This article proposes a correction method for image enhancement models based on an adaptive local gamma transformation and color compensation inspired by the illumination reflection model. It is demonstrated that the proposed method adaptively reduces the influence of uneven illumination to avoid overenhancement and improves the visual effect of low-light images.

This article is from the 26th ACM Conference on Innovation and Technology in Computer Science Education and discusses the design, effectiveness, and curricular impacts of an introductory data science course focused on practical programming skills and allowing students to concurrently complete the course in Python, R, or MATLAB. Students indicated a preference for the multi-language course design and the course became the recommended first programming course for a newly developed and approved undergraduate data science majors.

Article describes how memory allocation and management have a significant impact on performance and energy of modern applications. The authors observe that performance can vary by as much as 72% in some applications based on which memory allocator is used, and in this paper, the authors make a case for offloading memory allocation (and other similar management functions) from main processing cores to other processing units to boost performance, reduce energy consumption, and customize services to specific applications or application domains.

Article investigating HUMIRA effects mentioned in Twitter posts using a relational similarity-based method. The authors were able to identify effects previously known as well as potentially unreported, which demonstrates the power of this method and its potential for studying effects of other medications shared by Twitter users.

Article and accompanying poster presenting a prototype for the use of Edge with MR devices to provide cooperative perception capability to the MR device.

Article analyses the impact of Covid-19 on various cyber-security related aspects.

Data management plan for the grant, "CAREER: Reinventing Network-on-Chips of GPU-Accelerated Systems." Research seeking to reinvent on-chip networks for GPU-accelerated systems to remove a communication bottleneck. A major outcome of the project is a set of techniques that enable the development of effective and efficient network-on-chip architectures. Graphics processing units (GPUs) have rapidly evolved to become high-performance accelerators for data-parallel computing. To fully take advantage of the computing power of GPUs, on-chip networks need to provide timely data movement to satisfy the requests of data by the processing cores. Currently, there exists a big gap between the fast-growing processing power of the GPU processing cores and the slow-increasing on-chip network bandwidth. Because of this, GPU-accelerated systems are interconnect-dominated and the on-chip network becomes their performance bottleneck.

Article conducting an intensive study on the problems of low recognition efficiency and noise in the overlapping structure of protein functional modules, based on topological characteristics of PPI network. Developing a protein function module recognition method ECTG based on Topological Features and Gene expression data for Protein Complex Identification. The experimental results show that the ECTG algorithm can detect protein functional modules better.

Data management plan for the grant, "UNT Gencyber Academy."

Article states that, to pave the road towards precision medicine in cancer, patients with similar biology ought to be grouped into same cancer subtypes. On breast cancer subtyping, unlike existing tools, SUPREME generates patient embeddings from multiple similarity networks utilizing multiomics features and integrates them with raw features to capture complementary signals.

Article asserts that Alzheimer’s disease (AD) is a neurodegenerative disease that affects millions of people worldwide. The authors of the article propose two deep learning architectures based on RNN, namely Predicting Progression of Alzheimer’s Disease (PPAD) and PPAD-Autoencoder.

Data management plan for the grant, "Collaborative Research: Engaging Blind and Visually Impaired Youth in Computer Science through Music Programming."