340 research outputs found
Logarithmic Coefficients and Generalized Multifractality of Whole-Plane SLE
We consider the whole-plane SLE conformal map f from the unit disk to the
slit plane, and show that its mixed moments, involving a power p of the
derivative modulus |f'| and a power q of the map |f| itself, have closed forms
along some integrability curves in the (p,q) moment plane, which depend
continuously on the SLE parameter kappa. The generalization of this
integrability property to the m-fold transform of f is also given. We define a
generalized integral means spectrum corresponding to the singular behavior of
the mixed moments above. By inversion, it allows for a unified description of
the unbounded interior and bounded exterior versions of whole-plane SLE, and of
their m-fold generalizations. The average generalized spectrum of whole-plane
SLE takes four possible forms, separated by five phase transition lines in the
moment plane, whereas the average generalized spectrum of the m-fold
whole-plane SLE is directly obtained from a linear map acting in that plane. We
also conjecture the form of the universal generalized integral means spectrum.Comment: 51 pages, 11 figures; considerably revised and extended version.
Sections 4 and 5 fused, Section 7 deleted. Complete proof of Theorem 1.7
given. New Figures 2, 6 and
The source of real and nominal exchange rate fluctuations in Thailand: Real shock or nominal shock
This paper examines the source of exchange rate fluctuations in Thailand. We employed a structural vector auto-regression (SVAR) model with the long-run neutrality restriction of Blanchard and Quah (1989) to investigate the changes in real and nominal exchange rates from 1994 to 2015. In this paper, we assume that there are two types of shocks which related to exchange rate movements: real shocks and nominal shocks. The empirical analysis indicates that real shocks are the fundamental component in driving real and nominal exchange rate fluctuations
Survey on Mutation-based Test Data Generation
The critical activity of testing is the systematic selection of suitable test cases, which be able to reveal highly the faults. Therefore, mutation coverage is an effective criterion for generating test data. Since the test data generation process is very labor intensive, time-consuming and error-prone when done manually, the automation of this process is highly aspired. The researches about automatic test data generation contributed a set of tools, approaches, development and empirical results. In this paper, we will analyse and conduct a comprehensive survey on generating test data based on mutation. The paper also analyses the trends in this field
Effects of Data Standardization on Hyperparameter Optimization with the Grid Search Algorithm Based on Deep Learning: A Case Study of Electric Load Forecasting
This study investigates data standardization methods based on the grid search (GS) algorithm for energy load forecasting, including zero-mean, min-max, max, decimal, sigmoid, softmax, median, and robust, to determine the hyperparameters of deep learning (DL) models. The considered DL models are the convolutional neural network (CNN) and long short-term memory network (LSTMN). The procedure is made over (i) setting the configuration for CNN and LSTMN, (ii) establishing the hyperparameter values of CNN and LSTMN models based on epoch, batch, optimizer, dropout, filters, and kernel, (iii) using eight data standardization methods to standardize the input data, and (iv) using the GS algorithm to search the optimal hyperparameters based on the mean absolute error (MAE) and mean absolute percent error (MAPE) indexes. The effectiveness of the proposed method is verified on the power load data of the Australian state of Queensland and Vietnamese Ho Chi Minh city. The simulation results show that the proposed data standardization methods are appropriate, except for the zero-mean and min-max methods
EFL teachers’ perceptions of professional development activities and their effects in a non-anglosphere context
Providing teachers with adequate professional development (PD) is a central tenet to enhance education quality. In Vietnam, despite the blossoming of PD activities promoted over the past decade, the central question of how effectively these existing activities facilitate changes in teachers’ practice has been under-researched. This mixed-method study responded to the scarcity in understanding the effectiveness of PD activities in the Vietnamese setting by employing a questionnaire administered to 80 high school teachers and six semi-structured interviews. Evidence from the questionnaire and interviews revealed that EFL teachers participated in PD activities on an occasional basis. Institution-internal or in-house professional activities were most common, while joining a professional affiliation such as a TESOL association was the rarest. Also, PD activities have positively reinforced the teachers’ language proficiency, teaching practice, and planning practical lessons to meet students’ learning needs. The discussions and recommendations are made for enhancing the quality of PD activities
Multifactorial Evolutionary Algorithm For Clustered Minimum Routing Cost Problem
Minimum Routing Cost Clustered Tree Problem (CluMRCT) is applied in various
fields in both theory and application. Because the CluMRCT is NP-Hard, the
approximate approaches are suitable to find the solution for this problem.
Recently, Multifactorial Evolutionary Algorithm (MFEA) has emerged as one of
the most efficient approximation algorithms to deal with many different kinds
of problems. Therefore, this paper studies to apply MFEA for solving CluMRCT
problems. In the proposed MFEA, we focus on crossover and mutation operators
which create a valid solution of CluMRCT problem in two levels: first level
constructs spanning trees for graphs in clusters while the second level builds
a spanning tree for connecting among clusters. To reduce the consuming
resources, we will also introduce a new method of calculating the cost of
CluMRCT solution. The proposed algorithm is experimented on numerous types of
datasets. The experimental results demonstrate the effectiveness of the
proposed algorithm, partially on large instance
Design and Analysis of Ternary m-sequences with Interleaved Structure by d-Transform
Multilevel sequences find more and more applications in modern modulation schemes [4QPSK, 8QPSK,16QAM..]Â for the 3G ,4G system air interface [1,2].Furthermore, in modern cryptography they are also widerly used. It is also interesting to point out that the length L of these sequences are composite numbers( L=NS),that means the sequence can be easily implemented by interleaving S subsequences, each of length S.Therefore, the methods to develop multilevel sequence with interleaved structure draw a lot of attentions [3, 4]. In this contribution, a method for design and analysis of ternary m-sequences with interleaved structure is presented, based on the d-transform, Which turns out to be a very effective and versal tool for this purpose. Simulations have been made to verify the theory. We first introduce d-transform and its properties and then work out the procedure to design an interleaving sequence in d-transform. Keywords: d-transform,q-ary sequences, interleaved sequence
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