Pub Date : 2021-12-01DOI: 10.1109/CSCI54926.2021.00289
M. Anedda, M. Fadda, M. Farina, Roberto Girau, M. Sole, D. Giusto
Smart cities are characterized by smart heterogeneous devices that can interact and cooperate with each other by exchanging regularly big amounts of data with the big issue to treat sensitive data in a properly respectful manner, avoiding exposure to the risks that new technologies inevitably bring to the fore. This objective can only be pursued with adequate knowledge of the risks and methods of protection, for this reason in addition to producing materially functional results, it has been studied in depth the techniques of protection of personal data including the anonymization and pseud-anonymization of sensitive data. We provide the analysis of the state of the art that starts from the concepts of security and privacy and comes to an analysis of anonymization algorithms. This analysis tries to give an overview of the two fundamental issues in the field of data security: privacy, according to the European Regulation 2016 (GDPR) and the practical techniques with which it is preserved, with particular attention to anonymization algorithms: we analyze the advantages and disadvantages of the latter. The performance of the proposed solution is compared against that of a TraffictYpe-based DifferEntiated Reputation (TYDER) algorithm. This performance was evaluated in terms of QoS parameters such as delay, latency, packet loss and prediction error. The results show how MISSION outperforms TYDER in urban mobility scenario.
{"title":"Safe Social Internet of Thing for Urban Mobility Services","authors":"M. Anedda, M. Fadda, M. Farina, Roberto Girau, M. Sole, D. Giusto","doi":"10.1109/CSCI54926.2021.00289","DOIUrl":"https://doi.org/10.1109/CSCI54926.2021.00289","url":null,"abstract":"Smart cities are characterized by smart heterogeneous devices that can interact and cooperate with each other by exchanging regularly big amounts of data with the big issue to treat sensitive data in a properly respectful manner, avoiding exposure to the risks that new technologies inevitably bring to the fore. This objective can only be pursued with adequate knowledge of the risks and methods of protection, for this reason in addition to producing materially functional results, it has been studied in depth the techniques of protection of personal data including the anonymization and pseud-anonymization of sensitive data. We provide the analysis of the state of the art that starts from the concepts of security and privacy and comes to an analysis of anonymization algorithms. This analysis tries to give an overview of the two fundamental issues in the field of data security: privacy, according to the European Regulation 2016 (GDPR) and the practical techniques with which it is preserved, with particular attention to anonymization algorithms: we analyze the advantages and disadvantages of the latter. The performance of the proposed solution is compared against that of a TraffictYpe-based DifferEntiated Reputation (TYDER) algorithm. This performance was evaluated in terms of QoS parameters such as delay, latency, packet loss and prediction error. The results show how MISSION outperforms TYDER in urban mobility scenario.","PeriodicalId":206881,"journal":{"name":"2021 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129491018","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 will cover the planning and development of cloud applications that are used in the workplace. In addition to researching the feature needs of these applications, we will examine the risks and rewards of using these cloud applications for businesses. For instance, we go into how cloud software could be used in education as well as for small business and dive into the benefits that can be obtained from both. On the other hand, when conducting business on the cloud, there is always a risk that your data can be intercepted by an unwanted party through scripting or injection attacks. With the cloud becoming larger every year, we also dive into the European Union (EU) and the United States (US) privacy regulators and how they act in favor of the consumer, so that their data and rights are protected. Finally, we examine the many different scaling techniques and infrastructure providers can elect to deploy a combination of them, so that service quality does not degrade with an increase of traffic.
{"title":"Engineering Cloud Applications for the Workplace","authors":"Noah Bankston, Sandy Jarkas, Tara Jubran, Noah Pape, Sterling Walker, Terrell Brooks, Mohammed Mahmoud","doi":"10.1109/CSCI54926.2021.00138","DOIUrl":"https://doi.org/10.1109/CSCI54926.2021.00138","url":null,"abstract":"This paper will cover the planning and development of cloud applications that are used in the workplace. In addition to researching the feature needs of these applications, we will examine the risks and rewards of using these cloud applications for businesses. For instance, we go into how cloud software could be used in education as well as for small business and dive into the benefits that can be obtained from both. On the other hand, when conducting business on the cloud, there is always a risk that your data can be intercepted by an unwanted party through scripting or injection attacks. With the cloud becoming larger every year, we also dive into the European Union (EU) and the United States (US) privacy regulators and how they act in favor of the consumer, so that their data and rights are protected. Finally, we examine the many different scaling techniques and infrastructure providers can elect to deploy a combination of them, so that service quality does not degrade with an increase of traffic.","PeriodicalId":206881,"journal":{"name":"2021 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130659157","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-01DOI: 10.1109/CSCI54926.2021.00142
A. Delbem, A. Saraiva, J. London, R. Fanucchi
Artificial Intelligence in Complex Networks has contributed to several relevant fields involving energy systems, computer networks, environment, agriculture, health, and social organizations. However, investigations concerning multiple heterogeneous networks have been less frequent. Mixed systems usually require fine-grained data to retain a sufficient amount of details from each network. This type of modeling may enable the investigation of emerging behaviors or synergies. For example, a decision making may require the search for an improved network configuration (involving coarse and fine modifications on devices, procedures, and settings) with the lowest possible cost to soon mitigate effects from climate changes or other types of "attacks" (from economic crises, calamities, and recent pandemics). The generation of robust configurations for heterogeneous networks involves some challenges, pointed out in this paper. Among them, the efficient calculus of load flows has been one of the main challenges. To overcome it, we propose a load flow algorithm with sublinear time complexity for the construction and evaluation of several configurations. The new algorithm scales well and can deal with nonlinear dynamics in evaluations of entire sets of fine-grained network models that it may involve.
{"title":"Sublinear evaluation of complex networks for extensive exploration of configurations for critical scenarios and decision making","authors":"A. Delbem, A. Saraiva, J. London, R. Fanucchi","doi":"10.1109/CSCI54926.2021.00142","DOIUrl":"https://doi.org/10.1109/CSCI54926.2021.00142","url":null,"abstract":"Artificial Intelligence in Complex Networks has contributed to several relevant fields involving energy systems, computer networks, environment, agriculture, health, and social organizations. However, investigations concerning multiple heterogeneous networks have been less frequent. Mixed systems usually require fine-grained data to retain a sufficient amount of details from each network. This type of modeling may enable the investigation of emerging behaviors or synergies. For example, a decision making may require the search for an improved network configuration (involving coarse and fine modifications on devices, procedures, and settings) with the lowest possible cost to soon mitigate effects from climate changes or other types of \"attacks\" (from economic crises, calamities, and recent pandemics). The generation of robust configurations for heterogeneous networks involves some challenges, pointed out in this paper. Among them, the efficient calculus of load flows has been one of the main challenges. To overcome it, we propose a load flow algorithm with sublinear time complexity for the construction and evaluation of several configurations. The new algorithm scales well and can deal with nonlinear dynamics in evaluations of entire sets of fine-grained network models that it may involve.","PeriodicalId":206881,"journal":{"name":"2021 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"87 46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130378183","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-01DOI: 10.1109/CSCI54926.2021.00078
Choong-soo Han
Unfortunately, convenience is getting more overemphasized, the risk of smart world is getting more neglected. Smart worlds like smart cities, smart homes, smart factories, smart traffics are making web-based IT systems more and more. Many research papers tells us that web-based IT systems are fundamentally vulnerable. Truly, it is very difficult to defend against every cyber attack. Definitely, it is impossible to think about safe smart world without cybersecurity. It is really needed to reduce the risk of smart world. If access from overseas is not necessary, blocking cyber threats from abroad is the best way to reduce the risk of cyber infringements for smart world.
{"title":"Enhanced cybersecurity for safe smart world","authors":"Choong-soo Han","doi":"10.1109/CSCI54926.2021.00078","DOIUrl":"https://doi.org/10.1109/CSCI54926.2021.00078","url":null,"abstract":"Unfortunately, convenience is getting more overemphasized, the risk of smart world is getting more neglected. Smart worlds like smart cities, smart homes, smart factories, smart traffics are making web-based IT systems more and more. Many research papers tells us that web-based IT systems are fundamentally vulnerable. Truly, it is very difficult to defend against every cyber attack. Definitely, it is impossible to think about safe smart world without cybersecurity. It is really needed to reduce the risk of smart world. If access from overseas is not necessary, blocking cyber threats from abroad is the best way to reduce the risk of cyber infringements for smart world.","PeriodicalId":206881,"journal":{"name":"2021 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130085403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-01DOI: 10.1109/CSCI54926.2021.00274
Thubelihle S. Zulu, Topside E. Mathonsi
Poor VoIP quality in IP telephone infrastructure is a major concern and it can affect business growth, especially to businesses that deal with interacting with a client over the phone. Speech or audio signals are usually affected by codec mismatch, packet loss, and jitter which affect user perception of voice quality. VoIP telephone system is growing at a rapid speed and has received much attention because of their call cost internationally and national and fewer resources needed compared to traditional voice telephone systems or public switched telephone networks. The main aim of this paper is to develop a solution that will provide an enhanced voice quality in VoIP platform systems by implementing the amended VoIP codec transcoding system that auto negotiates VoIP codec with the intention of preventing VoIP codec mismatch via standalone and software VoIP codec transcoding system. An experimental research with technological tools such as SIP (Session Initiation Protocol) phone, asterisk PBX (Private Branch Exchange) systems and SBC (Session Border Control) will be conducted. A practical test will be carried out in any working environment with the converged network in order to test results or findings to solve the problem of codec mismatch with the intention of enhancing Voice quality and avoiding calls dropping issues in IP telephone infrastructure. This paper is introducing an amended VoIP codec transcoding system that auto-negotiate VoIP codec in order to prevent codec mismatch and enhance voice quality hence codec mismatch is not only the major concern for VoIP quality, VoIP quality can be affected by many factors, such as packet loss, jitter, packet delay, and bandwidth but this paper is focusing on the codec mismatch.
{"title":"An Enhanced VoIP Codec Transcoder to Enhance VoIP Quality for IP Telephone Infrastructure","authors":"Thubelihle S. Zulu, Topside E. Mathonsi","doi":"10.1109/CSCI54926.2021.00274","DOIUrl":"https://doi.org/10.1109/CSCI54926.2021.00274","url":null,"abstract":"Poor VoIP quality in IP telephone infrastructure is a major concern and it can affect business growth, especially to businesses that deal with interacting with a client over the phone. Speech or audio signals are usually affected by codec mismatch, packet loss, and jitter which affect user perception of voice quality. VoIP telephone system is growing at a rapid speed and has received much attention because of their call cost internationally and national and fewer resources needed compared to traditional voice telephone systems or public switched telephone networks. The main aim of this paper is to develop a solution that will provide an enhanced voice quality in VoIP platform systems by implementing the amended VoIP codec transcoding system that auto negotiates VoIP codec with the intention of preventing VoIP codec mismatch via standalone and software VoIP codec transcoding system. An experimental research with technological tools such as SIP (Session Initiation Protocol) phone, asterisk PBX (Private Branch Exchange) systems and SBC (Session Border Control) will be conducted. A practical test will be carried out in any working environment with the converged network in order to test results or findings to solve the problem of codec mismatch with the intention of enhancing Voice quality and avoiding calls dropping issues in IP telephone infrastructure. This paper is introducing an amended VoIP codec transcoding system that auto-negotiate VoIP codec in order to prevent codec mismatch and enhance voice quality hence codec mismatch is not only the major concern for VoIP quality, VoIP quality can be affected by many factors, such as packet loss, jitter, packet delay, and bandwidth but this paper is focusing on the codec mismatch.","PeriodicalId":206881,"journal":{"name":"2021 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127900617","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-01DOI: 10.1109/CSCI54926.2021.00232
D. Ahmed
Learning can be more efficient, effective and interesting if we can identify more about our students and know how they learn. Due to COVID-19, schools and colleges are offering online classes. It has a significant impact on students’ success. Therefore, course modality and teaching pedagogy need to be taken into consideration for crafting and creating instructional experiences that make leaning appealing and effective. A number of innovative teaching methods such as active learning, hybrid learning, social learning and flipped classrooms have been proposed and tested. Practically, several methods together can be helpful for students. In this study, I conducted an experiment and identified effective learning methods for graduate level courses. According to this study, 94% students responded positively about this course design. The results also show that 83.5% students prefer face-to-face classes and 97% students find in-class problem solving effective to understand a concept better. Many courses incorporate team-based learning which is a proven approach. In this study, the benefits and limitations of team-based programming projects are identified as well as students’ opinion in this regard. The results show that 85% students prefer team-based programming projects. Surprisingly 59.1% students mentioned all members do not contribute fairly evenly. This is a common problem in group works. So, small group size could be effective to overcome this problem.
{"title":"Discovering Effective Learning Methods and Impact of Team-based Programming Projects in Graduate Level Courses","authors":"D. Ahmed","doi":"10.1109/CSCI54926.2021.00232","DOIUrl":"https://doi.org/10.1109/CSCI54926.2021.00232","url":null,"abstract":"Learning can be more efficient, effective and interesting if we can identify more about our students and know how they learn. Due to COVID-19, schools and colleges are offering online classes. It has a significant impact on students’ success. Therefore, course modality and teaching pedagogy need to be taken into consideration for crafting and creating instructional experiences that make leaning appealing and effective. A number of innovative teaching methods such as active learning, hybrid learning, social learning and flipped classrooms have been proposed and tested. Practically, several methods together can be helpful for students. In this study, I conducted an experiment and identified effective learning methods for graduate level courses. According to this study, 94% students responded positively about this course design. The results also show that 83.5% students prefer face-to-face classes and 97% students find in-class problem solving effective to understand a concept better. Many courses incorporate team-based learning which is a proven approach. In this study, the benefits and limitations of team-based programming projects are identified as well as students’ opinion in this regard. The results show that 85% students prefer team-based programming projects. Surprisingly 59.1% students mentioned all members do not contribute fairly evenly. This is a common problem in group works. So, small group size could be effective to overcome this problem.","PeriodicalId":206881,"journal":{"name":"2021 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"13 24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124688574","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-01DOI: 10.1109/CSCI54926.2021.00135
T. Ovatman, Muhammed Enes Tırnakçı, A. Yılmaz
Recent advances in communication technology has begun to push the data centers towards high altitude platform stations (HAPS) due to their advantages in communication coverage, mobility and cooling. There are plenty of studies that focus on the communication aspects of such devices but the issues regarding deploying micro data centers on HAPS is rarely studied. In the future, there is a potential for a substantial amount of processing power to be offload to such stations to back up terrestrial stations in fog computing scenarios. In this study we have analyzed cloud workload handling and power consumption efficiencies of two different HAPS deployment scenarios. In our simulations, performed with CloudSim Plus, we have experimented with scenarios with varying number of lower and higher altitude HAPS and terrestrial base stations. In our experiments we have identified the trade-offs and cases to provide better performance in handling cloud workloads.
{"title":"Utilizing HAPS Deployed Data Centers in Offloading Cloud Workloads","authors":"T. Ovatman, Muhammed Enes Tırnakçı, A. Yılmaz","doi":"10.1109/CSCI54926.2021.00135","DOIUrl":"https://doi.org/10.1109/CSCI54926.2021.00135","url":null,"abstract":"Recent advances in communication technology has begun to push the data centers towards high altitude platform stations (HAPS) due to their advantages in communication coverage, mobility and cooling. There are plenty of studies that focus on the communication aspects of such devices but the issues regarding deploying micro data centers on HAPS is rarely studied. In the future, there is a potential for a substantial amount of processing power to be offload to such stations to back up terrestrial stations in fog computing scenarios. In this study we have analyzed cloud workload handling and power consumption efficiencies of two different HAPS deployment scenarios. In our simulations, performed with CloudSim Plus, we have experimented with scenarios with varying number of lower and higher altitude HAPS and terrestrial base stations. In our experiments we have identified the trade-offs and cases to provide better performance in handling cloud workloads.","PeriodicalId":206881,"journal":{"name":"2021 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"109 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127315207","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-01DOI: 10.1109/CSCI54926.2021.00303
Dena F. Mujtaba, N. Mahapatra
Seafood comprises the largest globally traded food commodity in the world. Its supply chains are complex, focus on quick distribution, and rely on processing practices that make it difficult to trace products to their source. This has resulted in seafood mislabeling, with investigations revealing mislabeling of more than 30% of marketed seafood products, though the full extent of seafood mislabeling in the U.S. is unknown. When two species are morphologically similar, it is difficult for humans to visually distinguish between them, thus making mislabeling difficult to detect. To address this problem, we present a novel deep-learning-based model to distinguish between morphologically similar fish species in images. Our approach uses transfer learning with state-of-the-art convolutional neural networks (CNN) to build upon previously learned features on millions of images, thereby improving the model’s classification accuracy. We compare three pretrained CNNs: VGG, ResNet, and RegNet. For evaluation, we utilize the FishNet Open Image Database, containing over 85,000 images from electronic monitoring footage of fisheries. We train and test two models: a 4-species classifier of visually-similar tuna species, and a binary classifier of visually-indistinguishable tuna often mislabeled. Our results show CNNs can be used to distinguish between morphologically similar fish species with high accuracy, which otherwise would often be mislabeled by humans.
{"title":"Convolutional Neural Networks for Morphologically Similar Fish Species Identification","authors":"Dena F. Mujtaba, N. Mahapatra","doi":"10.1109/CSCI54926.2021.00303","DOIUrl":"https://doi.org/10.1109/CSCI54926.2021.00303","url":null,"abstract":"Seafood comprises the largest globally traded food commodity in the world. Its supply chains are complex, focus on quick distribution, and rely on processing practices that make it difficult to trace products to their source. This has resulted in seafood mislabeling, with investigations revealing mislabeling of more than 30% of marketed seafood products, though the full extent of seafood mislabeling in the U.S. is unknown. When two species are morphologically similar, it is difficult for humans to visually distinguish between them, thus making mislabeling difficult to detect. To address this problem, we present a novel deep-learning-based model to distinguish between morphologically similar fish species in images. Our approach uses transfer learning with state-of-the-art convolutional neural networks (CNN) to build upon previously learned features on millions of images, thereby improving the model’s classification accuracy. We compare three pretrained CNNs: VGG, ResNet, and RegNet. For evaluation, we utilize the FishNet Open Image Database, containing over 85,000 images from electronic monitoring footage of fisheries. We train and test two models: a 4-species classifier of visually-similar tuna species, and a binary classifier of visually-indistinguishable tuna often mislabeled. Our results show CNNs can be used to distinguish between morphologically similar fish species with high accuracy, which otherwise would often be mislabeled by humans.","PeriodicalId":206881,"journal":{"name":"2021 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127435744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-01DOI: 10.1109/CSCI54926.2021.00286
Shubhangi Rastogi, D. Bansal
The prevalence of fake news has augmented with the rise of digital sources, especially social media. In this paper, current fake news research is studied and examined to offer a succinct road-map for future work. The paper presents a novel three-tier system depending on the lifespan of news and divides the research in three phases: early, mid and late-stage detection. The strategy to be followed for fake news detection varies with the time of detection. Fake news has shown adverse effects in a very short time period of propagation on social media. To mitigate this, it is required to detect fake news at an early stage when limited information about the news is available. In contrast, rich information can be examined like user engagement, propagation patterns, etc., at a later stage when news is deeply spread in the social network. Therefore, it is important to first analyze the time when the news disseminated, and then follow a suitable fake news detection methodology presented in the-state-of-the-art.
{"title":"Time is Important in Fake News Detection: a short review","authors":"Shubhangi Rastogi, D. Bansal","doi":"10.1109/CSCI54926.2021.00286","DOIUrl":"https://doi.org/10.1109/CSCI54926.2021.00286","url":null,"abstract":"The prevalence of fake news has augmented with the rise of digital sources, especially social media. In this paper, current fake news research is studied and examined to offer a succinct road-map for future work. The paper presents a novel three-tier system depending on the lifespan of news and divides the research in three phases: early, mid and late-stage detection. The strategy to be followed for fake news detection varies with the time of detection. Fake news has shown adverse effects in a very short time period of propagation on social media. To mitigate this, it is required to detect fake news at an early stage when limited information about the news is available. In contrast, rich information can be examined like user engagement, propagation patterns, etc., at a later stage when news is deeply spread in the social network. Therefore, it is important to first analyze the time when the news disseminated, and then follow a suitable fake news detection methodology presented in the-state-of-the-art.","PeriodicalId":206881,"journal":{"name":"2021 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127364121","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-01DOI: 10.1109/CSCI54926.2021.00110
Julian Cagnazzo, Osama Sam Abuomar, A. Yanguas-Gil, J. Elam
Atomic layer deposition (ALD) is a chemical engineering process used to coat surfaces with a thin film. It is a versatile process able to deposit a wide range of films using different chemical reagents. When developing novel ALD processes, a technician must determine the dosing time of each reagent. To accelerate this development process, we trained convolutional neural networks to predict the reagent saturation times of novel ALD reactions given the reagent dosing times and film growth rates of example reactions. We generated two kinds of models. Single reaction models made predictions based on a single example ALD reaction. Multiple reaction models made predictions based on ten example reactions using the same reagents with different dosing times.
{"title":"Atomic Layer Deposition Optimization Using Convolutional Neural Networks","authors":"Julian Cagnazzo, Osama Sam Abuomar, A. Yanguas-Gil, J. Elam","doi":"10.1109/CSCI54926.2021.00110","DOIUrl":"https://doi.org/10.1109/CSCI54926.2021.00110","url":null,"abstract":"Atomic layer deposition (ALD) is a chemical engineering process used to coat surfaces with a thin film. It is a versatile process able to deposit a wide range of films using different chemical reagents. When developing novel ALD processes, a technician must determine the dosing time of each reagent. To accelerate this development process, we trained convolutional neural networks to predict the reagent saturation times of novel ALD reactions given the reagent dosing times and film growth rates of example reactions. We generated two kinds of models. Single reaction models made predictions based on a single example ALD reaction. Multiple reaction models made predictions based on ten example reactions using the same reagents with different dosing times.","PeriodicalId":206881,"journal":{"name":"2021 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"162 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121877953","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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