土木工程施工课程线上平台教学实践

土木工程施工课程作为土木工程及工程管理专业的学科基础课和核心专业课程,在疫情防控期间"停课不停教""停课不停学"的要求下,通过线上平台进行授课。由于土木工程施工课程内容庞杂、综合性强、实践性强,且章节之间关联性较弱,探究既能使学生快速适应,又能保证教学质量的在线教学方法至关重要。以华南某高校土木工程施工课程为例,基于中国大学MOOC、建筑云课、腾讯课堂、QQ群等线上平台讲授教学内容,并运用问卷调查对课程线上教学效果进行评价。结果表明,线上教学为学生提供了丰富灵活的学习方式,显著提高了学生的自主学习能力,扩大了学生的知识面,达到了较好的学习效果。     

CLOI-NET: Class segmentation of industrial facilities’ point cloud datasets

Shape segmentation from point cloud data is a core step of the digital twinning process for industrial facilities. However, it is also a very labor intensive step, which counteracts the perceived value of the resulting model. The state-of-the-art method for automating cylinder detection can detect cylinders with 62% precision and 70% recall, while other shapes must then be segmented manually and shape segmentation is not achieved. This performance is promising, but it is far from drastically eliminating the manual labor cost. We argue that the use of class segmentation deep learning algorithms has the theoretical potential to perform better in terms of per point accuracy and less manual segmentation time needed. However, such algorithms could not be used so far due to the lack of a pre-trained dataset of laser scanned industrial shapes as well as the lack of appropriate geometric features in order to learn these shapes. In this paper, we tackle both problems in three steps. First, we parse the industrial point cloud through a novel class segmentation solution (CLOI-NET) that consists of an optimized PointNET++ based deep learning network and post-processing algorithms that enforce stronger contextual relationships per point. We then allow the user to choose the optimal manual annotation of a test facility by means of active learning to further improve the results. We achieve the first step by clustering points in meaningful spatial 3D windows based on their location. Then, we apply a class segmentation deep network, and output a probability distribution of all label categories per point and improve the predicted labels by enforcing post-processing rules. We finally optimize the results by finding the optimal amount of data to be used for training experiments. We validate our method on the largest richly annotated dataset of the most important to model industrial shapes (CLOI) and yield 82% average accuracy per point, 95.6% average AUC among all classes and estimated 70% labor hour savings in class segmentation. This proves that it is the first to automatically segment industrial point cloud shapes with no prior knowledge at commercially viable performance and is the foundation for efficient industrial shape modeling in cluttered point clouds.     

Comparison of food values for consumers’ preferences on imported fruits and vegetables within Japan,Taiwan, and Indonesia

International agricultural trade in fruits and vegetables has received much attention as an effective method to create a sustainable agriculture industry for a country. This study focuses on consumers’ perceptions of food values toward imported fruits and vegetables in Japan, Taiwan, and Indonesia by using the Best-Worst Scaling method. Seven food values were examined in this study: labeling product origin, food safety certification, high quality appearance, domestic rarity, price, how the product was grown, and freshness. An online survey was conducted and 1,350 total valid respondents were collected (500 Japanese, 333 Taiwanese, and 517 Indonesian). The Latent Class Multinomial Logit model was used to analyze consumers for each country. Results revealed that food safety certification and freshness were found as the most important and second most important food values for the majority group of consumers in each of these three countries, respectively. However, the remainder of food values do not have the same importance for each country. The study should help governments and international marketers enhance their agricultural trade policies and marketing strategies for these targeted markets.     

Bending capacity of composite girders with Class 3 section

In this research, the flexural behaviour of composite girders under non-monotonic service loads and the bending capacity of composite girders with Class 3 section were studied through experimental work. Three specimens were fabricated and, through the 4-point flexural test, the stiffness and strength of the composite girder under hogging moments were observed. Test specimens were overhanging simple support beams, in total 6 m long. From the test results, the deflection, stiffness, moment-curvature relationship, and strain distribution of the composite girder section under service and ultimate loading were analyzed. The flexural behaviour under reloading-unloading cycles and tension stiffening effects on the mechanical behaviour of composite girders were discussed. The ultimate strength of composite girders with different Class flange sections and a same Class web section were also studied. Test results were analyzed by design equations in Eurocode 3 and 4 for flexural stiffness and sectional resistances. Also, a new simple design equation for the bending capacity of composite girders with Class 3 sections was suggested.     

现有底框砌体结构应用于乙类建筑的加固实践

针对一幢现有的底框砌体结构校舍,结构体系不适用于乙类建筑,但仍需履行当前建筑功能,设计者根据实际情况采用维持原结构体系、对建筑进行全面抗震设计并加固,在原有基础上提高其抗震性能,以满足乙类建筑的抗震要求,可为同类型项目提供参考.     

CDIO模式下化工原理探究式课堂教学改革

我们在化工原理课堂教学中以学习任务为主线,开展探究式教学的改革措施,围绕学生的层次和专业背景精心设计教学案例。教学方案实施过程中,充分体现以学生为中心的理念,对学生系统地进行构思、设计、实现、运作(CDIO模式)的整体训练,提高其发现问题、提出问题和解决问题的能力,并增强其社会交往能力和团队精神。     

Class imbalance learning via a fuzzy total margin based support vector machine

The classification of imbalanced data is a major challenge for machine learning. In this paper, we presented a fuzzy total margin based support vector machine (FTM-SVM) method to handle the class imbalance learning (CIL) problem in the presence of outliers and noise. The proposed method incorporates total margin algorithm, different cost functions and the proper approach of fuzzification of the penalty into FTM-SVM and formulates them in nonlinear case. We considered an excellent type of fuzzy membership functions to assign fuzzy membership values and got six FTM-SVM settings. We evaluated the proposed FTM-SVM method on two artificial data sets and 16 real-world imbalanced data sets. Experimental results show that the proposed FTM-SVM method has higher G_Mean and F_Measure values than some existing CIL methods. Based on the overall results, we can conclude that the proposed FTM-SVM method is effective for CIL problem, especially in the presence of outliers and noise in data sets.     

Implementing flexible hybrid instruction in an electrical engineering course: The best of three worlds?

This study explored a modified version of hybrid instruction, referred to as the flexible hybrid format, in a lower division electrical engineering course offered at a large public university. The objective of the study is to use longitudinal data to investigate the impact of class attendance, out-of-class study time, and motivation on student exam performance. Generalized least squares and fixed effects models were used in the analyses. It was found that class attendance was indispensable; it was associated with exam performance even when all essential course material was made available online and students generally rated the online instruction component to be of higher quality. The benefit of class attendance was then explained by the ICAP hypothesis and spaced learning practice and it was suggested that online education might be more effective in teaching relatively simpler contents. Out-of-class effort significantly predicated performance in previous weeks, but not in the final period. The harmful effect of cramming was cited to explain this phenomenon. Hence, by implication, time management might be an issue in a flexible hybrid environment. Finally, motivation was found to be a robust predicator of performance and its effect was the strongest when the course was at its most challenging stage. Besides, the relationship between motivation and exam performance was likely to be bidirectional, as higher motivation resulted in better performance, which in turn further boosted motivation. Based on current findings, directions for future research were also suggested to verify our claims and improve our implementation.     

Do ozone and boric acid affect microleakage in class V composite restorations?

The aim of this in vitro study was to evaluate the effects of chlorhexidine gluconate (2%), sodium hypochloride (2.5%), ozone gas, and boric acid at different concentrations (1%, 3%, 5%, and 7%) on microleakage from composite restorations.

In a total of 80 extracted human canine teeth, a class V cavity was opened on the buccal surface and the samples were separated into eight groups. In the control group, no procedure was applied for cavity disinfection, then composite restoration (Z250, 3M) was made using single-stage, self-etch adhesive (Single Bond 3M). In the other groups, seven different disinfectants were used, then the cavity was restored. The teeth were split into two in the buccolingual direction, parallel to the long axes. Stain penetration was examined under stereomicroscope and scored. Examination with SEM was made on one sample from each group, selected at random. Statistical evaluations were made using Dunnett C Post Hoc Comparison and Kruskal–Wallis H tests.

In the occlusal region evaluation, the groups with the lowest level of leakage were the 3% and 5% boric acid groups, and the highest levels of microleakage were determined in the chlorhexidine group and the 1% boric acid group. In the gingival region, the lowest level of microleakage was in the 5% boric acid group and the highest levels were determined in the 1% and 7% boric acid groups.

Boric acid disinfectants used at suitable concentrations were not seen to create a risk in respect of microleakage.     

Class 4 stainless steel I beams subjected to fire

Structural elements composed of Class 4 sections are common in stainless steel buildings structures. These thin walled profiles are more susceptible to the occurrence of local buckling. Additionally, in beams the lateral-torsional buckling is also a common failure mode. These instability phenomena are intensified at high temperatures. This work has the main objective of presenting a numerical study on the fire behavior of beams with Class 4 stainless steel sections when subjected to pure bending and high temperatures. The influence of several parameters, as geometrical imperfections and residual stresses, on the ultimate load will be evaluated and comparisons between the numerical results and the Eurocode 3 rules will also be made.