Transforming the Quality Maternal Newborn Care Framework into an index (QMNCFi) to measure the quality of maternity care

BACKGROUND: The Quality Maternal and Newborn Care (QMNC) Framework describes the care that childbearing women and newborn infants need in all settings. It comprises five components and was designed for use in planning, workforce development, and resource allocation, aimed at improving the quality and cost effectiveness of maternal and newborn care globally. The purpose of this paper is to describe the first phase of a project designed to transform the Framework into a quantitative tool for service user assessment of the quality of maternity care. METHODS: Each component of the original Framework content was developed into a draft service user questionnaire and distributed to an expert panel, drawn from a range of low-, middle-, and high-resource countries. The panel consisted of five Framework authors, nine midwife researchers, six midwives, and five service user (consumer) advocates. Two rounds of discussion and revision were undertaken with the expert panel who commented on the importance, relevance and clarity of questions, and then on their necessity, wording, and order. A third round involved two experts in survey design. RESULTS: Following 24 responses in the first round, the questions were refined and returned to the panel. After incorporating the second-round comments from 16 experts, the survey was then sent to two experts in questionnaire design and construction. Face validity was affirmed through this consultative process. CONCLUSIONS: Despite Covid-19 pandemic-related restrictions, this robust iterative consultative process with an international expert panel has resulted in the prototype QMNC Framework index (QMNCFi)-a questionnaire designed for use in diverse settings to assess the quality of maternity care. The QMNCFi's psychometric properties are now being tested in an international online survey

The Exploration on Satisfaction and Loyalty: A Case of Non-Teacher Training Major Students in Chuxiong Normal University, China

Purpose: Talent training is the fundamental mission of the sustainable development of colleges and universities. This paper aimed to examine the factors impacting student satisfaction and loyalty, using a case of non-teacher training major students at Chuxiong Normal University, China. The conceptual framework contained academic aspect, reputation, service quality, facility, student satisfaction, and student loyalty. Research design, data, and methodology: The quantitative method distributed online questionnaires to 500 students. The sampling techniques involve judgmental sampling, quota sampling, convenience sampling, and snowball sampling. The index approved the construct validity of item-objective congruence (IOC). For the reliability test, each construct was verified by Cronbach's Alpha coefficient values in the pilot test of 30 participants. The data were analyzed by confirmatory factor analysis (CFA), including the goodness of model fit, reliability, and validity. Furthermore, structural equation modeling (SEM) was implemented to test hypotheses. Results: The findings were that academic aspects, service quality, and facility significantly impact student satisfaction. Additionally, student satisfaction had a significant impact on student loyalty. Conversely, reputation had no significant impact on student satisfaction. Conclusions: The improvement of student satisfaction and loyalty can be achieved by promoting a good reputation, strengthening the academic aspects, and enhancing service quality and facilities

Factor Analysis of Satisfaction and Continuance Intention to Use Online Payment Among University Students in Chengdu, China

Purpose: This paper aims to explore satisfaction and continuance intention to use online payment among university Students in Chengdu, China. The researcher applied quantitative survey research methods. The Technology Acceptance Model (TAM), Information Systems Success Model (ISSM), and Expectation Confirmation Theory (ECT) are used to construct the conceptual framework of the research, including service quality, privacy, confirmation, perceived usefulness, perceived security, satisfaction, and continuance intention. Research design, data, and methodology: The validity of the research tool was evaluated by the Item Objective Congruence (IOC) Index, and the Cronbach alpha coefficient in a pilot test evaluated the internal consistency reliability. In addition, the sampling techniques are judgmental, quota and convenience sampling. The questionnaire was distributed to 500 students using online payment in target universities, analyzed by confirmatory factor analysis (CFA) and structural equation modeling (SEM). Results: All hypotheses were supported in which the service quality had the strongest on satisfaction. Satisfaction has a direct impact on continuance intention. Conclusions: To improve students’ satisfaction with online payment and their willingness to continue using it, it is necessary to improve the service quality and strengthen the protection of users’ privacy on online payment platforms. Managers should pay special attention to the security of user information

Prototyping a Web-Scale Multimedia Retrieval Service Using Spark

International audienceThe world has experienced phenomenal growth in data production and storage in recent years, much of which has taken the form of media files. At the same time, computing power has become abundant with multi-core machines, grids, and clouds. Yet it remains a challenge to harness the available power and move toward gracefully searching and retrieving from web-scale media collections. Several researchers have experimented with using automatically distributed computing frameworks, notably Hadoop and Spark, for processing multimedia material, but mostly using small collections on small computing clusters. In this article, we describe a prototype of a (near) web-scale throughput-oriented MM retrieval service using the Spark framework running on the AWS cloud service. We present retrieval results using up to 43 billion SIFT feature vectors from the public YFCC 100M collection, making this the largest high-dimensional feature vector collection reported in the literature. We also present a publicly available demonstration retrieval system, running on our own servers, where the implementation of the Spark pipelines can be observed in practice using standard image benchmarks, and downloaded for research purposes. Finally, we describe a method to evaluate retrieval quality of the ever-growing high-dimensional index of the prototype, without actually indexing a web-scale media collection

A grid-based infrastructure for distributed retrieval

In large-scale distributed retrieval, challenges of latency, heterogeneity, and dynamicity emphasise the importance of infrastructural support in reducing the development costs of state-of-the-art solutions. We present a service-based infrastructure for distributed retrieval which blends middleware facilities and a design framework to ‘lift’ the resource sharing approach and the computational services of a European Grid platform into the domain of e-Science applications. In this paper, we give an overview of the DILIGENT Search Framework and illustrate its exploitation in the field of Earth Science

Cross-layer design of multi-hop wireless networks

MULTI -hop wireless networks are usually defined as a collection of nodes equipped with radio transmitters, which not only have the capability to communicate each other in a multi-hop fashion, but also to route each others’ data packets. The distributed nature of such networks makes them suitable for a variety of applications where there are no assumed reliable central entities, or controllers, and may significantly improve the scalability issues of conventional single-hop wireless networks. This Ph.D. dissertation mainly investigates two aspects of the research issues related to the efficient multi-hop wireless networks design, namely: (a) network protocols and (b) network management, both in cross-layer design paradigms to ensure the notion of service quality, such as quality of service (QoS) in wireless mesh networks (WMNs) for backhaul applications and quality of information (QoI) in wireless sensor networks (WSNs) for sensing tasks. Throughout the presentation of this Ph.D. dissertation, different network settings are used as illustrative examples, however the proposed algorithms, methodologies, protocols, and models are not restricted in the considered networks, but rather have wide applicability. First, this dissertation proposes a cross-layer design framework integrating a distributed proportional-fair scheduler and a QoS routing algorithm, while using WMNs as an illustrative example. The proposed approach has significant performance gain compared with other network protocols. Second, this dissertation proposes a generic admission control methodology for any packet network, wired and wireless, by modeling the network as a black box, and using a generic mathematical 0. Abstract 3 function and Taylor expansion to capture the admission impact. Third, this dissertation further enhances the previous designs by proposing a negotiation process, to bridge the applications’ service quality demands and the resource management, while using WSNs as an illustrative example. This approach allows the negotiation among different service classes and WSN resource allocations to reach the optimal operational status. Finally, the guarantees of the service quality are extended to the environment of multiple, disconnected, mobile subnetworks, where the question of how to maintain communications using dynamically controlled, unmanned data ferries is investigated

Design and Implementation of Distributed Resource Management for Time Sensitive Applications

In this paper, we address distributed convergence to fair allocations of CPU resources for time-sensitive applications. We propose a novel resource management framework where a centralized objective for fair allocations is decomposed into a pair of performance-driven recursive processes for updating: (a) the allocation of computing bandwidth to the applications (resource adaptation), executed by the resource manager, and (b) the service level of each application (service-level adaptation), executed by each application independently. We provide conditions under which the distributed recursive scheme exhibits convergence to solutions of the centralized objective (i.e., fair allocations). Contrary to prior work on centralized optimization schemes, the proposed framework exhibits adaptivity and robustness to changes both in the number and nature of applications, while it assumes minimum information available to both applications and the resource manager. We finally validate our framework with simulations using the TrueTime toolbox in MATLAB/Simulink

Measuring and Managing Answer Quality for Online Data-Intensive Services

Online data-intensive services parallelize query execution across distributed software components. Interactive response time is a priority, so online query executions return answers without waiting for slow running components to finish. However, data from these slow components could lead to better answers. We propose Ubora, an approach to measure the effect of slow running components on the quality of answers. Ubora randomly samples online queries and executes them twice. The first execution elides data from slow components and provides fast online answers; the second execution waits for all components to complete. Ubora uses memoization to speed up mature executions by replaying network messages exchanged between components. Our systems-level implementation works for a wide range of platforms, including Hadoop/Yarn, Apache Lucene, the EasyRec Recommendation Engine, and the OpenEphyra question answering system. Ubora computes answer quality much faster than competing approaches that do not use memoization. With Ubora, we show that answer quality can and should be used to guide online admission control. Our adaptive controller processed 37% more queries than a competing controller guided by the rate of timeouts.Comment: Technical Repor

Crashworthiness capability of jute and glass fibre reinforced epoxy tubes under quasi-static loading condition for automotive application

During last few years, the interest in using natural fibers as reinforcement in polymers has increased dramatically. Natural fibers are not only strong and lightweight but also relatively very cheap. This study examined the potential utilization of jute in the crash energy absorption. A combination of hand layup and vacuum bladder technique was kused to search the influence of utilizing jute fibre on crashworthiness parameters of composite materials. To improve the mechanical properties, jute fiber was hybridized with glass fiber. In this work, there are two main parts of study. Firstly, it is to investigate the effect of cross-sectional shapes, number of layers and temperature treatment on the progressive deformation of jute/epoxy composite tubes. Secondly, the suitable type of geometry was chosen to study the effect of hybrid (jute-glass/epoxy) onto the structural designs. All the tests were undergone quasi-static axial crushing of 10 mm/min. Their peak load (Pmax), mean load (Pm), energy absorption (EA) and specific energy absorption (SEA) were discussed in detail. In the study of types of five geometrical shapes (corrugated, circular, hexagonal, octagonal and decagonal cross sectional) with different number of layers (two, three and four layers). It is found that the corrugated geometric shape with three layers (RHS) gives the best energy absorption (30.92 J/g) in specific energy absorption parameter compared to other geometries used in present study. For the temperature treatment, the results showed that the post-curing by gradual temperature treatment (TT) improved the peak load by decreased with 55% as compared to similar circular specimen without temperature treatment (No TT). From the test, it is found that the substitution of one layer of jute fibre with one layer of glass fibre resulted in an improvement in the crashworthiness parameters than layers jute. The best result was obtained when hybrid jute-glass was used, where the energy absorption and specific energy absorption was improved by about 43% and 31%, respectively

Identifying hotspots and management of critical ecosystem services in rapidly urbanizing Yangtze River Delta Region, China

Rapid urbanization has altered many ecosystems, causing a decline in many ecosystem services, generating serious ecological crisis. To cope with these challenges, we presented a comprehensive framework comprising five core steps for identifying and managing hotspots of critical ecosystem services in a rapid urbanizing region. This framework was applied in the case study of the Yangtze River Delta (YRD) Region. The study showed that there was large spatial heterogeneity in the hotspots of ecosystem services in the region, hotspots of supporting services and regulating services aggregately distributing in the southwest mountainous areas while hotspots of provisioning services mainly in the northeast plain, and hotspots of cultural services widespread in the waterbodies and southwest mountainous areas. The regionalization of the critical ecosystem services was made through the hotspot analysis. This study provided valuable information for environmental planning and management in a rapid urbanizing region and helped improve China's ecological redlines policy at regional scale