The Chinese Consumers’Service Quality Satisfaction Differences of Cruise Tourism and Precision Marketing Strategy

The paper selected Chinese Cruise Line as the case study. Having based on the survey data of Chinese cruise tourism consumers, the factor analysis method, one-way analysis of variances method, cluster analysis method, and other quantitative and qualitative methods were taken to analyze Chinese consumers’ satisfaction differences of cruise tourism service quality with different segmentation markets and clusters markets, and the reasons of satisfaction differences were also explored. Then precision marketing strategy of Chinese cruise tourism with different segmentation markets and clusters markets from the supply-side reform perspective was discussed. The purpose of current research was to provide suggestions of precision management and precision marketing of Chinese cruise tourism for relevant enterprises and government departments.

Hybrid Chameleon and Honey Badger Optimization Algorithm for QoS-Based Cloud Service Composition Problem

Cloud computing facilitates the great potentiality of storing and managing remote access to services in terms of software as a service(SaaS).Several organizations have moved towards outsourcing over the cloud to reduce the burden on local resources.In this context,the metaheuristic optimization method is determined to be highly suitable for selecting appropriate services that comply with the requirements of the client’s requests,as the services stored over the cloud are too complex and scalable.To achieve better service composition,the parameters of Quality of Service(QoS)related to each service considered to be the best resource need to be selected and optimized for attaining potential services over the cloud.Thus,the cloud service composition needs to concentrate on the selection and integration of services over the cloud to satisfy the client’s requests.In this paper,a Hybrid Chameleon and Honey Badger Optimization Algorithm(HCHBOA)-based cloud service composition scheme is presented for achieving efficient services with satisfying the requirements ofQoS over the cloud.This proposed HCHBOA integrated the merits of the Chameleon Search Algorithm(CSA)and Honey Badger Optimization Algorithm(HBOA)for balancing the tradeoff between the rate of exploration and exploitation.It specifically used HBOA for tuning the parameters of CSA automatically so that CSA could adapt its performance depending on its incorporated tuning factors.The experimental results of the proposed HCHBOA with experimental datasets exhibited its predominance by improving the response time by 21.38%,availability by 20.93%and reliability by 19.31%with a minimized execution time of 23.18%,compared to the baseline cloud service composition schemes used for investigation.

QoS-Aware Cloud Service Optimization Algorithm in Cloud Manufacturing Environment

In a cloud manufacturing environment with abundant functionally equivalent cloud services,users naturally desire the highest-quality service(s).Thus,a comprehensive measurement of quality of service(QoS)is needed.Opti-mizing the plethora of cloud services has thus become a top priority.Cloud ser-vice optimization is negatively affected by untrusted QoS data,which are inevitably provided by some users.To resolve these problems,this paper proposes a QoS-aware cloud service optimization model and establishes QoS-information awareness and quantification mechanisms.Untrusted data are assessed by an information correction method.The weights discovered by the variable precision Rough Set,which mined the evaluation indicators from historical data,providing a comprehensive performance ranking of service quality.The manufacturing cloud service optimization algorithm thus provides a quantitative reference for service selection.In experimental simulations,this method recommended the optimal services that met users’needs,and effectively reduced the impact of dis-honest users on the selection results.

Quality of Service (QoS) Provisions in Wireless Sensor Networks and Related Challenges

Wireless sensor networks (WSNs) are required to provide different levels of Quality of Services (QoS) based on the type of applications. Providing QoS support in wireless sensor networks is an emerging area of research. Due to resource constraints like processing power, memory, bandwidth and power sources in sensor networks, QoS support in WSNs is a challenging task. In this paper, we discuss the QoS requirements in WSNs and present a survey of some of the QoS aware routing techniques in WSNs. We also explore the middleware approaches for QoS support in WSNs and finally, highlight some open issues and future direction of research for providing QoS in WSNs.

基于时间序列分析的Web Service QoS预测方法

通过网络提供服务的Web Service的服务质量会随着网络环境、服务器负载等因素的变化而变化,如何更好地帮助用户选择在未来一段时间内符合服务质量需求的Web Service,是目前服务计算领域中需要解决的关键问题之一。针对上述问题,提出了一种基于时间序列分析的Web Service QoS预测方法,并实现了相应的Web Service QoS自动预测工具。该工具能够根据Web Service的历史QoS数据,有效地预测未来短期内的QoS信息。以17832个Web Service的历史数据为基础,设计了相关实验,并验证了方法的有效性。

一种可扩展的Web Service QoS管理框架

Web Service是目前研究界和产业界广泛关注的技术之一.随着Web Service的广泛应用,研究者们普遍认识到,服务的非功能属性,即服务质量(Quality of Service,QoS)是面向服务的应用能否成功的关键因素之一.因此,研究者们尝试从多个角度对QoS相关问题展开了研究.然而,现有工作普遍关注基于QoS的动态服务选择和组装等上层应用技术,而对于如何获取、存储、度量QoS等基础支持技术研究较少,而这些基础性工作对QoS相关的研究工作具有显著的重要性.此外,不同应用领域对Web Service QoS的需求不尽相同,因此,需要有一套灵活的机制支持在QoS模型定义、QoS度量方法、QoS信息采集等方面体现出的领域特性.针对这个问题,文中提出了一个可扩展的Web Service QoS信息管理框架,详细分析了该框架涉及到的重要方法与核心技术,并给出了该框架在北京大学软件构件库系统中的设计决策和方案.最后,介绍了文中框架在一个863计划项目中的应用实例,该实例展示了用户根据其应用的领域需求对本框架进行扩展并进行Web Service QoS管理的方法,从而验证了本管理框架的可扩展性及实用性.

一种基于Web Service的分级QoS的研究与实现

随着WebService技术的广泛应用,QoS成为一个非常重要的问题.以服务响应时间为QoS参数,验证了一种基于WebService的分级QoS方法,提出了目标时间预设模型,并针对优化问题提出一种基于动态规划的解决方法,并实现了原型系统.实验数据表明这种方法有效地控制了负载平衡,实现了服务分级.

基于图卷积的多任务Web服务QoS预测

为满足用户对Web服务的高质量要求,提出一种基于图卷积的Web服务QoS预测算法,结合多任务学习使算法可以在一次预测中得到两种属性的QoS值。挖掘用户和服务之间隐藏的图结构信息,将用户和服务的编号信息转换成嵌入向量,得到初始特征,经过图卷积与特征融合处理操作获得更深层的特征信息,经过降噪自编码器对特征进行重构,提高算法的鲁棒性。在公开的QoS调用数据集上进行实验,并与3种方法对比,实验结果表明,该算法在各项评价指标上总体表现更好,为图神经网络在QoS预测方向的研究提供了思路。

Web Services内部架构对QoS的影响

为了研究Web Services的内部构建对Web Services服务质量(QoS)的影响,设计了对应的ACTTest程序来分析Web Services内部构建中的字符串连接连接方法、数据库操作方式、序列化、输出缓存、调用开销及集群等对Web Services的QoS影响,结果表明Web Services内部构建对QoS有着重要影响。实验结果对优化Web Services的内部架构和网络结构,提高网络及WS的性能和可扩展性具有重要意义。

基于代理的Web Services QoS模型研究

服务质量(QoS)描述了服务满足消费者需求的能力,提供有保证的QoS是Web服务在商业应用中获得成功的关键。本文分析了Web Services QoS的特点和实现过程,提出一种更适合于Web Services环境下的QoS建模过程,提出一种基于代理的有QoS保障的Web Services模型。通过在传统的Web Services架构的基础上进行扩展,增加一个代理,充分发挥代理技术的灵活性、可扩充性、可重用性等优点。将QoS的相关工作完全交给代理来完成,实现一个改进的Web Services QoS架构。

一种环境因素敏感的WebServiceQoS监控方法

面向服务系统的执行能力依赖第三方提供的服务,在复杂多变的网络环境中,这种依赖会带来服务质量(QoS)的不确定性.而QoS是衡量第三方服务质量的重要标准,因此,有效监控QoS是对Web服务实现质量控制的必要过程.现有监控方法都未考虑环境因素的影响,比如服务器位置、用户使用服务的位置和使用时间段负载等,而这些影响在实际监控中是存在的,忽略环境因素会导致监控结果与实际结果有悖.针对这一问题,提出了一种基于加权朴素贝叶斯算法w BSRM(weightednaive Bayes running monitoring)的Web Service QoS监控方法.受机器学习分类方法的启发,通过TF-IDF(term frequency-inverse document frequency)算法计算环境因素的影响,通过对部分样本进行学习,构建加权朴素贝叶斯分类器.将监控结果分类,满足QoS标准为c_0,不满足QoS标准为c_1,监控时调用分类器得到c_0和c_1的后验概率之比,对比值进行分析,可得监控结果满足QoS属性标准、不满足QoS属性标准和不能判断这3种情况.在网络开源数据以及随机数据集上的实验结果表明:利用TF-IDF算法能够准确地估算环境因子权值,通过加权朴素贝叶斯分类器,能够更好地监控QoS,效率显著优于现有方法.

一种改进近端优化的多目标流QoS调度策略

软件定义网络可以搭载灵活的流调度策略来提升网络服务系统的服务质量,但随着业务流量复杂度的提升,现有的流调度算法会因场景匹配度的下降而导致性能受到影响。为此提出一种基于深度强化学习的智能路由策略。该策略通过软件定义网络收集各链路信息,基于长短期记忆网络与近端策略优化算法实现特征提取与状态感知,最终决策生成符合业务场景下服务质量(quality of service,QoS)目标的动态流量调度策略,并实现QoS最大化。实验结果表明,所提的方案与现有的路由策略相比可以使整套系统QoS指标提升7.06%,有效地提升了业务系统的吞吐率。

Trade-offs and synergies between ecosystem services in Yutian County along the Keriya River Basin,Northwest China

The Keriya River Basin is located in an extremely arid climate zone on the southern edge of the Tarim Basin of Northwest China,exhibiting typical mountain-oasis-desert distribution characteristics.In recent decades,climate change and human activities have exerted significant impacts on the service functions of watershed ecosystems.However,the trade-offs and synergies between ecosystem services(ESs)have not been thoroughly examined.This study aims to reveal the spatiotemporal changes in ESs within the Keriya River Basin from 1995 to 2020 as well as the trade-offs and synergies between ESs.Leveraging the Integrated Valuation of Ecosystem Services and Trade-offs(InVEST)and Revised Wind Erosion Equation(RWEQ)using land use/land cover(LULC),climate,vegetation,soil,and hydrological data,we quantified the spatiotemporal changes in the five principal ESs(carbon storage,water yield,food production,wind and sand prevention,and habitat quality)of the watershed from 1995 to 2020.Spearman correlation coefficients were used to analyze the trade-offs and synergies between ES pairs.The findings reveal that water yield,carbon storage,and habitat quality exhibited relatively high levels in the upstream,while food production and wind and sand prevention dominated the midstream and downstream,respectively.Furthermore,carbon storage,food production,wind and sand prevention,and habitat quality demonstrated an increase at the watershed scale while water yield exhibited a decline from 1995 to 2020.Specifically,carbon storage,wind and sand prevention,and habitat quality presented an upward trend in the upstream but downward trend in the midstream and downstream.Food production in the midstream showed a continuously increasing trend during the study period.Trade-off relationships were identified between water yield and wind and sand prevention,water yield and carbon storage,food production and water yield,and habitat quality and wind and sand prevention.Prominent temporal and spatial synergistic relationships were observed between different ESs,notably between carbon storage and habitat quality,carbon storage and food production,food production and wind and sand prevention,and food production and habitat quality.Water resources emerged as a decisive factor for the sustainable development of the basin,thus highlighting the intricate trade-offs and synergies between water yield and the other four services,particularly the relationship with food production,which warrants further attention.This research is of great significance for the protection and sustainable development of river basins in arid areas.

Spatiotemporal variations in ecosystem services and their trade-offs and synergies against the background of the gully control and land consolidation project on the Loess Plateau,China

Studying the spatiotemporal variations in ecosystem services and their interrelationships on the Loess Plateau against the background of the gully control and land consolidation(GCLC)project has significant implications for ecological protection and quality development of the Yellow River Basin.Therefore,in this study,we took Yan'an City,Shaanxi Province of China,as the study area,selected four typical ecosystem services,including soil conservation service,water yield service,carbon storage service,and habitat quality service,and quantitatively evaluated the spatiotemporal variation characteristics and trade-offs and synergies of ecosystem services from 2010 to 2018 using the Integrated Valuation of Ecosystem Services and Trade-offs(InVEST)model.We also analysed the relationship between the GCLC project and regional ecosystem service changes in various regions(including 1 city,2 districts,and 10 counties)of Yan'an City and proposed a coordinated development strategy between the GCLC project and the ecological environment.The results showed that,from 2010 to 2018,soil conservation service decreased by 7.76%,while the other three ecosystem services changed relatively little,with water yield service increasing by 0.56% and carbon storage service and habitat quality service decreasing by 0.16% and 0.14%,respectively.The ecological environment of Yan'an City developed in a balanced way between 2010 and 2018,and the four ecosystem services showed synergistic relationships,among which the synergistic relationships between soil conservation service and water yield service and between carbon storage service and habitat quality service were significant.The GCLC project had a negative impact on the ecosystem services of Yan'an City,and the impact on carbon storage service was more significant.This study provides a theoretical basis for the scientific evaluation of the ecological benefits of the GCLC project and the realization of a win-win situation between food security and ecological security.

Effectiveness of Short Message Service Support on Adherence to Chemotherapy Treatment among Patients Attending Cancer Treatment Facilities in Kenya

Introduction: Cancer is a chronic debilitating disease that unnerves patients, communities, and nations. At some point in cancer patient’s disease experience, chemotherapy is used, and the patient is expected to adhere to treatment to improve survival and quality of life. Methods: This multisite Cluster Randomized Trial (CRT) evaluated the effectiveness of mobile phone Short Message Service (SMS) support on the adherence to treatment schedules among adult cancer patients in Kenya. Data was collected using questionnaires. Ethical approvals were obtained from relevant Ethical Review Boards (ERBs). Results: The mean adherence was 83%. There was a significant difference between treatment arms in relation to the adherence. The intervention arm had a higher mean adherence difference, M = 3.913, 95% CI 2.632-5.193, t (402) = 6.006, p ≤ 0.001), with Cohen’s d = 0.60. Although not significant, (χ2dd = 0.151, df = 1, p = 2.064), more women were perfect adheres than males. Perfect adherers were satisfied with SMS support (χ2dd = 7.620, df = 1, p = 0.06), were in the intervention arm (χ2dd = 22.942, df = 1, p ≤ 0.001), and had trust in the care provider (χ2dd = 10.591 p ≤ 0.001). SMS support was not significant in the multivariate analysis but had an estimated effect size of 0.958 (z = 1.424, p = 0.154, CI = 0.242-3.781), indicating that mean adherence was slightly better in the presence of the intervention. Conclusions: SMS-support intervention has demonstrated superiority in influencing adherence. Further, health system-related factors have a significant influence on the adherence to chemotherapy treatment. Interventions to re-design health systems that are responsive to unmet care needs of cancer patients must be explored. .

QoS驱动的Web services动态计价机制研究

结合Web services的服务质量(QoS)因素和用户经验,对Web services的计价机制进行研究,提出一种QoS驱动的Web services动态计价模型,描述其计价过程,并给出相应的实现算法。通过对模型的简单实现,经测试这一计价模型在准确性和合理性上具有一定优势。

Review on Service Curves of Typical Scheduling Algorithms

In recent years,various internet architectures,such as Integrated Services(IntServ),Differentiated Services(DiffServ),Time Sensitive Networking(TSN)and Deterministic Networking(DetNet),have been proposed to meet the quality-of-service(QoS)requirements of different network services.Concurrently,network calculus has found widespread application in network modeling and QoS analysis.Network calculus abstracts the details of how nodes or networks process data packets using the concept of service curves.This paper summarizes the service curves for typical scheduling algorithms,including Strict Priority(SP),Round Robin(RR),Cycling Queuing and Forwarding(CQF),Time Aware Shaper(TAS),Credit Based Shaper(CBS),and Asynchronous Traffic Shaper(ATS).It introduces the theory of network calculus and then provides an overview of various scheduling algorithms and their associated service curves.The delay bound analysis for different scheduling algorithms in specific scenarios is also conducted for more insights.

Spatiotemporal variations of ecosystem services and driving factors in the Tianchi Bogda Peak Natural Reserve of Xinjiang,China

Nature reserves play a significant role in providing ecosystem services and are key sites for biodiversity conservation.The Tianchi Bogda Peak Natural Reserve(TBPNR),located in Xinjiang Uygur Autonomous Region,China,is an important ecological barrier area in the temperate arid zone.The evaluation of its important ecosystem services is of great significance to improve the management level and ecological protection efficiency of the reserve.In the present study,we assessed the spatiotemporal variations of four ecosystem services(including net primary productivity(NPP),water yield,soil conservation,and habitat quality)in the TBPNR from 2000 to 2020 based on the environmental and social data using the Integrated Valuation of Ecosystem Services and Trade-offs(InVEST)model.In addition,the coldspot and hotspot areas of ecosystem services were identified by hotspot analysis,and the trade-off and synergistic relationships between ecosystem services were analyzed using factor analysis in a geographic detector.During the study period,NPP and soil conservation values in the reserve increased by 48.20%and 25.56%,respectively;conversely,water yield decreased by 16.56%,and there was no significant change in habitat quality.Spatially,both NPP and habitat quality values were higher in the northern part and lower in the southern part,whereas water yield showed an opposite trend.Correlation analysis revealed that NPP showed a synergistic relationship with habitat quality and soil conservation,and exhibited a trade-off relationship with water yield.Water yield and habitat quality also had a trade-off relationship.NPP and habitat quality were affected by annual average temperature and Normalized Difference Vegetation Index(NDVI),respectively,while water yield and soil conservation were more affected by digital elevation model(DEM).Therefore,attention should be paid to the spatial distribution and dynamics of trade-off and synergistic relationships between ecosystem services in future ecological management.The findings of the present study provide a reference that could facilitate the sustainable utilization of ecosystem services in the typical fragile areas of Northwest China.

基于改进和声搜索的配电网WSNs多路径QoS路由算法

针对智能配电网(Smart distribution network,SDN)中无线通信数据传输不可靠且网络寿命低等问题,提出一种基于改进和声搜索的无线传感器网络(Wireless sensor networks,WSNs)多路径QoS路由算法(Multipath QoS routing algorithm,MQRA)。首先,分析配电网的通信需求并建立数据传输模型;然后,针对无线传感器路由问题的特点对和声搜索算法(Harmony search,HS)做出改进;再将其自适应参数公式进行改进以避免算法陷入局部最优;通过在源节点与目的节点之间构建前传区域来优化转发节点集以避免数据回传,提升算法的运行效率;最后,在初始和声库生成阶段,综合考虑距离、丢包率以及节点剩余能量来改进轮盘法中的概率公式。仿真结果表明MQRA算法能有效降低数据传输的时延,提升数据可靠性并均衡节点能耗延长网络使用寿命。

云服务推荐中基于多源特征和多任务学习的时序QoS预测

随着云计算技术的普及,云服务数量指数级增长,用户不再满足于功能性需求,服务质量(Quality of Service,QoS)成为比较服务优劣的关键性能指标.如何在动态、复杂的云环境中实时、准确地预测服务质量并为用户推荐高质量服务成为热点问题.考虑到云服务器的负载、网络状态、用户接入云环境的偏好等随着时间变化,本文提出了基于多源特征和多任务学习的时序QoS预测方法(T-MST),它可以实时、准确地同时预测多种QoS属性.首先,TMST对用户、服务进行特征表示,通过Time2Vec刻画时序特征,再结合多种QoS属性的历史记录生成多源特征表示.其次,基于滑动窗口采用LSTM感知窗口内的时序关系,借助注意力机制细化窗口内不同时刻的关键性,从而构造待预测时刻的隐藏状态.最后,T-MST采用多任务预测层实现多种QoS属性的同时预测,它们共享上游模型,仅在预测层采用不同的感知模块以提升模型的鲁棒性和计算效率.本文基于真实世界的数据集进行了全面的实验验证,结果表明T-MST在吞吐量和响应时间的时序预测任务上平均绝对误差(Mean Absolute Error,MAE)分别平均提升了37.53%和20.38%,优于现有的时序QoS预测方法;而且TMST的计算效率更高,能够有效应对实时QoS预测的需求.