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Events for August 22, 2013
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Six Sigma Green Belt for Process Improvement
Thu, Aug 22, 2013 @ 09:00 AM - 05:00 PM
Executive Education
Conferences, Lectures, & Seminars
Speaker: TBA, Viterbi School of Engineering
Talk Title: Six Sigma Green Belt for Process Improvement
Abstract: Learn how to integrate principles of business, statistics and engineering to achieve tangible results. Master the use of Six Sigma to quantify the critical quality issues in your company. Once the issues have been quantified, statistics can be applied to provide probabilities of success and failure. Six Sigma methods increase productivity and enhance quality. As a Six Sigma green belt, you will be equipped to support and champion a Six Sigma implementation in your organization. To earn the Six Sigma Green Belt Certificate, you will be required to pass the Institute of Industrial Engineer's green belt exam (administered on the final day of the course).
During this course you will have the opportunity to apply what you have learned to an actual issue you face in your organization. Prior seminar participants have reported significant savings from implementing their projects.
*A financial services organization saw $128,000 in cost savings per quarter when they reduced transaction processing rework
*A state agency reduced project cost over-runs by 28 percent
*A transportation company saved more than $875,000 per year in turnover costs by improving the employee communications process
*Reduced errors in a painting operation led to increased first pass acceptance and more than $197,000 in annual savings
*A Web developer increased annual profits by 10 percent by cutting cycle time
*A wave solder operation saw defects reduced by half and costs reduced by $60,000 per year
Host: Corporate and Professional Programs
More Info: http://gapp.usc.edu/professional-programs/short-courses/industrial%2526systems/six-sigma-green-belt-process-improvement
Location: Olin Hall of Engineering (OHE) -
Audiences: Registered Attendees
Contact: Viterbi Professional Programs
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New Student Welcome Luau
Thu, Aug 22, 2013 @ 11:30 AM - 02:00 PM
Viterbi School of Engineering Student Affairs
Receptions & Special Events
Aloha!
All new undergraduate engineering students are invited to attend the annual New Student Luau. Join faculty, staff, and current Viterbi students as we enjoy some island-style food and fun! New students will meet each other, learn about getting involved in Viterbi student organizations, interact with faculty from each engineering department, and be in the class photo!Location: Engineering Quad
Audiences: Undergrad
Contact: Christine D'Arcy
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PhD Defense - Chengjie Zhang
Thu, Aug 22, 2013 @ 01:00 PM - 03:00 PM
Thomas Lord Department of Computer Science
University Calendar
Design of Cost-Efficient Multi-Sensor Collaboration in Wireless Sensor Networks
committee
Chair:
John Heidemann
Member:
Ramesh Govindan
Bhaskar Krishnamachari
Recent years have witnessed an increasing demand for monitoring tasks in industrial applications. Although effective in some applications, sensornet uptake has been slow in this emerging area, as shown by slow sensornet deployment in industry. Industries prefer well-tested but often expensive or complex sensing solutions because they provide known levels of accuracy, but this choice makes many problems uneconomic. The sensornet research community has made significant progress towards real-world applications with some pilot deployments. While sensornet research is promising, current prototypes are often not cost-effective or still in the early stages. Industry remains slow to adopt these approaches, because they are not seen to address concerns about accuracy for industry-relevant problems.
In this thesis, we propose Multi-Sensor Collaboration to achieve low-cost yet accurate event detection and enable sensornet usage in cost-sensitive industrial applications. We find that four advantages of collaboration improve cost-effectiveness. First, collaborative sensing can improve accuracy by suppressing false alarms with redundant or heterogeneous sensors. Second, collaborative sensing reduces capital cost by enabling low-cost sensors to be accurate enough to reach actionable results. Third, collaboration can reduce deployment cost, because it enables non-invasive sensing to provide sufficient accuracy with much less expensive installation. Finally, auto-tuning is important to reduce deployment costs, and collaborative sensing can assist auto-tuning by allowing sensors in different modalities to tune each other with their unique information.
The thesis of this proposed dissertation is that Multi-sensor collaboration enables sensor networks to accomplish real-world event detection tasks that are impractical for single-sensor systems. To frame the application domain, we categorize sensing applications by their two orthogonal propertiesâ collaboration scheme and sensing modality. Collaboration scheme, namely the relationship between sensors, is usually in two distinctive formsâcompetitive and complementary. Competitive collaboration means redundantly suppressing less accurate sensors’ results; complementary collaboration combines all relevant sensors’ partial results to form the final result. Modality means the type of the raw input of a sensor. To explore the application domain, we study both collaborations with either modality choice in three example applications. First, we evaluate signature matching in a vehicle classification context to study single-modal competitive collaboration. Second, we present a design of steam-choke blockage-detection system to study single-modal complementary collaboration. Finally, we implement and evaluate a detection system for oil-retrieval-line blockage to extend our complementary type study to multi-modality. We prove sensor collaboration can achieve cost-efficiency in the forgoing three specific applications. These applications are useful and allow deployment of sensing where not possible before. Further, the commonality between these applications and a large group of relevant applications strongly suggest that collaborative sensing help a larger application domain.
Location: Henry Salvatori Computer Science Center (SAL) - 322
Audiences: Everyone Is Invited
Contact: Lizsl De Leon
