scholarly journals cola: an R/Bioconductor package for consensus partitioning through a general framework

2020 ◽  
Author(s):  
Zuguang Gu ◽  
Matthias Schlesner ◽  
Daniel Hübschmann
Keyword(s):  
General Framework ◽  
Optimal Parameter ◽  
Complete Analysis ◽  
Bioconductor Package ◽  
Sample Classification ◽  
Consensus Classification ◽  
Partitioning Procedure ◽  
The Stability ◽  
Public Datasets ◽  
Parameter Values

Abstract Classification of high-throughput genomic data is a powerful method to assign samples to subgroups with specific molecular profiles. Consensus partitioning is the most widely applied approach to reveal subgroups by summarizing a consensus classification from a list of individual classifications generated by repeatedly executing clustering on random subsets of the data. It is able to evaluate the stability of the classification. We implemented a new R/Bioconductor package, cola, that provides a general framework for consensus partitioning. With cola, various parameters and methods can be user-defined and easily integrated into different steps of an analysis, e.g., feature selection, sample classification or defining signatures. cola provides a new method named ATC (ability to correlate to other rows) to extract features and recommends spherical k-means clustering (skmeans) for subgroup classification. We show that ATC and skmeans have better performance than other commonly used methods by a comprehensive benchmark on public datasets. We also benchmark key parameters in the consensus partitioning procedure, which helps users to select optimal parameter values. Moreover, cola provides rich functionalities to apply multiple partitioning methods in parallel and directly compare their results, as well as rich visualizations. cola can automate the complete analysis and generates a comprehensive HTML report.

scholarly journals Differential Transform Method as an Effective Tool for Investigating Fractional Dynamical Systems

2021 ◽  
Vol 11 (15) ◽  
pp. 6955
Author(s):  
Andrzej Rysak ◽  
Magdalena Gregorczyk
Keyword(s):  
Optimal Parameter ◽  
Differential Transform Method ◽  
Bifurcation Diagrams ◽  
Transform Method ◽  
Rossler System ◽  
Differential Transform ◽  
Rössler System ◽  
Fractional System ◽  
Parameter Values

This study investigates the use of the differential transform method (DTM) for integrating the Rössler system of the fractional order. Preliminary studies of the integer-order Rössler system, with reference to other well-established integration methods, made it possible to assess the quality of the method and to determine optimal parameter values that should be used when integrating a system with different dynamic characteristics. Bifurcation diagrams obtained for the Rössler fractional system show that, compared to the RK4 scheme-based integration, the DTM results are more resistant to changes in the fractionality of the system.

scholarly journals Selecting single cell clustering parameter values using subsampling-based robustness metrics

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Ryan B. Patterson-Cross ◽  
Ariel J. Levine ◽  
Vilas Menon
Keyword(s):  
Single Cell ◽  
Optimal Parameter ◽  
Clustering Algorithms ◽  
Cell Types ◽  
Parameter Selection ◽  
Data Set ◽  
Biologically Relevant ◽  
Cell Clustering ◽  
Parameter Values ◽  
Robustness Metrics

Abstract Background Generating and analysing single-cell data has become a widespread approach to examine tissue heterogeneity, and numerous algorithms exist for clustering these datasets to identify putative cell types with shared transcriptomic signatures. However, many of these clustering workflows rely on user-tuned parameter values, tailored to each dataset, to identify a set of biologically relevant clusters. Whereas users often develop their own intuition as to the optimal range of parameters for clustering on each data set, the lack of systematic approaches to identify this range can be daunting to new users of any given workflow. In addition, an optimal parameter set does not guarantee that all clusters are equally well-resolved, given the heterogeneity in transcriptomic signatures in most biological systems. Results Here, we illustrate a subsampling-based approach (chooseR) that simultaneously guides parameter selection and characterizes cluster robustness. Through bootstrapped iterative clustering across a range of parameters, chooseR was used to select parameter values for two distinct clustering workflows (Seurat and scVI). In each case, chooseR identified parameters that produced biologically relevant clusters from both well-characterized (human PBMC) and complex (mouse spinal cord) datasets. Moreover, it provided a simple “robustness score” for each of these clusters, facilitating the assessment of cluster quality. Conclusion chooseR is a simple, conceptually understandable tool that can be used flexibly across clustering algorithms, workflows, and datasets to guide clustering parameter selection and characterize cluster robustness.

Optimization of the Robust Stability Limit for Multi-Cutter Turning Processes

2015 ◽  
Author(s):  
Marta J. Reith ◽  
Daniel Bachrathy ◽  
Gabor Stepan
Keyword(s):  
Robust Stability ◽  
Optimal Parameter ◽  
Stability Limit ◽  
Boundary Function ◽  
Lower Envelope ◽  
Computation Method ◽  
Parameter Region ◽  
Dynamical Parameters ◽  
The Stability ◽  
Machining Parameter

Multi-cutter turning systems bear huge potential in increasing cutting performance. In this study we show that the stable parameter region can be extended by the optimal tuning of system parameters. The optimal parameter regions can be identified by means of stability charts. Since the stability boundaries are highly sensitive to the dynamical parameters of the machine tool, the reliable exploitation of the so-called stability pockets is limited. Still, the lower envelope of the stability lobes is an appropriate upper boundary function for optimization purposes with an objective function taken for maximal material removal rates. This lower envelope is computed by the Robust Stability Computation method presented in the paper. It is shown in this study, that according to theoretical results obtained for optimally tuned cutters, the safe stable machining parameter region can significantly be extended, which has also been validated by machining tests.

scholarly journals Research on Generation Method of Grasp Strategy Based on DeepLab V3+ for Three-Finger Gripper

Information ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 278
Author(s):  
Sanlong Jiang ◽  
Shaobo Li ◽  
Qiang Bai ◽  
Jing Yang ◽  
Yanming Miao ◽  
...  
Keyword(s):  
Field Of View ◽  
Convolution Kernel ◽  
Parallel Connection ◽  
Multi Scale ◽  
Spatial Pyramid Pooling ◽  
The Stability ◽  
Parameter Values ◽  
Filter Layer ◽  
Complex Dataset ◽  
Better Than

A reasonable grasping strategy is a prerequisite for the successful grasping of a target, and it is also a basic condition for the wide application of robots. Presently, mainstream grippers on the market are divided into two-finger grippers and three-finger grippers. According to human grasping experience, the stability of three-finger grippers is much better than that of two-finger grippers. Therefore, this paper’s focus is on the three-finger grasping strategy generation method based on the DeepLab V3+ algorithm. DeepLab V3+ uses the atrous convolution kernel and the atrous spatial pyramid pooling (ASPP) architecture based on atrous convolution. The atrous convolution kernel can adjust the field-of-view of the filter layer by changing the convolution rate. In addition, ASPP can effectively capture multi-scale information, based on the parallel connection of multiple convolution rates of atrous convolutional layers, so that the model performs better on multi-scale objects. The article innovatively uses the DeepLab V3+ algorithm to generate the grasp strategy of a target and optimizes the atrous convolution parameter values of ASPP. This study used the Cornell Grasp dataset to train and verify the model. At the same time, a smaller and more complex dataset of 60 was produced according to the actual situation. Upon testing, good experimental results were obtained.

scholarly journals Analysis of dengue model with fractal-fractional Caputo–Fabrizio operator

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Fatmawati ◽  
Muhammad Altaf Khan ◽  
Cicik Alfiniyah ◽  
Ebraheem Alzahrani
Keyword(s):  
Statistical Data ◽  
Dengue Infection ◽  
Fractional Operator ◽  
Novel Approach ◽  
Reduction Number ◽  
Best Fitting ◽  
The Stability ◽  
Parameter Values ◽  
Graphical Illustration ◽  
Stability Results

AbstractIn this work, we study the dengue dynamics with fractal-factional Caputo–Fabrizio operator. We employ real statistical data of dengue infection cases of East Java, Indonesia, from 2018 and parameterize the dengue model. The estimated basic reduction number for this dataset is $\mathcal{R}_{0}\approx2.2020$ R 0 ≈ 2.2020 . We briefly show the stability results of the model for the case when the basic reproduction number is $\mathcal{R}_{0} <1$ R 0 < 1 . We apply the fractal-fractional operator in the framework of Caputo–Fabrizio to the model and present its numerical solution by using a novel approach. The parameter values estimated for the model are used to compare with fractal-fractional operator, and we suggest that the fractal-fractional operator provides the best fitting for real cases of dengue infection when varying the values of both operators’ orders. We suggest some more graphical illustration for the model variables with various orders of fractal and fractional.

A numerical method for determining optimal parameter values in forced periodic operation

1992 ◽  
Vol 47 (3) ◽  
pp. 605-613 ◽  
Author(s):  
Fatih Özgülşen ◽  
Raymond A. Adomaitis ◽  
Ali Çinar
Keyword(s):  
Numerical Method ◽  
Optimal Parameter ◽  
Periodic Operation ◽  
Parameter Values

scholarly journals The Complex Adaptive Delta-Modulator in Sliding Mode Theory

Entropy ◽  
2020 ◽  
Vol 22 (8) ◽  
pp. 814
Author(s):  
Dhafer Almakhles
Keyword(s):  
Steady State ◽  
Discrete Time ◽  
Sliding Mode ◽  
Stability Conditions ◽  
Mode Theory ◽  
Dynamical Behaviors ◽  
Complex Adaptive ◽  
The Stability ◽  
Parameter Values

In this paper, we consider the stability and various dynamical behaviors of both discrete-time delta modulator (Δ-M) and adaptive Δ-M. The stability constraints and conditions of Δ-M and adaptive Δ-M are derived following the theory of quasi-sliding mode. Furthermore, the periodic behaviors are explored for both the systems with steady-state inputs and certain parameter values. The results derived in this paper are validated using simulated examples which confirms the derived stability conditions and the existence of periodicity.

scholarly journals Computational Optimization Study of Transcatheter Aortic Valve Leaflet Design Using Porcine and Bovine Leaflets

2019 ◽  
Vol 142 (1) ◽  
Author(s):  
Stefano Travaglino ◽  
Kyle Murdock ◽  
Anh Tran ◽  
Caitlin Martin ◽  
Liang Liang ◽  
...  
Keyword(s):  
Aortic Valve ◽  
Stress Reduction ◽  
Optimal Parameter ◽  
Peak Stress ◽  
Bayesian Optimization ◽  
Fe Model ◽  
Computational Optimization ◽  
Transcatheter Aortic Valve ◽  
Biaxial Tensile Testing ◽  
Parameter Values

Abstract In this study, a Bayesian optimization (BO) based computational framework is developed to investigate the design of transcatheter aortic valve (TAV) leaflets and to optimize leaflet geometry such that its peak stress under the blood pressure of 120 mmHg is reduced. A generic TAV model is parametrized by mathematical equations describing its 2D shape and its 3D stent-leaflet assembly line. Material properties previously obtained for bovine pericardium (BP) and porcine pericardium (PP) via a combination of flexural and biaxial tensile testing were incorporated into the finite element (FE) model of TAV. A BO approach was employed to investigate about 1000 leaflet designs for each material under the nominal circular deployment and physiological loading conditions. The optimal parameter values of the TAV model were obtained, corresponding to leaflet shapes that can reduce the peak stress by 16.7% in BP and 18.0% in PP, compared with that from the initial generic TAV model. Furthermore, it was observed that while peak stresses tend to concentrate near the stent-leaflet attachment edge, optimized geometries benefit from more uniform stress distributions in the leaflet circumferential direction. Our analysis also showed that increasing leaflet contact area redistributes peak stresses to the belly region contributing to peak stress reduction. The results from this study may inspire new TAV designs that can have better durability.

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