胶莱盆地南部大盛群、王氏群的划分与对比

胶莱盆地在胶东半岛地质构造及造山带研究中占有重要地位,其巨厚的白垩系陆相沉积是石油系统多年的研究目标。胶莱盆地南部白垩纪的岩石地层序列较其北部更为复杂,其认识几经反复,其中尤以大盛群与王氏群和莱阳群的部分单位的关系为甚。本次工作通过详细对比其沉积层序、相互关系、古生物组合、岩石学特征及同位素年龄等因素,认为大盛群与王氏群属同一沉积层序,沉积基底相同、沉积环境相似、古生物群落时代一致,二者具有同时代、同沉积相、同岩石组合的一致性,应是一套地层,建议今后使用统一地层名称。     

消防法制建设与消防监督的相关性探究

文章从我国消防法制建设的现状出发,简要介绍了现行的消防法律法规,并详细解读了其现存问题,最后分别从消防法制建设与消防监督两个角度提出了发展对策,以期能为改善我国现阶段的消防法制建设和消防监督体系带来一定的参考意见.     

Correlation between instrumental stress and oral processing property of chicken broiler breast under wooden breast myopathy

Wooden breast myopathy affects the quality of fresh and processed chicken breast muscle. The objective of this study was to construct a classification method by instrumental stress, and the effects of wooden breast myopathy on meat quality and oral processing property, and was to explore correlations between stress and oral processing parameters. The severity of wooden breast myopathy was highly correlated to fillet weight (R² = 0.740), thickness (R² = 0.826) and hardness (R² = 0.803) (P < 0.01). The 3D scatter model based on stress is robust and reliable to classify the fillets into four categories (normal, mild, moderate and severe wooden breast fillets), avoiding manual grading. Moisture, fat, collagen, pH, drip loss, cooking loss, thawing loss, purge loss, hardness, gumminess and chewiness significantly increased with the severity of wooden breast myopathy, whereas fat, ash and water/salt-soluble protein contents significantly decreased (P < 0.05). Shear force reached the maximum (36.32 N) when this myopathy was moderate. The myopathy led to an increase in masseter activity and the particle size of the bolus. Significantly higher correlations between stress, Dx(50) (R² = 0.790), Dx(90) (R² = 0.771) and D[4,3] (R² = 0.797) were found (P < 0.01). This study also showed that jaw movement and muscle activity could be used to understand the links between physical property and orally sensory property.     

Effect of lactose content on dielectric properties of whole milk and skim milk

Dielectric properties (dielectric constant ε′ and dielectric loss factor ε′′) of whole milk and skim milk with the lactose content of 4.56–6.44% and 4.57–6.47%, respectively, were measured over the frequency range of 20–4500 MHz at 25 °C using a vector network analyzer. The results showed that ε′ decreased with increasing frequency, and ε′′ changed with V shape and its minimum was noted at about 2000 MHz. Whole milk had lower dielectric properties than skim milk at almost same lactose content and a given frequency. ε′ had weak positive linear relationship with lactose content for whole milk, but had negative linear relationship for skim milk. No matter for which milk, ε′′ had very good negative linear relationship with lactose content below 1000 MHz and had good positive linear relationship above 2300 MHz. The study provides information on developing rapid lactose detector for milk in future.     

Optimal-correlation-based reconstruction for distributed compressed video sensing

Distributed compressed video sensing (DCVS) is a framework that integrates both compressed sensing and distributed video coding characteristics to achieve a low-complexity video coding. However, how to design an efficient joint reconstruction by leveraging more realistic signal models is still an open challenge. In this paper, we present a novel optimal-correlation-based reconstruction method for compressively sampled videos from multiple measurement vectors. In our method, the sparsity is mainly exploited through inter-signal correlations rather than the traditional frequency transform, wherein the optimization is not only over the signal space to satisfy data consistency but also over all possible linear correlation models to achieve minimum-l₁-norm correlation noise. Additionally, a two-phase Bregman iterative based algorithm is outlined for solving the optimization problem. Simulation results show that our proposal can achieve an improved reconstruction performance in comparison to the conventional approaches, and especially, offer a 0.7–9.9 dB gain in the average PSNR for DCVS.     

内插法在相关干涉仪测向体制中的应用

测向误差的减小一直以来都是无线电测向精度提高的一个难点,对于不同的测向体制所采用的减小测向误差的方法都不尽相同。本文主要介绍的是相关干涉仪测向体制的基本原理以及通过内插法的应用来减小测向误差的方法。     

Statistical Data Analysis in the Era of Big Data

Big data is on everyone's lips and often raises emotions. On the one hand, the notion is a basis for much technological optimism, mostly directed towards new business models, or simplifications and optimizations in professional and private life. On the other hand, it is a basis for dystopic perspectives, which are targeted, e.g., at profiling of the individual and their privacy space, overarching optimization in daily life and intransparency of decision making. In this article, after a short historical prolog, it is discussed what distinguishes big data from traditional data analysis. The underlying mathematical methods are introduced and scientific successes are reported. Additionally, the risks and limits – especially regarding the derivation of causal relationships – of data analysis are discussed.     

高光谱图像分类的融合分层深度网络联合稀疏表示算法

在高光谱图像分类领域中每个像素的局部邻域一旦包含来自不同类别的样本,联合稀疏表示将受邻域内字典原子与测试样本之间同谱异类的影响,严重降低分类性能.根据高光谱图像的特点,文中提出融合分层深度网络的联合稀疏表示算法.在光谱和空间特征学习之间交替提取判别性光谱信息和空间信息,构建兼具空谱特征的学习字典,用于联合稀疏表示.在分类过程中将学习字典与测试样本间的相关系数与分类误差融合并决策.在两个高光谱遥感数据集上的实验验证文中算法的有效性.     

Development of correlation equations on hydrogen properties for hydrogen refueling process by machine learning approach

The energy transition which refers to shift of the energy system from fossil-based resources to renewable and sustainable energy sources becomes a global issue to mitigate the progression of climate change. Hydrogen can play an important role in long-term decarbonization of energy system and achievement of carbon neutrality. Currently, the utilization of hydrogen in the energy system is focused on a road transportation sector as a fuel in a vehicle fleet.Compressing gaseous hydrogen is the most well-established technology for storage in hydrogen-fueled vehicles. The refueling hydrogen requires short filling time while ensuring the safety of storage tanks in a vehicle. However, a fast filling of hydrogen in high pressure leads to a rapid temperature rise of hydrogen stored in tank. Therefore, many numerical and experimental studies have been carried out to analyze the filling process. Various thermo-physical properties of gaseous hydrogen such as density, viscosity, and thermal conductivity are required for the numerical studies and the accurate hydrogen properties are essential to obtain reliable results.In this work, a polynomial equation is proposed with respect to temperature and pressure in ranges of 223.15 K < T < 373.15 K and 0.1 MPa < P < 100.1 MPa to present various hydrogen thermo-physical properties by adopting different coefficients. The coefficients are determined by a machine learning method to regress the equation using a great number of reference data. The equation is trained, tested, and validated using different datasets for each property. The order of the equation has been changed from 2 to 5. Then, the accuracies are estimated and compared with respect to the order. The average relative errors (REs) of the 5th order equation are assessed to lower than 0.3% except for molar volume and entropy. The accuracy of the equation is also examined with experimental data and other correlation equations for density, viscosity, and thermal conductivity which are required for numerical simulations of hydrogen refueling. The proposed equation presents better accuracy for viscosity and thermal conductivity than literature equations. In density calculation, a literature equation shows better performance than the proposed equation, but the difference between their accuracies is not so significant. In calculation time comparison, it is revealed that the proposed equation rapidly responses adequate to computational fluid dynamics (CFD) simulations.Results of the study can provide accurate and reliable hydrogen property values in a fast and robust means specifically for simulation of hydrogen refueling process, but not restricted only to the process. Correlation equations proposed in the present work can aid in optimizing a hydrogen value chain including production, storage, and utilization by providing accurate hydrogen property.