the qualities of a "bottom-up" approach to single-case research (SCR) data analysis. Although "top-down" models, for example, multi-level or hierarchical linear models, are gaining momentum and have much to offer, interventionists should be cautious about analyses that are not easily understood, are not governed by…

A multi-scale framework to link remotely sensed metrics with socioeconomic data

NASA Astrophysics Data System (ADS)

Watmough, Gary; Svenning, Jens-Christian; Palm, Cheryl; Sullivan, Clare; Danylo, Olha; McCallum, Ian

2017-04-01

There is increasing interest in the use of remotely sensed satellite data for estimating human poverty as it can bridge data gaps that prevent fine scale monitoring of development goals across large areas. The ways in which metrics derived from satellite imagery are linked with socioeconomic data are crucial for accurate estimation of poverty. Yet, to date, approaches in the literature linking satellite metrics with socioeconomic data are poorly characterized. Typically, approaches use a GIS approach such as circular buffer zones around a village or household or an administrative boundary such as a district or census enumeration area. These polygons are then used to extract environmental data from satellite imagery and related to the socioeconomic data in statistical analyses. The use of a single polygon to link environment and socioeconomic data is inappropriate in coupled human-natural systems as processes operate over multiple scales. Human interactions with the environment occur at multiple levels from individual (household) access to agricultural plots adjacent to homes, to communal access to common pool resources (CPR) such as forests at the village level. Here, we present a multi-scale framework that explicitly considers how people use the landscape. The framework is presented along with a case study example in Kenya. The multi-scale approach could enhance the modelling of human-environment interactions which will have important consequences for monitoring the sustainable development goals for human livelihoods and biodiversity conservation.

Process simulation and dynamic control for marine oily wastewater treatment using UV irradiation.

PubMed

Jing, Liang; Chen, Bing; Zhang, Baiyu; Li, Pu

2015-09-15

UV irradiation and advanced oxidation processes have been recently regarded as promising solutions in removing polycyclic aromatic hydrocarbons (PAHs) from marine oily wastewater. However, such treatment methods are generally not sufficiently understood in terms of reaction mechanisms, process simulation and process control. These deficiencies can drastically hinder their application in shipping and offshore petroleum industries which produce bilge/ballast water and produced water as the main streams of marine oily wastewater. In this study, the factorial design of experiment was carried out to investigate the degradation mechanism of a typical PAH, namely naphthalene, under UV irradiation in seawater. Based on the experimental results, a three-layer feed-forward artificial neural network simulation model was developed to simulate the treatment process and to forecast the removal performance. A simulation-based dynamic mixed integer nonlinear programming (SDMINP) approach was then proposed to intelligently control the treatment process by integrating the developed simulation model, genetic algorithm and multi-stage programming. The applicability and effectiveness of the developed approach were further tested though a case study. The experimental results showed that the influences of fluence rate and temperature on the removal of naphthalene were greater than those of salinity and initial concentration. The developed simulation model could well predict the UV-induced removal process under varying conditions. The case study suggested that the SDMINP approach, with the aid of the multi-stage control strategy, was able to significantly reduce treatment cost when comparing to the traditional single-stage process optimization. The developed approach and its concept/framework have high potential of applicability in other environmental fields where a treatment process is involved and experimentation and modeling are used for process simulation and control. Copyright © 2015 Elsevier Ltd. All rights reserved.

Methodological Considerations for an Evolving Model of Institutional Research.

ERIC Educational Resources Information Center

Jones, Timothy B.; Essien-Barrett, Barbara; Gill, Peggy B.

A multi-case study was used in the self-study of three programs within an academic department of a mid-sized Southern university. Multi-case methodology as a form of self-study encourages a process of self-renewal and programmatic change as it defines an active stakeholder role. The participants in the three case studies were university faculty…

Patient-centred performance monitoring systems and multi-agency care provision: a case study using a stakeholder participative approach.

PubMed

Connell, N A; Goddard, A R; Philp, I; Bray, J

1998-05-01

We describe the processes involved in the development of an information system which can assess how care given by a number of agencies could be monitored by those agencies. In particular, it addresses the problem of sharing information as the boundaries of each agency are crossed. It focuses on the care of one specific patient group--the rehabilitation of elderly patients in the community, which provided an ideal multi-agency setting. It also describes: how a stakeholder participative approach to information system development was undertaken, based in part on the Soft Systems Methodology (SSM) approach (Checkland, 1981, 1990); some of the difficulties encountered in using such an approach; and the ways in which these were addressed. The paper goes on to describe an assessment tool called SCARS (the Southampton Community Ability Rating Scale). It concludes by reflecting on the management lessons arising from this project. It also observes, inter alia, how stakeholders have a strong preference for simpler, non-IT based systems, and comments on the difficulties encountered by stakeholders in attempting to reconcile their perceptions of the needs of their discipline or specialty with a more patient-centred approach of an integrated system.

Multi-GPU implementation of a VMAT treatment plan optimization algorithm.

PubMed

Tian, Zhen; Peng, Fei; Folkerts, Michael; Tan, Jun; Jia, Xun; Jiang, Steve B

2015-06-01

Volumetric modulated arc therapy (VMAT) optimization is a computationally challenging problem due to its large data size, high degrees of freedom, and many hardware constraints. High-performance graphics processing units (GPUs) have been used to speed up the computations. However, GPU's relatively small memory size cannot handle cases with a large dose-deposition coefficient (DDC) matrix in cases of, e.g., those with a large target size, multiple targets, multiple arcs, and/or small beamlet size. The main purpose of this paper is to report an implementation of a column-generation-based VMAT algorithm, previously developed in the authors' group, on a multi-GPU platform to solve the memory limitation problem. While the column-generation-based VMAT algorithm has been previously developed, the GPU implementation details have not been reported. Hence, another purpose is to present detailed techniques employed for GPU implementation. The authors also would like to utilize this particular problem as an example problem to study the feasibility of using a multi-GPU platform to solve large-scale problems in medical physics. The column-generation approach generates VMAT apertures sequentially by solving a pricing problem (PP) and a master problem (MP) iteratively. In the authors' method, the sparse DDC matrix is first stored on a CPU in coordinate list format (COO). On the GPU side, this matrix is split into four submatrices according to beam angles, which are stored on four GPUs in compressed sparse row format. Computation of beamlet price, the first step in PP, is accomplished using multi-GPUs. A fast inter-GPU data transfer scheme is accomplished using peer-to-peer access. The remaining steps of PP and MP problems are implemented on CPU or a single GPU due to their modest problem scale and computational loads. Barzilai and Borwein algorithm with a subspace step scheme is adopted here to solve the MP problem. A head and neck (H&N) cancer case is then used to validate the authors' method. The authors also compare their multi-GPU implementation with three different single GPU implementation strategies, i.e., truncating DDC matrix (S1), repeatedly transferring DDC matrix between CPU and GPU (S2), and porting computations involving DDC matrix to CPU (S3), in terms of both plan quality and computational efficiency. Two more H&N patient cases and three prostate cases are used to demonstrate the advantages of the authors' method. The authors' multi-GPU implementation can finish the optimization process within ∼ 1 min for the H&N patient case. S1 leads to an inferior plan quality although its total time was 10 s shorter than the multi-GPU implementation due to the reduced matrix size. S2 and S3 yield the same plan quality as the multi-GPU implementation but take ∼4 and ∼6 min, respectively. High computational efficiency was consistently achieved for the other five patient cases tested, with VMAT plans of clinically acceptable quality obtained within 23-46 s. Conversely, to obtain clinically comparable or acceptable plans for all six of these VMAT cases that the authors have tested in this paper, the optimization time needed in a commercial TPS system on CPU was found to be in an order of several minutes. The results demonstrate that the multi-GPU implementation of the authors' column-generation-based VMAT optimization can handle the large-scale VMAT optimization problem efficiently without sacrificing plan quality. The authors' study may serve as an example to shed some light on other large-scale medical physics problems that require multi-GPU techniques.

StackSplit - a plugin for multi-event shear wave splitting analyses in SplitLab

NASA Astrophysics Data System (ADS)

Grund, Michael

2017-04-01

The SplitLab package (Wüstefeld et al., Computers and Geosciences, 2008), written in MATLAB, is a powerful and widely used tool for analysing seismological shear wave splitting of single event measurements. However, in many cases, especially temporary station deployments close to seaside or for recordings affected by strong anthropogenic noise, only multi-event approaches provide stable and reliable splitting results. In order to extend the original SplitLab environment for such analyses, I present the StackSplit plugin that can easily be implemented within the well accepted main program. StackSplit grants easy access to several different analysis approaches within SplitLab, including a new multiple waveform based inversion method as well as the most established standard stacking procedures. The possibility to switch between different analysis approaches at any time allows the user for the most flexible processing of individual multi-event splitting measurements for a single recording station. Besides the provided functions of the plugin, no other external program is needed for the multi-event analyses since StackSplit performs within the available SplitLab structure.

Single- and multi-channel underwater acoustic communication channel capacity: a computational study.

PubMed

Hayward, Thomas J; Yang, T C

2007-09-01

Acoustic communication channel capacity determines the maximum data rate that can be supported by an acoustic channel for a given source power and source/receiver configuration. In this paper, broadband acoustic propagation modeling is applied to estimate the channel capacity for a time-invariant shallow-water waveguide for a single source-receiver pair and for vertical source and receiver arrays. Without bandwidth constraints, estimated single-input, single-output (SISO) capacities approach 10 megabitss at 1 km range, but beyond 2 km range they decay at a rate consistent with previous estimates by Peloquin and Leinhos (unpublished, 1997), which were based on a sonar equation calculation. Channel capacities subject to source bandwidth constraints are approximately 30-90% lower than for the unconstrained case, and exhibit a significant wind speed dependence. Channel capacity is investigated for single-input, multi-output (SIMO) and multi-input, multi-output (MIMO) systems, both for finite arrays and in the limit of a dense array spanning the entire water column. The limiting values of the SIMO and MIMO channel capacities for the modeled environment are found to be about four times higher and up to 200-400 times higher, respectively, than for the SISO case. Implications for underwater acoustic communication systems are discussed.

Optimal subsystem approach to multi-qubit quantum state discrimination and experimental investigation

NASA Astrophysics Data System (ADS)

Xue, ShiChuan; Wu, JunJie; Xu, Ping; Yang, XueJun

2018-02-01

Quantum computing is a significant computing capability which is superior to classical computing because of its superposition feature. Distinguishing several quantum states from quantum algorithm outputs is often a vital computational task. In most cases, the quantum states tend to be non-orthogonal due to superposition; quantum mechanics has proved that perfect outcomes could not be achieved by measurements, forcing repetitive measurement. Hence, it is important to determine the optimum measuring method which requires fewer repetitions and a lower error rate. However, extending current measurement approaches mainly aiming at quantum cryptography to multi-qubit situations for quantum computing confronts challenges, such as conducting global operations which has considerable costs in the experimental realm. Therefore, in this study, we have proposed an optimum subsystem method to avoid these difficulties. We have provided an analysis of the comparison between the reduced subsystem method and the global minimum error method for two-qubit problems; the conclusions have been verified experimentally. The results showed that the subsystem method could effectively discriminate non-orthogonal two-qubit states, such as separable states, entangled pure states, and mixed states; the cost of the experimental process had been significantly reduced, in most circumstances, with acceptable error rate. We believe the optimal subsystem method is the most valuable and promising approach for multi-qubit quantum computing applications.

Program to Optimize Simulated Trajectories II (POST2) Surrogate Models for Mars Ascent Vehicle (MAV) Performance Assessment

NASA Technical Reports Server (NTRS)

Zwack, M. R.; Dees, P. D.; Thomas, H. D.; Polsgrove, T. P.; Holt, J. B.

2017-01-01

The primary purpose of the multiPOST tool is to enable the execution of much larger sets of vehicle cases to allow for broader trade space exploration. However, this exploration is not achieved solely with the increased case throughput. The multiPOST tool is applied to carry out a Design of Experiments (DOE), which is a set of cases that have been structured to capture a maximum amount of information about the design space with minimal computational effort. The results of the DOE are then used to fit a surrogate model, ultimately enabling parametric design space exploration. The approach used for the MAV study includes both DOE and surrogate modeling. First, the primary design considerations for the vehicle were used to develop the variables and ranges for the multiPOST DOE. The final set of DOE variables were carefully selected in order to capture the desired vehicle trades and take into account any special considerations for surrogate modeling. Next, the DOE sets were executed through multiPOST. Following successful completion of the DOE cases, a manual verification trial was performed. The trial involved randomly selecting cases from the DOE set and running them by hand. The results from the human analyst's run and multiPOST were then compared to ensure that the automated runs were being executed properly. Completion of the verification trials was then followed by surrogate model fitting. After fits to the multiPOST data were successfully created, the surrogate models were used as a stand-in for POST2 to carry out the desired MAV trades. Using the surrogate models in lieu of POST2 allowed for visualization of vehicle sensitivities to the input variables as well as rapid evaluation of vehicle performance. Although the models introduce some error into the output of the trade study, they were very effective at identifying areas of interest within the trade space for further refinement by human analysts. The next section will cover all of the ground rules and assumptions associated with DOE setup and multiPOST execution. Section 3.1 gives the final DOE variables and ranges, while section 3.2 addresses the POST2 specific assumptions. The results of the verification trials are given in section 4. Section 5 gives the surrogate model fitting results, including the goodness-of-fit metrics for each fit. Finally, the MAV specific results are discussed in section 6.

Only complementary voices tell the truth: a reevaluation of validity in multi-informant approaches of child and adolescent clinical assessments.

PubMed

Kaurin, Aleksandra; Egloff, Boris; Stringaris, Argyris; Wessa, Michèle

2016-08-01

Multi-informant approaches are thought to be key to clinical assessment. Classical theories of psychological measurements assume that only convergence among different informants' reports allows for an estimate of the true nature and causes of clinical presentations. However, the integration of multiple accounts is fraught with problems because findings in child and adolescent psychiatry do not conform to the fundamental expectation of convergence. Indeed, reports provided by different sources (self, parents, teachers, peers) share little variance. Moreover, in some cases informant divergence may be meaningful and not error variance. In this review, we give an overview of conceptual and theoretical foundations of valid multi-informant assessment and discuss why our common concepts of validity need revaluation.

A Framework of Multi Objectives Negotiation for Dynamic Supply Chain Model

NASA Astrophysics Data System (ADS)

Chai, Jia Yee; Sakaguchi, Tatsuhiko; Shirase, Keiichi

Trends of globalization and advances in Information Technology (IT) have created opportunity in collaborative manufacturing across national borders. A dynamic supply chain utilizes these advances to enable more flexibility in business cooperation. This research proposes a concurrent decision making framework for a three echelons dynamic supply chain model. The dynamic supply chain is formed by autonomous negotiation among agents based on multi agents approach. Instead of generating negotiation aspects (such as amount, price and due date) arbitrary, this framework proposes to utilize the information available at operational level of an organization in order to generate realistic negotiation aspect. The effectiveness of the proposed model is demonstrated by various case studies.

A new disaster victim identification management strategy targeting "near identification-threshold" cases: Experiences from the Boxing Day tsunami.

PubMed

Wright, Kirsty; Mundorff, Amy; Chaseling, Janet; Forrest, Alexander; Maguire, Christopher; Crane, Denis I

2015-05-01

The international disaster victim identification (DVI) response to the Boxing Day tsunami, led by the Royal Thai Police in Phuket, Thailand, was one of the largest and most complex in DVI history. Referred to as the Thai Tsunami Victim Identification operation, the group comprised a multi-national, multi-agency, and multi-disciplinary team. The traditional DVI approach proved successful in identifying a large number of victims quickly. However, the team struggled to identify certain victims due to incomplete or poor quality ante-mortem and post-mortem data. In response to these challenges, a new 'near-threshold' DVI management strategy was implemented to target presumptive identifications and improve operational efficiency. The strategy was implemented by the DNA Team, therefore DNA kinship matches that just failed to reach the reporting threshold of 99.9% were prioritized, however the same approach could be taken by targeting, for example, cases with partial fingerprint matches. The presumptive DNA identifications were progressively filtered through the Investigation, Dental and Fingerprint Teams to add additional information necessary to either strengthen or conclusively exclude the identification. Over a five-month period 111 victims from ten countries were identified using this targeted approach. The new identifications comprised 87 adults, 24 children and included 97 Thai locals. New data from the Fingerprint Team established nearly 60% of the total near-threshold identifications and the combined DNA/Physical method was responsible for over 30%. Implementing the new strategy, targeting near-threshold cases, had positive management implications. The process initiated additional ante-mortem information collections, and established a much-needed, distinct "end-point" for unresolved cases. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Using Case Study Multi-Methods to Investigate Close(r) Collaboration: Course-Based Tutoring and the Directive/Nondirective Instructional Continuum

ERIC Educational Resources Information Center

Corbett, Steven J.

2011-01-01

This essay presents case studies of "course-based tutoring" (CBT) and one-to-one tutorials in two sections of developmental first-year composition (FYC) at a large West Coast research university. The author's study uses a combination of rhetorical and discourse analyses and ethnographic and case study multi-methods to investigate both…

Multi-Stakeholder Dynamic Optimization Framework for System-of-Systems Development and Evolution

NASA Astrophysics Data System (ADS)

Fang, Zhemei

Architecture design for an "acknowledged" System-of-Systems (SoS), under performance uncertainty and constrained resources, remains a difficult problem. Composing an SoS via a proper mix of systems under the special control structure of an "acknowledged" SoS requires efficient distribution of the limited resources. However, due to the special traits of SoS, achieving an efficient distribution of the resources is not a trivial challenge. Currently, the major causes that lead to inefficient resource management for an "acknowledged" SoS include: 1) no central SoS managers with absolute authority to address conflict; 2) difficult balance between current and future decisions; 3) various uncertainties during development and operations (e.g., technology maturation, policy stability); 4) diverse sources of the resources; 5) high complexity in efficient formulation and computation due to the previous four factors. Although it is beyond the scope of this dissertation to simultaneously address all the five items, the thesis will focus on the first, second, and fifth points, and partially cover the third point. In a word, the dissertation aims to develop a generic framework for "acknowledged" SoS that leads to appropriate mathematical formulation and a solution approach that generates a near-optimal set of multi-stage architectural decisions with limited collaboration between conflicted and independent stakeholders. This dissertation proposes a multi-stakeholder dynamic optimization (MUSTDO) method, which integrates approximate dynamic programming and transfer contract coordination mechanism. The method solves a multi-stage architecture selection problem with an embedded formal, but simple, transfer contract coordination mechanism to address resource conflict. Once the values of transfer contract are calculated appropriately, even though the SoS participants make independent decisions, the aggregate solutions are close to the solutions from a hypothetical ideal centralized case where the top-level SoS managers have full authority. In addition, the thesis builds the bridge between a given SoS problem and the mathematical interpretations of the MUSTDO method using a three-phase approach for real world applications. The method is applied to two case studies: one in the defense realm and one in the commercial realm. The first application uses a naval warfare scenario to demonstrate that the aggregated capabilities in the decentralized case using MUSTDO method are close to the aggregated capabilities in a hypothetical centralized case. This evidence demonstrates that the MUSTDO method can help approach the SoS-level optimality with limited funding resource even if the participants make independent decisions. The solution also provides suggestions to the participants about the sequence of architecting decisions and the amount of transfer contract to be sent out to maximize individual capability over time. The suggested decisions incorporate the potential capability increase in the future, which differentiates itself from allocating all the resources to the current development. The quantified numbers of transfer contract in this case study are equivalent capabilities that are relevant to equipment loan or technology transfer. The second case study applies the MUSTDO-based framework to address a multi-airline fleet allocation problem with emissions allowances constraint provided by the regulators. Two representative airlines including the low-cost airline and the legacy airline aim to maximize individual profit by allocating six type of aircraft to a given ten-route network under the emissions constraint. Both the deterministic and stochastic experiments verify the effectiveness of the MUSTDO method by comparing the profit in the decentralized case and profit in a utopian centralized case. Meanwhile, sensitivity studies demonstrate that higher minimum demand requirement and lower discount factor can further improve the efficiency of emissions allowances utilization in MUSTDO method. Comparing to an alternate grandfathering approach, the MUSTDO method can guarantee a high-level efficiency of resource allocation by avoiding failed allocation decisions due to inaccurate information for the regulators. In summary, the framework aids the SoS managers and participants in the selection of the best architecture over a period of time with limited resources; the framework helps the decision makers to understand how they can affect each other and cooperate to achieve a more efficient solution without sharing full information. The major contribution of this dissertation includes: 1) provide a method to address multi-stage SoS composition decisions over time with resource constraint; 2) provide a method to manage resource conflict for stakeholders in an "acknowledged" system-of-systems; 2) provide a new perspective of long-term interactions between stakeholders in an SoS; 3) provide procedural framework to implement the MUSTDO method; 4) provide comparison of different applications of the MUSTDO framework in distinct fields.

Identifying natural compounds as multi-target-directed ligands against Alzheimer's disease: an in silico approach.

PubMed

Ambure, Pravin; Bhat, Jyotsna; Puzyn, Tomasz; Roy, Kunal

2018-04-23

Alzheimer's disease (AD) is a multi-factorial disease, which can be simply outlined as an irreversible and progressive neurodegenerative disorder with an unclear root cause. It is a major cause of dementia in old aged people. In the present study, utilizing the structural and biological activity information of ligands for five important and mostly studied vital targets (i.e. cyclin-dependant kinase 5, β-secretase, monoamine oxidase B, glycogen synthase kinase 3β, acetylcholinesterase) that are believed to be effective against AD, we have developed five classification models using linear discriminant analysis (LDA) technique. Considering the importance of data curation, we have given more attention towards the chemical and biological data curation, which is a difficult task especially in case of big data-sets. Thus, to ease the curation process we have designed Konstanz Information Miner (KNIME) workflows, which are made available at http://teqip.jdvu.ac.in/QSAR_Tools/ . The developed models were appropriately validated based on the predictions for experiment derived data from test sets, as well as true external set compounds including known multi-target compounds. The domain of applicability for each classification model was checked based on a confidence estimation approach. Further, these validated models were employed for screening of natural compounds collected from the InterBioScreen natural database ( https://www.ibscreen.com/natural-compounds ). Further, the natural compounds that were categorized as 'actives' in at least two classification models out of five developed models were considered as multi-target leads, and these compounds were further screened using the drug-like filter, molecular docking technique and then thoroughly analyzed using molecular dynamics studies. Finally, the most potential multi-target natural compounds against AD are suggested.

The Effectiveness of Simulated Robots for Supporting the Learning of Introductory Programming: A Multi-Case Case Study

ERIC Educational Resources Information Center

Major, Louis; Kyriacou, Theocharis; Brereton, Pearl

2014-01-01

This work investigates the effectiveness of simulated robots as tools to support the learning of programming. After the completion of a systematic review and exploratory research, a multi-case case study was undertaken. A simulator, named Kebot, was developed and used to run four 10-hour programming workshops. Twenty-three student participants…

Influence of Cultural, Organizational, and Automation Capability on Human Automation Trust: A Case Study of Auto-GCAS Experimental Test Pilots

NASA Technical Reports Server (NTRS)

Koltai, Kolina; Ho, Nhut; Masequesmay, Gina; Niedober, David; Skoog, Mark; Cacanindin, Artemio; Johnson, Walter; Lyons, Joseph

2014-01-01

This paper discusses a case study that examined the influence of cultural, organizational and automation capability upon human trust in, and reliance on, automation. In particular, this paper focuses on the design and application of an extended case study methodology, and on the foundational lessons revealed by it. Experimental test pilots involved in the research and development of the US Air Force's newly developed Automatic Ground Collision Avoidance System served as the context for this examination. An eclectic, multi-pronged approach was designed to conduct this case study, and proved effective in addressing the challenges associated with the case's politically sensitive and military environment. Key results indicate that the system design was in alignment with pilot culture and organizational mission, indicating the potential for appropriate trust development in operational pilots. These include the low-vulnerability/ high risk nature of the pilot profession, automation transparency and suspicion, system reputation, and the setup of and communications among organizations involved in the system development.

An Extended Case Study Methoology for Investigating Influence of Cultural, Organizational, and Automation Factors on Human-Automation Trust

NASA Technical Reports Server (NTRS)

Koltai, Kolina Sun; Ho, Nhut; Masequesmay, Gina; Niedober, David; Skoog, Mark; Johnson, Walter; Cacanindin, Artemio

2014-01-01

This paper discusses a case study that examined the influence of cultural, organizational and automation capability upon human trust in, and reliance on, automation. In particular, this paper focuses on the design and application of an extended case study methodology, and on the foundational lessons revealed by it. Experimental test pilots involved in the research and development of the US Air Forces newly developed Automatic Ground Collision Avoidance System served as the context for this examination. An eclectic, multi-pronged approach was designed to conduct this case study, and proved effective in addressing the challenges associated with the cases politically sensitive and military environment. Key results indicate that the system design was in alignment with pilot culture and organizational mission, indicating the potential for appropriate trust development in operational pilots. These include the low-vulnerabilityhigh risk nature of the pilot profession, automation transparency and suspicion, system reputation, and the setup of and communications among organizations involved in the system development.

Weather and seasonal climate prediction for South America using a multi-model superensemble

NASA Astrophysics Data System (ADS)

Chaves, Rosane R.; Ross, Robert S.; Krishnamurti, T. N.

2005-11-01

This work examines the feasibility of weather and seasonal climate predictions for South America using the multi-model synthetic superensemble approach for climate, and the multi-model conventional superensemble approach for numerical weather prediction, both developed at Florida State University (FSU). The effect on seasonal climate forecasts of the number of models used in the synthetic superensemble is investigated. It is shown that the synthetic superensemble approach for climate and the conventional superensemble approach for numerical weather prediction can reduce the errors over South America in seasonal climate prediction and numerical weather prediction.For climate prediction, a suite of 13 models is used. The forecast lead-time is 1 month for the climate forecasts, which consist of precipitation and surface temperature forecasts. The multi-model ensemble is comprised of four versions of the FSU-Coupled Ocean-Atmosphere Model, seven models from the Development of a European Multi-model Ensemble System for Seasonal to Interannual Prediction (DEMETER), a version of the Community Climate Model (CCM3), and a version of the predictive Ocean Atmosphere Model for Australia (POAMA). The results show that conditions over South America are appropriately simulated by the Florida State University Synthetic Superensemble (FSUSSE) in comparison to observations and that the skill of this approach increases with the use of additional models in the ensemble. When compared to observations, the forecasts are generally better than those from both a single climate model and the multi-model ensemble mean, for the variables tested in this study.For numerical weather prediction, the conventional Florida State University Superensemble (FSUSE) is used to predict the mass and motion fields over South America. Predictions of mean sea level pressure, 500 hPa geopotential height, and 850 hPa wind are made with a multi-model superensemble comprised of six global models for the period January, February, and December of 2000. The six global models are from the following forecast centers: FSU, Bureau of Meteorology Research Center (BMRC), Japan Meteorological Agency (JMA), National Centers for Environmental Prediction (NCEP), Naval Research Laboratory (NRL), and Recherche en Prevision Numerique (RPN). Predictions of precipitation are made for the period January, February, and December of 2001 with a multi-analysis-multi-model superensemble where, in addition to the six forecast models just mentioned, five additional versions of the FSU model are used in the ensemble, each with a different initialization (analysis) based on different physical initialization procedures. On the basis of observations, the results show that the FSUSE provides the best forecasts of the mass and motion field variables to forecast day 5, when compared to both the models comprising the ensemble and the multi-model ensemble mean during the wet season of December-February over South America. Individual case studies show that the FSUSE provides excellent predictions of rainfall for particular synoptic events to forecast day 3. Copyright

SU-D-206-01: Employing a Novel Consensus Optimization Strategy to Achieve Iterative Cone Beam CT Reconstruction On a Multi-GPU Platform

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, B; Southern Medical University, Guangzhou, Guangdong; Tian, Z

Purpose: While compressed sensing-based cone-beam CT (CBCT) iterative reconstruction techniques have demonstrated tremendous capability of reconstructing high-quality images from undersampled noisy data, its long computation time still hinders wide application in routine clinic. The purpose of this study is to develop a reconstruction framework that employs modern consensus optimization techniques to achieve CBCT reconstruction on a multi-GPU platform for improved computational efficiency. Methods: Total projection data were evenly distributed to multiple GPUs. Each GPU performed reconstruction using its own projection data with a conventional total variation regularization approach to ensure image quality. In addition, the solutions from GPUs were subjectmore » to a consistency constraint that they should be identical. We solved the optimization problem with all the constraints considered rigorously using an alternating direction method of multipliers (ADMM) algorithm. The reconstruction framework was implemented using OpenCL on a platform with two Nvidia GTX590 GPU cards, each with two GPUs. We studied the performance of our method and demonstrated its advantages through a simulation case with a NCAT phantom and an experimental case with a Catphan phantom. Result: Compared with the CBCT images reconstructed using conventional FDK method with full projection datasets, our proposed method achieved comparable image quality with about one third projection numbers. The computation time on the multi-GPU platform was ∼55 s and ∼ 35 s in the two cases respectively, achieving a speedup factor of ∼ 3.0 compared with single GPU reconstruction. Conclusion: We have developed a consensus ADMM-based CBCT reconstruction method which enabled performing reconstruction on a multi-GPU platform. The achieved efficiency made this method clinically attractive.« less

Territory management an appropriate approach for taking into account dynamic risks

NASA Astrophysics Data System (ADS)

Fernandez, M.; Ruegg, J.

2012-04-01

The territorial approach in risk analysis is well established in scientific communications in recent years, especially in the francophone literature. It is an especially appropriate approach for exploring a large number of criteria and factors influencing, on the territory, the composition of the vulnerabilities and risks. In these sense, this approach is appropriate to identify not only risks due to natural hazards but also social and environmental risks. Our case study explores the catastrophic landslide, a collapse of 6 millions cubic meters of rock in Los Chorros, in the municipality of San Cristobal Verapaz-Guatemala, in January 2009. We demonstrate that the same natural hazard has different consequences within this territory and may also increase or even create new vulnerabilities and risks for the population. The analysis shows that the same event can endanger various aspects of the territory: resources, functions (agriculture, or houses uses for example) and allocations and highlights the different types of vulnerabilities that land users (i.e., farmers, merchants transport drivers) face. To resolve a post-disaster situation, the actors choose one vulnerability among a set of vulnerabilities (in a multi-vulnerability context) and with this choice they define their own acceptable risk limits. To give an example, the transport driver choose to reduce the economic vulnerability when going to the local market and crossing the landslide (physical vulnerability). In the context of a developing country with weak development and limited resources, land users that become the Risk managers after the disaster are compelled to prioritize between different actions for reducing risks This study provides a novel approach to risk management by adding a political science and geography dimension through the territory approach for improving our understanding of multi-hazard and multi-risk management. Based on findings from this case study, this work asserts that risk is not unequivocal. On the contrary, in the case of the Los Chorros, the "primary" risk (the landslide), as evaluated by the authorities, was not perceived as such by the local community, which prioritized economic risks by creating their own road through the landslide area in defiance of authorities. In other words, certain attributes and characteristics of risk will be emphasized by some actors over others, (i.e. economic considerations over the perceived probability of another landslide). Their priorities will depend on their needs and mandates and as priorities change, so individual definitions of risk may change over time. This paper demonstrates that the risk is not uniform, that multiple risks persist especially in a developing country context becomes diffuse, changes or endures because it depends on the implications on the territory and on the risk definition made by the actors. The risk is variable, the result of a choice because its existence is attributed by the characteristics or criteria of vulnerability fostered by actors in their territories. Finally, the case study demonstrates that in developing countries, actors are forced to address and prioritize multiple risks due to limited resources. In this context, the challenge for managers of natural hazards is to move from risk management in the strict sense (i.e., pure hazard approach) to a broader risk management, taking into consideration what is important for the society and for the functioning of systems. Territory management in this sense is an appropriate approach for taking into account multiple stakeholder priorities, their relationships, available resources and limitations.

Multi-model ensemble hydrological simulation using a BP Neural Network for the upper Yalongjiang River Basin, China

NASA Astrophysics Data System (ADS)

Li, Zhanjie; Yu, Jingshan; Xu, Xinyi; Sun, Wenchao; Pang, Bo; Yue, Jiajia

2018-06-01

Hydrological models are important and effective tools for detecting complex hydrological processes. Different models have different strengths when capturing the various aspects of hydrological processes. Relying on a single model usually leads to simulation uncertainties. Ensemble approaches, based on multi-model hydrological simulations, can improve application performance over single models. In this study, the upper Yalongjiang River Basin was selected for a case study. Three commonly used hydrological models (SWAT, VIC, and BTOPMC) were selected and used for independent simulations with the same input and initial values. Then, the BP neural network method was employed to combine the results from the three models. The results show that the accuracy of BP ensemble simulation is better than that of the single models.

A study of pilot modeling in multi-controller tasks

NASA Technical Reports Server (NTRS)

Whitbeck, R. F.; Knight, J. R.

1972-01-01

A modeling approach, which utilizes a matrix of transfer functions to describe the human pilot in multiple input, multiple output control situations, is studied. The approach used was to extend a well established scalar Wiener-Hopf minimization technique to the matrix case and then study, via a series of experiments, the data requirements when only finite record lengths are available. One of these experiments was a two-controller roll tracking experiment designed to force the pilot to use rudder in order to coordinate and reduce the effects of aileron yaw. One model was computed for the case where the signals used to generate the spectral matrix are error and bank angle while another model was computed for the case where error and yaw angle are the inputs. Several anomalies were observed to be present in the experimental data. These are defined by the descriptive terms roll up, break up, and roll down. Due to these algorithm induced anomalies, the frequency band over which reliable estimates of power spectra can be achieved is considerably less than predicted by the sampling theorem.

Distributed learning and multi-objectivity in traffic light control

NASA Astrophysics Data System (ADS)

Brys, Tim; Pham, Tong T.; Taylor, Matthew E.

2014-01-01

Traffic jams and suboptimal traffic flows are ubiquitous in modern societies, and they create enormous economic losses each year. Delays at traffic lights alone account for roughly 10% of all delays in US traffic. As most traffic light scheduling systems currently in use are static, set up by human experts rather than being adaptive, the interest in machine learning approaches to this problem has increased in recent years. Reinforcement learning (RL) approaches are often used in these studies, as they require little pre-existing knowledge about traffic flows. Distributed constraint optimisation approaches (DCOP) have also been shown to be successful, but are limited to cases where the traffic flows are known. The distributed coordination of exploration and exploitation (DCEE) framework was recently proposed to introduce learning in the DCOP framework. In this paper, we present a study of DCEE and RL techniques in a complex simulator, illustrating the particular advantages of each, comparing them against standard isolated traffic actuated signals. We analyse how learning and coordination behave under different traffic conditions, and discuss the multi-objective nature of the problem. Finally we evaluate several alternative reward signals in the best performing approach, some of these taking advantage of the correlation between the problem-inherent objectives to improve performance.

Contract Monitoring in Agent-Based Systems: Case Study

NASA Astrophysics Data System (ADS)

Hodík, Jiří; Vokřínek, Jiří; Jakob, Michal

Monitoring of fulfilment of obligations defined by electronic contracts in distributed domains is presented in this paper. A two-level model of contract-based systems and the types of observations needed for contract monitoring are introduced. The observations (inter-agent communication and agents’ actions) are collected and processed by the contract observation and analysis pipeline. The presented approach has been utilized in a multi-agent system for electronic contracting in a modular certification testing domain.

An Assessment of Debt-for-Education Swaps. Case Studies on Swap Initiatives between Germany and Indonesia and between Spain and El Salvador

ERIC Educational Resources Information Center

Cassimon, Danny; Essers, Dennis; Renard, Robrecht

2011-01-01

A decade has passed since participants in the World Education Forum committed themselves to achieve, by 2015, the six Education for All (EFA) goals under the Dakar Framework for Action. Despite significant progress, some of the goals are likely to be missed by a large margin. Besides the absence of a well co-ordinated multi-donor approach in…

Pilot users in agile development processes: motivational factors.

PubMed

Johannessen, Liv Karen; Gammon, Deede

2010-01-01

Despite a wealth of research on user participation, few studies offer insights into how to involve multi-organizational users in agile development methods. This paper is a case study of user involvement in developing a system for electronic laboratory requisitions using agile methodologies in a multi-organizational context. Building on an interpretive approach, we illuminate questions such as: How does collaboration between users and developers evolve and how might it be improved? What key motivational aspects are at play when users volunteer and continue contributing in the face of considerable added burdens? The study highlights how agile methods in themselves appear to facilitate mutually motivating collaboration between user groups and developers. Lessons learned for leveraging the advantages of agile development processes include acknowledging the substantial and ongoing contributions of users and their roles as co-designers of the system.

Enabling multi-faceted measures of success for protected area management in Trinidad and Tobago.

PubMed

Granderson, Ainka A

2011-08-01

A key challenge has been to define and measure "success" in managing protected areas. A case study was conducted of efforts to evaluate the new protected area management system in Trinidad and Tobago using a participatory approach. The aim of the case study was to (1) examine whether stakeholder involvement better captures the multi-faceted nature of success and (2) identify the role and influence of various stakeholder groups in this process. An holistic and systematic framework was developed with stakeholder input that facilitated the integration of expert and lay knowledge, a broad emphasis on ecological, socio-economic, and institutional aspects, and the use of both quantitative and qualitative data allowing the evaluation to capture the multi-faceted nature and impacts of protected area management. Input from primary stakeholders, such as local communities, was critical as they have a high stake in protected area outcomes. Secondary and external stakeholders, including government agencies, non-governmental organizations, academia and the private sector, were also important in providing valuable technical assistance and serving as mediators. However, a lack of consensus over priorities, politics, and limited stakeholder capacity and data access pose significant barriers to engaging stakeholders to effectively measure the management success of protected areas. Copyright © 2011 Elsevier Ltd. All rights reserved.

Individual Differences in Written Corrective Feedback: A Multi-Case Study

ERIC Educational Resources Information Center

Li, Su; Li, Pengjing

2012-01-01

Written corrective feedback (WCF) has been a long time practice in L2 writing instruction. However, in many cases, the effects are not satisfactory. There have been controversies about it both theoretically and empirically. This paper reports a multi-case study exploring individual differences that impact learners' responses to WCF. Four students'…

A sustainable manufacturing system design: A fuzzy multi-objective optimization model.

PubMed

Nujoom, Reda; Mohammed, Ahmed; Wang, Qian

2017-08-10

In the past decade, there has been a growing concern about the environmental protection in public society as governments almost all over the world have initiated certain rules and regulations to promote energy saving and minimize the production of carbon dioxide (CO 2 ) emissions in many manufacturing industries. The development of sustainable manufacturing systems is considered as one of the effective solutions to minimize the environmental impact. Lean approach is also considered as a proper method for achieving sustainability as it can reduce manufacturing wastes and increase the system efficiency and productivity. However, the lean approach does not include environmental waste of such as energy consumption and CO 2 emissions when designing a lean manufacturing system. This paper addresses these issues by evaluating a sustainable manufacturing system design considering a measurement of energy consumption and CO 2 emissions using different sources of energy (oil as direct energy source to generate thermal energy and oil or solar as indirect energy source to generate electricity). To this aim, a multi-objective mathematical model is developed incorporating the economic and ecological constraints aimed for minimization of the total cost, energy consumption, and CO 2 emissions for a manufacturing system design. For the real world scenario, the uncertainty in a number of input parameters was handled through the development of a fuzzy multi-objective model. The study also addresses decision-making in the number of machines, the number of air-conditioning units, and the number of bulbs involved in each process of a manufacturing system in conjunction with a quantity of material flow for processed products. A real case study was used for examining the validation and applicability of the developed sustainable manufacturing system model using the fuzzy multi-objective approach.

Multivariate decoding of brain images using ordinal regression.

PubMed

Doyle, O M; Ashburner, J; Zelaya, F O; Williams, S C R; Mehta, M A; Marquand, A F

2013-11-01

Neuroimaging data are increasingly being used to predict potential outcomes or groupings, such as clinical severity, drug dose response, and transitional illness states. In these examples, the variable (target) we want to predict is ordinal in nature. Conventional classification schemes assume that the targets are nominal and hence ignore their ranked nature, whereas parametric and/or non-parametric regression models enforce a metric notion of distance between classes. Here, we propose a novel, alternative multivariate approach that overcomes these limitations - whole brain probabilistic ordinal regression using a Gaussian process framework. We applied this technique to two data sets of pharmacological neuroimaging data from healthy volunteers. The first study was designed to investigate the effect of ketamine on brain activity and its subsequent modulation with two compounds - lamotrigine and risperidone. The second study investigates the effect of scopolamine on cerebral blood flow and its modulation using donepezil. We compared ordinal regression to multi-class classification schemes and metric regression. Considering the modulation of ketamine with lamotrigine, we found that ordinal regression significantly outperformed multi-class classification and metric regression in terms of accuracy and mean absolute error. However, for risperidone ordinal regression significantly outperformed metric regression but performed similarly to multi-class classification both in terms of accuracy and mean absolute error. For the scopolamine data set, ordinal regression was found to outperform both multi-class and metric regression techniques considering the regional cerebral blood flow in the anterior cingulate cortex. Ordinal regression was thus the only method that performed well in all cases. Our results indicate the potential of an ordinal regression approach for neuroimaging data while providing a fully probabilistic framework with elegant approaches for model selection. Copyright © 2013. Published by Elsevier Inc.

Thermodynamic modeling of small scale biomass gasifiers: Development and assessment of the ''Multi-Box'' approach.

PubMed

Vakalis, Stergios; Patuzzi, Francesco; Baratieri, Marco

2016-04-01

Modeling can be a powerful tool for designing and optimizing gasification systems. Modeling applications for small scale/fixed bed biomass gasifiers have been interesting due to their increased commercial practices. Fixed bed gasifiers are characterized by a wide range of operational conditions and are multi-zoned processes. The reactants are distributed in different phases and the products from each zone influence the following process steps and thus the composition of the final products. The present study aims to improve the conventional 'Black-Box' thermodynamic modeling by means of developing multiple intermediate 'boxes' that calculate two phase (solid-vapor) equilibriums in small scale gasifiers. Therefore the model is named ''Multi-Box''. Experimental data from a small scale gasifier have been used for the validation of the model. The returned results are significantly closer with the actual case study measurements in comparison to single-stage thermodynamic modeling. Copyright © 2016 Elsevier Ltd. All rights reserved.

The Case for Diabetes Population Health Improvement: Evidence-Based Programming for Population Outcomes in Diabetes

PubMed Central

Maruthur, Nisa; Mathioudakis, Nestoras; Spanakis, Elias; Rubin, Daniel; Zilbermint, Mihail; Hill-Briggs, Felicia

2017-01-01

Purpose of Review The goal of this review is to describe diabetes within a population health improvement framework and to review the evidence for a diabetes population health continuum of intervention approaches, including diabetes prevention and chronic and acute diabetes management, to improve clinical and economic outcomes. Recent Findings Recent studies have shown that compared to usual care, lifestyle interventions in prediabetes lower diabetes risk at the population-level and that group-based programs have low incremental medial cost effectiveness ratio for health systems. Effective outpatient interventions that improve diabetes control and process outcomes are multi-level, targeting the patient, provider, and healthcare system simultaneously and integrate community health workers as a liaison between the patient and community-based healthcare resources. A multi-faceted approach to diabetes management is also effective in the inpatient setting. Interventions shown to promote safe and effective glycemic control and use of evidence-based glucose management practices include provider reminder and clinical decision support systems, automated computer order entry, provider education, and organizational change. Summary Future studies should examine the cost-effectiveness of multi-faceted outpatient and inpatient diabetes management programs to determine the best financial models for incorporating them into diabetes population health strategies. PMID:28567711

A multi-species exchange model for fully fluctuating polymer field theory simulations.

PubMed

Düchs, Dominik; Delaney, Kris T; Fredrickson, Glenn H

2014-11-07

Field-theoretic models have been used extensively to study the phase behavior of inhomogeneous polymer melts and solutions, both in self-consistent mean-field calculations and in numerical simulations of the full theory capturing composition fluctuations. The models commonly used can be grouped into two categories, namely, species models and exchange models. Species models involve integrations of functionals that explicitly depend on fields originating both from species density operators and their conjugate chemical potential fields. In contrast, exchange models retain only linear combinations of the chemical potential fields. In the two-component case, development of exchange models has been instrumental in enabling stable complex Langevin (CL) simulations of the full complex-valued theory. No comparable stable CL approach has yet been established for field theories of the species type. Here, we introduce an extension of the exchange model to an arbitrary number of components, namely, the multi-species exchange (MSE) model, which greatly expands the classes of soft material systems that can be accessed by the complex Langevin simulation technique. We demonstrate the stability and accuracy of the MSE-CL sampling approach using numerical simulations of triblock and tetrablock terpolymer melts, and tetrablock quaterpolymer melts. This method should enable studies of a wide range of fluctuation phenomena in multiblock/multi-species polymer blends and composites.

Models for Type Ia Supernovae and Related Astrophysical Transients

NASA Astrophysics Data System (ADS)

Röpke, Friedrich K.; Sim, Stuart A.

2018-06-01

We give an overview of recent efforts to model Type Ia supernovae and related astrophysical transients resulting from thermonuclear explosions in white dwarfs. In particular we point out the challenges resulting from the multi-physics multi-scale nature of the problem and discuss possible numerical approaches to meet them in hydrodynamical explosion simulations and radiative transfer modeling. We give examples of how these methods are applied to several explosion scenarios that have been proposed to explain distinct subsets or, in some cases, the majority of the observed events. In case we comment on some of the successes and shortcoming of these scenarios and highlight important outstanding issues.

A multi-material topology optimization approach for wrinkle-free design of cable-suspended membrane structures

NASA Astrophysics Data System (ADS)

Luo, Yangjun; Niu, Yanzhuang; Li, Ming; Kang, Zhan

2017-06-01

In order to eliminate stress-related wrinkles in cable-suspended membrane structures and to provide simple and reliable deployment, this study presents a multi-material topology optimization model and an effective solution procedure for generating optimal connected layouts for membranes and cables. On the basis of the principal stress criterion of membrane wrinkling behavior and the density-based interpolation of multi-phase materials, the optimization objective is to maximize the total structural stiffness while satisfying principal stress constraints and specified material volume requirements. By adopting the cosine-type relaxation scheme to avoid the stress singularity phenomenon, the optimization model is successfully solved through a standard gradient-based algorithm. Four-corner tensioned membrane structures with different loading cases were investigated to demonstrate the effectiveness of the proposed method in automatically finding the optimal design composed of curved boundary cables and wrinkle-free membranes.

Estimation of Survival Probabilities for Use in Cost-effectiveness Analyses: A Comparison of a Multi-state Modeling Survival Analysis Approach with Partitioned Survival and Markov Decision-Analytic Modeling

PubMed Central

Williams, Claire; Lewsey, James D.; Mackay, Daniel F.; Briggs, Andrew H.

2016-01-01

Modeling of clinical-effectiveness in a cost-effectiveness analysis typically involves some form of partitioned survival or Markov decision-analytic modeling. The health states progression-free, progression and death and the transitions between them are frequently of interest. With partitioned survival, progression is not modeled directly as a state; instead, time in that state is derived from the difference in area between the overall survival and the progression-free survival curves. With Markov decision-analytic modeling, a priori assumptions are often made with regard to the transitions rather than using the individual patient data directly to model them. This article compares a multi-state modeling survival regression approach to these two common methods. As a case study, we use a trial comparing rituximab in combination with fludarabine and cyclophosphamide v. fludarabine and cyclophosphamide alone for the first-line treatment of chronic lymphocytic leukemia. We calculated mean Life Years and QALYs that involved extrapolation of survival outcomes in the trial. We adapted an existing multi-state modeling approach to incorporate parametric distributions for transition hazards, to allow extrapolation. The comparison showed that, due to the different assumptions used in the different approaches, a discrepancy in results was evident. The partitioned survival and Markov decision-analytic modeling deemed the treatment cost-effective with ICERs of just over £16,000 and £13,000, respectively. However, the results with the multi-state modeling were less conclusive, with an ICER of just over £29,000. This work has illustrated that it is imperative to check whether assumptions are realistic, as different model choices can influence clinical and cost-effectiveness results. PMID:27698003

Estimation of Survival Probabilities for Use in Cost-effectiveness Analyses: A Comparison of a Multi-state Modeling Survival Analysis Approach with Partitioned Survival and Markov Decision-Analytic Modeling.

PubMed

Williams, Claire; Lewsey, James D; Mackay, Daniel F; Briggs, Andrew H

2017-05-01

Modeling of clinical-effectiveness in a cost-effectiveness analysis typically involves some form of partitioned survival or Markov decision-analytic modeling. The health states progression-free, progression and death and the transitions between them are frequently of interest. With partitioned survival, progression is not modeled directly as a state; instead, time in that state is derived from the difference in area between the overall survival and the progression-free survival curves. With Markov decision-analytic modeling, a priori assumptions are often made with regard to the transitions rather than using the individual patient data directly to model them. This article compares a multi-state modeling survival regression approach to these two common methods. As a case study, we use a trial comparing rituximab in combination with fludarabine and cyclophosphamide v. fludarabine and cyclophosphamide alone for the first-line treatment of chronic lymphocytic leukemia. We calculated mean Life Years and QALYs that involved extrapolation of survival outcomes in the trial. We adapted an existing multi-state modeling approach to incorporate parametric distributions for transition hazards, to allow extrapolation. The comparison showed that, due to the different assumptions used in the different approaches, a discrepancy in results was evident. The partitioned survival and Markov decision-analytic modeling deemed the treatment cost-effective with ICERs of just over £16,000 and £13,000, respectively. However, the results with the multi-state modeling were less conclusive, with an ICER of just over £29,000. This work has illustrated that it is imperative to check whether assumptions are realistic, as different model choices can influence clinical and cost-effectiveness results.

X-framework: Space system failure analysis framework

NASA Astrophysics Data System (ADS)

Newman, John Steven

Space program and space systems failures result in financial losses in the multi-hundred million dollar range every year. In addition to financial loss, space system failures may also represent the loss of opportunity, loss of critical scientific, commercial and/or national defense capabilities, as well as loss of public confidence. The need exists to improve learning and expand the scope of lessons documented and offered to the space industry project team. One of the barriers to incorporating lessons learned include the way in which space system failures are documented. Multiple classes of space system failure information are identified, ranging from "sound bite" summaries in space insurance compendia, to articles in journals, lengthy data-oriented (what happened) reports, and in some rare cases, reports that treat not only the what, but also the why. In addition there are periodically published "corporate crisis" reports, typically issued after multiple or highly visible failures that explore management roles in the failure, often within a politically oriented context. Given the general lack of consistency, it is clear that a good multi-level space system/program failure framework with analytical and predictive capability is needed. This research effort set out to develop such a model. The X-Framework (x-fw) is proposed as an innovative forensic failure analysis approach, providing a multi-level understanding of the space system failure event beginning with the proximate cause, extending to the directly related work or operational processes and upward through successive management layers. The x-fw focus is on capability and control at the process level and examines: (1) management accountability and control, (2) resource and requirement allocation, and (3) planning, analysis, and risk management at each level of management. The x-fw model provides an innovative failure analysis approach for acquiring a multi-level perspective, direct and indirect causation of failures, and generating better and more consistent reports. Through this approach failures can be more fully understood, existing programs can be evaluated and future failures avoided. The x-fw development involved a review of the historical failure analysis and prevention literature, coupled with examination of numerous failure case studies. Analytical approaches included use of a relational failure "knowledge base" for classification and sorting of x-fw elements and attributes for each case. In addition a novel "management mapping" technique was developed as a means of displaying an integrated snapshot of indirect causes within the management chain. Further research opportunities will extend the depth of knowledge available for many of the component level cases. In addition, the x-fw has the potential to expand the scope of space sector lessons learned, and contribute to knowledge management and organizational learning.

Multi-mode reliability-based design of horizontal curves.

PubMed

Essa, Mohamed; Sayed, Tarek; Hussein, Mohamed

2016-08-01

Recently, reliability analysis has been advocated as an effective approach to account for uncertainty in the geometric design process and to evaluate the risk associated with a particular design. In this approach, a risk measure (e.g. probability of noncompliance) is calculated to represent the probability that a specific design would not meet standard requirements. The majority of previous applications of reliability analysis in geometric design focused on evaluating the probability of noncompliance for only one mode of noncompliance such as insufficient sight distance. However, in many design situations, more than one mode of noncompliance may be present (e.g. insufficient sight distance and vehicle skidding at horizontal curves). In these situations, utilizing a multi-mode reliability approach that considers more than one failure (noncompliance) mode is required. The main objective of this paper is to demonstrate the application of multi-mode (system) reliability analysis to the design of horizontal curves. The process is demonstrated by a case study of Sea-to-Sky Highway located between Vancouver and Whistler, in southern British Columbia, Canada. Two noncompliance modes were considered: insufficient sight distance and vehicle skidding. The results show the importance of accounting for several noncompliance modes in the reliability model. The system reliability concept could be used in future studies to calibrate the design of various design elements in order to achieve consistent safety levels based on all possible modes of noncompliance. Copyright © 2016 Elsevier Ltd. All rights reserved.

Two Formal Gas Models For Multi-Agent Sweeping and Obstacle Avoidance

NASA Technical Reports Server (NTRS)

Kerr, Wesley; Spears, Diana; Spears, William; Thayer, David

2004-01-01

The task addressed here is a dynamic search through a bounded region, while avoiding multiple large obstacles, such as buildings. In the case of limited sensors and communication, maintaining spatial coverage - especially after passing the obstacles - is a challenging problem. Here, we investigate two physics-based approaches to solving this task with multiple simulated mobile robots, one based on artificial forces and the other based on the kinetic theory of gases. The desired behavior is achieved with both methods, and a comparison is made between them. Because both approaches are physics-based, formal assurances about the multi-robot behavior are straightforward, and are included in the paper.

Interviewing patients and practitioners working together in teams. A multi-layered puzzle: putting the pieces together.

PubMed

Ringstad, Oystein

2010-08-01

This paper presents and evaluates a methodological approach aiming at analysing some of the complex interaction between patients and different health care practitioners working together in teams. Qualitative health care research describes the values, perceptions and conceptions of patients and practitioners. In modern clinical work patients and professional practitioners often work together on complex cases involving different kinds of knowledge and values, each of them representing different perspectives. We need studies designed to capture this complexity. The methodological approach presented here is exemplified with a study in rehabilitation medicine. In this part of the health care system the clinical work is organized in multi-professional clinical teams including patients, handling complex rehabilitation processes. In the presented approach data are collected in individual in-depth interviews to have thorough descriptions of each individual perspective. The interaction in the teams is analysed by comparing different descriptions of the same situations from the involved individuals. We may then discuss how these perceptions relate to each other and how the individuals in the team interact. Two examples from an empirical study are presented and discussed, illustrating how communication, differences in evaluations and the interpretation of incidents, arguments, emotions and interpersonal relations may be discussed. It is argued that this approach may give information which can supplement the methods commonly applied in qualitative health care research today.

Probabilistic simulation of the human factor in structural reliability

NASA Technical Reports Server (NTRS)

Chamis, C. C.

1993-01-01

A formal approach is described in an attempt to computationally simulate the probable ranges of uncertainties of the human factor in structural probabilistic assessments. A multi-factor interaction equation (MFIE) model has been adopted for this purpose. Human factors such as marital status, professional status, home life, job satisfaction, work load and health, are considered to demonstrate the concept. Parametric studies in conjunction with judgment are used to select reasonable values for the participating factors (primitive variables). Suitability of the MFIE in the subsequently probabilistic sensitivity studies are performed to assess the validity of the whole approach. Results obtained show that the uncertainties for no error range from five to thirty percent for the most optimistic case.

A Three-Dimensional Target Depth-Resolution Method with a Single-Vector Sensor

PubMed Central

Zhao, Anbang; Bi, Xuejie; Hui, Juan; Zeng, Caigao; Ma, Lin

2018-01-01

This paper mainly studies and verifies the target number category-resolution method in multi-target cases and the target depth-resolution method of aerial targets. Firstly, target depth resolution is performed by using the sign distribution of the reactive component of the vertical complex acoustic intensity; the target category and the number resolution in multi-target cases is realized with a combination of the bearing-time recording information; and the corresponding simulation verification is carried out. The algorithm proposed in this paper can distinguish between the single-target multi-line spectrum case and the multi-target multi-line spectrum case. This paper presents an improved azimuth-estimation method for multi-target cases, which makes the estimation results more accurate. Using the Monte Carlo simulation, the feasibility of the proposed target number and category-resolution algorithm in multi-target cases is verified. In addition, by studying the field characteristics of the aerial and surface targets, the simulation results verify that there is only amplitude difference between the aerial target field and the surface target field under the same environmental parameters, and an aerial target can be treated as a special case of a surface target; the aerial target category resolution can then be realized based on the sign distribution of the reactive component of the vertical acoustic intensity so as to realize three-dimensional target depth resolution. By processing data from a sea experiment, the feasibility of the proposed aerial target three-dimensional depth-resolution algorithm is verified. PMID:29649173

A Three-Dimensional Target Depth-Resolution Method with a Single-Vector Sensor.

PubMed

Zhao, Anbang; Bi, Xuejie; Hui, Juan; Zeng, Caigao; Ma, Lin

2018-04-12

This paper mainly studies and verifies the target number category-resolution method in multi-target cases and the target depth-resolution method of aerial targets. Firstly, target depth resolution is performed by using the sign distribution of the reactive component of the vertical complex acoustic intensity; the target category and the number resolution in multi-target cases is realized with a combination of the bearing-time recording information; and the corresponding simulation verification is carried out. The algorithm proposed in this paper can distinguish between the single-target multi-line spectrum case and the multi-target multi-line spectrum case. This paper presents an improved azimuth-estimation method for multi-target cases, which makes the estimation results more accurate. Using the Monte Carlo simulation, the feasibility of the proposed target number and category-resolution algorithm in multi-target cases is verified. In addition, by studying the field characteristics of the aerial and surface targets, the simulation results verify that there is only amplitude difference between the aerial target field and the surface target field under the same environmental parameters, and an aerial target can be treated as a special case of a surface target; the aerial target category resolution can then be realized based on the sign distribution of the reactive component of the vertical acoustic intensity so as to realize three-dimensional target depth resolution. By processing data from a sea experiment, the feasibility of the proposed aerial target three-dimensional depth-resolution algorithm is verified.

Practical aspects and applications of the biological effective dose three-dimensional calculation for multi-phase radiotherapy treatment plans

NASA Astrophysics Data System (ADS)

Kauweloa, Kevin Ikaika

The approximate BED (BEDA) is calculated for multi-phase cases due to current treatment planning systems (TPSs) being incapable of performing BED calculations. There has been no study on the mathematical accuracy and precision of BEDA relative to the true BED (BEDT), and how that might negatively impact patient care. The purpose of the first aim was to study the mathematical accuracy and precision in both hypothetical and clinical situations, while the next two aims were to create multi-phase BED optimization ideas for both multi-target liver stereotactic body radiation therapy (SBRT) cases, and gynecological cases where patients are treated with high-dose rate (HDR) brachytherapy along with external beam radiotherapy (EBRT). MATLAB algorithms created for this work were used to mathematically analyze the accuracy and precision of BEDA relative to BEDT in both hypothetical and clinical situations on a 3D basis. The organs-at-risk (OARs) of ten head & neck and ten prostate cancer patients were studied for the clinical situations. The accuracy of BEDA was shown to vary between OARs as well as between patients. The percentage of patients with an overall BEDA percent error less than 1% were, 50% for the Optic Chiasm and Brainstem, 70% for the Left and Right Optic Nerves, as well as the Rectum and Bladder, and 80% for the Normal Brain and Spinal Cord. As seen for each OAR among different patients, there were always cases where the percent error was greater than 1%. This is a cause for concern since the goal of radiation therapy is to reduce the overall uncertainty of treatment, and calculating BEDA distributions increases the treatment uncertainty with percent errors greater than 1%. The revealed inaccuracy and imprecision of BEDA supports the argument to use BEDT. The multi-target liver study involved applying BEDT in order to reduce the number of dose limits to one rather than have one for each fractionation scheme in multi-target liver SBRT treatments. A BEDT limit was found using the current, clinically accepted dose limits, allowing the BEDT distributions to be calculated, which could be used to determine whether at least 700 cc of the healthy liver did not receive the BEDT limit. Three previously multi-target liver cancer patients were studied. For each case, it was shown that the conventional treatment plans were relatively conservative and that more than 700 cc of the healthy liver received less than the BED T limit. These results show that greater doses can be delivered to the targets without exceeding the BEDT limit to the healthy tissue, which typically causes radiation toxicity. When applying BEDT to gynecological cases, the BEDT can reveal the relative effect each treatment would have individually hence the cumulative BEDT would better inform the physician of the potential results with the patient's treatment. The problem presented for these cases, however, is the method in summing dose distributions together when there is significant motion between treatments and the presence of applicators for the HDR phase. One way to calculate the cumulative BEDT is to use structure guided deformable image registration (SG-DIR) that only focuses on the anatomical contours, to avoid errors introduced by the applicators. Eighteen gynecological patients were studied and VelocityAI was used to perform this SG- DIR. In addition, formalism was developed to assess and characterize the remnant dose-mapping error from this approach, from the shortest distance between contour points (SDBP). The results revealed that warping errors rendered relatively large normal tissue complication probability (NTCP) values which are certainly non negligible and does render this method not clinically viable. However, a more accurate SG-DIR algorithm could improve the accuracy of BEDT distributions in these multi-phase cases.

Case-Based Multi-Sensor Intrusion Detection

NASA Astrophysics Data System (ADS)

Schwartz, Daniel G.; Long, Jidong

2009-08-01

Multi-sensor intrusion detection systems (IDSs) combine the alerts raised by individual IDSs and possibly other kinds of devices such as firewalls and antivirus software. A critical issue in building a multi-sensor IDS is alert-correlation, i.e., determining which alerts are caused by the same attack. This paper explores a novel approach to alert correlation using case-based reasoning (CBR). Each case in the CBR system's library contains a pattern of alerts raised by some known attack type, together with the identity of the attack. Then during run time, the alert streams gleaned from the sensors are compared with the patterns in the cases, and a match indicates that the attack described by that case has occurred. For this purpose the design of a fast and accurate matching algorithm is imperative. Two such algorithms were explored: (i) the well-known Hungarian algorithm, and (ii) an order-preserving matching of our own device. Tests were conducted using the DARPA Grand Challenge Problem attack simulator. These showed that the both matching algorithms are effective in detecting attacks; but the Hungarian algorithm is inefficient; whereas the order-preserving one is very efficient, in fact runs in linear time.

Nutrient supplementation approaches in the treatment of ADHD.

PubMed

Rucklidge, Julia J; Johnstone, Jeanette; Kaplan, Bonnie J

2009-04-01

Attention-deficit/hyperactivity disorder (ADHD) is a chronic, debilitating psychiatric illness that often co-occurs with other common psychiatric problems. Although empirical evidence supports pharmacological and behavioral treatments, side effects, concerns regarding safety and fears about long-term use all contribute to families searching for alternative methods of treating the symptoms of ADHD. This review presents the published evidence on supplementation, including single ingredients (e.g., minerals, vitamins, amino acids and essential fatty acids), botanicals and multi-ingredient formulas in the treatment of ADHD symptoms. In most cases, evidence is sparse, mixed and lacking information. Of those supplements where we found published studies, the evidence is best for zinc (two positive randomized, controlled trials); there is mixed evidence for carnitine, pycnogenol and essential fatty acids, and more research is needed before drawing conclusions about vitamins, magnesium, iron, SAM-e, tryptophan and Ginkgo biloba with ginseng. To date, there is no evidence to support the use of St John's wort, tyrosine or phenylalanine in the treatment of ADHD symptoms. Multi-ingredient approaches are an intriguing yet under-researched area; we discuss the benefits of this approach considering the heterogeneous nature of ADHD.

Cloudwave: distributed processing of "big data" from electrophysiological recordings for epilepsy clinical research using Hadoop.

PubMed

Jayapandian, Catherine P; Chen, Chien-Hung; Bozorgi, Alireza; Lhatoo, Samden D; Zhang, Guo-Qiang; Sahoo, Satya S

2013-01-01

Epilepsy is the most common serious neurological disorder affecting 50-60 million persons worldwide. Multi-modal electrophysiological data, such as electroencephalography (EEG) and electrocardiography (EKG), are central to effective patient care and clinical research in epilepsy. Electrophysiological data is an example of clinical "big data" consisting of more than 100 multi-channel signals with recordings from each patient generating 5-10GB of data. Current approaches to store and analyze signal data using standalone tools, such as Nihon Kohden neurology software, are inadequate to meet the growing volume of data and the need for supporting multi-center collaborative studies with real time and interactive access. We introduce the Cloudwave platform in this paper that features a Web-based intuitive signal analysis interface integrated with a Hadoop-based data processing module implemented on clinical data stored in a "private cloud". Cloudwave has been developed as part of the National Institute of Neurological Disorders and Strokes (NINDS) funded multi-center Prevention and Risk Identification of SUDEP Mortality (PRISM) project. The Cloudwave visualization interface provides real-time rendering of multi-modal signals with "montages" for EEG feature characterization over 2TB of patient data generated at the Case University Hospital Epilepsy Monitoring Unit. Results from performance evaluation of the Cloudwave Hadoop data processing module demonstrate one order of magnitude improvement in performance over 77GB of patient data. (Cloudwave project: http://prism.case.edu/prism/index.php/Cloudwave).

Cloudwave: Distributed Processing of “Big Data” from Electrophysiological Recordings for Epilepsy Clinical Research Using Hadoop

PubMed Central

Jayapandian, Catherine P.; Chen, Chien-Hung; Bozorgi, Alireza; Lhatoo, Samden D.; Zhang, Guo-Qiang; Sahoo, Satya S.

2013-01-01

Epilepsy is the most common serious neurological disorder affecting 50–60 million persons worldwide. Multi-modal electrophysiological data, such as electroencephalography (EEG) and electrocardiography (EKG), are central to effective patient care and clinical research in epilepsy. Electrophysiological data is an example of clinical “big data” consisting of more than 100 multi-channel signals with recordings from each patient generating 5–10GB of data. Current approaches to store and analyze signal data using standalone tools, such as Nihon Kohden neurology software, are inadequate to meet the growing volume of data and the need for supporting multi-center collaborative studies with real time and interactive access. We introduce the Cloudwave platform in this paper that features a Web-based intuitive signal analysis interface integrated with a Hadoop-based data processing module implemented on clinical data stored in a “private cloud”. Cloudwave has been developed as part of the National Institute of Neurological Disorders and Strokes (NINDS) funded multi-center Prevention and Risk Identification of SUDEP Mortality (PRISM) project. The Cloudwave visualization interface provides real-time rendering of multi-modal signals with “montages” for EEG feature characterization over 2TB of patient data generated at the Case University Hospital Epilepsy Monitoring Unit. Results from performance evaluation of the Cloudwave Hadoop data processing module demonstrate one order of magnitude improvement in performance over 77GB of patient data. (Cloudwave project: http://prism.case.edu/prism/index.php/Cloudwave) PMID:24551370

Multi-criteria analysis for improving strategic environmental assessment of water programmes. A case study in semi-arid region of Brazil.

PubMed

Garfì, Marianna; Ferrer-Martí, Laia; Bonoli, Alessandra; Tondelli, Simona

2011-03-01

Multi-criteria analysis (MCA) is a family of decision-making tools that can be used in strategic environmental assessment (SEA) procedures to ensure that environmental, social and economic aspects are integrated into the design of human development strategies and planning, in order to increase the contribution of the environment and natural resources to poverty reduction. The aim of this paper is to highlight the contribution of a particular multi-criteria technique, the analytic hierarchy process (AHP), in two stages of the SEA procedure applied to water programmes in developing countries: the comparison of alternatives and monitoring. This proposal was validated through its application to a case study in Brazilian semi-arid region. The objective was to select and subsequently monitor the most appropriate programme for safe water availability. On the basis of the SEA results, a project was identified and implemented with successful results. In terms of comparisons of alternatives, AHP meets the requirements of human development programme assessment, including the importance of simplicity, a multidisciplinary and flexible approach, and a focus on the beneficiaries' concerns. With respect to monitoring, the study shows that AHP contributes to SEA by identifying the most appropriate indicators, in order to control the impacts of a project. Copyright © 2010 Elsevier Ltd. All rights reserved.

Towards a macrosystems approach for successful coastal ...

EPA Pesticide Factsheets

Managing coastal resources for resiliency and sustainability often requires integrative, multi-disciplinary approaches across varying spatial and temporal scales to engage stakeholders and inform decision-makers. We discuss case studies integrating wetland ecology, economics, sociology and other disciplines to help solve management problems, especially those concerning increasing nutrient loads and climate change (e.g., accelerated sea level rise, increased flooding, warming temperatures). One goal of the macrosystems approach is to provide the science necessary to assess tradeoffs for different management, restoration, and climate adaptation actions. In the first case study we examine the conversion of a cranberry farm in New England to a freshwater wetland with connectivity to Cape Cod Bay (MA). A second example examines climate adaptation actions in coastal wetlands of the northeastern US to mitigate accelerated sea level rise. Various restoration actions (e.g., dam removal, hydrological engineering) and climate adaptation interventions (e.g., living shoreline, thin layer sediment application) are underway, and we discuss the adaptive management and macrosystems approaches for each example. One focus of management actions is the provision of select ecosystem services. For each study, we discuss tradeoffs in the provision of services from different actions. By presenting examples of how a macrosystems approach works in practice, we hope to show its transferabi

Australian Schizophrenia Research Bank: a database of comprehensive clinical, endophenotypic and genetic data for aetiological studies of schizophrenia.

PubMed

Loughland, Carmel; Draganic, Daren; McCabe, Kathryn; Richards, Jacqueline; Nasir, Aslam; Allen, Joanne; Catts, Stanley; Jablensky, Assen; Henskens, Frans; Michie, Patricia; Mowry, Bryan; Pantelis, Christos; Schall, Ulrich; Scott, Rodney; Tooney, Paul; Carr, Vaughan

2010-11-01

This article describes the establishment of the Australian Schizophrenia Research Bank (ASRB), which operates to collect, store and distribute linked clinical, cognitive, neuroimaging and genetic data from a large sample of people with schizophrenia and healthy controls. Recruitment sources for the schizophrenia sample include a multi-media national advertising campaign, inpatient and community treatment services and non-government support agencies. Healthy controls have been recruited primarily through multi-media advertisements. All participants undergo an extensive diagnostic and family history assessment, neuropsychological evaluation, and blood sample donation for genetic studies. Selected individuals also complete structural MRI scans. Preliminary analyses of 493 schizophrenia cases and 293 healthy controls are reported. Mean age was 39.54 years (SD = 11.1) for the schizophrenia participants and 37.38 years (SD = 13.12) for healthy controls. Compared to the controls, features of the schizophrenia sample included a higher proportion of males (cases 65.9%; controls 46.8%), fewer living in married or de facto relationships (cases 16.1%; controls 53.6%) and fewer years of education (cases 13.05, SD = 2.84; controls 15.14, SD = 3.13), as well as lower current IQ (cases 102.68, SD = 15.51; controls 118.28, SD = 10.18). These and other sample characteristics are compared to those reported in another large Australian sample (i.e. the Low Prevalence Disorders Study), revealing some differences that reflect the different sampling methods of these two studies. The ASRB is a valuable and accessible schizophrenia research facility for use by approved scientific investigators. As recruitment continues, the approach to sampling for both cases and controls will need to be modified to ensure that the ASRB samples are as broadly representative as possible of all cases of schizophrenia and healthy controls.

Genetic Basis of Autoantibody Positive and Negative Rheumatoid Arthritis Risk in a Multi-ethnic Cohort Derived from Electronic Health Records

PubMed Central

Kurreeman, Fina; Liao, Katherine; Chibnik, Lori; Hickey, Brendan; Stahl, Eli; Gainer, Vivian; Li, Gang; Bry, Lynn; Mahan, Scott; Ardlie, Kristin; Thomson, Brian; Szolovits, Peter; Churchill, Susanne; Murphy, Shawn N.; Cai, Tianxi; Raychaudhuri, Soumya; Kohane, Isaac; Karlson, Elizabeth; Plenge, Robert M.

2011-01-01

Discovering and following up on genetic associations with complex phenotypes require large patient cohorts. This is particularly true for patient cohorts of diverse ancestry and clinically relevant subsets of disease. The ability to mine the electronic health records (EHRs) of patients followed as part of routine clinical care provides a potential opportunity to efficiently identify affected cases and unaffected controls for appropriate-sized genetic studies. Here, we demonstrate proof-of-concept that it is possible to use EHR data linked with biospecimens to establish a multi-ethnic case-control cohort for genetic research of a complex disease, rheumatoid arthritis (RA). In 1,515 EHR-derived RA cases and 1,480 controls matched for both genetic ancestry and disease-specific autoantibodies (anti-citrullinated protein antibodies [ACPA]), we demonstrate that the odds ratios and aggregate genetic risk score (GRS) of known RA risk alleles measured in individuals of European ancestry within our EHR cohort are nearly identical to those derived from a genome-wide association study (GWAS) of 5,539 autoantibody-positive RA cases and 20,169 controls. We extend this approach to other ethnic groups and identify a large overlap in the GRS among individuals of European, African, East Asian, and Hispanic ancestry. We also demonstrate that the distribution of a GRS based on 28 non-HLA risk alleles in ACPA+ cases partially overlaps with ACPA- subgroup of RA cases. Our study demonstrates that the genetic basis of rheumatoid arthritis risk is similar among cases of diverse ancestry divided into subsets based on ACPA status and emphasizes the utility of linking EHR clinical data with biospecimens for genetic studies. PMID:21211616

Tracking Virus Particles in Fluorescence Microscopy Images Using Multi-Scale Detection and Multi-Frame Association.

PubMed

Jaiswal, Astha; Godinez, William J; Eils, Roland; Lehmann, Maik Jorg; Rohr, Karl

2015-11-01

Automatic fluorescent particle tracking is an essential task to study the dynamics of a large number of biological structures at a sub-cellular level. We have developed a probabilistic particle tracking approach based on multi-scale detection and two-step multi-frame association. The multi-scale detection scheme allows coping with particles in close proximity. For finding associations, we have developed a two-step multi-frame algorithm, which is based on a temporally semiglobal formulation as well as spatially local and global optimization. In the first step, reliable associations are determined for each particle individually in local neighborhoods. In the second step, the global spatial information over multiple frames is exploited jointly to determine optimal associations. The multi-scale detection scheme and the multi-frame association finding algorithm have been combined with a probabilistic tracking approach based on the Kalman filter. We have successfully applied our probabilistic tracking approach to synthetic as well as real microscopy image sequences of virus particles and quantified the performance. We found that the proposed approach outperforms previous approaches.

[Diagnostic values of bronchoscopy and multi-slice spiral CT for congenital dysplasia of the respiratory system in infants: a comparative study].

PubMed

Wang, Xing-Lu; Huang, Ying; Li, Qu-Bei; Dai, Ji-Hong

2013-09-01

To investigate and compare the diagnostic values of bronchoscopy and multi-slice spiral computed tomography (CT) for congenital dysplasia of the respiratory system in infants. Analysis was performed on the clinical data, bronchoscopic findings and multi-slice spiral CT findings of 319 infants (≤1 years old) who underwent bronchoscopy and/or multi-slice spiral CT and were diagnosed with congenital dysplasia of the respiratory system. A total of 476 cases of congenital dysplasia of the respiratory system were found in the 319 infants, including primary dysplasia of the respiratory system (392 cases) and compressive dysplasia of the respiratory system (84 cases). Of the 392 cases of primary dysplasia of the respiratory system, 225 (57.4%) were diagnosed by bronchoscopy versus 167 (42.6%) by multi-slice spiral CT. There were significant differences in etiological diagnosis between bronchoscopy and multi-slice spiral CT in infants with congenital dysplasia of the respiratory system (P<0.05). All 76 cases of primary dysplasia of the respiratory system caused by tracheobronchomalacia were diagnosed by bronchoscopy and all 17 cases of primary dysplasia of the respiratory system caused by lung tissue dysplasia were diagnosed by multi-slice spiral CT. Of the 84 cases of compressive dysplasia of the respiratory system, 74 cases were diagnosed by multi-slice spiral CT and only 10 cases were diagnosed by bronchoscopy. Compared with multi-slice spiral CT, bronchoscopy can detect primary dysplasia of the respiratory system more directly. Bronchoscopy is valuable in the confirmed diagnosis of tracheobronchomalacia. Multi-slice spiral CT has a higher diagnostic value for lung tissue dysplasia than bronchoscopy.

Multi-criteria decision assessments using Subjective Logic: Methodology and the case of urban water strategies

NASA Astrophysics Data System (ADS)

Moglia, Magnus; Sharma, Ashok K.; Maheepala, Shiroma

2012-07-01

SummaryPlanning of regional and urban water resources, and in particular with Integrated Urban Water Management approaches, often considers inter-relationships between human uses of water, the health of the natural environment as well as the cost of various management strategies. Decision makers hence typically need to consider a combination of social, environmental and economic goals. The types of strategies employed can include water efficiency measures, water sensitive urban design, stormwater management, or catchment management. Therefore, decision makers need to choose between different scenarios and to evaluate them against a number of criteria. This type of problem has a discipline devoted to it, i.e. Multi-Criteria Decision Analysis, which has often been applied in water management contexts. This paper describes the application of Subjective Logic in a basic Bayesian Network to a Multi-Criteria Decision Analysis problem. By doing this, it outlines a novel methodology that explicitly incorporates uncertainty and information reliability. The application of the methodology to a known case study context allows for exploration. By making uncertainty and reliability of assessments explicit, it allows for assessing risks of various options, and this may help in alleviating cognitive biases and move towards a well formulated risk management policy.

A Scalable and Robust Multi-Agent Approach to Distributed Optimization

NASA Technical Reports Server (NTRS)

Tumer, Kagan

2005-01-01

Modularizing a large optimization problem so that the solutions to the subproblems provide a good overall solution is a challenging problem. In this paper we present a multi-agent approach to this problem based on aligning the agent objectives with the system objectives, obviating the need to impose external mechanisms to achieve collaboration among the agents. This approach naturally addresses scaling and robustness issues by ensuring that the agents do not rely on the reliable operation of other agents We test this approach in the difficult distributed optimization problem of imperfect device subset selection [Challet and Johnson, 2002]. In this problem, there are n devices, each of which has a "distortion", and the task is to find the subset of those n devices that minimizes the average distortion. Our results show that in large systems (1000 agents) the proposed approach provides improvements of over an order of magnitude over both traditional optimization methods and traditional multi-agent methods. Furthermore, the results show that even in extreme cases of agent failures (i.e., half the agents fail midway through the simulation) the system remains coordinated and still outperforms a failure-free and centralized optimization algorithm.

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

ERIC Educational Resources Information Center

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…

Logistic-based patient grouping for multi-disciplinary treatment.

PubMed

Maruşter, Laura; Weijters, Ton; de Vries, Geerhard; van den Bosch, Antal; Daelemans, Walter

2002-01-01

Present-day healthcare witnesses a growing demand for coordination of patient care. Coordination is needed especially in those cases in which hospitals have structured healthcare into specialty-oriented units, while a substantial portion of patient care is not limited to single units. From a logistic point of view, this multi-disciplinary patient care creates a tension between controlling the hospital's units, and the need for a control of the patient flow between units. A possible solution is the creation of new units in which different specialties work together for specific groups of patients. A first step in this solution is to identify the salient patient groups in need of multi-disciplinary care. Grouping techniques seem to offer a solution. However, most grouping approaches in medicine are driven by a search for pathophysiological homogeneity. In this paper, we present an alternative logistic-driven grouping approach. The starting point of our approach is a database with medical cases for 3,603 patients with peripheral arterial vascular (PAV) diseases. For these medical cases, six basic logistic variables (such as the number of visits to different specialist) are selected. Using these logistic variables, clustering techniques are used to group the medical cases in logistically homogeneous groups. In our approach, the quality of the resulting grouping is not measured by statistical significance, but by (i) the usefulness of the grouping for the creation of new multi-disciplinary units; (ii) how well patients can be selected for treatment in the new units. Given a priori knowledge of a patient (e.g. age, diagnosis), machine learning techniques are employed to induce rules that can be used for the selection of the patients eligible for treatment in the new units. In the paper, we describe the results of the above-proposed methodology for patients with PAV diseases. Two groupings and the accompanied classification rule sets are presented. One grouping is based on all the logistic variables, and another grouping is based on two latent factors found by applying factor analysis. On the basis of the experimental results, we can conclude that it is possible to search for medical logistic homogenous groups (i) that can be characterized by rules based on the aggregated logistic variables; (ii) for which we can formulate rules to predict to which cluster new patients belong.

A comprehensive multi-scenario based approach for a reliable flood-hazard assessment: a case-study application

NASA Astrophysics Data System (ADS)

Lanni, Cristiano; Mazzorana, Bruno; Volcan, Claudio; Bertagnolli, Rudi

2015-04-01

Flood hazard is generally assessed by assuming the return period of the rainfall as a proxy for the return period of the discharge and the related hydrograph. Frequently this deterministic view is extended also to the straightforward application of hydrodynamic models. However, the climate (i.e. precipitation), the catchment (i.e. geology, soil and antecedent soil-moisture condition) and the anthropogenic (i.e. drainage system and its regulation) systems interact in a complex way, and the occurrence probability of a flood inundation event can significantly differ from the occurrence probability of the triggering event (i.e. rainfall). In order to reliably determine the spatial patterns of flood intensities and probabilities, the rigorous determination of flood event scenarios is beneficial because it provides a clear, rationale method to recognize and unveil the inherent stochastic behavior of natural processes. Therefore, a multi-scenario approach for hazard assessment should be applied and should consider the possible events taking place in the area potentially subject to flooding (i.e. floodplains). Here, we apply a multi-scenario approach for the assessment of the flood hazard around the Idro lake (Italy). We consider and estimate the probability of occurrence of several scenarios related to the initial (i.e. initial water level in the lake) and boundary (i.e. shape of the hydrograph, downslope drainage, spillway opening operations) conditions characterizing the lake. Finally, we discuss the advantages and issues of the presented methodological procedure compared to traditional (and essentially deterministic) approaches.

Signal Processing in Functional Near-Infrared Spectroscopy (fNIRS): Methodological Differences Lead to Different Statistical Results.

PubMed

Pfeifer, Mischa D; Scholkmann, Felix; Labruyère, Rob

2017-01-01

Even though research in the field of functional near-infrared spectroscopy (fNIRS) has been performed for more than 20 years, consensus on signal processing methods is still lacking. A significant knowledge gap exists between established researchers and those entering the field. One major issue regularly observed in publications from researchers new to the field is the failure to consider possible signal contamination by hemodynamic changes unrelated to neurovascular coupling (i.e., scalp blood flow and systemic blood flow). This might be due to the fact that these researchers use the signal processing methods provided by the manufacturers of their measurement device without an advanced understanding of the performed steps. The aim of the present study was to investigate how different signal processing approaches (including and excluding approaches that partially correct for the possible signal contamination) affect the results of a typical functional neuroimaging study performed with fNIRS. In particular, we evaluated one standard signal processing method provided by a commercial company and compared it to three customized approaches. We thereby investigated the influence of the chosen method on the statistical outcome of a clinical data set (task-evoked motor cortex activity). No short-channels were used in the present study and therefore two types of multi-channel corrections based on multiple long-channels were applied. The choice of the signal processing method had a considerable influence on the outcome of the study. While methods that ignored the contamination of the fNIRS signals by task-evoked physiological noise yielded several significant hemodynamic responses over the whole head, the statistical significance of these findings disappeared when accounting for part of the contamination using a multi-channel regression. We conclude that adopting signal processing methods that correct for physiological confounding effects might yield more realistic results in cases where multi-distance measurements are not possible. Furthermore, we recommend using manufacturers' standard signal processing methods only in case the user has an advanced understanding of every signal processing step performed.

Investigating accident causation through information network modelling.

PubMed

Griffin, T G C; Young, M S; Stanton, N A

2010-02-01

Management of risk in complex domains such as aviation relies heavily on post-event investigations, requiring complex approaches to fully understand the integration of multi-causal, multi-agent and multi-linear accident sequences. The Event Analysis of Systemic Teamwork methodology (EAST; Stanton et al. 2008) offers such an approach based on network models. In this paper, we apply EAST to a well-known aviation accident case study, highlighting communication between agents as a central theme and investigating the potential for finding agents who were key to the accident. Ultimately, this work aims to develop a new model based on distributed situation awareness (DSA) to demonstrate that the risk inherent in a complex system is dependent on the information flowing within it. By identifying key agents and information elements, we can propose proactive design strategies to optimize the flow of information and help work towards avoiding aviation accidents. Statement of Relevance: This paper introduces a novel application of an holistic methodology for understanding aviation accidents. Furthermore, it introduces an ongoing project developing a nonlinear and prospective method that centralises distributed situation awareness and communication as themes. The relevance of findings are discussed in the context of current ergonomic and aviation issues of design, training and human-system interaction.

Design synthesis and optimization of permanent magnet synchronous machines based on computationally-efficient finite element analysis

NASA Astrophysics Data System (ADS)

Sizov, Gennadi Y.

In this dissertation, a model-based multi-objective optimal design of permanent magnet ac machines, supplied by sine-wave current regulated drives, is developed and implemented. The design procedure uses an efficient electromagnetic finite element-based solver to accurately model nonlinear material properties and complex geometric shapes associated with magnetic circuit design. Application of an electromagnetic finite element-based solver allows for accurate computation of intricate performance parameters and characteristics. The first contribution of this dissertation is the development of a rapid computational method that allows accurate and efficient exploration of large multi-dimensional design spaces in search of optimum design(s). The computationally efficient finite element-based approach developed in this work provides a framework of tools that allow rapid analysis of synchronous electric machines operating under steady-state conditions. In the developed modeling approach, major steady-state performance parameters such as, winding flux linkages and voltages, average, cogging and ripple torques, stator core flux densities, core losses, efficiencies and saturated machine winding inductances, are calculated with minimum computational effort. In addition, the method includes means for rapid estimation of distributed stator forces and three-dimensional effects of stator and/or rotor skew on the performance of the machine. The second contribution of this dissertation is the development of the design synthesis and optimization method based on a differential evolution algorithm. The approach relies on the developed finite element-based modeling method for electromagnetic analysis and is able to tackle large-scale multi-objective design problems using modest computational resources. Overall, computational time savings of up to two orders of magnitude are achievable, when compared to current and prevalent state-of-the-art methods. These computational savings allow one to expand the optimization problem to achieve more complex and comprehensive design objectives. The method is used in the design process of several interior permanent magnet industrial motors. The presented case studies demonstrate that the developed finite element-based approach practically eliminates the need for using less accurate analytical and lumped parameter equivalent circuit models for electric machine design optimization. The design process and experimental validation of the case-study machines are detailed in the dissertation.

Design of Quiet Rotorcraft Approach Trajectories

NASA Technical Reports Server (NTRS)

Padula, Sharon L.; Burley, Casey L.; Boyd, D. Douglas, Jr.; Marcolini, Michael A.

2009-01-01

A optimization procedure for identifying quiet rotorcraft approach trajectories is proposed and demonstrated. The procedure employs a multi-objective genetic algorithm in order to reduce noise and create approach paths that will be acceptable to pilots and passengers. The concept is demonstrated by application to two different helicopters. The optimized paths are compared with one another and to a standard 6-deg approach path. The two demonstration cases validate the optimization procedure but highlight the need for improved noise prediction techniques and for additional rotorcraft acoustic data sets.

Sustainability assessment of tertiary wastewater treatment technologies: a multi-criteria analysis.

PubMed

Plakas, K V; Georgiadis, A A; Karabelas, A J

2016-01-01

The multi-criteria analysis gives the opportunity to researchers, designers and decision-makers to examine decision options in a multi-dimensional fashion. On this basis, four tertiary wastewater treatment (WWT) technologies were assessed regarding their sustainability performance in producing recycled wastewater, considering a 'triple bottom line' approach (i.e. economic, environmental, and social). These are powdered activated carbon adsorption coupled with ultrafiltration membrane separation (PAC-UF), reverse osmosis, ozone/ultraviolet-light oxidation and heterogeneous photo-catalysis coupled with low-pressure membrane separation (photocatalytic membrane reactor, PMR). The participatory method called simple multi-attribute rating technique exploiting ranks was employed for assigning weights to selected sustainability indicators. This sustainability assessment approach resulted in the development of a composite index as a final metric, for each WWT technology evaluated. The PAC-UF technology appears to be the most appropriate technology, attaining the highest composite value regarding the sustainability performance. A scenario analysis confirmed the results of the original scenario in five out of seven cases. In parallel, the PMR was highlighted as the technology with the least variability in its performance. Nevertheless, additional actions and approaches are proposed to strengthen the objectivity of the final results.

StackSplit - a plugin for multi-event shear wave splitting analyses in SplitLab

NASA Astrophysics Data System (ADS)

Grund, Michael

2017-08-01

SplitLab is a powerful and widely used tool for analysing seismological shear wave splitting of single event measurements. However, in many cases, especially temporary station deployments close to the noisy seaside, ocean bottom or for recordings affected by strong anthropogenic noise, only multi-event approaches provide stable and reliable splitting results. In order to extend the original SplitLab environment for such analyses, I present the StackSplit plugin that can easily be implemented within the well accepted main program. StackSplit grants easy access to several different analysis approaches within SplitLab, including a new multiple waveform based inversion method as well as the most established standard stacking procedures. The possibility to switch between different analysis approaches at any time allows the user for the most flexible processing of individual multi-event splitting measurements for a single recording station. Besides the provided functions of the plugin, no other external program is needed for the multi-event analyses since StackSplit performs within the available SplitLab structure which is based on MATLAB. The effectiveness and use of this plugin is demonstrated with data examples of a long running seismological recording station in Finland.

Compromise-based Robust Prioritization of Climate Change Adaptation Strategies for Watershed Management

NASA Astrophysics Data System (ADS)

Kim, Y.; Chung, E. S.

2014-12-01

This study suggests a robust prioritization framework for climate change adaptation strategies under multiple climate change scenarios with a case study of selecting sites for reusing treated wastewater (TWW) in a Korean urban watershed. The framework utilizes various multi-criteria decision making techniques, including the VIKOR method and the Shannon entropy-based weights. In this case study, the sustainability of TWW use is quantified with indicator-based approaches with the DPSIR framework, which considers both hydro-environmental and socio-economic aspects of the watershed management. Under the various climate change scenarios, the hydro-environmental responses to reusing TWW in potential alternative sub-watersheds are determined using the Hydrologic Simulation Program in Fortran (HSPF). The socio-economic indicators are obtained from the statistical databases. Sustainability scores for multiple scenarios are estimated individually and then integrated with the proposed approach. At last, the suggested framework allows us to prioritize adaptation strategies in a robust manner with varying levels of compromise between utility-based and regret-based strategies.

Unofficial Road Building in the Amazon: Socioeconomic and Biophysical Explanations

NASA Technical Reports Server (NTRS)

Perz, Stephen G.; Caldas, Marcellus M.; Arima, Eugenio; Walker, Robert J.

2007-01-01

Roads have manifold social and environmental impacts, including regional development, social conflicts and habitat fragmentation. 'Road ecology' has emerged as an approach to evaluate the various ecological and hydrological impacts of roads. This article aims to complement road ecology by examining the socio-spatial processes of road building itself. Focusing on the Brazilian Amazon, a heavily-studied context due to forest fragmentation by roads, the authors consider non-state social actors who build 'unofficial roads' for the purpose of gaining access to natural resources to support livelihoods and community development. They examine four case studies of roads with distinct histories in order to explain the socio-spatial processes behind road building in terms of profit maximization, land tenure claims, co-operative and conflictive political ecologies, and constraints as well as opportunities afforded by the biophysical environment. The study cases illustrate the need for a multi-pronged theoretical approach to understanding road building, and call for more attention to the role of non-state actors in unofficial road construction.

Penalty methods for the numerical solution of American multi-asset option problems

NASA Astrophysics Data System (ADS)

Nielsen, Bjørn Fredrik; Skavhaug, Ola; Tveito, Aslak

2008-12-01

We derive and analyze a penalty method for solving American multi-asset option problems. A small, non-linear penalty term is added to the Black-Scholes equation. This approach gives a fixed solution domain, removing the free and moving boundary imposed by the early exercise feature of the contract. Explicit, implicit and semi-implicit finite difference schemes are derived, and in the case of independent assets, we prove that the approximate option prices satisfy some basic properties of the American option problem. Several numerical experiments are carried out in order to investigate the performance of the schemes. We give examples indicating that our results are sharp. Finally, the experiments indicate that in the case of correlated underlying assets, the same properties are valid as in the independent case.

An alternative to Rasch analysis using triadic comparisons and multi-dimensional scaling

NASA Astrophysics Data System (ADS)

Bradley, C.; Massof, R. W.

2016-11-01

Rasch analysis is a principled approach for estimating the magnitude of some shared property of a set of items when a group of people assign ordinal ratings to them. In the general case, Rasch analysis not only estimates person and item measures on the same invariant scale, but also estimates the average thresholds used by the population to define rating categories. However, Rasch analysis fails when there is insufficient variance in the observed responses because it assumes a probabilistic relationship between person measures, item measures and the rating assigned by a person to an item. When only a single person is rating all items, there may be cases where the person assigns the same rating to many items no matter how many times he rates them. We introduce an alternative to Rasch analysis for precisely these situations. Our approach leverages multi-dimensional scaling (MDS) and requires only rank orderings of items and rank orderings of pairs of distances between items to work. Simulations show one variant of this approach - triadic comparisons with non-metric MDS - provides highly accurate estimates of item measures in realistic situations.

A generalized volumetric dispersion model for a class of two-phase separation/reaction: finite difference solutions

NASA Astrophysics Data System (ADS)

Siripatana, Chairat; Thongpan, Hathaikarn; Promraksa, Arwut

2017-03-01

This article explores a volumetric approach in formulating differential equations for a class of engineering flow problems involving component transfer within or between two phases. In contrast to conventional formulation which is based on linear velocities, this work proposed a slightly different approach based on volumetric flow-rate which is essentially constant in many industrial processes. In effect, many multi-dimensional flow problems found industrially can be simplified into multi-component or multi-phase but one-dimensional flow problems. The formulation is largely generic, covering counter-current, concurrent or batch, fixed and fluidized bed arrangement. It was also intended to use for start-up, shut-down, control and steady state simulation. Since many realistic and industrial operation are dynamic with variable velocity and porosity in relation to position, analytical solutions are rare and limited to only very simple cases. Thus we also provide a numerical solution using Crank-Nicolson finite difference scheme. This solution is inherently stable as tested against a few cases published in the literature. However, it is anticipated that, for unconfined flow or non-constant flow-rate, traditional formulation should be applied.

A multi-centre evaluation of oral cancer in Southern and Western Nigeria: an African oral pathology research consortium initiative.

PubMed

Omitola, Olufemi Gbenga; Soyele, Olujide Oladele; Sigbeku, Opeyemi; Okoh, Dickson; Akinshipo, Abdulwarith Olaitan; Butali, Azeez; Adeola, Henry Ademola

2017-01-01

Oral cancer is a leading cause of cancer deaths among African populations. Lack of standard cancer registries and under-reporting has inaccurately depicted its magnitude in Nigeria. Development of multi-centre collaborative oral pathology networks such as the African Oral Pathology Research Consortium (AOPRC) facilitates skill and expertise exchange and fosters a robust and systematic investigation of oral diseases across Africa. In this descriptive cross-sectional study, we have leveraged the auspices of the AOPRC to examine the burden of oral cancer in Nigeria, using a multi-centre approach. Data from 4 major tertiary health institutions in Western and Southern Nigeria was generated using a standardized data extraction format and analysed using the SPSS data analysis software (version 20.0; SPSS Inc. Chicago, IL). Of the 162 cases examined across the 4 centres, we observed that oral squamous cell carcinomas (OSCC) occurred mostly in the 6 th and 7 th decades of life and maxillary were more frequent than mandibular OSCC lesions. Regional variations were observed both for location, age group and gender distribution. Significant regional differences was found between poorly, moderately and well differentiated OSCC (p value = 0.0071). A multi-centre collaborative oral pathology research approach is an effective way to achieve better insight into the patterns and distribution of various oral diseases in men of African descent. The wider outlook for AOPRC is to employ similar approaches to drive intensive oral pathology research targeted at addressing the current morbidity and mortality of various oral diseases across Africa.

Automated unsupervised multi-parametric classification of adipose tissue depots in skeletal muscle

PubMed Central

Valentinitsch, Alexander; Karampinos, Dimitrios C.; Alizai, Hamza; Subburaj, Karupppasamy; Kumar, Deepak; Link, Thomas M.; Majumdar, Sharmila

2012-01-01

Purpose To introduce and validate an automated unsupervised multi-parametric method for segmentation of the subcutaneous fat and muscle regions in order to determine subcutaneous adipose tissue (SAT) and intermuscular adipose tissue (IMAT) areas based on data from a quantitative chemical shift-based water-fat separation approach. Materials and Methods Unsupervised standard k-means clustering was employed to define sets of similar features (k = 2) within the whole multi-modal image after the water-fat separation. The automated image processing chain was composed of three primary stages including tissue, muscle and bone region segmentation. The algorithm was applied on calf and thigh datasets to compute SAT and IMAT areas and was compared to a manual segmentation. Results The IMAT area using the automatic segmentation had excellent agreement with the IMAT area using the manual segmentation for all the cases in the thigh (R2: 0.96) and for cases with up to moderate IMAT area in the calf (R2: 0.92). The group with the highest grade of muscle fat infiltration in the calf had the highest error in the inner SAT contour calculation. Conclusion The proposed multi-parametric segmentation approach combined with quantitative water-fat imaging provides an accurate and reliable method for an automated calculation of the SAT and IMAT areas reducing considerably the total post-processing time. PMID:23097409

Sustainability assessment of alternative end-uses for disused areas based on multi-criteria decision-making method.

PubMed

De Feo, Giovanni; De Gisi, Sabino; De Vita, Sabato; Notarnicola, Michele

2018-08-01

The main aim of this study was to define and apply a multidisciplinary and multi-criteria approach to sustainability in evaluating alternative end-uses for disused areas. Taking into account the three pillars of sustainability (social, economic and environmental dimension) as well as the need for stakeholders to have new practical instruments, the innovative approach consists of four modules stated (i) sociological, (ii) economic, (iii) environmental and (iv) multi-criteria assessment. By means of a case study on a small Municipality in Southern Italy, three end-uses alternatives, representing three essential services for citizens, were selected: Municipal gym; Market area; Municipal Solid Waste (MSW) separate collection centre. The sociological module was useful to select the most socially sound alternative by means of a consultative referendum, simulated with the use of a structured questionnaire administered to a sample of the population. The economic evaluation was conducted defining the bill of quantities with regarding to six main items (soil handling, landfill disposal tax, public services, structure and services, completion work, equipment and furnishings). The environmental evaluation was performed applying the Delphi method with local technicians who were involved in a qualitative-quantitative evaluation of the three alternatives with regarding to eight possible environmental impacts (landscape impact, soil handling, odour, traffic, noise, atmospheric pollution, wastewater, waste). Finally, the Simple Additive Weighting was used as multi-criteria technique to define alternatives priorities. The obtained results showed how the multi-criteria analysis is a useful decision support tool able to identify transparently and efficiently the most sustainable solutions to a complex social problem. Copyright © 2018 Elsevier B.V. All rights reserved.

Grounding a new information technology implementation framework in behavioral science: a systematic analysis of the literature on IT use.

PubMed

Kukafka, Rita; Johnson, Stephen B; Linfante, Allison; Allegrante, John P

2003-06-01

Many interventions to improve the success of information technology (IT) implementations are grounded in behavioral science, using theories, and models to identify conditions and determinants of successful use. However, each model in the IT literature has evolved to address specific theoretical problems of particular disciplinary concerns, and each model has been tested and has evolved using, in most cases, a more or less restricted set of IT implementation procedures. Functionally, this limits the perspective for taking into account the multiple factors at the individual, group, and organizational levels that influence use behavior. While a rich body of literature has emerged, employing prominent models such as the Technology Adoption Model, Social-Cognitive Theory, and Diffusion of Innovation Theory, the complexity of defining a suitable multi-level intervention has largely been overlooked. A gap exists between the implementation of IT and the integration of theories and models that can be utilized to develop multi-level approaches to identify factors that impede usage behavior. We present a novel framework that is intended to guide synthesis of more than one theoretical perspective for the purpose of planning multi-level interventions to enhance IT use. This integrative framework is adapted from PRECEDE/PROCEDE, a conceptual framework used by health planners in hundreds of published studies to direct interventions that account for the multiple determinants of behavior. Since we claim that the literature on IT use behavior does not now include a multi-level approach, we undertook a systematic literature analysis to confirm this assertion. Our framework facilitated organizing this literature synthesis and our analysis was aimed at determining if the IT implementation approaches in the published literature were characterized by an approach that considered at least two levels of IT usage determinants. We found that while 61% of studies mentioned or referred to theory, none considered two or more levels. In other words, although the researchers employ behavioral theory, they omit two fundamental propositions: (1) IT usage is influenced by multiple factors and (2) interventions must be multi-dimensional. Our literature synthesis may provide additional insight into the reason for high failure rates associated with underutilized systems, and underscores the need to move beyond the current dominant approach that employs a single model to guide IT implementation plans that aim to address factors associated with IT acceptance and subsequent positive use behavior.

Agent Architectures for Compliance

NASA Astrophysics Data System (ADS)

Burgemeestre, Brigitte; Hulstijn, Joris; Tan, Yao-Hua

A Normative Multi-Agent System consists of autonomous agents who must comply with social norms. Different kinds of norms make different assumptions about the cognitive architecture of the agents. For example, a principle-based norm assumes that agents can reflect upon the consequences of their actions; a rule-based formulation only assumes that agents can avoid violations. In this paper we present several cognitive agent architectures for self-monitoring and compliance. We show how different assumptions about the cognitive architecture lead to different information needs when assessing compliance. The approach is validated with a case study of horizontal monitoring, an approach to corporate tax auditing recently introduced by the Dutch Customs and Tax Authority.

MODELING LEFT-TRUNCATED AND RIGHT-CENSORED SURVIVAL DATA WITH LONGITUDINAL COVARIATES

PubMed Central

Su, Yu-Ru; Wang, Jane-Ling

2018-01-01

There is a surge in medical follow-up studies that include longitudinal covariates in the modeling of survival data. So far, the focus has been largely on right censored survival data. We consider survival data that are subject to both left truncation and right censoring. Left truncation is well known to produce biased sample. The sampling bias issue has been resolved in the literature for the case which involves baseline or time-varying covariates that are observable. The problem remains open however for the important case where longitudinal covariates are present in survival models. A joint likelihood approach has been shown in the literature to provide an effective way to overcome those difficulties for right censored data, but this approach faces substantial additional challenges in the presence of left truncation. Here we thus propose an alternative likelihood to overcome these difficulties and show that the regression coefficient in the survival component can be estimated unbiasedly and efficiently. Issues about the bias for the longitudinal component are discussed. The new approach is illustrated numerically through simulations and data from a multi-center AIDS cohort study. PMID:29479122

Integrating the Ergonomics Techniques with Multi Criteria Decision Making as a New Approach for Risk Management: An Assessment of Repetitive Tasks -Entropy Case Study.

PubMed

Khandan, Mohammad; Nili, Majid; Koohpaei, Alireza; Mosaferchi, Saeedeh

2016-01-01

Nowadays, the health work decision makers need to analyze a huge amount of data and consider many conflicting evaluation criteria and sub-criteria. Therefore, an ergonomic evaluation in the work environment in order to the control occupational disorders is considered as the Multi Criteria Decision Making (MCDM) problem. In this study, the ergonomic risks factors, which may influence health, were evaluated in a manufacturing company in 2014. Then entropy method was applied to prioritize the different risk factors. This study was done with a descriptive-analytical approach and 13 tasks were included from total number of employees who were working in the seven halls of an ark opal manufacturing (240). Required information was gathered by the demographic questionnaire and Assessment of Repetitive Tasks (ART) method for repetitive task assessment. In addition, entropy was used to prioritize the risk factors based on the ergonomic control needs. The total exposure score based on the ART method calculated was equal to 30.07 ±12.43. Data analysis illustrated that 179 cases (74.6% of tasks) were in the high level of risk area and 13.8% were in the medium level of risk. ART- entropy results revealed that based on the weighted factors, higher value belongs to grip factor and the lowest value was related to neck and hand posture and duration. Based on the limited financial resources, it seems that MCDM in many challenging situations such as control procedures and priority approaches could be used successfully. Other MCDM methods for evaluating and prioritizing the ergonomic problems are recommended.

Aspiration dynamics of multi-player games in finite populations

PubMed Central

Du, Jinming; Wu, Bin; Altrock, Philipp M.; Wang, Long

2014-01-01

On studying strategy update rules in the framework of evolutionary game theory, one can differentiate between imitation processes and aspiration-driven dynamics. In the former case, individuals imitate the strategy of a more successful peer. In the latter case, individuals adjust their strategies based on a comparison of their pay-offs from the evolutionary game to a value they aspire, called the level of aspiration. Unlike imitation processes of pairwise comparison, aspiration-driven updates do not require additional information about the strategic environment and can thus be interpreted as being more spontaneous. Recent work has mainly focused on understanding how aspiration dynamics alter the evolutionary outcome in structured populations. However, the baseline case for understanding strategy selection is the well-mixed population case, which is still lacking sufficient understanding. We explore how aspiration-driven strategy-update dynamics under imperfect rationality influence the average abundance of a strategy in multi-player evolutionary games with two strategies. We analytically derive a condition under which a strategy is more abundant than the other in the weak selection limiting case. This approach has a long-standing history in evolutionary games and is mostly applied for its mathematical approachability. Hence, we also explore strong selection numerically, which shows that our weak selection condition is a robust predictor of the average abundance of a strategy. The condition turns out to differ from that of a wide class of imitation dynamics, as long as the game is not dyadic. Therefore, a strategy favoured under imitation dynamics can be disfavoured under aspiration dynamics. This does not require any population structure, and thus highlights the intrinsic difference between imitation and aspiration dynamics. PMID:24598208

Aspiration dynamics of multi-player games in finite populations.

PubMed

Du, Jinming; Wu, Bin; Altrock, Philipp M; Wang, Long

2014-05-06

On studying strategy update rules in the framework of evolutionary game theory, one can differentiate between imitation processes and aspiration-driven dynamics. In the former case, individuals imitate the strategy of a more successful peer. In the latter case, individuals adjust their strategies based on a comparison of their pay-offs from the evolutionary game to a value they aspire, called the level of aspiration. Unlike imitation processes of pairwise comparison, aspiration-driven updates do not require additional information about the strategic environment and can thus be interpreted as being more spontaneous. Recent work has mainly focused on understanding how aspiration dynamics alter the evolutionary outcome in structured populations. However, the baseline case for understanding strategy selection is the well-mixed population case, which is still lacking sufficient understanding. We explore how aspiration-driven strategy-update dynamics under imperfect rationality influence the average abundance of a strategy in multi-player evolutionary games with two strategies. We analytically derive a condition under which a strategy is more abundant than the other in the weak selection limiting case. This approach has a long-standing history in evolutionary games and is mostly applied for its mathematical approachability. Hence, we also explore strong selection numerically, which shows that our weak selection condition is a robust predictor of the average abundance of a strategy. The condition turns out to differ from that of a wide class of imitation dynamics, as long as the game is not dyadic. Therefore, a strategy favoured under imitation dynamics can be disfavoured under aspiration dynamics. This does not require any population structure, and thus highlights the intrinsic difference between imitation and aspiration dynamics.

Using VCL as an Aspect-Oriented Approach to Requirements Modelling

NASA Astrophysics Data System (ADS)

Amálio, Nuno; Kelsen, Pierre; Ma, Qin; Glodt, Christian

Software systems are becoming larger and more complex. By tackling the modularisation of crosscutting concerns, aspect orientation draws attention to modularity as a means to address the problems of scalability, complexity and evolution in software systems development. Aspect-oriented modelling (AOM) applies aspect-orientation to the construction of models. Most existing AOM approaches are designed without a formal semantics, and use multi-view partial descriptions of behaviour. This paper presents an AOM approach based on the Visual Contract Language (VCL): a visual language for abstract and precise modelling, designed with a formal semantics, and comprising a novel approach to visual behavioural modelling based on design by contract where behavioural descriptions are total. By applying VCL to a large case study of a car-crash crisis management system, the paper demonstrates how modularity of VCL's constructs, at different levels of granularity, help to tackle complexity. In particular, it shows how VCL's package construct and its associated composition mechanisms are key in supporting separation of concerns, coarse-grained problem decomposition and aspect-orientation. The case study's modelling solution has a clear and well-defined modular structure; the backbone of this structure is a collection of packages encapsulating local solutions to concerns.

Multi-Organization Multi-Discipline Effort Developing a Mitigation Concept for Planetary Defense

NASA Technical Reports Server (NTRS)

Leung, Ronald Y.; Barbee, Brent W.; Seery, Bernard D.; Bambacus, Myra; Finewood, Lee; Greenaugh, Kevin C.; Lewis, Anthony; Dearborn, David; Miller, Paul L.; Weaver, Robert P.;

Development of multi-functional streetscape green infrastructure using a performance index approach.

PubMed

Tiwary, A; Williams, I D; Heidrich, O; Namdeo, A; Bandaru, V; Calfapietra, C

2016-01-01

This paper presents a performance evaluation framework for streetscape vegetation. A performance index (PI) is conceived using the following seven traits, specific to the street environments - Pollution Flux Potential (PFP), Carbon Sequestration Potential (CSP), Thermal Comfort Potential (TCP), Noise Attenuation Potential (NAP), Biomass Energy Potential (BEP), Environmental Stress Tolerance (EST) and Crown Projection Factor (CPF). Its application is demonstrated through a case study using fifteen street vegetation species from the UK, utilising a combination of direct field measurements and inventoried literature data. Our results indicate greater preference to small-to-medium size trees and evergreen shrubs over larger trees for streetscaping. The proposed PI approach can be potentially applied two-fold: one, for evaluation of the performance of the existing street vegetation, facilitating the prospects for further improving them through management strategies and better species selection; two, for planning new streetscapes and multi-functional biomass as part of extending the green urban infrastructure. Copyright © 2015 Elsevier Ltd. All rights reserved.

Flexible resource management and its effect on project cost and duration

NASA Astrophysics Data System (ADS)

Pinha, Denis C.; Ahluwalia, Rashpal S.

2018-06-01

In practice, most projects result in cost overruns and schedule slippage due to poor resource management. This paper presents an approach that aims at reducing project duration and costs by empowering project managers to assess different scenarios. The proposed approach addresses combinatorial modes for tasks, multi-skilled resources, and multiple calendars for resources. A case study reported in the literature is presented to demonstrate the capabilities of this method. As for practical implications, this approach enhances the decision-making process which results in improved solutions in terms of total project duration and cost. From an academic viewpoint, this paper adds empirical evidence to enrich the existing literature, as it highlights relevant issues to model properly the complexity of real-life projects.

Person-centred web-based support--development through a Swedish multi-case study.

PubMed

Josefsson, Ulrika; Berg, Marie; Koinberg, Ingalill; Hellström, Anna-Lena; Nolbris, Margaretha Jenholt; Ranerup, Agneta; Lundin, Carina Sparud; Skärsäter, Ingela

2013-10-19

Departing from the widespread use of the internet in modern society and the emerging use of web applications in healthcare this project captures persons' needs and expectations in order to develop highly usable web recourses. The purpose of this paper is to outline a multi-case research project focused on the development and evaluation of person-centred web-based support for people with long-term illness. To support the underlying idea to move beyond the illness, we approach the development of web support from the perspective of the emergent area of person-centred care. The project aims to contribute to the ongoing development of web-based supports in health care and to the emerging field of person-centred care. The research design uses a meta-analytical approach through its focus on synthesizing experiences from four Swedish regional and national cases of design and use of web-based support in long-term illness. The cases include children (bladder dysfunction and urogenital malformation), young adults (living close to persons with mental illness), and two different cases of adults (women with breast cancer and childbearing women with type 1 diabetes). All of the cases are ongoing, though in different stages of design, implementation, and analysis. This, we argue, will lead to a synthesis of results on a meta-level not yet described. To allow valid comparisons between the four cases we explore and problematize them in relation to four main aspects: 1) The use of people's experiences and needs; 2) The role of use of theories in the design of person-centred web-based supports; 3) The evaluation of the effects of health outcomes for the informants involved and 4) The development of a generic person-centred model for learning and social support for people with long-term illness and their significant others. Person-centred web-based support is a new area and few studies focus on how web-based interventions can contribute to the development of person-centred care. In summary, the main intention of the project outlined here is to contribute with both a synthesis of results on meta-level from four cases and a substantial contribution to the field person-centred care.

Complementary methods to plan pedestrian evacuation of the French Riviera's beaches in case of tsunami threat: graph- and multi-agent-based modelling

NASA Astrophysics Data System (ADS)

Sahal, A.; Leone, F.; Péroche, M.

2013-07-01

Small amplitude tsunamis have impacted the French Mediterranean shore (French Riviera) in the past centuries. Some caused casualties; others only generated economic losses. While the North Atlantic and Mediterranean tsunami warning system is being tested and is almost operational, no awareness and preparedness measure is being implemented at a local scale. Evacuation is to be considered along the French Riviera, but no plan exists within communities. We show that various approaches can provide local stakeholders with evacuation capacities assessments to develop adapted evacuation plans through the case study of the Cannes-Antibes region. The complementarity between large- and small-scale approaches is demonstrated with the use of macro-simulators (graph-based) and micro-simulators (multi-agent-based) to select shelter points and choose evacuation routes for pedestrians located on the beach. The first one allows automatically selecting shelter points and measuring and mapping their accessibility. The second one shows potential congestion issues during pedestrian evacuations, and provides leads for the improvement of urban environment. Temporal accessibility to shelters is compared to potential local and distal tsunami travel times, showing a 40 min deficit for an adequate crisis management in the first scenario, and a 30 min surplus for the second one.

The Chandra Deep Field South as a test case for Global Multi Conjugate Adaptive Optics

NASA Astrophysics Data System (ADS)

Portaluri, E.; Viotto, V.; Ragazzoni, R.; Gullieuszik, M.; Bergomi, M.; Greggio, D.; Biondi, F.; Dima, M.; Magrin, D.; Farinato, J.

2017-04-01

The era of the next generation of giant telescopes requires not only the advent of new technologies but also the development of novel methods, in order to exploit fully the extraordinary potential they are built for. Global Multi Conjugate Adaptive Optics (GMCAO) pursues this approach, with the goal of achieving good performance over a field of view of a few arcmin and an increase in sky coverage. In this article, we show the gain offered by this technique to an astrophysical application, such as the photometric survey strategy applied to the Chandra Deep Field South as a case study. We simulated a close-to-real observation of a 500 × 500 arcsec2 extragalactic deep field with a 40-m class telescope that implements GMCAO. We analysed mock K-band images of 6000 high-redshift (up to z = 2.75) galaxies therein as if they were real to recover the initial input parameters. We attained 94.5 per cent completeness for source detection with SEXTRACTOR. We also measured the morphological parameters of all the sources with the two-dimensional fitting tools GALFIT. The agreement we found between recovered and intrinsic parameters demonstrates GMCAO as a reliable approach to assist extremely large telescope (ELT) observations of extragalactic interest.

A scale space feature based registration technique for fusion of satellite imagery

NASA Technical Reports Server (NTRS)

Raghavan, Srini; Cromp, Robert F.; Campbell, William C.

1997-01-01

Feature based registration is one of the most reliable methods to register multi-sensor images (both active and passive imagery) since features are often more reliable than intensity or radiometric values. The only situation where a feature based approach will fail is when the scene is completely homogenous or densely textural in which case a combination of feature and intensity based methods may yield better results. In this paper, we present some preliminary results of testing our scale space feature based registration technique, a modified version of feature based method developed earlier for classification of multi-sensor imagery. The proposed approach removes the sensitivity in parameter selection experienced in the earlier version as explained later.

Collaborative simulation method with spatiotemporal synchronization process control

NASA Astrophysics Data System (ADS)

Zou, Yisheng; Ding, Guofu; Zhang, Weihua; Zhang, Jian; Qin, Shengfeng; Tan, John Kian

2016-10-01

When designing a complex mechatronics system, such as high speed trains, it is relatively difficult to effectively simulate the entire system's dynamic behaviors because it involves multi-disciplinary subsystems. Currently,a most practical approach for multi-disciplinary simulation is interface based coupling simulation method, but it faces a twofold challenge: spatial and time unsynchronizations among multi-directional coupling simulation of subsystems. A new collaborative simulation method with spatiotemporal synchronization process control is proposed for coupling simulating a given complex mechatronics system across multiple subsystems on different platforms. The method consists of 1) a coupler-based coupling mechanisms to define the interfacing and interaction mechanisms among subsystems, and 2) a simulation process control algorithm to realize the coupling simulation in a spatiotemporal synchronized manner. The test results from a case study show that the proposed method 1) can certainly be used to simulate the sub-systems interactions under different simulation conditions in an engineering system, and 2) effectively supports multi-directional coupling simulation among multi-disciplinary subsystems. This method has been successfully applied in China high speed train design and development processes, demonstrating that it can be applied in a wide range of engineering systems design and simulation with improved efficiency and effectiveness.

Who needs collaborative care treatment? A qualitative study exploring attitudes towards and experiences with mental healthcare among general practitioners and care managers.

PubMed

Møller, Marlene Christina Rosengaard; Mygind, Anna; Bro, Flemming

2018-05-30

Collaborative care treatment is widely recognized as an effective approach to improve the quality of mental healthcare through enhanced and structured collaboration between general practice and specialized psychiatry. However, studies indicate that the complexity of collaborative care treatment interventions challenge the implementation in real-life general practice settings. Four Danish Collaborative Care Models were launched in 2014 for patients with mild/moderate anxiety and depression. These involved collaboration between general practitioners, care managers and consultant psychiatrists. Taking a multi-practice bottom-up approach, this paper aims to explore the perceived barriers and enablers related to collaborative care for patients with mental health problems and to investigate the actual experiences with a Danish collaborative care model in a single-case study in order to identify enablers and barriers for successful implementation. Combining interviews and observations of usual treatment practices, we conducted a multi-practice study among general practitioners who were not involved in the Danish collaborative care models to explore their perspectives on existing mental health treatment and to investigate (from a bottom-up approach) their perceptions of and need for collaborative care in mental health treatment. Additionally, by combining observations and qualitative interviews, we followed the implementation of a Danish collaborative care model in a single-case study to convey identified barriers and enablers of the collaborative care model. Experienced and perceived enablers of the Danish collaborative care model mainly consisted of a need for new treatment options to deal with mild/moderate anxiety and depression. The model was considered to meet the need for a free fast track to high-quality treatment. Experienced barriers included: poor adaptation of the model to the working conditions and needs in daily general practice, time consumption, unsustainable logistical set-up and unclear care manager role. General practitioners in the multi-practice study considered access to treatment and not collaboration with specialised psychiatry to be essential for this group of patients. The study calls for increased attention to implementation processes and better adaptation of collaborative care models to the clinical reality of general practice. Future interventions should address the treatment needs of specific patient populations and should involve relevant stakeholders in the design and implementation processes.

Approaches in Characterizing Genetic Structure and Mapping in a Rice Multiparental Population.

PubMed

Raghavan, Chitra; Mauleon, Ramil; Lacorte, Vanica; Jubay, Monalisa; Zaw, Hein; Bonifacio, Justine; Singh, Rakesh Kumar; Huang, B Emma; Leung, Hei

2017-06-07

Multi-parent Advanced Generation Intercross (MAGIC) populations are fast becoming mainstream tools for research and breeding, along with the technology and tools for analysis. This paper demonstrates the analysis of a rice MAGIC population from data filtering to imputation and processing of genetic data to characterizing genomic structure, and finally quantitative trait loci (QTL) mapping. In this study, 1316 S6:8 indica MAGIC (MI) lines and the eight founders were sequenced using Genotyping by Sequencing (GBS). As the GBS approach often includes missing data, the first step was to impute the missing SNPs. The observable number of recombinations in the population was then explored. Based on this case study, a general outline of procedures for a MAGIC analysis workflow is provided, as well as for QTL mapping of agronomic traits and biotic and abiotic stress, using the results from both association and interval mapping approaches. QTL for agronomic traits (yield, flowering time, and plant height), physical (grain length and grain width) and cooking properties (amylose content) of the rice grain, abiotic stress (submergence tolerance), and biotic stress (brown spot disease) were mapped. Through presenting this extensive analysis in the MI population in rice, we highlight important considerations when choosing analytical approaches. The methods and results reported in this paper will provide a guide to future genetic analysis methods applied to multi-parent populations. Copyright © 2017 Raghavan et al.

Integration of topological modification within the modeling of multi-physics systems: Application to a Pogo-stick

NASA Astrophysics Data System (ADS)

Abdeljabbar Kharrat, Nourhene; Plateaux, Régis; Miladi Chaabane, Mariem; Choley, Jean-Yves; Karra, Chafik; Haddar, Mohamed

2018-05-01

The present work tackles the modeling of multi-physics systems applying a topological approach while proceeding with a new methodology using a topological modification to the structure of systems. Then the comparison with the Magos' methodology is made. Their common ground is the use of connectivity within systems. The comparison and analysis of the different types of modeling show the importance of the topological methodology through the integration of the topological modification to the topological structure of a multi-physics system. In order to validate this methodology, the case of Pogo-stick is studied. The first step consists in generating a topological graph of the system. Then the connectivity step takes into account the contact with the ground. During the last step of this research; the MGS language (Modeling of General System) is used to model the system through equations. Finally, the results are compared to those obtained by MODELICA. Therefore, this proposed methodology may be generalized to model multi-physics systems that can be considered as a set of local elements.

Multi-objective decision-making model based on CBM for an aircraft fleet

NASA Astrophysics Data System (ADS)

Luo, Bin; Lin, Lin

2018-04-01

Modern production management patterns, in which multi-unit (e.g., a fleet of aircrafts) are managed in a holistic manner, have brought new challenges for multi-unit maintenance decision making. To schedule a good maintenance plan, not only does the individual machine maintenance have to be considered, but also the maintenance of the other individuals have to be taken into account. Since most condition-based maintenance researches for aircraft focused on solely reducing maintenance cost or maximizing the availability of single aircraft, as well as considering that seldom researches concentrated on both the two objectives: minimizing cost and maximizing the availability of a fleet (total number of available aircraft in fleet), a multi-objective decision-making model based on condition-based maintenance concentrated both on the above two objectives is established. Furthermore, in consideration of the decision maker may prefer providing the final optimal result in the form of discrete intervals instead of a set of points (non-dominated solutions) in real decision-making problem, a novel multi-objective optimization method based on support vector regression is proposed to solve the above multi-objective decision-making model. Finally, a case study regarding a fleet is conducted, with the results proving that the approach efficiently generates outcomes that meet the schedule requirements.

Perventricular double-device closure of wide-spaced multi-hole perimembranous ventricular septal defect.

PubMed

Liang, Fei; Hongxin, Li; Zhang, Hai-Zhou; Wenbin, Guo; Zou, Cheng-Wei; Farhaj, Zeeshan

2017-04-17

Device closure of a wide-spaced multi-hole PmVSD is difficult to succeed in percutaneous approach. This study is to evaluate the feasibility, safety and efficacy of perventricular device closure of wide-spaced multi-hole PmVSD using a double-device implanting technique. Sixteen patients with wide-spaced multi-hole PmVSD underwent perventricular closure with two devices through an inferior median sternotomy approach under transesophageal echocardiographic guidance. The largest hole and its adjacent small holes were occluded with an optimal-sized device. The far-away residual hole was occluded with the other device using a probe-assisted delivery system. All patients were followed up for a period of 1 to 4 years to determine the residual shunt, atrioventricular block and the adjacent valvular function. The number of the holes of the PmVSD was 2 to 4. The maximum distance between the holes was 5.0 to 10.0 mm (median, 6.4 mm). The diameter of the largest hole was 2.5 to 7.0 mm (median, 3.6 mm). The success rate of double-device closure was 100%. Immediate residual shunts were found in 6 patients (38%), and incomplete right bundle branch block at discharge occurred in 3 cases (19%). Both complications decreased to 6% at 1-year follow-up. Neither of them had a severe device-related complication. Perventricular closure of a wide-spaced multi-hole PmVSD using a double-device implanting technique is feasible, safe, and efficacious. In multi-hole PmVSDs with the distance between the holes of more than 5 mm, double-device implantation may achieve a complete occlusion.

Characteristics of recent dust storms over the Indian region using real time multi-satellite observations from the direct broadcast receiving system at IMD

NASA Astrophysics Data System (ADS)

Mitra, A. K.; Sharma, A. K.; Soni, V. K.; Kundu, P. K.

2013-04-01

In this study, observations from microwave satellites, visible and infrared instruments have been analyzed to detect dust storm over north and north-west part of India during 18-23 March 2012. This study investigated the approach to utilize the multi satellite data of Moderate Resolution Imaging Spectroradiometer (MODIS) on-board the Terra and Aqua satellite and the Advanced Microwave Sounding Unit (AMSU) on-board NOAA satellite to study the characteristics of dust storms from real time direct broadcast (DB) receiving system installed at three places of India Meteorological Department (IMD). The dust storm detection is based on the infrared brightness temperature (BT) difference between channels at 11 and 12 μm and polarized BT difference between two channels of 89 and 23.8 GHz. It is found that the significant differences between the BT of channel 89 and 23.8 can be used as a discriminator of identifying dust storm. The Total Ozone Mapping Spectroradiometer (TOMS) Aerosol Index (AI) and AMSU-A 23 GHz channel BT from NOAA satellite over the north and north-west part of India have also been analyzed. The result indicated the characteristic behavior between BT and AI during the different phases of the dust storm. Finally, the occurrence of dust outbreaks has also been validated with sky radiometer of IMD, which confirms the presence of a dust storm over the Indian region. Further, the findings of the study and its approaches apply to the other dust storm cases which occurred during the months of April and June 2012. The integrated approach suggested the potential to use high resolution data of microwave as well as thermal-infrared using multi-satellite observations from real time direct broadcast system for the detection of severe, moderate or weak dust storms very well. The approach is found to be promising for operational application.

A framework for multi-stakeholder decision-making and ...

EPA Pesticide Factsheets

We propose a decision-making framework to compute compromise solutions that balance conflicting priorities of multiple stakeholders on multiple objectives. In our setting, we shape the stakeholder dis-satisfaction distribution by solving a conditional-value-at-risk (CVaR) minimization problem. The CVaR problem is parameterized by a probability level that shapes the tail of the dissatisfaction distribution. The proposed approach allows us to compute a family of compromise solutions and generalizes multi-stakeholder settings previously proposed in the literature that minimize average and worst-case dissatisfactions. We use the concept of the CVaR norm to give a geometric interpretation to this problem +and use the properties of this norm to prove that the CVaR minimization problem yields Pareto optimal solutions for any choice of the probability level. We discuss a broad range of potential applications of the framework that involve complex decision-making processes. We demonstrate the developments using a biowaste facility location case study in which we seek to balance stakeholder priorities on transportation, safety, water quality, and capital costs. This manuscript describes the methodology of a new decision-making framework that computes compromise solutions that balance conflicting priorities of multiple stakeholders on multiple objectives as needed for SHC Decision Science and Support Tools project. A biowaste facility location is employed as the case study

Design and analysis of compound flexible skin based on deformable honeycomb

NASA Astrophysics Data System (ADS)

Zou, Tingting; Zhou, Li

2017-04-01

In this study, we focused at the development and verification of a robust framework for surface crack detection in steel pipes using measured vibration responses; with the presence of multiple progressive damage occurring in different locations within the structure. Feature selection, dimensionality reduction, and multi-class support vector machine were established for this purpose. Nine damage cases, at different locations, orientations and length, were introduced into the pipe structure. The pipe was impacted 300 times using an impact hammer, after each damage case, the vibration data were collected using 3 PZT wafers which were installed on the outer surface of the pipe. At first, damage sensitive features were extracted using the frequency response function approach followed by recursive feature elimination for dimensionality reduction. Then, a multi-class support vector machine learning algorithm was employed to train the data and generate a statistical model. Once the model is established, decision values and distances from the hyper-plane were generated for the new collected data using the trained model. This process was repeated on the data collected from each sensor. Overall, using a single sensor for training and testing led to a very high accuracy reaching 98% in the assessment of the 9 damage cases used in this study.

Machine learning action parameters in lattice quantum chromodynamics

NASA Astrophysics Data System (ADS)

Shanahan, Phiala E.; Trewartha, Daniel; Detmold, William

2018-05-01

Numerical lattice quantum chromodynamics studies of the strong interaction are important in many aspects of particle and nuclear physics. Such studies require significant computing resources to undertake. A number of proposed methods promise improved efficiency of lattice calculations, and access to regions of parameter space that are currently computationally intractable, via multi-scale action-matching approaches that necessitate parametric regression of generated lattice datasets. The applicability of machine learning to this regression task is investigated, with deep neural networks found to provide an efficient solution even in cases where approaches such as principal component analysis fail. The high information content and complex symmetries inherent in lattice QCD datasets require custom neural network layers to be introduced and present opportunities for further development.

Multi-GPU implementation of a VMAT treatment plan optimization algorithm

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tian, Zhen, E-mail: Zhen.Tian@UTSouthwestern.edu, E-mail: Xun.Jia@UTSouthwestern.edu, E-mail: Steve.Jiang@UTSouthwestern.edu; Folkerts, Michael; Tan, Jun

Purpose: Volumetric modulated arc therapy (VMAT) optimization is a computationally challenging problem due to its large data size, high degrees of freedom, and many hardware constraints. High-performance graphics processing units (GPUs) have been used to speed up the computations. However, GPU’s relatively small memory size cannot handle cases with a large dose-deposition coefficient (DDC) matrix in cases of, e.g., those with a large target size, multiple targets, multiple arcs, and/or small beamlet size. The main purpose of this paper is to report an implementation of a column-generation-based VMAT algorithm, previously developed in the authors’ group, on a multi-GPU platform tomore » solve the memory limitation problem. While the column-generation-based VMAT algorithm has been previously developed, the GPU implementation details have not been reported. Hence, another purpose is to present detailed techniques employed for GPU implementation. The authors also would like to utilize this particular problem as an example problem to study the feasibility of using a multi-GPU platform to solve large-scale problems in medical physics. Methods: The column-generation approach generates VMAT apertures sequentially by solving a pricing problem (PP) and a master problem (MP) iteratively. In the authors’ method, the sparse DDC matrix is first stored on a CPU in coordinate list format (COO). On the GPU side, this matrix is split into four submatrices according to beam angles, which are stored on four GPUs in compressed sparse row format. Computation of beamlet price, the first step in PP, is accomplished using multi-GPUs. A fast inter-GPU data transfer scheme is accomplished using peer-to-peer access. The remaining steps of PP and MP problems are implemented on CPU or a single GPU due to their modest problem scale and computational loads. Barzilai and Borwein algorithm with a subspace step scheme is adopted here to solve the MP problem. A head and neck (H and N) cancer case is then used to validate the authors’ method. The authors also compare their multi-GPU implementation with three different single GPU implementation strategies, i.e., truncating DDC matrix (S1), repeatedly transferring DDC matrix between CPU and GPU (S2), and porting computations involving DDC matrix to CPU (S3), in terms of both plan quality and computational efficiency. Two more H and N patient cases and three prostate cases are used to demonstrate the advantages of the authors’ method. Results: The authors’ multi-GPU implementation can finish the optimization process within ∼1 min for the H and N patient case. S1 leads to an inferior plan quality although its total time was 10 s shorter than the multi-GPU implementation due to the reduced matrix size. S2 and S3 yield the same plan quality as the multi-GPU implementation but take ∼4 and ∼6 min, respectively. High computational efficiency was consistently achieved for the other five patient cases tested, with VMAT plans of clinically acceptable quality obtained within 23–46 s. Conversely, to obtain clinically comparable or acceptable plans for all six of these VMAT cases that the authors have tested in this paper, the optimization time needed in a commercial TPS system on CPU was found to be in an order of several minutes. Conclusions: The results demonstrate that the multi-GPU implementation of the authors’ column-generation-based VMAT optimization can handle the large-scale VMAT optimization problem efficiently without sacrificing plan quality. The authors’ study may serve as an example to shed some light on other large-scale medical physics problems that require multi-GPU techniques.« less

A Qualitative Multi-Site Case Study: Examining Principals' Leadership Styles and School Performance

ERIC Educational Resources Information Center

Preyear, Loukisha

2015-01-01

The purpose of this qualitative multi-site case study was to explore the impact of principals' leadership styles on student academic achievement in a high-poverty low-performing school district in Louisiana. A total of 17 participants, principals and teachers, from this school district were used in this study. Data source triangulation of…

The CLUVA project: Climate-change scenarios and their impact on urban areas in Africa

NASA Astrophysics Data System (ADS)

Di Ruocco, Angela; Weets, Guy; Gasparini, Paolo; Jørgensen, Gertrud; Lindley, Sarah; Pauleit, Stephan; Vahed, Anwar; Schiano, Pasquale; Kabisch, Sigrun; Vedeld, Trond; Coly, Adrien; Tonye, Emmanuel; Touré, Hamidou; Kombe, Wilbard; Yeshitela, Kumelachew

2013-04-01

CLUVA (CLimate change and Urban Vulnerability in Africa; http://www.cluva.eu/) is a 3 years project, funded by the European Commission in 2010. Its main objective is the estimate of the impacts of climate changes in the next 40 years at urban scale in Africa. The mission of CLUVA is to develop methods and knowledge to assess risks cascading from climate-changes. It downscales IPCC climate projections to evaluate threats to selected African test cities; mainly floods, sea-level rise, droughts, heat waves and desertification. The project evaluates and links: social vulnerability; vulnerability of in-town ecosystems and urban-rural interfaces; vulnerability of urban built environment and lifelines; and related institutional and governance dimensions of adaptation. A multi-scale and multi-disciplinary quantitative, probabilistic, modelling is applied. CLUVA brings together climate experts, risk management experts, urban planners and social scientists with their African counterparts in an integrated research effort focusing on the improvement of the capacity of scientific institutions, local councils and civil society to cope with climate change. The CLUVA approach was set-up in the first year of the project and developed as follows: an ensemble of eight global projections of climate changes is produced for east and west Africa until 2050 considering the new IPCC (International Panel on Climate Changes; http://www.ipcc.ch/) scenarios. These are then downscaled to urban level, where territorial modeling is required to compute hazard effects on the vulnerable physical system (urban ecosystems, informal settlements, lifelines such as transportation and sewer networks) as well as on the social context, in defined time frames, and risk analysis is then employed to assess expected consequences. An investigation of the existing urban planning and governance systems and its interface with climate risks is performed. With the aid of the African partners, the developed approach is currently being applied to selected African case studies: Addis Ababa - Ethiopia; Dar es Salaam - Tanzania, Douala - Cameroun; Ouagadougou - Burkina Faso, St. Louis - Senegal. The poster will illustrate the CLUVA's framework to assess climate-change-related risks at an urban scale in Africa, and will report on the progresses of selected case studies to demonstrate feasibility of a multi-scale and multi-risk quantitative approach for risk management.

Development of an International Canine Spinal Cord Injury observational registry: a collaborative data-sharing network to optimize translational studies of SCI.

PubMed

Moore, Sarah A; Zidan, Natalia; Spitzbarth, Ingo; Nout-Lomas, Yvette S; Granger, Nicolas; da Costa, Ronaldo C; Levine, Jonathan M; Jeffery, Nick D; Stein, Veronika M; Tipold, Andrea; Olby, Natasha J

2018-05-23

Prospective cross-sectional cohort study. The canine spontaneous model of spinal cord injury (SCI) is as an important pre-clinical platform as it recapitulates key facets of human injury in a naturally occurring context. The establishment of an observational canine SCI registry constitutes a key step in performing epidemiologic studies and assessing the impact of therapeutic strategies to enhance translational research. Further, accumulating information on dogs with SCI may contribute to current "big data" approaches to enhance understanding of the disease using heterogeneous multi-institutional, multi-species datasets from both pre-clinical and human studies. Multiple veterinary academic institutions across the United States and Europe. Common data elements recommended for experimental and human SCI studies were reviewed and adapted for use in a web-based registry, to which all dogs presenting to member veterinary tertiary care facilities were prospectively entered over ~1 year. Analysis of data accumulated during the first year of the registry suggests that 16% of dogs with SCI present with severe, sensorimotor-complete injury and that 15% of cases are seen by a tertiary care facility within 8 h of injury. Similar to the human SCI population, 34% were either overweight or obese. Severity of injury and timing of presentation suggests that neuroprotective studies using the canine clinical model could be conducted efficiently using a multi-institutional approach. Additionally, pet dogs with SCI experience similar comorbidities to people with SCI, in particular obesity, and could serve as an important model to evaluate the effects of this condition.

Development and Applications of Advanced Electronic Structure Methods

NASA Astrophysics Data System (ADS)

Bell, Franziska

This dissertation contributes to three different areas in electronic structure theory. The first part of this thesis advances the fundamentals of orbital active spaces. Orbital active spaces are not only essential in multi-reference approaches, but have also become of interest in single-reference methods as they allow otherwise intractably large systems to be studied. However, despite their great importance, the optimal choice and, more importantly, their physical significance are still not fully understood. In order to address this problem, we studied the higher-order singular value decomposition (HOSVD) in the context of electronic structure methods. We were able to gain a physical understanding of the resulting orbitals and proved a connection to unrelaxed natural orbitals in the case of Moller-Plesset perturbation theory to second order (MP2). In the quest to find the optimal choice of the active space, we proposed a HOSVD for energy-weighted integrals, which yielded the fastest convergence in MP2 correlation energy for small- to medium-sized active spaces to date, and is also potentially transferable to coupled-cluster theory. In the second part, we studied monomeric and dimeric glycerol radical cations and their photo-induced dissociation in collaboration with Prof. Leone and his group. Understanding the mechanistic details involved in these processes are essential for further studies on the combustion of glycerol and carbohydrates. To our surprise, we found that in most cases, the experimentally observed appearance energies arise from the separation of product fragments from one another rather than rearrangement to products. The final chapters of this work focus on the development, assessment, and application of the spin-flip method, which is a single-reference approach, but capable of describing multi-reference problems. Systems exhibiting multi-reference character, which arises from the (near-) degeneracy of orbital energies, are amongst the most interesting in chemistry, biology and materials science, yet amongst the most challenging to study with electronic structure methods. In particular, we explored a substituted dimeric BPBP molecule with potential tetraradical character, which gained attention as one of the most promising candidates for an organic conductor. Furthermore, we extended the spin-flip approach to include variable orbital active spaces and multiple spin-flips. This allowed us to perform wave-function-based studies of ground- and excited-states of polynuclear metal complexes, polyradicals, and bond-dissociation processes involving three or more bonds.

Multi-level, multi-scale resource selection functions and resistance surfaces for conservation planning: Pumas as a case study

PubMed Central

Vickers, T. Winston; Ernest, Holly B.; Boyce, Walter M.

2017-01-01

The importance of examining multiple hierarchical levels when modeling resource use for wildlife has been acknowledged for decades. Multi-level resource selection functions have recently been promoted as a method to synthesize resource use across nested organizational levels into a single predictive surface. Analyzing multiple scales of selection within each hierarchical level further strengthens multi-level resource selection functions. We extend this multi-level, multi-scale framework to modeling resistance for wildlife by combining multi-scale resistance surfaces from two data types, genetic and movement. Resistance estimation has typically been conducted with one of these data types, or compared between the two. However, we contend it is not an either/or issue and that resistance may be better-modeled using a combination of resistance surfaces that represent processes at different hierarchical levels. Resistance surfaces estimated from genetic data characterize temporally broad-scale dispersal and successful breeding over generations, whereas resistance surfaces estimated from movement data represent fine-scale travel and contextualized movement decisions. We used telemetry and genetic data from a long-term study on pumas (Puma concolor) in a highly developed landscape in southern California to develop a multi-level, multi-scale resource selection function and a multi-level, multi-scale resistance surface. We used these multi-level, multi-scale surfaces to identify resource use patches and resistant kernel corridors. Across levels, we found puma avoided urban, agricultural areas, and roads and preferred riparian areas and more rugged terrain. For other landscape features, selection differed among levels, as did the scales of selection for each feature. With these results, we developed a conservation plan for one of the most isolated puma populations in the U.S. Our approach captured a wide spectrum of ecological relationships for a population, resulted in effective conservation planning, and can be readily applied to other wildlife species. PMID:28609466

Multi-level, multi-scale resource selection functions and resistance surfaces for conservation planning: Pumas as a case study.

PubMed

Zeller, Katherine A; Vickers, T Winston; Ernest, Holly B; Boyce, Walter M

2017-01-01

The importance of examining multiple hierarchical levels when modeling resource use for wildlife has been acknowledged for decades. Multi-level resource selection functions have recently been promoted as a method to synthesize resource use across nested organizational levels into a single predictive surface. Analyzing multiple scales of selection within each hierarchical level further strengthens multi-level resource selection functions. We extend this multi-level, multi-scale framework to modeling resistance for wildlife by combining multi-scale resistance surfaces from two data types, genetic and movement. Resistance estimation has typically been conducted with one of these data types, or compared between the two. However, we contend it is not an either/or issue and that resistance may be better-modeled using a combination of resistance surfaces that represent processes at different hierarchical levels. Resistance surfaces estimated from genetic data characterize temporally broad-scale dispersal and successful breeding over generations, whereas resistance surfaces estimated from movement data represent fine-scale travel and contextualized movement decisions. We used telemetry and genetic data from a long-term study on pumas (Puma concolor) in a highly developed landscape in southern California to develop a multi-level, multi-scale resource selection function and a multi-level, multi-scale resistance surface. We used these multi-level, multi-scale surfaces to identify resource use patches and resistant kernel corridors. Across levels, we found puma avoided urban, agricultural areas, and roads and preferred riparian areas and more rugged terrain. For other landscape features, selection differed among levels, as did the scales of selection for each feature. With these results, we developed a conservation plan for one of the most isolated puma populations in the U.S. Our approach captured a wide spectrum of ecological relationships for a population, resulted in effective conservation planning, and can be readily applied to other wildlife species.

Power calculation for comparing diagnostic accuracies in a multi-reader, multi-test design.

PubMed

Kim, Eunhee; Zhang, Zheng; Wang, Youdan; Zeng, Donglin

2014-12-01

Receiver operating characteristic (ROC) analysis is widely used to evaluate the performance of diagnostic tests with continuous or ordinal responses. A popular study design for assessing the accuracy of diagnostic tests involves multiple readers interpreting multiple diagnostic test results, called the multi-reader, multi-test design. Although several different approaches to analyzing data from this design exist, few methods have discussed the sample size and power issues. In this article, we develop a power formula to compare the correlated areas under the ROC curves (AUC) in a multi-reader, multi-test design. We present a nonparametric approach to estimate and compare the correlated AUCs by extending DeLong et al.'s (1988, Biometrics 44, 837-845) approach. A power formula is derived based on the asymptotic distribution of the nonparametric AUCs. Simulation studies are conducted to demonstrate the performance of the proposed power formula and an example is provided to illustrate the proposed procedure. © 2014, The International Biometric Society.

School-Based Cognitive-Behavioral Therapy for an Adolescent Presenting with ADHD and Explosive Anger: A Case Study

ERIC Educational Resources Information Center

Parker, Janise; Zaboski, Brian; Joyce-Beaulieu, Diana

2016-01-01

This case demonstrates the efficacy of utilizing an intensive, multi-faceted behavioral intervention paradigm. A comprehensive, integrative, school-based service model was applied to address attention deficit hyperactivity disorder symptomology, oppositional behaviors, and explosive anger at the secondary level. The case reviews a multi-modal…

A multi-level approach for investigating socio-economic and agricultural risk factors associated with rates of reported cases of Escherichia coli O157 in humans in Alberta, Canada.

PubMed

Pearl, D L; Louie, M; Chui, L; Doré, K; Grimsrud, K M; Martin, S W; Michel, P; Svenson, L W; McEwen, S A

2009-10-01

Using negative binomial and multi-level Poisson models, the authors determined the statistical significance of agricultural and socio-economic risk factors for rates of reported disease associated with Escherichia coli O157 in census subdivisions (CSDs) in Alberta, Canada, 2000-2002. Variables relating to population stability, aboriginal composition of the CSDs, and the economic relationship between CSDs and urban centres were significant risk factors. The percentage of individuals living in low-income households was not a statistically significant risk factor for rates of disease. The statistical significance of cattle density, recorded at a higher geographical level, depended on the method used to correct for overdispersion, the number of levels included in the multi-level models, and the choice of using all reported cases or only sporadic cases. Our results highlight the importance of local socio-economic risk factors in determining rates of disease associated with E. coli O157, but their relationship with individual risk factors requires further evaluation.

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

NASA Astrophysics Data System (ADS)

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.

Snow instability evaluation: calculating the skier-induced stress in a multi-layered snowpack

NASA Astrophysics Data System (ADS)

Monti, F.; Gaume, J.; van Herwijnen, A.; Schweizer, J.

2015-08-01

The process of dry-snow slab avalanche formation can be divided into two phases: failure initiation and crack propagation. Several approaches tried to quantify slab avalanche release probability in terms of failure initiation based on shear stress and strength. Though it is known that both the properties of the weak layer and the slab play a major role in avalanche release, most previous approaches only considered slab properties in terms of slab depth, average density and skier penetration. For example, for the skier stability index, the additional stress (e.g. due to a skier) at the depth of the weak layer is calculated by assuming that the snow cover can be considered a semi-infinite, elastic half-space. We suggest a new approach based on a simplification of the multi-layered elasticity theory in order to easily compute the additional stress due to a skier at the depth of the weak layer taking into account the layering of the snow slab and the substratum. We first tested the proposed approach on simplified snow profiles, then on manually observed snow profiles including a stability test and, finally, on simulated snow profiles. Our simple approach well reproduced the additional stress obtained by finite element simulations for the simplified profiles - except that the sequence of layering in the slab cannot be replicated. Once implemented into the classical skier stability index and applied to manually observed snow profiles classified into different stability classes, the classification accuracy improved with the new approach. Finally, we implemented the refined skier stability index into the 1-D snow cover model SNOWPACK. For the two study cases presented in this paper, this approach showed promising results even though further verification is still needed. In the future, we intend to implement the proposed approach for describing skier-induced stress within a multi-layered snowpack into more complex models which take into account not only failure initiation but also crack propagation.

Fuzzy Logic in Legal Education

ERIC Educational Resources Information Center

Balkir, Z. Gonul; Alniacik, Umit; Apaydin, Eylem

2011-01-01

The necessity of examination of every case within its peculiar conditions in social sciences requires different approaches complying with the spirit and nature of social sciences. Multiple realities require different and various perceptual interpretations. In modern world and social sciences, interpretation of perception of valued and multi-valued…

Navier-Stokes calculations on multi-element airfoils using a chimera-based solver

NASA Technical Reports Server (NTRS)

Jasper, Donald W.; Agrawal, Shreekant; Robinson, Brian A.

1993-01-01

A study of Navier-Stokes calculations of flows about multielement airfoils using a chimera grid approach is presented. The chimera approach utilizes structured, overlapped grids which allow great flexibility of grid arrangement and simplifies grid generation. Calculations are made for two-, three-, and four-element airfoils, and modeling of the effect of gap distance between elements is demonstrated for a two element case. Solutions are obtained using the thin-layer form of the Reynolds averaged Navier-Stokes equations with turbulence closure provided by the Baldwin-Lomax algebraic model or the Baldwin-Barth one equation model. The Baldwin-Barth turbulence model is shown to provide better agreement with experimental data and to dramatically improve convergence rates for some cases. Recently developed, improved farfield boundary conditions are incorporated into the solver for greater efficiency. Computed results show good comparison with experimental data which include aerodynamic forces, surface pressures, and boundary layer velocity profiles.

Reynolds-averaged Navier-Stokes based ice accretion for aircraft wings

NASA Astrophysics Data System (ADS)

Lashkajani, Kazem Hasanzadeh

This thesis addresses one of the current issues in flight safety towards increasing icing simulation capabilities for prediction of complex 2D and 3D glaze ice shapes over aircraft surfaces. During the 1980's and 1990's, the field of aero-icing was established to support design and certification of aircraft flying in icing conditions. The multidisciplinary technologies used in such codes were: aerodynamics (panel method), droplet trajectory calculations (Lagrangian framework), thermodynamic module (Messinger model) and geometry module (ice accretion). These are embedded in a quasi-steady module to simulate the time-dependent ice accretion process (multi-step procedure). The objectives of the present research are to upgrade the aerodynamic module from Laplace to Reynolds-Average Navier-Stokes equations solver. The advantages are many. First, the physical model allows accounting for viscous effects in the aerodynamic module. Second, the solution of the aero-icing module directly provides the means for characterizing the aerodynamic effects of icing, such as loss of lift and increased drag. Third, the use of a finite volume approach to solving the Partial Differential Equations allows rigorous mesh and time convergence analysis. Finally, the approaches developed in 2D can be easily transposed to 3D problems. The research was performed in three major steps, each providing insights into the overall numerical approaches. The most important realization comes from the need to develop specific mesh generation algorithms to ensure feasible solutions in very complex multi-step aero-icing calculations. The contributions are presented in chronological order of their realization. First, a new framework for RANS based two-dimensional ice accretion code, CANICE2D-NS, is developed. A multi-block RANS code from U. of Liverpool (named PMB) is providing the aerodynamic field using the Spalart-Allmaras turbulence model. The ICEM-CFD commercial tool is used for the iced airfoil remeshing and field smoothing. The new coupling is fully automated and capable of multi-step ice accretion simulations via a quasi-steady approach. In addition, the framework allows for flow analysis and aerodynamic performance prediction of the iced airfoils. The convergence of the quasi-steady algorithm is verified and identifies the need for an order of magnitude increase in the number of multi-time steps in icing simulations to achieve solver independent solutions. Second, a Multi-Block Navier-Stokes code, NSMB, is coupled with the CANICE2D icing framework. Attention is paid to the roughness implementation of the ONERA roughness model within the Spalart-Allmaras turbulence model, and to the convergence of the steady and quasi-steady iterative procedure. Effects of uniform surface roughness in quasi-steady ice accretion simulation are analyzed through different validation test cases. The results of CANICE2D-NS show good agreement with experimental data both in terms of predicted ice shapes as well as aerodynamic analysis of predicted and experimental ice shapes. Third, an efficient single-block structured Navier-Stokes CFD code, NSCODE, is coupled with the CANICE2D-NS icing framework. Attention is paid to the roughness implementation of the Boeing model within the Spalart-Allmaras turbulence model, and to acceleration of the convergence of the steady and quasi-steady iterative procedures. Effects of uniform surface roughness in quasi-steady ice accretion simulation are analyzed through different validation test cases, including code to code comparisons with the same framework coupled with the NSMB Navier-Stokes solver. The efficiency of the J-multigrid approach to solve the flow equations on complex iced geometries is demonstrated. Since it was noted in all these calculations that the ICEM-CFD grid generation package produced a number of issues such as inefficient mesh quality and smoothing deficiencies (notably grid shocks), a fourth study proposes a new mesh generation algorithm. A PDE based multi-block structured grid generation code, NSGRID, is developed for this purpose. The study includes the developments of novel mesh generation algorithms over complex glaze ice shapes containing multi-curvature ice accretion geometries, such as single/double ice horns. The twofold approaches tackle surface geometry discretization as well as field mesh generation. An adaptive curvilinear curvature control algorithm is constructed solving a 1D elliptic PDE equation with periodic source terms. This method controls the arclength grid spacing so that high convex and concave curvature regions around ice horns are appropriately captured and is shown to effectively treat the grid shock problem. Then, a novel blended method is developed by defining combinations of source terms with 2D elliptic equations. The source terms include two common control functions, Sorenson and Spekreijse, and an additional third source term to improve orthogonality. This blended method is shown to be very effective for improving grid quality metrics for complex glaze ice meshes with RANS resolution. The performance in terms of residual reduction per non-linear iteration of several solution algorithms (Point-Jacobi, Gauss-Seidel, ADI, Point and Line SOR) are discussed within the context of a full Multi-grid operator. Details are given on the various formulations used in the linearization process. It is shown that the performance of the solution algorithm depends on the type of control function used. Finally, the algorithms are validated on standard complex experimental ice shapes, demonstrating the applicability of the methods. Finally, the automated framework of RANS based two-dimensional multi-step ice accretion, CANICE2D-NS is developed, coupled with a Multi-Block Navier-Stokes CFD code, NSCODE2D, a Multi-Block elliptic grid generation code, NSGRID2D, and a Multi-Block Eulerian droplet solver, NSDROP2D (developed at Polytechnique Montreal). The framework allows Lagrangian and Eulerian droplet computations within a chimera approach treating multi-elements geometries. The code was tested on public and confidential validation test cases including standard NATO cases. In addition, up to 10 times speedup is observed in the mesh generation procedure by using the implicit line SOR and ADI smoothers within a multigrid procedure. The results demonstrate the benefits and robustness of the new framework in predicting ice shapes and aerodynamic performance parameters.

A new approach to assess the skier additional stress within a multi-layered snowpack

NASA Astrophysics Data System (ADS)

Monti, Fabiano; Gaume, Johan; van Herwijnen, Alec; Schweizer, Jürg

2014-05-01

The physical and mechanical processes of dry-snow slab avalanche formation can be distinguished into two subsequent phases: failure initiation and crack propagation. Several approaches tried to quantify slab avalanche release probability in terms of failure initiation, based on a simple strength-of-material approach (strength vs. stress). Even if it is known that both weak layer and slab properties play a major role in avalanche release, apart from weak layer characteristics, often only the slab thickness and its average density were considered. For calculating the amount of additional stress (e.g. due to a skier) at the depth of the weak layer, the snow cover was often assumed to be a semi-infinite elastic half space in order to apply Boussinesq's theory. However, finite element (FE) calculations have shown that slab layering strongly influences the stress at depth. To avoid FE calculations, we suggest a new approach based on a simplification of multi-layered elasticity theory. It allows computing the additional stress due to a skier at the depth of the weak layer, taking into account the layering of the snow slab and the substratum. The proposed approach was first tested on simplified snow profiles and compared reasonably well with FE calculations. We then implemented the method to refine the classical skier stability index. Using manually observed snow profiles, classified in different stability classes using stability tests, we obtained a satisfactory discrimination power. Lastly, the refined skier stability index was implemented into the 1-D snow cover model SNOWPACK and presented on two case studies. In the future, it will be interesting to implement the proposed method for describing skier-induced stress within a multi-layered snowpack into more complex models which take into account not only failure initiation but also crack propagation.

Gene prioritization and clustering by multi-view text mining

PubMed Central

2010-01-01

Background Text mining has become a useful tool for biologists trying to understand the genetics of diseases. In particular, it can help identify the most interesting candidate genes for a disease for further experimental analysis. Many text mining approaches have been introduced, but the effect of disease-gene identification varies in different text mining models. Thus, the idea of incorporating more text mining models may be beneficial to obtain more refined and accurate knowledge. However, how to effectively combine these models still remains a challenging question in machine learning. In particular, it is a non-trivial issue to guarantee that the integrated model performs better than the best individual model. Results We present a multi-view approach to retrieve biomedical knowledge using different controlled vocabularies. These controlled vocabularies are selected on the basis of nine well-known bio-ontologies and are applied to index the vast amounts of gene-based free-text information available in the MEDLINE repository. The text mining result specified by a vocabulary is considered as a view and the obtained multiple views are integrated by multi-source learning algorithms. We investigate the effect of integration in two fundamental computational disease gene identification tasks: gene prioritization and gene clustering. The performance of the proposed approach is systematically evaluated and compared on real benchmark data sets. In both tasks, the multi-view approach demonstrates significantly better performance than other comparing methods. Conclusions In practical research, the relevance of specific vocabulary pertaining to the task is usually unknown. In such case, multi-view text mining is a superior and promising strategy for text-based disease gene identification. PMID:20074336

Distributed Damage Estimation for Prognostics based on Structural Model Decomposition

NASA Technical Reports Server (NTRS)

Daigle, Matthew; Bregon, Anibal; Roychoudhury, Indranil

2011-01-01

Model-based prognostics approaches capture system knowledge in the form of physics-based models of components, and how they fail. These methods consist of a damage estimation phase, in which the health state of a component is estimated, and a prediction phase, in which the health state is projected forward in time to determine end of life. However, the damage estimation problem is often multi-dimensional and computationally intensive. We propose a model decomposition approach adapted from the diagnosis community, called possible conflicts, in order to both improve the computational efficiency of damage estimation, and formulate a damage estimation approach that is inherently distributed. Local state estimates are combined into a global state estimate from which prediction is performed. Using a centrifugal pump as a case study, we perform a number of simulation-based experiments to demonstrate the approach.

Detection and classification of interstitial lung diseases and emphysema using a joint morphological-fuzzy approach

NASA Astrophysics Data System (ADS)

Chang Chien, Kuang-Che; Fetita, Catalin; Brillet, Pierre-Yves; Prêteux, Françoise; Chang, Ruey-Feng

2009-02-01

Multi-detector computed tomography (MDCT) has high accuracy and specificity on volumetrically capturing serial images of the lung. It increases the capability of computerized classification for lung tissue in medical research. This paper proposes a three-dimensional (3D) automated approach based on mathematical morphology and fuzzy logic for quantifying and classifying interstitial lung diseases (ILDs) and emphysema. The proposed methodology is composed of several stages: (1) an image multi-resolution decomposition scheme based on a 3D morphological filter is used to detect and analyze the different density patterns of the lung texture. Then, (2) for each pattern in the multi-resolution decomposition, six features are computed, for which fuzzy membership functions define a probability of association with a pathology class. Finally, (3) for each pathology class, the probabilities are combined up according to the weight assigned to each membership function and two threshold values are used to decide the final class of the pattern. The proposed approach was tested on 10 MDCT cases and the classification accuracy was: emphysema: 95%, fibrosis/honeycombing: 84% and ground glass: 97%.

Closed-loop, pilot/vehicle analysis of the approach and landing task

NASA Technical Reports Server (NTRS)

Anderson, M. R.; Schmidt, D. K.

1986-01-01

In the case of approach and landing, it is universally accepted that the pilot uses more than one vehicle response, or output, to close his control loops. Therefore, to model this task, a multi-loop analysis technique is required. The analysis problem has been in obtaining reasonable analytic estimates of the describing functions representing the pilot's loop compensation. Once these pilot describing functions are obtained, appropriate performance and workload metrics must then be developed for the landing task. The optimal control approach provides a powerful technique for obtaining the necessary describing functions, once the appropriate task objective is defined in terms of a quadratic objective function. An approach is presented through the use of a simple, reasonable objective function and model-based metrics to evaluate loop performance and pilot workload. The results of an analysis of the LAHOS (Landing and Approach of Higher Order Systems) study performed by R.E. Smith is also presented.

Factors Influencing Teachers' Technology Self-Efficacy: A Case Study

ERIC Educational Resources Information Center

Farah, Amy Caroline

2012-01-01

Factors influencing teachers' levels of technology self-efficacy were examined through a qualitative multi-site, multi-subject case study research design. An initial survey was administered to all full-time, certified teachers at three school sites in order to gauge teachers' current level of technology self-efficacy. From that…

Co-Labeling for Multi-View Weakly Labeled Learning.

PubMed

Xu, Xinxing; Li, Wen; Xu, Dong; Tsang, Ivor W

2016-06-01

It is often expensive and time consuming to collect labeled training samples in many real-world applications. To reduce human effort on annotating training samples, many machine learning techniques (e.g., semi-supervised learning (SSL), multi-instance learning (MIL), etc.) have been studied to exploit weakly labeled training samples. Meanwhile, when the training data is represented with multiple types of features, many multi-view learning methods have shown that classifiers trained on different views can help each other to better utilize the unlabeled training samples for the SSL task. In this paper, we study a new learning problem called multi-view weakly labeled learning, in which we aim to develop a unified approach to learn robust classifiers by effectively utilizing different types of weakly labeled multi-view data from a broad range of tasks including SSL, MIL and relative outlier detection (ROD). We propose an effective approach called co-labeling to solve the multi-view weakly labeled learning problem. Specifically, we model the learning problem on each view as a weakly labeled learning problem, which aims to learn an optimal classifier from a set of pseudo-label vectors generated by using the classifiers trained from other views. Unlike traditional co-training approaches using a single pseudo-label vector for training each classifier, our co-labeling approach explores different strategies to utilize the predictions from different views, biases and iterations for generating the pseudo-label vectors, making our approach more robust for real-world applications. Moreover, to further improve the weakly labeled learning on each view, we also exploit the inherent group structure in the pseudo-label vectors generated from different strategies, which leads to a new multi-layer multiple kernel learning problem. Promising results for text-based image retrieval on the NUS-WIDE dataset as well as news classification and text categorization on several real-world multi-view datasets clearly demonstrate that our proposed co-labeling approach achieves state-of-the-art performance for various multi-view weakly labeled learning problems including multi-view SSL, multi-view MIL and multi-view ROD.

A General Formulation for Robust and Efficient Integration of Finite Differences and Phase Unwrapping on Sparse Multidimensional Domains

NASA Astrophysics Data System (ADS)

Costantini, Mario; Malvarosa, Fabio; Minati, Federico

2010-03-01

Phase unwrapping and integration of finite differences are key problems in several technical fields. In SAR interferometry and differential and persistent scatterers interferometry digital elevation models and displacement measurements can be obtained after unambiguously determining the phase values and reconstructing the mean velocities and elevations of the observed targets, which can be performed by integrating differential estimates of these quantities (finite differences between neighboring points).In this paper we propose a general formulation for robust and efficient integration of finite differences and phase unwrapping, which includes standard techniques methods as sub-cases. The proposed approach allows obtaining more reliable and accurate solutions by exploiting redundant differential estimates (not only between nearest neighboring points) and multi-dimensional information (e.g. multi-temporal, multi-frequency, multi-baseline observations), or external data (e.g. GPS measurements). The proposed approach requires the solution of linear or quadratic programming problems, for which computationally efficient algorithms exist.The validation tests obtained on real SAR data confirm the validity of the method, which was integrated in our production chain and successfully used also in massive productions.

A subjective framework for seat comfort based on a heuristic multi criteria decision making technique and anthropometry.

PubMed

Fazlollahtabar, Hamed

2010-12-01

Consumer expectations for automobile seat comfort continue to rise. With this said, it is evident that the current automobile seat comfort development process, which is only sporadically successful, needs to change. In this context, there has been growing recognition of the need for establishing theoretical and methodological automobile seat comfort. On the other hand, seat producer need to know the costumer's required comfort to produce based on their interests. The current research methodologies apply qualitative approaches due to anthropometric specifications. The most significant weakness of these approaches is the inexact extracted inferences. Despite the qualitative nature of the consumer's preferences there are some methods to transform the qualitative parameters into numerical value which could help seat producer to improve or enhance their products. Nonetheless this approach would help the automobile manufacturer to provide their seats from the best producer regarding to the consumers idea. In this paper, a heuristic multi criteria decision making technique is applied to make consumers preferences in the numeric value. This Technique is combination of Analytical Hierarchy Procedure (AHP), Entropy method, and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). A case study is conducted to illustrate the applicability and the effectiveness of the proposed heuristic approach. Copyright © 2010 Elsevier Ltd. All rights reserved.

Multi-step approach for comparing the local air pollution contributions of conventional and innovative MSW thermo-chemical treatments.

PubMed

Ragazzi, M; Rada, E C

2012-10-01

In the sector of municipal solid waste management the debate on the performances of conventional and novel thermo-chemical technologies is still relevant. When a plant must be constructed, decision makers often select a technology prior to analyzing the local environmental impact of the available options, as this type of study is generally developed when the design of the plant has been carried out. Additionally, in the literature there is a lack of comparative analyses of the contributions to local air pollution from different technologies. The present study offers a multi-step approach, based on pollutant emission factors and atmospheric dilution coefficients, for a local comparative analysis. With this approach it is possible to check if some assumptions related to the advantages of the novel thermochemical technologies, in terms of local direct impact on air quality, can be applied to municipal solid waste treatment. The selected processes concern combustion, gasification and pyrolysis, alone or in combination. The pollutants considered are both carcinogenic and non-carcinogenic. A case study is presented concerning the location of a plant in an alpine region and its contribution to the local air pollution. Results show that differences among technologies are less than expected. Performances of each technology are discussed in details. Copyright © 2012 Elsevier Ltd. All rights reserved.

Multi-site precipitation downscaling using a stochastic weather generator

NASA Astrophysics Data System (ADS)

Chen, Jie; Chen, Hua; Guo, Shenglian

2018-03-01

Statistical downscaling is an efficient way to solve the spatiotemporal mismatch between climate model outputs and the data requirements of hydrological models. However, the most commonly-used downscaling method only produces climate change scenarios for a specific site or watershed average, which is unable to drive distributed hydrological models to study the spatial variability of climate change impacts. By coupling a single-site downscaling method and a multi-site weather generator, this study proposes a multi-site downscaling approach for hydrological climate change impact studies. Multi-site downscaling is done in two stages. The first stage involves spatially downscaling climate model-simulated monthly precipitation from grid scale to a specific site using a quantile mapping method, and the second stage involves the temporal disaggregating of monthly precipitation to daily values by adjusting the parameters of a multi-site weather generator. The inter-station correlation is specifically considered using a distribution-free approach along with an iterative algorithm. The performance of the downscaling approach is illustrated using a 10-station watershed as an example. The precipitation time series derived from the National Centers for Environment Prediction (NCEP) reanalysis dataset is used as the climate model simulation. The precipitation time series of each station is divided into 30 odd years for calibration and 29 even years for validation. Several metrics, including the frequencies of wet and dry spells and statistics of the daily, monthly and annual precipitation are used as criteria to evaluate the multi-site downscaling approach. The results show that the frequencies of wet and dry spells are well reproduced for all stations. In addition, the multi-site downscaling approach performs well with respect to reproducing precipitation statistics, especially at monthly and annual timescales. The remaining biases mainly result from the non-stationarity of NCEP precipitation. Overall, the proposed approach is efficient for generating multi-site climate change scenarios that can be used to investigate the spatial variability of climate change impacts on hydrology.

Landfill Site Selection by AHP Based Multi-criteria Decision Making Tool: A Case Study in Kolkata, India

NASA Astrophysics Data System (ADS)

Majumdar, Ankush; Hazra, Tumpa; Dutta, Amit

2017-09-01

This work presents a Multi-criteria Decision Making (MCDM) tool to select a landfill site from three candidate sites proposed for Kolkata Municipal Corporation (KMC) area that complies with accessibility, receptor, environment, public acceptability, geological and economic criteria. Analytical Hierarchy Process has been used to solve the MCDM problem. Suitability of the three sites (viz. Natagachi, Gangajoara and Kharamba) as landfills as proposed by KMC has been checked by Landfill Site Sensitivity Index (LSSI) as well as Economic Viability Index (EVI). Land area availability for disposing huge quantity of Municipal Solid Waste for the design period has been checked. Analysis of the studied sites show that they are moderately suitable for landfill facility construction as both LSSI and EVI scores lay between 300 and 750. The proposed approach represents an effective MCDM tool for siting sanitary landfill in growing metropolitan cities of developing countries like India.

How to use multi-criteria decision analysis methods for reimbursement decision-making in healthcare: a step-by-step guide.

PubMed

Diaby, Vakaramoko; Goeree, Ron

2014-02-01

In recent years, the quest for more comprehensiveness, structure and transparency in reimbursement decision-making in healthcare has prompted the research into alternative decision-making frameworks. In this environment, multi-criteria decision analysis (MCDA) is arising as a valuable tool to support healthcare decision-making. In this paper, we present the main MCDA decision support methods (elementary methods, value-based measurement models, goal programming models and outranking models) using a case study approach. For each family of methods, an example of how an MCDA model would operate in a real decision-making context is presented from a critical perspective, highlighting the parameters setting, the selection of the appropriate evaluation model as well as the role of sensitivity and robustness analyses. This study aims to provide a step-by-step guide on how to use MCDA methods for reimbursement decision-making in healthcare.

Advances in multi-scale modeling of solidification and casting processes

NASA Astrophysics Data System (ADS)

Liu, Baicheng; Xu, Qingyan; Jing, Tao; Shen, Houfa; Han, Zhiqiang

2011-04-01

The development of the aviation, energy and automobile industries requires an advanced integrated product/process R&D systems which could optimize the product and the process design as well. Integrated computational materials engineering (ICME) is a promising approach to fulfill this requirement and make the product and process development efficient, economic, and environmentally friendly. Advances in multi-scale modeling of solidification and casting processes, including mathematical models as well as engineering applications are presented in the paper. Dendrite morphology of magnesium and aluminum alloy of solidification process by using phase field and cellular automaton methods, mathematical models of segregation of large steel ingot, and microstructure models of unidirectionally solidified turbine blade casting are studied and discussed. In addition, some engineering case studies, including microstructure simulation of aluminum casting for automobile industry, segregation of large steel ingot for energy industry, and microstructure simulation of unidirectionally solidified turbine blade castings for aviation industry are discussed.

Variable structure control of spacecraft reorientation maneuvers

NASA Technical Reports Server (NTRS)

Sira-Ramirez, H.; Dwyer, T. A. W., III

1986-01-01

A Variable Structure Control (VSC) approach is presented for multi-axial spacecraft reorientation maneuvers. A nonlinear sliding surface is proposed which results in an asymptotically stable, ideal linear sliding motion of Cayley-Rodriques attitude parameters. By imposing a desired equivalent dynamics on the attitude parameters, the approach is devoid of optimal control considerations. The single axis case provides a design scheme for the multiple axes design problem. Illustrative examples are presented.

Dynamic Appliances Scheduling in Collaborative MicroGrids System

PubMed Central

Bilil, Hasnae; Aniba, Ghassane; Gharavi, Hamid

2017-01-01

In this paper a new approach which is based on a collaborative system of MicroGrids (MG’s), is proposed to enable household appliance scheduling. To achieve this, appliances are categorized into flexible and non-flexible Deferrable Loads (DL’s), according to their electrical components. We propose a dynamic scheduling algorithm where users can systematically manage the operation of their electric appliances. The main challenge is to develop a flattening function calculus (reshaping) for both flexible and non-flexible DL’s. In addition, implementation of the proposed algorithm would require dynamically analyzing two successive multi-objective optimization (MOO) problems. The first targets the activation schedule of non-flexible DL’s and the second deals with the power profiles of flexible DL’s. The MOO problems are resolved by using a fast and elitist multi-objective genetic algorithm (NSGA-II). Finally, in order to show the efficiency of the proposed approach, a case study of a collaborative system that consists of 40 MG’s registered in the load curve for the flattening program has been developed. The results verify that the load curve can indeed become very flat by applying the proposed scheduling approach. PMID:28824226

Barrett's Esophagus Methylation Profiles — EDRN Public Portal

Cancer.gov

We propose a nested case-control study of biomarkers in the setting of BE. By bringing together research institutions with large populations of patients with BE, we will perform a multi-center study of FISH and hypermethylation markers as possible prognostic factors in BE. The centers will select from their cohorts who have progressed to HGD or to adenocarcinoma of the esophagus ("progressors"), and who also donated samples prior to the development of cancer, when their histology was felt to be benign. These subjects will be compared to individuals who have been under endoscopic surveillance, but who have not progressed to HGD or EAC ("non-progressors"). Using this approach, we hope to identify promising markers for risk stratification in BE. We expect to be able to make successful application for a prospective study of markers identified in this case-control study.

A hybrid formulation for the numerical simulation of condensed phase explosives

NASA Astrophysics Data System (ADS)

Michael, L.; Nikiforakis, N.

2016-07-01

In this article we present a new formulation and an associated numerical algorithm, for the simulation of combustion and transition to detonation of condensed-phase commercial- and military-grade explosives, which are confined by (or in general interacting with one or more) compliant inert materials. Examples include confined rate-stick problems and interaction of shock waves with gas cavities or solid particles in explosives. This formulation is based on an augmented Euler approach to account for the mixture of the explosive and its products, and a multi-phase diffuse interface approach to solve for the immiscible interaction between the mixture and the inert materials, so it is in essence a hybrid (augmented Euler and multi-phase) model. As such, it has many of the desirable features of the two approaches and, critically for our applications of interest, it provides the accurate recovery of temperature fields across all components. Moreover, it conveys a lot more physical information than augmented Euler, without the complexity of full multi-phase Baer-Nunziato-type models or the lack of robustness of augmented Euler models in the presence of more than two components. The model can sustain large density differences across material interfaces without the presence of spurious oscillations in velocity and pressure, and it can accommodate realistic equations of state and arbitrary (pressure- or temperature-based) reaction-rate laws. Under certain conditions, we show that the formulation reduces to well-known augmented Euler or multi-phase models, which have been extensively validated and used in practice. The full hybrid model and its reduced forms are validated against problems with exact (or independently-verified numerical) solutions and evaluated for robustness for rate-stick and shock-induced cavity collapse case-studies.

Principal Sensemaking of Inclusion: A Multi-Case Study of Five Urban School Principals

ERIC Educational Resources Information Center

DeMatthews, David Edward

2012-01-01

This study examined how five principals working in one urban school district made sense of inclusion. I employed a multi-case study guided by the theoretical framework of sensemaking. Weick's sensemaking theory was useful in examining the way principals made sense of inclusion. Each of the seven characteristics of Weick's sensemaking…

A Multi-Parameter Approach for Calculating Crack Instability

NASA Technical Reports Server (NTRS)

Zanganeh, M.; Forman, R. G.

2014-01-01

An accurate fracture control analysis of spacecraft pressure systems, boosters, rocket hardware and other critical low-cycle fatigue cases where the fracture toughness highly impacts cycles to failure requires accurate knowledge of the material fracture toughness. However, applicability of the measured fracture toughness values using standard specimens and transferability of the values to crack instability analysis of the realistically complex structures is refutable. The commonly used single parameter Linear Elastic Fracture Mechanics (LEFM) approach which relies on the key assumption that the fracture toughness is a material property would result in inaccurate crack instability predictions. In the past years extensive studies have been conducted to improve the single parameter (K-controlled) LEFM by introducing parameters accounting for the geometry or in-plane constraint effects]. Despite the importance of the thickness (out-of-plane constraint) effects in fracture control problems, the literature is mainly limited to some empirical equations for scaling the fracture toughness data] and only few theoretically based developments can be found. In aerospace hardware where the structure might have only one life cycle and weight reduction is crucial, reducing the design margin of safety by decreasing the uncertainty involved in fracture toughness evaluations would result in lighter hardware. In such conditions LEFM would not suffice and an elastic-plastic analysis would be vital. Multi-parameter elastic plastic crack tip field quantifying developments combined with statistical methods] have been shown to have the potential to be used as a powerful tool for tackling such problems. However, these approaches have not been comprehensively scrutinized using experimental tests. Therefore, in this paper a multi-parameter elastic-plastic approach has been used to study the crack instability problem and the transferability issue by considering the effects of geometrical constraints as well as the thickness. The feasibility of the approach has been examined using a wide range of specimen geometries and thicknesses manufactured from 7075-T7351 aluminum alloy.

A multi-disciplinary approach to study coastal complex landslides: the case of Torino di Sangro (Central Italy)

NASA Astrophysics Data System (ADS)

Sciarra, Marco; Carabba, Luigi; Urbano, Tullio; Calista, Monia

2016-04-01

This work illustrates the studies carried out on a complex landslide phenomenon between the Sangro and Osento River's mouths, near Torino di Sangro village in Southern Abruzzo Region (Italy). Historical activity of this landslide is well-documented since 1916; the activation/reactivation of the movements caused several interruptions of a national railway and the damage of few houses. The Torino di Sangro case study can be regarded as representative of many large landslides distributed along the central Adriatic coast (e.g., Ancona, Ortona, Vasto and Petacciato Landslides) that affect densely populated urban areas with a large amount of man-made infrastructure. The main controlling factors of these large and deep-seated landslides are still debated. From the geological and geomorphological viewpoint, the central Adriatic coast is characterized by a low-relief landscape (mesa) carved on clay-sandstone-conglomerate bedrock belonging to the Upper Pliocene - Lower Pleistocene marine deposits and locally to the Middle Pleistocene marine to continental transitional deposits. This high coast is widely affected by slope instability (rock falls, rotational, complex and shallow landslides) on both active and inactive sea cliffs, the first being mainly affected by wave-cut erosion and the latter influenced by heavy rainfall and changes of pore pressure. The main landslide has the typical characteristics of a deep-seated gravitation deformation. The landslide study was based on a multidisciplinary approach including: 1) definition and GIS mapping of geology and geomorphology factors (slope, aspect, topographic curvature, bedrock lithology, near-surface deposits, deposit thickness and land use), by means of DTM processing, multi-temporal analysis, and large-scale geomorphological field survey; 2) monitoring system in the landslide; 3) application of empiric models for the analysis of unstable sandstone-conglomerate escarpments; 4) slope stability analysis performed using a stress-strain numerical modeling solved by a Finite Difference Method (FLAC 2D). This study suggests that rock falls and shallow landslide are hazardous phenomenal that involve the near-surface cover of a bigger and more complex landslide. The distinction between secondary processes, which appear to be the most hazardous in the short-term, and deep-seated one, demonstrated that accurate multi-approach analysis provide important information that can be supportive for local administration and decision makers, and for the comprehension of the factors controlling large and deep-seated landslide affecting the Adriatic coastal slopes.

Fusion of multi-source remote sensing data for agriculture monitoring tasks

NASA Astrophysics Data System (ADS)

Skakun, S.; Franch, B.; Vermote, E.; Roger, J. C.; Becker Reshef, I.; Justice, C. O.; Masek, J. G.; Murphy, E.

2016-12-01

Remote sensing data is essential source of information for enabling monitoring and quantification of crop state at global and regional scales. Crop mapping, state assessment, area estimation and yield forecasting are the main tasks that are being addressed within GEO-GLAM. Efficiency of agriculture monitoring can be improved when heterogeneous multi-source remote sensing datasets are integrated. Here, we present several case studies of utilizing MODIS, Landsat-8 and Sentinel-2 data along with meteorological data (growing degree days - GDD) for winter wheat yield forecasting, mapping and area estimation. Archived coarse spatial resolution data, such as MODIS, VIIRS and AVHRR, can provide daily global observations that coupled with statistical data on crop yield can enable the development of empirical models for timely yield forecasting at national level. With the availability of high-temporal and high spatial resolution Landsat-8 and Sentinel-2A imagery, course resolution empirical yield models can be downscaled to provide yield estimates at regional and field scale. In particular, we present the case study of downscaling the MODIS CMG based generalized winter wheat yield forecasting model to high spatial resolution data sets, namely harmonized Landsat-8 - Sentinel-2A surface reflectance product (HLS). Since the yield model requires corresponding in season crop masks, we propose an automatic approach to extract winter crop maps from MODIS NDVI and MERRA2 derived GDD using Gaussian mixture model (GMM). Validation for the state of Kansas (US) and Ukraine showed that the approach can yield accuracies > 90% without using reference (ground truth) data sets. Another application of yearly derived winter crop maps is their use for stratification purposes within area frame sampling for crop area estimation. In particular, one can simulate the dependence of error (coefficient of variation) on the number of samples and strata size. This approach was used for estimating the area of winter crops in Ukraine for 2013-2016. The GMM-GDD approach is further extended for HLS data to provide automatic winter crop mapping at 30 m resolution for crop yield model and area estimation. In case of persistent cloudiness, addition of Sentinel-1A synthetic aperture radar (SAR) images is explored for automatic winter crop mapping.

On a Thermodynamic Approach to Material Selection for Service in Aggressive Multi-Component Gaseous and/or Vapor Environments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Glazoff, Michael Vasily; Marschman, Steven Craig; Soelberg, Nicholas Ray

This report fulfills the M4 milestone, M4FT-15IN08020110 UNF Analysis Support, under Work Package Number FT-15IN080201. The issue of materials selection for many engineering applications represents an important problem, particularly in cases where material failure is possible as a result of corrosive environments. For example, 304 dual purpose or 316 stainless steel is used in the construction of many used nuclear fuel storage canisters. Deployed all over the world, these canisters are housed inside shielded enclosures and cooled passively by convective airflow. When located along seaboards or particular industrial areas, salt, other corrosive chemicals, and moisture can become entrained in themore » air that cools the canisters. It is important to develop an understanding of what impact, if any, that chemical environment will have on those canisters. In many cases of corrosion in aggressive gaseous environments, the material selection process is based on some general recommendations, anecdotal evidence, and/or the past experience of that particular project’s participants. For gaseous mixtures, the theoretical basis is practically limited to the construction of the so-called “Ellingham diagrams” for pure metals. These plots predict the equilibrium temperature between different individual metals, their respective oxides, and oxygen gas. Similar diagrams can be constructed for the reactions with sulfur, nitrogen, carbon, etc. In the generalization of this approach by Richardson and Jeffes, additional scales can be superimposed upon an Ellingham diagram that would correspond to different gaseous mixtures, e.g. CO/CO 2, or H 2/H 2O. However, while the general approach to predicting the stability of a multi-component heterogeneous alloy (e.g., steel or a superalloy) in a multi-component aggressive gaseous environment was developed in very general form, actual examples of its applications to concrete real-life problems are practically absent. This is related to alloy design, corrosion protection, and material selection for different applications. In this work, an effort was made to advance in that direction using modern computational thermodynamics methodology, software, and databases by Thermo-Calc Inc. The developed methodology is illustrated by the case study – a process of nuclear waste immobilization using a chemical engineering approach described below. The developed methodology can be considered a practical illustration of the Ellingham approach generalization and could be used for obtaining thermodynamic guidance on a given process’ feasibility using equipment/sensors made of a particular multicomponent heterogeneous metallic alloy.« less

A comparative study of linear and nonlinear MIMO feedback configurations

NASA Technical Reports Server (NTRS)

Desoer, C. A.; Lin, C. A.

1984-01-01

In this paper, a comparison is conducted of several feedback configurations which have appeared in the literature (e.g. unity-feedback, model-reference, etc.). The linear time-invariant multi-input multi-output case is considered. For each configuration, the stability conditions are specified, the relation between achievable I/O maps and the achievable disturbance-to-output maps is examined, and the effect of various subsystem perturbations on the system performance is studied. In terms of these considerations, it is demonstrated that one of the configurations considered is better than all the others. The results are then extended to the nonlinear multi-input multi-output case.

Limitations Of The Current State Space Modelling Approach In Multistage Machining Processes Due To Operation Variations

NASA Astrophysics Data System (ADS)

Abellán-Nebot, J. V.; Liu, J.; Romero, F.

2009-11-01

The State Space modelling approach has been recently proposed as an engineering-driven technique for part quality prediction in Multistage Machining Processes (MMP). Current State Space models incorporate fixture and datum variations in the multi-stage variation propagation, without explicitly considering common operation variations such as machine-tool thermal distortions, cutting-tool wear, cutting-tool deflections, etc. This paper shows the limitations of the current State Space model through an experimental case study where the effect of the spindle thermal expansion, cutting-tool flank wear and locator errors are introduced. The paper also discusses the extension of the current State Space model to include operation variations and its potential benefits.

Estimating hydraulic parameters of a heterogeneous aquitard using long-term multi-extensometer and groundwater level data

NASA Astrophysics Data System (ADS)

Zhuang, Chao; Zhou, Zhifang; Illman, Walter A.; Guo, Qiaona; Wang, Jinguo

2017-09-01

The classical aquitard-drainage model COMPAC has been modified to simulate the compaction process of a heterogeneous aquitard consisting of multiple sub-units (Multi-COMPAC). By coupling Multi-COMPAC with the parameter estimation code PEST++, the vertical hydraulic conductivity ( K v) and elastic ( S ske) and inelastic ( S skp) skeletal specific-storage values of each sub-unit can be estimated using observed long-term multi-extensometer and groundwater level data. The approach was first tested through a synthetic case with known parameters. Results of the synthetic case revealed that it was possible to accurately estimate the three parameters for each sub-unit. Next, the methodology was applied to a field site located in Changzhou city, China. Based on the detailed stratigraphic information and extensometer data, the aquitard of interest was subdivided into three sub-units. Parameters K v, S ske and S skp of each sub-unit were estimated simultaneously and then were compared with laboratory results and with bulk values and geologic data from previous studies, demonstrating the reliability of parameter estimates. Estimated S skp values ranged within the magnitude of 10-4 m-1, while K v ranged over 10-10-10-8 m/s, suggesting moderately high heterogeneity of the aquitard. However, the elastic deformation of the third sub-unit, consisting of soft plastic silty clay, is masked by delayed drainage, and the inverse procedure leads to large uncertainty in the S ske estimate for this sub-unit.

Mentorship in Practice: A Multi-Method Approach.

ERIC Educational Resources Information Center

Schreck, Timothy J.; And Others

This study was conducted to evaluate a field-based mentorship program using a multi-method approach. It explored the use of mentorship as practiced in the Florida Compact, a business education partnership established in Florida in 1987. The study was designed to identify differences between mentors and mentorees, as well as differences within…

Evolving Relationship Structures in Multi-sourcing Arrangements: The Case of Mission Critical Outsourcing

NASA Astrophysics Data System (ADS)

Heitlager, Ilja; Helms, Remko; Brinkkemper, Sjaak

Information Technology Outsourcing practice and research mainly considers the outsourcing phenomenon as a generic fulfilment of the IT function by external parties. Inspired by the logic of commodity, core competencies and economies of scale; assets, existing departments and IT functions are transferred to external parties. Although the generic approach might work for desktop outsourcing, where standardisation is the dominant factor, it does not work for the management of mission critical applications. Managing mission critical applications requires a different approach where building relationships is critical. The relationships involve inter and intra organisational parties in a multi-sourcing arrangement, called an IT service chain, consisting of multiple (specialist) parties that have to collaborate closely to deliver high quality services.

Designing multi-reservoir system designs via efficient water-energy-food nexus trade-offs - Selecting new hydropower dams for the Blue Nile and Nepal's Koshi Basin

NASA Astrophysics Data System (ADS)

Harou, J. J.; Hurford, A.; Geressu, R. T.

2015-12-01

Many of the world's multi-reservoir water resource systems are being considered for further development of hydropower and irrigation aiming to meet economic, political and ecological goals. Complex river basins serve many needs so how should the different proposed groupings of reservoirs and their operations be evaluated? How should uncertainty about future supply and demand conditions be factored in? What reservoir designs can meet multiple goals and perform robustly in a context of global change? We propose an optimized multi-criteria screening approach to identify best performing designs, i.e., the selection, size and operating rules of new reservoirs within multi-reservoir systems in a context of deeply uncertain change. Reservoir release operating rules and storage sizes are optimized concurrently for each separate infrastructure design under consideration across many scenarios representing plausible future conditions. Outputs reveal system trade-offs using multi-dimensional scatter plots where each point represents an approximately Pareto-optimal design. The method is applied to proposed Blue Nile River reservoirs in Ethiopia, where trade-offs between capital costs, total and firm energy output, aggregate storage and downstream irrigation and energy provision for the best performing designs are evaluated. The impact of filling period for large reservoirs is considered in a context of hydrological uncertainty. The approach is also applied to the Koshi basin in Nepal where combinations of hydropower storage and run-of-river dams are being considered for investment. We show searching for investment portfolios that meet multiple objectives provides stakeholders with a rich view on the trade-offs inherent in the nexus and how different investment bundles perform differently under plausible futures. Both case-studies show how the proposed approach helps explore and understand the implications of investing in new dams in a global change context.

Inexact fuzzy-stochastic mixed-integer programming approach for long-term planning of waste management--Part A: methodology.

PubMed

Guo, P; Huang, G H

2009-01-01

In this study, an inexact fuzzy chance-constrained two-stage mixed-integer linear programming (IFCTIP) approach is proposed for supporting long-term planning of waste-management systems under multiple uncertainties in the City of Regina, Canada. The method improves upon the existing inexact two-stage programming and mixed-integer linear programming techniques by incorporating uncertainties expressed as multiple uncertainties of intervals and dual probability distributions within a general optimization framework. The developed method can provide an effective linkage between the predefined environmental policies and the associated economic implications. Four special characteristics of the proposed method make it unique compared with other optimization techniques that deal with uncertainties. Firstly, it provides a linkage to predefined policies that have to be respected when a modeling effort is undertaken; secondly, it is useful for tackling uncertainties presented as intervals, probabilities, fuzzy sets and their incorporation; thirdly, it facilitates dynamic analysis for decisions of facility-expansion planning and waste-flow allocation within a multi-facility, multi-period, multi-level, and multi-option context; fourthly, the penalties are exercised with recourse against any infeasibility, which permits in-depth analyses of various policy scenarios that are associated with different levels of economic consequences when the promised solid waste-generation rates are violated. In a companion paper, the developed method is applied to a real case for the long-term planning of waste management in the City of Regina, Canada.

Snow instability evaluation: calculating the skier-induced stress in a multi-layered snowpack

NASA Astrophysics Data System (ADS)

Monti, Fabiano; Gaume, Johan; van Herwijnen, Alec; Schweizer, Jürg

2016-03-01

The process of dry-snow slab avalanche formation can be divided into two phases: failure initiation and crack propagation. Several approaches tried to quantify slab avalanche release probability in terms of failure initiation based on shear stress and strength. Though it is known that both the properties of the weak layer and the slab play a major role in avalanche release, most previous approaches only considered slab properties in terms of slab depth, average density and skier penetration. For example, for the skier stability index, the additional stress (e.g. due to a skier) at the depth of the weak layer is calculated by assuming that the snow cover can be considered a semi-infinite, elastic, half-space. We suggest a new approach based on a simplification of the multi-layered elasticity theory in order to easily compute the additional stress due to a skier at the depth of the weak layer, taking into account the layering of the snow slab and the substratum. We first tested the proposed approach on simplified snow profiles, then on manually observed snow profiles including a stability test and, finally, on simulated snow profiles. Our simple approach reproduced the additional stress obtained by finite element simulations for the simplified profiles well - except that the sequence of layering in the slab cannot be replicated. Once implemented into the classical skier stability index and applied to manually observed snow profiles classified into different stability classes, the classification accuracy improved with the new approach. Finally, we implemented the refined skier stability index into the 1-D snow cover model SNOWPACK. The two study cases presented in this paper showed promising results even though further verification is still needed. In the future, we intend to implement the proposed approach for describing skier-induced stress within a multi-layered snowpack into more complex models which take into account not only failure initiation but also crack propagation.

Mr-Moose: An advanced SED-fitting tool for heterogeneous multi-wavelength datasets

NASA Astrophysics Data System (ADS)

Drouart, G.; Falkendal, T.

2018-04-01

We present the public release of Mr-Moose, a fitting procedure that is able to perform multi-wavelength and multi-object spectral energy distribution (SED) fitting in a Bayesian framework. This procedure is able to handle a large variety of cases, from an isolated source to blended multi-component sources from an heterogeneous dataset (i.e. a range of observation sensitivities and spectral/spatial resolutions). Furthermore, Mr-Moose handles upper-limits during the fitting process in a continuous way allowing models to be gradually less probable as upper limits are approached. The aim is to propose a simple-to-use, yet highly-versatile fitting tool fro handling increasing source complexity when combining multi-wavelength datasets with fully customisable filter/model databases. The complete control of the user is one advantage, which avoids the traditional problems related to the "black box" effect, where parameter or model tunings are impossible and can lead to overfitting and/or over-interpretation of the results. Also, while a basic knowledge of Python and statistics is required, the code aims to be sufficiently user-friendly for non-experts. We demonstrate the procedure on three cases: two artificially-generated datasets and a previous result from the literature. In particular, the most complex case (inspired by a real source, combining Herschel, ALMA and VLA data) in the context of extragalactic SED fitting, makes Mr-Moose a particularly-attractive SED fitting tool when dealing with partially blended sources, without the need for data deconvolution.

MR-MOOSE: an advanced SED-fitting tool for heterogeneous multi-wavelength data sets

NASA Astrophysics Data System (ADS)

Drouart, G.; Falkendal, T.

2018-07-01

We present the public release of MR-MOOSE, a fitting procedure that is able to perform multi-wavelength and multi-object spectral energy distribution (SED) fitting in a Bayesian framework. This procedure is able to handle a large variety of cases, from an isolated source to blended multi-component sources from a heterogeneous data set (i.e. a range of observation sensitivities and spectral/spatial resolutions). Furthermore, MR-MOOSE handles upper limits during the fitting process in a continuous way allowing models to be gradually less probable as upper limits are approached. The aim is to propose a simple-to-use, yet highly versatile fitting tool for handling increasing source complexity when combining multi-wavelength data sets with fully customisable filter/model data bases. The complete control of the user is one advantage, which avoids the traditional problems related to the `black box' effect, where parameter or model tunings are impossible and can lead to overfitting and/or over-interpretation of the results. Also, while a basic knowledge of PYTHON and statistics is required, the code aims to be sufficiently user-friendly for non-experts. We demonstrate the procedure on three cases: two artificially generated data sets and a previous result from the literature. In particular, the most complex case (inspired by a real source, combining Herschel, ALMA, and VLA data) in the context of extragalactic SED fitting makes MR-MOOSE a particularly attractive SED fitting tool when dealing with partially blended sources, without the need for data deconvolution.

On the estimation of the worst-case implant-induced RF-heating in multi-channel MRI.

PubMed

Córcoles, Juan; Zastrow, Earl; Kuster, Niels

2017-06-21

The increasing use of multiple radiofrequency (RF) transmit channels in magnetic resonance imaging (MRI) systems makes it necessary to rigorously assess the risk of RF-induced heating. This risk is especially aggravated with inclusions of medical implants within the body. The worst-case RF-heating scenario is achieved when the local tissue deposition in the at-risk region (generally in the vicinity of the implant electrodes) reaches its maximum value while MRI exposure is compliant with predefined general specific absorption rate (SAR) limits or power requirements. This work first reviews the common approach to estimate the worst-case RF-induced heating in multi-channel MRI environment, based on the maximization of the ratio of two Hermitian forms by solving a generalized eigenvalue problem. It is then shown that the common approach is not rigorous and may lead to an underestimation of the worst-case RF-heating scenario when there is a large number of RF transmit channels and there exist multiple SAR or power constraints to be satisfied. Finally, this work derives a rigorous SAR-based formulation to estimate a preferable worst-case scenario, which is solved by casting a semidefinite programming relaxation of this original non-convex problem, whose solution closely approximates the true worst-case including all SAR constraints. Numerical results for 2, 4, 8, 16, and 32 RF channels in a 3T-MRI volume coil for a patient with a deep-brain stimulator under a head imaging exposure are provided as illustrative examples.

On the estimation of the worst-case implant-induced RF-heating in multi-channel MRI

NASA Astrophysics Data System (ADS)

Córcoles, Juan; Zastrow, Earl; Kuster, Niels

2017-06-01

The increasing use of multiple radiofrequency (RF) transmit channels in magnetic resonance imaging (MRI) systems makes it necessary to rigorously assess the risk of RF-induced heating. This risk is especially aggravated with inclusions of medical implants within the body. The worst-case RF-heating scenario is achieved when the local tissue deposition in the at-risk region (generally in the vicinity of the implant electrodes) reaches its maximum value while MRI exposure is compliant with predefined general specific absorption rate (SAR) limits or power requirements. This work first reviews the common approach to estimate the worst-case RF-induced heating in multi-channel MRI environment, based on the maximization of the ratio of two Hermitian forms by solving a generalized eigenvalue problem. It is then shown that the common approach is not rigorous and may lead to an underestimation of the worst-case RF-heating scenario when there is a large number of RF transmit channels and there exist multiple SAR or power constraints to be satisfied. Finally, this work derives a rigorous SAR-based formulation to estimate a preferable worst-case scenario, which is solved by casting a semidefinite programming relaxation of this original non-convex problem, whose solution closely approximates the true worst-case including all SAR constraints. Numerical results for 2, 4, 8, 16, and 32 RF channels in a 3T-MRI volume coil for a patient with a deep-brain stimulator under a head imaging exposure are provided as illustrative examples.

Simulating Carbon cycle and phenology in complex forests using a multi-layer process based ecosystem model; evaluation and use of 3D-CMCC-Forest Ecosystem Model in a deciduous and an evergreen neighboring forests, within the area of Brasschaat (Be)

NASA Astrophysics Data System (ADS)

Marconi, S.; Collalti, A.; Santini, M.; Valentini, R.

2013-12-01

3D-CMCC-Forest Ecosystem Model is a process based model formerly developed for complex forest ecosystems to estimate growth, water and carbon cycles, phenology and competition processes on a daily/monthly time scale. The Model integrates some characteristics of the functional-structural tree models with the robustness of the light use efficiency approach. It treats different heights, ages and species as discrete classes, in competition for light (vertical structure) and space (horizontal structure). The present work evaluates the results of the recently developed daily version of 3D-CMCC-FEM for two neighboring different even aged and mono specific study cases. The former is a heterogeneous Pedunculate oak forest (Quercus robur L. ), the latter a more homogeneous Scot pine forest (Pinus sylvestris L.). The multi-layer approach has been evaluated against a series of simplified versions to determine whether the improved model complexity in canopy structure definition increases its predictive ability. Results show that a more complex structure (three height layers) should be preferable to simulate heterogeneous scenarios (Pedunculate oak stand), where heights distribution within the canopy justify the distinction in dominant, dominated and sub-dominated layers. On the contrary, it seems that using a multi-layer approach for more homogeneous stands (Scot pine stand) may be disadvantageous. Forcing the structure of an homogeneous stand to a multi-layer approach may in fact increase sources of uncertainty. On the other hand forcing complex forests to a mono layer simplified model, may cause an increase in mortality and a reduction in average DBH and Height. Compared with measured CO2 flux data, model results show good ability in estimating carbon sequestration trends, on both a monthly/seasonal and daily time scales. Moreover the model simulates quite well leaf phenology and the combined effects of the two different forest stands on CO2 fluxes.

A comparative study of machine learning models for ethnicity classification

NASA Astrophysics Data System (ADS)

Trivedi, Advait; Bessie Amali, D. Geraldine

2017-11-01

This paper endeavours to adopt a machine learning approach to solve the problem of ethnicity recognition. Ethnicity identification is an important vision problem with its use cases being extended to various domains. Despite the multitude of complexity involved, ethnicity identification comes naturally to humans. This meta information can be leveraged to make several decisions, be it in target marketing or security. With the recent development of intelligent systems a sub module to efficiently capture ethnicity would be useful in several use cases. Several attempts to identify an ideal learning model to represent a multi-ethnic dataset have been recorded. A comparative study of classifiers such as support vector machines, logistic regression has been documented. Experimental results indicate that the logical classifier provides a much accurate classification than the support vector machine.

A Multi-Faceted Formative Assessment Approach: Better Recognising the Learning Needs of Students

ERIC Educational Resources Information Center

Jenkins, James O.

2010-01-01

Students are increasingly subject to a series of learning pressures that prevent effective engagement in assessment. Thus, the aim of this study was to create a multi-faceted formative assessment approach that better enabled students to engage in the assessment process. A formative assessment approach, consisting of six key initiatives, is…

Machine learning action parameters in lattice quantum chromodynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shanahan, Phiala; Trewartha, Daneil; Detmold, William

Numerical lattice quantum chromodynamics studies of the strong interaction underpin theoretical understanding of many aspects of particle and nuclear physics. Such studies require significant computing resources to undertake. A number of proposed methods promise improved efficiency of lattice calculations, and access to regions of parameter space that are currently computationally intractable, via multi-scale action-matching approaches that necessitate parametric regression of generated lattice datasets. The applicability of machine learning to this regression task is investigated, with deep neural networks found to provide an efficient solution even in cases where approaches such as principal component analysis fail. Finally, the high information contentmore » and complex symmetries inherent in lattice QCD datasets require custom neural network layers to be introduced and present opportunities for further development.« less

The Role of Science in Advising the Decision Making Process: A Pathway for Building Effective Climate Change Mitigation Policies in Mexico at the Local Level.

PubMed

Barraza, Roberto; Velazquez-Angulo, Gilberto; Flores-Tavizón, Edith; Romero-González, Jaime; Huertas-Cardozo, José Ignacio

2016-04-27

This study examines a pathway for building urban climate change mitigation policies by presenting a multi-dimensional and transdisciplinary approach in which technical, economic, environmental, social, and political dimensions interact. Now, more than ever, the gap between science and policymaking needs to be bridged; this will enable judicious choices to be made in regarding energy and climate change mitigation strategies, leading to positive social impacts, in particular for the populations at-risk at the local level. Through a case study in Juarez, Chihuahua, Mexico, we propose a multidimensional and transdisciplinary approach with the role of scientist as policy advisers to improve the role of science in decision-making on mitigation policies at the local level in Mexico.

Machine learning action parameters in lattice quantum chromodynamics

DOE PAGES

Shanahan, Phiala; Trewartha, Daneil; Detmold, William

2018-05-16

Numerical lattice quantum chromodynamics studies of the strong interaction underpin theoretical understanding of many aspects of particle and nuclear physics. Such studies require significant computing resources to undertake. A number of proposed methods promise improved efficiency of lattice calculations, and access to regions of parameter space that are currently computationally intractable, via multi-scale action-matching approaches that necessitate parametric regression of generated lattice datasets. The applicability of machine learning to this regression task is investigated, with deep neural networks found to provide an efficient solution even in cases where approaches such as principal component analysis fail. Finally, the high information contentmore » and complex symmetries inherent in lattice QCD datasets require custom neural network layers to be introduced and present opportunities for further development.« less

A custom correlation coefficient (CCC) approach for fast identification of multi-SNP association patterns in genome-wide SNPs data.

PubMed

Climer, Sharlee; Yang, Wei; de las Fuentes, Lisa; Dávila-Román, Victor G; Gu, C Charles

2014-11-01

Complex diseases are often associated with sets of multiple interacting genetic factors and possibly with unique sets of the genetic factors in different groups of individuals (genetic heterogeneity). We introduce a novel concept of custom correlation coefficient (CCC) between single nucleotide polymorphisms (SNPs) that address genetic heterogeneity by measuring subset correlations autonomously. It is used to develop a 3-step process to identify candidate multi-SNP patterns: (1) pairwise (SNP-SNP) correlations are computed using CCC; (2) clusters of so-correlated SNPs identified; and (3) frequencies of these clusters in disease cases and controls compared to identify disease-associated multi-SNP patterns. This method identified 42 candidate multi-SNP associations with hypertensive heart disease (HHD), among which one cluster of 22 SNPs (six genes) included 13 in SLC8A1 (aka NCX1, an essential component of cardiac excitation-contraction coupling) and another of 32 SNPs had 29 from a different segment of SLC8A1. While allele frequencies show little difference between cases and controls, the cluster of 22 associated alleles were found in 20% of controls but no cases and the other in 3% of controls but 20% of cases. These suggest that both protective and risk effects on HHD could be exerted by combinations of variants in different regions of SLC8A1, modified by variants from other genes. The results demonstrate that this new correlation metric identifies disease-associated multi-SNP patterns overlooked by commonly used correlation measures. Furthermore, computation time using CCC is a small fraction of that required by other methods, thereby enabling the analyses of large GWAS datasets. © 2014 WILEY PERIODICALS, INC.

A custom correlation coefficient (CCC) approach for fast identification of multi-SNP association patterns in genome-wide SNPs data

PubMed Central

Climer, Sharlee; Yang, Wei; de las Fuentes, Lisa; Dávila-Román, Victor G.; Gu, C. Charles

2014-01-01

Complex diseases are often associated with sets of multiple interacting genetic factors and possibly with unique sets of the genetic factors in different groups of individuals (genetic heterogeneity). We introduce a novel concept of Custom Correlation Coefficient (CCC) between single nucleotide polymorphisms (SNPs) that address genetic heterogeneity by measuring subset correlations autonomously. It is used to develop a 3-step process to identify candidate multi-SNP patterns: (1) pairwise (SNP-SNP) correlations are computed using CCC; (2) clusters of so-correlated SNPs identified; and (3) frequencies of these clusters in disease cases and controls compared to identify disease-associated multi-SNP patterns. This method identified 42 candidate multi-SNP associations with hypertensive heart disease (HHD), among which one cluster of 22 SNPs (6 genes) included 13 in SLC8A1 (aka NCX1, an essential component of cardiac excitation-contraction coupling) and another of 32 SNPs had 29 from a different segment of SLC8A1. While allele frequencies show little difference between cases and controls, the cluster of 22 associated alleles were found in 20% of controls but no cases and the other in 3% of controls but 20% of cases. These suggest that both protective and risk effects on HHD could be exerted by combinations of variants in different regions of SLC8A1, modified by variants from other genes. The results demonstrate that this new correlation metric identifies disease-associated multi-SNP patterns overlooked by commonly used correlation measures. Furthermore, computation time using CCC is a small fraction of that required by other methods, thereby enabling the analyses of large GWAS datasets. PMID:25168954

Prospective Observational Study of Single-Site Multiport Per-umbilical Laparoscopic Endosurgery versus Conventional Multiport Laparoscopic Cholecystectomy: Critical Appraisal of a Unique Umbilical Approach

PubMed Central

Jategaonkar, Priyadarshan Anand; Yadav, Sudeep Pradeep

2014-01-01

Purpose. This prospective observational study compares an innovative approach of Single-Site Multi-Port Per-umbilical Laparoscopic Endo-surgery (SSMPPLE) cholecystectomy with the gold standard—Conventional Multi-port Laparoscopic Cholecystectomy (CMLC)—to assess the feasibility and efficacy of the former. Methods. In all, 646 patients were studied. SSMPPLE cholecystectomy utilized three ports inserted through three independent mini-incisions at the umbilicus. Only the day-to-day rigid laparoscopic instruments were used in all cases. The SSMPPLE cholecystectomy group had 320 patients and the CMLC group had 326 patients. The outcomes were statistically compared. Results. SSMPPLE cholecystectomy had average operative time of 43.8 min and blood loss of 9.4 mL. Their duration of hospitalization was 1.3 days (range, 1–5). Six patients (1.9%) of this group were converted to CMLC. Eleven patients had controlled gallbladder perforations at dissection. The Visual Analogue Scores for pain on postoperative days 0 and 7, the operative time, and the scar grades were significantly better for SSMPPLE than CMLC. However, umbilical sepsis and seroma outcomes were similar. We had no bile-duct injuries or port-site hernias in this study. Conclusion. SSMPPLE cholecystectomy approach complies with the principles of laparoscopic triangulation; it seems feasible and safe method of minimally invasive cholecystectomy. Overall, it has a potential to emerge as an economically viable alternative to single-port surgery. PMID:24876955

[Research on the methods for multi-class kernel CSP-based feature extraction].

PubMed

Wang, Jinjia; Zhang, Lingzhi; Hu, Bei

2012-04-01

To relax the presumption of strictly linear patterns in the common spatial patterns (CSP), we studied the kernel CSP (KCSP). A new multi-class KCSP (MKCSP) approach was proposed in this paper, which combines the kernel approach with multi-class CSP technique. In this approach, we used kernel spatial patterns for each class against all others, and extracted signal components specific to one condition from EEG data sets of multiple conditions. Then we performed classification using the Logistic linear classifier. Brain computer interface (BCI) competition III_3a was used in the experiment. Through the experiment, it can be proved that this approach could decompose the raw EEG singles into spatial patterns extracted from multi-class of single trial EEG, and could obtain good classification results.

A multi-disciplinary approach for the structural monitoring of Cultural Heritages in a seismic area

NASA Astrophysics Data System (ADS)

Fabrizia Buongiorno, Maria; Musacchio, Massimo; Guerra, Ignazio; Porco, Giacinto; Stramondo, Salvatore; Casula, Giuseppe; Caserta, Arrigo; Speranza, Fabio; Doumaz, Fawzi; Giovanna Bianchi, Maria; Luzi, Guido; Ilaria Pannaccione Apa, Maria; Montuori, Antonio; Gaudiosi, Iolanda; Vecchio, Antonio; Gervasi, Anna; Bonali, Elena; Romano, Dolores; Falcone, Sergio; La Piana, Carmelo

2014-05-01

In the recent years, the concepts of seismic risk vulnerability and structural health monitoring have become very important topics in the field of both structural and civil engineering for the identification of appropriate risk indicators and risk assessment methodologies in Cultural Heritages monitoring. The latter, which includes objects, building and sites with historical, architectural and/or engineering relevance, concerns the management, the preservation and the maintenance of the heritages within their surrounding environmental context, in response to climate changes and natural hazards (e.g. seismic, volcanic, landslides and flooding hazards). Within such a framework, the complexity and the great number of variables to be considered require a multi-disciplinary approach including strategies, methodologies and tools able to provide an effective monitoring of Cultural Heritages form both scientific and operational viewpoints. Based on this rationale, in this study, an advanced, technological and operationally-oriented approach is presented and tested, which enables measuring and monitoring Cultural Heritage conservation state and geophysical/geological setting of the area, in order to mitigate the seismic risk of the historical public goods at different spatial scales*. The integration between classical geophysical methods with new emerging sensing techniques enables a multi-depth, multi-resolution, and multi-scale monitoring in both space and time. An integrated system of methodologies, instrumentation and data-processing approaches for non-destructive Cultural Heritage investigations is proposed, which concerns, in detail, the analysis of seismogenetic sources, the geological-geotechnical setting of the area and site seismic effects evaluation, proximal remote sensing techniques (e.g. terrestrial laser scanner, ground-based radar systems, thermal cameras), high-resolution aerial and satellite-based remote sensing methodologies (e.g. aeromagnetic surveys, synthetic aperture radar, optical, multispectral and panchromatic measurements), static and dynamic structural health monitoring analysis (e.g. screening tests with georadar, sonic instruments, sclerometers and optic fibers). The final purpose of the proposed approach is the development of an investigation methodology for short- and long-term Cultural Heritages preservation in response to seismic stress, which has specific features of scalability, modularity and exportability for every possible monitoring configuration. Moreover, it allows gathering useful information to furnish guidelines for Institution and local Administration to plan consolidation actions and therefore prevention activity. Some preliminary results will be presented for the test site of Calabria Region, where some architectural heritages have been properly selected as case studies for monitoring purposes. *The present work is supported and funded by Ministero dell'Università, dell'Istruzione e della Ricerca (MIUR) under the research project PON01-02710 "MASSIMO" - "Monitoraggio in Area Sismica di Sistemi Monumentali".

Multi-parameter optimization of piezoelectric actuators for multi-mode active vibration control of cylindrical shells

NASA Astrophysics Data System (ADS)

Hu, K. M.; Li, Hua

2018-07-01

A novel technique for the multi-parameter optimization of distributed piezoelectric actuators is presented in this paper. The proposed method is designed to improve the performance of multi-mode vibration control in cylindrical shells. The optimization parameters of actuator patch configuration include position, size, and tilt angle. The modal control force of tilted orthotropic piezoelectric actuators is derived and the multi-parameter cylindrical shell optimization model is established. The linear quadratic energy index is employed as the optimization criterion. A geometric constraint is proposed to prevent overlap between tilted actuators, which is plugged into a genetic algorithm to search the optimal configuration parameters. A simply-supported closed cylindrical shell with two actuators serves as a case study. The vibration control efficiencies of various parameter sets are evaluated via frequency response and transient response simulations. The results show that the linear quadratic energy indexes of position and size optimization decreased by 14.0% compared to position optimization; those of position and tilt angle optimization decreased by 16.8%; and those of position, size, and tilt angle optimization decreased by 25.9%. It indicates that, adding configuration optimization parameters is an efficient approach to improving the vibration control performance of piezoelectric actuators on shells.

An enhanced SOCP-based method for feeder load balancing using the multi-terminal soft open point in active distribution networks

DOE PAGES

Ji, Haoran; Wang, Chengshan; Li, Peng; ...

2017-09-20

The integration of distributed generators (DGs) exacerbates the feeder power flow fluctuation and load unbalanced condition in active distribution networks (ADNs). The unbalanced feeder load causes inefficient use of network assets and network congestion during system operation. The flexible interconnection based on the multi-terminal soft open point (SOP) significantly benefits the operation of ADNs. The multi-terminal SOP, which is a controllable power electronic device installed to replace the normally open point, provides accurate active and reactive power flow control to enable the flexible connection of feeders. An enhanced SOCP-based method for feeder load balancing using the multi-terminal SOP is proposedmore » in this paper. Furthermore, by regulating the operation of the multi-terminal SOP, the proposed method can mitigate the unbalanced condition of feeder load and simultaneously reduce the power losses of ADNs. Then, the original non-convex model is converted into a second-order cone programming (SOCP) model using convex relaxation. In order to tighten the SOCP relaxation and improve the computation efficiency, an enhanced SOCP-based approach is developed to solve the proposed model. Finally, case studies are performed on the modified IEEE 33-node system to verify the effectiveness and efficiency of the proposed method.« less

An enhanced SOCP-based method for feeder load balancing using the multi-terminal soft open point in active distribution networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ji, Haoran; Wang, Chengshan; Li, Peng

The integration of distributed generators (DGs) exacerbates the feeder power flow fluctuation and load unbalanced condition in active distribution networks (ADNs). The unbalanced feeder load causes inefficient use of network assets and network congestion during system operation. The flexible interconnection based on the multi-terminal soft open point (SOP) significantly benefits the operation of ADNs. The multi-terminal SOP, which is a controllable power electronic device installed to replace the normally open point, provides accurate active and reactive power flow control to enable the flexible connection of feeders. An enhanced SOCP-based method for feeder load balancing using the multi-terminal SOP is proposedmore » in this paper. Furthermore, by regulating the operation of the multi-terminal SOP, the proposed method can mitigate the unbalanced condition of feeder load and simultaneously reduce the power losses of ADNs. Then, the original non-convex model is converted into a second-order cone programming (SOCP) model using convex relaxation. In order to tighten the SOCP relaxation and improve the computation efficiency, an enhanced SOCP-based approach is developed to solve the proposed model. Finally, case studies are performed on the modified IEEE 33-node system to verify the effectiveness and efficiency of the proposed method.« less

The Nature of E-Learning Adoption by Stakeholders of a University in Africa

ERIC Educational Resources Information Center

Ansong, Eric; Boateng, Richard; Boateng, Sheena L.; Anderson, Augustus B.

2017-01-01

Studies looking at the nature of technology adoption from a multi-dimensional perspective have remained below expectation especially in African countries. This study, therefore, sought to explore the nature of e-learning adoption in the University of Ghana using a multi-stakeholder approach. A quantitative survey approach was adopted for this…

The Impact of Using Multi-Sensory Approach for Teaching Students with Learning Disabilities

ERIC Educational Resources Information Center

Obaid, Majeda Al Sayyed

2013-01-01

The purpose of this study is to investigate the effect of using the Multi-Sensory Approach for teaching students with learning disabilities on the sixth grade students' achievement in mathematics at Jordanian public schools. To achieve the purpose of the study, a pre/post-test was constructed to measure students' achievement in mathematics. The…

Combining multiple decisions: applications to bioinformatics

NASA Astrophysics Data System (ADS)

Yukinawa, N.; Takenouchi, T.; Oba, S.; Ishii, S.

2008-01-01

Multi-class classification is one of the fundamental tasks in bioinformatics and typically arises in cancer diagnosis studies by gene expression profiling. This article reviews two recent approaches to multi-class classification by combining multiple binary classifiers, which are formulated based on a unified framework of error-correcting output coding (ECOC). The first approach is to construct a multi-class classifier in which each binary classifier to be aggregated has a weight value to be optimally tuned based on the observed data. In the second approach, misclassification of each binary classifier is formulated as a bit inversion error with a probabilistic model by making an analogy to the context of information transmission theory. Experimental studies using various real-world datasets including cancer classification problems reveal that both of the new methods are superior or comparable to other multi-class classification methods.

Multi-template image matching using alpha-rooted biquaternion phase correlation with application to logo recognition

NASA Astrophysics Data System (ADS)

DelMarco, Stephen

2011-06-01

Hypercomplex approaches are seeing increased application to signal and image processing problems. The use of multicomponent hypercomplex numbers, such as quaternions, enables the simultaneous co-processing of multiple signal or image components. This joint processing capability can provide improved exploitation of the information contained in the data, thereby leading to improved performance in detection and recognition problems. In this paper, we apply hypercomplex processing techniques to the logo image recognition problem. Specifically, we develop an image matcher by generalizing classical phase correlation to the biquaternion case. We further incorporate biquaternion Fourier domain alpha-rooting enhancement to create Alpha-Rooted Biquaternion Phase Correlation (ARBPC). We present the mathematical properties which justify use of ARBPC as an image matcher. We present numerical performance results of a logo verification problem using real-world logo data, demonstrating the performance improvement obtained using the hypercomplex approach. We compare results of the hypercomplex approach to standard multi-template matching approaches.

Problem-oriented patient record model as a conceptual foundation for a multi-professional electronic patient record.

PubMed

De Clercq, Etienne

2008-09-01

It is widely accepted that the development of electronic patient records, or even of a common electronic patient record, is one possible way to improve cooperation and data communication between nurses and physicians. Yet, little has been done so far to develop a common conceptual model for both medical and nursing patient records, which is a first challenge that should be met to set up a common electronic patient record. In this paper, we describe a problem-oriented conceptual model and we show how it may suit both nursing and medical perspectives in a hospital setting. We started from existing nursing theory and from an initial model previously set up for primary care. In a hospital pilot site, a multi-disciplinary team refined this model using one large and complex clinical case (retrospective study) and nine ongoing cases (prospective study). An internal validation was performed through hospital-wide multi-professional interviews and through discussions around a graphical user interface prototype. To assess the consistency of the model, a computer engineer specified it. Finally, a Belgian expert working group performed an external assessment of the model. As a basis for a common patient record we propose a simple problem-oriented conceptual model with two levels of meta-information. The model is mapped with current nursing theories and it includes the following concepts: "health care element", "health approach", "health agent", "contact", "subcontact" and "service". These concepts, their interrelationships and some practical rules for using the model are illustrated in this paper. Our results are compatible with ongoing standardization work at the Belgian and European levels. Our conceptual model is potentially a foundation for a multi-professional electronic patient record that is problem-oriented and therefore patient-centred.

Using the social entrepreneurship approach to generate innovative and sustainable malaria diagnosis interventions in Tanzania: a case study

PubMed Central

2010-01-01

Background There have been a number of interventions to date aimed at improving malaria diagnostic accuracy in sub-Saharan Africa. Yet, limited success is often reported for a number of reasons, especially in rural settings. This paper seeks to provide a framework for applied research aimed to improve malaria diagnosis using a combination of the established methods, participatory action research and social entrepreneurship. Methods This case study introduces the idea of using the social entrepreneurship approach (SEA) to create innovative and sustainable applied health research outcomes. The following key elements define the SEA: (1) identifying a locally relevant research topic and plan, (2) recognizing the importance of international multi-disciplinary teams and the incorporation of local knowledge, (3) engaging in a process of continuous innovation, adaptation and learning, (4) remaining motivated and determined to achieve sustainable long-term research outcomes and, (5) sharing and transferring ownership of the project with the international and local partner. Evaluation The SEA approach has a strong emphasis on innovation lead by local stakeholders. In this case, innovation resulted in a unique holistic research program aimed at understanding patient, laboratory and physician influences on accurate diagnosis of malaria. An evaluation of milestones for each SEA element revealed that the success of one element is intricately related to the success of other elements. Conclusions The SEA will provide an additional framework for researchers and local stakeholders that promotes innovation and adaptability. This approach will facilitate the development of new ideas, strategies and approaches to understand how health issues, such as malaria, affect vulnerable communities. PMID:20128922

Using the social entrepreneurship approach to generate innovative and sustainable malaria diagnosis interventions in Tanzania: a case study.

PubMed

Allen, Lisa K; Hetherington, Erin; Manyama, Mange; Hatfield, Jennifer M; van Marle, Guido

2010-02-03

There have been a number of interventions to date aimed at improving malaria diagnostic accuracy in sub-Saharan Africa. Yet, limited success is often reported for a number of reasons, especially in rural settings. This paper seeks to provide a framework for applied research aimed to improve malaria diagnosis using a combination of the established methods, participatory action research and social entrepreneurship. This case study introduces the idea of using the social entrepreneurship approach (SEA) to create innovative and sustainable applied health research outcomes. The following key elements define the SEA: (1) identifying a locally relevant research topic and plan, (2) recognizing the importance of international multi-disciplinary teams and the incorporation of local knowledge, (3) engaging in a process of continuous innovation, adaptation and learning, (4) remaining motivated and determined to achieve sustainable long-term research outcomes and, (5) sharing and transferring ownership of the project with the international and local partner. The SEA approach has a strong emphasis on innovation lead by local stakeholders. In this case, innovation resulted in a unique holistic research program aimed at understanding patient, laboratory and physician influences on accurate diagnosis of malaria. An evaluation of milestones for each SEA element revealed that the success of one element is intricately related to the success of other elements. The SEA will provide an additional framework for researchers and local stakeholders that promotes innovation and adaptability. This approach will facilitate the development of new ideas, strategies and approaches to understand how health issues, such as malaria, affect vulnerable communities.

A multi-views multi-learners approach towards dysarthric speech recognition using multi-nets artificial neural networks.

PubMed

Shahamiri, Seyed Reza; Salim, Siti Salwah Binti

2014-09-01

Automatic speech recognition (ASR) can be very helpful for speakers who suffer from dysarthria, a neurological disability that damages the control of motor speech articulators. Although a few attempts have been made to apply ASR technologies to sufferers of dysarthria, previous studies show that such ASR systems have not attained an adequate level of performance. In this study, a dysarthric multi-networks speech recognizer (DM-NSR) model is provided using a realization of multi-views multi-learners approach called multi-nets artificial neural networks, which tolerates variability of dysarthric speech. In particular, the DM-NSR model employs several ANNs (as learners) to approximate the likelihood of ASR vocabulary words and to deal with the complexity of dysarthric speech. The proposed DM-NSR approach was presented as both speaker-dependent and speaker-independent paradigms. In order to highlight the performance of the proposed model over legacy models, multi-views single-learner models of the DM-NSRs were also provided and their efficiencies were compared in detail. Moreover, a comparison among the prominent dysarthric ASR methods and the proposed one is provided. The results show that the DM-NSR recorded improved recognition rate by up to 24.67% and the error rate was reduced by up to 8.63% over the reference model.

Design of a multi-agent hydroeconomic model to simulate a complex human-water system: Early insights from the Jordan Water Project

NASA Astrophysics Data System (ADS)

Yoon, J.; Klassert, C. J. A.; Lachaut, T.; Selby, P. D.; Knox, S.; Gorelick, S.; Rajsekhar, D.; Tilmant, A.; Avisse, N.; Harou, J. J.; Gawel, E.; Klauer, B.; Mustafa, D.; Talozi, S.; Sigel, K.

2015-12-01

Our work focuses on development of a multi-agent, hydroeconomic model for purposes of water policy evaluation in Jordan. The model adopts a modular approach, integrating biophysical modules that simulate natural and engineered phenomena with human modules that represent behavior at multiple levels of decision making. The hydrologic modules are developed using spatially-distributed groundwater and surface water models, which are translated into compact simulators for efficient integration into the multi-agent model. For the groundwater model, we adopt a response matrix method approach in which a 3-dimensional MODFLOW model of a complex regional groundwater system is converted into a linear simulator of groundwater response by pre-processing drawdown results from several hundred numerical simulation runs. Surface water models for each major surface water basin in the country are developed in SWAT and similarly translated into simple rainfall-runoff functions for integration with the multi-agent model. The approach balances physically-based, spatially-explicit representation of hydrologic systems with the efficiency required for integration into a complex multi-agent model that is computationally amenable to robust scenario analysis. For the multi-agent model, we explicitly represent human agency at multiple levels of decision making, with agents representing riparian, management, supplier, and water user groups. The agents' decision making models incorporate both rule-based heuristics as well as economic optimization. The model is programmed in Python using Pynsim, a generalizable, open-source object-oriented code framework for modeling network-based water resource systems. The Jordan model is one of the first applications of Pynsim to a real-world water management case study. Preliminary results from a tanker market scenario run through year 2050 are presented in which several salient features of the water system are investigated: competition between urban and private farmer agents, the emergence of a private tanker market, disparities in economic wellbeing to different user groups caused by unique supply conditions, and response of the complex system to various policy interventions.

Project Based Learning in Multi-Grade Class

ERIC Educational Resources Information Center

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,…

Evaluating a multi-criteria model for hazard assessment in urban design. The Porto Marghera case study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Luria, Paolo; Aspinall, Peter A

2003-08-01

The aim of this paper is to describe a new approach to major industrial hazard assessment, which has been recently studied by the authors in conjunction with the Italian Environmental Protection Agency ('ARPAV'). The real opportunity for developing a different approach arose from the need of the Italian EPA to provide the Venice Port Authority with an appropriate estimation of major industrial hazards in Porto Marghera, an industrial estate near Venice (Italy). However, the standard model, the quantitative risk analysis (QRA), only provided a list of individual quantitative risk values, related to single locations. The experimental model is based onmore » a multi-criteria approach--the Analytic Hierarchy Process--which introduces the use of expert opinions, complementary skills and expertise from different disciplines in conjunction with quantitative traditional analysis. This permitted the generation of quantitative data on risk assessment from a series of qualitative assessments, on the present situation and on three other future scenarios, and use of this information as indirect quantitative measures, which could be aggregated for obtaining the global risk rate. This approach is in line with the main concepts proposed by the last European directive on Major Hazard Accidents, which recommends increasing the participation of operators, taking the other players into account and, moreover, paying more attention to the concepts of 'urban control', 'subjective risk' (risk perception) and intangible factors (factors not directly quantifiable)« less

Benefits of a one health approach: An example using Rift Valley fever.

PubMed

Rostal, Melinda K; Ross, Noam; Machalaba, Catherine; Cordel, Claudia; Paweska, Janusz T; Karesh, William B

2018-06-01

One Health has been promoted by international institutions as a framework to improve public health outcomes. Despite strong overall interest in One Health, country-, local- and project-level implementation remains limited, likely due to the lack of pragmatic and tested operational methods for implementation and metrics for evaluation. Here we use Rift Valley fever virus as an example to demonstrate the value of using a One Health approach for both scientific and resources advantages. We demonstrate that coordinated, a priori investigations between One Health sectors can yield higher statistical power to elucidate important public health relationships as compared to siloed investigations and post-hoc analyses. Likewise, we demonstrate that across a project or multi-ministry health study a One Health approach can result in improved resource efficiency, with resultant cost-savings (35% in the presented case). The results of these analyses demonstrate that One Health approaches can be directly and tangibly applied to health investigations.

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

PubMed

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.

Coordination of networked systems on digraphs with multiple leaders via pinning control

NASA Astrophysics Data System (ADS)

Chen, Gang; Lewis, Frank L.

2012-02-01

It is well known that achieving consensus among a group of multi-vehicle systems by local distributed control is feasible if and only if all nodes in the communication digraph are reachable from a single (root) node. In this article, we take into account a more general case that the communication digraph of the networked multi-vehicle systems is weakly connected and has two or more zero-in-degree and strongly connected subgraphs, i.e. there are two or more leader groups. Based on the pinning control strategy, the feasibility problem of achieving second-order controlled consensus is studied. At first, a necessary and sufficient condition is given when the topology is fixed. Then the method to design the controller and the rule to choose the pinned vehicles are discussed. The proposed approach allows us to extend several existing results for undirected graphs to directed balanced graphs. A sufficient condition is proposed in the case where the coupling topology is variable. As an illustrative example, a second-order controlled consensus scheme is applied to coordinate the movement of networked multiple mobile robots.

A Qualitative Multi-Case Study of the Influence of Personal and Professional Ethics on the Leadership of Public School Superintendents

ERIC Educational Resources Information Center

McDermott, Brian J.

2010-01-01

The purpose of this study is to examine the influence of personal and professional ethics on the leadership of public school superintendents. A multi-case, qualitative research design was used to gather data from four practicing public school superintendents. Transformational leadership theory and the three pillars of ethics of leadership…

A Multi-Case Study of University Students' Language-Learning Experience Mediated by Mobile Technologies: A Socio-Cultural Perspective

ERIC Educational Resources Information Center

Ma, Qing

2017-01-01

Emerging mobile technologies can be considered a new form of social and cultural artefact that mediates people's language learning. This multi-case study investigates how mobile technologies mediate a group of Hong Kong university students' L2 learning, which serves as a lens with which to capture the personalised, unique, contextual and…

The Influence of Game Design on the Collaborative Problem Solving Process: A Cross-Case Study of Multi-Player Collaborative Gameplay Analysis

ERIC Educational Resources Information Center

Yildirim, Nilay

2013-01-01

This cross-case study examines the relationships between game design attributes and collaborative problem solving process in the context of multi-player video games. The following game design attributes: sensory stimuli elements, level of challenge, and presentation of game goals and rules were examined to determine their influence on game…

Global dynamic optimization approach to predict activation in metabolic pathways.

PubMed

de Hijas-Liste, Gundián M; Klipp, Edda; Balsa-Canto, Eva; Banga, Julio R

2014-01-06

During the last decade, a number of authors have shown that the genetic regulation of metabolic networks may follow optimality principles. Optimal control theory has been successfully used to compute optimal enzyme profiles considering simple metabolic pathways. However, applying this optimal control framework to more general networks (e.g. branched networks, or networks incorporating enzyme production dynamics) yields problems that are analytically intractable and/or numerically very challenging. Further, these previous studies have only considered a single-objective framework. In this work we consider a more general multi-objective formulation and we present solutions based on recent developments in global dynamic optimization techniques. We illustrate the performance and capabilities of these techniques considering two sets of problems. First, we consider a set of single-objective examples of increasing complexity taken from the recent literature. We analyze the multimodal character of the associated non linear optimization problems, and we also evaluate different global optimization approaches in terms of numerical robustness, efficiency and scalability. Second, we consider generalized multi-objective formulations for several examples, and we show how this framework results in more biologically meaningful results. The proposed strategy was used to solve a set of single-objective case studies related to unbranched and branched metabolic networks of different levels of complexity. All problems were successfully solved in reasonable computation times with our global dynamic optimization approach, reaching solutions which were comparable or better than those reported in previous literature. Further, we considered, for the first time, multi-objective formulations, illustrating how activation in metabolic pathways can be explained in terms of the best trade-offs between conflicting objectives. This new methodology can be applied to metabolic networks with arbitrary topologies, non-linear dynamics and constraints.

Application of the 2016 diagnostic approach for autoimmune encephalitis from Lancet Neurology to Chinese patients.

PubMed

Li, Lin; Sun, Lin; Du, Rong; Zheng, Yuanchu; Dai, Feifei; Ma, Qiuying; Wang, Jiawei

2017-11-06

A unified clinical approach to diagnose autoimmune encephalitis was published in Lancet Neurology in 2016. Purpose of our study is to examine the feasibility and reasonability of the 2016 "A clinical approach to diagnosis of autoimmune encephalitis" in China with a retrospective study. We retrospectively collected 95 cases of autoimmune encephalitis and non autoimmune encephalitis cases with detailed clinical data from Beijing Tongren Hospital and the China National Knowledge Infrastructure (CNKI). All cases were analysed stepwise according to the approach in Lancet Neurology to compare the new diagnosis with the final clinical diagnosis. The disease course of these 95 cases ranged from 2 to 540 days. Initial symptoms include fever, headache, seizure, mental and behavioral disorders, memory deterioration and illusion. Based on symptoms and signs when the patient came to the hospital, the sensitivity and specificity of criteria were as follows: possible autoimmune encephalitis (pAE) 84% and 94%, definite autoimmune limbic encephalitis (dALE) 38% and 96%, probable anti-N-methyl-D-aspartate receptor encephalitis (prNMDARE) 49% and 98%. The sensitivities of the above three criteria and the specificity of pAE were low during early disease stage, while the specificities of dALE and prNMDAER remained relatively high in different time periods. This new autoimmune encephalitis diagnostic approach can recognize possible autoimmune encephalitis. The chances of a case being autoimmune-mediated following classification as autoimmune encephalitis with the new criteria are high. The flowchart is recommended to use as a whole. At the early disease stage, criteria with low sensitivity and high specificity, such as dALE and prNMDARE, lead most cases to enter subsequent diagnosis steps, namely autoantibody detection in the flowchart. Final diagnoses can only be made by autoantibody tests. These factors may make it challenging for clinicians to make diagnosis promptly and to begin immune-modulating therapy immediately. Moreover, the criteria for patients with paraneoplastic syndromes (PNSs) should be considered to avoid diagnosis omission. For Chinese patients, a multi-centre, prospective study on the clinical manifestations, laboratory diagnostic technology, therapy, and prognosis is greatly needed.

Online Teaching in Networked Learning Communities: A Multi-Method Approach to Studying the Role of the Teacher

ERIC Educational Resources Information Center

De Laat, Maarten; Lally, Vic; Lipponen, Lasse; Simons, Robert-Jan

2007-01-01

The aim of this paper is to study the online teaching styles of two teachers who each tutor a networked learning community (NLC), within the same workshop. The study is undertaking empirical work using a multi-method approach in order to triangulate and contextualise our findings and enrich our understanding of the teacher participation in these…

A multi-frequency receiver function inversion approach for crustal velocity structure

NASA Astrophysics Data System (ADS)

Li, Xuelei; Li, Zhiwei; Hao, Tianyao; Wang, Sheng; Xing, Jian

2017-05-01

In order to constrain the crustal velocity structures better, we developed a new nonlinear inversion approach based on multi-frequency receiver function waveforms. With the global optimizing algorithm of Differential Evolution (DE), low-frequency receiver function waveforms can primarily constrain large-scale velocity structures, while high-frequency receiver function waveforms show the advantages in recovering small-scale velocity structures. Based on the synthetic tests with multi-frequency receiver function waveforms, the proposed approach can constrain both long- and short-wavelength characteristics of the crustal velocity structures simultaneously. Inversions with real data are also conducted for the seismic stations of KMNB in southeast China and HYB in Indian continent, where crustal structures have been well studied by former researchers. Comparisons of inverted velocity models from previous and our studies suggest good consistency, but better waveform fitness with fewer model parameters are achieved by our proposed approach. Comprehensive tests with synthetic and real data suggest that the proposed inversion approach with multi-frequency receiver function is effective and robust in inverting the crustal velocity structures.

Building multi-country collaboration on watershed ...

EPA Pesticide Factsheets

Community-based watershed resilience programs that bridge public health and environmental outcomes often require cross-boundary, multi-country collaboration. The CRESSIDA project, led by the Regional Environmental Center for Central and Eastern Europe (REC) and supported by the US Environmental Protection Agency (EPA), forwards a resilience-focused approach for Western Balkan communities in the Drini and Drina river watersheds with the goal of safeguarding public health and the environment. The initial phases of this project give a contextualized example of how to advance resilience-driven environmental health goals in Western Balkan communities, and experience within the region has garnered several theme areas that require focus in order to promote a holistic watershed management program. In this paper, using CRESSIDA as a case study, we show (1) how watershed projects designed with resilience-driven environmental health goals can work in context, (2) provide data surrounding contextualized problems with resilience and suggest tools and strategies for the implementation of projects to address these problems, and (3) explore how cross-boundary foci are central to the success of these approaches in watersheds that comprise several countries. Published in the journal, Reviews on Environmental Health.

Super-resolved Parallel MRI by Spatiotemporal Encoding

PubMed Central

Schmidt, Rita; Baishya, Bikash; Ben-Eliezer, Noam; Seginer, Amir; Frydman, Lucio

2016-01-01

Recent studies described an alternative “ultrafast” scanning method based on spatiotemporal (SPEN) principles. SPEN demonstrates numerous potential advantages over EPI-based alternatives, at no additional expense in experimental complexity. An important aspect that SPEN still needs to achieve for providing a competitive acquisition alternative entails exploiting parallel imaging algorithms, without compromising its proven capabilities. The present work introduces a combination of multi-band frequency-swept pulses simultaneously encoding multiple, partial fields-of-view; together with a new algorithm merging a Super-Resolved SPEN image reconstruction and SENSE multiple-receiving methods. The ensuing approach enables one to reduce both the excitation and acquisition times of ultrafast SPEN acquisitions by the customary acceleration factor R, without compromises in either the ensuing spatial resolution, SAR deposition, or the capability to operate in multi-slice mode. The performance of these new single-shot imaging sequences and their ancillary algorithms were explored on phantoms and human volunteers at 3T. The gains of the parallelized approach were particularly evident when dealing with heterogeneous systems subject to major T2/T2* effects, as is the case upon single-scan imaging near tissue/air interfaces. PMID:24120293

An adaptive multi-level simulation algorithm for stochastic biological systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lester, C., E-mail: lesterc@maths.ox.ac.uk; Giles, M. B.; Baker, R. E.

2015-01-14

Discrete-state, continuous-time Markov models are widely used in the modeling of biochemical reaction networks. Their complexity often precludes analytic solution, and we rely on stochastic simulation algorithms (SSA) to estimate system statistics. The Gillespie algorithm is exact, but computationally costly as it simulates every single reaction. As such, approximate stochastic simulation algorithms such as the tau-leap algorithm are often used. Potentially computationally more efficient, the system statistics generated suffer from significant bias unless tau is relatively small, in which case the computational time can be comparable to that of the Gillespie algorithm. The multi-level method [Anderson and Higham, “Multi-level Montemore » Carlo for continuous time Markov chains, with applications in biochemical kinetics,” SIAM Multiscale Model. Simul. 10(1), 146–179 (2012)] tackles this problem. A base estimator is computed using many (cheap) sample paths at low accuracy. The bias inherent in this estimator is then reduced using a number of corrections. Each correction term is estimated using a collection of paired sample paths where one path of each pair is generated at a higher accuracy compared to the other (and so more expensive). By sharing random variables between these paired paths, the variance of each correction estimator can be reduced. This renders the multi-level method very efficient as only a relatively small number of paired paths are required to calculate each correction term. In the original multi-level method, each sample path is simulated using the tau-leap algorithm with a fixed value of τ. This approach can result in poor performance when the reaction activity of a system changes substantially over the timescale of interest. By introducing a novel adaptive time-stepping approach where τ is chosen according to the stochastic behaviour of each sample path, we extend the applicability of the multi-level method to such cases. We demonstrate the efficiency of our method using a number of examples.« less

A fuzzy MCDM model with objective and subjective weights for evaluating service quality in hotel industries

NASA Astrophysics Data System (ADS)

Zoraghi, Nima; Amiri, Maghsoud; Talebi, Golnaz; Zowghi, Mahdi

2013-12-01

This paper presents a fuzzy multi-criteria decision-making (FMCDM) model by integrating both subjective and objective weights for ranking and evaluating the service quality in hotels. The objective method selects weights of criteria through mathematical calculation, while the subjective method uses judgments of decision makers. In this paper, we use a combination of weights obtained by both approaches in evaluating service quality in hotel industries. A real case study that considered ranking five hotels is illustrated. Examples are shown to indicate capabilities of the proposed method.

Decerns: A framework for multi-criteria decision analysis

DOE PAGES

Yatsalo, Boris; Didenko, Vladimir; Gritsyuk, Sergey; ...

2015-02-27

A new framework, Decerns, for multicriteria decision analysis (MCDA) of a wide range of practical problems on risk management is introduced. Decerns framework contains a library of modules that are the basis for two scalable systems: DecernsMCDA for analysis of multicriteria problems, and DecernsSDSS for multicriteria analysis of spatial options. DecernsMCDA includes well known MCDA methods and original methods for uncertainty treatment based on probabilistic approaches and fuzzy numbers. As a result, these MCDA methods are described along with a case study on analysis of multicriteria location problem.

Detecting Inconsistencies in Multi-View Models with Variability

NASA Astrophysics Data System (ADS)

Lopez-Herrejon, Roberto Erick; Egyed, Alexander

Multi-View Modeling (MVM) is a common modeling practice that advocates the use of multiple, different and yet related models to represent the needs of diverse stakeholders. Of crucial importance in MVM is consistency checking - the description and verification of semantic relationships amongst the views. Variability is the capacity of software artifacts to vary, and its effective management is a core tenet of the research in Software Product Lines (SPL). MVM has proven useful for developing one-of-a-kind systems; however, to reap the potential benefits of MVM in SPL it is vital to provide consistency checking mechanisms that cope with variability. In this paper we describe how to address this need by applying Safe Composition - the guarantee that all programs of a product line are type safe. We evaluate our approach with a case study.

Multifocal necrotising fasciitis: an overlooked entity?

PubMed

El-Khani, Ussamah; Nehme, Jean; Darwish, Ammar; Jamnadas-Khoda, Benjamin; Scerri, Godwin; Heppell, Simon; Bennett, Nicholas

2012-04-01

The aim of the study is to report a case of multi-focal necrotising fasciitis, review research on this subject to identify common aetiological factors and highlight suggestions to improve management. Necrotising fasciitis is a severe, life-threatening soft tissue infection that typically arises from a single area, usually secondary to a minor penetrating injury. Multi-focal necrotising fasciitis, where there is more than one non-contiguous area of necrosis, is much less commonly reported. There are no guidelines specific to the management of multi-focal necrotising fasciitis, and its under-reporting may lead to missed management opportunities. A systematic literature review in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol. A search of MEDLINE, OLD MEDLINE and the Cochrane Collaboration was performed from 1966 to March 2011 using 16 search terms. All articles were screened for genuine non-contiguous multi-focal necrotising fasciitis. Of the papers that met this criterion, data on patient demographics, likely inciting injury, presentation time-line, microbial agents, sites affected, objective assessment scores, treatment and outcome were extracted. A total of 31 studies met our inclusion criteria and 33 individual cases of multi-focal necrotising fasciitis were included in the quantitative analysis. About half (52%) of cases were type II necrotising fasciitis; 42% of cases had identifiable inciting injuries; 21% of cases developed multi-focal lesions non-synchronously, of which 86% were type II. Nearly all (94%) of cases had incomplete objective assessment scores. One case identified inflammatory imaging findings prior to clinical necrosis. Multifocality in necrotising fasciitis is likely to be associated with type II disease. We postulate that validated objective tools will aid necrotising fasciitis management pathways that will identify high-risk groups for multifocality and advise early pre-emptive imaging. We recommend the adoption of regional multi-focal necrotising fasciitis registers. Copyright © 2011 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights reserved.

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

PubMed

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.

On the transition from the Ginzburg-Landau equation to the extended Fisher-Kolmogorov equation

NASA Astrophysics Data System (ADS)

Rottschäfer, Vivi; Doelman, Arjen

1998-07-01

The Ginzburg-Landau (GL) equation ‘generically’ describes the behaviour of small perturbations of a marginally unstable basic state in systems on unbounded domains. In this paper we consider the transition from this generic situation to a degenerate (co-dimension 2) case in which the GL approach is no longer valid. Instead of studying a general underlying model problem, we consider a two-dimensional system of coupled reaction-diffusion equations in one spatial dimension. We show that near the degeneration the behaviour of small perturbations is governed by the extended Fisher-Kolmogorov (eFK) equation (at leading order). The relation between the GL-equation and the eFK-equation is quite subtle, but can be analysed in detail. The main goal of this paper is to study this relation, which we do asymptotically. The asymptotic analysis is compared to numerical simulations of the full reaction-diffusion system. As one approaches the co-dimension 2 point, we observe that the stable stationary periodic patterns predicted by the GL-equation evolve towards various different families of stable, stationary (but not necessarily periodic) so-called ‘multi-bump’ solutions. In the literature, these multi-bump patterns are shown to exist as solutions of the eFK-equation, but there is no proof of the asymptotic stability of these solutions. Our results suggest that these multi-bump patterns can also be asymptotically stable in large classes of model problems.

Vulnerability and risk of deltaic social-ecological systems exposed to multiple hazards.

PubMed

Hagenlocher, Michael; Renaud, Fabrice G; Haas, Susanne; Sebesvari, Zita

2018-08-01

Coastal river deltas are hotspots of global change impacts. Sustainable delta futures are increasingly threatened due to rising hazard exposure combined with high vulnerabilities of deltaic social-ecological systems. While the need for integrated multi-hazard approaches has been clearly articulated, studies on vulnerability and risk in deltas either focus on local case studies or single hazards and do not apply a social-ecological systems perspective. As a result, vulnerabilities and risks in areas with strong social and ecological coupling, such as coastal deltas, are not fully understood and the identification of risk reduction and adaptation strategies are often based on incomplete assumptions. To overcome these limitations, we propose an innovative modular indicator library-based approach for the assessment of multi-hazard risk of social-ecological systems across and within coastal deltas globally, and apply it to the Amazon, Ganges-Brahmaputra-Meghna (GBM), and Mekong deltas. Results show that multi-hazard risk is highest in the GBM delta and lowest in the Amazon delta. The analysis reveals major differences between social and environmental vulnerability across the three deltas, notably in the Mekong and the GBM deltas where environmental vulnerability is significantly higher than social vulnerability. Hotspots and drivers of risk vary spatially, thus calling for spatially targeted risk reduction and adaptation strategies within the deltas. Ecosystems have been identified as both an important element at risk as well as an entry point for risk reduction and adaptation strategies. Copyright © 2018. Published by Elsevier B.V.

["Nicht von schlechten Eltern - NischE": A Family Orientated Collaborative Care Approach to Support Children in Families with Mentally Ill Parents].

PubMed

Wabnitz, Pascal; Kronmüller, Klaus-Thomas; Wieskus-Friedemann, Erwin; Kliem, Sabine; Hoppmann, Johannes; Burek, Monika; Löhr, Michael; Kemper, Ulrich; Nienaber, André

2016-11-01

"Nicht von schlechten Eltern - NischE": A Family Orientated Collaborative Care Approach to Support Children in Families with Mentally Ill Parents The present work describes the setting- and multi-professional offer "NischE" in Gütersloh, a systemic approach for the care of children and their mentally ill parents. Children of mentally ill parents are a special risk group for developing their own mental illness. The aim of the collaborative care model between child and adolescent psychiatry, youth services and adult psychiatry is to enable affected families in terms of family-focused practice a low threshold access to different services. For this purpose, two positions have been created to advise the affected families and support access to the help system in the sense of a systemic case management in a project. The article describes the background and the need for the development of the offer, the current scientific knowledge base on the subject and illustrates the procedure using a case study from practice.

Brand Coherence at a Major Multi-Campus Public Research University: An Exploratory Case Study

ERIC Educational Resources Information Center

Zinkan, Rob

2016-01-01

With increased competition and other market forces affecting higher education, branding has emerged as a strategic imperative for colleges and universities. Branding in academia faces many inherent challenges, including institutions' multi-pronged missions and decentralized organizational structures. In some cases, branding is not widely…

Implementing service improvement projects within pre-registration nursing education: a multi-method case study evaluation.

PubMed

Baillie, Lesley; Bromley, Barbara; Walker, Moira; Jones, Rebecca; Mhlanga, Fortune

2014-01-01

Preparing healthcare students for quality and service improvement is important internationally. A United Kingdom (UK) initiative aims to embed service improvement in pre-registration education. A UK university implemented service improvement teaching for all nursing students. In addition, the degree pathway students conducted service improvement projects as the basis for their dissertations. The study aimed to evaluate the implementation of service improvement projects within a pre-registration nursing curriculum. A multi-method case study was conducted, using student questionnaires, focus groups with students and academic staff, and observation of action learning sets. Questionnaire data were analysed using SPSS v19. Qualitative data were analysed using Ritchie and Spencer's (1994) Framework Approach. Students were very positive about service improvement. The degree students, who conducted service improvement projects in practice, felt more knowledgeable than advanced diploma students. Selecting the project focus was a key issue and students encountered some challenges in practice. Support for student service improvement projects came from action learning sets, placement staff, and academic staff. Service improvement projects had a positive effect on students' learning. An effective partnership between the university and partner healthcare organisations, and support for students in practice, is essential. Copyright © 2013 Elsevier Ltd. All rights reserved.

Using ecosystem services in decision-making to support sustainable development: Critiques, model development, a case study, and perspectives.

PubMed

Zagonari, Fabio

2016-04-01

In this paper, I propose a general, consistent, and operational approach that accounts for ecosystem services in a decision-making context: I link ecosystem services to sustainable development criteria; adopt multi-criteria analysis to measure ecosystem services, with weights provided by stakeholders used to account for equity issues; apply both temporal and spatial discount rates; and adopt a technique to order performance of the possible solutions based on their similarity to an ideal solution (TOPSIS) to account for uncertainty about the parameters and functions. Applying this approach in a case study of an offshore research platform in Italy (CNR Acqua Alta) revealed that decisions depend non-linearly on the degree of loss aversion, to a smaller extent on a global focus (as opposed to a local focus), and to the smallest extent on social concerns (as opposed to economic or environmental concerns). Application of the general model to the case study leads to the conclusion that the ecosystem services framework is likely to be less useful in supporting decisions than in identifying the crucial features on which decisions depend, unless experts from different disciplines are involved, stakeholders are represented, and experts and stakeholders achieve mutual understanding. Copyright © 2016 Elsevier B.V. All rights reserved.

Person-centred web-based support - development through a Swedish multi-case study

PubMed Central

2013-01-01

Background Departing from the widespread use of the internet in modern society and the emerging use of web applications in healthcare this project captures persons’ needs and expectations in order to develop highly usable web recourses. The purpose of this paper is to outline a multi-case research project focused on the development and evaluation of person-centred web-based support for people with long-term illness. To support the underlying idea to move beyond the illness, we approach the development of web support from the perspective of the emergent area of person-centred care. The project aims to contribute to the ongoing development of web-based supports in health care and to the emerging field of person-centred care. Methods/Design The research design uses a meta-analytical approach through its focus on synthesizing experiences from four Swedish regional and national cases of design and use of web-based support in long-term illness. The cases include children (bladder dysfunction and urogenital malformation), young adults (living close to persons with mental illness), and two different cases of adults (women with breast cancer and childbearing women with type 1 diabetes). All of the cases are ongoing, though in different stages of design, implementation, and analysis. This, we argue, will lead to a synthesis of results on a meta-level not yet described. Discussion To allow valid comparisons between the four cases we explore and problematize them in relation to four main aspects: 1) The use of people’s experiences and needs; 2) The role of use of theories in the design of person-centred web-based supports; 3) The evaluation of the effects of health outcomes for the informants involved and 4) The development of a generic person-centred model for learning and social support for people with long-term illness and their significant others. Person-centred web-based support is a new area and few studies focus on how web-based interventions can contribute to the development of person-centred care. In summary, the main intention of the project outlined here is to contribute with both a synthesis of results on meta-level from four cases and a substantial contribution to the field person-centred care. PMID:24139057

Social vulnerability assessment using spatial multi-criteria analysis (SEVI model) and the Social Vulnerability Index (SoVI model) - a case study for Bucharest, Romania

NASA Astrophysics Data System (ADS)

Armaş, I.; Gavriş, A.

2013-06-01

In recent decades, the development of vulnerability frameworks has enlarged the research in the natural hazards field. Despite progress in developing the vulnerability studies, there is more to investigate regarding the quantitative approach and clarification of the conceptual explanation of the social component. At the same time, some disaster-prone areas register limited attention. Among these, Romania's capital city, Bucharest, is the most earthquake-prone capital in Europe and the tenth in the world. The location is used to assess two multi-criteria methods for aggregating complex indicators: the social vulnerability index (SoVI model) and the spatial multi-criteria social vulnerability index (SEVI model). Using the data of the 2002 census we reduce the indicators through a factor analytical approach to create the indices and examine if they bear any resemblance to the known vulnerability of Bucharest city through an exploratory spatial data analysis (ESDA). This is a critical issue that may provide better understanding of the social vulnerability in the city and appropriate information for authorities and stakeholders to consider in their decision making. The study emphasizes that social vulnerability is an urban process that increased in a post-communist Bucharest, raising the concern that the population at risk lacks the capacity to cope with disasters. The assessment of the indices indicates a significant and similar clustering pattern of the census administrative units, with an overlap between the clustering areas affected by high social vulnerability. Our proposed SEVI model suggests adjustment sensitivity, useful in the expert-opinion accuracy.

A Bottom-up Vulnerability Analysis of Water Systems with Decentralized Decision Making and Demographic Shifts- the Case of Jordan.

NASA Astrophysics Data System (ADS)

Lachaut, T.; Yoon, J.; Klassert, C. J. A.; Talozi, S.; Mustafa, D.; Knox, S.; Selby, P. D.; Haddad, Y.; Gorelick, S.; Tilmant, A.

2016-12-01

Probabilistic approaches to uncertainty in water systems management can face challenges of several types: non stationary climate, sudden shocks such as conflict-driven migrations, or the internal complexity and dynamics of large systems. There has been a rising trend in the development of bottom-up methods that place focus on the decision side instead of probability distributions and climate scenarios. These approaches are based on defining acceptability thresholds for the decision makers and considering the entire range of possibilities over which such thresholds are crossed. We aim at improving the knowledge on the applicability and relevance of this approach by enlarging its scope beyond climate uncertainty and single decision makers; thus including demographic shifts, internal system dynamics, and multiple stakeholders at different scales. This vulnerability analysis is part of the Jordan Water Project and makes use of an ambitious multi-agent model developed by its teams with the extensive cooperation of the Ministry of Water and Irrigation of Jordan. The case of Jordan is a relevant example for migration spikes, rapid social changes, resource depletion and climate change impacts. The multi-agent modeling framework used provides a consistent structure to assess the vulnerability of complex water resources systems with distributed acceptability thresholds and stakeholder interaction. A proof of concept and preliminary results are presented for a non-probabilistic vulnerability analysis that involves different types of stakeholders, uncertainties other than climatic and the integration of threshold-based indicators. For each stakeholder (agent) a vulnerability matrix is constructed over a multi-dimensional domain, which includes various hydrologic and/or demographic variables.

Teachers' Lived Experiences about Teaching-Learning Process in Multi-Grade Classes

ERIC Educational Resources Information Center

Mortazavizadeh, Seyyed Heshmatollah; Nili, Mohammad Reza; Isfahani, Ahmad Reza Nasr; Hassani, Mohammad

2017-01-01

This study seeks to recognize teachers' lived experiences about teaching-learning process in multi-grade classes. The approach of the study is qualitative under the rubric of phenomenological studies. The statistical population consisted of the teachers of multi-grade classes in a non-prosperous province and a prosperous one. 14 teachers were…

Multi-scale heat and mass transfer modelling of cell and tissue cryopreservation

PubMed Central

Xu, Feng; Moon, Sangjun; Zhang, Xiaohui; Shao, Lei; Song, Young Seok; Demirci, Utkan

2010-01-01

Cells and tissues undergo complex physical processes during cryopreservation. Understanding the underlying physical phenomena is critical to improve current cryopreservation methods and to develop new techniques. Here, we describe multi-scale approaches for modelling cell and tissue cryopreservation including heat transfer at macroscale level, crystallization, cell volume change and mass transport across cell membranes at microscale level. These multi-scale approaches allow us to study cell and tissue cryopreservation. PMID:20047939

Merging Contexts and Shifting Practice within Professional Development Schools: Teachers as Teacher Educators and the Nature of Resistance--A Critical Multi-Case Study

ERIC Educational Resources Information Center

Wallace, Mary Ann

2012-01-01

This qualitative critical multi-case study examines the nature of resistance as it emerges within the work of two urban secondary teachers acting as teacher educators, each teaching a secondary teacher preparation course within their own respective school context. Both research sites are discursively and functionally similar in terms of their…

The Multi-Disciplinary Graduate Program in Educational Research. Final Report, Part IV; The Utilization of Sociological Ideas in Organizational Planning: A Case Study.

ERIC Educational Resources Information Center

Lazarsfeld, Paul F., Ed.

This document, the fourth in the final report on the Multi-Disciplinary Graduate Program in Educational Research, is a qualitative case study designed to show the form of sociological contributions to and the role of sociologists in policy formulation at an American Educational Research Association (AERA) colloquium. Discussions at the conference…

Labeled RFS-Based Track-Before-Detect for Multiple Maneuvering Targets in the Infrared Focal Plane Array.

PubMed

Li, Miao; Li, Jun; Zhou, Yiyu

2015-12-08

The problem of jointly detecting and tracking multiple targets from the raw observations of an infrared focal plane array is a challenging task, especially for the case with uncertain target dynamics. In this paper a multi-model labeled multi-Bernoulli (MM-LMB) track-before-detect method is proposed within the labeled random finite sets (RFS) framework. The proposed track-before-detect method consists of two parts-MM-LMB filter and MM-LMB smoother. For the MM-LMB filter, original LMB filter is applied to track-before-detect based on target and measurement models, and is integrated with the interacting multiple models (IMM) approach to accommodate the uncertainty of target dynamics. For the MM-LMB smoother, taking advantage of the track labels and posterior model transition probability, the single-model single-target smoother is extended to a multi-model multi-target smoother. A Sequential Monte Carlo approach is also presented to implement the proposed method. Simulation results show the proposed method can effectively achieve tracking continuity for multiple maneuvering targets. In addition, compared with the forward filtering alone, our method is more robust due to its combination of forward filtering and backward smoothing.

Labeled RFS-Based Track-Before-Detect for Multiple Maneuvering Targets in the Infrared Focal Plane Array

PubMed Central

Li, Miao; Li, Jun; Zhou, Yiyu

2015-01-01

The problem of jointly detecting and tracking multiple targets from the raw observations of an infrared focal plane array is a challenging task, especially for the case with uncertain target dynamics. In this paper a multi-model labeled multi-Bernoulli (MM-LMB) track-before-detect method is proposed within the labeled random finite sets (RFS) framework. The proposed track-before-detect method consists of two parts—MM-LMB filter and MM-LMB smoother. For the MM-LMB filter, original LMB filter is applied to track-before-detect based on target and measurement models, and is integrated with the interacting multiple models (IMM) approach to accommodate the uncertainty of target dynamics. For the MM-LMB smoother, taking advantage of the track labels and posterior model transition probability, the single-model single-target smoother is extended to a multi-model multi-target smoother. A Sequential Monte Carlo approach is also presented to implement the proposed method. Simulation results show the proposed method can effectively achieve tracking continuity for multiple maneuvering targets. In addition, compared with the forward filtering alone, our method is more robust due to its combination of forward filtering and backward smoothing. PMID:26670234

Opportunistic tri-band carrier aggregation in licensed spectrum for multi-operator 5G hetnet

NASA Astrophysics Data System (ADS)

Maksymuk, Taras; Kyryk, Maryan; Klymash, Mykhailo; Jo, Minho; Romaniuk, Ryszard; Kotyra, Andrzej; Zhanpeisova, Aizhan; Kozbekova, Ainur

2017-08-01

Increasing capacity of mobile networks is a real challenge due to rapid increasing of traffic demands and spectrum scarcity. Carrier aggregation technology is aimed to increase the user data rate by combining the throughput of few spectrum bands, even if they are not physically collocated. Utilization of unlicensed Wi-Fi 5 GHz band for mobile transmission opens new perspectives for carrier aggregation due to vast amount of spectrum range, which can be available for aggregation to supplement data rates for end users. There are many solutions proposed to enable mobile data transmission in unlicensed band without disturbing interference for the existing Wi-Fi users. The paper presents a new approach for opportunistic carrier aggregation in licensed and unlicensed band for multi-operator 5G network. It allows multiple network operators to utilize unlicensed spectrum opportunistically if it is not currently used by Wi-Fi or other mobile network operators. Performance of the proposed approach has been simulated in case of two competing operators. Simulation results reveal that applying the proposed method ensures achieving satisfactory performance of carrier aggregation for the case of two network operators.

A Multi-Band Uncertainty Set Based Robust SCUC With Spatial and Temporal Budget Constraints

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dai, Chenxi; Wu, Lei; Wu, Hongyu

2016-11-01

The dramatic increase of renewable energy resources in recent years, together with the long-existing load forecast errors and increasingly involved price sensitive demands, has introduced significant uncertainties into power systems operation. In order to guarantee the operational security of power systems with such uncertainties, robust optimization has been extensively studied in security-constrained unit commitment (SCUC) problems, for immunizing the system against worst uncertainty realizations. However, traditional robust SCUC models with single-band uncertainty sets may yield over-conservative solutions in most cases. This paper proposes a multi-band robust model to accurately formulate various uncertainties with higher resolution. By properly tuning band intervalsmore » and weight coefficients of individual bands, the proposed multi-band robust model can rigorously and realistically reflect spatial/temporal relationships and asymmetric characteristics of various uncertainties, and in turn could effectively leverage the tradeoff between robustness and economics of robust SCUC solutions. The proposed multi-band robust SCUC model is solved by Benders decomposition (BD) and outer approximation (OA), while taking the advantage of integral property of the proposed multi-band uncertainty set. In addition, several accelerating techniques are developed for enhancing the computational performance and the convergence speed. Numerical studies on a 6-bus system and the modified IEEE 118-bus system verify the effectiveness of the proposed robust SCUC approach for enhancing uncertainty modeling capabilities and mitigating conservativeness of the robust SCUC solution.« less

Communication: Density functional theory model for multi-reference systems based on the exact-exchange hole normalization

NASA Astrophysics Data System (ADS)

Laqua, Henryk; Kussmann, Jörg; Ochsenfeld, Christian

2018-03-01

The correct description of multi-reference electronic ground states within Kohn-Sham density functional theory (DFT) requires an ensemble-state representation, employing fractionally occupied orbitals. However, the use of fractional orbital occupation leads to non-normalized exact-exchange holes, resulting in large fractional-spin errors for conventional approximative density functionals. In this communication, we present a simple approach to directly include the exact-exchange-hole normalization into DFT. Compared to conventional functionals, our model strongly improves the description for multi-reference systems, while preserving the accuracy in the single-reference case. We analyze the performance of our proposed method at the example of spin-averaged atoms and spin-restricted bond dissociation energy surfaces.

Communication: Density functional theory model for multi-reference systems based on the exact-exchange hole normalization.

PubMed

Laqua, Henryk; Kussmann, Jörg; Ochsenfeld, Christian

2018-03-28

The correct description of multi-reference electronic ground states within Kohn-Sham density functional theory (DFT) requires an ensemble-state representation, employing fractionally occupied orbitals. However, the use of fractional orbital occupation leads to non-normalized exact-exchange holes, resulting in large fractional-spin errors for conventional approximative density functionals. In this communication, we present a simple approach to directly include the exact-exchange-hole normalization into DFT. Compared to conventional functionals, our model strongly improves the description for multi-reference systems, while preserving the accuracy in the single-reference case. We analyze the performance of our proposed method at the example of spin-averaged atoms and spin-restricted bond dissociation energy surfaces.

Health communication in primary health care -a case study of ICT development for health promotion.

PubMed

Mahmud, Amina Jama; Olander, Ewy; Eriksén, Sara; Haglund, Bo Ja

2013-01-30

Developing Information and Communication Technology (ICT) supported health communication in PHC could contribute to increased health literacy and empowerment, which are foundations for enabling people to increase control over their health, as a way to reduce increasing lifestyle related ill health. However, to increase the likelihood of success of implementing ICT supported health communication, it is essential to conduct a detailed analysis of the setting and context prior to the intervention. The aim of this study was to gain a better understanding of health communication for health promotion in PHC with emphasis on the implications for a planned ICT supported interactive health channel. A qualitative case study, with a multi-methods approach was applied. Field notes, document study and focus groups were used for data collection. Data was then analyzed using qualitative content analysis. Health communication is an integral part of health promotion practice in PHC in this case study. However, there was a lack of consensus among health professionals on what a health promotion approach was, causing discrepancy in approaches and practices of health communication. Two themes emerged from the data analysis: Communicating health and environment for health communication. The themes represented individual and organizational factors that affected health communication practice in PHC and thus need to be taken into consideration in the development of the planned health channel. Health communication practiced in PHC is individual based, preventive and reactive in nature, as opposed to population based, promotive and proactive in line with a health promotion approach. The most significant challenge in developing an ICT supported health communication channel for health promotion identified in this study, is profiling a health promotion approach in PHC. Addressing health promotion values and principles in the design of ICT supported health communication channel could facilitate health communication for promoting health, i.e. 'health promoting communication'.

Health communication in primary health care -A case study of ICT development for health promotion

PubMed Central

2013-01-01

Background Developing Information and Communication Technology (ICT) supported health communication in PHC could contribute to increased health literacy and empowerment, which are foundations for enabling people to increase control over their health, as a way to reduce increasing lifestyle related ill health. However, to increase the likelihood of success of implementing ICT supported health communication, it is essential to conduct a detailed analysis of the setting and context prior to the intervention. The aim of this study was to gain a better understanding of health communication for health promotion in PHC with emphasis on the implications for a planned ICT supported interactive health channel. Methods A qualitative case study, with a multi-methods approach was applied. Field notes, document study and focus groups were used for data collection. Data was then analyzed using qualitative content analysis. Results Health communication is an integral part of health promotion practice in PHC in this case study. However, there was a lack of consensus among health professionals on what a health promotion approach was, causing discrepancy in approaches and practices of health communication. Two themes emerged from the data analysis: Communicating health and environment for health communication. The themes represented individual and organizational factors that affected health communication practice in PHC and thus need to be taken into consideration in the development of the planned health channel. Conclusions Health communication practiced in PHC is individual based, preventive and reactive in nature, as opposed to population based, promotive and proactive in line with a health promotion approach. The most significant challenge in developing an ICT supported health communication channel for health promotion identified in this study, is profiling a health promotion approach in PHC. Addressing health promotion values and principles in the design of ICT supported health communication channel could facilitate health communication for promoting health, i.e. ‘health promoting communication’. PMID:23363566

The CSAICLAWPS project: a multi-scalar, multi-data source approach to providing climate services for both modelling of climate change impacts on crop yields and development of community-level adaptive capacity for sustainable food security

NASA Astrophysics Data System (ADS)

Forsythe, N. D.; Fowler, H. J.

2017-12-01

The "Climate-smart agriculture implementation through community-focused pursuit of land and water productivity in South Asia" (CSAICLAWPS) project is a research initiative funded by the (UK) Royal Society through its Challenge Grants programme which is part of the broader UK Global Challenges Research Fund (GCRF). CSAICLAWPS has three objectives: a) development of "added-value" - bias assessed, statistically down-scaled - climate projections for selected case study sites across South Asia; b) investigation of crop failure modes under both present (observed) and future (projected) conditions; and c) facilitation of developing local adaptive capacity and resilience through stakeholder engagement. At AGU we will be presenting both next steps and progress to date toward these three objectives: [A] We have carried out bias assessments of a substantial multi-model RCM ensemble (MME) from the CORDEX South Asia (CORDEXdomain for case studies in three countries - Pakistan, India and Sri Lanka - and (stochastically) produced synthetic time-series for these sites from local observations using a Python-based implementation of the principles underlying the Climate Research Unit Weather Generator (CRU-WG) in order to enable probabilistic simulation of current crop yields. [B] We have characterised present response of local crop yields to climate variability in key case study sites using AquaCrop simulations parameterised based on input (agronomic practices, soil conditions, etc) from smallholder farmers. [C] We have implemented community-based hydro-climatological monitoring in several case study "revenue villages" (panchayats) in the Nainital District of Uttarakhand. The purpose of this is not only to increase availability of meteorological data, but also has the aspiration of, over time, leading to enhanced quantitative awareness of present climate variability and potential future conditions (as projected by RCMs). Next steps in our work will include: 1) future crop yield simulations driven by "perturbation" of synthetic time-series using "change factors from the CORDEX-SA MME; 2) stakeholder dialogues critically evaluating potential strategies at the grassroots (implementation) level to mitigate impacts of climate variability and change on crop yields.

Enhancement of global flood damage assessments using building material based vulnerability curves

NASA Astrophysics Data System (ADS)

Englhardt, Johanna; de Ruiter, Marleen; de Moel, Hans; Aerts, Jeroen

2017-04-01

This study discusses the development of an enhanced approach for flood damage and risk assessments using vulnerability curves that are based on building material information. The approach draws upon common practices in earthquake vulnerability assessments, and is an alternative for land-use or building occupancy approach in flood risk assessment models. The approach is of particular importance for studies where there is a large variation in building material, such as large scale studies or studies in developing countries. A case study of Ethiopia is used to demonstrate the impact of the different methodological approaches on direct damage assessments due to flooding. Generally, flood damage assessments use damage curves for different land-use or occupancy types (i.e. urban or residential and commercial classes). However, these categories do not necessarily relate directly to vulnerability of damage by flood waters. For this, the construction type and building material may be more important, as is used in earthquake risk assessments. For this study, we use building material classification data of the PAGER1 project to define new building material based vulnerability classes for flood damage. This approach will be compared to the widely applied land-use based vulnerability curves such as used by De Moel et al. (2011). The case of Ethiopia demonstrates and compares the feasibility of this novel flood vulnerability method on a country level which holds the potential to be scaled up to a global level. The study shows that flood vulnerability based on building material also allows for better differentiation between flood damage in urban and rural settings, opening doors to better link to poverty studies when such exposure data is available. Furthermore, this new approach paves the road to the enhancement of multi-risk assessments as the method enables the comparison of vulnerability across different natural hazard types that also use material-based vulnerability curves. Finally, this approach allows for more accuracy in estimating losses as a result of direct damages. 1 http://earthquake.usgs.gov/data/pager/

Improved Holistic Analysis of Rayleigh Waves for Single- and Multi-Offset Data: Joint Inversion of Rayleigh-Wave Particle Motion and Vertical- and Radial-Component Velocity Spectra

NASA Astrophysics Data System (ADS)

Dal Moro, Giancarlo; Moustafa, Sayed S. R.; Al-Arifi, Nassir S.

2018-01-01

Rayleigh waves often propagate according to complex mode excitation so that the proper identification and separation of specific modes can be quite difficult or, in some cases, just impossible. Furthermore, the analysis of a single component (i.e., an inversion procedure based on just one objective function) necessarily prevents solving the problems related to the non-uniqueness of the solution. To overcome these issues and define a holistic analysis of Rayleigh waves, we implemented a procedure to acquire data that are useful to define and efficiently invert the three objective functions defined from the three following "objects": the velocity spectra of the vertical- and radial-components and the Rayleigh-wave particle motion (RPM) frequency-offset data. Two possible implementations are presented. In the first case we consider classical multi-offset (and multi-component) data, while in a second possible approach we exploit the data recorded by a single three-component geophone at a fixed offset from the source. Given the simple field procedures, the method could be particularly useful for the unambiguous geotechnical exploration of large areas, where more complex acquisition procedures, based on the joint acquisition of Rayleigh and Love waves, would not be economically viable. After illustrating the different kinds of data acquisition and the data processing, the results of the proposed methodology are illustrated in a case study. Finally, a series of theoretical and practical aspects are discussed to clarify some issues involved in the overall procedure (data acquisition and processing).

The need of a multi-actor perspective to understand expectations from virtual presence: managing elderly homecare informatics.

PubMed

Mettler, Tobias; Vimarlund, Vivian

2011-12-01

Different studies have analysed a wide range of use cases and scenarios for using IT-based services in homecare settings for elderly people. In most instances, the impact of such services has been studied using a one-dimensional approach, either focusing on the benefits for the patient or health service provider. The objective of this contribution is to explore a model for identifying and understanding outcomes of IT-based homecare services from a multi-actor perspective. In order to better understand the state of the art in homecare informatics, we conducted a literature review. We use experiences from previous research in the area of informatics to develop the proposed model. The proposed model consists of four core activities 'identify involved actors', 'understand consequences', 'clarify contingencies', 'take corrective actions', and one additional activity 'brainstorming IT use'. The primary goal of innovating organisations, processes and services in homecare informatics today, is to offer continued care, better decision support both to practitioners and patients, as well as effective distribution of resources. A multi-actor analysis perspective is needed to understand utility determination for the involved stakeholders.

Multi-metric calibration of hydrological model to capture overall flow regimes

NASA Astrophysics Data System (ADS)

Zhang, Yongyong; Shao, Quanxi; Zhang, Shifeng; Zhai, Xiaoyan; She, Dunxian

2016-08-01

Flow regimes (e.g., magnitude, frequency, variation, duration, timing and rating of change) play a critical role in water supply and flood control, environmental processes, as well as biodiversity and life history patterns in the aquatic ecosystem. The traditional flow magnitude-oriented calibration of hydrological model was usually inadequate to well capture all the characteristics of observed flow regimes. In this study, we simulated multiple flow regime metrics simultaneously by coupling a distributed hydrological model with an equally weighted multi-objective optimization algorithm. Two headwater watersheds in the arid Hexi Corridor were selected for the case study. Sixteen metrics were selected as optimization objectives, which could represent the major characteristics of flow regimes. Model performance was compared with that of the single objective calibration. Results showed that most metrics were better simulated by the multi-objective approach than those of the single objective calibration, especially the low and high flow magnitudes, frequency and variation, duration, maximum flow timing and rating. However, the model performance of middle flow magnitude was not significantly improved because this metric was usually well captured by single objective calibration. The timing of minimum flow was poorly predicted by both the multi-metric and single calibrations due to the uncertainties in model structure and input data. The sensitive parameter values of the hydrological model changed remarkably and the simulated hydrological processes by the multi-metric calibration became more reliable, because more flow characteristics were considered. The study is expected to provide more detailed flow information by hydrological simulation for the integrated water resources management, and to improve the simulation performances of overall flow regimes.

Sustainable Remediation of Legacy Mine Drainage: A Case Study of the Flight 93 National Memorial.

PubMed

Emili, Lisa A; Pizarchik, Joseph; Mahan, Carolyn G

2016-03-01

Pollution from mining activities is a global environmental concern, not limited to areas of current resource extraction, but including a broader geographic area of historic (legacy) and abandoned mines. The pollution of surface waters from acid mine drainage is a persistent problem and requires a holistic and sustainable approach to addressing the spatial and temporal complexity of mining-specific problems. In this paper, we focus on the environmental, socio-economic, and legal challenges associated with the concurrent activities to remediate a coal mine site and to develop a national memorial following a catastrophic event. We provide a conceptual construct of a socio-ecological system defined at several spatial, temporal, and organizational scales and a critical synthesis of the technical and social learning processes necessary to achieving sustainable environmental remediation. Our case study is an example of a multi-disciplinary management approach, whereby collaborative interaction of stakeholders, the emergence of functional linkages for information exchange, and mediation led to scientifically informed decision making, creative management solutions, and ultimately environmental policy change.

Projects without a purpose: Why a top down strategy to resilience matters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kingery, Kristine M.; Fowler, Kimberly M.; Harrove

Energy resilience is a key focus of the current administration and Department of Defense (DoD) leaders, and is in the title of every energy conference session. Most case studies and success stories focus on resilience projects hardening systems or microgriding critical infrastructure. Some case studies focus on unique financing approaches to bring private sector innovation and increased investment to military installations. Many times, what initially look like innovative resilience projects, end as isolated systems or stranded infrastructure. This article will explore how the DoD can make greater strides advancing resilience objectives and ultimately developing projects that support installation mission readinessmore » by first focusing on top down strategies. The Army established energy and water security/resilience requirements, developed a comprehensive measurement framework, is evolving integrated planning approaches in collaboration with local communities, and is supporting project development activities across third-party and appropriated programs. The Army’s multi-year strategic energy and water security planning activities can provide helpful guidance to both the lifecycle of programs or individual projects, and ensure resilience projects both have and achieve a purpose.« less

Nature's Medicines: Traditional Knowledge and Intellectual Property Management. Case Studies from the National Institutes of Health (NIH), USA

PubMed Central

Gupta, Ranjan; Gabrielsen, Bjarne; Ferguson, Steven M.

2009-01-01

With the emergence and re-emergence of infectious diseases and development of multi-drug resistance, there is a dire need to find newer cures and to produce more drugs and vaccines in the pipeline. To meet these increasing demands biomedical researchers and pharmaceutical companies are combining advanced methods of drug discovery, such as combinatorial chemistry, high-throughput screening and genomics, with conventional approaches using natural products and traditional knowledge. However, such approaches require much international cooperation and understanding of international laws and conventions as well as local customs and traditions. This article reviews the forty years of cumulative experience at the National Institutes of Health (initiated by the National Cancer Institute) in natural products drug discovery. It presents (1) three major cooperative programs (2) the legal mechanisms for cooperation and (3) illustrative case studies from these programs. We hope that these discussions and our lessons learned would be helpful to others seeking to develop their own models of cooperation for the benefit of global health. PMID:16475917

A fuzzy multi-objective linear programming approach for integrated sheep farming and wildlife in land management decisions: a case study in the Patagonian rangelands

NASA Astrophysics Data System (ADS)

Metternicht, Graciela; Blanco, Paula; del Valle, Hector; Laterra, Pedro; Hardtke, Leonardo; Bouza, Pablo

2015-04-01

Wildlife is part of the Patagonian rangelands sheep farming environment, with the potential of providing extra revenue to livestock owners. As sheep farming became less profitable, farmers and ranchers could focus on sustainable wildlife harvesting. It has been argued that sustainable wildlife harvesting is ecologically one of the most rational forms of land use because of its potential to provide multiple products of high value, while reducing pressure on ecosystems. The guanaco (Lama guanicoe) is the most conspicuous wild ungulate of Patagonia. Guanaco ?bre, meat, pelts and hides are economically valuable and have the potential to be used within the present Patagonian context of production systems. Guanaco populations in South America, including Patagonia, have experienced a sustained decline. Causes for this decline are related to habitat alteration, competition for forage with sheep, and lack of reasonable management plans to develop livelihoods for ranchers. In this study we propose an approach to explicitly determinate optimal stocking rates based on trade-offs between guanaco density and livestock grazing intensity on rangelands. The focus of our research is on finding optimal sheep stocking rates at paddock level, to ensure the highest production outputs while: a) meeting requirements of sustainable conservation of guanacos over their minimum viable population; b) maximizing soil carbon sequestration, and c) minimizing soil erosion. In this way, determination of optimal stocking rate in rangelands becomes a multi-objective optimization problem that can be addressed using a Fuzzy Multi-Objective Linear Programming (MOLP) approach. Basically, this approach converts multi-objective problems into single-objective optimizations, by introducing a set of objective weights. Objectives are represented using fuzzy set theory and fuzzy memberships, enabling each objective function to adopt a value between 0 and 1. Each objective function indicates the satisfaction of the decision maker towards the respective objective. Fuzzy logic is closer to intuitive thinking used by decision makers, making it a user-friendly approach for them to select alternatives. The proposed approach was applied in a study area of approximately 40,000 hectares in semiarid Patagonian rangelands where extensive, continuous sheep grazing for wool production is the main land use. Multi- and hyper-spectral data were combined with ancillary data within a GIS environment, and used to derive maps of forage production, guanacos density, soil organic carbon and soil erosion. Different scenarios, with different objectives weights were evaluated. Results showed that under scenario 1, where livestock production is predicted to have the highest values, guanaco numbers decrease substantially as well as soil carbon sequestration, and soil erosion exhibit the highest values. On the other hand, when guanaco population is prioritized, livestock production has the lowest value. A compromise alternative resulted from a scenario where variables are assigned same weight; under this condition, high livestock production is predicted, while conservation of guanaco population is sustainable, carbon sequestration is maximized and soil erosion minimized.

Phase aided 3D imaging and modeling: dedicated systems and case studies

NASA Astrophysics Data System (ADS)

Yin, Yongkai; He, Dong; Liu, Zeyi; Liu, Xiaoli; Peng, Xiang

2014-05-01

Dedicated prototype systems for 3D imaging and modeling (3DIM) are presented. The 3D imaging systems are based on the principle of phase-aided active stereo, which have been developed in our laboratory over the past few years. The reported 3D imaging prototypes range from single 3D sensor to a kind of optical measurement network composed of multiple node 3D-sensors. To enable these 3D imaging systems, we briefly discuss the corresponding calibration techniques for both single sensor and multi-sensor optical measurement network, allowing good performance of the 3DIM prototype systems in terms of measurement accuracy and repeatability. Furthermore, two case studies including the generation of high quality color model of movable cultural heritage and photo booth from body scanning are presented to demonstrate our approach.

Automated Interval velocity picking for Atlantic Multi-Channel Seismic Data

NASA Astrophysics Data System (ADS)

Singh, Vishwajit

2016-04-01

This paper described the challenge in developing and testing a fully automated routine for measuring interval velocities from multi-channel seismic data. Various approaches are employed for generating an interactive algorithm picking interval velocity for continuous 1000-5000 normal moveout (NMO) corrected gather and replacing the interpreter's effort for manual picking the coherent reflections. The detailed steps and pitfalls for picking the interval velocities from seismic reflection time measurements are describe in these approaches. Key ingredients these approaches utilized for velocity analysis stage are semblance grid and starting model of interval velocity. Basin-Hopping optimization is employed for convergence of the misfit function toward local minima. SLiding-Overlapping Window (SLOW) algorithm are designed to mitigate the non-linearity and ill- possessedness of root-mean-square velocity. Synthetic data case studies addresses the performance of the velocity picker generating models perfectly fitting the semblance peaks. A similar linear relationship between average depth and reflection time for synthetic model and estimated models proposed picked interval velocities as the starting model for the full waveform inversion to project more accurate velocity structure of the subsurface. The challenges can be categorized as (1) building accurate starting model for projecting more accurate velocity structure of the subsurface, (2) improving the computational cost of algorithm by pre-calculating semblance grid to make auto picking more feasible.

Potential slab avalanche release area identification from estimated winter terrain: a multi-scale, fuzzy logic approach

NASA Astrophysics Data System (ADS)

Veitinger, Jochen; Purves, Ross Stuart; Sovilla, Betty

2016-10-01

Avalanche hazard assessment requires a very precise estimation of the release area, which still depends, to a large extent, on expert judgement of avalanche specialists. Therefore, a new algorithm for automated identification of potential avalanche release areas was developed. It overcomes some of the limitations of previous tools, which are currently not often applied in hazard mitigation practice. By introducing a multi-scale roughness parameter, fine-scale topography and its attenuation under snow influence is captured. This allows the assessment of snow influence on terrain morphology and, consequently, potential release area size and location. The integration of a wind shelter index enables the user to define release area scenarios as a function of the prevailing wind direction or single storm events. A case study illustrates the practical usefulness of this approach for the definition of release area scenarios under varying snow cover and wind conditions. A validation with historical data demonstrated an improved estimation of avalanche release areas. Our method outperforms a slope-based approach, in particular for more frequent avalanches; however, the application of the algorithm as a forecasting tool remains limited, as snowpack stability is not integrated. Future research activity should therefore focus on the coupling of the algorithm with snowpack conditions.

A cloud model based multi-attribute decision making approach for selection and evaluation of groundwater management schemes

NASA Astrophysics Data System (ADS)

Lu, Hongwei; Ren, Lixia; Chen, Yizhong; Tian, Peipei; Liu, Jia

2017-12-01

Due to the uncertainty (i.e., fuzziness, stochasticity and imprecision) existed simultaneously during the process for groundwater remediation, the accuracy of ranking results obtained by the traditional methods has been limited. This paper proposes a cloud model based multi-attribute decision making framework (CM-MADM) with Monte Carlo for the contaminated-groundwater remediation strategies selection. The cloud model is used to handle imprecise numerical quantities, which can describe the fuzziness and stochasticity of the information fully and precisely. In the proposed approach, the contaminated concentrations are aggregated via the backward cloud generator and the weights of attributes are calculated by employing the weight cloud module. A case study on the remedial alternative selection for a contaminated site suffering from a 1,1,1-trichloroethylene leakage problem in Shanghai, China is conducted to illustrate the efficiency and applicability of the developed approach. Totally, an attribute system which consists of ten attributes were used for evaluating each alternative through the developed method under uncertainty, including daily total pumping rate, total cost and cloud model based health risk. Results indicated that A14 was evaluated to be the most preferred alternative for the 5-year, A5 for the 10-year, A4 for the 15-year and A6 for the 20-year remediation.

Multi-normed spaces based on non-discrete measures and their tensor products

NASA Astrophysics Data System (ADS)

Helemskii, A. Ya.

2018-04-01

Lambert discovered a new type of structures situated, in a sense, between normed spaces and abstract operator spaces. His definition was based on the notion of amplifying a normed space by means of the spaces \\ell_2^n. Later, several mathematicians studied more general structures (`p-multi- normed spaces') introduced by means of the spaces \\ell_p^n, 1≤ p≤∞. We pass from \\ell_p to L_p(X,μ) with an arbitrary measure. This becomes possible in the framework of the non- coordinate approach to the notion of amplification. In the case of a discrete counting measure, this approach is equivalent to the approach in the papers mentioned. Two categories arise. One consists of amplifications by means of an arbitrary normed space, and the other consists of p-convex amplifications by means of L_p(X,μ). Each of them has its own tensor product of objects (the existence of each product is proved by a separate explicit construction). As a final result, we show that the `p-convex' tensor product has an especially transparent form for the minimal L_p-amplifications of L_q-spaces, where q is conjugate to p. Namely, tensoring L_q(Y,ν) and L_q(Z,λ), we obtain L_q(Y× Z, ν×λ).

A Multi-Family Group Intervention for Adolescent Depression: The BEST MOOD Program.

PubMed

Poole, Lucinda A; Lewis, Andrew J; Toumbourou, John W; Knight, Tess; Bertino, Melanie D; Pryor, Reima

2017-06-01

Depression is the most common mental disorder for young people, and it is associated with educational underachievement, self-harm, and suicidality. Current psychological therapies for adolescent depression are usually focused only on individual-level change and often neglect family or contextual influences. The efficacy of interventions may be enhanced with a broader therapeutic focus on family factors such as communication, conflict, support, and cohesion. This article describes a structured multi-family group approach to the treatment of adolescent depression: Behaviour Exchange Systems Therapy for adolescent depression (BEST MOOD). BEST MOOD is a manualized intervention that is designed to address both individual and family factors in the treatment of adolescent depression. BEST MOOD adopts a family systems approach that also incorporates psychoeducation and elements of attachment theories. The program consists of eight multifamily group therapy sessions delivered over 2 hours per week, where parents attend the first four sessions and young people and siblings join from week 5. The program design is specifically aimed to engage youth who are initially resistant to treatment and to optimize youth and family mental health outcomes. This article presents an overview of the theoretical model, session content, and evaluations to date, and provides a case study to illustrate the approach. © 2016 Family Process Institute.

Applying a new theory to smoking cessation: case of multi-theory model (MTM) for health behavior change.

PubMed

Sharma, Manoj; Khubchandani, Jagdish; Nahar, Vinayak K

2017-01-01

Background: Smoking continues to be a public health problem worldwide. Smoking and tobacco use are associated with cardiovascular diseases that include coronary heart disease, atherosclerosis, cerebrovascular disease, and abdominal aortic aneurysm. Programs for quitting smoking have played a significant role in reduction of smoking in the United States. The smoking cessation interventions include counseling, nicotine replacement therapy, buproprion therapy, and varenicline therapy. The success rates with each of these approaches vary with clear need for improvement. Moreover, there is a need for a robust theory that can guide smoking cessation counseling interventions and increase the success rates. A fourth generation approach using multi-theory model (MTM) of health behavior change is introduced in this article for smoking cessation. An approach for developing and evaluating an intervention for smoking cessation is presented along with a measurement tool. Methods: A literature review reifying the MTM of health behavior change for smoking cessation has been presented. An instrument designed to measure constructs of MTM and associated smoking cessation behavior has been developed. Results: The instrument developed is available for validation, reliability and prediction study pertaining to smoking cessation. The intervention is available for testing in a randomized control trial involving smokers. Conclusion: MTM is a robust theory that holds promise for testing and application to smoking cessation.

Indoor positioning using differential Wi-Fi lateration

NASA Astrophysics Data System (ADS)

Retscher, Guenther; Tatschl, Thomas

2017-12-01

For Wi-Fi positioning usually location fingerprinting or (tri)lateration are employed whereby the received signal strengths (RSSs) of the surrounding Wi-Fi Access Points (APs) are scanned on the mobile devices and used to perform localization. Within the scope of this study, the position of a mobile user is determined on the basis of lateration. Two new differential approaches are developed and compared to two common models, i.e., the one-slope and multi-wall model, for the conversion of the measured RSS of the Wi-Fi signals into ranges. The two novel methods are termed DWi-Fi as they are derived either from the well-known DGPS or VLBI positioning principles. They make use of a network of reference stations deployed in the area of interest. From continuous RSS observations on these reference stations correction parameters are derived and applied by the user in real-time. This approach leads to a reduced influence of temporal and spatial variations and various propagation effects on the positioning result. In practical use cases conducted in a multi-storey office building with three different smartphones, it is proven that the two DWi-Fi approaches outperform the common models as static positioning yielded to position errors of about 5 m in average under good spatial conditions.

A Multi-Agent System Architecture for Sensor Networks

PubMed Central

Fuentes-Fernández, Rubén; Guijarro, María; Pajares, Gonzalo

2009-01-01

The design of the control systems for sensor networks presents important challenges. Besides the traditional problems about how to process the sensor data to obtain the target information, engineers need to consider additional aspects such as the heterogeneity and high number of sensors, and the flexibility of these networks regarding topologies and the sensors in them. Although there are partial approaches for resolving these issues, their integration relies on ad hoc solutions requiring important development efforts. In order to provide an effective approach for this integration, this paper proposes an architecture based on the multi-agent system paradigm with a clear separation of concerns. The architecture considers sensors as devices used by an upper layer of manager agents. These agents are able to communicate and negotiate services to achieve the required functionality. Activities are organized according to roles related with the different aspects to integrate, mainly sensor management, data processing, communication and adaptation to changes in the available devices and their capabilities. This organization largely isolates and decouples the data management from the changing network, while encouraging reuse of solutions. The use of the architecture is facilitated by a specific modelling language developed through metamodelling. A case study concerning a generic distributed system for fire fighting illustrates the approach and the comparison with related work. PMID:22303172

A multi-agent system architecture for sensor networks.

PubMed

Fuentes-Fernández, Rubén; Guijarro, María; Pajares, Gonzalo

2009-01-01

The design of the control systems for sensor networks presents important challenges. Besides the traditional problems about how to process the sensor data to obtain the target information, engineers need to consider additional aspects such as the heterogeneity and high number of sensors, and the flexibility of these networks regarding topologies and the sensors in them. Although there are partial approaches for resolving these issues, their integration relies on ad hoc solutions requiring important development efforts. In order to provide an effective approach for this integration, this paper proposes an architecture based on the multi-agent system paradigm with a clear separation of concerns. The architecture considers sensors as devices used by an upper layer of manager agents. These agents are able to communicate and negotiate services to achieve the required functionality. Activities are organized according to roles related with the different aspects to integrate, mainly sensor management, data processing, communication and adaptation to changes in the available devices and their capabilities. This organization largely isolates and decouples the data management from the changing network, while encouraging reuse of solutions. The use of the architecture is facilitated by a specific modelling language developed through metamodelling. A case study concerning a generic distributed system for fire fighting illustrates the approach and the comparison with related work.

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

NASA Astrophysics Data System (ADS)

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.

Multi-scale simulation of plant stem reinforcement by brachysclereids: A case study in apple fruit peduncles.

PubMed

Horbens, Melanie; Branke, Dominik; Gärtner, Roland; Voigt, Axel; Stenger, Florian; Neinhuis, Christoph

2015-10-01

Sclereid formation in addition to or in gaps of fragmented fibre rings is common in dicotyledonous plant stems. Whether this sclereid formation is force-triggered remains open so far. In fruit peduncles of several Malus species as modified plant stems, for example, the persistent fibre ring is displaced to the centre by formation of cortex parenchyma during growth. Parenchyma cells subsequently differentiate into an additional layer of brachysclereids, previously interpreted as an adaptation to continuously rising fruit loads. The present study pursues a multi-scale numerical modelling approach, to verify the important effect for different cellular architectures in both sclerenchyma categories on the stiffness of these tissues and the entire peduncle. First, different material properties are simulated analogue to plant tissues on the basis of three cell types. A regular three-dimensional and a random Voronoi microstructure combined with various mechanical cell wall parameters are applied. Using homogenisation simulations based on HILL's principle, numerical calculations predict a lower effective homogenised tissue stiffness of isodiametric brachysclereids compared to those of fibres, confirming experimentally obtained data from Malus fruit peduncles. Furthermore, a curved peduncle model with a complex arrangement of different material layers is generated. Diverse material sets are tested under three representative loadings, using an adaptive diffuse domain approach (AMDiS). The model explains the function of sclereids as considerable contributors to the stiffness against bending and tensile deformations, as well as torsion, especially in consequence of superimposed load conditions in the case of a curved plant stem. Copyright © 2015 Elsevier Inc. All rights reserved.

The Role of Science in Advising the Decision Making Process: A Pathway for Building Effective Climate Change Mitigation Policies in Mexico at the Local Level

PubMed Central

Barraza, Roberto; Velazquez-Angulo, Gilberto; Flores-Tavizón, Edith; Romero-González, Jaime; Huertas-Cardozo, José Ignacio

2016-01-01

This study examines a pathway for building urban climate change mitigation policies by presenting a multi-dimensional and transdisciplinary approach in which technical, economic, environmental, social, and political dimensions interact. Now, more than ever, the gap between science and policymaking needs to be bridged; this will enable judicious choices to be made in regarding energy and climate change mitigation strategies, leading to positive social impacts, in particular for the populations at-risk at the local level. Through a case study in Juarez, Chihuahua, Mexico, we propose a multidimensional and transdisciplinary approach with the role of scientist as policy advisers to improve the role of science in decision-making on mitigation policies at the local level in Mexico. PMID:27128933

An evaluation of multiple trauma severity indices created by different index development strategies.

PubMed

Gustafson, D H; Fryback, D G; Rose, J H; Prokop, C T; Detmer, D E; Rossmeissl, J C; Taylor, C M; Alemi, F; Carnazzo, A J

1983-07-01

Evaluation of the effectiveness of emergency trauma care systems is complicated by the need to adjust for the widely variable case mix found in trauma patient populations. Several strategies have been advanced to construct the severity indices that can control for these population differences. This article describes a validity and reliability comparison of trauma severity indices developed under three different approaches: 1) use of a multi-attribute utility (MAU) model; 2) an actuarial approach relying on empirical data bases; and 3) an "ad hoc" approach. Seven criteria were identified to serve as standards of comparison for four different indices. The study's findings indicate that the index developed using the MAU theory approach associates most closely with physician judgments of trauma severity. When correlated with a morbidity outcome measure, the MAU-based index shows higher levels of agreement than the other indices. The index development approach based on the principles of MAU theory has several advantages and it appears to be a powerful tool in the creation of effective severity indices.

NASA Earth Science Partnerships - A Multi-Level Approach to Effectively Collaborating with Communities and Organizations to Utilize Earth Science Data for Societal Benefit

NASA Astrophysics Data System (ADS)

Favors, J.

2016-12-01

NASA's Earth Science Division (ESD) seeks to develop a scientific understanding of the Earth as a dynamic, integrated system of diverse components that interact in complex ways - analogous to the human body. The Division approaches this goal through a coordinated series of satellite and airborne missions, sponsored basic and applied research, technology development, and science education. Integral to this approach are strong collaborations and partnerships with a spectrum of organizations that produce substantive benefit to communities - both locally and globally. This presentation will showcase various ways ESD approaches partnering and will highlight best practices, challenges, and provide case studies related to rapid partnerships, co-location of scientists and end-user communities, capacity building, and ESD's new Partnerships Program which is built around taking an innovative approach to partnering that fosters interdisplinary teaming & co-production of knowledge to broaden the applicability of Earth observations and answer new, big questions for partners and NASA, alike.

Soil moisture mapping using Sentinel 1 images: the proposed approach and its preliminary validation carried out in view of an operational product

NASA Astrophysics Data System (ADS)

Paloscia, S.; Pettinato, S.; Santi, E.; Pierdicca, N.; Pulvirenti, L.; Notarnicola, C.; Pace, G.; Reppucci, A.

2011-11-01

The main objective of this research is to develop, test and validate a soil moisture (SMC)) algorithm for the GMES Sentinel-1 characteristics, within the framework of an ESA project. The SMC product, to be generated from Sentinel-1 data, requires an algorithm able to process operationally in near-real-time and deliver the product to the GMES services within 3 hours from observations. Two different complementary approaches have been proposed: an Artificial Neural Network (ANN), which represented the best compromise between retrieval accuracy and processing time, thus allowing compliance with the timeliness requirements and a Bayesian Multi-temporal approach, allowing an increase of the retrieval accuracy, especially in case where little ancillary data are available, at the cost of computational efficiency, taking advantage of the frequent revisit time achieved by Sentinel-1. The algorithm was validated in several test areas in Italy, US and Australia, and finally in Spain with a 'blind' validation. The Multi-temporal Bayesian algorithm was validated in Central Italy. The validation results are in all cases very much in line with the requirements. However, the blind validation results were penalized by the availability of only VV polarization SAR images and MODIS lowresolution NDVI, although the RMS is slightly > 4%.

Leadership Development Institute: A California Community College Multi-College District Case Study

ERIC Educational Resources Information Center

Leon, Bianca R.

2016-01-01

The purpose of this study is to examine a community college district Grow Your Own (GYO) leadership program in the Western United States, the Multi College Leadership Development Institute (MCLDI). The MCLDI was developed in-house for a multi-campus community college district and offered to interested employees at all position levels with the…

Fluxomics - connecting 'omics analysis and phenotypes.

PubMed

Winter, Gal; Krömer, Jens O

2013-07-01

In our modern 'omics era, metabolic flux analysis (fluxomics) represents the physiological counterpart of its siblings transcriptomics, proteomics and metabolomics. Fluxomics integrates in vivo measurements of metabolic fluxes with stoichiometric network models to allow the determination of absolute flux through large networks of the central carbon metabolism. There are many approaches to implement fluxomics including flux balance analysis (FBA), (13) C fluxomics and (13) C-constrained FBA as well as many experimental settings for flux measurement including dynamic, stationary and semi-stationary. Here we outline the principles of the different approaches and their relative advantages. We demonstrate the unique contribution of flux analysis for phenotype elucidation using a thoroughly studied metabolic reaction as a case study, the microbial aerobic/anaerobic shift, highlighting the importance of flux analysis as a single layer of data as well as interlaced in multi-omics studies. © 2012 John Wiley & Sons Ltd and Society for Applied Microbiology.

Ab initio calculation of resonant Raman intensities of transition metal dichalcogenides

NASA Astrophysics Data System (ADS)

Miranda, Henrique; Reichardt, Sven; Molina-Sanchez, Alejandro; Wirtz, Ludger

Raman spectroscopy is used to characterize optical and vibrational properties of materials. Its computational simulation is important for the interpretation of experimental results. Two approaches are the bond polarizability model and density functional perturbation theory. However, both are known to not capture resonance effects. These resonances and quantum interference effects are important to correctly reproduce the intensities as a function of laser energy as, e.g., reported for the case of multi-layer MoTe21.We present two fully ab initio approaches that overcome this limitation. In the first, we calculate finite difference derivatives of the dielectric susceptibility with the phonon displacements2. In the second we calculate electron-light and electron-phonon matrix elements from density functional theory and use them to evaluate expressions for the Raman intensity derived from time-dependent perturbation theory. These expressions are implemented in a computer code that performs the calculations as a post-processing step. We compare both methods and study the case of triple-layer MoTe2. Luxembourg National Research Fund (FNR).

GLISTRboost: Combining Multimodal MRI Segmentation, Registration, and Biophysical Tumor Growth Modeling with Gradient Boosting Machines for Glioma Segmentation.

PubMed

Bakas, Spyridon; Zeng, Ke; Sotiras, Aristeidis; Rathore, Saima; Akbari, Hamed; Gaonkar, Bilwaj; Rozycki, Martin; Pati, Sarthak; Davatzikos, Christos

2016-01-01

We present an approach for segmenting low- and high-grade gliomas in multimodal magnetic resonance imaging volumes. The proposed approach is based on a hybrid generative-discriminative model. Firstly, a generative approach based on an Expectation-Maximization framework that incorporates a glioma growth model is used to segment the brain scans into tumor, as well as healthy tissue labels. Secondly, a gradient boosting multi-class classification scheme is used to refine tumor labels based on information from multiple patients. Lastly, a probabilistic Bayesian strategy is employed to further refine and finalize the tumor segmentation based on patient-specific intensity statistics from the multiple modalities. We evaluated our approach in 186 cases during the training phase of the BRAin Tumor Segmentation (BRATS) 2015 challenge and report promising results. During the testing phase, the algorithm was additionally evaluated in 53 unseen cases, achieving the best performance among the competing methods.

Singular value decomposition based impulsive noise reduction in multi-frequency phase-sensitive demodulation of electrical impedance tomography

NASA Astrophysics Data System (ADS)

Hao, Zhenhua; Cui, Ziqiang; Yue, Shihong; Wang, Huaxiang

2018-06-01

As an important means in electrical impedance tomography (EIT), multi-frequency phase-sensitive demodulation (PSD) can be viewed as a matched filter for measurement signals and as an optimal linear filter in the case of Gaussian-type noise. However, the additive noise usually possesses impulsive noise characteristics, so it is a challenging task to reduce the impulsive noise in multi-frequency PSD effectively. In this paper, an approach for impulsive noise reduction in multi-frequency PSD of EIT is presented. Instead of linear filters, a singular value decomposition filter is employed as the pre-stage filtering module prior to PSD, which has advantages of zero phase shift, little distortion, and a high signal-to-noise ratio (SNR) in digital signal processing. Simulation and experimental results demonstrated that the proposed method can effectively eliminate the influence of impulsive noise in multi-frequency PSD, and it was capable of achieving a higher SNR and smaller demodulation error.

Carotene Degradation and Isomerization during Thermal Processing: A Review on the Kinetic Aspects.

PubMed

Colle, Ines J P; Lemmens, Lien; Knockaert, Griet; Van Loey, Ann; Hendrickx, Marc

2016-08-17

Kinetic models are important tools for process design and optimization to balance desired and undesired reactions taking place in complex food systems during food processing and preservation. This review covers the state of the art on kinetic models available to describe heat-induced conversion of carotenoids, in particular lycopene and β-carotene. First, relevant properties of these carotenoids are discussed. Second, some general aspects of kinetic modeling are introduced, including both empirical single-response modeling and mechanism-based multi-response modeling. The merits of multi-response modeling to simultaneously describe carotene degradation and isomerization are demonstrated. The future challenge in this research field lies in the extension of the current multi-response models to better approach the real reaction pathway and in the integration of kinetic models with mass transfer models in case of reaction in multi-phase food systems.

Multi-Sensor Characterization of the Boreal Forest: Initial Findings

NASA Technical Reports Server (NTRS)

Reith, Ernest; Roberts, Dar A.; Prentiss, Dylan

2001-01-01

Results are presented in an initial apriori knowledge approach toward using complementary multi-sensor multi-temporal imagery in characterizing vegetated landscapes over a site in the Boreal Ecosystem-Atmosphere Study (BOREAS). Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and Airborne Synthetic Aperture Radar (AIRSAR) data were segmented using multiple endmember spectral mixture analysis and binary decision tree approaches. Individual date/sensor land cover maps had overall accuracies between 55.0% - 69.8%. The best eight land cover layers from all dates and sensors correctly characterized 79.3% of the cover types. An overlay approach was used to create a final land cover map. An overall accuracy of 71.3% was achieved in this multi-sensor approach, a 1.5% improvement over our most accurate single scene technique, but 8% less than the original input. Black spruce was evaluated to be particularly undermapped in the final map possibly because it was also contained within jack pine and muskeg land coverages.

A WENO-Limited, ADER-DT, Finite-Volume Scheme for Efficient, Robust, and Communication-Avoiding Multi-Dimensional Transport

DOE Office of Scientific and Technical Information (OSTI.GOV)

Norman, Matthew R

2014-01-01

The novel ADER-DT time discretization is applied to two-dimensional transport in a quadrature-free, WENO- and FCT-limited, Finite-Volume context. Emphasis is placed on (1) the serial and parallel computational properties of ADER-DT and this framework and (2) the flexibility of ADER-DT and this framework in efficiently balancing accuracy with other constraints important to transport applications. This study demonstrates a range of choices for the user when approaching their specific application while maintaining good parallel properties. In this method, genuine multi-dimensionality, single-step and single-stage time stepping, strict positivity, and a flexible range of limiting are all achieved with only one parallel synchronizationmore » and data exchange per time step. In terms of parallel data transfers per simulated time interval, this improves upon multi-stage time stepping and post-hoc filtering techniques such as hyperdiffusion. This method is evaluated with standard transport test cases over a range of limiting options to demonstrate quantitatively and qualitatively what a user should expect when employing this method in their application.« less

Bayesian adaptive bandit-based designs using the Gittins index for multi-armed trials with normally distributed endpoints.

PubMed

Smith, Adam L; Villar, Sofía S

2018-01-01

Adaptive designs for multi-armed clinical trials have become increasingly popular recently because of their potential to shorten development times and to increase patient response. However, developing response-adaptive designs that offer patient-benefit while ensuring the resulting trial provides a statistically rigorous and unbiased comparison of the different treatments included is highly challenging. In this paper, the theory of Multi-Armed Bandit Problems is used to define near optimal adaptive designs in the context of a clinical trial with a normally distributed endpoint with known variance. We report the operating characteristics (type I error, power, bias) and patient-benefit of these approaches and alternative designs using simulation studies based on an ongoing trial. These results are then compared to those recently published in the context of Bernoulli endpoints. Many limitations and advantages are similar in both cases but there are also important differences, specially with respect to type I error control. This paper proposes a simulation-based testing procedure to correct for the observed type I error inflation that bandit-based and adaptive rules can induce.

The Effectiveness of a Multi Sensory Approach in Improving Letter-Sound Correspondence among Mild Intellectual Disabled Students in State of Kuwait

ERIC Educational Resources Information Center

Moustafa, Amr; Ghani, Mohd Zuri

2016-01-01

This research examines the effectiveness of multi sensory approach for the purpose of improving the knowledge on English Letter sound correspondence among mild disabled students in the state of Kuwait. The discussion in this study is based on the multisensory approach that could be applied in the teaching of reading skills as well as phonemic…

Teaching and Learning Science Through Song: Exploring the experiences of students and teachers

NASA Astrophysics Data System (ADS)

Governor, Donna; Hall, Jori; Jackson, David

2013-12-01

This qualitative, multi-case study explored the use of science-content music for teaching and learning in six middle school science classrooms. The researcher sought to understand how teachers made use of content-rich songs for teaching science, how they impacted student engagement and learning, and what the experiences of these teachers and students suggested about using songs for middle school classroom science instruction. Data gathered included three teacher interviews, one classroom observation and a student focus-group discussion from each of six cases. The data from each unit of analysis were examined independently and then synthesized in a multi-case analysis, resulting in a number of merged findings, or assertions, about the experience. The results of this study indicated that teachers used content-rich music to enhance student understanding of concepts in science by developing content-based vocabulary, providing students with alternative examples and explanations of concepts, and as a sense-making experience to help build conceptual understanding. The use of science-content songs engaged students by providing both situational and personal interest, and provided a mnemonic device for remembering key concepts in science. The use of songs has relevance from a constructivist approach as they were used to help students build meaning; from a socio-cultural perspective in terms of student engagement; and from a cognitive viewpoint in that in these cases they helped students make connections in learning. The results of this research have implications for science teachers and the science education community in developing new instructional strategies for the middle school science classroom.

A spatial multi-objective optimization model for sustainable urban wastewater system layout planning.

PubMed

Dong, X; Zeng, S; Chen, J

2012-01-01

Design of a sustainable city has changed the traditional centralized urban wastewater system towards a decentralized or clustering one. Note that there is considerable spatial variability of the factors that affect urban drainage performance including urban catchment characteristics. The potential options are numerous for planning the layout of an urban wastewater system, which are associated with different costs and local environmental impacts. There is thus a need to develop an approach to find the optimal spatial layout for collecting, treating, reusing and discharging the municipal wastewater of a city. In this study, a spatial multi-objective optimization model, called Urban wastewateR system Layout model (URL), was developed. It is solved by a genetic algorithm embedding Monte Carlo sampling and a series of graph algorithms. This model was illustrated by a case study in a newly developing urban area in Beijing, China. Five optimized system layouts were recommended to the local municipality for further detailed design.

Enhancing community based health programs in Iran: a multi-objective location-allocation model.

PubMed

Khodaparasti, S; Maleki, H R; Jahedi, S; Bruni, M E; Beraldi, P

2017-12-01

Community Based Organizations (CBOs) are important health system stakeholders with the mission of addressing the social and economic needs of individuals and groups in a defined geographic area, usually no larger than a county. The access and success efforts of CBOs vary, depending on the integration between health care providers and CBOs but also in relation to the community participation level. To achieve widespread results, it is important to carefully design an efficient network which can serve as a bridge between the community and the health care system. This study addresses this challenge through a location-allocation model that deals with the hierarchical nature of the system explicitly. To reflect social welfare concerns of equity, local accessibility, and efficiency, we develop the model in a multi-objective framework, capturing the ambiguity in the decision makers' aspiration levels through a fuzzy goal programming approach. This study reports the findings for the real case of Shiraz city, Fars province, Iran, obtained by a thorough analysis of the results.

A framework for service enterprise workflow simulation with multi-agents cooperation

NASA Astrophysics Data System (ADS)

Tan, Wenan; Xu, Wei; Yang, Fujun; Xu, Lida; Jiang, Chuanqun

2013-11-01

Process dynamic modelling for service business is the key technique for Service-Oriented information systems and service business management, and the workflow model of business processes is the core part of service systems. Service business workflow simulation is the prevalent approach to be used for analysis of service business process dynamically. Generic method for service business workflow simulation is based on the discrete event queuing theory, which is lack of flexibility and scalability. In this paper, we propose a service workflow-oriented framework for the process simulation of service businesses using multi-agent cooperation to address the above issues. Social rationality of agent is introduced into the proposed framework. Adopting rationality as one social factor for decision-making strategies, a flexible scheduling for activity instances has been implemented. A system prototype has been developed to validate the proposed simulation framework through a business case study.

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

PubMed

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.

Comparison of a traditional with a new approach based on Graph Theory to vulnerability assessment to natural hazards: a study case on a socio-economic complex system

NASA Astrophysics Data System (ADS)

Arosio, Marcello; Martina, Mario L. V.

2017-04-01

The emergent behaviour of the contemporary complex, socio-technical and interconnected society makes the collective risk greater than the sum of the parts and this requires a holistic, systematic and integrated approach. Although there have been major improvements in recent years, there are still some limitation in term of a holistic approach that is able to include the emergent value hidden in the connections between exposed elements and the interactions between the different spheres of the multi-hazards, vulnerability, exposure and resilience. To deal with these challenges it is necessary to consider the connections between the exposed elements (e.g. populations, schools, hospital, etc.) and to quantify the relative importance of the elements and their interconnections (e.g. the need of injured people to go to hospital or children to school). In a system (e.g. road, hospital and ecological network, etc.), or in a System of System (e.g. socio-technical urban service), there are critical elements that, beyond the intrinsic vulnerability, can be characterized by greater or lower vulnerability because of their physical, geographical, cyber or logical connections. To this aim, we propose in this study a comparative analysis between traditional reductionist approach and a new holistic approach to vulnerability assessment to natural hazards. The analysis considers a study case of a socio-economic complex system through an innovative approach based on the properties of graph G=(N,L). A graph consists of two sets N (nodes) and L (links): the nodes represent the single exposed elements (physical, social, environmental, etc.) to a hazard, while the links (or connections) represent the interaction between the elements. The final goal is to illustrate an application of this innovative approach of integrated collective vulnerability assessment.

Evicase: an evidence-based case structuring approach for personalized healthcare.

PubMed

Carmeli, Boaz; Casali, Paolo; Goldbraich, Anna; Goldsteen, Abigail; Kent, Carmel; Licitra, Lisa; Locatelli, Paolo; Restifo, Nicola; Rinott, Ruty; Sini, Elena; Torresani, Michele; Waks, Zeev

2012-01-01

The personalized medicine era stresses a growing need to combine evidence-based medicine with case based reasoning in order to improve the care process. To address this need we suggest a framework to generate multi-tiered statistical structures we call Evicases. Evicase integrates established medical evidence together with patient cases from the bedside. It then uses machine learning algorithms to produce statistical results and aggregators, weighted predictions, and appropriate recommendations. Designed as a stand-alone structure, Evicase can be used for a range of decision support applications including guideline adherence monitoring and personalized prognostic predictions.

Acoustic classification of multiple simultaneous bird species: a multi-instance multi-label approach

Treesearch

F. Briggs; B. Lakshminarayanan; L. Neal; X.Z. Fern; R. Raich; S.F. Hadley; A.S. Hadley; M.G. Betts

2012-01-01

Although field-collected recordings typically contain multiple simultaneously vocalizing birds of different species, acoustic species classification in this setting has received little study so far. This work formulates the problem of classifying the set of species present in an audio recording using the multi-instance multi-label (MIML) framework for machine learning...

Evaluation of Renal Function after Percutaneous Nephrolithotomy-Does the Number of Percutaneous Access Tracts Matter?

PubMed

Gorbachinsky, Ilya; Wood, Kyle; Colaco, Marc; Hemal, Sij; Mettu, Jayadev; Mirzazadeh, Majid; Assimos, Dean G; Gutierrez-Aćeves, Jorge

2016-07-01

Renal function following percutaneous nephrolithotomy has long been a concern to urologists, especially in the setting of multi-tract access. We determined whether the risk of renal injury after multi-tract percutaneous nephrolithotomy was greater than after a single access approach. We retrospectively reviewed the records of 307 consecutive patients treated with percutaneous nephrolithotomy from 2011 to 2012 at Wake Forest Health. Perioperative (99m)Tc-mercaptoacetyltriglycine nuclear renogram parameters along with serum creatinine values were assessed within 1 year of the procedure. Patients were stratified by single access vs multi-access (2 or more). We identified 110 cases in which renography was done before and after percutaneous nephrolithotomy. A total of 74 patients (67.3%) underwent single access percutaneous nephrolithotomy while 36 (32.7%) underwent multi-access percutaneous nephrolithotomy. Serum creatinine did not significantly differ between the 2 cohorts postoperatively (p = 0.09). There was a significant 2.28% decrease in renal function based on mercaptoacetyltriglycine nuclear renogram results after percutaneous nephrolithotomy of the affected kidney in patients with multiple accesses (p <0.01). This relationship was not observed when patients were stratified by multiple comorbidities associated with nephrolithiasis. Multi-access percutaneous nephrolithotomy is associated with a small reduction in the function of the targeted kidney compared to a single access approach. Copyright © 2016 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

A Pareto-based Ensemble with Feature and Instance Selection for Learning from Multi-Class Imbalanced Datasets.

PubMed

Fernández, Alberto; Carmona, Cristobal José; José Del Jesus, María; Herrera, Francisco

2017-09-01

Imbalanced classification is related to those problems that have an uneven distribution among classes. In addition to the former, when instances are located into the overlapped areas, the correct modeling of the problem becomes harder. Current solutions for both issues are often focused on the binary case study, as multi-class datasets require an additional effort to be addressed. In this research, we overcome these problems by carrying out a combination between feature and instance selections. Feature selection will allow simplifying the overlapping areas easing the generation of rules to distinguish among the classes. Selection of instances from all classes will address the imbalance itself by finding the most appropriate class distribution for the learning task, as well as possibly removing noise and difficult borderline examples. For the sake of obtaining an optimal joint set of features and instances, we embedded the searching for both parameters in a Multi-Objective Evolutionary Algorithm, using the C4.5 decision tree as baseline classifier in this wrapper approach. The multi-objective scheme allows taking a double advantage: the search space becomes broader, and we may provide a set of different solutions in order to build an ensemble of classifiers. This proposal has been contrasted versus several state-of-the-art solutions on imbalanced classification showing excellent results in both binary and multi-class problems.

A Bayesian Alternative for Multi-objective Ecohydrological Model Specification

NASA Astrophysics Data System (ADS)

Tang, Y.; Marshall, L. A.; Sharma, A.; Ajami, H.

2015-12-01

Process-based ecohydrological models combine the study of hydrological, physical, biogeochemical and ecological processes of the catchments, which are usually more complex and parametric than conceptual hydrological models. Thus, appropriate calibration objectives and model uncertainty analysis are essential for ecohydrological modeling. In recent years, Bayesian inference has become one of the most popular tools for quantifying the uncertainties in hydrological modeling with the development of Markov Chain Monte Carlo (MCMC) techniques. Our study aims to develop appropriate prior distributions and likelihood functions that minimize the model uncertainties and bias within a Bayesian ecohydrological framework. In our study, a formal Bayesian approach is implemented in an ecohydrological model which combines a hydrological model (HyMOD) and a dynamic vegetation model (DVM). Simulations focused on one objective likelihood (Streamflow/LAI) and multi-objective likelihoods (Streamflow and LAI) with different weights are compared. Uniform, weakly informative and strongly informative prior distributions are used in different simulations. The Kullback-leibler divergence (KLD) is used to measure the dis(similarity) between different priors and corresponding posterior distributions to examine the parameter sensitivity. Results show that different prior distributions can strongly influence posterior distributions for parameters, especially when the available data is limited or parameters are insensitive to the available data. We demonstrate differences in optimized parameters and uncertainty limits in different cases based on multi-objective likelihoods vs. single objective likelihoods. We also demonstrate the importance of appropriately defining the weights of objectives in multi-objective calibration according to different data types.

Investigation on pitch system loads by means of an integral multi body simulation approach

NASA Astrophysics Data System (ADS)

Berroth, J.; Jacobs, G.; Kroll, T.; Schelenz, R.

2016-09-01

In modern horizontal axis wind turbines the rotor blades are adjusted by three individual pitch systems to control power output. The pitch system consists of either a hydraulic or an electrical actuator, the blade bearing, the rotor blade itself and the control. In case of an electrical drive a gearbox is used to transmit the high torques that are required for blade pitch angle adjustment. In this contribution a new integral multi body simulation approach is presented that enables detailed assessment of dynamic pitch system loads. The simulation results presented are compared and evaluated with measurement data of a 2 MW-class reference wind turbine. Major focus of this contribution is on the assessment of non linear tooth contact behaviour incorporating tooth backlash for the single gear stages and the impact on dynamic pitch system loads.

Chemical Countermeasures for Antibiotic Resistance

DTIC Science & Technology

2012-04-01

INTRODUCTION: New approaches are required to control multi-drug resistant (MDR) bacterial infections in military medical facilities, as injured...Warfighters are highly susceptible to such infections . MDR bacterial infections can cause sepsis, cellulitis and skin abscesses, pneumonia, toxic shock...syndrome, osteomyelitis, and endocarditis among other symptoms. Serious cases result in organ failure (especially kidney), loss of limbs (via amputation

[Algorithm for the prevention of female genital mutilation. Case study from primary care].

PubMed

Alcón Belchí, Carolina; Jiménez Ruiz, Ismael; Pastor Bravo, María del Mar; Almansa Martínez, Pilar

2016-03-01

Create and implement a protocol for identifying and preventing female genital mutilation in a municipality of the Region of Murcia. A bibliographical review and significant databases were consulted for the creation of the algorithm performance. These include Cuiden, Dialnet, Medes, Medline, and other documentary sources of interest. The instrument for data collection was completed by interviewing parents of girls at risk. The multi-disciplinary team was formed; the female genital mutilation risk cases were collected, and were summoned to the nursing consulting room. Two girls had been mutilated, the rest were at risk of female genital mutilation, and in one case the risk was imminent. The algorithm designed guides practitioners in their performance, achieving an effective detection and prevention of genital mutilation of girls. This is a first approach to the development of a regional protocol. Copyright © 2015 Elsevier España, S.L.U. All rights reserved.

A discriminative model-constrained graph cuts approach to fully automated pediatric brain tumor segmentation in 3-D MRI.

PubMed

Wels, Michael; Carneiro, Gustavo; Aplas, Alexander; Huber, Martin; Hornegger, Joachim; Comaniciu, Dorin

2008-01-01

In this paper we present a fully automated approach to the segmentation of pediatric brain tumors in multi-spectral 3-D magnetic resonance images. It is a top-down segmentation approach based on a Markov random field (MRF) model that combines probabilistic boosting trees (PBT) and lower-level segmentation via graph cuts. The PBT algorithm provides a strong discriminative observation model that classifies tumor appearance while a spatial prior takes into account the pair-wise homogeneity in terms of classification labels and multi-spectral voxel intensities. The discriminative model relies not only on observed local intensities but also on surrounding context for detecting candidate regions for pathology. A mathematically sound formulation for integrating the two approaches into a unified statistical framework is given. The proposed method is applied to the challenging task of detection and delineation of pediatric brain tumors. This segmentation task is characterized by a high non-uniformity of both the pathology and the surrounding non-pathologic brain tissue. A quantitative evaluation illustrates the robustness of the proposed method. Despite dealing with more complicated cases of pediatric brain tumors the results obtained are mostly better than those reported for current state-of-the-art approaches to 3-D MR brain tumor segmentation in adult patients. The entire processing of one multi-spectral data set does not require any user interaction, and takes less time than previously proposed methods.

Improving case study research in medical education: a systematised review.

PubMed

Cheek, Colleen; Hays, Richard; Smith, Janie; Allen, Penny

2018-05-01

Case study research (CSR) is a research approach that guides holistic investigation of a real phenomenon. This approach may be useful in medical education to provide critical analyses of teaching and learning, and to reveal the underlying elements of leadership and innovation. There are variations in the definition, design and choice of methods, which may diminish the value of CSR as a form of inquiry. This paper reports an analysis of CSR papers in the medical education literature. The review aims to describe how CSR has been used and how more consistency might be achieved to promote understanding and value. A systematised review was undertaken to quantify the number of CSR articles published in scholarly medical education journals over the last 10 years. A typology of CSR proposed by Thomas and Myers to integrate the various ways in which CSR is constructed was applied. Of the 362 full-text articles assessed, 290 were excluded as they did not meet the eligibility criteria; 76 of these were titled 'case study'. Of the 72 included articles, 50 used single-case and 22 multi-case design; 46 connected with theory and 26 were atheoretical. In some articles it was unclear what the subject was or how the subject was being analysed. In this study, more articles titled 'case study' failed than succeeded in meeting the eligibility criteria. Well-structured, clearly written CSR in medical education has the potential to increase understanding of more complex situations, but this review shows there is considerable variation in how it is conducted, which potentially limits its utility and translation into education practice. Case study research might be of more value in medical education if researchers were to follow more consistently principles of design, and harness rich observation with connection of ideas and knowledge to engage the reader in what is most interesting. © 2017 John Wiley & Sons Ltd and The Association for the Study of Medical Education.

Targeting the human macrophage with combinations of drugs and inhibitors of Ca2+ and K+ transport to enhance the killing of intracellular multi-drug resistant Mycobacterium tuberculosis (MDR-TB)--a novel, patentable approach to limit the emergence of XDR-TB.

PubMed

Martins, Marta

2011-05-01

The emergence of resistance in tuberculosis has become a serious problem for the control of this disease. For that reason, new therapeutic strategies that can be implemented in the clinical setting are urgently needed. The design of new compounds active against mycobacteria must take into account that tuberculosis is mainly an intracellular infection of the alveolar macrophage and therefore must maintain activity within the host cells. An alternative therapeutic approach will be described in this review, focusing on the activation of the phagocytic cell and the subsequent killing of the internalized bacteria. This approach explores the combined use of antibiotics and phenothiazines, or Ca(2+) and K(+) flux inhibitors, in the infected macrophage. Targeting the infected macrophage and not the internalized bacteria could overcome the problem of bacterial multi-drug resistance. This will potentially eliminate the appearance of new multi-drug resistant tuberculosis (MDR-TB) cases and subsequently prevent the emergence of extensively-drug resistant tuberculosis (XDR-TB). Patents resulting from this novel and innovative approach could be extremely valuable if they can be implemented in the clinical setting. Other patents will also be discussed such as the treatment of TB using immunomodulator compounds (for example: betaglycans).

Modeling Joint Exposures and Health Outcomes for Cumulative Risk Assessment: The Case of Radon and Smoking

PubMed Central

Chahine, Teresa; Schultz, Bradley D.; Zartarian, Valerie G.; Xue, Jianping; Subramanian, SV; Levy, Jonathan I.

2011-01-01

Community-based cumulative risk assessment requires characterization of exposures to multiple chemical and non-chemical stressors, with consideration of how the non-chemical stressors may influence risks from chemical stressors. Residential radon provides an interesting case example, given its large attributable risk, effect modification due to smoking, and significant variability in radon concentrations and smoking patterns. In spite of this fact, no study to date has estimated geographic and sociodemographic patterns of both radon and smoking in a manner that would allow for inclusion of radon in community-based cumulative risk assessment. In this study, we apply multi-level regression models to explain variability in radon based on housing characteristics and geological variables, and construct a regression model predicting housing characteristics using U.S. Census data. Multi-level regression models of smoking based on predictors common to the housing model allow us to link the exposures. We estimate county-average lifetime lung cancer risks from radon ranging from 0.15 to 1.8 in 100, with high-risk clusters in areas and for subpopulations with high predicted radon and smoking rates. Our findings demonstrate the viability of screening-level assessment to characterize patterns of lung cancer risk from radon, with an approach that can be generalized to multiple chemical and non-chemical stressors. PMID:22016710

Let's talk about death: data collection for verbal autopsies in a demographic and health surveillance site in Malaysia.

PubMed

Allotey, Pascale A; Reidpath, Daniel D; Evans, Natalie C; Devarajan, Nirmala; Rajagobal, Kanason; Bachok, Ruhaida; Komahan, Kridaraan

2015-01-01

Verbal autopsies have gained considerable ground as an acceptable alternative to medically determined cause of death. Unlike with clinical or more administrative settings for data collection, verbal autopsies require significant involvement of families and communities, which introduces important social and cultural considerations. However, there is very little clear guidance about the methodological issues in data collection. The objectives of this case study were: to explore the range of bereavement rituals within the multi-ethnic, multi-faith population of the district; to investigate the preparedness of communities to talk about death; to describe the verbal autopsy process; to assess the effects of collecting verbal autopsy data on data collectors; and to determine the most accurate sources of information about deaths in the community. A case study approach was used, using focus group discussions, indepth interviews and field notes. Thematic analyses were undertaken using NVivo. Consideration of cultural bereavement practices is importance to acceptance and response rates to verbal autopsies. They are also important to the timing of verbal autopsy interviews. Well trained data collectors, regardless of health qualifications are able to collect good quality data, but debriefing is important to their health and well being. This article contributes to guidance on the data collection procedures for verbal autopsies within community settings.

Meeting Indigenous peoples' objectives in environmental flow assessments: Case studies from an Australian multi-jurisdictional water sharing initiative

NASA Astrophysics Data System (ADS)

Jackson, Sue; Pollino, Carmel; Maclean, Kirsten; Bark, Rosalind; Moggridge, Bradley

2015-03-01

The multi-dimensional relationships that Indigenous peoples have with water are only recently gaining recognition in water policy and management activities. Although Australian water policy stipulates that the native title interests of Indigenous peoples and their social, cultural and spiritual objectives be included in water plans, improved rates of Indigenous access to water have been slow to eventuate, particularly in those regions where the water resource is fully developed or allocated. Experimentation in techniques and approaches to both identify and determine Indigenous water requirements will be needed if environmental assessment processes and water sharing plans are to explicitly account for Indigenous water values. Drawing on two multidisciplinary case studies conducted in Australia's Murray-Darling Basin, we engage Indigenous communities to (i) understand their values and explore the application of methods to derive water requirements to meet those values; (ii) assess the impact of alternative water planning scenarios designed to address over-allocation to irrigation; and (iii) define additional volumes of water and potential works needed to meet identified Indigenous requirements. We provide a framework where Indigenous values can be identified and certain water needs quantified and advance a methodology to integrate Indigenous social, cultural and environmental objectives into environmental flow assessments.

Risk assessments using the Strain Index and the TLV for HAL, Part II: Multi-task jobs and prevalence of CTS.

PubMed

Kapellusch, Jay M; Silverstein, Barbara A; Bao, Stephen S; Thiese, Mathew S; Merryweather, Andrew S; Hegmann, Kurt T; Garg, Arun

2018-02-01

The Strain Index (SI) and the American Conference of Governmental Industrial Hygienists (ACGIH) threshold limit value for hand activity level (TLV for HAL) have been shown to be associated with prevalence of distal upper-limb musculoskeletal disorders such as carpal tunnel syndrome (CTS). The SI and TLV for HAL disagree on more than half of task exposure classifications. Similarly, time-weighted average (TWA), peak, and typical exposure techniques used to quantity physical exposure from multi-task jobs have shown between-technique agreement ranging from 61% to 93%, depending upon whether the SI or TLV for HAL model was used. This study compared exposure-response relationships between each model-technique combination and prevalence of CTS. Physical exposure data from 1,834 workers (710 with multi-task jobs) were analyzed using the SI and TLV for HAL and the TWA, typical, and peak multi-task job exposure techniques. Additionally, exposure classifications from the SI and TLV for HAL were combined into a single measure and evaluated. Prevalent CTS cases were identified using symptoms and nerve-conduction studies. Mixed effects logistic regression was used to quantify exposure-response relationships between categorized (i.e., low, medium, and high) physical exposure and CTS prevalence for all model-technique combinations, and for multi-task workers, mono-task workers, and all workers combined. Except for TWA TLV for HAL, all model-technique combinations showed monotonic increases in risk of CTS with increased physical exposure. The combined-models approach showed stronger association than the SI or TLV for HAL for multi-task workers. Despite differences in exposure classifications, nearly all model-technique combinations showed exposure-response relationships with prevalence of CTS for the combined sample of mono-task and multi-task workers. Both the TLV for HAL and the SI, with the TWA or typical techniques, appear useful for epidemiological studies and surveillance. However, the utility of TWA, typical, and peak techniques for job design and intervention is dubious.

Resonance Frequency Breathing Biofeedback to Reduce Symptoms of Subthreshold PTSD with an Air Force Special Tactics Operator: A Case Study.

PubMed

Petta, Lorene M

2017-06-01

The prevalence rates of post-traumatic stress disorder (PTSD) have been estimated to be several times higher in military populations compared to the national average. Special Tactics operators are a group that is more likely to avoid seeking psychological care due to the stigma and other consequences the diagnosis may have on their military careers. There is a need for more effective and less stigmatizing interventions to treat this population. Psychophysiological methods have been proven to be efficacious in treating PTSD, yet have received less attention as an adjunctive intervention. Resonance frequency (RF) biofeedback is a form of cardiorespiratory intervention that has shown promise as an effective treatment. The current case study examined the use of RF biofeedback in combination with other physiological and evidence-based methods as part of a comprehensive treatment approach. The client showed a significant drop from his initial scores on a screening assessment by the end of treatment, and demonstrated continued progress despite a 3-month break from the therapy. This author proposed that the synergistic effects of the multi-phased treatment approach contributed to the client's progress. Furthermore, a case was made for using multiple techniques when treating subthreshold PTSD and related symptoms within a treatment resistant population.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Düchs, Dominik; Delaney, Kris T., E-mail: kdelaney@mrl.ucsb.edu; Fredrickson, Glenn H., E-mail: ghf@mrl.ucsb.edu

Field-theoretic models have been used extensively to study the phase behavior of inhomogeneous polymer melts and solutions, both in self-consistent mean-field calculations and in numerical simulations of the full theory capturing composition fluctuations. The models commonly used can be grouped into two categories, namely, species models and exchange models. Species models involve integrations of functionals that explicitly depend on fields originating both from species density operators and their conjugate chemical potential fields. In contrast, exchange models retain only linear combinations of the chemical potential fields. In the two-component case, development of exchange models has been instrumental in enabling stable complexmore » Langevin (CL) simulations of the full complex-valued theory. No comparable stable CL approach has yet been established for field theories of the species type. Here, we introduce an extension of the exchange model to an arbitrary number of components, namely, the multi-species exchange (MSE) model, which greatly expands the classes of soft material systems that can be accessed by the complex Langevin simulation technique. We demonstrate the stability and accuracy of the MSE-CL sampling approach using numerical simulations of triblock and tetrablock terpolymer melts, and tetrablock quaterpolymer melts. This method should enable studies of a wide range of fluctuation phenomena in multiblock/multi-species polymer blends and composites.« less

Modelling Creativity: Identifying Key Components through a Corpus-Based Approach.

PubMed

Jordanous, Anna; Keller, Bill

2016-01-01

Creativity is a complex, multi-faceted concept encompassing a variety of related aspects, abilities, properties and behaviours. If we wish to study creativity scientifically, then a tractable and well-articulated model of creativity is required. Such a model would be of great value to researchers investigating the nature of creativity and in particular, those concerned with the evaluation of creative practice. This paper describes a unique approach to developing a suitable model of how creative behaviour emerges that is based on the words people use to describe the concept. Using techniques from the field of statistical natural language processing, we identify a collection of fourteen key components of creativity through an analysis of a corpus of academic papers on the topic. Words are identified which appear significantly often in connection with discussions of the concept. Using a measure of lexical similarity to help cluster these words, a number of distinct themes emerge, which collectively contribute to a comprehensive and multi-perspective model of creativity. The components provide an ontology of creativity: a set of building blocks which can be used to model creative practice in a variety of domains. The components have been employed in two case studies to evaluate the creativity of computational systems and have proven useful in articulating achievements of this work and directions for further research.

Assessing landscape hydroperiods across the Mekong Basin using multi-scale remote sensing to understand water-energy-food tradeoffs

NASA Astrophysics Data System (ADS)

Torbick, N.; Salas, W.; Qi, J.; Huang, X.

2017-12-01

In the Lower Mekong River Basin (LMRB), population growth and transitioning economies, shifting climate, and intense pressures for resources are driving tradeoffs among the water-enegery-food (WEF) nexus. Rice production and irrigation, wetlands habitat, and damn constructions are intertwinned across the region. There are 11 major hydropower dams on the main stem of the Lower Mekong River and many smaller dams in the basin. At the same time increased pressure for food production has amplified cropping intensity and irrigation infrastructure projects. These human acitivies are impacting inundation patterns and phenology of wetland and lake ecosystems. We are mapping rice, wetlands, and lake inundation dynamics using multi-scale satellite remote sensing. New opportunities exist for moderate scale, near-daily mapping of rice, wetland, shrimp, and lake hydroperiod with multi-source imaging and BigData computational approaches on the NAS cloud. Primarily we rely on Sentinel-1 IW and PALSAR-2 ScanSAR to map inundation dynamics at 10m resolution including under canopy conditions using double bounce properties. As part of this effort we are assessing different damn impacts at case studies in Thailand, Cambodia, Laos, and Vietnam with high resolution commercial imagery, social surveys, and socioeconomic models. These dams are currently regulated individually without coordination. As a result, their operation has outsized impacts on lake and wetland ecologies, negatively affecting the associated ecosystem services that local communities have relied on. All new products are shared openly with the science community. Case study illustrations will be presented.

E-learning and blended learning in textile engineering education: a closed feedback loop approach

NASA Astrophysics Data System (ADS)

Charitopoulos, A.; Vassiliadis, S.; Rangoussi, M.; Koulouriotis, D.

2017-10-01

E-learning has gained a significant role in typical education and in professional training, thanks to the flexibility it offers to the time and location parameters of the education event framework. Purely e-learning scenarios are mostly limited either to Open University-type higher education institutions or to graduate level or professional degrees; blended learning scenarios are progressively becoming popular thanks to their balanced approach. The aim of the present work is to propose approaches that exploit the e-learning and the blended-learning scenarios for Textile Engineering education programmes, especially for multi-institutional ones. The “E-Team” European MSc degree programme organized by AUTEX is used as a case study. The proposed solution is based on (i) a free and open-source e-learning platform (moodle) and (ii) blended learning educational scenarios. Educational challenges addressed include student engagement, student error / failure handling, as well as collaborative learning promotion and support.

A High Performance Computing Study of a Scalable FISST-Based Approach to Multi-Target, Multi-Sensor Tracking

NASA Astrophysics Data System (ADS)

Hussein, I.; Wilkins, M.; Roscoe, C.; Faber, W.; Chakravorty, S.; Schumacher, P.

2016-09-01

Finite Set Statistics (FISST) is a rigorous Bayesian multi-hypothesis management tool for the joint detection, classification and tracking of multi-sensor, multi-object systems. Implicit within the approach are solutions to the data association and target label-tracking problems. The full FISST filtering equations, however, are intractable. While FISST-based methods such as the PHD and CPHD filters are tractable, they require heavy moment approximations to the full FISST equations that result in a significant loss of information contained in the collected data. In this paper, we review Smart Sampling Markov Chain Monte Carlo (SSMCMC) that enables FISST to be tractable while avoiding moment approximations. We study the effect of tuning key SSMCMC parameters on tracking quality and computation time. The study is performed on a representative space object catalog with varying numbers of RSOs. The solution is implemented in the Scala computing language at the Maui High Performance Computing Center (MHPCC) facility.

TRIAD: The Translational Research Informatics and Data Management Grid

PubMed Central

Payne, P.; Ervin, D.; Dhaval, R.; Borlawsky, T.; Lai, A.

2011-01-01

Objective Multi-disciplinary and multi-site biomedical research programs frequently require infrastructures capable of enabling the collection, management, analysis, and dissemination of heterogeneous, multi-dimensional, and distributed data and knowledge collections spanning organizational boundaries. We report on the design and initial deployment of an extensible biomedical informatics platform that is intended to address such requirements. Methods A common approach to distributed data, information, and knowledge management needs in the healthcare and life science settings is the deployment and use of a service-oriented architecture (SOA). Such SOA technologies provide for strongly-typed, semantically annotated, and stateful data and analytical services that can be combined into data and knowledge integration and analysis “pipelines.” Using this overall design pattern, we have implemented and evaluated an extensible SOA platform for clinical and translational science applications known as the Translational Research Informatics and Data-management grid (TRIAD). TRIAD is a derivative and extension of the caGrid middleware and has an emphasis on supporting agile “working interoperability” between data, information, and knowledge resources. Results Based upon initial verification and validation studies conducted in the context of a collection of driving clinical and translational research problems, we have been able to demonstrate that TRIAD achieves agile “working interoperability” between distributed data and knowledge sources. Conclusion Informed by our initial verification and validation studies, we believe TRIAD provides an example instance of a lightweight and readily adoptable approach to the use of SOA technologies in the clinical and translational research setting. Furthermore, our initial use cases illustrate the importance and efficacy of enabling “working interoperability” in heterogeneous biomedical environments. PMID:23616879

TRIAD: The Translational Research Informatics and Data Management Grid.

PubMed

Payne, P; Ervin, D; Dhaval, R; Borlawsky, T; Lai, A

2011-01-01

Multi-disciplinary and multi-site biomedical research programs frequently require infrastructures capable of enabling the collection, management, analysis, and dissemination of heterogeneous, multi-dimensional, and distributed data and knowledge collections spanning organizational boundaries. We report on the design and initial deployment of an extensible biomedical informatics platform that is intended to address such requirements. A common approach to distributed data, information, and knowledge management needs in the healthcare and life science settings is the deployment and use of a service-oriented architecture (SOA). Such SOA technologies provide for strongly-typed, semantically annotated, and stateful data and analytical services that can be combined into data and knowledge integration and analysis "pipelines." Using this overall design pattern, we have implemented and evaluated an extensible SOA platform for clinical and translational science applications known as the Translational Research Informatics and Data-management grid (TRIAD). TRIAD is a derivative and extension of the caGrid middleware and has an emphasis on supporting agile "working interoperability" between data, information, and knowledge resources. Based upon initial verification and validation studies conducted in the context of a collection of driving clinical and translational research problems, we have been able to demonstrate that TRIAD achieves agile "working interoperability" between distributed data and knowledge sources. Informed by our initial verification and validation studies, we believe TRIAD provides an example instance of a lightweight and readily adoptable approach to the use of SOA technologies in the clinical and translational research setting. Furthermore, our initial use cases illustrate the importance and efficacy of enabling "working interoperability" in heterogeneous biomedical environments.

A general mixture equation of state for double bonding carboxylic acids with ≥2 association sites

NASA Astrophysics Data System (ADS)

Marshall, Bennett D.

2018-05-01

In this paper, we obtain the first general multi-component solution to Wertheim's thermodynamic perturbation theory for the case that molecules can participate in cyclic double bonds. In contrast to previous authors, we do not restrict double bonding molecules to a 2-site association scheme. Each molecule in a multi-component mixture can have an arbitrary number of donor and acceptor association sites. The one restriction on the theory is that molecules can have at most one pair of double bonding sites. We also incorporate the effect of hydrogen bond cooperativity in cyclic double bonds. We then apply this new association theory to 2-site and 3-site models for carboxylic acids within the polar perturbed chain statistical associating fluid theory equation of state. We demonstrate the accuracy of the approach by comparison to both pure and multi-component phase equilibria data. It is demonstrated that the 3-site association model gives substantially a different hydrogen bonding structure than a 2-site approach. We also demonstrate that inclusion of hydrogen bond cooperativity has a substantial effect on a liquid phase hydrogen bonding structure.

Psychological Needs, Engagement, and Work Intentions: A Bayesian Multi-Measurement Mediation Approach and Implications for HRD

ERIC Educational Resources Information Center

Shuck, Brad; Zigarmi, Drea; Owen, Jesse

2015-01-01

Purpose: The purpose of this study was to empirically examine the utility of self-determination theory (SDT) within the engagement-performance linkage. Design/methodology/approach: Bayesian multi-measurement mediation modeling was used to estimate the relation between SDT, engagement and a proxy measure of performance (e.g. work intentions) (N =…

Multi-dimensional Upwind Fluctuation Splitting Scheme with Mesh Adaption for Hypersonic Viscous Flow. Degree awarded by Virginia Polytechnic Inst. and State Univ., 9 Nov. 2001

NASA Technical Reports Server (NTRS)

Wood, William A., III

2002-01-01

A multi-dimensional upwind fluctuation splitting scheme is developed and implemented for two-dimensional and axisymmetric formulations of the Navier-Stokes equations on unstructured meshes. Key features of the scheme are the compact stencil, full upwinding, and non-linear discretization which allow for second-order accuracy with enforced positivity. Throughout, the fluctuation splitting scheme is compared to a current state-of-the-art finite volume approach, a second-order, dual mesh upwind flux difference splitting scheme (DMFDSFV), and is shown to produce more accurate results using fewer computer resources for a wide range of test cases. A Blasius flat plate viscous validation case reveals a more accurate upsilon-velocity profile for fluctuation splitting, and the reduced artificial dissipation production is shown relative to DMFDSFV. Remarkably, the fluctuation splitting scheme shows grid converged skin friction coefficients with only five points in the boundary layer for this case. The second half of the report develops a local, compact, anisotropic unstructured mesh adaptation scheme in conjunction with the multi-dimensional upwind solver, exhibiting a characteristic alignment behavior for scalar problems. The adaptation strategy is extended to the two-dimensional and axisymmetric Navier-Stokes equations of motion through the concept of fluctuation minimization.

Paradise nearly Gained. Volume 2: Case Studies of Impact and Diversity for Frontline Management Initiative Practice.

ERIC Educational Resources Information Center

Barratt-Pugh, Llandis; Soutar, Geoffrey N.

This document presents the case studies from a multi-phase study of the impact of Australia's Frontline Management Initiative (FMI), which provides a framework for competency-based development of frontline managers in Australian enterprises. Nineteen organizational case studies and one individual case study of the FMI's impacts are included. The…

Community-Engagement Strategies of the Developmental Disabilities Practice-Based Research Network (DD-PBRN)

PubMed Central

Tyler, Carl; Werner, James J.

2016-01-01

There is often a rich but untold history of events that occurred and relationships that formed prior to the launching of a practice-based research network (PBRN.) This is particularly the case in PBRNs that are community-based and comprised of partnerships outside of the health care system. In this article we summarize an organizational "prenatal history" prior to the birth of a PBRN devoted to persons with developmental disabilities. Using a case study approach, this article describes the historical events that preceded and fostered the evolution of this PBRN and contrasts how the processes leading to the creation of this multi-stakeholder community-based PBRN differ from those of typical academic-clinical practice PBRNs. We propose potential advantages and complexities inherent to this newest iteration of PBRNs. PMID:25381081

A multi-sensor scenario for coastal surveillance

NASA Astrophysics Data System (ADS)

van den Broek, A. C.; van den Broek, S. P.; van den Heuvel, J. C.; Schwering, P. B. W.; van Heijningen, A. W. P.

2007-10-01

Maritime borders and coastal zones are susceptible to threats such as drug trafficking, piracy, undermining economical activities. At TNO Defence, Security and Safety various studies aim at improving situational awareness in a coastal zone. In this study we focus on multi-sensor surveillance of the coastal environment. We present a study on improving classification results for small sea surface targets using an advanced sensor suite and a scenario in which a small boat is approaching the coast. A next generation sensor suite mounted on a tower has been defined consisting of a maritime surveillance and tracking radar system, capable of producing range profiles and ISAR imagery of ships, an advanced infrared camera and a laser range profiler. For this suite we have developed a multi-sensor classification procedure, which is used to evaluate the capabilities for recognizing and identifying non-cooperative ships in coastal waters. We have found that the different sensors give complementary information. Each sensor has its own specific distance range in which it contributes most. A multi-sensor approach reduces the number of misclassifications and reliable classification results are obtained earlier compared to a single sensor approach.

Incorporating ecosystem function concept in environmental planning and decision making by means of multi-criteria evaluation: the case-study of Kalloni, Lesbos, Greece.

PubMed

Oikonomou, Vera; Dimitrakopoulos, Panayiotis G; Troumbis, Andreas Y

2011-01-01

Nature provides life-support services which do not merely constitute the basis for ecosystem integrity but also benefit human societies. The importance of such multiple outputs is often ignored or underestimated in environmental planning and decision making. The economic valuation of ecosystem functions or services has been widely used to make these benefits economically visible and thus address this deficiency. Alternatively, the relative importance of the components of ecosystem value can be identified and compared by means of multi-criteria evaluation. Hereupon, this article proposes a conceptual framework that couples ecosystem function analysis, multi criteria evaluation and social research methodologies for introducing an ecosystem function-based planning and management approach. The framework consists of five steps providing the structure of a participative decision making process which is then tested and ratified, by applying the discrete multi-criteria method NAIADE, in the Kalloni Natura 2000 site, on Lesbos, Greece. Three scenarios were developed and evaluated with regard to their impacts on the different types of ecosystem functions and the social actors' value judgements. A conflict analysis permitted the better elaboration of the different views, outlining the coalitions formed in the local community and shaping the way towards reaching a consensus.

Incorporating Ecosystem Function Concept in Environmental Planning and Decision Making by Means of Multi-Criteria Evaluation: The Case-Study of Kalloni, Lesbos, Greece

NASA Astrophysics Data System (ADS)

Oikonomou, Vera; Dimitrakopoulos, Panayiotis G.; Troumbis, Andreas Y.

2011-01-01

Nature provides life-support services which do not merely constitute the basis for ecosystem integrity but also benefit human societies. The importance of such multiple outputs is often ignored or underestimated in environmental planning and decision making. The economic valuation of ecosystem functions or services has been widely used to make these benefits economically visible and thus address this deficiency. Alternatively, the relative importance of the components of ecosystem value can be identified and compared by means of multi-criteria evaluation. Hereupon, this article proposes a conceptual framework that couples ecosystem function analysis, multi criteria evaluation and social research methodologies for introducing an ecosystem function-based planning and management approach. The framework consists of five steps providing the structure of a participative decision making process which is then tested and ratified, by applying the discrete multi-criteria method NAIADE, in the Kalloni Natura 2000 site, on Lesbos, Greece. Three scenarios were developed and evaluated with regard to their impacts on the different types of ecosystem functions and the social actors' value judgements. A conflict analysis permitted the better elaboration of the different views, outlining the coalitions formed in the local community and shaping the way towards reaching a consensus.

Voxel-based Gaussian naïve Bayes classification of ischemic stroke lesions in individual T1-weighted MRI scans.

PubMed

Griffis, Joseph C; Allendorfer, Jane B; Szaflarski, Jerzy P

2016-01-15

Manual lesion delineation by an expert is the standard for lesion identification in MRI scans, but it is time-consuming and can introduce subjective bias. Alternative methods often require multi-modal MRI data, user interaction, scans from a control population, and/or arbitrary statistical thresholding. We present an approach for automatically identifying stroke lesions in individual T1-weighted MRI scans using naïve Bayes classification. Probabilistic tissue segmentation and image algebra were used to create feature maps encoding information about missing and abnormal tissue. Leave-one-case-out training and cross-validation was used to obtain out-of-sample predictions for each of 30 cases with left hemisphere stroke lesions. Our method correctly predicted lesion locations for 30/30 un-trained cases. Post-processing with smoothing (8mm FWHM) and cluster-extent thresholding (100 voxels) was found to improve performance. Quantitative evaluations of post-processed out-of-sample predictions on 30 cases revealed high spatial overlap (mean Dice similarity coefficient=0.66) and volume agreement (mean percent volume difference=28.91; Pearson's r=0.97) with manual lesion delineations. Our automated approach agrees with manual tracing. It provides an alternative to automated methods that require multi-modal MRI data, additional control scans, or user interaction to achieve optimal performance. Our fully trained classifier has applications in neuroimaging and clinical contexts. Copyright © 2015 Elsevier B.V. All rights reserved.

Fully refocused multi-shot spatiotemporally encoded MRI: robust imaging in the presence of metallic implants.

PubMed

Ben-Eliezer, Noam; Solomon, Eddy; Harel, Elad; Nevo, Nava; Frydman, Lucio

2012-12-01

An approach has been recently introduced for acquiring arbitrary 2D NMR spectra or images in a single scan, based on the use of frequency-swept RF pulses for the sequential excitation and acquisition of the spins response. This spatiotemporal-encoding (SPEN) approach enables a unique, voxel-by-voxel refocusing of all frequency shifts in the sample, for all instants throughout the data acquisition. The present study investigates the use of this full-refocusing aspect of SPEN-based imaging in the multi-shot MRI of objects, subject to sizable field inhomogeneities that complicate conventional imaging approaches. 2D MRI experiments were performed at 7 T on phantoms and on mice in vivo, focusing on imaging in proximity to metallic objects. Fully refocused SPEN-based spin echo imaging sequences were implemented, using both Cartesian and back-projection trajectories, and compared with k-space encoded spin echo imaging schemes collected on identical samples under equal bandwidths and acquisition timing conditions. In all cases assayed, the fully refocused spatiotemporally encoded experiments evidenced a ca. 50 % reduction in signal dephasing in the proximity of the metal, as compared to analogous results stemming from the k-space encoded spin echo counterparts. The results in this study suggest that SPEN-based acquisition schemes carry the potential to overcome strong field inhomogeneities, of the kind that currently preclude high-field, high-resolution tissue characterizations in the neighborhood of metallic implants.

Attributing foodborne salmonellosis in humans to animal reservoirs in the European Union using a multi-country stochastic model.

PubMed

DE Knegt, L V; Pires, S M; Hald, T

2015-04-01

A Bayesian modelling approach comparing the occurrence of Salmonella serovars in animals and humans was used to attribute salmonellosis cases to broilers, turkeys, pigs, laying hens, travel and outbreaks in 24 European Union countries. Salmonella data for animals and humans, covering the period from 2007 to 2009, were mainly obtained from studies and reports published by the European Food Safety Authority. Availability of food sources for consumption was derived from trade and production data from the European Statistical Office. Results showed layers as the most important reservoir of human salmonellosis in Europe, with 42·4% (7 903 000 cases, 95% credibility interval 4 181 000-14 510 000) of cases, 95·9% of which was caused by S. Enteritidis. In Finland and Sweden, most cases were travel-related, while in most other countries the main sources were related to the laying hen or pig reservoir, highlighting differences in the epidemiology of Salmonella, surveillance focus and eating habits across the European Union.

Full space device optimization for solar cells.

PubMed

Baloch, Ahmer A B; Aly, Shahzada P; Hossain, Mohammad I; El-Mellouhi, Fedwa; Tabet, Nouar; Alharbi, Fahhad H

2017-09-20

Advances in computational materials have paved a way to design efficient solar cells by identifying the optimal properties of the device layers. Conventionally, the device optimization has been governed by single or double descriptors for an individual layer; mostly the absorbing layer. However, the performance of the device depends collectively on all the properties of the material and the geometry of each layer in the cell. To address this issue of multi-property optimization and to avoid the paradigm of reoccurring materials in the solar cell field, a full space material-independent optimization approach is developed and presented in this paper. The method is employed to obtain an optimized material data set for maximum efficiency and for targeted functionality for each layer. To ensure the robustness of the method, two cases are studied; namely perovskite solar cells device optimization and cadmium-free CIGS solar cell. The implementation determines the desirable optoelectronic properties of transport mediums and contacts that can maximize the efficiency for both cases. The resulted data sets of material properties can be matched with those in materials databases or by further microscopic material design. Moreover, the presented multi-property optimization framework can be extended to design any solid-state device.

A multiobjective modeling approach to locate multi-compartment containers for urban-sorted waste

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tralhao, Lino, E-mail: lmlrt@inescc.p; Coutinho-Rodrigues, Joao, E-mail: coutinho@dec.uc.p; Alcada-Almeida, Luis, E-mail: alcada@inescc.p

2010-12-15

The location of multi-compartment sorted waste containers for recycling purposes in cities is an important problem in the context of urban waste management. The costs associated with those facilities and the impacts placed on populations are important concerns. This paper introduces a mixed-integer, multiobjective programming approach to identify the locations and capacities of such facilities. The approach incorporates an optimization model in a Geographical Information System (GIS)-based interactive decision support system that includes four objectives. The first objective minimizes the total investment cost; the second one minimizes the average distance from dwellings to the respective multi-compartment container; the last twomore » objectives address the 'pull' and 'push' characteristics of the decision problem, one by minimizing the number of individuals too close to any container, and the other by minimizing the number of dwellings too far from the respective multi-compartment container. The model determines the number of facilities to be opened, the respective container capacities, their locations, their respective shares of the total waste of each type to be collected, and the dwellings assigned to each facility. The approach proposed was tested with a case study for the historical center of Coimbra city, Portugal, where a large urban renovation project, addressing about 800 buildings, is being undertaken. This paper demonstrates that the models and techniques incorporated in the interactive decision support system (IDSS) can be used to assist a decision maker (DM) in analyzing this complex problem in a realistically sized urban application. Ten solutions consisting of different combinations of underground containers for the disposal of four types of sorted waste in 12 candidate sites, were generated. These solutions and tradeoffs among the objectives are presented to the DM via tables, graphs, color-coded maps and other graphics. The DM can then use this information to 'guide' the IDSS in identifying additional solutions of potential interest. Nevertheless, this research showed that a particular solution with a better objective balance can be identified. The actual sequence of additional solutions generated will depend upon the objectives and preferences of the DM in a specific application.« less

The multi-reference retaining the excitation degree perturbation theory: A size-consistent, unitary invariant, and rapidly convergent wavefunction based ab initio approach

NASA Astrophysics Data System (ADS)

Fink, Reinhold F.

2009-02-01

The retaining the excitation degree (RE) partitioning [R.F. Fink, Chem. Phys. Lett. 428 (2006) 461(20 September)] is reformulated and applied to multi-reference cases with complete active space (CAS) reference wave functions. The generalised van Vleck perturbation theory is employed to set up the perturbation equations. It is demonstrated that this leads to a consistent and well defined theory which fulfils all important criteria of a generally applicable ab initio method: The theory is proven numerically and analytically to be size-consistent and invariant with respect to unitary orbital transformations within the inactive, active and virtual orbital spaces. In contrast to most previously proposed multi-reference perturbation theories the necessary condition for a proper perturbation theory to fulfil the zeroth order perturbation equation is exactly satisfied with the RE partitioning itself without additional projectors on configurational spaces. The theory is applied to several excited states of the benchmark systems CH2 , SiH2 , and NH2 , as well as to the lowest states of the carbon, nitrogen and oxygen atoms. In all cases comparisons are made with full configuration interaction results. The multi-reference (MR)-RE method is shown to provide very rapidly converging perturbation series. Energy differences between states of similar configurations converge even faster.

Emergency surgical treatment of cervico-mediastinal lymph-haemangioma in a 2-month-old infant, indicated by acute inner tumour haemorrhage.

PubMed

Drebov, R; Stoichev, R; Argirova, M; Mitev, Pl; Gagov, E

2013-01-01

Cervico-Mediastinal Lymphangiomas (CML) are caused by atresia of the efferent lymphatics or lack of communication between lymphatics and venous channels. Cervico-Mediastinal Lymphangiomas in certain cases require emergency surgery to secure decompression of the airways. The purpose of this study is to present a multidisciplinary surgical approach in the treatment of urgently complicated Cervico-Mediastinal Lymphangiomas, and to asses the surgical tactics and satisfactory outcome after a two-stage operation. The paper presents a case of a 48-day-old girl with acute haemorrhage of Cervico-Mediastinal Lymphangioma, resulting from an increased arterial blood pressure due to thrombosis of the internal jugular vein. This condition required the convening of an emergency multidisciplinary surgical team which resolved emergency decompression by removal of the cervical tumour component. The authors discuss the reasons for the emergency indications for operation in this case, the dynamics in multi-stage treatment, the regression of the mediastinal component resulting from the developed inflammation, the intraoperative difficulties and functional complications resulting from the strife after radicalism. The presented case shows indications for emergency surgical intervention in acute growing CML. It illustrates the need for a multidisciplinary surgical approach involving a team of experts in paediatric, vascular, cardiac and aesthetic surgery.