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Events Calendar



Events for the 4th week of May

  • PhD Defense - Yurong Jiang - Crowd-Sourced Collaborative Sensing in Highly Mobile Environments

    Mon, May 23, 2016 @ 11:00 AM - 01:00 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Yurong Jiang, PhD Candidate

    Talk Title: Crowd-Sourced Collaborative Sensing in Highly Mobile Environments

    Abstract: Title: Crowd-Sourced Collaborative Sensing in Highly Mobile Environments

    Location: SAL 213

    Time: 11am-1pm, May 23rd, 2016

    PhD Candidate: Yurong Jiang

    Committee Members:
    Ramesh Govindan (chair)
    Bhaskar Krishnamachari (outside member)
    Gaurav Sukhatme


    Abstract:

    Networked sensing has revolutionized various aspects of our lives. In particular, it has allowed us to minutely quantify many aspects of our existence: what we eat, how we sleep, how we use our time, and so forth. We have seen such quantification from the smart devices we use daily, such as smartphones and wearable devices. Those smart devices usually have more than ten high precision sensors to sense both internal and external information. Another domain that will likely to see such quantification in near future is automobiles. Modern vehicles are equipped with several hundred sensors that govern the operation of internal vehicular subsystems. Those sensors from both smart devices and automobiles, coupled with online information (cloud computing, maps, traffic, etc.) and other databases as well as crowd-sourced information from other users, can enable various forms of context sensing, and can be used to design new features for both mobile devices and vehicles. We abstract those aspects for context sensing into three parts: mobile and vehicular sensing, cloud assistance and crowdsourcing. Though each part itself comes with different challenges, accurate context sensing usually requires a careful combination of one or more of the three aspects, which brings new challenges for designing and developing context sensing systems. In this dissertation, we focus on three challenges, Programmability, Accuracy and Timeliness, in designing efficient and accurate context sensing system for mobile devices and vehicles. We will leverage the mobile and vehicle sensors, cloud information and crowdsourcing, collectively to ease context sensing programming, improve context sensing accuracy and timeliness.

    First, for Programmability, we focus on programming context descriptions using information from cloud and vehicle sensors. As more sensor-based apps are developed for vehicular platforms, we think many of these apps will be programmed using an event-based paradigm, where apps try to detect events and perform actions on detection. However, modern vehicles have several hundred sensors, these sensors can be combined in complex ways together with cloud information in order to detect some complicated context, e.g. dangerous driving. Moreover, these sensor processing algorithms may incur significant costs in acquiring sensor and cloud information. Thus, we propose a programming framework called CARLOG to simplify the task of programming these event detection algorithms. CARLOG uses Datalog to express sensor processing algorithms, but incorporates novel query optimization methods that can be used to minimize bandwidth usage, energy or latency, without sacrificing correctness of query execution. Experimental results on a prototype show that CARLOG can reduce latency by nearly two orders of magnitude relative to an unoptimized Datalog engine.

    Second, for Accuracy, we focus on automotive positioning accuracy. Positioning accuracy is an important factor for all kinds of context sensing applications for automobiles. Lane-level precise positioning of an automobile can improve navigation experience and on-board application context awareness. However, GPS by itself cannot provide such precision in obstructed urban environments. We propose a system called CARLOC for lane-level positioning of automobiles which carefully incorporates the three aspects in context sensing. CARLOC uses three key ideas in concert to improve positioning accuracy: it uses digital maps to match the vehicle to known road segments; it uses vehicular sensors to obtain odometry and bearing information; and it uses crowd-sourced location estimates of roadway landmarks that can be detected by sensors available in modern vehicles. CARLOC unifies these ideas in a probabilistic position estimation framework, widely used in robotics, called the sequential Monte Carlo method. Through extensive experiments, we show our system achieves sub-meter positioning accuracy even in obstructed environment, which is an order of magnitude improvement over a high-end GPS device.

    Finally, for context sensing applications, Timeliness is another important problem we need to take care of. We consider how to ensure the timeliness and availability of media content from mobile devices. Motivated by an availability gap for visual media, where images and videos are uploaded from mobile devices well after they are generated, we explore the selective, timely retrieval of media content from a collection of mobile devices. We envision this capability being driven by similarity-based queries posed to a cloud search front-end, which in turn dynamically retrieves media objects from mobile devices that best match the respective queries within a given time limit. We design and implement a general crowdsourcing framework called MediaScope that supports various geometric queries and contains a novel retrieval algorithm to maximize the retrieval of relevant information. In experiments on a prototype, our system achieves near optimal performance under different scenarios.


    Host: Yurong Jiang

    Location: Henry Salvatori Computer Science Center (SAL) - 213

    Audiences: Everyone Is Invited

    Posted By: Ryan Rozan

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  • USC Stem Cell Seminar: Brigid Hogan, Duke

    Tue, May 24, 2016 @ 11:00 AM - 12:00 PM

    Biomedical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Brigid Hogan, Duke

    Talk Title: The life of breath: Stem cells of the adult lung

    Series: Eli and Edythe Broad Center for Regenerative Medicine and Stem Cell Research at USC Distinguished Speakers Series

    Abstract: The lung is composed of a tree-like system of branched tubes lined by a mucociliary epithelium. These carry air into the millions of thin-walled, highly vascularized peripheral gas-exchange sacs known as alveoli. The mesenchyme of the lung also contributes important stromal components, including airway and alveolar smooth muscle, fibroblasts/lipofibroblasts and an extensive vascular network. Cell turnover in both epithelial and mesodermal compartments of the mouse lung is normally very low, but in response to specific injuries and viral and bacterial infections there is extensive proliferation and differentiation of progenitor cells in different anatomical regions. A major goal has been to use lineage tracing to identify the specific subtypes of progenitor cells that help to maintain the lung at steady state and to promote repair. This has revealed unexpected plasticity in epithelial cell fate in response to changes in their local environment. 3D organoid assays have been established to screen for small molecules and pathways regulating progenitor cell behavior. Most recently Crispr/Cas9 technology has been used to identify the function of genes implicated in epithelial cell morphogenesis and differentiation.

    Host: Francesca Mariani

    More Info: https://calendar.usc.edu/event/speaker_brigid_hogan_duke?utm_campaign=widget&utm_medium=widget&utm_source=USC+Event+Calendar%3A+Beta#.VvGY6HDFl04
    Webcast: http://keckmedia.usc.edu/stem-cell-semina

    Location: Eli & Edythe Broad CIRM Center for Regenerative Medicine & Stem Cell Resch. (BCC) - First Floor Conference Room

    WebCast Link: http://keckmedia.usc.edu/stem-cell-seminar

    Audiences: Everyone Is Invited

    Posted By: Cristy Lytal/USC Stem Cell

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  • The Multilevel Framework of System Safety: Foundational Research and Future Prospects

    Wed, May 25, 2016 @ 04:30 PM - 06:00 PM

    Astronautical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Mark S. Avnet, Assistant Professor of Industrial & Systems Engineering and Aerospace Engineering, Texas A&M University

    Talk Title: The Multilevel Framework of System Safety: Foundational Research and Future Prospects

    Series: SAE Distinguished Speaker Series

    Abstract: Although it is generally accepted that accidents in complex systems result from many interacting factors that are generally analyzed separately using methods from distinct disciplines, researchers have only scratched the surface in developing collaborative and holistic approaches to address system safety. Recent research provides a system-level perspective but does not fully incorporate the richness of disciplinary methods developed over several decades. Based on the historical timeline of methodological approaches and semi-structured interviews with safety experts, this research develops a framework for examining system safety from a multilevel perspective, including proximate technical causes, human error, organizational culture, and societal influences. At each level of the framework, a set of methods, tools, and disciplinary knowledge exists and has been widely applied. Each disciplinary perspective provides a unique lens with which to examine system safety. The framework provides a platform for interdisciplinary research and can serve as the basis for specific practical guidelines for design, management, accident investigation, and policymaking. The System Safety Database, intended as the engine for operationalizing the framework, will generate reports and provide essential information to those responsible for ensuring safety, investigating accidents, conducting system safety research, and/or managing hazardous systems. The framework and accompanying database will provide stakeholders at all levels, from operators to policymakers, with the tools and perspectives needed to improve safety in complex socio-technical systems.

    RSVP at the event link below.

    Biography: Mark S. Avnet is an Assistant Professor of Industrial and Systems Engineering and Aerospace Engineering at Texas A&M University. He is the director of the System Architecture and Management Laboratory, which conducts interdisciplinary research on an array of socio-technical systems and engineering design problems. Mark holds an S.B. in Physics from the Massachusetts Institute of Technology, an M.A. in Science, Technology, and Public Policy from The George Washington University, and a Ph.D. in Engineering Systems from MIT. He has worked in industry as a software developer and has served at NASA Centers and Headquarters in a variety of technical and policy roles. Before joining the faculty at Texas A&M, Mark was a management consultant with McKinsey and Company, where he focused on the design and implementation of operational improvement programs with an emphasis on manufacturing optimization, procurement, and organizational change in the aerospace industry. His current research focuses on the technical and organizational factors that influence safety in complex systems.

    Host: Prof. Azad Madni, INCOSE USC

    More Info: http://goo.gl/forms/2dbgE1twsd
    Webcast: https://bluejeans.com/249816249 ; Meeting ID: 249816249 ; Dial in: +1-888-240-2560

    More Information: May Speaker_Flyer.pdf

    Location: Ronald Tutor Hall of Engineering (RTH) - 526

    WebCast Link: https://bluejeans.com/249816249 ; Meeting ID: 249816249 ; Dial in: +1-888-240-2560

    Audiences: Everyone Is Invited

    Posted By: Azad Madni

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