在线气体分析系统在炼钢厂的应用

介绍宣钢炼钢厂转炉煤气回收过程的在线气体分析,比较激光分析仪和抽气式气体分析仪的工作原理及特点。     

处理器验证激励在线筛选技术

如何生成高质量的验证激励是功能验证中的核心问题之一.随着功能验证的不断进行,验证激励的有效性也随之降低.为了提高验证激励的质量,提出一种在线筛选技术来处理验证激励.该技术采用单分类支持向量机来在线地构建分类器,以对新生成的验证激励是否冗余进行预测,如果是冗余的,则不进入仿真阶段进行仿真.在此基础上,进一步提出指令序列核函数来衡量不同指令序列的相似程度.实验结果表明,与约束随机生成技术相比,文中技术可以减少约83%的验证激励及79%的验证时间.     

基于工作过程的电子商务在线作业系统分析与设计

首先对工作过程的意义进行阐述,然后分析电子商务课程特点,最后对该在线作业管理系统做出简要的概述,分析该系统功能需求与业务流程设计,并对该系统的数据库设计与数据组织存储进行详细的分析,为进一步设计开发该系统做好铺垫。     

酒店信息搜索系统设计

讲解使用Google Map API确定酒店地理位置,并对酒店周边的信息进行搜索。     

校园电子商务系统设计

针对校园电子商务的产生和发展进行了阐述,对校园电子商务的功能模块进行设计和描述,提出了校园电子商务带来的影响,并探讨了校园电子商务在信用、物流、市场规划、管理模式、安全支付等方面存在的问题。     

病理学精品课程网站“在线测试”的建设和应用探讨

介绍了病理学精品课程网站的建设以及在线考试系统的实现技术,从提高网站建设和在线测试质量的角度研究探讨了在线测试系统。该系统对病理学课程教学质量和水平的提高能起到积极的促进作用,并可在其他课程的标准化考试中推广应用。     

一种具有平衡标签预测能力的在线哈希算法

针对传统离线哈希算法训练模型耗时、占用内存大和不易更新模型的问题,以及现实图像集的标签存在大量损失的现象,提出了一种能够平衡标签预测的在线哈希算法（BLPOH）。BLPOH通过标签预测模块生成预测标签,并融合残缺的真实标签,能够有效缓解因标签损失导致的模型性能下降。观察到标签存在分布不平衡现象,提出标签类别相似性平衡算法并应用于标签预测模块,提升标签预测的准确性。将旧数据的信息加入哈希函数的在线更新过程,提升模型对旧数据的兼容性。通过在两个广泛使用的数据集上进行实验,并和一些当前先进的算法进行对比,结果证实了BLPOH的优越性。     

The impact of risk and protective factors on online teaching experience in high school Italian teachers during the COVID-19 pandemic

The lockdown due to COVID-19 in Italy resulted in the sudden closure of schools, with a shift from traditional teaching to the online one. Through an online questionnaire, this survey explores teachers' experience of online teaching, the level of risk factors (e.g., stress) and protective factors (e.g., locus of control) and their impact on satisfaction levels during the social distancing. One hundred seven high school teachers from Lombardy, an Italian region very affected by the COVID-19 outbreak, participated. Results show that depression and stress are the main predictors of satisfaction levels for online teaching. In addition, coping, locus of control and self-efficacy emerge as important protective factors. Finally, although there is great satisfaction with the online teaching experience, critical elements emerged. This study is relevant because it describes the critical elements of the online teaching experience, and identifies some protective factors and the main risk factors in teachers operating in an area strongly marked by social restrictions imposed by the pandemic. High school teachers emerge as a sub-group of the general population with specific psychological reactions. Considering the results, it is possible to suggest providing high-quality educational support and crisis-psychological oriented services to teachers, and help to maintain the psychological well-being.     

Promoting the integration of technology in teaching: An analysis of the factors that increase the intention to use technologies among Italian teachers

Background: The rapid spread of COVID-19 forced many countries to adopt severe containment measures, transferring all didactic activities into virtual environments. However, the integration of technology in teaching may present difficulties, especially in some countries, such as Italy. Objectives: The present study analyzed how the two main factors of the Technology Acceptance Model (TAM), namely perceived usefulness and perceived ease of use, combined with online teaching self-efficacy, were associated with the intention to use technology to teach. We posited a moderated moderation model in which perceived usefulness represented the main predictor, with self-efficacy and perceived ease of use as moderators of intention to use technology to teach. Method: The model was tested through multiple regressions, using the PROCESS macro on SPSS 26 with a sample of 178 upper secondary school teachers in Italy. Results and conclusions: Regressions showed that each variable significantly predicted the intention to use technology. In addition, a moderation effect of self-efficacy on the perceived usefulness of using technology was found for medium and high-level of perceived ease of use of technology. Implications: The present study provides targeted implications for distance education policy and practice to promote its adoption (or the blended modality) in Italian upper schools.     

Land‐use dynamic discovery based on heterogeneous mobility sources

Nowadays, cities are the most relevant type of human settlement and their population has been endlessly growing for decades. At the same time, we are witnessing an explosion of digital data that capture many different aspects and details of city life. This allows detecting human mobility patterns in urban areas with more detail than ever before. In this context, based on the fusion of mobility data from different and heterogeneous sources, such as public transport, transport‐network connectivity and Online Social Networks, this study puts forward a novel approach to uncover the actual land use of a city. Unlike previous solutions, our work avoids a time‐invariant approach and it considers the temporal factor based on the assumption that urban areas are not used by citizens all the time in the same manner. We have tested our solution in two different cities showing high accuracy rates.