Digital Commons Network^™

The Unprecedented Stressors Of Early Childhood Educators During The Covid-19 Pandemic And Post-Pandemic Restoration: A Case Study, Ida Mae Lewis

Doctoral Dissertations and Projects

The purpose of this case study was to describe the unprecedented stressors of early childhood educators (ECE) during the COVID-19 pandemic and the post-pandemic restoration at two early childhood education centers (ECEC) in a midwestern state. The central research question was: How did the COVID-19 pandemic’s unprecedented stressors impact ECE in the post-pandemic era? Data collection included structured interviews with open-ended questions, focus groups, and documents. The three data sources were triangulated for themes, perspectives, and interpretations, and coding was used to help gain a deep understanding of the stressors experienced by early childhood educators. The conceptual framework guiding this …

Philosophies Of Empirical And Habitual Teaching: Healthy Vocal Methodologies In Higher Education For The Twenty-First Century, Katie Denise Osuamkpe

Doctoral Dissertations and Projects

Despite research done on healthy vocal methodologies, there are continuous changes in how best to prepare collegiate music students, relating to their emotional health through empirical and habitual teachings. This study will show how healthy vocal methodologies can influence higher education vocal students of the twenty-first century. This qualitative study can build a bridge to related topics in an exploratory framework with perspectives on: Dr. William Hettler’s Emotional Well-Being and its seven dimensions, Jean Piaget's Cognitive Construction Theory, Peter Salovey and John Mayer's Emotional Intelligence Theory, Daniel Goleman’s Social Emotional Learning Methodology, Susan Brookhart’s “Classroometrics” Theory, Howard Gardner’s Theory of …

Choral Educators’ Perspectives On Block Scheduling In Middle Schools, Heather Anderson Perryman

Doctoral Dissertations and Projects

The purpose of this study is to identify how common the practice of block scheduling is currently among American public middle schools. This study also determines the perspectives of choral music educators working in public middle schools with existing block schedules. More extant literature is needed to examine block scheduling practices at the middle school level and the possible effects of block scheduling on middle school choral programs. Such an examination is essential for ascertaining curriculum needs, staffing issues, scheduling challenges, and choral music education advocacy initiatives. A qualitative design and case study approach are utilized to infer connections between …

Clpfudatabase: A Suite Of R Packages For Energy Conversion Chain Analysis, Matthew Kuperus Heun, Zeke Marshall, Emmanuel Aramendia

University Faculty Publications and Creative Works

Energy flowing through societal energy conversion chains (ECCs) enables economic activity and facilitates human flourishing. To understand economic growth and human well-being, the field of societal energy analysis (Common, 1976) evaluates ECCs from the primary stage (resources extracted from the environment, such as coal, oil, natural gas, wind, and solar), to the final stage (energy purchased by consumers, such as refined petroleum and electricity), to the useful stage (energy desired by the end user, such as heat, motion, and light), and sometimes to energy services (such as thermal comfort, transport, and illumination). Societal exergy analysis (SEA) (Ertesvåg, 2001), an extension …

Nonlinear Ferroelectric Characteristics Of Barium Titanate Nanocrystals Determined Via A Polymer Nanocomposite Approach, Qiong Li, Elshad Allahyarov, Tianxiong Ju, Lei Zhu

Faculty Scholarship

The growing demand for high energy storage materials has garnered substantial attention towards lead-free ferroelectric nanocrystals (NCs), such as BaTiO3 (BTO), for next-generation multilayer ceramic capacitors. Notably, it remains challenging to accurately measure the dielectric constant and polarization-electric field (P-E) hysteresis loop for BTO NCs. Herein, we report on nonlinear ferroelectric characteristics of BTO NCs via a polymer nanocomposite approach. Specifically, poly(vinyl pyrrolidone) (PVP)/BTO nanocomposite films of 3-10 μm thickness, containing 380 nm tetragonal-phased and 60 nm cubic-phased BTO NCs with uniform particle dispersion, were prepared. Theoretical deconvolution of the broad experimental P-E loops of the PVP/BTO NC composite films …

Clpfudatabase: A Suite Of R Packages For Energy Conversion Chain Analysis, Matthew Kuperus Heun, Zeke Marshall, Emmanuel Aramendia

University Faculty Publications and Creative Works

Energy flowing through societal energy conversion chains (ECCs) enables economic activity and facilitates human flourishing. To understand economic growth and human well-being, the field of societal energy analysis (Common, 1976) evaluates ECCs from the primary stage (resources extracted from the environment, such as coal, oil, natural gas, wind, and solar), to the final stage (energy purchased by consumers, such as refined petroleum and electricity), to the useful stage (energy desired by the end user, such as heat, motion, and light), and sometimes to energy services (such as thermal comfort, transport, and illumination). Societal exergy analysis (SEA) (Ertesvåg, 2001), an extension …

Steeper Size Spectra With Decreasing Phytoplankton Biomass Indicate Strong Trophic Amplification And Future Fish Declines, Angus Atkinson, Axel G. Rossberg, Ursula Gaedke, Gary Sprules, Ryan F. Heneghan, Stratos Batziakas, Maria Grigoratou, Elaine Fileman, Katrin Schmidt, Constantin Frangoulis

School of Geography, Earth and Environmental Sciences

Under climate change, model ensembles suggest that declines in phytoplankton biomass amplify into greater reductions at higher trophic levels, with serious implications for fisheries and carbon storage. However, the extent and mechanisms of this trophic amplification vary greatly among models, and validation is problematic. In situ size spectra offer a novel alternative, comparing biomass of small and larger organisms to quantify the net efficiency of energy transfer through natural food webs that are already challenged with multiple climate change stressors. Our global compilation of pelagic size spectrum slopes supports trophic amplification empirically, independently from model simulations. Thus, even a modest …

Comparing The Effectiveness Of Static And Dynamic Audiovisual In An Additional Geography Lesson In One Pathway College In Jakarta, Erni Adelina, Peny Meliaty Hutabarat

Jurnal Vokasi Indonesia

Students are now used to using audiovisual platforms to learn as they once were forced to adapt to this type of learning due to face-to-face lessons were impossible at that time because of the pandemic. Audiovisual learning resources came out sporadically to accommodate the needs of study at home or anywhere possible. The static audiovisual (enhanced podcast) and dynamic audiovisual (video) are two types of virtual platforms educators continuously harness to support their lesson teachings even though the face-to-face meetings have been allowed gradually. However, there are not many studies conducted to analyze whether one type is more effective in …

Reflections Of “Use Of Comics In Social Studies Education” Course: The Opinion And Experiences Of Teachers, Genç Osman İlhan, Maide Şin

SANE journal: Sequential Art Narrative in Education

It is well known that a quality teacher education is necessary for qualified education. Teachers must be well-trained in multiple areas and have an open-minded structure. They must develop strategies based on the lesson and students, which needs effective material development and use. The materials to be used could be prepared by others and can be incorporated into the classroom setting or teachers could design and present them to students, which is essential for the quality of instruction. When a teacher creates and effectively employs instructional materials, his/her self-confidence will increase and teaching will be enriched and made easier. Comics …

Effects Of Different Projectile Nose Shapes On The Impact Performance Of The Aluminium 2024 Thin Plate, Dlair O. Ramadan

Polytechnic Journal

. In this study, the impact performance of the Al2024 thin plate target was determined through a numerical approach. Two different-nosed hard steel projectiles, including a blunt and a sphere, were used in order to obtain the ballistic impact of the target. ANSYS Autodyn was used to model a three-dimensional (3D) model that corresponds to a previous experimental study. The ballistic resistance of the target was numerically evaluated in terms of ballistic limit velocity, residual velocity, and energy absorption and compared at different incident angles such as 0°, 15°, and 30°. To validate the numerical outcomes, the Recht-Ipson model was …

Faculty Senate Agenda January 8, 2024, Utah State University

Faculty Senate & Faculty Senate Executive Committee

• 3:00 Call to Order
• 3:05 University Business
• 3:20 Faculty Senate Business
• 3:30 Information

• 3:35 Reports

• 4:00 Old Business

• 4:05 New Business

• Adjourn: 4:30

Faculty Senate Monthly Packet January 2024, Portland State University Faculty Senate

Faculty Senate Monthly Packets

The January 8, 2024 monthly packet includes the January agenda, appendices, and the Faculty Senate minutes and attachments from the meeting held January 8, 2024.

Preparing Elementary Preservice Teachers For Inquiry-Based Science And Mathematics Instruction Through A Novel Initiative, Tye Campbell, Diandra Singh, Cathlene Hillier, J-F, Haleigh Sears

Teacher Education and Leadership Faculty Publications

Over the past several decades, policymakers, researchers, and practitioners have placed an emphasis on inquiry-based science and mathematics instruction in elementary school. While inquiry-based science and mathematics instruction can support student learning and engagement, teacher preparation programs have experienced challenges in preparing elementary teachers to use and maintain inquiry-based teaching practices. In this study, we describe how one teacher preparation program in Canada partnered with a local elementary school to design a novel initiative that provided elementary preservice teachers with authentic opportunities to employ inquiry-based instructional practices for science and mathematics. Using a thematic approach, we explored 46 elementary preservice …

Educational Policies Committee Minutes January 4, 2024, Utah State University

Educational Policies Committee

• Approval of Minutes - December 7, 2023
• Subcommittee Reports
• Other Business
• Adjourn: 3:45 pm

Radio Measurements Of The Depth Of Air-Shower Maximum At The Pierre Auger Observatory, A. Abdul Halim, P. Abreu, M. Aglietta, I. Allekotte, K. Almeida Cheminant, A. Almela, B. Fick, D. Nitz, K. Nguyen, A. Puyleart, Et Al.

Michigan Tech Publications

The Auger Engineering Radio Array (AERA), part of the Pierre Auger Observatory, is currently the largest array of radio antenna stations deployed for the detection of cosmic rays, spanning an area of 17 km2 with 153 radio stations. It detects the radio emission of extensive air showers produced by cosmic rays in the 30-80 MHz band. Here, we report the AERA measurements of the depth of the shower maximum (Xmax), a probe for mass composition, at cosmic-ray energies between 1017.5 and 1018.8 eV, which show agreement with earlier measurements with the fluorescence technique at the Pierre Auger Observatory. We show …

Demonstrating Agreement Between Radio And Fluorescence Measurements Of The Depth Of Maximum Of Extensive Air Showers At The Pierre Auger Observatory, A. Abdul Halim, P. Abreu, M. Aglietta, I. Allekotte, K. Almeida Cheminant, A. Almela, B. Fick, D. Nitz, K. Nguyen, A. Puyleart, Et Al.

Michigan Tech Publications

We show, for the first time, radio measurements of the depth of shower maximum (Xmax) of air showers induced by cosmic rays that are compared to measurements of the established fluorescence method at the same location. Using measurements at the Pierre Auger Observatory we show full compatibility between our radio and the previously published fluorescence dataset, and between a subset of air showers observed simultaneously with both radio and fluorescence techniques, a measurement setup unique to the Pierre Auger Observatory. Furthermore, we show radio Xmax resolution as a function of energy and demonstrate the ability to make competitive high-resolution Xmax …

Various Closed-Form Solitonic Wave Solutions Of Conformable Higher-Dimensional Fokas Model In Fluids And Plasma Physics, Mohammad A. Tashtoush, Israa A. Ibrahim, Wafaa M. Taha, Mizal H. Dawi, Ali F. Jameel, Emad A. Az-Zo’Bi

Iraqi Journal for Computer Science and Mathematics

This work focuses on finding closed-form analytic solutions of a higher-dimensional fractional model, in conformable sense, known by the (4+1)-dimensional Fokas equation. Fractional partial differential equations(FPDEs)and systemscan describe heritable real-world occurrences. However, solving such modelscan be difficult, especially for nonlinearproblems. The homogeneous balancing method (HBM) is investigated and extended to handle the (4+1)-dimensional Fokas equation with Kerr law nonlinearity.The HBM has theability to solve linear and nonlinear fractional problems,incorporatingthe concepts of some fractional calculus principles, including fractional derivative techniques. It's important to note that there isn't a singleanduniversally applicable method to solve such equations due to their complexity. The specific …

Approach For Detecting Arabic Fake News Using Deep Learning, Khalid Shaker, Arwa Alqudsi

Iraqi Journal for Computer Science and Mathematics

Fake news has spread more widely over the past few years. The development of social media and internet websites has fueled the spread of fake news, causing it to mix with accurate information. The majority of studies on Fake News Detection FND were in English, but recent attention has been focused on Arabic. However, there aren't many studies on Arabic fake news detection. In this work, a newArabic fake news detection approachhas been proposedusing Arabic dataset publically availableand a translated English fake news dataset intoArabic. A new model Text-CNNs based on 1D Convolution Neural Networks CNNs has been used for …

Embedded Deep Learning To Improve The Performance Of Approaches For Extinct Heritage Images Denoising, Ali Salim Rasheed, Alaa Hamza Omran

Iraqi Journal for Computer Science and Mathematics

Many advanced deep convolutional neural network (DCNN) methods have proven their efficacy in reconstructing the texture of super-resolution images (SR) from low-resolution images (LR). Nevertheless, the objective of achieving super-resolution (SR) reconstruction using Deep Convolutional Neural Networks (DCNN) becomes difficult when the input image is distorted by noise. Photographs captured at the inception of the camera are presently regarded as acultural heritage that chronicles an important periodin human history; however, they are marred by low resolution and noise as a result of obsolescence and the primitive nature of the technology that captured them, in contrast to the technological advances that …

Tackling The Berth Allocation Problem Via Harmony Search Algorithm, Hazlina Hamdan, Bilal Ahmed, Abdullah Muhammed, Nor Azura Husin

Iraqi Journal for Computer Science and Mathematics

Berth Allocation Problem (BAP) is a renowned difficultcombinatorial optimization problemthat plays acrucial role in maritime transportation systems. BAP is categorizedas non-deterministic polynomial-time hard (NP-hard) problems, thatis very toughto resolveforoptimality within an acceptabletimeframe. Many metaheuristic algorithms have been suggestedto tacklethis problem, and yet, mostof these algorithms have some drawbacks such as theyhave a weak ability to explore the solutionspace (they struggleescaping fromlocal minima) and they face the difficulties to operate on different datasets. Consequently, the need to either enhance the existing algorithms or utilize a newalgorithm is still necessary. Harmony Search Algorithm(HSA) is one ofthe recentpopulation-based optimization methodswhichinspired by modern-nature. HSA …

Enhancing Wireless Sensor Networks Features Using Software-Defined Networking Techniquesand Aco Algorithms, Ghassan A. Abed

Iraqi Journal for Computer Science and Mathematics

Wireless sensor networks (WSNs) are the most important networks for things such as monitoring natural phenomena, agriculture, health care, and so on. There are several challenges associated with using WSNs,the most important of which areenergy consumption, expansion issues, or even datarouting issues.There are many techniques and algorithms that can address these challengesand make it easier to useWSNs. These techniques and algorithms vary depending on the challenge to be overcome. In this study, Software Defined Network (SDN) technology was used for the purpose of improving WSNs and saving energy for nodes in those networks. TheAnt Colony Optimization (ACO) algorithm, which is …

Physics 100 Level Laboratory Data Collection Tables, Kalani Hettiarachchilage

Open Educational Resources

The physics 100-level laboratory part demonstrates and applies the material learned from related classes. This document shows guidelines for collecting data and analyzing them by using Microsoft Excel. Laboratory components of PHY 114/ PHY 206/SLS 261 (Introduction to Physics and Nature of Physical Processes), PHY116/PHY 121 (Physics I and General Physics I), and PHY 156/PHY 161 (Physics II and General Physics II) at College of Staten Island are in-person mandatory sessions for students and it is required to pass to receive a passing grade for that class. This part is taught by different instructors. Although everyone is supposed to follow …

Training Data Augmentation With Data Distilled By Principal Component Analysis, Nikolay Metodiev Sirakov, Tahsin Shahnewaz, Arie Nakhmmani

Faculty Publications

This work develops a new method for vector data augmentation. The proposed method applies principal component analysis (PCA), determines the eigenvectors of a set of training vectors for a machine learning (ML) method and uses them to generate the distilled vectors. The training and PCA-distilled vectors have the same dimension. The user chooses the number of vectors to be distilled and augmented to the set of training vectors. A statistical approach determines the lowest number of vectors to be distilled such that when augmented to the original vectors, the extended set trains an ML classifier to achieve a required accuracy. …

An Integrative Computational Intelligence For Robust Anomaly Detection In Social Networks, Helina Rajini Suresh, K R. Harsavarthini, R Mageswaran, Hirald Dwaraka Praveena, C Gnanaprakasam, C.Sakthi Lakshmi Priya

Iraqi Journal for Computer Science and Mathematics

Anomaly detection is one of the most important tasks for maintaining the integrity, security, and trustworthiness of online communities in a social network. This paper proposes AdaptoDetect, which represents a new framework; it discusses a new anomaly detection approach called Pufferfish Optimization Technique for feature selection, together with a Graph Embedding Autoencoder for identifying anomalies. What makes AdaptoDetect special is that, with the use of POT, it has a distinctive capability in dynamic adaptation against network changes by selecting only the most relevant features in social network data. The technique for optimization underlines the important attributes for anomaly detection so …

Prompt Engineering: Unleashing The Power Of Largelanguage Models To Defend Against Social Engineering Attacks, Prof. Bashar M. Nema, Ahmed I. Nezer, Wisam Makki Salim

Iraqi Journal for Computer Science and Mathematics

Prompt Engineering is an emerging area of study that pertains tothe act of conceptualizing, perfecting, and executing prompts that guide an AI model to an intended purpose. The AI model is an LLM, which they are the “hit” of our time and probably the controversial type of AI. They are capable of executing several tasks using natural language processing algorithms. Due to their ease of use and fast development, they are becoming highly dependent. We found that to interactcorrectly with these models and gain the best performance, several techniques should be taken into consideration. Moreover, there are additional methods or …

Fuzzy-Weightedzero-Inconsistency, Fwzic,Multi-Criteria Decision Making, Mcdm, Weighting Methods, Fuzzy Set, Mahmood M. Salih, Rasha A. Yousif

Iraqi Journal for Computer Science and Mathematics

Researchers in various fields have consistently used Multi-Criteria Decision-Making (MCDM) methods for discipline improvement, employing both standard and novel approaches. Selecting a weighting mechanismfor evaluation criteriais critical in MCDM problems. Recognizing the importanceofremaining up to date on such developments in methodology, this study aims to review severalinnovative methods integrated with Fuzzy Weighted Zero Inconsistency (FWZIC). Relying onthe papers taken from the significant databases:IEEE Xplore (IEEE), ScienceDirect (SD), Scopus, and PubMed from 23 August 2023 to 30 October 2023, where each method was read and analyzed for its characteristics and steps. These indexes were deemaed extensive and dependable enough to encompass …

Mobile Augmented Reality Framework In Stem Education: A Systematic Literature Review, Danakorn Nincarean Eh Phon, Nur Fatin Razlieya Binti Mohd Razali

Iraqi Journal for Computer Science and Mathematics

There is a growing concern with preparing a sufficient numberof highly qualified professional in areas of Science, Technology, Engineering and Mathematics (STEM). However, the number of students to reach proficiency and pursue in STEM majors seems to be decreasing. Augmented Reality (AR) is one of the evolving technologies that have potential and effect on learning, especially in STEM education. The aim of this paper is to review and analyzeexisting works that are related to AR in STEM Education. In this study, the common design elements, components or features fordesigning educational AR framework in STEM education were analyzed. This paper determined …

A Novel Deep Learning Approach For Classification Of Bird Sound Using Mel Frequency Cepstral Coefficients, Aymen Saad, Muhammad Mun’Im Ahmad Zabidi, Israa S. Kamil, Usman Ullah Sheikh

Iraqi Journal for Computer Science and Mathematics

Monitoring animal populationsis one important matter to better understand changes in their population, behavior, and biodiversity. Bird sounds are the main tool to classify bird species acoustically. The sounds of birds are an indicator for ecologists as it responds to changes in their environment. The recognition among a variety of bird species to get important features is computationally expensive. With the unbalanced classes and scarcity of training data, the performance accuracy is degrading.This paper aims to classify species ofbirds using lightweight convolutional neural networks (LWCNNs) basis on using a spectrogram image of Brazilian bird sounds as a dataset. For extracting …

Hybrid Honey Badger Algorithm With Artificial Neural Network(Hba-Ann)For Website Phishing Detection, Muhammad Arif Mohamad, Muhammad Aliif Ahmad, Zuriani Mustaffa

Iraqi Journal for Computer Science and Mathematics

Phishing is a sort of cyberattack that refers to the practice of fabricating fake websites that imitate authentic websites in order to trick users into disclosing private information. Identifying these fake sites is challenging due to their deceptive nature as they often mimic legitimate websites, making it difficult for users to distinguish between the real and fake ones. Artificial Neural Network (ANN) is one popular method for website phishing detection. ANN is capable of detecting phishing websites by identifying patterns and characteristics connected to phishing websites through a network training phase. Technically, in the network training phase of ANN, neurons …

The Gompertz Nadarajah-Haghighi (Gonh) Distribution Properties With Application To Real Data, Dalya Dh Ahmed, Mundher A. Khaleel

Iraqi Journal for Computer Science and Mathematics

In this study, we propose a continuous statistical distribution consisting of four parameters based on the Gompertz family called the Gompertz Nadarajah-Haghighi(GoNH) distribution.Adding parameters to the basic distribution provides the distribution with flexibility and efficiency in analysing real-world data.The model that was recently suggested has many mathematical and statistical properties. Explicit formulasfor its moments, moment-generating function, survival function, risk function, characteristic function, quantile function, expansion of pdf, and ordered statistics are only a few of the many mathematical and statistical features of the recently proposed model. The maximum likelihoodestimates (MLE)method was used to estimate the model’s parameters. We conducted varioussimulation …