Left to right: Bryan Delius (MS student) and Mike Heithaus going to their study sites, which occur from the mouth of the Shark River to 30 km upstream

This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. This image is made available for non-commercial or educational use only.

Early morning in a short-hydroperiod Everglades marsh (south of TS/Ph-1b), Taylor Slough

This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. This image is made available for non-commercial or educational use only.

Making chamber measurements of net ecosystem exchange in a short-hydroperiod Everglades marsh (at TS/Ph-1b), Taylor Slough

This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. This image is made available for non-commercial or educational use only.

Eddy covariance and meteorological tower in a long-hydroperiod Everglades marsh during the height of the wet season, 2008 (at SRS-2), Shark River Slough

This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. This image is made available for non-commercial or educational use only.

Long-hydroperiod Everglades marsh, wet season, 2008 (near SRS-2), Shark River Slough

This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. This image is made available for non-commercial or educational use only.

Eddy covariance tower in long-hydroperiod Everglades marsh in mid-dry season, 2009 (at SRS-2), Shark River Slough

This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. This image is made available for non-commercial or educational use only.

Long-hydroperiod Everglades marsh under extremely dry conditions, late dry season, 2009 (near SRS-2), Shark River Slough

This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. This image is made available for non-commercial or educational use only.

Bryan Delius (MS student, left) takes a small muscle plug from a bull shark with the help of Derek Burkholder (PhD student, right), Shark River

This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. This image is made available for non-commercial or educational use only.

Towards simulation and emulation of large-scale computer networks

Developing analytical models that can accurately describe behaviors of Internet-scale networks is difficult. This is due, in part, to the heterogeneous structure, immense size and rapidly changing properties of today's networks. The lack of analytical models makes large-scale network simulation an indispensable tool for studying immense networks. However, large-scale network simulation has not been commonly used to study networks of Internet-scale. This can be attributed to three factors: 1) current large-scale network simulators are geared towards simulation research and not network research, 2) the memory required to execute an Internet-scale model is exorbitant, and 3) large-scale network models are difficult to validate. This dissertation tackles each of these problems. ^ First, this work presents a method for automatically enabling real-time interaction, monitoring, and control of large-scale network models. Network researchers need tools that allow them to focus on creating realistic models and conducting experiments. However, this should not increase the complexity of developing a large-scale network simulator. This work presents a systematic approach to separating the concerns of running large-scale network models on parallel computers and the user facing concerns of configuring and interacting with large-scale network models. ^ Second, this work deals with reducing memory consumption of network models. As network models become larger, so does the amount of memory needed to simulate them. This work presents a comprehensive approach to exploiting structural duplications in network models to dramatically reduce the memory required to execute large-scale network experiments. ^ Lastly, this work addresses the issue of validating large-scale simulations by integrating real protocols and applications into the simulation. With an emulation extension, a network simulator operating in real-time can run together with real-world distributed applications and services. As such, real-time network simulation not only alleviates the burden of developing separate models for applications in simulation, but as real systems are included in the network model, it also increases the confidence level of network simulation. This work presents a scalable and flexible framework to integrate real-world applications with real-time simulation.^

Nonnative African jewelfish are more fit but not bolder at the invasion front: a trait comparison across an Everglades range expansion

This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. Any opinions, findings, conclusions, or recommendations expressed in the material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

Effects of Cooperative and Individual Integrated Learning System on Attitudes and Achievement in Mathematics

The purpose of this study was to determine the effects of a computer-based Integrated Learning Systems (ILS) model used with adult high school students engaging mathematics activities. This study examined achievement, attitudinal and behavior differences between students completing ILS activities in a traditional, individualized format compared to cooperative learning groups.

A Human Resource Development Performance Improvement Model for Workers with Mental Retardation in Supported Employment

This literature review discusses the factors for successful job retention of adult workers with mental retardation, including external factors related to work environments and internal issues of the individual worker. Through the synthesis of the literature, a performance improvement model for supported employment is discussed based on Holton’s (1999) human resource development/performance improvement model.

Near Term Computer Management Strategy For Hospitality Managers and Computer System Vendors

In his dialogue - Near Term Computer Management Strategy For Hospitality Managers and Computer System Vendors - by William O'Brien, Associate Professor, School of Hospitality Management at Florida International University, Associate Professor O’Brien initially states: “The computer revolution has only just begun. Rapid improvement in hardware will continue into the foreseeable future; over the last five years it has set the stage for more significant improvements in software technology still to come. John Naisbitt's information electronics economy¹ based on the creation and distribution of information has already arrived and as computer devices improve, hospitality managers will increasingly do at least a portion of their work with software tools.” At the time of this writing Assistant Professor O’Brien will have you know, contrary to what some people might think, the computer revolution is not over, it’s just beginning; it’s just an embryo. Computer technology will only continue to develop and expand, says O’Brien with citation. “A complacent few of us who feel “we have survived the computer revolution” will miss opportunities as a new wave of technology moves through the hospitality industry,” says ‘Professor O’Brien. “Both managers who buy technology and vendors who sell it can profit from strategy based on understanding the wave of technological innovation,” is his informed opinion. Property managers who embrace rather than eschew innovation, in this case computer technology, will benefit greatly from this new science in hospitality management, O’Brien says. “The manager who is not alert to or misunderstands the nature of this wave of innovation will be the constant victim of technology,” he advises. On the vendor side of the equation, O’Brien observes, “Computer-wise hospitality managers want systems which are easier and more profitable to operate. Some view their own industry as being somewhat behind the times… They plan to pay significantly less for better computer devices. Their high expectations are fed by vendor marketing efforts…” he says. O’Brien warns against taking a gamble on a risky computer system by falling victim to un-substantiated claims and pie-in-the-sky promises. He recommends affiliating with turn-key vendors who provide hardware, software, and training, or soliciting the help of large mainstream vendors such as IBM, NCR, or Apple. Many experts agree that the computer revolution has merely and genuinely morphed into the software revolution, informs O’Brien; “…recognizing that a computer is nothing but a box in which programs run.” Yes, some of the empirical data in this article is dated by now, but the core philosophy of advancing technology, and properties continually tapping current knowledge is sound.

Personal computer security system

This work consists on the design and implementation of a complete monitored security system. Two computers make up the basic system: one computer is the transmitter and the other is the receiver. Both computers interconnect by modems. Depending on the status of the input sensors (magnetic contacts, motion detectors and others) the transmitter detects an alarm condition and sends a detailed report of the event via modem to the receiver computer.