Model reduction by weighted Component Cost Analysis
Kim, Jae H.; Skelton, Robert E.
1990-01-01
Component Cost Analysis considers any given system driven by a white noise process as an interconnection of different components, and assigns a metric called 'component cost' to each component. These component costs measure the contribution of each component to a predefined quadratic cost function. A reduced-order model of the given system may be obtained by deleting those components that have the smallest component costs. The theory of Component Cost Analysis is extended to include finite-bandwidth colored noises. The results also apply when actuators have dynamics of their own. Closed-form analytical expressions of component costs are also derived for a mechanical system described by its modal data. This is very useful to compute the modal costs of very high order systems. A numerical example for MINIMAST system is presented.
Trajectory modeling of gestational weight: A functional principal component analysis approach.
Directory of Open Access Journals (Sweden)
Menglu Che
Full Text Available Suboptimal gestational weight gain (GWG, which is linked to increased risk of adverse outcomes for a pregnant woman and her infant, is prevalent. In the study of a large cohort of Canadian pregnant women, our goals are to estimate the individual weight growth trajectory using sparsely collected bodyweight data, and to identify the factors affecting the weight change during pregnancy, such as prepregnancy body mass index (BMI, dietary intakes and physical activity. The first goal was achieved through functional principal component analysis (FPCA by conditional expectation. For the second goal, we used linear regression with the total weight gain as the response variable. The trajectory modeling through FPCA had a significantly smaller root mean square error (RMSE and improved adaptability than the classic nonlinear mixed-effect models, demonstrating a novel tool that can be used to facilitate real time monitoring and interventions of GWG. Our regression analysis showed that prepregnancy BMI had a high predictive value for the weight changes during pregnancy, which agrees with the published weight gain guideline.
Multi-component fiber track modelling of diffusion-weighted magnetic resonance imaging data
Directory of Open Access Journals (Sweden)
Yasser M. Kadah
2010-01-01
Full Text Available In conventional diffusion tensor imaging (DTI based on magnetic resonance data, each voxel is assumed to contain a single component having diffusion properties that can be fully represented by a single tensor. Even though this assumption can be valid in some cases, the general case involves the mixing of components, resulting in significant deviation from the single tensor model. Hence, a strategy that allows the decomposition of data based on a mixture model has the potential of enhancing the diagnostic value of DTI. This project aims to work towards the development and experimental verification of a robust method for solving the problem of multi-component modelling of diffusion tensor imaging data. The new method demonstrates significant error reduction from the single-component model while maintaining practicality for clinical applications, obtaining more accurate Fiber tracking results.
Singh, Rupinder
2018-02-01
Hot chamber (HC) die casting process is one of the most widely used commercial processes for the casting of low temperature metals and alloys. This process gives near-net shape product with high dimensional accuracy. However in actual field environment the best settings of input parameters is often conflicting as the shape and size of the casting changes and one have to trade off among various output parameters like hardness, dimensional accuracy, casting defects, microstructure etc. So for online inspection of the cast components properties (without affecting the production line) the weight measurement has been established as one of the cost effective method (as the difference in weight of sound and unsound casting reflects the possible casting defects) in field environment. In the present work at first stage the effect of three input process parameters (namely: pressure at 2nd phase in HC die casting; metal pouring temperature and die opening time) has been studied for optimizing the cast component weight `W' as output parameter in form of macro model based upon Taguchi L9 OA. After this Buckingham's π approach has been applied on Taguchi based macro model for the development of micro model. This study highlights the Taguchi-Buckingham based combined approach as a case study (for conversion of macro model into micro model) by identification of optimum levels of input parameters (based on Taguchi approach) and development of mathematical model (based on Buckingham's π approach). Finally developed mathematical model can be used for predicting W in HC die casting process with more flexibility. The results of study highlights second degree polynomial equation for predicting cast component weight in HC die casting and suggest that pressure at 2nd stage is one of the most contributing factors for controlling the casting defect/weight of casting.
Liao, Shuxin; Wang, Yunfang; Xiao, Shufang; Deng, Xujie; Fang, Bimei; Yang, Fang
2018-03-30
To establish a new model for birth weight prediction using 2- and 3-dimensional ultrasonography (US) by principal component analysis (PCA). Two- and 3-dimensional US was prospectively performed in women with normal singleton pregnancies within 7 days before delivery (37-41 weeks' gestation). The participants were divided into a development group (n = 600) and a validation group (n = 597). Principal component analysis and stepwise linear regression analysis were used to develop a new prediction model. The new model's accuracy in predicting fetal birth weight was confirmed by the validation group through comparisons with previously published formulas. A total of 1197 cases were recruited in this study. All interclass and intraclass correlation coefficients of US measurements were greater than 0.75. Two principal components (PCs) were considered primary in determining estimated fetal birth weight, which were derived from 9 US measurements. Stepwise linear regression analysis showed a positive association between birth weight and PC1 and PC2. In the development group, our model had a small mean percentage error (mean ± SD, 3.661% ± 3.161%). At least a 47.558% decrease in the mean percentage error and a 57.421% decrease in the standard deviation of the new model compared with previously published formulas were noted. The results were similar to those in the validation group, and the new model covered 100% of birth weights within 10% of actual birth weights. The birth weight prediction model based on 2- and 3-dimensional US by PCA could help improve the precision of estimated fetal birth weight. © 2018 by the American Institute of Ultrasound in Medicine.
variance components and genetic parameters for live weight
African Journals Online (AJOL)
admin
Against this background the present study estimated the (co)variance .... Starting values for the (co)variance components of two-trait models were ..... Estimates of genetic parameters for weaning weight of beef accounting for direct-maternal.
Qu, Mingkai; Wang, Yan; Huang, Biao; Zhao, Yongcun
2018-06-01
The traditional source apportionment models, such as absolute principal component scores-multiple linear regression (APCS-MLR), are usually susceptible to outliers, which may be widely present in the regional geochemical dataset. Furthermore, the models are merely built on variable space instead of geographical space and thus cannot effectively capture the local spatial characteristics of each source contributions. To overcome the limitations, a new receptor model, robust absolute principal component scores-robust geographically weighted regression (RAPCS-RGWR), was proposed based on the traditional APCS-MLR model. Then, the new method was applied to the source apportionment of soil metal elements in a region of Wuhan City, China as a case study. Evaluations revealed that: (i) RAPCS-RGWR model had better performance than APCS-MLR model in the identification of the major sources of soil metal elements, and (ii) source contributions estimated by RAPCS-RGWR model were more close to the true soil metal concentrations than that estimated by APCS-MLR model. It is shown that the proposed RAPCS-RGWR model is a more effective source apportionment method than APCS-MLR (i.e., non-robust and global model) in dealing with the regional geochemical dataset. Copyright © 2018 Elsevier B.V. All rights reserved.
Variance components for body weight in Japanese quails (Coturnix japonica
Directory of Open Access Journals (Sweden)
RO Resende
2005-03-01
Full Text Available The objective of this study was to estimate the variance components for body weight in Japanese quails by Bayesian procedures. The body weight at hatch (BWH and at 7 (BW07, 14 (BW14, 21 (BW21 and 28 days of age (BW28 of 3,520 quails was recorded from August 2001 to June 2002. A multiple-trait animal model with additive genetic, maternal environment and residual effects was implemented by Gibbs sampling methodology. A single Gibbs sampling with 80,000 rounds was generated by the program MTGSAM (Multiple Trait Gibbs Sampling in Animal Model. Normal and inverted Wishart distributions were used as prior distributions for the random effects and the variance components, respectively. Variance components were estimated based on the 500 samples that were left after elimination of 30,000 rounds in the burn-in period and 100 rounds of each thinning interval. The posterior means of additive genetic variance components were 0.15; 4.18; 14.62; 27.18 and 32.68; the posterior means of maternal environment variance components were 0.23; 1.29; 2.76; 4.12 and 5.16; and the posterior means of residual variance components were 0.084; 6.43; 22.66; 31.21 and 30.85, at hatch, 7, 14, 21 and 28 days old, respectively. The posterior means of heritability were 0.33; 0.35; 0.36; 0.43 and 0.47 at hatch, 7, 14, 21 and 28 days old, respectively. These results indicate that heritability increased with age. On the other hand, after hatch there was a marked reduction in the maternal environment variance proportion of the phenotypic variance, whose estimates were 0.50; 0.11; 0.07; 0.07 and 0.08 for BWH, BW07, BW14, BW21 and BW28, respectively. The genetic correlation between weights at different ages was high, except for those estimates between BWH and weight at other ages. Changes in body weight of quails can be efficiently achieved by selection.
Fields, Christina M.
2013-01-01
The Spaceport Command and Control System (SCCS) Simulation Computer Software Configuration Item (CSCI) is responsible for providing simulations to support test and verification of SCCS hardware and software. The Universal Coolant Transporter System (UCTS) was a Space Shuttle Orbiter support piece of the Ground Servicing Equipment (GSE). The initial purpose of the UCTS was to provide two support services to the Space Shuttle Orbiter immediately after landing at the Shuttle Landing Facility. The UCTS is designed with the capability of servicing future space vehicles; including all Space Station Requirements necessary for the MPLM Modules. The Simulation uses GSE Models to stand in for the actual systems to support testing of SCCS systems during their development. As an intern at Kennedy Space Center (KSC), my assignment was to develop a model component for the UCTS. I was given a fluid component (dryer) to model in Simulink. I completed training for UNIX and Simulink. The dryer is a Catch All replaceable core type filter-dryer. The filter-dryer provides maximum protection for the thermostatic expansion valve and solenoid valve from dirt that may be in the system. The filter-dryer also protects the valves from freezing up. I researched fluid dynamics to understand the function of my component. The filter-dryer was modeled by determining affects it has on the pressure and velocity of the system. I used Bernoulli's Equation to calculate the pressure and velocity differential through the dryer. I created my filter-dryer model in Simulink and wrote the test script to test the component. I completed component testing and captured test data. The finalized model was sent for peer review for any improvements. I participated in Simulation meetings and was involved in the subsystem design process and team collaborations. I gained valuable work experience and insight into a career path as an engineer.
Weighted Components of i-Government Enterprise Architecture
Budiardjo, E. K.; Firmansyah, G.; Hasibuan, Z. A.
2017-01-01
Lack of government performance, among others due to the lack of coordination and communication among government agencies. Whilst, Enterprise Architecture (EA) in the government can be use as a strategic planning tool to improve productivity, efficiency, and effectivity. However, the existence components of Government Enterprise Architecture (GEA) do not show level of importance, that cause difficulty in implementing good e-government for good governance. This study is to explore the weight of GEA components using Principal Component Analysis (PCA) in order to discovered an inherent structure of e-government. The results show that IT governance component of GEA play a major role in the GEA. The rest of components that consist of e-government system, e-government regulation, e-government management, and application key operational, contributed more or less the same. Beside that GEA from other countries analyzes using comparative base on comon enterprise architecture component. These weighted components use to construct i-Government enterprise architecture. and show the relative importance of component in order to established priorities in developing e-government.
A Weighted Configuration Model and Inhomogeneous Epidemics
Britton, Tom; Deijfen, Maria; Liljeros, Fredrik
2011-12-01
A random graph model with prescribed degree distribution and degree dependent edge weights is introduced. Each vertex is independently equipped with a random number of half-edges and each half-edge is assigned an integer valued weight according to a distribution that is allowed to depend on the degree of its vertex. Half-edges with the same weight are then paired randomly to create edges. An expression for the threshold for the appearance of a giant component in the resulting graph is derived using results on multi-type branching processes. The same technique also gives an expression for the basic reproduction number for an epidemic on the graph where the probability that a certain edge is used for transmission is a function of the edge weight (reflecting how closely `connected' the corresponding vertices are). It is demonstrated that, if vertices with large degree tend to have large (small) weights on their edges and if the transmission probability increases with the edge weight, then it is easier (harder) for the epidemic to take off compared to a randomized epidemic with the same degree and weight distribution. A recipe for calculating the probability of a large outbreak in the epidemic and the size of such an outbreak is also given. Finally, the model is fitted to three empirical weighted networks of importance for the spread of contagious diseases and it is shown that R 0 can be substantially over- or underestimated if the correlation between degree and weight is not taken into account.
Component Reification in Systems Modelling
DEFF Research Database (Denmark)
Bendisposto, Jens; Hallerstede, Stefan
When modelling concurrent or distributed systems in Event-B, we often obtain models where the structure of the connected components is specified by constants. Their behaviour is specified by the non-deterministic choice of event parameters for events that operate on shared variables. From a certain......? These components may still refer to shared variables. Events of these components should not refer to the constants specifying the structure. The non-deterministic choice between these components should not be via parameters. We say the components are reified. We need to address how the reified components get...... reflected into the original model. This reflection should indicate the constraints on how to connect the components....
Component Composition Using Feature Models
DEFF Research Database (Denmark)
Eichberg, Michael; Klose, Karl; Mitschke, Ralf
2010-01-01
interface description languages. If this variability is relevant when selecting a matching component then human interaction is required to decide which components can be bound. We propose to use feature models for making this variability explicit and (re-)enabling automatic component binding. In our...... approach, feature models are one part of service specifications. This enables to declaratively specify which service variant is provided by a component. By referring to a service's variation points, a component that requires a specific service can list the requirements on the desired variant. Using...... these specifications, a component environment can then determine if a binding of the components exists that satisfies all requirements. The prototypical environment Columbus demonstrates the feasibility of the approach....
Data driven propulsion system weight prediction model
Gerth, Richard J.
1994-10-01
The objective of the research was to develop a method to predict the weight of paper engines, i.e., engines that are in the early stages of development. The impetus for the project was the Single Stage To Orbit (SSTO) project, where engineers need to evaluate alternative engine designs. Since the SSTO is a performance driven project the performance models for alternative designs were well understood. The next tradeoff is weight. Since it is known that engine weight varies with thrust levels, a model is required that would allow discrimination between engines that produce the same thrust. Above all, the model had to be rooted in data with assumptions that could be justified based on the data. The general approach was to collect data on as many existing engines as possible and build a statistical model of the engines weight as a function of various component performance parameters. This was considered a reasonable level to begin the project because the data would be readily available, and it would be at the level of most paper engines, prior to detailed component design.
Characteristic gene selection via weighting principal components by singular values.
Directory of Open Access Journals (Sweden)
Jin-Xing Liu
Full Text Available Conventional gene selection methods based on principal component analysis (PCA use only the first principal component (PC of PCA or sparse PCA to select characteristic genes. These methods indeed assume that the first PC plays a dominant role in gene selection. However, in a number of cases this assumption is not satisfied, so the conventional PCA-based methods usually provide poor selection results. In order to improve the performance of the PCA-based gene selection method, we put forward the gene selection method via weighting PCs by singular values (WPCS. Because different PCs have different importance, the singular values are exploited as the weights to represent the influence on gene selection of different PCs. The ROC curves and AUC statistics on artificial data show that our method outperforms the state-of-the-art methods. Moreover, experimental results on real gene expression data sets show that our method can extract more characteristic genes in response to abiotic stresses than conventional gene selection methods.
The contribution of fat component to gestational weight gain
Directory of Open Access Journals (Sweden)
2013-12-01
Full Text Available Objective: to estimate the role of adipose tissue in gestational weight gain (GWG and preferential fat deposition among normal-weight women. Subjects and methods: prospective cohort study of 84 pregnancies: maternal body mass index 18,5–24,9 kg/m2, singleton term pregnancy, nondiabetic women, somatically well. GWG and skinfold thickness were evaluated in the 1st, 2nd, 3d trimesters, on the 3d day after delivery. Results: fat mass gain in low GWG was similar to recommended GWG and in the high-GWG group was greater one. Women with recommended and low GWG returned to their initial fat level on the 3d day after delivery, in excessive weight gain fat significantly increased (р=0,025. Compared to initial recommended GWG resulted in triceps skinfold thicknesses loss (р=0,001, in abdominal skinfold gained nothing and in thighs skinfold thicknesses increasing (р=0,021. Inadequate GWG leads to fat loss in arms (р=0,017, fat of abdominal area and thighs return to initial level. In excessive GWG fat in the upper trunk and arms not changed, in the lower area (thighs significantly increased compared to initial level (р=0,001 or other groups (р=0,001. Conclusion: excessive GWG was associated with greater adipose tissue cumulation and its deposition preferentially over the thighs. Inadequate GWG was clearly linked to low fat-free mass gain.
Dealing with multicollinearity in predicting egg components from egg weight and egg dimension
Directory of Open Access Journals (Sweden)
Tarek M. Shafey
2014-10-01
Full Text Available Measurements of 174 eggs from meat-type breeder flock (Ross at 36 weeks of age were used to study the problem of multicollinearity (MC instability in the estimation of egg components of yolk weight (YKWT, albumen weight (ALBWT and eggshell weight (SHWT. Egg weight (EGWT, egg shape index (ESI=egg width (EGWD*100/egg length (EGL and their interaction (EGWTESI were used in the context of un-centred vs centred data and principal components regression (PCR models. The pairwise phenotypic correlations, variance inflation factor (VIF, eigenvalues, condition index (CI, and variance proportions were examined. Egg weight had positive correlations with EGWD and EGL (r=0.56 and 0.50, respectively; P<0.0001 and EGL had a negative correlation with ESI (r=-0.79; P<0.0001. The highest correlation was observed between EGWT and ALBWT (r=0.94; P<0.0001, while the lowest was between EGWD and SHWT (r=0.33; P<0.0001. Multicollinearity problems were found in EGWT, ESI and their interaction as shown by VIF (>10, eigenvalues (near zero, CI (>30 and high corresponding proportions of variance of EGWT, ESI and EGWTESI with respect to EGWTESI. Results from this study suggest that mean centring and PCR were appropriate to overcome the MC instability in the estimation of egg components from EGWT and ESI. These methods improved the meaning of intercept values and produced much lower standard error values for regression coefficients than those from un-centred data.
A model of objective weighting for EIA.
Ying, L G; Liu, Y C
1995-06-01
In spite of progress achieved in the research of environmental impact assessment (EIA), the problem of weight distribution for a set of parameters has not as yet, been properly solved. This paper presents an approach of objective weighting by using a procedure of P ij principal component-factor analysis (P ij PCFA), which suits specifically those parameters measured directly by physical scales. The P ij PCFA weighting procedure reforms the conventional weighting practice in two aspects: first, the expert subjective judgment is replaced by the standardized measure P ij as the original input of weight processing and, secondly, the principal component-factor analysis is introduced to approach the environmental parameters for their respective contributions to the totality of the regional ecosystem. Not only is the P ij PCFA weighting logical in theoretical reasoning, it also suits practically all levels of professional routines in natural environmental assessment and impact analysis. Having been assured of objectivity and accuracy in the EIA case study of the Chuansha County in Shanghai, China, the P ij PCFA weighting procedure has the potential to be applied in other geographical fields that need assigning weights to parameters that are measured by physical scales.
Stochastic Modeling Of Wind Turbine Drivetrain Components
DEFF Research Database (Denmark)
Rafsanjani, Hesam Mirzaei; Sørensen, John Dalsgaard
2014-01-01
reliable components are needed for wind turbine. In this paper focus is on reliability of critical components in drivetrain such as bearings and shafts. High failure rates of these components imply a need for more reliable components. To estimate the reliability of these components, stochastic models...... are needed for initial defects and damage accumulation. In this paper, stochastic models are formulated considering some of the failure modes observed in these components. The models are based on theoretical considerations, manufacturing uncertainties, size effects of different scales. It is illustrated how...
Modelling Livestock Component in FSSIM
Thorne, P.J.; Hengsdijk, H.; Janssen, S.J.C.; Louhichi, K.; Keulen, van H.; Thornton, P.K.
2009-01-01
This document summarises the development of a ruminant livestock component for the Farm System Simulator (FSSIM). This includes treatments of energy and protein transactions in ruminant livestock that have been used as a basis for the biophysical simulations that will generate the input production
Variance components and genetic parameters for body weight and ...
African Journals Online (AJOL)
model included a direct as well as a maternal additive genetic effect, while only the direct additive genetic eff'ect had a sig- .... deviations from the log likelihood value obtained under the ... (1995).lt would therefore be fair to assume that a.
Modeling the degradation of nuclear components
International Nuclear Information System (INIS)
Stock, D.; Samanta, P.; Vesely, W.
1993-01-01
This paper describes component level reliability models that use information on degradation to predict component reliability, and which have been used to evaluate different maintenance and testing policies. The models are based on continuous time Markov processes, and are a generalization of reliability models currently used in Probabilistic Risk Assessment. An explanation of the models, the model parameters, and an example of how these models can be used to evaluate maintenance policies are discussed
Geographically weighted regression model on poverty indicator
Slamet, I.; Nugroho, N. F. T. A.; Muslich
2017-12-01
In this research, we applied geographically weighted regression (GWR) for analyzing the poverty in Central Java. We consider Gaussian Kernel as weighted function. The GWR uses the diagonal matrix resulted from calculating kernel Gaussian function as a weighted function in the regression model. The kernel weights is used to handle spatial effects on the data so that a model can be obtained for each location. The purpose of this paper is to model of poverty percentage data in Central Java province using GWR with Gaussian kernel weighted function and to determine the influencing factors in each regency/city in Central Java province. Based on the research, we obtained geographically weighted regression model with Gaussian kernel weighted function on poverty percentage data in Central Java province. We found that percentage of population working as farmers, population growth rate, percentage of households with regular sanitation, and BPJS beneficiaries are the variables that affect the percentage of poverty in Central Java province. In this research, we found the determination coefficient R2 are 68.64%. There are two categories of district which are influenced by different of significance factors.
Modelization of cooling system components
Energy Technology Data Exchange (ETDEWEB)
Copete, Monica; Ortega, Silvia; Vaquero, Jose Carlos; Cervantes, Eva [Westinghouse Electric (Spain)
2010-07-01
In the site evaluation study for licensing a new nuclear power facility, the criteria involved could be grouped in health and safety, environment, socio-economics, engineering and cost-related. These encompass different aspects such as geology, seismology, cooling system requirements, weather conditions, flooding, population, and so on. The selection of the cooling system is function of different parameters as the gross electrical output, energy consumption, available area for cooling system components, environmental conditions, water consumption, and others. Moreover, in recent years, extreme environmental conditions have been experienced and stringent water availability limits have affected water use permits. Therefore, modifications or alternatives of current cooling system designs and operation are required as well as analyses of the different possibilities of cooling systems to optimize energy production taking into account water consumption among other important variables. There are two basic cooling system configurations: - Once-through or Open-cycle; - Recirculating or Closed-cycle. In a once-through cooling system (or open-cycle), water from an external water sources passes through the steam cycle condenser and is then returned to the source at a higher temperature with some level of contaminants. To minimize the thermal impact to the water source, a cooling tower may be added in a once-through system to allow air cooling of the water (with associated losses on site due to evaporation) prior to returning the water to its source. This system has a high thermal efficiency, and its operating and capital costs are very low. So, from an economical point of view, the open-cycle is preferred to closed-cycle system, especially if there are no water limitations or environmental restrictions. In a recirculating system (or closed-cycle), cooling water exits the condenser, goes through a fixed heat sink, and is then returned to the condenser. This configuration
Di Lorenzo, Flaviana; Silipo, Alba; Molinaro, Antonio; Parrilli, Michelangelo; Schiraldi, Chiara; D'Agostino, Antonella; Izzo, Elisabetta; Rizza, Luisa; Bonina, Andrea; Bonina, Francesco; Lanzetta, Rosa
2017-02-10
The Opuntia ficus-indica multiple properties are reflected in the increasing interest of chemists in the identification of its natural components having pharmaceutical and/or cosmetical applications. Here we report the structural elucidation of Opuntia ficus-indica mucilage that highlighted the presence of components differing for their chemical nature and the molecular weight distribution. The high molecular weight components were identified as a linear galactan polymer and a highly branched xyloarabinan. The low molecular weight components were identified as lactic acid, D-mannitol, piscidic, eucomic and 2-hydroxy-4-(4'-hydroxyphenyl)-butanoic acids. A wound healing assay was performed in order to test the cicatrizing properties of the various components, highlighting the ability of these latter to fasten dermal regeneration using a simplified in vitro cellular model based on a scratched keratinocytes monolayer. The results showed that the whole Opuntia mucilage and the low molecular weight components are active in the wound repair. Copyright © 2016 Elsevier Ltd. All rights reserved.
Time-Weighted Balanced Stochastic Model Reduction
DEFF Research Database (Denmark)
Tahavori, Maryamsadat; Shaker, Hamid Reza
2011-01-01
A new relative error model reduction technique for linear time invariant (LTI) systems is proposed in this paper. Both continuous and discrete time systems can be reduced within this framework. The proposed model reduction method is mainly based upon time-weighted balanced truncation and a recently...
Tweaking the Four-Component Model
Curzer, Howard J.
2014-01-01
By maintaining that moral functioning depends upon four components (sensitivity, judgment, motivation, and character), the Neo-Kohlbergian account of moral functioning allows for uneven moral development within individuals. However, I argue that the four-component model does not go far enough. I offer a more accurate account of moral functioning…
Pump Component Model in SPACE Code
International Nuclear Information System (INIS)
Kim, Byoung Jae; Kim, Kyoung Doo
2010-08-01
This technical report describes the pump component model in SPACE code. A literature survey was made on pump models in existing system codes. The models embedded in SPACE code were examined to check the confliction with intellectual proprietary rights. Design specifications, computer coding implementation, and test results are included in this report
Overview of the model component in ECOCLIM
DEFF Research Database (Denmark)
Geels, Camilla; Boegh, Eva; Bendtsen, J
and atmospheric models. We will use the model system to 1) quantify the potential effects of climate change on ecosystem exchange of GHG and 2) estimate the impacts of changes in management practices including land use change and nitrogen (N) loads. Here the various model components will be introduced...
Gettens, Katelyn M; Gorin, Amy A
2017-10-01
Weight loss maintenance is a complex, multifaceted process that presents a significant challenge for most individuals who lose weight. A growing body of literature indicates a strong relationship between cognitive dysfunction and excessive body weight, and suggests that a subset of high-order cognitive processes known as executive functions (EF) likely play an important role in weight management. Recent reviews cover neuropsychological correlates of weight status yet fail to address the role of executive function in the central dilemma of successful weight loss maintenance. In this paper, we provide an overview of the existing literature examining executive functions as they relate to weight status and initial weight loss. Further, we propose a novel conceptual model of the relationships between EF, initial weight loss, and weight loss maintenance, mapping specific executive functions onto strategies known to be associated with both phases of the weight control process. Implications for the development of more efficacious weight loss maintenance interventions are discussed.
Directory of Open Access Journals (Sweden)
Muhammad Cahyadi
2016-01-01
Full Text Available Quantitative trait locus (QTL is a particular region of the genome containing one or more genes associated with economically important quantitative traits. This study was conducted to identify QTL regions for body weight and growth traits in purebred Korean native chicken (KNC. F1 samples (n = 595 were genotyped using 127 microsatellite markers and 8 single nucleotide polymorphisms that covered 2,616.1 centi Morgan (cM of map length for 26 autosomal linkage groups. Body weight traits were measured every 2 weeks from hatch to 20 weeks of age. Weight of half carcass was also collected together with growth rate. A multipoint variance component linkage approach was used to identify QTLs for the body weight traits. Two significant QTLs for growth were identified on chicken chromosome 3 (GGA3 for growth 16 to18 weeks (logarithm of the odds [LOD] = 3.24, Nominal p value = 0.0001 and GGA4 for growth 6 to 8 weeks (LOD = 2.88, Nominal p value = 0.0003. Additionally, one significant QTL and three suggestive QTLs were detected for body weight traits in KNC; significant QTL for body weight at 4 weeks (LOD = 2.52, nominal p value = 0.0007 and suggestive QTL for 8 weeks (LOD = 1.96, Nominal p value = 0.0027 were detected on GGA4; QTLs were also detected for two different body weight traits: body weight at 16 weeks on GGA3 and body weight at 18 weeks on GGA19. Additionally, two suggestive QTLs for carcass weight were detected at 0 and 70 cM on GGA19. In conclusion, the current study identified several significant and suggestive QTLs that affect growth related traits in a unique resource pedigree in purebred KNC. This information will contribute to improving the body weight traits in native chicken breeds, especially for the Asian native chicken breeds.
Attentional weights in vision as products of spatial and nonspatial components
DEFF Research Database (Denmark)
Nordfang, Maria; Staugaard, Camilla; Bundesen, Claus
2018-01-01
The relationship between visual attentional selection of items in particular spatial locations and selection by nonspatial criteria was investigated in a partial report experiment with report of letters (as many as possible) from brief postmasked exposures of circular arrays of letters and digits....... The data were fitted by mathematical models based on Bundesen's (Psychological Review, 97, 523-547, 1990) theory of visual attention (TVA). Both attentional weights of targets (letters) and attentional weights of distractors (digits) showed strong variations across the eight possible target locations......, but for each of the ten participants, the ratio of the weight of a distractor at a given location to the weight of a target at the same location was approximately constant. The results were accommodated by revising the weight equation of TVA such that the attentional weight of an object equals a product...
Health status monitoring for ICU patients based on locally weighted principal component analysis.
Ding, Yangyang; Ma, Xin; Wang, Youqing
2018-03-01
Intelligent status monitoring for critically ill patients can help medical stuff quickly discover and assess the changes of disease and then make appropriate treatment strategy. However, general-type monitoring model now widely used is difficult to adapt the changes of intensive care unit (ICU) patients' status due to its fixed pattern, and a more robust, efficient and fast monitoring model should be developed to the individual. A data-driven learning approach combining locally weighted projection regression (LWPR) and principal component analysis (PCA) is firstly proposed and applied to monitor the nonlinear process of patients' health status in ICU. LWPR is used to approximate the complex nonlinear process with local linear models, in which PCA could be further applied to status monitoring, and finally a global weighted statistic will be acquired for detecting the possible abnormalities. Moreover, some improved versions are developed, such as LWPR-MPCA and LWPR-JPCA, which also have superior performance. Eighteen subjects were selected from the Physiobank's Multi-parameter Intelligent Monitoring for Intensive Care II (MIMIC II) database, and two vital signs of each subject were chosen for online monitoring. The proposed method was compared with several existing methods including traditional PCA, Partial least squares (PLS), just in time learning combined with modified PCA (L-PCA), and Kernel PCA (KPCA). The experimental results demonstrated that the mean fault detection rate (FDR) of PCA can be improved by 41.7% after adding LWPR. The mean FDR of LWPR-MPCA was increased by 8.3%, compared with the latest reported method L-PCA. Meanwhile, LWPR spent less training time than others, especially KPCA. LWPR is first introduced into ICU patients monitoring and achieves the best monitoring performance including adaptability to changes in patient status, sensitivity for abnormality detection as well as its fast learning speed and low computational complexity. The algorithm
Probabilistic Modeling of Wind Turbine Drivetrain Components
DEFF Research Database (Denmark)
Rafsanjani, Hesam Mirzaei
Wind energy is one of several energy sources in the world and a rapidly growing industry in the energy sector. When placed in offshore or onshore locations, wind turbines are exposed to wave excitations, highly dynamic wind loads and/or the wakes from other wind turbines. Therefore, most components...... in a wind turbine experience highly dynamic and time-varying loads. These components may fail due to wear or fatigue, and this can lead to unplanned shutdown repairs that are very costly. The design by deterministic methods using safety factors is generally unable to account for the many uncertainties. Thus......, a reliability assessment should be based on probabilistic methods where stochastic modeling of failures is performed. This thesis focuses on probabilistic models and the stochastic modeling of the fatigue life of the wind turbine drivetrain. Hence, two approaches are considered for stochastic modeling...
Modeling accelerator structures and RF components
International Nuclear Information System (INIS)
Ko, K., Ng, C.K.; Herrmannsfeldt, W.B.
1993-03-01
Computer modeling has become an integral part of the design and analysis of accelerator structures RF components. Sophisticated 3D codes, powerful workstations and timely theory support all contributed to this development. We will describe our modeling experience with these resources and discuss their impact on ongoing work at SLAC. Specific examples from R ampersand D on a future linear collide and a proposed e + e - storage ring will be included
A principal components model of soundscape perception.
Axelsson, Östen; Nilsson, Mats E; Berglund, Birgitta
2010-11-01
There is a need for a model that identifies underlying dimensions of soundscape perception, and which may guide measurement and improvement of soundscape quality. With the purpose to develop such a model, a listening experiment was conducted. One hundred listeners measured 50 excerpts of binaural recordings of urban outdoor soundscapes on 116 attribute scales. The average attribute scale values were subjected to principal components analysis, resulting in three components: Pleasantness, eventfulness, and familiarity, explaining 50, 18 and 6% of the total variance, respectively. The principal-component scores were correlated with physical soundscape properties, including categories of dominant sounds and acoustic variables. Soundscape excerpts dominated by technological sounds were found to be unpleasant, whereas soundscape excerpts dominated by natural sounds were pleasant, and soundscape excerpts dominated by human sounds were eventful. These relationships remained after controlling for the overall soundscape loudness (Zwicker's N(10)), which shows that 'informational' properties are substantial contributors to the perception of soundscape. The proposed principal components model provides a framework for future soundscape research and practice. In particular, it suggests which basic dimensions are necessary to measure, how to measure them by a defined set of attribute scales, and how to promote high-quality soundscapes.
Shaikh, Alauddin; Mallick, Nazrul Islam
2012-11-01
Introduction: The aim of this study was to find out the effects of plyometrics training and weight training among university male students.Procedure: 60 male students from the different colleges of the Burdwan University were randomly selected as subjects and their age were 19-25 years served as Weight training Group (WTG), second group served as Plyometric Training Group (PTG) and the third group served as Control Group (CT). Eight weeks weight training and six weeks plyometric training were given for experiment accordingly. The control group was not given any training except of their routine. The selected subjects were measured of their motor ability components, speed, endurance, explosive power and agility. ANCOVA was calculation for statistical treatment.Finding: Plyometric training and weight training groups significantly increase speed, endurance, explosive power and agility.Conclusion: The plyometric training has significantly improved speed, explosive power, muscular endurance and agility. The weight training programme has significantly improved agility, muscular endurance, and explosive power. The plometric training is superior to weight training in improving explosive power, agility and muscular endurance.
Thermochemical modelling of multi-component systems
International Nuclear Information System (INIS)
Sundman, B.; Gueneau, C.
2015-01-01
Computational thermodynamic, also known as the Calphad method, is a standard tool in industry for the development of materials and improving processes and there is an intense scientific development of new models and databases. The calculations are based on thermodynamic models of the Gibbs energy for each phase as a function of temperature, pressure and constitution. Model parameters are stored in databases that are developed in an international scientific collaboration. In this way, consistent and reliable data for many properties like heat capacity, chemical potentials, solubilities etc. can be obtained for multi-component systems. A brief introduction to this technique is given here and references to more extensive documentation are provided. (authors)
Independent Component Analysis in Multimedia Modeling
DEFF Research Database (Denmark)
Larsen, Jan
2003-01-01
largely refers to text, images/video, audio and combinations of such data. We review a number of applications within single and combined media with the hope that this might provide inspiration for further research in this area. Finally, we provide a detailed presentation of our own recent work on modeling......Modeling of multimedia and multimodal data becomes increasingly important with the digitalization of the world. The objective of this paper is to demonstrate the potential of independent component analysis and blind sources separation methods for modeling and understanding of multimedia data, which...
PCA: Principal Component Analysis for spectra modeling
Hurley, Peter D.; Oliver, Seb; Farrah, Duncan; Wang, Lingyu; Efstathiou, Andreas
2012-07-01
The mid-infrared spectra of ultraluminous infrared galaxies (ULIRGs) contain a variety of spectral features that can be used as diagnostics to characterize the spectra. However, such diagnostics are biased by our prior prejudices on the origin of the features. Moreover, by using only part of the spectrum they do not utilize the full information content of the spectra. Blind statistical techniques such as principal component analysis (PCA) consider the whole spectrum, find correlated features and separate them out into distinct components. This code, written in IDL, classifies principal components of IRS spectra to define a new classification scheme using 5D Gaussian mixtures modelling. The five PCs and average spectra for the four classifications to classify objects are made available with the code.
Directory of Open Access Journals (Sweden)
S. Roy
2013-12-01
Full Text Available The present investigation is an experimental approach to deposit electroless Ni-P-W coating on mild steel substrate and find out the optimum combination of various tribological performances on the basis of minimum friction and wear, using weighted principal component analysis (WPCA. In this study three main tribological parameters are chosen viz. load (A, speed (B and time(C. The responses are coefficient of friction and wear depth. Here Weighted Principal Component Analysis (WPCA method is adopted to convert the multi-responses into single performance index called multiple performance index (MPI and Taguchi L27 orthogonal array is used to design the experiment and to find the optimum combination of tribological parameters for minimum coefficient of friction and wear depth. ANOVA is performed to find the significance of the each tribological process parameters and their interactions. The EDX analysis, SEM and XRD are performed to study the composition and structural aspects.
Subsidence of a cementless femoral component influenced by body weight and body mass index.
Stihsen, Christoph; Radl, Roman; Keshmiri, Armin; Rehak, Peter; Windhager, Reinhard
2012-05-01
This trial was designed to evaluate the impact of physical characteristics such as body mass index, body weight and height on distal stem migration of a cementless femoral component, as the influence of obesity on the outcome of THA is still debated in literature and conflicting results have been found. In this retrospective cohort study, migration patterns for 102 implants were analysed using the Einzel-Bild-Roentgen-Analyse (EBRA-FCA, femoral component analysis). In all cases the Vision 2000 stem was implanted and combined with the Duraloc acetabular component (DePuy, Warsaw, Indiana). The mean follow-up was 93 months. EBRA-FCA evaluations revealed a mean subsidence of 1.38 mm after two years, 2.06 mm after five and 2.24 mm after seven years. Five stems loosened aseptically. Correlation between increased migration over the whole period and aseptic loosening was highly significant (p < 0.001). Surgical technique had a significant influence on migration and stem stability (p = 0.002) but physical patient characteristics such as body weight over 75 kg and height over 165 cm also significantly influenced stem subsidence towards progressive migration (p = 0.001, p < 0.001). However, a high BMI did not trigger progressive stem migration (p = 0.87). Being of the male gender raised the odds for increased migration (p = 0.03). Physical characteristics such as body weight and height showed significant influence on migration patterns of this cementless femoral component. The operating surgeon should be aware that body weight above 75 kg and height over 165 cm may trigger increased stem migration and the surgeon should aim to fit these prostheses as tightly as possible. However this study demonstrates that a high BMI does not trigger progressive stem migration. Further investigations are needed to confirm our findings.
Lessells, C.M.; Dingemanse, N.J.; Both, C.; Blem, C.
2002-01-01
We collected 328 freshly laid Great Tit (Parus major) eggs from 38 clutches in 1999 to determine the relationship of whole egg weight, wet yolk weight, wet albumen weight, dry shell weight, and the occurrence of laying gaps with mean ambient temperature in the three days preceding laying, while
Lessells, C.M.; Dingemanse, N.J.; Both, C.
2002-01-01
We collected 328 freshly laid Great Tit (Parus major) eggs from 38 clutches in 1999 to determine the relationship of whole egg weight, wet yolk weight, wet albumen weight, dry shell weight, and the occurrence of laying gaps with mean ambient temperature in the three days preceding laying, while
Pool scrubbing models for iodine components
Energy Technology Data Exchange (ETDEWEB)
Fischer, K [Battelle Ingenieurtechnik GmbH, Eschborn (Germany)
1996-12-01
Pool scrubbing is an important mechanism to retain radioactive fission products from being carried into the containment atmosphere or into the secondary piping system. A number of models and computer codes has been developed to predict the retention of aerosols and fission product vapours that are released from the core and injected into water pools of BWR and PWR type reactors during severe accidents. Important codes in this field are BUSCA, SPARC and SUPRA. The present paper summarizes the models for scrubbing of gaseous Iodine components in these codes, discusses the experimental validation, and gives an assessment of the state of knowledge reached and the open questions which persist. The retention of gaseous Iodine components is modelled by the various codes in a very heterogeneous manner. Differences show up in the chemical species considered, the treatment of mass transfer boundary layers on the gaseous and liquid sides, the gas-liquid interface geometry, calculation of equilibrium concentrations and numerical procedures. Especially important is the determination of the pool water pH value. This value is affected by basic aerosols deposited in the water, e.g. Cesium and Rubidium compounds. A consistent model requires a mass balance of these compounds in the pool, thus effectively coupling the pool scrubbing phenomena of aerosols and gaseous Iodine species. Since the water pool conditions are also affected by drainage flow of condensate water from different regions in the containment, and desorption of dissolved gases on the pool surface is determined by the gas concentrations above the pool, some basic limitations of specialized pool scrubbing codes are given. The paper draws conclusions about the necessity of coupling between containment thermal-hydraulics and pool scrubbing models, and proposes ways of further simulation model development in order to improve source term predictions. (author) 2 tabs., refs.
Pool scrubbing models for iodine components
International Nuclear Information System (INIS)
Fischer, K.
1996-01-01
Pool scrubbing is an important mechanism to retain radioactive fission products from being carried into the containment atmosphere or into the secondary piping system. A number of models and computer codes has been developed to predict the retention of aerosols and fission product vapours that are released from the core and injected into water pools of BWR and PWR type reactors during severe accidents. Important codes in this field are BUSCA, SPARC and SUPRA. The present paper summarizes the models for scrubbing of gaseous Iodine components in these codes, discusses the experimental validation, and gives an assessment of the state of knowledge reached and the open questions which persist. The retention of gaseous Iodine components is modelled by the various codes in a very heterogeneous manner. Differences show up in the chemical species considered, the treatment of mass transfer boundary layers on the gaseous and liquid sides, the gas-liquid interface geometry, calculation of equilibrium concentrations and numerical procedures. Especially important is the determination of the pool water pH value. This value is affected by basic aerosols deposited in the water, e.g. Cesium and Rubidium compounds. A consistent model requires a mass balance of these compounds in the pool, thus effectively coupling the pool scrubbing phenomena of aerosols and gaseous Iodine species. Since the water pool conditions are also affected by drainage flow of condensate water from different regions in the containment, and desorption of dissolved gases on the pool surface is determined by the gas concentrations above the pool, some basic limitations of specialized pool scrubbing codes are given. The paper draws conclusions about the necessity of coupling between containment thermal-hydraulics and pool scrubbing models, and proposes ways of further simulation model development in order to improve source term predictions. (author) 2 tabs., refs
Variance components for direct and maternal effects on body weights of Katahdin lambs
The aim of this study was to estimate genetic parameters for BW in Katahdin lambs. Six animal models were used to study direct and maternal effects on birth (BWT), weaning (WWT) and postweaning (PWWT) weights using 41,066 BWT, 33,980 WWT, and 22,793 PWWT records collected over 17 yr in 100 flocks. F...
Dalcin, A. T.; Jerome, G. J.; Fitzpatrick, S. L.; Louis, T. A.; Wang, N?Y.; Bennett, W. L.; Durkin, N.; Clark, J. M.; Daumit, G. L.; Appel, L. J.; Coughlin, J. W.
2015-01-01
Summary Background Behavioural weight loss programs are effective first?line treatments for obesity and are recommended by the US Preventive Services Task Force. Gaining an understanding of intervention components that are found helpful by different demographic groups can improve tailoring of weight loss programs. This paper examined the perceived helpfulness of different weight loss program components. Methods Participants (n?=?236) from the active intervention conditions of the Practice?bas...
Computational needs for modelling accelerator components
International Nuclear Information System (INIS)
Hanerfeld, H.
1985-06-01
The particle-in-cell MASK is being used to model several different electron accelerator components. These studies are being used both to design new devices and to understand particle behavior within existing structures. Studies include the injector for the Stanford Linear Collider and the 50 megawatt klystron currently being built at SLAC. MASK is a 2D electromagnetic code which is being used by SLAC both on our own IBM 3081 and on the CRAY X-MP at the NMFECC. Our experience with running MASK illustrates the need for supercomputers to continue work of the kind described. 3 refs., 2 figs
Integration of Simulink Models with Component-based Software Models
DEFF Research Database (Denmark)
Marian, Nicolae
2008-01-01
Model based development aims to facilitate the development of embedded control systems by emphasizing the separation of the design level from the implementation level. Model based design involves the use of multiple models that represent different views of a system, having different semantics...... of abstract system descriptions. Usually, in mechatronics systems, design proceeds by iterating model construction, model analysis, and model transformation. Constructing a MATLAB/Simulink model, a plant and controller behavior is simulated using graphical blocks to represent mathematical and logical...... constraints. COMDES (Component-based Design of Software for Distributed Embedded Systems) is such a component-based system framework developed by the software engineering group of Mads Clausen Institute for Product Innovation (MCI), University of Southern Denmark. Once specified, the software model has...
Optimal design of multi-state weighted k-out-of-n systems based on component design
International Nuclear Information System (INIS)
Li Wei; Zuo, Ming J.
2008-01-01
This paper presents a study on design optimization of multi-state weighted k-out-of-n systems. The studied system reliability model is more general than the traditional k-out-of-n system model. The system and its components are capable of assuming a whole range of performance levels, varying from perfect functioning to complete failure. A utility value corresponding to each state is used to indicate the corresponding performance level. A widely studied reliability optimization problem is the 'component selection problem', which involves selection of components with known reliability and cost characteristics. Less adequately addressed has been the problem of determining system cost and utility based on the relationships between component reliability, cost and utility. This paper addresses this topic. All the optimization problems dealt with in this paper can be categorized as either minimizing the expected total system cost subject to system reliability requirements, or maximizing system reliability subject to total system cost limitation. The resulting optimization problems are too complicated to be solved by traditional optimization approaches; therefore, genetic algorithm (GA) is used to solve them. Our results show that GA is a powerful tool for solving these kinds of problems
Integration of Simulink Models with Component-based Software Models
Directory of Open Access Journals (Sweden)
MARIAN, N.
2008-06-01
Full Text Available Model based development aims to facilitate the development of embedded control systems by emphasizing the separation of the design level from the implementation level. Model based design involves the use of multiple models that represent different views of a system, having different semantics of abstract system descriptions. Usually, in mechatronics systems, design proceeds by iterating model construction, model analysis, and model transformation. Constructing a MATLAB/Simulink model, a plant and controller behavior is simulated using graphical blocks to represent mathematical and logical constructs and process flow, then software code is generated. A Simulink model is a representation of the design or implementation of a physical system that satisfies a set of requirements. A software component-based system aims to organize system architecture and behavior as a means of computation, communication and constraints, using computational blocks and aggregates for both discrete and continuous behavior, different interconnection and execution disciplines for event-based and time-based controllers, and so on, to encompass the demands to more functionality, at even lower prices, and with opposite constraints. COMDES (Component-based Design of Software for Distributed Embedded Systems is such a component-based system framework developed by the software engineering group of Mads Clausen Institute for Product Innovation (MCI, University of Southern Denmark. Once specified, the software model has to be analyzed. One way of doing that is to integrate in wrapper files the model back into Simulink S-functions, and use its extensive simulation features, thus allowing an early exploration of the possible design choices over multiple disciplines. The paper describes a safe translation of a restricted set of MATLAB/Simulink blocks to COMDES software components, both for continuous and discrete behavior, and the transformation of the software system into the S
Can model weighting improve probabilistic projections of climate change?
Energy Technology Data Exchange (ETDEWEB)
Raeisaenen, Jouni; Ylhaeisi, Jussi S. [Department of Physics, P.O. Box 48, University of Helsinki (Finland)
2012-10-15
Recently, Raeisaenen and co-authors proposed a weighting scheme in which the relationship between observable climate and climate change within a multi-model ensemble determines to what extent agreement with observations affects model weights in climate change projection. Within the Third Coupled Model Intercomparison Project (CMIP3) dataset, this scheme slightly improved the cross-validated accuracy of deterministic projections of temperature change. Here the same scheme is applied to probabilistic temperature change projection, under the strong limiting assumption that the CMIP3 ensemble spans the actual modeling uncertainty. Cross-validation suggests that probabilistic temperature change projections may also be improved by this weighting scheme. However, the improvement relative to uniform weighting is smaller in the tail-sensitive logarithmic score than in the continuous ranked probability score. The impact of the weighting on projection of real-world twenty-first century temperature change is modest in most parts of the world. However, in some areas mainly over the high-latitude oceans, the mean of the distribution is substantially changed and/or the distribution is considerably narrowed. The weights of individual models vary strongly with location, so that a model that receives nearly zero weight in some area may still get a large weight elsewhere. Although the details of this variation are method-specific, it suggests that the relative strengths of different models may be difficult to harness by weighting schemes that use spatially uniform model weights. (orig.)
de Roon, Martijn; van Gemert, Willemijn A; Peeters, Petra H; Schuit, A.J.; Monninkhof, Evelyn M
2017-01-01
The aim of this study was to determine the long-term effects of a weight loss intervention with or without an exercise component on body weight and physical activity. Women were randomized to diet (n = 97) or exercise (N = 98) for 16 weeks. During the intervention, both groups had achieved the set
Weighted functional linear regression models for gene-based association analysis.
Belonogova, Nadezhda M; Svishcheva, Gulnara R; Wilson, James F; Campbell, Harry; Axenovich, Tatiana I
2018-01-01
Functional linear regression models are effectively used in gene-based association analysis of complex traits. These models combine information about individual genetic variants, taking into account their positions and reducing the influence of noise and/or observation errors. To increase the power of methods, where several differently informative components are combined, weights are introduced to give the advantage to more informative components. Allele-specific weights have been introduced to collapsing and kernel-based approaches to gene-based association analysis. Here we have for the first time introduced weights to functional linear regression models adapted for both independent and family samples. Using data simulated on the basis of GAW17 genotypes and weights defined by allele frequencies via the beta distribution, we demonstrated that type I errors correspond to declared values and that increasing the weights of causal variants allows the power of functional linear models to be increased. We applied the new method to real data on blood pressure from the ORCADES sample. Five of the six known genes with P models. Moreover, we found an association between diastolic blood pressure and the VMP1 gene (P = 8.18×10-6), when we used a weighted functional model. For this gene, the unweighted functional and weighted kernel-based models had P = 0.004 and 0.006, respectively. The new method has been implemented in the program package FREGAT, which is freely available at https://cran.r-project.org/web/packages/FREGAT/index.html.
International Nuclear Information System (INIS)
Mbagwu, J.S.C.; Chukwu, W.I.E.
1994-06-01
A knowledge of the soil properties influencing the water-stability of soil aggregates is needed for selecting those more easily-determined properties that would be useful in areas where lack of facilities makes its direct determination impossible. In this laboratory study we evaluated the main soil physical, chemical and mineralogical properties influencing the stability of macro aggregates of some Italian surface soils in water. The objective is to select a subset of soil properties which predict optimally, soil aggregate stability. The index of stability used is the mean weight diameter of water-stable aggregates whereas the method of evaluation is the principal component analysis (PCA). The range in coefficients of variation (CV) among the properties was least in the physical (12.0-61.0%), medium in the mineralogical (28.0-116.2%) and highest in the chemical (8.2-110.8%) properties. The wider the range in CV in each subset of properties, the greater the number of components extracted by the PCA. The component defining variables, i.e. those with the highest loadings on each component and therefore, provide the best relationship between the variables and aggregate stability, revealed the ratio of total sand/clay and plastic limit as the significant physical properties. The significant chemical properties are Al 2 O 3 , FeO, MgO and MnO which contribute positively to aggregate stability. Feldspar, quartz and muscovite are the significant mineralogical properties each of which is negatively related to aggregate stability. These soil components are useful for developing empirical models for estimating the stability of aggregates of these soils in water. (author). 38 refs, 7 tabs
Accurate modeling of UV written waveguide components
DEFF Research Database (Denmark)
Svalgaard, Mikael
BPM simulation results of UV written waveguide components that are indistinguishable from measurements can be achieved on the basis of trajectory scan data and an equivalent step index profile that is very easy to measure.......BPM simulation results of UV written waveguide components that are indistinguishable from measurements can be achieved on the basis of trajectory scan data and an equivalent step index profile that is very easy to measure....
Accurate modelling of UV written waveguide components
DEFF Research Database (Denmark)
Svalgaard, Mikael
BPM simulation results of UV written waveguide components that are indistinguishable from measurements can be achieved on the basis of trajectory scan data and an equivalent step index profile that is very easy to measure.......BPM simulation results of UV written waveguide components that are indistinguishable from measurements can be achieved on the basis of trajectory scan data and an equivalent step index profile that is very easy to measure....
Puverel, S; Houlbrèque, F; Tambutté, E; Zoccola, D; Payan, P; Caminiti, N; Tambutté, S; Allemand, D
2007-08-01
Biominerals contain both inorganic and organic components. Organic components are collectively termed the organic matrix, and this matrix has been reported to play a crucial role in mineralization. Several matrix proteins have been characterized in vertebrates, but only a few in invertebrates, primarily in Molluscs and Echinoderms. Methods classically used to extract organic matrix proteins eliminate potential low molecular weight matrix components, since cut-offs ranging from 3.5 to 10 kDa are used to desalt matrix extracts. Consequently, the presence of such components remains unknown and these are never subjected to further analyses. In the present study, we have used microcolonies from the Scleractinian coral Stylophora pistillata to study newly synthesized matrix components by labelling them with 14C-labelled amino acids. Radioactive matrix components were investigated by a method in which both total organic matrix and fractions of matrix below and above 5 kDa were analyzed. Using this method and SDS-PAGE analyses, we were able to detect the presence of low molecular mass matrix components (weight molecules, these probably form the bulk of newly synthesized organic matrix components. Our results suggest that these low molecular weight components may be peptides, which can be involved in the regulation of coral skeleton mineralization.
Asymmetric Gepner models II. Heterotic weight lifting
Energy Technology Data Exchange (ETDEWEB)
Gato-Rivera, B. [NIKHEF Theory Group, Kruislaan 409, 1098 SJ Amsterdam (Netherlands); Instituto de Fisica Fundamental, CSIC, Serrano 123, Madrid 28006 (Spain); Schellekens, A.N., E-mail: t58@nikhef.n [NIKHEF Theory Group, Kruislaan 409, 1098 SJ Amsterdam (Netherlands); Instituto de Fisica Fundamental, CSIC, Serrano 123, Madrid 28006 (Spain); IMAPP, Radboud Universiteit, Nijmegen (Netherlands)
2011-05-21
A systematic study of 'lifted' Gepner models is presented. Lifted Gepner models are obtained from standard Gepner models by replacing one of the N=2 building blocks and the E{sub 8} factor by a modular isomorphic N=0 model on the bosonic side of the heterotic string. The main result is that after this change three family models occur abundantly, in sharp contrast to ordinary Gepner models. In particular, more than 250 new and unrelated moduli spaces of three family models are identified. We discuss the occurrence of fractionally charged particles in these spectra.
Asymmetric Gepner models II. Heterotic weight lifting
International Nuclear Information System (INIS)
Gato-Rivera, B.; Schellekens, A.N.
2011-01-01
A systematic study of 'lifted' Gepner models is presented. Lifted Gepner models are obtained from standard Gepner models by replacing one of the N=2 building blocks and the E 8 factor by a modular isomorphic N=0 model on the bosonic side of the heterotic string. The main result is that after this change three family models occur abundantly, in sharp contrast to ordinary Gepner models. In particular, more than 250 new and unrelated moduli spaces of three family models are identified. We discuss the occurrence of fractionally charged particles in these spectra.
Generalized structured component analysis a component-based approach to structural equation modeling
Hwang, Heungsun
2014-01-01
Winner of the 2015 Sugiyama Meiko Award (Publication Award) of the Behaviormetric Society of Japan Developed by the authors, generalized structured component analysis is an alternative to two longstanding approaches to structural equation modeling: covariance structure analysis and partial least squares path modeling. Generalized structured component analysis allows researchers to evaluate the adequacy of a model as a whole, compare a model to alternative specifications, and conduct complex analyses in a straightforward manner. Generalized Structured Component Analysis: A Component-Based Approach to Structural Equation Modeling provides a detailed account of this novel statistical methodology and its various extensions. The authors present the theoretical underpinnings of generalized structured component analysis and demonstrate how it can be applied to various empirical examples. The book enables quantitative methodologists, applied researchers, and practitioners to grasp the basic concepts behind this new a...
Siregar, M. Fajrul Falah
2015-01-01
Good Performance Student Selection Program of MIN Tanjung Sari aims to increase students interest in learning. The selection is based on determined criterion. To assist the selection process, then a decision support system is needed. The method used is Simple Additive Weighting and Weighted Sum Model. In this research the results of both methods performed will be tested with the three periods of good performance students data possessed by MIN Tanjung Sari Medan Selayang. This s...
The Influence of Normalization Weight in Population Pharmacokinetic Covariate Models.
Goulooze, Sebastiaan C; Völler, Swantje; Välitalo, Pyry A J; Calvier, Elisa A M; Aarons, Leon; Krekels, Elke H J; Knibbe, Catherijne A J
2018-03-23
In covariate (sub)models of population pharmacokinetic models, most covariates are normalized to the median value; however, for body weight, normalization to 70 kg or 1 kg is often applied. In this article, we illustrate the impact of normalization weight on the precision of population clearance (CL pop ) parameter estimates. The influence of normalization weight (70, 1 kg or median weight) on the precision of the CL pop estimate, expressed as relative standard error (RSE), was illustrated using data from a pharmacokinetic study in neonates with a median weight of 2.7 kg. In addition, a simulation study was performed to show the impact of normalization to 70 kg in pharmacokinetic studies with paediatric or obese patients. The RSE of the CL pop parameter estimate in the neonatal dataset was lowest with normalization to median weight (8.1%), compared with normalization to 1 kg (10.5%) or 70 kg (48.8%). Typical clearance (CL) predictions were independent of the normalization weight used. Simulations showed that the increase in RSE of the CL pop estimate with 70 kg normalization was highest in studies with a narrow weight range and a geometric mean weight away from 70 kg. When, instead of normalizing with median weight, a weight outside the observed range is used, the RSE of the CL pop estimate will be inflated, and should therefore not be used for model selection. Instead, established mathematical principles can be used to calculate the RSE of the typical CL (CL TV ) at a relevant weight to evaluate the precision of CL predictions.
3D Weight Matrices in Modeling Real Estate Prices
Mimis, A.
2016-10-01
Central role in spatial econometric models of real estate data has the definition of the weight matrix by which we capture the spatial dependence between the observations. The weight matrices presented in literature so far, treats space in a two dimensional manner leaving out the effect of the third dimension or in our case the difference in height where the property resides. To overcome this, we propose a new definition of the weight matrix including the third dimensional effect by using the Hadamard product. The results illustrated that the level effect can be absorbed into the new weight matrix.
Skill and independence weighting for multi-model assessments
International Nuclear Information System (INIS)
Sanderson, Benjamin M.; Wehner, Michael; Knutti, Reto
2017-01-01
We present a weighting strategy for use with the CMIP5 multi-model archive in the fourth National Climate Assessment, which considers both skill in the climatological performance of models over North America as well as the inter-dependency of models arising from common parameterizations or tuning practices. The method exploits information relating to the climatological mean state of a number of projection-relevant variables as well as metrics representing long-term statistics of weather extremes. The weights, once computed can be used to simply compute weighted means and significance information from an ensemble containing multiple initial condition members from potentially co-dependent models of varying skill. Two parameters in the algorithm determine the degree to which model climatological skill and model uniqueness are rewarded; these parameters are explored and final values are defended for the assessment. The influence of model weighting on projected temperature and precipitation changes is found to be moderate, partly due to a compensating effect between model skill and uniqueness. However, more aggressive skill weighting and weighting by targeted metrics is found to have a more significant effect on inferred ensemble confidence in future patterns of change for a given projection.
Directory of Open Access Journals (Sweden)
Davide Biagini
2011-04-01
Full Text Available To evaluate the effect of sexual neutering and age of castration on empty body weight (EBW components and estimated nitrogen excretion and efficiency, a trial was carried out on 3 groups of double-muscled Piemontese calves: early castrated (EC, 5th month of age, late castrated (LC, 12th month of age and intact males (IM, control group. Animals were fed at the same energy and protein level and slaughtered at 18th month of age. Live and slaughtering performances and EBW components were recorded, whereas N excretion was calculated by difference between diet and weight gain N content. In live and slaughtering performances, IM showed higher final, carcass and total meat weight than EC and LC (P<0.01. In EBW components, IM showed higher blood and head weight than EC and LC (P<0.01 and 0.05 respectively, and differences were found between EC and LC for head weights (P<0.01. IM showed higher body crude protein (BCP than EC and LC (P<0.01 and 0.05 respectively, but BCP/EBW ratio was higher only in IM than EC (P<0.05. Estimated N daily gain was higher in IM than EC and LC (P<0.01. Only LC showed higher excretion than IM (P<0.05, and N efficiency was higher in IM than EC and LC (P<0.05 and 0.01 respectively. In conclusion, for the Piemontese hypertrophied cattle castration significantly increases N excretion (+7% and reduces N efficiency (-15%, leading to a lower level of sustainability.
Counterregulation of insulin by leptin as key component of autonomic regulation of body weight
Borer, Katarina T
2014-01-01
A re-examination of the mechanism controlling eating, locomotion, and metabolism prompts formulation of a new explanatory model containing five features: a coordinating joint role of the (1) autonomic nervous system (ANS); (2) the suprachiasmatic (SCN) master clock in counterbalancing parasympathetic digestive and absorptive functions and feeding with sympathetic locomotor and thermogenic energy expenditure within a circadian framework; (3) interaction of the ANS/SCN command with brain substrates of reward encompassing dopaminergic projections to ventral striatum and limbic and cortical forebrain. These drive the nonhomeostatic feeding and locomotor motivated behaviors in interaction with circulating ghrelin and lateral hypothalamic neurons signaling through melanin concentrating hormone and orexin-hypocretin peptides; (4) counterregulation of insulin by leptin of both gastric and adipose tissue origin through: potentiation by leptin of cholecystokinin-mediated satiation, inhibition of insulin secretion, suppression of insulin lipogenesis by leptin lipolysis, and modulation of peripheral tissue and brain sensitivity to insulin action. Thus weight-loss induced hypoleptimia raises insulin sensitivity and promotes its parasympathetic anabolic actions while obesity-induced hyperleptinemia supresses insulin lipogenic action; and (5) inhibition by leptin of bone mineral accrual suggesting that leptin may contribute to the maintenance of stability of skeletal, lean-body, as well as adipose tissue masses. PMID:25317239
Tritium permeation model for plasma facing components
Longhurst, G. R.
1992-12-01
This report documents the development of a simplified one-dimensional tritium permeation and retention model. The model makes use of the same physical mechanisms as more sophisticated, time-transient codes such as implantation, recombination, diffusion, trapping and thermal gradient effects. It takes advantage of a number of simplifications and approximations to solve the steady-state problem and then provides interpolating functions to make estimates of intermediate states based on the steady-state solution. The model is developed for solution using commercial spread-sheet software such as Lotus 123. Comparison calculations are provided with the verified and validated TMAP4 transient code with good agreement. Results of calculations for the ITER CDA diverter are also included.
Tritium permeation model for plasma facing components
International Nuclear Information System (INIS)
Longhurst, G.R.
1992-12-01
This report documents the development of a simplified one-dimensional tritium permeation and retention model. The model makes use of the same physical mechanisms as more sophisticated, time-transient codes such as implantation, recombination, diffusion, trapping and thermal gradient effects. It takes advantage of a number of simplifications and approximations to solve the steady-state problem and then provides interpolating functions to make estimates of intermediate states based on the steady-state solution. The model is developed for solution using commercial spread-sheet software such as Lotus 123. Comparison calculations are provided with the verified and validated TMAP4 transient code with good agreement. Results of calculations for the ITER CDA diverter are also included
Nitrogen component in nonpoint source pollution models
Pollutants entering a water body can be very destructive to the health of that system. Best Management Practices (BMPs) and/or conservation practices are used to reduce these pollutants, but understanding the most effective practices is very difficult. Watershed models are an effective tool to aid...
Binenbaum, Gil; Ying, Gui-Shuang; Quinn, Graham E; Huang, Jiayan; Dreiseitl, Stephan; Antigua, Jules; Foroughi, Negar; Abbasi, Soraya
2012-12-01
To develop a birth weight (BW), gestational age (GA), and postnatal-weight gain retinopathy of prematurity (ROP) prediction model in a cohort of infants meeting current screening guidelines. Multivariate logistic regression was applied retrospectively to data from infants born with BW less than 1501 g or GA of 30 weeks or less at a single Philadelphia hospital between January 1, 2004, and December 31, 2009. In the model, BW, GA, and daily weight gain rate were used repeatedly each week to predict risk of Early Treatment of Retinopathy of Prematurity type 1 or 2 ROP. If risk was above a cut-point level, examinations would be indicated. Of 524 infants, 20 (4%) had type 1 ROP and received laser treatment; 28 (5%) had type 2 ROP. The model (Children's Hospital of Philadelphia [CHOP]) accurately predicted all infants with type 1 ROP; missed 1 infant with type 2 ROP, who did not require laser treatment; and would have reduced the number of infants requiring examinations by 49%. Raising the cut point to miss one type 1 ROP case would have reduced the need for examinations by 79%. Using daily weight measurements to calculate weight gain rate resulted in slightly higher examination reduction than weekly measurements. The BW-GA-weight gain CHOP ROP model demonstrated accurate ROP risk assessment and a large reduction in the number of ROP examinations compared with current screening guidelines. As a simple logistic equation, it can be calculated by hand or represented as a nomogram for easy clinical use. However, larger studies are needed to achieve a highly precise estimate of sensitivity prior to clinical application.
Models for predicting objective function weights in prostate cancer IMRT
International Nuclear Information System (INIS)
Boutilier, Justin J.; Lee, Taewoo; Craig, Tim; Sharpe, Michael B.; Chan, Timothy C. Y.
2015-01-01
Purpose: To develop and evaluate the clinical applicability of advanced machine learning models that simultaneously predict multiple optimization objective function weights from patient geometry for intensity-modulated radiation therapy of prostate cancer. Methods: A previously developed inverse optimization method was applied retrospectively to determine optimal objective function weights for 315 treated patients. The authors used an overlap volume ratio (OV) of bladder and rectum for different PTV expansions and overlap volume histogram slopes (OVSR and OVSB for the rectum and bladder, respectively) as explanatory variables that quantify patient geometry. Using the optimal weights as ground truth, the authors trained and applied three prediction models: logistic regression (LR), multinomial logistic regression (MLR), and weighted K-nearest neighbor (KNN). The population average of the optimal objective function weights was also calculated. Results: The OV at 0.4 cm and OVSR at 0.1 cm features were found to be the most predictive of the weights. The authors observed comparable performance (i.e., no statistically significant difference) between LR, MLR, and KNN methodologies, with LR appearing to perform the best. All three machine learning models outperformed the population average by a statistically significant amount over a range of clinical metrics including bladder/rectum V53Gy, bladder/rectum V70Gy, and dose to the bladder, rectum, CTV, and PTV. When comparing the weights directly, the LR model predicted bladder and rectum weights that had, on average, a 73% and 74% relative improvement over the population average weights, respectively. The treatment plans resulting from the LR weights had, on average, a rectum V70Gy that was 35% closer to the clinical plan and a bladder V70Gy that was 29% closer, compared to the population average weights. Similar results were observed for all other clinical metrics. Conclusions: The authors demonstrated that the KNN and MLR
Models for predicting objective function weights in prostate cancer IMRT
Energy Technology Data Exchange (ETDEWEB)
Boutilier, Justin J., E-mail: j.boutilier@mail.utoronto.ca; Lee, Taewoo [Department of Mechanical and Industrial Engineering, University of Toronto, 5 King’s College Road, Toronto, Ontario M5S 3G8 (Canada); Craig, Tim [Radiation Medicine Program, UHN Princess Margaret Cancer Centre, 610 University of Avenue, Toronto, Ontario M5T 2M9, Canada and Department of Radiation Oncology, University of Toronto, 148 - 150 College Street, Toronto, Ontario M5S 3S2 (Canada); Sharpe, Michael B. [Radiation Medicine Program, UHN Princess Margaret Cancer Centre, 610 University of Avenue, Toronto, Ontario M5T 2M9 (Canada); Department of Radiation Oncology, University of Toronto, 148 - 150 College Street, Toronto, Ontario M5S 3S2 (Canada); Techna Institute for the Advancement of Technology for Health, 124 - 100 College Street, Toronto, Ontario M5G 1P5 (Canada); Chan, Timothy C. Y. [Department of Mechanical and Industrial Engineering, University of Toronto, 5 King’s College Road, Toronto, Ontario M5S 3G8, Canada and Techna Institute for the Advancement of Technology for Health, 124 - 100 College Street, Toronto, Ontario M5G 1P5 (Canada)
2015-04-15
Purpose: To develop and evaluate the clinical applicability of advanced machine learning models that simultaneously predict multiple optimization objective function weights from patient geometry for intensity-modulated radiation therapy of prostate cancer. Methods: A previously developed inverse optimization method was applied retrospectively to determine optimal objective function weights for 315 treated patients. The authors used an overlap volume ratio (OV) of bladder and rectum for different PTV expansions and overlap volume histogram slopes (OVSR and OVSB for the rectum and bladder, respectively) as explanatory variables that quantify patient geometry. Using the optimal weights as ground truth, the authors trained and applied three prediction models: logistic regression (LR), multinomial logistic regression (MLR), and weighted K-nearest neighbor (KNN). The population average of the optimal objective function weights was also calculated. Results: The OV at 0.4 cm and OVSR at 0.1 cm features were found to be the most predictive of the weights. The authors observed comparable performance (i.e., no statistically significant difference) between LR, MLR, and KNN methodologies, with LR appearing to perform the best. All three machine learning models outperformed the population average by a statistically significant amount over a range of clinical metrics including bladder/rectum V53Gy, bladder/rectum V70Gy, and dose to the bladder, rectum, CTV, and PTV. When comparing the weights directly, the LR model predicted bladder and rectum weights that had, on average, a 73% and 74% relative improvement over the population average weights, respectively. The treatment plans resulting from the LR weights had, on average, a rectum V70Gy that was 35% closer to the clinical plan and a bladder V70Gy that was 29% closer, compared to the population average weights. Similar results were observed for all other clinical metrics. Conclusions: The authors demonstrated that the KNN and MLR
How Many Separable Sources? Model Selection In Independent Components Analysis
DEFF Research Database (Denmark)
Woods, Roger P.; Hansen, Lars Kai; Strother, Stephen
2015-01-01
among potential model categories with differing numbers of Gaussian components. Based on simulation studies, the assumptions and approximations underlying the Akaike Information Criterion do not hold in this setting, even with a very large number of observations. Cross-validation is a suitable, though....../Principal Components Analysis (mixed ICA/PCA) model described here accommodates one or more Gaussian components in the independent components analysis model and uses principal components analysis to characterize contributions from this inseparable Gaussian subspace. Information theory can then be used to select from...... might otherwise be questionable. Failure of the Akaike Information Criterion in model selection also has relevance in traditional independent components analysis where all sources are assumed non-Gaussian....
Vehicle Weight in Gipps' Car-Following Model
Nerem, Sebastian
2013-01-01
Car-following models are mathematical models, which describe the situation where vehicles drive behind each other on a single lane road section with no overtaking possibilities. The purpose of the models is to estimate how a vehicle reacts to the behavior of the vehicle ahead. A weakness in these models is that they do not take the weight of each vehicle into account. It can however be shown that a vehicle?s weight affects its driving behavior.The purpose of this master?s thesis is to investi...
Model-integrating software components engineering flexible software systems
Derakhshanmanesh, Mahdi
2015-01-01
In his study, Mahdi Derakhshanmanesh builds on the state of the art in modeling by proposing to integrate models into running software on the component-level without translating them to code. Such so-called model-integrating software exploits all advantages of models: models implicitly support a good separation of concerns, they are self-documenting and thus improve understandability and maintainability and in contrast to model-driven approaches there is no synchronization problem anymore between the models and the code generated from them. Using model-integrating components, software will be
Directory of Open Access Journals (Sweden)
Gayo Willy
2016-01-01
Full Text Available Philippine Stock Exchange Composite Index (PSEi is the main stock index of the Philippine Stock Exchange (PSE. PSEi is computed using a weighted mean of the top 30 publicly traded companies in the Philippines, called component stocks. It provides a single value by which the performance of the Philippine stock market is measured. Unfortunately, these weights, which may vary for every trading day, are not disclosed by the PSE. In this paper, we propose a model of forecasting the PSEi by estimating the weights based on historical data and forecasting each component stock using Monte Carlo simulation based on a Geometric Brownian Motion (GBM assumption. The model performance is evaluated and its forecast compared is with the results using a direct GBM forecast of PSEi over different forecast periods. Results showed that the forecasts using WGBM will yield smaller error compared to direct GBM forecast of PSEi.
Modeling money demand components in Lebanon using autoregressive models
International Nuclear Information System (INIS)
Mourad, M.
2008-01-01
This paper analyses monetary aggregate in Lebanon and its different component methodology of AR model. Thirteen variables in monthly data have been studied for the period January 1990 through December 2005. Using the Augmented Dickey-Fuller (ADF) procedure, twelve variables are integrated at order 1, thus they need the filter (1-B)) to become stationary, however the variable X 1 3,t (claims on private sector) becomes stationary with the filter (1-B)(1-B 1 2) . The ex-post forecasts have been calculated for twelve horizons and for one horizon (one-step ahead forecast). The quality of forecasts has been measured using the MAPE criterion for which the forecasts are good because the MAPE values are lower. Finally, a pursuit of this research using the cointegration approach is proposed. (author)
Integration of Simulink Models with Component-based Software Models
DEFF Research Database (Denmark)
Marian, Nicolae; Top, Søren
2008-01-01
, communication and constraints, using computational blocks and aggregates for both discrete and continuous behaviour, different interconnection and execution disciplines for event-based and time-based controllers, and so on, to encompass the demands to more functionality, at even lower prices, and with opposite...... to be analyzed. One way of doing that is to integrate in wrapper files the model back into Simulink S-functions, and use its extensive simulation features, thus allowing an early exploration of the possible design choices over multiple disciplines. The paper describes a safe translation of a restricted set...... of MATLAB/Simulink blocks to COMDES software components, both for continuous and discrete behaviour, and the transformation of the software system into the S-functions. The general aim of this work is the improvement of multi-disciplinary development of embedded systems with the focus on the relation...
Public health component in building information modeling
Trufanov, A. I.; Rossodivita, A.; Tikhomirov, A. A.; Berestneva, O. G.; Marukhina, O. V.
2018-05-01
A building information modelling (BIM) conception has established itself as an effective and practical approach to plan, design, construct, and manage buildings and infrastructure. Analysis of the governance literature has shown that the BIM-developed tools do not take fully into account the growing demands from ecology and health fields. In this connection, it is possible to offer an optimal way of adapting such tools to the necessary consideration of the sanitary and hygienic specifications of materials used in construction industry. It is proposed to do it through the introduction of assessments that meet the requirements of national sanitary standards. This approach was demonstrated in the case study of Revit® program.
Spencer, Lisa; Rollo, Megan; Hauck, Yvonne; MacDonald-Wicks, Lesley; Wood, Lisa; Hutchesson, Melinda; Giglia, Roslyn; Smith, Roger; Collins, Clare
2015-01-01
What are the effects of weight management interventions that include a diet component on weight-related outcomes in pregnant and postpartum women?The primary objective of this systematic review is to evaluate the effectiveness of weight management interventions which include a diet component and are aimed at limiting gestational weight gain and postpartum weight retention in women.The second objective of this systematic review is to investigate included intervention components with respect to effect on weight-related outcomes. This may include, but is not limited to: length of intervention, use of face-to-face counselling, group or individual consultations, use of other interventions components including exercise, use of goals and use of support tools like food diaries, coaching, including email or text message support. Around half of all women of reproductive age are either overweight or obese, with women aged 25-34 years having a greater risk of substantial weight gain compared with men of all ages. Excessive gestational weight gain (GWG) and postpartum weight retention (PPWR) may play a significant role in long term obesity. Having one child doubles the five- and 10-year obesity incidence for women, with many women who gain excessive weight during pregnancy remaining obese permanently. Excessive GWG and/or PPWR can also significantly contribute to short- and long-term adverse health outcomes for mother, baby and future pregnancies.Maternal obesity increases the risk of pregnancy related complications such as pre-eclampsia, gestational diabetes mellitus, stillbirth and the rate of caesarean section. Childhood obesity is a further long term complication of maternal obesity for offspring, which may persist in to adulthood. Excess GWG is also a risk factor for PPWR both in the short and long-term. Nehring et al. conducted a meta-analysis with over 65,000 women showing that, compared to women who gained weight within recommendations during pregnancy, women with GWG
How Many Separable Sources? Model Selection In Independent Components Analysis
Woods, Roger P.; Hansen, Lars Kai; Strother, Stephen
2015-01-01
Unlike mixtures consisting solely of non-Gaussian sources, mixtures including two or more Gaussian components cannot be separated using standard independent components analysis methods that are based on higher order statistics and independent observations. The mixed Independent Components Analysis/Principal Components Analysis (mixed ICA/PCA) model described here accommodates one or more Gaussian components in the independent components analysis model and uses principal components analysis to characterize contributions from this inseparable Gaussian subspace. Information theory can then be used to select from among potential model categories with differing numbers of Gaussian components. Based on simulation studies, the assumptions and approximations underlying the Akaike Information Criterion do not hold in this setting, even with a very large number of observations. Cross-validation is a suitable, though computationally intensive alternative for model selection. Application of the algorithm is illustrated using Fisher's iris data set and Howells' craniometric data set. Mixed ICA/PCA is of potential interest in any field of scientific investigation where the authenticity of blindly separated non-Gaussian sources might otherwise be questionable. Failure of the Akaike Information Criterion in model selection also has relevance in traditional independent components analysis where all sources are assumed non-Gaussian. PMID:25811988
Algorithmic fault tree construction by component-based system modeling
International Nuclear Information System (INIS)
Majdara, Aref; Wakabayashi, Toshio
2008-01-01
Computer-aided fault tree generation can be easier, faster and less vulnerable to errors than the conventional manual fault tree construction. In this paper, a new approach for algorithmic fault tree generation is presented. The method mainly consists of a component-based system modeling procedure an a trace-back algorithm for fault tree synthesis. Components, as the building blocks of systems, are modeled using function tables and state transition tables. The proposed method can be used for a wide range of systems with various kinds of components, if an inclusive component database is developed. (author)
Accessibility to Nodes of Interest: Demographic Weighting the Logistic Model
Directory of Open Access Journals (Sweden)
Gioacchino DE CANDIA
2015-11-01
Full Text Available This research fits into the genre of spatial analysis, aimed at better understanding of population dynamics in relation to the presence and distribution of infrastructure and related services. Specifically, the analysis uses a model of the gravitational type, based on the assumption of the impedance (attractiveness territorial, based on a curve of type logistics to determine the accessibility of the same, to which to add a system of weights. In this sense, the model was weighted according to the population, to determine the level of “population served” in terms of infrastructure and related services included in the model.
Data Driven Broiler Weight Forecasting using Dynamic Neural Network Models
DEFF Research Database (Denmark)
Johansen, Simon Vestergaard; Bendtsen, Jan Dimon; Riisgaard-Jensen, Martin
2017-01-01
In this article, the dynamic influence of environmental broiler house conditions and broiler growth is investigated. Dynamic neural network forecasting models have been trained on farm-scale broiler batch production data from 12 batches from the same house. The model forecasts future broiler weight...... and uses environmental conditions such as heating, ventilation, and temperature along with broiler behavior such as feed and water consumption. Training data and forecasting data is analyzed to explain when the model might fail at generalizing. We present ensemble broiler weight forecasts to day 7, 14, 21...
Efficient transfer of sensitivity information in multi-component models
International Nuclear Information System (INIS)
Abdel-Khalik, Hany S.; Rabiti, Cristian
2011-01-01
In support of adjoint-based sensitivity analysis, this manuscript presents a new method to efficiently transfer adjoint information between components in a multi-component model, whereas the output of one component is passed as input to the next component. Often, one is interested in evaluating the sensitivities of the responses calculated by the last component to the inputs of the first component in the overall model. The presented method has two advantages over existing methods which may be classified into two broad categories: brute force-type methods and amalgamated-type methods. First, the presented method determines the minimum number of adjoint evaluations for each component as opposed to the brute force-type methods which require full evaluation of all sensitivities for all responses calculated by each component in the overall model, which proves computationally prohibitive for realistic problems. Second, the new method treats each component as a black-box as opposed to amalgamated-type methods which requires explicit knowledge of the system of equations associated with each component in order to reach the minimum number of adjoint evaluations. (author)
Newton-Gauss Algorithm of Robust Weighted Total Least Squares Model
Directory of Open Access Journals (Sweden)
WANG Bin
2015-06-01
Full Text Available Based on the Newton-Gauss iterative algorithm of weighted total least squares (WTLS, a robust WTLS (RWTLS model is presented. The model utilizes the standardized residuals to construct the weight factor function and the square root of the variance component estimator with robustness is obtained by introducing the median method. Therefore, the robustness in both the observation and structure spaces can be simultaneously achieved. To obtain standardized residuals, the linearly approximate cofactor propagation law is employed to derive the expression of the cofactor matrix of WTLS residuals. The iterative calculation steps for RWTLS are also described. The experiment indicates that the model proposed in this paper exhibits satisfactory robustness for gross errors handling problem of WTLS, the obtained parameters have no significant difference with the results of WTLS without gross errors. Therefore, it is superior to the robust weighted total least squares model directly constructed with residuals.
Energy Technology Data Exchange (ETDEWEB)
Kutter, R
1981-12-04
Physical theories to inquire lifetime and reliability of mechanical structures or components under multiscale random stress do not exist. Today those dates were examinated e.g. in development of aircrafts and motorcars by fatigue-testing of original components and sections during long terms. Knowing the distributions of stress and material-parameters the same testing is to be realized simulationary on highspeed computers. This study gives methods to reduce the necessary computation time to attending ones even to proof reliability up to R=1-10/sup -9/. These methods were of Monte-Carlo-Simulation with weighted parameters and respect to life-history.
Component based modelling of piezoelectric ultrasonic actuators for machining applications
International Nuclear Information System (INIS)
Saleem, A; Ahmed, N; Salah, M; Silberschmidt, V V
2013-01-01
Ultrasonically Assisted Machining (UAM) is an emerging technology that has been utilized to improve the surface finishing in machining processes such as turning, milling, and drilling. In this context, piezoelectric ultrasonic transducers are being used to vibrate the cutting tip while machining at predetermined amplitude and frequency. However, modelling and simulation of these transducers is a tedious and difficult task. This is due to the inherent nonlinearities associated with smart materials. Therefore, this paper presents a component-based model of ultrasonic transducers that mimics the nonlinear behaviour of such a system. The system is decomposed into components, a mathematical model of each component is created, and the whole system model is accomplished by aggregating the basic components' model. System parameters are identified using Finite Element technique which then has been used to simulate the system in Matlab/SIMULINK. Various operation conditions are tested and performed to demonstrate the system performance
Components in models of learning: Different operationalisations and relations between components
Directory of Open Access Journals (Sweden)
Mirkov Snežana
2013-01-01
Full Text Available This paper provides the presentation of different operationalisations of components in different models of learning. Special emphasis is on the empirical verifications of relations between components. Starting from the research of congruence between learning motives and strategies, underlying the general model of school learning that comprises different approaches to learning, we have analyzed the empirical verifications of factor structure of instruments containing the scales of motives and learning strategies corresponding to these motives. Considering the problems in the conceptualization of the achievement approach to learning, we have discussed the ways of operational sing the goal orientations and exploring their role in using learning strategies, especially within the model of the regulation of constructive learning processes. This model has served as the basis for researching learning styles that are the combination of a large number of components. Complex relations between the components point to the need for further investigation of the constructs involved in various models. We have discussed the findings and implications of the studies of relations between the components involved in different models, especially between learning motives/goals and learning strategies. We have analyzed the role of regulation in the learning process, whose elaboration, as indicated by empirical findings, can contribute to a more precise operationalisation of certain learning components. [Projekat Ministarstva nauke Republike Srbije, br. 47008: Unapređivanje kvaliteta i dostupnosti obrazovanja u procesima modernizacije Srbije i br. 179034: Od podsticanja inicijative, saradnje i stvaralaštva u obrazovanju do novih uloga i identiteta u društvu
Models for integrated components coupled with their EM environment
Ioan, D.; Schilders, W.H.A.; Ciuprina, G.; Meijs, van der N.P.; Schoenmaker, W.
2008-01-01
Abstract: Purpose – The main aim of this study is the modelling of the interaction of on-chip components with their electromagnetic environment. Design/methodology/approach – The integrated circuit is decomposed in passive and active components interconnected by means of terminals and connectors
Model dependence of energy-weighted sum rules
International Nuclear Information System (INIS)
Kirson, M.W.
1977-01-01
The contribution of the nucleon-nucleon interaction to energy-weighted sum rules for electromagnetic multipole transitions is investigated. It is found that only isoscalar electric transitions might have model-independent energy-weighted sum rules. For these transitions, explicit momentum and angular momentum dependence of the nuclear force give rise to corrections to the sum rule which are found to be negligibly small, thus confirming the model independence of these specific sum rules. These conclusions are unaffected by correlation effects. (author)
Feature-based component model for design of embedded systems
Zha, Xuan Fang; Sriram, Ram D.
2004-11-01
An embedded system is a hybrid of hardware and software, which combines software's flexibility and hardware real-time performance. Embedded systems can be considered as assemblies of hardware and software components. An Open Embedded System Model (OESM) is currently being developed at NIST to provide a standard representation and exchange protocol for embedded systems and system-level design, simulation, and testing information. This paper proposes an approach to representing an embedded system feature-based model in OESM, i.e., Open Embedded System Feature Model (OESFM), addressing models of embedded system artifacts, embedded system components, embedded system features, and embedded system configuration/assembly. The approach provides an object-oriented UML (Unified Modeling Language) representation for the embedded system feature model and defines an extension to the NIST Core Product Model. The model provides a feature-based component framework allowing the designer to develop a virtual embedded system prototype through assembling virtual components. The framework not only provides a formal precise model of the embedded system prototype but also offers the possibility of designing variation of prototypes whose members are derived by changing certain virtual components with different features. A case study example is discussed to illustrate the embedded system model.
Pan, Wenjing; Peña, Jorge
2017-10-01
This study examined how exposure to pictures of women with different body sizes (thin, obese), physical attractiveness levels (attractive, unattractive), along with exposure to weight-related messages (pro-anorexia, anti-anorexia) embedded in a fashion website affected female participants' planned behavior toward weight loss. Participants exposed to attractive model pictures showed higher intentions, attitudes, and subjective norms to lose weight compared with unattractive models. Additionally, participants exposed to thin and attractive model pictures indicated the highest attitudes and self-efficacy to lose weight, whereas those exposed to thin and unattractive model pictures indicated the lowest. Furthermore, weight-related messages moderated the effect of model appearance (body size and attractiveness) on controllability of weight-loss activities. However, website pictures' body size differences had no main effects on planned behavior toward weight loss. These effects are discussed in the light of social comparison mechanisms.
Longitudinal functional principal component modelling via Stochastic Approximation Monte Carlo
Martinez, Josue G.; Liang, Faming; Zhou, Lan; Carroll, Raymond J.
2010-01-01
model averaging using a Bayesian formulation. A relatively straightforward reversible jump Markov Chain Monte Carlo formulation has poor mixing properties and in simulated data often becomes trapped at the wrong number of principal components. In order
Modeling The Skeleton Weight of an Adult Caucasian Man.
Avtandilashvili, Maia; Tolmachev, Sergei Y
2018-05-17
The reference value for the skeleton weight of an adult male (10.5 kg) recommended by the International Commission on Radiological Protection in Publication 70 is based on weights of dissected skeletons from 44 individuals, including two U.S. Transuranium and Uranium Registries whole-body donors. The International Commission on Radiological Protection analysis of anatomical data from 31 individuals with known values of body height demonstrated significant correlation between skeleton weight and body height. The corresponding regression equation, Wskel (kg) = -10.7 + 0.119 × H (cm), published in International Commission on Radiological Protection Publication 70 is typically used to estimate the skeleton weight from body height. Currently, the U.S. Transuranium and Uranium Registries holds data on individual bone weights from a total of 40 male whole-body donors, which has provided a unique opportunity to update the International Commission on Radiological Protection skeleton weight vs. body height equation. The original International Commission on Radiological Protection Publication 70 and the new U.S. Transuranium and Uranium Registries data were combined in a set of 69 data points representing a group of 33- to 95-y-old individuals with body heights and skeleton weights ranging from 155 to 188 cm and 6.5 to 13.4 kg, respectively. Data were fitted with a linear least-squares regression. A significant correlation between the two parameters was observed (r = 0.28), and an updated skeleton weight vs. body height equation was derived: Wskel (kg) = -6.5 + 0.093 × H (cm). In addition, a correlation of skeleton weight with multiple variables including body height, body weight, and age was evaluated using multiple regression analysis, and a corresponding fit equation was derived: Wskel (kg) = -0.25 + 0.046 × H (cm) + 0.036 × Wbody (kg) - 0.012 × A (y). These equations will be used to estimate skeleton weights and, ultimately, total skeletal actinide activities for
Dynamic airspace configuration method based on a weighted graph model
Directory of Open Access Journals (Sweden)
Chen Yangzhou
2014-08-01
Full Text Available This paper proposes a new method for dynamic airspace configuration based on a weighted graph model. The method begins with the construction of an undirected graph for the given airspace, where the vertices represent those key points such as airports, waypoints, and the edges represent those air routes. Those vertices are used as the sites of Voronoi diagram, which divides the airspace into units called as cells. Then, aircraft counts of both each cell and of each air-route are computed. Thus, by assigning both the vertices and the edges with those aircraft counts, a weighted graph model comes into being. Accordingly the airspace configuration problem is described as a weighted graph partitioning problem. Then, the problem is solved by a graph partitioning algorithm, which is a mixture of general weighted graph cuts algorithm, an optimal dynamic load balancing algorithm and a heuristic algorithm. After the cuts algorithm partitions the model into sub-graphs, the load balancing algorithm together with the heuristic algorithm transfers aircraft counts to balance workload among sub-graphs. Lastly, airspace configuration is completed by determining the sector boundaries. The simulation result shows that the designed sectors satisfy not only workload balancing condition, but also the constraints such as convexity, connectivity, as well as minimum distance constraint.
DEFF Research Database (Denmark)
Widyas, Nuzul; Jensen, Just; Nielsen, Vivi Hunnicke
Selection experiment was performed for weight gain in 13 generations of outbred mice. A total of 18 lines were included in the experiment. Nine lines were allotted to each of the two treatment diets (19.3 and 5.1 % protein). Within each diet three lines were selected upwards, three lines were...... selected downwards and three lines were kept as controls. Bayesian statistical methods are used to estimate the genetic variance components. Mixed model analysis is modified including mutation effect following the methods by Wray (1990). DIC was used to compare the model. Models including mutation effect...... have better fit compared to the model with only additive effect. Mutation as direct effect contributes 3.18% of the total phenotypic variance. While in the model with interactions between additive and mutation, it contributes 1.43% as direct effect and 1.36% as interaction effect of the total variance...
Robustness of Component Models in Energy System Simulators
DEFF Research Database (Denmark)
Elmegaard, Brian
2003-01-01
During the development of the component-based energy system simulator DNA (Dynamic Network Analysis), several obstacles to easy use of the program have been observed. Some of these have to do with the nature of the program being based on a modelling language, not a graphical user interface (GUI......). Others have to do with the interaction between models of the nature of the substances in an energy system (e.g., fuels, air, flue gas), models of the components in a system (e.g., heat exchangers, turbines, pumps), and the solver for the system of equations. This paper proposes that the interaction...
Option valuation with the simplified component GARCH model
DEFF Research Database (Denmark)
Dziubinski, Matt P.
We introduce the Simplified Component GARCH (SC-GARCH) option pricing model, show and discuss sufficient conditions for non-negativity of the conditional variance, apply it to low-frequency and high-frequency financial data, and consider the option valuation, comparing the model performance...
Integrating environmental component models. Development of a software framework
Schmitz, O.
2014-01-01
Integrated models consist of interacting component models that represent various natural and social systems. They are important tools to improve our understanding of environmental systems, to evaluate cause–effect relationships of human–natural interactions, and to forecast the behaviour of
Energy Technology Data Exchange (ETDEWEB)
Guo, Y. [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Parsons, T. [National Renewable Energy Laboratory (NREL), Golden, CO (United States); King, R. [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Dykes, K. [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Veers, P. [National Renewable Energy Laboratory (NREL), Golden, CO (United States)
2015-06-09
This report summarizes the theory, verification, and validation of a new sizing tool for wind turbine drivetrain components, the Drivetrain Systems Engineering (DriveSE) tool. DriveSE calculates the dimensions and mass properties of the hub, main shaft, main bearing(s), gearbox, bedplate, transformer if up-tower, and yaw system. The level of fi¬ delity for each component varies depending on whether semiempirical parametric or physics-based models are used. The physics-based models have internal iteration schemes based on system constraints and design criteria. Every model is validated against available industry data or finite-element analysis. The verification and validation results show that the models reasonably capture primary drivers for the sizing and design of major drivetrain components.
Pugh, Sarah J; Richardson, Gale A; Hutcheon, Jennifer A; Himes, Katherine P; Brooks, Maria M; Day, Nancy L; Bodnar, Lisa M
2015-11-01
Maternal overweight and obesity affect two-thirds of women of childbearing age and may increase the risk of impaired child cognition. Our objective was to test the hypothesis that high/low gestational weight gain (GWG) and high/low prepregnancy BMI were associated with offspring intelligence quotient (IQ) and executive function at age 10. Mother-infant dyads (n = 763) enrolled in a birth cohort study were followed from early pregnancy to 10 y postpartum. IQ was assessed by trained examiners with the use of the Stanford Binet Intelligence Scale-4th edition. Executive function was assessed by the number of perseverative errors on the Wisconsin Card Sorting Test and time to complete Part B on the Trail Making Test. Self-reported total GWG was converted to gestational-age-standardized GWG z score. Multivariable linear regression and negative binomial regression were used to estimate independent and joint effects of GWG and BMI on outcomes while adjusting for covariates. At enrollment, the majority of women in the Maternal Health Practices and Child Development cohort were unmarried and unemployed, and more than one-half reported their race as black. The mean ± SD GWG z score was -0.5 ± 1.8, and 27% of women had a pregravid BMI ≥ 25. The median (IQR) number of perseverative errors was 23 (17, 29), the mean ± SD time on Part B was 103 ± 42.6 s, and 44% of children had a low average IQ (≤ 89). Maternal obesity was associated with 3.2 lower IQ points (95% CI: -5.6, -0.8) and a slower time to complete the executive function scale Part B (adjusted β: 12.7 s; 95% CI: 2.8, 23 s) compared with offspring of normal-weight mothers. Offspring of mothers whose GWG was >+1 SD, compared with -1 to +1 SD, performed 15 s slower on the executive function task (95% CI: 1.8, 28 s). There was no association between GWG z score and offspring composite IQ score (adjusted β: -0.32; 95% CI: -0.72, 0.10). Prepregnancy BMI did not modify these associations. Although GWG may be important
Directory of Open Access Journals (Sweden)
Mahalingam Vasantha
Full Text Available Tuberculosis still remains a major public health problem even though it is treatable and curable. Weight gain measurement during anti tuberculosis (TB treatment period is an important component to assess the progress of TB patients. In this study, Latent Growth Models (LGMs were implemented in a longitudinal design to predict the change in weight of TB patients who were given three different regimens under randomized controlled clinical trial for anti-TB treatment. Linear and Quadratic LGMs were fitted using Mplus software. The age, sex and treatment response of the TB patients were used as time invariant independent variables of the growth trajectories. The quadratic trend was found to be better in explaining the changes in weight without grouping than the quadratic model for three group comparisons. A significant increase in the change of weight over time was identified while a significant quadratic effect indicated that weights were sustained over time. The growth rate was similar in both the groups. The treatment response had significant association with the growth rate of weight scores of the patients.
International Nuclear Information System (INIS)
Khorasani, R.; Pourmahdian, S.
2007-01-01
The Precise prediction of polypropylene synthesized by heterogeneous Ziegler-Natta catalysts needs good knowledge of parameters affecting on polymerization. molecular weight and molecular weight distribution are among important characteristics of a polymer determining physical-mechanical properties. broadening of molecular weight distribution is an important and well known characteristic of polypropylene synthesized by heterogeneous Ziegler-Natta catalysts, So it is important to understand the origin of broad molecular weight. Two main factors in broadening molecular weight, namely mass transfer resistances and multiplicity of active sites, are discussed in this paper and a model including these factors is presented. Then we calculate molecular weight and molecular weight distribution by the model and compare our results with
Component and system simulation models for High Flux Isotope Reactor
International Nuclear Information System (INIS)
Sozer, A.
1989-08-01
Component models for the High Flux Isotope Reactor (HFIR) have been developed. The models are HFIR core, heat exchangers, pressurizer pumps, circulation pumps, letdown valves, primary head tank, generic transport delay (pipes), system pressure, loop pressure-flow balance, and decay heat. The models were written in FORTRAN and can be run on different computers, including IBM PCs, as they do not use any specific simulation languages such as ACSL or CSMP. 14 refs., 13 figs
Mäkinen, Mauno; Marttunen, Mauri; Komulainen, Erkki; Terevnikov, Viacheslav; Puukko-Viertomies, Leena-Riitta; Aalberg, Veikko; Lindberg, Nina
2015-01-01
The proportion of overweight and obese youths is high. The present study aimed to investigate the development of self-image and its components during a one-year follow-up among non-referred adolescents with excess and normal weight. Furthermore, we separately analyzed the data for girls and boys. Altogether 86 8(th) grades (41 girls and 45 boys) with a relative weight of 26% or more above the median and 91 controls (43 girls and 48 boys) with normal weight participated the follow-up. The Offer Self-Image Questionnaire, Revised (OSIQ-R) was used to assess self-image at baseline and on follow-up. In the OSIQ-R, a low total raw score implies positive adjustment, while a high raw score implies poor adjustment and a negative self-image. The study design was doubly correlated (pairs and time), and a linear mixed model was used in the statistical analysis. In OSIQ-R total scores, a comparative improvement was observed in girls with normal weight. Among these girls, significant change scores compared to zero were seen in impulse control, social functioning, vocational attitudes, self-confidence, self-reliance, body image, sexuality, and ethical values. In girls with excess weight, none of the change scores compared to zero were statistically significant. When the girls with normal and excess weight were compared, the difference in change scores was largest in sexuality and vocational attitudes. Change scores compared to zero were significant in sexuality and idealism for boys with excess weight, and in impulse control, mental health, self-reliance, and sexuality for normal weight boys. When the boys with excess and normal weight were compared, no statistically significant differences emerged in change scores. In mid-adolescent girls, the influence of overweight and obesity on the development of self-image is substantial. Weight management programs directed at overweight adolescent girls should include psychological interventions aiming to diminish self-image distress
A probabilistic model for component-based shape synthesis
Kalogerakis, Evangelos
2012-07-01
We present an approach to synthesizing shapes from complex domains, by identifying new plausible combinations of components from existing shapes. Our primary contribution is a new generative model of component-based shape structure. The model represents probabilistic relationships between properties of shape components, and relates them to learned underlying causes of structural variability within the domain. These causes are treated as latent variables, leading to a compact representation that can be effectively learned without supervision from a set of compatibly segmented shapes. We evaluate the model on a number of shape datasets with complex structural variability and demonstrate its application to amplification of shape databases and to interactive shape synthesis. © 2012 ACM 0730-0301/2012/08-ART55.
A new weighted mean temperature model in China
Liu, Jinghong; Yao, Yibin; Sang, Jizhang
2018-01-01
The Global Positioning System (GPS) has been applied in meteorology to monitor the change of Precipitable Water Vapor (PWV) in atmosphere, transformed from Zenith Wet Delay (ZWD). A key factor in converting the ZWD into the PWV is the weighted mean temperature (Tm), which has a direct impact on the accuracy of the transformation. A number of Bevis-type models, like Tm -Ts and Tm -Ts,Ps type models, have been developed by statistics approaches, and are not able to clearly depict the relationship between Tm and the surface temperature, Ts . A new model for Tm , called weighted mean temperature norm model (abbreviated as norm model), is derived as a function of Ts , the lapse rate of temperature, δ, the tropopause height, htrop , and the radiosonde station height, hs . It is found that Tm is better related to Ts through an intermediate temperature. The small effects of lapse rate can be ignored and the tropopause height be obtained from an empirical model. Then the norm model is reduced to a simplified form, which causes fewer loss of accuracy and needs two inputs, Ts and hs . In site-specific fittings, the norm model performs much better, with RMS values reduced averagely by 0.45 K and the Mean of Absolute Differences (MAD) values by 0.2 K. The norm model is also found more appropriate than the linear models to fit Tm in a large area, not only with the RMS value reduced from 4.3 K to 3.80 K, correlation coefficient R2 increased from 0.84 to 0.88, and MAD decreased from 3.24 K to 2.90 K, but also with the distribution of simplified model values to be more reasonable. The RMS and MAD values of the differences between reference and computed PWVs are reduced by on average 16.3% and 14.27%, respectively, when using the new norm models instead of the linear model.
Individual model evaluation and probabilistic weighting of models
International Nuclear Information System (INIS)
Atwood, C.L.
1994-01-01
This note stresses the importance of trying to assess the accuracy of each model individually. Putting a Bayesian probability distribution on a population of models faces conceptual and practical complications, and apparently can come only after the work of evaluating the individual models. Moreover, the primary issue is open-quotes How good is this modelclose quotes? Therefore, the individual evaluations are first in both chronology and importance. They are not easy, but some ideas are given here on how to perform them
Weighted Low-Rank Approximation of Matrices and Background Modeling
Dutta, Aritra
2018-04-15
We primarily study a special a weighted low-rank approximation of matrices and then apply it to solve the background modeling problem. We propose two algorithms for this purpose: one operates in the batch mode on the entire data and the other one operates in the batch-incremental mode on the data and naturally captures more background variations and computationally more effective. Moreover, we propose a robust technique that learns the background frame indices from the data and does not require any training frames. We demonstrate through extensive experiments that by inserting a simple weight in the Frobenius norm, it can be made robust to the outliers similar to the $\\\\ell_1$ norm. Our methods match or outperform several state-of-the-art online and batch background modeling methods in virtually all quantitative and qualitative measures.
Weighted Low-Rank Approximation of Matrices and Background Modeling
Dutta, Aritra; Li, Xin; Richtarik, Peter
2018-01-01
We primarily study a special a weighted low-rank approximation of matrices and then apply it to solve the background modeling problem. We propose two algorithms for this purpose: one operates in the batch mode on the entire data and the other one operates in the batch-incremental mode on the data and naturally captures more background variations and computationally more effective. Moreover, we propose a robust technique that learns the background frame indices from the data and does not require any training frames. We demonstrate through extensive experiments that by inserting a simple weight in the Frobenius norm, it can be made robust to the outliers similar to the $\\ell_1$ norm. Our methods match or outperform several state-of-the-art online and batch background modeling methods in virtually all quantitative and qualitative measures.
Weighted Distances in Scale-Free Configuration Models
Adriaans, Erwin; Komjáthy, Júlia
2018-01-01
In this paper we study first-passage percolation in the configuration model with empirical degree distribution that follows a power-law with exponent τ \\in (2,3) . We assign independent and identically distributed (i.i.d.) weights to the edges of the graph. We investigate the weighted distance (the length of the shortest weighted path) between two uniformly chosen vertices, called typical distances. When the underlying age-dependent branching process approximating the local neighborhoods of vertices is found to produce infinitely many individuals in finite time—called explosive branching process—Baroni, Hofstad and the second author showed in Baroni et al. (J Appl Probab 54(1):146-164, 2017) that typical distances converge in distribution to a bounded random variable. The order of magnitude of typical distances remained open for the τ \\in (2,3) case when the underlying branching process is not explosive. We close this gap by determining the first order of magnitude of typical distances in this regime for arbitrary, not necessary continuous edge-weight distributions that produce a non-explosive age-dependent branching process with infinite mean power-law offspring distributions. This sequence tends to infinity with the amount of vertices, and, by choosing an appropriate weight distribution, can be tuned to be any growing function that is O(log log n) , where n is the number of vertices in the graph. We show that the result remains valid for the the erased configuration model as well, where we delete loops and any second and further edges between two vertices.
Frequency weighted model predictive control of wind turbine
DEFF Research Database (Denmark)
Klauco, Martin; Poulsen, Niels Kjølstad; Mirzaei, Mahmood
2013-01-01
This work is focused on applying frequency weighted model predictive control (FMPC) on three blade horizontal axis wind turbine (HAWT). A wind turbine is a very complex, non-linear system influenced by a stochastic wind speed variation. The reduced dynamics considered in this work are the rotatio...... predictive controller are presented. Statistical comparison between frequency weighted MPC, standard MPC and baseline PI controller is shown as well.......This work is focused on applying frequency weighted model predictive control (FMPC) on three blade horizontal axis wind turbine (HAWT). A wind turbine is a very complex, non-linear system influenced by a stochastic wind speed variation. The reduced dynamics considered in this work...... are the rotational degree of freedom of the rotor and the tower for-aft movement. The MPC design is based on a receding horizon policy and a linearised model of the wind turbine. Due to the change of dynamics according to wind speed, several linearisation points must be considered and the control design adjusted...
Towards a Component Based Model for Database Systems
Directory of Open Access Journals (Sweden)
Octavian Paul ROTARU
2004-02-01
Full Text Available Due to their effectiveness in the design and development of software applications and due to their recognized advantages in terms of reusability, Component-Based Software Engineering (CBSE concepts have been arousing a great deal of interest in recent years. This paper presents and extends a component-based approach to object-oriented database systems (OODB introduced by us in [1] and [2]. Components are proposed as a new abstraction level for database system, logical partitions of the schema. In this context, the scope is introduced as an escalated property for transactions. Components are studied from the integrity, consistency, and concurrency control perspective. The main benefits of our proposed component model for OODB are the reusability of the database design, including the access statistics required for a proper query optimization, and a smooth information exchange. The integration of crosscutting concerns into the component database model using aspect-oriented techniques is also discussed. One of the main goals is to define a method for the assessment of component composition capabilities. These capabilities are restricted by the component’s interface and measured in terms of adaptability, degree of compose-ability and acceptability level. The above-mentioned metrics are extended from database components to generic software components. This paper extends and consolidates into one common view the ideas previously presented by us in [1, 2, 3].[1] Octavian Paul Rotaru, Marian Dobre, Component Aspects in Object Oriented Databases, Proceedings of the International Conference on Software Engineering Research and Practice (SERP’04, Volume II, ISBN 1-932415-29-7, pages 719-725, Las Vegas, NV, USA, June 2004.[2] Octavian Paul Rotaru, Marian Dobre, Mircea Petrescu, Integrity and Consistency Aspects in Component-Oriented Databases, Proceedings of the International Symposium on Innovation in Information and Communication Technology (ISIICT
Remucal, Christina K; Cory, Rose M; Sander, Michael; McNeill, Kristopher
2012-09-04
Suwannee River fulvic acid (SRFA) was dialyzed through a 100-500 molecular weight cutoff dialysis membrane, and the dialysate and retentate were analyzed by UV-visible absorption and high-resolution Orbitrap mass spectrometry (MS). A significant fraction (36% based on dissolved organic carbon) of SRFA passed through the dialysis membrane. The fraction of SRFA in the dialysate had a different UV-visible absorption spectrum and was enriched in low molecular weight molecules with a more aliphatic composition relative to the initial SRFA solution. Comparison of the SRFA spectra collected by Orbitrap MS and Fourier transform ion cyclotron resonance MS (FT-ICR MS) demonstrated that the mass accuracy of the Orbitrap MS is sufficient for determination of unique molecular formulas of compounds with masses masses detected by Orbitrap MS were found in the 100-200 Da mass range. Many of these low molecular masses corresponded to molecular formulas of previously identified compounds in organic matter, lignin, and plants, and the use of the standard addition method provided an upper concentration estimate of selected target compounds in SRFA. Collectively, these results provide evidence that SRFA contains low molecular weight components that are present individually or in loosely bound assemblies.
Sub-component modeling for face image reconstruction in video communications
Shiell, Derek J.; Xiao, Jing; Katsaggelos, Aggelos K.
2008-08-01
Emerging communications trends point to streaming video as a new form of content delivery. These systems are implemented over wired systems, such as cable or ethernet, and wireless networks, cell phones, and portable game systems. These communications systems require sophisticated methods of compression and error-resilience encoding to enable communications across band-limited and noisy delivery channels. Additionally, the transmitted video data must be of high enough quality to ensure a satisfactory end-user experience. Traditionally, video compression makes use of temporal and spatial coherence to reduce the information required to represent an image. In many communications systems, the communications channel is characterized by a probabilistic model which describes the capacity or fidelity of the channel. The implication is that information is lost or distorted in the channel, and requires concealment on the receiving end. We demonstrate a generative model based transmission scheme to compress human face images in video, which has the advantages of a potentially higher compression ratio, while maintaining robustness to errors and data corruption. This is accomplished by training an offline face model and using the model to reconstruct face images on the receiving end. We propose a sub-component AAM modeling the appearance of sub-facial components individually, and show face reconstruction results under different types of video degradation using a weighted and non-weighted version of the sub-component AAM.
Modeling fabrication of nuclear components: An integrative approach
Energy Technology Data Exchange (ETDEWEB)
Hench, K.W.
1996-08-01
Reduction of the nuclear weapons stockpile and the general downsizing of the nuclear weapons complex has presented challenges for Los Alamos. One is to design an optimized fabrication facility to manufacture nuclear weapon primary components in an environment of intense regulation and shrinking budgets. This dissertation presents an integrative two-stage approach to modeling the casting operation for fabrication of nuclear weapon primary components. The first stage optimizes personnel radiation exposure for the casting operation layout by modeling the operation as a facility layout problem formulated as a quadratic assignment problem. The solution procedure uses an evolutionary heuristic technique. The best solutions to the layout problem are used as input to the second stage - a simulation model that assesses the impact of competing layouts on operational performance. The focus of the simulation model is to determine the layout that minimizes personnel radiation exposures and nuclear material movement, and maximizes the utilization of capacity for finished units.
International Nuclear Information System (INIS)
Gholinezhad, Hadi; Zeinal Hamadani, Ali
2017-01-01
This paper develops a new model for redundancy allocation problem. In this paper, like many recent papers, the choice of the redundancy strategy is considered as a decision variable. But, in our model each subsystem can exploit both active and cold-standby strategies simultaneously. Moreover, the model allows for component mixing such that components of different types may be used in each subsystem. The problem, therefore, boils down to determining the types of components, redundancy levels, and number of active and cold-standby units of each type for each subsystem to maximize system reliability by considering such constraints as available budget, weight, and space. Since RAP belongs to the NP-hard class of optimization problems, a genetic algorithm (GA) is developed for solving the problem. Finally, the performance of the proposed algorithm is evaluated by applying it to a well-known test problem from the literature with relatively satisfactory results. - Highlights: • A new model for the redundancy allocation problem in series–parallel systems is proposed. • The redundancy strategy of each subsystem is considered as a decision variable and can be active, cold-standby or mixed. • Component mixing is allowed, in other words components of any subsystem can be non-identical. • A genetic algorithm is developed for solving the problem. • Computational experiments demonstrate that the new model leads to interesting results.
Modeling cellular networks in fading environments with dominant specular components
Alammouri, Ahmad; Elsawy, Hesham; Salem, Ahmed Sultan; Di Renzo, Marco; Alouini, Mohamed-Slim
2016-01-01
to the Nakagami-m fading in some special cases. However, neither the Rayleigh nor the Nakagami-m accounts for dominant specular components (DSCs) which may appear in realistic fading channels. In this paper, we present a tractable model for cellular networks
Modeling the evaporation of sessile multi-component droplets
Diddens, C.; Kuerten, Johannes G.M.; van der Geld, C.W.M.; Wijshoff, H.M.A.
2017-01-01
We extended a mathematical model for the drying of sessile droplets, based on the lubrication approximation, to binary mixture droplets. This extension is relevant for e.g. inkjet printing applications, where ink consisting of several components are used. The extension involves the generalization of
Incremental principal component pursuit for video background modeling
Rodriquez-Valderrama, Paul A.; Wohlberg, Brendt
2017-03-14
An incremental Principal Component Pursuit (PCP) algorithm for video background modeling that is able to process one frame at a time while adapting to changes in background, with a computational complexity that allows for real-time processing, having a low memory footprint and is robust to translational and rotational jitter.
Do Knowledge-Component Models Need to Incorporate Representational Competencies?
Rau, Martina Angela
2017-01-01
Traditional knowledge-component models describe students' content knowledge (e.g., their ability to carry out problem-solving procedures or their ability to reason about a concept). In many STEM domains, instruction uses multiple visual representations such as graphs, figures, and diagrams. The use of visual representations implies a…
Hybrid time/frequency domain modeling of nonlinear components
DEFF Research Database (Denmark)
Wiechowski, Wojciech Tomasz; Lykkegaard, Jan; Bak, Claus Leth
2007-01-01
This paper presents a novel, three-phase hybrid time/frequency methodology for modelling of nonlinear components. The algorithm has been implemented in the DIgSILENT PowerFactory software using the DIgSILENT Programming Language (DPL), as a part of the work described in [1]. Modified HVDC benchmark...
Data and information needs for WPP testing and component modeling
International Nuclear Information System (INIS)
Kuhn, W.L.
1987-01-01
The modeling task of the Waste Package Program (WPP) is to develop conceptual models that describe the interactions of waste package components with their environment and the interactions among waste package components. The task includes development and maintenance of a database of experimental data, and statistical analyses to fit model coefficients, test the significance of the fits, and propose experimental designs. The modeling task collaborates with experimentalists to apply physicochemical principles to develop the conceptual models, with emphasis on the subsequent mathematical development. The reason for including the modeling task in the predominantly experimental WPP is to keep the modeling of component behavior closely associated with the experimentation. Whenever possible, waste package degradation processes are described in terms of chemical reactions or transport processes. The integration of equations for assumed or calculated repository conditions predicts variations with time in the repository. Within the context of the waste package program, the composition and rate of arrival of brine to the waste package are environmental variables. These define the environment to be simulated or explored during waste package component and interactions testing. The containment period is characterized by rapid changes in temperature, pressure, oxygen fugacity, and salt porosity. Brine migration is expected to be most rapid during this period. The release period is characterized by modest and slowly changing temperatures, high pressure, low oxygen fugacity, and low porosity. The need is to define the scenario within which waste package degradation calculations are to be made and to quantify the rate of arrival and composition of the brine. Appendix contains 4 vugraphs
Sparse Principal Component Analysis in Medical Shape Modeling
DEFF Research Database (Denmark)
Sjöstrand, Karl; Stegmann, Mikkel Bille; Larsen, Rasmus
2006-01-01
Principal component analysis (PCA) is a widely used tool in medical image analysis for data reduction, model building, and data understanding and exploration. While PCA is a holistic approach where each new variable is a linear combination of all original variables, sparse PCA (SPCA) aims...... analysis in medicine. Results for three different data sets are given in relation to standard PCA and sparse PCA by simple thresholding of sufficiently small loadings. Focus is on a recent algorithm for computing sparse principal components, but a review of other approaches is supplied as well. The SPCA...
Directory of Open Access Journals (Sweden)
Newton T. Pégolo
2009-01-01
Full Text Available Genotype by environment interactions (GEI have attracted increasing attention in tropical breeding programs because of the variety of production systems involved. In this work, we assessed GEI in 450-day adjusted weight (W450 Nelore cattle from 366 Brazilian herds by comparing traditional univariate single-environment model analysis (UM and random regression first order reaction norm models for six environmental variables: standard deviations of herd-year (RRMw and herd-year-season-management (RRMw-m groups for mean W450, standard deviations of herd-year (RRMg and herd-year-season-management (RRMg-m groups adjusted for 365-450 days weight gain (G450 averages, and two iterative algorithms using herd-year-season-management group solution estimates from a first RRMw-m and RRMg-m analysis (RRMITw-m and RRMITg-m, respectively. The RRM results showed similar tendencies in the variance components and heritability estimates along environmental gradient. Some of the variation among RRM estimates may have been related to the precision of the predictor and to correlations between environmental variables and the likely components of the weight trait. GEI, which was assessed by estimating the genetic correlation surfaces, had values < 0.5 between extreme environments in all models. Regression analyses showed that the correlation between the expected progeny differences for UM and the corresponding differences estimated by RRM was higher in intermediate and favorable environments than in unfavorable environments (p < 0.0001.
Modeling cellular networks in fading environments with dominant specular components
AlAmmouri, Ahmad
2016-07-26
Stochastic geometry (SG) has been widely accepted as a fundamental tool for modeling and analyzing cellular networks. However, the fading models used with SG analysis are mainly confined to the simplistic Rayleigh fading, which is extended to the Nakagami-m fading in some special cases. However, neither the Rayleigh nor the Nakagami-m accounts for dominant specular components (DSCs) which may appear in realistic fading channels. In this paper, we present a tractable model for cellular networks with generalized two-ray (GTR) fading channel. The GTR fading explicitly accounts for two DSCs in addition to the diffuse components and offers high flexibility to capture diverse fading channels that appear in realistic outdoor/indoor wireless communication scenarios. It also encompasses the famous Rayleigh and Rician fading as special cases. To this end, the prominent effect of DSCs is highlighted in terms of average spectral efficiency. © 2016 IEEE.
Cognitive components underpinning the development of model-based learning.
Potter, Tracey C S; Bryce, Nessa V; Hartley, Catherine A
2017-06-01
Reinforcement learning theory distinguishes "model-free" learning, which fosters reflexive repetition of previously rewarded actions, from "model-based" learning, which recruits a mental model of the environment to flexibly select goal-directed actions. Whereas model-free learning is evident across development, recruitment of model-based learning appears to increase with age. However, the cognitive processes underlying the development of model-based learning remain poorly characterized. Here, we examined whether age-related differences in cognitive processes underlying the construction and flexible recruitment of mental models predict developmental increases in model-based choice. In a cohort of participants aged 9-25, we examined whether the abilities to infer sequential regularities in the environment ("statistical learning"), maintain information in an active state ("working memory") and integrate distant concepts to solve problems ("fluid reasoning") predicted age-related improvements in model-based choice. We found that age-related improvements in statistical learning performance did not mediate the relationship between age and model-based choice. Ceiling performance on our working memory assay prevented examination of its contribution to model-based learning. However, age-related improvements in fluid reasoning statistically mediated the developmental increase in the recruitment of a model-based strategy. These findings suggest that gradual development of fluid reasoning may be a critical component process underlying the emergence of model-based learning. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.
Geographically Weighted Logistic Regression Applied to Credit Scoring Models
Directory of Open Access Journals (Sweden)
Pedro Henrique Melo Albuquerque
Full Text Available Abstract This study used real data from a Brazilian financial institution on transactions involving Consumer Direct Credit (CDC, granted to clients residing in the Distrito Federal (DF, to construct credit scoring models via Logistic Regression and Geographically Weighted Logistic Regression (GWLR techniques. The aims were: to verify whether the factors that influence credit risk differ according to the borrower’s geographic location; to compare the set of models estimated via GWLR with the global model estimated via Logistic Regression, in terms of predictive power and financial losses for the institution; and to verify the viability of using the GWLR technique to develop credit scoring models. The metrics used to compare the models developed via the two techniques were the AICc informational criterion, the accuracy of the models, the percentage of false positives, the sum of the value of false positive debt, and the expected monetary value of portfolio default compared with the monetary value of defaults observed. The models estimated for each region in the DF were distinct in their variables and coefficients (parameters, with it being concluded that credit risk was influenced differently in each region in the study. The Logistic Regression and GWLR methodologies presented very close results, in terms of predictive power and financial losses for the institution, and the study demonstrated viability in using the GWLR technique to develop credit scoring models for the target population in the study.
Models for describing the thermal characteristics of building components
DEFF Research Database (Denmark)
Jimenez, M.J.; Madsen, Henrik
2008-01-01
, for example. For the analysis of these tests, dynamic analysis models and methods are required. However, a wide variety of models and methods exists, and the problem of choosing the most appropriate approach for each particular case is a non-trivial and interdisciplinary task. Knowledge of a large family....... The characteristics of each type of model are highlighted. Some available software tools for each of the methods described will be mentioned. A case study also demonstrating the difference between linear and nonlinear models is considered....... of these approaches may therefore be very useful for selecting a suitable approach for each particular case. This paper presents an overview of models that can be applied for modelling the thermal characteristics of buildings and building components using data from outdoor testing. The choice of approach depends...
Formal Model-Driven Engineering: Generating Data and Behavioural Components
Directory of Open Access Journals (Sweden)
Chen-Wei Wang
2012-12-01
Full Text Available Model-driven engineering is the automatic production of software artefacts from abstract models of structure and functionality. By targeting a specific class of system, it is possible to automate aspects of the development process, using model transformations and code generators that encode domain knowledge and implementation strategies. Using this approach, questions of correctness for a complex, software system may be answered through analysis of abstract models of lower complexity, under the assumption that the transformations and generators employed are themselves correct. This paper shows how formal techniques can be used to establish the correctness of model transformations used in the generation of software components from precise object models. The source language is based upon existing, formal techniques; the target language is the widely-used SQL notation for database programming. Correctness is established by giving comparable, relational semantics to both languages, and checking that the transformations are semantics-preserving.
Longitudinal functional principal component modelling via Stochastic Approximation Monte Carlo
Martinez, Josue G.
2010-06-01
The authors consider the analysis of hierarchical longitudinal functional data based upon a functional principal components approach. In contrast to standard frequentist approaches to selecting the number of principal components, the authors do model averaging using a Bayesian formulation. A relatively straightforward reversible jump Markov Chain Monte Carlo formulation has poor mixing properties and in simulated data often becomes trapped at the wrong number of principal components. In order to overcome this, the authors show how to apply Stochastic Approximation Monte Carlo (SAMC) to this problem, a method that has the potential to explore the entire space and does not become trapped in local extrema. The combination of reversible jump methods and SAMC in hierarchical longitudinal functional data is simplified by a polar coordinate representation of the principal components. The approach is easy to implement and does well in simulated data in determining the distribution of the number of principal components, and in terms of its frequentist estimation properties. Empirical applications are also presented.
A minimal model for two-component dark matter
International Nuclear Information System (INIS)
Esch, Sonja; Klasen, Michael; Yaguna, Carlos E.
2014-01-01
We propose and study a new minimal model for two-component dark matter. The model contains only three additional fields, one fermion and two scalars, all singlets under the Standard Model gauge group. Two of these fields, one fermion and one scalar, are odd under a Z_2 symmetry that renders them simultaneously stable. Thus, both particles contribute to the observed dark matter density. This model resembles the union of the singlet scalar and the singlet fermionic models but it contains some new features of its own. We analyze in some detail its dark matter phenomenology. Regarding the relic density, the main novelty is the possible annihilation of one dark matter particle into the other, which can affect the predicted relic density in a significant way. Regarding dark matter detection, we identify a new contribution that can lead either to an enhancement or to a suppression of the spin-independent cross section for the scalar dark matter particle. Finally, we define a set of five benchmarks models compatible with all present bounds and examine their direct detection prospects at planned experiments. A generic feature of this model is that both particles give rise to observable signals in 1-ton direct detection experiments. In fact, such experiments will be able to probe even a subdominant dark matter component at the percent level.
Evaluation of the RELAP5/MOD3 multidimensional component model
International Nuclear Information System (INIS)
Tomlinson, E.T.; Rens, T.E.; Coffield, R.D.
1994-01-01
Accurate plenum predictions, which are directly related to the mixing models used, are an important plant modeling consideration because of the consequential impact on basic transient performance calculations for the integrated system. The effect of plenum is a time shift between inlet and outlet temperature changes to the particular volume. Perfect mixing, where the total volume interacts instantaneously with the total inlet flow, does not occur because of effects such as inlet/outlet nozzle jetting, flow stratification, nested vortices within the volume and the general three-dimensional velocity distribution of the flow field. The time lag which exists between the inlet and outlet flows impacts the predicted rate of temperature change experienced by various plant system components and this impacts local component analyses which are affected by the rate of temperature change. This study includes a comparison of two-dimensional plenum mixing predictions using CFD-FLOW3D, RELAP5/MOD3 and perfect mixing models. Three different geometries (flat, square and tall) are assessed for scalar transport times using a wide range of inlet velocity and isothermal conditions. In addition, the three geometries were evaluated for low flow conditions with the inlet flow experiencing a large step temperature decrease. A major conclusion from this study is that the RELAP5/MOD3 multidimensional component model appears to be adequately predicting plenum mixing for a wide range of thermal-hydraulic conditions representative of plant transients
Evaluating fugacity models for trace components in landfill gas
Energy Technology Data Exchange (ETDEWEB)
Shafi, Sophie [Integrated Waste Management Centre, Sustainable Systems Department, Building 61, School of Industrial and Manufacturing Science, Cranfield University, Cranfield, Bedfordshire MK43 0AL (United Kingdom); Sweetman, Andrew [Department of Environmental Science, Lancaster University, Lancaster LA1 4YQ (United Kingdom); Hough, Rupert L. [Integrated Waste Management Centre, Sustainable Systems Department, Building 61, School of Industrial and Manufacturing Science, Cranfield University, Cranfield, Bedfordshire MK43 0AL (United Kingdom); Smith, Richard [Integrated Waste Management Centre, Sustainable Systems Department, Building 61, School of Industrial and Manufacturing Science, Cranfield University, Cranfield, Bedfordshire MK43 0AL (United Kingdom); Rosevear, Alan [Science Group - Waste and Remediation, Environment Agency, Reading RG1 8DQ (United Kingdom); Pollard, Simon J.T. [Integrated Waste Management Centre, Sustainable Systems Department, Building 61, School of Industrial and Manufacturing Science, Cranfield University, Cranfield, Bedfordshire MK43 0AL (United Kingdom)]. E-mail: s.pollard@cranfield.ac.uk
2006-12-15
A fugacity approach was evaluated to reconcile loadings of vinyl chloride (chloroethene), benzene, 1,3-butadiene and trichloroethylene in waste with concentrations observed in landfill gas monitoring studies. An evaluative environment derived from fictitious but realistic properties such as volume, composition, and temperature, constructed with data from the Brogborough landfill (UK) test cells was used to test a fugacity approach to generating the source term for use in landfill gas risk assessment models (e.g. GasSim). SOILVE, a dynamic Level II model adapted here for landfills, showed greatest utility for benzene and 1,3-butadiene, modelled under anaerobic conditions over a 10 year simulation. Modelled concentrations of these components (95 300 {mu}g m{sup -3}; 43 {mu}g m{sup -3}) fell within measured ranges observed in gas from landfills (24 300-180 000 {mu}g m{sup -3}; 20-70 {mu}g m{sup -3}). This study highlights the need (i) for representative and time-referenced biotransformation data; (ii) to evaluate the partitioning characteristics of organic matter within waste systems and (iii) for a better understanding of the role that gas extraction rate (flux) plays in producing trace component concentrations in landfill gas. - Fugacity for trace component in landfill gas.
Traceable components of terrestrial carbon storage capacity in biogeochemical models.
Xia, Jianyang; Luo, Yiqi; Wang, Ying-Ping; Hararuk, Oleksandra
2013-07-01
Biogeochemical models have been developed to account for more and more processes, making their complex structures difficult to be understood and evaluated. Here, we introduce a framework to decompose a complex land model into traceable components based on mutually independent properties of modeled biogeochemical processes. The framework traces modeled ecosystem carbon storage capacity (Xss ) to (i) a product of net primary productivity (NPP) and ecosystem residence time (τE ). The latter τE can be further traced to (ii) baseline carbon residence times (τ'E ), which are usually preset in a model according to vegetation characteristics and soil types, (iii) environmental scalars (ξ), including temperature and water scalars, and (iv) environmental forcings. We applied the framework to the Australian Community Atmosphere Biosphere Land Exchange (CABLE) model to help understand differences in modeled carbon processes among biomes and as influenced by nitrogen processes. With the climate forcings of 1990, modeled evergreen broadleaf forest had the highest NPP among the nine biomes and moderate residence times, leading to a relatively high carbon storage capacity (31.5 kg cm(-2) ). Deciduous needle leaf forest had the longest residence time (163.3 years) and low NPP, leading to moderate carbon storage (18.3 kg cm(-2) ). The longest τE in deciduous needle leaf forest was ascribed to its longest τ'E (43.6 years) and small ξ (0.14 on litter/soil carbon decay rates). Incorporation of nitrogen processes into the CABLE model decreased Xss in all biomes via reduced NPP (e.g., -12.1% in shrub land) or decreased τE or both. The decreases in τE resulted from nitrogen-induced changes in τ'E (e.g., -26.7% in C3 grassland) through carbon allocation among plant pools and transfers from plant to litter and soil pools. Our framework can be used to facilitate data model comparisons and model intercomparisons via tracking a few traceable components for all terrestrial carbon
International Nuclear Information System (INIS)
Schwarz, I.
1979-01-01
Twelve human growth hormone (hGH) preparations were studied on analytical polyacrilamide gel electrophoresis with the purpose of evaluating degree of homogeneity of the extracts, the geometric mean radius (R) sup(-) and the molecular weight (MW) of the protein hormone. A standard curve was used for ten proteins of known molecular weight, where the square root of the retardation coefficient (K sub(R)) was plotted against R sup(-). Five isohormones were identified and defined as charge isomers, based on their different relative free mobility and on their similar R sup(-)(1.81-1.97 nm) and MW (20300-26000 d) values. The heterogeneity of all preparations was due to the presence in general of three isohormones. In five preparations, isohormones B, C 1 and C 2 , were predominant. In recent hGH (IEA) preparations by the method of ROOS, the isohormones C 2 , D and E were identified while in an older one, isohormones E and E 1 were detected. From two to five minor components were found in all samples. Moreover the same type of analysis was carried out on several fractions from protein peaks II and III eluting from Sephadex G 100 purification of three hGH (IEA) extracts. The isohormones start to appear in peak II and their relative concentration is in agreement with the peak III profile read at 280 nm. Practically all secondary components were present in peak II and in most of peak III, showing a type of heterogeneity due to hGH polymeric forms and a relatively small presence of contaminants. (Author) [pt
Wang, Tao; He, Bin
2004-03-01
The recognition of mental states during motor imagery tasks is crucial for EEG-based brain computer interface research. We have developed a new algorithm by means of frequency decomposition and weighting synthesis strategy for recognizing imagined right- and left-hand movements. A frequency range from 5 to 25 Hz was divided into 20 band bins for each trial, and the corresponding envelopes of filtered EEG signals for each trial were extracted as a measure of instantaneous power at each frequency band. The dimensionality of the feature space was reduced from 200 (corresponding to 2 s) to 3 by down-sampling of envelopes of the feature signals, and subsequently applying principal component analysis. The linear discriminate analysis algorithm was then used to classify the features, due to its generalization capability. Each frequency band bin was weighted by a function determined according to the classification accuracy during the training process. The present classification algorithm was applied to a dataset of nine human subjects, and achieved a success rate of classification of 90% in training and 77% in testing. The present promising results suggest that the present classification algorithm can be used in initiating a general-purpose mental state recognition based on motor imagery tasks.
Scale modeling flow-induced vibrations of reactor components
International Nuclear Information System (INIS)
Mulcahy, T.M.
1982-06-01
Similitude relationships currently employed in the design of flow-induced vibration scale-model tests of nuclear reactor components are reviewed. Emphasis is given to understanding the origins of the similitude parameters as a basis for discussion of the inevitable distortions which occur in design verification testing of entire reactor systems and in feature testing of individual component designs for the existence of detrimental flow-induced vibration mechanisms. Distortions of similitude parameters made in current test practice are enumerated and selected example tests are described. Also, limitations in the use of specific distortions in model designs are evaluated based on the current understanding of flow-induced vibration mechanisms and structural response
Model of community emergence in weighted social networks
Kumpula, J. M.; Onnela, J.-P.; Saramäki, J.; Kertész, J.; Kaski, K.
2009-04-01
Over the years network theory has proven to be rapidly expanding methodology to investigate various complex systems and it has turned out to give quite unparalleled insight to their structure, function, and response through data analysis, modeling, and simulation. For social systems in particular the network approach has empirically revealed a modular structure due to interplay between the network topology and link weights between network nodes or individuals. This inspired us to develop a simple network model that could catch some salient features of mesoscopic community and macroscopic topology formation during network evolution. Our model is based on two fundamental mechanisms of network sociology for individuals to find new friends, namely cyclic closure and focal closure, which are mimicked by local search-link-reinforcement and random global attachment mechanisms, respectively. In addition we included to the model a node deletion mechanism by removing all its links simultaneously, which corresponds for an individual to depart from the network. Here we describe in detail the implementation of our model algorithm, which was found to be computationally efficient and produce many empirically observed features of large-scale social networks. Thus this model opens a new perspective for studying such collective social phenomena as spreading, structure formation, and evolutionary processes.
Two-component mixture cure rate model with spline estimated nonparametric components.
Wang, Lu; Du, Pang; Liang, Hua
2012-09-01
In some survival analysis of medical studies, there are often long-term survivors who can be considered as permanently cured. The goals in these studies are to estimate the noncured probability of the whole population and the hazard rate of the susceptible subpopulation. When covariates are present as often happens in practice, to understand covariate effects on the noncured probability and hazard rate is of equal importance. The existing methods are limited to parametric and semiparametric models. We propose a two-component mixture cure rate model with nonparametric forms for both the cure probability and the hazard rate function. Identifiability of the model is guaranteed by an additive assumption that allows no time-covariate interactions in the logarithm of hazard rate. Estimation is carried out by an expectation-maximization algorithm on maximizing a penalized likelihood. For inferential purpose, we apply the Louis formula to obtain point-wise confidence intervals for noncured probability and hazard rate. Asymptotic convergence rates of our function estimates are established. We then evaluate the proposed method by extensive simulations. We analyze the survival data from a melanoma study and find interesting patterns for this study. © 2011, The International Biometric Society.
Modelling raster-based monthly water balance components for Europe
Energy Technology Data Exchange (ETDEWEB)
Ulmen, C.
2000-11-01
The terrestrial runoff component is a comparatively small but sensitive and thus significant quantity in the global energy and water cycle at the interface between landmass and atmosphere. As opposed to soil moisture and evapotranspiration which critically determine water vapour fluxes and thus water and energy transport, it can be measured as an integrated quantity over a large area, i.e. the river basin. This peculiarity makes terrestrial runoff ideally suited for the calibration, verification and validation of general circulation models (GCMs). Gauging stations are not homogeneously distributed in space. Moreover, time series are not necessarily continuously measured nor do they in general have overlapping time periods. To overcome this problems with regard to regular grid spacing used in GCMs, different methods can be applied to transform irregular data to regular so called gridded runoff fields. The present work aims to directly compute the gridded components of the monthly water balance (including gridded runoff fields) for Europe by application of the well-established raster-based macro-scale water balance model WABIMON used at the Federal Institute of Hydrology, Germany. Model calibration and validation is performed by separated examination of 29 representative European catchments. Results indicate a general applicability of the model delivering reliable overall patterns and integrated quantities on a monthly basis. For time steps less then too weeks further research and structural improvements of the model are suggested. (orig.)
Zhang, Shengyong
2017-07-01
Spot welding has been widely used for vehicle body construction due to its advantages of high speed and adaptability for automation. An effort to increase the stiffness-to-weight ratio of spot-welded structures is investigated based upon nonlinear finite element analysis. Topology optimization is conducted for reducing weight in the overlapping regions by choosing an appropriate topology. Three spot-welded models (lap, doubt-hat and T-shape) that approximate “typical” vehicle body components are studied for validating and illustrating the proposed method. It is concluded that removing underutilized material from overlapping regions can result in a significant increase in structural stiffness-to-weight ratio.
Three-Component Forward Modeling for Transient Electromagnetic Method
Directory of Open Access Journals (Sweden)
Bin Xiong
2010-01-01
Full Text Available In general, the time derivative of vertical magnetic field is considered only in the data interpretation of transient electromagnetic (TEM method. However, to survey in the complex geology structures, this conventional technique has begun gradually to be unsatisfied with the demand of field exploration. To improve the integrated interpretation precision of TEM, it is necessary to study the three-component forward modeling and inversion. In this paper, a three-component forward algorithm for 2.5D TEM based on the independent electric and magnetic field has been developed. The main advantage of the new scheme is that it can reduce the size of the global system matrix to the utmost extent, that is to say, the present is only one fourth of the conventional algorithm. In order to illustrate the feasibility and usefulness of the present algorithm, several typical geoelectric models of the TEM responses produced by loop sources at air-earth interface are presented. The results of the numerical experiments show that the computation speed of the present scheme is increased obviously and three-component interpretation can get the most out of the collected data, from which we can easily analyze or interpret the space characteristic of the abnormity object more comprehensively.
Integrated modelling of the edge plasma and plasma facing components
International Nuclear Information System (INIS)
Coster, D.P.; Bonnin, X.; Mutzke, A.; Schneider, R.; Warrier, M.
2007-01-01
Modelling of the interaction between the edge plasma and plasma facing components (PFCs) has tended to place more emphasis on either the plasma or the PFCs. Either the PFCs do not change with time and the plasma evolution is studied, or the plasma is assumed to remain static and the detailed interaction of the plasma and the PFCs are examined, with no back-reaction on the plasma taken into consideration. Recent changes to the edge simulation code, SOLPS, now allow for changes in both the plasma and the PFCs to be considered. This has been done by augmenting the code to track the time-development of the properties of plasma facing components (PFCs). Results of standard mixed-materials scenarios (base and redeposited C; Be) are presented
The International Trade Network: weighted network analysis and modelling
International Nuclear Information System (INIS)
Bhattacharya, K; Mukherjee, G; Manna, S S; Saramäki, J; Kaski, K
2008-01-01
Tools of the theory of critical phenomena, namely the scaling analysis and universality, are argued to be applicable to large complex web-like network structures. Using a detailed analysis of the real data of the International Trade Network we argue that the scaled link weight distribution has an approximate log-normal distribution which remains robust over a period of 53 years. Another universal feature is observed in the power-law growth of the trade strength with gross domestic product, the exponent being similar for all countries. Using the 'rich-club' coefficient measure of the weighted networks it has been shown that the size of the rich-club controlling half of the world's trade is actually shrinking. While the gravity law is known to describe well the social interactions in the static networks of population migration, international trade, etc, here for the first time we studied a non-conservative dynamical model based on the gravity law which excellently reproduced many empirical features of the ITN
Legal weight truck cask model impact limiter response
International Nuclear Information System (INIS)
Meinert, N.M.; Shappert, L.B.
1989-01-01
Dynamic and quasi-static quarter-scale model testing was performed to supplement the analytical case presented in the Nuclear Assurance Corporation Legal Weight Truck (NAC LWT) cask transport licensing application. Four successive drop tests from 9.0 meters (30 feet) onto an unyielding surface and one 1.0-meter (40-inch) drop onto a scale mild steel pin 3.8 centimeters (1.5 inches) in diameter, corroborated the impact limiter design and structural analyses presented in the licensing application. Quantitative measurements, made during drop testing, support the impact limiter analyses. High-speed photography of the tests confirm that only a small amount of energy is elastically stored in the aluminum honeycomb and that oblique drop slapdown is not significant. The qualitative conclusion is that the limiter protected LWT cask will not sustain permanent structural damage and containment will be maintained, subsequent to a hypothetical accident, as shown by structural analyses
A weight restricted DEA model for FMEA risk prioritization
Directory of Open Access Journals (Sweden)
Pauli Adriano de Almada Garcia
2012-01-01
Full Text Available In this paper we present a linear programming (LP approach to risk prioritization in failure mode and effects analysis (FMEA. The LP is a data envelopment analysis (DEA-based model considering weight restriction. In a FMEA, we commonly consider three criteria to prioritize the failure modes, occurrence, severity and detectability. These criteria are in an ordinal scale commonly varying from 1 to 10, higher the figure worse the result. Considering the values established for each criteria, in traditional FMEA one adopts a Risk Priority Number, calculated considering the product of criteria, which has been very criticized due to its shortcoming. Through the proposed approach a frontier is established considering the less critical failure modes. Considering this frontier, one can establish how much each failure mode must be improved to become relatively acceptable. A simplified case concerning an AFWS of a two loops PWR power plant is presented to shows the applicability of the proposed approach.
Selimkhanov, Jangir; Thompson, W Clayton; Patterson, Terrell A; Hadcock, John R; Scott, Dennis O; Maurer, Tristan S; Musante, Cynthia J
2016-01-01
The purpose of this work is to develop a mathematical model of energy balance and body weight regulation that can predict species-specific response to common pre-clinical interventions. To this end, we evaluate the ability of a previously published mathematical model of mouse metabolism to describe changes in body weight and body composition in rats in response to two short-term interventions. First, we adapt the model to describe body weight and composition changes in Sprague-Dawley rats by fitting to data previously collected from a 26-day caloric restriction study. The calibrated model is subsequently used to describe changes in rat body weight and composition in a 23-day cannabinoid receptor 1 antagonist (CB1Ra) study. While the model describes body weight data well, it fails to replicate body composition changes with CB1Ra treatment. Evaluation of a key model assumption about deposition of fat and fat-free masses shows a limitation of the model in short-term studies due to the constraint placed on the relative change in body composition components. We demonstrate that the model can be modified to overcome this limitation, and propose additional measurements to further test the proposed model predictions. These findings illustrate how mathematical models can be used to support drug discovery and development by identifying key knowledge gaps and aiding in the design of additional experiments to further our understanding of disease-relevant and species-specific physiology.
Directory of Open Access Journals (Sweden)
Jangir Selimkhanov
Full Text Available The purpose of this work is to develop a mathematical model of energy balance and body weight regulation that can predict species-specific response to common pre-clinical interventions. To this end, we evaluate the ability of a previously published mathematical model of mouse metabolism to describe changes in body weight and body composition in rats in response to two short-term interventions. First, we adapt the model to describe body weight and composition changes in Sprague-Dawley rats by fitting to data previously collected from a 26-day caloric restriction study. The calibrated model is subsequently used to describe changes in rat body weight and composition in a 23-day cannabinoid receptor 1 antagonist (CB1Ra study. While the model describes body weight data well, it fails to replicate body composition changes with CB1Ra treatment. Evaluation of a key model assumption about deposition of fat and fat-free masses shows a limitation of the model in short-term studies due to the constraint placed on the relative change in body composition components. We demonstrate that the model can be modified to overcome this limitation, and propose additional measurements to further test the proposed model predictions. These findings illustrate how mathematical models can be used to support drug discovery and development by identifying key knowledge gaps and aiding in the design of additional experiments to further our understanding of disease-relevant and species-specific physiology.
Language Model Combination and Adaptation Using Weighted Finite State Transducers
Liu, X.; Gales, M. J. F.; Hieronymus, J. L.; Woodland, P. C.
2010-01-01
In speech recognition systems language model (LMs) are often constructed by training and combining multiple n-gram models. They can be either used to represent different genres or tasks found in diverse text sources, or capture stochastic properties of different linguistic symbol sequences, for example, syllables and words. Unsupervised LM adaption may also be used to further improve robustness to varying styles or tasks. When using these techniques, extensive software changes are often required. In this paper an alternative and more general approach based on weighted finite state transducers (WFSTs) is investigated for LM combination and adaptation. As it is entirely based on well-defined WFST operations, minimum change to decoding tools is needed. A wide range of LM combination configurations can be flexibly supported. An efficient on-the-fly WFST decoding algorithm is also proposed. Significant error rate gains of 7.3% relative were obtained on a state-of-the-art broadcast audio recognition task using a history dependently adapted multi-level LM modelling both syllable and word sequences
Ren, Anna N; Neher, Robert E; Bell, Tyler; Grimm, James
2018-06-01
Preoperative planning is important to achieve successful implantation in primary total knee arthroplasty (TKA). However, traditional TKA templating techniques are not accurate enough to predict the component size to a very close range. With the goal of developing a general predictive statistical model using patient demographic information, ordinal logistic regression was applied to build a proportional odds model to predict the tibia component size. The study retrospectively collected the data of 1992 primary Persona Knee System TKA procedures. Of them, 199 procedures were randomly selected as testing data and the rest of the data were randomly partitioned between model training data and model evaluation data with a ratio of 7:3. Different models were trained and evaluated on the training and validation data sets after data exploration. The final model had patient gender, age, weight, and height as independent variables and predicted the tibia size within 1 size difference 96% of the time on the validation data, 94% of the time on the testing data, and 92% on a prospective cadaver data set. The study results indicated the statistical model built by ordinal logistic regression can increase the accuracy of tibia sizing information for Persona Knee preoperative templating. This research shows statistical modeling may be used with radiographs to dramatically enhance the templating accuracy, efficiency, and quality. In general, this methodology can be applied to other TKA products when the data are applicable. Copyright © 2018 Elsevier Inc. All rights reserved.
Modeling and numerical simulation of multi-component flow in porous media
International Nuclear Information System (INIS)
Saad, B.
2011-01-01
This work deals with the modelization and numerical simulation of two phase multi-component flow in porous media. The study is divided into two parts. First we study and prove the mathematical existence in a weak sense of two degenerate parabolic systems modeling two phase (liquid and gas) two component (water and hydrogen) flow in porous media. In the first model, we assume that there is a local thermodynamic equilibrium between both phases of hydrogen by using the Henry's law. The second model consists of a relaxation of the previous model: the kinetic of the mass exchange between dissolved hydrogen and hydrogen in the gas phase is no longer instantaneous. The second part is devoted to the numerical analysis of those models. Firstly, we propose a numerical scheme to compare numerical solutions obtained with the first model and numerical solutions obtained with the second model where the characteristic time to recover the thermodynamic equilibrium goes to zero. Secondly, we present a finite volume scheme with a phase-by-phase upstream weighting scheme without simplified assumptions on the state law of gas densities. We also validate this scheme on a 2D test cases. (author)
Directory of Open Access Journals (Sweden)
Sachin Ashok Sonawane
2018-04-01
Full Text Available This paper reports the results of research to examine the effects of cutting parameters such as pulse-on time, pulse-off time, servo voltage, peak current, wire feed rate and cable tension on surface finish, overcut and metal removal rate (MRR during Wire Electrical Discharge Machining (WEDM of grade-5 titanium (Ti-6Al-4V. Taguchi’s L27 orthogonal design method is used for experimentation. Multi-response optimization is performed by applying weighted principal component analysis (WPCA. The optimum values of cutting variables are found as a pulse on time 118 μs, pulse off time 45 μs, servo voltage 40 volts, peak current 190 Amp. , wire feed rate 5 m/min and cable tension 5 gram. On the other hand, Analysis of Variance (ANOVA, simulation results indicate that pulse-on time is the primary influencing variable which affects the response characteristics contributing 76.00%. The results of verification experiments show improvement in the value of output characteristics at the optimal cutting variables settings. Scanning electron microscopic (SEM analysis of the surface after machining indicates the formation of craters, resolidified material, tool material transfer and increase in the thickness of recast layer at higher values of the pulse on time.
Dutta, Aritra
2017-07-02
Principal component pursuit (PCP) is a state-of-the-art approach for background estimation problems. Due to their higher computational cost, PCP algorithms, such as robust principal component analysis (RPCA) and its variants, are not feasible in processing high definition videos. To avoid the curse of dimensionality in those algorithms, several methods have been proposed to solve the background estimation problem in an incremental manner. We propose a batch-incremental background estimation model using a special weighted low-rank approximation of matrices. Through experiments with real and synthetic video sequences, we demonstrate that our method is superior to the state-of-the-art background estimation algorithms such as GRASTA, ReProCS, incPCP, and GFL.
Dutta, Aritra; Li, Xin; Richtarik, Peter
2017-01-01
Principal component pursuit (PCP) is a state-of-the-art approach for background estimation problems. Due to their higher computational cost, PCP algorithms, such as robust principal component analysis (RPCA) and its variants, are not feasible in processing high definition videos. To avoid the curse of dimensionality in those algorithms, several methods have been proposed to solve the background estimation problem in an incremental manner. We propose a batch-incremental background estimation model using a special weighted low-rank approximation of matrices. Through experiments with real and synthetic video sequences, we demonstrate that our method is superior to the state-of-the-art background estimation algorithms such as GRASTA, ReProCS, incPCP, and GFL.
Two-component scattering model and the electron density spectrum
Zhou, A. Z.; Tan, J. Y.; Esamdin, A.; Wu, X. J.
2010-02-01
In this paper, we discuss a rigorous treatment of the refractive scintillation caused by a two-component interstellar scattering medium and a Kolmogorov form of density spectrum. It is assumed that the interstellar scattering medium is composed of a thin-screen interstellar medium (ISM) and an extended interstellar medium. We consider the case that the scattering of the thin screen concentrates in a thin layer represented by a δ function distribution and that the scattering density of the extended irregular medium satisfies the Gaussian distribution. We investigate and develop equations for the flux density structure function corresponding to this two-component ISM geometry in the scattering density distribution and compare our result with the observations. We conclude that the refractive scintillation caused by this two-component ISM scattering gives a more satisfactory explanation for the observed flux density variation than does the single extended medium model. The level of refractive scintillation is strongly sensitive to the distribution of scattering material along the line of sight (LOS). The theoretical modulation indices are comparatively less sensitive to the scattering strength of the thin-screen medium, but they critically depend on the distance from the observer to the thin screen. The logarithmic slope of the structure function is sensitive to the scattering strength of the thin-screen medium, but is relatively insensitive to the thin-screen location. Therefore, the proposed model can be applied to interpret the structure functions of flux density observed in pulsar PSR B2111 + 46 and PSR B0136 + 57. The result suggests that the medium consists of a discontinuous distribution of plasma turbulence embedded in the interstellar medium. Thus our work provides some insight into the distribution of the scattering along the LOS to the pulsar PSR B2111 + 46 and PSR B0136 + 57.
A multi-component evaporation model for beam melting processes
Klassen, Alexander; Forster, Vera E.; Körner, Carolin
2017-02-01
In additive manufacturing using laser or electron beam melting technologies, evaporation losses and changes in chemical composition are known issues when processing alloys with volatile elements. In this paper, a recently described numerical model based on a two-dimensional free surface lattice Boltzmann method is further developed to incorporate the effects of multi-component evaporation. The model takes into account the local melt pool composition during heating and fusion of metal powder. For validation, the titanium alloy Ti-6Al-4V is melted by selective electron beam melting and analysed using mass loss measurements and high-resolution microprobe imaging. Numerically determined evaporation losses and spatial distributions of aluminium compare well with experimental data. Predictions of the melt pool formation in bulk samples provide insight into the competition between the loss of volatile alloying elements from the irradiated surface and their advective redistribution within the molten region.
Flexible Multibody Systems Models Using Composite Materials Components
International Nuclear Information System (INIS)
Neto, Maria Augusta; Ambr'osio, Jorge A. C.; Leal, Rog'erio Pereira
2004-01-01
The use of a multibody methodology to describe the large motion of complex systems that experience structural deformations enables to represent the complete system motion, the relative kinematics between the components involved, the deformation of the structural members and the inertia coupling between the large rigid body motion and the system elastodynamics. In this work, the flexible multibody dynamics formulations of complex models are extended to include elastic components made of composite materials, which may be laminated and anisotropic. The deformation of any structural member must be elastic and linear, when described in a coordinate frame fixed to one or more material points of its domain, regardless of the complexity of its geometry. To achieve the proposed flexible multibody formulation, a finite element model for each flexible body is used. For the beam composite material elements, the sections properties are found using an asymptotic procedure that involves a two-dimensional finite element analysis of their cross-section. The equations of motion of the flexible multibody system are solved using an augmented Lagrangian formulation and the accelerations and velocities are integrated in time using a multi-step multi-order integration algorithm based on the Gear method
Sparse principal component analysis in medical shape modeling
Sjöstrand, Karl; Stegmann, Mikkel B.; Larsen, Rasmus
2006-03-01
Principal component analysis (PCA) is a widely used tool in medical image analysis for data reduction, model building, and data understanding and exploration. While PCA is a holistic approach where each new variable is a linear combination of all original variables, sparse PCA (SPCA) aims at producing easily interpreted models through sparse loadings, i.e. each new variable is a linear combination of a subset of the original variables. One of the aims of using SPCA is the possible separation of the results into isolated and easily identifiable effects. This article introduces SPCA for shape analysis in medicine. Results for three different data sets are given in relation to standard PCA and sparse PCA by simple thresholding of small loadings. Focus is on a recent algorithm for computing sparse principal components, but a review of other approaches is supplied as well. The SPCA algorithm has been implemented using Matlab and is available for download. The general behavior of the algorithm is investigated, and strengths and weaknesses are discussed. The original report on the SPCA algorithm argues that the ordering of modes is not an issue. We disagree on this point and propose several approaches to establish sensible orderings. A method that orders modes by decreasing variance and maximizes the sum of variances for all modes is presented and investigated in detail.
Modeling for thermodynamic activities of components in simulated reprocessing solutions
International Nuclear Information System (INIS)
Sasahira, Akira; Hoshikawa, Tadahiro; Kawamura, Fumio
1992-01-01
Analyses of chemical reactions have been widely carried out for soluble fission products encountered in nuclear fuel reprocessing. For detailed analyses of reactions, a prediction of the activity or activity coefficient for nitric acid, water, and several nitrates of fission products is needed. An idea for the predicted nitric acid activity was presented earlier. The model, designated the hydration model, does not predict the nitrate activity. It did, however, suggest that the activity of water would be a function of nitric acid activity but not the molar fraction of water. If the activities of nitric acid and water are accurately predicted, the activity of the last component, nitrate, can be calculated using the Gibbs-Duhem relation for chemical potentials. Therefore, in this study, the earlier hydration model was modified to evaluate the water activity more accurately. The modified model was experimentally examined in stimulated reprocessing solutions. It is concluded that the modified model was suitable for water activity, but further improvement was needed for the activity evaluation of nitric acid in order to calculate the nitrate activity
Predicting birth weight with conditionally linear transformation models.
Möst, Lisa; Schmid, Matthias; Faschingbauer, Florian; Hothorn, Torsten
2016-12-01
Low and high birth weight (BW) are important risk factors for neonatal morbidity and mortality. Gynecologists must therefore accurately predict BW before delivery. Most prediction formulas for BW are based on prenatal ultrasound measurements carried out within one week prior to birth. Although successfully used in clinical practice, these formulas focus on point predictions of BW but do not systematically quantify uncertainty of the predictions, i.e. they result in estimates of the conditional mean of BW but do not deliver prediction intervals. To overcome this problem, we introduce conditionally linear transformation models (CLTMs) to predict BW. Instead of focusing only on the conditional mean, CLTMs model the whole conditional distribution function of BW given prenatal ultrasound parameters. Consequently, the CLTM approach delivers both point predictions of BW and fetus-specific prediction intervals. Prediction intervals constitute an easy-to-interpret measure of prediction accuracy and allow identification of fetuses subject to high prediction uncertainty. Using a data set of 8712 deliveries at the Perinatal Centre at the University Clinic Erlangen (Germany), we analyzed variants of CLTMs and compared them to standard linear regression estimation techniques used in the past and to quantile regression approaches. The best-performing CLTM variant was competitive with quantile regression and linear regression approaches in terms of conditional coverage and average length of the prediction intervals. We propose that CLTMs be used because they are able to account for possible heteroscedasticity, kurtosis, and skewness of the distribution of BWs. © The Author(s) 2014.
A Systematic Evaluation of Ultrasound-based Fetal Weight Estimation Models on Indian Population
Directory of Open Access Journals (Sweden)
Sujitkumar S. Hiwale
2017-12-01
Conclusion: We found that the existing fetal weight estimation models have high systematic and random errors on Indian population, with a general tendency of overestimation of fetal weight in the LBW category and underestimation in the HBW category. We also observed that these models have a limited ability to predict babies at a risk of either low or high birth weight. It is recommended that the clinicians should consider all these factors, while interpreting estimated weight given by the existing models.
Directory of Open Access Journals (Sweden)
Martijn de Roon
2017-03-01
This study shows largely sustained weight loss one year after completing a weight loss program with and without exercise in overweight postmenopausal women. Although the mainly exercise group maintained more physically active compared to the diet group, maintenance of weight loss did not differ between groups.
Nugroho, N. F. T. A.; Slamet, I.
2018-05-01
Poverty is a socio-economic condition of a person or group of people who can not fulfil their basic need to maintain and develop a dignified life. This problem still cannot be solved completely in Central Java Province. Currently, the percentage of poverty in Central Java is 13.32% which is higher than the national poverty rate which is 11.13%. In this research, data of percentage of poor people in Central Java Province has been analyzed through geographically weighted regression (GWR). The aim of this research is therefore to model poverty percentage data in Central Java Province using GWR with weighted function of kernel bisquare, and tricube. As the results, we obtained GWR model with bisquare and tricube kernel weighted function on poverty percentage data in Central Java province. From the GWR model, there are three categories of region which are influenced by different of significance factors.
Understanding science teacher enhancement programs: Essential components and a model
Spiegel, Samuel Albert
Researchers and practioners alike recognize that "the national goal that every child in the United States has access to high-quality school education in science and mathematics cannot be realized without the availability of effective professional development of teachers" (Hewson, 1997, p. 16). Further, there is a plethora of reports calling for the improvement of professional development efforts (Guskey & Huberman, 1995; Kyle, 1995; Loucks-Horsley, Hewson, Love, & Stiles, 1997). In this study I analyze a successful 3-year teacher enhancement program, one form of professional development, to: (1) identify essential components of an effective teacher enhancement program; and (2) create a model to identify and articulate the critical issues in designing, implementing, and evaluating teacher enhancement programs. Five primary sources of information were converted into data: (1) exit questionnaires, (2) exit surveys, (3) exit interview transcripts, (4) focus group transcripts, and (5) other artifacts. Additionally, a focus group was used to conduct member checks. Data were analyzed in an iterative process which led to the development of the list of essential components. The Components are categorized by three organizers: Structure (e.g., science research experience, a mediator throughout the program), Context (e.g., intensity, collaboration), and Participant Interpretation (e.g., perceived to be "safe" to examine personal beliefs and practices, actively engaged). The model is based on: (1) a 4-year study of a successful teacher enhancement program; (2) an analysis of professional development efforts reported in the literature; and (3) reflective discussions with implementors, evaluators, and participants of professional development programs. The model consists of three perspectives, cognitive, symbolic interaction, and organizational, representing different viewpoints from which to consider issues relevant to the success of a teacher enhancement program. These
Modeling Organic Contaminant Desorption from Municipal Solid Waste Components
Knappe, D. R.; Wu, B.; Barlaz, M. A.
2002-12-01
Approximately 25% of the sites on the National Priority List (NPL) of Superfund are municipal landfills that accepted hazardous waste. Unlined landfills typically result in groundwater contamination, and priority pollutants such as alkylbenzenes are often present. To select cost-effective risk management alternatives, better information on factors controlling the fate of hydrophobic organic contaminants (HOCs) in landfills is required. The objectives of this study were (1) to investigate the effects of HOC aging time, anaerobic sorbent decomposition, and leachate composition on HOC desorption rates, and (2) to simulate HOC desorption rates from polymers and biopolymer composites with suitable diffusion models. Experiments were conducted with individual components of municipal solid waste (MSW) including polyvinyl chloride (PVC), high-density polyethylene (HDPE), newsprint, office paper, and model food and yard waste (rabbit food). Each of the biopolymer composites (office paper, newsprint, rabbit food) was tested in both fresh and anaerobically decomposed form. To determine the effects of aging on alkylbenzene desorption rates, batch desorption tests were performed after sorbents were exposed to toluene for 30 and 250 days in flame-sealed ampules. Desorption tests showed that alkylbenzene desorption rates varied greatly among MSW components (PVC slowest, fresh rabbit food and newsprint fastest). Furthermore, desorption rates decreased as aging time increased. A single-parameter polymer diffusion model successfully described PVC and HDPE desorption data, but it failed to simulate desorption rate data for biopolymer composites. For biopolymer composites, a three-parameter biphasic polymer diffusion model was employed, which successfully simulated both the initial rapid and the subsequent slow desorption of toluene. Toluene desorption rates from MSW mixtures were predicted for typical MSW compositions in the years 1960 and 1997. For the older MSW mixture, which had a
Modeling photoionization of aqueous DNA and its components.
Pluhařová, Eva; Slavíček, Petr; Jungwirth, Pavel
2015-05-19
Radiation damage to DNA is usually considered in terms of UVA and UVB radiation. These ultraviolet rays, which are part of the solar spectrum, can indeed cause chemical lesions in DNA, triggered by photoexcitation particularly in the UVB range. Damage can, however, be also caused by higher energy radiation, which can ionize directly the DNA or its immediate surroundings, leading to indirect damage. Thanks to absorption in the atmosphere, the intensity of such ionizing radiation is negligible in the solar spectrum at the surface of Earth. Nevertheless, such an ionizing scenario can become dangerously plausible for astronauts or flight personnel, as well as for persons present at nuclear power plant accidents. On the beneficial side, ionizing radiation is employed as means for destroying the DNA of cancer cells during radiation therapy. Quantitative information about ionization of DNA and its components is important not only for DNA radiation damage, but also for understanding redox properties of DNA in redox sensing or labeling, as well as charge migration along the double helix in nanoelectronics applications. Until recently, the vast majority of experimental and computational data on DNA ionization was pertinent to its components in the gas phase, which is far from its native aqueous environment. The situation has, however, changed for the better due to the advent of photoelectron spectroscopy in liquid microjets and its most recent application to photoionization of aqueous nucleosides, nucleotides, and larger DNA fragments. Here, we present a consistent and efficient computational methodology, which allows to accurately evaluate ionization energies and model photoelectron spectra of aqueous DNA and its individual components. After careful benchmarking, the method based on density functional theory and its time-dependent variant with properly chosen hybrid functionals and polarizable continuum solvent model provides ionization energies with accuracy of 0.2-0.3 e
Chungchunlam, Sylvia M S; Henare, Sharon J; Ganesh, Siva; Moughan, Paul J
2017-06-01
Protein is the most satiating macronutrient and is source dependent, with whey protein thought to be particularly satiating. The purported satiating effect of whey protein may be due to the unique mixture of proteins in whey or to the major constituent individual proteins (β-lactoglobulin and α-lactalbumin). The objective of the study was to compare the effects of isoenergetic (~2100kJ, ~500kcal) preload meals enriched (~50g protein) with either whey protein isolate (WP), β-lactoglobulin (BL) isolate or α-lactalbumin (AL) isolate, on food intake at an ad libitum test meal 120min later and subjective ratings of appetite (hunger, desire to eat, prospective food consumption and fullness) using visual analogue scales (VAS). Twenty adult normal-weight women (mean age 24.2±0.8years; mean BMI 22.7±0.4kg/m 2 ) participated in the study which used a single-blind completely randomised block design, where each subject consumed each of the three preload meals. Energy intake at the ad libitum test meal and total energy intakes (preload+test meal) did not differ between the three preload meals (p>0.05). There were no significant differences observed for the VAS scores and net incremental area under the curve (net iAUC) during the 120min following consumption of the three preload meals for subjective ratings of appetite (p>0.05). The findings show that the satiating effect of whey protein was similar to that of BL or AL individually and suggest that the major whey protein components BL and AL do not mediate the satiating effect of whey protein. The present human trial was registered with the Australian New Zealand Clinical Trials Registry (www.anzctr.org.au) as ACTRN12615000344594. Copyright © 2017 Elsevier Inc. All rights reserved.
Chen, Yuan; Watson, Heather M.; Gao, Junjie; Sinha, Sarmistha Halder; Cassady, Carolyn J.; Vincent, John B.
2011-01-01
Chromium was proposed to be an essential element over 50 y ago and was shown to have therapeutic potential in treating the symptoms of type 2 diabetes; however, its mechanism of action at a molecular level is unknown. One chromium-binding biomolecule, low-molecular weight chromium-binding substance (LMWCr or chromodulin), has been found to be biologically active in in vitro assays and proposed as a potential candidate for the in vivo biologically active form of chromium. Characterization of the organic component of LMWCr has proven difficult. Treating bovine LMWCr with trifluoroacetic acid followed by purification on a graphite powder micro-column generates a heptapeptide fragment of LMWCr. The peptide sequence of the fragment was analyzed by MS and tandem MS (MS/MS and MS/MS/MS) using collision-induced dissociation and post-source decay. Two candidate sequences, pEEEEGDD and pEEEGEDD (where pE is pyroglutamate), were identified from the MS/MS experiments; additional tandem MS suggests the sequence is pEEEEGDD. The N-terminal glutamate residues explain the inability to sequence LMWCr by the Edman method. Langmuir isotherms and Hill plots were used to analyze the binding constants of chromic ions to synthetic peptides similar in composition to apoLMWCr. The sequence pEEEEGDD was found to bind 4 chromic ions per peptide with nearly identical cooperativity and binding constants to those of apoLMWCr. This work should lead to further studies elucidating or eliminating a potential role for LMWCr in treating the symptoms of type 2 diabetes and other conditions resulting from improper carbohydrate and lipid metabolism. PMID:21593351
A Behavioral Weight Reduction Model for Moderately Mentally Retarded Adolescents.
Rotatori, Anthony F.; And Others
1980-01-01
A behavioral weight reduction treatment and maintenance program for moderately mentally retarded adolescents which involves six phases from background information collection to followup relies on stimulus control procedures to modify eating behaviors. Data from pilot studies show an average weekly weight loss of .5 to 1 pound per S. (CL)
On combined gravity gradient components modelling for applied geophysics
International Nuclear Information System (INIS)
Veryaskin, Alexey; McRae, Wayne
2008-01-01
Gravity gradiometry research and development has intensified in recent years to the extent that technologies providing a resolution of about 1 eotvos per 1 second average shall likely soon be available for multiple critical applications such as natural resources exploration, oil reservoir monitoring and defence establishment. Much of the content of this paper was composed a decade ago, and only minor modifications were required for the conclusions to be just as applicable today. In this paper we demonstrate how gravity gradient data can be modelled, and show some examples of how gravity gradient data can be combined in order to extract valuable information. In particular, this study demonstrates the importance of two gravity gradient components, Txz and Tyz, which, when processed together, can provide more information on subsurface density contrasts than that derived solely from the vertical gravity gradient (Tzz)
Modelling safety of multistate systems with ageing components
Energy Technology Data Exchange (ETDEWEB)
Kołowrocki, Krzysztof; Soszyńska-Budny, Joanna [Gdynia Maritime University, Department of Mathematics ul. Morska 81-87, Gdynia 81-225 Poland (Poland)
2016-06-08
An innovative approach to safety analysis of multistate ageing systems is presented. Basic notions of the ageing multistate systems safety analysis are introduced. The system components and the system multistate safety functions are defined. The mean values and variances of the multistate systems lifetimes in the safety state subsets and the mean values of their lifetimes in the particular safety states are defined. The multi-state system risk function and the moment of exceeding by the system the critical safety state are introduced. Applications of the proposed multistate system safety models to the evaluation and prediction of the safty characteristics of the consecutive “m out of n: F” is presented as well.
Modelling safety of multistate systems with ageing components
International Nuclear Information System (INIS)
Kołowrocki, Krzysztof; Soszyńska-Budny, Joanna
2016-01-01
An innovative approach to safety analysis of multistate ageing systems is presented. Basic notions of the ageing multistate systems safety analysis are introduced. The system components and the system multistate safety functions are defined. The mean values and variances of the multistate systems lifetimes in the safety state subsets and the mean values of their lifetimes in the particular safety states are defined. The multi-state system risk function and the moment of exceeding by the system the critical safety state are introduced. Applications of the proposed multistate system safety models to the evaluation and prediction of the safty characteristics of the consecutive “m out of n: F” is presented as well.
Component vibration of VVER-reactors - diagnostics and modelling
International Nuclear Information System (INIS)
Altstadt, E.; Scheffler, M.; Weiss, F.-P.
1995-01-01
Flow induced vibrations of reactor pressure vessel (RPV) internals (control element and core barrel motions) at VVER-440 reactors have led to the development of dedicated methods for on-line monitoring. These methods need a certain developed stage of the faults to be detected. To achieve a real sensitive early detection of mechanical faults of RPV internals, a theoretical vibration model was developed based on finite elements. The model comprises the whole primary circuit including the steam generators (SG). By means of that model all eigenfrequencies up to 30 Hz and the corresponding mode shapes were calculated for the normal vibration behaviour. Moreover the shift of eigenfrequencies and of amplitudes due to the degradation or to the failure of internal clamping and spring elements could be investigated, showing that a recognition of such degradations even inside the RPV is possible by pure excore vibration measurements. A true diagnostic, that is the identification of the failed component, might become possible because different faults influence different and well separated eigenfrequencies. (author)
CSIR Research Space (South Africa)
Leenen, L
2007-12-01
Full Text Available The authors present a variant of the Weighted Maximum Satisfiability Problem (Weighted Max-SAT), which is a modeling of the Semiring Constraint Satisfaction framework. They show how to encode a Semiring Constraint Satisfaction Problem (SCSP...
Zhai, Liang; Li, Shuang; Zou, Bin; Sang, Huiyong; Fang, Xin; Xu, Shan
2018-05-01
Considering the spatial non-stationary contributions of environment variables to PM2.5 variations, the geographically weighted regression (GWR) modeling method has been using to estimate PM2.5 concentrations widely. However, most of the GWR models in reported studies so far were established based on the screened predictors through pretreatment correlation analysis, and this process might cause the omissions of factors really driving PM2.5 variations. This study therefore developed a best subsets regression (BSR) enhanced principal component analysis-GWR (PCA-GWR) modeling approach to estimate PM2.5 concentration by fully considering all the potential variables' contributions simultaneously. The performance comparison experiment between PCA-GWR and regular GWR was conducted in the Beijing-Tianjin-Hebei (BTH) region over a one-year-period. Results indicated that the PCA-GWR modeling outperforms the regular GWR modeling with obvious higher model fitting- and cross-validation based adjusted R2 and lower RMSE. Meanwhile, the distribution map of PM2.5 concentration from PCA-GWR modeling also clearly depicts more spatial variation details in contrast to the one from regular GWR modeling. It can be concluded that the BSR enhanced PCA-GWR modeling could be a reliable way for effective air pollution concentration estimation in the coming future by involving all the potential predictor variables' contributions to PM2.5 variations.
BWR Refill-Reflood Program, Task 4.7 - model development: TRAC-BWR component models
International Nuclear Information System (INIS)
Cheung, Y.K.; Parameswaran, V.; Shaug, J.C.
1983-09-01
TRAC (Transient Reactor Analysis Code) is a computer code for best-estimate analysis for the thermal hydraulic conditions in a reactor system. The development and assessment of the BWR component models developed under the Refill/Reflood Program that are necessary to structure a BWR-version of TRAC are described in this report. These component models are the jet pump, steam separator, steam dryer, two-phase level tracking model, and upper-plenum mixing model. These models have been implemented into TRAC-B02. Also a single-channel option has been developed for individual fuel-channel analysis following a system-response calculation
Directory of Open Access Journals (Sweden)
Sun Zhangzhen
2012-08-01
Full Text Available In this paper, an improved weighted least squares (WLS, together with autoregressive (AR model, is proposed to improve prediction accuracy of earth rotation parameters(ERP. Four weighting schemes are developed and the optimal power e for determination of the weight elements is studied. The results show that the improved WLS-AR model can improve the ERP prediction accuracy effectively, and for different prediction intervals of ERP, different weight scheme should be chosen.
Stochastic Models of Defects in Wind Turbine Drivetrain Components
DEFF Research Database (Denmark)
Rafsanjani, Hesam Mirzaei; Sørensen, John Dalsgaard
2013-01-01
The drivetrain in a wind turbine nacelle typically consists of a variety of heavily loaded components, like the main shaft, bearings, gearbox and generator. The variations in environmental load challenge the performance of all the components of the drivetrain. Failure of each of these components...
Exploring a minimal two-component p53 model
International Nuclear Information System (INIS)
Sun, Tingzhe; Zhu, Feng; Shen, Pingping; Yuan, Ruoshi; Xu, Wei
2010-01-01
The tumor suppressor p53 coordinates many attributes of cellular processes via interlocked feedback loops. To understand the biological implications of feedback loops in a p53 system, a two-component model which encompasses essential feedback loops was constructed and further explored. Diverse bifurcation properties, such as bistability and oscillation, emerge by manipulating the feedback strength. The p53-mediated MDM2 induction dictates the bifurcation patterns. We first identified irradiation dichotomy in p53 models and further proposed that bistability and oscillation can behave in a coordinated manner. Further sensitivity analysis revealed that p53 basal production and MDM2-mediated p53 degradation, which are central to cellular control, are most sensitive processes. Also, we identified that the much more significant variations in amplitude of p53 pulses observed in experiments can be derived from overall amplitude parameter sensitivity. The combined approach with bifurcation analysis, stochastic simulation and sampling-based sensitivity analysis not only gives crucial insights into the dynamics of the p53 system, but also creates a fertile ground for understanding the regulatory patterns of other biological networks
Modeling and validation of existing VAV system components
Energy Technology Data Exchange (ETDEWEB)
Nassif, N.; Kajl, S.; Sabourin, R. [Ecole de Technologie Superieure, Montreal, PQ (Canada)
2004-07-01
The optimization of supervisory control strategies and local-loop controllers can improve the performance of HVAC (heating, ventilating, air-conditioning) systems. In this study, the component model of the fan, the damper and the cooling coil were developed and validated against monitored data of an existing variable air volume (VAV) system installed at Montreal's Ecole de Technologie Superieure. The measured variables that influence energy use in individual HVAC models included: (1) outdoor and return air temperature and relative humidity, (2) supply air and water temperatures, (3) zone airflow rates, (4) supply duct, outlet fan, mixing plenum static pressures, (5) fan speed, and (6) minimum and principal damper and cooling and heating coil valve positions. The additional variables that were considered, but not measured were: (1) fan and outdoor airflow rate, (2) inlet and outlet cooling coil relative humidity, and (3) liquid flow rate through the heating or cooling coils. The paper demonstrates the challenges of the validation process when monitored data of existing VAV systems are used. 7 refs., 11 figs.
Parameter estimation of component reliability models in PSA model of Krsko NPP
International Nuclear Information System (INIS)
Jordan Cizelj, R.; Vrbanic, I.
2001-01-01
In the paper, the uncertainty analysis of component reliability models for independent failures is shown. The present approach for parameter estimation of component reliability models in NPP Krsko is presented. Mathematical approaches for different types of uncertainty analyses are introduced and used in accordance with some predisposed requirements. Results of the uncertainty analyses are shown in an example for time-related components. As the most appropriate uncertainty analysis proved the Bayesian estimation with the numerical estimation of a posterior, which can be approximated with some appropriate probability distribution, in this paper with lognormal distribution.(author)
Prenatal centrifugation: A model for fetal programming of adult weight?
Baer, Lisa A.; Rushing, Linda; Wade, Charles E.; Ronca, April E.
2005-08-01
'Fetal programming' is a newly emerging field that is revealing astounding insights into the prenatal origins of adult disease, including metabolic, endocrine, and cardiovascular pathophysiology. In the present study, we tested the hypothesis that rat pups conceived, gestated and born at 2-g have significantly reduced birth weights and increased adult body weights as compared to 1-g controls. Offspring were produced by mating young adult male and female rats that were adapted to 2-g centrifugation. Female rats underwent conception, pregnancy and birth at 2-g. Newborn pups in the 2-g condition were removed from the centrifuge and fostered to non-manipulated, newly parturient dams maintained at 1-g. Comparisons were made with 1-g stationary controls, also cross- fostered at birth. As compared to 1-g controls, birth weights of pups gestated and born at 2-g were significantly reduced. Pup body weights were significantly reduced until Postnatal day (P)12. Beginning on P63, body weights of 2-g-gestated offspring exceeded those of 1-g controls by 7-10%. Thus, prenatal rearing at 2-g restricts neonatal growth and increases adult body weight. Collectively, these data support the hypothesis that 2-g centrifugation alters the intrauterine milieu, thereby inducing persistent changes in adult phenotype.
DEFF Research Database (Denmark)
Larsen, Kristian Traberg; Huang, Tao; Ried-Larsen, Mathias
2016-01-01
The objective of the present study was to evaluate the effectiveness of a one-year multi-component immersive day-camp weight-loss intervention for children with overweight and obesity. The study design was a parallel-group randomized controlled trial. One hundred fifteen 11-13-year-old children...
Toro-Ramos, Tatiana; Lee, Dong-Hwa; Kim, Youngin; Michaelides, Andreas; Oh, Tae Jung; Kim, Kyoung Min; Jang, Hak Chul; Lim, Soo
2017-11-01
There are inconsistent results for the effectiveness of using smartphone applications (apps) or websites on weight loss. We investigated the efficacy of a smartphone intervention using a designated app that utilizes a lifestyle intervention-focused approach, including a human coaching element, toward weight loss in overweight or obese Korean adults. One hundred four adults aged 20-60 years with a body mass index ≥23 kg/m 2 , who signed up for a smartphone program for weight loss (using the Noom app), were recruited. Participants received an in-person orientation about the study and app use, and a baseline blood sample was obtained. The in-app intervention with daily behavior and nutrition education content and coaching lasted 15 weeks. The primary endpoint of the study was a change in weight. The secondary endpoints were changes in metabolic risk factors such as blood pressure, waist circumference, and glucose and lipid profiles. Body composition changes were also assessed, and body weight at 52 weeks was measured to ascertain long-term effects. Participants showed a clinically significant weight loss effect of -7.5% at the end of the 15-week program (P smartphone app was a useful tool to maintain weight loss in overweight or obese people.
Jiskoot, G; Benneheij, S H; Beerthuizen, A; de Niet, J E; de Klerk, C; Timman, R; Busschbach, J J; Laven, J S E
2017-03-06
Obesity in women with polycystic ovary syndrome (PCOS) negatively affects all clinical features, and a 5 to 10% weight loss has shown promising results on reproductive, metabolic and psychological level. Incorporating a healthy diet, increasing physical activity and changing dysfunctional thought patterns in women with PCOS are key points in losing weight. The biggest challenge in weight management programs is to achieve a reasonable and sustainable weight loss. The aim of this study is to explore whether Cognitive Behavioural Therapy (CBT) by a mental health professional, working in a multidisciplinary team with a dietician and a physical therapist (a three-component intervention), is more effective for weight loss in the long term, within 12 months. We will also explore whether mobile phone applications are effective in supporting behavioural change and sustainable weight loss. The present study is a longitudinal randomized controlled trial (RCT) to study the effectiveness of a three-component 1-year cognitive-behavioural lifestyle intervention in overweight/obese women with PCOS. A total of 210 participants are randomly assigned to three groups: 1) CBT provided by the multidisciplinary team or; 2) CBT provided by the multidisciplinary team and Short Message Service (SMS) or; 3) usual care: encourage weight loss through publicly available services (control group). The primary aim of the 12-month intervention is to explore whether a three-component 1-year cognitive-behavioural lifestyle intervention is effective to decrease weight, when compared to usual care. Secondary outcomes include: the effect of the intervention on the PCOS phenotype, waist circumference, waist to hip ratio, ovulation rates, total testosterone, SHBG, free androgen index (FAI), AMH, hirsutism, acne, fasting glucose, blood pressure and all psychological parameters. Additionally, we assessed time to pregnancy, ongoing pregnancies, clinical pregnancies, miscarriages and birth weight. All
Connected Component Model for Multi-Object Tracking.
He, Zhenyu; Li, Xin; You, Xinge; Tao, Dacheng; Tang, Yuan Yan
2016-08-01
In multi-object tracking, it is critical to explore the data associations by exploiting the temporal information from a sequence of frames rather than the information from the adjacent two frames. Since straightforwardly obtaining data associations from multi-frames is an NP-hard multi-dimensional assignment (MDA) problem, most existing methods solve this MDA problem by either developing complicated approximate algorithms, or simplifying MDA as a 2D assignment problem based upon the information extracted only from adjacent frames. In this paper, we show that the relation between associations of two observations is the equivalence relation in the data association problem, based on the spatial-temporal constraint that the trajectories of different objects must be disjoint. Therefore, the MDA problem can be equivalently divided into independent subproblems by equivalence partitioning. In contrast to existing works for solving the MDA problem, we develop a connected component model (CCM) by exploiting the constraints of the data association and the equivalence relation on the constraints. Based upon CCM, we can efficiently obtain the global solution of the MDA problem for multi-object tracking by optimizing a sequence of independent data association subproblems. Experiments on challenging public data sets demonstrate that our algorithm outperforms the state-of-the-art approaches.
Two-component network model in voice identification technologies
Directory of Open Access Journals (Sweden)
Edita K. Kuular
2018-03-01
Full Text Available Among the most important parameters of biometric systems with voice modalities that determine their effectiveness, along with reliability and noise immunity, a speed of identification and verification of a person has been accentuated. This parameter is especially sensitive while processing large-scale voice databases in real time regime. Many research studies in this area are aimed at developing new and improving existing algorithms for presentation and processing voice records to ensure high performance of voice biometric systems. Here, it seems promising to apply a modern approach, which is based on complex network platform for solving complex massive problems with a large number of elements and taking into account their interrelationships. Thus, there are known some works which while solving problems of analysis and recognition of faces from photographs, transform images into complex networks for their subsequent processing by standard techniques. One of the first applications of complex networks to sound series (musical and speech analysis are description of frequency characteristics by constructing network models - converting the series into networks. On the network ontology platform a previously proposed technique of audio information representation aimed on its automatic analysis and speaker recognition has been developed. This implies converting information into the form of associative semantic (cognitive network structure with amplitude and frequency components both. Two speaker exemplars have been recorded and transformed into pertinent networks with consequent comparison of their topological metrics. The set of topological metrics for each of network models (amplitude and frequency one is a vector, and together those combine a matrix, as a digital "network" voiceprint. The proposed network approach, with its sensitivity to personal conditions-physiological, psychological, emotional, might be useful not only for person identification
Focused information criterion and model averaging based on weighted composite quantile regression
Xu, Ganggang; Wang, Suojin; Huang, Jianhua Z.
2013-01-01
We study the focused information criterion and frequentist model averaging and their application to post-model-selection inference for weighted composite quantile regression (WCQR) in the context of the additive partial linear models. With the non
Forecast Accuracy and Economic Gains from Bayesian Model Averaging using Time Varying Weights
L.F. Hoogerheide (Lennart); R.H. Kleijn (Richard); H.K. van Dijk (Herman); M.J.C.M. Verbeek (Marno)
2009-01-01
textabstractSeveral Bayesian model combination schemes, including some novel approaches that simultaneously allow for parameter uncertainty, model uncertainty and robust time varying model weights, are compared in terms of forecast accuracy and economic gains using financial and macroeconomic time
Li, Huibin
2014-06-01
In the theory of differential geometry, surface normal, as a first order surface differential quantity, determines the orientation of a surface at each point and contains informative local surface shape information. To fully exploit this kind of information for 3D face recognition (FR), this paper proposes a novel highly discriminative facial shape descriptor, namely multi-scale and multi-component local normal patterns (MSMC-LNP). Given a normalized facial range image, three components of normal vectors are first estimated, leading to three normal component images. Then, each normal component image is encoded locally to local normal patterns (LNP) on different scales. To utilize spatial information of facial shape, each normal component image is divided into several patches, and their LNP histograms are computed and concatenated according to the facial configuration. Finally, each original facial surface is represented by a set of LNP histograms including both global and local cues. Moreover, to make the proposed solution robust to the variations of facial expressions, we propose to learn the weight of each local patch on a given encoding scale and normal component image. Based on the learned weights and the weighted LNP histograms, we formulate a weighted sparse representation-based classifier (W-SRC). In contrast to the overwhelming majority of 3D FR approaches which were only benchmarked on the FRGC v2.0 database, we carried out extensive experiments on the FRGC v2.0, Bosphorus, BU-3DFE and 3D-TEC databases, thus including 3D face data captured in different scenarios through various sensors and depicting in particular different challenges with respect to facial expressions. The experimental results show that the proposed approach consistently achieves competitive rank-one recognition rates on these databases despite their heterogeneous nature, and thereby demonstrates its effectiveness and its generalizability. © 2014 Elsevier B.V.
Weighted-indexed semi-Markov models for modeling financial returns
International Nuclear Information System (INIS)
D’Amico, Guglielmo; Petroni, Filippo
2012-01-01
In this paper we propose a new stochastic model based on a generalization of semi-Markov chains for studying the high frequency price dynamics of traded stocks. We assume that the financial returns are described by a weighted-indexed semi-Markov chain model. We show, through Monte Carlo simulations, that the model is able to reproduce important stylized facts of financial time series such as the first-passage-time distributions and the persistence of volatility. The model is applied to data from the Italian and German stock markets from 1 January 2007 until the end of December 2010. (paper)
Model validation and calibration based on component functions of model output
International Nuclear Information System (INIS)
Wu, Danqing; Lu, Zhenzhou; Wang, Yanping; Cheng, Lei
2015-01-01
The target in this work is to validate the component functions of model output between physical observation and computational model with the area metric. Based on the theory of high dimensional model representations (HDMR) of independent input variables, conditional expectations are component functions of model output, and the conditional expectations reflect partial information of model output. Therefore, the model validation of conditional expectations tells the discrepancy between the partial information of the computational model output and that of the observations. Then a calibration of the conditional expectations is carried out to reduce the value of model validation metric. After that, a recalculation of the model validation metric of model output is taken with the calibrated model parameters, and the result shows that a reduction of the discrepancy in the conditional expectations can help decrease the difference in model output. At last, several examples are employed to demonstrate the rationality and necessity of the methodology in case of both single validation site and multiple validation sites. - Highlights: • A validation metric of conditional expectations of model output is proposed. • HDRM explains the relationship of conditional expectations and model output. • An improved approach of parameter calibration updates the computational models. • Validation and calibration process are applied at single site and multiple sites. • Validation and calibration process show a superiority than existing methods
An ontology for component-based models of water resource systems
Elag, Mostafa; Goodall, Jonathan L.
2013-08-01
Component-based modeling is an approach for simulating water resource systems where a model is composed of a set of components, each with a defined modeling objective, interlinked through data exchanges. Component-based modeling frameworks are used within the hydrologic, atmospheric, and earth surface dynamics modeling communities. While these efforts have been advancing, it has become clear that the water resources modeling community in particular, and arguably the larger earth science modeling community as well, faces a challenge of fully and precisely defining the metadata for model components. The lack of a unified framework for model component metadata limits interoperability between modeling communities and the reuse of models across modeling frameworks due to ambiguity about the model and its capabilities. To address this need, we propose an ontology for water resources model components that describes core concepts and relationships using the Web Ontology Language (OWL). The ontology that we present, which is termed the Water Resources Component (WRC) ontology, is meant to serve as a starting point that can be refined over time through engagement by the larger community until a robust knowledge framework for water resource model components is achieved. This paper presents the methodology used to arrive at the WRC ontology, the WRC ontology itself, and examples of how the ontology can aid in component-based water resources modeling by (i) assisting in identifying relevant models, (ii) encouraging proper model coupling, and (iii) facilitating interoperability across earth science modeling frameworks.
A Bayesian posterior predictive framework for weighting ensemble regional climate models
Directory of Open Access Journals (Sweden)
Y. Fan
2017-06-01
Full Text Available We present a novel Bayesian statistical approach to computing model weights in climate change projection ensembles in order to create probabilistic projections. The weight of each climate model is obtained by weighting the current day observed data under the posterior distribution admitted under competing climate models. We use a linear model to describe the model output and observations. The approach accounts for uncertainty in model bias, trend and internal variability, including error in the observations used. Our framework is general, requires very little problem-specific input, and works well with default priors. We carry out cross-validation checks that confirm that the method produces the correct coverage.
Prostate cancer detection from model-free T1-weighted time series and diffusion imaging
Haq, Nandinee F.; Kozlowski, Piotr; Jones, Edward C.; Chang, Silvia D.; Goldenberg, S. Larry; Moradi, Mehdi
2015-03-01
The combination of Dynamic Contrast Enhanced (DCE) images with diffusion MRI has shown great potential in prostate cancer detection. The parameterization of DCE images to generate cancer markers is traditionally performed based on pharmacokinetic modeling. However, pharmacokinetic models make simplistic assumptions about the tissue perfusion process, require the knowledge of contrast agent concentration in a major artery, and the modeling process is sensitive to noise and fitting instabilities. We address this issue by extracting features directly from the DCE T1-weighted time course without modeling. In this work, we employed a set of data-driven features generated by mapping the DCE T1 time course to its principal component space, along with diffusion MRI features to detect prostate cancer. The optimal set of DCE features is extracted with sparse regularized regression through a Least Absolute Shrinkage and Selection Operator (LASSO) model. We show that when our proposed features are used within the multiparametric MRI protocol to replace the pharmacokinetic parameters, the area under ROC curve is 0.91 for peripheral zone classification and 0.87 for whole gland classification. We were able to correctly classify 32 out of 35 peripheral tumor areas identified in the data when the proposed features were used with support vector machine classification. The proposed feature set was used to generate cancer likelihood maps for the prostate gland.
A probabilistic model for component-based shape synthesis
Kalogerakis, Evangelos; Chaudhuri, Siddhartha; Koller, Daphne; Koltun, Vladlen
2012-01-01
represents probabilistic relationships between properties of shape components, and relates them to learned underlying causes of structural variability within the domain. These causes are treated as latent variables, leading to a compact representation
Measurement and Modelling of MIC Components Using Conductive Lithographic Films
Shepherd, P. R.; Taylor, C.; Evans l, P. S. A.; Harrison, D. J.
2001-01-01
Conductive Lithographic Films (CLFs) have previously demonstrated useful properties in printed mi-crowave circuits, combining low cost with high speed of manufacture. In this paper we examine the formation of various passive components via the CLF process, which enables further integration of printed microwave integrated circuits. The printed components include vias, resistors and overlay capacitors, and offer viable alternatives to traditional manufacturing processes for Microwave Inte-grate...
Conceptual Model of Weight Management in Overweight and Obese African-American Females.
Sutton, Suzanne M; Magwood, Gayenell S; Nemeth, Lynne S; Jenkins, Carolyn M
2017-04-01
Weight management of overweight and obese (OWO) African-American females (AAFs) is a poorly defined concept, leading to ineffective treatment of overweight and obesity, prevention of health sequelae, and risk reduction. A conceptual model of the phenomenon of weight management in OWO AAFs was developed through dimensional analysis of the literature. Constructs were identified and sorted into the dimensions of perspective, context, conditions, process, and consequences and integrated into an explanatory matrix. Through dimensional analysis, weight management in OWO AAFs was characterized as a multidimensional concept, defined from the perspective of weight loss in community-dwelling AAFs. Behaviors associated with weight management are strongly influenced by intrinsic factors and extrinsic conditions, which influence engagement in the processes and consequences of weight management. The resulting conceptual model of weight management in OWO AAFs provides a framework for research interventions applicable in a variety of settings. © 2016 Wiley Periodicals, Inc.
Koch, Julian; Cüneyd Demirel, Mehmet; Stisen, Simon
2018-05-01
The process of model evaluation is not only an integral part of model development and calibration but also of paramount importance when communicating modelling results to the scientific community and stakeholders. The modelling community has a large and well-tested toolbox of metrics to evaluate temporal model performance. In contrast, spatial performance evaluation does not correspond to the grand availability of spatial observations readily available and to the sophisticate model codes simulating the spatial variability of complex hydrological processes. This study makes a contribution towards advancing spatial-pattern-oriented model calibration by rigorously testing a multiple-component performance metric. The promoted SPAtial EFficiency (SPAEF) metric reflects three equally weighted components: correlation, coefficient of variation and histogram overlap. This multiple-component approach is found to be advantageous in order to achieve the complex task of comparing spatial patterns. SPAEF, its three components individually and two alternative spatial performance metrics, i.e. connectivity analysis and fractions skill score, are applied in a spatial-pattern-oriented model calibration of a catchment model in Denmark. Results suggest the importance of multiple-component metrics because stand-alone metrics tend to fail to provide holistic pattern information. The three SPAEF components are found to be independent, which allows them to complement each other in a meaningful way. In order to optimally exploit spatial observations made available by remote sensing platforms, this study suggests applying bias insensitive metrics which further allow for a comparison of variables which are related but may differ in unit. This study applies SPAEF in the hydrological context using the mesoscale Hydrologic Model (mHM; version 5.8), but we see great potential across disciplines related to spatially distributed earth system modelling.
2015-04-24
debonding, matrix cracking , and fiber breakage have been considered for creating blast mitigation configurations [17]. For similar purposes...to demonstrate a process for identifying suitable stiffness, inertia , and damping characteristics of the various components. In addition to the
Weight information labels on media models reduce body dissatisfaction in adolescent girls
Veldhuis, Jolanda; Konijn, Elly A; Seidell, Jacob C
2012-01-01
PURPOSE: To examine how weight information labels on variously sized media models affect (pre)adolescent girls' body perceptions and how they compare themselves with media models. METHODS: We used a three (body shape: extremely thin vs. thin vs. normal weight) × three (information label: 6-kg
Wu, Ya-Ke; Chu, Nain-Feng
2015-01-01
Overweight and obesity are serious public health and medical problems among children and adults worldwide. Behavioural change has been demonstrably contributory to weight management programs. Behavioural change-based weight loss programs require a theoretical framework. We will review the transtheoretical model and the organisational development theory in weight management. The transtheoretical model is a behaviour theory of individual level frequently used for weight management programs. The organisational development theory is a more complicated behaviour theory that applies to behavioural change on the system level. Both of these two theories have their respective strengths and weaknesses. In this manuscript, we try to introduce the transtheoretical model and the organisational development theory in the context of weight loss programs among population that are overweight or obese. Ultimately, we wish to present a new framework/strategy of weight management by integrating these two theories together. Copyright © 2015 Asian Oceanian Association for the Study of Obesity. Published by Elsevier Ltd. All rights reserved.
Directory of Open Access Journals (Sweden)
Jinlu Sheng
2016-07-01
Full Text Available To effectively extract the typical features of the bearing, a new method that related the local mean decomposition Shannon entropy and improved kernel principal component analysis model was proposed. First, the features are extracted by time–frequency domain method, local mean decomposition, and using the Shannon entropy to process the original separated product functions, so as to get the original features. However, the features been extracted still contain superfluous information; the nonlinear multi-features process technique, kernel principal component analysis, is introduced to fuse the characters. The kernel principal component analysis is improved by the weight factor. The extracted characteristic features were inputted in the Morlet wavelet kernel support vector machine to get the bearing running state classification model, bearing running state was thereby identified. Cases of test and actual were analyzed.
Parameters Estimation of Geographically Weighted Ordinal Logistic Regression (GWOLR) Model
Zuhdi, Shaifudin; Retno Sari Saputro, Dewi; Widyaningsih, Purnami
2017-06-01
A regression model is the representation of relationship between independent variable and dependent variable. The dependent variable has categories used in the logistic regression model to calculate odds on. The logistic regression model for dependent variable has levels in the logistics regression model is ordinal. GWOLR model is an ordinal logistic regression model influenced the geographical location of the observation site. Parameters estimation in the model needed to determine the value of a population based on sample. The purpose of this research is to parameters estimation of GWOLR model using R software. Parameter estimation uses the data amount of dengue fever patients in Semarang City. Observation units used are 144 villages in Semarang City. The results of research get GWOLR model locally for each village and to know probability of number dengue fever patient categories.
Karim, Mohammad Ehsanul; Platt, Robert W
2017-06-15
Correct specification of the inverse probability weighting (IPW) model is necessary for consistent inference from a marginal structural Cox model (MSCM). In practical applications, researchers are typically unaware of the true specification of the weight model. Nonetheless, IPWs are commonly estimated using parametric models, such as the main-effects logistic regression model. In practice, assumptions underlying such models may not hold and data-adaptive statistical learning methods may provide an alternative. Many candidate statistical learning approaches are available in the literature. However, the optimal approach for a given dataset is impossible to predict. Super learner (SL) has been proposed as a tool for selecting an optimal learner from a set of candidates using cross-validation. In this study, we evaluate the usefulness of a SL in estimating IPW in four different MSCM simulation scenarios, in which we varied the specification of the true weight model specification (linear and/or additive). Our simulations show that, in the presence of weight model misspecification, with a rich and diverse set of candidate algorithms, SL can generally offer a better alternative to the commonly used statistical learning approaches in terms of MSE as well as the coverage probabilities of the estimated effect in an MSCM. The findings from the simulation studies guided the application of the MSCM in a multiple sclerosis cohort from British Columbia, Canada (1995-2008), to estimate the impact of beta-interferon treatment in delaying disability progression. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.
Using Avatars to Model Weight Loss Behaviors: Participant Attitudes and Technology Development
Napolitano, Melissa A.; Hayes, Sharon; Russo, Giuseppe; Muresu, Debora; Giordano, Antonio; Foster, Gary D.
2013-01-01
Background: Virtual reality and other avatar-based technologies are potential methods for demonstrating and modeling weight loss behaviors. This study examined avatar-based technology as a tool for modeling weight loss behaviors. Methods: This study consisted of two phases: (1) an online survey to obtain feedback about using avatars for modeling weight loss behaviors and (2) technology development and usability testing to create an avatar-based technology program for modeling weight loss behaviors. Results: Results of phase 1 (n = 128) revealed that interest was high, with 88.3% stating that they would participate in a program that used an avatar to help practice weight loss skills in a virtual environment. In phase 2, avatars and modules to model weight loss skills were developed. Eight women were recruited to participate in a 4-week usability test, with 100% reporting they would recommend the program and that it influenced their diet/exercise behavior. Most women (87.5%) indicated that the virtual models were helpful. After 4 weeks, average weight loss was 1.6 kg (standard deviation = 1.7). Conclusion: This investigation revealed a high level of interest in an avatar-based program, with formative work indicating promise. Given the high costs associated with in vivo exposure and practice, this study demonstrates the potential use of avatar-based technology as a tool for modeling weight loss behaviors. PMID:23911189
Thomas, Diana M; Ivanescu, Andrada E; Martin, Corby K; Heymsfield, Steven B; Marshall, Kaitlyn; Bodrato, Victoria E; Williamson, Donald A; Anton, Stephen D; Sacks, Frank M; Ryan, Donna; Bray, George A
2015-03-01
Currently, early weight-loss predictions of long-term weight-loss success rely on fixed percent-weight-loss thresholds. The objective was to develop thresholds during the first 3 mo of intervention that include the influence of age, sex, baseline weight, percent weight loss, and deviations from expected weight to predict whether a participant is likely to lose 5% or more body weight by year 1. Data consisting of month 1, 2, 3, and 12 treatment weights were obtained from the 2-y Preventing Obesity Using Novel Dietary Strategies (POUNDS Lost) intervention. Logistic regression models that included covariates of age, height, sex, baseline weight, target energy intake, percent weight loss, and deviation of actual weight from expected were developed for months 1, 2, and 3 that predicted the probability of losing model. The AUC statistic quantified the ROC curve's capacity to classify participants likely to lose models yielding the highest AUC were retained as optimal. For comparison with current practice, ROC curves relying solely on percent weight loss were also calculated. Optimal models for months 1, 2, and 3 yielded ROC curves with AUCs of 0.68 (95% CI: 0.63, 0.74), 0.75 (95% CI: 0.71, 0.81), and 0.79 (95% CI: 0.74, 0.84), respectively. Percent weight loss alone was not better at identifying true positives than random chance (AUC ≤0.50). The newly derived models provide a personalized prediction of long-term success from early weight-loss variables. The predictions improve on existing fixed percent-weight-loss thresholds. Future research is needed to explore model application for informing treatment approaches during early intervention. © 2015 American Society for Nutrition.
Design and Application of an Ontology for Component-Based Modeling of Water Systems
Elag, M.; Goodall, J. L.
2012-12-01
Many Earth system modeling frameworks have adopted an approach of componentizing models so that a large model can be assembled by linking a set of smaller model components. These model components can then be more easily reused, extended, and maintained by a large group of model developers and end users. While there has been a notable increase in component-based model frameworks in the Earth sciences in recent years, there has been less work on creating framework-agnostic metadata and ontologies for model components. Well defined model component metadata is needed, however, to facilitate sharing, reuse, and interoperability both within and across Earth system modeling frameworks. To address this need, we have designed an ontology for the water resources community named the Water Resources Component (WRC) ontology in order to advance the application of component-based modeling frameworks across water related disciplines. Here we present the design of the WRC ontology and demonstrate its application for integration of model components used in watershed management. First we show how the watershed modeling system Soil and Water Assessment Tool (SWAT) can be decomposed into a set of hydrological and ecological components that adopt the Open Modeling Interface (OpenMI) standard. Then we show how the components can be used to estimate nitrogen losses from land to surface water for the Baltimore Ecosystem study area. Results of this work are (i) a demonstration of how the WRC ontology advances the conceptual integration between components of water related disciplines by handling the semantic and syntactic heterogeneity present when describing components from different disciplines and (ii) an investigation of a methodology by which large models can be decomposed into a set of model components that can be well described by populating metadata according to the WRC ontology.
Obesity and internalized weight stigma: a formulation model for an emerging psychological problem.
Ratcliffe, Denise; Ellison, Nell
2015-03-01
Obese individuals frequently experience weight stigma and this is associated with psychological distress and difficulties. The process of external devaluation can lead to negative self-perception and evaluation and some obese individuals develop "internalized weight stigma". The prevalence of weight stigma is well established but there is a lack of information about the interplay between external and internal weight stigma. To synthesize the literature on the psychological effects of weight stigma into a formulation model that addresses the maintenance of internalized weight stigma. Current research on the psychological impact of weight stigma was reviewed. We identify cognitive, behavioural and attentional processes that maintain psychological conditions where self-evaluation plays a central role. A model was developed based on clinical utility. The model focuses on identifying factors that influence and maintain internalized weight stigma. We highlight the impact of negative societal and interpersonal experiences of weight stigma on how individuals view themselves as an obese person. Processing the self as a stigmatized individual is at the core of the model. Maintenance factors include negative self-judgements about the meaning of being an obese individual, attentional and mood shifts, and avoidance and safety behaviours. In addition, eating and weight management behaviours become deregulated and maintain both obesity and weight stigma. As obesity increases, weight stigma and the associated psychological effects are likely to increase. We provide a framework for formulating and intervening with internalized weight stigma as well as making therapists aware of the applicability and transferability of strategies that they may already use with other presenting problems.
Monitor-Based Statistical Model Checking for Weighted Metric Temporal Logic
DEFF Research Database (Denmark)
Bulychev, Petr; David, Alexandre; Larsen, Kim Guldstrand
2012-01-01
We present a novel approach and implementation for ana- lysing weighted timed automata (WTA) with respect to the weighted metric temporal logic (WMTL≤ ). Based on a stochastic semantics of WTAs, we apply statistical model checking (SMC) to estimate and test probabilities of satisfaction with desi......We present a novel approach and implementation for ana- lysing weighted timed automata (WTA) with respect to the weighted metric temporal logic (WMTL≤ ). Based on a stochastic semantics of WTAs, we apply statistical model checking (SMC) to estimate and test probabilities of satisfaction...
Tampubolon, Meabeng
2016-01-01
Decision support system (DSS) is a system that can assist a person in making decisions more effectively and efficiently. Given this system, problems faced can be solved, such as the determination of the best private universities. There beberpa methods that can be used in building a Weighted Method SPK like product and weighted sum models. Methods weighted product (WP) use multiplication to connect rating attributes, where each rating should be used with attribute weights pangka...
Chiu, Ming Ming; McBride-Chang, Catherine; Lin, Dan
2012-01-01
The authors tested the component model of reading (CMR) among 186,725 fourth grade students from 38 countries (45 regions) on five continents by analyzing the 2006 Progress in International Reading Literacy Study data using measures of ecological (country, family, school, teacher), psychological, and cognitive components. More than 91% of the differences in student difficulty occurred at the country (61%) and classroom (30%) levels (ecological), with less than 9% at the student level (cognitive and psychological). All three components were negatively associated with reading difficulties: cognitive (student's early literacy skills), ecological (family characteristics [socioeconomic status, number of books at home, and attitudes about reading], school characteristics [school climate and resources]), and psychological (students' attitudes about reading, reading self-concept, and being a girl). These results extend the CMR by demonstrating the importance of multiple levels of factors for reading deficits across diverse cultures.
Pu, Yuanyuan; Zou, Qingsong; Hou, Dianzhi; Zhang, Yiping; Chen, Shan
2017-01-20
Ultrasonic degradation of six dextran samples with different initial molecular weights (IMW) has been performed to investigate the degradation behavior and chain scission mechanism of dextrans. The weight-average molecular weight (Mw) and polydispersity index (D value) were monitored by High Performance Gel Permeation Chromatography (HPGPC). Results showed that Mw and D value decreased with increasing ultrasonic time, resulting in a more homologous dextran solution with lower molecular weight. A significant degradation occurred in dextrans with higher IMW, particularly at the initial stage of the ultrasonic treatment. The Malhotra model was found to well describe the molecular weight kinetics for all dextran samples. Experimental data was fitted into two chain scission models to study dextran chain scission mechanism and the model performance was compared. Results indicated that the midpoint scission model agreed well with experimental results, with a linear regression factor of R 2 >0.99. Copyright © 2016 Elsevier Ltd. All rights reserved.
Bikker, P.
1994-01-01
In pig production, optimization of the conversion of animal feeding-stuffs into body components, especially lean meat, requires knowledge of the response relationships between nutrient intake and animal performance. In this study, the separate effects of protein and energy intake on rate
Energy Technology Data Exchange (ETDEWEB)
Fleming, K.; Long, N.; Swindler, A.
2012-05-01
This paper describes the Building Component Library (BCL), the U.S. Department of Energy's (DOE) online repository of building components that can be directly used to create energy models. This comprehensive, searchable library consists of components and measures as well as the metadata which describes them. The library is also designed to allow contributors to easily add new components, providing a continuously growing, standardized list of components for users to draw upon.
A New Global Regression Analysis Method for the Prediction of Wind Tunnel Model Weight Corrections
Ulbrich, Norbert Manfred; Bridge, Thomas M.; Amaya, Max A.
2014-01-01
A new global regression analysis method is discussed that predicts wind tunnel model weight corrections for strain-gage balance loads during a wind tunnel test. The method determines corrections by combining "wind-on" model attitude measurements with least squares estimates of the model weight and center of gravity coordinates that are obtained from "wind-off" data points. The method treats the least squares fit of the model weight separate from the fit of the center of gravity coordinates. Therefore, it performs two fits of "wind- off" data points and uses the least squares estimator of the model weight as an input for the fit of the center of gravity coordinates. Explicit equations for the least squares estimators of the weight and center of gravity coordinates are derived that simplify the implementation of the method in the data system software of a wind tunnel. In addition, recommendations for sets of "wind-off" data points are made that take typical model support system constraints into account. Explicit equations of the confidence intervals on the model weight and center of gravity coordinates and two different error analyses of the model weight prediction are also discussed in the appendices of the paper.
New approaches to the modelling of multi-component fuel droplet heating and evaporation
Sazhin, Sergei S
2015-02-25
The previously suggested quasi-discrete model for heating and evaporation of complex multi-component hydrocarbon fuel droplets is described. The dependence of density, viscosity, heat capacity and thermal conductivity of liquid components on carbon numbers n and temperatures is taken into account. The effects of temperature gradient and quasi-component diffusion inside droplets are taken into account. The analysis is based on the Effective Thermal Conductivity/Effective Diffusivity (ETC/ED) model. This model is applied to the analysis of Diesel and gasoline fuel droplet heating and evaporation. The components with relatively close n are replaced by quasi-components with properties calculated as average properties of the a priori defined groups of actual components. Thus the analysis of the heating and evaporation of droplets consisting of many components is replaced with the analysis of the heating and evaporation of droplets consisting of relatively few quasi-components. It is demonstrated that for Diesel and gasoline fuel droplets the predictions of the model based on five quasi-components are almost indistinguishable from the predictions of the model based on twenty quasi-components for Diesel fuel droplets and are very close to the predictions of the model based on thirteen quasi-components for gasoline fuel droplets. It is recommended that in the cases of both Diesel and gasoline spray combustion modelling, the analysis of droplet heating and evaporation is based on as little as five quasi-components.
DEFF Research Database (Denmark)
Nørgaard, Sisse A; Sand, Fredrik W; Sørensen, Dorte B
2018-01-01
The streptozotocin (STZ)-induced diabetic mouse is a widely used model of diabetes and diabetic nephropathy (DN). However, it is a well-known issue that this model is challenged by high weight loss, which despite supportive measures often results in high euthanization rates. To overcome...... these issues, we hypothesized that supplementing STZ-induced diabetic mice with water-softened chow in addition to normal chow would reduce weight loss, lower the need for supportive treatment, and reduce the number of mice reaching the humane endpoint of 20% weight loss. In a 15 week STZ-induced DN study we...... demonstrated that diabetic male mice receiving softened chow had reduced acute weight loss following STZ treatment ( p = 0.045) and additionally fewer mice were euthanized due to weight loss. By supplementing the diabetic mice with softened chow, no mice reached 20% weight loss whereas 37.5% of the mice...
MODELING OF SYSTEM COMPONENTS OF EDUCATIONAL PROGRAMS IN HIGH SCHOOL
Directory of Open Access Journals (Sweden)
E. K. Samerkhanova
2016-01-01
Full Text Available Based on the principles of System Studies, describes the components of the educational programs of the control system. Educational Program Management is a set of substantive, procedural, resource, subject-activity, efficiently and evaluation components, which ensures the integrity of integration processes at all levels of education. Ensuring stability and development in the management of educational programs is achieved by identifying and securing social norms, the status of the educational institution program managers to ensure the achievement of modern quality of education.Content Management provides the relevant educational content in accordance with the requirements of the educational and professional standards; process control ensures the efficient organization of rational distribution process flows; Resource Management provides optimal distribution of personnel, information and methodological, material and technical equipment of the educational program; contingent management provides subject-activity interaction of participants of the educational process; quality control ensures the quality of educational services.
Implementing components of the routines-based model
McWilliam, Robin; Fernández Valero, Rosa
2015-01-01
The MBR is comprised of 17 components that can generally be grouped into practices related to (a) functional assessment and intervention planning (for example, Routines-Based Interview), (b) organization of services (including location and staffing), (c) service delivery to children and families (using a consultative approach with families and teachers, integrated therapy), (d) classroom organization (for example, classroom zones), and (e) supervision and training through ch...
Virtual enterprise model for the electronic components business in the Nuclear Weapons Complex
Energy Technology Data Exchange (ETDEWEB)
Ferguson, T.J.; Long, K.S.; Sayre, J.A. [Sandia National Labs., Albuquerque, NM (United States); Hull, A.L. [Sandia National Labs., Livermore, CA (United States); Carey, D.A.; Sim, J.R.; Smith, M.G. [Allied-Signal Aerospace Co., Kansas City, MO (United States). Kansas City Div.
1994-08-01
The electronic components business within the Nuclear Weapons Complex spans organizational and Department of Energy contractor boundaries. An assessment of the current processes indicates a need for fundamentally changing the way electronic components are developed, procured, and manufactured. A model is provided based on a virtual enterprise that recognizes distinctive competencies within the Nuclear Weapons Complex and at the vendors. The model incorporates changes that reduce component delivery cycle time and improve cost effectiveness while delivering components of the appropriate quality.
Effect of Model Selection on Computed Water Balance Components
Jhorar, R.K.; Smit, A.A.M.F.R.; Roest, C.W.J.
2009-01-01
Soil water flow modelling approaches as used in four selected on-farm water management models, namely CROPWAT. FAIDS, CERES and SWAP, are compared through numerical experiments. The soil water simulation approaches used in the first three models are reformulated to incorporate ail evapotranspiration
Exploring component-based approaches in forest landscape modeling
H. S. He; D. R. Larsen; D. J. Mladenoff
2002-01-01
Forest management issues are increasingly required to be addressed in a spatial context, which has led to the development of spatially explicit forest landscape models. The numerous processes, complex spatial interactions, and diverse applications in spatial modeling make the development of forest landscape models difficult for any single research group. New...
Scalable Power-Component Models for Concept Testing
2011-08-17
motor speed can be either positive or negative dependent upon the propelling or regenerative braking scenario. The simulation provides three...the machine during generation or regenerative braking . To use the model, the user modifies the motor model criteria parameters by double-clicking... SYSTEMS ENGINEERING AND TECHNOLOGY SYMPOSIUM MODELING & SIMULATION, TESTING AND VALIDATION (MSTV) MINI-SYMPOSIUM AUGUST 9-11 DEARBORN, MICHIGAN
Modeling dynamics of biological and chemical components of aquatic ecosystems
International Nuclear Information System (INIS)
Lassiter, R.R.
1975-05-01
To provide capability to model aquatic ecosystems or their subsystems as needed for particular research goals, a modeling strategy was developed. Submodels of several processes common to aquatic ecosystems were developed or adapted from previously existing ones. Included are submodels for photosynthesis as a function of light and depth, biological growth rates as a function of temperature, dynamic chemical equilibrium, feeding and growth, and various types of losses to biological populations. These submodels may be used as modules in the construction of models of subsystems or ecosystems. A preliminary model for the nitrogen cycle subsystem was developed using the modeling strategy and applicable submodels. (U.S.)
Application of the weighted total field-scattering field technique to 3D-PSTD light scattering model
Hu, Shuai; Gao, Taichang; Liu, Lei; Li, Hao; Chen, Ming; Yang, Bo
2018-04-01
PSTD (Pseudo Spectral Time Domain) is an excellent model for the light scattering simulation of nonspherical aerosol particles. However, due to the particularity of its discretization form of the Maxwell's equations, the traditional Total Field/Scattering Field (TF/SF) technique for FDTD (Finite Differential Time Domain) is not applicable to PSTD, and the time-consuming pure scattering field technique is mainly applied to introduce the incident wave. To this end, the weighted TF/SF technique proposed by X. Gao is generalized and applied to the 3D-PSTD scattering model. Using this technique, the incident light can be effectively introduced by modifying the electromagnetic components in an inserted connecting region between the total field and the scattering field region with incident terms, where the incident terms are obtained by weighting the incident field by a window function. To optimally determine the thickness of connection region and the window function type for PSTD calculations, their influence on the modeling accuracy is firstly analyzed. To further verify the effectiveness and advantages of the weighted TF/SF technique, the improved PSTD model is validated against the PSTD model equipped with pure scattering field technique in both calculation accuracy and efficiency. The results show that, the performance of PSTD seems to be not sensitive to variation of window functions. The number of the connection layer required decreases with the increasing of spatial resolution, where for spatial resolution of 24 grids per wavelength, a 6-layer region is thick enough. The scattering phase matrices and integral scattering parameters obtained by the improved PSTD show an excellent consistency with those well-tested models for spherical and nonspherical particles, illustrating that the weighted TF/SF technique can introduce the incident precisely. The weighted TF/SF technique shows higher computational efficiency than pure scattering technique.
Energy Technology Data Exchange (ETDEWEB)
Fabiano, Sebastiano; Mancino, Stefano; Stefanini, Matteo; Chiocchi, Marcello; Simonetti, Giovanni [University ' ' Tor Vergata' ' , Department of Diagnostic Imaging, Molecular Imaging, Interventional Radiology, Nuclear Medicine and Radiotherapy, Rome (Italy); Mauriello, Alessandro; Spagnoli, Luigi Giusto [University ' ' Tor Vergata' ' , Department of Biopathology and Image Diagnostics, Institute of Anatomic Pathology, Rome (Italy)
2008-12-15
The American Heart Association modified classification for atherosclerotic plaque lesions has defined vulnerable plaques as those prone to rupture. The aim of our study was to assess the sensitivity and specificity of 1.5-T magnetic resonance imaging (MRI) in the evaluation of the characteristics of plaque components. Twelve carotid endarterectomy specimens were imaged by ex-vivo high-resolution 1.5-T MRI. Thirty-four cross-section axial images were selected for pixel-by-pixel basis analysis to demonstrate the most significant tissue features. Data were then submitted for histopathological examination and each specimen analysed in the light of the histological components (lipid core, fibrous tissue, fibrous/loose connective tissue, calcifications). The overall sensitivity and specificity rates for each tissue type were, respectively, 92% and 74% for the lipid core, 82% and 94% for the fibrous tissue, 72% and 87% for the fibrous/loose connective tissue, and 98% and 99% for calcification. The use of 1.5-T MRI appears to be a reliable tool to characterise plaque components and could help in the screening of patients with high risk of plaque rupture. The possibility of applying MRI in clinical daily practice may change the non-invasive approach to carotid artery diagnostic imaging, thus allowing an early identification of patients with vulnerable plaques. (orig.)
Multi-objective optimization for generating a weighted multi-model ensemble
Lee, H.
2017-12-01
Many studies have demonstrated that multi-model ensembles generally show better skill than each ensemble member. When generating weighted multi-model ensembles, the first step is measuring the performance of individual model simulations using observations. There is a consensus on the assignment of weighting factors based on a single evaluation metric. When considering only one evaluation metric, the weighting factor for each model is proportional to a performance score or inversely proportional to an error for the model. While this conventional approach can provide appropriate combinations of multiple models, the approach confronts a big challenge when there are multiple metrics under consideration. When considering multiple evaluation metrics, it is obvious that a simple averaging of multiple performance scores or model ranks does not address the trade-off problem between conflicting metrics. So far, there seems to be no best method to generate weighted multi-model ensembles based on multiple performance metrics. The current study applies the multi-objective optimization, a mathematical process that provides a set of optimal trade-off solutions based on a range of evaluation metrics, to combining multiple performance metrics for the global climate models and their dynamically downscaled regional climate simulations over North America and generating a weighted multi-model ensemble. NASA satellite data and the Regional Climate Model Evaluation System (RCMES) software toolkit are used for assessment of the climate simulations. Overall, the performance of each model differs markedly with strong seasonal dependence. Because of the considerable variability across the climate simulations, it is important to evaluate models systematically and make future projections by assigning optimized weighting factors to the models with relatively good performance. Our results indicate that the optimally weighted multi-model ensemble always shows better performance than an arithmetic
A fuzzy approach to the Weighted Overlap Dominance model
DEFF Research Database (Denmark)
Franco de los Rios, Camilo Andres; Hougaard, Jens Leth; Nielsen, Kurt
2013-01-01
Decision support models are required to handle the various aspects of multi-criteria decision problems in order to help the individual understand its possible solutions. In this sense, such models have to be capable of aggregating and exploiting different types of measurements and evaluations...... is presented for ordering and identifying the best alternatives under an interactive procedure that takes into account the natural imprecision and relevance of information....
Local Model Checking of Weighted CTL with Upper-Bound Constraints
DEFF Research Database (Denmark)
Jensen, Jonas Finnemann; Larsen, Kim Guldstrand; Srba, Jiri
2013-01-01
We present a symbolic extension of dependency graphs by Liu and Smolka in order to model-check weighted Kripke structures against the logic CTL with upper-bound weight constraints. Our extension introduces a new type of edges into dependency graphs and lifts the computation of fixed-points from...
A three-component, hierarchical model of executive attention
Whittle, Sarah; Pantelis, Christos; Testa, Renee; Tiego, Jeggan; Bellgrove, Mark
2017-01-01
Executive attention refers to the goal-directed control of attention. Existing models of executive attention distinguish between three correlated, but empirically dissociable, factors related to selectively attending to task-relevant stimuli (Selective Attention), inhibiting task-irrelevant responses (Response Inhibition), and actively maintaining goal-relevant information (Working Memory Capacity). In these models, Selective Attention and Response Inhibition are moderately strongly correlate...
Economic Modeling as a Component of Academic Strategic Planning.
MacKinnon, Joyce; Sothmann, Mark; Johnson, James
2001-01-01
Computer-based economic modeling was used to enable a school of allied health to define outcomes, identify associated costs, develop cost and revenue models, and create a financial planning system. As a strategic planning tool, it assisted realistic budgeting and improved efficiency and effectiveness. (Contains 18 references.) (SK)
Component vibration of VVER-reactors - diagnostics and modelling
International Nuclear Information System (INIS)
Altstadt, E.; Scheffler, M.; Weiss, F.P.
1994-01-01
The model comprises the whole primary circuit, including steam generators, loops, coolant pumps, main isolating valves and certainly the reactor pressure vessel and its internals. It was developed using the finite-element-code ANSYS. The model has a modular structure, so that various operational and assembling states can easily be considered. (orig./DG)
PyCatch: Component based hydrological catchment modelling
Lana-Renault, N.; Karssenberg, D.J.
2013-01-01
Dynamic numerical models are powerful tools for representing and studying environmental processes through time. Usually they are constructed with environmental modelling languages, which are high-level programming languages that operate at the level of thinking of the scientists. In this paper we
Character expansion methods for matrix models of dually weighted graphs
International Nuclear Information System (INIS)
Kazakov, V.A.; Staudacher, M.; Wynter, T.
1996-01-01
We consider generalized one-matrix models in which external fields allow control over the coordination numbers on both the original and dual lattices. We rederive in a simple fashion a character expansion formula for these models originally due to Itzykson and Di Francesco, and then demonstrate how to take the large N limit of this expansion. The relationship to the usual matrix model resolvent is elucidated. Our methods give as a by-product an extremely simple derivation of the Migdal integral equation describing the large N limit of the Itzykson-Zuber formula. We illustrate and check our methods by analysing a number of models solvable by traditional means. We then proceed to solve a new model: a sum over planar graphs possessing even coordination numbers on both the original and the dual lattice. We conclude by formulating equations for the case of arbitrary sets of even, self-dual coupling constants. This opens the way for studying the deep problem of phase transitions from random to flat lattices. (orig.). With 4 figs
a Quadtree Organization Construction and Scheduling Method for Urban 3d Model Based on Weight
Yao, C.; Peng, G.; Song, Y.; Duan, M.
2017-09-01
The increasement of Urban 3D model precision and data quantity puts forward higher requirements for real-time rendering of digital city model. Improving the organization, management and scheduling of 3D model data in 3D digital city can improve the rendering effect and efficiency. This paper takes the complexity of urban models into account, proposes a Quadtree construction and scheduling rendering method for Urban 3D model based on weight. Divide Urban 3D model into different rendering weights according to certain rules, perform Quadtree construction and schedule rendering according to different rendering weights. Also proposed an algorithm for extracting bounding box extraction based on model drawing primitives to generate LOD model automatically. Using the algorithm proposed in this paper, developed a 3D urban planning&management software, the practice has showed the algorithm is efficient and feasible, the render frame rate of big scene and small scene are both stable at around 25 frames.
A QUADTREE ORGANIZATION CONSTRUCTION AND SCHEDULING METHOD FOR URBAN 3D MODEL BASED ON WEIGHT
Directory of Open Access Journals (Sweden)
C. Yao
2017-09-01
Full Text Available The increasement of Urban 3D model precision and data quantity puts forward higher requirements for real-time rendering of digital city model. Improving the organization, management and scheduling of 3D model data in 3D digital city can improve the rendering effect and efficiency. This paper takes the complexity of urban models into account, proposes a Quadtree construction and scheduling rendering method for Urban 3D model based on weight. Divide Urban 3D model into different rendering weights according to certain rules, perform Quadtree construction and schedule rendering according to different rendering weights. Also proposed an algorithm for extracting bounding box extraction based on model drawing primitives to generate LOD model automatically. Using the algorithm proposed in this paper, developed a 3D urban planning&management software, the practice has showed the algorithm is efficient and feasible, the render frame rate of big scene and small scene are both stable at around 25 frames.
Modeling and Analysis of Component Faults and Reliability
DEFF Research Database (Denmark)
Le Guilly, Thibaut; Olsen, Petur; Ravn, Anders Peter
2016-01-01
This chapter presents a process to design and validate models of reactive systems in the form of communicating timed automata. The models are extended with faults associated with probabilities of occurrence. This enables a fault tree analysis of the system using minimal cut sets that are automati......This chapter presents a process to design and validate models of reactive systems in the form of communicating timed automata. The models are extended with faults associated with probabilities of occurrence. This enables a fault tree analysis of the system using minimal cut sets...... that are automatically generated. The stochastic information on the faults is used to estimate the reliability of the fault affected system. The reliability is given with respect to properties of the system state space. We illustrate the process on a concrete example using the Uppaal model checker for validating...... the ideal system model and the fault modeling. Then the statistical version of the tool, UppaalSMC, is used to find reliability estimates....
Shibata, Yoshiyuki; Imai, Shingo; Nobutomo, Tatsuya; Miyoshi, Tasuku; Yamamoto, Shin-Ichiroh
2010-01-01
The purpose of this study is to develop a body weight support gait training system for stroke and spinal cord injury. This system consists of a powered orthosis, treadmill and equipment of body weight support. Attachment of the powered orthosis is able to fit subject who has difference of body size. This powered orthosis is driven by pneumatic McKibben actuator. Actuators are arranged as pair of antagonistic bi-articular muscle model and two pairs of antagonistic mono-articular muscle model like human musculoskeletal system. Part of the equipment of body weight support suspend subject by wire harness, and body weight of subject is supported continuously by counter weight. The powered orthosis is attached equipment of body weight support by parallel linkage, and movement of the powered orthosis is limited at sagittal plane. Weight of the powered orthosis is compensated by parallel linkage with gas-spring. In this study, we developed system that has orthosis powered by pneumatic McKibben actuators and equipment of body weight support. We report detail of our developed body weight support gait training system.
Multiparticle production in a two-component dual parton model
International Nuclear Information System (INIS)
Aurenche, P.; Bopp, F.W.; Capella, A.; Kwiecinski, J.; Maire, M.; Ranft, J.; Tran Thanh Van, J.
1992-01-01
The dual parton model (DPM) describes soft and semihard multiparticle production. The version of the DPM presented in this paper includes soft and hard mechanisms as well as diffractive processes. The model is formulated as a Monte Carlo event generator. We calculate in this model, in the energy range of the hadron colliders, rapidity distributions and the rise of the rapidity plateau with the collision energy, transverse-momentum distributions and the rise of average transverse momenta with the collision energy, multiplicity distributions in different pseudorapidity regions, and transverse-energy distributions. For most of these quantities we find a reasonable agreement with experimental data
Time-series modeling of long-term weight self-monitoring data.
Helander, Elina; Pavel, Misha; Jimison, Holly; Korhonen, Ilkka
2015-08-01
Long-term self-monitoring of weight is beneficial for weight maintenance, especially after weight loss. Connected weight scales accumulate time series information over long term and hence enable time series analysis of the data. The analysis can reveal individual patterns, provide more sensitive detection of significant weight trends, and enable more accurate and timely prediction of weight outcomes. However, long term self-weighing data has several challenges which complicate the analysis. Especially, irregular sampling, missing data, and existence of periodic (e.g. diurnal and weekly) patterns are common. In this study, we apply time series modeling approach on daily weight time series from two individuals and describe information that can be extracted from this kind of data. We study the properties of weight time series data, missing data and its link to individuals behavior, periodic patterns and weight series segmentation. Being able to understand behavior through weight data and give relevant feedback is desired to lead to positive intervention on health behaviors.
A weighted coupling metric for business process models
Vanderfeesten, I.T.P.; Cardoso, J.; Reijers, H.A.; Eder, J.; Tomassen, S.L.; Opdahl, A.; Sindre, G.
2007-01-01
Various efforts recently aimed at the development of quality metrics for process models. In this paper, we propose a new notion of coupling, which has been used successfully in software engineering for many years. It extends other work by specifically incorporating the effects of different types of
Choo, Jina; Kang, Hyuncheol
2015-05-01
To identify predictors of initial weight loss among women with abdominal obesity by using a path model. Successful weight loss in the initial stages of long-term weight management may promote weight loss maintenance. A longitudinal study design. Study participants were 75 women with abdominal obesity, who were enrolled in a 12-month Community-based Heart and Weight Management Trial and followed until a 6-month assessment. The Weight Efficacy Lifestyle, Exercise Self-Efficacy and Health Promoting Lifestyle Profile-II measured diet self-efficacy, exercise self-efficacy and health-promoting behaviour respectively. All endogenous and exogenous variables used in our path model were change variables from baseline to 6 months. Data were collected between May 2011-May 2012. Based on the path model, increases in both diet and exercise self-efficacy had significant effects on increases in health-promoting behaviour. Increases in diet self-efficacy had a significant indirect effect on initial weight loss via increases in health-promoting behaviour. Increases in health-promoting behaviour had a significant effect on initial weight loss. Among women with abdominal obesity, increased diet self-efficacy and health-promoting behaviour were predictors of initial weight loss. A mechanism by which increased diet self-efficacy predicts initial weight loss may be partially attributable to health-promoting behavioural change. However, more work is still needed to verify causality. Based on the current findings, intensive nursing strategies for increasing self-efficacy for weight control and health-promoting behaviour may be essential components for better weight loss in the initial stage of a weight management intervention. © 2015 John Wiley & Sons Ltd.
Comprehensive FDTD modelling of photonic crystal waveguide components
DEFF Research Database (Denmark)
Lavrinenko, Andrei; Borel, Peter Ingo; Frandsen, Lars Hagedorn
2004-01-01
Planar photonic crystal waveguide structures have been modelled using the finite-difference-time-domain method and perfectly matched layers have been employed as boundary conditions. Comprehensive numerical calculations have been performed and compared to experimentally obtained transmission...
Background, design and conceptual model of the cluster randomized multiple-component workplace study
DEFF Research Database (Denmark)
Christensen, Jeanette Reffstrup; Bredahl, Thomas Viskum Gjelstrup; Hadrévi, Jenny
2016-01-01
health care workers. This was done through a multi-component intervention including 1) intelligent physical exercise training (IPET), dietary advice and weight loss (DAW) and cognitive behavioural training (CBT). DISCUSSION: The FRIDOM program has the potential to provide evidence-based knowledge...
New methods for the characterization of pyrocarbon; The two component model of pyrocarbon
Energy Technology Data Exchange (ETDEWEB)
Luhleich, H.; Sutterlin, L.; Hoven, H.; Nickel, H.
1972-04-19
In the first part, new experiments to clarify the origin of different pyrocarbon components are described. Three new methods (plasma-oxidation, wet-oxidation, ultrasonic method) are presented to expose the carbon black like component in the pyrocarbon deposited in fluidized beds. In the second part, a two component model of pyrocarbon is proposed and illustrated by examples.
System level modeling and component level control of fuel cells
Xue, Xingjian
This dissertation investigates the fuel cell systems and the related technologies in three aspects: (1) system-level dynamic modeling of both PEM fuel cell (PEMFC) and solid oxide fuel cell (SOFC); (2) condition monitoring scheme development of PEM fuel cell system using model-based statistical method; and (3) strategy and algorithm development of precision control with potential application in energy systems. The dissertation first presents a system level dynamic modeling strategy for PEM fuel cells. It is well known that water plays a critical role in PEM fuel cell operations. It makes the membrane function appropriately and improves the durability. The low temperature operating conditions, however, impose modeling difficulties in characterizing the liquid-vapor two phase change phenomenon, which becomes even more complex under dynamic operating conditions. This dissertation proposes an innovative method to characterize this phenomenon, and builds a comprehensive model for PEM fuel cell at the system level. The model features the complete characterization of multi-physics dynamic coupling effects with the inclusion of dynamic phase change. The model is validated using Ballard stack experimental result from open literature. The system behavior and the internal coupling effects are also investigated using this model under various operating conditions. Anode-supported tubular SOFC is also investigated in the dissertation. While the Nernst potential plays a central role in characterizing the electrochemical performance, the traditional Nernst equation may lead to incorrect analysis results under dynamic operating conditions due to the current reverse flow phenomenon. This dissertation presents a systematic study in this regard to incorporate a modified Nernst potential expression and the heat/mass transfer into the analysis. The model is used to investigate the limitations and optimal results of various operating conditions; it can also be utilized to perform the
The SOS model partition function and the elliptic weight functions
International Nuclear Information System (INIS)
Pakuliak, S; Silantyev, A; Rubtsov, V
2008-01-01
We generalized a recent observation (Khoroshkin and Pakuliak 2005 Theor. Math. Phys. 145 1373) that the partition function of the six-vertex model with domain wall boundary conditions can be obtained from a calculation of projections of the product of total currents in the quantum affine algebra U q (sl 2 -hat) in its current realization. A generalization is done for the elliptic current algebra (Enriquez and Felder 1998 Commun. Math. Phys. 195 651, Enriquez and Rubtsov 1997 Ann. Sci. Ecole Norm. Sup. 30 821). The projections of the product of total currents in this case are calculated explicitly and are presented as integral transforms of a product of the total currents. It is proved that the integral kernel of this transform is proportional to the partition function of the SOS model with domain wall boundary conditions
Connection between weighted LPC and higher-order statistics for AR model estimation
Kamp, Y.; Ma, C.
1993-01-01
This paper establishes the relationship between a weighted linear prediction method used for robust analysis of voiced speech and the autoregressive modelling based on higher-order statistics, known as cumulants
Berry, D.P.; Buckley, F.; Dillon, P.; Evans, R.D.; Rath, M.; Veerkamp, R.F.
2003-01-01
(Co)variance components for milk yield, body condition score (BCS), body weight (BW), BCS change and BW change over different herd-year mean milk yields (HMY) and nutritional environments (concentrate feeding level, grazing severity and silage quality) were estimated using a random regression model.
A QUADTREE ORGANIZATION CONSTRUCTION AND SCHEDULING METHOD FOR URBAN 3D MODEL BASED ON WEIGHT
C. Yao; G. Peng; Y. Song; M. Duan
2017-01-01
The increasement of Urban 3D model precision and data quantity puts forward higher requirements for real-time rendering of digital city model. Improving the organization, management and scheduling of 3D model data in 3D digital city can improve the rendering effect and efficiency. This paper takes the complexity of urban models into account, proposes a Quadtree construction and scheduling rendering method for Urban 3D model based on weight. Divide Urban 3D model into different rendering weigh...
A Bayesian Analysis of Unobserved Component Models Using Ox
Directory of Open Access Journals (Sweden)
Charles S. Bos
2011-05-01
Full Text Available This article details a Bayesian analysis of the Nile river flow data, using a similar state space model as other articles in this volume. For this data set, Metropolis-Hastings and Gibbs sampling algorithms are implemented in the programming language Ox. These Markov chain Monte Carlo methods only provide output conditioned upon the full data set. For filtered output, conditioning only on past observations, the particle filter is introduced. The sampling methods are flexible, and this advantage is used to extend the model to incorporate a stochastic volatility process. The volatility changes both in the Nile data and also in daily S&P 500 return data are investigated. The posterior density of parameters and states is found to provide information on which elements of the model are easily identifiable, and which elements are estimated with less precision.
Mass models for disk and halo components in spiral galaxies
International Nuclear Information System (INIS)
Athanassoula, E.; Bosma, A.
1987-01-01
The mass distribution in spiral galaxies is investigated by means of numerical simulations, summarizing the results reported by Athanassoula et al. (1986). Details of the modeling technique employed are given, including bulge-disk decomposition; computation of bulge and disk rotation curves (assuming constant mass/light ratios for each); and determination (for spherical symmetry) of the total halo mass out to the optical radius, the concentration indices, the halo-density power law, the core radius, the central density, and the velocity dispersion. Also discussed are the procedures for incorporating galactic gas and checking the spiral structure extent. It is found that structural constraints limit disk mass/light ratios to a range of 0.3 dex, and that the most likely models are maximum-disk models with m = 1 disturbances inhibited. 19 references
Modeling of a remote inspection system for NSSS components
International Nuclear Information System (INIS)
Choi, Yoo Rark; Kim, Jae Hee; Lee, Jae Cheol
2003-03-01
Safety inspection for safety-critical unit of nuclear power plant has been processed using off-line technology. Thus we can not access safety inspection system and inspection data via network such as internet. We are making an on-line control and data access system based on WWW and JAVA technologies which can be used during plant operation to overcome these problems. Users can access inspection systems and inspection data only using web-browser. This report discusses about analysis of the existing remote system and essential techniques such as Web, JAVA, client/server model, and multi-tier model. This report also discusses about a system modeling that we have been developed using these techniques and provides solutions for developing an on-line control and data access system
Ivanescu, Andrada E; Martin, Corby K; Heymsfield, Steven B; Marshall, Kaitlyn; Bodrato, Victoria E; Williamson, Donald A; Anton, Stephen D; Sacks, Frank M; Ryan, Donna; Bray, George A
2015-01-01
Background: Currently, early weight-loss predictions of long-term weight-loss success rely on fixed percent-weight-loss thresholds. Objective: The objective was to develop thresholds during the first 3 mo of intervention that include the influence of age, sex, baseline weight, percent weight loss, and deviations from expected weight to predict whether a participant is likely to lose 5% or more body weight by year 1. Design: Data consisting of month 1, 2, 3, and 12 treatment weights were obtained from the 2-y Preventing Obesity Using Novel Dietary Strategies (POUNDS Lost) intervention. Logistic regression models that included covariates of age, height, sex, baseline weight, target energy intake, percent weight loss, and deviation of actual weight from expected were developed for months 1, 2, and 3 that predicted the probability of losing <5% of body weight in 1 y. Receiver operating characteristic (ROC) curves, area under the curve (AUC), and thresholds were calculated for each model. The AUC statistic quantified the ROC curve’s capacity to classify participants likely to lose <5% of their body weight at the end of 1 y. The models yielding the highest AUC were retained as optimal. For comparison with current practice, ROC curves relying solely on percent weight loss were also calculated. Results: Optimal models for months 1, 2, and 3 yielded ROC curves with AUCs of 0.68 (95% CI: 0.63, 0.74), 0.75 (95% CI: 0.71, 0.81), and 0.79 (95% CI: 0.74, 0.84), respectively. Percent weight loss alone was not better at identifying true positives than random chance (AUC ≤0.50). Conclusions: The newly derived models provide a personalized prediction of long-term success from early weight-loss variables. The predictions improve on existing fixed percent-weight-loss thresholds. Future research is needed to explore model application for informing treatment approaches during early intervention. The POUNDS Lost study was registered at clinicaltrials.gov as NCT00072995. PMID:25733628
Three-Component Dust Models for Interstellar Extinction C ...
Indian Academy of Sciences (India)
without standard' method were used to constrain the dust characteristics in the mean ISM (RV = 3.1), ... Interstellar dust models have evolved as the observational data have advanced, and the most popular dust ... distribution comes from the IRAS observation which shows an excess of 12 μ and. 25 μ emission from the ISM ...
Ingels, John Spencer; Misra, Ranjita; Stewart, Jonathan; Lucke-Wold, Brandon; Shawley-Brzoska, Samantha
2017-01-01
The role of dietary tracking on weight loss remains unexplored despite being part of multiple diabetes and weight management programs. Hence, participants of the Diabetes Prevention and Management (DPM) program (12 months, 22 sessions) tracked their food intake for the duration of the study. A scatterplot of days tracked versus total weight loss revealed a nonlinear relationship. Hence, the number of possible tracking days was divided to create the 3 groups of participants: rare trackers (66% total days tracked). After controlling for initial body mass index, hemoglobin A 1c , and gender, only consistent trackers had significant weight loss (-9.99 pounds), following a linear relationship with consistent loss throughout the year. In addition, the weight loss trend for the rare and inconsistent trackers followed a nonlinear path, with the holidays slowing weight loss and the onset of summer increasing weight loss. These results show the importance of frequent dietary tracking for consistent long-term weight loss success.
Soil Structure - A Neglected Component of Land-Surface Models
Fatichi, S.; Or, D.; Walko, R. L.; Vereecken, H.; Kollet, S. J.; Young, M.; Ghezzehei, T. A.; Hengl, T.; Agam, N.; Avissar, R.
2017-12-01
Soil structure is largely absent in most standard sampling and measurements and in the subsequent parameterization of soil hydraulic properties deduced from soil maps and used in Earth System Models. The apparent omission propagates into the pedotransfer functions that deduce parameters of soil hydraulic properties primarily from soil textural information. Such simple parameterization is an essential ingredient in the practical application of any land surface model. Despite the critical role of soil structure (biopores formed by decaying roots, aggregates, etc.) in defining soil hydraulic functions, only a few studies have attempted to incorporate soil structure into models. They mostly looked at the effects on preferential flow and solute transport pathways at the soil profile scale; yet, the role of soil structure in mediating large-scale fluxes remains understudied. Here, we focus on rectifying this gap and demonstrating potential impacts on surface and subsurface fluxes and system wide eco-hydrologic responses. The study proposes a systematic way for correcting the soil water retention and hydraulic conductivity functions—accounting for soil-structure—with major implications for near saturated hydraulic conductivity. Modification to the basic soil hydraulic parameterization is assumed as a function of biological activity summarized by Gross Primary Production. A land-surface model with dynamic vegetation is used to carry out numerical simulations with and without the role of soil-structure for 20 locations characterized by different climates and biomes across the globe. Including soil structure affects considerably the partition between infiltration and runoff and consequently leakage at the base of the soil profile (recharge). In several locations characterized by wet climates, a few hundreds of mm per year of surface runoff become deep-recharge accounting for soil-structure. Changes in energy fluxes, total evapotranspiration and vegetation productivity
Feedback loops and temporal misalignment in component-based hydrologic modeling
Elag, Mostafa M.; Goodall, Jonathan L.; Castronova, Anthony M.
2011-12-01
In component-based modeling, a complex system is represented as a series of loosely integrated components with defined interfaces and data exchanges that allow the components to be coupled together through shared boundary conditions. Although the component-based paradigm is commonly used in software engineering, it has only recently been applied for modeling hydrologic and earth systems. As a result, research is needed to test and verify the applicability of the approach for modeling hydrologic systems. The objective of this work was therefore to investigate two aspects of using component-based software architecture for hydrologic modeling: (1) simulation of feedback loops between components that share a boundary condition and (2) data transfers between temporally misaligned model components. We investigated these topics using a simple case study where diffusion of mass is modeled across a water-sediment interface. We simulated the multimedia system using two model components, one for the water and one for the sediment, coupled using the Open Modeling Interface (OpenMI) standard. The results were compared with a more conventional numerical approach for solving the system where the domain is represented by a single multidimensional array. Results showed that the component-based approach was able to produce the same results obtained with the more conventional numerical approach. When the two components were temporally misaligned, we explored the use of different interpolation schemes to minimize mass balance error within the coupled system. The outcome of this work provides evidence that component-based modeling can be used to simulate complicated feedback loops between systems and guidance as to how different interpolation schemes minimize mass balance error introduced when components are temporally misaligned.
Component-based modeling of systems for automated fault tree generation
International Nuclear Information System (INIS)
Majdara, Aref; Wakabayashi, Toshio
2009-01-01
One of the challenges in the field of automated fault tree construction is to find an efficient modeling approach that can support modeling of different types of systems without ignoring any necessary details. In this paper, we are going to represent a new system of modeling approach for computer-aided fault tree generation. In this method, every system model is composed of some components and different types of flows propagating through them. Each component has a function table that describes its input-output relations. For the components having different operational states, there is also a state transition table. Each component can communicate with other components in the system only through its inputs and outputs. A trace-back algorithm is proposed that can be applied to the system model to generate the required fault trees. The system modeling approach and the fault tree construction algorithm are applied to a fire sprinkler system and the results are presented
Research on development model of nuclear component based on life cycle management
International Nuclear Information System (INIS)
Bao Shiyi; Zhou Yu; He Shuyan
2005-01-01
At present the development process of nuclear component, even nuclear component itself, is more and more supported by computer technology. This increasing utilization of the computer and software has led to the faster development of nuclear technology on one hand and also brought new problems on the other hand. Especially, the combination of hardware, software and humans has increased nuclear component system complexities to an unprecedented level. To solve this problem, Life Cycle Management technology is adopted in nuclear component system. Hence, an intensive discussion on the development process of a nuclear component is proposed. According to the characteristics of the nuclear component development, such as the complexities and strict safety requirements of the nuclear components, long-term design period, changeable design specifications and requirements, high capital investment, and satisfaction for engineering codes/standards, the development life-cycle model of nuclear component is presented. The development life-cycle model is classified at three levels, namely, component level development life-cycle, sub-component development life-cycle and component level verification/certification life-cycle. The purposes and outcomes of development processes are stated in detailed. A process framework for nuclear component based on system engineering and development environment of nuclear component is discussed for future research work. (authors)
Five-component propagation model for steam explosion analysis
International Nuclear Information System (INIS)
Yang, Y.; Moriyama, Kiyofumi; Park, H.S.; Maruyama, Yu; Sugimoto, Jun
1999-01-01
A five-field simulation code JASMINE-pro has been developed at JAERI for the calculation of the propagation and explosion phase of steam explosions. The basic equations and the constitutive relationships specifically utilized in the propagation models in the code are introduced in this paper. Some calculations simulating the KROTOS 1D and 2D steam explosion experiments are also stated in the paper to show the present capability of the code. (author)
Component-oriented approach to the development and use of numerical models in high energy physics
International Nuclear Information System (INIS)
Amelin, N.S.; Komogorov, M.Eh.
2002-01-01
We discuss the main concepts of a component approach to the development and use of numerical models in high energy physics. This approach is realized as the NiMax software system. The discussed concepts are illustrated by numerous examples of the system user session. In appendix chapter we describe physics and numerical algorithms of the model components to perform simulation of hadronic and nuclear collisions at high energies. These components are members of hadronic application modules that have been developed with the help of the NiMax system. Given report is served as an early release of the NiMax manual mainly for model component users
International Nuclear Information System (INIS)
Gu, Zhipeng; Huang, Bingxue; Li, Yiwen; Tian, Meng; Li, Li; Yu, Xixun
2016-01-01
To enhance implant stability and prolong the service life of artificial joint component, a new approach was proposed to improve the wear resistance of artificial joint component and endow artificial joint component with the biological efficacy of resistance to aseptic loosening. Strontium calcium polyphosphate (SCPP) were interfused in ultrahigh molecular weight polyethylene (UHMWPE) by a combination of liquid nitrogen ball-milling and flat-panel curing process to prepare the SCPP/UHMWPE composites. The micro-structure, mechanical characterization, tribological characterization and bioactivities of various SCPP/UHMWPE composites were investigated. The results suggested that this method could statistically improve the wear resistance of UHMWPE resulting from a good SCPP particle dispersion. Moreover, it is also observed that the SCPP/UHMWPE composites-wear particles could promote the production of OPG by osteoblasts and decrease the production of RANKL by osteoblasts, and then increase the OPG/RANKL ratio. This indicated that the SCPP/UHMWPE composites had potential efficacy to prevent and treat aseptic loosening. Above all, the SCPP/UHMWPE composites with a suitable SCPP content would be the promising materials for fabricating artificial joint component with ability to resist aseptic loosening. - Highlights: • SCPP/UHMWPE composites could enhance biological efficacy of resistance to aseptic loosening. • SCPP would improve biological efficacy with a few sacrifice of wear resistance. • The results might provide a promising wear-resistant material for fabricating acetabular cup.
Energy Technology Data Exchange (ETDEWEB)
Gu, Zhipeng [College of Polymer Science and Engineering, Sichuan University, Chengdu 610065 (China); Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu 610041 (China); Huang, Bingxue; Li, Yiwen [College of Polymer Science and Engineering, Sichuan University, Chengdu 610065 (China); Tian, Meng [Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu 610041 (China); Li, Li [Department of Oncology, the 452 Hospital of Chinese PLA, Chengdu 610021 (China); Yu, Xixun, E-mail: yuxixun@163.com [College of Polymer Science and Engineering, Sichuan University, Chengdu 610065 (China)
2016-04-01
To enhance implant stability and prolong the service life of artificial joint component, a new approach was proposed to improve the wear resistance of artificial joint component and endow artificial joint component with the biological efficacy of resistance to aseptic loosening. Strontium calcium polyphosphate (SCPP) were interfused in ultrahigh molecular weight polyethylene (UHMWPE) by a combination of liquid nitrogen ball-milling and flat-panel curing process to prepare the SCPP/UHMWPE composites. The micro-structure, mechanical characterization, tribological characterization and bioactivities of various SCPP/UHMWPE composites were investigated. The results suggested that this method could statistically improve the wear resistance of UHMWPE resulting from a good SCPP particle dispersion. Moreover, it is also observed that the SCPP/UHMWPE composites-wear particles could promote the production of OPG by osteoblasts and decrease the production of RANKL by osteoblasts, and then increase the OPG/RANKL ratio. This indicated that the SCPP/UHMWPE composites had potential efficacy to prevent and treat aseptic loosening. Above all, the SCPP/UHMWPE composites with a suitable SCPP content would be the promising materials for fabricating artificial joint component with ability to resist aseptic loosening. - Highlights: • SCPP/UHMWPE composites could enhance biological efficacy of resistance to aseptic loosening. • SCPP would improve biological efficacy with a few sacrifice of wear resistance. • The results might provide a promising wear-resistant material for fabricating acetabular cup.
Mathematical Model for Multicomponent Adsorption Equilibria Using Only Pure Component Data
DEFF Research Database (Denmark)
Marcussen, Lis
2000-01-01
A mathematical model for nonideal adsorption equilibria in multicomponent mixtures is developed. It is applied with good results for pure substances and for prediction of strongly nonideal multicomponent equilibria using only pure component data. The model accounts for adsorbent...
International Nuclear Information System (INIS)
Carl Stern; Martin Lee
1999-01-01
Phase I work studied the feasibility of developing software for automatic component calibration and error correction in beamline optics models. A prototype application was developed that corrects quadrupole field strength errors in beamline models
Carl-Stern
1999-01-01
Phase I work studied the feasibility of developing software for automatic component calibration and error correction in beamline optics models. A prototype application was developed that corrects quadrupole field strength errors in beamline models.
Three Fundamental Components of the Autopoiesic Leadership Model
Directory of Open Access Journals (Sweden)
Mateja Kalan
2017-06-01
Full Text Available Research Question (RQ: What type of leadership could be developed upon transformational leadership? Purpose: The purpose of the research was to create a new leadership style. Its variables can be further developed upon transformational leadership variables. Namely, this leadership style is known as a successful leadership style in successful organisations. Method: In the research of published papers from scientific databases, we relied on the triangulation of theories. To clarify the research question, we have researched different authors, who based their research papers on different hypotheses. In some articles, hypotheses were even contradictory. Results: Through the research, we have concluded that authors often changed certain variables when researching the topic of transformational leadership. We have correlated these variables and developed a new model, naming it autopoiesic leadership. Its main variables are (1 goal orientation, (2 emotional sensitivity, and (3 manager’s flexibility in organisations. Organisation: Our research can have a positive effect on managers in terms of recognising the importance of selected variables. Practical application of autopoiesic leadership can imply more efficiency in business processes of a company, increasing its financial performance. Society: Autopoiesic leadership is a leadership style that largely influences the use of the individual’s internal resources. Thus, she or he becomes internally motivated, and this is the basis for quality work. This strengthens employees’ social aspect which consequently also has a positive effect on their life outside the organisational system, i.e. their family and broader living environment. Originality: In the worldwide literature, we have noticed the concept autopoiesis in papers about management subjects, but the autopoiesic leadership model has not been developed so far. Limitations / Future Research: We based our research on the triangulation of theories
A two-component dark matter model with real singlet scalars ...
Indian Academy of Sciences (India)
2016-01-05
Jan 5, 2016 ... We propose a two-component dark matter (DM) model, each component of which is a real singlet scalar, to explain results from both direct and indirect detection experiments. We put the constraints on the model parameters from theoretical bounds, PLANCK relic density results and direct DM experiments.
Xu, Peng; Tian, Yin; Lei, Xu; Hu, Xiao; Yao, Dezhong
2008-12-01
How to localize the neural electric activities within brain effectively and precisely from the scalp electroencephalogram (EEG) recordings is a critical issue for current study in clinical neurology and cognitive neuroscience. In this paper, based on the charge source model and the iterative re-weighted strategy, proposed is a new maximum neighbor weight based iterative sparse source imaging method, termed as CMOSS (Charge source model based Maximum neighbOr weight Sparse Solution). Different from the weight used in focal underdetermined system solver (FOCUSS) where the weight for each point in the discrete solution space is independently updated in iterations, the new designed weight for each point in each iteration is determined by the source solution of the last iteration at both the point and its neighbors. Using such a new weight, the next iteration may have a bigger chance to rectify the local source location bias existed in the previous iteration solution. The simulation studies with comparison to FOCUSS and LORETA for various source configurations were conducted on a realistic 3-shell head model, and the results confirmed the validation of CMOSS for sparse EEG source localization. Finally, CMOSS was applied to localize sources elicited in a visual stimuli experiment, and the result was consistent with those source areas involved in visual processing reported in previous studies.
Relative Error Model Reduction via Time-Weighted Balanced Stochastic Singular Perturbation
DEFF Research Database (Denmark)
Tahavori, Maryamsadat; Shaker, Hamid Reza
2012-01-01
A new mixed method for relative error model reduction of linear time invariant (LTI) systems is proposed in this paper. This order reduction technique is mainly based upon time-weighted balanced stochastic model reduction method and singular perturbation model reduction technique. Compared...... by using the concept and properties of the reciprocal systems. The results are further illustrated by two practical numerical examples: a model of CD player and a model of the atmospheric storm track....
Modelling insights on the partition of evapotranspiration components across biomes
Fatichi, Simone; Pappas, Christoforos
2017-04-01
Recent studies using various methodologies have found a large variability (from 35 to 90%) in the ratio of transpiration to total evapotranspiration (denoted as T:ET) across biomes or even at the global scale. Concurrently, previous results suggest that T:ET is independent of mean precipitation and has a positive correlation with Leaf Area Index (LAI). We used the mechanistic ecohydrological model, T&C, with a refined process-based description of soil resistance and a detailed treatment of canopy biophysics and ecophysiology, to investigate T:ET across multiple biomes. Contrary to observation-based estimates, simulation results highlight a well-constrained range of mean T:ET across biomes that is also robust to perturbations of the most sensitive parameters. Simulated T:ET was confirmed to be independent of average precipitation, while it was found to be uncorrelated with LAI across biomes. Higher values of LAI increase evaporation from interception but suppress ground evaporation with the two effects largely cancelling each other in many sites. These results offer mechanistic, model-based, evidence to the ongoing research about the range of T:ET and the factors affecting its magnitude across biomes.
Virtual Models Linked with Physical Components in Construction
DEFF Research Database (Denmark)
Sørensen, Kristian Birch
The use of virtual models supports a fundamental change in the working practice of the construction industry. It changes the primary information carrier (drawings) from simple manually created depictions of the building under construction to visually realistic digital representations that also...... engineering and business development in an iterative and user needs centred system development process. The analysis of future business perspectives presents an extensive number of new working processes that can assist in solving major challenges in the construction industry. Three of the most promising...... practices and development of new ontologies. Based on the experiences gained in this PhD project, some of the important future challenges are also to show the benefits of using modern information and communication technology to practitioners in the construction industry and to communicate this knowledge...
Analysis of litter size and average litter weight in pigs using a recursive model
DEFF Research Database (Denmark)
Varona, Luis; Sorensen, Daniel; Thompson, Robin
2007-01-01
An analysis of litter size and average piglet weight at birth in Landrace and Yorkshire using a standard two-trait mixed model (SMM) and a recursive mixed model (RMM) is presented. The RMM establishes a one-way link from litter size to average piglet weight. It is shown that there is a one......-to-one correspondence between the parameters of SMM and RMM and that they generate equivalent likelihoods. As parameterized in this work, the RMM tests for the presence of a recursive relationship between additive genetic values, permanent environmental effects, and specific environmental effects of litter size......, on average piglet weight. The equivalent standard mixed model tests whether or not the covariance matrices of the random effects have a diagonal structure. In Landrace, posterior predictive model checking supports a model without any form of recursion or, alternatively, a SMM with diagonal covariance...
Reliability analysis of nuclear component cooling water system using semi-Markov process model
International Nuclear Information System (INIS)
Veeramany, Arun; Pandey, Mahesh D.
2011-01-01
Research highlights: → Semi-Markov process (SMP) model is used to evaluate system failure probability of the nuclear component cooling water (NCCW) system. → SMP is used because it can solve reliability block diagram with a mixture of redundant repairable and non-repairable components. → The primary objective is to demonstrate that SMP can consider Weibull failure time distribution for components while a Markov model cannot → Result: the variability in component failure time is directly proportional to the NCCW system failure probability. → The result can be utilized as an initiating event probability in probabilistic safety assessment projects. - Abstract: A reliability analysis of nuclear component cooling water (NCCW) system is carried out. Semi-Markov process model is used in the analysis because it has potential to solve a reliability block diagram with a mixture of repairable and non-repairable components. With Markov models it is only possible to assume an exponential profile for component failure times. An advantage of the proposed model is the ability to assume Weibull distribution for the failure time of components. In an attempt to reduce the number of states in the model, it is shown that usage of poly-Weibull distribution arises. The objective of the paper is to determine system failure probability under these assumptions. Monte Carlo simulation is used to validate the model result. This result can be utilized as an initiating event probability in probabilistic safety assessment projects.
Hill, Briony; Skouteris, Helen; McCabe, Marita; Milgrom, Jeannette; Kent, Bridie; Herring, Sharon J; Hartley-Clark, Linda; Gale, Janette
2013-02-01
nearly half of all women exceed the guideline recommended pregnancy weight gain for their Body Mass Index (BMI) category. Excessive gestational weight gain (GWG) is correlated positively with postpartum weight retention and is a predictor of long-term, higher BMI in mothers and their children. Psychosocial factors are generally not targeted in GWG behaviour change interventions, however, multifactorial, conceptual models that include these factors, may be useful in determining the pathways that contribute to excessive GWG. We propose a conceptual model, underpinned by health behaviour change theory, which outlines the psychosocial determinants of GWG, including the role of motivation and self-efficacy towards healthy behaviours. This model is based on a review of the existing literature in this area. there is increasing evidence to show that psychosocial factors, such as increased depressive symptoms, anxiety, lower self-esteem and body image dissatisfaction, are associated with excessive GWG. What is less known is how these factors might lead to excessive GWG. Our conceptual model proposes a pathway of factors that affect GWG, and may be useful for understanding the mechanisms by which interventions impact on weight management during pregnancy. This involves tracking the relationships among maternal psychosocial factors, including body image concerns, motivation to adopt healthy lifestyle behaviours, confidence in adopting healthy lifestyle behaviours for the purposes of weight management, and actual behaviour changes. health-care providers may improve weight gain outcomes in pregnancy if they assess and address psychosocial factors in pregnancy. Copyright © 2011 Elsevier Ltd. All rights reserved.
International Nuclear Information System (INIS)
Reynolds, Jacob G.
2013-01-01
Partial molar properties are the changes occurring when the fraction of one component is varied while the fractions of all other component mole fractions change proportionally. They have many practical and theoretical applications in chemical thermodynamics. Partial molar properties of chemical mixtures are difficult to measure because the component mole fractions must sum to one, so a change in fraction of one component must be offset with a change in one or more other components. Given that more than one component fraction is changing at a time, it is difficult to assign a change in measured response to a change in a single component. In this study, the Component Slope Linear Model (CSLM), a model previously published in the statistics literature, is shown to have coefficients that correspond to the intensive partial molar properties. If a measured property is plotted against the mole fraction of a component while keeping the proportions of all other components constant, the slope at any given point on a graph of this curve is the partial molar property for that constituent. Actually plotting this graph has been used to determine partial molar properties for many years. The CSLM directly includes this slope in a model that predicts properties as a function of the component mole fractions. This model is demonstrated by applying it to the constant pressure heat capacity data from the NaOH-NaAl(OH 4 H 2 O system, a system that simplifies Hanford nuclear waste. The partial molar properties of H 2 O, NaOH, and NaAl(OH) 4 are determined. The equivalence of the CSLM and the graphical method is verified by comparing results detennined by the two methods. The CSLM model has been previously used to predict the liquidus temperature of spinel crystals precipitated from Hanford waste glass. Those model coefficients are re-interpreted here as the partial molar spinel liquidus temperature of the glass components
Directory of Open Access Journals (Sweden)
Kelishadi Roya
2009-12-01
Full Text Available Abstract Objectives This study aimed to determine the prevalence of the metabolic syndrome, abnormalities of liver enzymes and sonographic fatty liver, as well as the inter-related associations in normal weight, overweight and obese children and adolescents. Methods This cross-sectional study was conducted among a sample of 1107 students (56.1% girls, aged 6-18 years in Isfahan, Iran. In addition to physical examination, fasting blood glucose, serum lipid profile and liver enzymes were determined. Liver sonography was performed among 931 participants. These variables were compared among participants with different body mass index (BMI categories. Results From lower to higher BMI category, alanine aminotransferase (ALT, total cholesterol, LDL-cholesterol, triglycerides and systolic blood pressure increased, and HDL-cholesterol decreased significantly. Elevated ALT, aspartate aminotransferase (AST and alkaline phosphatase (ALP were documented in respectively 4.1%, 6.6% and 9.8% of normal weight group. The corresponding figure was 9.5%, 9.8% and 9.1% in overweight group, and 16.9%, 14.9% and 10.8% in obese group, respectively. In all BMI categories, ALT increased significantly by increasing the number of the components of the metabolic syndrome. Odds ratio for elevated liver enzymes and sonographic fatty liver increased significantly with higher number of the components of the metabolic syndrome and higher BMI categories before and after adjustment for age. Conclusions Because of the interrelationship of biochemical and sonographic indexes of fatty liver with the components of the metabolic syndrome, and with increase in their number, it is suggested to determine the clinical impact of such association in future longitudinal studies.
Modelling the effect of mixture components on permeation through skin.
Ghafourian, T; Samaras, E G; Brooks, J D; Riviere, J E
2010-10-15
A vehicle influences the concentration of penetrant within the membrane, affecting its diffusivity in the skin and rate of transport. Despite the huge amount of effort made for the understanding and modelling of the skin absorption of chemicals, a reliable estimation of the skin penetration potential from formulations remains a challenging objective. In this investigation, quantitative structure-activity relationship (QSAR) was employed to relate the skin permeation of compounds to the chemical properties of the mixture ingredients and the molecular structures of the penetrants. The skin permeability dataset consisted of permeability coefficients of 12 different penetrants each blended in 24 different solvent mixtures measured from finite-dose diffusion cell studies using porcine skin. Stepwise regression analysis resulted in a QSAR employing two penetrant descriptors and one solvent property. The penetrant descriptors were octanol/water partition coefficient, logP and the ninth order path molecular connectivity index, and the solvent property was the difference between boiling and melting points. The negative relationship between skin permeability coefficient and logP was attributed to the fact that most of the drugs in this particular dataset are extremely lipophilic in comparison with the compounds in the common skin permeability datasets used in QSAR. The findings show that compounds formulated in vehicles with small boiling and melting point gaps will be expected to have higher permeation through skin. The QSAR was validated internally, using a leave-many-out procedure, giving a mean absolute error of 0.396. The chemical space of the dataset was compared with that of the known skin permeability datasets and gaps were identified for future skin permeability measurements. Copyright 2010 Elsevier B.V. All rights reserved.
On the Likely Utility of Hybrid Weights Optimized for Variances in Hybrid Error Covariance Models
Satterfield, E.; Hodyss, D.; Kuhl, D.; Bishop, C. H.
2017-12-01
Because of imperfections in ensemble data assimilation schemes, one cannot assume that the ensemble covariance is equal to the true error covariance of a forecast. Previous work demonstrated how information about the distribution of true error variances given an ensemble sample variance can be revealed from an archive of (observation-minus-forecast, ensemble-variance) data pairs. Here, we derive a simple and intuitively compelling formula to obtain the mean of this distribution of true error variances given an ensemble sample variance from (observation-minus-forecast, ensemble-variance) data pairs produced by a single run of a data assimilation system. This formula takes the form of a Hybrid weighted average of the climatological forecast error variance and the ensemble sample variance. Here, we test the extent to which these readily obtainable weights can be used to rapidly optimize the covariance weights used in Hybrid data assimilation systems that employ weighted averages of static covariance models and flow-dependent ensemble based covariance models. Univariate data assimilation and multi-variate cycling ensemble data assimilation are considered. In both cases, it is found that our computationally efficient formula gives Hybrid weights that closely approximate the optimal weights found through the simple but computationally expensive process of testing every plausible combination of weights.
A global weighted mean temperature model based on empirical orthogonal function analysis
Li, Qinzheng; Chen, Peng; Sun, Langlang; Ma, Xiaping
2018-03-01
A global empirical orthogonal function (EOF) model of the tropospheric weighted mean temperature called GEOFM_Tm was developed using high-precision Global Geodetic Observing System (GGOS) Atmosphere Tm data during the years 2008-2014. Due to the quick convergence of EOF decomposition, it is possible to use the first four EOF series, which consists base functions Uk and associated coefficients Pk, to represent 99.99% of the overall variance of the original data sets and its spatial-temporal variations. Results show that U1 displays a prominent latitude distribution profile with positive peaks located at low latitude region. U2 manifests an asymmetric pattern that positive values occurred over 30° in the Northern Hemisphere, and negative values were observed at other regions. U3 and U4 displayed significant anomalies in Tibet and North America, respectively. Annual variation is the major component of the first and second associated coefficients P1 and P2, whereas P3 and P4 mainly reflects both annual and semi-annual variation components. Furthermore, the performance of constructed GEOFM_Tm was validated by comparison with GTm_III and GTm_N with different kinds of data including GGOS Atmosphere Tm data in 2015 and radiosonde data from Integrated Global Radiosonde Archive (IGRA) in 2014. Generally speaking, GEOFM_Tm can achieve the same accuracy and reliability as GTm_III and GTm_N models in a global scale, even has improved in the Antarctic and Greenland regions. The MAE and RMS of GEOFM_Tm tend to be 2.49 K and 3.14 K with respect to GGOS Tm data, respectively; and 3.38 K and 4.23 K with respect to IGRA sounding data, respectively. In addition, those three models have higher precision at low latitude than middle and high latitude regions. The magnitude of Tm remains at the range of 220-300 K, presented a high correlation with geographic latitude. In the Northern Hemisphere, there was a significant enhancement at high latitude region reaching 270 K during summer
Zoraghi, Nima; Amiri, Maghsoud; Talebi, Golnaz; Zowghi, Mahdi
2013-12-01
This paper presents a fuzzy multi-criteria decision-making (FMCDM) model by integrating both subjective and objective weights for ranking and evaluating the service quality in hotels. The objective method selects weights of criteria through mathematical calculation, while the subjective method uses judgments of decision makers. In this paper, we use a combination of weights obtained by both approaches in evaluating service quality in hotel industries. A real case study that considered ranking five hotels is illustrated. Examples are shown to indicate capabilities of the proposed method.
Directory of Open Access Journals (Sweden)
Matthew Thakur
Full Text Available Joint degeneration observed in the rat monoiodoacetate (MIA model of osteoarthritis shares many histological features with the clinical condition. The accompanying pain phenotype has seen the model widely used to investigate the pathophysiology of osteoarthritis pain, and for preclinical screening of analgesic compounds. We have investigated the pathophysiological sequellae of MIA used at low (1 mg or high (2 mg dose. Intra-articular 2 mg MIA induced expression of ATF-3, a sensitive marker for peripheral neuron stress/injury, in small and large diameter DRG cell profiles principally at levels L4 and 5 (levels predominated by neurones innervating the hindpaw rather than L3. At the 7 day timepoint, ATF-3 signal was significantly smaller in 1 mg MIA treated animals than in the 2 mg treated group. 2 mg, but not 1 mg, intra-articular MIA was also associated with a significant reduction in intra-epidermal nerve fibre density in plantar hindpaw skin, and produced spinal cord dorsal and ventral horn microgliosis. The 2 mg treatment evoked mechanical pain-related hypersensitivity of the hindpaw that was significantly greater than the 1 mg treatment. MIA treatment produced weight bearing asymmetry and cold hypersensitivity which was similar at both doses. Additionally, while pregabalin significantly reduced deep dorsal horn evoked neuronal responses in animals treated with 2 mg MIA, this effect was much reduced or absent in the 1 mg or sham treated groups. These data demonstrate that intra-articular 2 mg MIA not only produces joint degeneration, but also evokes significant axonal injury to DRG cells including those innervating targets outside of the knee joint such as hindpaw skin. This significant neuropathic component needs to be taken into account when interpreting studies using this model, particularly at doses greater than 1 mg MIA.
A review of typical thermal fatigue failure models for solder joints of electronic components
Li, Xiaoyan; Sun, Ruifeng; Wang, Yongdong
2017-09-01
For electronic components, cyclic plastic strain makes it easier to accumulate fatigue damage than elastic strain. When the solder joints undertake thermal expansion or cold contraction, different thermal strain of the electronic component and its corresponding substrate is caused by the different coefficient of thermal expansion of the electronic component and its corresponding substrate, leading to the phenomenon of stress concentration. So repeatedly, cracks began to sprout and gradually extend [1]. In this paper, the typical thermal fatigue failure models of solder joints of electronic components are classified and the methods of obtaining the parameters in the model are summarized based on domestic and foreign literature research.
Markov and semi-Markov switching linear mixed models used to identify forest tree growth components.
Chaubert-Pereira, Florence; Guédon, Yann; Lavergne, Christian; Trottier, Catherine
2010-09-01
Tree growth is assumed to be mainly the result of three components: (i) an endogenous component assumed to be structured as a succession of roughly stationary phases separated by marked change points that are asynchronous among individuals, (ii) a time-varying environmental component assumed to take the form of synchronous fluctuations among individuals, and (iii) an individual component corresponding mainly to the local environment of each tree. To identify and characterize these three components, we propose to use semi-Markov switching linear mixed models, i.e., models that combine linear mixed models in a semi-Markovian manner. The underlying semi-Markov chain represents the succession of growth phases and their lengths (endogenous component) whereas the linear mixed models attached to each state of the underlying semi-Markov chain represent-in the corresponding growth phase-both the influence of time-varying climatic covariates (environmental component) as fixed effects, and interindividual heterogeneity (individual component) as random effects. In this article, we address the estimation of Markov and semi-Markov switching linear mixed models in a general framework. We propose a Monte Carlo expectation-maximization like algorithm whose iterations decompose into three steps: (i) sampling of state sequences given random effects, (ii) prediction of random effects given state sequences, and (iii) maximization. The proposed statistical modeling approach is illustrated by the analysis of successive annual shoots along Corsican pine trunks influenced by climatic covariates. © 2009, The International Biometric Society.
Yu, Hong; Cao, Yong-Gang
2009-03-01
Physicians ask many complex questions during the patient encounter. Information retrieval systems that can provide immediate and relevant answers to these questions can be invaluable aids to the practice of evidence-based medicine. In this study, we first automatically identify topic keywords from ad hoc clinical questions with a Condition Random Field model that is trained over thousands of manually annotated clinical questions. We then report on a linear model that assigns query weights based on their automatically identified semantic roles: topic keywords, domain specific terms, and their synonyms. Our evaluation shows that this weighted keyword model improves information retrieval from the Text Retrieval Conference Genomics track data.
The attention-weighted sample-size model of visual short-term memory
DEFF Research Database (Denmark)
Smith, Philip L.; Lilburn, Simon D.; Corbett, Elaine A.
2016-01-01
exceeded that predicted by the sample-size model for both simultaneously and sequentially presented stimuli. Instead, the set-size effect and the serial position curves with sequential presentation were predicted by an attention-weighted version of the sample-size model, which assumes that one of the items...
Ryu, Duchwan; Liang, Faming; Mallick, Bani K.
2013-01-01
be modeled by a dynamic system which changes with time and location. In this article, we propose a radial basis function network-based dynamic model which is able to catch the nonlinearity of the data and propose to use the dynamically weighted particle
De Luca, G.; Magnus, J.R.
2011-01-01
In this article, we describe the estimation of linear regression models with uncertainty about the choice of the explanatory variables. We introduce the Stata commands bma and wals, which implement, respectively, the exact Bayesian model-averaging estimator and the weighted-average least-squares
Miao, Ming-San; Peng, Meng-Fan; Ma, Rui-Juan; Bai, Ming; Liu, Bao-Song
2018-03-01
Objective: To study the effects of the different components of the total flavonoids and total saponins from Mao Dongqing's active site on the rats of TIA model, determine the optimal reactive components ratio of Mao Dongqing on the rats of TIA. Methods: TIA rat model was induced by tail vein injection of tert butyl alcohol, the blank group was injected with the same amount of physiological saline, then behavioral score wasevaluated. Determination the level of glutamic acid in serum, the activity of Na+-K+-ATP enzyme, CA ++ -ATP enzyme and Mg ++ -ATP enzyme in Brain tissue, observe the changes of hippocampus in brain tissue, the comprehensive weight method was used to evaluate the efficacy of each component finally. Results: The contents of total flavonoids and total saponins in the active part of Mao Dongqing can significantly improve the pathological changes of brain tissue in rats, improve the activity of Na + -K + -ATP enzyme, Ca ++ -ATP enzyme and Mg ++ -ATP enzyme in the brain of rats, and reduce the level of glutamic acid in serum. The most significant of the contents was the ratio of 10:6. The different proportions of total flavonoids and total saponins in the active part of Mao Dongqing all has a better effect on the rats with TIA, and the ratio of 10:6 is the best active component for preventing and controlling TIA.
Characterizing long-term patterns of weight change in China using latent class trajectory modeling.
Directory of Open Access Journals (Sweden)
Lauren Paynter
Full Text Available Over the past three decades, obesity-related diseases have increased tremendously in China, and are now the leading causes of morbidity and mortality. Patterns of weight change can be used to predict risk of obesity-related diseases, increase understanding of etiology of disease risk, identify groups at particularly high risk, and shape prevention strategies.Latent class trajectory modeling was used to compute weight change trajectories for adults aged 18 to 66 using the China Health and Nutrition Survey (CHNS data (n = 12,611. Weight change trajectories were computed separately for males and females by age group at baseline due to differential age-related patterns of weight gain in China with urbanization. Generalized linear mixed effects models examined the association between weight change trajectories and baseline characteristics including urbanicity, BMI category, age, and year of study entry.Trajectory classes were identified for each of six age-sex subgroups corresponding to various degrees of weight loss, maintenance and weight gain. Baseline BMI status was a significant predictor of trajectory membership for all age-sex subgroups. Baseline overweight/obesity increased odds of following 'initial loss with maintenance' trajectories. We found no significant association between baseline urbanization and trajectory membership after controlling for other covariates.Trajectory analysis identified patterns of weight change for age by gender groups. Lack of association between baseline urbanization status and trajectory membership suggests that living in a rural environment at baseline was not protective. Analyses identified age-specific nuances in weight change patterns, pointing to the importance of subgroup analyses in future research.
Experiment planning using high-level component models at W7-X
International Nuclear Information System (INIS)
Lewerentz, Marc; Spring, Anett; Bluhm, Torsten; Heimann, Peter; Hennig, Christine; Kühner, Georg; Kroiss, Hugo; Krom, Johannes G.; Laqua, Heike; Maier, Josef; Riemann, Heike; Schacht, Jörg; Werner, Andreas; Zilker, Manfred
2012-01-01
Highlights: ► Introduction of models for an abstract description of fusion experiments. ► Component models support creating feasible experiment programs at planning time. ► Component models contain knowledge about physical and technical constraints. ► Generated views on models allow to present crucial information. - Abstract: The superconducting stellarator Wendelstein 7-X (W7-X) is a fusion device, which is capable of steady state operation. Furthermore W7-X is a very complex technical system. To cope with these requirements a modular and strongly hierarchical component-based control and data acquisition system has been designed. The behavior of W7-X is characterized by thousands of technical parameters of the participating components. The intended sequential change of those parameters during an experiment is defined in an experiment program. Planning such an experiment program is a crucial and complex task. To reduce the complexity an abstract, more physics-oriented high-level layer has been introduced earlier. The so-called high-level (physics) parameters are used to encapsulate technical details. This contribution will focus on the extension of this layer to a high-level component model. It completely describes the behavior of a component for a certain period of time. It allows not only defining simple value ranges but also complex dependencies between physics parameters. This can be: dependencies within components, dependencies between components or temporal dependencies. Component models can now be analyzed to generate various views of an experiment. A first implementation of such an analyze process is already finished. A graphical preview of a planned discharge can be generated from a chronological sequence of component models. This allows physicists to survey complex planned experiment programs at a glance.
Energy Technology Data Exchange (ETDEWEB)
Nordgaard, Erland Loeken
2009-07-01
The tendency during the past decades in the quality of oil reserves shows that conventional crude oil is gradually being depleted and the demand being replaced by heavy crude oils. These oils contain more of a class high-molecular weight components termed asphaltenes. This class is mainly responsible for stable water-in-crude oil emulsions. Both heavy and lighter crude oils in addition contain substantial amounts of naphthenic acids creating naphthenate deposits in topside facilities. The asphaltene class is defined by solubility and consists of several thousand different structures which may behave differently in oil-water systems. The nature of possible sub fractions of the asphaltene has been received more attention lately, but still the properties and composition of such is not completely understood. In this work, the problem has been addressed by synthesizing model compounds for the asphaltenes, on the basis that an acidic function incorporated could be crucial. Such acidic, poly aromatic surfactants turned out to be highly inter facially active as studied by the pendant drop technique. Langmuir monolayer compressions combined with fluorescence of deposited films indicated that the interfacial activity was a result of an efficient packing of the aromatic cores in the molecules, giving stabilizing interactions at the o/w interface. Droplet size distributions of emulsions studied by PFG NMR and adsorption onto hydrophilic silica particles demonstrated the high affinity to o/w interfaces and that the efficient packing gave higher emulsion stability. Comparing to a model compound lacking the acidic group, it was obvious that sub fractions of asphaltenes that contain an acidic, or maybe similar hydrogen bonding functions, could be responsible for stable w/o emulsions. Indigenous tetrameric acids are the main constituent of calcium naphthenate deposits. Several synthetic model tetra acids have been prepared and their properties have been compared to the indigenous
Han, Yuemei; Kawamura, Kimitaka; Chen, Qingcai; Mochida, Michihiro
2016-02-01
A laboratory study on the heterogeneous reactions of straight-chain aldehydes was performed by exposing n-octanal, nonanal, and decanal vapors to ambient aerosol particles. The aerosol and blank filters were extracted using methanol. The extracts were nebulized and the resulting compositions were examined using a high-resolution time-of-flight aerosol mass spectrometer. The mass spectral analysis showed that the exposures of the aldehydes to aerosol samples increased the peak intensities in the high mass range. The peaks in the mass spectra of the aerosol samples after exposure to different aldehydes were characterized by a homologous series of peak shifts due to the addition of multiple CH2 units. This result is explained by the formation of high-molecular-weight (HMW) compounds that contain single or multiple aldehyde moieties. The HMW fragment peaks for the blank filters exposed to n-aldehydes were relatively weak, indicating an important contribution from the ambient aerosol components to the formation of the HMW compounds. Among the factors affecting the overall interaction of aldehydes with atmospheric aerosol components, gas phase diffusion possibly limited the reactions under the studied conditions; therefore, their occurrence to a similar degree in the atmosphere is not ruled out, at least for the reactions involving n-nonanal and decanal. The major formation pathways for the observed HMW products may be the self-reactions of n-aldehydes mediated by atmospheric aerosol components and the reactions of n-aldehydes with organic aerosol components. The observed formation of HMW compounds encourages further investigations into their effects on the aerosol properties as well as the organic aerosol mass in the atmosphere.
Directory of Open Access Journals (Sweden)
Marjan Mansourian
2017-01-01
Full Text Available Background: In this study, we aimed to determine comprehensive maternal characteristics associated with birth weight using Bayesian modeling. Materials and Methods: A total of 526 participants were included in this prospective study. Nutritional status, supplement consumption during the pregnancy, demographic and socioeconomic characteristics, anthropometric measures, physical activity, and pregnancy outcomes were considered as effective variables on the birth weight. Bayesian approach of complex statistical models using Markov chain Monte Carlo approach was used for modeling the data considering the real distribution of the response variable. Results: There was strong positive correlation between infant birth weight and the maternal intake of Vitamin C, folic acid, Vitamin B3, Vitamin A, selenium, calcium, iron, phosphorus, potassium, magnesium as micronutrients, and fiber and protein as macronutrients based on the 95% high posterior density regions for parameters in the Bayesian model. None of the maternal characteristics had statistical association with birth weight. Conclusion: Higher maternal macro- and micro-nutrient intake during pregnancy was associated with a lower risk of delivering low birth weight infants. These findings support recommendations to expand intake of nutrients during pregnancy to high level.
The Impact of Weights on the Quality of Agricultural Producers' Multicriteria Decision Models
Directory of Open Access Journals (Sweden)
Agata Sielska
2015-01-01
Full Text Available Decisions regarding agricultural production involve multiple goals. A multicriteria approach allows decision makers to consider more aspects of the decision scenario, although it also leads to other problems, such as difficulties with the selection of goals or criteria, as well as assigning them appropriate weights. It is argued that not only do goals vary depending on the decision-makers' socioeconomic features, but their relative importance changes as well. A simulation study has been conducted based on the Farm Accountancy Data Network (FADN database. We use the distance-to-the-negative-solution maximization model. Seven sets of criteria and different sets of weights are considered. The main purpose of the study is to determine the impact of weights on the quality of the model. Quality is assessed by comparing the optimal and observed values of the decision variables. The results lead to the conclusion that the differences between the quality of various models are small. (original abstract
A new model for reliability optimization of series-parallel systems with non-homogeneous components
International Nuclear Information System (INIS)
Feizabadi, Mohammad; Jahromi, Abdolhamid Eshraghniaye
2017-01-01
In discussions related to reliability optimization using redundancy allocation, one of the structures that has attracted the attention of many researchers, is series-parallel structure. In models previously presented for reliability optimization of series-parallel systems, there is a restricting assumption based on which all components of a subsystem must be homogeneous. This constraint limits system designers in selecting components and prevents achieving higher levels of reliability. In this paper, a new model is proposed for reliability optimization of series-parallel systems, which makes possible the use of non-homogeneous components in each subsystem. As a result of this flexibility, the process of supplying system components will be easier. To solve the proposed model, since the redundancy allocation problem (RAP) belongs to the NP-hard class of optimization problems, a genetic algorithm (GA) is developed. The computational results of the designed GA are indicative of high performance of the proposed model in increasing system reliability and decreasing costs. - Highlights: • In this paper, a new model is proposed for reliability optimization of series-parallel systems. • In the previous models, there is a restricting assumption based on which all components of a subsystem must be homogeneous. • The presented model provides a possibility for the subsystems’ components to be non- homogeneous in the required conditions. • The computational results demonstrate the high performance of the proposed model in improving reliability and reducing costs.
Spahlholz, J; Pabst, A; Riedel-Heller, S G; Luck-Sikorski, C
2016-12-01
The association between obesity and perceived weight discrimination has been investigated in several studies. Although there is evidence that perceived weight discrimination is associated with negative outcomes on psychological well-being, there is a lack of research examining possible buffering effects of coping strategies in dealing with experiences of weight discrimination. The present study aims to fill that gap. We examined the relationship between perceived weight discrimination and depressive symptoms and tested whether problem-solving strategies and/or avoidant coping strategies mediated this effect. Using structural equation modeling, we analyzed representative cross-sectional data of n=484 German-speaking individuals with obesity (BMI⩾30 kg m -2 ), aged 18 years and older. Results revealed a direct effect of perceived weight discrimination on depressive symptoms. Further, the data supported a mediational linkage for avoidant coping strategies, not for problem-solving strategies. Higher scores of perceived weight discrimination experiences were associated with both coping strategies, but only avoidant coping strategies were positively linked to more symptoms of depression. Perceived weight discrimination was associated with increased depressive symptoms both directly and indirectly through situational coping strategies. Avoidant coping has the potential to exacerbate depressive symptoms, whereas problem-solving strategies were ineffective in dealing with experiences of weight discrimination. We emphasize the importance of coping strategies in dealing with experiences of weight discrimination and the need to distinguish between using a strategy and benefiting from it without detriment.
Directory of Open Access Journals (Sweden)
Ryan Louise
2007-11-01
Full Text Available Abstract Background The Conditional Autoregressive (CAR model is widely used in many small-area ecological studies to analyse outcomes measured at an areal level. There has been little evaluation of the influence of different neighbourhood weight matrix structures on the amount of smoothing performed by the CAR model. We examined this issue in detail. Methods We created several neighbourhood weight matrices and applied them to a large dataset of births and birth defects in New South Wales (NSW, Australia within 198 Statistical Local Areas. Between the years 1995–2003, there were 17,595 geocoded birth defects and 770,638 geocoded birth records with available data. Spatio-temporal models were developed with data from 1995–2000 and their fit evaluated within the following time period: 2001–2003. Results We were able to create four adjacency-based weight matrices, seven distance-based weight matrices and one matrix based on similarity in terms of a key covariate (i.e. maternal age. In terms of agreement between observed and predicted relative risks, categorised in epidemiologically relevant groups, generally the distance-based matrices performed better than the adjacency-based neighbourhoods. In terms of recovering the underlying risk structure, the weight-7 model (smoothing by maternal-age 'Covariate model' was able to correctly classify 35/47 high-risk areas (sensitivity 74% with a specificity of 47%, and the 'Gravity' model had sensitivity and specificity values of 74% and 39% respectively. Conclusion We found considerable differences in the smoothing properties of the CAR model, depending on the type of neighbours specified. This in turn had an effect on the models' ability to recover the observed risk in an area. Prior to risk mapping or ecological modelling, an exploratory analysis of the neighbourhood weight matrix to guide the choice of a suitable weight matrix is recommended. Alternatively, the weight matrix can be chosen a priori
DEFF Research Database (Denmark)
Pouzet, B; Mow, T; Kreilgaard, Mads
2003-01-01
compounds in an animal model of weight gain. With the aim of evaluating whether the rat can be used as a model for antipsychotic-induced weight gain, we have investigated the effect of chronic treatment (3 weeks) with one antipsychotic drug inducing weight gain in clinic (olanzapine) and one antipsychotic...
Amalia, Junita; Purhadi, Otok, Bambang Widjanarko
2017-11-01
Poisson distribution is a discrete distribution with count data as the random variables and it has one parameter defines both mean and variance. Poisson regression assumes mean and variance should be same (equidispersion). Nonetheless, some case of the count data unsatisfied this assumption because variance exceeds mean (over-dispersion). The ignorance of over-dispersion causes underestimates in standard error. Furthermore, it causes incorrect decision in the statistical test. Previously, paired count data has a correlation and it has bivariate Poisson distribution. If there is over-dispersion, modeling paired count data is not sufficient with simple bivariate Poisson regression. Bivariate Poisson Inverse Gaussian Regression (BPIGR) model is mix Poisson regression for modeling paired count data within over-dispersion. BPIGR model produces a global model for all locations. In another hand, each location has different geographic conditions, social, cultural and economic so that Geographically Weighted Regression (GWR) is needed. The weighting function of each location in GWR generates a different local model. Geographically Weighted Bivariate Poisson Inverse Gaussian Regression (GWBPIGR) model is used to solve over-dispersion and to generate local models. Parameter estimation of GWBPIGR model obtained by Maximum Likelihood Estimation (MLE) method. Meanwhile, hypothesis testing of GWBPIGR model acquired by Maximum Likelihood Ratio Test (MLRT) method.
Reduction of bias in neutron multiplicity assay using a weighted point model
Energy Technology Data Exchange (ETDEWEB)
Geist, W. H. (William H.); Krick, M. S. (Merlyn S.); Mayo, D. R. (Douglas R.)
2004-01-01
Accurate assay of most common plutonium samples was the development goal for the nondestructive assay technique of neutron multiplicity counting. Over the past 20 years the technique has been proven for relatively pure oxides and small metal items. Unfortunately, the technique results in large biases when assaying large metal items. Limiting assumptions, such as unifoh multiplication, in the point model used to derive the multiplicity equations causes these biases for large dense items. A weighted point model has been developed to overcome some of the limitations in the standard point model. Weighting factors are detemiined from Monte Carlo calculations using the MCNPX code. Monte Carlo calculations give the dependence of the weighting factors on sample mass and geometry, and simulated assays using Monte Carlo give the theoretical accuracy of the weighted-point-model assay. Measured multiplicity data evaluated with both the standard and weighted point models are compared to reference values to give the experimental accuracy of the assay. Initial results show significant promise for the weighted point model in reducing or eliminating biases in the neutron multiplicity assay of metal items. The negative biases observed in the assay of plutonium metal samples are caused by variations in the neutron multiplication for neutrons originating in various locations in the sample. The bias depends on the mass and shape of the sample and depends on the amount and energy distribution of the ({alpha},n) neutrons in the sample. When the standard point model is used, this variable-multiplication bias overestimates the multiplication and alpha values of the sample, and underestimates the plutonium mass. The weighted point model potentially can provide assay accuracy of {approx}2% (1 {sigma}) for cylindrical plutonium metal samples < 4 kg with {alpha} < 1 without knowing the exact shape of the samples, provided that the ({alpha},n) source is uniformly distributed throughout the
Finding Non-Zero Stable Fixed Points of the Weighted Kuramoto model is NP-hard
Taylor, Richard
2015-01-01
The Kuramoto model when considered over the full space of phase angles [$0,2\\pi$) can have multiple stable fixed points which form basins of attraction in the solution space. In this paper we illustrate the fundamentally complex relationship between the network topology and the solution space by showing that determining the possibility of multiple stable fixed points from the network topology is NP-hard for the weighted Kuramoto Model. In the case of the unweighted model this problem is shown...
A two-component dark matter model with real singlet scalars ...
Indian Academy of Sciences (India)
2016-01-05
component dark matter model with real singlet scalars confronting GeV -ray excess from galactic centre and Fermi bubble. Debasish Majumdar Kamakshya Prasad Modak Subhendu Rakshit. Special: Cosmology Volume 86 Issue ...
Model-Based Design Tools for Extending COTS Components To Extreme Environments, Phase II
National Aeronautics and Space Administration — The innovation in this project is model-based design (MBD) tools for predicting the performance and useful life of commercial-off-the-shelf (COTS) components and...
New approaches to the modelling of multi-component fuel droplet heating and evaporation
Sazhin, Sergei S; Elwardany, Ahmed E; Heikal, Morgan R
2015-01-01
numbers n and temperatures is taken into account. The effects of temperature gradient and quasi-component diffusion inside droplets are taken into account. The analysis is based on the Effective Thermal Conductivity/Effective Diffusivity (ETC/ED) model
Detailed finite element method modeling of evaporating multi-component droplets
Energy Technology Data Exchange (ETDEWEB)
Diddens, Christian, E-mail: C.Diddens@tue.nl
2017-07-01
The evaporation of sessile multi-component droplets is modeled with an axisymmetic finite element method. The model comprises the coupled processes of mixture evaporation, multi-component flow with composition-dependent fluid properties and thermal effects. Based on representative examples of water–glycerol and water–ethanol droplets, regular and chaotic examples of solutal Marangoni flows are discussed. Furthermore, the relevance of the substrate thickness for the evaporative cooling of volatile binary mixture droplets is pointed out. It is shown how the evaporation of the more volatile component can drastically decrease the interface temperature, so that ambient vapor of the less volatile component condenses on the droplet. Finally, results of this model are compared with corresponding results of a lubrication theory model, showing that the application of lubrication theory can cause considerable errors even for moderate contact angles of 40°. - Graphical abstract:.
DEFF Research Database (Denmark)
Janssen, Hans; Blocken, Bert; Carmeliet, Jan
2007-01-01
While the transfer equations for moisture and heat in building components are currently undergoing standardisation, atmospheric boundary conditions, conservative modelling and numerical efficiency are not addressed. In a first part, this paper adds a comprehensive description of those boundary...
A proposed centralised distribution model for the South African automotive component industry
Directory of Open Access Journals (Sweden)
Micheline J. Naude
2009-12-01
Full Text Available Purpose: This article explores the possibility of developing a distribution model, similar to the model developed and implemented by the South African pharmaceutical industry, which could be implemented by automotive component manufacturers for supply to independent retailers. Problem Investigated: The South African automotive components distribution chain is extensive with a number of players of varying sizes, from the larger spares distribution groups to a number of independent retailers. Distributing to the smaller independent retailers is costly for the automotive component manufacturers. Methodology: This study is based on a preliminary study of an explorative nature. Interviews were conducted with a senior staff member from a leading automotive component manufacturer in KwaZulu Natal and nine participants at a senior management level at five of their main customers (aftermarket retailers. Findings: The findings from the empirical study suggest that the aftermarket component industry is mature with the role players well established. The distribution chain to the independent retailer is expensive in terms of transaction and distribution costs for the automotive component manufacturer. A proposed centralised distribution model for supply to independent retailers has been developed which should reduce distribution costs for the automotive component manufacturer in terms of (1 the lowest possible freight rate; (2 timely and controlled delivery; and (3 reduced congestion at the customer's receiving dock. Originality: This research is original in that it explores the possibility of implementing a centralised distribution model for independent retailers in the automotive component industry. Furthermore, there is a dearth of published research on the South African automotive component industry particularly addressing distribution issues. Conclusion: The distribution model as suggested is a practical one and should deliver added value to automotive
International Nuclear Information System (INIS)
Morita, K.; Fukuda, K.; Tobita, Y.; Kondo, Sa.; Suzuki, T.; Maschek, W.
2003-01-01
A new multi-component vaporization/condensation (V/C) model was developed to provide a generalized model for safety analysis codes of liquid metal cooled reactors (LMRs). These codes simulate thermal-hydraulic phenomena of multi-phase, multi-component flows, which is essential to investigate core disruptive accidents of LMRs such as fast breeder reactors and accelerator driven systems. The developed model characterizes the V/C processes associated with phase transition by employing heat transfer and mass-diffusion limited models for analyses of relatively short-time-scale multi-phase, multi-component hydraulic problems, among which vaporization and condensation, or simultaneous heat and mass transfer, play an important role. The heat transfer limited model describes the non-equilibrium phase transition processes occurring at interfaces, while the mass-diffusion limited model is employed to represent effects of non-condensable gases and multi-component mixture on V/C processes. Verification of the model and method employed in the multi-component V/C model of a multi-phase flow code was performed successfully by analyzing a series of multi-bubble condensation experiments. The applicability of the model to the accident analysis of LMRs is also discussed by comparison between steam and metallic vapor systems. (orig.)
Revealing the equivalence of two clonal survival models by principal component analysis
International Nuclear Information System (INIS)
Lachet, Bernard; Dufour, Jacques
1976-01-01
The principal component analysis of 21 chlorella cell survival curves, adjusted by one-hit and two-hit target models, lead to quite similar projections on the principal plan: the homologous parameters of these models are linearly correlated; the reason for the statistical equivalence of these two models, in the present state of experimental inaccuracy, is revealed [fr
A model-based software development methodology for high-end automotive components
Ravanan, Mahmoud
2014-01-01
This report provides a model-based software development methodology for high-end automotive components. The V-model is used as a process model throughout the development of the software platform. It offers a framework that simplifies the relation between requirements, design, implementation,
Nørgaard, Sisse A; Sand, Fredrik W; Sørensen, Dorte B; Abelson, Klas Sp; Søndergaard, Henrik
2018-01-01
The streptozotocin (STZ)-induced diabetic mouse is a widely used model of diabetes and diabetic nephropathy (DN). However, it is a well-known issue that this model is challenged by high weight loss, which despite supportive measures often results in high euthanization rates. To overcome these issues, we hypothesized that supplementing STZ-induced diabetic mice with water-softened chow in addition to normal chow would reduce weight loss, lower the need for supportive treatment, and reduce the number of mice reaching the humane endpoint of 20% weight loss. In a 15 week STZ-induced DN study we demonstrated that diabetic male mice receiving softened chow had reduced acute weight loss following STZ treatment ( p = 0.045) and additionally fewer mice were euthanized due to weight loss. By supplementing the diabetic mice with softened chow, no mice reached 20% weight loss whereas 37.5% of the mice without this supplement reached this humane endpoint ( p = 0.0027). Excretion of corticosterone metabolites in faeces was reduced in diabetic mice on softened chow ( p = 0.0007), suggesting lower levels of general stress. Finally, it was demonstrated that the water-softened chow supplement did not significantly affect the induction of key disease parameters, i.e. %HbA1C and albuminuria nor result in abnormal teeth wear. In conclusion, supplementation of softened food is refining the STZ-induced diabetic mouse model significantly by reducing stress, weight loss and the number of animals sacrificed due to humane endpoints, while maintaining the key phenotypes of diabetes and nephropathy.
Prediction model of critical weight loss in cancer patients during particle therapy.
Zhang, Zhihong; Zhu, Yu; Zhang, Lijuan; Wang, Ziying; Wan, Hongwei
2018-01-01
The objective of this study is to investigate the predictors of critical weight loss in cancer patients receiving particle therapy, and build a prediction model based on its predictive factors. Patients receiving particle therapy were enroled between June 2015 and June 2016. Body weight was measured at the start and end of particle therapy. Association between critical weight loss (defined as >5%) during particle therapy and patients' demographic, clinical characteristic, pre-therapeutic nutrition risk screening (NRS 2002) and BMI were evaluated by logistic regression and decision tree analysis. Finally, 375 cancer patients receiving particle therapy were included. Mean weight loss was 0.55 kg, and 11.5% of patients experienced critical weight loss during particle therapy. The main predictors of critical weight loss during particle therapy were head and neck tumour location, total radiation dose ≥70 Gy on the primary tumour, and without post-surgery, as indicated by both logistic regression and decision tree analysis. Prediction model that includes tumour locations, total radiation dose and post-surgery had a good predictive ability, with the area under receiver operating characteristic curve 0.79 (95% CI: 0.71-0.88) and 0.78 (95% CI: 0.69-0.86) for decision tree and logistic regression model, respectively. Cancer patients with head and neck tumour location, total radiation dose ≥70 Gy and without post-surgery were at higher risk of critical weight loss during particle therapy, and early intensive nutrition counselling or intervention should be target at this population. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Xu, Yiming; Smith, Scot E; Grunwald, Sabine; Abd-Elrahman, Amr; Wani, Suhas P; Nair, Vimala D
2017-09-11
Digital soil mapping (DSM) is gaining momentum as a technique to help smallholder farmers secure soil security and food security in developing regions. However, communications of the digital soil mapping information between diverse audiences become problematic due to the inconsistent scale of DSM information. Spatial downscaling can make use of accessible soil information at relatively coarse spatial resolution to provide valuable soil information at relatively fine spatial resolution. The objective of this research was to disaggregate the coarse spatial resolution soil exchangeable potassium (K ex ) and soil total nitrogen (TN) base map into fine spatial resolution soil downscaled map using weighted generalized additive models (GAMs) in two smallholder villages in South India. By incorporating fine spatial resolution spectral indices in the downscaling process, the soil downscaled maps not only conserve the spatial information of coarse spatial resolution soil maps but also depict the spatial details of soil properties at fine spatial resolution. The results of this study demonstrated difference between the fine spatial resolution downscaled maps and fine spatial resolution base maps is smaller than the difference between coarse spatial resolution base maps and fine spatial resolution base maps. The appropriate and economical strategy to promote the DSM technique in smallholder farms is to develop the relatively coarse spatial resolution soil prediction maps or utilize available coarse spatial resolution soil maps at the regional scale and to disaggregate these maps to the fine spatial resolution downscaled soil maps at farm scale.
Stability equation and two-component Eigenmode for domain walls in scalar potential model
International Nuclear Information System (INIS)
Dias, G.S.; Graca, E.L.; Rodrigues, R. de Lima
2002-08-01
Supersymmetric quantum mechanics involving a two-component representation and two-component eigenfunctions is applied to obtain the stability equation associated to a potential model formulated in terms of two coupled real scalar fields. We investigate the question of stability by introducing an operator technique for the Bogomol'nyi-Prasad-Sommerfield (BPS) and non-BPS states on two domain walls in a scalar potential model with minimal N 1-supersymmetry. (author)
Seismic assessment and performance of nonstructural components affected by structural modeling
Energy Technology Data Exchange (ETDEWEB)
Hur, Jieun; Althoff, Eric; Sezen, Halil; Denning, Richard; Aldemir, Tunc [Ohio State University, Columbus (United States)
2017-03-15
Seismic probabilistic risk assessment (SPRA) requires a large number of simulations to evaluate the seismic vulnerability of structural and nonstructural components in nuclear power plants. The effect of structural modeling and analysis assumptions on dynamic analysis of 3D and simplified 2D stick models of auxiliary buildings and the attached nonstructural components is investigated. Dynamic characteristics and seismic performance of building models are also evaluated, as well as the computational accuracy of the models. The presented results provide a better understanding of the dynamic behavior and seismic performance of auxiliary buildings. The results also help to quantify the impact of uncertainties associated with modeling and analysis of simplified numerical models of structural and nonstructural components subjected to seismic shaking on the predicted seismic failure probabilities of these systems.
Directory of Open Access Journals (Sweden)
Georgios C Manikis
Full Text Available The purpose of this study was to compare the performance of four diffusion models, including mono and bi-exponential both Gaussian and non-Gaussian models, in diffusion weighted imaging of rectal cancer.Nineteen patients with rectal adenocarcinoma underwent MRI examination of the rectum before chemoradiation therapy including a 7 b-value diffusion sequence (0, 25, 50, 100, 500, 1000 and 2000 s/mm2 at a 1.5T scanner. Four different diffusion models including mono- and bi-exponential Gaussian (MG and BG and non-Gaussian (MNG and BNG were applied on whole tumor volumes of interest. Two different statistical criteria were recruited to assess their fitting performance, including the adjusted-R2 and Root Mean Square Error (RMSE. To decide which model better characterizes rectal cancer, model selection was relied on Akaike Information Criteria (AIC and F-ratio.All candidate models achieved a good fitting performance with the two most complex models, the BG and the BNG, exhibiting the best fitting performance. However, both criteria for model selection indicated that the MG model performed better than any other model. In particular, using AIC Weights and F-ratio, the pixel-based analysis demonstrated that tumor areas better described by the simplest MG model in an average area of 53% and 33%, respectively. Non-Gaussian behavior was illustrated in an average area of 37% according to the F-ratio, and 7% using AIC Weights. However, the distributions of the pixels best fitted by each of the four models suggest that MG failed to perform better than any other model in all patients, and the overall tumor area.No single diffusion model evaluated herein could accurately describe rectal tumours. These findings probably can be explained on the basis of increased tumour heterogeneity, where areas with high vascularity could be fitted better with bi-exponential models, and areas with necrosis would mostly follow mono-exponential behavior.
Thøgersen-Ntoumani, Cecilie; Ntoumanis, Nikos; Nikitaras, Nikitas
2010-06-01
This study used self-determination theory (Deci, E.L., & Ryan, R.M. (2000). The 'what' and 'why' of goal pursuits: Human needs and the self-determination of behavior. Psychological Inquiry, 11, 227-268.) to examine predictors of body image concerns and unhealthy weight control behaviours in a sample of 350 Greek adolescent girls. A process model was tested which proposed that perceptions of parental autonomy support and two life goals (health and image) would predict adolescents' degree of satisfaction of their basic psychological needs. In turn, psychological need satisfaction was hypothesised to negatively predict body image concerns (i.e. drive for thinness and body dissatisfaction) and, indirectly, unhealthy weight control behaviours. The predictions of the model were largely supported indicating that parental autonomy support and adaptive life goals can indirectly impact upon the extent to which female adolescents engage in unhealthy weight control behaviours via facilitating the latter's psychological need satisfaction.
Regional income inequality model based on theil index decomposition and weighted variance coeficient
Sitepu, H. R.; Darnius, O.; Tambunan, W. N.
2018-03-01
Regional income inequality is an important issue in the study on economic development of a certain region. Rapid economic development may not in accordance with people’s per capita income. The method of measuring the regional income inequality has been suggested by many experts. This research used Theil index and weighted variance coefficient in order to measure the regional income inequality. Regional income decomposition which becomes the productivity of work force and their participation in regional income inequality, based on Theil index, can be presented in linear relation. When the economic assumption in j sector, sectoral income value, and the rate of work force are used, the work force productivity imbalance can be decomposed to become the component in sectors and in intra-sectors. Next, weighted variation coefficient is defined in the revenue and productivity of the work force. From the quadrate of the weighted variation coefficient result, it was found that decomposition of regional revenue imbalance could be analyzed by finding out how far each component contribute to regional imbalance which, in this research, was analyzed in nine sectors of economic business.
Directory of Open Access Journals (Sweden)
Zhao Xihai
2010-07-01
Full Text Available Abstract Background Atherosclerotic plaque morphology and components are predictors of subsequent cardiovascular events. However, associations of plaque eccentricity with plaque morphology and plaque composition are unclear. This study investigated associations of plaque eccentricity with plaque components and morphology in the proximal superficial femoral artery using cardiovascular magnetic resonance (CMR. Methods Twenty-eight subjects with an ankle-brachial index less than 1.00 were examined with 1.5T high-spatial-resolution, multi-contrast weighted CMR. One hundred and eighty diseased locations of the proximal superficial femoral artery (about 40 mm were analyzed. The eccentric lesion was defined as [(Maximum wall thickness- Minimum wall thickness/Maximum wall thickness] ≥ 0.5. The arterial morphology and plaque components were measured using semi-automatic image analysis software. Results One hundred and fifteen locations were identified as eccentric lesions and sixty-five as concentric lesions. The eccentric lesions had larger wall but similar lumen areas, larger mean and maximum wall thicknesses, and more calcification and lipid rich necrotic core, compared to concentric lesions. For lesions with the same lumen area, the degree of eccentricity was associated with an increased wall area. Eccentricity (dichotomous as eccentric or concentric was independently correlated with the prevalence of calcification (odds ratio 3.78, 95% CI 1.47-9.70 after adjustment for atherosclerotic risk factors and wall area. Conclusions Plaque eccentricity is associated with preserved lumen size and advanced plaque features such as larger plaque burden, more lipid content, and increased calcification in the superficial femoral artery.
The n-component cubic model and flows: subgraph break-collapse method
International Nuclear Information System (INIS)
Essam, J.W.; Magalhaes, A.C.N. de.
1988-01-01
We generalise to the n-component cubic model the subgraph break-collapse method which we previously developed for the Potts model. The relations used are based on expressions which we recently derived for the Z(λ) model in terms of mod-λ flows. Our recursive algorithm is similar, for n = 2, to the break-collapse method for the Z(4) model proposed by Mariz and coworkers. It allows the exact calculation for the partition function and correlation functions for n-component cubic clusters with n as a variable, without the need to examine all of the spin configurations. (author) [pt
Intentional weight loss reduces mortality rate in a rodent model of dietary obesity.
Vasselli, Joseph R; Weindruch, Richard; Heymsfield, Steven B; Pi-Sunyer, F Xavier; Boozer, Carol N; Yi, Nengjun; Wang, Chenxi; Pietrobelli, Angelo; Allison, David B
2005-04-01
We used a rodent model of dietary obesity to evaluate effects of caloric restriction-induced weight loss on mortality rate. Research Measures and Procedures: In a randomized parallel-groups design, 312 outbred Sprague-Dawley rats (one-half males) were assigned at age 10 weeks to one of three diets: low fat (LF; 18.7% calories as fat) with caloric intake adjusted to maintain body weight 10% below that for ad libitum (AL)-fed rat food, high fat (HF; 45% calories as fat) fed at the same level, or HF fed AL. At age 46 weeks, the lightest one-third of the AL group was discarded to ensure a more obese group; the remaining animals were randomly assigned to one of three diets: HF-AL, HF with energy restricted to produce body weights of animals restricted on the HF diet throughout life, or LF with energy restricted to produce the body weights of animals restricted on the LF diet throughout life. Life span, body weight, and leptin levels were measured. Animals restricted throughout life lived the longest (p < 0.001). Life span was not different among animals that had been obese and then lost weight and animals that had been nonobese throughout life (p = 0.18). Animals that were obese and lost weight lived substantially longer than animals that remained obese throughout life (p = 0.002). Diet composition had no effect on life span (p = 0.52). Weight loss after the onset of obesity during adulthood leads to a substantial increase in longevity in rats.
Sun, Chuanzhi; Wang, Lei; Tan, Jiubin; Zhao, Bo; Tang, Yangchao
2016-02-01
The paper designs a roundness measurement model with multi-systematic error, which takes eccentricity, probe offset, radius of tip head of probe, and tilt error into account for roundness measurement of cylindrical components. The effects of the systematic errors and radius of components are analysed in the roundness measurement. The proposed method is built on the instrument with a high precision rotating spindle. The effectiveness of the proposed method is verified by experiment with the standard cylindrical component, which is measured on a roundness measuring machine. Compared to the traditional limacon measurement model, the accuracy of roundness measurement can be increased by about 2.2 μm using the proposed roundness measurement model for the object with a large radius of around 37 mm. The proposed method can improve the accuracy of roundness measurement and can be used for error separation, calibration, and comparison, especially for cylindrical components with a large radius.
Weight Loss Self-Efficacy and Modelled Behaviour: Gaining Competence through Example
Schulz, Benjamin R.; McDonald, Marvin J.
2011-01-01
The Weight Efficacy Life-Style Questionnaire (WEL) and the International Physical Activity Questionnaire (IPAQ) assessed self-efficacy and physical activity for 124 volunteers aged 17-61. It was administered before and after participants attended a video modelling workshop. Half of the participants in the treatment and control groups were given…
Das, Bhibha M.; Evans, Ellen M.
2014-01-01
Objective: To examine weight management barriers, using the Health Belief Model, in first-year college students. Participants: First-year college students (n = 45), with data collected in April, May, and November 2013. Methods: Nominal group technique sessions (n = 8) were conducted. Results: First-year students recognize benefits to weight…
Ma, Xiao; Zheng, Wei-Fan; Jiang, Bao-Shan; Zhang, Ji-Ye
2016-10-01
With the development of traffic systems, some issues such as traffic jams become more and more serious. Efficient traffic flow theory is needed to guide the overall controlling, organizing and management of traffic systems. On the basis of the cellular automata model and the traffic flow model with look-ahead potential, a new cellular automata traffic flow model with negative exponential weighted look-ahead potential is presented in this paper. By introducing the negative exponential weighting coefficient into the look-ahead potential and endowing the potential of vehicles closer to the driver with a greater coefficient, the modeling process is more suitable for the driver’s random decision-making process which is based on the traffic environment that the driver is facing. The fundamental diagrams for different weighting parameters are obtained by using numerical simulations which show that the negative exponential weighting coefficient has an obvious effect on high density traffic flux. The complex high density non-linear traffic behavior is also reproduced by numerical simulations. Project supported by the National Natural Science Foundation of China (Grant Nos. 11572264, 11172247, 11402214, and 61373009).
Model ZD-I paper base weight measuring and controlling system
International Nuclear Information System (INIS)
Li Nianzu; Song Debin; Wu Guoliang; Hou Yaoxin; Li Dazhen
1988-01-01
Model ZD-I Base Weight Measuring and Controlling System has been developed for the automation process in paper-making industry. A single-board microprocessor is installed in the system. The mass thickness can be controlled within 1 g/m 2 if the changing range of concentration and water content is less than 10%
A New Integrated Weighted Model in SNOW-V10: Verification of Categorical Variables
Huang, Laura X.; Isaac, George A.; Sheng, Grant
2014-01-01
This paper presents the verification results for nowcasts of seven categorical variables from an integrated weighted model (INTW) and the underlying numerical weather prediction (NWP) models. Nowcasting, or short range forecasting (0-6 h), over complex terrain with sufficient accuracy is highly desirable but a very challenging task. A weighting, evaluation, bias correction and integration system (WEBIS) for generating nowcasts by integrating NWP forecasts and high frequency observations was used during the Vancouver 2010 Olympic and Paralympic Winter Games as part of the Science of Nowcasting Olympic Weather for Vancouver 2010 (SNOW-V10) project. Forecast data from Canadian high-resolution deterministic NWP system with three nested grids (at 15-, 2.5- and 1-km horizontal grid-spacing) were selected as background gridded data for generating the integrated nowcasts. Seven forecast variables of temperature, relative humidity, wind speed, wind gust, visibility, ceiling and precipitation rate are treated as categorical variables for verifying the integrated weighted forecasts. By analyzing the verification of forecasts from INTW and the NWP models among 15 sites, the integrated weighted model was found to produce more accurate forecasts for the 7 selected forecast variables, regardless of location. This is based on the multi-categorical Heidke skill scores for the test period 12 February to 21 March 2010.
Penfield, Randall D.; Bergeron, Jennifer M.
2005-01-01
This article applies a weighted maximum likelihood (WML) latent trait estimator to the generalized partial credit model (GPCM). The relevant equations required to obtain the WML estimator using the Newton-Raphson algorithm are presented, and a simulation study is described that compared the properties of the WML estimator to those of the maximum…
Magis, David; Raiche, Gilles
2012-01-01
This paper focuses on two estimators of ability with logistic item response theory models: the Bayesian modal (BM) estimator and the weighted likelihood (WL) estimator. For the BM estimator, Jeffreys' prior distribution is considered, and the corresponding estimator is referred to as the Jeffreys modal (JM) estimator. It is established that under…
Entropy-optimal weight constraint elicitation with additive multi-attribute utility models
Valkenhoef , van Gert; Tervonen, Tommi
2016-01-01
We consider the elicitation of incomplete preference information for the additive utility model in terms of linear constraints on the weights. Eliciting incomplete preferences using holistic pair-wise judgments is convenient for the decision maker, but selecting the best pair-wise comparison is
College Students' Motivation toward Weight Training: An Application of Expectancy-Value Model
Gao, Zan; Xiang, Ping
2008-01-01
Guided by an expectancy-value model of achievement choice (Eccles et al., 1983; Wigfield & Eccles, 2000), the relationships among expectancy-related beliefs, subjective task values (importance, interest, and usefulness), and achievement outcomes (intention, engagement, and performance) were examined in a college-level beginning weight training…
Two component WIMP-FImP dark matter model with singlet fermion, scalar and pseudo scalar
Energy Technology Data Exchange (ETDEWEB)
Dutta Banik, Amit; Pandey, Madhurima; Majumdar, Debasish [Saha Institute of Nuclear Physics, HBNI, Astroparticle Physics and Cosmology Division, Kolkata (India); Biswas, Anirban [Harish Chandra Research Institute, Allahabad (India)
2017-10-15
We explore a two component dark matter model with a fermion and a scalar. In this scenario the Standard Model (SM) is extended by a fermion, a scalar and an additional pseudo scalar. The fermionic component is assumed to have a global U(1){sub DM} and interacts with the pseudo scalar via Yukawa interaction while a Z{sub 2} symmetry is imposed on the other component - the scalar. These ensure the stability of both dark matter components. Although the Lagrangian of the present model is CP conserving, the CP symmetry breaks spontaneously when the pseudo scalar acquires a vacuum expectation value (VEV). The scalar component of the dark matter in the present model also develops a VEV on spontaneous breaking of the Z{sub 2} symmetry. Thus the various interactions of the dark sector and the SM sector occur through the mixing of the SM like Higgs boson, the pseudo scalar Higgs like boson and the singlet scalar boson. We show that the observed gamma ray excess from the Galactic Centre as well as the 3.55 keV X-ray line from Perseus, Andromeda etc. can be simultaneously explained in the present two component dark matter model and the dark matter self interaction is found to be an order of magnitude smaller than the upper limit estimated from the observational results. (orig.)
Penalising Model Component Complexity: A Principled, Practical Approach to Constructing Priors
Simpson, Daniel
2017-04-06
In this paper, we introduce a new concept for constructing prior distributions. We exploit the natural nested structure inherent to many model components, which defines the model component to be a flexible extension of a base model. Proper priors are defined to penalise the complexity induced by deviating from the simpler base model and are formulated after the input of a user-defined scaling parameter for that model component, both in the univariate and the multivariate case. These priors are invariant to repa-rameterisations, have a natural connection to Jeffreys\\' priors, are designed to support Occam\\'s razor and seem to have excellent robustness properties, all which are highly desirable and allow us to use this approach to define default prior distributions. Through examples and theoretical results, we demonstrate the appropriateness of this approach and how it can be applied in various situations.
Penalising Model Component Complexity: A Principled, Practical Approach to Constructing Priors
Simpson, Daniel; Rue, Haavard; Riebler, Andrea; Martins, Thiago G.; Sø rbye, Sigrunn H.
2017-01-01
In this paper, we introduce a new concept for constructing prior distributions. We exploit the natural nested structure inherent to many model components, which defines the model component to be a flexible extension of a base model. Proper priors are defined to penalise the complexity induced by deviating from the simpler base model and are formulated after the input of a user-defined scaling parameter for that model component, both in the univariate and the multivariate case. These priors are invariant to repa-rameterisations, have a natural connection to Jeffreys' priors, are designed to support Occam's razor and seem to have excellent robustness properties, all which are highly desirable and allow us to use this approach to define default prior distributions. Through examples and theoretical results, we demonstrate the appropriateness of this approach and how it can be applied in various situations.
Focused information criterion and model averaging based on weighted composite quantile regression
Xu, Ganggang
2013-08-13
We study the focused information criterion and frequentist model averaging and their application to post-model-selection inference for weighted composite quantile regression (WCQR) in the context of the additive partial linear models. With the non-parametric functions approximated by polynomial splines, we show that, under certain conditions, the asymptotic distribution of the frequentist model averaging WCQR-estimator of a focused parameter is a non-linear mixture of normal distributions. This asymptotic distribution is used to construct confidence intervals that achieve the nominal coverage probability. With properly chosen weights, the focused information criterion based WCQR estimators are not only robust to outliers and non-normal residuals but also can achieve efficiency close to the maximum likelihood estimator, without assuming the true error distribution. Simulation studies and a real data analysis are used to illustrate the effectiveness of the proposed procedure. © 2013 Board of the Foundation of the Scandinavian Journal of Statistics..
Frequency-Weighted Model Predictive Control of Trailing Edge Flaps on a Wind Turbine Blade
DEFF Research Database (Denmark)
Castaignet, Damien; Couchman, Ian; Poulsen, Niels Kjølstad
2013-01-01
flapwise blade root moment and trailing edge flap deflection. Frequency-weighted MPC is chosen for its ability to handle constraints on the trailing edge flaps deflection, and to target at loads with given frequencies only. The controller is first tested in servo-aeroelastic simulations, before being......This paper presents the load reduction achieved with trailing edge flaps during a full-scale test on a Vestas V27 wind turbine. The trailing edge flap controller is a frequency-weighted linear model predictive control (MPC) where the quadratic cost consists of costs on the zero-phase filtered...
Boos, Moritz; Seer, Caroline; Lange, Florian; Kopp, Bruno
2016-01-01
Cognitive determinants of probabilistic inference were examined using hierarchical Bayesian modeling techniques. A classic urn-ball paradigm served as experimental strategy, involving a factorial two (prior probabilities) by two (likelihoods) design. Five computational models of cognitive processes were compared with the observed behavior. Parameter-free Bayesian posterior probabilities and parameter-free base rate neglect provided inadequate models of probabilistic inference. The introduction of distorted subjective probabilities yielded more robust and generalizable results. A general class of (inverted) S-shaped probability weighting functions had been proposed; however, the possibility of large differences in probability distortions not only across experimental conditions, but also across individuals, seems critical for the model's success. It also seems advantageous to consider individual differences in parameters of probability weighting as being sampled from weakly informative prior distributions of individual parameter values. Thus, the results from hierarchical Bayesian modeling converge with previous results in revealing that probability weighting parameters show considerable task dependency and individual differences. Methodologically, this work exemplifies the usefulness of hierarchical Bayesian modeling techniques for cognitive psychology. Theoretically, human probabilistic inference might be best described as the application of individualized strategic policies for Bayesian belief revision.
Refined weighted sum of gray gases model for air-fuel combustion and its impacts
DEFF Research Database (Denmark)
Yin, Chungen
2013-01-01
Radiation is the principal mode of heat transfer in utility boiler furnaces. Models for radiative properties play a vital role in reliable simulations of utility boilers and simulation-based design and optimization. The weighted sum of gray gases model (WSGGM) is one of the most widely used models...... in computational fluid dynamics (CFD) simulation of air-fuel combustion processes. It represents a reasonable compromise between an oversimplified gray gas model and a comprehensive approach addressing high-resolution dependency of radiative properties and intensity upon wavelength. The WSGGM coefficients...
A mesoscopic reaction rate model for shock initiation of multi-component PBX explosives.
Liu, Y R; Duan, Z P; Zhang, Z Y; Ou, Z C; Huang, F L
2016-11-05
The primary goal of this research is to develop a three-term mesoscopic reaction rate model that consists of a hot-spot ignition, a low-pressure slow burning and a high-pressure fast reaction terms for shock initiation of multi-component Plastic Bonded Explosives (PBX). Thereinto, based on the DZK hot-spot model for a single-component PBX explosive, the hot-spot ignition term as well as its reaction rate is obtained through a "mixing rule" of the explosive components; new expressions for both the low-pressure slow burning term and the high-pressure fast reaction term are also obtained by establishing the relationships between the reaction rate of the multi-component PBX explosive and that of its explosive components, based on the low-pressure slow burning term and the high-pressure fast reaction term of a mesoscopic reaction rate model. Furthermore, for verification, the new reaction rate model is incorporated into the DYNA2D code to simulate numerically the shock initiation process of the PBXC03 and the PBXC10 multi-component PBX explosives, and the numerical results of the pressure histories at different Lagrange locations in explosive are found to be in good agreements with previous experimental data. Copyright © 2016 Elsevier B.V. All rights reserved.
Directory of Open Access Journals (Sweden)
Fabio Panariello
2011-01-01
Full Text Available Excess body weight is one of the most common physical health problems among patients with schizophrenia that increases the risk for many medical problems, including type 2 diabetes mellitus, coronary heart disease, osteoarthritis, and hypertension, and accounts in part for 20% shorter life expectancy than in general population. Among patients with severe mental illness, obesity can be attributed to an unhealthy lifestyle, personal genetic profile, as well as the effects of psychotropic medications, above all antipsychotic drugs. Novel “atypical” antipsychotic drugs represent a substantial improvement on older “typical” drugs. However, clinical experience has shown that some, but not all, of these drugs can induce substantial weight gain. Animal models of antipsychotic-related weight gain and animal transgenic models of knockout or overexpressed genes of antipsychotic receptors have been largely evaluated by scientific community for changes in obesity-related gene expression or phenotypes. Moreover, pharmacogenomic approaches have allowed to detect more than 300 possible candidate genes for antipsychotics-induced body weight gain. In this paper, we summarize current thinking on: (1 the role of polymorphisms in several candidate genes, (2 the possible roles of various neurotransmitters and neuropeptides in this adverse drug reaction, and (3 the state of development of animal models in this matter. We also outline major areas for future research.
Energy Technology Data Exchange (ETDEWEB)
Oppermann, Helge; Metschkoll, Matthias; Froeschl, Juergen [BMW AG, Muenchen (Germany); Becker, Ingo [Industrieanlagen Betriebsgesellschaft (IABG) mbH, Ottobrunn (Germany). Abt. Festigkeit, Berechnung, Methodenentwicklung
2013-07-01
The increasing number of fiber composite components in car body structures requires the application of new joining techniques between steel and composite materials. Qualified methods for durability assessment are necessary due to the local high load for these lightweight joining techniques. The present contribution presents the actual results of a running method development project for a durability assessment of lightweight adhesive Bondings. After the description of the state of the art the different influences as load type, environmental temperature, etc. on the cyclic and static strength are shown by specimen tests and the main influence quantities are identified. In a second step the advantages and disadvantages of different concepts of durability assessments of adhesive joints are identified by test results. Finally, an outlook about future tests with component specimens for model verification will be given and the obtained results are concluded. (orig.)
Robust geographically weighted regression of modeling the Air Polluter Standard Index (APSI)
Warsito, Budi; Yasin, Hasbi; Ispriyanti, Dwi; Hoyyi, Abdul
2018-05-01
The Geographically Weighted Regression (GWR) model has been widely applied to many practical fields for exploring spatial heterogenity of a regression model. However, this method is inherently not robust to outliers. Outliers commonly exist in data sets and may lead to a distorted estimate of the underlying regression model. One of solution to handle the outliers in the regression model is to use the robust models. So this model was called Robust Geographically Weighted Regression (RGWR). This research aims to aid the government in the policy making process related to air pollution mitigation by developing a standard index model for air polluter (Air Polluter Standard Index - APSI) based on the RGWR approach. In this research, we also consider seven variables that are directly related to the air pollution level, which are the traffic velocity, the population density, the business center aspect, the air humidity, the wind velocity, the air temperature, and the area size of the urban forest. The best model is determined by the smallest AIC value. There are significance differences between Regression and RGWR in this case, but Basic GWR using the Gaussian kernel is the best model to modeling APSI because it has smallest AIC.
Directory of Open Access Journals (Sweden)
Da Liu
2013-01-01
Full Text Available A combined forecast with weights adaptively selected and errors calibrated by Hidden Markov model (HMM is proposed to model the day-ahead electricity price. Firstly several single models were built to forecast the electricity price separately. Then the validation errors from every individual model were transformed into two discrete sequences: an emission sequence and a state sequence to build the HMM, obtaining a transmission matrix and an emission matrix, representing the forecasting ability state of the individual models. The combining weights of the individual models were decided by the state transmission matrixes in HMM and the best predict sample ratio of each individual among all the models in the validation set. The individual forecasts were averaged to get the combining forecast with the weights obtained above. The residuals of combining forecast were calibrated by the possible error calculated by the emission matrix of HMM. A case study of day-ahead electricity market of Pennsylvania-New Jersey-Maryland (PJM, USA, suggests that the proposed method outperforms individual techniques of price forecasting, such as support vector machine (SVM, generalized regression neural networks (GRNN, day-ahead modeling, and self-organized map (SOM similar days modeling.
Ahmadi, Maryam; Damanabi, Shahla; Sadoughi, Farahnaz
2014-04-01
National Health Information System plays an important role in ensuring timely and reliable access to Health information, which is essential for strategic and operational decisions that improve health, quality and effectiveness of health care. In other words, using the National Health information system you can improve the quality of health data, information and knowledge used to support decision making at all levels and areas of the health sector. Since full identification of the components of this system - for better planning and management influential factors of performanceseems necessary, therefore, in this study different attitudes towards components of this system are explored comparatively. This is a descriptive and comparative kind of study. The society includes printed and electronic documents containing components of the national health information system in three parts: input, process and output. In this context, search for information using library resources and internet search were conducted, and data analysis was expressed using comparative tables and qualitative data. The findings showed that there are three different perspectives presenting the components of national health information system Lippeveld and Sauerborn and Bodart model in 2000, Health Metrics Network (HMN) model from World Health Organization in 2008, and Gattini's 2009 model. All three models outlined above in the input (resources and structure) require components of management and leadership, planning and design programs, supply of staff, software and hardware facilities and equipment. Plus, in the "process" section from three models, we pointed up the actions ensuring the quality of health information system, and in output section, except for Lippeveld Model, two other models consider information products and use and distribution of information as components of the national health information system. the results showed that all the three models have had a brief discussion about the
Stefanutti, Luca; Robusto, Egidio; Vianello, Michelangelo; Anselmi, Pasquale
2013-06-01
A formal model is proposed that decomposes the implicit association test (IAT) effect into three process components: stimuli discrimination, automatic association, and termination criterion. Both response accuracy and reaction time are considered. Four independent and parallel Poisson processes, one for each of the four label categories of the IAT, are assumed. The model parameters are the rate at which information accrues on the counter of each process and the amount of information that is needed before a response is given. The aim of this study is to present the model and an illustrative application in which the process components of a Coca-Pepsi IAT are decomposed.
OSCAR2000 : a multi-component 3-dimensional oil spill contingency and response model
International Nuclear Information System (INIS)
Reed, M.; Daling, P.S.; Brakstad, O.G.; Singsaas, I.; Faksness, L.-G.; Hetland, B.; Ekrol, N.
2000-01-01
Researchers at SINTEF in Norway have studied the weathering of surface oil. They developed a realistic model to analyze alternative spill response strategies. The model represented the formation and composition of the water-accommodated fraction (WAF) of oil for both treated and untreated oil spills. As many as 25 components, pseudo-components, or metabolites were allowed for the specification of oil. Calculations effected using OSCAR were verified in great detail on numerous occasions. The model made it possible to determine rather realistically the dissolution, transformation, and toxicology of dispersed oil clouds, as well as evaporation, emulsification, and natural dispersion. OSCAR comprised a data-based oil weathering model, a three-dimensional oil trajectory and chemical fates model, an oil spill combat model, exposure models for birds, marine mammals, fish and ichthyoplankton. 17 refs., 1 tab., 11 figs
DEFF Research Database (Denmark)
Stamatelos, Dimtrios; Kappatos, Vassilios
2017-01-01
Purpose – This paper presents the development of an advanced structural assessment approach for aerospace components (metallic and composites). This work focuses on developing an automatic image processing methodology based on Non Destructive Testing (NDT) data and numerical models, for predicting...... the residual strength of these components. Design/methodology/approach – An image processing algorithm, based on the threshold method, has been developed to process and quantify the geometric characteristics of damages. Then, a parametric Finite Element (FE) model of the damaged component is developed based...... on the inputs acquired from the image processing algorithm. The analysis of the metallic structures is employing the Extended FE Method (XFEM), while for the composite structures the Cohesive Zone Model (CZM) technique with Progressive Damage Modelling (PDM) is used. Findings – The numerical analyses...
Model of the fine-grain component of martian soil based on Viking lander data
International Nuclear Information System (INIS)
Nussinov, M.D.; Chernyak, Y.B.; Ettinger, J.L.
1978-01-01
A model of the fine-grain component of the Martian soil is proposed. The model is based on well-known physical phenomena, and enables an explanation of the evolution of the gases released in the GEX (gas exchange experiments) and GCMS (gas chromatography-mass spectrometer experiments) of the Viking landers. (author)
Van Mechelen, Iven; Kiers, Henk A.L.
1999-01-01
The three-mode component analysis model is discussed as a tool for a contextualized study of personality. When applied to person x situation x response data, the model includes sets of latent dimensions for persons, situations, and responses as well as a so-called core array, which may be considered
A mass-density model can account for the size-weight illusion
Bergmann Tiest, Wouter M.; Drewing, Knut
2018-01-01
When judging the heaviness of two objects with equal mass, people perceive the smaller and denser of the two as being heavier. Despite the large number of theories, covering bottom-up and top-down approaches, none of them can fully account for all aspects of this size-weight illusion and thus for human heaviness perception. Here we propose a new maximum-likelihood estimation model which describes the illusion as the weighted average of two heaviness estimates with correlated noise: One estimate derived from the object’s mass, and the other from the object’s density, with estimates’ weights based on their relative reliabilities. While information about mass can directly be perceived, information about density will in some cases first have to be derived from mass and volume. However, according to our model at the crucial perceptual level, heaviness judgments will be biased by the objects’ density, not by its size. In two magnitude estimation experiments, we tested model predictions for the visual and the haptic size-weight illusion. Participants lifted objects which varied in mass and density. We additionally varied the reliability of the density estimate by varying the quality of either visual (Experiment 1) or haptic (Experiment 2) volume information. As predicted, with increasing quality of volume information, heaviness judgments were increasingly biased towards the object’s density: Objects of the same density were perceived as more similar and big objects were perceived as increasingly lighter than small (denser) objects of the same mass. This perceived difference increased with an increasing difference in density. In an additional two-alternative forced choice heaviness experiment, we replicated that the illusion strength increased with the quality of volume information (Experiment 3). Overall, the results highly corroborate our model, which seems promising as a starting point for a unifying framework for the size-weight illusion and human heaviness
A mass-density model can account for the size-weight illusion.
Wolf, Christian; Bergmann Tiest, Wouter M; Drewing, Knut
2018-01-01
When judging the heaviness of two objects with equal mass, people perceive the smaller and denser of the two as being heavier. Despite the large number of theories, covering bottom-up and top-down approaches, none of them can fully account for all aspects of this size-weight illusion and thus for human heaviness perception. Here we propose a new maximum-likelihood estimation model which describes the illusion as the weighted average of two heaviness estimates with correlated noise: One estimate derived from the object's mass, and the other from the object's density, with estimates' weights based on their relative reliabilities. While information about mass can directly be perceived, information about density will in some cases first have to be derived from mass and volume. However, according to our model at the crucial perceptual level, heaviness judgments will be biased by the objects' density, not by its size. In two magnitude estimation experiments, we tested model predictions for the visual and the haptic size-weight illusion. Participants lifted objects which varied in mass and density. We additionally varied the reliability of the density estimate by varying the quality of either visual (Experiment 1) or haptic (Experiment 2) volume information. As predicted, with increasing quality of volume information, heaviness judgments were increasingly biased towards the object's density: Objects of the same density were perceived as more similar and big objects were perceived as increasingly lighter than small (denser) objects of the same mass. This perceived difference increased with an increasing difference in density. In an additional two-alternative forced choice heaviness experiment, we replicated that the illusion strength increased with the quality of volume information (Experiment 3). Overall, the results highly corroborate our model, which seems promising as a starting point for a unifying framework for the size-weight illusion and human heaviness perception.
A Co-modeling Method Based on Component Features for Mechatronic Devices in Aero-engines
Wang, Bin; Zhao, Haocen; Ye, Zhifeng
2017-08-01
Data-fused and user-friendly design of aero-engine accessories is required because of their structural complexity and stringent reliability. This paper gives an overview of a typical aero-engine control system and the development process of key mechatronic devices used. Several essential aspects of modeling and simulation in the process are investigated. Considering the limitations of a single theoretic model, feature-based co-modeling methodology is suggested to satisfy the design requirements and compensate for diversity of component sub-models for these devices. As an example, a stepper motor controlled Fuel Metering Unit (FMU) is modeled in view of the component physical features using two different software tools. An interface is suggested to integrate the single discipline models into the synthesized one. Performance simulation of this device using the co-model and parameter optimization for its key components are discussed. Comparison between delivery testing and the simulation shows that the co-model for the FMU has a high accuracy and the absolute superiority over a single model. Together with its compatible interface with the engine mathematical model, the feature-based co-modeling methodology is proven to be an effective technical measure in the development process of the device.
International Nuclear Information System (INIS)
Meisner, Aaron M.; Finkbeiner, Douglas P.
2015-01-01
We apply the Finkbeiner et al. two-component thermal dust emission model to the Planck High Frequency Instrument maps. This parameterization of the far-infrared dust spectrum as the sum of two modified blackbodies (MBBs) serves as an important alternative to the commonly adopted single-MBB dust emission model. Analyzing the joint Planck/DIRBE dust spectrum, we show that two-component models provide a better fit to the 100-3000 GHz emission than do single-MBB models, though by a lesser margin than found by Finkbeiner et al. based on FIRAS and DIRBE. We also derive full-sky 6.'1 resolution maps of dust optical depth and temperature by fitting the two-component model to Planck 217-857 GHz along with DIRBE/IRAS 100 μm data. Because our two-component model matches the dust spectrum near its peak, accounts for the spectrum's flattening at millimeter wavelengths, and specifies dust temperature at 6.'1 FWHM, our model provides reliable, high-resolution thermal dust emission foreground predictions from 100 to 3000 GHz. We find that, in diffuse sky regions, our two-component 100-217 GHz predictions are on average accurate to within 2.2%, while extrapolating the Planck Collaboration et al. single-MBB model systematically underpredicts emission by 18.8% at 100 GHz, 12.6% at 143 GHz, and 7.9% at 217 GHz. We calibrate our two-component optical depth to reddening, and compare with reddening estimates based on stellar spectra. We find the dominant systematic problems in our temperature/reddening maps to be zodiacal light on large angular scales and the cosmic infrared background anisotropy on small angular scales
Dynamics of an SAITS alcoholism model on unweighted and weighted networks
Huo, Hai-Feng; Cui, Fang-Fang; Xiang, Hong
2018-04-01
A novel SAITS alcoholism model on networks is introduced, in which alcoholics are divided into light problem alcoholics and heavy problem alcoholics. Susceptible individuals can enter into the compartment of heavy problem alcoholics directly by contacting with light problem alcoholics or heavy problem alcoholics and the heavy problem alcoholics who receive treatment can relapse into the compartment of heavy problem alcoholics are also considered. First, the dynamics of our model on unweighted networks, including the basic reproduction number, existence and stability of equilibria are studied. Second, the models with fixed weighted and adaptive weighted networks are introduced and investigated. At last, some simulations are presented to illustrate and extend our results. Our results show that it is very important to treat alcoholics to quit the drinking.
A mouse model of weight-drop closed head injury: emphasis on cognitive and neurological deficiency
Directory of Open Access Journals (Sweden)
Igor Khalin
2016-01-01
Full Text Available Traumatic brain injury (TBI is a leading cause of death and disability in individuals worldwide. Producing a clinically relevant TBI model in small-sized animals remains fairly challenging. For good screening of potential therapeutics, which are effective in the treatment of TBI, animal models of TBI should be established and standardized. In this study, we established mouse models of closed head injury using the Shohami weight-drop method with some modifications concerning cognitive deficiency assessment and provided a detailed description of the severe TBI animal model. We found that 250 g falling weight from 2 cm height produced severe closed head injury in C57BL/6 male mice. Cognitive disorders in mice with severe closed head injury could be detected using passive avoidance test on day 7 after injury. Findings from this study indicate that weight-drop injury animal models are suitable for further screening of brain neuroprotectants and potentially are similar to those seen in human TBI.
Directory of Open Access Journals (Sweden)
Moritz eBoos
2016-05-01
Full Text Available Cognitive determinants of probabilistic inference were examined using hierarchical Bayesian modelling techniques. A classic urn-ball paradigm served as experimental strategy, involving a factorial two (prior probabilities by two (likelihoods design. Five computational models of cognitive processes were compared with the observed behaviour. Parameter-free Bayesian posterior probabilities and parameter-free base rate neglect provided inadequate models of probabilistic inference. The introduction of distorted subjective probabilities yielded more robust and generalizable results. A general class of (inverted S-shaped probability weighting functions had been proposed; however, the possibility of large differences in probability distortions not only across experimental conditions, but also across individuals, seems critical for the model’s success. It also seems advantageous to consider individual differences in parameters of probability weighting as being sampled from weakly informative prior distributions of individual parameter values. Thus, the results from hierarchical Bayesian modelling converge with previous results in revealing that probability weighting parameters show considerable task dependency and individual differences. Methodologically, this work exemplifies the usefulness of hierarchical Bayesian modelling techniques for cognitive psychology. Theoretically, human probabilistic inference might be best described as the application of individualized strategic policies for Bayesian belief revision.
Kuss, DJ; Shorter, GW; Van Rooij, AJ; Griffiths, MD; Schoenmakers, T
2014-01-01
Internet usage has grown exponentially over the last decade. Research indicates that excessive Internet use can lead to symptoms associated with addiction. To date, assessment of potential Internet addiction has varied regarding populations studied and instruments used, making reliable prevalence estimations difficult. To overcome the present problems a preliminary study was conducted testing a parsimonious Internet addiction components model based on Griffiths’ addiction components (2005), i...
Wilson, R. B.; Banerjee, P. K.
1987-01-01
This Annual Status Report presents the results of work performed during the third year of the 3-D Inelastic Analysis Methods for Hot Sections Components program (NASA Contract NAS3-23697). The objective of the program is to produce a series of computer codes that permit more accurate and efficient three-dimensional analyses of selected hot section components, i.e., combustor liners, turbine blades, and turbine vanes. The computer codes embody a progression of mathematical models and are streamlined to take advantage of geometrical features, loading conditions, and forms of material response that distinguish each group of selected components.
Taneja, Vidya S.
1996-01-01
In this paper we develop the mathematical theory of proportional and scale change models to perform reliability analysis. The results obtained will be applied for the Reaction Control System (RCS) thruster valves on an orbiter. With the advent of extended EVA's associated with PROX OPS (ISSA & MIR), and docking, the loss of a thruster valve now takes on an expanded safety significance. Previous studies assume a homogeneous population of components with each component having the same failure rate. However, as various components experience different stresses and are exposed to different environments, their failure rates change with time. In this paper we model the reliability of a thruster valves by treating these valves as a censored repairable system. The model for each valve will take the form of a nonhomogeneous process with the intensity function that is either treated as a proportional hazard model, or a scale change random effects hazard model. Each component has an associated z, an independent realization of the random variable Z from a distribution G(z). This unobserved quantity z can be used to describe heterogeneity systematically. For various models methods for estimating the model parameters using censored data will be developed. Available field data (from previously flown flights) is from non-renewable systems. The estimated failure rate using such data will need to be modified for renewable systems such as thruster valve.
Learning versus correct models: influence of model type on the learning of a free-weight squat lift.
McCullagh, P; Meyer, K N
1997-03-01
It has been assumed that demonstrating the correct movement is the best way to impart task-relevant information. However, empirical verification with simple laboratory skills has shown that using a learning model (showing an individual in the process of acquiring the skill to be learned) may accelerate skill acquisition and increase retention more than using a correct model. The purpose of the present study was to compare the effectiveness of viewing correct versus learning models on the acquisition of a sport skill (free-weight squat lift). Forty female participants were assigned to four learning conditions: physical practice receiving feedback, learning model with model feedback, correct model with model feedback, and learning model without model feedback. Results indicated that viewing either a correct or learning model was equally effective in learning correct form in the squat lift.
Layout Optimization Model for the Production Planning of Precast Concrete Building Components
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Dong Wang
2018-05-01
Full Text Available Precast concrete comprises the basic components of modular buildings. The efficiency of precast concrete building component production directly impacts the construction time and cost. In the processes of precast component production, mold setting has a significant influence on the production efficiency and cost, as well as reducing the resource consumption. However, the development of mold setting plans is left to the experience of production staff, with outcomes dependent on the quality of human skill and experience available. This can result in sub-optimal production efficiencies and resource wastage. Accordingly, in order to improve the efficiency of precast component production, this paper proposes an optimization model able to maximize the average utilization rate of pallets used during the molding process. The constraints considered were the order demand, the size of the pallet, layout methods, and the positional relationship of components. A heuristic algorithm was used to identify optimization solutions provided by the model. Through empirical analysis, and as exemplified in the case study, this research is significant in offering a prefabrication production planning model which improves pallet utilization rates, shortens component production time, reduces production costs, and improves the resource utilization. The results clearly demonstrate that the proposed method can facilitate the precast production plan providing strong practical implications for production planners.
Exploring the Subtleties of Inverse Probability Weighting and Marginal Structural Models.
Breskin, Alexander; Cole, Stephen R; Westreich, Daniel
2018-05-01
Since being introduced to epidemiology in 2000, marginal structural models have become a commonly used method for causal inference in a wide range of epidemiologic settings. In this brief report, we aim to explore three subtleties of marginal structural models. First, we distinguish marginal structural models from the inverse probability weighting estimator, and we emphasize that marginal structural models are not only for longitudinal exposures. Second, we explore the meaning of the word "marginal" in "marginal structural model." Finally, we show that the specification of a marginal structural model can have important implications for the interpretation of its parameters. Each of these concepts have important implications for the use and understanding of marginal structural models, and thus providing detailed explanations of them may lead to better practices for the field of epidemiology.
Characterizing and Modeling the Cost of Rework in a Library of Reusable Software Components
Basili, Victor R.; Condon, Steven E.; ElEmam, Khaled; Hendrick, Robert B.; Melo, Walcelio
1997-01-01
In this paper we characterize and model the cost of rework in a Component Factory (CF) organization. A CF is responsible for developing and packaging reusable software components. Data was collected on corrective maintenance activities for the Generalized Support Software reuse asset library located at the Flight Dynamics Division of NASA's GSFC. We then constructed a predictive model of the cost of rework using the C4.5 system for generating a logical classification model. The predictor variables for the model are measures of internal software product attributes. The model demonstrates good prediction accuracy, and can be used by managers to allocate resources for corrective maintenance activities. Furthermore, we used the model to generate proscriptive coding guidelines to improve programming, practices so that the cost of rework can be reduced in the future. The general approach we have used is applicable to other environments.
SASSYS-1 balance-of-plant component models for an integrated plant response
International Nuclear Information System (INIS)
Ku, J.-Y.
1989-01-01
Models of power plant heat transfer components and rotating machinery have been added to the balance-of-plant model in the SASSYS-1 liquid metal reactor systems analysis code. This work is part of a continuing effort in plant network simulation based on the general mathematical models developed. The models described in this paper extend the scope of the balance-of-plant model to handle non-adiabatic conditions along flow paths. While the mass and momentum equations remain the same, the energy equation now contains a heat source term due to energy transfer across the flow boundary or to work done through a shaft. The heat source term is treated fully explicitly. In addition, the equation of state is rewritten in terms of the quality and separate parameters for each phase. The models are simple enough to run quickly, yet include sufficient detail of dominant plant component characteristics to provide accurate results. 5 refs., 16 figs., 2 tabs
A new enhanced index tracking model in portfolio optimization with sum weighted approach
Siew, Lam Weng; Jaaman, Saiful Hafizah; Hoe, Lam Weng
2017-04-01
Index tracking is a portfolio management which aims to construct the optimal portfolio to achieve similar return with the benchmark index return at minimum tracking error without purchasing all the stocks that make up the index. Enhanced index tracking is an improved portfolio management which aims to generate higher portfolio return than the benchmark index return besides minimizing the tracking error. The objective of this paper is to propose a new enhanced index tracking model with sum weighted approach to improve the existing index tracking model for tracking the benchmark Technology Index in Malaysia. The optimal portfolio composition and performance of both models are determined and compared in terms of portfolio mean return, tracking error and information ratio. The results of this study show that the optimal portfolio of the proposed model is able to generate higher mean return than the benchmark index at minimum tracking error. Besides that, the proposed model is able to outperform the existing model in tracking the benchmark index. The significance of this study is to propose a new enhanced index tracking model with sum weighted apporach which contributes 67% improvement on the portfolio mean return as compared to the existing model.
A Case Study on a Combination NDVI Forecasting Model Based on the Entropy Weight Method
Energy Technology Data Exchange (ETDEWEB)
Huang, Shengzhi; Ming, Bo; Huang, Qiang; Leng, Guoyong; Hou, Beibei
2017-05-05
It is critically meaningful to accurately predict NDVI (Normalized Difference Vegetation Index), which helps guide regional ecological remediation and environmental managements. In this study, a combination forecasting model (CFM) was proposed to improve the performance of NDVI predictions in the Yellow River Basin (YRB) based on three individual forecasting models, i.e., the Multiple Linear Regression (MLR), Artificial Neural Network (ANN), and Support Vector Machine (SVM) models. The entropy weight method was employed to determine the weight coefficient for each individual model depending on its predictive performance. Results showed that: (1) ANN exhibits the highest fitting capability among the four orecasting models in the calibration period, whilst its generalization ability becomes weak in the validation period; MLR has a poor performance in both calibration and validation periods; the predicted results of CFM in the calibration period have the highest stability; (2) CFM generally outperforms all individual models in the validation period, and can improve the reliability and stability of predicted results through combining the strengths while reducing the weaknesses of individual models; (3) the performances of all forecasting models are better in dense vegetation areas than in sparse vegetation areas.
Low-level profiling and MARTE-compatible modeling of software components for real-time systems
Triantafyllidis, K.; Bondarev, E.; With, de P.H.N.
2012-01-01
In this paper, we present a method for (a) profiling of individual components at high accuracy level, (b) modeling of the components with the accurate data obtained from profiling, and (c) model conversion to the MARTE profile. The resulting performance models of individual components are used at
International Nuclear Information System (INIS)
Byun, Choong Sup; Song, Dong Soo; Jun, Hwang Yong
2006-01-01
In a design point of view, component cooling water (CCW) system is not full-interactively designed with its heat loads. Heat loads are calculated from the CCW design flow and temperature condition which is determined with conservatism. Then the CCW heat exchanger is sized by using total maximized heat loads from above calculation. This approach does not give the optimized performance results and the exact trends of CCW system and the loads during transient. Therefore a combined model for performance analysis of containment and the component cooling water(CCW) system is developed by using GOTHIC software code. The model is verified by using the design parameters of component cooling water heat exchanger and the heat loads during the recirculation mode of loss of coolant accident scenario. This model may be used for calculating the realistic containment response and CCW performance, and increasing the ultimate heat sink temperature limits
A Component-Based Modeling and Validation Method for PLC Systems
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Rui Wang
2014-05-01
Full Text Available Programmable logic controllers (PLCs are complex embedded systems that are widely used in industry. This paper presents a component-based modeling and validation method for PLC systems using the behavior-interaction-priority (BIP framework. We designed a general system architecture and a component library for a type of device control system. The control software and hardware of the environment were all modeled as BIP components. System requirements were formalized as monitors. Simulation was carried out to validate the system model. A realistic example from industry of the gates control system was employed to illustrate our strategies. We found a couple of design errors during the simulation, which helped us to improve the dependability of the original systems. The results of experiment demonstrated the effectiveness of our approach.
Extending a Consensus-based Fuzzy Ordered Weighting Average (FOWA Model in New Water Quality Indices
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Mohammad Ali Baghapour
2017-07-01
Full Text Available In developing a specific WQI (Water Quality Index, many water quality parameters are involved with different levels of importance. The impact of experts’ different opinions and viewpoints, current risks affecting their opinions, and plurality of the involved parameters double the significance of the issue. Hence, the current study tries to apply a consensus-based FOWA (Fuzzy Ordered Weighting Average model as one of the most powerful and well-known Multi Criteria Decision Making (MCDM techniques to determine the importance of the used parameters in the development of such WQIs which is shown with an example. This operator has provided the capability of modeling the risks in decision-making through applying the optimistic degree of stakeholders and their power coupled with the use of fuzzy numbers. Totally, 22 water quality parameters for drinking purposes are considered in this study. To determine the weight of each parameter, the viewpoints of 4 decision-making groups of experts are taken into account. After determining the final weights, to validate the use of each parameter in a potential WQI, consensus degrees of both the decision makers and the parameters are calculated. All calculations are carried out by using the expertise software called Group Fuzzy Decision Making (GFDM. The highest and the lowest weight values, 0.999 and 0.073 respectively, are related to Hg and temperature. Regarding the type of consumption that is drinking, the parameters’ weights and ranks are consistent with their health impacts. Moreover, the decision makers’ highest and lowest consensus degrees were 0.9905 and 0.9669, respectively. Among the water quality parameters, temperature (with consensus degree of 0.9972 and Pb (with consensus degree of 0.9665, received the highest and lowest agreement from the decision making group. This study indicates that the weight of parameters in determining water quality largely depends on the experts’ opinions and
Extending a Consensus-based Fuzzy Ordered Weighting Average (FOWA Model in New Water Quality Indices
Directory of Open Access Journals (Sweden)
Mohammad Ali Baghapour
2017-07-01
Full Text Available In developing a specific WQI (Water Quality Index, many quality parameters are involved with different levels of importance. The impact of experts’ different opinions and viewpoints, current risks affecting their opinions, and plurality of the involved parameters double the significance of the issue. Hence, the current study tries to apply a consensus-based FOWA (Fuzzy Ordered Weighting Average model as one of the most powerful and well-known Multi-Criteria Decision- Making (MCDM techniques to determine the importance of the used parameters in the development of such WQIs which is shown with an example. This operator has provided the capability of modeling the risks in decision-making through applying the optimistic degree of stakeholders and their power coupled with the use of fuzzy numbers. Totally, 22 water quality parameters for drinking purposes were considered in this study. To determine the weight of each parameter, the viewpoints of 4 decision-making groups of experts were taken into account. After determining the final weights, to validate the use of each parameter in a potential WQI, consensus degrees of both the decision makers and the parameters are calculated. The highest and the lowest weight values, 0.999 and 0.073 respectively, were related to Hg and temperature. Regarding the type of consumption that was drinking, the parameters’ weights and ranks were consistent with their health impacts. Moreover, the decision makers’ highest and lowest consensus degrees were 0.9905 and 0.9669, respectively. Among the water quality parameters, temperature (with consensus degree of 0.9972 and Pb (with consensus degree of 0.9665, received the highest and lowest agreement with the decision-making group. This study indicated that the weight of parameters in determining water quality largely depends on the experts’ opinions and approaches. Moreover, using the FOWA model provides results accurate and closer- to-reality on the significance of
Jiskoot, Geranne; Benneheij, Sofie; Beerthuizen, Annemerle; Niet, J.E.; Klerk, Cora; Timman, Reinier; Busschbach, Jan; Laven, Joop
2017-01-01
textabstractBackground: Obesity in women with polycystic ovary syndrome (PCOS) negatively affects all clinical features, and a 5 to 10% weight loss has shown promising results on reproductive, metabolic and psychological level. Incorporating a healthy diet, increasing physical activity and changing dysfunctional thought patterns in women with PCOS are key points in losing weight. The biggest challenge in weight management programs is to achieve a reasonable and sustainable weight loss. The ai...
Slushy weightings for the optimal pilot model. [considering visual tracking task
Dillow, J. D.; Picha, D. G.; Anderson, R. O.
1975-01-01
A pilot model is described which accounts for the effect of motion cues in a well defined visual tracking task. The effect of visual and motion cues are accounted for in the model in two ways. First, the observation matrix in the pilot model is structured to account for the visual and motion inputs presented to the pilot. Secondly, the weightings in the quadratic cost function associated with the pilot model are modified to account for the pilot's perception of the variables he considers important in the task. Analytic results obtained using the pilot model are compared to experimental results and in general good agreement is demonstrated. The analytic model yields small improvements in tracking performance with the addition of motion cues for easily controlled task dynamics and large improvements in tracking performance with the addition of motion cues for difficult task dynamics.
Mean-Variance-CvaR Model of Multiportfolio Optimization via Linear Weighted Sum Method
Directory of Open Access Journals (Sweden)
Younes Elahi
2014-01-01
Full Text Available We propose a new approach to optimizing portfolios to mean-variance-CVaR (MVC model. Although of several researches have studied the optimal MVC model of portfolio, the linear weighted sum method (LWSM was not implemented in the area. The aim of this paper is to investigate the optimal portfolio model based on MVC via LWSM. With this method, the solution of the MVC model of portfolio as the multiobjective problem is presented. In data analysis section, this approach in investing on two assets is investigated. An MVC model of the multiportfolio was implemented in MATLAB and tested on the presented problem. It is shown that, by using three objective functions, it helps the investors to manage their portfolio better and thereby minimize the risk and maximize the return of the portfolio. The main goal of this study is to modify the current models and simplify it by using LWSM to obtain better results.
Validation of a RANS transition model using a high-order weighted compact nonlinear scheme
Tu, GuoHua; Deng, XiaoGang; Mao, MeiLiang
2013-04-01
A modified transition model is given based on the shear stress transport (SST) turbulence model and an intermittency transport equation. The energy gradient term in the original model is replaced by flow strain rate to saving computational costs. The model employs local variables only, and then it can be conveniently implemented in modern computational fluid dynamics codes. The fifth-order weighted compact nonlinear scheme and the fourth-order staggered scheme are applied to discrete the governing equations for the purpose of minimizing discretization errors, so as to mitigate the confusion between numerical errors and transition model errors. The high-order package is compared with a second-order TVD method on simulating the transitional flow of a flat plate. Numerical results indicate that the high-order package give better grid convergence property than that of the second-order method. Validation of the transition model is performed for transitional flows ranging from low speed to hypersonic speed.
Directory of Open Access Journals (Sweden)
Victor Yurievich Stroganov
2017-02-01
Full Text Available This article contains the systematization of the major production functions of repair activities network and the list of planning and control functions, which are described in the form of business processes (BP. Simulation model for analysis of the delivery effectiveness of components under conditions of probabilistic uncertainty was proposed. It has been shown that a significant portion of the total number of business processes is represented by the management and planning of the parts and components movement. Questions of construction of experimental design techniques on the simulation model in the conditions of non-stationarity were considered.
Towards a Complete Model for Software Component Deployment on Heterogeneous Platform
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Švogor Ivan
2014-12-01
Full Text Available This report briefly describes an ongoing research related to optimization of allocating software components to heterogeneous computing platform (which includes CPU, GPU and FPGA. Research goal is also presented, along with current hot topics of the research area, related research teams, and finally results and contribution of my research. It involves mathematical modelling which results in goal function, optimization method which finds a suboptimal solution to the goal function and a software modeling tool which enables graphical representation of the problem at hand and help developers determine component placement in the system design phase.
Mechanisms underlying weight loss and metabolic improvements in rodent models of bariatric surgery
Arble, Deanna M.; Sandoval, Darleen A.; Seeley, Randy J.
2014-01-01
Obesity is a growing health risk with few successful treatment options and fewer still that target both obesity and obesity-associated comorbidities. Despite ongoing scientific efforts, the most effective treatment option to date was not developed from basic research but by surgeons observing outcomes in the clinic. Bariatric surgery is the most successful treatment for significant weight loss, resolution of type 2 diabetes and the prevention of future weight gain. Recent work with animal models has shed considerable light on the molecular underpinnings of the potent effects of these ‘metabolic’ surgical procedures. Here we review data from animal models and how these studies have evolved our understanding of the critical signalling systems that mediate the effects of bariatric surgery. These insights could lead to alternative therapies able to accomplish effects similar to bariatric surgery in a less invasive manner. PMID:25374275
Directory of Open Access Journals (Sweden)
Alanna McEneny-King
2017-10-01
Full Text Available The total body weight-based dosing strategy currently used in the prophylactic treatment of hemophilia A may not be appropriate for all populations. The assumptions that guide weight-based dosing are not valid in overweight and obese populations, resulting in overdosing and ineffective resource utilization. We explored different weight metrics including lean body weight, ideal body weight, and adjusted body weight to determine an alternative dosing strategy that is both safe and resource-efficient in normal and overweight/obese adult patients. Using a validated population pharmacokinetic model, we simulated a variety of dosing regimens using different doses, weight metrics, and frequencies; we also investigated the implications of assuming various levels of endogenous factor production. Ideal body weight performed the best across all of the regimens explored, maintaining safety while moderating resource consumption for overweight and obese patients.
Allocation of Energy Consumption among Provinces in China: A Weighted ZSG-DEA Model
Siqin Xiong; Yushen Tian; Junping Ji; Xiaoming Ma
2017-01-01
To realize the sustainable development of energy, the Chinese government has formulated a series of national goals of total energy control and energy structure optimization. Under the national constraints, how to efficiently allocate the constrained total amount of energy consumption to each province is a fundamental problem to be solved. Based on a data envelopment analysis (DEA) model and a zero-sum game theory (ZSG), this paper constructs a weighted zero-sum game data envelopment analysis ...
Olanzapine-induced weight gain: lessons learned from developing rat models
van der Zwaal, E.M.
2011-01-01
Olanzapine is an effective and commonly prescribed antipsychotic drug, used for the treatment of schizophrenia and bipolar disorder. Unfortunately significant weight gain is a common side effect. In order to effectively address this side effect, it is crucial to gain insight into the underlying mechanisms. Therefore, this thesis describes the development of a number of rat models that were designed to determine the effects of olanzapine on different aspects of energy balance. In both short- a...
International Nuclear Information System (INIS)
Brown, T.A.; Gillespie, G.H.
1999-01-01
Ion-beam optics models for simulating electrostatic prisms (deflectors) of different geometries have been developed for the computer code TRACE 3-D. TRACE 3-D is an envelope (matrix) code, which includes a linear space charge model, that was originally developed to model bunched beams in magnetic transport systems and radiofrequency (RF) accelerators. Several new optical models for a number of electrostatic lenses and accelerator columns have been developed recently that allow the code to be used for modeling beamlines and accelerators with electrostatic components. The new models include a number of options for: (1) Einzel lenses, (2) accelerator columns, (3) electrostatic prisms, and (4) electrostatic quadrupoles. A prescription for setting up the initial beam appropriate to modeling 2-D (continuous) beams has also been developed. The models for electrostatic prisms are described in this paper. The electrostatic prism model options allow the modeling of cylindrical, spherical, and toroidal electrostatic deflectors. The application of these models in the development of ion-beam transport systems is illustrated through the modeling of a spherical electrostatic analyzer as a component of the new low energy beamline at CAMS
Component Degradation Susceptibilities As The Bases For Modeling Reactor Aging Risk
International Nuclear Information System (INIS)
Unwin, Stephen D.; Lowry, Peter P.; Toyooka, Michael Y.
2010-01-01
The extension of nuclear power plant operating licenses beyond 60 years in the United States will be necessary if we are to meet national energy needs while addressing the issues of carbon and climate. Characterizing the operating risks associated with aging reactors is problematic because the principal tool for risk-informed decision-making, Probabilistic Risk Assessment (PRA), is not ideally-suited to addressing aging systems. The components most likely to drive risk in an aging reactor - the passives - receive limited treatment in PRA, and furthermore, standard PRA methods are based on the assumption of stationary failure rates: a condition unlikely to be met in an aging system. A critical barrier to modeling passives aging on the wide scale required for a PRA is that there is seldom sufficient field data to populate parametric failure models, and nor is there the availability of practical physics models to predict out-year component reliability. The methodology described here circumvents some of these data and modeling needs by using materials degradation metrics, integrated with conventional PRA models, to produce risk importance measures for specific aging mechanisms and component types. We suggest that these measures have multiple applications, from the risk-screening of components to the prioritization of materials research.
Pennel, Cara L; Burdine, James N; Prochaska, John D; McLeroy, Kenneth R
Community health assessment and community health improvement planning are continuous, systematic processes for assessing and addressing health needs in a community. Since there are different models to guide assessment and planning, as well as a variety of organizations and agencies that carry out these activities, there may be confusion in choosing among approaches. By examining the various components of the different assessment and planning models, we are able to identify areas for coordination, ways to maximize collaboration, and strategies to further improve community health. We identified 11 common assessment and planning components across 18 models and requirements, with a particular focus on health department, health system, and hospital models and requirements. These common components included preplanning; developing partnerships; developing vision and scope; collecting, analyzing, and interpreting data; identifying community assets; identifying priorities; developing and implementing an intervention plan; developing and implementing an evaluation plan; communicating and receiving feedback on the assessment findings and/or the plan; planning for sustainability; and celebrating success. Within several of these components, we discuss characteristics that are critical to improving community health. Practice implications include better understanding of different models and requirements by health departments, hospitals, and others involved in assessment and planning to improve cross-sector collaboration, collective impact, and community health. In addition, federal and state policy and accreditation requirements may be revised or implemented to better facilitate assessment and planning collaboration between health departments, hospitals, and others for the purpose of improving community health.
Bridging Weighted Rules and Graph Random Walks for Statistical Relational Models
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Seyed Mehran Kazemi
2018-02-01
Full Text Available The aim of statistical relational learning is to learn statistical models from relational or graph-structured data. Three main statistical relational learning paradigms include weighted rule learning, random walks on graphs, and tensor factorization. These paradigms have been mostly developed and studied in isolation for many years, with few works attempting at understanding the relationship among them or combining them. In this article, we study the relationship between the path ranking algorithm (PRA, one of the most well-known relational learning methods in the graph random walk paradigm, and relational logistic regression (RLR, one of the recent developments in weighted rule learning. We provide a simple way to normalize relations and prove that relational logistic regression using normalized relations generalizes the path ranking algorithm. This result provides a better understanding of relational learning, especially for the weighted rule learning and graph random walk paradigms. It opens up the possibility of using the more flexible RLR rules within PRA models and even generalizing both by including normalized and unnormalized relations in the same model.
Astuti, H. N.; Saputro, D. R. S.; Susanti, Y.
2017-06-01
MGWR model is combination of linear regression model and geographically weighted regression (GWR) model, therefore, MGWR model could produce parameter estimation that had global parameter estimation, and other parameter that had local parameter in accordance with its observation location. The linkage between locations of the observations expressed in specific weighting that is adaptive bi-square. In this research, we applied MGWR model with weighted adaptive bi-square for case of DHF in Surakarta based on 10 factors (variables) that is supposed to influence the number of people with DHF. The observation unit in the research is 51 urban villages and the variables are number of inhabitants, number of houses, house index, many public places, number of healthy homes, number of Posyandu, area width, level population density, welfare of the family, and high-region. Based on this research, we obtained 51 MGWR models. The MGWR model were divided into 4 groups with significant variable is house index as a global variable, an area width as a local variable and the remaining variables vary in each. Global variables are variables that significantly affect all locations, while local variables are variables that significantly affect a specific location.
Han, Seunghoon; Jeon, Sangil; Hong, Taegon; Lee, Jongtae; Bae, Soo Hyeon; Park, Wan-su; Park, Gab-jin; Youn, Sunil; Jang, Doo Yeon; Kim, Kyung-Soo; Yim, Dong-Seok
2015-01-01
No wholly successful weight-control drugs have been developed to date, despite the tremendous demand. We present an exposure–response model of sibutramine mesylate that can be applied during clinical development of other weight-control drugs. Additionally, we provide a model-based evaluation of sibutramine efficacy. Data from a double-blind, randomized, placebo-controlled, multicenter study were used (N=120). Subjects in the treatment arm were initially given 8.37 mg sibutramine base daily, and those who lost sibutramine, including the placebo effect, were modeled using NONMEM 7.2. An asymptotic model approaching the final body weight was chosen to describe the time course of weight loss. Extent of weight loss was described successfully using a sigmoidal exposure–response relationship of the drug with a constant placebo effect in each individual. The placebo effect was influenced by subjects’ sex and baseline body mass index. Maximal weight loss was predicted to occur around 1 year after treatment initiation. The difference in mean weight loss between the sibutramine (daily 12.55 mg) and placebo groups was predicted to be 4.5% in a simulation of 1 year of treatment, with considerable overlap of prediction intervals. Our exposure–response model, which included the placebo effect, is the first example of a quantitative model that can be used to predict the efficacy of weight-control drugs. Similar approaches can help decision-making during clinical development of novel weight-loss drugs. PMID:26392753
Han, Seunghoon; Jeon, Sangil; Hong, Taegon; Lee, Jongtae; Bae, Soo Hyeon; Park, Wan-su; Park, Gab-jin; Youn, Sunil; Jang, Doo Yeon; Kim, Kyung-Soo; Yim, Dong-Seok
2015-01-01
No wholly successful weight-control drugs have been developed to date, despite the tremendous demand. We present an exposure-response model of sibutramine mesylate that can be applied during clinical development of other weight-control drugs. Additionally, we provide a model-based evaluation of sibutramine efficacy. Data from a double-blind, randomized, placebo-controlled, multicenter study were used (N=120). Subjects in the treatment arm were initially given 8.37 mg sibutramine base daily, and those who lost sibutramine, including the placebo effect, were modeled using NONMEM 7.2. An asymptotic model approaching the final body weight was chosen to describe the time course of weight loss. Extent of weight loss was described successfully using a sigmoidal exposure-response relationship of the drug with a constant placebo effect in each individual. The placebo effect was influenced by subjects' sex and baseline body mass index. Maximal weight loss was predicted to occur around 1 year after treatment initiation. The difference in mean weight loss between the sibutramine (daily 12.55 mg) and placebo groups was predicted to be 4.5% in a simulation of 1 year of treatment, with considerable overlap of prediction intervals. Our exposure-response model, which included the placebo effect, is the first example of a quantitative model that can be used to predict the efficacy of weight-control drugs. Similar approaches can help decision-making during clinical development of novel weight-loss drugs.
Hybrid Wing-Body (HWB) Pressurized Fuselage Modeling, Analysis, and Design for Weight Reduction
Mukhopadhyay, Vivek
2012-01-01
This paper describes the interim progress for an in-house study that is directed toward innovative structural analysis and design of next-generation advanced aircraft concepts, such as the Hybrid Wing-Body (HWB) and the Advanced Mobility Concept-X flight vehicles, for structural weight reduction and associated performance enhancement. Unlike the conventional, skin-stringer-frame construction for a cylindrical fuselage, the box-type pressurized fuselage panels in the HWB undergo significant deformation of the outer aerodynamic surfaces, which must be minimized without significant structural weight penalty. Simple beam and orthotropic plate theory is first considered for sizing, analytical verification, and possible equivalent-plate analysis with appropriate simplification. By designing advanced composite stiffened-shell configurations, significant weight reduction may be possible compared with the sandwich and ribbed-shell structural concepts that have been studied previously. The study involves independent analysis of the advanced composite structural concepts that are presently being developed by The Boeing Company for pressurized HWB flight vehicles. High-fidelity parametric finite-element models of test coupons, panels, and multibay fuselage sections, were developed for conducting design studies and identifying critical areas of potential failure. Interim results are discussed to assess the overall weight/strength advantages.
Mehak, Adrienne; Friedman, Aliza; Cassin, Stephanie E
2018-03-01
Self-objectification and weight bias internalization are two internalization processes that are positively correlated with binge eating among young women. However, the mechanisms underlying these relationships are understudied. Consistent with objectification theory, this study examined appearance anxiety and body shame as mediators between self-objectification, weight bias internalization and binge eating. Female undergraduates (N=102) completed self-report measures of self-objectification, weight bias internalization, appearance anxiety, body shame, and binge eating. Results indicated that women who self-objectified and internalized negative weight-related attitudes reported greater binge eating (r s =.43 and r s =.57, respectively) and these associations were mediated by the combined effects of body shame and appearance anxiety. The contrast between the two mediators was also significant, such that body shame emerged as a stronger mediator within both mediational models. Results demonstrated that these internalization processes contribute to negative affect in young women, which may in turn lead to binge eating. Copyright © 2018 Elsevier Ltd. All rights reserved.
International Nuclear Information System (INIS)
Fang Zheng; Zhang Quanru
2006-01-01
A model has been derived to predict thermodynamic properties of ternary metallic systems from those of its three binaries. In the model, the excess Gibbs free energies and the interaction parameter ω 123 for three components of a ternary are expressed as a simple sum of those of the three sub-binaries, and the mole fractions of the components of the ternary are identical with the sub-binaries. This model is greatly simplified compared with the current symmetrical and asymmetrical models. It is able to overcome some shortcomings of the current models, such as the arrangement of the components in the Gibbs triangle, the conversion of mole fractions between ternary and corresponding binaries, and some necessary processes for optimizing the various parameters of these models. Two ternary systems, Mg-Cu-Ni and Cd-Bi-Pb are recalculated to demonstrate the validity and precision of the present model. The calculated results on the Mg-Cu-Ni system are better than those in the literature. New parameters in the Margules equations expressing the excess Gibbs free energies of three binary systems of the Cd-Bi-Pb ternary system are also given
Failure Predictions for VHTR Core Components using a Probabilistic Contiuum Damage Mechanics Model
Energy Technology Data Exchange (ETDEWEB)
Fok, Alex
2013-10-30
The proposed work addresses the key research need for the development of constitutive models and overall failure models for graphite and high temperature structural materials, with the long-term goal being to maximize the design life of the Next Generation Nuclear Plant (NGNP). To this end, the capability of a Continuum Damage Mechanics (CDM) model, which has been used successfully for modeling fracture of virgin graphite, will be extended as a predictive and design tool for the core components of the very high- temperature reactor (VHTR). Specifically, irradiation and environmental effects pertinent to the VHTR will be incorporated into the model to allow fracture of graphite and ceramic components under in-reactor conditions to be modeled explicitly using the finite element method. The model uses a combined stress-based and fracture mechanics-based failure criterion, so it can simulate both the initiation and propagation of cracks. Modern imaging techniques, such as x-ray computed tomography and digital image correlation, will be used during material testing to help define the baseline material damage parameters. Monte Carlo analysis will be performed to address inherent variations in material properties, the aim being to reduce the arbitrariness and uncertainties associated with the current statistical approach. The results can potentially contribute to the current development of American Society of Mechanical Engineers (ASME) codes for the design and construction of VHTR core components.
DEFF Research Database (Denmark)
Vestergaard-Poulsen, Peter; Hansen, Brian; Østergaard, Leif
2007-01-01
compartment. A global optimum was found from a wide range of parameter permutations using cluster computing. We also present simulations of cell swelling and changes of exchange rate and intracellular diffusion as possible cellular mechanisms in ischemia. RESULTS: Our model estimates an extracellular volume...... compartments and slow water exchange. Our model reproduces the signal changes observed in ischemia via physiologically credible mechanisms. CONCLUSION: Our modeling suggests that transverse relaxation has a profound influence on the diffusion attenuated MR signal. Our simulations indicate cell swelling...... model to the diffusion-weighted MR signal obtained from cortical gray matter in healthy subjects. Our model includes variable volume fractions, intracellular restriction effects, and exchange between compartments in addition to individual diffusion coefficients and transverse relaxation rates for each...
Energy Technology Data Exchange (ETDEWEB)
Zhou, Ping; Lv, Youbin; Wang, Hong; Chai, Tianyou
2017-09-01
Optimal operation of a practical blast furnace (BF) ironmaking process depends largely on a good measurement of molten iron quality (MIQ) indices. However, measuring the MIQ online is not feasible using the available techniques. In this paper, a novel data-driven robust modeling is proposed for online estimation of MIQ using improved random vector functional-link networks (RVFLNs). Since the output weights of traditional RVFLNs are obtained by the least squares approach, a robustness problem may occur when the training dataset is contaminated with outliers. This affects the modeling accuracy of RVFLNs. To solve this problem, a Cauchy distribution weighted M-estimation based robust RFVLNs is proposed. Since the weights of different outlier data are properly determined by the Cauchy distribution, their corresponding contribution on modeling can be properly distinguished. Thus robust and better modeling results can be achieved. Moreover, given that the BF is a complex nonlinear system with numerous coupling variables, the data-driven canonical correlation analysis is employed to identify the most influential components from multitudinous factors that affect the MIQ indices to reduce the model dimension. Finally, experiments using industrial data and comparative studies have demonstrated that the obtained model produces a better modeling and estimating accuracy and stronger robustness than other modeling methods.
DEFF Research Database (Denmark)
Ravn, Bjarne Gottlieb; Andersen, Claus Bo; Wanheim, Tarras
2001-01-01
There are three demands on a component that must undergo a die-cavity elasticity analysis. The demands to the product are specified as: (i) to be able to measure the loading profile which results in elestic die-cavity deflections; (ii) to be able to compute the elestic deflections using FE; (iii...
International Nuclear Information System (INIS)
Boutilier, J; Chan, T; Lee, T; Craig, T; Sharpe, M
2014-01-01
Purpose: To develop a statistical model that predicts optimization objective function weights from patient geometry for intensity-modulation radiotherapy (IMRT) of prostate cancer. Methods: A previously developed inverse optimization method (IOM) is applied retrospectively to determine optimal weights for 51 treated patients. We use an overlap volume ratio (OVR) of bladder and rectum for different PTV expansions in order to quantify patient geometry in explanatory variables. Using the optimal weights as ground truth, we develop and train a logistic regression (LR) model to predict the rectum weight and thus the bladder weight. Post hoc, we fix the weights of the left femoral head, right femoral head, and an artificial structure that encourages conformity to the population average while normalizing the bladder and rectum weights accordingly. The population average of objective function weights is used for comparison. Results: The OVR at 0.7cm was found to be the most predictive of the rectum weights. The LR model performance is statistically significant when compared to the population average over a range of clinical metrics including bladder/rectum V53Gy, bladder/rectum V70Gy, and mean voxel dose to the bladder, rectum, CTV, and PTV. On average, the LR model predicted bladder and rectum weights that are both 63% closer to the optimal weights compared to the population average. The treatment plans resulting from the LR weights have, on average, a rectum V70Gy that is 35% closer to the clinical plan and a bladder V70Gy that is 43% closer. Similar results are seen for bladder V54Gy and rectum V54Gy. Conclusion: Statistical modelling from patient anatomy can be used to determine objective function weights in IMRT for prostate cancer. Our method allows the treatment planners to begin the personalization process from an informed starting point, which may lead to more consistent clinical plans and reduce overall planning time
Energy Technology Data Exchange (ETDEWEB)
Boutilier, J; Chan, T; Lee, T [University of Toronto, Toronto, Ontario (Canada); Craig, T; Sharpe, M [University of Toronto, Toronto, Ontario (Canada); The Princess Margaret Cancer Centre - UHN, Toronto, ON (Canada)
2014-06-15
Purpose: To develop a statistical model that predicts optimization objective function weights from patient geometry for intensity-modulation radiotherapy (IMRT) of prostate cancer. Methods: A previously developed inverse optimization method (IOM) is applied retrospectively to determine optimal weights for 51 treated patients. We use an overlap volume ratio (OVR) of bladder and rectum for different PTV expansions in order to quantify patient geometry in explanatory variables. Using the optimal weights as ground truth, we develop and train a logistic regression (LR) model to predict the rectum weight and thus the bladder weight. Post hoc, we fix the weights of the left femoral head, right femoral head, and an artificial structure that encourages conformity to the population average while normalizing the bladder and rectum weights accordingly. The population average of objective function weights is used for comparison. Results: The OVR at 0.7cm was found to be the most predictive of the rectum weights. The LR model performance is statistically significant when compared to the population average over a range of clinical metrics including bladder/rectum V53Gy, bladder/rectum V70Gy, and mean voxel dose to the bladder, rectum, CTV, and PTV. On average, the LR model predicted bladder and rectum weights that are both 63% closer to the optimal weights compared to the population average. The treatment plans resulting from the LR weights have, on average, a rectum V70Gy that is 35% closer to the clinical plan and a bladder V70Gy that is 43% closer. Similar results are seen for bladder V54Gy and rectum V54Gy. Conclusion: Statistical modelling from patient anatomy can be used to determine objective function weights in IMRT for prostate cancer. Our method allows the treatment planners to begin the personalization process from an informed starting point, which may lead to more consistent clinical plans and reduce overall planning time.
Hypothalamic deep brain stimulation reduces weight gain in an obesity-animal model.
Directory of Open Access Journals (Sweden)
William P Melega
Full Text Available Prior studies of appetite regulatory networks, primarily in rodents, have established that targeted electrical stimulation of ventromedial hypothalamus (VMH can alter food intake patterns and metabolic homeostasis. Consideration of this method for weight modulation in humans with severe overeating disorders and morbid obesity can be further advanced by modeling procedures and assessing endpoints that can provide preclinical data on efficacy and safety. In this study we adapted human deep brain stimulation (DBS stereotactic methods and instrumentation to demonstrate in a large animal model the modulation of weight gain with VMH-DBS. Female Göttingen minipigs were used because of their dietary habits, physiologic characteristics, and brain structures that resemble those of primates. Further, these animals become obese on extra-feeding regimens. DBS electrodes were first bilaterally implanted into the VMH of the animals (n = 8 which were then maintained on a restricted food regimen for 1 mo following the surgery. The daily amount of food was then doubled for the next 2 mo in all animals to produce obesity associated with extra calorie intake, with half of the animals (n = 4 concurrently receiving continuous low frequency (50 Hz VMH-DBS. Adverse motoric or behavioral effects were not observed subsequent to the surgical procedure or during the DBS period. Throughout this 2 mo DBS period, all animals consumed the doubled amount of daily food. However, the animals that had received VMH-DBS showed a cumulative weight gain (6.1±0.4 kg; mean ± SEM that was lower than the nonstimulated VMH-DBS animals (9.4±1.3 kg; p<0.05, suggestive of a DBS-associated increase in metabolic rate. These results in a porcine obesity model demonstrate the efficacy and behavioral safety of a low frequency VMH-DBS application as a potential clinical strategy for modulation of body weight.
Hydrodynamic Cucker-Smale model with normalized communication weights and time delay
Choi, Young-Pil
2017-07-17
We study a hydrodynamic Cucker-Smale-type model with time delay in communication and information processing, in which agents interact with each other through normalized communication weights. The model consists of a pressureless Euler system with time delayed non-local alignment forces. We resort to its Lagrangian formulation and prove the existence of its global in time classical solutions. Moreover, we derive a sufficient condition for the asymptotic flocking behavior of the solutions. Finally, we show the presence of a critical phenomenon for the Eulerian system posed in the spatially one-dimensional setting.
voom: Precision weights unlock linear model analysis tools for RNA-seq read counts.
Law, Charity W; Chen, Yunshun; Shi, Wei; Smyth, Gordon K
2014-02-03
New normal linear modeling strategies are presented for analyzing read counts from RNA-seq experiments. The voom method estimates the mean-variance relationship of the log-counts, generates a precision weight for each observation and enters these into the limma empirical Bayes analysis pipeline. This opens access for RNA-seq analysts to a large body of methodology developed for microarrays. Simulation studies show that voom performs as well or better than count-based RNA-seq methods even when the data are generated according to the assumptions of the earlier methods. Two case studies illustrate the use of linear modeling and gene set testing methods.
Reliability Assessment of IGBT Modules Modeled as Systems with Correlated Components
DEFF Research Database (Denmark)
Kostandyan, Erik; Sørensen, John Dalsgaard
2013-01-01
configuration. The estimated system reliability by the proposed method is a conservative estimate. Application of the suggested method could be extended for reliability estimation of systems composing of welding joints, bolts, bearings, etc. The reliability model incorporates the correlation between...... was applied for the systems failure functions estimation. It is desired to compare the results with the true system failure function, which is possible to estimate using simulation techniques. Theoretical model development should be applied for the further research. One of the directions for it might...... be modeling the system based on the Sequential Order Statistics, by considering the failure of the minimum (weakest component) at each loading level. The proposed idea to represent the system by the independent components could also be used for modeling reliability by Sequential Order Statistics....
Refinement and verification in component-based model-driven design
DEFF Research Database (Denmark)
Chen, Zhenbang; Liu, Zhiming; Ravn, Anders Peter
2009-01-01
Modern software development is complex as it has to deal with many different and yet related aspects of applications. In practical software engineering this is now handled by a UML-like modelling approach in which different aspects are modelled by different notations. Component-based and object-o...... be integrated in computer-aided software engineering (CASE) tools for adding formally supported checking, transformation and generation facilities.......Modern software development is complex as it has to deal with many different and yet related aspects of applications. In practical software engineering this is now handled by a UML-like modelling approach in which different aspects are modelled by different notations. Component-based and object...
International Nuclear Information System (INIS)
Sengupta, S.K.; Boyle, J.S.
1993-05-01
Variables describing atmospheric circulation and other climate parameters derived from various GCMs and obtained from observations can be represented on a spatio-temporal grid (lattice) structure. The primary objective of this paper is to explore existing as well as some new statistical methods to analyze such data structures for the purpose of model diagnostics and intercomparison from a statistical perspective. Among the several statistical methods considered here, a new method based on common principal components appears most promising for the purpose of intercomparison of spatio-temporal data structures arising in the task of model/model and model/data intercomparison. A complete strategy for such an intercomparison is outlined. The strategy includes two steps. First, the commonality of spatial structures in two (or more) fields is captured in the common principal vectors. Second, the corresponding principal components obtained as time series are then compared on the basis of similarities in their temporal evolution
Photonic Beamformer Model Based on Analog Fiber-Optic Links’ Components
International Nuclear Information System (INIS)
Volkov, V A; Gordeev, D A; Ivanov, S I; Lavrov, A P; Saenko, I I
2016-01-01
The model of photonic beamformer for wideband microwave phased array antenna is investigated. The main features of the photonic beamformer model based on true-time-delay technique, DWDM technology and fiber chromatic dispersion are briefly analyzed. The performance characteristics of the key components of photonic beamformer for phased array antenna in the receive mode are examined. The beamformer model composed of the components available on the market of fiber-optic analog communication links is designed and tentatively investigated. Experimental demonstration of the designed model beamforming features includes actual measurement of 5-element microwave linear array antenna far-field patterns in 6-16 GHz frequency range for antenna pattern steering up to 40°. The results of experimental testing show good accordance with the calculation estimates. (paper)
International Nuclear Information System (INIS)
Brown, T.A.; Gillespie, G.H.
2000-01-01
Ion-beam optics models for simulating electrostatic prisms (deflectors) of different geometries have been developed for the envelope (matrix) computer code TRACE 3-D as a part of the development of a suite of electrostatic beamline element models which includes lenses, acceleration columns, quadrupoles and prisms. The models for electrostatic prisms are described in this paper. The electrostatic prism model options allow the first-order modeling of cylindrical, spherical and toroidal electrostatic deflectors. The application of these models in the development of ion-beam transport systems is illustrated through the modeling of a spherical electrostatic analyzer as a component of the new low-energy beamline at the Center for Accelerator Mass Spectrometry. Although initial tests following installation of the new beamline showed that the new spherical electrostatic analyzer was not behaving as predicted by these first-order models, operational conditions were found under which the analyzer now works properly as a double-focusing spherical electrostatic prism
The feature-weighted receptive field: an interpretable encoding model for complex feature spaces.
St-Yves, Ghislain; Naselaris, Thomas
2017-06-20
We introduce the feature-weighted receptive field (fwRF), an encoding model designed to balance expressiveness, interpretability and scalability. The fwRF is organized around the notion of a feature map-a transformation of visual stimuli into visual features that preserves the topology of visual space (but not necessarily the native resolution of the stimulus). The key assumption of the fwRF model is that activity in each voxel encodes variation in a spatially localized region across multiple feature maps. This region is fixed for all feature maps; however, the contribution of each feature map to voxel activity is weighted. Thus, the model has two separable sets of parameters: "where" parameters that characterize the location and extent of pooling over visual features, and "what" parameters that characterize tuning to visual features. The "where" parameters are analogous to classical receptive fields, while "what" parameters are analogous to classical tuning functions. By treating these as separable parameters, the fwRF model complexity is independent of the resolution of the underlying feature maps. This makes it possible to estimate models with thousands of high-resolution feature maps from relatively small amounts of data. Once a fwRF model has been estimated from data, spatial pooling and feature tuning can be read-off directly with no (or very little) additional post-processing or in-silico experimentation. We describe an optimization algorithm for estimating fwRF models from data acquired during standard visual neuroimaging experiments. We then demonstrate the model's application to two distinct sets of features: Gabor wavelets and features supplied by a deep convolutional neural network. We show that when Gabor feature maps are used, the fwRF model recovers receptive fields and spatial frequency tuning functions consistent with known organizational principles of the visual cortex. We also show that a fwRF model can be used to regress entire deep
Directory of Open Access Journals (Sweden)
Kristian Traberg Larsen
Full Text Available The objective of the present study was to evaluate the effectiveness of a one-year multi-component immersive day-camp weight-loss intervention for children with overweight and obesity. The study design was a parallel-group randomized controlled trial. One hundred fifteen 11-13-year-old children with overweight and obesity were randomized into either: A six-week day-camp intervention arm focusing on increased physical activity, and healthy diet followed by a subsequent one-year family-based intervention, or a standard intervention arm consisting of one weekly exercise session for six weeks. Body mass index (BMI was the primary outcome. BMI z-score, clustered cardiovascular risk z-score, and body composition were secondary outcomes. All outcomes were measured at baseline, six week-, and 52 week follow-up. After six weeks, children from the day-camp intervention arm had improved their BMI (-2.2 kg/m2 (95% CI -2.6 to -1.7, P<0.001 and all secondary outcomes when compared to the children from the standard intervention arm. After 52 weeks, the day-camp intervention arm had a lower BMI (-1.2 kg/m2 (95% CI -1.8 to -0.5, P = 0.001, and BMI z-score (-0.20 (95% CI -0.35 to -0.05, P = 0.008, and clustered cardiovascular risk z-score (-0.23 (95% CI -0.37 to -0.08, P = 0.002 compared to the standard intervention arm. No group differences were detected in body composition after 52 weeks. This study shows that the day-camp intervention arm is effective in reducing BMI and improving the metabolic health of children with overweight and obesity. However, the effects seem to be diminishing over time.
A review of multi-component maintenance models with economic dependence
R. Dekker (Rommert); R.E. Wildeman (Ralph); F.A. van der Duyn Schouten (Frank)
1997-01-01
textabstractIn this paper we review the literature on multi-component maintenance models with economic dependence. The emphasis is on papers that appeared after 1991, but there is an overlap with Section 2 of the most recent review paper by Cho and Parlar (1991). We distinguish between stationary
Specification and Generation of Environment for Model Checking of Software Components
Czech Academy of Sciences Publication Activity Database
Pařízek, P.; Plášil, František
2007-01-01
Roč. 176, - (2007), s. 143-154 ISSN 1571-0661 R&D Projects: GA AV ČR 1ET400300504 Institutional research plan: CEZ:AV0Z10300504 Keywords : software components * behavior protocols * model checking * automated generation of environment Subject RIV: JC - Computer Hardware ; Software
Helpful Components Involved in the Cognitive-Experiential Model of Dream Work
Tien, Hsiu-Lan Shelley; Chen, Shuh-Chi; Lin, Chia-Huei
2009-01-01
The purpose of the study was to examine the helpful components involved in the Hill's cognitive-experiential dream work model. Participants were 27 volunteer clients from colleges and universities in northern and central parts of Taiwan. Each of the clients received 1-2 sessions of dream interpretations. The cognitive-experiential dream work model…
A Bayesian analysis of the PPP puzzle using an unobserved components model
R.H. Kleijn (Richard); H.K. van Dijk (Herman)
2001-01-01
textabstractThe failure to describe the time series behaviour of most real exchange rates as temporary deviations from fixed long-term means may be due to time variation of the equilibria themselves, see Engel (2000). We implement this idea using an unobserved components model and decompose the
Passively model-locked Nd: YAG laser with a component GaAs
International Nuclear Information System (INIS)
Zhang Zhuhong; Qian Liejia; Chen Shaohe; Fan Dianyuan; Mao Hongwei
1992-01-01
An all solid-state passively mode-locked Nd: YAG laser with a 400 μm, (100) oriented GaAs component is reported for the first time and model locked pulses with a duration of 16 ps, average energy of 10 μJ were obtained with a probability of 90%
Kou, Jisheng; Sun, Shuyu
2017-01-01
A general diffuse interface model with a realistic equation of state (e.g. Peng-Robinson equation of state) is proposed to describe the multi-component two-phase fluid flow based on the principles of the NVT-based framework which is an attractive
A two-component dark matter model with real singlet scalars ...
Indian Academy of Sciences (India)
Theoretical framework. In the present work, the dark matter candidate has two components S and S′ both of ... The scalar sector potential (for Higgs and two real singlet scalars) in this framework can then be written .... In this work we obtain the allowed values of model parameters (δ2, δ′2, MS and M′S) using three direct ...
Ontologies to Support RFID-Based Link between Virtual Models and Construction Components
DEFF Research Database (Denmark)
Sørensen, Kristian Birch; Christiansson, Per; Svidt, Kjeld
2010-01-01
the virtual models and the physical components in the construction process can improve the information handling and sharing in construction and building operation management. Such a link can be created by means of Radio Frequency Identification (RFID) technology. Ontologies play an important role...
Correlation inequalities for two-component hypercubic φ4 models. Pt. 2
International Nuclear Information System (INIS)
Soria, J.L.; Instituto Tecnologico de Tijuana
1990-01-01
We continue the program started in the first paper (J. Stat. Phys. 52 (1988) 711-726). We find new and already known correlation inequalities for a family of two-component hypercubic φ 4 models, using techniques of rotated correlation inequalities and random walk representation. (orig.)
Hontelez, J.A.M.; Wijnmalen, D.J.D.
1993-01-01
We discuss a method to determine strategies for preventive maintenance of systems consisting of gradually deteriorating components. A model has been developed to compute not only the range of conditions inducing a repair action, but also inspection moments based on the last known condition value so
Quantifying functional connectivity in multi-subject fMRI data using component models
DEFF Research Database (Denmark)
Madsen, Kristoffer Hougaard; Churchill, Nathan William; Mørup, Morten
2017-01-01
of functional connectivity, evaluated on both simulated and experimental resting-state fMRI data. It was demonstrated that highly flexible subject-specific component subspaces, as well as very constrained average models, are poor predictors of whole-brain functional connectivity, whereas the best...
Particle Markov Chain Monte Carlo Techniques of Unobserved Component Time Series Models Using Ox
DEFF Research Database (Denmark)
Nonejad, Nima
This paper details Particle Markov chain Monte Carlo techniques for analysis of unobserved component time series models using several economic data sets. PMCMC combines the particle filter with the Metropolis-Hastings algorithm. Overall PMCMC provides a very compelling, computationally fast...... and efficient framework for estimation. These advantages are used to for instance estimate stochastic volatility models with leverage effect or with Student-t distributed errors. We also model changing time series characteristics of the US inflation rate by considering a heteroskedastic ARFIMA model where...
Around power law for PageRank components in Buckley-Osthus model of web graph
Gasnikov, Alexander; Zhukovskii, Maxim; Kim, Sergey; Noskov, Fedor; Plaunov, Stepan; Smirnov, Daniil
2017-01-01
In the paper we investigate power law for PageRank components for the Buckley-Osthus model for web graph. We compare different numerical methods for PageRank calculation. With the best method we do a lot of numerical experiments. These experiments confirm the hypothesis about power law. At the end we discuss real model of web-ranking based on the classical PageRank approach.
The use of error components models in business finance. : a review article and an application
Καραθανάσης, Γεώργιος Α.; Φίλιππας, Νικόλαος
1993-01-01
This study applies and tests several stock valuation models of companies whose shares are traded in the Athens Stock Exchange. The relevant equations are estimated for the five major sectors of the Athens Stock Exchange (Banks, Textiles, Foods, Buildings, Commercials) using a specification which combines cross sectional and time series data. This is the Error Components Model. In view of the results obtained the most important variables across sectors appear to be dividends fol...
Component simulation in problems of calculated model formation of automatic machine mechanisms
Telegin Igor; Kozlov Alexander; Zhirkov Alexander
2017-01-01
The paper deals with the problems of the component simulation method application in the problems of the automation of the mechanical system model formation with the further possibility of their CAD-realization. The purpose of the investigations mentioned consists in the automation of the CAD-model formation of high-speed mechanisms in automatic machines and in the analysis of dynamic processes occurred in their units taking into account their elasto-inertial properties, power dissipation, gap...
Modelling the Load Curve of Aggregate Electricity Consumption Using Principal Components
Matteo Manera; Angelo Marzullo
2003-01-01
Since oil is a non-renewable resource with a high environmental impact, and its most common use is to produce combustibles for electricity, reliable methods for modelling electricity consumption can contribute to a more rational employment of this hydrocarbon fuel. In this paper we apply the Principal Components (PC) method to modelling the load curves of Italy, France and Greece on hourly data of aggregate electricity consumption. The empirical results obtained with the PC approach are compa...
Space-time latent component Modeling of Geo-referenced health data
Lawson, Andrew B.; Song, Hae-Ryoung; Cai, Bo; Hossain, Md Monir; Huang, Kun
2010-01-01
Latent structure models have been proposed in many applications. For space time health data it is often important to be able to find underlying trends in time which are supported by subsets of small areas. Latent structure modeling is one approach to this analysis. This paper presents a mixture-based approach that can be appied to component selction. The analysis of a Georgia ambulatory asthma county level data set is presented and a simulation-based evaluation is made.
Guo, Yang; Lin, Wenfang; Yu, Shuyang; Ji, Yang
2018-01-01
Predictive maintenance plays an important role in modern Cyber-Physical Systems (CPSs) and data-driven methods have been a worthwhile direction for Prognostics Health Management (PHM). However, two main challenges have significant influences on the traditional fault diagnostic models: one is that extracting hand-crafted features from multi-dimensional sensors with internal dependencies depends too much on expertise knowledge; the other is that imbalance pervasively exists among faulty and normal samples. As deep learning models have proved to be good methods for automatic feature extraction, the objective of this paper is to study an optimized deep learning model for imbalanced fault diagnosis for CPSs. Thus, this paper proposes a weighted Long Recurrent Convolutional LSTM model with sampling policy (wLRCL-D) to deal with these challenges. The model consists of 2-layer CNNs, 2-layer inner LSTMs and 2-Layer outer LSTMs, with under-sampling policy and weighted cost-sensitive loss function. Experiments are conducted on PHM 2015 challenge datasets, and the results show that wLRCL-D outperforms other baseline methods. PMID:29621131
Directory of Open Access Journals (Sweden)
Zhenyu Wu
2018-04-01
Full Text Available Predictive maintenance plays an important role in modern Cyber-Physical Systems (CPSs and data-driven methods have been a worthwhile direction for Prognostics Health Management (PHM. However, two main challenges have significant influences on the traditional fault diagnostic models: one is that extracting hand-crafted features from multi-dimensional sensors with internal dependencies depends too much on expertise knowledge; the other is that imbalance pervasively exists among faulty and normal samples. As deep learning models have proved to be good methods for automatic feature extraction, the objective of this paper is to study an optimized deep learning model for imbalanced fault diagnosis for CPSs. Thus, this paper proposes a weighted Long Recurrent Convolutional LSTM model with sampling policy (wLRCL-D to deal with these challenges. The model consists of 2-layer CNNs, 2-layer inner LSTMs and 2-Layer outer LSTMs, with under-sampling policy and weighted cost-sensitive loss function. Experiments are conducted on PHM 2015 challenge datasets, and the results show that wLRCL-D outperforms other baseline methods.
Ribeiro, Manuel Castro; Sousa, António Jorge; Pereira, Maria João
2016-05-01
The geographical distribution of health outcomes is influenced by socio-economic and environmental factors operating on different spatial scales. Geographical variations in relationships can be revealed with semi-parametric Geographically Weighted Poisson Regression (sGWPR), a model that can combine both geographically varying and geographically constant parameters. To decide whether a parameter should vary geographically, two models are compared: one in which all parameters are allowed to vary geographically and one in which all except the parameter being evaluated are allowed to vary geographically. The model with the lower corrected Akaike Information Criterion (AICc) is selected. Delivering model selection exclusively according to the AICc might hide important details in spatial variations of associations. We propose assisting the decision by using a Linear Model of Coregionalization (LMC). Here we show how LMC can refine sGWPR on ecological associations between socio-economic and environmental variables and low birth weight outcomes in the west-north-central region of Portugal. Copyright © 2016 Elsevier Ltd. All rights reserved.
Genetic parameters for quail body weights using a random ...
African Journals Online (AJOL)
A model including fixed and random linear regressions is described for analyzing body weights at different ages. In this study, (co)variance components, heritabilities for quail weekly weights and genetic correlations among these weights were estimated using a random regression model by DFREML under DXMRR option.
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
With the fast growth of Chinese economic,more and more capital will be invested in environmental projects.How to select the environmental investment projects(alternatives)for obtaining the best environmental quality and economic benefits is an important problem for the decision makers.The purpose of this paper is to develop a decision-making model to rank a finite number of alternatives with several and sometimes conflicting criteria.A model for ranking the projects of municipal sewage treatment plants is proposed by using exports' information and the data of the real projects.And,the ranking result is given based on the PROMETHEE method. Furthermore,by means of the concept of the weight stability intervals(WSI),the sensitivity of the ranking results to the size of criteria values and the change of weights value of criteria are discussed.The result shows that some criteria,such as"proportion of benefit to projoct cost",will influence the ranking result of alternatives very strong while others not.The influence are not only from the value of criterion but also from the changing the weight of criterion.So,some criteria such as"proportion of benefit to projoct cost" are key critera for ranking the projects. Decision makers must be cautious to them.
Why weight? Modelling sample and observational level variability improves power in RNA-seq analyses.
Liu, Ruijie; Holik, Aliaksei Z; Su, Shian; Jansz, Natasha; Chen, Kelan; Leong, Huei San; Blewitt, Marnie E; Asselin-Labat, Marie-Liesse; Smyth, Gordon K; Ritchie, Matthew E
2015-09-03
Variations in sample quality are frequently encountered in small RNA-sequencing experiments, and pose a major challenge in a differential expression analysis. Removal of high variation samples reduces noise, but at a cost of reducing power, thus limiting our ability to detect biologically meaningful changes. Similarly, retaining these samples in the analysis may not reveal any statistically significant changes due to the higher noise level. A compromise is to use all available data, but to down-weight the observations from more variable samples. We describe a statistical approach that facilitates this by modelling heterogeneity at both the sample and observational levels as part of the differential expression analysis. At the sample level this is achieved by fitting a log-linear variance model that includes common sample-specific or group-specific parameters that are shared between genes. The estimated sample variance factors are then converted to weights and combined with observational level weights obtained from the mean-variance relationship of the log-counts-per-million using 'voom'. A comprehensive analysis involving both simulations and experimental RNA-sequencing data demonstrates that this strategy leads to a universally more powerful analysis and fewer false discoveries when compared to conventional approaches. This methodology has wide application and is implemented in the open-source 'limma' package. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.
Annesi, James J; Johnson, Ping H; Tennant, Gisèle A; Porter, Kandice J; Mcewen, Kristin L
2016-01-01
For decades, behavioral weight-loss treatments have been unsuccessful beyond the short term. Development and testing of innovative, theoretically based methods that depart from current failed practices is a priority for behavioral medicine. To evaluate a new, theory-based protocol in which exercise support methods are employed to facilitate improvements in psychosocial predictors of controlled eating and sustained weight loss. Women with obesity were randomized into either a comparison treatment that incorporated a print manual plus telephone follow-ups (n = 55) or an experimental treatment of The Coach Approach exercise-support protocol followed after 2 months by group nutrition sessions focused on generalizing self-regulatory skills from an exercise support to a controlled eating context (n = 55). Repeated-measures analysis of variance contrasted group changes in weight, physical activity, fruit and vegetable intake, mood, and exercise- and eating-related self-regulation and self-efficacy over 24 months. Regression analyses determined salient interrelations of change scores over both the weight-loss phase (baseline-month 6) and weight-loss maintenance phase (month 6-month 24). Improvements in all psychological measures, physical activity, and fruit and vegetable intake were significantly greater in the experimental group where a mean weight loss of 5.7 kg (6.1% of initial body weight) occurred at month 6, and was largely maintained at a loss of 5.1 kg (5.4%) through the full 24 months of the study. After establishing temporal intervals for changes in self-regulation, self-efficacy, and mood that best predicted improvements in physical activity and eating, a consolidated multiple mediation model suggested that change in self-regulation best predicted weight loss, whereas change in self-efficacy best predicted maintenance of lost weight. Because for most participants loss of weight remained greater than that required for health benefits, and costs for treatment
Bian, Zunjian; du, yongming; li, hua
2016-04-01
Land surface temperature (LST) as a key variable plays an important role on hydrological, meteorology and climatological study. Thermal infrared directional anisotropy is one of essential factors to LST retrieval and application on longwave radiance estimation. Many approaches have been proposed to estimate directional brightness temperatures (DBT) over natural and urban surfaces. While less efforts focus on 3-D scene and the surface component temperatures used in DBT models are quiet difficult to acquire. Therefor a combined 3-D model of TRGM (Thermal-region Radiosity-Graphics combined Model) and energy balance method is proposed in the paper for the attempt of synchronously simulation of component temperatures and DBT in the row planted canopy. The surface thermodynamic equilibrium can be final determined by the iteration strategy of TRGM and energy balance method. The combined model was validated by the top-of-canopy DBTs using airborne observations. The results indicated that the proposed model performs well on the simulation of directional anisotropy, especially the hotspot effect. Though we find that the model overestimate the DBT with Bias of 1.2K, it can be an option as a data reference to study temporal variance of component temperatures and DBTs when field measurement is inaccessible
Mixture modeling of multi-component data sets with application to ion-probe zircon ages
Sambridge, M. S.; Compston, W.
1994-12-01
A method is presented for detecting multiple components in a population of analytical observations for zircon and other ages. The procedure uses an approach known as mixture modeling, in order to estimate the most likely ages, proportions and number of distinct components in a given data set. Particular attention is paid to estimating errors in the estimated ages and proportions. At each stage of the procedure several alternative numerical approaches are suggested, each having their own advantages in terms of efficency and accuracy. The methodology is tested on synthetic data sets simulating two or more mixed populations of zircon ages. In this case true ages and proportions of each population are known and compare well with the results of the new procedure. Two examples are presented of its use with sets of SHRIMP U-238 - Pb-206 zircon ages from Palaeozoic rocks. A published data set for altered zircons from bentonite at Meishucun, South China, previously treated as a single-component population after screening for gross alteration effects, can be resolved into two components by the new procedure and their ages, proportions and standard errors estimated. The older component, at 530 +/- 5 Ma (2 sigma), is our best current estimate for the age of the bentonite. Mixture modeling of a data set for unaltered zircons from a tonalite elsewhere defines the magmatic U-238 - Pb-206 age at high precision (2 sigma +/- 1.5 Ma), but one-quarter of the 41 analyses detect hidden and significantly older cores.
International Nuclear Information System (INIS)
Memarzadeh, Milad; Pozzi, Matteo; Kolter, J. Zico
2016-01-01
System management includes the selection of maintenance actions depending on the available observations: when a system is made up by components known to be similar, data collected on one is also relevant for the management of others. This is typically the case of wind farms, which are made up by similar turbines. Optimal management of wind farms is an important task due to high cost of turbines' operation and maintenance: in this context, we recently proposed a method for planning and learning at system-level, called PLUS, built upon the Partially Observable Markov Decision Process (POMDP) framework, which treats transition and emission probabilities as random variables, and is therefore suitable for including model uncertainty. PLUS models the components as independent or identical. In this paper, we extend that formulation, allowing for a weaker similarity among components. The proposed approach, called Multiple Uncertain POMDP (MU-POMDP), models the components as POMDPs, and assumes the corresponding parameters as dependent random variables. Through this framework, we can calibrate specific degradation and emission models for each component while, at the same time, process observations at system-level. We compare the performance of the proposed MU-POMDP with PLUS, and discuss its potential and computational complexity. - Highlights: • A computational framework is proposed for adaptive monitoring and control. • It adopts a scheme based on Markov Chain Monte Carlo for inference and learning. • Hierarchical Bayesian modeling is used to allow a system-level flow of information. • Results show potential of significant savings in management of wind farms.
Directory of Open Access Journals (Sweden)
Peter Vestergaard-Poulsen
Full Text Available Chronic stress has detrimental effects on physiology, learning and memory and is involved in the development of anxiety and depressive disorders. Besides changes in synaptic formation and neurogenesis, chronic stress also induces dendritic remodeling in the hippocampus, amygdala and the prefrontal cortex. Investigations of dendritic remodeling during development and treatment of stress are currently limited by the invasive nature of histological and stereological methods. Here we show that high field diffusion-weighted MRI combined with quantitative biophysical modeling of the hippocampal dendritic loss in 21 day restraint stressed rats highly correlates with former histological findings. Our study strongly indicates that diffusion-weighted MRI is sensitive to regional dendritic loss and thus a promising candidate for non-invasive studies of dendritic plasticity in chronic stress and stress-related disorders.
Directory of Open Access Journals (Sweden)
D. A. Palharim D. A. Palharim
2013-07-01
Full Text Available Abstract: We used 138,976 records of information of body weights ranging from 60 to 610 days of age, from 27,327 Nelore cattle of herds in the state of Mato Grosso. The random regression model with the covariance function of fourth order to describe the variability of the effects of additive genetic, animal and maternal permanent environment and maternal genetic effect and maternal, showed heritability estimates from 0.209 to 0.423 at the beginning by the end of the trajectory, respectively. There is enough genetic variability to promote genetic gain satisfactory performance for weight after weaning period the animals. Keywords: beef cattle, genetic parameters, selection.
The weighted-sum-of-gray-gases model for arbitrary solution methods in radiative transfer
International Nuclear Information System (INIS)
Modest, M.F.
1991-01-01
In this paper the weighted-sum-of-gray-gases approach for radiative transfer in non-gray participating media, first developed by Hottel in the context of the zonal method, has been shown to be applicable to the general radiative equation of transfer. Within the limits of the weighted-sum-of-gray-gases model (non-scattering media within a black-walled enclosure) any non-gray radiation problem can be solved by any desired solution method after replacing the medium by an equivalent small number of gray media with constant absorption coefficients. Some examples are presented for isothermal media and media at radiative equilibrium, using the exact integral equations as well as the popular P-1 approximation of the equivalent gray media solution. The results demonstrate the equivalency of the method with the quadrature of spectral results, as well as the tremendous computer times savings (by a minimum of 95%) which are achieved
Computational models for residual creep life prediction of power plant components
International Nuclear Information System (INIS)
Grewal, G.S.; Singh, A.K.; Ramamoortry, M.
2006-01-01
All high temperature - high pressure power plant components are prone to irreversible visco-plastic deformation by the phenomenon of creep. The steady state creep response as well as the total creep life of a material is related to the operational component temperature through, respectively, the exponential and inverse exponential relationships. Minor increases in the component temperature can thus have serious consequences as far as the creep life and dimensional stability of a plant component are concerned. In high temperature steam tubing in power plants, one mechanism by which a significant temperature rise can occur is by the growth of a thermally insulating oxide film on its steam side surface. In the present paper, an elegantly simple and computationally efficient technique is presented for predicting the residual creep life of steel components subjected to continual steam side oxide film growth. Similarly, fabrication of high temperature power plant components involves extensive use of welding as the fabrication process of choice. Naturally, issues related to the creep life of weldments have to be seriously addressed for safe and continual operation of the welded plant component. Unfortunately, a typical weldment in an engineering structure is a zone of complex microstructural gradation comprising of a number of distinct sub-zones with distinct meso-scale and micro-scale morphology of the phases and (even) chemistry and its creep life prediction presents considerable challenges. The present paper presents a stochastic algorithm, which can be' used for developing experimental creep-cavitation intensity versus residual life correlations for welded structures. Apart from estimates of the residual life in a mean field sense, the model can be used for predicting the reliability of the plant component in a rigorous probabilistic setting. (author)
Analytical probabilistic modeling of RBE-weighted dose for ion therapy
Wieser, H. P.; Hennig, P.; Wahl, N.; Bangert, M.
2017-12-01
Particle therapy is especially prone to uncertainties. This issue is usually addressed with uncertainty quantification and minimization techniques based on scenario sampling. For proton therapy, however, it was recently shown that it is also possible to use closed-form computations based on analytical probabilistic modeling (APM) for this purpose. APM yields unique features compared to sampling-based approaches, motivating further research in this context. This paper demonstrates the application of APM for intensity-modulated carbon ion therapy to quantify the influence of setup and range uncertainties on the RBE-weighted dose. In particular, we derive analytical forms for the nonlinear computations of the expectation value and variance of the RBE-weighted dose by propagating linearly correlated Gaussian input uncertainties through a pencil beam dose calculation algorithm. Both exact and approximation formulas are presented for the expectation value and variance of the RBE-weighted dose and are subsequently studied in-depth for a one-dimensional carbon ion spread-out Bragg peak. With V and B being the number of voxels and pencil beams, respectively, the proposed approximations induce only a marginal loss of accuracy while lowering the computational complexity from order O(V × B^2) to O(V × B) for the expectation value and from O(V × B^4) to O(V × B^2) for the variance of the RBE-weighted dose. Moreover, we evaluated the approximated calculation of the expectation value and standard deviation of the RBE-weighted dose in combination with a probabilistic effect-based optimization on three patient cases considering carbon ions as radiation modality against sampled references. The resulting global γ-pass rates (2 mm,2%) are > 99.15% for the expectation value and > 94.95% for the standard deviation of the RBE-weighted dose, respectively. We applied the derived analytical model to carbon ion treatment planning, although the concept is in general applicable to other
Ferrer, Rebecca A; Klein, William M P; Persoskie, Alexander; Avishai-Yitshak, Aya; Sheeran, Paschal
2016-10-01
Although risk perception is a key predictor in health behavior theories, current conceptions of risk comprise only one (deliberative) or two (deliberative vs. affective/experiential) dimensions. This research tested a tripartite model that distinguishes among deliberative, affective, and experiential components of risk perception. In two studies, and in relation to three common diseases (cancer, heart disease, diabetes), we used confirmatory factor analyses to examine the factor structure of the tripartite risk perception (TRIRISK) model and compared the fit of the TRIRISK model to dual-factor and single-factor models. In a third study, we assessed concurrent validity by examining the impact of cancer diagnosis on (a) levels of deliberative, affective, and experiential risk perception, and (b) the strength of relations among risk components, and tested predictive validity by assessing relations with behavioral intentions to prevent cancer. The tripartite factor structure was supported, producing better model fit across diseases (studies 1 and 2). Inter-correlations among the components were significantly smaller among participants who had been diagnosed with cancer, suggesting that affected populations make finer-grained distinctions among risk perceptions (study 3). Moreover, all three risk perception components predicted unique variance in intentions to engage in preventive behavior (study 3). The TRIRISK model offers both a novel conceptualization of health-related risk perceptions, and new measures that enhance predictive validity beyond that engendered by unidimensional and bidimensional models. The present findings have implications for the ways in which risk perceptions are targeted in health behavior change interventions, health communications, and decision aids.
Ryu, Duchwan
2013-03-01
The sea surface temperature (SST) is an important factor of the earth climate system. A deep understanding of SST is essential for climate monitoring and prediction. In general, SST follows a nonlinear pattern in both time and location and can be modeled by a dynamic system which changes with time and location. In this article, we propose a radial basis function network-based dynamic model which is able to catch the nonlinearity of the data and propose to use the dynamically weighted particle filter to estimate the parameters of the dynamic model. We analyze the SST observed in the Caribbean Islands area after a hurricane using the proposed dynamic model. Comparing to the traditional grid-based approach that requires a supercomputer due to its high computational demand, our approach requires much less CPU time and makes real-time forecasting of SST doable on a personal computer. Supplementary materials for this article are available online. © 2013 American Statistical Association.
EM Simulation Accuracy Enhancement for Broadband Modeling of On-Wafer Passive Components
DEFF Research Database (Denmark)
Johansen, Tom Keinicke; Jiang, Chenhui; Hadziabdic, Dzenan
2007-01-01
This paper describes methods for accuracy enhancement in broadband modeling of on-wafer passive components using electromagnetic (EM) simulation. It is shown that standard excitation schemes for integrated component simulation leads to poor correlation with on-wafer measurements beyond the lower...... GHz frequency range. We show that this is due to parasitic effects and higher-order modes caused by the excitation schemes. We propose a simple equivalent circuit for the parasitic effects in the well-known ground ring excitation scheme. An extended L-2L calibration method is shown to improve...
Weighted regularized statistical shape space projection for breast 3D model reconstruction.
Ruiz, Guillermo; Ramon, Eduard; García, Jaime; Sukno, Federico M; Ballester, Miguel A González
2018-05-02
The use of 3D imaging has increased as a practical and useful tool for plastic and aesthetic surgery planning. Specifically, the possibility of representing the patient breast anatomy in a 3D shape and simulate aesthetic or plastic procedures is a great tool for communication between surgeon and patient during surgery planning. For the purpose of obtaining the specific 3D model of the breast of a patient, model-based reconstruction methods can be used. In particular, 3D morphable models (3DMM) are a robust and widely used method to perform 3D reconstruction. However, if additional prior information (i.e., known landmarks) is combined with the 3DMM statistical model, shape constraints can be imposed to improve the 3DMM fitting accuracy. In this paper, we present a framework to fit a 3DMM of the breast to two possible inputs: 2D photos and 3D point clouds (scans). Our method consists in a Weighted Regularized (WR) projection into the shape space. The contribution of each point in the 3DMM shape is weighted allowing to assign more relevance to those points that we want to impose as constraints. Our method is applied at multiple stages of the 3D reconstruction process. Firstly, it can be used to obtain a 3DMM initialization from a sparse set of 3D points. Additionally, we embed our method in the 3DMM fitting process in which more reliable or already known 3D points or regions of points, can be weighted in order to preserve their shape information. The proposed method has been tested in two different input settings: scans and 2D pictures assessing both reconstruction frameworks with very positive results. Copyright © 2018 Elsevier B.V. All rights reserved.
Arumsari, Nurvita; Sutidjo, S. U.; Brodjol; Soedjono, Eddy S.
2014-03-01
Diarrhea has been one main cause of morbidity and mortality to children around the world, especially in the developing countries According to available data that was mentioned. It showed that sanitary and healthy lifestyle implementation by the inhabitants was not good yet. Inadequacy of environmental influence and the availability of health services were suspected factors which influenced diarrhea cases happened followed by heightened percentage of the diarrheic. This research is aimed at modelling the diarrheic by using Geographically Weighted Lasso method. With the existence of spatial heterogeneity was tested by Breusch Pagan, it was showed that diarrheic modeling with weighted regression, especially GWR and GWL, can explain the variation in each location. But, the absence of multi-collinearity cases on predictor variables, which were affecting the diarrheic, resulted in GWR and GWL modelling to be not different or identical. It is shown from the resulting MSE value. While from R2 value which usually higher on GWL model showed a significant variable predictor based on more parametric shrinkage value.
Allocation of Energy Consumption among Provinces in China: A Weighted ZSG-DEA Model
Directory of Open Access Journals (Sweden)
Siqin Xiong
2017-11-01
Full Text Available To realize the sustainable development of energy, the Chinese government has formulated a series of national goals of total energy control and energy structure optimization. Under the national constraints, how to efficiently allocate the constrained total amount of energy consumption to each province is a fundamental problem to be solved. Based on a data envelopment analysis (DEA model and a zero-sum game theory (ZSG, this paper constructs a weighted zero-sum game data envelopment analysis (ZSG-DEA model to allocate the energy consumption quota. Additionally, this paper compares the results with the current administrative targets, to examine the efficiency and feasibility of each allocation mechanism. Finally, this paper employs the proposed model to determine the optimal energy structure for each province in China. The results indicate that by 2020, the national goal of energy structure adjustment will be realized, and energy structure will be diversified in most regions, whereas the coal-dominated status in primary energy consumption will not change. Additionally, the weighted ZSG-DEA model focuses on allocation efficiency while the government considers more regional economic disparity. Therefore, this study suggests a mixture of the two allocation mechanisms in accordance with specific conditions.
A Canine Non-Weight-Bearing Model with Radial Neurectomy for Rotator Cuff Repair.
Directory of Open Access Journals (Sweden)
Xiaoxi Ji
Full Text Available The major concern of using a large animal model to study rotator cuff repair is the high rate of repair retears. The purpose of this study was to test a non-weight-bearing (NWB canine model for rotator cuff repair research.First, in the in vitro study, 18 shoulders were randomized to 3 groups. 1 Full-width transections repaired with modified Mason-Allen sutures using 3-0 polyglactin suture, 2 Group 1 repaired using number 2 (#2 polyester braid and long-chain polyethylene suture, and 3 Partial-width transections leaving the superior 2 mm infraspinatus tendon intact without repair. In the in vivo study of 6 dogs, the infraspinatus tendon was partially transected as the same as the in vitro group 3. A radial neurectomy was performed to prevent weight bearing. The operated limb was slung in a custom-made jacket for 6 weeks.In the in vitro study, mean ultimate tensile load and stiffness in Group 2 were significantly higher than Group 1 and 3 (p<0.05. In the in vivo study, gross inspection and histology showed that the preserved superior 2-mm portion of the infraspinatus tendon remained intact with normal structure.Based on the biomechanical and histological findings, this canine NWB model may be an appropriate and useful model for studies of rotator cuff repair.
The Development of Nursing Care Services Model for Low Birth Weight Infants
Directory of Open Access Journals (Sweden)
Dessie Wanda
2017-01-01
Full Text Available Introduction: Low birth weight (LBW infants deal with various problems during transitional period from intra-uterine and extra-uterine because of immature organs’ functions. This leads to LBW as the second death cause in Indonesia, particularly in the fi rst seventh days of infants’ lifes. The problem continues to occur at home when the infants have discharged. This research was aimed to develop the nursing care services model for LBW infants and to test the model. Method: The research design was an action research using quantitative and qualitative approach. This design was chosen as it facilitated improvement in health care system, which was involving nurses and other health providers. Results: Nursing care services provided by the nursing team are hindered by several factors, such as various level of nurses’ knowledge, not optimal health education activities, incomplete standard operational procedure, ethical dilemma, paramedic functions, and documentation system. This model was developed based on conservation and becoming a mother/maternal role attainment theory, family-centered care principles, and input from the experts through focus group discussion. Discussion: The result of this research is going to increase the quality of nursing care for LBW infants by achieving nurses’ and parents’ satisfaction in giving care for their infants which can lead to lower infant death rate.Key words: Model, Low birth weight infant, Nursing services, Action research
Research on The Construction of Flexible Multi-body Dynamics Model based on Virtual Components
Dong, Z. H.; Ye, X.; Yang, F.
2018-05-01
Focus on the harsh operation condition of space manipulator, which cannot afford relative large collision momentum, this paper proposes a new concept and technology, called soft-contact technology. In order to solve the problem of collision dynamics of flexible multi-body system caused by this technology, this paper also proposes the concepts of virtual components and virtual hinges, and constructs flexible dynamic model based on virtual components, and also studies on its solutions. On this basis, this paper uses NX to carry out model and comparison simulation for space manipulator in 3 different modes. The results show that using the model of multi-rigid body + flexible body hinge + controllable damping can make effective control on amplitude for the force and torque caused by target satellite collision.
Finsler Geometry Modeling of Phase Separation in Multi-Component Membranes
Directory of Open Access Journals (Sweden)
Satoshi Usui
2016-08-01
Full Text Available A Finsler geometric surface model is studied as a coarse-grained model for membranes of three components, such as zwitterionic phospholipid (DOPC, lipid (DPPC and an organic molecule (cholesterol. To understand the phase separation of liquid-ordered (DPPC rich L o and liquid-disordered (DOPC rich L d , we introduce a binary variable σ ( = ± 1 into the triangulated surface model. We numerically determine that two circular and stripe domains appear on the surface. The dependence of the morphological change on the area fraction of L o is consistent with existing experimental results. This provides us with a clear understanding of the origin of the line tension energy, which has been used to understand these morphological changes in three-component membranes. In addition to these two circular and stripe domains, a raft-like domain and budding domain are also observed, and the several corresponding phase diagrams are obtained.
Modelling Creativity: Identifying Key Components through a Corpus-Based Approach.
Jordanous, Anna; Keller, Bill
2016-01-01
Creativity is a complex, multi-faceted concept encompassing a variety of related aspects, abilities, properties and behaviours. If we wish to study creativity scientifically, then a tractable and well-articulated model of creativity is required. Such a model would be of great value to researchers investigating the nature of creativity and in particular, those concerned with the evaluation of creative practice. This paper describes a unique approach to developing a suitable model of how creative behaviour emerges that is based on the words people use to describe the concept. Using techniques from the field of statistical natural language processing, we identify a collection of fourteen key components of creativity through an analysis of a corpus of academic papers on the topic. Words are identified which appear significantly often in connection with discussions of the concept. Using a measure of lexical similarity to help cluster these words, a number of distinct themes emerge, which collectively contribute to a comprehensive and multi-perspective model of creativity. The components provide an ontology of creativity: a set of building blocks which can be used to model creative practice in a variety of domains. The components have been employed in two case studies to evaluate the creativity of computational systems and have proven useful in articulating achievements of this work and directions for further research.
Steady-State Plant Model to Predict Hydroden Levels in Power Plant Components
Energy Technology Data Exchange (ETDEWEB)
Glatzmaier, Greg C.; Cable, Robert; Newmarker, Marc
2017-06-27
The National Renewable Energy Laboratory (NREL) and Acciona Energy North America developed a full-plant steady-state computational model that estimates levels of hydrogen in parabolic trough power plant components. The model estimated dissolved hydrogen concentrations in the circulating heat transfer fluid (HTF), and corresponding partial pressures within each component. Additionally for collector field receivers, the model estimated hydrogen pressure in the receiver annuli. The model was developed to estimate long-term equilibrium hydrogen levels in power plant components, and to predict the benefit of hydrogen mitigation strategies for commercial power plants. Specifically, the model predicted reductions in hydrogen levels within the circulating HTF that result from purging hydrogen from the power plant expansion tanks at a specified target rate. Our model predicted hydrogen partial pressures from 8.3 mbar to 9.6 mbar in the power plant components when no mitigation treatment was employed at the expansion tanks. Hydrogen pressures in the receiver annuli were 8.3 to 8.4 mbar. When hydrogen partial pressure was reduced to 0.001 mbar in the expansion tanks, hydrogen pressures in the receiver annuli fell to a range of 0.001 mbar to 0.02 mbar. When hydrogen partial pressure was reduced to 0.3 mbar in the expansion tanks, hydrogen pressures in the receiver annuli fell to a range of 0.25 mbar to 0.28 mbar. Our results show that controlling hydrogen partial pressure in the expansion tanks allows us to reduce and maintain hydrogen pressures in the receiver annuli to any practical level.
Kia, Mohammad; Wright, Timothy M; Cross, Michael B; Mayman, David J; Pearle, Andrew D; Sculco, Peter K; Westrich, Geoffrey H; Imhauser, Carl W
2018-01-01
The correct amount of external rotation of the femoral component during TKA is controversial because the resulting changes in biomechanical knee function associated with varying degrees of femoral component rotation are not well understood. We addressed this question using a computational model, which allowed us to isolate the biomechanical impact of geometric factors including bony shapes, location of ligament insertions, and implant size across three different knees after posterior-stabilized (PS) TKA. Using a computational model of the tibiofemoral joint, we asked: (1) Does external rotation unload the medial collateral ligament (MCL) and what is the effect on lateral collateral ligament tension? (2) How does external rotation alter tibiofemoral contact loads and kinematics? (3) Does 3° external rotation relative to the posterior condylar axis align the component to the surgical transepicondylar axis (sTEA) and what anatomic factors of the femoral condyle explain variations in maximum MCL tension among knees? We incorporated a PS TKA into a previously developed computational knee model applied to three neutrally aligned, nonarthritic, male cadaveric knees. The computational knee model was previously shown to corroborate coupled motions and ligament loading patterns of the native knee through a range of flexion. Implant geometries were virtually installed using hip-to-ankle CT scans through measured resection and anterior referencing surgical techniques. Collateral ligament properties were standardized across each knee model by defining stiffness and slack lengths based on the healthy population. The femoral component was externally rotated from 0° to 9° relative to the posterior condylar axis in 3° increments. At each increment, the knee was flexed under 500 N compression from 0° to 90° simulating an intraoperative examination. The computational model predicted collateral ligament forces, compartmental contact forces, and tibiofemoral internal/external and
Fitting a Bivariate Measurement Error Model for Episodically Consumed Dietary Components
Zhang, Saijuan
2011-01-06
There has been great public health interest in estimating usual, i.e., long-term average, intake of episodically consumed dietary components that are not consumed daily by everyone, e.g., fish, red meat and whole grains. Short-term measurements of episodically consumed dietary components have zero-inflated skewed distributions. So-called two-part models have been developed for such data in order to correct for measurement error due to within-person variation and to estimate the distribution of usual intake of the dietary component in the univariate case. However, there is arguably much greater public health interest in the usual intake of an episodically consumed dietary component adjusted for energy (caloric) intake, e.g., ounces of whole grains per 1000 kilo-calories, which reflects usual dietary composition and adjusts for different total amounts of caloric intake. Because of this public health interest, it is important to have models to fit such data, and it is important that the model-fitting methods can be applied to all episodically consumed dietary components.We have recently developed a nonlinear mixed effects model (Kipnis, et al., 2010), and have fit it by maximum likelihood using nonlinear mixed effects programs and methodology (the SAS NLMIXED procedure). Maximum likelihood fitting of such a nonlinear mixed model is generally slow because of 3-dimensional adaptive Gaussian quadrature, and there are times when the programs either fail to converge or converge to models with a singular covariance matrix. For these reasons, we develop a Monte-Carlo (MCMC) computation of fitting this model, which allows for both frequentist and Bayesian inference. There are technical challenges to developing this solution because one of the covariance matrices in the model is patterned. Our main application is to the National Institutes of Health (NIH)-AARP Diet and Health Study, where we illustrate our methods for modeling the energy-adjusted usual intake of fish and whole
Fitting a Bivariate Measurement Error Model for Episodically Consumed Dietary Components
Zhang, Saijuan; Krebs-Smith, Susan M.; Midthune, Douglas; Perez, Adriana; Buckman, Dennis W.; Kipnis, Victor; Freedman, Laurence S.; Dodd, Kevin W.; Carroll, Raymond J
2011-01-01
There has been great public health interest in estimating usual, i.e., long-term average, intake of episodically consumed dietary components that are not consumed daily by everyone, e.g., fish, red meat and whole grains. Short-term measurements of episodically consumed dietary components have zero-inflated skewed distributions. So-called two-part models have been developed for such data in order to correct for measurement error due to within-person variation and to estimate the distribution of usual intake of the dietary component in the univariate case. However, there is arguably much greater public health interest in the usual intake of an episodically consumed dietary component adjusted for energy (caloric) intake, e.g., ounces of whole grains per 1000 kilo-calories, which reflects usual dietary composition and adjusts for different total amounts of caloric intake. Because of this public health interest, it is important to have models to fit such data, and it is important that the model-fitting methods can be applied to all episodically consumed dietary components.We have recently developed a nonlinear mixed effects model (Kipnis, et al., 2010), and have fit it by maximum likelihood using nonlinear mixed effects programs and methodology (the SAS NLMIXED procedure). Maximum likelihood fitting of such a nonlinear mixed model is generally slow because of 3-dimensional adaptive Gaussian quadrature, and there are times when the programs either fail to converge or converge to models with a singular covariance matrix. For these reasons, we develop a Monte-Carlo (MCMC) computation of fitting this model, which allows for both frequentist and Bayesian inference. There are technical challenges to developing this solution because one of the covariance matrices in the model is patterned. Our main application is to the National Institutes of Health (NIH)-AARP Diet and Health Study, where we illustrate our methods for modeling the energy-adjusted usual intake of fish and whole
Invasion percolation of single component, multiphase fluids with lattice Boltzmann models
International Nuclear Information System (INIS)
Sukop, M.C.; Or, Dani
2003-01-01
Application of the lattice Boltzmann method (LBM) to invasion percolation of single component multiphase fluids in porous media offers an opportunity for more realistic modeling of the configurations and dynamics of liquid/vapor and liquid/solid interfaces. The complex geometry of connected paths in standard invasion percolation models arises solely from the spatial arrangement of simple elements on a lattice. In reality, fluid interfaces and connectivity in porous media are naturally controlled by the details of the pore geometry, its dynamic interaction with the fluid, and the ambient fluid potential. The multiphase LBM approach admits realistic pore geometry derived from imaging techniques and incorporation of realistic hydrodynamics into invasion percolation models
Modelling with Relational Calculus of Object and Component Systems - rCOS
DEFF Research Database (Denmark)
Chen, Zhenbang; Hannousse, Abdel Hakim; Hung, Dang Van
2008-01-01
This chapter presents a formalization of functional and behavioural requirements, and a refinement of requirements to a design for CoCoME using the Relational Calculus of Object and Component Systems (rCOS). We give a model of requirements based on an abstraction of the use cases described...... in Chapter 3.2. Then the refinement calculus of rCOS is used to derive design models corresponding to the top level designs of Chapter 3.4. We demonstrate how rCOS supports modelling different views and their relationships of the system and the separation of concerns in the development....
Detailed measurements and modelling of thermo active components using a room size test facility
DEFF Research Database (Denmark)
Weitzmann, Peter; Svendsen, Svend
2005-01-01
measurements in an office sized test facility with thermo active ceiling and floor as well as modelling of similar conditions in a computer program designed for analysis of building integrated heating and cooling systems. A method for characterizing the cooling capacity of thermo active components is described...... typically within 1-2K of the measured results. The simulation model, whose room model splits up the radiative and convective heat transfer between room and surfaces, can also be used to predict the dynamical conditions, where especially the temperature rise during the day is important for designing...
Amran, T. G.; Janitra Yose, Mindy
2018-03-01
As the free trade Asean Economic Community (AEC) causes the tougher competition, it is important that Indonesia’s automotive industry have high competitiveness as well. A model of logistics performance measurement was designed as an evaluation tool for automotive component companies to improve their logistics performance in order to compete in AEC. The design of logistics performance measurement model was based on the Logistics Scorecard perspectives, divided into two stages: identifying the logistics business strategy to get the KPI and arranging the model. 23 KPI was obtained. The measurement result can be taken into consideration of determining policies to improve the performance logistics competitiveness.
Gomes, Marcos José Timbó Lima; Cunto, Flávio; da Silva, Alan Ricardo
2017-09-01
Generalized Linear Models (GLM) with negative binomial distribution for errors, have been widely used to estimate safety at the level of transportation planning. The limited ability of this technique to take spatial effects into account can be overcome through the use of local models from spatial regression techniques, such as Geographically Weighted Poisson Regression (GWPR). Although GWPR is a system that deals with spatial dependency and heterogeneity and has already been used in some road safety studies at the planning level, it fails to account for the possible overdispersion that can be found in the observations on road-traffic crashes. Two approaches were adopted for the Geographically Weighted Negative Binomial Regression (GWNBR) model to allow discrete data to be modeled in a non-stationary form and to take note of the overdispersion of the data: the first examines the constant overdispersion for all the traffic zones and the second includes the variable for each spatial unit. This research conducts a comparative analysis between non-spatial global crash prediction models and spatial local GWPR and GWNBR at the level of traffic zones in Fortaleza/Brazil. A geographic database of 126 traffic zones was compiled from the available data on exposure, network characteristics, socioeconomic factors and land use. The models were calibrated by using the frequency of injury crashes as a dependent variable and the results showed that GWPR and GWNBR achieved a better performance than GLM for the average residuals and likelihood as well as reducing the spatial autocorrelation of the residuals, and the GWNBR model was more able to capture the spatial heterogeneity of the crash frequency. Copyright © 2017 Elsevier Ltd. All rights reserved.
Guo, Jinyun; Mu, Dapeng; Liu, Xin; Yan, Haoming; Dai, Honglei
2014-08-01
The Level-2 monthly GRACE gravity field models issued by Center for Space Research (CSR), GeoForschungs Zentrum (GFZ), and Jet Propulsion Laboratory (JPL) are treated as observations used to extract the equivalent water height (EWH) with the robust independent component analysis (RICA). The smoothing radii of 300, 400, and 500 km are tested, respectively, in the Gaussian smoothing kernel function to reduce the observation Gaussianity. Three independent components are obtained by RICA in the spatial domain; the first component matches the geophysical signal, and the other two match the north-south strip and the other noises. The first mode is used to estimate EWHs of CSR, JPL, and GFZ, and compared with the classical empirical decorrelation method (EDM). The EWH STDs for 12 months in 2010 extracted by RICA and EDM show the obvious fluctuation. The results indicate that the sharp EWH changes in some areas have an important global effect, like in Amazon, Mekong, and Zambezi basins.
Vestergaard-Poulsen, Peter; Hansen, Brian; Ostergaard, Leif; Jakobsen, Rikke
2007-09-01
To understand the diffusion attenuated MR signal from normal and ischemic brain tissue in order to extract structural and physiological information using mathematical modeling, taking into account the transverse relaxation rates in gray matter. We fit our diffusion model to the diffusion-weighted MR signal obtained from cortical gray matter in healthy subjects. Our model includes variable volume fractions, intracellular restriction effects, and exchange between compartments in addition to individual diffusion coefficients and transverse relaxation rates for each compartment. A global optimum was found from a wide range of parameter permutations using cluster computing. We also present simulations of cell swelling and changes of exchange rate and intracellular diffusion as possible cellular mechanisms in ischemia. Our model estimates an extracellular volume fraction of 0.19 in accordance with the accepted value from histology. The absolute apparent diffusion coefficient obtained from the model was similar to that of experiments. The model and the experimental results indicate significant differences in diffusion and transverse relaxation between the tissue compartments and slow water exchange. Our model reproduces the signal changes observed in ischemia via physiologically credible mechanisms. Our modeling suggests that transverse relaxation has a profound influence on the diffusion attenuated MR signal. Our simulations indicate cell swelling as the primary cause of the diffusion changes seen in the acute phase of brain ischemia. (c) 2007 Wiley-Liss, Inc.
The ORC method. Effective modelling of thermal performance of multilayer building components
Energy Technology Data Exchange (ETDEWEB)
Akander, Jan
2000-02-01
The ORC Method (Optimised RC-networks) provides a means of modelling one- or multidimensional heat transfer in building components, in this context within building simulation environments. The methodology is shown, primarily applied to heat transfer in multilayer building components. For multilayer building components, the analytical thermal performance is known, given layer thickness and material properties. The aim of the ORC Method is to optimise the values of the thermal resistances and heat capacities of an RC-model such as to give model performance a good agreement with the analytical performance, for a wide range of frequencies. The optimisation procedure is made in the frequency domain, where the over-all deviation between model and analytical frequency response, in terms of admittance and dynamic transmittance, is minimised. It is shown that ORC's are effective in terms of accuracy and computational time in comparison to finite difference models when used in building simulations, in this case with IDA/ICE. An ORC configuration of five mass nodes has been found to model building components in Nordic countries well, within the application of thermal comfort and energy requirement simulations. Simple RC-networks, such as the surface heat capacity and the simple R-C-configuration are not appropriate for detailed building simulation. However, these can be used as basis for defining the effective heat capacity of a building component. An approximate method is suggested on how to determine the effective heat capacity without the use of complex numbers. This entity can be calculated on basis of layer thickness and material properties with the help of two time constants. The approximate method can give inaccuracies corresponding to 20%. In-situ measurements have been carried out in an experimental building with the purpose of establishing the effective heat capacity of external building components that are subjected to normal thermal conditions. The auxiliary
Weight loss and brown adipose tissue reduction in rat model of sleep apnea
Directory of Open Access Journals (Sweden)
de Oliveira Patricia G
2008-07-01
Full Text Available Abstract Background - Obesity is related to obstructive sleep apnea-hypopnea syndrome (OSAHS, but its roles in OSAHS as cause or consequence are not fully clarified. Isocapnic intermittent hypoxia (IIH is a model of OSAHS. We verified the effect of IIH on body weight and brown adipose tissue (BAT of Wistar rats. Methods Nine-month-old male breeders Wistar rats of two groups were studied: 8 rats submitted to IIH and 5 control rats submitted to sham IIH. The rats were weighed at the baseline and at the end of three weeks, after being placed in the IIH apparatus seven days per week, eight hours a day, in the lights on period, simulating an apnea index of 30/hour. After experimental period, the animals were weighed and measured as well as the BAT, abdominal, perirenal, and epididymal fat, the heart, and the gastrocnemius muscle. Results Body weight of the hypoxia group decreased 17 ± 7 grams, significantly different from the variation observed in the control group (p = 0,001. The BAT was 15% lighter in the hypoxia group and reached marginally the alpha error probability (p = 0.054. Conclusion Our preliminary results justify a larger study for a longer time in order to confirm the effect of isocapnic intermittent hypoxia on body weight and BAT.
International Nuclear Information System (INIS)
Shin, Ho Cheol; Park, Moon Ghu; You, Skin
2006-01-01
Recently, many on-line approaches to instrument channel surveillance (drift monitoring and fault detection) have been reported worldwide. On-line monitoring (OLM) method evaluates instrument channel performance by assessing its consistency with other plant indications through parametric or non-parametric models. The heart of an OLM system is the model giving an estimate of the true process parameter value against individual measurements. This model gives process parameter estimate calculated as a function of other plant measurements which can be used to identify small sensor drifts that would require the sensor to be manually calibrated or replaced. This paper describes an improvement of auto associative kernel regression (AAKR) by introducing a correlation coefficient weighting on kernel distances. The prediction performance of the developed method is compared with conventional auto-associative kernel regression
Directory of Open Access Journals (Sweden)
Fidel Ernesto Castro Morales
2016-03-01
Full Text Available Abstract Objectives: to propose the use of a Bayesian hierarchical model to study the allometric scaling of the fetoplacental weight ratio, including possible confounders. Methods: data from 26 singleton pregnancies with gestational age at birth between 37 and 42 weeks were analyzed. The placentas were collected immediately after delivery and stored under refrigeration until the time of analysis, which occurred within up to 12 hours. Maternal data were collected from medical records. A Bayesian hierarchical model was proposed and Markov chain Monte Carlo simulation methods were used to obtain samples from distribution a posteriori. Results: the model developed showed a reasonable fit, even allowing for the incorporation of variables and a priori information on the parameters used. Conclusions: new variables can be added to the modelfrom the available code, allowing many possibilities for data analysis and indicating the potential for use in research on the subject.
Directory of Open Access Journals (Sweden)
Kennedy Kwami Edem Kukuia
2018-01-01
Full Text Available Trichilia monadelpha is a common medicinal plant used traditionally in treating central nervous system conditions such as epilepsy, depression, pain, and psychosis. In this study, the antidepressant-like effect of crude extracts of the stem bark of T. monadelpha was investigated using two classical murine models, forced swimming test (FST and tail suspension test (TST. The extracts, petroleum ether, ethyl acetate, and hydroethanolic extracts (30–300 mg/kg, p.o., standard drug (imipramine; fluoxetine, 3–30 mg/kg, p.o., and saline (vehicle were given to mice one hour prior to the acute study. In a separate experiment the components (flavonoids, saponins, alkaloids, tannins, and terpenoids; 30–300 mg/kg, p.o. from the most efficacious extract fraction were screened to ascertain which components possessed the antidepressant effect. All the extracts and components significantly induced a decline in immobility in the FST and TST, indicative of an antidepressant-like activity. The extracts and some components showed increase in swimming and climbing in the FST as well as a significant enhancement in swinging and/or curling scores in the TST, suggesting a possible involvement of monoaminergic and/or opioidergic activity. This study reveals the antidepressant-like potential of the stem bark extracts and components of T. monadelpha.
Superfluid drag in the two-component Bose-Hubbard model
Sellin, Karl; Babaev, Egor
2018-03-01
In multicomponent superfluids and superconductors, co- and counterflows of components have, in general, different properties. A. F. Andreev and E. P. Bashkin [Sov. Phys. JETP 42, 164 (1975)] discussed, in the context of He3/He4 superfluid mixtures, that interparticle interactions produce a dissipationless drag. The drag can be understood as a superflow of one component induced by phase gradients of the other component. Importantly, the drag can be both positive (entrainment) and negative (counterflow). The effect is known to have crucial importance for many properties of diverse physical systems ranging from the dynamics of neutron stars and rotational responses of Bose mixtures of ultracold atoms to magnetic responses of multicomponent superconductors. Although substantial literature exists that includes the drag interaction phenomenologically, only a few regimes are covered by quantitative studies of the microscopic origin of the drag and its dependence on microscopic parameters. Here we study the microscopic origin and strength of the drag interaction in a quantum system of two-component bosons on a lattice with short-range interaction. By performing quantum Monte Carlo simulations of a two-component Bose-Hubbard model we obtain dependencies of the drag strength on the boson-boson interactions and properties of the optical lattice. Of particular interest are the strongly correlated regimes where the ratio of coflow and counterflow superfluid stiffnesses can diverge, corresponding to the case of saturated drag.
International Nuclear Information System (INIS)
Kim, Bo Gyung; Kang, Hyun Gook; Kim, Hee Eun; Lee, Seung Jun; Seong, Poong Hyun
2013-01-01
Highlights: • Integrated fault coverage is introduced for reflecting characteristics of fault-tolerant techniques in the reliability model of digital protection system in NPPs. • The integrated fault coverage considers the process of fault-tolerant techniques from detection to fail-safe generation process. • With integrated fault coverage, the unavailability of repairable component of DPS can be estimated. • The new developed reliability model can reveal the effects of fault-tolerant techniques explicitly for risk analysis. • The reliability model makes it possible to confirm changes of unavailability according to variation of diverse factors. - Abstract: With the improvement of digital technologies, digital protection system (DPS) has more multiple sophisticated fault-tolerant techniques (FTTs), in order to increase fault detection and to help the system safely perform the required functions in spite of the possible presence of faults. Fault detection coverage is vital factor of FTT in reliability. However, the fault detection coverage is insufficient to reflect the effects of various FTTs in reliability model. To reflect characteristics of FTTs in the reliability model, integrated fault coverage is introduced. The integrated fault coverage considers the process of FTT from detection to fail-safe generation process. A model has been developed to estimate the unavailability of repairable component of DPS using the integrated fault coverage. The new developed model can quantify unavailability according to a diversity of conditions. Sensitivity studies are performed to ascertain important variables which affect the integrated fault coverage and unavailability
McIntyre, N.; Keir, G.
2014-12-01
Water supply systems typically encompass components of both natural systems (e.g. catchment runoff, aquifer interception) and engineered systems (e.g. process equipment, water storages and transfers). Many physical processes of varying spatial and temporal scales are contained within these hybrid systems models. The need to aggregate and simplify system components has been recognised for reasons of parsimony and comprehensibility; and the use of probabilistic methods for modelling water-related risks also prompts the need to seek computationally efficient up-scaled conceptualisations. How to manage the up-scaling errors in such hybrid systems models has not been well-explored, compared to research in the hydrological process domain. Particular challenges include the non-linearity introduced by decision thresholds and non-linear relations between water use, water quality, and discharge strategies. Using a case study of a mining region, we explore the nature of up-scaling errors in water use, water quality and discharge, and we illustrate an approach to identification of a scale-adjusted model including an error model. Ways forward for efficient modelling of such complex, hybrid systems are discussed, including interactions with human, energy and carbon systems models.
Directory of Open Access Journals (Sweden)
Hiekata Takashi
2006-01-01
Full Text Available A new two-stage blind source separation (BSS method for convolutive mixtures of speech is proposed, in which a single-input multiple-output (SIMO-model-based independent component analysis (ICA and a new SIMO-model-based binary masking are combined. SIMO-model-based ICA enables us to separate the mixed signals, not into monaural source signals but into SIMO-model-based signals from independent sources in their original form at the microphones. Thus, the separated signals of SIMO-model-based ICA can maintain the spatial qualities of each sound source. Owing to this attractive property, our novel SIMO-model-based binary masking can be applied to efficiently remove the residual interference components after SIMO-model-based ICA. The experimental results reveal that the separation performance can be considerably improved by the proposed method compared with that achieved by conventional BSS methods. In addition, the real-time implementation of the proposed BSS is illustrated.
User's guide to the weather model: a component of the western spruce budworm modeling system.
W. P. Kemp; N. L. Crookston; P. W. Thomas
1989-01-01
A stochastic model useful in simulating daily maximum and minimum temperature and precipitation developed by Bruhn and others has been adapted for use in the western spruce budworm modeling system. This document describes how to use the weather model and illustrates some aspects of its behavior.
Resolution and Probabilistic Models of Components in CryoEM Maps of Mature P22 Bacteriophage
Pintilie, Grigore; Chen, Dong-Hua; Haase-Pettingell, Cameron A.; King, Jonathan A.; Chiu, Wah
2016-01-01
CryoEM continues to produce density maps of larger and more complex assemblies with multiple protein components of mixed symmetries. Resolution is not always uniform throughout a cryoEM map, and it can be useful to estimate the resolution in specific molecular components of a large assembly. In this study, we present procedures to 1) estimate the resolution in subcomponents by gold-standard Fourier shell correlation (FSC); 2) validate modeling procedures, particularly at medium resolutions, which can include loop modeling and flexible fitting; and 3) build probabilistic models that combine high-accuracy priors (such as crystallographic structures) with medium-resolution cryoEM densities. As an example, we apply these methods to new cryoEM maps of the mature bacteriophage P22, reconstructed without imposing icosahedral symmetry. Resolution estimates based on gold-standard FSC show the highest resolution in the coat region (7.6 Å), whereas other components are at slightly lower resolutions: portal (9.2 Å), hub (8.5 Å), tailspike (10.9 Å), and needle (10.5 Å). These differences are indicative of inherent structural heterogeneity and/or reconstruction accuracy in different subcomponents of the map. Probabilistic models for these subcomponents provide new insights, to our knowledge, and structural information when taking into account uncertainty given the limitations of the observed density. PMID:26743049
Machine learning of frustrated classical spin models. I. Principal component analysis
Wang, Ce; Zhai, Hui
2017-10-01
This work aims at determining whether artificial intelligence can recognize a phase transition without prior human knowledge. If this were successful, it could be applied to, for instance, analyzing data from the quantum simulation of unsolved physical models. Toward this goal, we first need to apply the machine learning algorithm to well-understood models and see whether the outputs are consistent with our prior knowledge, which serves as the benchmark for this approach. In this work, we feed the computer data generated by the classical Monte Carlo simulation for the X Y model in frustrated triangular and union jack lattices, which has two order parameters and exhibits two phase transitions. We show that the outputs of the principal component analysis agree very well with our understanding of different orders in different phases, and the temperature dependences of the major components detect the nature and the locations of the phase transitions. Our work offers promise for using machine learning techniques to study sophisticated statistical models, and our results can be further improved by using principal component analysis with kernel tricks and the neural network method.
Russ, Christine Runyan II
1998-01-01
Although research describing relationships between psychosocial factors and various eating patterns is growing, a model which explains the mechanisms through which these factors may operate is lacking. A model to explain overeating patterns among normal weight college females was developed and tested. The model contained the following variables: global adjustment, eating and weight cognitions, emotional eating, and self-efficacy. Three hundred ninety-o...
The multi-component model of working memory: explorations in experimental cognitive psychology.
Repovs, G; Baddeley, A
2006-04-28
There are a number of ways one can hope to describe and explain cognitive abilities, each of them contributing a unique and valuable perspective. Cognitive psychology tries to develop and test functional accounts of cognitive systems that explain the capacities and properties of cognitive abilities as revealed by empirical data gathered by a range of behavioral experimental paradigms. Much of the research in the cognitive psychology of working memory has been strongly influenced by the multi-component model of working memory [Baddeley AD, Hitch GJ (1974) Working memory. In: Recent advances in learning and motivation, Vol. 8 (Bower GA, ed), pp 47-90. New York: Academic Press; Baddeley AD (1986) Working memory. Oxford, UK: Clarendon Press; Baddeley A. Working memory: Thought and action. Oxford: Oxford University Press, in press]. By expanding the notion of a passive short-term memory to an active system that provides the basis for complex cognitive abilities, the model has opened up numerous questions and new lines of research. In this paper we present the current revision of the multi-component model that encompasses a central executive, two unimodal storage systems: a phonological loop and a visuospatial sketchpad, and a further component, a multimodal store capable of integrating information into unitary episodic representations, termed episodic buffer. We review recent empirical data within experimental cognitive psychology that has shaped the development of the multicomponent model and the understanding of the capacities and properties of working memory. Research based largely on dual-task experimental designs and on neuropsychological evidence has yielded valuable information about the fractionation of working memory into independent stores and processes, the nature of representations in individual stores, the mechanisms of their maintenance and manipulation, the way the components of working memory relate to each other, and the role they play in other
Directory of Open Access Journals (Sweden)
Samy Ismail Elmahdy
2016-01-01
Full Text Available In the current study, Penang Island, which is one of the several mountainous areas in Malaysia that is often subjected to landslide hazard, was chosen for further investigation. A multi-criteria Evaluation and the spatial probability weighted approach and model builder was applied to map and analyse landslides in Penang Island. A set of automated algorithms was used to construct new essential geological and morphometric thematic maps from remote sensing data. The maps were ranked using the weighted probability spatial model based on their contribution to the landslide hazard. Results obtained showed that sites at an elevation of 100–300 m, with steep slopes of 10°–37° and slope direction (aspect in the E and SE directions were areas of very high and high probability for the landslide occurrence; the total areas were 21.393 km2 (11.84% and 58.690 km2 (32.48%, respectively. The obtained map was verified by comparing variogram models of the mapped and the occurred landslide locations and showed a strong correlation with the locations of occurred landslides, indicating that the proposed method can successfully predict the unpredictable landslide hazard. The method is time and cost effective and can be used as a reference for geological and geotechnical engineers.
Using ELM-based weighted probabilistic model in the classification of synchronous EEG BCI.
Tan, Ping; Tan, Guan-Zheng; Cai, Zi-Xing; Sa, Wei-Ping; Zou, Yi-Qun
2017-01-01
Extreme learning machine (ELM) is an effective machine learning technique with simple theory and fast implementation, which has gained increasing interest from various research fields recently. A new method that combines ELM with probabilistic model method is proposed in this paper to classify the electroencephalography (EEG) signals in synchronous brain-computer interface (BCI) system. In the proposed method, the softmax function is used to convert the ELM output to classification probability. The Chernoff error bound, deduced from the Bayesian probabilistic model in the training process, is adopted as the weight to take the discriminant process. Since the proposed method makes use of the knowledge from all preceding training datasets, its discriminating performance improves accumulatively. In the test experiments based on the datasets from BCI competitions, the proposed method is compared with other classification methods, including the linear discriminant analysis, support vector machine, ELM and weighted probabilistic model methods. For comparison, the mutual information, classification accuracy and information transfer rate are considered as the evaluation indicators for these classifiers. The results demonstrate that our method shows competitive performance against other methods.
Thøgersen-Ntoumani, Cecilie; Ntoumanis, Nikos
2009-01-01
This study used self-determination theory (Deci, E.L., & Ryan, R.M. (2000). The 'what' and 'why' of goal pursuits: Human needs and the self-determination of behavior. Psychological Inquiry, 11, 227-268.) to examine predictors of body image concerns and unhealthy weight control behaviours in a sample of 350 Greek adolescent girls. A process model was tested which proposed that perceptions of parental autonomy support and two life goals (health and image) would predict adolescents' degree of sa...
International Nuclear Information System (INIS)
Haddad, Khaled; Egodawatta, Prasanna; Rahman, Ataur; Goonetilleke, Ashantha
2013-01-01
Reliable pollutant build-up prediction plays a critical role in the accuracy of urban stormwater quality modelling outcomes. However, water quality data collection is resource demanding compared to streamflow data monitoring, where a greater quantity of data is generally available. Consequently, available water quality datasets span only relatively short time scales unlike water quantity data. Therefore, the ability to take due consideration of the variability associated with pollutant processes and natural phenomena is constrained. This in turn gives rise to uncertainty in the modelling outcomes as research has shown that pollutant loadings on catchment surfaces and rainfall within an area can vary considerably over space and time scales. Therefore, the assessment of model uncertainty is an essential element of informed decision making in urban stormwater management. This paper presents the application of a range of regression approaches such as ordinary least squares regression, weighted least squares regression and Bayesian weighted least squares regression for the estimation of uncertainty associated with pollutant build-up prediction using limited datasets. The study outcomes confirmed that the use of ordinary least squares regression with fixed model inputs and limited observational data may not provide realistic estimates. The stochastic nature of the dependent and independent variables need to be taken into consideration in pollutant build-up prediction. It was found that the use of the Bayesian approach along with the Monte Carlo simulation technique provides a powerful tool, which attempts to make the best use of the available knowledge in prediction and thereby presents a practical solution to counteract the limitations which are otherwise imposed on water quality modelling. - Highlights: ► Water quality data spans short time scales leading to significant model uncertainty. ► Assessment of uncertainty essential for informed decision making in water
Directory of Open Access Journals (Sweden)
Ackermann Marko
2015-01-01
Full Text Available The ratio of tangential to total pushrim force, the so-called Fraction Effective Force (FEF, has been used to evaluate wheelchair propulsion efficiency based on the fact that only the tangential component of the force on the pushrim contributes to actual wheelchair propulsion. Experimental studies, however, consistently show low FEF values and recent experimental as well as modelling investigations have conclusively shown that a more tangential pushrim force direction can lead to a decrease and not increase in propulsion efficiency. This study aims at quantifying the contributions of active, inertial and gravitational forces to the normal pushrim component. In order to achieve this goal, an inverse dynamics-based framework is proposed to estimate individual contributions to the pushrim forces using a model of the wheelchair-user system. The results show that the radial pushrim force component arise to a great extent due to purely mechanical effects, including inertial and gravitational forces. These results corroborate previous findings according to which radial pushrim force components are not necessarily a result of inefficient propulsion strategies or hand-rim friction requirements. This study proposes a novel framework to quantify the individual contributions of active, inertial and gravitational forces to pushrim forces during wheelchair propulsion.
Reliability prediction system based on the failure rate model for electronic components
International Nuclear Information System (INIS)
Lee, Seung Woo; Lee, Hwa Ki
2008-01-01
Although many methodologies for predicting the reliability of electronic components have been developed, their reliability might be subjective according to a particular set of circumstances, and therefore it is not easy to quantify their reliability. Among the reliability prediction methods are the statistical analysis based method, the similarity analysis method based on an external failure rate database, and the method based on the physics-of-failure model. In this study, we developed a system by which the reliability of electronic components can be predicted by creating a system for the statistical analysis method of predicting reliability most easily. The failure rate models that were applied are MILHDBK- 217F N2, PRISM, and Telcordia (Bellcore), and these were compared with the general purpose system in order to validate the effectiveness of the developed system. Being able to predict the reliability of electronic components from the stage of design, the system that we have developed is expected to contribute to enhancing the reliability of electronic components
Kou, Jisheng; Sun, Shuyu
2016-01-01
A general diffuse interface model with a realistic equation of state (e.g. Peng-Robinson equation of state) is proposed to describe the multi-component two-phase fluid flow based on the principles of the NVT-based framework which is a latest
Phinney, David Martin; Frelka, John C; Heldman, Dennis Ray
2017-01-01
Prediction of temperature-dependent thermophysical properties (thermal conductivity, density, specific heat, and thermal diffusivity) is an important component of process design for food manufacturing. Current models for prediction of thermophysical properties of foods are based on the composition, specifically, fat, carbohydrate, protein, fiber, water, and ash contents, all of which change with temperature. The objectives of this investigation were to reevaluate and improve the prediction expressions for thermophysical properties. Previously published data were analyzed over the temperature range from 10 to 150 °C. These data were analyzed to create a series of relationships between the thermophysical properties and temperature for each food component, as well as to identify the dependence of the thermophysical properties on more specific structural properties of the fats, carbohydrates, and proteins. Results from this investigation revealed that the relationships between the thermophysical properties of the major constituents of foods and temperature can be statistically described by linear expressions, in contrast to the current polynomial models. Links between variability in thermophysical properties and structural properties were observed. Relationships for several thermophysical properties based on more specific constituents have been identified. Distinctions between simple sugars (fructose, glucose, and lactose) and complex carbohydrates (starch, pectin, and cellulose) have been proposed. The relationships between the thermophysical properties and proteins revealed a potential correlation with the molecular weight of the protein. The significance of relating variability in constituent thermophysical properties with structural properties--such as molecular mass--could significantly improve composition-based prediction models and, consequently, the effectiveness of process design. © 2016 Institute of Food Technologists®.
NCWin — A Component Object Model (COM) for processing and visualizing NetCDF data
Liu, Jinxun; Chen, J.M.; Price, D.T.; Liu, S.
2005-01-01
NetCDF (Network Common Data Form) is a data sharing protocol and library that is commonly used in large-scale atmospheric and environmental data archiving and modeling. The NetCDF tool described here, named NCWin and coded with Borland C + + Builder, was built as a standard executable as well as a COM (component object model) for the Microsoft Windows environment. COM is a powerful technology that enhances the reuse of applications (as components). Environmental model developers from different modeling environments, such as Python, JAVA, VISUAL FORTRAN, VISUAL BASIC, VISUAL C + +, and DELPHI, can reuse NCWin in their models to read, write and visualize NetCDF data. Some Windows applications, such as ArcGIS and Microsoft PowerPoint, can also call NCWin within the application. NCWin has three major components: 1) The data conversion part is designed to convert binary raw data to and from NetCDF data. It can process six data types (unsigned char, signed char, short, int, float, double) and three spatial data formats (BIP, BIL, BSQ); 2) The visualization part is designed for displaying grid map series (playing forward or backward) with simple map legend, and displaying temporal trend curves for data on individual map pixels; and 3) The modeling interface is designed for environmental model development by which a set of integrated NetCDF functions is provided for processing NetCDF data. To demonstrate that the NCWin can easily extend the functions of some current GIS software and the Office applications, examples of calling NCWin within ArcGIS and MS PowerPoint for showing NetCDF map animations are given.
Jadhav, J. R.; Mantha, S. S.; Rane, S. B.
2015-06-01
The demands for automobiles increased drastically in last two and half decades in India. Many global automobile manufacturers and Tier-1 suppliers have already set up research, development and manufacturing facilities in India. The Indian automotive component industry started implementing Lean practices to fulfill the demand of these customers. United Nations Industrial Development Organization (UNIDO) has taken proactive approach in association with Automotive Component Manufacturers Association of India (ACMA) and the Government of India to assist Indian SMEs in various clusters since 1999 to make them globally competitive. The primary objectives of this research are to study the UNIDO-ACMA Model as well as ISM Model of Lean implementation and validate the ISM Model by comparing with UNIDO-ACMA Model. It also aims at presenting a roadmap for Lean implementation in Indian automotive component industry. This paper is based on secondary data which include the research articles, web articles, doctoral thesis, survey reports and books on automotive industry in the field of Lean, JIT and ISM. ISM Model for Lean practice bundles was developed by authors in consultation with Lean practitioners. The UNIDO-ACMA Model has six stages whereas ISM Model has eight phases for Lean implementation. The ISM-based Lean implementation model is validated through high degree of similarity with UNIDO-ACMA Model. The major contribution of this paper is the proposed ISM Model for sustainable Lean implementation. The ISM-based Lean implementation framework presents greater insight of implementation process at more microlevel as compared to UNIDO-ACMA Model.
Directory of Open Access Journals (Sweden)
Teeraphan Laomettachit
Full Text Available To understand the molecular mechanisms that regulate cell cycle progression in eukaryotes, a variety of mathematical modeling approaches have been employed, ranging from Boolean networks and differential equations to stochastic simulations. Each approach has its own characteristic strengths and weaknesses. In this paper, we propose a "standard component" modeling strategy that combines advantageous features of Boolean networks, differential equations and stochastic simulations in a framework that acknowledges the typical sorts of reactions found in protein regulatory networks. Applying this strategy to a comprehensive mechanism of the budding yeast cell cycle, we illustrate the potential value of standard component modeling. The deterministic version of our model reproduces the phenotypic properties of wild-type cells and of 125 mutant strains. The stochastic version of our model reproduces the cell-to-cell variability of wild-type cells and the partial viability of the CLB2-dbΔ clb5Δ mutant strain. Our simulations show that mathematical modeling with "standard components" can capture in quantitative detail many essential properties of cell cycle control in budding yeast.
General model for Pc-based simulation of PWR and BWR plant components
Energy Technology Data Exchange (ETDEWEB)
Ratemi, W M; Abomustafa, A M [Faculty of enginnering, alfateh univerity Tripoli, (Libyan Arab Jamahiriya)
1995-10-01
In this paper, we present a basic mathematical model derived from physical principles to suit the simulation of PWR-components such as pressurizer, intact steam generator, ruptured steam generator, and the reactor component of a BWR-plant. In our development, we produced an NMMS-package for nuclear modular modelling simulation. Such package is installed on a personal computer and it is designed to be user friendly through color graphics windows interfacing. The package works under three environments, namely, pre-processor, simulation, and post-processor. Our analysis of results using cross graphing technique for steam generator tube rupture (SGTR) accident, yielded a new proposal for on-line monitoring of control strategy of SGTR-accident for nuclear or conventional power plant. 4 figs.
Kuss, DJ; Shorter, GW; Van Rooij, AJ; Van de Mheen, D; Griffiths, MD
2014-01-01
There is growing concern over excessive and sometimes problematic Internet use. Drawing upon the framework of the components model of addiction (Griffiths, 2005), Internet addiction appears as behavioural addiction characterised by the following symptoms: salience, withdrawal, tolerance, mood modification, relapse and conflict. A number of factors have been associated with an increased risk for Internet addiction, including personality traits. The overall aim of this study was to establish th...
Evaluation of low dose ionizing radiation effect on some blood components in animal model
El-Shanshoury, H.; El-Shanshoury, G.; Abaza, A.
2016-01-01
Exposure to ionizing radiation is known to have lethal effects in blood cells. It is predicted that an individual may spend days, weeks or even months in a radiation field without becoming alarmed. The study aimed to discuss the evaluation of low dose ionizing radiation (IR) effect on some blood components in animal model. Hematological parameters were determined for 110 animal rats (divided into 8 groups) pre- and post-irradiation. An attempt to explain the blood changes resulting from both ...
Some results of model calculations of the solar S-component radio emission
International Nuclear Information System (INIS)
Krueger, A.; Hildebrandt, J.
1985-01-01
Numerical calculations of special characteristics of the solar S-component microwave radiation are presented on the basis of recent sunspot and plage models. Quantitative results are discussed and can be used for the plasma diagnostics of solar active regions by comparisons with observations with high spatial and spectral resolution. The possibility of generalized applications to magnetic stars and stellar activity is briefly noted. (author)
Fatemeh PooraghaRoodbarde; Siavash Talepasand; Issac Rahimian Boogar
2017-01-01
Objective: The present study aimed at examining the effect of multidimensional motivation interventions based on Martin's model on cognitive and behavioral components of motivation.Methods: The research design was prospective with pretest, posttest, and follow-up, and 2 experimental groups. In this study, 90 students (45 participants in the experimental group and 45 in the control group) constituted the sample of the study, and they were selected by available sampling method. Motivation inter...
Energy Technology Data Exchange (ETDEWEB)
Bernacki, Bruce E.
2012-10-05
This brief report contains a critique of two key components of FiveFocal's cost model for glass compression molding of chalcogenide lenses for infrared applications. Molding preforms and mold technology have the greatest influence on the ultimate cost of the product and help determine the volumes needed to select glass molding over conventional single-point diamond turning or grinding and polishing. This brief report highlights key areas of both technologies with recommendations for further study.
Directory of Open Access Journals (Sweden)
Christian NZENGUE PEGNET
2011-07-01
Full Text Available The recent financial turmoil has clearly highlighted the potential role of financial factors on amplification of macroeconomic developments and stressed the importance of analyzing the relationship between banks’ balance sheets and economic activity. This paper assesses the impact of the bank capital channel in the transmission of schocks in Europe on the basis of bank's balance sheet data. The empirical analysis is carried out through a Principal Component Analysis and in a Vector Error Correction Model.