Providing Reliable Data Transport for Dynamic Event Sensing in Wireless Sensor Networks

In this paper, we propose a Loss Tolerant Reliable (LTR) data transport mechanism for dynamic Event Sensing (LTRES) in WSNs. In LTRES, a reliable event sensing requirement at the transport layer is dynamically determined by the sink. A distributed source rate adaptation mechanism is designed, incorporating a loss rate based lightweight congestion control mechanism, to regulate the data traffic injected into the network so that the reliability requirement can be satisfied. An equation based fair rate control algorithm is used to improve the fairness among the LTRES flows sharing the congestion path. The performance evaluations show that LTRES can provide LTR data transport service for multiple events with short convergence time, low lost rate and high overall bandwidth utilization.

Spatio-Temporal Event Model for Cyber-Physical Systems

The emerging Cyber-Physical Systems (CPSs) are envisioned to integrate computation, communication and control with the physical world. Therefore, CPS requires close interactions between the cyber and physical worlds both in time and space. These interactions are usually governed by events, which occur in the physical world and should autonomously be reflected in the cyber-world, and actions, which are taken by the CPS as a result of detection of events and certain decision mechanisms. Both event detection and action decision operations should be performed accurately and timely to guarantee temporal and spatial correctness. This calls for a flexible architecture and task representation framework to analyze CP operations. In this paper, we explore the temporal and spatial properties of events, define a novel CPS architecture, and develop a layered spatiotemporal event model for CPS. The event is represented as a function of attribute-based, temporal, and spatial event conditions. Moreover, logical operators are used to combine different types of event conditions to capture composite events. To the best of our knowledge, this is the first event model that captures the heterogeneous characteristics of CPS for formal temporal and spatial analysis.

Maxwell Arboretum Anniversary Celebration

What a pleasure it is to have this opportunity to welcome you to campus today as we celebrate the 35th anniversary of the Earl G. Maxwell Arboretum. Henry Van Dyke once wrote that "He that planteth a tree ... provideth a kindness for many generations, and faces that he hath not seen shall bless him."

Opening Remarks for Master Conservationist Presentations

It is a distinct honor for me to help recognize the 2003 Master Conservationists tonight. Tonight's event marks the 20th anniversary of the program sponsored by the Omaha World-Herald and the Institute of Agriculture and Natural Resources at the University of Nebraska-Lincoln.

ARDC 10th Anniversary/Building Renaming

Thank you for being with us today as we celebrate both the 10th anniversary of this great building and its new name.

SCREC District VIP Event

Folks, it's a great treat to have this opportunity to share with you how we in the Institute of Agriculture and Natural Resources are at work for Nebraska. I want to talk with you a little bit today about that work, our land-grant university history, and where our vision for Nebraska's future is taking us.

Haskell Agricultural Laboratory 50th Anniversary Celebration

Today we celebrate 50 years of work done here at the Haskell Agricultural Laboratory for Nebraska. Work that addresses issues of great importance here. Work that matters. As your land-grant university, it is a point of pride for us to celebrate work done for our state. We are at work for Nebraska. That's our heritage. It's why we're here.

Model complexity affects transient population dynamics following a dispersal event: A case study with pea aphids

Stage-structured population models predict transient population dynamics if the population deviates from the stable stage distribution. Ecologists’ interest in transient dynamics is growing because populations regularly deviate from the stable stage distribution, which can lead to transient dynamics that differ significantly from the stable stage dynamics. Because the structure of a population matrix (i.e., the number of life-history stages) can influence the predicted scale of the deviation, we explored the effect of matrix size on predicted transient dynamics and the resulting amplification of population size. First, we experimentally measured the transition rates between the different life-history stages and the adult fecundity and survival of the aphid, Acythosiphon pisum. Second, we used these data to parameterize models with different numbers of stages. Third, we compared model predictions with empirically measured transient population growth following the introduction of a single adult aphid. We find that the models with the largest number of life-history stages predicted the largest transient population growth rates, but in all models there was a considerable discrepancy between predicted and empirically measured transient peaks and a dramatic underestimation of final population sizes. For instance, the mean population size after 20 days was 2394 aphids compared to the highest predicted population size of 531 aphids; the predicted asymptotic growth rate (λmax) was consistent with the experiments. Possible explanations for this discrepancy are discussed. Includes 4 supplemental files.