Digital Commons Network^™

Direct Adaptive Control For A Trajectory Tracking Uav, Nirmit Prabhakar

Doctoral Dissertations and Master's Theses

This research focuses on the theoretical development and analysis of a direct adaptive control algorithm to enable a fixed-wing UAV to track reference trajectories while in the presence of persistent external disturbances. A typical application of this work is autonomous flight through urban environments, where reference trajectories would be provided by a path planning algorithm and the vehicle would be subjected to significant wind gust disturbances. Full 6-DOF nonlinear and linear UAV simulation models are developed and used to study the performance of the direct adaptive control system for various scenarios. A stability proof is developed to prove convergence of …

Variable Fidelity Studies In Wake Vortex Evolution, Safety, And Control, Petr Kazarin

Doctoral Dissertations and Master's Theses

The purpose of this research is to develop a variable-fidelity approach for addressing the safety of unmanned aerial system (UAS) operations in the national aerospace system (NAS). This task is implemented on the basis of safety investigation toolkit for analysis and reporting wake vortex safety system (SITAR WVSS) code, which is a dynamic low-fidelity model addressing generation, evolution, and interaction of the leader-aircraft wake vortex with the follower-aircraft lifting surfaces.

The first part of the dissertation deals with the generation, evolution, and interaction of the wake vortices produced by an aircraft. In particular, it presents the results of the vortex …

Topology Optimization Using Load Path And Homogenization, Kaveh Gharibi

Doctoral Dissertations and Master's Theses

In this work, the connection between topology optimization and load transfer has been established. New methods for determining load paths in two dimensional structures, plates and shells are introduced. In the two-dimensional space, there are two load paths with their total derivative equal to the transferred load, their partial derivatives related to stress tensor, and satisfying equilibrium. In the presence of a body load the stress tensor can be decomposed into solenoidal and irrotational fields using Gurtin or Helmholtz decomposition. The load path is calculated using the solenoidal field. A novel method for topology optimization using load paths and total …

Carnivorous Pitcher Plants Eat A Diet Of Certain Spiders, Regardless Of What's On The Menu, Marc A. Milne, Deborah A. Waller

Biological Sciences Faculty Publications

The purple pitcher plant, Sarracenia purpurea, is a low-lying carnivorous plant that uses pitcher-shaped leaves to catch arthropod prey for nutrition. Spiders make up a significant portion of these prey. To determine the tendency of specific spider taxa to be captured by the plant, we compared the composition (by taxonomic family) of three spider assemblages: those captured by the plant, those residing on or over the plant, and those found nearby in the local environment. Although there were some broad similarities within the three spider assemblages, significant differences existed when specific families and guilds were considered. While some families …

Females In Stem Field: Is Equality Part Of The Problem? A Conversation., Amanda M. Wolcott

Faculty and Staff Publications & Presentations

No abstract provided.

A Deep Eastern Equatorial Pacific Thermocline During The Last Glacial Maximum, H. L. Ford, C. L. Mcchesney, J. E. Hertzberg, J. F. Mcmanus

OES Faculty Publications

The mean state and variability of the tropical Pacificis influenced by the depth of the thermocline. During the Last Glacial Maximum (~21,000 years ago), the zonal sea surface temperature gradient across the equatorial Pacific was reduced and productivity was generally lower than modern. To understand the thermocline depth’s role in determining the Last Glacial Maximum tropical mean state, we reconstruct the upper ocean δ¹⁸O profile from multiple species of planktic foraminifera. We synthesize existing records of surface and subsurface dwelling foraminifera to reconstruct the vertical δ¹⁸O gradient throughout the eastern equatorial Pacific. We find the thermocline …

Hot Spots And Hot Moments Of Soil Moisture Explain Fluctuations In Iron And Carbon Cycling In A Humid Tropical Forest Soil, Diego Barcellos, Christine S. O'Connell, Whendee L. Silver, Christof Meile, Aaron Thompson

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Soils from humid forests undergo spatial and temporal variations in moisture and oxygen (O₂) in response to rainfall, and induce changes in iron (Fe) and carbon (C) biogeochemistry. We hypothesized that high rainfall periods stimulate Fe and C cycling, with the greatest effects in areas of high soil moisture. To test this, we measured Fe and C cycling across three catenas at valley, slope, and ridge positions every two days for a two-month period in a rainforest in Puerto Rico. Over 12 days without rain, soil moisture, Fe^II, rapidly reducible Fe oxides (Fe^III_RR), …

Successful Negotiations: A Phenomenological Study Of The Lived Experiences Of Superintendents Who Successfully Negotiate Teacher Contracts, Kelly A. Theurer

Doctoral Dissertations and Projects

New York State has a long history related to teachers’ unions. Superintendents are often the main players for school districts when negotiating teachers’ contracts. While much has been researched about negotiations, there is a gap in the literature in relation to the motivating factors of superintendents to successfully negotiate teachers’ contracts. The purpose of this transcendental phenomenological study was to describe the lived experiences of school superintendents who have successfully negotiated teachers’ contracts within suburban areas of New York State. The central research question was: What are the lived experiences of school superintendents who have successfully negotiated teachers’ contracts in …

Bio-Inspired Polydopamine Surface Modification Of Nanodiamonds And Its Reduction Of Silver Nanoparticles, Yun Zeng, Wenyan Liu, Risheng Wang

Chemistry Faculty Research & Creative Works

Surface functionalization of nanodiamonds (NDs) is still challenging due to the diversity of functional groups on the ND surfaces. Here, we demonstrate a simple protocol for the multifunctional surface modification of NDs by using mussel-inspired polydopamine (PDA) coating. In addition, the functional layer of PDA on NDs could serve as a reducing agent to synthesize and stabilize metal nanoparticles. Dopamine (DA) can self-polymerize and spontaneously form PDA layers on ND surfaces if the NDs and dopamine are simply mixed together. The thickness of a PDA layer is controlled by varying the concentration of DA. A typical result shows that a …

Class Discussion Management And Analysis Application, Venky Shankararaman, Swapna Gottipati, Seshan Ramaswami, Chirag Chhablan

Research Collection School Of Computing and Information Systems

Discussion-based teaching is popular in several courses because it creates opportunities for students to practice important skills useful for the working environment. In order to make this pedagogy impactful and effective, instructors employ technologies such as online discussion forums and student response systems to conduct and manage classroom discussions. More recently mobile devices have become prevalent and researchers have been exploring how this device can help support education. In this paper we report the innovative use of mobile technology and supporting backend tools to manage classroom discussions. We have implemented a class discussion and management application, LiveClass. This application records …

Early Detection Of Disease Using Electronic Health Records And Fisher's Wishart Discriminant Analysis, Sijia Yang, Jian Bian, Zeyi Sun, Licheng Wang, Haojin Zhu, Haoyi Xiong, Yu Li

Engineering Management and Systems Engineering Faculty Research & Creative Works

Linear Discriminant Analysis (LDA) is a simple and effective technique for pattern classification, while it is also widely-used for early detection of diseases using Electronic Health Records (EHR) data. However, the performance of LDA for EHR data classification is frequently affected by two main factors: ill-posed estimation of LDA parameters (e.g., covariance matrix), and "linear inseparability" of the EHR data for classification. To handle these two issues, in this paper, we propose a novel classifier FWDA -- Fisher's Wishart Discriminant Analysis, which is developed as a faster and robust nonlinear classifier. Specifically, FWDA first surrogates the distribution of "potential" inverse …

Leveling The Playing Field: Supporting Neurodiversity Via Virtual Realities, Louanne E. Boyd, Kendra Day, Natalia Stewart, Kaitlyn Abdo, Kathleen Lamkin, Erik J. Linstead

Mathematics, Physics, and Computer Science Faculty Articles and Research

Neurodiversity is a term that encapsulates the diverse expression of human neurology. By thinking in broad terms about neurological development, we can become focused on delivering a diverse set of design features to meet the needs of the human condition. In this work, we move toward developing virtual environments that support variations in sensory processing. If we understand that people have differences in sensory perception that result in their own unique sensory traits, many of which are clustered by diagnostic labels such as Autism Spectrum Disorder (ASD), Sensory Processing Disorder, Attention-Deficit/Hyperactivity Disorder, Rett syndrome, dyslexia, and so on, then we …

Spatial Factor Models For High-Dimensional And Large Spatial Data: An Application In Forest Variable Mapping, Daniel Taylor-Rodríguez, Andrew O. Finley, Abhirup Datta, Chad Babcock, Hans-Erik Andersen, Bruce D. Cook, Douglas C. Morton, Sudipto Banerjee

Mathematics and Statistics Faculty Publications and Presentations

Gathering information about forest variables is an expensive and arduous activity. As such, directly collecting the data required to produce high-resolution maps over large spatial domains is infeasible. Next generation collection initiatives of remotely sensed Light Detection and Ranging (LiDAR) data are specifically aimed at producing complete-coverage maps over large spatial domains. Given that LiDAR data and forest characteristics are often strongly correlated, it is possible to make use of the former to model, predict, and map forest variables over regions of interest. This entails dealing with the high-dimensional (∼10² ) spatially dependent LiDAR outcomes over a large number …

Differentially Private Location Protection With Continuous Time Stamps For Vanets, Zhili Chen, Xianyue Bao, Zuobin Ying, Ximeng Liu, Hong Zhong

Research Collection School Of Computing and Information Systems

Vehicular Ad hoc Networks (VANETs) have higher requirements of continuous Location-Based Services (LBSs). However, the untrusted server could reveal the users’ location privacy in the meantime. Syntactic-based privacy models have been widely used in most of the existing location privacy protection schemes. Whereas, they are suffering from background knowledge attacks, neither do they take the continuous time stamps into account. Therefore we propose a new differential privacy definition in the context of location protection for the VANETs, and we designed an obfuscation mechanism so that fine-grained locations and trajectories will not exposed when vehicles request location-based services on continuous time …

Identifying Elderly With Poor Sleep Quality Using Unobtrusive In-Home Sensors For Early Intervention, Xiaoping Ma, W K P Neranjana Nadee Rodrigo Goonawardene, Hwee-Pink Tan

Research Collection School Of Computing and Information Systems

Along with the upward trend in population ageing is the increasing proportion of the elderly population living alone in the community. This group is especially vulnerable as the onset of various physical, social and mental health issues may be more likely and may go undetected. However, smart homes enabled with elderly monitoring and care systems (EMCS) can now be used to alert caregivers of anomalies in the daily living patterns of the elderly. In this study, we focus on the sleep quality as the key living pattern, as it has been shown that poor sleep quality can lead to health …

Centroid-Amenities: An Interactive Visual Analytical Tool For Exploring And Analyzing Amenities In Singapore, Xue Qian Jazreel Siew, Sean Jia Ming Koh

Research Collection School Of Computing and Information Systems

Planning for civic amenities in a fast-changing urban setting such as Singapore is never an easy task. And as urban planners look toward more data-driven approaches toward urban planning, so grows the demand for more flexible geospatial analytics tools to facilitate a more iterative and granular approach toward urban planning. Such specific tools however, are not always readily available as plugins for traditional desktop GIS software, as numerous customizations must be made to model specific temporal planning scenarios for quick analysis, which could prove both costly and time-consuming. Hence, to address this need, open-source tools such as R Shiny could …

Artefact: An R Implementation Of The Autospearman Function, Jirayus Jiarpakdee, Chakkrit Tantithamthavorn, Christoph Treude

Research Collection School Of Computing and Information Systems

This artefact is the implementation of AutoSpearman, an automated metric selection approach based on correlation analyses. The goal of AutoSpearman is to automatically mitigate correlated metrics prior to constructing analytical models. This artefact is implemented as an R package and is available in the GitHub repository. We provide descriptions and R code snippets for the installation of AutoSpearman and usage examples.

Cross-Border Interbank Payments And Settlements: Emerging Opportunities For Digital Transformation, Yi Meng Lau, Et Al

Research Collection School Of Computing and Information Systems

The report “Cross-Border Interbank Payments and Settlements” is a cross-jurisdictional industry collaboration between Canada, Singapore and the United Kingdom to examine the existing challenges and frictions that arise when undertaking crossborder payments. This report explores proposals for new and more efficient models for processing cross-border transactions.

Joint Representation Learning Of Cross-Lingual Words And Entities Via Attentive Distant Supervision, Yixin Cao, Lei Hou, Juanzi Li, Zhiyuan Liu, Chengjiang Li, Xu Chen, Tiansi Dong

Research Collection School Of Computing and Information Systems

Joint representation learning of words and entities benefits many NLP tasks, but has not been well explored in cross-lingual settings. In this paper, we propose a novel method for joint representation learning of cross-lingual words and entities. It captures mutually complementary knowledge, and enables cross-lingual inferences among knowledge bases and texts. Our method does not require parallel corpora, and automatically generates comparable data via distant supervision using multi-lingual knowledge bases. We utilize two types of regularizers to align cross-lingual words and entities, and design knowledge attention and crosslingual attention to further reduce noises. We conducted a series of experiments on …

Latent Dirichlet Allocation For Textual Student Feedback Analysis, Swapna Gottipati, Venky Shankararaman, Jeff Lin

Research Collection School Of Computing and Information Systems

Education institutions collect feedback from students upon course completion and analyse it to improve curriculum design, delivery methodology and students' learning experience. A large part of feedback comes in the form textual comments, which pose a challenge in quantifying and deriving insights. In this paper, we present a novel approach of the Latent Dirichlet Allocation (LDA) model to address this difficulty in handling textual student feedback. The analysis of quantitative part of student feedback provides generalratings and helps to identify aspects of the teaching that are successful and those that can improve. The reasons for the failure or success, however, …

Heterogeneous Embedding Propagation For Large-Scale E-Commerce User Alignment, Vincent W. Zheng, Mo Sha, Yuchen Li, Hongxia Yang, Yuan Fang, Zhenjie Zhang, Kian-Lee Tan, Kevin Chen-Chuan Chang

Research Collection School Of Computing and Information Systems

We study the important problem of user alignment in e-commerce: to predict whether two online user identities that access an e-commerce site from different devices belong to one real-world person. As input, we have a set of user activity logs from Taobao and some labeled user identity linkages. User activity logs can be modeled using a heterogeneous interaction graph (HIG), and subsequently the user alignment task can be formulated as a semi-supervised HIG embedding problem. HIG embedding is challenging for two reasons: its heterogeneous nature and the presence of edge features. To address the challenges, we propose a novel Heterogeneous …

Ten Years Of Hunting For Similar Code For Fun And Profit (Keynote), Stephane Glondu, Lingxiao Jiang, Zhendong Su

Research Collection School Of Computing and Information Systems

In 2007, the Deckard paper was published at ICSE. Since its publication, it has led to much follow-up research and applications. The paper made two core contributions: a novel vector embedding of structured code for fast similarity detection, and an application of the embedding for clone detection, resulting in the Deckard tool. The vector embedding is simple and easy to adapt. Similar code detection is also fundamental for a range of classical and emerging problems in software engineering, security, and computer science education (e.g., code reuse, refactoring, porting, translation, synthesis, program repair, malware detection, and feedback generation). Both have buttressed …

Vt-Revolution: Interactive Programming Tutorials Made Possible, Lingfeng Bao, Zhenchang Xing, Xin Xia, David Lo, Shanping Li

Research Collection School Of Computing and Information Systems

Programming video tutorials showcase programming tasks and associated workflows. Although video tutorials are easy to create, it isoften difficult to explore the captured workflows and interact withthe programs in the videos. In this work, we propose a tool named VTRevolution – an interactive programming video tutorial authoring system. VTRevolution has two components: 1) a tutorial authoring system leverages operating system level instrumentation to log workflow history while tutorial authors are creating programming video tutorials; 2) a tutorial watching system enhances the learning experience of video tutorials by providing operation history and timeline-based browsing interactions. Our tutorial authoring system does not …

Infar: Insight Extraction From App Reviews, Cuiyun Gao, Jichuan Zeng, David Lo, Chin-Yew Lin, Michael R. Lyu, Irwin King

Research Collection School Of Computing and Information Systems

App reviews play an essential role for users to convey their feedback about using the app. The critical information contained in app reviews can assist app developers for maintaining and updating mobile apps. However, the noisy nature and large-quantity of daily generated app reviews make it difficult to understand essential information carried in app reviews. Several prior studies have proposed methods that can automatically classify or cluster user reviews into a few app topics (e.g., security). These methods usually act on a static collection of user reviews. However, due to the dynamic nature of user feedback (i.e., reviews keep coming …

Improving Knowledge Tracing Model By Integrating Problem Difficulty, Sein Minn, Feida Zhu, Michel C. Desmarais

Research Collection School Of Computing and Information Systems

Intelligent Tutoring Systems (ITS) are designed for providing personalized instructions to students with the needs of their skills. Assessment of student knowledge acquisition dynamically is nontrivial during her learning process with ITS. Knowledge tracing, a popular student modeling technique for student knowledge assessment in adaptive tutoring, which is used for tracing student's knowledge state and detecting student's knowledge acquisition by using decomposed individual skill or problems with a single skill per problem. Unfortunately, recent KT models fail to deal with practices of complex skill composition and variety of concepts included in a problem simultaneously. Our goal is to investigate a …

Learning Probabilistic Models For Model Checking: An Evolutionary Approach And An Empirical Study, Jingyi Wang, Jun Sun, Qixia Yuan, Jun Pang

Research Collection School Of Computing and Information Systems

Many automated system analysis techniques (e.g., model checking, model-based testing) rely on first obtaining a model of the system under analysis. System modeling is often done manually, which is often considered as a hindrance to adopt model-based system analysis and development techniques. To overcome this problem, researchers have proposed to automatically “learn” models based on sample system executions and shown that the learned models can be useful sometimes. There are however many questions to be answered. For instance, how much shall we generalize from the observed samples and how fast would learning converge? Or, would the analysis result based on …

Learning Generalized Video Memory For Automatic Video Captioning, Poo-Hee Chang, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Recent video captioning methods have made great progress by deep learning approaches with convolutional neural networks (CNN) and recurrent neural networks (RNN). While there are techniques that use memory networks for sentence decoding, few work has leveraged on the memory component to learn and generalize the temporal structure in video. In this paper, we propose a new method, namely Generalized Video Memory (GVM), utilizing a memory model for enhancing video description generation. Based on a class of self-organizing neural networks, GVM’s model is able to learn new video features incrementally. The learned generalized memory is further exploited to decode the …

Privacy-Preserving Communication And Power Injection Over Vehicle Networks And 5g Smart Grid Slice, Yinghui Zhang, Jin Li, Dong Zheng, Ping Li, Yangguang Tian

Research Collection School Of Computing and Information Systems

As an important combination of autonomous vehicle networks (AVNs) and smart grid, the vehicle-to-grid (V2G) network can facilitate the adoption of renewable resources. Based on V2G networks, parked electric vehicles (EVs) can charge during off-peak hours and inject excess power to the grid during peak hours for earnings. However, each EV's power injection bids in V2G are sensitive and vehicle-to-vehicle (V2V) communication may be eavesdropped, which has become an obstacle to the wide deployments of AVNs. Aiming to efficiently tackle these security and privacy issues in AVNs, we propose an efficient privacy-preserving communication and power injection (ePPCP) scheme without pairings, …

Imaginary People Representing Real Numbers: Generating Personas From Online Social Media Data, Jisun An, Haewoon Kwak, Soongyo Jung, Joni Salminen, M. Admad, Bernard J. Jansen

Research Collection School Of Computing and Information Systems

We develop a methodology to automate creating imaginary people, referred to as personas, by processing complex behavioral and demographic data of social media audiences. From a popular social media account containing more than 30 million interactions by viewers from 198 countries engaging with more than 4,200 online videos produced by a global media corporation, we demonstrate that our methodology has several novel accomplishments, including: (a) identifying distinct user behavioral segments based on the user content consumption patterns; (b) identifying impactful demographics groupings; and (c) creating rich persona descriptions by automatically adding pertinent attributes, such as names, photos, and personal characteristics. …

Comparing Specific Excess Power Of General Aviation Aircraft, Yohan Forbes Auguste

Theses and Dissertations

The high number of Loss of Control and Controlled Flight into Terrain Accidents in General Aviation (GA) suggests that there is a lack of understanding and recognition of low energy states by pilots of GA aircraft. As a result there is a desire to implement an energy management system in GA aircraft to alert the pilot of low energy conditions and to give the required corrective action to get to a desired energy state. This requires an understanding of the performance capabilities of GA aircraft in terms of their ability to change their energy state. The ability to change the …