Pub Date : 2020-10-07DOI: 10.1109/AICT50176.2020.9368645
Aliya Bannayeva, Mustafa Aslanov
This research focuses on a text prediction model for the Azerbaijani language. Parsed and cleaned Azerbaijani Wikipedia is used as corpus for the language model. In total, there are more than a million distinct words and sentences, and over seven hundred million characters.For the language model itself, a statistical model with n-grams is implemented. N-grams are contiguous sequences of n strings or characters from a given sample of text or speech. The Markov Chain is used as the model to predict the next word.The Markov Chain focuses on the probabilities of the sequence of words in the n-grams, rather than the probabilities of the entire corpus. This simplifies the task at hand and yields in less computational overhead, while still maintaining sensible results. Logically, the higher the N in the n-grams, the more sensible the resulting prediction.Concretely, bigrams, trigrams, quadgrams and fivegrams are implemented. For the evaluation of the model, intrinsic type of evaluation is used, which computes the perplexity rate.
{"title":"Development of the N-gram Model for Azerbaijani Language","authors":"Aliya Bannayeva, Mustafa Aslanov","doi":"10.1109/AICT50176.2020.9368645","DOIUrl":"https://doi.org/10.1109/AICT50176.2020.9368645","url":null,"abstract":"This research focuses on a text prediction model for the Azerbaijani language. Parsed and cleaned Azerbaijani Wikipedia is used as corpus for the language model. In total, there are more than a million distinct words and sentences, and over seven hundred million characters.For the language model itself, a statistical model with n-grams is implemented. N-grams are contiguous sequences of n strings or characters from a given sample of text or speech. The Markov Chain is used as the model to predict the next word.The Markov Chain focuses on the probabilities of the sequence of words in the n-grams, rather than the probabilities of the entire corpus. This simplifies the task at hand and yields in less computational overhead, while still maintaining sensible results. Logically, the higher the N in the n-grams, the more sensible the resulting prediction.Concretely, bigrams, trigrams, quadgrams and fivegrams are implemented. For the evaluation of the model, intrinsic type of evaluation is used, which computes the perplexity rate.","PeriodicalId":136491,"journal":{"name":"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129956486","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 : 2020-10-07DOI: 10.1109/AICT50176.2020.9368575
Sobiya Arsheen, A. Wahid, Khaleel Ahmad, Khujamatov Khalim
Flying Adhoc Network (FANET) is an emerging topic of research in the wireless network area, FANET has several common features with its predecessor e.g. Mobile Adhoc Network (MANET) and Vehicle Adhoc Network (VANET), but the network has several unique features also which make it different from other networks. The sparseness of nodes, coupled with frequent changing of topology significantly affects the data transmission rate of the network. To overcome this problem, FANET can be assisted with Delay Tolerant Network (DTN) approach to exploit its mobility and routing features. The main aim of this work is to make Flying Adhoc Network reliable by deploying two MAC protocols i.e. IEEE 802.11 and IEEE 802.15 and realize the functionality of Delay Tolerant Network (DTN) in a FANET.
{"title":"Flying Ad hoc Network Expedited by DTN Scenario: Reliable and Cost-effective MAC Protocols Perspective","authors":"Sobiya Arsheen, A. Wahid, Khaleel Ahmad, Khujamatov Khalim","doi":"10.1109/AICT50176.2020.9368575","DOIUrl":"https://doi.org/10.1109/AICT50176.2020.9368575","url":null,"abstract":"Flying Adhoc Network (FANET) is an emerging topic of research in the wireless network area, FANET has several common features with its predecessor e.g. Mobile Adhoc Network (MANET) and Vehicle Adhoc Network (VANET), but the network has several unique features also which make it different from other networks. The sparseness of nodes, coupled with frequent changing of topology significantly affects the data transmission rate of the network. To overcome this problem, FANET can be assisted with Delay Tolerant Network (DTN) approach to exploit its mobility and routing features. The main aim of this work is to make Flying Adhoc Network reliable by deploying two MAC protocols i.e. IEEE 802.11 and IEEE 802.15 and realize the functionality of Delay Tolerant Network (DTN) in a FANET.","PeriodicalId":136491,"journal":{"name":"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131154830","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 : 2020-10-07DOI: 10.1109/AICT50176.2020.9368675
M. Farkhadov, N. Petukhova, Mukhabbat Farkhadova
This paper proposes a computerized audio simulator to teach how to correctly pronounce sounds, syllables, and words of the Russian language; the simulator is based on automatic speech recognition systems. The sound and speech simulator is designed to help hearing-impaired people to learn how to correctly pronounce sounds. If we deploy such a service on the Internet and provide high-speed online access to the service, we significantly increase the number of people who can learn how to pronounce sounds.
{"title":"Web-based Sound and Speech Training Software to Help Hearing-impaired People","authors":"M. Farkhadov, N. Petukhova, Mukhabbat Farkhadova","doi":"10.1109/AICT50176.2020.9368675","DOIUrl":"https://doi.org/10.1109/AICT50176.2020.9368675","url":null,"abstract":"This paper proposes a computerized audio simulator to teach how to correctly pronounce sounds, syllables, and words of the Russian language; the simulator is based on automatic speech recognition systems. The sound and speech simulator is designed to help hearing-impaired people to learn how to correctly pronounce sounds. If we deploy such a service on the Internet and provide high-speed online access to the service, we significantly increase the number of people who can learn how to pronounce sounds.","PeriodicalId":136491,"journal":{"name":"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133336184","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 : 2020-10-07DOI: 10.1109/AICT50176.2020.9368569
F. Haque, Anika Hossain Orthy, Shahnewaz Siddique
Starting around 815AD/200AH scholars have put immense effort towards gathering and sifting authentic hadiths, which are prophetic traditions of the Muslim community. The authenticity of a hadith solely depends on the reliability of its reporters and narrators. Till now scholars have had to do this task manually by precisely anatomizing each hadith’s chain of narrators or the list of people related to the transmission of a particular hadith. The evolution of modern computer science techniques has enabled new methods and introduced a potential paradigm shift in the science of hadith authentication. Focusing on the chain of narrators (also known as "Isnad") of a hadith, we have used a technique called ‘Sentiment Analysis’ from Natural Language Processing (NLP) to build a text classifier which tries to predict the authenticity of a hadith. It learns from our custom-made dataset of Isnads and predicts an unknown hadith to be either authentic or fabricated based upon its Isnad. Our classifier was 86% accurate when tested on the test hadith dataset.
{"title":"Hadith Authenticity Prediction using Sentiment Analysis and Machine Learning","authors":"F. Haque, Anika Hossain Orthy, Shahnewaz Siddique","doi":"10.1109/AICT50176.2020.9368569","DOIUrl":"https://doi.org/10.1109/AICT50176.2020.9368569","url":null,"abstract":"Starting around 815AD/200AH scholars have put immense effort towards gathering and sifting authentic hadiths, which are prophetic traditions of the Muslim community. The authenticity of a hadith solely depends on the reliability of its reporters and narrators. Till now scholars have had to do this task manually by precisely anatomizing each hadith’s chain of narrators or the list of people related to the transmission of a particular hadith. The evolution of modern computer science techniques has enabled new methods and introduced a potential paradigm shift in the science of hadith authentication. Focusing on the chain of narrators (also known as \"Isnad\") of a hadith, we have used a technique called ‘Sentiment Analysis’ from Natural Language Processing (NLP) to build a text classifier which tries to predict the authenticity of a hadith. It learns from our custom-made dataset of Isnads and predicts an unknown hadith to be either authentic or fabricated based upon its Isnad. Our classifier was 86% accurate when tested on the test hadith dataset.","PeriodicalId":136491,"journal":{"name":"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130137693","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 : 2020-10-07DOI: 10.1109/AICT50176.2020.9368747
Thaer Thaher, Badie Sartawi
The Artificial Bee Colony (ABC) is a novel nature-inspired metaheuristic optimization algorithm that mimics the behavior of honey bees searching for food sources. The main drawback of ABC, similar to the most of metaheuristics, is the premature convergence (i.e., the earlier stuck into local optima). Recently, the structured population approach, in which the individuals are distributed into multiple sub-populations (called islands), has been widely exploited to maintain the required diversity during the search process and thus reducing the prematurity problem. In this paper, the island model, which is a common structured population approach, is incorporated with the ABC to introduce a parallel variant called (iABC). Besides, an experimental design approach is proposed to analyze the sensitivity of iABC to the parameters of the island model as well as the main specific parameters. The linear regression model and the Analysis of variance (ANOVA) are utilized to estimate the effect of parameters and identify the importance of them. Two well-known benchmark functions are used for evaluation purposes. Experimental results revealed that most parameters and their low-order interactions have a significant influence on the performance of the iABC. Furthermore, the proposed iABC proved its superiority compared to other state-of-the-art algorithms.
{"title":"An Experimental Design Approach to Analyse the Performance of Island-Based Parallel Artificial Bee Colony Algorithm","authors":"Thaer Thaher, Badie Sartawi","doi":"10.1109/AICT50176.2020.9368747","DOIUrl":"https://doi.org/10.1109/AICT50176.2020.9368747","url":null,"abstract":"The Artificial Bee Colony (ABC) is a novel nature-inspired metaheuristic optimization algorithm that mimics the behavior of honey bees searching for food sources. The main drawback of ABC, similar to the most of metaheuristics, is the premature convergence (i.e., the earlier stuck into local optima). Recently, the structured population approach, in which the individuals are distributed into multiple sub-populations (called islands), has been widely exploited to maintain the required diversity during the search process and thus reducing the prematurity problem. In this paper, the island model, which is a common structured population approach, is incorporated with the ABC to introduce a parallel variant called (iABC). Besides, an experimental design approach is proposed to analyze the sensitivity of iABC to the parameters of the island model as well as the main specific parameters. The linear regression model and the Analysis of variance (ANOVA) are utilized to estimate the effect of parameters and identify the importance of them. Two well-known benchmark functions are used for evaluation purposes. Experimental results revealed that most parameters and their low-order interactions have a significant influence on the performance of the iABC. Furthermore, the proposed iABC proved its superiority compared to other state-of-the-art algorithms.","PeriodicalId":136491,"journal":{"name":"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114779960","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 : 2020-10-07DOI: 10.1109/AICT50176.2020.9368828
K. Izrailov, A. Chechulin, L. Vitkova
The concept of a Smart City is the forefront in the development of our near future. One of the most important parts of such cities is the transport infrastructure. Threats implementation for such infrastructure can have critical consequences for a city. To prevent such threats in the future we should investigate and counteraction them in the present. The first step in this way can be the creation of a threats classification for the transport infrastructure of a Smart City. The paper describes a set of methods that can be used for this. As a result, a scheme for categorical and cluster classifications creation is proposed. The categorical classification relies on the division of categories for elements grouping. The cluster one uses machine learning methods for elements grouping. Examples of classifications applying for the top-10 threats from the official state database are given.
{"title":"Threats Classification Method for the Transport Infrastructure of a Smart City","authors":"K. Izrailov, A. Chechulin, L. Vitkova","doi":"10.1109/AICT50176.2020.9368828","DOIUrl":"https://doi.org/10.1109/AICT50176.2020.9368828","url":null,"abstract":"The concept of a Smart City is the forefront in the development of our near future. One of the most important parts of such cities is the transport infrastructure. Threats implementation for such infrastructure can have critical consequences for a city. To prevent such threats in the future we should investigate and counteraction them in the present. The first step in this way can be the creation of a threats classification for the transport infrastructure of a Smart City. The paper describes a set of methods that can be used for this. As a result, a scheme for categorical and cluster classifications creation is proposed. The categorical classification relies on the division of categories for elements grouping. The cluster one uses machine learning methods for elements grouping. Examples of classifications applying for the top-10 threats from the official state database are given.","PeriodicalId":136491,"journal":{"name":"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125544749","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}
This paper proposes an approach to the classification of network anomalies and provides a description of the relationship of anomalies classified due to the occurrence and nature of changes in network traffic. A scheme for detecting network anomalies and abuses based on network traffic indicators also models for identifying and detecting network anomalies are presented.
{"title":"Improvement the schemes and models of detecting network traffic anomalies on computer systems","authors":"Yusupov Sabirjan Yusupdjanovich, Gulomov Sherzod Rajaboevich","doi":"10.1109/AICT50176.2020.9368781","DOIUrl":"https://doi.org/10.1109/AICT50176.2020.9368781","url":null,"abstract":"This paper proposes an approach to the classification of network anomalies and provides a description of the relationship of anomalies classified due to the occurrence and nature of changes in network traffic. A scheme for detecting network anomalies and abuses based on network traffic indicators also models for identifying and detecting network anomalies are presented.","PeriodicalId":136491,"journal":{"name":"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129842216","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 : 2020-10-07DOI: 10.1109/AICT50176.2020.9368689
K. Nisar, A. Mu'azu, Ibrahim A. Lawal, Sohrab Khan, Shuaib K. Memon
It has proven that to provide priority to different traffic types in wireless vehicular networking (VANET) is attracting wide attention for guaranteeing high quality real-time traffic routing. Choosing a reliable and stable route with Quality of Service (QoS) constraints is always a challenging task because of the high mobility in VANET. This paper proposes an approach that prioritizes the transmission of traffic data packet according to the transmission distance and urgency metrics of messages before making a selection of routes. The approach utilizes a priority classifying a mechanism to differentiate traffic information into various priorities imposed in the VANET communications. The performance of the proposed approach was simulated extensively using NCTUns simulator in terms of throughput, packet loss and delay. The results obtained show efficient solutions on the impact of mobility for the prioritized flows in enhancing safety messaging. This approach makes safety messages to be transmitted with high reliability and low delay as compared to non-prioritized traffic flows.
{"title":"Reliable Priority Based QoS Real-Time Traffic Routing in VANET: Open Issues & Parameter","authors":"K. Nisar, A. Mu'azu, Ibrahim A. Lawal, Sohrab Khan, Shuaib K. Memon","doi":"10.1109/AICT50176.2020.9368689","DOIUrl":"https://doi.org/10.1109/AICT50176.2020.9368689","url":null,"abstract":"It has proven that to provide priority to different traffic types in wireless vehicular networking (VANET) is attracting wide attention for guaranteeing high quality real-time traffic routing. Choosing a reliable and stable route with Quality of Service (QoS) constraints is always a challenging task because of the high mobility in VANET. This paper proposes an approach that prioritizes the transmission of traffic data packet according to the transmission distance and urgency metrics of messages before making a selection of routes. The approach utilizes a priority classifying a mechanism to differentiate traffic information into various priorities imposed in the VANET communications. The performance of the proposed approach was simulated extensively using NCTUns simulator in terms of throughput, packet loss and delay. The results obtained show efficient solutions on the impact of mobility for the prioritized flows in enhancing safety messaging. This approach makes safety messages to be transmitted with high reliability and low delay as compared to non-prioritized traffic flows.","PeriodicalId":136491,"journal":{"name":"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131480055","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 : 2020-10-07DOI: 10.1109/AICT50176.2020.9368576
M. Farkhadov, Aleksander Eliseev, N. Petukhova
Artificial intelligence-based medical systems can by now diagnose various disorders highly accurately. However, we should stress that despite encouraging and ever improving results, people still distrust such systems. We review relevant publications over the past five years, to identify the main causes of such mistrust and ways to overcome it. Our study showes that the main reasons to distrust these systems are opaque models, blackbox algorithms, and potentially unrepresentful training samples. We demonstrate that explainable artificial intelligence, aimed to create more user-friendly and understandable systems, has become a noticeable new topic in theoretical research and practical development. Another notable trend is to develop approaches to build hybrid systems, where artificial and human intelligence interact according to the teamwork model.
{"title":"Explained Artificial Intelligence Helps to Integrate Artificial and Human Intelligence Into Medical Diagnostic Systems: Analytical Review of Publications","authors":"M. Farkhadov, Aleksander Eliseev, N. Petukhova","doi":"10.1109/AICT50176.2020.9368576","DOIUrl":"https://doi.org/10.1109/AICT50176.2020.9368576","url":null,"abstract":"Artificial intelligence-based medical systems can by now diagnose various disorders highly accurately. However, we should stress that despite encouraging and ever improving results, people still distrust such systems. We review relevant publications over the past five years, to identify the main causes of such mistrust and ways to overcome it. Our study showes that the main reasons to distrust these systems are opaque models, blackbox algorithms, and potentially unrepresentful training samples. We demonstrate that explainable artificial intelligence, aimed to create more user-friendly and understandable systems, has become a noticeable new topic in theoretical research and practical development. Another notable trend is to develop approaches to build hybrid systems, where artificial and human intelligence interact according to the teamwork model.","PeriodicalId":136491,"journal":{"name":"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133692436","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 : 2020-10-07DOI: 10.1109/AICT50176.2020.9368580
Fahiba Farhin, M. S. Kaiser, M. Mahmud
The Internet of Healthcare Things (IoHT) is an emerging intelligent pervasive framework that interconnects smart healthcare devices, stakeholders (e.g., doctors, patients, researchers, healthcare professionals, etc.), and infrastructure using smart sensors. Emergence of novel tools and techniques for data sensing and analysis during the last decade have allowed many researchers to develop and deliver services tailored for the IoHT. This resulted in a considerable number of research outcomes addressing the applications, challenges, and probable solutions targeting secured communication within the IoHT framework. Despite considerable efforts dedicated to it, secured service provisioning still remains as a major challenge. This work provides a detailed account on the current challenges and solutions towards providing secured service provisioning focusing on the IoHT attacks and countermeasures with an aim to facilitate more investigation in this area.
{"title":"Towards Secured Service Provisioning for the Internet of Healthcare Things","authors":"Fahiba Farhin, M. S. Kaiser, M. Mahmud","doi":"10.1109/AICT50176.2020.9368580","DOIUrl":"https://doi.org/10.1109/AICT50176.2020.9368580","url":null,"abstract":"The Internet of Healthcare Things (IoHT) is an emerging intelligent pervasive framework that interconnects smart healthcare devices, stakeholders (e.g., doctors, patients, researchers, healthcare professionals, etc.), and infrastructure using smart sensors. Emergence of novel tools and techniques for data sensing and analysis during the last decade have allowed many researchers to develop and deliver services tailored for the IoHT. This resulted in a considerable number of research outcomes addressing the applications, challenges, and probable solutions targeting secured communication within the IoHT framework. Despite considerable efforts dedicated to it, secured service provisioning still remains as a major challenge. This work provides a detailed account on the current challenges and solutions towards providing secured service provisioning focusing on the IoHT attacks and countermeasures with an aim to facilitate more investigation in this area.","PeriodicalId":136491,"journal":{"name":"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117314004","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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