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2021 IEEE 15th International Symposium on Applied Computational Intelligence and Informatics (SACI)最新文献

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ICT-supported Learning: Concepts going viral 信息通信技术支持的学习:概念传播
2021 IEEE 15th International Symposium on Applied Computational Intelligence and Informatics (SACI) Pub Date : 2021-05-19 DOI: 10.1109/SACI51354.2021.9465605
A. Tick, J. Beke
{"title":"ICT-supported Learning: Concepts going viral","authors":"A. Tick, J. Beke","doi":"10.1109/SACI51354.2021.9465605","DOIUrl":"https://doi.org/10.1109/SACI51354.2021.9465605","url":null,"abstract":"The COVID-19 pandemic set off unexpected and unprecedented changes in all sectors of the economy, including education. Digitalization and digitization have become the main driving force of the transformation in education practices. The COVID-19 pandemic ushered in a dramatic shift in the way education is delivered. The sudden move to online platforms brought concepts like digital-, online-, mixed-. hybrid-, blended education/learning to the forefront, while other concepts such as elearning, distance and mobile learning are still popular. This paper considers the usage, popularity and spread of these terms, and through backing them with ICT advancement, LMS and Moodle improvements and the time-space-group triangle of elearning, it depicts the viral nature of these narratives. The paper concludes that the use of the terms follows the nature of epidemics.","PeriodicalId":321907,"journal":{"name":"2021 IEEE 15th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131002215","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
Classification of Malaria-Infected Cells using Convolutional Neural Networks 使用卷积神经网络对疟疾感染细胞进行分类
2021 IEEE 15th International Symposium on Applied Computational Intelligence and Informatics (SACI) Pub Date : 2021-05-19 DOI: 10.1109/SACI51354.2021.9465636
Katarina Mitrovic, Danijela Milošević
{"title":"Classification of Malaria-Infected Cells using Convolutional Neural Networks","authors":"Katarina Mitrovic, Danijela Milošević","doi":"10.1109/SACI51354.2021.9465636","DOIUrl":"https://doi.org/10.1109/SACI51354.2021.9465636","url":null,"abstract":"Malaria is a disease which, despite being present for over a century, still claims a significant number of lives every year. The advancement of artificial intelligence have opened the door to developing innovative methods in malaria treatment. Introducing machine learning approaches to this field can be beneficial in the disease prevention, detection, and therapy. In this work, convolutional neural networks for malaria detection are developed, based on the classification of thin blood smear images of the potentially infected cells. Input data was preprocessed using the image segmentation, file organization, image size standardization, color channel adjustment, and data splitting. Further, the proposed methodology included image conversion, network architecture defining, parameter tuning and network training. Various architectures of convolutional neural networks were developed and evaluated. In addition, multiple values of different network layer parameters were assessed. This study was implemented in Clojure programming language. Proposed network architecture includes two convolutional and pooling layers followed by activation functions, batch normalization and two linear layers. This convolutional neural network provided the best results and achieved an 82.7% accuracy. Furthermore, this paper proposes another network model with lightweight configuration and a slight accuracy decrease.","PeriodicalId":321907,"journal":{"name":"2021 IEEE 15th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123166631","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: 5
Hungarian Traffic Sign Detection and Classification using Semi-Supervised Learning 使用半监督学习的匈牙利交通标志检测和分类
2021 IEEE 15th International Symposium on Applied Computational Intelligence and Informatics (SACI) Pub Date : 2021-05-19 DOI: 10.1109/SACI51354.2021.9465555
Levente Kovács, Gábor Kertész
{"title":"Hungarian Traffic Sign Detection and Classification using Semi-Supervised Learning","authors":"Levente Kovács, Gábor Kertész","doi":"10.1109/SACI51354.2021.9465555","DOIUrl":"https://doi.org/10.1109/SACI51354.2021.9465555","url":null,"abstract":"Semi-supervised learning is a special way to improve the classification performance of a model where labeled data are not available. By using unlabeled observations and handling them as training data in a transfer learning buildup, we get a structure often referred to as self-supervision. In case of traffic sign detection and classification the task is complicated to the large number of tables and the different representations from country to country. While a number of public datasets are available, these might not give satisfying performance; to deal with this issue, a semi-supervised method is presented where frames of dashcam recordings are automatically annotated and reused as training samples.","PeriodicalId":321907,"journal":{"name":"2021 IEEE 15th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114345698","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
Influence of the Temperature on the Open-Circuit Voltage and Short-Circuit Current of a yellow colorized Dye Sensitized Solar Cell using Correlation Approach 温度对黄色染料敏化太阳能电池开路电压和短路电流的影响
2021 IEEE 15th International Symposium on Applied Computational Intelligence and Informatics (SACI) Pub Date : 2021-05-19 DOI: 10.1109/SACI51354.2021.9465600
Z. Varga, Ervin Rácz
{"title":"Influence of the Temperature on the Open-Circuit Voltage and Short-Circuit Current of a yellow colorized Dye Sensitized Solar Cell using Correlation Approach","authors":"Z. Varga, Ervin Rácz","doi":"10.1109/SACI51354.2021.9465600","DOIUrl":"https://doi.org/10.1109/SACI51354.2021.9465600","url":null,"abstract":"Future of the electricity producing has been seen in the renewable energy sources such as sun energy. One widely available light harvesting application is the solar cell which has a promising and encouraging global influence. On the other hand, the consequences of the global climate change made researchers develop a new form of solar cell which is the Dye Sensitized Solar Cell (DSSC). It is a third-generation solar cell which appears as a low-cost technology. Although, there are attempts to develop the electrical parameters of DSSC, but still the temperature dependence is worth to investigate using statistical approaches. This article illustrates the open-circuit voltage and the short-circuit current of a yellow colorized DSSC on the basis of the cell temperature using Pearson, Spearman and Kendall correlation.","PeriodicalId":321907,"journal":{"name":"2021 IEEE 15th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114494636","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
On uniform stability with growth rates in Banach spaces Banach空间中具有生长速率的一致稳定性
2021 IEEE 15th International Symposium on Applied Computational Intelligence and Informatics (SACI) Pub Date : 2021-05-19 DOI: 10.1109/SACI51354.2021.9465607
Rovana Boruga Toma, Diana Ioana Borlea Patrascu, Daniela Maria-Magdalena Toth
{"title":"On uniform stability with growth rates in Banach spaces","authors":"Rovana Boruga Toma, Diana Ioana Borlea Patrascu, Daniela Maria-Magdalena Toth","doi":"10.1109/SACI51354.2021.9465607","DOIUrl":"https://doi.org/10.1109/SACI51354.2021.9465607","url":null,"abstract":"The paper considers three concepts of uniform stability of evolution operators: uniform exponential stability, uniform polynomial stability and uniform h-stability. Some characterizations of these notions and connections between these concepts are given.","PeriodicalId":321907,"journal":{"name":"2021 IEEE 15th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115950422","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: 6
Accelerating Data Ingress for Range-Scan Optimized HBase Instances 加速范围扫描优化HBase实例的数据进入
2021 IEEE 15th International Symposium on Applied Computational Intelligence and Informatics (SACI) Pub Date : 2021-05-19 DOI: 10.1109/SACI51354.2021.9465633
Adrian-Ioan Argesanu, G. Andreescu
{"title":"Accelerating Data Ingress for Range-Scan Optimized HBase Instances","authors":"Adrian-Ioan Argesanu, G. Andreescu","doi":"10.1109/SACI51354.2021.9465633","DOIUrl":"https://doi.org/10.1109/SACI51354.2021.9465633","url":null,"abstract":"HBase was designed to get high performance for read-intensive workloads, making it very attractive for use cases involving retrieval of contiguous sets of rows. HBase instances set up for fast reads often force users to compromise on write performance, which in turn can lead to temporary degradation of read capabilities. In this paper we study existing write penalty mitigation options and introduce our software solution, which not only accelerates bulk data ingress but also retains egress performance without any post-processing or alterations of the soft-schema. Our experiments show that the proposed software solution yields a 47 % reduction of ingestion duration.","PeriodicalId":321907,"journal":{"name":"2021 IEEE 15th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127279648","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
Fuzzy Model for Common Vulnerability Scoring System 通用漏洞评分系统的模糊模型
2021 IEEE 15th International Symposium on Applied Computational Intelligence and Informatics (SACI) Pub Date : 2021-05-19 DOI: 10.1109/SACI51354.2021.9465614
Mera Saulaiman, M. Takács, M. Kozlovszky, Á. Csilling
{"title":"Fuzzy Model for Common Vulnerability Scoring System","authors":"Mera Saulaiman, M. Takács, M. Kozlovszky, Á. Csilling","doi":"10.1109/SACI51354.2021.9465614","DOIUrl":"https://doi.org/10.1109/SACI51354.2021.9465614","url":null,"abstract":"The Common Vulnerability Scoring System (CVSS) is a widely used open standard for measuring the severity of software vulnerabilities based on defined metric values. It uses optimized equations to combine several aspects of a vulnerability to derive the score. In this paper the possibility of implementing this CVSS calculator in fuzzy logic is discussed, using the Fuzzy Logic toolbox from MATLAB extended in Simulink environment.The model is evaluated by comparing the results of both systems for a few test cases. The possibility of implementing an optimized CVSS calculator using Fuzzy logic is discussed.Taking advantage of the possibility available in Fuzzy logic we discuss the possibility to extend the calculator with domain-specific metrics.","PeriodicalId":321907,"journal":{"name":"2021 IEEE 15th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125562680","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
eGauss+ evolving clustering in classification eGauss+进化聚类在分类中的应用
2021 IEEE 15th International Symposium on Applied Computational Intelligence and Informatics (SACI) Pub Date : 2021-05-19 DOI: 10.1109/SACI51354.2021.9465615
I. Škrjanc
{"title":"eGauss+ evolving clustering in classification","authors":"I. Škrjanc","doi":"10.1109/SACI51354.2021.9465615","DOIUrl":"https://doi.org/10.1109/SACI51354.2021.9465615","url":null,"abstract":"In this paper, eGauss+ evolving clustering is used in classification, which forms very small clusters in the shape of hyper-ellipsoids in a single-pass manner going through the data set. At the end of procedure small cluster forming phase the merging procedure is used which merges these small clusters, i.e. merges granules into bigger clusters. The merging procedure is based on cluster volumes, which merge two closed and similar cluster into a new one. The resulting cluster center is a weighted averaging of merged cluster centers, together with covariance matrix which is calculated from the covariance matrices of the small clusters. The proposed classification algorithm was used on two classical classification data sets, i.e. iris and breast cancer data set, and compared with other methods. The method shows very similar results, but has an important advantage, namely it works recursively, in a single-pass manner.","PeriodicalId":321907,"journal":{"name":"2021 IEEE 15th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129740956","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
Computational Capacity Analysis of Platforms for Low-Cost Autonomous Ultraviolet Germicidal Robots 低成本自主紫外杀菌机器人平台计算能力分析
2021 IEEE 15th International Symposium on Applied Computational Intelligence and Informatics (SACI) Pub Date : 2021-05-19 DOI: 10.1109/SACI51354.2021.9465624
S. G. Pfleger, P. Plentz
{"title":"Computational Capacity Analysis of Platforms for Low-Cost Autonomous Ultraviolet Germicidal Robots","authors":"S. G. Pfleger, P. Plentz","doi":"10.1109/SACI51354.2021.9465624","DOIUrl":"https://doi.org/10.1109/SACI51354.2021.9465624","url":null,"abstract":"The use of Ultraviolet Germicidal Irradiation (UVGI) to disinfect environments gained prominence during the current pandemic of COVID-19, as a method to reduce the contamination. Given the risks that the technique can bring to human health and other living beings, autonomous robots become useful for the application of UVGI. This document presents a study of the technical feasibility of using some platforms as a processing and control unit for low-cost autonomous disinfectant robots. For this, each platform is subjected to the UVGI irradiance calculation, a task that requires a high processing capacity. The results show that all tested platforms meet the processing capacity criteria, being eligible to compose a low-cost disinfectant robot.","PeriodicalId":321907,"journal":{"name":"2021 IEEE 15th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129932176","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
Computation of COVID-19 epidemiological data in Hungary using dynamic model inversion 基于动态模型反演的匈牙利COVID-19流行病学数据计算
2021 IEEE 15th International Symposium on Applied Computational Intelligence and Informatics (SACI) Pub Date : 2021-05-07 DOI: 10.1109/SACI51354.2021.9465563
B. Csutak, Péter Polcz, G. Szederkényi
{"title":"Computation of COVID-19 epidemiological data in Hungary using dynamic model inversion","authors":"B. Csutak, Péter Polcz, G. Szederkényi","doi":"10.1109/SACI51354.2021.9465563","DOIUrl":"https://doi.org/10.1109/SACI51354.2021.9465563","url":null,"abstract":"In this paper, we estimate epidemiological data of the COVID-19 pandemic in Hungary using only the daily number of hospitalized patients, and applying well-known techniques from systems and control theory. We use a previously published and validated compartmental model for the description of epidemic spread. Exploiting the fact that an important subsystem of the model is linear, first we compute the number of latent infected persons in time. Then an estimate can be given for the number of people in other compartments. From these data, it is possible to track the time dependent reproduction numbers via a recursive least squares estimate. The credibility of the obtained results is discussed using available data from the literature.","PeriodicalId":321907,"journal":{"name":"2021 IEEE 15th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124018246","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: 5
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