Teaching Status and Teaching Reform Ideas of Physical Chemistry Experiments for Food Quality and Safety Major

Physical chemistry experiments are an important branch of chemical experiments.In view of problems and shortcomings in physical chemistry experiment teaching of food quality and safety major in Chengdu University,the teaching methods of physical chemistry experiment course of food quality and safety major were explored and practiced,aiming to arouse students enthusiasm for experiments and cultivate their ability of independent learning,comprehensive thinking and independent problem solving.

Assessment of Quality of Experience (QoE) of Web and Video Services over a Mobile Network Using a Network Emulator

This paper investigates the subjective assessment of QoE of web and video services over a mobile network. To achieve this, the authors used the network emulator (NetEm) traffic control functionality to simulate the dynamic behaviour of a mobile network. Experiments were conducted in a laboratory setting and test conditions were varied to ascertain the QoE, with a focus on QoE metrics such as delay and packet loss ratio. From the experiments conducted, it was observed that there was a negative correlation between delay and average mean opinion score (MOS), and between packet loss ratio and average MOS. The results obtained can be adopted by network operators to provide better services which would lead to improved subscriber base and profitability for the operators and better QoE for the end users.

基于QoE理论的智慧医院平台可用性量表开发

目的基于体验质量(Quality of Experience,QoE)理论构建智慧医院平台可用性量表,为智慧医院建设提供科学测量工具。方法采用文献回顾、焦点会议法、预调查对量表条目进行筛选、修订,形成正式量表。便利选取山东省8所智慧医院平台的1000名用户进行调查,评价量表的信度和效度。结果智慧医院平台可用性量表包括6个维度24个条目。探索性因子提取出6个公因子:安全性、易用性、影响性、响应性、可靠性、灵活性。累计方差贡献率为64.045%,总体Cronbach’sα系数为0.941,6个维度的Cronbach’sα系数为0.782~0.963,重测信度为0.967。平均内容效度指数为0.972,条目水平内容效度指数为0.86~1.00。量表6个维度和系统可用性量表相关性系数为0.606~0.653,总体相关系数为0.647。结论基于QoE理论的智慧医院平台可用性量表具有较好的信度和效度,可作为用户对智慧医院平台体验情况的测量工具。

移动边缘网络中基于QoE的网络媒体流卸载算法

针对移动边缘计算中新兴网络媒体流业务面临的高时延、高能耗、高带宽、低用户体验质量(QoE)等问题,提出一种基于QoE反馈配置卸载(QFCO)算法。首先,联合考虑预处理和优先级划分,从而最大化网络资源利用率,并为计算任务赋予不同的权重建立资源分配关系;然后,综合考虑截止时间、计算资源、功率和带宽等约束,以任务时延、能耗和精确度加权和为优化目标建立QoE模型,利用拉格朗日乘数法求解。仿真结果表明,相比深度增强学习在线卸载(DROO)算法,所提算法可有效实现资源的整体优化配置,更好地提升用户体验质量。

An Evaluation Scale of Medical Services Quality Based on “Patients' Experience”

An evaluation scale of medical services quality was developed on the basis of ＂patients＇ experience＂. The questionnaires were developed by, among others, searching relevant literature, col- lecting well-established assessment scales, measuring patients＇ experience and satisfaction, brain-storming, literature analysis. Delphi method was adopted for expert consultation. Scale items were screened and revised. The key indexes were converted. Field surveys were conducted for testing the reliability and validity of the scale. Our modified evaluation scale for measuring medical services quality based on ＂patients＇ experience＂ included 6 dimensions （tangibility, reliability, responsiveness, assurance, empathy and continuity）, and 50 items. The novel scale based on ＂patients＇ experience＂ may better serve the purpose of assessin~ medical services quality.

Heterogeneous Quality of Experience Guarantees Over Wireless Networks

Quality of experience(Qo E), which is very critical for the experience of users in wireless networks, has been extensively studied. However, due to different human perceptions, quantifying the effective capacity of wireless network subject to diverse Qo E is very difficult, which leads to many new challenges regarding Qo E guarantees in wireless networks. In this paper, we formulate the Qo E guarantees model for cellular wireless networks. Based on the model, we convert the effective capacity maximization problem into the equivalent convex optimization problem. Then, we develop the optimal Qo E-driven power allocation scheme, which can maximize the effective capacity. The obtained simulation results verified our proposed power allocation scheme, showing that the effective capacity can be significantly increased compared with that of traditional Qo E guarantees based schemes.

Quality of experience based scheduling algorithm in LTE network with various traffics

Quality of experience （ QoE ） based scheduling algorithm of long term evalution （ LTE ） network with various traffics is studied. Utility functions are adopted to estimate mean opinion score （MOS） for different traffics and a new MOS metric called normalized MOS is defined. A scheduling algorithm based on normalized MOS and greedy algorithm is proposed, aiming at maximizing the entirety MOS level of the whole users in the cell. We compare the performance of the proposed algorithm with other typical scheduling algorithms and the simulation results show that the algorithm pro- posed outperform other ones in term of QoE and fairness.

QoE oriented intelligent online learning evaluation technology in B5G scenario

Students'demand for online learning has exploded during the post-COvID-19 pandemic era.However,due to their poor learning experience,students'dropout rate and learning performance of online learning are not always satisfactory.The technical advantages of Beyond Fifth Generation(B5G)can guarantee a good multimedia Quality of Experience(QoE).As a special case of multimedia services,online learning takes into account both the usability of the service and the cognitive development of the users.Factors that affect the Quality of Online Learning Experience(OL-QoE)become more complicated.To get over this dilemma,we propose a systematic scheme by integrating big data,Machine Learning(ML)technologies,and educational psychology theory.Specifically,we first formulate a general definition of OL-QoE by data analysis and experimental verification.This formula considers both the subjective and objective factors(i.e.,video watching ratio and test scores)that most affect OLQoE.Then,we induce an extended layer to the classic Broad Learning System(BLS)to construct an Extended Broad Learning System(EBLS)for the students'OL-QoE prediction.Since the extended layer can increase the width of the BLS model and reduce the redundant nodes of BLS,the proposed EBLS can achieve a trade-off between the prediction accuracy and computation complexity.Finally,we provide a series of early intervention suggestions for different types of students according to their predicted OL-QoE values.Through timely interventions,their OL-QoE and learning performance can be improved.Experimental results verify the effectiveness oftheproposed scheme.

Quality of Experience Effects in Video Delivery

With the popularization of smartphones and high-speed networks, a larger number of users are getting used to watching videos online and have increasing requirements of video quality. Therefore, the video content delivery has become a progressively challenging task, especially for ultra-high-definition(UHD) videos and heterogonous networks. Recently, quality of experience(QoE), which represents the true visual experience of users, has shown its advantages in management of video delivery and thus attracted increasing attention. In a video delivery system, the user QoE can be greatly influenced by numerous effects from video sources to display terminals. In this paper, we first investigate the significant differences between quality of service(QoS) and QoE. In addition, we summarize the end-to-end QoE effects in video delivery and present their classification based on the deployment. We also specifically analyze the impacts of different kinds of factors on QoE in video transmission systems.

Recommendations for Big Data in Online Video Quality of Experience Assessment

Real-time video application usage is increasing rapidly. Hence, accurate and efficient assessment of video Quality of Experience (QoE) is a crucial concern for end-users and communication service providers. After considering the relevant literature on QoS, QoE and characteristics of video trans-missions, this paper investigates the role of big data in video QoE assessment. The impact of QoS parameters on video QoE are established based on test-bed experiments. Essentially big data is employed as a method to establish a sensible mapping between network QoS parameters and the resulting video QoE. Ultimately, based on the outcome of experiments, recommendations/re- quirements are made for a Big Data-driven QoE model.

Quality of Experience in Internet of Things: A Systematic Literature Review

With the rapid growth of the Internet of Things paradigm,a tremendous number of applications and services that require minimal or no human involvement have been developed to enhance the quality of everyday life in various domains.In order to ensure that such services provide their functionalities with the expected quality,it is essential tomeasure and evaluate this quality,which can be in some cases a challenging task due to the lack of human intervention and feedback.Recently,the vast majority of the Quality of Experience QoE works mainly address the multimedia services.However,the introduction of Internet of Things IoT has brought a new level of complexity into the field of QoE evaluation.With the emerging of the new IoT technologies such as machine to machine communication and artificial intelligence,there is a crucial demand to utilize additional evaluation metrics alongside the traditional subjective and objective human factors and network quality factors.In this systematic review,a comprehensive survey of the QoE evaluation in IoT is presented.It reviews the existing quality of experience definitions,influencing factors,metrics,and models.The review is concluded by identifying the current gaps in the literature and suggested some future research directions accordingly.

Influences of Network Delay on Quality of Experience for Soft Objects in Networked Real-Time Game with Haptic Sense

In this paper, we investigate the influences of network delay on QoE (Quality of Experience) such as the operability of haptic interface device and the fairness between players for soft objects in a networked real-time game subjectively and objectively. We handle a networked balloon bursting game in which two players burst balloons (i.e., soft objects) in a 3D virtual space by using haptic interface devices, and the players compete for the number of burst balloons. As a result, we find that the operability depends on the network delay from the local terminal to the other terminal, and the fairness is mainly dependent on the difference in network delay between the players’ terminals. We confirm that there exists a trade-off relationship between the operability and the fairness. We also see that the contribution of the fairness is larger than that of the operability to the comprehensive quality (i.e., the weighted sum of the operability and fairness). Assessment results further show that the output timing of terminals should be adjusted to the terminal which has the latest output timing to maintain the fairness when the difference in network delay between the terminals is large. In this way, the comprehensive quality at each terminal can be maintained as high as possible.

The Impacts of Lower Population Growth on the Quality of Life and Economic Development：China＇s Experience

China is the most populous country in the world.The total Population on the mainland of China has in-creased from 540 million in 1949 to 1.18 billion by the end of 1993.China adopted a population policy by namc of"controlling population growth and im-proving the quality of the human resources',which has been deeply rooted in the hearts of the Chinese pcoplc.The overw helming majority of the Chinese people have recognized the necessity for implementing the family planning programme not only for the sustained devel-opment of the country,but also for the benefits of their own familie cs.

Progress in applying patient experience in nursing quality improvement

Background： Improving and sustaining the quality of nursing care is an intractable and persistent challenge. The patient experience of nursing care can give a different perspective on nursing quality and help clinical nursing staff to direct quality improvement. Attempts to identify what is patient experience,the relationship with nursing care, and the application of patient experience in nursing quality improvement practice, in order to provide advices for constructing the quality standards and quality improvement strategies of nursing care.Methods： We conducted a literature review of original research publications. The database platforms Pubmed, Web of Science, China National Knowledge Infrastructure（CNKI） and Wanfang were searched from inception until end of August 2015. After screening retrieved articles, 40 sources（articles and organizational websites） were selected for analysis for the connotation, development and application of patient experience in nursing quality researches.Results： Our study identified several concepts about patient experience, roughly sorted out the development path of patient experience in worldwide and the application of patient experience in nursing quality improvement. It points out four precautions when applying patient experience in nursing quality improvement, which are differentiating patient satisfaction and patient experience, choosing appropriate data collection method and appropriate feedback time, and the last but the most important, applying theories to actual clinical practice.Conclusions： Professional indexes are important to maintain the care quality, but it cannot fully reflect quality of nursing care, which needs patient experience as the supplement. Nursing staffs need to make more efforts to enhance patient＇s nursing care experience, and apply the research results to clinical practice, and finally make patient-centered care come true. For future study, the evaluation system and management strategies about patient experience need to be developed to guide nursing quality improvement.

基于自动机器学习的QoE预测模型研究

准确预测流媒体视频的用户体验质量(QoE)是提升其服务的关键所在。流媒体QoE预测模型通常基于视频质量和网络传输质量等客观指标进行评估,然而,QoE的主观性为准确评估带来了极大的挑战。为了更精确地预测用户体验质量,文章首次将自动机器学习用于流媒体视频的QoE预测,提出了基于自动机器学习的QoE预测模型。该模型通过特征分析从视频质量评估指标和网络质量评估指标中选择最优特征作为输入,采用H2O AutoML自动机器学习算法进行QoE建模。为了评估方法的有效性,在公开数据集SQoE-Ⅲ数据库上进行实验,并与基于传统机器学习的XGBoot算法的QoE模型结果进行对比分析。实验结果显示,通过自动选择和调优,基于自动机器学习的QoE预测模型取得了显著的进展。该模型的MAE为5.53699、RMSE为7.35987,有效提升了QoE预测的准确性。该研究为QoE建模提供了新的思路和方法,精确预测了用户对视频流的感知满意度。

Outpatient Experience of Human Caring Scale （OEHC-Scale）： Improvement by Delphi Method

Based on the outpatient interview and literature review, the initial framework of the outpatient experience of human caring scale was formed with 9 dimensions of outpatient process. The research aim was to improve the scale by Delphi method. Sixteen experts in medical management, human caring or medical education were invited to evaluate the importance of the dimensions and items of the scale and provided some expertise via filling out the DeLphi consultation questionnaires twice in the consulting round. In the first round, the recovery rate showing the experts＇ positivity was 80%; the coefficient of reliability （Cr） ascertaining the authority of the evaluation was 0.92; the mean and full mark ratios responding the concentration of the evaluation were 2.88-4.94 and 6.25%-93.75% respectively; the coefficients of variation （CV） and the Kendall＇s W determining the concordance of the evaluation were 5.06%-52.15% and 0.21-0.24 respectively. In the second round, the recovery rate was 93.75%; the Cr was 0.93; the mean was 3.93-4.93; the full mark ratios were 26.67%-93.33%; the Kendall＇s W was 0.14- 0.31, the CV was 5.25%-23.61%. Via the two-round Delphi study, the scale that included 10 dimensions and 61 items has been improved. Ten dimensions are pre-hospital medical service, guidance, registration, waiting, diagnosis ＆ treatment, paying, inspection ＆ assay, medicine receiving, therapy/injection/transfusion and global evaluation. It was concluded that Chinese scholars have paid high attention to human caring and outpatient experience. The experts have given high agreements about the dimensions which were established with Chinese outpatient process. The dimensions are different from the similar researches about outpatient experience study. In the future, it is necessary to survey the outpatients to test the construct validity, internal consistency reliability and others of the scale to improve the scale.

3GPP R17 NR QoE标准进展及演进技术研究

5G新业务在用户体验方面提出新的要求,针对5G用户业务体验的保障、优化及提升成为业界重点关注的问题之一。3GPP R17版本开展支持5G用户业务体验端到端保障机制的标准研究与制定工作,研究并制定支持5G新业务的用户体验数据采集、优化等系列标准流程,并将在R18版本进一步增强用户业务体验的技术方案,更好地支持5G XR等新业务的高品质服务保障的需求。对3GPP R17和R18用户业务体验无线网技术解决方案进行分析研究,并结合5G新业务需求,展望该方案在增强5G网络高质量业务体验方面的广阔应用场景。

QoE-driven voice quality evaluation model of VoIP based on network simulation

The quality of experience（ QoE） evaluation model for voice over IP（ VoI P） service is studied to analyze the impact of network parameters on voice quality and monitor voice quality in real-time for operators.Firstly,the influence of some network parameters on the voice quality of VoI P is investigated. Then,a simulation platform for VoI P transmission is built to collect voice data under different network enviornments. According to the simulation results,a new mapping model between these arguments and VoI P voice quality is deduced. Finally,the accuracy of this voice quality evaluation model is examined and the results demanstrate that it has high reliability and feasibility.

Explaining Customer Experience of Digital Financial Advice

The goal of this paper is to analyze the customer experience of digital-driven financial advice systems. It is the objective of this study to develop a cross-cultural model for validating customer experiences of digital financial advice. In doing so, both objective and subjective system aspects have been considered. It is found that experiential subjective system aspects are the most important. Surveys have been conducted in The United Kingdom and The Netherlands. In exploratory factor analysis, five dominant factors were obtained in the UK and six factors in The Netherlands to explain customer experience. Based on the factor scores, multiple regression analysis has been performed to develop the digital customer experience model （DCX model）. This is the first cross-cultural model to evaluate customer experience of financial advice. In an era in which financial institutions and FinTech companies battle for the engagement of customers, the DCX model is the first to fundamentally drive value creation, differentiation, regulation, and future research.