Pub Date : 2023-04-01DOI: 10.1109/MPRV.2023.3263366
A. Diaz-Artiles, A. Ekblaw, Gregory Falco, Jeremy D. Frank, J. Paradiso
{"title":"Pervasive Computing in Space","authors":"A. Diaz-Artiles, A. Ekblaw, Gregory Falco, Jeremy D. Frank, J. Paradiso","doi":"10.1109/MPRV.2023.3263366","DOIUrl":"https://doi.org/10.1109/MPRV.2023.3263366","url":null,"abstract":"","PeriodicalId":55021,"journal":{"name":"IEEE Pervasive Computing","volume":"8 1","pages":"4-6"},"PeriodicalIF":1.6,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88369650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-01DOI: 10.1109/MPRV.2023.3263415
Zac Manchester, A. Loeb
The space age was enabled by the invention of the transistor, and the close association of computing with the final frontier continues today. In fact, progress in low-power embedded electronics over the last decade has spawned a new breed of small, low-cost spacecraft, and a burgeoning commercial industry around them. This article documents some of that recent progress, while also looking forward to the tremendous opportunities that lie ahead at the intersection of embedded computing and space exploration.
{"title":"Space: The Ultimate Computational Edge","authors":"Zac Manchester, A. Loeb","doi":"10.1109/MPRV.2023.3263415","DOIUrl":"https://doi.org/10.1109/MPRV.2023.3263415","url":null,"abstract":"The space age was enabled by the invention of the transistor, and the close association of computing with the final frontier continues today. In fact, progress in low-power embedded electronics over the last decade has spawned a new breed of small, low-cost spacecraft, and a burgeoning commercial industry around them. This article documents some of that recent progress, while also looking forward to the tremendous opportunities that lie ahead at the intersection of embedded computing and space exploration.","PeriodicalId":55021,"journal":{"name":"IEEE Pervasive Computing","volume":"22 1","pages":"43-48"},"PeriodicalIF":1.6,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42956900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-01DOI: 10.1109/mprv.2023.3280355
{"title":"Call for 2023 Major Awards Nominations","authors":"","doi":"10.1109/mprv.2023.3280355","DOIUrl":"https://doi.org/10.1109/mprv.2023.3280355","url":null,"abstract":"","PeriodicalId":55021,"journal":{"name":"IEEE Pervasive Computing","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135673443","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-29DOI: 10.1109/mprv.2023.3244009
Claudio Pinhanez, Florian Michahelles, Albrecht Schmidt
AI technology and systems are increasingly used in devices and systems that are part of the pervasive computing fabric of the world. However, people are critical in the design, operation, and use of those AI systems, and society has to ensure that those systems operate transparently, promote equitable outcomes, respect privacy, and effectively serve people’s needs. In this context, this special section focuses on human-centered AI provides a forum for papers investigating new forms of human–AI interactions and experiences that enhance and extend human capabilities in the context of pervasive applications and systems.
{"title":"Human-Centered AI","authors":"Claudio Pinhanez, Florian Michahelles, Albrecht Schmidt","doi":"10.1109/mprv.2023.3244009","DOIUrl":"https://doi.org/10.1109/mprv.2023.3244009","url":null,"abstract":"AI technology and systems are increasingly used in devices and systems that are part of the pervasive computing fabric of the world. However, people are critical in the design, operation, and use of those AI systems, and society has to ensure that those systems operate transparently, promote equitable outcomes, respect privacy, and effectively serve people’s needs. In this context, this special section focuses on human-centered AI provides a forum for papers investigating new forms of human–AI interactions and experiences that enhance and extend human capabilities in the context of pervasive applications and systems.","PeriodicalId":55021,"journal":{"name":"IEEE Pervasive Computing","volume":"56 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2023-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138528969","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1109/MPRV.2022.3229166
Michael Ungersböck, Thomas Hiessl, D. Schall, F. Michahelles
As the adoption of federated learning (FL) in the manufacturing industry grows and systems get increasingly complex, a need to inspect their behavior arises. Stakeholders of the FL process want a more transparent system to understand the current state and analyze how its performance changed over time. However, current representation approaches are often not designed for industrial applications and do not cover the entire FL model lifecycle. We propose the lifecycle dashboard, which considers the different requirements and perspectives of industrial stakeholders by visualizing information from the FL server. In addition, our representation approach is generic enough to be applied to different use cases and industries. We evaluate the lifecycle dashboard in a semistructured expert interview, show improvements in the understandability of FL systems, and discuss possible use cases in the industry.
{"title":"Explainable Federated Learning: A Lifecycle Dashboard for Industrial Settings","authors":"Michael Ungersböck, Thomas Hiessl, D. Schall, F. Michahelles","doi":"10.1109/MPRV.2022.3229166","DOIUrl":"https://doi.org/10.1109/MPRV.2022.3229166","url":null,"abstract":"As the adoption of federated learning (FL) in the manufacturing industry grows and systems get increasingly complex, a need to inspect their behavior arises. Stakeholders of the FL process want a more transparent system to understand the current state and analyze how its performance changed over time. However, current representation approaches are often not designed for industrial applications and do not cover the entire FL model lifecycle. We propose the lifecycle dashboard, which considers the different requirements and perspectives of industrial stakeholders by visualizing information from the FL server. In addition, our representation approach is generic enough to be applied to different use cases and industries. We evaluate the lifecycle dashboard in a semistructured expert interview, show improvements in the understandability of FL systems, and discuss possible use cases in the industry.","PeriodicalId":55021,"journal":{"name":"IEEE Pervasive Computing","volume":"22 1","pages":"19-28"},"PeriodicalIF":1.6,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43336063","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1109/mprv.2023.3251905
This Conference looks for significant contributions to the Computer Networks, Communications, wireless and mobile computing for wired and wireless networks in theoretical and practical aspects. Original papers are invited on computer Networks, network protocols and wireless networks, Data communication Technologies, network security and mobile computing. The goal of this Conference is to bring together researchers and practitioners from academia and industry to focus on advanced networking concepts and establishing new collaborations in these areas.
{"title":"Call for Participation: IEEE Quantum Week is Open for Submissions","authors":"","doi":"10.1109/mprv.2023.3251905","DOIUrl":"https://doi.org/10.1109/mprv.2023.3251905","url":null,"abstract":"This Conference looks for significant contributions to the Computer Networks, Communications, wireless and mobile computing for wired and wireless networks in theoretical and practical aspects. Original papers are invited on computer Networks, network protocols and wireless networks, Data communication Technologies, network security and mobile computing. The goal of this Conference is to bring together researchers and practitioners from academia and industry to focus on advanced networking concepts and establishing new collaborations in these areas.","PeriodicalId":55021,"journal":{"name":"IEEE Pervasive Computing","volume":"1 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47389531","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1109/mprv.2023.3312652
Soto Anno, Kota Tsubouchi, Masamichi Shimosaka
This article studies crowd dynamics forecast one week in advance to detect irregular urban events, which plays an important role in infection prevention and crowd control. Previous approaches have failed to deal with the scarcity of anomalous events, resulting in a large model bias, and could not quantify the number of visitors in anomalous crowding. We proposed an unbiased regression using importance weighting (IW), called CityOutlook, and successfully reduced the model bias and showed promising results. However, the straightforward weighting of the scarce data risks leading to the instability of the model due to the increase in model variance. To address this issue, we propose a nontrivial extension of our prior work called CityOutlook+ that realizes unbiased and less-variant regression by performing synthetic minority oversampling based on the importance. We evaluate CityOutlook+ using real datasets and demonstrate the superiority of our model to CityOutlook and state-of-the-art approaches.
{"title":"CityOutlook+: Early Crowd Dynamics Forecast Through Unbiased Regression With Importance-Based Synthetic Oversampling","authors":"Soto Anno, Kota Tsubouchi, Masamichi Shimosaka","doi":"10.1109/mprv.2023.3312652","DOIUrl":"https://doi.org/10.1109/mprv.2023.3312652","url":null,"abstract":"This article studies crowd dynamics forecast one week in advance to detect irregular urban events, which plays an important role in infection prevention and crowd control. Previous approaches have failed to deal with the scarcity of anomalous events, resulting in a large model bias, and could not quantify the number of visitors in anomalous crowding. We proposed an unbiased regression using importance weighting (IW), called CityOutlook, and successfully reduced the model bias and showed promising results. However, the straightforward weighting of the scarce data risks leading to the instability of the model due to the increase in model variance. To address this issue, we propose a nontrivial extension of our prior work called CityOutlook+ that realizes unbiased and <italic xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">less-variant</i> regression by performing synthetic minority oversampling based on the importance. We evaluate CityOutlook+ using real datasets and demonstrate the superiority of our model to CityOutlook and state-of-the-art approaches.","PeriodicalId":55021,"journal":{"name":"IEEE Pervasive Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135754555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1109/mprv.2023.3321218
Alfredo J. Perez, Sherali Zeadally, David Kingsley Tan
More than 6 billion smartphones available worldwide can enable governments and public health organizations to develop apps to manage global pandemics. However, hackers can take advantage of this opportunity to target the public in nefarious ways through malware disguised as pandemics-related apps. A recent analysis conducted during the COVID-19 pandemic showed that several variants of COVID-19 related malware were installed by the public from nontrusted sources. We propose the use of app permissions and an extra feature (the total number of permissions) to develop a static detector using machine learning (ML) models to enable the fast-detection of pandemics-related Android malware at installation time. Using a dataset of more than 2000 COVID-19 related apps and by evaluating ML models created using decision trees and Naive Bayes, our results show that pandemics-related malware apps can be detected with an accuracy above 90% using decision tree models with app permissions and the proposed feature.
{"title":"Detecting Mobile Malware Associated With Global Pandemics","authors":"Alfredo J. Perez, Sherali Zeadally, David Kingsley Tan","doi":"10.1109/mprv.2023.3321218","DOIUrl":"https://doi.org/10.1109/mprv.2023.3321218","url":null,"abstract":"More than 6 billion smartphones available worldwide can enable governments and public health organizations to develop apps to manage global pandemics. However, hackers can take advantage of this opportunity to target the public in nefarious ways through malware disguised as pandemics-related apps. A recent analysis conducted during the COVID-19 pandemic showed that several variants of COVID-19 related malware were installed by the public from nontrusted sources. We propose the use of app permissions and an extra feature (the total number of permissions) to develop a static detector using machine learning (ML) models to enable the fast-detection of pandemics-related Android malware at installation time. Using a dataset of more than 2000 COVID-19 related apps and by evaluating ML models created using decision trees and Naive Bayes, our results show that pandemics-related malware apps can be detected with an accuracy above 90% using decision tree models with app permissions and the proposed feature.","PeriodicalId":55021,"journal":{"name":"IEEE Pervasive Computing","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135058249","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1109/MPRV.2022.3232620
Bumsoo Kang, Seungwoo Kang, Inseok Hwang
Computer-mediated interaction services connect people over a distance. However, we address that those people are often “locked in a frame”—which includes an interaction mode, a point in time, or a context of either person. We observe that such lock-ins make it difficult to shape the interaction to be mutually symmetric. In this article, we propose a semantic-equivalent melding of space and time to provide a new form of empathetic interaction. We present HomeMeld and MomentMeld, which aim to meld space and time by applying AI, respectively. HomeMeld provides a sense of living together to a family living apart with AI-driven autonomous robotic avatars. MomentMeld utilizes an ensemble of visual AI to create interaction topics by matching semantic-equivalent photos. In-the-wild experiments reveal that HomeMeld and MomentMeld open new possibilities for empathetic interaction. Finally, we introduce a new interaction service leveraging technical synergy of HomeMeld and MomentMeld.
{"title":"AI-driven Family Interaction Over Melded Space and Time","authors":"Bumsoo Kang, Seungwoo Kang, Inseok Hwang","doi":"10.1109/MPRV.2022.3232620","DOIUrl":"https://doi.org/10.1109/MPRV.2022.3232620","url":null,"abstract":"Computer-mediated interaction services connect people over a distance. However, we address that those people are often “locked in a frame”—which includes an interaction mode, a point in time, or a context of either person. We observe that such lock-ins make it difficult to shape the interaction to be mutually symmetric. In this article, we propose a semantic-equivalent melding of space and time to provide a new form of empathetic interaction. We present HomeMeld and MomentMeld, which aim to meld space and time by applying AI, respectively. HomeMeld provides a sense of living together to a family living apart with AI-driven autonomous robotic avatars. MomentMeld utilizes an ensemble of visual AI to create interaction topics by matching semantic-equivalent photos. In-the-wild experiments reveal that HomeMeld and MomentMeld open new possibilities for empathetic interaction. Finally, we introduce a new interaction service leveraging technical synergy of HomeMeld and MomentMeld.","PeriodicalId":55021,"journal":{"name":"IEEE Pervasive Computing","volume":"22 1","pages":"85-94"},"PeriodicalIF":1.6,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46267852","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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