Search Results for « Mobile device proficiency »

The ever increasing demands for using resource-constrained mobile devices for running more resource intensive applications nowadays has initiated the development of cyber foraging solutions that offload parts or whole computational intensive tasks to more powerful surrogate stationary computers and run them on behalf of mobile devices as required. The choice of proper mix of mobile devices and surrogates has remained an unresolved challenge though. In this paper, we propose a new decision-making mechanism for cyber foraging systems to select the best locations to run an application, based on context metrics such as the specifications of surrogates, the specifications of mobile devices, application specification, and communication network specification. Experimental results show faster response time and lower energy consumption of benched applications compared to when applications run wholly on mobile devices and when applications are offloaded to surrogates blindly for execution.

Mobile device proficiency is increasingly required to participate in society. Unfortunately, there still exists a digital divide between younger and older adults, especially with respect to mobile devices (i.e., tablet computers and smartphones). Training is an important goal to ensure that older adults can reap the benefits of these devices. However, efficient/effective training depends on the ability to gauge current proficiency levels. We developed a new scale to accurately assess the mobile device proficiency of older adults: the Mobile Device Proficiency Questionnaire (MDPQ). We present and validate the MDPQ and a short 16-question version of the MDPQ (MDPQ-16). The MDPQ, its subscales, and the MDPQ-16 were found to be highly reliable and valid measures of mobile device proficiency in a large sample. We conclude that the MDPQ and MDPQ-16 may serve as useful tools for facilitating mobile device training of older adults and measuring mobile device proficiency for research purposes.

Distributing the inference of convolutional neural network (CNN) to multiple mobile devices has been studied in recent years to achieve real-time inference without losing accuracy. However, how to map CNN to devices remains a challenge. On the one hand, scheduling the workload of state-of-the-art CNNs with multiple devices is NP-Hard because the structures of CNNs are directed acyclic graphs (DAG) rather than simple chains. On the other hand, distributing the inference workload suffers from expensive communication and unbalanced computation due to the wireless environment and heterogeneous devices. This paper presents PICO, a pipeline cooperation framework to accelerate the inference of versatile CNNs on diverse mobile devices. At its core, PICO features: (1) a generic graph partition algorithm that considers the characteristics of any given CNN and orchestrates it into a list of model pieces with suitable granularity, and (2) a many-to-many mapping algorithm that produces the best pipeline configuration for heterogeneous devices. In our experiment with 2 ~ 8 Raspberry-Pi devices, the throughput can be improved by 1.8 ~ 6.8x under different CPU frequencies.

• Developed and validated two shortened Japanese MDPQ versions using item response theory. • MDPQ-J14 and MDPQ-J20OA provide efficient, age-appropriate assessment of device proficiency. • Shortened tools reduce respondent burden while maintaining reliability and validity. • Cultural adaptation led to exclusion of less relevant subcategories for Japanese users. Mobile devices enhance the independence and quality of life of older adults by supporting communication, information access, and daily functioning. However, many older individuals struggle to effectively use such technologies. Accurate assessment of mobile device proficiency is essential for tailoring support and promoting digital inclusion in the aging population. Although the Japanese version of the Mobile Device Proficiency Questionnaire (MDPQ-J) has demonstrated strong validity, its 46-item format imposes a burden on respondents and limits its utility in field settings. This study aimed to develop and validate shortened versions of the MDPQ-J using item response theory to provide efficient and psychometrically sound tools for assessing mobile device proficiency in older Japanese adults. A total of 229 Japanese participants, including 108 older adults (aged >65years), completed the full 46-item MDPQ-J. Rasch analysis and item response theory were applied to evaluate dimensionality, item fit, and local independence. A reduction in the number of items in the MDPQ-J was appropriate, and two shortened versions were developed: MDPQ-J14 for the general population and MDPQ-J20OA for older adults. Items were selected based on model fit, local independence, and discrimination parameters. In MDPQ-J14, “Use video-messaging apps” showed the highest discrimination, whereas in MDPQ-J20OA, “Copy and paste text using the touchscreen” demonstrated the strongest item discrimination. The MDPQ-J14 and MDPQ-J20OA are efficient, valid, and culturally appropriate tools for assessing mobile device proficiency. Their brevity and flexibility make them suitable for wide application in research, education, and gerontechnology interventions in aging societies.

The ARMrayan Multimedia Mobile CMS (Content Management System) is the first mobile CMS that gives the opportunity to users for creating multimedia J2ME mobile applications with their desired content, design and logo; simply, without any need for writing even a line of code. The low-level programming and compatibility problems of the J2ME, along with UI designing difficulties, makes it hard for most people -even programmers- to broadcast their content to the widespread mobile phones used by nearly all people. This system provides user-friendly, PC-based tools for creating a tree index of pages and inserting multiple multimedia contents (e.g. sound, video and picture) in each page for creating a J2ME mobile application. The output is a stand-alone Java mobile application that has a user interface, shows texts and pictures and plays music and videos regardless of the type of devices used as long as the devices support the J2ME platform. Bitmap fonts have also been used thus Middle Eastern languages can be easily supported on all mobile phone devices. We omitted programming concepts for users in order to simplify multimedia content-oriented mobile application designing for use in educational, cultural or marketing centers. Ordinary operators can now create a variety of multimedia mobile applications such as tutorials, catalogues, books, and guides in minutes rather than months. Simplicity and power has been the goal of this CMS. In this paper, we present the software engineered-designed concepts of the ARMrayan MCMS along with the implementation challenges faces and solutions adapted.

Technology can help support the goal of many older adults to live independently, though cognitive, attitudinal, and other barriers often result in a "digital divide" in which older adults use and adopt new technology at a lower rate compared to younger adults. Due to the many potential benefits of technology it is not surprising that interest in tools that assess technology proficiency among older adults has increased. These tools can help support older adult technology research and training. However, to understand these issues more broadly, especially cross-cultural determinants of technology proficiency, translated, validated, and standardized measures of proficiency are necessary. For example, according to the last Eurobarometer (European Commission, 2015), Spain has experienced the largest increase in technology adoption among European Union nations in the past few years, indicating potential cultural mediation of technology adoption and use. To benefit the investigation of cross-cultural differences and their causes, we adapted the Mobile Device Proficiency Questionnaire (MDPQ) and Computer Proficiency Questionnaire (CPQ) for older adults in Spain, including the full and brief forms of each measure. Consistent with English versions of the questionnaires, the scales and their subscales were found to be reliable and valid measures of mobile device and computer proficiency in Spanish older adults. However, in contrast to earlier studies, the factor structure for both questionnaires simplified into two factors for the population under study. We conclude that the Spanish versions of the MDPQ and CPQ can be employed as useful tools for measuring mobile device and computer proficiency in the Spanish older adult population for research and training purposes.

ARM TrustZone is widely deployed on commercial-off-the-shelf mobile devices for secure execution. However, many Apps cannot enjoy this feature because it brings many constraints to App developers. Previous works have been proposed to build a secure execution environment for developers on top of TrustZone. Unfortunately, these works are still not fully-fledged solutions for mobile Apps, especially for emerging intelligent Apps. To this end, we propose LEAP, which is a lightweight developer-friendly TEE solution for mobile Apps. LEAP enables isolated codes to execute in parallel and access peripheral (e.g., mobile GPUs) with ease, flexibly manages system resources upon different workloads, and offers the auto DevOps tool to help developers prepare the codes running on it. We implement the LEAP prototype on the off-the-shelf ARM platform and conduct extensive experiments on it. The experimental results show that Apps can be adapted to run with LEAP easily and efficiently. Compared to the state-of-the-art work along this research line, LEAP can achieve an average 3.57x speedup in supporting intelligent Apps using mobile GPU acceleration.

This study investigated key factors affecting mobile device proficiency and usage patterns among community-dwelling older adults with chronic diseases. Cross-sectional data from 164 older adults in a hypertension management program were utilized. Mobile device proficiency was measured using the Mobile Device Proficiency Questionnaire. Age, education, and food insecurity were negatively associated with the mobile device proficiency score, whereas self-rated health showed a significantly positive association. Mobile device proficiency varied across subscales, highlighting distinct usage patterns. While most participants reported being proficient in basic device navigation and internet use, fewer than 30 % indicated proficiency in data management. Older adults demonstrated varying levels of mobile device proficiency, with significant gaps in advanced functions like data management. These findings emphasize the need for early digital exposure, literacy-appropriate educational resources, and tailored support for older adults to promote health management and well-being. Healthcare policies should allocate resources to community-based initiatives addressing digital access gaps.

This report presents the CuriosAI team's submission to the EgoExo4D Proficiency Estimation Challenge at CVPR 2025. We propose two methods for multi-view skill assessment: (1) a multi-task learning framework using Sapiens-2B that jointly predicts proficiency and scenario labels (43.6 % accuracy), and (2) a two-stage pipeline combining zero-shot scenario recognition with view-specific VideoMAE classifiers (47.8 % accuracy). The superior performance of the two-stage approach demonstrates the effectiveness of scenario-conditioned modeling for proficiency estimation.

Mobile device proficiency is critical for older adults’ well-being, independence, and social connectivity. The Mobile Device Proficiency Questionnaire (MDPQ) is widely used but shows factor structure inconsistencies across cultures, and no validated Chinese version existed despite China’s unique digital ecosystem. This study translated and psychometrically validated the MDPQ for Chinese older adults. The MDPQ was translated and evaluated with 792 Chinese older adults (mean age = 67.08 years; 70.6% female) using a multi-method approach combining Classical Test Theory (exploratory factor analysis, confirmatory factor analysis, and Exploratory Structural Equation Modeling) and Rasch analysis. The Chinese MDPQ revealed a culturally relevant three-factor structure comprising 31 items: Basic Operations, Email Management, and Advanced Functions. Rasch analysis identified monotonicity violations in the original five-point response scale, leading to a collapsing of response categories from five to three points to improve measurement precision. Adequate external validity was demonstrated through medium to large correlations with frequency of internet use and eHealth literacy. The adapted Chinese MDPQ demonstrated satisfactory psychometric properties, supporting its use for assessing mobile device proficiency among Chinese older adults. The findings suggest that adapting mobile device proficiency measures requires careful consideration of domestic digital ecosystems and usage contexts, as cultural and technological factors influence both the structure and scaling of such instruments.