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2023’S Billion-Dollar Disasters List Shattered The Us Record With 28 Big Weather And Climate Disasters Amid Earth’S Hottest Year On Record, Shuang-Ye Wu

Department of Earth, Environment and Sustainability Faculty Publications

The U.S. set an unwelcome record for weather and climate disasters in 2023, with 28 disasters that exceeded more than US$1 billion in damage each.

While it wasn’t the most expensive year overall – the costliest years included multiple hurricane strikes – it had the highest number of billion-dollar storms, floods, droughts and fires of any year since counting began in 1980, with six more than any other year, accounting for inflation.

Dorothy Leland Oral History, Dorothy Leland, Lorenzo Spaccarelli

Raymond College

No abstract provided.

Indigenous Peoples And Local Communities Report Ongoing And Widespread Climate Change Impacts On Local Social-Ecological Systems, Victoria Sharakhmatova, Victoria Reyes-García, David García-Del-Amo, Santiago Álvarez-Fernández, Petra Benyei, Laura Calvet-Mir, André B. Junqueira, Vanesse Labeyrie, Xiaoyue Li, Sara Miñarro, Vincent Porcher, Anna Porcuna-Ferrer, Anna Schlingmann, Christoph Schunko, Ramin Soleymani, Adrien Tofighi-Niaki, Mariam Abazeri, Emmanuel M.N.A.N. Attoh, Ayansina Ayanlade, Julia Vieira Da Cunha Ávila, Daniel Babai, Rodrigo C. Bulamah, Joao Campos-Silva, Rosario Carmona, Julián Caviedes, Rumbidzayi Chakauya, Mouna Chambon, Zhuo Chen, Fasco Chengula, Esther Conde, Aida Cuní-Sanchez

Faculty Publications

The effects of climate change depend on specific local circumstances, posing a challenge for worldwide research to comprehensively encompass the diverse impacts on various local social-ecological systems. Here we use a place-specific but cross-culturally comparable protocol to document climate change indicators and impacts as locally experienced and analyze their distribution. We collected first-hand data in 48 sites inhabited by Indigenous Peoples and local communities and covering all climate zones and nature-dependent livelihoods. We documented 1,661 site-agreed reports of change corresponding to 369 indicators. Reports of change vary according to climate zone and livelihood activity. We provide compelling evidence that climate …

Light That Appears To Come From A Source That Does Not Exist, Itamar Stern, Yakov Bloch, Einav Grynszpan, Merav Kahn, Yakir Aharonov, Justin Dressel, Eliahu Cohen, John C. Howell

Mathematics, Physics, and Computer Science Faculty Articles and Research

Superoscillatory, band-limited functions oscillate faster than their fastest Fourier component. Superoscillations have been intensively explored recently as they give rise to many out-of-the-spectrum phenomena entailing both fundamental and applied significance. We experimentally demonstrate a form of superoscillations which is manifested by light apparently coming from a source located far away from the actual one. These superoscillations are sensed through sharp transverse shifts in the local wave vector at the minima of a pinhole diffraction pattern. We call this phenomenon “optical ventriloquism.”

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 …

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 …

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 …

Comparison Of Empirical And Analytical Eigenfunctions As Bases For Reduced Order Methods In Heat Transfer, Jakob G. Bates, Matthew R. Jones, Christopher R. Dillon, John Tencer

Student Works

Reduced order methods using spectral representations show promise in facilitating and accelerating heat transfer analyses. This paper proposes a taxonomy for reduced order methods, classifying a method as reduced order compression, modelling, or analysis. The performance of bases formed with analytical and empirical eigenfunctions are compared for representative reduced order tasks. The Akaike Information Criterion is applied in a novel way to compare the performance of these bases. The present study finds that both bases are parsimonious for reduced order compression tasks. Empirical eigenfunctions are more robust to for reduced order modelling with variations in modelling parameters such as thermal …

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 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

Design And Development Of Iot-Enabled Power Management System For Smart Home With Enhanced Security Feature, Indu Bala, Bhukya Arun Kumar

Iraqi Journal for Computer Science and Mathematics

This article presents a proposed architecture for a smart and secure home automation system that incorporates advanced Internet of Things (IoT) capabilities. The system under consideration has been developed with the objective of maximizing the efficiency of power consumption in domestic electrical appliances. By employing a continuous monitoring mechanism for the power consumption of individual devices, this system serves the twin purpose of mitigating the risk of short circuits resulting from excessive electrical loads and enabling users to monitor the energy consumption of each appliance. Consequently, it facilitates the efficient management of billing processes. The proposed model utilizes Internet of …

Development Of Synthetic Data Generator For Ornament Based On Data Mining Techniques, Ahmed Hussein Ali, Saad Ahmed Dheyab, Rasha Talal Hameed

Iraqi Journal for Computer Science and Mathematics

Artificial intelligence tools depend on generating various images on the available datasets, but there is a lot of data that is not completely available, especially images of heritage and archaeological ornament. In this paper, a tool was developed to generate ornament based on the geometric shapes of heritage ornaments. A group of basic geometric shapes was collected. The new ornament are reshaped in three stages, relying on the permutation equation and reshaping of the overlapping sizes of the shapes, In the first stage, the number of layers that make up the ornament is determined. In the second stage,the formation of …

Healthcare Privacy-Preserving Federated Transfer Learning Using Ckks-Based Homomorphic Encryption And Pyhfeltool, Anmar A. Al-Janabi, Sufyan Al Janabi, Belal Al Khateeb

Iraqi Journal for Computer Science and Mathematics

Digitization of healthcare data has shown an urgent necessity to deal with privacy concerns within the fieldof deep learning for healthcare organizations. A promising approach is federated transfer learning, enabling medical institutions to train deep learning models collaboratively through sharing model parameters rather than raw data. The objective of this research is to improve the current privacy-preserving federated transfer learning systems that use medical data by implementing homomorphic encryption utilizing PYthon for Homomorphic Encryption Libraries (PYFHEL). The study leverages a federated transfer learning model to classify cardiac arrhythmia. The procedure begins by converting raw Electrocardiogram (ECG) scans into 2-D ECG …

Automatic Temperature Control System Using African Vultures Optimization Algorithm, Mostafa Abdulghafoor Mohammed, Muntadher Khamees, Dina Hassan Abbas

Iraqi Journal for Computer Science and Mathematics

One of the most important tasks in control engineering is tuning a PID controller for maximum efficiency. However, without a great deal of practice, manual adjustment of PID settings might result in erroneous results. Using met heuristic algorithms is one method for tweaking the PID controller. These algorithms, which are inspired bythe laws of nature, can effectively find the sweet spot for the PID settings. Therefore, instead of manually tweaking the PID controller, using met heuristic methods can greatly enhance the system's performance while decreasing the related expenses. A reliable temperature control system is crucial to the production of a …

Enhanced Cancer Subclassification Using Multi-Omics Clustering And Quantum Cat Swarm Optimization, Mazin Abed Mohammed, Ali Mahmoud Ali

Iraqi Journal for Computer Science and Mathematics

Integrating multiple omics data can significantly improve the accuracy of cancer subclassification, a challenging task due to the high dimensionality and limited sample sizes. The integration of these data sets can enhance model performance. This study addresses these challenges by employing Quantum Cat Swarm Optimization (QCSO) for feature selection, along with K-means clustering and Support Vector Machine (SVM) for classification. Using QCSO, the most significant features were identified, resulting in an increase in accuracy from 81% to100%. Performance was evaluated using accuracy, F1-score, precision, recall, ROC, and the silhouette metric, all of which confirmed the effectiveness of the feature selection …

Soft Computing-Based Generalized Least Deviation Methodalgorithm For Modeling And Forecasting Covid-19 Usingquasilinear Recurrence Equations, Mostafa Abotaleb

Iraqi Journal for Computer Science and Mathematics

This study introduces an advanced algorithm based on the Generalized Least Deviation Method(GLDM) tailored for the univariate time series analysis of COVID-19 data. At the core of this approach is theoptimization of a loss function, strategically designed to enhance the accuracy of the model’s predictions. Thealgorithm leverages second-order terms, crucial for capturing the complexities inherent in time series data. Ourfindings reveal that by optimizing the loss function and effectively utilizing second-order model dynamics, there is amarked improvement in the predictive performance. This advancement leads to a robust and practical forecasting tool,significantly enhancing the accuracy and reliability of univariate time series …

Designing And Implementing An Ecg Reader And Heart Disease Classification Device Using Deep Learning (Comprehensive Review), Ghasaq Saad Jameel, M N. Al-Turfi, Dr. Hussain Falih Mahdi, Saba Nasser Hussain

Iraqi Journal for Computer Science and Mathematics

Cardiovascular cases remain a significant health care concern, necessitating new development methods for their prompt and accurate identification where a promising advancements is demonstrated using Deep Learning (DL) in automating heart anomalies detection, including irregular heartbeats, heart attacks, and abnormal heart rhythms, through the analysis of electrocardiogram (ECG) signals, which guided this article to explore the integration of DL methodologies in examining ECG data to enhance the diagnosis of various cardiac ailments and delves into the development of novel ECG devices designed to facilitate efficient data acquisition while ensuring patient comfort and accessibility.The devices used must provide real-time monitoring, seamless …

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. …

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 …

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 …