Open Access. Powered by Scholars. Published by Universities.®

Physical Sciences and Mathematics Commons™

Open Access. Powered by Scholars. Published by Universities.®

Artificial Intelligence and Robotics

Institution
Keyword
Publication Year
Publication
Publication Type
File Type

Articles 1681 - 1710 of 8518

Full-Text Articles in Physical Sciences and Mathematics

Evolution Of Winning Solutions In The 2021 Low-Power Computer Vision Challenge, Xiao Hu, Ziteng Jiao, Ayden Kocher, Zhenyu Wu, Junjie Liu, James C. Davis, George K. Thiruvathukal, Yung-Hsiang Lu Jan 2023

Evolution Of Winning Solutions In The 2021 Low-Power Computer Vision Challenge, Xiao Hu, Ziteng Jiao, Ayden Kocher, Zhenyu Wu, Junjie Liu, James C. Davis, George K. Thiruvathukal, Yung-Hsiang Lu

Computer Science: Faculty Publications and Other Works

Mobile and embedded devices are becoming ubiquitous. Applications such as rescue with autonomous robots and event analysis on traffic cameras rely on devices with limited power supply and computational sources. Thus, the demand for efficient computer vision algorithms increases. Since 2015, we have organized the IEEE Low-Power Computer Vision Challenge to advance the state of the art in low-power computer vision. We describe the competition organizing details including the challenge design, the reference solution, the dataset, the referee system, and the evolution of the solutions from two winning teams. We examine the winning teams’ development patterns and design decisions, focusing …

Go to article

A Survey On Artificial Intelligence-Based Acoustic Source Identification, Ruba Zaheer, Iftekhar Ahmad, Daryoush Habibi, Kazi Y. Islam, Quoc Viet Phung Jan 2023

A Survey On Artificial Intelligence-Based Acoustic Source Identification, Ruba Zaheer, Iftekhar Ahmad, Daryoush Habibi, Kazi Y. Islam, Quoc Viet Phung

Research outputs 2022 to 2026

The concept of Acoustic Source Identification (ASI), which refers to the process of identifying noise sources has attracted increasing attention in recent years. The ASI technology can be used for surveillance, monitoring, and maintenance applications in a wide range of sectors, such as defence, manufacturing, healthcare, and agriculture. Acoustic signature analysis and pattern recognition remain the core technologies for noise source identification. Manual identification of acoustic signatures, however, has become increasingly challenging as dataset sizes grow. As a result, the use of Artificial Intelligence (AI) techniques for identifying noise sources has become increasingly relevant and useful. In this paper, we …

Go to article

Communety: Deep Learning-Based Face Recognition System For The Prediction Of Cohesive Communities, Syed Afaq Ali Shah, Weifeng Deng, Muhammad Aamir Cheema, Abdul Bais Jan 2023

Communety: Deep Learning-Based Face Recognition System For The Prediction Of Cohesive Communities, Syed Afaq Ali Shah, Weifeng Deng, Muhammad Aamir Cheema, Abdul Bais

Research outputs 2022 to 2026

Effective mining of social media, which consists of a large number of users is a challenging task. Traditional approaches rely on the analysis of text data related to users to accomplish this task. However, text data lacks significant information about the social users and their associated groups. In this paper, we propose CommuNety, a deep learning system for the prediction of cohesive networks using face images from photo albums. The proposed deep learning model consists of hierarchical CNN architecture to learn descriptive features related to each cohesive network. The paper also proposes a novel Face Co-occurrence Frequency algorithm to quantify …

Go to article

Chatgpt In Higher Education: Considerations For Academic Integrity And Student Learning, Miriam Sullivan, Andrew Kelly, Paul Mclaughlan Jan 2023

Chatgpt In Higher Education: Considerations For Academic Integrity And Student Learning, Miriam Sullivan, Andrew Kelly, Paul Mclaughlan

Research outputs 2022 to 2026

The release of ChatGPT has sparked significant academic integrity concerns in higher education. However, some commentators have pointed out that generative artificial intelligence (AI) tools such as ChatGPT can enhance student learning, and consequently, academics should adapt their teaching and assessment practices to embrace the new reality of living, working, and studying in a world where AI is freely available. Despite this important debate, there has been very little academic literature published on ChatGPT and other generative AI tools. This article uses content analysis to examine news articles (N=100) about how ChatGPT is disrupting higher education, concentrating specifically on Australia, …

Go to article

Artificial Intelligence And Precision Health Through Lenses Of Ethics And Social Determinants Of Health: Protocol For A State-Of-The-Art Literature Review, Sarah Wamala-Andersson, Matt X. Richardson, Sara Landerdahl Stridsberg, Jillian Ryan, Felix Sukums, Yong-Shian Goh Jan 2023

Artificial Intelligence And Precision Health Through Lenses Of Ethics And Social Determinants Of Health: Protocol For A State-Of-The-Art Literature Review, Sarah Wamala-Andersson, Matt X. Richardson, Sara Landerdahl Stridsberg, Jillian Ryan, Felix Sukums, Yong-Shian Goh

Research outputs 2022 to 2026

Background: Precision health is a rapidly developing field, largely driven by the development of artificial intelligence (AI)–related solutions. AI facilitates complex analysis of numerous health data risk assessment, early detection of disease, and initiation of timely preventative health interventions that can be highly tailored to the individual. Despite such promise, ethical concerns arising from the rapid development and use of AI-related technologies have led to development of national and international frameworks to address responsible use of AI. Objective: We aimed to address research gaps and provide new knowledge regarding (1) examples of existing AI applications and what role they play …

Go to article

Emulating Future Neurotechnology Using Magic, Jay A. Olson, Mariève Cyr, Despina Z. Artenie, Thomas Strandberg, Lars Hall, Matthew L. Tompkins, Amir Raz, Petter Johansson Dec 2022

Emulating Future Neurotechnology Using Magic, Jay A. Olson, Mariève Cyr, Despina Z. Artenie, Thomas Strandberg, Lars Hall, Matthew L. Tompkins, Amir Raz, Petter Johansson

Psychology Faculty Articles and Research

Recent developments in neuroscience and artificial intelligence have allowed machines to decode mental processes with growing accuracy. Neuroethicists have speculated that perfecting these technologies may result in reactions ranging from an invasion of privacy to an increase in self-understanding. Yet, evaluating these predictions is difficult given that people are poor at forecasting their reactions. To address this, we developed a paradigm using elements of performance magic to emulate future neurotechnologies. We led 59 participants to believe that a (sham) neurotechnological machine could infer their preferences, detect their errors, and reveal their deep-seated attitudes. The machine gave participants randomly assigned positive …

Go to article

Simulation-Driven Based Utility Evaluation And Recommendation Of Expressway Proactive Speed Limit, Geqi Qi, Sijin Liu, Yikang He, Meng Wang, Ailing Huang Dec 2022

Simulation-Driven Based Utility Evaluation And Recommendation Of Expressway Proactive Speed Limit, Geqi Qi, Sijin Liu, Yikang He, Meng Wang, Ailing Huang

Journal of System Simulation

Abstract: Outside the specific punishment area, the traditional roadside passive speed limit mode lacks traffic management, and thus which indirectly leads to the inconsistency or even sudden change of vehicle behaviors in time and space, thereby affects the traffic efficiency and safety. Focusing on the proactive speed limit mode at vehicle side, a utility evaluation and recommendation method is proposed, which carries out the multi-scenario traffic simulation for varied proactive and passive speed limit considering road line types, traffic flow and vehicle type proportion. From the two perspectives of safety and efficiency, the utility evaluation indicators and weights are extracted …

Go to article

Short-Term Prediction Method Of Wind Power Based On Blp-Alo-Svm, Yefeng Jiao, Yan Wang, Zhicheng Ji Dec 2022

Short-Term Prediction Method Of Wind Power Based On Blp-Alo-Svm, Yefeng Jiao, Yan Wang, Zhicheng Ji

Journal of System Simulation

Abstract: To effectively predict the short-term wind power and its fluctuation range, a prediction method based on hybrid algorithm-optimized support vector machine is proposed. Exploratory data analysis is used to preprocess the original wind speed data to improve the data quality. Chaotic map, Levy flight strategy and particle swarm optimization are used to improve the ant lion algorithm. The support vector machine model optimized by hybrid algorithm is used to predict the wind power. The experimental results show that, compared with the new wind power prediction model, the prediction error of the output results of the method is lower, and …

Go to article

Low Voltage Ride-Through Modeling For Wind Turbines Based On Neural Odes, Qiping Lai, Tannan Xiao, Dongsheng Li, Chen Shen Dec 2022

Low Voltage Ride-Through Modeling For Wind Turbines Based On Neural Odes, Qiping Lai, Tannan Xiao, Dongsheng Li, Chen Shen

Journal of System Simulation

Abstract: Considering the difficulty of equivalent modeling of low voltage ride-through(LVRT) characteristics of a wind farm, a neural ordinary differential equation(ODE)-based wind farm LVRT modeling methodis proposed. The input of the model is the voltage and wind speed of each wind turbine at the grid connection point of wind farm, and the output is the current at the grid connection point. The model can better characterize the strong nonlinear switching process and describe LVRT characteristics of wind farms under different wind speed scenarios. A simulation example of a wind farm including three doubly-fed induction generators(DFIGs) is established on …

Go to article

Sis-Based Modeling And Simulation Analysis On Exercise Benefit Perception Transmission, Lei Wang, Jinhai Sun, Tuojian Li Dec 2022

Sis-Based Modeling And Simulation Analysis On Exercise Benefit Perception Transmission, Lei Wang, Jinhai Sun, Tuojian Li

Journal of System Simulation

Abstract: In order to distinguish the relationship between individual health behavior change and collective health behavior emergence, deal with the challenges of mathematical description of typical health information dissemination processes in social networks and social experiments, SIS(susceptible-infected-susceptible)model is introduced to simulate the dissemination process of classical health information exercise effect perception to meet the requirements of social system complexity, individual diversity and intelligence. To carry out numerical experiments on the propagation process of exercise effect perception to identify the phase change process of the collective health behavior emergence, agent-based modeling and simulation are utilized through NetLogo. Experimental results show …

Go to article

Simulation On Flood Disaster In Urban Building Complex System Based On Lbm, Shen Zhang, Zewang Yang, Yifan Wang, Liang Sun, Ming Cheng, Fankai Meng, Ting Li Dec 2022

Simulation On Flood Disaster In Urban Building Complex System Based On Lbm, Shen Zhang, Zewang Yang, Yifan Wang, Liang Sun, Ming Cheng, Fankai Meng, Ting Li

Journal of System Simulation

Abstract: Because of the extreme climate change, the potential flood disaster risk in the southeast coastal areas of China can not be ignored. Based on lattice Boltzmann computational fluid dynamics method, a three-dimensional simulation study of waterlogging process in tsunami impact scenario is carried out for a coastal city building complex system, and the reliability and accuracy of the numerical simulation method for the flood impact test of an ideal building complex are verified. The results show that the buildings along rivers and coastlines have obvious cloaking effect, while the buildings inside the city are less affected by floods. The …

Go to article

Research On Complex Combat Network Dynamic Evolution Based On Information Entropy, Lianyi Zhang, Xisheng Shen, Duzheng Qing, Han Zhang, Min Zhou, Xifu Wang Dec 2022

Research On Complex Combat Network Dynamic Evolution Based On Information Entropy, Lianyi Zhang, Xisheng Shen, Duzheng Qing, Han Zhang, Min Zhou, Xifu Wang

Journal of System Simulation

Abstract: Network-centric warfare, distributed and decentralized command and control gradually replace separately the traditional platform-centric warfare and centralized command and control, and information has become a combat capability. Based on the new information weapon equipment system operation loop, a complex combat network model based on information entropy is constructed, and the combat capability measurement method is proposed. On the basis of the combat capability upgrade being the network driving force, the dynamic evolution rule of the complex combat network is designed and the preferential evolution and stochastic evolution models are constructed. According to a typical system combat example, the influence …

Go to article

Research On Modeling And Simulation Technology Of Microwave Radar High Precision Tracking Loop, Jiaji Lou, Jing Ma, Xiaowei Li, Yue Zhao, Youbin Song Dec 2022

Research On Modeling And Simulation Technology Of Microwave Radar High Precision Tracking Loop, Jiaji Lou, Jing Ma, Xiaowei Li, Yue Zhao, Youbin Song

Journal of System Simulation

Abstract: Aiming at the key problem of high-precision tracking loop design of a measurement radar for the weak signal (low carrier to noise ratio signal) in dynamic environment, the design and optimization methods of carrier tracking loop and code tracking loop are focused on. A signal structure with a single carrier as a pilot is proposed, and the loop structure of the frequency-locked loop and the phase-locked loop working together is studied. The modeling and simulation on the two structures show that for the week signal tracking in a dynamic environment, the loop combination structure of the frequency-serial auxiliary …

Go to article

Research On Parameter Construction Method Of Blue Army Equipment Model Based On A Deep Network, Boyuan Zhang, Guanghong Gong, Ze Wang, Ni Li Dec 2022

Research On Parameter Construction Method Of Blue Army Equipment Model Based On A Deep Network, Boyuan Zhang, Guanghong Gong, Ze Wang, Ni Li

Journal of System Simulation

Abstract: The modeling of blue army equipment is an indispensable part of adversarial simulation environment construction. Aiming at the limited available parameters of "information-poor" and "small sample" characteristics to the blue system, a deep network-based method is proposed to generate the parameters of blue army equipment model. By injecting the information into the simulation model of the blue army equipment, the simulation data is generated and trained in the deep neural network. The obtained network has a certain generalization ability to the unknown parameters prediction of the same type of equipment and can be used directly in prediction or be …

Go to article

Fast Generation Method Of Multi-Sensing Channel Fusion Virtual Experiment, Jingwei Deng, Hanwu He, Yueming Wu, Jianhao Su Dec 2022

Fast Generation Method Of Multi-Sensing Channel Fusion Virtual Experiment, Jingwei Deng, Hanwu He, Yueming Wu, Jianhao Su

Journal of System Simulation

Abstract: Aiming at the low development efficiency and single experience in traditional virtual experiments, a rapid generation method of multi-sensing channel fusion virtual experiment visualization is proposed. The experimental steps and sequence of experimental steps of the virtual experiment are defined. A parameterized description method of experimental elements based on Petri net is proposed to describe the sequence of experimental steps, which breaks through the constraints the established procedure steps of traditional virtual experiments and supports the exploratory virtual experiments. The visual expression method of the routing graph and the conversion method between the routing graph and the Petri …

Go to article

Multi-Robot Path Planning Based On Cbs Algorithm, Qiao Qiao, Yan Wang, Zhicheng Ji Dec 2022

Multi-Robot Path Planning Based On Cbs Algorithm, Qiao Qiao, Yan Wang, Zhicheng Ji

Journal of System Simulation

Abstract: Aiming at the long multi-robot planning path and long one-way search running time of conflict-based search(CBS) in the multi-agent path finding(MAPF), an improved CBS algorithm is proposed, which in a two-way A* focus search is used to optimize the search direction and search method. The suboptimal factorωis introduced into the underlying search function of the CBS algorithm to improve the efficiency of path search. The one-way search in the conflict search algorithm is optimized to a two-way A* search. The experimental results show that the path cost of the improved CBS algorithm is shortened …

Go to article

Reliability Parameter Optimization Complex System Simulation Based On R-Vikor Method, Zhiguang Wang, Baiting Liu, Xiaolei Wang, Tao Liu, Zhaowei Yang Dec 2022

Reliability Parameter Optimization Complex System Simulation Based On R-Vikor Method, Zhiguang Wang, Baiting Liu, Xiaolei Wang, Tao Liu, Zhaowei Yang

Journal of System Simulation

Abstract: The operation of complex simulation system is not isolated, and always affected by multiple external factors and its own performance. In simulation reliability calculation, parameters need to be chosen, and different performance indexes need to be taken into account when comparing with the reference model. The research is transformed into the multi-attribute decision. An system simulation trusted parameter optimization method based on R-VIKOR(resist rank reversal of visekriterijumska optimizacija | kompromisno resenje) is proposed. Multiple sets of aerodynamic parameters of the new model are obtained through model migration theory, and similarity calculation is carried out with the optimal parameters of …

Go to article

Research On Low Computational Predictive Control Strategy Of Three-Level Four-Arm Apf, Guifeng Wang, Jinxing Guo Dec 2022

Research On Low Computational Predictive Control Strategy Of Three-Level Four-Arm Apf, Guifeng Wang, Jinxing Guo

Journal of System Simulation

Abstract: Four-arm active power filter(APF) is an ideal device to the power quality of three-phase four-wire distribution network. Owing to the sufficient number of base vectors, three-level four-arm APF has better current tracking performance, but the prediction calculation amount is too large when model predictive current control is applied. A model prediction voltage control strategy based on the idea of space stratification is proposed. Based on the deadbeat control idea and the discrete mathematical model in αβγ coordinate system, the expected reference voltage is predicted from the reference current, and the multiple current predictions are converted into the single voltage …

Go to article

Machine Learning And Protein Allostery, Sian Xiao, Gennady M. Verkhivker, Peng Tao Dec 2022

Machine Learning And Protein Allostery, Sian Xiao, Gennady M. Verkhivker, Peng Tao

Mathematics, Physics, and Computer Science Faculty Articles and Research

The fundamental biological importance and complexity of allosterically regulated proteins stem from their central role in signal transduction and cellular processes. Recently, machine-learning approaches have been developed and actively deployed to facilitate theoretical and experimental studies of protein dynamics and allosteric mechanisms. In this review, we survey recent developments in applications of machine-learning methods for studies of allosteric mechanisms, prediction of allosteric effects and allostery-related physicochemical properties, and allosteric protein engineering. We also review the applications of machine-learning strategies for characterization of allosteric mechanisms and drug design targeting SARS-CoV-2. Continuous development and task-specific adaptation of machine-learning methods for protein allosteric …

Go to article

Simulation Research On Appearance Detection Of Ampoules Based On Lightweight Network And Model Compression, Zhihao Zhu, Yan Wang, Zhicheng Ji Dec 2022

Simulation Research On Appearance Detection Of Ampoules Based On Lightweight Network And Model Compression, Zhihao Zhu, Yan Wang, Zhicheng Ji

Journal of System Simulation

Abstract: Aiming at the large scale and redundant parameters of target detection network model, which result in the difficult to deploy the ampoule bottle appearance defect detection model to edge devices, an LC-Faster R-CNN defect detection algorithm based on lightweight network and model compression is proposed. MobileNet-V2 is used as the backbone, and the redundant channels in the convolutional network are trimmed by model pruning strategy. The floating-point parameters are quantized into integers through saturation truncation mapping. Knowledge distillation is used to restore the accuracy of the compressed network. Tested on the self-built ampoule appearance defect dataset, the model volume …

Go to article

Research On Iterative Calculation And Optimization Methods Of Aero-Engine On-Board Model, Xinghua Luo, Jia Geng, Ming Li, Bei Liu, Lei Wang, Zhiping Song Dec 2022

Research On Iterative Calculation And Optimization Methods Of Aero-Engine On-Board Model, Xinghua Luo, Jia Geng, Ming Li, Bei Liu, Lei Wang, Zhiping Song

Journal of System Simulation

Abstract: Aeroengine is a complex and time-varying multivariable thermophysical system. The research on the convergence accuracy and rate of the component-level model is of great significance to the model-based engine health management, performance and fault-tolerant control. The existing engine component-level models are generally based on the traditional quasi-Newton method to solve the equilibrium equations simultaneously. Compared with the traditional Newton-Raphson method (N-R method), the convergence speed is optimized, but it is difficult to meet accuracy and real-time requirements of the dynamic model airborne applications within the full envelope. An adaptive variable step factor quasi-Newton method is proposed, which can reduce …

Go to article

Long-Term Resilience Simulation On Low-Carbon Urban Grid Based On Evolutionary Game, Zhengda Cui, Weiqiang Yao, Qin Xu, Chen Fang, Ying Chen Dec 2022

Long-Term Resilience Simulation On Low-Carbon Urban Grid Based On Evolutionary Game, Zhengda Cui, Weiqiang Yao, Qin Xu, Chen Fang, Ying Chen

Journal of System Simulation

Abstract: Because of the more frequent extreme disasters, the resilience of urban grid becomes more important. In the background of carbon neutralization policy, the decarbonization transition of urban grid also affects the development of grid resilience. An evolutionary game is used to simulate the resilience evolution of low-carbon urban grid and the evolution model is constructed. The decision to install photovoltaic and energy storage system for residents and to upgrade the grid for resilience is considered in the model and the stability conditions of equilibriums of the evolutionary game are analyzed. The resilience evolution simulation model considering disaster stochasticity is …

Go to article

Anomaly Detection Method Of Electrical Power Consumption Based On Deep Autoencoder, Ningke Sun, Yan Wang, Zhicheng Ji Dec 2022

Anomaly Detection Method Of Electrical Power Consumption Based On Deep Autoencoder, Ningke Sun, Yan Wang, Zhicheng Ji

Journal of System Simulation

Abstract: Aiming at the nonlinear and non-stationary characteristics of electrical power consumption data, an abnormal electrical power consumption detection model based on deep autoencoder is proposed. Gated recurrent unit (GRU) network of the deep learning is combined with autoencoder structure, and the encoder and decoder parts of traditional autoencoder are realized by gated recurrent unit network, which gives full play to the data feature extraction capability of gated recurrent unit and the data reconstruction function of autoencoder structure. Based on the reconstruction error between original data and reconstructed data, abnormal data points of the electrical power consumption are detected. By …

Go to article

Research On Emotional Contagion And Intervention Strategy Of Indoor Evacuation Based On Risk Perception, Yang Zeng, Jinling Li, Haixiang Guo, Weiming Chen Dec 2022

Research On Emotional Contagion And Intervention Strategy Of Indoor Evacuation Based On Risk Perception, Yang Zeng, Jinling Li, Haixiang Guo, Weiming Chen

Journal of System Simulation

Abstract: Aiming at the panic emotion contagion in the indoor emergency evacuation with multi-exit and multi-obstacle, an emotional contagion model is constructed on personality traits, risk perception differences of age and gender, and consciousness regulation. The simulation is carried out by using AnyLogic, which combines individual emotions with evacuation speed to realize the real-time updating of emotional state and speed. That personnel intervention in the process of evacuation can effectively alleviate the spread of panic emotion, is verified and can provide the theoretical basis for panic contagion in the process of emergency evacuation. The results show that the degree of …

Go to article

Overview Of Research And Application On Autonomous Vehicle Oriented Perception System Simulation, Ruoxuan Wang, Jianping Wu, Hui Xu Dec 2022

Overview Of Research And Application On Autonomous Vehicle Oriented Perception System Simulation, Ruoxuan Wang, Jianping Wu, Hui Xu

Journal of System Simulation

Abstract: Following the rapid progress of science and technology, vehicles with autonomous driving or auxiliary driving function enter into vehicle market. However, in the past decade, traffic accidents still occurred frequently, and the safety of these functions become the focus. Simulation technology provides a good platform to test the perception system of autonomous vehicle. Focus on the sensor simulation modeling of autonomous vehicle perception system, from the perspective of single sensor simulation, multi-sensor simulation and classic simulation platform including millimeter wave radar, lidar and camera, the existing research are reviewed, and the shortcomings and development trends of simulation modeling of …

Go to article

Towards Parking Lot Occupancy Assessment Using Aerial Imagery And Computer Vision, John Jewell Dec 2022

Towards Parking Lot Occupancy Assessment Using Aerial Imagery And Computer Vision, John Jewell

Electronic Thesis and Dissertation Repository

Advances in Computer Vision and Aerial Imaging have enabled countless downstream applications. To this end, aerial imagery could be leveraged to analyze the usage of parking lots. This would enable retail centres to allocate space better and eliminate the parking oversupply problem. With this use case in mind, the proposed research introduces a novel framework for parking lot occupancy assessments. The framework consists of a pipeline of components that map a sequence of image sets spanning a parking lot at different time intervals to a parking lot turnover heatmap that encodes the frequency each parking stall was used. The pipeline …

Go to article

Creating Data From Unstructured Text With Context Rule Assisted Machine Learning (Craml), Stephen Meisenbacher, Peter Norlander Dec 2022

Creating Data From Unstructured Text With Context Rule Assisted Machine Learning (Craml), Stephen Meisenbacher, Peter Norlander

School of Business: Faculty Publications and Other Works

Popular approaches to building data from unstructured text come with limitations, such as scalability, interpretability, replicability, and real-world applicability. These can be overcome with Context Rule Assisted Machine Learning (CRAML), a method and no-code suite of software tools that builds structured, labeled datasets which are accurate and reproducible. CRAML enables domain experts to access uncommon constructs within a document corpus in a low-resource, transparent, and flexible manner. CRAML produces document-level datasets for quantitative research and makes qualitative classification schemes scalable over large volumes of text. We demonstrate that the method is useful for bibliographic analysis, transparent analysis of proprietary data, …

Go to article

A Hybrid Artificial Intelligence Model For Detecting Keratoconus, Zaid Abdi Alkareem Alyasseri, Ali H. Al-Timemy, Ammar Kamal Abasi, Alexandru Lavric, Husam Jasim Mohammed, Hidenori Takahashi, Jose Arthur Milhomens Filho, Mauro Campos, Rossen M. Hazarbassanov, Siamak Yousefi Dec 2022

A Hybrid Artificial Intelligence Model For Detecting Keratoconus, Zaid Abdi Alkareem Alyasseri, Ali H. Al-Timemy, Ammar Kamal Abasi, Alexandru Lavric, Husam Jasim Mohammed, Hidenori Takahashi, Jose Arthur Milhomens Filho, Mauro Campos, Rossen M. Hazarbassanov, Siamak Yousefi

Machine Learning Faculty Publications

Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity …

Go to article

Folk Theories, Recommender Systems, And Human-Centered Explainable Artificial Intelligence (Hcxai), Michael Ridley Dec 2022

Folk Theories, Recommender Systems, And Human-Centered Explainable Artificial Intelligence (Hcxai), Michael Ridley

Electronic Thesis and Dissertation Repository

This study uses folk theories to enhance human-centered “explainable AI” (HCXAI). The complexity and opacity of machine learning has compelled the need for explainability. Consumer services like Amazon, Facebook, TikTok, and Spotify have resulted in machine learning becoming ubiquitous in the everyday lives of the non-expert, lay public. The following research questions inform this study: What are the folk theories of users that explain how a recommender system works? Is there a relationship between the folk theories of users and the principles of HCXAI that would facilitate the development of more transparent and explainable recommender systems? Using the Spotify music …

Go to article

Utilizing Remote Sensing Technology To Relocate Lubra Village And Visualize Flood Damages, Ronan Wallace Dec 2022

Utilizing Remote Sensing Technology To Relocate Lubra Village And Visualize Flood Damages, Ronan Wallace

Mathematics, Statistics, and Computer Science Honors Projects

As weather patterns change worldwide, isolated communities impacted by climate change go unnoticed and we need community and habitat-conscious solutions. In Himalayan Mustang, Nepal, indigenous Lubra village faces threats of increasing flash flooding. After every flood, residual concrete-like sediment hardens across the riverbed, causing the riverbed elevation to rise. As elevation increases, sediment encroaches on Lubra’s agricultural fields and homes, magnifying flood vulnerability. In the last monsoon season alone, the village witnessed floods swallowing several fields and damaging two homes. One solution considers relocating the village to a new location entirely. However, relocation poses a challenging task, as eight centuries …

Go to article

First Prev Next Last