Development of New Approach in Reliability Analysis for Excellent Predictive Quality of the Approximation Using Adaptive Kriging

2019 ◽  
Vol 44 ◽  
pp. 44-63
Author(s):  
Nassim Kernou ◽  
Youcef Bouafia
Keyword(s):  
Structural Reliability ◽  
Computational Cost ◽  
Computation Time ◽  
Point Method ◽  
Global Approximation ◽  
New Approach ◽  
Predictive Quality ◽  
Kriging Approximation ◽  
Adaptive Kriging

This study presents the results of a new approach for structural reliability analyses using adaptive kriging, confirmation simulation, and the pilot point method. Its main objective is to develop an efficient and accurate global approximation while controlling the computational cost and accuracy of prediction. The main contribution of research is to reduce computation time and successfully analyze complex problems with accurate results while ensuring excellent predictive quality of the approximation. For an excellent predictability of the kriging approximation, pilot point method and confirmation simulation are proposed. Simply, the predictive quality of the initial kriging approximation is improved by adding adaptive information, and the points are referred to as “pilot points” in areas where the kriging variance is maximized. Outcomes are confirmed with numerical simulations. The purpose is to select the minimum number of design experiments to ensure a good relative accuracy of the predictors with respect to the original models. Numerical examples show the efficiency of the proposed method compared to other structural reliability approaches.

scholarly journals Reliability-Based Robust Design Optimization of Structures Considering Uncertainty in Design Variables

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Shujuan Wang ◽  
Qiuyang Li ◽  
Gordon J. Savage
Keyword(s):  
Sensitivity Analysis ◽  
Design Optimization ◽  
Robust Design ◽  
Structural Reliability ◽  
Computational Cost ◽  
Optimization Process ◽  
Robust Design Optimization ◽  
Global Approximation ◽  
Design Variables ◽  
Uncertainty In Design

This paper investigates the structural design optimization to cover both the reliability and robustness under uncertainty in design variables. The main objective is to improve the efficiency of the optimization process. To address this problem, a hybrid reliability-based robust design optimization (RRDO) method is proposed. Prior to the design optimization, the Sobol sensitivity analysis is used for selecting key design variables and providing response variance as well, resulting in significantly reduced computational complexity. The single-loop algorithm is employed to guarantee the structural reliability, allowing fast optimization process. In the case of robust design, the weighting factor balances the response performance and variance with respect to the uncertainty in design variables. The main contribution of this paper is that the proposed method applies the RRDO strategy with the usage of global approximation and the Sobol sensitivity analysis, leading to the reduced computational cost. A structural example is given to illustrate the performance of the proposed method.

scholarly journals Linear Geometric ICA: Fundamentals and Algorithms

2003 ◽  
Vol 15 (2) ◽  
pp. 419-439 ◽  
Author(s):  
Fabian J. Theis ◽  
Andreas Jung ◽  
Carlos G. Puntonet ◽  
Elmar W. Lang
Keyword(s):  
Computational Cost ◽  
Geometric Approach ◽  
Convergence Condition ◽  
Geometric Algorithms ◽  
Data Sets ◽  
New Approach ◽  
Geometric Convergence ◽  
Mixing Matrix ◽  
Unit Vectors

Geometric algorithms for linear independent component analysis (ICA) have recently received some attention due to their pictorial description and their relative ease of implementation. The geometric approach to ICA was proposed first by Puntonet and Prieto (1995). We will reconsider geometric ICA in a theoretic framework showing that fixed points of geometric ICA fulfill a geometric convergence condition (GCC), which the mixed images of the unit vectors satisfy too. This leads to a conjecture claiming that in the nongaussian unimodal symmetric case, there is only one stable fixed point, implying the uniqueness of geometric ICA after convergence. Guided by the principles of ordinary geometric ICA, we then present a new approach to linear geometric ICA based on histograms observing a considerable improvement in separation quality of different distributions and a sizable reduction in computational cost, by a factor of 100, compared to the ordinary geometric approach. Furthermore, we explore the accuracy of the algorithm depending on the number of samples and the choice of the mixing matrix, and compare geometric algorithms with classical ICA algorithms, namely, Extended Infomax and FastICA. Finally, we discuss the problem of high-dimensional data sets within the realm of geometrical ICA algorithms.

A Circle Intersection Method for Bi-Objective Optimization

2021 ◽  
pp. 1-36
Author(s):  
Jianhua Zhou ◽  
Mian Li ◽  
Xiaojin Fu
Keyword(s):  
Pareto Front ◽  
Computational Cost ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
New Approach ◽  
Pareto Point ◽  
Objective Space ◽  
Anchor Points ◽  
Intersection Method

Abstract Multi-Objective Optimization (MOO) problems are encountered in many applications, of which bi-objective problems are frequently met. Despite the computational efforts, the quality of the Pareto front is also a considerable issue. An evenly distributed Pareto front is desirable in certain cases when a continuous representation of the Pareto front is needed. In this paper, a new approach called Circle Intersection (CI) is proposed. Firstly, the anchor points are computed. Then in the normalized objective space, a circle with a proper radius of r centering at one of the anchor points or the latest obtained Pareto point is drawn. Interestingly, the intersection of the circle and the feasible boundary can be determined whether it is a Pareto point or not. For a convex or concave feasible boundary, the intersection is exactly the Pareto point, while for other cases the intersection can provide useful information for searching the true Pareto point even if it is not a Pareto point. A novel MOO formulation is proposed for CI correspondingly. Sixteen examples are used to demonstrate the applicability of the proposed method and results are compared to those of NNC, MOGOA, and NSGA-II. Computational results show that the proposed CI method is able to obtain a well-distributed Pareto front with a better quality or with less computational cost.

Defining Generic Attributes for IDS Classification

2015 ◽  
Vol 74 (1) ◽  
Author(s):  
Hamid H. Jebur ◽  
Mohd Aizaini Maarof ◽  
Anazida Zainal
Keyword(s):  
Detection System ◽  
Computational Cost ◽  
Computation Time ◽  
Classification Model ◽  
Detection Accuracy ◽  
Features Selection ◽  
New Approach ◽  
Total Data ◽  
Overall Performance ◽  
Computer Resources

Detection accuracy of Intrusion Detection System (IDS) depends on classifying network traffic based on data features. Using all features for classification consumes more computation time and computer resources. Some of these features may be redundant and irrelevant therefore, they affect the detection of traffic anomalies and the overall performance of the IDS. The literature proposed different algorithms and techniques to define the most relevant sets of features of KDD cup 1999 that can achieve high detection accuracy and maintain the same performance as the total data features. However, all these algorithms and techniques did not produce optimal solutions even when they utilized same datasets. In this paper, a new approach is proposed to analyze the researches that have been conducted on KDD cup 1999 for features selection to define the possibility of determining effective generic features of the common dataset KDD cup 1999 for constructing an efficient classification model. The approach does not rely on algorithms, which shortens the computational cost and reduces the computer resources. The essence of the approach is based on selecting the most frequent features of each class and all classes in all researches, then a threshold is used to define the most significant generic features. The results revealed two sets of features containing 7 and 8 features. The classification accuracy by using eight features is almost the same as using all dataset features.

scholarly journals A new approach for disparity map determination

1970 ◽  
Vol 4 (1) ◽  
pp. 9-13 ◽  
Author(s):  
M Mozammel Hoque Chowdhury ◽  
Md Al-Amin Bhuiyan
Keyword(s):  
Computational Cost ◽  
Computation Time ◽  
Disparity Estimation ◽  
Scene Reconstruction ◽  
Main Task ◽  
Stereo Correspondence ◽  
Disparity Map ◽  
New Approach ◽  
3D Scene ◽  
3D Scene Reconstruction

This article presents a new method to determine disparity map useful for three-dimensional (3D) scene reconstruction. The main task behind the computation of disparity map is stereo correspondence matching. In recent years, several stereo matching algorithms have been developed to find corresponding pairs in two images: left and right images captured by a stereo camera. But these algorithms exhibit a very high computational cost. With a view to reduce the computation time and produce a smooth and detailed disparity map, a fast and new approach based on average disparity estimation is proposed in this research, which can tackle additive noise. Experimental results confirm that the method achieves a substantial gain in accuracy with less expense of computation time. Key Words: Disparity map, Stereo correspondence, Stereo Vision, 3D Scene Reconstruction. DOI: 10.3329/diujst.v4i1.4348 Daffodil International University Journal of Science and Technology Vol.4(1) 2009 pp.9-13

Driving Torsion Scans with Wavefront Propagation

2020 ◽  
Author(s):  
Yudong Qiu ◽  
Daniel Smith ◽  
Chaya Stern ◽  
mudong feng ◽  
Lee-Ping Wang
Keyword(s):  
Potential Energy ◽  
Force Field ◽  
Degrees Of Freedom ◽  
Computational Cost ◽  
Initial Guess ◽  
Field Development ◽  
Force Field Development ◽  
Wavefront Propagation ◽  
Open Source Software Package

<div>The parameterization of torsional / dihedral angle potential energy terms is a crucial part of developing molecular mechanics force fields.</div><div>Quantum mechanical (QM) methods are often used to provide samples of the potential energy surface (PES) for fitting the empirical parameters in these force field terms.</div><div>To ensure that the sampled molecular configurations are thermodynamically feasible, constrained QM geometry optimizations are typically carried out, which relax the orthogonal degrees of freedom while fixing the target torsion angle(s) on a grid of values.</div><div>However, the quality of results and computational cost are affected by various factors on a non-trivial PES, such as dependence on the chosen scan direction and the lack of efficient approaches to integrate results started from multiple initial guesses.</div><div>In this paper we propose a systematic and versatile workflow called \textit{TorsionDrive} to generate energy-minimized structures on a grid of torsion constraints by means of a recursive wavefront propagation algorithm, which resolves the deficiencies of conventional scanning approaches and generates higher quality QM data for force field development.</div><div>The capabilities of our method are presented for multi-dimensional scans and multiple initial guess structures, and an integration with the MolSSI QCArchive distributed computing ecosystem is described.</div><div>The method is implemented in an open-source software package that is compatible with many QM software packages and energy minimization codes.</div>

Machine Learning-based Virtual Screening Strategy Reveals Some Natural Compounds As Potential PAK4 Inhibitors In Triple Negative Breast Cancer

2020 ◽  
Vol 18 ◽  
Author(s):  
Opeyemi Iwaloye ◽  
Olusola Olalekan Elekofehinti ◽  
Babatomiwa Kikiowo ◽  
Emmanuel Ayo Oluwarotimi ◽  
Toyin Mary Fadipe
Keyword(s):  
Breast Cancer ◽  
Virtual Screening ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Binding Free Energy ◽  
Natural Compounds ◽  
Energy Calculation ◽  
Reference Drug ◽  
Predictive Quality

Background: P-21 activating kinase 4 (PAK4) is implicated in poor prognosis of many cancers, especially in the progression of Triple Negative Breast Cancer (TNBC). The present study was aimed at designing some potential drug candidates as PAK4 inhibitors for breast cancer therapy. Objective: This study aimed to finding novel inhibitors of PAK4 from natural compounds using computational approach. Methods: An e-pharmacophore model was developed from docked PAK4-coligand complex and used to screen over a thousand natural compounds downloaded from BIOFACQUIM and NPASS databases to match a minimum of 5 sites for selected (ADDDHRR) hypothesis. The robustness of the virtual screening method was accessed by well-established methods including EF, ROC, BEDROC, AUAC, and the RIE. Compounds with fitness score greater than one were filtered by applying molecular docking (HTVS, SP, XP and Induced fit docking) and ADME prediction. Using Machine learningbased approach QSAR model was generated using Automated QSAR. The computed top model kpls_des_17 (R2= 0.8028, RMSE = 0.4884 and Q2 = 0.7661) was used to predict the pIC50 of the lead compounds. Internal and external validations were accessed to determine the predictive quality of the model. Finally the binding free energy calculation was computed. Results: The robustness/predictive quality of the models were affirmed. The hits had better binding affinity than the reference drug and interacted with key amino acids for PAK4 inhibition. Overall, the present analysis yielded three potential inhibitors that are predicted to bind with PAK4 better than reference drug tamoxifen. The three potent novel inhibitors vitexin, emodin and ziganein recorded IFD score of -621.97 kcal/mol, -616.31 kcal/mol and -614.95 kcal/mol, respectively while showing moderation for ADME properties and inhibition constant. Conclusion: It is expected that the findings reported in this study may provide insight for designing effective and less toxic PAK4 inhibitors for triple negative breast cancer.

Guideline for the management of long tunnelled external ventricular drains in chronic hydrocephalus

2021 ◽  
Vol 30 (7) ◽  
pp. 416-421
Author(s):  
Phillip Correia Copley ◽  
John Emelifeonwu ◽  
Pasquale Gallo ◽  
Drahoslav Sokol ◽  
Jothy Kandasamy ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Nursing Care ◽  
Pilocytic Astrocytoma ◽  
Parental Education ◽  
Chronic Hydrocephalus ◽  
Treatment Protocols ◽  
New Approach ◽  
Viable Treatment

This article reports on the journey of a child with an inoperable hypothalamic-origin pilocytic astrocytoma causing hydrocephalus, which was refractory to treatment with shunts, and required a new approach. With multidisciplinary support, excellent nursing care and parental education, the child's hydrocephalus was managed long term in the community with bilateral long-tunnelled external ventricular drains (LTEVDs). This article describes the patient's journey and highlights the treatment protocols that were created to achieve this feat. Despite the difficulties in initially setting up these protocols, they proved successful and thus the team managing the patient proposed that LTEVDs are a viable treatment option for children with hydrocephalus in the context of inoperable tumours to help maximise quality of life.

Analyzing of UVLC system considering the effect of water depth

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Mustafa B. Al-Deen ◽  
Mazin Ali A. Ali ◽  
Zeyad A. Saleh
Keyword(s):  
Coastal Water ◽  
Water Depth ◽  
Bit Error Rate ◽  
Multiple Input Multiple Output ◽  
Visible Light Communications ◽  
New Approach ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Depth Water

Abstract This paper presents a new approach to discover the effect of depth water for underwater visible light communications (UVLC). The quality of the optical link was investigated with varying water depth under coastal water types. The performance of the UVLC with multiple input–multiple output (MIMO) techniques was examined in terms of bit error rate (BER) and data rate. The theoretical result explains that there is a good performance for UVLC system under coastal water.

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