Digital Commons Network^™

Sustainable – Low-Cost - Upgrade Of Activated Sludge Process For Nitrogen And Phosphorus (N&P) Removal From Wastewater, Abanoub N. Basta

Theses and Dissertations

Many municipal wastewater treatment plants (WWTPs) in developing countries were designed primarily for organic matter and suspended solids removal and therefore face increasing difficulty in meeting modern nitrogen (N) and phosphorus (P) discharge requirements. Conventional biological nutrient removal upgrades commonly require additional reactor volume, recirculation systems, aeration energy, and capital investment. Accordingly, sustainable retrofit strategies that improve nutrient removal within existing treatment footprints are increasingly needed, particularly in water-scarce and land-constrained regions.

This study investigated the integration of water hyacinth (Eichhornia crassipes) into the aeration stage of an activated sludge process as a hybrid nature-based enhancement for nitrogen and phosphorus …

Port And Vessel Communication Traffic Intrusion Detection: A Variational Autoencoder‑Enhanced Multilayer Perceptron Approach, Chien-Lin Chiang, Hsien-Cheng Chou, Ming-Yuan Peng, Yi-Yuan Chiang, Yu-Shun Liu

Journal of Marine Science and Technology–Taiwan

Port and vessel networks increasingly operate on IP/Ethernet backbones with high‑noise, high‑dimensional traffic. We present a lightweight hybrid intrusion‑detection model that couples a variational autoencoder (VAE) with a multilayer perceptron (MLP) and augments training with a boundary‑oriented latent‑space mixup strategy. The VAE models the distribution of normal traffic and identifies anomalies through reconstruction errors. Subsequently, it generates robust latent vectors, enabling the MLP to perform highly accurate supervised classification. On the UNSW‑NB15 dataset, the proposed pipeline attains ≥97% accuracy and an outstanding recall of 99.56% in binary intrusion detection, and visualization of the latent space (PCA) together with reconstruction‑error analyses …

Sar Ship Detection Based On Shallow Feature Guidance, Chenxu Xia, Peng Chen, Ya Zhang, Ying Li

Journal of Marine Science and Technology–Taiwan

Maritime ship detection is of great significance for both military security and civilian applications. Synthetic Aperture Radar (SAR), with its all-weather and all-day imaging capability, plays a vital role in maritime surveillance. Nevertheless, SAR ship targets typically appear small in scale, embedded in complex backgrounds, blurred at boundaries, and easily confused with near-shore features, which pose substantial challenges for accurate detection. To address these issues, we propose a SAR ship detection network that integrates dual enhancements of small-object representation and edge information. The network introduces two key components: the Small Target Refine Pyramid (STRP) to strengthen shallow feature representation for …

Could 'Real Existing Ai' Be Sentient?, Tim Crane

Animal Sentience

Jonathan Birch is rightly sceptical about the idea that today’s AI machines (e.g. LLMs) are candidates for sentience. Nonetheless, he gives three reasons for taking the future possibility of AI sentience seriously. I dispute them all. Birch fails to distinguish the very idea of an artificial mind from computational AI (what I call ‘Real Existing AI’); he does not adequately distinguish a simulation from a replica or copy; and he fails to acknowledge that the appeal to computational functionalism in this context is straightforwardly question-begging.

Engineering Small-Sized Cations With Strong Solvation For High-Voltage Supercapacitors, Tong Huo, Pan Liu, Hao Chen, Peng Zhang, Zhen-Lei Chen, Guo-Fu Sun, Zhi-Qiang Shi, Jing Wang

Journal of Electrochemistry

Supercapacitors (SCs) have attracted much attention in the field of energy storage due to their high power density and long cycle life. However, their relatively low energy density limits their application in a wider range of fields. Methods to increase energy density include enhancing specific capacitance and extending operating voltage window. Herein, we report a novel electrolyte salt, tetramethylammonium bis(fluorosulfonyl)imide (TMA-FSI), the resulting electrolyte formed with propylene carbonate (PC), designated as TMF, exhibited a wide electrochemical stability window (ESW) of 5.09 V. On the one hand, we found that the small size of TMA⁺ enables it to enter the …

Exploring Conceptions Of Engineering Design And Sustainability In Informal K–12 Engineering Education, Mobina Beheshti, Eunice Y. Kang, Avneet Hira

Journal of Pre-College Engineering Education Research (J-PEER)

In this study we investigate K–12 students’ conceptualizations of sustainability, their perspectives on the role of engineers in sustainable practices, and how augmented reality (AR) can facilitate sustainability-oriented engineering design activities in informal settings. The AR technology used in this study includes the Merge Cube (a physical cube that serves as a digital canvas for AR) and CoSpaces Edu (an online platform that allows students to create 3D models and animate them using code). We employ a design-based research methodology, using qualitative narrative and artifact analysis to address the research questions: (1) What are students’ conceptions of sustainability and the …

Harnessing Nigeria’S Aquaculture And Fisheries Component Of The Blue Economy, B. S. Awe, O. Adeoti

Blue Economy

Nigeria aims to diversify from carbon to blue economy. Target 7 of Goal 14 of the United Nations 2030 Agenda for Sustainable Development, the creation of the Federal Ministry of Marine and Blue Economy, and the passage of the National Policy on Marine and Blue Economy (2025 -2034) in May 2025 are the three frameworks driving this ambition. However, water pollution and changes in climate are central to harnessing the aquaculture and fisheries component of the blue economy. With increasing waste disposal in waterways and waterbodies and decreasing river water flow due to changes in climate, these have implications for …

Safety And Resilience In Disaster Debris Removal And Clean-Up Operations: A Field And Training Guide For Resilience Workers In Disaster Debris Removal And Cleanup, Mohsen Shahandashti, Ph.D, P.E., Abhijit Roy, Ph.D, Zhe Yin, Ph.D, P.E., Pmp, Leed Ap, Antonio Balderrama, Ph.D, P.E., Sandesh Adhikari, Santosh Acharya

Mavs Open Press Open Educational Resources

A practical safety guide for the people who clear debris after disasters, and for the trainers who prepare them. Built for crews of every experience level--from seasoned operators to first-time volunteers--it teaches how to read a damaged site, recognize hidden and shifting hazards, work safely around heavy equipment and hazardous materials, and make sound decisions under pressure. Every chapter pairs clear guidance with a one-page field job aid, facilitator notes for trainers, and a real-world scenario, all grounded in OSHA, FEMA, EPA, and NIOSH guidance.

Safety and Resilience in Disaster Debris Removal and Clean-Up Operations Copyright © 2026 by Mohsen …

Hands-On Ransomware: An Experiential Wannacry Case Study For Undergraduate Cybersecurity Education, Eli Creek Richmond, Thomas R. Devine

Military Cyber Affairs

Ransomware represents one of the most disruptive threats in the cyber landscape, yet hands-on malware analysis remains rare in undergraduate cybersecurity curricula. This paper presents the design, implementation, and evaluation of an experiential learning module centered on the WannaCry ransomware case study, deployed in a senior-level course at West Virginia University. Students performed static and dynamic analysis using industry-standard tools. Pre- and post-module assessments demonstrated measurable gains in self-reported competency across seven technical dimensions. The module's competencies align directly with DoD Cyber Workforce Framework Work Role 212, Cyber Defense Forensics Analyst, supporting education-to-workforce pipeline development.

Hybrid Deep (Cnn-Bilstm) Intrusion Detection For Defense And Mission-Critical Networks, Corey A Cheng, Jermaine Anim-Addo, Asma Jakir Hussain, Zion O Smith-Fox, Sanjay Goel, Yuksel Celik

Military Cyber Affairs

This article examines how hybrid deep learning can strengthen intrusion detection for military and defense networks. Using the CSE-CIC-IDS2018 dataset, the study evaluates a CNN-BiLSTM model designed to detect benign traffic and multiple attack categories, including DDoS, DoS, botnet, brute-force, web attack, and infiltration activity. The model achieved strong multi-class detection performance, with 0.9893 accuracy and 0.9979 ROC-AUC. The findings suggest that AI-supported intrusion detection can improve cyber defense operations, analyst triage, and protection of mission-critical networks.

Comparison Of Gravity Separation And Flotation For Pyrite Recovery From Tailings, Gülay Bulut, Gönül Göksu Gökçe, Dilruba Karamanlı, Oğuzhan Mert Gürkan, Ergin Sarp Zenzirci, Binnur Kırım, Alim Gül

Journal of Sustainable Mining

Tailings generated during the production of lead, zinc, and copper concentrates contain significant amounts of sulfide minerals, particularly pyrite. Pyrite, which remains in tailings after the recovery of other metals, is one of the main contributors to acid mine drainage (AMD). Therefore, recovering pyrite from tailings is environmentally and economically an important issue. In this study, pyrite recovery from tailings was investigated using flotation and gravity separation methods. Mineralogical characterization and liberation analyses were conducted by Mineral Liberation Analysis (MLA), indicating that pyrite is the major sulfide mineral with over 76% liberation degree even in the coarsest fractions. Flotation tests …

Empowering Edge Intelligence Through Reparameterized Lightweight Transformers And Distributed Inference, Hosein Esmaeili, Mohammad Ali Afshar Kazemi, Reza Radfar, Nazanin Pilevari

Turkish Journal of Electrical Engineering and Computer Sciences

Deploying advanced transformer-based models on resource-constrained edge devices remains a significant challenge due to their high memory footprint and substantial compute requirements. In this paper, we propose a reparameterized transformer framework that integrates High-Rank Factorization (HRF) during training, layer merging at inference, and dynamic, load-balanced distributed inference across multiple devices. To further reduce resource usage, our framework supports mixed-precision quantization down to 4-bit, enabling flexible accuracy–latency–energy trade-offs. Experimental evaluations on the ESC-50 environmental sound dataset demonstrate that our method matches or exceeds the performance of larger baseline models while using 20–30% fewer parameters, achieving up to 48% latency reduction in …

Reliable Performance Analysis Of Polyurea Coatings Used In Offshore Wind Turbines, Yu-Chang Lin, Yen-Fu Liu, I-Ming Pan, Ming-Yuan Lin, Kang-Yu Liao, Hung-Hua Sheu, Hung-Bin Lee

Journal of Marine Science and Technology–Taiwan

This study explores the weather resistance, mechanical properties and corrosion resistance of polyurea coatings in marine environments. The relevant analysis results can be used as a reliability assessment of offshore wind turbine structural coatings during their service life under the influence of marine environments. The long-term experiment uses seawater and 70°C thermal aging conditions as coating reliability assessment items. The microstructure of the samples that have been immersed in seawater for a long time and thermally aged is observed using a scanning electron microscope (SEM). The results show that the surface of the 100 and 125 series polyurea coatings is …

Synchronous Deep Reinforcement Learning For Optimized Storage Assignment Of Ship Blocks, Gawon Lee, Jaehyeon Heo, Misung Kim, Hyerim Bae

Journal of Marine Science and Technology–Taiwan

This paper presents a deep reinforcement learning (RL) framework for optimizing block storage allocation in shipbuilding yards. During the shipbuilding process, vessels are constructed in block units to maximize the operational efficiency. Following assembly, these blocks must be stored in limited yard spaces, creating a complex variant of the binary packing problem. This storage allocation problem is further complicated by operational constraints, including the barge capacity and transportation time restrictions. Moreover, poor storage decisions can lead to redundant block movements, which can adversely affect downstream processes and increase operational costs. To resolve this problem, a policy-gradient-based synchronous RL model was …

A Resilience Early Warning Assessment Of The Maritime Supply Chain: A Case Study Of China’S New Energy Vehicle Exports, Xiuqian Chen, Liangyong Chu, Mengyao Wang, Jiayin Du, Yiming Zhang, Xiyao Xu

Journal of Marine Science and Technology–Taiwan

Enhancing resilience through early warning is a critical strategy for mitigating disruption risks in the maritime supply chain (MSC). This study proposes a novel early warning assessment framework to determine the resilience of the MSC. It is referred to as a resilience early warning system. An evaluation index system for shipping enterprises is developed based on four dimensions: withstand capacity, adaptive capacity, learning capability, and the external environment. A resilience assessment model that uses the Bayesian best-worst method (BBWM) and the extension cloud model (ECM) is established to quantify MSC resilience. An early warning evaluation model based on a Bayesian …

Recent Advances In Bioethanol Production From Water Hyacinth: A Critical Review, Umuamina A. Matola, Mahir Mohammed Said, Olga-Ioanna Kalantzi, Abraham K. Temu

Tanzania Journal of Engineering and Technology (TJET)

Water hyacinth (WH) is a highly invasive tropical aquatic weed with high holocellulose and low lignin content, making it a promising lignocellulosic feedstock for second-generation bioethanol production. Producing bioethanol from WH offers a sustainable approach to simultaneously managing invasive biomass and producing renewable energy. This review critically evaluates recent advancements in bioethanol production from WH by examining pretreatment, hydrolysis, and fermentation technologies reported between 2014 and 2024. A PRISMA-guided literature search was conducted using the Scopus and Web of Science databases, and fifty-nine original research articles were selected for analysis. The reviewed studies were comparatively assessed based on pretreatment strategies, …

Hyperlattice-Valued And Superhyperlattice-Valued Uncertain Sets With Decision Applications, Takaaki Fujita, Ajoy Kanti Das, Sankar Prasad Mondal, Arif Mehmood, Arkan Ghaib

Neutrosophic Systems with Applications

Fuzzy set theory enriches classical sets by assigning to each element a graded membership in [0,1], thereby capturing partial inclusion and uncertainty. The notion of an Uncertain Set further abstracts this idea by allowing membership to take values in a general degree-domain, providing a unified language that subsumes fuzzy, intuitionistic fuzzy, neutrosophic, plithogenic, and related models. On the algebraic side, a hyperlattice replaces one lattice operation by a multivalued hyperoperation, enabling the representation of ambiguous or non-deterministic combinations, while a superhyperlattice iterates this structure through powerset lifting to obtain higher-order layers of interaction. Motivated by these developments, we introduce HyperLattice-valued …

A Unified Framework For Neutrosophic Estimation Using Fractional Power, Exponential, And Logarithmic Functions With Bivariate Auxiliary Information, Anchal Yadav, Anuj Yadav

Neutrosophic Systems with Applications

This study develops a generalized neutrosophic ratio-type estimator for estimating the population mean by incorporating information from two auxiliary variables under Simple Random Sampling Without Replacement (SRSWOR). The proposed methodology extends the conventional single-auxiliary-variable approach by jointly incorporating bivariate auxiliary information within the neutrosophic framework, thereby accounting for uncertainty, indeterminacy, and inconsistency in the available information. The bias and mean squared error of the proposed estimator are derived using first-order approximations, and the corresponding efficiency conditions are established through theoretical comparisons with existing neutrosophic estimators. The performance of the proposed estimator is further examined using a real medical dataset represented …

20 Years Of Neutrosophic Statistics: A Bibliometric Analysis, Hammad Khalid, Arshad Hameed

Neutrosophic Systems with Applications

Florentin Smarandache introduced neutrosophic statistics (NS), a formalism for representing uncertainty and indeterminacy in observations, parameters and statistics in an extension to classical and interval statistics. Although widespread in various contexts, such as statistical quality control, hypothesis testing, medical diagnosis, and decision science, and increasingly used and developed, the scientific evolution and conceptual framework of the science of decision making remain largely unexamined. To fill this gap, the present study has been conducted with a comprehensive bibliometric analysis of NS research articles published between 2003 to 2025 from Scopus which has been conducted following the SPAR-4-SLR protocol. In all, 501 …

Artificial Intelligence In Food Engineering For Food Safety, Quality Assurance, And Human Health, Ayad Abbood Abdulhasan, A. M. Mustafa, F. F. Sayyid, Marwan B. Hussein, Mohanad Muzahem Khalaf

AUIQ Technical Engineering Science

Artificial intelligence (AI) is increasingly reshaping food engineering by providing data-driven tools for safeguarding food safety, ensuring quality assurance, and improving human health outcomes. This review synthesizes current evidence on the application of machine learning, deep learning, computer vision, and the Internet of Things (IoT) across the food production continuum, from raw material inspection to consumer-facing nutrition guidance. We examine how convolutional neural networks, hyperspectral imaging, and sensor-fusion approaches enable rapid, non-destructive detection of contaminants and pathogens, and how predictive models support shelf-life estimation and quality grading. We further discuss AI-enabled traceability systems, including blockchain-integrated supply chains, and the growing …

How Do Governments Combat Jihad Online?, Noah Cook

Honors College Theses

Since the September 11th, 2001 attacks, jihadist groups like ISIS, al-Qaeda, and al-Shabaab have used the internet as a tool for recruitment, radicalization, and propaganda dissemination. Since then, governments, non-governmental organizations, and private companies have developed strategies to combat jihadism on the internet. This paper examines how these actors have worked to mitigate the digital jihadist footprint and its effects by analyzing three main approaches to countering violent Islamist extremism on the internet: counter narrative initiatives, awareness-raising programs, and content removals. This paper finds that each of these methods has its own strengths and weaknesses. Counter narrative campaigns show the …

Herding Cubecats: Challenges And Lessons Learned From A Student-Led Cubesat Organization, Matthew Verbryke, Samuel Kohls, Nathan Nguyen, Michael Carovillano, Donghoon Kim

Small Satellite Conference

1. What is CubeCats?

CubeCats is a student-led technical engineering organization founded in 2015 at the University of Cincinnati (UC) with the mission of providing its members with hands-on, educational experience in space systems engineering, primarily through the design, development, testing, launch, and operation of flight-worthy CubeSats and High Altitude Balloons.

CubeCats’ operating model differs significantly from many university-based satellite programs:

• The organization is entirely managed and run by students, the majority of whom are undergraduates (UC faculty and staff serve primarily in an advisory role)
• The organization is entirely volunteer-based, with no direct integration into coursework or on-campus research …

The Effects Of Space On Pharmacology And Traditional Medicine: A Review Of Current Literature And Its Potential Impacts On Space Therapeutics, Pratyush Majumdar

Small Satellite Conference

Astronauts in space commonly take medicine for sleep disorders, muscle aches, and other miscellaneous conditions. These medications are taken under the assumption that they will work in space comparable to their effect on Earth, but mounting evidence is emerging to demonstrate that this is not the case. Using the principles of pharmacokinetics and pharmacodynamics, there are many physiological changes that alter how a drug is processed, changing their therapeutic effect. As mission times get longer, there is a heavier need to understand these changes and compensate for them in order to keep astronauts safe.

Experimental Investigation On Nanocellulose And Aluminium-Oxide Hybrid Nanofluid As A New Coolant For Radiator, D. Ramasamy, Sivaraos Sivaraos, K. Kadirgama

The Nexus of Sustainability and Energy Technology Journal

Improved efficiency leads to more compact design of the radiator. The research is conducted to prove that addition of Aluminium Oxide and nanocellulose originating from plant base with varying concentration provides a better thermal efficiency compared to usage of distilled water as radiator coolant. The objective of the research is to improve a new radiator coolant based on combination of aluminium oxide and nanocellulose with readily available coolants which is Ethylene Glycol and to investigate the erosion of nanocellulose coolant on automotive radiator. The scope of the research are the nanocellulose dispersed in base fluid which is from 60:40, (EG:W). …

Synergistic Reinforcement Of Lignin–Chitosan Hydrogels Using Vanillin As A Sustainable Green Crosslinker, Moses Ayitey-Adjin Jr., Mohammad Jahid Hasan, Jeremy Erb, Kishore Chand, Garry S. Crosson, Kenya Crosson, Esteban Ureña-Benavides, Erick Salvador Vasquez-Guardado

Chemical and Materials Engineering Faculty Publications

While bio-based hydrogels derived from lignin and chitosan are promising sustainable adsorbents, their practical application is hindered by poor mechanical stability. This study addresses this limitation by synthesizing lignin-chitosan hydrogels using vanillin as a green, bio-derived crosslinker via a facile solution-casting method. The formation of imine (Schiff base) linkages between the aldehyde groups of vanillin and the primary amines of chitosan was confirmed by FTIR spectroscopy (C = N stretching at ~ 1602 cm^− 1). SEM and TGA results demonstrated a reduction in the pore size of the crosslinked hydrogel and an enhanced residual thermal mass. Rheological and …

Compact 1 Ghz Electron Paramagnetic Resonance Spectrometers For Preclinical Imaging Studies, Tanden A. Hovey

Electronic Theses and Dissertations

Magnetic resonance is one of the most generally useful scientific techniques. New horizons of understanding are revealed as technological advances make possible explorations of nuclear spins and electron spins at higher and lower magnetic fields and electromagnetic frequencies. While the greatest current effort is on ever higher magnetic fields and microwave frequencies, both in nuclear magnetic resonance (NMR) and electron paramagnetic resonance (EPR), the Eaton lab focusses on developing high signal-to-noise performance EPR at low microwave frequencies. EPR provides information about O2, pH, viscosity, glutathione concentrations, and reactive oxygen species in living organisms that MRI cannot. To yield clinically or …

Improving The Concrete Compressive And Flexural Strength With A Low Fraction Addition Of Carboxylated Nitro-Oxidized Cellulose Nanofibrils From Banana Rachis, Ngesa Ezekiel Mushi, Emmanuel Kagya

Tanzania Journal of Science

Conventionally, concrete strength depends on the bonding interface, especially in hydrated products such as calcium silicate hydrate (CSH). As a result, concrete is sensitive to tensile load. With its unique properties, a low fraction of carboxylated nitro-oxidized cellulose nanofibrils (NOCNF) from the banana rachis is employed to improve the mechanical performance of the concrete nanostructurally. Compressive and flexural strength using the NOCNF content at 0, 0.05, and 0.1 wt.%, cured for 7 and 28 days, were evaluated. Notably, the compressive strength increased by 16 % and the flexural strength by 13 % at 0.1 wt.% NOCNF compared to plain concrete …

Assessment Of The Radionuclide Concentration Levels Of Water And Sediments Along The Mara River, Gasper Kachenge, Abubakary Salama, Abdalah Kileo, Furaha Chuma

Tanzania Journal of Science

For many years, several factors have impacted the water quality of the Mara River, including population growth, agricultural expansion, livestock keeping, mining, and industrial activities. These factors have intensified water pollution and climate change effects around the river. While previous studies have mainly focused on assessing heavy metal pollution risks on the Mara River, this study evaluates the concentration levels of radionuclides in boreholes, water, and sediments along the river and its tributaries. Naturally occurring radioactive materials, including 226Ra, ²³²Th, and ⁴⁰K, were evaluated. A high-purity germanium radiation detector (HPGe) with a coaxial detector system coupled with Gamma Vision software …

Enhancing Algae Biofilm Quantity And Value Through Controlled Light Intensity For Treatment Of Municipal Anaerobic Digestor Effluent, Joshua D. Wintch, Ronald C. Sims

Biological Engineering Student Research

Rotating algae biofilm reactors (RABRs) have been shown to remove nutrients from wastewater and to cultivate algae for bioproducts. Another key variable in RABR technology for cultivating microalgae biomass is light intensity. The goal of this study was to address a gap in the design and operation of algae biofilm reactors by analyzing the effects of light intensity on biomass quality and quantity, chemical precipitation of phosphorus, and phosphorus uptake into biomass. This study utilized a triplicate laboratory-scale experiment with PAR intensities from 10 to 2000 µmol m⁻²·s⁻¹. Municipal wastewater anaerobic digester effluent (ADE) was utilized …

Correlation And Redundancy Analysis Of Statistical Features For Permanent Magnet Synchronous Motor Fault Detection, Ibrahim Muhammad, Benjamin Olabisi Akinloye

Mansoura Engineering Journal

Feature selection plays a critical role in designing efficient and interpretable condition monitoring frameworks for electrical drives. In this paper, a correlation analysis of statistical and spectral features is performed for Permanent Magnet Synchronous Motor (PMSM) fault detection in naval windlass systems. Using both simulated data from a MATLAB/Simulink model and real shipboard current signals acquired from five Nigerian Navy vessels over one-month monitoring periods, higher-order statistical moments (Mean, Variance, Standard Deviation, Skewness, Kurtosis) and the Fault Severity Index (FSI) were computed alongside Total Harmonic Distortion (THD). Pearson correlation coefficients were employed to quantify feature relationships under healthy and faulty …