Pub Date : 2024-06-03DOI: 10.1109/mprv.2024.3394268
Fahim Kawsar
The metaverse is rapidly evolving from a concept of the future into a vibrant digital playground, where individuals can engage with each other, learn, and explore through immersive virtual experiences. This emerging space offers thrilling opportunities for global connection, allowing us to share ideas and innovations without the constraints of physical distance. However, as we immerse ourselves more in these virtual worlds, concerns are rising about their effects on our real-life social abilities.
{"title":"Beyond Pixels","authors":"Fahim Kawsar","doi":"10.1109/mprv.2024.3394268","DOIUrl":"https://doi.org/10.1109/mprv.2024.3394268","url":null,"abstract":"The metaverse is rapidly evolving from a concept of the future into a vibrant digital playground, where individuals can engage with each other, learn, and explore through immersive virtual experiences. This emerging space offers thrilling opportunities for global connection, allowing us to share ideas and innovations without the constraints of physical distance. However, as we immerse ourselves more in these virtual worlds, concerns are rising about their effects on our real-life social abilities.","PeriodicalId":55021,"journal":{"name":"IEEE Pervasive Computing","volume":"5 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141252104","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 : 2024-06-03DOI: 10.1109/mprv.2024.3385171
{"title":"Get Published in the New IEEE Transactions on Privacy","authors":"","doi":"10.1109/mprv.2024.3385171","DOIUrl":"https://doi.org/10.1109/mprv.2024.3385171","url":null,"abstract":"","PeriodicalId":55021,"journal":{"name":"IEEE Pervasive Computing","volume":"45 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141943851","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 : 2024-06-03DOI: 10.1109/mprv.2024.3383955
Lakmal Meegahapola
The “Emerging Rockstar” segment in IEEE Pervasive Computing highlights rising stars in the field of pervasive computing through captivating interviews. In the series’ inaugural article, Dr. Lakmal Meegahapola, a member of IEEE Pervasive Computing's editorial board, conducts an interview with Dr. Jingxian Wang, an Assistant Professor at the National University of Singapore.
{"title":"Jingxian Wang: “Pushing the Limits of Battery-Free Internet-of-Things”","authors":"Lakmal Meegahapola","doi":"10.1109/mprv.2024.3383955","DOIUrl":"https://doi.org/10.1109/mprv.2024.3383955","url":null,"abstract":"The “Emerging Rockstar” segment in IEEE Pervasive Computing highlights rising stars in the field of pervasive computing through captivating interviews. In the series’ inaugural article, Dr. Lakmal Meegahapola, a member of IEEE Pervasive Computing's editorial board, conducts an interview with Dr. Jingxian Wang, an Assistant Professor at the National University of Singapore.","PeriodicalId":55021,"journal":{"name":"IEEE Pervasive Computing","volume":"14 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141252105","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 : 2024-06-03DOI: 10.1109/mprv.2024.3399486
{"title":"IEEE Computer Society Has You Covered!","authors":"","doi":"10.1109/mprv.2024.3399486","DOIUrl":"https://doi.org/10.1109/mprv.2024.3399486","url":null,"abstract":"","PeriodicalId":55021,"journal":{"name":"IEEE Pervasive Computing","volume":"38 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141969358","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 : 2024-06-03DOI: 10.1109/mprv.2023.3329546
Andrei C. Rusu, Katayoun Farrahi, Mahesan Niranjan
The effectiveness of an epidemic control policy relies largely on how much effort is invested in every public health measure. Unfortunately, it is seldom possible to optimally allocate funds to these measures if the isolated effect of each intervention cannot be reliably estimated. We show how this challenge can be overcome by utilizing EpiCURB, a simulation-control framework that enables us to measure the effect of both untargeted and prioritized interventions on the epidemic outcome, where the latter are guided by reinforcement learning routines that effectively rank eligible individuals.
{"title":"EpiCURB: Learning to Derive Epidemic Control Policies","authors":"Andrei C. Rusu, Katayoun Farrahi, Mahesan Niranjan","doi":"10.1109/mprv.2023.3329546","DOIUrl":"https://doi.org/10.1109/mprv.2023.3329546","url":null,"abstract":"The effectiveness of an epidemic control policy relies largely on how much effort is invested in every public health measure. Unfortunately, it is seldom possible to optimally allocate funds to these measures if the isolated effect of each intervention cannot be reliably estimated. We show how this challenge can be overcome by utilizing EpiCURB, a simulation-control framework that enables us to measure the effect of both untargeted and prioritized interventions on the epidemic outcome, where the latter are guided by reinforcement learning routines that effectively rank eligible individuals.","PeriodicalId":55021,"journal":{"name":"IEEE Pervasive Computing","volume":"72 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141252201","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 : 2024-06-03DOI: 10.1109/mprv.2024.3385179
{"title":"IEEE Computer Society Career Center","authors":"","doi":"10.1109/mprv.2024.3385179","DOIUrl":"https://doi.org/10.1109/mprv.2024.3385179","url":null,"abstract":"","PeriodicalId":55021,"journal":{"name":"IEEE Pervasive Computing","volume":"29 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141969357","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 : 2024-06-03DOI: 10.1109/mprv.2023.3346548
Orit Shaer, Angelora Cooper
Generative Artificial Intelligence (AI), including large language and image models, have created new opportunities for pervasive computing education. How do we integrate emerging AI models and tools into our courses in a way that fosters critical engagement? How do we teach students to use AI models and tools responsibly, thoughtfully, and ethically, while being aware of their capabilities and limitations? In this article, we share insights from integrating generative AI tools and machine learning (ML) models into a project-based undergraduate tangible and embodied interaction (TEI) course by employing co-creation processes. TEI is an evolving area within human–computer interaction, which focuses on integrating computation into our daily physical environments and objects, thus fostering an embodied, multisensory, and often collaborative interaction experience. We use the term co-creation to describe a process, where humans and AI work together to create new artifacts or solve a problem. We integrated structured co-creation activities into various phases of the project including ideation, conceptual design, and prototyping. We describe practical ways and learning goals for integrating emerging generative AI tools and ML models into the project design process, provide insight on how novice interaction designers iterate and collaborate with generative AI and ML models, and reflect on the merits and limitations of using generative AI tools and ML models for project-based interaction design courses for pervasive computing.
生成式人工智能（AI），包括大型语言和图像模型，为普适计算教育创造了新的机遇。我们如何将新兴的人工智能模型和工具整合到课程中，以促进批判性参与？我们如何教导学生负责任地、深思熟虑地、合乎道德地使用人工智能模型和工具，同时意识到它们的能力和局限性？在本文中，我们将分享通过采用共同创造过程，将人工智能生成工具和机器学习（ML）模型整合到基于项目的本科生有形与具身互动（TEI）课程中的心得。TEI 是人机交互中一个不断发展的领域，其重点是将计算整合到我们的日常物理环境和物体中，从而促进一种具身、多感官且经常是协作式的交互体验。我们使用 "共同创造 "一词来描述这一过程，即人类与人工智能共同创造新的人工制品或解决问题。我们将结构化的共同创造活动融入项目的各个阶段，包括构思、概念设计和原型设计。我们介绍了将新兴的生成式人工智能工具和 ML 模型整合到项目设计过程中的实用方法和学习目标，深入探讨了新手交互设计师如何与生成式人工智能和 ML 模型进行迭代和协作，并反思了在基于项目的普适计算交互设计课程中使用生成式人工智能工具和 ML 模型的优点和局限性。
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