Numerical Analysis and Scientific Computing Commons^™

Real-Time Rfi Mitigation In Radio Astronomy, Emily Ramey, Nick Joslyn, Richard Prestage, Michael Lam, Luke Hawkins, Tim Blattner, Mark Whitehead

Senior Honors Papers / Undergraduate Theses

As the use of wireless technology has increased around the world, Radio Frequency Interference (RFI) has become more and more of a problem for radio astronomers. Preventative measures exist to limit the presence of RFI, and programs exist to remove it from saved data, but the use of algorithms to detect and remove RFI as an observation is occurring is much less common. Such a method would be incredibly useful for observations in which the data must undergo several rounds of processing before being saved, as in pulsar timing studies. Strategies for real-time mitigation have been discussed and tested with …

Arecibo Message, Joshua P. Tan

Open Educational Resources

This two week assignment asks students to interpret and analyze the 1974 Arecibo Message sent by Drake and Sagan. Week 1 introduces the concepts behind the construction of the message and engages with a critical analysis of the architecture and the contents of the message. Week 2 asks students to develop software in a Jupyter Notebook (available for free from the Anaconda Python Distribution) to interpret messages that were similar to those produced by Drake and Sagan.

The Fluid Representations Of Networks Estimating Liquid Viscosity, Jan Jaap R. Van Assen, Shin'ya Nishida, Roland W. Fleming

MODVIS Workshop

No abstract provided.

Simplicity Diffexpress: A Bespoke Cloud-Based Interface For Rna-Seq Differential Expression Modeling And Analysis, Cintia C. Palu, Marcelo Ribeiro-Alves, Yanxin Wu, Brendan Lawlor, Pavel V. Baranov, Brian Kelly, Paul Walsh

Department of Computer Science Publications

One of the key challenges for transcriptomics-based research is not only the processing of large data but also modeling the complexity of features that are sources of variation across samples, which is required for an accurate statistical analysis. Therefore, our goal is to foster access for wet lab researchers to bioinformatics tools, in order to enhance their ability to explore biological aspects and validate hypotheses with robust analysis. In this context, user-friendly interfaces can enable researchers to apply computational biology methods without requiring bioinformatics expertise. Such bespoke platforms can improve the quality of the findings by allowing the researcher to …

Fluid Transport In Porous Media For Engineering Applications, Eric M. Benner

Chemical and Biological Engineering ETDs

This doctoral dissertation presents three topics in modeling fluid transport through porous media used in engineering applications. The results provide insights into the design of fuel cell components, catalyst and drug delivery particles, and aluminum- based materials. Analytical and computational methods are utilized for the modeling of the systems of interest. Theoretical analysis of capillary-driven transport in porous media show that both geometric and evaporation effects significantly change the time dependent behavior of liquid imbibition and give a steady state flux into the medium. The evaporation–capillary number is significant in determining the time-dependent behavior of capillary flows in porous media. …

Depressiongnn: Depression Prediction Using Graph Neural Network On Smartphone And Wearable Sensors, Param Bidja

Honors Scholar Theses

Depression prediction is a complicated classification problem because depression diagnosis involves many different social, physical, and mental signals. Traditional classification algorithms can only reach an accuracy of no more than 70% given the complexities of depression. However, a novel approach using Graph Neural Networks (GNN) can be used to reach over 80% accuracy, if a graph can represent the depression data set to capture differentiating features. Building such a graph requires 1) the definition of node features, which must be highly correlated with depression, and 2) the definition for edge metrics, which must also be highly correlated with depression. In …

The Effects Of Finite Precision On The Simulation Of The Double Pendulum, Rebecca Wild

Senior Honors Projects, 2010-2019

We use mathematics to study physical problems because abstracting the information allows us to better analyze what could happen given any range and combination of parameters. The problem is that for complicated systems mathematical analysis becomes extremely cumbersome. The only effective and reasonable way to study the behavior of such systems is to simulate the event on a computer. However, the fact that the set of floating-point numbers is finite and the fact that they are unevenly distributed over the real number line raises a number of concerns when trying to simulate systems with chaotic behavior. In this research we …

Modeling A Chaotic Billiard: The Bunimovich Stadium, Randal Shoemaker

Senior Honors Projects, 2010-2019

The Bunimovich stadium is a chaotic dynamical system in which a single particle, known as a billiard, moves indefinitely within a barrier without loss of momentum. Mathematicians and physicists have been interested in its properties since it was discovered to be chaotic in the 1970’s [5] [3] [4]. The Bunimovich stadium is actively researched [9]. This thesis and its accompanying software, the Bunimovich Stadia Evolution Viewer (BSEV), present a novel visual representation of the the chaotic dynamical system. The goal for the software is to provide insights into the stadium’s properties to aid researchers. This tool allows one to visualize …

Visualization And Machine Learning Techniques For Nasa’S Em-1 Big Data Problem, Antonio P. Garza Iii, Jose Quinonez, Misael Santana, Nibhrat Lohia

SMU Data Science Review

In this paper, we help NASA solve three Exploration Mission-1 (EM-1) challenges: data storage, computation time, and visualization of complex data. NASA is studying one year of trajectory data to determine available launch opportunities (about 90TBs of data). We improve data storage by introducing a cloud-based solution that provides elasticity and server upgrades. This migration will save $120k in infrastructure costs every four years, and potentially avoid schedule slips. Additionally, it increases computational efficiency by 125%. We further enhance computation via machine learning techniques that use the classic orbital elements to predict valid trajectories. Our machine learning model decreases trajectory …

Automate Nuclei Detection Using Neural Networks, Jonathan Flores, Thejas Prasad, Jordan Kassof, Robert Slater

SMU Data Science Review

Nuclei identification is a pivotal first step in many areas of biomedical research. Pathologists often observe images containing microscopic nuclei as part of their day to day jobs. During research, pathologists must identify nuclei characteristics from microscopic images such as: volume of nuclei, size, density and individual position within image. The pathology field can benefit from image detection enhancements done through the use of computer image segmentation techniques. This research presents methods that can be used to identify all the cell nuclei contained in images. Multiple techniques were experimented with such as edge detection and Convolutional Neural Networks with U-Net …

Powers And Behaviors Of Directed Self-Assembly, Trent Allen Rogers

Graduate Theses and Dissertations

In nature there are a variety of self-assembling systems occurring at varying scales which give rise to incredibly complex behaviors. Theoretical models of self-assembly allow us to gain insight into the fundamental nature of self-assembly independent of the specific physical implementation. In Winfree's abstract tile assembly model (aTAM), the atomic components are unit square "tiles" which have "glues" on their four sides. Beginning from a seed assembly, these tiles attach one at a time during the assembly process in an asynchronous and nondeterministic manner.

We can gain valuable insights into the nature of self-assembly by comparing different models of self-assembly …

Multimodal Review Generation For Recommender Systems, Quoc Tuan Truong, Hady W. Lauw

Research Collection School Of Computing and Information Systems

Key to recommender systems is learning user preferences, which are expressed through various modalities. In online reviews, for instance, this manifests in numerical rating, textual content, as well as visual images. In this work, we hypothesize that modelling these modalities jointly would result in a more holistic representation of a review towards more accurate recommendations. Therefore, we propose Multimodal Review Generation (MRG), a neural approach that simultaneously models a rating prediction component and a review text generation component. We hypothesize that the shared user and item representations would augment the rating prediction with richer information from review text, while sensitizing …

On-The-Fly Android Static Analysis With Applications In Vulnerability Discovery, Daoyuan Wu

Dissertations and Theses Collection (Open Access)

Static analysis is a common program analysis technique extensively used in the software security field. Widely-used static analysis tools for Android, e.g., Amandroid and FlowDroid, perform the whole-app analysis which is comprehensive yet at the cost of huge overheads. In this dissertation, we make a first attempt to explore a novel on-demand analysis that creatively leverages bytecode search to guide inter-procedural analysis on the fly or just in time, and develop such on-the-fly analysis into a tool, called BackDroid, for Android apps. We further explore how the core technique of on-the-fly static analysis in BackDroid can enable different vulnerability studies …

Neural Multimodal Belief Tracker With Adaptive Attention For Dialogue Systems, Zheng Zhang, Lizi Liao, Minlie Huang, Xiaoyan Zhu, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Multimodal dialogue systems are attracting increasing attention with a more natural and informative way for human-computer interaction. As one of its core components, the belief tracker estimates the user's goal at each step of the dialogue and provides a direct way to validate the ability of dialogue understanding. However, existing studies on belief trackers are largely limited to textual modality, which cannot be easily extended to capture the rich semantics in multimodal systems such as those with product images. For example, in fashion domain, the visual appearance of clothes play a crucial role in understanding the user's intention. In this …

Faster: Fusion Analytics For Public Transport Event Response Industrial Applications Track, Sebastien Blandin, Laura Wynter, Hasan Poonawala, Sean Laguna, Basile Dura

Research Collection School Of Computing and Information Systems

The Autonomous Agents and Multiagent Systems (AAMAS) conference series gathers researchers from around the world to share the latest advances in the field. It is the premier forum for research in the theory and practice of autonomous agents and multiagent systems. AAMAS 2002, the first of the series, was held in Bologna, followed by Melbourne (2003), New York (2004), Utrecht (2005), Hakodate (2006), Honolulu (2007), Estoril (2008), Budapest (2009), Toronto (2010), Taipei (2011), Valencia (2012), Saint Paul (2013), Paris (2014), Istanbul (2015), Singapore (2016), São Paulo (2017) and Stockholm (2018). This volume is the proceedings of AAMAS 2019, the 18th …

Pptds: A Privacy-Preserving Truth Discovery Scheme In Crowd Sensing Systems, Chuan Zhang, Liehuang Zhu, Chang Xu, Kashif Sharif, Ximeng Liu

Research Collection School Of Computing and Information Systems

Benefiting from the fast development of human-carried mobile devices, crowd sensing has become an emerging paradigm to sense and collect data. However, reliability of sensory data provided by participating users is still a major concern. To address this reliability challenge, truth discovery is an effective technology to improve data accuracy, and has garnered significant attention. Nevertheless, many of state of art works in truth discovery, either failed to address the protection of participants' privacy or incurred tremendous overhead on the user side. In this paper, we first propose a privacy-preserving truth discovery scheme, named PPTDS-I, which is implemented on two …

Community Detection Via Neighborhood Overlap And Spanning Tree Computations, Ketki Kulkarni, Aris Pagourtzis, Katerina Potika, Petros Potikas, Dora Souliou

Faculty Publications, Computer Science

Most social networks of today are populated with several millions of active users, while the most popular of them accommodate way more than one billion. Analyzing such huge complex networks has become particularly demanding in computational terms. A task of paramount importance for understanding the structure of social networks as well as of many other real-world systems is to identify communities, that is, sets of nodes that are more densely connected to each other than to other nodes of the network. In this paper we propose two algorithms for community detection in networks, by employing the neighborhood overlap metric …

Orca Travel Grant Recipient An Interview With Emily Hoard, Emily Hoard

Steeplechase: An ORCA Student Journal

No abstract provided.

New Clock-Driven Algorithm Based On Separation Of Synaptic Conductance Computation, Zhijie Wang, Peng Xia, Han Fang, Xiaochun Gu

Journal of System Simulation

Abstract: In order to reduce the computing time when simulating the biologic neural network, an efficient clock-driven algorithm based on the separation of synaptic conductance computation is presented. It is found that the calculation of the synaptic state variables can be separated into two independent parts: one called conductance coefficient related with the pre-synaptic neuron, and the other called synaptic current. By introducing the data structure of the virtual synapse cluster to storing sequences of synaptic conductance coefficient, the former part can be calculated independently according to the spiking states of pre-synaptic neuron at each time step. When calculating the …

Grasping Simulation Of Linkage Underactuated Mechanical Finger, Xiali Li, Tianyi Lan, Licheng Wu

Journal of System Simulation

Abstract: For verifying the design rationality and the property of a linkage underactuated finger, Solidworks is utilized to simulate the grasp operation of the finger with some different objects at the different positions. The simulations can be used to analyze the grasping range, the underactuated characteristic, the uniformity of grasp motion and the mechanical property. The finger mechanism contains springs that brings adaptive grasp capability of different objects. The results show that the finger can make suitable capability for grasping the objects whose size can vary from 0.106 to 0.851 times of the finger length. And the finger can give …

Soil Data Construction Method For Cross-Country Trafficability Analysis, Kunwei Li, You Xiong, Zhang Xin, Fen Tang

Journal of System Simulation

Abstract: Soil is one of the most important factors influencing the off-road maneuver of the army. The combination of soil and weather factors makes cross-country trafficability analysis extremely complicated. The soil data from unified soil classification system (USCS) are the basis for the analysis of soil trafficability. In this paper, the random forest method is used to predict the type of soil by using various attribute information. The method extracts sample data from existing USCS soil data to construct multiple random forest models, then analyses the accuracy of random forests and the importance of characteristic variables, and finally uses the …

Image Feature Extraction And Online Grading Method For Weight And Shape Of Strawberry, Zhang Qing, Xiangjun Zou, Guichao Lin, Yanhui Sun

Journal of System Simulation

Abstract: To deal with the classification problems of strawberry in production, a machine vision based strawberry weight and shape grading method was proposed. The strawberry image was segmented by thresholding to extract the fruit. The area and perimeter parameters of the fruit were then calculated and used to build the strawberry weight grading model through regression analysis. Elliptic Fourier descriptor was used to extract the shape features of the fruit, and these shape features were applied to train a support vector machine (SVM) which represented the strawberry shape grading model. 200 samples of strawberries were selected to test both …

Dp-Q(Λ): Real-Time Path Planning For Multi-Agent In Large-Scale Web3d Scene, Fengting Yan, Jinyuan Jia

Journal of System Simulation

Abstract: The path planning of multi-agent in an unknown large-scale scene needs an efficient and stable algorithm, and needs to solve multi-agent collision avoidance problem, and then completes a real-time path planning in Web3D. To solve above problems, the DP-Q(λ) algorithm is proposed; and the direction constraints, high reward or punishment weight training methods are used to adjust the values of reward or punishment by using a probability p (0-1 random number). The value from reward or punishment determines its next step path planning strategy. If the next position is free, the agent could walk to it. The above strategy …

Modeling And Simulation Of False Report Filtering Scheme Based On Position In Wireless Sensor Networks, Zhixiong Liu, Limiao Li

Journal of System Simulation

Abstract: In wireless sensor networks, the adversary can inject false reports from compromised nodes. Previous security designs cannot detect faked reports that are forged coordinately by a group of compromised nodes. Furthermore, in sparse areas, some events failed to be reported to sink. This paper proposes a position based filtering scheme (PFS). It derives the optimal coverage degree ω, and the nodes are deployed accordingly. After deployment, each node distributes its position to some other nodes. When a report is generated for an observed event, it must carry t distinct MACs (Message Authentication Codes) along with positions of all detecting …

Multi-Chromosome Genetic Algorithm For Multiple Traveling Salesman Problem, Duofu Ye, Liu Gang, He Bing

Journal of System Simulation

Abstract: A multi-traveling salesman model with time window is established, and two objective functions for the number of traveling salesmen and the sum of travel time are designed. A multi - chromosome coding method is designed to develop complex mutation operator tree, which overcomes the problem of large searching space of traditional genetic algorithms. The performances of algorithms are compared by simulation, and the simulation results show that the genetic algorithm with complex multi-chromosome mutation tree can balance the two objective functions of the number of TSP and total travel time well, improve the algorithm of travel speed, and reduce …

Design And Realization Of Ship Virtual Fire Training System Based On Hmd, Zhang Bo, Sun Jun, Shang Lei, Hongji Xu, Yang Cheng

Journal of System Simulation

Abstract: Aiming at the shortcomings of ship fire training in real environment and the advantages and application of virtual reality technology in education and training, the virtual fire training system of ship based on head mount display (HMD) is developed. The system is developed using the Unity 3D Virtual Reality Development Engine as a platform, using client / server mode, supporting multi-person cooperative operation, and running the terminal for HTC Vive virtual reality hardware. The system combines the fire diffuser mechanism, the water shooting hydrodynamic equation and the particle system; completes the model establishment and visualization process, and improves …

Virtual Scene Simulation Of Pilot Response In Taking-Off And Landing Processes Of Carrier-Based Aircraft, Ke Peng, Chenglin Xu, Songyang Liu, Minggao Li, Zhao Xin

Journal of System Simulation

Abstract: A research and implementation method based on biomechanics simulation and virtual scene simulation was put forward to investigate the dynamics responses of pilots during the taking off and landing processes of carrier-based aircraft. The human biomechanics calculation of pilots and 3D virtual scene simulation of flight scene were combined to design and develop the integrated virtual simulation platform. This platform has the functions of data management and analysis, human biological dynamics calculation, synchronous analysis of key results, 3D virtual scene simulation of taking-off and landing processes and human response. The verification was carried out using the experiments from …

Modeling And Timing Simulation Of Turbojet Engine Starting Process, Wang Lei, Liying Yang, Hongda Zhang, Yuqing He

Journal of System Simulation

Abstract: The turbojet engine is complicated in its starting process and requires collaboration and cooperation involving all the execution structures, thus higher demand is put forward for the control system. How to model the engine starting process, and then accurately describe and analyze the impact of actuator states on engine performance directly affect the engine control system performance. According to the working principle of the JetCat-P400 German turbojet starting process, the rotor speed mathematical model of the turbojet engine starting process is constructed by the component method. The parameters of the model are identified by combining the experimental data of …

Wind Speed Noise Reduction In Wind Farm Based On Variational Mode Decomposition, Xinghua Xu, Tinglong Pan, Dinghui Wu

Journal of System Simulation

Abstract: Wind power forecast is based on the existing data, and the wind speed data in wind power are mixed with different types of noise. In order to improve the precision of prediction, noise reduction is needed. However, the traditional empirical mode decomposition noise reduction method has the phenomenon of mode mixing. To improve the effect of the noise reduction, a kind of noise reduction method based on variational mode decomposition is proposed. The variational mode decomposition is a new method which has good noise immunity and no mode mixing. To thoroughly research the application of variational mode decomposition …

Predictive Control For Permanent Magnet Synchronous Motor Based On Imc Observer, Zhiling Ren, Zhongbao Zhang, Limin Hou, Guangquan Zhang, Lin Dong, Zhao Xing

Journal of System Simulation

Abstract: Predictive control strategy is applied to permanent magnet synchronous motor control system, it can achieve fast dynamic response and high-precision tracking control, but depending on the mathematical model of the motor, the load disturbance will affect the control performance of system. A new control method combining an observer based on internal model control (IMC) and predictive control was presented. The inner-loop current controller and the outer-loop speed controller based separately on model predictive control algorithm and deadbeat current predictive control algorithm were designed to form dual-loop predictive control system. An IMC observer is designed to estimate the load disturbance, …