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  1. Thirugnanam S, Soong LW, Prabhu CM, Singh AK
    Sensors (Basel), 2023 May 26;23(11).
    PMID: 37299822 DOI: 10.3390/s23115095
    The need for power-efficient devices, such as smart sensor nodes, mobile devices, and portable digital gadgets, is markedly increasing and these devices are becoming commonly used in daily life. These devices continue to demand an energy-efficient cache memory designed on Static Random-Access Memory (SRAM) with enhanced speed, performance, and stability to perform on-chip data processing and faster computations. This paper presents an energy-efficient and variability-resilient 11T (E2VR11T) SRAM cell, which is designed with a novel Data-Aware Read-Write Assist (DARWA) technique. The E2VR11T cell comprises 11 transistors and operates with single-ended read and dynamic differential write circuits. The simulated results in a 45 nm CMOS technology exhibit 71.63% and 58.77% lower read energy than ST9T and LP10T and lower write energies of 28.25% and 51.79% against S8T and LP10T cells, respectively. The leakage power is reduced by 56.32% and 40.90% compared to ST9T and LP10T cells. The read static noise margin (RSNM) is improved by 1.94× and 0.18×, while the write noise margin (WNM) is improved by 19.57% and 8.70% against C6T and S8T cells. The variability investigation using the Monte Carlo simulation on 5000 samples highly validates the robustness and variability resilience of the proposed cell. The improved overall performance of the proposed E2VR11T cell makes it suitable for low-power applications.
    Matched MeSH terms: Computers, Handheld*
  2. Fornace KM, Surendra H, Abidin TR, Reyes R, Macalinao MLM, Stresman G, et al.
    Int J Health Geogr, 2018 06 18;17(1):21.
    PMID: 29914506 DOI: 10.1186/s12942-018-0141-0
    BACKGROUND: Identifying fine-scale spatial patterns of disease is essential for effective disease control and elimination programmes. In low resource areas without formal addresses, novel strategies are needed to locate residences of individuals attending health facilities in order to efficiently map disease patterns. We aimed to assess the use of Android tablet-based applications containing high resolution maps to geolocate individual residences, whilst comparing the functionality, usability and cost of three software packages designed to collect spatial information.

    RESULTS: Using Open Data Kit GeoODK, we designed and piloted an electronic questionnaire for rolling cross sectional surveys of health facility attendees as part of a malaria elimination campaign in two predominantly rural sites in the Rizal, Palawan, the Philippines and Kulon Progo Regency, Yogyakarta, Indonesia. The majority of health workers were able to use the tablets effectively, including locating participant households on electronic maps. For all households sampled (n = 603), health facility workers were able to retrospectively find the participant household using the Global Positioning System (GPS) coordinates and data collected by tablet computers. Median distance between actual house locations and points collected on the tablet was 116 m (IQR 42-368) in Rizal and 493 m (IQR 258-886) in Kulon Progo Regency. Accuracy varied between health facilities and decreased in less populated areas with fewer prominent landmarks.

    CONCLUSIONS: Results demonstrate the utility of this approach to develop real-time high-resolution maps of disease in resource-poor environments. This method provides an attractive approach for quickly obtaining spatial information on individuals presenting at health facilities in resource poor areas where formal addresses are unavailable and internet connectivity is limited. Further research is needed on how to integrate these with other health data management systems and implement in a wider operational context.

    Matched MeSH terms: Computers, Handheld*
  3. Sohayla M. Attalla, Nihal A. Hanafy, Mahfuza Akter, Sakinah Ruhi
    MyJurnal
    Introduction: The twenty-first-century learning is adopting the student-centered learning techniques and the teach- ers are mainly facilitators to direct the process of learning and so social media and mobile applications became an important learning platform. Mobile learning (M-learning) is the practice of learning activities through a portable device such as cellular phone or a personal digital assistant. The aim of this research is to screen the medical stu- dents’ intention toward the adoption of M-learning and to determine factors affecting the intentions of the medical students to practice M-learning. Methods: A cross-sectional study among medical students was performed through a questionnaire based on the Theory of Reasoned Action and the Technology Acceptance Model. The study included 129 students in different stages of the medical study. Results: Results showed that the factors affecting the students’ inten¬tion to practice M-learning include the students’ attitude, perceived usefulness, perceived ease of use, and availability of resources. In the current sample 82.7% of students are already using M-Learning; 41.7% are using it for assessment, 22.8% are using it for learning and 35.5% are using it for both. Conclusion: It was concluded that most medical students have higher intention to adopt M-learning and they are mostly using it for assessment purposes rather than in learning.
    Matched MeSH terms: Computers, Handheld
  4. Venkataramani P, Sadanandan T, Savanna RS, Sugathan S
    Med Educ, 2019 05;53(5):499-500.
    PMID: 30891812 DOI: 10.1111/medu.13860
    Matched MeSH terms: Computers, Handheld
  5. O'Donovan J, Maruthappu M
    Med Teach, 2015 May;37(5):463-9.
    PMID: 25182187 DOI: 10.3109/0142159X.2014.956063
    To assess the feasibility and impact of using low-cost Android tablets to deliver video tutorials and remote online peer-tutoring for clinical skills between two countries.
    Matched MeSH terms: Computers, Handheld
  6. Simon SK, Seldon HL
    Stud Health Technol Inform, 2012;182:125-32.
    PMID: 23138087
    A target of telehealth is to maintain or improve the health of people outside the normal healthcare infrastructure. A modern paradigm in healthcare, and one which fits perfectly with telehealth, is "person self-monitoring", and this fits with the concept of "personal health record" (PHR). One factor in maintaining health is to monitor physiological parameters; this is of course especially important in people with chronic maladies such as diabetes or heart disease. Parameters to be monitored include blood pressure, pulse rate, temperature, weight, blood glucose, oxygen saturation, electrocardiogram (ECG), etc. So one task within telehealth would be to help monitor an individual's physiological parameters outside of healthcare institutions and store the results in a PHR in a way which is available, comprehensible and beneficial to the individual concerned and to healthcare providers. To date many approaches to this problem have been fragmented - emphasizing only part of the problem - or proprietary and not freely verifiable. We describe a framework to approach this task; it emphasizes the implementation of standards for data acquisition, storage and transmission in order to maximize the compatibility among disparate components, e.g. various PHR systems. Data from mobile biosensors is collected on a smartphone using the IEEE 11073 standard where possible; the data can be stored in a PHR on the phone (using standard formats) or can be converted in real-time into more useful information in the PHR, which is based on the International Classification for Primary Care (ICPC2e). The phone PHR data or information can be uploaded to a central online PHR using either the Wi-Fi or GSM transmission protocol together with the Continuity of Care Record message format (CCR, ASTM E2369).
    Matched MeSH terms: Computers, Handheld
  7. Salleh R, Man CS, Ahmad MH, Palaniveloo L, Zulkafly N, Ab Halim SA, et al.
    Geriatr Gerontol Int, 2020 Dec;20 Suppl 2:73-78.
    PMID: 33370860 DOI: 10.1111/ggi.14006
    AIM: Older persons are vulnerable to food insecurity. Therefore, this study aimed to determine the prevalence of food insecurity and associated factors among older persons in Malaysia.

    METHODS: This is a cross-sectional study with two-stage stratified random sampling. In total, 3977 older persons participated in this study. Face-to-face interviews were conducted using a mobile device to obtain information about socio-demographic background, food insecurity, non-communicable diseases, social support and living arrangements. Descriptive and multiple complex sample logistic regression analyses were performed for data analysis.

    RESULTS: The overall prevalence of food insecurity among older persons was 10.4%. Older persons from rural areas with no or only primary and secondary education, income less than RM 2000 (USD 477.57), at risk of malnutrition and not receiving very high social support were more likely to be food-insecure.

    CONCLUSION: Approximately, one-tenth of Malaysian older adults were classified as food-insecure; particularly those living in rural areas from lower socio-economic status, not receiving very high social support and malnourished were more likely to be at risk. A specific nutrition program, such as meals on wheels and food vouchers, should be targeted toward older persons who are at risk to improve their malnutrition status. Geriatr Gerontol Int 2020; 20: 73-78.

    Matched MeSH terms: Computers, Handheld
  8. Ackermann L, Lo CH, Mani N, Mayor J
    PLoS One, 2020;15(12):e0240519.
    PMID: 33259476 DOI: 10.1371/journal.pone.0240519
    In recent years, the popularity of tablets has skyrocketed and there has been an explosive growth in apps designed for children. Howhever, many of these apps are released without tests for their effectiveness. This is worrying given that the factors influencing children's learning from touchscreen devices need to be examined in detail. In particular, it has been suggested that children learn less from passive video viewing relative to equivalent live interaction, which would have implications for learning from such digital tools. However, this so-called video deficit may be reduced by allowing children greater influence over their learning environment. Across two touchscreen-based experiments, we examined whether 2- to 4-year-olds benefit from actively choosing what to learn more about in a digital word learning task. We designed a tablet study in which "active" participants were allowed to choose which objects they were taught the label of, while yoked "passive" participants were presented with the objects chosen by their active peers. We then examined recognition of the learned associations across different tasks. In Experiment 1, children in the passive condition outperformed those in the active condition (n = 130). While Experiment 2 replicated these findings in a new group of Malay-speaking children (n = 32), there were no differences in children's learning or recognition of the novel word-object associations using a more implicit looking time measure. These results suggest that there may be performance costs associated with active tasks designed as in the current study, and at the very least, there may not always be systematic benefits associated with active learning in touchscreen-based word learning tasks. The current studies add to the evidence that educational apps need to be evaluated before release: While children might benefit from interactive apps under certain conditions, task design and requirements need to consider factors that may detract from successful performance.
    Matched MeSH terms: Computers, Handheld
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