2020 18th International Conference on Emerging eLearning Technologies and Applications (ICETA)最新文献_第5页

Speech Emotion Recognition Overview and Experimental Results 语音情感识别综述及实验结果

2020 18th International Conference on Emerging eLearning Technologies and Applications (ICETA) Pub Date : 2020-11-12 DOI: 10.1109/ICETA51985.2020.9379218

Eva Lieskovská, Maroš Jakubec, R. Jarina

引用次数: 3

Parametric audio quality estimation models for broadcasting systems and web-casting applications based on the Genetic Programming 基于遗传规划的广播系统和网络广播应用的参数音频质量估计模型

2020 18th International Conference on Emerging eLearning Technologies and Applications (ICETA) Pub Date : 2020-11-12 DOI: 10.1109/ICETA51985.2020.9379251

M. Jakubik, P. Počta

{"title":"Parametric audio quality estimation models for broadcasting systems and web-casting applications based on the Genetic Programming","authors":"M. Jakubik, P. Počta","doi":"10.1109/ICETA51985.2020.9379251","DOIUrl":"https://doi.org/10.1109/ICETA51985.2020.9379251","url":null,"abstract":"The COVID-19 pandemic has been one of the biggest disruptions to education that the world has ever experienced, affecting the most of the world student population. Many countries turned to online based distance education to ensure that learning never stops. As a consequence, throughout the globe there has been an increasing trend among the students to use different broadcasting systems and web-casting applications for the purpose of online learning. However, the video or audio quality that these various applications offer will be the key factor for their acceptance, i.e. whether or not the students will be willing to use those systems for online learning. Therefore, a machine learning technique, i.e. Genetic Programming, is used in this work for the purpose of assessing audio quality using an objective approach. A design and performance evaluation of the parametric models estimating the audio quality perceived by the end user of broadcasting systems and web-casting applications are presented in this paper. To estimate the quality of audio broadcasting systems and web-casting applications, a set of parameters influencing the quality is used as an input for the developed parametric quality estimation models. The results obtained by the developed parametric audio quality estimation models have validated Genetic Programming as a powerful technique, providing a good accuracy and generalization capabilities. This makes it a possible candidate for the estimation of audio quality perceived by the end user in the context of the broadcasting systems and web-casting applications.","PeriodicalId":149716,"journal":{"name":"2020 18th International Conference on Emerging eLearning Technologies and Applications (ICETA)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125439238","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: 1

API for Communication between Motion Sensors and Raspberry Pi 用于运动传感器和树莓派之间通信的API

2020 18th International Conference on Emerging eLearning Technologies and Applications (ICETA) Pub Date : 2020-11-12 DOI: 10.1109/ICETA51985.2020.9379226

O. Kováč, E. Pietriková

引用次数: 1

SMART environment control in virtual and mixed reality based on cognitive user abilities 基于认知用户能力的虚拟和混合现实智能环境控制

2020 18th International Conference on Emerging eLearning Technologies and Applications (ICETA) Pub Date : 2020-11-12 DOI: 10.1109/ICETA51985.2020.9379157

M. Sivý, B. Sobota, Š. Korečko, M. Hudák

引用次数: 2

E-Health device for remote health monitoring 用于远程健康监测的电子保健设备

2020 18th International Conference on Emerging eLearning Technologies and Applications (ICETA) Pub Date : 2020-11-12 DOI: 10.1109/ICETA51985.2020.9379268

J. Lenický, M. Hradsky, M. Kalina, J. Erdelyi, P. Cicák

引用次数: 0

Evaluation of Modeling Differences of Nodal vs. Zonal Pricing Based Electricity Markets: Optimization Models and Network Representation 基于节点与区域定价的电力市场建模差异评估:优化模型与网络表示

2020 18th International Conference on Emerging eLearning Technologies and Applications (ICETA) Pub Date : 2020-11-12 DOI: 10.1109/ICETA51985.2020.9379255

L. Jansen, L. Buzna

{"title":"Evaluation of Modeling Differences of Nodal vs. Zonal Pricing Based Electricity Markets: Optimization Models and Network Representation","authors":"L. Jansen, L. Buzna","doi":"10.1109/ICETA51985.2020.9379255","DOIUrl":"https://doi.org/10.1109/ICETA51985.2020.9379255","url":null,"abstract":"Firstly, this work briefly introduces the Collaborative Doctoral Program (CDP), which fosters collaborations between the Joint Research Centre and Universities, in order to provide a European qualification framework to doctoral students, who are trained to be at the intersect of science and policy through multinational projects. Secondly, this work provides an example of research conducted in the context of the CDP in the field of energy modeling aiming at developing improved modeling tools to assess the efficiency of nodal against zonal pricing and providing evidence for policy-makers. The electricity system is evolving with increasing incorporation of renewable energies, therefore also the transmission system is facing expanding challenges. As a consequence, also electricity markets are evolving. A topic of increasing interest is nodal pricing as an alternative to zonal pricing-based electricity markets in Europe. This work is giving an overview of different formulations of optimization problems in power systems and in particular, in electricity markets, which are commonly applied in literature. We focus on two different aspects being the type of optimization problem and the representation of the transmission network. In this context, the trade-off between modeling accuracy and computational efforts is the topic assessed in this study. We find that computational times increase drastically when employing unit-commitment, but remain rather moderate when sticking to economic dispatch using DC- as well as AC-OPF. The representation of networks in terms of aggregated node systems, which are relevant when aiming to compare zonal to nodal pricing-based electricity markets, show that power flows within zones are difficult to predict and it is vital to further investigate the aggregation of nodes into zones to support comparative studies.","PeriodicalId":149716,"journal":{"name":"2020 18th International Conference on Emerging eLearning Technologies and Applications (ICETA)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127624908","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

Technical Challenges and Vision of Slovak National Telepresence Infrastructure during the COVID-19 Pandemic 2019冠状病毒病大流行期间斯洛伐克国家网真基础设施的技术挑战和愿景

2020 18th International Conference on Emerging eLearning Technologies and Applications (ICETA) Pub Date : 2020-11-12 DOI: 10.1109/ICETA51985.2020.9379151

F. Jakab, D. Cymbalák, R. Vápeník, P. Hrčka, J. Kováčová

引用次数: 0

Level and Ways of Educating Future Teachers in the Use of Digital Technologies: Basic Results of a Questionnaire Survey 未来教师使用数字技术的水平与途径:一项问卷调查的基本结果

2020 18th International Conference on Emerging eLearning Technologies and Applications (ICETA) Pub Date : 2020-11-12 DOI: 10.1109/ICETA51985.2020.9379158

T. Javorcik, T. Havlaskova

引用次数: 1

Innovative changes in the curriculum of information and communication technologies in the Czech Republic from the perspective of primary school teachers 从小学教师的角度看捷克共和国信息与通信技术课程的创新变化

2020 18th International Conference on Emerging eLearning Technologies and Applications (ICETA) Pub Date : 2020-11-12 DOI: 10.1109/ICETA51985.2020.9379233

Hana Bucková, Jirí Dostál

引用次数: 2

Comparison of Algorithms for Fuzzy Decision Tree Induction 模糊决策树归纳算法的比较

2020 18th International Conference on Emerging eLearning Technologies and Applications (ICETA) Pub Date : 2020-11-12 DOI: 10.1109/ICETA51985.2020.9379189

J. Rabcan, Patrik Rusnak, J. Kostolny, R. Stankovic

{"title":"Comparison of Algorithms for Fuzzy Decision Tree Induction","authors":"J. Rabcan, Patrik Rusnak, J. Kostolny, R. Stankovic","doi":"10.1109/ICETA51985.2020.9379189","DOIUrl":"https://doi.org/10.1109/ICETA51985.2020.9379189","url":null,"abstract":"The objective of the classification is to assign a class label to a data sample based on previous, learned experience. Despite the long tradition of classification algorithms research, there is not a unique technique that yields the best classification performance in all scenarios. Many real-world problems are uncertain. In this case, the crisp classification can be difficult to perform. The usage of fuzzy logic can be useful to describe real-world problems with higher accuracy. In this paper, we describe and compare algorithms of Fuzzy Decision Trees (FDTs), which are an extension of traditional decision trees. These algorithms are popular for their easy understandability and interpretability. But today there are many algorithms for FDT induction. These algorithms differ in many aspects. The most common difference is in information measures for selecting splitting attributes. Generally, the goal of decision tree induction is to create the smallest tree which is the most accurate as possible. In this paper, we use various information measures to induct FDTs and compare the accuracy and size of obtained FDTs. In comparison, information measures that are based on a generalization of the Shannon entropy and cumulative mutual information are included. The comparison shows that FDTs based on the cumulative mutual information acquired the best results. These results will also be included in a course on data mining that is taught at Faculty of Management Science and Informatics of University of Zilina.","PeriodicalId":149716,"journal":{"name":"2020 18th International Conference on Emerging eLearning Technologies and Applications (ICETA)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134340418","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: 1