This study evaluates STEM students' preconceptions regarding Quality of Service (QoS) in telecommunications and networking with the goal of understanding the nature of these preconceptions to improve student learning in this discipline. In this study we explain the importance of identifying preconceptions with which students enter our classrooms and illustrate a mechanism successfully used in this identification process. Researchers have explained it incumbent on educators to address preconceptions in order to effectively change student beliefs 1 .Analyzing the causes of these will allow teachers to instruct effectively from the start of the topic rather that lose time by re-teaching the material. As networks grow to handle increasing demands for capacity and QoS, telecommunications professionals are responsible for engineering and managing these networks. A solid understanding of factors that affect QoS is imperative and, as such, telecommunications networking instruction must be properly informed.

Existing systems for reporting cellular outages do not provide adequate geographical granularity and do not provide a real-time view of the state of the communication network. This work presents a system for real-time measurement of both coverage and quality of service via crowdsourced measurements from consumer and first responder phones. Baseline coverage and quality of service data is collected prior to a major disaster. During a major disaster, real-time data is compared to baseline to identify areas of congestion or outages. Such information can be used by incident commanders to more effectively deploy resources during major disasters. Furthermore, such system state information can be used to support automatic deployment of temporary cellular network base stations, such as on drones.

No abstract

is an associate professor in the College of Applied Science and Technology (CAST) in the department of Electrical, Computer and Telecommunications Engineering Technology at the Rochester Institute of Technology since 1990. Previously, he was a Large Business Systems Communications Engineer for NEC America, specializing in large scale deployment of voice and data network switching equipment. He teaches in the Master of Science Telecommunications Engineering Technology program and conducts research in Real Time Audio Collaboration (RTAC) and the feasibility, logistics and implementation of live recording sessions carried and delivered over IP networks, Anomaly Detection for Music developing recommender systems for listeners and consumers and 3-D Audio perception, STEM Education related to preconceptions and concept inventories related to telecommunications. Indelicato holds a Bachelor of Engineering in Electrical Engineering (BEEE) from Manhattan College, a Master of Science in Information Systems Engineering (MSISE) from Brooklyn Polytechnic University and is an active member of IEEE, ASEE, and the Audio Engineering Society (AES).

Purpose: Automatic speech recognition (ASR) is commonly used to produce telephone captions to provide telecommunication access for individuals who are d/Deaf and hard of hearing (DHH). However, little is known about the effects of degraded telephone audio on the intelligibility of ASR captioning. This research note investigates the accuracy of telephone captions produced by ASR under degraded audio conditions. Method: Packet loss, delay, and repetition are common sources of degradation in sound quality for telephone audio. Eleven sets of wideband filtered sentences were degraded by high and low levels of simulated packet loss, delay, and repetition. These sets, along with a clean set of sentences, were submitted to ASR, and the accuracy of the resulting output was evaluated using three metrics: a word recognition score, word error rate, and word information loss. Results: The resulting pattern of data indicated the relative impact of each degraded condition on message intelligibility. The high and low packet loss conditions had the largest effect on message intelligibility. This finding was interpreted to indicate that packet loss can have a substantial impact on the accuracy of telephone captions produced with ASR. Conclusions: The results of this investigation point to a potential area of improvement in service quality that could have a substantial impact on telecommunication services for consumers who are DHH. Further research in this area is needed to provide additional information concerning the scope and impact of packet loss on the accuracy of telephone captioning produced by ASR. Supplemental Material: https://doi.org/10.23641/asha.21699557