the silent treasures of kano metropolis

African Journals Online (AJOL)

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Bajopas Volume 9 Number 1 June, 2016. Bayero Journal of Pure ... imageries (at 0.5m resolution) with the aid of Quantum GIS; road stock inventory; road .... The detail finding is presented in Table 1 and Figure 1 below. Table 1: Classes of Road Network in Kano Metropolis. Category. A. Number. T. Length (M). %. Arterial. 6.

Profitability analysis of plantain marketing in Kaduna metropolis ...

African Journals Online (AJOL)

Profitability analysis of plantain marketing in Kaduna metropolis, Kaduna state Nigeria. ... The study was carried out to analyze the profitability of plantain marketing and to examine the ... EMAIL FREE FULL TEXT EMAIL FREE FULL TEXT

MAPPING OF HEALTH FACILITIES IN JIMETA METROPOLIS: A ...

African Journals Online (AJOL)

PROF EKWUEME

one of the major problems hindering the proper planning and monitoring of the various health facilities ... A digital map, showing the spatial distribution of health facilities in Jimeta metropolis .... mapping process to quicken map production.

Buenos Aires: The Unattainable Energy Transition of a Fragmented Metropolis

International Nuclear Information System (INIS)

Prevot-Schapira, Marie-France; Velut, Sebastien

2013-01-01

The case of Buenos Aires (13 million inhabitants) exemplifies the evolution of energy supply and distribution in a developing metropolis characterized by the growth of consumption, spatial extension and social contrasts. After the 2001 economic and political crisis, the energy sectors underwent a major reorganization. For the city this meant growing state intervention in energy supply, private firms and the fixing of energy prices. The resulting evolution does not meet the criteria of energy transition as conceived in Europe, but it highlights the weight of the federal government upon a fragmented metropolis where local actors struggle to find their own spaces of action

Current epidemiology of hypertension in Port Harcourt metropolis ...

African Journals Online (AJOL)

Current epidemiology of hypertension in Port Harcourt metropolis, Rivers State ... the University of Port Harcourt Teaching Hospital formed the cohort for this study. ... is high and only a small fraction of hypertensives are aware of their condition.

Model structure selection in convolutive mixtures

DEFF Research Database (Denmark)

Dyrholm, Mads; Makeig, S.; Hansen, Lars Kai

2006-01-01

The CICAAR algorithm (convolutive independent component analysis with an auto-regressive inverse model) allows separation of white (i.i.d) source signals from convolutive mixtures. We introduce a source color model as a simple extension to the CICAAR which allows for a more parsimonious represent......The CICAAR algorithm (convolutive independent component analysis with an auto-regressive inverse model) allows separation of white (i.i.d) source signals from convolutive mixtures. We introduce a source color model as a simple extension to the CICAAR which allows for a more parsimonious...... representation in many practical mixtures. The new filter-CICAAR allows Bayesian model selection and can help answer questions like: ’Are we actually dealing with a convolutive mixture?’. We try to answer this question for EEG data....

Consistency of the MLE under mixture models

OpenAIRE

Chen, Jiahua

2016-01-01

The large-sample properties of likelihood-based statistical inference under mixture models have received much attention from statisticians. Although the consistency of the nonparametric MLE is regarded as a standard conclusion, many researchers ignore the precise conditions required on the mixture model. An incorrect claim of consistency can lead to false conclusions even if the mixture model under investigation seems well behaved. Under a finite normal mixture model, for instance, the consis...

Rainwater Quality Assessment in Uyo Metropolis using Water ...

African Journals Online (AJOL)

DR UDOUSORO

Nigerian Journal of Chemical Research. Vol. 20, 2015 ... metropolis, and pollution index to identify the individual parameter that was of risk. Twenty-two ... rainwater; and to apply PI (pollution ... clean plastic buckets placed on a raised platform ...

Numerical simulations of the O(3) and CP1 models using the Langevin equations and the Metropolis algorithm

International Nuclear Information System (INIS)

Abdalla, E.; Carneiro, C.E.I.

1988-12-01

The O(3) model, the pure CP 1 model and the CP 1 model minimally coupled to fermions are numerically simulated. The equivalence between the O(3) and the bound state of the pure CP 1 model is investigated. It is shown that: the relations g O(3 ) = 2 g CP 1 and E O(3 )= 2E CP 1 + 2, for the coupling constants and energies hold beyond the classical level; the mass gap as a function of the coupling is the same for both models. The mass gap for the CP 1 minimally coupled to fermions is also calculated. The calculations are performed using different techniques. The proposal by Namiki and colaborators to enforce constraints on Langevin equations and Parisi's technique to calculate correlation functions via Langevin equations is tested. The results are compared with those obtained using the multi-hit Metropolis algorithm. (author) [pt

Probabilistic mixture-based image modelling

Czech Academy of Sciences Publication Activity Database

Haindl, Michal; Havlíček, Vojtěch; Grim, Jiří

2011-01-01

Roč. 47, č. 3 (2011), s. 482-500 ISSN 0023-5954 R&D Projects: GA MŠk 1M0572; GA ČR GA102/08/0593 Grant - others:CESNET(CZ) 387/2010; GA MŠk(CZ) 2C06019; GA ČR(CZ) GA103/11/0335 Institutional research plan: CEZ:AV0Z10750506 Keywords : BTF texture modelling * discrete distribution mixtures * Bernoulli mixture * Gaussian mixture * multi-spectral texture modelling Subject RIV: BD - Theory of Information Impact factor: 0.454, year: 2011 http://library.utia.cas.cz/separaty/2011/RO/haindl-0360244.pdf

Poisson Mixture Regression Models for Heart Disease Prediction.

Science.gov (United States)

Mufudza, Chipo; Erol, Hamza

2016-01-01

Early heart disease control can be achieved by high disease prediction and diagnosis efficiency. This paper focuses on the use of model based clustering techniques to predict and diagnose heart disease via Poisson mixture regression models. Analysis and application of Poisson mixture regression models is here addressed under two different classes: standard and concomitant variable mixture regression models. Results show that a two-component concomitant variable Poisson mixture regression model predicts heart disease better than both the standard Poisson mixture regression model and the ordinary general linear Poisson regression model due to its low Bayesian Information Criteria value. Furthermore, a Zero Inflated Poisson Mixture Regression model turned out to be the best model for heart prediction over all models as it both clusters individuals into high or low risk category and predicts rate to heart disease componentwise given clusters available. It is deduced that heart disease prediction can be effectively done by identifying the major risks componentwise using Poisson mixture regression model.

Poisson Mixture Regression Models for Heart Disease Prediction

Science.gov (United States)

Erol, Hamza

2016-01-01

Early heart disease control can be achieved by high disease prediction and diagnosis efficiency. This paper focuses on the use of model based clustering techniques to predict and diagnose heart disease via Poisson mixture regression models. Analysis and application of Poisson mixture regression models is here addressed under two different classes: standard and concomitant variable mixture regression models. Results show that a two-component concomitant variable Poisson mixture regression model predicts heart disease better than both the standard Poisson mixture regression model and the ordinary general linear Poisson regression model due to its low Bayesian Information Criteria value. Furthermore, a Zero Inflated Poisson Mixture Regression model turned out to be the best model for heart prediction over all models as it both clusters individuals into high or low risk category and predicts rate to heart disease componentwise given clusters available. It is deduced that heart disease prediction can be effectively done by identifying the major risks componentwise using Poisson mixture regression model. PMID:27999611

Mixture of Regression Models with Single-Index

OpenAIRE

Xiang, Sijia; Yao, Weixin

2016-01-01

In this article, we propose a class of semiparametric mixture regression models with single-index. We argue that many recently proposed semiparametric/nonparametric mixture regression models can be considered special cases of the proposed model. However, unlike existing semiparametric mixture regression models, the new pro- posed model can easily incorporate multivariate predictors into the nonparametric components. Backfitting estimates and the corresponding algorithms have been proposed for...

METROPOLIS OF THE XXI CENTURY AND ITS COMMUNICATIVE PROBLEM: A PHILOSOPHICAL ASPECT

Directory of Open Access Journals (Sweden)

Krivykh Elena Georgievna

2012-12-01

nodal point in the process of urban growth. A classical form of a traditional city remains as one of the most important aesthetic values, although now it's a vanishing trend. Centrifugal tendencies are strengthened in the process of urbanization. A metropolis, reflecting the diversity of its functions, becomes a dynamic "space of stream" (M. Castels with a polycentric structure, imbued with functional links. A city becomes a machine that is constantly reproducing new massages. This continuity is perceived as a form that can only characterize the modern city as a whole. Informative saturation of the social environment leads to confusion of the genuine and non-genuine. The conception of Cristian De Portzamparc, a French architect, is considered as an example of an active research into the formation of the communicative space of a metropolis. A metropolis is presented as a complex self-developing system full of various social networks where physical space is no longer an alienating barrier.

Estimation of land surface temperature of Kaduna metropolis ...

African Journals Online (AJOL)

Estimation of land surface temperature of Kaduna metropolis, Nigeria using landsat images. Isa Zaharaddeen, Ibrahim I. Baba, Ayuba Zachariah. Abstract. Understanding the spatial variation of Land Surface Temperature (LST), will be helpful in urban micro climate studies. This study estimates the land surface temperature ...

Mixture Modeling: Applications in Educational Psychology

Science.gov (United States)

Harring, Jeffrey R.; Hodis, Flaviu A.

2016-01-01

Model-based clustering methods, commonly referred to as finite mixture modeling, have been applied to a wide variety of cross-sectional and longitudinal data to account for heterogeneity in population characteristics. In this article, we elucidate 2 such approaches: growth mixture modeling and latent profile analysis. Both techniques are…

BClass: A Bayesian Approach Based on Mixture Models for Clustering and Classification of Heterogeneous Biological Data

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Arturo Medrano-Soto

2004-12-01

Full Text Available Based on mixture models, we present a Bayesian method (called BClass to classify biological entities (e.g. genes when variables of quite heterogeneous nature are analyzed. Various statistical distributions are used to model the continuous/categorical data commonly produced by genetic experiments and large-scale genomic projects. We calculate the posterior probability of each entry to belong to each element (group in the mixture. In this way, an original set of heterogeneous variables is transformed into a set of purely homogeneous characteristics represented by the probabilities of each entry to belong to the groups. The number of groups in the analysis is controlled dynamically by rendering the groups as 'alive' and 'dormant' depending upon the number of entities classified within them. Using standard Metropolis-Hastings and Gibbs sampling algorithms, we constructed a sampler to approximate posterior moments and grouping probabilities. Since this method does not require the definition of similarity measures, it is especially suitable for data mining and knowledge discovery in biological databases. We applied BClass to classify genes in RegulonDB, a database specialized in information about the transcriptional regulation of gene expression in the bacterium Escherichia coli. The classification obtained is consistent with current knowledge and allowed prediction of missing values for a number of genes. BClass is object-oriented and fully programmed in Lisp-Stat. The output grouping probabilities are analyzed and interpreted using graphical (dynamically linked plots and query-based approaches. We discuss the advantages of using Lisp-Stat as a programming language as well as the problems we faced when the data volume increased exponentially due to the ever-growing number of genomic projects.

Relative abundance of mosquito species in Katsina Metropolis ...

African Journals Online (AJOL)

A study was conducted on the relative abundance of mosquito species, around selected areas of Katsina metropolis, Katsina State, Nigeria during the months of January, February, April and June 2010. Mosquitoes were collected from five sampling sites: Kofar Durbi, Kofar Kaura, Kofar Marusa, GRA and Layout. These were ...

Youth unemployment and its consequences in Calabar metropolis ...

African Journals Online (AJOL)

In this paper, consequences of youth unemployment in Nigeria were examined using Calabar metropolis in Cross River State as a case study. The literature is full of scholarly research on the social phenomenon of youth unemployment around the globe. This phenomenon has continued in Nigeria in the face of unfulfilled ...

Women in Educational Leadership within the Tamale Metropolis

Science.gov (United States)

Segkulu, L.; Gyimah, K.

2016-01-01

Within the Tamale Metropolis, it is observed that only a few women occupy top level management positions within the Ghana Education Service (GES). A descriptive survey was therefore conducted in 2013/2014 academic year to assess the factors affecting the gender disparity in educational leadership within the Service. Specifically, the study sought…

ANALYSIS OF RAINFALL PATTERN AND FLOOD INCIDENCES IN WARRI METROPOLIS, NIGERIA

Directory of Open Access Journals (Sweden)

R. Olanrewaju

2017-01-01

Full Text Available Climate change has led to changes in the known patterns of rainfall and other climatic variables as well as increase in the frequency and magnitude of natural disasters including floods in different parts of the world; and flood is indeed a global environmental issue that had destroyed lives and property amidst other untold hardships. The study examined rainfall characteristics in Warri metropolis for the past 30 years (1986-2015 vis-à-vis the flood situation in the metropolis; as well as the factors responsible and adaptation strategies to flood in the area. Dividing the study area into four zones after Sada (1977, the researchers collected rainfall data from the archives of Nigerian Meteorological Agency; 268 copies of questionnaire and oral interview were used. The result of the correlation analysis performed showed a negative relationship of -0.156 between rainfall and time (years, this implies that rainfall is decreasing over time. The trend line regression equation Y=243.75-0.4572X, confirms that rainfall in Warri Metropolis is decreasing at the rate of -0.45 per year. However, the p-value 0.412 is greater than 0.05, hence, the trend is not statistically significant at 95% level of confidence. It was discovered that rainfall, absence of drainage and poor urban planning practices (as factor 1 contributed 51.09% while overflowing of rivers, blocked/ poor drainage and untarred roads (as factor 2 contributed 44.10% variance to flood occurrence in the metropolis. Recommendations given included continual monitoring and study of rainfall characteristics and other climatic data and dissemination of such information for planning purposes; construction of integrated drainage system and river rechannelisation, legislation against dumping of refuse on roads and drainages; proper urban planning including implementation of the metropolitan urban drainage master plan. 

mixtools: An R Package for Analyzing Mixture Models

Directory of Open Access Journals (Sweden)

Tatiana Benaglia

2009-10-01

Full Text Available The mixtools package for R provides a set of functions for analyzing a variety of finite mixture models. These functions include both traditional methods, such as EM algorithms for univariate and multivariate normal mixtures, and newer methods that reflect some recent research in finite mixture models. In the latter category, mixtools provides algorithms for estimating parameters in a wide range of different mixture-of-regression contexts, in multinomial mixtures such as those arising from discretizing continuous multivariate data, in nonparametric situations where the multivariate component densities are completely unspecified, and in semiparametric situations such as a univariate location mixture of symmetric but otherwise unspecified densities. Many of the algorithms of the mixtools package are EM algorithms or are based on EM-like ideas, so this article includes an overview of EM algorithms for finite mixture models.

Quality Determination of Pipe-Borne Water in Sokoto Metropolis ...

African Journals Online (AJOL)

The quality of the pipe-borne water supplied to Sokoto metropolis was determined in this study. The total bacterial count was carried out using surface plating method of inoculation. The coliforms were enumerated using multiple tube fermentation technique (Most Probable Number Method). Some physicochemical ...

Constraint map for landfill site selection in Akure Metropolis ...

African Journals Online (AJOL)

An integration of remote sensing, soil type, geological, geoelectrical, hydrogeological and geotechnical data was carried out in a GIS environment with a view to developing a constraint map for the location of landfill (waste disposal) site(s) in Akure, Metropolis.. Geomorphological features identified from satellite images ...

Radiation survey of mobile and wireless technology masts in public places in Kaduna metropolis Nigeria

International Nuclear Information System (INIS)

Onoh, N. I.; Ogbanje, G. O.; Jonah, S. A.

2014-01-01

Work was done to measure radiation exposure of the populace in Kaduna metropolis from radiation emitted from global satellite communication masts. Base stations were surveyed in residential, school and office areas. Parameters sampled include the electric field strength, magnetic field strength, power density and ionizing radiation dose rate of the 20 surveyed masts belonging to four service providers. The instruments deployed include the Rf- EMF strength meter Model 480836 used to measure the first three parameters and Radiation Monitor Radex RD 1503 used to determine the forth parameter. The result obtained in this work was compared with the limits set by international regulatory bodies. Our result shows that electromagnetic and ionizing radiation exposures from the surveyed masts are far below the standard limits. Based on this, the population in Kaduna metropolis is not subjected to any adverse health effects from the Global System of Mobile Communication/Universal Mobile Telecommunication System masts at the moment.

Evaluation of some industrial effluents in Jos metropolis, Plateau ...

African Journals Online (AJOL)

Sometimes effluents gain access into wells or streams within the community. Analyses aimed to determine the strength of effluents of three different industries in Jos metropolis: industry A (a food industry), industry B (a pharmaceutical outfit) and Industry C (a water treatment plant) using parameters such as physicochemical, ...

Food Consumption Pattern in Ogbomoso Metropolis of Oyo State ...

African Journals Online (AJOL)

The study shed light on food consumption pattern in Ogbomoso Metropolis using Almost Ideal Demand System. Information on different classes of food consumed by the household was obtained using a multistage random technique. The result showed that demand for root and tubers and vegetables are elastic than ...

Statistical Analysis of Deviance among Children in Makurdi Metropolis

African Journals Online (AJOL)

This study sampled a total of four hundred and three individuals from designated households in Makurdi metropolis, Benue State. The study respondents responded to a self-report survey which gathered information on three deviant acts: alcoholism, smoking and dropping out of school. Criteria for deviant acts were defined, ...

An equiratio mixture model for non-additive components : a case study for aspartame/acesulfame-K mixtures

NARCIS (Netherlands)

Schifferstein, H.N.J.

1996-01-01

The Equiratio Mixture Model predicts the psychophysical function for an equiratio mixture type on the basis of the psychophysical functions for the unmixed components. The model reliably estimates the sweetness of mixtures of sugars and sugar-alchohols, but is unable to predict intensity for

Economics of fish farming in Ibadan Metropolis | Yusuf | Nigerian ...

African Journals Online (AJOL)

The study assesses the economics of fish farming in Ibadan Metropolis. The data for the study were collected from 50 fish farmers with the aid of structured questionnaires. The data were analyses using descriptive, gross margin and regression techniques. The study revealed that most farmers had secondary education and ...

Discovering the energy, economic and environmental potentials of urban wastes: An input–output model for a metropolis case

International Nuclear Information System (INIS)

Song, Junnian; Yang, Wei; Li, Zhaoling; Higano, Yoshiro; Wang, Xian’en

2016-01-01

Highlights: • A waste-to-energy system is constructed incorporating various urban wastes and technologies. • Waste-to-energy industries are formed and introduced into current socioeconomic system. • A novel input–output simulation model is developed and applied to a metropolis. • Complete energy, economic and environmental potentials of urban wastes are discovered. - Abstract: Tremendous amounts of wastes are generated in urban areas due to accelerating industrialization and urbanization. The current unreasonable waste disposal patterns and potential energy value of urban wastes necessitates the promotion of waste-to-energy implementation. This study is intent on discovering the complete energy, economic and environmental potentials of urban wastes taking municipal solid wastes, waste oil, organic wastewater and livestock manure into consideration. A waste-to-energy system is constructed incorporating these wastes and five waste-to-energy technologies. A novel input–output simulation model is developed and applied to a metropolis to introduce the waste-to-energy system into the current socioeconomic system and form five waste-to-energy industries. The trends in waste generation and energy recovery potential, economic benefits and greenhouse gas mitigation contribution for the study area are estimated and explored from 2011 to 2025. By 2025, biodiesel production and power generation could amount to 72.11 thousand t and 1.59 billion kW h respectively. Due to the highest energy recovery and the most subsidies, the organic wastewater biogas industry has the highest output and net profit, followed by the waste incineration power generation industry. In total 17.97 million t (carbon dioxide-equivalent) accumulative greenhouse gas emission could be mitigated. The organic wastewater biogas industry and waste incineration power generation industry are more advantageous for the study area in terms of better energy, economic and environmental performances. The

Hygiene practices among street food vendors in Tamale Metropolis ...

African Journals Online (AJOL)

The study noted that street food business in the Tamale Metropolis was women dominated (76%). Majority of vendors (78%) were aged 20-39 years. Public toilets (pit latrines) were accessible to all vending sites. Though high number of street food vendors had some form of formal education (66%) and knowledge of food ...

Effects of noise-induced hearing loss within Port Harcourt metropolis ...

African Journals Online (AJOL)

This paper investigates the effects of Noise-Induced Hearing Loss within Port Harcourt Metropolis using a micro-controlled diagnostic audiometer (Kamplex KLD21).The data was obtained at two specific locations namely: Rivers State University of Science and Technology and Port Harcourt International Airport.

Survey of waste disposal methods in Awka metropolis | Bill | Journal ...

African Journals Online (AJOL)

Waste disposal methods commonly practiced in Awka metropolis, Anambra state were investigated from August to October, 2013. Data was analyzed with both descriptive statistics of frequency and percentages, and alternate hypotheses were tested using Analysis of Variance (ANOVA) at a significance level of 0.05.

Prevalence of Demodicosis of Dogs in Makurdi Metropolis | Ogbaje ...

African Journals Online (AJOL)

A survey of prevalence of demodicosis of dogs was conducted between October, 2010 and April, 2011 in Makurdi Metropolis. A total of 316 dogs were sampled. 111(35.1%) of the dogs were positive of the disease. The Local breed (Nigeria Mongrels) were the most affected 65(58.6%) followed by Cross breeds (Nigeria ...

Road network: the silent treasures of Kano metropolis | Ibrahim ...

African Journals Online (AJOL)

The methods used include analysis of secondary data generated from the 2011 satellite imageries (at 0.5m resolution) with the aid of Quantum GIS; road stock inventory; road classification and mapping; as well as field observation. The result shows that, Kano metropolis is well stocked with all sorts of road networks and ...

Stochastic radiative transfer model for mixture of discontinuous vegetation canopies

International Nuclear Information System (INIS)

Shabanov, Nikolay V.; Huang, D.; Knjazikhin, Y.; Dickinson, R.E.; Myneni, Ranga B.

2007-01-01

Modeling of the radiation regime of a mixture of vegetation species is a fundamental problem of the Earth's land remote sensing and climate applications. The major existing approaches, including the linear mixture model and the turbid medium (TM) mixture radiative transfer model, provide only an approximate solution to this problem. In this study, we developed the stochastic mixture radiative transfer (SMRT) model, a mathematically exact tool to evaluate radiation regime in a natural canopy with spatially varying optical properties, that is, canopy, which exhibits a structured mixture of vegetation species and gaps. The model solves for the radiation quantities, direct input to the remote sensing/climate applications: mean radiation fluxes over whole mixture and over individual species. The canopy structure is parameterized in the SMRT model in terms of two stochastic moments: the probability of finding species and the conditional pair-correlation of species. The second moment is responsible for the 3D radiation effects, namely, radiation streaming through gaps without interaction with vegetation and variation of the radiation fluxes between different species. We performed analytical and numerical analysis of the radiation effects, simulated with the SMRT model for the three cases of canopy structure: (a) non-ordered mixture of species and gaps (TM); (b) ordered mixture of species without gaps; and (c) ordered mixture of species with gaps. The analysis indicates that the variation of radiation fluxes between different species is proportional to the variation of species optical properties (leaf albedo, density of foliage, etc.) Gaps introduce significant disturbance to the radiation regime in the canopy as their optical properties constitute major contrast to those of any vegetation species. The SMRT model resolves deficiencies of the major existing mixture models: ignorance of species radiation coupling via multiple scattering of photons (the linear mixture model

Evaluating Mixture Modeling for Clustering: Recommendations and Cautions

Science.gov (United States)

Steinley, Douglas; Brusco, Michael J.

2011-01-01

This article provides a large-scale investigation into several of the properties of mixture-model clustering techniques (also referred to as latent class cluster analysis, latent profile analysis, model-based clustering, probabilistic clustering, Bayesian classification, unsupervised learning, and finite mixture models; see Vermunt & Magdison,…

Maximum likelihood estimation of finite mixture model for economic data

Science.gov (United States)

Phoong, Seuk-Yen; Ismail, Mohd Tahir

2014-06-01

Finite mixture model is a mixture model with finite-dimension. This models are provides a natural representation of heterogeneity in a finite number of latent classes. In addition, finite mixture models also known as latent class models or unsupervised learning models. Recently, maximum likelihood estimation fitted finite mixture models has greatly drawn statistician's attention. The main reason is because maximum likelihood estimation is a powerful statistical method which provides consistent findings as the sample sizes increases to infinity. Thus, the application of maximum likelihood estimation is used to fit finite mixture model in the present paper in order to explore the relationship between nonlinear economic data. In this paper, a two-component normal mixture model is fitted by maximum likelihood estimation in order to investigate the relationship among stock market price and rubber price for sampled countries. Results described that there is a negative effect among rubber price and stock market price for Malaysia, Thailand, Philippines and Indonesia.

Infection of dogs with Babesia canis in Gwagwalada metropolis of ...

African Journals Online (AJOL)

Epidemiological investigation was carried out to determine the prevalence of infection with Babesia canis in dogs in Gwagwalada metropolis of the Federal Capital Territory, Abuja Nigeria, from November 2013 to January 2014. Blood samples were collected from 101 dogs and examined for the parasite. Data obtained were ...

The South African functional metropolis – A synthesis | Geyer | Town ...

African Journals Online (AJOL)

Confusing usage of terms such as metropolis and metropolitan region in planning policy in South Africa has led to the need for a fundamental investigation into the morphological and functional properties of the country's three largest cities. Using Gauteng, Cape Town and Durban as examples, the article distinguishes ...

Assessment of metals pollution in some herbs from Kano metropolis ...

African Journals Online (AJOL)

Assessment of metals pollution in some herbs from Kano metropolis. M.I. Mohammed, Y Inuwa. Abstract. No Abstract. Keywords: Herbs, metals, Kano, Nigeria. Full Text: EMAIL FREE FULL TEXT EMAIL FREE FULL TEXT · DOWNLOAD FULL TEXT DOWNLOAD FULL TEXT · AJOL African Journals Online. HOW TO USE ...

Cooperative conflict detection and resolution of civil unmanned aerial vehicles in metropolis

Directory of Open Access Journals (Sweden)

Jian Yang

2016-06-01

Full Text Available Unmanned air vehicles have recently attracted attention of many researchers because of their potential civil applications. A systematic integration of unmanned air vehicles in non-segregated airspace is required that allows safe operation of unmanned air vehicles along with other manned aircrafts. One of the critical issues is conflict detection and resolution. This article proposes to solve unmanned air vehicles’ conflict detection and resolution problem in metropolis airspace. First, the structure of metropolis airspace in the coming future is studied, and the airspace conflict problem between different unmanned air vehicles is analyzed by velocity obstacle theory. Second, a conflict detection and resolution framework in metropolis is proposed, and factors that have influences on conflict-free solutions are discussed. Third, the multi-unmanned air vehicle conflict resolution problem is formalized as a nonlinear optimization problem with the aim of minimizing overall conflict resolution consumption. The safe separation constraint is further discussed to improve the computation efficiency. When the speeds of conflict-involved unmanned air vehicles are equal, the nonlinear safe separation constraint is transformed into linear constraints. The problem is solved by mixed integer convex programming. When unmanned air vehicles are with unequal speeds, we propose to solve the nonlinear optimization problem by stochastic parallel gradient descent–based method. Our approaches are demonstrated in computational examples.

A Bootstrap Metropolis-Hastings Algorithm for Bayesian Analysis of Big Data.

Science.gov (United States)

Liang, Faming; Kim, Jinsu; Song, Qifan

2016-01-01

Markov chain Monte Carlo (MCMC) methods have proven to be a very powerful tool for analyzing data of complex structures. However, their computer-intensive nature, which typically require a large number of iterations and a complete scan of the full dataset for each iteration, precludes their use for big data analysis. In this paper, we propose the so-called bootstrap Metropolis-Hastings (BMH) algorithm, which provides a general framework for how to tame powerful MCMC methods to be used for big data analysis; that is to replace the full data log-likelihood by a Monte Carlo average of the log-likelihoods that are calculated in parallel from multiple bootstrap samples. The BMH algorithm possesses an embarrassingly parallel structure and avoids repeated scans of the full dataset in iterations, and is thus feasible for big data problems. Compared to the popular divide-and-combine method, BMH can be generally more efficient as it can asymptotically integrate the whole data information into a single simulation run. The BMH algorithm is very flexible. Like the Metropolis-Hastings algorithm, it can serve as a basic building block for developing advanced MCMC algorithms that are feasible for big data problems. This is illustrated in the paper by the tempering BMH algorithm, which can be viewed as a combination of parallel tempering and the BMH algorithm. BMH can also be used for model selection and optimization by combining with reversible jump MCMC and simulated annealing, respectively.

Geo-spatial analysis of crime in Kaduna Metropolis, Nigeria | Ayuba ...

African Journals Online (AJOL)

The study also revealed that Tudunwada, Sabon Tasha, Rigachikun and Rigasa are the major crime hotspots in the metropolis. This research, therefore recommends more effort should be put towards fighting crime especially in the months of December and January as the two months have the highest number of crimes ...

The Growth Of Kaduna Metropolis Between 1973 And 2012 The Physical Planning Implications

Directory of Open Access Journals (Sweden)

Afon

2015-08-01

Full Text Available This paper examined the growth and development pattern of Kaduna metropolis Nigeria over a period of 39 years with a view to identifying its physical planning implications. The study employs the use of Remote Sensing data and GIS technology. Data used for the study include Landsat Imagery of 1973 1990 and 2001 and NigeriaSat-1 of 2006 and GeoEye image of 2012 and the population data for 1963 1991 and 2006. The data was used to determine the pattern of growth rate of growth land consumption rate and land absorption efficiency of the study area. The study established that Kaduna metropolis have been increasing like most cities of the world of which the highest growth was witnessed between 2006 to 2012 with 13.4 growth rate per annum. It also revealed that the pattern of growths witnessed were along the major routes. The study also revealed that there is a relationship between population growth and urban growth in Kaduna metropolis The study concluded that the need for available data is vital to the understanding of the dynamic of the urban environment. More commitment had to be done on the part of government and research to ensure that the gap is closed.

Mapping of health facilities in Jimeta Metropolis: a digital approach ...

African Journals Online (AJOL)

In planning for any suitable development in any field, the primary requirement is the relevant data and maps. This is one of the major problems hindering the proper planning and monitoring of the various health facilities located in Jimeta metropolis. Survey techniques -were employed for the acquisition of data, GPS was ...

Adaptive Metropolis Sampling with Product Distributions

Science.gov (United States)

Wolpert, David H.; Lee, Chiu Fan

2005-01-01

The Metropolis-Hastings (MH) algorithm is a way to sample a provided target distribution pi(z). It works by repeatedly sampling a separate proposal distribution T(x,x') to generate a random walk {x(t)}. We consider a modification of the MH algorithm in which T is dynamically updated during the walk. The update at time t uses the {x(t' less than t)} to estimate the product distribution that has the least Kullback-Leibler distance to pi. That estimate is the information-theoretically optimal mean-field approximation to pi. We demonstrate through computer experiments that our algorithm produces samples that are superior to those of the conventional MH algorithm.

Modeling text with generalizable Gaussian mixtures

DEFF Research Database (Denmark)

Hansen, Lars Kai; Sigurdsson, Sigurdur; Kolenda, Thomas

2000-01-01

We apply and discuss generalizable Gaussian mixture (GGM) models for text mining. The model automatically adapts model complexity for a given text representation. We show that the generalizability of these models depends on the dimensionality of the representation and the sample size. We discuss...

Geo-products of urban areas: Silesian Metropolis, Southern Poland

Science.gov (United States)

Chybiorz, Ryszard; Abramowicz, Anna

2017-04-01

Silesian Metropolis is located in the Silesian Voivodeship, in the most important industrial region in Poland. It consist of 14 cities with powiat rights, which create the largest urban center in Poland and one of the largest in Central and Eastern Europe. Almost 2 million people live in its territory. A large concentration of the population is associated with industrialization and especially with the development of the mining industry (Upper Silesian Coal Basin) and the processing industry (steelworks, textile industry) at the end of 19th century. One hundred years later, during the creation of the modern sectors of the economy, processes of metallurgy and mining restructuring have been started. Created mechanisms and conditions for development of post-industrial areas were consistent with the principles of sustainable development and had many new features, including cultural and touristic features. The Industrial Monuments Route was opened for the inhabitants and visitors in October 2006. The route joined the European Route of Industrial Heritage (ERIH) in 2010. Its most interesting mining attractions are located in Silesian Metropolis, and the most frequently visited object on the route is the Guido Historical Coal Mine in Zabrze and the Historical Silver Mine in Tarnowskie Góry. The project, which is realized in Zabrze, will provide for tourists a system of underground corridors, which were used for coal transportation in the 19th century. Visitors will be able to actively explore the work of miners, moving by underground boats, railway and suspension railway. Surface mines are also available for geotourists. The Ecological and Geological Education Center GEOsfera was created in a former Triassic quarry in Jaworzno. Although the area of the Silesian Metropolis is characterized by a very large devastation of the environment, the following objects were created (and are still created) on the basis of inanimate nature and they have a touristic value for the region

Analysis of Intra-Urban Traffic Problems in Nigeria: A Study of Lagos Metropolis

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A. Raji Bashiru

2013-07-01

local government areas. However, the observed spatial and temporal pattern o.l vehicular traffic congestion enabled us to suggest possible measures for the reduction of traffic congestion within the metropolis.

Wheelchair accessibility to public buildings in the Kumasi metropolis, Ghana

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Cosmos Yarfi

2017-09-01

Conclusion: The results of this study show that public buildings in the Kumasi metropolis are not wheelchair accessible. An important observation made during this study was that there is an intention to improve accessibility when buildings are being constructed or renovated, but there are no laid down guidelines as how to make the buildings accessible for wheelchair users.

Analisi della dipendenza spaziale dei prezzi delle abitazioni e dei sottomercati abitativi nella Tainan Metropolis, Taiwan

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Bor-Ming Hsieh

2012-06-01

Full Text Available All’interno di questo studio vengono utilizzate diverse metodologie, comprese alcune tecniche di analisi statistica e spaziale, sia per definire i sottomercati spaziali dei prezzi delle abitazioni che per esaminare la dipendenza spaziale dei prezzi delle abitazioni. I dati sono desunti dai prezzi delle transazioni relativi al 2009, riferite all’edilizia abitativa nella Tainan Metropolis. La Tainan Metropolis è una nuova metropoli formata dalla fusione dell'ex Tainan City e di Tainan County. In seguito alla fusione delle municipalità verranno adeguati i confini amministrativi e, nel frattempo, è opportuno individuare i sottomercati spaziali dei prezzi delle abitazioni nell'area metropolitana in relazione ai sottomercati relativi ai precedenti confini amministrativi. Si è constatato che i prezzi più alti delle abitazioni sono concentrati nella zona del centro della città, mentre i prezzi più bassi sono diffusi soprattutto nell'anello esterno al centro della città di Tainan Metropolis. Nella sperimentazione dell’autocorrelazione spaziale dei prezzi delle abitazioni, si è rilevato che si riscontrava una significativa dipendenza spaziale tra i prezzi delle case. I risultati della modellazione dei prezzi delle abitazioni mostrano che i sottomercati spaziali derivati da tecniche di autocorrelazione spaziale hanno impatti più forti e più significativi sui prezzi delle case, inoltre, rispetto ai due modelli alternativi, il modello ha una migliore goodness-of-fit. Le tecniche spaziali possono essere considerate metodi appropriati per classificare sottomercati spaziali dei prezzi delle abitazioni soprattutto nelle aree metropolitane.

My sound Is My life. Macchine sonore non omologate nella metropoli

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Antonio Bove

2008-12-01

Full Text Available Nell’ordine costituito della metropoli, i luoghi del divetimento sono spazl interni ai processi di accumulo, funzionali al ritmo della produzione. L’ordine stabilisce un posto preciso per “lo svago”inserito nella settimana lavorativa come elemento di ricarica per l’uomo-lavoratore, traendone anzi profitto.

Modeling abundance using N-mixture models: the importance of considering ecological mechanisms.

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Joseph, Liana N; Elkin, Ché; Martin, Tara G; Possinghami, Hugh P

2009-04-01

Predicting abundance across a species' distribution is useful for studies of ecology and biodiversity management. Modeling of survey data in relation to environmental variables can be a powerful method for extrapolating abundances across a species' distribution and, consequently, calculating total abundances and ultimately trends. Research in this area has demonstrated that models of abundance are often unstable and produce spurious estimates, and until recently our ability to remove detection error limited the development of accurate models. The N-mixture model accounts for detection and abundance simultaneously and has been a significant advance in abundance modeling. Case studies that have tested these new models have demonstrated success for some species, but doubt remains over the appropriateness of standard N-mixture models for many species. Here we develop the N-mixture model to accommodate zero-inflated data, a common occurrence in ecology, by employing zero-inflated count models. To our knowledge, this is the first application of this method to modeling count data. We use four variants of the N-mixture model (Poisson, zero-inflated Poisson, negative binomial, and zero-inflated negative binomial) to model abundance, occupancy (zero-inflated models only) and detection probability of six birds in South Australia. We assess models by their statistical fit and the ecological realism of the parameter estimates. Specifically, we assess the statistical fit with AIC and assess the ecological realism by comparing the parameter estimates with expected values derived from literature, ecological theory, and expert opinion. We demonstrate that, despite being frequently ranked the "best model" according to AIC, the negative binomial variants of the N-mixture often produce ecologically unrealistic parameter estimates. The zero-inflated Poisson variant is preferable to the negative binomial variants of the N-mixture, as it models an ecological mechanism rather than a

Self-organising mixture autoregressive model for non-stationary time series modelling.

Science.gov (United States)

Ni, He; Yin, Hujun

2008-12-01

Modelling non-stationary time series has been a difficult task for both parametric and nonparametric methods. One promising solution is to combine the flexibility of nonparametric models with the simplicity of parametric models. In this paper, the self-organising mixture autoregressive (SOMAR) network is adopted as a such mixture model. It breaks time series into underlying segments and at the same time fits local linear regressive models to the clusters of segments. In such a way, a global non-stationary time series is represented by a dynamic set of local linear regressive models. Neural gas is used for a more flexible structure of the mixture model. Furthermore, a new similarity measure has been introduced in the self-organising network to better quantify the similarity of time series segments. The network can be used naturally in modelling and forecasting non-stationary time series. Experiments on artificial, benchmark time series (e.g. Mackey-Glass) and real-world data (e.g. numbers of sunspots and Forex rates) are presented and the results show that the proposed SOMAR network is effective and superior to other similar approaches.

Semiparametric Mixtures of Regressions with Single-index for Model Based Clustering

OpenAIRE

Xiang, Sijia; Yao, Weixin

2017-01-01

In this article, we propose two classes of semiparametric mixture regression models with single-index for model based clustering. Unlike many semiparametric/nonparametric mixture regression models that can only be applied to low dimensional predictors, the new semiparametric models can easily incorporate high dimensional predictors into the nonparametric components. The proposed models are very general, and many of the recently proposed semiparametric/nonparametric mixture regression models a...

Modeling of Multicomponent Mixture Separation Processes Using Hollow fiber Membrane

Energy Technology Data Exchange (ETDEWEB)

Kim, Sin-Ah; Kim, Jin-Kuk; Lee, Young Moo; Yeo, Yeong-Koo [Hanyang University, Seoul (Korea, Republic of)

2015-02-15

So far, most of research activities on modeling of membrane separation processes have been focused on binary feed mixture. But, in actual separation operations, binary feed is hard to find and most separation processes involve multicomponent feed mixture. In this work models for membrane separation processes treating multicomponent feed mixture are developed. Various model types are investigated and validity of proposed models are analysed based on experimental data obtained using hollowfiber membranes. The proposed separation models show quick convergence and exhibit good tracking performance.

Views of Physics Teachers in Ilorin Metropolis on the Impact of ...

African Journals Online (AJOL)

In this study, efforts were made to find out the views of 47 Physics Teachers in Ilorin metropolis on the impact of religion on the utilization of the applications of Physics. Thirty of them were Christians while Seventeen were. Moslems. The instrument was a questionnaire comprising 12 statements. Findings from the study ...

Prevalence Incidence Mixture Models

Science.gov (United States)

The R package and webtool fits Prevalence Incidence Mixture models to left-censored and irregularly interval-censored time to event data that is commonly found in screening cohorts assembled from electronic health records. Absolute and relative risk can be estimated for simple random sampling, and stratified sampling (the two approaches of superpopulation and a finite population are supported for target populations). Non-parametric (absolute risks only), semi-parametric, weakly-parametric (using B-splines), and some fully parametric (such as the logistic-Weibull) models are supported.

The 'politics of poverty' in a post-apartheid South African metropolis ...

African Journals Online (AJOL)

The 'politics of poverty' in a post-apartheid South African metropolis. Kamila Naidoo. Abstract. No Abstract. African Sociological Review Vol. 9(2) 2005: 55-78. Full Text: EMAIL FREE FULL TEXT EMAIL FREE FULL TEXT · DOWNLOAD FULL TEXT DOWNLOAD FULL TEXT · http://dx.doi.org/10.4314/asr.v9i2.23261.

A comparative study of noise pollution levels in some selected areas in Ilorin Metropolis, Nigeria.

Science.gov (United States)

Oyedepo, Olayinka S; Saadu, Abdullahi A

2009-11-01

The noise pollution is a major problem for the quality of life in urban areas. This study was conducted to compare the noise pollution levels at busy roads/road junctions, passengers loading parks, commercial, industrial and residential areas in Ilorin metropolis. A total number of 47-locations were selected within the metropolis. Statistical analysis shows significant difference (P noise pollution levels between industrial areas and low density residential areas, industrial areas and high density areas, industrial areas and passengers loading parks, industrial areas and commercial areas, busy roads/road junctions and low density areas, passengers loading parks and commercial areas and commercial areas and low density areas. There is no significant difference (P > 0.05) in noise pollution levels between industrial areas and busy roads/road junctions, busy roads/road junctions and high density areas, busy roads/road junctions and passengers loading parks, busy roads/road junctions and commercial areas, passengers loading parks and high density areas, passengers loading parks and commercial areas and commercial areas and high density areas. The results show that Industrial areas have the highest noise pollution levels (110.2 dB(A)) followed by busy roads/Road junctions (91.5 dB(A)), Passengers loading parks (87.8 dB(A)) and Commercial areas (84.4 dB(A)). The noise pollution levels in Ilorin metropolis exceeded the recommended level by WHO at 34 of 47 measuring points. It can be concluded that the city is environmentally noise polluted and road traffic and industrial machineries are the major sources of it. Noting the noise emission standards, technical control measures, planning and promoting the citizens awareness about the high noise risk may help to relieve the noise problem in the metropolis.

A Dirichlet process mixture model for brain MRI tissue classification.

Science.gov (United States)

Ferreira da Silva, Adelino R

2007-04-01

Accurate classification of magnetic resonance images according to tissue type or region of interest has become a critical requirement in diagnosis, treatment planning, and cognitive neuroscience. Several authors have shown that finite mixture models give excellent results in the automated segmentation of MR images of the human normal brain. However, performance and robustness of finite mixture models deteriorate when the models have to deal with a variety of anatomical structures. In this paper, we propose a nonparametric Bayesian model for tissue classification of MR images of the brain. The model, known as Dirichlet process mixture model, uses Dirichlet process priors to overcome the limitations of current parametric finite mixture models. To validate the accuracy and robustness of our method we present the results of experiments carried out on simulated MR brain scans, as well as on real MR image data. The results are compared with similar results from other well-known MRI segmentation methods.

Turning Simulation into Estimation: Generalized Exchange Algorithms for Exponential Family Models.

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Maarten Marsman

Full Text Available The Single Variable Exchange algorithm is based on a simple idea; any model that can be simulated can be estimated by producing draws from the posterior distribution. We build on this simple idea by framing the Exchange algorithm as a mixture of Metropolis transition kernels and propose strategies that automatically select the more efficient transition kernels. In this manner we achieve significant improvements in convergence rate and autocorrelation of the Markov chain without relying on more than being able to simulate from the model. Our focus will be on statistical models in the Exponential Family and use two simple models from educational measurement to illustrate the contribution.

A Note on the Use of Mixture Models for Individual Prediction.

Science.gov (United States)

Cole, Veronica T; Bauer, Daniel J

Mixture models capture heterogeneity in data by decomposing the population into latent subgroups, each of which is governed by its own subgroup-specific set of parameters. Despite the flexibility and widespread use of these models, most applications have focused solely on making inferences for whole or sub-populations, rather than individual cases. The current article presents a general framework for computing marginal and conditional predicted values for individuals using mixture model results. These predicted values can be used to characterize covariate effects, examine the fit of the model for specific individuals, or forecast future observations from previous ones. Two empirical examples are provided to demonstrate the usefulness of individual predicted values in applications of mixture models. The first example examines the relative timing of initiation of substance use using a multiple event process survival mixture model whereas the second example evaluates changes in depressive symptoms over adolescence using a growth mixture model.

A Study of the Solid Waste Chain in Benin Metropolis, Nigeria ...

African Journals Online (AJOL)

Benin metropolis like other fast urbanizing towns and cities in Nigeria is faces with a solid waste management problem. Solid waste is seen in huge heaps on any piece of unused land, around buildings, in the open market places and in drainage and water ways. The work reported in this paper involves a study of the path ...

A Robust Non-Gaussian Data Assimilation Method for Highly Non-Linear Models

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Elias D. Nino-Ruiz

2018-03-01

Full Text Available In this paper, we propose an efficient EnKF implementation for non-Gaussian data assimilation based on Gaussian Mixture Models and Markov-Chain-Monte-Carlo (MCMC methods. The proposed method works as follows: based on an ensemble of model realizations, prior errors are estimated via a Gaussian Mixture density whose parameters are approximated by means of an Expectation Maximization method. Then, by using an iterative method, observation operators are linearized about current solutions and posterior modes are estimated via a MCMC implementation. The acceptance/rejection criterion is similar to that of the Metropolis-Hastings rule. Experimental tests are performed on the Lorenz 96 model. The results show that the proposed method can decrease prior errors by several order of magnitudes in a root-mean-square-error sense for nearly sparse or dense observational networks.

Examining Work and Family Conflict among Female Bankers in Accra Metropolis, Ghana

Science.gov (United States)

Kissi-Abrokwah, Bernard; Andoh-Robertson, Theophilus; Tutu-Danquah, Cecilia; Agbesi, Catherine Selorm

2015-01-01

This study investigated the effects and solutions of work and family conflict among female bankers in Accra Metropolis. Using triangulatory mixed method design, a structured questionnaire was randomly administered to 300 female bankers and 15 female Bankers who were interviewed were also sampled by using convenient sampling technique. The…

Structure-reactivity modeling using mixture-based representation of chemical reactions.

Science.gov (United States)

Polishchuk, Pavel; Madzhidov, Timur; Gimadiev, Timur; Bodrov, Andrey; Nugmanov, Ramil; Varnek, Alexandre

2017-09-01

We describe a novel approach of reaction representation as a combination of two mixtures: a mixture of reactants and a mixture of products. In turn, each mixture can be encoded using an earlier reported approach involving simplex descriptors (SiRMS). The feature vector representing these two mixtures results from either concatenated product and reactant descriptors or the difference between descriptors of products and reactants. This reaction representation doesn't need an explicit labeling of a reaction center. The rigorous "product-out" cross-validation (CV) strategy has been suggested. Unlike the naïve "reaction-out" CV approach based on a random selection of items, the proposed one provides with more realistic estimation of prediction accuracy for reactions resulting in novel products. The new methodology has been applied to model rate constants of E2 reactions. It has been demonstrated that the use of the fragment control domain applicability approach significantly increases prediction accuracy of the models. The models obtained with new "mixture" approach performed better than those required either explicit (Condensed Graph of Reaction) or implicit (reaction fingerprints) reaction center labeling.

URBAN STRUGGLES IN CURITIBA METROPOLIS: POPULAR HOUSING, LAND OCCUPATIONS AND RESISTANCE

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Danilo Volochko

2016-07-01

Full Text Available The forms of exploitation and expropriation in the city imply the emergence of land and buildings occupations in peripheral and central areas. In Curitiba, slums, neighborhoods without infrastructure, popular housing, vacant land sites and buildings make part of multiple processes and temporalities that emerge of the city which is mythically taken as urban planning model. The research seeks to analyze organized land occupations in order to understand its links with the reproduction of the metropolis, revealing the scale of the place, of everyday life, of sociability in these occupations, their socio-political organization strategies and resistance, revealing urban struggles as an amalgam between local particularities and global processes, placing the debate in the realization of the right to the city. Key-words: urban struggles, production of space, land occupations, spatial justice.

Stochastic cluster algorithms for discrete Gaussian (SOS) models

International Nuclear Information System (INIS)

Evertz, H.G.; Hamburg Univ.; Hasenbusch, M.; Marcu, M.; Tel Aviv Univ.; Pinn, K.; Muenster Univ.; Solomon, S.

1990-10-01

We present new Monte Carlo cluster algorithms which eliminate critical slowing down in the simulation of solid-on-solid models. In this letter we focus on the two-dimensional discrete Gaussian model. The algorithms are based on reflecting the integer valued spin variables with respect to appropriately chosen reflection planes. The proper choice of the reflection plane turns out to be crucial in order to obtain a small dynamical exponent z. Actually, the successful versions of our algorithm are a mixture of two different procedures for choosing the reflection plane, one of them ergodic but slow, the other one non-ergodic and also slow when combined with a Metropolis algorithm. (orig.)

Social Media as Contact Zones : Young Londoners Remapping the Metropolis through Digital Media

NARCIS (Netherlands)

Leurs, K.H.A.|info:eu-repo/dai/nl/343295334

2015-01-01

Social media use among urban, young Londoners of diverse cultural backgrounds constitutes a contemporary, postcolonial contact zone in Europe. By taking digital practices as an entry point to consider intercultural encounters in the postcolonial metropolis, I bring new media studies into a much

Identifiability in N-mixture models: a large-scale screening test with bird data.

Science.gov (United States)

Kéry, Marc

2018-02-01

Binomial N-mixture models have proven very useful in ecology, conservation, and monitoring: they allow estimation and modeling of abundance separately from detection probability using simple counts. Recently, doubts about parameter identifiability have been voiced. I conducted a large-scale screening test with 137 bird data sets from 2,037 sites. I found virtually no identifiability problems for Poisson and zero-inflated Poisson (ZIP) binomial N-mixture models, but negative-binomial (NB) models had problems in 25% of all data sets. The corresponding multinomial N-mixture models had no problems. Parameter estimates under Poisson and ZIP binomial and multinomial N-mixture models were extremely similar. Identifiability problems became a little more frequent with smaller sample sizes (267 and 50 sites), but were unaffected by whether the models did or did not include covariates. Hence, binomial N-mixture model parameters with Poisson and ZIP mixtures typically appeared identifiable. In contrast, NB mixtures were often unidentifiable, which is worrying since these were often selected by Akaike's information criterion. Identifiability of binomial N-mixture models should always be checked. If problems are found, simpler models, integrated models that combine different observation models or the use of external information via informative priors or penalized likelihoods, may help. © 2017 by the Ecological Society of America.

Modeling of non-additive mixture properties using the Online CHEmical database and Modeling environment (OCHEM

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Oprisiu Ioana

2013-01-01

Full Text Available Abstract The Online Chemical Modeling Environment (OCHEM, http://ochem.eu is a web-based platform that provides tools for automation of typical steps necessary to create a predictive QSAR/QSPR model. The platform consists of two major subsystems: a database of experimental measurements and a modeling framework. So far, OCHEM has been limited to the processing of individual compounds. In this work, we extended OCHEM with a new ability to store and model properties of binary non-additive mixtures. The developed system is publicly accessible, meaning that any user on the Web can store new data for binary mixtures and develop models to predict their non-additive properties. The database already contains almost 10,000 data points for the density, bubble point, and azeotropic behavior of binary mixtures. For these data, we developed models for both qualitative (azeotrope/zeotrope and quantitative endpoints (density and bubble points using different learning methods and specially developed descriptors for mixtures. The prediction performance of the models was similar to or more accurate than results reported in previous studies. Thus, we have developed and made publicly available a powerful system for modeling mixtures of chemical compounds on the Web.

ODE constrained mixture modelling: a method for unraveling subpopulation structures and dynamics.

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Jan Hasenauer

2014-07-01

Full Text Available Functional cell-to-cell variability is ubiquitous in multicellular organisms as well as bacterial populations. Even genetically identical cells of the same cell type can respond differently to identical stimuli. Methods have been developed to analyse heterogeneous populations, e.g., mixture models and stochastic population models. The available methods are, however, either incapable of simultaneously analysing different experimental conditions or are computationally demanding and difficult to apply. Furthermore, they do not account for biological information available in the literature. To overcome disadvantages of existing methods, we combine mixture models and ordinary differential equation (ODE models. The ODE models provide a mechanistic description of the underlying processes while mixture models provide an easy way to capture variability. In a simulation study, we show that the class of ODE constrained mixture models can unravel the subpopulation structure and determine the sources of cell-to-cell variability. In addition, the method provides reliable estimates for kinetic rates and subpopulation characteristics. We use ODE constrained mixture modelling to study NGF-induced Erk1/2 phosphorylation in primary sensory neurones, a process relevant in inflammatory and neuropathic pain. We propose a mechanistic pathway model for this process and reconstructed static and dynamical subpopulation characteristics across experimental conditions. We validate the model predictions experimentally, which verifies the capabilities of ODE constrained mixture models. These results illustrate that ODE constrained mixture models can reveal novel mechanistic insights and possess a high sensitivity.

ODE constrained mixture modelling: a method for unraveling subpopulation structures and dynamics.

Science.gov (United States)

Hasenauer, Jan; Hasenauer, Christine; Hucho, Tim; Theis, Fabian J

2014-07-01

Functional cell-to-cell variability is ubiquitous in multicellular organisms as well as bacterial populations. Even genetically identical cells of the same cell type can respond differently to identical stimuli. Methods have been developed to analyse heterogeneous populations, e.g., mixture models and stochastic population models. The available methods are, however, either incapable of simultaneously analysing different experimental conditions or are computationally demanding and difficult to apply. Furthermore, they do not account for biological information available in the literature. To overcome disadvantages of existing methods, we combine mixture models and ordinary differential equation (ODE) models. The ODE models provide a mechanistic description of the underlying processes while mixture models provide an easy way to capture variability. In a simulation study, we show that the class of ODE constrained mixture models can unravel the subpopulation structure and determine the sources of cell-to-cell variability. In addition, the method provides reliable estimates for kinetic rates and subpopulation characteristics. We use ODE constrained mixture modelling to study NGF-induced Erk1/2 phosphorylation in primary sensory neurones, a process relevant in inflammatory and neuropathic pain. We propose a mechanistic pathway model for this process and reconstructed static and dynamical subpopulation characteristics across experimental conditions. We validate the model predictions experimentally, which verifies the capabilities of ODE constrained mixture models. These results illustrate that ODE constrained mixture models can reveal novel mechanistic insights and possess a high sensitivity.

Implementation and statistical analysis of Metropolis algorithm for SU(3)

International Nuclear Information System (INIS)

Katznelson, E.; Nobile, A.

1984-12-01

In this paper we study the statistical properties of an implementation of the Metropolis algorithm for SU(3) gauge theory. It is shown that the results have normal distribution. We demonstrate that in this case error analysis can be carried on in a simple way and we show that applying it to both the measurement strategy and the output data analysis has an important influence on the performance and reliability of the simulation. (author)

Optimal mixture experiments

CERN Document Server

Sinha, B K; Pal, Manisha; Das, P

2014-01-01

The book dwells mainly on the optimality aspects of mixture designs. As mixture models are a special case of regression models, a general discussion on regression designs has been presented, which includes topics like continuous designs, de la Garza phenomenon, Loewner order domination, Equivalence theorems for different optimality criteria and standard optimality results for single variable polynomial regression and multivariate linear and quadratic regression models. This is followed by a review of the available literature on estimation of parameters in mixture models. Based on recent research findings, the volume also introduces optimal mixture designs for estimation of optimum mixing proportions in different mixture models, which include Scheffé’s quadratic model, Darroch-Waller model, log- contrast model, mixture-amount models, random coefficient models and multi-response model.  Robust mixture designs and mixture designs in blocks have been also reviewed. Moreover, some applications of mixture desig...

Hotel location decision-making in the Kumasi Metropolis of Ghana: with whom and why?

Directory of Open Access Journals (Sweden)

Issahaku Adam

2012-01-01

Full Text Available Knowledge on the people involved in hotel location decision-making and why they are involved is key to destination planning and development. Insights gained into this subject are useful to future destination planners. Despite its importance, the subject of whom to involve in the hotel location decision and why they should be involved, has received limited research interest in Ghana. This study identifies the people involved in hotel location decisions and assesses the reasons why they are involved. Data was collected from hotel owners in the Kumasi Metropolis and analysed with the chi-square test of independence. Extended family members were mostly involved in the hotel location decisions and for mainly personal reasons. It was concluded that hotel owners in the Kumasi Metropolis involve their family members in the location choice for non-professional reasons.

Infinite von Mises-Fisher Mixture Modeling of Whole Brain fMRI Data

DEFF Research Database (Denmark)

Røge, Rasmus; Madsen, Kristoffer Hougaard; Schmidt, Mikkel Nørgaard

2017-01-01

spherical manifold are rarely analyzed, in part due to the computational challenges imposed by directional statistics. In this letter, we discuss a Bayesian von Mises-Fisher (vMF) mixture model for data on the unit hypersphere and present an efficient inference procedure based on collapsed Markov chain...... Monte Carlo sampling. Comparing the vMF and gaussian mixture models on synthetic data, we demonstrate that the vMF model has a slight advantage inferring the true underlying clustering when compared to gaussian-based models on data generated from both a mixture of vMFs and a mixture of gaussians......Cluster analysis of functional magnetic resonance imaging (fMRI) data is often performed using gaussian mixture models, but when the time series are standardized such that the data reside on a hypersphere, this modeling assumption is questionable. The consequences of ignoring the underlying...

Assessing the Benefits of Yield Management in the Hospitality Industry in the Kumasi Metropolis of Ghana

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Owusu Boahen

2013-10-01

Full Text Available Ghana's hotel industry has a great deal of potential for future development. However, revenue loss due to lost opportunity arising from unused rooms or no shows is a challenge facing the industry. Maximizing revenue is important in the industry because of high costs of operation. Yield Management (YM offers one of the potential revenue maximization strategies in the hotel business operations. This study aims at evaluating the effect of yield management practices on business operations in the hotel industry in the Kumasi Metropolis of Ghana. The study adopted a combination of qualitative and quantitative approach. The study relied on primary data which was collected through field survey using semi-structured interview and questionnaires instruments. Descriptive statistics was used to analyse qualitative data whilst the qualitative data was analysed through deduction and inferences. The study revealed that that the implementation of yield management has positive impact in hotel business operations in the Kumasi Metropolis in terms of profitability competitive advantage operational efficiency productivity and cost saving. it is recommended that the hotel industry, particularly in the Kumasi Metropolis,  should invest in  information technology education as well as staff training to improve their skill capacity since effective practices YM depends on effective information system.

Models for the computation of opacity of mixtures

International Nuclear Information System (INIS)

Klapisch, Marcel; Busquet, Michel

2013-01-01

We compare four models for the partial densities of the components of mixtures. These models yield different opacities as shown on polystyrene, acrylic and polyimide in local thermodynamical equilibrium (LTE). Two of these models, the ‘whole volume partial pressure’ model (M1) and its modification (M2) are not thermodynamically consistent (TC). The other two models are TC and minimize free energy. M3, the ‘partial volume equal pressure’ model, uses equality of chemical potential. M4 uses commonality of free electron density. The latter two give essentially identical results in LTE, but M4’s convergence is slower. M4 is easily generalized to non-LTE conditions. Non-LTE effects are shown by the variation of the Planck mean opacity of the mixtures with temperature and density. (paper)

New models for predicting thermophysical properties of ionic liquid mixtures.

Science.gov (United States)

Huang, Ying; Zhang, Xiangping; Zhao, Yongsheng; Zeng, Shaojuan; Dong, Haifeng; Zhang, Suojiang

2015-10-28

Potential applications of ILs require the knowledge of the physicochemical properties of ionic liquid (IL) mixtures. In this work, a series of semi-empirical models were developed to predict the density, surface tension, heat capacity and thermal conductivity of IL mixtures. Each semi-empirical model only contains one new characteristic parameter, which can be determined using one experimental data point. In addition, as another effective tool, artificial neural network (ANN) models were also established. The two kinds of models were verified by a total of 2304 experimental data points for binary mixtures of ILs and molecular compounds. The overall average absolute deviations (AARDs) of both the semi-empirical and ANN models are less than 2%. Compared to previously reported models, these new semi-empirical models require fewer adjustable parameters and can be applied in a wider range of applications.

Modeling mixtures of thyroid gland function disruptors in a vertebrate alternative model, the zebrafish eleutheroembryo

International Nuclear Information System (INIS)

Thienpont, Benedicte; Barata, Carlos; Raldúa, Demetrio

2013-01-01

Maternal thyroxine (T4) plays an essential role in fetal brain development, and even mild and transitory deficits in free-T4 in pregnant women can produce irreversible neurological effects in their offspring. Women of childbearing age are daily exposed to mixtures of chemicals disrupting the thyroid gland function (TGFDs) through the diet, drinking water, air and pharmaceuticals, which has raised the highest concern for the potential additive or synergic effects on the development of mild hypothyroxinemia during early pregnancy. Recently we demonstrated that zebrafish eleutheroembryos provide a suitable alternative model for screening chemicals impairing the thyroid hormone synthesis. The present study used the intrafollicular T4-content (IT4C) of zebrafish eleutheroembryos as integrative endpoint for testing the hypotheses that the effect of mixtures of TGFDs with a similar mode of action [inhibition of thyroid peroxidase (TPO)] was well predicted by a concentration addition concept (CA) model, whereas the response addition concept (RA) model predicted better the effect of dissimilarly acting binary mixtures of TGFDs [TPO-inhibitors and sodium-iodide symporter (NIS)-inhibitors]. However, CA model provided better prediction of joint effects than RA in five out of the six tested mixtures. The exception being the mixture MMI (TPO-inhibitor)-KClO 4 (NIS-inhibitor) dosed at a fixed ratio of EC 10 that provided similar CA and RA predictions and hence it was difficult to get any conclusive result. There results support the phenomenological similarity criterion stating that the concept of concentration addition could be extended to mixture constituents having common apical endpoints or common adverse outcomes. - Highlights: • Potential synergic or additive effect of mixtures of chemicals on thyroid function. • Zebrafish as alternative model for testing the effect of mixtures of goitrogens. • Concentration addition seems to predict better the effect of mixtures of

Modeling mixtures of thyroid gland function disruptors in a vertebrate alternative model, the zebrafish eleutheroembryo

Energy Technology Data Exchange (ETDEWEB)

Thienpont, Benedicte; Barata, Carlos [Department of Environmental Chemistry, Institute of Environmental Assessment and Water Research (IDAEA, CSIC), Jordi Girona, 18-26, 08034 Barcelona (Spain); Raldúa, Demetrio, E-mail: drpqam@cid.csic.es [Department of Environmental Chemistry, Institute of Environmental Assessment and Water Research (IDAEA, CSIC), Jordi Girona, 18-26, 08034 Barcelona (Spain); Maladies Rares: Génétique et Métabolisme (MRGM), University of Bordeaux, EA 4576, F-33400 Talence (France)

2013-06-01

Maternal thyroxine (T4) plays an essential role in fetal brain development, and even mild and transitory deficits in free-T4 in pregnant women can produce irreversible neurological effects in their offspring. Women of childbearing age are daily exposed to mixtures of chemicals disrupting the thyroid gland function (TGFDs) through the diet, drinking water, air and pharmaceuticals, which has raised the highest concern for the potential additive or synergic effects on the development of mild hypothyroxinemia during early pregnancy. Recently we demonstrated that zebrafish eleutheroembryos provide a suitable alternative model for screening chemicals impairing the thyroid hormone synthesis. The present study used the intrafollicular T4-content (IT4C) of zebrafish eleutheroembryos as integrative endpoint for testing the hypotheses that the effect of mixtures of TGFDs with a similar mode of action [inhibition of thyroid peroxidase (TPO)] was well predicted by a concentration addition concept (CA) model, whereas the response addition concept (RA) model predicted better the effect of dissimilarly acting binary mixtures of TGFDs [TPO-inhibitors and sodium-iodide symporter (NIS)-inhibitors]. However, CA model provided better prediction of joint effects than RA in five out of the six tested mixtures. The exception being the mixture MMI (TPO-inhibitor)-KClO{sub 4} (NIS-inhibitor) dosed at a fixed ratio of EC{sub 10} that provided similar CA and RA predictions and hence it was difficult to get any conclusive result. There results support the phenomenological similarity criterion stating that the concept of concentration addition could be extended to mixture constituents having common apical endpoints or common adverse outcomes. - Highlights: • Potential synergic or additive effect of mixtures of chemicals on thyroid function. • Zebrafish as alternative model for testing the effect of mixtures of goitrogens. • Concentration addition seems to predict better the effect of

Bayesian Plackett-Luce Mixture Models for Partially Ranked Data.

Science.gov (United States)

Mollica, Cristina; Tardella, Luca

2017-06-01

The elicitation of an ordinal judgment on multiple alternatives is often required in many psychological and behavioral experiments to investigate preference/choice orientation of a specific population. The Plackett-Luce model is one of the most popular and frequently applied parametric distributions to analyze rankings of a finite set of items. The present work introduces a Bayesian finite mixture of Plackett-Luce models to account for unobserved sample heterogeneity of partially ranked data. We describe an efficient way to incorporate the latent group structure in the data augmentation approach and the derivation of existing maximum likelihood procedures as special instances of the proposed Bayesian method. Inference can be conducted with the combination of the Expectation-Maximization algorithm for maximum a posteriori estimation and the Gibbs sampling iterative procedure. We additionally investigate several Bayesian criteria for selecting the optimal mixture configuration and describe diagnostic tools for assessing the fitness of ranking distributions conditionally and unconditionally on the number of ranked items. The utility of the novel Bayesian parametric Plackett-Luce mixture for characterizing sample heterogeneity is illustrated with several applications to simulated and real preference ranked data. We compare our method with the frequentist approach and a Bayesian nonparametric mixture model both assuming the Plackett-Luce model as a mixture component. Our analysis on real datasets reveals the importance of an accurate diagnostic check for an appropriate in-depth understanding of the heterogenous nature of the partial ranking data.

Modeling the effects of binary mixtures on survival in time.

NARCIS (Netherlands)

Baas, J.; van Houte, B.P.P.; van Gestel, C.A.M.; Kooijman, S.A.L.M.

2007-01-01

In general, effects of mixtures are difficult to describe, and most of the models in use are descriptive in nature and lack a strong mechanistic basis. The aim of this experiment was to develop a process-based model for the interpretation of mixture toxicity measurements, with effects of binary

High-Dimensional Exploratory Item Factor Analysis by a Metropolis-Hastings Robbins-Monro Algorithm

Science.gov (United States)

Cai, Li

2010-01-01

A Metropolis-Hastings Robbins-Monro (MH-RM) algorithm for high-dimensional maximum marginal likelihood exploratory item factor analysis is proposed. The sequence of estimates from the MH-RM algorithm converges with probability one to the maximum likelihood solution. Details on the computer implementation of this algorithm are provided. The…

Environmental Awareness and School Sanitation in Calabar Metropolis of Cross Rivers State, Nigeria

Science.gov (United States)

Anijaobi-Idem, F. N.; Ukata, B. N.; Bisong, N. N

2015-01-01

This descriptive survey designed study explored the influence of environmental awareness on secondary school sanitation in Calabar Metropolis. 1 hypothesis was formulated to direct the investigation. 300 subjects made up of 30 principals and 270 teachers constituted the sample drawn from the population of principals and teachers in secondary…

Essays on the future in honor of Nick Metropolis

CERN Document Server

Rota, Gian-Carlo

2000-01-01

This collection represents a unique undertaking in scientific publishing to honor Nick Metropolis. Nick was the last survivor of the World War II Manhattan Project in Los Alamos, and was an important member of the Los Alamos national Laboratory until his death in October, 1999. In this volume, some of the leading scientists and humanists of our time have contributed essays related to their respective disciplines, exploring various aspects of future developments in science and society, philosophy, national security, nuclear power, pure and applied mathematics, physics and biology, particle physics, computing, and information science.

FAST MUSIC SPECTRUM PEAK SEARCH VIA METROPOLIS-HASTINGS SAMPLER

Institute of Scientific and Technical Information of China (English)

Guo Qinghua; Liao Guisheng

2005-01-01

A fast MUltiple SIgnal Classification (MUSIC) spectrum peak search algorithm is devised, which regards the power of the MUSIC spectrum function as target distribution up to a constant of proportionality, and uses Metropolis-Hastings (MH) sampler, one of the most popular Markov Chain Monte Carlo (MCMC) techniques, to sample from it. The proposed method reduces greatly the tremendous computation and storage costs in conventional MUSIC techniques i.e., about two and four orders of magnitude in computation and storage costs under the conditions of the experiment in the paper respectively.

KONVERGENSI ESTIMATOR DALAM MODEL MIXTURE BERBASIS MISSING DATA

Directory of Open Access Journals (Sweden)

N Dwidayati

2014-06-01

Full Text Available Abstrak __________________________________________________________________________________________ Model mixture dapat mengestimasi proporsi pasien yang sembuh (cured dan fungsi survival pasien tak sembuh (uncured. Pada kajian ini, model mixture dikembangkan untuk  analisis cure rate berbasis missing data. Ada beberapa metode yang dapat digunakan untuk analisis missing data. Salah satu metode yang dapat digunakan adalah Algoritma EM, Metode ini didasarkan pada 2 (dua langkah, yaitu: (1 Expectation Step dan (2 Maximization Step. Algoritma EM merupakan pendekatan iterasi untuk mempelajari model dari data dengan nilai hilang melalui 4 (empat langkah, yaitu(1 pilih himpunan inisial dari parameter untuk sebuah model, (2 tentukan nilai ekspektasi untuk data hilang, (3 buat induksi parameter model baru dari gabungan nilai ekspekstasi dan data asli, dan (4 jika parameter tidak converged, ulangi langkah 2 menggunakan model baru. Berdasar kajian yang dilakukan dapat ditunjukkan bahwa pada algoritma EM, log-likelihood untuk missing data mengalami kenaikan setelah dilakukan setiap iterasi dari algoritmanya. Dengan demikian berdasar algoritma EM, barisan likelihood konvergen jika likelihood terbatas ke bawah.   Abstract __________________________________________________________________________________________ Model mixture can estimate proportion of recovering patient  and function of patient survival do not recover. At this study, model mixture developed to analyse cure rate bases on missing data. There are some method which applicable to analyse missing data. One of method which can be applied is Algoritma EM, This method based on 2 ( two step, that is: ( 1 Expectation Step and ( 2 Maximization Step. EM Algorithm is approach of iteration to study model from data with value loses through 4 ( four step, yaitu(1 select;chooses initial gathering from parameter for a model, ( 2 determines expectation value for data to lose, ( 3 induce newfangled parameter

Behavioral pattern of commercial public transport passengers in Lagos metropolis

Directory of Open Access Journals (Sweden)

Oluwaseyi Joseph Afolabi

2017-05-01

Full Text Available This study examined the travel behavior of commercial public transport passengers in Lagos State, Nigeria. The descriptive research survey was used in order to assess the opinions of the respondents using the questionnaire. A total of 84 samples were used as representative population, while two null hypotheses were formulated and tested using the Pearson Product Moment Correlation Coefficient at 0.05 level of significant. The results that were obtained indicated that a positive correlation exists between frequency of   travel and commuters income in Lagos Metropolis and also that a positive correlation exists between frequency of travel and distance covered by commuters in Lagos Metropolis. Secondary data was also sourced to serve as complement to the primary data, thus allowing for a robust research. Descriptive statistical tools such as percentages were also adopted to present the socio-economic characteristics in the area. Findings showed that about 57% of sampled population are male, 62 % are civil servants, 48% of respondents travel for business purposes. Also, that majority of the respondents (50% said that the commercial public transport is highly prone to accident, while about 64% of the respondents commute on daily basis. It was established that lack of transport infrastructure coupled with poor road maintenance were seen as the leading causes of inaccessibility of the area.

Challenges in modelling the random structure correctly in growth mixture models and the impact this has on model mixtures.

Science.gov (United States)

Gilthorpe, M S; Dahly, D L; Tu, Y K; Kubzansky, L D; Goodman, E

2014-06-01

Lifecourse trajectories of clinical or anthropological attributes are useful for identifying how our early-life experiences influence later-life morbidity and mortality. Researchers often use growth mixture models (GMMs) to estimate such phenomena. It is common to place constrains on the random part of the GMM to improve parsimony or to aid convergence, but this can lead to an autoregressive structure that distorts the nature of the mixtures and subsequent model interpretation. This is especially true if changes in the outcome within individuals are gradual compared with the magnitude of differences between individuals. This is not widely appreciated, nor is its impact well understood. Using repeat measures of body mass index (BMI) for 1528 US adolescents, we estimated GMMs that required variance-covariance constraints to attain convergence. We contrasted constrained models with and without an autocorrelation structure to assess the impact this had on the ideal number of latent classes, their size and composition. We also contrasted model options using simulations. When the GMM variance-covariance structure was constrained, a within-class autocorrelation structure emerged. When not modelled explicitly, this led to poorer model fit and models that differed substantially in the ideal number of latent classes, as well as class size and composition. Failure to carefully consider the random structure of data within a GMM framework may lead to erroneous model inferences, especially for outcomes with greater within-person than between-person homogeneity, such as BMI. It is crucial to reflect on the underlying data generation processes when building such models.

Nonparametric Identification and Estimation of Finite Mixture Models of Dynamic Discrete Choices

OpenAIRE

Hiroyuki Kasahara; Katsumi Shimotsu

2006-01-01

In dynamic discrete choice analysis, controlling for unobserved heterogeneity is an important issue, and finite mixture models provide flexible ways to account for unobserved heterogeneity. This paper studies nonparametric identifiability of type probabilities and type-specific component distributions in finite mixture models of dynamic discrete choices. We derive sufficient conditions for nonparametric identification for various finite mixture models of dynamic discrete choices used in appli...

A study of finite mixture model: Bayesian approach on financial time series data

Science.gov (United States)

Phoong, Seuk-Yen; Ismail, Mohd Tahir

2014-07-01

Recently, statistician have emphasized on the fitting finite mixture model by using Bayesian method. Finite mixture model is a mixture of distributions in modeling a statistical distribution meanwhile Bayesian method is a statistical method that use to fit the mixture model. Bayesian method is being used widely because it has asymptotic properties which provide remarkable result. In addition, Bayesian method also shows consistency characteristic which means the parameter estimates are close to the predictive distributions. In the present paper, the number of components for mixture model is studied by using Bayesian Information Criterion. Identify the number of component is important because it may lead to an invalid result. Later, the Bayesian method is utilized to fit the k-component mixture model in order to explore the relationship between rubber price and stock market price for Malaysia, Thailand, Philippines and Indonesia. Lastly, the results showed that there is a negative effect among rubber price and stock market price for all selected countries.

Robust non-rigid point set registration using student's-t mixture model.

Directory of Open Access Journals (Sweden)

Zhiyong Zhou

Full Text Available The Student's-t mixture model, which is heavily tailed and more robust than the Gaussian mixture model, has recently received great attention on image processing. In this paper, we propose a robust non-rigid point set registration algorithm using the Student's-t mixture model. Specifically, first, we consider the alignment of two point sets as a probability density estimation problem and treat one point set as Student's-t mixture model centroids. Then, we fit the Student's-t mixture model centroids to the other point set which is treated as data. Finally, we get the closed-form solutions of registration parameters, leading to a computationally efficient registration algorithm. The proposed algorithm is especially effective for addressing the non-rigid point set registration problem when significant amounts of noise and outliers are present. Moreover, less registration parameters have to be set manually for our algorithm compared to the popular coherent points drift (CPD algorithm. We have compared our algorithm with other state-of-the-art registration algorithms on both 2D and 3D data with noise and outliers, where our non-rigid registration algorithm showed accurate results and outperformed the other algorithms.

Hydrogenic ionization model for mixtures in non-LTE plasmas

International Nuclear Information System (INIS)

Djaoui, A.

1999-01-01

The Hydrogenic Ionization Model for Mixtures (HIMM) is a non-Local Thermodynamic Equilibrium (non-LTE), time-dependent ionization model for laser-produced plasmas containing mixtures of elements (species). In this version, both collisional and radiative rates are taken into account. An ionization distribution for each species which is consistent with the ambient electron density is obtained by use of an iterative procedure in a single calculation for all species. Energy levels for each shell having a given principal quantum number and for each ion stage of each species in the mixture are calculated using screening constants. Steady-state non-LTE as well as LTE solutions are also provided. The non-LTE rate equations converge to the LTE solution at sufficiently high densities or as the radiation temperature approaches the electron temperature. The model is particularly useful at low temperatures where convergence problems are usually encountered in our previous models. We apply our model to typical situation in x-ray laser research, laser-produced plasmas and inertial confinement fusion. Our results compare well with previously published results for a selenium plasma. (author)

Nonlinear Structured Growth Mixture Models in M"plus" and OpenMx

Science.gov (United States)

Grimm, Kevin J.; Ram, Nilam; Estabrook, Ryne

2010-01-01

Growth mixture models (GMMs; B. O. Muthen & Muthen, 2000; B. O. Muthen & Shedden, 1999) are a combination of latent curve models (LCMs) and finite mixture models to examine the existence of latent classes that follow distinct developmental patterns. GMMs are often fit with linear, latent basis, multiphase, or polynomial change models…

Direct Importance Estimation with Gaussian Mixture Models

Science.gov (United States)

Yamada, Makoto; Sugiyama, Masashi

The ratio of two probability densities is called the importance and its estimation has gathered a great deal of attention these days since the importance can be used for various data processing purposes. In this paper, we propose a new importance estimation method using Gaussian mixture models (GMMs). Our method is an extention of the Kullback-Leibler importance estimation procedure (KLIEP), an importance estimation method using linear or kernel models. An advantage of GMMs is that covariance matrices can also be learned through an expectation-maximization procedure, so the proposed method — which we call the Gaussian mixture KLIEP (GM-KLIEP) — is expected to work well when the true importance function has high correlation. Through experiments, we show the validity of the proposed approach.

Employee Motivation on the Organisational Growth of Printing Industry in the Kumasi Metropolis

Science.gov (United States)

Enninful, Ebenezer Kofi; Boakye-Amponsah, Abraham; Osei-Poku, Patrick

2015-01-01

The printing industry is supposed to be a major contributor to Ghana's development through employment creation and the enhancement of information to the general public. The main purpose of the study was to assess employee motivation on the printing industry within Kumasi Metropolis. The study employed both the quantitative and qualitative surveys…

Combinatorial bounds on the α-divergence of univariate mixture models

KAUST Repository

Nielsen, Frank

2017-06-20

We derive lower- and upper-bounds of α-divergence between univariate mixture models with components in the exponential family. Three pairs of bounds are presented in order with increasing quality and increasing computational cost. They are verified empirically through simulated Gaussian mixture models. The presented methodology generalizes to other divergence families relying on Hellinger-type integrals.

Communication: Modeling electrolyte mixtures with concentration dependent dielectric permittivity

Science.gov (United States)

Chen, Hsieh; Panagiotopoulos, Athanassios Z.

2018-01-01

We report a new implicit-solvent simulation model for electrolyte mixtures based on the concept of concentration dependent dielectric permittivity. A combining rule is found to predict the dielectric permittivity of electrolyte mixtures based on the experimentally measured dielectric permittivity for pure electrolytes as well as the mole fractions of the electrolytes in mixtures. Using grand canonical Monte Carlo simulations, we demonstrate that this approach allows us to accurately reproduce the mean ionic activity coefficients of NaCl in NaCl-CaCl2 mixtures at ionic strengths up to I = 3M. These results are important for thermodynamic studies of geologically relevant brines and physiological fluids.

A general mixture model and its application to coastal sandbar migration simulation

Science.gov (United States)

Liang, Lixin; Yu, Xiping

2017-04-01

A mixture model for general description of sediment laden flows is developed and then applied to coastal sandbar migration simulation. Firstly the mixture model is derived based on the Eulerian-Eulerian approach of the complete two-phase flow theory. The basic equations of the model include the mass and momentum conservation equations for the water-sediment mixture and the continuity equation for sediment concentration. The turbulent motion of the mixture is formulated for the fluid and the particles respectively. A modified k-ɛ model is used to describe the fluid turbulence while an algebraic model is adopted for the particles. A general formulation for the relative velocity between the two phases in sediment laden flows, which is derived by manipulating the momentum equations of the enhanced two-phase flow model, is incorporated into the mixture model. A finite difference method based on SMAC scheme is utilized for numerical solutions. The model is validated by suspended sediment motion in steady open channel flows, both in equilibrium and non-equilibrium state, and in oscillatory flows as well. The computed sediment concentrations, horizontal velocity and turbulence kinetic energy of the mixture are all shown to be in good agreement with experimental data. The mixture model is then applied to the study of sediment suspension and sandbar migration in surf zones under a vertical 2D framework. The VOF method for the description of water-air free surface and topography reaction model is coupled. The bed load transport rate and suspended load entrainment rate are all decided by the sea bed shear stress, which is obtained from the boundary layer resolved mixture model. The simulation results indicated that, under small amplitude regular waves, erosion occurred on the sandbar slope against the wave propagation direction, while deposition dominated on the slope towards wave propagation, indicating an onshore migration tendency. The computation results also shows that

Optimal designs for linear mixture models

NARCIS (Netherlands)

Mendieta, E.J.; Linssen, H.N.; Doornbos, R.

1975-01-01

In a recent paper Snee and Marquardt (1974) considered designs for linear mixture models, where the components are subject to individual lower and/or upper bounds. When the number of components is large their algorithm XVERT yields designs far too extensive for practical purposes. The purpose of

Flexible Mixture-Amount Models for Business and Industry Using Gaussian Processes

NARCIS (Netherlands)

A. Ruseckaite (Aiste); D. Fok (Dennis); P.P. Goos (Peter)

2016-01-01

markdownabstractMany products and services can be described as mixtures of ingredients whose proportions sum to one. Specialized models have been developed for linking the mixture proportions to outcome variables, such as preference, quality and liking. In many scenarios, only the mixture

Optimization and benchmarking of a perturbative Metropolis Monte Carlo quantum mechanics/molecular mechanics program.

Science.gov (United States)

Feldt, Jonas; Miranda, Sebastião; Pratas, Frederico; Roma, Nuno; Tomás, Pedro; Mata, Ricardo A

2017-12-28

In this work, we present an optimized perturbative quantum mechanics/molecular mechanics (QM/MM) method for use in Metropolis Monte Carlo simulations. The model adopted is particularly tailored for the simulation of molecular systems in solution but can be readily extended to other applications, such as catalysis in enzymatic environments. The electrostatic coupling between the QM and MM systems is simplified by applying perturbation theory to estimate the energy changes caused by a movement in the MM system. This approximation, together with the effective use of GPU acceleration, leads to a negligible added computational cost for the sampling of the environment. Benchmark calculations are carried out to evaluate the impact of the approximations applied and the overall computational performance.

Sound speed models for a noncondensible gas-steam-water mixture

International Nuclear Information System (INIS)

Ransom, V.H.; Trapp, J.A.

1984-01-01

An analytical expression is derived for the homogeneous equilibrium speed of sound in a mixture of noncondensible gas, steam, and water. The expression is based on the Gibbs free energy interphase equilibrium condition for a Gibbs-Dalton mixture in contact with a pure liquid phase. Several simplified models are discussed including the homogeneous frozen model. These idealized models can be used as a reference for data comparison and also serve as a basis for empirically corrected nonhomogeneous and nonequilibrium models

Optimal designs for linear mixture models

NARCIS (Netherlands)

Mendieta, E.J.; Linssen, H.N.; Doornbos, R.

1975-01-01

In a recent paper Snee and Marquardt [8] considered designs for linear mixture models, where the components are subject to individual lower and/or upper bounds. When the number of components is large their algorithm XVERT yields designs far too extensive for practical purposes. The purpose of this

On Two Mixture-Based Clustering Approaches Used in Modeling an Insurance Portfolio

Directory of Open Access Journals (Sweden)

Tatjana Miljkovic

2018-05-01

Full Text Available We review two complementary mixture-based clustering approaches for modeling unobserved heterogeneity in an insurance portfolio: the generalized linear mixed cluster-weighted model (CWM and mixture-based clustering for an ordered stereotype model (OSM. The latter is for modeling of ordinal variables, and the former is for modeling losses as a function of mixed-type of covariates. The article extends the idea of mixture modeling to a multivariate classification for the purpose of testing unobserved heterogeneity in an insurance portfolio. The application of both methods is illustrated on a well-known French automobile portfolio, in which the model fitting is performed using the expectation-maximization (EM algorithm. Our findings show that these mixture-based clustering methods can be used to further test unobserved heterogeneity in an insurance portfolio and as such may be considered in insurance pricing, underwriting, and risk management.

Analysis of Solid Waste Management Logistics and Its Attendant Challenges in Lagos Metropolis

Directory of Open Access Journals (Sweden)

Boye Benedict Ayantoyinbo

2018-06-01

Full Text Available This study examined the relationship between waste management logistics and identified metrics for waste management logistics performance. Secondly, the study assessed the various challenges inhibiting the performance of LAWMA in the State. Random table sampling and purposive sampling were used to select 47 waste collection centres with 10 questionnaires distributed per centre (470 in total across the 20 Local Government Areas (LGA in Lagos State. However, only 339 questionnaires were retrieved from the sampled population. Multiple regression analysis was used to predict the relationship between waste management logistics and identified metrics for waste logistics performance. Descriptive statistics was used to explain the challenges of the Lagos State Waste Management Authority (LAWMA. The results established that the volume of solid waste and commitment of staff are crucial to waste management logistics and one factor that strongly affects waste logistics is traffic in the metropolis. Conclusively, waste collection turnaround must be increased and government and private investors should provide enabling infrastructure and trained personnel for effective solid waste management in Lagos metropolis.

Prior selection for Gumbel distribution parameters using multiple-try metropolis algorithm for monthly maxima PM10 data

Science.gov (United States)

Amin, Nor Azrita Mohd; Adam, Mohd Bakri; Ibrahim, Noor Akma

2014-09-01

The Multiple-try Metropolis (MTM) algorithm is the new alternatives in the field of Bayesian extremes for summarizing the posterior distribution. MTM produce efficient estimation scheme for modelling extreme data in term of the convergence and small burn-in periods. The main objective is to explore the accuracy of the parameter estimation to the change of priors and compare the results with a classical likelihood-based analysis. Focus is on modelling the extreme data based on block maxima approach using Gumbel distribution. The comparative study between MTM and MLE is shown by the numerical problems. Several goodness of fit tests are compute for selecting the best model. The application is on the monthly maxima PM10 data for Johor state.

Tourists' perceptions of the quality of public transportation services in the Accra metropolis: a Servqual approach

Directory of Open Access Journals (Sweden)

R. Y. Nutsugbodo

2013-01-01

Full Text Available All over the world, commuters (tourists are entreating public transport service providers to ensure that they provide quality service to their clienteles and not to be interested in only the financial gains. This study sought to examine tourists’ perception of the quality of public transportation services within the Accra Metropolis, Ghana using a SERVQUAL approach. The SERVQUAL scale was modified to aid in evaluating how tourists perceive public transportation services within this jurisdiction. Accidental sampling procedure was used to collect samples from 200 tourists at selected transport terminals. The study concluded that the tourists had a negative perception of public transport services within the metropolis. The implication for this study is that it is intended to provide strong basis for more in-depth studies into this phenomenon.

Modeling phase equilibria for acid gas mixtures using the CPA equation of state. Part II: Binary mixtures with CO2

DEFF Research Database (Denmark)

Tsivintzelis, Ioannis; Kontogeorgis, Georgios; Michelsen, Michael Locht

2011-01-01

In Part I of this series of articles, the study of H2S mixtures has been presented with CPA. In this study the phase behavior of CO2 containing mixtures is modeled. Binary mixtures with water, alcohols, glycols and hydrocarbons are investigated. Both phase equilibria (vapor–liquid and liquid–liqu...

Mixture estimation with state-space components and Markov model of switching

Czech Academy of Sciences Publication Activity Database

Nagy, Ivan; Suzdaleva, Evgenia

2013-01-01

Roč. 37, č. 24 (2013), s. 9970-9984 ISSN 0307-904X R&D Projects: GA TA ČR TA01030123 Institutional support: RVO:67985556 Keywords : probabilistic dynamic mixtures, * probability density function * state-space models * recursive mixture estimation * Bayesian dynamic decision making under uncertainty * Kerridge inaccuracy Subject RIV: BC - Control Systems Theory Impact factor: 2.158, year: 2013 http://library.utia.cas.cz/separaty/2013/AS/nagy-mixture estimation with state-space components and markov model of switching.pdf

Introduction to the special section on mixture modeling in personality assessment.

Science.gov (United States)

Wright, Aidan G C; Hallquist, Michael N

2014-01-01

Latent variable models offer a conceptual and statistical framework for evaluating the underlying structure of psychological constructs, including personality and psychopathology. Complex structures that combine or compare categorical and dimensional latent variables can be accommodated using mixture modeling approaches, which provide a powerful framework for testing nuanced theories about psychological structure. This special series includes introductory primers on cross-sectional and longitudinal mixture modeling, in addition to empirical examples applying these techniques to real-world data collected in clinical settings. This group of articles is designed to introduce personality assessment scientists and practitioners to a general latent variable framework that we hope will stimulate new research and application of mixture models to the assessment of personality and its pathology.

The R Package bgmm : Mixture Modeling with Uncertain Knowledge

Directory of Open Access Journals (Sweden)

Przemys law Biecek

2012-04-01

Full Text Available Classical supervised learning enjoys the luxury of accessing the true known labels for the observations in a modeled dataset. Real life, however, poses an abundance of problems, where the labels are only partially defined, i.e., are uncertain and given only for a subsetof observations. Such partial labels can occur regardless of the knowledge source. For example, an experimental assessment of labels may have limited capacity and is prone to measurement errors. Also expert knowledge is often restricted to a specialized area and is thus unlikely to provide trustworthy labels for all observations in the dataset. Partially supervised mixture modeling is able to process such sparse and imprecise input. Here, we present an R package calledbgmm, which implements two partially supervised mixture modeling methods: soft-label and belief-based modeling. For completeness, we equipped the package also with the functionality of unsupervised, semi- and fully supervised mixture modeling. On real data we present the usage of bgmm for basic model-fitting in all modeling variants. The package can be applied also to selection of the best-fitting from a set of models with different component numbers or constraints on their structures. This functionality is presented on an artificial dataset, which can be simulated in bgmm from a distribution defined by a given model.

New Flexible Models and Design Construction Algorithms for Mixtures and Binary Dependent Variables

NARCIS (Netherlands)

A. Ruseckaite (Aiste)

2017-01-01

markdownabstractThis thesis discusses new mixture(-amount) models, choice models and the optimal design of experiments. Two chapters of the thesis relate to the so-called mixture, which is a product or service whose ingredients’ proportions sum to one. The thesis begins by introducing mixture

Response Mixture Modeling: Accounting for Heterogeneity in Item Characteristics across Response Times.

Science.gov (United States)

Molenaar, Dylan; de Boeck, Paul

2018-06-01

In item response theory modeling of responses and response times, it is commonly assumed that the item responses have the same characteristics across the response times. However, heterogeneity might arise in the data if subjects resort to different response processes when solving the test items. These differences may be within-subject effects, that is, a subject might use a certain process on some of the items and a different process with different item characteristics on the other items. If the probability of using one process over the other process depends on the subject's response time, within-subject heterogeneity of the item characteristics across the response times arises. In this paper, the method of response mixture modeling is presented to account for such heterogeneity. Contrary to traditional mixture modeling where the full response vectors are classified, response mixture modeling involves classification of the individual elements in the response vector. In a simulation study, the response mixture model is shown to be viable in terms of parameter recovery. In addition, the response mixture model is applied to a real dataset to illustrate its use in investigating within-subject heterogeneity in the item characteristics across response times.

Modeling Phase Equilibria for Acid Gas Mixtures Using the CPA Equation of State. I. Mixtures with H2S

DEFF Research Database (Denmark)

Tsivintzelis, Ioannis; Kontogeorgis, Georgios; Michelsen, Michael Locht

2010-01-01

(water, methanol, and glycols) are modeled assuming presence or not of cross-association interactions. Such interactions are accounted for using either a combining rule or a cross-solvation energy obtained from spectroscopic data. Using the parameters obtained from the binary systems, one ternary......The Cubic-Plus-Association (CPA) equation of state is applied to a large variety of mixtures containing H2S, which are of interest in the oil and gas industry. Binary H2S mixtures with alkanes, CO2, water, methanol, and glycols are first considered. The interactions of H2S with polar compounds...... and three quaternary mixtures are considered. It is shown that overall excellent correlation for binary, mixtures and satisfactory prediction results for multicomponent systems are obtained. There are significant differences between the various modeling approaches and the best results are obtained when...

Mixture modeling methods for the assessment of normal and abnormal personality, part II: longitudinal models.

Science.gov (United States)

Wright, Aidan G C; Hallquist, Michael N

2014-01-01

Studying personality and its pathology as it changes, develops, or remains stable over time offers exciting insight into the nature of individual differences. Researchers interested in examining personal characteristics over time have a number of time-honored analytic approaches at their disposal. In recent years there have also been considerable advances in person-oriented analytic approaches, particularly longitudinal mixture models. In this methodological primer we focus on mixture modeling approaches to the study of normative and individual change in the form of growth mixture models and ipsative change in the form of latent transition analysis. We describe the conceptual underpinnings of each of these models, outline approaches for their implementation, and provide accessible examples for researchers studying personality and its assessment.

Estimating Lion Abundance using N-mixture Models for Social Species.

Science.gov (United States)

Belant, Jerrold L; Bled, Florent; Wilton, Clay M; Fyumagwa, Robert; Mwampeta, Stanslaus B; Beyer, Dean E

2016-10-27

Declining populations of large carnivores worldwide, and the complexities of managing human-carnivore conflicts, require accurate population estimates of large carnivores to promote their long-term persistence through well-informed management We used N-mixture models to estimate lion (Panthera leo) abundance from call-in and track surveys in southeastern Serengeti National Park, Tanzania. Because of potential habituation to broadcasted calls and social behavior, we developed a hierarchical observation process within the N-mixture model conditioning lion detectability on their group response to call-ins and individual detection probabilities. We estimated 270 lions (95% credible interval = 170-551) using call-ins but were unable to estimate lion abundance from track data. We found a weak negative relationship between predicted track density and predicted lion abundance from the call-in surveys. Luminosity was negatively correlated with individual detection probability during call-in surveys. Lion abundance and track density were influenced by landcover, but direction of the corresponding effects were undetermined. N-mixture models allowed us to incorporate multiple parameters (e.g., landcover, luminosity, observer effect) influencing lion abundance and probability of detection directly into abundance estimates. We suggest that N-mixture models employing a hierarchical observation process can be used to estimate abundance of other social, herding, and grouping species.

On the Bayesian calibration of computer model mixtures through experimental data, and the design of predictive models

Science.gov (United States)

Karagiannis, Georgios; Lin, Guang

2017-08-01

For many real systems, several computer models may exist with different physics and predictive abilities. To achieve more accurate simulations/predictions, it is desirable for these models to be properly combined and calibrated. We propose the Bayesian calibration of computer model mixture method which relies on the idea of representing the real system output as a mixture of the available computer model outputs with unknown input dependent weight functions. The method builds a fully Bayesian predictive model as an emulator for the real system output by combining, weighting, and calibrating the available models in the Bayesian framework. Moreover, it fits a mixture of calibrated computer models that can be used by the domain scientist as a mean to combine the available computer models, in a flexible and principled manner, and perform reliable simulations. It can address realistic cases where one model may be more accurate than the others at different input values because the mixture weights, indicating the contribution of each model, are functions of the input. Inference on the calibration parameters can consider multiple computer models associated with different physics. The method does not require knowledge of the fidelity order of the models. We provide a technique able to mitigate the computational overhead due to the consideration of multiple computer models that is suitable to the mixture model framework. We implement the proposed method in a real-world application involving the Weather Research and Forecasting large-scale climate model.

Kyiv Small Rivers in Metropolis Water Objects System

Science.gov (United States)

Krelshteyn, P.; Dubnytska, M.

2017-12-01

The article answers the question, what really are the small underground rivers with artificial watercourses: water bodies or city engineering infrastructure objects? The place of such rivers in metropolis water objects system is identified. The ecological state and the degree of urbanization of small rivers, as well as the dynamics of change in these indicators are analysed on the Kiev city example with the help of water objects cadastre. It was found that the registration of small rivers in Kyiv city is not conducted, and the summary information on such water objects is absent and is not taken into account when making managerial decisions at the urban level. To solve this problem, we propose to create some water bodies accounting system (water cadastre).

Evaluation of thermodynamic properties of fluid mixtures by PC-SAFT model

International Nuclear Information System (INIS)

Almasi, Mohammad

2014-01-01

Experimental and calculated partial molar volumes (V ¯ m,1 ) of MIK with (♦) 2-PrOH, (♢) 2-BuOH, (●) 2-PenOH at T = 298.15 K. (—) PC-SAFT model. - Highlights: • Densities and viscosities of the mixtures (MIK + 2-alkanols) were measured. • PC-SAFT model was applied to correlate the volumetric properties of binary mixtures. • Agreement between experimental data and calculated values by PC-SAFT model is good. - Abstract: Densities and viscosities of binary mixtures of methyl isobutyl ketone (MIK) with polar solvents namely, 2-propanol, 2-butanol and 2-pentanol, were measured at 7 temperatures (293.15–323.15 K) over the entire range of composition. Using the experimental data, excess molar volumes V m E , isobaric thermal expansivity α p , partial molar volumes V ¯ m,i and viscosity deviations Δη, have been calculated due to their importance in the study of specific molecular interactions. The observed negative and positive values of deviation/excess parameters were explained on the basis of the intermolecular interactions occur in these mixtures. The Perturbed Chain Statistical Association Fluid Theory (PC-SAFT) has been used to correlate the volumetric behavior of the mixtures

Detecting Housing Submarkets using Unsupervised Learning of Finite Mixture Models

DEFF Research Database (Denmark)

Ntantamis, Christos

association between prices that can be attributed, among others, to unobserved neighborhood effects. In this paper, a model of spatial association for housing markets is introduced. Spatial association is treated in the context of spatial heterogeneity, which is explicitly modeled in both a global and a local....... The identified mixtures are considered as the different spatial housing submarkets. The main advantage of the approach is that submarkets are recovered by the housing prices data compared to submarkets imposed by administrative or geographical criteria. The Finite Mixture Model is estimated using the Figueiredo...

78 FR 59731 - License Amendment Request for Closure of Calcium Fluoride Ponds at Honeywell Metropolis Works...

Science.gov (United States)

2013-09-27

... Closure of Calcium Fluoride Ponds at Honeywell Metropolis Works, Honeywell International, Inc. AGENCY... Federal Regulations (10 CFR) to approve the closure of the calcium fluoride ponds in-place, by... areas: Land use; transportation; geology, soils and seismology; hydrology; ecological resources; air...

Phylogenetic mixtures and linear invariants for equal input models.

Science.gov (United States)

Casanellas, Marta; Steel, Mike

2017-04-01

The reconstruction of phylogenetic trees from molecular sequence data relies on modelling site substitutions by a Markov process, or a mixture of such processes. In general, allowing mixed processes can result in different tree topologies becoming indistinguishable from the data, even for infinitely long sequences. However, when the underlying Markov process supports linear phylogenetic invariants, then provided these are sufficiently informative, the identifiability of the tree topology can be restored. In this paper, we investigate a class of processes that support linear invariants once the stationary distribution is fixed, the 'equal input model'. This model generalizes the 'Felsenstein 1981' model (and thereby the Jukes-Cantor model) from four states to an arbitrary number of states (finite or infinite), and it can also be described by a 'random cluster' process. We describe the structure and dimension of the vector spaces of phylogenetic mixtures and of linear invariants for any fixed phylogenetic tree (and for all trees-the so called 'model invariants'), on any number n of leaves. We also provide a precise description of the space of mixtures and linear invariants for the special case of [Formula: see text] leaves. By combining techniques from discrete random processes and (multi-) linear algebra, our results build on a classic result that was first established by James Lake (Mol Biol Evol 4:167-191, 1987).

Volunteer tourists' motivations for choosing homestay in the Kumasi Metropolis of Ghana

Directory of Open Access Journals (Sweden)

Elizabeth Agyeiwaah

2013-01-01

Full Text Available Volunteer tourists’ motivations for choosing homestay accommodation have received little attention from researchers. The objective of this research was to explore the push and pull factors that account for volunteer tourists’ choice of homestay in the Kumasi Metropolis of Ghana. Insights gained from this study will inure better understanding of volunteer tourists’ behaviour to ensure appropriate service delivery by homestay providers. With the help of the "Push and Pull" motivation model by Dann (1977, the findings indicated two main push factors: socio-cultural immersion and economic value; and pull factors: environmental sensitiveness and community service and development. The study found that the most important push and pull factors as perceived by volunteers to Ghana are socio-cultural immersion and environmental sensitiveness. The study confirms the supporting role of homestay for volunteer tourists to Ghana. In the end, the implications of this study are discussed.

Beta Regression Finite Mixture Models of Polarization and Priming

Science.gov (United States)

Smithson, Michael; Merkle, Edgar C.; Verkuilen, Jay

2011-01-01

This paper describes the application of finite-mixture general linear models based on the beta distribution to modeling response styles, polarization, anchoring, and priming effects in probability judgments. These models, in turn, enhance our capacity for explicitly testing models and theories regarding the aforementioned phenomena. The mixture…

A predictive model of natural gas mixture combustion in internal combustion engines

Directory of Open Access Journals (Sweden)

Henry Espinoza

2007-05-01

Full Text Available This study shows the development of a predictive natural gas mixture combustion model for conventional com-bustion (ignition engines. The model was based on resolving two areas; one having unburned combustion mixture and another having combustion products. Energy and matter conservation equations were solved for each crankshaft turn angle for each area. Nonlinear differential equations for each phase’s energy (considering compression, combustion and expansion were solved by applying the fourth-order Runge-Kutta method. The model also enabled studying different natural gas components’ composition and evaluating combustion in the presence of dry and humid air. Validation results are shown with experimental data, demonstrating the software’s precision and accuracy in the results so produced. The results showed cylinder pressure, unburned and burned mixture temperature, burned mass fraction and combustion reaction heat for the engine being modelled using a natural gas mixture.

A Dirichlet process mixture of generalized Dirichlet distributions for proportional data modeling.

Science.gov (United States)

Bouguila, Nizar; Ziou, Djemel

2010-01-01

In this paper, we propose a clustering algorithm based on both Dirichlet processes and generalized Dirichlet distribution which has been shown to be very flexible for proportional data modeling. Our approach can be viewed as an extension of the finite generalized Dirichlet mixture model to the infinite case. The extension is based on nonparametric Bayesian analysis. This clustering algorithm does not require the specification of the number of mixture components to be given in advance and estimates it in a principled manner. Our approach is Bayesian and relies on the estimation of the posterior distribution of clusterings using Gibbs sampler. Through some applications involving real-data classification and image databases categorization using visual words, we show that clustering via infinite mixture models offers a more powerful and robust performance than classic finite mixtures.

A quantitative trait locus mixture model that avoids spurious LOD score peaks.

Science.gov (United States)

Feenstra, Bjarke; Skovgaard, Ib M

2004-06-01

In standard interval mapping of quantitative trait loci (QTL), the QTL effect is described by a normal mixture model. At any given location in the genome, the evidence of a putative QTL is measured by the likelihood ratio of the mixture model compared to a single normal distribution (the LOD score). This approach can occasionally produce spurious LOD score peaks in regions of low genotype information (e.g., widely spaced markers), especially if the phenotype distribution deviates markedly from a normal distribution. Such peaks are not indicative of a QTL effect; rather, they are caused by the fact that a mixture of normals always produces a better fit than a single normal distribution. In this study, a mixture model for QTL mapping that avoids the problems of such spurious LOD score peaks is presented.

Color Texture Segmentation by Decomposition of Gaussian Mixture Model

Czech Academy of Sciences Publication Activity Database

Grim, Jiří; Somol, Petr; Haindl, Michal; Pudil, Pavel

2006-01-01

Roč. 19, č. 4225 (2006), s. 287-296 ISSN 0302-9743. [Iberoamerican Congress on Pattern Recognition. CIARP 2006 /11./. Cancun, 14.11.2006-17.11.2006] R&D Projects: GA AV ČR 1ET400750407; GA MŠk 1M0572; GA MŠk 2C06019 EU Projects: European Commission(XE) 507752 - MUSCLE Institutional research plan: CEZ:AV0Z10750506 Keywords : texture segmentation * gaussian mixture model * EM algorithm Subject RIV: IN - Informatics, Computer Science Impact factor: 0.402, year: 2005 http://library.utia.cas.cz/separaty/historie/grim-color texture segmentation by decomposition of gaussian mixture model.pdf

Supervised Gaussian mixture model based remote sensing image ...

African Journals Online (AJOL)

Using the supervised classification technique, both simulated and empirical satellite remote sensing data are used to train and test the Gaussian mixture model algorithm. For the purpose of validating the experiment, the resulting classified satellite image is compared with the ground truth data. For the simulated modelling, ...

Three Different Ways of Calibrating Burger's Contact Model for Viscoelastic Model of Asphalt Mixtures by Discrete Element Method

DEFF Research Database (Denmark)

Feng, Huan; Pettinari, Matteo; Stang, Henrik

2016-01-01

modulus. Three different approaches have been used and compared for calibrating the Burger's contact model. Values of the dynamic modulus and phase angle of asphalt mixtures were predicted by conducting DE simulation under dynamic strain control loading. The excellent agreement between the predicted......In this paper the viscoelastic behavior of asphalt mixture was investigated by employing a three-dimensional discrete element method. Combined with Burger's model, three contact models were used for the construction of constitutive asphalt mixture model with viscoelastic properties...

Maximum likelihood pixel labeling using a spatially variant finite mixture model

International Nuclear Information System (INIS)

Gopal, S.S.; Hebert, T.J.

1996-01-01

We propose a spatially-variant mixture model for pixel labeling. Based on this spatially-variant mixture model we derive an expectation maximization algorithm for maximum likelihood estimation of the pixel labels. While most algorithms using mixture models entail the subsequent use of a Bayes classifier for pixel labeling, the proposed algorithm yields maximum likelihood estimates of the labels themselves and results in unambiguous pixel labels. The proposed algorithm is fast, robust, easy to implement, flexible in that it can be applied to any arbitrary image data where the number of classes is known and, most importantly, obviates the need for an explicit labeling rule. The algorithm is evaluated both quantitatively and qualitatively on simulated data and on clinical magnetic resonance images of the human brain

Metis: A Pure Metropolis Markov Chain Monte Carlo Bayesian Inference Library

Energy Technology Data Exchange (ETDEWEB)

Bates, Cameron Russell [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Mckigney, Edward Allen [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2018-01-09

The use of Bayesian inference in data analysis has become the standard for large scienti c experiments [1, 2]. The Monte Carlo Codes Group(XCP-3) at Los Alamos has developed a simple set of algorithms currently implemented in C++ and Python to easily perform at-prior Markov Chain Monte Carlo Bayesian inference with pure Metropolis sampling. These implementations are designed to be user friendly and extensible for customization based on speci c application requirements. This document describes the algorithmic choices made and presents two use cases.

Metropolis-Hastings Algorithms in Function Space for Bayesian Inverse Problems

KAUST Repository

Ernst, Oliver

2015-01-07

We consider Markov Chain Monte Carlo methods adapted to a Hilbert space setting. Such algorithms occur in Bayesian inverse problems where the solution is a probability measure on a function space according to which one would like to integrate or sample. We focus on Metropolis-Hastings algorithms and, in particular, we introduce and analyze a generalization of the existing pCN-proposal. This new proposal allows to exploit the geometry or anisotropy of the target measure which in turn might improve the statistical efficiency of the corresponding MCMC method. Numerical experiments for a real-world problem confirm the improvement.

Metropolis-Hastings Algorithms in Function Space for Bayesian Inverse Problems

KAUST Repository

Ernst, Oliver

2015-01-01

We consider Markov Chain Monte Carlo methods adapted to a Hilbert space setting. Such algorithms occur in Bayesian inverse problems where the solution is a probability measure on a function space according to which one would like to integrate or sample. We focus on Metropolis-Hastings algorithms and, in particular, we introduce and analyze a generalization of the existing pCN-proposal. This new proposal allows to exploit the geometry or anisotropy of the target measure which in turn might improve the statistical efficiency of the corresponding MCMC method. Numerical experiments for a real-world problem confirm the improvement.

The trends of modeling the ways of formation, distribution and exploitation of megapolis lands using geo-information systems

Directory of Open Access Journals (Sweden)

Kostyantyn Mamonov

2017-10-01

Full Text Available The areas of need for ways of modeling the formation, distribution and use of land metropolis using GIS are identified. The article is to define the areas of modeling ways of formation, distribution and use of land metropolis using GIS. In the study, the following objectives are set: to develop an algorithm process data base (Data System creation for pecuniary valuation of land settlements with the use of GIS; to offer process model taking into account the influence of one factor modules using geographic information systems; to identify components of geo providing expert money evaluation of land metropolis; to describe the general procedure for expert money assessment of land and property by using geographic information system software; to develop an algorithm methods for expert evaluation of land. Identified tools built algorithms used for modeling the ways of formation, distribution and use of land metropolis using GIS. Directions ways of modeling the formation, distribution and use of land metropolis using GIS.

Nonparametric Mixture of Regression Models.

Science.gov (United States)

Huang, Mian; Li, Runze; Wang, Shaoli

2013-07-01

Motivated by an analysis of US house price index data, we propose nonparametric finite mixture of regression models. We study the identifiability issue of the proposed models, and develop an estimation procedure by employing kernel regression. We further systematically study the sampling properties of the proposed estimators, and establish their asymptotic normality. A modified EM algorithm is proposed to carry out the estimation procedure. We show that our algorithm preserves the ascent property of the EM algorithm in an asymptotic sense. Monte Carlo simulations are conducted to examine the finite sample performance of the proposed estimation procedure. An empirical analysis of the US house price index data is illustrated for the proposed methodology.

Evaluation of thermodynamic properties of fluid mixtures by PC-SAFT model

Energy Technology Data Exchange (ETDEWEB)

Almasi, Mohammad, E-mail: m.almasi@khouzestan.srbiau.ac.ir

2014-09-10

Experimental and calculated partial molar volumes (V{sup ¯}{sub m,1}) of MIK with (♦) 2-PrOH, (♢) 2-BuOH, (●) 2-PenOH at T = 298.15 K. (—) PC-SAFT model. - Highlights: • Densities and viscosities of the mixtures (MIK + 2-alkanols) were measured. • PC-SAFT model was applied to correlate the volumetric properties of binary mixtures. • Agreement between experimental data and calculated values by PC-SAFT model is good. - Abstract: Densities and viscosities of binary mixtures of methyl isobutyl ketone (MIK) with polar solvents namely, 2-propanol, 2-butanol and 2-pentanol, were measured at 7 temperatures (293.15–323.15 K) over the entire range of composition. Using the experimental data, excess molar volumes V{sub m}{sup E}, isobaric thermal expansivity α{sub p}, partial molar volumes V{sup ¯}{sub m,i} and viscosity deviations Δη, have been calculated due to their importance in the study of specific molecular interactions. The observed negative and positive values of deviation/excess parameters were explained on the basis of the intermolecular interactions occur in these mixtures. The Perturbed Chain Statistical Association Fluid Theory (PC-SAFT) has been used to correlate the volumetric behavior of the mixtures.

Metal Mixture Modeling Evaluation project: 2. Comparison of four modeling approaches

Science.gov (United States)

Farley, Kevin J.; Meyer, Joe; Balistrieri, Laurie S.; DeSchamphelaere, Karl; Iwasaki, Yuichi; Janssen, Colin; Kamo, Masashi; Lofts, Steve; Mebane, Christopher A.; Naito, Wataru; Ryan, Adam C.; Santore, Robert C.; Tipping, Edward

2015-01-01

As part of the Metal Mixture Modeling Evaluation (MMME) project, models were developed by the National Institute of Advanced Industrial Science and Technology (Japan), the U.S. Geological Survey (USA), HDR⎪HydroQual, Inc. (USA), and the Centre for Ecology and Hydrology (UK) to address the effects of metal mixtures on biological responses of aquatic organisms. A comparison of the 4 models, as they were presented at the MMME Workshop in Brussels, Belgium (May 2012), is provided herein. Overall, the models were found to be similar in structure (free ion activities computed by WHAM; specific or non-specific binding of metals/cations in or on the organism; specification of metal potency factors and/or toxicity response functions to relate metal accumulation to biological response). Major differences in modeling approaches are attributed to various modeling assumptions (e.g., single versus multiple types of binding site on the organism) and specific calibration strategies that affected the selection of model parameters. The models provided a reasonable description of additive (or nearly additive) toxicity for a number of individual toxicity test results. Less-than-additive toxicity was more difficult to describe with the available models. Because of limitations in the available datasets and the strong inter-relationships among the model parameters (log KM values, potency factors, toxicity response parameters), further evaluation of specific model assumptions and calibration strategies is needed.

Identifying Clusters with Mixture Models that Include Radial Velocity Observations

Science.gov (United States)

Czarnatowicz, Alexis; Ybarra, Jason E.

2018-01-01

The study of stellar clusters plays an integral role in the study of star formation. We present a cluster mixture model that considers radial velocity data in addition to spatial data. Maximum likelihood estimation through the Expectation-Maximization (EM) algorithm is used for parameter estimation. Our mixture model analysis can be used to distinguish adjacent or overlapping clusters, and estimate properties for each cluster.Work supported by awards from the Virginia Foundation for Independent Colleges (VFIC) Undergraduate Science Research Fellowship and The Research Experience @Bridgewater (TREB).

Estimation of value at risk and conditional value at risk using normal mixture distributions model

Science.gov (United States)

Kamaruzzaman, Zetty Ain; Isa, Zaidi

2013-04-01

Normal mixture distributions model has been successfully applied in financial time series analysis. In this paper, we estimate the return distribution, value at risk (VaR) and conditional value at risk (CVaR) for monthly and weekly rates of returns for FTSE Bursa Malaysia Kuala Lumpur Composite Index (FBMKLCI) from July 1990 until July 2010 using the two component univariate normal mixture distributions model. First, we present the application of normal mixture distributions model in empirical finance where we fit our real data. Second, we present the application of normal mixture distributions model in risk analysis where we apply the normal mixture distributions model to evaluate the value at risk (VaR) and conditional value at risk (CVaR) with model validation for both risk measures. The empirical results provide evidence that using the two components normal mixture distributions model can fit the data well and can perform better in estimating value at risk (VaR) and conditional value at risk (CVaR) where it can capture the stylized facts of non-normality and leptokurtosis in returns distribution.

Semiparametric accelerated failure time cure rate mixture models with competing risks.

Science.gov (United States)

Choi, Sangbum; Zhu, Liang; Huang, Xuelin

2018-01-15

Modern medical treatments have substantially improved survival rates for many chronic diseases and have generated considerable interest in developing cure fraction models for survival data with a non-ignorable cured proportion. Statistical analysis of such data may be further complicated by competing risks that involve multiple types of endpoints. Regression analysis of competing risks is typically undertaken via a proportional hazards model adapted on cause-specific hazard or subdistribution hazard. In this article, we propose an alternative approach that treats competing events as distinct outcomes in a mixture. We consider semiparametric accelerated failure time models for the cause-conditional survival function that are combined through a multinomial logistic model within the cure-mixture modeling framework. The cure-mixture approach to competing risks provides a means to determine the overall effect of a treatment and insights into how this treatment modifies the components of the mixture in the presence of a cure fraction. The regression and nonparametric parameters are estimated by a nonparametric kernel-based maximum likelihood estimation method. Variance estimation is achieved through resampling methods for the kernel-smoothed likelihood function. Simulation studies show that the procedures work well in practical settings. Application to a sarcoma study demonstrates the use of the proposed method for competing risk data with a cure fraction. Copyright © 2017 John Wiley & Sons, Ltd.

The Semiparametric Normal Variance-Mean Mixture Model

DEFF Research Database (Denmark)

Korsholm, Lars

1997-01-01

We discuss the normal vairance-mean mixture model from a semi-parametric point of view, i.e. we let the mixing distribution belong to a non parametric family. The main results are consistency of the non parametric maximum likelihood estimat or in this case, and construction of an asymptotically...... normal and efficient estimator....

Nonlinear Structured Growth Mixture Models in Mplus and OpenMx

Science.gov (United States)

Grimm, Kevin J.; Ram, Nilam; Estabrook, Ryne

2014-01-01

Growth mixture models (GMMs; Muthén & Muthén, 2000; Muthén & Shedden, 1999) are a combination of latent curve models (LCMs) and finite mixture models to examine the existence of latent classes that follow distinct developmental patterns. GMMs are often fit with linear, latent basis, multiphase, or polynomial change models because of their common use, flexibility in modeling many types of change patterns, the availability of statistical programs to fit such models, and the ease of programming. In this paper, we present additional ways of modeling nonlinear change patterns with GMMs. Specifically, we show how LCMs that follow specific nonlinear functions can be extended to examine the presence of multiple latent classes using the Mplus and OpenMx computer programs. These models are fit to longitudinal reading data from the Early Childhood Longitudinal Study-Kindergarten Cohort to illustrate their use. PMID:25419006

Water budget analysis and management for Bangkok Metropolis, Thailand.

Science.gov (United States)

Singkran, Nuanchan

2017-09-01

The water budget of the Bangkok Metropolis system was analyzed using a material flow analysis model. Total imported flows into the system were 80,080 million m 3 per year (Mm 3 y -1 ) including inflows from the Chao Phraya and Mae Klong rivers and rainwater. Total exported flows out of the system were 78,528 Mm 3 y -1 including outflow into the lower Chao Phraya River and tap water (TW) distributed to suburbs. Total rates of stock exchange (1,552 Mm 3 y -1 ) were found in the processes of water recycling, TW distribution, domestic use, swine farming, aquaculture, and paddy fields. Only 21% of the total amount of wastewater (1,255 Mm 3 y -1 ) was collected, with insufficient treatment capacity of about 415 Mm 3 y -1 . Domestic and business (industrial and commercial sectors) areas were major point sources, whereas paddy fields were a major non-point source of wastewater. To manage Bangkok's water budget, critical measures have to be considered. Wastewater treatment capacity and efficiency of wastewater collection should be improved. On-site wastewater treatment plants for residential areas should be installed. Urban planning and land use zoning are suggested to control land use activities. Green technology should be supported to reduce wastewater from farming.

Bayesian mixture models for source separation in MEG

International Nuclear Information System (INIS)

Calvetti, Daniela; Homa, Laura; Somersalo, Erkki

2011-01-01

This paper discusses the problem of imaging electromagnetic brain activity from measurements of the induced magnetic field outside the head. This imaging modality, magnetoencephalography (MEG), is known to be severely ill posed, and in order to obtain useful estimates for the activity map, complementary information needs to be used to regularize the problem. In this paper, a particular emphasis is on finding non-superficial focal sources that induce a magnetic field that may be confused with noise due to external sources and with distributed brain noise. The data are assumed to come from a mixture of a focal source and a spatially distributed possibly virtual source; hence, to differentiate between those two components, the problem is solved within a Bayesian framework, with a mixture model prior encoding the information that different sources may be concurrently active. The mixture model prior combines one density that favors strongly focal sources and another that favors spatially distributed sources, interpreted as clutter in the source estimation. Furthermore, to address the challenge of localizing deep focal sources, a novel depth sounding algorithm is suggested, and it is shown with simulated data that the method is able to distinguish between a signal arising from a deep focal source and a clutter signal. (paper)

Model-based experimental design for assessing effects of mixtures of chemicals

NARCIS (Netherlands)

Baas, J.; Stefanowicz, A.M.; Klimek, B.; Laskowski, R.; Kooijman, S.A.L.M.

2010-01-01

We exposed flour beetles (Tribolium castaneum) to a mixture of four poly aromatic hydrocarbons (PAHs). The experimental setup was chosen such that the emphasis was on assessing partial effects. We interpreted the effects of the mixture by a process-based model, with a threshold concentration for

Modelling of phase equilibria for associating mixtures using an equation of state

International Nuclear Information System (INIS)

Ferreira, Olga; Brignole, Esteban A.; Macedo, Eugenia A.

2004-01-01

In the present work, the group contribution with association equation of state (GCA-EoS) is extended to represent phase equilibria in mixtures containing acids, esters, and ketones, with water, alcohols, and any number of inert components. Association effects are represented by a group-contribution approach. Self- and cross-association between the associating groups present in these mixtures are considered. The GCA-EoS model is compared to the group-contribution method MHV2, which does not take into account explicitly association effects. The results obtained with the GCA-EoS model are, in general, more accurate when compared to the ones achieved by the MHV2 equation with less number of parameters. Model predictions are presented for binary self- and cross-associating mixtures

Gravel-Sand-Clay Mixture Model for Predictions of Permeability and Velocity of Unconsolidated Sediments

Science.gov (United States)

Konishi, C.

2014-12-01

Gravel-sand-clay mixture model is proposed particularly for unconsolidated sediments to predict permeability and velocity from volume fractions of the three components (i.e. gravel, sand, and clay). A well-known sand-clay mixture model or bimodal mixture model treats clay contents as volume fraction of the small particle and the rest of the volume is considered as that of the large particle. This simple approach has been commonly accepted and has validated by many studies before. However, a collection of laboratory measurements of permeability and grain size distribution for unconsolidated samples show an impact of presence of another large particle; i.e. only a few percent of gravel particles increases the permeability of the sample significantly. This observation cannot be explained by the bimodal mixture model and it suggests the necessity of considering the gravel-sand-clay mixture model. In the proposed model, I consider the three volume fractions of each component instead of using only the clay contents. Sand becomes either larger or smaller particles in the three component mixture model, whereas it is always the large particle in the bimodal mixture model. The total porosity of the two cases, one is the case that the sand is smaller particle and the other is the case that the sand is larger particle, can be modeled independently from sand volume fraction by the same fashion in the bimodal model. However, the two cases can co-exist in one sample; thus, the total porosity of the mixed sample is calculated by weighted average of the two cases by the volume fractions of gravel and clay. The effective porosity is distinguished from the total porosity assuming that the porosity associated with clay is zero effective porosity. In addition, effective grain size can be computed from the volume fractions and representative grain sizes for each component. Using the effective porosity and the effective grain size, the permeability is predicted by Kozeny-Carman equation

Mixture models with entropy regularization for community detection in networks

Science.gov (United States)

Chang, Zhenhai; Yin, Xianjun; Jia, Caiyan; Wang, Xiaoyang

2018-04-01

Community detection is a key exploratory tool in network analysis and has received much attention in recent years. NMM (Newman's mixture model) is one of the best models for exploring a range of network structures including community structure, bipartite and core-periphery structures, etc. However, NMM needs to know the number of communities in advance. Therefore, in this study, we have proposed an entropy regularized mixture model (called EMM), which is capable of inferring the number of communities and identifying network structure contained in a network, simultaneously. In the model, by minimizing the entropy of mixing coefficients of NMM using EM (expectation-maximization) solution, the small clusters contained little information can be discarded step by step. The empirical study on both synthetic networks and real networks has shown that the proposed model EMM is superior to the state-of-the-art methods.

Model-based experimental design for assessing effects of mixtures of chemicals

Energy Technology Data Exchange (ETDEWEB)

Baas, Jan, E-mail: jan.baas@falw.vu.n [Vrije Universiteit of Amsterdam, Dept of Theoretical Biology, De Boelelaan 1085, 1081 HV Amsterdam (Netherlands); Stefanowicz, Anna M., E-mail: anna.stefanowicz@uj.edu.p [Institute of Environmental Sciences, Jagiellonian University, Gronostajowa 7, 30-387 Krakow (Poland); Klimek, Beata, E-mail: beata.klimek@uj.edu.p [Institute of Environmental Sciences, Jagiellonian University, Gronostajowa 7, 30-387 Krakow (Poland); Laskowski, Ryszard, E-mail: ryszard.laskowski@uj.edu.p [Institute of Environmental Sciences, Jagiellonian University, Gronostajowa 7, 30-387 Krakow (Poland); Kooijman, Sebastiaan A.L.M., E-mail: bas@bio.vu.n [Vrije Universiteit of Amsterdam, Dept of Theoretical Biology, De Boelelaan 1085, 1081 HV Amsterdam (Netherlands)

2010-01-15

We exposed flour beetles (Tribolium castaneum) to a mixture of four poly aromatic hydrocarbons (PAHs). The experimental setup was chosen such that the emphasis was on assessing partial effects. We interpreted the effects of the mixture by a process-based model, with a threshold concentration for effects on survival. The behavior of the threshold concentration was one of the key features of this research. We showed that the threshold concentration is shared by toxicants with the same mode of action, which gives a mechanistic explanation for the observation that toxic effects in mixtures may occur in concentration ranges where the individual components do not show effects. Our approach gives reliable predictions of partial effects on survival and allows for a reduction of experimental effort in assessing effects of mixtures, extrapolations to other mixtures, other points in time, or in a wider perspective to other organisms. - We show a mechanistic approach to assess effects of mixtures in low concentrations.

Model-based experimental design for assessing effects of mixtures of chemicals

International Nuclear Information System (INIS)

Baas, Jan; Stefanowicz, Anna M.; Klimek, Beata; Laskowski, Ryszard; Kooijman, Sebastiaan A.L.M.

2010-01-01

We exposed flour beetles (Tribolium castaneum) to a mixture of four poly aromatic hydrocarbons (PAHs). The experimental setup was chosen such that the emphasis was on assessing partial effects. We interpreted the effects of the mixture by a process-based model, with a threshold concentration for effects on survival. The behavior of the threshold concentration was one of the key features of this research. We showed that the threshold concentration is shared by toxicants with the same mode of action, which gives a mechanistic explanation for the observation that toxic effects in mixtures may occur in concentration ranges where the individual components do not show effects. Our approach gives reliable predictions of partial effects on survival and allows for a reduction of experimental effort in assessing effects of mixtures, extrapolations to other mixtures, other points in time, or in a wider perspective to other organisms. - We show a mechanistic approach to assess effects of mixtures in low concentrations.

Improved Denoising via Poisson Mixture Modeling of Image Sensor Noise.

Science.gov (United States)

Zhang, Jiachao; Hirakawa, Keigo

2017-04-01

This paper describes a study aimed at comparing the real image sensor noise distribution to the models of noise often assumed in image denoising designs. A quantile analysis in pixel, wavelet transform, and variance stabilization domains reveal that the tails of Poisson, signal-dependent Gaussian, and Poisson-Gaussian models are too short to capture real sensor noise behavior. A new Poisson mixture noise model is proposed to correct the mismatch of tail behavior. Based on the fact that noise model mismatch results in image denoising that undersmoothes real sensor data, we propose a mixture of Poisson denoising method to remove the denoising artifacts without affecting image details, such as edge and textures. Experiments with real sensor data verify that denoising for real image sensor data is indeed improved by this new technique.

Determining of migraine prognosis using latent growth mixture models.

Science.gov (United States)

Tasdelen, Bahar; Ozge, Aynur; Kaleagasi, Hakan; Erdogan, Semra; Mengi, Tufan

2011-04-01

This paper presents a retrospective study to classify patients into subtypes of the treatment according to baseline and longitudinally observed values considering heterogenity in migraine prognosis. In the classical prospective clinical studies, participants are classified with respect to baseline status and followed within a certain time period. However, latent growth mixture model is the most suitable method, which considers the population heterogenity and is not affected drop-outs if they are missing at random. Hence, we planned this comprehensive study to identify prognostic factors in migraine. The study data have been based on a 10-year computer-based follow-up data of Mersin University Headache Outpatient Department. The developmental trajectories within subgroups were described for the severity, frequency, and duration of headache separately and the probabilities of each subgroup were estimated by using latent growth mixture models. SAS PROC TRAJ procedures, semiparametric and group-based mixture modeling approach, were applied to define the developmental trajectories. While the three-group model for the severity (mild, moderate, severe) and frequency (low, medium, high) of headache appeared to be appropriate, the four-group model for the duration (low, medium, high, extremely high) was more suitable. The severity of headache increased in the patients with nausea, vomiting, photophobia and phonophobia. The frequency of headache was especially related with increasing age and unilateral pain. Nausea and photophobia were also related with headache duration. Nausea, vomiting and photophobia were the most significant factors to identify developmental trajectories. The remission time was not the same for the severity, frequency, and duration of headache.

Natural activities of 40K, 238U and 232Th in elephant grass (Pennisetum purpureum) in Ibadan metropolis, Nigeria

International Nuclear Information System (INIS)

Jibiri, N.N.; Ajao, A.O.

2004-01-01

Samples of elephant grass collected at some pasturing farmlands across different locations in Ibadan metropolis were analyzed for their natural radioactivity concentrations due to 40 K, 238 U and 232 Th radionuclides. Radioactivity measurements were carried out using γ-ray spectroscopy. The average radioactivity concentration of 40 K was found to be 64.5±8.1 Bq kg -1 , 25.7±5.5 Bq kg -1 for 238 U and 33.4±3.9 Bq kg -1 for 232 Th. The radiological health implication to the population that may result from these values is found to be very low and almost insignificant. No artificial radionuclide, however, was detected in any of the samples, hence, measurements have been taken as representing baseline values of these radionuclides in the grass in the metropolis

Thermodiffusion in Multicomponent Mixtures Thermodynamic, Algebraic, and Neuro-Computing Models

CERN Document Server

Srinivasan, Seshasai

2013-01-01

Thermodiffusion in Multicomponent Mixtures presents the computational approaches that are employed in the study of thermodiffusion in various types of mixtures, namely, hydrocarbons, polymers, water-alcohol, molten metals, and so forth. We present a detailed formalism of these methods that are based on non-equilibrium thermodynamics or algebraic correlations or principles of the artificial neural network. The book will serve as single complete reference to understand the theoretical derivations of thermodiffusion models and its application to different types of multi-component mixtures. An exhaustive discussion of these is used to give a complete perspective of the principles and the key factors that govern the thermodiffusion process.

Stakeholders' Perception on Teachers' Assessment Effectiveness in Secondary Schools in Port Harcourt Metropolis in Rivers State

Science.gov (United States)

Ogidi, Reuben C.; Udechukwu, Jonathan O.

2017-01-01

The study sought to investigate the perception of stakeholders on teachers' assessment effectiveness in secondary schools in Port Harcourt Metropolis in Rivers State. Three research questions and one hypothesis were formulated to guide the study. The study adopted survey research design. The sample of the study consisted of 20 principles, 30 vice…

Finite Mixture Multilevel Multidimensional Ordinal IRT Models for Large Scale Cross-Cultural Research

Science.gov (United States)

de Jong, Martijn G.; Steenkamp, Jan-Benedict E. M.

2010-01-01

We present a class of finite mixture multilevel multidimensional ordinal IRT models for large scale cross-cultural research. Our model is proposed for confirmatory research settings. Our prior for item parameters is a mixture distribution to accommodate situations where different groups of countries have different measurement operations, while…

Consumers’Willingness to Pay for Safety Attributes of Bread in Lagos Metropolis, Nigeria

OpenAIRE

Anyam, Osemeke E.; Fashogbon, Ayodele E.; Oni, Omobowale A.

2013-01-01

This study examined consumer’s willingness to pay for food safety attributes in bread in Lagos metropolis. It empirically analyzed the factors driving willingness to pay for improved bread and the effect of attributes on willingness to pay and mean willingness to pay for improved bread. The data for the study using a well-structured questionnaire containing Choice Experiment (CE) questions for eliciting willingness to pay was collected from 150 respondents using a two-stage random sampling te...

Experiments with Mixtures Designs, Models, and the Analysis of Mixture Data

CERN Document Server

Cornell, John A

2011-01-01

The most comprehensive, single-volume guide to conducting experiments with mixtures"If one is involved, or heavily interested, in experiments on mixtures of ingredients, one must obtain this book. It is, as was the first edition, the definitive work."-Short Book Reviews (Publication of the International Statistical Institute)"The text contains many examples with worked solutions and with its extensive coverage of the subject matter will prove invaluable to those in the industrial and educational sectors whose work involves the design and analysis of mixture experiments."-Journal of the Royal S

Evidence for a magma reservoir beneath the Taipei metropolis of Taiwan from both S-wave shadows and P-wave delays.

Science.gov (United States)

Lin, Cheng-Horng

2016-12-23

There are more than 7 million people living near the Tatun volcano group in northern Taiwan. For the safety of the Taipei metropolis, in particular, it has been debated for decades whether or not these volcanoes are active. Here I show evidence of a deep magma reservoir beneath the Taipei metropolis from both S-wave shadows and P-wave delays. The reservoir is probably composed of either a thin magma layer overlay or many molten sills within thick partially molten rocks. Assuming that 40% of the reservoir is partially molten, its total volume could be approximately 350 km 3 . The exact location and geometry of the magma reservoir will be obtained after dense seismic arrays are deployed in 2017-2020.

A semi-nonparametric mixture model for selecting functionally consistent proteins.

Science.gov (United States)

Yu, Lianbo; Doerge, Rw

2010-09-28

High-throughput technologies have led to a new era of proteomics. Although protein microarray experiments are becoming more common place there are a variety of experimental and statistical issues that have yet to be addressed, and that will carry over to new high-throughput technologies unless they are investigated. One of the largest of these challenges is the selection of functionally consistent proteins. We present a novel semi-nonparametric mixture model for classifying proteins as consistent or inconsistent while controlling the false discovery rate and the false non-discovery rate. The performance of the proposed approach is compared to current methods via simulation under a variety of experimental conditions. We provide a statistical method for selecting functionally consistent proteins in the context of protein microarray experiments, but the proposed semi-nonparametric mixture model method can certainly be generalized to solve other mixture data problems. The main advantage of this approach is that it provides the posterior probability of consistency for each protein.

A numerical model for boiling heat transfer coefficient of zeotropic mixtures

Science.gov (United States)

Barraza Vicencio, Rodrigo; Caviedes Aedo, Eduardo

2017-12-01

Zeotropic mixtures never have the same liquid and vapor composition in the liquid-vapor equilibrium. Also, the bubble and the dew point are separated; this gap is called glide temperature (Tglide). Those characteristics have made these mixtures suitable for cryogenics Joule-Thomson (JT) refrigeration cycles. Zeotropic mixtures as working fluid in JT cycles improve their performance in an order of magnitude. Optimization of JT cycles have earned substantial importance for cryogenics applications (e.g, gas liquefaction, cryosurgery probes, cooling of infrared sensors, cryopreservation, and biomedical samples). Heat exchangers design on those cycles is a critical point; consequently, heat transfer coefficient and pressure drop of two-phase zeotropic mixtures are relevant. In this work, it will be applied a methodology in order to calculate the local convective heat transfer coefficients based on the law of the wall approach for turbulent flows. The flow and heat transfer characteristics of zeotropic mixtures in a heated horizontal tube are investigated numerically. The temperature profile and heat transfer coefficient for zeotropic mixtures of different bulk compositions are analysed. The numerical model has been developed and locally applied in a fully developed, constant temperature wall, and two-phase annular flow in a duct. Numerical results have been obtained using this model taking into account continuity, momentum, and energy equations. Local heat transfer coefficient results are compared with available experimental data published by Barraza et al. (2016), and they have shown good agreement.

Text document classification based on mixture models

Czech Academy of Sciences Publication Activity Database

Novovičová, Jana; Malík, Antonín

2004-01-01

Roč. 40, č. 3 (2004), s. 293-304 ISSN 0023-5954 R&D Projects: GA AV ČR IAA2075302; GA ČR GA102/03/0049; GA AV ČR KSK1019101 Institutional research plan: CEZ:AV0Z1075907 Keywords : text classification * text categorization * multinomial mixture model Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.224, year: 2004

Reduced chemical kinetic model of detonation combustion of one- and multi-fuel gaseous mixtures with air

Science.gov (United States)

Fomin, P. A.

2018-03-01

Two-step approximate models of chemical kinetics of detonation combustion of (i) one hydrocarbon fuel CnHm (for example, methane, propane, cyclohexane etc.) and (ii) multi-fuel gaseous mixtures (∑aiCniHmi) (for example, mixture of methane and propane, synthesis gas, benzene and kerosene) are presented for the first time. The models can be used for any stoichiometry, including fuel/fuels-rich mixtures, when reaction products contain molecules of carbon. Owing to the simplicity and high accuracy, the models can be used in multi-dimensional numerical calculations of detonation waves in corresponding gaseous mixtures. The models are in consistent with the second law of thermodynamics and Le Chatelier's principle. Constants of the models have a clear physical meaning. The models can be used for calculation thermodynamic parameters of the mixture in a state of chemical equilibrium.

Dark-Black Stains on Rooftops: Implications on the Quality of Water Harvested from Rooftops in Uyo Metropolis-Nigeria

Directory of Open Access Journals (Sweden)

Ihom A.P.

2017-04-01

Full Text Available The study Dark-Black Stains on Rooftops: Implications on the Quality of Water Harvested from Rooftops in Uyo Metropolis-Nigeria has been undertaken. The study took samples of harvested rainwater from the rooftops of buildings in four different locations in Uyo Metropolis. The samples were taken for analysis at the Ministry of Science and Technology Laboratory-Uyo. The parameters of the harvested rainwater investigated covered physical and chemical properties, heavy metals, total organic carbon (TOC and total coliform count (TCC. Gravimetric, titrimetric and instrumental methods of analysis were used in determining the various parameters investigated. The result was analysed by comparing it with WHO and Ministry of Environment standard specifications for drinking water. The result was equally compared with the composition of the dark-black stains on the rooftops to establish whether the stains on the rooftops were from the rainwater. Findings were astounding; the rainwater was acidic in all the four stations and could not meet up with WHO standard for drinking water. Lead values of 0.75 mg/l and 0.22 mg/l in stations 2 and 3 respectively exceeded WHO standard specification of 0.01mg/l for drinking water. The iron content in the water from stations 2, 3, and 4 all exceeded WHO standard specification for drinking water of 0.30mg/l. All the four stations had cadmium content in the rainwater, which was more than WHO specification for drinking water of 0.003mg/l. The water showed bacteria contamination with total coliform count of 118MPN/100ml in station 4. Some of the parameters in the rainwater also reported in the composition of the dark-black stains on the rooftops an indication that the rain contributed to the dark-black stains on the rooftops in Uyo metropolis. The study concluded that harvested rainwater from the rooftops of buildings in Uyo metropolis is polluted and is not suitable for drinking, bathing and even for use in fish farming. The

Rainforest metropolis casts 1,000-km defaunation shadow.

Science.gov (United States)

Tregidgo, Daniel J; Barlow, Jos; Pompeu, Paulo S; de Almeida Rocha, Mayana; Parry, Luke

2017-08-08

Tropical rainforest regions are urbanizing rapidly, yet the role of emerging metropolises in driving wildlife overharvesting in forests and inland waters is unknown. We present evidence of a large defaunation shadow around a rainforest metropolis. Using interviews with 392 rural fishers, we show that fishing has severely depleted a large-bodied keystone fish species, tambaqui ( Colossoma macropomum ), with an impact extending over 1,000 km from the rainforest city of Manaus (population 2.1 million). There was strong evidence of defaunation within this area, including a 50% reduction in body size and catch rate (catch per unit effort). Our findings link these declines to city-based boats that provide rural fishers with reliable access to fish buyers and ice and likely impact rural fisher livelihoods and flooded forest biodiversity. This empirical evidence that urban markets can defaunate deep into rainforest wilderness has implications for other urbanizing socioecological systems.

The Politics of Security Deployment of Security Operatives to Jos Metropolis, Plateau State, Nigeria 2001-2014

Directory of Open Access Journals (Sweden)

Dantani Umar

2017-01-01

Full Text Available The paper examines the politics of security deployment by the Federal Government of Nigeria to Jos, metropolis. A cross-sectional study was conducted and Public Opinion Theory adopted. Methodologically, mixed methods of data collection were conducted that involved the administration of 377 questionnaires to adult respondents, six In-Depth Interviews with religious and community leaders while three Key Informant Interviews with security personnel working with Special Task Force. The survey reveals that, the deployment of Mobile Police from 2001-2010 and the formation of Special Task Force in 2010 has generated mixed reactions and divergent perceptions among the residents of Jos metropolis. Majority of the ethnic groups that are predominantly Christians were more contented with the deployment of the Mobile Police whereas ethnic groups that are dominantly Muslims questioned the neutrality, capability, performance and strength of the Nigerian Police Force in managing the crises. The study recommends that, security personnel should display high degree of neutrality in order to earn the confidence of the residents and change their perceptions.

Investigating the Impact of Item Parameter Drift for Item Response Theory Models with Mixture Distributions

Directory of Open Access Journals (Sweden)

Yoon Soo ePark

2016-02-01

Full Text Available This study investigates the impact of item parameter drift (IPD on parameter and ability estimation when the underlying measurement model fits a mixture distribution, thereby violating the item invariance property of unidimensional item response theory (IRT models. An empirical study was conducted to demonstrate the occurrence of both IPD and an underlying mixture distribution using real-world data. Twenty-one trended anchor items from the 1999, 2003, and 2007 administrations of Trends in International Mathematics and Science Study (TIMSS were analyzed using unidimensional and mixture IRT models. TIMSS treats trended anchor items as invariant over testing administrations and uses pre-calibrated item parameters based on unidimensional IRT. However, empirical results showed evidence of two latent subgroups with IPD. Results showed changes in the distribution of examinee ability between latent classes over the three administrations. A simulation study was conducted to examine the impact of IPD on the estimation of ability and item parameters, when data have underlying mixture distributions. Simulations used data generated from a mixture IRT model and estimated using unidimensional IRT. Results showed that data reflecting IPD using mixture IRT model led to IPD in the unidimensional IRT model. Changes in the distribution of examinee ability also affected item parameters. Moreover, drift with respect to item discrimination and distribution of examinee ability affected estimates of examinee ability. These findings demonstrate the need to caution and evaluate IPD using a mixture IRT framework to understand its effect on item parameters and examinee ability.

Investigating the Impact of Item Parameter Drift for Item Response Theory Models with Mixture Distributions.

Science.gov (United States)

Park, Yoon Soo; Lee, Young-Sun; Xing, Kuan

2016-01-01

This study investigates the impact of item parameter drift (IPD) on parameter and ability estimation when the underlying measurement model fits a mixture distribution, thereby violating the item invariance property of unidimensional item response theory (IRT) models. An empirical study was conducted to demonstrate the occurrence of both IPD and an underlying mixture distribution using real-world data. Twenty-one trended anchor items from the 1999, 2003, and 2007 administrations of Trends in International Mathematics and Science Study (TIMSS) were analyzed using unidimensional and mixture IRT models. TIMSS treats trended anchor items as invariant over testing administrations and uses pre-calibrated item parameters based on unidimensional IRT. However, empirical results showed evidence of two latent subgroups with IPD. Results also showed changes in the distribution of examinee ability between latent classes over the three administrations. A simulation study was conducted to examine the impact of IPD on the estimation of ability and item parameters, when data have underlying mixture distributions. Simulations used data generated from a mixture IRT model and estimated using unidimensional IRT. Results showed that data reflecting IPD using mixture IRT model led to IPD in the unidimensional IRT model. Changes in the distribution of examinee ability also affected item parameters. Moreover, drift with respect to item discrimination and distribution of examinee ability affected estimates of examinee ability. These findings demonstrate the need to caution and evaluate IPD using a mixture IRT framework to understand its effects on item parameters and examinee ability.

Influence of high power ultrasound on rheological and foaming properties of model ice-cream mixtures

Directory of Open Access Journals (Sweden)

Verica Batur

2010-03-01

Full Text Available This paper presents research of the high power ultrasound effect on rheological and foaming properties of ice cream model mixtures. Ice cream model mixtures are prepared according to specific recipes, and afterward undergone through different homogenization techniques: mechanical mixing, ultrasound treatment and combination of mechanical and ultrasound treatment. Specific diameter (12.7 mm of ultrasound probe tip has been used for ultrasound treatment that lasted 5 minutes at 100 percent amplitude. Rheological parameters have been determined using rotational rheometer and expressed as flow index, consistency coefficient and apparent viscosity. From the results it can be concluded that all model mixtures have non-newtonian, dilatant type behavior. The highest viscosities have been observed for model mixtures that were homogenizes with mechanical mixing, and significantly lower values of viscosity have been observed for ultrasound treated ones. Foaming properties are expressed as percentage of increase in foam volume, foam stability index and minimal viscosity. It has been determined that ice cream model mixtures treated only with ultrasound had minimal increase in foam volume, while the highest increase in foam volume has been observed for ice cream mixture that has been treated in combination with mechanical and ultrasound treatment. Also, ice cream mixtures having higher amount of proteins in composition had shown higher foam stability. It has been determined that optimal treatment time is 10 minutes.

Piecewise Linear-Linear Latent Growth Mixture Models with Unknown Knots

Science.gov (United States)

Kohli, Nidhi; Harring, Jeffrey R.; Hancock, Gregory R.

2013-01-01

Latent growth curve models with piecewise functions are flexible and useful analytic models for investigating individual behaviors that exhibit distinct phases of development in observed variables. As an extension of this framework, this study considers a piecewise linear-linear latent growth mixture model (LGMM) for describing segmented change of…

Gaussian Mixture Model of Heart Rate Variability

Science.gov (United States)

Costa, Tommaso; Boccignone, Giuseppe; Ferraro, Mario

2012-01-01

Heart rate variability (HRV) is an important measure of sympathetic and parasympathetic functions of the autonomic nervous system and a key indicator of cardiovascular condition. This paper proposes a novel method to investigate HRV, namely by modelling it as a linear combination of Gaussians. Results show that three Gaussians are enough to describe the stationary statistics of heart variability and to provide a straightforward interpretation of the HRV power spectrum. Comparisons have been made also with synthetic data generated from different physiologically based models showing the plausibility of the Gaussian mixture parameters. PMID:22666386

Modelling of phase equilibria of glycol ethers mixtures using an association model

DEFF Research Database (Denmark)

Garrido, Nuno M.; Folas, Georgios; Kontogeorgis, Georgios

2008-01-01

Vapor-liquid and liquid-liquid equilibria of glycol ethers (surfactant) mixtures with hydrocarbons, polar compounds and water are calculated using an association model, the Cubic-Plus-Association Equation of State. Parameters are estimated for several non-ionic surfactants of the polyoxyethylene ...

Linking asphalt binder fatigue to asphalt mixture fatigue performance using viscoelastic continuum damage modeling

Science.gov (United States)

Safaei, Farinaz; Castorena, Cassie; Kim, Y. Richard

2016-08-01

Fatigue cracking is a major form of distress in asphalt pavements. Asphalt binder is the weakest asphalt concrete constituent and, thus, plays a critical role in determining the fatigue resistance of pavements. Therefore, the ability to characterize and model the inherent fatigue performance of an asphalt binder is a necessary first step to design mixtures and pavements that are not susceptible to premature fatigue failure. The simplified viscoelastic continuum damage (S-VECD) model has been used successfully by researchers to predict the damage evolution in asphalt mixtures for various traffic and climatic conditions using limited uniaxial test data. In this study, the S-VECD model, developed for asphalt mixtures, is adapted for asphalt binders tested under cyclic torsion in a dynamic shear rheometer. Derivation of the model framework is presented. The model is verified by producing damage characteristic curves that are both temperature- and loading history-independent based on time sweep tests, given that the effects of plasticity and adhesion loss on the material behavior are minimal. The applicability of the S-VECD model to the accelerated loading that is inherent of the linear amplitude sweep test is demonstrated, which reveals reasonable performance predictions, but with some loss in accuracy compared to time sweep tests due to the confounding effects of nonlinearity imposed by the high strain amplitudes included in the test. The asphalt binder S-VECD model is validated through comparisons to asphalt mixture S-VECD model results derived from cyclic direct tension tests and Accelerated Loading Facility performance tests. The results demonstrate good agreement between the asphalt binder and mixture test results and pavement performance, indicating that the developed model framework is able to capture the asphalt binder's contribution to mixture fatigue and pavement fatigue cracking performance.

THE DEVELOPMENT TREND OF METROPOLIS VEHICLE 大城市交通工具發展趨勢

DEFF Research Database (Denmark)

Dai, Zheng; Gao, Tian

2009-01-01

The traffic matching problem of metropolis is embodied by that the traffic-jam, traffic pollution，traffic system inefficacy and all of the area can not be covered with traffic system. The problem can be solved by a new way of traffic. Public traffic and individual traffic are two aspects of city ...

A compressibility based model for predicting the tensile strength of directly compressed pharmaceutical powder mixtures.

Science.gov (United States)

Reynolds, Gavin K; Campbell, Jacqueline I; Roberts, Ron J

2017-10-05

A new model to predict the compressibility and compactability of mixtures of pharmaceutical powders has been developed. The key aspect of the model is consideration of the volumetric occupancy of each powder under an applied compaction pressure and the respective contribution it then makes to the mixture properties. The compressibility and compactability of three pharmaceutical powders: microcrystalline cellulose, mannitol and anhydrous dicalcium phosphate have been characterised. Binary and ternary mixtures of these excipients have been tested and used to demonstrate the predictive capability of the model. Furthermore, the model is shown to be uniquely able to capture a broad range of mixture behaviours, including neutral, negative and positive deviations, illustrating its utility for formulation design. Copyright © 2017 Elsevier B.V. All rights reserved.

Investigating Individual Differences in Toddler Search with Mixture Models

Science.gov (United States)

Berthier, Neil E.; Boucher, Kelsea; Weisner, Nina

2015-01-01

Children's performance on cognitive tasks is often described in categorical terms in that a child is described as either passing or failing a test, or knowing or not knowing some concept. We used binomial mixture models to determine whether individual children could be classified as passing or failing two search tasks, the DeLoache model room…

Application of association models to mixtures containing alkanolamines

DEFF Research Database (Denmark)

Avlund, Ane Søgaard; Eriksen, Daniel Kunisch; Kontogeorgis, Georgios

2011-01-01

Two association models,the CPA and sPC-SAFT equations of state, are applied to binarymixtures containing alkanolamines and hydrocarbons or water. CPA is applied to mixtures of MEA and DEA, while sPC-SAFT is applied to MEA–n-heptane liquid–liquid equilibria and MEA–water vapor–liquid equilibria. T...

A Frank mixture copula family for modeling higher-order correlations of neural spike counts

International Nuclear Information System (INIS)

Onken, Arno; Obermayer, Klaus

2009-01-01

In order to evaluate the importance of higher-order correlations in neural spike count codes, flexible statistical models of dependent multivariate spike counts are required. Copula families, parametric multivariate distributions that represent dependencies, can be applied to construct such models. We introduce the Frank mixture family as a new copula family that has separate parameters for all pairwise and higher-order correlations. In contrast to the Farlie-Gumbel-Morgenstern copula family that shares this property, the Frank mixture copula can model strong correlations. We apply spike count models based on the Frank mixture copula to data generated by a network of leaky integrate-and-fire neurons and compare the goodness of fit to distributions based on the Farlie-Gumbel-Morgenstern family. Finally, we evaluate the importance of using proper single neuron spike count distributions on the Shannon information. We find notable deviations in the entropy that increase with decreasing firing rates. Moreover, we find that the Frank mixture family increases the log likelihood of the fit significantly compared to the Farlie-Gumbel-Morgenstern family. This shows that the Frank mixture copula is a useful tool to assess the importance of higher-order correlations in spike count codes.

A nonlinear isobologram model with Box-Cox transformation to both sides for chemical mixtures.

Science.gov (United States)

Chen, D G; Pounds, J G

1998-12-01

The linear logistical isobologram is a commonly used and powerful graphical and statistical tool for analyzing the combined effects of simple chemical mixtures. In this paper a nonlinear isobologram model is proposed to analyze the joint action of chemical mixtures for quantitative dose-response relationships. This nonlinear isobologram model incorporates two additional new parameters, Ymin and Ymax, to facilitate analysis of response data that are not constrained between 0 and 1, where parameters Ymin and Ymax represent the minimal and the maximal observed toxic response. This nonlinear isobologram model for binary mixtures can be expressed as [formula: see text] In addition, a Box-Cox transformation to both sides is introduced to improve the goodness of fit and to provide a more robust model for achieving homogeneity and normality of the residuals. Finally, a confidence band is proposed for selected isobols, e.g., the median effective dose, to facilitate graphical and statistical analysis of the isobologram. The versatility of this approach is demonstrated using published data describing the toxicity of the binary mixtures of citrinin and ochratoxin as well as a new experimental data from our laboratory for mixtures of mercury and cadmium.

Effect of impervious surface area and vegetation changes on mean surface temperature over Tshwane metropolis, Gauteng Province, South Africa

CSIR Research Space (South Africa)

Adeyemi, A

2015-11-01

Full Text Available The Tshwane Metropolis, Gauteng Province, South Africa, continues to experience rapid urbanization as a result of population growth. This has led to the conversion of natural lands into large man-made landscapes i.e., increase in impervious surfaces...

Copula Based Factorization in Bayesian Multivariate Infinite Mixture Models

OpenAIRE

Martin Burda; Artem Prokhorov

2012-01-01

Bayesian nonparametric models based on infinite mixtures of density kernels have been recently gaining in popularity due to their flexibility and feasibility of implementation even in complicated modeling scenarios. In economics, they have been particularly useful in estimating nonparametric distributions of latent variables. However, these models have been rarely applied in more than one dimension. Indeed, the multivariate case suffers from the curse of dimensionality, with a rapidly increas...

Automatic categorization of web pages and user clustering with mixtures of hidden Markov models

NARCIS (Netherlands)

Ypma, A.; Heskes, T.M.; Zaiane, O.R.; Srivastav, J.

2003-01-01

We propose mixtures of hidden Markov models for modelling clickstreams of web surfers. Hence, the page categorization is learned from the data without the need for a (possibly cumbersome) manual categorization. We provide an EM algorithm for training a mixture of HMMs and show that additional static

Option Pricing with Asymmetric Heteroskedastic Normal Mixture Models

DEFF Research Database (Denmark)

Rombouts, Jeroen V. K; Stentoft, Lars

2015-01-01

We propose an asymmetric GARCH in mean mixture model and provide a feasible method for option pricing within this general framework by deriving the appropriate risk neutral dynamics. We forecast the out-of-sample prices of a large sample of options on the S&P 500 index from January 2006 to December...

Finite mixture models for the computation of isotope ratios in mixed isotopic samples

Science.gov (United States)

Koffler, Daniel; Laaha, Gregor; Leisch, Friedrich; Kappel, Stefanie; Prohaska, Thomas

2013-04-01

Finite mixture models have been used for more than 100 years, but have seen a real boost in popularity over the last two decades due to the tremendous increase in available computing power. The areas of application of mixture models range from biology and medicine to physics, economics and marketing. These models can be applied to data where observations originate from various groups and where group affiliations are not known, as is the case for multiple isotope ratios present in mixed isotopic samples. Recently, the potential of finite mixture models for the computation of 235U/238U isotope ratios from transient signals measured in individual (sub-)µm-sized particles by laser ablation - multi-collector - inductively coupled plasma mass spectrometry (LA-MC-ICPMS) was demonstrated by Kappel et al. [1]. The particles, which were deposited on the same substrate, were certified with respect to their isotopic compositions. Here, we focus on the statistical model and its application to isotope data in ecogeochemistry. Commonly applied evaluation approaches for mixed isotopic samples are time-consuming and are dependent on the judgement of the analyst. Thus, isotopic compositions may be overlooked due to the presence of more dominant constituents. Evaluation using finite mixture models can be accomplished unsupervised and automatically. The models try to fit several linear models (regression lines) to subgroups of data taking the respective slope as estimation for the isotope ratio. The finite mixture models are parameterised by: • The number of different ratios. • Number of points belonging to each ratio-group. • The ratios (i.e. slopes) of each group. Fitting of the parameters is done by maximising the log-likelihood function using an iterative expectation-maximisation (EM) algorithm. In each iteration step, groups of size smaller than a control parameter are dropped; thereby the number of different ratios is determined. The analyst only influences some control

Option Pricing with Asymmetric Heteroskedastic Normal Mixture Models

DEFF Research Database (Denmark)

Rombouts, Jeroen V.K.; Stentoft, Lars

This paper uses asymmetric heteroskedastic normal mixture models to fit return data and to price options. The models can be estimated straightforwardly by maximum likelihood, have high statistical fit when used on S&P 500 index return data, and allow for substantial negative skewness and time...... varying higher order moments of the risk neutral distribution. When forecasting out-of-sample a large set of index options between 1996 and 2009, substantial improvements are found compared to several benchmark models in terms of dollar losses and the ability to explain the smirk in implied volatilities...

Maximum likelihood estimation of semiparametric mixture component models for competing risks data.

Science.gov (United States)

Choi, Sangbum; Huang, Xuelin

2014-09-01

In the analysis of competing risks data, the cumulative incidence function is a useful quantity to characterize the crude risk of failure from a specific event type. In this article, we consider an efficient semiparametric analysis of mixture component models on cumulative incidence functions. Under the proposed mixture model, latency survival regressions given the event type are performed through a class of semiparametric models that encompasses the proportional hazards model and the proportional odds model, allowing for time-dependent covariates. The marginal proportions of the occurrences of cause-specific events are assessed by a multinomial logistic model. Our mixture modeling approach is advantageous in that it makes a joint estimation of model parameters associated with all competing risks under consideration, satisfying the constraint that the cumulative probability of failing from any cause adds up to one given any covariates. We develop a novel maximum likelihood scheme based on semiparametric regression analysis that facilitates efficient and reliable estimation. Statistical inferences can be conveniently made from the inverse of the observed information matrix. We establish the consistency and asymptotic normality of the proposed estimators. We validate small sample properties with simulations and demonstrate the methodology with a data set from a study of follicular lymphoma. © 2014, The International Biometric Society.

Modeling adsorption of binary and ternary mixtures on microporous media

DEFF Research Database (Denmark)

Monsalvo, Matias Alfonso; Shapiro, Alexander

2007-01-01

it possible using the same equation of state to describe the thermodynamic properties of the segregated and the bulk phases. For comparison, we also used the ideal adsorbed solution theory (IAST) to describe adsorption equilibria. The main advantage of these two models is their capabilities to predict......The goal of this work is to analyze the adsorption of binary and ternary mixtures on the basis of the multicomponent potential theory of adsorption (MPTA). In the MPTA, the adsorbate is considered as a segregated mixture in the external potential field emitted by the solid adsorbent. This makes...... multicomponent adsorption equilibria on the basis of single-component adsorption data. We compare the MPTA and IAST models to a large set of experimental data, obtaining reasonable good agreement with experimental data and high degree of predictability. Some limitations of both models are also discussed....

Analysis of real-time mixture cytotoxicity data following repeated exposure using BK/TD models

International Nuclear Information System (INIS)

Teng, S.; Tebby, C.; Barcellini-Couget, S.; De Sousa, G.; Brochot, C.; Rahmani, R.; Pery, A.R.R.

2016-01-01

Cosmetic products generally consist of multiple ingredients. Thus, cosmetic risk assessment has to deal with mixture toxicity on a long-term scale which means it has to be assessed in the context of repeated exposure. Given that animal testing has been banned for cosmetics risk assessment, in vitro assays allowing long-term repeated exposure and adapted for in vitro – in vivo extrapolation need to be developed. However, most in vitro tests only assess short-term effects and consider static endpoints which hinder extrapolation to realistic human exposure scenarios where concentration in target organs is varies over time. Thanks to impedance metrics, real-time cell viability monitoring for repeated exposure has become possible. We recently constructed biokinetic/toxicodynamic models (BK/TD) to analyze such data (Teng et al., 2015) for three hepatotoxic cosmetic ingredients: coumarin, isoeugenol and benzophenone-2. In the present study, we aim to apply these models to analyze the dynamics of mixture impedance data using the concepts of concentration addition and independent action. Metabolic interactions between the mixture components were investigated, characterized and implemented in the models, as they impacted the actual cellular exposure. Indeed, cellular metabolism following mixture exposure induced a quick disappearance of the compounds from the exposure system. We showed that isoeugenol substantially decreased the metabolism of benzophenone-2, reducing the disappearance of this compound and enhancing its in vitro toxicity. Apart from this metabolic interaction, no mixtures showed any interaction, and all binary mixtures were successfully modeled by at least one model based on exposure to the individual compounds. - Highlights: • We could predict cell response over repeated exposure to mixtures of cosmetics. • Compounds acted independently on the cells. • Metabolic interactions impacted exposure concentrations to the compounds.

Analysis of real-time mixture cytotoxicity data following repeated exposure using BK/TD models

Energy Technology Data Exchange (ETDEWEB)

Teng, S.; Tebby, C. [Models for Toxicology and Ecotoxicology Unit, INERIS, Parc Technologique Alata, BP 2, 60550 Verneuil-en-Halatte (France); Barcellini-Couget, S. [ODESIA Neosciences, Sophia Antipolis, 400 route des chappes, 06903 Sophia Antipolis (France); De Sousa, G. [INRA, ToxAlim, 400 route des Chappes, BP, 167 06903 Sophia Antipolis, Cedex (France); Brochot, C. [Models for Toxicology and Ecotoxicology Unit, INERIS, Parc Technologique Alata, BP 2, 60550 Verneuil-en-Halatte (France); Rahmani, R. [INRA, ToxAlim, 400 route des Chappes, BP, 167 06903 Sophia Antipolis, Cedex (France); Pery, A.R.R., E-mail: alexandre.pery@agroparistech.fr [AgroParisTech, UMR 1402 INRA-AgroParisTech Ecosys, 78850 Thiverval Grignon (France); INRA, UMR 1402 INRA-AgroParisTech Ecosys, 78850 Thiverval Grignon (France)

2016-08-15

Cosmetic products generally consist of multiple ingredients. Thus, cosmetic risk assessment has to deal with mixture toxicity on a long-term scale which means it has to be assessed in the context of repeated exposure. Given that animal testing has been banned for cosmetics risk assessment, in vitro assays allowing long-term repeated exposure and adapted for in vitro – in vivo extrapolation need to be developed. However, most in vitro tests only assess short-term effects and consider static endpoints which hinder extrapolation to realistic human exposure scenarios where concentration in target organs is varies over time. Thanks to impedance metrics, real-time cell viability monitoring for repeated exposure has become possible. We recently constructed biokinetic/toxicodynamic models (BK/TD) to analyze such data (Teng et al., 2015) for three hepatotoxic cosmetic ingredients: coumarin, isoeugenol and benzophenone-2. In the present study, we aim to apply these models to analyze the dynamics of mixture impedance data using the concepts of concentration addition and independent action. Metabolic interactions between the mixture components were investigated, characterized and implemented in the models, as they impacted the actual cellular exposure. Indeed, cellular metabolism following mixture exposure induced a quick disappearance of the compounds from the exposure system. We showed that isoeugenol substantially decreased the metabolism of benzophenone-2, reducing the disappearance of this compound and enhancing its in vitro toxicity. Apart from this metabolic interaction, no mixtures showed any interaction, and all binary mixtures were successfully modeled by at least one model based on exposure to the individual compounds. - Highlights: • We could predict cell response over repeated exposure to mixtures of cosmetics. • Compounds acted independently on the cells. • Metabolic interactions impacted exposure concentrations to the compounds.

Analysis of real-time mixture cytotoxicity data following repeated exposure using BK/TD models.

Science.gov (United States)

Teng, S; Tebby, C; Barcellini-Couget, S; De Sousa, G; Brochot, C; Rahmani, R; Pery, A R R

2016-08-15

Cosmetic products generally consist of multiple ingredients. Thus, cosmetic risk assessment has to deal with mixture toxicity on a long-term scale which means it has to be assessed in the context of repeated exposure. Given that animal testing has been banned for cosmetics risk assessment, in vitro assays allowing long-term repeated exposure and adapted for in vitro - in vivo extrapolation need to be developed. However, most in vitro tests only assess short-term effects and consider static endpoints which hinder extrapolation to realistic human exposure scenarios where concentration in target organs is varies over time. Thanks to impedance metrics, real-time cell viability monitoring for repeated exposure has become possible. We recently constructed biokinetic/toxicodynamic models (BK/TD) to analyze such data (Teng et al., 2015) for three hepatotoxic cosmetic ingredients: coumarin, isoeugenol and benzophenone-2. In the present study, we aim to apply these models to analyze the dynamics of mixture impedance data using the concepts of concentration addition and independent action. Metabolic interactions between the mixture components were investigated, characterized and implemented in the models, as they impacted the actual cellular exposure. Indeed, cellular metabolism following mixture exposure induced a quick disappearance of the compounds from the exposure system. We showed that isoeugenol substantially decreased the metabolism of benzophenone-2, reducing the disappearance of this compound and enhancing its in vitro toxicity. Apart from this metabolic interaction, no mixtures showed any interaction, and all binary mixtures were successfully modeled by at least one model based on exposure to the individual compounds. Copyright © 2016 Elsevier Inc. All rights reserved.

Effects of Test Conditions on APA Rutting and Prediction Modeling for Asphalt Mixtures

Directory of Open Access Journals (Sweden)

Hui Wang

2017-01-01

Full Text Available APA rutting tests were conducted for six kinds of asphalt mixtures under air-dry and immersing conditions. The influences of test conditions, including load, temperature, air voids, and moisture, on APA rutting depth were analyzed by using grey correlation method, and the APA rutting depth prediction model was established. Results show that the modified asphalt mixtures have bigger rutting depth ratios of air-dry to immersing conditions, indicating that the modified asphalt mixtures have better antirutting properties and water stability than the matrix asphalt mixtures. The grey correlation degrees of temperature, load, air void, and immersing conditions on APA rutting depth decrease successively, which means that temperature is the most significant influencing factor. The proposed indoor APA rutting prediction model has good prediction accuracy, and the correlation coefficient between the predicted and the measured rutting depths is 96.3%.

Microbial comparative pan-genomics using binomial mixture models

Directory of Open Access Journals (Sweden)

Ussery David W

2009-08-01

Full Text Available Abstract Background The size of the core- and pan-genome of bacterial species is a topic of increasing interest due to the growing number of sequenced prokaryote genomes, many from the same species. Attempts to estimate these quantities have been made, using regression methods or mixture models. We extend the latter approach by using statistical ideas developed for capture-recapture problems in ecology and epidemiology. Results We estimate core- and pan-genome sizes for 16 different bacterial species. The results reveal a complex dependency structure for most species, manifested as heterogeneous detection probabilities. Estimated pan-genome sizes range from small (around 2600 gene families in Buchnera aphidicola to large (around 43000 gene families in Escherichia coli. Results for Echerichia coli show that as more data become available, a larger diversity is estimated, indicating an extensive pool of rarely occurring genes in the population. Conclusion Analyzing pan-genomics data with binomial mixture models is a way to handle dependencies between genomes, which we find is always present. A bottleneck in the estimation procedure is the annotation of rarely occurring genes.

Equivalence of truncated count mixture distributions and mixtures of truncated count distributions.

Science.gov (United States)

Böhning, Dankmar; Kuhnert, Ronny

2006-12-01

This article is about modeling count data with zero truncation. A parametric count density family is considered. The truncated mixture of densities from this family is different from the mixture of truncated densities from the same family. Whereas the former model is more natural to formulate and to interpret, the latter model is theoretically easier to treat. It is shown that for any mixing distribution leading to a truncated mixture, a (usually different) mixing distribution can be found so that the associated mixture of truncated densities equals the truncated mixture, and vice versa. This implies that the likelihood surfaces for both situations agree, and in this sense both models are equivalent. Zero-truncated count data models are used frequently in the capture-recapture setting to estimate population size, and it can be shown that the two Horvitz-Thompson estimators, associated with the two models, agree. In particular, it is possible to achieve strong results for mixtures of truncated Poisson densities, including reliable, global construction of the unique NPMLE (nonparametric maximum likelihood estimator) of the mixing distribution, implying a unique estimator for the population size. The benefit of these results lies in the fact that it is valid to work with the mixture of truncated count densities, which is less appealing for the practitioner but theoretically easier. Mixtures of truncated count densities form a convex linear model, for which a developed theory exists, including global maximum likelihood theory as well as algorithmic approaches. Once the problem has been solved in this class, it might readily be transformed back to the original problem by means of an explicitly given mapping. Applications of these ideas are given, particularly in the case of the truncated Poisson family.

Concentration addition, independent action and generalized concentration addition models for mixture effect prediction of sex hormone synthesis in vitro.

Directory of Open Access Journals (Sweden)

Niels Hadrup

Full Text Available Humans are concomitantly exposed to numerous chemicals. An infinite number of combinations and doses thereof can be imagined. For toxicological risk assessment the mathematical prediction of mixture effects, using knowledge on single chemicals, is therefore desirable. We investigated pros and cons of the concentration addition (CA, independent action (IA and generalized concentration addition (GCA models. First we measured effects of single chemicals and mixtures thereof on steroid synthesis in H295R cells. Then single chemical data were applied to the models; predictions of mixture effects were calculated and compared to the experimental mixture data. Mixture 1 contained environmental chemicals adjusted in ratio according to human exposure levels. Mixture 2 was a potency adjusted mixture containing five pesticides. Prediction of testosterone effects coincided with the experimental Mixture 1 data. In contrast, antagonism was observed for effects of Mixture 2 on this hormone. The mixtures contained chemicals exerting only limited maximal effects. This hampered prediction by the CA and IA models, whereas the GCA model could be used to predict a full dose response curve. Regarding effects on progesterone and estradiol, some chemicals were having stimulatory effects whereas others had inhibitory effects. The three models were not applicable in this situation and no predictions could be performed. Finally, the expected contributions of single chemicals to the mixture effects were calculated. Prochloraz was the predominant but not sole driver of the mixtures, suggesting that one chemical alone was not responsible for the mixture effects. In conclusion, the GCA model seemed to be superior to the CA and IA models for the prediction of testosterone effects. A situation with chemicals exerting opposing effects, for which the models could not be applied, was identified. In addition, the data indicate that in non-potency adjusted mixtures the effects cannot

XDGMM: eXtreme Deconvolution Gaussian Mixture Modeling

Science.gov (United States)

Holoien, Thomas W.-S.; Marshall, Philip J.; Wechsler, Risa H.

2017-08-01

XDGMM uses Gaussian mixtures to do density estimation of noisy, heterogenous, and incomplete data using extreme deconvolution (XD) algorithms which is compatible with the scikit-learn machine learning methods. It implements both the astroML and Bovy et al. (2011) algorithms, and extends the BaseEstimator class from scikit-learn so that cross-validation methods work. It allows the user to produce a conditioned model if values of some parameters are known.

Excess Properties of Aqueous Mixtures of Methanol: Simple Models Versus Experiment

Czech Academy of Sciences Publication Activity Database

Vlček, Lukáš; Nezbeda, Ivo

roč. 131-132, - (2007), s. 158-162 ISSN 0167-7322. [International Conference on Solution Chemistry /29./. Portorož, 21.08.2005-25.08.2005] R&D Projects: GA AV ČR(CZ) IAA4072303; GA AV ČR(CZ) 1ET400720409 Institutional research plan: CEZ:AV0Z40720504 Keywords : aqueous mixtures * primitive models * water-alcohol mixtures Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 0.982, year: 2007

Microbial Content of “Bowl Water” Used for Communal Handwashing in Preschools within Accra Metropolis, Ghana

Directory of Open Access Journals (Sweden)

Patience B. Tetteh-Quarcoo

2016-01-01

Full Text Available Objective. This study aimed at determining the microbial content of “bowl water” used for communal handwashing in preschools within the Accra Metropolis. Method. Six (6 preschools in the Accra Metropolis were involved in the study. Water samples and swabs from the hands of the preschool children were collected. The samples were analysed and tested for bacteria, fungi, parasites, and rotavirus. Results. Eight different bacteria, two different parasites, and a fungus were isolated while no rotavirus was detected. Unlike the rest of the microbes, bacterial isolates were found among samples from all the schools, with Staphylococcus species being the most prevalent (40.9%. Out of the three schools that had parasites in their water, two of them had Cryptosporidium parvum. The fungus isolated from two out of the six schools was Aspergillus niger. All bacteria isolated were found to be resistant to cotrimoxazole, ciprofloxacin, and ampicillin and susceptible to amikacin and levofloxacin. Conclusion. Although handwashing has the ability to get rid of microbes, communal handwashing practices using water in bowls could be considered a possible transmission route and may be of public concern.

The Metropolis Monte Carlo method with CUDA enabled Graphic Processing Units

Energy Technology Data Exchange (ETDEWEB)

Hall, Clifford [Computational Materials Science Center, George Mason University, 4400 University Dr., Fairfax, VA 22030 (United States); School of Physics, Astronomy, and Computational Sciences, George Mason University, 4400 University Dr., Fairfax, VA 22030 (United States); Ji, Weixiao [Computational Materials Science Center, George Mason University, 4400 University Dr., Fairfax, VA 22030 (United States); Blaisten-Barojas, Estela, E-mail: blaisten@gmu.edu [Computational Materials Science Center, George Mason University, 4400 University Dr., Fairfax, VA 22030 (United States); School of Physics, Astronomy, and Computational Sciences, George Mason University, 4400 University Dr., Fairfax, VA 22030 (United States)

2014-02-01

We present a CPU–GPU system for runtime acceleration of large molecular simulations using GPU computation and memory swaps. The memory architecture of the GPU can be used both as container for simulation data stored on the graphics card and as floating-point code target, providing an effective means for the manipulation of atomistic or molecular data on the GPU. To fully take advantage of this mechanism, efficient GPU realizations of algorithms used to perform atomistic and molecular simulations are essential. Our system implements a versatile molecular engine, including inter-molecule interactions and orientational variables for performing the Metropolis Monte Carlo (MMC) algorithm, which is one type of Markov chain Monte Carlo. By combining memory objects with floating-point code fragments we have implemented an MMC parallel engine that entirely avoids the communication time of molecular data at runtime. Our runtime acceleration system is a forerunner of a new class of CPU–GPU algorithms exploiting memory concepts combined with threading for avoiding bus bandwidth and communication. The testbed molecular system used here is a condensed phase system of oligopyrrole chains. A benchmark shows a size scaling speedup of 60 for systems with 210,000 pyrrole monomers. Our implementation can easily be combined with MPI to connect in parallel several CPU–GPU duets. -- Highlights: •We parallelize the Metropolis Monte Carlo (MMC) algorithm on one CPU—GPU duet. •The Adaptive Tempering Monte Carlo employs MMC and profits from this CPU—GPU implementation. •Our benchmark shows a size scaling-up speedup of 62 for systems with 225,000 particles. •The testbed involves a polymeric system of oligopyrroles in the condensed phase. •The CPU—GPU parallelization includes dipole—dipole and Mie—Jones classic potentials.

The Metropolis Monte Carlo method with CUDA enabled Graphic Processing Units

International Nuclear Information System (INIS)

Hall, Clifford; Ji, Weixiao; Blaisten-Barojas, Estela

2014-01-01

We present a CPU–GPU system for runtime acceleration of large molecular simulations using GPU computation and memory swaps. The memory architecture of the GPU can be used both as container for simulation data stored on the graphics card and as floating-point code target, providing an effective means for the manipulation of atomistic or molecular data on the GPU. To fully take advantage of this mechanism, efficient GPU realizations of algorithms used to perform atomistic and molecular simulations are essential. Our system implements a versatile molecular engine, including inter-molecule interactions and orientational variables for performing the Metropolis Monte Carlo (MMC) algorithm, which is one type of Markov chain Monte Carlo. By combining memory objects with floating-point code fragments we have implemented an MMC parallel engine that entirely avoids the communication time of molecular data at runtime. Our runtime acceleration system is a forerunner of a new class of CPU–GPU algorithms exploiting memory concepts combined with threading for avoiding bus bandwidth and communication. The testbed molecular system used here is a condensed phase system of oligopyrrole chains. A benchmark shows a size scaling speedup of 60 for systems with 210,000 pyrrole monomers. Our implementation can easily be combined with MPI to connect in parallel several CPU–GPU duets. -- Highlights: •We parallelize the Metropolis Monte Carlo (MMC) algorithm on one CPU—GPU duet. •The Adaptive Tempering Monte Carlo employs MMC and profits from this CPU—GPU implementation. •Our benchmark shows a size scaling-up speedup of 62 for systems with 225,000 particles. •The testbed involves a polymeric system of oligopyrroles in the condensed phase. •The CPU—GPU parallelization includes dipole—dipole and Mie—Jones classic potentials.

Note: A pure-sampling quantum Monte Carlo algorithm with independent Metropolis

Energy Technology Data Exchange (ETDEWEB)

Vrbik, Jan [Department of Mathematics, Brock University, St. Catharines, Ontario L2S 3A1 (Canada); Ospadov, Egor; Rothstein, Stuart M., E-mail: srothstein@brocku.ca [Department of Physics, Brock University, St. Catharines, Ontario L2S 3A1 (Canada)

2016-07-14

Recently, Ospadov and Rothstein published a pure-sampling quantum Monte Carlo algorithm (PSQMC) that features an auxiliary Path Z that connects the midpoints of the current and proposed Paths X and Y, respectively. When sufficiently long, Path Z provides statistical independence of Paths X and Y. Under those conditions, the Metropolis decision used in PSQMC is done without any approximation, i.e., not requiring microscopic reversibility and without having to introduce any G(x → x′; τ) factors into its decision function. This is a unique feature that contrasts with all competing reptation algorithms in the literature. An example illustrates that dependence of Paths X and Y has adverse consequences for pure sampling.

Note: A pure-sampling quantum Monte Carlo algorithm with independent Metropolis

International Nuclear Information System (INIS)

Vrbik, Jan; Ospadov, Egor; Rothstein, Stuart M.

2016-01-01

Recently, Ospadov and Rothstein published a pure-sampling quantum Monte Carlo algorithm (PSQMC) that features an auxiliary Path Z that connects the midpoints of the current and proposed Paths X and Y, respectively. When sufficiently long, Path Z provides statistical independence of Paths X and Y. Under those conditions, the Metropolis decision used in PSQMC is done without any approximation, i.e., not requiring microscopic reversibility and without having to introduce any G(x → x′; τ) factors into its decision function. This is a unique feature that contrasts with all competing reptation algorithms in the literature. An example illustrates that dependence of Paths X and Y has adverse consequences for pure sampling.

Concentration addition and independent action model: Which is better in predicting the toxicity for metal mixtures on zebrafish larvae.

Science.gov (United States)

Gao, Yongfei; Feng, Jianfeng; Kang, Lili; Xu, Xin; Zhu, Lin

2018-01-01

The joint toxicity of chemical mixtures has emerged as a popular topic, particularly on the additive and potential synergistic actions of environmental mixtures. We investigated the 24h toxicity of Cu-Zn, Cu-Cd, and Cu-Pb and 96h toxicity of Cd-Pb binary mixtures on the survival of zebrafish larvae. Joint toxicity was predicted and compared using the concentration addition (CA) and independent action (IA) models with different assumptions in the toxic action mode in toxicodynamic processes through single and binary metal mixture tests. Results showed that the CA and IA models presented varying predictive abilities for different metal combinations. For the Cu-Cd and Cd-Pb mixtures, the CA model simulated the observed survival rates better than the IA model. By contrast, the IA model simulated the observed survival rates better than the CA model for the Cu-Zn and Cu-Pb mixtures. These findings revealed that the toxic action mode may depend on the combinations and concentrations of tested metal mixtures. Statistical analysis of the antagonistic or synergistic interactions indicated that synergistic interactions were observed for the Cu-Cd and Cu-Pb mixtures, non-interactions were observed for the Cd-Pb mixtures, and slight antagonistic interactions for the Cu-Zn mixtures. These results illustrated that the CA and IA models are consistent in specifying the interaction patterns of binary metal mixtures. Copyright © 2017 Elsevier B.V. All rights reserved.

A general mixture model for mapping quantitative trait loci by using molecular markers

NARCIS (Netherlands)

Jansen, R.C.

1992-01-01

In a segregating population a quantitative trait may be considered to follow a mixture of (normal) distributions, the mixing proportions being based on Mendelian segregation rules. A general and flexible mixture model is proposed for mapping quantitative trait loci (QTLs) by using molecular markers.

Genetic Analysis of Somatic Cell Score in Danish Holsteins Using a Liability-Normal Mixture Model

DEFF Research Database (Denmark)

Madsen, P; Shariati, M M; Ødegård, J

2008-01-01

Mixture models are appealing for identifying hidden structures affecting somatic cell score (SCS) data, such as unrecorded cases of subclinical mastitis. Thus, liability-normal mixture (LNM) models were used for genetic analysis of SCS data, with the aim of predicting breeding values for such cas...

Latent Transition Analysis with a Mixture Item Response Theory Measurement Model

Science.gov (United States)

Cho, Sun-Joo; Cohen, Allan S.; Kim, Seock-Ho; Bottge, Brian

2010-01-01

A latent transition analysis (LTA) model was described with a mixture Rasch model (MRM) as the measurement model. Unlike the LTA, which was developed with a latent class measurement model, the LTA-MRM permits within-class variability on the latent variable, making it more useful for measuring treatment effects within latent classes. A simulation…

Modelling of associating mixtures for applications in the oil & gas and chemical industries

DEFF Research Database (Denmark)

Kontogeorgis, Georgios; Folas, Georgios; Muro Sunè, Nuria

2007-01-01

Thermodynamic properties and phase equilibria of associating mixtures cannot often be satisfactorily modelled using conventional models such as cubic equations of state. CPA (cubic-plus-association) is an equation of state (EoS), which combines the SRK EoS with the association term of SAFT. For non......-alcohol (glycol)-alkanes and certain acid and amine-containing mixtures. Recent results include glycol-aromatic hydrocarbons including multiphase, multicomponent equilibria and gas hydrate calculations in combination with the van der Waals-Platteeuw model. This article will outline some new applications...... thermodynamic models especially those combining cubic EoS with local composition activity coefficient models are included. (C) 2007 Elsevier B.V. All rights reserved....

Mixture

Directory of Open Access Journals (Sweden)

Silva-Aguilar Martín

2011-01-01

Full Text Available Metals are ubiquitous pollutants present as mixtures. In particular, mixture of arsenic-cadmium-lead is among the leading toxic agents detected in the environment. These metals have carcinogenic and cell-transforming potential. In this study, we used a two step cell transformation model, to determine the role of oxidative stress in transformation induced by a mixture of arsenic-cadmium-lead. Oxidative damage and antioxidant response were determined. Metal mixture treatment induces the increase of damage markers and the antioxidant response. Loss of cell viability and increased transforming potential were observed during the promotion phase. This finding correlated significantly with generation of reactive oxygen species. Cotreatment with N-acetyl-cysteine induces effect on the transforming capacity; while a diminution was found in initiation, in promotion phase a total block of the transforming capacity was observed. Our results suggest that oxidative stress generated by metal mixture plays an important role only in promotion phase promoting transforming capacity.

Data Requirements and Modeling for Gas Hydrate-Related Mixtures and a Comparison of Two Association Models

DEFF Research Database (Denmark)

Liang, Xiaodong; Aloupis, Georgios; Kontogeorgis, Georgios M.

2017-01-01

the performance of the CPA and sPC-SAFT EOS for modeling the fluid-phase equilibria of gas hydrate-related systems and will try to explore how the models can help in suggesting experimental measurements. These systems contain water, hydrocarbon (alkane or aromatic), and either methanol or monoethylene glycol...... parameter sets have been chosen for the sPC-SAFT EOS for a fair comparison. The comparisons are made for pure fluid properties, vapor liquid-equilibria, and liquid liquid equilibria of binary and ternary mixtures as well as vapor liquid liquid equilibria of quaternary mixtures. The results show, from...

Household solid waste generation rate and physical composition analysis: case of Sekondi-Takoradi Metropolis in the western region, Ghana

Directory of Open Access Journals (Sweden)

Eugene Atta Nyankson

2015-06-01

Full Text Available Sekondi-Takoradi Metropolis, one of the rapidly expanding cities of Ghana has been facing serious problems with solid waste management. This is mainly due to the lack of available information about the types and quantity of solid waste generation in the area. Hence, the objective of this study was to determine the rate of household solid waste generation and its composition in the aforesaid city. The methodology and procedures for this study were derived from the Standard Test Method for Determination of the Composition of Unprocessed MSW (ASTM D 5231-92. All samples were hand sorted into 6 waste categories (paper, plastic, organics, metals, glass, and other waste. The study revealed that by weight, organic wastes constitutes the largest proportion of household solid waste (38% followed by 19% plastics, 7% papers, 4% metals, 4% glass and 28% other wastes (comprising of sand, stones, ash, inert substances. The rate of daily waste generation per capita in the low, middle and high income households were 0.27±0.19, 0.4±0.19 and 0.58±0.24 kg/cap/day, respectively. The study revealed that there is no waste treatment or recovery facility established within the metropolis hence no significant waste recovery and reuse activities exist. The study showed that more than 38 % of the waste generated in Sekondi-Takoradi Metropolis is decomposable organic matter that can be re-used through composting as well as 34% of the waste having recycling potential thereby considerably mitigating the solid waste problem. DOI: http://dx.doi.org/10.3126/ije.v4i2.12644 International Journal of Environment Vol.4(2 2015: 221-235

Modeling the surface tension of complex, reactive organic-inorganic mixtures

Science.gov (United States)

Schwier, A. N.; Viglione, G. A.; Li, Z.; McNeill, V. Faye

2013-11-01

Atmospheric aerosols can contain thousands of organic compounds which impact aerosol surface tension, affecting aerosol properties such as heterogeneous reactivity, ice nucleation, and cloud droplet formation. We present new experimental data for the surface tension of complex, reactive organic-inorganic aqueous mixtures mimicking tropospheric aerosols. Each solution contained 2-6 organic compounds, including methylglyoxal, glyoxal, formaldehyde, acetaldehyde, oxalic acid, succinic acid, leucine, alanine, glycine, and serine, with and without ammonium sulfate. We test two semi-empirical surface tension models and find that most reactive, complex, aqueous organic mixtures which do not contain salt are well described by a weighted Szyszkowski-Langmuir (S-L) model which was first presented by Henning et al. (2005). Two approaches for modeling the effects of salt were tested: (1) the Tuckermann approach (an extension of the Henning model with an additional explicit salt term), and (2) a new implicit method proposed here which employs experimental surface tension data obtained for each organic species in the presence of salt used with the Henning model. We recommend the use of method (2) for surface tension modeling of aerosol systems because the Henning model (using data obtained from organic-inorganic systems) and Tuckermann approach provide similar modeling results and goodness-of-fit (χ2) values, yet the Henning model is a simpler and more physical approach to modeling the effects of salt, requiring less empirically determined parameters.

Combinatorial bounds on the α-divergence of univariate mixture models

KAUST Repository

Nielsen, Frank; Sun, Ke

2017-01-01

We derive lower- and upper-bounds of α-divergence between univariate mixture models with components in the exponential family. Three pairs of bounds are presented in order with increasing quality and increasing computational cost. They are verified

General mixture item response models with different item response structures: Exposition with an application to Likert scales.

Science.gov (United States)

Tijmstra, Jesper; Bolsinova, Maria; Jeon, Minjeong

2018-01-10

This article proposes a general mixture item response theory (IRT) framework that allows for classes of persons to differ with respect to the type of processes underlying the item responses. Through the use of mixture models, nonnested IRT models with different structures can be estimated for different classes, and class membership can be estimated for each person in the sample. If researchers are able to provide competing measurement models, this mixture IRT framework may help them deal with some violations of measurement invariance. To illustrate this approach, we consider a two-class mixture model, where a person's responses to Likert-scale items containing a neutral middle category are either modeled using a generalized partial credit model, or through an IRTree model. In the first model, the middle category ("neither agree nor disagree") is taken to be qualitatively similar to the other categories, and is taken to provide information about the person's endorsement. In the second model, the middle category is taken to be qualitatively different and to reflect a nonresponse choice, which is modeled using an additional latent variable that captures a person's willingness to respond. The mixture model is studied using simulation studies and is applied to an empirical example.

A nonparametric mixture model for cure rate estimation.

Science.gov (United States)

Peng, Y; Dear, K B

2000-03-01

Nonparametric methods have attracted less attention than their parametric counterparts for cure rate analysis. In this paper, we study a general nonparametric mixture model. The proportional hazards assumption is employed in modeling the effect of covariates on the failure time of patients who are not cured. The EM algorithm, the marginal likelihood approach, and multiple imputations are employed to estimate parameters of interest in the model. This model extends models and improves estimation methods proposed by other researchers. It also extends Cox's proportional hazards regression model by allowing a proportion of event-free patients and investigating covariate effects on that proportion. The model and its estimation method are investigated by simulations. An application to breast cancer data, including comparisons with previous analyses using a parametric model and an existing nonparametric model by other researchers, confirms the conclusions from the parametric model but not those from the existing nonparametric model.

Finite mixture models for sub-pixel coastal land cover classification

CSIR Research Space (South Africa)

Ritchie, Michaela C

2017-05-01

Full Text Available Models for Sub- pixel Coastal Land Cover Classification M. Ritchie Dr. M. Lück-Vogel Dr. P. Debba Dr. V. Goodall ISRSE - 37 Tshwane, South Africa 10 May 2017 2Study Area Africa South Africa FALSE BAY 3Strand Gordon’s Bay Study Area WorldView-2 Image.../Urban 1 10 10 Herbaceous Vegetation 1 5 5 Shadow 1 8 8 Sparse Vegetation 1 3 3 Water 1 10 10 Woody Vegetation 1 5 5 11 Maximum Likelihood Classification (MLC) 12 Gaussian Mixture Discriminant Analysis (GMDA) 13 A B C t-distribution Mixture Discriminant...

Instructional Methods and Students' End of Term Achievement in Biology in Selected Secondary Schools in Sokoto Metropolis, Sokoto State Nigeria

Science.gov (United States)

Shamsuddeen, Abdulrahman; Amina, Hassan

2016-01-01

This study investigated the Correlation between instructional methods and students end of term achievement in Biology in selected secondary schools in Sokoto Metropolis, Sokoto State Nigeria. The study addressed three Specific objectives. To examine the relationship between; Cooperative learning methods, guided discovery, Simulation Method and…

Dynamic classification of fetal heart rates by hierarchical Dirichlet process mixture models.

Directory of Open Access Journals (Sweden)

Kezi Yu

Full Text Available In this paper, we propose an application of non-parametric Bayesian (NPB models for classification of fetal heart rate (FHR recordings. More specifically, we propose models that are used to differentiate between FHR recordings that are from fetuses with or without adverse outcomes. In our work, we rely on models based on hierarchical Dirichlet processes (HDP and the Chinese restaurant process with finite capacity (CRFC. Two mixture models were inferred from real recordings, one that represents healthy and another, non-healthy fetuses. The models were then used to classify new recordings and provide the probability of the fetus being healthy. First, we compared the classification performance of the HDP models with that of support vector machines on real data and concluded that the HDP models achieved better performance. Then we demonstrated the use of mixture models based on CRFC for dynamic classification of the performance of (FHR recordings in a real-time setting.

Quality of life of deaf and hard of hearing students in Ibadan metropolis, Nigeria.

Science.gov (United States)

Jaiyeola, Mofadeke T; Adeyemo, Adebolajo A

2018-01-01

Quality of Life encompasses an individual's well-being and health, social participation and satisfaction with functional daily living. Disabilities such as deafness can impact on the quality of life with spatial variance to the environment. Deafness causes communicative problems with significant consequences in cognitive, social, and emotional well-being of affected individuals. However, information relating to the quality of life of deaf and hard of hearing individuals, especially students in developing countries like Nigeria, which could be used to design special health-related interventions is sparse. This study examined the quality of life of deaf and hard of hearing students in Ibadan metropolis, Nigeria. One hundred and ten deaf and hard of hearing students participated in this cross-sectional study. Participants were drawn from all four secondary schools for the Deaf in Ibadan metropolis. The 26 item Brief version of the WHO Quality of Life questionnaire was used for data collection. The data was analyzed using descriptive and inferential statistics at statistical significance of pdeaf and hard of hearing students had poor quality of life. Attending the special school for the Deaf, upper socio-economic status and age (≥17years) are significantly associated with better quality of life. However, gender and age at onset of hearing loss had no significant influence on the quality of life. The Deaf community available in the special school appeared to protect against stigma and discrimination, while also promoting social interactions between deaf and hard of hearing individuals.

Metropolis Parking Problems and Management Planning Solutions for Traffic Operation Effectiveness

Directory of Open Access Journals (Sweden)

Yuejun Liu

2012-01-01

Full Text Available Advances in mobility are clearly illustrated by the rapid development of urbanization and motorization in developing countries. Following the dramatic incensement of traffic demand, the parking problem has been becoming much more seriously important in many metropolises. With the aim of seeking solutions as to how the parking system could operate more efficiently by using new technologies and new methodologies, this paper discusses the application of geographic information system into the parking planning and management for traffic operation effectiveness in metropolis. The concentration of this paper includes the characteristics of parking demand and the causations of parking problems, especially the basic parking principle and strategies for solving parking problems from the perspective of geographic information system are discussed in enough detail in this paper.

Modelling phase equilibria for acid gas mixtures using the CPA equation of state. Part V: Multicomponent mixtures containing CO₂ and alcohols

DEFF Research Database (Denmark)

Tsivintzelis, Ioannis; Kontogeorgis, Georgios M.

2015-01-01

of CPA for ternary and multicomponent CO2 mixtures containing alcohols (methanol, ethanol or propanol) water and hydrocarbons. This work belongs to a series of studies aiming to arrive in a single "engineering approach" for applying CPA to acid gas mixtures, without introducing significant changes...... to the model. In this direction, CPA results were obtained using various approaches, i.e. different association schemes for pure CO2 (assuming that it is a non-associating compound, or that it is a self-associating fluid with two, three or four association sites) and different possibilities for modelling...... mixtures of CO2 with water and alcohols (only use of one interaction parameter kij or assuming cross-association interactions and obtaining the relevant parameters either via a combining rule or using an experimental value for the cross-association energy). It is concluded that CPA is a powerful model...

Detecting Math Anxiety with a Mixture Partial Credit Model

Science.gov (United States)

Ölmez, Ibrahim Burak; Cohen, Allan S.

2017-01-01

The purpose of this study was to investigate a new methodology for detection of differences in middle grades students' math anxiety. A mixture partial credit model analysis revealed two distinct latent classes based on homogeneities in response patterns within each latent class. Students in Class 1 had less anxiety about apprehension of math…

A general mixture theory. I. Mixtures of spherical molecules

Science.gov (United States)

Hamad, Esam Z.

1996-08-01

We present a new general theory for obtaining mixture properties from the pure species equations of state. The theory addresses the composition and the unlike interactions dependence of mixture equation of state. The density expansion of the mixture equation gives the exact composition dependence of all virial coefficients. The theory introduces multiple-index parameters that can be calculated from binary unlike interaction parameters. In this first part of the work, details are presented for the first and second levels of approximations for spherical molecules. The second order model is simple and very accurate. It predicts the compressibility factor of additive hard spheres within simulation uncertainty (equimolar with size ratio of three). For nonadditive hard spheres, comparison with compressibility factor simulation data over a wide range of density, composition, and nonadditivity parameter, gave an average error of 2%. For mixtures of Lennard-Jones molecules, the model predictions are better than the Weeks-Chandler-Anderson perturbation theory.

A globally accurate theory for a class of binary mixture models

Science.gov (United States)

Dickman, Adriana G.; Stell, G.

The self-consistent Ornstein-Zernike approximation results for the 3D Ising model are used to obtain phase diagrams for binary mixtures described by decorated models, yielding the plait point, binodals, and closed-loop coexistence curves for the models proposed by Widom, Clark, Neece, and Wheeler. The results are in good agreement with series expansions and experiments.

Application of the Electronic Nose Technique to Differentiation between Model Mixtures with COPD Markers

Directory of Open Access Journals (Sweden)

Jacek Namieśnik

2013-04-01

Full Text Available The paper presents the potential of an electronic nose technique in the field of fast diagnostics of patients suspected of Chronic Obstructive Pulmonary Disease (COPD. The investigations were performed using a simple electronic nose prototype equipped with a set of six semiconductor sensors manufactured by FIGARO Co. They were aimed at verification of a possibility of differentiation between model reference mixtures with potential COPD markers (N,N-dimethylformamide and N,N-dimethylacetamide. These mixtures contained volatile organic compounds (VOCs such as acetone, isoprene, carbon disulphide, propan-2-ol, formamide, benzene, toluene, acetonitrile, acetic acid, dimethyl ether, dimethyl sulphide, acrolein, furan, propanol and pyridine, recognized as the components of exhaled air. The model reference mixtures were prepared at three concentration levels—10 ppb, 25 ppb, 50 ppb v/v—of each component, except for the COPD markers. Concentration of the COPD markers in the mixtures was from 0 ppb to 100 ppb v/v. Interpretation of the obtained data employed principal component analysis (PCA. The investigations revealed the usefulness of the electronic device only in the case when the concentration of the COPD markers was twice as high as the concentration of the remaining components of the mixture and for a limited number of basic mixture components.

Modeling phase equilibria for acid gas mixtures using the CPA equation of state. Part IV. Applications to mixtures of CO2 with alkanes

DEFF Research Database (Denmark)

Tsivintzelis, Ioannis; Ali, Shahid; Kontogeorgis, Georgios

2015-01-01

The thermodynamic properties of pure gaseous, liquid or supercritical CO2 and CO2 mixtures with hydrocarbons and other compounds such as water, alcohols, and glycols are very important in many processes in the oil and gas industry. Design of such processes requires use of accurate thermodynamic...... models, capable of predicting the complex phase behavior of multicomponent mixtures as well as their volumetric properties. In this direction, over the last several years, the cubic-plus-association (CPA) thermodynamic model has been successfully used for describing volumetric properties and phase...

Language Barrier And The Performance of Secondary School Students in EnglishLanguage in Katsina Metropolis

OpenAIRE

Nwabudike Christopher Eziafa; Ojoko E. A.; George Anaso Nwaorah

2014-01-01

This research work centres on Language Barrier and the Performance of Secondary School Students in English Language in Katsina Metropolis. The study identifies the causes of failure in English Language in secondary schools, the factors responsible for the inability of students to learn English language as a second language and the effect of mother tongue interference on the performance of students in English language in the study area. Data for this study  were collected through the use of st...

I-optimal mixture designs

OpenAIRE

GOOS, Peter; JONES, Bradley; SYAFITRI, Utami

2013-01-01

In mixture experiments, the factors under study are proportions of the ingredients of a mixture. The special nature of the factors in a mixture experiment necessitates specific types of regression models, and specific types of experimental designs. Although mixture experiments usually are intended to predict the response(s) for all possible formulations of the mixture and to identify optimal proportions for each of the ingredients, little research has been done concerning their I-optimal desi...

Equilibrium based analytical model for estimation of pressure magnification during deflagration of hydrogen air mixtures

Energy Technology Data Exchange (ETDEWEB)

Karanam, Aditya; Sharma, Pavan K.; Ganju, Sunil; Singh, Ram Kumar [Bhabha Atomic Research Centre (BARC), Mumbai (India). Reactor Safety Div.

2016-12-15

During postulated accident sequences in nuclear reactors, hydrogen may get released from the core and form a flammable mixture in the surrounding containment structure. Ignition of such mixtures and the subsequent pressure rise are an imminent threat for safe and sustainable operation of nuclear reactors. Methods for evaluating post ignition characteristics are important for determining the design safety margins in such scenarios. This study presents two thermo-chemical models for determining the post ignition state. The first model is based on internal energy balance while the second model uses the concept of element potentials to minimize the free energy of the system with internal energy imposed as a constraint. Predictions from both the models have been compared against published data over a wide range of mixture compositions. Important differences in the regions close to flammability limits and for stoichiometric mixtures have been identified and explained. The equilibrium model has been validated for varied temperatures and pressures representative of initial conditions that may be present in the containment during accidents. Special emphasis has been given to the understanding of the role of dissociation and its effect on equilibrium pressure, temperature and species concentrations.

Equilibrium based analytical model for estimation of pressure magnification during deflagration of hydrogen air mixtures

International Nuclear Information System (INIS)

Karanam, Aditya; Sharma, Pavan K.; Ganju, Sunil; Singh, Ram Kumar

2016-01-01

During postulated accident sequences in nuclear reactors, hydrogen may get released from the core and form a flammable mixture in the surrounding containment structure. Ignition of such mixtures and the subsequent pressure rise are an imminent threat for safe and sustainable operation of nuclear reactors. Methods for evaluating post ignition characteristics are important for determining the design safety margins in such scenarios. This study presents two thermo-chemical models for determining the post ignition state. The first model is based on internal energy balance while the second model uses the concept of element potentials to minimize the free energy of the system with internal energy imposed as a constraint. Predictions from both the models have been compared against published data over a wide range of mixture compositions. Important differences in the regions close to flammability limits and for stoichiometric mixtures have been identified and explained. The equilibrium model has been validated for varied temperatures and pressures representative of initial conditions that may be present in the containment during accidents. Special emphasis has been given to the understanding of the role of dissociation and its effect on equilibrium pressure, temperature and species concentrations.

Thermodynamic parameters for mixtures of quartz under shock wave loading in views of the equilibrium model

International Nuclear Information System (INIS)

Maevskii, K. K.; Kinelovskii, S. A.

2015-01-01

The numerical results of modeling of shock wave loading of mixtures with the SiO 2 component are presented. The TEC (thermodynamic equilibrium component) model is employed to describe the behavior of solid and porous multicomponent mixtures and alloys under shock wave loading. State equations of a Mie–Grüneisen type are used to describe the behavior of condensed phases, taking into account the temperature dependence of the Grüneisen coefficient, gas in pores is one of the components of the environment. The model is based on the assumption that all components of the mixture under shock-wave loading are in thermodynamic equilibrium. The calculation results are compared with the experimental data derived by various authors. The behavior of the mixture containing components with a phase transition under high dynamic loads is described

Adapting cultural mixture modeling for continuous measures of knowledge and memory fluency.

Science.gov (United States)

Tan, Yin-Yin Sarah; Mueller, Shane T

2016-09-01

Previous research (e.g., cultural consensus theory (Romney, Weller, & Batchelder, American Anthropologist, 88, 313-338, 1986); cultural mixture modeling (Mueller & Veinott, 2008)) has used overt response patterns (i.e., responses to questionnaires and surveys) to identify whether a group shares a single coherent attitude or belief set. Yet many domains in social science have focused on implicit attitudes that are not apparent in overt responses but still may be detected via response time patterns. We propose a method for modeling response times as a mixture of Gaussians, adapting the strong-consensus model of cultural mixture modeling to model this implicit measure of knowledge strength. We report the results of two behavioral experiments and one simulation experiment that establish the usefulness of the approach, as well as some of the boundary conditions under which distinct groups of shared agreement might be recovered, even when the group identity is not known. The results reveal that the ability to recover and identify shared-belief groups depends on (1) the level of noise in the measurement, (2) the differential signals for strong versus weak attitudes, and (3) the similarity between group attitudes. Consequently, the method shows promise for identifying latent groups among a population whose overt attitudes do not differ, but whose implicit or covert attitudes or knowledge may differ.

Effective dielectric mixture model for characterization of diesel contaminated soil

International Nuclear Information System (INIS)

Al-Mattarneh, H.M.A.

2007-01-01

Human exposure to contaminated soil by diesel isomers can have serious health consequences like neurological diseases or cancer. The potential of dielectric measuring techniques for electromagnetic characterization of contaminated soils was investigated in this paper. The purpose of the research was to develop an empirical dielectric mixture model for soil hydrocarbon contamination application. The paper described the basic theory and elaborated in dielectric mixture theory. The analytical and empirical models were explained in simple algebraic formulas. The experimental study was then described with reference to materials, properties and experimental results. The results of the analytical models were also mathematically explained. The proposed semi-empirical model was also presented. According to the result of the electromagnetic properties of dry soil contaminated with diesel, the diesel presence had no significant effect on the electromagnetic properties of dry soil. It was concluded that diesel had no contribution to the soil electrical conductivity, which confirmed the nonconductive character of diesel. The results of diesel-contaminated soil at saturation condition indicated that both dielectric constant and loss factors of soil were decreased with increasing diesel content. 15 refs., 2 tabs., 9 figs

Students' Perception of Factors Influencing Teaching and Learning of Mathematics in Senior Secondary Schools in Maiduguri Metropolis, Borno State, Nigeria

Science.gov (United States)

Dauda, Bala; Jambo, Hyelni Emmanuel; Umar, Muhammad Amin

2016-01-01

This study examined students' perception of factors influencing teaching and learning of mathematics in senior secondary schools in Maiduguri Metropolis of Borno State, Nigeria. The objectives of the study were to determine the extent to which students perceived: qualification, method of teaching, instructional materials and attitude of both…

Estimating animal abundance with N-mixture models using the R-INLA package for R

KAUST Repository

Meehan, Timothy D.

2017-05-03

Successful management of wildlife populations requires accurate estimates of abundance. Abundance estimates can be confounded by imperfect detection during wildlife surveys. N-mixture models enable quantification of detection probability and often produce abundance estimates that are less biased. The purpose of this study was to demonstrate the use of the R-INLA package to analyze N-mixture models and to compare performance of R-INLA to two other common approaches -- JAGS (via the runjags package), which uses Markov chain Monte Carlo and allows Bayesian inference, and unmarked, which uses Maximum Likelihood and allows frequentist inference. We show that R-INLA is an attractive option for analyzing N-mixture models when (1) familiar model syntax and data format (relative to other R packages) are desired, (2) survey level covariates of detection are not essential, (3) fast computing times are necessary (R-INLA is 10 times faster than unmarked, 300 times faster than JAGS), and (4) Bayesian inference is preferred.

Using finite mixture models in thermal-hydraulics system code uncertainty analysis

Energy Technology Data Exchange (ETDEWEB)

Carlos, S., E-mail: scarlos@iqn.upv.es [Department d’Enginyeria Química i Nuclear, Universitat Politècnica de València, Camí de Vera s.n, 46022 València (Spain); Sánchez, A. [Department d’Estadística Aplicada i Qualitat, Universitat Politècnica de València, Camí de Vera s.n, 46022 València (Spain); Ginestar, D. [Department de Matemàtica Aplicada, Universitat Politècnica de València, Camí de Vera s.n, 46022 València (Spain); Martorell, S. [Department d’Enginyeria Química i Nuclear, Universitat Politècnica de València, Camí de Vera s.n, 46022 València (Spain)

2013-09-15

Highlights: • Best estimate codes simulation needs uncertainty quantification. • The output variables can present multimodal probability distributions. • The analysis of multimodal distribution is performed using finite mixture models. • Two methods to reconstruct output variable probability distribution are used. -- Abstract: Nuclear Power Plant safety analysis is mainly based on the use of best estimate (BE) codes that predict the plant behavior under normal or accidental conditions. As the BE codes introduce uncertainties due to uncertainty in input parameters and modeling, it is necessary to perform uncertainty assessment (UA), and eventually sensitivity analysis (SA), of the results obtained. These analyses are part of the appropriate treatment of uncertainties imposed by current regulation based on the adoption of the best estimate plus uncertainty (BEPU) approach. The most popular approach for uncertainty assessment, based on Wilks’ method, obtains a tolerance/confidence interval, but it does not completely characterize the output variable behavior, which is required for an extended UA and SA. However, the development of standard UA and SA impose high computational cost due to the large number of simulations needed. In order to obtain more information about the output variable and, at the same time, to keep computational cost as low as possible, there has been a recent shift toward developing metamodels (model of model), or surrogate models, that approximate or emulate complex computer codes. In this way, there exist different techniques to reconstruct the probability distribution using the information provided by a sample of values as, for example, the finite mixture models. In this paper, the Expectation Maximization and the k-means algorithms are used to obtain a finite mixture model that reconstructs the output variable probability distribution from data obtained with RELAP-5 simulations. Both methodologies have been applied to a separated

New approach in modeling Cr(VI) sorption onto biomass from metal binary mixtures solutions

Energy Technology Data Exchange (ETDEWEB)

Liu, Chang [College of Environmental Science and Engineering, Anhui Normal University, South Jiuhua Road, 189, 241002 Wuhu (China); Chemical Engineering Department, Escola Politècnica Superior, Universitat de Girona, Ma Aurèlia Capmany, 61, 17071 Girona (Spain); Fiol, Núria [Chemical Engineering Department, Escola Politècnica Superior, Universitat de Girona, Ma Aurèlia Capmany, 61, 17071 Girona (Spain); Villaescusa, Isabel, E-mail: Isabel.Villaescusa@udg.edu [Chemical Engineering Department, Escola Politècnica Superior, Universitat de Girona, Ma Aurèlia Capmany, 61, 17071 Girona (Spain); Poch, Jordi [Applied Mathematics Department, Escola Politècnica Superior, Universitat de Girona, Ma Aurèlia Capmany, 61, 17071 Girona (Spain)

2016-01-15

In the last decades Cr(VI) sorption equilibrium and kinetic studies have been carried out using several types of biomasses. However there are few researchers that consider all the simultaneous processes that take place during Cr(VI) sorption (i.e., sorption/reduction of Cr(VI) and simultaneous formation and binding of reduced Cr(III)) when formulating a model that describes the overall sorption process. On the other hand Cr(VI) scarcely exists alone in wastewaters, it is usually found in mixtures with divalent metals. Therefore, the simultaneous removal of Cr(VI) and divalent metals in binary mixtures and the interactive mechanism governing Cr(VI) elimination have gained more and more attention. In the present work, kinetics of Cr(VI) sorption onto exhausted coffee from Cr(VI)–Cu(II) binary mixtures has been studied in a stirred batch reactor. A model including Cr(VI) sorption and reduction, Cr(III) sorption and the effect of the presence of Cu(II) in these processes has been developed and validated. This study constitutes an important advance in modeling Cr(VI) sorption kinetics especially when chromium sorption is in part based on the sorbent capacity of reducing hexavalent chromium and a metal cation is present in the binary mixture. - Highlights: • A kinetic model including Cr(VI) reduction, Cr(VI) and Cr(III) sorption/desorption • Synergistic effect of Cu(II) on Cr(VI) elimination included in the model • Model validation by checking it against independent sets of data.

New approach in modeling Cr(VI) sorption onto biomass from metal binary mixtures solutions

International Nuclear Information System (INIS)

Liu, Chang; Fiol, Núria; Villaescusa, Isabel; Poch, Jordi

2016-01-01

In the last decades Cr(VI) sorption equilibrium and kinetic studies have been carried out using several types of biomasses. However there are few researchers that consider all the simultaneous processes that take place during Cr(VI) sorption (i.e., sorption/reduction of Cr(VI) and simultaneous formation and binding of reduced Cr(III)) when formulating a model that describes the overall sorption process. On the other hand Cr(VI) scarcely exists alone in wastewaters, it is usually found in mixtures with divalent metals. Therefore, the simultaneous removal of Cr(VI) and divalent metals in binary mixtures and the interactive mechanism governing Cr(VI) elimination have gained more and more attention. In the present work, kinetics of Cr(VI) sorption onto exhausted coffee from Cr(VI)–Cu(II) binary mixtures has been studied in a stirred batch reactor. A model including Cr(VI) sorption and reduction, Cr(III) sorption and the effect of the presence of Cu(II) in these processes has been developed and validated. This study constitutes an important advance in modeling Cr(VI) sorption kinetics especially when chromium sorption is in part based on the sorbent capacity of reducing hexavalent chromium and a metal cation is present in the binary mixture. - Highlights: • A kinetic model including Cr(VI) reduction, Cr(VI) and Cr(III) sorption/desorption • Synergistic effect of Cu(II) on Cr(VI) elimination included in the model • Model validation by checking it against independent sets of data

A BGK model for reactive mixtures of polyatomic gases with continuous internal energy

Science.gov (United States)

Bisi, M.; Monaco, R.; Soares, A. J.

2018-03-01

In this paper we derive a BGK relaxation model for a mixture of polyatomic gases with a continuous structure of internal energies. The emphasis of the paper is on the case of a quaternary mixture undergoing a reversible chemical reaction of bimolecular type. For such a mixture we prove an H -theorem and characterize the equilibrium solutions with the related mass action law of chemical kinetics. Further, a Chapman-Enskog asymptotic analysis is performed in view of computing the first-order non-equilibrium corrections to the distribution functions and investigating the transport properties of the reactive mixture. The chemical reaction rate is explicitly derived at the first order and the balance equations for the constituent number densities are derived at the Euler level.

A Bayesian approach to the analysis of quantal bioassay studies using nonparametric mixture models.

Science.gov (United States)

Fronczyk, Kassandra; Kottas, Athanasios

2014-03-01

We develop a Bayesian nonparametric mixture modeling framework for quantal bioassay settings. The approach is built upon modeling dose-dependent response distributions. We adopt a structured nonparametric prior mixture model, which induces a monotonicity restriction for the dose-response curve. Particular emphasis is placed on the key risk assessment goal of calibration for the dose level that corresponds to a specified response. The proposed methodology yields flexible inference for the dose-response relationship as well as for other inferential objectives, as illustrated with two data sets from the literature. © 2013, The International Biometric Society.

Evaluation of Distance Measures Between Gaussian Mixture Models of MFCCs

DEFF Research Database (Denmark)

Jensen, Jesper Højvang; Ellis, Dan P. W.; Christensen, Mads Græsbøll

2007-01-01

In music similarity and in the related task of genre classification, a distance measure between Gaussian mixture models is frequently needed. We present a comparison of the Kullback-Leibler distance, the earth movers distance and the normalized L2 distance for this application. Although...

Parameter Estimation and Model Selection for Mixtures of Truncated Exponentials

DEFF Research Database (Denmark)

Langseth, Helge; Nielsen, Thomas Dyhre; Rumí, Rafael

2010-01-01

Bayesian networks with mixtures of truncated exponentials (MTEs) support efficient inference algorithms and provide a flexible way of modeling hybrid domains (domains containing both discrete and continuous variables). On the other hand, estimating an MTE from data has turned out to be a difficul...

Fitting N-mixture models to count data with unmodeled heterogeneity: Bias, diagnostics, and alternative approaches

Science.gov (United States)

Duarte, Adam; Adams, Michael J.; Peterson, James T.

2018-01-01

Monitoring animal populations is central to wildlife and fisheries management, and the use of N-mixture models toward these efforts has markedly increased in recent years. Nevertheless, relatively little work has evaluated estimator performance when basic assumptions are violated. Moreover, diagnostics to identify when bias in parameter estimates from N-mixture models is likely is largely unexplored. We simulated count data sets using 837 combinations of detection probability, number of sample units, number of survey occasions, and type and extent of heterogeneity in abundance or detectability. We fit Poisson N-mixture models to these data, quantified the bias associated with each combination, and evaluated if the parametric bootstrap goodness-of-fit (GOF) test can be used to indicate bias in parameter estimates. We also explored if assumption violations can be diagnosed prior to fitting N-mixture models. In doing so, we propose a new model diagnostic, which we term the quasi-coefficient of variation (QCV). N-mixture models performed well when assumptions were met and detection probabilities were moderate (i.e., ≥0.3), and the performance of the estimator improved with increasing survey occasions and sample units. However, the magnitude of bias in estimated mean abundance with even slight amounts of unmodeled heterogeneity was substantial. The parametric bootstrap GOF test did not perform well as a diagnostic for bias in parameter estimates when detectability and sample sizes were low. The results indicate the QCV is useful to diagnose potential bias and that potential bias associated with unidirectional trends in abundance or detectability can be diagnosed using Poisson regression. This study represents the most thorough assessment to date of assumption violations and diagnostics when fitting N-mixture models using the most commonly implemented error distribution. Unbiased estimates of population state variables are needed to properly inform management decision

Using Bayesian statistics for modeling PTSD through Latent Growth Mixture Modeling : implementation and discussion

NARCIS (Netherlands)

Depaoli, Sarah; van de Schoot, Rens; van Loey, Nancy; Sijbrandij, Marit

2015-01-01

BACKGROUND: After traumatic events, such as disaster, war trauma, and injuries including burns (which is the focus here), the risk to develop posttraumatic stress disorder (PTSD) is approximately 10% (Breslau & Davis, 1992). Latent Growth Mixture Modeling can be used to classify individuals into

Development of reversible jump Markov Chain Monte Carlo algorithm in the Bayesian mixture modeling for microarray data in Indonesia

Science.gov (United States)

Astuti, Ani Budi; Iriawan, Nur; Irhamah, Kuswanto, Heri

2017-12-01

In the Bayesian mixture modeling requires stages the identification number of the most appropriate mixture components thus obtained mixture models fit the data through data driven concept. Reversible Jump Markov Chain Monte Carlo (RJMCMC) is a combination of the reversible jump (RJ) concept and the Markov Chain Monte Carlo (MCMC) concept used by some researchers to solve the problem of identifying the number of mixture components which are not known with certainty number. In its application, RJMCMC using the concept of the birth/death and the split-merge with six types of movement, that are w updating, θ updating, z updating, hyperparameter β updating, split-merge for components and birth/death from blank components. The development of the RJMCMC algorithm needs to be done according to the observed case. The purpose of this study is to know the performance of RJMCMC algorithm development in identifying the number of mixture components which are not known with certainty number in the Bayesian mixture modeling for microarray data in Indonesia. The results of this study represent that the concept RJMCMC algorithm development able to properly identify the number of mixture components in the Bayesian normal mixture model wherein the component mixture in the case of microarray data in Indonesia is not known for certain number.

Characterization of Mixtures. Part 2: QSPR Models for Prediction of Excess Molar Volume and Liquid Density Using Neural Networks.

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Ajmani, Subhash; Rogers, Stephen C; Barley, Mark H; Burgess, Andrew N; Livingstone, David J

2010-09-17

In our earlier work, we have demonstrated that it is possible to characterize binary mixtures using single component descriptors by applying various mixing rules. We also showed that these methods were successful in building predictive QSPR models to study various mixture properties of interest. Here in, we developed a QSPR model of an excess thermodynamic property of binary mixtures i.e. excess molar volume (V(E) ). In the present study, we use a set of mixture descriptors which we earlier designed to specifically account for intermolecular interactions between the components of a mixture and applied successfully to the prediction of infinite-dilution activity coefficients using neural networks (part 1 of this series). We obtain a significant QSPR model for the prediction of excess molar volume (V(E) ) using consensus neural networks and five mixture descriptors. We find that hydrogen bond and thermodynamic descriptors are the most important in determining excess molar volume (V(E) ), which is in line with the theory of intermolecular forces governing excess mixture properties. The results also suggest that the mixture descriptors utilized herein may be sufficient to model a wide variety of properties of binary and possibly even more complex mixtures. Copyright © 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Theory of synergistic effects: Hill-type response surfaces as 'null-interaction' models for mixtures.

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Schindler, Michael

2017-08-02

The classification of effects caused by mixtures of agents as synergistic, antagonistic or additive depends critically on the reference model of 'null interaction'. Two main approaches are currently in use, the Additive Dose (ADM) or concentration addition (CA) and the Multiplicative Survival (MSM) or independent action (IA) models. We compare several response surface models to a newly developed Hill response surface, obtained by solving a logistic partial differential equation (PDE). Assuming that a mixture of chemicals with individual Hill-type dose-response curves can be described by an n-dimensional logistic function, Hill's differential equation for pure agents is replaced by a PDE for mixtures whose solution provides Hill surfaces as 'null-interaction' models and relies neither on Bliss independence or Loewe additivity nor uses Chou's unified general theory. An n-dimensional logistic PDE decribing the Hill-type response of n-component mixtures is solved. Appropriate boundary conditions ensure the correct asymptotic behaviour. Mathematica 11 (Wolfram, Mathematica Version 11.0, 2016) is used for the mathematics and graphics presented in this article. The Hill response surface ansatz can be applied to mixtures of compounds with arbitrary Hill parameters. Restrictions which are required when deriving analytical expressions for response surfaces from other principles, are unnecessary. Many approaches based on Loewe additivity turn out be special cases of the Hill approach whose increased flexibility permits a better description of 'null-effect' responses. Missing sham-compliance of Bliss IA, known as Colby's model in agrochemistry, leads to incompatibility with the Hill surface ansatz. Examples of binary and ternary mixtures illustrate the differences between the approaches. For Hill-slopes close to one and doses below the half-maximum effect doses MSM (Colby, Bliss, Finney, Abbott) predicts synergistic effects where the Hill model indicates 'null

Multi-Step Time Series Forecasting with an Ensemble of Varied Length Mixture Models.

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Ouyang, Yicun; Yin, Hujun

2018-05-01

Many real-world problems require modeling and forecasting of time series, such as weather temperature, electricity demand, stock prices and foreign exchange (FX) rates. Often, the tasks involve predicting over a long-term period, e.g. several weeks or months. Most existing time series models are inheritably for one-step prediction, that is, predicting one time point ahead. Multi-step or long-term prediction is difficult and challenging due to the lack of information and uncertainty or error accumulation. The main existing approaches, iterative and independent, either use one-step model recursively or treat the multi-step task as an independent model. They generally perform poorly in practical applications. In this paper, as an extension of the self-organizing mixture autoregressive (AR) model, the varied length mixture (VLM) models are proposed to model and forecast time series over multi-steps. The key idea is to preserve the dependencies between the time points within the prediction horizon. Training data are segmented to various lengths corresponding to various forecasting horizons, and the VLM models are trained in a self-organizing fashion on these segments to capture these dependencies in its component AR models of various predicting horizons. The VLM models form a probabilistic mixture of these varied length models. A combination of short and long VLM models and an ensemble of them are proposed to further enhance the prediction performance. The effectiveness of the proposed methods and their marked improvements over the existing methods are demonstrated through a number of experiments on synthetic data, real-world FX rates and weather temperatures.

Nonparametric e-Mixture Estimation.

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Takano, Ken; Hino, Hideitsu; Akaho, Shotaro; Murata, Noboru

2016-12-01

This study considers the common situation in data analysis when there are few observations of the distribution of interest or the target distribution, while abundant observations are available from auxiliary distributions. In this situation, it is natural to compensate for the lack of data from the target distribution by using data sets from these auxiliary distributions-in other words, approximating the target distribution in a subspace spanned by a set of auxiliary distributions. Mixture modeling is one of the simplest ways to integrate information from the target and auxiliary distributions in order to express the target distribution as accurately as possible. There are two typical mixtures in the context of information geometry: the [Formula: see text]- and [Formula: see text]-mixtures. The [Formula: see text]-mixture is applied in a variety of research fields because of the presence of the well-known expectation-maximazation algorithm for parameter estimation, whereas the [Formula: see text]-mixture is rarely used because of its difficulty of estimation, particularly for nonparametric models. The [Formula: see text]-mixture, however, is a well-tempered distribution that satisfies the principle of maximum entropy. To model a target distribution with scarce observations accurately, this letter proposes a novel framework for a nonparametric modeling of the [Formula: see text]-mixture and a geometrically inspired estimation algorithm. As numerical examples of the proposed framework, a transfer learning setup is considered. The experimental results show that this framework works well for three types of synthetic data sets, as well as an EEG real-world data set.

Quality of life of deaf and hard of hearing students in Ibadan metropolis, Nigeria.

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Mofadeke T Jaiyeola

Full Text Available Quality of Life encompasses an individual's well-being and health, social participation and satisfaction with functional daily living. Disabilities such as deafness can impact on the quality of life with spatial variance to the environment. Deafness causes communicative problems with significant consequences in cognitive, social, and emotional well-being of affected individuals. However, information relating to the quality of life of deaf and hard of hearing individuals, especially students in developing countries like Nigeria, which could be used to design special health-related interventions is sparse. This study examined the quality of life of deaf and hard of hearing students in Ibadan metropolis, Nigeria. One hundred and ten deaf and hard of hearing students participated in this cross-sectional study. Participants were drawn from all four secondary schools for the Deaf in Ibadan metropolis. The 26 item Brief version of the WHO Quality of Life questionnaire was used for data collection. The data was analyzed using descriptive and inferential statistics at statistical significance of p<0.05. Majority (57.8% of the deaf and hard of hearing students had poor quality of life. Attending the special school for the Deaf, upper socio-economic status and age (≥17years are significantly associated with better quality of life. However, gender and age at onset of hearing loss had no significant influence on the quality of life. The Deaf community available in the special school appeared to protect against stigma and discrimination, while also promoting social interactions between deaf and hard of hearing individuals.

An odor interaction model of binary odorant mixtures by a partial differential equation method.

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Yan, Luchun; Liu, Jiemin; Wang, Guihua; Wu, Chuandong

2014-07-09

A novel odor interaction model was proposed for binary mixtures of benzene and substituted benzenes by a partial differential equation (PDE) method. Based on the measurement method (tangent-intercept method) of partial molar volume, original parameters of corresponding formulas were reasonably displaced by perceptual measures. By these substitutions, it was possible to relate a mixture's odor intensity to the individual odorant's relative odor activity value (OAV). Several binary mixtures of benzene and substituted benzenes were respectively tested to establish the PDE models. The obtained results showed that the PDE model provided an easily interpretable method relating individual components to their joint odor intensity. Besides, both predictive performance and feasibility of the PDE model were proved well through a series of odor intensity matching tests. If combining the PDE model with portable gas detectors or on-line monitoring systems, olfactory evaluation of odor intensity will be achieved by instruments instead of odor assessors. Many disadvantages (e.g., expense on a fixed number of odor assessors) also will be successfully avoided. Thus, the PDE model is predicted to be helpful to the monitoring and management of odor pollutions.

Modeling Math Growth Trajectory--An Application of Conventional Growth Curve Model and Growth Mixture Model to ECLS K-5 Data

Science.gov (United States)

Lu, Yi

2016-01-01

To model students' math growth trajectory, three conventional growth curve models and three growth mixture models are applied to the Early Childhood Longitudinal Study Kindergarten-Fifth grade (ECLS K-5) dataset in this study. The results of conventional growth curve model show gender differences on math IRT scores. When holding socio-economic…

Sustainable go-green logistics solutions for Istanbul metropolis

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Andrei ANGHELUTA

2011-01-01

Full Text Available Nowadays CO2 emissions have exponentially increased over the last decade due to cities development and population growth. Logistics has a major impact, mainly negative, on the environment degradation. In this paper we focus on innovative “green” logistics solutions, which can be applied at the big city level, in economic and population expansion (emerging metropolis. That scope is to reduce simultaneously pollution and traffic congestion in agglomerated area. As an example we use a DHL Business Plan for Istanbul, aiming to implement a non- or little-polluting transport mode (by land and by sea and estimative cost calculation that will be incurred by this challenging task. The final result of the research reveals that, although we expect to have higher cost for such a non polluting challenge, on the long run, the benefits of a durable go-green policy has higher impact in terms of money savings, environment protection and next generation life standards. As the output is positive, these results can be successfully applied to other cities or large very populated area, but analysis is needed to figure out which combination of schemes fitted for a particular location.

Pathologic analysis of control plans for air pollution management in tehran metropolis: a qualitative study.

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Shahrabi, Narges Salehi; Pourezzat, Aliasghar; Ahmad, Fayaz-Bakhsh; Mafimoradi, Shiva; Poursafa, Parinaz

2013-09-01

Regarding the importance of air pollution issue for large cities, as Tehran metropolis, many plans, programs, projects and regulations have been developed to manage urban air pollution. However, most of them failed to decline the pollution. The purpose of this study is to pathologically analyze air-pollution control plans in order to offer effective solutions for Tehran metropolis. A qualitative content analysis and a semi-structured interview with 14 practicing professionals were used to identify key causes and sources of Tehran's air pollution, to recognize challenges and obstacles towards effective performance of air-pollution control plans in this metropolitan area, and to suggest the most effective controlling solutions. Challenges related to air-pollution control plans can be divided into two major categories: Firstly lack of integrated and organized stewardship and secondly those related to political, economical, social and technical environmental abbreviated as PEST, challenges. For effective control of the Tehran air pollution, the following eight controlling alternatives were identified: Systematization of plan preparation process, organizing the stewardship, standardization and utilization of new technologies and professional experts, cultural and infrastructural development, realization of social justice, developing coordination and controlling mechanisms, improving citizen's participatory capacity, and focusing on effective management of fuel and energy. Controlling air pollution in Tehran should be considered as a priority for policymakers to make enforcements through applying a systemic cycle of preparation effective and comprehensive plans. Further, implement the enforcements and evaluate the environmental impact of the plans through involving all stakeholders.

Assessment of the use and misuse of Cannabis sativa amongst some residents of Jos metropolis, Nigeria

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N S Jimam

2015-01-01

Full Text Available Background: Cannabis can be used for its medicinal properties when used appropriately. However, the misuse of the product can cause some unwanted effects such as psychological dependence, and therefore addiction. Objective: The objective of the study was to determine the extent of misuse of Cannabis sativa in Jos and environs. Materials and Methods: The use and misuse of C. sativa in Jos metropolis was studied using a structured self-administered questionnaire which was administered to 400 respondents in the metropolis. Result: The result showed that 59.9% of the participants were male while 40.1% were female with 88.2% of the population being youth between the ages of 20-35 years. The result also shows that at least 31.3% of the studied population had used C. sativa, for different reasons including among others: to boost confidence (11.4%, 5.1% take it to increase alertness, 5.1% take it to decrease fatigue, 0.3% take it to decrease stress, 5.4% take it to get high while 4% take it for other reasons. Conclusion: The result of the study showed an observed high incidence of C. sativa intake among the study population who were mostly youths for different purposes, including to: Boost confidence, feel high, increase alertness, and decrease fatigue. Similarly, a high percentage of the respondents said the drug is used for hair treatment.

Pathologic Analysis of Control Plans for Air Pollution Management in Tehran Metropolis: A Cross-Sectional Study.

Science.gov (United States)

Salehi Shahrabi, Narges; Pourezzat, Aliasghar; Mobaraki, Hossein; Mafimoradi, Shiva

2013-11-01

The centralization of human activities is associated with different pollutants which enter into environment easily and cause the urban environment more vulnerable. Regarding the importance of air pollution issue for Tehran metropolis, many plans and regulations have been developed. However, most of them failed to decline the pollution. The purpose of this study was to pathologically analyze air-pollution control plans to offer effective solutions for Tehran metropolis. A Qualitative content analysis in addition to a semi-structured interview with 14 practicing professional were used to identify 1) key sources of Tehran's air pollution, 2) recognize challenges towards effective performance of pertinent plans and 3), offer effective solutions. Related challenges to air-pollution control plans can be divided into two major categories including lack of integrated and organized stewardship and PEST challenges. For controlling the air pollution of Tehran effectively, various controlling alternatives were identified as systematization of plan preparation process, standardization and utilization of new technologies & experts, infrastructural development, realization of social justice, developing coordination mechanisms, improving citizens' participatory capacity and focusing on effective management of fuel and energy. Controlling air pollution in Tehran needs a serious attention of policymakers to make enforcements through applying a systemic cycle of preparation comprehensive plans. Further, implement the enforcements and evaluate the environmental impact of the plans through involving all stakeholders.

Distinguishing Continuous and Discrete Approaches to Multilevel Mixture IRT Models: A Model Comparison Perspective

Science.gov (United States)

Zhu, Xiaoshu

2013-01-01

The current study introduced a general modeling framework, multilevel mixture IRT (MMIRT) which detects and describes characteristics of population heterogeneity, while accommodating the hierarchical data structure. In addition to introducing both continuous and discrete approaches to MMIRT, the main focus of the current study was to distinguish…

Spatially adaptive mixture modeling for analysis of FMRI time series.

Science.gov (United States)

Vincent, Thomas; Risser, Laurent; Ciuciu, Philippe

2010-04-01

Within-subject analysis in fMRI essentially addresses two problems, the detection of brain regions eliciting evoked activity and the estimation of the underlying dynamics. In Makni et aL, 2005 and Makni et aL, 2008, a detection-estimation framework has been proposed to tackle these problems jointly, since they are connected to one another. In the Bayesian formalism, detection is achieved by modeling activating and nonactivating voxels through independent mixture models (IMM) within each region while hemodynamic response estimation is performed at a regional scale in a nonparametric way. Instead of IMMs, in this paper we take advantage of spatial mixture models (SMM) for their nonlinear spatial regularizing properties. The proposed method is unsupervised and spatially adaptive in the sense that the amount of spatial correlation is automatically tuned from the data and this setting automatically varies across brain regions. In addition, the level of regularization is specific to each experimental condition since both the signal-to-noise ratio and the activation pattern may vary across stimulus types in a given brain region. These aspects require the precise estimation of multiple partition functions of underlying Ising fields. This is addressed efficiently using first path sampling for a small subset of fields and then using a recently developed fast extrapolation technique for the large remaining set. Simulation results emphasize that detection relying on supervised SMM outperforms its IMM counterpart and that unsupervised spatial mixture models achieve similar results without any hand-tuning of the correlation parameter. On real datasets, the gain is illustrated in a localizer fMRI experiment: brain activations appear more spatially resolved using SMM in comparison with classical general linear model (GLM)-based approaches, while estimating a specific parcel-based HRF shape. Our approach therefore validates the treatment of unsmoothed fMRI data without fixed GLM

Modeling diffusion coefficients in binary mixtures of polar and non-polar compounds

DEFF Research Database (Denmark)

Medvedev, Oleg; Shapiro, Alexander

2005-01-01

The theory of transport coefficients in liquids, developed previously, is tested on a description of the diffusion coefficients in binary polar/non-polar mixtures, by applying advanced thermodynamic models. Comparison to a large set of experimental data shows good performance of the model. Only f...

Statistical imitation system using relational interest points and Gaussian mixture models

CSIR Research Space (South Africa)

Claassens, J

2009-11-01

Full Text Available The author proposes an imitation system that uses relational interest points (RIPs) and Gaussian mixture models (GMMs) to characterize a behaviour. The system's structure is inspired by the Robot Programming by Demonstration (RDP) paradigm...

IDENTIFYING ANTHROPOGENIC METALLIC POLLUTANTS USING FREQUENCY DEPENDENT MAGNETIC SUSCEPTIBILITY MEASUREMENTS IN ABUJA METROPOLIS

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Jatto S. Solomon

2017-07-01

Full Text Available Soil formed from lithological and weathering processes of parent rocks generally exhibit paramagnetic properties due to some minerals contained in the rocks and thus have significant value of magnetic susceptibility. This susceptibility arising from the influence of the parent rocks tend to mask anthropogenic grains pollutants released into the environment by human activities. Hence, it becomes difficult to identify the effect of the lithological and anthropogenic magnetic susceptibility in complex soil found in urban areas. The superparamagnetic effect of lithological soil, a single state domain and multi-domain state of anthropogenic grains can easily be investigated by frequency dependent measurements where readings between 0-2.0% indicates the absence of lithological influence, 2.0-8.0% indicates multi-domain grains or mixture of both single stage and multi-domian grains and 8.0-12% indicates the superparamagntic (SP grain from lithological origin. In this work frequency dependent measurements were carried out along 5 selected road networks within the 5 districts of Abuja phase 1. Measurements were also carried out in 379 random points at the surface and depth of 40.0cm to investigate the distribution of anthropogenic grains in Abuja metropolis using the Bartington susceptibility meter. Frequency dependent measurements along the selected road networks indicate0-3.0% immediately after the roads pavement to a distance of about 3.0m from the road, indicating that the magnetic susceptibility arise mostly form anthropogenic influence rather than lithological processes. At the distance of 3.0-8.0m, frequency dependent values of about 3.0-8.0% were recorded, indicating mixture of both superparamagnetic and multi-domain grains. Beyond the distance of 8.0m, the frequency dependent values are mostly above 8.0.0%, indicating virtually all SP grains. The spatial distribution frequency dependent surface map shows the presence of anthropogenic grains in

Validation of a mixture-averaged thermal diffusion model for premixed lean hydrogen flames

Science.gov (United States)

Schlup, Jason; Blanquart, Guillaume

2018-03-01

The mixture-averaged thermal diffusion model originally proposed by Chapman and Cowling is validated using multiple flame configurations. Simulations using detailed hydrogen chemistry are done on one-, two-, and three-dimensional flames. The analysis spans flat and stretched, steady and unsteady, and laminar and turbulent flames. Quantitative and qualitative results using the thermal diffusion model compare very well with the more complex multicomponent diffusion model. Comparisons are made using flame speeds, surface areas, species profiles, and chemical source terms. Once validated, this model is applied to three-dimensional laminar and turbulent flames. For these cases, thermal diffusion causes an increase in the propagation speed of the flames as well as increased product chemical source terms in regions of high positive curvature. The results illustrate the necessity for including thermal diffusion, and the accuracy and computational efficiency of the mixture-averaged thermal diffusion model.

An Empirical Bayes Mixture Model for Effect Size Distributions in Genome-Wide Association Studies.

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Wesley K Thompson

2015-12-01

Full Text Available Characterizing the distribution of effects from genome-wide genotyping data is crucial for understanding important aspects of the genetic architecture of complex traits, such as number or proportion of non-null loci, average proportion of phenotypic variance explained per non-null effect, power for discovery, and polygenic risk prediction. To this end, previous work has used effect-size models based on various distributions, including the normal and normal mixture distributions, among others. In this paper we propose a scale mixture of two normals model for effect size distributions of genome-wide association study (GWAS test statistics. Test statistics corresponding to null associations are modeled as random draws from a normal distribution with zero mean; test statistics corresponding to non-null associations are also modeled as normal with zero mean, but with larger variance. The model is fit via minimizing discrepancies between the parametric mixture model and resampling-based nonparametric estimates of replication effect sizes and variances. We describe in detail the implications of this model for estimation of the non-null proportion, the probability of replication in de novo samples, the local false discovery rate, and power for discovery of a specified proportion of phenotypic variance explained from additive effects of loci surpassing a given significance threshold. We also examine the crucial issue of the impact of linkage disequilibrium (LD on effect sizes and parameter estimates, both analytically and in simulations. We apply this approach to meta-analysis test statistics from two large GWAS, one for Crohn's disease (CD and the other for schizophrenia (SZ. A scale mixture of two normals distribution provides an excellent fit to the SZ nonparametric replication effect size estimates. While capturing the general behavior of the data, this mixture model underestimates the tails of the CD effect size distribution. We discuss the

An Empirical Bayes Mixture Model for Effect Size Distributions in Genome-Wide Association Studies.

Science.gov (United States)

Thompson, Wesley K; Wang, Yunpeng; Schork, Andrew J; Witoelar, Aree; Zuber, Verena; Xu, Shujing; Werge, Thomas; Holland, Dominic; Andreassen, Ole A; Dale, Anders M

2015-12-01

Characterizing the distribution of effects from genome-wide genotyping data is crucial for understanding important aspects of the genetic architecture of complex traits, such as number or proportion of non-null loci, average proportion of phenotypic variance explained per non-null effect, power for discovery, and polygenic risk prediction. To this end, previous work has used effect-size models based on various distributions, including the normal and normal mixture distributions, among others. In this paper we propose a scale mixture of two normals model for effect size distributions of genome-wide association study (GWAS) test statistics. Test statistics corresponding to null associations are modeled as random draws from a normal distribution with zero mean; test statistics corresponding to non-null associations are also modeled as normal with zero mean, but with larger variance. The model is fit via minimizing discrepancies between the parametric mixture model and resampling-based nonparametric estimates of replication effect sizes and variances. We describe in detail the implications of this model for estimation of the non-null proportion, the probability of replication in de novo samples, the local false discovery rate, and power for discovery of a specified proportion of phenotypic variance explained from additive effects of loci surpassing a given significance threshold. We also examine the crucial issue of the impact of linkage disequilibrium (LD) on effect sizes and parameter estimates, both analytically and in simulations. We apply this approach to meta-analysis test statistics from two large GWAS, one for Crohn's disease (CD) and the other for schizophrenia (SZ). A scale mixture of two normals distribution provides an excellent fit to the SZ nonparametric replication effect size estimates. While capturing the general behavior of the data, this mixture model underestimates the tails of the CD effect size distribution. We discuss the implications of

Assessing variation in life-history tactics within a population using mixture regression models: a practical guide for evolutionary ecologists.

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Hamel, Sandra; Yoccoz, Nigel G; Gaillard, Jean-Michel

2017-05-01

Mixed models are now well-established methods in ecology and evolution because they allow accounting for and quantifying within- and between-individual variation. However, the required normal distribution of the random effects can often be violated by the presence of clusters among subjects, which leads to multi-modal distributions. In such cases, using what is known as mixture regression models might offer a more appropriate approach. These models are widely used in psychology, sociology, and medicine to describe the diversity of trajectories occurring within a population over time (e.g. psychological development, growth). In ecology and evolution, however, these models are seldom used even though understanding changes in individual trajectories is an active area of research in life-history studies. Our aim is to demonstrate the value of using mixture models to describe variation in individual life-history tactics within a population, and hence to promote the use of these models by ecologists and evolutionary ecologists. We first ran a set of simulations to determine whether and when a mixture model allows teasing apart latent clustering, and to contrast the precision and accuracy of estimates obtained from mixture models versus mixed models under a wide range of ecological contexts. We then used empirical data from long-term studies of large mammals to illustrate the potential of using mixture models for assessing within-population variation in life-history tactics. Mixture models performed well in most cases, except for variables following a Bernoulli distribution and when sample size was small. The four selection criteria we evaluated [Akaike information criterion (AIC), Bayesian information criterion (BIC), and two bootstrap methods] performed similarly well, selecting the right number of clusters in most ecological situations. We then showed that the normality of random effects implicitly assumed by evolutionary ecologists when using mixed models was often

Beyond GLMs: a generative mixture modeling approach to neural system identification.

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Lucas Theis

Full Text Available Generalized linear models (GLMs represent a popular choice for the probabilistic characterization of neural spike responses. While GLMs are attractive for their computational tractability, they also impose strong assumptions and thus only allow for a limited range of stimulus-response relationships to be discovered. Alternative approaches exist that make only very weak assumptions but scale poorly to high-dimensional stimulus spaces. Here we seek an approach which can gracefully interpolate between the two extremes. We extend two frequently used special cases of the GLM-a linear and a quadratic model-by assuming that the spike-triggered and non-spike-triggered distributions can be adequately represented using Gaussian mixtures. Because we derive the model from a generative perspective, its components are easy to interpret as they correspond to, for example, the spike-triggered distribution and the interspike interval distribution. The model is able to capture complex dependencies on high-dimensional stimuli with far fewer parameters than other approaches such as histogram-based methods. The added flexibility comes at the cost of a non-concave log-likelihood. We show that in practice this does not have to be an issue and the mixture-based model is able to outperform generalized linear and quadratic models.

Smoothed particle hydrodynamics model for phase separating fluid mixtures. I. General equations

NARCIS (Netherlands)

Thieulot, C; Janssen, LPBM; Espanol, P

We present a thermodynamically consistent discrete fluid particle model for the simulation of a recently proposed set of hydrodynamic equations for a phase separating van der Waals fluid mixture [P. Espanol and C.A.P. Thieulot, J. Chem. Phys. 118, 9109 (2003)]. The discrete model is formulated by

LUR models for particulate matters in the Taipei metropolis with high densities of roads and strong activities of industry, commerce and construction.

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Lee, Jui-Huna; Wu, Chang-Fu; Hoek, Gerard; de Hoogh, Kees; Beelen, Rob; Brunekreef, Bert; Chan, Chang-Chuan

2015-05-01

Traffic intensity, length of road, and proximity to roads are the most common traffic indicators in the land use regression (LUR) models for particulate matter in ESCAPE study areas in Europe. This study explored what local variables can improve the performance of LUR models in an Asian metropolis with high densities of roads and strong activities of industry, commerce and construction. By following the ESCAPE procedure, we derived LUR models of PM₂.₅, PM₂.₅ absorbance, PM₁₀, and PMcoarse (PM₂.₅-₁₀) in Taipei. The overall annual average concentrations of PM₂.₅, PM₁₀, and PMcoarse were 26.0 ± 5.6, 48.6 ± 5.9, and 23.3 ± 3.1 μg/m(3), respectively, and the absorption coefficient of PM₂.₅ was 2.0 ± 0.4 × 10(-5)m(-1). Our LUR models yielded R(2) values of 95%, 96%, 87%, and 65% for PM₂.₅, PM₂.₅ absorbance, PM₁₀, and PMcoarse, respectively. PM₂.₅ levels were increased by local traffic variables, industrial, construction, and residential land-use variables and decreased by rivers; while PM₂.₅ absorbance levels were increased by local traffic variables, industrial, and commercial land-use variables in the models. PMcoarse levels were increased by elevated highways. Road area explained more variance than road length by increasing the incremental value of 27% and 6% adjusted R(2) for PM₂.₅ and PM₁₀ models, respectively. In the PM₂.₅ absorbance model, road area and transportation facility explain 29% more variance than road length. In the PMcoarse model, industrial and new local variables instead of road length improved the incremental value of adjusted R(2) from 39% to 60%. We concluded that road area can better explain the spatial distribution of PM₂.₅ and PM₂.₅ absorbance concentrations than road length. By incorporating road area and other new local variables, the performance of each PM LUR model was improved. The results suggest that road area is a better indicator of traffic intensity rather

Study of the Internal Mechanical response of an asphalt mixture by 3-D Discrete Element Modeling

DEFF Research Database (Denmark)

Feng, Huan; Pettinari, Matteo; Hofko, Bernhard

2015-01-01

and the reliability of which have been validated. The dynamic modulus of asphalt mixtures were predicted by conducting Discrete Element simulation under dynamic strain control loading. In order to reduce the calculation time, a method based on frequency–temperature superposition principle has been implemented......In this paper the viscoelastic behavior of asphalt mixture was investigated by employing a three-dimensional Discrete Element Method (DEM). The cylinder model was filled with cubic array of spheres with a specified radius, and was considered as a whole mixture with uniform contact properties....... The ball density effect on the internal stress distribution of the asphalt mixture model has been studied when using this method. Furthermore, the internal stresses under dynamic loading have been studied. The agreement between the predicted and the laboratory test results of the complex modulus shows...

Finite mixture model: A maximum likelihood estimation approach on time series data

Science.gov (United States)

Yen, Phoong Seuk; Ismail, Mohd Tahir; Hamzah, Firdaus Mohamad

2014-09-01

Recently, statistician emphasized on the fitting of finite mixture model by using maximum likelihood estimation as it provides asymptotic properties. In addition, it shows consistency properties as the sample sizes increases to infinity. This illustrated that maximum likelihood estimation is an unbiased estimator. Moreover, the estimate parameters obtained from the application of maximum likelihood estimation have smallest variance as compared to others statistical method as the sample sizes increases. Thus, maximum likelihood estimation is adopted in this paper to fit the two-component mixture model in order to explore the relationship between rubber price and exchange rate for Malaysia, Thailand, Philippines and Indonesia. Results described that there is a negative effect among rubber price and exchange rate for all selected countries.

Deposition behaviour of model biofuel ash in mixtures with quartz sand. Part 1: Experimental data

Energy Technology Data Exchange (ETDEWEB)

Mischa Theis; Christian Mueller; Bengt-Johan Skrifvars; Mikko Hupa; Honghi Tran [Aabo Akademi Process Chemistry Centre, Aabo (Finland). Combustion and Materials Chemistry

2006-10-15

Model biofuel ash of well-defined size and melting properties was fed into an entrained flow reactor (EFR) to simulate the deposition behaviour of commercially applied biofuel mixtures in large-scale boilers. The aim was to obtain consistent experimental data that can be used for validation of computational fluid dynamics (CFD)-based deposition models. The results showed that while up to 80 wt% of the feed was lost to the EFR wall, the composition of the model ash particles collected at the reactor exit did not change. When model ashes were fed into the reactor individually, the ash particles were found to be sticky when they contained more than 15 wt% molten phase. When model ashes were fed in mixtures with silica sand, it was found that only a small amount of sand particles was captured in the deposits; the majority rebounded upon impact. The presence of sand in the feed mixture reduced the deposit buildup by more than could be expected from linear interpolation between the model ash and the sand. The results suggested that sand addition to model ash may prevent deposit buildup through erosion. 22 refs., 6 figs., 3 tabs.

Ion swarm data for electrical discharge modeling in air and flue gas mixtures

International Nuclear Information System (INIS)

Nelson, D.; Benhenni, M.; Eichwald, O.; Yousfi, M.

2003-01-01

The first step of this work is the determination of the elastic and inelastic ion-molecule collision cross sections for the main ions (N 2 + , O 2 + , CO 2 + , H 2 O + and O - ) usually present either in the air or flue gas discharges. The obtained cross section sets, given for ion kinetic energies not exceeding 100 eV, correspond to the interactions of each ion with its parent molecule (symmetric case) or nonparent molecule (asymmetric case). Then by using these different cross section sets, it is possible to obtain the ion swarm data for the different gas mixtures involving N 2 , CO 2 , H 2 O and O 2 molecules whatever their relative proportions. These ion swarm data are obtained from an optimized Monte Carlo method well adapted for the ion transport in gas mixtures. This also allows us to clearly show that the classical linear approximations usually applied for the ion swarm data in mixtures such as Blanc's law are far to be valid. Then, the ion swarm data are given in three cases of gas mixtures: a dry air (80% N 2 , 20% O 2 ), a ternary gas mixture (82% N 2 , 12% CO 2 , 6% O 2 ) and a typical flue gas (76% N 2 , 12% CO 2 , 6% O 2 , 6% H 2 O). From these reliable ion swarm data, electrical discharge modeling for a wire to plane electrode configuration has been carried out in these three mixtures at the atmospheric pressure for different applied voltages. Under the same discharge conditions, large discrepancies in the streamer formation and propagation have been observed in these three mixture cases. They are due to the deviations existing not only between the different effective electron-molecule ionization rates but also between the ion transport properties mainly because of the presence of a highly polar molecule such as H 2 O. This emphasizes the necessity to properly consider the ion transport in the discharge modeling

A Bayesian Approach to Model Selection in Hierarchical Mixtures-of-Experts Architectures.

Science.gov (United States)

Tanner, Martin A.; Peng, Fengchun; Jacobs, Robert A.

1997-03-01

There does not exist a statistical model that shows good performance on all tasks. Consequently, the model selection problem is unavoidable; investigators must decide which model is best at summarizing the data for each task of interest. This article presents an approach to the model selection problem in hierarchical mixtures-of-experts architectures. These architectures combine aspects of generalized linear models with those of finite mixture models in order to perform tasks via a recursive "divide-and-conquer" strategy. Markov chain Monte Carlo methodology is used to estimate the distribution of the architectures' parameters. One part of our approach to model selection attempts to estimate the worth of each component of an architecture so that relatively unused components can be pruned from the architecture's structure. A second part of this approach uses a Bayesian hypothesis testing procedure in order to differentiate inputs that carry useful information from nuisance inputs. Simulation results suggest that the approach presented here adheres to the dictum of Occam's razor; simple architectures that are adequate for summarizing the data are favored over more complex structures. Copyright 1997 Elsevier Science Ltd. All Rights Reserved.

Risk Estimation for Lung Cancer in Libya: Analysis Based on Standardized Morbidity Ratio, Poisson-Gamma Model, BYM Model and Mixture Model

Science.gov (United States)

Alhdiri, Maryam Ahmed; Samat, Nor Azah; Mohamed, Zulkifley

2017-03-01

Cancer is the most rapidly spreading disease in the world, especially in developing countries, including Libya. Cancer represents a significant burden on patients, families, and their societies. This disease can be controlled if detected early. Therefore, disease mapping has recently become an important method in the fields of public health research and disease epidemiology. The correct choice of statistical model is a very important step to producing a good map of a disease. Libya was selected to perform this work and to examine its geographical variation in the incidence of lung cancer. The objective of this paper is to estimate the relative risk for lung cancer. Four statistical models to estimate the relative risk for lung cancer and population censuses of the study area for the time period 2006 to 2011 were used in this work. They are initially known as Standardized Morbidity Ratio, which is the most popular statistic, which used in the field of disease mapping, Poisson-gamma model, which is one of the earliest applications of Bayesian methodology, Besag, York and Mollie (BYM) model and Mixture model. As an initial step, this study begins by providing a review of all proposed models, which we then apply to lung cancer data in Libya. Maps, tables and graph, goodness-of-fit (GOF) were used to compare and present the preliminary results. This GOF is common in statistical modelling to compare fitted models. The main general results presented in this study show that the Poisson-gamma model, BYM model, and Mixture model can overcome the problem of the first model (SMR) when there is no observed lung cancer case in certain districts. Results show that the Mixture model is most robust and provides better relative risk estimates across a range of models. Creative Commons Attribution License

The Ghost-Image on Metropolitan Borders—In Terms of Phantom of the Opera and 19th-Century Metropolis Paris

Directory of Open Access Journals (Sweden)

Changnam Lee

2013-12-01

Full Text Available This paper reviews Gaston Leroux’s Phantom of the Opera in the context of the social and cultural changes of the metropolis Paris at the end of the 19th century. The Phantom of the Opera, a success in the literary world and widely proliferated in its musical and film renditions afterward, is considered and interpreted mainly in the literary and artistic tradition. In this paper, however, this work will be considered from an urban sociological perspective, especially from that of Walter Benjamin, who developed the theory of the urban culture, focusing on the dreaming collectives at the end of the 19th century. Leroux’s novel can be regarded as an exemplary social form of the collective dreams of the period expressed in arts, architectures, popular stories and films and other popular arts. Given the premise that the dream images in the novel, so-called kitsch, reflect the fears and desires of the bourgeois middle class that were pathologized in the figure of the ghost, this paper reveals the cultural, social and transnational implications of the Ghost-Image in relation to the rapidly changing borders of the 19th century metropolis.

Improved models for the prediction of activity coefficients in nearly athermal mixtures: Part I. Empirical modifications of free-volume models

DEFF Research Database (Denmark)

Kontogeorgis, Georgios M.; Coutsikos, Philipos; Tassios, Dimitrios

1994-01-01

Mixtures containing exclusively normal, branched and cyclic alkanes, as well as saturated hydrocarbon polymers (e.g. poly(ethylene) and poly(isobutylene)), are known to exhibit almost athermal behavior. Several new activity coefficient models containing both combinatorial and free-volume contribu......Mixtures containing exclusively normal, branched and cyclic alkanes, as well as saturated hydrocarbon polymers (e.g. poly(ethylene) and poly(isobutylene)), are known to exhibit almost athermal behavior. Several new activity coefficient models containing both combinatorial and free...

Market segment derivation and profiling via a finite mixture model framework

NARCIS (Netherlands)

Wedel, M; Desarbo, WS

The Marketing literature has shown how difficult it is to profile market segments derived with finite mixture models. especially using traditional descriptor variables (e.g., demographics). Such profiling is critical for the proper implementation of segmentation strategy. we propose a new finite

Mathematical Modeling of Nonstationary Separation Processes in Gas Centrifuge Cascade for Separation of Multicomponent Isotope Mixtures

Directory of Open Access Journals (Sweden)

Orlov Alexey

2016-01-01

Full Text Available This article presents results of development of the mathematical model of nonstationary separation processes occurring in gas centrifuge cascades for separation of multicomponent isotope mixtures. This model was used for the calculation parameters of gas centrifuge cascade for separation of germanium isotopes. Comparison of obtained values with results of other authors revealed that developed mathematical model is adequate to describe nonstationary separation processes in gas centrifuge cascades for separation of multicomponent isotope mixtures.

A mixture model for robust registration in Kinect sensor

Science.gov (United States)

Peng, Li; Zhou, Huabing; Zhu, Shengguo

2018-03-01

The Microsoft Kinect sensor has been widely used in many applications, but it suffers from the drawback of low registration precision between color image and depth image. In this paper, we present a robust method to improve the registration precision by a mixture model that can handle multiply images with the nonparametric model. We impose non-parametric geometrical constraints on the correspondence, as a prior distribution, in a reproducing kernel Hilbert space (RKHS).The estimation is performed by the EM algorithm which by also estimating the variance of the prior model is able to obtain good estimates. We illustrate the proposed method on the public available dataset. The experimental results show that our approach outperforms the baseline methods.

PREVALENCE OF LOW BACK PAIN AND BACK ERGONOMICS AWARENESS AMONG TEACHERS OF SELECTED SECONDARY SCHOOLS IN KANO METROPOLIS

Directory of Open Access Journals (Sweden)

Farida Garba Sumaila

2015-12-01

Full Text Available Background: Low back pain (LBP is regarded as the commonest musculoskeletal problem in the world which affects people across various strata of the society from lay men on the street to teachers as well as health care providers in health institutions. Therefore the purpose of this study is to determine the prevalence of low back pain and back education awareness among secondary school teachers in Kano Metropolis. Methodos: 200 questionnaires were distributed and only 157 were retrieved, one out of which 4 were invalid because of incomplete data so that only 153 were relevant and used for analysis giving a return rate of 76.5%. The study revealed that 96 out of 153 respondents have low back pain implying 62.7% prevalence. The level of back ergonomic awareness on the other hand was found to be moderate (43.1%. Results: Based on the outcomes of the study, it was concluded that there is a high prevalence of low back pain among secondary school teachers in Kano metropolis. However, the level of back ergonomic awareness is moderate. Conclusion: Therefore proper intervention to prevent exposure to LBP among school teachers should be enhanced and teachers should be well educated on the importance of ergonomic intervention in their working environments.

Diabetes in the Cape Coast metropolis of Ghana: an assessment of risk factors, nutritional practices and lifestyle changes.

Science.gov (United States)

Gato, Worlanyo E; Acquah, Samuel; Apenteng, Bettye A; Opoku, Samuel T; Boakye, Blessed K

2017-09-01

Despite the significant increase in the incidence of diabetes in Ghana, research in this area has been lagging. The purpose of the study was to assess the risk factors associated with diabetes in the Cape Coast metropolis of Ghana, and to describe nutritional practices and efforts toward lifestyle change. A convenient sample of 482 adults from the Cape Coast metropolis was surveyed using a self-reported questionnaire. The survey collected information on the demographic, socioeconomic characteristics, health status and routine nutritional practices of respondents. The aims of the study were addressed using multivariable regression analyses. A total of 8% of respondents reported that they had been diagnosed with diabetes. Older age and body weight were found to be independently associated with diabetes. Individuals living with diabetes were no more likely than those without diabetes to have taken active steps at reducing their weight. The percentage of self-reported diabetes in this population was consistent with what has been reported in previous studies in Ghana. The findings from this study highlight the need for more patient education on physical activity and weight management. © The Author 2017. Published by Oxford University Press on behalf of Royal Society of Tropical Medicine and Hygiene. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

A mixture model-based approach to the clustering of microarray expression data.

Science.gov (United States)

McLachlan, G J; Bean, R W; Peel, D

2002-03-01

This paper introduces the software EMMIX-GENE that has been developed for the specific purpose of a model-based approach to the clustering of microarray expression data, in particular, of tissue samples on a very large number of genes. The latter is a nonstandard problem in parametric cluster analysis because the dimension of the feature space (the number of genes) is typically much greater than the number of tissues. A feasible approach is provided by first selecting a subset of the genes relevant for the clustering of the tissue samples by fitting mixtures of t distributions to rank the genes in order of increasing size of the likelihood ratio statistic for the test of one versus two components in the mixture model. The imposition of a threshold on the likelihood ratio statistic used in conjunction with a threshold on the size of a cluster allows the selection of a relevant set of genes. However, even this reduced set of genes will usually be too large for a normal mixture model to be fitted directly to the tissues, and so the use of mixtures of factor analyzers is exploited to reduce effectively the dimension of the feature space of genes. The usefulness of the EMMIX-GENE approach for the clustering of tissue samples is demonstrated on two well-known data sets on colon and leukaemia tissues. For both data sets, relevant subsets of the genes are able to be selected that reveal interesting clusterings of the tissues that are either consistent with the external classification of the tissues or with background and biological knowledge of these sets. EMMIX-GENE is available at http://www.maths.uq.edu.au/~gjm/emmix-gene/

A modeling approach for heat conduction and radiation diffusion in plasma-photon mixture in temperature nonequilibrium

Energy Technology Data Exchange (ETDEWEB)

Chang, Chong [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2016-08-09

We present a simple approach for determining ion, electron, and radiation temperatures of heterogeneous plasma-photon mixtures, in which temperatures depend on both material type and morphology of the mixture. The solution technique is composed of solving ion, electron, and radiation energy equations for both mixed and pure phases of each material in zones containing random mixture and solving pure material energy equations in subdivided zones using interface reconstruction. Application of interface reconstruction is determined by the material configuration in the surrounding zones. In subdivided zones, subzonal inter-material energy exchanges are calculated by heat fluxes across the material interfaces. Inter-material energy exchange in zones with random mixtures is modeled using the length scale and contact surface area models. In those zones, inter-zonal heat flux in each material is determined using the volume fractions.

A modeling approach for heat conduction and radiation diffusion in plasma-photon mixture in temperature nonequilibrium

International Nuclear Information System (INIS)

Chang, Chong

2016-01-01

We present a simple approach for determining ion, electron, and radiation temperatures of heterogeneous plasma-photon mixtures, in which temperatures depend on both material type and morphology of the mixture. The solution technique is composed of solving ion, electron, and radiation energy equations for both mixed and pure phases of each material in zones containing random mixture and solving pure material energy equations in subdivided zones using interface reconstruction. Application of interface reconstruction is determined by the material configuration in the surrounding zones. In subdivided zones, subzonal inter-material energy exchanges are calculated by heat fluxes across the material interfaces. Inter-material energy exchange in zones with random mixtures is modeled using the length scale and contact surface area models. In those zones, inter-zonal heat flux in each material is determined using the volume fractions.

Pathologic analysis of control plans for air pollution management in tehran metropolis: A qualitative study

Directory of Open Access Journals (Sweden)

Narges Salehi Shahrabi

2013-01-01

Full Text Available Background: Regarding the importance of air pollution issue for large cities, as Tehran metropolis, many plans, programs, projects and regulations have been developed to manage urban air pollution. However, most of them failed to decline the pollution. The purpose of this study is to pathologically analyze air-pollution control plans in order to offer effective solutions for Tehran metropolis. Methods: A qualitative content analysis and a semi-structured interview with 14 practicing professionals were used to identify key causes and sources of Tehran′s air pollution, to recognize challenges and obstacles towards effective performance of air-pollution control plans in this metropolitan area, and to suggest the most effective controlling solutions. Results: Challenges related to air-pollution control plans can be divided into two major categories: Firstly lack of integrated and organized stewardship and secondly those related to political, economical, social and technical environmental abbreviated as PEST, challenges. For effective control of the Tehran air pollution, the following eight controlling alternatives were identified: Systematization of plan preparation process, organizing the stewardship, standardization and utilization of new technologies and professional experts, cultural and infrastructural development, realization of social justice, developing coordination and controlling mechanisms, improving citizen′s participatory capacity, and focusing on effective management of fuel and energy. Conclusions: Controlling air pollution in Tehran should be considered as a priority for policymakers to make enforcements through applying a systemic cycle of preparation effective and comprehensive plans. Further, implement the enforcements and evaluate the environmental impact of the plans through involving all stakeholders.

Interpreting the Contemporary Metropolis: Notes on the Urban Debate and on Ignasi Solà-Morales

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Gonçalo Furtado

2014-07-01

Full Text Available The theory of urbanism faces the difficult task of struggling to make acknowledgeable the complexity of the metropolitan form. In this sense, the legacy of the recently diseased history researcher and architecture theorist Ignási Sola-Morales arises as a sharp, generous and open perspective. Besides an apparent sense of enigma, his work has the genuine capacity of describing the cartography the metropolis and its form in its contemporary complexity. Being a teacher at the COAC (Cataluña’s college of architects allowed him to draw one of the most remarkable and sharp theoretical cartographies of the contemporaneous condition of the metropolitan architecture. A complex line of thought towards architecture being born from a cross from artistic and philosophical ideas, capable of causing breaches on the architectural culture.His writings correspond, in a certain way, to a selection of “categories” on which to lay the provisory interpretations of a contemporary metropolis and its form that is, in his own words, multiple, non convergent and of an instable shape arising from the crystallization of various forces. From all that, the outcome is a complex system united, as far as I’m concerned, by the permanent generosity of proposing to romantically rise above the bizarreness of a late-capitalism, post-historical world. In this paper we intend to show how the work of Ignási Sola Morales presents, in a generous, sharp and open way besides all the apparent enigma, the genuine capacity of cartographing the city and its form in all its contemporaneous complexity. 

Assessment of cancer and noncancer health risks from exposure to PAHs in street dust in the Tamale Metropolis, Ghana.

Science.gov (United States)

Obiri, Samuel; Cobbina, Samuel J; Armah, Frederick A; Luginaah, Isaac

2013-01-01

This study is part of a broader initiative to characterize, quantify and assess the human health risk associated with exposure to polycyclic aromatic hydrocarbons (PAHs) in street dust along the Trans-ECOWAS highway in West Africa. In the first part, PAHs were characterized and quantified in low- and high-traffic zones. In this study, cancer and noncancer human health risks from exposure to (PAHs) in street dust in the Tamale metropolis, Ghana were assessed in accordance with the USEPA risk assessment guidelines. The results of the study as obtained from inhalation of benzo [a] anthracene (BaA), benzo [a] pyrene (BaP), benzo [k] fluoranthene (BkF) and chrysene via central tendency exposure parameters (CTE) by trespassers (street hawkers including children and adults) in street dust within low traffic zones in the Tamale metropolis are 1.6E-02, 4.7E-02, 1.8E-03, and 1.6E-04 respectively. For reasonable maximum exposure parameters (RME), risk values of 1.2E-01, 3.5E-01, 1.3E-02 and 1.2E-03 respectively were obtained for benzo [a] anthracene, benzo [a] pyrene, benzo [k] fluoranthene and chrysene. Hazard index for acenaphthene, anthracene, fluoranthene, fluorine, naphthalene and pyrene in the CTE and RME scenarios were 2.2, 3.E-01, 2.6, 2.6, 100, 38 and 12, 1.7,15, 14, 550, 210 respectively. Generally, the cancer health risk associated with inhalation of benzo [a] anthracene, benzo [a] pyrene, benzo [k] fluoranthene and chrysene revealed that resident adults and children in the Tamale metropolis are at risk from exposure to these chemicals. The results of this preliminary assessment that quantified PAH related health risks along this part of the Trans-ECOWAS highway revealed that, there is the need for regulatory agencies to put in comprehensive measures to mitigate the risks posed to these categories of human receptors.

Three-dimensional modeling and simulation of asphalt concrete mixtures based on X-ray CT microstructure images

Directory of Open Access Journals (Sweden)

Hainian Wang

2014-02-01

Full Text Available X-ray CT (computed tomography was used to scan asphalt mixture specimen to obtain high resolution continuous cross-section images and the meso-structure. According to the theory of three-dimensional (3D reconstruction, the 3D reconstruction algorithm was investigated in this paper. The key to the reconstruction technique is the acquisition of the voxel positions and the relationship between the pixel element and node. Three-dimensional numerical model of asphalt mixture specimen was created by a self-developed program. A splitting test was conducted to predict the stress distributions of the asphalt mixture and verify the rationality of the 3D model.

Parallelization Experience with Four Canonical Econometric Models Using ParMitISEM

Directory of Open Access Journals (Sweden)

Nalan Baştürk

2016-03-01

Full Text Available This paper presents the parallel computing implementation of the MitISEM algorithm, labeled Parallel MitISEM. The basic MitISEM algorithm provides an automatic and flexible method to approximate a non-elliptical target density using adaptive mixtures of Student-t densities, where only a kernel of the target density is required. The approximation can be used as a candidate density in Importance Sampling or Metropolis Hastings methods for Bayesian inference on model parameters and probabilities. We present and discuss four canonical econometric models using a Graphics Processing Unit and a multi-core Central Processing Unit version of the MitISEM algorithm. The results show that the parallelization of the MitISEM algorithm on Graphics Processing Units and multi-core Central Processing Units is straightforward and fast to program using MATLAB. Moreover the speed performance of the Graphics Processing Unit version is much higher than the Central Processing Unit one.

Lattice Boltzmann scheme for mixture modeling: analysis of the continuum diffusion regimes recovering Maxwell-Stefan model and incompressible Navier-Stokes equations.

Science.gov (United States)

Asinari, Pietro

2009-11-01

A finite difference lattice Boltzmann scheme for homogeneous mixture modeling, which recovers Maxwell-Stefan diffusion model in the continuum limit, without the restriction of the mixture-averaged diffusion approximation, was recently proposed [P. Asinari, Phys. Rev. E 77, 056706 (2008)]. The theoretical basis is the Bhatnagar-Gross-Krook-type kinetic model for gas mixtures [P. Andries, K. Aoki, and B. Perthame, J. Stat. Phys. 106, 993 (2002)]. In the present paper, the recovered macroscopic equations in the continuum limit are systematically investigated by varying the ratio between the characteristic diffusion speed and the characteristic barycentric speed. It comes out that the diffusion speed must be at least one order of magnitude (in terms of Knudsen number) smaller than the barycentric speed, in order to recover the Navier-Stokes equations for mixtures in the incompressible limit. Some further numerical tests are also reported. In particular, (1) the solvent and dilute test cases are considered, because they are limiting cases in which the Maxwell-Stefan model reduces automatically to Fickian cases. Moreover, (2) some tests based on the Stefan diffusion tube are reported for proving the complete capabilities of the proposed scheme in solving Maxwell-Stefan diffusion problems. The proposed scheme agrees well with the expected theoretical results.

An evaluation of the Bayesian approach to fitting the N-mixture model for use with pseudo-replicated count data

Science.gov (United States)

Toribo, S.G.; Gray, B.R.; Liang, S.

2011-01-01

The N-mixture model proposed by Royle in 2004 may be used to approximate the abundance and detection probability of animal species in a given region. In 2006, Royle and Dorazio discussed the advantages of using a Bayesian approach in modelling animal abundance and occurrence using a hierarchical N-mixture model. N-mixture models assume replication on sampling sites, an assumption that may be violated when the site is not closed to changes in abundance during the survey period or when nominal replicates are defined spatially. In this paper, we studied the robustness of a Bayesian approach to fitting the N-mixture model for pseudo-replicated count data. Our simulation results showed that the Bayesian estimates for abundance and detection probability are slightly biased when the actual detection probability is small and are sensitive to the presence of extra variability within local sites.

Transient Response Analysis of Metropolis Learning in Games

KAUST Repository

Jaleel, Hassan

2017-10-19

The objective of this work is to provide a qualitative description of the transient properties of stochastic learning dynamics like adaptive play, log-linear learning, and Metropolis learning. The solution concept used in these learning dynamics for potential games is that of stochastic stability, which is based on the stationary distribution of the reversible Markov chain representing the learning process. However, time to converge to a stochastically stable state is exponential in the inverse of noise, which limits the use of stochastic stability as an effective solution concept for these dynamics. We propose a complete solution concept that qualitatively describes the state of the system at all times. The proposed concept is prevalent in control systems literature where a solution to a linear or a non-linear system has two parts, transient response and steady state response. Stochastic stability provides the steady state response of stochastic learning rules. In this work, we study its transient properties. Starting from an initial condition, we identify the subsets of the state space called cycles that have small hitting times and long exit times. Over the long time scales, we provide a description of how the distributions over joint action profiles transition from one cycle to another till it reaches the globally optimal state.

Transient Response Analysis of Metropolis Learning in Games

KAUST Repository

Jaleel, Hassan; Shamma, Jeff S.

2017-01-01

The objective of this work is to provide a qualitative description of the transient properties of stochastic learning dynamics like adaptive play, log-linear learning, and Metropolis learning. The solution concept used in these learning dynamics for potential games is that of stochastic stability, which is based on the stationary distribution of the reversible Markov chain representing the learning process. However, time to converge to a stochastically stable state is exponential in the inverse of noise, which limits the use of stochastic stability as an effective solution concept for these dynamics. We propose a complete solution concept that qualitatively describes the state of the system at all times. The proposed concept is prevalent in control systems literature where a solution to a linear or a non-linear system has two parts, transient response and steady state response. Stochastic stability provides the steady state response of stochastic learning rules. In this work, we study its transient properties. Starting from an initial condition, we identify the subsets of the state space called cycles that have small hitting times and long exit times. Over the long time scales, we provide a description of how the distributions over joint action profiles transition from one cycle to another till it reaches the globally optimal state.

Variable selection for mixture and promotion time cure rate models.

Science.gov (United States)

Masud, Abdullah; Tu, Wanzhu; Yu, Zhangsheng

2016-11-16

Failure-time data with cured patients are common in clinical studies. Data from these studies are typically analyzed with cure rate models. Variable selection methods have not been well developed for cure rate models. In this research, we propose two least absolute shrinkage and selection operators based methods, for variable selection in mixture and promotion time cure models with parametric or nonparametric baseline hazards. We conduct an extensive simulation study to assess the operating characteristics of the proposed methods. We illustrate the use of the methods using data from a study of childhood wheezing. © The Author(s) 2016.

Nonparametric Mixture Models for Supervised Image Parcellation.

Science.gov (United States)

Sabuncu, Mert R; Yeo, B T Thomas; Van Leemput, Koen; Fischl, Bruce; Golland, Polina

2009-09-01

We present a nonparametric, probabilistic mixture model for the supervised parcellation of images. The proposed model yields segmentation algorithms conceptually similar to the recently developed label fusion methods, which register a new image with each training image separately. Segmentation is achieved via the fusion of transferred manual labels. We show that in our framework various settings of a model parameter yield algorithms that use image intensity information differently in determining the weight of a training subject during fusion. One particular setting computes a single, global weight per training subject, whereas another setting uses locally varying weights when fusing the training data. The proposed nonparametric parcellation approach capitalizes on recently developed fast and robust pairwise image alignment tools. The use of multiple registrations allows the algorithm to be robust to occasional registration failures. We report experiments on 39 volumetric brain MRI scans with expert manual labels for the white matter, cerebral cortex, ventricles and subcortical structures. The results demonstrate that the proposed nonparametric segmentation framework yields significantly better segmentation than state-of-the-art algorithms.

Travel Characteristics and Commuting Pattern of Lagos Metropolis Residents: an Assessment

Directory of Open Access Journals (Sweden)

OSOBA, Samson Babatunde

2015-06-01

Full Text Available Urban travel is not solely the function of travel, but also on people’s participation in activities and how these were done. This study utilized 2,500 households’ samples in Lagos metropolis. The questionnaire about intra-city trip patterns was administered in direct proportion to the population size of each Local Government Areas (LGAs. Systematic sampling technique was used to select every tenth building on the identified streets. lt is observed that more than 95% of residents depends on roads, while less than 5% depends on Rail and Ferry. Work and business trips characterized the weekdays, while social, shopping and recreation trips dominate the weekends. This situation leads to too many vehicular traffic on the roads during the peak periods, leading to congestion and loss of valuable man-hours. Transportation planners in Lagos need to develop alternative intra-city transportation systems.

Prevalence of Overweight and Obesity among Students in the Kumasi Metropolis

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D. B. Kumah

2015-01-01

Full Text Available The aim was to determine the prevalence of obesity and overweight among students in the Kumasi metropolis. In a descriptive cross-sectional study, 500 students aged 10 to 20 years were examined from two junior high schools selected by multistage sampling technique and three randomly selected senior high schools. Height and weight were measured in all participants and the body mass index (BMI of each individual was calculated. Body mass index classes were calculated according to the International Obesity Task Force standards. Out of the 500 students, 290 (58.00% were males and 210 (42.00% were females. The prevalence of underweight, normal weight, overweight, and obesity was 7.40%, 79.60%, 12.20%, and 0.80%, respectively. Overweight was more prevalent among students than obesity. There is therefore the need to establish effective public health promotion campaigns among students in order to curtail future implications on health.

A new decomposition-based computer-aided molecular/mixture design methodology for the design of optimal solvents and solvent mixtures

DEFF Research Database (Denmark)

Karunanithi, A.T.; Achenie, L.E.K.; Gani, Rafiqul

2005-01-01

This paper presents a novel computer-aided molecular/mixture design (CAMD) methodology for the design of optimal solvents and solvent mixtures. The molecular/mixture design problem is formulated as a mixed integer nonlinear programming (MINLP) model in which a performance objective is to be optim......This paper presents a novel computer-aided molecular/mixture design (CAMD) methodology for the design of optimal solvents and solvent mixtures. The molecular/mixture design problem is formulated as a mixed integer nonlinear programming (MINLP) model in which a performance objective...... is to be optimized subject to structural, property, and process constraints. The general molecular/mixture design problem is divided into two parts. For optimal single-compound design, the first part is solved. For mixture design, the single-compound design is first carried out to identify candidates...... and then the second part is solved to determine the optimal mixture. The decomposition of the CAMD MINLP model into relatively easy to solve subproblems is essentially a partitioning of the constraints from the original set. This approach is illustrated through two case studies. The first case study involves...

Easy and flexible mixture distributions

DEFF Research Database (Denmark)

Fosgerau, Mogens; Mabit, Stefan L.

2013-01-01

We propose a method to generate flexible mixture distributions that are useful for estimating models such as the mixed logit model using simulation. The method is easy to implement, yet it can approximate essentially any mixture distribution. We test it with good results in a simulation study...

Modeling Hydrodynamic State of Oil and Gas Condensate Mixture in a Pipeline

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Dudin Sergey

2016-01-01

Based on the developed model a calculation method was obtained which is used to analyze hydrodynamic state and composition of hydrocarbon mixture in each ith section of the pipeline when temperature-pressure and hydraulic conditions change.

Two-component mixture model: Application to palm oil and exchange rate

Science.gov (United States)

Phoong, Seuk-Yen; Ismail, Mohd Tahir; Hamzah, Firdaus Mohamad

2014-12-01

Palm oil is a seed crop which is widely adopt for food and non-food products such as cookie, vegetable oil, cosmetics, household products and others. Palm oil is majority growth in Malaysia and Indonesia. However, the demand for palm oil is getting growth and rapidly running out over the years. This phenomenal cause illegal logging of trees and destroy the natural habitat. Hence, the present paper investigates the relationship between exchange rate and palm oil price in Malaysia by using Maximum Likelihood Estimation via Newton-Raphson algorithm to fit a two components mixture model. Besides, this paper proposes a mixture of normal distribution to accommodate with asymmetry characteristics and platykurtic time series data.

Rheology of petrolatum-paraffin oil mixtures : Applications to analogue modelling of geological processes

NARCIS (Netherlands)

Duarte, João C.; Schellart, Wouter P.; Cruden, Alexander R.

2014-01-01

Paraffins have been widely used in analogue modelling of geological processes. Petrolatum and paraffin oil are commonly used to lubricate model boundaries and to simulate weak layers. In this paper, we present rheological tests of petrolatum, paraffin oil and several homogeneous mixtures of the two.

An Empirical Bayes Mixture Model for Effect Size Distributions in Genome-Wide Association Studies

DEFF Research Database (Denmark)

Thompson, Wesley K.; Wang, Yunpeng; Schork, Andrew J.

2015-01-01

-wide association study (GWAS) test statistics. Test statistics corresponding to null associations are modeled as random draws from a normal distribution with zero mean; test statistics corresponding to non-null associations are also modeled as normal with zero mean, but with larger variance. The model is fit via...... analytically and in simulations. We apply this approach to meta-analysis test statistics from two large GWAS, one for Crohn’s disease (CD) and the other for schizophrenia (SZ). A scale mixture of two normals distribution provides an excellent fit to the SZ nonparametric replication effect size estimates. While...... minimizing discrepancies between the parametric mixture model and resampling-based nonparametric estimates of replication effect sizes and variances. We describe in detail the implications of this model for estimation of the non-null proportion, the probability of replication in de novo samples, the local...

Mixture-mixture design for the fingerprint optimization of chromatographic mobile phases and extraction solutions for Camellia sinensis.

Science.gov (United States)

Borges, Cleber N; Bruns, Roy E; Almeida, Aline A; Scarminio, Ieda S

2007-07-09

A composite simplex centroid-simplex centroid mixture design is proposed for simultaneously optimizing two mixture systems. The complementary model is formed by multiplying special cubic models for the two systems. The design was applied to the simultaneous optimization of both mobile phase chromatographic mixtures and extraction mixtures for the Camellia sinensis Chinese tea plant. The extraction mixtures investigated contained varying proportions of ethyl acetate, ethanol and dichloromethane while the mobile phase was made up of varying proportions of methanol, acetonitrile and a methanol-acetonitrile-water (MAW) 15%:15%:70% mixture. The experiments were block randomized corresponding to a split-plot error structure to minimize laboratory work and reduce environmental impact. Coefficients of an initial saturated model were obtained using Scheffe-type equations. A cumulative probability graph was used to determine an approximate reduced model. The split-plot error structure was then introduced into the reduced model by applying generalized least square equations with variance components calculated using the restricted maximum likelihood approach. A model was developed to calculate the number of peaks observed with the chromatographic detector at 210 nm. A 20-term model contained essentially all the statistical information of the initial model and had a root mean square calibration error of 1.38. The model was used to predict the number of peaks eluted in chromatograms obtained from extraction solutions that correspond to axial points of the simplex centroid design. The significant model coefficients are interpreted in terms of interacting linear, quadratic and cubic effects of the mobile phase and extraction solution components.

Discrete Element Method Modeling of the Rheological Properties of Coke/Pitch Mixtures.

Science.gov (United States)

Majidi, Behzad; Taghavi, Seyed Mohammad; Fafard, Mario; Ziegler, Donald P; Alamdari, Houshang

2016-05-04

Rheological properties of pitch and pitch/coke mixtures at temperatures around 150 °C are of great interest for the carbon anode manufacturing process in the aluminum industry. In the present work, a cohesive viscoelastic contact model based on Burger's model is developed using the discrete element method (DEM) on the YADE, the open-source DEM software. A dynamic shear rheometer (DSR) is used to measure the viscoelastic properties of pitch at 150 °C. The experimental data obtained is then used to estimate the Burger's model parameters and calibrate the DEM model. The DSR tests were then simulated by a three-dimensional model. Very good agreement was observed between the experimental data and simulation results. Coke aggregates were modeled by overlapping spheres in the DEM model. Coke/pitch mixtures were numerically created by adding 5, 10, 20, and 30 percent of coke aggregates of the size range of 0.297-0.595 mm (-30 + 50 mesh) to pitch. Adding up to 30% of coke aggregates to pitch can increase its complex shear modulus at 60 Hz from 273 Pa to 1557 Pa. Results also showed that adding coke particles increases both storage and loss moduli, while it does not have a meaningful effect on the phase angle of pitch.

Partitioning detectability components in populations subject to within-season temporary emigration using binomial mixture models.

Science.gov (United States)

O'Donnell, Katherine M; Thompson, Frank R; Semlitsch, Raymond D

2015-01-01

Detectability of individual animals is highly variable and nearly always binomial mixture models to account for multiple sources of variation in detectability. The state process of the hierarchical model describes ecological mechanisms that generate spatial and temporal patterns in abundance, while the observation model accounts for the imperfect nature of counting individuals due to temporary emigration and false absences. We illustrate our model's potential advantages, including the allowance of temporary emigration between sampling periods, with a case study of southern red-backed salamanders Plethodon serratus. We fit our model and a standard binomial mixture model to counts of terrestrial salamanders surveyed at 40 sites during 3-5 surveys each spring and fall 2010-2012. Our models generated similar parameter estimates to standard binomial mixture models. Aspect was the best predictor of salamander abundance in our case study; abundance increased as aspect became more northeasterly. Increased time-since-rainfall strongly decreased salamander surface activity (i.e. availability for sampling), while higher amounts of woody cover objects and rocks increased conditional detection probability (i.e. probability of capture, given an animal is exposed to sampling). By explicitly accounting for both components of detectability, we increased congruence between our statistical modeling and our ecological understanding of the system. We stress the importance of choosing survey locations and protocols that maximize species availability and conditional detection probability to increase population parameter estimate reliability.

Applications of the Simple Multi-Fluid Model to Correlations of the Vapor-Liquid Equilibrium of Refrigerant Mixtures Containing Carbon Dioxide

Science.gov (United States)

Akasaka, Ryo

This study presents a simple multi-fluid model for Helmholtz energy equations of state. The model contains only three parameters, whereas rigorous multi-fluid models developed for several industrially important mixtures usually have more than 10 parameters and coefficients. Therefore, the model can be applied to mixtures where experimental data is limited. Vapor-liquid equilibrium (VLE) of the following seven mixtures have been successfully correlated with the model: CO2 + difluoromethane (R-32), CO2 + trifluoromethane (R-23), CO2 + fluoromethane (R-41), CO2 + 1,1,1,2- tetrafluoroethane (R-134a), CO2 + pentafluoroethane (R-125), CO2 + 1,1-difluoroethane (R-152a), and CO2 + dimethyl ether (DME). The best currently available equations of state for the pure refrigerants were used for the correlations. For all mixtures, average deviations in calculated bubble-point pressures from experimental values are within 2%. The simple multi-fluid model will be helpful for design and simulations of heat pumps and refrigeration systems using the mixtures as working fluid.

Densities of Pure Ionic Liquids and Mixtures: Modeling and Data Analysis

DEFF Research Database (Denmark)

Abildskov, Jens; O’Connell, John P.

2015-01-01

Our two-parameter corresponding states model for liquid densities and compressibilities has been extended to more pure ionic liquids and to their mixtures with one or two solvents. A total of 19 new group contributions (5 new cations and 14 new anions) have been obtained for predicting pressure...

Modelling time course gene expression data with finite mixtures of linear additive models.

Science.gov (United States)

Grün, Bettina; Scharl, Theresa; Leisch, Friedrich

2012-01-15

A model class of finite mixtures of linear additive models is presented. The component-specific parameters in the regression models are estimated using regularized likelihood methods. The advantages of the regularization are that (i) the pre-specified maximum degrees of freedom for the splines is less crucial than for unregularized estimation and that (ii) for each component individually a suitable degree of freedom is selected in an automatic way. The performance is evaluated in a simulation study with artificial data as well as on a yeast cell cycle dataset of gene expression levels over time. The latest release version of the R package flexmix is available from CRAN (http://cran.r-project.org/).

A non-ideal model for predicting the effect of dissolved salt on the flash point of solvent mixtures.

Science.gov (United States)

Liaw, Horng-Jang; Wang, Tzu-Ai

2007-03-06

Flash point is one of the major quantities used to characterize the fire and explosion hazard of liquids. Herein, a liquid with dissolved salt is presented in a salt-distillation process for separating close-boiling or azeotropic systems. The addition of salts to a liquid may reduce fire and explosion hazard. In this study, we have modified a previously proposed model for predicting the flash point of miscible mixtures to extend its application to solvent/salt mixtures. This modified model was verified by comparison with the experimental data for organic solvent/salt and aqueous-organic solvent/salt mixtures to confirm its efficacy in terms of prediction of the flash points of these mixtures. The experimental results confirm marked increases in liquid flash point increment with addition of inorganic salts relative to supplementation with equivalent quantities of water. Based on this evidence, it appears reasonable to suggest potential application for the model in assessment of the fire and explosion hazard for solvent/salt mixtures and, further, that addition of inorganic salts may prove useful for hazard reduction in flammable liquids.

A Mixture Model of Consumers' Intended Purchase Decisions for Genetically Modified Foods

OpenAIRE

Kristine M. Grimsrud; Robert P. Berrens; Ron C. Mittelhammer

2006-01-01

A finite probability mixture model is used to analyze the existence of multiple market segments for a pre-market good. The approach has at least two principal benefits. First, the model is capable of identifying likely market segments and their differentiating characteristics. Second, the model can be used to estimate the discount different consumer groups require to purchase the good. The model is illustrated using stated preference survey data collected on consumer responses to the potentia...

Application of pattern mixture models to address missing data in longitudinal data analysis using SPSS.

Science.gov (United States)

Son, Heesook; Friedmann, Erika; Thomas, Sue A

2012-01-01

Longitudinal studies are used in nursing research to examine changes over time in health indicators. Traditional approaches to longitudinal analysis of means, such as analysis of variance with repeated measures, are limited to analyzing complete cases. This limitation can lead to biased results due to withdrawal or data omission bias or to imputation of missing data, which can lead to bias toward the null if data are not missing completely at random. Pattern mixture models are useful to evaluate the informativeness of missing data and to adjust linear mixed model (LMM) analyses if missing data are informative. The aim of this study was to provide an example of statistical procedures for applying a pattern mixture model to evaluate the informativeness of missing data and conduct analyses of data with informative missingness in longitudinal studies using SPSS. The data set from the Patients' and Families' Psychological Response to Home Automated External Defibrillator Trial was used as an example to examine informativeness of missing data with pattern mixture models and to use a missing data pattern in analysis of longitudinal data. Prevention of withdrawal bias, omitted data bias, and bias toward the null in longitudinal LMMs requires the assessment of the informativeness of the occurrence of missing data. Missing data patterns can be incorporated as fixed effects into LMMs to evaluate the contribution of the presence of informative missingness to and control for the effects of missingness on outcomes. Pattern mixture models are a useful method to address the presence and effect of informative missingness in longitudinal studies.

A binary mixture operated heat pump

International Nuclear Information System (INIS)

Hihara, E.; Saito, T.

1991-01-01

This paper evaluates the performance of possible binary mixtures as working fluids in high- temperature heat pump applications. The binary mixtures, which are potential alternatives of fully halogenated hydrocarbons, include HCFC142b/HCFC22, HFC152a/HCFC22, HFC134a/HCFC22. The performance of the mixtures is estimated by a thermodynamic model and a practical model in which the heat transfer is considered in heat exchangers. One of the advantages of binary mixtures is a higher coefficient of performance, which is caused by the small temperature difference between the heat-sink/-source fluid and the refrigerant. The mixture HCFC142b/HCFC22 is promising from the stand point of thermodynamic performance

Induced polarization of clay-sand mixtures: experiments and modeling

International Nuclear Information System (INIS)

Okay, G.; Leroy, P.; Tournassat, C.; Ghorbani, A.; Jougnot, D.; Cosenza, P.; Camerlynck, C.; Cabrera, J.; Florsch, N.; Revil, A.

2012-01-01

were performed with a cylindrical four-electrode sample-holder (cylinder made of PVC with 30 cm in length and 19 cm in diameter) associated with a SIP-Fuchs II impedance meter and non-polarizing Cu/CuSO 4 electrodes. These electrodes were installed at 10 cm from the base of the sample holder and regularly spaced (each 90 degree). The results illustrate the strong impact of the Cationic Exchange Capacity (CEC) of the clay minerals upon the complex conductivity. The amplitude of the in-phase conductivity of the kaolinite-clay samples is strongly dependent to saturating fluid salinity for all volumetric clay fractions, whereas the in-phase conductivity of the smectite-clay samples is quite independent on the salinity, except at the low clay content (5% and 1% of clay in volume). This is due to the strong and constant surface conductivity of smectite associated with its very high CEC. The quadrature conductivity increases steadily with the CEC and the clay content. We observe that the dependence on frequency of the quadrature conductivity of sand-kaolinite mixtures is more important than for sand-bentonite mixtures. For both types of clay, the quadrature conductivity seems to be fairly independent on the pore fluid salinity except at very low clay contents (1% in volume of kaolinite-clay). This is due to the constant surface site density of Na counter-ions in the Stern layer of clay materials. At the lowest clay content (1%), the magnitude of the quadrature conductivity increases with the salinity, as expected for silica sands. In this case, the surface site density of Na counter-ions in the Stern layer increases with salinity. The experimental data show good agreement with predicted values given by our Spectral Induced Polarization (SIP) model. This complex conductivity model considers the electrochemical polarization of the Stern layer coating the clay particles and the Maxwell-Wagner polarization. We use the differential effective medium theory to calculate the complex

ESTIMASI BAYESIAN PADA MODEL PERSAMAAN STRUKTURAL DENGAN VARIABEL KATEGORIK TERURUT

Directory of Open Access Journals (Sweden)

Rini Yunita

2016-05-01

Full Text Available Abstract  This article explains about parameter estimation of structural equation model with ordered categorical variable using Bayes method. The basic assumptions of SEM are the data type is continuous, minimum scale is interval, and it has to satisfy the normality assumption. The categorical data is ordinal data which the observation is in discrete form, and to treat the categorical data as normally distributed continuous data is by finding threshold parameter for each categorical data. Bayes method only focuses on individual data by combining sample data and the research data before (prior information, in order to minimize the error rate. Hence, the parameter estimation of structural equation model can be obtained well. In this estimation process, it is done numerically by using Monte Carlo method, i.e. Gibbs Sampling and Metropolis Hasting. Keywords:   Structural Equation Modeling ,categorical data, Threshold, Gibbs Sampling, Metropolis Hasting. Abstrak Dalam artikel ini dijelaskan tentang estimasi parameter dari model persamaan struktural dengan variabel kategorik terurut dengan menggunakan metode Bayes. Asumsi dasar dari SEM adalah  jenis datanya kontinu dan minimal berskala interval serta memenuhi asumsi normalitas. Sementara data kategorik merupakan data ordinal dengan pengamatan dalam bentuk diskrit, untuk dapat memperlakukan data kategorik sebagai data kontinu berdistribusi normal yaitu dengan mencari treshold paramater untuk masing-masing data kategorik. Metode Bayes  hanya berfokus pada data individu dengan menggabungkan antara data sampel dengan data penelitian sebelumnya (informasi prior, dengan tujuan untuk meminimalkan tingkat kesalahan. Sehingga estimasi parameter dari model persamaan struktural dapat dihasilkan dengan baik. Dalam proses estimasi, hal ini dilakukan secara numerik dengan menggunakan metode Monte Carlo, yaitu Gibbs Sampling dan Metropolis Hasting. Kata Kunci:  Model Persamaan Struktural, data kategorik

Flexible mixture modeling via the multivariate t distribution with the Box-Cox transformation: an alternative to the skew-t distribution.

Science.gov (United States)

Lo, Kenneth; Gottardo, Raphael

2012-01-01

Cluster analysis is the automated search for groups of homogeneous observations in a data set. A popular modeling approach for clustering is based on finite normal mixture models, which assume that each cluster is modeled as a multivariate normal distribution. However, the normality assumption that each component is symmetric is often unrealistic. Furthermore, normal mixture models are not robust against outliers; they often require extra components for modeling outliers and/or give a poor representation of the data. To address these issues, we propose a new class of distributions, multivariate t distributions with the Box-Cox transformation, for mixture modeling. This class of distributions generalizes the normal distribution with the more heavy-tailed t distribution, and introduces skewness via the Box-Cox transformation. As a result, this provides a unified framework to simultaneously handle outlier identification and data transformation, two interrelated issues. We describe an Expectation-Maximization algorithm for parameter estimation along with transformation selection. We demonstrate the proposed methodology with three real data sets and simulation studies. Compared with a wealth of approaches including the skew-t mixture model, the proposed t mixture model with the Box-Cox transformation performs favorably in terms of accuracy in the assignment of observations, robustness against model misspecification, and selection of the number of components.

Sworn testimony of the model evidence: Gaussian Mixture Importance (GAME) sampling

Science.gov (United States)

Volpi, Elena; Schoups, Gerrit; Firmani, Giovanni; Vrugt, Jasper A.

2017-07-01

What is the "best" model? The answer to this question lies in part in the eyes of the beholder, nevertheless a good model must blend rigorous theory with redeeming qualities such as parsimony and quality of fit. Model selection is used to make inferences, via weighted averaging, from a set of K candidate models, Mk; k=>(1,…,K>), and help identify which model is most supported by the observed data, Y>˜=>(y˜1,…,y˜n>). Here, we introduce a new and robust estimator of the model evidence, p>(Y>˜|Mk>), which acts as normalizing constant in the denominator of Bayes' theorem and provides a single quantitative measure of relative support for each hypothesis that integrates model accuracy, uncertainty, and complexity. However, p>(Y>˜|Mk>) is analytically intractable for most practical modeling problems. Our method, coined GAussian Mixture importancE (GAME) sampling, uses bridge sampling of a mixture distribution fitted to samples of the posterior model parameter distribution derived from MCMC simulation. We benchmark the accuracy and reliability of GAME sampling by application to a diverse set of multivariate target distributions (up to 100 dimensions) with known values of p>(Y>˜|Mk>) and to hypothesis testing using numerical modeling of the rainfall-runoff transformation of the Leaf River watershed in Mississippi, USA. These case studies demonstrate that GAME sampling provides robust and unbiased estimates of the evidence at a relatively small computational cost outperforming commonly used estimators. The GAME sampler is implemented in the MATLAB package of DREAM and simplifies considerably scientific inquiry through hypothesis testing and model selection.

The phase behavior of a hard sphere chain model of a binary n-alkane mixture

International Nuclear Information System (INIS)

Malanoski, A. P.; Monson, P. A.

2000-01-01

Monte Carlo computer simulations have been used to study the solid and fluid phase properties as well as phase equilibrium in a flexible, united atom, hard sphere chain model of n-heptane/n-octane mixtures. We describe a methodology for calculating the chemical potentials for the components in the mixture based on a technique used previously for atomic mixtures. The mixture was found to conform accurately to ideal solution behavior in the fluid phase. However, much greater nonidealities were seen in the solid phase. Phase equilibrium calculations indicate a phase diagram with solid-fluid phase equilibrium and a eutectic point. The components are only miscible in the solid phase for dilute solutions of the shorter chains in the longer chains. (c) 2000 American Institute of Physics

Modeling of the flame propagation in coal-dust- methane air mixture in an enclosed sphere volume

International Nuclear Information System (INIS)

Krainov, A Yu; Moiseeva, K M

2016-01-01

The results of the numerical simulation of the flame front propagation in coal-dust- methane-air mixture in an enclosed volume with the ignition source in the center of the volume are presented. The mathematical model is based on a dual-velocity two-phase model of the reacting gas-dispersion medium. The system of equations includes the mass-conversation equation, the impulse-conversation equation, the total energy-conversation equation of the gas and particles taking into account the thermal conductivity and chemical reactions in the gas and on the particle surface, mass-conversation equation of the mixture gas components considering the diffusion and the burn-out and the particle burn-out equation. The influence of the coal particle mass on the pressure in the volume after the mixture burn out and on the burn-out time has been investigated. It has been shown that the burning rate of the coal-dust methane air mixtures depends on the coal particle size. (paper)

Generalization of two-phase model with topology microstructure of mixture to Lagrange-Euler methodology

International Nuclear Information System (INIS)

Vladimir V Chudanov; Alexei A Leonov

2005-01-01

Full text of publication follows: One of the mathematical models (hyperbolic type) for describing evolution of compressible two-phase mixtures was offered in [1] to deal with the following applications: interfaces between compressible materials; shock waves in multiphase mixtures; evolution of homogeneous two-phase flows; cavitation in liquids. The basic difficulties of this model was connected to discretization of the non-conservative equation terms. As result, the class of problems concerned with passage of shock waves through fields with a discontinuing profile of a volume fraction was not described by means of this model. A class of schemes that are able to converge to the correct solution of such problems was received in [2] due to a deeper analysis of two-phase model. The technique offered in [2] was implemented on a Eulerian grid via the Godunov scheme. In present paper the additional analysis of two-phase model in view of microstructure of an mixture topology is carried out in Lagrange mass coordinates. As result, the equations averaged over the set of all possible realizations for two-phase mixture are received. The numerical solution is carried out with use of PPM method [3] in two steps: at first - the equations averaged over mass variable are solved; on the second - the solution, found on the previous step, is re-mapped to a fixed Eulerian grid. Such approach allows to expand the proposed technique on two-dimensional (three-dimensional) case, as in the Lagrange variables the Euler equations system is split on two (three) identical subsystems, each of which describes evolution of considered medium in the given direction. The accuracy and robustness of the described procedure are demonstrated on a sequence of the numerical problems. References: (1). R. Saurel, R. Abgrall, A multiphase Godunov method for compressible multi-fluid and multiphase flows, J. Comput. Phys. 150 (1999) 425-467; (2). R. Saurel, R. Abgrall, Discrete equations for physical and

Personal exposure to mixtures of volatile organic compounds: modeling and further analysis of the RIOPA data.

Science.gov (United States)

Batterman, Stuart; Su, Feng-Chiao; Li, Shi; Mukherjee, Bhramar; Jia, Chunrong

2014-06-01

Emission sources of volatile organic compounds (VOCs*) are numerous and widespread in both indoor and outdoor environments. Concentrations of VOCs indoors typically exceed outdoor levels, and most people spend nearly 90% of their time indoors. Thus, indoor sources generally contribute the majority of VOC exposures for most people. VOC exposure has been associated with a wide range of acute and chronic health effects; for example, asthma, respiratory diseases, liver and kidney dysfunction, neurologic impairment, and cancer. Although exposures to most VOCs for most persons fall below health-based guidelines, and long-term trends show decreases in ambient emissions and concentrations, a subset of individuals experience much higher exposures that exceed guidelines. Thus, exposure to VOCs remains an important environmental health concern. The present understanding of VOC exposures is incomplete. With the exception of a few compounds, concentration and especially exposure data are limited; and like other environmental data, VOC exposure data can show multiple modes, low and high extreme values, and sometimes a large portion of data below method detection limits (MDLs). Field data also show considerable spatial or interpersonal variability, and although evidence is limited, temporal variability seems high. These characteristics can complicate modeling and other analyses aimed at risk assessment, policy actions, and exposure management. In addition to these analytic and statistical issues, exposure typically occurs as a mixture, and mixture components may interact or jointly contribute to adverse effects. However most pollutant regulations, guidelines, and studies remain focused on single compounds, and thus may underestimate cumulative exposures and risks arising from coexposures. In addition, the composition of VOC mixtures has not been thoroughly investigated, and mixture components show varying and complex dependencies. Finally, although many factors are known to

A Mixture Innovation Heterogeneous Autoregressive Model for Structural Breaks and Long Memory

DEFF Research Database (Denmark)

Nonejad, Nima

We propose a flexible model to describe nonlinearities and long-range dependence in time series dynamics. Our model is an extension of the heterogeneous autoregressive model. Structural breaks occur through mixture distributions in state innovations of linear Gaussian state space models. Monte...... Carlo simulations evaluate the properties of the estimation procedures. Results show that the proposed model is viable and flexible for purposes of forecasting volatility. Model uncertainty is accounted for by employing Bayesian model averaging. Bayesian model averaging provides very competitive...... forecasts compared to any single model specification. It provides further improvements when we average over nonlinear specifications....

Polarisation of Social Inequalities in Disadvantaged Neighbourhoods of Bucharest Metropolis

Directory of Open Access Journals (Sweden)

ALINA T. CHICOŞ

2013-01-01

Full Text Available This paper gives an insight into the statistical interpretation of socio-spatial changes of Bucharest urban landscape in connection to the transformations of the urban planning visions across the last decades. Special emphasis is placed on the emergence of disadvantaged neighbourhoods which are defined by a clear homogenisation of certain social classes on a precarious housing infrastructure. This came as a result of a historical hierarchy of the urban social space. Moreover, Bucharest was shaped in relation to different socio-economic and socio-cultural policies that determined the creation of a polarisation between north and south or between centre and periphery which were subject to numerous socio-urban inversions during the communist and post-communist eras. Hence, life in a large metropolis is vulnerable to inequalities appearing within the urban pattern that intensifies, in some cases, towards residential segregation. The historical-geographical analysis of vectors behind clusters of sensitive areas in the 20th and 21st centuries strengthens the importance of social cohesion measures in the future urban policies and territorial planning.

Phase equilibria for mixtures containing nonionic surfactant systems: Modeling and experiments

International Nuclear Information System (INIS)

Shin, Moon Sam; Kim, Hwayong

2008-01-01

Surfactants are important materials with numerous applications in the cosmetic, pharmaceutical, and food industries due to inter-associating and intra-associating bond. We present a lattice fluid equation-of-state that combines the quasi-chemical nonrandom lattice fluid model with Veytsman statistics for (intra + inter) molecular association to calculate phase behavior for mixtures containing nonionic surfactants. We also measured binary (vapor + liquid) equilibrium data for {2-butoxyethanol (C 4 E 1 ) + n-hexane} and {2-butoxyethanol (C 4 E 1 ) + n-heptane} systems at temperatures ranging from (303.15 to 323.15) K. A static apparatus was used in this study. The presented equation-of-state correlated well with the measured and published data for mixtures containing nonionic surfactant systems

Analysis of vehicular fallouts from traffic in the Kumasi Metropolis, Ghana

Directory of Open Access Journals (Sweden)

D.K. Essumang

2006-12-01

Full Text Available Concentrations of platinum, lead, cadmium, copper, and zinc in dust from areas of high, medium, low and very low vehicular movements in Kumasi Metropolis in the Ashanti Region of the Republic of Ghana was measured. High concentrations of platinum, lead, copper, and zinc were found to be associated with soils from areas of high traffic densities suggesting that vehicles (that ply these areas also contribute heavy metals to the environment. The results of the study shows that the road and users, like residents living in buildings within these areas, those engaged in commercial activities like hawking, and the general public are at risk of exposure to the toxic effects of Pt, Pb, Cd, Cu, and Zn as they inhale those metals released from the exhaust of vehicles into the environment. According to these results, there is the potential for exposure to high levels of Pt, Cd, Pb, Cu, and Zn for road users and those living in urban environments or along the highways.

A Generic Model for Prediction of Separation Performance of Olefin/Paraffin Mixture by Glassy Polymer Membranes

Directory of Open Access Journals (Sweden)

A.A. Ghoreyshi

2008-02-01

Full Text Available The separation of olefin/paraffin mixtures is an important process in petrochemical industries, which is traditionally performed by low temperature distillation with a high-energy consumption, or complex extractive distillationand adsorption techniques. Membrane separation process is emerging as an alternative for traditional separation processes with respect to low energy and simple operation. Investigations made by various researchers on polymeric membranes it is found that special glassy polymers render them as suitable materials for olefin/paraffin mixture separation. In this regard, having some knowledge on the possible transport mechanism of these processes would play a significant role in their design and applications. In this study, separation behavior of olefin/paraffin mixtures through glassy polymers was modeled by three different approaches: the so-called dual transport model, the basic adsorption-diffusion theory and the general Maxwell-Stefan formulation. The systems chosen to validate the developed transport models are separation of ethane-ethylene mixture by 6FDA-6FpDA polyimide membrane and propane-propylene mixture by 6FDA-TrMPD polyimide membrane for which the individual sorption and permeation data are available in the literature. Acritical examination of dual transport model shows that this model fails clearly to predict even the proper trend for selectivities. The adjustment of pemeabilities by accounting for the contribution of non-selective bulk flow in the transport model introduced no improvement in the predictability of the model. The modeling results based on the basic adsorption-diffusion theory revealed that in this approach only using mixed permeability data, an acceptable result is attainable which fades out the advantages of predictibility of multicomponent separation performance from pure component data. Finally, the results obtained from the model developed based on Maxwell-Stefan formulation approach show a

Fast Bayesian Inference in Dirichlet Process Mixture Models.

Science.gov (United States)

Wang, Lianming; Dunson, David B

2011-01-01

There has been increasing interest in applying Bayesian nonparametric methods in large samples and high dimensions. As Markov chain Monte Carlo (MCMC) algorithms are often infeasible, there is a pressing need for much faster algorithms. This article proposes a fast approach for inference in Dirichlet process mixture (DPM) models. Viewing the partitioning of subjects into clusters as a model selection problem, we propose a sequential greedy search algorithm for selecting the partition. Then, when conjugate priors are chosen, the resulting posterior conditionally on the selected partition is available in closed form. This approach allows testing of parametric models versus nonparametric alternatives based on Bayes factors. We evaluate the approach using simulation studies and compare it with four other fast nonparametric methods in the literature. We apply the proposed approach to three datasets including one from a large epidemiologic study. Matlab codes for the simulation and data analyses using the proposed approach are available online in the supplemental materials.

Personal Exposure to Mixtures of Volatile Organic Compounds: Modeling and Further Analysis of the RIOPA Data

Science.gov (United States)

Batterman, Stuart; Su, Feng-Chiao; Li, Shi; Mukherjee, Bhramar; Jia, Chunrong

2015-01-01

INTRODUCTION Emission sources of volatile organic compounds (VOCs) are numerous and widespread in both indoor and outdoor environments. Concentrations of VOCs indoors typically exceed outdoor levels, and most people spend nearly 90% of their time indoors. Thus, indoor sources generally contribute the majority of VOC exposures for most people. VOC exposure has been associated with a wide range of acute and chronic health effects; for example, asthma, respiratory diseases, liver and kidney dysfunction, neurologic impairment, and cancer. Although exposures to most VOCs for most persons fall below health-based guidelines, and long-term trends show decreases in ambient emissions and concentrations, a subset of individuals experience much higher exposures that exceed guidelines. Thus, exposure to VOCs remains an important environmental health concern. The present understanding of VOC exposures is incomplete. With the exception of a few compounds, concentration and especially exposure data are limited; and like other environmental data, VOC exposure data can show multiple modes, low and high extreme values, and sometimes a large portion of data below method detection limits (MDLs). Field data also show considerable spatial or interpersonal variability, and although evidence is limited, temporal variability seems high. These characteristics can complicate modeling and other analyses aimed at risk assessment, policy actions, and exposure management. In addition to these analytic and statistical issues, exposure typically occurs as a mixture, and mixture components may interact or jointly contribute to adverse effects. However most pollutant regulations, guidelines, and studies remain focused on single compounds, and thus may underestimate cumulative exposures and risks arising from coexposures. In addition, the composition of VOC mixtures has not been thoroughly investigated, and mixture components show varying and complex dependencies. Finally, although many factors are

Separation of a multicomponent mixture by gaseous diffusion: modelization of the enrichment in a capillary - application to a pilot cascade

International Nuclear Information System (INIS)

Doneddu, F.

1982-01-01

Starting from the modelization of gaseous flow in a porous medium (flow in a capillary), we generalize the law of enrichment in an infinite cylindrical capillary, established for an isotropic linear mixture, to a multicomponent mixture. A generalization is given of the notion of separation yields and characteristic pressure classically used for separations of isotropic linear mixtures. We present formulas for diagonalizing the diffusion operator, modelization of a multistage, gaseous diffusion cascade and comparison with the experimental results of a drain cascade (N 2 -SF 6 -UF 6 mixture). [fr

Soot modeling of counterflow diffusion flames of ethylene-based binary mixture fuels

KAUST Repository

Wang, Yu; Raj, Abhijeet Dhayal; Chung, Suk-Ho

2015-01-01

of ethylene and its binary mixtures with methane, ethane and propane based on the method of moments. The soot model has 36 soot nucleation reactions from 8 PAH molecules including pyrene and larger PAHs. Soot surface growth reactions were based on a modified

Discrete Element Method Modeling of the Rheological Properties of Coke/Pitch Mixtures

Directory of Open Access Journals (Sweden)

Behzad Majidi

2016-05-01

Full Text Available Rheological properties of pitch and pitch/coke mixtures at temperatures around 150 °C are of great interest for the carbon anode manufacturing process in the aluminum industry. In the present work, a cohesive viscoelastic contact model based on Burger’s model is developed using the discrete element method (DEM on the YADE, the open-source DEM software. A dynamic shear rheometer (DSR is used to measure the viscoelastic properties of pitch at 150 °C. The experimental data obtained is then used to estimate the Burger’s model parameters and calibrate the DEM model. The DSR tests were then simulated by a three-dimensional model. Very good agreement was observed between the experimental data and simulation results. Coke aggregates were modeled by overlapping spheres in the DEM model. Coke/pitch mixtures were numerically created by adding 5, 10, 20, and 30 percent of coke aggregates of the size range of 0.297–0.595 mm (−30 + 50 mesh to pitch. Adding up to 30% of coke aggregates to pitch can increase its complex shear modulus at 60 Hz from 273 Pa to 1557 Pa. Results also showed that adding coke particles increases both storage and loss moduli, while it does not have a meaningful effect on the phase angle of pitch.

Spatial Mixture Modelling for Unobserved Point Processes: Examples in Immunofluorescence Histology.

Science.gov (United States)

Ji, Chunlin; Merl, Daniel; Kepler, Thomas B; West, Mike

2009-12-04

We discuss Bayesian modelling and computational methods in analysis of indirectly observed spatial point processes. The context involves noisy measurements on an underlying point process that provide indirect and noisy data on locations of point outcomes. We are interested in problems in which the spatial intensity function may be highly heterogenous, and so is modelled via flexible nonparametric Bayesian mixture models. Analysis aims to estimate the underlying intensity function and the abundance of realized but unobserved points. Our motivating applications involve immunological studies of multiple fluorescent intensity images in sections of lymphatic tissue where the point processes represent geographical configurations of cells. We are interested in estimating intensity functions and cell abundance for each of a series of such data sets to facilitate comparisons of outcomes at different times and with respect to differing experimental conditions. The analysis is heavily computational, utilizing recently introduced MCMC approaches for spatial point process mixtures and extending them to the broader new context here of unobserved outcomes. Further, our example applications are problems in which the individual objects of interest are not simply points, but rather small groups of pixels; this implies a need to work at an aggregate pixel region level and we develop the resulting novel methodology for this. Two examples with with immunofluorescence histology data demonstrate the models and computational methodology.

Are separate-phase thermal-hydraulic models better than mixture-fluid approaches? It depends. Rather not

International Nuclear Information System (INIS)

Hoeld, A.

2004-01-01

The thermal-hydraulic theory of single- and especially two-phase flow systems used for plant transient analysis is dominated by separate-phase models. The corresponding mostly very comprehensive codes (TRAC, RELAP, CATHARE, ATHLET etc.) are looked as to be by far more efficient than a 3 eq. mixture-fluid approach and code also if they show deficiencies in describing flow situations within inner loops as for example the distribution into parallel channels (and thus the simulation of 3D thermal-hydraulic phenomena). This may be justified if comparing them to the very simple 'homogeneous equilibrium models (HEM)', but not if looking to the more refined non-homogeneous 'separate-region' mixture-fluid approaches based on appropriate drift-flux correlation packages which can have, on the contrary, enormous advantages with respect to such separate-phase models. Especially if comparing the basic (and starting) eqs. of such theoretical models of both types the differences are remarkable. Single-phase and mixture-fluid models start from genuine conservation eqs. for mass, energy and momentum, demanding (in case of two-phase flow) additionally an adequate drift flux package (in order to get a relation for a fourth independent variable), a heat transfer coefficients package (over the whole range of the possible fields of application) and correlations for single- and two-phase friction. The other types of models are looking at each phase separately with corresponding 'field' eqs. for each phase, connected by exchange (=closure) terms which substitute the classical constitutive packages for drift, heat transfer and friction. That the drift-flux, heat transfer into a coolant channel and friction along a wall and between the phases is described better by a separate-phase approach is at least doubtful. The corresponding mixture-fluid correlations are based over a wide range on a treasure of experience and measurements, their pseudo-stationary treatment can (due to their small time

Modelling and parameter estimation in reactive continuous mixtures: the catalytic cracking of alkanes - part II

Directory of Open Access Journals (Sweden)

F. C. PEIXOTO

1999-09-01

Full Text Available Fragmentation kinetics is employed to model a continuous reactive mixture of alkanes under catalytic cracking conditions. Standard moment analysis techniques are employed, and a dynamic system for the time evolution of moments of the mixture's dimensionless concentration distribution function (DCDF is found. The time behavior of the DCDF is recovered with successive estimations of scaled gamma distributions using the moments time data.

Methodology for predicting oily mixture properties in the mathematical modeling of molecular distillation

Directory of Open Access Journals (Sweden)

M. F. Gayol

2017-06-01

Full Text Available A methodology for predicting the thermodynamic and transport properties of a multi-component oily mixture, in which the different mixture components are grouped into a small number of pseudo components is shown. This prediction of properties is used in the mathematical modeling of molecular distillation, which consists of a system of differential equations in partial derivatives, according to the principles of the Transport Phenomena and is solved by an implicit finite difference method using a computer code. The mathematical model was validated with experimental data, specifically the molecular distillation of a deodorizer distillate (DD of sunflower oil. The results obtained were satisfactory, with errors less than 10% with respect to the experimental data in a temperature range in which it is possible to apply the proposed method.

Methodology for predicting oily mixture properties in the mathematical modeling of molecular distillation

International Nuclear Information System (INIS)

Gayol, M.F.; Pramparo, M.C.; Miró Erdmann, S.M.

2017-01-01

A methodology for predicting the thermodynamic and transport properties of a multi-component oily mixture, in which the different mixture components are grouped into a small number of pseudo components is shown. This prediction of properties is used in the mathematical modeling of molecular distillation, which consists of a system of differential equations in partial derivatives, according to the principles of the Transport Phenomena and is solved by an implicit finite difference method using a computer code. The mathematical model was validated with experimental data, specifically the molecular distillation of a deodorizer distillate (DD) of sunflower oil. The results obtained were satisfactory, with errors less than 10% with respect to the experimental data in a temperature range in which it is possible to apply the proposed method. [es

The use of an MHV-2 equation of state for modeling the thermodynamic properties of refrigerant mixtures

International Nuclear Information System (INIS)

Morrison, J.D.; Barley, M.H.; Parker, I.B.

1995-01-01

This paper reports on the development and application of a thermodynamic model based on the second-order Modified Huron Vidal equation of state (MHV-2) to predict the properties of ternary mixtures of the refrigerants R32, R125, and R134a. The mixing rules of this equation of state have been used to incorporate directly an activity-coefficient model for the excess Gibbs free energy. The parameters for the activity-coefficient model have been derived from experimental VLE data for binary mixtures. This methodology has enabled the production of a thermodynamically consistent model which can be used to predict the phase equilibria of R32/R125/R134a mixtures. The input data used in the model are presented in the paper and the predictions of the model are compared with available experimental data. The model has been used to predict the behavior of ternary refrigerant blends of R32/R125/R134a in fractionation scenarios, such as liquid charging and vapor leakage, which are of direct interest to the refrigeration industry. Details of these applications and comparisons with experimental data are discussed, along with other general uses of the thermodynamic model

Dirichlet Process Parsimonious Mixtures for clustering

OpenAIRE

Chamroukhi, Faicel; Bartcus, Marius; Glotin, Hervé

2015-01-01

The parsimonious Gaussian mixture models, which exploit an eigenvalue decomposition of the group covariance matrices of the Gaussian mixture, have shown their success in particular in cluster analysis. Their estimation is in general performed by maximum likelihood estimation and has also been considered from a parametric Bayesian prospective. We propose new Dirichlet Process Parsimonious mixtures (DPPM) which represent a Bayesian nonparametric formulation of these parsimonious Gaussian mixtur...

N-mix for fish: estimating riverine salmonid habitat selection via N-mixture models

Science.gov (United States)

Som, Nicholas A.; Perry, Russell W.; Jones, Edward C.; De Juilio, Kyle; Petros, Paul; Pinnix, William D.; Rupert, Derek L.

2018-01-01

Models that formulate mathematical linkages between fish use and habitat characteristics are applied for many purposes. For riverine fish, these linkages are often cast as resource selection functions with variables including depth and velocity of water and distance to nearest cover. Ecologists are now recognizing the role that detection plays in observing organisms, and failure to account for imperfect detection can lead to spurious inference. Herein, we present a flexible N-mixture model to associate habitat characteristics with the abundance of riverine salmonids that simultaneously estimates detection probability. Our formulation has the added benefits of accounting for demographics variation and can generate probabilistic statements regarding intensity of habitat use. In addition to the conceptual benefits, model application to data from the Trinity River, California, yields interesting results. Detection was estimated to vary among surveyors, but there was little spatial or temporal variation. Additionally, a weaker effect of water depth on resource selection is estimated than that reported by previous studies not accounting for detection probability. N-mixture models show great promise for applications to riverine resource selection.

Multivariate spatial Gaussian mixture modeling for statistical clustering of hemodynamic parameters in functional MRI

International Nuclear Information System (INIS)

Fouque, A.L.; Ciuciu, Ph.; Risser, L.; Fouque, A.L.; Ciuciu, Ph.; Risser, L.

2009-01-01

In this paper, a novel statistical parcellation of intra-subject functional MRI (fMRI) data is proposed. The key idea is to identify functionally homogenous regions of interest from their hemodynamic parameters. To this end, a non-parametric voxel-based estimation of hemodynamic response function is performed as a prerequisite. Then, the extracted hemodynamic features are entered as the input data of a Multivariate Spatial Gaussian Mixture Model (MSGMM) to be fitted. The goal of the spatial aspect is to favor the recovery of connected components in the mixture. Our statistical clustering approach is original in the sense that it extends existing works done on univariate spatially regularized Gaussian mixtures. A specific Gibbs sampler is derived to account for different covariance structures in the feature space. On realistic artificial fMRI datasets, it is shown that our algorithm is helpful for identifying a parsimonious functional parcellation required in the context of joint detection estimation of brain activity. This allows us to overcome the classical assumption of spatial stationarity of the BOLD signal model. (authors)

Bayesian Non-Parametric Mixtures of GARCH(1,1 Models

Directory of Open Access Journals (Sweden)

John W. Lau

2012-01-01

Full Text Available Traditional GARCH models describe volatility levels that evolve smoothly over time, generated by a single GARCH regime. However, nonstationary time series data may exhibit abrupt changes in volatility, suggesting changes in the underlying GARCH regimes. Further, the number and times of regime changes are not always obvious. This article outlines a nonparametric mixture of GARCH models that is able to estimate the number and time of volatility regime changes by mixing over the Poisson-Kingman process. The process is a generalisation of the Dirichlet process typically used in nonparametric models for time-dependent data provides a richer clustering structure, and its application to time series data is novel. Inference is Bayesian, and a Markov chain Monte Carlo algorithm to explore the posterior distribution is described. The methodology is illustrated on the Standard and Poor's 500 financial index.

Modeling of Video Sequences by Gaussian Mixture: Application in Motion Estimation by Block Matching Method

Directory of Open Access Journals (Sweden)

Abdenaceur Boudlal

2010-01-01

Full Text Available This article investigates a new method of motion estimation based on block matching criterion through the modeling of image blocks by a mixture of two and three Gaussian distributions. Mixture parameters (weights, means vectors, and covariance matrices are estimated by the Expectation Maximization algorithm (EM which maximizes the log-likelihood criterion. The similarity between a block in the current image and the more resembling one in a search window on the reference image is measured by the minimization of Extended Mahalanobis distance between the clusters of mixture. Performed experiments on sequences of real images have given good results, and PSNR reached 3 dB.

Study of normal and shear material properties for viscoelastic model of asphalt mixture by discrete element method

DEFF Research Database (Denmark)

Feng, Huan; Pettinari, Matteo; Stang, Henrik

2015-01-01

In this paper, the viscoelastic behavior of asphalt mixture was studied by using discrete element method. The dynamic properties of asphalt mixture were captured by implementing Burger’s contact model. Different ways of taking into account of the normal and shear material properties of asphalt mi...

Mathematical Modeling and Evaluation of Human Motions in Physical Therapy Using Mixture Density Neural Networks.

Science.gov (United States)

Vakanski, A; Ferguson, J M; Lee, S

2016-12-01

The objective of the proposed research is to develop a methodology for modeling and evaluation of human motions, which will potentially benefit patients undertaking a physical rehabilitation therapy (e.g., following a stroke or due to other medical conditions). The ultimate aim is to allow patients to perform home-based rehabilitation exercises using a sensory system for capturing the motions, where an algorithm will retrieve the trajectories of a patient's exercises, will perform data analysis by comparing the performed motions to a reference model of prescribed motions, and will send the analysis results to the patient's physician with recommendations for improvement. The modeling approach employs an artificial neural network, consisting of layers of recurrent neuron units and layers of neuron units for estimating a mixture density function over the spatio-temporal dependencies within the human motion sequences. Input data are sequences of motions related to a prescribed exercise by a physiotherapist to a patient, and recorded with a motion capture system. An autoencoder subnet is employed for reducing the dimensionality of captured sequences of human motions, complemented with a mixture density subnet for probabilistic modeling of the motion data using a mixture of Gaussian distributions. The proposed neural network architecture produced a model for sets of human motions represented with a mixture of Gaussian density functions. The mean log-likelihood of observed sequences was employed as a performance metric in evaluating the consistency of a subject's performance relative to the reference dataset of motions. A publically available dataset of human motions captured with Microsoft Kinect was used for validation of the proposed method. The article presents a novel approach for modeling and evaluation of human motions with a potential application in home-based physical therapy and rehabilitation. The described approach employs the recent progress in the field of

Gaussian Process-Mixture Conditional Heteroscedasticity.

Science.gov (United States)

Platanios, Emmanouil A; Chatzis, Sotirios P

2014-05-01

Generalized autoregressive conditional heteroscedasticity (GARCH) models have long been considered as one of the most successful families of approaches for volatility modeling in financial return series. In this paper, we propose an alternative approach based on methodologies widely used in the field of statistical machine learning. Specifically, we propose a novel nonparametric Bayesian mixture of Gaussian process regression models, each component of which models the noise variance process that contaminates the observed data as a separate latent Gaussian process driven by the observed data. This way, we essentially obtain a Gaussian process-mixture conditional heteroscedasticity (GPMCH) model for volatility modeling in financial return series. We impose a nonparametric prior with power-law nature over the distribution of the model mixture components, namely the Pitman-Yor process prior, to allow for better capturing modeled data distributions with heavy tails and skewness. Finally, we provide a copula-based approach for obtaining a predictive posterior for the covariances over the asset returns modeled by means of a postulated GPMCH model. We evaluate the efficacy of our approach in a number of benchmark scenarios, and compare its performance to state-of-the-art methodologies.

Mixtures of skewed Kalman filters

KAUST Repository

Kim, Hyoungmoon; Ryu, Duchwan; Mallick, Bani K.; Genton, Marc G.

2014-01-01

Normal state-space models are prevalent, but to increase the applicability of the Kalman filter, we propose mixtures of skewed, and extended skewed, Kalman filters. To do so, the closed skew-normal distribution is extended to a scale mixture class

A thermodynamically consistent model for granular-fluid mixtures considering pore pressure evolution and hypoplastic behavior

Science.gov (United States)

Hess, Julian; Wang, Yongqi

2016-11-01

A new mixture model for granular-fluid flows, which is thermodynamically consistent with the entropy principle, is presented. The extra pore pressure described by a pressure diffusion equation and the hypoplastic material behavior obeying a transport equation are taken into account. The model is applied to granular-fluid flows, using a closing assumption in conjunction with the dynamic fluid pressure to describe the pressure-like residual unknowns, hereby overcoming previous uncertainties in the modeling process. Besides the thermodynamically consistent modeling, numerical simulations are carried out and demonstrate physically reasonable results, including simple shear flow in order to investigate the vertical distribution of the physical quantities, and a mixture flow down an inclined plane by means of the depth-integrated model. Results presented give insight in the ability of the deduced model to capture the key characteristics of granular-fluid flows. We acknowledge the support of the Deutsche Forschungsgemeinschaft (DFG) for this work within the Project Number WA 2610/3-1.

A constrained Metropolis-Hastings search for EMRIs in the Mock LISA Data Challenge 1B

International Nuclear Information System (INIS)

Gair, Jonathan R; Porter, Edward; Babak, Stanislav; Barack, Leor

2008-01-01

We describe a search for the extreme-mass-ratio inspiral sources in the Round 1B Mock LISA Data Challenge data sets. The search algorithm is a Monte Carlo search based on the Metropolis-Hastings algorithm, but also incorporates simulated, thermostated and time annealing, plus a harmonic identification stage designed to reduce the chance of the chain locking onto secondary maxima. In this paper, we focus on describing the algorithm that we have been developing. We give the results of the search of the Round 1B data, although parameter recovery has improved since that deadline. Finally, we describe several modifications to the search pipeline that we are currently investigating for incorporation in future searches

Measurement and modelling of hydrogen bonding in 1-alkanol plus n-alkane binary mixtures

DEFF Research Database (Denmark)

von Solms, Nicolas; Jensen, Lars; Kofod, Jonas L.

2007-01-01

Two equations of state (simplified PC-SAFT and CPA) are used to predict the monomer fraction of 1-alkanols in binary mixtures with n-alkanes. It is found that the choice of parameters and association schemes significantly affects the ability of a model to predict hydrogen bonding in mixtures, eve...... studies, which is clarified in the present work. New hydrogen bonding data based on infrared spectroscopy are reported for seven binary mixtures of alcohols and alkanes. (C) 2007 Elsevier B.V. All rights reserved....... though pure-component liquid densities and vapour pressures are predicted equally accurately for the associating compound. As was the case in the study of pure components, there exists some confusion in the literature about the correct interpretation and comparison of experimental data and theoretical...

On Partial Defaults in Portfolio Credit Risk : A Poisson Mixture Model Approach

OpenAIRE

Weißbach, Rafael; von Lieres und Wilkau, Carsten

2005-01-01

Most credit portfolio models exclusively calculate the loss distribution for a portfolio of performing counterparts. Conservative default definitions cause considerable insecurity about the loss for a long time after the default. We present three approaches to account for defaulted counterparts in the calculation of the economic capital. Two of the approaches are based on the Poisson mixture model CreditRisk+ and derive a loss distribution for an integrated portfolio. The third method treats ...

Modelling phase equilibria for acid gas mixtures using the CPA equation of state. Part VI. Multicomponent mixtures with glycols relevant to oil and gas and to liquid or supercritical CO_2 transport applications

International Nuclear Information System (INIS)

Tsivintzelis, Ioannis; Kontogeorgis, Georgios M.

2016-01-01

Highlights: • CPA EoS was applied to predict the phase behaviour of multicomponent mixtures containing CO_2, glycols, water and alkanes. • Mixtures relevant to oil and gas, CO_2 capture and liquid or supercritical CO_2 transport applications were investigated. • Results are presented using various modelling approaches/association schemes. • The predicting ability of the model was evaluated against experimental data. • Conclusions for the best modelling approach are drawn. - Abstract: In this work the Cubic Plus Association (CPA) equation of state is applied to multicomponent mixtures containing CO_2 with alkanes, water, and glycols. Various modelling approaches are used i.e. different association schemes for pure CO_2 (assuming that it is a non-associating compound, or that it is a self-associating fluid with two, three or four association sites) and different possibilities for modelling mixtures of CO_2 with other hydrogen bonding fluids (only use of one interaction parameter k_i_j or assuming cross association interactions and obtaining the relevant parameters either via a combining rule or using an experimental value for the cross association energy). Initially, new binary interaction parameters were estimated for (CO_2 + glycol) binary mixtures. Having the binary parameters from the binary systems, the model was applied in a predictive way (i.e. no parameters were adjusted to data on ternary and multicomponent mixtures) to model the phase behaviour of ternary and quaternary systems with CO_2 and glycols. It is concluded that CPA performs satisfactorily for most multicomponent systems considered. Some differences between the various modelling approaches are observed. This work is the last part of a series of studies, which aim to arrive in a single “engineering approach” for applying CPA to acid gas mixtures, without introducing significant changes to the model. An overall assessment, based also on the obtained results of this series (Tsivintzelis

Spatial patterns monitoring of road traffic injuries in Karachi metropolis.

Science.gov (United States)

Lateef, Muhammad U

2011-06-01

This article aims to assess the pattern of road traffic injuries (RTIs) and fatalities in Karachi metropolis. Assessing the pattern of RTIs in Karachi at this juncture is important for many reasons. The rapid motorisation in the recent years due to the availability of credit has significantly increased the traffic volume of the city. Since then, the roads of Karachi have continuously developed at a rapid pace. This development has come with a high human loss, because the construction of multilevel flyovers, signal-free corridors and the resulting high-speed traffic ultimately increase the severity of injuries. The reasons for this high proportion are inadequate infrastructure, poor enforcement of safety regulations, high crash severity index and greater population of vulnerable road user groups (riders and pedestrians). This research is the first of its kind in the country to have a geocoded database of fatalities and injuries in a geographical information system for the entire city of Karachi. In fact, road crashes are both predictable and preventable. Developing countries should learn from the experience of highly motorised nations to avoid the high burden of RTIs by adopting road safety and prevention measures.

Determinant of flexible Parametric Estimation of Mixture Cure ...

African Journals Online (AJOL)

PROF. OLIVER OSUAGWA

2015-12-01

Dec 1, 2015 ... Suitability of four parametric mixture cure models were considered namely; Log .... regression analysis which relies on the ... The parameter of mixture cure fraction model was ..... Stochastic Models of Tumor Latency and Their.

Accounting for misclassification in electronic health records-derived exposures using generalized linear finite mixture models.

Science.gov (United States)

Hubbard, Rebecca A; Johnson, Eric; Chubak, Jessica; Wernli, Karen J; Kamineni, Aruna; Bogart, Andy; Rutter, Carolyn M

2017-06-01

Exposures derived from electronic health records (EHR) may be misclassified, leading to biased estimates of their association with outcomes of interest. An example of this problem arises in the context of cancer screening where test indication, the purpose for which a test was performed, is often unavailable. This poses a challenge to understanding the effectiveness of screening tests because estimates of screening test effectiveness are biased if some diagnostic tests are misclassified as screening. Prediction models have been developed for a variety of exposure variables that can be derived from EHR, but no previous research has investigated appropriate methods for obtaining unbiased association estimates using these predicted probabilities. The full likelihood incorporating information on both the predicted probability of exposure-class membership and the association between the exposure and outcome of interest can be expressed using a finite mixture model. When the regression model of interest is a generalized linear model (GLM), the expectation-maximization algorithm can be used to estimate the parameters using standard software for GLMs. Using simulation studies, we compared the bias and efficiency of this mixture model approach to alternative approaches including multiple imputation and dichotomization of the predicted probabilities to create a proxy for the missing predictor. The mixture model was the only approach that was unbiased across all scenarios investigated. Finally, we explored the performance of these alternatives in a study of colorectal cancer screening with colonoscopy. These findings have broad applicability in studies using EHR data where gold-standard exposures are unavailable and prediction models have been developed for estimating proxies.

Microstructure and hydrogen bonding in water-acetonitrile mixtures.

Science.gov (United States)

Mountain, Raymond D

2010-12-16

The connection of hydrogen bonding between water and acetonitrile in determining the microheterogeneity of the liquid mixture is examined using NPT molecular dynamics simulations. Mixtures for six, rigid, three-site models for acetonitrile and one water model (SPC/E) were simulated to determine the amount of water-acetonitrile hydrogen bonding. Only one of the six acetonitrile models (TraPPE-UA) was able to reproduce both the liquid density and the experimental estimates of hydrogen bonding derived from Raman scattering of the CN stretch band or from NMR quadrupole relaxation measurements. A simple modification of the acetonitrile model parameters for the models that provided poor estimates produced hydrogen-bonding results consistent with experiments for two of the models. Of these, only one of the modified models also accurately determined the density of the mixtures. The self-diffusion coefficient of liquid acetonitrile provided a final winnowing of the modified model and the successful, unmodified model. The unmodified model is provisionally recommended for simulations of water-acetonitrile mixtures.

Examining the cost efficiency of Chinese hydroelectric companies using a finite mixture model

International Nuclear Information System (INIS)

Barros, Carlos Pestana; Chen, Zhongfei; Managi, Shunsuke; Antunes, Olinda Sequeira

2013-01-01

This paper evaluates the operational activities of Chinese hydroelectric power companies over the period 2000–2010 using a finite mixture model that controls for unobserved heterogeneity. In so doing, a stochastic frontier latent class model, which allows for the existence of different technologies, is adopted to estimate cost frontiers. This procedure not only enables us to identify different groups among the hydro-power companies analysed, but also permits the analysis of their cost efficiency. The main result is that three groups are identified in the sample, each equipped with different technologies, suggesting that distinct business strategies need to be adapted to the characteristics of China's hydro-power companies. Some managerial implications are developed. - Highlights: ► This paper evaluates the operational activities of Chinese electricity hydric companies. ► This study uses data from 2000 to 2010 using a finite mixture model. ► The model procedure identifies different groups of Chinese hydric companies analysed. ► Three groups are identified in the sample, each equipped with completely different “technologies”. ► This suggests that distinct business strategies need to be adapted to the characteristics of the hydric companies

Multi-temperature mixture of fluids

Directory of Open Access Journals (Sweden)

Ruggeri Tommaso

2009-01-01

Full Text Available We present a survey on some recent results concerning the different models of a mixture of compressible fluids. In particular we discuss the most realistic case of a mixture when each constituent has its own temperature (MT and we first compare the solutions of this model with the one with a unique common temperature (ST . In the case of Eulerian fluids it will be shown that the corresponding (ST differential system is a principal subsystem of the (MT one. Global behavior of smooth solutions for large time for both systems will also be discussed through the application of the Shizuta-Kawashima condition. Then we introduce the concept of the average temperature of mixture based upon the consideration that the internal energy of the mixture is the same as in the case of a single-temperature mixture. As a consequence, it is shown that the entropy of the mixture reaches a local maximum in equilibrium. Through the procedure of Maxwellian iteration a new constitutive equation for non-equilibrium temperatures of constituents is obtained in a classical limit, together with the Fick's law for the diffusion flux. Finally, to justify the Maxwellian iteration, we present for dissipative fluids a possible approach of a classical theory of mixture with multi-temperature and we prove that the differences of temperatures between the constituents imply the existence of a new dynamical pressure even if the fluids have a zero bulk viscosity.

Bayesian Kernel Mixtures for Counts.

Science.gov (United States)

Canale, Antonio; Dunson, David B

2011-12-01

Although Bayesian nonparametric mixture models for continuous data are well developed, there is a limited literature on related approaches for count data. A common strategy is to use a mixture of Poissons, which unfortunately is quite restrictive in not accounting for distributions having variance less than the mean. Other approaches include mixing multinomials, which requires finite support, and using a Dirichlet process prior with a Poisson base measure, which does not allow smooth deviations from the Poisson. As a broad class of alternative models, we propose to use nonparametric mixtures of rounded continuous kernels. An efficient Gibbs sampler is developed for posterior computation, and a simulation study is performed to assess performance. Focusing on the rounded Gaussian case, we generalize the modeling framework to account for multivariate count data, joint modeling with continuous and categorical variables, and other complications. The methods are illustrated through applications to a developmental toxicity study and marketing data. This article has supplementary material online.

Mapping quantitative trait loci in a selectively genotyped outbred population using a mixture model approach

NARCIS (Netherlands)

Johnson, David L.; Jansen, Ritsert C.; Arendonk, Johan A.M. van

1999-01-01

A mixture model approach is employed for the mapping of quantitative trait loci (QTL) for the situation where individuals, in an outbred population, are selectively genotyped. Maximum likelihood estimation of model parameters is obtained from an Expectation-Maximization (EM) algorithm facilitated by

An Odor Interaction Model of Binary Odorant Mixtures by a Partial Differential Equation Method

Directory of Open Access Journals (Sweden)

Luchun Yan

2014-07-01

Full Text Available A novel odor interaction model was proposed for binary mixtures of benzene and substituted benzenes by a partial differential equation (PDE method. Based on the measurement method (tangent-intercept method of partial molar volume, original parameters of corresponding formulas were reasonably displaced by perceptual measures. By these substitutions, it was possible to relate a mixture’s odor intensity to the individual odorant’s relative odor activity value (OAV. Several binary mixtures of benzene and substituted benzenes were respectively tested to establish the PDE models. The obtained results showed that the PDE model provided an easily interpretable method relating individual components to their joint odor intensity. Besides, both predictive performance and feasibility of the PDE model were proved well through a series of odor intensity matching tests. If combining the PDE model with portable gas detectors or on-line monitoring systems, olfactory evaluation of odor intensity will be achieved by instruments instead of odor assessors. Many disadvantages (e.g., expense on a fixed number of odor assessors also will be successfully avoided. Thus, the PDE model is predicted to be helpful to the monitoring and management of odor pollutions.

The STIRPAT Analysis on Carbon Emission in Chinese Cities: An Asymmetric Laplace Distribution Mixture Model

Directory of Open Access Journals (Sweden)

Shanshan Wang

2017-12-01

Full Text Available In cities’ policy-making, it is a hot issue to grasp the determinants of carbon dioxide emission in Chinese cities. And the common method is to use the STIRPAT model, where its coefficients represent the influence intensity of each determinants of carbon emission. However, less work discusses estimation accuracy, especially in the framework of non-normal distribution and heterogeneity among cities’ emission. To improve the estimation accuracy, this paper employs a new method to estimate the STIRPAT model. The method uses a mixture of Asymmetric Laplace distributions (ALDs to approximate the true distribution of the error term. Meantime, a designed two-layer EM algorithm is used to obtain estimators. We test the robustness via the comparison results of five different models. We find that the ALDs Mixture Model is more reliable the others. Further, a significant Kuznets curve relationship is identified in China.

Partitioning detectability components in populations subject to within-season temporary emigration using binomial mixture models.

Directory of Open Access Journals (Sweden)

Katherine M O'Donnell

Full Text Available Detectability of individual animals is highly variable and nearly always < 1; imperfect detection must be accounted for to reliably estimate population sizes and trends. Hierarchical models can simultaneously estimate abundance and effective detection probability, but there are several different mechanisms that cause variation in detectability. Neglecting temporary emigration can lead to biased population estimates because availability and conditional detection probability are confounded. In this study, we extend previous hierarchical binomial mixture models to account for multiple sources of variation in detectability. The state process of the hierarchical model describes ecological mechanisms that generate spatial and temporal patterns in abundance, while the observation model accounts for the imperfect nature of counting individuals due to temporary emigration and false absences. We illustrate our model's potential advantages, including the allowance of temporary emigration between sampling periods, with a case study of southern red-backed salamanders Plethodon serratus. We fit our model and a standard binomial mixture model to counts of terrestrial salamanders surveyed at 40 sites during 3-5 surveys each spring and fall 2010-2012. Our models generated similar parameter estimates to standard binomial mixture models. Aspect was the best predictor of salamander abundance in our case study; abundance increased as aspect became more northeasterly. Increased time-since-rainfall strongly decreased salamander surface activity (i.e. availability for sampling, while higher amounts of woody cover objects and rocks increased conditional detection probability (i.e. probability of capture, given an animal is exposed to sampling. By explicitly accounting for both components of detectability, we increased congruence between our statistical modeling and our ecological understanding of the system. We stress the importance of choosing survey locations and

Application of fuzzy logic to determine the odour intensity of model gas mixtures using electronic nose

Science.gov (United States)

Szulczyński, Bartosz; Gębicki, Jacek; Namieśnik, Jacek

2018-01-01

The paper presents the possibility of application of fuzzy logic to determine the odour intensity of model, ternary gas mixtures (α-pinene, toluene and triethylamine) using electronic nose prototype. The results obtained using fuzzy logic algorithms were compared with the values obtained using multiple linear regression (MLR) model and sensory analysis. As the results of the studies, it was found the electronic nose prototype along with the fuzzy logic pattern recognition system can be successfully used to estimate the odour intensity of tested gas mixtures. The correctness of the results obtained using fuzzy logic was equal to 68%.

Mixtures of endocrine disrupting contaminants modelled on human high end exposures

DEFF Research Database (Denmark)

Christiansen, Sofie; Kortenkamp, A.; Petersen, Marta Axelstad

2012-01-01

exceeding 1 is expected to lead to effects in the rat, a total dose more than 62 times higher than human exposures should lead to responses. Considering the high uncertainty of this estimate, experience on lowest‐observed‐adverse‐effect‐level (LOAEL)/NOAEL ratios and statistical power of rat studies, we...... expected that combined doses 150 times higher than high end human intake estimates should give no, or only borderline effects, whereas doses 450 times higher should produce significant responses. Experiments indeed showed clear developmental toxicity of the 450‐fold dose in terms of increased nipple...... though each individual chemical is present at low, ineffective doses, but the effects of mixtures modelled based on human intakes have not previously been investigated. To address this issue for the first time, we selected 13 chemicals for a developmental mixture toxicity study in rats where data about...

Modelling interactions in grass-clover mixtures

NARCIS (Netherlands)

Nassiri Mahallati, M.

1998-01-01

The study described in this thesis focuses on a quantitative understanding of the complex interactions in binary mixtures of perennial ryegrass (Lolium perenne L.) and white clover (Trifolium repens L.) under cutting. The first part of the study describes the dynamics of growth, production

Thermodynamic modeling of CO2 mixtures

DEFF Research Database (Denmark)

Bjørner, Martin Gamel

Knowledge of the thermodynamic properties and phase equilibria of mixtures containing carbon dioxide (CO2) is important in several industrial processes such as enhanced oil recovery, carbon capture and storage, and supercritical extractions, where CO2 is used as a solvent. Despite this importance...

Measurement and correlation of critical properties for binary mixtures and ternary mixtures containing gasoline additives

International Nuclear Information System (INIS)

Wang, Lipu; Han, Kewei; Xia, Shuqian; Ma, Peisheng; Yan, Fangyou

2014-01-01

Highlights: • A high-pressure view cell was used to measure the critical properties of mixtures. • Three binary mixtures’ and three ternary mixtures’ critical properties were reported. • The experimental data of each system covered the whole mole fraction range. • The critical properties of the ternary mixtures were predicted with the PR–WS model. • Empirical equations were used to correlate the experimental results. - Abstract: The critical properties of three binary mixtures and three ternary mixtures containing gasoline additives (including methanol + 1-propanol, heptane + ethanol, heptane + 1-propanol, methanol + 1-propanol + heptane, methanol + 1-propanol + methyl tert-butyl ether (MTBE), and ethanol + heptane + MTBE) were determined by a high-pressure cell. All the critical lines of binary mixtures belong to the type I described by Scott and van Konynenburg. The system of methanol + 1-propanol showed little non-ideal behavior due to their similar molecular structures. The heptane + ethanol and heptane + 1-propanol systems showed visible non-ideal behavior for their great differences in molecular structure. The Peng–Robinson equation of state combined with the Wong–Sandler mixing rule (PR–WS) was applied to correlate the critical properties of binary mixtures. The critical points of the three ternary mixtures were predicted by the PR–WS model with the binary interaction parameters using the procedure proposed by Heidemann and Khalil. The predicted critical temperatures were in good agreement with the experimental values, while the predicted critical pressures differed from the measured values. The experimental values of binary mixtures were fitted well with the Redlich–Kister equation. The critical properties of ternary mixtures were correlated with the Cibulka’s equation, and the critical surfaces were plotted using the Cibulka’s equations

Regional SAR Image Segmentation Based on Fuzzy Clustering with Gamma Mixture Model

Science.gov (United States)

Li, X. L.; Zhao, Q. H.; Li, Y.

2017-09-01

Most of stochastic based fuzzy clustering algorithms are pixel-based, which can not effectively overcome the inherent speckle noise in SAR images. In order to deal with the problem, a regional SAR image segmentation algorithm based on fuzzy clustering with Gamma mixture model is proposed in this paper. First, initialize some generating points randomly on the image, the image domain is divided into many sub-regions using Voronoi tessellation technique. Each sub-region is regarded as a homogeneous area in which the pixels share the same cluster label. Then, assume the probability of the pixel to be a Gamma mixture model with the parameters respecting to the cluster which the pixel belongs to. The negative logarithm of the probability represents the dissimilarity measure between the pixel and the cluster. The regional dissimilarity measure of one sub-region is defined as the sum of the measures of pixels in the region. Furthermore, the Markov Random Field (MRF) model is extended from pixels level to Voronoi sub-regions, and then the regional objective function is established under the framework of fuzzy clustering. The optimal segmentation results can be obtained by the solution of model parameters and generating points. Finally, the effectiveness of the proposed algorithm can be proved by the qualitative and quantitative analysis from the segmentation results of the simulated and real SAR images.

Shear viscosity of liquid mixtures: Mass dependence

International Nuclear Information System (INIS)

Kaushal, Rohan; Tankeshwar, K.

2002-06-01

Expressions for zeroth, second, and fourth sum rules of transverse stress autocorrelation function of two component fluid have been derived. These sum rules and Mori's memory function formalism have been used to study shear viscosity of Ar-Kr and isotopic mixtures. It has been found that theoretical result is in good agreement with the computer simulation result for the Ar-Kr mixture. The mass dependence of shear viscosity for different mole fraction shows that deviation from ideal linear model comes even from mass difference in two species of fluid mixture. At higher mass ratio shear viscosity of mixture is not explained by any of the emperical model. (author)

Shear viscosity of liquid mixtures Mass dependence

CERN Document Server

Kaushal, R

2002-01-01

Expressions for zeroth, second, and fourth sum rules of transverse stress autocorrelation function of two component fluid have been derived. These sum rules and Mori's memory function formalism have been used to study shear viscosity of Ar-Kr and isotopic mixtures. It has been found that theoretical result is in good agreement with the computer simulation result for the Ar-Kr mixture. The mass dependence of shear viscosity for different mole fraction shows that deviation from ideal linear model comes even from mass difference in two species of fluid mixture. At higher mass ratio shear viscosity of mixture is not explained by any of the emperical model.

A mixture model for robust point matching under multi-layer motion.

Directory of Open Access Journals (Sweden)

Jiayi Ma

Full Text Available This paper proposes an efficient mixture model for establishing robust point correspondences between two sets of points under multi-layer motion. Our algorithm starts by creating a set of putative correspondences which can contain a number of false correspondences, or outliers, in addition to the true correspondences (inliers. Next we solve for correspondence by interpolating a set of spatial transformations on the putative correspondence set based on a mixture model, which involves estimating a consensus of inlier points whose matching follows a non-parametric geometrical constraint. We formulate this as a maximum a posteriori (MAP estimation of a Bayesian model with hidden/latent variables indicating whether matches in the putative set are outliers or inliers. We impose non-parametric geometrical constraints on the correspondence, as a prior distribution, in a reproducing kernel Hilbert space (RKHS. MAP estimation is performed by the EM algorithm which by also estimating the variance of the prior model (initialized to a large value is able to obtain good estimates very quickly (e.g., avoiding many of the local minima inherent in this formulation. We further provide a fast implementation based on sparse approximation which can achieve a significant speed-up without much performance degradation. We illustrate the proposed method on 2D and 3D real images for sparse feature correspondence, as well as a public available dataset for shape matching. The quantitative results demonstrate that our method is robust to non-rigid deformation and multi-layer/large discontinuous motion.

Toxicology of Chemical Mixtures: A Review of Mixtures Assessment

National Research Council Canada - National Science Library

Bjarnason, Stephen

2004-01-01

.... Recent advances in disciplines such as genomics, proteomics, metabonomics and physiologically-based pharmacokinetic modeling should assist in the hazard assessment of complex chemical mixtures. However, the process of regulatory assessment of these types of exposures will remain both complex and difficult.

Process Dissociation and Mixture Signal Detection Theory

Science.gov (United States)

DeCarlo, Lawrence T.

2008-01-01

The process dissociation procedure was developed in an attempt to separate different processes involved in memory tasks. The procedure naturally lends itself to a formulation within a class of mixture signal detection models. The dual process model is shown to be a special case. The mixture signal detection model is applied to data from a widely…

Mapping behavioral landscapes for animal movement: a finite mixture modeling approach

Science.gov (United States)

Tracey, Jeff A.; Zhu, Jun; Boydston, Erin E.; Lyren, Lisa M.; Fisher, Robert N.; Crooks, Kevin R.

2013-01-01

Because of its role in many ecological processes, movement of animals in response to landscape features is an important subject in ecology and conservation biology. In this paper, we develop models of animal movement in relation to objects or fields in a landscape. We take a finite mixture modeling approach in which the component densities are conceptually related to different choices for movement in response to a landscape feature, and the mixing proportions are related to the probability of selecting each response as a function of one or more covariates. We combine particle swarm optimization and an Expectation-Maximization (EM) algorithm to obtain maximum likelihood estimates of the model parameters. We use this approach to analyze data for movement of three bobcats in relation to urban areas in southern California, USA. A behavioral interpretation of the models revealed similarities and differences in bobcat movement response to urbanization. All three bobcats avoided urbanization by moving either parallel to urban boundaries or toward less urban areas as the proportion of urban land cover in the surrounding area increased. However, one bobcat, a male with a dispersal-like large-scale movement pattern, avoided urbanization at lower densities and responded strictly by moving parallel to the urban edge. The other two bobcats, which were both residents and occupied similar geographic areas, avoided urban areas using a combination of movements parallel to the urban edge and movement toward areas of less urbanization. However, the resident female appeared to exhibit greater repulsion at lower levels of urbanization than the resident male, consistent with empirical observations of bobcats in southern California. Using the parameterized finite mixture models, we mapped behavioral states to geographic space, creating a representation of a behavioral landscape. This approach can provide guidance for conservation planning based on analysis of animal movement data using

Properties of Direct Coal Liquefaction Residue Modified Asphalt Mixture

Directory of Open Access Journals (Sweden)

Jie Ji

2017-01-01

Full Text Available The objectives of this paper are to use Direct Coal Liquefaction Residue (DLCR to modify the asphalt binders and mixtures and to evaluate the performance of modified asphalt mixtures. The dynamic modulus and phase angle of DCLR and DCLR-composite modified asphalt mixture were analyzed, and the viscoelastic properties of these modified asphalt mixtures were compared to the base asphalt binder SK-90 and Styrene-Butadiene-Styrene (SBS modified asphalt mixtures. The master curves of the asphalt mixtures were shown, and dynamic and viscoelastic behaviors of asphalt mixtures were described using the Christensen-Anderson-Marasteanu (CAM model. The test results show that the dynamic moduli of DCLR and DCLR-composite asphalt mixtures are higher than those of the SK-90 and SBS modified asphalt mixtures. Based on the viscoelastic parameters of CAM models of the asphalt mixtures, the high- and low-temperature performance of DLCR and DCLR-composite modified asphalt mixtures are obviously better than the SK-90 and SBS modified asphalt mixtures. In addition, the DCLR and DCLR-composite modified asphalt mixtures are more insensitive to the frequency compared to SK-90 and SBS modified asphalt mixtures.

Discrete Element Method Modeling of the Rheological Properties of Coke/Pitch Mixtures

OpenAIRE

Majidi, Behzad; Taghavi, Seyed Mohammad; Fafard, Mario; Ziegler, Donald P.; Alamdari, Houshang

2016-01-01

Rheological properties of pitch and pitch/coke mixtures at temperatures around 150 °C are of great interest for the carbon anode manufacturing process in the aluminum industry. In the present work, a cohesive viscoelastic contact model based on Burger’s model is developed using the discrete element method (DEM) on the YADE, the open-source DEM software. A dynamic shear rheometer (DSR) is used to measure the viscoelastic properties of pitch at 150 °C. The experimental data obtained is then use...

Determinants of knowledge and use of psychoactive substance among commercial motorcyclist in Sokoto metropolis, Northwest Nigeria

Directory of Open Access Journals (Sweden)

M.O.Raji

2017-01-01

Full Text Available Background Substance abuse, also known as drug abuse, is a patterned use of a drug in which the user consumes the substance in amounts or with methods which are harmful to themselves or others, and is a form of substance related disorder. Riding commercial motorcycle entails lot of risk, compounded by abuse of drugs, the scenario can only be worse. This study aimed to assess the determinants of knowledge and use of psychoactive substances among commercial motorcyclist in Sokoto metropolis. Methods The study was a cross sectional descriptive study conducted in Sokoto metropolis, among Commercial motorcyclist, 253 respondents were recruited using multi stage sampling technique. Data was obtained using interviewer administered structured questionnaire containing 47‐item structured questions. Data was analysed using IBM statistical software package version 21, 5% was set as level of significance Result Majority of respondent believed that use of alcohol 214 (84.6, cannabis 147 (58.1 and codeine 171 (67.6 can lead to mental problems. Thirty percent of the respondents reported ever use of psychoactive substances. Most of the respondents (49.3% initiated use of Psychoactive substances between 16‐20 years of age. Respondents who had some formal education had less odds of ever using psychoactive substances (p=0.001, OR= 0.337. Respondents who had ever encouraged fellow commercial motorcyclist to use psychoactive substances had 22 times odds of ever having used psychoactive substances (p=0.000 Conclusion Substance abuse is prevalent among commercial motorcyclist. Despite good knowledge of psychoactive substances and the consequences associated with it, the use was still relatively high. The main predictor of ever use of psychoactive substances was willingness to be friends with someone who use psychoactive substance. There is need for continuous counselling and education of commercial motorcyclist, by road safety workers, on the dangers associated

Using dynamic N-mixture models to test cavity limitation on northern flying squirrel demographic parameters using experimental nest box supplementation.

Science.gov (United States)

Priol, Pauline; Mazerolle, Marc J; Imbeau, Louis; Drapeau, Pierre; Trudeau, Caroline; Ramière, Jessica

2014-06-01

Dynamic N-mixture models have been recently developed to estimate demographic parameters of unmarked individuals while accounting for imperfect detection. We propose an application of the Dail and Madsen (2011: Biometrics, 67, 577-587) dynamic N-mixture model in a manipulative experiment using a before-after control-impact design (BACI). Specifically, we tested the hypothesis of cavity limitation of a cavity specialist species, the northern flying squirrel, using nest box supplementation on half of 56 trapping sites. Our main purpose was to evaluate the impact of an increase in cavity availability on flying squirrel population dynamics in deciduous stands in northwestern Québec with the dynamic N-mixture model. We compared abundance estimates from this recent approach with those from classic capture-mark-recapture models and generalized linear models. We compared apparent survival estimates with those from Cormack-Jolly-Seber (CJS) models. Average recruitment rate was 6 individuals per site after 4 years. Nevertheless, we found no effect of cavity supplementation on apparent survival and recruitment rates of flying squirrels. Contrary to our expectations, initial abundance was not affected by conifer basal area (food availability) and was negatively affected by snag basal area (cavity availability). Northern flying squirrel population dynamics are not influenced by cavity availability at our deciduous sites. Consequently, we suggest that this species should not be considered an indicator of old forest attributes in our study area, especially in view of apparent wide population fluctuations across years. Abundance estimates from N-mixture models were similar to those from capture-mark-recapture models, although the latter had greater precision. Generalized linear mixed models produced lower abundance estimates, but revealed the same relationship between abundance and snag basal area. Apparent survival estimates from N-mixture models were higher and less precise

Polymer mixtures in confined geometries: Model systems to explore ...

Indian Academy of Sciences (India)

to mean field behavior for very long chains, the critical behavior of mixtures confined into thin film geometry falls in the 2d Ising class irrespective of chain length. ..... AB interface does not approach the wall; (b) corresponds to a temperature .... Very recently, these theoretical studies have been extended to polymer mixtures.

Bayesian mixture modeling of significant p values: A meta-analytic method to estimate the degree of contamination from H₀.

Science.gov (United States)

Gronau, Quentin Frederik; Duizer, Monique; Bakker, Marjan; Wagenmakers, Eric-Jan

2017-09-01

Publication bias and questionable research practices have long been known to corrupt the published record. One method to assess the extent of this corruption is to examine the meta-analytic collection of significant p values, the so-called p -curve (Simonsohn, Nelson, & Simmons, 2014a). Inspired by statistical research on false-discovery rates, we propose a Bayesian mixture model analysis of the p -curve. Our mixture model assumes that significant p values arise either from the null-hypothesis H ₀ (when their distribution is uniform) or from the alternative hypothesis H1 (when their distribution is accounted for by a simple parametric model). The mixture model estimates the proportion of significant results that originate from H ₀, but it also estimates the probability that each specific p value originates from H ₀. We apply our model to 2 examples. The first concerns the set of 587 significant p values for all t tests published in the 2007 volumes of Psychonomic Bulletin & Review and the Journal of Experimental Psychology: Learning, Memory, and Cognition; the mixture model reveals that p values higher than about .005 are more likely to stem from H ₀ than from H ₁. The second example concerns 159 significant p values from studies on social priming and 130 from yoked control studies. The results from the yoked controls confirm the findings from the first example, whereas the results from the social priming studies are difficult to interpret because they are sensitive to the prior specification. To maximize accessibility, we provide a web application that allows researchers to apply the mixture model to any set of significant p values. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Modeling of columnar and equiaxed solidification of binary mixtures

International Nuclear Information System (INIS)

Roux, P.

2005-12-01

This work deals with the modelling of dendritic solidification in binary mixtures. Large scale phenomena are represented by volume averaging of the local conservation equations. This method allows to rigorously derive the partial differential equations of averaged fields and the closure problems associated to the deviations. Such problems can be resolved numerically on periodic cells, representative of dendritic structures, in order to give a precise evaluation of macroscopic transfer coefficients (Drag coefficients, exchange coefficients, diffusion-dispersion tensors...). The method had already been applied for a model of columnar dendritic mushy zone and it is extended to the case of equiaxed dendritic solidification, where solid grains can move. The two-phase flow is modelled with an Eulerian-Eulerian approach and the novelty is to account for the dispersion of solid velocity through the kinetic agitation of the particles. A coupling of the two models is proposed thanks to an original adaptation of the columnar model, allowing for undercooling calculation: a solid-liquid interfacial area density is introduced and calculated. At last, direct numerical simulations of crystal growth are proposed with a diffuse interface method for a representation of local phenomena. (author)

Tractography segmentation using a hierarchical Dirichlet processes mixture model.

Science.gov (United States)

Wang, Xiaogang; Grimson, W Eric L; Westin, Carl-Fredrik

2011-01-01

In this paper, we propose a new nonparametric Bayesian framework to cluster white matter fiber tracts into bundles using a hierarchical Dirichlet processes mixture (HDPM) model. The number of clusters is automatically learned driven by data with a Dirichlet process (DP) prior instead of being manually specified. After the models of bundles have been learned from training data without supervision, they can be used as priors to cluster/classify fibers of new subjects for comparison across subjects. When clustering fibers of new subjects, new clusters can be created for structures not observed in the training data. Our approach does not require computing pairwise distances between fibers and can cluster a huge set of fibers across multiple subjects. We present results on several data sets, the largest of which has more than 120,000 fibers. Copyright © 2010 Elsevier Inc. All rights reserved.

Assessing clustering strategies for Gaussian mixture filtering a subsurface contaminant model

KAUST Repository

Liu, Bo

2016-02-03

An ensemble-based Gaussian mixture (GM) filtering framework is studied in this paper in term of its dependence on the choice of the clustering method to construct the GM. In this approach, a number of particles sampled from the posterior distribution are first integrated forward with the dynamical model for forecasting. A GM representation of the forecast distribution is then constructed from the forecast particles. Once an observation becomes available, the forecast GM is updated according to Bayes’ rule. This leads to (i) a Kalman filter-like update of the particles, and (ii) a Particle filter-like update of their weights, generalizing the ensemble Kalman filter update to non-Gaussian distributions. We focus on investigating the impact of the clustering strategy on the behavior of the filter. Three different clustering methods for constructing the prior GM are considered: (i) a standard kernel density estimation, (ii) clustering with a specified mixture component size, and (iii) adaptive clustering (with a variable GM size). Numerical experiments are performed using a two-dimensional reactive contaminant transport model in which the contaminant concentration and the heterogenous hydraulic conductivity fields are estimated within a confined aquifer using solute concentration data. The experimental results suggest that the performance of the GM filter is sensitive to the choice of the GM model. In particular, increasing the size of the GM does not necessarily result in improved performances. In this respect, the best results are obtained with the proposed adaptive clustering scheme.

Fitting a mixture of von Mises distributions in order to model data on wind direction in Peninsular Malaysia

International Nuclear Information System (INIS)

Masseran, N.; Razali, A.M.; Ibrahim, K.; Latif, M.T.

2013-01-01

Highlights: • We suggest a simple way for wind direction modeling using the mixture of von Mises distribution. • We determine the most suitable probability model for wind direction regime in Malaysia. • We provide the circular density plots to show the most prominent directions of wind blows. - Abstract: A statistical distribution for describing wind direction provides information about the wind regime at a particular location. In addition, this information complements knowledge of wind speed, which allows researchers to draw some conclusions about the energy potential of wind and aids the development of efficient wind energy generation. This study focuses on modeling the frequency distribution of wind direction, including some characteristics of wind regime that cannot be represented by a unimodal distribution. To identify the most suitable model, a finite mixture of von Mises distributions were fitted to the average hourly wind direction data for nine wind stations located in Peninsular Malaysia. The data used were from the years 2000 to 2009. The suitability of each mixture distribution was judged based on the R 2 coefficient and the histogram plot with a density line. The results showed that the finite mixture of the von Mises distribution with H number of components was the best distribution to describe the wind direction distributions in Malaysia. In addition, the circular density plots of the suitable model clearly showed the most prominent directions of wind blows than the other directions

The Support Reduction Algorithm for Computing Non-Parametric Function Estimates in Mixture Models

OpenAIRE

GROENEBOOM, PIET; JONGBLOED, GEURT; WELLNER, JON A.

2008-01-01

In this paper, we study an algorithm (which we call the support reduction algorithm) that can be used to compute non-parametric M-estimators in mixture models. The algorithm is compared with natural competitors in the context of convex regression and the ‘Aspect problem’ in quantum physics.

Modelling and simulation of an energy transport phenomenon in a solid-fluid mixture

International Nuclear Information System (INIS)

Costa, M.L.M.; Sampaio, R.; Gama, R.M.S. da.

1989-08-01

In the present work a model for a local description of the energy transfer phenomenon in a binary (solid-fluid) saturated mixture is proposed. The heat transfer in a saturated flow (through a porous medium) between two parallel plates is simulated by using the Finite Volumes Method. (author) [pt

Catalytically stabilized combustion of lean methane-air-mixtures: a numerical model

Energy Technology Data Exchange (ETDEWEB)

Dogwiler, U; Benz, P; Mantharas, I [Paul Scherrer Inst. (PSI), Villigen (Switzerland)

1997-06-01

The catalytically stabilized combustion of lean methane/air mixtures has been studied numerically under conditions closely resembling the ones prevailing in technical devices. A detailed numerical model has been developed for a laminar, stationary, 2-D channel flow with full heterogeneous and homogeneous reaction mechanisms. The computations provide direct information on the coupling between heterogeneous-homogeneous combustion and in particular on the means of homogeneous ignitions and stabilization. (author) 4 figs., 3 refs.

On population size estimators in the Poisson mixture model.

Science.gov (United States)

Mao, Chang Xuan; Yang, Nan; Zhong, Jinhua

2013-09-01

Estimating population sizes via capture-recapture experiments has enormous applications. The Poisson mixture model can be adopted for those applications with a single list in which individuals appear one or more times. We compare several nonparametric estimators, including the Chao estimator, the Zelterman estimator, two jackknife estimators and the bootstrap estimator. The target parameter of the Chao estimator is a lower bound of the population size. Those of the other four estimators are not lower bounds, and they may produce lower confidence limits for the population size with poor coverage probabilities. A simulation study is reported and two examples are investigated. © 2013, The International Biometric Society.

Dynamic mean field theory for lattice gas models of fluid mixtures confined in mesoporous materials.

Science.gov (United States)

Edison, J R; Monson, P A

2013-11-12

We present the extension of dynamic mean field theory (DMFT) for fluids in porous materials (Monson, P. A. J. Chem. Phys. 2008, 128, 084701) to the case of mixtures. The theory can be used to describe the relaxation processes in the approach to equilibrium or metastable equilibrium states for fluids in pores after a change in the bulk pressure or composition. It is especially useful for studying systems where there are capillary condensation or evaporation transitions. Nucleation processes associated with these transitions are emergent features of the theory and can be visualized via the time dependence of the density distribution and composition distribution in the system. For mixtures an important component of the dynamics is relaxation of the composition distribution in the system, especially in the neighborhood of vapor-liquid interfaces. We consider two different types of mixtures, modeling hydrocarbon adsorption in carbon-like slit pores. We first present results on bulk phase equilibria of the mixtures and then the equilibrium (stable/metastable) behavior of these mixtures in a finite slit pore and an inkbottle pore. We then use DMFT to describe the evolution of the density and composition in the pore in the approach to equilibrium after changing the state of the bulk fluid via composition or pressure changes.

Estimating demographic parameters using a combination of known-fate and open N-mixture models.

Science.gov (United States)

Schmidt, Joshua H; Johnson, Devin S; Lindberg, Mark S; Adams, Layne G

2015-10-01

Accurate estimates of demographic parameters are required to infer appropriate ecological relationships and inform management actions. Known-fate data from marked individuals are commonly used to estimate survival rates, whereas N-mixture models use count data from unmarked individuals to estimate multiple demographic parameters. However, a joint approach combining the strengths of both analytical tools has not been developed. Here we develop an integrated model combining known-fate and open N-mixture models, allowing the estimation of detection probability, recruitment, and the joint estimation of survival. We demonstrate our approach through both simulations and an applied example using four years of known-fate and pack count data for wolves (Canis lupus). Simulation results indicated that the integrated model reliably recovered parameters with no evidence of bias, and survival estimates were more precise under the joint model. Results from the applied example indicated that the marked sample of wolves was biased toward individuals with higher apparent survival rates than the unmarked pack mates, suggesting that joint estimates may be more representative of the overall population. Our integrated model is a practical approach for reducing bias while increasing precision and the amount of information gained from mark-resight data sets. We provide implementations in both the BUGS language and an R package.

Growth Kinetics and Modeling of Direct Oxynitride Growth with NO-O2 Gas Mixtures

Energy Technology Data Exchange (ETDEWEB)

Everist, Sarah; Nelson, Jerry; Sharangpani, Rahul; Smith, Paul Martin; Tay, Sing-Pin; Thakur, Randhir

1999-05-03

We have modeled growth kinetics of oxynitrides grown in NO-O₂ gas mixtures from first principles using modified Deal-Grove equations. Retardation of oxygen diffusion through the nitrided dielectric was assumed to be the dominant growth-limiting step. The model was validated against experimentally obtained curves with good agreement. Excellent uniformity, which exceeded expected walues, was observed.

Heat transfer analysis of porous media receiver with different transport and thermophysical models using mixture as feeding gas

International Nuclear Information System (INIS)

Wang, Fuqiang; Tan, Jianyu; Wang, Zhiqiang

2014-01-01

Highlights: • Using local thermal non-equilibrium model to solve heat transfer of porous media. • CH 4 /H 2 O mixture is adopted as feeding gas of porous media receiver. • Radiative transfer equation between porous strut is solved by Rosseland approximation. • Transport and thermophysical models not included in Fluent are programmed by UDFs. • Variations of model on thermal performance of porous media receiver are studied. - Abstract: The local thermal non-equilibrium model is adopted to solve the steady state heat and mass transfer problems of porous media solar receiver. The fluid entrance surface is subjected to concentrated solar radiation, and CH 4 /H 2 O mixture is adopted as feeding gas. The radiative heat transfer equation between porous strut is solved by Rosseland approximation. The impacts of variation in transport and thermophysical characteristics model of gas mixture on thermal performance of porous media receiver are investigated. The transport and thermophysical characteristics models which are not included in software Fluent are programmed by user defined functions (UDFs). The numerical results indicate that models of momentum source term for porous media receiver have significant impact on pressure drop and static pressure distribution, and the radiative heat transfer cannot be omitted during the thermal performance analysis of porous media receiver

General multi-group macroscopic modeling for thermo-chemical non-equilibrium gas mixtures

Science.gov (United States)

Liu, Yen; Panesi, Marco; Sahai, Amal; Vinokur, Marcel

2015-04-01

relaxation model, which can only be applied to molecules, the new model is applicable to atoms, molecules, ions, and their mixtures. Numerical examples and model validations are carried out with two gas mixtures using the maximum entropy linear model: one mixture consists of nitrogen molecules undergoing internal excitation and dissociation and the other consists of nitrogen atoms undergoing internal excitation and ionization. Results show that the original hundreds to thousands of microscopic equations can be reduced to two macroscopic equations with almost perfect agreement for the total number density and total internal energy using only one or two groups. We also obtain good prediction of the microscopic state populations using 5-10 groups in the macroscopic equations.

General multi-group macroscopic modeling for thermo-chemical non-equilibrium gas mixtures.

Science.gov (United States)

Liu, Yen; Panesi, Marco; Sahai, Amal; Vinokur, Marcel

2015-04-07

relaxation model, which can only be applied to molecules, the new model is applicable to atoms, molecules, ions, and their mixtures. Numerical examples and model validations are carried out with two gas mixtures using the maximum entropy linear model: one mixture consists of nitrogen molecules undergoing internal excitation and dissociation and the other consists of nitrogen atoms undergoing internal excitation and ionization. Results show that the original hundreds to thousands of microscopic equations can be reduced to two macroscopic equations with almost perfect agreement for the total number density and total internal energy using only one or two groups. We also obtain good prediction of the microscopic state populations using 5-10 groups in the macroscopic equations.

Solvable Model of a Generic Trapped Mixture of Interacting Bosons: Many-Body and Mean-Field Properties

Science.gov (United States)

Klaiman, S.; Streltsov, A. I.; Alon, O. E.

2018-04-01

A solvable model of a generic trapped bosonic mixture, N 1 bosons of mass m 1 and N 2 bosons of mass m 2 trapped in an harmonic potential of frequency ω and interacting by harmonic inter-particle interactions of strengths λ 1, λ 2, and λ 12, is discussed. It has recently been shown for the ground state [J. Phys. A 50, 295002 (2017)] that in the infinite-particle limit, when the interaction parameters λ 1(N 1 ‑ 1), λ 2(N 2 ‑ 1), λ 12 N 1, λ 12 N 2 are held fixed, each of the species is 100% condensed and its density per particle as well as the total energy per particle are given by the solution of the coupled Gross-Pitaevskii equations of the mixture. In the present work we investigate properties of the trapped generic mixture at the infinite-particle limit, and find differences between the many-body and mean-field descriptions of the mixture, despite each species being 100%. We compute analytically and analyze, both for the mixture and for each species, the center-of-mass position and momentum variances, their uncertainty product, the angular-momentum variance, as well as the overlap of the exact and Gross-Pitaevskii wavefunctions of the mixture. The results obtained in this work can be considered as a step forward in characterizing how important are many-body effects in a fully condensed trapped bosonic mixture at the infinite-particle limit.

Modelling phase equilibria for acid gas mixtures using the CPA equation of state. Part VI. Multicomponent mixtures with glycols relevant to oil and gas and to liquid or supercritical CO2 transport applications

DEFF Research Database (Denmark)

Tsivintzelis, Ioannis; Kontogeorgis, Georgios M.

2016-01-01

to data on ternary and multicomponent mixtures) to model the phase behaviour of ternary and quaternary systems with CO2 and glycols. It is concluded that CPA performs satisfactorily for most multicomponent systems considered. Some differences between the various modelling approaches are observed....... This work is the last part of a series of studies, which aim to arrive in a single "engineering approach" for applying CPA to acid gas mixtures, without introducing significant changes to the model. An overall assessment, based also on the obtained results of this series (Tsivintzelis et al., 2010, 2011...

Manual hierarchical clustering of regional geochemical data using a Bayesian finite mixture model

International Nuclear Information System (INIS)

Ellefsen, Karl J.; Smith, David B.

2016-01-01

Interpretation of regional scale, multivariate geochemical data is aided by a statistical technique called “clustering.” We investigate a particular clustering procedure by applying it to geochemical data collected in the State of Colorado, United States of America. The clustering procedure partitions the field samples for the entire survey area into two clusters. The field samples in each cluster are partitioned again to create two subclusters, and so on. This manual procedure generates a hierarchy of clusters, and the different levels of the hierarchy show geochemical and geological processes occurring at different spatial scales. Although there are many different clustering methods, we use Bayesian finite mixture modeling with two probability distributions, which yields two clusters. The model parameters are estimated with Hamiltonian Monte Carlo sampling of the posterior probability density function, which usually has multiple modes. Each mode has its own set of model parameters; each set is checked to ensure that it is consistent both with the data and with independent geologic knowledge. The set of model parameters that is most consistent with the independent geologic knowledge is selected for detailed interpretation and partitioning of the field samples. - Highlights: • We evaluate a clustering procedure by applying it to geochemical data. • The procedure generates a hierarchy of clusters. • Different levels of the hierarchy show geochemical processes at different spatial scales. • The clustering method is Bayesian finite mixture modeling. • Model parameters are estimated with Hamiltonian Monte Carlo sampling.

The impact of covariance misspecification in multivariate Gaussian mixtures on estimation and inference: an application to longitudinal modeling.

Science.gov (United States)

Heggeseth, Brianna C; Jewell, Nicholas P

2013-07-20

Multivariate Gaussian mixtures are a class of models that provide a flexible parametric approach for the representation of heterogeneous multivariate outcomes. When the outcome is a vector of repeated measurements taken on the same subject, there is often inherent dependence between observations. However, a common covariance assumption is conditional independence-that is, given the mixture component label, the outcomes for subjects are independent. In this paper, we study, through asymptotic bias calculations and simulation, the impact of covariance misspecification in multivariate Gaussian mixtures. Although maximum likelihood estimators of regression and mixing probability parameters are not consistent under misspecification, they have little asymptotic bias when mixture components are well separated or if the assumed correlation is close to the truth even when the covariance is misspecified. We also present a robust standard error estimator and show that it outperforms conventional estimators in simulations and can indicate that the model is misspecified. Body mass index data from a national longitudinal study are used to demonstrate the effects of misspecification on potential inferences made in practice. Copyright © 2013 John Wiley & Sons, Ltd.

Volatility modeling for IDR exchange rate through APARCH model with student-t distribution

Science.gov (United States)

Nugroho, Didit Budi; Susanto, Bambang

2017-08-01

The aim of this study is to empirically investigate the performance of APARCH(1,1) volatility model with the Student-t error distribution on five foreign currency selling rates to Indonesian rupiah (IDR), including the Swiss franc (CHF), the Euro (EUR), the British pound (GBP), Japanese yen (JPY), and the US dollar (USD). Six years daily closing rates over the period of January 2010 to December 2016 for a total number of 1722 observations have analysed. The Bayesian inference using the efficient independence chain Metropolis-Hastings and adaptive random walk Metropolis methods in the Markov chain Monte Carlo (MCMC) scheme has been applied to estimate the parameters of model. According to the DIC criterion, this study has found that the APARCH(1,1) model under Student-t distribution is a better fit than the model under normal distribution for any observed rate return series. The 95% highest posterior density interval suggested the APARCH models to model the IDR/JPY and IDR/USD volatilities. In particular, the IDR/JPY and IDR/USD data, respectively, have significant negative and positive leverage effect in the rate returns. Meanwhile, the optimal power coefficient of volatility has been found to be statistically different from 2 in adopting all rate return series, save the IDR/EUR rate return series.

EmpiriciSN: Re-sampling Observed Supernova/Host Galaxy Populations Using an XD Gaussian Mixture Model

Science.gov (United States)

Holoien, Thomas W.-S.; Marshall, Philip J.; Wechsler, Risa H.

2017-06-01

We describe two new open-source tools written in Python for performing extreme deconvolution Gaussian mixture modeling (XDGMM) and using a conditioned model to re-sample observed supernova and host galaxy populations. XDGMM is new program that uses Gaussian mixtures to perform density estimation of noisy data using extreme deconvolution (XD) algorithms. Additionally, it has functionality not available in other XD tools. It allows the user to select between the AstroML and Bovy et al. fitting methods and is compatible with scikit-learn machine learning algorithms. Most crucially, it allows the user to condition a model based on the known values of a subset of parameters. This gives the user the ability to produce a tool that can predict unknown parameters based on a model that is conditioned on known values of other parameters. EmpiriciSN is an exemplary application of this functionality, which can be used to fit an XDGMM model to observed supernova/host data sets and predict likely supernova parameters using a model conditioned on observed host properties. It is primarily intended to simulate realistic supernovae for LSST data simulations based on empirical galaxy properties.

EmpiriciSN: Re-sampling Observed Supernova/Host Galaxy Populations Using an XD Gaussian Mixture Model

Energy Technology Data Exchange (ETDEWEB)

Holoien, Thomas W.-S.; /Ohio State U., Dept. Astron. /Ohio State U., CCAPP /KIPAC, Menlo Park /SLAC; Marshall, Philip J.; Wechsler, Risa H.; /KIPAC, Menlo Park /SLAC

2017-05-11

We describe two new open-source tools written in Python for performing extreme deconvolution Gaussian mixture modeling (XDGMM) and using a conditioned model to re-sample observed supernova and host galaxy populations. XDGMM is new program that uses Gaussian mixtures to perform density estimation of noisy data using extreme deconvolution (XD) algorithms. Additionally, it has functionality not available in other XD tools. It allows the user to select between the AstroML and Bovy et al. fitting methods and is compatible with scikit-learn machine learning algorithms. Most crucially, it allows the user to condition a model based on the known values of a subset of parameters. This gives the user the ability to produce a tool that can predict unknown parameters based on a model that is conditioned on known values of other parameters. EmpiriciSN is an exemplary application of this functionality, which can be used to fit an XDGMM model to observed supernova/host data sets and predict likely supernova parameters using a model conditioned on observed host properties. It is primarily intended to simulate realistic supernovae for LSST data simulations based on empirical galaxy properties.

Phase behavior of mixtures of oppositely charged nanoparticles: Heterogeneous Poisson-Boltzmann cell model applied to lysozyme and succinylated lysozyme

NARCIS (Netherlands)

Biesheuvel, P.M.; Lindhoud, S.; Vries, de R.J.; Stuart, M.A.C.

2006-01-01

We study the phase behavior of mixtures of oppositely charged nanoparticles, both theoretically and experimentally. As an experimental model system we consider mixtures of lysozyme and lysozyme that has been chemically modified in such a way that its charge is nearly equal in magnitude but opposite

A model for radiative heat transfer in mixtures of a hot solid or molten material with water and steam

International Nuclear Information System (INIS)

Vaeth, L.

1997-05-01

A model has been devised for describing the radiative heat transfer in mixtures of a hot radiant material with water and steam, to be used, e.g., in the framework of a multiphase, multicomponent flow simulation. The main features of the model are: 1. The radiative heat transfer is modelled for a homogeneous mixture of one continuous material with droplets/bubbles of the other two, of the kind normally assumed for the material distribution in one cell of a bigger calculational problem. Neither the heat transfer over the cell boundaries nor the finite dimensions of the cell are taken into account. 2. The geometry of the mixture (radiant material continuous or discontinuous, droplet/bubble diameters and number densities) is taken into account. 3. The optical properties of water and water vapour are modelled as functions of the temperature of the radiant and, in the case of water vapour, also of the absorbing material. 4. The model distinguishes between heat transfer to the surface of the water (leading to evaporation) and into the bulk of the water (pure heating). (orig./DG) [de

Hazardous waste management and weight-based indicators-The case of Haifa Metropolis

International Nuclear Information System (INIS)

Elimelech, E.; Ayalon, O.; Flicstein, B.

2011-01-01

The quantity control of hazardous waste in Israel relies primarily on the Environmental Services Company (ESC) reports. With limited management tools, the Ministry of Environmental Protection (MoEP) has no applicable methodology to confirm or monitor the actual amounts of hazardous waste produced by various industrial sectors. The main goal of this research was to develop a method for estimating the amounts of hazardous waste produced by various sectors. In order to achieve this goal, sector-specific indicators were tested on three hazardous waste producing sectors in the Haifa Metropolis: petroleum refineries, dry cleaners, and public hospitals. The findings reveal poor practice of hazardous waste management in the dry cleaning sector and in the public hospitals sector. Large discrepancies were found in the dry cleaning sector, between the quantities of hazardous waste reported and the corresponding indicator estimates. Furthermore, a lack of documentation on hospitals' pharmaceutical and chemical waste production volume was observed. Only in the case of petroleum refineries, the reported amount was consistent with the estimate.

Hazardous waste management and weight-based indicators--the case of Haifa Metropolis.

Science.gov (United States)

Elimelech, E; Ayalon, O; Flicstein, B

2011-01-30

The quantity control of hazardous waste in Israel relies primarily on the Environmental Services Company (ESC) reports. With limited management tools, the Ministry of Environmental Protection (MoEP) has no applicable methodology to confirm or monitor the actual amounts of hazardous waste produced by various industrial sectors. The main goal of this research was to develop a method for estimating the amounts of hazardous waste produced by various sectors. In order to achieve this goal, sector-specific indicators were tested on three hazardous waste producing sectors in the Haifa Metropolis: petroleum refineries, dry cleaners, and public hospitals. The findings reveal poor practice of hazardous waste management in the dry cleaning sector and in the public hospitals sector. Large discrepancies were found in the dry cleaning sector, between the quantities of hazardous waste reported and the corresponding indicator estimates. Furthermore, a lack of documentation on hospitals' pharmaceutical and chemical waste production volume was observed. Only in the case of petroleum refineries, the reported amount was consistent with the estimate. Copyright © 2010 Elsevier B.V. All rights reserved.

Bayesian nonparametric meta-analysis using Polya tree mixture models.