Distance education programs in Information Technology (IT) suffer from several unique challenges. First, technology equipment like computers, routers, switches, and Information Security hardware is expensive and could easily consume a large portion of a department's annual budget. Second, suitable access to the equipment by students is often limited to normal faculty workdays, excluding evenings and weekends. Finally, adapting labs for delivery through any means other than the traditional classroom environment is extremely difficult in terms of resources, development time, and commitment from faculty and administrators. In this paper, the authors present an in-house solution that was developed to allow students to reserve computers, routers, and switches via the internet; conduct their hands-on exercises at their convenience, save/restore their configurations and exercises, and automatically restore the equipment to neutral state for the next user.
In this paper, we establish the need (based on literature and anecdotal evidence) for an infrastructure for CS1 courses to visually support problem solving from the initial problem statement to the code. Then, we describe how using Unified Modeling Language supported by CASE software (Rational Rose) can be used with carefully prepared course materials (selected projects, prepared databases, written lab manuals), to create this infrastructure. The advantage of this infrastructure is that it can be used throughout the student's academic career in software development to support problem solving and collaborative learning. The authors' extensive experience in developing and teaching the Software Engineering and IT courses were the major factor in implementation of the Object-Orientation with Unified Modeling Language in entry level software development courses.
The information technology (IT) field is perhaps one of the most dynamic professions in modern history.Rapid advances in technology, along with dynamic nature of IT content have placed colleges and universities in a major predicament relative to procuring needed equipment and maintaining currency. On one hand, there is an increased need for trained IT professionals with current skills; on the other hand there is a major threat as academic institution are unable to meet the market demands due to limitation of available resources. Our solution to this challenge was to create an avenue for institutions to share resources in very innovative and mutually beneficial ways. In the wake of budget cuts and shrinking resources, our solution will ultimately allow schools to capitalize on the technologies available at each institution by pooling them into a large network of heterogeneous facilities that can be accessed over the Internet. A key feature of this process is the fact that everything is handled automatically by our locally developed in-house solution, thus freeing instructors of the burden of trying to locate needed resources for their students
Model estimation and prediction of a river flow system are investigated using nonlinear system identification techniques. We demonstrate how the dynamics of the system, rainfall, and river flow can be modeled using NARMAX (Nonlinear Autoregressive Moving Average with eXogenuous input) models. The parameters of the model are estimated using an orthogonal least squares algorithm with intelligent structure detection. The identification of the nonlinear model is described to represent the relationship between local rainfall and river flow at Enoree station (inputs) and river flow at Whitmire (output) for a river flow system in South Carolina.
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