BackgroundFour oscillometric devices, including the Omron M6 Comfort, Omron HEM-7420, Withings BP-800, and Polygreen KP-7670, designed for self-blood pressure measurement (SBPM) were evaluated according to the European Society of Hypertension (ESH) International Protocol Revision 2010 in four separate studies.MethodsThe four devices measure brachial blood pressure (BP) using the oscillometric method. The Withings BP-800 has to be connected to an Apple® iOS device such as an iPhone®, iPad®, or iPod®. The ESH International Protocol Revision 2010 includes a total number of 33 subjects. The difference between observer and device BP values was calculated for each measure. Ninety-nine pairs of BP differences were classified into three categories (≤5 mmHg, ≤10 mmHg, ≤15 mmHg). The protocol procedures were followed precisely in each of the four studies.ResultsAll four tested devices passed the validation process. The mean differences between the device and mercury readings were: −1.8±5.1 mmHg and −0.4±2.8 mmHg for systolic and diastolic BP, respectively, using the Omron M6 Comfort device; 2.5±4.6 mmHg and −1.2±4.3 mmHg for the Omron HEM-7420 device; −0.2±5.0 mmHg and 0.4±4.2 mmHg for the Withings BP-800 device; and 3.0±5.3 mmHg and 0.3±5.2 mmHg for the Polygreen KP-7670 device.ConclusionOmron M6 Comfort, Omron HEM-7420, Withings BP-800, and Polygreen KP-7670 readings differing by less than 5 mmHg, 10 mmHg, and 15 mmHg fulfill the ESH International Protocol Revision 2010 requirements, and therefore are suitable for use by patients for SBPM, if used correctly.
Cloud Computing (CC) has become increasingly popular since it provides a wide variety of customized and reliable computational services. With the rapid growth of this technology, more and more IT services providers compete to offer high-quality and cost-effective cloud services that best fulfill their customers' needs. Given the vast diversity of these offers, the choice of the most appropriate Cloud Service Provider (CSP) became a dilemma that confuses most cloud customers. Many diverged criteria have to be considered to precisely evaluate services offered by several CSPs, some of these criteria cannot be quantified easily such as usability and security. The selection of the best CSP is thus a complex Multi-Criteria Decision Making (MCDM) problem that needs to be addressed efficiently. Previous studies of this problem employed MCDM methods that are either unfeasible when it is difficult or meaningless to quantify alternatives over criteria or computationally expensive and inconsistent when relative preferences of alternatives and criteria are used instead. In this paper, we propose a novel MCDM approach that is feasible, efficient and consistent using relative preferences of criteria and alternatives. The proposed approach incorporates Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and the Best Worst Method (BWM) to rank CSPs using evaluation criteria characterizing their services. The integrated approach has been tested and validated through a use-case scenario which demonstrates its effectiveness and correctness. We have also compared the proposed approach to the most commonly used MCDM approach, Analytical Hierarchical Process (AHP). The results clearly show that the proposed approach outperforms AHP in terms of computational complexity and consistency; hence, it is more efficient and reliable than AHP. INDEX TERMS Cloud computing (CC), cloud service providers (CSPs), multiple-criteria decision-making (MCDM), best worst method (BWM), technique for order of preference by similarity to ideal solution (TOPSIS), analytical hierarchical process (AHP).
The rapid growth of Information and Communication Technologies (ICT)—specifically, the Internet—has given emergence to e-learning. Resultantly, web-based e-learning systems are being increasingly developed to enhance the learning process. However, the utilization of such systems is low, mainly owing to poor quality content and overall design problems. To improve usage, it is imperative to identify the factors with the most significant impact on the quality of these systems so that the e-learning industry keeps these factors in consideration while developing e-learning systems. This study focused on the identification and prioritization of factors related to the design quality of e-learning systems through a hierarchical quality model. Thus, firstly, an extensive literature review was conducted to identify the factors that most affect the quality of web-based e-learning systems. Secondly, among the identified factors, only those with the most significant effect were considered. To identify the most important quality criteria, a survey was conducted. An instrument was deployed among 157 subjects, including e-learning designers, developers, students, teachers, and educational administrators. Finally, a second instrument was distributed among 51 participants to make a pairwise comparison among the criteria and rank them according to their relative importance. The identified and prioritized factors were classified into four main categories. Among these four factors, content was identified as the most important factor, whereas design was found to be the least important factor.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.