关键词： 位置感知计算   轨迹数据挖掘   GPS室外定位   WiFi室内定位  

摘要： 如今智能手机的发展发生了质的飞越,无论是硬件技术还是软件技术,双核、四核智能手机在现今的人们看来已是很平常,操作系统也在更新换代,对于人工智能已不是遥不可及。智能手机平台上的各种应用给人们提供了极大的便利。因此,利用智能手机来实现数字化轨迹感知正是适应了这一主流趋势,充分拓展了智能手机的应用范围。随着人们对4A(anything,anywhere,anybody,anytime)位置信息的需求不断增加,当前实时位置信息已成为人们最受关注的服务之一,现如今人们的活动范围越来越大,随之而来的是越来越多的不确定性。这种移动性和不确定性给数字化轨迹研究带来了更多可能性,也让位置感知计算推进了一大步。该技术通过GPS和WiFi进行结合,在不同的情景下使用不同的定位方式,以移动设备终端进行数据采集,对行为轨迹信息结构设计和语义化,便于用户进行行为轨迹信息的分析查询。

关键词： 物联网技术   移动计算   人脸识别  

摘要： 水利工程管理中的日常巡查非常重要,为此也出台了一系列的巡查办法,但现有的巡查模式多基于人工,效率较低。利用物联网技术、移动计算及人脸识别等技术手段,开发基于B/S架构的智能巡检系统,该系统可以提高水利工程巡查效率,确保工程持续安全、可靠运行。

关键词： Computation offloading   Mobile cloud   Complexity-aware   Context-aware   Makespan  

摘要： Mobile cloud computing is the emerging paradigm to improve mobile device computation issues using cloud resources. Computation offloading is an efficient way of transferring certain tasks from mobile devices to the cloud. The computationally intensive task of the mobile application executes on the remote cloud. In computational offloading, the decision making plays a vital role to decide whether a task to be offloaded to the cloud or to execute in the local side. The existing research focused either on the offloading part of the cloud side or the context of mobile devices. However, this paper considered both the cloud side and the mobiles side to make the efficient decision offloading decision. This paper proposes a novel multi-objective efficient offloading decision framework for supporting computational offloading based on the mobile applications' complexity and the context of mobile devices. The main purpose of this framework is to improve the mobile devices, which executes the high computational task that consumes the high battery power and CPU utilization. The proposed framework dynamically explores and decides the optimal cloud by using the enhanced particle swarm optimization algorithm. Moreover, this paper reduces the battery power consumption, virtual machine cost and makespan of the task for providing the quality of services.

关键词： Creativity   Mobile computing platforms   User-driven innovations   Travel journals  

摘要： Web 2.0 code-free interfaces and mobile computing platforms allow consumers to creatively create content and share with their peers. As a result, numerous user-driven innovation-oriented communities started to emerge. Nowadays, these communities are available through smartphones. Especially in the field of tourism these platforms started to reshape marketing practices as well as tourist behaviour. Therefore, this study analysed a mobile computing travel platform by integrating creativity theory and platform engagement to explain this phenomenon. First, the study demonstrates users' innovative traits influencing their online behaviour. Second. for marketers this study illustrates the importance of an effective working environment to support consumers producing user-driven innovate as well as the opportunities to attract highly innovative users. (C) 2017 Elsevier Inc. All rights reserved.

关键词： Big-Data-as-a-Service   Cloud Computing   Content Delivery   Mobile-Edge Computing   Quality of Service   Resource-Constraint  

摘要： The overwhelming growth of resource-intensive and latency-sensitive applications trigger challenges in legacy systems of mobile cloud computing (MCC) architecture. Such challenges include congestion in the backhaul link, high latency, inefficient bandwidth usage, insufficient performance, and quality of service (QoS) metrics. The objective of this study was to find out the cost-efficient design that maximizes resource utilization at the edge of the mobile network which in return minimizes the task processing costs. Thus, this study proposes a cooperative mobile edge computing (coopMEC) to address the aforementioned challenges in MCC architecture. Also, in the proposed approach, resource-intensive jobs can be unloaded from users' equipment to MEC layer which is potential for enhancing performance in resource-constrained mobile devices. The simulation results demonstrate the potential gain from the proposed approach in terms of reducing response delay and resource consumption. This, in turn, improves performance, QoS, and guarantees cost-effectiveness in meeting users' demands.

关键词： 语音情感识别   特征提取   模板匹配   移动终端   安卓  

摘要： 近年来,情感识别技术备受人工智能领域研究者的关注,因为它可以极大改善人机交互系统的用户体验,从而进一步提升产品的用户粘性。考虑到智能手机等移动终端设备使用的便利性,设计一种基于安卓(Android)移动平台的实时性语音情感识别系统。该系统能够实时性地采集说话人的语音,并对每一句语音提取基音频率、振幅、频谱能量分布等情感特征参数,然后采用模板匹配方法判别每一句语音的情感类型,输出说话人的语音情感识别结果。该系统将语音采集、特征提取、情感判别模型与Android系统有机结合,并具有实时性和识别性能较高的特点。

关键词： GPS室外定位   WIFI室内定位   Android开发  

摘要： 近几年,伴随着智能手机的迅速发展,智能手机行业已经非常成熟,并且智能手机已经趋于一个稳定的方向发展。特别是近两年,市场对高端手机的需求不断增加,智能手机向着创新和高端化方向发展。因此,智能手机的功能也越来越丰富,智能手机的硬件技术和软件技术都有了质的飞跃,移动设备平台上的各种功能应用给我们提供了极大的便利。所以,利用移动设备来实现数字化轨迹感知技术就是应了这一时代主流趋势,充分拓展了移动设备的应用范围。数字化轨迹正是用到了智能手机里的集成GPS传感器和WIFI感知功能。

关键词： Electrical and Computer Engineering   Mobile computing Energy conservation  

摘要： Mobile computing is one of the largest untapped reservoirs in today's pervasive computing world as it has the potential to enable a variety of in-situ, real-time applications. However, the domain of mobile computing suffers from the constraints of limited resources such as device battery, CPU, and memory while at the same time users' expectations in terms of response times, accuracy, and data rates are increasing at a fast pace. As a result, achieving high energy efficiency while main- taining a high quality of service is a crucial challenge. Many of the mobile applications that are pervasive in our lives–such as localization, object/activity recognition, and mobile gaming to name a few–are expected to perform seamlessly with near-instantaneous responses, but are also affected by the same constraints. Current solutions based on offloading computationally-intensive applica- tions from resource-constrained mobile devices to powerful remote computing platforms (such as the Cloud) or nearby mobile devices, suffer from uncertainty in wireless network connectivity or availability of devices in proximity, respectively. To overcome the limitation of current works, the paradigm of approximate computing emerges as a solution to enable resource-intensive mobile applications in resource-constrained environment. Approximate computing reduces the amount of computation that an application is expected to per- form, as a result of which the execution time reduces, which in turn reduces the energy consumption of the application. The gain achieved via reduction in energy consumption, however, comes with a potential loss in the accuracy of the results (within acceptable limits). By leveraging approximate computing, we achieve dynamically a tradeoff between accuracy (or optimality of the results pro- duced by an application) and utilization of the available resources (such as battery, CPU cycles, memory, and I/O data rate). The goal of this thesis is to design new techniques so as to en

关键词： Enterprise mobility   Smartphone apps   Application development   Smartphone email   Remote computing   Codeless application development  

摘要： The adoption of mobile devices, particularly smartphones, has grown steadily over the last decade, also permeating the enterprise sector. Enterprises are investing heavily in mobilization to improve employee productivity and perform business workflows, including smartphones and tablets. Enterprise mobility is expected to be more than a $250 billion market in 2019. Strategies to achieve mobilization range from building native apps, using mobile enterprise application platforms (MEAPS), developing with a mobile backend as a service (mBaaS), relying on application virtualization, and employing application refactoring. Enterprises are not yet experiencing the many benefits of mobilization, even though there is great promise. Email and browsing are used heavily, but the practical adoption of enterprise mobility to deliver value beyond these applications is in its infancy and faces barriers. Enterprises deploy few business workflows (<5 percent). Barriers include the heavy task burden in executing workflows on mobile devices, the irrelevance of available mobile features, non-availability of necessary business functions, the high cost of network access, increased security risks associated with smartphones, and increased complexity of mobile application development. This dissertation identifies key barriers to user productivity on smartphones and investigates user-aware solutions that leverage redundancies in user behavior to reduce burden, focusing on the following mobility aspects: (1) Workflow Mobilization: For an employee to successfully perform workflows on a smartphone, a mobile app must be available, and the specific workflow must survive the defeaturization process necessary for mobilization. While typical mobilization strategies offer mobile access to a few heavily-used features, there is a long-tail problem for enterprise application mobilization, in that many application features are left unsupported or are too difficult to access. We propose a do-it-yourself (DI

摘要： Intelligent Sensing as a novel methodology for user-centered research; development of new services and applications based on human sensing, computation, and problem solving; engineering of improved Intelligent Sensing platforms including quality control mechanisms; incentive design of work; usage of Participatory Sensing for professional business; and theoretical frameworks for evaluation (Xu et al. 2017a, b, c, d). Feature fusion methods research based on deep belief networks for speech emotion recognition under noise condition. Energy-efficient analysis of an IEEE 802.11 PCF MAC protocol based on WLAN.