Computer Sciences 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 …

Audio Mixing Using Image Neural Style Transfer Networks, Susan Mckeever, Xuehao Liu, Sarah Jane Delany

Conference papers

Image style transfer networks are used to blend images, producing images that are a mix of source images. The process is based on controlled extraction of style and content aspects of images, using pre-trained Convolutional Neural Networks (CNNs). Our interest lies in adopting these image style transfer networks for the purpose of transforming sounds. Audio signals can be presented as grey-scale images of audio spectrograms. The purpose of our work is to investigate whether audio spectrogram inputs can be used with image neural transfer networks to produce new sounds. Using musical instrument sounds as source sounds, we apply and compare …

Reimagining Medical Education In The Age Of Ai, Steven A. Wartman, C. Donald Combs

Computational Modeling & Simulation Engineering Faculty Publications

Available medical knowledge exceeds the organizing capacity of the human mind, yet medical education remains based on information acquisition and application. Complicating this information overload crisis among learners is the fact that physicians' skill sets now must include collaborating with and managing artificial intelligence (AI) applications that aggregate big data, generate diagnostic and treatment recommendations, and assign confidence ratings to those recommendations. Thus, an overhaul of medical school curricula is due and should focus on knowledge management (rather than information acquisition), effective use of AI, improved communication, and empathy cultivation.

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 …

Using Neural Networks To Classify Discrete Circular Probability Distributions, Madelyn Gaumer

HMC Senior Theses

Given the rise in the application of neural networks to all sorts of interesting problems, it seems natural to apply them to statistical tests. This senior thesis studies whether neural networks built to classify discrete circular probability distributions can outperform a class of well-known statistical tests for uniformity for discrete circular data that includes the Rayleigh Test¹, the Watson Test², and the Ajne Test³. Each neural network used is relatively small with no more than 3 layers: an input layer taking in discrete data sets on a circle, a hidden layer, and an output …

Applied Machine Learning For Classification Of Musculoskeletal Inference Using Neural Networks And Component Analysis, Shaswat Sharma

Electronic Theses and Dissertations

Artificial Intelligence (AI) is acquiring more recognition than ever by researchers and machine learning practitioners. AI has found significance in many applications like biomedical research for cancer diagnosis using image analysis, pharmaceutical research, and, diagnosis and prognosis of diseases based on knowledge about patients' previous conditions. Due to the increased computational power of modern computers implementing AI, there has been an increase in the feasibility of performing more complex research.

Within the field of orthopedic biomechanics, this research considers complex time-series dataset of the "sit-to-stand" motion of 48 Total Hip Arthroplasty (THA) patients that was collected by the Human Dynamics …

Application Of Retrograde Analysis To Fighting Games, Kristen Yu

Electronic Theses and Dissertations

With the advent of the fighting game AI competition, there has been recent interest in two-player fighting games. Monte-Carlo Tree-Search approaches currently dominate the competition, but it is unclear if this is the best approach for all fighting games. In this thesis we study the design of two-player fighting games and the consequences of the game design on the types of AI that should be used for playing the game, as well as formally define the state space that fighting games are based on. Additionally, we also characterize how AI can solve the game given a simultaneous action game model, …

[Accepted Article Manuscript Version (Postprint)] Identification And Parasocial Relationships With Characters From Star Wars: The Force Awakens., Alice Hall

Communication and Media Faculty Works

This study investigated identification and parasocial relationships (PSRs) with media characters by examining viewers’ responses to the movie Star Wars: The Force Awakens through an online survey of 113 audience members who saw the film in a theater within a month of its release. Participants reported stronger PSR and identification with the more familiar characters from the first trilogy than with the new characters introduced in the film, although the association with identification was limited to older participants. Star Wars fanship was associated with identification and PSR for old and new characters. Familiarity with the earlier films was associated with …

Artificial Intelligence: How Knowledge Is Created, Transferred, And Used, Jörg Hellwig Phd, Sarah Huggett, Mark Siebert, Bamini Jayabalasingham Phd

Public Reports

This document summarizes Key Findings from the full report "Artificial Intelligence: how knowledge is created, transferred, and used", available alongside other relevant material on the Elsevier Artificial Intelligence resource centre.The RELX group has extensive data assets, powerful computing capabilities, and a vast technological talent base. These allow Elsevier to provide unique insights on AI through this report. We hope these will be of interest to research evaluators, research funders, policy makers, and researchers, as they seek to navigate this complex, evolving, and fast-growing field.

Radically Simplifying Gated Recurrent Architectures Without Loss Of Performance, Jonathan Boardman, Ying Xie

Published and Grey Literature from PhD Candidates

Long Short-Term Memory (LSTM) units are a family of Recurrent Neural Network (RNN) architectures that have proven incredibly effective at learning from sequence data. They are also extremely complex, making them expensive to train and difficult to understand. A recent trend towards simplification has produced the Gated Recurrent Unit (GRU) and the Minimal Gated Unit (MGU), both of which perform as well as the LSTM (or better) on a variety of tasks. The MGU is one of the simplest gated recurrent architectures at the moment. Our study demonstrates that it is possible to radically simplify the MGU without significant loss …

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 …

Work-In-Progress Reports Submitted To The Library Of Congress As Part Of Digital Libraries, Intelligent Data Analytics, And Augmented Description, Chulwoo Pack, Yi Liu, Leen-Kiat Soh, Elizabeth Lorang

School of Computing: Technical Reports

This document includes work-in-progress reports submitted to the Library of Congress as part of the Aida digital libraries research team's work on Digital Libraries, Intelligent Data Analytics, and Augmented Description: A Demonstration Project. These work-in-progress reports provide a snapshot glimpse, as well as underlying rationale and decision-making, at various points in the development of the project and its machine learning explorations. Reports cover explorations on historic newspapers, minimally-processed manuscript collections, materials digitized from physical originals and those digitized from microform surrogates, and investigate challenges related to image segmentation and document zoning, classification, document image quality analysis, metadata generation, and more.

Android Application For Mnist Handwritten Digits Classification, Mina Gabriel

Project Topics and Ideas

Use Neural Network architecture to classify MNIST handwritten digits dataset, student/s should implement a phone application (Android) to demonstrate their work, application will then be published to the app store for other students and CISC faculty members for evaluation and feedback.

Regulation Of Artificial Intelligence In Selected Jurisdictions, Jenny Gesley, Tariq Ahmad, Edouardo Soares, Ruth Levush, Gustavo Guerra, James Martin, Kelly Buchanan, Laney Zhang, Sayuri Umeda, Astghik Grigoryan, Nicolas Boring, Elin Hofverberg, Clare Feikhert-Ahalt, Graciela Rodriguez-Ferrand, George Sadek, Hanibal Goitom

Copyright, Fair Use, Scholarly Communication, etc.

Comparative Summary

This report examines the emerging regulatory and policy landscape surrounding artificial intelligence (AI) in jurisdictions around the world and in the European Union (EU). In addition, a survey of international organizations describes the approach that United Nations (UN) agencies and regional organizations have taken towards AI. As the regulation of AI is still in its infancy, guidelines, ethics codes, and actions by and statements from governments and their agencies on AI are also addressed. While the country surveys look at various legal issues, including data protection and privacy, transparency, human oversight, surveillance, public administration and services, autonomous vehicles, …

The Use Of Deep Learning Distributed Representations In The Identification Of Abusive Text, Susan Mckeever, Hao Chen, Sarah Jane Delany

Conference papers

The selection of optimal feature representations is a critical step in the use of machine learning in text classification. Traditional features (e.g. bag of words and n-grams) have dominated for decades, but in the past five years, the use of learned distributed representations has become increasingly common. In this paper, we summarise and present a categorisation of the stateof-the-art distributed representation techniques, including word and sentence embedding models. We carry out an empirical analysis of the performance of the various feature representations using the scenario of detecting abusive comments. We compare classification accuracies across a range of off-the-shelf embedding models …

Facial Re-Enactment, Speech Synthesis And The Rise Of The Deepfake, Nicholas Gardiner

Theses : Honours

Emergent technologies in the fields of audio speech synthesis and video facial manipulation have the potential to drastically impact our societal patterns of multimedia consumption. At a time when social media and internet culture is plagued by misinformation, propaganda and “fake news”, their latent misuse represents a possible looming threat to fragile systems of information sharing and social democratic discourse. It has thus become increasingly recognised in both academic and mainstream journalism that the ramifications of these tools must be examined to determine what they are and how their widespread availability can be managed.

This research project seeks to examine …

Predictive Modeling Of Webpage Aesthetics, Ang Chen

Masters Theses

"Aesthetics plays a key role in web design. However, most websites have been developed based on designers' inspirations or preferences. While perceptions of aesthetics are intuitive abilities of humankind, the underlying principles for assessing aesthetics are not well understood. In recent years, machine learning methods have shown promising results in image aesthetic assessment. In this research, we used machine learning methods to study and explore the underlying principles of webpage aesthetics"--Abstract, page iii.