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1
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On the development of SCILAB compatible software for the analysis and control of repetitive processes

100%
Ładowski Ł., Cichy B., Gałkowski K., Rogers E.
International Journal of Applied Mathematics and Computer Science
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2008
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tom 18
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nr 3
377-387
EN
In this paper further results on the development of a S CILAB compatible software package for the analysis and control of repetitive processes is described. The core of the package consists of a simulation tool which enables the user to inspect the response of a given example to an input, design a control law for stability and/or performance, and also simulate the response of a controlled process to a specified reference signal.
2
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Generation of realizations of Gaussian random functions on digital computers

100%
Huk J.
Mathematica Applicanda
|
1977
|
tom 5
|
nr 9
PL
Artykuł nie zawiera streszczenia
EN
This is an extensive survey of methods for simulation of Gaussian random functions and fields on digital computers. The methods are classified as follows: generation of Gaussian random sequences with a given covariance function and spectral density function of a special type, and by discrete Fourier transform of uniform random numbers; generation of stationary and non-stationary Gaussian processes by filtration; and generation of stationary Gaussian processes, Gaussian fields and vector-valued fields by summing harmonics. (MR0488619)
3
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Using a vision cognitive algorithm to schedule virtual machines

100%
Zhao J., Mhedheb Y., Tao J., Jrad F., Liu Q., Streit A.
International Journal of Applied Mathematics and Computer Science
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2014
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tom 24
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nr 3
535-550
EN
Scheduling virtual machines is a major research topic for cloud computing, because it directly influences the performance, the operation cost and the quality of services. A large cloud center is normally equipped with several hundred thousand physical machines. The mission of the scheduler is to select the best one to host a virtual machine. This is an NPhard global optimization problem with grand challenges for researchers. This work studies the Virtual Machine (VM) scheduling problem on the cloud. Our primary concern with VM scheduling is the energy consumption, because the largest part of a cloud center operation cost goes to the kilowatts used. We designed a scheduling algorithm that allocates an incoming virtual machine instance on the host machine, which results in the lowest energy consumption of the entire system. More specifically, we developed a new algorithm, called vision cognition, to solve the global optimization problem. This algorithm is inspired by the observation of how human eyes see directly the smallest/largest item without comparing them pairwisely. We theoretically proved that the algorithm works correctly and converges fast. Practically, we validated the novel algorithm, together with the scheduling concept, using a simulation approach. The adopted cloud simulator models different cloud infrastructures with various properties and detailed runtime information that can usually not be acquired from real clouds. The experimental results demonstrate the benefit of our approach in terms of reducing the cloud center energy consumption.
4
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Coupled analytical and numerical approach to uncovering new regulatory mechanisms of intracellular processes

100%
Śmieja J.
International Journal of Applied Mathematics and Computer Science
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2010
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tom 20
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nr 4
781-788
EN
The paper deals with the analysis of signaling pathways aimed at uncovering new regulatory processes regulating cell responses. First, general issues of comparing simulation and experimental data are discussed, and various aspects of data normalization are covered. Then, a model of a particular signaling pathway, induced by Interferon-β, is briefly introduced. It serves as an example illustrating how mathematical modeling can be used for inferring the structure of a regulatory system governing the dynamics of intracellular processes. In this pathway, experimental results suggest that a hitherto unknown process is responsible for a decrease in the levels of one of the important molecules used in the pathway. Then, equilibrium points of the model are analyzed, allowing the rejection of all but one explanation of the phenomena observed experimentally. Numerical simulations confirm that the model can mimic the dynamics of the processes in the pathway under consideration. Finally, some remarks about the applicability of the method based on an analysis of equilibrium points are made.
5
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Pairs of successes in Bernoulli trials and a new n-estimator for the binomial distribution

88%
Kühne W., Neumann P., Stoyan D., Stoyan H.
Applicationes Mathematicae
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1993-1995
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tom 22
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nr 3
331-337
EN
The problem of estimating the number, n, of trials, given a sequence of k independent success counts obtained by replicating the n-trial experiment is reconsidered in this paper. In contrast to existing methods it is assumed here that more information than usual is available: not only the numbers of successes are given but also the number of pairs of consecutive successes. This assumption is realistic in a class of problems of spatial statistics. There typically k = 1, in which case the classical estimators cannot be used. The quality of the new estimator is analysed and, for k > 1, compared with that of a classical n-estimator. The theoretical basis for this is the distribution of the number of success pairs in Bernoulli trials, which can be determined by an elementary Markov chain argument.
6
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A robust controller design method and stability analysis of an underactuated underwater vehicle

88%
Chin C. S., Lau M. W. S., Low E., Gerald Gim Lee seet
International Journal of Applied Mathematics and Computer Science
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2006
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tom 16
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nr 3
345-356
EN
The problem of designing a stabilizing feedback controller for an underactuated system is a challenging one since a nonlinear system is not stabilizable by a smooth static state feedback law. A necessary condition for the asymptotical stabilization of an underactuated vehicle to a single equilibrium is that its gravitational field has nonzero elements corresponding to unactuated dynamics. However, global asymptotical stability (GAS) cannot be guaranteed. In this paper, a robust proportional-integral-derivative (PID) controller on actuated dynamics is proposed and unactuated dynamics are shown to be global exponentially bounded by the Sordalen lemma. This gives a necessary and sufficient condition to guarantee the global asymptotic stability (GAS) of the URV system. The proposed method is first adopted on a remotely-operated vehicle RRC ROV II designed by the Robotic Research Centre in the Nanyang Technological University (NTU). Through the simulation using the ROV Design and Analysis toolbox (RDA) written at the NTU in the MATLAB/SIMULINK environment, the RRC ROV II is robust against parameter perturbations.
7
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Methods for estimating vehicle queues at a marine terminal: a computational comparison

88%
Chen G., Yang Z.-Z.
International Journal of Applied Mathematics and Computer Science
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2014
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tom 24
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nr 3
611-619
EN
A long queue of vehicles at the gate of a marine terminal is a common traffic phenomenon in a port-city, which sometimes causes problems in urban traffic. In order to be able to solve this issue, we firstly need accurate models to estimate such a vehicle queue length. In this paper, we compare the existing methods in a case study, and evaluate their advantages and disadvantages. Particularly, we develop a simulation-based regression model, using the micro traffic simulation software PARAMIC. In simulation, it is found that the queue transient process follows a natural logarithm curve. Then, based on these curves, we develop a queue length estimation model. In the numerical experiment, the proposed model exhibits better estimation accuracy than the other existing methods.
8
Content available remote

Application of a Java-based framework to parallel simulation of large-scale systems

88%
Niewiadomska-Szynkiewicz E., Żmuda M., Żmuda M.
International Journal of Applied Mathematics and Computer Science
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2003
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tom 13
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nr 4
537-547
EN
Large-scale systems, such as computer and telecommunication networks, complex control systems and many others, operate in inherently parallel environments. It follows that there are many opportunities to admit parallelism into both the algorithm of control implementation and simulation of the system operation considered. The paper addresses issues associated with the application of parallel discrete event simulation (PDES). We discuss the PDES terminology and methodology. Particular attention is paid to the software environment CSA SPV (em Complex Systems Analysis and Simulation-Parallel Version), which provides a framework for simulation experiments performed on parallel computers. CSA SPV was applied to investigate several real-life problems. The case studies are presented for both computer and water networks.
9
Content available remote

Stochastic models of progression of cancer andtheir use in controlling cancer-related mortality

75%
Kimmel M., Gorlova O. Y.
International Journal of Applied Mathematics and Computer Science
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2003
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tom 13
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nr 3
279-287
EN
A construction of a realistic statistical model of lung cancer risk and progression is proposed. The essential elements of the model are genetic and behavioral determinants of susceptibility, progression of the disease from precursor lesions through early (localized) tumors to disseminated disease, detection by various modalities, and medical intervention. Using model estimates as a foundation, mortality reduction caused by early-detection and intervention programs can be predicted under different scenarios. Genetic indicators of susceptibility to lung cancer should be used to define the highest-risk subgroups of the high-risk behavior population (smokers). The calibration and validation of the model requires applying our techniques to a variety of data sets available, including public registry data of the SEER type, data from the NCI lung cancer chest X-ray screening studies, and the recent ELCAP CT-scan screening study.
10
Content available remote

Nonparametric estimation of simplified vine copula models: comparison of methods

75%
Nagler T., Schellhase C., Czado C.
Dependence Modeling
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2017
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tom 5
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nr 1
99-120
EN
In the last decade, simplified vine copula models have been an active area of research. They build a high dimensional probability density from the product of marginals densities and bivariate copula densities. Besides parametric models, several approaches to nonparametric estimation of vine copulas have been proposed. In this article, we extend these approaches and compare them in an extensive simulation study and a real data application. We identify several factors driving the relative performance of the estimators. The most important one is the strength of dependence. No method was found to be uniformly better than all others. Overall, the kernel estimators performed best, but do worse than penalized B-spline estimators when there is weak dependence and no tail dependence.
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