Data management plan for the grant "IUCRC Phase I University of North Texas: Center for Electric, Connected and Autonomous Technologies for Mobility (eCAT)."

This article is a study where the authors integrated the multi-omics datasets such as copy number aberration, DNA methylation, gene and microRNA expression to identify the signature microRNA-gene associations from frequently aberrated DNA regions across pan-cancer utilizing a LASSO-based regression approach.

Data management plan for the grant, "REU Site: TaMaLe - Testing and Machine Learning for Context-Driven Systems: Research Experience for Undergraduates." TaMaLe (Testing and Machine Learning for Context-Driven Systems), a renewal Research Experience for Undergraduates (REU) Site at University of North Texas, engages 10 undergraduate students for 10 weeks with problems in the context-driven system domain. The students explore research problems to improve the reliability and security of context-driven systems. Context-driven systems, such as mobile apps, face constant streams of input from both users and context changes in their environments. Users interact with apps through touch and speech interfaces. These systems also respond to context events that occur in their environments such as changes to network connection, battery level, screen orientation, and more. The combined explosion of possible user events and context event sequences pose new challenges that require cost effective testing solutions. Students and mentors in this REU program work in small teams to develop and empirically evaluate new software testing techniques for context-driven systems using strategies such as reinforcement learning and combinatorial-based techniques.

This article describes a system for pupil size estimation with a user interface to allow rapid adjustment of parameters and extraction of pupil parameters of interest in order to identify Parkinson's disease (PD) as early as possible.

This article presents a novel approach of introducing a weighted temporal feature to bias a topic clustering toward articles in a similar time frame, performed over a set of finance journal abstracts from 1974 to 2020 to demonstrate how time can be emphasized in trend detection. The authors detect trending finance topics that are not identifiable when we use a standard clustering approach with no temporal bias.

Data management plan for the grant, "REU Site: Interdisciplinary Research Experience on Accelerated Deep Learning through A Hardware-Software Collaborative Approach." This Research Experiences for Undergraduates (REU) Site Program at the University of North Texas will enhance the knowledge and research skills of a diverse cohort of undergraduate students through empowering, innovative, and interdisciplinary research experiences in developing Deep Learning applications and systems. The program aims to 1) expose undergraduate students to real-world and cutting-edge research focused on accelerated deep learning through combined hardware and software development; 2) encourage more undergraduate students to continue their academic careers and seek graduate degrees in computer science, computer engineering, and related disciplines; 3) develop research skills and improve communication and collaborative skills in undergraduate students.

This article proposes a novel preconditioned and accelerated Gauss–Siedel algorithm referred to as Symmetric Successive Overrelaxation Preconditioned Gauss-Seidel (SSORGS) to address the signal detection challenges associated with massive MIMO technology.

Article describes study which sought to evaluate methods for activity recognition for toddlers.

This article proves that a variant of the Courtois-Finiasz-Sendrier signature is strongly existentially unforgeable under chosen message attack in the random oracle model, assuming hardness of the Permuted Goppa Syndrome Decoding Problem (also known as the Niederreiter problem).

This article discusses the effectiveness of utilizing local spatial variations in environmental data to uncover the statistical relationships between West Nile Virus (WNV) risk and environmental factors.

This paper shows that introducing mobility increases the rate of convergence in partially connected and disconnected wireless sensor networks (WSN).

Poster for the 2014 MCBIOS Conference. This poster discusses classifying drug resistance in the NCI60 cancer cell lines based on the mRNA expression levels of the 48 ABC transporters.

Poster for the 2014 MidSouth Computational Biology and Bioinformatics Society (MCBIOS) Annual Conference. This poster discusses a comparison of machine learning algorithms for identifying cancer types.

Poster for the 2014 UNT Graduate Exhibition in the Computer Science and Information Technology category. This poster discusses data mining techniques for predicting breast cancer survivability among women in the United States.

This book chapter discusses predicting subjectivity orientation of online forum threads.

This article uses full-length 16S rRNA gene alignments from the SILVA database to simulate the PCR products of the combined variable regions.

This paper discusses secure embedded platforms for networked automotive systems.

In this paper, the authors explore several computational models for incongruity resolution.

This encyclopedia article gives an overview of the broad area of real-time systems. This task is daunting because real-time systems are everywhere, and yet no generally accepted definition differentiates real-time systems from non-real-time systems.

In this paper, the authors evaluate the extent to which human-written book summaries can be obtained through cut-and-paste operations from the original book. The authors analyze the effect of the parameters involved in the decomposition algorithm, and highlight the distinctions in coverage obtained for different summary types.

This paper discusses linguistic ethnography.

In this paper, the authors explore unsupervised techniques for the task of automatic short answer grading.

In this paper, the authors present a schema to build one way functions from a family of Boolean gates. Moreover, the authors relate characteristics of these Boolean gate truth tables to properties of the derived one-way functions.

This paper discusses learning to identify emotions in text.