School of Computing
The School of Computing has roots in the Departments of Electrical Engineering and Computer Science, and Engineering Technology. It was established as a stand alone school in 2021.
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SoC Research Publications
Publications of faculty of the School of Computing -
SoC Theses
The School of Computing Master's theses
Recent Submissions
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An LDOP approach for face identification under unconstrained scenarios
(Taylor & Francis, 2023-03-01)In unconstrained environments, it encounters a number of challenges when considering handcrafted features for face recognition, including changes in pose, illumination and facial expression and plastic surgery variations, ... -
Is Facial Recognition Biased at Near-Infrared Spectrum as Well?
(IEEE, 2022-11-15)Published academic research and media articles suggest face recognition is biased across demographics. Specifically, unequal performance is obtained for women, dark-skinned people, and older adults. However, these published ... -
Federated nearest neighbor classification with a colony of fruit-flies
(AAAI, 2022-06-28)The mathematical formalization of a neurological mechanism in the fruit-fly olfactory circuit as a locality sensitive hash (Flyhash) and bloom filter (FBF) has been recently proposed and "reprogrammed" for various ... -
Allan deviation of social learning distributed network time synchronization
(IEEE, 2022-12-02)The objective of this paper is to demonstrate that the concept of a recently published social learning distributed network time synchronization (SLDNTS) algorithm under a Global Positioning System (GPS) denial environment ... -
Secrecy rate of relay and intelligent reflecting surface antenna-assisted MIMO
(IEEE, 2022-12-02)This paper proposes the use of an amplify-and-forward (AF) relay in addition to intelligent reflecting surface (IRS) antennas to ensure higher secrecy rates compared to IRS-only multiple-input multiple-output (MIMO) ... -
Artificial intelligence (AI) for hybrid information-centric networking (HICN): Part I
(John Wiley & Sons, Ltd, 2022-09-01)[No abstract available] -
Deep learning-based approaches for prediction of post-translational modification sites in proteins
(Wichita State University, 2022-12)Protein post-translational modification plays an important role in a myriad of biological processes. Computational prediction approaches serve as complementary methods for the characterization of post-translational ... -
AR Extractor : Automatically extracting constraints from android documentation using NLP techniques
(Wichita State University, 2022-12)When developing android apps, it is difficult for the programmers to follow all programming constrains in Android documents. Programming rules are difficult to be manually identified and documented by programmers. As those ... -
Deep learning models for natural disaster assessment using satellite imagery
(Wichita State University, 2022-12)The current methods to assess damage which has occurred during a disaster are usually manual based assessments. This work talks about developing an automated damage assessment model using computer vision and deep ... -
Secure data storage resilient against compromised users via an access structure
(IEEE, 2022-11-09)Consider a source and multiple users who observe the independent and identically distributed (i.i.d.) copies of correlated Gaussian random variables. The source wishes to compress and store its observation in a public ... -
Adaptive scaffolding toward transdisciplinary collaboration: Reflective polyvocal self-study
(Springer International Publishing, 2022-12-16)Contemporary global challenges require experts from various disciplines to work together. Since every field of knowledge has its unique language and discipline-based culture, collaborative inquiry presents an additional ... -
Secure reboots for real-time cyber-physical systems
(Association for Computing Machinery, 2022-11-07)Cyber-Physical Systems (CPS) such as industrial control systems, automobiles, and medical devices often consist of applications with real-time properties. Due to the safety-critical nature of the application domain, multiple ... -
Real-time scheduling of TrustZone-enabled DNN workloads
(Association for Computing Machinery, 2022-11-07)Limited resources in embedded devices often hinder the execution of computation-heavy machine learning processes. Running deep neural network (DNN) workloads while preserving the integrity of the model parameters and without ... -
An examination of bias of facial analysis based BMI prediction models
(IEEE, 2022-06-19)Obesity is one of the most important public health problems that the world is facing today. A recent trend is in the development of intervention tools that predict BMI using facial images for weight monitoring and management ... -
On improving cross-dataset generalization of deepfake detectors
(IEEE, 2022-06-19)Facial manipulation by deep fake has caused major security risks and raised severe societal concerns. As a countermeasure, a number of deep fake detection methods have been proposed recently. Most of them model deep fake ... -
Work in progress: Exploring schedule-based side-channels in TrustZone-enabled real-time systems
(IEEE, 2022-05-04)Our research demonstrates the existence of side-channel information leaks in TrustZone-enabled real-time systems. Our algorithm can infer the critical tasks’ arrival times and pinpoint when the system switches between ... -
Touch detection in augmented Omni-surface for human-robot teaming
(Association for Industry, Engineering and Management Systems (AIEMS), 2022-12)This paper proposes an architecture that augments arbitrary surfaces into an interactive touching interface. The proposed architecture can detect the number of touching fingertips of human operators by detecting and ... -
Integration of instance-based learning and computed torque control for an effective assist-as-needed support in human-exoskeleton interaction
(Association for Industry, Engineering and Management Systems (AIEMS), 2022-12)The physiological responses that arise from human-robot interaction may vary across subjects in magnitude and rate. Such individual variations may require instance-based learning over model-based learning algorithms. For ... -
Commitment over multiple-access channels
(Institute of Electrical and Electronics Engineers Inc., 2022-09-04)The problem of multi-user commitment is one in which multiple users first commit to individual messages with a bookmaker and later reveal their messages. The objective of the bookmaker is then to decide whether the revealed ... -
Utilizing machine learning to predict offshore wind farm power output for European countries
(IEEE, 2022-10-25)One might assume that the types of energy resources used by a country and its level of development are related since developed nations focus on using alternative energy sources like the wind to produce green and sustainable ...
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