• Shared Context through Multi-Level Attention Transformers for Text Classification 

  Thota, Charan Tej (2021)

  Natural language processing (NLP) has seen recent explosive growth by creating artificial intelligence with human-level intelligence. Understanding the context using an attention mechanism could be further improved by ...

• Wideband high-power transmission line pulse transformers 

  Kovarik, James (2021)

  Geometric transformers are often used in radar and communications systems to transition between signal driving and radiating elements that terminate in significantly different geometries with unity input/output impedance. ...

• Challenges and solutions for large-scale integration of emerging technologies 

  Iqbal, Md Arif (2021)

  The semiconductor revolution so far has been primarily driven by the ability to shrink devices and interconnects proportionally (Moore's law) while achieving incremental benefits. In sub-10nm nodes, device scaling reaches ...

• On-chip Voltage Regulator– Circuit Design and Automation 

  Ahmed, Farid Uddin (2021)

  With the increase of density and complexity of high-performance integrated circuits and systems, including many-core chips and system-on-chip (SoC), it is becoming difficult to meet the power delivery and regulation ...

• Measuring Level of Degradation in Power Semiconductor Devices using Emerging Techniques 

  Hanif, Abu (2021)

  High thermal and electrical stress, over a period of time tends to deteriorate the health of power electronic switches. Being a key element in any high-power converter systems, power switches such as insulated-gate bipolar ...

• Fault Diagnosis and Condition Monitoring of Power Electronic Components Using Spread Spectrum Time Domain Reflectometry (SSTDR) and the Concept of Dynamic Safe Operating Area (SOA) 

  Roy, Sourov (2021)

  Fault diagnosis and condition monitoring (CM) of power electronic components with a goal of improving system reliability and availability have been one of the major focus areas in the power electronics field in the last ...

• Ocular motion classification for mobile device presentation attack detection 

  Lowe, Jesse (2020)

  As a practical pursuit of quantified uniqueness, biometrics explores the parameters that make us who we are and provides the tools we need to secure the integrity of that identity. In our culture of constant connectivity, ...

• AudioCNN: Audio Event Classification With Deep Learning Based Multi-Channel Fusion Networks 

  Chilukuri, Nagababu (2020)

  In recent years, there is growing interest in environmental sound classification with a plethora of real-world applications, especially in audio fields like speech and music. Recent research works have proven spectral ...

• Automated End-to-End Management of the Deep Learning Lifecycle 

  Gharibi, Gharib (2020)

  Deep learning has improved the state-of-the-art results in an ever-growing number of domains. This success heavily relies on the development of deep learning models--an experimental, iterative process that produces tens ...

• Learning Efficient Deep Feature Extraction For Mobile Ocular Biometrics 

  Reddy, Narsi (2020)

  Ocular biometrics uses physical traits from eye regions such as iris, conjunctival vasculature, and periocular for recognizing the person. Ocular biometrics has gained popularity amongst research and industry alike for its ...

• Enriching Knowledge Graphs Using Machine Learning Techniques 

  Gharibi, Mohamed (2020)

  A knowledge graph represents millions of facts and reliable information about people, places, and things. These knowledge graphs have proven their reliability and their usage for providing better search results; answering ...

• Data-Driven Modeling of the Lake Chad Basin Hydrologic Systems 

  Djimadoumngar, Kim-Ndor (University of Missouri -- Kansas City, 2019)

  The drying of the Lake, located in Central Africa, is one example of a water crisis, which requires more research and studies. The lake has been progressively shrinking since the 1960s due to climate change and anthropogenic ...

• Anisotropic Mesh Adaptation for Image Segmentation based on Partial Differential Equations 

  Abbas, Karrar Kadhim (2020)

  As the resolution of digital images increases significantly, the processing of images becomes more challenging in terms of accuracy and efficiency. In this dissertation, we consider image segmentation by solving a partial ...

• Deep Open Representative Learning for Image and Text Classification 

  Chandrashekar, Mayanka (2020)

  An essential goal of artificial intelligence is to support the knowledge discovery process from data to the knowledge that is useful in decision making. The challenges in the knowledge discovery process are typically due ...

• Class Representative Projection for Text-based Zero-Shot Learning 

  Narne, Sai Sri (2020)

  There have been significant advances in supervised machine learning and enormous benefits from deep learning for a range of diverse applications. Despite the success of deep learning, in reality, very few works have shown ...

• The Holistic Course Delivery: A Novel Pedagogy for Collegiate Introductory Computer Programming 

  Copus, Belinda Joan (2020)

  For many years there have not been enough computer science graduates to fill open positions. One of the chief barriers to the formation of computer science graduates is that many students are unsuccessful in the introductory ...

• Compression for Machine Vision and Beyond 

  Zhang, Zhaobin (2020)

  Compression has been one of the most fundamental and elusive challenges in both academia and industry. With the sheer increase of high-definition video content over the internet, developing improved compression algorithms ...

• Numerical Analysis of Helical and Log-periodic Antennas for Short Pulse Applications 

  Al-Shaikhli, Waleed (2020)

  The planar log-periodic (LP) and helical antennas are numerically studied as two antennas with a wide range of applications. The advantages of the LP antenna are the large adjustable bandwidth as a frequency independence ...

• Topic Sentiment Trend Detection and Prediction for Social Media 

  Thota, Aashish (2020)

  Social media often plays a crucial role in disseminating information to warn the public about health concerns. Opioid addiction has become of the significant outbreaks in the United States. Studying opioid issues in social ...

• DeepSampling: Image Sampling Technique for Cost-Effective Deep Learning 

  Gaikwad, Priyanka V. (2020)

  Deep learning is beneficial from big data while facing computationally expensive, with an increase in data size. Some severe data issues, such as the presence of highly skewed, sparse, and imbalanced data, would substantially ...

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