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This study investigates near-shore circulation and wave characteristics applied to a case-study site in Monterey Bay, California. We integrate physics-based models to resolve wave conditions (based on inputs from a global wave model, wind data from an operational weather platform, and predictions from a regional flow model) together with a linear machine learning algorithm that combines forecasts...
Genome-wide association studies have discovered many biologically important associations of genes with phenotypes. Typically, genome-wide association analyses formally test the association of each genetic feature (SNP, CNV, etc) with the phenotype of interest and summarize the results with multiplicity-adjusted p-values. However, very small p-values only provide evidence against the null hypothesis...
We consider the problem of causal structure learning from data with missing values, assumed to be drawn from a Gaussian copula model. First, we extend the 'Rank PC' algorithm, designed for Gaussian copula models with purely continuous data (so-called nonparanormal models), to incomplete data by applying rank correlation to pairwise complete observations and replacing the sample size with an effective...
With the rapid rise of various e-commerce and social network platforms, users are generating large amounts of heterogeneous behavior data, such as purchasehistory, adding-to-favorite, adding-to-cart and click activities, and this kind of user behavior data is usually binary, only reflecting a user's action or inaction (i.e., implicit feedback data). Tensor factorization is a promising means of modeling...
For modeling of distribution of electromagnetic waves taking into account a land relief Simulink model founded on formation of a surface of the electromagnetic field on large territories is offered.
Given a collection of basic customer demographics (e.g., age and gender) andtheir behavioral data (e.g., item purchase histories), how can we predictsensitive demographics (e.g., income and occupation) that not every customermakes available?This demographics prediction problem is modeled as a classification task inwhich a customer's sensitive demographic y is predicted from his featurevector x. So...
Model-based software estimation uses algorithms and past project data to make predictions for new projects. This paper presents a comparative assessment of four modeling approaches, including the original COCOMO, COCOMO calibration, k-Nearest Neighbors, and a combination of COCOMO calibration and k-Nearest Neighbors. Our results indicate that using kNN to select the nearest projects and calibrating...
This paper considers a problem for modeling mathematically waveform of some Electrocardiogram (ECG) which is the process of measuring and recording the electrical activity of the heart over a period of time. Such a modeling is done by using the smoothing Bézier-Bernstein curves. A concise representation for desigining the optimal curves with high precision is derived, which has the additional merit...
The use of information technology in the study of human behavior is a subject of great scientific interest. Cultural and personality aspects are factors that influence how people interact with one another in a crowd. This paper presents a methodology to detect cultural characteristics of crowds in video sequences. Based on filmed sequences, pedestrians are detected, tracked and characterized. Such...
This paper presents a rapidly and lower neural networks to treat those waste water index that is difficult to be measured. Model called soft sensor is composited two parts: one is used to estimate the principal linear output, the other one is used to adjust estimated error to obtain better accuracy. Selection of features that effects greatly computation scale and predict accuracy is discussed also...
The paper provides the mathematical model describing the movement of different kinds of avalanche snow mass and its interaction with obstacles based on the modified method of particle dynamics. Further, the authors introduce their algorithm to calculate avalanche impact on buildings and structures; this algorithm underlies a computer program that allows you to set the basic parameters of a building,...
This paper proposes modelling ranked load curves using algebraic polynomials. Starting from the assumption of some characteristic parameters of load profiles: maximum power, minimum power and the energy consumption in a time period, characteristic coefficients of different types of algebraic polynomials such as: linear, parabolic and third-order are obtained. The modelling of real load profile has...
Multi-agent simulations are useful for exploring collective patterns of individual behavior in social, biological, economic, network, and physical systems. However, there is no provenance support for multi-agent models (MAMs) in a distributed setting. To this end, we introduce ProvMASS, a novel approach to capture provenance of MAMs in a distributed memory by combining inter-process identification,...
Total number of failures of a software system can help practitioners to have a better understanding of the software quality. In this paper, we propose a model to predict the total number of software failures in a software system by analyzing the failure data from testing using models based on Zipf's law together with the information on code coverage. Failure data and code coverage are combined in...
System identification is a powerful technique for building accurate mathematical models of complex systems from experimental input/output data. Mathematical models that predict the behavior of the column are highly useful to improve the working conditions of distillation columns and increase throughput or lower energy consumption. This paper models a pseudo binary distillation column using a black-box...
The paper describes a procedure to identify the dq inductances of an electric machine, which is here applied to a dual three-phase PM machine. A hybrid simulation/ experimental approach is utilised. A power converter is used to force step current transients and the responses are recorded. These are then fed into a combined parameter estimation/ simulation model, which yields at the output the machine...
The present work presents the design, construction and use of a discrete event simulator for student flow in academic study periods, as a tool to improve the allocation of resources and to make decisions for the reduction of student dropout rates and optimization of the career completion time.
Questions of computer realization for new class — three levels of adaptive manufacturing control system were considered. They were marked with special features that allow to form demands to methods of process description. It was shown that suggested homogeneous method suits mathematical description perfectly. The method consists of static linear programming task and differential equations. Local methods...
Permanent magnet synchronous machines with high torque density, which is a frequent requirement for high level applications, are characterized by saturation and cross-saturation effects which need to be taken into account in simulation models used for the purpose of control system design or for optimized design of the machine geometry. In this paper three simulation models of permanent magnet machines...
This paper proposes an estimation method for the latent variable Rasch model based on the method of least squares which allows a continuous data set using. The research suggests the application of original approaches within the method for the solution of some applied problems. The authors explain how to use it for task assignment and work organization, decision-making under certainty and the securities...
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