Pub Date : 2021-12-01DOI: 10.1109/CSCI54926.2021.00239
Hiroki Wakabayashi, H. Nakayama, R. Onuma, H. Kaminaga, Y. Miyadera, Shoichi Nakamura
Opportunities for conducting discussions and expressing opinions on the Web have increased. It is desirable to fully understand the processes and main points of such discussions. In particular, it is important to understand both the main points of discussions and trends of opinions together rather than superficial results. However, such understanding is often difficult since the number of utterances increases as time passes and discussions become complicated. In this research, we aimed at developing methods for visualizing discussions in comments to Web news so that novices can understand both the main points and trends of opinions. This paper mainly overviews a prototype of a discussion visualization system.
{"title":"Discussion Visualization Based on Analysis of Comments to Web News","authors":"Hiroki Wakabayashi, H. Nakayama, R. Onuma, H. Kaminaga, Y. Miyadera, Shoichi Nakamura","doi":"10.1109/CSCI54926.2021.00239","DOIUrl":"https://doi.org/10.1109/CSCI54926.2021.00239","url":null,"abstract":"Opportunities for conducting discussions and expressing opinions on the Web have increased. It is desirable to fully understand the processes and main points of such discussions. In particular, it is important to understand both the main points of discussions and trends of opinions together rather than superficial results. However, such understanding is often difficult since the number of utterances increases as time passes and discussions become complicated. In this research, we aimed at developing methods for visualizing discussions in comments to Web news so that novices can understand both the main points and trends of opinions. This paper mainly overviews a prototype of a discussion visualization system.","PeriodicalId":206881,"journal":{"name":"2021 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125924076","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 : 2021-12-01DOI: 10.1109/CSCI54926.2021.00176
Changfeng Yu, Cheng Zhang, Hao Zhang, Jie Wang
We present an efficient algorithm to automatically reformat text contained in multiple nodes that are spread out in a DOM tree of an HTML file converted from a PDF document. Reformatting text on the fly is needed for hierarchical reading and other text-analytic applications. A naive approach would traverse the DOM tree multiple times, failing to meet the requirement of real-time reformatting. Our algorithm meets the real-time requirement by indexing text nodes and sentences with a pair of tag holders inserted into each text node to allow fast reformatting.
{"title":"AutoTR: Efficient Reformatting Text Spread out in a DOM Tree for Text-Analytic Applications","authors":"Changfeng Yu, Cheng Zhang, Hao Zhang, Jie Wang","doi":"10.1109/CSCI54926.2021.00176","DOIUrl":"https://doi.org/10.1109/CSCI54926.2021.00176","url":null,"abstract":"We present an efficient algorithm to automatically reformat text contained in multiple nodes that are spread out in a DOM tree of an HTML file converted from a PDF document. Reformatting text on the fly is needed for hierarchical reading and other text-analytic applications. A naive approach would traverse the DOM tree multiple times, failing to meet the requirement of real-time reformatting. Our algorithm meets the real-time requirement by indexing text nodes and sentences with a pair of tag holders inserted into each text node to allow fast reformatting.","PeriodicalId":206881,"journal":{"name":"2021 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125950190","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 : 2021-12-01DOI: 10.1109/CSCI54926.2021.00284
Daiyaan Ijaz, Fady Nissan, Henry Dare, Jonathan Williams, Sean Radatz, William Parker, S. Bogle, Mohammed Mahmoud
The rising use of social media has changed how humans fundamentally interact with computers and with each other. The widespread and continuous use of social media has led to increasing awareness of its impact on mental health and the addictiveness of these interactions. It has also changed interpersonal interaction, how companies conduct marketing, and the way information is presented online. This paper discusses how the devices we use to communicate have become an integral part of life, how the increased connectivity has impacted our society, social media addiction, interface design, user experience and other developments with Human Computer Interaction (HCI) in social media.
{"title":"The Impact of Social Media On HCI","authors":"Daiyaan Ijaz, Fady Nissan, Henry Dare, Jonathan Williams, Sean Radatz, William Parker, S. Bogle, Mohammed Mahmoud","doi":"10.1109/CSCI54926.2021.00284","DOIUrl":"https://doi.org/10.1109/CSCI54926.2021.00284","url":null,"abstract":"The rising use of social media has changed how humans fundamentally interact with computers and with each other. The widespread and continuous use of social media has led to increasing awareness of its impact on mental health and the addictiveness of these interactions. It has also changed interpersonal interaction, how companies conduct marketing, and the way information is presented online. This paper discusses how the devices we use to communicate have become an integral part of life, how the increased connectivity has impacted our society, social media addiction, interface design, user experience and other developments with Human Computer Interaction (HCI) in social media.","PeriodicalId":206881,"journal":{"name":"2021 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"140 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123421882","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 : 2021-12-01DOI: 10.1109/CSCI54926.2021.00058
M. Amini, L. Njilla, Ahmed Imteaj, Calvin Mark
The optimal operation of complex networks and critical infrastructures requires solving various large-scale decision-making problems. These problems usually are formulated as optimization problems with several variables and constraints. This leads to the high computational complexity of solving the underlying optimization problem. Hence, we require efficient methods to first model the operational objective function and constraints of the complex networks, and how they can leverage available computational resources to achieve the optimal operation of the entire system. We further need to ensure data security of decision-making entities, e.g., network flow problems, and their impact on the secure operation of the system. The proposed framework and algorithms in this paper include distributed intelligence among heterogeneous agents in a complex network represented by a graph of nodes and edges among them. Our utilized methods act as efficient computational algorithms to solve the underlying optimization problems of these networks in a computationally-efficient fashion. In order to evaluate the introduced distributed algorithm for linear-constrained optimization with a quadratic cost function, we used a random network with different numbers of nodes and edges. We illustrate the run-time and convergence of the distributed method over various networks.
{"title":"Distributed Network Optimization for Secure Operation of Interdependent Complex Networks","authors":"M. Amini, L. Njilla, Ahmed Imteaj, Calvin Mark","doi":"10.1109/CSCI54926.2021.00058","DOIUrl":"https://doi.org/10.1109/CSCI54926.2021.00058","url":null,"abstract":"The optimal operation of complex networks and critical infrastructures requires solving various large-scale decision-making problems. These problems usually are formulated as optimization problems with several variables and constraints. This leads to the high computational complexity of solving the underlying optimization problem. Hence, we require efficient methods to first model the operational objective function and constraints of the complex networks, and how they can leverage available computational resources to achieve the optimal operation of the entire system. We further need to ensure data security of decision-making entities, e.g., network flow problems, and their impact on the secure operation of the system. The proposed framework and algorithms in this paper include distributed intelligence among heterogeneous agents in a complex network represented by a graph of nodes and edges among them. Our utilized methods act as efficient computational algorithms to solve the underlying optimization problems of these networks in a computationally-efficient fashion. In order to evaluate the introduced distributed algorithm for linear-constrained optimization with a quadratic cost function, we used a random network with different numbers of nodes and edges. We illustrate the run-time and convergence of the distributed method over various networks.","PeriodicalId":206881,"journal":{"name":"2021 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"113 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123699009","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 : 2021-12-01DOI: 10.1109/CSCI54926.2021.00197
Luiz Manella Pereira, S. S. Iyengar, M. Amini
Network resilience is crucial to ensure reliable and secure operation of critical infrastructures. Although graph theoretic methods have been developed to quantify the topological resilience of networks, i.e., measuring resilience with respect to connectivity, in this study we propose to use the tools from Topological Data Analysis (TDA), Algebraic Topology, and Optimal Transport (OT). In our prior work, we used these tools to create a resilience metric that bypassed the need to embed a network onto a space. We also hypothesized that embeddings could encode different information about a network and that different embeddings could result in different outcomes when computing resilience. In this paper we attempt to test this hypothesis. We will utilize the WEGL framework to compute the embedding for the considered network and compare the results against our prior work, which did not use an embedding process. To our knowledge, this is the first attempt to study the ramifications of choosing an embedding, thus providing a novel understanding into how to choose an embedding and whether such a choice matters when quantifying resilience.
{"title":"On the Impact of the Embedding Process on Network Resilience Quantification","authors":"Luiz Manella Pereira, S. S. Iyengar, M. Amini","doi":"10.1109/CSCI54926.2021.00197","DOIUrl":"https://doi.org/10.1109/CSCI54926.2021.00197","url":null,"abstract":"Network resilience is crucial to ensure reliable and secure operation of critical infrastructures. Although graph theoretic methods have been developed to quantify the topological resilience of networks, i.e., measuring resilience with respect to connectivity, in this study we propose to use the tools from Topological Data Analysis (TDA), Algebraic Topology, and Optimal Transport (OT). In our prior work, we used these tools to create a resilience metric that bypassed the need to embed a network onto a space. We also hypothesized that embeddings could encode different information about a network and that different embeddings could result in different outcomes when computing resilience. In this paper we attempt to test this hypothesis. We will utilize the WEGL framework to compute the embedding for the considered network and compare the results against our prior work, which did not use an embedding process. To our knowledge, this is the first attempt to study the ramifications of choosing an embedding, thus providing a novel understanding into how to choose an embedding and whether such a choice matters when quantifying resilience.","PeriodicalId":206881,"journal":{"name":"2021 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123797435","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 : 2021-12-01DOI: 10.1109/CSCI54926.2021.00154
J. Dobes, D. Cerny
There are many situations when systems of non-linear differential algebraic equations need to be solved with extraordinary precision. A steady-state analysis (determining the steady-state period of a system after a transient) is a typical case because a vector of unknown variables should be exactly the same after a numerical integration on the period-long interval. Therefore, we need to develop such kinds of numerical algorithms that are computationally effective, even at very high requirements on the accuracy of the results. In the paper, an efficient and reliable algorithm for solving systems of algebraic-differential nonlinear equations is characterized first. Unlike in other cases, the procedure is based on a sophisticated arrangement of the Newton interpolation polynomial (i.e., not the Lagrange one). This feature provides greater flexibility in rapidly changing interpolation step sizes and orders during numerical integration. At the end of the paper, two complicated examples are presented to demonstrate that the algorithm’s computational requirement is quite low, even at very high demands on the accuracy of results.
{"title":"An Algorithm to Solve Systems of Nonlinear Differential-Algebraic Equations With Extraordinary Efficiency Even at High Demanded Precisions","authors":"J. Dobes, D. Cerny","doi":"10.1109/CSCI54926.2021.00154","DOIUrl":"https://doi.org/10.1109/CSCI54926.2021.00154","url":null,"abstract":"There are many situations when systems of non-linear differential algebraic equations need to be solved with extraordinary precision. A steady-state analysis (determining the steady-state period of a system after a transient) is a typical case because a vector of unknown variables should be exactly the same after a numerical integration on the period-long interval. Therefore, we need to develop such kinds of numerical algorithms that are computationally effective, even at very high requirements on the accuracy of the results. In the paper, an efficient and reliable algorithm for solving systems of algebraic-differential nonlinear equations is characterized first. Unlike in other cases, the procedure is based on a sophisticated arrangement of the Newton interpolation polynomial (i.e., not the Lagrange one). This feature provides greater flexibility in rapidly changing interpolation step sizes and orders during numerical integration. At the end of the paper, two complicated examples are presented to demonstrate that the algorithm’s computational requirement is quite low, even at very high demands on the accuracy of results.","PeriodicalId":206881,"journal":{"name":"2021 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125355774","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 : 2021-12-01DOI: 10.1109/CSCI54926.2021.00272
F. Belamri, Samra Boulfekhar, Pr Djamil Aissani
The unique characteristics of the Ad Hoc Vehicle Network (VANET), such as high mobility and dynamic network topology, greatly affect data transmission. Indeed, selecting a promising route that forward data is subject to multiple Quality of Service (QoS) constraint such as link failure. In this paper, we propose the Ant Colony Link state aware geographic Opportunistic routing protocol ACLSGO. Based on path robustness and Ant Colony Optimization (ACO), the proposed ACLSGO selects the best candidate node set and determines the optimal priority node to transmit the data. Simulation results show that ACLSGO protocol outperforms LSGO in terms of packet delivery ratio, throughput and also the average end-to-end delay is considerably reduced.
{"title":"ACLSGO: Ant Colony Link State aware Geographic Opportunistic routing protocol for VANET","authors":"F. Belamri, Samra Boulfekhar, Pr Djamil Aissani","doi":"10.1109/CSCI54926.2021.00272","DOIUrl":"https://doi.org/10.1109/CSCI54926.2021.00272","url":null,"abstract":"The unique characteristics of the Ad Hoc Vehicle Network (VANET), such as high mobility and dynamic network topology, greatly affect data transmission. Indeed, selecting a promising route that forward data is subject to multiple Quality of Service (QoS) constraint such as link failure. In this paper, we propose the Ant Colony Link state aware geographic Opportunistic routing protocol ACLSGO. Based on path robustness and Ant Colony Optimization (ACO), the proposed ACLSGO selects the best candidate node set and determines the optimal priority node to transmit the data. Simulation results show that ACLSGO protocol outperforms LSGO in terms of packet delivery ratio, throughput and also the average end-to-end delay is considerably reduced.","PeriodicalId":206881,"journal":{"name":"2021 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126949922","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 : 2021-12-01DOI: 10.1109/CSCI54926.2021.00195
Richard Romero Izurieta, Luis Jhony Caucha Morales, Segundo Moisés Toapanta Toapanta, Luis Enrique Mafla Gallegos, José Antonio Orizaga Trejo
Public organizations have the responsibility by law to manage sensitive data that must be shared; the problem was found that organizations are very vulnerable and that computer attacks are becoming more and more effective and dangerous. As an objective of this research, the Information Security of public organizations in Ecuador was analyzed, the current status was known and improvements in its management were proposed. The deductive method was applied for the review and analysis of factors and variables that allow improving information security management in public organizations. The result was an Information security management model based on strategic planning, process and matrices for the evaluation of the information security management capacity. It was concluded that public organizations in Ecuador have a low level of information security management capacity, 70% are at a "Formative" level and 22% at a "Managed" level. To Manage Information Security in an optimal way, it is necessary to start from a strategic planning that allows directing the resources and capacities available to the achievement of the objectives established for the organization.
{"title":"Analysis of the Information Security of Public Organizations in Ecuador","authors":"Richard Romero Izurieta, Luis Jhony Caucha Morales, Segundo Moisés Toapanta Toapanta, Luis Enrique Mafla Gallegos, José Antonio Orizaga Trejo","doi":"10.1109/CSCI54926.2021.00195","DOIUrl":"https://doi.org/10.1109/CSCI54926.2021.00195","url":null,"abstract":"Public organizations have the responsibility by law to manage sensitive data that must be shared; the problem was found that organizations are very vulnerable and that computer attacks are becoming more and more effective and dangerous. As an objective of this research, the Information Security of public organizations in Ecuador was analyzed, the current status was known and improvements in its management were proposed. The deductive method was applied for the review and analysis of factors and variables that allow improving information security management in public organizations. The result was an Information security management model based on strategic planning, process and matrices for the evaluation of the information security management capacity. It was concluded that public organizations in Ecuador have a low level of information security management capacity, 70% are at a \"Formative\" level and 22% at a \"Managed\" level. To Manage Information Security in an optimal way, it is necessary to start from a strategic planning that allows directing the resources and capacities available to the achievement of the objectives established for the organization.","PeriodicalId":206881,"journal":{"name":"2021 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114961423","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 : 2021-12-01DOI: 10.1109/CSCI54926.2021.00294
A. Diallo, C. Diallo
Applying deep learning to IoT data classification would yield deeper and more useful insights. IoT field is very wide and has several applications. In this paper we focus on smart home, especially human activity recognition within a house equipped with ambient sensors. Firstly, we describe ARAS Human Activity Dataset that are used in models training and testing. Secondly, we apply three deep learning models to it in order to classify the activities carried out by residents within the house. The deep learning models that we use in our experiments are : a Multilayer Perceptron (MLP), a Recurrent Neural Network(RNN) and Long short-term memory(LSTM). The results show best performances with MLP followed by RNN. In addition, it should be noted that there is a strong correlation between the frequency of activities and their recognition rate.
{"title":"Human Activity Recognition in Smart Home using Deep Learning Models","authors":"A. Diallo, C. Diallo","doi":"10.1109/CSCI54926.2021.00294","DOIUrl":"https://doi.org/10.1109/CSCI54926.2021.00294","url":null,"abstract":"Applying deep learning to IoT data classification would yield deeper and more useful insights. IoT field is very wide and has several applications. In this paper we focus on smart home, especially human activity recognition within a house equipped with ambient sensors. Firstly, we describe ARAS Human Activity Dataset that are used in models training and testing. Secondly, we apply three deep learning models to it in order to classify the activities carried out by residents within the house. The deep learning models that we use in our experiments are : a Multilayer Perceptron (MLP), a Recurrent Neural Network(RNN) and Long short-term memory(LSTM). The results show best performances with MLP followed by RNN. In addition, it should be noted that there is a strong correlation between the frequency of activities and their recognition rate.","PeriodicalId":206881,"journal":{"name":"2021 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114396861","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 : 2021-12-01DOI: 10.1109/CSCI54926.2021.00252
Cami Czejdo, S. Bhattacharya
Advances in Artificial Intelligence (AI) Language Models (LMs) and their new applications are continuously reported. LMs, respond to plain text that is readily human interpretable. Based on these human-like responses, hopes are created for achieving human-level performance for various language tasks soon. This paper discusses challenges in applying current LMs to design an AI Mental Health Assistant. The results of experiments are encouraging but show that significant research and development efforts are necessary to reach the practical usefulness of AI. We discuss that chaining multiple LMs might be needed to filter or post-process the results. Additionally, the models themselves might need to go through enhanced training with a more significant emphasis on empathy, ethics, and moral standards, especially in the very sensitive mental health area.
{"title":"Towards Language Models for AI Mental Health Assistant Design","authors":"Cami Czejdo, S. Bhattacharya","doi":"10.1109/CSCI54926.2021.00252","DOIUrl":"https://doi.org/10.1109/CSCI54926.2021.00252","url":null,"abstract":"Advances in Artificial Intelligence (AI) Language Models (LMs) and their new applications are continuously reported. LMs, respond to plain text that is readily human interpretable. Based on these human-like responses, hopes are created for achieving human-level performance for various language tasks soon. This paper discusses challenges in applying current LMs to design an AI Mental Health Assistant. The results of experiments are encouraging but show that significant research and development efforts are necessary to reach the practical usefulness of AI. We discuss that chaining multiple LMs might be needed to filter or post-process the results. Additionally, the models themselves might need to go through enhanced training with a more significant emphasis on empathy, ethics, and moral standards, especially in the very sensitive mental health area.","PeriodicalId":206881,"journal":{"name":"2021 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"96 1 Suppl 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129038649","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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