Pub Date : 2020-03-01DOI: 10.1109/ICICT50521.2020.00058
Gilang Maulana Majid, Anjan Pal
This study explores online users' comments in response to rumor corrections. Specifically, it considers a video rumor correction that was posted on YouTube and debunked a rumor in the wake of Indonesia's post-election protests and riots. Content analysis was employed on 500 comments that were posted in response to the rumor-corrections. This study finds that the volume of anti-correction comments (53.60%) was approximately five times greater than the volume of the pro-correction comments (10.80%). In-depth analysis of anti-correction comments revealed different voices, including rejection of evidence, distrust in authorities, critical inspection of evidence, and lack of sufficient evidence. Essentially, this study shows that rumor corrections must be followed-up in order to gain public trust.
{"title":"Conspiracy and Rumor Correction: Analysis of Social Media Users' Comments","authors":"Gilang Maulana Majid, Anjan Pal","doi":"10.1109/ICICT50521.2020.00058","DOIUrl":"https://doi.org/10.1109/ICICT50521.2020.00058","url":null,"abstract":"This study explores online users' comments in response to rumor corrections. Specifically, it considers a video rumor correction that was posted on YouTube and debunked a rumor in the wake of Indonesia's post-election protests and riots. Content analysis was employed on 500 comments that were posted in response to the rumor-corrections. This study finds that the volume of anti-correction comments (53.60%) was approximately five times greater than the volume of the pro-correction comments (10.80%). In-depth analysis of anti-correction comments revealed different voices, including rejection of evidence, distrust in authorities, critical inspection of evidence, and lack of sufficient evidence. Essentially, this study shows that rumor corrections must be followed-up in order to gain public trust.","PeriodicalId":445000,"journal":{"name":"2020 3rd International Conference on Information and Computer Technologies (ICICT)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115160173","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 : 2020-03-01DOI: 10.1109/ICICT50521.2020.00059
Robison Cris Brito, Carlos Vinícius Ferrareze, F. Favarim, J. T. Oliva, E. Todt
The broiler production in Brazil has been worldwide prominence, and it is fundamental for the development of the Brazilian economy. Chickens are intensively raised and confined into aviaries, in which all broilers are the same age and genetic origin. Most poultry farmers reuse the poultry manure for several consecutive batches in order to reduce costs. However, this practice can increase humidity and ammonia production. The excess of ammonia gas causes stress and diseases in broilers. Consequently, broiler production can be reduced and cause losses to poultry farmers. For this reason, the continuous monitoring of ammonia gas concentration in aviaries is necessary. Therefore, the cost of commercially available devices for the accomplishment of this task is considered high. In this work, a low-cost prototype for the monitoring of Ammonia gas in aviaries was developed. To do so, the NodeMCU module was used to measure, through sensors, the Ammonia gas concentration and send real-time information to an Android mobile application, which is available to poultry farmer. The data processed by the NodeMCU is sent to a Spring Boot server and stored into a cloud database. Also, the user can receive notifications when the Ammonia level is higher than a tolerated limit. As a result, the cost for the prototype development was approximately U$$ 30.00, considering only hardware components. In this, our prototype can be popularized among poultry farmers for a more affordable price concerning other commercially available devices.
{"title":"A Novel System for Ammonia Gas Control in Broiler Production Environment","authors":"Robison Cris Brito, Carlos Vinícius Ferrareze, F. Favarim, J. T. Oliva, E. Todt","doi":"10.1109/ICICT50521.2020.00059","DOIUrl":"https://doi.org/10.1109/ICICT50521.2020.00059","url":null,"abstract":"The broiler production in Brazil has been worldwide prominence, and it is fundamental for the development of the Brazilian economy. Chickens are intensively raised and confined into aviaries, in which all broilers are the same age and genetic origin. Most poultry farmers reuse the poultry manure for several consecutive batches in order to reduce costs. However, this practice can increase humidity and ammonia production. The excess of ammonia gas causes stress and diseases in broilers. Consequently, broiler production can be reduced and cause losses to poultry farmers. For this reason, the continuous monitoring of ammonia gas concentration in aviaries is necessary. Therefore, the cost of commercially available devices for the accomplishment of this task is considered high. In this work, a low-cost prototype for the monitoring of Ammonia gas in aviaries was developed. To do so, the NodeMCU module was used to measure, through sensors, the Ammonia gas concentration and send real-time information to an Android mobile application, which is available to poultry farmer. The data processed by the NodeMCU is sent to a Spring Boot server and stored into a cloud database. Also, the user can receive notifications when the Ammonia level is higher than a tolerated limit. As a result, the cost for the prototype development was approximately U$$ 30.00, considering only hardware components. In this, our prototype can be popularized among poultry farmers for a more affordable price concerning other commercially available devices.","PeriodicalId":445000,"journal":{"name":"2020 3rd International Conference on Information and Computer Technologies (ICICT)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115170117","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 : 2020-03-01DOI: 10.1109/ICICT50521.2020.00079
A. Abdelaziz, Mahmoud Mandour, A. Elbayoumy, G. Abdel-Hamid
Prioritizing handover calls is an important process in cellular networks. The blocking/dropping calls occurred when there is no free channel is assigned for the subscriber. So, we are going to devise a new scheme for handling the calls among the network. In this paper, the main idea is to maintain an acceptable blocking/dropping trade-off probability for the indoor cells. The proposed solution will show how to change dynamically the number of reserved channels and optimizing it based on the incoming offered traffic type (new or handover calls). The Guard Channel and Non-Prioritized schemes are considered. Finally, the results reveal that call blocking and dropping probabilities performs better while compared with the other existing scheme.
{"title":"Dynamic Channel Allocation Scheme for Handover Calls in Cellular Networks","authors":"A. Abdelaziz, Mahmoud Mandour, A. Elbayoumy, G. Abdel-Hamid","doi":"10.1109/ICICT50521.2020.00079","DOIUrl":"https://doi.org/10.1109/ICICT50521.2020.00079","url":null,"abstract":"Prioritizing handover calls is an important process in cellular networks. The blocking/dropping calls occurred when there is no free channel is assigned for the subscriber. So, we are going to devise a new scheme for handling the calls among the network. In this paper, the main idea is to maintain an acceptable blocking/dropping trade-off probability for the indoor cells. The proposed solution will show how to change dynamically the number of reserved channels and optimizing it based on the incoming offered traffic type (new or handover calls). The Guard Channel and Non-Prioritized schemes are considered. Finally, the results reveal that call blocking and dropping probabilities performs better while compared with the other existing scheme.","PeriodicalId":445000,"journal":{"name":"2020 3rd International Conference on Information and Computer Technologies (ICICT)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125756954","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 : 2020-03-01DOI: 10.1109/ICICT50521.2020.00025
Rebecca Miao, Zhenyi Yang, V. Gavrishchaka
Identification of rare states and training models with limited data is fundamentally challenging for mainstream machine learning. Alternative approaches include one-shot learning using similarities to reference classes, meta-learning training on many related tasks and transfer learning using relevant pre-trained model. However, their performance quickly deteriorates with decreasing number of available reference classes and related tasks or lack of relevant problem for transfer learning. Previously, we proposed ensemble decomposition learning (EDL) where boosting-ensemble components trained on just two broad classes provide large number of implicit reference classes. Domain-expert knowledge such as complexity measures can be directly incorporated within EDL to reduce dependence on training data. However, success of EDL and similar approaches requires variety of complexity measures sufficiently flexible for further tuning given enough data which is not always available. Therefore, addition of complementary measures not requiring fine-tuning is important. Persistent homology (PH), one of computational topology tools, offers noise-tolerant topological summary of data set. Direct application of PH to high-dimensional data is often prohibitive and requires domain-specific dimensionality reduction. Here we suggest that PH computed on complexity measures rather than raw data could provide robust complementary metrics for enhancement of rare state representation as illustrated in the context of personalized medicine application using data from www.physionet.org.
{"title":"Topological Representation of Rare States Using Combination of Persistent Homology and Complexity Measures","authors":"Rebecca Miao, Zhenyi Yang, V. Gavrishchaka","doi":"10.1109/ICICT50521.2020.00025","DOIUrl":"https://doi.org/10.1109/ICICT50521.2020.00025","url":null,"abstract":"Identification of rare states and training models with limited data is fundamentally challenging for mainstream machine learning. Alternative approaches include one-shot learning using similarities to reference classes, meta-learning training on many related tasks and transfer learning using relevant pre-trained model. However, their performance quickly deteriorates with decreasing number of available reference classes and related tasks or lack of relevant problem for transfer learning. Previously, we proposed ensemble decomposition learning (EDL) where boosting-ensemble components trained on just two broad classes provide large number of implicit reference classes. Domain-expert knowledge such as complexity measures can be directly incorporated within EDL to reduce dependence on training data. However, success of EDL and similar approaches requires variety of complexity measures sufficiently flexible for further tuning given enough data which is not always available. Therefore, addition of complementary measures not requiring fine-tuning is important. Persistent homology (PH), one of computational topology tools, offers noise-tolerant topological summary of data set. Direct application of PH to high-dimensional data is often prohibitive and requires domain-specific dimensionality reduction. Here we suggest that PH computed on complexity measures rather than raw data could provide robust complementary metrics for enhancement of rare state representation as illustrated in the context of personalized medicine application using data from www.physionet.org.","PeriodicalId":445000,"journal":{"name":"2020 3rd International Conference on Information and Computer Technologies (ICICT)","volume":"2014 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128020880","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 : 2020-03-01DOI: 10.1109/icict50521.2020.00003
{"title":"[Copyright notice]","authors":"","doi":"10.1109/icict50521.2020.00003","DOIUrl":"https://doi.org/10.1109/icict50521.2020.00003","url":null,"abstract":"","PeriodicalId":445000,"journal":{"name":"2020 3rd International Conference on Information and Computer Technologies (ICICT)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126753799","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 : 2020-03-01DOI: 10.1109/ICICT50521.2020.00085
Kimo Bumanglag, H. Kettani
The Domain Name System (DNS) protocol has been in use for over thirty years. As the primary method of resolving domain names to Internet Protocol (IP) addresses, it is a fundamental component of the Internet. Despite its position of importance, the protocol lacks built-in security mechanisms to address confidentiality, integrity, or availability. Malware can use DNS to fulfill attacker objectives, such as establishing command and control (C2) or exfiltrating data. Various enhancements have been implemented in an attempt to address security after-the-fact. The latest such enhancement is DNS over HTTPS. Methods have also been developed to detect malware's use of DNS. In this paper, we review the weaknesses of the DNS protocol and how malware has abused those weaknesses, enhancements to DNS security, and how malware uses DNS and how that use is detected, with a special emphasis on the effects that DNS over HTTPS may have on an organization's security.
{"title":"On the Impact of DNS Over HTTPS Paradigm on Cyber Systems","authors":"Kimo Bumanglag, H. Kettani","doi":"10.1109/ICICT50521.2020.00085","DOIUrl":"https://doi.org/10.1109/ICICT50521.2020.00085","url":null,"abstract":"The Domain Name System (DNS) protocol has been in use for over thirty years. As the primary method of resolving domain names to Internet Protocol (IP) addresses, it is a fundamental component of the Internet. Despite its position of importance, the protocol lacks built-in security mechanisms to address confidentiality, integrity, or availability. Malware can use DNS to fulfill attacker objectives, such as establishing command and control (C2) or exfiltrating data. Various enhancements have been implemented in an attempt to address security after-the-fact. The latest such enhancement is DNS over HTTPS. Methods have also been developed to detect malware's use of DNS. In this paper, we review the weaknesses of the DNS protocol and how malware has abused those weaknesses, enhancements to DNS security, and how malware uses DNS and how that use is detected, with a special emphasis on the effects that DNS over HTTPS may have on an organization's security.","PeriodicalId":445000,"journal":{"name":"2020 3rd International Conference on Information and Computer Technologies (ICICT)","volume":"196 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130307503","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 : 2020-03-01DOI: 10.1109/ICICT50521.2020.00096
S. Girija, R. Rao
Impulse noise is a major performance degrading factor, as it impairs the communication systems, such as mobile radio system, digital subscriber line system, and power line. Various Constant Modulus algorithms (CMA) were introduced to reduce the average of constant modulus error between the constant modulus and the equalizer output power in the impulsive noise environment. However, the existing blind learning methods generate large mis-adjustment and slow convergence rate in the impulse noise of Multiple Input Multiple Output (MIMO) system. To solve the impulse noise problem, the blind equalization method named Robust Adaptive Autoregressive weighted constant modulus algorithm (RAAWCMA) is introduced in this research work for MIMO system. Due to the feasibility and simplicity of stable convergence property, the proposed Robust Adaptive Autoregressive weighted constant modulus algorithm for blind equalization is utilized to solve the complexity of impulse noise in MIMO system. The proposed blind equalization method increases the performance of equalization by adjusting the weight vector based on the samples of output error. Moreover, the maximum average value obtained by the proposed algorithm is revealed based on the evaluation metrics, like Bit Error Rate, Symbol Error Rate, and Mean Square Error which acquire the values of 0.0005, 0.0005, and 0.0001 with the Rayleigh channel, and 0.0004, 0.0004, and 0.0001 with the Rician channel using six antennas.
{"title":"Robust Adaptive AutoRegressive Weighted Constant Modulus Algorithm for Blind Equalization in MIMO-OFDM System","authors":"S. Girija, R. Rao","doi":"10.1109/ICICT50521.2020.00096","DOIUrl":"https://doi.org/10.1109/ICICT50521.2020.00096","url":null,"abstract":"Impulse noise is a major performance degrading factor, as it impairs the communication systems, such as mobile radio system, digital subscriber line system, and power line. Various Constant Modulus algorithms (CMA) were introduced to reduce the average of constant modulus error between the constant modulus and the equalizer output power in the impulsive noise environment. However, the existing blind learning methods generate large mis-adjustment and slow convergence rate in the impulse noise of Multiple Input Multiple Output (MIMO) system. To solve the impulse noise problem, the blind equalization method named Robust Adaptive Autoregressive weighted constant modulus algorithm (RAAWCMA) is introduced in this research work for MIMO system. Due to the feasibility and simplicity of stable convergence property, the proposed Robust Adaptive Autoregressive weighted constant modulus algorithm for blind equalization is utilized to solve the complexity of impulse noise in MIMO system. The proposed blind equalization method increases the performance of equalization by adjusting the weight vector based on the samples of output error. Moreover, the maximum average value obtained by the proposed algorithm is revealed based on the evaluation metrics, like Bit Error Rate, Symbol Error Rate, and Mean Square Error which acquire the values of 0.0005, 0.0005, and 0.0001 with the Rayleigh channel, and 0.0004, 0.0004, and 0.0001 with the Rician channel using six antennas.","PeriodicalId":445000,"journal":{"name":"2020 3rd International Conference on Information and Computer Technologies (ICICT)","volume":"149 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131633537","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 : 2020-03-01DOI: 10.1109/ICICT50521.2020.00089
Chandrasekar Vuppalapati, Anitha Ilapakurti, Sharat Kedari, Rajasekar Vuppalapati, J. Vuppalapati, S. Kedari
Big Data surrounds us. Every minute, our smartphone collects huge amount of data from geolocations to next clickable item on the ecommerce site. Data has become one of the most important commodities for the individuals and companies. Nevertheless, this data revolution has not touched every economic sector, especially rural economies, e.g., small farmers have largely passed over the data revolution, in the developing countries due to infrastructure and compute constrained environments. Not only this is a huge missed opportunity for the big data companies, it is one of the significant obstacle in the path towards sustainable food and a huge inhibitor closing economic disparities. The purpose of the paper is to develop a framework to deploy artificial intelligence models in constrained compute environments that enable remote rural areas and small farmers to join the data revolution and start contribution to the digital economy and empowers the world through the data to create a sustainable food for our collective future.
{"title":"Democratization of AI, Albeit Constrained IoT Devices & Tiny ML, for Creating a Sustainable Food Future","authors":"Chandrasekar Vuppalapati, Anitha Ilapakurti, Sharat Kedari, Rajasekar Vuppalapati, J. Vuppalapati, S. Kedari","doi":"10.1109/ICICT50521.2020.00089","DOIUrl":"https://doi.org/10.1109/ICICT50521.2020.00089","url":null,"abstract":"Big Data surrounds us. Every minute, our smartphone collects huge amount of data from geolocations to next clickable item on the ecommerce site. Data has become one of the most important commodities for the individuals and companies. Nevertheless, this data revolution has not touched every economic sector, especially rural economies, e.g., small farmers have largely passed over the data revolution, in the developing countries due to infrastructure and compute constrained environments. Not only this is a huge missed opportunity for the big data companies, it is one of the significant obstacle in the path towards sustainable food and a huge inhibitor closing economic disparities. The purpose of the paper is to develop a framework to deploy artificial intelligence models in constrained compute environments that enable remote rural areas and small farmers to join the data revolution and start contribution to the digital economy and empowers the world through the data to create a sustainable food for our collective future.","PeriodicalId":445000,"journal":{"name":"2020 3rd International Conference on Information and Computer Technologies (ICICT)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128286426","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 : 2020-03-01DOI: 10.1109/ICICT50521.2020.00076
Kevin Matthe Caramancion
Disinformation or "fake news" has continuously proven to be a pervasive threat in the digital space. The spread and persistence of disinformation especially in the social networking media sites currently factors as one of the most challenging threat for users and content administrators alike. Its ecosystem encompasses several attributing factors including but not limited to humans as information users and source, social communication model as its channel, current trust models in place as defense and guards against it, and finally the archival correction that may halt its persistence in the social space. In this paper, the author aims to explore the dynamics of the several interacting fields i.e. Psychology and Computer Science, their influence on its phenomenon, which provides an ideal interdisciplinary and holistic approach to its reduction and management. Another equally important section in this paper is its attempt to advocate to formally recognize disinformation as a cybersecurity threat for its prospective future categorization. The possible application of discourse analysis as a potential technological tool for its detection as solution is also discussed.
{"title":"An Exploration of Disinformation as a Cybersecurity Threat","authors":"Kevin Matthe Caramancion","doi":"10.1109/ICICT50521.2020.00076","DOIUrl":"https://doi.org/10.1109/ICICT50521.2020.00076","url":null,"abstract":"Disinformation or \"fake news\" has continuously proven to be a pervasive threat in the digital space. The spread and persistence of disinformation especially in the social networking media sites currently factors as one of the most challenging threat for users and content administrators alike. Its ecosystem encompasses several attributing factors including but not limited to humans as information users and source, social communication model as its channel, current trust models in place as defense and guards against it, and finally the archival correction that may halt its persistence in the social space. In this paper, the author aims to explore the dynamics of the several interacting fields i.e. Psychology and Computer Science, their influence on its phenomenon, which provides an ideal interdisciplinary and holistic approach to its reduction and management. Another equally important section in this paper is its attempt to advocate to formally recognize disinformation as a cybersecurity threat for its prospective future categorization. The possible application of discourse analysis as a potential technological tool for its detection as solution is also discussed.","PeriodicalId":445000,"journal":{"name":"2020 3rd International Conference on Information and Computer Technologies (ICICT)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124441724","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 : 2020-03-01DOI: 10.1109/ICICT50521.2020.00013
Weiwei Xie, Mingyan He, Bo Tang
This paper presents a study of examining the statistical correlation between wildfire and weather by mining historical spatial and temporal wildfire and climate data. Large wildfires have been recently becoming more frequent, intense and destructive in the West of United States. The occurrence of wildfires can be determined by many human and natural factors, such as the availability of fuels, physical settings, and weather conditions, among which weather is of great interest and importance for wildfire forecasting. The availability of landscape fire data sets and weather data sets now enables the analysis of correlation between wildfire and weather which indicates the possibility of wildfire for given weather conditions in one region. This paper investigates the relation between wildfire and drought conditions in California and visualize the results using geographic information system (GIS) computing technology. Our data analysis findings show a high correlation between the normalized number of wildfires per forest unit area and drought severity, illustrating the potential of forecasting wildfire using weather data.
{"title":"Data-Enabled Correlation Analysis between Wildfire and Climate using GIS","authors":"Weiwei Xie, Mingyan He, Bo Tang","doi":"10.1109/ICICT50521.2020.00013","DOIUrl":"https://doi.org/10.1109/ICICT50521.2020.00013","url":null,"abstract":"This paper presents a study of examining the statistical correlation between wildfire and weather by mining historical spatial and temporal wildfire and climate data. Large wildfires have been recently becoming more frequent, intense and destructive in the West of United States. The occurrence of wildfires can be determined by many human and natural factors, such as the availability of fuels, physical settings, and weather conditions, among which weather is of great interest and importance for wildfire forecasting. The availability of landscape fire data sets and weather data sets now enables the analysis of correlation between wildfire and weather which indicates the possibility of wildfire for given weather conditions in one region. This paper investigates the relation between wildfire and drought conditions in California and visualize the results using geographic information system (GIS) computing technology. Our data analysis findings show a high correlation between the normalized number of wildfires per forest unit area and drought severity, illustrating the potential of forecasting wildfire using weather data.","PeriodicalId":445000,"journal":{"name":"2020 3rd International Conference on Information and Computer Technologies (ICICT)","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126341351","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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