Unifying an Introduction to Artificial Intelligence Course through Machine Learning Laboratory Experiences

This paper presents work on a collaborative project funded by the National Science Foundation that incorporates machine learning as a unifying theme to teach fundamental concepts typically covered in the introductory Artificial Intelligence courses. The project involves the development of an adaptable framework for the presentation of core AI topics. This is accomplished through the development, implementation, and testing of a suite of adaptable, hands-on laboratory projects that can be closely integrated into the AI course. Through the design and implementation of learning systems that enhance commonly-deployed applications, our model acknowledges that intelligent systems are best taught through their application to challenging problems. The goals of the project are to (1) enhance the student learning experience in the AI course, (2) increase student interest and motivation to learn AI by providing a framework for the presentation of the major AI topics that emphasizes the strong connection between AI and computer science and engineering, and (3) highlight the bridge that machine learning provides between AI technology and modern software engineering

Introducing instrumentation and data acquisition to mechanical engineering students using LabVIEW

For several years, LabVIEW has been used within the Department of Mechanical Engineering at the University of Strathclyde as the basis for introducing the basic concepts and practice of data acquisition, and more generally, instrumentation, to postgraduate engineering students and undergraduate project students. The objectives of introducing LabVIEW within the curriculum were to expose students to instrumentation and experimental analysis, and to create courseware that could be used flexibly for a range of students. It was also important that staff time for laboratory work be kept to manageable levels. A course module was developed which allows engineering students with very little or no previous knowledge of instrumentation or programming to become acquainted with the basics of programming, experimentation and data acquisition. The basic course structure has been used to teach both undergraduates and postgraduates as well as laboratory technical staff. The paper describes the objectives of the use of LabVIEW for teaching, the structure of the module developed, and the response of students who have been subjected to the course, and how it is intended to expand the delivery to greater student numbers

Teaching Computational Fluid Dynamics (Cfd) To Design Engineers

© 2008 ASEEComputational Fluid Dynamics (CFD) can provide detailed thermal flow information, such as temperature field, pressure field and velocity field, in equipment and process in various industries. Due to the recent rapid growth of powerful computer resources and the development of commercial CFD software packages, CFD has been proven a useful tool for mechanical design engineers. CFD has also gained broad acceptance in the engineering education. It has been adopted in both undergraduate and graduate level courses in many universities. The teaching of CFD in current engineering education can be classified into two types, one is to focus on the numerical methods with little emphasis on using the software and the other is to introduce a CFD software as a virtual reality laboratory in Fluid Mechanics class without emphasis on teaching software. In the first type, students need strong mathematical background to succeed in the class and also need further training to effectively use modern commercial software for real industrial application. While in the second type, students only learned an abstract form of CFD processes, thus they will not be able to use CFD commercial software without further training in this area. This paper is about the use of CFD in teaching graduate students at this university who were in a two year design track program. Many of these students did not have a good background in mathematics, fluid dynamics, heat transfer, and programming, however, most of them were good at computer aided design in ProE and were very interested in learning CFD as a design tool in industries. STAR-CCM+ was chosen as the CFD software to teach students the entire CFD process in a single integrated software environment. After building a geometry model in ProE, students learned to import the CAD model, set up mesh model, physical model and solver, and postprocess the results in STAR-CCM+. Based on projects, CFD numerical methods and fundamentals of heat transfer and fluid flow were introduced to help students understand the CFD process, interpret, and validate simulation results

Load flow studies on stand alone microgrid system in Ranau, Sabah

This paper presents the power flow or load flow analysis of Ranau microgrid, a standalone microgrid in the district of Ranau,West Coast Division of Sabah. Power flow for IEEE 9 bus also performed and analyzed. Power flow is define as an important tool involving numerical analysis applied to power system. Power flow uses simplified notation such as one line diagram and per-unit system focusing on voltages, voltage angles, real power and reactive power. To achieved that purpose, this research is done by analyzing the power flow analysis and calculation of all the elements in the microgrid such as generators, buses, loads, transformers, transmission lines using the Power Factory DIGSilent 14 software to calculate the power flow. After the analysis and calculations, the results were analysed and compared

An investigation into the adoption of CDIO in distance learning

The Conceive, Design, Implement and Operate Initiative (CDIO) uses integrated learning to develop deep learning of the disciplinary knowledge base whilst simultaneously developing personal, interpersonal, product, process and system building skills. This is achieved through active and experiential learning methods that expose students to experiences engineers will encounter in their profession. These are incorporated not only in the design-build-test experiences that form a crucial part of a CDIO programme but also in discipline focused studies. Active and experiential learning methods are, of course, more difficult to incorporate into distance education. This paper investigates these difficulties and the implications in providing a programme that best achieves the goals of the CDIO approach through contemporary distance education methods. First, the key issues of adopting the CDIO approach in conventional oncampus courses are considered with reference to the development of the CDIO engineering programmes at the University of Liverpool. The different models of distance based delivery of engineering programmes provided by the Open University in the UK, and Deakin University and the University of Southern Queensland in Australia are then presented and issues that may present obstacles to the future adoption of the CDIO approach in these programmes are discussed. The effectiveness and suitability of various solutions to foreseen difficulties in delivering CDIO programmes through distance education are then considered. These include the further development, increased use and interinstitutional sharing of technology based facilities such as Internet facilitated access to laboratory facilities and computer aided learning (CAL) laboratory simulations, on campus workshops, and the development of a virtual engineering enterprise

Educating and Training Accelerator Scientists and Technologists for Tomorrow

Accelerator science and technology is inherently an integrative discipline that combines aspects of physics, computational science, electrical and mechanical engineering. As few universities offer full academic programs, the education of accelerator physicists and engineers for the future has primarily relied on a combination of on-the-job training supplemented with intense courses at regional accelerator schools. This paper describes the approaches being used to satisfy the educational interests of a growing number of interested physicists and engineers.Comment: 19 pages, 3 figure