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  • Distributed fine-tuning of CNNs for image retrieval on multiple mobile devices
    Pervasive Mob. Comput. (IF 2.769) Pub Date : 2020-03-09
    Gwangseon Jang; Jin-woo Lee; Jae-Gil Lee; Yunxin Liu

    The high performance of mobile devices has enabled deep learning to be extended to also exploit its strengths on such devices. However, because their computing power is not yet sufficient to perform on-device training, a pre-trained model is usually downloaded to mobile devices, and only inference is performed on them. This situation leads to the problem that accuracy may be degraded if the characteristics

    更新日期:2020-03-20
  • From seen to unseen: Designing keyboard-less interfaces for text entry on the constrained screen real estate of Augmented Reality headsets
    Pervasive Mob. Comput. (IF 2.769) Pub Date : 2020-03-19
    Lik Hang Lee; Tristan Braud; Kit Yung Lam; Yui Pan Yau; Pan Hui

    Text input is a very challenging task in the constrained screen real-estate of Augmented Reality headsets. Typical keyboards spread over multiple lines and occupy a significant portion of the screen. In this article, we explore the feasibility of single-line text entry systems for smartglasses. We first design FITE, a dynamic keyboard where the characters are positioned depending on their probability

    更新日期:2020-03-20
  • Unsupervised domain adaptation for activity recognition across heterogeneous datasets
    Pervasive Mob. Comput. (IF 2.769) Pub Date : 2020-03-14
    Andrea Rosales Sanabria; Juan Ye

    Sensor-based human activity recognition is to recognise human daily activities through a collection of ambient and wearable sensors. It is the key enabler for many healthcare applications, especially in ambient assisted living. The advance of sensing and communication technologies has driven the deployment of sensors in many residential and care home settings. However, the challenge still resides in

    更新日期:2020-03-20
  • Online distributed distance-based outlier clearance approaches for wireless sensor networks
    Pervasive Mob. Comput. (IF 2.769) Pub Date : 2020-02-20
    Tianwei Dai; Zhengtao Ding

    One key challenge for sensor networks is to provide the real-time high reliable sensor measurements with the minimum resource consumption. Outlier clearance in sensor networks can ensure the quality of sensor measurements and dependable monitoring. In this paper, we propose two online distributed outlier clearance approaches with low computational complexity and memory usage that can identify and remove

    更新日期:2020-03-07
  • Model checking smart contracts for Ethereum
    Pervasive Mob. Comput. (IF 2.769) Pub Date : 2020-02-13
    Thomas Osterland; Thomas Rose

    One important promise of the blockchain technology is the concept of smart contracts. They offer means for the secure execution of procedures that no entity can manipulate. This enables applications like the automation of business processes, i.e. entire business relationships in peer-to-peer collaborations can be automated securely. While the blockchain guarantees proper execution it assures the correctness

    更新日期:2020-03-07
  • Privacy and utility preserving sensor-data transformations
    Pervasive Mob. Comput. (IF 2.769) Pub Date : 2020-03-02
    Mohammad Malekzadeh; Richard G. Clegg; Andrea Cavallaro; Hamed Haddadi

    Sensitive inferences and user re-identification are major threats to privacy when raw sensor data from wearable or portable devices are shared with cloud-assisted applications. To mitigate these threats, we propose mechanisms to transform sensor data before sharing them with applications running on users’ devices. These transformations aim at eliminating patterns that can be used for user re-identification

    更新日期:2020-03-07
  • Overcoming 5G ultra-density with game theory: Alpha-beta pruning aided conflict detection
    Pervasive Mob. Comput. (IF 2.769) Pub Date : 2020-03-01
    Tuğçe Bilen; Berk Canberk

    The capacity and coverage needs of 5G NR (New Radio) networks are satisfied by deploying a high number of small cells in the coverage area of a macro cell. In 5G Dual Connectivity (DC), these small cells are represented as eNBs with 4G characteristics different from the macro cells which are the 5G NR gNBs. The mobile node (MN) can establish a connection with these cells in different technologies at

    更新日期:2020-03-07
  • Forecasting Occurrences of Activities.
    Pervasive Mob. Comput. (IF 2.769) Pub Date : 2017-07-12
    Bryan Minor,Diane J Cook

    While activity recognition has been shown to be valuable for pervasive computing applications, less work has focused on techniques for forecasting the future occurrence of activities. We present an activity forecasting method to predict the time that will elapse until a target activity occurs. This method generates an activity forecast using a regression tree classifier and offers an advantage over

    更新日期:2019-11-01
  • Modeling Patterns of Activities using Activity Curves.
    Pervasive Mob. Comput. (IF 2.769) Pub Date : 2016-06-28
    Prafulla N Dawadi,Diane J Cook,Maureen Schmitter-Edgecombe

    Pervasive computing offers an unprecedented opportunity to unobtrusively monitor behavior and use the large amount of collected data to perform analysis of activity-based behavioral patterns. In this paper, we introduce the notion of an activity curve, which represents an abstraction of an individual's normal daily routine based on automatically-recognized activities. We propose methods to detect changes

    更新日期:2019-11-01
  • Improving Biomedical Signal Search Results in Big Data Case-Based Reasoning Environments.
    Pervasive Mob. Comput. (IF 2.769) Pub Date : 2016-06-14
    Jonathan Woodbridge,Bobak Mortazavi,Alex A T Bui,Majid Sarrafzadeh

    Time series subsequence matching has importance in a variety of areas in healthcare informatics. These include case-based diagnosis and treatment as well as discovery of trends among patients. However, few medical systems employ subsequence matching due to high computational and memory complexities. This manuscript proposes a randomized Monte Carlo sampling method to broaden search criteria with minimal

    更新日期:2019-11-01
  • Accelerometry-based Recognition of the Placement Sites of a Wearable Sensor.
    Pervasive Mob. Comput. (IF 2.769) Pub Date : 2015-07-28
    Andrea Mannini,Angelo M Sabatini,Stephen S Intille

    This work describes an automatic method to recognize the position of an accelerometer worn on five different parts of the body: ankle, thigh, hip, arm and wrist from raw accelerometer data. Automatic detection of body position of a wearable sensor would enable systems that allow users to wear sensors flexibly on different body parts or permit systems that need to automatically verify sensor placement

    更新日期:2019-11-01
  • Activity Recognition on Streaming Sensor Data.
    Pervasive Mob. Comput. (IF 2.769) Pub Date : 2014-04-15
    Narayanan C Krishnan,Diane J Cook

    Many real-world applications that focus on addressing needs of a human, require information about the activities being performed by the human in real-time. While advances in pervasive computing have lead to the development of wireless and non-intrusive sensors that can capture the necessary activity information, current activity recognition approaches have so far experimented on either a scripted or

    更新日期:2019-11-01
  • Accelerometer-based on-body sensor localization for health and medical monitoring applications.
    Pervasive Mob. Comput. (IF 2.769) Pub Date : 2012-02-22
    Alireza Vahdatpour,Navid Amini,Wenyao Xu,Majid Sarrafzadeh

    In this paper, we present a technique to recognize the position of sensors on the human body. Automatic on-body device localization ensures correctness and accuracy of measurements in health and medical monitoring systems. In addition, it provides opportunities to improve the performance and usability of ubiquitous devices. Our technique uses accelerometers to capture motion data to estimate the location

    更新日期:2019-11-01
  • Context Awareness in a Handheld Exercise Agent.
    Pervasive Mob. Comput. (IF 2.769) Pub Date : 2010-02-18
    Timothy W Bickmore,Daniel Mauer,Thomas Brown

    Work towards the development of a handheld health counseling agent designed to promote physical activity is described. Previous work on automated health counselors is discussed, along with the affordances of mobility and context awareness for health behavior interventions. We present a general-purpose software architecture for the rapid design and deployment of mobile health counseling agents. We also

    更新日期:2019-11-01
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