Computer Engineering Commons^™

On The Involutive Matrices Of The Kth Degree, Hasan Kele ̧S

Iraqi Journal for Computer Science and Mathematics

In this study, the gradation of involutive matrices, whose definitions were given before, is conducted.The solutions of the equationx2=1 in real numbers are1. Meanwhile, in the solution of the equationxk=1in real numbers, there is always the number1 that is independent of the power ofk2Z+. This feature, which isrevealed by this equation in real numbers, is the subject of the research. In particular, the kind of situation in whichthe equation would display in the matrices is determined. Initially, the second-order square matrices are studied byobtaining some of their properties. Then, new cases arising from the known addition, subtraction, multiplication,scalar multiplication, and …

A Deep Neural Network For Early Detection And Prediction Of Chronic Kidney Disease, Vijendra Singh, Vijayan K. Asari, Rajkumar Rajasekaran

Electrical and Computer Engineering Faculty Publications

Diabetes and high blood pressure are the primary causes of Chronic Kidney Disease (CKD). Glomerular Filtration Rate (GFR) and kidney damage markers are used by researchers around the world to identify CKD as a condition that leads to reduced renal function over time. A person with CKD has a higher chance of dying young. Doctors face a difficult task in diagnosing the different diseases linked to CKD at an early stage in order to prevent the disease. This research presents a novel deep learning model for the early detection and prediction of CKD. This research objectives to create a deep …

Chaotic Dynamics In The 2d System Of Nonsmooth Ordinarydifferential Equations, Zain-Aldeen S. A. Rahman, Basil H. Jasim, Yasir I. A. Al-Yasir

Iraqi Journal for Computer Science and Mathematics

Over the last decade, the chaotic behaviors of dynamical systems have been extensively explored.Recently, discovering or developing a 2D system of ordinary differential equations (ODEs) capable of exhibitingchaotic dynamical behaviors is an attractive research topic. In this study, a chaotic system with a 2D system ofnonsmooth ODEs has been developed. This system is can exhibit chaotic dynamical behaviors. Its main dynamicalbehaviors, including time-series trajectories, phase portraits of attractors, and equilibria and their stability, have beeninvestigated. The developed system has been verified by an excessive variety of fascinating chaotic behaviors, such aschaotic attractor, symmetry, sensitivity to initial conditions (ICs), fractal dimension, …

Identification Method Of Power Internet Attack Information Based On Machine Learning, Yitong Niu, Korneev Andrei

Iraqi Journal for Computer Science and Mathematics

To solve the problem of large recognition errors in traditional attack information identificationmethods, we propose a machine learning (ML)-based identification method for electric power Internet attackinformation. Based on the Internet attack information, an Internet attack information model is constructed, theidentification principle of the power Internet attack information is analysed based on ML, hash fixing is conducted toensure that the same attack information will be assigned to the same thread and that the deviation generated by noisecan be avoided so that the real-time lossless processing of the power Internet attack information can be ensured. Thevulnerability adjacency matrix is constructed, and the …

Icu Liberation: Early Mobility And Exercise, Leann Volkers, Holly Kockler, Kristi Patterson

Nursing Posters

The aim of this project was to streamline and standardize the delivery of the follow up Important Message from Medicare (IMM) for IP admissions across CC and Carris-RWF in compliance with regulatory standards of care.

Key drivers identified:

• Site specific variation
• Underutilization of Epic functionality
• Use of data to understand performance

A Half- Yearly E-Newsletter Of The Department Of Computer Science And Engineering, Manipal Institute Of Technology - Jan 2022, Ashalatha Nayak Dr.

Faculty work

No abstract provided.

Exploring The Concept Of The Digital Educator During Covid-19, Fernando Jimenez, Gracia Sanchez, Jose Palma, Luis Miralles-Pechuán, Juan A. Botia

Articles

T In many machine learning classification problems, datasets are usually of high dimensionality and therefore require efficient and effective methods for identifying the relative importance of their attributes, eliminating the redundant and irrelevant ones. Due to the huge size of the search space of the possible solutions, the attribute subset evaluation feature selection methods are not very suitable, so in these scenarios feature ranking methods are used. Most of the feature ranking methods described in the literature are univariate methods, which do not detect interactions between factors. In this paper, we propose two new multivariate feature ranking methods based on …

Assisting End-Users In Creating Chatbots By Improving Training Data, Aparna Roy, Chris Egersdoerfer

Summer REU Program

No abstract provided.

Choosing Wearable Internet Of Things Devices For Managing Safety In Construction Using Fuzzy Analytic Hierarchy Process As A Decision Support System, Sharique Khalid

Theses, Dissertations and Capstones

Many safety and health risks are faced daily by workers in the field of construction. There is unpredictability and risk embedded in the job and work environment. When compared with other industries, the construction industry has one of the highest numbers of worker injuries, illnesses, fatalities, and near-misses. To eliminate these risky events and make worker performance more predictable, new safety technologies such as the Internet of Things (IoT) and Wearable Sensing Devices (WSD) have been highlighted as effective safety systems. Some of these Wearable Internet of Things (WIoT) and sensory devices are already being used in other industries to …

A Trusted Platform For Unmanned Aerial Vehicle-Based Bridge Inspection Management System, Hwapyeong Song

Theses, Dissertations and Capstones

Bridge inspection has a pivotal role in assuring the safety of critical structures constituting society. However, high cost, worker safety, and low objectivity of quality are classic problems in traditional visual inspection. Recent trends in bridge inspection have led to a proliferation of research utilizing Unmanned Aerial Vehicles (UAVs). This thesis proposes a Trusted Platform for Bridge Inspection Management System (Trusted-BIMS) for safe and efficient bridge inspection by proving the UAV-based inspection process and improving the prototype of the previous study. Designed based on a Zero-Trust (ZT) strategy, Trusted-BIMS consist of (1) a database-driven web framework with security features for …

Improving Dysarthric Speech Recognition By Enriching Training Datasets, Sophie Cullen

Dissertations

Dysarthria is a motor speech disorder that results from disruptions in the neuro-motor interface and is characterised by poor articulation of phonemes and hyper-nasality and is characteristically different from normal speech. Many modern automatic speech recognition systems focus on a narrow range of speech diversity therefore as a consequence of this they exclude a groups of speakers who deviate in aspects of gender, race, age and speech impairment when building training datasets. This study attempts to develop an automatic speech recognition system that deals with dysarthric speech with limited dysarthric speech data. Speech utterances collected from the TORGO database are …

Performance Of Wlan In Downlink Mu-Mimo Channel With The Least Cost In Terms Of Increased Delay, Lemlem Kassa, Jianhua Deng, Mark Davis, Jingye Cai

Articles

To improve the performance of IEEE 802.11 wireless local area (WLAN) networks, different frame-aggregation algorithms are proposed by IEEE 802.11n/ac standards to improve the throughput performance of WLANs. However, this improvement will also have a related cost in terms of increasing delay. The traffic load generated by mixed types of applications in current modern networks demands different network performance requirements in terms of maintaining some form of an optimal trade-off between maximizing throughput and minimizing delay. However, the majority of existing researchers have only attempted to optimize either one (to maximize throughput or minimize the delay). Both the performance of …

Real-Time Stock Market Recommendation & Prediction Using Multi Source Data, Kalpana Konety

Dissertations

Stock investors must be cognizant of both the current price of their stock and the price at which they want to sell it in the future. This does not stop investors to monitor past price patterns and apply their knowledge to the present. ’Past performance is not an indicator of future success’, as the saying goes. To put it another way, historical stock data alone isn’t enough to forecast future stock prices. Another key factor to consider in a trading strategy is the impact of market psychology. Financial data, which is a type of multimedia data, provides a wealth of …

Measuring And Comparing Social Bias In Static And Contextual Word Embeddings, Alan Cueva Mora

Dissertations

Word embeddings have been considered one of the biggest breakthroughs of deep learning for natural language processing. They are learned numerical vector representations of words where similar words have similar representations. Contextual word embeddings are the promising second-generation of word embeddings assigning a representation to a word based on its context. This can result in different representations for the same word depending on the context (e.g. river bank and commercial bank). There is evidence of social bias (human-like implicit biases based on gender, race, and other social constructs) in word embeddings. While detecting bias in static (classical or non-contextual) word …

Hybridization Of Biologically Inspired Algorithms For Discrete Optimisation Problems, Elihu Essian-Thompson

Dissertations

In the field of Optimization Algorithms, despite the popularity of hybrid designs, not enough consideration has been given to hybridization strategies. This paper aims to raise awareness of the benefits that such a study can bring. It does this by conducting a systematic review of popular algorithms used for optimization, within the context of Combinatorial Optimization Problems. Then, a comparative analysis is performed between Hybrid and Base versions of the algorithms to demonstrate an increase in optimization performance when hybridization is employed.

A Water-Surface Self-Leveling Landing Platform For Small-Scale Uavs, Mbidi Santos

Electronic Theses and Dissertations

Because many of the most widely used UAVs, such as the Vertical Take-Off and Landing (VTOL), cannot land securely on sloped or fast-changing surfaces, there is a need to design better deployment and landing stations. This document proposes an approach to design a water-surface self-leveling landing platform by implementing the best concept to be used as a safe ground for UAVs to land and deploy on open waters. After conceptualizing multiple design ideas, these options were laid out in a decision matrix with four criteria: degrees of freedom, mechanical complexity, manufacturing, and cost. The chosen concept was the spherical parallel …

Classification Of Electropherograms Using Machine Learning For Parkinson’S Disease, Soroush Dehghan

Electronic Theses and Dissertations

Parkinson’s disease (PD) is a neurodegenerative movement disorder that progresses gradually over time. The onset of symptoms in people who are suffering from PD can vary from case to case, and it depends on the progression of the disease in each patient. The PD symptoms gradually develop and exacerbate the patient’s movements throughout time. An early diagnosis of PD could improve the outcomes of treatments and could potentially delay the progression of this disorder and that makes discovering a new diagnostic method valuable. In this study, I investigate the feasibility of using a machine learning (ML) approach to classify PD …

A Sound Artist’S Breakdown Of Field Recording Over History, Maria Chavez, Kristina Warren

Mathematics & Computer Science Faculty Scholarship

The conceptual sound artist, turntablist, and curator Maria Chavez muses about storing and accessing sounds. Building on Ursula Le Guin’s concept of the carrier bag, she describes four eras of sound recording and containment.

Data Analytics And Visualization For Virtual Simulation, Sri Lekha Koppaka

Browse all Theses and Dissertations

Healthcare organizations attract a diversity of caregivers and patients by providing essential care. While interacting with people of various races, ethnicity, and economical background, caregivers need to be empathetic and compassionate. Proper training and exposure are needed to understand the patient’s background and handle different situations and provide the best care for the patient. With social determinants of health (SDOH) as the basis, the thesis focuses on providing exposure through “Wright LIFE (Lifelike Immersion for Equity) - A simulation-based training tool” to two such scenarios covering patients from the LGBTQIA+ community & autism spectrum disorder (ASD). This interactive tool helps …

Computer Enabled Interventions To Communication And Behavioral Problems In Collaborative Work Environments, Ashutosh Shivakumar

Browse all Theses and Dissertations

Task success in co-located and distributed collaborative work settings is characterized by clear and efficient communication between participating members. Communication issues like 1) Unwanted interruptions and 2) Delayed feedback in collaborative work based distributed scenarios have the potential to impede task coordination and significantly decrease the probability of accomplishing task objective. Research shows that 1) Interrupting tasks at random moments can cause users to take up to 30% longer to resume tasks, commit up to twice the errors, and experience up to twice the negative effect than when interrupted at boundaries 2) Skill retention in collaborative learning tasks improves with …

A Knowledge-Based Model For Context-Aware Smart Service Systems, Thang Le Dinh, Thanh Thoa Pham Thi, Cuong Pham-Nguyen, Le Nguyen Hoai Nam

Articles

The advancement of the Internet of Things, big data, and mobile computing leads to the need for smart services that enable the context awareness and the adaptability to their changing contexts. Today, designing a smart service system is a complex task due to the lack of an adequate model support in awareness and pervasive environment. In this paper, we present the concept of a context-aware smart service system and propose a knowledge model for context-aware smart service systems. The proposed model organizes the domain and context-aware knowledge into knowledge components based on the three levels of services: Services, Service system, …

Transferring Studies Across Embodiments: A Case Study In Confusion Detection, Na Li, Robert J. Ross

Articles

Human-robot studies are expensive to conduct and difficult to control, and as such researchers sometimes turn to human-avatar interaction in the hope of faster and cheaper data collection that can be transferred to the robot domain. In terms of our work, we are particularly interested in the challenge of detecting and modelling user confusion in interaction, and as part of this research programme, we conducted situated dialogue studies to investigate users' reactions in confusing scenarios that we give in both physical and virtual environments. In this paper, we present a combined review of these studies and the results that we …

A Systematic Review Of How Cloud Infrastructure And Gdpr Have Affected Digital Investigations In A Multinational Business Context, Stuart Fraser, A.Omar Portillo-Dominguez

Other

With cloud infrastructure becoming an ever more popular platform for business network implementations, and with ever-tightening data protection regulation, the ability to carry out digital investigations has become more difficult. This has led to areas of research that have looked to restore the balance to digital investigations in this environment. These areas include the use of blockchain, data tracing, and digital forensics as a service. With so many methods to consider, this article looks at how each method aims to return the balance and make it possible to carry out an investigation that complies with new privacy regulations (e.g., the …

Topological Hierarchies And Decomposition: From Clustering To Persistence, Kyle A. Brown

Browse all Theses and Dissertations

Hierarchical clustering is a class of algorithms commonly used in exploratory data analysis (EDA) and supervised learning. However, they suffer from some drawbacks, including the difficulty of interpreting the resulting dendrogram, arbitrariness in the choice of cut to obtain a flat clustering, and the lack of an obvious way of comparing individual clusters. In this dissertation, we develop the notion of a topological hierarchy on recursively-defined subsets of a metric space. We look to the field of topological data analysis (TDA) for the mathematical background to associate topological structures such as simplicial complexes and maps of covers to clusters in …

Virtual Reality-Based Serious Role-Playing Games As Digital Experiential Learning Tools To Deliver Healthcare Skills Through Mobile Devices, Dixit Bharatkumar Patel

Browse all Theses and Dissertations

Inadequate professional training and practices related to health care may result in severe complications to care experiences and outcomes. Moreover, healthcare professionals are as susceptible to the possibility of implicit biases as any other group. Importantly, the health care training is critical and challenging as minor prejudicial beliefs have an adverse influence or serious consequences on patients' health outcomes. Thus, facilitating serious role-playing virtual care practices along with raising awareness of healthcare professionals about the enduring impact of implicit/explicit biases and Social Determinants of Health (SDH) on health outcomes assist to advance the patient-provider relation, care experiences (e.g., healthcare experience …

Automatically Inferring Image Bases Of Arm32 Binaries, Daniel T. Chong

Browse all Theses and Dissertations

Reverse engineering tools rely on the critical image base value for tasks such as correctly mapping code into virtual memory for an emulator or accurately determining branch destinations for a disassembler. However, binaries are often stripped and therefore, do not explicitly state this value. Currently available solutions for calculating this essential value generally require user input in the form of parameter configurations or manual binary analysis, thus these methods are limited by the experience and knowledge of the user. In this thesis, we propose a user-independent solution for determining the image base of ARM32 binaries and describe our implementation. Our …

Nanomechanical Resonators: Toward Atomic Scale, Bo Xu, Pengcheng Zhang, Jiankai Zhu, Zuheng Liu, Alexander Eichler, Xu-Qian Zheng, Jaesung Lee, Aneesh Dash, Swapnil More, Song Wu, Yanan Yanan, Hao Jia, Akshay Naik, Adrian Bachtold, Rui Yang, Philip X.-L. Feng, Zenghui Wang

Department of Electrical and Computer Engineering: Faculty Publications

The quest for realizing and manipulating ever smaller man-made movable structures and dynamical machines has spurred tremendous endeavors, led to important discoveries, and inspired researchers to venture to new grounds. Scientific feats and technological milestones of miniaturization of mechanical structures have been widely accomplished by advances in machining and sculpturing ever shrinking features out of bulk materials such as silicon. With the flourishing multidisciplinary field of low-dimensional nanomaterials, including one-dimensional (1D) nanowires/nanotubes, and two-dimensional (2D) atomic layers such as graphene/phosphorene, growing interests and sustained efforts have been devoted to creating mechanical devices toward the ultimate limit of miniaturization— genuinely down …

Dielectrophoretic Trapping Of Carbon Nanotubes For Temperature Sensing, Kaylee Burdette

Theses, Dissertations and Capstones

Conventional sensors are rapidly approaching efficiency limitations at their current size. In designing more efficient sensors, low dimensional materials such as carbon nanotubes (CNTs), quantum dots, and DNA origami can be used to enable higher degrees of sensitivity. Because of the high atomic surface to core ratio, these materials can be used to detect slight changes in chemical composition, strain, and temperature. CNTs offer unique advantages in different types of sensors due to their electromechanical properties. In temperature sensing, the high responsiveness to temperature and durability can be used to produce an accurate, reliable sensor in even extreme temperatures. This …

Agile Research - Getting Beyond The Buzzword, Trupti Narayan Rane

Engineering Management & Systems Engineering Faculty Publications

"Oh yeah, we're an Agile shop, we gave up Waterfall years ago." - product owners, managers, or could be anyone else. You will seldom have a conversation with a product or software development team member without the agile buzzword thrown at you at the drop of a hat. It would not be an oversell to say that Agile software development has been adopted at a large scale across several big and small organizations. Clearly, Agile is an ideology that is working, which made me explore more on its applicability in research. As someone who has been in the Information Technology …

Ransombuster Iot: A Intrusion Detection And Dataset Creation Tool For Ransomware Attacks Within Iot Networks, Jackson M. Walker

Cybersecurity Undergraduate Research Showcase

The proposed research follows the design-science guidelines(Hevner, 2004). This paper uses these design-science methods for developing the guidelines for the implementation of the proposed architecture, understanding previous research contributions, and evaluating of research. This paper proposes a network artifact for studying ransomware IoT intrusion detection techniques and offers a proposed network architecture to serve as a framework for creating a publicly available dataset for IoT research on ransomware.