Context-Aware Service IVlodes in the Cloud Computing Environment

This paper discussed the differences of context-aware service between the cloud computing environment and the traditional service system.Given the above differences,the paper subsequently analyzed the changes of context-aware service during preparation,organization and delivery,as well as the resulting changes in service acceptance of consumers.Because of these changes,the context-aware service modes in the cloud computing environment change are intelligent,immersive,highly interactive,and real-time.According to active and responded service,and authorization and non-authorized service,the paper drew a case diagram of context-aware service in Unified Modeling Language(UML) and established four categories of context-aware service modes.

Context-aware computing-based reducing cost of service method in resource discovery and interaction

Reducing cost of service is an important goal for resource discovery and interaction technologies. The shortcomings of transhipment-method and hibernation-method are to increase holistic cost of service and to slower resource discovery respectively. To overcome these shortcomings, a context-aware computing-based method is developed. This method, firstly, analyzes the courses of devices using resource discovery and interaction technologies to identify some types of context related to reducing cost of service, then, chooses effective methods such as stopping broadcast and hibernation to reduce cost of service according to information supplied by the context but not the transhipment-method’s simple hibernations. The results of experiments indicate that under the worst condition this method overcomes the shortcomings of transhipment-method, makes the “poor” devices hibernate longer than hibernation-method to reduce cost of service more effectively, and discovers resources faster than hibernation-method; under the best condition it is far better than hibernation-method in all aspects.

Context-aware Workflow Model for Supporting Composite Workflows

在最近的年里，几个研究人员在无所不在的计算 environments.However 上为服务自动化使用了工作流技术，上下文知道的 oprkflows 不提供一个方法填写几工作流以便得到更大规模或复杂的 workflow.They 的大多数仅仅提供一个简单工作流模型，不是合成工作流 model.In 这份报纸， autorhs 建议一个上下文知道的 worrkflow

A CAWL handler for context-aware composite workflow services

In distributed computing environment,workflow technologies have been continuously developed.Recently,there is an attempt to apply these technologies to context-aware services in ubiquitous computing environment.The middleware,which offers services in such environments,should support the automation services suited for the user using various types of situational information around the user.In this paper,based on context-aware workflow language(CAWL),we propose a CAWL based composite workflow handler for supporting composite workflow services,which can integrate more than two service flows and handle them.The test results shows that the proposed CAWL handler can provide the user with the composite workflow services to cope with various demands on a basis of a scenario document founded on CAWL.

Adaptive Service Selection Method in Mobile Cloud Computing

Despite the rapid advances in mobile technology,many constraints still prevent mobile devices from running resource-demanding applications in mobile environments.Cloud computing with flexibility,stability and scalability enables access to unlimited resources for mobile devices,so more studies have focused on cloud computing-based mobile services.Due to the stability of wireless networks,changes of Quality of Service(QoS) level and user' real-time preferences,it is becoming challenging to determine how to adaptively choose the"appropriate"service in mobile cloud computing environments.In this paper,we present an adaptive service selection method.This method first extracts user preferences from a service's evaluation and calculates the similarity of the service with the weighted Euclidean distance.Then,they are combined with user context data and the most suitable service is recommended to the user.In addition,we apply the fuzzy cognitive maps-based model to the adaptive policy,which improves the efficiency and performance of the algorithm.Finally,the experiment and simulation demonstrate that our approach is effective.

A Generic Service Architecture for Secure Ubiquitous Computing Systems

The development of ubiquitous computing systems benefits tremendously from the service-oriented computing concept in seamless interoperation of heterogeneous devices. However, architectures, services interfaces and network implementation of the existing service-oriented systems differ case by case. Furthermore, many systems lack the capability of being applied to resource constrained devices, for example, sensors. Therefore, we propose a standardized approach to present a service to the network and to access a networked service, which can be adopted by arbitrary types of devices. In this approach, services are specified and exposed through a set of standardized interfaces. Moreover, a virtual community concept is introduced to determine a secure boundary within which services can be freely discovered, accessed and composed into applications;a hierarchical management scheme is presented which enables the third party management of services and their underlying resources. In this way, application control logic goes into the network and environment context is dealt with intelligently by the system. A prototype system is developed to validate our ideas. Results show the feasibility of this open distributed system software architecture.

基于上下文提取与注意力融合的遮挡服装图像分割

针对遮挡服装图像分割准确率低的问题,提出一种融合上下文提取与注意力机制的遮挡服装图像实例分割方法。以Mask R-CNN为基础网络,首先采用上下文提取模块优化ResNet的输出特征,通过融合不同速率的多路径特征从多个感受野中捕获图像的上下文信息,强化遮挡服装特征表示的识别及提取能力;然后引入通道注意力机制与空间注意力机制的残差连接,自适应地专注于捕捉遮挡服装图像的空间和通道维度上的语义相互依赖关系,降低上下文提取模块在处理特征图时因冗余的上下文关系扩大造成误定位与误识别的概率;最后,采用目标检测损失函数CIoU计算原理作为非极大值抑制的评判标准,关注预测框和真实框的重叠与非重叠区域,最大程度地选择遮挡服装的最优目标框,使预测框更加贴近真实框。结果表明,与其它方法相比,改进方法显著改善了不同遮挡程度服装图像的误分割现象,能提取出更精确的服装实例,其对遮挡服装图像的平均分割精度比原模型提升了4.4%。

属性偏序形式结构的数学形式化

属性偏序形式结构,作为一种基于人类认知原理和粒计算思想的知识发现和知识表示新理论,目前已有广泛的应用,但其理论基础缺乏抽象化数学化,这势必影响该理论的系统发展。针对上述问题,研究了属性偏序形式结构的数学形式化描述问题。首先,基于粒计算的思想提出了知识表示的形式化框架。在此基础上,通过定义对象集合的覆盖和最简覆盖,给出属性偏序形式结构的粒和粒群的概念,进而通过对粒衍生出粒群的充要条件的讨论,给出了属性偏序形式结构中的知识结构,从而完成属性偏序形式结构的数学形式化描述。最后,通过具体实例展示了利用数学形式化描述构造属性偏序形式结构的过程,并揭示了该过程所体现的人类认知规律。

数字化背景下计算机公共课程教学方法探索

在数字化背景下,我国提出要实施国家教育数字化战略行动,推动新工科等领域的人才培养和对应课程的高质量建设。于是,计算机公共基础课程作为建设“四新”学科的重要支撑,其数字化转型、改革和应用必将得到更多的关注,同时也将面临新的挑战和机遇。该文总结目前的大学计算机公共基础课程教学中存在的问题,并探讨在教育数字化转型背景下对该课程的教学改革思路,重点在于如何通过大数据、人工智能等结合新兴的数字化技术分析学生的学习过程、教师的教学过程及二者的交流过程,促进教师的教学能力及学生对计算机知识的自主学习和综合运用能力,并尝试以数字技术为依托改革课程体系和教学模式,实现计算机公共基础课程教学的数字化转型。

海量层次信息的Focus+Context交互式可视化技术

综述了海量层次信息可视化与Focus+Context技术的相关工作,针对海量层次信息可视化的交互问题,在嵌套圆可视化技术的基础上提出了基于上下文感知的Focus+Context交互式可视化技术.首先,基于外切圆排列方法提出对圆心进行三角网格剖分的方法,为变形计算建立上下文;然后,针对变形计算前后上下文一致性问题,在三角网格邻居跟踪方法的基础上,提出了用于同层兄弟节点上下文感知的外切圆变形排列方法,以及用于父子节点上下文感知的嵌套圆迭代排列方法.实验结果表明。上述方法在实现焦点突出的鱼眼视图的同时,能够有效地解决Focus+Context交互式可视化的上下文感知问题.上述方法应用于文件系统海量层次信息的交互式可视化问题,提供了交互式可视化工具.

面向信息可视化的语义Focus+Context人机交互技术

大数据成为继云计算和物联网之后,国际学术界和产业界所共同瞩目的又一个研究热点.信息可视化是辅助用户洞悉大数据背后隐藏的知识和规律的重要方法和有力工具.如何在图形用户界面中对大规模信息以符合认知规律的方式进行可视化,并且使得计算机能够智能化的理解用户意图以配合其进行高效的人机交互,是信息可视化面临的挑战之一.文中提出一种面向信息可视化的语义Focus+Context人机交互技术.首先,在基于空间距离的经典Focus+Context数学模型基础上对其进行语义建模和扩展,建立了面向信息空间和可视化表征空间的语义距离模型以及语义关注度模型,定义了交互中的焦点对象与语义上下文.其次,在此基础上建立了语义Focus+Context用户界面模型,给出了界面抽象元素和实体元素以及映射关系的形式化描述,同时建立了Focus+Context交互循环机制.最后,给出了应用于经典Focus+Context及鱼眼数学模型的描述,表明文中提出方法具有很好的兼容性描述能力;同时,给出了面向文件系统主题聚集的语义Focus+Context应用,给出了基于主题语义关注度与嵌套圆鱼眼视图的动态可视化实例,应用实例表明文中提出技术能够有效支持用户在信息可视化界面中对大规模信息进行智能化的可视化和交互探索.

Adaptive Mobile Applications to Dynamic Context

Context-aware computing is a mobile computing paradigm in which applications can discover and take advantage of contextual information, such as user location, time of the day, nearby people and devices, and user activity. This paper intends to study the context-awareness in depth and demonstrate the usefulness of this new technology through two mobile applications that are adaptive to dynamic context.

An Application of Context Middleware Based on Fuzzy Logic for Wireless Sensor Networks

The research of context-aware computing based on wireless sensor network (WSN) aims at intelligently connecting computers, users, and environment. So its application system should be flexibly adaptable to dynamic changes of context and application requirements and proactively provides the information satisfied with current context for users. The middleware can be very effective to provide the support runtime services for context-aware computing. In this paper we propose middleware architecture for context processing. This architecture is based on fuzzy logic control (FLC) system for context reasoning and sensor fusion. We propose a formal context representation model in which a user’s context is described by a set of roles and relations correspond to a context space. A middleware prototype has been developed, which detect tourist’ physical context and provide reminding. The experiments prove that the model and approach proposed are feasible.

Context-Based Mobile User Interface

Context awareness is increasingly gaining applicability in interactive ubiquitous mobile computing systems. Each context-aware application has its own set of behaviors to react to context modifications. Hence, every software engineer needs to clearly understand the goal of the development and to categorize the context in the application. We incorporate context-based modifications into the appearance or the behavior of the interface, either at the design time or at the run time. In this paper, we present application behavior adaption to the context modification via a context-based user interface in a mobile application. We are interested in a context-based user interface in a mobile device that is automatically adapted based on the context information. We use the adaption tree, named in our methodology, to represent the adaption of mobile device user interface to various context information. The context includes the user’s domain information and dynamic environment changes. Each path in the adaption tree, from the root to the leaf, presents an adaption rule. An e-commerce application is chosen to illustrate our approach. This mobile application was developed based on the adaption tree in the Android platform. The automatic adaption to the context information has enhanced human-computer interactions.

大智移云背景下企业财务数智化转型路径研究

在“大智移云”时代背景下,大数据、云计算、人工智能、物联网等新一代信息技术迅速发展,并与各行各业进行了深度融合,不仅带动了企业财务管理数字化转型的全面升级,也给企业财务管理带来了新的机遇与挑战。文章以“大智移云”背景下企业财务数智化转型为研究对象,从财务数智化的背景与转型必要性出发,分析财务数智化转型“三大进程”的整体规划,并基于此从确定财务数智化平台建设目标、围绕“五化”推动财务数智化转型两大方面提出了企业财务数智化转型的路径,以期为推动企业财务数智化转型提供参考。

情景感知驱动的移动对象多模式轨迹预测技术综述

如何利用多源异构时空数据进行准确的轨迹预测并且反映移动对象的移动特性是轨迹预测领域的核心问题.现有的大多数轨迹预测方法是长序列轨迹模式预测模型,根据历史轨迹的特点进行预测,或将当前移动对象的轨迹位置放入时空语义场景根据历史移动对象轨迹预测位置.综述当前常用的轨迹预测模型和算法,涉及不同的研究领域.首先,阐述了多模式轨迹预测的主流工作,轨迹预测的基本模型类;其次,对不同类的预测模型进行总结,包括数学统计类、机器学习类、滤波算法,以及上述领域具有代表性的算法;再次,对情景感知技术进行了介绍,描述了不同领域的学者对情景感知的定义,阐述了情景感知技术所包含的关键技术点,诸如情景感知计算、情景获取和情景推理的不同类模型,分析了情景感知的不同分类、过滤、存储和融合以及它们的实现方法等.详细介绍了情景感知驱动的轨迹预测模型技术路线及各阶段任务的工作原理.给出了情景感知技术在真实场景中的应用,包括位置推荐,兴趣点推荐等,通过与传统算法对比,分析情景感知技术在此类应用中的优劣.详细介绍了情景感知结合LSTM(long short-term memory)技术应用于行人轨迹预测领域的新方法.最后,总结了轨迹预测和情景感知研究的当前问题和未来发展趋势.

国内外计算思维教育的研究脉络与实践比较

计算思维是信息社会所必备的素养,不仅是发达国家课程计划的重要内容,也是我国强国战略所需人才的核心素养。计算思维的培养与形成离不开有效的教学实践,因此国内外针对计算思维教学实践形成了各具特色的研究思路,对于计算思维实践成效的评价也取得了一定的成果。本研究从数量、地区分布、重要成果等多个方面梳理了国内外计算思维教育研究的缘起、发展和趋势的基本脉络。通过对计算思维教育的宏观发展路向、中观的实践活动过程、微观的评价方法和评价工具的比较与研究,厘清了计算思维教育研究的问题与走向。

覆盖多粒度下的形式概念更新方法

多粒度形式概念分析是数据挖掘与知识发现的重要工具。文中研究了覆盖多粒度下的形式概念的粗化和细化更新方法。首先,举例说明了现有的概念粗化更新算法可能导致概念缺失,通过分析缺失概念的本质特征,对现有概念粗化算法进行补充,并证明了新算法的正确性。其次,举例说明了现有的概念细化更新算法可能会生成冗余概念,通过分析冗余细概念的内涵特性,对现有的概念细化更新算法进行了优化,并证明了新算法生成结果的无冗余性,具有更低的时间复杂度。最后,通过实验验证了所提算法的有效性。

介粒度空间中的最优粒度选择和属性约简

以往的形式概念分析采用介粒度形式背景,满足对数据跨层粒化的需求,但其既没有将寻找最优粒度和属性约简有效结合起来,又没有在多粒度的背景下高效地解决组合爆炸问题。为此,基于介粒度中粒度选择和属性约简的联系,提出了一种新的最优粒度选择方式——最优粒度约简,以同步进行粒度选择和属性约简。鉴于寻找最优粒度约简存在组合爆炸的问题,设计了逐步搜索方法,通过已搜索的信息更新粒度空间,去除大量非最优粒度约简,显著提高了搜索效率。实验结果表明了所提方法的有效性和优势。