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Yooyoung Lee, Amy Yates, Haiying Guan, Jonathan G. Fiscus, Daniel Zhou
The interest of forensic techniques capable of detecting many different manipulation types has been growing, and system developments with machine learning technology have been evolving in recent years. There has been, however, a lack of diverse data
Kamal Choudhary, Kevin Garrity, Andrew C. Reid, Brian DeCost, Adam Biacchi, Angela R. Hight Walker, Zachary Trautt, Jason Hattrick-Simpers, Aaron Kusne, Andrea Centrone, Albert Davydov, Francesca Tavazza, Jie Jiang, Ruth Pachter, Gowoon Cheon, Evan Reed, Ankit Agrawal, Xiaofeng Qian, Vinit Sharma, Houlong Zhuang, Sergei Kalinin, Ghanshyam Pilania, Pinar Acar, Subhasish Mandal, David Vanderbilt, Karin Rabe
The Joint Automated Repository for Various Integrated Simulations (JARVIS) is an integrated infrastructure to accelerate materials discovery and design using density functional theory (DFT), classical force-fields (FF), and machine learning (ML) techniques
Manufacturers need to be resilient to effectively mitigate substantial disruptions to manufacturing operations so they may remain competitive. Disruptions resulting from the COVID-19 global pandemic have caused manufacturers to experience new challenges
In the era of the Internet of Things, botnet threats are rising, which has prompted many studies on botnet detection and measurement. In contrast, this study aims to predict botnet attacks, such as massive spam emails and distributed denial-of-service
Keith Curtis, George Awad, Shahzad K. Rajput, Ian Soboroff
This is the introduction paper to the International Workshop on Deep Video Understanding. In recent years, a growing trend towards working on understanding videos (in particular movies) in a more deeper level started to motivate researchers working in
We present a Multi-Window Data Augmentation (MWA-SER) approach for speech emotion recognition. MWA-SER is a unimodal approach that focuses on two key concepts; designing the speech augmentation method and building the deep learning model to recognize the
Recent progress in artificial intelligence is largely attributed to the rapid development of machine learning, especially in the algorithm and neural network models. However, it is the performance of the hardware, in particular the energy efficiency of a
The English word manufacturing firstly appeared in 1683 and it was derived from Latin manu factus, meaning making by hand. For more than thousands of years now, and four Industrial Revolutions, the physical, and mostly mechanical processes, associated with
Michael Paul Majurski, Derek Juba, Timothy Blattner, Peter Bajcsy, Walid Keyrouz
Neural Networks are trained on data, learn relationships in that data, and then are deployed to the world to operate on new data. For example, a traffic sign classification AI can differentiate stop signs and speed limit signs. One potential problem is
Kamran Sayrafian, Masoud Roudneshin, Amir G. Aghdam
Recent advancements in micro-electronics have led to the development of miniature-sized wearable sensors that can be used for a variety of health monitoring applications. These sensors are typically powered by small batteries which could require frequent
When people try to understand nuanced language they typically process multiple input sensor modalities to complete this cognitive task. It turns out the human brain has even a specialized neuron formation, called sagittal stratum, to help us understand
Jun Wang, Andy Tam, Paul A. Reneke, Richard Peacock, Thomas Cleary, Eugene Yujun Fu, Grace Ngai, Hong Va Leong
This paper presents a study to examine the potential use of machine learning algorithms to build a model to forecast the likelihood of flashover occurrence for a single-floor multi-room compartment. Synthetic temperature data for heat detectors from
Jun Wang, Youwei Jia, Eugene Yujun Fu, Jiajia Li, Andy Tam
This paper aims to facilitate the use of machine learning to carry out supervised classification/regression tasks for time series data in fire research. Specifically, a feature engineering tool, FAST (Feature extrAction and Selection for Time-series), is
Mobile edge computing (MEC) is an emerging paradigm that integrates computing resources in wireless access networks to process computational tasks in close proximity to mobile users with low latency. In this paper, we propose an online double deep Q