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The aim of this paper is (i)to study breast cancer growth by mean of a mathematical model describing cell population dynamics during cancer growth, and (ii)to use this model to reproduce and explain experimental data. We started from a linear model describing cancer subpopulations evolution based on the Cancer Stem Cell (CSC) theory, and we added feedback mechanisms from the cell populations to mimic...
Panel data from the 27 provinces in China are analyzed using special kinds of regression models to ascertain the main factors influencing medical expenditures. The findings show that economic growth, government investment in health, supply of health care services and medical technology progress are the key factors affecting health care costs. The faster the economy develops and the more the government...
Accurate reporting of results is extremely important. This is especially relevant for energy and environmental data associated with government driven incentives and disincentives (such as tax benefits for energy efficiency or mandatory GHG emission reporting). Any abnormalities in the data can significantly affect reported results. It is therefore critically important to properly evaluate all data...
This paper deals with the simulation and analysis of large-scale migrations by proposing an improved version of Agent-Based Social Simulation model. The model includes hierarchical layers that reflects regional quality. We extract migrant samples from the PUMS database using logistic regression, and use random forest as the core algorithm to find linear solutions for the relationships among several...
Axial compressor systems are predisposed to instability near their optimum operating point. Instabilities include surge or stall, leading to severe consequences to the operational health and integrity of compressor system. The Moore-Greitzer (MG) model has been commonly recognized as a standard when characterizing the dynamics within an axial compressor and is advantageous for the development of a...
We develop an abstract approximation and convergence framework for the estimation of random parameters in infinite dimensional dynamical systems governed by regularly dissipative operators in a Gelfand triple setting. Our results are motivated by a problem involving the development of a data analysis system for a transdermal alcohol biosensor. Our approach combines some recent results for random abstract...
An effective novel algorithm to reduce the dimensionality of labeled proportional data is presented which uses an optimal linear projection to project the data into a low-dimensional space. Assuming that each class of the projected data is generated by a mixture of Dirichlet distributions, KL-divergence is used as a dissimilarity measure to maximize the mutual information of projected classes, thus...
This paper presents the modelling of a water level system using neurofuzzy. The modelling stage is necessary to design of a control law of a system. In this study, a water level system is modelled using neurofuzzy system: the first called ANFIS and the second a Takagi-Sugeno (TS) tuned by particle swarm optimisation PSO. The two models constructed are evaluated by applying a proportional integral...
Gray-Box Models which combine a phenomenological model with a black box tool are useful for determining the values of not well known parameters of the model. In this work an indirect strategy for training these gray box models using least-square support vector machine and genetic algorithms is presented. The gray box model was tested in a Continuous Stirred Tank Reactor process with good results (Index...
For design fair public service system using the weighted p-median problem exist some approaches which use reduction coefficients. These coefficients allow to take probability of failure/occupation of service center into account and to make the location-allocation model more realistic. If the nearest service center is occupied by some other user, the demand is served from the second nearest service...
In 2015 an outbreak of Middle East Respiratory Syndrome (MERS) has occurred in South Korea, which has been known to be the second biggest outbreak of MERS so far. In this paper we study an estimation of the basic reproduction number of the coronavirus (CoV) of MERS based on the reported data from the MERS spread in South Korea. To this end we employ a mathematical model described by a set of ordinary...
The study applied the Theory of Planned Behavior (TPB) model to predict high school students' intentions to use bioenergy in India. TPB is one of the most widely cited and applied theories in explaining human behaviors in environmental matters. In the TPB model, intention to act is primarily determined by three psychological constructs: Attitude towards the behavior, Subjective Norm (SN) and Perceived...
Aiming at producing more realistic and informed agent-based simulations of social systems, one often need to build realistic synthetic populations. Apart of this synthetic population generation, the question of generating realistic social networks is an important phase. We examined the articles published in the Journal of Artificial Societies and Social Simulation (JASSS) in between 1998 and 2015...
In this paper, we construct, fit, and validate a hidden Markov model for predicting variability and uncertainty in generation from distributed (PV) systems. The model is unique in that it: 1) predicts metrics that are directly related to operational reserves, 2) accounts for the effects of stochastic volatility and geographic autocorrelation, and 3) conditions on latent variables referred to as “volatility...
A fundamental open question that has been studied by sociologists since the 70s and recently started being addressed by the computer-science community is the understanding of the role that influence and selection play in shaping the evolution of socio-cultural systems. Quantifying these forces in real settings is still a big challenge, especially in the large-scale case in which the entire social...
In this paper, we proposes a new mathematical model for evaluating a given anonymized dataset that needs to be reidentified. Many anonymization algorithms have been proposed in the area called privacy-preserving data publishing (PPDP), but, no anonymization algorithms are suitable for all scenarios because many factors are involved. In order to address the issues of anonymization, we propose a new...
Even though the agent-based simulation modelling has become a standard tool in transport research, current implementations still treat travellers as passive data structures, updated synchronously at infrequent, predefined points in time, thus failing to cover within-the-day decision making and negotiation necessary for cooperative behaviour in a dynamic transport system. Leveraging the fully agent-based...
Recently, in (Hatzikos and Owens, 2002b) and (Hatzikos and Owens, 2002a) it was explored whether or not Genetic Algorithm (GAs) based approach can be used in the context of norm-optimal Iterative Learning Control (ILC). It turned out the answer was positive for both linear and nonlinear plant models. However, this approach is still immature in the sense that it can produce very ‘noisy’ intermediate...
This paper is concerned with dynamical population models obtained from short and long-term changes in size and age composition due to demographic processes such as births, deaths, migration, etc. Both deterministic and stochastic models are presented. The parameters which are embedded in the models may be either unavailable or noisy, therefore system identification methods are invoked to estimate...
Data Caching on mobile clients is widely seen as an effective solution to increase data availability. A population is a “group of plant, group of people, and group of animal etc.” all is same species that live together and reproduce. Here a group of cached data items at clients in mobile ad hoc network called Group of Cached Data items (GCD). In this paper, the growth rates of cached data items at...
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