3,973 research outputs found
Fuzzy Adaptive Tuning of a Particle Swarm Optimization Algorithm for Variable-Strength Combinatorial Test Suite Generation
Combinatorial interaction testing is an important software testing technique
that has seen lots of recent interest. It can reduce the number of test cases
needed by considering interactions between combinations of input parameters.
Empirical evidence shows that it effectively detects faults, in particular, for
highly configurable software systems. In real-world software testing, the input
variables may vary in how strongly they interact, variable strength
combinatorial interaction testing (VS-CIT) can exploit this for higher
effectiveness. The generation of variable strength test suites is a
non-deterministic polynomial-time (NP) hard computational problem
\cite{BestounKamalFuzzy2017}. Research has shown that stochastic
population-based algorithms such as particle swarm optimization (PSO) can be
efficient compared to alternatives for VS-CIT problems. Nevertheless, they
require detailed control for the exploitation and exploration trade-off to
avoid premature convergence (i.e. being trapped in local optima) as well as to
enhance the solution diversity. Here, we present a new variant of PSO based on
Mamdani fuzzy inference system
\cite{Camastra2015,TSAKIRIDIS2017257,KHOSRAVANIAN2016280}, to permit adaptive
selection of its global and local search operations. We detail the design of
this combined algorithm and evaluate it through experiments on multiple
synthetic and benchmark problems. We conclude that fuzzy adaptive selection of
global and local search operations is, at least, feasible as it performs only
second-best to a discrete variant of PSO, called DPSO. Concerning obtaining the
best mean test suite size, the fuzzy adaptation even outperforms DPSO
occasionally. We discuss the reasons behind this performance and outline
relevant areas of future work.Comment: 21 page
VoroCrust: Voronoi Meshing Without Clipping
Polyhedral meshes are increasingly becoming an attractive option with
particular advantages over traditional meshes for certain applications. What
has been missing is a robust polyhedral meshing algorithm that can handle broad
classes of domains exhibiting arbitrarily curved boundaries and sharp features.
In addition, the power of primal-dual mesh pairs, exemplified by
Voronoi-Delaunay meshes, has been recognized as an important ingredient in
numerous formulations. The VoroCrust algorithm is the first provably-correct
algorithm for conforming polyhedral Voronoi meshing for non-convex and
non-manifold domains with guarantees on the quality of both surface and volume
elements. A robust refinement process estimates a suitable sizing field that
enables the careful placement of Voronoi seeds across the surface circumventing
the need for clipping and avoiding its many drawbacks. The algorithm has the
flexibility of filling the interior by either structured or random samples,
while preserving all sharp features in the output mesh. We demonstrate the
capabilities of the algorithm on a variety of models and compare against
state-of-the-art polyhedral meshing methods based on clipped Voronoi cells
establishing the clear advantage of VoroCrust output.Comment: 18 pages (including appendix), 18 figures. Version without compressed
images available on https://www.dropbox.com/s/qc6sot1gaujundy/VoroCrust.pdf.
Supplemental materials available on
https://www.dropbox.com/s/6p72h1e2ivw6kj3/VoroCrust_supplemental_materials.pd
Wireless Sensors Network Application: A Decentralized Approach for Traffic Control and Management
Prevalence of cesarean section on demand in Assiut Governorate, Egypt
Background: The current study aims to evaluate the prevalence of CS on demand in Women's health hospital, Assiut University and Abnob Central Hospital in Assiut Governorate, Egypt.Methods: A cross sectional study conducted in Assiut Women Health Hospital and Abnob central hospital from January 2017 to December 2017. The total number of cesarean section done was 180 cases and the number of CS on demand was 64 (35.6%). The demographic data were collected by one of the study investigators. Women were asked about the causes of requesting CS before surgery.Results: The study group was 64 women with age ranging from 18-40 years old, 40 primipara and 24 multipara. Of those 24 women, 21 of them previously delivered vaginally and only 3 women delivered by emergency CS. Twenty- six women had a history of previous abortion. Fear of pain was the main cause for CS on demand in the whole study participants (57.8%). In primipara, the main cause for requesting CS is fear of pain in 62.5% of participants followed by fear on the baby in 45 % of women. On the other hand, in multipara, the main cause for CS on demand was bad history of previous experience (60%) followed by fear of pain in 50% of cases. There was statistical significant difference between both groups in only two causes; fear of pelvic floor injuries (50% in multipara vs. 20% in primipara, p=0.02) and bad history of previous experience (60% in multipara vs. 0% in primipara, p=0.001). Other causes were not statistically different.Conclusions: The incidence of cesarean sections performed on request without medical indications is rising. The reasons for this are not only for perceived medical benefit, but also due to social, cultural, and psychological factors
Spontaneous triplet pregnancy with twin fetuses papyraeci: a rare case report and review of the literature
A fetal death in a multiple pregnancy with one or more normally surviving fetus is unusual. Fetus papyraceous (FP) is a rare obstetric complication in multiple gestations. It is defined as retention of a mummified parchment like remains of a dead fetus in multiple pregnancy associated with a viable twin. It is important to reassure the patient of the normal outcome expected in most of the cases. Herein, we report a rare case of twin FP in a spontaneous triplet pregnancy with a literature review of maternal and neonatal outcomes and management of similar cases
On the Rothe-Galerkin spectral discretisation for a class of variable fractional-order nonlinear wave equations
In this contribution, a wave equation with a time-dependent variable-order
fractional damping term and a nonlinear source is considered. Avoiding the
circumstances of expressing the nonlinear variable-order fractional wave
equations via closed-form expressions in terms of special functions, we
investigate the existence and uniqueness of this problem with Rothe's method.
First, the weak formulation for the considered wave problem is proposed. Then,
the uniqueness of a solution is established by employing Gr\"onwall's lemma.
The Rothe scheme's basic idea is to use Rothe functions to extend the solutions
on single-time steps over the entire time frame. Inspired by that, we next
introduce a uniform mesh time-discrete scheme based on a discrete convolution
approximation in the backward sense. By applying some reasonable assumptions to
the given data, we can predict a priori estimates for the time-discrete
solution. Employing these estimates side by side with Rothe functions leads to
proof of the solution's existence over the whole time interval. Finally, the
full discretisation of the problem is introduced by invoking Galerkin spectral
techniques in the spatial direction, and numerical examples are given
Alikhanov Legendre–Galerkin spectral method for the coupled nonlinear time-space fractional Ginzburg–Landau complex system
A finite difference/Galerkin spectral discretization for the temporal and spatial fractional coupled Ginzburg-Landau system is proposed and analyzed. The Alikhanov L2-1 sigma difference formula is utilized to discretize the time Caputo fractional derivative, while the Legendre-Galerkin spectral approximation is used to approximate the Riesz spatial fractional operator. The scheme is shown efficiently applicable with spectral accuracy in space and second-order in time. A discrete form of the fractional Gronwall inequality is applied to establish the error estimates of the approximate solution based on the discrete energy estimates technique. The key aspects of the implementation of the numerical continuation are complemented with some numerical experiments to confirm the theoretical claims
Maximum Likelihood Inference for Univariate Delay Differential Equation Models with Multiple Delays
This article presents statistical inference methodology based on maximum likelihoods for delay differential equation models in the univariate setting. Maximum likelihood inference is obtained for single and multiple unknown delay parameters as well as other parameters of interest that govern the trajectories of the delay differential equation models. The maximum likelihood estimator is obtained based on adaptive grid and Newton-Raphson algorithms. Our methodology estimates correctly the delay parameters as well as other unknown parameters (such as the initial starting values) of the dynamical system based on simulation data. We also develop methodology to compute the information matrix and confidence intervals for all unknown parameters based on the likelihood inferential framework. We present three illustrative examples related to biological systems. The computations have been carried out with help of mathematical software: MATLAB® 8.0 R2014b
Association between aortic sclerosis and coronary artery disease
Background: Although there is a recognized link between cardiovascular hazards and coronary artery disease (CAD), it is still unknown whether aortic sclerosis and CAD are linked.Objective: This study aimed to check whether if there is a link between aortic sclerosis and the existence and severity of coronary artery disease .Patients and methods: 204 individuals were enrolled in the study, transthoracic echocardiographic, and coronary angiography were done. Aortic leaflets were tested for the amount of thickness in the short axis view. The involvement of coronary arteries represented by the gensini score and the association between aortic valve sclerosis score and the degree and severity of coronary affection was investigated using the Gensini score.Results: The individuals were divided into 2 groups grounded on the severity of aortic valve sclerosis. Group A (GP A) included patients with aortic valve sclerosis (AVS) ≥ 2 and group B (GP B) included patients with AVS < 2. In GP A, the right coronary cusp was the most afflicted one, whereas the LAD was the most affected in coronaries. The degree and severity of CAD were more significant in GP A, as evidenced by a higher Gensini score value of 39.27 versus 28.84 in GP B.Conclusion: AVS has been found to be correlated with the presence and severity of CAD and could be used as a potential surrogate marker for the illness
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