An Efficient Framework for Utilizing Underloaded Servers in Compute Cloud

In cloud data centers, the consolidation of workload is one of the phases during which the available hosts are allocated tasks. This phenomenon ensures that the least possible number of hosts is used without compromise in meeting the Service Level Agreement (SLA). To consolidate the workloads, the hosts are segregated into three categories: normal hosts, under-loaded hosts, and overloaded hosts based on their utilization. It is to be noted that the identification of an extensively used host or underloaded host is challenging to accomplish. Threshold values were proposed in the literature to detect this scenario. The current study aims to improve the existing methods that choose the underloaded hosts, get rid of Virtual Machines (VMs) from them, and finally place them in some other hosts. The researcher proposes a Host Resource Utilization Aware (HRUAA) Algorithm to detect those underloaded and place its virtual machines on different hosts in a vibrant Cloud environment. The mechanism presented in this study is contrasted with existing mechanisms empirically. The results attained from the study establish that numerous hosts can be shut down, while at the same time, the user's workload requirement can also be met. The proposed method is energy-efficient in workload consolidation, saves cost and time, and leverages active hosts.     

含虚拟同步机的微电网频率稳定约束优化调度模型研究

多类型虚拟同步机(virtual synchronous machine,VSM)的混杂并网增加了微电网运行控制的复杂性,不同资源的功率协调控制与能量管理是含VSM的微电网需解决的关键问题。该文计及各类型VSM(风机VSM、光伏VSM和储能VSM)的虚拟惯量和有功调频特性,对含VSM的微电网整体惯量和备用容量需求进行修正计算。在此基础上,考虑微电网在并网与孤岛运行模式下频率响应能力的差异性,构建一种含多类型VSM的微电网频率稳定约束优化调度模型,以提升微电网在不同扰动场景下的稳健运行能力。在改进的IEEE 13节点微电网系统中开展算例分析,仿真结果表明所提模型相较传统模型具有更好的频率适应性。     

考虑负荷频率特性的新能源场站一次调频控制方法

随着大容量高比例的新能源集中接入电网,传统电网可用的频率响应资源占比逐步减少。为了充分发挥新能源场站参与电网快速一次调频的潜力,提高电网的电能质量,在新能源场站常规有功-频率下垂控制方法基础上,提出了一种考虑负荷频率特性的新能源场站一次调频控制方法,该方法提高了系统频率的抗扰动能力。采用MATLAB/Simulink对典型负荷频率特性的新能源场站一次调频控制方法进行了仿真验证,结果表明所提出的控制方法可以显著提高系统频率稳定性,对新能源场站一次调频具有重要参考意义。     

线上教学案例

当因疫情原因无法进行线下授课时,如何做好线上授课就显得非常重要。文章主要从以下方面论述了作者的线上教学情况,即课前准备、授课方式、课后作业、课后巩固、考试。     

Exploring age and gender differences of computational thinkers in primary school: A developmental perspective

Over the past decade, the call to foster computational thinking (CT) in every child has received considerable attention. However, there is little understanding of whether children are developmentally ready to think computationally and what specific CT concepts and skills can be developed at various ages. This study explored the developmental and gender differences in CT skills of 197 Grade 4–6 students (aged 9–13) before being exposed to instruction and investigated the age–gender interaction effects on their CT acquisition in an intervention combining both programming and non-programming (unplugged) activities. Results show that students' CT skills followed a developmental progression before instruction. Gender difference across ages was insignificant in conditionals, logical operators, pattern recognition and generalization skills. Additionally, students of different ages developed CT differently during the intervention, and their CT acquisition was unaffected by gender. Implications for practice and research in CT education were discussed.     

热泵季节性能系数的研究

热泵是开发可再生能源的机械。它通过使用一份电能或机械能,获得数倍的可再生能源,是重要的节能技术和环保技术。本文重点研究热泵的季节性能系数。由于环境温度的变化或供热负荷的变化,热泵的瞬时特性可能变化,其季节性能系数的分析有重要的理论意义和实用价值。文中建议把热泵可再生能源贡献率的计算方法作为国家标准,以促进我国热泵制造产业发展,大力推广热泵节能技术。     

Global estimates of evapotranspiration and gross primary production based on MODIS and global meteorology data

The simulation of gross primary production (GPP) at various spatial and temporal scales remains a major challenge for quantifying the global carbon cycle. We developed a light use efficiency model, called EC-LUE, driven by only four variables: normalized difference vegetation index (NDVI), photosynthetically active radiation (PAR), air temperature, and the Bowen ratio of sensible to latent heat flux. The EC-LUE model may have the most potential to adequately address the spatial and temporal dynamics of GPP because its parameters (i.e., the potential light use efficiency and optimal plant growth temperature) are invariant across the various land cover types. However, the application of the previous EC-LUE model was hampered by poor prediction of Bowen ratio at the large spatial scale. In this study, we substituted the Bowen ratio with the ratio of evapotranspiration (ET) to net radiation, and revised the RS-PM (Remote Sensing-Penman Monteith) model for quantifying ET. Fifty-four eddy covariance towers, including various ecosystem types, were selected to calibrate and validate the revised RS-PM and EC-LUE models. The revised RS-PM model explained 82% and 68% of the observed variations of ET for all the calibration and validation sites, respectively. Using estimated ET as input, the EC-LUE model performed well in calibration and validation sites, explaining 75% and 61% of the observed GPP variation for calibration and validation sites respectively.Global patterns of ET and GPP at a spatial resolution of 0.5° latitude by 0.6° longitude during the years 2000-2003 were determined using the global MERRA dataset (Modern Era Retrospective-Analysis for Research and Applications) and MODIS (Moderate Resolution Imaging Spectroradiometer). The global estimates of ET and GPP agreed well with the other global models from the literature, with the highest ET and GPP over tropical forests and the lowest values in dry and high latitude areas. However, comparisons with observed GPP at eddy flux towers showed significant underestimation of ET and GPP due to lower net radiation of MERRA dataset. Applying a procedure to correct the systematic errors of global meteorological data would improve global estimates of GPP and ET. The revised RS-PM and EC-LUE models will provide the alternative approaches making it possible to map ET and GPP over large areas because (1) the model parameters are invariant across various land cover types and (2) all driving forces of the models may be derived from remote sensing data or existing climate observation networks.     

Using an online tool to support school‐based ICT policy planning in primary education

An important step towards the successful integration of information and communication technology (ICT) in schools is to facilitate their capacity to develop a school‐based ICT policy resulting in an ICT policy plan. Such a plan can be defined as a school document containing strategic and operational elements concerning the integration of ICT in education. To write such a plan in an efficient way is challenging for schools. Therefore, an online tool [Planning for ICT in Schools (pICTos)] has been developed to guide schools in this process. A multiple case study research project was conducted with three Flemish primary schools to explore the process of developing a school‐based ICT policy plan and the supportive role of pICTos within this process. Data from multiple sources (i.e. interviews with school leaders and ICT coordinators, school policy documents analysis and a teacher questionnaire) were collected and analysed. The results indicate that schools shape their ICT policy based on specific school data collected and presented by the pICTos environment. School teams learned about the actual and future place of ICT in teaching and learning. Consequently, different policy decisions were made according to each school's vision on ‘good’ education and ICT integration.     

基于倒排索引的密文数据库检索方法研究

针对实际密文数据库的应用,在全文检索倒排索引技术的基础上,设计了一种通过密文倒排索引文件对其进行快速检索的方法。密文索引文件中主要包含有索引项、相对应的记录主键等信息。检索时,通过用检索词匹配索引文件中的索引项,找到对应的记录主键集合,再根据记录主键集合查询密文数据库,获取相应的密文数据,进行解密即可获取明文数据信息。整个检索过程中不对数据库进行解密,从而实现了在不解密的情况下对密文数据库的快速检索。     

Predicting gross primary production from the enhanced vegetation index and photosynthetically active radiation: Evaluation and calibration

The approach of using primarily satellite observations to estimate ecosystem gross primary production (GPP) without resorting to interpolation of many surface observations has recently shown promising results. Previous work has shown that the remote sensing based greenness and radiation (GR) model can give accurate GPP estimates in crops. However, the feasibility of its application and the model calibration to other ecosystems remain unknown. With the enhanced vegetation index (EVI) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) images and the surface based estimates of photosynthetically active radiation (PAR), we provide an analysis of the GR model for estimating monthly GPP using flux measurements at fifteen sites, representing a wide range of ecosystems with various canopy structures and climate characteristics. Results demonstrate that the GR model can provide better estimates of GPP than that of the temperature and greenness (TG) model for the overall data classified as non-forest (NF), deciduous forest (DF) and evergreen forest (EF) sites. Calibration of the GR model is also conducted and has shown reasonable results for all sites with a root mean square error of 47.18 g C/m²/month. Different coefficients acquired for the three plant functional types indicate that there are shifts of importance among various factors that determine the monthly vegetation GPP. The analysis firstly shows the potential use of the GR model in estimating GPP across biomes while it also points to the needs of further considerations in future operational applications.