270 research outputs found
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Imagery as Process Representation in Problem Solving
In this paper, we describe the characteristics of imagery phenomena in problem solving, develop a model for the process of forming and observing mental images in problem solving, and check the model against data obtained from subjects. Then, we describe the interaction between imaging and problem solving observed in our experiments, and discuss the use of our model to simulate it. We also discuss the relation between mental models and mental image briefly
Studies on LeftâBehind Children in China: Reviewing Paradigm Shifts
More than 60 million children have been left behind in rural China by parents going to work in cities. Given the effects of childâparent separation (CPS) on development, this phenomenon has drawn considerable governmental and academic attention in recent years. Outlining developments with reference to relevant studies, this review characterizes the perspectives used to explore and understand this phenomenon in terms of three major paradigms: (1) the diagnostic approach, which takes for granted the assumption that CPS would be the only cause of negative effects observed among leftâbehind children (LBC), and has focused primarily on measuring psychological and behavioral disorders among these âproblematic kidsâ; (2) the advanced diagnostic approach, which refines the previous approach by incorporating theories and techniques developed outside of China, elaborating on the early approach by bringing into consideration more factors and exploring the interactions between CPS and these factors, particularly social ones; (3) the sociologically oriented approach, which provides the research with a much broader framework in terms of how to orient the phenomenon of LBC, especially the transformation of Chinaâs social and economic systems during the last 30 years of urbanization, where the reproduction of labor has been based on a âsplitting family structure,â such that problems associated with the phenomenon of LBC cannot be solved without systematic social and economic changes. Based on these analyses, future directions for research on LBC in China are also discussed.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/147833/1/cad20267_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/147833/2/cad20267.pd
The shifted classical circulant and skew circulant splitting iterative methods for Toeplitz matrices
It is known that every Toeplitz matrix T enjoys a circulant and skew circulant splitting (denoted by CSCS), i.e., T=C-S with C a circulant matrix and S a skew circulant matrix. Based on the variant of such a splitting (also referred to as CSCS), we first develop classical CSCS iterative methods and then introduce shifted CSCS iterative methods for solving hermitian positive definite Toeplitz systems in this paper. The convergence of each method is analyzed. Numerical experiments show that the classical CSCS iterative methods work slightly better than the Gauss-Seidel (GS) iterative methods if the CSCS is convergent and that there is always a constant such that the shifted CSCS iteration converges much faster than the Gauss-Seidel iteration, no matter whether the CSCS itself is convergent or not.National Natural Science Foundation of China No. 11371075The authors would like to thank the supports of the National Natural Science Foundation of China under Grant No. 11371075, the research innovation program of Hunan province for postgraduate students under Grant
No. CX2015B374, the Portuguese Funds through FCTâFundacËao para a CiËencia, within the Project
UID/MAT/00013/2013.info:eu-repo/semantics/publishedVersio
Trigonometric transform splitting methods for real symmetric Toeplitz systems
In this paper, we study efficient iterative methods for real symmetric Toeplitz systems based
on the trigonometric transformation splitting (TTS) of the real symmetric Toeplitz matrix
A. Theoretical analyses show that if the generating function f of the n Ă n Toeplitz matrix
A is a real positive even function, then the TTS iterative methods converge to the unique
solution of the linear system of equations for sufficient large n. Moreover, we derive an
upper bound of the contraction factor of the TTS iteration which is dependent solely on the
spectra of the two TTS matrices involved.
Different from the CSCS iterative method in Ng (2003) in which all operations counts
concern complex operations when the DFTs are employed, even if the Toeplitz matrix
A is real and symmetric, our method only involves real arithmetics when the DCTs and
DSTs are used. The numerical experiments show that our method works better than CSCS
iterative method and much better than the positive definite and skew-symmetric splitting
(PSS) iterative method in Bai et al. (2005) and the symmetric GaussâSeidel (SGS) iterative
method.National Natural Science Foundation of China under Grant No. 11371075info:eu-repo/semantics/publishedVersio
MataDoc: Margin and Text Aware Document Dewarping for Arbitrary Boundary
Document dewarping from a distorted camera-captured image is of great value
for OCR and document understanding. The document boundary plays an important
role which is more evident than the inner region in document dewarping. Current
learning-based methods mainly focus on complete boundary cases, leading to poor
document correction performance of documents with incomplete boundaries. In
contrast to these methods, this paper proposes MataDoc, the first method
focusing on arbitrary boundary document dewarping with margin and text aware
regularizations. Specifically, we design the margin regularization by
explicitly considering background consistency to enhance boundary perception.
Moreover, we introduce word position consistency to keep text lines straight in
rectified document images. To produce a comprehensive evaluation of MataDoc, we
propose a novel benchmark ArbDoc, mainly consisting of document images with
arbitrary boundaries in four typical scenarios. Extensive experiments confirm
the superiority of MataDoc with consideration for the incomplete boundary on
ArbDoc and also demonstrate the effectiveness of the proposed method on
DocUNet, DIR300, and WarpDoc datasets.Comment: 12 page
Causal SAR ATR with Limited Data via Dual Invariance
Synthetic aperture radar automatic target recognition (SAR ATR) with limited
data has recently been a hot research topic to enhance weak generalization.
Despite many excellent methods being proposed, a fundamental theory is lacked
to explain what problem the limited SAR data causes, leading to weak
generalization of ATR. In this paper, we establish a causal ATR model
demonstrating that noise that could be blocked with ample SAR data, becomes
a confounder with limited data for recognition. As a result, it has a
detrimental causal effect damaging the efficacy of feature extracted from
SAR images, leading to weak generalization of SAR ATR with limited data. The
effect of on feature can be estimated and eliminated by using backdoor
adjustment to pursue the direct causality between and the predicted class
. However, it is difficult for SAR images to precisely estimate and
eliminated the effect of on . The limited SAR data scarcely powers the
majority of existing optimization losses based on empirical risk minimization
(ERM), thus making it difficult to effectively eliminate 's effect. To
tackle with difficult estimation and elimination of 's effect, we propose a
dual invariance comprising the inner-class invariant proxy and the
noise-invariance loss. Motivated by tackling change with invariance, the
inner-class invariant proxy facilitates precise estimation of 's effect on
by obtaining accurate invariant features for each class with the limited
data. The noise-invariance loss transitions the ERM's data quantity necessity
into a need for noise environment annotations, effectively eliminating 's
effect on by cleverly applying the previous 's estimation as the noise
environment annotations. Experiments on three benchmark datasets indicate that
the proposed method achieves superior performance
Gene cloning and expression profile of a novel carotenoid hydroxylase (CYP97C) from the green alga Haematococcus pluvialis
A full-length complementary DNA (cDNA) sequence of epsilon-ring CHY (designated Haecyp97c) was cloned from the green alga Haematococcus pluvialis by reverse transcription polymerase chain reaction (RT-PCR) and rapid amplification of cDNA ends methods. The Haecyp97c cDNA sequence was 1,995 base pairs (bp) in length, which contained a 1,620-bp open reading frame, a 46-bp 5'-untranslated region (UTR), and a 329-bp 3'-UTR with the characteristic of the poly (A) tail. The deduced protein had a calculated molecular mass of 58.71 kDa with an estimated isoelectric point of 7.94. Multiple alignment analysis revealed that the deduced amino acid sequence of HaeCYP97C shared high identity of 72-85 % with corresponding CYP97Cs from other eukaryotes. The catalytic motifs of cytochrome P450s were detected in the amino acid sequence of HaeCYP97C. The transcriptional levels of Haecyp97c and xanthophylls accumulation under high light (HL) stress have been examined. The results revealed that Haecyp97c transcript was strongly increased after 13-28 h under HL stress. Meanwhile, the concentrations of chlorophylls, carotenes, and lutein were decreased, and zeaxanthin and astaxanthin concentrations were increased rapidly, respectively. These facts indicated that HaeCYP97C was perhaps involved in xanthophyll biosynthesis, which plays an important role in adaption to HL for H. pluvialis.A full-length complementary DNA (cDNA) sequence of epsilon-ring CHY (designated Haecyp97c) was cloned from the green alga Haematococcus pluvialis by reverse transcription polymerase chain reaction (RT-PCR) and rapid amplification of cDNA ends methods. The Haecyp97c cDNA sequence was 1,995 base pairs (bp) in length, which contained a 1,620-bp open reading frame, a 46-bp 5'-untranslated region (UTR), and a 329-bp 3'-UTR with the characteristic of the poly (A) tail. The deduced protein had a calculated molecular mass of 58.71 kDa with an estimated isoelectric point of 7.94. Multiple alignment analysis revealed that the deduced amino acid sequence of HaeCYP97C shared high identity of 72-85 % with corresponding CYP97Cs from other eukaryotes. The catalytic motifs of cytochrome P450s were detected in the amino acid sequence of HaeCYP97C. The transcriptional levels of Haecyp97c and xanthophylls accumulation under high light (HL) stress have been examined. The results revealed that Haecyp97c transcript was strongly increased after 13-28 h under HL stress. Meanwhile, the concentrations of chlorophylls, carotenes, and lutein were decreased, and zeaxanthin and astaxanthin concentrations were increased rapidly, respectively. These facts indicated that HaeCYP97C was perhaps involved in xanthophyll biosynthesis, which plays an important role in adaption to HL for H. pluvialis
A resiliency framework for an enterprise cloud
This paper presents a systematic approach to develop a resilient software system which can be developed as emerging services and analytics for resiliency. While using the resiliency as a good example for enterprise cloud security, all resilient characteristics should be blended together to produce greater impacts. A framework, Cloud Computing Adoption Framework (CCAF), is presented in details. CCAF has four major types of emerging services and each one has been explained in details with regard to the individual function and how each one can be integrated. CCAF is an architectural framework that blends software resilience, service components and guidelines together and provides real case studies to produce greater impacts to the organizations adopting Cloud Computing and security. CCAF provides business alignments and provides agility, efficiency and integration for business competitive edge. In order to validate user requirements and system designs, a large scale survey has been conducted with detailed analysis provided for each major question. We present our discussion and conclude that the use of CCAF framework can illustrate software resilience and security improvement for enterprise security. CCAF framework itself is validated as an emerging service for Enterprise Cloud Computing with analytics showing survey analysi
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