Journal ArticleSensors (Basel, Switzerland) · August 2024
The rising incidence of type 2 diabetes underscores the need for technological innovations aimed at enhancing diabetes management by aiding individuals in monitoring their dietary intake. This has resulted in the development of technologies capable of trac ...
Full textCite
ConferenceASEE Annual Conference and Exposition Conference Proceedings · June 23, 2024
A significant gap in education lies in the need for mechanisms that enable early detection of potentially at-risk students. Through access to an earlier prediction of student performance, instructors are given ample time to meet with and assist under-achie ...
Cite
ConferenceIEEE Wireless Communications and Networking Conference Wcnc · January 1, 2023
Video forgery attacks threaten surveillance systems by replacing the video captures with unrealistic synthesis, which can be powered by the latest augmented reality and virtual reality technologies. From the machine perception aspect, visual objects often ...
Full textCite
ConferenceProceedings of the International Joint Conference on Neural Networks · January 1, 2023
In this paper, we address the problem of blind image deblurring with high efficiency. We propose a set of lightweight deep-Wiener-networks to achieve the task with real-time speed. The network contains a deep neural network for estimating the parameters of ...
Full textCite
Journal ArticleInternational Journal of Mechanical Engineering Education · January 1, 2022
Grading engineering drawings takes a significant amount of an instructor’s time, especially in large classrooms. In many cases, teaching assistants help with grading, adding levels of inconsistency and unfairness. To help in grading automation of CAD drawi ...
Full textCite
ConferenceLecture Notes of the Institute for Computer Sciences Social Informatics and Telecommunications Engineering Lnicst · January 1, 2022
Human activity recognition (HAR) has been adopting deep learning to substitute well-established analysis techniques that rely on hand-crafted feature extraction and classication techniques. However, the architecture of convolutional neural network (CNN) mo ...
Full textCite
ConferenceCommunications in Computer and Information Science · January 1, 2021
Recognizing fine-grained hand activities has widely attracted the research community’s attention in recent years. However, rather than enriched sen-sor-based datasets of whole-body activities, there are limited data available for acceler-ator-based fine-gr ...
Full textCite
ConferenceUbicomp Iswc 2020 Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers · September 10, 2020
Label Scarcity and Data Augmentation have long been challenging problems in the research of Human-oriented Artificial Intelligence. Following the trends of Deep Learning, Human Activity Recognition (HAR) tasks have been significantly optimized in the recen ...
Full textCite
ConferenceASEE Annual Conference and Exposition Conference Proceedings · June 22, 2020
Student stress is an important issue that is gaining more attention with time in our universities because of the increase in competition in every aspect of the educational process, from college admission to finding a good job that satisfies students' expec ...
Cite
Journal ArticleSensors (Basel, Switzerland) · March 2020
The difficulty level of learning tasks is a concern that often needs to be considered in the teaching process. Teachers usually dynamically adjust the difficulty of exercises according to the prior knowledge and abilities of students to achieve better teac ...
Full textCite
Journal ArticleInternational Journal of Engineering Education · January 1, 2019
A lecture-based theoretical approach is frequently utilized when teaching courses in electrical circuits and the educational learning objectives are often limited solely to content learning. This paper describes how a lecture-based electrical circuits' cou ...
Cite
Journal ArticleSensors (Basel, Switzerland) · October 2018
Most activity classifiers focus on recognizing application-specific activities that are mostly performed in a scripted manner, where there is very little room for variation within the activity. These classifiers are mainly good at recognizing short scripte ...
Full textCite
ConferenceProceedings of the 2018 IEEE International Conference on Pervasive Computing and Communications · 2018
Most activity classifiers focus on recognizing application-specific activities that are mostly performed in a scripted manner, where there is very little room for variation within the activity. These classifiers are mainly good at recognizing short scripte ...
Full textLink to itemCite
Chapter · December 29, 2016
Within previous chapters of this book, members of the engineering education community describe emerging educational shifts in engineering teaching that draw on creativity and many ways of knowing. In this chapter, we project the future of these shifts usin ...
Full textLink to itemCite
Chapter · May 1, 2016
Electronic textiles provide a means for embedding electronics and conductive wires into fabric to make smart garments that can serve as platforms for a wide variety of applications. This chapter presents prototypes developed by the Virginia Tech E-Textiles ...
Full textLink to itemCite
Journal ArticleComputer · October 1, 2015
An activity classifier based on an abstract model of the human body is suitable for use in an e-textile monitoring system without the need to retrain the recognition model to accommodate different users, sensor types, or garments. ...
Full textCite
ConferenceProceedings of the 2015 ACM International Symposium on Wearable Computers · 2015
Research in activity classification has focused on the sensors, the classification techniques and the machine learning algorithms used in the classifier. In this work, we study a higher level of activity classification. We present two methods that can take ...
Full textLink to itemCite