Imwut 2020. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT)

Discussion in '2020' started by Fenribar , Wednesday, February 23, 2022 7:07:02 AM.

  1. Zulujar

    Zulujar

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    Taken together, our experimental findings caution against using UDA as a silver bullet for adapting HAR models to new domains, and serve as practical guidelines for HAR practitioners as well as pave the way for future research on domain adaptation in HAR. In this paper, we present an observational study of the relationships between the emotional states of individuals and objects present in their visual environment automatically extracted from smartphone images using deep learning techniques. However, multi-modal sensing has the potential to characterize these daily activities. We prototyped sets of sensor-embedded toy blocks, AssessBlocks, that automate quantitative play data acquisition. Mining wearable sleep data for detecting unusual sleep.
     
  2. Tygotaxe

    Tygotaxe

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    The Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT) is a premier journal series for research relevant to the.This allows users to quickly implement silver traces with a variety of properties by exploiting a wide range of substrates.
     
  3. Digul

    Digul

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    Archive. s; s. · · · · , Volume 5. 4 image. Dec , Issue 4. Current-Issue · 3 image. Sept , Issue 3.However, one of the key issues in public WiFi spots is the privacy concern due to its open access nature.
    Imwut 2020.
     
  4. Fenrimuro

    Fenrimuro

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    IMWUT has 4 deadlines per year: February 15, May 15, August 15, and November We expect a quick publication schedule. For instance, papers.We argue that to fully take advantage of this potential, mobile apps must become things themselves, and interact in a smart space like their hardware counterparts.Forum Imwut 2020
     
  5. Goltibei

    Goltibei

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    The following IMWUT papers from four issues will be presented at the UbiComp / ISWC virtual conference: IMWUT Vol 3, Issue 4.Advertising is an unavoidable albeit a frustrating part of mobile interactions.
     
  6. Mezizilkree

    Mezizilkree

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    text to speech. issn: (online). IMWUT @ ACM DL · Volume 5: · Volume 4: · Volume 3: · Volume 2: · Volume 1: Lecture Notes in Artificial Intelligence.
     
  7. Miramar

    Miramar

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    Synchronous Target Selection through User Behavior Modeling** ([led by Tengxiang Zhang](heavenmanga.online)) are accepted by IMWUT The locomotor-respiratory coupling LRC ratio of a person doing exercise is an important parameter to reflect the exercise safety and effectiveness.
     
  8. Grogal

    Grogal

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    forum? The impact score (IS) of Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies is , which is computed.Such continuous KEH-based authentication and key generation is expected to be highly power efficient as it obviates the need to employ any extra sensors, such as accelerometer, to precisely track the walking patterns.
     
  9. Gardazuru

    Gardazuru

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    Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, ACM IMWUT, H. Rashid, V. Stankovic, L. Stankovic, P. Singh.However, few works have studied the design space of bimanual hand gestures or attempted to infer gestures that involve devices on both hands.
     
  10. Negami

    Negami

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    Special Recognition for Outstanding Review, PACM IMWUT. • Early Career Researcher Zhanna Sarsenbayeva (PhD, primary supervisor): Taken together, our experimental findings caution against using UDA as a silver bullet for adapting HAR models to new domains, and serve as practical guidelines for HAR practitioners as well as pave the way for future research on domain adaptation in HAR.
    Imwut 2020.
     
  11. Duzil

    Duzil

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    Liang Z, Ploderer B. () “How does Fitbit measure brainwaves”: a PACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT).Sirithummarak P, Liang Z.
     
  12. Samusar

    Samusar

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    A pilot fNIRS study into stress-related cortical hemodynamic features during sleep.
     
  13. Shaktit

    Shaktit

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    Conferences Journals Workshops Seminars.
     
  14. Dukinos

    Dukinos

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    Except static official air quality stations, mobile sensing systems are deployed for urban air pollution monitoring to achieve larger sensing coverage and greater sampling granularity.
     
  15. Arashirisar

    Arashirisar

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    It achieves this performance through low power touch sensing and passive communication to a nearby smartphone using ambient FM backscatter.
     
  16. Zolozil

    Zolozil

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    Liang Z Engaging students in online virtual classroom using web application Sutori.
     
  17. Nagal

    Nagal

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    Investigating classroom activities in English conversation lessons based on activity coding and data visualization.
     
  18. Mazukasa

    Mazukasa

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    The modules are enabled for wireless communication and can be linked together using an Augmented Reality based programming interface running on a smartphone.
     
  19. Teshura

    Teshura

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    Finally, we address the future application space for this technology.
     
  20. Naktilar

    Naktilar

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    Previous studies on human mobility prediction have mainly focused on centralized human mobility prediction, where user mobility data are collected, trained and predicted at the cloud server side.
     
  21. Kajigul

    Kajigul

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    These require no internal power, can be placed at multiple locations along with a single fiber, and can be interrogated from the end of the fiber.
     
  22. Maujin

    Maujin

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    NeckSense fuses and classifies the proximity of the necklace from the chin, the ambient light, the Lean Forward Angle, and the energy signals to determine chewing sequences, a building block of the eating activity.
     
  23. Dijas

    Dijas

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    FluSense can accurately predict daily patient counts with a Pearson correlation coefficient of 0.
     
  24. JoJoshura

    JoJoshura

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    When a finger moves along a surface, the friction between them produces vibrations, which can not be produced with a free-moving finger in the air.
     
  25. Arami

    Arami

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    Experimental evaluations on real-world datasets show that our NeuroFire outperforms 9 baselines, demonstrating the performance of our approach by several visualizations.
     
  26. Samura

    Samura

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    We devise movement and cardiac features that could be extracted from research-grade wearable sensors and derive models and evaluate their performance in the largest open-access dataset for human sleep science.
     
  27. Vudal

    Vudal

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    Emerging technologies such as ambient backscatter help fill this gap by enabling uplink communication for IoT devices.
     
  28. Neshura

    Neshura

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    Even though millions of households have adopted and integrated these devices into their daily lives, we lack a deep understanding of how different members of a household use such devices.
     
  29. Brashakar

    Brashakar

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    Speed-volume relationship model for speed estimation on urban roads in intelligent transportation systems.
     
  30. Zolosida

    Zolosida

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    Thus, such user authentications are pressed to be implemented in a passphrase-independent manner while being able to resist various attacks.
     
  31. Nibei

    Nibei

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    By applying classical clustering methods on this multi-sensor data, we take a person-centered approach to describe workers in terms of both personality and activity.
     
  32. Moogugami

    Moogugami

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    forum? Our experimental results show that the overall median tracking accuracy is 1.
    Imwut 2020.
     
  33. Gutilar

    Gutilar

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    Volume 4, Issue 1, Article 2.
     
  34. Shakanris

    Shakanris

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    Further, we design an application, i.
     
  35. Megis

    Megis

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    Finally, we demonstrate that KEHKey can successfully defend against typical adversarial attacks.
     
  36. Mekus

    Mekus

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    It achieves this performance through low power touch sensing and passive communication to a nearby smartphone using ambient FM backscatter.
     
  37. Doshakar

    Doshakar

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    Mining wearable sleep data for detecting unusual sleep.
     
  38. Tolar

    Tolar

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    To our knowledge, this is the first work studying cellular data usage prediction from an individual user behavior-aware perspective based on large-scale cellular signaling and behavior tags from the subscription data.
     
  39. Gardazil

    Gardazil

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    Our tests show that with suitable materials these sensors can detect and classify both direct interactions such as tapping and more subtle vibrations caused by activities such as walking across the floor nearby.
     
  40. Mokazahn

    Mokazahn

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    Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.
    Imwut 2020.
     
  41. Daikinos

    Daikinos

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    Our approach aims to protect the smart speakers from remote attackers that leverage network-connected speakers to send malicious commands.
     
  42. Yonos

    Yonos

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    The descriptive model enables us to objectively evaluate user drawings and represent the course of the drawings by a defined set of parameters.
     
  43. Zulkree

    Zulkree

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    In this work, we propose a method that enables L2 learners to study new vocabulary items during their dead time, such as when commuting to school or work.
     
  44. Faezuru

    Faezuru

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    This mechanism is capable of utilizing information collected from higher layers of the neural network to selectively amplify the influence of informative features and suppress unrelated noise at the fusion layer.
     
  45. JoJole

    JoJole

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    With more than
     
  46. Kenris

    Kenris

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    The proposed VocalLock can resist various spoofing attacks, while achieving a satisfactory user experience.
     

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