Artificial Intelligence and Robotics Commons^™

Fast False Scene Jamming Algorithm For Sar-Gmti Based On Moving Jamming Station, Mingxing Fang, Daping Bi, Aiguo Shen

Journal of System Simulation

Abstract: Traditional false scene jamming of SAR is invalid for SAR-GMTI system, which does not have the feature of moving targets, so a fast false scene jamming algorithm for SAR-GMTI based on moving jamming station is proposed. Through reasonable simplification of the traditional algorithm, the fast false scene jamming algorithm of matrix form is put forward. The method is proposed to take advantage of both fast false scene jamming algorithm and moving jamming station, so it can produce false scene jamming with real moving feature. It not only solves the real-time problem of traditional false scene jmming, but …

Research On Dynamic Framed Binary Tree Anti-Collision Algorithm For Rfid System, Xiaohong Zhang, Weihui Zhou

Journal of System Simulation

Abstract: Based on dynamic frame-slotted ALOHA algorithm and binary search tree algorithm, a dynamic framed binary tree (DFBT) anti-collision algorithm is presented to solve the problem of multi-tag collision in radio frequency identification (RFID). Vogt algorithm is adopted to estimate tags number, then the dynamic frame-slotted ALOHA (DFSA) algorithm is used to identify tags, and the unidentified tags are extracted and the highest collision bit is judged by readers. The highest collision tags are grouped by the collision bit within the binary search tree (BST) algorithm. Simulation results show that the DFBT algorithm can improve the identification efficiency and stability …

Smooth Transition Method Over Entire Speed Range Of Switched Reluctance Motor, Diansheng Sun

Journal of System Simulation

Abstract: In order to smoothly switch different control modes of switched reluctance motor under the condition of low speed and high speed, a novel scheme using function fitting method to control turn-on angle, turn-off angle and phase current chopping is proposed. The active disturbance rejection speed control system is structured for switched reluctance motor in order to restrain all kinds of disturbance and improve the dynamic performance. Simulation results indicate that the principle of the method is correct and the turn-on angle, turn-off angle and phase current chopping is coordinated to realize the smooth switching of different control modes with …

Formation Mechanism And Simulation Analysis Of Railgun Armature Electromagnetic Transition, Zhiheng Wang, Wan Mei, Xiaojiang Li

Journal of System Simulation

Abstract: Armature transition of railgun causes rails erosion and change of launching parameters, which is one of the key problems restricting the performance of railgun. The formation mechanism of armature transition at the down-slope of driving current is analyzed. The armature transition estimation model and electromagnetic parameters calculation model are given. The formation process of armature transition at the down-slope of driving current is simulated by AYNSYS Workbench. The current and magnetic field distribution are simulated, so as the armature deformation caused by the armature electromagnetic force. The effect of current dropping rate on armature transition is analyzed. The …

Modified Fractional Order Sliding Model Control For Dc Speed Regulating System, Zhicheng Zhao, Zhitao Zhao, Jinggang Zhang, Xianjiao Zhao

Journal of System Simulation

Abstract: An improved fractional order sliding model control (FOSMC) is proposed for DC speed regulating system to eliminate static error easily caused by disturbance in sliding model control. Second order mathematical model is established through taking the derivative of first-order mathematical model of DC speed regulating system. The theory of fractional calculus is introduced to the switching function of sliding mode, and fractional sliding model is designed combining exponential reaching law and second order mathematical model. The control signal of voltage can be obtained through taking output of the controller and integrator in series. Stability analysis of the system is …

A Mppt Control Method Of Wind Turbines With Nonsingular And Fast Terminal Sliding Mode, Dazhong Li, Wu Feng

Journal of System Simulation

Abstract: In order to improve the energy capture efficiency of doubly-fed induction generator (DFIG), a control method is designed based on direct speed control (DSC) to achieve maximum power point tracking (MPPT). An effective wind speed estimator based on high-degree cubature Kalman filter (HCKF) and Newton-Raphson method (NR) is proposed for solving the difficulty in obtaining effective wind speed using traditional control strategy. A speed controller based on nonsingular fast terminal sliding mode surface is designed to obtain a faster speed response for the speed loop. The numerical simulation research of the 2.4MW wind turbine under rapidly variable wind …

Relevance Analysis Of Deicing Parameters And Deicing Efficiency Of Aircraft Ground, Bin Chen, Liwen Wang

Journal of System Simulation

Abstract: Aircraft ground freezing could lead to potential danger and delay for flight. To alleviate these problems, the main method is to use the deicing fluids to clean ice or snow on the aircraft body, which lacks of reference of the deicing fluids parameters and efficiency. To study the effect of the deicing fluids parameters on the aircraft deicing efficiency, the deicing mechanism is analyzed.The black box mathematical model of the deicing process is generalized abstractly. The deicing process is divided into two subprocesses to establish the deicing model.The relevance between the deicing fluids parameters and deicing efficiency is studied …

A Novel Algorithm For Improving Fairness Between Uplink And Downlink Flows In Heterogeneous Network, Peiyu Li, Zheqing Li, Wang Hui, Xia Qian

Journal of System Simulation

Abstract: In order to improve the fairness between uplink and downlink flows in AP optimization, a novel algorithm called FOUD(fairness over uplink and downlink) is proposed.Considering the influence of the attempt limit and the bit error rate of wireless, the FOUD algorithm modeling of AP and wireless stations is studied separately by using two-dimensional Markov chain, which derives the probability of data sending under the condition of different bit error rate and different number of uplink and downlink flows. Simulation results show that FOUD can improve the fairness of the uplink and downlink bandwidth as well as the …

Frequency Domain Analysis Of Common Configuration Semi-Submersible Drilling Platform Based On System Simulation, Chen Bo, Zhiyong Yu, Lü Yong, Xiaojian Li

Journal of System Simulation

Abstract: To analysis of 4 semi-submersible drilling platform hydrodynamic performance providing a comprehensive guidance for system selection. The 1:1 3D wet surface model is established by ANSYS and numerical simulation is carried out based on the dynamic analysis software AQWA. Simulation results show that longitudinal waves impact the surge, heaving and pitching motion a lot, beam seas have large effects on the sway, heave, roll motion vertical heave response increases significantly, as will as surge, sway, heave damping coefficient of vector direction and the added mass coefficient of algebraic. We can not only increase the number of columns to …

A Method Of Finding The Shortest Path Of Dynamic Networks, Lunwen Wang, Zhang Ling

Journal of System Simulation

Abstract: We analyze the research status of finding the shortest path of dynamic networks, analyze the complexity of getting the shortest path, study the relationship between the structure of the dynamic networks and finding the shortest path of the dynamic networks. It is proved that dynamic networks defined by velocity automatically meet weak FIFO’s condition. The networks whose passing function of any side is not decreasing function equals dynamic networks which use velocity. The sufficient condition of directly using Dijkstra algorithm to get the shortest path is that the networks must meet weak FIFO’s condition. How to build a …

Fuzzy Sliding Backstepping Mode Control For Flight Simulator Servo Based On Friction And Disturbance Compensation, Huibo Liu, Shanglei Liu

Journal of System Simulation

Abstract: Considering friction, modeling errors and other uncertainties of flight simulator servo system, a compensation strategy which combines model-based friction compensation with nonlinear disturbance observer compensation was proposed. First, the friction is modeled , whose parameters are identified by using genetic algorithm, and using the identified model to compensate. Second, using a nonlinear disturbance observer to estimate the modeling errors, friction less-compensation or over-compensation and other uncertainties, and using this observed value to compensate. The system adopted sliding backstepping controller to ensure the stabilization of the system. Finally, the fuzzy algorithm is adopted to adjust the switching gain of sliding …

Preliminary Study Of Modeling And Simulation Technology Oriented To Neo-Type Artificial Intelligent Systems, Libo Hu, Xudong Chai, Zhang Lin, Li Tan, Duzheng Qing, Tingyu Lin, Liu Yang

Journal of System Simulation

Abstract: A brief interpretation of the rapidly developing “New Internet+ Big Data+ Artificial Intelligence+” era is given in the paperand the essence and the architectureof neo-type artificial intelligence systems are explained. The meaning of neo-type artificial intelligence system oriented modelling and simulation technology is proposed and the new challenges they are facing are discussed. The research contents and preliminaryresults on neo-type artificial intelligence system oriented modelling and simulation technology are given, which includeneo-type artificial intelligence system oriented modelling/secondary modelling, intelligent simulation computer, smart cloud simulation and intelligent simulation hardware/software supporting system technology, and intelligent simulation system application engineering technology. Several …

Emerging Roles Of Virtual Patients In The Age Of Ai, C. Donald Combs, P. Ford Combs

Computational Modeling & Simulation Engineering Faculty Publications

Today's web-enabled and virtual approach to medical education is different from the 20th century's Flexner-dominated approach. Now, lectures get less emphasis and more emphasis is placed on learning via early clinical exposure, standardized patients, and other simulations. This article reviews literature on virtual patients (VPs) and their underlying virtual reality technology, examines VPs' potential through the example of psychiatric intake teaching, and identifies promises and perils posed by VP use in medical education.

Abso2luteu-Net: Tissue Oxygenation Calculation Using Photoacoustic Imaging And Convolutional Neural Networks, Kevin Hoffer-Hawlik, Geoffrey P. Luke

ENGS 88 Honors Thesis (AB Students)

Photoacoustic (PA) imaging uses incident light to generate ultrasound signals within tissues. Using PA imaging to accurately measure hemoglobin concentration and calculate oxygenation (sO₂) requires prior tissue knowledge and costly computational methods. However, this thesis shows that machine learning algorithms can accurately and quickly estimate sO₂. absO₂luteU-Net, a convolutional neural network, was trained on Monte Carlo simulated multispectral PA data and predicted sO₂ with higher accuracy compared to simple linear unmixing, suggesting machine learning can solve the fluence estimation problem. This project was funded by the Kaminsky Family Fund and the Neukom Institute.

An Evaluation Of Learning Employing Natural Language Processing And Cognitive Load Assessment, Mrunal Tipari

Dissertations

One of the key goals of Pedagogy is to assess learning. Various paradigms exist and one of this is Cognitivism. It essentially sees a human learner as an information processor and the mind as a black box with limited capacity that should be understood and studied. With respect to this, an approach is to employ the construct of cognitive load to assess a learner's experience and in turn design instructions better aligned to the human mind. However, cognitive load assessment is not an easy activity, especially in a traditional classroom setting. This research proposes a novel method for evaluating learning …

Deep Learning: Edge-Cloud Data Analytics For Iot, Katarina Grolinger, Ananda M. Ghosh

Electrical and Computer Engineering Publications

Sensors, wearables, mobile and other Internet of Thing (IoT) devices are becoming increasingly integrated in all aspects of our lives. They are capable of collecting massive quantities of data that are typically transmitted to the cloud for processing. However, this results in increased network traffic and latencies. Edge computing has a potential to remedy these challenges by moving computation physically closer to the network edge where data are generated. However, edge computing does not have sufficient resources for complex data analytics tasks. Consequently, this paper investigates merging cloud and edge computing for IoT data analytics and presents a deep learning-based …

Image-Based Roadway Assessment Using Convolutional Neural Networks, Weilian Song

Theses and Dissertations--Computer Science

Road crashes are one of the main causes of death in the United States. To reduce the number of accidents, roadway assessment programs take a proactive approach, collecting data and identifying high-risk roads before crashes occur. However, the cost of data acquisition and manual annotation has restricted the effect of these programs. In this thesis, we propose methods to automate the task of roadway safety assessment using deep learning. Specifically, we trained convolutional neural networks on publicly available roadway images to predict safety-related metrics: the star rating score and free-flow speed. Inference speeds for our methods are mere milliseconds, enabling …

Healthcare Robotics: Key Factors That Impact Robot Adoption In Healthcare, Sujatha Alla, Pilar Pazos

Engineering Management & Systems Engineering Faculty Publications

In the current dynamic business environment, healthcare organizations are focused on improving patient satisfaction, performance, and efficiency. The healthcare industry is considered a complex system that is highly reliant of new technologies to support clinical as well as business processes. Robotics is one of such technologies that is considered to have the potential to increase efficiency in a wide range of clinical services. Although the use of robotics in healthcare is at the early stages of adoption, some studies have shown the capacity of this technology to improve precision, accessibility through less invasive procedures, and reduction of human error during …

Emotion Forecasting In Dyadic Conversation : Characterizing And Predicting Future Emotion With Audio-Visual Information Using Deep Learning, Sadat Shahriar

Legacy Theses & Dissertations (2009 - 2024)

Emotion forecasting is the task of predicting the future emotion of a speaker, i.e., the emotion label of the future speaking turn–based on the speaker’s past and current audio-visual cues. Emotion forecasting systems require new problem formulations that differ from traditional emotion recognition systems. In this thesis, we first explore two types of forecasting windows(i.e., analysis windows for which the speaker’s emotion is being forecasted): utterance forecasting and time forecasting. Utterance forecasting is based on speaking turns and forecasts what the speaker’s emotion will be after one, two, or three speaking turns. Time forecasting forecasts what the speaker’s emotion will …

Volumetric Error Compensation For Industrial Robots And Machine Tools, Le Ma

Doctoral Dissertations

“A more efficient and increasingly popular volumetric error compensation method for machine tools is to compute compensation tables in axis space with tool tip volumetric measurements. However, machine tools have high-order geometric errors and some workspace is not reachable by measurement devices, the compensation method suffers a curve-fitting challenge, overfitting measurements in measured space and losing accuracy around and out of the measured space. Paper I presents a novel method that aims to uniformly interpolate and extrapolate the compensation tables throughout the entire workspace. By using a uniform constraint to bound the tool tip error slopes, an optimal model with …

Controlled Switching In Kalman Filtering And Iterative Learning Controls, He Li

Masters Theses

“Switching is not an uncommon phenomenon in practical systems and processes, for examples, power switches opening and closing, transmissions lifting from low gear to high gear, and air planes crossing different layers in air. Switching can be a disaster to a system since frequent switching between two asymptotically stable subsystems may result in unstable dynamics. On the contrary, switching can be a benefit to a system since controlled switching is sometimes imposed by the designers to achieve desired performance. This encourages the study of system dynamics and performance when undesired switching occurs or controlled switching is imposed. In this research, …

Artificial Intelligence In The Aviation Manufacturing Process For Complex Assemblies And Components, Elena Vishnevskaya, Ian Mcandrew, Michael Johnson

Publications

Aviation manufacturing is at the leading edge of technology with materials, designs and processes where automation is not only integral; but complex systems require more advanced systems to produce and verify processes. Critical Infrastructure theory is now used to protect systems and equipment from external software infections and cybersecurity techniques add an extra layer of protection. In this research, it is argued that Artificial Intelligence can reduce these risks and allow complex processes to be less exposed to the threat of external problems, internal errors or mistakes in operation.

Relation Prediction Over Biomedical Knowledge Bases For Drug Repositioning, Mehmet Bakal

Theses and Dissertations--Computer Science

Identifying new potential treatment options for medical conditions that cause human disease burden is a central task of biomedical research. Since all candidate drugs cannot be tested with animal and clinical trials, in vitro approaches are first attempted to identify promising candidates. Likewise, identifying other essential relations (e.g., causation, prevention) between biomedical entities is also critical to understand biomedical processes. Hence, it is crucial to develop automated relation prediction systems that can yield plausible biomedical relations to expedite the discovery process. In this dissertation, we demonstrate three approaches to predict treatment relations between biomedical entities for the drug repositioning task …

Speech Interfaces And Pilot Performance: A Meta-Analysis, Kenneth A. Ward

International Journal of Aviation, Aeronautics, and Aerospace

As the aviation industry modernizes, new technology and interfaces must support growing aircraft complexity without increasing pilot workload. Natural language processing presents just such a simple and intuitive interface, yet the performance implications for use by pilots remain unknown. A meta-analysis was conducted to understand performance effects of using speech and voice interfaces in a series of pilot task analogs. The inclusion criteria selected studies that involved participants performing a demanding primary task, such as driving, while interacting with a vehicle system to enter numbers, dial radios, or enter a navigation destination. Compared to manual system interfaces, voice interfaces reduced …

Computational Modeling Of Trust Factors Using Reinforcement Learning, C. M. Kuzio, A. Dinh, C. Stone, L. Vidyaratne, K. M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

As machine-learning algorithms continue to expand their scope and approach more ambiguous goals, they may be required to make decisions based on data that is often incomplete, imprecise, and uncertain. The capabilities of these models must, in turn, evolve to meet the increasingly complex challenges associated with the deployment and integration of intelligent systems into modern society. Historical variability in the performance of traditional machine-learning models in dynamic environments leads to ambiguity of trust in decisions made by such algorithms. Consequently, the objective of this work is to develop a novel computational model that effectively quantifies the reliability of autonomous …

End-To-End Learning Via A Convolutional Neural Network For Cancer Cell Line Classification, Darlington A. Akogo, Xavier-Lewis Palmer

Electrical & Computer Engineering Faculty Publications

Purpose: Computer vision for automated analysis of cells and tissues usually include extracting features from images before analyzing such features via various machine learning and machine vision algorithms. The purpose of this work is to explore and demonstrate the ability of a Convolutional Neural Network (CNN) to classify cells pictured via brightfield microscopy without the need of any feature extraction, using a minimum of images, improving work-flows that involve cancer cell identification.

Design/methodology/approach: The methodology involved a quantitative measure of the performance of a Convolutional Neural Network in distinguishing between two cancer lines. In their approach, they trained, validated and …

Effective Plant Discrimination Based On The Combination Of Local Binary Pattern Operators And Multiclass Support Vector Machine Methods, Vi N T Le, Beniamin Apopei, Kamal Alameh

Research outputs 2014 to 2021

Accurate crop and weed discrimination plays a critical role in addressing the challenges of weed management in agriculture. The use of herbicides is currently the most common approach to weed control. However, herbicide resistant plants have long been recognised as a major concern due to the excessive use of herbicides. Effective weed detection techniques can reduce the cost of weed management and improve crop quality and yield. A computationally efficient and robust plant classification algorithm is developed and applied to the classification of three crops: Brassica napus (canola), Zea mays (maize/corn), and radish. The developed algorithm is based on the …

Optimizing The Performance Of Complex Engineering Systems Aided By Artificial Neural Networks, Khalil Qatu

Electronic Theses and Dissertations

In the first problem Polyetherimide graphene nanoplatelets papers (PEIGNP) were tested with different graphene loadings varying from 0-97 weight percent (WT%). The resulting stress-strain curves were utilized to develop two ANN models. Stress-controlled and strain-controlled models. Both models shoan excellent correlation to the experimental. Several Mechanical properties were calculated from the predicted stress-strain curves namely; toughness maximum strength maximum strain and maximum tangent modulus. Both models captured the same overall behavior of the PEIGNP composite. However the strain-controlled model was found to predict lower stress than the stress-controlled model. Finally a Graphical User Interface (GUI) was developed to aid in …

Dedicated Hardware For Machine/Deep Learning: Domain Specific Architectures, Angel Izael Solis

Open Access Theses & Dissertations

Artificial intelligence has come a very long way from being a mere spectacle on the silver screen in the 1920s [Hml18]. As artificial intelligence continues to evolve, and we begin to develop more sophisticated Artificial Neural Networks, the need for specialized and more efficient machines (less computational strain while maintaining the same performance results) becomes increasingly evident. Though these “new” techniques, such as Multilayer Perceptron’s, Convolutional Neural Networks and Recurrent Neural Networks, may seem as if they are on the cutting edge of technology, many of these ideas are over 60 years old! However, many of these earlier models, at …

Sky Surveys Scheduling Using Reinforcement Learning, Andres Felipe Alba Hernandez

Graduate Research Theses & Dissertations

Modern cosmic sky surveys (e.g., CMB S4, DES, LSST) collect a complex diversity of astronomical objects. Each of class of objects presents different requirements for observation time and sensitivity. For determining the best sequence of exposures for mapping the sky systematically, conventional scheduling methods do not optimize the use of survey time and resources. Dynamic sky survey scheduling is an NP-hard problem that has been therefore treated primarily with heuristic methods. We present an alternative scheduling method based on reinforcement learning (RL) that aims to optimize the use of telescope resources for scheduling sky surveys.

We present an exploration of …