1,102 research outputs found
Anthropology as an interdisciplinary field
No full textThe article discusses anthropology as an interdisciplinary field from the author's own research experience.AnthropologySociologySSCI0ARTICLE120-243
Stratego/XT 0.17. A Language and Toolset for Program Transformation
No full textPreprint of paper published in: Science of Computer Programming (Elsevier), 72 (1-2), 2008; doi:10.1016/j.scico.2007.11.003 Stratego/XT is a language and toolset for program transformation. The Stratego language provides rewrite rules for expressing basic transformations, programmable rewriting strategies for controlling the application of rules, concrete syntax for expressing the patterns of rules in the syntax of the object language, and dynamic rewrite rules for expressing context-sensitive transformations, thus supporting the development of transformation components at a high level of abstraction. The XT toolset offers a collection of flexible, reusable transformation components, and tools for generating such components from declarative specifications. Complete program transformation systems are composed from these components. This paper gives an overview of Stratego/XT 0.17, including a description of the Stratego language and XT transformation tools; a discussion of the implementation techniques and software engineering process; and a description of applications built with Stratego/XT.Software Computer TechnologyElectrical Engineering, Mathematics and Computer Scienc
Provenance of the first terrigenous sediments in the western Sichuan Basin during the Late Triassic: Implications for basin evolution from marine to continental
No full textThe Late Triassic was a key period for the evolution of the western Sichuan Basin from marine to continental sedimentation. However, the provenance of the earliest terrigenous sediments during this period remains debated, hindering our understanding of the tectonic events that ruled the evolution of the basin at that time. Herein, samples of fine sandstone from the Upper Triassic Ma'antang and Xiaotangzi formations in the western Sichuan Basin were collected for petrology, heavy mineral analysis, bulk rock geochemistry, and detrital U-Pb dating. In addition, corresponding data from potential source areas were collected for comparison. The sedi-mentological, geochronological, and geochemical characteristics of terrigenous sediments suggest that the clastic materials were mainly sourced from the Qinling orogenic belt and Yangtze Craton (including the northern and western margin). The Longmen Shan thrust belt likely provided clastics since the Early Norian. Siliciclastic deposits of the Late Triassic sedimentary succession of the western Sichuan Basin (Ma'antang and Xiaotangzi formations) yielded young zircon U-Pb ages of 214-245 Ma, suggesting that these zircons were likely sourced from the magmatic activities in the South Qinling orogenic belt or Yidun Island Arc. Combined with previous research, this study predates the transformation of the western Sichuan Basin from marine to continental sedi-mentation in the Late Carnian/Early Norian period
XT-ADS sensitivity analysis
No full textThis work has been carried out in the first period (March-June 2010) In which the author Joined the Central Design Team in Mol (B) for the CDT/FASTEF EU FP7 project. Before to start with the deep characterisation foreseen during the WP2 for FASTEF (100 MW LBE cooled reactor, working in both critical and sub-critical modes), a preliminary code tuning has been carried out by adopting the XT-ADS core layout (developed in IP EUROTRANS, EU FP6 project). The tuning deals with the neutronic codes, in particular: ERANOS (deterministic) and MCNPX (Monte Carlo). The main results have been included in the two SCK-CEN calculation notes here reported. The first calculation note (ANS/RMS/TS/ARTD00CDT-02/827/10-15) highlights the main differences between the ERANOS and MCNPX models for XT-ADS. Then the ERANOS input has been modified to consider the same assumptions adopted by MCNPX. A further tuning of both models yields, as a whole, a reduction of the MCNPX-ERANOS keff difference (at BoL) from by about 2700 pcm down to 1000 pcm. The second calculation note (ANS/RMS/TS/ARTD00CDT-02/827/10-16) summarizes the XT-ADS sensitivity analysis performed by ERANOS ver. 2.1 with two different nuclear data Iibraries: JEFF3.1 and ENDF/BVI.8. The study, carried out by exploiting the basics of standard perturbation theory, points out which nuclides, which cross-section and which range of energy yield the most significant impact on the core reactivity. As in the first note, the ERANOS evaluations (performed in a reference and voided configurations) have been compared with the results obtained with the MCNFX code
estimation and tests of hypotheses
No full textIn this paper we study nonparametric estimation and hypothesis testing procedures for the functional coefficient AR (FAR) models of the form Xt = f1(Xt-d)Xt-1 +…+ fp(Xt-d)Xt-p +εt, first proposed by Chen and Tsay (1993). As a direct generalization of the linear AR model, the FAR model is a rich class of models that includes many successful parametric nonlinear time series models such as the threshold AR models of Tong (1983), exponential AR models of Haggan and Ozaki (1978) and many others. We propose a local linear estimation procedure for estimating the coefficient functions and study its asymptotic properties. In addition, we propose two testing procedures. The first one tests whether all the coefficient functions are constant (i.e. whether the process is linear). The second one tests if all the coefficient functions are continuous, (i.e. if any threshold type of nonlinearity presents in the process). Some simulation results are presented
Functional coefficient autoregressive models: Estimation and tests of hypotheses
No full textIn this paper we study nonparametric estimation and hypothesis testing procedures for the functional coefficient AR (FAR) models of the form Xt = f1(Xt-d)Xt-1 +…+ fp(Xt-d)Xt-p +εt, first proposed by Chen and Tsay (1993). As a direct generalization of the linear AR model, the FAR model is a rich class of models that includes many successful parametric nonlinear time series models such as the threshold AR models of Tong (1983), exponential AR models of Haggan and Ozaki (1978) and many others. We propose a local linear estimation procedure for estimating the coefficient functions and study its asymptotic properties. In addition, we propose two testing procedures. The first one tests whether all the coefficient functions are constant (i.e. whether the process is linear). The second one tests if all the coefficient functions are continuous, (i.e. if any threshold type of nonlinearity presents in the process). Some simulation results are presented
Differential Identities with Engel Conditions
No full textThis thesis focuses on kernel inclusions of algebraic automorphisms, generalized derivations with Engel conditions and generalized derivations cocentralizing polynomials. In Chapter 1 we consider algebraic automorphisms with kernel inclusions. Let R be a prime ring. For an automorphism σ of R we let R(σ) def. = {x ∈ R | σ(x) = x}. Assume that σ is algebraic. We characterize the automorphism τ of R such that R(σ) ⊆ R(τ).
In Chapters 2,3 and 4 we consider certain identities with generalized derivations. Firstly, we concern generalized derivations cocentralizing polynomials. Let R be a prime ring with extended centroid C and let f(X1, . . . ,Xt) be a polynomial over C with zero constant term. Let D and G be generalized derivations of R. We characterize D,G and f(X1, . . . ,Xt) satisfying
D(f(x1, . . . , xt))f(x1, . . . , xt) − f(x1, . . . , xt)G(f(x1, . . . , xt))∈ C for all x1, . . . , xt in R.
Secondly, we consider certain Engel conditions on polynomials with generalized derivations. Precisely, we characterize D and f(X1, . . . ,Xt) such that the following Engel identity is satisfied:
[D(f(x1, . . . , xt)), f(x1, . . . , xt)]k= 0
for all x1, . . . , xt in R.
At the end, we concern a generalization of the previous two situations. Precisely, we characterize D,G and f(X1, . . . ,Xt) satisfying
[D(f(x1, . . . , xt))f(x1, . . . , xt)−f(x1, . . . , xt)G(f(x1, . . . , xt)), f(x1, . . . , xt)]k= 0
for all x1, . . . , xt in R
Strong convergence of approximation fixed points for nonexpansive nonself-mapping
No full textLet C be a closed convex subset of a uniformly smooth Banach
space E, and T:C→E a nonexpansive nonself-mapping satisfying the weakly inwardness condition such that F(T)≠∅, and f:C→C a fixed contractive mapping. For t∈(0,1), the implicit iterative sequence {xt} is defined by xt=P(tf(xt)+(1−t)Txt), the explicit iterative sequence {xn} is given by xn+1=P(αnf(xn)+(1−αn)Txn), where αn∈(0,1) and P is a sunny nonexpansive retraction of E onto C.
We prove that {xt} strongly converges to a fixed point of T
as t→0, and {xn} strongly converges to a fixed point of T as αn satisfying appropriate conditions. The results presented extend and improve the corresponding results of Hong-Kun Xu (2004) and Yisheng Song and Rudong Chen (2006)
XT-SECA: An Efficient and Accurate XGBoost–Transformer Model for Urban Functional Zone Classification
No full textThe remote sensing classification of urban functional zones provides scientific support for urban planning, land resource optimization, and ecological environment protection. However, urban functional zone classification encounters significant challenges in accuracy and efficiency due to complicated image structures, ambiguous critical features, and high computational complexity. To tackle these challenges, this work proposes a novel XT-SECA algorithm employing a strengthened efficient channel attention mechanism (SECA) to integrate the feature-extraction XGBoost branch and the feature-enhancement Transformer feedforward branch. The SECA optimizes the feature-fusion process through dynamic pooling and adaptive convolution kernel strategies, reducing feature confusion between various functional zones. XT-SECA is characterized by sufficient learning of complex image structures, effective representation of significant features, and efficient computational performance. The Futian, Luohu, and Nanshan districts in Shenzhen City are selected to conduct urban functional zone classification by XT-SECA, and they feature administrative management, technological innovation, and commercial finance functions, respectively. XT-SECA can effectively distinguish diverse functional zones such as residential zones and public management and service zones, which are easily confused by current mainstream algorithms. Compared with the commonly adopted algorithms for urban functional zone classification, including Random Forest (RF), Long Short-Term Memory (LSTM) network, and Multi-Layer Perceptron (MLP), XT-SECA demonstrates significant advantages in terms of overall accuracy, precision, recall, F1-score, and Kappa coefficient, with an accuracy enhancement of 3.78%, 42.86%, and 44.17%, respectively. The Kappa coefficient is increased by 4.53%, 51.28%, and 52.73%, respectively
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