Within the scope of this research, a generic software architecture for the banking industry is proposed and studied to improve the analysis regarding customer retention and attrition. The prototype of the proposed architecture model is improved and its performance is tested in terms of scalability and responsiveness. The results are promising and indicating that the proposed system is serviceable.
{"title":"Software Architecture of a System Designed for Churn Analysis and Customer Retention in Banking Industry","authors":"Erdal Bozan, Guven Gul, Umit Tigrak, Emir Demirci, Hakan Saribiyik, M. Aktaş","doi":"10.1109/ICCSA50381.2020.00023","DOIUrl":"https://doi.org/10.1109/ICCSA50381.2020.00023","url":null,"abstract":"Within the scope of this research, a generic software architecture for the banking industry is proposed and studied to improve the analysis regarding customer retention and attrition. The prototype of the proposed architecture model is improved and its performance is tested in terms of scalability and responsiveness. The results are promising and indicating that the proposed system is serviceable.","PeriodicalId":124171,"journal":{"name":"2020 20th International Conference on Computational Science and Its Applications (ICCSA)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126548409","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}
Pub Date : 2020-07-01DOI: 10.1109/ICCSA50381.2020.00020
Symphorien Karl Yoki Donzia, Haeng-Kon Kim, Young-Pil Geum
World Currently, there are many forms and areas of application of e-government. At the same time, there is a growing variety of technologies available to improve online administration. The research aims to develop a process model to measure citizen satisfaction. This document presents a complete overview of the e-government landscape through an advanced review of these technologies. This finding suggests that the personalization of e-government initiatives is ideal for the local needs of constituents. Understand the needs of all public segments to ensure that the electronic government system truly helps each citizen meet their human development needs. And enabling citizens to participate in the design of online administration services are the recommendations of the case studies by providing a secure experience to web visitors through the development of a security and disaster recovery plan for the 'online administration. This document allows the user to be the primary determinant of e-government adoption and satisfaction. Of course, we will emphasize that software design research studies the methods to determine the best way to divide a system, how the components are identified and communicated, how the information is communicated, how the elements of a system can evolve independently. The component model of our service is setting by the UML model, that is made up for use case, class and sequence diagrams.
{"title":"Software Design of E-government model Conception","authors":"Symphorien Karl Yoki Donzia, Haeng-Kon Kim, Young-Pil Geum","doi":"10.1109/ICCSA50381.2020.00020","DOIUrl":"https://doi.org/10.1109/ICCSA50381.2020.00020","url":null,"abstract":"World Currently, there are many forms and areas of application of e-government. At the same time, there is a growing variety of technologies available to improve online administration. The research aims to develop a process model to measure citizen satisfaction. This document presents a complete overview of the e-government landscape through an advanced review of these technologies. This finding suggests that the personalization of e-government initiatives is ideal for the local needs of constituents. Understand the needs of all public segments to ensure that the electronic government system truly helps each citizen meet their human development needs. And enabling citizens to participate in the design of online administration services are the recommendations of the case studies by providing a secure experience to web visitors through the development of a security and disaster recovery plan for the 'online administration. This document allows the user to be the primary determinant of e-government adoption and satisfaction. Of course, we will emphasize that software design research studies the methods to determine the best way to divide a system, how the components are identified and communicated, how the information is communicated, how the elements of a system can evolve independently. The component model of our service is setting by the UML model, that is made up for use case, class and sequence diagrams.","PeriodicalId":124171,"journal":{"name":"2020 20th International Conference on Computational Science and Its Applications (ICCSA)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129911672","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}
Pub Date : 2020-07-01DOI: 10.1109/iccsa50381.2020.00002
{"title":"Title Page","authors":"","doi":"10.1109/iccsa50381.2020.00002","DOIUrl":"https://doi.org/10.1109/iccsa50381.2020.00002","url":null,"abstract":"","PeriodicalId":124171,"journal":{"name":"2020 20th International Conference on Computational Science and Its Applications (ICCSA)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116704378","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}
Pub Date : 2020-07-01DOI: 10.1109/ICCSA50381.2020.00015
Itamir Filho, S. Sampaio, João Carlos A. Tenório, Edvaldo Vasconcelos de C. Filho, Matheus Estevam de C. Pessoa, R. S. Malaquias, Pedro Arthur Fernades
This article presents the strategies used for the development and implementation of a dashboard for an Electronic Health Record System, specifically the platform called SigSaude, which integrates the student-run clinics of the Federal University of Rio Grande do Norte. Built over a set of ELK Stack software, the SigSaude dashboard allows the visual analysis of patient information through interactive graphics, facilitating the process of data interpretation by researchers and managers and supporting a data-based decision approach. In this paper the authors describe the development process in four steps: configuring the database for Logstash, masking the data and obtaining the geolocation to create the dataset, indexing data using Elasticsearch, and building indexed data views using Kibana. The authors also present the current version of the SigSaude dashboard which displays graphs involving the users' blood type, marital status, whether they know their parents or not, ethnicity and age, as well as a map component that makes it possible to see the number of registered users by city. Finally, the authors discuss the lessons learned on the development of the SigSaude dashboard.
{"title":"Development of a Health Dashboard for an Electronic Health Record System","authors":"Itamir Filho, S. Sampaio, João Carlos A. Tenório, Edvaldo Vasconcelos de C. Filho, Matheus Estevam de C. Pessoa, R. S. Malaquias, Pedro Arthur Fernades","doi":"10.1109/ICCSA50381.2020.00015","DOIUrl":"https://doi.org/10.1109/ICCSA50381.2020.00015","url":null,"abstract":"This article presents the strategies used for the development and implementation of a dashboard for an Electronic Health Record System, specifically the platform called SigSaude, which integrates the student-run clinics of the Federal University of Rio Grande do Norte. Built over a set of ELK Stack software, the SigSaude dashboard allows the visual analysis of patient information through interactive graphics, facilitating the process of data interpretation by researchers and managers and supporting a data-based decision approach. In this paper the authors describe the development process in four steps: configuring the database for Logstash, masking the data and obtaining the geolocation to create the dataset, indexing data using Elasticsearch, and building indexed data views using Kibana. The authors also present the current version of the SigSaude dashboard which displays graphs involving the users' blood type, marital status, whether they know their parents or not, ethnicity and age, as well as a map component that makes it possible to see the number of registered users by city. Finally, the authors discuss the lessons learned on the development of the SigSaude dashboard.","PeriodicalId":124171,"journal":{"name":"2020 20th International Conference on Computational Science and Its Applications (ICCSA)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132431422","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}
Pub Date : 2020-07-01DOI: 10.1109/ICCSA50381.2020.00014
J. S. Nunes, S. Sampaio, R. S. Malaquias, Itamir de Morais Barroca Filho
The adoption of the microservice architectural style is proving very advantageous as it facilitates the creation of distributed, scalable and available solutions, favoring the use of cloud and container infrastructures. For these and other advantages has been widely adopted by large global companies in the application development market like Uber, Netflix, Amazon, SoundCloud, and many others. If on the one hand the use of microservices provides scalability, maintainability and availability, on the other hand it requires a high degree of observability of operations. However, traditional monitoring tools are incomplete to deal with this distributed scenario. Thus, this paper proposes the use of an integrated and scalable service mesh-based architecture to be incorporated into a health platform project whose main objective is to increase the observability capabilities of the system, allowing the contextualized monitoring of transactions between the various microservices.
{"title":"Deploying the observability of the SigSaude system using service mesh","authors":"J. S. Nunes, S. Sampaio, R. S. Malaquias, Itamir de Morais Barroca Filho","doi":"10.1109/ICCSA50381.2020.00014","DOIUrl":"https://doi.org/10.1109/ICCSA50381.2020.00014","url":null,"abstract":"The adoption of the microservice architectural style is proving very advantageous as it facilitates the creation of distributed, scalable and available solutions, favoring the use of cloud and container infrastructures. For these and other advantages has been widely adopted by large global companies in the application development market like Uber, Netflix, Amazon, SoundCloud, and many others. If on the one hand the use of microservices provides scalability, maintainability and availability, on the other hand it requires a high degree of observability of operations. However, traditional monitoring tools are incomplete to deal with this distributed scenario. Thus, this paper proposes the use of an integrated and scalable service mesh-based architecture to be incorporated into a health platform project whose main objective is to increase the observability capabilities of the system, allowing the contextualized monitoring of transactions between the various microservices.","PeriodicalId":124171,"journal":{"name":"2020 20th International Conference on Computational Science and Its Applications (ICCSA)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114236313","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}
Pub Date : 2020-07-01DOI: 10.1109/ICCSA50381.2020.00013
A. Abayomi-Alli, Olabode Atinuke, S. Onashoga, S. Misra, O. Arogundade, O. Abayomi-Alli
Facial recognition is a type of biometric that deals with the facial region of a human image. The low recognition accuracy of existing Facial Recognition Systems (FRS) is due to the low quality of captured images. The assessment of image quality, therefore, becomes a requirement to be taken before passing such an image through the FRS. This study presents a proposed Facial Image Quality Assessment (FIQA) model using an ensemble of pre-trained deep learning models (EFQnet). The system known as EFQnet is an ensemble of ResNet-50, DenseNet, and Inception-Net CNN pre-trained models. It utilizes a performance-based ground truth that forecasts a quality score for the input image between 0 to 1. The three models are ensemble using full fully connected Feedforward Neural Network and AMSGrad stochastic gradient Descent algorithm. When trained and fully implemented EFQnet will be evaluated on standard IQA databases and finally deployed in a Personal Identity Verification (PIV) scenario.
{"title":"Facial Image Quality Assessment using an Ensemble of Pre-Trained Deep Learning Models (EFQnet)","authors":"A. Abayomi-Alli, Olabode Atinuke, S. Onashoga, S. Misra, O. Arogundade, O. Abayomi-Alli","doi":"10.1109/ICCSA50381.2020.00013","DOIUrl":"https://doi.org/10.1109/ICCSA50381.2020.00013","url":null,"abstract":"Facial recognition is a type of biometric that deals with the facial region of a human image. The low recognition accuracy of existing Facial Recognition Systems (FRS) is due to the low quality of captured images. The assessment of image quality, therefore, becomes a requirement to be taken before passing such an image through the FRS. This study presents a proposed Facial Image Quality Assessment (FIQA) model using an ensemble of pre-trained deep learning models (EFQnet). The system known as EFQnet is an ensemble of ResNet-50, DenseNet, and Inception-Net CNN pre-trained models. It utilizes a performance-based ground truth that forecasts a quality score for the input image between 0 to 1. The three models are ensemble using full fully connected Feedforward Neural Network and AMSGrad stochastic gradient Descent algorithm. When trained and fully implemented EFQnet will be evaluated on standard IQA databases and finally deployed in a Personal Identity Verification (PIV) scenario.","PeriodicalId":124171,"journal":{"name":"2020 20th International Conference on Computational Science and Its Applications (ICCSA)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132395722","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}
Pub Date : 2020-07-01DOI: 10.1109/ICCSA50381.2020.00017
J. C. Silva, L. M. Araújo
Mobile devices, especially tablets and smartphones, have achieved enormous popularity over the last ten years due to their ease of use and multifunctionality, thus gaining meritoriously a prominent space in our daily lives. On the opposite side, despite improvements in usability and intuitiveness, to use desktop devices users must learn how to interact with the operating system, how to achieve tasks, and fulfill system's specifications. This paper aims to present a methodology that responds to identified needs of users allowing them to execute desktop tasks from mobile applications. Based on real-time database, picture-driven computing, task automation and mobile interactive systems the approach aims to reduce the challenges that users face while trying to perform a task, as well as improving the efficiency of task performance. The approach combines the features and capabilities of both PyAutoGUI and Firebase tools to simplify the process used by such users to perform tasks. The use of mobile devices enhances the usability of the new interactive system. This paper describes the methodology and the research is illustrated by means of a daily task application example.
{"title":"Android App Development Applied to Remote Tasks Simplification","authors":"J. C. Silva, L. M. Araújo","doi":"10.1109/ICCSA50381.2020.00017","DOIUrl":"https://doi.org/10.1109/ICCSA50381.2020.00017","url":null,"abstract":"Mobile devices, especially tablets and smartphones, have achieved enormous popularity over the last ten years due to their ease of use and multifunctionality, thus gaining meritoriously a prominent space in our daily lives. On the opposite side, despite improvements in usability and intuitiveness, to use desktop devices users must learn how to interact with the operating system, how to achieve tasks, and fulfill system's specifications. This paper aims to present a methodology that responds to identified needs of users allowing them to execute desktop tasks from mobile applications. Based on real-time database, picture-driven computing, task automation and mobile interactive systems the approach aims to reduce the challenges that users face while trying to perform a task, as well as improving the efficiency of task performance. The approach combines the features and capabilities of both PyAutoGUI and Firebase tools to simplify the process used by such users to perform tasks. The use of mobile devices enhances the usability of the new interactive system. This paper describes the methodology and the research is illustrated by means of a daily task application example.","PeriodicalId":124171,"journal":{"name":"2020 20th International Conference on Computational Science and Its Applications (ICCSA)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133954362","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}
Pub Date : 2020-07-01DOI: 10.1109/ICCSA50381.2020.00024
N. Lal, Mrityunjay Singh, S. Pandey, A. Solanki
Now a day's huge amount of data is available in an unstructured format, users need useful information related to query or phrase that has been written in search engines. Search engine rank and indexed the data as per the nature of data and documents like structure (SQL data), unstructured (e-books, PPT, text, Streamed Data, songs, movies, research data), or semi-structured (XML). Indexing and ranking is the main issue in Information retrieval system to retrieve the appropriate results of the query from Dataspace due to heterogeneity. Indexing of unstructured data can reduce the processing time of query for fast retrieval of data. This paper proposed a ranked cluster approach using Modified cosine similarity and Vector space model (VSM) which may be replaced with the traditional cosine similarity approach for better results on the dataset. Here we applying the vector space model, Document term matrix, and TF-IDF weights for indexing and ranking of the heterogeneous data. Consequently, the documents which match the query the most are displayed first and ranking of the documents is done according to similarity with the query of unstructured data over Dataspace.
{"title":"A Proposed Ranked Clustering Approach for Unstructured Data from Dataspace using VSM","authors":"N. Lal, Mrityunjay Singh, S. Pandey, A. Solanki","doi":"10.1109/ICCSA50381.2020.00024","DOIUrl":"https://doi.org/10.1109/ICCSA50381.2020.00024","url":null,"abstract":"Now a day's huge amount of data is available in an unstructured format, users need useful information related to query or phrase that has been written in search engines. Search engine rank and indexed the data as per the nature of data and documents like structure (SQL data), unstructured (e-books, PPT, text, Streamed Data, songs, movies, research data), or semi-structured (XML). Indexing and ranking is the main issue in Information retrieval system to retrieve the appropriate results of the query from Dataspace due to heterogeneity. Indexing of unstructured data can reduce the processing time of query for fast retrieval of data. This paper proposed a ranked cluster approach using Modified cosine similarity and Vector space model (VSM) which may be replaced with the traditional cosine similarity approach for better results on the dataset. Here we applying the vector space model, Document term matrix, and TF-IDF weights for indexing and ranking of the heterogeneous data. Consequently, the documents which match the query the most are displayed first and ranking of the documents is done according to similarity with the query of unstructured data over Dataspace.","PeriodicalId":124171,"journal":{"name":"2020 20th International Conference on Computational Science and Its Applications (ICCSA)","volume":"20 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114111099","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}
Pub Date : 2020-07-01DOI: 10.1109/ICCSA50381.2020.00025
A. Razzaq
This is a doctoral research symposium that is prepared to encounter the challenges of IoT systems and data in the Ocean. Managing and analyzing the big data of oceanography is difficult because of increasing the growth of massive data. The use of IoT devices/sensors is becoming more complex day by day. This research discusses the critical challenges of IoT applications and data in the Ocean, also will keep eyes on how microservice architecture plays essential roles in IoT applications. We intent to mitigate or decrease the complexity of IoT data and increase the scalability for the IoT systems in the Ocean. Also, we intend to increase a profound comprehension of the challenges and solutions, migration process, architecture design and description in MSA with IoT systems in the Ocean. We are expecting the outcome will be: (i) MSA systematic study for IoT applications, (ii) process to enhance the scalability of legacy systems (iii) adoption process of monolithic systems to MSA (iv) MSA process or software architecture selection process for IoT applications in the Ocean (v) Recommendations and Guidelines for the developer and scientific use (vi) recommendations for future work.
{"title":"Microservices Architecture for IoT Applications in the Ocean : Microservices Architecture based Framework for Reducing the Complexity and Increasing the Scalability of IoT Applications in the Ocean","authors":"A. Razzaq","doi":"10.1109/ICCSA50381.2020.00025","DOIUrl":"https://doi.org/10.1109/ICCSA50381.2020.00025","url":null,"abstract":"This is a doctoral research symposium that is prepared to encounter the challenges of IoT systems and data in the Ocean. Managing and analyzing the big data of oceanography is difficult because of increasing the growth of massive data. The use of IoT devices/sensors is becoming more complex day by day. This research discusses the critical challenges of IoT applications and data in the Ocean, also will keep eyes on how microservice architecture plays essential roles in IoT applications. We intent to mitigate or decrease the complexity of IoT data and increase the scalability for the IoT systems in the Ocean. Also, we intend to increase a profound comprehension of the challenges and solutions, migration process, architecture design and description in MSA with IoT systems in the Ocean. We are expecting the outcome will be: (i) MSA systematic study for IoT applications, (ii) process to enhance the scalability of legacy systems (iii) adoption process of monolithic systems to MSA (iv) MSA process or software architecture selection process for IoT applications in the Ocean (v) Recommendations and Guidelines for the developer and scientific use (vi) recommendations for future work.","PeriodicalId":124171,"journal":{"name":"2020 20th International Conference on Computational Science and Its Applications (ICCSA)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133486619","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}
Pub Date : 2020-07-01DOI: 10.1109/ICCSA50381.2020.00022
Weronika Westwanska, J. Respondek
In this article we present a new approach to object segmentation. We use a Convolutional Neural Network with a specific architecture called U-net to recognize an object in a colored image and efficiently segment it with a new approach which we find more accurate than the one we applied in our earlier work. We focused on fast and memory-efficient segmentation process applied after training of U-net, using a single point to represent the object. The main purpose of this work is to prove that proposed simplified object representation in training of neural network leads to accurate results in meaning of counting instances of an object and in a field of segmentation process. We present results of series of experiments analyzing accuracy of computations achieved using our algorithm on nine neural networks trained on different values of various parameters.
{"title":"Machine Learning in Object Recognition and Segmentation by Certain Class Neural Networks","authors":"Weronika Westwanska, J. Respondek","doi":"10.1109/ICCSA50381.2020.00022","DOIUrl":"https://doi.org/10.1109/ICCSA50381.2020.00022","url":null,"abstract":"In this article we present a new approach to object segmentation. We use a Convolutional Neural Network with a specific architecture called U-net to recognize an object in a colored image and efficiently segment it with a new approach which we find more accurate than the one we applied in our earlier work. We focused on fast and memory-efficient segmentation process applied after training of U-net, using a single point to represent the object. The main purpose of this work is to prove that proposed simplified object representation in training of neural network leads to accurate results in meaning of counting instances of an object and in a field of segmentation process. We present results of series of experiments analyzing accuracy of computations achieved using our algorithm on nine neural networks trained on different values of various parameters.","PeriodicalId":124171,"journal":{"name":"2020 20th International Conference on Computational Science and Its Applications (ICCSA)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129654705","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}
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