Digital Commons Network^™

Advancing The Rights Of Nature: Lessons From Sauk-Suiattle V. City Of Seattle, Harry S. Katz

American Indian Law Journal

Advocates for the “rights of nature” seek recognition of legal rights for natural elements such as mountains, rivers, and non-human species as a means of protecting the environment. In the United States, Tribal Nations have been at the forefront of this nascent movement. In a 2022 Washington state case, the Sauk-Suiattle Indian Tribe sued the City of Seattle, alleging that the City’s hydroelectric dams on the Skagit River infringe upon the rights of salmon. Those rights, they claim, include the salmon’s rights to exist, flourish, regenerate, and evolve. The case, known as Sauk-Suiattle Indian Tribe v. City of Seattle, …

Algorithmic Editors: Section 230, Big Tech, And The Need For Clarity, Richard Gruters

Seton Hall Law Review

No abstract provided.

Improving Mathematical Problem-Solving Performance Through The Use Of Reading Comprehension Strategies, Rebecca Yonan

Masters Projects

Research shows that math problem solving relies on more than arithmetic computation. Word problem solving is a combination of text comprehension and word memory. Being able to successfully solve word problems at the elementary level helps prepare students for algebra, and higher academics. Learning to solve word problems teaches students problem solving techniques that can be applied in their adult lives. This project creates an instructional routine where lessons are built around teaching primarily through word problem solving. Students will receive instruction on text comprehension, math vocabulary building, word memory, and arithmetic computation in order to simultaneously increase their math …

A Neutrosophic Homological-Gröbner Framework For Ai-Driven Media Education Evaluation, Mona Gharib, Hafiz Muhammad Athar Farid, José M. Merigó, Muhammad Riaz

Sustainable Machine Intelligence Journal

The integration of artificial intelligence (AI) with media technologies has transformed teaching in Journalism and Communication, introducing new challenges for quality evaluation. Traditional assessment methods fail to capture the uncertainty, inconsistency, and incompleteness inherent in modern educational data. This paper proposes a Neutrosophic Homological–Gröbner Framework, which unifies three perspectives: neutrosophic sets to encode uncertain evidence, homological algebra to analyze structural coherence, and Gröbner bases to systematically simplify interdependent evaluation rules.

Within this framework, diverse evidence is encoded into neutrosophic triplets, daggregate into course-level indicators, and organized into neutrosophic chain complexes, where Betti indices reveal coherence and fragmentation. Educational policies are …

High-Performance Deep Learning Techniques For Plant Disease Detection: Performance Analysis, Validation, And Applications, Doaa El-Shahat, Ahmed Elmasry

Sustainable Machine Intelligence Journal

The early detection of plant diseases is an indispensable task to improve crop yields and production quality. Crop disease observations by experienced pathologists are difficult and might take a long time. Therefore, deep learning (DL) techniques have been utilized to present an automated detection technique that could accurately and timely detect plant diseases. Several DL models in the literature were proposed, but no paper conducted a comparative study between those models to determine which of them was the best alternative for this task. Therefore, twenty-one DL models are compared in this review paper to show which of them could achieve …

Rf-Et-Ann: Hybrid Machine Learning Model For Forecasting Short-Term Photovoltaic Power Production, Walid Abdullah, Ahmed Ismail Ebada, Mohamed Abouhawwash

Sustainable Machine Intelligence Journal

Accurately forecasting photovoltaic (PV) power generation is a challenging problem due to the non-linear and highly variable characteristics of solar data, which is strongly influenced by several interdependent factors, such as environmental conditions, system characteristics, and technical aspects. In this study, a newly proposed machine learning (ML) technique based on integrating random forest (RF), extra trees (ET), and artificial neural networks (ANN) is presented to tackle this problem with better predictive accuracy, ensuring that solar energy is used more consistently, effectively, and economically; this model is dubbed RF-ET-ANN for short. Hybridization of these three models will help capture non-linear aspects …

Gnmsa: An Accurate Parameter Estimation Of Semi-Empirical Proton Exchange Membrane Fuel Cells Model Using A Hybrid Artificial Intelligence–Based Optimization Approach, Dina Atef, Doaa El-Shahat, Hafiz Burhan Ul Haq, Zaka Ur Rehman, Muhammad Nauman Irshad

Sustainable Machine Intelligence Journal

The PEMFC parameter estimation problem has recently piqued the interest of several researchers due to its significance in reaching better PEMFC modeling. However, existing PEMFC parameter estimation algorithms encounter significant difficulty in solving this problem because of its complex and highly nonlinear nature. Therefore, this paper presents a new hybrid approach, termed GNMSA, for addressing this problem more accurately. This hybrid approach combines the exploration operator of the generalized normal distribution optimization with the exploitation operator of the mantis search optimization (MSA), resulting in this strong variant that has high abilities to alleviate stagnation in local optima and expedite convergence …

An Enhanced Optimization Algorithm For Estimating Pem Fuel Cells Parameters: Performance Comparison And Real-World Applicability, Ibrahim Alrashdi, Karam M. Sallam

Sustainable Machine Intelligence Journal

Accurate modeling is critical for the efficient design, control, and optimization of a proton exchange membrane (PEM) fuel cell. This problem is regarded as a multi-modal, multi-variate, non-linear optimization problem, and several methods in the literature have been presented to tackle it. However, those methods still suffer from either being stuck into local optima or a slow convergence rate. To solve this problem more accurately in terms of final results and convergence speed, this study proposes a hybrid optimization algorithm based on enhancing the recently proposed crested porcupine optimizer (CPO) using two new optimization methods, namely ranking-based optimization and exploration-exploitation …

Securing U.S. Leadership In Agentic Ai Literacy And Adoption: U.S. Vs Chinese Government Policies And Initiatives, Satyadhar Joshi

Harrisburg University Other Works

This paper conducts a comparative analysis of U.S. and Chinese frameworks for AI literacy and adoption, with focus on agentic AI and Artificial General Intelligence (AGI) systems capable of autonomous reasoning and execution. We examine national policies, educational integration, governance structures, and technological roadmaps, employing both qualitative review and quantitative modeling. Mathematical formulations include multi-dimensional literacy scoring, Bass diffusion models for adoption dynamics, risk assessment functions, regulatory effectiveness indices, competitiveness metrics, and optimization frameworks for resource allocation. Our analysis reveals divergent paradigms: the U.S. Favors decentralized, innovation-driven approaches with emphasis on interoperability and public-private collaboration; while China pursues centralized, state-led …

The Bg News January 14, 2026, Bowling Green State University

BG News (Student Newspaper)

The BGSU campus student newspaper. January 14, 2026. Volume 105-Issue 13.

Truncated Exponentiated Ailamujia Exponential Distribution: Properties And Applications, Samer Abdulqader Salih, Dabya Mahmood Ali, Hind Khaled Kolaib, Alaa Abdulrahman Khalaf

Baghdad Science Journal

Probability distribution has shown its practicality in almost every area of human effort. This paper introduces a novel family of distributions called the [0, 1] Truncated Exponentiated Ailamujia-G family. The [0, 1] Truncated Exponentiated Ailamujia Exponential ([0, 1]TEAE) distribution, which is a sub-model of the recently created family, is completely constructed. The [0, 1]TEAE distribution is created by merging the [0, 1] Truncated and Exponentiated Ailamujia distributions. the mathematical features of the [0, 1]TEAE distribution, including moments, skewness, kurtosis, incomplete moments, renyi entropy, quantile function, and probability-weighted moments, are extensively examined. The quantiles for the chosen parameter values are clearly …

Influence Of Rotation And An Inclined Magnetic Field For The Peristaltic Flow Of Viscoplastic Fluid Through A Porous Medium, Khalid Khaleefah Jassim, Mohammed Salim Ramadhan

Baghdad Science Journal

This research deals with the influencing of rotation and an inclined magnetic field on the analysis of blended convection heat transfer within a viscoelastic fluid that flows peristaltically through an inclined tapered asymmetric channel, that traversing in a porous media. The foundational equations of continuity, momentum, and energy were established in Cartesian coordinates. Furthermore, a range of dimensionless numbers, including Reynolds number, Brandt number, and Froude number, were introduced to regulate the governing equations in their imensionless forms. The governing equations were further simplified under the presumption of long wave lengths and small Reynolds numbers. The perturbation method was utilized …

A Proposed Cryptographic Algorithm Based On Three-Pass Protocol And The Elliptic Curve Cryptography, Rifaat Z. Khalaf, Hamza B. Habib

Baghdad Science Journal

The internet lately has become an integral part of people’s lifestyles. It impacts various aspects of their daily lives, including education, communication, etc. Hence, the need for efficient and fast cryptography algorithms has increased. In this paper, a new cryptographic algorithm is proposed using the authenticated Three-Pass Protocol (TPP) and the Elliptic Curve Cryptography (ECC). In the proposed algorithm, the ECC is used to encrypt and decrypt data (a text of size 128 bits), and the TPP is used for transmitting this data without sharing the keys. In the standard ECC, the receiver publishes the elliptic curve (EC) equation, the …

Improving Energy And Capacity-Awareness Of Effective Satellite Communication In 6g Heterogeneous Internet Of Things, Ahmed Mahdi Jubair, Khitam Abdulbasit Mohammed, Fouad H. Awad

Baghdad Science Journal

The spreading of Sixth Generation (6G) communication within the Internet of Things (IoT) is one of the recent innovations in networking services. As the number of devices becomes increasingly connected through extensive communication network connectivity, energy efficiency has become a significant concern with the widespread use of massive IoT devices. While general lack of energy optimization can lead to several issues, including data loss, link failure, and high-power utilization, directly affect the communication quality of the network. To address these challenges, it is crucial to develop a model that combines effective optimization and resource allocation, based on both Quality of …

Robust Qr Code Counterfeit Detection By Integrating Vgg19 Neural Embedding And Triplet Loss, Gede Putra Kusuma, Yulianto Yulianto, Renaldy Fredyan, Hendi Chandi, Jeffry William Tan, Philip Kwan, Muhammad Dafa Syukur

Baghdad Science Journal

Detecting counterfeit Quick Response codes plays a critical role in protecting the integrity of products and documents. This paper presents a novel methodology to increase the reliability of QR code counterfeit detection by integrating neural embedding VGG19 and triplet loss. The approach uses deep neural networks. Specifically, the modification of the VGG19 architecture is used to extract unique features from QR codes. These features are embedded in a multi-dimensional space using neural embedding methods. The use of the triplet loss function aims to increase the discriminative power of the embeddings, ensuring the discriminative power of the embeddings, and ensuring that …

Bioinformatics-Inspired Secure Video Encryption Using Chaotic Maps And Light Streaming Algorithms, Rajaa K. Hasoun, Rasha S. Ali, Ahmed G. Hameed, Ghassan H. Abdul-Majeed

Baghdad Science Journal

The Traditional encryption methods, such as AES, can be too slow for large video files, necessitating the development of faster and more efficient solutions for real-time video security. This research aims to enhance video security during transmission by developing a novel video encryption algorithm that is both fast and robust, specifically designed to handle large video datasets efficiently. The proposed video encryption algorithm integrates lightweight streaming algorithms for enhanced speed, modern cryptographic techniques, and chaotic maps for heightened security. The encryption process involves three key steps: Dividing the video into frames and scrambling/encrypting each frame, employing three innovative techniques: vertical …

The Relationship Between The Health Science Reasoning Test And Successful Completion Of An Associate Degree Nursing Program: A Retrospective Predictive Study, Joyce A.Ajkuce Kucerovy

Doctoral Dissertations and Projects

The purpose of this study was to retrospectively identify whether the addition of an entrance exam such as the Health Science Reasoning Test (HSRT) to the current admission criteria of an associate degree nursing (ADN) education program would aid in selecting students with the highest chance of successfully completing the program and entering the workforce. A nonexperimental, retrospective, quantitative, predictive correlational study design was used. A retrospective convenience sample of 320 first-year nursing students in an ADN education program was obtained. The G* power analysis showed a minimum sample size of 107 students was needed. Statistical analysis involved a multiple …

Reproducible Semantic Data Management Workflow For Materials Data Science: Generating Knowledge Graphs With Robust Fairifcation Pipelines, Kyle R. Henrikson, Van D. Tran, Meredith Francis, Isabella Giammattei, Quynh D. Tran, Laura S. Bruckman, Erika I. Barcelos, Roger H. French

Student Scholarship

Combining data from multiple sources is crucial for efficient knowledge aggregation in materials data science. FAIR data from ontology and Linked Data principles enable this. Semantic data management streamlines data exchange and aggregation, ensuring information is available and extractable. FAIRLinked and GraphDB provide solutions for consolidating, hosting, and extracting meaningful insight from multimodal data.

Developing Pattern Recognition And Interpretable Convolutional Neural Network Based Frameworks For Identifying Drug Resistant And Pan Cancer Mirnas From Expression Data, Joginder Jsingh

Doctoral Theses

Micro Ribonucleic Acids (miRNAs) are short length (∼24) non-coding RNAs and are considered as key biomarkers in cancer diagnosis and treatment. They play a vital role in classifying cancer patients from normal ones and drug resistant patients from control ones. The control patients are those who have not received any drug for cancer treatment. The objective is to identify a subset of miRNAs those help in the classification of the patients using expression data. The thesis is comprised of four contributory chapters in addition to an introduction and conclusion. In the first two contributory chapters, computational methods for ranking and …

Butte Medical Monitoring Working Group Meeting, Mike Mcanulty, Eric Hassler

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Determination Of Sample Size In Vaccine Trials, Meghna Bose

Doctoral Theses

Sample size determination is an important as well as delicate problem in clinical trials. Often, prior information available before the beginning of the trial is used to estimate the sample size. Hence, it is of importance to quantify the prior information available in terms of an Effective Sample Size (ESS). The problem of finding Effective Sample Size (ESS) in Phase II clinical trials, where toxicity and efficacy are the two components of the treatment response vector, is considered. In particular, one of the components is assumed to be binary, and the other is assumed to be continuous. Theoretical expressions for …

Livestreaming A Doitocracy: Platform-Jumping Participatory Practices In Modular Synthesis Gear Cultures, Eliot Bates

Publications and Research

Earth Modular Society (EMS) is a cross-platform community dedicated to live hardware modular synthesis, with their primary efforts going into a 24/7 modular “radio station” that livestreams on Twitch and YouTube, and a supporting Discord chat server. Although part of the broader modular synthesis gear culture (a large-scale social formation that coalesces around specific classes of fetishized technical objects), EMS represents a new development in gear cultures as it foregrounds live performance and minimizes the accrual of status via conspicuous consumption. The normative governance structures of platform-specific gear culture communities preclude all but one or a handful of users from …

Electronic Encyclopedia Of Traditional Medicinal Plants At The Museum Pusaka Nias As Supporting Media For Students’ Plant Awareness, Ester Novi Kurnia Zebua, Siti Zubaidah, Sitoresmi Prabaningtyas

Jurnal Pendidikan: Teori, Penelitian, dan Pengembangan

Low student awareness of the existence, diversity, and importance of plants in daily life—referred to as plant awareness, which includes attention, attitudes, relative interest, and knowledge toward plants—remains a challenge in biology learning, partly due to the limited use of electronic learning media that integrate biodiversity with local wisdom or indigenous knowledge. Traditional medicinal plants from the Museum Pusaka Nias have strong potential as contextual learning resources; however, they have not been optimally developed in electronic form. This study aimed to develop an electronic encyclopedia of Nias traditional medicinal plants for high school biology learning and to examine students' plant …

Development Of A Structured Inquiry-Based Heat Transfer E-Module To Encourage Elementary School Students' Critical Thinking Skills, Chintia M. P Ati, Alvin J. Hano

Jurnal Pendidikan: Teori, Penelitian, dan Pengembangan

The study is undermanned by the students' lack of critical thinking skills and the lack of digital learning media. The purpose of the study is to produce credible, pragmatic, and effective e-modules to improve critical v-grade thinking skills. The study USES model development methods Lee and Owens, 2004. The 36 student classes vs. SDN oesapa small 2 mussels are traveling in kalor transfer content during the full term of year 2021-2022. Analysis shows that an e-module effectively enhances the student's critical thinking skills. Critical n-gain thinking skills by 0.7201. The conclusion that structured e-modules effectively promote critical thinking skills. This …

Beyond Beltway And Bible Belt: Re-Imagining The Democratic Party And The American Left, Ben Agger

Fast Capitalism

No abstract provided.

Valuable Objects And Their Differentiation In Social Space And Time, Emmanuel Smikun

Fast Capitalism

No abstract provided.

Timescapes Of The Network Society, Robert Hassan

Fast Capitalism

Since the late ‘70s, the mutually reinforcing interaction between neoliberal economics and the revolution in information and communication technologies (ICTs) has transformed the world in many ways. “Globalization” is what we have come to call this process, and many aspects of its profound effect have been analyzed from a range of perspectives (e.g. Appadurai 1990; Robertson 1993; Omahe 1993; Waters 1995; Bauman 1998; Steger 2003). This paper discusses a central element of this change through globalization that has so far received relatively little attention—our relationship with time and how this is changing, in turn, the nature of power and politics. …

Climate Change Deniers Versus Climate Change Decriers: The Pragmatics Of Climate Defense In The Age Of Disinformation, Timothy W. Luke

Fast Capitalism

Thirty-five years ago, Bill McKibben published his best-selling popular depiction of climate change, The End of Nature. Nearly a decade ago, Naomi Klein's global best-seller This Changes Everything: Capitalism vs. The Climate presented her detailed brief: “thought leaders” must resist and reverse the degradation of Earth's climate in the face of denials that this policy change was impossible. As popular activists, McKibben and Klein both believe “more information leads to good and great change.” This gambit presumes when presented disturbing facts on how and why rising fossil fuel use is degrading the climate, like-minded readers will wisely rise, readily organize …

A Capitalist Stranglehold On “Artificial Intelligence”: A Gallop Through Piracy, Privacy Invasion, Lock-In And A Fever Dream Of Democratisation, Aidan Cornelius-Bell

Fast Capitalism

In this paper, I discuss the emergence of personal computing, the rise of platform-controlled smartphones and tablets, and the recent surge in artificial intelligence technologies. I explore how these technological advancements have often been shaped by the interests of capital, with recent trends towards increased platform lock-in, control, and exploitation of users (workers). I argue that without a strong push for open-source, democratised AI, these technologies risk being used to further the globalised colonial capitalist project. I highlight the potential for open-source hardware and software to counter the proprietary and un-hackable future of AI, offering a radical alternative that empowers …

Threads Of Empathy: An Integrative Model Of Empathy In The Schools, Arthur J. Clark, Tara M. Simpson

Journal of Human Services Scholarship and Interprofessional Collaboration

Empathy has a distinctive and evolving history in education for cultivating human relationships and engendering mutual understanding. Within a school setting, empathic engagement is essential for the social and emotional development of children and adolescents. From an educational perspective, literature from multiple disciplines and specialties illustrate innovative practices to harness empathy in the classroom and beyond. The representative initiatives hold promise for developing an integrative model of empathy within a school or a school district through a program involving interprofessional collaboration.