HCC: Small: Integrating User Context and Conceptual Perceptions for Understandable Wireless Access on Open-Platform Smartphones

该项目将提供算法和工具包，使最终用户在动态无线接入网络上使用开放平台智能手机时获得更好的应用体验。一个新的基于模型的诊断引擎，帮助用户了解的访问问题，应用程序的性能下降。认知感知反馈完成了一个执行-评估循环，使用户能够构建对故障排除过程和根本原因的正确概念感知。智能手机与定制的软件将分发进行用户研究，并评估用户互动的有效性时，处理无线接入问题。正式的因果关系和状态模型相结合的杠杆，以解决复杂的无线接入问题。一个独特的贡献是集成应用程序级的用户上下文与网络级的诊断模型，用户的移动性和物理环境是无线接入性能的重要因素。机器学习算法用于使用来自设备上传感器的噪声数据进行鲁棒的上下文推断。Norman的认知框架被用于在具有有限输入方法的小屏幕智能手机上迭代呈现和感知故障排除过程。这项工作填补了向移动的用户提供诊断工具的差距。该项目的成功将产生新的感知工具，这些工具可以通过移动的应用程序商店直接向公众传播，以显著增强当今智能手机上经常误导的信号指示器。将开发一个互动的基于网络的教育门户网站，以更好地让学生参与进来，并将通过麻省大学洛厄尔分校的继续教育和企业教育部推出在线课程模块，以接触IT专业人员。

This project will provide algorithms and toolkits to empower end users for better application experience when using open-platform smartphones over dynamic wireless access networks. A novel model-based diagnosis engine helps users to understand the access problems as application performance degrades. The cognition-aware feedback completes an execution-evaluation loop for the users to construct correct conceptual perceptions of the troubleshooting process and the root cause. Smartphones with customized software will be distributed to conduct user studies and evaluate the user-interaction effectiveness when dealing with wireless access problems.The combination of formal causality and state models is leveraged to troubleshoot complex wireless access problems. A unique contribution is to integrate application-level user context with network-level diagnostic models, as user mobility and physical environment are important factors of wireless access performance. Machine-learning algorithms are used for robust context inference using noisy data from on-device sensors. Norman's cognition framework is used for iterative presentation and perception of the troubleshooting process on small-screen smartphones with limited input methods.This work fills in the gap of providing diagnostic tools to the mobile users. The success of this project will result in new perception tools, which can be disseminated directly to the public through mobile application stores, to significantly enhance the often-misleading signal indicator on smartphones today. An interactive Web-based education portal will be developed to better involve students and online course modules will be introduced through UMass Lowell's Division of Continuing Studies and Corporate Education to reach IT professionals.