Digital Commons Network^™

Is 2020: Developing An Acm/Ais Information Systems Model Curriculum For Undergraduate Programs, Paul M. Leidig, Hannu Salmela, Greg Anderson, Jeff Babb, Lesley Gardner, Jay F. Nunamaker Jr., Brenda Scholtz, Venky Shankararaman, Raja Sooriamurthi, Mark Thouin, Carina De Villiers

Faculty Publications

The Association of Computing Machinery (ACM) and the Association for Information Systems (AIS) engaged in a project to revise the Information Systems Curriculum. The IS2010 model curriculum has been widely used for nearly a decade. However, its value may be decreasing as new approaches to model curricula have been introduced. The AIS and ACM established an exploratory taskforce which found there have been substantial changes in the IS field, and that current graduates’ technical skills do not appear to meet industry needs. The IS discipline must express its core in terms of a standard curriculum that meet stakeholder demands. A …

Green Talent Management And Turnover Intention: The Roles Of Leader Stara Competence And Digital Task Interdependence, Samuel Ogbeibu, Charbel Jose Chiappetta Jabbour, John Burgess, James Gaskin, Douglas W.S. Renwick

Faculty Publications

Purpose – Congruent with the world-wide call to combat global warming concerns within the context of advancements in smart technology, artificial intelligence, robotics, algorithms (STARA), and digitalisation, organisational leaders are being pressured to ensure that talented employees are effectively managed (nurtured and retained) to curb the potential risk of staff turnover. By managing such talent(s), organisations may be able to not only retain them, but consequently foster environmental sustainability too. Equally, recent debates encourage the need for teams to work digitally and interdependently on set tasks, and for leaders to cultivate competencies fundamental to STARA, as this may further help …

Task Adherence: An Agentic Perspective On Task-Focused Dedication In An Interrupting Work Environment, Tanner Skousen, Justin Ames, James Gaskin

Faculty Publications

Purpose – Knowledge workers live and work in a technology-enabled, push-notification world full of interruptions that create information overload, often requiring these workers to utilize task switching as a mechanism to meet multiple competing tasks’ demands. Previous research has examined both the positive and, more often, negative effects from interruptions and task switching on knowledge workers’ performance. However, this paper aims to examine knowledge workers’ agentic approach to managing interruption signals and consequent task switching to remain dedicated to the task at hand.

Design/methodology/approach – Using an inductive grounded theory approach, we analyzed data from semi-structured interviews with knowledge workers …

The Reliability Of The Physical Evidence At The Battle Of The Little Big Horn: Can The Physical Evidence Found Provide An Accurate Picture?, Albert Winkler Dr.

Faculty Publications

Often, artifacts, most importantly bullets and spent shell casings, found at the location of the Battle of the Little Big Horn have been used independently of other sources to make or refute certain theories on the encounter. Books and articles based on these finds have advanced many arguments on troop dispositions, types of weapons employed, army movements, the locations of the fighting, and the duration and intensity of combat. Yet many of these studies have not adequately addressed the question of the validity of this physical evidence. The purpose of the this article is to summarize earlier arguments on the …

Swill-Tac: Skill-Oriented Dynamic Task Allocation With Willingness For Complex Job In Crowdsourcing, Riya Samanta, Soumya K. Ghosh, Sajal K. Das

Computer Science Faculty Research & Creative Works

Allocating tasks to the best-fit candidates is a classical problem in crowdsourcing (CS). Most of the existing approaches assume that the task and candidate knowledge is known in advance and ignore the effect of enrolled candidates' willingness on the CS system's selection decision. For instance, an unwilling candidate assigned to a task may quit without completing it, thus depreciating the utility of the CS platform. In practice, a task or candidate may arrive or leave the CS system dynamically. Moreover, a complex task may be broken into smaller sub-tasks, each requiring a variety of computations and expertise. To overcome these …

Detection Dns Tunneling Botnets, Bohdan Savenko, Sergii Lysenko, Kira Bobrovnikova, Oleg Savenko, George Markowsky

Computer Science Faculty Research & Creative Works

Botnets are often used in cyberattacks on network services and individual users, so the ability to detect botnets is very important. Botnets use DNS tunneling to send malicious command-and-control (CC) commands to victims' hosts. Unfortunately, DNS tunneling attacks are very hard to detect. The paper presents a new approach for DNS tunneling botnet detection, which considers all the features and architectural characteristics of botnets. The technique described in this paper is highly efficient at detecting DNS tunneling attacks.

Efficient Route Selection For Drone-Based Delivery Under Time-Varying Dynamics, Arindam Khanda, Federico Coro, Francesco Betti Sorbelli, Cristina M. Pinotti, Sajal K. Das

Computer Science Faculty Research & Creative Works

The use of drones can be a valuable solution for the problem of delivering goods for many reasons. In fact, they can be efficiently employed in time-critical situations when there is a traffic jam on the roads, to serve customers in hard-to-reach places, or simply to expand the business. However, due to limited battery capacities and the fact that drones can serve a single customer at a time, a drone-based delivery system (DBDS) aims to minimize the drones' energy usage for completing a route from the depot to the customer and go back to the depot for new deliveries. In …

Improving Lossy Compression For Sz By Exploring The Best-Fit Lossless Compression Techniques, Jinyang Liu, Sihuan Li, Sheng Di, Xin Liang, Kai Zhao, Dingwen Tao, Zizhong Chen, Franck Cappello

Computer Science Faculty Research & Creative Works

In the past decades, various lossy compressors have been studied broadly due to the ever-increasing volume of data being produced by today's scientific applications. SZ has been one of the best error-bounded lossy compressors ever raised, and it has a flexible framework that includes four adjustable steps: prediction, quantization, variable-length encoding, and lossless compression. In this paper, we improve the lossy compression performances of the SZ compression model by exploring different existing lossless compression techniques using the Squash data compression benchmark. Specifically, we first characterize the bytes outputted by the first three steps in SZ, then we investigate the best …

Optimizing Error-Bounded Lossy Compression For Scientific Data On Gpus, Jiannan Tian, Sheng Di, Xiaodong Yu, Cody Rivera, Kai Zhao, Sian Jin, Yunhe Feng, Xin Liang, Dingwen Tao, Franck Cappello

Computer Science Faculty Research & Creative Works

Error-bounded lossy compression is a critical technique for significantly reducing scientific data volumes. With ever-emerging heterogeneous high-performance computing (HPC) architecture, GPU-accelerated error-bounded compressors (such as CUSZ and cuZFP) have been developed. However, they suffer from either low performance or low compression ratios. To this end, we propose CUSZ+ to target both high compression ratios and throughputs. We identify that data sparsity and data smoothness are key factors for high compression throughputs. Our key contributions in this work are fourfold: (1) We propose an efficient compression workflow to adaptively perform run-length encoding and/or variable-length encoding. (2) We derive Lorenzo reconstruction in …

User Guide For Dust Modeling Using Cmaq 5.3.1 And Wrf 4.2.1, Zachary D. Lawless, Ariel S. Cable, Cameron B. Van Dyke, Bradley R. Adams

Faculty Publications

Researchers at Brigham Young University (BYU) have developed a software framework for modeling dust emission and transport using the Community Multiscale Air Quality (CMAQ) modeling system in conjunction with the Weather Research and Forecasting (WRF) model and other utility programs. This framework uses meteorological data, land use data, and soil properties to predict dust concentrations for a specified area. This User Guide describes the start-to-finish process required to install and utilize relevant software to calculate and visualize dust concentrations. Note that the examples and figures provided in the guide are specific to Utah in the western United States, where this …

An Editing Process For Blind Or Visually Impaired Editors, Matt Baker, E.M. Nightingale, Suzy Bills

Faculty Publications

In the US, hundreds of thousands of individuals with visual disabilities work in occupations that typically entail editing text. Editing technologies for blind or visually impaired people have been analyzed by researchers for usability, accessibility, and feasibility. However, a tutorial is needed to provide blind or visually impaired workers with information on how to use these technologies. Key concepts: Technologies that blind or visually impaired individuals can use for editing text present challenges. Such challenges include the lack of usability in word processors’ text-editing features, navigational and sense-making issues with screen readers, limited text displayed by refreshable braille displays, and …

Quality-Of-Service Architecture For Cloud Computing Networking, Ken R. Owens Jr., Steve Eugene Watkins

Electrical and Computer Engineering Faculty Research & Creative Works

Quality-of-service (QoS) performance is an important consideration for real-time and high-priority traffic on internet protocol (IP) networks. Service differentiation can provide a more efficient and customer-oriented internet. The “best-effort” internet models in use today cannot provide guarantees or service differentiation for end-to-end individual and aggregate data flows. Hardware-based models and software-based models do not completely address the total service-enabled solution. We propose a hybrid architecture that combines software and hardware features to handle network traffic with diverse QoS requirements. Since cloud providers leverage IP networks today, the model is based on a systems engineering approach that uses cloud computing technologies. …

The Effects Of Pornography On Unethical Behavior In Business, Nathan W. Mecham, Melissa F. Lewis-Western, David A. Wood

Faculty Publications

Pornography is no longer an activity confined to a small group of individuals or the privacy of one’s home. Rather, it has permeated modern culture, including the work environment. Given the pervasive nature of pornography, we study how viewing pornography affects unethical behavior at work. Using survey data from a sample that approximates a nationally representative sample in terms of demographics, we find a positive correlation between viewing pornography and intended unethical behavior. We then conduct an experiment to provide causal evidence. The experiment confirms the survey—consuming pornography causes individuals to be less ethical. We find that this relationship is …

Design Of Dual-Band Decoupling Network For Two Antennas, Min Li, Lijun Jiang, Kwan Lawrence Yeung

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents a dual-band decoupling network for two antennas. Design formulas are derived with systematic design procedures. Two benchmarks are presented to elaborate on the design procedure. Results show that the network offers impedance matching, high isolation, and high efficiency at both frequencies, verifying the proposed concept and theory.

Multi-Polarization Phase Retrieval In Near Field Far-Field Transformation, Yuan Ping, Lijun Jiang

Electrical and Computer Engineering Faculty Research & Creative Works

In near field far-field transformation (NFFFT), accurate recovery of the current distribution is subjected to the phase measurement. Phase retrieval is an alternative way to recover the current distribution by utilizing the magnitude-only near field sampling data. In phase retrieval algorithm, sufficient independent measurement data are required. Multi-polarization algorithm is employed to generate different current distribution, then, obtaining more independent near field data. Experimental validations of a numeric examples show its potentialities and interest.

Model Computation With Second-Order Radiative Transfer Equation For Snow Medium Using Coupled Finite Element Method And Method Of Moment And Relaxed Hierarchical Equivalent Source Algorithm, Hamsalekha A. Kumaresan, H. T. Ewe, Gobi Vetharatnam, Li (Lijun) Jun Jiang

Electrical and Computer Engineering Faculty Research & Creative Works

Active microwave remote sensing is essential to monitor the conditions of the environment by analyzing the microwave returns from the earth terrain. Various Computational Electromagnetics (CEM) techniques are implemented to study the backscattering coefficient of numerous earth terrains such as vegetation and snow medium. In this paper, a theoretical model based on second order radiative transfer equation is investigated by incorporating two computational methods which are known as coupled Finite Element Method (FEM) and Method of Moment (MoM), and Relaxed Hierarchical Equivalent Source Algorithm (RHESA). These theoretical models consider three shapes of scatterers which can be used to represent the …

Hybrid Beamforming With Deep Learning For Large-Scale Antenna Arrays, Rentao Hu, Lijun Jiang, Ping Li

Electrical and Computer Engineering Faculty Research & Creative Works

The emergence of highly directional beamforming technology makes millimeter wave frequency band communication possible in future wireless communication networks. Based on the multipath characteristics of millimeter wave frequency communication, a high-precision multipath channel estimation algorithm based on signal subspace is proposed. In the mobile terminal, an iterative heuristic radiofrequency combination algorithm based on spatial points is proposed. The analog precoding at the base station uses deep learning to accelerate the calculation, and then the multi-user communication is modeled to design the digital precoding. The simulation results show that the multi-channel estimation algorithm can estimate 4 paths with an error of …

Review On Resistive Switching Mechanisms Of Bio-Organic Thin Film For Non-Volatile Memory Application, Kuan Yew Cheong, Ilias Ait Tayeb, Feng Zhao, Jafri Malin Abdullah

Electrical and Computer Engineering Faculty Research & Creative Works

Bio-organic, as one of the sustainable and bioresorbable materials, has been used as an active thin film in producing resistive switching random access memory (RRAM) due to its specialized properties. This type of nonvolatile memory consists of a simple unit structure with the processed and solidified bio-organic-based thin film sandwiched between two electrodes. Its memory characteristics are significantly affected by the resistive-switching mechanism. However, to date, the reported mechanisms are very diverse and scattered, and to our best knowledge, there is no literature that reviewed comprehensively the mechanisms of resistive switching in bio-organic-based thin films. Therefore, the objective of this …

Package Power Distribution Current Density In Applications With Large Transient Currents, Matthew Doyle, Wiren D. Becker, Matteo Cocchini, Kyle Schoneck, Samuel Connor, Layne Berge, Siqi Bai, James L. Drewniak

Electrical and Computer Engineering Faculty Research & Creative Works

A method to model, measure, and characterize a high-transient current in an electrical packaging solution is described herein. These methods help overcome the challenge of generating model to hardware correlation in high current applications. A specialized test platform is developed and used to characterize current density in test hardware. The measurements are used to characterize a custom power distribution network and verify validity of current density predictions. This data is critical in high-current applications for finding and measuring current density through plane pinch points that can cause early failures in the field due to electromigration and delamination.

Automated Cervical Digitized Histology Whole-Slide Image Analysis Toolbox, Sudhir Sornapudi, Ravitej Addanki, R. Joe Stanley, William V. Stoecker, Rodney Long, Rosemary Zuna, Shellaine R. Frazier, Sameer Antani

Electrical and Computer Engineering Faculty Research & Creative Works

Background: Cervical intraepithelial neoplasia (CIN) is regarded as a potential precancerous state of the uterine cervix. Timely and appropriate early treatment of CIN can help reduce cervical cancer mortality. Accurate estimation of CIN grade correlated with human papillomavirus type, which is the primary cause of the disease, helps determine the patient's risk for developing the disease. Colposcopy is used to select women for biopsy. Expert pathologists examine the biopsied cervical epithelial tissue under a microscope. The examination can take a long time and is prone to error and often results in high inter-and intra-observer variability in outcomes. Methodology: We propose …

High-Frequency Modeling Of Permanent Magnet Synchronous Motor Considering Internal Imbalances, Yuandong Guo, Muqi Ouyang, Zhifei Xu, Minho Kim, Junesang Lee, Jungrae Ha, Hyewon Lee, Sangwon Yun, Jun Fan, Hongseok Kim

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, an accurate high-frequency modeling methodology for a permanent magnet synchronous motor (PMSM) in a vehicular electrical braking system is presented, which is suitable for analyzing various electromagnetic interference problems caused by a motor drive system. The proposed modeling approach is established according to the vector fitting technique and based on the S-parameter measurements of the PMSM. The equivalent circuit model of the PMSM converted from a measured S-parameter matrix can better describe the impedance characteristics of the three-phase PMSM under study compared to the existing equivalent circuit models because the imbalances inside the motor are taken into …

Nnbmss: A Novel And Fast Method For Model Structure Selection, Amaury Lendasse, Kallin Khan, Edward Ratner

Engineering Management and Systems Engineering Faculty Research & Creative Works

In This Paper, We Present a New Method to Perform Model Structure Selection. This Proposed Method Can Be Used to Select the Complexity of Any Continuous Regression Method. We Also Present an Asymptotic Mathematical Proof of the Proposed Method and the New Method is Illustrated on a Benchmark. Compared to the Well-Known 10-Fold Cross-Validation, the Computational Time Associated to Our New Method is Approximately Divided by a Factor 8 as Illustrated on the Benchmark.

A Multi-Elm Model For Incomplete Data, Baichuan Chi, Amaury Lendasse, Edward Ratner, Renjie Hu

Engineering Management and Systems Engineering Faculty Research & Creative Works

This Paper Presents a Novel Model of Extreme Learning Machines (Elms) for Incomplete Data. Elms Are Fast Accurate Randomized Neural Networks. Nevertheless, Elm Can Only Be Applied on the Complete Dataset. Therefore, a Novel Multi-Elm Model for Incomplete Data is Proposed, Consisting of Multiple Secondary Elms and One Primary Elm. the Secondary Elms Are Approximating the Primary Elm's Hidden Neurons' Outputs for the Data with Missing Values. as Summarized in the Experimental Section, This Model Can Be Applied on Data with Any Missing Patterns, without using Imputations and Can Outperform the Traditional Imputation Methods within a Reasonable Fraction of Missing …

Machine Learning For Measuring And Analyzing Online Social Communications, Chris Bronk, Amaury Lendasse, Peggy Lindner, Dan S. Wallach, Barbara Hammer

Engineering Management and Systems Engineering Faculty Research & Creative Works

In This Paper, We Propose a Framework for Application of a Novel Machine Learning-Based System for Analyzing Online Social Communications. as an Example, We Are Targeting Anti-Semitic Graphical Memes Posted to Social Media. We Presented Very Promising Preliminary Results on a Facebook Dataset that Consists of a Total of 10000 Labeled Memes. We Can Conclude that Machine Learning Will Soon Be Able to Successfully Analyze and Monitor Complex Social Communications.

Small-And Large-Scale Strain Sensing Using Frequency Selective Surfaces, Swathi Muthyala Ramesh, Kristen M. Donnell

Electrical and Computer Engineering Faculty Research & Creative Works

Frequency selective surfaces (FSSs) are arrays of conductive elements or patches that have specific reflection and transmission responses. In this work, an FSS sensor designed to measure small (0% - 0.5%) and large (0% - 5%) scale strain is presented. The proposed unit cell of the sensor consists of two passive dipoles (of different dimensions) arranged normal to one another. This was done to reduce the error of small-scale strain on the large-scale strain measurement, and vice versa. Strain sensing is achieved by monitoring the change in the resonant frequencies of the two dipoles using an interrogating signal linearly polarized …

Multidimensional Extensions To Generalized Averaged Models For Multi-Frequency-Excited Dynamic Systems, Kartikeya Jayadurga Prasad Veeramraju, Jonathan W. Kimball

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a novel Harmonic Axis Decoupling (HAD) method is proposed for extending the capabilities of the Generalized Averaged Modeling (GAM) technique. The conventional GAM technique is first revisited, and the problems encountered in the multiplication of two Double Fourier Series (DFS) signals in the time domain are investigated. The method of translating Fourier vectors to Discrete Fourier Images (DFI) in the frequency plane is proposed, and the ramifications of this conversion on DFS product terms in the time domain are investigated. The two-dimensional DFI convolution technique resulting from HAD is used for the dynamic modeling of power converters …

Novel Transformer With Variable Leakage And Magnetizing Inductances, Angshuman Sharma, Jonathan W. Kimball

Electrical and Computer Engineering Faculty Research & Creative Works

This paper introduces the concept of a novel variable inductance transformer (VIT) whose leakage and magnetizing inductances can be varied dynamically and independently to aid the advancement of research in isolated power electronic converters. In this transformer, the leakage inductance can be varied by varying the length of overlap between the primary and secondary windings, while the magnetizing inductance can be varied by varying the air gap between the core legs. Individual controls for the two inductances ensure that one can be varied independent of the other, as needed to satisfy different power conversion objectives. In this paper, the analytical …

Developing Optimal Energy Arbitrage Strategy For Energy Storage System Using Reinforcement Learning, Haotian Chen, Rui Bo, Waqas Ur Rehman

Electrical and Computer Engineering Faculty Research & Creative Works

This paper introduced a reinforcement learning based method for developing operational strategy for an energy storage system (ESS) to achieve energy arbitrage in a microgrid or power system. In comparison to conventional energy resources such as gas turbines units or wind plant, it is more challenging to design an optimal strategy for ESS because of their limited energy and the impact of future electricity prices. The energy arbitrage problem also presents unique challenges than the economic dispatch problem because the ESS owner has very limited information of the system compared to those available to grid operators. In this work, reinforcement …

On The Effect Of Design Parameters On Fringing Fields Of A Loop-Based Fss, Swathi Muthyala Ramesh, Mahboobeh Mahmoodi, Kristen M. Donnell

Electrical and Computer Engineering Faculty Research & Creative Works

Frequency selective surfaces (FSSs) are periodic arrays of conductive elements that act as spatial filters of electromagnetic energy. FSSs have found recent application as sensors, filters, reflectors and radomes, amongst others. Often miniaturization techniques are used to improve the stability of the FSS to incident angle (of the excitation). However, due to the type of coupling (internal/self-vs. external/mutual with adjacent elements), some designs are more responsive to miniaturization techniques than others. Hence, this paper quantifies the effect of the ratios of inter-element spacing-to-substrate thickness (S/h) and side length-to-substrate thickness (SL/h) on fringing fields (and hence coupling and potential for miniaturization) …

Using Gated Recurrent Units For Selective Harmonic Current Mitigation-Pwm In Grid-Tied Cascaded H-Bridge Converters, Morteza Dabbaghjamanesh, Amirhossein Moeini, Jonathan Kimball, Jie Zhang

Electrical and Computer Engineering Faculty Research & Creative Works

Grid-tied converters become more popular for electric vehicle, renewable energy, and energy storage systems applications. Different modulation techniques such as low-frequency (e.g., selective harmonic elimination-PWM, selective harmonic mitigation-PWM, and selective harmonic current mitigation-PWM (SHCM-PWM)) and high-frequency modulation techniques (e.g., phase shift-PWM and space vector modulation) are used in the literature for grid-tied converters. Low-frequency modulation techniques have a high-efficiency due to the low-switching power losses. One of the main challenges of low-frequency modulation techniques such as SHCM-PWM is how to implement the proposed technique in real-time, due to the transcendental Fourier equations of SHCM-PWM. In this paper, a deep learning …