Digital Commons Network^™

Factors Influencing Adoption Of Hr Analytics By Individuals And Organizations, Weam Tunsi, Rana Abu Tayyoun, Mohammed Othman, Yahya Saleh, Ramiz Assaf, Ali Bakir

Information Sciences Letters

In this paper, we explore the factors influencing the adoption of Human Resources (HR) Analytics by HR professionals in large Palestinian enterprises. A convenience sample of 151 HR professionals from the service and manufacturing sectors participated in a questionnaire-based survey. The study identified self-efficacy, performance expectancy, effort expectancy, resource availability, quantitative self-efficacy, data availability, and social influence as the most significant factors positively influencing individual acceptance and adoption of HR Analytics. Fear appeals, on the other hand, had no significant effect. The study proposes a conceptual framework to help policymakers in organizations understand how to adopt HR Analytics.

Eliminating Adversarial Noise Via Information Discard And Robust Representation Restoration, Dawei Zhou, Yukun Chen, Nannan Wang, Decheng Liu, Xinbo Gao, Tongliang Liu

Machine Learning Faculty Publications

Deep neural networks (DNNs) are vulnerable to adversarial noise. Denoising model-based defense is a major protection strategy. However, denoising models may fail and induce negative effects in fully white-box scenarios. In this work, we start from the latent inherent properties of adversarial samples to break the limitations. Unlike solely learning a mapping from adversarial samples to natural samples, we aim to achieve denoising by destroying the spatial characteristics of adversarial noise and preserving the robust features of natural information. Motivated by this, we propose a defense based on information discard and robust representation restoration. Our method utilize complementary masks to …

Which Is Better For Learning With Noisy Labels: The Semi-Supervised Method Or Modeling Label Noise?, Yu Yao, Mingming Gong, Yuxuan Du, Jun Yu, Bo Han, Kun Zhang, Tongliang Liu

Machine Learning Faculty Publications

In real life, accurately annotating large-scale datasets is sometimes difficult. Datasets used for training deep learning models are likely to contain label noise. To make use of the dataset containing label noise, two typical methods have been proposed. One is to employ the semi-supervised method by exploiting labeled confident examples and unlabeled unconfident examples. The other one is to model label noise and design statistically consistent classifiers. A natural question remains unsolved: which one should be used for a specific real-world application? In this paper, we answer the question from the perspective of causal data generative process. Specifically, the performance …

Adults' Recollections And Reflections On The Impacts Of Grade Retention, April Dockery

Curriculum and Instruction (Ed.D.) Dissertations

This qualitative study chronicles the experiences of retention as told by adults who experienced retention. Through criterion sampling and snowball sampling, ten participants were identified and interviewed to learn more about their experiences with retention. Through one-on-one interviews, the researcher sought to examine what characterizes the experiences and responses of adults who were retained during their K-12 academic career. Their in-depth responses revealed participants’ perceptions of retention and the effects that it produced in their lives. This study humanized the data by allowing participants to tell an account of retention that coincides with past research. The findings of this study …

Waterbody Size Predicts Bank- And Boat-Angler Efforts, Derek S. Kane, Kevin L. Pope, Keith D. Koupal, Mark A. Pegg, Christopher J. Chizinski, Mark A. Kaemingk

Nebraska Cooperative Fish and Wildlife Research Unit: Staff Publications

Bank- and boat-angler efforts are logistically difficult and costly to estimate, preventing landscape-scale estimates that are required to address current and future challenges (e.g., climate change, invasive species) for inland recreational fisheries. Using a large Nebraska, USA, recreational fishery dataset (N = 67 waterbodies), we demonstrate that waterbody size can be used to predict bank- and boat-angler efforts across a heterogeneous landscape of extra small (< 104 ha) and large (> 647 ha) waterbodies. Bank and boat anglers respond to waterbody size, however these relationships appear to be unique between the two angler types. Boat-angler efforts increased as a function of waterbody size, whereas bank-angler …

Advancing Our Understanding Of Martian Proton Aurora Through A Coordinated Multi-Model Comparison Campaign, Andrea C. G. Hughes, Michael Scott Chaffin, Edwin J. Mierkiewicz, Justin Deighan, Rebecca Jolitz, Esa Kallio, Guillaume Gronof, Valery I. Shematovich, Dmitry Bisikalo, Cyril L. Simon Wedlund, Jasper S. Halekas, Nicholas M. Schneider, Birgit Ritter, Zachary Girazian, Sonal Jain, Jean-Claude M. C. G´Erard, Bradley Michael Hegyi

Publications

Proton aurora are the most commonly observed yet least studied type of aurora at Mars. In order to better understand the physics and driving processes of Martian proton aurora, we undertake a multi-model comparison campaign. We compare results from four different proton/hydrogen precipitation models with unique abilities to represent Martian proton aurora: Jolitz model (3-D Monte Carlo), Kallio model (3-D Monte Carlo), Bisikalo/Shematovich et al. model (1-D kinetic Monte Carlo), and Gronoff et al. model (1-D kinetic). This campaign is divided into two steps: an inter-model comparison and a data-model comparison. The inter-model comparison entails modeling five different representative cases …

She Is An Expert In This Research Field: The Signal Of Recent Publications' Relevance, Gil Zeevi, Osnat Mokryn

Northeast Journal of Complex Systems (NEJCS)

Assessing the expertise of researchers has garnered increased interest recently. This heightened focus arises from the growing emphasis on interdisciplinary science and the subsequent need to form expert teams. When forming these teams, the coordinators need to assess expertise in fields that are often very different from theirs. The conventional reliance on signals of success, prestige, and academic impact can unintentionally perpetuate biases within the assessment process. This traditional approach favors senior researchers and those affiliated with prestigious institutions, potentially overlooking talented individuals from underrepresented backgrounds or institutions. This paper addresses the challenge of determining expertise by proposing a methodology …

A Perspective Note On Μ_N Σ Baire’S Space, N. Raksha Ben, G. Hari Siva Annam, G. Helen Rajapushpam

Neutrosophic Systems with Applications

This paper presents an introduction to many novel types of sets, including μN strongly dense sets, μN strongly nowhere dense sets, μN strongly first category sets, and μN strongly nowhere residual sets. The features of these sets are briefly elucidated. In addition, by the use of these techniques, we have successfully obtained the highly Baire space μN, and it is imperative to elucidate its inherent features.

Descriptive Norms Caused Increases In Mask Wearing During The Covid-19 Pandemic, Samantha L. Heiman, Scott Claessens, Jessica D. Ayers, Diego Guevara Beltrán, Andrew Van Horn, Edward R. Hirt, Athena Aktipis, Peter M. Todd

Psychological Sciences Faculty Publications and Presentations

Human sociality is governed by two types of social norms: injunctive norms, which prescribe what people ought to do, and descriptive norms, which reflect what people actually do. The process by which these norms emerge and their causal influences on cooperative behavior over time are not well understood. Here, we study these questions through social norms influencing mask wearing during the COVID-19 pandemic. Leveraging 2 years of data from the United States (18 time points; n = 915), we tracked mask wearing and perceived injunctive and descriptive mask wearing norms as the pandemic unfolded. Longitudinal trends suggested that norms and …

Architectura Transtopica: Totems Of A Journeyman, Ioannis Galanopoulos Papavasileiou

All Works

The project Architectura Transtopica: Totems of a Journeyman argues in favour of using and interpreting fixed architectural structures as metaphors and symbols of expatriation. The primary inquiry of this paper is to consider how autobiographic re-enactments of lived experiences with architecture, triggered by non-country specific places, illustrate one’s life journey. Building on studies that are at the intersection of social and cultural studies, humanistic geography, evolutionary ecology, anthropology, art and architecture (Alahdadi, 2018; Avci et al., 2017; Kunz, 2016; Martin et al., 2015; Cotton, 2015; Mathur, 2011; Cresswell, 2006; Relph, 1977), I argue here that producing creative parallels of expatriation …

A Perspective Note On Μ_N Σ Baire’S Space, N. Raksha Ben, G. Hari Siva Annam, G. Helen Rajapushpam

Neutrosophic Systems with Applications

This paper presents an introduction to many novel types of sets, including μN strongly dense sets, μN strongly nowhere dense sets, μN strongly first category sets, and μN strongly nowhere residual sets. The features of these sets are briefly elucidated. In addition, by the use of these techniques, we have successfully obtained the highly Baire space μN, and it is imperative to elucidate its inherent features.

A Professional Development Program For Science Adjunct Faculty: The Mentoring-Learning Community (Mlc), Linda B. Purvis, Jason D. Lang, Julie A. Luft

Georgia Journal of Science

Institutions of higher education have become increasingly dependent on adjunct faculty. These faculty members are often unfamiliar with current teaching strategies emphasizing an active learning approach. To support science adjunct faculty in learning about active learning, a professional development program was designed and implemented by the authors of this study, the Mentoring-Learning Community. The Mentoring-Learning Community program design was informed by literature regarding the use of professional development programs that focused on adjunct faculty. To determine the impact of this program, participants in the Mentoring-Learning Community were observed and interviewed over one semester. Mentoring-Learning Community participants transformed through all three …

Analyzing The Strengths, Weaknesses, Opportunities, And Threats Of Ai In Libraries, Parbat Chhetri

Library Philosophy and Practice (e-journal)

This article provides a comprehensive analysis of the strengths, weaknesses, opportunities, and threats (SWOT) associated with the integration of Artificial Intelligence (AI) in libraries. AI has the potential to transform library and information science, revolutionizing processes, and services. The strengths of AI in libraries include efficient information retrieval and management, enhanced user experiences through personalization, automation of routine tasks, and improved decision-making through data analysis. However, the weaknesses of AI in libraries encompass ethical considerations and biases, the potential lack of human touch and personalized assistance, technical challenges, and concerns about job displacement. The article also explores the opportunities presented …

The Spectrum Of Nim-Values For Achievement Games For Generating Finite Groups, Bret J. Benesh, Dana C. Ernst, Nándor Sieben

Mathematics Faculty Publications

We study an impartial achievement game introduced by Anderson and Harary. The game is played by two players who alternately select previously unselected elements of a finite group. The game ends when the jointly selected elements generate the group. The last player able to make a move is the winner of the game. We prove that the spectrum of nim-values of these games is {0, 1, 2, 3, 4}. This positively answers two conjectures from a previous paper by the last two authors.

Sentiment Analysis Before And During The Covid-19 Pandemic, Emily Musgrove

Mathematics Summer Fellows

This study examines the change in connotative language use before and during the Covid-19 pandemic. By analyzing news articles from several major US newspapers, we found that there is a statistically significant correlation between the sentiment of the text and the publication period. Specifically, we document a large, systematic, and statistically significant decline in the overall sentiment of articles published in major news outlets. While our results do not directly gauge the sentiment of the population, our findings have important implications regarding the social responsibility of journalists and media outlets especially in times of crisis.

Self-Inductance And Magnetic Flux, Diego Castano, Teresa M. Castano

Chemistry and Physics Faculty Articles

The canonical equation for self-inductance involving magnetic flux is examined, and a more general form is presented that can be applied to continuous current distributions. We attempt to clarify and extend the use of the standard equation by recasting it in its more versatile form.

One Formula For Non-Prime Numbers: Motivations And Characteristics, Mahmoud Mansour, Kamal Hassan Prof.

Basic Science Engineering

Primes are essential for computer encryption and cryptography, as they are fundamental units of whole numbers and are of the highest importance due to their mathematical qualities. However, identifying a pattern of primes is not easy. Thinking in a different way may get benefits, by considering the opposite side of the problem which means focusing on non-prime numbers. Recently, researchers introduced, the pattern of non-primes in two maximal sets while in this paper, non-primes are presented in one formula. Getting one-way formula for non-primes may pave the way for further applications based on the idea of primes.

Allied Health Faculty Members’ Perspective On Interprofessional Collaborative Practice: A Hermeneutic Phenomenological Study, Prajakta Khare-Ranade, Margaret Newsham Beckley, Mary Geders Falcetti

Dissertations

A framework for interprofessional collaborative practice (IPCP) was developed by the World Health Organization (WHO) (WHO, 2010) in response to the need to address the complicated conditions that exist in today’s health systems. Much of the focus of today’s health service delivery is predicated on the social determinants of health (Barzansky et al., 2019), which refer to the environmental conditions associated with where people are born, live, go to school, work, play, age, and worship that have an impact on health, function, quality of life, and risks (Healthy People 2030, n.d.). IPCP is thought to be the only approach effective …

Density Dependence And Dynamics Of Dipole-Dipole Interactions Among Rydberg Atoms, Hannah Conley

Physics and Astronomy Summer Fellows

After trapping atoms, exciting them to an initial high-energy Rydberg state, and allowing them a brief time to exchange energy with each other through dipole-dipole interactions, we observe how their energies are redistributed among various energy levels. The measurements we make in this physical experiment do not give insight into how individual atoms interact or metrics like fidelity and entanglement entropy, which impact our results. For this reason, it is useful to compare our results from the physical experiment to those of our simulation on a supercomputer, in which we can track the final and initial energy of individual atoms …

Gamma-Ray Spectroscopy Of One-Neutron Knockout From 72se, Alyssa Himmelreich

Physics and Astronomy Summer Fellows

We studied single-neuron excitations of the exotic nucleus ⁷¹Se with the one-neutron knockout reaction from a ⁷²Se beam at the National Superconducting Cyclotron Laboratory. We measured gamma rays de-exciting states in ⁷¹Se using the Gretina gamma-ray tracking array and the momentum of the ⁷¹Se reaction product with the S800 Magnetic Spectrograph. We utilize a supercomputer to run multiple simulations and fit them to our gamma-ray spectrum. Using gamma-ray yields and level schemes, we can determine the number of times each excited state was populated by neutron knockout. We deduced cross sections for populating single-neutron excitations of …

Enhanced Quantum Chemistry With Machine Learning, Brock Dyer

Physics and Astronomy Summer Fellows

This file is a catalogue of the relevant quantum mechanical and computer programming topics that I learned during the summer which will be helping me to generate an artificial intelligence that will be able to perform computational chemical calculations at a much faster rate and comparable or better accuracy than current methods.

Improving The Efficiency Of Liquid-Hydrogen Simulation Via Event Storage, Jake Kosa

Physics and Astronomy Summer Fellows

We contributed to the analysis of gamma-ray spectroscopy data collected at the Facility for Rare Isotope Beams at Michigan State University by speeding up the UCGretina simulation code, used in the analysis and planning of experiments. Simulating beam-target interactions in a liquid-hydrogen target system is a time intensive task, even when parallelized. In the process of analyzing data, a large number of simulations must be run for different gamma-ray energies, target positions, and lifetimes of excited states. We are addressing the most computationally intensive component of the simulations by adding the ability to simulate a large sample of beam particles …

The Impact Framework And Implementation For Accessible In Silico Clinical Phenotyping In The Digital Era, Andrew Wen, Huan He, Sunyang Fu, Sijia Liu, Kurt Miller, Liwei Wang, Kirk E Roberts, Steven D Bedrick, William R Hersh, Hongfang Liu

Faculty, Staff and Student Publications

Clinical phenotyping is often a foundational requirement for obtaining datasets necessary for the development of digital health applications. Traditionally done via manual abstraction, this task is often a bottleneck in development due to time and cost requirements, therefore raising significant interest in accomplishing this task via in-silico means. Nevertheless, current in-silico phenotyping development tends to be focused on a single phenotyping task resulting in a dearth of reusable tools supporting cross-task generalizable in-silico phenotyping. In addition, in-silico phenotyping remains largely inaccessible for a substantial portion of potentially interested users. Here, we highlight the barriers to the usage of in-silico phenotyping …

Non-Invasive Arterial Blood Pressure Measurement And Spo2 Estimation Using Ppg Signal: A Deep Learning Framework, Yan Chu, Kaichen Tang, Yu-Chun Hsu, Tongtong Huang, Dulin Wang, Wentao Li, Sean I Savitz, Xiaoqian Jiang, Shayan Shams

Faculty, Staff and Student Publications

BACKGROUND: Monitoring blood pressure and peripheral capillary oxygen saturation plays a crucial role in healthcare management for patients with chronic diseases, especially hypertension and vascular disease. However, current blood pressure measurement methods have intrinsic limitations; for instance, arterial blood pressure is measured by inserting a catheter in the artery causing discomfort and infection.

METHOD: Photoplethysmogram (PPG) signals can be collected via non-invasive devices, and therefore have stimulated researchers' interest in exploring blood pressure estimation using machine learning and PPG signals as a non-invasive alternative. In this paper, we propose a Transformer-based deep learning architecture that utilizes PPG signals to conduct …

The Screening Of The Protective Antigens Of Aeromonas Hydrophila Using The Reverse Vaccinology Approach: Potential Candidates For Subunit Vaccine Development, Ting Zhang, Minying Zhang, Zehua Xu, Yang He, Xiaoheng Zhao, Hanliang Cheng, Xiangning Chen, Jianhe Xu, Zhujin Ding

Faculty, Staff and Student Publications

The threat of bacterial septicemia caused by Aeromonas hydrophila infection to aquaculture growth can be prevented through vaccination, but differences among A. hydrophila strains may affect the effectiveness of non-conserved subunit vaccines or non-inactivated A. hydrophila vaccines, making the identification and development of conserved antigens crucial. In this study, a bioinformatics analysis of 4268 protein sequences encoded by the A. hydrophila J-1 strain whole genome was performed based on reverse vaccinology. The specific analysis included signal peptide prediction, transmembrane helical structure prediction, subcellular localization prediction, and antigenicity and adhesion evaluation, as well as interspecific and intraspecific homology comparison, thereby screening …

Psychological Trauma In Terrorism (Pt2r): Phase 1 End Of Year Report, Matthew Crayne, Neil Shortland, Jennifer L. Mezzapelle, National Counterterrorism Innovation, Technology, And Education Center

Reports, Projects, and Research

About the Report. This report summarizes the findings of Phase 1 of the PT2R project, a study in the structural design of terrorism and targeted violence research as a profession. Drawn from qualitative analysis of interviews with 35 active terrorism and targeted violence researchers, this report provides a comprehensive job analysis of terrorism research which can be used to inform future selection, assessment, and training of researchers. Additionally, we explore the issue of exposure to traumatic material as a necessary component of terrorism and targeted violence research and identify job-embedded risk factors for psychosocial harm to researchers.

Heat Transfer To Rolling Or Sliding Drops On Inclined Heated Superhydrophobic Surfaces, Joseph Merkley Furner

Theses and Dissertations

This thesis examines the time resolved heat transfer to drops rolling or sliding along inclined, subcritical heated non-wetting surfaces. Results were experimentally obtained using IR imaging for a smooth hydrophobic surface and post as well as rib structured superhydrophobic surfaces of varying solid fraction (f_s = 0.06 - 0.5). Tests were performed at varying inclination angle (α = 10, 15, 20, and 25°), drop volume (12, 20, 30, and 40 μL), and surface temperature (T_w = 50, 65, and 80 °C). Rib structured superhydrophobic surfaces were explored for drops moving parallel and perpendicular to the rib structures. The findings indicate …

State Of Urbanization In Nepal: The Official Definition And Reality, Keshav Bhattarai, Ambika P. Adhikari, Shiva Gautam

Himalayan Research Papers Archive

Nepali government’s official delineation of several human settlements as new urban areas has been questionable because many important criteria such as urban infrastructure and services, open space, population density and economic viability are not thoroughly analyzed while defining what is urban. Many settlements in Nepal officially defined as urban, often driven by political considerations, are operating in the rural framework forming ruralopolises. This paper analyzes various criteria needed for defining urbanization that are internationally accepted to assess Nepal’s official definition of urban settlements. Urban areas have been expanding in Nepal at the cost of agricultural, forest, and shrubland land uses. …

Carbon Nanotubes Animated, Nicholas Onyemeke

Chemistry Summer Fellows

In this project, I implemented the knowledge about carbon nanotubes into an animated short. The animated short is meant to simplify the research so that anyone can understand regardless of their background in science. The research I did was on how nanotubes can be used in the medical field as a measure to inhibit bacteria growth. A nanotube dye solution was synthesized to inoculate bacteria along with an antibiotic solution with the nanotubes. This was done to observe how well the nanotubes can inhibit bacteria growth without the need for a drug compared to the effectiveness when it has a …

On Training Neurons With Bounded Compilations, Lance Kennedy

Master of Science in Computer Science Theses

Knowledge compilation offers a formal approach to explaining and verifying the behavior of machine learning systems, such as neural networks. Unfortunately, compiling even an individual neuron into a tractable representation such as an Ordered Binary Decision Diagram (OBDD), is an NP-hard problem. In this thesis, we consider the problem of training a neuron from data, subject to the constraint that it has a compact representation as an OBDD. Our approach is based on the observation that a neuron can be compiled into an OBDD in polytime if (1) the neuron has integer weights, and (2) its aggregate weight is bounded. …