Pub Date : 2021-01-22DOI: 10.1080/24751839.2021.1871819
Vimal Kumar, N. Tyagi
ABSTRACT The bandwidth-intensive applications on Smart-Mobile-Devices (SMDs) are increasing with SMD's colossal growth. The overlapped cellular and non-cellular networks, in hot-spot-places, and SMDs capabilities are significant reasons for this growth. SMD's interfaces-RAT (Radio-Access-Technology) can have complementary link characteristics. The end-users can avail always-best-connectivity (ABC) on their SMDs with complementary RAT characteristics. This paper proposes an Integrated-multi-RAT-utilization (Im-Ru) framework for multipath-computing support to realize ABC for the end-users. The Im-Ru framework has two approaches. The First is a hybrid-RAT-discovery model based on SMD's interfaces, current-location, and identification using ANDSF and MIIS servers. The second is the user's preference-based RAT-selection using weighted-RAT-parameters. We observe that the Im-Ru framework for multipath-computing is useful in future 5G-NR networks. We analyzed the Im-Ru's performance related to average-throughput improvement over the existing approaches for SMD's different speeds and observed a significant improvement. The experimental results show that Im-Ru is more reliable by realizing lower packet-loss and delay than existing work.
{"title":"An integrated-multi-RAT framework for multipath-computing in heterogeneous-wireless network","authors":"Vimal Kumar, N. Tyagi","doi":"10.1080/24751839.2021.1871819","DOIUrl":"https://doi.org/10.1080/24751839.2021.1871819","url":null,"abstract":"ABSTRACT The bandwidth-intensive applications on Smart-Mobile-Devices (SMDs) are increasing with SMD's colossal growth. The overlapped cellular and non-cellular networks, in hot-spot-places, and SMDs capabilities are significant reasons for this growth. SMD's interfaces-RAT (Radio-Access-Technology) can have complementary link characteristics. The end-users can avail always-best-connectivity (ABC) on their SMDs with complementary RAT characteristics. This paper proposes an Integrated-multi-RAT-utilization (Im-Ru) framework for multipath-computing support to realize ABC for the end-users. The Im-Ru framework has two approaches. The First is a hybrid-RAT-discovery model based on SMD's interfaces, current-location, and identification using ANDSF and MIIS servers. The second is the user's preference-based RAT-selection using weighted-RAT-parameters. We observe that the Im-Ru framework for multipath-computing is useful in future 5G-NR networks. We analyzed the Im-Ru's performance related to average-throughput improvement over the existing approaches for SMD's different speeds and observed a significant improvement. The experimental results show that Im-Ru is more reliable by realizing lower packet-loss and delay than existing work.","PeriodicalId":32180,"journal":{"name":"Journal of Information and Telecommunication","volume":"5 1","pages":"350 - 374"},"PeriodicalIF":2.7,"publicationDate":"2021-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/24751839.2021.1871819","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48410749","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 : 2021-01-01DOI: 10.1080/24751839.2021.1963912
Jose Fabio Ribeiro Bezerra
{"title":"Content-based fake news classification through modified voting ensemble","authors":"Jose Fabio Ribeiro Bezerra","doi":"10.1080/24751839.2021.1963912","DOIUrl":"https://doi.org/10.1080/24751839.2021.1963912","url":null,"abstract":"","PeriodicalId":32180,"journal":{"name":"Journal of Information and Telecommunication","volume":"5 1","pages":"499-513"},"PeriodicalIF":2.7,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"60140756","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 : 2020-12-25DOI: 10.1080/24751839.2020.1843121
Redwan Hasif Alvi, M. H. Rahman, Adib Al Shaeed Khan, R. Rahman
ABSTRACT Neonatal sepsis that is a major threat for maternal and neonatal health worldwide. In this work we design non-invasive, deep learning classification models for predicting accurately and efficiently the early-onset sepsis in neonates in Neonatal Intensive Care Units. By non-invasive, it means that no external instrument or foreign body is introduced when taking data for the classifier. Moreover, the data collected for the purpose of predicting and classifying subjects with neonatal sepsis is in the form of tabular, structured data. The deep learning classification models we design and propose in this are known for working with time series, sequential or image data. Hence, the objective of the current research is to propose such a model that makes use of the powerful tools inherent in Neural Networks for pattern recognition, and use them to outperform traditional machine learning algorithms to detect early-onset neonatal sepsis. Real life neonatal sepsis data samples from two different hospitals are used (Crecer’s Hospital Centre in Cartagena-Colombia and Children’s Hospital of Philadelphia) to make the evaluation of the Neural Networks as authentic as possible.
{"title":"Deep learning approach on tabular data to predict early-onset neonatal sepsis","authors":"Redwan Hasif Alvi, M. H. Rahman, Adib Al Shaeed Khan, R. Rahman","doi":"10.1080/24751839.2020.1843121","DOIUrl":"https://doi.org/10.1080/24751839.2020.1843121","url":null,"abstract":"ABSTRACT Neonatal sepsis that is a major threat for maternal and neonatal health worldwide. In this work we design non-invasive, deep learning classification models for predicting accurately and efficiently the early-onset sepsis in neonates in Neonatal Intensive Care Units. By non-invasive, it means that no external instrument or foreign body is introduced when taking data for the classifier. Moreover, the data collected for the purpose of predicting and classifying subjects with neonatal sepsis is in the form of tabular, structured data. The deep learning classification models we design and propose in this are known for working with time series, sequential or image data. Hence, the objective of the current research is to propose such a model that makes use of the powerful tools inherent in Neural Networks for pattern recognition, and use them to outperform traditional machine learning algorithms to detect early-onset neonatal sepsis. Real life neonatal sepsis data samples from two different hospitals are used (Crecer’s Hospital Centre in Cartagena-Colombia and Children’s Hospital of Philadelphia) to make the evaluation of the Neural Networks as authentic as possible.","PeriodicalId":32180,"journal":{"name":"Journal of Information and Telecommunication","volume":"5 1","pages":"226 - 246"},"PeriodicalIF":2.7,"publicationDate":"2020-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/24751839.2020.1843121","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46500511","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 : 2020-12-25DOI: 10.1080/24751839.2020.1857039
E. Szwarc, I. Nielsen, Czeslaw Smutnicki, G. Bocewicz, Z. Banaszak, J. Bilski
ABSTRACT Selection of competent employees is one of the numerous factors that determine the success of a project. The literature describes many approaches that help decision makers to recruit candidates with the required skills. Only a few of them consider the disruptions that can occur during the implementation of a project, such as employee absenteeism and fluctuations in the duration of activities, etc. Collectively, what these approaches amount to is proactive planning of employee teams with redundant competences. Searching for competence frameworks robust to disruptions involves time-consuming calculations, which do not guarantee that an admissible solution will be found. In view of this, in the present study, we propose sufficient conditions, the fulfilment of which guarantees the existence of such a solution. By testing these conditions, one can determine whether there exists an admissible solution, i.e. whether it is at all worth searching for a robust competence framework. The possibilities of practical application of the proposed method are illustrated with an example.
{"title":"Competence-oriented project team planning – university case study","authors":"E. Szwarc, I. Nielsen, Czeslaw Smutnicki, G. Bocewicz, Z. Banaszak, J. Bilski","doi":"10.1080/24751839.2020.1857039","DOIUrl":"https://doi.org/10.1080/24751839.2020.1857039","url":null,"abstract":"ABSTRACT Selection of competent employees is one of the numerous factors that determine the success of a project. The literature describes many approaches that help decision makers to recruit candidates with the required skills. Only a few of them consider the disruptions that can occur during the implementation of a project, such as employee absenteeism and fluctuations in the duration of activities, etc. Collectively, what these approaches amount to is proactive planning of employee teams with redundant competences. Searching for competence frameworks robust to disruptions involves time-consuming calculations, which do not guarantee that an admissible solution will be found. In view of this, in the present study, we propose sufficient conditions, the fulfilment of which guarantees the existence of such a solution. By testing these conditions, one can determine whether there exists an admissible solution, i.e. whether it is at all worth searching for a robust competence framework. The possibilities of practical application of the proposed method are illustrated with an example.","PeriodicalId":32180,"journal":{"name":"Journal of Information and Telecommunication","volume":"5 1","pages":"310 - 333"},"PeriodicalIF":2.7,"publicationDate":"2020-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/24751839.2020.1857039","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44402716","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 : 2020-12-02DOI: 10.1080/24751839.2020.1847490
Inga Vagale, E. Lipenbergs, V. Bobrovs, G. Ivanovs
ABSTRACT In modern world, technology plays a significant role. Upcoming services, demanding a specific level of service quality that should be guaranteed no matter what, will impose obligations to network performance and capacity. European strategy for broadband development prescribes a set of quality indicators that networks should correspond. But imposed obligations themselves don’t guarantee the persistent level of quality. European initiatives of geographical mapping of broadband access, which are developed in order to monitor the development of internet access services, propose guidance for gathering and representation of estimated QoS parameters at the so-called QoS-1 level, whereas monitoring of actual network performance on QoS-2 level and representation of real and objective internet quality indicators rests undefined. Besides ensuring that quality is described in meaningful and comparable manner the general measurement methodology that suits various purposes should be established. This research is aimed to develop principles of monitoring and objective representation of internet access service quality parameters in specific location on QoS-2 level, as well as to establish joint mechanism to obtain the quality of service data that would be appropriate for different needs. This research is directed to the mobile internet access service.
{"title":"Development of internet measurement principles for representation of measured provision of service (QoS-2)","authors":"Inga Vagale, E. Lipenbergs, V. Bobrovs, G. Ivanovs","doi":"10.1080/24751839.2020.1847490","DOIUrl":"https://doi.org/10.1080/24751839.2020.1847490","url":null,"abstract":"ABSTRACT In modern world, technology plays a significant role. Upcoming services, demanding a specific level of service quality that should be guaranteed no matter what, will impose obligations to network performance and capacity. European strategy for broadband development prescribes a set of quality indicators that networks should correspond. But imposed obligations themselves don’t guarantee the persistent level of quality. European initiatives of geographical mapping of broadband access, which are developed in order to monitor the development of internet access services, propose guidance for gathering and representation of estimated QoS parameters at the so-called QoS-1 level, whereas monitoring of actual network performance on QoS-2 level and representation of real and objective internet quality indicators rests undefined. Besides ensuring that quality is described in meaningful and comparable manner the general measurement methodology that suits various purposes should be established. This research is aimed to develop principles of monitoring and objective representation of internet access service quality parameters in specific location on QoS-2 level, as well as to establish joint mechanism to obtain the quality of service data that would be appropriate for different needs. This research is directed to the mobile internet access service.","PeriodicalId":32180,"journal":{"name":"Journal of Information and Telecommunication","volume":"5 1","pages":"267 - 277"},"PeriodicalIF":2.7,"publicationDate":"2020-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/24751839.2020.1847490","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42374035","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 : 2020-11-27DOI: 10.1080/24751839.2020.1847507
Jiho Cho, Hongsuk Yi, Heejin Jung, Khac-Hoai Nam Bui
ABSTRACT Recently, with the rapid development of deep learning models, traffic analysis using image datasets recently has attracted more attention. Specifically, the network traffic can be represented to images as the input for deep learning models to provide various applications (e.g. Spatio-Temporal traffic forecasting). In this study, we propose a new image generation approach for traffic density classification in terms of large-scale road network. Particularly, traffic volume and speed are at certain areas able to be measured by using surveillance systems (e.g. loop detectors). However, measuring the density is difficult which depends on the spatial correlation from the perspective of the network. Consequently, an effective image generation approach, based on information arrival and departure time of vehicles, is proposed to deal with this problem. Regarding the experiment, traffic density classification using a convolutional neural network is executed on roadside equipment data of 11 continuous intersections for evaluating the effectiveness of the proposed approach.
{"title":"An image generation approach for traffic density classification at large-scale road network","authors":"Jiho Cho, Hongsuk Yi, Heejin Jung, Khac-Hoai Nam Bui","doi":"10.1080/24751839.2020.1847507","DOIUrl":"https://doi.org/10.1080/24751839.2020.1847507","url":null,"abstract":"ABSTRACT Recently, with the rapid development of deep learning models, traffic analysis using image datasets recently has attracted more attention. Specifically, the network traffic can be represented to images as the input for deep learning models to provide various applications (e.g. Spatio-Temporal traffic forecasting). In this study, we propose a new image generation approach for traffic density classification in terms of large-scale road network. Particularly, traffic volume and speed are at certain areas able to be measured by using surveillance systems (e.g. loop detectors). However, measuring the density is difficult which depends on the spatial correlation from the perspective of the network. Consequently, an effective image generation approach, based on information arrival and departure time of vehicles, is proposed to deal with this problem. Regarding the experiment, traffic density classification using a convolutional neural network is executed on roadside equipment data of 11 continuous intersections for evaluating the effectiveness of the proposed approach.","PeriodicalId":32180,"journal":{"name":"Journal of Information and Telecommunication","volume":"5 1","pages":"296 - 309"},"PeriodicalIF":2.7,"publicationDate":"2020-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/24751839.2020.1847507","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43212639","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 : 2020-11-27DOI: 10.1080/24751839.2020.1847379
Botambu Collins, Dinh Tuyen Hoang, N. Nguyen, D. Hwang
ABSTRACT Social media following its introduction has witnessed a lot of scholarly attention in recent years due to its growing popularity. These various social media sites have become the mecca of information because of their less costly and easy accessibility. Although these sites were developed to enhance our lives, they are seen as both angelic and vicious. Growing misinformation and fake content by malicious users have not only plagued our online social media ecosystem into chaos, but it also meted untold suffering to humankind. Recently, social media has witnessed a reverberation amid the proliferation of fake news which has made people reluctant to engage in genuine news sharing for fear that such information is false. Consequently, there is a dire need for these fake content to be detected and removed from social media. This study explores the various methods of combating fake news on social media such as Natural Language Processing, Hybrid model. We surmised that detecting fake news is a challenging and complex issue, however, it remains a workable task. Revelation in this study holds that the application of hybrid-machine learning techniques and the collective effort of humans could stand a higher chance of fighting misinformation on social media.
{"title":"Trends in combating fake news on social media – a survey","authors":"Botambu Collins, Dinh Tuyen Hoang, N. Nguyen, D. Hwang","doi":"10.1080/24751839.2020.1847379","DOIUrl":"https://doi.org/10.1080/24751839.2020.1847379","url":null,"abstract":"ABSTRACT Social media following its introduction has witnessed a lot of scholarly attention in recent years due to its growing popularity. These various social media sites have become the mecca of information because of their less costly and easy accessibility. Although these sites were developed to enhance our lives, they are seen as both angelic and vicious. Growing misinformation and fake content by malicious users have not only plagued our online social media ecosystem into chaos, but it also meted untold suffering to humankind. Recently, social media has witnessed a reverberation amid the proliferation of fake news which has made people reluctant to engage in genuine news sharing for fear that such information is false. Consequently, there is a dire need for these fake content to be detected and removed from social media. This study explores the various methods of combating fake news on social media such as Natural Language Processing, Hybrid model. We surmised that detecting fake news is a challenging and complex issue, however, it remains a workable task. Revelation in this study holds that the application of hybrid-machine learning techniques and the collective effort of humans could stand a higher chance of fighting misinformation on social media.","PeriodicalId":32180,"journal":{"name":"Journal of Information and Telecommunication","volume":"5 1","pages":"247 - 266"},"PeriodicalIF":2.7,"publicationDate":"2020-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/24751839.2020.1847379","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45998250","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 : 2020-11-27DOI: 10.1080/24751839.2020.1847506
C. Orłowski, Dawid Cygert, P. Nowak
ABSTRACT The aim of this article is extended for [Orłowski, C., Cygert, D., & Nowak, P. (2020). Continuous improvement process model for supporting the construction of Internet of Things system design environments. In Communications in computer and information science (pp. 424–435). Springer. https://doi.org/10.1007/978-981-15-3380-8_37] proposal build a model of continuous improvement systems design support, the Internet of Things (IoT). The model was based on the authors’ experience gained during the design process IoT nodes. Therefore, the article presents both the research experiment and the extent to which this experiment pointed to the need to design a production environment. This environment is still being developed. To achieve this goal, the article was divided into four main parts. At the beginning a basic project was presented, which goal was to create an IoT node. During its implementation, there were requirements for a system that would be used to monitor the status of IoT nodes and data flow. Therefore, the second chapter presents the functions of the production environment necessary for both designing the nodes and monitoring their condition. While in the paper [Orłowski, C., Cygert, D., & Nowak, P. (2020). Continuous improvement process model for supporting the construction of Internet of Things system design environments. In Communications in computer and information science (pp. 424–435). Springer. https://doi.org/10.1007/978-981-15-3380-8_37], the basic functions were introduced in the presented article the scope was extended by the functionalities currently tested. They were then called the functions of the application enabling platform (AEP) used in IoT to assess their usefulness in improving the monitoring and maintenance processes of IoT nodes.
{"title":"Extended continuous improvement model for Internet of Things system design environments","authors":"C. Orłowski, Dawid Cygert, P. Nowak","doi":"10.1080/24751839.2020.1847506","DOIUrl":"https://doi.org/10.1080/24751839.2020.1847506","url":null,"abstract":"ABSTRACT The aim of this article is extended for [Orłowski, C., Cygert, D., & Nowak, P. (2020). Continuous improvement process model for supporting the construction of Internet of Things system design environments. In Communications in computer and information science (pp. 424–435). Springer. https://doi.org/10.1007/978-981-15-3380-8_37] proposal build a model of continuous improvement systems design support, the Internet of Things (IoT). The model was based on the authors’ experience gained during the design process IoT nodes. Therefore, the article presents both the research experiment and the extent to which this experiment pointed to the need to design a production environment. This environment is still being developed. To achieve this goal, the article was divided into four main parts. At the beginning a basic project was presented, which goal was to create an IoT node. During its implementation, there were requirements for a system that would be used to monitor the status of IoT nodes and data flow. Therefore, the second chapter presents the functions of the production environment necessary for both designing the nodes and monitoring their condition. While in the paper [Orłowski, C., Cygert, D., & Nowak, P. (2020). Continuous improvement process model for supporting the construction of Internet of Things system design environments. In Communications in computer and information science (pp. 424–435). Springer. https://doi.org/10.1007/978-981-15-3380-8_37], the basic functions were introduced in the presented article the scope was extended by the functionalities currently tested. They were then called the functions of the application enabling platform (AEP) used in IoT to assess their usefulness in improving the monitoring and maintenance processes of IoT nodes.","PeriodicalId":32180,"journal":{"name":"Journal of Information and Telecommunication","volume":"5 1","pages":"279 - 295"},"PeriodicalIF":2.7,"publicationDate":"2020-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/24751839.2020.1847506","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45492163","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 : 2020-11-23DOI: 10.1080/24751839.2020.1833136
T. Mayeesha, Abdullah Md. Sarwar, R. Rahman
ABSTRACT Recent advances in the field of natural language processing has improved state-of-the-art performances on many tasks including question answering for languages like English. Bengali language is ranked seventh and is spoken by about 300 million people all over the world. But due to lack of data and active research on QA similar progress has not been achieved for Bengali. Unlike English, there is no benchmark large scale QA dataset collected for Bengali, no pretrained language model that can be modified for Bengali question answering and no human baseline score for QA has been established either. In this work we use state-of-the-art transformer models to train QA system on a synthetic reading comprehension dataset translated from one of the most popular benchmark datasets in English called SQuAD 2.0. We collect a smaller human annotated QA dataset from Bengali Wikipedia with popular topics from Bangladeshi culture for evaluating our models. Finally, we compare our models with human children to set up a benchmark score using survey experiments.
{"title":"Deep learning based question answering system in Bengali","authors":"T. Mayeesha, Abdullah Md. Sarwar, R. Rahman","doi":"10.1080/24751839.2020.1833136","DOIUrl":"https://doi.org/10.1080/24751839.2020.1833136","url":null,"abstract":"ABSTRACT Recent advances in the field of natural language processing has improved state-of-the-art performances on many tasks including question answering for languages like English. Bengali language is ranked seventh and is spoken by about 300 million people all over the world. But due to lack of data and active research on QA similar progress has not been achieved for Bengali. Unlike English, there is no benchmark large scale QA dataset collected for Bengali, no pretrained language model that can be modified for Bengali question answering and no human baseline score for QA has been established either. In this work we use state-of-the-art transformer models to train QA system on a synthetic reading comprehension dataset translated from one of the most popular benchmark datasets in English called SQuAD 2.0. We collect a smaller human annotated QA dataset from Bengali Wikipedia with popular topics from Bangladeshi culture for evaluating our models. Finally, we compare our models with human children to set up a benchmark score using survey experiments.","PeriodicalId":32180,"journal":{"name":"Journal of Information and Telecommunication","volume":"5 1","pages":"145 - 178"},"PeriodicalIF":2.7,"publicationDate":"2020-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/24751839.2020.1833136","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43802747","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 : 2020-11-10DOI: 10.1080/24751839.2020.1829387
Lucie Svitáková, M. Valenta, J. Pokorný
ABSTRACT Nowadays, open-source graph databases do not include an inherent mechanism for data relocation that would be based on their usage. They often do not offer even appropriate monitoring that could help to make such a decision. Information about data utilization could, however, work as an input to some decision-making process about more suitable data regrouping that could be much more efficient in terms of intra-network communication. Therefore, we created a module for the graph computational framework TinkerPop that logs traffic generated by the user queries. These logged records serve as an input for the algorithm of Adaptive Partitioning that we enhanced with better balancing, avoidance of local optima and the notion of weighted graphs. This approach yields a 70–80% improvement in intra-network communication, which is comparable to other methods, namely Ja-be-Ja, that offers similar results but has higher computational demands.
{"title":"Enhanced adaptive partitioning in a distributed graph database","authors":"Lucie Svitáková, M. Valenta, J. Pokorný","doi":"10.1080/24751839.2020.1829387","DOIUrl":"https://doi.org/10.1080/24751839.2020.1829387","url":null,"abstract":"ABSTRACT Nowadays, open-source graph databases do not include an inherent mechanism for data relocation that would be based on their usage. They often do not offer even appropriate monitoring that could help to make such a decision. Information about data utilization could, however, work as an input to some decision-making process about more suitable data regrouping that could be much more efficient in terms of intra-network communication. Therefore, we created a module for the graph computational framework TinkerPop that logs traffic generated by the user queries. These logged records serve as an input for the algorithm of Adaptive Partitioning that we enhanced with better balancing, avoidance of local optima and the notion of weighted graphs. This approach yields a 70–80% improvement in intra-network communication, which is comparable to other methods, namely Ja-be-Ja, that offers similar results but has higher computational demands.","PeriodicalId":32180,"journal":{"name":"Journal of Information and Telecommunication","volume":"5 1","pages":"104 - 120"},"PeriodicalIF":2.7,"publicationDate":"2020-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/24751839.2020.1829387","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45590621","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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