一种基于逻辑的洗衣机模糊控制器

一般的洗衣机模糊控制器都是基于经验的模糊控制,其相应的模糊语言规则并没有揭示输入输出的逻辑关系。一种基于逻辑的洗衣机控制器设计方法被提出。这个例子说明基于逻辑的模糊控制与基于经验的模糊控制相比,基于逻辑的模糊控制更合理更简便。通过控制输出的比较,说明在达到相同精度的条件下,基于逻辑的模糊控制需要计算量更少。     

叠加式力标准机部分计量特性和检测方法浅析

针对叠加式力标准机部分计量特性和检测方法进行分析,提出新的技术规范。     

小议“凯旋一号”超高层基础选型

首先阐述了项目"凯旋一号"工程概况,然后对筏板基础及旋挖桩与长螺旋压灌桩的优缺点的进行对比,最后得出了对于该项目采用筏板基础较好的结论。     

基于成像传感器噪声的相机源辨识算法研究

通过分析数码相机的成像特点,文章提出了一种基于图像噪声的相机源辨识方法。通过抽取反映传感器噪声的特征,并训练分类器实现相机型号的辨识。实验结果表明所提取的新特征比前面算法所提取的特征能更好的体现同一品牌相机的模式是噪声的特点,因此具有更高的识别率,且鲁棒性更好。     

喷油螺杆空压机在牙轮钻机上的使用与改进

为提高空压机的利用效率,降低空压机的故障率及使用成本,对喷油螺杆空压机在使用过程中出现的问题进行了分析,探索了相应的改进方法,改进后空压机的故障率及使用成本明显降低,牙轮钻机的使用效率明显提高。     

Using automated analysis to assess middle school students' competence with scientific argumentation

Argumentation is fundamental to science education, both as a prominent feature of scientific reasoning and as an effective mode of learning—a perspective reflected in contemporary frameworks and standards. The successful implementation of argumentation in school science, however, requires a paradigm shift in science assessment from the measurement of knowledge and understanding to the measurement of performance and knowledge in use. Performance tasks requiring argumentation must capture the many ways students can construct and evaluate arguments in science, yet such tasks are both expensive and resource-intensive to score. In this study we explore how machine learning text classification techniques can be applied to develop efficient, valid, and accurate constructed-response measures of students' competency with written scientific argumentation that are aligned with a validated argumentation learning progression. Data come from 933 middle school students in the San Francisco Bay Area and are based on three sets of argumentation items in three different science contexts. The findings demonstrate that we have been able to develop computer scoring models that can achieve substantial to almost perfect agreement between human-assigned and computer-predicted scores. Model performance was slightly weaker for harder items targeting higher levels of the learning progression, largely due to the linguistic complexity of these responses and the sparsity of higher-level responses in the training data set. Comparing the efficacy of different scoring approaches revealed that breaking down students' arguments into multiple components (e.g., the presence of an accurate claim or providing sufficient evidence), developing computer models for each component, and combining scores from these analytic components into a holistic score produced better results than holistic scoring approaches. However, this analytical approach was found to be differentially biased when scoring responses from English learners (EL) students as compared to responses from non-EL students on some items. Differences in the severity between human and computer scores for EL between these approaches are explored, and potential sources of bias in automated scoring are discussed.     

Destroy All Humans: The Dematerialisation of the Designer in an Age of Automation and its Impact on Graphic Design—A Literature Review

Digital automation is on the rise in a diverse range of industries. The technologies employed here often make use of artificial intelligence (AI) and its common form, machine learning (ML) to augment or replace the work completed by human agents. The recent emergence of a variety of design automation platforms inspired the authors to undertake a review of the research literature on the impact of Automation, AI and ML on visual communication, and its subset practice of graphic design, with a view to understanding the implications for the education of practitioners entering that specific field. This review discovered that there was relatively little research published on the topic but what did exist noted that graphic design as we have known it has an uncertain future. Furthermore, the scant literature argued for a shift in educational and professional focus away from the aesthetic and technical skills required to design visual modes of communication and towards a deeper engagement with the softer, more human skills associated with negotiation, facilitation and judgement. The paucity of literature on this topic suggests to the authors that visual communication design education and the industry are poorly prepared for the impact of automation, AI and ML on them.     

基于深度学习的领域知识对齐模型研究:知识网络视角

随着大数据的迅速发展,知识网络在不同语言、不同领域和不同模态等情境下呈现高度多样性和复杂性,如何对齐与整合多源情境下的异构知识网络,成为研究者所面临的严峻挑战。本文在知识网络深度表示学习的基础上,提出一种由知识网络构建、跨语言网络表示学习和统计机器学习三个模块构成的知识网络对齐(knowledge network alignment,KNA)模型。为验证模型的有效性,在中英文双语知识网络数据集上开展实证研究,借助于网络表示学习算法将异构知识网络表征到同一空间,利用已知的对齐链接来训练统计机器学习模型,并通过模型来预测未知的节点对齐链接。KNA模型在跨语言共词网络对齐任务中取得Precision@1值为0.7731,高于基线方法 (0.6806),验证了KNA模型在跨语言知识网络对齐上的有效性。研究结果对于改进知识网络的节点对齐效果,促进多源情境下的异构知识网络融合具有重要意义。     

Reflections on gaze data in statistics education

Gaze data are still uncommon in statistics education despite their promise. Gaze data provide teachers and researchers with a new window into complex cognitive processes. This article discusses how gaze data can inform and be used by teachers both for their own teaching practice and with students. With our own eye-tracking research as an example, background information on eye-tracking and possible applications of eye-tracking in statistics education is provided. Teachers indicated that our eye-tracking research created awareness of the difficulties students have when interpreting histograms. Gaze data showed details of students' strategies that neither teachers nor students were aware of. With this discussion paper, we hope to contribute to the future usage and implementation of gaze data in statistics education by teachers, researchers, educational and textbook designers, and students.     

基于“数控”职业证书专业课程体系的创新与考核

从“专业与行业对接”“课程标准与职业标准对接”“岗位技能考核体系与专业课程体系对接”的角度,探讨“数控机床操作调整工”职业技能鉴定考证的课程体系搭建问题,即实现“以考证促专业建设,以考证提教学质量”。并指出了如何实现最优化的考证考核方式,对已实现“双证书制”高职院校的课程改革和制度创新提供一定的借鉴。