Proceedings of the 2nd World Symposium on Software Engineering最新文献_第5页

The Practice Exploration of "Flipped Classroom" Mode Based on Micro Lesson in Rope Skipping Teaching 基于微课的“翻转课堂”模式在跳绳教学中的实践探索

Proceedings of the 2nd World Symposium on Software Engineering Pub Date : 2020-09-25 DOI: 10.1145/3425329.3426867

Wenbao Li

引用次数: 0

An Analysis Scheme to Interpret Students' Cognitive Process in Error Finding Test 学生认错测验认知过程的分析方案

Proceedings of the 2nd World Symposium on Software Engineering Pub Date : 2020-09-25 DOI: 10.1145/3425329.3425350

Lianzhen Liu, Wei Liu, Xinyu Li, Jing Xu, Wen-Fang Cheng

{"title":"An Analysis Scheme to Interpret Students' Cognitive Process in Error Finding Test","authors":"Lianzhen Liu, Wei Liu, Xinyu Li, Jing Xu, Wen-Fang Cheng","doi":"10.1145/3425329.3425350","DOIUrl":"https://doi.org/10.1145/3425329.3425350","url":null,"abstract":"Finding errors in the source code is a typical kinds of test in the programming courses, which is helpful to assess the students' ability in program comprehension and debugging. In this paper, we propose an analysis scheme to interpret the measured line-level eye movement in an error-finding test of C language. An eye-tracking measurement system is implemented to collect the student's eye movement; during the test, the students select the error lines by mouse click in the web pages. We divide the students' eye movement into multiple cognitive tasks according to their decision actions, i.e. the mouse click events. For each cognitive task, we formulate the line-level program execution sequence around the code line selected by the students. A new metric, namely Matched Movement Ratio (MMR), is proposed to describe the proportion of line-level eye-focus jumping events that matches with the program execution sequence. We validate the calculation of MMR by two case studies, and further utilize this metric to conduct group study for 19 students in a test about bubble-sorting algorithm. Experiment results show that, MMR can differentiate the students by their code tracing performance in error-finding missions. Although our scheme can not infer the whole cognitive process in test, MMR can work as a reference quantifying the students' cognitive efforts tracing the code lines. Our results provide evidences for the teacher to diagnose the weakness of students and provide improvement suggestions in programming courses.","PeriodicalId":213589,"journal":{"name":"Proceedings of the 2nd World Symposium on Software Engineering","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128712819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Research on the Perception of Calligraphy Time Sequence Based on Markov Chain 基于马尔科夫链的书法时间序列感知研究

Proceedings of the 2nd World Symposium on Software Engineering Pub Date : 2020-09-25 DOI: 10.1145/3425329.3425342

Ruimin Lyu, Lilin Mei, Hong-guang Xing, Lei Meng

{"title":"Research on the Perception of Calligraphy Time Sequence Based on Markov Chain","authors":"Ruimin Lyu, Lilin Mei, Hong-guang Xing, Lei Meng","doi":"10.1145/3425329.3425342","DOIUrl":"https://doi.org/10.1145/3425329.3425342","url":null,"abstract":"Sequential restoration relates to the psychological phenomenon that one can imaginatively reconstruct the writing process by observing the stroke traces on a piece of calligraphy. While traditional theory emphasizes this phenomenon as a unique aesthetic feature of calligraphy, and neuroaesthetics studies its biological basis, this paper introduces the idea of quantifying it. In order to quantify sequential restoration, and to explore the factors that affect it, a sequentiality quantization method based on Markov chain is proposed. First, beholders' perception of the sequential order of predefined marker points on the calligraphy work is modeled as a Markov chain. Then, the entropy rate of the Markov model is calculated to measure its uncertainty. Finally, the metric sequentialiy is defined as the normalized negative entropy rate. The feasibility of this method is verified through the actual measurement of the character \"Zou\". The effect of graphic transforms on the sequentiality of single brush stroke was studied, and the result shows that graphic transforms, including mirror and rotation, significantly affect sequentiality. The experiment also shows that the textural details of a brush stroke are not the primary factor in forming the sequential restoration experience, but the viewer's own experience of stroke order is more important.","PeriodicalId":213589,"journal":{"name":"Proceedings of the 2nd World Symposium on Software Engineering","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116665749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Intelligent Safety Monitoring and Early Warning System for Construction Site 建筑工地智能安全监测预警系统

Proceedings of the 2nd World Symposium on Software Engineering Pub Date : 2020-06-02 DOI: 10.1145/3425329.3425331

Zheyuan Hu, Jun Cai, Huiwei Wang, Dehao Zhang, Yang Liu, Xin Li, Yanlong Li, F. Zhao, Hongjun Zhang

{"title":"Intelligent Safety Monitoring and Early Warning System for Construction Site","authors":"Zheyuan Hu, Jun Cai, Huiwei Wang, Dehao Zhang, Yang Liu, Xin Li, Yanlong Li, F. Zhao, Hongjun Zhang","doi":"10.1145/3425329.3425331","DOIUrl":"https://doi.org/10.1145/3425329.3425331","url":null,"abstract":"Faced with the complex environment and difficult construction of infrastructure projects, designing an intelligent safety monitoring and early warning system for construction sites can effectively detect existing violations and reduce the probability of accidents. Existing violation detection methods for construction sites mainly include hand-crafted feature extraction and deep neural network. However, the method of extracting features is usually difficult to design and the architecture of the deep learning-based method is simple, which might lead to poor detection performance in extreme cases (Insufficient light, small detection object, occlusion, etc.) and cannot be used in actual detection environment. Therefore, we improve the existing target detection algorithm by adding image preprocessing module, multi-scale feature fusion module, and repulsion loss term. We also use the KCF algorithm to continuously track targets to identify specific violations. On this basis, we develop an intelligent safety monitoring and early warning system to classify the detected violations and send the information to the responsible person in time, which significantly improves the management capacity at the construction site. Through a series of experiments, we compared the impact of different modules on detection accuracy. The results show that our model has a significant improvement compared to existing methods on our dataset, especially in harsh environments.","PeriodicalId":213589,"journal":{"name":"Proceedings of the 2nd World Symposium on Software Engineering","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132493999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Alternative Effort-optimal Model-based Strategy for State Machine Testing of IoT Systems 物联网系统状态机测试的另一种基于努力优化模型的策略

Proceedings of the 2nd World Symposium on Software Engineering Pub Date : 2020-05-20 DOI: 10.1145/3425329.3425330

Vaclav Rechtberger, Miroslav Bures, Bestoun S. Ahmed

引用次数: 4