Powerful Mobile Devices Research Articles

The inter-rater reliability of the Powered Mobility Device Assessment Training Tool.

The prescription of powered mobility devices for clients is an important role for occupational therapists. However, the skill of may powered mobility device users to drive their devices remains unknown and clients are provided with only brief education on their use. Few assessments exist to guide mobility device use assessment, and none of these incorporate the training clients need. The aim of this paper was to investigate the inter-rater reliability of a new assessment and training tool called the Powered Mobility Device Assessment Training Tool (PoMoDATT). The PoMoDATT comprises an initial interview and then Part A- cognitive skills, Part B physical and psychosocial skills and Part C driving skills and behaviours. The assessment outcome is a profile of the client's physical, cognitive and psychosocial skills related to powered mobility device use. The driving assessments of 24 powered mobility device users were video-recorded, and four experienced occupational therapists scored the clients on the 26 items of Part C of the PoMoDATT. Following clarification of three items which included re-scoring and data re-analysis, the inter-rater reliability for the PoMoDATT Part C items ranged from ICC (2, 1) 0.641 to 0.938 suggesting moderate to excellent agreement. The PoMoDATT Part C has demonstrated adequate inter-rater reliability to support its use by occupational therapists to assess powered mobility device user's capacities and abilities and to highlight ongoing training needs.

Lifelong learning as integrational resource of knowledge economy

The paper examines the meaning and the main features of the knowledge economy. It also analyses present-day challenges for the knowledge economy under new economic conditions. Research indicates arguments justifying the thesis that knowledge is a specific resource, which, unlike all other economic resources, can be unlimited under the condition of the continuous nature of education. Modern problems of market economy require deep rethinking and effective use of the characteristics of the knowledge economy for building new market relationships. Current economic problems will be successfully solved if one carefully considers the features of the Knowledge economy. The expanding Internet, ever more powerful mobile devices, and other innovations make the task of designing effective formal and informal learning challenging, especially in light of the high rate of change in these new technologies.

Mobile Cloud Support for Semantic-Enriched Speech Recognition in Social Care

Nowadays, most users carry high computing power mobile devices where speech recognition is certainly one of the main technologies available in every modern smartphone, although battery draining and application performance (resource shortage) have a big impact on the experienced quality. Shifting applications and services to the cloud may help to improve mobile user satisfaction as demonstrated by several ongoing efforts in the mobile cloud area. However, the quality of speech recognition is still not sufficient in many complex cases to replace the common hand written text, especially when prompt reaction to short-term provisioning requests is required. To address the new scenario, this paper proposes a mobile cloud infrastructure to support the extraction of semantics information from speech recognition in the Social Care domain, where carers have to speak about their patients conditions in order to have reliable notes used afterward to plan the best support. We present not only an architecture proposal, but also a real prototype that we have deployed and thoroughly assessed with different queries, accents, and in presence of load peaks, in our experimental mobile cloud Platform as a Service (PaaS) testbed based on Cloud Foundry.

AI for Network Traffic Control

The fourteen articles in this special section present high-quality unpublished work regarding the latest advances in the area of AI-inspired network traffic control. Network traffic control is a key enabler for network systems as it helps achieve significant information delivery efficiency as well as resource utilization through monitoring, inspecting, and regulating data flows. In light of evolving IoT technology and the coming of the beyond fifth generation (5G) era, powerful smart mobile devices and ubiquitous ultra-dense radio networks have greatly enlarged network scale while bringing explosive amounts of data traffic, which impose considerable pressure on the management of the Internet. Moreover, the advances in central cloud and smart edge services have substantially changed the traffic flow models and the service architecture of the Internet. New technologies are thus required to handle traffic control in a highly scalable and adaptive mode.

A distributed fuzzy system for dangerous events real-time alerting

In recent years, several dangerous events (such as terrorism, violent crimes, explosions) happened across the globe. In some cases, some events simultaneously occurred in different places in the same city. The primary method used for alerting authorities in these situations is the phone call of people that are near the location of the event. Commonly, in such case, people get excited phone calls that make complicated the work of the operator that needs to understand relevant information such as the location of the event, the number of individuals that are involved and so on. Moreover may also happen that scared or injured people are not able to communicate. But in these cases, rapid responses are fundamental to save human lives and to stop the criminal action. The pervasive use of powerful mobile devices embedding several kinds of sensors and providing great computational capabilities gives the technological support for developing more complex applications. In this paper, we propose a distributed fuzzy system that can infer in real-time critical situations by analysing data gathered from user’s smart-phones about the environment and the individual.

Privacy-aware task data management using TPR*-Tree for trajectory-based crowdsourcing

Spatial crowdsourcing is a promising architecture for collecting various types of data online with the aid of participants’ powerful mobile devices. However, it is also associated with certain privacy and security issues, which can reduce the quality of the crowdsourcing service. Some crowd tasks require the collection of connected data points. When a location-anonymous method is employed to ensure the privacy of location data points, the location trajectory data may become meaningless. To solve the privacy problem for trajectory data in large-scale crowdsourcing systems, we proposed a spatial task management method for privacy-preserving trajectory-based crowdsourcing, using a 3DES encryption and compressive-sensing-based trajectory data decryption method which is called DES-TraVec (3DES-based trajectory vector) cryptography algorithm. To provide a real-time crowdsourcing service, we proposed the use of an extended TPR*-Tree to bulk load the crowdsourcing results and manage the benders service requests so that the proposed method could support participants’ privacy and ensure quick answers for crowdsourcing services. The experimental results demonstrated that the proposed method is efficient in preserving trajectory-based crowdsourcing data and is faster than the current method.

Power mobility for children: a survey study of American and Canadian therapists' perspectives and practices.

To explore the views and practices of paediatric occupational therapists and physical therapists in Canada and the USA regarding the implementation of power mobility for children with mobility limitations. This descriptive study utilized a web-based survey that included questions pertaining to therapists' decisions to trial and use power mobility, agreement or disagreement with statements developed from published practice considerations regarding power mobility, and the frequency of performing tasks related to power mobility prescription and training. Most respondents reported that child characteristics (e.g. cognition, safety awareness) were important factors in decision-making about power mobility, whereas other child characteristics (e.g. communication abilities, age) were not as important. Family resources and home accessibility were also not considered important. The average age at which respondents considered power mobility for children was 2years 3months. The majority of respondents agreed with statements developed from published practice considerations and most frequently performed various power mobility tasks twice a year or less. Although most respondents appeared to have positive views regarding power mobility, few appeared to actively perform power mobility tasks in their practice. Resources to support therapists in the early introduction of power mobility may be beneficial. Occupational and physical therapists positively view early introduction of power mobility for children with mobility limitations. Few therapists actively provide early power mobility experiences. Power mobility training and monitoring power mobility devices are important therapist roles.

'Power in Mobility': parent and therapist perspectives of the experiences of children learning to use powered mobility.

The aim of this study was to gain insights, from the perspectives of both parents and pediatric therapists, into the experiences of children learning to use a power mobility device. The purposive sample included 33 participants: 14 parents of children who were learning, or had learned, to use a power mobility device and 19 pediatric occupational therapists or physical therapists. Data were gathered face-to-face via seven focus groups consisting of either parents or therapists, and eight one-on-one interviews. Data were analyzed using the constant comparative method. Three main themes were identified: (1) 'Power in mobility' described how learning to use powered mobility changed more than just a child's locomotor abilities; (2) 'There is no recipe' revealed how learning to use powered mobility occurred along an individualized continuum of skills that often unfolded over time in a cyclical process; (3) 'Emotional journey' explored how learning to use powered mobility was an emotionally charged undertaking for all those involved. Learning to use a power mobility device is a complex process that often requires perseverance and determination on the part of the child, family, and therapist. Powered mobility use impacts more than just a child's locomotor abilities. Learning to use a power mobility device is a highly individualized process. Learning to use powered mobility may be an emotionally charged process.

Stabilization of Nickel-Rich Layered Cathode Materials of High Energy Density by Ca Doping

Lithium-ion batteries have been considered the most important devices to power mobile or small-sized devices due to their high energy density. LixCoO2 has been studied as a cathode material for the Li-ion battery. However, the limitation of its capacity impedes the development of high capacity cathode materials with Ni, Mn, etc. in them. The substitution of Mn and Ni for Co leads to the formation of solid solution phase LiNixMnyCo1-x-yO2 (NMC, both x and y 0.8 in the metal site), poor cycle retention capability still remains to be overcome. In this study, aiming to improve the stability of the physical and chemical bonding, we investigate the stabilization effect of Ca in the Ni-rich layered compound Li(Ni0.83Co0.12Mn0.05)O2, and then Ca is added to the modified secondary particles to lower the degree of cationic mixing of the final particles. For the optimization of the final grains added with Ca, the Ca content (x = 0, 2.5, 5.0, 10.0 at.%) versus Li is analyzed.

Modified Ride-On Cars and Young Children with Disabilities: Effects of Combining Mobility and Social Training.

Research has shown that the use of power mobility devices is safe and beneficial for motor and cognitive development in children with motor disabilities; nevertheless, strong evidence of the benefits for social skill development is limited. This study aimed to examine the effects of combining ride-on car training with an adult-directed, social interaction program in a hospital-based environment on mobility and social functions in young children with motor disabilities. This study used a prospective, nonequivalent pretest-posttest control group design. Twenty-nine young children with motor disabilities, aged between 1 and 3 years, were recruited from local hospitals in Taiwan. The treatment group (n = 15) underwent 2-h ride-on car training sessions twice per week for a total of 9 weeks in the hospital environment. The control group (n = 14) underwent a 9-week home education program (mean: 200 min/week) focusing on mobility and social skills training. The Chinese version of the Pediatric Evaluation of Disability Inventory, Parenting Stress Index, and Goal Attainment Scaling were administered to all participants before and after the intervention, and at the end of the 9-week follow-up phase. Mobility and social functions significantly improved in both groups after the 9-week intervention, but this improvement was not maintained at the follow-up phase. The treatment group showed significantly better improvement in social function, parenting stress levels, and goal achievement than the control group at posttest. This two-group design study showed the benefits of combining a ride-on car use with a family-centered, structured, social interaction program for positive impacts on mobility, social function, and parenting stress levels. The combination of a modified ride-on car and a social training program has the potential to enhance socialization in young children with motor disabilities. www.ClinicalTrials.gov, identifier NCT02527499.

6DoF Object Tracking based on 3D Scans for Augmented Reality Remote Live Support

Tracking the 6DoF pose of arbitrary 3D objects is a fundamental topic in Augmented Reality (AR) research, having received a large amount of interest in the last decades. The necessity of accurate and computationally efficient object tracking is evident for a broad base of today’s AR applications. In this work we present a fully comprehensive pipeline for 6DoF Object Tracking based on 3D scans of objects, covering object registration, initialization and frame to frame tracking, implemented to optimize the user experience and to perform well in all typical challenging conditions such as fast motion, occlusions and illumination changes. Furthermore, we present the deployment of our tracking system in a Remote Live Support AR application with 3D object-aware registration of annotations and remote execution for delay and performance optimization. Experimental results demonstrate the tracking quality, real-time capability and the advantages of remote execution for computationally less powerful mobile devices.

Investigation of Next Generation Internet Protocol Mobility-Assisted Solutions for Low Power and Lossy Networks

With the phenomenal increase of computing devices, especially the low powered mobile devices created many new requirements for traditional networking protocols and standards. The IPv6 was introduced as the solution for addressing requirements but still, some major issues persist due to the limitations of computing devices such as power related limitations, the challenge in the deployment environments and restrictions allied to computing and memory capacity. Many new standards were proposed such as the IPv6 over Low-Power Wireless Personal Area Networks (6LoWPAN), the IPv6 routing protocol for Low Power and Lossy Networks (RPL) to meet the challenges. Even though RPL greatly satisfies the requirements for low-powered networks, quite a few issues remain open for enhancement, especially with respect to mobility support. This present paper examines next-generation internet protocol mobility schemes for the RPL and 6LoWPAN and analyzes how the proposed variants satisfy the necessities for low power and lossy networks.

Power Mobility Training Methods for Children: A Systematic Review.

To summarize and critically appraise the existing evidence related to power mobility training methods used in research studies conducted with children 21 years or younger. A systematic review was conducted using 16 electronic databases to identify primary source quantitative studies published in peer-reviewed journals. Data extraction, determination of level of evidence, evaluation of methodological rigor, and assessment of the risk of bias were completed. The Evidence Alert Traffic Light Grading System (EATLS) was used. Twenty-seven studies were included in the review. Levels of evidence were II to V; scientific rigor scores were 2 to 7. An overall Yellow EATLS level of evidence was found indicating that therapists should use caution when providing power mobility training interventions and measure outcomes related to established goals in areas such as development, functional skills, or use of a power mobility device.

Energy Efficient Congestion Control for Multipath TCP in Heterogeneous Networks

In this paper, we propose a receiver energy efficient congestion control algorithm based on multipath transmission control protocol (MPTCP) to enable the battery powered mobile devices receive more data than MPTCP with the same energy consumption. First, based on the receiver energy consumption model of wireless interface, a constrained optimization problem to maximize energy efficiency is formed. With genetic algorithm, a rate distribution vector is obtained as a near-optimal solution. Second, we adjust the congestion windows based on the acquired vector to schedule packets over each path directly. Jointly considering energy efficiency, round trip time and path loss rate, a novel congestion control algorithm is proposed to adjust the increment of congestion window when an acknowledgement is received in the congestion avoidance phase. The energy efficiency term is obtained by extending the energy efficient rate distribution vector into the window-based congestion control algorithm via fluid model. The simulation results demonstrate that the proposed algorithm shifts part of traffic from the higher energy consumption paths to the lower ones. It improves throughput greatly and achieves higher energy efficiency, almost twice the size of MPTCP.

Spatial task management method for location privacy aware crowdsourcing

Spatial crowdsourcing is a promising architecture that collects various types of data online with the help of participants powerful mobile devices. Humans are involved in the crowdsourcing process, thereby increasing its accuracy; however, it is also associated with some privacy and security problems. The crowd tasks are executed in participants mobile devices, and the results are send to the server through networks, so that attackers could eavesdrop participants location information. Thus, we studied and proposed a spatial task assignment method for privacy-aware spatial crowdsourcing using a secure grid-based index. The secure grid index used an encrypted grid number and grid cell-based local coordinate system to protect participants location privacy. By using the grid based index in spatial task management process, it also could increase the spatial task processing time. In the experimental test, we showed that the proposed method is faster than the current method and extremely efficient when the spatial crowdsourcing tasks are geometry based tasks.

Feasibility of a Modified Ride-on Car Intervention on Play Behaviors during an Inclusive Playgroup

ABSTRACTAims: Children with mobility related disabilities often experience limited participation and access to social interactions. An emerging pediatric powered mobility device are modified ride-on cars that provide self-directed mobility experiences to children with disabilities. This study aimed to determine: (1) the feasibility of a modified ride-on car intervention during an inclusive playgroup, (2) the effect of a modified ride-on car intervention on the play behaviors of children with and without mobility related disabilities. Method: A single-subject research design was implemented. Thirteen children participated in a weekly inclusive playgroup. The five children with mobility related disabilities were provided modified ride-on cars during the intervention. Children's play behaviors were classified with Howes' Peer Play Scale. Intervention effects were examined using nonoverlap of all pairs (NAP). Results: The intervention was feasible based on participants' good attendance, retention rates, and successful use of modified ride-on cars. Overall children did not experience significant changes in play behaviors, with a few exceptions for decreased solitary, and increased parallel play, and/or direct peer interaction, among children with mobility related disabilities. Future research could examine modified ride-on car use by children with mobility related disabilities focusing on changes in unique play interactions between children with and without disabilities.

EDAWS: A distributed framework with efficient data analytics workspace towards discriminative services for critical infrastructures

Critical infrastructure systems which are interrelated with people’s daily life perform functions in multiple domains. However, with the explosion of specialized textual information in such systems, providing discriminative services for users through potential knowledge discovery becomes an essential and technical concern. Once massive data analytics is conducted in standalone server, the performance will degenerate tremendously. Alternatively, people cannot conveniently get such discriminative (self-caring) services. To address these concerns, we propose the general solution of EDAWS: a Novel Distributed Framework with Efficient Data Analytics Workspace towards Discriminative Service for Critical Infrastructures, through leveraging the state-of-the-art software technologies and computing paradigms. We argue it from the following aspects: Firstly, the server-side platform facilitates native data capture, storage, index and data mining with a systematic organization. Secondly, a text-mining approach with index building in parallel is conducted for various functional business, by exploiting the potential of Lucene-based distributed cluster. Thirdly, with the widespread usage of tiny but powerful mobile devices, the server-side platform could be accessed by mobile-side clients remotely in a more convenient way. To demonstrate our solution, a case study of smart residence prototype towards discriminative services in terms of information retrieval, personalized information push, and hot topic discovery is thoroughly discussed. The extensively experimental studies are conducted for the prototype over various real-world datasets. Experimental results indicate that, data processing which runs on computing nodes has good scalability with data sizes and computing nodes, and the prototype passes from data to discriminative services successfully.

Crowdsensing Multimedia Data: Security and Privacy Issues

Recent smartphones are equipped with various sensors, such as an accelerometer, GPS, and a gravity sensor, and have high-performance wireless communication capabilities. Through the ubiquitous presence of powerful mobile devices, crowdsensing lets ordinary people collectively gather and share real-time multimedia data. Multimedia crowdsensing has made large-scale participatory sensing viable in a speedy and cost-efficient manner, but it also introduces some security and privacy concerns. Personally identifiable information of participants can be exposed while sharing individually owned sensor data. This article identifies security and privacy issues in multimedia crowdsensing and describes existing solutions that are designed to protect both data producers and consumers in multimedia crowdsensing. This article is part of a special issue on cybersecurity.

Mobile Live Video Streaming Optimization via Crowdsourcing Brokerage

Nowadays, people can enjoy a rich real-time sensing cognition of what they are interested in anytime and anywhere by leveraging powerful mobile devices such as smartphones. As a key support for the propagation of these richer live media contents, cellular-based access technologies play a vital role to provide reliable and ubiquitous Internet access to mobile devices. However, these limited wireless network channel conditions vary and fluctuate depending on weather, building shields, congestion, etc., which degrade the quality of live video streaming dramatically. To address this challenge, we propose to use crowdsourcing brokerage in future networks which can improve each mobile user's bandwidth condition and reduce the fluctuation of network condition. Further, to serve mobile users better in this crowdsourcing style, we study the brokerage scheduling problem which aims at maximizing the user's quality of experience satisfaction degree cost effectively. Both offline and online algorithms are proposed to solve this problem. The results of extensive evaluations demonstrate that by leveraging crowdsourcing technique, our solution can cost-effectively guarantee a higher quality view experience.

Environmental barriers to participation and facilitators for use of three types of assistive technology devices

ABSTRACTThe aim was to compare the presence of environmental barriers to participation and facilitators for assistive technology (AT) use and study the relation between barriers and AT use in three different AT devices. A cross-sectional survey was conducted. Inclusion criteria were ≥one year of experience as a user of myoelectric prosthesis (MEP), powered mobility device (PMD), or assistive technology for cognition (ATC) and age 20-90 years. Overall, 156 participants answered the Swedish version of the Craig Hospital Inventory of Environmental Factors and a study-specific questionnaire on facilitating factors. Non-parametric tests were used for comparisons. Barriers to participation were lowest in MEP users (md=0.12; p>0.001), and highest in ATC users (md=1.56; p>0.001) with the least support for AT use (p>0.001 - p=0.048). A positive correlation between fewer barriers and higher use of MEP was seen (r=0.30, p=0.038). The greatest barriers to participation were Natural environment, Surroundings and Information, and the most support came from relatives and professionals. Support, training and education are vital in the use of AT. These factors may lead to a more sustained and prolonged use of AT and may enable increased participation. Future research should focus on interventions that meet the needs of people with cognitive disabilities.