Computational Engineering Commons^™

Multicellular And Multiscale Models Of Microbes And Host Systems, Elebeoba May

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

I-Guide Climbers: A Model For Multidisciplinary Academic Labs For Early Career Development, Iman Haqiqi, Wei Hu, Ramya Kumaran, Pin-Ching Li, Nicholas Manning, Alex Michels, Ayman Nassar, Jinwoo Park, Jimeng Shi, Adam Tonks, Zhaonan Wang

I-GUIDE Forum

In this paper, we propose a new form of multidisciplinary academic collaboration that goes beyond the traditional modes of knowledge exchange. We argue that most research collaboration today is based on interactions between closely related disciplines, in which researchers share data, methods, and insights within a common framework or problem. However, such collaboration may not foster the development of the communication and management skills essential to a multi-disciplinary research career. Therefore, we suggest establishing a network of researchers from divergent, yet complementary, disciplines who are interested in improving these skills through regular interactions and feedback. The main goal of this …

Deep Semantic Hashing For Aerial Livestock Detection, Shosei Anegawa, Franz Kurfess, Sumona Mukhopadhyay

College of Engineering Summer Undergraduate Research Program

The goal of this project is to be able to accurately detect and count livestock in footage captured by a drone in real time. The main problems with this arise from the fact that a drone can only carry limited computing resources, and hashing is conventionally thought of as a great method of doing image classification very quickly and thus even on low-power devices. In this project, we use both a Faster-RCNN, which is a state-of-the art object detection model as a benchmark to develop a hashing model that can perform a similar task much more quickly. These two models …

National Conference On Computing 4.0 Empowering The Next Generation Of Technology (Era Of Computing 4.0 And Its Impact On Technology And Intelligent Systems), Subhrajit Pradhan Prof (Dr), Chandan Kumar Sahoo Dr., Tarini Prasad Pattnaik Prof., Tamasha Priyadarshini Prof

Conference Proceedings - Full Volumes

As we enter the era of Computing 4.0, the landscape of technology and intelligent systems is rapidly evolving, with groundbreaking advancements in artificial intelligence, machine learning, data science, and beyond. The theme of this conference revolves around exploring and shaping the future of these intelligent systems that will revolutionize industries and transform the way we live, work, and interact with technology.

Conference Topics

• Quantum Computing and Quantum Information
• Edge Computing and Fog Computing
• Artificial Intelligence and Machine Learning in Computing 4.0
• Internet of Things (IOT) and Smart Cities
• Block chain and Distributed Ledger Technologies
• Cybersecurity and Privacy in the Computing …

Predictive Maintenance Of Base Transceiver Station Power System Using Xgboost Algorithm: A Case Study Of Econet Wireless, Zimbabwe, Tavengwa Masamha

African Conference on Information Systems and Technology

Faults incurred by Base Transceiver Stations pose challenges to telecommunication organisations. Mostly the faults are due to BTS failures. BTS power system failures can have a significant impact on organizational performance in the telecommunications industry. These failures can cause disruptions in mobile network coverage, leading to dropped calls, slow data speeds, and difficulty connecting to the network. ECONET Zimbabwe has been experiencing unprecedented BTS power system failures for the past five years. Team Data Science Process was the pillar of the study methodology. The XGBoost algorithm was employed to develop a predictive model for the maintenance of Base Transceiver Station …

Automatic Cardiac Mri Image Segmentation And Mesh Generation, Ziyuan Li

McKelvey School of Engineering Theses & Dissertations

Segmenting and reconstructing cardiac anatomical structures from magnetic resonance (MR) images is essential for the quantitative measurement and automatic diagnosis of cardiovascular diseases [1]. However, manual evaluation of the time-series cardiac MRI (CMRI) obtained during routine clinical care are laborious, inefficient, and tends to produce biased and non-reproducible results [2]. This thesis proposes an end-to-end pipeline for automatically segmenting short-axis (SAX) CMRI images and generating high-quality 2D and 3D meshes suitable for finite element analysis. The main advantage of our approach is that it can not only work as a stand-alone pipeline for the automatic CMR image segmentation and mesh …

Permeability Prediction For Expansive Soil Based On Physical Properties Using Artificial Neural Networks, Ferry Fatnanta, Imam Suprayogi, Nicola Rabb Ranata, Soewignjo Agus Nugroho, Agus Ika Putra

Makara Journal of Technology

Permeability is a soil parameter related to the construction industry to understand the processes of infiltration, runoff, and settlement. The risk of testing errors is inevitable in permeability investigations, especially in expansive soils. Trial and error in permeability testing becomes difficult due to soils with small pore sizes and large shrinkage expansion. Several studies related to soil physical properties that affect permeability have been conducted. However, the correlation results obtained still have poor accuracy. Artificial neural networks (ANN) are machine learning systems that can change their structure to solve problems that are included in the system. The use of ANNs …

Using Dynamic Task Allocation To Evaluate Driving Performance, Situation Awareness, And Cognitive Load At Different Levels Of Partial Autonomy, Viraj R. Patel

Theses and Dissertations

The state of the art of autonomous vehicles requires operators to remain vigilant while performing secondary tasks. The goal of this research was to investigate how dynamically allocated secondary tasks affected driving performance, cognitive load, and situation awareness. Secondary tasks were presented at rates based on the autonomy level present and whether the autonomous system was engaged. A rapid secondary task rate was also presented for two short periods regardless of whether autonomy was engaged. There was a three-minute familiarization phase followed by a data collection phase where participants responded to secondary tasks while preventing the vehicle from colliding into …

Singular Integration By Interpolation For Integral Equations, Ioannis Kyriakou

Doctoral Dissertations

Maxwell’s equations and the laws of Electromagnetics (EM) govern a plethora of electrical, optical phenomena with applications on wireless, cellular, communications, medical and computer hardware technologies to name a few. A major contributor to the technological progress in these areas has been due to the development of simulation and design tools that enable engineers and scientists to model, analyze and predict the EM interactions in their systems of interest. At the core of such tools is the field of Computational Electromagnetics (CEM), which studies the solution of Maxwell’s equations with the aid of computers. The advances in these applications technologies, …

Graphical Image Rendering: Modeling, Animation Of Facial Or Wild Images, Rohit Kaushik, Chirag Vashisht, Eva Kaushik

International Journal of Computer and Communication Technology

In this comparative study, we intend to analyse different methodologies to perform 3-Dimensional modeling and printing, by using raw images as input without any supervision by a human. Since the input consists of only raw images, the foundation of the methods is finding symmetry in images. But the images that seem symmetric are not symmetric due to the perspective effect and utterance of other factors. The method uses factors like depth, albedo, point of view, and lighting from the input image to formulate 3D shapes. A 3D template model with feature points is created, and by deforming the 3D template …

Employee Attrition System Prediction Using Random Forest Classifier, Soumen Nayak, Pranati Palai

International Journal of Computer and Communication Technology

Despite rising unemployment, most job coverage of the COVID-19 outbreak has concentrated on layoffs. Employees have been fired for reasons related to the epidemic, which has been a less prominent issue. COVID-19 is still doing damage to the country's economy. Companies are in the midst of a recession, so they are beginning to fire off unproductive employees. Making critical decisions like laying off employees or cutting an employee's compensation is a challenging undertaking that must be done with extreme attention and accuracy. Adding negligence would harm the employee's career and the company's image in the industry. In this paper, we …

Visualizing Transaction-Level Modeling Simulations Of Deep Neural Networks, Nataniel Farzan, Emad Arasteh

Engineering Technical Reports

The growing complexity of data-intensive software demands constant innovation in computer hardware design. Performance is a critical factor in rapidly evolving applications such as artificial intelligence (AI). Transaction-level modeling (TLM) is a valuable technique used to represent hardware and software behavior in a simulated environment. However, extracting actionable insights from TLM simulations is not a trivial task. We present Netmemvisual, an interactive, cross-platform visualization tool for exposing memory bottlenecks in TLM simulations. We demonstrate how Netmemvisual helps system designers rapidly analyze complex TLM simulations to find memory contention. We describe the project’s current features, experimental results with two state-of-the-art deep …

Evaluation Of Static Horizontal Louvers On Annual Daylighting Performance In Classrooms, Kamal A. Saleem, Samir S. Hosny, Ashraf Nessim

Future Engineering Journal

Daylighting has a great impact on students’ health, learning performance, and productivity. The goal of this paper is to enhance daylighting performance by examining year-round daylighting performance of Southern facades in the case of one central window in a classroom located in Cairo, Egypt by using static external horizontal shading devices during the Fall, Spring and Summer semesters The scope of the study is to evaluate and assess the effect of the window-to-wall ratio (WWR) in addition to the louvers’ configurations of depth and count parameters of the classroom on annual daylighting performance metrics for classrooms’ southern facades by using …

Who Is (Communicatively More) Responsible Behind The Wheel? Applying The Theory Of Communicative Responsibility To Tam In The Context Of Using Navigation Technology, Sungbin Youk, Hee Sun Park

Human-Machine Communication

By examining how perceived usefulness and ease of use relate to the user’s perception (i.e., communicative responsibility), the communicative behavior of the navigation system (i.e., the landmarks used to give directions), and the context of driving (i.e., familiarity of the driving location), this study applies the theory of communicative responsibility to the technology acceptance model to better understand why users are more likely to adopt certain navigation technologies while driving. We hypothesized that users’ perceived symmetry in communicative responsibility independently and interactively (with communicative behavior of the navigation system and the driving situation) affects perceived ease of use and usefulness …

Human-Machine Communication: Complete Volume. Volume 6

Human-Machine Communication

his is the complete volume of HMC Volume 6.

Deep Cnn-Based Automated Optical Inspection For Aerospace Components, Shashi Bhushan Jha

Doctoral Dissertations and Master's Theses

ABSTRACT

The defect detection problem is of outmost importance in high-tech industries such as aerospace manufacturing and is widely employed using automated industrial quality control systems. In the aerospace manufacturing industry, composite materials are extensively applied as structural components in civilian and military aircraft. To ensure the quality of the product and high reliability, manual inspection and traditional automatic optical inspection have been employed to identify the defects throughout production and maintenance. These inspection techniques have several limitations such as tedious, time- consuming, inconsistent, subjective, labor intensive, expensive, etc. To make the operation effective and efficient, modern automated optical inspection …

Resilience Model For Teams Of Autonomous Unmanned Aerial Vehicles (Uav) Executing Surveillance Missions, Robert Koeneke

Doctoral Dissertations and Master's Theses

Teams of low-cost Unmanned Aerial Vehicles (UAVs) have gained acceptance as an alternative for cooperatively searching and surveilling terrains. These UAVs are assembled with low-reliability components, so unit failures are possible. Losing UAVs to failures decreases the team's coverage efficiency and impacts communication, given that UAVs are also communication nodes. Such is the case of a Flying Ad Hoc Network (FANET), where the failure of a communication node may isolate segments of the network covering several nodes. The main goal of this study is to develop a resilience model that would allow us to analyze the effects of individual UAV …

Neurocomputing And Interfacing Digital Tasting System: Research, Design, And Evaluation, Amira J. Zaylaa, Ahmad El Hajj

BAU Journal - Science and Technology

The continuous evolution in computing and interfacing has been extended to develop multi-sensory experiences in many domains such as neurological, auditory, vision, and haptic domains. So far, only a few remarkable system approaches have been approved to be serving the taste sensation digitally. Although taste sensation is linked to the brain, there is a lack of optimal neurocomputing digital taste sensation systems. Our study provides a new neurocomputing method to digitally stimulate the sense of taste by electrical stimulation on the human tongue. We aim to link chemical stimulation and electrical stimulation in order to design an electronic interface for …

Resources Based Planning Framework For Infrastructure Maintenance And Rehabilitation Projects, Heba Gad

Theses and Dissertations

Infrastructure maintenance and rehabilitation projects involve activities scattered over a large geographical area (e.g., scattered road segments maintenance, telecom towers maintenance program, etc.). Planning such projects require a resource-based approach that accounts for the implications of resource mobility between activities’ locations in terms of time & cost. Existing scheduling techniques fall short of addressing the unique challenges of the scattered nature of these projects in combination with organization's limited resources availability. To address this need, this research presents a resources-based planning framework for infrastructure maintenance and rehabilitation scattered projects with the objective of enhancing resources utilization achieving time and cost …

Deep Learning-Based Gated Recurrent Unit Approach To Stock Market Forecasting: An Analysis Of Intel's Stock Data, Nrusingha Tripathy, Ibanga Kpereobong Friday, Dharashree Rath, Debasish Swapnesh Kumar Nayak, Subrat Kumar Nayak

International Journal of Smart Sensor and Adhoc Network

The stock price index prediction is a very challenging task that's because the market has a very complicated nonlinear movement system. This fluctuation is influenced by many different factors. Multiple examples demonstrate the suitability of Machine Learning (ML) models like Neural Network algorithms (NN) and Long Short-Term Memory (LSTM) for such time series predictions, as well as how frequently they produce satisfactory outcomes. However, relatively few studies have employed robust feature engineering sequence models to forecast future prices. In this paper, we propose a cutting-edge stock price prediction model based on a Deep Learning (DL) technique. We chose the stock …