Dr. Khalid Ammar received his Ph.D degree in Electrical Engineering from University of Sherbrooke, Canada, and a Master of Engineering degree from Concordia University, Montreal Canada. Dr. Khalid Ammar worked on the design and the implementation of highly specialized computer system for biomedical applications at Sherbrook Medical Devices Research Group, Sherbrook, Canada. He previously worked with Nortel Networks, Ottawa, Canada as a senior ASIC applications Engineer, provided design guidance and expertise to Nortel design community through the ASIC design flow. Dr. Khalid Ammar affiliated with Electrical and Computer Engineering department where he taught several electrical and computer engineering courses. His areas of interest are VLSI and Embedded Systems.
Continuous assessment of the program learning outcomes (PLOs) is a fundamental part of a higher education program for program improvement and desirable to maintain the requirements of accreditation bodies. Accreditation bodies provide considerable flexibility to institutions to show how the assessment are carried out, which is generally carried out by assessing the course learning outcomes (CLOs) and mapping CLOs to PLOs. While this provides an indication of which PLO is achieved and which needs attention, it risks missing out many fine-grained aspects of the learning outcomes. In this paper, we identify specific performance indicators (PIs) for each dimension for every PLO to precisely measure all individual performance criterion within the various dimensions of a PLO which leads to a proper remedial action for the program continuous improvement. We share the experiences learnt while developing and implementing this model for our program, with the updated Accreditation Board for Engineering and Technology (ABET) student learning outcomes (SLO) 1-7.
Traffic injuries and deaths are important road traffic issues worldwide, road accidents are a major reason of death, killing around 1.24 million people yearly and leaving 20–50 million be distressed with injuries, traffic accidents are still considered the prime factor in cause of mortality between 5–14 years old children and among 15–29 years old young adults . These numbers could have been reduced if the vehicles had been travelling at more appropriate speed. The most commonly reported factors linked to the severity of accidents and deaths are due to reckless speeding or drivers may drive within the speed limits, but they are not aware of the sudden changes on road condition that could affect their safety and the safety of other road users. In response to the needed speed limit enforcement to save lives, health, and economy, this work presents a system that helps to minimize the speed-related accidents. The system is remotely operated and instantly preventing vehicles from speeding. The traffic management authorities can enforce the optimum safe speed limit whenever and wherever necessary in real time while the vehicles are running on the roads.