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.

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.

A Wealth of Experience

ZHONG Zhenyu has been working as a freelance French interpreter since 2002. During the past 10 years, his services have been used by many forums and conferences between China and Africa as well as training classes for African people in China. It always brings him great pleasure every time he in- teracts with Africans, especially those from Guinea and Mali where he worked for about four years.

DREAMS OF AN INTEGRATED THEORY OF EXPERIENCE

本文从法位学的角度谈关于人类经验一体化理论的一些设想。 人类总是努力认识周围世界的格局和意义,没有这二者,就达不到人类所渴求的认识一体化。但是知识界却常常分割成许多各自严守畛域的学科、学派。 一百年来,学者们力图使社会研究也变成客观的科学,语言学、心理学等莫不如此,一时蔚为风气。但是,在错综复杂的经验领域里,精确的预测和计量是难以办到的;勉强做去,常常导致简单化。 各种学科隔离分立的趋向,多少为另一种倾向所抵销,就是一种学术风尚,由于思想的交流,会影响到其他学科。二十年代心理学从Wundt的理论转向行为主义,语言学者Bloomfield也随之将注意力从内心移到作为行为的语言。后来,语言学者Chomsky又一度促使心理学者转而考察语言与人的固有观念的关系。 本文作者主张应当将注意力集中于观察事物的人,而不是集中于物。科学的首要原则是把观察事物的人看得重于人所观察的事物。这样,象“句”或“词”这样的语言术语,就要以人的交际活动作为下定义的出发点。从五十年代起,作者即试图表明,语言是人的行为的一部分,有一定的结构,后者可以应用跟分析足球比赛、礼拜仪式等一样的方法加以分析。为此创造了两个术语,并渐被人类学界所采用,就是“唯位”(emic,取自pho-nemic“音位的”)和“唯素”(etic,取自phonetic“音素的”)。唯位观点是圈内人的观点,他只对自幼学会的语言中具有对比(互相区别)作用的特征作出反应;唯素观点则是圈外人的观点,他对是否有对比作用是不加区分的。后来,又由此扩而大之,试图在语法中找出类似音位的唯位单位,称之为“法位”,从而建立了法位学。作者认为,观察者本身也必须包括在研究对象之中。正是由于观察者这个因素,人们才必须对上述的唯位的和唯素的知识加以区别。 近年来,作者写过三部著作,向哲学、文艺学和自然科学的研究者介绍语言学的原理和概念。如果这几方面的学者也能从相反的方向来考察语言,一座双向的学术交流的桥梁就架设起来了。 作者自己从物理学借来三个术语,把它应用到语言学中,就是“粒子”、“波”、“场”。语言学里已经有个很有用的术语“单位”,如把单位看作是可以从它的环境中分离出来加以研究的东西,就可以叫做“粒子”,亦即当它是有一定界限,可以分类,常常可以科学地测量的东西。但纯粹采取“粒子”的观点,不足以探究音或词相互融合的现象。在急速的说话中,音常被省略或替换,就是在舒缓的说话中,也要受前后的音的影响。这里就用得着“波”这个概念。波峰是波的核心,可以借以辨别音;这样,为了方便,可以只辨别单位而不必确定其界限。按照粒子观点,可以将音列表、分类、编入词典等等,而按照波的观点,可以更精细地讨论音的物理特性。 “场”的观点强调的是经验的相互关系。但它不把经验单纯看作一套关系。语言学把关系所构成的体系也看作一个单位。据此,作者认为一种语言的音位表也是关于这一语言的一个重要事实,本身也是个(场)单位。又如,知识不仅仅是己知片断的总和,而是有结构的体系,各个片断有系统地组成一个总的关系的场。 每个单位不是孤立自足的,而是把一定的环境也包括在内作为它的构成要素。认为可以离开环境客观地 发现一个单位、事物或关系,乃是一种幻想。感知一个单位,就牵连到观察者自己在内。当他感知两个单位之间,或一个单位的两个特征之间存在的对比时,他就给这个单位加上了自己的双项性牵连。如果把一个单位感知为实体或粒子(单一的东西、情境、关系或体系),他就加上了单项性牵连。如果他把某一单位看作是处在变化、生长、衰败或融合的过程中(例如观察破败中的房子),那就把他的感知作为带有波的性质的环境成分加上去;如果他从关系(场)的角度观察一个单位(例如研究房子的楼面布置和房间安排,或它跟同一楼区其他房屋的关系),他就加上了观察者的关系成分。如果把三者合起来,就加进三项性的观察者环境成分(例如那座破败中(波)的旧房子(粒子)的楼面布置(场))。 法位学采取这单项、双项、三项三种观察焦点,并把它们全都看作法位学理论明白宣示的、不可缺少的一部分,并且看作环境的一部分,而这环境又构成客观单位本身的一部分。目前,作者夫妇又把法位学观点推进一步,通过法位本身的描写,加上了一个四项性观点,提出:法位具有四个特征,每个特征都牵涉到一种为法位所不可缺少的环境,所以法位又叫“环境中的单位”。这四个环境成分是:1)轨位,即一个单位在比它更大的单位中所占的位置(如主语在英语被动句中的位置)。2)类别,其中一个成员可以填补这个轨位(如名词短语可以填补主语轨位)。3)作用,即类别在轨位中的语义作用(如在被动句中表示受事性主语)。这个环境不是形式的东西,它是整个法位的意义。形式和意义(如类别和作用)不能分割,形式类别离开它的语义环境就无法确定,反之语义作用不联系它的形式表现也无由确定。所以法位学不采取先研究句法,然后才研究语义,或者反过来先探讨认为先已存在的意义分类,再赋予结构形式的作法。4)接应,这个环境在单位所出现的结构中是观察不到的,它是一般的背景,别的结构,信仰,体系,期望等。这些东西制约或影响这一法位类别中哪一个成员要出现,或者反过来受其制约。

Trade-off in Optimizing Energy Consumption and End User Quality of Experience in Radio Access Network

To reduce network access latency, network traffic volume and server load, caching capacity has been proposed as a component of evolved Node B(e Node B) in the ratio access network(RAN). These e Node B caches reduce transport energy consumption but lead to additional energy cost by equipping every e Node B with caching capacity. Existing researches focus on how to minimize total energy consumption, but often ignore the trade-off between energy efficiency and end user quality of experience, which may lead to undesired network performance degradation. In this paper, for the first time, we build an energy model to formulate the problem of minimizing total energy consumption at e Node B caches by taking a trade-off between energy efficiency and end user quality of experience. Through coordinating all the e Node B caches in the same RAN, the proposed model can take a good balance between caching energy and transport energy consumption while also guarantee end user quality of experience. The experimental results demonstrate the effectiveness of the proposed model. Compared with the existing works, our proposal significantly reduces the energy consumption by approximately 17% while keeps superior end user quality of experience performance.

An introduction of the experience in treating Ventricular premature beat with stasis heat

Ventricular premature beat,a kind of arrhythmia,is one of common diseases which not only decreases the quality of life but also has the danger of death.The pathogenesis in Traditional Chinese Medicine is that the injury of heart and kidney is the essence and the block of solid evil such as phlegm and blood stasis is the manifestation.The teacher,Li Yuan,has worked in clinic for decades and considered that the important pathogenesis of the VP beat is“heat transformed from Yang”,which cannot be ignored as it is on the influence of diverse factors and can be observed in different symptoms and different treatment states of the disease.

Accumulation in simultaneous interpretation： The development of a successful interpreter

Accumulation of vocabulary, knowledge and experience is the foundation of comprehension and expression in simultaneous interpretation. This paper suggests the importance of accumulation in the development of a successful interpreter.

Energy-efficient task offloading strategy in mobile edge computing for resource-intensive mobile applications

Mobile Edge Computing (MEC) has been considered a promising solution that can address capacity and performance challenges in legacy systems such as Mobile Cloud Computing (MCC). In particular, such challenges include intolerable delay, congestion in the core network, insufficient Quality of Experience (QoE), high cost of resource utility, such as energy and bandwidth. The aforementioned challenges originate from limited resources in mobile devices, the multi-hop connection between end-users and the cloud, high pressure from computation-intensive and delay-critical applications. Considering the limited resource setting at the MEC, improving the efficiency of task offloading in terms of both energy and delay in MEC applications is an important and urgent problem to be solved. In this paper, the key objective is to propose a task offloading scheme that minimizes the overall energy consumption along with satisfying capacity and delay requirements. Thus, we propose a MEC-assisted energy-efficient task offloading scheme that leverages the cooperative MEC framework. To achieve energy efficiency, we propose a novel hybrid approach established based on Particle Swarm Optimization (PSO) and Grey Wolf Optimizer (GWO) to solve the optimization problem. The proposed approach considers efficient resource allocation such as sub-carriers, power, and bandwidth for offloading to guarantee minimum energy consumption. The simulation results demonstrate that the proposed strategy is computational-efficient compared to benchmark methods. Moreover, it improves energy utilization, energy gain, response delay, and offloading utility.

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.

The Practice of Palliative Care amongst Nurses in Selected Hospitals in Eastern Nigeria

In recent times, palliative care nursing has caught the attention of nurse researchers in Africa as more individuals are being diagnosed with chronic diseases of the aged like cancer, cardiac and cerebrovascular conditions. This study examined the influence of knowledge and attitude on the practice of palliative care among practicing nurses in eastern part of Nigeria. A descriptive cross-sectional research design was used for the study. The population of the study is all registered, licensed and practicing nurses working in the named public and private hospitals where palliative care is supposedly well established. Proportionate sampling technique was used to select 289 respondents. Three commercial instruments that were modified were used for data collection. Level of significance was set at 5%. The study was conducted from October 2018 to June 2019. Results revealed that 52.7% of the respondents had satisfactory practice of palliative care, 73.7% of the respondents had adequate knowledge of palliative care (mean 2.64 (1.06) and 77.5% of the respondents had positive attitude towards palliative care (Mean 2.81 (1.14)). There was also a significant weak positive association between nurses’ educational level and their knowledge of palliative care with an effect size of 21.9% (P = 0.003). There was also a significant association between nurses’ years of experience and their attitude to palliative care with an effect size of 35.6% (P < 0.001). There was no significant association between type of hospital facility nurses work in and their practice of palliative care (P = 0.343). Recommendations were made on how to improve the practice of palliative care among professional nurses.

＂Intelligent＂ Knowledge Reuse for Complex Logistics Projects： An Application of Ontology-Driven and Case-Based Reasoning

The application potential of ontology-driven and CBR （case-based reasoning） is demonstrated for the business knowledge management particularly with respect to the reuse of knowledge of experience concerning logistics projects. The relevance of poorly structured, qualitative and especially in natural language represented knowledge is outlined for purposes of knowledge management, particularly with respect to the management of project-related knowledge. It is elucidated how this kind of knowledge can be preprocessed and reused with the support of a computer. At first, the technique of CBR is outlined in its basic fundamentals. Thereupon, it will be shown how the technique of ontologies can be used for the computer-supported processing of knowledge represented in natural language and integrated in computer-assisted CBR systems. A simple application example illustrates how ontology-driven and CBR can be used in practice within the reuse of project-related knowledge. Finally, it will be addressed which further need for research exists in principle.

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.

基于改进MORE协议的无线Mesh网络簇内路由研究

针对视频流传输中延时较大影响用户服务体验问题,本文在无线Mesh网络中以MORE(MAC-independent Opportunistic Routing&Encoding)协议为基础提出一种簇内路由协议,该协议对于MORE协议在传输中源节点和目的节点持续发送重传的问题,增添了拒绝确认机制,有效地节省了数据包传输过程中的时间,并通过改进MORE协议的编码方式,提出延时最小化网络编码,降低了系统整体的时延水平,保证了系统用户服务体验质量.仿真实验结果表明基于改进MORE协议的簇内路由协议能够有效地降低时延,达到较好的用户服务体验质量.

A Novel Deep Learning Method for Application Identification in Wireless Network

In modern wireless communication network, the increased consumer demands for multi-type applications and high quality services have become a prominent trend, and put considerable pressure on the wireless network. In that case, the Quality of Experience(Qo E) has received much attention and has become a key performance measurement for the application and service. In order to meet the users' expectations, the management of the resource is crucial in wireless network, especially the Qo E based resource allocation. One of the effective way for resource allocation management is accurate application identification. In this paper, we propose a novel deep learning based method for application identification. We first analyse the requirement of managing Qo E for wireless communication, and review the limitation of the traditional identification methods. After that, a deep learning based method is proposed for automatically extracting the features and identifying the type of application. The proposed method is evaluated by using the practical wireless traffic data, and the experiments verify the effectiveness of our method.

QoE-Driven Social Aware Caching Placement for Terrestrial-Satellite Networks

In remote terrestrial-satellite networks, caching is a very promising technique to alleviate the burden of space cloudlet(e.g., cache-enabled satellite user terminal) and to improve subscribers' quality of experience(Qo E) in terms of buffering delay and achievable video streaming rate. In this paper, we studied a Qo E-driven caching placement optimization problem for video streaming that takes into account the required video streaming rate and the social relationship among users. Social ties between users are used to designate a set of helpers with caching capability, which can cache popular files proactively when the cloudlet is idle. We model the utility function of Qo E as a logarithmic function. Then, the caching placement problem is formulated as an optimization problem to maximize the user's average Qo E subject to the storage capacity constraints of the helpers and the cloudlets. Furthermore, we reformulate the problem into a monotone submodular optimization problem with a partition matroid constraint, and an efficient greedy algorithm with 1-1 e approximation ratio is proposed to solve it. Simulation results show that the proposed caching placement approach significantly outperforms the traditional approaches in terms of Qo E, while yields about the same delay and hit ratio performance compare to the delay-minimized scheme.

HAS Dynamic Buffer-Driven Resource Management to Enhance QoE in Mobile Network

Hypertext transfer protocol(HTTP) adaptive streaming(HAS) plays a key role in mobile video transmission. Considering the multi-segment and multi-rate features of HAS, this paper proposes a buffer-driven resource management(BDRM) method to enhance HAS quality of experience(QoE) in mobile network. Different from the traditional methods only focusing on base station side without considering the buffer, the proposed method takes both station and client sides into account and end user's buffer plays as the drive of whole schedule process. The proposed HAS QoE influencing factors are composed of initial delay, rebuffering and quality level. The BDRM method decomposes the HAS QoE maximization problem into client and base station sides separately to solve it in multicell and multi-user video playing scene in mobile network. In client side, the decision is made based on buffer probe and rate request algorithm by each user separately. It guarantees the less rebuffering events and decides which HAS segment rate to fetch. While, in the base station side, the schedule of wireless resource is made to maximize the quality level of all access clients and decides the final rate pulled from HAS server. The drive of buffer and twice rate request schemes make BDRMtake full advantage of HAS's multi-segment and multi-rate features. As to the simulation results, compared with proportional fair(PF), Max C/I and traditional HAS schedule(THS) methods, the proposed BDRM method decreases rebuffering percent to 1.96% from 11.1% with PF and from 7.01% with THS and increases the mean MOS of all users to 3.94 from 3.42 with PF method and from 2.15 with Max C/I method. It also guarantees a high fairness with 0.98 from the view of objective and subjective assessment metrics.

Two-Phase Rate Adaptation Strategy for Improving Real-Time Video QoE in Mobile Networks

With the popularity of smart handheld devices, mobile streaming video has multiplied the global network traffic in recent years. A huge concern of users' quality of experience(Qo E) has made rate adaptation methods very attractive. In this paper, we propose a two-phase rate adaptation strategy to improve users' real-time video Qo E. First, to measure and assess video Qo E, we provide a continuous Qo E prediction engine modeled by RNN recurrent neural network. Different from traditional Qo E models which consider the Qo E-aware factors separately or incompletely, our RNN-Qo E model accounts for three descriptive factors(video quality, rebuffering, and rate change) and reflects the impact of cognitive memory and recency. Besides, the video playing is separated into the initial startup phase and the steady playback phase, and we takes different optimization goals for each phase: the former aims at shortening the startup delay while the latter ameliorates the video quality and the rebufferings. Simulation results have shown that RNN-Qo E can follow the subjective Qo E quite well, and the proposed strategy can effectively reduce the occurrence of rebufferings caused by the mismatch between the requested video rates and the fluctuated throughput and attains standout performance on real-time Qo E compared with classical rate adaption methods.

LED Adaptive Deployment Optimization in Indoor VLC Networks

Driven by the continuous penetration of high data rate services and applications,a large amount of unregulated visible light spectrum is used for communication to fully meet the needs of 6th generation(6G)mobile technologies.Visible light communication(VLC)faces many challenges as a solution that complements existing radio frequency(RF)networks.This paper studies the optimal configuration of LEDs in indoor environments under the constraints of illumination and quality of experience(QoE).Based on the Voronoi tessellation(VT)and centroidal Voronoi tessellation(CVT)theory,combined with the Lloyd’s algorithm,we propose two approaches for optimizing LED deployments to meet the illumination and QoE requirements of all users.Focusing on(i)the minimization of the number of LEDs to be installed in order to meet illumination and average QoE constraints,and(ii)the maximization of the average QoE of users to be served with a fixed number of LEDs.Monte Carlo simulations are carried out for different user distribution compared with hexagonal,square and VT deployment.The simulation results illustrate that under the same conditions,the proposed deployment approach can provide less LEDs and achieve better QoE performance.