大数据时代的农药创制

随着农药创制研究和应用工作的不断积累和深入,农药的各种性质,如活性、毒性、代谢等的测量、记录和分析数据,已有一定的积累,并达到了一定的规模。随着信息技术的发展,在农药创制中,有效地利用这些数据已成为可能。阐述了大数据的定义、特点,提出了大数据时代的农药创制理念和农药创制的现代模式。     

大数据时代下的高校普通化学教学改革探析

随着大数据科学技术的快速发展,我们的社会已进入了"大数据"时代,信息技术产业的革新已经渗透到整个社会,给人们的生产和生活带来了巨大的改变。受信息技术产业快速发展的影响,高校教学工作也面临着前所未有的挑战,同时对高校教学改革提出了全新的问题,以高等工科普通化学教学改革为例,本文提出了大数据背景下高校教学改革的策略。     

Spectral Analysis of Uneven Data in a Bipolar Charging Agglomeration System

This paper presents particle dynamics analysis (PDA) results from three measurement sections of a bipolar charged agglomeration system. The periodogram model and the Burg algorithm for autoregressive spectral estimates were used for the spectral analysis of the unevenly spaced data. The one‐dimensional energy spectrum from the Burg algorithm is smoother than that from periodogram model. The spectrum of the main flow velocity with charging is lower than for the case without charging. The results show that the one‐dimensional kinetic energy distribution at all frequencies can be well represented by the one‐dimensional energy spectrum. The dissipation rate was then obtained from the energy spectrum. The results also show that there is a lower dissipation rate in measurement section 1 with charging than without charging.     

Breakthrough Curves Analysis and Statistical Design of Phenol Adsorption on Activated Carbon

Activated carbon was used as an adsorbent for the removal of phenol from aqueous solution under various operating conditions. Statistical design using MATLAB® tools was employed to study the effects of three variables on six different response factors. MATLAB® software was employed to solve proposed quadratic model equations and for fitting a quadratic response surface. All the models with a very high adjusted R‐square predicted the experimental data well. The Thomas, the Yoon‐Nelson, the Wolborska, the bed depth service time, and the linear driving force models were used to predict breakthrough curves for experimental data. The results showed that the linear driving force model was suitable for the prediction of the breakthrough curve data.     

大数据分析在采油工程管理中的应用

计算机技术的发展已经改变了人们的生产生活方式,在采油工程管理中通过大数据分析可以实现科学的工程管理,同时根据采油过程中的需要以及生产和科研的发展要求,定制一系列的方案,最终解决生产实际中的各项问题。大数据分析对于我国油田的高产值以及管理水平的提升具有至关重要的作用,因此主要对大数据分析在采油工程管理中的应用进行分析。     

基于大数据的人力资源管理浅析

对于企业人力资源管理者来说,无论是对过去的总结,还是对未来的预测和规划都离不开数据。如何将大数据、人工智能与企业人力资源管理有机结合,成了当下研究的热点问题。本文重点研究微观大数据和宏观大数据,阐述微观大数据和宏观大数据的概念,以及其在企业人力资源管理中的重要作用。     

Statistical Analysis of the Effect of the Temperature and Inlet Humidities on the Parameters of a PEMFC Model

An individual PEM fuel cell 6‐parameter mechanistic model was developed. In parallel, experimental polarization curves were obtained at different temperature and inlet gas humidities conditions. The 6 model parameters were determined by fitting the semi empirical model to the experimental curve using a non linear regression method. Finally, a statistical analysis was carried out in order to determine which operating conditions (temperature and inlet humidities) have a significant effect on which model parameters. A black box model was built in order to relate the model parameter values to the significant operating conditions for each one of them. The obtained model was able to satisfactory reproduce the experimental behaviour of the system at low current densities.     

基于转型发展和大数据时代双重背景无机化学及实验教学改革探究

在转型发展和大数据时代双重背景下,人们获取新知识的能力和习惯发生了很大改变,促使教学手段、教学模式和课堂模式向着信息化前进,传统的教学模式远远不能满足现代人才的培养需要,无机化学及实验的教学改革迫在眉睫,本文从改变传统教学模式(建立多元化教学模式和信息化课堂教学模式)、整合优化教学内容、构建新的考核体系等三个方面进行了无机化学课程及实验教学改革实践探究。     

Investigations on the compressive strength of silica fume concrete using statistical methods

The present paper deals with a mathematical model developed using statistical methods to predict the 28-day compressive strength of silica fume concrete with water-to-cementitious material (w/cm) ratios ranging from 0.3 to 0.42 and silica fume replacement percentages from 5 to 30. Strength results of 26 concrete mixes, on more than 300 test specimens, have been analyzed for statistical modeling. The ratios of compressive strengths between silica fume and control concrete have been related to silica fume replacement percentage. The expression, being derived with strength ratios and not with absolute values of strength, is independent of the specimen parameters and is applicable to all types of specimens. On examining the validity of the model with the results of previous researchers, it was observed that for results on both cubes and cylinders, predictions were obtained within 7.5% of the experimentally obtained values.     

Application of Statistical Physics on the Modeling of Water Vapor Desorption Isotherms

The sorption isotherms give information about the interaction of biopolymers with water vapor. These isotherms are extremely important in the modeling of the drying processes and in the prediction of the humidity changes during the product storage. An analytical expression for modeling of water vapor sorption isotherms of agricultural products was developed using the statistical physics formalism. The statistical model was further used to fit and interpret desorption isotherms of Tunisian olive leaves and some food products. In this model, five parameters in relation to the desorption process intervene, such as the number of water molecules per site n, the receptor sites density N _M , the energetic parameters a ₁ and a ₂, and the number of multilayers N ₂. The fitting results are discussed to explain the behavior of different parameters versus temperature. The statistical model was used to investigate thermodynamics functions that govern in the desorption mechanism, such as entropy, internal energy, and Gibbs free enthalpy.     

Statistical Assessment Methods for the Sensitivity of Energetic Materials

The joint research project Particle Processing and Characterization was started in March 2003 under the EUROPA ERG1 Arrangement, with the objective to study the influence of crystallization and processing techniques on particle quality and its implication for the formulation of PBX with IM behavior. As sensitivity assessment is a crucial task of the project, impact sensitivity tests of HMX and RDX samples have been performed at two different laboratories, and several statistical techniques have been tested in addition to the standard BAM “1/6” and Bruceton “up and down” methods.     

Proximate analysis based multiple regression models for higher heating value estimation of low rank coals

In this paper, multiple nonlinear regression models for estimation of higher heating value of coals are developed using proximate analysis data obtained generally from the low rank coal samples as-received basis. In this modeling study, three main model structures depended on the number of proximate analysis parameters, which are named the independent variables, such as moisture, ash, volatile matter and fixed carbon, are firstly categorized. Secondly, sub-model structures with different arrangements of the independent variables are considered. Each sub-model structure is analyzed with a number of model equations in order to find the best fitting model using multiple nonlinear regression method. Based on the results of nonlinear regression analysis, the best model for each sub-structure is determined. Among them, the models giving highest correlation for three main structures are selected. Although the selected all three models predicts HHV rather accurately, the model involving four independent variables provides the most accurate estimation of HHV. Additionally, when the chosen model with four independent variables and a literature model are tested with extra proximate analysis data, it is seen that that the developed model in this study can give more accurate prediction of HHV of coals. It can be concluded that the developed model is effective tool for HHV estimation of low rank coals.     

Statistical modeling of the geometrical structure of the system of artificial air pores in autoclaved aerated concrete

The geometrical structure of the system of artificial air pores in autoclaved concrete is studied, based on samples from laboratory and industry. The single pores are approximated by spheres, the corresponding radius distribution is determined by means of stereological methods. The resulting distribution is not a classical standard distribution, but instead requires a mixture of three components, one of them Gaussian. The pore system as a whole is approximated by the penetrable-concentric-shell or “cherry-pit” model, which consists of spheres that are partially penetrable. The corresponding hard cores form a random packing of hard spheres. The goodness-of-fit of the model is tested by means of information available from planar sections: the section profile radius distribution and the pair correlation function of profile centers.     

Data Analysis and Modeling of Constant Pressure Batch Dewatering of Fine Particle Suspensions

The problems of data analysis and modeling of experimental constant pressure batch dewatering of materials forming compressible cakes are considered. Dewatering in these materials is typically completed in two stages, viz. cake formation and cake consolidation. A data representation method especially useful for determining the transition point between the filtration and consolidation stages, as well as for comparing accuracy of model predictions, is illustrated. It is shown that dewatering occurs via one of three qualitatively different pathways. A simplified model for engineering analysis of the process is presented. A time-invariant spatially uniform volume fraction of solids approximation is invoked in the cake formation stage. A time-dependent spatially uniform volume fraction of solids assumption is made in the cake consolidation stage. The two models contain four model parameters and have a common physical basis in Darcy's law. Interrelationships between key process parameters are determined and employed to predict the temporal evolution of dewatering in the cake consolidation stage as well as the end point of dewatering.     

灰色关联分析和多元二次非线性回归分析模型研究及应用

基于大庆油田采油二厂压裂措施资料,运用灰色关联分析方法选取对裂缝导流能力影响较大的因素,然后运用多元二次回归分析做进一步的定量研究,并与DPS系统的分析结果进行对比。结果表明,灰色关联分析可以较好的得到与裂缝导流能力关系密切的因素,回归分析可以得出因素间的具体定量关系,且回归分析计算的精度较高,多元二次回归分析和DPS平均拟合误差分别为0.940%、0.916%,预测平均误差分别为1.850%、1.831%,研究为油田开发动态数据规律研究提供了有效的方法。     

统计数据的启示

列举了若干统计数据,说明我国涂料业主导思想和创新能力尚需提高。     

Statistical modeling of electrochemical removal of sodium in fermented food composts

Electrochemical removal of sodium ion from fermented food composts was analyzed and statistically modeled by response surface methodology (RSM). Empirical models were developed to describe relationships between the operating variables (operation time, current density and water contents) and three responses (removal efficiency, energy expenditure and energy efficiency). Statistical analysis indicated that operation time and current density have significant effect on all responses. Good agreement between predicted and measured values confirmed the usefulness of the model. The models were verified by additional experimental at optimum conditions.     

乾安油田东部地区葡萄花油层沉积微相研究

根据岩芯和钻测井资料,以地质相、测井相分析为基础,对乾安油田东部地区葡萄花油层进行了详细的沉积相研究,在研究层段识别出了三角洲平原分流河道、分流河道间、天然堤、席状砂等微相。在对葡油层精细划分与对比、单砂体研究基础上,详细分析沉积微相的平面展布特征。     

简述大数据在环境保护中的作用

随着生态文明建设的不断发展,生态文明体制的深化改革,以及大数据、"互联网+"等信息技术的迅速发展,大数据技术已成为推进生态文明建设的重要手段,在生态环境保护中的作用越来越明显。目前,大数据技术在环境质量监测、环境管理、环境政策及法治以及环境影响评价等四个方面均有一定的应用并取得了一定的成果,本文从这四个角度简单描述了大数据在生态环境保护中的具体作用。