II-New: Infrastructure to Support Integrated Research and Education in Socially Intelligent Computing at Missouri S&T

由于缺乏专用和现实的基础设施，国际社会在社会智能计算方面进行原创性和实用性研究的努力在范围、规模和质量方面受到了阻碍。社会智能计算是一种新兴的重要范式，以整合人和计算机，创造以前仅靠人类或计算机无法实现的新形式的协作、通信和智能。这项提案要求提供资金，在PI的机构中建立这样一个基础设施，以支持综合研究和教育。所要求的基础设施包括高端计算和存储服务器、台式计算机、笔记本电脑、智能电话、传感器、照相机、软件和配件，用于从社会与互联网和移动电话的日常互动中产生的大规模数据中收集、处理和提取知识。总体目标是利用从社会计算数据中获得的知识，创建一系列造福社会的实用服务和应用程序。特别是，提案中确定了三个强调社会与技术的紧密结合的研究项目：a)通过挖掘互联网使用数据来检测大学环境中的抑郁障碍；b)通过挖掘互联网和智能手机的使用来对人类进行“指纹识别”；以及c)通过融合不同种类的传感器数据来跟踪社交世界中的人类。智力价值计划中的研究活动被很好地描述了，可能会极大地推动社交智能计算的技术水平。PI开创了挖掘真实互联网数据来检测大学生抑郁行为的先河。他之前的研究已经确定了关键的互联网使用特征，这些特征在有抑郁症状的学生和没有抑郁症状的学生之间显示出强烈的统计差异。他下一步计划利用计算智能技术设计分类器，这种分类器可以高精度地主动检测大学生的抑郁行为，同时保持透明和保护隐私。他还在探索挖掘互联网使用模式以识别人类指纹的可行性，并将其应用于互联网取证和减轻内部攻击。类似的技术将被应用于从智能手机中挖掘传感器数据，以便提取指纹移动模式，并为各种普及服务奠定基础。虽然传统的跟踪算法要么利用摄像机网络，要么利用物理传感数据或电子信号，PI计划追求一种融合多个正交数据源的集成方法，并结合用于室外和室内环境中的人类跟踪的新的特征提取和模式识别技术。广泛影响该项目在不同领域的应用，包括心理健康筛查、内部攻击和欺诈预防、电话和车辆盗窃检测、参与式传感等。研究成果将定期与心理学、执法、法医、商业等不同的利益相关者分享。PI及其团队在网络、安全和计算机视觉方面的课程将通过该项目的内容得到加强，基础设施将帮助学生通过实践经验学习。研究结果、学习材料和团队经验将通过会议和网络定期向广大受众(包括HBCU和K-12的教育工作者和学生)传播。

The PI's efforts to conduct original and practical research in socially intelligent computing - an emerging and important paradigm centered on integrating people and computers to create new forms of collaboration, communication, and intelligence previously unachievable by humans or computers alone - have been hindered, in scope, scale and quality, by the lack of a dedicated and realistic infrastructure. This proposal requests funds to set up such an infrastructure at the PI's institution, which will support integrated research and education. The infrastructure requested includes high-end computational and storage servers, desktop machines, laptops, smart phones, sensors, cameras, software and accessories for collecting, processing and extracting knowledge from large scale data arising from the daily interactions of society with the Internet and with mobile phones. The overall goal is to utilize the knowledge gained from social computing data to create a spectrum of practical services and applications benefitting society. In particular, three research projects that emphasize the close integrations of society with technology are identified in the proposal: a) Detection of depressive disorders in college settings by mining Internet usage data; b) Human "fingerprinting" by mining Internet and smart phone usage; and c) Tracking humans in the social world by fusing heterogeneous sensor data.Intellectual MeritThe planned research activities are well described and will likely significantly advance the state of the art in socially intelligent computing. The PI has pioneered the mining of real Internet data to detect depressive behavior in college students. His prior research has identified critical Internet usage features that show strong statistical differences between students with and without depressive symptoms. He next plans to design, using computational intelligence techniques, classifiers which can proactively detect depressive behavior in college students with high accuracy while being transparent and preserving privacy. He is also exploring the feasibility of mining Internet usage patterns to fingerprint humans, with applications to Internet forensics and mitigation of insider attacks. Similar techniques will be applied to mine sensor data from smart phones in order to fingerprint mobility patterns and to lay the foundation for a variety of pervasive services. While conventional tracking algorithms leverage either a network of cameras or physical sensory data or electronic signals, the PI plans to pursue an integrated approach that fuses multiple orthogonal data source and which incorporates novel feature extraction and pattern recognition techniques for human tracking in both outdoor and indoor environments.Broader ImpactThis project has applications in diverse areas including mental health screening, insider attack and fraud prevention, phone and vehicle theft detection, participatory sensing etc. Research outcomes will be shared periodically with diverse stakeholders in psychology, law enforcement, forensics, business, etc. The courses taught by the PI and his team in networking, security and computer vision will be enhanced with content deriving from this project, and the infrastructure will help students learn by practical experience. Research findings, learning materials and team experiences will be disseminated periodically to a wide audience (including educators and students in HBCUs and K-12) via conferences and the Web.