Higher education quality assurance involves the formal assessment and analysis of performance monitoring processes and areas of progress. Within the scope of globalization, it is not possible to ensure credit transfer and student mobility, to address the needs of manpower, or to increase economic productivity without maintaining the performance of higher education programs. In a globalized framework of the job market, Engineering graduates should prove themselves as having a solid educational foundation and are being capable of leading the way in innovation, emerging technologies, and in anticipating the welfare and safety needs of the public. Generally, Quality assurance and improvement in higher education are achieved through accreditation. To name just two agencies; ABET, the EUR-ACE (European Accredited Engineer). Both agencies of them accredit also international programs.
As a student, your degree is a significant achievement and perhaps the largest investment you will make toward your future. The quality of education you receive makes a big difference in your career success. Accreditation:
- Verifies that your educational background meets the global standard for technical education in your profession.
- Enhances your employment opportunities in multinational companies.
- Paves the way for you to work globally.
As an institution, accreditation tells your prospective students, peers and the professions you serve that your program:
- Has received international recognition of its quality.
- Promotes “best practices” in education.
- Directly involves faculty and staff in self-assessment and continuous quality improvement processes.
- Is based on “learning outcomes,” rather than “teaching inputs.”
This talk will focus on ABET accreditation process, and will clarify the ways to go through all its stages. Nevertheless, if the institution choses to seek accreditation from any other agency, the procedures should not be much different, as the whole idea focus on i) satisfying a number of criteria ii) a thoroughly assessment process, and iii) a well-documented and published information.
Robot Operating System (ROS): How did it revolutionize robotics software development?
Robot Operating System (ROS) becomes nowadays the de-facto standard for developing robotics applications. The pre-birth initiatives were emerging from STanford AI Robot (STAIR) project and Personal Robots (PR) program, which aimed at creating dynamic software systems for robotics applications, until 2007 when Willow Garage, a major robotics investor, boosted the development of this initiative and contributed to the release of the first ROS software packages in 2009. The first version of ROS was released in 2010 and nowadays ROS becomes the largest ecosystem and platform for robotics software development. In just a few years of its release, ROS has witnessed a huge community with increasing number of users and developers from academia and industry, as well as hobbyists. How did ROS revolutionize robotics software development in just a few years?
In this presentation, I will give an overview of ROS and its evolution in the past years after its release. I will unveil the secrets of ROS that makes it a revolutionary solution for developing robotics applications. I will share my experience, as a computer scientists working on robotics, with developing robotics applications in the pre-ROS and post-ROS times, and how ROS made a complete shift in the software engineering and development approaches for mobile robots. The presentation will also give a small overview of the main concepts of ROS and the most important libraries and packages that comes with it. Video demonstrations and real illustrations will be presented.
Energy harvesting in smart industrial machines: Generating the energy you need from the sources you know
A smart system can be defined as a system incorporating sensing, actuation, control and communication, in order to adjust to or inform about the system’s context or own condition. Through technological advances, particularly in microelectronics, “smartness” has been demonstrated in a number of application domains, ranging from smart healthcare and smart homes, to smart cities and smart industries. To realize smartness on large scale, however, the energy supply to the necessary technologies is still a challenge. Batteries have been the go-to solution in cases where a fixed electrical infrastructure is infeasible or impossible. Batteries, however, have a limited energy capacity and lifetime, resulting in maintenance requirements that are typically undesirable at scale. Consequently, the conversion of ambient energy sources – commonly referred to as energy harvesting – is investigated as an alternative.
In this talk, an introduction as to what energy harvesting is, what it can be used for, and what challenges it faces, will be given. It will provide a holistic view, covering examples of energy sources to be exploited, conversion mechanisms to be utilized, and implementation aspects to be considered for system integration. During the talk, concrete cases of energy harvesting systems for smart industry applications will be explored in order to provide tangible examples. Moreover, open research challenges for energy harvesting and self-powered smart systems will be addressed, and an outlook on research trends given.
Hybrid Dynamical systems : a time scale approach
Immunity to change: Artificial Immune Systems (AIS) for Cyber-Physical Systems (CPS)
In cyber-physical systems (CPS), such as intelligent production and service systems (e.g. flexible/reconfigurable manufacturing systems), and intelligent transportation systems (public transportation and traffic control), change can have important impacts on organization, performance, quality of service and user safety and satisfaction. Change can be expected or unexpected. It can be related to product/service requirements and design, resource availability and reliability, process capability, and environment (natural, social, legal, economic) stability. For example, change in production systems may appear in the form of several kinds of disturbances (also called disruptions), such as supply unavailability, machine failures, tool breakage, workforce absenteeism, quality problems, rush orders, etc. In transportation systems, accidents, traffic congestion, or freeing the way to emergency vehicles (ambulances, firefighters, etc.) may disturb the fluidity of traffic and affect the expected execution of preset organization and pre-established timetables of public transportation resources (buses, trains, metros, trams, etc.). Thus, detecting disturbances on-line, and identifying their risky consequences timely are important tasks that enable advised decision-making and reaction to maintain performance and quality of service. The speech will provide an overview of artificial immune systems (AIS) as an artificial intelligence paradigm to achieve distributed and adaptive control of change and disturbances in CPS. A generic reactive decision-making framework will be presented, on-going developments in manufacturing and transportation systems will be described, and future research opportunities will be highlighted.