Mainstreaming Multi-Risk Approaches into Policy

Directory of Open Access Journals (Sweden)

Anna Scolobig

2017-12-01

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

Multi-level decision making models, methods and applications

CERN Document Server

Zhang, Guangquan; Gao, Ya

2015-01-01

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

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

Science.gov (United States)

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

2018-05-10

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

A new approach combining analytical methods for workplace exposure assessment of inhalable multi-walled carbon nanotubes

NARCIS (Netherlands)

Tromp, P.C.; Kuijpers, E.; Bekker, C.; Godderis, L.; Lan, Q.; Jedynska, A.D.; Vermeulen, R.; Pronk, A.

2017-01-01

To date there is no consensus about the most appropriate analytical method for measuring carbon nanotubes (CNTs), hampering the assessment and limiting the comparison of data. The goal of this study is to develop an approach for the assessment of the level and nature of inhalable multi-wall CNTs

Multi combined Adlerian supervision in Counseling

OpenAIRE

Gungor, Abdi

2017-01-01

For counselor professional and counselor education, supervision is an important process, in which more experienced professional helps and guides less experienced professional. To provide an effective and beneficial supervision, various therapy, development, or process based approaches and models have been developed. In addition, different eclectic models integrating more than one model have been developed. In this paper, as a supervision model, multi combined Adlerian supervision model is pro...

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

Science.gov (United States)

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

2011-10-01

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

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

Science.gov (United States)

Zhang, Yue; Berhane, Kiros

2014-01-01

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

Improving survey response rates from parents in school-based research using a multi-level approach.

Science.gov (United States)

Schilpzand, Elizabeth J; Sciberras, Emma; Efron, Daryl; Anderson, Vicki; Nicholson, Jan M

2015-01-01

While schools can provide a comprehensive sampling frame for community-based studies of children and their families, recruitment is challenging. Multi-level approaches which engage multiple school stakeholders have been recommended but few studies have documented their effects. This paper compares the impact of a standard versus enhanced engagement approach on multiple indicators of recruitment: parent response rates, response times, reminders required and sample characteristics. Parents and teachers were distributed a brief screening questionnaire as a first step for recruitment to a longitudinal study, with two cohorts recruited in consecutive years (cohort 1 2011, cohort 2 2012). For cohort 2, additional engagement strategies included the use of pre-notification postcards, improved study materials, and recruitment progress graphs provided to school staff. Chi-square and t-tests were used to examine cohort differences. Compared to cohort 1, a higher proportion of cohort 2 parents responded to the survey (76% versus 69%; p value of investing in a relatively simple multi-level strategy to maximise parent response rates, and potentially reduce recruitment time and costs.

“HABITAT MAPPING” GEODATABASE, AN INTEGRATED INTERDISCIPLINARY AND MULTI-SCALE APPROACH FOR DATA MANAGEMENT

OpenAIRE

Grande, Valentina; Angeletti, Lorenzo; Campiani, Elisabetta; Conese, Ilaria; Foglini, Federica; Leidi, Elisa; Mercorella, Alessandra; Taviani, Marco

2016-01-01

Abstract Historically, a number of different key concepts and methods dealing with marine habitat classifications and mapping have been developed to date. The EU CoCoNET project provides a new attempt in establishing an integrated approach on the definition of habitats. This scheme combines multi-scale geological and biological data, in fact it consists of three levels (Geomorphological level, Substrate level and Biological level) which in turn are divided into several h...

Semiparametric score level fusion: Gaussian copula approach

NARCIS (Netherlands)

Susyanyo, N.; Klaassen, C.A.J.; Veldhuis, Raymond N.J.; Spreeuwers, Lieuwe Jan

2015-01-01

Score level fusion is an appealing method for combining multi-algorithms, multi- representations, and multi-modality biometrics due to its simplicity. Often, scores are assumed to be independent, but even for dependent scores, accord- ing to the Neyman-Pearson lemma, the likelihood ratio is the

Coupled numerical approach combining finite volume and lattice Boltzmann methods for multi-scale multi-physicochemical processes

Energy Technology Data Exchange (ETDEWEB)

Chen, Li; He, Ya-Ling [Key Laboratory of Thermo-Fluid Science and Engineering of MOE, School of Energy and Power Engineering, Xi' an Jiaotong University, Xi' an, Shaanxi 710049 (China); Kang, Qinjun [Computational Earth Science Group (EES-16), Los Alamos National Laboratory, Los Alamos, NM (United States); Tao, Wen-Quan, E-mail: wqtao@mail.xjtu.edu.cn [Key Laboratory of Thermo-Fluid Science and Engineering of MOE, School of Energy and Power Engineering, Xi' an Jiaotong University, Xi' an, Shaanxi 710049 (China)

2013-12-15

A coupled (hybrid) simulation strategy spatially combining the finite volume method (FVM) and the lattice Boltzmann method (LBM), called CFVLBM, is developed to simulate coupled multi-scale multi-physicochemical processes. In the CFVLBM, computational domain of multi-scale problems is divided into two sub-domains, i.e., an open, free fluid region and a region filled with porous materials. The FVM and LBM are used for these two regions, respectively, with information exchanged at the interface between the two sub-domains. A general reconstruction operator (RO) is proposed to derive the distribution functions in the LBM from the corresponding macro scalar, the governing equation of which obeys the convection–diffusion equation. The CFVLBM and the RO are validated in several typical physicochemical problems and then are applied to simulate complex multi-scale coupled fluid flow, heat transfer, mass transport, and chemical reaction in a wall-coated micro reactor. The maximum ratio of the grid size between the FVM and LBM regions is explored and discussed. -- Highlights: •A coupled simulation strategy for simulating multi-scale phenomena is developed. •Finite volume method and lattice Boltzmann method are coupled. •A reconstruction operator is derived to transfer information at the sub-domains interface. •Coupled multi-scale multiple physicochemical processes in micro reactor are simulated. •Techniques to save computational resources and improve the efficiency are discussed.

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

OpenAIRE

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

2010-01-01

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

A Multi-targeted Approach to Suppress Tumor-Promoting Inflammation

Science.gov (United States)

Samadi, Abbas K.; Georgakilas, Alexandros G.; Amedei, Amedeo; Amin, Amr; Bishayee, Anupam; Lokeshwar, Bal L.; Grue, Brendan; Panis, Carolina; Boosani, Chandra S.; Poudyal, Deepak; Stafforini, Diana M.; Bhakta, Dipita; Niccolai, Elena; Guha, Gunjan; Rupasinghe, H.P. Vasantha; Fujii, Hiromasa; Honoki, Kanya; Mehta, Kapil; Aquilano, Katia; Lowe, Leroy; Hofseth, Lorne J.; Ricciardiello, Luigi; Ciriolo, Maria Rosa; Singh, Neetu; Whelan, Richard L.; Chaturvedi, Rupesh; Ashraf, S. Salman; Kumara, HMC Shantha; Nowsheen, Somaira; Mohammed, Sulma I.; Helferich, William G.; Yang, Xujuan

2015-01-01

Cancers harbor significant genetic heterogeneity and patterns of relapse following many therapies are due to evolved resistance to treatment. While efforts have been made to combine targeted therapies, significant levels of toxicity have stymied efforts to effectively treat cancer with multi-drug combinations using currently approved therapeutics. We discuss the relationship between tumor-promoting inflammation and cancer as part of a larger effort to develop a broad-spectrum therapeutic approach aimed at a wide range of targets to address this heterogeneity. Specifically, macrophage migration inhibitory factor, cyclooxygenase-2, transcription factor nuclear factor-kappaB, tumor necrosis factor alpha, inducible nitric oxide synthase, protein kinase B, and CXC chemokines are reviewed as important antiinflammatory targets while curcumin, resveratrol, epigallocatechin gallate, genistein, lycopene, and anthocyanins are reviewed as low-cost, low toxicity means by which these targets might all be reached simultaneously. Future translational work will need to assess the resulting synergies of rationally designed antiinflammatory mixtures (employing low-toxicity constituents), and then combine this with similar approaches targeting the most important pathways across the range of cancer hallmark phenotypes. PMID:25951989

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

DEFF Research Database (Denmark)

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

A MultiAir®/MultiFuel Approach to Enhancing Engine System Efficiency

Energy Technology Data Exchange (ETDEWEB)

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

2015-05-20

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

Mathematical model comparing of the multi-level economics systems

Science.gov (United States)

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

2017-12-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

1996-12-31

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

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

Energy Technology Data Exchange (ETDEWEB)

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

1995-12-31

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

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

International Nuclear Information System (INIS)

Fahmy, F.H.

1995-01-01

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

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

Science.gov (United States)

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

2016-04-01

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

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

International Nuclear Information System (INIS)

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

2003-01-01

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

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

Science.gov (United States)

Bittig, Arne T; Uhrmacher, Adelinde M

2017-01-01

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

Data management and data analysis techniques in pharmacoepidemiological studies using a pre-planned multi-database approach

DEFF Research Database (Denmark)

Bazelier, Marloes T.; Eriksson, Irene; de Vries, Frank

2015-01-01

pharmacoepidemiological multi-database studies published from 2007 onwards that combined data for a pre-planned common analysis or quantitative synthesis. Information was retrieved about study characteristics, methods used for individual-level analyses and meta-analyses, data management and motivations for performing...... meta-analysis (27%), while a semi-aggregate approach was applied in three studies (14%). Information on central programming or heterogeneity assessment was missing in approximately half of the publications. Most studies were motivated by improving power (86%). CONCLUSIONS: Pharmacoepidemiological multi...

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

Science.gov (United States)

Mehrbod, Mehrdad; Tu, Nan; Miao, Lixin

2015-06-01

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

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

Science.gov (United States)

Granovsky, Alexander A

2011-06-07

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

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

Directory of Open Access Journals (Sweden)

Stephanie Bettina Linek

2015-07-01

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

Modeling Multi-Level Systems

CERN Document Server

Iordache, Octavian

2011-01-01

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

Detecting bots using multi-level traffic analysis

DEFF Research Database (Denmark)

Stevanovic, Matija; Pedersen, Jens Myrup

2016-01-01

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

Multi-Scale Approach to Understanding Source-Sink Dynamics of Amphibians

Science.gov (United States)

2015-12-01

spotted salamander, A. maculatum) at Fort Leonard Wood (FLW), Missouri. We used a multi-faceted approach in which we combined ecological , genetic...spotted salamander, A. maculatum) at Fort Leonard Wood , Missouri through a combination of intensive ecological field studies, genetic analyses, and...spatial demographic networks to identify optimal locations for wetland construction and restoration. Ecological Applications. Walls, S. C., Ball, L. C

Improving survey response rates from parents in school-based research using a multi-level approach.

Directory of Open Access Journals (Sweden)

Elizabeth J Schilpzand

Full Text Available While schools can provide a comprehensive sampling frame for community-based studies of children and their families, recruitment is challenging. Multi-level approaches which engage multiple school stakeholders have been recommended but few studies have documented their effects. This paper compares the impact of a standard versus enhanced engagement approach on multiple indicators of recruitment: parent response rates, response times, reminders required and sample characteristics.Parents and teachers were distributed a brief screening questionnaire as a first step for recruitment to a longitudinal study, with two cohorts recruited in consecutive years (cohort 1 2011, cohort 2 2012. For cohort 2, additional engagement strategies included the use of pre-notification postcards, improved study materials, and recruitment progress graphs provided to school staff. Chi-square and t-tests were used to examine cohort differences.Compared to cohort 1, a higher proportion of cohort 2 parents responded to the survey (76% versus 69%; p < 0.001, consented to participate (71% versus 56%; p < 0.001, agreed to teacher participation (90% versus 82%; p < 0.001 and agreed to follow-up contact (91% versus 80%; p < 0.001. Fewer cohort 2 parents required reminders (52% versus 63%; p < 0.001, and cohort 2 parents responded more promptly than cohort 1 parents (mean difference: 19.4 days, 95% CI: 18.0 to 20.9, p < 0.001.These results illustrate the value of investing in a relatively simple multi-level strategy to maximise parent response rates, and potentially reduce recruitment time and costs.

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

Science.gov (United States)

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

2010-11-01

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

Horizontal and vertical combination of multi-tenancy patterns in service-oriented applications

Science.gov (United States)

Mietzner, Ralph; Leymann, Frank; Unger, Tobias

2011-02-01

Software as a service (SaaS) providers exploit economies of scale by offering the same instance of an application to multiple customers typically in a single-instance multi-tenant architecture model. Therefore the applications must be scalable, multi-tenant aware and configurable. In this article, we show how the services in a service-oriented SaaS application can be deployed using different multi-tenancy patterns. We describe how services in different multi-tenancy patterns can be composed on the application level. In addition to that, we also describe how these multi-tenancy patterns can be applied to middleware and hardware components. We then show with some real world examples how the different multi-tenancy patterns can be combined.

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

Science.gov (United States)

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

2016-04-01

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

A multi-resolution approach to heat kernels on discrete surfaces

KAUST Repository

Vaxman, Amir; Ben-Chen, Mirela; Gotsman, Craig

2010-01-01

process - limits this type of analysis to 3D models of modest resolution. We show how to use the unique properties of the heat kernel of a discrete two dimensional manifold to overcome these limitations. Combining a multi-resolution approach with a novel

Multi-phase flow monitoring with electrical impedance tomography using level set based method

International Nuclear Information System (INIS)

Liu, Dong; Khambampati, Anil Kumar; Kim, Sin; Kim, Kyung Youn

2015-01-01

Highlights: • LSM has been used for shape reconstruction to monitor multi-phase flow using EIT. • Multi-phase level set model for conductivity is represented by two level set functions. • LSM handles topological merging and breaking naturally during evolution process. • To reduce the computational time, a narrowband technique was applied. • Use of narrowband and optimization approach results in efficient and fast method. - Abstract: In this paper, a level set-based reconstruction scheme is applied to multi-phase flow monitoring using electrical impedance tomography (EIT). The proposed scheme involves applying a narrowband level set method to solve the inverse problem of finding the interface between the regions having different conductivity values. The multi-phase level set model for the conductivity distribution inside the domain is represented by two level set functions. The key principle of the level set-based method is to implicitly represent the shape of interface as the zero level set of higher dimensional function and then solve a set of partial differential equations. The level set-based scheme handles topological merging and breaking naturally during the evolution process. It also offers several advantages compared to traditional pixel-based approach. Level set-based method for multi-phase flow is tested with numerical and experimental data. It is found that level set-based method has better reconstruction performance when compared to pixel-based method

Multi-level learning: improving the prediction of protein, domain and residue interactions by allowing information flow between levels

Directory of Open Access Journals (Sweden)

McDermott Drew

2009-08-01

Full Text Available Abstract Background Proteins interact through specific binding interfaces that contain many residues in domains. Protein interactions thus occur on three different levels of a concept hierarchy: whole-proteins, domains, and residues. Each level offers a distinct and complementary set of features for computationally predicting interactions, including functional genomic features of whole proteins, evolutionary features of domain families and physical-chemical features of individual residues. The predictions at each level could benefit from using the features at all three levels. However, it is not trivial as the features are provided at different granularity. Results To link up the predictions at the three levels, we propose a multi-level machine-learning framework that allows for explicit information flow between the levels. We demonstrate, using representative yeast interaction networks, that our algorithm is able to utilize complementary feature sets to make more accurate predictions at the three levels than when the three problems are approached independently. To facilitate application of our multi-level learning framework, we discuss three key aspects of multi-level learning and the corresponding design choices that we have made in the implementation of a concrete learning algorithm. 1 Architecture of information flow: we show the greater flexibility of bidirectional flow over independent levels and unidirectional flow; 2 Coupling mechanism of the different levels: We show how this can be accomplished via augmenting the training sets at each level, and discuss the prevention of error propagation between different levels by means of soft coupling; 3 Sparseness of data: We show that the multi-level framework compounds data sparsity issues, and discuss how this can be dealt with by building local models in information-rich parts of the data. Our proof-of-concept learning algorithm demonstrates the advantage of combining levels, and opens up

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

Science.gov (United States)

Liu, Min; Wang, Xueping; Zhang, Hongzhong

2018-03-01

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

Multi-stage decoding of multi-level modulation codes

Science.gov (United States)

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

1991-01-01

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

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

Science.gov (United States)

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

2014-01-01

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

Multi-criteria approach with linear combination technique and analytical hierarchy process in land evaluation studies

Directory of Open Access Journals (Sweden)

Orhan Dengiz

2018-01-01

Full Text Available Land evaluation analysis is a prerequisite to achieving optimum utilization of the available land resources. Lack of knowledge on best combination of factors that suit production of yields has contributed to the low production. The aim of this study was to determine the most suitable areas for agricultural uses. For that reasons, in order to determine land suitability classes of the study area, multi-criteria approach was used with linear combination technique and analytical hierarchy process by taking into consideration of some land and soil physico-chemical characteristic such as slope, texture, depth, derange, stoniness, erosion, pH, EC, CaCO3 and organic matter. These data and land mapping unites were taken from digital detailed soil map scaled as 1:5.000. In addition, in order to was produce land suitability map GIS was program used for the study area. This study was carried out at Mahmudiye, Karaamca, Yazılı, Çiçeközü, Orhaniye and Akbıyık villages in Yenişehir district of Bursa province. Total study area is 7059 ha. 6890 ha of total study area has been used as irrigated agriculture, dry farming agriculture, pasture while, 169 ha has been used for non-agricultural activities such as settlement, road water body etc. Average annual temperature and precipitation of the study area are 16.1oC and 1039.5 mm, respectively. Finally after determination of land suitability distribution classes for the study area, it was found that 15.0% of the study area has highly (S1 and moderately (S2 while, 85% of the study area has marginally suitable and unsuitable coded as S3 and N. It was also determined some relation as compared results of linear combination technique with other hierarchy approaches such as Land Use Capability Classification and Suitability Class for Agricultural Use methods.

Interconnected Levels of Multi-Stage Marketing

DEFF Research Database (Denmark)

Vedel, Mette; Geersbro, Jens; Ritter, Thomas

2012-01-01

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

A combined stochastic programming and optimal control approach to personal finance and pensions

DEFF Research Database (Denmark)

Konicz, Agnieszka Karolina; Pisinger, David; Rasmussen, Kourosh Marjani

2015-01-01

The paper presents a model that combines a dynamic programming (stochastic optimal control) approach and a multi-stage stochastic linear programming approach (SLP), integrated into one SLP formulation. Stochastic optimal control produces an optimal policy that is easy to understand and implement....

Combined multi-analytical approach for study of pore system in bricks: How much porosity is there?

Energy Technology Data Exchange (ETDEWEB)

Coletti, Chiara, E-mail: chiara.coletti@studenti.unipd.it [Department of Geosciences, University of Padova, Via G. Gradenigo 6, 35131 Padova (Italy); Department of Mineralogy and Petrology, Faculty of Science, University of Granada, Avda. Fuentenueva s/n, 18002 Granada (Spain); Cultrone, Giuseppe [Department of Mineralogy and Petrology, Faculty of Science, University of Granada, Avda. Fuentenueva s/n, 18002 Granada (Spain); Maritan, Lara; Mazzoli, Claudio [Department of Geosciences, University of Padova, Via G. Gradenigo 6, 35131 Padova (Italy)

2016-11-15

During the firing of bricks, mineralogical and textural transformations produce an artificial aggregate characterised by significant porosity. Particularly as regards pore-size distribution and the interconnection model, porosity is an important parameter to evaluate and predict the durability of bricks. The pore system is in fact the main element, which correlates building materials and their environment (especially in cases of aggressive weathering, e.g., salt crystallisation and freeze-thaw cycles) and determines their durability. Four industrial bricks with differing compositions and firing temperatures were analysed with “direct” and “indirect” techniques, traditional methods (mercury intrusion porosimetry, hydric tests, nitrogen adsorption) and new analytical approaches based on digital image reconstruction of 2D and 3D models (back-scattered electrons and computerised X-ray micro-Tomography, respectively). The comparison of results from different analytical methods in the “overlapping ranges” of porosity and the careful reconstruction of a cumulative curve, allowed overcoming their specific limitations and achieving better knowledge on the pore system of bricks. - Highlights: •Pore-size distribution and structure of the pore system in four commercial bricks •A multi-analytical approach combining “direct” and “indirect” techniques •Traditional methods vs. new approaches based on 2D/3D digital image reconstruction •The use of “overlapping ranges” to overcome the limitations of various techniques.

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

KAUST Repository

Castrillon, Julio

2015-11-10

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

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

Science.gov (United States)

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

2017-01-01

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

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

Science.gov (United States)

Yu, Rongjie; Abdel-Aty, Mohamed

2013-09-01

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

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

KAUST Repository

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

2015-01-01

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

Multi-level methods and approximating distribution functions

International Nuclear Information System (INIS)

Wilson, D.; Baker, R. E.

2016-01-01

Biochemical reaction networks are often modelled using discrete-state, continuous-time Markov chains. System statistics of these Markov chains usually cannot be calculated analytically and therefore estimates must be generated via simulation techniques. There is a well documented class of simulation techniques known as exact stochastic simulation algorithms, an example of which is Gillespie’s direct method. These algorithms often come with high computational costs, therefore approximate stochastic simulation algorithms such as the tau-leap method are used. However, in order to minimise the bias in the estimates generated using them, a relatively small value of tau is needed, rendering the computational costs comparable to Gillespie’s direct method. The multi-level Monte Carlo method (Anderson and Higham, Multiscale Model. Simul. 10:146–179, 2012) provides a reduction in computational costs whilst minimising or even eliminating the bias in the estimates of system statistics. This is achieved by first crudely approximating required statistics with many sample paths of low accuracy. Then correction terms are added until a required level of accuracy is reached. Recent literature has primarily focussed on implementing the multi-level method efficiently to estimate a single system statistic. However, it is clearly also of interest to be able to approximate entire probability distributions of species counts. We present two novel methods that combine known techniques for distribution reconstruction with the multi-level method. We demonstrate the potential of our methods using a number of examples.

Multi-level methods and approximating distribution functions

Energy Technology Data Exchange (ETDEWEB)

Wilson, D., E-mail: daniel.wilson@dtc.ox.ac.uk; Baker, R. E. [Mathematical Institute, University of Oxford, Radcliffe Observatory Quarter, Woodstock Road, Oxford, OX2 6GG (United Kingdom)

2016-07-15

Biochemical reaction networks are often modelled using discrete-state, continuous-time Markov chains. System statistics of these Markov chains usually cannot be calculated analytically and therefore estimates must be generated via simulation techniques. There is a well documented class of simulation techniques known as exact stochastic simulation algorithms, an example of which is Gillespie’s direct method. These algorithms often come with high computational costs, therefore approximate stochastic simulation algorithms such as the tau-leap method are used. However, in order to minimise the bias in the estimates generated using them, a relatively small value of tau is needed, rendering the computational costs comparable to Gillespie’s direct method. The multi-level Monte Carlo method (Anderson and Higham, Multiscale Model. Simul. 10:146–179, 2012) provides a reduction in computational costs whilst minimising or even eliminating the bias in the estimates of system statistics. This is achieved by first crudely approximating required statistics with many sample paths of low accuracy. Then correction terms are added until a required level of accuracy is reached. Recent literature has primarily focussed on implementing the multi-level method efficiently to estimate a single system statistic. However, it is clearly also of interest to be able to approximate entire probability distributions of species counts. We present two novel methods that combine known techniques for distribution reconstruction with the multi-level method. We demonstrate the potential of our methods using a number of examples.

Generating multi-double-scroll attractors via nonautonomous approach.

Science.gov (United States)

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

2016-08-01

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

Tile-Level Annotation of Satellite Images Using Multi-Level Max-Margin Discriminative Random Field

Directory of Open Access Journals (Sweden)

Hong Sun

2013-05-01

Full Text Available This paper proposes a multi-level max-margin discriminative analysis (M3DA framework, which takes both coarse and fine semantics into consideration, for the annotation of high-resolution satellite images. In order to generate more discriminative topic-level features, the M3DA uses the maximum entropy discrimination latent Dirichlet Allocation (MedLDA model. Moreover, for improving the spatial coherence of visual words neglected by M3DA, conditional random field (CRF is employed to optimize the soft label field composed of multiple label posteriors. The framework of M3DA enables one to combine word-level features (generated by support vector machines and topic-level features (generated by MedLDA via the bag-of-words representation. The experimental results on high-resolution satellite images have demonstrated that, using the proposed method can not only obtain suitable semantic interpretation, but also improve the annotation performance by taking into account the multi-level semantics and the contextual information.

Investigating the Group-Level Impact of Advanced Dual-Echo fMRI Combinations

Directory of Open Access Journals (Sweden)

Adam Kettinger

2016-12-01

Full Text Available Multi-echo fMRI data acquisition has been widely investigated and suggested to optimize sensitivity for detecting the BOLD signal. Several methods have also been proposed for the combination of data with different echo times. The aim of the present study was to investigate how these advance echo combination methods provide advantages over the simple averaging of echoes when state-of-the-art group-level random-effect analyses are performed. Both resting-state and task-based dual-echo fMRI data were collected from 27 healthy adult individuals (14 male, mean age = 25.75 years using standard echo-planar acquisition methods at 3T. Both resting-state and task-based data were subjected to a standard image pre-processing pipeline. Subsequently the two echoes were combined as a weighted average, using four different strategies for calculating the weights: (1 simple arithmetic averaging, (2 BOLD sensitivity weighting, (3 temporal-signal-to-noise ratio weighting and (4 temporal BOLD sensitivity weighting. Our results clearly show that the simple averaging of data with the different echoes is sufficient. Advanced echo combination methods may provide advantages on a single-subject level but when considering random-effects group level statistics they provide no benefit regarding sensitivity (i.e. group-level t-values compared to the simple echo-averaging approach. One possible reason for the lack of clear advantages may be that apart from increasing the average BOLD sensitivity at the single-subject level, the advanced weighted averaging methods also inflate the inter-subject variance. As the echo combination methods provide very similar results, the recommendation is to choose between them depending on the availability of time for collecting additional resting-state data or whether subject-level or group-level analyses are planned.

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

Science.gov (United States)

Lee, Jongpil; Nam, Juhan

2017-08-01

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

Multi-stage decoding for multi-level block modulation codes

Science.gov (United States)

Lin, Shu

1991-01-01

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

Multi level configuration of ETO products

DEFF Research Database (Denmark)

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

2007-01-01

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

A single-phase multi-level D-STATCOM inverter using modular multi-level converter (MMC) topology for renewable energy sources

Science.gov (United States)

Sotoodeh, Pedram

This dissertation presents the design of a novel multi-level inverter with FACTS capability for small to mid-size (10-20kW) permanent-magnet wind installations using modular multi-level converter (MMC) topology. The aim of the work is to design a new type of inverter with D-STATCOM option to provide utilities with more control on active and reactive power transfer of distribution lines. The inverter is placed between the renewable energy source, specifically a wind turbine, and the distribution grid in order to fix the power factor of the grid at a target value, regardless of wind speed, by regulating active and reactive power required by the grid. The inverter is capable of controlling active and reactive power by controlling the phase angle and modulation index, respectively. The unique contribution of the proposed work is to combine the two concepts of inverter and D-STATCOM using a novel voltage source converter (VSC) multi-level topology in a single unit without additional cost. Simulations of the proposed inverter, with 5 and 11 levels, have been conducted in MATLAB/Simulink for two systems including 20 kW/kVAR and 250 W/VAR. To validate the simulation results, a scaled version (250 kW/kVAR) of the proposed inverter with 5 and 11 levels has been built and tested in the laboratory. Experimental results show that the reduced-scale 5- and 11-level inverter is able to fix PF of the grid as well as being compatible with IEEE standards. Furthermore, total cost of the prototype models, which is one of the major objectives of this research, is comparable with market prices.

Fuzzy Multi-objective Linear Programming Approach

Directory of Open Access Journals (Sweden)

Amna Rehmat

2007-07-01

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

Combining on-hardware prototyping and high-level simulation for DSE of multi-ASIP systems

NARCIS (Netherlands)

Meloni, P.; Pomata, S.; Raffo, L.; Piscitelli, R.; Pimentel, A.D.; McAllister, J.; Bhattacharyya, S.

2012-01-01

Modern heterogeneous multi-processor embedded systems very often expose to the designer a large number of degrees of freedom, related to the application partitioning/mapping and to the component- and system-level architecture composition. The number is even larger when the designer targets systems

Generating multi-double-scroll attractors via nonautonomous approach

Energy Technology Data Exchange (ETDEWEB)

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

2016-08-15

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

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

Science.gov (United States)

Wang, Bao-Zhen; Chen, Zhi

2013-01-01

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

Multi-Level Secure Local Area Network

OpenAIRE

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

2011-01-01

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

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

Science.gov (United States)

Zhu, Yanhan; Ye, Jian

2012-01-01

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

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

Directory of Open Access Journals (Sweden)

Beatrice Scholtes

2015-12-01

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

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

CSIR Research Space (South Africa)

Brown, Dane

2016-09-01

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

The Multi-Scale Model Approach to Thermohydrology at Yucca Mountain

International Nuclear Information System (INIS)

Glascoe, L; Buscheck, T A; Gansemer, J; Sun, Y

2002-01-01

The Multi-Scale Thermo-Hydrologic (MSTH) process model is a modeling abstraction of them1 hydrology (TH) of the potential Yucca Mountain repository at multiple spatial scales. The MSTH model as described herein was used for the Supplemental Science and Performance Analyses (BSC, 2001) and is documented in detail in CRWMS M and O (2000) and Glascoe et al. (2002). The model has been validated to a nested grid model in Buscheck et al. (In Review). The MSTH approach is necessary for modeling thermal hydrology at Yucca Mountain for two reasons: (1) varying levels of detail are necessary at different spatial scales to capture important TH processes and (2) a fully-coupled TH model of the repository which includes the necessary spatial detail is computationally prohibitive. The MSTH model consists of six ''submodels'' which are combined in a manner to reduce the complexity of modeling where appropriate. The coupling of these models allows for appropriate consideration of mountain-scale thermal hydrology along with the thermal hydrology of drift-scale discrete waste packages of varying heat load. Two stages are involved in the MSTH approach, first, the execution of submodels, and second, the assembly of submodels using the Multi-scale Thermohydrology Abstraction Code (MSTHAC). MSTHAC assembles the submodels in a five-step process culminating in the TH model output of discrete waste packages including a mountain-scale influence

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

DEFF Research Database (Denmark)

Micconi, Laura

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

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

Data.gov (United States)

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

Nanotechnology-based combinational drug delivery: an emerging approach for cancer therapy.

Science.gov (United States)

Parhi, Priyambada; Mohanty, Chandana; Sahoo, Sanjeeb Kumar

2012-09-01

Combination therapy for the treatment of cancer is becoming more popular because it generates synergistic anticancer effects, reduces individual drug-related toxicity and suppresses multi-drug resistance through different mechanisms of action. In recent years, nanotechnology-based combination drug delivery to tumor tissues has emerged as an effective strategy by overcoming many biological, biophysical and biomedical barriers that the body stages against successful delivery of anticancer drugs. The sustained, controlled and targeted delivery of chemotherapeutic drugs in a combination approach enhanced therapeutic anticancer effects with reduced drug-associated side effects. In this article, we have reviewed the scope of various nanotechnology-based combination drug delivery approaches and also summarized the current perspective and challenges facing the successful treatment of cancer. Copyright © 2012 Elsevier Ltd. All rights reserved.

Modeling activity recognition of multi resident using label combination of multi label classification in smart home

Science.gov (United States)

Mohamed, Raihani; Perumal, Thinagaran; Sulaiman, Md Nasir; Mustapha, Norwati; Zainudin, M. N. Shah

2017-10-01

Pertaining to the human centric concern and non-obtrusive way, the ambient sensor type technology has been selected, accepted and embedded in the environment in resilient style. Human activities, everyday are gradually becoming complex and thus complicate the inferences of activities when it involving the multi resident in the same smart environment. Current works solutions focus on separate model between the resident, activities and interactions. Some study use data association and extra auxiliary of graphical nodes to model human tracking information in an environment and some produce separate framework to incorporate the auxiliary for interaction feature model. Thus, recognizing the activities and which resident perform the activity at the same time in the smart home are vital for the smart home development and future applications. This paper will cater the above issue by considering the simplification and efficient method using the multi label classification framework. This effort eliminates time consuming and simplifies a lot of pre-processing tasks comparing with previous approach. Applications to the multi resident multi label learning in smart home problems shows the LC (Label Combination) using Decision Tree (DT) as base classifier can tackle the above problems.

On combining multi-normalization and ancillary measures for the optimal score level fusion of fingerprint and voice biometrics

Science.gov (United States)

Mohammed Anzar, Sharafudeen Thaha; Sathidevi, Puthumangalathu Savithri

2014-12-01

In this paper, we have considered the utility of multi-normalization and ancillary measures, for the optimal score level fusion of fingerprint and voice biometrics. An efficient matching score preprocessing technique based on multi-normalization is employed for improving the performance of the multimodal system, under various noise conditions. Ancillary measures derived from the feature space and the score space are used in addition to the matching score vectors, for weighing the modalities, based on their relative degradation. Reliability (dispersion) and the separability (inter-/intra-class distance and d-prime statistics) measures under various noise conditions are estimated from the individual modalities, during the training/validation stage. The `best integration weights' are then computed by algebraically combining these measures using the weighted sum rule. The computed integration weights are then optimized against the recognition accuracy using techniques such as grid search, genetic algorithm and particle swarm optimization. The experimental results show that, the proposed biometric solution leads to considerable improvement in the recognition performance even under low signal-to-noise ratio (SNR) conditions and reduces the false acceptance rate (FAR) and false rejection rate (FRR), making the system useful for security as well as forensic applications.

Incorporating a multi-criteria decision procedure into the combined dynamic programming/production simulation algorithm for generation expansion planning

International Nuclear Information System (INIS)

Yang, H.T.; Chen, S.L.

1989-01-01

A multi-objective optimization approach to generation expansion planning is presented. The approach is designed by adding a new multi-criteria decision (MCD) procedure to the conventional algorithm which combines dynamic programming with production simulation method. The MCD procedure can help decision makers weight the relative importance of multiple attributes associated with the decision alternatives, and find the near-best compromise solution efficiently at each optimization step of the conventional algorithm. Practical application of proposed approach to feasibility evaluation of the fourth nuclear power plant of Tawian is also presented, demonstrating the effectiveness and limitations of the approach

Multi-level and hybrid modelling approaches for systems biology.

Science.gov (United States)

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

2017-01-01

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

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

Directory of Open Access Journals (Sweden)

Marko Budinich

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

A Container-based Trusted Multi-level Security Mechanism

Directory of Open Access Journals (Sweden)

Li Xiao-Yong

2017-01-01

Full Text Available Multi-level security mechanism has been widely applied in the military, government, defense and other domains in which information is required to be divided by security-level. Through this type of security mechanism, users at different security levels are provided with information at corresponding security levels. Traditional multi-level security mechanism which depends on the safety of operating system finally proved to be not practical. We propose a container-based trusted multi-level security mechanism in this paper to improve the applicability of the multi-level mechanism. It guarantees multi-level security of the system through a set of multi-level security policy rules and trusted techniques. The technical feasibility and application scenarios are also discussed. The ease of realization, strong practical significance and low cost of our method will largely expand the application of multi-level security mechanism in real life.

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

Science.gov (United States)

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

2016-04-01

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

Three essays on multi-level optimization models and applications

Science.gov (United States)

Rahdar, Mohammad

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

Multi-Level Model

Directory of Open Access Journals (Sweden)

Constanta Nicoleta BODEA

2008-01-01

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

A Multi-Model Approach for System Diagnosis

DEFF Research Database (Denmark)

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

2007-01-01

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

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

National Research Council Canada - National Science Library

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

2003-01-01

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

Non-linear interactions of multi-level atoms with a near-resonant standing wave

International Nuclear Information System (INIS)

O'Kane, T.J.; Scholten, R.E.; Walkiewicz, M.R.; Farrell, P.M.

1998-01-01

Using a semiclassical density matrix formalism we have calculated the behavior of multi-level atoms interacting with a standing wave field, and show how complex non-linear phenomena, including multi-photon effects, combine to produce saturation spectra as observed in experiments. We consider both 20-level sodium and 24-level rubidium models, contrasting these with a simple 2-level case. The influence of parameters such as atomic trajectory and the time the atom remains in the beam are shown to have a critical effect on the lineshape of these resonances and the emission/absorption processes. Stable oscillations in the excited state populations for both the two-level and multi-level cases are shown to be limit cycles. These limit cycles undergo period doubling as the system evolves into chaos. Finally, using a Monte Carlo treatment, these processes average to produce saturated absorption spectra complete with power and Doppler broadening effects consistent with experiment. (authors)

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

Science.gov (United States)

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

2017-10-01

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

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

Directory of Open Access Journals (Sweden)

Esther Mwangi

2012-08-01

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

Information rich mapping requirement to product architecture through functional system deployment: The multi entity domain approach

DEFF Research Database (Denmark)

Hauksdóttir, Dagný; Mortensen, Niels Henrik

2017-01-01

may impede the ability to evolve, maintain or reuse systems. In this paper the Multi Entity Domain Approach (MEDA) is presented. The approach combines different design information within the domain views, incorporates both Software and Hardware design and supports iterative requirements definition...

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

Science.gov (United States)

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

2013-10-01

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

Coupled multi-physics simulation frameworks for reactor simulation: A bottom-up approach

International Nuclear Information System (INIS)

Tautges, Timothy J.; Caceres, Alvaro; Jain, Rajeev; Kim, Hong-Jun; Kraftcheck, Jason A.; Smith, Brandon M.

2011-01-01

A 'bottom-up' approach to multi-physics frameworks is described, where first common interfaces to simulation data are developed, then existing physics modules are adapted to communicate through those interfaces. Physics modules read and write data through those common interfaces, which also provide access to common simulation services like parallel IO, mesh partitioning, etc.. Multi-physics codes are assembled as a combination of physics modules, services, interface implementations, and driver code which coordinates calling these various pieces. Examples of various physics modules and services connected to this framework are given. (author)

Multi-level predictive maintenance for multi-component systems

International Nuclear Information System (INIS)

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

2015-01-01

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

A multi-objective approach for developing national energy efficiency plans

International Nuclear Information System (INIS)

Haydt, Gustavo; Leal, Vítor; Dias, Luís

2014-01-01

This paper proposes a new approach to deal with the problem of building national energy efficiency (EE) plans, considering multiple objectives instead of only energy savings. The objectives considered are minimizing the influence of energy use on climate change, minimizing the financial risk from the investment, maximizing the security of energy supply, minimizing investment costs, minimizing the impacts of building new power plants and transmission infrastructures, and maximizing the local air quality. These were identified through literature review and interaction with real decision makers. A database of measures is established, from which millions of potential EE plans can be built by combining measures and their respective degree of implementation. Finally, a hybrid multi-objective and multi-criteria decision analysis (MCDA) model is proposed to search and select the EE plans that best match the decision makers’ preferences. An illustration of the working mode and the type of results obtained from this novel hybrid model is provided through an application to Portugal. For each of five decision perspectives a wide range of potential best plans were identified. These wide ranges show the relevance of introducing multi-objective analysis in a comprehensive search space as a tool to inform decisions about national EE plans. - Highlights: • A multiple objective approach to aid the choice of national energy efficiency plans. • A hybrid multi-objective MCDA model is proposed to search among the possible plans. • The model identified relevant plans according to five different idealized DMs. • The approach is tested with Portugal

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

Science.gov (United States)

Ayadi, Omar; Felfel, Houssem; Masmoudi, Faouzi

2017-07-01

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

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

NARCIS (Netherlands)

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

2017-01-01

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

Multi-level molecular modelling for plasma medicine

International Nuclear Information System (INIS)

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

2016-01-01

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

A new multi-objective reserve constrained combined heat and power dynamic economic emission dispatch

International Nuclear Information System (INIS)

Niknam, Taher; Azizipanah-Abarghooee, Rasoul; Roosta, Alireza; Amiri, Babak

2012-01-01

Combined heat and power units are playing an ever increasing role in conventional power stations due to advantages such as reduced emissions and operational cost savings. This paper investigates a more practical formulation of the complex non-convex, non-smooth and non-linear multi-objective dynamic economic emission dispatch that incorporates combined heat and power units. Integrating these types of units, and their power ramp constraints, require an efficient tool to cope with the joint characteristics of power and heat. Unlike previous approaches, the spinning reserve requirements of this system are clearly formulated in the problem. In this way, a new multi-objective optimisation based on an enhanced firefly algorithm is proposed to achieve a set of non-dominated (Pareto-optimal) solutions. A new tuning parameter based on a chaotic mechanism and novel self adaptive probabilistic mutation strategies are used to improve the overall performance of the algorithm. The numerical results demonstrate how the proposed framework was applied in real time studies. -- Highlights: ► Investigate a practical formulation of the DEED (Dynamic Economic Emission Dispatch). ► Consider combined heat and power units. ► Consider power ramp constraints. ► Consider the system spinning reserve requirements. ► Present a new multi-objective optimization firefly.

An integrated approach for multi-level sample size determination

International Nuclear Information System (INIS)

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

1997-01-01

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

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

Directory of Open Access Journals (Sweden)

Chunhui Chen

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

A computational intelligent approach to multi-factor analysis of violent crime information system

Science.gov (United States)

Liu, Hongbo; Yang, Chao; Zhang, Meng; McLoone, Seán; Sun, Yeqing

2017-02-01

Various scientific studies have explored the causes of violent behaviour from different perspectives, with psychological tests, in particular, applied to the analysis of crime factors. The relationship between bi-factors has also been extensively studied including the link between age and crime. In reality, many factors interact to contribute to criminal behaviour and as such there is a need to have a greater level of insight into its complex nature. In this article we analyse violent crime information systems containing data on psychological, environmental and genetic factors. Our approach combines elements of rough set theory with fuzzy logic and particle swarm optimisation to yield an algorithm and methodology that can effectively extract multi-knowledge from information systems. The experimental results show that our approach outperforms alternative genetic algorithm and dynamic reduct-based techniques for reduct identification and has the added advantage of identifying multiple reducts and hence multi-knowledge (rules). Identified rules are consistent with classical statistical analysis of violent crime data and also reveal new insights into the interaction between several factors. As such, the results are helpful in improving our understanding of the factors contributing to violent crime and in highlighting the existence of hidden and intangible relationships between crime factors.

FEM × DEM: a new efficient multi-scale approach for geotechnical problems with strain localization

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Nguyen Trung Kien

2017-01-01

Full Text Available The paper presents a multi-scale modeling of Boundary Value Problem (BVP approach involving cohesive-frictional granular materials in the FEM × DEM multi-scale framework. On the DEM side, a 3D model is defined based on the interactions of spherical particles. This DEM model is built through a numerical homogenization process applied to a Volume Element (VE. It is then paired with a Finite Element code. Using this numerical tool that combines two scales within the same framework, we conducted simulations of biaxial and pressuremeter tests on a cohesive-frictional granular medium. In these cases, it is known that strain localization does occur at the macroscopic level, but since FEMs suffer from severe mesh dependency as soon as shear band starts to develop, the second gradient regularization technique has been used. As a consequence, the objectivity of the computation with respect to mesh dependency is restored.

Power magnetic devices a multi-objective design approach

CERN Document Server

Sudhoff, Scott D

2014-01-01

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

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

Directory of Open Access Journals (Sweden)

Junjun Yin

2016-10-01

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

Time-dependent evolution of rock slopes by a multi-modelling approach

Science.gov (United States)

Bozzano, F.; Della Seta, M.; Martino, S.

2016-06-01

This paper presents a multi-modelling approach that incorporates contributions from morpho-evolutionary modelling, detailed engineering-geological modelling and time-dependent stress-strain numerical modelling to analyse the rheological evolution of a river valley slope over approximately 102 kyr. The slope is located in a transient, tectonically active landscape in southwestern Tyrrhenian Calabria (Italy), where gravitational processes drive failures in rock slopes. Constraints on the valley profile development were provided by a morpho-evolutionary model based on the correlation of marine and river strath terraces. Rock mass classes were identified through geomechanical parameters that were derived from engineering-geological surveys and outputs of a multi-sensor slope monitoring system. The rock mass classes were associated to lithotechnical units to obtain a high-resolution engineering-geological model along a cross section of the valley. Time-dependent stress-strain numerical modelling reproduced the main morpho-evolutionary stages of the valley slopes. The findings demonstrate that a complex combination of eustatism, uplift and Mass Rock Creep (MRC) deformations can lead to first-time failures of rock slopes when unstable conditions are encountered up to the generation of stress-controlled shear zones. The multi-modelling approach enabled us to determine that such complex combinations may have been sufficient for the first-time failure of the S. Giovanni slope at approximately 140 ka (MIS 7), even without invoking any trigger. Conversely, further reactivations of the landslide must be related to triggers such as earthquakes, rainfall and anthropogenic activities. This failure involved a portion of the slope where a plasticity zone resulted from mass rock creep that evolved with a maximum strain rate of 40% per thousand years, after the formation of a river strath terrace. This study demonstrates that the multi-modelling approach presented herein is a useful

MKEM: a Multi-level Knowledge Emergence Model for mining undiscovered public knowledge

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Song Min

2010-04-01

Full Text Available Abstract Background Since Swanson proposed the Undiscovered Public Knowledge (UPK model, there have been many approaches to uncover UPK by mining the biomedical literature. These earlier works, however, required substantial manual intervention to reduce the number of possible connections and are mainly applied to disease-effect relation. With the advancement in biomedical science, it has become imperative to extract and combine information from multiple disjoint researches, studies and articles to infer new hypotheses and expand knowledge. Methods We propose MKEM, a Multi-level Knowledge Emergence Model, to discover implicit relationships using Natural Language Processing techniques such as Link Grammar and Ontologies such as Unified Medical Language System (UMLS MetaMap. The contribution of MKEM is as follows: First, we propose a flexible knowledge emergence model to extract implicit relationships across different levels such as molecular level for gene and protein and Phenomic level for disease and treatment. Second, we employ MetaMap for tagging biological concepts. Third, we provide an empirical and systematic approach to discover novel relationships. Results We applied our system on 5000 abstracts downloaded from PubMed database. We performed the performance evaluation as a gold standard is not yet available. Our system performed with a good precision and recall and we generated 24 hypotheses. Conclusions Our experiments show that MKEM is a powerful tool to discover hidden relationships residing in extracted entities that were represented by our Substance-Effect-Process-Disease-Body Part (SEPDB model.

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

DEFF Research Database (Denmark)

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

2017-01-01

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

[A cloud detection algorithm for MODIS images combining Kmeans clustering and multi-spectral threshold method].

Science.gov (United States)

Wang, Wei; Song, Wei-Guo; Liu, Shi-Xing; Zhang, Yong-Ming; Zheng, Hong-Yang; Tian, Wei

2011-04-01

An improved method for detecting cloud combining Kmeans clustering and the multi-spectral threshold approach is described. On the basis of landmark spectrum analysis, MODIS data is categorized into two major types initially by Kmeans method. The first class includes clouds, smoke and snow, and the second class includes vegetation, water and land. Then a multi-spectral threshold detection is applied to eliminate interference such as smoke and snow for the first class. The method is tested with MODIS data at different time under different underlying surface conditions. By visual method to test the performance of the algorithm, it was found that the algorithm can effectively detect smaller area of cloud pixels and exclude the interference of underlying surface, which provides a good foundation for the next fire detection approach.

A novel method for a multi-level hierarchical composite with brick-and-mortar structure.

Science.gov (United States)

Brandt, Kristina; Wolff, Michael F H; Salikov, Vitalij; Heinrich, Stefan; Schneider, Gerold A

2013-01-01

The fascination for hierarchically structured hard tissues such as enamel or nacre arises from their unique structure-properties-relationship. During the last decades this numerously motivated the synthesis of composites, mimicking the brick-and-mortar structure of nacre. However, there is still a lack in synthetic engineering materials displaying a true hierarchical structure. Here, we present a novel multi-step processing route for anisotropic 2-level hierarchical composites by combining different coating techniques on different length scales. It comprises polymer-encapsulated ceramic particles as building blocks for the first level, followed by spouted bed spray granulation for a second level, and finally directional hot pressing to anisotropically consolidate the composite. The microstructure achieved reveals a brick-and-mortar hierarchical structure with distinct, however not yet optimized mechanical properties on each level. It opens up a completely new processing route for the synthesis of multi-level hierarchically structured composites, giving prospects to multi-functional structure-properties relationships.

A novel method for a multi-level hierarchical composite with brick-and-mortar structure

Science.gov (United States)

Brandt, Kristina; Wolff, Michael F. H.; Salikov, Vitalij; Heinrich, Stefan; Schneider, Gerold A.

2013-07-01

The fascination for hierarchically structured hard tissues such as enamel or nacre arises from their unique structure-properties-relationship. During the last decades this numerously motivated the synthesis of composites, mimicking the brick-and-mortar structure of nacre. However, there is still a lack in synthetic engineering materials displaying a true hierarchical structure. Here, we present a novel multi-step processing route for anisotropic 2-level hierarchical composites by combining different coating techniques on different length scales. It comprises polymer-encapsulated ceramic particles as building blocks for the first level, followed by spouted bed spray granulation for a second level, and finally directional hot pressing to anisotropically consolidate the composite. The microstructure achieved reveals a brick-and-mortar hierarchical structure with distinct, however not yet optimized mechanical properties on each level. It opens up a completely new processing route for the synthesis of multi-level hierarchically structured composites, giving prospects to multi-functional structure-properties relationships.

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

Science.gov (United States)

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.

Dry Port Location Problem: A Hybrid Multi-Criteria Approach

Directory of Open Access Journals (Sweden)

BENTALEB Fatimazahra

2016-03-01

Full Text Available Choosing a location for a dry port is a problem which becomes more essential and crucial. This study deals with the problem of locating dry ports. On this matter, a model combining multi-criteria (MACBETH and mono-criteria (BARYCENTER methods to find a solution to dry port location problem has been proposed. In the first phase, a systematic literature review was carried out on dry port location problem and then a methodological classification was presented for this research. In the second phase, a hybrid multi-criteria approach was developed in order to determine the best dry port location taking different criteria into account. A Computational practice and a qualitative analysis from a case study in the Moroccan context have been provided. The results show that the optimal location is very convenient with the geographical region and the government policies.

A multi-model ensemble approach to seabed mapping

Science.gov (United States)

Diesing, Markus; Stephens, David

2015-06-01

Seabed habitat mapping based on swath acoustic data and ground-truth samples is an emergent and active marine science discipline. Significant progress could be achieved by transferring techniques and approaches that have been successfully developed and employed in such fields as terrestrial land cover mapping. One such promising approach is the multiple classifier system, which aims at improving classification performance by combining the outputs of several classifiers. Here we present results of a multi-model ensemble applied to multibeam acoustic data covering more than 5000 km2 of seabed in the North Sea with the aim to derive accurate spatial predictions of seabed substrate. A suite of six machine learning classifiers (k-Nearest Neighbour, Support Vector Machine, Classification Tree, Random Forest, Neural Network and Naïve Bayes) was trained with ground-truth sample data classified into seabed substrate classes and their prediction accuracy was assessed with an independent set of samples. The three and five best performing models were combined to classifier ensembles. Both ensembles led to increased prediction accuracy as compared to the best performing single classifier. The improvements were however not statistically significant at the 5% level. Although the three-model ensemble did not perform significantly better than its individual component models, we noticed that the five-model ensemble did perform significantly better than three of the five component models. A classifier ensemble might therefore be an effective strategy to improve classification performance. Another advantage is the fact that the agreement in predicted substrate class between the individual models of the ensemble could be used as a measure of confidence. We propose a simple and spatially explicit measure of confidence that is based on model agreement and prediction accuracy.

All-fiber 7x1 signal combiner for incoherent laser beam combining

DEFF Research Database (Denmark)

Noordegraaf, Danny; Maack, Martin D.; Skovgaard, Peter M. W.

2011-01-01

We demonstrate an all-fiber 7x1 signal combiner for incoherent laser beam combining. This is a potential key component for reaching several kW of stabile laser output power. The combiner couples the output from 7 single-mode (SM) fiber lasers into a single multi-mode (MM) fiber. The input signal ...... in device temperature is observed. At an intermediate power level of 600 W a beam parameter product (BPP) of 2.22 mm x mrad is measured, corresponding to an M2 value of 6.5. These values are approaching the theoretical limit dictated by brightness conservation....

Computational Identification of Potential Multi-drug Combinations for Reduction of Microglial Inflammation in Alzheimer Disease

Directory of Open Access Journals (Sweden)

Thomas J. Anastasio

2015-06-01

Full Text Available Like other neurodegenerative diseases, Alzheimer Disease (AD has a prominent inflammatory component mediated by brain microglia. Reducing microglial inflammation could potentially halt or at least slow the neurodegenerative process. A major challenge in the development of treatments targeting brain inflammation is the sheer complexity of the molecular mechanisms that determine whether microglia become inflammatory or take on a more neuroprotective phenotype. The process is highly multifactorial, raising the possibility that a multi-target/multi-drug strategy could be more effective than conventional monotherapy. This study takes a computational approach in finding combinations of approved drugs that are potentially more effective than single drugs in reducing microglial inflammation in AD. This novel approach exploits the distinct advantages of two different computer programming languages, one imperative and the other declarative. Existing programs written in both languages implement the same model of microglial behavior, and the input/output relationships of both programs agree with each other and with data on microglia over an extensive test battery. Here the imperative program is used efficiently to screen the model for the most efficacious combinations of 10 drugs, while the declarative program is used to analyze in detail the mechanisms of action of the most efficacious combinations. Of the 1024 possible drug combinations, the simulated screen identifies only 7 that are able to move simulated microglia at least 50% of the way from a neurotoxic to a neuroprotective phenotype. Subsequent analysis shows that of the 7 most efficacious combinations, 2 stand out as superior both in strength and reliability. The model offers many experimentally testable and therapeutically relevant predictions concerning effective drug combinations and their mechanisms of action.

Computational identification of potential multi-drug combinations for reduction of microglial inflammation in Alzheimer disease.

Science.gov (United States)

Anastasio, Thomas J

2015-01-01

Like other neurodegenerative diseases, Alzheimer Disease (AD) has a prominent inflammatory component mediated by brain microglia. Reducing microglial inflammation could potentially halt or at least slow the neurodegenerative process. A major challenge in the development of treatments targeting brain inflammation is the sheer complexity of the molecular mechanisms that determine whether microglia become inflammatory or take on a more neuroprotective phenotype. The process is highly multifactorial, raising the possibility that a multi-target/multi-drug strategy could be more effective than conventional monotherapy. This study takes a computational approach in finding combinations of approved drugs that are potentially more effective than single drugs in reducing microglial inflammation in AD. This novel approach exploits the distinct advantages of two different computer programming languages, one imperative and the other declarative. Existing programs written in both languages implement the same model of microglial behavior, and the input/output relationships of both programs agree with each other and with data on microglia over an extensive test battery. Here the imperative program is used efficiently to screen the model for the most efficacious combinations of 10 drugs, while the declarative program is used to analyze in detail the mechanisms of action of the most efficacious combinations. Of the 1024 possible drug combinations, the simulated screen identifies only 7 that are able to move simulated microglia at least 50% of the way from a neurotoxic to a neuroprotective phenotype. Subsequent analysis shows that of the 7 most efficacious combinations, 2 stand out as superior both in strength and reliability. The model offers many experimentally testable and therapeutically relevant predictions concerning effective drug combinations and their mechanisms of action.

Combining landscape-level conservation planning and biodiversity offset programs: a case study.

Science.gov (United States)

Underwood, Jared G

2011-01-01

Habitat loss is a major factor in the endangerment and extinction of species around the world. One promising strategy to balance continued habitat loss and biodiversity conservation is that of biodiversity offsets. However, a major concern with offset programs is their consistency with landscape-level conservation goals. While merging offset policies and landscape-level conservation planning is thought to provide advantages over a traditional disconnected approach, few such landscape-level conservation-offset plans have been designed and implemented, so the effectiveness of such a strategy remains uncertain. In this study, we quantitatively assess the conservation impact of combining landscape-level conservation planning and biodiversity offset programs by comparing regions of San Diego County, USA with the combined approach to regions with only an offset program. This comparison is generally very difficult due to a variety of complicating factors. We overcome these complications and quantify the benefits to rare and threatened species of implementing a combined approach by assessing the amount of each species' predicted distribution, and the number of documented locations, conserved in comparison to the same metric for areas with an offset policy alone. We found that adoption of the combined approach has increased conservation for many rare species, often 5-10 times more than in the comparison area, and that conservation has been focused in the areas most important for these species. The level of conservation achieved reduces uncertainty that these species will persist in the region into the future. This San Diego County example demonstrates the potential benefits of combining landscape-level conservation planning and biodiversity offset programs.

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

Science.gov (United States)

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

2017-09-01

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

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

KAUST Repository

Ponto, Kevin

2011-06-01

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

EGSIEM combination service: combination of GRACE monthly K-band solutions on normal equation level

Science.gov (United States)

Meyer, Ulrich; Jean, Yoomin; Arnold, Daniel; Jäggi, Adrian

2017-04-01

The European Gravity Service for Improved Emergency Management (EGSIEM) project offers a scientific combination service, combining for the first time monthly GRACE gravity fields of different analysis centers (ACs) on normal equation (NEQ) level and thus taking all correlations between the gravity field coefficients and pre-eliminated orbit and instrument parameters correctly into account. Optimal weights for the individual NEQs are commonly derived by variance component estimation (VCE), as is the case for the products of the International VLBI Service (IVS) or the DTRF2008 reference frame realisation that are also derived by combination on NEQ-level. But variance factors are based on post-fit residuals and strongly depend on observation sampling and noise modeling, which both are very diverse in case of the individual EGSIEM ACs. These variance factors do not necessarily represent the true error levels of the estimated gravity field parameters that are still governed by analysis noise. We present a combination approach where weights are derived on solution level, thereby taking the analysis noise into account.

MultiDrizzle: An Integrated Pyraf Script for Registering, Cleaning and Combining Images

Science.gov (United States)

Koekemoer, A. M.; Fruchter, A. S.; Hook, R. N.; Hack, W.

We present the new PyRAF-based `MultiDrizzle' script, which is aimed at providing a one-step approach to combining dithered HST images. The purpose of this script is to allow easy interaction with the complex suite of tasks in the IRAF/STSDAS `dither' package, as well as the new `PyDrizzle' task, while at the same time retaining the flexibility of these tasks through a number of parameters. These parameters control the various individual steps, such as sky subtraction, image registration, `drizzling' onto separate output images, creation of a clean median image, transformation of the median with `blot' and creation of cosmic ray masks, as well as the final image combination step using `drizzle'. The default parameters of all the steps are set so that the task will work automatically for a wide variety of different types of images, while at the same time allowing adjustment of individual parameters for special cases. The script currently works for both ACS and WFPC2 data, and is now being tested on STIS and NICMOS images. We describe the operation of the script and the effect of various parameters, particularly in the context of combining images from dithered observations using ACS and WFPC2. Additional information is also available at the `MultiDrizzle' home page: http://www.stsci.edu/~koekemoe/multidrizzle/

Multi-Level Determinants of Parasitic Fly Infection in Forest Passerines

Science.gov (United States)

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

2013-01-01

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

Using a multi-scale approach to identify and quantify oil and gas emissions: a case study for GHG emissions verification

Science.gov (United States)

Sweeney, C.; Kort, E. A.; Rella, C.; Conley, S. A.; Karion, A.; Lauvaux, T.; Frankenberg, C.

2015-12-01

Along with a boom in oil and natural gas production in the US, there has been a substantial effort to understand the true environmental impact of these operations on air and water quality, as well asnet radiation balance. This multi-institution effort funded by both governmental and non-governmental agencies has provided a case study for identification and verification of emissions using a multi-scale, top-down approach. This approach leverages a combination of remote sensing to identify areas that need specific focus and airborne in-situ measurements to quantify both regional and large- to mid-size single-point emitters. Ground-based networks of mobile and stationary measurements provide the bottom tier of measurements from which process-level information can be gathered to better understand the specific sources and temporal distribution of the emitters. The motivation for this type of approach is largely driven by recent work in the Barnett Shale region in Texas as well as the San Juan Basin in New Mexico and Colorado; these studies suggest that relatively few single-point emitters dominate the regional emissions of CH4.

Application of the level set method for multi-phase flow computation in fusion engineering

International Nuclear Information System (INIS)

Luo, X-Y.; Ni, M-J.; Ying, A.; Abdou, M.

2006-01-01

Numerical simulation of multi-phase flow is essential to evaluate the feasibility of a liquid protection scheme for the power plant chamber. The level set method is one of the best methods for computing and analyzing the motion of interface among the multi-phase flow. This paper presents a general formula for the second-order projection method combined with the level set method to simulate unsteady incompressible multi-phase flow with/out phase change flow encountered in fusion science and engineering. The third-order ENO scheme and second-order semi-implicit Crank-Nicholson scheme is used to update the convective and diffusion term. The numerical results show this method can handle the complex deformation of the interface and the effect of liquid-vapor phase change will be included in the future work

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

International Nuclear Information System (INIS)

Thetiot, R.

2000-01-01

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

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

Science.gov (United States)

Chadli, Abdelhafid; Bendella, Fatima; Tranvouez, Erwan

2015-01-01

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

A hybrid multi-level optimization approach for the dynamic synthesis/design and operation/control under uncertainty of a fuel cell system

International Nuclear Information System (INIS)

Kim, Kihyung; Spakovsky, Michael R. von; Wang, M.; Nelson, Douglas J.

2011-01-01

During system development, large-scale, complex energy systems require multi-disciplinary efforts to achieve system quality, cost, and performance goals. As systems become larger and more complex, the number of possible system configurations and technologies, which meet the designer's objectives optimally, increases greatly. In addition, both transient and environmental effects may need to be taken into account. Thus, the difficulty of developing the system via the formulation of a single optimization problem in which the optimal synthesis/design and operation/control of the system are achieved simultaneously is great and rather problematic. This difficulty is further heightened with the introduction of uncertainty analysis, which transforms the problem from a purely deterministic one into a probabilistic one. Uncertainties, system complexity and nonlinearity, and large numbers of decision variables quickly render the single optimization problem unsolvable by conventional, single-level, optimization strategies. To address these difficulties, the strategy adopted here combines a dynamic physical decomposition technique for large-scale optimization with a response sensitivity analysis method for quantifying system response uncertainties to given uncertainty sources. The feasibility of such a hybrid approach is established by applying it to the synthesis/design and operation/control of a 5 kW proton exchange membrane (PEM) fuel cell system.

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

Science.gov (United States)

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%).

R Package multiPIM: A Causal Inference Approach to Variable Importance Analysis

Directory of Open Access Journals (Sweden)

Stephan J Ritter

2014-04-01

Full Text Available We describe the R package multiPIM, including statistical background, functionality and user options. The package is for variable importance analysis, and is meant primarily for analyzing data from exploratory epidemiological studies, though it could certainly be applied in other areas as well. The approach taken to variable importance comes from the causal inference field, and is different from approaches taken in other R packages. By default, multiPIM uses a double robust targeted maximum likelihood estimator (TMLE of a parameter akin to the attributable risk. Several regression methods/machine learning algorithms are available for estimating the nuisance parameters of the models, including super learner, a meta-learner which combines several different algorithms into one. We describe a simulation in which the double robust TMLE is compared to the graphical computation estimator. We also provide example analyses using two data sets which are included with the package.

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

Science.gov (United States)

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

2016-12-14

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

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

International Nuclear Information System (INIS)

Ivanov, K.; Avramova, M.

2007-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2007-07-01

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

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

Science.gov (United States)

Kwag, Shinyoung

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

The Combined Multi-objective Optimization Design for a Light Guide Rod

International Nuclear Information System (INIS)

Yang, Yu-Sen; Fung, Rong-Fong; Shih, Chun-Yao; Chien, Hong-Yao

2013-01-01

The light guide rod (LGR) has been popularly used for the vehicles, and the automobile lamp industries need mass production to match this trend. This paper aims to develop a systemic way to find the best parameters' combination for the LGR, and the parameters are usually restricted to some levels and random values. In this paper, the LGR example with two optical performances of illuminance flux and uniformity is to be optimized by use of the real-coded genetic algorithm (RGA) and grey relational analysis (GRA). The illuminance flux and uniformity of the best parameters' combination are obtained and compared with the initial set. Comparisons with Taguchi-Grey can improve 5% of gain and comparisons with Pareto genetic algorithm (PaGA) can improve 1.7% of gain. The combined multi-objective optimization can saving 7% time and it is found that the new proposed method has positive gains in performances.

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

OpenAIRE

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

2017-01-01

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

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

OpenAIRE

Monica Lagazio; Nazneen Sherif; Mike Cushman

2014-01-01

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

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

Science.gov (United States)

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

2017-02-01

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

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

Science.gov (United States)

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

2015-11-06

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

Combination of precise GNSS orbit and clock solutions in a multi-constellation, multi-frequency environment

Science.gov (United States)

Ortiz Geist, Estefania

2015-04-01

Precise GNSS orbit and clock solutions are essential for the generation of the Terrestrial Reference Frame (TRF) and required for a broad variety of applications. Over the last decades the combination products of the International GNSS Service (IGS) have become the standard for all kinds of GNSS applications requiring highest accuracy. The emerging new GNSS constellations Galileo, BeiDou and the QZSS as well as the modernization of the already established GPS and GLONASS constellations will stimulate a new development in the GNSS data processing in order to gain be best benefit from the new signals and systems for geodetic and geodynamic applications. This introduces the question regarding the influence of this development on the orbit and clock products. What are the consequences for the consistency of the contributions from the Analysis Centres (ACs) of the IGS and how does the combination procedure need to react on his development? Another set of questions is related to the expected scenario in which not all IGS ACs will likely include all GNSS. The algorithm for the orbit and clock combination needs to be adapted for a multi-system combination to keep on one hand the internal consistency between the GNSS during the combination procedure but also consider the differences in the expected orbit qualities between the satellite systems (e.g., due to the number of satellites or network coverage). To investigate these questions ESOC and AIUB have agreed on a joint research fellowship for three years. The objective of this research is to analyse the capabilities and challenges when combining hybrid multi-GNSS solutions and to develop a concept, which compares and combines orbit and clock contributions to come up with a consistent, reliable, truly combined multi-GNSS combination product. Well-defined test scenarios shall be constructed and analysed based on the GNSS data processing software packages in the two institutions, namely "NAPEOS" and "Bernese GNSS Software

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

Directory of Open Access Journals (Sweden)

Wuqiang Yang

2006-04-01

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

Evaluation of the molecular level visualisation approach for teaching and learning chemistry in Thailand

Science.gov (United States)

Phenglengdi, Butsari

This research evaluates the use of a molecular level visualisation approach in Thai secondary schools. The goal is to obtain insights about the usefulness of this approach, and to examine possible improvements in how the approach might be applied in the future. The methodology used for this research used both qualitative and quantitative approaches. Data were collected in the form of pre- and post-intervention multiple choice questions, open-ended-questions, drawing exercises, one-to-one interviews and video recordings of class activity. The research was conducted in two phases, involving a total of 261 students from the 11th Grade in Thailand. The use of VisChem animations in three studies was evaluated in Phase I. Study 1 was a pilot study exploring the benefits of incorporating VisChem animations to portray the molecular level. Study 2 compared test results between students exposed to these animations of molecular level events, and those not. Finally, in Study 3, test results were gathered from different types of schools (a rural school, a city school, and a university school). The results showed that students (and teachers) had misconceptions at the molecular level, and VisChem animations could help students understand chemistry concepts at the molecular level across all three types of schools. While the animation treatment group had a better score on the topic of states of water, the non-animation treatment group had a better score on the topic of dissolving sodium chloride in water than the animation group. The molecular level visualisation approach as a learning design was evaluated in Phase II. This approach involved a combination of VisChem animations, pictures, and diagrams together with the seven-step VisChem learning design. The study involved three classes of students, each with a different treatment, described as Class A - Traditional approach; Class B - VisChem animations with traditional approach; and Class C - Molecular level visualisation approach

Multi-level converter with auxiliary resonant-commutated pole

NARCIS (Netherlands)

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

1998-01-01

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

Prediction of a service demand using combined forecasting approach

Science.gov (United States)

Zhou, Ling

2017-08-01

Forecasting facilitates cutting down operational and management costs while ensuring service level for a logistics service provider. Our case study here is to investigate how to forecast short-term logistic demand for a LTL carrier. Combined approach depends on several forecasting methods simultaneously, instead of a single method. It can offset the weakness of a forecasting method with the strength of another, which could improve the precision performance of prediction. Main issues of combined forecast modeling are how to select methods for combination, and how to find out weight coefficients among methods. The principles of method selection include that each method should apply to the problem of forecasting itself, also methods should differ in categorical feature as much as possible. Based on these principles, exponential smoothing, ARIMA and Neural Network are chosen to form the combined approach. Besides, least square technique is employed to settle the optimal weight coefficients among forecasting methods. Simulation results show the advantage of combined approach over the three single methods. The work done in the paper helps manager to select prediction method in practice.

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

Science.gov (United States)

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

2015-02-01

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

Multi-unit price promotions and their impact on purchase decisions and sales

NARCIS (Netherlands)

Drechsler, Salome; Leeflang, Peter S. H.; Bijmolt, Tammo H. A.; Natter, Martin

2017-01-01

Purpose - The purpose of this paper is to compare the impact of different multi-unit promotions (MUPs) and a single-unit promotion (SUP) on store-level sales and consumer-level purchase probability and quantity decision. Design/methodology/approach - The paper combines two empirical studies. Study 1

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

Directory of Open Access Journals (Sweden)

Ijaz Ahmad

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

Optimal Multi-Level Lot Sizing for Requirements Planning Systems

OpenAIRE

Earle Steinberg; H. Albert Napier

1980-01-01

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

Data management and data analysis techniques in pharmacoepidemiological studies using a pre-planned multi-database approach: a systematic literature review.

Science.gov (United States)

Bazelier, Marloes T; Eriksson, Irene; de Vries, Frank; Schmidt, Marjanka K; Raitanen, Jani; Haukka, Jari; Starup-Linde, Jakob; De Bruin, Marie L; Andersen, Morten

2015-09-01

To identify pharmacoepidemiological multi-database studies and to describe data management and data analysis techniques used for combining data. Systematic literature searches were conducted in PubMed and Embase complemented by a manual literature search. We included pharmacoepidemiological multi-database studies published from 2007 onwards that combined data for a pre-planned common analysis or quantitative synthesis. Information was retrieved about study characteristics, methods used for individual-level analyses and meta-analyses, data management and motivations for performing the study. We found 3083 articles by the systematic searches and an additional 176 by the manual search. After full-text screening of 75 articles, 22 were selected for final inclusion. The number of databases used per study ranged from 2 to 17 (median = 4.0). Most studies used a cohort design (82%) instead of a case-control design (18%). Logistic regression was most often used for individual-level analyses (41%), followed by Cox regression (23%) and Poisson regression (14%). As meta-analysis method, a majority of the studies combined individual patient data (73%). Six studies performed an aggregate meta-analysis (27%), while a semi-aggregate approach was applied in three studies (14%). Information on central programming or heterogeneity assessment was missing in approximately half of the publications. Most studies were motivated by improving power (86%). Pharmacoepidemiological multi-database studies are a well-powered strategy to address safety issues and have increased in popularity. To be able to correctly interpret the results of these studies, it is important to systematically report on database management and analysis techniques, including central programming and heterogeneity testing. © 2015 The Authors. Pharmacoepidemiology and Drug Safety published by John Wiley & Sons, Ltd.

On multi-level thinking and scientific understanding

Science.gov (United States)

McIntyre, Michael Edgeworth

2017-10-01

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

An unprecedented multi attribute decision making using graph theory matrix approach

Directory of Open Access Journals (Sweden)

N.K. Geetha

2018-02-01

Full Text Available A frame work for investigating the best combination of functioning parameters on a variable compression ratio diesel engine is proposed in the present study using a multi attribute optimization methodology, Graph Theory Matrix Approach. The functioning parameters, attributes, sub attributes and functioning variables of sub attributes are chosen based on expert’s opinion and literature review. The directed graphs are developed for attributes and sub attributes. The ‘Parameter Index’ was calculated for all trials to choose the best trial. The experimental results are verified with the theoretical data. Functioning parameters with combination of compression ratio of 17, fuel injection pressure of 20 N/mm2 and fuel injection pressure of 21°bTDC was found to be best. The proposed method allows the decision maker to systematically and logically find the best combination of functioning parameters.

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

Science.gov (United States)

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

2015-08-01

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

Thermo-mechanical analysis for multi-level HLW repository concept

International Nuclear Information System (INIS)

Kwon, Sang Ki; Choi, Jong Won

2004-01-01

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

PELAKSANAAN JUAL BELI MELALUI SISTEM MULTI LEVEL MARKETING PERSPEKTIF HUKUM ISLAM

Directory of Open Access Journals (Sweden)

Ayu Dewi Utami

2016-03-01

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

Multi-target consensus circle pursuit for multi-agent systems via a distributed multi-flocking method

Science.gov (United States)

Pei, Huiqin; Chen, Shiming; Lai, Qiang

2016-12-01

This paper studies the multi-target consensus pursuit problem of multi-agent systems. For solving the problem, a distributed multi-flocking method is designed based on the partial information exchange, which is employed to realise the pursuit of multi-target and the uniform distribution of the number of pursuing agents with the dynamic target. Combining with the proposed circle formation control strategy, agents can adaptively choose the target to form the different circle formation groups accomplishing a multi-target pursuit. The speed state of pursuing agents in each group converges to the same value. A Lyapunov approach is utilised to analyse the stability of multi-agent systems. In addition, a sufficient condition is given for achieving the dynamic target consensus pursuit, and which is then analysed. Finally, simulation results verify the effectiveness of the proposed approaches.

Development of multi-functional combine harvester with grain harvesting and straw baling

International Nuclear Information System (INIS)

Tang, Z.; Li, Y.; Cheng, C.

2017-01-01

The decomposition and burning of straw results in serious environmental pollution, and research is needed to improve strategies for straw collection to reduce pollution. This work presents an integrated design of multi-functional rice combine harvester that allows grain harvesting and straw baling. This multi-functional combine harvester could reduce the energy consumption required for rice harvesting and simplify the process of harvesting and baling. The transmission schematic, matching parameters and the rotation speed of threshing cylinder and square baler were designed and checked. Then the evaluation of grain threshing and straw baling were tested on a transverse threshing cylinders device tes rig and straw square bales compression test rig. The test results indicated that, with a feeding rate of 3.0 kg/s, the remaining straw flow rate at the discharge outlet was only 1.22 kg/s, which indicates a variable mass threshing process by the transverse threshing cylinder. Then the optimal diameter, length and rotating speed of multi-functional combine harvester transverse threshing cylinder were 554 mm, 1590 mm, and 850 r/min, respectively. The straw bale compression rotating speed of crank compression slider and piston was 95 r/min. Field trials by the multi-functional combine harvester formed bales with height×width×length of 40×50×54-63 cm, bale mass of 22.5 to 26.0 kg and bale density 206 to 216 kg/m3. This multi-functional combine harvester could be used for stem crops (such as rice, wheat and soybean) grain harvesting and straw square baling, which could reduce labor cost and power consumption.

Development of multi-functional combine harvester with grain harvesting and straw baling

Energy Technology Data Exchange (ETDEWEB)

Tang, Z.; Li, Y.; Cheng, C.

2017-09-01

The decomposition and burning of straw results in serious environmental pollution, and research is needed to improve strategies for straw collection to reduce pollution. This work presents an integrated design of multi-functional rice combine harvester that allows grain harvesting and straw baling. This multi-functional combine harvester could reduce the energy consumption required for rice harvesting and simplify the process of harvesting and baling. The transmission schematic, matching parameters and the rotation speed of threshing cylinder and square baler were designed and checked. Then the evaluation of grain threshing and straw baling were tested on a transverse threshing cylinders device tes rig and straw square bales compression test rig. The test results indicated that, with a feeding rate of 3.0 kg/s, the remaining straw flow rate at the discharge outlet was only 1.22 kg/s, which indicates a variable mass threshing process by the transverse threshing cylinder. Then the optimal diameter, length and rotating speed of multi-functional combine harvester transverse threshing cylinder were 554 mm, 1590 mm, and 850 r/min, respectively. The straw bale compression rotating speed of crank compression slider and piston was 95 r/min. Field trials by the multi-functional combine harvester formed bales with height×width×length of 40×50×54-63 cm, bale mass of 22.5 to 26.0 kg and bale density 206 to 216 kg/m3. This multi-functional combine harvester could be used for stem crops (such as rice, wheat and soybean) grain harvesting and straw square baling, which could reduce labor cost and power consumption.

A multi-tiered approach for assessing the forestry and wood products industries' impact on the carbon balance.

Science.gov (United States)

Knauf, Marcus

2015-12-01

The forestry and wood products industries play a significant role in CO 2 emissions reduction by increasing carbon stocks in living forest biomass and wood products. Moreover, wood can substitute for fossil fuels. Different methods can be used to assess the impact of regional forestry and wood products industries on regional CO 2 emissions. This article considers three of those methods and combines them into a multi-tiered approach. The multi-tiered approach proposed in this article combines: 1) a Kyoto-Protocol-oriented method focused on changes in CO 2 emissions resulting from regional industrial production, 2) a consumer-oriented method focused on changes in CO 2 emissions resulting from regional consumption, and 3) a value-creation-oriented method focused on changes in CO 2 emissions resulting from forest management and wood usage strategies. North Rhine-Westphalia is both a typical German state and an example of a region where each of these three methods yields different results. It serves as a test case with which to illustrate the advantages of the proposed approach. This case study argues that the choice of assessment methods is essential when developing and evaluating a strategy for reducing CO 2 emissions. Emissions can be reduced through various social and economic processes. Since none of the assessment methods considered above is suitable for all of these processes, only a multi-tiered approach may ensure that strategy development results in an optimal emissions reduction strategy.

A multi-objective approach to solid waste management

International Nuclear Information System (INIS)

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

2010-01-01

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

A multi-objective approach to solid waste management.

Science.gov (United States)

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

2010-01-01

The issue addressed in this paper consists in the localization and dimensioning of transfer stations, which constitute a necessary intermediate level in the logistic chain of the solid waste stream, from municipalities to the incinerator. Contextually, the determination of the number and type of vehicles involved is carried out in an integrated optimization approach. The model considers both initial investment and operative costs related to transportation and transfer stations. Two conflicting objectives are evaluated, the minimization of total cost and the minimization of environmental impact, measured by pollution. The design of the integrated waste management system is hence approached in a multi-objective optimization framework. To determine the best means of compromise, goal programming, weighted sum and fuzzy multi-objective techniques have been employed. The proposed analysis highlights how different attitudes of the decision maker towards the logic and structure of the problem result in the employment of different methodologies and the obtaining of different results. The novel aspect of the paper lies in the proposal of an effective decision support system for operative waste management, rather than a further contribution to the transportation problem. The model was applied to the waste management of optimal territorial ambit (OTA) of Palermo (Italy). 2010 Elsevier Ltd. All rights reserved.

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

Science.gov (United States)

Gustafsson, Lena; Perhans, Karin

2010-12-01

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

NMR-MPar: A Fault-Tolerance Approach for Multi-Core and Many-Core Processors

Directory of Open Access Journals (Sweden)

Vanessa Vargas

2018-03-01

Full Text Available Multi-core and many-core processors are a promising solution to achieve high performance by maintaining a lower power consumption. However, the degree of miniaturization makes them more sensitive to soft-errors. To improve the system reliability, this work proposes a fault-tolerance approach based on redundancy and partitioning principles called N-Modular Redundancy and M-Partitions (NMR-MPar. By combining both principles, this approach allows multi-/many-core processors to perform critical functions in mixed-criticality systems. Benefiting from the capabilities of these devices, NMR-MPar creates different partitions that perform independent functions. For critical functions, it is proposed that N partitions with the same configuration participate of an N-modular redundancy system. In order to validate the approach, a case study is implemented on the KALRAY Multi-Purpose Processing Array (MPPA-256 many-core processor running two parallel benchmark applications. The traveling salesman problem and matrix multiplication applications were selected to test different device’s resources. The effectiveness of NMR-MPar is assessed by software-implemented fault-injection. For evaluation purposes, it is considered that the system is intended to be used in avionics. Results show the improvement of the application reliability by two orders of magnitude when implementing NMR-MPar on the system. Finally, this work opens the possibility to use massive parallelism for dependable applications in embedded systems.

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

Directory of Open Access Journals (Sweden)

Diveev Askhat

2016-01-01

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

Combined genetic algorithm and multiple linear regression (GA-MLR) optimizer: Application to multi-exponential fluorescence decay surface.

Science.gov (United States)

Fisz, Jacek J

2006-12-07

The optimization approach based on the genetic algorithm (GA) combined with multiple linear regression (MLR) method, is discussed. The GA-MLR optimizer is designed for the nonlinear least-squares problems in which the model functions are linear combinations of nonlinear functions. GA optimizes the nonlinear parameters, and the linear parameters are calculated from MLR. GA-MLR is an intuitive optimization approach and it exploits all advantages of the genetic algorithm technique. This optimization method results from an appropriate combination of two well-known optimization methods. The MLR method is embedded in the GA optimizer and linear and nonlinear model parameters are optimized in parallel. The MLR method is the only one strictly mathematical "tool" involved in GA-MLR. The GA-MLR approach simplifies and accelerates considerably the optimization process because the linear parameters are not the fitted ones. Its properties are exemplified by the analysis of the kinetic biexponential fluorescence decay surface corresponding to a two-excited-state interconversion process. A short discussion of the variable projection (VP) algorithm, designed for the same class of the optimization problems, is presented. VP is a very advanced mathematical formalism that involves the methods of nonlinear functionals, algebra of linear projectors, and the formalism of Fréchet derivatives and pseudo-inverses. Additional explanatory comments are added on the application of recently introduced the GA-NR optimizer to simultaneous recovery of linear and weakly nonlinear parameters occurring in the same optimization problem together with nonlinear parameters. The GA-NR optimizer combines the GA method with the NR method, in which the minimum-value condition for the quadratic approximation to chi(2), obtained from the Taylor series expansion of chi(2), is recovered by means of the Newton-Raphson algorithm. The application of the GA-NR optimizer to model functions which are multi

Multi-Level Sensor Fusion Algorithm Approach for BMD Interceptor Applications

National Research Council Canada - National Science Library

Allen, Doug

1998-01-01

... through fabrication and testing of advanced sensor hardware concepts and advanced sensor fusion algorithms. Advanced sensor concepts include onboard LADAR in conjunction with a multi-color passive IR sensor...

Field Trials of the Multi-Source Approach for Resistivity and Induced Polarization Data Acquisition

Science.gov (United States)

LaBrecque, D. J.; Morelli, G.; Fischanger, F.; Lamoureux, P.; Brigham, R.

2013-12-01

Implementing systems of distributed receivers and transmitters for resistivity and induced polarization data is an almost inevitable result of the availability of wireless data communication modules and GPS modules offering precise timing and instrument locations. Such systems have a number of advantages; for example, they can be deployed around obstacles such as rivers, canyons, or mountains which would be difficult with traditional 'hard-wired' systems. However, deploying a system of identical, small, battery powered, transceivers, each capable of injecting a known current and measuring the induced potential has an additional and less obvious advantage in that multiple units can inject current simultaneously. The original purpose for using multiple simultaneous current sources (multi-source) was to increase signal levels. In traditional systems, to double the received signal you inject twice the current which requires you to apply twice the voltage and thus four times the power. Alternatively, one approach to increasing signal levels for large-scale surveys collected using small, battery powered transceivers is it to allow multiple units to transmit in parallel. In theory, using four 400 watt transmitters on separate, parallel dipoles yields roughly the same signal as a single 6400 watt transmitter. Furthermore, implementing the multi-source approach creates the opportunity to apply more complex current flow patterns than simple, parallel dipoles. For a perfect, noise-free system, multi-sources adds no new information to a data set that contains a comprehensive set of data collected using single sources. However, for realistic, noisy systems, it appears that multi-source data can substantially impact survey results. In preliminary model studies, the multi-source data produced such startling improvements in subsurface images that even the authors questioned their veracity. Between December of 2012 and July of 2013, we completed multi-source surveys at five sites

Multilevel and multi-user sustainability assessment of farming systems

Energy Technology Data Exchange (ETDEWEB)

Van Passel, Steven, E-mail: Steven.vanpassel@uhasselt.be [Hasselt University, Faculty of Business Economics, Centre for Environmental Sciences, Agoralaan, Building D, 3590, Diepenbeek (Belgium); University of Antwerp, Department Bioscience Engineering, Groenenborgerlaan 171, 2020 Antwerp (Belgium); Meul, Marijke [University College Ghent, Department of Biosciences and Landscape Architecture, Campus Schoonmeersen, Building C, Schoonmeersstraat 52, 9000, Gent (Belgium)

2012-01-15

Sustainability assessment is needed to build sustainable farming systems. A broad range of sustainability concepts, methodologies and applications already exists. They differ in level, focus, orientation, measurement, scale, presentation and intended end-users. In this paper we illustrate that a smart combination of existing methods with different levels of application can make sustainability assessment more profound, and that it can broaden the insights of different end-user groups. An overview of sustainability assessment tools on different levels and for different end-users shows the complementarities and the opportunities of using different methods. In a case-study, a combination of the sustainable value approach (SVA) and MOTIFS is used to perform a sustainability evaluation of farming systems in Flanders. SVA is used to evaluate sustainability at sector level, and is especially useful to support policy makers, while MOTIFS is used to support and guide farmers towards sustainability at farm level. The combined use of the two methods with complementary goals can widen the insights of both farmers and policy makers, without losing the particularities of the different approaches. To stimulate and support further research and applications, we propose guidelines for multilevel and multi-user sustainability assessments. - Highlights: Black-Right-Pointing-Pointer We give an overview of sustainability assessment tools for agricultural systems. Black-Right-Pointing-Pointer SVA and MOTIFS are used to evaluate the sustainability of dairy farming in Flanders. Black-Right-Pointing-Pointer Combination of methods with different levels broadens the insights of different end-user groups. Black-Right-Pointing-Pointer We propose guidelines for multilevel and multi-user sustainability assessments.

Multilevel and multi-user sustainability assessment of farming systems

International Nuclear Information System (INIS)

Van Passel, Steven; Meul, Marijke

2012-01-01

Sustainability assessment is needed to build sustainable farming systems. A broad range of sustainability concepts, methodologies and applications already exists. They differ in level, focus, orientation, measurement, scale, presentation and intended end-users. In this paper we illustrate that a smart combination of existing methods with different levels of application can make sustainability assessment more profound, and that it can broaden the insights of different end-user groups. An overview of sustainability assessment tools on different levels and for different end-users shows the complementarities and the opportunities of using different methods. In a case-study, a combination of the sustainable value approach (SVA) and MOTIFS is used to perform a sustainability evaluation of farming systems in Flanders. SVA is used to evaluate sustainability at sector level, and is especially useful to support policy makers, while MOTIFS is used to support and guide farmers towards sustainability at farm level. The combined use of the two methods with complementary goals can widen the insights of both farmers and policy makers, without losing the particularities of the different approaches. To stimulate and support further research and applications, we propose guidelines for multilevel and multi-user sustainability assessments. - Highlights: ► We give an overview of sustainability assessment tools for agricultural systems. ► SVA and MOTIFS are used to evaluate the sustainability of dairy farming in Flanders. ► Combination of methods with different levels broadens the insights of different end-user groups. ► We propose guidelines for multilevel and multi-user sustainability assessments.

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

Energy Technology Data Exchange (ETDEWEB)

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

2014-11-01

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

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

Science.gov (United States)

Yokoi, Kensuke

2009-07-01

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

A Single Rod Multi-modality Multi-interface Level Sensor Using an AC Current Source

Directory of Open Access Journals (Sweden)

Abdulgader Hwili

2008-05-01

Full Text Available Crude oil separation is an important process in the oil industry. To make efficient use of the separators, it is important to know their internal behaviour, and to measure the levels of multi-interfaces between different materials, such as gas-foam, foam-oil, oil-emulsion, emulsion-water and water-solids. A single-rod multi-modality multi-interface level sensor is presented, which has a current source, and electromagnetic modalities. Some key issues have been addressed, including the effect of salt content and temperature i.e. conductivity on the measurement.

A MULTI CRITERIA APPROACH TO DESIGNING THE CELLULAR MANUFACTURING SYSTEM

Directory of Open Access Journals (Sweden)

Rika Ampuh Hadiguna

2005-01-01

Full Text Available Cellular manufacturing system design problems such as design framework, manufacturing cells layout and layout evaluation. The research objective is developing the framework to designing manufacturing cells with considering the organization and management aspects in shopfloor. In this research have compared the existing layout with proposed layout which applied the multi criteria approach. The proposed method is combining Analytical Hierarchy Process (AHP, Clustering and heuristic approach. The result has show that grouping with Single Linkage Clustering (SLC to be selected as manufacturing cells. The comparison of clustering weight is 0,567, 0,245 and 0,188 for SLC, Complete Linkage Clustering (CLC and Average Linkage Clustering (ALC, respectively. This result shows that generating layout by using grouping result from SLC. The evaluation result shows that types of manufacturing cells better than process layout which used the existing system.

The exposure of Sydney (Australia) to earthquake-generated tsunamis, storms and sea level rise: a probabilistic multi-hazard approach.

Science.gov (United States)

Dall'Osso, F; Dominey-Howes, D; Moore, C; Summerhayes, S; Withycombe, G

2014-12-10

Approximately 85% of Australia's population live along the coastal fringe, an area with high exposure to extreme inundations such as tsunamis. However, to date, no Probabilistic Tsunami Hazard Assessments (PTHA) that include inundation have been published for Australia. This limits the development of appropriate risk reduction measures by decision and policy makers. We describe our PTHA undertaken for the Sydney metropolitan area. Using the NOAA NCTR model MOST (Method for Splitting Tsunamis), we simulate 36 earthquake-generated tsunamis with annual probabilities of 1:100, 1:1,000 and 1:10,000, occurring under present and future predicted sea level conditions. For each tsunami scenario we generate a high-resolution inundation map of the maximum water level and flow velocity, and we calculate the exposure of buildings and critical infrastructure. Results indicate that exposure to earthquake-generated tsunamis is relatively low for present events, but increases significantly with higher sea level conditions. The probabilistic approach allowed us to undertake a comparison with an existing storm surge hazard assessment. Interestingly, the exposure to all the simulated tsunamis is significantly lower than that for the 1:100 storm surge scenarios, under the same initial sea level conditions. The results have significant implications for multi-risk and emergency management in Sydney.

Multi-level spondylolysis.

Science.gov (United States)

Hersh, David S; Kim, Yong H; Razi, Afshin

2011-01-01

The incidence of isthmic spondylolysis is approximately 3% to 6% in the general population. Spondylolytic defects involving multiple vertebral levels, on the other hand, are extremely rare. Only a handful of reports have examined the outcomes of surgical treatment of multi-level spondylolysis. Here, we present one case of bilateral pars defects at L3, L4, and L5. The patient, a 46-year-old female, presented with lower back pain radiating into the left lower extremity. Radiographs and CT scans of the lumbar spine revealed bilateral pars defects at L3-L5. The patient underwent lumbar discectomy and interbody fusion of L4-S1 as well as direct repair of the pars defect at L3. There were no postoperative complications, and by seven months the patient had improved clinically. While previous reports describe the use of either direct repair or fusion in the treatment of spondylolysis, we are unaware of reports describing the use of both techniques at adjacent levels.

Combining simulation and multi-objective optimisation for equipment quantity optimisation in container terminals

OpenAIRE

Lin, Zhougeng

2013-01-01

This thesis proposes a combination framework to integrate simulation and multi-objective optimisation (MOO) for container terminal equipment optimisation. It addresses how the strengths of simulation and multi-objective optimisation can be integrated to find high quality solutions for multiple objectives with low computational cost. Three structures for the combination framework are proposed respectively: pre-MOO structure, integrated MOO structure and post-MOO structure. The applications of ...

Due date assignment procedures with dynamically updated coefficients for multi-level assembly job shops

NARCIS (Netherlands)

Adam, N.R.; Bertrand, J.W.M.; Morehead, D.C.; Surkis, J.

1993-01-01

This paper presents a study of due date assignment procedures in job shop environments where multi-level assembly jobs are processed and due dates are internally assigned. Most of the reported studies in the literature have focused on string type jobs. We propose a dynamic update approach (which

Multi-color and artistic dithering

OpenAIRE

Ostromoukhov, Victor; Hersch, Roger D.

1999-01-01

A multi-color dithering algorithm is proposed, which converts a barycentric combination of color intensities into a multi-color non-overlapping surface coverage. Multi-color dithering is a generalization of standard bi-level dithering. Combined with tetrahedral color separation, multi-color dithering makes it possible to print images made of a set of non-standard inks. In contrast to most previous color halftoning methods, multi-color dithering ensures by construction that the different selec...

Combined multi-criteria and cost-benefit analysis

DEFF Research Database (Denmark)

Moshøj, Claus Rehfeld

1996-01-01

The paper is an introduction to both theory and application of combined Cost-Benefit and Multi-Criteria Analysis. The first section is devoted to basic utility theory and its practical application in Cost-Benefit Analysis. Based on some of the problems encountered, arguments in favour...... of the application of utility-based Multi-Criteria Analyses methods as an extension and refinement of the traditional Cost-Benefit Analysis are provided. The theory presented in this paper is closely related the methods used in the WARP software (Leleur & Jensen, 1989). The presentation is however wider in scope.......The second section introduces the stated preference methodology used in WARP to create weight profiles for project pool sensitivity analysis. This section includes a simple example. The third section discusses how decision makers can get a priori aid to make their pair-wise comparisons based on project pool...

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

Science.gov (United States)

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

2017-12-01

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

Approximate ideal multi-objective solution Q(λ) learning for optimal carbon-energy combined-flow in multi-energy power systems

International Nuclear Information System (INIS)

Zhang, Xiaoshun; Yu, Tao; Yang, Bo; Zheng, Limin; Huang, Linni

2015-01-01

Highlights: • A novel optimal carbon-energy combined-flow (OCECF) model is firstly established. • A novel approximate ideal multi-objective solution Q(λ) learning is designed. • The proposed algorithm has a high convergence stability and reliability. • The proposed algorithm can be applied for OCECF in a large-scale power grid. - Abstract: This paper proposes a novel approximate ideal multi-objective solution Q(λ) learning for optimal carbon-energy combined-flow in multi-energy power systems. The carbon emissions, fuel cost, active power loss, voltage deviation and carbon emission loss are chosen as the optimization objectives, which are simultaneously optimized by five different Q-value matrices. The dynamic optimal weight of each objective is calculated online from the entire Q-value matrices such that the greedy action policy can be obtained. Case studies are carried out to evaluate the optimization performance for carbon-energy combined-flow in an IEEE 118-bus system and the regional power grid of southern China.

Fuzzy Continuous Review Inventory Model using ABC Multi-Criteria Classification Approach: A Single Case Study

Directory of Open Access Journals (Sweden)

Meriastuti - Ginting

2015-07-01

Full Text Available Abstract. Inventory is considered as the most expensive, yet important,to any companies. It representsapproximately 50% of the total investment. Inventory cost has become one of the majorcontributorsto inefficiency, therefore it should be managed effectively. This study aims to propose an alternative inventory model,  by using ABC multi-criteria classification approach to minimize total cost. By combining FANP (Fuzzy Analytical Network Process and TOPSIS (Technique of Order Preferences by Similarity to the Ideal Solution, the ABC multi-criteria classification approach identified 12 items of 69 inventory items as “outstanding important class” that contributed to 80% total inventory cost. This finding  is then used as the basis to determine the proposed continuous review inventory model.This study found that by using fuzzy trapezoidal cost, the inventory  turnover ratio can be increased, and inventory cost can be decreased by 78% for each item in “class A” inventory.Keywords:ABC multi-criteria classification, FANP-TOPSIS, continuous review inventory model lead-time demand distribution, trapezoidal fuzzy number 

Multi-phase classification by a least-squares support vector machine approach in tomography images of geological samples

Science.gov (United States)

Khan, Faisal; Enzmann, Frieder; Kersten, Michael

2016-03-01

Image processing of X-ray-computed polychromatic cone-beam micro-tomography (μXCT) data of geological samples mainly involves artefact reduction and phase segmentation. For the former, the main beam-hardening (BH) artefact is removed by applying a best-fit quadratic surface algorithm to a given image data set (reconstructed slice), which minimizes the BH offsets of the attenuation data points from that surface. A Matlab code for this approach is provided in the Appendix. The final BH-corrected image is extracted from the residual data or from the difference between the surface elevation values and the original grey-scale values. For the segmentation, we propose a novel least-squares support vector machine (LS-SVM, an algorithm for pixel-based multi-phase classification) approach. A receiver operating characteristic (ROC) analysis was performed on BH-corrected and uncorrected samples to show that BH correction is in fact an important prerequisite for accurate multi-phase classification. The combination of the two approaches was thus used to classify successfully three different more or less complex multi-phase rock core samples.

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

OpenAIRE

Kong Xiangying

2013-01-01

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

Quantum state preparation using multi-level-atom optics

International Nuclear Information System (INIS)

Busch, Th; Deasy, K; Chormaic, S Nic

2007-01-01

One of the most important characteristics for controlling processes on the quantum scale is the fidelity or robustness of the techniques being used. In the case of single atoms localized in micro-traps, it was recently shown that the use of time-dependent tunnelling interactions in a multi-trap setup can be viewed as analogous to the area of multi-level optics. The atom's centre-of-mass can then be controlled with a high fidelity, using a STIRAP-type process. Here, we review previous work that led to the development of multi-level atom optics and present two examples of our most recent work on quantum state preparation

Multi-Level Marketing as a business model

Directory of Open Access Journals (Sweden)

Bogdan Gregor

2013-03-01

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

Functional copmponents produced by multi-jet modelling combined with electroforming and machining

Directory of Open Access Journals (Sweden)

Baier, Oliver

2014-08-01

Full Text Available In fuel cell technology, certain components are used that are responsible for guiding liquid media. When these components are produced by conventional manufacturing, there are often sealing issues, and trouble- and maintenance-free deployment cannot be ensured. Against this background, a new process combination has been developed in a joint project between the University of Duisburg-Essen, the Center for Fuel Cell Technology (ZBT, and the company Galvano-T electroplating forming GmbH. The approach is to combine multi-jet modelling (MJM, electroforming and milling in order to produce a defined external geometry. The wax models are generated on copper base plates and copper-coated to a desirable thickness. Following this, the undefined electroplated surfaces are machined to achieve the desired measurement, and the wax is melted out. This paper presents, first, how this process is technically feasible, then describes how the MJM on a 3-D Systems ThermoJet was adapted to stabilise the process.In the AiF-sponsored ZIM project, existing limits and possibilities are shown and different approaches of electroplating are investigated. This paper explores whether or not activation of the wax structure by a conductive initial layer is required. Using the described process chain, different parts were built: a heat exchanger, a vaporiser, and a reformer (in which pellets were integrated in an intermediate step. In addition, multiple-layer parts with different functions were built by repeating the process combination several times.

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

International Nuclear Information System (INIS)

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

2015-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2015-05-15

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

A Multi-organisational Approach to Service Delivery

Science.gov (United States)

Purchase, Valerie; Mills, John; Parry, Glenn

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

Metaheuristics for bi-level optimization

CERN Document Server

2013-01-01

This book provides a complete background on metaheuristics to solve complex bi-level optimization problems (continuous/discrete, mono-objective/multi-objective) in a diverse range of application domains. Readers learn to solve large scale bi-level optimization problems by efficiently combining metaheuristics with complementary metaheuristics and mathematical programming approaches. Numerous real-world examples of problems demonstrate how metaheuristics are applied in such fields as networks, logistics and transportation, engineering design, finance and security.

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

International Nuclear Information System (INIS)

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

2010-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2010-11-01

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

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

Science.gov (United States)

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

2014-09-01

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

Multi-Level Formation of Complex Software Systems

Directory of Open Access Journals (Sweden)

Hui Li

2016-05-01

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

Representation and Integration: Combining Robot Control, High-Level Planning, and Action Learning

DEFF Research Database (Denmark)

Petrick, Ronald; Kraft, Dirk; Mourao, Kira

We describe an approach to integrated robot control, high-level planning, and action effect learning that attempts to overcome the representational difficulties that exist between these diverse areas. Our approach combines ideas from robot vision, knowledgelevel planning, and connectionist machine......-level action specifications, suitable for planning, from a robot’s interactions with the world. We present a detailed overview of our approach and show how it supports the learning of certain aspects of a high-level lepresentation from low-level world state information....... learning, and focuses on the representational needs of these components.We also make use of a simple representational unit called an instantiated state transition fragment (ISTF) and a related structure called an object-action complex (OAC). The goal of this work is a general approach for inducing high...

Keabsahan Dan Kekuatan Hukum Layanan Multi Level Marketing Di Kota Manado

OpenAIRE

Mandang, Christian Leonardo

2016-01-01

Tujuan dilakukannya penelitian ini adalah untuk mengetahui apa landasan hukum yang mendasari keabsahan layanan Multi Level Marketing dan bagaimana sebuah Perusahaan dapat memenuhi syarat untuk menjalankan sistem Multi Level Marketing. Dengan menggunakan metode penelitian yuridis normatif, maka dapat disimpulkan: 1. Kehadiran Perusahaan dan kegiatan USAha Multi Level Marketing baik secara global maupun secara nasional, khususnya kehadirannya di negara Indonesia berperan untuk membantu berbagai...

Developing Multi-Level Institutions from Top-Down Ancestors

Directory of Open Access Journals (Sweden)

Martha Dowsley

2007-11-01

Full Text Available The academic literature contains numerous examples of the failures of both top-down and bottom-up common pool resource management frameworks. Many authors agree that management regimes instead need to utilize a multi-level governance approach to meet diverse objectives in management. However, many currently operating systems do not have that history. This paper explores the conversion of ancestral top-down regimes to complex systems involving multiple scales, levels and objectives through the management of the polar bear (Ursus maritimus in its five range countries. The less successful polar bear management systems continue to struggle with the challenges of developing institutions with the capacity to learn and change, addressing multiple objectives while recognizing the conservation backbone to management, and matching the institutional scale with biophysical, economic and social scales. The comparatively successful institutions incorporate these features, but reveal on-going problems with vertical links that are partially dealt with through the creation of links to other groups.

Prioritizing the refactoring need for critical component using combined approach

Directory of Open Access Journals (Sweden)

Rajni Sehgal

2018-10-01

Full Text Available One of the most promising strategies that will smooth out the maintainability issues of the software is refactoring. Due to lack of proper design approach, the code often inherits some bad smells which may lead to improper functioning of the code, especially when it is subject to change and requires some maintenance. A lot of studies have been performed to optimize the refactoring strategy which is also a very expensive process. In this paper, a component based system is considered, and a Fuzzy Multi Criteria Decision Making (FMCDM model is proposed by combining subjective and objective weights to rank the components as per their urgency of refactoring. Jdeodorant tool is used to detect the code smells from the individual components of a software system. The objective method uses the Entropy approach to rank the component having the code smell. The subjective method uses the Fuzzy TOPSIS approach based on decision makers’ judgement, to identify the critically and dependency of these code smells on the overall software. The suggested approach is implemented on component-based software having 15 components. The constitute components are ranked based on refactoring requirements.

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

International Nuclear Information System (INIS)

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

2011-01-01

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

Mapping of multi-floor buildings: A barometric approach

DEFF Research Database (Denmark)

Özkil, Ali Gürcan; Fan, Zhun; Xiao, Jizhong

2011-01-01

This paper presents a new method for mapping multi5floor buildings. The method combines laser range sensor for metric mapping and barometric pressure sensor for detecting floor transitions and map segmentation. We exploit the fact that the barometric pressure is a function of the elevation......, and it varies between different floors. The method is tested with a real robot in a typical indoor environment, and the results show that physically consistent multi5floor representations are achievable....

A public health framework to translate risk factors related to political violence and war into multi-level preventive interventions.

Science.gov (United States)

De Jong, Joop T V M

2010-01-01

Political violence, armed conflicts and human rights violations are produced by a variety of political, economic and socio-cultural factors. Conflicts can be analyzed with an interdisciplinary approach to obtain a global understanding of the relative contribution of risk and protective factors. A public health framework was designed to address these risk factors and protective factors. The framework resulted in a matrix that combined primary, secondary and tertiary interventions with their implementation on the levels of the society-at-large, the community, and the family and individual. Subsequently, the risk and protective factors were translated into multi-sectoral, multi-modal and multi-level preventive interventions involving the economy, governance, diplomacy, the military, human rights, agriculture, health, and education. Then the interventions were slotted in their appropriate place in the matrix. The interventions can be applied in an integrative form by international agencies, governments and non-governmental organizations, and molded to meet the requirements of the historic, political-economic and socio-cultural context. The framework maps the complementary fit among the different actors while engaging themselves in preventive, rehabilitative and reconstructive interventions. The framework shows how the economic, diplomatic, political, criminal justice, human rights, military, health and rural development sectors can collaborate to promote peace or prevent the aggravation or continuation of violence. A deeper understanding of the association between risk and protective factors and the developmental pathways of generic, country-specific and culture-specific factors leading to political violence is needed.

Transition in governance of river basin management in The Netherlands through multi-level social learning

NARCIS (Netherlands)

Van Herk, S.; Rijke, J.S.; Zevenbergen, C.; Ashley, R.

2012-01-01

This paper presents a case study of a new adaptive, multi-level governance approach that supported a transition in river basin management in the Netherlands. The floods of 1993 and 1995 in the Netherlands triggered a paradigm shift in flood management. The 2.3 billion Euro flood safety programme

Device-Level Models Using Multi-Valley Effective Mass

Science.gov (United States)

Baczewski, Andrew D.; Frees, Adam; Gamble, John King; Gao, Xujiao; Jacobson, N. Tobias; Mitchell, John A.; Montaño, Inès; Muller, Richard P.; Nielsen, Erik

2015-03-01

Continued progress in quantum electronics depends critically on the availability of robust device-level modeling tools that capture a wide range of physics and effective mass theory (EMT) is one means of building such models. Recent developments in multi-valley EMT show quantitative agreement with more detailed atomistic tight-binding calculations of phosphorus donors in silicon (Gamble, et. al., arXiv:1408.3159). Leveraging existing PDE solvers, we are developing a framework in which this multi-valley EMT is coupled to an integrated device-level description of several experimentally active qubit technologies. Device-level simulations of quantum operations will be discussed, as well as the extraction of process matrices at this level of theory. The authors gratefully acknowledge support from the Sandia National Laboratories Truman Fellowship Program, which is funded by the Laboratory Directed Research and Development (LDRD) Program. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Security Administration under contract DE-AC04-94AL85000.

Pracovní motivace v multi-level marketingu

OpenAIRE

Mrázková, Tereza

2015-01-01

The purpose of this work is to analyse the motivation in multi-level marketing company. The thesis introduces basic general marketing tools, but also multi-level marketing and the theory of motivation. The research in practical part was done in the form of electronical survey, which was completed by 71 responders. The responders were employees of specific company. The thesis does not only focus on the motivation in work in general, but also on the difference in motivation between male and fem...

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

International Nuclear Information System (INIS)

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

2014-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2014-08-21

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

A multi-technique approach for the characterization of Roman mural paintings

Energy Technology Data Exchange (ETDEWEB)

Toschi, Francesco [CNR-IMIP (Istituto di Metodologie Inorganiche e dei Plasmi), Area della Ricerca Roma 1, Via Salaria Km. 29,300, 00016 Monterotondo, Roma, (Italy); Paladini, Alessandra, E-mail: alessandra.paladini@cnr.it [CNR-IMIP (Istituto di Metodologie Inorganiche e dei Plasmi), Area della Ricerca Roma 1, Via Salaria Km. 29,300, 00016 Monterotondo, Roma, (Italy); Colosi, Francesca [CNR-ITABC (Istituto per le Tecnologie Applicate ai Beni Culturali), Area della Ricerca Roma 1, Via Salaria Km. 29,300, 00016 Monterotondo, Roma (Italy); Cafarelli, Patrizia; Valentini, Veronica [CNR-IMIP (Istituto di Metodologie Inorganiche e dei Plasmi), Area della Ricerca Roma 1, Via Salaria Km. 29,300, 00016 Monterotondo, Roma, (Italy); Falconieri, Mauro; Gagliardi, Serena [ENEA, C.R. Casaccia, via Anguillarese 301, 00060 Roma (Italy); Santoro, Paola [CNR-ISMA (Istituto di Studi sul Mediterraneo Antico), Area della Ricerca Roma 1, Via Salaria Km. 29,300, 00016 Monterotondo, Roma (Italy)

2013-11-01

In the frame of an ongoing archeological study on the Sabina area, a countryside close to Rome, white and red samples of roman wall paintings have been investigated by combining X-ray diffraction and different spectroscopic methodologies, namely laser induced breakdown spectroscopy, μ-Raman and Fourier transform infrared attenuated total reflectance spectroscopy. The used multi-technique approach has allowed the unambiguous identification of the red pigment as red ochre and has provided insight on the provenance of both the pigment and the material used for the realization of the wall paintings. The experimental results have confirmed some assumptions on the use of local materials in roman rural architecture.

A multi-technique phytoremediation approach to purify metals contaminated soil from e-waste recycling site.

Science.gov (United States)

Luo, Jie; Cai, Limei; Qi, Shihua; Wu, Jian; Sophie Gu, Xiaowen

2017-12-15

Multiple techniques for soil decontamination were combined to enhance the phytoremediation efficiency of Eucalyptus globulese and alleviate the corresponding environmental risks. The approach constituted of chelating agent using, electrokinetic remediation, plant hormone foliar application and phytoremediation was designed to remediate multi-metal contaminated soils from a notorious e-waste recycling town. The decontamination ability of E. globulese increased from 1.35, 58.47 and 119.18 mg per plant for Cd, Pb and Cu in planting controls to 7.57, 198.68 and 174.34 mg per plant in individual EDTA treatments, respectively, but simultaneously, 0.9-11.5 times more metals leached from chelator treatments relative to controls. Low (2 V) and moderate (4 V) voltage electric fields provoked the growth of the species while high voltage (10 V) had an opposite effect and metal concentrations of the plants elevated with the increment of voltage. Volumes of the leachate decreased from 1224 to 134 mL with voltage increasing from 0 to 10 V due to electroosmosis and electrolysis. Comparing with individual phytoremediation, foliar cytokinin treatments produced 56% more biomass and intercepted 2.5 times more leachate attributed to the enhanced transpiration rate. The synergistic combination of the individuals resulted in the most biomass production and metal accumulation of the species under the stress condition relative to other methods. Time required for the multi-technique approach to decontaminate Cd, Pb and Cu from soil was 2.1-10.4 times less than individual chelator addition, electric field application or plant hormone utilization. It's especially important that nearly no leachate (60 mL in total) was collected from the multi-technique system. This approach is a suitable method to remediate metal polluted site considering its decontamination efficiency and associated environmental negligible risk. Copyright © 2017 Elsevier Ltd. All rights reserved.

Realistic modelling of external flooding scenarios - A multi-disciplinary approach

International Nuclear Information System (INIS)

Brinkman, J.L.

2014-01-01

Extreme phenomena, such as storm surges or high river water levels, may endanger the safety of nuclear power plants (NPPs) by inundation of the plant site with subsequent damage on safety-related buildings. Flooding may result in simultaneous failures of safety-related components, such as service water pumps and electrical equipment. In addition, the accessibility of the plant may be impeded due to flooding of the plant environment. These consequences are so severe that, (re)assessments of flood risk and flood protection measures should be based on accurate state-of-the-art methods. Dutch nuclear regulations require that a nuclear power plant shall withstand all external initiating events with a return period lower than one million years. For external flooding, this requirement is the basis of the so-called nuclear design level (nucleair ontwerp peil, NOP) of the buildings for external flooding, i.e. the water level at which a system - among others, the nuclear island and the ultimate heat sink - should still function properly. In determining the NOP, the mean water level, wave height and wave behaviour during storm surges are taken into account. This concept could also be used to implement external flooding in a PSA, by assuming that floods exceeding NOP levels directly lead to core damage. However, this straightforward modelling ignores some important aspects: the first is the mitigating effect of the external flood protection as dikes or dunes; the second aspect is that although water levels lower than NOP will not directly lead to core damage, they could do so indirectly as a result of combinations of system loss by flooding and random failure of required safety systems that have to bring the plant in a safe, stable state. Time is a third aspect: failure mechanisms need time to develop and time (via duration of the flood) determines the amount of water on site. This paper describes a PSA approach that takes the (structural) reliability of the external defences

Multi-model predictive control method for nuclear steam generator water level

International Nuclear Information System (INIS)

Hu Ke; Yuan Jingqi

2008-01-01

The dynamics of a nuclear steam generator (SG) is very different according to the power levels and changes as time goes on. Therefore, it is an intractable as well as challenging task to improve the water level control system of the SG. In this paper, a robust model predictive control (RMPC) method is developed for the level control problem. Based on a multi-model framework, a combination of a local nominal model with a polytopic uncertain linear parameter varying (LPV) model is built to approximate the system's non-linear behavior. The optimization problem solved here is based on a receding horizon scheme involving the linear matrix inequality (LMI) technique. Closed loop stability and constraints satisfaction in the entire operating range are guaranteed by the feasibility of the optimization problem. Finally, simulation results show the effectiveness and the good performance of the proposed method

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

DEFF Research Database (Denmark)

Jørgensen, Ulrik

2012-01-01

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

Governance and the Commons in a Multi-Level World

Directory of Open Access Journals (Sweden)

Derek Armitage

2007-11-01

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

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

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Y. H. Subagadis

2014-09-01

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

Multi-level discriminative dictionary learning with application to large scale image classification.

Science.gov (United States)

Shen, Li; Sun, Gang; Huang, Qingming; Wang, Shuhui; Lin, Zhouchen; Wu, Enhua

2015-10-01

The sparse coding technique has shown flexibility and capability in image representation and analysis. It is a powerful tool in many visual applications. Some recent work has shown that incorporating the properties of task (such as discrimination for classification task) into dictionary learning is effective for improving the accuracy. However, the traditional supervised dictionary learning methods suffer from high computation complexity when dealing with large number of categories, making them less satisfactory in large scale applications. In this paper, we propose a novel multi-level discriminative dictionary learning method and apply it to large scale image classification. Our method takes advantage of hierarchical category correlation to encode multi-level discriminative information. Each internal node of the category hierarchy is associated with a discriminative dictionary and a classification model. The dictionaries at different layers are learnt to capture the information of different scales. Moreover, each node at lower layers also inherits the dictionary of its parent, so that the categories at lower layers can be described with multi-scale information. The learning of dictionaries and associated classification models is jointly conducted by minimizing an overall tree loss. The experimental results on challenging data sets demonstrate that our approach achieves excellent accuracy and competitive computation cost compared with other sparse coding methods for large scale image classification.

Modelling approach to simulate reductions in LDL cholesterol levels after combined intake of statins and phytosterols/-stanols in humans

Science.gov (United States)

2011-01-01

Background To examine the effects on LDL cholesterol of the combined use of statins and phytosterols/-stanols, in vivo studies and clinical trials are necessary. However, for a better interpretation of the experimental data as well as to possibly predict cholesterol levels given a certain dosing regimen of statins and phytosterols/-stanols a more theoretically based approach is helpful. This study aims to construct a mathematical model to simulate reductions in low-density lipoprotein (LDL) cholesterol in persons who combine the use of statins with a high intake of phytosterols/-stanols, e.g. by the use of functional foods. Methods and Results The proposed model includes the cholesterol pool size in the liver and serum levels of very low-density lipoprotein (VLDL) cholesterol. Both an additional and a multiplicative effect of phytosterol/-stanol intake on LDL cholesterol reduction were predicted from the model. The additional effect relates to the decrease of dietary cholesterol uptake reduction, the multiplicative effect relates to the decrease in enterohepatic recycling efficiency, causing increased cholesterol elimination through bile. From the model, it was demonstrated that a daily intake of 2 g phytosterols/-stanols reduces LDL cholesterol level by about 8% to 9% on top of the reduction resulting from statin use. The additional decrease in LDL cholesterol caused by phytosterol/-stanol use at the recommended level of 2 g/d appeared to be similar or even greater than the decrease achieved by doubling the statin dose. Conclusion We proposed a simplified mathematical model to simulate the reduction in LDL cholesterol after separate and combined intake of statins and functional foods acting on intestinal (re)absorption of cholesterol or bile acids in humans. In future work, this model can be extended to include more complex (regulatory) mechanisms. PMID:22018353

Modelling approach to simulate reductions in LDL cholesterol levels after combined intake of statins and phytosterols/-stanols in humans

Directory of Open Access Journals (Sweden)

Eussen Simone RBM

2011-10-01

Full Text Available Abstract Background To examine the effects on LDL cholesterol of the combined use of statins and phytosterols/-stanols, in vivo studies and clinical trials are necessary. However, for a better interpretation of the experimental data as well as to possibly predict cholesterol levels given a certain dosing regimen of statins and phytosterols/-stanols a more theoretically based approach is helpful. This study aims to construct a mathematical model to simulate reductions in low-density lipoprotein (LDL cholesterol in persons who combine the use of statins with a high intake of phytosterols/-stanols, e.g. by the use of functional foods. Methods and Results The proposed model includes the cholesterol pool size in the liver and serum levels of very low-density lipoprotein (VLDL cholesterol. Both an additional and a multiplicative effect of phytosterol/-stanol intake on LDL cholesterol reduction were predicted from the model. The additional effect relates to the decrease of dietary cholesterol uptake reduction, the multiplicative effect relates to the decrease in enterohepatic recycling efficiency, causing increased cholesterol elimination through bile. From the model, it was demonstrated that a daily intake of 2 g phytosterols/-stanols reduces LDL cholesterol level by about 8% to 9% on top of the reduction resulting from statin use. The additional decrease in LDL cholesterol caused by phytosterol/-stanol use at the recommended level of 2 g/d appeared to be similar or even greater than the decrease achieved by doubling the statin dose. Conclusion We proposed a simplified mathematical model to simulate the reduction in LDL cholesterol after separate and combined intake of statins and functional foods acting on intestinal (reabsorption of cholesterol or bile acids in humans. In future work, this model can be extended to include more complex (regulatory mechanisms.

OBJECT-ORIENTED CHANGE DETECTION BASED ON MULTI-SCALE APPROACH

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Y. Jia

2016-06-01

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

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

Directory of Open Access Journals (Sweden)

Qiaoning Yang

2015-10-01

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

Multi-model approach to characterize human handwriting motion.

Science.gov (United States)

Chihi, I; Abdelkrim, A; Benrejeb, M

2016-02-01

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

A MULTI-OBJECTIVE APPROACH TO THE EVALUATION OF INNOVATIVE POTENTIAL OF THE TOURISM INDUSTRY ORGANIZATIONS

Directory of Open Access Journals (Sweden)

Tat’yana Pavlovna Levchenko

2018-02-01

Full Text Available Speaking about innovation in the tourism industry and hotel business, in particular, it usually means events of a systemic nature, with quality novelty, aimed at achieving positive changes, stable functioning and dynamic development. Along with general economic factors that determine the uneven demand for services of hospitality, it is explained by the sharp increase in dependence of their tourism and recreational opportunities from innovative potential (IP, capability of adapting to challenging competitive environment. The article considers a multi-objective approach to the study of the innovative potential of the tourism industry organizations. Its essence lies in the fact that the choice of the structural elements from the point of view of their value and importance (in any combination cannot be established a priori, without sufficient objective analysis on some of the more important criteria for achieving the goals. A diagnostic analysis and evaluation of the innovation potential of several hotel organizations from the standpoint of a multi-purpose approach is performed.

Structural diversity: a multi-dimensional approach to assess recreational services in urban parks.

Science.gov (United States)

Voigt, Annette; Kabisch, Nadja; Wurster, Daniel; Haase, Dagmar; Breuste, Jürgen

2014-05-01

Urban green spaces provide important recreational services for urban residents. In general, when park visitors enjoy "the green," they are in actuality appreciating a mix of biotic, abiotic, and man-made park infrastructure elements and qualities. We argue that these three dimensions of structural diversity have an influence on how people use and value urban parks. We present a straightforward approach for assessing urban parks that combines multi-dimensional landscape mapping and questionnaire surveys. We discuss the method as well the results from its application to differently sized parks in Berlin and Salzburg.

All-fiber 7x1 signal combiner for incoherent laser beam combining

Science.gov (United States)

Noordegraaf, D.; Maack, M. D.; Skovgaard, P. M. W.; Johansen, J.; Becker, F.; Belke, S.; Blomqvist, M.; Laegsgaard, J.

2011-02-01

We demonstrate an all-fiber 7x1 signal combiner for incoherent laser beam combining. This is a potential key component for reaching several kW of stabile laser output power. The combiner couples the output from 7 single-mode (SM) fiber lasers into a single multi-mode (MM) fiber. The input signal fibers have a core diameter of 17 μm and the output MM fiber has a core diameter of 100 μm. In a tapered section light gradually leaks out of the SM fibers and is captured by a surrounding fluorine-doped cladding. The combiner is tested up to 2.5 kW of combined output power and only a minor increase in device temperature is observed. At an intermediate power level of 600 W a beam parameter product (BPP) of 2.22 mm x mrad is measured, corresponding to an M2 value of 6.5. These values are approaching the theoretical limit dictated by brightness conservation.

An Approach for Autonomy: A Collaborative Communication Framework for Multi-Agent Systems

Science.gov (United States)

Dufrene, Warren Russell, Jr.

2005-01-01

Research done during the last three years has studied the emersion properties of Complex Adaptive Systems (CAS). The deployment of Artificial Intelligence (AI) techniques applied to remote Unmanned Aerial Vehicles has led the author to investigate applications of CAS within the field of Autonomous Multi-Agent Systems. The core objective of current research efforts is focused on the simplicity of Intelligent Agents (IA) and the modeling of these agents within complex systems. This research effort looks at the communication, interaction, and adaptability of multi-agents as applied to complex systems control. The embodiment concept applied to robotics has application possibilities within multi-agent frameworks. A new framework for agent awareness within a virtual 3D world concept is possible where the vehicle is composed of collaborative agents. This approach has many possibilities for applications to complex systems. This paper describes the development of an approach to apply this virtual framework to the NASA Goddard Space Flight Center (GSFC) tetrahedron structure developed under the Autonomous Nano Technology Swarm (ANTS) program and the Super Miniaturized Addressable Reconfigurable Technology (SMART) architecture program. These projects represent an innovative set of novel concepts deploying adaptable, self-organizing structures composed of many tetrahedrons. This technology is pushing current applied Agents Concepts to new levels of requirements and adaptability.

Multi-level iteration optimization for diffusive critical calculation

International Nuclear Information System (INIS)

Li Yunzhao; Wu Hongchun; Cao Liangzhi; Zheng Youqi

2013-01-01

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

A Multi-Temporal Remote Sensing Approach to Freshwater Turtle Conservation

Science.gov (United States)

Mui, Amy B.

Freshwater turtles are a globally declining taxa, and estimates of population status are not available for many species. Primary causes of decline stem from widespread habitat loss and degradation, and obtaining spatially-explicit information on remaining habitat across a relevant spatial scale has proven challenging. The discipline of remote sensing science has been employed widely in studies of biodiversity conservation, but it has not been utilized as frequently for cryptic, and less vagile species such as turtles, despite their vulnerable status. The work presented in this thesis investigates how multi-temporal remote sensing imagery can contribute key information for building spatially-explicit and temporally dynamic models of habitat and connectivity for the threatened, Blanding's turtle (Emydoidea blandingii) in southern Ontario, Canada. I began with outlining a methodological approach for delineating freshwater wetlands from high spatial resolution remote sensing imagery, using a geographic object-based image analysis (GEOBIA) approach. This method was applied to three different landscapes in southern Ontario, and across two biologically relevant seasons during the active (non-hibernating) period of Blanding's turtles. Next, relevant environmental variables associated with turtle presence were extracted from remote sensing imagery, and a boosted regression tree model was developed to predict the probability of occurrence of this species. Finally, I analysed the movement potential for Blanding's turtles in a disturbed landscape using a combination of approaches. Results indicate that (1) a parsimonious GEOBIA approach to land cover mapping, incorporating texture, spectral indices, and topographic information can map heterogeneous land cover with high accuracy, (2) remote-sensing derived environmental variables can be used to build habitat models with strong predictive power, and (3) connectivity potential is best estimated using a variety of approaches

Multi-Period Natural Gas Market Modeling. Applications, Stochastic Extensions and Solution Approaches

International Nuclear Information System (INIS)

Egging, R.G.

2010-11-01

This dissertation develops deterministic and stochastic multi-period mixed complementarity problems (MCP) for the global natural gas market, as well as solution approaches for large-scale stochastic MCP. The deterministic model is unique in the combination of the level of detail of the actors in the natural gas markets and the transport options, the detailed regional and global coverage, the multi-period approach with endogenous capacity expansions for transportation and storage infrastructure, the seasonal variation in demand and the representation of market power according to Nash-Cournot theory. The model is applied to several scenarios for the natural gas market that cover the formation of a cartel by the members of the Gas Exporting Countries Forum, a low availability of unconventional gas in the United States, and cost reductions in long-distance gas transportation. The results provide insights in how different regions are affected by various developments, in terms of production, consumption, traded volumes, prices and profits of market participants. The stochastic MCP is developed and applied to a global natural gas market problem with four scenarios for a time horizon until 2050 with nineteen regions and containing 78,768 variables. The scenarios vary in the possibility of a gas market cartel formation and varying depletion rates of gas reserves in the major gas importing regions. Outcomes for hedging decisions of market participants show some significant shifts in the timing and location of infrastructure investments, thereby affecting local market situations. A first application of Benders decomposition (BD) is presented to solve a large-scale stochastic MCP for the global gas market with many hundreds of first-stage capacity expansion variables and market players exerting various levels of market power. The largest problem solved successfully using BD contained 47,373 variables of which 763 first-stage variables, however using BD did not result in

On decoding of multi-level MPSK modulation codes

Science.gov (United States)

Lin, Shu; Gupta, Alok Kumar

1990-01-01

The decoding problem of multi-level block modulation codes is investigated. The hardware design of soft-decision Viterbi decoder for some short length 8-PSK block modulation codes is presented. An effective way to reduce the hardware complexity of the decoder by reducing the branch metric and path metric, using a non-uniform floating-point to integer mapping scheme, is proposed and discussed. The simulation results of the design are presented. The multi-stage decoding (MSD) of multi-level modulation codes is also investigated. The cases of soft-decision and hard-decision MSD are considered and their performance are evaluated for several codes of different lengths and different minimum squared Euclidean distances. It is shown that the soft-decision MSD reduces the decoding complexity drastically and it is suboptimum. The hard-decision MSD further simplifies the decoding while still maintaining a reasonable coding gain over the uncoded system, if the component codes are chosen properly. Finally, some basic 3-level 8-PSK modulation codes using BCH codes as component codes are constructed and their coding gains are found for hard decision multistage decoding.

Multi-level governance in EU climate law

NARCIS (Netherlands)

Vedder, Hans; Woerdman, Edwin; Roggenkamp, Martha; Holwerda, Marijn

2015-01-01

This chapter analyses the multi-level governance in EU climate law; it connects the international arena, with EU and national decision-making and relates climate change considerations to competitiveness concerns.

The multi-level perspective analysis: Indonesia geothermal energy transition study

Science.gov (United States)

Wisaksono, A.; Murphy, J.; Sharp, J. H.; Younger, P. L.

2018-01-01

The study adopts a multi-level perspective in technology transition to analyse how the transition process in the development of geothermal energy in Indonesia is able to compete against the incumbent fossil-fuelled energy sources. Three levels of multi-level perspective are socio-technical landscape (ST-landscape), socio-technical regime (ST-regime) and niche innovations in Indonesia geothermal development. The identification, mapping and analysis of the dynamic relationship between each level are the important pillars of the multi-level perspective framework. The analysis considers the set of rules, actors and controversies that may arise in the technological transition process. The identified geothermal resource risks are the basis of the emerging geothermal technological innovations in Indonesian geothermal. The analysis of this study reveals the transition pathway, which yields a forecast for the Indonesian geothermal technology transition in the form of scenarios and probable impacts.

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

Directory of Open Access Journals (Sweden)

Aleksandras Chlebnikovas

2015-10-01

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

Near-Earth object hazardous impact: A Multi-Criteria Decision Making approach.

Science.gov (United States)

Sánchez-Lozano, J M; Fernández-Martínez, M

2016-11-16

The impact of a near-Earth object (NEO) may release large amounts of energy and cause serious damage. Several NEO hazard studies conducted over the past few years provide forecasts, impact probabilities and assessment ratings, such as the Torino and Palermo scales. These high-risk NEO assessments involve several criteria, including impact energy, mass, and absolute magnitude. The main objective of this paper is to provide the first Multi-Criteria Decision Making (MCDM) approach to classify hazardous NEOs. Our approach applies a combination of two methods from a widely utilized decision making theory. Specifically, the Analytic Hierarchy Process (AHP) methodology is employed to determine the criteria weights, which influence the decision making, and the Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) is used to obtain a ranking of alternatives (potentially hazardous NEOs). In addition, NEO datasets provided by the NASA Near-Earth Object Program are utilized. This approach allows the classification of NEOs by descending order of their TOPSIS ratio, a single quantity that contains all of the relevant information for each object.

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

Science.gov (United States)

Wałach, Daniel; Sagan, Joanna; Gicala, Magdalena

2017-10-01

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

A practical approach for solving multi-objective reliability redundancy allocation problems using extended bare-bones particle swarm optimization

International Nuclear Information System (INIS)

Zhang, Enze; Wu, Yifei; Chen, Qingwei

2014-01-01

This paper proposes a practical approach, combining bare-bones particle swarm optimization and sensitivity-based clustering for solving multi-objective reliability redundancy allocation problems (RAPs). A two-stage process is performed to identify promising solutions. Specifically, a new bare-bones multi-objective particle swarm optimization algorithm (BBMOPSO) is developed and applied in the first stage to identify a Pareto-optimal set. This algorithm mainly differs from other multi-objective particle swarm optimization algorithms in the parameter-free particle updating strategy, which is especially suitable for handling the complexity and nonlinearity of RAPs. Moreover, by utilizing an approach based on the adaptive grid to update the global particle leaders, a mutation operator to improve the exploration ability and an effective constraint handling strategy, the integrated BBMOPSO algorithm can generate excellent approximation of the true Pareto-optimal front for RAPs. This is followed by a data clustering technique based on difference sensitivity in the second stage to prune the obtained Pareto-optimal set and obtain a small, workable sized set of promising solutions for system implementation. Two illustrative examples are presented to show the feasibility and effectiveness of the proposed approach

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

Science.gov (United States)

Stanga, I. C.; Grozavu, A.

2012-04-01

Vulnerability assessment aims, most frequently, to emphasize internal fragility of a system comparing to a reference standard, to similar systems or in relation to a given hazard. Internal fragility, either biophysical or structural, may affect the capacity to predict, to prepare for, to cope with or to recover from a disaster. Thus, vulnerability is linked to resilience and adaptive capacity. From local level to global one, vulnerability factors and corresponding indicators are different and their significance must be tested and validated in a well-structured conceptual and methodological framework. In this paper, the authors aim to show the real vulnerability of rural settlements in Eastern Romania in a multi-level approach. The research area, Tutova Hills, counts about 3421 sq.km and more than 200.000 inhabitants in 421 villages characterized by deficient accessibility, lack of endowments, subsistential agriculture, high pressure on natural environment (especially on forest and soil resources), poverty and aging process of population. Factors that could influence the vulnerability of these rural settlements have been inventoried and assigned into groups through a cluster analysis: habitat and technical urban facilities, infrastructure, economical, social and demographical indicators, environment quality, management of emergency situations etc. Firstly, the main difficulty was to convert qualitative variable in quantitative indicators and to standardize all values to make possible mathematical and statistical processing of data. Secondly, the great variability of vulnerability factors, their different measuring units and their high amplitude of variation require different method of standardization in order to obtain values between zero (minimum vulnerability) and one (maximum vulnerability). Final vulnerability indicators were selected and integrated in a general scheme, according to their significance resulted from an appropriate factor analysis: linear and

Un approccio “multi-scala” per la gestione del patrimonio culturale italiano / A “multi-scale” approach for the management of Italian cultural heritage

Directory of Open Access Journals (Sweden)

Fabio Donato

2011-11-01

Questo articolo intende dunque svolgere una riflessione critica sulla opportunità di indirizzarsi verso una gestione di tipo “multi-scala”, che comprenda sia un livello organizzativo “micro” sia un livello organizzativo “meso”. L'effettiva capacità di funzionamento del modello “multi-scala” deriverà dalla capacità di rendere armonici e sinergici tra di loro tali due livelli organizzativi. Today, the management model adopted for Italian cultural organizations and Italian cultural heritage derives from the new public management theory, that has been designed, crafted and firstly implemented in Anglophone countries. Instead, the management model should be consistent with the features of the cultural heritage of the specific country. In the Italian case, that is a widespread cultural heritage, strongly linked with the history of the territory. Hence, this article aims at analyzing the opportunity of developing a “multi-scale” management approach, able to combine the traditional “micro” organizational perspective, with a “meso” organizational perspective.

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

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Zhao Hongbo

2009-09-01

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

ROBUST LOCALISATION OF MULTIPLE SPEAKERS EXPLOITING HEAD MOVEMENTS AND MULTI-CONDITIONAL TRAINING OF BINAURAL CUES

DEFF Research Database (Denmark)

May, Tobias; Ma, Ning; Brown, Guy

2015-01-01

differences (ITDs) and interaural level dif- ferences (ILDs) in the front and rear hemifield, a machine hearing system is presented which combines supervised learning of binaural cues using multi-conditional training (MCT) with a head movement strategy. A systematic evaluation showed that this approach...

Multi-Level Anomaly Detection on Time-Varying Graph Data

Energy Technology Data Exchange (ETDEWEB)

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

2015-01-01

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

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

International Nuclear Information System (INIS)

Sayyaadi, Hoseyn

2009-01-01

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

A Community Multi-Omics Approach towards the Assessment of Surface Water Quality in an Urban River System

Directory of Open Access Journals (Sweden)

David J. Beale

2017-03-01

Full Text Available A multi-omics approach was applied to an urban river system (the Brisbane River (BR, Queensland, Australia in order to investigate surface water quality and characterize the bacterial population with respect to water contaminants. To do this, bacterial metagenomic amplicon-sequencing using Illumina next-generation sequencing (NGS of the V5–V6 hypervariable regions of the 16S rRNA gene and untargeted community metabolomics using gas chromatography coupled with mass spectrometry (GC-MS were utilized. The multi-omics data, in combination with fecal indicator bacteria (FIB counts, trace metal concentrations (by inductively coupled plasma mass spectrometry (ICP-MS and in-situ water quality measurements collected from various locations along the BR were then used to assess the health of the river ecosystem. Sites sampled represented the transition from less affected (upstream to polluted (downstream environments along the BR. Chemometric analysis of the combined datasets indicated a clear separation between the sampled environments. Burkholderiales and Cyanobacteria were common key factors for differentiation of pristine waters. Increased sugar alcohol and short-chain fatty acid production was observed by Actinomycetales and Rhodospirillaceae that are known to form biofilms in urban polluted and brackish waters. Results from this study indicate that a multi-omics approach enables a deep understanding of the health of an aquatic ecosystem, providing insight into the bacterial diversity present and the metabolic output of the population when exposed to environmental contaminants.

A multi-user selective undo/redo approach for collaborative CAD systems

Directory of Open Access Journals (Sweden)

Yuan Cheng

2014-04-01

Full Text Available The engineering design process is a creative process, and the designers must repeatedly apply Undo/Redo operations to modify CAD models to explore new solutions. Undo/Redo has become one of most important functions in interactive graphics and CAD systems. Undo/Redo in a collaborative CAD system is also very helpful for collaborative awareness among a group of cooperative designers to eliminate misunderstanding and to recover from design error. However, Undo/Redo in a collaborative CAD system is much more complicated. This is because a single erroneous operation is propagated to other remote sites, and operations are interleaved at different sites. This paper presents a multi-user selective Undo/Redo approach in full distributed collaborative CAD systems. We use site ID and State Vectors to locate the Undo/Redo target at each site. By analyzing the composition of the complex CAD model, a tree-like structure called Feature Combination Hierarchy is presented to describe the decomposition of a CAD model. Based on this structure, the dependency relationship among features is clarified. B-Rep re-evaluation is simplified with the assistance of the Feature Combination Hierarchy. It can be proven that the proposed Undo/Redo approach satisfies the intention preservation and consistency maintenance correctness criteria for collaborative systems.

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

Directory of Open Access Journals (Sweden)

Dane Brown

2017-07-01

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

Multi-objective thermodynamic optimization of combined Brayton and inverse Brayton cycles using genetic algorithms

International Nuclear Information System (INIS)

Besarati, S.M.; Atashkari, K.; Jamali, A.; Hajiloo, A.; Nariman-zadeh, N.

2010-01-01

This paper presents a simultaneous optimization study of two outputs performance of a previously proposed combined Brayton and inverse Brayton cycles. It has been carried out by varying the upper cycle pressure ratio, the expansion pressure of the bottom cycle and using variable, above atmospheric, bottom cycle inlet pressure. Multi-objective genetic algorithms are used for Pareto approach optimization of the cycle outputs. The two important conflicting thermodynamic objectives that have been considered in this work are net specific work (w s ) and thermal efficiency (η th ). It is shown that some interesting features among optimal objective functions and decision variables involved in the Baryton and inverse Brayton cycles can be discovered consequently.

Multi-level Reconfigurable Self-organization in Overlay Services

NARCIS (Netherlands)

Pournaras, E.

2013-01-01

Large-scale decentralized systems organized in overlay networks are complex to manage. Such systems integrate organizational complexity in the application-level resulting in low abstraction and modularity in their services. This thesis introduces a multi-level conceptual architecture for overlay

PENGEMBANGAN MEDIA LUBANG MULTI LEVEL UNTUK PEMBELAJARAN LEMPAR TANGKAP BOLA KECIL

Directory of Open Access Journals (Sweden)

Tri Aryo Trubus Anom

2017-02-01

Full Text Available This research aims to develop a media Hole Multi Level to capture the small ball throwing learning grade IV elementary school level that can increase students roll control. The model of the research is the development of research and data analysis in the form of a percentage of data types with a description of the qualitative and quantitative. Procedure development include; 1 Potential problems, 2 Data collection, 3 Early media product design Multi Level Hole, 4 Design Validation by expert penjas and learning experts, 5 Revision products I, 6 Trials I in MI Ma’arif NU Darmakradenan, 7 Product revision II, 8 Trial II at four elementary school in the village of Darmakradenan, 9 Product revision III, 10 And products. The results of expert validation against the media Pit Multi Level was 80%, I Test of 83,23%, and II trials of 85.97%. Those results can be concluded that the development of the media Pit Multi Level can be used to capture the small ball throwing learning grade IV elementary school level.

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

Energy Technology Data Exchange (ETDEWEB)

Thetiot, R

2000-07-01

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

Shoreline change after 12 years of tsunami in Banda Aceh, Indonesia: a multi-resolution, multi-temporal satellite data and GIS approach

Science.gov (United States)

Sugianto, S.; Heriansyah; Darusman; Rusdi, M.; Karim, A.

2018-04-01

The Indian Ocean Tsunami event on the 26 December 2004 has caused severe damage of some shorelines in Banda Aceh City, Indonesia. Tracing back the impact can be seen using remote sensing data combined with GIS. The approach is incorporated with image processing to analyze the extent of shoreline changes with multi-temporal data after 12 years of tsunami. This study demonstrates multi-resolution and multi-temporal satellite images of QuickBird and IKONOS to demarcate the shoreline of Banda Aceh shoreline from before and after tsunami. The research has demonstrated a significant change to the shoreline in the form of abrasion between 2004 and 2005 from few meters to hundred meters’ change. The change between 2004 and 2011 has not returned to the previous stage of shoreline before the tsunami, considered post tsunami impact. The abrasion occurs between 18.3 to 194.93 meters. Further, the change in 2009-2011 shows slowly change of shoreline of Banda Aceh, considered without impact of tsunami e.g. abrasion caused by ocean waves that erode the coast and on specific areas accretion occurs caused by sediment carried by the river flow into the sea near the shoreline of the study area.

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

Directory of Open Access Journals (Sweden)

2007-05-01

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

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

NARCIS (Netherlands)

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

2017-01-01

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

Composite decision support by combining cost-benefit and multi-criteria decision

DEFF Research Database (Denmark)

Barfod, Michael Bruhn; Salling, Kim Bang; Leleur, Steen

2011-01-01

This paper concerns composite decision support based on combining cost-benefit analysis (CBA) with multi-criteria decision analysis (MCDA) for the assessment of economic as well as strategic impacts within transport projects. Specifically a composite model for assessment (COSIMA) is presented...

Entanglement of Grassmannian Coherent States for Multi-Partite n-Level Systems

Directory of Open Access Journals (Sweden)

Ghader Najarbashi

2011-01-01

Full Text Available In this paper, we investigate the entanglement of multi-partite Grassmannian coherent states (GCSs described by Grassmann numbers for n>2 degree of nilpotency. Choosing an appropriate weight function, we show that it is possible to construct some well-known entangled pure states, consisting of GHZ, W, Bell, cluster type and bi-separable states, which are obtained by integrating over tensor product of GCSs. It is shown that for three level systems, the Grassmann creation and annihilation operators b and b^† together with bz form a closed deformed algebra, i.e., SU_q(2 with q=e^{2πi/3}, which is useful to construct entangled qutrit-states. The same argument holds for three level squeezed states. Moreover combining the Grassmann and bosonic coherent states we construct maximal entangled super coherent states.

Investigations of phosphate coatings of galvanized steel sheets by a surface-analytical multi-method approach

International Nuclear Information System (INIS)

Bubert, H.; Garten, R.; Klockenkaemper, R.; Puderbach, H.

1983-01-01

Corrosion protective coatings on galvanized steel sheets have been studied by a combination of SEM, EDX, AES, ISS and SIMS. Analytical statements concerning such rough, poly-crystalline and contaminated surfaces of technical samples are quite difficult to obtain. The use of a surface-analytical multi-method approach overcomes, the intrinsic limitations of the individual method applied, thus resulting in a consistent picture of those technical surfaces. Such results can be used to examine technical faults and to optimize the technical process. (Author)

Antimicrobial combinations: Bliss independence and Loewe additivity derived from mechanistic multi-hit models

Science.gov (United States)

Yu, Guozhi; Hozé, Nathanaël; Rolff, Jens

2016-01-01

Antimicrobial peptides (AMPs) and antibiotics reduce the net growth rate of bacterial populations they target. It is relevant to understand if effects of multiple antimicrobials are synergistic or antagonistic, in particular for AMP responses, because naturally occurring responses involve multiple AMPs. There are several competing proposals describing how multiple types of antimicrobials add up when applied in combination, such as Loewe additivity or Bliss independence. These additivity terms are defined ad hoc from abstract principles explaining the supposed interaction between the antimicrobials. Here, we link these ad hoc combination terms to a mathematical model that represents the dynamics of antimicrobial molecules hitting targets on bacterial cells. In this multi-hit model, bacteria are killed when a certain number of targets are hit by antimicrobials. Using this bottom-up approach reveals that Bliss independence should be the model of choice if no interaction between antimicrobial molecules is expected. Loewe additivity, on the other hand, describes scenarios in which antimicrobials affect the same components of the cell, i.e. are not acting independently. While our approach idealizes the dynamics of antimicrobials, it provides a conceptual underpinning of the additivity terms. The choice of the additivity term is essential to determine synergy or antagonism of antimicrobials. This article is part of the themed issue ‘Evolutionary ecology of arthropod antimicrobial peptides’. PMID:27160596

Antimicrobial combinations: Bliss independence and Loewe additivity derived from mechanistic multi-hit models.

Science.gov (United States)

Baeder, Desiree Y; Yu, Guozhi; Hozé, Nathanaël; Rolff, Jens; Regoes, Roland R

2016-05-26

Antimicrobial peptides (AMPs) and antibiotics reduce the net growth rate of bacterial populations they target. It is relevant to understand if effects of multiple antimicrobials are synergistic or antagonistic, in particular for AMP responses, because naturally occurring responses involve multiple AMPs. There are several competing proposals describing how multiple types of antimicrobials add up when applied in combination, such as Loewe additivity or Bliss independence. These additivity terms are defined ad hoc from abstract principles explaining the supposed interaction between the antimicrobials. Here, we link these ad hoc combination terms to a mathematical model that represents the dynamics of antimicrobial molecules hitting targets on bacterial cells. In this multi-hit model, bacteria are killed when a certain number of targets are hit by antimicrobials. Using this bottom-up approach reveals that Bliss independence should be the model of choice if no interaction between antimicrobial molecules is expected. Loewe additivity, on the other hand, describes scenarios in which antimicrobials affect the same components of the cell, i.e. are not acting independently. While our approach idealizes the dynamics of antimicrobials, it provides a conceptual underpinning of the additivity terms. The choice of the additivity term is essential to determine synergy or antagonism of antimicrobials.This article is part of the themed issue 'Evolutionary ecology of arthropod antimicrobial peptides'. © 2016 The Author(s).

Multi-agent approach for power system in a smart grid protection context

DEFF Research Database (Denmark)

Abedini, Reza; Pinto, Tiago; Morais, Hugo

2013-01-01

electricity markets and in the other hand with increasing penetration of Distributed Generation (DG) because of environment issues and diminishing in fossil fuel reserves and its price growth, made microgrid more attractive. Micro grids are considers as partial of SmartGrid system to accommodate DGs as well......With increasing penetration of electricity application in society and the need of majority of appliance to electricity, high level of reliability becomes more essential; in one hand with deregulation of electricity market in production, transmission and distribution and emerge of competitive...... proposes a new approach for protection in a Microgrid environment as a part of SmartGrid: Multi-agent system to Protections Coordination (MAS-ProteC) which integrated in MASGriP (Multi-Agent Smart Grid Platform), providing protection services within network operation in SmartGrid in electricity market...

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

Science.gov (United States)

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

2015-01-01

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

A Review of Structure Construction of Silk Fibroin Biomaterials from Single Structures to Multi-Level Structures

Directory of Open Access Journals (Sweden)

Yu Qi

2017-03-01

Full Text Available The biological performance of artificial biomaterials is closely related to their structure characteristics. Cell adhesion, migration, proliferation, and differentiation are all strongly affected by the different scale structures of biomaterials. Silk fibroin (SF, extracted mainly from silkworms, has become a popular biomaterial due to its excellent biocompatibility, exceptional mechanical properties, tunable degradation, ease of processing, and sufficient supply. As a material with excellent processability, SF can be processed into various forms with different structures, including particulate, fiber, film, and three-dimensional (3D porous scaffolds. This review discusses and summarizes the various constructions of SF-based materials, from single structures to multi-level structures, and their applications. In combination with single structures, new techniques for creating special multi-level structures of SF-based materials, such as micropatterning and 3D-printing, are also briefly addressed.

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

Science.gov (United States)

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

2016-01-01

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

Extension of the HAL QCD approach to inelastic and multi-particle scatterings in lattice QCD

Science.gov (United States)

Aoki, S.

We extend the HAL QCD approach, with which potentials between two hadrons can be obtained in QCD at energy below inelastic thresholds, to inelastic and multi-particle scatterings. We first derive asymptotic behaviors of the Nambu-Bethe-Salpeter (NBS) wave function at large space separations for systems with more than 2 particles, in terms of the one-shell $T$-matrix consrainted by the unitarity of quantum field theories. We show that its asymptotic behavior contains phase shifts and mixing angles of $n$ particle scatterings. This property is one of the essential ingredients of the HAL QCD scheme to define "potential" from the NBS wave function in quantum field theories such as QCD. We next construct energy independent but non-local potentials above inelastic thresholds, in terms of these NBS wave functions. We demonstrate an existence of energy-independent coupled channel potentials with a non-relativistic approximation, where momenta of all particles are small compared with their own masses. Combining these two results, we can employ the HAL QCD approach also to investigate inelastic and multi-particle scatterings.

Multi-Criteria Approach in Multifunctional Building Design Process

Science.gov (United States)

Gerigk, Mateusz

2017-10-01

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

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

Science.gov (United States)

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

2017-04-01

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

A collision dynamics model of a multi-level train

Science.gov (United States)

2006-11-05

In train collisions, multi-level rail passenger vehicles can deform in modes that are different from the behavior of single level cars. The deformation in single level cars usually occurs at the front end during a collision. In one particular inciden...

Multi-morbidity, dependency, and frailty singly or in combination have different impact on health outcomes.

Science.gov (United States)

Woo, Jean; Leung, Jason

2014-04-01

Multi-morbidity, dependency, and frailty were studied simultaneously in a community-living cohort of 4,000 men and women aged 65 years and over to examine the independent and combined effects on four health outcomes (mortality, decline in physical function, depression, and polypharmacy). The influence of socioeconomic status on these relationships is also examined. Mortality data was documented after a mean follow-up period of 9 years, while other health outcomes were documented after 4 years of follow-up. Fifteen percent of the cohort did not have any of these syndromes. Of the remaining participants, nearly one third had multi-morbidity and frailty (pre-frail and frail), while all three syndromes were present in 11 %. All syndromes as well as socioeconomic status were significantly associated with all health outcomes. Mortality was only increased for age, being male, frailty status, and combinations of syndromes that included frailty. Both multi-morbidity and frailtymale was protective. Only a combination of all three syndromes, and age per se, increased the risk of depressive symptoms at 4 years while being male conferred reduced risk. Multi-morbidity, but not frailty status or dependency, and all syndrome combinations that included multi-morbidity were associated with use of ≥ four medications. Decline in homeostatic function with age may thus be quantified and taken into account in prediction of various health outcomes, with a view to prevention, management, formulation of guidelines, service planning, and the conduct of randomized controlled trials of interventions or treatment.

Multi-level governance-perspective on management of nuclear waste disposal. A comparative analysis

Energy Technology Data Exchange (ETDEWEB)

Brunnengraeber, Achim; Haefner, Daniel

2015-07-01

The primary aim of the project is to conduct a detailed social and political analysis of the preconditions for the development of an acceptable strategy for nuclear waste disposal in Germany. This includes the identification of stakeholders and their interests, responsibilities, value systems, views and expectations as well as paths for a constructive approach to dialogue and problem-solving. A focus of the research project will be an international comparative multi-level governance analysis of acceptance patterns and steering mechanisms for conflict resolution.

Multi-level governance-perspective on management of nuclear waste disposal. A comparative analysis

International Nuclear Information System (INIS)

Brunnengraeber, Achim; Haefner, Daniel

2015-01-01

The primary aim of the project is to conduct a detailed social and political analysis of the preconditions for the development of an acceptable strategy for nuclear waste disposal in Germany. This includes the identification of stakeholders and their interests, responsibilities, value systems, views and expectations as well as paths for a constructive approach to dialogue and problem-solving. A focus of the research project will be an international comparative multi-level governance analysis of acceptance patterns and steering mechanisms for conflict resolution.

A multi-attribute approach to the rationalization of radiation protection options

International Nuclear Information System (INIS)

Lombard, J.; Oudiz, A.

1979-01-01

Application of the ALARA principle requires the use of quantitative methods such as cost-benefit, cost-effectiveness, multi-attribute and other analyses. An example is presented of the application of a multi-attribute analysis in connection with the determination of ALARA levels for the light-water fuel cycle. Thirty-nine processing options for waste from different fuel cycle facilities have been identified. These are categorized on the basis of cost, of performance in terms of reduction of collective and individual detriment and, finally, of a subjective index of data reliability. Multi-attribute analysis can be used for classifying options on the basis of these four criteria. In particular, a method known as ''total outclassing analysis'' can be used for initial classification of options independently of the ''implicit value of human life''. The value of total outclassing analysis lies in the fact that it can be used for a classification of options which takes collective and individual detriment simultaneously into account. It thus represents a satisfactory synthesis of the individual approach (critical groups) and the collective approach. A finer classification can be obtained by carrying out a non-total outclassing analysis (ELECTRE method). At this stage the weighting of criteria becomes a necessity. The results, however, are fairly insensitive to modification of the ''implicit value of human life''. Generally, the study shows traditional radiation protection options to be justified, especially where the trapping of iodine in reactors is concerned, and stresses the value of retaining noble gases in reprocessing plants

Hydrotherapy combined with Snoezelen multi-sensory therapy.

Science.gov (United States)

Lavie, Efrat; Shapiro, Michele; Julius, Mona

2005-01-01

The aim of this article is to present a new and challenging model of treatment that combines two therapeutic interventions: hydrotherapy and Snoezelen or controlled multisensory stimulation. The combination of the two therapeutic approaches enhances the treatment effect by utilizing the unique characteristics of each approach. We believe that this combined model will further enhance each media to the benefit of the clients and create a new intervention approach. This article relates to a hydrotherapy swimming pool facility that has been established at the Williams Island Therapeutic Swimming and Recreation Center, Beit Issie Shapiro, Raanana in Israel, after acquiring many years of experience and gaining substantial knowledge both in the field of hydrotherapy and Snoezelen intervention. Beit Issie Shapiro is a non-profit community organization providing a range of services for children with developmental disabilities and their families. The organization provides direct services for nearly 6,000 children and adults each year. This article provides an overview of hydrotherapy and Snoezelen and presents a case study, which will demonstrate the new model of treatment and show how this new and innovative form of therapy can be used as a successful intervention. We believe it will open a path to enriching the repertoire of therapists helping people with special needs. This article is also addressed to researchers to provide ideas for further studies in this area.

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

Science.gov (United States)

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

2018-05-01

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

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

Science.gov (United States)

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

2017-09-01

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

THE SECURITY OF CRITICAL ENERGY INFRASTRUCTURE IN THE AGE OF MULTIPLE ATTACK VECTORS: NATO’S MULTI-FACETED APPROACH

Directory of Open Access Journals (Sweden)

Sorin Dumitru Ducaru

2017-06-01

Full Text Available The current NATO threat landscape is characterized by a combination or “hybrid blend” of unconventional emerging challenges (like cyber and terrorist attacks and re-emerging conventional ones (like Russia’s recent military resurgence and assertiveness, that led to the illegal annexation of Crimea and destabilization in Eastern Ukraine. While the resurgence of the Russian military activity pushed the Alliance in the direction of re-discovering its deterrence and collective defence role, the new, not-traditional, trans-national and essentially non-military treats that generate effects below the threshold of an armed attack require a new paradigm shift with a focus on resilience although the protection of critical energy infrastructure is first and foremost a national responsibility, NATO can contribute to meeting the infrastructure protection challenge on many levels. Given the fact that its core deterrence and defence mandate relies in a great measure on the security of Allies’ energy infrastructure NATO’s role and actions in reducing the vulnerabilities and strengthening the resilience of such infrastructure can only increase. A multi-faceted, multi-stakeholder and networked approach is needed to be able to strengthen defences and resilience of critical infrastructure such as energy. Understanding and defending against cyber or terrorist threat vectors, increased situational awareness, education, training, exercises, trusted partnerships as well as increasing strategic security dialogue and cooperation are key for such a comprehensive/network approach to the challenge.

Evaluation of Unmanned Aircraft Systems (UAS) for Weather and Climate using the Multi-testbed approach

Science.gov (United States)

Baker, B.; Lee, T.; Buban, M.; Dumas, E. J.

2017-12-01

Evaluation of Unmanned Aircraft Systems (UAS) for Weather and Climate using the Multi-testbed approachC. Bruce Baker1, Ed Dumas1,2, Temple Lee1,2, Michael Buban1,21NOAA ARL, Atmospheric Turbulence and Diffusion Division, Oak Ridge, TN2Oak Ridge Associated Universities, Oak Ridge, TN The development of a small Unmanned Aerial System (sUAS) testbeds that can be used to validate, integrate, calibrate and evaluate new technology and sensors for routine boundary layer research, validation of operational weather models, improvement of model parameterizations, and recording observations within high-impact storms is important for understanding the importance and impact of using sUAS's routinely as a new observing platform. The goal of the multi-testbed approach is to build a robust set of protocols to assess the cost and operational feasibility of unmanned observations for routine applications using various combinations of sUAS aircraft and sensors in different locations and field experiments. All of these observational testbeds serve different community needs, but they also use a diverse suite of methodologies for calibration and evaluation of different sensors and platforms for severe weather and boundary layer research. The primary focus will be to evaluate meteorological sensor payloads to measure thermodynamic parameters and define surface characteristics with visible, IR, and multi-spectral cameras. This evaluation will lead to recommendations for sensor payloads for VTOL and fixed-wing sUAS.

IS ROMANIA “GREEN” ENOUGH? – A MULTI-LEVEL APPROACH

Directory of Open Access Journals (Sweden)

Alina CIOMOŞ

2014-06-01

Full Text Available Climate changes’ effects are already present in our day to day life. The EU and national public authorities established strategies and public policies in order to enhance a more desirable behavior of the companies and citizens with regard to recycling and use of green energy. The companies try to make production choices that are more eco-friendly and to sustain campaigns helping cities to become “greener”. The environmentalist citizens occupy a growing share in the general population and are more vocal for convincing the others. But even with the “on the wave” eco-friendly attitude, is it done enough? The article will present some conclusions for Romania. The perspective taken is interdisciplinary and tries to draw a short review of the state of the art achievements in greening Romania’s economy, at macroeconomic level, while proposing new marketing approaches for enhancing further sustainable development, through promoting change in the companies and consumers attitudes and behaviors.

Multi-Level Interval Estimation for Locating damage in Structures by Using Artificial Neural Networks

International Nuclear Information System (INIS)

Pan Danguang; Gao Yanhua; Song Junlei

2010-01-01

A new analysis technique, called multi-level interval estimation method, is developed for locating damage in structures. In this method, the artificial neural networks (ANN) analysis method is combined with the statistics theory to estimate the range of damage location. The ANN is multilayer perceptron trained by back-propagation. Natural frequencies and modal shape at a few selected points are used as input to identify the location and severity of damage. Considering the large-scale structures which have lots of elements, multi-level interval estimation method is developed to reduce the estimation range of damage location step-by-step. Every step, estimation range of damage location is obtained from the output of ANN by using the method of interval estimation. The next ANN training cases are selected from the estimation range after linear transform, and the output of new ANN estimation range of damage location will gained a reduced estimation range. Two numerical example analyses on 10-bar truss and 100-bar truss are presented to demonstrate the effectiveness of the proposed method.

Multi-period natural gas market modeling Applications, stochastic extensions and solution approaches

Science.gov (United States)

Egging, Rudolf Gerardus

This dissertation develops deterministic and stochastic multi-period mixed complementarity problems (MCP) for the global natural gas market, as well as solution approaches for large-scale stochastic MCP. The deterministic model is unique in the combination of the level of detail of the actors in the natural gas markets and the transport options, the detailed regional and global coverage, the multi-period approach with endogenous capacity expansions for transportation and storage infrastructure, the seasonal variation in demand and the representation of market power according to Nash-Cournot theory. The model is applied to several scenarios for the natural gas market that cover the formation of a cartel by the members of the Gas Exporting Countries Forum, a low availability of unconventional gas in the United States, and cost reductions in long-distance gas transportation. 1 The results provide insights in how different regions are affected by various developments, in terms of production, consumption, traded volumes, prices and profits of market participants. The stochastic MCP is developed and applied to a global natural gas market problem with four scenarios for a time horizon until 2050 with nineteen regions and containing 78,768 variables. The scenarios vary in the possibility of a gas market cartel formation and varying depletion rates of gas reserves in the major gas importing regions. Outcomes for hedging decisions of market participants show some significant shifts in the timing and location of infrastructure investments, thereby affecting local market situations. A first application of Benders decomposition (BD) is presented to solve a large-scale stochastic MCP for the global gas market with many hundreds of first-stage capacity expansion variables and market players exerting various levels of market power. The largest problem solved successfully using BD contained 47,373 variables of which 763 first-stage variables, however using BD did not result in

MIMO wireless networks channels, techniques and standards for multi-antenna, multi-user and multi-cell systems

CERN Document Server

Clerckx, Bruno

2013-01-01

This book is unique in presenting channels, techniques and standards for the next generation of MIMO wireless networks. Through a unified framework, it emphasizes how propagation mechanisms impact the system performance under realistic power constraints. Combining a solid mathematical analysis with a physical and intuitive approach to space-time signal processing, the book progressively derives innovative designs for space-time coding and precoding as well as multi-user and multi-cell techniques, taking into consideration that MIMO channels are often far from ideal. Reflecting developments

Multi-diversity combining and selection for relay-assisted mixed RF/FSO system

Science.gov (United States)

Chen, Li; Wang, Weidong

2017-12-01

We propose and analyze multi-diversity combining and selection to enhance the performance of relay-assisted mixed radio frequency/free-space optics (RF/FSO) system. We focus on a practical scenario for cellular network where a single-antenna source is communicating to a multi-apertures destination through a relay equipped with multiple receive antennas and multiple transmit apertures. The RF single input multiple output (SIMO) links employ either maximal-ratio combining (MRC) or receive antenna selection (RAS), and the FSO multiple input multiple output (MIMO) links adopt either repetition coding (RC) or transmit laser selection (TLS). The performance is evaluated via an outage probability analysis over Rayleigh fading RF links and Gamma-Gamma atmospheric turbulence FSO links with pointing errors where channel state information (CSI) assisted amplify-and-forward (AF) scheme is considered. Asymptotic closed-form expressions at high signal-to-noise ratio (SNR) are also derived. Coding gain and diversity order for different combining and selection schemes are further discussed. Numerical results are provided to verify and illustrate the analytical results.

Multi-level analysis in information systems research: the case of enterprise resource planning system usage in China

Science.gov (United States)

Sun, Yuan; Bhattacherjee, Anol

2011-11-01

Information technology (IT) usage within organisations is a multi-level phenomenon that is influenced by individual-level and organisational-level variables. Yet, current theories, such as the unified theory of acceptance and use of technology, describe IT usage as solely an individual-level phenomenon. This article postulates a model of organisational IT usage that integrates salient organisational-level variables such as user training, top management support and technical support within an individual-level model to postulate a multi-level model of IT usage. The multi-level model was then empirically validated using multi-level data collected from 128 end users and 26 managers in 26 firms in China regarding their use of enterprise resource planning systems and analysed using the multi-level structural equation modelling (MSEM) technique. We demonstrate the utility of MSEM analysis of multi-level data relative to the more common structural equation modelling analysis of single-level data and show how single-level data can be aggregated to approximate multi-level analysis when multi-level data collection is not possible. We hope that this article will motivate future scholars to employ multi-level data and multi-level analysis for understanding organisational phenomena that are truly multi-level in nature.

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

Science.gov (United States)

Khraief, Chadia; Benzarti, Faouzi; Amiri, Hamid

2018-04-01

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

A multi-criteria methodology for energy planning and developing renewable energy sources at a regional level: A case study Thassos, Greece

International Nuclear Information System (INIS)

Mourmouris, J.C.; Potolias, C.

2013-01-01

Rational energy planning under the pressure of environmental and economic problems is imperative to humanity. An evaluational framework is proposed in order to support energy planning for promoting the use of renewable energy sources. A multi-criteria decision analysis is adopted, detailing exploitation of renewable energy sources (including Wind, Solar, Biomass, Geothermal, and small Hydro) for power and heat generation. The aim of this paper is the analysis and development of a multilevel decision-making structure, utilizing multiple criteria for energy planning and exploitation of Renewable Energy Sources of at the regional level. The proposed evaluation framework focuses on the use of a multi-criteria approach as a tool for supporting energy planning in the area of concern, based on a pool of qualitative and quantitative evaluation criteria. The final aim of this study is to discover the optimal amount of each Renewable Energy Source that can be produced in the region and to contribute to an optimal energy mix. In this paper, a case study for the island of Thassos, Greece is analyzed. The results prove that Renewable Energy Sources exploitation at a regional level can satisfy increasing power demands through environmental-friendly energy systems that combine wind power, biomass and PV systems. - Highlights: ► An evaluational framework is proposed in order to support energy planning. ► A multi-criteria decision analysis is adopted, detailing exploitation of RES for power and heat generation. ► The aim is to discover the optimal amount of each RES that can be produced in each region.

Combining low level features and visual attributes for VHR remote sensing image classification

Science.gov (United States)

Zhao, Fumin; Sun, Hao; Liu, Shuai; Zhou, Shilin

2015-12-01

Semantic classification of very high resolution (VHR) remote sensing images is of great importance for land use or land cover investigation. A large number of approaches exploiting different kinds of low level feature have been proposed in the literature. Engineers are often frustrated by their conclusions and a systematic assessment of various low level features for VHR remote sensing image classification is needed. In this work, we firstly perform an extensive evaluation of eight features including HOG, dense SIFT, SSIM, GIST, Geo color, LBP, Texton and Tiny images for classification of three public available datasets. Secondly, we propose to transfer ground level scene attributes to remote sensing images. Thirdly, we combine both low-level features and mid-level visual attributes to further improve the classification performance. Experimental results demonstrate that i) Dene SIFT and HOG features are more robust than other features for VHR scene image description. ii) Visual attribute competes with a combination of low level features. iii) Multiple feature combination achieves the best performance under different settings.

Multi-Level Security Cannot Realise NEC Objectives

NARCIS (Netherlands)

Schotanus, H.A.; Hartog, T.; Verkoelen, C.A.A.

2012-01-01

Multi-Level Security (MLS) is often viewed as the holy grail of information security, especially in those environments where information of different classifications is being processed. In this paper we argue that MLS cannot facilitate the right balance between need-to-protect and duty-to-share as

An Evolutionary Approach for Bilevel Multi-objective Problems

Science.gov (United States)

Deb, Kalyanmoy; Sinha, Ankur

Evolutionary multi-objective optimization (EMO) algorithms have been extensively applied to find multiple near Pareto-optimal solutions over the past 15 years or so. However, EMO algorithms for solving bilevel multi-objective optimization problems have not received adequate attention yet. These problems appear in many applications in practice and involve two levels, each comprising of multiple conflicting objectives. These problems require every feasible upper-level solution to satisfy optimality of a lower-level optimization problem, thereby making them difficult to solve. In this paper, we discuss a recently proposed bilevel EMO procedure and show its working principle on a couple of test problems and on a business decision-making problem. This paper should motivate other EMO researchers to engage more into this important optimization task of practical importance.

Multicomponent Pharmaceutical Cocrystals: A Novel Approach for Combination Therapy.

Science.gov (United States)

Fatima, Zeeshan; Srivastava, Dipti; Kaur, Chanchal Deep

2018-03-05

Cocrystallization is a technique for modifying the physicochemical and pharmacokinetic properties of an active pharmaceutical ingredient (API) embodying the concept of supramolecular synthon. Most of the examples cited in the literature are of cocrystals formed between an API and a coformer chosen from the generally recognized as safe (GRAS) substance list, however, few examples exist where a cocrystal consists of two or more APIs. These cocrystals are commonly known as multi API, multi drug or drug- drug cocrystals. The formation of such cocrystals is feasible by virtue of non covalent interactions between the APIs, which help them in retaining their biologic activity. In addition, drug- drug cocrystals also offer the potential solution to the limitations such as solubility, stability differences and chemical interaction between the APIs which is often faced during the traditional combination therapy. Cocrystallization of two or more APIs can be employed for delivery of combination drugs for the better and efficacious management of many complex disorders where existing monotherapies do not furnish the desired therapeutic effect. This review on the existing drug-drug cocrystals is to gain insight for better designing of multi API cocrystals with improved physicochemical and pharmacokinetic profile and its application in multiple target therapy. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

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

Science.gov (United States)

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

2012-04-01

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

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

Science.gov (United States)

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

A synchrotron-based local computed tomography combined with data-constrained modelling approach for quantitative analysis of anthracite coal microstructure

International Nuclear Information System (INIS)

Chen, Wen Hao; Yang, Sam Y. S.; Xiao, Ti Qiao; Mayo, Sherry C.; Wang, Yu Dan; Wang, Hai Peng

2014-01-01

A quantitative local computed tomography combined with data-constrained modelling has been developed. The method could improve distinctly the spatial resolution and the composition resolution in a sample larger than the field of view, for quantitative characterization of three-dimensional distributions of material compositions and void. Quantifying three-dimensional spatial distributions of pores and material compositions in samples is a key materials characterization challenge, particularly in samples where compositions are distributed across a range of length scales, and where such compositions have similar X-ray absorption properties, such as in coal. Consequently, obtaining detailed information within sub-regions of a multi-length-scale sample by conventional approaches may not provide the resolution and level of detail one might desire. Herein, an approach for quantitative high-definition determination of material compositions from X-ray local computed tomography combined with a data-constrained modelling method is proposed. The approach is capable of dramatically improving the spatial resolution and enabling finer details within a region of interest of a sample larger than the field of view to be revealed than by using conventional techniques. A coal sample containing distributions of porosity and several mineral compositions is employed to demonstrate the approach. The optimal experimental parameters are pre-analyzed. The quantitative results demonstrated that the approach can reveal significantly finer details of compositional distributions in the sample region of interest. The elevated spatial resolution is crucial for coal-bed methane reservoir evaluation and understanding the transformation of the minerals during coal processing. The method is generic and can be applied for three-dimensional compositional characterization of other materials

Combining multiple decisions: applications to bioinformatics

International Nuclear Information System (INIS)

Yukinawa, N; Ishii, S; Takenouchi, T; Oba, 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

Combining multi-pulse excitation and chirp coding in contrast-enhanced ultrasound imaging

International Nuclear Information System (INIS)

Crocco, M; Sciallero, C; Trucco, A; Pellegretti, P

2009-01-01

The development of techniques to separate the response of the contrast agent from that of the biological tissues is of great importance in ultrasound medical imaging. In the literature, one can find various solutions involving the use of multiple transmitted signals and the weighted sum of related echoes. In this paper, the combination of one of these multi-pulse techniques with a coded excitation is proposed and assessed. Coded excitation has been used mainly to increase the signal-to-noise ratio (SNR) and the penetration depth, provided that a matched filtering is applied in the reception chain. However, it has been shown that a signal with a long duration time also increases the backscattered echoes produced by the microbubbles and, consequently, the contrast-to-tissue ratio. Therefore, the implementation of a multi-pulse technique using a long coded pulse can yield a better contrast-to-tissue ratio and SNR. This paper investigates the combination of the linear chirp pulse with a multi-pulse technique based on the transmission of three pulses. The performance was evaluated using both simulated and real signals, assessing the improvement in the contrast-to-tissue ratio and SNR, the visual quality of the images obtained and the axial accuracy. A comparison with the same multi-pulse technique implemented using a traditional amplitude-modulated pulse revealed that the deployment of a chirp pulse produces several noticeable advantages and only a minor drawback

Joint Facial Action Unit Detection and Feature Fusion: A Multi-conditional Learning Approach.

Science.gov (United States)

Eleftheriadis, Stefanos; Rudovic, Ognjen; Pantic, Maja

2016-10-05

Automated analysis of facial expressions can benefit many domains, from marketing to clinical diagnosis of neurodevelopmental disorders. Facial expressions are typically encoded as a combination of facial muscle activations, i.e., action units. Depending on context, these action units co-occur in specific patterns, and rarely in isolation. Yet, most existing methods for automatic action unit detection fail to exploit dependencies among them, and the corresponding facial features. To address this, we propose a novel multi-conditional latent variable model for simultaneous fusion of facial features and joint action unit detection. Specifically, the proposed model performs feature fusion in a generative fashion via a low-dimensional shared subspace, while simultaneously performing action unit detection using a discriminative classification approach. We show that by combining the merits of both approaches, the proposed methodology outperforms existing purely discriminative/generative methods for the target task. To reduce the number of parameters, and avoid overfitting, a novel Bayesian learning approach based on Monte Carlo sampling is proposed, to integrate out the shared subspace. We validate the proposed method on posed and spontaneous data from three publicly available datasets (CK+, DISFA and Shoulder-pain), and show that both feature fusion and joint learning of action units leads to improved performance compared to the state-of-the-art methods for the task.

Rapid prototyping of multi-scale biomedical microdevices by combining additive manufacturing technologies.

Science.gov (United States)

Hengsbach, Stefan; Lantada, Andrés Díaz

2014-08-01

The possibility of designing and manufacturing biomedical microdevices with multiple length-scale geometries can help to promote special interactions both with their environment and with surrounding biological systems. These interactions aim to enhance biocompatibility and overall performance by using biomimetic approaches. In this paper, we present a design and manufacturing procedure for obtaining multi-scale biomedical microsystems based on the combination of two additive manufacturing processes: a conventional laser writer to manufacture the overall device structure, and a direct-laser writer based on two-photon polymerization to yield finer details. The process excels for its versatility, accuracy and manufacturing speed and allows for the manufacture of microsystems and implants with overall sizes up to several millimeters and with details down to sub-micrometric structures. As an application example we have focused on manufacturing a biomedical microsystem to analyze the impact of microtextured surfaces on cell motility. This process yielded a relevant increase in precision and manufacturing speed when compared with more conventional rapid prototyping procedures.

Minimization of the LCA impact of thermodynamic cycles using a combined simulation-optimization approach

International Nuclear Information System (INIS)

Brunet, Robert; Cortés, Daniel; Guillén-Gosálbez, Gonzalo; Jiménez, Laureano; Boer, Dieter

2012-01-01

This work presents a computational approach for the simultaneous minimization of the total cost and environmental impact of thermodynamic cycles. Our method combines process simulation, multi-objective optimization and life cycle assessment (LCA) within a unified framework that identifies in a systematic manner optimal design and operating conditions according to several economic and LCA impacts. Our approach takes advantages of the complementary strengths of process simulation (in which mass, energy balances and thermodynamic calculations are implemented in an easy manner) and rigorous deterministic optimization tools. We demonstrate the capabilities of this strategy by means of two case studies in which we address the design of a 10 MW Rankine cycle modeled in Aspen Hysys, and a 90 kW ammonia-water absorption cooling cycle implemented in Aspen Plus. Numerical results show that it is possible to achieve environmental and cost savings using our rigorous approach. - Highlights: ► Novel framework for the optimal design of thermdoynamic cycles. ► Combined use of simulation and optimization tools. ► Optimal design and operating conditions according to several economic and LCA impacts. ► Design of a 10MW Rankine cycle in Aspen Hysys, and a 90kW absorption cycle in Aspen Plus.

Minimization of the LCA impact of thermodynamic cycles using a combined simulation-optimization approach

Energy Technology Data Exchange (ETDEWEB)

Brunet, Robert; Cortes, Daniel [Departament d' Enginyeria Quimica, Escola Tecnica Superior d' Enginyeria Quimica, Universitat Rovira i Virgili, Campus Sescelades, Avinguda Paisos Catalans 26, 43007 Tarragona (Spain); Guillen-Gosalbez, Gonzalo [Departament d' Enginyeria Quimica, Escola Tecnica Superior d' Enginyeria Quimica, Universitat Rovira i Virgili, Campus Sescelades, Avinguda Paisos Catalans 26, 43007 Tarragona (Spain); Jimenez, Laureano [Departament d' Enginyeria Quimica, Escola Tecnica Superior d' Enginyeria Quimica, Universitat Rovira i Virgili, Campus Sescelades, Avinguda Paisos Catalans 26, 43007 Tarragona (Spain); Boer, Dieter [Departament d' Enginyeria Mecanica, Escola Tecnica Superior d' Enginyeria, Universitat Rovira i Virgili, Campus Sescelades, Avinguda Paisos Catalans 26, 43007, Tarragona (Spain)

2012-12-15

This work presents a computational approach for the simultaneous minimization of the total cost and environmental impact of thermodynamic cycles. Our method combines process simulation, multi-objective optimization and life cycle assessment (LCA) within a unified framework that identifies in a systematic manner optimal design and operating conditions according to several economic and LCA impacts. Our approach takes advantages of the complementary strengths of process simulation (in which mass, energy balances and thermodynamic calculations are implemented in an easy manner) and rigorous deterministic optimization tools. We demonstrate the capabilities of this strategy by means of two case studies in which we address the design of a 10 MW Rankine cycle modeled in Aspen Hysys, and a 90 kW ammonia-water absorption cooling cycle implemented in Aspen Plus. Numerical results show that it is possible to achieve environmental and cost savings using our rigorous approach. - Highlights: Black-Right-Pointing-Pointer Novel framework for the optimal design of thermdoynamic cycles. Black-Right-Pointing-Pointer Combined use of simulation and optimization tools. Black-Right-Pointing-Pointer Optimal design and operating conditions according to several economic and LCA impacts. Black-Right-Pointing-Pointer Design of a 10MW Rankine cycle in Aspen Hysys, and a 90kW absorption cycle in Aspen Plus.

A multi-resolution approach to heat kernels on discrete surfaces

KAUST Repository

Vaxman, Amir

2010-07-26

Studying the behavior of the heat diffusion process on a manifold is emerging as an important tool for analyzing the geometry of the manifold. Unfortunately, the high complexity of the computation of the heat kernel - the key to the diffusion process - limits this type of analysis to 3D models of modest resolution. We show how to use the unique properties of the heat kernel of a discrete two dimensional manifold to overcome these limitations. Combining a multi-resolution approach with a novel approximation method for the heat kernel at short times results in an efficient and robust algorithm for computing the heat kernels of detailed models. We show experimentally that our method can achieve good approximations in a fraction of the time required by traditional algorithms. Finally, we demonstrate how these heat kernels can be used to improve a diffusion-based feature extraction algorithm. © 2010 ACM.

Multi-level and Multi-component Bitmap Encoding for Efficient Search Operations

Directory of Open Access Journals (Sweden)

Madhu BHAN, Department of Computer Applications

2012-12-01

Full Text Available The growing interest in data warehousing for decision makers is becoming more and more crucial to make faster and efficient decisions. On-line decision needs short response times. Many indexing techniques have been created to achieve this goal in read only environments. Indexing technique that has attracted attention in multidimensional databases is Bitmap Indexing. The paper discusses the various existing bitmap indexing techniques along with their performance characteristics. The paper proposes two new bitmap indexing techniques in the class of multi-level and multi-component encoding schemes and prove that the two techniques have better space–time performance than some of the existing techniques used for range queries. We provide an analytical model for comparing the performance of our proposed encoding schemes with that of the existing ones.

Analysing barriers to service improvement using a multi-level theory of innovation: the case of glaucoma outpatient clinics.

Science.gov (United States)

Turner, Simon; Vasilakis, Christos; Utley, Martin; Foster, Paul; Kotecha, Aachal; Fulop, Naomi J

2018-05-01

The development and implementation of innovation by healthcare providers is understood as a multi-determinant and multi-level process. Theories at different analytical levels (i.e. micro and organisational) are needed to capture the processes that influence innovation by providers. This article combines a micro theory of innovation, actor-network theory, with organisational level processes using the 'resource based view of the firm'. It examines the influence of, and interplay between, innovation-seeking teams (micro) and underlying organisational capabilities (meso) during innovation processes. We used ethnographic methods to study service innovations in relation to ophthalmology services run by a specialist English NHS Trust at multiple locations. Operational research techniques were used to support the ethnographic methods by mapping the care process in the existing and redesigned clinics. Deficiencies in organisational capabilities for supporting innovation were identified, including manager-clinician relations and organisation-wide resources. The article concludes that actor-network theory can be combined with the resource-based view to highlight the influence of organisational capabilities on the management of innovation. Equally, actor-network theory helps to address the lack of theory in the resource-based view on the micro practices of implementing change. © 2018 The Authors. Sociology of Health & Illness published by John Wiley & Sons Ltd on behalf of Foundation for SHIL.

Detecting Neolithic Burial Mounds from LiDAR-Derived Elevation Data Using a Multi-Scale Approach and Machine Learning Techniques

Directory of Open Access Journals (Sweden)

Alexandre Guyot

2018-02-01

Full Text Available Airborne LiDAR technology is widely used in archaeology and over the past decade has emerged as an accurate tool to describe anthropomorphic landforms. Archaeological features are traditionally emphasised on a LiDAR-derived Digital Terrain Model (DTM using multiple Visualisation Techniques (VTs, and occasionally aided by automated feature detection or classification techniques. Such an approach offers limited results when applied to heterogeneous structures (different sizes, morphologies, which is often the case for archaeological remains that have been altered throughout the ages. This study proposes to overcome these limitations by developing a multi-scale analysis of topographic position combined with supervised machine learning algorithms (Random Forest. Rather than highlighting individual topographic anomalies, the multi-scalar approach allows archaeological features to be examined not only as individual objects, but within their broader spatial context. This innovative and straightforward method provides two levels of results: a composite image of topographic surface structure and a probability map of the presence of archaeological structures. The method was developed to detect and characterise megalithic funeral structures in the region of Carnac, the Bay of Quiberon, and the Gulf of Morbihan (France, which is currently considered for inclusion on the UNESCO World Heritage List. As a result, known archaeological sites have successfully been geo-referenced with a greater accuracy than before (even when located under dense vegetation and a ground-check confirmed the identification of a previously unknown Neolithic burial mound in the commune of Carnac.

An approach to multi-attribute utility analysis under parametric uncertainty

International Nuclear Information System (INIS)

Kelly, M.; Thorne, M.C.

2001-01-01

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

Multi-level Simulation of a Real Time Vibration Monitoring System Component

Science.gov (United States)

Robertson, Bryan A.; Wilkerson, Delisa

2005-01-01

This paper describes the development of a custom built Digital Signal Processing (DSP) printed circuit board designed to implement the Advanced Real Time Vibration Monitoring Subsystem proposed by Marshall Space Flight Center (MSFC) Transportation Directorate in 2000 for the Space Shuttle Main Engine Advanced Health Management System (AHMS). This Real Time Vibration Monitoring System (RTVMS) is being developed for ground use as part of the AHMS Health Management Computer-Integrated Rack Assembly (HMC-IRA). The HMC-IRA RTVMS design contains five DSPs which are highly interconnected through individual communication ports, shared memory, and a unique communication router that allows all the DSPs to receive digitized data fiom two multi-channel analog boards simultaneously. This paper will briefly cover the overall board design but will focus primarily on the state-of-the-art simulation environment within which this board was developed. This 16-layer board with over 1800 components and an additional mezzanine card has been an extremely challenging design. Utilization of a Mentor Graphics simulation environment provided the unique board and system level simulation capability to ascertain any timing or functional concerns before production. By combining VHDL, Synopsys Software and Hardware Models, and the Mentor Design Capture Environment, multiple simulations were developed to verify the RTVMS design. This multi-level simulation allowed the designers to achieve complete operability without error the first time the RTVMS printed circuit board was powered. The HMC-IRA design has completed all engineering and deliverable unit testing. P

Who multi-tasks and why? Multi-tasking ability, perceived multi-tasking ability, impulsivity, and sensation seeking.

Science.gov (United States)

Sanbonmatsu, David M; Strayer, David L; Medeiros-Ward, Nathan; Watson, Jason M

2013-01-01

The present study examined the relationship between personality and individual differences in multi-tasking ability. Participants enrolled at the University of Utah completed measures of multi-tasking activity, perceived multi-tasking ability, impulsivity, and sensation seeking. In addition, they performed the Operation Span in order to assess their executive control and actual multi-tasking ability. The findings indicate that the persons who are most capable of multi-tasking effectively are not the persons who are most likely to engage in multiple tasks simultaneously. To the contrary, multi-tasking activity as measured by the Media Multitasking Inventory and self-reported cell phone usage while driving were negatively correlated with actual multi-tasking ability. Multi-tasking was positively correlated with participants' perceived ability to multi-task ability which was found to be significantly inflated. Participants with a strong approach orientation and a weak avoidance orientation--high levels of impulsivity and sensation seeking--reported greater multi-tasking behavior. Finally, the findings suggest that people often engage in multi-tasking because they are less able to block out distractions and focus on a singular task. Participants with less executive control--low scorers on the Operation Span task and persons high in impulsivity--tended to report higher levels of multi-tasking activity.

Who multi-tasks and why? Multi-tasking ability, perceived multi-tasking ability, impulsivity, and sensation seeking.

Directory of Open Access Journals (Sweden)

David M Sanbonmatsu

Full Text Available The present study examined the relationship between personality and individual differences in multi-tasking ability. Participants enrolled at the University of Utah completed measures of multi-tasking activity, perceived multi-tasking ability, impulsivity, and sensation seeking. In addition, they performed the Operation Span in order to assess their executive control and actual multi-tasking ability. The findings indicate that the persons who are most capable of multi-tasking effectively are not the persons who are most likely to engage in multiple tasks simultaneously. To the contrary, multi-tasking activity as measured by the Media Multitasking Inventory and self-reported cell phone usage while driving were negatively correlated with actual multi-tasking ability. Multi-tasking was positively correlated with participants' perceived ability to multi-task ability which was found to be significantly inflated. Participants with a strong approach orientation and a weak avoidance orientation--high levels of impulsivity and sensation seeking--reported greater multi-tasking behavior. Finally, the findings suggest that people often engage in multi-tasking because they are less able to block out distractions and focus on a singular task. Participants with less executive control--low scorers on the Operation Span task and persons high in impulsivity--tended to report higher levels of multi-tasking activity.

Who Multi-Tasks and Why? Multi-Tasking Ability, Perceived Multi-Tasking Ability, Impulsivity, and Sensation Seeking

Science.gov (United States)

Sanbonmatsu, David M.; Strayer, David L.; Medeiros-Ward, Nathan; Watson, Jason M.

2013-01-01

The present study examined the relationship between personality and individual differences in multi-tasking ability. Participants enrolled at the University of Utah completed measures of multi-tasking activity, perceived multi-tasking ability, impulsivity, and sensation seeking. In addition, they performed the Operation Span in order to assess their executive control and actual multi-tasking ability. The findings indicate that the persons who are most capable of multi-tasking effectively are not the persons who are most likely to engage in multiple tasks simultaneously. To the contrary, multi-tasking activity as measured by the Media Multitasking Inventory and self-reported cell phone usage while driving were negatively correlated with actual multi-tasking ability. Multi-tasking was positively correlated with participants’ perceived ability to multi-task ability which was found to be significantly inflated. Participants with a strong approach orientation and a weak avoidance orientation – high levels of impulsivity and sensation seeking – reported greater multi-tasking behavior. Finally, the findings suggest that people often engage in multi-tasking because they are less able to block out distractions and focus on a singular task. Participants with less executive control - low scorers on the Operation Span task and persons high in impulsivity - tended to report higher levels of multi-tasking activity. PMID:23372720

Multi-level damage identification with response reconstruction

Science.gov (United States)

Zhang, Chao-Dong; Xu, You-Lin

2017-10-01

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

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

Science.gov (United States)

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

2018-04-01

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

Adjusting to Social Change - A Multi-Level Analysis in Three Cultures

Science.gov (United States)

2013-08-01

example, coping may be more collective in collectivist , compared to individualist , societies (Chang & Sivam, 2004). Some cultures have a greater sense...AFRL-AFOSR-UK-TR-2013-0041 Adjusting to Social Change - A multi-level Analysis in three cultures Prof Robin Goodwin...COVERED (From – To) 23 May 2012 – 22 May 2013 4. TITLE AND SUBTITLE Adjusting to Social Change - A multi-level Analysis in three cultures

A Hybrid Approach Combining the Multi-Temporal Scale Spatio-Temporal Network with the Continuous Triangular Model for Exploring Dynamic Interactions in Movement Data: A Case Study of Football

Directory of Open Access Journals (Sweden)

Pengdong Zhang

2018-01-01

Full Text Available Benefiting from recent advantages in location-aware technologies, movement data are becoming ubiquitous. Hence, numerous research topics with respect to movement data have been undertaken. Yet, the research of dynamic interactions in movement data is still in its infancy. In this paper, we propose a hybrid approach combining the multi-temporal scale spatio-temporal network (MTSSTN and the continuous triangular model (CTM for exploring dynamic interactions in movement data. The approach mainly includes four steps: first, the relative trajectory calculus (RTC is used to derive three types of interaction patterns; second, for each interaction pattern, a corresponding MTSSTN is generated; third, for each MTSSTN, the interaction intensity measures and three centrality measures (i.e., degree, betweenness and closeness are calculated; finally, the results are visualized at multiple temporal scales using the CTM and analyzed based on the generated CTM diagrams. Based on the proposed approach, three distinctive aims can be achieved for each interaction pattern at multiple temporal scales: (1 exploring the interaction intensities between any two individuals; (2 exploring the interaction intensities among multiple individuals, and (3 exploring the importance of each individual and identifying the most important individuals. The movement data obtained from a real football match are used as a case study to validate the effectiveness of the proposed approach. The results demonstrate that the proposed approach is useful in exploring dynamic interactions in football movement data and discovering insightful information.

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

Energy Technology Data Exchange (ETDEWEB)

Thetiot, R

2000-07-01

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

An Embodied Multi-Sensor Fusion Approach to Visual Motion Estimation Using Unsupervised Deep Networks.

Science.gov (United States)

Shamwell, E Jared; Nothwang, William D; Perlis, Donald

2018-05-04

Aimed at improving size, weight, and power (SWaP)-constrained robotic vision-aided state estimation, we describe our unsupervised, deep convolutional-deconvolutional sensor fusion network, Multi-Hypothesis DeepEfference (MHDE). MHDE learns to intelligently combine noisy heterogeneous sensor data to predict several probable hypotheses for the dense, pixel-level correspondence between a source image and an unseen target image. We show how our multi-hypothesis formulation provides increased robustness against dynamic, heteroscedastic sensor and motion noise by computing hypothesis image mappings and predictions at 76⁻357 Hz depending on the number of hypotheses being generated. MHDE fuses noisy, heterogeneous sensory inputs using two parallel, inter-connected architectural pathways and n (1⁻20 in this work) multi-hypothesis generating sub-pathways to produce n global correspondence estimates between a source and a target image. We evaluated MHDE on the KITTI Odometry dataset and benchmarked it against the vision-only DeepMatching and Deformable Spatial Pyramids algorithms and were able to demonstrate a significant runtime decrease and a performance increase compared to the next-best performing method.

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

CERN Document Server

Garcia, Emilia; Botti, Vicente

2015-01-01

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

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

Science.gov (United States)

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

2017-10-31

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

Rapid islanding detection using multi-level inverter for grid-interactive PV system

International Nuclear Information System (INIS)

Tsang, K.M.; Chan, W.L.

2014-01-01

Graphical abstract: - Highlights: • Novel reference signal is used to form an islanding detection scheme for PV system. • Supply fixed magnitude sinusoidal signal even if utility grid is disconnected. • Seamless transfer between grid-connected and stand-alone modes is possible. - Abstract: A novel reference signal generator is combined with a multi-level inverter to form a rapid islanding detection scheme for grid-interactive PV system. The reference signal generator can easily be synchronized with the utility grid signal and produced a fixed magnitude and very low total harmonic distortion (THD) sinusoidal signal which is in phase with the utility grid signal. Unlike conventional phase-locked loop (PLL) circuitry, the reference signal generator can also provide a fixed magnitude sinusoidal signal even if the utility grid is disconnected and automatically re-synchronous with the grid rapidly. Consequently, seamless transfer between grid-connected and stand-alone modes could easily be achieved if anti-islanding protection is not required. If a saturation element is applied to the raw reference signal followed by the synthesis of the truncated signal using a multi-level inverter, the distinct flat-top feature of the synthesized signal can quickly and easily be identified if the network is in islanding mode at the point of common coupling. Experimental results are included to demonstrate the effectiveness of the proposed detection scheme

Generating a high brightness multi-kilowatt laser by dense spectral combination of VBG stabilized single emitter laser diodes

Science.gov (United States)

Fritsche, H.; Koch, Ralf; Krusche, B.; Ferrario, F.; Grohe, Andreas; Pflueger, S.; Gries, W.

2014-05-01

Generating high power laser radiation with diode lasers is commonly realized by geometrical stacking of diode bars, which results in high output power but poor beam parameter product (BPP). The accessible brightness in this approach is limited by the fill factor, both in slow and fast axis. By using a geometry that accesses the BPP of the individual diodes, generating a multi kilowatt diode laser with a BPP comparable to fiber lasers is possible. We will demonstrate such a modular approach for generating multi kilowatt lasers by combining single emitter diode lasers. Single emitter diodes have advantages over bars, mainly a simplified cooling, better reliability and a higher brightness per emitter. Additionally, because single emitters can be arranged in many different geometries, they allow building laser modules where the brightness of the single emitters is preserved. In order to maintain the high brightness of the single emitter we developed a modular laser design which uses single emitters in a staircase arrangement, then coupling two of those bases with polarization combination which is our basic module. Those modules generate up to 160 W with a BPP better than 7.5 mm*mrad. For further power scaling wavelength stabilization is crucial. The wavelength is stabilized with only one Volume Bragg Grating (VBG) in front of a base providing the very same feedback to all of the laser diodes. This results in a bandwidth of BPP better than 7.5 mm*mrad, which can easily coupled into a 100 μm fiber and 0.15 NA.

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

DEFF Research Database (Denmark)

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

2010-01-01

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

What is at stake in multi-scale approaches

International Nuclear Information System (INIS)

Jamet, Didier

2008-01-01

Full text of publication follows: Multi-scale approaches amount to analyzing physical phenomena at small space and time scales in order to model their effects at larger scales. This approach is very general in physics and engineering; one of the best examples of success of this approach is certainly statistical physics that allows to recover classical thermodynamics and to determine the limits of application of classical thermodynamics. Getting access to small scale information aims at reducing the models' uncertainty but it has a cost: fine scale models may be more complex than larger scale models and their resolution may require the development of specific and possibly expensive methods, numerical simulation techniques and experiments. For instance, in applications related to nuclear engineering, the application of computational fluid dynamics instead of cruder models is a formidable engineering challenge because it requires resorting to high performance computing. Likewise, in two-phase flow modeling, the techniques of direct numerical simulation, where all the interfaces are tracked individually and where all turbulence scales are captured, are getting mature enough to be considered for averaged modeling purposes. However, resolving small scale problems is a necessary step but it is not sufficient in a multi-scale approach. An important modeling challenge is to determine how to treat small scale data in order to get relevant information for larger scale models. For some applications, such as single-phase turbulence or transfers in porous media, this up-scaling approach is known and is now used rather routinely. However, in two-phase flow modeling, the up-scaling approach is not as mature and specific issues must be addressed that raise fundamental questions. This will be discussed and illustrated. (author)

Multi-objective optimization for generating a weighted multi-model ensemble

Science.gov (United States)

Lee, H.

2017-12-01

Many studies have demonstrated that multi-model ensembles generally show better skill than each ensemble member. When generating weighted multi-model ensembles, the first step is measuring the performance of individual model simulations using observations. There is a consensus on the assignment of weighting factors based on a single evaluation metric. When considering only one evaluation metric, the weighting factor for each model is proportional to a performance score or inversely proportional to an error for the model. While this conventional approach can provide appropriate combinations of multiple models, the approach confronts a big challenge when there are multiple metrics under consideration. When considering multiple evaluation metrics, it is obvious that a simple averaging of multiple performance scores or model ranks does not address the trade-off problem between conflicting metrics. So far, there seems to be no best method to generate weighted multi-model ensembles based on multiple performance metrics. The current study applies the multi-objective optimization, a mathematical process that provides a set of optimal trade-off solutions based on a range of evaluation metrics, to combining multiple performance metrics for the global climate models and their dynamically downscaled regional climate simulations over North America and generating a weighted multi-model ensemble. NASA satellite data and the Regional Climate Model Evaluation System (RCMES) software toolkit are used for assessment of the climate simulations. Overall, the performance of each model differs markedly with strong seasonal dependence. Because of the considerable variability across the climate simulations, it is important to evaluate models systematically and make future projections by assigning optimized weighting factors to the models with relatively good performance. Our results indicate that the optimally weighted multi-model ensemble always shows better performance than an arithmetic

A multi-source satellite data approach for modelling Lake Turkana water level: calibration and validation using satellite altimetry data

Directory of Open Access Journals (Sweden)

N. M. Velpuri

2012-01-01

Full Text Available Lake Turkana is one of the largest desert lakes in the world and is characterized by high degrees of inter- and intra-annual fluctuations. The hydrology and water balance of this lake have not been well understood due to its remote location and unavailability of reliable ground truth datasets. Managing surface water resources is a great challenge in areas where in-situ data are either limited or unavailable. In this study, multi-source satellite-driven data such as satellite-based rainfall estimates, modelled runoff, evapotranspiration, and a digital elevation dataset were used to model Lake Turkana water levels from 1998 to 2009. Due to the unavailability of reliable lake level data, an approach is presented to calibrate and validate the water balance model of Lake Turkana using a composite lake level product of TOPEX/Poseidon, Jason-1, and ENVISAT satellite altimetry data. Model validation results showed that the satellite-driven water balance model can satisfactorily capture the patterns and seasonal variations of the Lake Turkana water level fluctuations with a Pearson's correlation coefficient of 0.90 and a Nash-Sutcliffe Coefficient of Efficiency (NSCE of 0.80 during the validation period (2004–2009. Model error estimates were within 10% of the natural variability of the lake. Our analysis indicated that fluctuations in Lake Turkana water levels are mainly driven by lake inflows and over-the-lake evaporation. Over-the-lake rainfall contributes only up to 30% of lake evaporative demand. During the modelling time period, Lake Turkana showed seasonal variations of 1–2 m. The lake level fluctuated in the range up to 4 m between the years 1998–2009. This study demonstrated the usefulness of satellite altimetry data to calibrate and validate the satellite-driven hydrological model for Lake Turkana without using any in-situ data. Furthermore, for Lake Turkana, we identified and outlined opportunities and challenges of using a calibrated

A multi-source satellite data approach for modelling Lake Turkana water level: Calibration and validation using satellite altimetry data

Science.gov (United States)

Velpuri, N.M.; Senay, G.B.; Asante, K.O.

2012-01-01

Lake Turkana is one of the largest desert lakes in the world and is characterized by high degrees of interand intra-annual fluctuations. The hydrology and water balance of this lake have not been well understood due to its remote location and unavailability of reliable ground truth datasets. Managing surface water resources is a great challenge in areas where in-situ data are either limited or unavailable. In this study, multi-source satellite-driven data such as satellite-based rainfall estimates, modelled runoff, evapotranspiration, and a digital elevation dataset were used to model Lake Turkana water levels from 1998 to 2009. Due to the unavailability of reliable lake level data, an approach is presented to calibrate and validate the water balance model of Lake Turkana using a composite lake level product of TOPEX/Poseidon, Jason-1, and ENVISAT satellite altimetry data. Model validation results showed that the satellitedriven water balance model can satisfactorily capture the patterns and seasonal variations of the Lake Turkana water level fluctuations with a Pearson's correlation coefficient of 0.90 and a Nash-Sutcliffe Coefficient of Efficiency (NSCE) of 0.80 during the validation period (2004-2009). Model error estimates were within 10% of the natural variability of the lake. Our analysis indicated that fluctuations in Lake Turkana water levels are mainly driven by lake inflows and over-the-lake evaporation. Over-the-lake rainfall contributes only up to 30% of lake evaporative demand. During the modelling time period, Lake Turkana showed seasonal variations of 1-2m. The lake level fluctuated in the range up to 4m between the years 1998-2009. This study demonstrated the usefulness of satellite altimetry data to calibrate and validate the satellite-driven hydrological model for Lake Turkana without using any in-situ data. Furthermore, for Lake Turkana, we identified and outlined opportunities and challenges of using a calibrated satellite-driven water balance

An expert-based approach to forest road network planning by combining Delphi and spatial multi-criteria evaluation.

Science.gov (United States)

Hayati, Elyas; Majnounian, Baris; Abdi, Ehsan; Sessions, John; Makhdoum, Majid

2013-02-01

Changes in forest landscapes resulting from road construction have increased remarkably in the last few years. On the other hand, the sustainable management of forest resources can only be achieved through a well-organized road network. In order to minimize the environmental impacts of forest roads, forest road managers must design the road network efficiently and environmentally as well. Efficient planning methodologies can assist forest road managers in considering the technical, economic, and environmental factors that affect forest road planning. This paper describes a three-stage methodology using the Delphi method for selecting the important criteria, the Analytic Hierarchy Process for obtaining the relative importance of the criteria, and finally, a spatial multi-criteria evaluation in a geographic information system (GIS) environment for identifying the lowest-impact road network alternative. Results of the Delphi method revealed that ground slope, lithology, distance from stream network, distance from faults, landslide susceptibility, erosion susceptibility, geology, and soil texture are the most important criteria for forest road planning in the study area. The suitability map for road planning was then obtained by combining the fuzzy map layers of these criteria with respect to their weights. Nine road network alternatives were designed using PEGGER, an ArcView GIS extension, and finally, their values were extracted from the suitability map. Results showed that the methodology was useful for identifying road that met environmental and cost considerations. Based on this work, we suggest future work in forest road planning using multi-criteria evaluation and decision making be considered in other regions and that the road planning criteria identified in this study may be useful.

Comet Methy-sens and DNMTs transcriptional analysis as a combined approach in epigenotoxicology

Directory of Open Access Journals (Sweden)

Alessio Perotti

2015-05-01

In conclusion, our data demonstrate that Comet Methy-sens, in combination with the analysis of transcriptional levels of DNA methyl transferases, represents a simple and multifunctional approach to implement biomonitoring studies on epigenotoxicological effects of known and unknown xenobiotics.

Optimal maintenance policy incorporating system level and unit level for mechanical systems

Science.gov (United States)

Duan, Chaoqun; Deng, Chao; Wang, Bingran

2018-04-01

The study works on a multi-level maintenance policy combining system level and unit level under soft and hard failure modes. The system experiences system-level preventive maintenance (SLPM) when the conditional reliability of entire system exceeds SLPM threshold, and also undergoes a two-level maintenance for each single unit, which is initiated when a single unit exceeds its preventive maintenance (PM) threshold, and the other is performed simultaneously the moment when any unit is going for maintenance. The units experience both periodic inspections and aperiodic inspections provided by failures of hard-type units. To model the practical situations, two types of economic dependence have been taken into account, which are set-up cost dependence and maintenance expertise dependence due to the same technology and tool/equipment can be utilised. The optimisation problem is formulated and solved in a semi-Markov decision process framework. The objective is to find the optimal system-level threshold and unit-level thresholds by minimising the long-run expected average cost per unit time. A formula for the mean residual life is derived for the proposed multi-level maintenance policy. The method is illustrated by a real case study of feed subsystem from a boring machine, and a comparison with other policies demonstrates the effectiveness of our approach.

Multi-level programming paradigm for extreme computing

International Nuclear Information System (INIS)

Petiton, S.; Sato, M.; Emad, N.; Calvin, C.; Tsuji, M.; Dandouna, M.

2013-01-01

In order to propose a framework and programming paradigms for post peta-scale computing, on the road to exa-scale computing and beyond, we introduced new languages, associated with a hierarchical multi-level programming paradigm, allowing scientific end-users and developers to program highly hierarchical architectures designed for extreme computing. In this paper, we explain the interest of such hierarchical multi-level programming paradigm for extreme computing and its well adaptation to several large computational science applications, such as for linear algebra solvers used for reactor core physic. We describe the YML language and framework allowing describing graphs of parallel components, which may be developed using PGAS-like language such as XMP, scheduled and computed on supercomputers. Then, we propose experimentations on supercomputers (such as the 'K' and 'Hooper' ones) of the hybrid method MERAM (Multiple Explicitly Restarted Arnoldi Method) as a case study for iterative methods manipulating sparse matrices, and the block Gauss-Jordan method as a case study for direct method manipulating dense matrices. We conclude proposing evolutions for this programming paradigm. (authors)

A framework to promote collective action within the One Health community of practice: Using participatory modelling to enable interdisciplinary, cross-sectoral and multi-level integration

Directory of Open Access Journals (Sweden)

Aurelie Binot

2015-12-01

The implementation of a One Health (OH approach in this context calls for improved integration among disciplines and improved cross-sectoral collaboration, involving stakeholders at different levels. For sure, such integration is not achieved spontaneously, implies methodological guidelines and has transaction costs. We explore pathways for implementing such collaboration in SEA context, highlighting the main challenges to be faced by researchers and other target groups involved in OH actions. On this basis, we propose a conceptual framework of OH integration. Throughout 3 components (field-based data management, professional training workshops and higher education, we suggest to develop a new culture of networking involving actors from various disciplines, sectors and levels (from the municipality to the Ministries through a participatory modelling process, fostering synergies and cooperation. This framework could stimulate long-term dialogue process, based on the combination of case studies implementation and capacity building. It aims for implementing both institutional OH dynamics (multi-stakeholders and cross-sectoral and research approaches promoting systems thinking and involving social sciences to follow-up and strengthen collective action.

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

DEFF Research Database (Denmark)

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

2017-01-01

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

Multi-scale model of the ionosphere from the combination of modern space-geodetic satellite techniques - project status and first results

Science.gov (United States)

Schmidt, M.; Hugentobler, U.; Jakowski, N.; Dettmering, D.; Liang, W.; Limberger, M.; Wilken, V.; Gerzen, T.; Hoque, M.; Berdermann, J.

2012-04-01

Near real-time high resolution and high precision ionosphere models are needed for a large number of applications, e.g. in navigation, positioning, telecommunications or astronautics. Today these ionosphere models are mostly empirical, i.e., based purely on mathematical approaches. In the DFG project 'Multi-scale model of the ionosphere from the combination of modern space-geodetic satellite techniques (MuSIK)' the complex phenomena within the ionosphere are described vertically by combining the Chapman electron density profile with a plasmasphere layer. In order to consider the horizontal and temporal behaviour the fundamental target parameters of this physics-motivated approach are modelled by series expansions in terms of tensor products of localizing B-spline functions depending on longitude, latitude and time. For testing the procedure the model will be applied to an appropriate region in South America, which covers relevant ionospheric processes and phenomena such as the Equatorial Anomaly. The project connects the expertise of the three project partners, namely Deutsches Geodätisches Forschungsinstitut (DGFI) Munich, the Institute of Astronomical and Physical Geodesy (IAPG) of the Technical University Munich (TUM) and the German Aerospace Center (DLR), Neustrelitz. In this presentation we focus on the current status of the project. In the first year of the project we studied the behaviour of the ionosphere in the test region, we setup appropriate test periods covering high and low solar activity as well as winter and summer and started the data collection, analysis, pre-processing and archiving. We developed partly the mathematical-physical modelling approach and performed first computations based on simulated input data. Here we present information on the data coverage for the area and the time periods of our investigations and we outline challenges of the multi-dimensional mathematical-physical modelling approach. We show first results, discuss problems

Life cycle tools combined with multi-criteria and participatory methods for agricultural sustainability: Insights from a systematic and critical review.

Science.gov (United States)

De Luca, Anna Irene; Iofrida, Nathalie; Leskinen, Pekka; Stillitano, Teodora; Falcone, Giacomo; Strano, Alfio; Gulisano, Giovanni

2017-10-01

Life cycle (LC) methodologies have attracted a great interest in agricultural sustainability assessments, even if, at the same time, they have sometimes been criticized for making unrealistic assumptions and subjective choices. To cope with these weaknesses, Multi-Criteria Decision Analysis (MCDA) and/or participatory methods can be used to balance and integrate different sustainability dimensions. The purpose of this study is to highlight how life cycle approaches were combined with MCDA and participatory methods to address agricultural sustainability in the published scientific literature. A systematic and critical review was developed, highlighting the following features: which multi-criterial and/or participatory methods have been associated with LC tools; how they have been integrated or complemented (methodological relationships); the intensity of the involvement of stakeholders (degree of participation); and which synergies have been achieved by combining the methods. The main typology of integration was represented by multi-criterial frameworks integrating LC evaluations. LC tools can provide MCDA studies with local and global information on how to reduce negative impacts and avoid burden shifts, while MCDA methods can help LC practitioners deal with subjective assumptions in an objective way, to take into consideration actors' values and to overcome trade-offs among the different dimensions of sustainability. Considerations concerning the further development of Life Cycle Sustainability Assessment (LCSA) have been identified as well. Copyright © 2017 Elsevier B.V. All rights reserved.

FBILI method for multi-level line transfer

Science.gov (United States)

Kuzmanovska, O.; Atanacković, O.; Faurobert, M.

2017-07-01

Efficient non-LTE multilevel radiative transfer calculations are needed for a proper interpretation of astrophysical spectra. In particular, realistic simulations of time-dependent processes or multi-dimensional phenomena require that the iterative method used to solve such non-linear and non-local problem is as fast as possible. There are several multilevel codes based on efficient iterative schemes that provide a very high convergence rate, especially when combined with mathematical acceleration techniques. The Forth-and-Back Implicit Lambda Iteration (FBILI) developed by Atanacković-Vukmanović et al. [1] is a Gauss-Seidel-type iterative scheme that is characterized by a very high convergence rate without the need of complementing it with additional acceleration techniques. In this paper we make the implementation of the FBILI method to the multilevel atom line transfer in 1D more explicit. We also consider some of its variants and investigate their convergence properties by solving the benchmark problem of CaII line formation in the solar atmosphere. Finally, we compare our solutions with results obtained with the well known code MULTI.

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

Directory of Open Access Journals (Sweden)

Phuoc Tran

2016-01-01

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

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

Science.gov (United States)

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

2016-01-01

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

Does regional disadvantage affect health-related sport and physical activity level? A multi-level analysis of individual behaviour.

Science.gov (United States)

Wicker, Pamela; Downward, Paul; Lera-López, Fernando

2017-11-01

This study examines the role of regional government quality in health-related participation in sport and physical activity among adults (18-64 years) in 28 European countries. The importance of the analysis rests in the relative autonomy that regional and local governments have over policy decisions connected with sport and physical activity. While existing studies have focussed on economic and infrastructural investment and expenditure, this research investigates the quality of regional governments across 208 regions within 28 European countries. The individual-level data stem from the 2013 Eurobarometer 80.2 (n = 18,675) and were combined with regional-level data from Eurostat. An individual's level of participation in sport and physical activity was measured by three variables reflecting whether an individual's activity level is below, meets, or exceeds the recommendations of the World Health Organization. The results of multi-level analyses reveal that regional government quality has a significant and positive association with individual participation in sport and physical activity at a level meeting or exceeding the guidelines. The impact is much larger than that of regional gross domestic product per capita, indicating that regional disadvantage in terms of political quality is more relevant than being disadvantaged in terms of economic wealth.

A Multi-Level Model of Information Seeking in the Clinical Domain

Science.gov (United States)

Hung, Peter W.; Johnson, Stephen B.; Kaufman, David R.; Mendonça, Eneida A.

2008-01-01

Objective: Clinicians often have difficulty translating information needs into effective search strategies to find appropriate answers. Information retrieval systems employing an intelligent search agent that generates adaptive search strategies based on human search expertise could be helpful in meeting clinician information needs. A prerequisite for creating such systems is an information seeking model that facilitates the representation of human search expertise. The purpose of developing such a model is to provide guidance to information seeking system development and to shape an empirical research program. Design: The information seeking process was modeled as a complex problem-solving activity. After considering how similarly complex activities had been modeled in other domains, we determined that modeling context-initiated information seeking across multiple problem spaces allows the abstraction of search knowledge into functionally consistent layers. The knowledge layers were identified in the information science literature and validated through our observations of searches performed by health science librarians. Results: A hierarchical multi-level model of context-initiated information seeking is proposed. Each level represents (1) a problem space that is traversed during the online search process, and (2) a distinct layer of knowledge that is required to execute a successful search. Grand strategy determines what information resources will be searched, for what purpose, and in what order. The strategy level represents an overall approach for searching a single resource. Tactics are individual moves made to further a strategy. Operations are mappings of abstract intentions to information resource-specific concrete input. Assessment is the basis of interaction within the strategic hierarchy, influencing the direction of the search. Conclusion: The described multi-level model provides a framework for future research and the foundation for development of an

Multi-omics approach to elucidate the gut microbiota activity: Metaproteomics and metagenomics connection.

Science.gov (United States)

Guirro, Maria; Costa, Andrea; Gual-Grau, Andreu; Mayneris-Perxachs, Jordi; Torrell, Helena; Herrero, Pol; Canela, Núria; Arola, Lluís

2018-02-10

Over the last few years, the application of high-throughput meta-omics methods has provided great progress in improving the knowledge of the gut ecosystem and linking its biodiversity to host health conditions, offering complementary support to classical microbiology. Gut microbiota plays a crucial role in relevant diseases such as obesity or cardiovascular disease (CVD), and its regulation is closely influenced by several factors, such as dietary composition. In fact, polyphenol-rich diets are the most palatable treatment to prevent hypertension associated with CVD, although the polyphenol-microbiota interactions have not been completely elucidated. For this reason, the aim of this study was to evaluate microbiota effect in obese rats supplemented by hesperidin, after being fed with cafeteria or standard diet, using a multi meta-omics approaches combining strategy of metagenomics and metaproteomics analysis. We reported that cafeteria diet induces obesity, resulting in changes in the microbiota composition, which are related to functional alterations at proteome level. In addition, hesperidin supplementation alters microbiota diversity and also proteins involved in important metabolic pathways. Overall, going deeper into strategies to integrate omics sciences is necessary to understand the complex relationships between the host, gut microbiota, and diet. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Heat and mass transfer intensification and shape optimization a multi-scale approach

CERN Document Server

2013-01-01

Is the heat and mass transfer intensification defined as a new paradigm of process engineering, or is it just a common and old idea, renamed and given the current taste? Where might intensification occur? How to achieve intensification? How the shape optimization of thermal and fluidic devices leads to intensified heat and mass transfers? To answer these questions, Heat & Mass Transfer Intensification and Shape Optimization: A Multi-scale Approach clarifies  the definition of the intensification by highlighting the potential role of the multi-scale structures, the specific interfacial area, the distribution of driving force, the modes of energy supply and the temporal aspects of processes.   A reflection on the methods of process intensification or heat and mass transfer enhancement in multi-scale structures is provided, including porous media, heat exchangers, fluid distributors, mixers and reactors. A multi-scale approach to achieve intensification and shape optimization is developed and clearly expla...

Multi-criteria decision making approaches for green supply chains

NARCIS (Netherlands)

Banasik, Aleksander; Bloemhof-Ruwaard, Jacqueline M.; Kanellopoulos, Argyris; Claassen, G.D.H.; Vorst, van der Jack G.A.J.

2016-01-01

Designing Green Supply Chains (GSCs) requires complex decision-support models that can deal with multiple dimensions of sustainability while taking into account specific characteristics of products and their supply chain. Multi-Criteria Decision Making (MCDM) approaches can be used to quantify

Cities, Europeanization and Multi-level Governance: Governing Climate Change through Transnational Municipal Networks

NARCIS (Netherlands)

Kern, K.; Bulkeley, H.

2009-01-01

This article focuses on a variant of multi-level governance and Europeanization, i.e. the transnational networking of local authorities. Focusing on local climate change policy, the article examines how transnational municipal networks (TMNs) govern in the context of multi-level European governance.

Combined object-oriented approach for development of process control systems

International Nuclear Information System (INIS)

Antonova, I.; Batchkova, I.

2013-01-01

Full text: The traditional approaches for development of software control system in automation an information technology based on a directly code creation are no longer effective and successful enough. The response to these challenges is the Model Driven Engineering (MDE) or its counter part in the field of architectures Model Driven Architecture (MDA). One of the most promising approach supporting MDE and MDA is UML. It does not specify a methodology for software or system design but aims to provide an integrated modeling framework for structural, functional and behavior descriptions. The success of UML in many object-oriented approaches led to an idea of applying UML to design of multi agent systems. The approach proposed in this paper applies modified Harmony methodology and is based on the combined use of UML profile for system engineering, IEC61499 standard and FIPA standard protocols. The benefits of object-oriented paradigm and the models of IEC61499 standard are extended with UML/SysML and FIPA notations. The development phases are illustrated with the UML models of a simple process control system. The main benefits of using the proposed approach can be summarized as: it provides consistency in the syntax and underlying semantics; increases the potential and likelihood of reuse; supports the whole software development life cycle in the field of process control. Including the SysML features, based on extended activity and parametric diagrams, flow ports and items to the proposed approach opens the possibilities for modeling of continuous system and support the development in field of process control. Another advantage, connected to the UML/MARTE profile is the possibility for analysis of the designed system and detailed design of the hardware and software platform of the modeled application. Key words: object-oriented modeling, control system, UML, SysML, IEC 61499

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

Science.gov (United States)

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…

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

Directory of Open Access Journals (Sweden)

J. Brimblecombe

2017-12-01

Conclusion: 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.

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

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Zabiniako Vitaly

2014-12-01

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

Role of calibration, validation, and relevance in multi-level uncertainty integration

International Nuclear Information System (INIS)

Li, Chenzhao; Mahadevan, Sankaran

2016-01-01

Calibration of model parameters is an essential step in predicting the response of a complicated system, but the lack of data at the system level makes it impossible to conduct this quantification directly. In such a situation, system model parameters are estimated using tests at lower levels of complexity which share the same model parameters with the system. For such a multi-level problem, this paper proposes a methodology to quantify the uncertainty in the system level prediction by integrating calibration, validation and sensitivity analysis at different levels. The proposed approach considers the validity of the models used for parameter estimation at lower levels, as well as the relevance at the lower level to the prediction at the system level. The model validity is evaluated using a model reliability metric, and models with multivariate output are considered. The relevance is quantified by comparing Sobol indices at the lower level and system level, thus measuring the extent to which a lower level test represents the characteristics of the system so that the calibration results can be reliably used in the system level. Finally the results of calibration, validation and relevance analysis are integrated in a roll-up method to predict the system output. - Highlights: • Relevance analysis to quantify the closeness of two models. • Stochastic model reliability metric to integrate multiple validation experiments. • Extend the model reliability metric to deal with multivariate output. • Roll-up formula to integrate calibration, validation, and relevance.

Quantitative multi-modal NDT data analysis

International Nuclear Information System (INIS)

Heideklang, René; Shokouhi, Parisa

2014-01-01

A single NDT technique is often not adequate to provide assessments about the integrity of test objects with the required coverage or accuracy. In such situations, it is often resorted to multi-modal testing, where complementary and overlapping information from different NDT techniques are combined for a more comprehensive evaluation. Multi-modal material and defect characterization is an interesting task which involves several diverse fields of research, including signal and image processing, statistics and data mining. The fusion of different modalities may improve quantitative nondestructive evaluation by effectively exploiting the augmented set of multi-sensor information about the material. It is the redundant information in particular, whose quantification is expected to lead to increased reliability and robustness of the inspection results. There are different systematic approaches to data fusion, each with its specific advantages and drawbacks. In our contribution, these will be discussed in the context of nondestructive materials testing. A practical study adopting a high-level scheme for the fusion of Eddy Current, GMR and Thermography measurements on a reference metallic specimen with built-in grooves will be presented. Results show that fusion is able to outperform the best single sensor regarding detection specificity, while retaining the same level of sensitivity

L1 Adaptive Control Augmentation System with Application to the X-29 Lateral/Directional Dynamics: A Multi-Input Multi-Output Approach

Science.gov (United States)

Griffin, Brian Joseph; Burken, John J.; Xargay, Enric

2010-01-01

This paper presents an L(sub 1) adaptive control augmentation system design for multi-input multi-output nonlinear systems in the presence of unmatched uncertainties which may exhibit significant cross-coupling effects. A piecewise continuous adaptive law is adopted and extended for applicability to multi-input multi-output systems that explicitly compensates for dynamic cross-coupling. In addition, explicit use of high-fidelity actuator models are added to the L1 architecture to reduce uncertainties in the system. The L(sub 1) multi-input multi-output adaptive control architecture is applied to the X-29 lateral/directional dynamics and results are evaluated against a similar single-input single-output design approach.

Assessing metacognition of grade 2 and grade 4 students using an adaptation of multi-method interview approach during mathematics problem-solving

Science.gov (United States)

Kuzle, A.

2018-06-01

The important role that metacognition plays as a predictor for student mathematical learning and for mathematical problem-solving, has been extensively documented. But only recently has attention turned to primary grades, and more research is needed at this level. The goals of this paper are threefold: (1) to present metacognitive framework during mathematics problem-solving, (2) to describe their multi-method interview approach developed to study student mathematical metacognition, and (3) to empirically evaluate the utility of their model and the adaptation of their approach in the context of grade 2 and grade 4 mathematics problem-solving. The results are discussed not only with regard to further development of the adapted multi-method interview approach, but also with regard to their theoretical and practical implications.

Radiative characterization of random fibrous media with long cylindrical fibers: Comparison of single- and multi-RTE approaches

Science.gov (United States)

Randrianalisoa, Jaona; Haussener, Sophia; Baillis, Dominique; Lipiński, Wojciech

2017-11-01

Radiative heat transfer is analyzed in participating media consisting of long cylindrical fibers with a diameter in the limit of geometrical optics. The absorption and scattering coefficients and the scattering phase function of the medium are determined based on the discrete-level medium geometry and optical properties of individual fibers. The fibers are assumed to be randomly oriented and positioned inside the medium. Two approaches are employed: a volume-averaged two-intensity approach referred to as multi-RTE approach and a homogenized single-intensity approach referred to as the single-RTE approach. Both approaches require effective properties, determined using direct Monte Carlo ray tracing techniques. The macroscopic radiative transfer equations (for single intensity or two volume-averaged intensities) with the corresponding effective properties are solved using Monte Carlo techniques and allow for the determination of the radiative flux distribution as well as overall transmittance and reflectance of the medium. The results are compared against predictions by the direct Monte Carlo simulation on the exact morphology. The effects of fiber volume fraction and optical properties on the effective radiative properties and the overall slab radiative characteristics are investigated. The single-RTE approach gives accurate predictions for high porosity fibrous media (porosity about 95%). The multi-RTE approach is recommended for isotropic fibrous media with porosity in the range of 79-95%.

Examining multi-level effects on corporate social responsibility and irresponsibility

Directory of Open Access Journals (Sweden)

Mazzei Matthew J.

2015-10-01

Full Text Available What influences firms to engage in socially responsible (irresponsible activities? Corporate social responsibility (CSR, the efforts of firms to create a positive and desirable impact on society, and corporate social irresponsibility (CSI, contrary actions of unethical behavior that negatively influence society, have become an important focus of discussion for both corporations and scholars. Despite this interest, our understanding of organizations’ socially responsible (irresponsible actions and their antecedents is still developing. A dearth of knowledge about the multi-level nature of the drivers of CSR and CSI continues to exist. Utilizing a longitudinal sample composed of 899 firms in 66 industries, we follow a prominent model to empirically examine industry-, firm-, and individual-level effects on CSR and CSI. Employing variance decomposition analysis, our results confirm that all three levels of investigation do indeed influence CSR and CSI. More substantively, our analysis estimates the magnitude of the effects attributable to each of the three levels for both CSR and CSI. We also compare multi-level influences on two separate CSR strategies, those targeting primary stakeholders (strategic CSR and those targeting secondary stakeholders (social CSR. We find greater industry- and firmlevel effects on social CSR, and higher individual-level effects on strategic CSR. Our results build on the conceptual work of previous authors by providing empirical analyses to confirm multilevel influences on CSR and extending prior multi-level theory to the concept of CSI. Further, we add to the emerging literature regarding stakeholder demands by examining the various influences on CSR strategies targeting different stakeholder groups.

A two-stage stochastic programming approach for operating multi-energy systems

DEFF Research Database (Denmark)

Zeng, Qing; Fang, Jiakun; Chen, Zhe

2017-01-01

This paper provides a two-stage stochastic programming approach for joint operating multi-energy systems under uncertainty. Simulation is carried out in a test system to demonstrate the feasibility and efficiency of the proposed approach. The test energy system includes a gas subsystem with a gas...

A Stochastic Programming Approach for a Multi-Site Supply Chain Planning in Textile and Apparel Industry under Demand Uncertainty

Directory of Open Access Journals (Sweden)

Houssem Felfel

2015-11-01

Full Text Available In this study, a new stochastic model is proposed to deal with a multi-product, multi-period, multi-stage, multi-site production and transportation supply chain planning problem under demand uncertainty. A two-stage stochastic linear programming approach is used to maximize the expected profit. Decisions such as the production amount, the inventory level of finished and semi-finished product, the amount of backorder and the quantity of products to be transported between upstream and downstream plants in each period are considered. The robustness of production supply chain plan is then evaluated using statistical and risk measures. A case study from a real textile and apparel industry is shown in order to compare the performances of the proposed stochastic programming model and the deterministic model.

Proposing New Heuristic Approaches for Preventive Maintenance Scheduling

Directory of Open Access Journals (Sweden)

majid Esmailian

2013-08-01

Full Text Available The purpose of preventive maintenance management is to perform a series of tasks that prevent or minimize production breakdowns and improve reliability of production facilities. An important objective of preventive maintenance management is to minimize downtime of production facilities. In order to accomplish this objective, personnel should efficiently allocate resources and determine an effective maintenance schedule. Gopalakrishnan (1997 developed a mathematical model and four heuristic approaches to solve the preventive maintenance scheduling problem of assigning skilled personnel to work with tasks that require a set of corresponding skills. However, there are several limitations in the prior work in this area of research. The craft combination problem has not been solved because the craft combination is assumed as given. The craft combination problem concerns the computation of all combinations of assigning multi skilled workers to accomplishment of a particular task. In fact, determining craft combinations is difficult because of the exponential number of craft combinations that are possible. This research provides a heuristic approach for determining the craft combination and four new heuristic approach solution for the preventive maintenance scheduling problem with multi skilled workforce constraints. In order to examine the new heuristic approach and to compare the new heuristic approach with heuristic approach of Gopalakrishnan (1997, 81 standard problems have been generated based on the criterion suggested by from Gopalakrishnan (1997. The average solution quality (SQ of the new heuristic approaches is 1.86% and in old heuristic approaches is 8.32%. The solution time of new heuristic approaches are shorter than old heuristic approaches. The solution time of new heuristic approaches is 0.78 second and old heuristic approaches is 6.43 second, but the solution time of mathematical model provided by Gopalakrishnan (1997 is 152 second. �

Energetic Variational Approach to Multi-Component Fluid Flows

Science.gov (United States)

Kirshtein, Arkadz; Liu, Chun; Brannick, James

2017-11-01

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

Improved quantitation and reproducibility in multi-PET/CT lung studies by combining CT information.

Science.gov (United States)

Holman, Beverley F; Cuplov, Vesna; Millner, Lynn; Endozo, Raymond; Maher, Toby M; Groves, Ashley M; Hutton, Brian F; Thielemans, Kris

2018-06-05

Matched attenuation maps are vital for obtaining accurate and reproducible kinetic and static parameter estimates from PET data. With increased interest in PET/CT imaging of diffuse lung diseases for assessing disease progression and treatment effectiveness, understanding the extent of the effect of respiratory motion and establishing methods for correction are becoming more important. In a previous study, we have shown that using the wrong attenuation map leads to large errors due to density mismatches in the lung, especially in dynamic PET scans. Here, we extend this work to the case where the study is sub-divided into several scans, e.g. for patient comfort, each with its own CT (cine-CT and 'snap shot' CT). A method to combine multi-CT information into a combined-CT has then been developed, which averages the CT information from each study section to produce composite CT images with the lung density more representative of that in the PET data. This combined-CT was applied to nine patients with idiopathic pulmonary fibrosis, imaged with dynamic 18 F-FDG PET/CT to determine the improvement in the precision of the parameter estimates. Using XCAT simulations, errors in the influx rate constant were found to be as high as 60% in multi-PET/CT studies. Analysis of patient data identified displacements between study sections in the time activity curves, which led to an average standard error in the estimates of the influx rate constant of 53% with conventional methods. This reduced to within 5% after use of combined-CTs for attenuation correction of the study sections. Use of combined-CTs to reconstruct the sections of a multi-PET/CT study, as opposed to using the individually acquired CTs at each study stage, produces more precise parameter estimates and may improve discrimination between diseased and normal lung.

Towards Multi-Method Research Approach in Empirical Software Engineering

Science.gov (United States)

Mandić, Vladimir; Markkula, Jouni; Oivo, Markku

This paper presents results of a literature analysis on Empirical Research Approaches in Software Engineering (SE). The analysis explores reasons why traditional methods, such as statistical hypothesis testing and experiment replication are weakly utilized in the field of SE. It appears that basic assumptions and preconditions of the traditional methods are contradicting the actual situation in the SE. Furthermore, we have identified main issues that should be considered by the researcher when selecting the research approach. In virtue of reasons for weak utilization of traditional methods we propose stronger use of Multi-Method approach with Pragmatism as the philosophical standpoint.

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

Science.gov (United States)

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.

PUMA Development through a Multi physics Approach

International Nuclear Information System (INIS)

Cheon, Jinsik; Kim, Junehyung; Lee, Byoungoon; Lee, Chanbock

2013-01-01

Meanwhile advances of numerical methods make it possible for the multi physics problem to be solved in a fully coupled way. In addition to a multidimensional, multi physical approach, a nuclear fuel performance analysis code, which is 1D code, should be improved by accommodating the state-of-the-art in the numerical analysis to support current fuel design and performance analysis. In particular, the coupling between the mechanical equilibrium equation and a set of numerically stiff kinetics equations for fission gas release is of great importance for a multi physics simulation of nuclear fuel. Instead, coupling between temperature and fuel constituent was found to be made with a relative ease by employing an ordinary differential equations solver. As an effort for a new SFR metal fuel performance analysis code, called PUMA (Performance of Uranium Metal fuel rod Analysis code), the deformation of U-Zr fuel for SFR in connection with a fission gas release model is analyzed. A finite element analyses for purely mechanical problems are performed using a backward differentiation formula, and are subjected to scrupulous verification with Abaqus. Then mechanical equilibrium equation and the equations for fission gas release are coupled with the same differential-algebraic equations (DAE) solver

Extending the enterprise through multi-level supply control

NARCIS (Netherlands)

Vlist, van der P.; Hoppenbrouwers, J.J.E.M.; Hegge, H.M.H.

1997-01-01

Demands for flexibility require larger parts of the supply chain to become customer driven. This article describes multi-level supply control (MLSC) as a mechanism to facilitate that; it allows to specify gradually and thus to shift the customer order decoupling point well across the boundary to the

Multi-octave spectral beam combiner on ultra-broadband photonic integrated circuit platform.

Science.gov (United States)

Stanton, Eric J; Heck, Martijn J R; Bovington, Jock; Spott, Alexander; Bowers, John E

2015-05-04

We present the design of a novel platform that is able to combine optical frequency bands spanning 4.2 octaves from ultraviolet to mid-wave infrared into a single, low M2 output waveguide. We present the design and realization of a key component in this platform that combines the wavelength bands of 350 nm - 1500 nm and 1500 nm - 6500 nm with demonstrated efficiency greater than 90% in near-infrared and mid-wave infrared. The multi-octave spectral beam combiner concept is realized using an integrated platform with silicon nitride waveguides and silicon waveguides. Simulated bandwidth is shown to be over four octaves, and measured bandwidth is shown over two octaves, limited by the availability of sources.

A multi-disciplinary approach for the integrated assessment of water alterations under climate change

Science.gov (United States)

Sperotto, Anna; Torresan, Silvia; Molina, Jose Luis; Pulido Velazquez, Manuel; Critto, Andrea; Marcomini, Antonio

2017-04-01

Understanding the co-evolution and interrelations between natural and human pressures on water systems is required to ensure a sustainable management of resources under uncertain climate change conditions. To pursue multi-disciplinary research is therefore necessary to consider the multiplicity of stressors affecting water resources, take into account alternative perspectives (i.e. social, economic and environmental objective and priorities) and deal with uncertainty which characterize climate change scenarios. However, approaches commonly adopted in water quality assessment are predominantly mono-disciplinary, single-stressors oriented and apply concepts and models specific of different academic disciplines (e.g. physics, hydrology, ecology, sociology, economy) which, in fact, seldom shed their conceptual blinders failing to provide truly integrated results. In this context, the paper discusses the benefits and limits of adopting a multi-disciplinary approach where different knowledge domains collaborate and quantitative and qualitative information, coming from multiple conceptual and model-based research, are integrated in a harmonic manner. Specifically, Bayesian Networks are used as meta-modelling tool for structuring and combining the probabilistic information available in existing hydrological models, climate change and land use projections, historical observations and expert opinion. The developed network allows to perform a stochastic multi-risk assessment considering the interlacing between climate (i.e. irregularities in water regime) and land use changes (i.e. agriculture, urbanization) and their cascading impacts on water quality parameters (i.e. nutrients loadings). Main objective of the model is the development of multi-risk scenarios to assess and communicate the probability of not meeting a "Good chemical water status" over future timeframe taking into account projected climatic and not climatic conditions. The outcomes are finally used to identify

Analytical approach to the multi-state lasing phenomenon in quantum dot lasers

Science.gov (United States)

Korenev, V. V.; Savelyev, A. V.; Zhukov, A. E.; Omelchenko, A. V.; Maximov, M. V.

2013-03-01

We introduce an analytical approach to describe the multi-state lasing phenomenon in quantum dot lasers. We show that the key parameter is the hole-to-electron capture rate ratio. If it is lower than a certain critical value, the complete quenching of ground-state lasing takes place at high injection levels. At higher values of the ratio, the model predicts saturation of the ground-state power. This explains the diversity of experimental results and their contradiction to the conventional rate equation model. Recently found enhancement of ground-state lasing in p-doped samples and temperature dependence of the ground-state power are also discussed.

Energy mesh optimization for multi-level calculation schemes

International Nuclear Information System (INIS)

Mosca, P.; Taofiki, A.; Bellier, P.; Prevost, A.

2011-01-01

The industrial calculations of third generation nuclear reactors are based on sophisticated strategies of homogenization and collapsing at different spatial and energetic levels. An important issue to ensure the quality of these calculation models is the choice of the collapsing energy mesh. In this work, we show a new approach to generate optimized energy meshes starting from the SHEM 281-group library. The optimization model is applied on 1D cylindrical cells and consists of finding an energy mesh which minimizes the errors between two successive collision probability calculations. The former is realized over the fine SHEM mesh with Livolant-Jeanpierre self-shielded cross sections and the latter is performed with collapsed cross sections over the energy mesh being optimized. The optimization is done by the particle swarm algorithm implemented in the code AEMC and multigroup flux solutions are obtained from standard APOLLO2 solvers. By this new approach, a set of new optimized meshes which encompass from 10 to 50 groups has been defined for PWR and BWR calculations. This set will allow users to adapt the energy detail of the solution to the complexity of the calculation (assembly, multi-assembly, two-dimensional whole core). Some preliminary verifications, in which the accuracy of the new meshes is measured compared to a direct 281-group calculation, show that the 30-group optimized mesh offers a good compromise between simulation time and accuracy for a standard 17 x 17 UO 2 assembly with and without control rods. (author)

Developing State Level Approaches under the State Level Concept

International Nuclear Information System (INIS)

Budlong Sylvester, K.; Murphy, C.L.; Boyer, B.; Pilat, J.F.

2015-01-01

With the pursuit of the State-Level Concept (SLC), the IAEA has sought to further evolve the international safeguards system in a manner which maintains (or improves) the effectiveness of the system in an environment of expanding demands and limited resources. The IAEA must not remain static and should continuously examine its practices to ensure it can capture opportunities for cost reductions while adapting to, and staying ahead of, emerging proliferation challenges. Contemporary safeguards have been focused on assessing the nuclear programme of the State as a whole, rather than on the basis of individual facilities. Since the IAEA's integrated safeguards program, State-level Approaches (SLAs) have been developed that seek to optimally combine the measures provided for by the Additional Protocol with those of traditional safeguards. This process resulted in facility specific approaches that, while making use of a State's broader conclusion, were nonetheless prescriptive. Designing SLAs on a State-by-State basis would avoid the shortcomings of a one-size-fits-all system. It would also enable the effective use of the Agency's information analysis and State evaluation efforts by linking this analysis to safeguards planning efforts. Acquisition Path Analysis (APA), along with the State Evaluation process, can be used to prioritize paths in a State in terms of their attractiveness for proliferation. While taking advantage of all safeguards relevant information, and tailoring safeguards to individual characteristics of the State, paths of the highest priority in all States will necessarily meet the same standard of coverage. Similarly, lower priority paths will have lower performance targets, thereby promoting nondiscrimination. Such an approach would improve understanding of safeguards implementation under the SLC and the rational for safeguards resource allocation. The potential roles for APA and performance targets in SLA development will be reviewed

Multi-Kernel Learning with Dartel Improves Combined MRI-PET Classification of Alzheimer’s Disease in AIBL Data: Group and Individual Analyses

Directory of Open Access Journals (Sweden)

Vahab Youssofzadeh

2017-07-01

Full Text Available Magnetic resonance imaging (MRI and positron emission tomography (PET are neuroimaging modalities typically used for evaluating brain changes in Alzheimer’s disease (AD. Due to their complementary nature, their combination can provide more accurate AD diagnosis or prognosis. In this work, we apply a multi-modal imaging machine-learning framework to enhance AD classification and prediction of diagnosis of subject-matched gray matter MRI and Pittsburgh compound B (PiB-PET data related to 58 AD, 108 mild cognitive impairment (MCI and 120 healthy elderly (HE subjects from the Australian imaging, biomarkers and lifestyle (AIBL dataset. Specifically, we combined a Dartel algorithm to enhance anatomical registration with multi-kernel learning (MKL technique, yielding an average of >95% accuracy for three binary classification problems: AD-vs.-HE, MCI-vs.-HE and AD-vs.-MCI, a considerable improvement from individual modality approach. Consistent with t-contrasts, the MKL weight maps revealed known brain regions associated with AD, i.e., (parahippocampus, posterior cingulate cortex and bilateral temporal gyrus. Importantly, MKL regression analysis provided excellent predictions of diagnosis of individuals by r2 = 0.86. In addition, we found significant correlations between the MKL classification and delayed memory recall scores with r2 = 0.62 (p < 0.01. Interestingly, outliers in the regression model for diagnosis were mainly converter samples with a higher likelihood of converting to the inclined diagnostic category. Overall, our work demonstrates the successful application of MKL with Dartel on combined neuromarkers from different neuroimaging modalities in the AIBL data. This lends further support in favor of machine learning approach in improving the diagnosis and risk prediction of AD.

Monitoring gas and heat emissions at Norris Geyser Basin, Yellowstone National Park, USA based on a combined eddy covariance and Multi-GAS approach

Science.gov (United States)

Lewicki, J. L.; Kelly, P. J.; Bergfeld, D.; Vaughan, R. G.; Lowenstern, J. B.

2017-11-01

.1, respectively, on average) were invariant during the measurement period and fell within the range of values measured in direct fumarole gas samples. The soil gas H2O/CO2 end member ratios ( 15-30) were variable and low relative to the fumarole end member, likely resulting from water vapor loss during cooling and condensation in the shallow subsurface, whereas the CO2/H2S end member ratio was high ( 160), presumably related to transport of CO2-dominated soil gas emissions mixed with trace fumarolic emissions to the Multi-GAS station. Nighttime eddy covariance ratios of H2O to CO2 flux were typically between the soil gas and fumarole end member H2O/CO2 ratios defined by Multi-GAS measurements. Overall, the combined eddy covariance and Multi-GAS approach provides a powerful tool for quasi-continuous measurements of gas and heat emissions for improved volcano-hydrothermal monitoring.

Monitoring gas and heat emissions at Norris Geyser Basin, Yellowstone National Park, USA based on a combined eddy covariance and Multi-GAS approach

Science.gov (United States)

Lewicki, Jennifer L.; Kelly, Peter; Bergfeld, Deborah; Vaughan, R. Greg; Lowenstern, Jacob B.

2017-01-01

fumarole H2O/CO2 and CO2/H2S end member ratios (101.7 and 27.1, respectively, on average) were invariant during the measurement period and fell within the range of values measured in direct fumarole gas samples. The soil gas H2O/CO2end member ratios (~ 15–30) were variable and low relative to the fumarole end member, likely resulting from water vapor loss during cooling and condensation in the shallow subsurface, whereas the CO2/H2S end member ratio was high (~ 160), presumably related to transport of CO2-dominated soil gas emissions mixed with trace fumarolic emissions to the Multi-GAS station. Nighttime eddy covariance ratios of H2O to CO2 flux were typically between the soil gas and fumarole end member H2O/CO2 ratios defined by Multi-GAS measurements. Overall, the combined eddy covariance and Multi-GAS approach provides a powerful tool for quasi-continuous measurements of gas and heat emissions for improved volcano-hydrothermal monitoring.

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

Directory of Open Access Journals (Sweden)

Amanda Bourne

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

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

Science.gov (United States)

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

2016-01-01

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

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

Directory of Open Access Journals (Sweden)

Gupta Neha

2016-01-01

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

On-chip power-combining techniques for watt-level linear power amplifiers in 0.18 μm CMOS

International Nuclear Information System (INIS)

Ren Zhixiong; Zhang Kefeng; Liu Lanqi; Li Cong; Chen Xiaofei; Liu Dongsheng; Liu Zhenglin; Zou Xuecheng

2015-01-01

Three linear CMOS power amplifiers (PAs) with high output power (more than watt-level output power) for high data-rate mobile applications are introduced. To realize watt-level output power, there are two 2.4 GHz PAs using an on-chip parallel combining transformer (PCT) and one 1.95 GHz PA using an on-chip series combining transformer (SCT) to combine output signals of multiple power stages. Furthermore, some linearization techniques including adaptive bias, diode linearizer, multi-gated transistors (MGTR) and the second harmonic control are applied in these PAs. Using the proposed power combiner, these three PAs are designed and fabricated in TSMC 0.18 μm RFCMOS process. According to the measurement results, the proposed two linear 2.4 GHz PAs achieve a gain of 33.2 dB and 34.3 dB, a maximum output power of 30.7 dBm and 29.4 dBm, with 29% and 31.3% of peak PAE, respectively. According to the simulation results, the presented linear 1.95 GHz PA achieves a gain of 37.5 dB, a maximum output power of 34.3 dBm with 36.3% of peak PAE. (paper)

A novel combined interventional radiologic and hepatobiliary surgical approach to a complex traumatic hilar biliary stricture

Directory of Open Access Journals (Sweden)

Rachel E. NeMoyer

Full Text Available Introduction: Benign strictures of the biliary system are challenging and uncommon conditions requiring a multidisciplinary team for appropriate management. Presentation of case: The patient is a 32-year-old male that developed a hilar stricture as sequelae of a gunshot wound. Due to the complex nature of the stricture and scarring at the porta hepatis a combined interventional radiologic and surgical approach was carried out to approach the hilum of the right and left hepatic ducts. The location of this stricture was found by ultrasound guidance intraoperatively using a balloon tipped catheter placed under fluoroscopy in the interventional radiology suite prior to surgery. This allowed the surgeons to select the line of parenchymal transection for best visualization of the stricture. A left hepatectomy was performed, the internal stent located and the right hepatic duct opened tangentially to allow a side-to-side Roux-en-Y hepaticojejunostomy (a Puestow-like anastomosis. Discussion: Injury to the intrahepatic biliary ductal confluence is rarely fatal, however, the associated injuries lead to severe morbidity as seen in this example. Management of these injuries poses a considerable challenge to the surgeon and treating physicians. Conclusion: Here we describe an innovative multi-disciplinary approach to the repair of this rare injury. Keywords: Combined approach, Interventional radiology, Hepatobiliary surgery, Complex traumatic hilar biliary stricture, Case report

CMT: a constrained multi-level thresholding approach for ChIP-Seq data analysis.

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Iman Rezaeian

Full Text Available Genome-wide profiling of DNA-binding proteins using ChIP-Seq has emerged as an alternative to ChIP-chip methods. ChIP-Seq technology offers many advantages over ChIP-chip arrays, including but not limited to less noise, higher resolution, and more coverage. Several algorithms have been developed to take advantage of these abilities and find enriched regions by analyzing ChIP-Seq data. However, the complexity of analyzing various patterns of ChIP-Seq signals still needs the development of new algorithms. Most current algorithms use various heuristics to detect regions accurately. However, despite how many formulations are available, it is still difficult to accurately determine individual peaks corresponding to each binding event. We developed Constrained Multi-level Thresholding (CMT, an algorithm used to detect enriched regions on ChIP-Seq data. CMT employs a constraint-based module that can target regions within a specific range. We show that CMT has higher accuracy in detecting enriched regions (peaks by objectively assessing its performance relative to other previously proposed peak finders. This is shown by testing three algorithms on the well-known FoxA1 Data set, four transcription factors (with a total of six antibodies for Drosophila melanogaster and the H3K4ac antibody dataset.

River modeling and multi-level fish health assessment to evaluate impacts from oil sands water releases (Part 2)

International Nuclear Information System (INIS)

Shaw, R.; Swanson, S.M.; Lagimodiere, M.; Gulley, J.

1995-01-01

A multi-level, multi-scale approach was used to assess potential impacts to fish health from oil sands water releases. The method used to arrive at predicted impacts involved assembling experimental data on the effects of chronic exposure to oil sands wastewaters on biochemical, physiological and whole-organism endpoint. This information was used to determine no effect levels (NOELs) and lowest effect levels (LOELs) for the suite of fish health parameters used in laboratory experiments (primarily biochemical and physiological measurement endpoints). LOELs and NOELs were compared to modeled concentrations of wastewater in the Athabasca River for five time snapshots. For each time period, concentrations were predicted based on mean annual flows and 7Q10 flows (low flows). This comparison was used to predict impacts on biochemical/physiological endpoints. Impacts on at the whole-organism and population-level were determined by comparing what the laboratory data would predict with what was observed in the field. This process was used to draw a conclusion regarding the health and sustainability of fish populations

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

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Rinku Roy Chowdhury

2011-01-01

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

Towards a Usability and Error "Safety Net": A Multi-Phased Multi-Method Approach to Ensuring System Usability and Safety.

Science.gov (United States)

Kushniruk, Andre; Senathirajah, Yalini; Borycki, Elizabeth

2017-01-01

The usability and safety of health information systems have become major issues in the design and implementation of useful healthcare IT. In this paper we describe a multi-phased multi-method approach to integrating usability engineering methods into system testing to ensure both usability and safety of healthcare IT upon widespread deployment. The approach involves usability testing followed by clinical simulation (conducted in-situ) and "near-live" recording of user interactions with systems. At key stages in this process, usability problems are identified and rectified forming a usability and technology-induced error "safety net" that catches different types of usability and safety problems prior to releasing systems widely in healthcare settings.

Multi-criteria framework as an innovative tradeoff approach to determine the shelf-life of high pressure-treated poultry.

Science.gov (United States)

Guillou, S; Lerasle, M; Simonin, H; Anthoine, V; Chéret, R; Federighi, M; Membré, J-M

2016-09-16

A multi-criteria framework combining safety, hygiene and sensorial quality was developed to investigate the possibility of extending the shelf-life and/or removing lactate by applying High Hydrostatic Pressure (HHP) in a ready-to-cook (RTC) poultry product. For this purpose, Salmonella and Listeria monocytogenes were considered as safety indicators and Escherichia coli as hygienic indicator. Predictive modeling was used to determine the influence of HHP and lactate concentration on microbial growth and survival of these indicators. To that end, probabilistic assessment exposure models developed in a previous study (Lerasle, M., Guillou, S., Simonin, H., Anthoine, V., Chéret, R., Federighi, M., Membré, J.M. 2014. Assessment of Salmonella and L. monocytogenes level in ready-to-cook poultry meat: Effect of various high pressure treatments and potassium lactate concentrations. International Journal of Food Microbiology 186, 74-83) were used for L. monocytogenes and Salmonella. Besides, for E. coli, an exposure assessment model was built by modeling data from challenge-test experiments. Finally, sensory tests and color measurements were performed to evaluate the effect of HHP on the organoleptic quality of an RTC product. Quantitative rules of decision based on safety, hygienic and organoleptic criteria were set. Hygienic and safety criteria were associated with probability to exceed maximum contamination levels of L. monocytogenes, Salmonella and E. coli at the end of the shelf-life whereas organoleptic criteria corresponded to absence of statistical difference between pressurized and unpressurized products. A tradeoff between safety and hygienic risk, color and taste, was then applied to define process and formulation enabling shelf-life extension. In the resulting operating window, one condition was experimentally assayed on naturally contaminated RTC products to validate the multi-criteria approach. As a conclusion, the framework was validated; it was possible to

An Efficacious Multi-Objective Fuzzy Linear Programming Approach for Optimal Power Flow Considering Distributed Generation.

Science.gov (United States)

Warid, Warid; Hizam, Hashim; Mariun, Norman; Abdul-Wahab, Noor Izzri

2016-01-01

This paper proposes a new formulation for the multi-objective optimal power flow (MOOPF) problem for meshed power networks considering distributed generation. An efficacious multi-objective fuzzy linear programming optimization (MFLP) algorithm is proposed to solve the aforementioned problem with and without considering the distributed generation (DG) effect. A variant combination of objectives is considered for simultaneous optimization, including power loss, voltage stability, and shunt capacitors MVAR reserve. Fuzzy membership functions for these objectives are designed with extreme targets, whereas the inequality constraints are treated as hard constraints. The multi-objective fuzzy optimal power flow (OPF) formulation was converted into a crisp OPF in a successive linear programming (SLP) framework and solved using an efficient interior point method (IPM). To test the efficacy of the proposed approach, simulations are performed on the IEEE 30-busand IEEE 118-bus test systems. The MFLP optimization is solved for several optimization cases. The obtained results are compared with those presented in the literature. A unique solution with a high satisfaction for the assigned targets is gained. Results demonstrate the effectiveness of the proposed MFLP technique in terms of solution optimality and rapid convergence. Moreover, the results indicate that using the optimal DG location with the MFLP algorithm provides the solution with the highest quality.

First 3D Cadastral Registration of Multi-level Ownerships Rights in the Netherlands

NARCIS (Netherlands)

Ploeger, H.D.; Stoter, J.E.; Roes, R; Van der Riet, E.; Biljecki, F.; Ledoux, H.

2016-01-01

This paper reports on the first 3D cadastral registration of multi-level ownerships rights in the Netherlands, which was accomplished in March 2016. It is the result of a study that was undertaken from 2013 to 2015 to determine how insight about multi-level ownership can be provided in 3D by the

A Holistic Approach with Special Reference to Heat Transfer in Multi-Component Porous Media Systems

Directory of Open Access Journals (Sweden)

A. K. Borah

2010-06-01

Full Text Available Problems involving multiphase flow, heat transfer and multi-component mass transport in porous media arise in a number of scientific engineering disciplines. Important technological applications include thermally enhanced oil recovery, subsurface contamination and remediation, capillary assisted thermal technologies, drying process, thermal insulation materials, multiphase trickle bed reactors, nuclear reactor safety analysis, high level radioactive waste repositories and geothermal energy exploitation. In this paper we demonstrate multiphase flows in porous media are driven by gravitational, capillary and viscous forces. But gravity causes phase migration in the direction of the gravitational field. Microscopic modelling efforts were made to accurately incorporate microscopic interfacial phenomena. Multi-scale modelling approaches were attempted in order to transmit information over various lengths scales, ranging from micro-scale, meso-scale, macro-scale and finally to the field scale.

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

Science.gov (United States)

Choi, H.; Kim, S.

2012-12-01

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

Assessing the potential hydrological impact of the Gibe III Dam on Lake Turkana water level using multi-source satellite data

Science.gov (United States)

Velpuri, N. M.; Senay, G. B.

2012-10-01

Lake Turkana, the largest desert lake in the world, is fed by ungauged or poorly gauged river systems. To meet the demand of electricity in the East African region, Ethiopia is currently building the Gibe III hydroelectric dam on the Omo River, which supplies more than 80% of the inflows to Lake Turkana. On completion, the Gibe III dam will be the tallest dam in Africa with a height of 241 m. However, the nature of interactions and potential impacts of regulated inflows to Lake Turkana are not well understood due to its remote location and unavailability of reliable in situ datasets. In this study, we used 12 yr (1998-2009) of existing multi-source satellite and model-assimilated global weather data. We used a calibrated multi-source satellite data-driven water balance model for Lake Turkana that takes into account model routed runoff, lake/reservoir evapotranspiration, direct rain on lakes/reservoirs and releases from the dam to compute lake water levels. The model evaluates the impact of the Gibe III dam using three different approaches - a historical approach, a rainfall based approach, and a statistical approach to generate rainfall-runoff scenarios. All the approaches provided comparable and consistent results. Model results indicated that the hydrological impact of the Gibe III dam on Lake Turkana would vary with the magnitude and distribution of rainfall post-dam commencement. On average, the reservoir would take up to 8-10 months, after commencement, to reach a minimum operation level of 201 m depth of water. During the dam filling period, the lake level would drop up to 1-2 m (95% confidence) compared to the lake level modeled without the dam. The lake level variability caused by regulated inflows after the dam commissioning were found to be within the natural variability of the lake of 4.8 m. Moreover, modeling results indicated that the hydrological impact of the Gibe III dam would depend on the initial lake level at the time of dam commencement. Areas

Quantifying hidden defect in multi-layered structures by using eddy current system combined with a scanner

International Nuclear Information System (INIS)

Huang Pingjie; Zhou Zekui; Wu Zhaotong

2005-01-01

The eddy current testing forward model of scanning inspection of multi-layered structures is introduced and simulation work is carried out to reveal the interaction between the scanning coil and defects with different geometric properties. A multi-frequency ECT experimental instrument combined with a scanner is established and scanning inspections are performed to detect the artificial etched flaws with different geometric parameters in the multi-layered structures. The predicted signals by the forward model are compared with the measured signals and the defects are characterized

Hybrid Fusion for Biometrics: Combining Score-level and Decision-level Fusion

NARCIS (Netherlands)

Tao, Q.; Veldhuis, Raymond N.J.

2008-01-01

A general framework of fusion at decision level, which works on ROCs instead of matching scores, is investigated. Under this framework, we further propose a hybrid fusion method, which combines the score-level and decision-level fusions, taking advantage of both fusion modes. The hybrid fusion

Multi-level risk factors for suicidal ideation among at-risk adolescent females : The role of hypothalamic-pituitary-adrenal axis responses to stress

NARCIS (Netherlands)

Giletta, M.; Calhoun, C.D.; Hastings, P.D.; Rudolph, K.D.; Nock, M.K.; Prinstein, M.J.

2015-01-01

Adopting a multi-level approach, this study examined risk factors for adolescent suicidal ideation, with specific attention to (a) hypothalamic-pituitary-adrenal (HPA) axis stress responses and (b) the interplay between HPA-axis and other risk factors from multiple domains (i.e., psychological,

New techniques for multi-level cross section calculation and fitting

International Nuclear Information System (INIS)

Froehner, F.H.

1980-09-01

A number of recent developments in multi-level cross section work are described. A new iteration scheme for the conversion of Reich-Moore resonance parameters to Kapur-Peierls parameters allows application of Turing's method for Gaussian broadening of meromorphic functions directly to multi-level cross section expressions, without recourse to the Voigt profiles psi and chi. This makes calculation of Doppler-broadened Reich-Moore and MLBW cross sections practically as fast as SLBW and Adler-Adler cross section calculations involving the Voigt profiles. A convenient distant-level treatment utilizing average resonance parameters is presented. Apart from effectively dealing with edge effects in resonance fitting work it also leads to a simple prescription for the determination of bound levels which reproduce the thermal cross sections correctly. A brief discussion of improved resonance shape fitting techniques is included, with empahsis on the importance of correlated errors and proper use of prior information by application of Bayes' theorem. (orig.) [de

New techniques for multi-level cross section calculation and fitting

International Nuclear Information System (INIS)

Froehner, F.H.

1981-01-01

A number of recent developments in multi-level cross section work are described. A new iteration scheme for the conversion of Reich-Moore resonance parameters to Kapur-Peierls parameters allows application of Turing's method for Gaussian broadening of meromorphic functions directly to multi-level cross section expressions, without recourse to the Voigt profiles psi and chi. This makes calculation of Doppler-broadened Reich-Moore and MLBW cross sections practically as fast as SLBW and Adler-Adler cross section calculations involving the Voigt profiles. A convenient distant-level treatment utilizing average resonance parameters is presented. Apart from effectively dealing with edge effects in resonance fitting work it also leads to a simple prescription for the determination of bound levels which reproduce the thermal cross sections correctly. A brief discussion of improved resonance shape fitting techniques is included, with emphasis on the importance of correlated errors and proper use of prior information by application of Bayes' theorem

A 3D convolutional neural network approach to land cover classification using LiDAR and multi-temporal Landsat imagery

Science.gov (United States)

Xu, Z.; Guan, K.; Peng, B.; Casler, N. P.; Wang, S. W.

2017-12-01

Landscape has complex three-dimensional features. These 3D features are difficult to extract using conventional methods. Small-footprint LiDAR provides an ideal way for capturing these features. Existing approaches, however, have been relegated to raster or metric-based (two-dimensional) feature extraction from the upper or bottom layer, and thus are not suitable for resolving morphological and intensity features that could be important to fine-scale land cover mapping. Therefore, this research combines airborne LiDAR and multi-temporal Landsat imagery to classify land cover types of Williamson County, Illinois that has diverse and mixed landscape features. Specifically, we applied a 3D convolutional neural network (CNN) method to extract features from LiDAR point clouds by (1) creating occupancy grid, intensity grid at 1-meter resolution, and then (2) normalizing and incorporating data into a 3D CNN feature extractor for many epochs of learning. The learned features (e.g., morphological features, intensity features, etc) were combined with multi-temporal spectral data to enhance the performance of land cover classification based on a Support Vector Machine classifier. We used photo interpretation for training and testing data generation. The classification results show that our approach outperforms traditional methods using LiDAR derived feature maps, and promises to serve as an effective methodology for creating high-quality land cover maps through fusion of complementary types of remote sensing data.

A multiobjective modeling approach to locate multi-compartment containers for urban-sorted waste

International Nuclear Information System (INIS)

Tralhao, Lino; Coutinho-Rodrigues, Joao; Alcada-Almeida, Luis

2010-01-01

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 two 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

A scenario framework to explore the future migration and adaptation in deltas: A multi-scale and participatory approach

Science.gov (United States)

Kebede, Abiy S.; Nicholls, Robert J.; Allan, Andrew; Arto, Inaki; Cazcarro, Ignacio; Fernandes, Jose A.; Hill, Chris T.; Hutton, Craig W.; Kay, Susan; Lawn, Jon; Lazar, Attila N.; Whitehead, Paul W.

2017-04-01

-economic factors), and (vi) delta-scale (e.g., future adaptation and migration policies) scenarios. The framework includes and combines expert-based and participatory approaches and provides improved specification of the role of scenarios to analyse the future state of adaptation and migration across the three deltas. It facilitates the development of appropriate and consistent endogenous and exogenous scenario futures: (i) at the delta-scale, (ii) across all deltas, and (iii) with wider climate change, environmental change, and adaptation & migration research. Key words: Coastal deltas, sea-level rise, migration and adaptation, multi-scale scenarios, participatory approach *DECCMA (Deltas, Vulnerability & Climate Change: Migration & Adaptation) project is part of the Collaborative ADAPTATION Research Initiative in Africa and Asia (CARIAA), with financial support from the UK Government's Department for International Development (DFID) and the International Development Research Centre (IDRC), Canada.

Multi-level deep supervised networks for retinal vessel segmentation.

Science.gov (United States)

Mo, Juan; Zhang, Lei

2017-12-01

Changes in the appearance of retinal blood vessels are an important indicator for various ophthalmologic and cardiovascular diseases, including diabetes, hypertension, arteriosclerosis, and choroidal neovascularization. Vessel segmentation from retinal images is very challenging because of low blood vessel contrast, intricate vessel topology, and the presence of pathologies such as microaneurysms and hemorrhages. To overcome these challenges, we propose a neural network-based method for vessel segmentation. A deep supervised fully convolutional network is developed by leveraging multi-level hierarchical features of the deep networks. To improve the discriminative capability of features in lower layers of the deep network and guide the gradient back propagation to overcome gradient vanishing, deep supervision with auxiliary classifiers is incorporated in some intermediate layers of the network. Moreover, the transferred knowledge learned from other domains is used to alleviate the issue of insufficient medical training data. The proposed approach does not rely on hand-crafted features and needs no problem-specific preprocessing or postprocessing, which reduces the impact of subjective factors. We evaluate the proposed method on three publicly available databases, the DRIVE, STARE, and CHASE_DB1 databases. Extensive experiments demonstrate that our approach achieves better or comparable performance to state-of-the-art methods with a much faster processing speed, making it suitable for real-world clinical applications. The results of cross-training experiments demonstrate its robustness with respect to the training set. The proposed approach segments retinal vessels accurately with a much faster processing speed and can be easily applied to other biomedical segmentation tasks.

On the multi-level solution algorithm for Markov chains

Energy Technology Data Exchange (ETDEWEB)

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

1996-12-31

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

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

International Nuclear Information System (INIS)

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

2014-01-01

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

Resolution improvement and noise reduction in human pinhole SPECT using a multi-ray approach and the SHINE method

International Nuclear Information System (INIS)

Seret, A.; Vanhove, C.; Defrise, M.

2009-01-01

Purpose: This work aimed at quantifying the gains in spatial resolution and noise that could be achieved when using resolution modelling based on a multi-ray approach and additionally the Statistical and Heuristic Noise Extraction (SHINE) method in human pinhole single photon emission tomography (PH-SPECT). Methods: PH-SPECT of two line phantoms and one homogeneous cylinder were recorded using parameters suited for studies of the human neck area. They were reconstructed using pinhole dedicated ordered subsets expectation maximisation algorithm including a resolution recovery technique based on 7 or 21 rays. Optionally, the SPECT data were SHINE pre-processed. Transverse and axial full widths at half-maximum (FWHM) were obtained from the line phantoms. The noise was quantified using the coefficient of variation (COV) derived from the uniform phantom. Two human PH-SPECT studies of the thyroid (a hot nodule and a very low uptake) were processed with the same algorithms. Results: Depending on the number of iterations, FWHM decreased by 30 to 50% when using the multi-ray approach in the reconstruction process. The SHINE method did not affect the resolution but decreased the COV by at least 20% and by 45% when combined with the multi-ray method. The two human studies illustrated the gain in spatial resolution and the decrease in noise afforded both by the multi-ray reconstruction and the SHINE method. Conclusion: Iterative reconstruction with resolution modelling allows to obtain high resolution human PH-SPECT studies with reduced noise content. The SHINE method affords an additional noise reduction without compromising the resolution. (orig.)

HSA-based multi-target combination therapy: regulating drugs' release from HSA and overcoming single drug resistance in a breast cancer model.

Science.gov (United States)

Gou, Yi; Zhang, Zhenlei; Li, Dongyang; Zhao, Lei; Cai, Meiling; Sun, Zhewen; Li, Yongping; Zhang, Yao; Khan, Hamid; Sun, Hongbing; Wang, Tao; Liang, Hong; Yang, Feng

2018-11-01

Multi-drug delivery systems, which may be promising solution to overcome obstacles, have limited the clinical success of multi-drug combination therapies to treat cancer. To this end, we used three different anticancer agents, Cu(BpT)Br, NAMI-A, and doxorubicin (DOX), to build human serum albumin (HSA)-based multi-drug delivery systems in a breast cancer model to investigate the therapeutic efficacy of overcoming single drug (DOX) resistance to cancer cells in vivo, and to regulate the drugs' release from HSA. The HSA complex structure revealed that NAMI-A and Cu(BpT)Br bind to the IB and IIA sub-domain of HSA by N-donor residue replacing a leaving group and coordinating to their metal centers, respectively. The MALDI-TOF mass spectra demonstrated that one DOX molecule is conjugated with lysine of HSA by a pH-sensitive linker. Furthermore, the release behavior of three agents form HSA can be regulated at different pH levels. Importantly, in vivo results revealed that the HSA-NAMI-A-Cu(BpT)Br-DOX complex not only increases the targeting ability compared with a combination of the three agents (the NAMI-A/Cu(BpT)Br/DOX mixture), but it also overcomes DOX resistance to drug-resistant breast cancer cell lines.

Quality assurance in clinical trials : a multi-disciplinary approach

International Nuclear Information System (INIS)

Cornes, D.

2001-01-01

Full text: Multi-disciplinary groups, such as medical physicists and radiation therapists, which work effectively together, can ensure continued improvements in radiation therapy quality. The same is also true for clinical trials, which have the added complication of requiring multi-institutional participation to collate sufficient data to effectively assess treatment benefits. It can be difficult to manage quality across all aspects of a multi-disciplinary and multi-institutional trial. A planned system of quality assurance is necessary to provide support for participating centres and facilitate a collaborative approach. To ensure protocol compliance a good relationship between the clinical trial group and treatment centre is idea with definition of mutual goals and objectives before and during the trial, and ongoing consultation and feedback throughout the trial process. To ensure good quality data and maximise the validity of results the study protocol must be strictly adhered to. Because of the need for meticulous attention to detail, both in treatment delivery and standards of documentation, clinical trials are often seen to further complicate the process of delivery of radiation therapy treatment. The Declaration of Helsinki and Good Clinical Practise Guidelines (adopted in May 1996, ICH) provide 'international ethical and scientific standards for designing, conducting, recording and reporting clinical research' and multi-disciplinary groups in each participating centre should also adhere to these guidelines. Copyright (2001) Australasian College of Physical Scientists and Engineers in Medicine

Pruning techniques for multi-objective system-level design space exploration

NARCIS (Netherlands)

Piscitelli, R.

2014-01-01

System-level design space exploration (DSE), which is performed early in the design process, is of eminent importance to the design of complex multi-processor embedded system architectures. During system-level DSE, system parameters like, e.g., the number and type of processors, the type and size of

Multi-indication and Combination Pricing and Reimbursement of Pharmaceuticals: Opportunities for Improved Health Care through Faster Uptake of New Innovations.

Science.gov (United States)

Persson, Ulf; Norlin, J M

2018-04-01

Many pharmaceuticals are effective in multiple indications and the degree of effectiveness may differ. A product-based pricing and reimbursement system with a single price per product is insufficient to reflect the variable values between different indications. The objective of this article is to present examples of actual pricing and reimbursement decisions using current value-based pricing in Sweden and to discuss their implications and possible solutions. The value of several cancer drugs was estimated for various indications based on a willingness-to-pay threshold of 1 million SEK (EUR 104,000) per QALY gained. For some drugs, the estimated value was higher than the drug acquisition cost in several indications, whilst in others, the estimated value was lower than the drug acquisition cost. Drugs used in combination present a special case. If a drug prolongs survival and consequently also a continued use of the anchor drug, the combination use may not be cost effective even at a zero price. In a product-based pricing and reimbursement system, patients may not get access to drugs or access may be delayed and manufacturers may be discouraged to invest in future indications. To overcome these issues, there are several approaches to link price and value. One approach is a "weighted-average" price based on an average of the value across all indications. Another is "multi-indication pricing," which enables price differentiation between indications. However, there are several barriers for applying multi-indication pricing and reimbursement schemes. One barrier is the lack of existing administrative infrastructure to track patients' indications.

A combinatorial approach to multi-skill workforce scheduling

NARCIS (Netherlands)

Firat, M.; Hurkens, C.A.J.

2010-01-01

This paper deals with scheduling complex tasks with an inhomogeneous set of resources. The problem is to assign technicians to tasks with multi-level skill requirements. Here the requirements are merely the presence of a set of technicians that possess the necessary capabilities. An additional

Multi-level emulation of a volcanic ash transport and dispersion model to quantify sensitivity to uncertain parameters

Science.gov (United States)

Harvey, Natalie J.; Huntley, Nathan; Dacre, Helen F.; Goldstein, Michael; Thomson, David; Webster, Helen

2018-01-01

Following the disruption to European airspace caused by the eruption of Eyjafjallajökull in 2010 there has been a move towards producing quantitative predictions of volcanic ash concentration using volcanic ash transport and dispersion simulators. However, there is no formal framework for determining the uncertainties of these predictions and performing many simulations using these complex models is computationally expensive. In this paper a Bayesian linear emulation approach is applied to the Numerical Atmospheric-dispersion Modelling Environment (NAME) to better understand the influence of source and internal model parameters on the simulator output. Emulation is a statistical method for predicting the output of a computer simulator at new parameter choices without actually running the simulator. A multi-level emulation approach is applied using two configurations of NAME with different numbers of model particles. Information from many evaluations of the computationally faster configuration is combined with results from relatively few evaluations of the slower, more accurate, configuration. This approach is effective when it is not possible to run the accurate simulator many times and when there is also little prior knowledge about the influence of parameters. The approach is applied to the mean ash column loading in 75 geographical regions on 14 May 2010. Through this analysis it has been found that the parameters that contribute the most to the output uncertainty are initial plume rise height, mass eruption rate, free tropospheric turbulence levels and precipitation threshold for wet deposition. This information can be used to inform future model development and observational campaigns and routine monitoring. The analysis presented here suggests the need for further observational and theoretical research into parameterisation of atmospheric turbulence. Furthermore it can also be used to inform the most important parameter perturbations for a small operational

Multi-Level Bitmap Indexes for Flash Memory Storage

Energy Technology Data Exchange (ETDEWEB)

Wu, Kesheng; Madduri, Kamesh; Canon, Shane

2010-07-23

Due to their low access latency, high read speed, and power-efficient operation, flash memory storage devices are rapidly emerging as an attractive alternative to traditional magnetic storage devices. However, tests show that the most efficient indexing methods are not able to take advantage of the flash memory storage devices. In this paper, we present a set of multi-level bitmap indexes that can effectively take advantage of flash storage devices. These indexing methods use coarsely binned indexes to answer queries approximately, and then use finely binned indexes to refine the answers. Our new methods read significantly lower volumes of data at the expense of an increased disk access count, thus taking full advantage of the improved read speed and low access latency of flash devices. To demonstrate the advantage of these new indexes, we measure their performance on a number of storage systems using a standard data warehousing benchmark called the Set Query Benchmark. We observe that multi-level strategies on flash drives are up to 3 times faster than traditional indexing strategies on magnetic disk drives.

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

International Nuclear Information System (INIS)

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

2017-01-01

would be treated via CWT facilities in the Marcellus, while most of the wastewater generated from the drilling, fracturing and production operations would be treated via underground injection control wells in the other shale plays. Moreover, the performance of the MGU-MEM-MWL model is enhanced by comparing with the three bi-level programs and the multi-objective approach. Results demonstrate that the MGU-MEM-MWL decisions would provide much comprehensive and systematic policies when considering the hierarchical structure within the shale-gas system.

Quantification of mold contamination in multi-level buildings using the Environmental Relative Moldiness Index

Science.gov (United States)

The goal of this study was to evaluate the possible use of the Environmental Relative Moldiness Index (ERMI) to quantify mold contamination in multi-level, office buildings. Settled-dust samples were collected in multi-level, office buildings and the ERMI value for each sample de...

Chinese Medical Question Answer Matching Using End-to-End Character-Level Multi-Scale CNNs

Directory of Open Access Journals (Sweden)

Sheng Zhang

2017-07-01

Full Text Available This paper focuses mainly on the problem of Chinese medical question answer matching, which is arguably more challenging than open-domain question answer matching in English due to the combination of its domain-restricted nature and the language-specific features of Chinese. We present an end-to-end character-level multi-scale convolutional neural framework in which character embeddings instead of word embeddings are used to avoid Chinese word segmentation in text preprocessing, and multi-scale convolutional neural networks (CNNs are then introduced to extract contextual information from either question or answer sentences over different scales. The proposed framework can be trained with minimal human supervision and does not require any handcrafted features, rule-based patterns, or external resources. To validate our framework, we create a new text corpus, named cMedQA, by harvesting questions and answers from an online Chinese health and wellness community. The experimental results on the cMedQA dataset show that our framework significantly outperforms several strong baselines, and achieves an improvement of top-1 accuracy by up to 19%.

Multi-level tree analysis of pulmonary artery/vein trees in non-contrast CT images

Science.gov (United States)

Gao, Zhiyun; Grout, Randall W.; Hoffman, Eric A.; Saha, Punam K.

2012-02-01

Diseases like pulmonary embolism and pulmonary hypertension are associated with vascular dystrophy. Identifying such pulmonary artery/vein (A/V) tree dystrophy in terms of quantitative measures via CT imaging significantly facilitates early detection of disease or a treatment monitoring process. A tree structure, consisting of nodes and connected arcs, linked to the volumetric representation allows multi-level geometric and volumetric analysis of A/V trees. Here, a new theory and method is presented to generate multi-level A/V tree representation of volumetric data and to compute quantitative measures of A/V tree geometry and topology at various tree hierarchies. The new method is primarily designed on arc skeleton computation followed by a tree construction based topologic and geometric analysis of the skeleton. The method starts with a volumetric A/V representation as input and generates its topologic and multi-level volumetric tree representations long with different multi-level morphometric measures. A new recursive merging and pruning algorithms are introduced to detect bad junctions and noisy branches often associated with digital geometric and topologic analysis. Also, a new notion of shortest axial path is introduced to improve the skeletal arc joining two junctions. The accuracy of the multi-level tree analysis algorithm has been evaluated using computer generated phantoms and pulmonary CT images of a pig vessel cast phantom while the reproducibility of method is evaluated using multi-user A/V separation of in vivo contrast-enhanced CT images of a pig lung at different respiratory volumes.

Multi-modal Social Networks: A MRF Learning Approach

Science.gov (United States)

2016-06-20

Network forensics: random infection vs spreading epidemic , Proceedings of ACM Sigmetrics. 11-JUN-12, London, UK. : , TOTAL: 4 06/09/2016 Received Paper...Multi-modal Social Networks A MRF Learning Approach The work primarily focused on two lines of research. 1. We propose new greedy algorithms...Box 12211 Research Triangle Park, NC 27709-2211 social networks , learning and inference REPORT DOCUMENTATION PAGE 11. SPONSOR/MONITOR’S REPORT

Tomographic Reconstruction from a Few Views: A Multi-Marginal Optimal Transport Approach

Energy Technology Data Exchange (ETDEWEB)

Abraham, I., E-mail: isabelle.abraham@cea.fr [CEA Ile de France (France); Abraham, R., E-mail: romain.abraham@univ-orleans.fr; Bergounioux, M., E-mail: maitine.bergounioux@univ-orleans.fr [Université d’Orléans, UFR Sciences, MAPMO, UMR 7349 (France); Carlier, G., E-mail: carlier@ceremade.dauphine.fr [CEREMADE, UMR CNRS 7534, Université Paris IX Dauphine, Pl. de Lattre de Tassigny (France)

2017-02-15

In this article, we focus on tomographic reconstruction. The problem is to determine the shape of the interior interface using a tomographic approach while very few X-ray radiographs are performed. We use a multi-marginal optimal transport approach. Preliminary numerical results are presented.

Topological structures of adiabatic phase for multi-level quantum systems

International Nuclear Information System (INIS)

Liu Zhengxin; Zhou Xiaoting; Liu Xin; Liu Xiongjun; Chen Jingling

2007-01-01

The topological properties of adiabatic gauge fields for multi-level (three-level in particular) quantum systems are studied in detail. Similar to the result that the adiabatic gauge field for SU(2) systems (e.g. two-level quantum system or angular momentum systems, etc) has a monopole structure, the curvature 2-forms of the adiabatic holonomies for SU(3) three-level and SU(3) eight-level quantum systems are shown to have monopole-like (for all levels) or instanton-like (for the degenerate levels) structures

Multilevel probabilistic approach to evaluate manufacturing defect in composite aircraft structures

International Nuclear Information System (INIS)

Caracciolo, Paola

2014-01-01

In this work it is developed a reliable approach and its feasibility to the design and analysis of a composite structures. The metric is compared the robustness and reliability designs versus the traditional design, to demonstrate the gain that can be achieved with a probabilistic approach. The use of the stochastic approach of the uncertain parameteters in combination with the multi-scale levels analysis is the main objective of this paper. The work is dedicated to analyze the uncertainties in the design, tests, manufacturing process, and key gates such as materials characteristic

Multilevel probabilistic approach to evaluate manufacturing defect in composite aircraft structures

Energy Technology Data Exchange (ETDEWEB)

Caracciolo, Paola, E-mail: paola.caracciolo@airbus.com [AIRBUS INDUSTRIES Germany, Department of Airframe Architecture and Integration-Research and Technology-Kreetslag, 10, D-21129, Hamburg (Germany)

2014-05-15

In this work it is developed a reliable approach and its feasibility to the design and analysis of a composite structures. The metric is compared the robustness and reliability designs versus the traditional design, to demonstrate the gain that can be achieved with a probabilistic approach. The use of the stochastic approach of the uncertain parameteters in combination with the multi-scale levels analysis is the main objective of this paper. The work is dedicated to analyze the uncertainties in the design, tests, manufacturing process, and key gates such as materials characteristic.

Simple Multi-level Microchannel Fabrication by Pseudo-Grayscale Backside Diffused Light Lithography.

Science.gov (United States)

Lai, David; Labuz, Joseph M; Kim, Jiwon; Luker, Gary D; Shikanov, Ariella; Takayama, Shuichi

2013-11-14

Photolithography of multi-level channel features in microfluidics is laborious and/or costly. Grayscale photolithography is mostly used with positive photoresists and conventional front side exposure, but the grayscale masks needed are generally costly and positive photoresists are not commonly used in microfluidic rapid prototyping. Here we introduce a simple and inexpensive alternative that uses pseudo-grayscale (pGS) photomasks in combination with backside diffused light lithography (BDLL) and the commonly used negative photoresist, SU-8. BDLL can produce smooth multi-level channels of gradually changing heights without use of true grayscale masks because of the use of diffused light. Since the exposure is done through a glass slide, the photoresist is cross-linked from the substrate side up enabling well-defined and stable structures to be fabricated from even unspun photoresist layers. In addition to providing unique structures and capabilities, the method is compatible with the "garage microfluidics" concept of creating useful tools at low cost since pGS BDLL can be performed with the use of only hot plates and a UV transilluminator: equipment commonly found in biology labs. Expensive spin coaters or collimated UV aligners are not needed. To demonstrate the applicability of pGS BDLL, a variety of weir-type cell traps were constructed with a single UV exposure to separate cancer cells (MDA-MB-231, 10-15 μm in size) from red blood cells (RBCs, 2-8 μm in size) as well as follicle clusters (40-50 μm in size) from cancer cells (MDA-MB-231, 10-15 μm in size).

A combined telemetry - tag return approach to estimate fishing and natural mortality rates of an estuarine fish

Science.gov (United States)

Bacheler, N.M.; Buckel, J.A.; Hightower, J.E.; Paramore, L.M.; Pollock, K.H.

2009-01-01

A joint analysis of tag return and telemetry data should improve estimates of mortality rates for exploited fishes; however, the combined approach has thus far only been tested in terrestrial systems. We tagged subadult red drum (Sciaenops ocellatus) with conventional tags and ultrasonic transmitters over 3 years in coastal North Carolina, USA, to test the efficacy of the combined telemetry - tag return approach. There was a strong seasonal pattern to monthly fishing mortality rate (F) estimates from both conventional and telemetry tags; highest F values occurred in fall months and lowest levels occurred during winter. Although monthly F values were similar in pattern and magnitude between conventional tagging and telemetry, information on F in the combined model came primarily from conventional tags. The estimated natural mortality rate (M) in the combined model was low (estimated annual rate ?? standard error: 0.04 ?? 0.04) and was based primarily upon the telemetry approach. Using high-reward tagging, we estimated different tag reporting rates for state agency and university tagging programs. The combined telemetry - tag return approach can be an effective approach for estimating F and M as long as several key assumptions of the model are met.

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

Science.gov (United States)

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

2014-01-01

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

space vector pulse width modulation of a multi-level diode clamped

African Journals Online (AJOL)

ES Obe

step by step development of MATLAB /SIMULINK modeling of the space vector ..... Pulse Width Mod. of Multi-Level Diode Clamped Converter 119 powergui. Discrete, .... Load. Figure 22: Block diagram of the three level DCC design. 3 LEVEL ...

Achieving strategic renewal: the multi-level influences of top and middle managers’ boundary-spanning

NARCIS (Netherlands)

Glaser, L.; Fourne, S.P.L.; Elfring, T.

2015-01-01

Drawing on corporate entrepreneurship (CE) and social network research, this study focuses on strategic renewal as a form of CE and examines the impact of boundary-spanning at top and middle management levels on business units’ exploratory innovation. Analyses of multi-source and multi-level data,