Over the last few years, many works have been done in earthquake prediction using different techniques and precursors in order to warn of earthquake damages and save human lives. Plenty of works have failed to sufficiently predict earthquakes, because of the complexity and the unpredictable nature of this task. Therefore, in this work we use the powerful deep learning technique. A useful algorithm that captures complex relationships in time series data. The technique is called long short-term memory (LSTM). The work employs this method in two cases of study; the first learns all the datasets in one model, the second case learns the correlations on two divided groups considering their range of magnitude. The results show that learning decomposed datasets gives more well-functioning predictions since it exploits the nature of each type of seismic events.
{"title":"LSTM-based Models for Earthquake Prediction","authors":"Asmae Berhich, Fatima-Zahra Belouadha, M. Kabbaj","doi":"10.1145/3386723.3387865","DOIUrl":"https://doi.org/10.1145/3386723.3387865","url":null,"abstract":"Over the last few years, many works have been done in earthquake prediction using different techniques and precursors in order to warn of earthquake damages and save human lives. Plenty of works have failed to sufficiently predict earthquakes, because of the complexity and the unpredictable nature of this task. Therefore, in this work we use the powerful deep learning technique. A useful algorithm that captures complex relationships in time series data. The technique is called long short-term memory (LSTM). The work employs this method in two cases of study; the first learns all the datasets in one model, the second case learns the correlations on two divided groups considering their range of magnitude. The results show that learning decomposed datasets gives more well-functioning predictions since it exploits the nature of each type of seismic events.","PeriodicalId":139072,"journal":{"name":"Proceedings of the 3rd International Conference on Networking, Information Systems & Security","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132780400","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}
Logistics Information Technology (LIC) is a key enabler of effective supply chain management activities. In 2015, $300 billion was spent on LIC by businesses worldwide, an increase of 1.8% and 3.8% over 2016 and 2017, respectively. With such large investments, companies run the risk of deteriorating financial performance if the (LIC) does not work as expected. In fact, there is a mix of evidence, some companies benefiting from the (LIC) while others do not benefit from the investment in the LIC. Despite substantial research on the use of information technology in a Supply Chain Management context, the impact of the LIC on business performance is unclear. In particular, the existing literature has reported conflicting results regarding the relationship between the LIC and the company's performance. Therefore, the purpose of our article is to investigate the roles of information technologies in SCM and to highlight this extremely important area of research. We find that the LIC is not universally associated with improving the performance of the company. In particular, LIC has several characteristics, and each characteristic is related to different performance indicators.
{"title":"Role of Information Technologies in Supply Chain Management","authors":"Heddoun Asmae, Benrrezzouq Rhizlane","doi":"10.1145/3386723.3387827","DOIUrl":"https://doi.org/10.1145/3386723.3387827","url":null,"abstract":"Logistics Information Technology (LIC) is a key enabler of effective supply chain management activities. In 2015, $300 billion was spent on LIC by businesses worldwide, an increase of 1.8% and 3.8% over 2016 and 2017, respectively. With such large investments, companies run the risk of deteriorating financial performance if the (LIC) does not work as expected. In fact, there is a mix of evidence, some companies benefiting from the (LIC) while others do not benefit from the investment in the LIC. Despite substantial research on the use of information technology in a Supply Chain Management context, the impact of the LIC on business performance is unclear. In particular, the existing literature has reported conflicting results regarding the relationship between the LIC and the company's performance. Therefore, the purpose of our article is to investigate the roles of information technologies in SCM and to highlight this extremely important area of research. We find that the LIC is not universally associated with improving the performance of the company. In particular, LIC has several characteristics, and each characteristic is related to different performance indicators.","PeriodicalId":139072,"journal":{"name":"Proceedings of the 3rd International Conference on Networking, Information Systems & Security","volume":"280 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132844536","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}
A. Nabou, M. Laanaoui, M. Ouzzif, Mohammed-Alamine El Houssaini
Mobile Ad hoc Network (MANET) considers as simple network that use the wireless communication between difference wireless devices named as nodes. MANET has many challenges in its functions due to absence of fixed infrastructure and autoconfiguration. Optimized Link State Routing Protocol (OLSR) is proactive MANET routing protocol dedicated to the large network density. However it can be affected by the congestion that decrease its performance by losing packets, taking more delay to receive packets and also minimize the throughput of the protocol. In this paper, we propose new method reckons on Normality Test that applied in statistic domain to detect the congestion in OLSR protocol without any modification in the algorithm and without any other additional control messages. To detect the congestion in OLSR we use Shapiro_Wilk (W) method to analyze the results of Throughput following two scenarios that leads to the congestion.
移动自组织网络(MANET)是一种简单的网络，在不同的无线设备之间进行无线通信，这些设备被称为节点。由于缺乏固定的基础设施和自动配置，MANET在功能上面临许多挑战。OLSR (Optimized Link State Routing Protocol)是面向大网络密度的主动MANET路由协议。然而，它可能会受到拥塞的影响，它的性能会因为丢失数据包而降低，接收数据包的延迟更长，并且还会使协议的吞吐量最小化。本文提出了一种应用于统计域的基于正态性检验的方法来检测OLSR协议中的拥塞，而不需要对算法进行任何修改，也不需要增加任何控制消息。为了检测OLSR中的拥塞，我们使用Shapiro_Wilk (W)方法来分析导致拥塞的两种情况下的吞吐量结果。
{"title":"Normality Test to Detect the Congestion in MANET by Using OLSR Protocol","authors":"A. Nabou, M. Laanaoui, M. Ouzzif, Mohammed-Alamine El Houssaini","doi":"10.1145/3386723.3387836","DOIUrl":"https://doi.org/10.1145/3386723.3387836","url":null,"abstract":"Mobile Ad hoc Network (MANET) considers as simple network that use the wireless communication between difference wireless devices named as nodes. MANET has many challenges in its functions due to absence of fixed infrastructure and autoconfiguration. Optimized Link State Routing Protocol (OLSR) is proactive MANET routing protocol dedicated to the large network density. However it can be affected by the congestion that decrease its performance by losing packets, taking more delay to receive packets and also minimize the throughput of the protocol. In this paper, we propose new method reckons on Normality Test that applied in statistic domain to detect the congestion in OLSR protocol without any modification in the algorithm and without any other additional control messages. To detect the congestion in OLSR we use Shapiro_Wilk (W) method to analyze the results of Throughput following two scenarios that leads to the congestion.","PeriodicalId":139072,"journal":{"name":"Proceedings of the 3rd International Conference on Networking, Information Systems & Security","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128610861","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}
Interactivity in language processing plays a pivotal role to allow models to better understand how to build the appropriate output. In the task of Natural Language to SQL, the fact of including the users' interactivity can be one of the practical solutions that haven't been studied deeply in the existing works published in the last decade. Using databases by users with limited familiarity in SQL will create an additional obstacle for these users to better exploit the content stored in the database systems. In this paper we present the already published studies and we discuss the utility of using the interactivity to definitely improve the query generation process in order to construct a model that generalize for unseen and complex sentences and to automatically generate the appropriate outputs.
{"title":"Inferring SQL Queries Using Interactivity","authors":"K. Ahkouk, M. Machkour, J. Antari","doi":"10.1145/3386723.3387820","DOIUrl":"https://doi.org/10.1145/3386723.3387820","url":null,"abstract":"Interactivity in language processing plays a pivotal role to allow models to better understand how to build the appropriate output. In the task of Natural Language to SQL, the fact of including the users' interactivity can be one of the practical solutions that haven't been studied deeply in the existing works published in the last decade. Using databases by users with limited familiarity in SQL will create an additional obstacle for these users to better exploit the content stored in the database systems. In this paper we present the already published studies and we discuss the utility of using the interactivity to definitely improve the query generation process in order to construct a model that generalize for unseen and complex sentences and to automatically generate the appropriate outputs.","PeriodicalId":139072,"journal":{"name":"Proceedings of the 3rd International Conference on Networking, Information Systems & Security","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126572500","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}
Road accidents are one of the primary concerns and critical issues that encounters societies nowadays: Crash events analysis is a key role in improving traffic safety and reducing potential inconveniences to road users. As such, novice drivers continue to be overrepresented in fatalities and injuries arising from crashes, especially in those that occur during nigh times under rainy weather conditions. In this study, we aim to investigate road crash events for novice drivers under reduced-visibility scenarios during multiple night-time driving simulations that have been conducted using a desktop driving simulator. This paper depicted the effect of both light rain and heavy rain on traffic safety by endorsing real-time driver inputs established as throttle pedal position, brake pedal position and wheel angle. To the authors' knowledge, minimal work has been directed to the examination of light and heavy rain on novice drivers crash events based on driver inputs during night times. Artificial Neural Networks (ANN) and Decision Trees (DT) machine learning models have been developed to analyze crash events; results depict that ANN model exhibited the best performances in terms of accuracy and AUC measures during all-weather covariates. Conventionally, and based on the findings, new insights into night-related crash events' assessments for novice drivers could be harnessed to assist enforcement endeavors to design crash avoidance/warning systems under reduced-visibility settings.
{"title":"Towards analyzing crash events for novice drivers under reduced-visibility settings: A simulator study","authors":"Z. E. A. Elassad, H. Mousannif, H. A. Moatassime","doi":"10.1145/3386723.3387849","DOIUrl":"https://doi.org/10.1145/3386723.3387849","url":null,"abstract":"Road accidents are one of the primary concerns and critical issues that encounters societies nowadays: Crash events analysis is a key role in improving traffic safety and reducing potential inconveniences to road users. As such, novice drivers continue to be overrepresented in fatalities and injuries arising from crashes, especially in those that occur during nigh times under rainy weather conditions. In this study, we aim to investigate road crash events for novice drivers under reduced-visibility scenarios during multiple night-time driving simulations that have been conducted using a desktop driving simulator. This paper depicted the effect of both light rain and heavy rain on traffic safety by endorsing real-time driver inputs established as throttle pedal position, brake pedal position and wheel angle. To the authors' knowledge, minimal work has been directed to the examination of light and heavy rain on novice drivers crash events based on driver inputs during night times. Artificial Neural Networks (ANN) and Decision Trees (DT) machine learning models have been developed to analyze crash events; results depict that ANN model exhibited the best performances in terms of accuracy and AUC measures during all-weather covariates. Conventionally, and based on the findings, new insights into night-related crash events' assessments for novice drivers could be harnessed to assist enforcement endeavors to design crash avoidance/warning systems under reduced-visibility settings.","PeriodicalId":139072,"journal":{"name":"Proceedings of the 3rd International Conference on Networking, Information Systems & Security","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122523654","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}
Mohamed Chouai, M. Merah, J. Sancho-Gómez, M. Mimi
Billions of suitcases and other belongings are checked every year in the X-ray systems of airports around the world. This process is of great importance because it involves the detection of possible dangerous objects such as weapons or explosives. However, the work done by airport surveillance personnel is not free from errors usually due to tiredness or distractions. This is a security problem that can always be reduced with the help of automatic intelligent tools. This paper proposes a machine learning (ML) application for image segmentation. First, it is used a color-based pixel segmentation of images to separate organic, inorganic, mixed and opaque objects from the background. Second, those five types of images are reduced in the so-called fusion phase and classified into only two: organic and inorganic. A comparative study of several ML algorithms with heuristics over a large data set of X-ray images is presented for the classification of organic and inorganic objects for a future dangerous object detection work.
{"title":"A machine learning color-based segmentation for object detection within dual X-ray baggage images","authors":"Mohamed Chouai, M. Merah, J. Sancho-Gómez, M. Mimi","doi":"10.1145/3386723.3387869","DOIUrl":"https://doi.org/10.1145/3386723.3387869","url":null,"abstract":"Billions of suitcases and other belongings are checked every year in the X-ray systems of airports around the world. This process is of great importance because it involves the detection of possible dangerous objects such as weapons or explosives. However, the work done by airport surveillance personnel is not free from errors usually due to tiredness or distractions. This is a security problem that can always be reduced with the help of automatic intelligent tools. This paper proposes a machine learning (ML) application for image segmentation. First, it is used a color-based pixel segmentation of images to separate organic, inorganic, mixed and opaque objects from the background. Second, those five types of images are reduced in the so-called fusion phase and classified into only two: organic and inorganic. A comparative study of several ML algorithms with heuristics over a large data set of X-ray images is presented for the classification of organic and inorganic objects for a future dangerous object detection work.","PeriodicalId":139072,"journal":{"name":"Proceedings of the 3rd International Conference on Networking, Information Systems & Security","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130498241","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}
Isma Boudouane, Amina Makhlouf, M. Harkat, N. Saadia, A. Ramdane-Cherif
Falls are one the major problems that threatens the health of the elderly. For this reason, many devices have been developed by researchers all around the globe to continuously monitor and detect critical events, like falls, which allow for a fast-medical intervention to take place. The proposed method for the detection of fall is based on the original version of the Histogram of Oriented Gradient (HOG) combined with Optical Flow and immobilization time to reduce the numbers of false detections. The method was implemented in a system composed of a portable camera and an embedded multi-core computer (Raspberry Pi) to parallelize computations which allows for real time detection. The results of 45 tests conducted on 09 subjects show that falls from standing position can be detected with 80% of sensitivity. The inclusion of immobilization time in the detection process improves the specificity for rotations by 14%.
{"title":"Post-Fall Time Accounting for Fall Detection Using a Portable Camera","authors":"Isma Boudouane, Amina Makhlouf, M. Harkat, N. Saadia, A. Ramdane-Cherif","doi":"10.1145/3386723.3387822","DOIUrl":"https://doi.org/10.1145/3386723.3387822","url":null,"abstract":"Falls are one the major problems that threatens the health of the elderly. For this reason, many devices have been developed by researchers all around the globe to continuously monitor and detect critical events, like falls, which allow for a fast-medical intervention to take place. The proposed method for the detection of fall is based on the original version of the Histogram of Oriented Gradient (HOG) combined with Optical Flow and immobilization time to reduce the numbers of false detections. The method was implemented in a system composed of a portable camera and an embedded multi-core computer (Raspberry Pi) to parallelize computations which allows for real time detection. The results of 45 tests conducted on 09 subjects show that falls from standing position can be detected with 80% of sensitivity. The inclusion of immobilization time in the detection process improves the specificity for rotations by 14%.","PeriodicalId":139072,"journal":{"name":"Proceedings of the 3rd International Conference on Networking, Information Systems & Security","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124681766","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 focuses on presenting a conceptual model in order to integrate sustainability in cloud computing resulting in facilitating transmission of knowledge in education with a focus on developing countries. From one perspective and while cloud computing has been considered as a recent area of research due to arguments round its value to organizational performance, sustainability has turned to be a typical common norm due to the discovery of uncertainty in various human aspects. From a different perspective, the role of Knowledge Management in enhancing organisational success has been detected in different researches. The main consensus after these researches is that the more effective management of knowledge is the more effective the organizational performance will be. Therefore, this paper presents a theoretical framework of potential links among cloud computing, knowledge management and sustainability.
{"title":"Modelling Sustainability, Cloud computing and knowledge transmission in education in developing countries","authors":"A. Mehrez, L. Aladel","doi":"10.1145/3386723.3387889","DOIUrl":"https://doi.org/10.1145/3386723.3387889","url":null,"abstract":"This paper focuses on presenting a conceptual model in order to integrate sustainability in cloud computing resulting in facilitating transmission of knowledge in education with a focus on developing countries. From one perspective and while cloud computing has been considered as a recent area of research due to arguments round its value to organizational performance, sustainability has turned to be a typical common norm due to the discovery of uncertainty in various human aspects. From a different perspective, the role of Knowledge Management in enhancing organisational success has been detected in different researches. The main consensus after these researches is that the more effective management of knowledge is the more effective the organizational performance will be. Therefore, this paper presents a theoretical framework of potential links among cloud computing, knowledge management and sustainability.","PeriodicalId":139072,"journal":{"name":"Proceedings of the 3rd International Conference on Networking, Information Systems & Security","volume":"145 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132177705","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}
G. M. Kossingou, Nadege Gladys Ndassimba, Edgard Ndassimba, Kéba Gueye, S. Ouya
The repeated political-military crises from 1996 to the present have disrupted the education system in CAR. The quantitative and qualitative level of primary and secondary schools in CAR is currently very low compared to the periods before the crisis. Several school facilities in rural areas have been destroyed and qualified basic 1 and 2 teachers are abandoning rural areas at risk occupied by rebels. For more than 15 years now, many primary and secondary school children in high-risk areas have not had access to school. As a direct result, the illiteracy rate and child soldiers in the rebellion are rising. This article proposes the use of the Moodle platform that is an open source platform, with many activity modules. These activities allow interaction between teachers and learners at a distance. The implementation of this e-learning platform is a solution for children and young people who have not been to school for a short or long time.It allows: • Catch-up training in primary school for children who have been out of school for a period of less than or equal to 5 years; • Catch-up courses at secondary school for young people who have been out of school for 5 years or less; • Training in agriculture, animal husbandry and fishing will be offered to young people who can no longer resume their studies; • This solution makes it possible to reduce the illiteracy rate among young people and to improve living conditions in the rural areas of countries in conflict.
{"title":"Proposal of the Solution of Virtual Basic Schools in Rural Areas of African Countries in Conflict: Case of the Central African Republic","authors":"G. M. Kossingou, Nadege Gladys Ndassimba, Edgard Ndassimba, Kéba Gueye, S. Ouya","doi":"10.1145/3386723.3387900","DOIUrl":"https://doi.org/10.1145/3386723.3387900","url":null,"abstract":"The repeated political-military crises from 1996 to the present have disrupted the education system in CAR. The quantitative and qualitative level of primary and secondary schools in CAR is currently very low compared to the periods before the crisis. Several school facilities in rural areas have been destroyed and qualified basic 1 and 2 teachers are abandoning rural areas at risk occupied by rebels. For more than 15 years now, many primary and secondary school children in high-risk areas have not had access to school. As a direct result, the illiteracy rate and child soldiers in the rebellion are rising. This article proposes the use of the Moodle platform that is an open source platform, with many activity modules. These activities allow interaction between teachers and learners at a distance. The implementation of this e-learning platform is a solution for children and young people who have not been to school for a short or long time.It allows: • Catch-up training in primary school for children who have been out of school for a period of less than or equal to 5 years; • Catch-up courses at secondary school for young people who have been out of school for 5 years or less; • Training in agriculture, animal husbandry and fishing will be offered to young people who can no longer resume their studies; • This solution makes it possible to reduce the illiteracy rate among young people and to improve living conditions in the rural areas of countries in conflict.","PeriodicalId":139072,"journal":{"name":"Proceedings of the 3rd International Conference on Networking, Information Systems & Security","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132134651","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}
D. Bystrov, Olimjon Toirov, Mustafakulova Gulzoda, Yakubova Dilfuza
A natural language (NL) is any of the languages naturally used by humans, i.e. not an artificial such as programming languages. Natural language generation systems convert information from computer databases into normal-sounding human language and natural language understanding systems convert samples of human language into more formal representations that are easier for computer programs to manipulate. Natural language is basically a system for describing perceptions. In this paper we discuss use of fuzzy logic in natural language processing and computation, the general process of NLP as well as some common techniques used, computational linguistic, linguistic approximation.
{"title":"Fuzzy Systems for Computational Linguistics and Natural Language","authors":"D. Bystrov, Olimjon Toirov, Mustafakulova Gulzoda, Yakubova Dilfuza","doi":"10.1145/3386723.3387873","DOIUrl":"https://doi.org/10.1145/3386723.3387873","url":null,"abstract":"A natural language (NL) is any of the languages naturally used by humans, i.e. not an artificial such as programming languages. Natural language generation systems convert information from computer databases into normal-sounding human language and natural language understanding systems convert samples of human language into more formal representations that are easier for computer programs to manipulate. Natural language is basically a system for describing perceptions. In this paper we discuss use of fuzzy logic in natural language processing and computation, the general process of NLP as well as some common techniques used, computational linguistic, linguistic approximation.","PeriodicalId":139072,"journal":{"name":"Proceedings of the 3rd International Conference on Networking, Information Systems & Security","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128686154","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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