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Sample records for model hmm framework

  1. HMM-based Trust Model

    DEFF Research Database (Denmark)

    ElSalamouny, Ehab; Nielsen, Mogens; Sassone, Vladimiro

    2010-01-01

    Probabilistic trust has been adopted as an approach to taking security sensitive decisions in modern global computing environments. Existing probabilistic trust frameworks either assume fixed behaviour for the principals or incorporate the notion of ‘decay' as an ad hoc approach to cope...... with their dynamic behaviour. Using Hidden Markov Models (HMMs) for both modelling and approximating the behaviours of principals, we introduce the HMM-based trust model as a new approach to evaluating trust in systems exhibiting dynamic behaviour. This model avoids the fixed behaviour assumption which is considered...... the major limitation of existing Beta trust model. We show the consistency of the HMM-based trust model and contrast it against the well known Beta trust model with the decay principle in terms of the estimation precision....

  2. Hidden Neural Networks: A Framework for HMM/NN Hybrids

    DEFF Research Database (Denmark)

    Riis, Søren Kamaric; Krogh, Anders Stærmose

    1997-01-01

    This paper presents a general framework for hybrids of hidden Markov models (HMM) and neural networks (NN). In the new framework called hidden neural networks (HNN) the usual HMM probability parameters are replaced by neural network outputs. To ensure a probabilistic interpretation the HNN is nor...... HMMs on TIMIT continuous speech recognition benchmarks. On the task of recognizing five broad phoneme classes an accuracy of 84% is obtained compared to 76% for a standard HMM. Additionally, we report a preliminary result of 69% accuracy on the TIMIT 39 phoneme task...

  3. An HMM-based comparative genomic framework for detecting introgression in eukaryotes.

    Directory of Open Access Journals (Sweden)

    Kevin J Liu

    2014-06-01

    Full Text Available One outcome of interspecific hybridization and subsequent effects of evolutionary forces is introgression, which is the integration of genetic material from one species into the genome of an individual in another species. The evolution of several groups of eukaryotic species has involved hybridization, and cases of adaptation through introgression have been already established. In this work, we report on PhyloNet-HMM-a new comparative genomic framework for detecting introgression in genomes. PhyloNet-HMM combines phylogenetic networks with hidden Markov models (HMMs to simultaneously capture the (potentially reticulate evolutionary history of the genomes and dependencies within genomes. A novel aspect of our work is that it also accounts for incomplete lineage sorting and dependence across loci. Application of our model to variation data from chromosome 7 in the mouse (Mus musculus domesticus genome detected a recently reported adaptive introgression event involving the rodent poison resistance gene Vkorc1, in addition to other newly detected introgressed genomic regions. Based on our analysis, it is estimated that about 9% of all sites within chromosome 7 are of introgressive origin (these cover about 13 Mbp of chromosome 7, and over 300 genes. Further, our model detected no introgression in a negative control data set. We also found that our model accurately detected introgression and other evolutionary processes from synthetic data sets simulated under the coalescent model with recombination, isolation, and migration. Our work provides a powerful framework for systematic analysis of introgression while simultaneously accounting for dependence across sites, point mutations, recombination, and ancestral polymorphism.

  4. HMM_Model-Checker pour la vérification probabiliste HMM_Model ...

    African Journals Online (AJOL)

    ASSIA

    probabiliste –Télescope Hubble. Abstract. Probabilistic verification for embedded systems continues to attract more and more followers in the research community. Given a probabilistic model, a formula of temporal logic, describing a property of a system and an exploration algorithm to check whether the property is satisfied ...

  5. Study on solitary word based on HMM model and Baum-Welch algorithm

    Directory of Open Access Journals (Sweden)

    Junxia CHEN

    Full Text Available This paper introduces the principle of Hidden Markov Model, which is used to describe the Markov process with unknown parameters, is a probability model to describe the statistical properties of the random process. On this basis, designed a solitary word detection experiment based on HMM model, by optimizing the experimental model, Using Baum-Welch algorithm for training the problem of solving the HMM model, HMM model to estimate the parameters of the λ value is found, in this view of mathematics equivalent to other linear prediction coefficient. This experiment in reducing unnecessary HMM training at the same time, reduced the algorithm complexity. In order to test the effectiveness of the Baum-Welch algorithm, The simulation of experimental data, the results show that the algorithm is effective.

  6. Speech-To-Text Conversion STT System Using Hidden Markov Model HMM

    Directory of Open Access Journals (Sweden)

    Su Myat Mon

    2015-06-01

    Full Text Available Abstract Speech is an easiest way to communicate with each other. Speech processing is widely used in many applications like security devices household appliances cellular phones ATM machines and computers. The human computer interface has been developed to communicate or interact conveniently for one who is suffering from some kind of disabilities. Speech-to-Text Conversion STT systems have a lot of benefits for the deaf or dumb people and find their applications in our daily lives. In the same way the aim of the system is to convert the input speech signals into the text output for the deaf or dumb students in the educational fields. This paper presents an approach to extract features by using Mel Frequency Cepstral Coefficients MFCC from the speech signals of isolated spoken words. And Hidden Markov Model HMM method is applied to train and test the audio files to get the recognized spoken word. The speech database is created by using MATLAB.Then the original speech signals are preprocessed and these speech samples are extracted to the feature vectors which are used as the observation sequences of the Hidden Markov Model HMM recognizer. The feature vectors are analyzed in the HMM depending on the number of states.

  7. Accelerated Profile HMM Searches.

    Directory of Open Access Journals (Sweden)

    Sean R Eddy

    2011-10-01

    Full Text Available Profile hidden Markov models (profile HMMs and probabilistic inference methods have made important contributions to the theory of sequence database homology search. However, practical use of profile HMM methods has been hindered by the computational expense of existing software implementations. Here I describe an acceleration heuristic for profile HMMs, the "multiple segment Viterbi" (MSV algorithm. The MSV algorithm computes an optimal sum of multiple ungapped local alignment segments using a striped vector-parallel approach previously described for fast Smith/Waterman alignment. MSV scores follow the same statistical distribution as gapped optimal local alignment scores, allowing rapid evaluation of significance of an MSV score and thus facilitating its use as a heuristic filter. I also describe a 20-fold acceleration of the standard profile HMM Forward/Backward algorithms using a method I call "sparse rescaling". These methods are assembled in a pipeline in which high-scoring MSV hits are passed on for reanalysis with the full HMM Forward/Backward algorithm. This accelerated pipeline is implemented in the freely available HMMER3 software package. Performance benchmarks show that the use of the heuristic MSV filter sacrifices negligible sensitivity compared to unaccelerated profile HMM searches. HMMER3 is substantially more sensitive and 100- to 1000-fold faster than HMMER2. HMMER3 is now about as fast as BLAST for protein searches.

  8. HMM Adaptation for child speech synthesis

    CSIR Research Space (South Africa)

    Govender, Avashna

    2015-09-01

    Full Text Available Hidden Markov Model (HMM)-based synthesis in combination with speaker adaptation has proven to be an approach that is well-suited for child speech synthesis. This paper describes the development and evaluation of different HMM-based child speech...

  9. HMM-ModE – Improved classification using profile hidden Markov models by optimising the discrimination threshold and modifying emission probabilities with negative training sequences

    Directory of Open Access Journals (Sweden)

    Nandi Soumyadeep

    2007-03-01

    Full Text Available Abstract Background Profile Hidden Markov Models (HMM are statistical representations of protein families derived from patterns of sequence conservation in multiple alignments and have been used in identifying remote homologues with considerable success. These conservation patterns arise from fold specific signals, shared across multiple families, and function specific signals unique to the families. The availability of sequences pre-classified according to their function permits the use of negative training sequences to improve the specificity of the HMM, both by optimizing the threshold cutoff and by modifying emission probabilities to minimize the influence of fold-specific signals. A protocol to generate family specific HMMs is described that first constructs a profile HMM from an alignment of the family's sequences and then uses this model to identify sequences belonging to other classes that score above the default threshold (false positives. Ten-fold cross validation is used to optimise the discrimination threshold score for the model. The advent of fast multiple alignment methods enables the use of the profile alignments to align the true and false positive sequences, and the resulting alignments are used to modify the emission probabilities in the original model. Results The protocol, called HMM-ModE, was validated on a set of sequences belonging to six sub-families of the AGC family of kinases. These sequences have an average sequence similarity of 63% among the group though each sub-group has a different substrate specificity. The optimisation of discrimination threshold, by using negative sequences scored against the model improves specificity in test cases from an average of 21% to 98%. Further discrimination by the HMM after modifying model probabilities using negative training sequences is provided in a few cases, the average specificity rising to 99%. Similar improvements were obtained with a sample of G-Protein coupled receptors

  10. A stochastic HMM-based forecasting model for fuzzy time series.

    Science.gov (United States)

    Li, Sheng-Tun; Cheng, Yi-Chung

    2010-10-01

    Recently, fuzzy time series have attracted more academic attention than traditional time series due to their capability of dealing with the uncertainty and vagueness inherent in the data collected. The formulation of fuzzy relations is one of the key issues affecting forecasting results. Most of the present works adopt IF-THEN rules for relationship representation, which leads to higher computational overhead and rule redundancy. Sullivan and Woodall proposed a Markov-based formulation and a forecasting model to reduce computational overhead; however, its applicability is limited to handling one-factor problems. In this paper, we propose a novel forecasting model based on the hidden Markov model by enhancing Sullivan and Woodall's work to allow handling of two-factor forecasting problems. Moreover, in order to make the nature of conjecture and randomness of forecasting more realistic, the Monte Carlo method is adopted to estimate the outcome. To test the effectiveness of the resulting stochastic model, we conduct two experiments and compare the results with those from other models. The first experiment consists of forecasting the daily average temperature and cloud density in Taipei, Taiwan, and the second experiment is based on the Taiwan Weighted Stock Index by forecasting the exchange rate of the New Taiwan dollar against the U.S. dollar. In addition to improving forecasting accuracy, the proposed model adheres to the central limit theorem, and thus, the result statistically approximates to the real mean of the target value being forecast.

  11. HMM filtering and parameter estimation of an electricity spot price model

    International Nuclear Information System (INIS)

    Erlwein, Christina; Benth, Fred Espen; Mamon, Rogemar

    2010-01-01

    In this paper we develop a model for electricity spot price dynamics. The spot price is assumed to follow an exponential Ornstein-Uhlenbeck (OU) process with an added compound Poisson process. In this way, the model allows for mean-reversion and possible jumps. All parameters are modulated by a hidden Markov chain in discrete time. They are able to switch between different economic regimes representing the interaction of various factors. Through the application of reference probability technique, adaptive filters are derived, which in turn, provide optimal estimates for the state of the Markov chain and related quantities of the observation process. The EM algorithm is applied to find optimal estimates of the model parameters in terms of the recursive filters. We implement this self-calibrating model on a deseasonalised series of daily spot electricity prices from the Nordic exchange Nord Pool. On the basis of one-step ahead forecasts, we found that the model is able to capture the empirical characteristics of Nord Pool spot prices. (author)

  12. A Framework for Bioacoustic Vocalization Analysis Using Hidden Markov Models

    Directory of Open Access Journals (Sweden)

    Ebenezer Out-Nyarko

    2009-11-01

    Full Text Available Using Hidden Markov Models (HMMs as a recognition framework for automatic classification of animal vocalizations has a number of benefits, including the ability to handle duration variability through nonlinear time alignment, the ability to incorporate complex language or recognition constraints, and easy extendibility to continuous recognition and detection domains. In this work, we apply HMMs to several different species and bioacoustic tasks using generalized spectral features that can be easily adjusted across species and HMM network topologies suited to each task. This experimental work includes a simple call type classification task using one HMM per vocalization for repertoire analysis of Asian elephants, a language-constrained song recognition task using syllable models as base units for ortolan bunting vocalizations, and a stress stimulus differentiation task in poultry vocalizations using a non-sequential model via a one-state HMM with Gaussian mixtures. Results show strong performance across all tasks and illustrate the flexibility of the HMM framework for a variety of species, vocalization types, and analysis tasks.

  13. HMM Logos for visualization of protein families

    Directory of Open Access Journals (Sweden)

    Schultz Jörg

    2004-01-01

    Full Text Available Abstract Background Profile Hidden Markov Models (pHMMs are a widely used tool for protein family research. Up to now, however, there exists no method to visualize all of their central aspects graphically in an intuitively understandable way. Results We present a visualization method that incorporates both emission and transition probabilities of the pHMM, thus extending sequence logos introduced by Schneider and Stephens. For each emitting state of the pHMM, we display a stack of letters. The stack height is determined by the deviation of the position's letter emission frequencies from the background frequencies. The stack width visualizes both the probability of reaching the state (the hitting probability and the expected number of letters the state emits during a pass through the model (the state's expected contribution. A web interface offering online creation of HMM Logos and the corresponding source code can be found at the Logos web server of the Max Planck Institute for Molecular Genetics http://logos.molgen.mpg.de. Conclusions We demonstrate that HMM Logos can be a useful tool for the biologist: We use them to highlight differences between two homologous subfamilies of GTPases, Rab and Ras, and we show that they are able to indicate structural elements of Ras.

  14. Comparison of HMM experts with MLP experts in the Full Combination Multi-Band Approach to Robust ASR

    OpenAIRE

    Hagen, Astrid; Morris, Andrew

    2000-01-01

    In this paper we apply the Full Combination (FC) multi-band approach, which has originally been introduced in the framework of posterior-based HMM/ANN (Hidden Markov Model/Artificial Neural Network) hybrid systems, to systems in which the ANN (or Multilayer Perceptron (MLP)) is itself replaced by a Multi Gaussian HMM (MGM). Both systems represent the most widely used statistical models for robust ASR (automatic speech recognition). It is shown how the FC formula for the likelihood--based MGMs...

  15. Efficient Blind System Identification of Non-Gaussian Auto-Regressive Models with HMM Modeling of the Excitation

    DEFF Research Database (Denmark)

    Li, Chunjian; Andersen, Søren Vang

    2007-01-01

    We propose two blind system identification methods that exploit the underlying dynamics of non-Gaussian signals. The two signal models to be identified are: an Auto-Regressive (AR) model driven by a discrete-state Hidden Markov process, and the same model whose output is perturbed by white Gaussi...... outputs. The signal models are general and suitable to numerous important signals, such as speech signals and base-band communication signals. Applications to speech analysis and blind channel equalization are given to exemplify the efficiency of the new methods....

  16. An HMM-Like Dynamic Time Warping Scheme for Automatic Speech Recognition

    Directory of Open Access Journals (Sweden)

    Ing-Jr Ding

    2014-01-01

    Full Text Available In the past, the kernel of automatic speech recognition (ASR is dynamic time warping (DTW, which is feature-based template matching and belongs to the category technique of dynamic programming (DP. Although DTW is an early developed ASR technique, DTW has been popular in lots of applications. DTW is playing an important role for the known Kinect-based gesture recognition application now. This paper proposed an intelligent speech recognition system using an improved DTW approach for multimedia and home automation services. The improved DTW presented in this work, called HMM-like DTW, is essentially a hidden Markov model- (HMM- like method where the concept of the typical HMM statistical model is brought into the design of DTW. The developed HMM-like DTW method, transforming feature-based DTW recognition into model-based DTW recognition, will be able to behave as the HMM recognition technique and therefore proposed HMM-like DTW with the HMM-like recognition model will have the capability to further perform model adaptation (also known as speaker adaptation. A series of experimental results in home automation-based multimedia access service environments demonstrated the superiority and effectiveness of the developed smart speech recognition system by HMM-like DTW.

  17. Metode Linear Predictive Coding (LPC Pada klasifikasi Hidden Markov Model (HMM Untuk Kata Arabic pada penutur Indonesia

    Directory of Open Access Journals (Sweden)

    Ririn Kusumawati

    2016-05-01

    In the classification, using Hidden Markov Model, voice signal is analyzed and searched the maximum possible value that can be recognized. The modeling results obtained parameters are used to compare with the sound of Arabic speakers. From the test results' Classification, Hidden Markov Models with Linear Predictive Coding extraction average accuracy of 78.6% for test data sampling frequency of 8,000 Hz, 80.2% for test data sampling frequency of 22050 Hz, 79% for frequencies sampling test data at 44100 Hz.

  18. AdOn HDP-HMM: An Adaptive Online Model for Segmentation and Classification of Sequential Data.

    Science.gov (United States)

    Bargi, Ava; Xu, Richard Yi Da; Piccardi, Massimo

    2017-09-21

    Recent years have witnessed an increasing need for the automated classification of sequential data, such as activities of daily living, social media interactions, financial series, and others. With the continuous flow of new data, it is critical to classify the observations on-the-fly and without being limited by a predetermined number of classes. In addition, a model should be able to update its parameters in response to a possible evolution in the distributions of the classes. This compelling problem, however, does not seem to have been adequately addressed in the literature, since most studies focus on offline classification over predefined class sets. In this paper, we present a principled solution for this problem based on an adaptive online system leveraging Markov switching models and hierarchical Dirichlet process priors. This adaptive online approach is capable of classifying the sequential data over an unlimited number of classes while meeting the memory and delay constraints typical of streaming contexts. In this paper, we introduce an adaptive ''learning rate'' that is responsible for balancing the extent to which the model retains its previous parameters or adapts to new observations. Experimental results on stationary and evolving synthetic data and two video data sets, TUM Assistive Kitchen and collated Weizmann, show a remarkable performance in terms of segmentation and classification, particularly for sequences from evolutionary distributions and/or those containing previously unseen classes.

  19. Effect of HMM Glutenin Subunits on Wheat Quality Attributes

    Directory of Open Access Journals (Sweden)

    Daniela Horvat

    2009-01-01

    Full Text Available Glutenin is a group of polymeric gluten proteins. Glutenin molecules consist of glutenin subunits linked together with disulphide bonds and having higher (HMM-GS and lower (LMM-GS molecular mass. The main objective of this study is the evaluation of the influence of HMM-GS on flour processing properties. Seven bread wheat genotypes with contrasting quality attributes and different HMM-GS composition were analyzed during three years. The composition and quantity of HMM-GS were determined by SDS-PAGE and RP-HPLC, respectively. The quality diversity among genotypes was estimated by the analysis of wheat grain, and flour and bread quality parameters. The presence of HMM glutenin subunits 1 and 2* at Glu-A1 and the subunits 5+10 at Glu-D1 loci, as well as a higher proportion of total HMM-GS, had a positive effect on wheat quality. Cluster analysis of the three groups of data (genotype and HMM-GS, flour and bread quality, and dough rheology yielded the same hierarchical structure for the first top three levels, and similarity of the corresponding dendrograms was proved by the principal eigenvalues of the corresponding Euclidian distance matrices. The obtained similarity in classification based on essentially different types of measurements reflects strong natural association between genetic data, product quality and physical properties. Principal component analysis (PCA was applied to effectively reduce large data set into lower dimensions of latent variables amenable for the analysis. PCA analysis of the total set of data (15 variables revealed a very strong interrelationship between the variables. The first three PCA components accounted for 96 % of the total variance, which was significant to the level of 0.05 and was considered as the level of experimental error. These data imply that the quality of wheat cultivars can be contributed to HMM-GS data and should be taken into account in breeding programs assisted by computer models with the aim to

  20. Important factors in HMM-based phonetic segmentation

    CSIR Research Space (South Africa)

    Van Niekerk, DR

    2007-11-01

    Full Text Available , window and step sizes. Taking into account that the segmentation system trains and applies the HMM models on a single speaker only, our first con- cern was the applicability of the window and step sizes that are commonly used for speech recognition...

  1. Appropriate baseline values for HMM-based speech recognition

    CSIR Research Space (South Africa)

    Barnard, E

    2004-11-01

    Full Text Available A number of issues realted to the development of speech-recognition systems with Hidden Markov Models (HMM) are discussed. A set of systematic experiments using the HTK toolkit and the TMIT database are used to elucidate matters such as the number...

  2. Cluster-Based Adaptation Using Density Forest for HMM Phone Recognition

    DEFF Research Database (Denmark)

    Abou-Zleikha, Mohamed; Tan, Zheng-Hua; Christensen, Mads Græsbøll

    2014-01-01

    The dissimilarity between the training and test data in speech recognition systems is known to have a considerable effect on the recognition accuracy. To solve this problem, we use density forest to cluster the data and use maximum a posteriori (MAP) method to build a cluster-based adapted Gaussian...... mixture models (GMMs) in HMM speech recognition. Specifically, a set of bagged versions of the training data for each state in the HMM is generated, and each of these versions is used to generate one GMM and one tree in the density forest. Thereafter, an acoustic model forest is built by replacing...... the data of each leaf (cluster) in each tree with the corresponding GMM adapted by the leaf data using the MAP method. The results show that the proposed approach achieves 3:8% (absolute) lower phone error rate compared with the standard HMM/GMM and 0:8% (absolute) lower PER compared with bagged HMM/GMM....

  3. HMM based automated wheelchair navigation using EOG traces in EEG

    Science.gov (United States)

    Aziz, Fayeem; Arof, Hamzah; Mokhtar, Norrima; Mubin, Marizan

    2014-10-01

    This paper presents a wheelchair navigation system based on a hidden Markov model (HMM), which we developed to assist those with restricted mobility. The semi-autonomous system is equipped with obstacle/collision avoidance sensors and it takes the electrooculography (EOG) signal traces from the user as commands to maneuver the wheelchair. The EOG traces originate from eyeball and eyelid movements and they are embedded in EEG signals collected from the scalp of the user at three different locations. Features extracted from the EOG traces are used to determine whether the eyes are open or closed, and whether the eyes are gazing to the right, center, or left. These features are utilized as inputs to a few support vector machine (SVM) classifiers, whose outputs are regarded as observations to an HMM. The HMM determines the state of the system and generates commands for navigating the wheelchair accordingly. The use of simple features and the implementation of a sliding window that captures important signatures in the EOG traces result in a fast execution time and high classification rates. The wheelchair is equipped with a proximity sensor and it can move forward and backward in three directions. The asynchronous system achieved an average classification rate of 98% when tested with online data while its average execution time was less than 1 s. It was also tested in a navigation experiment where all of the participants managed to complete the tasks successfully without collisions.

  4. An HMM posterior decoder for sequence feature prediction that includes homology information

    DEFF Research Database (Denmark)

    Käll, Lukas; Krogh, Anders Stærmose; Sonnhammer, Erik L. L.

    2005-01-01

    Motivation: When predicting sequence features like transmembrane topology, signal peptides, coil-coil structures, protein secondary structure or genes, extra support can be gained from homologs. Results: We present here a general hidden Markov model (HMM) decoding algorithm that combines probabil......Motivation: When predicting sequence features like transmembrane topology, signal peptides, coil-coil structures, protein secondary structure or genes, extra support can be gained from homologs. Results: We present here a general hidden Markov model (HMM) decoding algorithm that combines......://phobius.cgb.ki.se/poly.html . An implementation of the algorithm is available on request from the authors....

  5. Explorations in the History of Machines and Mechanisms : Proceedings of HMM2012

    CERN Document Server

    Ceccarelli, Marco

    2012-01-01

    This book contains the proceedings of HMM2012, the 4th International Symposium on Historical Developments in the field of Mechanism and Machine Science (MMS). These proceedings cover recent research concerning all aspects of the development of MMS from antiquity until the present and its historiography: machines, mechanisms, kinematics, dynamics, concepts and theories, design methods, collections of methods, collections of models, institutions and biographies.

  6. Objective measures to improve the selection of training speakers in HMM-based child speech synthesis

    CSIR Research Space (South Africa)

    Govender, Avashna

    2016-12-01

    Full Text Available Building synthetic child voices is considered a difficult task due to the challenges associated with data collection. As a result, speaker adaptation in conjunction with Hidden Markov Model (HMM)-based synthesis has become prevalent in this domain...

  7. Hidden Markov model approach for identifying the modular framework of the protein backbone.

    Science.gov (United States)

    Camproux, A C; Tuffery, P; Chevrolat, J P; Boisvieux, J F; Hazout, S

    1999-12-01

    The hidden Markov model (HMM) was used to identify recurrent short 3D structural building blocks (SBBs) describing protein backbones, independently of any a priori knowledge. Polypeptide chains are decomposed into a series of short segments defined by their inter-alpha-carbon distances. Basically, the model takes into account the sequentiality of the observed segments and assumes that each one corresponds to one of several possible SBBs. Fitting the model to a database of non-redundant proteins allowed us to decode proteins in terms of 12 distinct SBBs with different roles in protein structure. Some SBBs correspond to classical regular secondary structures. Others correspond to a significant subdivision of their bounding regions previously considered to be a single pattern. The major contribution of the HMM is that this model implicitly takes into account the sequential connections between SBBs and thus describes the most probable pathways by which the blocks are connected to form the framework of the protein structures. Validation of the SBBs code was performed by extracting SBB series repeated in recoding proteins and examining their structural similarities. Preliminary results on the sequence specificity of SBBs suggest promising perspectives for the prediction of SBBs or series of SBBs from the protein sequences.

  8. Geologic Framework Model (GFM2000)

    International Nuclear Information System (INIS)

    T. Vogt

    2004-01-01

    The purpose of this report is to document the geologic framework model, version GFM2000 with regard to input data, modeling methods, assumptions, uncertainties, limitations, and validation of the model results, and the differences between GFM2000 and previous versions. The version number of this model reflects the year during which the model was constructed. This model supersedes the previous model version, documented in Geologic Framework Model (GFM 3.1) (CRWMS M and O 2000 [DIRS 138860]). The geologic framework model represents a three-dimensional interpretation of the geology surrounding the location of the monitored geologic repository for spent nuclear fuel and high-level radioactive waste at Yucca Mountain. The geologic framework model encompasses and is limited to an area of 65 square miles (168 square kilometers) and a volume of 185 cubic miles (771 cubic kilometers). The boundaries of the geologic framework model (shown in Figure 1-1) were chosen to encompass the exploratory boreholes and to provide a geologic framework over the area of interest for hydrologic flow and radionuclide transport modeling through the unsaturated zone (UZ). The upper surface of the model is made up of the surface topography and the depth of the model is constrained by the inferred depth of the Tertiary-Paleozoic unconformity. The geologic framework model was constructed from geologic map and borehole data. Additional information from measured stratigraphic sections, gravity profiles, and seismic profiles was also considered. The intended use of the geologic framework model is to provide a geologic framework over the area of interest consistent with the level of detailed needed for hydrologic flow and radionuclide transport modeling through the UZ and for repository design. The model is limited by the availability of data and relative amount of geologic complexity found in an area. The geologic framework model is inherently limited by scale and content. The grid spacing used in

  9. Geologic Framework Model (GFM2000)

    Energy Technology Data Exchange (ETDEWEB)

    T. Vogt

    2004-08-26

    The purpose of this report is to document the geologic framework model, version GFM2000 with regard to input data, modeling methods, assumptions, uncertainties, limitations, and validation of the model results, and the differences between GFM2000 and previous versions. The version number of this model reflects the year during which the model was constructed. This model supersedes the previous model version, documented in Geologic Framework Model (GFM 3.1) (CRWMS M&O 2000 [DIRS 138860]). The geologic framework model represents a three-dimensional interpretation of the geology surrounding the location of the monitored geologic repository for spent nuclear fuel and high-level radioactive waste at Yucca Mountain. The geologic framework model encompasses and is limited to an area of 65 square miles (168 square kilometers) and a volume of 185 cubic miles (771 cubic kilometers). The boundaries of the geologic framework model (shown in Figure 1-1) were chosen to encompass the exploratory boreholes and to provide a geologic framework over the area of interest for hydrologic flow and radionuclide transport modeling through the unsaturated zone (UZ). The upper surface of the model is made up of the surface topography and the depth of the model is constrained by the inferred depth of the Tertiary-Paleozoic unconformity. The geologic framework model was constructed from geologic map and borehole data. Additional information from measured stratigraphic sections, gravity profiles, and seismic profiles was also considered. The intended use of the geologic framework model is to provide a geologic framework over the area of interest consistent with the level of detailed needed for hydrologic flow and radionuclide transport modeling through the UZ and for repository design. The model is limited by the availability of data and relative amount of geologic complexity found in an area. The geologic framework model is inherently limited by scale and content. The grid spacing used in the

  10. Spotting handwritten words and REGEX using a two stage BLSTM-HMM architecture

    Science.gov (United States)

    Bideault, Gautier; Mioulet, Luc; Chatelain, Clément; Paquet, Thierry

    2015-01-01

    In this article, we propose a hybrid model for spotting words and regular expressions (REGEX) in handwritten documents. The model is made of the state-of-the-art BLSTM (Bidirectional Long Short Time Memory) neural network for recognizing and segmenting characters, coupled with a HMM to build line models able to spot the desired sequences. Experiments on the Rimes database show very promising results.

  11. Using features of local densities, statistics and HMM toolkit (HTK for offline Arabic handwriting text recognition

    Directory of Open Access Journals (Sweden)

    El Moubtahij Hicham

    2017-12-01

    Full Text Available This paper presents an analytical approach of an offline handwritten Arabic text recognition system. It is based on the Hidden Markov Models (HMM Toolkit (HTK without explicit segmentation. The first phase is preprocessing, where the data is introduced in the system after quality enhancements. Then, a set of characteristics (features of local densities and features statistics are extracted by using the technique of sliding windows. Subsequently, the resulting feature vectors are injected to the Hidden Markov Model Toolkit (HTK. The simple database “Arabic-Numbers” and IFN/ENIT are used to evaluate the performance of this system. Keywords: Hidden Markov Models (HMM Toolkit (HTK, Sliding windows

  12. A Framework for Estimating Long Term Driver Behavior

    Directory of Open Access Journals (Sweden)

    Vijay Gadepally

    2017-01-01

    Full Text Available We present a framework for estimation of long term driver behavior for autonomous vehicles and vehicle safety systems. The Hybrid State System and Hidden Markov Model (HSS+HMM system discussed in this article is capable of describing the hybrid characteristics of driver and vehicle coupling. In our model, driving observations follow a continuous trajectory that can be measured to create continuous state estimates. These continuous state estimates can then be used to estimate the most likely driver state using decision-behavior coupling inherent to the HSS+HMM system. The HSS+HMM system is encompassed in a HSS structure and intersystem connectivity is determined by using signal processing and pattern recognition techniques. The proposed method is suitable for a number of autonomous and vehicle safety scenarios such as estimating intent of other vehicles near intersections or avoiding hazardous driving events such as unexpected lane changes. The long term driver behavior estimation system involves an extended HSS+HMM structure that is capable of including external information in the estimation process. Through the grafting and pruning of metastates, the HSS+HMM system can be dynamically updated to best represent driver choices given external information. Three application examples are also provided to elucidate the theoretical system.

  13. A Novel Approach to Detect Network Attacks Using G-HMM-Based Temporal Relations between Internet Protocol Packets

    Directory of Open Access Journals (Sweden)

    Han Kyusuk

    2011-01-01

    Full Text Available This paper introduces novel attack detection approaches on mobile and wireless device security and network which consider temporal relations between internet packets. In this paper we first present a field selection technique using a Genetic Algorithm and generate a Packet-based Mining Association Rule from an original Mining Association Rule for Support Vector Machine in mobile and wireless network environment. Through the preprocessing with PMAR, SVM inputs can account for time variation between packets in mobile and wireless network. Third, we present Gaussian observation Hidden Markov Model to exploit the hidden relationships between packets based on probabilistic estimation. In our G-HMM approach, we also apply G-HMM feature reduction for better initialization. We demonstrate the usefulness of our SVM and G-HMM approaches with GA on MIT Lincoln Lab datasets and a live dataset that we captured on a real mobile and wireless network. Moreover, experimental results are verified by -fold cross-validation test.

  14. Comparison of HMM and DTW methods in automatic recognition of pathological phoneme pronunciation

    OpenAIRE

    Wielgat, Robert; Zielinski, Tomasz P.; Swietojanski, Pawel; Zoladz, Piotr; Król, Daniel; Wozniak, Tomasz; Grabias, Stanislaw

    2007-01-01

    In the paper recently proposed Human Factor Cepstral Coefficients (HFCC) are used to automatic recognition of pathological phoneme pronunciation in speech of impaired children and efficiency of this approach is compared to application of the standard Mel-Frequency Cepstral Coefficients (MFCC) as a feature vector. Both dynamic time warping (DTW), working on whole words or embedded phoneme patterns, and hidden Markov models (HMM) are used as classifiers in the presented research. Obtained resul...

  15. Computer-Aided Modeling Framework

    DEFF Research Database (Denmark)

    Fedorova, Marina; Sin, Gürkan; Gani, Rafiqul

    Models are playing important roles in design and analysis of chemicals based products and the processes that manufacture them. Computer-aided methods and tools have the potential to reduce the number of experiments, which can be expensive and time consuming, and there is a benefit of working...... development and application. The proposed work is a part of the project for development of methods and tools that will allow systematic generation, analysis and solution of models for various objectives. It will use the computer-aided modeling framework that is based on a modeling methodology, which combines....... In this contribution, the concept of template-based modeling is presented and application is highlighted for the specific case of catalytic membrane fixed bed models. The modeling template is integrated in a generic computer-aided modeling framework. Furthermore, modeling templates enable the idea of model reuse...

  16. CMAQ Model Evaluation Framework

    Science.gov (United States)

    CMAQ is tested to establish the modeling system’s credibility in predicting pollutants such as ozone and particulate matter. Evaluation of CMAQ has been designed to assess the model’s performance for specific time periods and for specific uses.

  17. A Framework for Video Modeling

    NARCIS (Netherlands)

    Petkovic, M.; Jonker, Willem

    In recent years, research in video databases has increased greatly, but relatively little work has been done in the area of semantic content-based retrieval. In this paper, we present a framework for video modelling with emphasis on semantic content of video data. The video data model presented

  18. An improved segmentation-based HMM learning method for Condition-based Maintenance

    International Nuclear Information System (INIS)

    Liu, T; Lemeire, J; Cartella, F; Meganck, S

    2012-01-01

    In the domain of condition-based maintenance (CBM), persistence of machine states is a valid assumption. Based on this assumption, we present an improved Hidden Markov Model (HMM) learning algorithm for the assessment of equipment states. By a good estimation of initial parameters, more accurate learning can be achieved than by regular HMM learning methods which start with randomly chosen initial parameters. It is also better in avoiding getting trapped in local maxima. The data is segmented with a change-point analysis method which uses a combination of cumulative sum charts (CUSUM) and bootstrapping techniques. The method determines a confidence level that a state change happens. After the data is segmented, in order to label and combine the segments corresponding to the same states, a clustering technique is used based on a low-pass filter or root mean square (RMS) values of the features. The segments with their labelled hidden state are taken as 'evidence' to estimate the parameters of an HMM. Then, the estimated parameters are served as initial parameters for the traditional Baum-Welch (BW) learning algorithms, which are used to improve the parameters and train the model. Experiments on simulated and real data demonstrate that both performance and convergence speed is improved.

  19. Geologic Framework Model Analysis Model Report

    Energy Technology Data Exchange (ETDEWEB)

    R. Clayton

    2000-12-19

    The purpose of this report is to document the Geologic Framework Model (GFM), Version 3.1 (GFM3.1) with regard to data input, modeling methods, assumptions, uncertainties, limitations, and validation of the model results, qualification status of the model, and the differences between Version 3.1 and previous versions. The GFM represents a three-dimensional interpretation of the stratigraphy and structural features of the location of the potential Yucca Mountain radioactive waste repository. The GFM encompasses an area of 65 square miles (170 square kilometers) and a volume of 185 cubic miles (771 cubic kilometers). The boundaries of the GFM were chosen to encompass the most widely distributed set of exploratory boreholes (the Water Table or WT series) and to provide a geologic framework over the area of interest for hydrologic flow and radionuclide transport modeling through the unsaturated zone (UZ). The depth of the model is constrained by the inferred depth of the Tertiary-Paleozoic unconformity. The GFM was constructed from geologic map and borehole data. Additional information from measured stratigraphy sections, gravity profiles, and seismic profiles was also considered. This interim change notice (ICN) was prepared in accordance with the Technical Work Plan for the Integrated Site Model Process Model Report Revision 01 (CRWMS M&O 2000). The constraints, caveats, and limitations associated with this model are discussed in the appropriate text sections that follow. The GFM is one component of the Integrated Site Model (ISM) (Figure l), which has been developed to provide a consistent volumetric portrayal of the rock layers, rock properties, and mineralogy of the Yucca Mountain site. The ISM consists of three components: (1) Geologic Framework Model (GFM); (2) Rock Properties Model (RPM); and (3) Mineralogic Model (MM). The ISM merges the detailed project stratigraphy into model stratigraphic units that are most useful for the primary downstream models and the

  20. Geologic Framework Model Analysis Model Report

    International Nuclear Information System (INIS)

    Clayton, R.

    2000-01-01

    The purpose of this report is to document the Geologic Framework Model (GFM), Version 3.1 (GFM3.1) with regard to data input, modeling methods, assumptions, uncertainties, limitations, and validation of the model results, qualification status of the model, and the differences between Version 3.1 and previous versions. The GFM represents a three-dimensional interpretation of the stratigraphy and structural features of the location of the potential Yucca Mountain radioactive waste repository. The GFM encompasses an area of 65 square miles (170 square kilometers) and a volume of 185 cubic miles (771 cubic kilometers). The boundaries of the GFM were chosen to encompass the most widely distributed set of exploratory boreholes (the Water Table or WT series) and to provide a geologic framework over the area of interest for hydrologic flow and radionuclide transport modeling through the unsaturated zone (UZ). The depth of the model is constrained by the inferred depth of the Tertiary-Paleozoic unconformity. The GFM was constructed from geologic map and borehole data. Additional information from measured stratigraphy sections, gravity profiles, and seismic profiles was also considered. This interim change notice (ICN) was prepared in accordance with the Technical Work Plan for the Integrated Site Model Process Model Report Revision 01 (CRWMS M and O 2000). The constraints, caveats, and limitations associated with this model are discussed in the appropriate text sections that follow. The GFM is one component of the Integrated Site Model (ISM) (Figure l), which has been developed to provide a consistent volumetric portrayal of the rock layers, rock properties, and mineralogy of the Yucca Mountain site. The ISM consists of three components: (1) Geologic Framework Model (GFM); (2) Rock Properties Model (RPM); and (3) Mineralogic Model (MM). The ISM merges the detailed project stratigraphy into model stratigraphic units that are most useful for the primary downstream models and

  1. Bearing Performance Degradation Assessment Using Linear Discriminant Analysis and Coupled HMM

    International Nuclear Information System (INIS)

    Liu, T; Chen, J; Zhou, X N; Xiao, W B

    2012-01-01

    Bearing is one of the most important units in rotary machinery, its performance may vary significantly under different working stages. Thus it is critical to choose the most effective features for bearing performance degradation prediction. Linear Discriminant Analysis (LDA) is a useful method in finding few feature's dimensions that best discriminate a set of features extracted from original vibration signals. Another challenge in bearing performance degradation is how to build a model to recognize the different conditions with the data coming from different monitoring channels. In this paper, coupled hidden Markov models (CHMM) is presented to model interacting processes which can overcome the defections of the HMM. Because the input data in CHMM are collected by several sensors, and the interacting information can be fused by coupled modalities, it is more effective than HMM which used only one state chain. The model can be used in estimating the bearing performance degradation states according to several observation data. When becoming degradation pattern recognition, the new observation features should be input into the pre-trained CHMM and calculate the performance index (PI) of the outputs, the changing of PI could be used to describe the different degradation level of the bearings. The results show that PI will decline with the increase of the bearing degradation. Assessment results of the whole life time experimental bearing signals validate the feasibility and effectiveness of this method.

  2. Crystallization Kinetics within a Generic Modelling Framework

    DEFF Research Database (Denmark)

    Meisler, Kresten Troelstrup; von Solms, Nicolas; Gernaey, Krist

    2013-01-01

    An existing generic modelling framework has been expanded with tools for kinetic model analysis. The analysis of kinetics is carried out within the framework where kinetic constitutive models are collected, analysed and utilized for the simulation of crystallization operations. A modelling...... procedure is proposed to gain the information of crystallization operation kinetic model analysis and utilize this for faster evaluation of crystallization operations....

  3. Online adaptive learning of Left-Right Continuous HMM for bearings condition assessment

    International Nuclear Information System (INIS)

    Cartella, F; Liu, T; Meganck, S; Lemeire, J; Sahli, H

    2012-01-01

    Standard Hidden Markov Models (HMMs) approaches used for condition assessment of bearings assume that all the possible system states are fixed and known a priori and that training data from all of the associated states are available. Moreover, the training procedure is performed offline, and only once at the beginning, with the available training set. These assumptions significantly impede component diagnosis applications when all of the possible states of the system are not known in advance or environmental factors or operative conditions change during the tool's usage. The method introduced in this paper overcomes the above limitations and proposes an approach to detect unknown degradation modalities using a Left-Right Continuous HMM with a variable state space. The proposed HMM is combined with Change Point Detection algorithms to (i) estimate, from historical observations, the initial number of the model's states, as well as to perform an initial guess of the parameters, and (ii) to adaptively recognize new states and, consequently, adjust the model parameters during monitoring. The approach has been tested using real monitoring data taken from the NASA benchmark repository. A comparative study with state of the art techniques shows improvements in terms of reduction of the training procedure iterations, and early detection of unknown states.

  4. GeoFramework: A Modeling Framework for Solid Earth Geophysics

    Science.gov (United States)

    Gurnis, M.; Aivazis, M.; Tromp, J.; Tan, E.; Thoutireddy, P.; Liu, Q.; Choi, E.; Dicaprio, C.; Chen, M.; Simons, M.; Quenette, S.; Appelbe, B.; Aagaard, B.; Williams, C.; Lavier, L.; Moresi, L.; Law, H.

    2003-12-01

    As data sets in geophysics become larger and of greater relevance to other earth science disciplines, and as earth science becomes more interdisciplinary in general, modeling tools are being driven in new directions. There is now a greater need to link modeling codes to one another, link modeling codes to multiple datasets, and to make modeling software available to non modeling specialists. Coupled with rapid progress in computer hardware (including the computational speed afforded by massively parallel computers), progress in numerical algorithms, and the introduction of software frameworks, these lofty goals of merging software in geophysics are now possible. The GeoFramework project, a collaboration between computer scientists and geoscientists, is a response to these needs and opportunities. GeoFramework is based on and extends Pyre, a Python-based modeling framework, recently developed to link solid (Lagrangian) and fluid (Eulerian) models, as well as mesh generators, visualization packages, and databases, with one another for engineering applications. The utility and generality of Pyre as a general purpose framework in science is now being recognized. Besides its use in engineering and geophysics, it is also being used in particle physics and astronomy. Geology and geophysics impose their own unique requirements on software frameworks which are not generally available in existing frameworks and so there is a need for research in this area. One of the special requirements is the way Lagrangian and Eulerian codes will need to be linked in time and space within a plate tectonics context. GeoFramework has grown beyond its initial goal of linking a limited number of exiting codes together. The following codes are now being reengineered within the context of Pyre: Tecton, 3-D FE Visco-elastic code for lithospheric relaxation; CitComS, a code for spherical mantle convection; SpecFEM3D, a SEM code for global and regional seismic waves; eqsim, a FE code for dynamic

  5. Improving a HMM-based off-line handwriting recognition system using MME-PSO optimization

    Science.gov (United States)

    Hamdani, Mahdi; El Abed, Haikal; Hamdani, Tarek M.; Märgner, Volker; Alimi, Adel M.

    2011-01-01

    One of the trivial steps in the development of a classifier is the design of its architecture. This paper presents a new algorithm, Multi Models Evolvement (MME) using Particle Swarm Optimization (PSO). This algorithm is a modified version of the basic PSO, which is used to the unsupervised design of Hidden Markov Model (HMM) based architectures. For instance, the proposed algorithm is applied to an Arabic handwriting recognizer based on discrete probability HMMs. After the optimization of their architectures, HMMs are trained with the Baum- Welch algorithm. The validation of the system is based on the IfN/ENIT database. The performance of the developed approach is compared to the participating systems at the 2005 competition organized on Arabic handwriting recognition on the International Conference on Document Analysis and Recognition (ICDAR). The final system is a combination between an optimized HMM with 6 other HMMs obtained by a simple variation of the number of states. An absolute improvement of 6% of word recognition rate with about 81% is presented. This improvement is achieved comparing to the basic system (ARAB-IfN). The proposed recognizer outperforms also most of the known state-of-the-art systems.

  6. Cytoview: Development of a cell modelling framework

    Indian Academy of Sciences (India)

    2007-07-06

    Jul 6, 2007 ... The different issues that have been addressed are ontologies, feature description and model building. The framework describes dotted representations and tree data structures to integrate diverse pieces of data and parametric models enabling size, shape and location descriptions. The framework serves ...

  7. A framework for sustainable interorganizational business model

    OpenAIRE

    Neupane, Ganesh Prasad; Haugland, Sven A.

    2016-01-01

    Drawing on literature on business model innovations and sustainability, this paper develops a framework for sustainable interorganizational business models. The aim of the framework is to enhance the sustainability of firms’ business models by enabling firms to create future value by taking into account environmental, social and economic factors. The paper discusses two themes: (1) application of the term sustainability to business model innovation, and (2) implications of integrating sustain...

  8. Crystallization Kinetics within a Generic Modeling Framework

    DEFF Research Database (Denmark)

    Meisler, Kresten Troelstrup; von Solms, Nicolas; Gernaey, Krist V.

    2014-01-01

    of employing a well-structured model library for storage, use/reuse, and analysis of the kinetic models are highlighted. Examples illustrating the application of the modeling framework for kinetic model discrimination related to simulation of specific crystallization scenarios and for kinetic model parameter......A new and extended version of a generic modeling framework for analysis and design of crystallization operations is presented. The new features of this framework are described, with focus on development, implementation, identification, and analysis of crystallization kinetic models. Issues related...... to the modeling of various kinetic phenomena like nucleation, growth, agglomeration, and breakage are discussed in terms of model forms, model parameters, their availability and/or estimation, and their selection and application for specific crystallization operational scenarios under study. The advantages...

  9. A Unified Framework for Systematic Model Improvement

    DEFF Research Database (Denmark)

    Kristensen, Niels Rode; Madsen, Henrik; Jørgensen, Sten Bay

    2003-01-01

    A unified framework for improving the quality of continuous time models of dynamic systems based on experimental data is presented. The framework is based on an interplay between stochastic differential equation (SDE) modelling, statistical tests and multivariate nonparametric regression. This co......-batch bioreactor, where it is illustrated how an incorrectly modelled biomass growth rate can be pinpointed and an estimate provided of the functional relation needed to properly describe it....

  10. Frameworks for understanding and describing business models

    DEFF Research Database (Denmark)

    Nielsen, Christian; Roslender, Robin

    2014-01-01

    This chapter provides in a chronological fashion an introduction to six frameworks that one can apply to describing, understanding and also potentially innovating business models. These six frameworks have been chosen carefully as they represent six very different perspectives on business models...... and in this manner “complement” each other. There are a multitude of varying frameworks that could be chosen from and we urge the reader to search and trial these for themselves. The six chosen models (year of release in parenthesis) are: • Service-Profit Chain (1994) • Strategic Systems Auditing (1997) • Strategy...... Maps (2001) • Intellectual Capital Statements (2003) • Chesbrough’s framework for Open Business Models (2006) • Business Model Canvas (2008)...

  11. Model-based DSL frameworks

    NARCIS (Netherlands)

    Ivanov, Ivan; Bézivin, J.; Jouault, F.; Valduriez, P.

    2006-01-01

    More than five years ago, the OMG proposed the Model Driven Architecture (MDA™) approach to deal with the separation of platform dependent and independent aspects in information systems. Since then, the initial idea of MDA evolved and Model Driven Engineering (MDE) is being increasingly promoted to

  12. Fault diagnosis of nuclear-powered equipment based on HMM and SVM

    International Nuclear Information System (INIS)

    Yue Xia; Zhang Chunliang; Zhu Houyao; Quan Yanming

    2012-01-01

    For the complexity and the small fault samples of nuclear-powered equipment, a hybrid HMM/SVM method was introduced in fault diagnosis. The hybrid method has two steps: first, HMM is utilized for primary diagnosis, in which the range of possible failure is reduced and the state trends can be observed; then faults can be recognized taking the advantage of the generalization ability of SVM. Experiments on the main pump failure simulator show that the HMM/SVM system has a high recognition rate and can be used in the fault diagnosis of nuclear-powered equipment. (authors)

  13. A useful framework for optimal replacement models

    International Nuclear Information System (INIS)

    Aven, Terje; Dekker, Rommert

    1997-01-01

    In this note we present a general framework for optimization of replacement times. It covers a number of models, including various age and block replacement models, and allows a uniform analysis for all these models. A relation to the marginal cost concept is described

  14. Graphical Model Debugger Framework for Embedded Systems

    DEFF Research Database (Denmark)

    Zeng, Kebin

    2010-01-01

    Model Driven Software Development has offered a faster way to design and implement embedded real-time software by moving the design to a model level, and by transforming models to code. However, the testing of embedded systems has remained at the code level. This paper presents a Graphical Model...... Debugger Framework, providing an auxiliary avenue of analysis of system models at runtime by executing generated code and updating models synchronously, which allows embedded developers to focus on the model level. With the model debugger, embedded developers can graphically test their design model...

  15. A framework for API solubility modelling

    DEFF Research Database (Denmark)

    Conte, Elisa; Gani, Rafiqul; Crafts, Peter

    . In addition, most of the models are not predictive and requires experimental data for the calculation of the needed parameters. This work aims at developing an efficient framework for the solubility modelling of Active Pharmaceutical Ingredients (API) in water and organic solvents. With this framework......-SAFT) are used for solubility calculations when the needed interaction parameters or experimental data are available. The CI-UNIFAC is instead used when the previous models lack interaction parameters or when solubility data are not available. A new GC+ model for APIs solvent selection based...... on the hydrophobicity, hydrophilicity and polarity information of the API and solvent is also developed, for performing fast solvent selection and screening. Eventually, all the previous developments are integrated in a framework for their efficient and integrated use. Two case studies are presented: the first...

  16. A mixed model framework for teratology studies.

    Science.gov (United States)

    Braeken, Johan; Tuerlinckx, Francis

    2009-10-01

    A mixed model framework is presented to model the characteristic multivariate binary anomaly data as provided in some teratology studies. The key features of the model are the incorporation of covariate effects, a flexible random effects distribution by means of a finite mixture, and the application of copula functions to better account for the relation structure of the anomalies. The framework is motivated by data of the Boston Anticonvulsant Teratogenesis study and offers an integrated approach to investigate substantive questions, concerning general and anomaly-specific exposure effects of covariates, interrelations between anomalies, and objective diagnostic measurement.

  17. Driver Performance Model: 1. Conceptual Framework

    National Research Council Canada - National Science Library

    Heimerl, Joseph

    2001-01-01

    ...'. At the present time, no such comprehensive model exists. This report discusses a conceptual framework designed to encompass the relationships, conditions, and constraints related to direct, indirect, and remote modes of driving and thus provides a guide or 'road map' for the construction and creation of a comprehensive driver performance model.

  18. Computational models in physics teaching: a framework

    Directory of Open Access Journals (Sweden)

    Marco Antonio Moreira

    2012-08-01

    Full Text Available The purpose of the present paper is to present a theoretical framework to promote and assist meaningful physics learning through computational models. Our proposal is based on the use of a tool, the AVM diagram, to design educational activities involving modeling and computer simulations. The idea is to provide a starting point for the construction and implementation of didactical approaches grounded in a coherent epistemological view about scientific modeling.

  19. Efficient view based 3-D object retrieval using Hidden Markov Model

    Science.gov (United States)

    Jain, Yogendra Kumar; Singh, Roshan Kumar

    2013-12-01

    Recent research effort has been dedicated to view based 3-D object retrieval, because of highly discriminative property of 3-D object and has multi view representation. The state-of-art method is highly depending on their own camera array setting for capturing views of 3-D object and use complex Zernike descriptor, HAC for representative view selection which limit their practical application and make it inefficient for retrieval. Therefore, an efficient and effective algorithm is required for 3-D Object Retrieval. In order to move toward a general framework for efficient 3-D object retrieval which is independent of camera array setting and avoidance of representative view selection, we propose an Efficient View Based 3-D Object Retrieval (EVBOR) method using Hidden Markov Model (HMM). In this framework, each object is represented by independent set of view, which means views are captured from any direction without any camera array restriction. In this, views are clustered (including query view) to generate the view cluster, which is then used to build the query model with HMM. In our proposed method, HMM is used in twofold: in the training (i.e. HMM estimate) and in the retrieval (i.e. HMM decode). The query model is trained by using these view clusters. The EVBOR query model is worked on the basis of query model combining with HMM. The proposed approach remove statically camera array setting for view capturing and can be apply for any 3-D object database to retrieve 3-D object efficiently and effectively. Experimental results demonstrate that the proposed scheme has shown better performance than existing methods. [Figure not available: see fulltext.

  20. Building crop models within different crop modelling frameworks

    NARCIS (Netherlands)

    Adam, M.Y.O.; Corbeels, M.; Leffelaar, P.A.; Keulen, van H.; Wery, J.; Ewert, F.

    2012-01-01

    Modular frameworks for crop modelling have evolved through simultaneous progress in crop science and software development but differences among these frameworks exist which are not well understood, resulting in potential misuse for crop modelling. In this paper we review differences and similarities

  1. Hierarchical material models for fragmentation modeling in NIF-ALE-AMR

    International Nuclear Information System (INIS)

    Fisher, A C; Masters, N D; Koniges, A E; Anderson, R W; Gunney, B T N; Wang, P; Becker, R; Dixit, P; Benson, D J

    2008-01-01

    Fragmentation is a fundamental process that naturally spans micro to macroscopic scales. Recent advances in algorithms, computer simulations, and hardware enable us to connect the continuum to microstructural regimes in a real simulation through a heterogeneous multiscale mathematical model. We apply this model to the problem of predicting how targets in the NIF chamber dismantle, so that optics and diagnostics can be protected from damage. The mechanics of the initial material fracture depend on the microscopic grain structure. In order to effectively simulate the fragmentation, this process must be modeled at the subgrain level with computationally expensive crystal plasticity models. However, there are not enough computational resources to model the entire NIF target at this microscopic scale. In order to accomplish these calculations, a hierarchical material model (HMM) is being developed. The HMM will allow fine-scale modeling of the initial fragmentation using computationally expensive crystal plasticity, while the elements at the mesoscale can use polycrystal models, and the macroscopic elements use analytical flow stress models. The HMM framework is built upon an adaptive mesh refinement (AMR) capability. We present progress in implementing the HMM in the NIF-ALE-AMR code. Additionally, we present test simulations relevant to NIF targets

  2. Hierarchical material models for fragmentation modeling in NIF-ALE-AMR

    Energy Technology Data Exchange (ETDEWEB)

    Fisher, A C; Masters, N D; Koniges, A E; Anderson, R W; Gunney, B T N; Wang, P; Becker, R [Lawrence Livermore National Laboratory, PO Box 808, Livermore, CA 94551 (United States); Dixit, P; Benson, D J [University of California San Diego, 9500 Gilman Dr., La Jolla. CA 92093 (United States)], E-mail: fisher47@llnl.gov

    2008-05-15

    Fragmentation is a fundamental process that naturally spans micro to macroscopic scales. Recent advances in algorithms, computer simulations, and hardware enable us to connect the continuum to microstructural regimes in a real simulation through a heterogeneous multiscale mathematical model. We apply this model to the problem of predicting how targets in the NIF chamber dismantle, so that optics and diagnostics can be protected from damage. The mechanics of the initial material fracture depend on the microscopic grain structure. In order to effectively simulate the fragmentation, this process must be modeled at the subgrain level with computationally expensive crystal plasticity models. However, there are not enough computational resources to model the entire NIF target at this microscopic scale. In order to accomplish these calculations, a hierarchical material model (HMM) is being developed. The HMM will allow fine-scale modeling of the initial fragmentation using computationally expensive crystal plasticity, while the elements at the mesoscale can use polycrystal models, and the macroscopic elements use analytical flow stress models. The HMM framework is built upon an adaptive mesh refinement (AMR) capability. We present progress in implementing the HMM in the NIF-ALE-AMR code. Additionally, we present test simulations relevant to NIF targets.

  3. Spatial Modeling for Resources Framework (SMRF)

    Science.gov (United States)

    Spatial Modeling for Resources Framework (SMRF) was developed by Dr. Scott Havens at the USDA Agricultural Research Service (ARS) in Boise, ID. SMRF was designed to increase the flexibility of taking measured weather data and distributing the point measurements across a watershed. SMRF was developed...

  4. A model-based risk management framework

    Energy Technology Data Exchange (ETDEWEB)

    Gran, Bjoern Axel; Fredriksen, Rune

    2002-08-15

    The ongoing research activity addresses these issues through two co-operative activities. The first is the IST funded research project CORAS, where Institutt for energiteknikk takes part as responsible for the work package for Risk Analysis. The main objective of the CORAS project is to develop a framework to support risk assessment of security critical systems. The second, called the Halden Open Dependability Demonstrator (HODD), is established in cooperation between Oestfold University College, local companies and HRP. The objective of HODD is to provide an open-source test bed for testing, teaching and learning about risk analysis methods, risk analysis tools, and fault tolerance techniques. The Inverted Pendulum Control System (IPCON), which main task is to keep a pendulum balanced and controlled, is the first system that has been established. In order to make risk assessment one need to know what a system does, or is intended to do. Furthermore, the risk assessment requires correct descriptions of the system, its context and all relevant features. A basic assumption is that a precise model of this knowledge, based on formal or semi-formal descriptions, such as UML, will facilitate a systematic risk assessment. It is also necessary to have a framework to integrate the different risk assessment methods. The experiences so far support this hypothesis. This report presents CORAS and the CORAS model-based risk management framework, including a preliminary guideline for model-based risk assessment. The CORAS framework for model-based risk analysis offers a structured and systematic approach to identify and assess security issues of ICT systems. From the initial assessment of IPCON, we also believe that the framework is applicable in a safety context. Further work on IPCON, as well as the experiences from the CORAS trials, will provide insight and feedback for further improvements. (Author)

  5. An evaluation framework for participatory modelling

    Science.gov (United States)

    Krueger, T.; Inman, A.; Chilvers, J.

    2012-04-01

    Strong arguments for participatory modelling in hydrology can be made on substantive, instrumental and normative grounds. These arguments have led to increasingly diverse groups of stakeholders (here anyone affecting or affected by an issue) getting involved in hydrological research and the management of water resources. In fact, participation has become a requirement of many research grants, programs, plans and policies. However, evidence of beneficial outcomes of participation as suggested by the arguments is difficult to generate and therefore rare. This is because outcomes are diverse, distributed, often tacit, and take time to emerge. In this paper we develop an evaluation framework for participatory modelling focussed on learning outcomes. Learning encompasses many of the potential benefits of participation, such as better models through diversity of knowledge and scrutiny, stakeholder empowerment, greater trust in models and ownership of subsequent decisions, individual moral development, reflexivity, relationships, social capital, institutional change, resilience and sustainability. Based on the theories of experiential, transformative and social learning, complemented by practitioner experience our framework examines if, when and how learning has occurred. Special emphasis is placed on the role of models as learning catalysts. We map the distribution of learning between stakeholders, scientists (as a subgroup of stakeholders) and models. And we analyse what type of learning has occurred: instrumental learning (broadly cognitive enhancement) and/or communicative learning (change in interpreting meanings, intentions and values associated with actions and activities; group dynamics). We demonstrate how our framework can be translated into a questionnaire-based survey conducted with stakeholders and scientists at key stages of the participatory process, and show preliminary insights from applying the framework within a rural pollution management situation in

  6. A framework for benchmarking land models

    Directory of Open Access Journals (Sweden)

    Y. Q. Luo

    2012-10-01

    Full Text Available Land models, which have been developed by the modeling community in the past few decades to predict future states of ecosystems and climate, have to be critically evaluated for their performance skills of simulating ecosystem responses and feedback to climate change. Benchmarking is an emerging procedure to measure performance of models against a set of defined standards. This paper proposes a benchmarking framework for evaluation of land model performances and, meanwhile, highlights major challenges at this infant stage of benchmark analysis. The framework includes (1 targeted aspects of model performance to be evaluated, (2 a set of benchmarks as defined references to test model performance, (3 metrics to measure and compare performance skills among models so as to identify model strengths and deficiencies, and (4 model improvement. Land models are required to simulate exchange of water, energy, carbon and sometimes other trace gases between the atmosphere and land surface, and should be evaluated for their simulations of biophysical processes, biogeochemical cycles, and vegetation dynamics in response to climate change across broad temporal and spatial scales. Thus, one major challenge is to select and define a limited number of benchmarks to effectively evaluate land model performance. The second challenge is to develop metrics of measuring mismatches between models and benchmarks. The metrics may include (1 a priori thresholds of acceptable model performance and (2 a scoring system to combine data–model mismatches for various processes at different temporal and spatial scales. The benchmark analyses should identify clues of weak model performance to guide future development, thus enabling improved predictions of future states of ecosystems and climate. The near-future research effort should be on development of a set of widely acceptable benchmarks that can be used to objectively, effectively, and reliably evaluate fundamental properties

  7. Talking Cure Models: A Framework of Analysis

    Directory of Open Access Journals (Sweden)

    Christopher Marx

    2017-09-01

    Full Text Available Psychotherapy is commonly described as a “talking cure,” a treatment method that operates through linguistic action and interaction. The operative specifics of therapeutic language use, however, are insufficiently understood, mainly due to a multitude of disparate approaches that advance different notions of what “talking” means and what “cure” implies in the respective context. Accordingly, a clarification of the basic theoretical structure of “talking cure models,” i.e., models that describe therapeutic processes with a focus on language use, is a desideratum of language-oriented psychotherapy research. Against this background the present paper suggests a theoretical framework of analysis which distinguishes four basic components of “talking cure models”: (1 a foundational theory (which suggests how linguistic activity can affect and transform human experience, (2 an experiential problem state (which defines the problem or pathology of the patient, (3 a curative linguistic activity (which defines linguistic activities that are supposed to effectuate a curative transformation of the experiential problem state, and (4 a change mechanism (which defines the processes and effects involved in such transformations. The purpose of the framework is to establish a terminological foundation that allows for systematically reconstructing basic properties and operative mechanisms of “talking cure models.” To demonstrate the applicability and utility of the framework, five distinct “talking cure models” which spell out the details of curative “talking” processes in terms of (1 catharsis, (2 symbolization, (3 narrative, (4 metaphor, and (5 neurocognitive inhibition are introduced and discussed in terms of the framework components. In summary, we hope that our framework will prove useful for the objective of clarifying the theoretical underpinnings of language-oriented psychotherapy research and help to establish a more

  8. AGAMA: Action-based galaxy modeling framework

    Science.gov (United States)

    Vasiliev, Eugene

    2018-05-01

    The AGAMA library models galaxies. It computes gravitational potential and forces, performs orbit integration and analysis, and can convert between position/velocity and action/angle coordinates. It offers a framework for finding best-fit parameters of a model from data and self-consistent multi-component galaxy models, and contains useful auxiliary utilities such as various mathematical routines. The core of the library is written in C++, and there are Python and Fortran interfaces. AGAMA may be used as a plugin for the stellar-dynamical software packages galpy (ascl:1411.008), AMUSE (ascl:1107.007), and NEMO (ascl:1010.051).

  9. Model-based version management system framework

    International Nuclear Information System (INIS)

    Mehmood, W.

    2016-01-01

    In this paper we present a model-based version management system. Version Management System (VMS) a branch of software configuration management (SCM) aims to provide a controlling mechanism for evolution of software artifacts created during software development process. Controlling the evolution requires many activities to perform, such as, construction and creation of versions, identification of differences between versions, conflict detection and merging. Traditional VMS systems are file-based and consider software systems as a set of text files. File based VMS systems are not adequate for performing software configuration management activities such as, version control on software artifacts produced in earlier phases of the software life cycle. New challenges of model differencing, merge, and evolution control arise while using models as central artifact. The goal of this work is to present a generic framework model-based VMS which can be used to overcome the problem of tradition file-based VMS systems and provide model versioning services. (author)

  10. An entropic framework for modeling economies

    Science.gov (United States)

    Caticha, Ariel; Golan, Amos

    2014-08-01

    We develop an information-theoretic framework for economic modeling. This framework is based on principles of entropic inference that are designed for reasoning on the basis of incomplete information. We take the point of view of an external observer who has access to limited information about broad macroscopic economic features. We view this framework as complementary to more traditional methods. The economy is modeled as a collection of agents about whom we make no assumptions of rationality (in the sense of maximizing utility or profit). States of statistical equilibrium are introduced as those macrostates that maximize entropy subject to the relevant information codified into constraints. The basic assumption is that this information refers to supply and demand and is expressed in the form of the expected values of certain quantities (such as inputs, resources, goods, production functions, utility functions and budgets). The notion of economic entropy is introduced. It provides a measure of the uniformity of the distribution of goods and resources. It captures both the welfare state of the economy as well as the characteristics of the market (say, monopolistic, concentrated or competitive). Prices, which turn out to be the Lagrange multipliers, are endogenously generated by the economy. Further studies include the equilibrium between two economies and the conditions for stability. As an example, the case of the nonlinear economy that arises from linear production and utility functions is treated in some detail.

  11. Computational modeling of Metal-Organic Frameworks

    Science.gov (United States)

    Sung, Jeffrey Chuen-Fai

    In this work, the metal-organic frameworks MIL-53(Cr), DMOF-2,3-NH 2Cl, DMOF-2,5-NH2Cl, and HKUST-1 were modeled using molecular mechanics and electronic structure. The effect of electronic polarization on the adsorption of water in MIL-53(Cr) was studied using molecular dynamics simulations of water-loaded MIL-53 systems with both polarizable and non-polarizable force fields. Molecular dynamics simulations of the full systems and DFT calculations on representative framework clusters were utilized to study the difference in nitrogen adsorption between DMOF-2,3-NH2Cl and DMOF-2,5-NH 2Cl. Finally, the control of proton conduction in HKUST-1 by complexation of molecules to the Cu open metal site was investigated using the MS-EVB methodology.

  12. A method for identifying gas-liquid two-phase flow patterns on the basis of wavelet packet multi-scale information entropy and HMM

    International Nuclear Information System (INIS)

    Zhou Yunlong; Zhang Xueqing; Gao Yunpeng; Cheng Yue

    2009-01-01

    For studying flow regimes of gas/liquid two-phase in a vertical upward pipe, the conductance fluctuation information of four typical flow regimes was collected by a measuring the system with self-made multiple conductivity probes. Owing to the non-stationarity of conductance fluctuation signals of gas-liquid two-phase flow, a kind of' flow regime identification method based on wavelet packet Multi-scale Information Entropy and Hidden Markov Model (HMM) was put forward. First of all, the collected conductance fluctuation signals were decomposed into eight different frequency bands signals. Secondly, the wavelet packet multi-scale information entropy of different frequency bands signals were regarded as the input characteristic vectors of all states HMM which had been trained. In the end the regime identification of' the gas-liquid two-phase flow could be performed. The study showed that the method that HMM was applied to identify the flow regime was superior to the one that BP neural network was used, and the results proved that the method was efficient and feasible. (authors)

  13. Computer-aided modeling framework – a generic modeling template

    DEFF Research Database (Denmark)

    Fedorova, Marina; Sin, Gürkan; Gani, Rafiqul

    and test models systematically, efficiently and reliably. In this way, development of products and processes can be made faster, cheaper and more efficient. In this contribution, as part of the framework, a generic modeling template for the systematic derivation of problem specific models is presented....... The application of the modeling template is highlighted with a case study related to the modeling of a catalytic membrane reactor coupling dehydrogenation of ethylbenzene with hydrogenation of nitrobenzene...

  14. COSMO: a conceptual framework for service modelling and refinement

    NARCIS (Netherlands)

    Quartel, Dick; Steen, Maarten W.A.; Pokraev, S.; van Sinderen, Marten J.

    This paper presents a conceptual framework for service modelling and refinement, called the COSMO (COnceptual Service MOdelling) framework. This framework provides concepts to model and reason about services, and to support operations, such as composition and discovery, which are performed on them

  15. Business Model Innovation: An Integrative Conceptual Framework

    Directory of Open Access Journals (Sweden)

    Bernd Wirtz

    2017-01-01

    Full Text Available Purpose: The point of departure of this exploratory study is the gap between the increasing importance of business model innovation (BMI in science and management and the limited conceptual assistance available. Therefore, the study identi es and explores scattered BMI insights and deduces them into an integrative framework to enhance our understanding about this phenomenon and to present a helpful guidance for researchers and practitioners. Design/Methodology/Approach: The study identi es BMI insights through a literature-based investigation and consolidates them into an integrative BMI framework that presents the key elements and dimensions of BMI as well as their presumed relationships. Findings: The study enhances our understanding about the key elements and dimensions of BMI, presents further conceptual insights into the BMI phenomenon, supplies implications for science and management, and may serve as a helpful guidance for future research. Practical Implications: The presented framework provides managers with a tool to identify critical BMI issues and can serve as a conceptual BMI guideline. Research limitations: Given the vast amount of academic journals, it is unlikely that every applicable scienti c publication is included in the analysis. The illustrative examples are descriptive in nature, and thus do not provide empirical validity. Several implications for future research are provided. Originality/Value: The study’s main contribution lies in the unifying approach of the dispersed BMI knowledge. Since our understanding of BMI is still limited, this study should provide the necessary insights and conceptual assistance to further develop the concept and guide its practical application.

  16. A Procurement Performance Model for Construction Frameworks

    Directory of Open Access Journals (Sweden)

    Terence Y M Lam

    2015-07-01

    Full Text Available Collaborative construction frameworks have been developed in the United Kingdom (UK to create longer term relationships between clients and suppliers in order to improve project outcomes. Research undertaken into highways maintenance set within a major county council has confirmed that such collaborative procurement methods can improve time, cost and quality of construction projects. Building upon this and examining the same single case, this research aims to develop a performance model through identification of performance drivers in the whole project delivery process including pre and post contract phases. A priori performance model based on operational and sociological constructs was proposed and then checked by a pilot study. Factor analysis and central tendency statistics from the questionnaires as well as content analysis from the interview transcripts were conducted. It was confirmed that long term relationships, financial and non-financial incentives and stronger communication are the sociological behaviour factors driving performance. The interviews also established that key performance indicators (KPIs can be used as an operational measure to improve performance. With the posteriori performance model, client project managers can effectively collaboratively manage contractor performance through procurement measures including use of longer term and KPIs for the contract so that the expected project outcomes can be achieved. The findings also make significant contribution to construction framework procurement theory by identifying the interrelated sociological and operational performance drivers. This study is set predominantly in the field of highways civil engineering. It is suggested that building based projects or other projects that share characteristics are grouped together and used for further research of the phenomena discovered.

  17. HMMEditor: a visual editing tool for profile hidden Markov model

    Directory of Open Access Journals (Sweden)

    Cheng Jianlin

    2008-03-01

    Full Text Available Abstract Background Profile Hidden Markov Model (HMM is a powerful statistical model to represent a family of DNA, RNA, and protein sequences. Profile HMM has been widely used in bioinformatics research such as sequence alignment, gene structure prediction, motif identification, protein structure prediction, and biological database search. However, few comprehensive, visual editing tools for profile HMM are publicly available. Results We develop a visual editor for profile Hidden Markov Models (HMMEditor. HMMEditor can visualize the profile HMM architecture, transition probabilities, and emission probabilities. Moreover, it provides functions to edit and save HMM and parameters. Furthermore, HMMEditor allows users to align a sequence against the profile HMM and to visualize the corresponding Viterbi path. Conclusion HMMEditor provides a set of unique functions to visualize and edit a profile HMM. It is a useful tool for biological sequence analysis and modeling. Both HMMEditor software and web service are freely available.

  18. Conceptual Frameworks in the Doctoral Research Process: A Pedagogical Model

    Science.gov (United States)

    Berman, Jeanette; Smyth, Robyn

    2015-01-01

    This paper contributes to consideration of the role of conceptual frameworks in the doctoral research process. Through reflection on the two authors' own conceptual frameworks for their doctoral studies, a pedagogical model has been developed. The model posits the development of a conceptual framework as a core element of the doctoral…

  19. A Framework for the Specification of Acquisition Models

    National Research Council Canada - National Science Library

    Meyers, B

    2001-01-01

    .... The timing properties associated with the items receives special treatment. The value of a framework is that one can develop specifications of various acquisition models, such as waterfall, spiral, or incremental, as instances of that framework...

  20. Model based risk assessment - the CORAS framework

    Energy Technology Data Exchange (ETDEWEB)

    Gran, Bjoern Axel; Fredriksen, Rune; Thunem, Atoosa P-J.

    2004-04-15

    Traditional risk analysis and assessment is based on failure-oriented models of the system. In contrast to this, model-based risk assessment (MBRA) utilizes success-oriented models describing all intended system aspects, including functional, operational and organizational aspects of the target. The target models are then used as input sources for complementary risk analysis and assessment techniques, as well as a basis for the documentation of the assessment results. The EU-funded CORAS project developed a tool-supported methodology for the application of MBRA in security-critical systems. The methodology has been tested with successful outcome through a series of seven trial within the telemedicine and ecommerce areas. The CORAS project in general and the CORAS application of MBRA in particular have contributed positively to the visibility of model-based risk assessment and thus to the disclosure of several potentials for further exploitation of various aspects within this important research field. In that connection, the CORAS methodology's possibilities for further improvement towards utilization in more complex architectures and also in other application domains such as the nuclear field can be addressed. The latter calls for adapting the framework to address nuclear standards such as IEC 60880 and IEC 61513. For this development we recommend applying a trial driven approach within the nuclear field. The tool supported approach for combining risk analysis and system development also fits well with the HRP proposal for developing an Integrated Design Environment (IDE) providing efficient methods and tools to support control room systems design. (Author)

  1. A Smallholder Socio-hydrological Modelling Framework

    Science.gov (United States)

    Pande, S.; Savenije, H.; Rathore, P.

    2014-12-01

    Small holders are farmers who own less than 2 ha of farmland. They often have low productivity and thus remain at subsistence level. A fact that nearly 80% of Indian farmers are smallholders, who merely own a third of total farmlands and belong to the poorest quartile, but produce nearly 40% of countries foodgrains underlines the importance of understanding the socio-hydrology of a small holder. We present a framework to understand the socio-hydrological system dynamics of a small holder. It couples the dynamics of 6 main variables that are most relevant at the scale of a small holder: local storage (soil moisture and other water storage), capital, knowledge, livestock production, soil fertility and grass biomass production. The model incorporates rule-based adaptation mechanisms (for example: adjusting expenditures on food and fertilizers, selling livestocks etc.) of small holders when they face adverse socio-hydrological conditions, such as low annual rainfall, higher intra-annual variability in rainfall or variability in agricultural prices. It allows us to study sustainability of small holder farming systems under various settings. We apply the framework to understand the socio-hydrology of small holders in Aurangabad, Maharashtra, India. This district has witnessed suicides of many sugarcane farmers who could not extricate themselves out of the debt trap. These farmers lack irrigation and are susceptible to fluctuating sugar prices and intra-annual hydroclimatic variability. This presentation discusses two aspects in particular: whether government interventions to absolve the debt of farmers is enough and what is the value of investing in local storages that can buffer intra-annual variability in rainfall and strengthening the safety-nets either by creating opportunities for alternative sources of income or by crop diversification.

  2. Systematic identification of crystallization kinetics within a generic modelling framework

    DEFF Research Database (Denmark)

    Abdul Samad, Noor Asma Fazli Bin; Meisler, Kresten Troelstrup; Gernaey, Krist

    2012-01-01

    A systematic development of constitutive models within a generic modelling framework has been developed for use in design, analysis and simulation of crystallization operations. The framework contains a tool for model identification connected with a generic crystallizer modelling tool-box, a tool...

  3. HMMBinder: DNA-Binding Protein Prediction Using HMM Profile Based Features.

    Science.gov (United States)

    Zaman, Rianon; Chowdhury, Shahana Yasmin; Rashid, Mahmood A; Sharma, Alok; Dehzangi, Abdollah; Shatabda, Swakkhar

    2017-01-01

    DNA-binding proteins often play important role in various processes within the cell. Over the last decade, a wide range of classification algorithms and feature extraction techniques have been used to solve this problem. In this paper, we propose a novel DNA-binding protein prediction method called HMMBinder. HMMBinder uses monogram and bigram features extracted from the HMM profiles of the protein sequences. To the best of our knowledge, this is the first application of HMM profile based features for the DNA-binding protein prediction problem. We applied Support Vector Machines (SVM) as a classification technique in HMMBinder. Our method was tested on standard benchmark datasets. We experimentally show that our method outperforms the state-of-the-art methods found in the literature.

  4. HMMBinder: DNA-Binding Protein Prediction Using HMM Profile Based Features

    Directory of Open Access Journals (Sweden)

    Rianon Zaman

    2017-01-01

    Full Text Available DNA-binding proteins often play important role in various processes within the cell. Over the last decade, a wide range of classification algorithms and feature extraction techniques have been used to solve this problem. In this paper, we propose a novel DNA-binding protein prediction method called HMMBinder. HMMBinder uses monogram and bigram features extracted from the HMM profiles of the protein sequences. To the best of our knowledge, this is the first application of HMM profile based features for the DNA-binding protein prediction problem. We applied Support Vector Machines (SVM as a classification technique in HMMBinder. Our method was tested on standard benchmark datasets. We experimentally show that our method outperforms the state-of-the-art methods found in the literature.

  5. Development of TTS Engine for Indian Accent using Modified HMM Algorithm

    Directory of Open Access Journals (Sweden)

    Sasanko Sekhar Gantayat

    2018-03-01

    Full Text Available A text-to-speech (TTS system converts normal language text into speech. An intelligent text-to-speech program allows people with visual impairments or reading disabilities, to listen to written works on a home computer. Many computer operating systems and day to day software applications like Adobe Reader have included text-to-speech systems. This paper is presented to show that how HMM can be used as a tool to convert text to speech.

  6. Research study on harmonized molecular materials (HMM); Bunshi kyocho zairyo ni kansuru chosa kenkyu

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1997-03-01

    As functional material to satisfy various needs for environmental harmonization and efficient conversion for information-oriented and aging societies, HMM were surveyed. Living bodies effectively carry out transmission/processing of information, and transport/conversion of substances, and these functions are based on harmonization between organic molecules, and between those and metal or inorganic ones. HMM is a key substance to artificially realize these bio-related functions. Its R & D aims at (1) Making a breakthrough in production process based on innovation of material separation/conversion technology, (2) Contribution to an information-oriented society by high-efficiency devices, and (3) Growth of a functional bio-material industry. HMM is classified into three categories: (1) Assembly materials such as organic ultra-thin films (LB film, self-organizing film), and organic/inorganic hybrid materials for optoelectronics, sensors and devices, (2) Mesophase materials such as functional separation membrane and photo-conductive material, and (3) Microporous materials such as synthetic catalyst using guest/host materials. 571 refs., 88 figs., 21 tabs.

  7. Business model framework applications in health care: A systematic review.

    Science.gov (United States)

    Fredriksson, Jens Jacob; Mazzocato, Pamela; Muhammed, Rafiq; Savage, Carl

    2017-11-01

    It has proven to be a challenge for health care organizations to achieve the Triple Aim. In the business literature, business model frameworks have been used to understand how organizations are aligned to achieve their goals. We conducted a systematic literature review with an explanatory synthesis approach to understand how business model frameworks have been applied in health care. We found a large increase in applications of business model frameworks during the last decade. E-health was the most common context of application. We identified six applications of business model frameworks: business model description, financial assessment, classification based on pre-defined typologies, business model analysis, development, and evaluation. Our synthesis suggests that the choice of business model framework and constituent elements should be informed by the intent and context of application. We see a need for harmonization in the choice of elements in order to increase generalizability, simplify application, and help organizations realize the Triple Aim.

  8. LAMMPS Framework for Dynamic Bonding and an Application Modeling DNA

    DEFF Research Database (Denmark)

    Svaneborg, Carsten

    2012-01-01

    and bond types. When breaking bonds, all angular and dihedral interactions involving broken bonds are removed. The framework allows chemical reactions to be modeled, and use it to simulate a simplistic, coarse-grained DNA model. The resulting DNA dynamics illustrates the power of the present framework....

  9. A qualitative evaluation approach for energy system modelling frameworks

    DEFF Research Database (Denmark)

    Wiese, Frauke; Hilpert, Simon; Kaldemeyer, Cord

    2018-01-01

    properties define how useful it is in regard to the existing challenges. For energy system models, evaluation methods exist, but we argue that many decisions upon properties are rather made on the model generator or framework level. Thus, this paper presents a qualitative approach to evaluate frameworks...

  10. A Framework for Formal Modeling and Analysis of Organizations

    NARCIS (Netherlands)

    Jonker, C.M.; Sharpanskykh, O.; Treur, J.; P., Yolum

    2007-01-01

    A new, formal, role-based, framework for modeling and analyzing both real world and artificial organizations is introduced. It exploits static and dynamic properties of the organizational model and includes the (frequently ignored) environment. The transition is described from a generic framework of

  11. Implementation of a Tour Guide Robot System Using RFID Technology and Viterbi Algorithm-Based HMM for Speech Recognition

    Directory of Open Access Journals (Sweden)

    Neng-Sheng Pai

    2014-01-01

    Full Text Available This paper applied speech recognition and RFID technologies to develop an omni-directional mobile robot into a robot with voice control and guide introduction functions. For speech recognition, the speech signals were captured by short-time processing. The speaker first recorded the isolated words for the robot to create speech database of specific speakers. After the speech pre-processing of this speech database, the feature parameters of cepstrum and delta-cepstrum were obtained using linear predictive coefficient (LPC. Then, the Hidden Markov Model (HMM was used for model training of the speech database, and the Viterbi algorithm was used to find an optimal state sequence as the reference sample for speech recognition. The trained reference model was put into the industrial computer on the robot platform, and the user entered the isolated words to be tested. After processing by the same reference model and comparing with previous reference model, the path of the maximum total probability in various models found using the Viterbi algorithm in the recognition was the recognition result. Finally, the speech recognition and RFID systems were achieved in an actual environment to prove its feasibility and stability, and implemented into the omni-directional mobile robot.

  12. HMM Adaptation for Improving a Human Activity Recognition System

    Directory of Open Access Journals (Sweden)

    Rubén San-Segundo

    2016-09-01

    Full Text Available When developing a fully automatic system for evaluating motor activities performed by a person, it is necessary to segment and recognize the different activities in order to focus the analysis. This process must be carried out by a Human Activity Recognition (HAR system. This paper proposes a user adaptation technique for improving a HAR system based on Hidden Markov Models (HMMs. This system segments and recognizes six different physical activities (walking, walking upstairs, walking downstairs, sitting, standing and lying down using inertial signals from a smartphone. The system is composed of a feature extractor for obtaining the most relevant characteristics from the inertial signals, a module for training the six HMMs (one per activity, and the last module for segmenting new activity sequences using these models. The user adaptation technique consists of a Maximum A Posteriori (MAP approach that adapts the activity HMMs to the user, using some activity examples from this specific user. The main results on a public dataset have reported a significant relative error rate reduction of more than 30%. In conclusion, adapting a HAR system to the user who is performing the physical activities provides significant improvement in the system’s performance.

  13. Population Balance Models: A useful complementary modelling framework for future WWTP modelling

    DEFF Research Database (Denmark)

    Nopens, Ingmar; Torfs, Elena; Ducoste, Joel

    2014-01-01

    Population Balance Models (PBMs) represent a powerful modelling framework for the description of the dynamics of properties that are characterised by statistical distributions. This has been demonstrated in many chemical engineering applications. Modelling efforts of several current and future unit...

  14. Population balance models: a useful complementary modelling framework for future WWTP modelling

    DEFF Research Database (Denmark)

    Nopens, Ingmar; Torfs, Elena; Ducoste, Joel

    2015-01-01

    Population balance models (PBMs) represent a powerful modelling framework for the description of the dynamics of properties that are characterised by distributions. This distribution of properties under transient conditions has been demonstrated in many chemical engineering applications. Modelling...

  15. A Simulation and Modeling Framework for Space Situational Awareness

    International Nuclear Information System (INIS)

    Olivier, S.S.

    2008-01-01

    This paper describes the development and initial demonstration of a new, integrated modeling and simulation framework, encompassing the space situational awareness enterprise, for quantitatively assessing the benefit of specific sensor systems, technologies and data analysis techniques. The framework is based on a flexible, scalable architecture to enable efficient, physics-based simulation of the current SSA enterprise, and to accommodate future advancements in SSA systems. In particular, the code is designed to take advantage of massively parallel computer systems available, for example, at Lawrence Livermore National Laboratory. The details of the modeling and simulation framework are described, including hydrodynamic models of satellite intercept and debris generation, orbital propagation algorithms, radar cross section calculations, optical brightness calculations, generic radar system models, generic optical system models, specific Space Surveillance Network models, object detection algorithms, orbit determination algorithms, and visualization tools. The use of this integrated simulation and modeling framework on a specific scenario involving space debris is demonstrated

  16. Conceptualising Business Models: Definitions, Frameworks and Classifications

    OpenAIRE

    Erwin Fielt

    2013-01-01

    The business model concept is gaining traction in different disciplines but is still criticized for being fuzzy and vague and lacking consensus on its definition and compositional elements. In this paper we set out to advance our understanding of the business model concept by addressing three areas of foundational research: business model definitions, business model elements, and business model archetypes. We define a business model as a representation of the value logic of an organization in...

  17. Generic Model Predictive Control Framework for Advanced Driver Assistance Systems

    NARCIS (Netherlands)

    Wang, M.

    2014-01-01

    This thesis deals with a model predictive control framework for control design of Advanced Driver Assistance Systems, where car-following tasks are under control. The framework is applied to design several autonomous and cooperative controllers and to examine the controller properties at the

  18. A Modeling Framework for Conventional and Heat Integrated Distillation Columns

    DEFF Research Database (Denmark)

    Bisgaard, Thomas; Huusom, Jakob Kjøbsted; Abildskov, Jens

    2013-01-01

    In this paper, a generic, modular model framework for describing fluid separation by distillation is presented. At present, the framework is able to describe a conventional distillation column and a heat-integrated distillation column, but due to a modular structure the database can be further...

  19. A DSM-based framework for integrated function modelling

    DEFF Research Database (Denmark)

    Eisenbart, Boris; Gericke, Kilian; Blessing, Lucienne T. M.

    2017-01-01

    an integrated function modelling framework, which specifically aims at relating between the different function modelling perspectives prominently addressed in different disciplines. It uses interlinked matrices based on the concept of DSM and MDM in order to facilitate cross-disciplinary modelling and analysis...... of the functionality of a system. The article further presents the application of the framework based on a product example. Finally, an empirical study in industry is presented. Therein, feedback on the potential of the proposed framework to support interdisciplinary design practice as well as on areas of further...

  20. Conceptualising Business Models: Definitions, Frameworks and Classifications

    Directory of Open Access Journals (Sweden)

    Erwin Fielt

    2013-12-01

    Full Text Available The business model concept is gaining traction in different disciplines but is still criticized for being fuzzy and vague and lacking consensus on its definition and compositional elements. In this paper we set out to advance our understanding of the business model concept by addressing three areas of foundational research: business model definitions, business model elements, and business model archetypes. We define a business model as a representation of the value logic of an organization in terms of how it creates and captures customer value. This abstract and generic definition is made more specific and operational by the compositional elements that need to address the customer, value proposition, organizational architecture (firm and network level and economics dimensions. Business model archetypes complement the definition and elements by providing a more concrete and empirical understanding of the business model concept. The main contributions of this paper are (1 explicitly including the customer value concept in the business model definition and focussing on value creation, (2 presenting four core dimensions that business model elements need to cover, (3 arguing for flexibility by adapting and extending business model elements to cater for different purposes and contexts (e.g. technology, innovation, strategy (4 stressing a more systematic approach to business model archetypes by using business model elements for their description, and (5 suggesting to use business model archetype research for the empirical exploration and testing of business model elements and their relationships.

  1. HMM-based lexicon-driven and lexicon-free word recognition for online handwritten Indic scripts.

    Science.gov (United States)

    Bharath, A; Madhvanath, Sriganesh

    2012-04-01

    Research for recognizing online handwritten words in Indic scripts is at its early stages when compared to Latin and Oriental scripts. In this paper, we address this problem specifically for two major Indic scripts--Devanagari and Tamil. In contrast to previous approaches, the techniques we propose are largely data driven and script independent. We propose two different techniques for word recognition based on Hidden Markov Models (HMM): lexicon driven and lexicon free. The lexicon-driven technique models each word in the lexicon as a sequence of symbol HMMs according to a standard symbol writing order derived from the phonetic representation. The lexicon-free technique uses a novel Bag-of-Symbols representation of the handwritten word that is independent of symbol order and allows rapid pruning of the lexicon. On handwritten Devanagari word samples featuring both standard and nonstandard symbol writing orders, a combination of lexicon-driven and lexicon-free recognizers significantly outperforms either of them used in isolation. In contrast, most Tamil word samples feature the standard symbol order, and the lexicon-driven recognizer outperforms the lexicon free one as well as their combination. The best recognition accuracies obtained for 20,000 word lexicons are 87.13 percent for Devanagari when the two recognizers are combined, and 91.8 percent for Tamil using the lexicon-driven technique.

  2. Theoretical Models, Assessment Frameworks and Test Construction.

    Science.gov (United States)

    Chalhoub-Deville, Micheline

    1997-01-01

    Reviews the usefulness of proficiency models influencing second language testing. Findings indicate that several factors contribute to the lack of congruence between models and test construction and make a case for distinguishing between theoretical models. Underscores the significance of an empirical, contextualized and structured approach to the…

  3. POSITIVE LEADERSHIP MODELS: THEORETICAL FRAMEWORK AND RESEARCH

    Directory of Open Access Journals (Sweden)

    Javier Blanch, Francisco Gil

    2016-09-01

    Full Text Available The objective of this article is twofold; firstly, we establish the theoretical boundaries of positive leadership and the reasons for its emergence. It is related to the new paradigm of positive psychology that has recently been shaping the scope of organizational knowledge. This conceptual framework has triggered the development of the various forms of positive leadership (i.e. transformational, servant, spiritual, authentic, and positive. Although the construct does not seem univocally defined, these different types of leadership overlap and share a significant affinity. Secondly, we review the empirical evidence that shows the impact of positive leadership in organizations and we highlight the positive relationship between these forms of leadership and key positive organizational variables. Lastly, we analyse future research areas in order to further develop this concept.

  4. Koopman Operator Framework for Time Series Modeling and Analysis

    Science.gov (United States)

    Surana, Amit

    2018-01-01

    We propose an interdisciplinary framework for time series classification, forecasting, and anomaly detection by combining concepts from Koopman operator theory, machine learning, and linear systems and control theory. At the core of this framework is nonlinear dynamic generative modeling of time series using the Koopman operator which is an infinite-dimensional but linear operator. Rather than working with the underlying nonlinear model, we propose two simpler linear representations or model forms based on Koopman spectral properties. We show that these model forms are invariants of the generative model and can be readily identified directly from data using techniques for computing Koopman spectral properties without requiring the explicit knowledge of the generative model. We also introduce different notions of distances on the space of such model forms which is essential for model comparison/clustering. We employ the space of Koopman model forms equipped with distance in conjunction with classical machine learning techniques to develop a framework for automatic feature generation for time series classification. The forecasting/anomaly detection framework is based on using Koopman model forms along with classical linear systems and control approaches. We demonstrate the proposed framework for human activity classification, and for time series forecasting/anomaly detection in power grid application.

  5. Video event classification and image segmentation based on noncausal multidimensional hidden Markov models.

    Science.gov (United States)

    Ma, Xiang; Schonfeld, Dan; Khokhar, Ashfaq A

    2009-06-01

    In this paper, we propose a novel solution to an arbitrary noncausal, multidimensional hidden Markov model (HMM) for image and video classification. First, we show that the noncausal model can be solved by splitting it into multiple causal HMMs and simultaneously solving each causal HMM using a fully synchronous distributed computing framework, therefore referred to as distributed HMMs. Next we present an approximate solution to the multiple causal HMMs that is based on an alternating updating scheme and assumes a realistic sequential computing framework. The parameters of the distributed causal HMMs are estimated by extending the classical 1-D training and classification algorithms to multiple dimensions. The proposed extension to arbitrary causal, multidimensional HMMs allows state transitions that are dependent on all causal neighbors. We, thus, extend three fundamental algorithms to multidimensional causal systems, i.e., 1) expectation-maximization (EM), 2) general forward-backward (GFB), and 3) Viterbi algorithms. In the simulations, we choose to limit ourselves to a noncausal 2-D model whose noncausality is along a single dimension, in order to significantly reduce the computational complexity. Simulation results demonstrate the superior performance, higher accuracy rate, and applicability of the proposed noncausal HMM framework to image and video classification.

  6. A conceptual framework for measuring airline business model convergence

    OpenAIRE

    Daft, Jost; Albers, Sascha

    2012-01-01

    This paper develops a measurement framework that synthesizes the airline and strategy literature to identify relevant dimensions and elements of airline business models. The applicability of this framework for describing airline strategies and structures and, based on this conceptualization, for assessing the potential convergence of airline business models over time is then illustrated using a small sample of five German passenger airlines. For this sample, the perception of a rapprochement ...

  7. Modelling framework for groundwater flow at Sellafield

    International Nuclear Information System (INIS)

    Hooper, A.J.; Billington, D.E.; Herbert, A.W.

    1995-01-01

    The principal objective of Nirex is to develop a single deep geological repository for the safe disposal of low- and intermediate-level radioactive waste. In safety assessment, use is made of a variety of conceptual models that form the basis for modelling of the pathways by which radionuclides might return to the environment. In this paper, the development of a conceptual model for groundwater flow and transport through fractured rock on the various scales of interest is discussed. The approach is illustrated by considering how some aspects of the conceptual model are developed in particular numerical models. These representations of the conceptual model use fracture network geometries based on realistic rock properties. (author). refs., figs., tabs

  8. Geolocating fish using Hidden Markov Models and Data Storage Tags

    DEFF Research Database (Denmark)

    Thygesen, Uffe Høgsbro; Pedersen, Martin Wæver; Madsen, Henrik

    2009-01-01

    Geolocation of fish based on data from archival tags typically requires a statistical analysis to reduce the effect of measurement errors. In this paper we present a novel technique for this analysis, one based on Hidden Markov Models (HMM's). We assume that the actual path of the fish is generated...... by a biased random walk. The HMM methodology produces, for each time step, the probability that the fish resides in each grid cell. Because there is no Monte Carlo step in our technique, we are able to estimate parameters within the likelihood framework. The method does not require the distribution...... of inference in state-space models of animals. The technique can be applied to geolocation based on light, on tidal patterns, or measurement of other variables that vary with space. We illustrate the method through application to a simulated data set where geolocation relies on depth data exclusively....

  9. zipHMMlib: a highly optimised HMM library exploiting repetitions in the input to speed up the forward algorithm.

    Science.gov (United States)

    Sand, Andreas; Kristiansen, Martin; Pedersen, Christian N S; Mailund, Thomas

    2013-11-22

    Hidden Markov models are widely used for genome analysis as they combine ease of modelling with efficient analysis algorithms. Calculating the likelihood of a model using the forward algorithm has worst case time complexity linear in the length of the sequence and quadratic in the number of states in the model. For genome analysis, however, the length runs to millions or billions of observations, and when maximising the likelihood hundreds of evaluations are often needed. A time efficient forward algorithm is therefore a key ingredient in an efficient hidden Markov model library. We have built a software library for efficiently computing the likelihood of a hidden Markov model. The library exploits commonly occurring substrings in the input to reuse computations in the forward algorithm. In a pre-processing step our library identifies common substrings and builds a structure over the computations in the forward algorithm which can be reused. This analysis can be saved between uses of the library and is independent of concrete hidden Markov models so one preprocessing can be used to run a number of different models.Using this library, we achieve up to 78 times shorter wall-clock time for realistic whole-genome analyses with a real and reasonably complex hidden Markov model. In one particular case the analysis was performed in less than 8 minutes compared to 9.6 hours for the previously fastest library. We have implemented the preprocessing procedure and forward algorithm as a C++ library, zipHMM, with Python bindings for use in scripts. The library is available at http://birc.au.dk/software/ziphmm/.

  10. Multilevel Models: Conceptual Framework and Applicability

    Directory of Open Access Journals (Sweden)

    Roxana-Otilia-Sonia Hrițcu

    2015-10-01

    Full Text Available Individuals and the social or organizational groups they belong to can be viewed as a hierarchical system situated on different levels. Individuals are situated on the first level of the hierarchy and they are nested together on the higher levels. Individuals interact with the social groups they belong to and are influenced by these groups. Traditional methods that study the relationships between data, like simple regression, do not take into account the hierarchical structure of the data and the effects of a group membership and, hence, results may be invalidated. Unlike standard regression modelling, the multilevel approach takes into account the individuals as well as the groups to which they belong. To take advantage of the multilevel analysis it is important that we recognize the multilevel characteristics of the data. In this article we introduce the outlines of multilevel data and we describe the models that work with such data. We introduce the basic multilevel model, the two-level model: students can be nested into classes, individuals into countries and the general two-level model can be extended very easily to several levels. Multilevel analysis has begun to be extensively used in many research areas. We present the most frequent study areas where multilevel models are used, such as sociological studies, education, psychological research, health studies, demography, epidemiology, biology, environmental studies and entrepreneurship. We support the idea that since hierarchies exist everywhere, multilevel data should be recognized and analyzed properly by using multilevel modelling.

  11. An Ising model for metal-organic frameworks

    Science.gov (United States)

    Höft, Nicolas; Horbach, Jürgen; Martín-Mayor, Victor; Seoane, Beatriz

    2017-08-01

    We present a three-dimensional Ising model where lines of equal spins are frozen such that they form an ordered framework structure. The frame spins impose an external field on the rest of the spins (active spins). We demonstrate that this "porous Ising model" can be seen as a minimal model for condensation transitions of gas molecules in metal-organic frameworks. Using Monte Carlo simulation techniques, we compare the phase behavior of a porous Ising model with that of a particle-based model for the condensation of methane (CH4) in the isoreticular metal-organic framework IRMOF-16. For both models, we find a line of first-order phase transitions that end in a critical point. We show that the critical behavior in both cases belongs to the 3D Ising universality class, in contrast to other phase transitions in confinement such as capillary condensation.

  12. Mediation Analysis in a Latent Growth Curve Modeling Framework

    Science.gov (United States)

    von Soest, Tilmann; Hagtvet, Knut A.

    2011-01-01

    This article presents several longitudinal mediation models in the framework of latent growth curve modeling and provides a detailed account of how such models can be constructed. Logical and statistical challenges that might arise when such analyses are conducted are also discussed. Specifically, we discuss how the initial status (intercept) and…

  13. Theories and Frameworks for Online Education: Seeking an Integrated Model

    Science.gov (United States)

    Picciano, Anthony G.

    2017-01-01

    This article examines theoretical frameworks and models that focus on the pedagogical aspects of online education. After a review of learning theory as applied to online education, a proposal for an integrated "Multimodal Model for Online Education" is provided based on pedagogical purpose. The model attempts to integrate the work of…

  14. Real time natural object modeling framework

    International Nuclear Information System (INIS)

    Rana, H.A.; Shamsuddin, S.M.; Sunar, M.H.

    2008-01-01

    CG (Computer Graphics) is a key technology for producing visual contents. Currently computer generated imagery techniques are being developed and applied, particularly in the field of virtual reality applications, film production, training and flight simulators, to provide total composition of realistic computer graphic images. Natural objects like clouds are an integral feature of the sky without them synthetic outdoor scenes seem unrealistic. Modeling and animating such objects is a difficult task. Most systems are difficult to use, as they require adjustment of numerous, complex parameters and are non-interactive. This paper presents an intuitive, interactive system to artistically model, animate, and render visually convincing clouds using modern graphics hardware. A high-level interface models clouds through the visual use of cubes. Clouds are rendered by making use of hardware accelerated API -OpenGL. The resulting interactive design and rendering system produces perceptually convincing cloud models that can be used in any interactive system. (author)

  15. Cytoview: Development of a cell modelling framework

    Indian Academy of Sciences (India)

    PRAKASH KUMAR

    is an important aspect of cell modelling. ... 1Supercomputer Education and Research Centreand 2Bioinformatics Centre, Indian Institute ... Important aspects in each panel are listed. ... subsumption relationship, in which the child term is a more.

  16. An Efficient Algorithm for Modelling Duration in Hidden Markov Models, with a Dramatic Application

    DEFF Research Database (Denmark)

    Hauberg, Søren; Sloth, Jakob

    2008-01-01

    For many years, the hidden Markov model (HMM) has been one of the most popular tools for analysing sequential data. One frequently used special case is the left-right model, in which the order of the hidden states is known. If knowledge of the duration of a state is available it is not possible...... to represent it explicitly with an HMM. Methods for modelling duration with HMM's do exist (Rabiner in Proc. IEEE 77(2):257---286, [1989]), but they come at the price of increased computational complexity. Here we present an efficient and robust algorithm for modelling duration in HMM's, and this algorithm...

  17. Fisher information framework for time series modeling

    Science.gov (United States)

    Venkatesan, R. C.; Plastino, A.

    2017-08-01

    A robust prediction model invoking the Takens embedding theorem, whose working hypothesis is obtained via an inference procedure based on the minimum Fisher information principle, is presented. The coefficients of the ansatz, central to the working hypothesis satisfy a time independent Schrödinger-like equation in a vector setting. The inference of (i) the probability density function of the coefficients of the working hypothesis and (ii) the establishing of constraint driven pseudo-inverse condition for the modeling phase of the prediction scheme, is made, for the case of normal distributions, with the aid of the quantum mechanical virial theorem. The well-known reciprocity relations and the associated Legendre transform structure for the Fisher information measure (FIM, hereafter)-based model in a vector setting (with least square constraints) are self-consistently derived. These relations are demonstrated to yield an intriguing form of the FIM for the modeling phase, which defines the working hypothesis, solely in terms of the observed data. Cases for prediction employing time series' obtained from the: (i) the Mackey-Glass delay-differential equation, (ii) one ECG signal from the MIT-Beth Israel Deaconess Hospital (MIT-BIH) cardiac arrhythmia database, and (iii) one ECG signal from the Creighton University ventricular tachyarrhythmia database. The ECG samples were obtained from the Physionet online repository. These examples demonstrate the efficiency of the prediction model. Numerical examples for exemplary cases are provided.

  18. A Conceptual Framework of Business Model Emerging Resilience

    OpenAIRE

    Goumagias, Nik; Fernandes, Kiran; Cabras, Ignazio; Li, Feng; Shao, Jianhao; Devlin, Sam; Hodge, Victoria Jane; Cowling, Peter Ivan; Kudenko, Daniel

    2016-01-01

    In this paper we introduce an environmentally driven conceptual framework of Business Model change. Business models acquired substantial momentum in academic literature during the past decade. Several studies focused on what exactly constitutes a Business Model (role model, recipe, architecture etc.) triggering a theoretical debate about the Business Model’s components and their corresponding dynamics and relationships. In this paper, we argue that for Business Models as cognitive structures,...

  19. A general modeling framework for describing spatially structured population dynamics

    Science.gov (United States)

    Sample, Christine; Fryxell, John; Bieri, Joanna; Federico, Paula; Earl, Julia; Wiederholt, Ruscena; Mattsson, Brady; Flockhart, Tyler; Nicol, Sam; Diffendorfer, James E.; Thogmartin, Wayne E.; Erickson, Richard A.; Norris, D. Ryan

    2017-01-01

    Variation in movement across time and space fundamentally shapes the abundance and distribution of populations. Although a variety of approaches model structured population dynamics, they are limited to specific types of spatially structured populations and lack a unifying framework. Here, we propose a unified network-based framework sufficiently novel in its flexibility to capture a wide variety of spatiotemporal processes including metapopulations and a range of migratory patterns. It can accommodate different kinds of age structures, forms of population growth, dispersal, nomadism and migration, and alternative life-history strategies. Our objective was to link three general elements common to all spatially structured populations (space, time and movement) under a single mathematical framework. To do this, we adopt a network modeling approach. The spatial structure of a population is represented by a weighted and directed network. Each node and each edge has a set of attributes which vary through time. The dynamics of our network-based population is modeled with discrete time steps. Using both theoretical and real-world examples, we show how common elements recur across species with disparate movement strategies and how they can be combined under a unified mathematical framework. We illustrate how metapopulations, various migratory patterns, and nomadism can be represented with this modeling approach. We also apply our network-based framework to four organisms spanning a wide range of life histories, movement patterns, and carrying capacities. General computer code to implement our framework is provided, which can be applied to almost any spatially structured population. This framework contributes to our theoretical understanding of population dynamics and has practical management applications, including understanding the impact of perturbations on population size, distribution, and movement patterns. By working within a common framework, there is less chance

  20. A proposed best practice model validation framework for banks

    Directory of Open Access Journals (Sweden)

    Pieter J. (Riaan de Jongh

    2017-06-01

    Full Text Available Background: With the increasing use of complex quantitative models in applications throughout the financial world, model risk has become a major concern. The credit crisis of 2008–2009 provoked added concern about the use of models in finance. Measuring and managing model risk has subsequently come under scrutiny from regulators, supervisors, banks and other financial institutions. Regulatory guidance indicates that meticulous monitoring of all phases of model development and implementation is required to mitigate this risk. Considerable resources must be mobilised for this purpose. The exercise must embrace model development, assembly, implementation, validation and effective governance. Setting: Model validation practices are generally patchy, disparate and sometimes contradictory, and although the Basel Accord and some regulatory authorities have attempted to establish guiding principles, no definite set of global standards exists. Aim: Assessing the available literature for the best validation practices. Methods: This comprehensive literature study provided a background to the complexities of effective model management and focussed on model validation as a component of model risk management. Results: We propose a coherent ‘best practice’ framework for model validation. Scorecard tools are also presented to evaluate if the proposed best practice model validation framework has been adequately assembled and implemented. Conclusion: The proposed best practice model validation framework is designed to assist firms in the construction of an effective, robust and fully compliant model validation programme and comprises three principal elements: model validation governance, policy and process.

  1. Theoretical Tinnitus framework: A Neurofunctional Model

    Directory of Open Access Journals (Sweden)

    Iman Ghodratitoostani

    2016-08-01

    Full Text Available Subjective tinnitus is the conscious (attended awareness perception of sound in the absence of an external source and can be classified as an auditory phantom perception. The current tinnitus development models depend on the role of external events congruently paired with the causal physical events that precipitate the phantom perception. We propose a novel Neurofunctional tinnitus model to indicate that the conscious perception of phantom sound is essential in activating the cognitive-emotional value. The cognitive-emotional value plays a crucial role in governing attention allocation as well as developing annoyance within tinnitus clinical distress. Structurally, the Neurofunctional tinnitus model includes the peripheral auditory system, the thalamus, the limbic system, brain stem, basal ganglia, striatum and the auditory along with prefrontal cortices. Functionally, we assume the model includes presence of continuous or intermittent abnormal signals at the peripheral auditory system or midbrain auditory paths. Depending on the availability of attentional resources, the signals may or may not be perceived. The cognitive valuation process strengthens the lateral-inhibition and noise canceling mechanisms in the mid-brain, which leads to the cessation of sound perception and renders the signal evaluation irrelevant. However, the sourceless sound is eventually perceived and can be cognitively interpreted as suspicious or an indication of a disease in which the cortical top-down processes weaken the noise canceling effects. This results in an increase in cognitive and emotional negative reactions such as depression and anxiety. The negative or positive cognitive-emotional feedbacks within the top-down approach may have no relation to the previous experience of the patients. They can also be associated with aversive stimuli similar to abnormal neural activity in generating the phantom sound. Cognitive and emotional reactions depend on general

  2. Theoretical Tinnitus Framework: A Neurofunctional Model.

    Science.gov (United States)

    Ghodratitoostani, Iman; Zana, Yossi; Delbem, Alexandre C B; Sani, Siamak S; Ekhtiari, Hamed; Sanchez, Tanit G

    2016-01-01

    Subjective tinnitus is the conscious (attended) awareness perception of sound in the absence of an external source and can be classified as an auditory phantom perception. Earlier literature establishes three distinct states of conscious perception as unattended, attended, and attended awareness conscious perception. The current tinnitus development models depend on the role of external events congruently paired with the causal physical events that precipitate the phantom perception. We propose a novel Neurofunctional Tinnitus Model to indicate that the conscious (attended) awareness perception of phantom sound is essential in activating the cognitive-emotional value. The cognitive-emotional value plays a crucial role in governing attention allocation as well as developing annoyance within tinnitus clinical distress. Structurally, the Neurofunctional Tinnitus Model includes the peripheral auditory system, the thalamus, the limbic system, brainstem, basal ganglia, striatum, and the auditory along with prefrontal cortices. Functionally, we assume the model includes presence of continuous or intermittent abnormal signals at the peripheral auditory system or midbrain auditory paths. Depending on the availability of attentional resources, the signals may or may not be perceived. The cognitive valuation process strengthens the lateral-inhibition and noise canceling mechanisms in the mid-brain, which leads to the cessation of sound perception and renders the signal evaluation irrelevant. However, the "sourceless" sound is eventually perceived and can be cognitively interpreted as suspicious or an indication of a disease in which the cortical top-down processes weaken the noise canceling effects. This results in an increase in cognitive and emotional negative reactions such as depression and anxiety. The negative or positive cognitive-emotional feedbacks within the top-down approach may have no relation to the previous experience of the patients. They can also be

  3. A Framework for PSS Business Models: Formalization and Application

    OpenAIRE

    Adrodegari, Federico; Saccani, Nicola; Kowalkowski, Christian

    2016-01-01

    In order to successfully move "from products to solutions", companies need to redesign their business model. Nevertheless, service oriented BMs in product-centric firms are under-investigated in the literature: very few works develop a scheme of analysis of such BMs. To provide a first step into closing this gap, we propose a new framework to describe service-oriented BMs, pointing out the main BM components and related PSS characteristics. Thus, the proposed framework aims to help companies ...

  4. A community-based framework for aquatic ecosystem models

    DEFF Research Database (Denmark)

    Trolle, Didde; Hamilton, D. P.; Hipsey, M. R.

    2012-01-01

    Here, we communicate a point of departure in the development of aquatic ecosystem models, namely a new community-based framework, which supports an enhanced and transparent union between the collective expertise that exists in the communities of traditional ecologists and model developers. Through...... a literature survey, we document the growing importance of numerical aquatic ecosystem models while also noting the difficulties, up until now, of the aquatic scientific community to make significant advances in these models during the past two decades. Through a common forum for aquatic ecosystem modellers we...... aim to (i) advance collaboration within the aquatic ecosystem modelling community, (ii) enable increased use of models for research, policy and ecosystem-based management, (iii) facilitate a collective framework using common (standardised) code to ensure that model development is incremental, (iv...

  5. Frameworks for Assessing the Quality of Modeling and Simulation Capabilities

    Science.gov (United States)

    Rider, W. J.

    2012-12-01

    The importance of assuring quality in modeling and simulation has spawned several frameworks for structuring the examination of quality. The format and content of these frameworks provides an emphasis, completeness and flow to assessment activities. I will examine four frameworks that have been developed and describe how they can be improved and applied to a broader set of high consequence applications. Perhaps the first of these frameworks was known as CSAU [Boyack] (code scaling, applicability and uncertainty) used for nuclear reactor safety and endorsed the United States' Nuclear Regulatory Commission (USNRC). This framework was shaped by nuclear safety practice, and the practical structure needed after the Three Mile Island accident. It incorporated the dominant experimental program, the dominant analysis approach, and concerns about the quality of modeling. The USNRC gave it the force of law that made the nuclear industry take it seriously. After the cessation of nuclear weapons' testing the United States began a program of examining the reliability of these weapons without testing. This program utilizes science including theory, modeling, simulation and experimentation to replace the underground testing. The emphasis on modeling and simulation necessitated attention on the quality of these simulations. Sandia developed the PCMM (predictive capability maturity model) to structure this attention [Oberkampf]. PCMM divides simulation into six core activities to be examined and graded relative to the needs of the modeling activity. NASA [NASA] has built yet another framework in response to the tragedy of the space shuttle accidents. Finally, Ben-Haim and Hemez focus upon modeling robustness and predictive fidelity in another approach. These frameworks are similar, and applied in a similar fashion. The adoption of these frameworks at Sandia and NASA has been slow and arduous because the force of law has not assisted acceptance. All existing frameworks are

  6. Constructing rule-based models using the belief functions framework

    NARCIS (Netherlands)

    Almeida, R.J.; Denoeux, T.; Kaymak, U.; Greco, S.; Bouchon-Meunier, B.; Coletti, G.; Fedrizzi, M.; Matarazzo, B.; Yager, R.R.

    2012-01-01

    Abstract. We study a new approach to regression analysis. We propose a new rule-based regression model using the theoretical framework of belief functions. For this purpose we use the recently proposed Evidential c-means (ECM) to derive rule-based models solely from data. ECM allocates, for each

  7. Designing the Distributed Model Integration Framework – DMIF

    NARCIS (Netherlands)

    Belete, Getachew F.; Voinov, Alexey; Morales, Javier

    2017-01-01

    We describe and discuss the design and prototype of the Distributed Model Integration Framework (DMIF) that links models deployed on different hardware and software platforms. We used distributed computing and service-oriented development approaches to address the different aspects of

  8. A framework for quantifying net benefits of alternative prognostic models

    NARCIS (Netherlands)

    Rapsomaniki, E.; White, I.R.; Wood, A.M.; Thompson, S.G.; Feskens, E.J.M.; Kromhout, D.

    2012-01-01

    New prognostic models are traditionally evaluated using measures of discrimination and risk reclassification, but these do not take full account of the clinical and health economic context. We propose a framework for comparing prognostic models by quantifying the public health impact (net benefit)

  9. A Modeling Framework for Schedulability Analysis of Distributed Avionics Systems

    DEFF Research Database (Denmark)

    Han, Pujie; Zhai, Zhengjun; Nielsen, Brian

    2018-01-01

    This paper presents a modeling framework for schedulability analysis of distributed integrated modular avionics (DIMA) systems that consist of spatially distributed ARINC-653 modules connected by a unified AFDX network. We model a DIMA system as a set of stopwatch automata (SWA) in UPPAAL...

  10. Industrial Sector Energy Efficiency Modeling (ISEEM) Framework Documentation

    Energy Technology Data Exchange (ETDEWEB)

    Karali, Nihan [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Xu, Tengfang [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Sathaye, Jayant [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2012-12-12

    The goal of this study is to develop a new bottom-up industry sector energy-modeling framework with an agenda of addressing least cost regional and global carbon reduction strategies, improving the capabilities and limitations of the existing models that allows trading across regions and countries as an alternative.

  11. A community-based framework for aquatic ecosystem models

    NARCIS (Netherlands)

    Trolle, D.; Hamilton, D.P.; Hipsey, M.R.; Bolding, K.; Bruggeman, J.; Mooij, W.M.; Janse, J.H.; Nielsen, A.; Jeppesen, E.; Elliott, J.A.; Makler-Pick, V.; Petzoldt, T.; Rinke, K.; Flindt, M.R.; Arhonditsis, G.B.; Gal, G.; Bjerring, R.; Tominaga, K.; Hoen, 't J.; Downing, A.S.; Marques, D.M.; Fragoso, C.R.; Sondergaard, M.; Hanson, P.C.

    2012-01-01

    Here, we communicate a point of departure in the development of aquatic ecosystem models, namely a new community-based framework, which supports an enhanced and transparent union between the collective expertise that exists in the communities of traditional ecologists and model developers. Through a

  12. Learning effective connectivity from fMRI using autoregressive hidden Markov model with missing data.

    Science.gov (United States)

    Dang, Shilpa; Chaudhury, Santanu; Lall, Brejesh; Roy, Prasun Kumar

    2017-02-15

    Effective connectivity (EC) analysis of neuronal groups using fMRI delivers insights about functional-integration. However, fMRI signal has low-temporal resolution due to down-sampling and indirectly measures underlying neuronal activity. The aim is to address above issues for more reliable EC estimates. This paper proposes use of autoregressive hidden Markov model with missing data (AR-HMM-md) in dynamically multi-linked (DML) framework for learning EC using multiple fMRI time series. In our recent work (Dang et al., 2016), we have shown how AR-HMM-md for modelling single fMRI time series outperforms the existing methods. AR-HMM-md models unobserved neuronal activity and lost data over time as variables and estimates their values by joint optimization given fMRI observation sequence. The effectiveness in learning EC is shown using simulated experiments. Also the effects of sampling and noise are studied on EC. Moreover, classification-experiments are performed for Attention-Deficit/Hyperactivity Disorder subjects and age-matched controls for performance evaluation of real data. Using Bayesian model selection, we see that the proposed model converged to higher log-likelihood and demonstrated that group-classification can be performed with higher cross-validation accuracy of above 94% using distinctive network EC which characterizes patients vs. The full data EC obtained from DML-AR-HMM-md is more consistent with previous literature than the classical multivariate Granger causality method. The proposed architecture leads to reliable estimates of EC than the existing latent models. This framework overcomes the disadvantage of low-temporal resolution and improves cross-validation accuracy significantly due to presence of missing data variables and autoregressive process. Copyright © 2016 Elsevier B.V. All rights reserved.

  13. An Integrated Framework to Specify Domain-Specific Modeling Languages

    DEFF Research Database (Denmark)

    Zarrin, Bahram; Baumeister, Hubert

    2018-01-01

    , a logic-based specification language. The drawback of MS DSL Tools is it does not provide a formal and rigorous approach for semantics specifications. In this framework, we use Microsoft DSL Tools to define the metamodel and graphical notations of DSLs, and an extended version of ForSpec as a formal......In this paper, we propose an integrated framework that can be used by DSL designers to implement their desired graphical domain-specific languages. This framework relies on Microsoft DSL Tools, a meta-modeling framework to build graphical domain-specific languages, and an extension of ForSpec...... language to define their semantics. Integrating these technologies under the umbrella of Microsoft Visual Studio IDE allows DSL designers to utilize a single development environment for developing their desired domain-specific languages....

  14. A software engineering perspective on environmental modeling framework design: The object modeling system

    Science.gov (United States)

    The environmental modeling community has historically been concerned with the proliferation of models and the effort associated with collective model development tasks (e.g., code generation, data provisioning and transformation, etc.). Environmental modeling frameworks (EMFs) have been developed to...

  15. Automatic Model Generation Framework for Computational Simulation of Cochlear Implantation

    DEFF Research Database (Denmark)

    Mangado Lopez, Nerea; Ceresa, Mario; Duchateau, Nicolas

    2016-01-01

    . To address such a challenge, we propose an automatic framework for the generation of patient-specific meshes for finite element modeling of the implanted cochlea. First, a statistical shape model is constructed from high-resolution anatomical μCT images. Then, by fitting the statistical model to a patient......'s CT image, an accurate model of the patient-specific cochlea anatomy is obtained. An algorithm based on the parallel transport frame is employed to perform the virtual insertion of the cochlear implant. Our automatic framework also incorporates the surrounding bone and nerve fibers and assigns......Recent developments in computational modeling of cochlear implantation are promising to study in silico the performance of the implant before surgery. However, creating a complete computational model of the patient's anatomy while including an external device geometry remains challenging...

  16. A Bayesian framework for parameter estimation in dynamical models.

    Directory of Open Access Journals (Sweden)

    Flávio Codeço Coelho

    Full Text Available Mathematical models in biology are powerful tools for the study and exploration of complex dynamics. Nevertheless, bringing theoretical results to an agreement with experimental observations involves acknowledging a great deal of uncertainty intrinsic to our theoretical representation of a real system. Proper handling of such uncertainties is key to the successful usage of models to predict experimental or field observations. This problem has been addressed over the years by many tools for model calibration and parameter estimation. In this article we present a general framework for uncertainty analysis and parameter estimation that is designed to handle uncertainties associated with the modeling of dynamic biological systems while remaining agnostic as to the type of model used. We apply the framework to fit an SIR-like influenza transmission model to 7 years of incidence data in three European countries: Belgium, the Netherlands and Portugal.

  17. Automatic Model Generation Framework for Computational Simulation of Cochlear Implantation.

    Science.gov (United States)

    Mangado, Nerea; Ceresa, Mario; Duchateau, Nicolas; Kjer, Hans Martin; Vera, Sergio; Dejea Velardo, Hector; Mistrik, Pavel; Paulsen, Rasmus R; Fagertun, Jens; Noailly, Jérôme; Piella, Gemma; González Ballester, Miguel Ángel

    2016-08-01

    Recent developments in computational modeling of cochlear implantation are promising to study in silico the performance of the implant before surgery. However, creating a complete computational model of the patient's anatomy while including an external device geometry remains challenging. To address such a challenge, we propose an automatic framework for the generation of patient-specific meshes for finite element modeling of the implanted cochlea. First, a statistical shape model is constructed from high-resolution anatomical μCT images. Then, by fitting the statistical model to a patient's CT image, an accurate model of the patient-specific cochlea anatomy is obtained. An algorithm based on the parallel transport frame is employed to perform the virtual insertion of the cochlear implant. Our automatic framework also incorporates the surrounding bone and nerve fibers and assigns constitutive parameters to all components of the finite element model. This model can then be used to study in silico the effects of the electrical stimulation of the cochlear implant. Results are shown on a total of 25 models of patients. In all cases, a final mesh suitable for finite element simulations was obtained, in an average time of 94 s. The framework has proven to be fast and robust, and is promising for a detailed prognosis of the cochlear implantation surgery.

  18. Modeling of ultrasonic processes utilizing a generic software framework

    Science.gov (United States)

    Bruns, P.; Twiefel, J.; Wallaschek, J.

    2017-06-01

    Modeling of ultrasonic processes is typically characterized by a high degree of complexity. Different domains and size scales must be regarded, so that it is rather difficult to build up a single detailed overall model. Developing partial models is a common approach to overcome this difficulty. In this paper a generic but simple software framework is presented which allows to coupe arbitrary partial models by slave modules with well-defined interfaces and a master module for coordination. Two examples are given to present the developed framework. The first one is the parameterization of a load model for ultrasonically-induced cavitation. The piezoelectric oscillator, its mounting, and the process load are described individually by partial models. These partial models then are coupled using the framework. The load model is composed of spring-damper-elements which are parameterized by experimental results. In the second example, the ideal mounting position for an oscillator utilized in ultrasonic assisted machining of stone is determined. Partial models for the ultrasonic oscillator, its mounting, the simplified contact process, and the workpiece’s material characteristics are presented. For both applications input and output variables are defined to meet the requirements of the framework’s interface.

  19. Prediction of hourly solar radiation with multi-model framework

    International Nuclear Information System (INIS)

    Wu, Ji; Chan, Chee Keong

    2013-01-01

    Highlights: • A novel approach to predict solar radiation through the use of clustering paradigms. • Development of prediction models based on the intrinsic pattern observed in each cluster. • Prediction based on proper clustering and selection of model on current time provides better results than other methods. • Experiments were conducted on actual solar radiation data obtained from a weather station in Singapore. - Abstract: In this paper, a novel multi-model prediction framework for prediction of solar radiation is proposed. The framework started with the assumption that there are several patterns embedded in the solar radiation series. To extract the underlying pattern, the solar radiation series is first segmented into smaller subsequences, and the subsequences are further grouped into different clusters. For each cluster, an appropriate prediction model is trained. Hence a procedure for pattern identification is developed to identify the proper pattern that fits the current period. Based on this pattern, the corresponding prediction model is applied to obtain the prediction value. The prediction result of the proposed framework is then compared to other techniques. It is shown that the proposed framework provides superior performance as compared to others

  20. Generic modelling framework for economic analysis of battery systems

    DEFF Research Database (Denmark)

    You, Shi; Rasmussen, Claus Nygaard

    2011-01-01

    opportunities, a generic modelling framework is proposed to handle this task. This framework outlines a set of building blocks which are necessary for carrying out the economic analysis of various BS applications. Further, special focus is given on describing how to use the rainflow cycle counting algorithm...... for battery cycle life estimation, since the cycle life plays a central role in the economic analysis of BS. To illustrate the modelling framework, a case study using a Sodium Sulfur Battery (NAS) system with 5-minute regulating service is performed. The economic performances of two dispatch scenarios, a so......Deregulated electricity markets provide opportunities for Battery Systems (BS) to participate in energy arbitrage and ancillary services (regulation, operating reserves, contingency reserves, voltage regulation, power quality etc.). To evaluate the economic viability of BS with different business...

  1. HPeak: an HMM-based algorithm for defining read-enriched regions in ChIP-Seq data

    Directory of Open Access Journals (Sweden)

    Maher Christopher A

    2010-07-01

    Full Text Available Abstract Background Protein-DNA interaction constitutes a basic mechanism for the genetic regulation of target gene expression. Deciphering this mechanism has been a daunting task due to the difficulty in characterizing protein-bound DNA on a large scale. A powerful technique has recently emerged that couples chromatin immunoprecipitation (ChIP with next-generation sequencing, (ChIP-Seq. This technique provides a direct survey of the cistrom of transcription factors and other chromatin-associated proteins. In order to realize the full potential of this technique, increasingly sophisticated statistical algorithms have been developed to analyze the massive amount of data generated by this method. Results Here we introduce HPeak, a Hidden Markov model (HMM-based Peak-finding algorithm for analyzing ChIP-Seq data to identify protein-interacting genomic regions. In contrast to the majority of available ChIP-Seq analysis software packages, HPeak is a model-based approach allowing for rigorous statistical inference. This approach enables HPeak to accurately infer genomic regions enriched with sequence reads by assuming realistic probability distributions, in conjunction with a novel weighting scheme on the sequencing read coverage. Conclusions Using biologically relevant data collections, we found that HPeak showed a higher prevalence of the expected transcription factor binding motifs in ChIP-enriched sequences relative to the control sequences when compared to other currently available ChIP-Seq analysis approaches. Additionally, in comparison to the ChIP-chip assay, ChIP-Seq provides higher resolution along with improved sensitivity and specificity of binding site detection. Additional file and the HPeak program are freely available at http://www.sph.umich.edu/csg/qin/HPeak.

  2. Modeling framework for crew decisions during accident sequences

    International Nuclear Information System (INIS)

    Lukic, Y.D.; Worledge, D.H.; Hannaman, G.W.; Spurgin, A.J.

    1986-01-01

    The ability to model the average behavior of operating crews in the course of accident sequences is vital in learning on how to prevent damage to power plants and to maintain safety. This paper summarizes the work carried out in support of a Human Reliability Model framework. This work develops the mathematical framework of the model and identifies the parameters which could be measured in some way, e.g., through simulator experience and/or small scale tests. Selected illustrative examples are presented, of the numerical experiments carried out in order to understand the model sensitivity to parameter variation. These examples ar discussed with the objective of deriving insights of general nature regarding operating of the model which may lead to enhanced understanding of man/machine interactions

  3. New framework for standardized notation in wastewater treatment modelling

    DEFF Research Database (Denmark)

    Corominas, L.; Rieger, L.; Takacs, I.

    2010-01-01

    Many unit process models are available in the field of wastewater treatment. All of these models use their own notation, causing problems for documentation, implementation and connection of different models (using different sets of state variables). The main goal of this paper is to propose a new...... is a framework that can be used in whole plant modelling, which consists of different fields such as activated sludge, anaerobic digestion, sidestream treatment, membrane bioreactors, metabolic approaches, fate of micropollutants and biofilm processes. The main objective of this consensus building paper...... notational framework which allows unique and systematic naming of state variables and parameters of biokinetic models in the wastewater treatment field. The symbols are based on one main letter that gives a general description of the state variable or parameter and several subscript levels that provide...

  4. A Liver-Centric Multiscale Modeling Framework for Xenobiotics.

    Directory of Open Access Journals (Sweden)

    James P Sluka

    Full Text Available We describe a multi-scale, liver-centric in silico modeling framework for acetaminophen pharmacology and metabolism. We focus on a computational model to characterize whole body uptake and clearance, liver transport and phase I and phase II metabolism. We do this by incorporating sub-models that span three scales; Physiologically Based Pharmacokinetic (PBPK modeling of acetaminophen uptake and distribution at the whole body level, cell and blood flow modeling at the tissue/organ level and metabolism at the sub-cellular level. We have used standard modeling modalities at each of the three scales. In particular, we have used the Systems Biology Markup Language (SBML to create both the whole-body and sub-cellular scales. Our modeling approach allows us to run the individual sub-models separately and allows us to easily exchange models at a particular scale without the need to extensively rework the sub-models at other scales. In addition, the use of SBML greatly facilitates the inclusion of biological annotations directly in the model code. The model was calibrated using human in vivo data for acetaminophen and its sulfate and glucuronate metabolites. We then carried out extensive parameter sensitivity studies including the pairwise interaction of parameters. We also simulated population variation of exposure and sensitivity to acetaminophen. Our modeling framework can be extended to the prediction of liver toxicity following acetaminophen overdose, or used as a general purpose pharmacokinetic model for xenobiotics.

  5. Integrating knowledge seeking into knowledge management models and frameworks

    Directory of Open Access Journals (Sweden)

    Francois Lottering

    2012-09-01

    Objectives: This article investigates the theoretical status of the knowledge-seeking process in extant KM models and frameworks. It also statistically describes knowledge seeking and knowledge sharing practices in a sample of South African companies. Using this data, it proposes a KM model based on knowledge seeking. Method: Knowledge seeking is traced in a number of KM models and frameworks with a specific focus on Han Lai and Margaret Graham’s adapted KM cycle model, which separates knowledge seeking from knowledge sharing. This empirical investigation used a questionnaire to examine knowledge seeking and knowledge sharing practices in a sample of South African companies. Results: This article critiqued and elaborated on the adapted KM cycle model of Lai and Graham. It identified some of the key features of knowledge seeking practices in the workplace. It showed that knowledge seeking and sharing are human-centric actions and that seeking knowledge uses trust and loyalty as its basis. It also showed that one cannot separate knowledge seeking from knowledge sharing. Conclusion: The knowledge seeking-based KM model elaborates on Lai and Graham’s model. It provides insight into how and where people seek and share knowledge in the workplace. The article concludes that it is necessary to cement the place of knowledge seeking in KM models as well as frameworks and suggests that organisations should apply its findings to improving their knowledge management strategies.

  6. Composable Framework Support for Software-FMEA Through Model Execution

    Science.gov (United States)

    Kocsis, Imre; Patricia, Andras; Brancati, Francesco; Rossi, Francesco

    2016-08-01

    Performing Failure Modes and Effect Analysis (FMEA) during software architecture design is becoming a basic requirement in an increasing number of domains; however, due to the lack of standardized early design phase model execution, classic SW-FMEA approaches carry significant risks and are human effort-intensive even in processes that use Model-Driven Engineering.Recently, modelling languages with standardized executable semantics have emerged. Building on earlier results, this paper describes framework support for generating executable error propagation models from such models during software architecture design. The approach carries the promise of increased precision, decreased risk and more automated execution for SW-FMEA during dependability- critical system development.

  7. A Model-Driven Framework to Develop Personalized Health Monitoring

    Directory of Open Access Journals (Sweden)

    Algimantas Venčkauskas

    2016-07-01

    Full Text Available Both distributed healthcare systems and the Internet of Things (IoT are currently hot topics. The latter is a new computing paradigm to enable advanced capabilities in engineering various applications, including those for healthcare. For such systems, the core social requirement is the privacy/security of the patient information along with the technical requirements (e.g., energy consumption and capabilities for adaptability and personalization. Typically, the functionality of the systems is predefined by the patient’s data collected using sensor networks along with medical instrumentation; then, the data is transferred through the Internet for treatment and decision-making. Therefore, systems creation is indeed challenging. In this paper, we propose a model-driven framework to develop the IoT-based prototype and its reference architecture for personalized health monitoring (PHM applications. The framework contains a multi-layered structure with feature-based modeling and feature model transformations at the top and the application software generation at the bottom. We have validated the framework using available tools and developed an experimental PHM to test some aspects of the functionality of the reference architecture in real time. The main contribution of the paper is the development of the model-driven computational framework with emphasis on the synergistic effect of security and energy issues.

  8. Model-based safety architecture framework for complex systems

    NARCIS (Netherlands)

    Schuitemaker, Katja; Rajabali Nejad, Mohammadreza; Braakhuis, J.G.; Podofillini, Luca; Sudret, Bruno; Stojadinovic, Bozidar; Zio, Enrico; Kröger, Wolfgang

    2015-01-01

    The shift to transparency and rising need of the general public for safety, together with the increasing complexity and interdisciplinarity of modern safety-critical Systems of Systems (SoS) have resulted in a Model-Based Safety Architecture Framework (MBSAF) for capturing and sharing architectural

  9. The Guided System Development Framework: Modeling and Verifying Communication Systems

    DEFF Research Database (Denmark)

    Carvalho Quaresma, Jose Nuno; Probst, Christian W.; Nielson, Flemming

    2014-01-01

    the verified specification. The refinement process carries thus security properties from the model to the implementation. Our approach also supports verification of systems previously developed and deployed. Internally, the reasoning in our framework is based on the Beliefs and Knowledge tool, a verification...... tool based on belief logics and explicit attacker knowledge....

  10. A Graph Based Framework to Model Virus Integration Sites

    Directory of Open Access Journals (Sweden)

    Raffaele Fronza

    2016-01-01

    Here, we addressed the challenge to: 1 define the notion of CIS on graph models, 2 demonstrate that the structure of CIS enters in the category of scale-free networks and 3 show that our network approach analyzes CIS dynamically in an integrated systems biology framework using the Retroviral Transposon Tagged Cancer Gene Database (RTCGD as a testing dataset.

  11. Service business model framework and the service innovation scope

    NARCIS (Netherlands)

    van der Aa, W.; van der Rhee, B.; Victorino, L.

    2011-01-01

    In this paper we present a framework for service business models. We build on three streams of research. The first stream is the service management and marketing literature that focuses on the specific challenges of managing a service business. The second stream consists of research on e-business

  12. Model-Driven Policy Framework for Data Centers

    DEFF Research Database (Denmark)

    Caba, Cosmin Marius; Kentis, Angelos Mimidis; Soler, José

    2016-01-01

    . Moreover, the lack of simple solutions for managing the configuration and behavior of the DC components makes the DC hard to configure and slow in adapting to changes in business needs. In this paper, we propose a model-driven framework for policy-based management for DCs, to simplify not only the service...

  13. A compositional modelling framework for exploring MPSoC systems

    DEFF Research Database (Denmark)

    Tranberg-Hansen, Anders Sejer; Madsen, Jan

    2009-01-01

    This paper presents a novel compositional framework for system level performance estimation and exploration of Multi-Processor System On Chip (MPSoC) based systems. The main contributions are the definition of a compositional model which allows quantitative performance estimation to be carried ou...

  14. A Liver-centric Multiscale Modeling Framework for Xenobiotics

    Science.gov (United States)

    We describe a multi-scale framework for modeling acetaminophen-induced liver toxicity. Acetaminophen is a widely used analgesic. Overdose of acetaminophen can result in liver injury via its biotransformation into toxic product, which further induce massive necrosis. Our study foc...

  15. A Framework for Understanding Physics Students' Computational Modeling Practices

    Science.gov (United States)

    Lunk, Brandon Robert

    With the growing push to include computational modeling in the physics classroom, we are faced with the need to better understand students' computational modeling practices. While existing research on programming comprehension explores how novices and experts generate programming algorithms, little of this discusses how domain content knowledge, and physics knowledge in particular, can influence students' programming practices. In an effort to better understand this issue, I have developed a framework for modeling these practices based on a resource stance towards student knowledge. A resource framework models knowledge as the activation of vast networks of elements called "resources." Much like neurons in the brain, resources that become active can trigger cascading events of activation throughout the broader network. This model emphasizes the connectivity between knowledge elements and provides a description of students' knowledge base. Together with resources resources, the concepts of "epistemic games" and "frames" provide a means for addressing the interaction between content knowledge and practices. Although this framework has generally been limited to describing conceptual and mathematical understanding, it also provides a means for addressing students' programming practices. In this dissertation, I will demonstrate this facet of a resource framework as well as fill in an important missing piece: a set of epistemic games that can describe students' computational modeling strategies. The development of this theoretical framework emerged from the analysis of video data of students generating computational models during the laboratory component of a Matter & Interactions: Modern Mechanics course. Student participants across two semesters were recorded as they worked in groups to fix pre-written computational models that were initially missing key lines of code. Analysis of this video data showed that the students' programming practices were highly influenced by

  16. A Novel HMM Distributed Classifier for the Detection of Gait Phases by Means of a Wearable Inertial Sensor Network

    Directory of Open Access Journals (Sweden)

    Juri Taborri

    2014-09-01

    Full Text Available In this work, we decided to apply a hierarchical weighted decision, proposed and used in other research fields, for the recognition of gait phases. The developed and validated novel distributed classifier is based on hierarchical weighted decision from outputs of scalar Hidden Markov Models (HMM applied to angular velocities of foot, shank, and thigh. The angular velocities of ten healthy subjects were acquired via three uni-axial gyroscopes embedded in inertial measurement units (IMUs during one walking task, repeated three times, on a treadmill. After validating the novel distributed classifier and scalar and vectorial classifiers-already proposed in the literature, with a cross-validation, classifiers were compared for sensitivity, specificity, and computational load for all combinations of the three targeted anatomical segments. Moreover, the performance of the novel distributed classifier in the estimation of gait variability in terms of mean time and coefficient of variation was evaluated. The highest values of specificity and sensitivity (>0.98 for the three classifiers examined here were obtained when the angular velocity of the foot was processed. Distributed and vectorial classifiers reached acceptable values (>0.95 when the angular velocity of shank and thigh were analyzed. Distributed and scalar classifiers showed values of computational load about 100 times lower than the one obtained with the vectorial classifier. In addition, distributed classifiers showed an excellent reliability for the evaluation of mean time and a good/excellent reliability for the coefficient of variation. In conclusion, due to the better performance and the small value of computational load, the here proposed novel distributed classifier can be implemented in the real-time application of gait phases recognition, such as to evaluate gait variability in patients or to control active orthoses for the recovery of mobility of lower limb joints.

  17. Theoretical Models and Operational Frameworks in Public Health Ethics

    Science.gov (United States)

    Petrini, Carlo

    2010-01-01

    The article is divided into three sections: (i) an overview of the main ethical models in public health (theoretical foundations); (ii) a summary of several published frameworks for public health ethics (practical frameworks); and (iii) a few general remarks. Rather than maintaining the superiority of one position over the others, the main aim of the article is to summarize the basic approaches proposed thus far concerning the development of public health ethics by describing and comparing the various ideas in the literature. With this in mind, an extensive list of references is provided. PMID:20195441

  18. Theoretical Models and Operational Frameworks in Public Health Ethics

    Directory of Open Access Journals (Sweden)

    Carlo Petrini

    2010-01-01

    Full Text Available The article is divided into three sections: (i an overview of the main ethical models in public health (theoretical foundations; (ii a summary of several published frameworks for public health ethics (practical frameworks; and (iii a few general remarks. Rather than maintaining the superiority of one position over the others, the main aim of the article is to summarize the basic approaches proposed thus far concerning the development of public health ethics by describing and comparing the various ideas in the literature. With this in mind, an extensive list of references is provided.

  19. Parametric design and analysis framework with integrated dynamic models

    DEFF Research Database (Denmark)

    Negendahl, Kristoffer

    2014-01-01

    of building energy and indoor environment, are generally confined to late in the design process. Consequence based design is a framework intended for the early design stage. It involves interdisciplinary expertise that secures validity and quality assurance with a simulationist while sustaining autonomous...... control with the building designer. Consequence based design is defined by the specific use of integrated dynamic modeling, which includes the parametric capabilities of a scripting tool and building simulation features of a building performance simulation tool. The framework can lead to enhanced...

  20. A framework for quantifying net benefits of alternative prognostic models

    OpenAIRE

    Rapsomaniki, E.; White, I.R.; Wood, A.M.; Thompson, S.G.; Ford, I.

    2012-01-01

    New prognostic models are traditionally evaluated using measures of discrimination and risk reclassification, but these do not take full account of the clinical and health economic context. We propose a framework for comparing prognostic models by quantifying the public health impact (net benefit) of the treatment decisions they support, assuming a set of predetermined clinical treatment guidelines. The change in net benefit is more clinically interpretable than changes in traditional measure...

  1. Advancing Integrated Systems Modelling Framework for Life Cycle Sustainability Assessment

    Directory of Open Access Journals (Sweden)

    Anthony Halog

    2011-02-01

    Full Text Available The need for integrated methodological framework for sustainability assessment has been widely discussed and is urgent due to increasingly complex environmental system problems. These problems have impacts on ecosystems and human well-being which represent a threat to economic performance of countries and corporations. Integrated assessment crosses issues; spans spatial and temporal scales; looks forward and backward; and incorporates multi-stakeholder inputs. This study aims to develop an integrated methodology by capitalizing the complementary strengths of different methods used by industrial ecologists and biophysical economists. The computational methodology proposed here is systems perspective, integrative, and holistic approach for sustainability assessment which attempts to link basic science and technology to policy formulation. The framework adopts life cycle thinking methods—LCA, LCC, and SLCA; stakeholders analysis supported by multi-criteria decision analysis (MCDA; and dynamic system modelling. Following Pareto principle, the critical sustainability criteria, indicators and metrics (i.e., hotspots can be identified and further modelled using system dynamics or agent based modelling and improved by data envelopment analysis (DEA and sustainability network theory (SNT. The framework is being applied to development of biofuel supply chain networks. The framework can provide new ways of integrating knowledge across the divides between social and natural sciences as well as between critical and problem-solving research.

  2. The development of a sustainable development model framework

    International Nuclear Information System (INIS)

    Hannoura, Alim P.; Cothren, Gianna M.; Khairy, Wael M.

    2006-01-01

    The emergence of the 'sustainable development' concept as a response to the mining of natural resources for the benefit of multinational corporations has advanced the cause of long-term environmental management. A sustainable development model (SDM) framework that is inclusive of the 'whole' natural environment is presented to illustrate the integration of the sustainable development of the 'whole' ecosystem. The ecosystem approach is an inclusive framework that covers the natural environment relevant futures and constraints. These are dynamically interconnected and constitute the determinates of resources development component of the SDM. The second component of the SDM framework is the resources development patterns, i.e., the use of land, water, and atmospheric resources. All of these patterns include practices that utilize environmental resources to achieve a predefined outcome producing waste and by-products that require disposal into the environment. The water quality management practices represent the third component of the framework. These practices are governed by standards, limitations and available disposal means subject to quantity and quality permits. These interconnected standards, practices and permits shape the resulting environmental quality of the ecosystem under consideration. A fourth component, environmental indicators, of the SDM framework provides a measure of the ecosystem productivity and status that may differ based on societal values and culture. The four components of the SDM are interwoven into an outcome assessment process to form the management and feedback models. The concept of Sustainable Development is expressed in the management model as an objective function subject to desired constraints imposing the required bounds for achieving ecosystem sustainability. The development of the objective function and constrains requires monetary values for ecosystem functions, resources development activities and environmental cost. The

  3. An Ontology-Based Framework for Modeling User Behavior

    DEFF Research Database (Denmark)

    Razmerita, Liana

    2011-01-01

    and classifies its users according to their behavior. The user ontology is the backbone of OntobUMf and has been designed according to the Information Management System Learning Information Package (IMS LIP). The user ontology includes a Behavior concept that extends IMS LIP specification and defines...... characteristics of the users interacting with the system. Concrete examples of how OntobUMf is used in the context of a Knowledge Management (KM) System are provided. This paper discusses some of the implications of ontology-based user modeling for semantically enhanced KM and, in particular, for personal KM....... The results of this research may contribute to the development of other frameworks for modeling user behavior, other semantically enhanced user modeling frameworks, or other semantically enhanced information systems....

  4. A penalized framework for distributed lag non-linear models.

    Science.gov (United States)

    Gasparrini, Antonio; Scheipl, Fabian; Armstrong, Ben; Kenward, Michael G

    2017-09-01

    Distributed lag non-linear models (DLNMs) are a modelling tool for describing potentially non-linear and delayed dependencies. Here, we illustrate an extension of the DLNM framework through the use of penalized splines within generalized additive models (GAM). This extension offers built-in model selection procedures and the possibility of accommodating assumptions on the shape of the lag structure through specific penalties. In addition, this framework includes, as special cases, simpler models previously proposed for linear relationships (DLMs). Alternative versions of penalized DLNMs are compared with each other and with the standard unpenalized version in a simulation study. Results show that this penalized extension to the DLNM class provides greater flexibility and improved inferential properties. The framework exploits recent theoretical developments of GAMs and is implemented using efficient routines within freely available software. Real-data applications are illustrated through two reproducible examples in time series and survival analysis. © 2017 The Authors Biometrics published by Wiley Periodicals, Inc. on behalf of International Biometric Society.

  5. Open source data assimilation framework for hydrological modeling

    Science.gov (United States)

    Ridler, Marc; Hummel, Stef; van Velzen, Nils; Katrine Falk, Anne; Madsen, Henrik

    2013-04-01

    An open-source data assimilation framework is proposed for hydrological modeling. Data assimilation (DA) in hydrodynamic and hydrological forecasting systems has great potential to improve predictions and improve model result. The basic principle is to incorporate measurement information into a model with the aim to improve model results by error minimization. Great strides have been made to assimilate traditional in-situ measurements such as discharge, soil moisture, hydraulic head and snowpack into hydrologic models. More recently, remotely sensed data retrievals of soil moisture, snow water equivalent or snow cover area, surface water elevation, terrestrial water storage and land surface temperature have been successfully assimilated in hydrological models. The assimilation algorithms have become increasingly sophisticated to manage measurement and model bias, non-linear systems, data sparsity (time & space) and undetermined system uncertainty. It is therefore useful to use a pre-existing DA toolbox such as OpenDA. OpenDA is an open interface standard for (and free implementation of) a set of tools to quickly implement DA and calibration for arbitrary numerical models. The basic design philosophy of OpenDA is to breakdown DA into a set of building blocks programmed in object oriented languages. To implement DA, a model must interact with OpenDA to create model instances, propagate the model, get/set variables (or parameters) and free the model once DA is completed. An open-source interface for hydrological models exists capable of all these tasks: OpenMI. OpenMI is an open source standard interface already adopted by key hydrological model providers. It defines a universal approach to interact with hydrological models during simulation to exchange data during runtime, thus facilitating the interactions between models and data sources. The interface is flexible enough so that models can interact even if the model is coded in a different language, represent

  6. A framework for testing and comparing binaural models.

    Science.gov (United States)

    Dietz, Mathias; Lestang, Jean-Hugues; Majdak, Piotr; Stern, Richard M; Marquardt, Torsten; Ewert, Stephan D; Hartmann, William M; Goodman, Dan F M

    2018-03-01

    Auditory research has a rich history of combining experimental evidence with computational simulations of auditory processing in order to deepen our theoretical understanding of how sound is processed in the ears and in the brain. Despite significant progress in the amount of detail and breadth covered by auditory models, for many components of the auditory pathway there are still different model approaches that are often not equivalent but rather in conflict with each other. Similarly, some experimental studies yield conflicting results which has led to controversies. This can be best resolved by a systematic comparison of multiple experimental data sets and model approaches. Binaural processing is a prominent example of how the development of quantitative theories can advance our understanding of the phenomena, but there remain several unresolved questions for which competing model approaches exist. This article discusses a number of current unresolved or disputed issues in binaural modelling, as well as some of the significant challenges in comparing binaural models with each other and with the experimental data. We introduce an auditory model framework, which we believe can become a useful infrastructure for resolving some of the current controversies. It operates models over the same paradigms that are used experimentally. The core of the proposed framework is an interface that connects three components irrespective of their underlying programming language: The experiment software, an auditory pathway model, and task-dependent decision stages called artificial observers that provide the same output format as the test subject. Copyright © 2017 Elsevier B.V. All rights reserved.

  7. The ACTIVE conceptual framework as a structural equation model

    Science.gov (United States)

    Gross, Alden L.; Payne, Brennan R.; Casanova, Ramon; Davoudzadeh, Pega; Dzierzewski, Joseph M.; Farias, Sarah; Giovannetti, Tania; Ip, Edward H.; Marsiske, Michael; Rebok, George W.; Schaie, K. Warner; Thomas, Kelsey; Willis, Sherry; Jones, Richard N.

    2018-01-01

    Background/Study Context Conceptual frameworks are analytic models at a high level of abstraction. Their operationalization can inform randomized trial design and sample size considerations. Methods The Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE) conceptual framework was empirically tested using structural equation modeling (N=2,802). ACTIVE was guided by a conceptual framework for cognitive training in which proximal cognitive abilities (memory, inductive reasoning, speed of processing) mediate treatment-related improvement in primary outcomes (everyday problem-solving, difficulty with activities of daily living, everyday speed, driving difficulty), which in turn lead to improved secondary outcomes (health-related quality of life, health service utilization, mobility). Measurement models for each proximal, primary, and secondary outcome were developed and tested using baseline data. Each construct was then combined in one model to evaluate fit (RMSEA, CFI, normalized residuals of each indicator). To expand the conceptual model and potentially inform future trials, evidence of modification of structural model parameters was evaluated by age, years of education, sex, race, and self-rated health status. Results Preconceived measurement models for memory, reasoning, speed of processing, everyday problem-solving, instrumental activities of daily living (IADL) difficulty, everyday speed, driving difficulty, and health-related quality of life each fit well to the data (all RMSEA .95). Fit of the full model was excellent (RMSEA = .038; CFI = .924). In contrast with previous findings from ACTIVE regarding who benefits from training, interaction testing revealed associations between proximal abilities and primary outcomes are stronger on average by nonwhite race, worse health, older age, and less education (p conceptual model. Findings suggest that the types of people who show intervention effects on cognitive performance potentially may be

  8. The ACTIVE conceptual framework as a structural equation model.

    Science.gov (United States)

    Gross, Alden L; Payne, Brennan R; Casanova, Ramon; Davoudzadeh, Pega; Dzierzewski, Joseph M; Farias, Sarah; Giovannetti, Tania; Ip, Edward H; Marsiske, Michael; Rebok, George W; Schaie, K Warner; Thomas, Kelsey; Willis, Sherry; Jones, Richard N

    2018-01-01

    Background/Study Context: Conceptual frameworks are analytic models at a high level of abstraction. Their operationalization can inform randomized trial design and sample size considerations. The Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE) conceptual framework was empirically tested using structural equation modeling (N=2,802). ACTIVE was guided by a conceptual framework for cognitive training in which proximal cognitive abilities (memory, inductive reasoning, speed of processing) mediate treatment-related improvement in primary outcomes (everyday problem-solving, difficulty with activities of daily living, everyday speed, driving difficulty), which in turn lead to improved secondary outcomes (health-related quality of life, health service utilization, mobility). Measurement models for each proximal, primary, and secondary outcome were developed and tested using baseline data. Each construct was then combined in one model to evaluate fit (RMSEA, CFI, normalized residuals of each indicator). To expand the conceptual model and potentially inform future trials, evidence of modification of structural model parameters was evaluated by age, years of education, sex, race, and self-rated health status. Preconceived measurement models for memory, reasoning, speed of processing, everyday problem-solving, instrumental activities of daily living (IADL) difficulty, everyday speed, driving difficulty, and health-related quality of life each fit well to the data (all RMSEA .95). Fit of the full model was excellent (RMSEA = .038; CFI = .924). In contrast with previous findings from ACTIVE regarding who benefits from training, interaction testing revealed associations between proximal abilities and primary outcomes are stronger on average by nonwhite race, worse health, older age, and less education (p conceptual model. Findings suggest that the types of people who show intervention effects on cognitive performance potentially may be different from

  9. Name segmentation using hidden Markov models and its application in record linkage

    Directory of Open Access Journals (Sweden)

    Rita de Cassia Braga Gonçalves

    2014-10-01

    Full Text Available This study aimed to evaluate the use of hidden Markov models (HMM for the segmentation of person names and its influence on record linkage. A HMM was applied to the segmentation of patient’s and mother’s names in the databases of the Mortality Information System (SIM, Information Subsystem for High Complexity Procedures (APAC, and Hospital Information System (AIH. A sample of 200 patients from each database was segmented via HMM, and the results were compared to those from segmentation by the authors. The APAC-SIM and APAC-AIH databases were linked using three different segmentation strategies, one of which used HMM. Conformity of segmentation via HMM varied from 90.5% to 92.5%. The different segmentation strategies yielded similar results in the record linkage process. This study suggests that segmentation of Brazilian names via HMM is no more effective than traditional segmentation approaches in the linkage process.

  10. A VGI data integration framework based on linked data model

    Science.gov (United States)

    Wan, Lin; Ren, Rongrong

    2015-12-01

    This paper aims at the geographic data integration and sharing method for multiple online VGI data sets. We propose a semantic-enabled framework for online VGI sources cooperative application environment to solve a target class of geospatial problems. Based on linked data technologies - which is one of core components of semantic web, we can construct the relationship link among geographic features distributed in diverse VGI platform by using linked data modeling methods, then deploy these semantic-enabled entities on the web, and eventually form an interconnected geographic data network to support geospatial information cooperative application across multiple VGI data sources. The mapping and transformation from VGI sources to RDF linked data model is presented to guarantee the unique data represent model among different online social geographic data sources. We propose a mixed strategy which combined spatial distance similarity and feature name attribute similarity as the measure standard to compare and match different geographic features in various VGI data sets. And our work focuses on how to apply Markov logic networks to achieve interlinks of the same linked data in different VGI-based linked data sets. In our method, the automatic generating method of co-reference object identification model according to geographic linked data is discussed in more detail. It finally built a huge geographic linked data network across loosely-coupled VGI web sites. The results of the experiment built on our framework and the evaluation of our method shows the framework is reasonable and practicable.

  11. A Structural Model Decomposition Framework for Systems Health Management

    Science.gov (United States)

    Roychoudhury, Indranil; Daigle, Matthew J.; Bregon, Anibal; Pulido, Belamino

    2013-01-01

    Systems health management (SHM) is an important set of technologies aimed at increasing system safety and reliability by detecting, isolating, and identifying faults; and predicting when the system reaches end of life (EOL), so that appropriate fault mitigation and recovery actions can be taken. Model-based SHM approaches typically make use of global, monolithic system models for online analysis, which results in a loss of scalability and efficiency for large-scale systems. Improvement in scalability and efficiency can be achieved by decomposing the system model into smaller local submodels and operating on these submodels instead. In this paper, the global system model is analyzed offline and structurally decomposed into local submodels. We define a common model decomposition framework for extracting submodels from the global model. This framework is then used to develop algorithms for solving model decomposition problems for the design of three separate SHM technologies, namely, estimation (which is useful for fault detection and identification), fault isolation, and EOL prediction. We solve these model decomposition problems using a three-tank system as a case study.

  12. A structural model decomposition framework for systems health management

    Science.gov (United States)

    Roychoudhury, I.; Daigle, M.; Bregon, A.; Pulido, B.

    Systems health management (SHM) is an important set of technologies aimed at increasing system safety and reliability by detecting, isolating, and identifying faults; and predicting when the system reaches end of life (EOL), so that appropriate fault mitigation and recovery actions can be taken. Model-based SHM approaches typically make use of global, monolithic system models for online analysis, which results in a loss of scalability and efficiency for large-scale systems. Improvement in scalability and efficiency can be achieved by decomposing the system model into smaller local submodels and operating on these submodels instead. In this paper, the global system model is analyzed offline and structurally decomposed into local submodels. We define a common model decomposition framework for extracting submodels from the global model. This framework is then used to develop algorithms for solving model decomposition problems for the design of three separate SHM technologies, namely, estimation (which is useful for fault detection and identification), fault isolation, and EOL prediction. We solve these model decomposition problems using a three-tank system as a case study.

  13. Integrating knowledge seeking into knowledge management models and frameworks

    Directory of Open Access Journals (Sweden)

    Francois Lottering

    2012-02-01

    Full Text Available Background: A striking feature of the knowledge management (KM literature is that the standard list of KM processes either subsumes or overlooks the process of knowledge seeking. Knowledge seeking is manifestly under-theorised, making the need to address this gap in KM theory and practice clear and urgent.Objectives: This article investigates the theoretical status of the knowledge-seeking process in extant KM models and frameworks. It also statistically describes knowledge seeking and knowledge sharing practices in a sample of South African companies. Using this data, it proposes a KM model based on knowledge seeking.Method: Knowledge seeking is traced in a number of KM models and frameworks with a specific focus on Han Lai and Margaret Graham’s adapted KM cycle model, which separates knowledge seeking from knowledge sharing. This empirical investigation used a questionnaire to examine knowledge seeking and knowledge sharing practices in a sample of South African companies.Results: This article critiqued and elaborated on the adapted KM cycle model of Lai and Graham. It identified some of the key features of knowledge seeking practices in the workplace. It showed that knowledge seeking and sharing are human-centric actions and that seeking knowledge uses trust and loyalty as its basis. It also showed that one cannot separate knowledge seeking from knowledge sharing.Conclusion: The knowledge seeking-based KM model elaborates on Lai and Graham’s model. It provides insight into how and where people seek and share knowledge in the workplace. The article concludes that it is necessary to cement the place of knowledge seeking in KM models as well as frameworks and suggests that organisations should apply its findings to improving their knowledge management strategies. 

  14. Modelling Framework and Assistive Device for Peripheral Intravenous Injections

    Science.gov (United States)

    Kam, Kin F.; Robinson, Martin P.; Gilbert, Mathew A.; Pelah, Adar

    2016-02-01

    Intravenous access for blood sampling or drug administration that requires peripheral venepuncture is perhaps the most common invasive procedure practiced in hospitals, clinics and general practice surgeries.We describe an idealised mathematical framework for modelling the dynamics of the peripheral venepuncture process. Basic assumptions of the model are confirmed through motion analysis of needle trajectories during venepuncture, taken from video recordings of a skilled practitioner injecting into a practice kit. The framework is also applied to the design and construction of a proposed device for accurate needle guidance during venepuncture administration, assessed as consistent and repeatable in application and does not lead to over puncture. The study provides insights into the ubiquitous peripheral venepuncture process and may contribute to applications in training and in the design of new devices, including for use in robotic automation.

  15. A Modelling Framework for Conventional and Heat Integrated Distillation Columns

    DEFF Research Database (Denmark)

    Bisgaard, Thomas; Huusom, Jakob Kjøbsted; Abildskov, Jens

    2013-01-01

    of hydrocarbons such as separations of equimolar mixtures of benzene/toluene or propane/propene described by simple models, a generic, modular, model framework is presented in this work. At present, the framework is able to describe a conventional distillation column, a mechanical vapor recompression column......Diabatic operation of distillation columns can lead to signicant reductions in energy utilization and operation cost compared to conventional (adiabatic) distillation columns, at an expense of an increased complexity of design and operation. The earliest diabatic distillation conguration dates back...... to the late 70s, and various dierent congurations have appeared since. However, at present, no full-scale diabatic distillation columns are currently operating in the industry. Current studies related to alternative distillation congurations report very dierent gures for potential energy savings which...

  16. Neuroevolution Mechanism for Hidden Markov Model

    Directory of Open Access Journals (Sweden)

    Nabil M. Hewahi

    2011-12-01

    Full Text Available Hidden Markov Model (HMM is a statistical model based on probabilities. HMM is becoming one of the major models involved in many applications such as natural language
    processing, handwritten recognition, image processing, prediction systems and many more. In this research we are concerned with finding out the best HMM for a certain application domain. We propose a neuroevolution process that is based first on converting the HMM to a neural network, then generating many neural networks at random where each represents a HMM. We proceed by
    applying genetic operators to obtain new set of neural networks where each represents HMMs, and updating the population. Finally select the best neural network based on a fitness function.

  17. A Systematic Modelling Framework for Phase Transfer Catalyst Systems

    DEFF Research Database (Denmark)

    Anantpinijwatna, Amata; Sales-Cruz, Mauricio; Hyung Kim, Sun

    2016-01-01

    Phase-transfer catalyst systems contain two liquid phases, with a catalyst (PTC) that transfers between the phases, driving product formation in one phase and being regenerated in the other phase. Typically the reaction involves neutral species in an organic phase and regeneration involves ions i....... The application of the framework is made to two cases in order to highlight the performance and issues of activity coefficient models for predicting design and operation and the effects when different organic solvents are employed....

  18. Common and Innovative Visuals: A sparsity modeling framework for video.

    Science.gov (United States)

    Abdolhosseini Moghadam, Abdolreza; Kumar, Mrityunjay; Radha, Hayder

    2014-05-02

    Efficient video representation models are critical for many video analysis and processing tasks. In this paper, we present a framework based on the concept of finding the sparsest solution to model video frames. To model the spatio-temporal information, frames from one scene are decomposed into two components: (i) a common frame, which describes the visual information common to all the frames in the scene/segment, and (ii) a set of innovative frames, which depicts the dynamic behaviour of the scene. The proposed approach exploits and builds on recent results in the field of compressed sensing to jointly estimate the common frame and the innovative frames for each video segment. We refer to the proposed modeling framework by CIV (Common and Innovative Visuals). We show how the proposed model can be utilized to find scene change boundaries and extend CIV to videos from multiple scenes. Furthermore, the proposed model is robust to noise and can be used for various video processing applications without relying on motion estimation and detection or image segmentation. Results for object tracking, video editing (object removal, inpainting) and scene change detection are presented to demonstrate the efficiency and the performance of the proposed model.

  19. SVM-dependent pairwise HMM: an application to protein pairwise alignments.

    Science.gov (United States)

    Orlando, Gabriele; Raimondi, Daniele; Khan, Taushif; Lenaerts, Tom; Vranken, Wim F

    2017-12-15

    Methods able to provide reliable protein alignments are crucial for many bioinformatics applications. In the last years many different algorithms have been developed and various kinds of information, from sequence conservation to secondary structure, have been used to improve the alignment performances. This is especially relevant for proteins with highly divergent sequences. However, recent works suggest that different features may have different importance in diverse protein classes and it would be an advantage to have more customizable approaches, capable to deal with different alignment definitions. Here we present Rigapollo, a highly flexible pairwise alignment method based on a pairwise HMM-SVM that can use any type of information to build alignments. Rigapollo lets the user decide the optimal features to align their protein class of interest. It outperforms current state of the art methods on two well-known benchmark datasets when aligning highly divergent sequences. A Python implementation of the algorithm is available at http://ibsquare.be/rigapollo. wim.vranken@vub.be. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

  20. Progressive Learning of Topic Modeling Parameters: A Visual Analytics Framework.

    Science.gov (United States)

    El-Assady, Mennatallah; Sevastjanova, Rita; Sperrle, Fabian; Keim, Daniel; Collins, Christopher

    2018-01-01

    Topic modeling algorithms are widely used to analyze the thematic composition of text corpora but remain difficult to interpret and adjust. Addressing these limitations, we present a modular visual analytics framework, tackling the understandability and adaptability of topic models through a user-driven reinforcement learning process which does not require a deep understanding of the underlying topic modeling algorithms. Given a document corpus, our approach initializes two algorithm configurations based on a parameter space analysis that enhances document separability. We abstract the model complexity in an interactive visual workspace for exploring the automatic matching results of two models, investigating topic summaries, analyzing parameter distributions, and reviewing documents. The main contribution of our work is an iterative decision-making technique in which users provide a document-based relevance feedback that allows the framework to converge to a user-endorsed topic distribution. We also report feedback from a two-stage study which shows that our technique results in topic model quality improvements on two independent measures.

  1. Next generation framework for aquatic modeling of the Earth System

    Science.gov (United States)

    Fekete, B. M.; Wollheim, W. M.; Wisser, D.; Vörösmarty, C. J.

    2009-03-01

    Earth System model development is becoming an increasingly complex task. As scientists attempt to represent the physical and bio-geochemical processes and various feedback mechanisms in unprecedented detail, the models themselves are becoming increasingly complex. At the same time, the complexity of the surrounding IT infrastructure is growing as well. Earth System models must manage a vast amount of data in heterogeneous computing environments. Numerous development efforts are on the way to ease that burden and offer model development platforms that reduce IT challenges and allow scientists to focus on their science. While these new modeling frameworks (e.g. FMS, ESMF, CCA, OpenMI) do provide solutions to many IT challenges (performing input/output, managing space and time, establishing model coupling, etc.), they are still considerably complex and often have steep learning curves. The Next generation Framework for Aquatic Modeling of the Earth System (NextFrAMES, a revised version of FrAMES) have numerous similarities to those developed by other teams, but represents a novel model development paradigm. NextFrAMES is built around a modeling XML that lets modelers to express the overall model structure and provides an API for dynamically linked plugins to represent the processes. The model XML is executed by the NextFrAMES run-time engine that parses the model definition, loads the module plugins, performs the model I/O and executes the model calculations. NextFrAMES has a minimalistic view representing spatial domains and treats every domain (regardless of its layout such as grid, network tree, individual points, polygons, etc.) as vector of objects. NextFrAMES performs computations on multiple domains and interactions between different spatial domains are carried out through couplers. NextFrAMES allows processes to operate at different frequencies by providing rudimentary aggregation and disaggregation facilities. NextFrAMES was designed primarily for

  2. An Active Lattice Model in a Bayesian Framework

    DEFF Research Database (Denmark)

    Carstensen, Jens Michael

    1996-01-01

    A Markov Random Field is used as a structural model of a deformable rectangular lattice. When used as a template prior in a Bayesian framework this model is powerful for making inferences about lattice structures in images. The model assigns maximum probability to the perfect regular lattice...... by penalizing deviations in alignment and lattice node distance. The Markov random field represents prior knowledge about the lattice structure, and through an observation model that incorporates the visual appearance of the nodes, we can simulate realizations from the posterior distribution. A maximum...... a posteriori (MAP) estimate, found by simulated annealing, is used as the reconstructed lattice. The model was developed as a central part of an algorithm for automatic analylsis of genetic experiments, positioned in a lattice structure by a robot. The algorithm has been successfully applied to many images...

  3. A conceptual and disease model framework for osteoporotic kyphosis.

    Science.gov (United States)

    Bayliss, M; Miltenburger, C; White, M; Alvares, L

    2013-09-01

    This paper presents a multi-method research project to develop a conceptual framework for measuring outcomes in studies of osteoporotic kyphosis. The research involved literature research and qualitative interviews among clinicians who treat patients with kyphosis and among patients with the condition. Kyphosis due to at least one vertebral compression fracture is prevalent among osteoporotic patients, resulting in well-documented symptoms and impact on functioning and well-being. A three-part study led to development of a conceptual measurement framework for comprehensive assessment of symptoms, impact, and treatment benefit for kyphosis. A literature-based disease model (DM) was developed and tested with physicians (n = 10) and patients (n = 10), and FDA guidelines were used to develop a final disease model and a conceptual framework. The DM included signs, symptoms, causes/triggers, exacerbations, and functional status associated with kyphosis. The DM was largely confirmed, but physicians and patients added several concepts related to impact on functioning, and some concepts were not confirmed and removed from the DM. This study confirms the need for more comprehensive assessment of health outcomes in kyphosis, as most current studies omit key concepts.

  4. The ontology model of FrontCRM framework

    Science.gov (United States)

    Budiardjo, Eko K.; Perdana, Wira; Franshisca, Felicia

    2013-03-01

    Adoption and implementation of Customer Relationship Management (CRM) is not merely a technological installation, but the emphasis is more on the application of customer-centric philosophy and culture as a whole. CRM must begin at the level of business strategy, the only level that thorough organizational changes are possible to be done. Changes agenda can be directed to each departmental plans, and supported by information technology. Work processes related to CRM concept include marketing, sales, and services. FrontCRM is developed as framework to guide in identifying business processes related to CRM in which based on the concept of strategic planning approach. This leads to processes and practices identification in every process area related to marketing, sales, and services. The Ontology model presented on this paper by means serves as tools to avoid framework misunderstanding, to define practices systematically within process area and to find CRM software features related to those practices.

  5. Modeling Geomagnetic Variations using a Machine Learning Framework

    Science.gov (United States)

    Cheung, C. M. M.; Handmer, C.; Kosar, B.; Gerules, G.; Poduval, B.; Mackintosh, G.; Munoz-Jaramillo, A.; Bobra, M.; Hernandez, T.; McGranaghan, R. M.

    2017-12-01

    We present a framework for data-driven modeling of Heliophysics time series data. The Solar Terrestrial Interaction Neural net Generator (STING) is an open source python module built on top of state-of-the-art statistical learning frameworks (traditional machine learning methods as well as deep learning). To showcase the capability of STING, we deploy it for the problem of predicting the temporal variation of geomagnetic fields. The data used includes solar wind measurements from the OMNI database and geomagnetic field data taken by magnetometers at US Geological Survey observatories. We examine the predictive capability of different machine learning techniques (recurrent neural networks, support vector machines) for a range of forecasting times (minutes to 12 hours). STING is designed to be extensible to other types of data. We show how STING can be used on large sets of data from different sensors/observatories and adapted to tackle other problems in Heliophysics.

  6. A Structural Model Decomposition Framework for Hybrid Systems Diagnosis

    Science.gov (United States)

    Daigle, Matthew; Bregon, Anibal; Roychoudhury, Indranil

    2015-01-01

    Nowadays, a large number of practical systems in aerospace and industrial environments are best represented as hybrid systems that consist of discrete modes of behavior, each defined by a set of continuous dynamics. These hybrid dynamics make the on-line fault diagnosis task very challenging. In this work, we present a new modeling and diagnosis framework for hybrid systems. Models are composed from sets of user-defined components using a compositional modeling approach. Submodels for residual generation are then generated for a given mode, and reconfigured efficiently when the mode changes. Efficient reconfiguration is established by exploiting causality information within the hybrid system models. The submodels can then be used for fault diagnosis based on residual generation and analysis. We demonstrate the efficient causality reassignment, submodel reconfiguration, and residual generation for fault diagnosis using an electrical circuit case study.

  7. Generalized framework for context-specific metabolic model extraction methods

    Directory of Open Access Journals (Sweden)

    Semidán eRobaina Estévez

    2014-09-01

    Full Text Available Genome-scale metabolic models are increasingly applied to investigate the physiology not only of simple prokaryotes, but also eukaryotes, such as plants, characterized with compartmentalized cells of multiple types. While genome-scale models aim at including the entirety of known metabolic reactions, mounting evidence has indicated that only a subset of these reactions is active in a given context, including: developmental stage, cell type, or environment. As a result, several methods have been proposed to reconstruct context-specific models from existing genome-scale models by integrating various types of high-throughput data. Here we present a mathematical framework that puts all existing methods under one umbrella and provides the means to better understand their functioning, highlight similarities and differences, and to help users in selecting a most suitable method for an application.

  8. Modelling multimedia teleservices with OSI upper layers framework: Short paper

    Science.gov (United States)

    Widya, I.; Vanrijssen, E.; Michiels, E.

    The paper presents the use of the concepts and modelling principles of the Open Systems Interconnection (OSI) upper layers structure in the modelling of multimedia teleservices. It puts emphasis on the revised Application Layer Structure (OSI/ALS). OSI/ALS is an object based reference model which intends to coordinate the development of application oriented services and protocols in a consistent and modular way. It enables the rapid deployment and integrated use of these services. The paper emphasizes further on the nesting structure defined in OSI/ALS which allows the design of scalable and user tailorable/controllable teleservices. OSI/ALS consistent teleservices are moreover implementable on communication platforms of different capabilities. An analysis of distributed multimedia architectures which can be found in the literature, confirms the ability of the OSI/ALS framework to model the interworking functionalities of teleservices.

  9. A computational framework for modeling targets as complex adaptive systems

    Science.gov (United States)

    Santos, Eugene; Santos, Eunice E.; Korah, John; Murugappan, Vairavan; Subramanian, Suresh

    2017-05-01

    Modeling large military targets is a challenge as they can be complex systems encompassing myriad combinations of human, technological, and social elements that interact, leading to complex behaviors. Moreover, such targets have multiple components and structures, extending across multiple spatial and temporal scales, and are in a state of change, either in response to events in the environment or changes within the system. Complex adaptive system (CAS) theory can help in capturing the dynamism, interactions, and more importantly various emergent behaviors, displayed by the targets. However, a key stumbling block is incorporating information from various intelligence, surveillance and reconnaissance (ISR) sources, while dealing with the inherent uncertainty, incompleteness and time criticality of real world information. To overcome these challenges, we present a probabilistic reasoning network based framework called complex adaptive Bayesian Knowledge Base (caBKB). caBKB is a rigorous, overarching and axiomatic framework that models two key processes, namely information aggregation and information composition. While information aggregation deals with the union, merger and concatenation of information and takes into account issues such as source reliability and information inconsistencies, information composition focuses on combining information components where such components may have well defined operations. Since caBKBs can explicitly model the relationships between information pieces at various scales, it provides unique capabilities such as the ability to de-aggregate and de-compose information for detailed analysis. Using a scenario from the Network Centric Operations (NCO) domain, we will describe how our framework can be used for modeling targets with a focus on methodologies for quantifying NCO performance metrics.

  10. Flexible Modeling of Epidemics with an Empirical Bayes Framework

    Science.gov (United States)

    Brooks, Logan C.; Farrow, David C.; Hyun, Sangwon; Tibshirani, Ryan J.; Rosenfeld, Roni

    2015-01-01

    Seasonal influenza epidemics cause consistent, considerable, widespread loss annually in terms of economic burden, morbidity, and mortality. With access to accurate and reliable forecasts of a current or upcoming influenza epidemic’s behavior, policy makers can design and implement more effective countermeasures. This past year, the Centers for Disease Control and Prevention hosted the “Predict the Influenza Season Challenge”, with the task of predicting key epidemiological measures for the 2013–2014 U.S. influenza season with the help of digital surveillance data. We developed a framework for in-season forecasts of epidemics using a semiparametric Empirical Bayes framework, and applied it to predict the weekly percentage of outpatient doctors visits for influenza-like illness, and the season onset, duration, peak time, and peak height, with and without using Google Flu Trends data. Previous work on epidemic modeling has focused on developing mechanistic models of disease behavior and applying time series tools to explain historical data. However, tailoring these models to certain types of surveillance data can be challenging, and overly complex models with many parameters can compromise forecasting ability. Our approach instead produces possibilities for the epidemic curve of the season of interest using modified versions of data from previous seasons, allowing for reasonable variations in the timing, pace, and intensity of the seasonal epidemics, as well as noise in observations. Since the framework does not make strict domain-specific assumptions, it can easily be applied to some other diseases with seasonal epidemics. This method produces a complete posterior distribution over epidemic curves, rather than, for example, solely point predictions of forecasting targets. We report prospective influenza-like-illness forecasts made for the 2013–2014 U.S. influenza season, and compare the framework’s cross-validated prediction error on historical data to

  11. A business model design framework for viability : a business ecosystem approach

    NARCIS (Netherlands)

    D'Souza, Austin; Velthuijsen, Hugo; Wortmann, J.C.; Huitema, George

    2015-01-01

    Purpose: To facilitate the design of viable business models by proposing a novel business model design framework for viability. Design: A design science research method is adopted to develop a business model design framework for viability. The business model design framework for viability is

  12. An Improved Generalized Predictive Control in a Robust Dynamic Partial Least Square Framework

    Directory of Open Access Journals (Sweden)

    Jin Xin

    2015-01-01

    Full Text Available To tackle the sensitivity to outliers in system identification, a new robust dynamic partial least squares (PLS model based on an outliers detection method is proposed in this paper. An improved radial basis function network (RBFN is adopted to construct the predictive model from inputs and outputs dataset, and a hidden Markov model (HMM is applied to detect the outliers. After outliers are removed away, a more robust dynamic PLS model is obtained. In addition, an improved generalized predictive control (GPC with the tuning weights under dynamic PLS framework is proposed to deal with the interaction which is caused by the model mismatch. The results of two simulations demonstrate the effectiveness of proposed method.

  13. The Use of Hidden Markov Models for Anomaly Detection in Nuclear Core Condition Monitoring

    Science.gov (United States)

    Stephen, Bruce; West, Graeme M.; Galloway, Stuart; McArthur, Stephen D. J.; McDonald, James R.; Towle, Dave

    2009-04-01

    Unplanned outages can be especially costly for generation companies operating nuclear facilities. Early detection of deviations from expected performance through condition monitoring can allow a more proactive and managed approach to dealing with ageing plant. This paper proposes an anomaly detection framework incorporating the use of the Hidden Markov Model (HMM) to support the analysis of nuclear reactor core condition monitoring data. Fuel Grab Load Trace (FGLT) data gathered within the UK during routine refueling operations has been seen to provide information relating to the condition of the graphite bricks that comprise the core. Although manual analysis of this data is time consuming and requires considerable expertise, this paper demonstrates how techniques such as the HMM can provide analysis support by providing a benchmark model of expected behavior against which future refueling events may be compared. The presence of anomalous behavior in candidate traces is inferred through the underlying statistical foundation of the HMM which gives an observation likelihood averaged along the length of the input sequence. Using this likelihood measure, the engineer can be alerted to anomalous behaviour, indicating data which might require further detailed examination. It is proposed that this data analysis technique is used in conjunction with other intelligent analysis techniques currently employed to analyse FGLT to provide a greater confidence measure in detecting anomalous behaviour from FGLT data.

  14. LQCD workflow execution framework: Models, provenance and fault-tolerance

    International Nuclear Information System (INIS)

    Piccoli, Luciano; Simone, James N; Kowalkowlski, James B; Dubey, Abhishek

    2010-01-01

    Large computing clusters used for scientific processing suffer from systemic failures when operated over long continuous periods for executing workflows. Diagnosing job problems and faults leading to eventual failures in this complex environment is difficult, specifically when the success of an entire workflow might be affected by a single job failure. In this paper, we introduce a model-based, hierarchical, reliable execution framework that encompass workflow specification, data provenance, execution tracking and online monitoring of each workflow task, also referred to as participants. The sequence of participants is described in an abstract parameterized view, which is translated into a concrete data dependency based sequence of participants with defined arguments. As participants belonging to a workflow are mapped onto machines and executed, periodic and on-demand monitoring of vital health parameters on allocated nodes is enabled according to pre-specified rules. These rules specify conditions that must be true pre-execution, during execution and post-execution. Monitoring information for each participant is propagated upwards through the reflex and healing architecture, which consists of a hierarchical network of decentralized fault management entities, called reflex engines. They are instantiated as state machines or timed automatons that change state and initiate reflexive mitigation action(s) upon occurrence of certain faults. We describe how this cluster reliability framework is combined with the workflow execution framework using formal rules and actions specified within a structure of first order predicate logic that enables a dynamic management design that reduces manual administrative workload, and increases cluster-productivity.

  15. Spatial Modeling for Resources Framework (SMRF): A modular framework for developing spatial forcing data for snow modeling in mountain basins

    Science.gov (United States)

    Havens, Scott; Marks, Danny; Kormos, Patrick; Hedrick, Andrew

    2017-12-01

    In the Western US and many mountainous regions of the world, critical water resources and climate conditions are difficult to monitor because the observation network is generally very sparse. The critical resource from the mountain snowpack is water flowing into streams and reservoirs that will provide for irrigation, flood control, power generation, and ecosystem services. Water supply forecasting in a rapidly changing climate has become increasingly difficult because of non-stationary conditions. In response, operational water supply managers have begun to move from statistical techniques towards the use of physically based models. As we begin to transition physically based models from research to operational use, we must address the most difficult and time-consuming aspect of model initiation: the need for robust methods to develop and distribute the input forcing data. In this paper, we present a new open source framework, the Spatial Modeling for Resources Framework (SMRF), which automates and simplifies the common forcing data distribution methods. It is computationally efficient and can be implemented for both research and operational applications. We present an example of how SMRF is able to generate all of the forcing data required to a run physically based snow model at 50-100 m resolution over regions of 1000-7000 km2. The approach has been successfully applied in real time and historical applications for both the Boise River Basin in Idaho, USA and the Tuolumne River Basin in California, USA. These applications use meteorological station measurements and numerical weather prediction model outputs as input. SMRF has significantly streamlined the modeling workflow, decreased model set up time from weeks to days, and made near real-time application of a physically based snow model possible.

  16. Exploring uncertainty and model predictive performance concepts via a modular snowmelt-runoff modeling framework

    Science.gov (United States)

    Tyler Jon Smith; Lucy Amanda Marshall

    2010-01-01

    Model selection is an extremely important aspect of many hydrologic modeling studies because of the complexity, variability, and uncertainty that surrounds the current understanding of watershed-scale systems. However, development and implementation of a complete precipitation-runoff modeling framework, from model selection to calibration and uncertainty analysis, are...

  17. An Integrated Framework Advancing Membrane Protein Modeling and Design.

    Directory of Open Access Journals (Sweden)

    Rebecca F Alford

    2015-09-01

    Full Text Available Membrane proteins are critical functional molecules in the human body, constituting more than 30% of open reading frames in the human genome. Unfortunately, a myriad of difficulties in overexpression and reconstitution into membrane mimetics severely limit our ability to determine their structures. Computational tools are therefore instrumental to membrane protein structure prediction, consequently increasing our understanding of membrane protein function and their role in disease. Here, we describe a general framework facilitating membrane protein modeling and design that combines the scientific principles for membrane protein modeling with the flexible software architecture of Rosetta3. This new framework, called RosettaMP, provides a general membrane representation that interfaces with scoring, conformational sampling, and mutation routines that can be easily combined to create new protocols. To demonstrate the capabilities of this implementation, we developed four proof-of-concept applications for (1 prediction of free energy changes upon mutation; (2 high-resolution structural refinement; (3 protein-protein docking; and (4 assembly of symmetric protein complexes, all in the membrane environment. Preliminary data show that these algorithms can produce meaningful scores and structures. The data also suggest needed improvements to both sampling routines and score functions. Importantly, the applications collectively demonstrate the potential of combining the flexible nature of RosettaMP with the power of Rosetta algorithms to facilitate membrane protein modeling and design.

  18. A hybrid parallel framework for the cellular Potts model simulations

    Energy Technology Data Exchange (ETDEWEB)

    Jiang, Yi [Los Alamos National Laboratory; He, Kejing [SOUTH CHINA UNIV; Dong, Shoubin [SOUTH CHINA UNIV

    2009-01-01

    The Cellular Potts Model (CPM) has been widely used for biological simulations. However, most current implementations are either sequential or approximated, which can't be used for large scale complex 3D simulation. In this paper we present a hybrid parallel framework for CPM simulations. The time-consuming POE solving, cell division, and cell reaction operation are distributed to clusters using the Message Passing Interface (MPI). The Monte Carlo lattice update is parallelized on shared-memory SMP system using OpenMP. Because the Monte Carlo lattice update is much faster than the POE solving and SMP systems are more and more common, this hybrid approach achieves good performance and high accuracy at the same time. Based on the parallel Cellular Potts Model, we studied the avascular tumor growth using a multiscale model. The application and performance analysis show that the hybrid parallel framework is quite efficient. The hybrid parallel CPM can be used for the large scale simulation ({approx}10{sup 8} sites) of complex collective behavior of numerous cells ({approx}10{sup 6}).

  19. A constitutive model for magnetostriction based on thermodynamic framework

    International Nuclear Information System (INIS)

    Ho, Kwangsoo

    2016-01-01

    This work presents a general framework for the continuum-based formulation of dissipative materials with magneto–mechanical coupling in the viewpoint of irreversible thermodynamics. The thermodynamically consistent model developed for the magnetic hysteresis is extended to include the magnetostrictive effect. The dissipative and hysteretic response of magnetostrictive materials is captured through the introduction of internal state variables. The evolution rate of magnetostrictive strain as well as magnetization is derived from thermodynamic and dissipative potentials in accordance with the general principles of thermodynamics. It is then demonstrated that the constitutive model is competent to describe the magneto-mechanical behavior by comparing simulation results with the experimental data reported in the literature. - Highlights: • A thermodynamically consistent model is proposed to describe the magneto-mechanical coupling effect. • Internal state variables are introduced to capture the dissipative material response. • The evolution rate of the magnetostrictive strain is derived through thermodynamic and dissipation potentials.

  20. A framework for quantifying net benefits of alternative prognostic models

    DEFF Research Database (Denmark)

    Rapsomaniki, Eleni; White, Ian R; Wood, Angela M

    2012-01-01

    New prognostic models are traditionally evaluated using measures of discrimination and risk reclassification, but these do not take full account of the clinical and health economic context. We propose a framework for comparing prognostic models by quantifying the public health impact (net benefit......) of the treatment decisions they support, assuming a set of predetermined clinical treatment guidelines. The change in net benefit is more clinically interpretable than changes in traditional measures and can be used in full health economic evaluations of prognostic models used for screening and allocating risk...... reduction interventions. We extend previous work in this area by quantifying net benefits in life years, thus linking prognostic performance to health economic measures; by taking full account of the occurrence of events over time; and by considering estimation and cross-validation in a multiple...

  1. CIMS: A FRAMEWORK FOR INFRASTRUCTURE INTERDEPENDENCY MODELING AND ANALYSIS

    Energy Technology Data Exchange (ETDEWEB)

    Donald D. Dudenhoeffer; May R. Permann; Milos Manic

    2006-12-01

    Today’s society relies greatly upon an array of complex national and international infrastructure networks such as transportation, utilities, telecommunication, and even financial networks. While modeling and simulation tools have provided insight into the behavior of individual infrastructure networks, a far less understood area is that of the interrelationships among multiple infrastructure networks including the potential cascading effects that may result due to these interdependencies. This paper first describes infrastructure interdependencies as well as presenting a formalization of interdependency types. Next the paper describes a modeling and simulation framework called CIMS© and the work that is being conducted at the Idaho National Laboratory (INL) to model and simulate infrastructure interdependencies and the complex behaviors that can result.

  2. A Framework for Modeling Emerging Diseases to Inform Management.

    Science.gov (United States)

    Russell, Robin E; Katz, Rachel A; Richgels, Katherine L D; Walsh, Daniel P; Grant, Evan H C

    2017-01-01

    The rapid emergence and reemergence of zoonotic diseases requires the ability to rapidly evaluate and implement optimal management decisions. Actions to control or mitigate the effects of emerging pathogens are commonly delayed because of uncertainty in the estimates and the predicted outcomes of the control tactics. The development of models that describe the best-known information regarding the disease system at the early stages of disease emergence is an essential step for optimal decision-making. Models can predict the potential effects of the pathogen, provide guidance for assessing the likelihood of success of different proposed management actions, quantify the uncertainty surrounding the choice of the optimal decision, and highlight critical areas for immediate research. We demonstrate how to develop models that can be used as a part of a decision-making framework to determine the likelihood of success of different management actions given current knowledge.

  3. The Application of Architecture Frameworks to Modelling Exploration Operations Costs

    Science.gov (United States)

    Shishko, Robert

    2006-01-01

    Developments in architectural frameworks and system-of-systems thinking have provided useful constructs for systems engineering. DoDAF concepts, language, and formalisms, in particular, provide a natural way of conceptualizing an operations cost model applicable to NASA's space exploration vision. Not all DoDAF products have meaning or apply to a DoDAF inspired operations cost model, but this paper describes how such DoDAF concepts as nodes, systems, and operational activities relate to the development of a model to estimate exploration operations costs. The paper discusses the specific implementation to the Mission Operations Directorate (MOD) operational functions/activities currently being developed and presents an overview of how this powerful representation can apply to robotic space missions as well.

  4. A Framework for Uplink Intercell Interference Modeling with Channel-Based Scheduling

    KAUST Repository

    Tabassum, Hina; Yilmaz, Ferkan; Dawy, Zaher; Alouini, Mohamed-Slim

    2012-01-01

    This paper presents a novel framework for modeling the uplink intercell interference(ICI) in a multiuser cellular network. The proposed framework assists in quantifying the impact of various fading channel models and state-of-the-art scheduling

  5. Development of a distributed air pollutant dry deposition modeling framework

    International Nuclear Information System (INIS)

    Hirabayashi, Satoshi; Kroll, Charles N.; Nowak, David J.

    2012-01-01

    A distributed air pollutant dry deposition modeling system was developed with a geographic information system (GIS) to enhance the functionality of i-Tree Eco (i-Tree, 2011). With the developed system, temperature, leaf area index (LAI) and air pollutant concentration in a spatially distributed form can be estimated, and based on these and other input variables, dry deposition of carbon monoxide (CO), nitrogen dioxide (NO 2 ), sulfur dioxide (SO 2 ), and particulate matter less than 10 microns (PM10) to trees can be spatially quantified. Employing nationally available road network, traffic volume, air pollutant emission/measurement and meteorological data, the developed system provides a framework for the U.S. city managers to identify spatial patterns of urban forest and locate potential areas for future urban forest planting and protection to improve air quality. To exhibit the usability of the framework, a case study was performed for July and August of 2005 in Baltimore, MD. - Highlights: ► A distributed air pollutant dry deposition modeling system was developed. ► The developed system enhances the functionality of i-Tree Eco. ► The developed system employs nationally available input datasets. ► The developed system is transferable to any U.S. city. ► Future planting and protection spots were visually identified in a case study. - Employing nationally available datasets and a GIS, this study will provide urban forest managers in U.S. cities a framework to quantify and visualize urban forest structure and its air pollution removal effect.

  6. Reconfigurable Model Execution in the OpenMDAO Framework

    Science.gov (United States)

    Hwang, John T.

    2017-01-01

    NASA's OpenMDAO framework facilitates constructing complex models and computing their derivatives for multidisciplinary design optimization. Decomposing a model into components that follow a prescribed interface enables OpenMDAO to assemble multidisciplinary derivatives from the component derivatives using what amounts to the adjoint method, direct method, chain rule, global sensitivity equations, or any combination thereof, using the MAUD architecture. OpenMDAO also handles the distribution of processors among the disciplines by hierarchically grouping the components, and it automates the data transfer between components that are on different processors. These features have made OpenMDAO useful for applications in aircraft design, satellite design, wind turbine design, and aircraft engine design, among others. This paper presents new algorithms for OpenMDAO that enable reconfigurable model execution. This concept refers to dynamically changing, during execution, one or more of: the variable sizes, solution algorithm, parallel load balancing, or set of variables-i.e., adding and removing components, perhaps to switch to a higher-fidelity sub-model. Any component can reconfigure at any point, even when running in parallel with other components, and the reconfiguration algorithm presented here performs the synchronized updates to all other components that are affected. A reconfigurable software framework for multidisciplinary design optimization enables new adaptive solvers, adaptive parallelization, and new applications such as gradient-based optimization with overset flow solvers and adaptive mesh refinement. Benchmarking results demonstrate the time savings for reconfiguration compared to setting up the model again from scratch, which can be significant in large-scale problems. Additionally, the new reconfigurability feature is applied to a mission profile optimization problem for commercial aircraft where both the parametrization of the mission profile and the

  7. A python framework for environmental model uncertainty analysis

    Science.gov (United States)

    White, Jeremy; Fienen, Michael N.; Doherty, John E.

    2016-01-01

    We have developed pyEMU, a python framework for Environmental Modeling Uncertainty analyses, open-source tool that is non-intrusive, easy-to-use, computationally efficient, and scalable to highly-parameterized inverse problems. The framework implements several types of linear (first-order, second-moment (FOSM)) and non-linear uncertainty analyses. The FOSM-based analyses can also be completed prior to parameter estimation to help inform important modeling decisions, such as parameterization and objective function formulation. Complete workflows for several types of FOSM-based and non-linear analyses are documented in example notebooks implemented using Jupyter that are available in the online pyEMU repository. Example workflows include basic parameter and forecast analyses, data worth analyses, and error-variance analyses, as well as usage of parameter ensemble generation and management capabilities. These workflows document the necessary steps and provides insights into the results, with the goal of educating users not only in how to apply pyEMU, but also in the underlying theory of applied uncertainty quantification.

  8. A framework for quantifying net benefits of alternative prognostic models.

    Science.gov (United States)

    Rapsomaniki, Eleni; White, Ian R; Wood, Angela M; Thompson, Simon G

    2012-01-30

    New prognostic models are traditionally evaluated using measures of discrimination and risk reclassification, but these do not take full account of the clinical and health economic context. We propose a framework for comparing prognostic models by quantifying the public health impact (net benefit) of the treatment decisions they support, assuming a set of predetermined clinical treatment guidelines. The change in net benefit is more clinically interpretable than changes in traditional measures and can be used in full health economic evaluations of prognostic models used for screening and allocating risk reduction interventions. We extend previous work in this area by quantifying net benefits in life years, thus linking prognostic performance to health economic measures; by taking full account of the occurrence of events over time; and by considering estimation and cross-validation in a multiple-study setting. The method is illustrated in the context of cardiovascular disease risk prediction using an individual participant data meta-analysis. We estimate the number of cardiovascular-disease-free life years gained when statin treatment is allocated based on a risk prediction model with five established risk factors instead of a model with just age, gender and region. We explore methodological issues associated with the multistudy design and show that cost-effectiveness comparisons based on the proposed methodology are robust against a range of modelling assumptions, including adjusting for competing risks. Copyright © 2011 John Wiley & Sons, Ltd.

  9. Multi-stream LSTM-HMM decoding and histogram equalization for noise robust keyword spotting.

    Science.gov (United States)

    Wöllmer, Martin; Marchi, Erik; Squartini, Stefano; Schuller, Björn

    2011-09-01

    Highly spontaneous, conversational, and potentially emotional and noisy speech is known to be a challenge for today's automatic speech recognition (ASR) systems, which highlights the need for advanced algorithms that improve speech features and models. Histogram Equalization is an efficient method to reduce the mismatch between clean and noisy conditions by normalizing all moments of the probability distribution of the feature vector components. In this article, we propose to combine histogram equalization and multi-condition training for robust keyword detection in noisy speech. To better cope with conversational speaking styles, we show how contextual information can be effectively exploited in a multi-stream ASR framework that dynamically models context-sensitive phoneme estimates generated by a long short-term memory neural network. The proposed techniques are evaluated on the SEMAINE database-a corpus containing emotionally colored conversations with a cognitive system for "Sensitive Artificial Listening".

  10. Designing for Learning and Play - The Smiley Model as Framework

    DEFF Research Database (Denmark)

    Weitze, Charlotte Lærke

    2016-01-01

    digital games. The Smiley Model inspired and provided a scaffold or a heuristic for the overall gamified learning design –- as well as for the students’ learning game design processes when creating small games turning the learning situation into an engaging experience. The audience for the experiments......This paper presents a framework for designing engaging learning experiences in games – the Smiley Model. In this Design-Based Research project, student-game-designers were learning inside a gamified learning design - while designing and implementing learning goals from curriculum into the small...... was adult upper secondary general students as well as 7th grade primary school students. The intention with this article is to inspire future learning designers that would like to experiment with integrating learning and play....

  11. A Model-driven Framework for Educational Game Design

    Directory of Open Access Journals (Sweden)

    Bill Roungas

    2016-09-01

    Full Text Available Educational games are a class of serious games whose main purpose is to teach some subject to their players. Despite the many existing design frameworks, these games are too often created in an ad-hoc manner, and typically without the use of a game design document (GDD. We argue that a reason for this phenomenon is that current ways to structure, create and update GDDs do not increase the value of the artifact in the design and development process. As a solution, we propose a model-driven, web-based knowledge management environment that supports game designers in the creation of a GDD that accounts for and relates educational and entertainment game elements. The foundation of our approach is our devised conceptual model for educational games, which also defines the structure of the design environment. We present promising results from an evaluation of our environment with eight experts in serious games.

  12. A Categorical Framework for Model Classification in the Geosciences

    Science.gov (United States)

    Hauhs, Michael; Trancón y Widemann, Baltasar; Lange, Holger

    2016-04-01

    Models have a mixed record of success in the geosciences. In meteorology, model development and implementation has been among the first and most successful examples of triggering computer technology in science. On the other hand, notorious problems such as the 'equifinality issue' in hydrology lead to a rather mixed reputation of models in other areas. The most successful models in geosciences are applications of dynamic systems theory to non-living systems or phenomena. Thus, we start from the hypothesis that the success of model applications relates to the influence of life on the phenomenon under study. We thus focus on the (formal) representation of life in models. The aim is to investigate whether disappointment in model performance is due to system properties such as heterogeneity and historicity of ecosystems, or rather reflects an abstraction and formalisation problem at a fundamental level. As a formal framework for this investigation, we use category theory as applied in computer science to specify behaviour at an interface. Its methods have been developed for translating and comparing formal structures among different application areas and seems highly suited for a classification of the current "model zoo" in the geosciences. The approach is rather abstract, with a high degree of generality but a low level of expressibility. Here, category theory will be employed to check the consistency of assumptions about life in different models. It will be shown that it is sufficient to distinguish just four logical cases to check for consistency of model content. All four cases can be formalised as variants of coalgebra-algebra homomorphisms. It can be demonstrated that transitions between the four variants affect the relevant observations (time series or spatial maps), the formalisms used (equations, decision trees) and the test criteria of success (prediction, classification) of the resulting model types. We will present examples from hydrology and ecology in

  13. The SCEC Unified Community Velocity Model (UCVM) Software Framework for Distributing and Querying Seismic Velocity Models

    Science.gov (United States)

    Maechling, P. J.; Taborda, R.; Callaghan, S.; Shaw, J. H.; Plesch, A.; Olsen, K. B.; Jordan, T. H.; Goulet, C. A.

    2017-12-01

    Crustal seismic velocity models and datasets play a key role in regional three-dimensional numerical earthquake ground-motion simulation, full waveform tomography, modern physics-based probabilistic earthquake hazard analysis, as well as in other related fields including geophysics, seismology, and earthquake engineering. The standard material properties provided by a seismic velocity model are P- and S-wave velocities and density for any arbitrary point within the geographic volume for which the model is defined. Many seismic velocity models and datasets are constructed by synthesizing information from multiple sources and the resulting models are delivered to users in multiple file formats, such as text files, binary files, HDF-5 files, structured and unstructured grids, and through computer applications that allow for interactive querying of material properties. The Southern California Earthquake Center (SCEC) has developed the Unified Community Velocity Model (UCVM) software framework to facilitate the registration and distribution of existing and future seismic velocity models to the SCEC community. The UCVM software framework is designed to provide a standard query interface to multiple, alternative velocity models, even if the underlying velocity models are defined in different formats or use different geographic projections. The UCVM framework provides a comprehensive set of open-source tools for querying seismic velocity model properties, combining regional 3D models and 1D background models, visualizing 3D models, and generating computational models in the form of regular grids or unstructured meshes that can be used as inputs for ground-motion simulations. The UCVM framework helps researchers compare seismic velocity models and build equivalent simulation meshes from alternative velocity models. These capabilities enable researchers to evaluate the impact of alternative velocity models in ground-motion simulations and seismic hazard analysis applications

  14. An Integrated Hydro-Economic Modelling Framework to Evaluate Water Allocation Strategies I: Model Development.

    NARCIS (Netherlands)

    George, B.; Malano, H.; Davidson, B.; Hellegers, P.; Bharati, L.; Sylvain, M.

    2011-01-01

    In this paper an integrated modelling framework for water resources planning and management that can be used to carry out an analysis of alternative policy scenarios for water allocation and use is described. The modelling approach is based on integrating a network allocation model (REALM) and a

  15. Formulation, construction and analysis of kinetic models of metabolism: A review of modelling frameworks

    DEFF Research Database (Denmark)

    Saa, Pedro A.; Nielsen, Lars K.

    2017-01-01

    Kinetic models are critical to predict the dynamic behaviour of metabolic networks. Mechanistic kinetic models for large networks remain uncommon due to the difficulty of fitting their parameters. Recent modelling frameworks promise new ways to overcome this obstacle while retaining predictive ca...

  16. Modelling grain growth in the framework of Rational Extended Thermodynamics

    International Nuclear Information System (INIS)

    Kertsch, Lukas; Helm, Dirk

    2016-01-01

    Grain growth is a significant phenomenon for the thermomechanical processing of metals. Since the mobility of the grain boundaries is thermally activated and energy stored in the grain boundaries is released during their motion, a mutual interaction with the process conditions occurs. To model such phenomena, a thermodynamic framework for the representation of thermomechanical coupling phenomena in metals including a microstructure description is required. For this purpose, Rational Extended Thermodynamics appears to be a useful tool. We apply an entropy principle to derive a thermodynamically consistent model for grain coarsening due to the growth and shrinkage of individual grains. Despite the rather different approaches applied, we obtain a grain growth model which is similar to existing ones and can be regarded as a thermodynamic extension of that by Hillert (1965) to more general systems. To demonstrate the applicability of the model, we compare our simulation results to grain growth experiments in pure copper by different authors, which we are able to reproduce very accurately. Finally, we study the implications of the energy release due to grain growth on the energy balance. The present unified approach combining a microstructure description and continuum mechanics is ready to be further used to develop more elaborate material models for complex thermo-chemo-mechanical coupling phenomena. (paper)

  17. Modelling grain growth in the framework of Rational Extended Thermodynamics

    Science.gov (United States)

    Kertsch, Lukas; Helm, Dirk

    2016-05-01

    Grain growth is a significant phenomenon for the thermomechanical processing of metals. Since the mobility of the grain boundaries is thermally activated and energy stored in the grain boundaries is released during their motion, a mutual interaction with the process conditions occurs. To model such phenomena, a thermodynamic framework for the representation of thermomechanical coupling phenomena in metals including a microstructure description is required. For this purpose, Rational Extended Thermodynamics appears to be a useful tool. We apply an entropy principle to derive a thermodynamically consistent model for grain coarsening due to the growth and shrinkage of individual grains. Despite the rather different approaches applied, we obtain a grain growth model which is similar to existing ones and can be regarded as a thermodynamic extension of that by Hillert (1965) to more general systems. To demonstrate the applicability of the model, we compare our simulation results to grain growth experiments in pure copper by different authors, which we are able to reproduce very accurately. Finally, we study the implications of the energy release due to grain growth on the energy balance. The present unified approach combining a microstructure description and continuum mechanics is ready to be further used to develop more elaborate material models for complex thermo-chemo-mechanical coupling phenomena.

  18. A modelling framework to simulate foliar fungal epidemics using functional-structural plant models.

    Science.gov (United States)

    Garin, Guillaume; Fournier, Christian; Andrieu, Bruno; Houlès, Vianney; Robert, Corinne; Pradal, Christophe

    2014-09-01

    Sustainable agriculture requires the identification of new, environmentally responsible strategies of crop protection. Modelling of pathosystems can allow a better understanding of the major interactions inside these dynamic systems and may lead to innovative protection strategies. In particular, functional-structural plant models (FSPMs) have been identified as a means to optimize the use of architecture-related traits. A current limitation lies in the inherent complexity of this type of modelling, and thus the purpose of this paper is to provide a framework to both extend and simplify the modelling of pathosystems using FSPMs. Different entities and interactions occurring in pathosystems were formalized in a conceptual model. A framework based on these concepts was then implemented within the open-source OpenAlea modelling platform, using the platform's general strategy of modelling plant-environment interactions and extending it to handle plant interactions with pathogens. New developments include a generic data structure for representing lesions and dispersal units, and a series of generic protocols to communicate with objects representing the canopy and its microenvironment in the OpenAlea platform. Another development is the addition of a library of elementary models involved in pathosystem modelling. Several plant and physical models are already available in OpenAlea and can be combined in models of pathosystems using this framework approach. Two contrasting pathosystems are implemented using the framework and illustrate its generic utility. Simulations demonstrate the framework's ability to simulate multiscaled interactions within pathosystems, and also show that models are modular components within the framework and can be extended. This is illustrated by testing the impact of canopy architectural traits on fungal dispersal. This study provides a framework for modelling a large number of pathosystems using FSPMs. This structure can accommodate both

  19. Computer-aided modeling framework – a generic modeling template for catalytic membrane fixed bed reactors

    DEFF Research Database (Denmark)

    Fedorova, Marina; Sin, Gürkan; Gani, Rafiqul

    2013-01-01

    and users to generate and test models systematically, efficiently and reliably. In this way, development of products and processes can be faster, cheaper and very efficient. In this contribution, as part of the framework a generic modeling template for the systematic derivation of problem specific catalytic...... membrane fixed bed models is developed. The application of the modeling template is highlighted with a case study related to the modeling of a catalytic membrane reactor coupling dehydrogenation of ethylbenzene with hydrogenation of nitrobenzene....

  20. TP-model transformation-based-control design frameworks

    CERN Document Server

    Baranyi, Péter

    2016-01-01

    This book covers new aspects and frameworks of control, design, and optimization based on the TP model transformation and its various extensions. The author outlines the three main steps of polytopic and LMI based control design: 1) development of the qLPV state-space model, 2) generation of the polytopic model; and 3) application of LMI to derive controller and observer. He goes on to describe why literature has extensively studied LMI design, but has not focused much on the second step, in part because the generation and manipulation of the polytopic form was not tractable in many cases. The author then shows how the TP model transformation facilitates this second step and hence reveals new directions, leading to powerful design procedures and the formulation of new questions. The chapters of this book, and the complex dynamical control tasks which they cover, are organized so as to present and analyze the beneficial aspect of the family of approaches (control, design, and optimization). Additionally, the b...

  1. A Learning Framework for Control-Oriented Modeling of Buildings

    Energy Technology Data Exchange (ETDEWEB)

    Rubio-Herrero, Javier; Chandan, Vikas; Siegel, Charles M.; Vishnu, Abhinav; Vrabie, Draguna L.

    2018-01-18

    Buildings consume a significant amount of energy worldwide. Several building optimization and control use cases require models of energy consumption which are control oriented, have high predictive capability, imposes minimal data pre-processing requirements, and have the ability to be adapted continuously to account for changing conditions as new data becomes available. Data driven modeling techniques, that have been investigated so far, while promising in the context of buildings, have been unable to simultaneously satisfy all the requirements mentioned above. In this context, deep learning techniques such as Recurrent Neural Networks (RNNs) hold promise, empowered by advanced computational capabilities and big data opportunities. In this paper, we propose a deep learning based methodology for the development of control oriented models for building energy management and test in on data from a real building. Results show that the proposed methodology outperforms other data driven modeling techniques significantly. We perform a detailed analysis of the proposed methodology along dimensions such as topology, sensitivity, and downsampling. Lastly, we conclude by envisioning a building analytics suite empowered by the proposed deep framework, that can drive several use cases related to building energy management.

  2. Testing a Conceptual Change Model Framework for Visual Data

    Science.gov (United States)

    Finson, Kevin D.; Pedersen, Jon E.

    2015-01-01

    An emergent data analysis technique was employed to test the veracity of a conceptual framework constructed around visual data use and instruction in science classrooms. The framework incorporated all five key components Vosniadou (2007a, 2007b) described as existing in a learner's schema: framework theory, presuppositions, conceptual domains,…

  3. Understanding Global Change: Frameworks and Models for Teaching Systems Thinking

    Science.gov (United States)

    Bean, J. R.; Mitchell, K.; Zoehfeld, K.; Oshry, A.; Menicucci, A. J.; White, L. D.; Marshall, C. R.

    2017-12-01

    The scientific and education communities must impart to teachers, students, and the public an understanding of how the various factors that drive climate and global change operate, and why the rates and magnitudes of these changes related to human perturbation of Earth system processes today are cause for deep concern. Even though effective educational modules explaining components of the Earth and climate system exist, interdisciplinary learning tools are necessary to conceptually link the causes and consequences of global changes. To address this issue, the Understanding Global Change Project at the University of California Museum of Paleontology (UCMP) at UC Berkeley developed an interdisciplinary framework that organizes global change topics into three categories: (1) causes of climate change, both human and non-human (e.g., burning of fossil fuels, deforestation, Earth's tilt and orbit), (2) Earth system processes that shape the way the Earth works (e.g., Earth's energy budget, water cycle), and (3) the measurable changes in the Earth system (e.g., temperature, precipitation, ocean acidification). To facilitate student learning about the Earth as a dynamic, interacting system, a website will provide visualizations of Earth system models and written descriptions of how each framework topic is conceptually linked to other components of the framework. These visualizations and textual summarizations of relationships and feedbacks in the Earth system are a unique and crucial contribution to science communication and education, informed by a team of interdisciplinary scientists and educators. The system models are also mechanisms by which scientists can communicate how their own work informs our understanding of the Earth system. Educators can provide context and relevancy for authentic datasets and concurrently can assess student understanding of the interconnectedness of global change phenomena. The UGC resources will be available through a web-based platform and

  4. A Survey on Hidden Markov Model (HMM) Based Intention Prediction Techniques

    OpenAIRE

    Mrs. Manisha Bharati; Dr. Santosh Lomte

    2016-01-01

    The extensive use of virtualization in implementing cloud infrastructure brings unrivaled security concerns for cloud tenants or customers and introduces an additional layer that itself must be completely configured and secured. Intruders can exploit the large amount of cloud resources for their attacks. This paper discusses two approaches In the first three features namely ongoing attacks, autonomic prevention actions, and risk measure are Integrated to our Autonomic Cloud Intrus...

  5. A FRAMEWORK FOR AN OPEN SOURCE GEOSPATIAL CERTIFICATION MODEL

    Directory of Open Access Journals (Sweden)

    T. U. R. Khan

    2016-06-01

    Full Text Available The geospatial industry is forecasted to have an enormous growth in the forthcoming years and an extended need for well-educated workforce. Hence ongoing education and training play an important role in the professional life. Parallel, in the geospatial and IT arena as well in the political discussion and legislation Open Source solutions, open data proliferation, and the use of open standards have an increasing significance. Based on the Memorandum of Understanding between International Cartographic Association, OSGeo Foundation, and ISPRS this development led to the implementation of the ICA-OSGeo-Lab imitative with its mission “Making geospatial education and opportunities accessible to all”. Discussions in this initiative and the growth and maturity of geospatial Open Source software initiated the idea to develop a framework for a worldwide applicable Open Source certification approach. Generic and geospatial certification approaches are already offered by numerous organisations, i.e., GIS Certification Institute, GeoAcademy, ASPRS, and software vendors, i. e., Esri, Oracle, and RedHat. They focus different fields of expertise and have different levels and ways of examination which are offered for a wide range of fees. The development of the certification framework presented here is based on the analysis of diverse bodies of knowledge concepts, i.e., NCGIA Core Curriculum, URISA Body Of Knowledge, USGIF Essential Body Of Knowledge, the “Geographic Information: Need to Know", currently under development, and the Geospatial Technology Competency Model (GTCM. The latter provides a US American oriented list of the knowledge, skills, and abilities required of workers in the geospatial technology industry and influenced essentially the framework of certification. In addition to the theoretical analysis of existing resources the geospatial community was integrated twofold. An online survey about the relevance of Open Source was performed and

  6. a Framework for AN Open Source Geospatial Certification Model

    Science.gov (United States)

    Khan, T. U. R.; Davis, P.; Behr, F.-J.

    2016-06-01

    The geospatial industry is forecasted to have an enormous growth in the forthcoming years and an extended need for well-educated workforce. Hence ongoing education and training play an important role in the professional life. Parallel, in the geospatial and IT arena as well in the political discussion and legislation Open Source solutions, open data proliferation, and the use of open standards have an increasing significance. Based on the Memorandum of Understanding between International Cartographic Association, OSGeo Foundation, and ISPRS this development led to the implementation of the ICA-OSGeo-Lab imitative with its mission "Making geospatial education and opportunities accessible to all". Discussions in this initiative and the growth and maturity of geospatial Open Source software initiated the idea to develop a framework for a worldwide applicable Open Source certification approach. Generic and geospatial certification approaches are already offered by numerous organisations, i.e., GIS Certification Institute, GeoAcademy, ASPRS, and software vendors, i. e., Esri, Oracle, and RedHat. They focus different fields of expertise and have different levels and ways of examination which are offered for a wide range of fees. The development of the certification framework presented here is based on the analysis of diverse bodies of knowledge concepts, i.e., NCGIA Core Curriculum, URISA Body Of Knowledge, USGIF Essential Body Of Knowledge, the "Geographic Information: Need to Know", currently under development, and the Geospatial Technology Competency Model (GTCM). The latter provides a US American oriented list of the knowledge, skills, and abilities required of workers in the geospatial technology industry and influenced essentially the framework of certification. In addition to the theoretical analysis of existing resources the geospatial community was integrated twofold. An online survey about the relevance of Open Source was performed and evaluated with 105

  7. Hierarchical HMM based learning of navigation primitives for cooperative robotic endovascular catheterization.

    Science.gov (United States)

    Rafii-Tari, Hedyeh; Liu, Jindong; Payne, Christopher J; Bicknell, Colin; Yang, Guang-Zhong

    2014-01-01

    Despite increased use of remote-controlled steerable catheter navigation systems for endovascular intervention, most current designs are based on master configurations which tend to alter natural operator tool interactions. This introduces problems to both ergonomics and shared human-robot control. This paper proposes a novel cooperative robotic catheterization system based on learning-from-demonstration. By encoding the higher-level structure of a catheterization task as a sequence of primitive motions, we demonstrate how to achieve prospective learning for complex tasks whilst incorporating subject-specific variations. A hierarchical Hidden Markov Model is used to model each movement primitive as well as their sequential relationship. This model is applied to generation of motion sequences, recognition of operator input, and prediction of future movements for the robot. The framework is validated by comparing catheter tip motions against the manual approach, showing significant improvements in the quality of catheterization. The results motivate the design of collaborative robotic systems that are intuitive to use, while reducing the cognitive workload of the operator.

  8. Structural Equation Models in a Redundancy Analysis Framework With Covariates.

    Science.gov (United States)

    Lovaglio, Pietro Giorgio; Vittadini, Giorgio

    2014-01-01

    A recent method to specify and fit structural equation modeling in the Redundancy Analysis framework based on so-called Extended Redundancy Analysis (ERA) has been proposed in the literature. In this approach, the relationships between the observed exogenous variables and the observed endogenous variables are moderated by the presence of unobservable composites, estimated as linear combinations of exogenous variables. However, in the presence of direct effects linking exogenous and endogenous variables, or concomitant indicators, the composite scores are estimated by ignoring the presence of the specified direct effects. To fit structural equation models, we propose a new specification and estimation method, called Generalized Redundancy Analysis (GRA), allowing us to specify and fit a variety of relationships among composites, endogenous variables, and external covariates. The proposed methodology extends the ERA method, using a more suitable specification and estimation algorithm, by allowing for covariates that affect endogenous indicators indirectly through the composites and/or directly. To illustrate the advantages of GRA over ERA we propose a simulation study of small samples. Moreover, we propose an application aimed at estimating the impact of formal human capital on the initial earnings of graduates of an Italian university, utilizing a structural model consistent with well-established economic theory.

  9. A Production Model for Construction: A Theoretical Framework

    Directory of Open Access Journals (Sweden)

    Ricardo Antunes

    2015-03-01

    Full Text Available The building construction industry faces challenges, such as increasing project complexity and scope requirements, but shorter deadlines. Additionally, economic uncertainty and rising business competition with a subsequent decrease in profit margins for the industry demands the development of new approaches to construction management. However, the building construction sector relies on practices based on intuition and experience, overlooking the dynamics of its production system. Furthermore, researchers maintain that the construction industry has no history of the application of mathematical approaches to model and manage production. Much work has been carried out on how manufacturing practices apply to construction projects, mostly lean principles. Nevertheless, there has been little research to understand the fundamental mechanisms of production in construction. This study develops an in-depth literature review to examine the existing knowledge about production models and their characteristics in order to establish a foundation for dynamic production systems management in construction. As a result, a theoretical framework is proposed, which will be instrumental in the future development of mathematical production models aimed at predicting the performance and behaviour of dynamic project-based systems in construction.

  10. Conceptual Modeling Framework for E-Area PA HELP Infiltration Model Simulations

    Energy Technology Data Exchange (ETDEWEB)

    Dyer, J. A. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL)

    2017-11-30

    A conceptual modeling framework based on the proposed E-Area Low-Level Waste Facility (LLWF) closure cap design is presented for conducting Hydrologic Evaluation of Landfill Performance (HELP) model simulations of intact and subsided cap infiltration scenarios for the next E-Area Performance Assessment (PA).

  11. Airline Sustainability Modeling: A New Framework with Application of Bayesian Structural Equation Modeling

    DEFF Research Database (Denmark)

    Salarzadeh Jenatabadi, Hashem; Babashamsi, Peyman; Khajeheian, Datis

    2016-01-01

    There are many factors which could influence the sustainability of airlines. The main purpose of this study is to introduce a framework for a financial sustainability index and model it based on structural equation modeling (SEM) with maximum likelihood and Bayesian predictors. The introduced...

  12. A Bayesian Approach for Structural Learning with Hidden Markov Models

    Directory of Open Access Journals (Sweden)

    Cen Li

    2002-01-01

    Full Text Available Hidden Markov Models(HMM have proved to be a successful modeling paradigm for dynamic and spatial processes in many domains, such as speech recognition, genomics, and general sequence alignment. Typically, in these applications, the model structures are predefined by domain experts. Therefore, the HMM learning problem focuses on the learning of the parameter values of the model to fit the given data sequences. However, when one considers other domains, such as, economics and physiology, model structure capturing the system dynamic behavior is not available. In order to successfully apply the HMM methodology in these domains, it is important that a mechanism is available for automatically deriving the model structure from the data. This paper presents a HMM learning procedure that simultaneously learns the model structure and the maximum likelihood parameter values of a HMM from data. The HMM model structures are derived based on the Bayesian model selection methodology. In addition, we introduce a new initialization procedure for HMM parameter value estimation based on the K-means clustering method. Experimental results with artificially generated data show the effectiveness of the approach.

  13. AN INTEGRATED MODELING FRAMEWORK FOR CARBON MANAGEMENT TECHNOLOGIES

    Energy Technology Data Exchange (ETDEWEB)

    Anand B. Rao; Edward S. Rubin; Michael B. Berkenpas

    2004-03-01

    CO{sub 2} capture and storage (CCS) is gaining widespread interest as a potential method to control greenhouse gas emissions from fossil fuel sources, especially electric power plants. Commercial applications of CO{sub 2} separation and capture technologies are found in a number of industrial process operations worldwide. Many of these capture technologies also are applicable to fossil fuel power plants, although applications to large-scale power generation remain to be demonstrated. This report describes the development of a generalized modeling framework to assess alternative CO{sub 2} capture and storage options in the context of multi-pollutant control requirements for fossil fuel power plants. The focus of the report is on post-combustion CO{sub 2} capture using amine-based absorption systems at pulverized coal-fired plants, which are the most prevalent technology used for power generation today. The modeling framework builds on the previously developed Integrated Environmental Control Model (IECM). The expanded version with carbon sequestration is designated as IECM-cs. The expanded modeling capability also includes natural gas combined cycle (NGCC) power plants and integrated coal gasification combined cycle (IGCC) systems as well as pulverized coal (PC) plants. This report presents details of the performance and cost models developed for an amine-based CO{sub 2} capture system, representing the baseline of current commercial technology. The key uncertainties and variability in process design, performance and cost parameters which influence the overall cost of carbon mitigation also are characterized. The new performance and cost models for CO{sub 2} capture systems have been integrated into the IECM-cs, along with models to estimate CO{sub 2} transport and storage costs. The CO{sub 2} control system also interacts with other emission control technologies such as flue gas desulfurization (FGD) systems for SO{sub 2} control. The integrated model is applied to

  14. A Global Modeling Framework for Plasma Kinetics: Development and Applications

    Science.gov (United States)

    Parsey, Guy Morland

    The modern study of plasmas, and applications thereof, has developed synchronously with com- puter capabilities since the mid-1950s. Complexities inherent to these charged-particle, many- body, systems have resulted in the development of multiple simulation methods (particle-in-cell, fluid, global modeling, etc.) in order to both explain observed phenomena and predict outcomes of plasma applications. Recognizing that different algorithms are chosen to best address specific topics of interest, this thesis centers around the development of an open-source global model frame- work for the focused study of non-equilibrium plasma kinetics. After verification and validation of the framework, it was used to study two physical phenomena: plasma-assisted combustion and the recently proposed optically-pumped rare gas metastable laser. Global models permeate chemistry and plasma science, relying on spatial averaging to focus attention on the dynamics of reaction networks. Defined by a set of species continuity and energy conservation equations, the required data and constructed systems are conceptually similar across most applications, providing a light platform for exploratory and result-search parameter scan- ning. Unfortunately, it is common practice for custom code to be developed for each application-- an enormous duplication of effort which negatively affects the quality of the software produced. Presented herein, the Python-based Kinetic Global Modeling framework (KGMf) was designed to support all modeling phases: collection and analysis of reaction data, construction of an exportable system of model ODEs, and a platform for interactive evaluation and post-processing analysis. A symbolic ODE system is constructed for interactive manipulation and generation of a Jacobian, both of which are compiled as operation-optimized C-code. Plasma-assisted combustion and ignition (PAC/PAI) embody the modernization of burning fuel by opening up new avenues of control and optimization

  15. Models of Recognition, Repetition Priming, and Fluency : Exploring a New Framework

    Science.gov (United States)

    Berry, Christopher J.; Shanks, David R.; Speekenbrink, Maarten; Henson, Richard N. A.

    2012-01-01

    We present a new modeling framework for recognition memory and repetition priming based on signal detection theory. We use this framework to specify and test the predictions of 4 models: (a) a single-system (SS) model, in which one continuous memory signal drives recognition and priming; (b) a multiple-systems-1 (MS1) model, in which completely…

  16. Retrofitting Non-Cognitive-Diagnostic Reading Assessment under the Generalized DINA Model Framework

    Science.gov (United States)

    Chen, Huilin; Chen, Jinsong

    2016-01-01

    Cognitive diagnosis models (CDMs) are psychometric models developed mainly to assess examinees' specific strengths and weaknesses in a set of skills or attributes within a domain. By adopting the Generalized-DINA model framework, the recently developed general modeling framework, we attempted to retrofit the PISA reading assessments, a…

  17. A computer-aided framework for development, identification andmanagement of physiologically-based pharmacokinetic models

    DEFF Research Database (Denmark)

    Heitzig, Martina; Linninger, Andreas; Sin, Gürkan

    2014-01-01

    The objective of this work is the development of a generic computer-aided modelling framework to support the development of physiologically-based pharmacokinetic models thereby increasing the efficiency and quality of the modelling process. In particular, the framework systematizes the modelling...

  18. An Access Control Model for the Uniframe Framework

    National Research Council Canada - National Science Library

    Crespi, Alexander M

    2005-01-01

    ... security characteristics from the properties of individual components would aid in the creation of more secure systems In this thesis, a framework for characterizing the access control properties...

  19. A unified framework for benchmark dose estimation applied to mixed models and model averaging

    DEFF Research Database (Denmark)

    Ritz, Christian; Gerhard, Daniel; Hothorn, Ludwig A.

    2013-01-01

    for hierarchical data structures, reflecting increasingly common types of assay data. We illustrate the usefulness of the methodology by means of a cytotoxicology example where the sensitivity of two types of assays are evaluated and compared. By means of a simulation study, we show that the proposed framework......This article develops a framework for benchmark dose estimation that allows intrinsically nonlinear dose-response models to be used for continuous data in much the same way as is already possible for quantal data. This means that the same dose-response model equations may be applied to both...

  20. Computer-aided modeling framework for efficient model development, analysis and identification

    DEFF Research Database (Denmark)

    Heitzig, Martina; Sin, Gürkan; Sales Cruz, Mauricio

    2011-01-01

    Model-based computer aided product-process engineering has attained increased importance in a number of industries, including pharmaceuticals, petrochemicals, fine chemicals, polymers, biotechnology, food, energy, and water. This trend is set to continue due to the substantial benefits computer-aided...... methods introduce. The key prerequisite of computer-aided product-process engineering is however the availability of models of different types, forms, and application modes. The development of the models required for the systems under investigation tends to be a challenging and time-consuming task....... The methodology has been implemented into a computer-aided modeling framework, which combines expert skills, tools, and database connections that are required for the different steps of the model development work-flow with the goal to increase the efficiency of the modeling process. The framework has two main...

  1. Modeling and simulation of complex systems a framework for efficient agent-based modeling and simulation

    CERN Document Server

    Siegfried, Robert

    2014-01-01

    Robert Siegfried presents a framework for efficient agent-based modeling and simulation of complex systems. He compares different approaches for describing structure and dynamics of agent-based models in detail. Based on this evaluation the author introduces the "General Reference Model for Agent-based Modeling and Simulation" (GRAMS). Furthermore he presents parallel and distributed simulation approaches for execution of agent-based models -from small scale to very large scale. The author shows how agent-based models may be executed by different simulation engines that utilize underlying hard

  2. Exploring Higher Education Governance: Analytical Models and Heuristic Frameworks

    Directory of Open Access Journals (Sweden)

    Burhan FINDIKLI

    2017-08-01

    Full Text Available Governance in higher education, both at institutional and systemic levels, has experienced substantial changes within recent decades because of a range of world-historical processes such as massification, growth, globalization, marketization, public sector reforms, and the emergence of knowledge economy and society. These developments have made governance arrangements and decision-making processes in higher education more complex and multidimensional more than ever and forced scholars to build new analytical and heuristic tools and strategies to grasp the intricacy and diversity of higher education governance dynamics. This article provides a systematic discussion of how and through which tools prominent scholars of higher education have analyzed governance in this sector by examining certain heuristic frameworks and analytical models. Additionally, the article shows how social scientific analysis of governance in higher education has proceeded in a cumulative way with certain revisions and syntheses rather than radical conceptual and theoretical ruptures from Burton R. Clark’s seminal work to the present, revealing conceptual and empirical junctures between them.

  3. A Hybrid Programming Framework for Modeling and Solving Constraint Satisfaction and Optimization Problems

    OpenAIRE

    Sitek, Paweł; Wikarek, Jarosław

    2016-01-01

    This paper proposes a hybrid programming framework for modeling and solving of constraint satisfaction problems (CSPs) and constraint optimization problems (COPs). Two paradigms, CLP (constraint logic programming) and MP (mathematical programming), are integrated in the framework. The integration is supplemented with the original method of problem transformation, used in the framework as a presolving method. The transformation substantially reduces the feasible solution space. The framework a...

  4. Modelling Supported Driving as an Optimal Control Cycle : Framework and Model Characteristics

    NARCIS (Netherlands)

    Wang, M.; Treiber, M.; Daamen, W.; Hoogendoorn, S.P.; Van Arem, B.

    2013-01-01

    Driver assistance systems support drivers in operating vehicles in a safe, comfortable and efficient way, and thus may induce changes in traffic flow characteristics. This paper puts forward a receding horizon control framework to model driver assistance and cooperative systems. The accelerations of

  5. The BlueSky Smoke Modeling Framework: Recent Developments

    Science.gov (United States)

    Sullivan, D. C.; Larkin, N.; Raffuse, S. M.; Strand, T.; ONeill, S. M.; Leung, F. T.; Qu, J. J.; Hao, X.

    2012-12-01

    (TRMM) Multi-satellite Precipitation Analysis Real-Time (TMPA-RT) data set is being used to improve dead fuel moisture estimates. - EastFire live fuel moisture estimates, which are derived from NASA's MODIS direct broadcast, are being used to improve live fuel moisture estimates. - NASA's Multi-angle Imaging Spectroradiometer (MISR) stereo heights are being used to improve estimates of plume injection heights. Further, the Fire Location and Modeling of Burning Emissions (FLAMBÉ) model was incorporated into the BlueSky Framework as an alternative means of calculating fire emissions. FLAMBÉ directly estimates emissions on the basis of fire detections and radiance measures from NASA's MODIS and NOAA's GOES satellites. (The authors gratefully acknowledge NASA's Applied Sciences Program [Grant Nos. NN506AB52A and NNX09AV76G)], the USDA Forest Service, and the Joint Fire Science Program for their support.)

  6. A device model framework for magnetoresistive sensors based on the Stoner–Wohlfarth model

    International Nuclear Information System (INIS)

    Bruckner, Florian; Bergmair, Bernhard; Brueckl, Hubert; Palmesi, Pietro; Buder, Anton; Satz, Armin; Suess, Dieter

    2015-01-01

    The Stoner–Wohlfarth (SW) model provides an efficient analytical model to describe the behavior of magnetic layers within magnetoresistive sensors. Combined with a proper description of magneto-resistivity an efficient device model can be derived, which is necessary for an optimal electric circuit design. Parameters of the model are determined by global optimization of an application specific cost function which contains measured resistances for different applied fields. Several application cases are examined and used for validation of the device model. - Highlights: • An efficient device model framework for various types of magnetoresistive sensors is presented. • The model is based on the analytical solution of the Stoner–Wohlfarth model. • Numerical optimization methods provide optimal model parameters for a different application cases. • The model is applied to several application cases and is able to reproduce measured hysteresis and swiching behavior

  7. GLOFRIM v1.0-A globally applicable computational framework for integrated hydrological-hydrodynamic modelling

    NARCIS (Netherlands)

    Hoch, Jannis M.; Neal, Jeffrey C.; Baart, Fedor; Van Beek, Rens; Winsemius, Hessel C.; Bates, Paul D.; Bierkens, Marc F.P.

    2017-01-01

    We here present GLOFRIM, a globally applicable computational framework for integrated hydrological-hydrodynamic modelling. GLOFRIM facilitates spatially explicit coupling of hydrodynamic and hydrologic models and caters for an ensemble of models to be coupled. It currently encompasses the global

  8. Managing uncertainty in integrated environmental modelling: The UncertWeb framework.

    NARCIS (Netherlands)

    Bastin, L.; Cornford, D.; Jones, R.; Heuvelink, G.B.M.; Pebesma, E.; Stasch, C.; Nativi, S.; Mazzetti, P.

    2013-01-01

    Web-based distributed modelling architectures are gaining increasing recognition as potentially useful tools to build holistic environmental models, combining individual components in complex workflows. However, existing web-based modelling frameworks currently offer no support for managing

  9. D Geological Framework Models as a Teaching Aid for Geoscience

    Science.gov (United States)

    Kessler, H.; Ward, E.; Geological ModelsTeaching Project Team

    2010-12-01

    3D geological models have great potential as a resource for universities when teaching foundation geological concepts as it allows the student to visualise and interrogate UK geology. They are especially useful when dealing with the conversion of 2D field, map and GIS outputs into three dimensional geological units, which is a common problem for all students of geology. Today’s earth science students use a variety of skills and processes during their learning experience including the application of schema’s, spatial thinking, image construction, detecting patterns, memorising figures, mental manipulation and interpretation, making predictions and deducing the orientation of themselves and the rocks. 3D geological models can reinforce spatial thinking strategies and encourage students to think about processes and properties, in turn helping the student to recognise pre-learnt geological principles in the field and to convert what they see at the surface into a picture of what is going on at depth. Learning issues faced by students may also be encountered by experts, policy managers, and stakeholders when dealing with environmental problems. Therefore educational research of student learning in earth science may also improve environmental decision making. 3D geological framework models enhance the learning of Geosciences because they: ● enable a student to observe, manipulate and interpret geology; in particular the models instantly convert two-dimensional geology (maps, boreholes and cross-sections) into three dimensions which is a notoriously difficult geospatial skill to acquire. ● can be orientated to whatever the user finds comfortable and most aids recognition and interpretation. ● can be used either to teach geosciences to complete beginners or add to experienced students body of knowledge (whatever point that may be at). Models could therefore be packaged as a complete educational journey or students and tutor can select certain areas of the model

  10. Genetic Algorithms Principles Towards Hidden Markov Model

    Directory of Open Access Journals (Sweden)

    Nabil M. Hewahi

    2011-10-01

    Full Text Available In this paper we propose a general approach based on Genetic Algorithms (GAs to evolve Hidden Markov Models (HMM. The problem appears when experts assign probability values for HMM, they use only some limited inputs. The assigned probability values might not be accurate to serve in other cases related to the same domain. We introduce an approach based on GAs to find
    out the suitable probability values for the HMM to be mostly correct in more cases than what have been used to assign the probability values.

  11. Airline Sustainability Modeling: A New Framework with Application of Bayesian Structural Equation Modeling

    Directory of Open Access Journals (Sweden)

    Hashem Salarzadeh Jenatabadi

    2016-11-01

    Full Text Available There are many factors which could influence the sustainability of airlines. The main purpose of this study is to introduce a framework for a financial sustainability index and model it based on structural equation modeling (SEM with maximum likelihood and Bayesian predictors. The introduced framework includes economic performance, operational performance, cost performance, and financial performance. Based on both Bayesian SEM (Bayesian-SEM and Classical SEM (Classical-SEM, it was found that economic performance with both operational performance and cost performance are significantly related to the financial performance index. The four mathematical indices employed are root mean square error, coefficient of determination, mean absolute error, and mean absolute percentage error to compare the efficiency of Bayesian-SEM and Classical-SEM in predicting the airline financial performance. The outputs confirmed that the framework with Bayesian prediction delivered a good fit with the data, although the framework predicted with a Classical-SEM approach did not prepare a well-fitting model. The reasons for this discrepancy between Classical and Bayesian predictions, as well as the potential advantages and caveats with the application of Bayesian approach in airline sustainability studies, are debated.

  12. Estimation methods for nonlinear state-space models in ecology

    DEFF Research Database (Denmark)

    Pedersen, Martin Wæver; Berg, Casper Willestofte; Thygesen, Uffe Høgsbro

    2011-01-01

    The use of nonlinear state-space models for analyzing ecological systems is increasing. A wide range of estimation methods for such models are available to ecologists, however it is not always clear, which is the appropriate method to choose. To this end, three approaches to estimation in the theta...... logistic model for population dynamics were benchmarked by Wang (2007). Similarly, we examine and compare the estimation performance of three alternative methods using simulated data. The first approach is to partition the state-space into a finite number of states and formulate the problem as a hidden...... Markov model (HMM). The second method uses the mixed effects modeling and fast numerical integration framework of the AD Model Builder (ADMB) open-source software. The third alternative is to use the popular Bayesian framework of BUGS. The study showed that state and parameter estimation performance...

  13. Insight into model mechanisms through automatic parameter fitting: a new methodological framework for model development.

    Science.gov (United States)

    Tøndel, Kristin; Niederer, Steven A; Land, Sander; Smith, Nicolas P

    2014-05-20

    Striking a balance between the degree of model complexity and parameter identifiability, while still producing biologically feasible simulations using modelling is a major challenge in computational biology. While these two elements of model development are closely coupled, parameter fitting from measured data and analysis of model mechanisms have traditionally been performed separately and sequentially. This process produces potential mismatches between model and data complexities that can compromise the ability of computational frameworks to reveal mechanistic insights or predict new behaviour. In this study we address this issue by presenting a generic framework for combined model parameterisation, comparison of model alternatives and analysis of model mechanisms. The presented methodology is based on a combination of multivariate metamodelling (statistical approximation of the input-output relationships of deterministic models) and a systematic zooming into biologically feasible regions of the parameter space by iterative generation of new experimental designs and look-up of simulations in the proximity of the measured data. The parameter fitting pipeline includes an implicit sensitivity analysis and analysis of parameter identifiability, making it suitable for testing hypotheses for model reduction. Using this approach, under-constrained model parameters, as well as the coupling between parameters within the model are identified. The methodology is demonstrated by refitting the parameters of a published model of cardiac cellular mechanics using a combination of measured data and synthetic data from an alternative model of the same system. Using this approach, reduced models with simplified expressions for the tropomyosin/crossbridge kinetics were found by identification of model components that can be omitted without affecting the fit to the parameterising data. Our analysis revealed that model parameters could be constrained to a standard deviation of on

  14. Theories, models and frameworks used in capacity building interventions relevant to public health: a systematic review.

    Science.gov (United States)

    Bergeron, Kim; Abdi, Samiya; DeCorby, Kara; Mensah, Gloria; Rempel, Benjamin; Manson, Heather

    2017-11-28

    There is limited research on capacity building interventions that include theoretical foundations. The purpose of this systematic review is to identify underlying theories, models and frameworks used to support capacity building interventions relevant to public health practice. The aim is to inform and improve capacity building practices and services offered by public health organizations. Four search strategies were used: 1) electronic database searching; 2) reference lists of included papers; 3) key informant consultation; and 4) grey literature searching. Inclusion and exclusion criteria are outlined with included papers focusing on capacity building, learning plans, professional development plans in combination with tools, resources, processes, procedures, steps, model, framework, guideline, described in a public health or healthcare setting, or non-government, government, or community organizations as they relate to healthcare, and explicitly or implicitly mention a theory, model and/or framework that grounds the type of capacity building approach developed. Quality assessment were performed on all included articles. Data analysis included a process for synthesizing, analyzing and presenting descriptive summaries, categorizing theoretical foundations according to which theory, model and/or framework was used and whether or not the theory, model or framework was implied or explicitly identified. Nineteen articles were included in this review. A total of 28 theories, models and frameworks were identified. Of this number, two theories (Diffusion of Innovations and Transformational Learning), two models (Ecological and Interactive Systems Framework for Dissemination and Implementation) and one framework (Bloom's Taxonomy of Learning) were identified as the most frequently cited. This review identifies specific theories, models and frameworks to support capacity building interventions relevant to public health organizations. It provides public health practitioners

  15. Modeling sports highlights using a time-series clustering framework and model interpretation

    Science.gov (United States)

    Radhakrishnan, Regunathan; Otsuka, Isao; Xiong, Ziyou; Divakaran, Ajay

    2005-01-01

    In our past work on sports highlights extraction, we have shown the utility of detecting audience reaction using an audio classification framework. The audio classes in the framework were chosen based on intuition. In this paper, we present a systematic way of identifying the key audio classes for sports highlights extraction using a time series clustering framework. We treat the low-level audio features as a time series and model the highlight segments as "unusual" events in a background of an "usual" process. The set of audio classes to characterize the sports domain is then identified by analyzing the consistent patterns in each of the clusters output from the time series clustering framework. The distribution of features from the training data so obtained for each of the key audio classes, is parameterized by a Minimum Description Length Gaussian Mixture Model (MDL-GMM). We also interpret the meaning of each of the mixture components of the MDL-GMM for the key audio class (the "highlight" class) that is correlated with highlight moments. Our results show that the "highlight" class is a mixture of audience cheering and commentator's excited speech. Furthermore, we show that the precision-recall performance for highlights extraction based on this "highlight" class is better than that of our previous approach which uses only audience cheering as the key highlight class.

  16. Designing a framework to design a business model for the 'bottom of the pyramid' population

    NARCIS (Netherlands)

    Ver loren van Themaat, Tanye; Schutte, Cornelius S.L.; Lutters, Diederick

    2013-01-01

    This article presents a framework for developing and designing a business model to target the bottom of the pyramid (BoP) population. Using blue ocean strategy and business model literature, integrated with research on the BoP, the framework offers a systematic approach for organisations to analyse

  17. A Framework for Developing the Structure of Public Health Economic Models.

    Science.gov (United States)

    Squires, Hazel; Chilcott, James; Akehurst, Ronald; Burr, Jennifer; Kelly, Michael P

    2016-01-01

    A conceptual modeling framework is a methodology that assists modelers through the process of developing a model structure. Public health interventions tend to operate in dynamically complex systems. Modeling public health interventions requires broader considerations than clinical ones. Inappropriately simple models may lead to poor validity and credibility, resulting in suboptimal allocation of resources. This article presents the first conceptual modeling framework for public health economic evaluation. The framework presented here was informed by literature reviews of the key challenges in public health economic modeling and existing conceptual modeling frameworks; qualitative research to understand the experiences of modelers when developing public health economic models; and piloting a draft version of the framework. The conceptual modeling framework comprises four key principles of good practice and a proposed methodology. The key principles are that 1) a systems approach to modeling should be taken; 2) a documented understanding of the problem is imperative before and alongside developing and justifying the model structure; 3) strong communication with stakeholders and members of the team throughout model development is essential; and 4) a systematic consideration of the determinants of health is central to identifying the key impacts of public health interventions. The methodology consists of four phases: phase A, aligning the framework with the decision-making process; phase B, identifying relevant stakeholders; phase C, understanding the problem; and phase D, developing and justifying the model structure. Key areas for further research involve evaluation of the framework in diverse case studies and the development of methods for modeling individual and social behavior. This approach could improve the quality of Public Health economic models, supporting efficient allocation of scarce resources. Copyright © 2016 International Society for Pharmacoeconomics

  18. Professional Development Recognizing Technology Integration Modeled after the TPACK Framework

    Science.gov (United States)

    McCusker, Laura

    2017-01-01

    Public school teachers within a Pennsylvania intermediate unit are receiving inadequate job-embedded professional development that recognizes knowledge of content, pedagogy, and technology integration, as outlined by Mishra and Koehler's Technological Pedagogical Content Knowledge (TPACK) framework (2006). A school environment where teachers are…

  19. A conceptual modeling framework for discrete event simulation using hierarchical control structures.

    Science.gov (United States)

    Furian, N; O'Sullivan, M; Walker, C; Vössner, S; Neubacher, D

    2015-08-01

    Conceptual Modeling (CM) is a fundamental step in a simulation project. Nevertheless, it is only recently that structured approaches towards the definition and formulation of conceptual models have gained importance in the Discrete Event Simulation (DES) community. As a consequence, frameworks and guidelines for applying CM to DES have emerged and discussion of CM for DES is increasing. However, both the organization of model-components and the identification of behavior and system control from standard CM approaches have shortcomings that limit CM's applicability to DES. Therefore, we discuss the different aspects of previous CM frameworks and identify their limitations. Further, we present the Hierarchical Control Conceptual Modeling framework that pays more attention to the identification of a models' system behavior, control policies and dispatching routines and their structured representation within a conceptual model. The framework guides the user step-by-step through the modeling process and is illustrated by a worked example.

  20. Hidden Markov modelling of movement data from fish

    DEFF Research Database (Denmark)

    Pedersen, Martin Wæver

    Movement data from marine animals tagged with electronic tags are becoming increasingly diverse and plentiful. This trend entails a need for statistical methods that are able to filter the observations to extract the ecologically relevant content. This dissertation focuses on the development...... the behaviour of the animal. With the extended model can migratory and resident movement behaviour be related to geographical regions. For population inference multiple individual state-space analyses can be interconnected using mixed effects modelling. This framework provides parameter estimates...... approximated. This furthermore enables accurate probability densities of location to be computed. Finally, the performance of the HMM approach in analysing nonlinear state space models is compared with two alternatives: the AD Model Builder framework and BUGS, which relies on Markov chain Monte Carlo...

  1. Globally COnstrained Local Function Approximation via Hierarchical Modelling, a Framework for System Modelling under Partial Information

    DEFF Research Database (Denmark)

    Øjelund, Henrik; Sadegh, Payman

    2000-01-01

    be obtained. This paper presents a new approach for system modelling under partial (global) information (or the so called Gray-box modelling) that seeks to perserve the benefits of the global as well as local methodologies sithin a unified framework. While the proposed technique relies on local approximations......Local function approximations concern fitting low order models to weighted data in neighbourhoods of the points where the approximations are desired. Despite their generality and convenience of use, local models typically suffer, among others, from difficulties arising in physical interpretation...... simultaneously with the (local estimates of) function values. The approach is applied to modelling of a linear time variant dynamic system under prior linear time invariant structure where local regression fails as a result of high dimensionality....

  2. A conceptual modeling framework for discrete event simulation using hierarchical control structures

    Science.gov (United States)

    Furian, N.; O’Sullivan, M.; Walker, C.; Vössner, S.; Neubacher, D.

    2015-01-01

    Conceptual Modeling (CM) is a fundamental step in a simulation project. Nevertheless, it is only recently that structured approaches towards the definition and formulation of conceptual models have gained importance in the Discrete Event Simulation (DES) community. As a consequence, frameworks and guidelines for applying CM to DES have emerged and discussion of CM for DES is increasing. However, both the organization of model-components and the identification of behavior and system control from standard CM approaches have shortcomings that limit CM’s applicability to DES. Therefore, we discuss the different aspects of previous CM frameworks and identify their limitations. Further, we present the Hierarchical Control Conceptual Modeling framework that pays more attention to the identification of a models’ system behavior, control policies and dispatching routines and their structured representation within a conceptual model. The framework guides the user step-by-step through the modeling process and is illustrated by a worked example. PMID:26778940

  3. Strategic assessment of capacity consumption in railway networks: Framework and model

    DEFF Research Database (Denmark)

    Jensen, Lars Wittrup; Landex, Alex; Nielsen, Otto Anker

    2017-01-01

    In this paper, we develop a new framework for strategic planning purposes to calculate railway infrastructure occupation and capacity consumption in networks, independent of a timetable. Furthermore, a model implementing the framework is presented. In this model different train sequences...... are obtained efficiently with little input. The case illustrates the model's ability to quantify the capacity gain from infrastructure scenario to infrastructure scenario which can be used to increase the number of trains or improve the robustness of the system....

  4. A Framework Proposal For Choosing A New Business Implementation Model In Henkel

    OpenAIRE

    Li, Tsz Wan

    2015-01-01

    Henkel's New Business team is a corporate venturing unit that explores corporate entrepreneurial activities on behalf of Henkel Adhesives Technologies. The new business ideas are implemented through one of these models: incubator, venturing or innovation ecosystem. In current practice, there is no systematic framework in place to choose the implementation model. The goal of the thesis is to propose a framework for choosing the most appropriate model for implementation of a new business idea i...

  5. Framework for product knowledge and product related knowledge which supports product modelling for mass customization

    DEFF Research Database (Denmark)

    Riis, Jesper; Hansen, Benjamin Loer; Hvam, Lars

    2003-01-01

    on experience from product modelling projects in several companies. Among them for example companies manufacturing electronic switchboards, spray dryer systems and air conditioning equipment. The framework is divided into three views: the product knowledge view, the life phase system view and the transformation...... and personalization. The framework for product knowledge and product related knowledge is based on the following theories: axiomatic design, technical systems, theory of domains, theory of structuring, theory of properties and the framework for the content of product and product related models. The framework is built......The article presents a framework for product knowledge and product related knowledge which can be used to support the product modelling process which is needed for developing IT systems. These IT systems are important tools for many companies when they aim at achieving mass customization...

  6. Hydrogeologic Framework Model for the Saturated Zone Site Scale flow and Transport Model

    Energy Technology Data Exchange (ETDEWEB)

    T. Miller

    2004-11-15

    The purpose of this report is to document the 19-unit, hydrogeologic framework model (19-layer version, output of this report) (HFM-19) with regard to input data, modeling methods, assumptions, uncertainties, limitations, and validation of the model results in accordance with AP-SIII.10Q, Models. The HFM-19 is developed as a conceptual model of the geometric extent of the hydrogeologic units at Yucca Mountain and is intended specifically for use in the development of the ''Saturated Zone Site-Scale Flow Model'' (BSC 2004 [DIRS 170037]). Primary inputs to this model report include the GFM 3.1 (DTN: MO9901MWDGFM31.000 [DIRS 103769]), borehole lithologic logs, geologic maps, geologic cross sections, water level data, topographic information, and geophysical data as discussed in Section 4.1. Figure 1-1 shows the information flow among all of the saturated zone (SZ) reports and the relationship of this conceptual model in that flow. The HFM-19 is a three-dimensional (3-D) representation of the hydrogeologic units surrounding the location of the Yucca Mountain geologic repository for spent nuclear fuel and high-level radioactive waste. The HFM-19 represents the hydrogeologic setting for the Yucca Mountain area that covers about 1,350 km2 and includes a saturated thickness of about 2.75 km. The boundaries of the conceptual model were primarily chosen to be coincident with grid cells in the Death Valley regional groundwater flow model (DTN: GS960808312144.003 [DIRS 105121]) such that the base of the site-scale SZ flow model is consistent with the base of the regional model (2,750 meters below a smoothed version of the potentiometric surface), encompasses the exploratory boreholes, and provides a framework over the area of interest for groundwater flow and radionuclide transport modeling. In depth, the model domain extends from land surface to the base of the regional groundwater flow model (D'Agnese et al. 1997 [DIRS 100131], p 2). For the site

  7. Hydrogeologic Framework Model for the Saturated Zone Site Scale flow and Transport Model

    International Nuclear Information System (INIS)

    Miller, T.

    2004-01-01

    The purpose of this report is to document the 19-unit, hydrogeologic framework model (19-layer version, output of this report) (HFM-19) with regard to input data, modeling methods, assumptions, uncertainties, limitations, and validation of the model results in accordance with AP-SIII.10Q, Models. The HFM-19 is developed as a conceptual model of the geometric extent of the hydrogeologic units at Yucca Mountain and is intended specifically for use in the development of the ''Saturated Zone Site-Scale Flow Model'' (BSC 2004 [DIRS 170037]). Primary inputs to this model report include the GFM 3.1 (DTN: MO9901MWDGFM31.000 [DIRS 103769]), borehole lithologic logs, geologic maps, geologic cross sections, water level data, topographic information, and geophysical data as discussed in Section 4.1. Figure 1-1 shows the information flow among all of the saturated zone (SZ) reports and the relationship of this conceptual model in that flow. The HFM-19 is a three-dimensional (3-D) representation of the hydrogeologic units surrounding the location of the Yucca Mountain geologic repository for spent nuclear fuel and high-level radioactive waste. The HFM-19 represents the hydrogeologic setting for the Yucca Mountain area that covers about 1,350 km2 and includes a saturated thickness of about 2.75 km. The boundaries of the conceptual model were primarily chosen to be coincident with grid cells in the Death Valley regional groundwater flow model (DTN: GS960808312144.003 [DIRS 105121]) such that the base of the site-scale SZ flow model is consistent with the base of the regional model (2,750 meters below a smoothed version of the potentiometric surface), encompasses the exploratory boreholes, and provides a framework over the area of interest for groundwater flow and radionuclide transport modeling. In depth, the model domain extends from land surface to the base of the regional groundwater flow model (D'Agnese et al. 1997 [DIRS 100131], p 2). For the site-scale SZ flow model, the HFM

  8. Applying the Nominal Response Model within a Longitudinal Framework to Construct the Positive Family Relationships Scale

    Science.gov (United States)

    Preston, Kathleen Suzanne Johnson; Parral, Skye N.; Gottfried, Allen W.; Oliver, Pamella H.; Gottfried, Adele Eskeles; Ibrahim, Sirena M.; Delany, Danielle

    2015-01-01

    A psychometric analysis was conducted using the nominal response model under the item response theory framework to construct the Positive Family Relationships scale. Using data from the Fullerton Longitudinal Study, this scale was constructed within a long-term longitudinal framework spanning middle childhood through adolescence. Items tapping…

  9. Towards a Framework for Modelling and Verification of Relay Interlocking Systems

    DEFF Research Database (Denmark)

    Haxthausen, Anne Elisabeth

    2011-01-01

    This paper describes a framework currently under development for modelling, simulation, and verification of relay interlocking systems as used by the Danish railways. The framework is centred around a domain-specific language (DSL) for describing such systems, and provides (1) a graphical editor...

  10. Towards a Framework for Modelling and Verification of Relay Interlocking Systems

    DEFF Research Database (Denmark)

    Haxthausen, Anne Elisabeth

    2010-01-01

    This paper describes a framework currently under development for modelling, simulation, and verification of relay interlocking systems as used by the Danish railways. The framework is centred around a domain-specific language (DSL) for describing such systems, and provides (1) a graphical editor ...

  11. Assessing Students' Understandings of Biological Models and Their Use in Science to Evaluate a Theoretical Framework

    Science.gov (United States)

    Grünkorn, Juliane; Upmeier zu Belzen, Annette; Krüger, Dirk

    2014-01-01

    Research in the field of students' understandings of models and their use in science describes different frameworks concerning these understandings. Currently, there is no conjoint framework that combines these structures and so far, no investigation has focused on whether it reflects students' understandings sufficiently (empirical evaluation).…

  12. Risk Assessment of Bioaccumulation Substances. Part II: Description of a Model Framework

    NARCIS (Netherlands)

    Tamis, J.E.; Vries, de P.; Karman, C.C.

    2009-01-01

    This report provides a proposal for a framework for risk assessment of bioaccumulative substances, either from produced water discharges or present as background contamination. The proposed framework is such that it is compatible to the current EIF risk assessment models that are used in the

  13. A framework for performance evaluation of model-based optical trackers

    NARCIS (Netherlands)

    Smit, F.A.; Liere, van R.

    2008-01-01

    We describe a software framework to evaluate the performance of model-based optical trackers in virtual environments. The framework can be used to evaluate and compare the performance of different trackers under various conditions, to study the effects of varying intrinsic and extrinsic camera

  14. Model-based visual tracking the OpenTL framework

    CERN Document Server

    Panin, Giorgio

    2011-01-01

    This book has two main goals: to provide a unifed and structured overview of this growing field, as well as to propose a corresponding software framework, the OpenTL library, developed by the author and his working group at TUM-Informatik. The main objective of this work is to show, how most real-world application scenarios can be naturally cast into a common description vocabulary, and therefore implemented and tested in a fully modular and scalable way, through the defnition of a layered, object-oriented software architecture.The resulting architecture covers in a seamless way all processin

  15. A model-based Bayesian framework for ECG beat segmentation

    International Nuclear Information System (INIS)

    Sayadi, O; Shamsollahi, M B

    2009-01-01

    The study of electrocardiogram (ECG) waveform amplitudes, timings and patterns has been the subject of intense research, for it provides a deep insight into the diagnostic features of the heart's functionality. In some recent works, a Bayesian filtering paradigm has been proposed for denoising and compression of ECG signals. In this paper, it is shown that this framework may be effectively used for ECG beat segmentation and extraction of fiducial points. Analytic expressions for the determination of points and intervals are derived and evaluated on various real ECG signals. Simulation results show that the method can contribute to and enhance the clinical ECG beat segmentation performance

  16. EarthCube - Earth System Bridge: Spanning Scientific Communities with Interoperable Modeling Frameworks

    Science.gov (United States)

    Peckham, S. D.; DeLuca, C.; Gochis, D. J.; Arrigo, J.; Kelbert, A.; Choi, E.; Dunlap, R.

    2014-12-01

    In order to better understand and predict environmental hazards of weather/climate, ecology and deep earth processes, geoscientists develop and use physics-based computational models. These models are used widely both in academic and federal communities. Because of the large effort required to develop and test models, there is widespread interest in component-based modeling, which promotes model reuse and simplified coupling to tackle problems that often cross discipline boundaries. In component-based modeling, the goal is to make relatively small changes to models that make it easy to reuse them as "plug-and-play" components. Sophisticated modeling frameworks exist to rapidly couple these components to create new composite models. They allow component models to exchange variables while accommodating different programming languages, computational grids, time-stepping schemes, variable names and units. Modeling frameworks have arisen in many modeling communities. CSDMS (Community Surface Dynamics Modeling System) serves the academic earth surface process dynamics community, while ESMF (Earth System Modeling Framework) serves many federal Earth system modeling projects. Others exist in both the academic and federal domains and each satisfies design criteria that are determined by the community they serve. While they may use different interface standards or semantic mediation strategies, they share fundamental similarities. The purpose of the Earth System Bridge project is to develop mechanisms for interoperability between modeling frameworks, such as the ability to share a model or service component. This project has three main goals: (1) Develop a Framework Description Language (ES-FDL) that allows modeling frameworks to be described in a standard way so that their differences and similarities can be assessed. (2) Demonstrate that if a model is augmented with a framework-agnostic Basic Model Interface (BMI), then simple, universal adapters can go from BMI to a

  17. A Hybrid Programming Framework for Modeling and Solving Constraint Satisfaction and Optimization Problems

    Directory of Open Access Journals (Sweden)

    Paweł Sitek

    2016-01-01

    Full Text Available This paper proposes a hybrid programming framework for modeling and solving of constraint satisfaction problems (CSPs and constraint optimization problems (COPs. Two paradigms, CLP (constraint logic programming and MP (mathematical programming, are integrated in the framework. The integration is supplemented with the original method of problem transformation, used in the framework as a presolving method. The transformation substantially reduces the feasible solution space. The framework automatically generates CSP and COP models based on current values of data instances, questions asked by a user, and set of predicates and facts of the problem being modeled, which altogether constitute a knowledge database for the given problem. This dynamic generation of dedicated models, based on the knowledge base, together with the parameters changing externally, for example, the user’s questions, is the implementation of the autonomous search concept. The models are solved using the internal or external solvers integrated with the framework. The architecture of the framework as well as its implementation outline is also included in the paper. The effectiveness of the framework regarding the modeling and solution search is assessed through the illustrative examples relating to scheduling problems with additional constrained resources.

  18. Optimisation of Hidden Markov Model using Baum–Welch algorithm ...

    Indian Academy of Sciences (India)

    The present work is a part of development of Hidden Markov Model. (HMM) based ... the Himalaya. In this work, HMMs have been developed for forecasting of maximum and minimum ..... data collection teams of Snow and Avalanche Study.

  19. eTOXlab, an open source modeling framework for implementing predictive models in production environments.

    Science.gov (United States)

    Carrió, Pau; López, Oriol; Sanz, Ferran; Pastor, Manuel

    2015-01-01

    Computational models based in Quantitative-Structure Activity Relationship (QSAR) methodologies are widely used tools for predicting the biological properties of new compounds. In many instances, such models are used as a routine in the industry (e.g. food, cosmetic or pharmaceutical industry) for the early assessment of the biological properties of new compounds. However, most of the tools currently available for developing QSAR models are not well suited for supporting the whole QSAR model life cycle in production environments. We have developed eTOXlab; an open source modeling framework designed to be used at the core of a self-contained virtual machine that can be easily deployed in production environments, providing predictions as web services. eTOXlab consists on a collection of object-oriented Python modules with methods mapping common tasks of standard modeling workflows. This framework allows building and validating QSAR models as well as predicting the properties of new compounds using either a command line interface or a graphic user interface (GUI). Simple models can be easily generated by setting a few parameters, while more complex models can be implemented by overriding pieces of the original source code. eTOXlab benefits from the object-oriented capabilities of Python for providing high flexibility: any model implemented using eTOXlab inherits the features implemented in the parent model, like common tools and services or the automatic exposure of the models as prediction web services. The particular eTOXlab architecture as a self-contained, portable prediction engine allows building models with confidential information within corporate facilities, which can be safely exported and used for prediction without disclosing the structures of the training series. The software presented here provides full support to the specific needs of users that want to develop, use and maintain predictive models in corporate environments. The technologies used by e

  20. Unified and Modular Modeling and Functional Verification Framework of Real-Time Image Signal Processors

    Directory of Open Access Journals (Sweden)

    Abhishek Jain

    2016-01-01

    Full Text Available In VLSI industry, image signal processing algorithms are developed and evaluated using software models before implementation of RTL and firmware. After the finalization of the algorithm, software models are used as a golden reference model for the image signal processor (ISP RTL and firmware development. In this paper, we are describing the unified and modular modeling framework of image signal processing algorithms used for different applications such as ISP algorithms development, reference for hardware (HW implementation, reference for firmware (FW implementation, and bit-true certification. The universal verification methodology- (UVM- based functional verification framework of image signal processors using software reference models is described. Further, IP-XACT based tools for automatic generation of functional verification environment files and model map files are described. The proposed framework is developed both with host interface and with core using virtual register interface (VRI approach. This modeling and functional verification framework is used in real-time image signal processing applications including cellphone, smart cameras, and image compression. The main motivation behind this work is to propose the best efficient, reusable, and automated framework for modeling and verification of image signal processor (ISP designs. The proposed framework shows better results and significant improvement is observed in product verification time, verification cost, and quality of the designs.

  1. MoVES - A Framework for Modelling and Verifying Embedded Systems

    DEFF Research Database (Denmark)

    Brekling, Aske Wiid; Hansen, Michael Reichhardt; Madsen, Jan

    2009-01-01

    The MoVES framework is being developed to assist in the early phases of embedded systems design. A system is modelled as an application running on an execution platform. The application is modelled through the individual tasks, and the execution platform is modelled through the processing elements...... examples, how MoVES can be used to model and analyze embedded systems....

  2. Design of a Model Execution Framework: Repetitive Object-Oriented Simulation Environment (ROSE)

    Science.gov (United States)

    Gray, Justin S.; Briggs, Jeffery L.

    2008-01-01

    The ROSE framework was designed to facilitate complex system analyses. It completely divorces the model execution process from the model itself. By doing so ROSE frees the modeler to develop a library of standard modeling processes such as Design of Experiments, optimizers, parameter studies, and sensitivity studies which can then be applied to any of their available models. The ROSE framework accomplishes this by means of a well defined API and object structure. Both the API and object structure are presented here with enough detail to implement ROSE in any object-oriented language or modeling tool.

  3. Finite element model updating using bayesian framework and modal properties

    CSIR Research Space (South Africa)

    Marwala, T

    2005-01-01

    Full Text Available Finite element (FE) models are widely used to predict the dynamic characteristics of aerospace structures. These models often give results that differ from measured results and therefore need to be updated to match measured results. Some...

  4. Framework Model for Database Replication within the Availability Zones

    OpenAIRE

    Al-Mughrabi, Ala'a Atallah; Owaied, Hussein

    2013-01-01

    This paper presents a proposed model for database replication model in private cloud availability regions, which is an enhancement of the SQL Server AlwaysOn Layers of Protection Model presents by Microsoft in 2012. The enhancement concentrates in the database replication for private cloud availability regions through the use of primary and secondary servers. The processes of proposed model during the client send Write/Read Request to the server, in synchronous and semi synchronous replicatio...

  5. Evaluating bacterial gene-finding HMM structures as probabilistic logic programs

    DEFF Research Database (Denmark)

    Mørk, Søren; Holmes, Ian

    2012-01-01

    , a probabilistic dialect of Prolog. Results: We evaluate Hidden Markov Model structures for bacterial protein-coding gene potential, including a simple null model structure, three structures based on existing bacterial gene finders and two novel model structures. We test standard versions as well as ADPH length...

  6. Model Uncertainty and Robustness: A Computational Framework for Multimodel Analysis

    Science.gov (United States)

    Young, Cristobal; Holsteen, Katherine

    2017-01-01

    Model uncertainty is pervasive in social science. A key question is how robust empirical results are to sensible changes in model specification. We present a new approach and applied statistical software for computational multimodel analysis. Our approach proceeds in two steps: First, we estimate the modeling distribution of estimates across all…

  7. A Generic Software Framework for Data Assimilation and Model Calibration

    NARCIS (Netherlands)

    Van Velzen, N.

    2010-01-01

    The accuracy of dynamic simulation models can be increased by using observations in conjunction with a data assimilation or model calibration algorithm. However, implementing such algorithms usually increases the complexity of the model software significantly. By using concepts from object oriented

  8. A model-based framework for the analysis of team communication in nuclear power plants

    International Nuclear Information System (INIS)

    Chung, Yun Hyung; Yoon, Wan Chul; Min, Daihwan

    2009-01-01

    Advanced human-machine interfaces are rapidly changing the interaction between humans and systems, with the level of abstraction of the presented information, the human task characteristics, and the modes of communication all affected. To accommodate the changes in the human/system co-working environment, an extended communication analysis framework is needed that can describe and relate the tasks, verbal exchanges, and information interface. This paper proposes an extended analytic framework, referred to as the H-H-S (human-human-system) communication analysis framework, which can model the changes in team communication that are emerging in these new working environments. The stage-specific decision-making model and analysis tool of the proposed framework make the analysis of team communication easier by providing visual clues. The usefulness of the proposed framework is demonstrated with an in-depth comparison of the characteristics of communication in the conventional and advanced main control rooms of nuclear power plants

  9. A Framework for Sharing and Integrating Remote Sensing and GIS Models Based on Web Service

    Science.gov (United States)

    Chen, Zeqiang; Lin, Hui; Chen, Min; Liu, Deer; Bao, Ying; Ding, Yulin

    2014-01-01

    Sharing and integrating Remote Sensing (RS) and Geographic Information System/Science (GIS) models are critical for developing practical application systems. Facilitating model sharing and model integration is a problem for model publishers and model users, respectively. To address this problem, a framework based on a Web service for sharing and integrating RS and GIS models is proposed in this paper. The fundamental idea of the framework is to publish heterogeneous RS and GIS models into standard Web services for sharing and interoperation and then to integrate the RS and GIS models using Web services. For the former, a “black box” and a visual method are employed to facilitate the publishing of the models as Web services. For the latter, model integration based on the geospatial workflow and semantic supported marching method is introduced. Under this framework, model sharing and integration is applied for developing the Pearl River Delta water environment monitoring system. The results show that the framework can facilitate model sharing and model integration for model publishers and model users. PMID:24901016

  10. A framework for sharing and integrating remote sensing and GIS models based on Web service.

    Science.gov (United States)

    Chen, Zeqiang; Lin, Hui; Chen, Min; Liu, Deer; Bao, Ying; Ding, Yulin

    2014-01-01

    Sharing and integrating Remote Sensing (RS) and Geographic Information System/Science (GIS) models are critical for developing practical application systems. Facilitating model sharing and model integration is a problem for model publishers and model users, respectively. To address this problem, a framework based on a Web service for sharing and integrating RS and GIS models is proposed in this paper. The fundamental idea of the framework is to publish heterogeneous RS and GIS models into standard Web services for sharing and interoperation and then to integrate the RS and GIS models using Web services. For the former, a "black box" and a visual method are employed to facilitate the publishing of the models as Web services. For the latter, model integration based on the geospatial workflow and semantic supported marching method is introduced. Under this framework, model sharing and integration is applied for developing the Pearl River Delta water environment monitoring system. The results show that the framework can facilitate model sharing and model integration for model publishers and model users.

  11. Comparing droplet activation parameterisations against adiabatic parcel models using a novel inverse modelling framework

    Science.gov (United States)

    Partridge, Daniel; Morales, Ricardo; Stier, Philip

    2015-04-01

    Many previous studies have compared droplet activation parameterisations against adiabatic parcel models (e.g. Ghan et al., 2001). However, these have often involved comparisons for a limited number of parameter combinations based upon certain aerosol regimes. Recent studies (Morales et al., 2014) have used wider ranges when evaluating their parameterisations, however, no study has explored the full possible multi-dimensional parameter space that would be experienced by droplet activations within a global climate model (GCM). It is important to be able to efficiently highlight regions of the entire multi-dimensional parameter space in which we can expect the largest discrepancy between parameterisation and cloud parcel models in order to ascertain which regions simulated by a GCM can be expected to be a less accurate representation of the process of cloud droplet activation. This study provides a new, efficient, inverse modelling framework for comparing droplet activation parameterisations to more complex cloud parcel models. To achieve this we couple a Markov Chain Monte Carlo algorithm (Partridge et al., 2012) to two independent adiabatic cloud parcel models and four droplet activation parameterisations. This framework is computationally faster than employing a brute force Monte Carlo simulation, and allows us to transparently highlight which parameterisation provides the closest representation across all aerosol physiochemical and meteorological environments. The parameterisations are demonstrated to perform well for a large proportion of possible parameter combinations, however, for certain key parameters; most notably the vertical velocity and accumulation mode aerosol concentration, large discrepancies are highlighted. These discrepancies correspond for parameter combinations that result in very high/low simulated values of maximum supersaturation. By identifying parameter interactions or regimes within the multi-dimensional parameter space we hope to guide

  12. Modeling the marketing strategy-performance relationship : towards an hierarchical marketing performance framework

    NARCIS (Netherlands)

    Huizingh, Eelko K.R.E.; Zengerink, Evelien

    2001-01-01

    Accurate measurement of marketing performance is an important topic for both marketing academics and marketing managers. Many researchers have recognized that marketing performance measurement should go beyond financial measurement. In this paper we propose a conceptual framework that models

  13. A conceptual framework to model long-run qualitative change in the energy system

    OpenAIRE

    Ebersberger, Bernd

    2004-01-01

    A conceptual framework to model long-run qualitative change in the energy system / A. Pyka, B. Ebersberger, H. Hanusch. - In: Evolution and economic complexity / ed. J. Stanley Metcalfe ... - Cheltenham [u.a.] : Elgar, 2004. - S. 191-213

  14. An Integrated Qualitative and Quantitative Biochemical Model Learning Framework Using Evolutionary Strategy and Simulated Annealing.

    Science.gov (United States)

    Wu, Zujian; Pang, Wei; Coghill, George M

    2015-01-01

    Both qualitative and quantitative model learning frameworks for biochemical systems have been studied in computational systems biology. In this research, after introducing two forms of pre-defined component patterns to represent biochemical models, we propose an integrative qualitative and quantitative modelling framework for inferring biochemical systems. In the proposed framework, interactions between reactants in the candidate models for a target biochemical system are evolved and eventually identified by the application of a qualitative model learning approach with an evolution strategy. Kinetic rates of the models generated from qualitative model learning are then further optimised by employing a quantitative approach with simulated annealing. Experimental results indicate that our proposed integrative framework is feasible to learn the relationships between biochemical reactants qualitatively and to make the model replicate the behaviours of the target system by optimising the kinetic rates quantitatively. Moreover, potential reactants of a target biochemical system can be discovered by hypothesising complex reactants in the synthetic models. Based on the biochemical models learned from the proposed framework, biologists can further perform experimental study in wet laboratory. In this way, natural biochemical systems can be better understood.

  15. A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

    Science.gov (United States)

    Hagos, Samson; Feng, Zhe; Plant, Robert S.; Houze, Robert A.; Xiao, Heng

    2018-02-01

    A stochastic prognostic framework for modeling the population dynamics of convective clouds and representing them in climate models is proposed. The framework follows the nonequilibrium statistical mechanical approach to constructing a master equation for representing the evolution of the number of convective cells of a specific size and their associated cloud-base mass flux, given a large-scale forcing. In this framework, referred to as STOchastic framework for Modeling Population dynamics of convective clouds (STOMP), the evolution of convective cell size is predicted from three key characteristics of convective cells: (i) the probability of growth, (ii) the probability of decay, and (iii) the cloud-base mass flux. STOMP models are constructed and evaluated against CPOL radar observations at Darwin and convection permitting model (CPM) simulations. Multiple models are constructed under various assumptions regarding these three key parameters and the realisms of these models are evaluated. It is shown that in a model where convective plumes prefer to aggregate spatially and the cloud-base mass flux is a nonlinear function of convective cell area, the mass flux manifests a recharge-discharge behavior under steady forcing. Such a model also produces observed behavior of convective cell populations and CPM simulated cloud-base mass flux variability under diurnally varying forcing. In addition to its use in developing understanding of convection processes and the controls on convective cell size distributions, this modeling framework is also designed to serve as a nonequilibrium closure formulations for spectral mass flux parameterizations.

  16. Evaluating bacterial gene-finding HMM structures as probabilistic logic programs.

    Science.gov (United States)

    Mørk, Søren; Holmes, Ian

    2012-03-01

    Probabilistic logic programming offers a powerful way to describe and evaluate structured statistical models. To investigate the practicality of probabilistic logic programming for structure learning in bioinformatics, we undertook a simplified bacterial gene-finding benchmark in PRISM, a probabilistic dialect of Prolog. We evaluate Hidden Markov Model structures for bacterial protein-coding gene potential, including a simple null model structure, three structures based on existing bacterial gene finders and two novel model structures. We test standard versions as well as ADPH length modeling and three-state versions of the five model structures. The models are all represented as probabilistic logic programs and evaluated using the PRISM machine learning system in terms of statistical information criteria and gene-finding prediction accuracy, in two bacterial genomes. Neither of our implementations of the two currently most used model structures are best performing in terms of statistical information criteria or prediction performances, suggesting that better-fitting models might be achievable. The source code of all PRISM models, data and additional scripts are freely available for download at: http://github.com/somork/codonhmm. Supplementary data are available at Bioinformatics online.

  17. National culture and business model change: a framework for successful expansions

    DEFF Research Database (Denmark)

    Dalby, J.; Nielsen, L.S.; Lueg, Rainer

    2014-01-01

    Dalby, J., Nielsen, Lueg, R., L. S., Pedersen, L., Tomoni, A. C. 2014. National culture and business model change: a framework for successful expansions. Journal of Enterprising Culture, 22(4): 379-498.......Dalby, J., Nielsen, Lueg, R., L. S., Pedersen, L., Tomoni, A. C. 2014. National culture and business model change: a framework for successful expansions. Journal of Enterprising Culture, 22(4): 379-498....

  18. A generic framework for individual-based modelling and physical-biological interaction

    DEFF Research Database (Denmark)

    Christensen, Asbjørn; Mariani, Patrizio; Payne, Mark R.

    2018-01-01

    The increased availability of high-resolution ocean data globally has enabled more detailed analyses of physical-biological interactions and their consequences to the ecosystem. We present IBMlib, which is a versatile, portable and computationally effective framework for conducting Lagrangian...... scales. The open-source framework features a minimal robust interface to facilitate the coupling between individual-level biological models and oceanographic models, and we provide application examples including forward/backward simulations, habitat connectivity calculations, assessing ocean conditions...

  19. A scalable delivery framework and a pricing model for streaming media with advertisements

    Science.gov (United States)

    Al-Hadrusi, Musab; Sarhan, Nabil J.

    2008-01-01

    This paper presents a delivery framework for streaming media with advertisements and an associated pricing model. The delivery model combines the benefits of periodic broadcasting and stream merging. The advertisements' revenues are used to subsidize the price of the media content. The pricing is determined based on the total ads' viewing time. Moreover, this paper presents an efficient ad allocation scheme and three modified scheduling policies that are well suited to the proposed delivery framework. Furthermore, we study the effectiveness of the delivery framework and various scheduling polices through extensive simulation in terms of numerous metrics, including customer defection probability, average number of ads viewed per client, price, arrival rate, profit, and revenue.

  20. Introducing MERGANSER: A Flexible Framework for Ecological Niche Modeling

    Science.gov (United States)

    Klawonn, M.; Dow, E. M.

    2015-12-01

    Ecological Niche Modeling (ENM) is a collection of techniques to find a "fundamental niche", the range of environmental conditions suitable for a species' survival in the absence of inter-species interactions, given a set of environmental parameters. Traditional approaches to ENM face a number of obstacles including limited data accessibility, data management problems, computational costs, interface usability, and model validation. The MERGANSER system, which stands for Modeling Ecological Residency Given A Normalized Set of Environmental Records, addresses these issues through powerful data persistence and flexible data access, coupled with a clear presentation of results and fine-tuned control over model parameters. MERGANSER leverages data measuring 72 weather related phenomena, land cover, soil type, population, species occurrence, general species information, and elevation, totaling over 1.5 TB of data. To the best of the authors' knowledge, MERGANSER uses higher-resolution spatial data sets than previously published models. Since MERGANSER stores data in an instance of Apache SOLR, layers generated in support of niche models are accessible to users via simplified Apache Lucene queries. This is made even simpler via an HTTP front end that generates Lucene queries automatically. Specifically, a user need only enter the name of a place and a species to run a model. Using this approach to synthesizing model layers, the MERGANSER system has successfully reproduced previously published niche model results with a simplified user experience. Input layers for the model are generated dynamically using OpenStreetMap and SOLR's spatial search functionality. Models are then run using either user-specified or automatically determined parameters after normalizing them into a common grid. Finally, results are visualized in the web interface, which allows for quick validation. Model results and all surrounding metadata are also accessible to the user for further study.

  1. Scoping review identifies significant number of knowledge translation theories, models and frameworks with limited use.

    Science.gov (United States)

    Strifler, Lisa; Cardoso, Roberta; McGowan, Jessie; Cogo, Elise; Nincic, Vera; Khan, Paul A; Scott, Alistair; Ghassemi, Marco; MacDonald, Heather; Lai, Yonda; Treister, Victoria; Tricco, Andrea C; Straus, Sharon E

    2018-04-13

    To conduct a scoping review of knowledge translation (KT) theories, models and frameworks that have been used to guide dissemination or implementation of evidence-based interventions targeted to prevention and/or management of cancer or other chronic diseases. We used a comprehensive multistage search process from 2000-2016, which included traditional bibliographic database searching, searching using names of theories, models and frameworks, and cited reference searching. Two reviewers independently screened the literature and abstracted data. We found 596 studies reporting on the use of 159 KT theories, models or frameworks. A majority (87%) of the identified theories, models or frameworks were used in five or fewer studies, with 60% used once. The theories, models and frameworks were most commonly used to inform planning/design, implementation and evaluation activities, and least commonly used to inform dissemination and sustainability/scalability activities. Twenty-six were used across the full implementation spectrum (from planning/design to sustainability/scalability) either within or across studies. All were used for at least individual-level behavior change, while 48% were used for organization-level, 33% for community-level and 17% for system-level change. We found a significant number of KT theories, models and frameworks with a limited evidence base describing their use. Copyright © 2018. Published by Elsevier Inc.

  2. Towards a Two-Dimensional Framework for User Models

    NARCIS (Netherlands)

    Vrieze, P.T. de; Bommel, P. van; Klok, J.; Weide, Th.P. van der; Gensel, Jérôme; Sèdes, Florence; Martin, Hervé

    2003-01-01

    The focus of this paper is user modeling in the context of personalisation of information systems. Such a personalisation is essential to give users the feeling that the system is easily accessible. The way this adaptive personalization works is very dependent on the adaptation model that is

  3. Biochemical Space: A Framework for Systemic Annotation of Biological Models

    Czech Academy of Sciences Publication Activity Database

    Klement, M.; Děd, T.; Šafránek, D.; Červený, Jan; Müller, Stefan; Steuer, Ralf

    2014-01-01

    Roč. 306, JUL (2014), s. 31-44 ISSN 1571-0661 R&D Projects: GA MŠk(CZ) EE2.3.20.0256 Institutional support: RVO:67179843 Keywords : biological models * model annotation * systems biology * cyanobacteria Subject RIV: EH - Ecology, Behaviour

  4. A business model for IPTV service: A dynamic framework

    NARCIS (Netherlands)

    Bouwman, H.; Zhengjia, M.; Duin, P. van der; Limonard, S.

    2008-01-01

    Purpose - The purpose of this paper is to investigate a possible business model for telecom operators for entering the IPTV (digital television) market. Design/methodology/approach - The approach takes the form of a case study, literature search and interviews. Findings - The IPTV business model

  5. The Conceptual Framework of Factors Affecting Shared Mental Model

    Science.gov (United States)

    Lee, Miyoung; Johnson, Tristan; Lee, Youngmin; O'Connor, Debra; Khalil, Mohammed

    2004-01-01

    Many researchers have paid attention to the potentiality and possibility of the shared mental model because it enables teammates to perform their job better by sharing team knowledge, skills, attitudes, dynamics and environments. Even though theoretical and experimental evidences provide a close relationship between the shared mental model and…

  6. An ontological framework for model-based problem-solving

    NARCIS (Netherlands)

    Scholten, H.; Beulens, A.J.M.

    2012-01-01

    Multidisciplinary projects to solve real world problems of increasing complexity are more and more plagued by obstacles such as miscommunication between modellers with different disciplinary backgrounds and bad modelling practices. To tackle these difficulties, a body of knowledge on problems, on

  7. Integrating environmental component models. Development of a software framework

    NARCIS (Netherlands)

    Schmitz, O.

    2014-01-01

    Integrated models consist of interacting component models that represent various natural and social systems. They are important tools to improve our understanding of environmental systems, to evaluate cause–effect relationships of human–natural interactions, and to forecast the behaviour of

  8. Deep Modeling: Circuit Characterization Using Theory Based Models in a Data Driven Framework

    Energy Technology Data Exchange (ETDEWEB)

    Bolme, David S [ORNL; Mikkilineni, Aravind K [ORNL; Rose, Derek C [ORNL; Yoginath, Srikanth B [ORNL; Holleman, Jeremy [University of Tennessee, Knoxville (UTK); Judy, Mohsen [University of Tennessee, Knoxville (UTK), Department of Electrical Engineering and Computer Science

    2017-01-01

    Analog computational circuits have been demonstrated to provide substantial improvements in power and speed relative to digital circuits, especially for applications requiring extreme parallelism but only modest precision. Deep machine learning is one such area and stands to benefit greatly from analog and mixed-signal implementations. However, even at modest precisions, offsets and non-linearity can degrade system performance. Furthermore, in all but the simplest systems, it is impossible to directly measure the intermediate outputs of all sub-circuits. The result is that circuit designers are unable to accurately evaluate the non-idealities of computational circuits in-situ and are therefore unable to fully utilize measurement results to improve future designs. In this paper we present a technique to use deep learning frameworks to model physical systems. Recently developed libraries like TensorFlow make it possible to use back propagation to learn parameters in the context of modeling circuit behavior. Offsets and scaling errors can be discovered even for sub-circuits that are deeply embedded in a computational system and not directly observable. The learned parameters can be used to refine simulation methods or to identify appropriate compensation strategies. We demonstrate the framework using a mixed-signal convolution operator as an example circuit.

  9. A general framework for modeling growth and division of mammalian cells.

    Science.gov (United States)

    Gauthier, John H; Pohl, Phillip I

    2011-01-06

    Modeling the cell-division cycle has been practiced for many years. As time has progressed, this work has gone from understanding the basic principles to addressing distinct biological problems, e.g., the nature of the restriction point, how checkpoints operate, the nonlinear dynamics of the cell cycle, the effect of localization, etc. Most models consist of coupled ordinary differential equations developed by the researchers, restricted to deal with the interactions of a limited number of molecules. In the future, cell-cycle modeling--and indeed all modeling of complex biologic processes--will increase in scope and detail. A framework for modeling complex cell-biologic processes is proposed here. The framework is based on two constructs: one describing the entire lifecycle of a molecule and the second describing the basic cellular machinery. Use of these constructs allows complex models to be built in a straightforward manner that fosters rigor and completeness. To demonstrate the framework, an example model of the mammalian cell cycle is presented that consists of several hundred differential equations of simple mass action kinetics. The model calculates energy usage, amino acid and nucleotide usage, membrane transport, RNA synthesis and destruction, and protein synthesis and destruction for 33 proteins to give an in-depth look at the cell cycle. The framework presented here addresses how to develop increasingly descriptive models of complex cell-biologic processes. The example model of cellular growth and division constructed with the framework demonstrates that large structured models can be created with the framework, and these models can generate non-trivial descriptions of cellular processes. Predictions from the example model include those at both the molecular level--e.g., Wee1 spontaneously reactivates--and at the system level--e.g., pathways for timing-critical processes must shut down redundant pathways. A future effort is to automatically estimate

  10. Interaction between GIS and hydrologic model: A preliminary approach using ArcHydro Framework Data Model

    Directory of Open Access Journals (Sweden)

    Silvio Jorge C. Simões

    2013-08-01

    Full Text Available In different regions of Brazil, population growth and economic development can degrade water quality, compromising watershed health and human supply. Because of its ability to combine spatial and temporal data in the same environment and to create water resources management (WRM models, the Geographical Information System (GIS is a powerful tool for managing water resources, preventing floods and estimating water supply. This paper discusses the integration between GIS and hydrological models and presents a case study relating to the upper section of the Paraíba do Sul Basin (Sao Paulo State portion, situated in the Southeast of Brazil. The case study presented in this paper has a database suitable for the basin’s dimensions, including digitized topographic maps at a 50,000 scale. From an ArcGIS®/ArcHydro Framework Data Model, a geometric network was created to produce different raster products. This first grid derived from the digital elevation model grid (DEM is the flow direction map followed by flow accumulation, stream and catchment maps. The next steps in this research are to include the different multipurpose reservoirs situated along the Paraíba do Sul River and to incorporate rainfall time series data in ArcHydro to build a hydrologic data model within a GIS environment in order to produce a comprehensive spatial temporal model.

  11. A framework to establish credibility of computational models in biology.

    Science.gov (United States)

    Patterson, Eann A; Whelan, Maurice P

    2017-10-01

    Computational models in biology and biomedical science are often constructed to aid people's understanding of phenomena or to inform decisions with socioeconomic consequences. Model credibility is the willingness of people to trust a model's predictions and is often difficult to establish for computational biology models. A 3 × 3 matrix has been proposed to allow such models to be categorised with respect to their testability and epistemic foundation in order to guide the selection of an appropriate process of validation to supply evidence to establish credibility. Three approaches to validation are identified that can be deployed depending on whether a model is deemed untestable, testable or lies somewhere in between. In the latter two cases, the validation process involves the quantification of uncertainty which is a key output. The issues arising due to the complexity and inherent variability of biological systems are discussed and the creation of 'digital twins' proposed as a means to alleviate the issues and provide a more robust, transparent and traceable route to model credibility and acceptance. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  12. A Generalized Framework for Modeling Next Generation 911 Implementations.

    Energy Technology Data Exchange (ETDEWEB)

    Kelic, Andjelka; Aamir, Munaf Syed; Kelic, Andjelka; Jrad, Ahmad M.; Mitchell, Roger

    2018-02-01

    This document summarizes the current state of Sandia 911 modeling capabilities and then addresses key aspects of Next Generation 911 (NG911) architectures for expansion of existing models. Analysis of three NG911 implementations was used to inform heuristics , associated key data requirements , and assumptions needed to capture NG911 architectures in the existing models . Modeling of NG911 necessitates careful consideration of its complexity and the diversity of implementations. Draft heuristics for constructing NG911 models are pres ented based on the analysis along with a summary of current challenges and ways to improve future NG911 modeling efforts . We found that NG911 relies on E nhanced 911 (E911) assets such as 911 selective routers to route calls originating from traditional tel ephony service which are a majority of 911 calls . We also found that the diversity and transitional nature of NG911 implementations necessitates significant and frequent data collection to ensure that adequate model s are available for crisis action support .

  13. Calculation of real optical model potential for heavy ions in the framework of the folding model

    International Nuclear Information System (INIS)

    Goncharov, S.A.; Timofeyuk, N.K.; Kazacha, G.S.

    1987-01-01

    The code for calculation of a real optical model potential in the framework of the folding model is realized. The program of numerical Fourier-Bessel transformation based on Filon's integration rule is used. The accuracy of numerical calculations is ∼ 10 -4 for a distance interval up to a bout (2.5-3) times the size of nuclei. The potentials are calculated for interactions of 3,4 He with nuclei from 9 Be to 27 Al with different effective NN-interactions and densities obtained from electron scattering data. Calculated potentials are similar to phenomenological potentials in Woods-Saxon form. With calculated potentials the available elastic scattering data for the considered nuclei in the energy interval 18-56 MeV are analysed. The needed renormalizations for folding potentials are < or approx. 20%

  14. Extending the Modelling Framework for Gas-Particle Systems

    DEFF Research Database (Denmark)

    Rosendahl, Lasse Aistrup

    , with very good results. Single particle combustion has been tested using a number of different particle combustion models applied to coal and straw particles. Comparing the results of these calculations to measurements on straw burnout, the results indicate that for straw, existing heterogeneous combustion...... models perform well, and may be used in high temperature ranges. Finally, the particle tracking and combustion model is applied to an existing coal and straw co- fuelled burner. The results indicate that again, the straw follows very different trajectories than the coal particles, and also that burnout...

  15. Assessing uncertainties in global cropland futures using a conditional probabilistic modelling framework

    NARCIS (Netherlands)

    Engström, Kerstin; Olin, Stefan; Rounsevell, Mark D A; Brogaard, Sara; Van Vuuren, Detlef P.; Alexander, Peter; Murray-Rust, Dave; Arneth, Almut

    2016-01-01

    We present a modelling framework to simulate probabilistic futures of global cropland areas that are conditional on the SSP (shared socio-economic pathway) scenarios. Simulations are based on the Parsimonious Land Use Model (PLUM) linked with the global dynamic vegetation model LPJ-GUESS

  16. Model Adaptation for Prognostics in a Particle Filtering Framework

    Data.gov (United States)

    National Aeronautics and Space Administration — One of the key motivating factors for using particle filters for prognostics is the ability to include model parameters as part of the state vector to be estimated....

  17. A parametric framework for modelling of bioelectrical signals

    CERN Document Server

    Mughal, Yar Muhammad

    2016-01-01

    This book examines non-invasive, electrical-based methods for disease diagnosis and assessment of heart function. In particular, a formalized signal model is proposed since this offers several advantages over methods that rely on measured data alone. By using a formalized representation, the parameters of the signal model can be easily manipulated and/or modified, thus providing mechanisms that allow researchers to reproduce and control such signals. In addition, having such a formalized signal model makes it possible to develop computer tools that can be used for manipulating and understanding how signal changes result from various heart conditions, as well as for generating input signals for experimenting with and evaluating the performance of e.g. signal extraction methods. The work focuses on bioelectrical information, particularly electrical bio-impedance (EBI). Once the EBI has been measured, the corresponding signals have to be modelled for analysis. This requires a structured approach in order to move...

  18. A Framework for Modeling and Analyzing Complex Distributed Systems

    National Research Council Canada - National Science Library

    Lynch, Nancy A; Shvartsman, Alex Allister

    2005-01-01

    Report developed under STTR contract for topic AF04-T023. This Phase I project developed a modeling language and laid a foundation for computational support tools for specifying, analyzing, and verifying complex distributed system designs...

  19. Public–private partnership conceptual framework and models for the ...

    African Journals Online (AJOL)

    investment and inefficiencies within the public expenditure management systems are particularly detrimental, e.g., there .... a consolidation of different views, ideas, perceptions and ... contingency) exists between the PPP models key financial.

  20. A Flexible Framework Hydrological Informatic Modeling System - HIMS

    Science.gov (United States)

    WANG, L.; Wang, Z.; Changming, L.; Li, J.; Bai, P.

    2017-12-01

    Simulating water cycling process temporally and spatially fitting for the characteristics of the study area was important for floods prediction and streamflow simulation with high accuracy, as soil properties, land scape, climate, and land managements were the critical factors influencing the non-linear relationship of rainfall-runoff at watershed scales. Most existing hydrological models cannot simulate water cycle process at different places with customized mechanisms with fixed single structure and mode. This study develops Hydro-Informatic Modeling System (HIMS) model with modular of each critical hydrological process with multiple choices for various scenarios to solve this problem. HIMS has the structure accounting for two runoff generation mechanisms of infiltration excess and saturation excess and estimated runoff with different methods including Time Variance Gain Model (TVGM), LCM which has good performance at ungauged areas, besides the widely used Soil Conservation Service-Curve Number (SCS-CN) method. Channel routing model contains the most widely used Muskingum, and kinematic wave equation with new solving method. HIMS model performance with its symbolic runoff generation model LCM was evaluated through comparison with the observed streamflow datasets of Lasha river watershed at hourly, daily, and monthly time steps. Comparisons between simulational and obervational streamflows were found with NSE higher than 0.87 and WE within ±20%. Water balance analysis about precipitation, streamflow, actual evapotranspiration (ET), and soil moisture change was conducted temporally at annual time step and it has been proved that HIMS model performance was reliable through comparison with literature results at the Lhasa River watershed.

  1. Model Adaptation for Prognostics in a Particle Filtering Framework

    Directory of Open Access Journals (Sweden)

    Bhaskar Saha

    2011-01-01

    Full Text Available One of the key motivating factors for using particle filters for prognostics is the ability to include model parameters as part of the state vector to be estimated. This performs model adaptation in conjunction with state tracking, and thus, produces a tuned model that can used for long term predictions. This feature of particle filters works in most part due to the fact that they are not subject to the “curse of dimensionality”, i.e. the exponential growth of computational complexity with state dimension. However, in practice, this property holds for “well-designed” particle filters only as dimensionality increases. This paper explores the notion of wellness of design in the context of predicting remaining useful life for individual discharge cycles of Li-ion and Li-Polymer batteries. Prognostic metrics are used to analyze the tradeoff between different model designs and prediction performance. Results demonstrate how sensitivity analysis may be used to arrive at a well-designed prognostic model that can take advantage of the model adaptation properties of a particle filter.

  2. Model Adaptation for Prognostics in a Particle Filtering Framework

    Science.gov (United States)

    Saha, Bhaskar; Goebel, Kai Frank

    2011-01-01

    One of the key motivating factors for using particle filters for prognostics is the ability to include model parameters as part of the state vector to be estimated. This performs model adaptation in conjunction with state tracking, and thus, produces a tuned model that can used for long term predictions. This feature of particle filters works in most part due to the fact that they are not subject to the "curse of dimensionality", i.e. the exponential growth of computational complexity with state dimension. However, in practice, this property holds for "well-designed" particle filters only as dimensionality increases. This paper explores the notion of wellness of design in the context of predicting remaining useful life for individual discharge cycles of Li-ion batteries. Prognostic metrics are used to analyze the tradeoff between different model designs and prediction performance. Results demonstrate how sensitivity analysis may be used to arrive at a well-designed prognostic model that can take advantage of the model adaptation properties of a particle filter.

  3. Design theoretic analysis of three system modeling frameworks.

    Energy Technology Data Exchange (ETDEWEB)

    McDonald, Michael James

    2007-05-01

    This paper analyzes three simulation architectures from the context of modeling scalability to address System of System (SoS) and Complex System problems. The paper first provides an overview of the SoS problem domain and reviews past work in analyzing model and general system complexity issues. It then identifies and explores the issues of vertical and horizontal integration as well as coupling and hierarchical decomposition as the system characteristics and metrics against which the tools are evaluated. In addition, it applies Nam Suh's Axiomatic Design theory as a construct for understanding coupling and its relationship to system feasibility. Next it describes the application of MATLAB, Swarm, and Umbra (three modeling and simulation approaches) to modeling swarms of Unmanned Flying Vehicle (UAV) agents in relation to the chosen characteristics and metrics. Finally, it draws general conclusions for analyzing model architectures that go beyond those analyzed. In particular, it identifies decomposition along phenomena of interaction and modular system composition as enabling features for modeling large heterogeneous complex systems.

  4. Introducing a boreal wetland model within the Earth System model framework

    Science.gov (United States)

    Getzieh, R. J.; Brovkin, V.; Reick, C.; Kleinen, T.; Raddatz, T.; Raivonen, M.; Sevanto, S.

    2009-04-01

    Wetlands of the northern high latitudes with their low temperatures and waterlogged conditions are prerequisite for peat accumulation. They store at least 25% of the global soil organic carbon and constitute currently the largest natural source of methane. These boreal and subarctic peat carbon pools are sensitive to climate change since the ratio of carbon sequestration and emission is closely dependent on hydrology and temperature. Global biogeochemistry models used for simulations of CO2 dynamics in the past and future climates usually ignore changes in the peat storages. Our approach aims at the evaluation of the boreal wetland feedback to climate through the CO2 and CH4 fluxes on decadal to millennial time scales. A generic model of organic matter accumulation and decay in boreal wetlands is under development in the MPI for Meteorology in cooperation with the University of Helsinki. Our approach is to develop a wetland model which is consistent with the physical and biogeochemical components of the land surface module JSBACH as a part of the Earth System model framework ECHAM5-MPIOM-JSBACH. As prototypes, we use modelling approach by Frolking et al. (2001) for the peat dynamics and the wetland model by Wania (2007) for vegetation cover and plant productivity. An initial distribution of wetlands follows the GLWD-3 map by Lehner and Döll (2004). First results of the modelling approach will be presented. References: Frolking, S. E., N. T. Roulet, T. R. Moore, P. J. H. Richard, M. Lavoie and S. D. Muller (2001): Modeling Northern Peatland Decomposition and Peat Accumulation, Ecosystems, 4, 479-498. Lehner, B., Döll P. (2004): Development and validation of a global database of lakes, reservoirs and wetlands. Journal of Hydrology 296 (1-4), 1-22. Wania, R. (2007): Modelling northern peatland land surface processes, vegetation dynamics and methane emissions. PhD thesis, University of Bristol, 122 pp.

  5. A Reusable Framework for Regional Climate Model Evaluation

    Science.gov (United States)

    Hart, A. F.; Goodale, C. E.; Mattmann, C. A.; Lean, P.; Kim, J.; Zimdars, P.; Waliser, D. E.; Crichton, D. J.

    2011-12-01

    Climate observations are currently obtained through a diverse network of sensors and platforms that include space-based observatories, airborne and seaborne platforms, and distributed, networked, ground-based instruments. These global observational measurements are critical inputs to the efforts of the climate modeling community and can provide a corpus of data for use in analysis and validation of climate models. The Regional Climate Model Evaluation System (RCMES) is an effort currently being undertaken to address the challenges of integrating this vast array of observational climate data into a coherent resource suitable for performing model analysis at the regional level. Developed through a collaboration between the NASA Jet Propulsion Laboratory (JPL) and the UCLA Joint Institute for Regional Earth System Science and Engineering (JIFRESSE), the RCMES uses existing open source technologies (MySQL, Apache Hadoop, and Apache OODT), to construct a scalable, parametric, geospatial data store that incorporates decades of observational data from a variety of NASA Earth science missions, as well as other sources into a consistently annotated, highly available scientific resource. By eliminating arbitrary partitions in the data (individual file boundaries, differing file formats, etc), and instead treating each individual observational measurement as a unique, geospatially referenced data point, the RCMES is capable of transforming large, heterogeneous collections of disparate observational data into a unified resource suitable for comparison to climate model output. This facility is further enhanced by the availability of a model evaluation toolkit which consists of a set of Python libraries, a RESTful web service layer, and a browser-based graphical user interface that allows for orchestration of model-to-data comparisons by composing them visually through web forms. This combination of tools and interfaces dramatically simplifies the process of interacting with and

  6. A framework for modelling the complexities of food and water security under globalisation

    Science.gov (United States)

    Dermody, Brian J.; Sivapalan, Murugesu; Stehfest, Elke; van Vuuren, Detlef P.; Wassen, Martin J.; Bierkens, Marc F. P.; Dekker, Stefan C.

    2018-01-01

    We present a new framework for modelling the complexities of food and water security under globalisation. The framework sets out a method to capture regional and sectoral interdependencies and cross-scale feedbacks within the global food system that contribute to emergent water use patterns. The framework integrates aspects of existing models and approaches in the fields of hydrology and integrated assessment modelling. The core of the framework is a multi-agent network of city agents connected by infrastructural trade networks. Agents receive socio-economic and environmental constraint information from integrated assessment models and hydrological models respectively and simulate complex, socio-environmental dynamics that operate within those constraints. The emergent changes in food and water resources are aggregated and fed back to the original models with minimal modification of the structure of those models. It is our conviction that the framework presented can form the basis for a new wave of decision tools that capture complex socio-environmental change within our globalised world. In doing so they will contribute to illuminating pathways towards a sustainable future for humans, ecosystems and the water they share.

  7. framework for modelling the complexities of food and water security under globalisation

    Directory of Open Access Journals (Sweden)

    B. J. Dermody

    2018-01-01

    Full Text Available We present a new framework for modelling the complexities of food and water security under globalisation. The framework sets out a method to capture regional and sectoral interdependencies and cross-scale feedbacks within the global food system that contribute to emergent water use patterns. The framework integrates aspects of existing models and approaches in the fields of hydrology and integrated assessment modelling. The core of the framework is a multi-agent network of city agents connected by infrastructural trade networks. Agents receive socio-economic and environmental constraint information from integrated assessment models and hydrological models respectively and simulate complex, socio-environmental dynamics that operate within those constraints. The emergent changes in food and water resources are aggregated and fed back to the original models with minimal modification of the structure of those models. It is our conviction that the framework presented can form the basis for a new wave of decision tools that capture complex socio-environmental change within our globalised world. In doing so they will contribute to illuminating pathways towards a sustainable future for humans, ecosystems and the water they share.

  8. National water, food, and trade modeling framework: The case of Egypt.

    Science.gov (United States)

    Abdelkader, A; Elshorbagy, A; Tuninetti, M; Laio, F; Ridolfi, L; Fahmy, H; Hoekstra, A Y

    2018-05-22

    This paper introduces a modeling framework for the analysis of real and virtual water flows at national scale. The framework has two components: (1) a national water model that simulates agricultural, industrial and municipal water uses, and available water and land resources; and (2) an international virtual water trade model that captures national virtual water exports and imports related to trade in crops and animal products. This National Water, Food & Trade (NWFT) modeling framework is applied to Egypt, a water-poor country and the world's largest importer of wheat. Egypt's food and water gaps and the country's food (virtual water) imports are estimated over a baseline period (1986-2013) and projected up to 2050 based on four scenarios. Egypt's food and water gaps are growing rapidly as a result of steep population growth and limited water resources. The NWFT modeling framework shows the nexus of the population dynamics, water uses for different sectors, and their compounding effects on Egypt's food gap and water self-sufficiency. The sensitivity analysis reveals that for solving Egypt's water and food problem non-water-based solutions like educational, health, and awareness programs aimed at lowering population growth will be an essential addition to the traditional water resources development solution. Both the national and the global models project similar trends of Egypt's food gap. The NWFT modeling framework can be easily adapted to other nations and regions. Copyright © 2018. Published by Elsevier B.V.

  9. Stochastic programming framework for Lithuanian pension payout modelling

    Directory of Open Access Journals (Sweden)

    Audrius Kabašinskas

    2014-12-01

    Full Text Available The paper provides a scientific approach to the problem of selecting a pension fund by taking into account some specific characteristics of the Lithuanian Republic (LR pension accumulation system. The decision making model, which can be used to plan a long-term pension accrual of the Lithuanian Republic (LR citizens, in an optimal way is presented. This model focuses on factors that influence the sustainability of the pension system selection under macroeconomic, social and demographic uncertainty. The model is formalized as a single stage stochastic optimization problem where the long-term optimal strategy can be obtained based on the possible scenarios generated for a particular participant. Stochastic programming methods allow including the pension fund rebalancing moment and direction of investment, and taking into account possible changes of personal income, changes of society and the global financial market. The collection of methods used to generate scenario trees was found useful to solve strategic planning problems.

  10. A Flexible Atmospheric Modeling Framework for the CESM

    Energy Technology Data Exchange (ETDEWEB)

    Randall, David [Colorado State University; Heikes, Ross [Colorado State University; Konor, Celal [Colorado State University

    2014-11-12

    We have created two global dynamical cores based on the unified system of equations and Z-grid staggering on an icosahedral grid, which are collectively called UZIM (Unified Z-grid Icosahedral Model). The z-coordinate version (UZIM-height) can be run in hydrostatic and nonhydrostatic modes. The sigma-coordinate version (UZIM-sigma) runs in only hydrostatic mode. The super-parameterization has been included as a physics option in both models. The UZIM versions with the super-parameterization are called SUZI. With SUZI-height, we have completed aquaplanet runs. With SUZI-sigma, we are making aquaplanet runs and realistic climate simulations. SUZI-sigma includes realistic topography and a SiB3 model to parameterize the land-surface processes.

  11. A GBT-framework towards modal modelling of steel structures

    DEFF Research Database (Denmark)

    Hansen, Anders Bau; Jönsson, Jeppe

    2017-01-01

    In modern structural steel frame design, the modelling of joints between beams and columns are based on very simple assumptions. The joints are most often assumed to behave as a perfect hinge or as a rigid joint. This means that in the overall static analysis relative rotations and changes...... the rotational stiffness of a connection. Based on a modelling of any beam-to-column joint using finite shell elements and springs for single components such as bolts, it is the primary hypothesis that it is possible to formulate a generalized connection model with few degrees of freedom related to a relevant...... set of deformation modes. This hypothesis is based on the idea of modal decomposition performed in generalized beam theories (GBT). The question is – is it possible to formulate an eigenvalue problem with a solution corresponding to mode shapes for the deformation of the joint by using the finite...

  12. A kingdom-specific protein domain HMM library for improved annotation of fungal genomes

    Directory of Open Access Journals (Sweden)

    Oliver Stephen G

    2007-04-01

    Full Text Available Abstract Background Pfam is a general-purpose database of protein domain alignments and profile Hidden Markov Models (HMMs, which is very popular for the annotation of sequence data produced by genome sequencing projects. Pfam provides models that are often very general in terms of the taxa that they cover and it has previously been suggested that such general models may lack some of the specificity or selectivity that would be provided by kingdom-specific models. Results Here we present a general approach to create domain libraries of HMMs for sub-taxa of a kingdom. Taking fungal species as an example, we construct a domain library of HMMs (called Fungal Pfam or FPfam using sequences from 30 genomes, consisting of 24 species from the ascomycetes group and two basidiomycetes, Ustilago maydis, a fungal pathogen of maize, and the white rot fungus Phanerochaete chrysosporium. In addition, we include the Microsporidion Encephalitozoon cuniculi, an obligate intracellular parasite, and two non-fungal species, the oomycetes Phytophthora sojae and Phytophthora ramorum, both plant pathogens. We evaluate the performance in terms of coverage against the original 30 genomes used in training FPfam and against five more recently sequenced fungal genomes that can be considered as an independent test set. We show that kingdom-specific models such as FPfam can find instances of both novel and well characterized domains, increases overall coverage and detects more domains per sequence with typically higher bitscores than Pfam for the same domain families. An evaluation of the effect of changing E-values on the coverage shows that the performance of FPfam is consistent over the range of E-values applied. Conclusion Kingdom-specific models are shown to provide improved coverage. However, as the models become more specific, some sequences found by Pfam may be missed by the models in FPfam and some of the families represented in the test set are not present in FPfam

  13. gamboostLSS: An R Package for Model Building and Variable Selection in the GAMLSS Framework

    OpenAIRE

    Hofner, Benjamin; Mayr, Andreas; Schmid, Matthias

    2014-01-01

    Generalized additive models for location, scale and shape are a flexible class of regression models that allow to model multiple parameters of a distribution function, such as the mean and the standard deviation, simultaneously. With the R package gamboostLSS, we provide a boosting method to fit these models. Variable selection and model choice are naturally available within this regularized regression framework. To introduce and illustrate the R package gamboostLSS and its infrastructure, we...

  14. Development of a practical modeling framework for estimating the impact of wind technology on bird populations

    Energy Technology Data Exchange (ETDEWEB)

    Morrison, M.L. [California State Univ., Sacramento, CA (United States); Pollock, K.H. [North Carolina State Univ., Raleigh, NC (United States)

    1997-11-01

    One of the most pressing environmental concerns related to wind project development is the potential for avian fatalities caused by the turbines. The goal of this project is to develop a useful, practical modeling framework for evaluating potential wind power plant impacts that can be generalized to most bird species. This modeling framework could be used to get a preliminary understanding of the likelihood of significant impacts to birds, in a cost-effective way. The authors accomplish this by (1) reviewing the major factors that can influence the persistence of a wild population; (2) briefly reviewing various models that can aid in estimating population status and trend, including methods of evaluating model structure and performance; (3) reviewing survivorship and population projections; and (4) developing a framework for using models to evaluate the potential impacts of wind development on birds.

  15. Development of a practical modeling framework for estimating the impact of wind technology on bird populations

    International Nuclear Information System (INIS)

    Morrison, M.L.; Pollock, K.H.

    1997-11-01

    One of the most pressing environmental concerns related to wind project development is the potential for avian fatalities caused by the turbines. The goal of this project is to develop a useful, practical modeling framework for evaluating potential wind power plant impacts that can be generalized to most bird species. This modeling framework could be used to get a preliminary understanding of the likelihood of significant impacts to birds, in a cost-effective way. The authors accomplish this by (1) reviewing the major factors that can influence the persistence of a wild population; (2) briefly reviewing various models that can aid in estimating population status and trend, including methods of evaluating model structure and performance; (3) reviewing survivorship and population projections; and (4) developing a framework for using models to evaluate the potential impacts of wind development on birds

  16. Intrinsic flexibility of porous materials; theory, modelling and the flexibility window of the EMT zeolite framework

    International Nuclear Information System (INIS)

    Fletcher, Rachel E.; Wells, Stephen A.; Leung, Ka Ming; Edwards, Peter P.; Sartbaeva, Asel

    2015-01-01

    Framework materials possess intrinsic flexibility which can be investigated using geometric simulation. We review framework flexibility properties in energy materials and present novel results on the flexibility window of the EMT zeolite framework containing 18-crown-6 ether as a structure directing agent (SDA). Framework materials have structures containing strongly bonded polyhedral groups of atoms connected through their vertices. Typically the energy cost for variations of the inter-polyhedral geometry is much less than the cost of distortions of the polyhedra themselves – as in the case of silicates, where the geometry of the SiO 4 tetrahedral group is much more strongly constrained than the Si—O—Si bridging angle. As a result, framework materials frequently display intrinsic flexibility, and their dynamic and static properties are strongly influenced by low-energy collective motions of the polyhedra. Insight into these motions can be obtained in reciprocal space through the ‘rigid unit mode’ (RUM) model, and in real-space through template-based geometric simulations. We briefly review the framework flexibility phenomena in energy-relevant materials, including ionic conductors, perovskites and zeolites. In particular we examine the ‘flexibility window’ phenomenon in zeolites and present novel results on the flexibility window of the EMT framework, which shed light on the role of structure-directing agents. Our key finding is that the crown ether, despite its steric bulk, does not limit the geometric flexibility of the framework

  17. Surgical model-view-controller simulation software framework for local and collaborative applications.

    Science.gov (United States)

    Maciel, Anderson; Sankaranarayanan, Ganesh; Halic, Tansel; Arikatla, Venkata Sreekanth; Lu, Zhonghua; De, Suvranu

    2011-07-01

    Surgical simulations require haptic interactions and collaboration in a shared virtual environment. A software framework for decoupled surgical simulation based on a multi-controller and multi-viewer model-view-controller (MVC) pattern was developed and tested. A software framework for multimodal virtual environments was designed, supporting both visual interactions and haptic feedback while providing developers with an integration tool for heterogeneous architectures maintaining high performance, simplicity of implementation, and straightforward extension. The framework uses decoupled simulation with updates of over 1,000 Hz for haptics and accommodates networked simulation with delays of over 1,000 ms without performance penalty. The simulation software framework was implemented and was used to support the design of virtual reality-based surgery simulation systems. The framework supports the high level of complexity of such applications and the fast response required for interaction with haptics. The efficacy of the framework was tested by implementation of a minimally invasive surgery simulator. A decoupled simulation approach can be implemented as a framework to handle simultaneous processes of the system at the various frame rates each process requires. The framework was successfully used to develop collaborative virtual environments (VEs) involving geographically distributed users connected through a network, with the results comparable to VEs for local users.

  18. An Empirical Generative Framework for Computational Modeling of Language Acquisition

    Science.gov (United States)

    Waterfall, Heidi R.; Sandbank, Ben; Onnis, Luca; Edelman, Shimon

    2010-01-01

    This paper reports progress in developing a computer model of language acquisition in the form of (1) a generative grammar that is (2) algorithmically learnable from realistic corpus data, (3) viable in its large-scale quantitative performance and (4) psychologically real. First, we describe new algorithmic methods for unsupervised learning of…

  19. Interagency Modeling Atmospheric Assessment Center Local Jurisdiction: IMAAC Operations Framework

    Science.gov (United States)

    2010-03-01

    proposed model ( Daft & Lengel, 1986). All six Ohio LINC Cities were interviewed face- to-face providing the basis for the research evaluating...Cincinnati, DHS should work in partnership with Cincinnati Urban Area Leadership to convene a randomly selected, but statistically-significant, UASI...response system. Internal document. Daft , R. L. & Lengel, R. H. (1986). Organizational Information Requirements, Media Richness and Structural

  20. A Framework for Modelling Connective Tissue Changes in VIIP Syndrome

    Science.gov (United States)

    Ethier, C. R.; Best, L.; Gleason, R.; Mulugeta, L.; Myers, J. G.; Nelson, E. S.; Samuels, B. C.

    2014-01-01

    Insertion of astronauts into microgravity induces a cascade of physiological adaptations, notably including a cephalad fluid shift. Longer-duration flights carry an increased risk of developing Visual Impairment and Intracranial Pressure (VIIP) syndrome, a spectrum of ophthalmic changes including posterior globe flattening, choroidal folds, distension of the optic nerve sheath, kinking of the optic nerve and potentially permanent degradation of visual function. The slow onset of changes in VIIP, their chronic nature, and the similarity of certain clinical features of VIIP to ophthalmic findings in patients with raised intracranial pressure strongly suggest that: (i) biomechanical factors play a role in VIIP, and (ii) connective tissue remodeling must be accounted for if we wish to understand the pathology of VIIP. Our goal is to elucidate the pathophysiology of VIIP and suggest countermeasures based on biomechanical modeling of ocular tissues, suitably informed by experimental data, and followed by validation and verification. We specifically seek to understand the quasi-homeostatic state that evolves over weeks to months in space, during which ocular tissue remodeling occurs. This effort is informed by three bodies of work: (i) modeling of cephalad fluid shifts; (ii) modeling of ophthalmic tissue biomechanics in glaucoma; and (iii) modeling of connective tissue changes in response to biomechanical loading.

  1. Iberian (South American) Model of Judicial Review: Toward Conceptual Framework

    Science.gov (United States)

    Klishas, Andrey A.

    2016-01-01

    The paper explores Latin American countries legislation with the view to identify specific features of South American model of judicial review. The research methodology rests on comparative approach to analyzing national constitutions' provisions and experts' interpretations thereof. The constitutional provisions of Brazil, Peru, Mexico, and…

  2. Framework for Modelling Multiple Input Complex Aggregations for Interactive Installations

    DEFF Research Database (Denmark)

    Padfield, Nicolas; Andreasen, Troels

    2012-01-01

    on fuzzy logic and provides a method for variably balancing interaction and user input with the intention of the artist or director. An experimental design is presented, demonstrating an intuitive interface for parametric modelling of a complex aggregation function. The aggregation function unifies...

  3. The heterogeneous heuristic modeling framework for inferring decision processes

    NARCIS (Netherlands)

    Zhu, W.; Timmermans, H.J.P.; Rasouli, S.; Timmermans, H.J.P.

    2015-01-01

    Purpose – Increasing evidence suggests that choice behaviour in real world may be guided by principles of bounded rationality as opposed to typically assumed fully rational behaviour, based on the principle of utility- maximization. Under such circumstances, conventional rational choice models

  4. Understanding organizational congruence: formal model and simulation framework.

    NARCIS (Netherlands)

    Dignum, M.V.; Dignum, F.P.M.

    2007-01-01

    Despite a large number of studies, the effect of organizational structure on the performance and the individual cognition of its members is still not well understood. Our research aims at developing tools and formalisms to model organizations and evaluate their performance under different

  5. Business process model repositories – framework and survey

    NARCIS (Netherlands)

    Yan, Z.; Dijkman, R.M.; Grefen, P.W.P.J.

    2012-01-01

    Context: Large organizations often run hundreds or even thousands of different business processes. Managing such large collections of business process models is a challenging task. Software can assist in performing that task, by supporting common management functions such as storage, search and

  6. Technical note: River modelling to infer flood management framework

    African Journals Online (AJOL)

    River hydraulic models have successfully identified the weaknesses and areas for improvement with respect to flooding in the Sarawak River system, and can also be used to support decisions on flood management measures. Often, the big question is 'how'. This paper demonstrates a theoretical flood management ...

  7. A GBT-framework towards modal modelling of steel structures

    DEFF Research Database (Denmark)

    Hansen, Anders Bau; Jönsson, Jeppe

    2017-01-01

    In modern structural steel frame design, the modelling of joints between beams and columns are based on very simple assumptions. The joints are most often assumed to behave as a perfect hinge or as a rigid joint. This means that in the overall static analysis relative rotations and changes...

  8. Public–private partnership conceptual framework and models for the ...

    African Journals Online (AJOL)

    Well-functioning and appropriately institutional investors (pension funds, insurance companies, etc.) would be natural sources of long-term financing for water services infrastructure because liabilities would better match the longer terms of water infrastructure projects. The 'hybrid model' is in the middle of the water services ...

  9. Quasi-continuous stochastic simulation framework for flood modelling

    Science.gov (United States)

    Moustakis, Yiannis; Kossieris, Panagiotis; Tsoukalas, Ioannis; Efstratiadis, Andreas

    2017-04-01

    Typically, flood modelling in the context of everyday engineering practices is addressed through event-based deterministic tools, e.g., the well-known SCS-CN method. A major shortcoming of such approaches is the ignorance of uncertainty, which is associated with the variability of soil moisture conditions and the variability of rainfall during the storm event.In event-based modeling, the sole expression of uncertainty is the return period of the design storm, which is assumed to represent the acceptable risk of all output quantities (flood volume, peak discharge, etc.). On the other hand, the varying antecedent soil moisture conditions across the basin are represented by means of scenarios (e.g., the three AMC types by SCS),while the temporal distribution of rainfall is represented through standard deterministic patterns (e.g., the alternative blocks method). In order to address these major inconsistencies,simultaneously preserving the simplicity and parsimony of the SCS-CN method, we have developed a quasi-continuous stochastic simulation approach, comprising the following steps: (1) generation of synthetic daily rainfall time series; (2) update of potential maximum soil moisture retention, on the basis of accumulated five-day rainfall; (3) estimation of daily runoff through the SCS-CN formula, using as inputs the daily rainfall and the updated value of soil moisture retention;(4) selection of extreme events and application of the standard SCS-CN procedure for each specific event, on the basis of synthetic rainfall.This scheme requires the use of two stochastic modelling components, namely the CastaliaR model, for the generation of synthetic daily data, and the HyetosMinute model, for the disaggregation of daily rainfall to finer temporal scales. Outcomes of this approach are a large number of synthetic flood events, allowing for expressing the design variables in statistical terms and thus properly evaluating the flood risk.

  10. Implementation of a PETN failure model using ARIA's general chemistry framework

    Energy Technology Data Exchange (ETDEWEB)

    Hobbs, Michael L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-01-01

    We previously developed a PETN thermal decomposition model that accurately predicts thermal ignition and detonator failure [1]. This model was originally developed for CALORE [2] and required several complex user subroutines. Recently, a simplified version of the PETN decomposition model was implemented into ARIA [3] using a general chemistry framework without need for user subroutines. Detonator failure was also predicted with this new model using ENCORE. The model was simplified by 1) basing the model on moles rather than mass, 2) simplifying the thermal conductivity model, and 3) implementing ARIA’s new phase change model. This memo briefly describes the model, implementation, and validation.

  11. Asymmetric Joint Source-Channel Coding for Correlated Sources with Blind HMM Estimation at the Receiver

    Directory of Open Access Journals (Sweden)

    Ser Javier Del

    2005-01-01

    Full Text Available We consider the case of two correlated sources, and . The correlation between them has memory, and it is modelled by a hidden Markov chain. The paper studies the problem of reliable communication of the information sent by the source over an additive white Gaussian noise (AWGN channel when the output of the other source is available as side information at the receiver. We assume that the receiver has no a priori knowledge of the correlation statistics between the sources. In particular, we propose the use of a turbo code for joint source-channel coding of the source . The joint decoder uses an iterative scheme where the unknown parameters of the correlation model are estimated jointly within the decoding process. It is shown that reliable communication is possible at signal-to-noise ratios close to the theoretical limits set by the combination of Shannon and Slepian-Wolf theorems.

  12. histoneHMM: Differential analysis of histone modifications with broad genomic footprints

    Czech Academy of Sciences Publication Activity Database

    Heinig, M.; Colomé-Tatché, M.; Taudt, A.; Rintisch, C.; Schafer, S.; Pravenec, Michal; Hubner, N.; Vingron, M.; Johannes, F.

    2015-01-01

    Roč. 16, Feb 22 (2015), s. 60 ISSN 1471-2105 R&D Projects: GA MŠk(CZ) 7E10067; GA ČR(CZ) GA13-04420S Institutional support: RVO:67985823 Keywords : ChIP - seq * histone modifications * Hidden Markov model * computational biology * differential analysis Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 2.435, year: 2015

  13. Framework for an asymptotically safe standard model via dynamical breaking

    DEFF Research Database (Denmark)

    Abel, Steven; Sannino, Francesco

    2017-01-01

    We present a consistent embedding of the matter and gauge content of the Standard Model into an underlying asymptotically safe theory that has a well-determined interacting UV fixed point in the large color/flavor limit. The scales of symmetry breaking are determined by two mass-squared parameters...... with the breaking of electroweak symmetry being driven radiatively. There are no other free parameters in the theory apart from gauge couplings....

  14. One-Shot Learning of Human Activity With an MAP Adapted GMM and Simplex-HMM.

    Science.gov (United States)

    Rodriguez, Mario; Orrite, Carlos; Medrano, Carlos; Makris, Dimitrios

    2016-05-10

    This paper presents a novel activity class representation using a single sequence for training. The contribution of this representation lays on the ability to train an one-shot learning recognition system, useful in new scenarios where capturing and labeling sequences is expensive or impractical. The method uses a universal background model of local descriptors obtained from source databases available on-line and adapts it to a new sequence in the target scenario through a maximum a posteriori adaptation. Each activity sample is encoded in a sequence of normalized bag of features and modeled by a new hidden Markov model formulation, where the expectation-maximization algorithm for training is modified to deal with observations consisting in vectors in a unit simplex. Extensive experiments in recognition have been performed using one-shot learning over the public datasets Weizmann, KTH, and IXMAS. These experiments demonstrate the discriminative properties of the representation and the validity of application in recognition systems, achieving state-of-the-art results.

  15. A business case modelling framework for smart multi-energy districts

    OpenAIRE

    Good, Nicholas; Martinez Cesena, Eduardo Alejandro; Liu, Xuezhi; Mancarella, Pierluigi

    2017-01-01

    The potential energy, environmental, technical and economic benefits that might arise from multi-energy systems are increasing interest in smart districts. However, in a liberalised market, it is essential to develop a relevant attractive business case. This paper presents a holistic techno-economic framework that couples building/district, multi-network and business case assessment models for the development of robust business cases for smart multi-energy districts. The framework is demonstr...

  16. CASCADE: An Agent Based Framework For Modeling The Dynamics Of Smart Electricity Systems

    OpenAIRE

    Rylatt, R. M.; Gammon, Rupert; Boait, Peter John; Varga, L.; Allen, P.; Savill, M.; Snape, J. Richard; Lemon, Mark; Ardestani, B. M.; Pakka, V. H.; Fletcher, G.; Smith, S.; Fan, D.; Strathern, M.

    2013-01-01

    Collaborative project with Cranfield University The Complex Adaptive Systems, Cognitive Agents and Distributed Energy (CASCADE) project is developing a framework based on Agent Based Modelling (ABM). The CASCADE Framework can be used both to gain policy and industry relevant insights into the smart grid concept itself and as a platform to design and test distributed ICT solutions for smart grid based business entities. ABM is used to capture the behaviors of diff erent socia...

  17. CCHMM_PROF: a HMM-based coiled-coil predictor with evolutionary information

    DEFF Research Database (Denmark)

    Bartoli, Lisa; Fariselli, Piero; Krogh, Anders

    2009-01-01

    tools are available for predicting coiled-coil domains in protein sequences, including those based on position-specific score matrices and machine learning methods. RESULTS: In this article, we introduce a hidden Markov model (CCHMM_PROF) that exploits the information contained in multiple sequence...... alignments (profiles) to predict coiled-coil regions. The new method discriminates coiled-coil sequences with an accuracy of 97% and achieves a true positive rate of 79% with only 1% of false positives. Furthermore, when predicting the location of coiled-coil segments in protein sequences, the method reaches...

  18. A Semi-Continuous State-Transition Probability HMM-Based Voice Activity Detector

    Directory of Open Access Journals (Sweden)

    H. Othman

    2007-02-01

    Full Text Available We introduce an efficient hidden Markov model-based voice activity detection (VAD algorithm with time-variant state-transition probabilities in the underlying Markov chain. The transition probabilities vary in an exponential charge/discharge scheme and are softly merged with state conditional likelihood into a final VAD decision. Working in the domain of ITU-T G.729 parameters, with no additional cost for feature extraction, the proposed algorithm significantly outperforms G.729 Annex B VAD while providing a balanced tradeoff between clipping and false detection errors. The performance compares very favorably with the adaptive multirate VAD, option 2 (AMR2.

  19. A Semi-Continuous State-Transition Probability HMM-Based Voice Activity Detector

    Directory of Open Access Journals (Sweden)

    Othman H

    2007-01-01

    Full Text Available We introduce an efficient hidden Markov model-based voice activity detection (VAD algorithm with time-variant state-transition probabilities in the underlying Markov chain. The transition probabilities vary in an exponential charge/discharge scheme and are softly merged with state conditional likelihood into a final VAD decision. Working in the domain of ITU-T G.729 parameters, with no additional cost for feature extraction, the proposed algorithm significantly outperforms G.729 Annex B VAD while providing a balanced tradeoff between clipping and false detection errors. The performance compares very favorably with the adaptive multirate VAD, option 2 (AMR2.

  20. Generic framework for mining cellular automata models on protein-folding simulations.

    Science.gov (United States)

    Diaz, N; Tischer, I

    2016-05-13

    Cellular automata model identification is an important way of building simplified simulation models. In this study, we describe a generic architectural framework to ease the development process of new metaheuristic-based algorithms for cellular automata model identification in protein-folding trajectories. Our framework was developed by a methodology based on design patterns that allow an improved experience for new algorithms development. The usefulness of the proposed framework is demonstrated by the implementation of four algorithms, able to obtain extremely precise cellular automata models of the protein-folding process with a protein contact map representation. Dynamic rules obtained by the proposed approach are discussed, and future use for the new tool is outlined.

  1. Strategic Port Graph Rewriting: An Interactive Modelling and Analysis Framework

    Directory of Open Access Journals (Sweden)

    Maribel Fernández

    2014-07-01

    Full Text Available We present strategic portgraph rewriting as a basis for the implementation of visual modelling and analysis tools. The goal is to facilitate the specification, analysis and simulation of complex systems, using port graphs. A system is represented by an initial graph and a collection of graph rewriting rules, together with a user-defined strategy to control the application of rules. The strategy language includes constructs to deal with graph traversal and management of rewriting positions in the graph. We give a small-step operational semantics for the language, and describe its implementation in the graph transformation and visualisation tool PORGY.

  2. A model-based framework for incremental scale-up of wastewater treatment processes

    DEFF Research Database (Denmark)

    Mauricio Iglesias, Miguel; Sin, Gürkan

    Scale-up is traditionally done following specific ratios or rules of thumb which do not lead to optimal results. We present a generic framework to assist in scale-up of wastewater treatment processes based on multiscale modelling, multiobjective optimisation and a validation of the model at the new...... large scale. The framework is illustrated by the scale-up of a complete autotropic nitrogen removal process. The model based multiobjective scaleup offers a promising improvement compared to the rule of thumbs based emprical scale up rules...

  3. A system-level multiprocessor system-on-chip modeling framework

    DEFF Research Database (Denmark)

    Virk, Kashif Munir; Madsen, Jan

    2004-01-01

    We present a system-level modeling framework to model system-on-chips (SoC) consisting of heterogeneous multiprocessors and network-on-chip communication structures in order to enable the developers of today's SoC designs to take advantage of the flexibility and scalability of network-on-chip and...... SoC design. We show how a hand-held multimedia terminal, consisting of JPEG, MP3 and GSM applications, can be modeled as a multiprocessor SoC in our framework....

  4. The Modular Modeling System (MMS): A modeling framework for water- and environmental-resources management

    Science.gov (United States)

    Leavesley, G.H.; Markstrom, S.L.; Viger, R.J.

    2004-01-01

    The interdisciplinary nature and increasing complexity of water- and environmental-resource problems require the use of modeling approaches that can incorporate knowledge from a broad range of scientific disciplines. The large number of distributed hydrological and ecosystem models currently available are composed of a variety of different conceptualizations of the associated processes they simulate. Assessment of the capabilities of these distributed models requires evaluation of the conceptualizations of the individual processes, and the identification of which conceptualizations are most appropriate for various combinations of criteria, such as problem objectives, data constraints, and spatial and temporal scales of application. With this knowledge, "optimal" models for specific sets of criteria can be created and applied. The U.S. Geological Survey (USGS) Modular Modeling System (MMS) is an integrated system of computer software that has been developed to provide these model development and application capabilities. MMS supports the integration of models and tools at a variety of levels of modular design. These include individual process models, tightly coupled models, loosely coupled models, and fully-integrated decision support systems. A variety of visualization and statistical tools are also provided. MMS has been coupled with the Bureau of Reclamation (BOR) object-oriented reservoir and river-system modeling framework, RiverWare, under a joint USGS-BOR program called the Watershed and River System Management Program. MMS and RiverWare are linked using a shared relational database. The resulting database-centered decision support system provides tools for evaluating and applying optimal resource-allocation and management strategies to complex, operational decisions on multipurpose reservoir systems and watersheds. Management issues being addressed include efficiency of water-resources management, environmental concerns such as meeting flow needs for

  5. A framework for model-based optimization of bioprocesses under uncertainty: Identifying critical parameters and operating variables

    DEFF Research Database (Denmark)

    Morales Rodriguez, Ricardo; Meyer, Anne S.; Gernaey, Krist

    2011-01-01

    This study presents the development and application of a systematic model-based framework for bioprocess optimization, evaluated on a cellulosic ethanol production case study. The implementation of the framework involves the use of dynamic simulations, sophisticated uncertainty analysis (Monte...

  6. The digital transformation of business models in the creative industries: A holistic framework and emerging trends

    OpenAIRE

    Li, F.

    2018-01-01

    This paper examines how digital technologies facilitate business model innovations in the creative industries. Through a systematic literature review, a holistic business model framework is developed, which is then used to analyse the empirical evidence from the creative industries. The research found that digital technologies have facilitated pervasive changes in business models, and some significant trends have emerged. However, the reconfigured business models are often not ‘new’ in the un...

  7. Uncertainty in the environmental modelling process – A framework and guidance

    NARCIS (Netherlands)

    Refsgaard, J.C.; van der Sluijs, J.P.|info:eu-repo/dai/nl/073427489; Hojberg, A.L.; Vanrolleghem, P.

    2007-01-01

    A terminology and typology of uncertainty is presented together with a framework for the modelling process, its interaction with the broader water management process and the role of uncertainty at different stages in the modelling processes. Brief reviews have been made of 14 different (partly

  8. Developing the multi-level functioning interface framework for DER models

    DEFF Research Database (Denmark)

    Han, Xue; Bindner, Henrik W.; You, Shi

    2013-01-01

    The paper summarises several modelling applications of distributed energy resources (DERs) for various purposes, and describes the related operational issues regarding the complexity of the future distribution grid. Furthermore, a multi-level functioning interface framework is proposed for DER mo....... The information mapping for photovoltaic panel (PV) modelling is also provided as an example....

  9. A multiscale and multiphysics numerical framework for modelling of hygrothermal ageing in laminated composites

    NARCIS (Netherlands)

    Barcelos Carneiro M Rocha, Iuri; van der Meer, F.P.; Nijssen, RPL; Sluijs, Bert

    2017-01-01

    In this work, a numerical framework for modelling of hygrothermal ageing in laminated composites is proposed. The model consists of a macroscopic diffusion analysis based on Fick's second law coupled with a multiscale FE2 stress analysis in order to take microscopic degradation

  10. A Bayesian modelling framework for tornado occurrences in North America.

    Science.gov (United States)

    Cheng, Vincent Y S; Arhonditsis, George B; Sills, David M L; Gough, William A; Auld, Heather

    2015-03-25

    Tornadoes represent one of nature's most hazardous phenomena that have been responsible for significant destruction and devastating fatalities. Here we present a Bayesian modelling approach for elucidating the spatiotemporal patterns of tornado activity in North America. Our analysis shows a significant increase in the Canadian Prairies and the Northern Great Plains during the summer, indicating a clear transition of tornado activity from the United States to Canada. The linkage between monthly-averaged atmospheric variables and likelihood of tornado events is characterized by distinct seasonality; the convective available potential energy is the predominant factor in the summer; vertical wind shear appears to have a strong signature primarily in the winter and secondarily in the summer; and storm relative environmental helicity is most influential in the spring. The present probabilistic mapping can be used to draw inference on the likelihood of tornado occurrence in any location in North America within a selected time period of the year.

  11. A unified framework for data modeling on medical information systems.

    Science.gov (United States)

    Neves, J; Cortez, P; Rocha, M; Abelha, A; Machado, J; Alves, V; Basto, S; Botelho, H; Neves, J

    1999-01-01

    Medical Information Systems (MIS) are seen as a way of optimizing the use of existing health-care infrastructure, without resorting to new and costly hospital (re)construction. The qualitative (re)design of such an environment requires a basic understanding of patient and doctors related characteristics and capabilities. Patient care, patient education, medical education, and clinical research need to be considered to meet the basic requirements on the level of services desirable, determined on the basis of the patient's length of stay; i.e., used for modeling the significant entities of such a world. The aim is to extract conclusions for the level of services provided to the users. One's concept will capture, as well as will integrate, the basic design principles under which MIS may be set.

  12. A Framework for Conceptual Modeling of Geographic Data Quality

    DEFF Research Database (Denmark)

    Friis-Christensen, Anders; Christensen, J.V.; Jensen, Christian Søndergaard

    2004-01-01

    Sustained advances in wireless communications, geo-positioning, and consumer electronics pave the way to a kind of location-based service that relies on the tracking of the continuously changing positions of an entire population of service users. This type of service is characterized by large...... an object is moving. Empirical performance studies based on a real road network and GPS logs from cars areThe notion of data quality is of particular importance to geographic data. One reason is that such data is often inherently imprecise. Another is that the usability of the data is in large part...... determined by how "good" the data is, as different applications of geographic data require different qualities of the data are met. Such qualities concern the object level as well as the attribute level of the data. This paper presents a systematic and integrated approach to the conceptual modeling...

  13. A Monte Carlo Simulation Framework for Testing Cosmological Models

    Directory of Open Access Journals (Sweden)

    Heymann Y.

    2014-10-01

    Full Text Available We tested alternative cosmologies using Monte Carlo simulations based on the sam- pling method of the zCosmos galactic survey. The survey encompasses a collection of observable galaxies with respective redshifts that have been obtained for a given spec- troscopic area of the sky. Using a cosmological model, we can convert the redshifts into light-travel times and, by slicing the survey into small redshift buckets, compute a curve of galactic density over time. Because foreground galaxies obstruct the images of more distant galaxies, we simulated the theoretical galactic density curve using an average galactic radius. By comparing the galactic density curves of the simulations with that of the survey, we could assess the cosmologies. We applied the test to the expanding-universe cosmology of de Sitter and to a dichotomous cosmology.

  14. A Fuzzy Logic Framework for Integrating Multiple Learned Models

    Energy Technology Data Exchange (ETDEWEB)

    Hartog, Bobi Kai Den [Univ. of Nebraska, Lincoln, NE (United States)

    1999-03-01

    The Artificial Intelligence field of Integrating Multiple Learned Models (IMLM) explores ways to combine results from sets of trained programs. Aroclor Interpretation is an ill-conditioned problem in which trained programs must operate in scenarios outside their training ranges because it is intractable to train them completely. Consequently, they fail in ways related to the scenarios. We developed a general-purpose IMLM solution, the Combiner, and applied it to Aroclor Interpretation. The Combiner's first step, Scenario Identification (M), learns rules from very sparse, synthetic training data consisting of results from a suite of trained programs called Methods. S1 produces fuzzy belief weights for each scenario by approximately matching the rules. The Combiner's second step, Aroclor Presence Detection (AP), classifies each of three Aroclors as present or absent in a sample. The third step, Aroclor Quantification (AQ), produces quantitative values for the concentration of each Aroclor in a sample. AP and AQ use automatically learned empirical biases for each of the Methods in each scenario. Through fuzzy logic, AP and AQ combine scenario weights, automatically learned biases for each of the Methods in each scenario, and Methods' results to determine results for a sample.

  15. A framework for fuzzy model of thermoradiotherapy efficiency

    International Nuclear Information System (INIS)

    Kosterev, V.V.; Averkin, A.N.

    2005-01-01

    Full text: The use of hyperthermia as an adjuvant to radiation in the treatment of local and regional disease currently offers the most significant advantages. For processing of information of thermo radiotherapy efficiency, it is expedient to use the fuzzy logic based decision-support system - fuzzy system (FS). FSs are widely used in various application areas of control and decision making. Their popularity is due to the following reasons. Firstly, FS with triangular membership functions is universal approximator. Secondly, the designing of FS does not need the exact model of the process, but needs only qualitative linguistic dependences between the parameters. Thirdly, there are many program and hardware realizations of FS with very high speed of calculations. Fourthly, accuracy of the decisions received based on FS, usually is not worse and sometimes is better than accuracy of the decisions received by traditional methods. Moreover, dependence between input and output variables can be easily expressed in linguistic scales. The goal of this research is to choose the data fusion RULE's operators suitable to experimental results and taking into consideration uncertainty factor. Methods of aggregation and data fusion might be used which provide a methodology to extract comprehensible rules from data. Several data fusion algorithms have been developed and applied, individually and in combination, providing users with various levels of informational detail. In reviewing these emerging technology three basic categories (levels) of data fusion has been developed. These fusion levels are differentiated according to the amount of information they provide. Refs. 2 (author)

  16. Modeling Framework and Results to Inform Charging Infrastructure Investments

    Energy Technology Data Exchange (ETDEWEB)

    Melaina, Marc W [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Wood, Eric W [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2017-09-01

    The plug-in electric vehicle (PEV) market is experiencing rapid growth with dozens of battery electric (BEV) and plug-in hybrid electric (PHEV) models already available and billions of dollars being invested by automotive manufacturers in the PEV space. Electric range is increasing thanks to larger and more advanced batteries and significant infrastructure investments are being made to enable higher power fast charging. Costs are falling and PEVs are becoming more competitive with conventional vehicles. Moreover, new technologies such as connectivity and automation hold the promise of enhancing the value proposition of PEVs. This presentation outlines a suite of projects funded by the U.S. Department of Energy's Vehicle Technology Office to conduct assessments of the economic value and charging infrastructure requirements of the evolving PEV market. Individual assessments include national evaluations of PEV economic value (assuming 73M PEVs on the road in 2035), national analysis of charging infrastructure requirements (with community and corridor level resolution), and case studies of PEV ownership in Columbus, OH and Massachusetts.

  17. A new fit-for-purpose model testing framework: Decision Crash Tests

    Science.gov (United States)

    Tolson, Bryan; Craig, James

    2016-04-01

    Decision-makers in water resources are often burdened with selecting appropriate multi-million dollar strategies to mitigate the impacts of climate or land use change. Unfortunately, the suitability of existing hydrologic simulation models to accurately inform decision-making is in doubt because the testing procedures used to evaluate model utility (i.e., model validation) are insufficient. For example, many authors have identified that a good standard framework for model testing called the Klemes Crash Tests (KCTs), which are the classic model validation procedures from Klemeš (1986) that Andréassian et al. (2009) rename as KCTs, have yet to become common practice in hydrology. Furthermore, Andréassian et al. (2009) claim that the progression of hydrological science requires widespread use of KCT and the development of new crash tests. Existing simulation (not forecasting) model testing procedures such as KCTs look backwards (checking for consistency between simulations and past observations) rather than forwards (explicitly assessing if the model is likely to support future decisions). We propose a fundamentally different, forward-looking, decision-oriented hydrologic model testing framework based upon the concept of fit-for-purpose model testing that we call Decision Crash Tests or DCTs. Key DCT elements are i) the model purpose (i.e., decision the model is meant to support) must be identified so that model outputs can be mapped to management decisions ii) the framework evaluates not just the selected hydrologic model but the entire suite of model-building decisions associated with model discretization, calibration etc. The framework is constructed to directly and quantitatively evaluate model suitability. The DCT framework is applied to a model building case study on the Grand River in Ontario, Canada. A hypothetical binary decision scenario is analysed (upgrade or not upgrade the existing flood control structure) under two different sets of model building

  18. Pairagon: a highly accurate, HMM-based cDNA-to-genome aligner.

    Science.gov (United States)

    Lu, David V; Brown, Randall H; Arumugam, Manimozhiyan; Brent, Michael R

    2009-07-01

    The most accurate way to determine the intron-exon structures in a genome is to align spliced cDNA sequences to the genome. Thus, cDNA-to-genome alignment programs are a key component of most annotation pipelines. The scoring system used to choose the best alignment is a primary determinant of alignment accuracy, while heuristics that prevent consideration of certain alignments are a primary determinant of runtime and memory usage. Both accuracy and speed are important considerations in choosing an alignment algorithm, but scoring systems have received much less attention than heuristics. We present Pairagon, a pair hidden Markov model based cDNA-to-genome alignment program, as the most accurate aligner for sequences with high- and low-identity levels. We conducted a series of experiments testing alignment accuracy with varying sequence identity. We first created 'perfect' simulated cDNA sequences by splicing the sequences of exons in the reference genome sequences of fly and human. The complete reference genome sequences were then mutated to various degrees using a realistic mutation simulator and the perfect cDNAs were aligned to them using Pairagon and 12 other aligners. To validate these results with natural sequences, we performed cross-species alignment using orthologous transcripts from human, mouse and rat. We found that aligner accuracy is heavily dependent on sequence identity. For sequences with 100% identity, Pairagon achieved accuracy levels of >99.6%, with one quarter of the errors of any other aligner. Furthermore, for human/mouse alignments, which are only 85% identical, Pairagon achieved 87% accuracy, higher than any other aligner. Pairagon source and executables are freely available at http://mblab.wustl.edu/software/pairagon/

  19. A Physics-Based Modeling Framework for Prognostic Studies

    Science.gov (United States)

    Kulkarni, Chetan S.

    2014-01-01

    Prognostics and Health Management (PHM) methodologies have emerged as one of the key enablers for achieving efficient system level maintenance as part of a busy operations schedule, and lowering overall life cycle costs. PHM is also emerging as a high-priority issue in critical applications, where the focus is on conducting fundamental research in the field of integrated systems health management. The term diagnostics relates to the ability to detect and isolate faults or failures in a system. Prognostics on the other hand is the process of predicting health condition and remaining useful life based on current state, previous conditions and future operating conditions. PHM methods combine sensing, data collection, interpretation of environmental, operational, and performance related parameters to indicate systems health under its actual application conditions. The development of prognostics methodologies for the electronics field has become more important as more electrical systems are being used to replace traditional systems in several applications in the aeronautics, maritime, and automotive fields. The development of prognostics methods for electronics presents several challenges due to the great variety of components used in a system, a continuous development of new electronics technologies, and a general lack of understanding of how electronics fail. Similarly with electric unmanned aerial vehicles, electrichybrid cars, and commercial passenger aircraft, we are witnessing a drastic increase in the usage of batteries to power vehicles. However, for battery-powered vehicles to operate at maximum efficiency and reliability, it becomes crucial to both monitor battery health and performance and to predict end of discharge (EOD) and end of useful life (EOL) events. We develop an electrochemistry-based model of Li-ion batteries that capture the significant electrochemical processes, are computationally efficient, capture the effects of aging, and are of suitable

  20. A modeling framework for investment planning in interdependent infrastructures in multi-hazard environments.

    Energy Technology Data Exchange (ETDEWEB)

    Brown, Nathanael J. K.; Gearhart, Jared Lee; Jones, Dean A.; Nozick, Linda Karen; Prince, Michael

    2013-09-01

    Currently, much of protection planning is conducted separately for each infrastructure and hazard. Limited funding requires a balance of expenditures between terrorism and natural hazards based on potential impacts. This report documents the results of a Laboratory Directed Research & Development (LDRD) project that created a modeling framework for investment planning in interdependent infrastructures focused on multiple hazards, including terrorism. To develop this framework, three modeling elements were integrated: natural hazards, terrorism, and interdependent infrastructures. For natural hazards, a methodology was created for specifying events consistent with regional hazards. For terrorism, we modeled the terrorists actions based on assumptions regarding their knowledge, goals, and target identification strategy. For infrastructures, we focused on predicting post-event performance due to specific terrorist attacks and natural hazard events, tempered by appropriate infrastructure investments. We demonstrate the utility of this framework with various examples, including protection of electric power, roadway, and hospital networks.

  1. Designing A Framework To Design A Business Model For The 'Bottom Of The Pyramid' Population

    Directory of Open Access Journals (Sweden)

    Ver Loren van Themaat, Tanye

    2013-11-01

    Full Text Available This article presents a framework for developing and designing a business model to target the bottom of the pyramid (BoP population. Using blue ocean strategy and business model literature, integrated with research on the BoP, the framework offers a systematic approach for organisations to analyse and understand all aspects of the BoP and their environment, and then design a business model that minimises the risk of failure and fulfils the core requirements of the BoP. A case study on Capitec Bank demonstrates how the framework can be applied to the real world. The case study shows the practical examples that Capitec uses to target the BoP successfully, and the logic behind these actions. Further validation was done through interviews with experts in the relevant fields used in this study.

  2. Modeling complex biological flows in multi-scale systems using the APDEC framework

    Science.gov (United States)

    Trebotich, David

    2006-09-01

    We have developed advanced numerical algorithms to model biological fluids in multiscale flow environments using the software framework developed under the SciDAC APDEC ISIC. The foundation of our computational effort is an approach for modeling DNA laden fluids as ''bead-rod'' polymers whose dynamics are fully coupled to an incompressible viscous solvent. The method is capable of modeling short range forces and interactions between particles using soft potentials and rigid constraints. Our methods are based on higher-order finite difference methods in complex geometry with adaptivity, leveraging algorithms and solvers in the APDEC Framework. Our Cartesian grid embedded boundary approach to incompressible viscous flow in irregular geometries has also been interfaced to a fast and accurate level-sets method within the APDEC Framework for extracting surfaces from volume renderings of medical image data and used to simulate cardio-vascular and pulmonary flows in critical anatomies.

  3. A Framework for Relating Timed Transition Systems and Preserving TCTL Model Checking

    DEFF Research Database (Denmark)

    Jacobsen, Lasse; Jacobsen, Morten; Møller, Mikael Harkjær

    2010-01-01

    Many formal translations between time dependent models have been proposed over the years. While some of them produce timed bisimilar models, others preserve only reachability or (weak) trace equivalence. We suggest a general framework for arguing when a translation preserves Timed Computation Tree...... Logic (TCTL) or its safety fragment.The framework works at the level of timed transition systems, making it independent of the modeling formalisms and applicable to many of the translations published in the literature. Finally, we present a novel translation from extended Timed-Arc Petri Nets...... to Networks of Timed Automata and using the framework argue that itpreserves the full TCTL. The translation has been implemented in the verification tool TAPAAL....

  4. A Personalized Predictive Framework for Multivariate Clinical Time Series via Adaptive Model Selection.

    Science.gov (United States)

    Liu, Zitao; Hauskrecht, Milos

    2017-11-01

    Building of an accurate predictive model of clinical time series for a patient is critical for understanding of the patient condition, its dynamics, and optimal patient management. Unfortunately, this process is not straightforward. First, patient-specific variations are typically large and population-based models derived or learned from many different patients are often unable to support accurate predictions for each individual patient. Moreover, time series observed for one patient at any point in time may be too short and insufficient to learn a high-quality patient-specific model just from the patient's own data. To address these problems we propose, develop and experiment with a new adaptive forecasting framework for building multivariate clinical time series models for a patient and for supporting patient-specific predictions. The framework relies on the adaptive model switching approach that at any point in time selects the most promising time series model out of the pool of many possible models, and consequently, combines advantages of the population, patient-specific and short-term individualized predictive models. We demonstrate that the adaptive model switching framework is very promising approach to support personalized time series prediction, and that it is able to outperform predictions based on pure population and patient-specific models, as well as, other patient-specific model adaptation strategies.

  5. A Framework For Enhancing Privacy In Location Based Services Using K-Anonymity Model

    Directory of Open Access Journals (Sweden)

    Jane Mugi

    2015-08-01

    Full Text Available Abstract This paper presents a framework for enhancing privacy in Location Based Services using K-anonymity model. Users of location based services have to reveal their location information in order to use these services however this has threatened the user privacy. K-anonymity approach has been studied extensively in various forms. However it is only effective when the user location is fixed. When a user moves and continuously sends their location information the location service provider can approximate user trajectory which poses a threat to the trajectory privacy of the user. This framework will ensure that user privacy is enhanced for both snapshot and continuous queries. The efficiency and effectiveness of the proposed framework was evaluated the results indicate that the proposed framework has high success rate and good run time performance.

  6. A climate robust integrated modelling framework for regional impact assessment of climate change

    Science.gov (United States)

    Janssen, Gijs; Bakker, Alexander; van Ek, Remco; Groot, Annemarie; Kroes, Joop; Kuiper, Marijn; Schipper, Peter; van Walsum, Paul; Wamelink, Wieger; Mol, Janet

    2013-04-01

    Decision making towards climate proofing the water management of regional catchments can benefit greatly from the availability of a climate robust integrated modelling framework, capable of a consistent assessment of climate change impacts on the various interests present in the catchments. In the Netherlands, much effort has been devoted to developing state-of-the-art regional dynamic groundwater models with a very high spatial resolution (25x25 m2). Still, these models are not completely satisfactory to decision makers because the modelling concepts do not take into account feedbacks between meteorology, vegetation/crop growth, and hydrology. This introduces uncertainties in forecasting the effects of climate change on groundwater, surface water, agricultural yields, and development of groundwater dependent terrestrial ecosystems. These uncertainties add to the uncertainties about the predictions on climate change itself. In order to create an integrated, climate robust modelling framework, we coupled existing model codes on hydrology, agriculture and nature that are currently in use at the different research institutes in the Netherlands. The modelling framework consists of the model codes MODFLOW (groundwater flow), MetaSWAP (vadose zone), WOFOST (crop growth), SMART2-SUMO2 (soil-vegetation) and NTM3 (nature valuation). MODFLOW, MetaSWAP and WOFOST are coupled online (i.e. exchange information on time step basis). Thus, changes in meteorology and CO2-concentrations affect crop growth and feedbacks between crop growth, vadose zone water movement and groundwater recharge are accounted for. The model chain WOFOST-MetaSWAP-MODFLOW generates hydrological input for the ecological prediction model combination SMART2-SUMO2-NTM3. The modelling framework was used to support the regional water management decision making process in the 267 km2 Baakse Beek-Veengoot catchment in the east of the Netherlands. Computations were performed for regionalized 30-year climate change

  7. A framework for scalable parameter estimation of gene circuit models using structural information

    KAUST Repository

    Kuwahara, Hiroyuki

    2013-06-21

    Motivation: Systematic and scalable parameter estimation is a key to construct complex gene regulatory models and to ultimately facilitate an integrative systems biology approach to quantitatively understand the molecular mechanisms underpinning gene regulation. Results: Here, we report a novel framework for efficient and scalable parameter estimation that focuses specifically on modeling of gene circuits. Exploiting the structure commonly found in gene circuit models, this framework decomposes a system of coupled rate equations into individual ones and efficiently integrates them separately to reconstruct the mean time evolution of the gene products. The accuracy of the parameter estimates is refined by iteratively increasing the accuracy of numerical integration using the model structure. As a case study, we applied our framework to four gene circuit models with complex dynamics based on three synthetic datasets and one time series microarray data set. We compared our framework to three state-of-the-art parameter estimation methods and found that our approach consistently generated higher quality parameter solutions efficiently. Although many general-purpose parameter estimation methods have been applied for modeling of gene circuits, our results suggest that the use of more tailored approaches to use domain-specific information may be a key to reverse engineering of complex biological systems. The Author 2013.

  8. An Agent-Based Modeling Framework for Simulating Human Exposure to Environmental Stresses in Urban Areas

    Directory of Open Access Journals (Sweden)

    Liang Emlyn Yang

    2018-04-01

    Full Text Available Several approaches have been used to assess potential human exposure to environmental stresses and achieve optimal results under various conditions, such as for example, for different scales, groups of people, or points in time. A thorough literature review in this paper identifies the research gap regarding modeling approaches for assessing human exposure to environment stressors, and it indicates that microsimulation tools are becoming increasingly important in human exposure assessments of urban environments, in which each person is simulated individually and continuously. The paper further describes an agent-based model (ABM framework that can dynamically simulate human exposure levels, along with their daily activities, in urban areas that are characterized by environmental stresses such as air pollution and heat stress. Within the framework, decision-making processes can be included for each individual based on rule-based behavior in order to achieve goals under changing environmental conditions. The ideas described in this paper are implemented in a free and open source NetLogo platform. A basic modeling scenario of the ABM framework in Hamburg, Germany, demonstrates its utility in various urban environments and individual activity patterns, as well as its portability to other models, programs, and frameworks. The prototype model can potentially be extended to support environmental incidence management through exploring the daily routines of different groups of citizens, and comparing the effectiveness of different strategies. Further research is needed to fully develop an operational version of the model.

  9. A framework for scalable parameter estimation of gene circuit models using structural information

    KAUST Repository

    Kuwahara, Hiroyuki; Fan, Ming; Wang, Suojin; Gao, Xin

    2013-01-01

    Motivation: Systematic and scalable parameter estimation is a key to construct complex gene regulatory models and to ultimately facilitate an integrative systems biology approach to quantitatively understand the molecular mechanisms underpinning gene regulation. Results: Here, we report a novel framework for efficient and scalable parameter estimation that focuses specifically on modeling of gene circuits. Exploiting the structure commonly found in gene circuit models, this framework decomposes a system of coupled rate equations into individual ones and efficiently integrates them separately to reconstruct the mean time evolution of the gene products. The accuracy of the parameter estimates is refined by iteratively increasing the accuracy of numerical integration using the model structure. As a case study, we applied our framework to four gene circuit models with complex dynamics based on three synthetic datasets and one time series microarray data set. We compared our framework to three state-of-the-art parameter estimation methods and found that our approach consistently generated higher quality parameter solutions efficiently. Although many general-purpose parameter estimation methods have been applied for modeling of gene circuits, our results suggest that the use of more tailored approaches to use domain-specific information may be a key to reverse engineering of complex biological systems. The Author 2013.

  10. A framework for scalable parameter estimation of gene circuit models using structural information.

    Science.gov (United States)

    Kuwahara, Hiroyuki; Fan, Ming; Wang, Suojin; Gao, Xin

    2013-07-01

    Systematic and scalable parameter estimation is a key to construct complex gene regulatory models and to ultimately facilitate an integrative systems biology approach to quantitatively understand the molecular mechanisms underpinning gene regulation. Here, we report a novel framework for efficient and scalable parameter estimation that focuses specifically on modeling of gene circuits. Exploiting the structure commonly found in gene circuit models, this framework decomposes a system of coupled rate equations into individual ones and efficiently integrates them separately to reconstruct the mean time evolution of the gene products. The accuracy of the parameter estimates is refined by iteratively increasing the accuracy of numerical integration using the model structure. As a case study, we applied our framework to four gene circuit models with complex dynamics based on three synthetic datasets and one time series microarray data set. We compared our framework to three state-of-the-art parameter estimation methods and found that our approach consistently generated higher quality parameter solutions efficiently. Although many general-purpose parameter estimation methods have been applied for modeling of gene circuits, our results suggest that the use of more tailored approaches to use domain-specific information may be a key to reverse engineering of complex biological systems. http://sfb.kaust.edu.sa/Pages/Software.aspx. Supplementary data are available at Bioinformatics online.

  11. The Roy Adaptation Model: A Theoretical Framework for Nurses Providing Care to Individuals With Anorexia Nervosa.

    Science.gov (United States)

    Jennings, Karen M

    Using a nursing theoretical framework to understand, elucidate, and propose nursing research is fundamental to knowledge development. This article presents the Roy Adaptation Model as a theoretical framework to better understand individuals with anorexia nervosa during acute treatment, and the role of nursing assessments and interventions in the promotion of weight restoration. Nursing assessments and interventions situated within the Roy Adaptation Model take into consideration how weight restoration does not occur in isolation but rather reflects an adaptive process within external and internal environments, and has the potential for more holistic care.

  12. A MULTISCALE FRAMEWORK FOR THE STOCHASTIC ASSIMILATION AND MODELING OF UNCERTAINTY ASSOCIATED NCF COMPOSITE MATERIALS

    Energy Technology Data Exchange (ETDEWEB)

    Mehrez, Loujaine [University of Southern California; Ghanem, Roger [University of Southern California; McAuliffe, Colin [Altair Engineering, Inc.; Aitharaju, Venkat [General Motors; Rodgers, William [General Motors

    2016-06-06

    multiscale framework to construct stochastic macroscopic constitutive material models is proposed. A spectral projection approach, specifically polynomial chaos expansion, has been used to construct explicit functional relationships between the homogenized properties and input parameters from finer scales. A homogenization engine embedded in Multiscale Designer, software for composite materials, has been used for the upscaling process. The framework is demonstrated using non-crimp fabric composite materials by constructing probabilistic models of the homogenized properties of a non-crimp fabric laminate in terms of the input parameters together with the homogenized properties from finer scales.

  13. A Framework for the Optimization of Discrete-Event Simulation Models

    Science.gov (United States)

    Joshi, B. D.; Unal, R.; White, N. H.; Morris, W. D.

    1996-01-01

    With the growing use of computer modeling and simulation, in all aspects of engineering, the scope of traditional optimization has to be extended to include simulation models. Some unique aspects have to be addressed while optimizing via stochastic simulation models. The optimization procedure has to explicitly account for the randomness inherent in the stochastic measures predicted by the model. This paper outlines a general purpose framework for optimization of terminating discrete-event simulation models. The methodology combines a chance constraint approach for problem formulation, together with standard statistical estimation and analyses techniques. The applicability of the optimization framework is illustrated by minimizing the operation and support resources of a launch vehicle, through a simulation model.

  14. A preliminary three-dimensional geological framework model for Yucca Mountain

    International Nuclear Information System (INIS)

    Stirewalt, G.L.; Henderson, D.B.

    1995-01-01

    A preliminary three-dimensional geological framework model has been developed for the potential high-level radioactive waste disposal site at Yucca Mountain. The model is based on field data and was constructed using EarthVision (Version 2.0) software. It provides the basic geological framework in which variations in geological parameters and features in and adjacent to the repository block can be illustrated and analyzed. With further refinement and modification of the model through incorporation of additional data, it can be used by Nuclear Regulatory Commission (NRC) staff to determine whether representation of subsurface geological features in Department of Energy models is reasonable. Consequently, NRC staff will be able to use the model during pre-licensing and licensing phases to assess models for analyses of site suitability, design considerations, and repository performance

  15. A Framework to Implement IoT Network Performance Modelling Techniques for Network Solution Selection

    Directory of Open Access Journals (Sweden)

    Declan T. Delaney

    2016-12-01

    Full Text Available No single network solution for Internet of Things (IoT networks can provide the required level of Quality of Service (QoS for all applications in all environments. This leads to an increasing number of solutions created to fit particular scenarios. Given the increasing number and complexity of solutions available, it becomes difficult for an application developer to choose the solution which is best suited for an application. This article introduces a framework which autonomously chooses the best solution for the application given the current deployed environment. The framework utilises a performance model to predict the expected performance of a particular solution in a given environment. The framework can then choose an apt solution for the application from a set of available solutions. This article presents the framework with a set of models built using data collected from simulation. The modelling technique can determine with up to 85% accuracy the solution which performs the best for a particular performance metric given a set of solutions. The article highlights the fractured and disjointed practice currently in place for examining and comparing communication solutions and aims to open a discussion on harmonising testing procedures so that different solutions can be directly compared and offers a framework to achieve this within IoT networks.

  16. A Framework to Implement IoT Network Performance Modelling Techniques for Network Solution Selection.

    Science.gov (United States)

    Delaney, Declan T; O'Hare, Gregory M P

    2016-12-01

    No single network solution for Internet of Things (IoT) networks can provide the required level of Quality of Service (QoS) for all applications in all environments. This leads to an increasing number of solutions created to fit particular scenarios. Given the increasing number and complexity of solutions available, it becomes difficult for an application developer to choose the solution which is best suited for an application. This article introduces a framework which autonomously chooses the best solution for the application given the current deployed environment. The framework utilises a performance model to predict the expected performance of a particular solution in a given environment. The framework can then choose an apt solution for the application from a set of available solutions. This article presents the framework with a set of models built using data collected from simulation. The modelling technique can determine with up to 85% accuracy the solution which performs the best for a particular performance metric given a set of solutions. The article highlights the fractured and disjointed practice currently in place for examining and comparing communication solutions and aims to open a discussion on harmonising testing procedures so that different solutions can be directly compared and offers a framework to achieve this within IoT networks.

  17. A Theoretically Consistent Framework for Modelling Lagrangian Particle Deposition in Plant Canopies

    Science.gov (United States)

    Bailey, Brian N.; Stoll, Rob; Pardyjak, Eric R.

    2018-06-01

    We present a theoretically consistent framework for modelling Lagrangian particle deposition in plant canopies. The primary focus is on describing the probability of particles encountering canopy elements (i.e., potential deposition), and provides a consistent means for including the effects of imperfect deposition through any appropriate sub-model for deposition efficiency. Some aspects of the framework draw upon an analogy to radiation propagation through a turbid medium with which to develop model theory. The present method is compared against one of the most commonly used heuristic Lagrangian frameworks, namely that originally developed by Legg and Powell (Agricultural Meteorology, 1979, Vol. 20, 47-67), which is shown to be theoretically inconsistent. A recommendation is made to discontinue the use of this heuristic approach in favour of the theoretically consistent framework developed herein, which is no more difficult to apply under equivalent assumptions. The proposed framework has the additional advantage that it can be applied to arbitrary canopy geometries given readily measurable parameters describing vegetation structure.

  18. A participative and facilitative conceptual modelling framework for discrete event simulation studies in healthcare

    OpenAIRE

    Kotiadis, Kathy; Tako, Antuela; Vasilakis, Christos

    2014-01-01

    Existing approaches to conceptual modelling (CM) in discrete-event simulation do not formally support the participation of a group of stakeholders. Simulation in healthcare can benefit from stakeholder participation as it makes possible to share multiple views and tacit knowledge from different parts of the system. We put forward a framework tailored to healthcare that supports the interaction of simulation modellers with a group of stakeholders to arrive at a common conceptual model. The fra...

  19. Family Environment and Childhood Obesity: A New Framework with Structural Equation Modeling

    OpenAIRE

    Huang, Hui; Wan Mohamed Radzi, Che Wan Jasimah bt; Salarzadeh Jenatabadi, Hashem

    2017-01-01

    The main purpose of the current article is to introduce a framework of the complexity of childhood obesity based on the family environment. A conceptual model that quantifies the relationships and interactions among parental socioeconomic status, family food security level, child’s food intake and certain aspects of parental feeding behaviour is presented using the structural equation modeling (SEM) concept. Structural models are analysed in terms of the direct and indirect connections among ...

  20. Evaluation of uncertainty in geological framework models at Yucca Mountain, Nevada

    International Nuclear Information System (INIS)

    Bagtzoglou, A.C.; Stirewalt, G.L.; Henderson, D.B.; Seida, S.B.

    1995-01-01

    The first step towards determining compliance with the performance objectives for both the repository system and the geologic setting at Yucca Mountain requires the development of detailed geostratigraphic models. This paper proposes an approach for the evaluation of the degree of uncertainty inherent in geologic maps and associated three-dimensional geological models. Following this approach, an assessment of accuracy and completeness of the data and evaluation of conceptual uncertainties in the geological framework models can be performed

  1. A framework for extracting and representing project knowledge contexts using topic models and dynamic knowledge maps

    Science.gov (United States)

    Xu, Jin; Li, Zheng; Li, Shuliang; Zhang, Yanyan

    2015-07-01

    There is still a lack of effective paradigms and tools for analysing and discovering the contents and relationships of project knowledge contexts in the field of project management. In this paper, a new framework for extracting and representing project knowledge contexts using topic models and dynamic knowledge maps under big data environments is proposed and developed. The conceptual paradigm, theoretical underpinning, extended topic model, and illustration examples of the ontology model for project knowledge maps are presented, with further research work envisaged.

  2. Should students design or interact with models? Using the Bifocal Modelling Framework to investigate model construction in high school science

    Science.gov (United States)

    Fuhrmann, Tamar; Schneider, Bertrand; Blikstein, Paulo

    2018-05-01

    The Bifocal Modelling Framework (BMF) is an approach for science learning which links students' physical experimentation with computer modelling in real time, focusing on the comparison of the two media. In this paper, we explore how a Bifocal Modelling implementation supported learning outcomes related to both content and metamodeling knowledge, focusing on the role of designing models. Our study consisted of three conditions implemented with a total of 69 9th grade high-school students. The first and second classes were assigned two implementation modes of BMF: with and without a model design module. The third condition, employed as a control, consisted of a class that received instruction in the school's traditional approach. Our results indicate that students participating in both BMF implementations demonstrated improved content knowledge and a better understanding of metamodeling. However, only the 'BMF-with-design' group improved significantly in both content and metamodeling knowledge. Our qualitative analyses indicate that both BMF groups designed detailed models that included scientific explanations. However only students who engaged in the model design component: (1) completed a detailed model displaying molecular interaction; and (2) developed a critical perspective about models. We discuss the implications of those results for teaching scientific science concepts and metamodeling knowledge.

  3. Coupled model of INM-IO global ocean model, CICE sea ice model and SCM OIAS framework

    Science.gov (United States)

    Bayburin, Ruslan; Rashit, Ibrayev; Konstantin, Ushakov; Vladimir, Kalmykov; Gleb, Dyakonov

    2015-04-01

    Status of coupled Arctic model of ocean and sea ice is presented. Model consists of INM IO global ocean component of high resolution, Los Alamos National Laboratory CICE sea ice model and a framework SCM OIAS for the ocean-ice-atmosphere-land coupled modeling on massively-parallel architectures. Model is currently under development at the Institute of Numerical Mathematics (INM), Hydrometeorological Center (HMC) and P.P. Shirshov Institute of Oceanology (IO). Model is aimed at modeling of intra-annual variability of hydrodynamics in Arctic and. The computational characteristics of the world ocean-sea ice coupled model governed by SCM OIAS are presented. The model is parallelized using MPI technologies and currently can use efficiently up to 5000 cores. Details of programming implementation, computational configuration and physical phenomena parametrization are analyzed in terms of intercoupling complex. Results of five year computational experiment of sea ice, snow and ocean state evolution in Arctic region on tripole grid with horizontal resolution of 3-5 kilometers, closed by atmospheric forcing field from repeating "normal" annual course taken from CORE1 experiment data base are presented and analyzed in terms of the state of vorticity and warm Atlantic water expansion.

  4. A Bayesian posterior predictive framework for weighting ensemble regional climate models

    Directory of Open Access Journals (Sweden)

    Y. Fan

    2017-06-01

    Full Text Available We present a novel Bayesian statistical approach to computing model weights in climate change projection ensembles in order to create probabilistic projections. The weight of each climate model is obtained by weighting the current day observed data under the posterior distribution admitted under competing climate models. We use a linear model to describe the model output and observations. The approach accounts for uncertainty in model bias, trend and internal variability, including error in the observations used. Our framework is general, requires very little problem-specific input, and works well with default priors. We carry out cross-validation checks that confirm that the method produces the correct coverage.

  5. A Bayesian Framework of Uncertainties Integration in 3D Geological Model

    Science.gov (United States)

    Liang, D.; Liu, X.

    2017-12-01

    3D geological model can describe complicated geological phenomena in an intuitive way while its application may be limited by uncertain factors. Great progress has been made over the years, lots of studies decompose the uncertainties of geological model to analyze separately, while ignored the comprehensive impacts of multi-source uncertainties. Great progress has been made over the years, while lots of studies ignored the comprehensive impacts of multi-source uncertainties when analyzed them item by item from each source. To evaluate the synthetical uncertainty, we choose probability distribution to quantify uncertainty, and propose a bayesian framework of uncertainties integration. With this framework, we integrated data errors, spatial randomness, and cognitive information into posterior distribution to evaluate synthetical uncertainty of geological model. Uncertainties propagate and cumulate in modeling process, the gradual integration of multi-source uncertainty is a kind of simulation of the uncertainty propagation. Bayesian inference accomplishes uncertainty updating in modeling process. Maximum entropy principle makes a good effect on estimating prior probability distribution, which ensures the prior probability distribution subjecting to constraints supplied by the given information with minimum prejudice. In the end, we obtained a posterior distribution to evaluate synthetical uncertainty of geological model. This posterior distribution represents the synthetical impact of all the uncertain factors on the spatial structure of geological model. The framework provides a solution to evaluate synthetical impact on geological model of multi-source uncertainties and a thought to study uncertainty propagation mechanism in geological modeling.

  6. Frameworks for change in healthcare organisations: a formative evaluation of the NHS Change Model.

    Science.gov (United States)

    Martin, Graham P; Sutton, Elizabeth; Willars, Janet; Dixon-Woods, Mary

    2013-08-01

    Organisational change in complex healthcare systems is a multifaceted process. The English National Health Service recently introduced a 'Change Model' that seeks to offer an evidence-based framework for guiding change. We report findings from a formative evaluation of the NHS Change Model and make recommendations for those developing the Model and its users. The evaluation involved 28 interviews with managers and clinicians making use of the Change Model in relation to a variety of projects. Interviews were fully transcribed and were analysed using an approach based on the Framework method. Participants saw the Change Model as valuable and practically useful. Fidelity to core principles of the Model was variable: participants often altered the Model, especially when using it to orchestrate the work of others. In challenging organisational contexts, the Change Model was sometimes used to delegitimise opposition rather than identify shared purpose among different interest groups. Those guiding change may benefit from frameworks, guidance and toolkits to structure and inform their planning and activities. Participants' experiences suggested the Change Model has much potential. Further work on its design and on supporting materials may optimise the approach, but its utility rests in particular on organisational cultures that support faithful application. © The Author(s) 2013 Reprints and permissions:]br]sagepub.co.uk/journalsPermissions.nav.

  7. ToPS: a framework to manipulate probabilistic models of sequence data.

    Directory of Open Access Journals (Sweden)

    André Yoshiaki Kashiwabara

    Full Text Available Discrete Markovian models can be used to characterize patterns in sequences of values and have many applications in biological sequence analysis, including gene prediction, CpG island detection, alignment, and protein profiling. We present ToPS, a computational framework that can be used to implement different applications in bioinformatics analysis by combining eight kinds of models: (i independent and identically distributed process; (ii variable-length Markov chain; (iii inhomogeneous Markov chain; (iv hidden Markov model; (v profile hidden Markov model; (vi pair hidden Markov model; (vii generalized hidden Markov model; and (viii similarity based sequence weighting. The framework includes functionality for training, simulation and decoding of the models. Additionally, it provides two methods to help parameter setting: Akaike and Bayesian information criteria (AIC and BIC. The models can be used stand-alone, combined in Bayesian classifiers, or included in more complex, multi-model, probabilistic architectures using GHMMs. In particular the framework provides a novel, flexible, implementation of decoding in GHMMs that detects when the architecture can be traversed efficiently.

  8. Simulation-optimization framework for multi-site multi-season hybrid stochastic streamflow modeling

    Science.gov (United States)

    Srivastav, Roshan; Srinivasan, K.; Sudheer, K. P.

    2016-11-01

    A simulation-optimization (S-O) framework is developed for the hybrid stochastic modeling of multi-site multi-season streamflows. The multi-objective optimization model formulated is the driver and the multi-site, multi-season hybrid matched block bootstrap model (MHMABB) is the simulation engine within this framework. The multi-site multi-season simulation model is the extension of the existing single-site multi-season simulation model. A robust and efficient evolutionary search based technique, namely, non-dominated sorting based genetic algorithm (NSGA - II) is employed as the solution technique for the multi-objective optimization within the S-O framework. The objective functions employed are related to the preservation of the multi-site critical deficit run sum and the constraints introduced are concerned with the hybrid model parameter space, and the preservation of certain statistics (such as inter-annual dependence and/or skewness of aggregated annual flows). The efficacy of the proposed S-O framework is brought out through a case example from the Colorado River basin. The proposed multi-site multi-season model AMHMABB (whose parameters are obtained from the proposed S-O framework) preserves the temporal as well as the spatial statistics of the historical flows. Also, the other multi-site deficit run characteristics namely, the number of runs, the maximum run length, the mean run sum and the mean run length are well preserved by the AMHMABB model. Overall, the proposed AMHMABB model is able to show better streamflow modeling performance when compared with the simulation based SMHMABB model, plausibly due to the significant role played by: (i) the objective functions related to the preservation of multi-site critical deficit run sum; (ii) the huge hybrid model parameter space available for the evolutionary search and (iii) the constraint on the preservation of the inter-annual dependence. Split-sample validation results indicate that the AMHMABB model is

  9. Web of Objects Based Ambient Assisted Living Framework for Emergency Psychiatric State Prediction

    Science.gov (United States)

    Alam, Md Golam Rabiul; Abedin, Sarder Fakhrul; Al Ameen, Moshaddique; Hong, Choong Seon

    2016-01-01

    Ambient assisted living can facilitate optimum health and wellness by aiding physical, mental and social well-being. In this paper, patients’ psychiatric symptoms are collected through lightweight biosensors and web-based psychiatric screening scales in a smart home environment and then analyzed through machine learning algorithms to provide ambient intelligence in a psychiatric emergency. The psychiatric states are modeled through a Hidden Markov Model (HMM), and the model parameters are estimated using a Viterbi path counting and scalable Stochastic Variational Inference (SVI)-based training algorithm. The most likely psychiatric state sequence of the corresponding observation sequence is determined, and an emergency psychiatric state is predicted through the proposed algorithm. Moreover, to enable personalized psychiatric emergency care, a service a web of objects-based framework is proposed for a smart-home environment. In this framework, the biosensor observations and the psychiatric rating scales are objectified and virtualized in the web space. Then, the web of objects of sensor observations and psychiatric rating scores are used to assess the dweller’s mental health status and to predict an emergency psychiatric state. The proposed psychiatric state prediction algorithm reported 83.03 percent prediction accuracy in an empirical performance study. PMID:27608023

  10. A Community Framework for Integrative, Coupled Modeling of Human-Earth Systems

    Science.gov (United States)

    Barton, C. M.; Nelson, G. C.; Tucker, G. E.; Lee, A.; Porter, C.; Ullah, I.; Hutton, E.; Hoogenboom, G.; Rogers, K. G.; Pritchard, C.

    2017-12-01

    We live today in a humanized world, where critical zone dynamics are driven by coupled human and biophysical processes. First generation modeling platforms have been invaluable in providing insight into dynamics of biophysical systems and social systems. But to understand today's humanized planet scientifically and to manage it sustainably, we need integrative modeling of this coupled human-Earth system. To address both scientific and policy questions, we also need modeling that can represent variable combinations of human-Earth system processes at multiple scales. Simply adding more code needed to do this to large, legacy first generation models is impractical, expensive, and will make them even more difficult to evaluate or understand. We need an approach to modeling that mirrors and benefits from the architecture of the complexly coupled systems we hope to model. Building on a series of international workshops over the past two years, we present a community framework to enable and support an ecosystem of diverse models as components that can be interconnected as needed to facilitate understanding of a range of complex human-earth systems interactions. Models are containerized in Docker to make them platform independent. A Basic Modeling Interface and Standard Names ontology (developed by the Community Surface Dynamics Modeling System) is applied to make them interoperable. They are then transformed into RESTful micro-services to allow them to be connected and run in a browser environment. This enables a flexible, multi-scale modeling environment to help address diverse issues with combinations of smaller, focused, component models that are easier to understand and evaluate. We plan to develop, deploy, and maintain this framework for integrated, coupled modeling in an open-source collaborative development environment that can democratize access to advanced technology and benefit from diverse global participation in model development. We also present an initial

  11. Framework for non-coherent interface models at finite displacement jumps and finite strains

    Science.gov (United States)

    Ottosen, Niels Saabye; Ristinmaa, Matti; Mosler, Jörn

    2016-05-01

    This paper deals with a novel constitutive framework suitable for non-coherent interfaces, such as cracks, undergoing large deformations in a geometrically exact setting. For this type of interface, the displacement field shows a jump across the interface. Within the engineering community, so-called cohesive zone models are frequently applied in order to describe non-coherent interfaces. However, for existing models to comply with the restrictions imposed by (a) thermodynamical consistency (e.g., the second law of thermodynamics), (b) balance equations (in particular, balance of angular momentum) and (c) material frame indifference, these models are essentially fiber models, i.e. models where the traction vector is collinear with the displacement jump. This constraints the ability to model shear and, in addition, anisotropic effects are excluded. A novel, extended constitutive framework which is consistent with the above mentioned fundamental physical principles is elaborated in this paper. In addition to the classical tractions associated with a cohesive zone model, the main idea is to consider additional tractions related to membrane-like forces and out-of-plane shear forces acting within the interface. For zero displacement jump, i.e. coherent interfaces, this framework degenerates to existing formulations presented in the literature. For hyperelasticity, the Helmholtz energy of the proposed novel framework depends on the displacement jump as well as on the tangent vectors of the interface with respect to the current configuration - or equivalently - the Helmholtz energy depends on the displacement jump and the surface deformation gradient. It turns out that by defining the Helmholtz energy in terms of the invariants of these variables, all above-mentioned fundamental physical principles are automatically fulfilled. Extensions of the novel framework necessary for material degradation (damage) and plasticity are also covered.

  12. Optimizing Availability of a Framework in Series Configuration Utilizing Markov Model and Monte Carlo Simulation Techniques

    Directory of Open Access Journals (Sweden)

    Mansoor Ahmed Siddiqui

    2017-06-01

    Full Text Available This research work is aimed at optimizing the availability of a framework comprising of two units linked together in series configuration utilizing Markov Model and Monte Carlo (MC Simulation techniques. In this article, effort has been made to develop a maintenance model that incorporates three distinct states for each unit, while taking into account their different levels of deterioration. Calculations are carried out using the proposed model for two distinct cases of corrective repair, namely perfect and imperfect repairs, with as well as without opportunistic maintenance. Initially, results are accomplished using an analytical technique i.e., Markov Model. Validation of the results achieved is later carried out with the help of MC Simulation. In addition, MC Simulation based codes also work well for the frameworks that follow non-exponential failure and repair rates, and thus overcome the limitations offered by the Markov Model.

  13. Development of a landscape integrity model framework to support regional conservation planning.

    Science.gov (United States)

    Walston, Leroy J; Hartmann, Heidi M

    2018-01-01

    Land managers increasingly rely upon landscape assessments to understand the status of natural resources and identify conservation priorities. Many of these landscape planning efforts rely on geospatial models that characterize the ecological integrity of the landscape. These general models utilize measures of habitat disturbance and human activity to map indices of ecological integrity. We built upon these modeling frameworks by developing a Landscape Integrity Index (LII) model using geospatial datasets of the human footprint, as well as incorporation of other indicators of ecological integrity such as biodiversity and vegetation departure. Our LII model serves as a general indicator of ecological integrity in a regional context of human activity, biodiversity, and change in habitat composition. We also discuss the application of the LII framework in two related coarse-filter landscape conservation approaches to expand the size and connectedness of protected areas as regional mitigation for anticipated land-use changes.

  14. Predicting the resilience and recovery of aquatic systems: a framework for model evolution within environmental observatories

    Science.gov (United States)

    Hipsey, Matthew R.; Hamilton, David P.; Hanson, Paul C.; Carey, Cayelan C.; Coletti, Janaine Z; Read, Jordan S.; Ibelings, Bas W; Valensini, Fiona J; Brookes, Justin D

    2015-01-01

    Maintaining the health of aquatic systems is an essential component of sustainable catchmentmanagement, however, degradation of water quality and aquatic habitat continues to challenge scientistsand policy-makers. To support management and restoration efforts aquatic system models are requiredthat are able to capture the often complex trajectories that these systems display in response to multiplestressors. This paper explores the abilities and limitations of current model approaches in meeting this chal-lenge, and outlines a strategy based on integration of flexible model libraries and data from observationnetworks, within a learning framework, as a means to improve the accuracy and scope of model predictions.The framework is comprised of a data assimilation component that utilizes diverse data streams from sensornetworks, and a second component whereby model structural evolution can occur once the model isassessed against theoretically relevant metrics of system function. Given the scale and transdisciplinarynature of the prediction challenge, network science initiatives are identified as a means to develop and inte-grate diverse model libraries and workflows, and to obtain consensus on diagnostic approaches to modelassessment that can guide model adaptation. We outline how such a framework can help us explore thetheory of how aquatic systems respond to change by bridging bottom-up and top-down lines of enquiry,and, in doing so, also advance the role of prediction in aquatic ecosystem management.

  15. Hybrid modelling framework by using mathematics-based and information-based methods

    International Nuclear Information System (INIS)

    Ghaboussi, J; Kim, J; Elnashai, A

    2010-01-01

    Mathematics-based computational mechanics involves idealization in going from the observed behaviour of a system into mathematical equations representing the underlying mechanics of that behaviour. Idealization may lead mathematical models that exclude certain aspects of the complex behaviour that may be significant. An alternative approach is data-centric modelling that constitutes a fundamental shift from mathematical equations to data that contain the required information about the underlying mechanics. However, purely data-centric methods often fail for infrequent events and large state changes. In this article, a new hybrid modelling framework is proposed to improve accuracy in simulation of real-world systems. In the hybrid framework, a mathematical model is complemented by information-based components. The role of informational components is to model aspects which the mathematical model leaves out. The missing aspects are extracted and identified through Autoprogressive Algorithms. The proposed hybrid modelling framework has a wide range of potential applications for natural and engineered systems. The potential of the hybrid methodology is illustrated through modelling highly pinched hysteretic behaviour of beam-to-column connections in steel frames.

  16. Optimizing the structure of the natural gas market using an agent-based modeling framework

    Energy Technology Data Exchange (ETDEWEB)

    Van Benthem, M.

    2010-01-14

    The overall research question guiding this study is as follows: what is the optimal structure of the natural gas market, considering both the degrees of affordability and supply security resulting from this structure? The sub-questions are: How can the concepts of supply security and affordability be usefully defined? (Chapter 2); What should a modeling framework for analyzing the natural gas market with regard to these concepts look like? (Chapters 3 and 4); What general conclusions can be drawn on the basis of this framework? (Chapter 5); What is the effect of liberalization on the Dutch natural gas market? (Chapter 6); What are the possible effects of current trends unfolding in the Dutch natural gas market? (Chapter 7). The framework constructed in this study implicitly contains the necessary elements for deriving a sustainability indicator too. However, to limit the scope of the study, sustainability will not be analyzed explicitly. Chapter 2 provides an introductory description of the natural gas market. Starting from a description of the natural gas value chain, the process of liberalization is described as a change in the organization of the value chain. In addition, the concepts of affordability and supply security are discussed and appropriate quantitative indicators for both objectives are identified. In Chapter 3, a survey of existing gas market models is performed. On the basis of this survey, a classification system for natural gas market models is developed. Furthermore, the characteristics of a modeling framework fit for the purpose of this study are derived. In Chapter 4, a general, quantitative framework for natural gas market modeling is developed on the basis of agent-based computational economics. The model's structure, its dynamics, output and data requirements are described. Furthermore, the properties of each agent are explored, and the possibilities for model verification and validation are outlined. Chapter 5 provides a number of

  17. Optimizing the structure of the natural gas market using an agent-based modeling framework

    International Nuclear Information System (INIS)

    Van Benthem, M.

    2010-01-01

    The overall research question guiding this study is as follows: what is the optimal structure of the natural gas market, considering both the degrees of affordability and supply security resulting from this structure? The sub-questions are: How can the concepts of supply security and affordability be usefully defined? (Chapter 2); What should a modeling framework for analyzing the natural gas market with regard to these concepts look like? (Chapters 3 and 4); What general conclusions can be drawn on the basis of this framework? (Chapter 5); What is the effect of liberalization on the Dutch natural gas market? (Chapter 6); What are the possible effects of current trends unfolding in the Dutch natural gas market? (Chapter 7). The framework constructed in this study implicitly contains the necessary elements for deriving a sustainability indicator too. However, to limit the scope of the study, sustainability will not be analyzed explicitly. Chapter 2 provides an introductory description of the natural gas market. Starting from a description of the natural gas value chain, the process of liberalization is described as a change in the organization of the value chain. In addition, the concepts of affordability and supply security are discussed and appropriate quantitative indicators for both objectives are identified. In Chapter 3, a survey of existing gas market models is performed. On the basis of this survey, a classification system for natural gas market models is developed. Furthermore, the characteristics of a modeling framework fit for the purpose of this study are derived. In Chapter 4, a general, quantitative framework for natural gas market modeling is developed on the basis of agent-based computational economics. The model's structure, its dynamics, output and data requirements are described. Furthermore, the properties of each agent are explored, and the possibilities for model verification and validation are outlined. Chapter 5 provides a number of

  18. Data-Model and Inter-Model Comparisons of the GEM Outflow Events Using the Space Weather Modeling Framework

    Science.gov (United States)

    Welling, D. T.; Eccles, J. V.; Barakat, A. R.; Kistler, L. M.; Haaland, S.; Schunk, R. W.; Chappell, C. R.

    2015-12-01

    Two storm periods were selected by the Geospace Environment Modeling Ionospheric Outflow focus group for community collaborative study because of its high magnetospheric activity and extensive data coverage: the September 27 - October 4, 2002 corotating interaction region event and the October 22 - 29 coronal mass ejection event. During both events, the FAST, Polar, Cluster, and other missions made key observations, creating prime periods for data-model comparison. The GEM community has come together to simulate this period using many different methods in order to evaluate models, compare results, and expand our knowledge of ionospheric outflow and its effects on global dynamics. This paper presents Space Weather Modeling Framework (SWMF) simulations of these important periods compared against observations from the Polar TIDE, Cluster CODIF and EFW instruments. Emphasis will be given to the second event. Density and velocity of oxygen and hydrogen throughout the lobes, plasma sheet, and inner magnetosphere will be the focus of these comparisons. For these simulations, the SWMF couples the multifluid version of BATS-R-US MHD to a variety of ionospheric outflow models of varying complexity. The simplest is outflow arising from constant MHD inner boundary conditions. Two first-principles-based models are also leveraged: the Polar Wind Outflow Model (PWOM), a fluid treatment of outflow dynamics, and the Generalized Polar Wind (GPW) model, which combines fluid and particle-in-cell approaches. Each model is capable of capturing a different set of energization mechanisms, yielding different outflow results. The data-model comparisons will illustrate how well each approach captures reality and which energization mechanisms are most important. Inter-model comparisons will illustrate how the different outflow specifications affect the magnetosphere. Specifically, it is found that the GPW provides increased heavy ion outflow over a broader spatial range than the alternative

  19. Evaluating and Improving Cloud Processes in the Multi-Scale Modeling Framework

    Energy Technology Data Exchange (ETDEWEB)

    Ackerman, Thomas P. [Univ. of Washington, Seattle, WA (United States)

    2015-03-01

    The research performed under this grant was intended to improve the embedded cloud model in the Multi-scale Modeling Framework (MMF) for convective clouds by using a 2-moment microphysics scheme rather than the single moment scheme used in all the MMF runs to date. The technical report and associated documents describe the results of testing the cloud resolving model with fixed boundary conditions and evaluation of model results with data. The overarching conclusion is that such model evaluations are problematic because errors in the forcing fields control the results so strongly that variations in parameterization values cannot be usefully constrained

  20. IEA Wind Task 37: Systems Modeling Framework and Ontology for Wind Turbines and Plants

    Energy Technology Data Exchange (ETDEWEB)

    Dykes, Katherine L [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zahle, Frederik [Technical University of Denmark; Merz, Karl [SINTEF Energy Research; McWilliam, Mike [Technical University of Denmark; Bortolotti, Pietro [Technical University Munich

    2017-08-14

    This presentation will provide an overview of progress to date in the development of a system modeling framework and ontology for wind turbines and plants as part of the larger IEA Wind Task 37 on wind energy systems engineering. The goals of the effort are to create a set of guidelines for a common conceptual architecture for wind turbines and plants so that practitioners can more easily share descriptions of wind turbines and plants across multiple parties and reduce the effort for translating descriptions between models; integrate different models together and collaborate on model development; and translate models among different levels of fidelity in the system.

  1. COSMOS: A System-Level Modelling and Simulation Framework for Coprocessor-Coupled Reconfigurable Systems

    DEFF Research Database (Denmark)

    Wu, Kehuai; Madsen, Jan

    2007-01-01

    and resource management, and iii) present a SystemC based framework to model and simulate coprocessor-coupled reconfigurable systems. We illustrate how COSMOS may be used to capture the dynamic behavior of such systems and emphasize the need for capturing the system aspects of such systems in order to deal...

  2. Map Resource Packet: Course Models for the History-Social Science Framework, Grade Seven.

    Science.gov (United States)

    California State Dept. of Education, Sacramento.

    This packet of maps is an auxiliary resource to the "World History and Geography: Medieval and Early Modern Times. Course Models for the History-Social Science Framework, Grade Seven." The set includes: outline, precipitation, and elevation maps; maps for locating key places; landform maps; and historical maps. The list of maps are…

  3. Spatial optimization of watershed management practices for nitrogen load reduction using a modeling-optimization framework

    Science.gov (United States)

    Best management practices (BMPs) are perceived as being effective in reducing nutrient loads transported from non-point sources (NPS) to receiving water bodies. The objective of this study was to develop a modeling-optimization framework that can be used by watershed management p...

  4. A Reduced Form Framework for Modeling Volatility of Speculative Prices based on Realized Variation Measures

    DEFF Research Database (Denmark)

    Andersen, Torben G.; Bollerslev, Tim; Huang, Xin

    Building on realized variance and bi-power variation measures constructed from high-frequency financial prices, we propose a simple reduced form framework for effectively incorporating intraday data into the modeling of daily return volatility. We decompose the total daily return variability...

  5. From Conceptual Frameworks to Mental Models for Astronomy: Students' Perceptions

    Science.gov (United States)

    Pundak, David; Liberman, Ido; Shacham, Miri

    2017-01-01

    Considerable debate exists among discipline-based astronomy education researchers about how students change their perceptions in science and astronomy. The study questioned the development of astronomical models among students in institutions of higher education by examining how college students change their initial conceptual frameworks and…

  6. PIRPOSAL Model of Integrative STEM Education: Conceptual and Pedagogical Framework for Classroom Implementation

    Science.gov (United States)

    Wells, John G.

    2016-01-01

    The PIRPOSAL model is both a conceptual and pedagogical framework intended for use as a pragmatic guide to classroom implementation of Integrative STEM Education. Designerly questioning prompted by a "need to know" serves as the basis for transitioning student designers within and among multiple phases while they progress toward an…

  7. OpenDrift v1.0: a generic framework for trajectory modelling

    Science.gov (United States)

    Dagestad, Knut-Frode; Röhrs, Johannes; Breivik, Øyvind; Ådlandsvik, Bjørn

    2018-04-01

    OpenDrift is an open-source Python-based framework for Lagrangian particle modelling under development at the Norwegian Meteorological Institute with contributions from the wider scientific community. The framework is highly generic and modular, and is designed to be used for any type of drift calculations in the ocean or atmosphere. A specific module within the OpenDrift framework corresponds to a Lagrangian particle model in the traditional sense. A number of modules have already been developed, including an oil drift module, a stochastic search-and-rescue module, a pelagic egg module, and a basic module for atmospheric drift. The framework allows for the ingestion of an unspecified number of forcing fields (scalar and vectorial) from various sources, including Eulerian ocean, atmosphere and wave models, but also measurements or a priori values for the same variables. A basic backtracking mechanism is inherent, using sign reversal of the total displacement vector and negative time stepping. OpenDrift is fast and simple to set up and use on Linux, Mac and Windows environments, and can be used with minimal or no Python experience. It is designed for flexibility, and researchers may easily adapt or write modules for their specific purpose. OpenDrift is also designed for performance, and simulations with millions of particles may be performed on a laptop. Further, OpenDrift is designed for robustness and is in daily operational use for emergency preparedness modelling (oil drift, search and rescue, and drifting ships) at the Norwegian Meteorological Institute.

  8. The maintenance management framework models and methods for complex systems maintenance

    CERN Document Server

    Crespo Márquez, Adolfo

    2010-01-01

    “The Maintenance Management Framework” describes and reviews the concept, process and framework of modern maintenance management of complex systems; concentrating specifically on modern modelling tools (deterministic and empirical) for maintenance planning and scheduling. It will be bought by engineers and professionals involved in maintenance management, maintenance engineering, operations management, quality, etc. as well as graduate students and researchers in this field.

  9. A framework for evaluating forest landscape model predictions using empirical data and knowledge

    Science.gov (United States)

    Wen J. Wang; Hong S. He; Martin A. Spetich; Stephen R. Shifley; Frank R. Thompson; William D. Dijak; Qia. Wang

    2014-01-01

    Evaluation of forest landscape model (FLM) predictions is indispensable to establish the credibility of predictions. We present a framework that evaluates short- and long-term FLM predictions at site and landscape scales. Site-scale evaluation is conducted through comparing raster cell-level predictions with inventory plot data whereas landscape-scale evaluation is...

  10. A general framework for the evaluation of genetic association studies using multiple marginal models

    DEFF Research Database (Denmark)

    Kitsche, Andreas; Ritz, Christian; Hothorn, Ludwig A.

    2016-01-01

    OBJECTIVE: In this study, we present a simultaneous inference procedure as a unified analysis framework for genetic association studies. METHODS: The method is based on the formulation of multiple marginal models that reflect different modes of inheritance. The basic advantage of this methodology...

  11. Fingerprint states of odd mass 115I nuclei in the framework of particle rotor model

    International Nuclear Information System (INIS)

    Goswami, R.; Saha Sarkar, M.; Sen, S.

    2008-01-01

    Extensive theoretical as well as experimental investigation of the nuclear structure of odd-mass iodine nuclei have revealed systematic presence of strongly coupled bands in all neutron deficient as well as neutron rich odd-mass iodine isotopes. The present work shows that the positive as well as the negative parity are fairly well reproduced in the framework of particle rotor model

  12. A multi-disciplinary framework for bio-economic modeling in aquaculture: a welfare case study

    NARCIS (Netherlands)

    Noble, C.; Berrill, I.K.; Waller, B.; Schneider, O.; Kole, A.P.W.

    2012-01-01

    This article summarizes the framework that translated data from multiple disciplines into a bio-economic decision tool for modeling the costs and benefits of improving fish welfare in commercial aquaculture. This decision tool formed the basis of a recent EU research project, BENEFISH which was

  13. Data to Support Development of Geologic Framework Models for the Deep Borehole Field Test

    Energy Technology Data Exchange (ETDEWEB)

    Perry, Frank Vinton [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Kelley, Richard E. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2017-09-14

    This report summarizes work conducted in FY2017 to identify and document publically available data for developing a Geologic Framework Model (GFM) for the Deep Borehole Field Test (DBFT). Data was collected for all four of the sites being considered in 2017 for a DBFT site.

  14. Beyond a Definition: Toward a Framework for Designing and Specifying Mentoring Models

    Science.gov (United States)

    Dawson, Phillip

    2014-01-01

    More than three decades of mentoring research has yet to converge on a unifying definition of mentoring; this is unsurprising given the diversity of relationships classified as mentoring. This article advances beyond a definition toward a common framework for specifying mentoring models. Sixteen design elements were identified from the literature…

  15. A reduced order aerothermodynamic modeling framework for hypersonic vehicles based on surrogate and POD

    OpenAIRE

    Chen Xin; Liu Li; Long Teng; Yue Zhenjiang

    2015-01-01

    Aerothermoelasticity is one of the key technologies for hypersonic vehicles. Accurate and efficient computation of the aerothermodynamics is one of the primary challenges for hypersonic aerothermoelastic analysis. Aimed at solving the shortcomings of engineering calculation, computation fluid dynamics (CFD) and experimental investigation, a reduced order modeling (ROM) framework for aerothermodynamics based on CFD predictions using an enhanced algorithm of fast maximin Latin hypercube design ...

  16. An Analytical Framework for Evaluating E-Commerce Business Models and Strategies.

    Science.gov (United States)

    Lee, Chung-Shing

    2001-01-01

    Considers electronic commerce as a paradigm shift, or a disruptive innovation, and presents an analytical framework based on the theories of transaction costs and switching costs. Topics include business transformation process; scale effect; scope effect; new sources of revenue; and e-commerce value creation model and strategy. (LRW)

  17. IEA Wind Task 37 System Modeling Framework and Ontology for Wind Turbines and Plants

    NARCIS (Netherlands)

    Dykes, K; Sanchez Perez Moreno, S.; Zahle, Frederik; Ning, A; McWilliam, M.; Zaayer, M B

    2017-01-01

    This presentation will provide an overview of progress to date in the development of a system modeling framework and ontology for wind turbines and plants as part of the larger IEA Wind Task 37 on wind energy systems engineering. The goals of the effort are to create a set of guidelines for a common

  18. Supporting SME Collecting Organisations: A Business Model Framework for Digital Heritage Collections

    Directory of Open Access Journals (Sweden)

    Darren Peacock

    2009-08-01

    Full Text Available Increasing numbers of heritage collecting organisations such as archives, galleries, libraries and museums are moving towards the provision of digital content and services based on the collections they hold. The collections sector in Australia is characterised by a diverse range of often very small organisations, many of which are struggling with the transition to digital service delivery. One major reason for this struggle is the lack of suitable underlying business models for these organisations as they attempt to achieve a sustainable digital presence. The diverse characteristics of organisations within the collections sector make it difficult, if not impossible, to identify a single business model suitable for all organisations. We argue in this paper that the development of a flexible e-business model framework is a more useful strategy for achieving this goal. This paper presents a preliminary framework based on the literature, utilising the Core + Complement (C+ Business Model Framework for Content Providers initially developed by Krueger et al. (2003 and outlines how the framework will be refined and investigated empirically in future research within the Australian collections sector.

  19. A reference model and technical framework for mobile social software for learning

    NARCIS (Netherlands)

    De Jong, Tim; Specht, Marcus; Koper, Rob

    2008-01-01

    De Jong,T., Specht, M., & Koper, R. (2008). A reference model and technical framework for mobile social software for learning. In I. A. Sánchez & P. Isaías (Eds.), Proceedings of the IADIS Mobile Learning Conference 2008 (pp. 206-210). April, 11-13, 2008, Carvoeiro, Portugal.

  20. TLS and photogrammetry for the modeling of a historic wooden framework

    Science.gov (United States)

    Koehl, M.; Viale, M.

    2012-04-01

    The building which is the object of the study is located in the center of Andlau, France. This mansion that was built in 1582 was the residence of the Lords of Andlau from the XVIth century until the French Revolution. Its architecture represents the Renaissance style of the XVIth century in particular by its volutes and its spiral staircase inside the polygonal turret. In January 2005, the municipality of Andlau became the owner of this Seigneury which is intended to welcome the future Heritage Interpretation Center (HIC), a museum is also going to be created there. Three levels of attic of this building are going to be restored and isolated, the historic framework will that way be masked and the last three levels will not be accessible any more. In this context, our lab was asked to model the framework to allow to make diagnoses there, to learn to know and to consolidate the knowledge on this type of historic framework. Finally, next to a virtual visualization, we provided other applications in particular the creation of an accurate 3D model of the framework for animations, as well as for foundation of an historical information system and for supplying the future museum and HIC with digital data. The project contains different phases: the data acquisition, the model creation and data structuring, the creation of an interactive model and the integration in a historic information system. All levels of the attic were acquired: a 3D Trimble GX scanner and partially a Trimble CX scanner were used in particular for the acquisition of data in the highest part of the framework. The various scans were directly georeferenced in the field thanks to control points, then merged together in an unique point cloud covering the whole structure. Several panoramic photos were also realized to create a virtual tour of the framework and the surroundings of the Seigneury. The purpose of the project was to supply a 3D model allowing the creation of scenographies and interactive

  1. GLOFRIM v1.0 – A globally applicable computational framework for integrated hydrological–hydrodynamic modelling

    NARCIS (Netherlands)

    Hoch, J.M.; Neal, Jeffrey; Baart, Fedor; van Beek, L.P.H.; Winsemius, Hessel; Bates, Paul; Bierkens, M.F.P.

    2017-01-01

    We here present GLOFRIM, a globally applicable computational framework for integrated hydrological–hydrodynamic modelling. GLOFRIM facilitates spatially explicit coupling of hydrodynamic and hydrologic models and caters for an ensemble of models to be coupled. It currently encompasses the global

  2. A mathematical framework for agent based models of complex biological networks.

    Science.gov (United States)

    Hinkelmann, Franziska; Murrugarra, David; Jarrah, Abdul Salam; Laubenbacher, Reinhard

    2011-07-01

    Agent-based modeling and simulation is a useful method to study biological phenomena in a wide range of fields, from molecular biology to ecology. Since there is currently no agreed-upon standard way to specify such models, it is not always easy to use published models. Also, since model descriptions are not usually given in mathematical terms, it is difficult to bring mathematical analysis tools to bear, so that models are typically studied through simulation. In order to address this issue, Grimm et al. proposed a protocol for model specification, the so-called ODD protocol, which provides a standard way to describe models. This paper proposes an addition to the ODD protocol which allows the description of an agent-based model as a dynamical system, which provides access to computational and theoretical tools for its analysis. The mathematical framework is that of algebraic models, that is, time-discrete dynamical systems with algebraic structure. It is shown by way of several examples how this mathematical specification can help with model analysis. This mathematical framework can also accommodate other model types such as Boolean networks and the more general logical models, as well as Petri nets.

  3. An Integrated Framework for Process-Driven Model Construction in Disease Ecology and Animal Health.

    Science.gov (United States)

    Mancy, Rebecca; Brock, Patrick M; Kao, Rowland R

    2017-01-01

    Process models that focus on explicitly representing biological mechanisms are increasingly important in disease ecology and animal health research. However, the large number of process modelling approaches makes it difficult to decide which is most appropriate for a given disease system and research question. Here, we discuss different motivations for using process models and present an integrated conceptual analysis that can be used to guide the construction of infectious disease process models and comparisons between them. Our presentation complements existing work by clarifying the major differences between modelling approaches and their relationship with the biological characteristics of the epidemiological system. We first discuss distinct motivations for using process models in epidemiological research, identifying the key steps in model design and use associated with each. We then present a conceptual framework for guiding model construction and comparison, organised according to key aspects of epidemiological systems. Specifically, we discuss the number and type of disease states, whether to focus on individual hosts (e.g., cows) or groups of hosts (e.g., herds or farms), how space or host connectivity affect disease transmission, whether demographic and epidemiological processes are periodic or can occur at any time, and the extent to which stochasticity is important. We use foot-and-mouth disease and bovine tuberculosis in cattle to illustrate our discussion and support explanations of cases in which different models are used to address similar problems. The framework should help those constructing models to structure their approach to modelling decisions and facilitate comparisons between models in the literature.

  4. A model-based framework for design of intensified enzyme-based processes

    DEFF Research Database (Denmark)

    Román-Martinez, Alicia

    This thesis presents a generic and systematic model-based framework to design intensified enzyme-based processes. The development of the presented methodology was motivated by the needs of the bio-based industry for a more systematic approach to achieve intensification in its production plants...... in enzyme-based processes which have found significant application in the pharmaceutical, food, and renewable fuels sector. The framework uses model-based strategies for (bio)-chemical process design and optimization, including the use of a superstructure to generate all potential reaction......(s)-separation(s) options according to a desired performance criteria and a generic mathematical model represented by the superstructure to derive the specific models corresponding to a specific process option. In principle, three methods of intensification of bioprocess are considered in this thesis: 1. enzymatic one...

  5. GLOFRIM v1.0 - A globally applicable computational framework for integrated hydrological-hydrodynamic modelling

    Science.gov (United States)

    Hoch, Jannis M.; Neal, Jeffrey C.; Baart, Fedor; van Beek, Rens; Winsemius, Hessel C.; Bates, Paul D.; Bierkens, Marc F. P.

    2017-10-01

    We here present GLOFRIM, a globally applicable computational framework for integrated hydrological-hydrodynamic modelling. GLOFRIM facilitates spatially explicit coupling of hydrodynamic and hydrologic models and caters for an ensemble of models to be coupled. It currently encompasses the global hydrological model PCR-GLOBWB as well as the hydrodynamic models Delft3D Flexible Mesh (DFM; solving the full shallow-water equations and allowing for spatially flexible meshing) and LISFLOOD-FP (LFP; solving the local inertia equations and running on regular grids). The main advantages of the framework are its open and free access, its global applicability, its versatility, and its extensibility with other hydrological or hydrodynamic models. Before applying GLOFRIM to an actual test case, we benchmarked both DFM and LFP for a synthetic test case. Results show that for sub-critical flow conditions, discharge response to the same input signal is near-identical for both models, which agrees with previous studies. We subsequently applied the framework to the Amazon River basin to not only test the framework thoroughly, but also to perform a first-ever benchmark of flexible and regular grids on a large-scale. Both DFM and LFP produce comparable results in terms of simulated discharge with LFP exhibiting slightly higher accuracy as expressed by a Kling-Gupta efficiency of 0.82 compared to 0.76 for DFM. However, benchmarking inundation extent between DFM and LFP over the entire study area, a critical success index of 0.46 was obtained, indicating that the models disagree as often as they agree. Differences between models in both simulated discharge and inundation extent are to a large extent attributable to the gridding techniques employed. In fact, the results show that both the numerical scheme of the inundation model and the gridding technique can contribute to deviations in simulated inundation extent as we control for model forcing and boundary conditions. This study shows

  6. Following the genes: a framework for animal modeling of psychiatric disorders

    Directory of Open Access Journals (Sweden)

    Sawa Akira

    2011-11-01

    Full Text Available Abstract The number of individual cases of psychiatric disorders that can be ascribed to identified, rare, single mutations is increasing with great rapidity. Such mutations can be recapitulated in mice to generate animal models with direct etiological validity. Defining the underlying pathogenic mechanisms will require an experimental and theoretical framework to make the links from mutation to altered behavior in an animal or psychopathology in a human. Here, we discuss key elements of such a framework, including cell type-based phenotyping, developmental trajectories, linking circuit properties at micro and macro scales and definition of neurobiological phenotypes that are directly translatable to humans.

  7. Following the genes: a framework for animal modeling of psychiatric disorders

    LENUS (Irish Health Repository)

    Mitchell, Kevin

    2011-11-11

    Abstract The number of individual cases of psychiatric disorders that can be ascribed to identified, rare, single mutations is increasing with great rapidity. Such mutations can be recapitulated in mice to generate animal models with direct etiological validity. Defining the underlying pathogenic mechanisms will require an experimental and theoretical framework to make the links from mutation to altered behavior in an animal or psychopathology in a human. Here, we discuss key elements of such a framework, including cell type-based phenotyping, developmental trajectories, linking circuit properties at micro and macro scales and definition of neurobiological phenotypes that are directly translatable to humans.

  8. An approximate framework for quantum transport calculation with model order reduction

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Quan, E-mail: quanchen@eee.hku.hk [Department of Electrical and Electronic Engineering, The University of Hong Kong (Hong Kong); Li, Jun [Department of Chemistry, The University of Hong Kong (Hong Kong); Yam, Chiyung [Beijing Computational Science Research Center (China); Zhang, Yu [Department of Chemistry, The University of Hong Kong (Hong Kong); Wong, Ngai [Department of Electrical and Electronic Engineering, The University of Hong Kong (Hong Kong); Chen, Guanhua [Department of Chemistry, The University of Hong Kong (Hong Kong)

    2015-04-01

    A new approximate computational framework is proposed for computing the non-equilibrium charge density in the context of the non-equilibrium Green's function (NEGF) method for quantum mechanical transport problems. The framework consists of a new formulation, called the X-formulation, for single-energy density calculation based on the solution of sparse linear systems, and a projection-based nonlinear model order reduction (MOR) approach to address the large number of energy points required for large applied biases. The advantages of the new methods are confirmed by numerical experiments.

  9. A framework for different levels of integration of computational models into web-based virtual patients.

    Science.gov (United States)

    Kononowicz, Andrzej A; Narracott, Andrew J; Manini, Simone; Bayley, Martin J; Lawford, Patricia V; McCormack, Keith; Zary, Nabil

    2014-01-23

    Virtual patients are increasingly common tools used in health care education to foster learning of clinical reasoning skills. One potential way to expand their functionality is to augment virtual patients' interactivity by enriching them with computational models of physiological and pathological processes. The primary goal of this paper was to propose a conceptual framework for the integration of computational models within virtual patients, with particular focus on (1) characteristics to be addressed while preparing the integration, (2) the extent of the integration, (3) strategies to achieve integration, and (4) methods for evaluating the feasibility of integration. An additional goal was to pilot the first investigation of changing framework variables on altering perceptions of integration. The framework was constructed using an iterative process informed by Soft System Methodology. The Virtual Physiological Human (VPH) initiative has been used as a source of new computational models. The technical challenges associated with development of virtual patients enhanced by computational models are discussed from the perspectives of a number of different stakeholders. Concrete design and evaluation steps are discussed in the context of an exemplar virtual patient employing the results of the VPH ARCH project, as well as improvements for future iterations. The proposed framework consists of four main elements. The first element is a list of feasibility features characterizing the integration process from three perspectives: the computational modelling researcher, the health care educationalist, and the virtual patient system developer. The second element included three integration levels: basic, where a single set of simulation outcomes is generated for specific nodes in the activity graph; intermediate, involving pre-generation of simulation datasets over a range of input parameters; advanced, including dynamic solution of the model. The third element is the

  10. Coupled energy economic model framework for analyzing Swiss electricity markets in changing policy environments

    OpenAIRE

    Maire, Sophie

    2016-01-01

    Energy policy needs to rely on the proper understanding of the interactions between policy instruments, consumer preferences, investment behavior, market structure, electricity supply, and the wider policy environment. This asks for appropriate modeling tools, able to represent precisely electricity supply options, model all types of energy and climate policies, as well as the reactions of the rest of the economy. Chapter 2 describes the ELECTRA-CH framework, developed to analyze electrici...

  11. Use of GERAM as Basis for a Virtual Enterprise Framework Model

    DEFF Research Database (Denmark)

    Vesterager, Johan; Bernus, Peter; Larsen, Lars B

    2001-01-01

    In the IMS-project Globeman21, the enterprise reference architecture GERAM was used as basis for creation of a virtual enterprise framework model. The model was used to map different industrial pilot projects, to classify virtual en-terprise concepts, and as underlying structure for a virtual...... enterprise manage-ment methodology. The paper gives a survey of the use of GERAM and the re-sults obtained....

  12. Conceptual Framework for Agent-Based Modeling of Customer-Oriented Supply Networks

    OpenAIRE

    Solano-Vanegas , Clara ,; Carrillo-Ramos , Angela; Montoya-Torres , Jairo ,

    2015-01-01

    Part 3: Collaboration Frameworks; International audience; Supply Networks (SN) are complex systems involving the interaction of different actors, very often, with different objectives and goals. Among the different existing modeling approaches, agent-based systems can properly represent the autonomous behavior of SN links and, simultaneously, observe the general response of the system as a result of individual actions. Most of research using agent-based modeling in SN focuses on production is...

  13. A Self-Adaptive Hidden Markov Model for Emotion Classification in Chinese Microblogs

    Directory of Open Access Journals (Sweden)

    Li Liu

    2015-01-01

    we propose a modified version of hidden Markov model (HMM classifier, called self-adaptive HMM, whose parameters are optimized by Particle Swarm Optimization algorithms. Since manually labeling large-scale dataset is difficult, we also employ the entropy to decide whether a new unlabeled tweet shall be contained in the training dataset after being assigned an emotion using our HMM-based approach. In the experiment, we collected about 200,000 Chinese tweets from Sina Weibo. The results show that the F-score of our approach gets 76% on happiness and fear and 65% on anger, surprise, and sadness. In addition, the self-adaptive HMM classifier outperforms Naive Bayes and Support Vector Machine on recognition of happiness, anger, and sadness.

  14. Π4U: A high performance computing framework for Bayesian uncertainty quantification of complex models

    Science.gov (United States)

    Hadjidoukas, P. E.; Angelikopoulos, P.; Papadimitriou, C.; Koumoutsakos, P.

    2015-03-01

    We present Π4U, an extensible framework, for non-intrusive Bayesian Uncertainty Quantification and Propagation (UQ+P) of complex and computationally demanding physical models, that can exploit massively parallel computer architectures. The framework incorporates Laplace asymptotic approximations as well as stochastic algorithms, along with distributed numerical differentiation and task-based parallelism for heterogeneous clusters. Sampling is based on the Transitional Markov Chain Monte Carlo (TMCMC) algorithm and its variants. The optimization tasks associated with the asymptotic approximations are treated via the Covariance Matrix Adaptation Evolution Strategy (CMA-ES). A modified subset simulation method is used for posterior reliability measurements of rare events. The framework accommodates scheduling of multiple physical model evaluations based on an adaptive load balancing library and shows excellent scalability. In addition to the software framework, we also provide guidelines as to the applicability and efficiency of Bayesian tools when applied to computationally demanding physical models. Theoretical and computational developments are demonstrated with applications drawn from molecular dynamics, structural dynamics and granular flow.

  15. Π4U: A high performance computing framework for Bayesian uncertainty quantification of complex models

    International Nuclear Information System (INIS)

    Hadjidoukas, P.E.; Angelikopoulos, P.; Papadimitriou, C.; Koumoutsakos, P.

    2015-01-01

    We present Π4U, 1 an extensible framework, for non-intrusive Bayesian Uncertainty Quantification and Propagation (UQ+P) of complex and computationally demanding physical models, that can exploit massively parallel computer architectures. The framework incorporates Laplace asymptotic approximations as well as stochastic algorithms, along with distributed numerical differentiation and task-based parallelism for heterogeneous clusters. Sampling is based on the Transitional Markov Chain Monte Carlo (TMCMC) algorithm and its variants. The optimization tasks associated with the asymptotic approximations are treated via the Covariance Matrix Adaptation Evolution Strategy (CMA-ES). A modified subset simulation method is used for posterior reliability measurements of rare events. The framework accommodates scheduling of multiple physical model evaluations based on an adaptive load balancing library and shows excellent scalability. In addition to the software framework, we also provide guidelines as to the applicability and efficiency of Bayesian tools when applied to computationally demanding physical models. Theoretical and computational developments are demonstrated with applications drawn from molecular dynamics, structural dynamics and granular flow

  16. Π4U: A high performance computing framework for Bayesian uncertainty quantification of complex models

    Energy Technology Data Exchange (ETDEWEB)

    Hadjidoukas, P.E.; Angelikopoulos, P. [Computational Science and Engineering Laboratory, ETH Zürich, CH-8092 (Switzerland); Papadimitriou, C. [Department of Mechanical Engineering, University of Thessaly, GR-38334 Volos (Greece); Koumoutsakos, P., E-mail: petros@ethz.ch [Computational Science and Engineering Laboratory, ETH Zürich, CH-8092 (Switzerland)

    2015-03-01

    We present Π4U,{sup 1} an extensible framework, for non-intrusive Bayesian Uncertainty Quantification and Propagation (UQ+P) of complex and computationally demanding physical models, that can exploit massively parallel computer architectures. The framework incorporates Laplace asymptotic approximations as well as stochastic algorithms, along with distributed numerical differentiation and task-based parallelism for heterogeneous clusters. Sampling is based on the Transitional Markov Chain Monte Carlo (TMCMC) algorithm and its variants. The optimization tasks associated with the asymptotic approximations are treated via the Covariance Matrix Adaptation Evolution Strategy (CMA-ES). A modified subset simulation method is used for posterior reliability measurements of rare events. The framework accommodates scheduling of multiple physical model evaluations based on an adaptive load balancing library and shows excellent scalability. In addition to the software framework, we also provide guidelines as to the applicability and efficiency of Bayesian tools when applied to computationally demanding physical models. Theoretical and computational developments are demonstrated with applications drawn from molecular dynamics, structural dynamics and granular flow.

  17. A Model-Driven Co-Design Framework for Fusing Control and Scheduling Viewpoints.

    Science.gov (United States)

    Sundharam, Sakthivel Manikandan; Navet, Nicolas; Altmeyer, Sebastian; Havet, Lionel

    2018-02-20

    Model-Driven Engineering (MDE) is widely applied in the industry to develop new software functions and integrate them into the existing run-time environment of a Cyber-Physical System (CPS). The design of a software component involves designers from various viewpoints such as control theory, software engineering, safety, etc. In practice, while a designer from one discipline focuses on the core aspects of his field (for instance, a control engineer concentrates on designing a stable controller), he neglects or considers less importantly the other engineering aspects (for instance, real-time software engineering or energy efficiency). This may cause some of the functional and non-functional requirements not to be met satisfactorily. In this work, we present a co-design framework based on timing tolerance contract to address such design gaps between control and real-time software engineering. The framework consists of three steps: controller design, verified by jitter margin analysis along with co-simulation, software design verified by a novel schedulability analysis, and the run-time verification by monitoring the execution of the models on target. This framework builds on CPAL (Cyber-Physical Action Language), an MDE design environment based on model-interpretation, which enforces a timing-realistic behavior in simulation through timing and scheduling annotations. The application of our framework is exemplified in the design of an automotive cruise control system.

  18. A Model-Driven Co-Design Framework for Fusing Control and Scheduling Viewpoints

    Science.gov (United States)

    Navet, Nicolas; Havet, Lionel

    2018-01-01

    Model-Driven Engineering (MDE) is widely applied in the industry to develop new software functions and integrate them into the existing run-time environment of a Cyber-Physical System (CPS). The design of a software component involves designers from various viewpoints such as control theory, software engineering, safety, etc. In practice, while a designer from one discipline focuses on the core aspects of his field (for instance, a control engineer concentrates on designing a stable controller), he neglects or considers less importantly the other engineering aspects (for instance, real-time software engineering or energy efficiency). This may cause some of the functional and non-functional requirements not to be met satisfactorily. In this work, we present a co-design framework based on timing tolerance contract to address such design gaps between control and real-time software engineering. The framework consists of three steps: controller design, verified by jitter margin analysis along with co-simulation, software design verified by a novel schedulability analysis, and the run-time verification by monitoring the execution of the models on target. This framework builds on CPAL (Cyber-Physical Action Language), an MDE design environment based on model-interpretation, which enforces a timing-realistic behavior in simulation through timing and scheduling annotations. The application of our framework is exemplified in the design of an automotive cruise control system. PMID:29461489

  19. A Model-Driven Co-Design Framework for Fusing Control and Scheduling Viewpoints

    Directory of Open Access Journals (Sweden)

    Sakthivel Manikandan Sundharam

    2018-02-01

    Full Text Available Model-Driven Engineering (MDE is widely applied in the industry to develop new software functions and integrate them into the existing run-time environment of a Cyber-Physical System (CPS. The design of a software component involves designers from various viewpoints such as control theory, software engineering, safety, etc. In practice, while a designer from one discipline focuses on the core aspects of his field (for instance, a control engineer concentrates on designing a stable controller, he neglects or considers less importantly the other engineering aspects (for instance, real-time software engineering or energy efficiency. This may cause some of the functional and non-functional requirements not to be met satisfactorily. In this work, we present a co-design framework based on timing tolerance contract to address such design gaps between control and real-time software engineering. The framework consists of three steps: controller design, verified by jitter margin analysis along with co-simulation, software design verified by a novel schedulability analysis, and the run-time verification by monitoring the execution of the models on target. This framework builds on CPAL (Cyber-Physical Action Language, an MDE design environment based on model-interpretation, which enforces a timing-realistic behavior in simulation through timing and scheduling annotations. The application of our framework is exemplified in the design of an automotive cruise control system.

  20. Family Environment and Childhood Obesity: A New Framework with Structural Equation Modeling

    Directory of Open Access Journals (Sweden)

    Hui Huang

    2017-02-01

    Full Text Available The main purpose of the current article is to introduce a framework of the complexity of childhood obesity based on the family environment. A conceptual model that quantifies the relationships and interactions among parental socioeconomic status, family food security level, child’s food intake and certain aspects of parental feeding behaviour is presented using the structural equation modeling (SEM concept. Structural models are analysed in terms of the direct and indirect connections among latent and measurement variables that lead to the child weight indicator. To illustrate the accuracy, fit, reliability and validity of the introduced framework, real data collected from 630 families from Urumqi (Xinjiang, China were considered. The framework includes two categories of data comprising the normal body mass index (BMI range and obesity data. The comparison analysis between two models provides some evidence that in obesity modeling, obesity data must be extracted from the dataset and analysis must be done separately from the normal BMI range. This study may be helpful for researchers interested in childhood obesity modeling based on family environment.

  1. Toward a consistent modeling framework to assess multi-sectoral climate impacts.

    Science.gov (United States)

    Monier, Erwan; Paltsev, Sergey; Sokolov, Andrei; Chen, Y-H Henry; Gao, Xiang; Ejaz, Qudsia; Couzo, Evan; Schlosser, C Adam; Dutkiewicz, Stephanie; Fant, Charles; Scott, Jeffery; Kicklighter, David; Morris, Jennifer; Jacoby, Henry; Prinn, Ronald; Haigh, Martin

    2018-02-13

    Efforts to estimate the physical and economic impacts of future climate change face substantial challenges. To enrich the currently popular approaches to impact analysis-which involve evaluation of a damage function or multi-model comparisons based on a limited number of standardized scenarios-we propose integrating a geospatially resolved physical representation of impacts into a coupled human-Earth system modeling framework. Large internationally coordinated exercises cannot easily respond to new policy targets and the implementation of standard scenarios across models, institutions and research communities can yield inconsistent estimates. Here, we argue for a shift toward the use of a self-consistent integrated modeling framework to assess climate impacts, and discuss ways the integrated assessment modeling community can move in this direction. We then demonstrate the capabilities of such a modeling framework by conducting a multi-sectoral assessment of climate impacts under a range of consistent and integrated economic and climate scenarios that are responsive to new policies and business expectations.

  2. A hydroeconomic modeling framework for optimal integrated management of forest and water

    Science.gov (United States)

    Garcia-Prats, Alberto; del Campo, Antonio D.; Pulido-Velazquez, Manuel

    2016-10-01

    Forests play a determinant role in the hydrologic cycle, with water being the most important ecosystem service they provide in semiarid regions. However, this contribution is usually neither quantified nor explicitly valued. The aim of this study is to develop a novel hydroeconomic modeling framework for assessing and designing the optimal integrated forest and water management for forested catchments. The optimization model explicitly integrates changes in water yield in the stands (increase in groundwater recharge) induced by forest management and the value of the additional water provided to the system. The model determines the optimal schedule of silvicultural interventions in the stands of the catchment in order to maximize the total net benefit in the system. Canopy cover and biomass evolution over time were simulated using growth and yield allometric equations specific for the species in Mediterranean conditions. Silvicultural operation costs according to stand density and canopy cover were modeled using local cost databases. Groundwater recharge was simulated using HYDRUS, calibrated and validated with data from the experimental plots. In order to illustrate the presented modeling framework, a case study was carried out in a planted pine forest (Pinus halepensis Mill.) located in south-western Valencia province (Spain). The optimized scenario increased groundwater recharge. This novel modeling framework can be used in the design of a "payment for environmental services" scheme in which water beneficiaries could contribute to fund and promote efficient forest management operations.

  3. A discrete-time Bayesian network reliability modeling and analysis framework

    International Nuclear Information System (INIS)

    Boudali, H.; Dugan, J.B.

    2005-01-01

    Dependability tools are becoming an indispensable tool for modeling and analyzing (critical) systems. However the growing complexity of such systems calls for increasing sophistication of these tools. Dependability tools need to not only capture the complex dynamic behavior of the system components, but they must be also easy to use, intuitive, and computationally efficient. In general, current tools have a number of shortcomings including lack of modeling power, incapacity to efficiently handle general component failure distributions, and ineffectiveness in solving large models that exhibit complex dependencies between their components. We propose a novel reliability modeling and analysis framework based on the Bayesian network (BN) formalism. The overall approach is to investigate timed Bayesian networks and to find a suitable reliability framework for dynamic systems. We have applied our methodology to two example systems and preliminary results are promising. We have defined a discrete-time BN reliability formalism and demonstrated its capabilities from a modeling and analysis point of view. This research shows that a BN based reliability formalism is a powerful potential solution to modeling and analyzing various kinds of system components behaviors and interactions. Moreover, being based on the BN formalism, the framework is easy to use and intuitive for non-experts, and provides a basis for more advanced and useful analyses such as system diagnosis

  4. Patient-reported outcomes in insomnia: development of a conceptual framework and endpoint model.

    Science.gov (United States)

    Kleinman, Leah; Buysse, Daniel J; Harding, Gale; Lichstein, Kenneth; Kalsekar, Anupama; Roth, Thomas

    2013-01-01

    This article describes qualitative research conducted with patients with clinical diagnoses of insomnia and focuses on the development of a conceptual framework and endpoint model that identifies a hierarchy and interrelationships of potential outcomes in insomnia research. Focus groups were convened to discuss how patients experience insomnia and to generate items for patient-reported questionnaires on insomnia and associated daytime consequences. Results for the focus group produced two conceptual frameworks: one for sleep and one for daytime impairment. Each conceptual framework consists of hypothesized domains and items in each domain based on patient language taken from the focus group. These item pools may ultimately serve as a basis to develop new questionnaires to assess insomnia.

  5. More performance results and implementation of an object oriented track reconstruction model in different OO frameworks

    International Nuclear Information System (INIS)

    Gaines, Irwin; Qian Sijin

    2001-01-01

    This is an update of the report about an Object Oriented (OO) track reconstruction model, which was presented in the previous AIHENP'99 at Crete, Greece. The OO model for the Kalman filtering method has been designed for high energy physics experiments at high luminosity hadron colliders. It has been coded in the C++ programming language and successfully implemented into a few different OO computing environments of the CMS and ATLAS experiments at the future Large Hadron Collider at CERN. We shall report: (1) more performance result: (2) implementing the OO model into the new SW OO framework 'Athena' of ATLAS experiment and some upgrades of the OO model itself

  6. Survey of credit risk models in relation to capital adequacy framework for financial institutions

    Directory of Open Access Journals (Sweden)

    Poomjai Nacaskul

    2016-12-01

    Full Text Available This article (i iterates what is meant by credit risks and the mathematical-statistical modelling thereof, (ii elaborates the conceptual and technical links between credit risk modelling and capital adequacy framework for financial institutions, particularly as per the New Capital Accord (Basel II’s Internal Ratings-Based (IRB approach, (iii proffer a simple and intuitive taxonomy on contemporary credit risk modelling methodologies, and (iv discuses in some details a number of key models pertinent, in various stages of development, to various application areas in the banking and financial sector.

  7. Uncertainty Analysis Framework - Hanford Site-Wide Groundwater Flow and Transport Model

    Energy Technology Data Exchange (ETDEWEB)

    Cole, Charles R.; Bergeron, Marcel P.; Murray, Christopher J.; Thorne, Paul D.; Wurstner, Signe K.; Rogers, Phillip M.

    2001-11-09

    Pacific Northwest National Laboratory (PNNL) embarked on a new initiative to strengthen the technical defensibility of the predictions being made with a site-wide groundwater flow and transport model at the U.S. Department of Energy Hanford Site in southeastern Washington State. In FY 2000, the focus of the initiative was on the characterization of major uncertainties in the current conceptual model that would affect model predictions. The long-term goals of the initiative are the development and implementation of an uncertainty estimation methodology in future assessments and analyses using the site-wide model. This report focuses on the development and implementation of an uncertainty analysis framework.

  8. A general science-based framework for dynamical spatio-temporal models

    Science.gov (United States)

    Wikle, C.K.; Hooten, M.B.

    2010-01-01

    Spatio-temporal statistical models are increasingly being used across a wide variety of scientific disciplines to describe and predict spatially-explicit processes that evolve over time. Correspondingly, in recent years there has been a significant amount of research on new statistical methodology for such models. Although descriptive models that approach the problem from the second-order (covariance) perspective are important, and innovative work is being done in this regard, many real-world processes are dynamic, and it can be more efficient in some cases to characterize the associated spatio-temporal dependence by the use of dynamical models. The chief challenge with the specification of such dynamical models has been related to the curse of dimensionality. Even in fairly simple linear, first-order Markovian, Gaussian error settings, statistical models are often over parameterized. Hierarchical models have proven invaluable in their ability to deal to some extent with this issue by allowing dependency among groups of parameters. In addition, this framework has allowed for the specification of science based parameterizations (and associated prior distributions) in which classes of deterministic dynamical models (e. g., partial differential equations (PDEs), integro-difference equations (IDEs), matrix models, and agent-based models) are used to guide specific parameterizations. Most of the focus for the application of such models in statistics has been in the linear case. The problems mentioned above with linear dynamic models are compounded in the case of nonlinear models. In this sense, the need for coherent and sensible model parameterizations is not only helpful, it is essential. Here, we present an overview of a framework for incorporating scientific information to motivate dynamical spatio-temporal models. First, we illustrate the methodology with the linear case. We then develop a general nonlinear spatio-temporal framework that we call general quadratic

  9. Theoretical model estimation of guest diffusion in Metal-Organic Frameworks (MOFs)

    KAUST Repository

    Zheng, Bin

    2015-08-11

    Characterizing molecule diffusion in nanoporous matrices is critical to understanding the novel chemical and physical properties of metal-organic frameworks (MOFs). In this paper, we developed a theoretical model to fastly and accurately compute the diffusion rate of guest molecules in a zeolitic imidazolate framework-8 (ZIF-8). The ideal gas or equilibrium solution diffusion model was modified to contain the effect of periodical media via introducing the possibility of guests passing through the framework gate. The only input in our model is the energy barrier of guests passing through the MOF’s gate. Molecular dynamics (MD) methods were employed to gather the guest density profile, which then was used to deduce the energy barrier values. This produced reliable results that require a simulation time of 5 picoseconds, which is much shorter when using pure MD methods (in the billisecond scale) . Also, we used density functional theory (DFT) methods to obtain the energy profile of guests passing through gates, as this does not require specification of a force field for the MOF degrees of freedom. In the DFT calculation, we only considered one gate of MOFs each time; as this greatly reduced the computational cost. Based on the obtained energy barrier values we computed the diffusion rate of alkane and alcohol in ZIF-8 using our model, which was in good agreement with experimental test results and the calculation values from standard MD model. Our model shows the advantage of obtaining accurate diffusion rates for guests in MOFs for a lower computational cost and shorter calculation time. Thus, our analytic model calculation is especially attractive for high-throughput computational screening of the dynamic performance of guests in a framework.

  10. Improved hidden Markov model for nosocomial infections.

    Science.gov (United States)

    Khader, Karim; Leecaster, Molly; Greene, Tom; Samore, Matthew; Thomas, Alun

    2014-12-01

    We propose a novel hidden Markov model (HMM) for parameter estimation in hospital transmission models, and show that commonly made simplifying assumptions can lead to severe model misspecification and poor parameter estimates. A standard HMM that embodies two commonly made simplifying assumptions, namely a fixed patient count and binomially distributed detections is compared with a new alternative HMM that does not require these simplifying assumptions. Using simulated data, we demonstrate how each of the simplifying assumptions used by the standard model leads to model misspecification, whereas the alternative model results in accurate parameter estimates. © The Authors 2013. Published by Oxford University Press on behalf of the Institute of Mathematics and its Applications. All rights reserved.

  11. A modelling framework for reclamation planning of oil sands mines in northern Alberta

    International Nuclear Information System (INIS)

    Shaw, R.D.; Hamilton, H.R.; MacKinnon, M.D.; Gulley, J.R.

    1995-01-01

    The Reclamation Landscape Model Development Project was initiated in 1991 to develop a modelling framework to assist in oil sands mine reclamation planning. The initial year focused on developing a suite of computer simulation models suitable for evaluating hydrodynamic, water quality and biological conditions of fine-tails bottom lakes that would be capped with a layer of fresh water. That modelling framework was further refined in 1992--93 by incorporating probabilistic capabilities, developing of secondary production and food-chain components, and implementing of a model to simulate contaminant concentrations in the Athabasca River. In 1993--94 the emphasis expanded from a focus solely on developing tools for evaluating wet landscape options to developing an integrated modelling framework capable of evaluating both wet and dry landscape reclamation options. Major components completed in 1993--94 included development of a dry landscape module that includes surface runoff, groundwater seepage, air vapor and bioaccumulation components, a wetlands module to assist in evaluating treatment potential and for optimizing design of wetlands units, and a risk analysis module for quantifying risks to human health and ecological receptors. The Reclamation Landscape Model is a compartment modelling system that consists of a number of stand-alone computer programs that can be run in conjunction with one another or separately. The computer programs that simulate contaminant-fate processes range from simple empirical models to complex, mechanistic, three-dimensional, dynamic models, which are capable of predicting contaminant concentrations in water, soil, air and biota for a wide range of reclamation landscape units. Most of the component models have probabilistic capabilities

  12. Land Surface Verification Toolkit (LVT) - A Generalized Framework for Land Surface Model Evaluation

    Science.gov (United States)

    Kumar, Sujay V.; Peters-Lidard, Christa D.; Santanello, Joseph; Harrison, Ken; Liu, Yuqiong; Shaw, Michael

    2011-01-01

    Model evaluation and verification are key in improving the usage and applicability of simulation models for real-world applications. In this article, the development and capabilities of a formal system for land surface model evaluation called the Land surface Verification Toolkit (LVT) is described. LVT is designed to provide an integrated environment for systematic land model evaluation and facilitates a range of verification approaches and analysis capabilities. LVT operates across multiple temporal and spatial scales and employs a large suite of in-situ, remotely sensed and other model and reanalysis datasets in their native formats. In addition to the traditional accuracy-based measures, LVT also includes uncertainty and ensemble diagnostics, information theory measures, spatial similarity metrics and scale decomposition techniques that provide novel ways for performing diagnostic model evaluations. Though LVT was originally designed to support the land surface modeling and data assimilation framework known as the Land Information System (LIS), it also supports hydrological data products from other, non-LIS environments. In addition, the analysis of diagnostics from various computational subsystems of LIS including data assimilation, optimization and uncertainty estimation are supported within LVT. Together, LIS and LVT provide a robust end-to-end environment for enabling the concepts of model data fusion for hydrological applications. The evolving capabilities of LVT framework are expected to facilitate rapid model evaluation efforts and aid the definition and refinement of formal evaluation procedures for the land surface modeling community.

  13. Land surface Verification Toolkit (LVT) - a generalized framework for land surface model evaluation

    Science.gov (United States)

    Kumar, S. V.; Peters-Lidard, C. D.; Santanello, J.; Harrison, K.; Liu, Y.; Shaw, M.

    2012-06-01

    Model evaluation and verification are key in improving the usage and applicability of simulation models for real-world applications. In this article, the development and capabilities of a formal system for land surface model evaluation called the Land surface Verification Toolkit (LVT) is described. LVT is designed to provide an integrated environment for systematic land model evaluation and facilitates a range of verification approaches and analysis capabilities. LVT operates across multiple temporal and spatial scales and employs a large suite of in-situ, remotely sensed and other model and reanalysis datasets in their native formats. In addition to the traditional accuracy-based measures, LVT also includes uncertainty and ensemble diagnostics, information theory measures, spatial similarity metrics and scale decomposition techniques that provide novel ways for performing diagnostic model evaluations. Though LVT was originally designed to support the land surface modeling and data assimilation framework known as the Land Information System (LIS), it supports hydrological data products from non-LIS environments as well. In addition, the analysis of diagnostics from various computational subsystems of LIS including data assimilation, optimization and uncertainty estimation are supported within LVT. Together, LIS and LVT provide a robust end-to-end environment for enabling the concepts of model data fusion for hydrological applications. The evolving capabilities of LVT framework are expected to facilitate rapid model evaluation efforts and aid the definition and refinement of formal evaluation procedures for the land surface modeling community.

  14. Designing the Business Models for Circular Economy—Towards the Conceptual Framework

    Directory of Open Access Journals (Sweden)

    Mateusz Lewandowski

    2016-01-01

    Full Text Available Switching from the current linear model of economy to a circular one has recently attracted increased attention from major global companies e.g., Google, Unilever, Renault, and policymakers attending the World Economic Forum. The reasons for this are the huge financial, social and environmental benefits. However, the global shift from one model of economy to another also concerns smaller companies on a micro-level. Thus, comprehensive knowledge on designing circular business models is needed to stimulate and foster implementation of the circular economy. Existing business models for the circular economy have limited transferability and there is no comprehensive framework supporting every kind of company in designing a circular business model. This study employs a literature review to identify and classify the circular economy characteristics according to a business model structure. The investigation in the eight sub-domains of research on circular business models was used to redefine the components of the business model canvas in the context of the circular economy. Two new components—the take-back system and adoption factors—have been identified, thereby leading to the conceptualization of an extended framework for the circular business model canvas. Additionally, the triple fit challenge has been recognized as an enabler of the transition towards a circular business model. Some directions for further research have been outlined, as well.

  15. On New Cautious Structural Reliability Models in the Framework of imprecise Probabilities

    DEFF Research Database (Denmark)

    Utkin, Lev V.; Kozine, Igor

    2010-01-01

    models and gen-eralizing conventional ones to imprecise probabili-ties. The theoretical setup employed for this purpose is imprecise statistical reasoning (Walley 1991), whose general framework is provided by upper and lower previsions (expectations). The appeal of this theory is its ability to capture......Uncertainty of parameters in engineering design has been modeled in different frameworks such as inter-val analysis, fuzzy set and possibility theories, ran-dom set theory and imprecise probability theory. The authors of this paper for many years have been de-veloping new imprecise reliability...... both aleatory (stochas-tic) and epistemic uncertainty and the flexibility with which information can be represented. The previous research of the authors related to generalizing structural reliability models to impre-cise statistical measures is summarized in Utkin & Kozine (2002) and Utkin (2004...

  16. A Framework for Uplink Intercell Interference Modeling with Channel-Based Scheduling

    KAUST Repository

    Tabassum, Hina

    2012-12-29

    This paper presents a novel framework for modeling the uplink intercell interference(ICI) in a multiuser cellular network. The proposed framework assists in quantifying the impact of various fading channel models and state-of-the-art scheduling schemes on the uplink ICI. Firstly, we derive a semianalytical expression for the distribution of the location of the scheduled user in a given cell considering a wide range of scheduling schemes. Based on this, we derive the distribution and moment generating function (MGF) of the uplink ICI considering a single interfering cell. Consequently, we determine the MGF of the cumulative ICI observed from all interfering cells and derive explicit MGF expressions for three typical fading models. Finally, we utilize the obtained expressions to evaluate important network performance metrics such as the outage probability, ergodic capacity, and average fairness numerically. Monte-Carlo simulation results are provided to demonstrate the efficacy of the derived analytical expressions.

  17. Model-based Computer Aided Framework for Design of Process Monitoring and Analysis Systems

    DEFF Research Database (Denmark)

    Singh, Ravendra; Gernaey, Krist; Gani, Rafiqul

    2009-01-01

    In the manufacturing industry, for example, the pharmaceutical industry, a thorough understanding of the process is necessary in addition to a properly designed monitoring and analysis system (PAT system) to consistently obtain the desired end-product properties. A model-based computer....... The knowledge base provides the necessary information/data during the design of the PAT system while the model library generates additional or missing data needed for design and analysis. Optimization of the PAT system design is achieved in terms of product data analysis time and/or cost of monitoring equipment......-aided framework including the methods and tools through which the design of monitoring and analysis systems for product quality control can be generated, analyzed and/or validated, has been developed. Two important supporting tools developed as part of the framework are a knowledge base and a model library...

  18. Development and Implementation of a Telecommuting Evaluation Framework, and Modeling the Executive Telecommuting Adoption Process

    Science.gov (United States)

    Vora, V. P.; Mahmassani, H. S.

    2002-02-01

    This work proposes and implements a comprehensive evaluation framework to document the telecommuter, organizational, and societal impacts of telecommuting through telecommuting programs. Evaluation processes and materials within the outlined framework are also proposed and implemented. As the first component of the evaluation process, the executive survey is administered within a public sector agency. The survey data is examined through exploratory analysis and is compared to a previous survey of private sector executives. The ordinal probit, dynamic probit, and dynamic generalized ordinal probit (DGOP) models of telecommuting adoption are calibrated to identify factors which significantly influence executive adoption preferences and to test the robustness of such factors. The public sector DGOP model of executive willingness to support telecommuting under different program scenarios is compared with an equivalent private sector DGOP model. Through the telecommuting program, a case study of telecommuting travel impacts is performed to further substantiate research.

  19. A framework for treating DSM-5 alternative model for personality disorder features.

    Science.gov (United States)

    Hopwood, Christopher J

    2018-04-15

    Despite its demonstrated empirical superiority over the DSM-5 Section 2 categorical model of personality disorders for organizing the features of personality pathology, limitations remain with regard to the translation of the DSM-5 Section 3 alternative model of personality disorders (AMPD) to clinical practice. The goal of this paper is to outline a general and preliminary framework for approaching treatment from the perspective of the AMPD. Specific techniques are discussed for the assessment and treatment of both Criterion A personality dysfunction and Criterion B maladaptive traits. A concise and step-by-step model is presented for clinical decision making with the AMPD, in the hopes of offering clinicians a framework for treating personality pathology and promoting further research on the clinical utility of the AMPD. Copyright © 2018 John Wiley & Sons, Ltd. Copyright © 2018 John Wiley & Sons, Ltd.

  20. Toward University Modeling Instruction—Biology: Adapting Curricular Frameworks from Physics to Biology

    Science.gov (United States)

    Manthey, Seth; Brewe, Eric

    2013-01-01

    University Modeling Instruction (UMI) is an approach to curriculum and pedagogy that focuses instruction on engaging students in building, validating, and deploying scientific models. Modeling Instruction has been successfully implemented in both high school and university physics courses. Studies within the physics education research (PER) community have identified UMI's positive impacts on learning gains, equity, attitudinal shifts, and self-efficacy. While the success of this pedagogical approach has been recognized within the physics community, the use of models and modeling practices is still being developed for biology. Drawing from the existing research on UMI in physics, we describe the theoretical foundations of UMI and how UMI can be adapted to include an emphasis on models and modeling for undergraduate introductory biology courses. In particular, we discuss our ongoing work to develop a framework for the first semester of a two-semester introductory biology course sequence by identifying the essential basic models for an introductory biology course sequence. PMID:23737628

  1. Toward university modeling instruction--biology: adapting curricular frameworks from physics to biology.

    Science.gov (United States)

    Manthey, Seth; Brewe, Eric

    2013-06-01

    University Modeling Instruction (UMI) is an approach to curriculum and pedagogy that focuses instruction on engaging students in building, validating, and deploying scientific models. Modeling Instruction has been successfully implemented in both high school and university physics courses. Studies within the physics education research (PER) community have identified UMI's positive impacts on learning gains, equity, attitudinal shifts, and self-efficacy. While the success of this pedagogical approach has been recognized within the physics community, the use of models and modeling practices is still being developed for biology. Drawing from the existing research on UMI in physics, we describe the theoretical foundations of UMI and how UMI can be adapted to include an emphasis on models and modeling for undergraduate introductory biology courses. In particular, we discuss our ongoing work to develop a framework for the first semester of a two-semester introductory biology course sequence by identifying the essential basic models for an introductory biology course sequence.

  2. A framework for modeling scenario-based barrier island storm impacts

    Science.gov (United States)

    Mickey, Rangley; Long, Joseph W.; Dalyander, P. Soupy; Plant, Nathaniel G.; Thompson, David M.

    2018-01-01

    Methods for investigating the vulnerability of existing or proposed coastal features to storm impacts often rely on simplified parametric models or one-dimensional process-based modeling studies that focus on changes to a profile across a dune or barrier island. These simple studies tend to neglect the impacts to curvilinear or alongshore varying island planforms, influence of non-uniform nearshore hydrodynamics and sediment transport, irregular morphology of the offshore bathymetry, and impacts from low magnitude wave events (e.g. cold fronts). Presented here is a framework for simulating regionally specific, low and high magnitude scenario-based storm impacts to assess the alongshore variable vulnerabilities of a coastal feature. Storm scenarios based on historic hydrodynamic conditions were derived and simulated using the process-based morphologic evolution model XBeach. Model results show that the scenarios predicted similar patterns of erosion and overwash when compared to observed qualitative morphologic changes from recent storm events that were not included in the dataset used to build the scenarios. The framework model simulations were capable of predicting specific areas of vulnerability in the existing feature and the results illustrate how this storm vulnerability simulation framework could be used as a tool to help inform the decision-making process for scientists, engineers, and stakeholders involved in coastal zone management or restoration projects.

  3. VHDL-AMS Simulation Framework for Molecular-FET Device-to-Circuit Modeling and Design

    Directory of Open Access Journals (Sweden)

    Mariagrazia Graziano

    2018-01-01

    Full Text Available We concentrate on Molecular-FET as a device and present a new modular framework based on VHDL-AMS. We have implemented different Molecular-FET models within the framework. The framework allows comparison between the models in terms of the capability to calculate accurate I-V characteristics. It also provides the option to analyze the impact of Molecular-FET and its implementation in the circuit with the extension of its use in an architecture based on the crossbar configuration. This analysis evidences the effect of choices of technological parameters, the ability of models to capture the impact of physical quantities, and the importance of considering defects at circuit fabrication level. The comparison tackles the computational efforts of different models and techniques and discusses the trade-off between accuracy and performance as a function of the circuit analysis final requirements. We prove this methodology using three different models and test them on a 16-bit tree adder included in Pentium 4 that, to the best of our knowledge, is the biggest circuits based on molecular device ever designed and analyzed.

  4. Nursing management of sensory overload in psychiatry – Theoretical densification and modification of the framework model

    Science.gov (United States)

    Scheydt, Stefan; Needham, Ian; Behrens, Johann

    2017-01-01

    Background: Within the scope of the research project on the subjects of sensory overload and stimulus regulation, a theoretical framework model of the nursing care of patients with sensory overload in psychiatry was developed. In a second step, this theoretical model should now be theoretically compressed and, if necessary, modified. Aim: Empirical verification as well as modification, enhancement and theoretical densification of the framework model of nursing care of patients with sensory overload in psychiatry. Method: Analysis of 8 expert interviews by summarizing and structuring content analysis methods based on Meuser and Nagel (2009) as well as Mayring (2010). Results: The developed framework model (Scheydt et al., 2016b) could be empirically verified, theoretically densificated and extended by one category (perception modulation). Thus, four categories of nursing care of patients with sensory overload can be described in inpatient psychiatry: removal from stimuli, modulation of environmental factors, perceptual modulation as well as help somebody to help him- or herself / coping support. Conclusions: Based on the methodological approach, a relatively well-saturated, credible conceptualization of a theoretical model for the description of the nursing care of patients with sensory overload in stationary psychiatry could be worked out. In further steps, these measures have to be further developed, implemented and evaluated regarding to their efficacy.

  5. An ice sheet model validation framework for the Greenland ice sheet

    Science.gov (United States)

    Price, Stephen F.; Hoffman, Matthew J.; Bonin, Jennifer A.; Howat, Ian M.; Neumann, Thomas; Saba, Jack; Tezaur, Irina; Guerber, Jeffrey; Chambers, Don P.; Evans, Katherine J.; Kennedy, Joseph H.; Lenaerts, Jan; Lipscomb, William H.; Perego, Mauro; Salinger, Andrew G.; Tuminaro, Raymond S.; van den Broeke, Michiel R.; Nowicki, Sophie M. J.

    2017-01-01

    We propose a new ice sheet model validation framework - the Cryospheric Model Comparison Tool (CmCt) - that takes advantage of ice sheet altimetry and gravimetry observations collected over the past several decades and is applied here to modeling of the Greenland ice sheet. We use realistic simulations performed with the Community Ice Sheet Model (CISM) along with two idealized, non-dynamic models to demonstrate the framework and its use. Dynamic simulations with CISM are forced from 1991 to 2013, using combinations of reanalysis-based surface mass balance and observations of outlet glacier flux change. We propose and demonstrate qualitative and quantitative metrics for use in evaluating the different model simulations against the observations. We find that the altimetry observations used here are largely ambiguous in terms of their ability to distinguish one simulation from another. Based on basin-scale and whole-ice-sheet-scale metrics, we find that simulations using both idealized conceptual models and dynamic, numerical models provide an equally reasonable representation of the ice sheet surface (mean elevation differences of framework demonstrates that our proposed metrics can distinguish relatively better from relatively worse simulations and that dynamic ice sheet models, when appropriately initialized and forced with the right boundary conditions, demonstrate a predictive skill with respect to observed dynamic changes that have occurred on Greenland over the past few decades. An extensible design will allow for continued use of the CmCt as future altimetry, gravimetry, and other remotely sensed data become available for use in ice sheet model validation.

  6. An analytical framework to assist decision makers in the use of forest ecosystem model predictions

    Science.gov (United States)

    Larocque, Guy R.; Bhatti, Jagtar S.; Ascough, J.C.; Liu, J.; Luckai, N.; Mailly, D.; Archambault, L.; Gordon, Andrew M.

    2011-01-01

    The predictions from most forest ecosystem models originate from deterministic simulations. However, few evaluation exercises for model outputs are performed by either model developers or users. This issue has important consequences for decision makers using these models to develop natural resource management policies, as they cannot evaluate the extent to which predictions stemming from the simulation of alternative management scenarios may result in significant environmental or economic differences. Various numerical methods, such as sensitivity/uncertainty analyses, or bootstrap methods, may be used to evaluate models and the errors associated with their outputs. However, the application of each of these methods carries unique challenges which decision makers do not necessarily understand; guidance is required when interpreting the output generated from each model. This paper proposes a decision flow chart in the form of an analytical framework to help decision makers apply, in an orderly fashion, different steps involved in examining the model outputs. The analytical framework is discussed with regard to the definition of problems and objectives and includes the following topics: model selection, identification of alternatives, modelling tasks and selecting alternatives for developing policy or implementing management scenarios. Its application is illustrated using an on-going exercise in developing silvicultural guidelines for a forest management enterprise in Ontario, Canada.

  7. A Stochastic Hybrid Systems framework for analysis of Markov reward models

    International Nuclear Information System (INIS)

    Dhople, S.V.; DeVille, L.; Domínguez-García, A.D.

    2014-01-01

    In this paper, we propose a framework to analyze Markov reward models, which are commonly used in system performability analysis. The framework builds on a set of analytical tools developed for a class of stochastic processes referred to as Stochastic Hybrid Systems (SHS). The state space of an SHS is comprised of: (i) a discrete state that describes the possible configurations/modes that a system can adopt, which includes the nominal (non-faulty) operational mode, but also those operational modes that arise due to component faults, and (ii) a continuous state that describes the reward. Discrete state transitions are stochastic, and governed by transition rates that are (in general) a function of time and the value of the continuous state. The evolution of the continuous state is described by a stochastic differential equation and reward measures are defined as functions of the continuous state. Additionally, each transition is associated with a reset map that defines the mapping between the pre- and post-transition values of the discrete and continuous states; these mappings enable the definition of impulses and losses in the reward. The proposed SHS-based framework unifies the analysis of a variety of previously studied reward models. We illustrate the application of the framework to performability analysis via analytical and numerical examples

  8. Activity Recognition Using Hybrid Generative/Discriminative Models on Home Environments Using Binary Sensors

    Directory of Open Access Journals (Sweden)

    Araceli Sanchis

    2013-04-01

    Full Text Available Activities of daily living are good indicators of elderly health status, and activity recognition in smart environments is a well-known problem that has been previously addressed by several studies. In this paper, we describe the use of two powerful machine learning schemes, ANN (Artificial Neural Network and SVM (Support Vector Machines, within the framework of HMM (Hidden Markov Model in order to tackle the task of activity recognition in a home setting. The output scores of the discriminative models, after processing, are used as observation probabilities of the hybrid approach. We evaluate our approach by comparing these hybrid models with other classical activity recognition methods using five real datasets. We show how the hybrid models achieve significantly better recognition performance, with significance level p < 0:05, proving that the hybrid approach is better suited for the addressed domain.

  9. A framework for implementation of organ effect models in TOPAS with benchmarks extended to proton therapy

    International Nuclear Information System (INIS)

    Ramos-Méndez, J; Faddegon, B; Perl, J; Schümann, J; Paganetti, H; Shin, J

    2015-01-01

    The aim of this work was to develop a framework for modeling organ effects within TOPAS (TOol for PArticle Simulation), a wrapper of the Geant4 Monte Carlo toolkit that facilitates particle therapy simulation. The DICOM interface for TOPAS was extended to permit contour input, used to assign voxels to organs. The following dose response models were implemented: The Lyman–Kutcher–Burman model, the critical element model, the population based critical volume model, the parallel-serial model, a sigmoid-based model of Niemierko for normal tissue complication probability and tumor control probability (TCP), and a Poisson-based model for TCP. The framework allows easy manipulation of the parameters of these models and the implementation of other models.As part of the verification, results for the parallel-serial and Poisson model for x-ray irradiation of a water phantom were compared to data from the AAPM Task Group 166. When using the task group dose-volume histograms (DVHs), results were found to be sensitive to the number of points in the DVH, with differences up to 2.4%, some of which are attributable to differences between the implemented models. New results are given with the point spacing specified. When using Monte Carlo calculations with TOPAS, despite the relatively good match to the published DVH’s, differences up to 9% were found for the parallel-serial model (for a maximum DVH difference of 2%) and up to 0.5% for the Poisson model (for a maximum DVH difference of 0.5%). However, differences of 74.5% (in Rectangle1), 34.8% (in PTV) and 52.1% (in Triangle) for the critical element, critical volume and the sigmoid-based models were found respectively.We propose a new benchmark for verification of organ effect models in proton therapy. The benchmark consists of customized structures in the spread out Bragg peak plateau, normal tissue, tumor, penumbra and in the distal region. The DVH’s, DVH point spacing, and results of the organ effect models are

  10. Coding with partially hidden Markov models

    DEFF Research Database (Denmark)

    Forchhammer, Søren; Rissanen, J.

    1995-01-01

    Partially hidden Markov models (PHMM) are introduced. They are a variation of the hidden Markov models (HMM) combining the power of explicit conditioning on past observations and the power of using hidden states. (P)HMM may be combined with arithmetic coding for lossless data compression. A general...... 2-part coding scheme for given model order but unknown parameters based on PHMM is presented. A forward-backward reestimation of parameters with a redefined backward variable is given for these models and used for estimating the unknown parameters. Proof of convergence of this reestimation is given....... The PHMM structure and the conditions of the convergence proof allows for application of the PHMM to image coding. Relations between the PHMM and hidden Markov models (HMM) are treated. Results of coding bi-level images with the PHMM coding scheme is given. The results indicate that the PHMM can adapt...

  11. A coupled modeling framework for sustainable watershed management in transboundary river basins

    Science.gov (United States)

    Furqan Khan, Hassaan; Yang, Y. C. Ethan; Xie, Hua; Ringler, Claudia

    2017-12-01

    There is a growing recognition among water resource managers that sustainable watershed management needs to not only account for the diverse ways humans benefit from the environment, but also incorporate the impact of human actions on the natural system. Coupled natural-human system modeling through explicit modeling of both natural and human behavior can help reveal the reciprocal interactions and co-evolution of the natural and human systems. This study develops a spatially scalable, generalized agent-based modeling (ABM) framework consisting of a process-based semi-distributed hydrologic model (SWAT) and a decentralized water system model to simulate the impacts of water resource management decisions that affect the food-water-energy-environment (FWEE) nexus at a watershed scale. Agents within a river basin are geographically delineated based on both political and watershed boundaries and represent key stakeholders of ecosystem services. Agents decide about the priority across three primary water uses: food production, hydropower generation and ecosystem health within their geographical domains. Agents interact with the environment (streamflow) through the SWAT model and interact with other agents through a parameter representing willingness to cooperate. The innovative two-way coupling between the water system model and SWAT enables this framework to fully explore the feedback of human decisions on the environmental dynamics and vice versa. To support non-technical stakeholder interactions, a web-based user interface has been developed that allows for role-play and participatory modeling. The generalized ABM framework is also tested in two key transboundary river basins, the Mekong River basin in Southeast Asia and the Niger River basin in West Africa, where water uses for ecosystem health compete with growing human demands on food and energy resources. We present modeling results for crop production, energy generation and violation of eco

  12. A coupled modeling framework for sustainable watershed management in transboundary river basins

    Directory of Open Access Journals (Sweden)

    H. F. Khan

    2017-12-01

    Full Text Available There is a growing recognition among water resource managers that sustainable watershed management needs to not only account for the diverse ways humans benefit from the environment, but also incorporate the impact of human actions on the natural system. Coupled natural–human system modeling through explicit modeling of both natural and human behavior can help reveal the reciprocal interactions and co-evolution of the natural and human systems. This study develops a spatially scalable, generalized agent-based modeling (ABM framework consisting of a process-based semi-distributed hydrologic model (SWAT and a decentralized water system model to simulate the impacts of water resource management decisions that affect the food–water–energy–environment (FWEE nexus at a watershed scale. Agents within a river basin are geographically delineated based on both political and watershed boundaries and represent key stakeholders of ecosystem services. Agents decide about the priority across three primary water uses: food production, hydropower generation and ecosystem health within their geographical domains. Agents interact with the environment (streamflow through the SWAT model and interact with other agents through a parameter representing willingness to cooperate. The innovative two-way coupling between the water system model and SWAT enables this framework to fully explore the feedback of human decisions on the environmental dynamics and vice versa. To support non-technical stakeholder interactions, a web-based user interface has been developed that allows for role-play and participatory modeling. The generalized ABM framework is also tested in two key transboundary river basins, the Mekong River basin in Southeast Asia and the Niger River basin in West Africa, where water uses for ecosystem health compete with growing human demands on food and energy resources. We present modeling results for crop production, energy generation and violation of

  13. Development and Evaluation of an Integrated Hydrological Modeling Framework for Monitoring and Understanding Floods and Droughts

    Science.gov (United States)

    Yang, Z. L.; Wu, W. Y.; Lin, P.; Maidment, D. R.

    2017-12-01

    Extreme water events such as catastrophic floods and severe droughts have increased in recent decades. Mitigating the risk to lives, food security, infrastructure, energy supplies, as well as numerous other industries posed by these extreme events requires informed decision-making and planning based on sound science. We are developing a global water modeling capability by building models that will provide total operational water predictions (evapotranspiration, soil moisture, groundwater, channel flow, inundation, snow) at unprecedented spatial resolutions and updated frequencies. Toward this goal, this talk presents an integrated global hydrological modeling framework that takes advantage of gridded meteorological forcing, land surface modeling, channeled flow modeling, ground observations, and satellite remote sensing. Launched in August 2016, the National Water Model successfully incorporates weather forecasts to predict river flows for more than 2.7 million rivers across the continental United States, which transfers a "synoptic weather map" to a "synoptic river flow map" operationally. In this study, we apply a similar framework to a high-resolution global river network database, which is developed from a hierarchical Dominant River Tracing (DRT) algorithm, and runoff output from the Global Land Data Assimilation System (GLDAS) to a vector-based river routing model (The Routing Application for Parallel Computation of Discharge, RAPID) to produce river flows from 2001 to 2016 using Message Passing Interface (MPI) on Texas Advanced Computer Center's Stampede system. In this simulation, global river discharges for more than 177,000 rivers are computed every 30 minutes. The modeling framework's performance is evaluated with various observations including river flows at more than 400 gauge stations globally. Overall, the model exhibits a reasonably good performance in simulating the averaged patterns of terrestrial water storage, evapotranspiration and runoff. The

  14. Application of computer-aided multi-scale modelling framework – Aerosol case study

    DEFF Research Database (Denmark)

    Heitzig, Martina; Sin, Gürkan; Glarborg, Peter

    2011-01-01

    Model-based computer aided product-process engineering has attained increased importance in a number of industries, including pharmaceuticals, petrochemicals, fine chemicals, polymers, biotechnology, food, energy and water. This trend is set to continue due to the substantial benefits computer-aided...... methods provide. The key prerequisite of computer-aided product-process engineering is however the availability of models of different types, forms and application modes. The development of the models required for the systems under investigation tends to be a challenging and time-consuming task involving...... numerous steps, expert skills and different modelling tools. This motivates the development of a computer-aided modelling framework that supports the user during model development, documentation, analysis, identification, application and re-use with the goal to increase the efficiency of the modelling...

  15. Two-Stage Hidden Markov Model in Gesture Recognition for Human Robot Interaction

    Directory of Open Access Journals (Sweden)

    Nhan Nguyen-Duc-Thanh

    2012-07-01

    Full Text Available Hidden Markov Model (HMM is very rich in mathematical structure and hence can form the theoretical basis for use in a wide range of applications including gesture representation. Most research in this field, however, uses only HMM for recognizing simple gestures, while HMM can definitely be applied for whole gesture meaning recognition. This is very effectively applicable in Human-Robot Interaction (HRI. In this paper, we introduce an approach for HRI in which not only the human can naturally control the robot by hand gesture, but also the robot can recognize what kind of task it is executing. The main idea behind this method is the 2-stages Hidden Markov Model. The 1st HMM is to recognize the prime command-like gestures. Based on the sequence of prime gestures that are recognized from the 1st stage and which represent the whole action, the 2nd HMM plays a role in task recognition. Another contribution of this paper is that we use the output Mixed Gaussian distribution in HMM to improve the recognition rate. In the experiment, we also complete a comparison of the different number of hidden states and mixture components to obtain the optimal one, and compare to other methods to evaluate this performance.

  16. Monthly streamflow forecasting based on hidden Markov model and Gaussian Mixture Regression

    Science.gov (United States)

    Liu, Yongqi; Ye, Lei; Qin, Hui; Hong, Xiaofeng; Ye, Jiajun; Yin, Xingli

    2018-06-01

    Reliable streamflow forecasts can be highly valuable for water resources planning and management. In this study, we combined a hidden Markov model (HMM) and Gaussian Mixture Regression (GMR) for probabilistic monthly streamflow forecasting. The HMM is initialized using a kernelized K-medoids clustering method, and the Baum-Welch algorithm is then executed to learn the model parameters. GMR derives a conditional probability distribution for the predictand given covariate information, including the antecedent flow at a local station and two surrounding stations. The performance of HMM-GMR was verified based on the mean square error and continuous ranked probability score skill scores. The reliability of the forecasts was assessed by examining the uniformity of the probability integral transform values. The results show that HMM-GMR obtained reasonably high skill scores and the uncertainty spread was appropriate. Different HMM states were assumed to be different climate conditions, which would lead to different types of observed values. We demonstrated that the HMM-GMR approach can handle multimodal and heteroscedastic data.

  17. An Integrated Scenario Ensemble-Based Framework for Hurricane Evacuation Modeling: Part 1-Decision Support System.

    Science.gov (United States)

    Davidson, Rachel A; Nozick, Linda K; Wachtendorf, Tricia; Blanton, Brian; Colle, Brian; Kolar, Randall L; DeYoung, Sarah; Dresback, Kendra M; Yi, Wenqi; Yang, Kun; Leonardo, Nicholas

    2018-03-30

    This article introduces a new integrated scenario-based evacuation (ISE) framework to support hurricane evacuation decision making. It explicitly captures the dynamics, uncertainty, and human-natural system interactions that are fundamental to the challenge of hurricane evacuation, but have not been fully captured in previous formal evacuation models. The hazard is represented with an ensemble of probabilistic scenarios, population behavior with a dynamic decision model, and traffic with a dynamic user equilibrium model. The components are integrated in a multistage stochastic programming model that minimizes risk and travel times to provide a tree of evacuation order recommendations and an evaluation of the risk and travel time performance for that solution. The ISE framework recommendations offer an advance in the state of the art because they: (1) are based on an integrated hazard assessment (designed to ultimately include inland flooding), (2) explicitly balance the sometimes competing objectives of minimizing risk and minimizing travel time, (3) offer a well-hedged solution that is robust under the range of ways the hurricane might evolve, and (4) leverage the substantial value of increasing information (or decreasing degree of uncertainty) over the course of a hurricane event. A case study for Hurricane Isabel (2003) in eastern North Carolina is presented to demonstrate how the framework is applied, the type of results it can provide, and how it compares to available methods of a single scenario deterministic analysis and a two-stage stochastic program. © 2018 Society for Risk Analysis.

  18. Developing policy analytics for public health strategy and decisions-the Sheffield alcohol policy model framework.

    Science.gov (United States)

    Brennan, Alan; Meier, Petra; Purshouse, Robin; Rafia, Rachid; Meng, Yang; Hill-Macmanus, Daniel

    This paper sets out the development of a methodological framework for detailed evaluation of public health strategies for alcohol harm reduction to meet UK policy-makers needs. Alcohol is known to cause substantial harms, and controlling its affordability and availability are effective policy options. Analysis and synthesis of a variety of public and commercial data sources is needed to evaluate impact on consumers, health services, crime, employers and industry, so a sound evaluation of impact is important. We discuss the iterative process to engage with stakeholders, identify evidence/data and develop analytic approaches and produce a final model structure. We set out a series of steps in modelling impact including: classification and definition of population subgroups of interest, identification and definition of harms and outcomes for inclusion, classification of modifiable components of risk and their baseline values, specification of the baseline position on policy variables especially prices, estimating effects of changing policy variables on risk factors including price elasticities, quantifying risk functions relating risk factors to harms including 47 health conditions, crimes, absenteeism and unemployment, and monetary valuation. The most difficult model structuring decisions are described, as well as the final results framework used to provide decision support to national level policymakers in the UK. In the discussion we explore issues around the relationship between modelling and policy debates, valuation and scope, limitations of evidence/data, how the framework can be adapted to other countries and decisions. We reflect on the approach taken and outline ongoing plans for further development.

  19. Tailored motivational message generation: A model and practical framework for real-time physical activity coaching.

    Science.gov (United States)

    Op den Akker, Harm; Cabrita, Miriam; Op den Akker, Rieks; Jones, Valerie M; Hermens, Hermie J

    2015-06-01

    This paper presents a comprehensive and practical framework for automatic generation of real-time tailored messages in behavior change applications. Basic aspects of motivational messages are time, intention, content and presentation. Tailoring of messages to the individual user may involve all aspects of communication. A linear modular system is presented for generating such messages. It is explained how properties of user and context are taken into account in each of the modules of the system and how they affect the linguistic presentation of the generated messages. The model of motivational messages presented is based on an analysis of existing literature as well as the analysis of a corpus of motivational messages used in previous studies. The model extends existing 'ontology-based' approaches to message generation for real-time coaching systems found in the literature. Practical examples are given on how simple tailoring rules can be implemented throughout the various stages of the framework. Such examples can guide further research by clarifying what it means to use e.g. user targeting to tailor a message. As primary example we look at the issue of promoting daily physical activity. Future work is pointed out in applying the present model and framework, defining efficient ways of evaluating individual tailoring components, and improving effectiveness through the creation of accurate and complete user- and context models. Copyright © 2015 Elsevier Inc. All rights reserved.

  20. Dubinin-Astakhov model for acetylene adsorption on metal-organic frameworks

    International Nuclear Information System (INIS)

    Cheng, Peifu; Hu, Yun Hang

    2016-01-01

    Graphical abstract: It was demonstrated that Dubinin-Astakhov equation can be exploited as a general isotherm model for C2H2 adsorption on metal-organic frameworks (MOFs), including MOF-5, ZIF-8, HKUST-1, and MIL-53. - Highlights: • Dubinin-Astakhov equation is demonstrated to be a general model for C_2H_2 adsorption on metal-organic frameworks (MOFs). • Surface areas obtained with Dubinin-Astakhov equation from C_2H_2 adsorption on MOFs are consistent with BET surface areas from N_2 adsorption. • C_2H_2 on MOF-5, ZIF-8, and MIL-53 is a physical adsorption, whereas its adsorption on HKUST-1 is due to a chemical bonding. - Abstract: Acetylene (C_2H_2) is explosive at a pressure above 29 psi, causing a safety issue for its storage and applications. C_2H_2 adsorption on metal-organic frameworks (MOFs) has been explored to solve the issue. However, a suitable isotherm equation for C_2H_2 adsorption on various MOFs has not been found. In this paper, it was demonstrated that Dubinin-Astakhov equation can be exploited as a general isotherm model to depict C_2H_2 adsorption on MOF-5, ZIF-8, HKUST-1, and MIL-53. In contrast, commonly used Langmuir and BET models exhibited their inapplicability for C_2H_2 adsorption on those MOFs.