Physical Sciences and Mathematics Commons^™

A Full-Ocean-Depth Rated Modular Lander And Pressure-Retaining Sampler Capable Of Collecting Hadal-Endemic Microbes Under In Situ Conditions, Logan M. Peoples, Matthew Norenberg, David Price, Madeline Mcgoldrick, Mark Novotny, Alexander Bochdansky, Douglas H. Bartlett

OES Faculty Publications

The hadal zone remains one of the least studied environments because of its inaccessibility, in part because of hydrostatic pressures extending to 110 MPa. Few instruments are capable of sampling from such great depths. We have developed a full-ocean-depth-capable lander that can be fit with sampling packages for the collection of still images, video, motile megafauna, and hadal seawater. One payload includes a pressure-retaining sampler (PRS) able to maintain seawater samples under in situ pressure during recovery. We describe the technical specifications of the lander and the PRS and preliminary results from three deployments at depths in excess of 10,700 …

Detecting Special-Cause Variation 'Events' From Process Data Signatures, Timothy M. Young, Olga Khaliukova, Nicolas André, Alexander Petutschnigg, Timothy G. Rials, Chung-Hao Chen

Electrical & Computer Engineering Faculty Publications

The ability to detect the special-cause variation of incoming feedstocks from advanced sensor technology is invaluable to manufacturers. Many on-line sensors produce data signatures that require further off-line statistical processing for interpretation by operational personnel. However, early detection of changes in variation in incoming feedstocks may be imperative to promote early-stage preventive measures. A method is proposed in this applied study for developing control bands to quantify the variation of data signatures in the context of statistical process control (SPC). Control bands based on pointwise prediction intervals constructed from the Bonferroni Inequality and Bayesian smoothing splines are developed. Applications using …

Ieee Access Special Section Editorial: Wirelessly Powered Networks, And Technologies, Theofanis P. Raptis, Nuno B. Carvalho, Diego Masotti, Lei Shu, Cong Wang, Yuanyuan Yang

Computer Science Faculty Publications

Wireless Power Transfer (WPT) is, by definition, a process that occurs in any system where electrical energy is transmitted from a power source to a load without the connection of electrical conductors. WPT is the driving technology that will enable the next stage in the current consumer electronics revolution, including battery-less sensors, passive RF identification (RFID), passive wireless sensors, the Internet of Things and 5G, and machine-to-machine solutions. WPT-enabled devices can be powered by harvesting energy from the surroundings, including electromagnetic (EM) energy, leading to a new communication networks paradigm, the Wirelessly Powered Networks.

Drug Repositioning Based On Bounded Nuclear Norm Regularization, Mengyun Yang, Huimin Lao, Yaohang Li, Jianxin Wang

Computer Science Faculty Publications

Motivation: Computational drug repositioning is a cost-effective strategy to identify novel indications for existing drugs. Drug repositioning is often modeled as a recommendation system problem. Taking advantage of the known drug–disease associations, the objective of the recommendation system is to identify new treatments by filling out the unknown entries in the drug–disease association matrix, which is known as matrix completion. Underpinned by the fact that common molecular pathways contribute to many different diseases, the recommendation system assumes that the underlying latent factors determining drug–disease associations are highly correlated. In other words, the drug–disease matrix to be completed is low-rank. Accordingly, …

A Survey Of Attention Deficit Hyperactivity Disorder Identification Using Psychophysiological Data, S. De Silva, S. Dayarathna, G. Ariyarathne, D. Meedeniya, Sampath Jayarathna

Computer Science Faculty Publications

Attention Deficit Hyperactivity Disorder (ADHD) is one of the most common neurological disorders among children, that affects different areas in the brain that allows executing certain functionalities. This may lead to a variety of impairments such as difficulties in paying attention or focusing, controlling impulsive behaviours and overreacting. The continuous symptoms may have a severe impact in the long-term. This paper explores the ADHD identification studies using eye movement data and functional Magnetic Resonance Imaging (fMRI). This study discusses different machine learning techniques, existing models and analyses the existing literature. We have identified the current challenges and possible future directions …

Clinical Big Data And Deep Learning: Applications, Challenges, And Future Outlooks, Ying Yu, Liangliang Liu, Yaohang Li, Jianxin Wang

Computer Science Faculty Publications

The explosion of digital healthcare data has led to a surge of data-driven medical research based on machine learning. In recent years, as a powerful technique for big data, deep learning has gained a central position in machine learning circles for its great advantages in feature representation and pattern recognition. This article presents a comprehensive overview of studies that employ deep learning methods to deal with clinical data. Firstly, based on the analysis of the characteristics of clinical data, various types of clinical data (e.g., medical images, clinical notes, lab results, vital signs and demographic informatics) are discussed and details …

Multi-View Cluster Analysis With Incomplete Data To Understand Treatment Effects, Guoqing Chao, Jiangwen Sun, Jin Lu, An-Li Wang, Daniel D. Langleben, Chiang-Shan Li, Jinbo Bi

Computer Science Faculty Publications

Multi-view cluster analysis, as a popular granular computing method, aims to partition sample subjects into consistent clusters across different views in which the subjects are characterized. Frequently, data entries can be missing from some of the views. The latest multi-view co-clustering methods cannot effectively deal with incomplete data, especially when there are mixed patterns of missing values. We propose an enhanced formulation for a family of multi-view co-clustering methods to cope with the missing data problem by introducing an indicator matrix whose elements indicate which data entries are observed and assessing cluster validity only on observed entries. In comparison with …

Exposing Students To Stem Careers Through Hands-On Activities With Drones And Robots, Vukica M. Jovanović, George Mcleod, Thomas E. Alberts, Cynthia Tomovic, Otilia Popescu, Tysha Batts, Ms. Mary Louise Sandy

Engineering Technology Faculty Publications

Autonomous robots have been used in a variety of ways from collecting specimen in hazardous environments to space exploration. These robots can be found in various manufacturing systems as Autonomous Guided Vehicles (AGVs) to transport parts and assemblies throughout the manufacturing system. They have also been used as a vehicle to convey design thinking and other STEM-related concepts in mechanical engineering/mechanical engineering technology, electrical engineering/electrical engineering technology, computer science, and computer engineering. Various outreach events have included robotics based activities that engage students in building and programming autonomous robots for the purpose of achieving a specific task. These events are …

Comparison Of Observed And Simulated Drop Size Distributions From Large Eddy Simulations With Bin Microphysics, Mikael K. White, Patrick Y. Chuang, Orlando Ayala, Lian-Ping Wang, Graham Feingold

Engineering Technology Faculty Publications

Two case studies of marine stratocumulus (one nocturnal and drizzling, the other daytime and nonprecipitating) are simulated by the UCLA large-eddy simulation model with bin microphysics for comparison with aircraft in situ observations. A high-bin-resolution variant of the microphysics is implemented for closer comparison with cloud drop size distribution (DSD) observations and a turbulent collision–coalescence kernel to evaluate the role of turbulence on drizzle formation. Simulations agree well with observational constraints, reproducing observed thermodynamic profiles (i.e., liquid water potential temperature and total moisture mixing ratio) as well as liquid water path. Cloud drop number concentration and liquid water content profiles …

Reliability Estimation Of Reciprocating Seals Based On Multivariate Dependence Analysis And It's Experimental Validation, Chao Zhang, Rentong Chen, Shaoping Wang, Yujie Qian, Mileta M. Tomovic

Engineering Technology Faculty Publications

Accurate reliability estimation for reciprocating seals is of great significance due to their wide use in numerous engineering applications. This work proposes a reliability estimation method for reciprocating seals based on multivariate dependence analysis of different performance indicators. Degradation behavior corresponding to each performance indicator is first described by the Wiener process. Dependence among different performance indicators is then captured using D-vine copula, and a weight-based copula selection method is utilized to determine the optimal bivariate copula for each dependence relationship. A two-stage Bayesian method is used to estimate the parameters in the proposed model. Finally, a reciprocating seal degradation …

Spin Response Function For Spin Transparency Mode Of Rhic, V. S. Morozov, P. Adams, Y. S. Derbenev, Y. Filatov, H. Huang, A. M. Kondratenko, M. A. Kondratenko, F. Lin, F. Méot, V. Ptitsyn, W. B. Schmidke, Y. Zhang

Engineering Technology Faculty Publications

In the Spin Transparency (ST) mode of RHIC, the axes of its Siberian snakes are parallel. The spin tune in the ST mode is zero and the spin motion becomes degenerate: any spin direction repeats every particle turn. In contrast, the lattice of a conventional collider determines a unique stable periodic spin direction, so that the collider operates in the Preferred Spin (PS) mode. Contributions of perturbing magnetic fields to the spin resonance strengths in the PS mode are usually calculated using the spin response function. However, in that form, it is not applicable in the ST mode. This paper …

Sparsity Promoting Regularization For Effective Noise Suppression In Spect Image Reconstruction, Wei Zheng, Si Li, Andrzej Krol, C. Ross Schmidtlein, Xueying Zeng, Yuesheng Xu

Mathematics & Statistics Faculty Publications

The purpose of this research is to develop an advanced reconstruction method for low-count, hence high-noise, Single-Photon Emission Computed Tomography (SPECT) image reconstruction. It consists of a novel reconstruction model to suppress noise while conducting reconstruction and an efficient algorithm to solve the model. A novel regularizer is introduced as the nonconvex denoising term based on the approximate sparsity of the image under a geometric tight frame transform domain. The deblurring term is based on the negative log-likelihood of the SPECT data model. To solve the resulting nonconvex optimization problem a Preconditioned Fixed-point Proximity Algorithm (PFPA) is introduced. We prove …

Linear Difference Equations: Integrated- Environmentalist Approach For Teaching Mathematics, John A. Adam

Mathematics & Statistics Faculty Publications

There are at least eight known approaches for teaching mathematics that have been described in the literature. These include the Integrated Environmentalist, Formative, Social-Constructivist, Structuralist, New Maths, Problem Solving, Cultural, and Behaviorist approaches (Neyland, 1995). This paper presents some examples for teaching mathematics using the Integrated-Environmentalist approach, which is based on the assumption that the content knowledge in mathematics cannot be separated from the meaningful context from which it is taken, and in which it can be explained. In this approach for teaching mathematics the environment is used as the main source of mathematical meaning, stimulation to do creative work …

On Hybrid Temporal Basis Functions For Stable Numerical Solution Of Time Domain Boundary Integral Equations, Fang Q. Hu

Mathematics & Statistics Faculty Publications

Problems in unsteady aerodynamics and aeroacoustics can sometimes be formulated as integral equations, such as the boundary integral equations. Numerical discretization of integral equations in the time domain often leads to so-called March-On-in-Time (MOT) schemes. In the literature, the temporal basis functions used in MOT schemes have been largely limited to low-order shifted Lagrange basis functions. In order to evaluate the accuracy and effectiveness of the temporal basis functions, a Fourier analysis of the temporal interpolation schemes is carried out. Based on the Fourier analysis, the spectral resolutions of various temporal basis functions are quantified. It is argued that hybrid …

A Review: Thermal Stability Of Methylammonium Lead Halide Based Perovskite Solar Cells, Tanzila Tasnim Ava, Abdullah Al Mamun, Sylvain Marsillac, Gon Namkoong

Electrical & Computer Engineering Faculty Publications

Perovskite solar cells have achieved photo-conversion efficiencies greater than 20%, making them a promising candidate as an emerging solar cell technology. While perovskite solar cells are expected to eventually compete with existing silicon-based solar cells on the market, their long-term stability has become a major bottleneck. In particular, perovskite films are found to be very sensitive to external factors such as air, UV light, light soaking, thermal stress and others. Among these stressors, light, oxygen and moisture-induced degradation can be slowed by integrating barrier or interface layers within the device architecture. However, the most representative perovskite absorber material, CH_{3 …}

Charge Storage In Wo³ Polymorphs And Their Application As Supercapacitor Electrode Material, Vaibhav Lokhande, Abhishek Lokhande, Gon Namkoong, Jin Hyeok Kim, Taeksoo Ji

Electrical & Computer Engineering Faculty Publications

Tungsten oxide is a versatile material with different applications. It has many polymorphs with varying performance in energy storage application. We report simple and facile way to synthesize four phases of tungsten oxide from same precursor materials only by changing the pH and temperature values. Monoclinic, hexagonal, orthorhombic and tetragonal phase obtained, were analyzed and tested for supercapacitor application. The electrochemical analysis of four phases indicates that the hexagonal phase is best-suited electrode material for supercapacitor. The hexagonal phase exhibits higher specific capacitance (377.5 Fg^-1 at 2 mVs^-1), higher surface capacitive contribution (75%), better stability and rate …

The Effect Of Tube Geometry On The Chiral Plasma, S. Jin, D. Zou, X. Lu, Mounir Laroussi

Electrical & Computer Engineering Faculty Publications

A chiral plasma plume has recently been reported inside a circular quartz tube without the use of an external magnetic field. It is believed that the quartz tube plays an important role in the formation of the chiral plasma plume. In this paper, to better understand how this interesting structure is generated, the effect of the tube geometry on the chiral plasma is investigated. First, the effect of the thickness of the tube wall on the chiral plasma is investigated. It is interesting to find that a too thin or too thick tube wall is not favorable for generating the …

Computational Modeling Of Trust Factors Using Reinforcement Learning, C. M. Kuzio, A. Dinh, C. Stone, L. Vidyaratne, K. M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

As machine-learning algorithms continue to expand their scope and approach more ambiguous goals, they may be required to make decisions based on data that is often incomplete, imprecise, and uncertain. The capabilities of these models must, in turn, evolve to meet the increasingly complex challenges associated with the deployment and integration of intelligent systems into modern society. Historical variability in the performance of traditional machine-learning models in dynamic environments leads to ambiguity of trust in decisions made by such algorithms. Consequently, the objective of this work is to develop a novel computational model that effectively quantifies the reliability of autonomous …

Compact -300 Kv Dc Inverted Insulator Photogun With Biased Anode And Alkali-Antimonide Photocathode, C. Hernandez-Garcia, P. Adderley, B. Bullard, J. Benesch, J. Grames, J. Gubeli, F. Hannon, J. Hansknecht, J. Jordan, R. Kazimi, G. A. Krafft, M. A. Mamun, M. Poelker, M. L. Stutzman, R. Suleiman, M. Tiefenback, Y. Wang, S. Zhang, H. Baumgart, G. Palacios-Serrano, S. Wijethunga, J. Yoskowitz, C. A. Valerio Lizarraga, R. Montoya Soto, A. Canales Ramos

Electrical & Computer Engineering Faculty Publications

This contribution describes the latest milestones of a multiyear program to build and operate a compact −300  kV dc high voltage photogun with inverted insulator geometry and alkali-antimonide photocathodes. Photocathode thermal emittance measurements and quantum efficiency charge lifetime measurements at average current up to 4.5 mA are presented, as well as an innovative implementation of ion generation and tracking simulations to explain the benefits of a biased anode to repel beam line ions from the anode-cathode gap, to dramatically improve the operating lifetime of the photogun and eliminate the occurrence of micro-arc discharges.

The Role Of Data Analytics In Education: Possibilities & Limitations, Robert L. Moore

STEMPS Faculty Publications

In the last decade, we have seen dramatic increases in the integration of technology within education. It has now become commonplace for K-5 educators to apply learning management systems (LMS) in ways that were previously only seen in higher education contexts. Similarly, on the higher education side, we are seeing a significant increase in online learning evidenced by the growing number of for-profit online colleges and universities (Picciano, 2012). This chapter utilizes Khan’s Learning Framework (Khan, 2001, 2005) to explore the role data analytics can play in education by looking at the possibilities and limitations of analytics.

Transfer Learning Approach To Multiclass Classification Of Child Facial Expressions, Megan A. Witherow, Manar D. Samad, Khan M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

The classification of facial expression has been extensively studied using adult facial images which are not appropriate ground truths for classifying facial expressions in children. The state-of-the-art deep learning approaches have been successful in the classification of facial expressions in adults. A deep learning model may be better able to learn the subtle but important features underlying child facial expressions and improve upon the performance of traditional machine learning and feature extraction methods. However, unlike adult data, only a limited number of ground truth images exist for training and validating models for child facial expression classification and there is a …

Ignition Of A Plasma Discharge Inside An Electrodeless Chamber: Methods And Characteristics, Mounir Laroussi

Electrical & Computer Engineering Faculty Publications

In this paper the generation and diagnostics of a reduced pressure (300 mTorr to 3 Torr) plasma generated inside an electrodeless containment vessel/chamber are presented. The plasma is ignited by a guided ionization wave emitted by a low temperature pulsed plasma jet. The diagnostics techniques include Intensified Charge Coupled Device (ICCD) imaging, emission spectroscopy, and Langmuir probe. The reduced-pressure discharge parameters measured are the magnitude of the electric field, the plasma electron number density and temperature, and discharge expansion speed.

How Ceo Wealth Affects The Riskiness Of A Firm, Sonik Mandal, Charlie Swartz, Sanjib Guha, Carl B. Mcgowan Jr.

Finance Faculty Publications

The objective of this paper is to analyze the relationship between the ownership level of managers and the risk averse behavior of the firm. We measure the ownership level of the managers by the ratio of their ownership of the company relative to their total wealth for a sample of 69 individuals from the Forbes 400 list of the wealthiest individuals in the world for the period from 2001-11 using an unbalanced panel data analysis. The dependent variable is the Altman Z-score of each firm and we further test these relationships using financial leverage. The independent variables are delta and …

The Predictive Performance Of Objective Measures Of Physical Activity Derived From Accelerometry Data For 5-Year All-Cause Mortality In Older Adults: National Health And Nutritional Examination Survey 2003-2006, Ekaterina Smirnova, Andrew Leroux, Quy Cao, Lucia Tabacu, Vadim Zipunnikov, Ciprian Crainiceanu, Jacek Urbanek

Mathematics & Statistics Faculty Publications

Background: Declining physical activity (PA) is a hallmark of aging. Wearable technology provides reliable measures of the frequency, duration, intensity, and timing of PA. Accelerometry-derived measures of PA are compared to established predictors of 5-year all-cause mortality in older adults in terms of individual, relative, and combined predictive performance.

Methods: Participants between 50 and 85 years old from the 2003-2006 National Health and Nutritional Examination Survey (NHANES, n = 2978) wore a hip-worn accelerometer in the free-living environment for up to 7 days. A total of 33 predictors of 5-year all-cause mortality (number of events = 297), including 20 measures …

Towards Comprehensive Observing And Modeling Systems For Monitoring And Predicting Regional To Coastal Sea Level, Rui M. Ponte, Mark Carson, Mauro Cirano, Catia M. Domingues, Tal Ezer, Xuebin Zhang

CCPO Publications

A major challenge for managing impacts and implementing effective mitigation and adaptation strategies for coastal zones affected by future sea level (SL) rise is our very limited capacity to predict SL change on coastal scales, over various timescales. Predicting coastal SL requires the ability to monitor and simulate a multitude of physical processes affecting SL, from local effects of wind waves and river runoff to remote influences of the large-scale ocean circulation on the coast. Here we assess our current understanding of the causes of coastal SL variability on seasonal to multi-decadal timescales, including geodetic, oceanographic and atmospheric aspects of …

Impacts Of Basin-Scale Climate Modes On Coastal Sea Level: A Review, Weiqing Han, Detlef Stammer, Philip Thompson, Tal Ezer, Hindu Palanisamy, Xuebin Zhang, Catia M. Domingues, Lei Zhang, Dongliang Yuan

CCPO Publications

Global sea level rise (SLR) associated with a warming climate exerts significant stress on coastal societies and low-lying island regions. The rates of coastal SLR observed in the past few decades, however, have large spatial and temporal differences from the global mean, which to a large part have been attributed to basin-scale climate modes. In this paper, we review our current state of knowledge about climate modes’ impacts on coastal sea level variability from interannual-to-multidecadal timescales. Relevant climate modes, their impacts and associated driving mechanisms through both remote and local processes are elaborated separately for the Pacific, Indian and Atlantic …

Automated Trading Systems Statistical And Machine Learning Methods And Hardware Implementation: A Survey, Boming Huang, Yuziang Huan, Li Da Xu, Lirong Zheng, Zhuo Zou

Information Technology & Decision Sciences Faculty Publications

Automated trading, which is also known as algorithmic trading, is a method of using a predesigned computer program to submit a large number of trading orders to an exchange. It is substantially a real-time decision-making system which is under the scope of Enterprise Information System (EIS). With the rapid development of telecommunication and computer technology, the mechanisms underlying automated trading systems have become increasingly diversified. Considerable effort has been exerted by both academia and trading firms towards mining potential factors that may generate significantly higher profits. In this paper, we review studies on trading systems built using various methods and …

Experimental Investigation On The Effects Of Website Aesthetics On User Performance In Different Virtual Tasks, Meinald T. Thielsch, Russell Haines, Leonie Flacke

Information Technology & Decision Sciences Faculty Publications

In Human-Computer Interaction research, the positive effect of aesthetics on users' subjective impressions and reactions is well-accepted. However, results regarding the influence of interface aesthetics on a user's individual performance as an objective outcome are very mixed, yet of urgent interest due to the proceeding of digitalization. In this web-based experiment (N = 331), the effect of interface aesthetics on individual performance considering three different types of tasks (search, creative, and transfer tasks) is investigated. The tasks were presented on an either aesthetic or unaesthetic website, which differed significantly in subjective aesthetics. Goal orientation (learning versus performance goals) was included …

Challenges With Large Transverse Momentum In Semi-Inclusive Deeply Inelastic Scattering, J. O. Gonzalez-Hernandez, T. C. Rogers, N. Sato, B. Wang

Physics Faculty Publications

We survey the current phenomenological status of semi-inclusive deeply inelastic scattering at moderate hard scales and in the limit of very large transverse momentum. As the transverse momentum becomes comparable to or larger than the overall hard scale, the differential cross sections should be calculable with fixed order perturbative QCD (pQCD) methods, while small transverse momentum (transverse-momentum-dependent factorization) approximations should eventually break down. We find large disagreement between HERMES and COMPASS data and fixed order calculations done with modern parton densities, even in regions of kinematics where such calculations should be expected to be very accurate. Possible interpretations are suggested.

Question 1: Clock Variation; Question 2: Recycling Coffee Pods, Larry Weinstein

Physics Faculty Publications

The article presents questions and answers regarding the impact of gravity on pendulum clocks and the recycling of coffee pods.