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369 Matching Results
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Pareto Optimization of CNN Models via Hardware-Aware Neural Architecture Search for Drainage Crossing Classification on Resource-Limited Devices
Article describes how embedded devices, constrained by limited memory and processors, require deep learning models to be tailored to their specifications. This research explores customized model architectures for classifying drainage crossing images.
Date:
November 12, 2023
Creator:
Li, Yuke; Baik, Jiwon; Rahman, Md Marufi; Anagnostopoulos, Iraklis; Li, Ruopu & Shu, Tong
Object Type:
Article
System:
The UNT Digital Library
Securing Industrial Control Systems: Components, Cyber Threats, and Machine Learning-Driven Defense Strategies
Article describes how Industrial Control Systems (ICS), which include Supervisory Control and Data Acquisition (SCADA) systems, Distributed Control Systems (DCS), and Programmable Logic Controllers (PLC), play a crucial role in managing and regulating industrial processes. This article presents an overview of ICS security, covering its components, protocols, industrial applications, and performance aspects.
Date:
October 30, 2023
Creator:
Nankya, Mary; Chataut, Robin & Akl, Robert
Object Type:
Article
System:
The UNT Digital Library
Feasibility of PROMIS using computerized adaptive testing during inpatient rehabilitation
Article describes how there has been an increased significance on patient-reported outcomes in clinical settings. The authors aimed to evaluate the feasibility of administering patient-reported outcome measures by computerized adaptive testing (CAT) using a tablet computer with rehabilitation inpatients, assess workload demands on staff, and estimate the extent to which rehabilitation inpatients have elevated T-scores on six Patient Reported Outcomes Measurement Information System (PROMIS) measures.
Date:
May 10, 2023
Creator:
Rafiq, Riyad Bin; Yount, Susan; Jerousek, Sara; Roth, Elliot J.; Cella, David; Albert, Mark et al.
Object Type:
Article
System:
The UNT Digital Library
Accuracy-Constrained Efficiency Optimization and GPU Profiling of CNN Inference for Detecting Drainage Crossing Locations
Article describes how the accurate and efficient determination of hydrologic connectivity has garnered significant attention from both academic and industrial sectors due to its critical implications for environment management. To address these challenges, the focus of the author's study is on detecting drainage crossings through the application of advanced convolutional neural networks.
Date:
November 12, 2023
Creator:
Zhang, Yicheng; Pandey, Dhroov; Wu, Di; Kundu, Turja; Li, Ruopu & Shu, Tong
Object Type:
Article
System:
The UNT Digital Library
Predicting psoriasis using routine laboratory tests with random forest
Article describes how psoriasis is a chronic inflammatory skin disease that affects approximately 125 million people worldwide. The goal of the authors' study is to derive a powerful predictive model for psoriasis disease based on only routine hospital tests.
Date:
October 19, 2021
Creator:
Zhou, Jing; Li, Yuzhen & Guo, Xuan
Object Type:
Article
System:
The UNT Digital Library
FlexiChain 3.0: Distributed Ledger Technology-Based Intelligent Transportation for Vehicular Digital Asset Exchange in Smart Cities
Article describes how, due to the enormous amounts of data being generated between users, Intelligent Transportation Systems (ITS) are complex Cyber-Physical Systems that necessitate a reliable and safe infrastructure. In this work, the authors explore Distributed Ledger Technology (DLT) and collect data about consensus algorithms and their applicability to be used in the IoV as the backbone of ITS.
Date:
April 19, 2023
Creator:
Alkhodair, Ahmad; Mohanty, Saraju P. & Kougianos, Elias
Object Type:
Article
System:
The UNT Digital Library
SUPREME: multiomics data integration using graph convolutional networks
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.
Date:
June 28, 2023
Creator:
Kesimoglu, Ziynet Nesibe & Bozdag, Serdar
Object Type:
Article
System:
The UNT Digital Library
PPAD: a deep learning architecture to predict progression of Alzheimer’s disease
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.
Date:
June 30, 2023
Creator:
Olaimat, Mohammad Al; Martinez, Jared; Saeed, Fahad & Bozdag, Serdar
Object Type:
Article
System:
The UNT Digital Library
NRPreTo: A Machine Learning-Based Nuclear Receptor and Subfamily Prediction Tool
Article asserts that the nuclear receptor (NR) superfamily includes phylogenetically related ligand-activated proteins, which play a key role in various cellular activities. The authors developed Nuclear Receptor Prediction Tool (NRPreTo), a two-level NR prediction tool with a unique training approach where in addition to the sequence-based features used by existing NR prediction tools, six additional feature groups depicting various physiochemical, structural, and evolutionary features of proteins were utilized.
Date:
May 30, 2023
Creator:
Madugula, Sita Sirisha; Pandey, Suman; Amalapurapu, Shreya & Bozdag, Serdar
Object Type:
Article
System:
The UNT Digital Library
NextGen-Malloc: Giving Memory Allocator Its Own Room in the House
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.
Date:
June 22, 2023
Creator:
Li, Ruihao; Wu, Qinzhe; Kavi, Krishna M.; Mehta, Gayatri; Yadwadkar, Neeraja J. & John, Lizy Kurian
Object Type:
Article
System:
The UNT Digital Library
FZ-GPU: A Fast and High-Ratio Lossy Compressor for Scientific Computing Applications on GPUs
Article describes how today's large-scale scientific applications running on high-performance computing (HPC) systems generate vast data volumes. Thus, data compression is becoming a critical technique to mitigate the storage burden and data-movement cost. In this paper, the authors develop a fast and high- ratio error-bounded lossy compressor on GPUs for scientific data (called FZ-GPU).
Date:
August 7, 2023
Creator:
Zhang, Bouyan; Tian, Jiannan; Di, Sheng; Yu, Xiaodong; Feng, Yunhe; Liang, Xin et al.
Object Type:
Article
System:
The UNT Digital Library
OptiFit: Computer-Vision-Based Smartphone Application to Measure the Foot from Images and 3D Scans
Article asserts that the foot is a vital organ, as it stabilizes the impact forces between the human skeletal system and the ground. The authors present an instep girth measurement algorithm, and they used a pixel per metric algorithm for measurement; these algorithms were accordingly integrated with the application.
Date:
December 6, 2022
Creator:
Rafiq, Riyad Bin; Hoque, Kazi Miftahul; Kabir, Muhammad Ashad; Ahmed, Sayed & Laird, Craig
Object Type:
Article
System:
The UNT Digital Library
Visual object tracking: Progress, challenge, and future
Article discusses how visual object tracking aims to continuously localize the target object of interest in a video sequence. To provide the community an overview, in this commentary, the authors discuss visual tracking from different aspects.
Date:
February 21, 2023
Creator:
Zhang, Libo & Fan, Heng
Object Type:
Article
System:
The UNT Digital Library
agroString: Visibility and Provenance through a Private Blockchain Platform for Agricultural Dispense towards Consumers
Article discusses the large quantities of farm and meat products that rot and are wasted if correct actions are not taken leading to serious health concerns if consumed. Because there is no proper system for tracking and communicating the status of goods to consumers, a right which according to the authors should be a given, they propose a method of increased communication using Corda private blockchain.
Date:
October 27, 2022
Creator:
Vangipuram, Sukrutha L. T.; Mohanty, Saraju P.; Kougianos, Elias & Ray, Chittaranjan
Object Type:
Article
System:
The UNT Digital Library
Role of Artificial Intelligence for Analysis of COVID-19 Vaccination-Related Tweets: Opportunities, Challenges, and Future Trends
Article states that vaccines, though reliable preventative measures for diseases, also raise public concerns; public apprehension and doubts challenge the acceptance of new vaccines including the COVID-19 vaccines. This study is the first attempt to review the role of AI approaches in COVID-19 vaccination-related sentiment analysis.
Date:
September 5, 2022
Creator:
Aljedaani, Wajdi; Saad, Eysha; Rustam, Furqan; de la Torre Díez, Isabel & Ashraf, Imran
Object Type:
Article
System:
The UNT Digital Library
Privacy-Preserving Object Detection with Secure Convolutional Neural Networks for Vehicular Edge Computing
Article discusses how with the wider adoption of edge computing services, intelligent edge devices, and high-speed V2X communication, compute-intensive tasks for autonomous vehicles, such as object detection using camera, LiDAR, and/or radar data, can be partially offloaded to road-side edge servers. The authors aim to address the privacy problem by protecting both vehicles' sensor data and the detection results.
Date:
October 31, 2022
Creator:
Bai, Tianyu; Fu, Song & Yang, Qing
Object Type:
Article
System:
The UNT Digital Library
Electroencephalogram Signals for Detecting Confused Students in Online Education Platforms with Probability-Based Features
Article discusses how despite the advantages of online education, it lacks face-to-face settings, which makes it very difficult to analyze the students’ level of interaction, understanding, and confusion. This study proposes a novel engineering approach that uses probability-based features (PBF) for increasing the efficacy of machine learning models.
Date:
September 9, 2022
Creator:
Daghriri, Talal; Rustam, Furqan; Aljedaani, Wajdi; Bashiri, Abdullateef H. & Ashraf, Imran
Object Type:
Article
System:
The UNT Digital Library
Autoencoder Composite Scoring to Evaluate Prosthetic Performance in Individuals with Lower Limb Amputation
Authors of the article created an overall assessment metric using a deep learning autoencoder to directly compare clinical outcomes in a comparison of lower limb amputees using two different prosthetic devices—a mechanical knee and a microprocessor-controlled knee. The proposed methods were used on data collected from ten participants with a dysvascular transfemoral amputation recruited for a prosthetics research study.
Date:
October 18, 2022
Creator:
Tabashum, Thasina; Xiao, Ting; Jayaraman, Chandrasekaran; Mummidisetty, Chaithanya K.; Jayaraman, Arun & Albert, Mark
Object Type:
Article
System:
The UNT Digital Library
PharmaChain: A blockchain to ensure counterfeit‐free pharmaceutical supply chain
Article discusses how globalisation has facilitated different industries to eliminate geographical boundaries and equipped organisations to work collectively to produce goods. The authors of the article propose a novel Distributed Ledger Technology (DLT) based transparent supply chain for PSC and proof-of-concept is implemented to analyse the scalability and efficiency of the proposed architecture.
Date:
July 5, 2022
Creator:
Bapatla, Anand K.; Mohanty, Saraju P.; Kougianos, Elias; Putha, Deepak & Bapatla, Anusha
Object Type:
Article
System:
The UNT Digital Library
Detection of DDoS Attack in Software-Defined Networking Environment and Its Protocol-wise Analysis using Machine Learning
Article describes how distributed-denial-of-service (DDoS) attacks can cause a great menace to numerous organizations and their stakeholders. The authors assert that the objective of this research work is to take into account a DDoS afflicted SDN specific dataset and detect the malicious traffic by using various machine learning algorithms namely., K-Nearest Neighbours, Logistic Regression, Multilayer Perceptron, Iterative Dichotomiser 3, and Stochastic Gradient Descent.
Date:
January 10, 2022
Creator:
Prasad, Ashwani; Prasad, Sanjana; Arockiasamy, Karmel; P, Karthika & Yuan, Xiaohui
Object Type:
Article
System:
The UNT Digital Library
A Gaze into the Internal Logic of Graph Neural Networks, with Logic
Article exploring graph node property prediction. Originally presented as part of the application track at the 38th International Conference on Logic Programming in Haifa, Israel.
Date:
August 4, 2022
Creator:
Tarau, Paul
Object Type:
Article
System:
The UNT Digital Library
Detecting Covid-19 chaos driven phishing/malicious URL attacks by a fuzzy logic and data mining based intelligence system
Article analyses the impact of Covid-19 on various cyber-security related aspects.
Date:
June 7, 2022
Creator:
Zahra, Syed Rameem; Chishti, Mohammad Ahsan; Baba, Asif Iqbal & Wu, Fan
Object Type:
Article
System:
The UNT Digital Library
A Parallel Convolution and Decision Fusion-Based Flower Classification Method
This article proposes a novel flower classification method that combines enhanced VGG16 (E-VGG16) with decision fusion.
Date:
August 4, 2022
Creator:
Jia, Lianyin; Zhai, Hongsong; Yuan, Xiaohui; Jiang, Ying & Ding, Jiaman
Object Type:
Article
System:
The UNT Digital Library
Computing microRNA-gene interaction networks in pan-cancer using miRDriver
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.
Date:
March 8, 2022
Creator:
Bose, Banabithi; Moravec, Matthew & Bozdag, Serdar
Object Type:
Article
System:
The UNT Digital Library