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Agent-based models have been used to capture and analyze the essential behaviors of combat units although the number of agents used has been fairly low. We experiment with a microscopically detailed agent model in which over 20,000 soldiers are represented individually (one agent per soldier) in a simulation of the Battle of Isandlwana in 1879. We describe how a rule based model can be specified for...
Selecting predicitve gene pools from thousands of gene expression values is one of the main tasks in microarray data analysis. For this purpose multivariate techniques have proven much better, in terms of predicitve value and biological relevance, than univariate techniques as they are able to capture relevant relationships and interactions between genes. An additional goal for gene-expression profiling...
Virtual platform is renowned for architecture exploration and validation, early software development, hardware/software co-development of Electronic System Level (ESL) System-on-Chip (SoC) design process. In Virtual Platform System (VPS), multi-level abstraction models should be properly adopted to achieve higher simulation performance while maintaining the platform design efforts as minimal as possible...
Gene synthesis is a key step to convert digitally predicted proteins to functional proteins. However, it is a relatively expensive and labor-intensive process. About 30–50% of the synthesized proteins are not soluble, thereby further reduces the efficacy of gene synthesis as a method for protein function characterization. Solubility prediction from primary protein sequences holds the promise to dramatically...
In recent years there has been renewed interest in the renewable power generation from ocean energy worldwide as well as in South Africa. South Africa's energy market is overwhelmingly fossil fuel based. Currently, the country has been experiencing shortages. This paper deals specifically with the assessment of the deep sea marine current energy contained in the Agulhas current located off South Africa's...
Smart cities combine technology and human resources to improve the quality of life and reduce expenditures. Ensuring the safety of city residents remains one of the open problems, as standard budgetary investments fail to decrease crime levels. This work takes steps toward implementing smart, safe cities, by combining the use of personal mobile devices and social networks to make users aware of the...
In order to get the excellent accuracy for price forecast in the steel market, the adaptive Radial Basis Function (RBF) Neural Network (NN) model, Back Propagation (BP) NN model and Sliding Window (SW) model are utilized to forecast the price of the steel products in this paper. Eight steel products, which extracted from Shanghai Baoshan steel market of China at January, 2011 to December 2011, are...
In this paper, we present different combined clustering methods and we evaluate their performances and their results on a dataset with ground truth. This dataset, built from several sources, contains a scientific social network in which textual data is associated to each vertex and the classes are known. Indeed, while the clustering task is widely studied both in graph clustering and in non supervised...
This research made an early investigation on firm failure prediction (FFP) in hospitality industry of China using support vector machine (SVM) and classical statistical models, and an early comparison on difference of identified significant variables in FFPs for developed and developing countries. The findings indicate that: (a) working capital turnover, equity turnover, ratio of owners' equity, equity...
Accuracy assessment is essential after the classification of remote sensed image. For it is expensive for field survey of every sample, how to select an effective sample that is the unbiased estimation of the population which defined as the all the pixels on the classified map is a very important problem. The classification errors are not randomly distributed on the classified map but distributed...
Crop plantation map is a fundamental data in the research and production of agriculture. Remote sensing is a fast, economic and irreplaceable tool in this research and application area. By the analysis of the penology of winter wheat and summer maize using the data from agro-meteorological station and the characteristics analysis of the 8-day time-series MODIS NDVI of winter wheat and summer maize,...
Due to the establishment of Poyang Lake National Nature Reserve, we pay more attention to water pollution, so it is important to improve early warning mechanisms. My article will analysis the main source of Poyang Lake water quality parameters, establish gray GM(1,1)model, through the river into the lake water quality data to predict the water quality of Poyang lake area .Inspect after get results...
The development of business failure prediction system to prevent the significant loss of social costs caused by the companies' unexpected bankruptcy is a popular investigation issue. Because of the constraint on the statistic assumptions, the forecasting models established by traditional statistic methods have some limits in its identity. Therefore, in recent years various algorithms imitating of...
Uncertainties originating from the behaviour of target species and modelling approaches affect predictive accuracy and information retrieved, which can thus influence the applicability and reliability of a model. This paper aimed to assess the effects of aggregation functions for computing composite habitat preference on the prediction of species distributions and habitat preference evaluation using...
In this paper, four new forecasting models ¨C univariate LS-SVM model and three hybrid models of ARIMA and LS-SVM models are introduced for wind power output forecasting. Historical data of 78 wind farms are used to compare and evaluate the performance of the best models. Empirical analysis indicates that the proposed univariate LS-SVM model and hybrid models can not significantly outperform linear...
Variable selection is the problem of choosing the subset of explanatory variables for a regression or classification model such that the resulting model is best according to some criterion. Here we consider the use of population-based incremental learning (PBIL) to select the variables for a linear regression model to predict a quantitative trait in living organisms. The data here is simulated to...
The recognition of humans and their activities from video sequences is currently a very active area of research because of its applications in video surveillance, design of realistic entertainment systems, multimedia communications, and medical diagnosis. This paper presents an automatic gait recognition system that recognizes a person by the way he/she walks. The gait signature is obtained based...
The oscillometric method still challenges accurate blood pressure measurement due to its difficulty compensating for pregnancy, age, hypo-, and hypertension. Global sensitivity analysis methods were used to develop a simplified model that is useful for directing and optimizing the design of an automated oscillometric blood pressure measurement system. The most influential biological and design parameters...
Although atlas-based methods simplify the segmentation process by making it more automated, such methods are often very sensitive to the computationally expensive image registration step. Also, existing methods based on a parametric deformation model may fail when the transformation between the atlas and target images can not be properly described with this model. This paper presents a novel and efficient...
The structure of vegetation canopies largely controls the functioning of ecosystems. There is a substantial demand for spatial information on canopy structure. This paper examines the retrieval of an important forest structure property, leaf area index (LAI) from spectro-directional satellite observations (PROBA/CHRIS) using a forest reflectance model and a look-up table approach. Retrieved parameter...
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