GENERATION OF 3D JULIA SETS FROM SWITCHING POLYNOMIAL MAPS

Fractals ◽  
2009 ◽  
Vol 17 (02) ◽  
pp. 205-210
Author(s):  
JIN CHENG ◽  
JIANRONG TAN ◽  
CHUNBIAO GAN
Keyword(s):  
Julia Sets ◽  
Quadratic Polynomial ◽  
Experimental Results ◽  
Polynomial Maps ◽  
Novel Approach ◽  
3D Fractals

Inspired by the study of 3D fractals based on quadratic polynomial maps,1 this paper presents a novel approach for generating 3D Julia sets by utilizing a family of switching polynomial maps in order to further enrich the form of 3D fractals. Rotational symmetries in the structures of resulting Julia sets with different switching parameters are theoretically analyzed and proved. Experimental results obtained from various parameters and coefficients in the switching maps are provided and discussed in detail. It is hoped that the investigations conducted in this paper can bring on new perspectives for the generalization of 3D fractals.

ON A GENERALIZED FATOU–JULIA THEOREM IN MULTICOMPLEX SPACES

Fractals ◽  
2009 ◽  
Vol 17 (03) ◽  
pp. 241-255 ◽  
Author(s):  
V. GARANT–PELLETIER ◽  
D. ROCHON
Keyword(s):  
Julia Set ◽  
Julia Sets ◽  
Quadratic Polynomial ◽  
Mandelbrot Set ◽  
Topological Characterization ◽  
Multicomplex Numbers ◽  
3D Fractals

In this article we introduce the hypercomplex 3D fractals generated from Multicomplex Dynamics. We generalize the well known Mandelbrot and filled-in Julia sets for the multicomplex numbers (i.e. bicomplex, tricomplex, etc.). In particular, we give a multicomplex version of the so-called Fatou-Julia theorem. More precisely, we present a complete topological characterization in ℝ2n of the multicomplex filled-in Julia set for a quadratic polynomial in multicomplex numbers of the form w2 + c. We also point out the symmetries between the principal 3D slices of the generalized Mandelbrot set for tricomplex numbers.

Mining discriminative patches for script identification in natural scene images

2021 ◽  
Vol 40 (1) ◽  
pp. 551-563
Author(s):  
Liqiong Lu ◽  
Dong Wu ◽  
Ziwei Tang ◽  
Yaohua Yi ◽  
Faliang Huang
Keyword(s):  
Neural Networks ◽  
Experimental Results ◽  
The Other ◽  
Natural Scene ◽  
Fixed Size ◽  
Script Identification ◽  
Aspect Ratios ◽  
Novel Approach ◽  
Public Datasets ◽  
Natural Scene Images

This paper focuses on script identification in natural scene images. Traditional CNNs (Convolution Neural Networks) cannot solve this problem perfectly for two reasons: one is the arbitrary aspect ratios of scene images which bring much difficulty to traditional CNNs with a fixed size image as the input. And the other is that some scripts with minor differences are easily confused because they share a subset of characters with the same shapes. We propose a novel approach combing Score CNN, Attention CNN and patches. Attention CNN is utilized to determine whether a patch is a discriminative patch and calculate the contribution weight of the discriminative patch to script identification of the whole image. Score CNN uses a discriminative patch as input and predict the score of each script type. Firstly patches with the same size are extracted from the scene images. Secondly these patches are used as inputs to Score CNN and Attention CNN to train two patch-level classifiers. Finally, the results of multiple discriminative patches extracted from the same image via the above two classifiers are fused to obtain the script type of this image. Using patches with the same size as inputs to CNN can avoid the problems caused by arbitrary aspect ratios of scene images. The trained classifiers can mine discriminative patches to accurately identify some confusing scripts. The experimental results show the good performance of our approach on four public datasets.

Revealing the nanodomain structure of silicon oxycarbide via preferential etching and pore analysis

2016 ◽  
Vol 09 (03) ◽  
pp. 1650043 ◽  
Author(s):  
Haolin Wu ◽  
Jie Yang ◽  
Haibiao Chen ◽  
Feng Pan
Keyword(s):  
Porous Structure ◽  
Gas Adsorption ◽  
Inverse Image ◽  
Silicon Oxycarbide ◽  
Experimental Results ◽  
Porous Network ◽  
Pore Analysis ◽  
Novel Approach ◽  
Nanodomain Structure ◽  
Nanocomposite Structures

Preferentially etching either carbon or silica from silicon oxycarbide (SiOC) created a porous network as an inverse image of the removed phase. The porous structure was analyzed by gas adsorption, and the experimental results verified the nanodomain structure of SiOC. This work demonstrated a novel approach for analyzing materials containing nanocomposite structures.

scholarly journals A Novel Approach to Measure the Hydraulic Capacitance of a Microfluidic Membrane Pump

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Chun-Hui Wu ◽  
Chia-Wei Chen ◽  
Long-Sheng Kuo ◽  
Ping-Hei Chen
Keyword(s):  
Linear Correlation ◽  
Experimental Results ◽  
Membrane Thickness ◽  
Membrane Pump ◽  
Novel Approach ◽  
Hydraulic Capacitance ◽  
Linear And Nonlinear ◽  
Center Deflection ◽  
Membrane Deflection ◽  
Good Agreement

A novel approach was proposed to measure the hydraulic capacitance of a microfluidic membrane pump. Membrane deflection equations were modified from various studies to propose six theoretical equations to estimate the hydraulic capacitance of a microfluidic membrane pump. Thus, measuring the center deflection of the membrane allows the corresponding pressure and hydraulic capacitance of the pump to be determined. This study also investigated how membrane thickness affected the Young’s modulus of a polydimethylsiloxane (PDMS) membrane. Based on the experimental results, a linear correlation was proposed to estimate the hydraulic capacitance. The measured hydraulic capacitance data and the proposed equations in the linear and nonlinear regions qualitatively exhibited good agreement.

COMPARING VIRUS CLASSIFICATION USING GENOMIC MATERIALS ACCORDING TO DIFFERENT TAXONOMIC LEVELS

2013 ◽  
Vol 11 (06) ◽  
pp. 1343003 ◽  
Author(s):  
JING-DOO WANG
Keyword(s):  
Molecular Biology ◽  
Dna Sequences ◽  
Protein Sequences ◽  
Experimental Results ◽  
Virus Classification ◽  
Taxonomic Level ◽  
Biological Classification ◽  
Novel Approach

In this paper, three genomic materials — DNA sequences, protein sequences, and regions (domains) are used to compare methods of virus classification. Virus classes (categories) are divided by various taxonomic level of virus into three datasets for 6 order, 42 family, and 33 genera. To increase the robustness and comparability of experimental results of virus classification, the classes are selected that contain at least 10 instances, and meanwhile each instance contains at least one region name. Experimental results show that the approach using region names achieved the best accuracies — reaching 99.9%, 97.3%, and 99.0% for 6 orders, 42 families, and 33 genera, respectively. This paper not only involves exhaustive experiments that compare virus classifications using different genomic materials, but also proposes a novel approach to biological classification based on molecular biology instead of traditional morphology.

Probabilistic Feature Attention as an Alternative to Variables in Phonotactic Learning

2021 ◽  
pp. 1-56
Author(s):  
Brandon Prickett
Keyword(s):  
Experimental Work ◽  
Experimental Results ◽  
Phonological Acquisition ◽  
Novel Approach ◽  
Free Model ◽  
Cast Doubt ◽  
Feature Attention ◽  
Phonotactic Learning ◽  
Past Experimental Work ◽  
Algebraic Representations

Abstract Since Halle (1962), explicit algebraic variables (often called alpha notation) have been commonplace in phonological theory. However, Hayes and Wilson (2008) proposed a variable-free model of phonotactic learning, sparking a debate about whether such algebraic representations are necessary to capture human phonological acquisition. While past experimental work has found evidence that suggested a need for variables in models of phonology (Berent et al. 2012, Moreton 2012, Gallagher 2013), this paper presents a novel mechanism, Probabilistic Feature Attention (PFA), that allows a variable-free model of phonotactics to predict a number of these phenomena. Additionally, experimental results involving phonological generalization that cannot be explained by variables are captured by this novel approach. These results cast doubt on whether variables are necessary to capture human-like phonotactic learning and provide a useful alternative to such representations.

An Efficient and Effective Approach to Developing Engineering E-Training Courses

2011 ◽  
pp. 26-39
Author(s):  
Judy C.R. Tseng ◽  
Wen-Ling Tsai ◽  
Gwo-Jen Hwang ◽  
Po-Han Wu
Keyword(s):  
New Technologies ◽  
Experimental Results ◽  
Traditional Learning ◽  
The Novel ◽  
Learning Materials ◽  
Challenging Issue ◽  
Novel Approach ◽  
Training Courses ◽  
Oriented Approach

In developing traditional learning materials, quality is the key issue to be considered. However, for high technical e-training courses, not only the quality of the learning materials but also the efficiency of developing the courses needs to be taken into consideration. It is a challenging issue for experienced engineers to develop up-to-date e-training courses for inexperienced engineers before further new technologies are proposed. To cope with these problems, a concept relationship-oriented approach is proposed in this paper. A system for developing e-training courses has been implemented based on the novel approach. Experimental results showed that the novel approach can significantly shorten the time needed for developing e-training courses, such that engineers can receive up-to-date technologies in time.

Selective Querying for Adapting Hierarchical Web Service Compositions

2011 ◽  
pp. 125-144
Author(s):  
John Harney ◽  
Prashant Doshi
Keyword(s):  
Web Service ◽  
Efficient Solution ◽  
Experimental Results ◽  
Novel Approach ◽  
Nested Structure

Web Service compositions (WSC) often operate in volatile environments where the parameters of the component services change during execution. To remain optimal, the WSC could adapt to these changes by querying the participating providers for their revised parameters. Previously, the value of changed information (VOC) has been utilized in simple WSCs to selectively query only those services whose revised parameters are expected to bring about significant changes in the composition. In many cases, however, in order to promote scalability, a WSC is formulated as a more complex, nested structure – a higher-level WSC may be composed of WSs and lower-level WSCs – inducing a natural hierarchy over the composition. This chapter presents a novel approach that extends the capabilities of VOC-driven querying to address the problem of adapting hierarchical WSCs. It shows how to compose and adapt hierarchical WSCs by first deriving a model of volatility for lower-level WSCs and then by descending down the levels of nesting and computing the VOC for WSCs at each level. Experimental results demonstrate that this approach provides an effective and efficient solution for complex, hierarchical WSCs.

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