Physical Sciences and Mathematics Commons^™

Correlations Between Soil Redness And Soil Properties That Affect Non-Native Annual Plant Distribution In Chaparral And California Sage Scrub, Madeline Blua

Electronic Theses, Projects, and Dissertations

Non-native annual plant species have degraded California Sage Scrub and chaparral and present obstacles to shrubland restoration. Red soil patches in chaparral and California Sage Scrub of San Bernardino and Riverside counties appear to support fewer non-native annual plants than non-red soils. The purpose of this study was to confirm differences in vegetation cover between red and non-red soils in shrublands and to use soil analyses to determine possible causes. During vegetation surveys conducted in April of 2018, it was confirmed that red soil sites had lower cover of non-native plants and higher cover of native plant species than the …

Assessing The Potential Equity Outcomes Of Maine’S Climate Action Plan: Framework, Analysis And Recommendations, Senator George J. Mitchell Center For Sustainability Solutions

General University of Maine Publications

The recommendations of these groups have now been completed and the equity assessment that you see before you contains an analysis that was carried out by the University of Maine’s Senator George J. Mitchell Center for Sustainability Solutions (hereafter, Mitchell Center) to assess the recommendations’ attention to equity issues.

While the impacts of Maine decreasing its greenhouse gas emissions will not be large relative to global emissions, the state’s Climate Action Plan is an important step in the right direction. Maine is not only leading by example, but is also creating policies that will reduce emissions as well as enhance …

Low-Information Radiation Imaging Using Rotating Scatter Mask Systems And Neural Network Algorithms, Robert J. Olesen

Theses and Dissertations

While recent studies have demonstrated the directional capabilities of the single-detector rotating scatter mask (RSM) system for discrete, dual-particle environments, there has been little progress towards adapting it as a true imaging device. In this research, two algorithms were developed and tested using an RSM mask design previously optimized for directional detection and simulated 137Cs signals from a variety of source distributions. The first, maximum-likelihood expectation-maximization (ML-EM), was shown to generate noisy images, with relatively low accuracy (145% average relative error) and signal-to-noise ratio (0.27) for most source distributions simulated. The second, a novel regenerative neural network (ReGeNN), performed exceptionally …

Considering Students’ Abilities In The Academic Advising Process, Samia Loucif, Laila Gassoumi, Joao Negreiros

All Works

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. Academic advising is time-consuming work. At the same time, it needs to be efficient and productive in assisting the students to choose appropriate academic courses towards the completion of their selected programs in a beneficial manner. In addition, both private and public educational institutions are, currently, operating in an extremely competitive market and are, thus, faced with various challenges. Among these are the twin challenges of student retention and the rate of success in completion of their chosen academic courses. The mentioned challenges have a direct bearing on the quality of …

Large Signal Modeling For Llc Resonant Converter, Zheng Kai, Jianbing Li, Zhou Dongfang, Li Kai, Songzhen Zhang

Journal of System Simulation

Abstract: The large-signal model modeling issue of LLC resonant converter was dealt with by using averaged large-signal modeling method, on the basis of a full-bridge LLC voltage-multiplying resonant converter. The SSOC (self-sustained oscillation controller) was analyzed, and the operation mode of LLC resonant converter under the SSOC mode was investigated. The nonlinear state space model of LLC resonant converter was established by analyzing linear approximation of nonlinear terms and harmonic balance, and the averaged large-signal model of LLC resonant converter was proposed. Two curves of large signal model and nonlinear state space model were proved to be identical …

Simulation Research On Influence Of Blood Flow On Heating During Hifu Treatment, Suqin Dai, Shengyou Qian, Yaosheng Gui, Xiao Sheng

Journal of System Simulation

Abstract: When blood vessel exists in the tumor tissue, and its boundary portion close to the vessel will be strongly influenced by the cooling effect of the blood vessel. This influence will lead to the incomplete cancer treatment. To study the influence of blood flow on heating towards the above situation, concave spherical transducer was used as the heat source, and sound intensity distribution was obtained by Rayleigh integral. Pennes equation was solved with finite difference method, then the dose distribution was calculated to determine the thermal damage degree of tissue using quantitative relationship between the heating time and temperature. …

Velocity Deception Jamming Analysis Of Coherent Video Simulation Of Anti-Ship Pd Seeker, Cuiqiong Mo, Jiahai Li, Huanyao Dai, Qiuju Chen, Zhao Jing

Journal of System Simulation

Abstract: According to existed experimental evaluation of radar electronic jamming simulation for terminal guidance, the ballistic calculation model was simplified relatively. Particle model was usually adopted which made simulation results have serious distortion. The pulse Doppler radar seeker was discussed in six degree of freedom trajectory simulation of the closed loop (PDRS) for coherent video simulation, and simulation results show that the VGPO has no direct effect on the angle tracking loop, just through guidance filter affects the convergence angle velocity estimation, which leads to little change of guidance precision. The conclusion and anechoic chamber measurements results show that the …

Algorithm For Solving Symmetric Cone Complementarity Problems, Leifu Gao, Dongmei Yu

Journal of System Simulation

Abstract: A monotonic trust region algorithm for symmetric cone complementarity problems was proposed based on a smoothing function. The problem was transformed into unconstrained optimization problem and the trust region subproblem was constructed. The problem was solved by using trust region algorithm combined with nonmonotonic strategies, and the global convergence of the algorithm was proved. Numerical experimental results demonstrate that the algorithm is effective for symmetric cone complementarity problems.

Launch Dynamic Characteristics Simulation Analysis Of Vehicular Gatling Gun In Different Road Surface, Junnuo Zhang, Ruilin Wang, Li Tao, Binbin Hua

Journal of System Simulation

Abstract: To study the influence of firing accuracy on a certain vehicular Gatling gun in different road surface, a rigid-flexible coupling multi-body dynamic simulation model was established based on virtual prototyping technology. Considering the interaction relations between the tires and road surface, vehicle and machine gun, the vehicle vibration characteristics and the muzzle response characteristics and vertical-target dispersion were obtained by analyzing the machine gun system in different road surface. The influence of road surface on fire accuracy was demonstrated by contrasting and analyzing the simulation curves. The study results have provided a theoretical support and direction …

Research Of Marshalling Yard Dispersion Based On Simulation In Container Terminal, Yu Hang, Le Meilong

Journal of System Simulation

Abstract: As development of the precision management in the container terminal, close attention was paid to the research on the optimization of the marshalling yard template. The new concept called the yard dispersion in the container yard template was proposed and the professional simulation software Flexsim-CT was used to build a container handling simulation model which includes berth, quay crane, yard scheduling, yard crane, and trucks. The impact of the different yard dispersion on the total handling time and the efficiency of the quay crane under varying service burden was analyzed. The case study combines the simulation model with …

Pid Closed Loop Control Performance Analysis Of Piezostack-Driven Jet Dispensing Valve, Yunbo Fu, Xinbo Li, Guojun Liu, Jianfang Liu, Yaowu Shi

Journal of System Simulation

Abstract: A new type of piezostack-driven jetting dispenser was proposed which used hydraulic magnification, and analyzed its injection process and injection condition. The open loop model of dispensing system was built by AMESim software. The simulation proved the feasibility. The closed loop control system with PID (Proportion Integration Differentiation) algorithm was set up to improve performance of open loop dispensing system, and the open and closed loop control performance was compared under the simulation environment. Analysis shows that PID closed loop system can improve performance of piezostack-driven jetting dispensing system. When nozzle diameter is 0.1mm and syringe pressure …

Deep Learning Techniques For Structural Response Prediction During Strong Ground Motions, Ahmed A. Torky, Susumu Ohno Prof., Toshide Kashima Prof.

Civil Engineering

In this paper, deep learning techniques are applied to predict a building’s structural response to strong ground motions. Data from sensors near and inside structures measure accelerations during strong ground motions. The Building Research Institute (BRI) ANX building, an eight-story structure, has experienced major earthquakes since 1998. Sensors in the building provide and accumulate big data of historic events. Changes of the natural frequency of the ANX building from the big data is initially quantified. The time-series data of the historic events can be used to predict future response to future events using deep learning models rapidly. Although previous literature …

Electromagnetic Reciprocity In The Presence Of Topological Insulators, Huai-Yi Xie, P. T. Leung

Physics Faculty Publications and Presentations

Electromagnetic reciprocity is studied in the presence of topological insulators (TI) with application of axion electrodynamics for harmonic electromagnetic fields. The corresponding generalized Lorentz and Feld-Tai type lemmas are derived in terms of the axion coupling parameter, and their correlation to the conditional symmetry in source-observer coordinates for the various Green dyadics is established subjected to different types of boundary conditions. Possible application of the results to the probing of the topological magneto-electric effects from TI is discussed.

Patagonian Aridification At The Onset Of The Mid‐Miocene Climatic Optimum, Robin B. Trayler, Matthew J. Kohn, M. Susana Bargo, José I. Cuitiño, Richard F. Kay, Caroline A. E. Strömberg, Sergio F. Vizcaíno

Geosciences Faculty Publications and Presentations

Fossil‐rich sediments of the Santa Cruz Formation, Patagonia, Argentina, span the initiation of the Miocene Climatic Optimum (MCO), the most recent period of warm and wet conditions in the Cenozoic. These conditions drove the expansion of tropical and subtropical ecosystems to much higher latitudes, with the fossiliferous Santa Cruz Formation recording one of the southernmost examples. We collected new carbon and oxygen isotope compositions of herbivore tooth enamel from fossils ~17.4 to 16.4 Ma in age to investigate ecological and climatic changes across the initiation of the MCO. Enamel δ¹³C values are consistent with a C₃‐dominated …

A First-Year Research Experience: The Freshman Project In Physics At Loyola University Chicago, Jonathan Bougie, Asim Gangopadhyaya, Sherita Moses, Robert Polak, Gordon Ramsey, Weronika Walkosz

Physics: Faculty Publications and Other Works

Undergraduate research has become an essential mode of engaging and retaining students in physics. At Loyola University Chicago, first-year physics students have been participating in the Freshman Projects program for over twenty years, which has coincided with a period of significant growth for our department. In this paper, we describe how the Freshman Projects program has played an important role in advancing undergraduate research at Loyola and the profound impact it has made on our program. We conclude with suggestions for adoption of similar programs at other institutions.

Artificial Intelligence In Pursuit-Evasion Games, Specifically In The Scotland Yard Game, Arif M. Alamri

Theses and Dissertations

This research provides a heuristic algorithm for the detectives, who try to collectively capture a criminal known as Mr. X, in the Scotland Yard pursuer-evasion game. In Scotland Yard, a team of detectives attempts to converge on and capture a criminal known as Mr. X. The heuristic algorithm developed in this thesis is designed to emulate human strategies when playing the game. The algorithm uses the current state of the board at each time step, including the current positions of the detectives as well as the last known position of Mr. X. The heuristic algorithm then analyses all of the …

The Impact Of Herbal Infusion Consumption On Oxidative Stress And Cancer: The Good, The Bad, The Misunderstood, Wamidh H. Talib, Israa A. Al-Ataby, Asma Ismail Mahmod, Sajidah Jawarneh, Lina T. Al Kury, Intisar Hadi Al-Yasari

All Works

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. The release of reactive oxygen species (ROS) and oxidative stress is associated with the development of many ailments, including cardiovascular diseases, diabetes and cancer. The causal link between oxidative stress and cancer is well established and antioxidants are suggested as a protective mechanism against cancer development. Recently, an increase in the consumption of antioxidant supplements was observed globally. The main sources of these antioxidants include fruits, vegetables, and beverage. Herbal infusions are highly popular beverages consumed daily for different reasons. Studies showed the potent antioxidant effects of plants used in the …

Marble: Model-Based Robustness Analysis Of Stateful Deep Learning Systems, Xiaoning Du, Yi Li, Xiaofei Xie, Lei Ma, Yang Liu, Jianjun Zhao

Research Collection School Of Computing and Information Systems

State-of-the-art deep learning (DL) systems are vulnerable to adversarial examples, which hinders their potential adoption in safetyand security-critical scenarios. While some recent progress has been made in analyzing the robustness of feed-forward neural networks, the robustness analysis for stateful DL systems, such as recurrent neural networks (RNNs), still remains largely uncharted. In this paper, we propose Marble, a model-based approach for quantitative robustness analysis of real-world RNN-based DL systems. Marble builds a probabilistic model to compactly characterize the robustness of RNNs through abstraction. Furthermore, we propose an iterative refinement algorithm to derive a precise abstraction, which enables accurate quantification of …

Group Instance: Flexible Co-Location Resistant Virtual Machine Placement In Iaas Clouds, Vu Duc Long, Nguyen Binh Duong Ta

Research Collection School Of Computing and Information Systems

This paper proposes and analyzes a new virtual machine (VM) placement technique called Group Instance to deal with co-location attacks in public Infrastructure-as-a-Service (IaaS) clouds. Specifically, Group Instance organizes cloud users into groups with pre-determined sizes set by the cloud provider. Our empirical results obtained via experiments with real-world data sets containing million of VM requests have demonstrated the effectiveness of the new technique. In particular, the advantages of Group Instance are three-fold: 1) it is simple and highly configurable to suit the financial and security needs of cloud providers, 2) it produces better or at least similar performance compared …

Learning To Collaborate In Multi-Module Recommendation Via Multi-Agent Reinforcement Learning Without Communication, Xu He, An Bo, Yanghua Li, Haikai Chen, Rundong Wang, Xinrun Wang, Runsheng Yu, Xin Li, Zhirong Wang

Research Collection School Of Computing and Information Systems

With the rise of online e-commerce platforms, more and more customers prefer to shop online. To sell more products, online platforms introduce various modules to recommend items with different properties such as huge discounts. A web page often consists of different independent modules. The ranking policies of these modules are decided by different teams and optimized individually without cooperation, which might result in competition between modules. Thus, the global policy of the whole page could be sub-optimal. In this paper, we propose a novel multi-agent cooperative reinforcement learning approach with the restriction that different modules cannot communicate. Our contributions are …

Querying Recurrent Convoys Over Trajectory Data, Munkh-Erdene Yadamjav, Zhifeng Bao, Baihua Zheng, Farhana M. Choudhury, Hanan Samet

Research Collection School Of Computing and Information Systems

Moving objects equipped with location-positioning devices continuously generate a large amount of spatio-temporal trajectory data. An interesting finding over a trajectory stream is a group of objects that are travelling together for a certain period of time. Existing studies on mining co-moving objects do not consider an important correlation between co-moving objects, which is the reoccurrence of the movement pattern. In this study, we define a problem of finding recurrent pattern of co-moving objects from streaming trajectories and propose an efficient solution that enables us to discover recent co-moving object patterns repeated within a given time period. Experimental results on …

Zone Path Construction (Zac) Based Approaches For Effective Real-Time Ridesharing, Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet

Research Collection School Of Computing and Information Systems

Real-time ridesharing systems such as UberPool, Lyft Line, GrabShare have become hugely popular as they reduce the costs for customers, improve per trip revenue for drivers and reduce traffic on the roads by grouping customers with similar itineraries. The key challenge in these systems is to group the "right" requests to travel together in the "right" available vehicles in real-time, so that the objective (e.g., requests served, revenue or delay) is optimized. This challenge has been addressed in existing work by: (i) generating as many relevant feasible (with respect to the available delay for customers) combinations of requests as possible …

Coronavirus: Pandemics, Artificial Intelligence And Personal Data: How To Manage Pandemics Using Ai And What That Means For Personal Data Protection, Warren B. Chik

Research Collection Yong Pung How School Of Law

This chapter discusses the hearing of essential and urgent court matters in the Singapore courts during the COVID-19 pandemic. On 27 march 2020, the Singapore judiciary notified courst users that remote hearings were to be implemented for certain types of hearings by means of video and telephone conferencing facilities. Court users were also provided with indicative lists of matters which might be considered essential and urgent.

Emulating Condensed Matter Systems In Classical Wave Metamaterials, Matthew Weiner

Dissertations, Theses, and Capstone Projects

One of the best tools we have for the edification of physics is the analogy. When we take our classical set of states and dynamical variables in phase space and treat them as vectors and Hermitian operators respectively in Hilbert space through the canonical quantization, we lose out on a lot of the intuition developed with the previous classical physics. With classical physics, through our own experiences and understanding of how systems should behave, we create easy-to-understand analogies: we compare the Bohr model of the atom to the motion of the planets, we compare electrical circuits to the flow of …

Role Of Influence In Complex Networks, Nur Dean

Dissertations, Theses, and Capstone Projects

Game theory is a wide ranging research area; that has attracted researchers from various fields. Scientists have been using game theory to understand the evolution of cooperation in complex networks. However, there is limited research that considers the structure and connectivity patterns in networks, which create heterogeneity among nodes. For example, due to the complex ways most networks are formed, it is common to have some highly “social” nodes, while others are highly isolated. This heterogeneity is measured through metrics referred to as “centrality” of nodes. Thus, the more “social” nodes tend to also have higher centrality.

In this thesis, …

Parametrically Excited Star-Shaped Patterns At The Interface Of Binary Bose-Einstein Condensates, D. K. Maity, K. Mukherjee, Simeon I. Mistakidis, S. Das, P. G. Kevrekidis, S. Majumder, P. Schmelcher

Physics Faculty Research & Creative Works

A Faraday-Wave-Like Parametric Instability Is Investigated Via Mean-Field And Floquet Analysis In Immiscible Binary Bose-Einstein Condensates. The Condensates Form A So-Called Ball-Shell Structure In A Two-Dimensional Harmonic Trap. To Trigger The Dynamics, The Scattering Length Of The Core Condensate Is Periodically Modulated In Time. We Reveal That In The Dynamics The Interface Becomes Unstable Towards The Formation Of Oscillating Patterns. The Interface Oscillates Subharmonically, Exhibiting An M-Fold Rotational Symmetry That Can Be Controlled By Maneuvering The Amplitude And The Frequency Of The Modulation. Using Floquet Analysis We Are Able To Predict The Generated Interfacial Tension Of The Mixture And Derive …

Physics-Constrained Hyperspectral Data Exploitation Across Diverse Atmospheric Scenarios, Nicholas M. Westing

Theses and Dissertations

Hyperspectral target detection promises new operational advantages, with increasing instrument spectral resolution and robust material discrimination. Resolving surface materials requires a fast and accurate accounting of atmospheric effects to increase detection accuracy while minimizing false alarms. This dissertation investigates deep learning methods constrained by the processes governing radiative transfer to efficiently perform atmospheric compensation on data collected by long-wave infrared (LWIR) hyperspectral sensors. These compensation methods depend on generative modeling techniques and permutation invariant neural network architectures to predict LWIR spectral radiometric quantities. The compensation algorithms developed in this work were examined from the perspective of target detection performance using …

Creating A Culture Of Data-Driven Decision-Making, Kevin Bryan Rogers

Doctoral Dissertations and Projects

Researchers have consistently shown that a supportive culture is one of the most crucial success factors in the implementation of any big data solution. Creating a culture that supports data-driven decision-making is a difficult but ultimately required step in transforming an organization into one that can readily and successfully adopt business intelligence technologies. The purpose of this qualitative case study was to understand the ways in which organizations can foster a culture of smarter decision-making and accountability so that businesses can improve operational metrics and ultimately profitability. Participants identified three major themes that drive the adoption of a data-driven culture. …

Direct Digital Synthesis: A Flexible Architecture For Advanced Signals Research For Future Satellite Navigation Payloads, Pranav R. Patel

Theses and Dissertations

In legacy Global Positioning System (GPS) Satellite Navigation (SatNav) payloads, the architecture does not provide the flexibility to adapt to changing circumstances and environments. GPS SatNav payloads have largely remained unchanged since the system became fully operational in April 1995. Since then, the use of GPS has become ubiquitous in our day-to-day lives. GPS availability is now a basic assumption for distributed infrastructure; it has become inextricably tied to our national power grids, cellular networks, and global financial systems. Emerging advancements of easy to use radio technologies, such as software-defined radios (SDRs), have greatly lowered the difficulty of discovery and …

Integrating Affect Perception Tasks From The New York Emotion Battery Into A Comprehensive Measure Of Neuropsychological Change Across The Lifespan, Melinda A. Cornwell

Dissertations, Theses, and Capstone Projects

Background: The ability to perceive others’ emotions is a vital skill for social competency, impacting the success of personal and professional relationships (Brinton & Fujiki, 2011; Cassidy et al., 1992; Côté & Miners, 2006). According to Socioemotional Selectivity Theory (SST; Carstensen, 1991), human motivation develops to become more discerning in choosing milieus that yield the most gratifying return on the investment of personal resources (e.g., time, attention, and effort), perhaps explaining why some research findings indicate that older adults may demonstrate an affect perception (AP) bias described as a positivity effect (Reed et al., 2014). Moreover, AP predicts cognitive and …