Digital Commons Network^™

Morphological And Molecular Characterization Of Banana Clones Growing In Turkey, Fi̇li̇z Baysal, Sezai̇ Erci̇sli̇

Turkish Journal of Botany

This study was conducted to estimate genetic relationships among banana clones growing in Turkey via some morphological parameters and two molecular marker systems. In terms of yield parameters such as bunch weight, hand number, fruit weight, and total fruit number, Grand Nain (GN) clone came to the forefront with the highest values. It was followed by Azman (AZ), Dwarf Cavendish (DC), and Erdemli Yerli (EY) clones, respectively. To see the variation between clones more clearly, 24 RAPD (Random Amplified Polymorphic DNA) primers and 48 SRAP (Sequence Related Amplified Polymorphism) primer combinations were used in molecular analysis. The total number of …

It's About Time: Emphasizing Temporal Dynamics In Dynamic Personality Regulation, Joshua Wilt

Faculty Scholarship

People change over time. These changes are thought to represent some self-regulatory, dynamic processes. However, dynamic processes need to be distinguished from mere stochastic variation. Just as the Brownian motion of a dust mote does not help us understand the basic principles of classical physics, neither does random variation within an individual describe the complexity of self-regulatory processes. This regulation implies solving the problem of competing goals and desires within the constraints of situational presses. And what people feel, think, and do at one moment affects what they feel, think and do in the next moment. Thus, describing and explaining …

Artificial Intelligence In Canadian Healthcare: Will The Law Protect Us From Algorithmic Bias Resulting In Discrimination?, Bradley Henderson, Colleen M. Flood, Teresa Scassa

Canadian Journal of Law and Technology

In this article, we canvas why AI may perpetuate or exacerbate extant discrimination through a review of the training, development, and implementation of healthcare-related AI applications and set out policy options to militate against such discrimination. The article is divided into eight short parts including this introduction. Part II focuses on explaining AI, some of its basic functions and processes, and its relevance to healthcare. In Part III, we define and explain the difference and relationship between algorithmic bias and data bias, both of which can result in discrimination in healthcare settings, and provide some prominent examples of healthcare-related AI …

Epanorama October 2021, Southern Adventist University

Panorama Parent Newsletter

This electronic issue of Panorama includes information on Southern Adventist University's 27th presidential inauguration of Ken Shaw and how he and his wife are connecting with the students.

Fertilizer Use In Aquaculture, Bartholomew W. Green

United States Department of Agriculture-Agricultural Research Service / University of Nebraska-Lincoln: Faculty Publications

Aquaculture ponds traditionally are fertilized to stimulate primary productivity, which serves as the base of the pond natural food web and provides ancillary ecosystem services. Fertilizer can be made regularly or based on some water quality variable or measure of algal productivity. Nutrients from chemical fertilizers are available sooner for phytoplankton growth compared to organic fertilizers that first must undergo microbial decomposition before nitrogen and phosphorus concentrations increase. Primary production increases with increased fertilizer application if productivity is limited by primary nutrients rather than by light. In semi-intensive and intensive production systems, natural pond productivity enhanced by targeted fertilization protocols …

Ecuadorian And Uruguayan Teachers' Perceptions And Experiences Of Teaching Online During Covid, Ximena D. Burgin, Sheila Coli, Mayra C. Daniel

Faculty Articles, Papers, and Other Scholarship

Purpose: The COVID-19 pandemic is a unique event that forced K-12 schools to rethink the delivery of instruction to protect the well-being of school system stakeholders. Teachers, school administrators, and parents had to adapt to and embrace new ways of teaching and learning by utilizing available technology. The purpose of this study was to examine the challenges encountered by in-service teachers when moving from face-to-face to online teaching. Design/methodology/approach: This study utilized a qualitative phenomenological research methodology to examine Ecuadorian and Uruguayan teachers’ perceptions and experiences transitioning from face-to-face to online teaching during the COVID-19 pandemic. This comparative study used …

Hybrid Quantum-Classical Unit Commitment, Reza Mahroo, Amin Kargarian

Faculty Publications

This paper proposes a hybrid quantum-classical algorithm to solve a fundamental power system problem called unit commitment (UC). The UC problem is decomposed into a quadratic subproblem, a quadratic unconstrained binary optimization (QUBO) subproblem, and an unconstrained quadratic subproblem. A classical optimization solver solves the first and third subproblems, while the QUBO subproblem is solved by a quantum algorithm called quantum approximate optimization algorithm (QAOA). The three subproblems are then coordinated iteratively using a three-block alternating direction method of multipliers algorithm. Using Qiskit on the IBM Q system as the simulation environment, simulation results demonstrate the validity of the proposed …

Flood-Aware Optimal Power Flow For Proactive Day-Ahead Transmission Substation Hardening, Mohadese Movahednia, Amin Kargarian

Faculty Publications

Power system components, particularly electrical substations, may be severely damaged due to flooding, resulting in prolonged power outages and resilience degradation. This problem is more severe in low-elevated regions such as Louisiana. Protective operational actions such as placing tiger dams around substations before flooding can reduce substation vulnerability, damage costs, and energy not supplied cost, thus enhancing power grid resilience. This paper proposes a stochastic mixed-integer programming model for protecting transmission substations one day before flood events using tiger dams. A flood-aware optimal power flow problem is formulated for transmission system operators with respect to the protected/unprotected status of substations. …

A Deep Learning Approach To Optimal Sampling Problems, Xinxin Wang, Xiangyu Meng, Fangfei Li

Faculty Publications

Time-triggered and event-triggered sampling methods have been widely adopted in control systems. Optimal sampling problems of the two mechanisms have also received great attentions. However, for high-dimensional systems, analytical methods have some limitations. In this study, we propose a model-free method, called soft greedy policy for neural network fitting, to calculate the optimal sampling period of the time-triggered impulse control and the optimal threshold of the event-triggered impulse control. A neural network is used to approximate the objective function and then is trained. This approach is more widely applicable than the analytical method. At the same time, compared with different …

Using Powder Diffraction To Give Insight Into Structures Of Ir2(Diisocyanomenthane)4x2 [Dimen] (X = Cl; Pf6; Bph4), Mairead Brownell

Scripps Senior Theses

Ir2(dimen)42+ (dimen = 1,8-diisocyanomenthane) has been studied extensively as model compound to better understand catalysis of photochemical reactions. Although Ir2(dimen)42+ has been used primarily to observe the photophysical changes of metal-metal transitions, it gives great insight into the transitions that allow other d8-d8 metal complexes to undergo photochemical processes and generate hydrogen gas. The large visible range by which Ir2(dimen)42+ (1) can be electronically excited in solution is indicative of its two solution phase ground states, which interestingly have been hypothesized to resemble two unique packing structures observed in the powder state. In this study, the powder diffraction patterns of …

Deconstructing U.S. Army Maps Of Korea: A Case Study For Rethinking Historical Environmental Data, Lee Beckwith

Scripps Senior Theses

At a time when the natural world and global climate are experiencing extreme changes at unprecedented speeds, understanding these environmental changes over time is more important than ever. With advances in remote sensing technology, large amounts of information about the natural world are becoming more accessible than ever before; however, satellite-collected data are only available from 1984 onwards. To understand how land use has changed on longer timescales, researchers have turned towards archival maps as a data source. Archival maps are a rich source of environmental information; however, they are often saturated with complicated colonial histories. Maps, more so than …

Event-Triggered Control For Discrete-Time Systems Using A Positive Systems Approach, Frederic Mazenc, Michael Malisoff, Corina Barbalata, Zhong Ping Jiang

Faculty Publications

We provide an output feedback event-triggered controller for discrete-time linear systems. We make novel use of positive systems, interval observers, an event-triggered state estimator, and triggering times that are computed from estimator values. This provides a discrete-time analog of our recent positive systems approach for continuous-time systems. A key novel ingredient in our discrete-time event triggers is their use of vectors of absolute values, instead of the usual Euclidean norm. We illustrate the benefits of our method using a model for event-triggered BlueROV2 underwater vehicles.

Cable Decoupling And Cable-Based Stiffening Of Continuum Robots, Parsa Molaei, Nekita A. Pitts, Genevieve Palardy, Ji Su, Matthew K. Mahlin, James H. Neilan, Hunter B. Gilbert

Faculty Publications

Cable-driven continuum robots, which are robots with a continuously flexible backbone and no identifiable joints that are actuated by cables, have shown great potential for many applications in unstructured, uncertain environments. However, the standard design for a cable-driven continuum robot segment, which bends a continuous backbone along a circular arc, has many compliant modes of deformation which are uncontrolled, and which may result in buckling or other undesirable behaviors if not ameliorated. In this paper, we detail an approach for using additional cables to selectively stiffen planar cable-driven robots without substantial coupling to the actuating cables. A mechanics-based model based …

Spoken Language Interaction With Robots: Recommendations For Future Research, Casey Kennington

Computer Science Faculty Publications and Presentations

With robotics rapidly advancing, more effective human–robot interaction is increasingly needed to realize the full potential of robots for society. While spoken language must be part of the solution, our ability to provide spoken language interaction capabilities is still very limited. In this article, based on the report of an interdisciplinary workshop convened by the National Science Foundation, we identify key scientific and engineering advances needed to enable effective spoken language interaction with robotics. We make 25 recommendations, involving eight general themes: putting human needs first, better modeling the social and interactive aspects of language, improving robustness, creating new methods …

Developers Perception Of Peer Code Review In Research Software Development, Nasir U. Eisty, Jeffrey C. Carver

Computer Science Faculty Publications and Presentations

Context Research software is software developed by and/or used by researchers, across a wide variety of domains, to perform their research. Because of the complexity of research software, developers cannot conduct exhaustive testing. As a result, researchers have lower confidence in the correctness of the output of the software. Peer code review, a standard software engineering practice, has helped address this problem in other types of software.

Objective Peer code review is less prevalent in research software than it is in other types of software. In addition, the literature does not contain any studies about the use of peer code …

Drones, Virtual Reality, And Modeling: Communicating Catastrophic Dam Failure, H. R. Spero, I. Vazquez-Lopez, K. Miller, R. Joshaghani, S. Cutchin, J. Enterkine

Computer Science Faculty Publications and Presentations

Dam failures occur worldwide and can be economically and ecologically devastating. Communicating the scale of these risks to the general public and decision-makers is imperative. Two-dimensional (2D) dam failure hydraulic models inform owners and floodplain managers of flood regimes but have limitations when shared with non-specialists. This study addresses these limitations by constructing a 3D Virtual Reality (VR) environment to display the 1976 Teton Dam disaster case study using a pipeline composed of (1) 2D hydraulic model data (extrapolated into 3D), (2) a 3D reconstructed dam, and (3) a terrain model processed from UAS (Uncrewed Airborne System) imagery using Structure …

Understanding Intention For Machine Theory Of Mind: A Position Paper, Casey Kennington

Computer Science Faculty Publications and Presentations

Theory of Mind is often characterized as the ability to recognize desires, beliefs, and intentions of others. In this position paper, I look at the literature on modeling Theory of Mind in machines and find that, to date, intention is not usually a focus. I define what I mean by intention—choice with commitment—following prior work. Intention has a long history of research in some communities, and I offer one theoretical framework for modeling intention as a starting point. I take inspiration from how children learn intention through joint attention with others and how that leads to Theory of Mind. I …

Measuring Fairness In Ranked Results: An Analytical And Empirical Comparison, Amifa Raj, Michael D. Ekstrand

Computer Science Faculty Publications and Presentations

Information access systems, such as search and recommender systems, often use ranked lists to present results believed to be relevant to the user's information need. Evaluating these lists for their fairness along with other traditional metrics provides a more complete understanding of an information access system's behavior beyond accuracy or utility constructs. To measure the (un)fairness of rankings, particularly with respect to the protected group(s) of producers or providers, several metrics have been proposed in the last several years. However, an empirical and comparative analyses of these metrics showing the applicability to specific scenario or real data, conceptual similarities, and …

Incremental Unit Networks For Distributed, Symbolic Multimodal Processing And Representation, Mir Tahsin Imtiaz, Casey Kennington

Computer Science Faculty Publications and Presentations

Incremental dialogue processing has been an important topic in spoken dialogue systems research, but the broader research community that makes use of language interaction (e.g., chatbots, conversational AI, spoken interaction with robots) have not adopted incremental processing despite research showing that humans perceive incremental dialogue as more natural. In this paper, we extend prior work that identifies the requirements for making spoken interaction with a system natural with the goal that our framework will be generalizable to many domains where speech is the primary method of communication. The Incremental Unit framework offers a model of incremental processing that has been …

Symbol And Communicative Grounding Through Object Permanence With A Mobile Robot, Josue Torres-Fonseca, Catherine Henry, Casey Kennington

Computer Science Faculty Publications and Presentations

Object permanence is the ability to form and recall mental representations of objects even when they are not in view. Despite being a crucial developmental step for children, object permanence has had only some exploration as it relates to symbol and communicative grounding in spoken dialogue systems. In this paper, we leverage SLAM as a module for tracking object permanence and use a robot platform to move around a scene where it discovers objects and learns how they are denoted. We evaluated by comparing our system’s effectiveness at learning words from human dialogue partners both with and without object permanence. …

Classification Of Surface Pavement Cracks As Top-Down, Bottom-Up, And Cement-Treated Reflective Cracking Based On Deep Learning Methods, Nirmal Dhakal, Mostafa A. Elseifi, Zia U.A. Zihan, Zhongjie Zhang, Christophe N. Fillastre, Jagannath Upadhyay

Faculty Publications

The treatment and repair strategies for reflective and fatigue cracking that initiate at the pavement surface (i.e., top-down cracking) and at the bottom of the asphalt concrete layer (i.e., bottom-up cracking) are noticeably different. However, pavement management engineers are facing difficulties in identifying these cracks in the field because they usually appear in visually identical patterns. The objective of this study was to develop artificial neural network (ANN) and convolutional neural network (CNN) applications to differentiate and classify top-down, bottom-up, and cement-treated reflective cracking in in-service flexible pavements using deep-learning models. The developed CNN model achieved an accuracy of 93.8% …

Event-Triggered Prediction-Based Delay Compensation Approach, Frederic Mazenc, Michael Malisoff, Corina Barbalata

Faculty Publications

We provide a new event-triggered delay compensation approach for linear systems with arbitrarily long constant input delays. Our prediction map is expressible as a solution of a discrete time system. Our method ensures input-to-state stability. We also provide an analog under measurement delays, where the prediction map is expressible as a solution of a continuous-discrete system. Significant novel features are our combined use of matrices of absolute values and our prediction based event triggers, instead of Euclidean norms, and the fact that the predictor dynamics always has the same dimension as that of the original system. Our marine robotic example …

Estimation For Model Parameters And Maximum Power Points Of Photovoltaic Modules Using Stochastic Fractal Search Algorithms, Duy C. Huynh, Matthew W. Dunnigan, Corina Barbalata

Faculty Publications

The performance of a photovoltaic (PV) power generation system could be improved through the optimal control and operation of a PV module which is one of the fundamental components of this system. Thus, an appropriate PV module model along with precise knowledge of its parameters is necessary. This paper proposes a novel technique to estimate the source current, the saturation current of diodes, the shunt resistance, the series resistance, the ideality coefficient of diodes and the maximum power points (MPPs) of PV modules at the same time. This estimation problem can be described by the minimization of the root mean …

Event-Triggered Control For Continuous-Time Linear Systems With A Delay In The Input, Frederic Mazenc, Michael Malisoff, Corina Barbalata

Faculty Publications

We provide an event-triggered control technique for a family of linear time-varying continuous-time systems with a constant known pointwise delay in the input. We adopt a subpredictor based prediction technique, and we provide sufficient conditions that ensure that Zeno behavior does not occur. At each time, only delayed measurements are needed to implement the control. Also, the delay can be an arbitrarily large constant. We prove an input-to-state stability property for the closed-loop system, using the theory of cooperative systems. We apply our method to a gyroscopic control problem for a curve tracking dynamics arising in marine robotics.

Thermodynamic Characterization Of Grease Oxidation–Thermal Stability Via Pressure Differential Scanning Calorimetry, Jude A. Osara, Piet M. Lugt, Michael D. Bryant, Michael M. Khonsari

Faculty Publications

This study investigates and characterizes, via thermodynamic laws, a widely employed standard for measuring oxidation-thermal stability of lubricating greases—ASTM 5483—based on first-order chemical kinetics, using pressure differential scanning calorimetry (PDSC). Steps and active mechanisms in the controlled test are analyzed and modeled using energy and entropy transformations. Applying the degradation-entropy generation (DEG) theorem, oxidation induction time is related to accumulated oxidation entropy and entropy transfer by mass flow to obtain characteristic degradation coefficients. These DEG coefficients are calibrated using available measured data from the literature and subsequently used to predict induction times at various temperatures. DEG elements—trajectories, planes, and domain—presented …

On The Use Of High-Frequency Surface Wave Oceanographic Research Radars As Bistatic Single-Frequency Oblique Ionospheric Sounders, Stephen R. Kaeppler, Ethan S. Miller, Daniel Cole, Teresa Updyke

CCPO Publications

We demonstrate that bistatic reception of high-frequency oceanographic radars can be used as single-frequency oblique ionospheric sounders. We develop methods that are agnostic of the software-defined radio system to estimate the group range from the bistatic observations. The group range observations are used to estimate the virtual height and equivalent vertical frequency at the midpoint of the oblique propagation path. Uncertainty estimates of the virtual height and equivalent vertical frequency are presented. We apply this analysis to observations collected from two experiments run at two locations in different years, but utilizing similar software-defined radio data collection systems. In the first …

Math Department 2021-2022 Newsletter, Mathematics Department

Mathematics Newsletter

Welcome to our annual Mathematics Department Newsletter. As we are slowly coming out of the pandemic, we were able to resume many of our normal events.

Evolutionary Kuramoto Dynamics, Elizabeth A. Tripp, Feng Fu, Scott D. Pauls

Mathematics Faculty Publications

Biological systems have a variety of time-keeping mechanisms ranging from molecular clocks within cells to a complex interconnected unit across an entire organism. The suprachiasmatic nucleus, comprising interconnected oscillatory neurons, serves as a master-clock in mammals. The ubiquity of such systems indicates an evolutionary benefit that outweighs the cost of establishing and maintaining them, but little is known about the process of evolutionary development. To begin to address this shortfall, we introduce and analyse a new evolutionary game theoretic framework modelling the behaviour and evolution of systems of coupled oscillators. Each oscillator is characterized by a pair of dynamic behavioural …

A Distinguished Subgroup Of Compact Abelian Groups, Dikran Dikranjan, Wayne Lewis, Peter Loth, Adolf Mader

Mathematics Faculty Publications

Here “group” means additive abelian group. A compact group G contains δ" role="presentation" style="box-sizing: border-box; max-height: none; display: inline; line-height: normal; font-size: 13.2px; text-align: left; word-spacing: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px; margin: 0px; position: relative;">δ–subgroups, that is, compact totally disconnected subgroups Δ" role="presentation" style="box-sizing: border-box; max-height: none; display: inline; line-height: normal; font-size: 13.2px; text-align: left; word-spacing: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px; margin: 0px; position: relative;">Δ such that G/Δ" role="presentation" style="box-sizing: …

Religious Violence And Twitter: Networks Of Knowledge, Empathy And Fascination, Samah Senbel, Carly Seigel, Emily Bryan

School of Computer Science & Engineering Faculty Publications

Twitter analysis through data mining, text analysis, and visualization, coupled with the application of actor-network-theory, reveals a coalition of heterogenous religious affiliations around grief and fascination. While religious violence has always existed, the prevalence of social media has led to an increase in the magnitude of discussions around the topic. This paper examines the different reactions on Twitter to violence targeting three religious communities: the 2015 Charleston Church shooting, the 2018 Pittsburgh Synagogue shooting, and the 2019 Christchurch Mosque shootings. The attacks were all perpetrated by white nationalists with firearms. By analyzing large Twitter datasets in response to the attacks, …