虚拟视景下数字化军校全息强化数据感知

构建数字化军校全息强化数据感知模型,实现对课堂及教学过程的三维虚拟视景仿真重建。提出基于云端一体化数据融合和三维虚拟视景重构的数字化军校全息强化数据感知模型。采用多模态的全息三维视觉重组技术建立军校全息信息管理的视觉特征采样模型,结合三维虚拟场景的层次化结构分析,进行数字化军校教学场景特征重组,在线程分配和用户自主交互的三维图模型中实现对数字化军校全息强化的数据特征筛选和清洗,基于场景渲染和帧误差补偿技术,进行数字化军校教学场景三维可视化重构和视景仿真过程中的误差补偿控制,提高数字化军校全息强化数据感知能力。仿真结果表明,采用该方法进行数字化军校全息信息感知,提高了三维视景重构能力,视景重建的视觉逼真度较高。

数据监督促民生,诉求件件有着落——淄川区人大常委会运用大数据强化对政府部门工作监督

淄博市人大常委会审议通过了《关于运用淄博12345政务服务热线大数据依法强化对市政府部门工作监督的决议》,淄博市淄川区人大常委会认真贯彻落实《决议》,把政府部门办理政务服务热线群众诉求列入今年专项工作评议内容并赋予较重分值。

探究强化大数据分析推进反窃电工作

随着电力大数据技术的不断发展和完善,电力大数据技术已经被广泛应用于反窃电检查及排查中。应用电力大数据技术进行反窃电系统设计,可以更加准确地排查出窃电风险,从而对维护供电市场秩序、确保居民用电安全、维护国家社会稳定等产生重要的意义。近年来,社会上陆续出现了一些窃电的事件,此类窃电作案方式流动性大,隐蔽性强,甚至出现了一些具有一定专业技术手段的窃电方法,而我们的用电检查人员还停留在传统的查窃电方法上,缺乏利用新的技术手段防范窃电新技术,未能及时发现窃电现象。因此有必要对目前新形势下对现有平台进行数据分析、探讨和研究,有效支撑反窃电工作。 结合这些反窃电流程与方法将电力大数据技术进行科学的应用,有助于充分提升反窃电工作效率,对传统的人工反窃电排查产生重要的优化作用。

模糊先验引导的高效强化学习移动机器人导航

针对移动机器人仅使用RGB D相机在室内场景下执行坐标点主动视觉导航任务,提出了一种基于模糊先验引导的高效强化学习控制算法,设计了一种先验与强化学习的融合控制方式。结果表明,所提出的融合控制方法能够在确保较好的导航准确率基础上,避免训练中无意义的探索并缩短强化学习训练时长,实现强化学习策略的高效学习。

Evaluation of straightening capacity of plate roll straightener

Straightening machine is widely used for improving the quality of the defective mild steel plates.In general,the capacity of straightening machine is affected by material properties,the initial shape of the incoming plate and the plastic ratio.The mechanics model describing the capacity of the machine was developed.The deviation of the straightening capacity curves was studied.Then,the presented model was evaluated by comparative study to filed production data.Finally,the influences of overstretch,straightening speed,strengthening coefficient,elastic modulus,width of the plate on the straightening capacity were studied.It is convenient to determine whether the plate can be straightened or not by a series of straightening capacity curves.The straightening speed,width of the plate and elastic modulus of the material are more sensitive to the straightening capacity than the strengthening coefficient.

Multiple Cropping Intensity in China Derived from Agro-meteorological Observations and MODIS Data

Double-and triple-cropping in a year have played a very important role in meeting the rising need for food in China.However,the intensified agricultural practices have significantly altered biogeochemical cycles and soil quality.Understanding and mapping cropping intensity in China′s agricultural systems are therefore necessary to better estimate carbon,nitrogen and water fluxes within agro-ecosystems on the national scale.In this study,we investigated the spatial pattern of crop calendar and multiple cropping rotations in China using phenological records from 394 agro-meteorological stations(AMSs)across China.The results from the analysis of in situ field observations were used to develop a new algorithm that identifies the spatial distribution of multiple cropping in China from moderate resolution imaging spectroradiometer(MODIS)time series data with a 500 m spatial resolution and an 8-day temporal resolution.According to the MODIS-derived multiple cropping distribution in 2002,the proportion of cropland cultivated with multiple crops reached 34%in China.Double-cropping accounted for approximately 94.6%and triple-cropping for 5.4%.The results demonstrat that MODIS EVI(Enhanced Vegetation Index)time series data have the capability and potential to delineate the dynamics of double-and triple-cropping practices.The resultant multiple cropping map could be used to evaluate the impacts of agricultural intensification on biogeochemical cycles.

Intensification of Deep Hydrodesulfurization Through a Two-stage Combination of Monolith and Trickle Bed Reactors

Deep hydrodesulfurization （HDS） is an important process to produce high quality liquid fuels with ultra-low sul- fur. Process intensification for deep HDS could be implemented by developing new active catalysts and/or new types of reactors. In this work, the kinetics of dibenzothiophene （DBT） hydrodesulfurization over Ni-P/SBA-15/ cordierite catalyst was investigated at 340-380 ℃ and 3.0-5.0 MPa. The first-order reaction model with respect to both DBT and H2 was used to fit the kinetics data in a batch recycle operation system. It is found that both the activation energy and rate constant over the Ni-P monolithic catalyst under our operating conditions are close to those over conventionally used HDS catalysts. Comparative performance studies of two types of reactors, i.e., trickle bed reactor and monolithic reactor, were performed based on reactor modeling and simulation. The results indicate that the productivity of the monolithic reactor is 3 times higher than that of the trickle bed reactor on a catalyst weight basis since effective utilization of the catalyst is higher in the monolithic reactor, but the volumetric productivity of the monolithic reactor is lower for HDS of DBT. Based on simulation results, a two- reactor-in-series configuration for hydrodesulfurization is proposed, in which a monolithic reactor is followed by a tickled bed reactor so as to attain intensified performance of the system converting fuel oil of different sulfur-containing compounds. It is illustrated that the two reactor scheme outperforms the trickle bed reactor both on reactor volume and catalyst mass bases while the content of sulfur is reduced from 200 μg·g-1 to about 10 μ·g-1.

Fortified Financial Forecasting Models Based on Non-Linear Searching Approaches

The paper＇s aim is how to forecast data with variations involving at times series data to get the best forecasting model. When researchers are going to forecast data with variations involving at times series data （i.e., secular trends, cyclical variations, seasonal effects, and stochastic variations）, they believe the best forecasting model is the one which realistically considers the underlying causal factors in a situational relationship and therefore has the best ＂track records＂ in generating data. Paper＇s models can be adjusted for variations in related a time series which processes a great deal of randomness, to improve the accuracy of the financial forecasts. Because of Na＇fve forecasting models are based on an extrapolation of past values for future. These models may be adjusted for seasonal, secular, and cyclical trends in related data. When a data series processes a great deal of randomness, smoothing techniques, such as moving averages and exponential smoothing, may improve the accuracy of the financial forecasts. But neither Na＇fve models nor smoothing techniques are capable of identifying major future changes in the direction of a situational data series. Hereby, nonlinear techniques, like direct and sequential search approaches, overcome those shortcomings can be used. The methodology which we have used is based on inferential analysis. To build the models to identify the major future changes in the direction of a situational data series, a comparative model building is applied. Hereby, the paper suggests using some of the nonlinear techniques, like direct and sequential search approaches, to reduce the technical shortcomings. The final result of the paper is to manipulate, to prepare, and to integrate heuristic non-linear searching methods to serve calculating adjusted factors to produce the best forecast data.

提高电子政务信息共享平台数据质量的对策与方法——一个省级信用信息服务平台数据处理实例

探讨了电子政务信息共享模式及其数据质量要求,通过"江苏省企业信用基础信息数据库和服务平台"的建设实践,分析了数据归集与共享中存在的质量问题,从技术角度论述了提高数据质量的对策和方法,并提出一个针对省级信用信息服务平台的数据质量评估模型。

小学数学教学中核心素养的渗透

小学生处在教育教学的启蒙时期,也是基础阶段,应当让学生准确地掌握数学知识点,培养学生的各种能力,以督促他们更好地进行学习,教师在课堂教学中,应当以培养学生的核心素养为重,使学生离开了课堂,离开了学校以后,能够用数学的眼光去发现问题,用数学的思维去分析问题,用数学的方法解决问题。

State Sampling Dependence of Hopfield Network Inference

The fully connected Hopfield network is inferred based on observed magnetizations and pairwise correlations.We present the system in the glassy phase with low temperature and high memory load.We find that the inference error is very sensitive to the form of state sampling.When a single state is sampled to compute magnetizations and correlations,the inference error is almost indistinguishable irrespective of the sampled state.However,the error can be greatly reduced if the data is collected with state transitions.Our result holds for different disorder samples and accounts for the previously observed large fluctuations of inference error at low temperatures.

Research on the Office Automation System Development and Practice based on Database Optimization and Security Enhancement Technology

In the paper, we conduct research on the office automation system development and practice based on database optimization and security enhancement technology. Office automation is with the rapid development of computer technology and puts forward a new concept, the abbreviation for OA, refers to the enterprise through the use of advanced science and technology, the allocation of the information resources in a reasonable manner, so as to improve the work efficiency and quality of staff, auxiliary management to make decisions, to obtain more economic benefits and main including images, text, audio, data and other information collection, and processing and storage. Among them, the office automation is based on the staff as the main body, with advanced scientific technology by combining with computer technology and form comprehensive office mode. Our proposed method serves as the novel paradigm for the development of the office automation which is meaningful.

Program for Solar Water Heating Systems Based on the F-Chart Method

This paper aims at presenting an application developed in Java for optimizing the design of centralized solar water heating systems with forced circulation, based on the f-chart method. The program uses data from the Brazilian Solar Atlas, performance data of flat plate collectors and thermal reservoirs from the standardized tests run within the Brazilian Labeling Program, and values of water consumption of appliances defined by the ABNT. The program finds the inclination of the collector that maximizes the annual solar fraction, or for the winter, and enables the use of arrays in series and parallel collectors. From the investment costs and O ＆ M （operations and maintenance） of solar heating systems, the program carries out economical analysis using classical parameters as net present value, discounted payback and internal rate of return. The program was validated through examples from the book of Duffle ＆ Beckman and also by comparison with the results from a project developed at UFRGS, having obtained good agreement.

欧美央行或集体紧缩

在通胀高企的背景下,海外各大央行的政策空间已经非常狭窄,留给他们的选项或许只有一个,那就是加快货币紧缩。2月通胀数据强化了美联储加息的必要性,但更重要的是,美联储将以怎样的节奏加息?俄乌事件具有“滞胀”效应,对金融市场也造成一定冲击。出于金融稳定考虑,美联储可能在3月议息会议上先加息25 bp,同时暗示如果通胀居高不下,将在接下来的议息会议上加息50 bp。

Thermal contact conductance estimation and experimental validation in hot stamping process

The variation in temperature of the blank would make major contribution to the mechanical properties of final component in hot stamping of ultra high strength steel(UHSS).It is important to use accurate thermal contact conductance(TCC) to carry out finite element simulation of hot stamping for reliable caculation results.In this paper,a flat compression test was performanced on a servo press.A fast response temperature measurement and data acquisition system was designed to obtain the temperature history of blank and die under different pressures.The thermal contact conductance between blank and die was got using an optimization algorithm.The error between the temperature curves using calculated thermal contact conductance and the curves of measurement temperature was analyzed.Result shows that reliable simulation results of temperature can be got through accurate thermal contact conductance.

An explanation of the elliptic flow difference between proton and anti-proton from the UrQMD model with hadron potentials

The time evolution of both proton and anti-proton v2 flows from Au＋Au collisions at √SNN=7.7 GeV are examined by using both pure cascade and mean-field potential versions of the UrQMD model. Due to a stronger repulsion at the early stage introduced by the repulsive potentials and hence much less annihilation probabilities, anti-protons are frozen out earlier with smaller v2 values. Therefore, the experimental data of anti-proton v2 as well as the flow difference between proton and anti-proton can be reasonably described with the potential version of UrQMD.

Modeling Dynamic Evolution of Online Friendship Network

In this paper,we study the dynamic evolution of friendship network in SNS(Social Networking Site).Our analysis suggests that an individual joining a community depends not only on the number of friends he or she has within the community,but also on the friendship network generated by those friends.In addition,we propose a model which is based on two processes:first,connecting nearest neighbors;second,strength driven attachment mechanism.The model reflects two facts:first,in the social network it is a universal phenomenon that two nodes are connected when they have at least one common neighbor;second,new nodes connect more likely to nodes which have larger weights and interactions,a phenomenon called strength driven attachment(also called weight driven attachment).From the simulation results,we find that degree distribution P(k),strength distribution P(s),and degree-strength correlation are all consistent with empirical data.