Computer Aided Diagnosis System For Breast Cancer Using Deep Learning.,
2022
University of Louisville
Computer Aided Diagnosis System For Breast Cancer Using Deep Learning., Asma Baccouche
Electronic Theses and Dissertations
The recent rise of big data technology surrounding the electronic systems and developed toolkits gave birth to new promises for Artificial Intelligence (AI). With the continuous use of data-centric systems and machines in our lives, such as social media, surveys, emails, reports, etc., there is no doubt that data has gained the center of attention by scientists and motivated them to provide more decision-making and operational support systems across multiple domains. With the recent breakthroughs in artificial intelligence, the use of machine learning and deep learning models have achieved remarkable advances in computer vision, ecommerce, cybersecurity, and healthcare. Particularly, numerous …
Role Of Machine Learning In Early Diagnosis Of Kidney Diseases.,
2022
University of Louisville
Role Of Machine Learning In Early Diagnosis Of Kidney Diseases., Mohamed Nazih Mohamed Ibrahim Shehata
Electronic Theses and Dissertations
Machine learning (ML) and deep learning (DL) approaches have been used as indispensable tools in modern artificial intelligence-based computer-aided diagnostic (AIbased CAD) systems that can provide non-invasive, early, and accurate diagnosis of a given medical condition. These AI-based CAD systems have proven themselves to be reproducible and have the generalization ability to diagnose new unseen cases with several diseases and medical conditions in different organs (e.g., kidneys, prostate, brain, liver, lung, breast, and bladder). In this dissertation, we will focus on the role of such AI-based CAD systems in early diagnosis of two kidney diseases, namely: acute rejection (AR) post …
Adaptive Risk Network Dependency Analysis Of Complex Hierarchical Systems,
2022
Old Dominion University
Adaptive Risk Network Dependency Analysis Of Complex Hierarchical Systems, Katherine L. Smith
Computational Modeling & Simulation Engineering Theses & Dissertations
Recently the number, variety, and complexity of interconnected systems have been increasing while the resources available to increase resilience of those systems have been decreasing. Therefore, it has become increasingly important to quantify the effects of risks and the resulting disruptions over time as they ripple through networks of systems. This dissertation presents a novel modeling and simulation methodology which quantifies resilience, as impact on performance over time, and risk, as the impact of probabilistic disruptions. This work includes four major contributions over the state-of-the-art which are: (1) cyclic dependencies are captured by separation of performance variables into layers which …
A Novel Testbed For Evaluation Of Operational Technology Communications Protocols And Their On-Device Implementations,
2022
University of Nebraska-Lincoln
A Novel Testbed For Evaluation Of Operational Technology Communications Protocols And Their On-Device Implementations, Matthew Boeding
Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research
Operational Technology (OT) and Infrastructure Technology (IT) systems are converging with the rapid addition of centralized remote management in OT systems. Previously air-gapped systems are now interconnected through the internet with application-specific protocols. This has led to systems that had limited access points being remotely accessible. In different OT sectors, legacy protocols previously transmitted over serial communication were updated to allow internet communication with legacy devices. New protocols such as IEC-61850 were also introduced for monitoring of different OT resources. The IEC-61850 standard’s Generic Object Oriented Substation Event (GOOSE) protocol outlines the representation and communication of a variety of different …
Femtosecond Laser Surface Processing To Create Self-Organized Micro- And Nano-Scale Features On Composite And Ceramic Materials,
2022
University of Nebraska-Lincoln
Femtosecond Laser Surface Processing To Create Self-Organized Micro- And Nano-Scale Features On Composite And Ceramic Materials, Nate Koeppe
Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research
Femtosecond laser surface processing (FLSP) is applied to a range of materials in this thesis. The materials studied were a carbon fiber reinforced polymer (CFRP), a thermosetting polymer, silicon nitride (Si3N4), and ceramic alumina. The CFRP is a composite material consisting of a thermosetting polymer and carbon fibers. The CFRP are referred to as a composite and the thermosetting polymer is referred to as a resin in this thesis. Alumina can exist in many different forms. The alumina used is 0.5 mm thick nonporous alumina sheets purchased from McMaster-Carr, and will be referred to as alumina …
Miner-Town: Self-Driving Robotics Testbed For Vehicle-To-Grid Simulation,
2022
University of Texas at El Paso
Miner-Town: Self-Driving Robotics Testbed For Vehicle-To-Grid Simulation, Carlos Adolfo Cortes Pliego
Open Access Theses & Dissertations
Autonomous vehicles and Vehicle-to-Grid (V2G) technology bring promising implications in boosting energy efficiency, helping the environment, improving our productivity, and have the potential to stabilize the grid during peak times and reduce car accidents. However, implementing and testing these complex novel technologies in the real world comes with high risks and investment. For these reasons, there is the need to research, test, and validate these theories in a compact and controlled environment at minimal cost. This thesis presents a modular autonomous vehicle testbed for the exploration of Vehicle-to-Grid and charging activities in pedestrian filled environments such as a University campus. …
Structured Encryption For Knowledge Graphs,
2022
Singapore Management University
Structured Encryption For Knowledge Graphs, Yujie Xue, Lanxiang Chen, Yu Mi, Lingfang Zeng, Fatemeh Rezaeibagha, Robert H. Deng
Research Collection School Of Computing and Information Systems
We investigate the problem of structured encryption (STE) for knowledge graphs (KGs) where the knowledge of data can be efficiently and privately queried. Presently, the application of natural language processing (NLP) for knowledge-based search is gradually emerging. Compared with the traditional search based only on keywords of documents-symmetric searchable encryption (SSE), the knowledge-based search system transforms the latent knowledge contained in documents into a semantic network as a knowledge base, which greatly improves the accuracy and relevance of search results. In order to develop a knowledge-based search, the contents of documents are analyzed and extracted using KG techniques (e.g. multi-relational …
Application Of Deep Learning For Medical Sciences And Epidemiology Data Analysis And Diagnostic Modeling,
2022
University of Southern Mississippi
Application Of Deep Learning For Medical Sciences And Epidemiology Data Analysis And Diagnostic Modeling, Somenath Chakraborty
Dissertations
Machine Learning and Artificial Intelligence have made significant progress concurrent with new advancements in hardware and software technologies. Deep learning methods heavily utilize parallel computing and Graphical Processing Units(GPU). It is already used in many applications ranging from image classification, object detection, segmentation, cyber security problems and others. Deep Learning is emerging as a viable choice in dealing with today’s real-time medical problems. We need new methods and technologies in the field of Medical Science and Epidemiology for detecting and diagnosing emerging threats from new viruses such as COVID-19. The use of Artificial Intelligence in these domains is becoming more …
Optimized Three Deep Learning Models Based-Pso Hyperparameters For Beijing Pm2.5 Prediction,
2022
Hohai University, China and Universitas Ahmad Dahlan, Indonesia
Optimized Three Deep Learning Models Based-Pso Hyperparameters For Beijing Pm2.5 Prediction, Andri Pranolo, Yingchi Mao, Aji Prasetya Wibawa, Agung Bella Putra Utama, Felix Andika Dwiyanto
Knowledge Engineering and Data Science
Deep learning is a machine learning approach that produces excellent performance in various applications, including natural language processing, image identification, and forecasting. Deep learning network performance depends on the hyperparameter settings. This research attempts to optimize the deep learning architecture of Long short term memory (LSTM), Convolutional neural network (CNN), and Multilayer perceptron (MLP) for forecasting tasks using Particle swarm optimization (PSO), a swarm intelligence-based metaheuristic optimization methodology: Proposed M-1 (PSO-LSTM), M-2 (PSO-CNN), and M-3 (PSO-MLP). Beijing PM2.5 datasets was analyzed to measure the performance of the proposed models. PM2.5 as a target variable was affected by dew point, pressure, …
Comparison Of Machine Learning Techniques For Activities Of Daily Living Classification With Electromyographic Data,
2022
Western University
Comparison Of Machine Learning Techniques For Activities Of Daily Living Classification With Electromyographic Data, Sergio A. Salinas, Mohamed Elgalhud, Luke Tambakis, Sanket Salunke, Kshitija Patel, Kenneth Mcisaac, Katarina Grolinger, Ana Luisa Trejos, Abdelkader Ouda, Hamada Ghenniwa
Electrical and Computer Engineering Publications
Advances in data science and wearable robotic devices present an opportunity to improve rehabilitation outcomes. Some of these devices incorporate electromyography (EMG) electrodes that sense physiological patient activity, making it possible to develop rehabilitation systems able to assess the patient’s progress when performing activities of daily living (ADLs). However, additional research is needed to improve the ability to interpret EMG signals. To address this issue, an off-line classification approach for the 26 upper-limb ADLs included in the KIN-MUS UJI dataset is presented in this paper. The ADLs were performed by 22 subjects, while seven EMG signals were recorded from their …
Simulating Sub-Threshold Communication Channels Through Neurons,
2022
University of Nebraska-Lincoln
Simulating Sub-Threshold Communication Channels Through Neurons, Richard Maina
School of Computing: Dissertations, Theses, and Student Research
Molecular Communication is an emerging paradigm with the potential to revolutionize the technology behind wearable and implantable devices and the broad range of functions they support, from tracking physical activity to medical diagnostics. This can be achieved through intra-body communication networks that take advantage of natural biological processes as a means of transmitting, propagating and receiving information. In this thesis we focus particularly on using the neuron as a means to facilitate information transfer for interconnected wearable or implantable devices through a technique known as sub-threshold electrical stimulation. We develop upon a prior work by introducing a linear model of …
Game On,
2022
DePaul University
Game On
DePaul Magazine
Video game industry icon Eugene Jarvis and DePaul alumna and Trustee Sasha Gerritson take the College of Computing and Digital Media to the next level with a landmark gift. The gift renames the college in honor of Jarvis and launches the Jarvis Student Center for Innovation and Collaboration, a multidisciplinary, student-focused space.
Advance In Contextualizing Focal Structure Sets In Complex Network Analysis,
2022
University of Arkansas Little Rock
Advance In Contextualizing Focal Structure Sets In Complex Network Analysis, Mustafa Alassad
Theses and Dissertations
Focal Structures are key sets of individuals who may be responsible for online socially minded events, protests, or leading citizen engagement efforts on social media networks. Discovering focal structure sets who able to promote online social campaigns is important, but complex, as they are typically active locally, globally, and acting unlike central users and influencers, focal structure sets can influence large social media networks. Researchers applied a greedy algorithm to discover focal structure sets in social media networks. However, the outcomes were lacking on the users’ activities and interests that made the analysis incomplete. In this research, I present a …
A Modified Point Matching Method For Non-Rigid Image Registration,
2022
1.Dept. of Computer Science and Technology, Changzhi College, Changzhi 046011, China;
A Modified Point Matching Method For Non-Rigid Image Registration, Jintai Shangguan, Yawen Dang, Wei Lian
Journal of System Simulation
Abstract: Aiming at the problem that the registration results tend to converge to local minima due to the complexity of the relative position changes between two point sets in the non-rigid body point matching process, a joint estimation method for non-rigid body point matching based on precenter alignment is proposed, a modified matching method for non-rigid image registration based on centre preregistration is proposed. To better achieve the point matching accuracy between two point sets, a centre preregistration step is applied before the iterative closest point matching algorithm, which converges to a solution more close to a global optimum and …
Transfer Method Of Operational Simulation Experiment Scope Using Compromised Case-Based Reasoning,
2022
1.Graduate school, National Defense University, Beijing 100091;2.Joint Operations College, National Defense University, Beijing 100091;
Transfer Method Of Operational Simulation Experiment Scope Using Compromised Case-Based Reasoning, Jun Ma, Jingyu Yang, Xi Wu
Journal of System Simulation
Abstract: The scope of operational simulation experiment is usually determined by experts, which costs relatively high. In order to transfer the knowledge of experimental scope selection from historical data of operational simulation experiment to new operational experiment cases, the method of compromised case-based reasoning is proposed. According to the data characteristics of the case, the representation method of the operational simulation experiment case is proposed; according to the structure and attribute characteristics of the case, the hybrid similarity calculation method of subjective and objective comprehensive weighting is proposed; aiming at the problems of retrieval failure and less information content …
Optimal Dispatch Of Integrated Energy System Considering Ladder-Type Carbon Trading,
2022
1.North China Electric Power University, Beijing 102206, China;
Optimal Dispatch Of Integrated Energy System Considering Ladder-Type Carbon Trading, Liying Wang, Jialin Lin, Houqi Dong, Ming Zeng, Yuqing Wang
Journal of System Simulation
Abstract: With the development of the electricity market and carbon market,the introduction of demand response and carbon trading mechanisms into the operation and dispatch of integrated energy systems will help guide users and system operators to optimize electricity consumption and dispatch plans.The comprehensive incentive measures such as time-of-use electricity prices and demand response incentive subsidies are used to guide users to participate in demand response.A two-layer stochastic optimal scheduling model for a comprehensive energy system considering the ladder-type carbon trading mechanism and demand response is constructed based on IGDT (information gap decision theory) theory.The two-layer model is converted …
Bi-Level Optimization Of Distribution Network For Hybrid Energy Storage System Of Storage Battery And Hydrogen Storage,
2022
1.State Grid Anhui Electric Power Company, Bengbu Power Supply Company, Bengbu 233000, China;
Bi-Level Optimization Of Distribution Network For Hybrid Energy Storage System Of Storage Battery And Hydrogen Storage, Feibo Feng, Xingde Yan, Baoqiang Zheng, Xiaofeng Yin, Mengzhen Zhou, Xin Jiang
Journal of System Simulation
Abstract: Under the background of carbon neutralization and emission peaking goals and the utilization of clean hydrogen energy, aiming at the demand of distribution network configuring electrochemical energy storage and hydrogen energy storage system to form a hybrid energy storage system to improve power quality, a bi-level optimization model of the hybrid energy storage system is established. The upper level location and capacity model comprehensively considers the investment cost, network loss cost and voltage offset, while the lower level optimization operation model considers the operation cost of hybrid energy storage system, and the voltage stability index is introduced for evaluation. …
Simulation Model Of Forest Fire Spread Based On Swarm Intelligence,
2022
1.School of Computer and Information Engineering, Central South University of Forestry & Technology, Changsha 410004, China;
Simulation Model Of Forest Fire Spread Based On Swarm Intelligence, Aibin Chen, Fubo Ding, Guoxiong Zhou, Bo Zhou
Journal of System Simulation
Abstract: Aiming at the shortcomings of high computational complexity and low simulation accuracy of traditional forest fire spread model, a forest fire spread simulation model based on swarm intelligence is proposed.By establishing fuel factor matrix and landform factor matrix, and combining with the real-time meteorological information, the computational complexity is reduced; the spread behavior of the forest fire is abstracted as the cluster behavior of each module fire point, and the correlation between modules is considered to improve the accuracy of forest fire spread simulation model.The model is compared with Wang Zhengfei model and two-dimensional cellular automata model. …
Two Stage Optimization Algorithm To Solve The Green Packing Vehicle Routing Problem,
2022
1.Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China;
Two Stage Optimization Algorithm To Solve The Green Packing Vehicle Routing Problem, Rong Hu, Wen Jiang, Bin Qian, Naikang Yu
Journal of System Simulation
Abstract: The green open vehicle routing problem with two-dimensional loading constraints (2L-GOVRP) is integration of the green open vehicle routing problem and two-dimensional bin packing problem. The model of 2L-GOVRP is established and a two-stage optimization algorithm (TSOA) is proposed to minimize fuel consumption. In the first stage of TSOA, adaptive whale optimization algorithm (AWOA) is designed to solve the vehicle routing problem, which determine the initial delivery route of the vehicle (the initial solution of 2L-GOVRP). The algorithm has four kinds of variable neighborhoods local operation to perform a local search. In the second stage of TSOA, the skyline …
A Method Of Loose Coupling Entity Modeling Based On Variable Rules,
2022
Electronic Encounter Institution, National University of Defense Technology, Hefei 230037, China;
A Method Of Loose Coupling Entity Modeling Based On Variable Rules, Zheng Yang, Zhimin Xiang, Shiwen Ma
Journal of System Simulation
Abstract: Operational Entity Modeling is a hot research topic in the field of combat simulation. A loose coupling entity modeling method based on variable rules is proposed. The architecture of operational entity model based on variable rules and the internal and external interaction mechanism of the model are presented in terms of entity, mission, action, interaction, event and rule. On this basis, the running framework of operational entity model is designed, and the entity model uniform scheduling mechanism is standardized, which solves the problems of over-tight coupling of operational rules in the operational entity model and low reliability of the …
