Detection of correlation characteristics between financial time series based on multi-resolution analysis

Interactions between financial time series are complex and changeable in both time and frequency domains. To reveal the evolution characteristics of the time-varying relations between bivariate time series from a multi-resolution perspective, this study introduces an approach combining wavelet analysis and complex networks. In addition, to reduce the influence the phase lag between the time series has on the correlations, we propose dynamic time-warping (DTW) correlation coefficients to reflect the correlation degree between bivariate time series. Unlike previous studies that symbolized the time series only based on the correlation strength, the second-level symbol is set according to the correlation length during the coarse-graining process. This study presents a novel method to analyze bivariate time series and provides more information for investors and decision makers when investing in the stock market. We choose the closing prices of two stocks in China’s market as the sample and explore the evolutionary behavior of correlation modes from different resolutions. Furthermore, we perform experiments to discover the critical correlation modes between the bull market and the bear market on the high-resolution scale, the clustering effect during the financial crisis on the middle-resolution scale, and the potential pseudo period on the low-resolution scale. The experimental results exactly match reality, which provides powerful evidence to prove that our method is effective in financial time series analysis.     

Pull out of FRP reinforcement from masonry pillars: Experimental and numerical results

In this paper, debonding phenomena between carbon fiber reinforced polymer (CFRP) strips and masonry support were investigated on the basis of single-lap shear tests, considering different dimensions of the bond length. To capture the post-peak response of the CFRP–masonry joint, the slip between the support and the reinforcement strip was controlled using a clip gauge positioned at the end of the reinforcement. The tests were simulated by means of a finite element model able to capture the post-peak snap-back behavior due to the failure process. The numerical model is based on zero-thickness interface elements and on a proper non-linear cohesive law. The comparison between experimental and numerical results was performed in terms of overall response, measured by both the machine stroke and the clip gauge positioned at the free end of the reinforcement. The cases of effective bond length greater and lesser than the minimum anchorage length, suggested by the CNR Italian recommendation, were considered.     

Application of Vis–NIR hyperspectral imaging in classification between fresh and frozen-thawed pork Longissimus Dorsi muscles

Fresh and frozen-thawed (F-T) pork meats were classified by Vis–NIR hyperspectral imaging. Eight optimal wavelengths (624, 673, 460, 588, 583, 448, 552 and 609 nm) were selected by successive projections algorithm (SPA). The first three principal components (PCs) obtained by principal component analysis (PCA) accounted for over 99.98% of variance. Gray-level-gradient co-occurrence matrix (GLGCM) was applied to extract 45 textural features from the PC images. The correct classification rate (CCR) was employed to evaluate the performance of the partial least squares-discriminate analysis (PLS-DA) models, by using (A) the reflected spectra at full wavelengths and (B) those at the optimal wavelengths, (C) the extracted textures based on the PC images, and (D) the fused variables combining spectra at the optimal wavelengths and textures. The results showed that the best CCR of 97.73% was achieved by applying (D), confirming the high potential of textures for fresh and F-T meat discrimination.     

Challenges in the CO2 emissions of the Turkish power sector: Evidence from a two-level decomposition approach

Decarbonization of the energy system is urgent to avert the disruptions in the climate. Considering its share, the low carbon transition of the power sector is pivotal. Growing electricity demand poses unique challenges for Turkey to enact deep decarbonization. It is vital to uncover the contributing causes of emissions to provide strategic oversight for carbon management activities. This study investigates key drivers of CO₂ emissions from the power sector using the Logarithmic Mean Divisia Index decomposition method. While efficiency improvement contributes to sustainable yet minor mitigation, changes in the fossil-fuel share indicate a cycling but significant overall impact.     

膨胀剂对约束条件下UHPC早期抗裂性能影响的试验研究

超高性能混凝土(UHPC)在钢桥面铺装结构中由于铺装材料受到钢板、栓钉等的约束,加上材料本身水胶比小,更易收缩,早期容易承受拉应力导致开裂。通过在拌和过程中添加膨胀剂可以起到减小收缩的作用,但该方法对于约束条件下的UHPC铺装的早期抗裂性能提升是否有促进作用,仍需通过更多试验进行合理评估和深入研究。通过圆环法对3组不同配方的UHPC在均匀约束条件下的早期抗裂性能进行定量测试,并将试验数据进行回归分析和计算,得到了各组的平均应力发展速率,进而评估了各组的开裂风险等级。试验结果表明,通过在UHPC中加入适量膨胀剂,可使其最终收缩应力减小,并可降低其收缩应力发展速率,进一步降低其在约束条件下的开裂风险。     

Model Selection for Unsupervised Learning of Visual Context

This study addresses the problem of choosing the most suitable probabilistic model selection criterion for unsupervised learning of visual context of a dynamic scene using mixture models. A rectified Bayesian Information Criterion (BICr) and a Completed Likelihood Akaike’s Information Criterion (CL-AIC) are formulated to estimate the optimal model order (complexity) for a given visual scene. Both criteria are designed to overcome poor model selection by existing popular criteria when the data sample size varies from small to large and the true mixture distribution kernel functions differ from the assumed ones. Extensive experiments on learning visual context for dynamic scene modelling are carried out to demonstrate the effectiveness of BICr and CL-AIC, compared to that of existing popular model selection criteria including BIC, AIC and Integrated Completed Likelihood (ICL). Our study suggests that for learning visual context using a mixture model, BICr is the most appropriate criterion given sparse data, while CL-AIC should be chosen given moderate or large data sample sizes.     

Behaviour of Surface Defects in Wire Rod Rolling

Defects are often present in rolled products, such as wire rod. The market demand for wire rod without any defects has increased. In the final wire rod products, defects originating from steel making, casting, pre‐rolling of billets and during wire rod rolling can appear. In this work, artificial V‐shaped longitudinal surface cracks have been analysed experimentally and by means of FEM. The results indicate that the experiments and FEM calculations show the same tendency except in two cases, where instability due to fairly “round” false round bars disturbed the experiment. FE studies in combination with practical experiments are necessary in order to understand the behaviour of the material flows in the groove and to explain whether the crack will open up as a V‐shape or if it will be closed as an I‐shape.     

埋地管道在冻土带的热力变形分析

埋地油气管道通过永冻土地带时,由于管内介质与周围的冻土发生了热力作用,使冰土解冻,在管道周围形成融化圈。文章分析了永冻土的特点,建立了永冻土地带土壤传热数学模型:融化圈内外传热方程、管道向土壤和土壤表面向大气所放热量的守恒关系、融化圈界面处土壤温度、相变界面处固相变为液相的传热条件。还建立了埋地管道模型,并以穿过永冻土地带土壤的输油管道为例,分析并计算了各种应力的最大值所在的位置和大小,提出了在永冻土地带减小管道热力变形的措施。     

变频调速系统中电动机和变频器选择及问题分析

本文分析了选用标准笼形电动机的容量计算方法、问题分析和选用变频器的型式、容量、注意事项。