Embedded Selforganising Systems最新文献

Role of Training in The Successful Implementation of Hospital Information Systems 培训在成功实施医院信息系统中的作用

Embedded Selforganising Systems Pub Date : 2023-11-25 DOI: 10.14464/ess.v10i7.659

Oyuntungalag Buyantur, Sumjidmaa Tumurchudur, Munkhzul Ochirbat, Zaya Mashlai

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Introduction to the Proceedings of the ISCSET 2023 2023 年国际社会科学和技术教育会议论文集简介

Embedded Selforganising Systems Pub Date : 2023-10-19 DOI: 10.14464/ess.v10i7.644

U. Tudevdagva, René Bergelt

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Learning Styles and Cultural Differences: A comparative study of cultural differences in Austrian and Mongolian Students 学习风格与文化差异：奥地利和蒙古学生文化差异的比较研究

Embedded Selforganising Systems Pub Date : 2023-10-03 DOI: 10.14464/ess.v10i7.613

Ariunaa Khaskhuu, Nyambayar Chimed-Ochir

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Developing Information Competences of the Students in Technical Direction with Helping the Technology of “Network Boomerang” Principles 利用 "网络回旋镖 "技术培养技术方向学生的信息能力

Embedded Selforganising Systems Pub Date : 2023-09-30 DOI: 10.14464/ess.v10i7.633

Dilnoza Zaripova

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Some Results and Evaluation of Training for the Development of Students’ Spatial Visualization 培养学生空间视觉能力培训的一些结果和评价

Embedded Selforganising Systems Pub Date : 2023-09-29 DOI: 10.14464/ess.v10i7.630

Suvd Erdenechimeg, G. Danaa

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Innovative Teaching Methodology for Developing Digital Competence in Future Engineering Pedagogues 培养未来工程教育工作者数字能力的创新教学方法

Embedded Selforganising Systems Pub Date : 2023-09-28 DOI: 10.14464/ess.v10i7.628

Насибахон Расулова

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Influence Rate Evaluation by Students’ Opinion: University, Library, Courses and Professors 学生意见对评价的影响率：大学、图书馆、课程和教授

Embedded Selforganising Systems Pub Date : 2023-09-28 DOI: 10.14464/ess.v10i7.631

U. Tudevdagva, Narantsatsral Delgerkhuu, Gansaikhan Osorkhuu, Batdorj Davaagombo, Yeruulbat Galbadrakh, Serjmyadag Sergelen

{"title":"Influence Rate Evaluation by Students’ Opinion: University, Library, Courses and Professors","authors":"U. Tudevdagva, Narantsatsral Delgerkhuu, Gansaikhan Osorkhuu, Batdorj Davaagombo, Yeruulbat Galbadrakh, Serjmyadag Sergelen","doi":"10.14464/ess.v10i7.631","DOIUrl":"https://doi.org/10.14464/ess.v10i7.631","url":null,"abstract":"This paper describes a cooperative study of university lecturers with a focus on figuring out influence factors of students’ achievements in higher education. The evaluation survey is applied as the main method for research. Several lecturers (research team) who teach different courses in the university together developed influence factors in the form of survey questions, which are divided into four core groups: university, library, courses, and professors. The research team plans to collect as much data periodically from all universities in the country which is open to supporting this study. This paper showed the analyses of the first step of the study. 291 students from eight different universities voluntarily sent responses to an online survey.The collected data is processed by structure-oriented evaluation (SURE) model and by standard statistic function. The SURE evaluation score was calculated as 0.88 which we can read that all defined influence factors received evaluation scores from students with very high positive answers. The statistic maximum scores emphasized some factors that influence a lot to students’ achievement and students confirmed by their responses that some factors are very important for them. Further statistic ANOVA test was made for the case of the university group with 13 factors.For the ANOVA test, the null hypothesis. H0 – Null hypothesis stands for no difference between groups. No influence of study years on evaluation scores. By the ANOVA test, the null hypothesis isn’t proven. This concludes first step analyses as not significant statistically. Therefore, the researchteam needs to continue data collection and may apply some other statistical methods to compare the first results.","PeriodicalId":322203,"journal":{"name":"Embedded Selforganising Systems","volume":"230 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139335245","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

First-Year Students' Satisfaction by E-Learning 一年级学生对电子学习的满意度

Embedded Selforganising Systems Pub Date : 2023-09-27 DOI: 10.14464/ess.v10i7.614

Orkhontuya Puntsag, Javkhlantuya Altansuvd, Tuvshinjargal Radnaa

{"title":"First-Year Students' Satisfaction by E-Learning","authors":"Orkhontuya Puntsag, Javkhlantuya Altansuvd, Tuvshinjargal Radnaa","doi":"10.14464/ess.v10i7.614","DOIUrl":"https://doi.org/10.14464/ess.v10i7.614","url":null,"abstract":"Universities around the world have been using electronic learning systems more and more in recent years. Due to the Covid-19 pandemic, Mongolian universities are changing the way of teaching online and thus starting from the second semester of the 2019-2020 academic year. The purpose of this study is to investigate the satisfaction of students towards e-learning and the factors affecting it. 321 first-year students of the School of Nursing of NUMS participated in this survey, the survey questionnaire filled in Google form, and received by electronically. The relationship between satisfaction and its influencing factors was evaluated by using the Pearson test (correlation coefficient). According to the indicators of the research results, students' satisfaction is the most satisfied with learning materials (4.16), student engagement (4.15), and the lowest with e-educational technology (3.25). Due to this, there is a didactic need to improve the quality of e-learning and to update the lesson technology. Students' satisfaction level had a direct strong positive correlation (r=0.65) with grade (r=0.65) and a weak direct positive correlation (r=0.38) with lesson access (p<0.001), and e-learning satisfaction scores had a direct correlation (p<0.001) to the quality of teaching, supply of learning materials, assessment, and student engagement.","PeriodicalId":322203,"journal":{"name":"Embedded Selforganising Systems","volume":"53 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139335445","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

Evaluation of Python Error Message Interpretation: Study on Students with Different Levels of Programming Experience Python 错误信息解释评估：对不同编程经验水平学生的研究

Embedded Selforganising Systems Pub Date : 2023-09-26 DOI: 10.14464/ess.v10i7.626

Gantogoo Oyunbat, Ahmad Hamdy Sayed Hassanien

{"title":"Evaluation of Python Error Message Interpretation: Study on Students with Different Levels of Programming Experience","authors":"Gantogoo Oyunbat, Ahmad Hamdy Sayed Hassanien","doi":"10.14464/ess.v10i7.626","DOIUrl":"https://doi.org/10.14464/ess.v10i7.626","url":null,"abstract":"Error messages are a helpful tool for everyone interested in learning a programming language. Even after learning the language, novice and experienced programmers alike, have to interact with an error message one way or another. However, there is no single programming language that is usedacross all platforms and systems, so the programmers have to write programs in many different languages. If the programming languages have similar structures, working with a new language is relatively easy. We have asked the question, whether the same effect could be observed in case of error messages. We designed an online survey which was conducted internationally to measure whether the general experience of programmers from any programming language influences the programmer’s ability to correct python error message. The survey was aimed at students who have some experience with programming. We find in comparison with novices, on average the experiencedprogrammers find and fix an error in the code given the sameerror message with its corresponding code snippet. Additionally,we see correlations between the average of correctly fixed errorsand number of programming languages that the participants hadexperience with, as well as their chosen major and their age.","PeriodicalId":322203,"journal":{"name":"Embedded Selforganising Systems","volume":"60 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139335836","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

Automated Identification of Wood Surface Defects Based on Deep Learning 基于深度学习的木材表面缺陷自动识别技术

Embedded Selforganising Systems Pub Date : 2023-09-25 DOI: 10.14464/ess.v10i7.627

Besfort Syla, Shadi M. Saleh, Wolfram Hardt

{"title":"Automated Identification of Wood Surface Defects Based on Deep Learning","authors":"Besfort Syla, Shadi M. Saleh, Wolfram Hardt","doi":"10.14464/ess.v10i7.627","DOIUrl":"https://doi.org/10.14464/ess.v10i7.627","url":null,"abstract":"Wood plates are widely used in the interior design of houses primarily for their aesthetic value. However, considering its esthetical values, surface defect detection is necessary. The development of computer vision and CNN-based object detection methods has opened the way for wood surface defect detection process automation. This paper investigates deep-learning applications for automatic wood surface defect detection. It includes the evaluation of deep learning algorithms, including data generation and labeling, preprocessing, model training, and evaluation. Many adjustments regarding the dataset size, the model, and the modification of the neural network were made to evaluate the model's performance in the specified challenge. The results indicate that modifications can increase the YOLOv5s performance in detection. The model with GCNet added and trained in 4800 images has achieved 88.1% of mAP. The paper also evaluates the time performance of models based on different GPU units. The results show that in A100 40GB GPU, the maximum time to process a wood plate is 2.2 seconds. Finally, an Active learning approach for the continual increase in performance while detecting with the smaller size of manual labeling has been implemented. After detecting 500 images in 5 cycles, the model achieved 98.8% of mAP. This scientific paper concludes that YOLOv5s modified model is suitable for wood surface defect detection. It can perform with high accuracy in real time. Moreover, applying the active learning approach can facilitate the labeling process by increasing the performance during detection.","PeriodicalId":322203,"journal":{"name":"Embedded Selforganising Systems","volume":"42 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139336570","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