网络技术专业校内生产性实训及效果分析

对北京信息职业技术学院网络技术专业校内生产性实训的实施过程和效果进行了总结与分析。从生产性实训设计思路、生产性实训载体、生产性实训的效果三个方面进行了论述。分析了网络技术专业校内生产性实训的设计思路、项目的组织、实训活动的安排以及实训的效果。     

基于BS的人才管理系统的设计与实现

目前计算机、网络技术的发展和应用日益普及,大力发展人才开发事业是当前任何企事业单位的迫切需求,使得目前人才库建设的任务日益繁重,借助于计算机网络实现人才库系统建设是一个重要的发展趋势。本文根据地方政府管理部门对人才资源的管理需求,分析了建设人才资源数据库系统的功能要求与需求特点,并根据系统的特点,分析了人才资源数据库的实体一关系,对于重要功能模块进行了设计与测试。     

基于asp的学籍管理系统的分析

自2001年高校扩大招生以来,高校的学生也逐年增加,这就给高校的学籍管理带来了更加信繁杂的管理。这就为学校学籍管理系统提出了更加高的性能要求。所以,结合现有的技术,开发一款性能稳定、数据安全、高效的学籍管理系统就显的格外重要,本文结合我校的实际学籍管理工作,对学籍管理系统进行了分析,并提出了解决方案。     

A Cellular Automata Based Rainfall-Runoff Model for Urban Inundation Analysis Under Different Land Uses

Recently many runoff models based on cellular automaton (CA) have been developed to simulate floods; however, the existing models cannot be readily applied to complex urban environments. This study proposes a novel rainfall-runoff model based on CA (RRCA) to simulate inundation. Its main contributions include a fine runoff generation process that considers 12 urban scenarios rather than a single land use type and the confluence process determined by the new transition rules considering water supply and demand (WS-WD transition rules). RRCA was compared with another CA based flood model (E2DCA). With the benchmark model, the results showed that there was good agreement, with an R-squared greater than 0.9, and that RRCA was more sensitive to waterlogging levels than E2DCA. Furthermore, the simulated vegetation interception, infiltration and drainage processes had varying degrees of impact on waterlogging. Corresponding measures can be taken in urban flood management according to the identification of areas experiencing drainage difficulties.

     

江阴市"十四五"水利高质量发展规划的思考

总结江阴市"十三五"水利发展规划在水安全、水资源、水生态、农村水利、水管理服务及水利发展保障等方面的完成情况.分析江阴市水利发展存在的主要短板、问题.围绕建设高质量的水安全保障体系、水资源配置体系、水生态治理体系、水利管理体系、水利服务体系,系统提出江阴市"十四五"水利高质量发展规划思路.     

Hot corrosion ofα-SiC ceramics by V2O5 melt

The corrosion behaviour of-SiC in V₂O₅ melt has been investigated at elevated temperatures. The corrosion products on the surface of the specimen are removed using HF. The morphologies are also examined. From the observations of bubble formation in the scale and the temperature dependence of the corrosion rate, a kinetic mechanism is proposed. Based on the consistency of the plotted data with the proposed equation and high values of surface reaction rate constant, a diffusion controlling process has been developed.     

肠道杆菌的扫描电镜观察

我们用扫描电镜观察肠道杆菌种(Enterobacteriaceae)中的四种细菌,大肠埃希氏杆菌(Escherichiacoli),普通变形杆菌(Proteus vulgaris),伤寒沙门氏菌(Salmonella typhi)和福氏志贺氏菌(Shigella Flexneri)。未处理的菌落标本,菌落表面都可形成一层厚薄不同的表膜(Surface film)。四种细菌菌落的表膜,形状不一,千姿百态。适当处理后的菌落标本,则可显示菌体的本来面目。四种细菌菌体在菌落表面的分布和排列,也是各不相同,千差万别。本文根据扫描电镜的观察,对四种不同菌落进行了讨论。     

Feasibility of the indirect determination of blast-induced rock movement based on three new hybrid intelligent models

Engineering with Computers - The indirect and accurate determination of blast-induced rock movement has important significance in the reduction of ore loss and dilution and in the protection of...     

Maximizing learning without sacrificing the fun: Stealth assessment,adaptivity and learning supports in educational games

In this study, we investigated the validity of a stealth assessment of physics understanding in an educational game, as well as the effectiveness of different game-level delivery methods and various in-game supports on learning. Using a game called Physics Playground, we randomly assigned 263 ninth- to eleventh-grade students into four groups: adaptive, linear, free choice and no-treatment control. Each condition had access to the same in-game learning supports during gameplay. Results showed that: (a) the stealth assessment estimates of physics understanding were valid—significantly correlating with the external physics test scores; (b) there was no significant effect of game-level delivery method on students' learning; and (c) physics animations were the most effective (among eight supports tested) in predicting both learning outcome and in-game performance (e.g. number of game levels solved). We included student enjoyment, gender and ethnicity in our analyses as moderators to further investigate the research questions.     

Stock Price Forecasting: An Echo State Network Approach

Forecasting stock prices using deep learning models suffers from problems such as low accuracy, slow convergence, and complex network structures. This study developed an echo state network (ESN) model to mitigate such problems. We compared our ESN with a long short-term memory (LSTM) network by forecasting the stock data of Kweichow Moutai, a leading enterprise in China’s liquor industry. By analyzing data for 120, 240, and 300 days, we generated forecast data for the next 40, 80, and 100 days, respectively, using both ESN and LSTM. In terms of accuracy, ESN had the unique advantage of capturing nonlinear data. Mean absolute error (MAE) was used to present the accuracy results. The MAEs of the data forecast by ESN were 0.024, 0.024, and 0.025, which were, respectively, 0.065, 0.007, and 0.009 less than those of LSTM. In terms of convergence, ESN has a reservoir state-space structure, which makes it perform faster than other models. Root-mean-square error (RMSE) was used to present the convergence time. In our experiment, the RMSEs of ESN were 0.22, 0.27, and 0.26, which were, respectively, 0.08, 0.01, and 0.12 less than those of LSTM. In terms of network structure, ESN consists only of input, reservoir, and output spaces, making it a much simpler model than the others. The proposed ESN was found to be an effective model that, compared to others, converges faster, forecasts more accurately, and builds time-series analyses more easily.