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(SI15-120) Exploring Fractional Difference Equations and their Applications with Mahgoub-Transform
No full textWe discuss the introduction and study of the nabla discrete Mahgoub transform along with its defining properties. The transform of fractional sums and fractional differences are derived, demonstrating the applicability of the transform from the computational viewpoint. Employing the transform, fractional difference equations with initial value problems are solved, thereby enhancing the knowledge of their closed forms. As a side-effect of the Mahgoub-transforms, an attractive connection is established, showing that the discrete Mittag-Leffler function acts as the eigenfunction for the Caputo-type fractional difference operator nabla. These results strengthen the core basis for fractional calculus and herald industrial applications in various science and engineering fields
Protecting The Poor: Financial Distress In Credit Unions
No full textCredit unions are essential to financial inclusion, particularly in underserved communities; however, they face increasing instability, closures, and consolidations. Traditional corporate bankruptcy models, such as the Altman Z-Score, were designed for profit-driven firms and do not adequately account for the nonprofit, member-owned structure of credit unions. As a result, they overlook both the financial and governance dynamics that shape credit union performance. This dissertation addressed that gap by examining the financial indicators that are most useful for identifying early signs of distress, while interpreting those indicators through the lens of Agency Theory.
Drawing on longitudinal data from the National Credit Union Administration (NCUA) from 2013 to 2024, this study analyzed both financial and governance-related indicators, including capital adequacy, asset quality, liquidity, lending practices, earnings, and operational efficiency. Statistical procedures, such as multicollinearity testing, logistic regression, and discriminant analysis, are applied to isolate the most reliable measures.
The findings highlight ratios such as the loan-to-share ratio, short-term shares ratio, average loan size, and operational expense ratios as significant indicators of financial distress. Importantly, these measures are not only financial markers but also reflect agency-related governance issues, such as weak cost control, risk-prone lending, or excessive managerial conservatism. These measures are useful for both managers to evaluate the financial health of their credit unions and for current and prospective members to make informed decisions about their future actions with the credit unions.
This research contributes to the limited literature on credit union distress in several ways. It demonstrates how financial indicators can serve as early warning signs when interpreted in conjunction with Agency Theory. It also provides practical insights for regulators and managers seeking to enhance oversight and safeguard community-based financial institutions, which are crucial to financial inclusion
Mechanical Property And Thermal Stability Characterization Of Additively Manufactured Chicken Feather Fiber/Polybutylene Succinate (PBS) Green Composites And In-Situ Pore Detection From FDM 3d Printing Videos
No full textThe poultry industry generates millions of tons of chicken feathers annually, most of which are underutilized and discarded as waste materials. Chicken feather fiber (CFF), primarily composed of keratin, possesses low density, biodegradability, and favorable mechanical properties, making it a promising reinforcement for sustainable composite materials. This research primarily focused on developing sustainable bio-composites using poultry waste, chicken feather fiber, and biodegradable polymers, specifically Polybutylene Succinate (PBS), for additive manufacturing applications. Composite filaments of varying fiber loadings (0.5, 1, and 2 wt%) were produced through filament extrusion and processed into test specimens using fused deposition modeling (FDM).
Mechanical properties were examined by performing tensile and flexural measurements, yield behavior evaluation, and elastic modulus assessment.Microstructural features were observed through SEM imaging and optical analysis using a Motic digital microscope. TGA testing was carried out to evaluate the thermal behavior of the materials. In addition to material characterization, this study also integrated a computer vision approach for automated pore detection during the FDM process, enhancing in-situ monitoring capabilities.
Results indicated that incorporating CFF led to slight reductions in tensile strength but showed improvements in stiffness and partial recovery of flexural properties at higher fiber contents. Notably, the 0.2% offset yield strength exhibited a noticeable improvement when 0.5 wt% carbon fiber filler (CFF) was incorporated, suggesting a greater resistance to the initiation of plastic deformation, even at a relatively low fiber concentration. SEM and optical microscopic analysis provided regular fiber dispersion and satisfactory interfacial adhesion within the PBS matrix. TGA analysis indicated an increase in the initial degradation temperature and a delay in decomposition for CFF-reinforced PBS composites compared to pure PBS. The computer vision model successfully identified pores in the printing videos, indicating its usefulness for real-time quality monitoring.
Overall, this work shows that CFF can be effectively used as a reinforcement for biodegradable PBS in 3D printing applications, thereby addressing poultry waste management while advancing sustainable material development. For future research, it is recommended that continuous or long-fiber reinforcement systems be investigated, as these may significantly enhance mechanical properties, particularly in biomedical or structural load-bearing applications.
Index Terms - 3D printing filament, chicken feather fiber (CFF), computer vision, filament extrusion, mechanical properties, polybutylene succinate (PBS), thermal stability
Machine Learning-Based Detection Of Covert Data Exfiltration Via Electromagnetic Side-Channel Emissions From Computer Memory In Air-Gapped Systems
No full textAir-gapped computer systems are physically isolated from unsecured networks. Though isolated, they remain vulnerable to covert data exfiltration via electromagnetic side channels and other covert-channel attacks. This research presents a comprehensive approach to detecting electromagnetic data exfiltration by establishing a controlled laboratory environment using low-cost, readily available hardware components. The study shows a proof-of-concept covert data transmission system that exploits electromagnetic emissions from computer memory access patterns through software-controlled Random Access Memory (RAM) operations.
The research methodology involved developing a C++ transmitter program that modulates CPU and memory-intensive operations to generate detectable electromagnetic signals at 100 MHz frequency, and implementing a Python-based receiver integrated with RTL-SDR (Software Defined Radio) for signal detection and analysis. A methodologically generated dataset containing 1,194 timestamped process metrics was generated with binary classification labels, deliberately sized to ensure proper ground truth quality after rejecting an initial larger dataset that exhibited severe data leakage. The final dataset captures both normal system behavior and periods of active covert transmission, intentionally including realistic operational noise to provide an authentic detection challenge.
Machine learning analysis using Random Forest classification achieved highly successful detection performance with 92.47% accuracy and 98.56% ROC-AUC score. Rigorous validation, including shuffled-label baseline testing (54.60% accuracy, 48.40% ROC-AUC), confirmed the absence of data leakage and validated genuine detection capability. Memory usage patterns exhibited the highest feature importance (0.8475), validating theoretical predictions about memory-based electromagnetic covert channels creating distinctive behavioral signatures.
The findings demonstrate that while electromagnetic covert channels can be successfully implemented using commodity hardware, they are reliably detectable through machine learning-based analysis of standard system behavioral metrics. The study provides significant implications for cybersecurity in air-gapped networks and sensitive computing environments, and contributes a valuable, publicly available dataset for future research in covert channel detection.
Index Terms - air-gap security, covert channels, electromagnetic emissions, machine learning, random forest, rtl-sdr, side-channel attacks
(SI14-12) Some Novel Fractional Discrete Inequalities of Gronwall-Bellman Type and Their Applications to Fractional Difference Equations
Full text linkIn this study, we develop multiple power nonlinear generalizations of Gronwall-Bellman type fractional discrete inequalities and fractional sum inequalities through combining functions with powered unknown functions.We have employed technique of reducing power non-linearity into linearity to furnish these refinements. These novel findings present a broader framework for dealing with wider range of nonlinear fractional difference equations and fractional sum-difference equations. The utilization of these inequalities enables to study certain crucial classes of fractional difference equations that arise in the realm of fractional difference calculus, both quantitatively and qualitatively. Several illustrations are provided to examine the boundedness of initial value problems of fractional difference equations, demonstrating the reliability and effectiveness of our findings
(R2127) On 2-Absorbing Hesitant Primary Fuzzy Ideals of Rings
Full text linkBy presenting 2-absorbing hesitant primary fuzzy ideals, we begin the investigation of a generalisation of hesitant primary fuzzy ideals (HPRFI) in rings in this research. The concepts of a weakly completely 2-absorbing hesitant primary fuzzy ideal (WC2-AHPRFI) and a Weakly completely 2-absorbing hesitant fuzzy ideal (WC2-AHFI) are developed, and their structural features and attributes are examined. We introduce the idea of a 2-absorbing hesitant K-fuzzy ideal (2-AHK-FI), 2-absorbing hesitant K-primary fuzzy ideal (2-AHK-PRFI) and examine a few of its characteristics
Green Synthesis And Characterization Of Fe-Ti Mixed Nanoparticles For Enhanced Lead Removal From Aqueous Solutions
Full text linkHeavy metal contamination in water resources presents a significant environmental and public health challenge, with lead a particular concern due to its toxicity and persistence. This study reports the green synthesis of Fe-Ti mixed oxide nanoparticles (NPs) using dextrose as a green source and investigates their effectiveness in lead removal from aqueous solutions. The synthesized NPs were characterized using XRD, FTIR, XPS, SEM-EDS, and BET analysis, revealing an amorphous structure with a high surface area (292.89 m² g¹) and mesoporous characteristics. XPS analysis confirmed the presence of mixed Fe³⁺/Fe²⁺ valence states in a Ti⁴⁺-rich framework, creating diverse binding sites for lead adsorption. The material exhibited optimal lead removal at pH 5, with adsorption following pseudo-second-order kinetics (R² \u3e 0.99) and a Langmuir isotherm model (R² \u3e 0.98). Maximum adsorption capacity reached 25.10 mg g⁻¹ at 40°C, showing endothermic behavior. The low point of zero charge (0.22) and surface hydroxyl groups enabled efficient lead binding may be through multiple mechanisms. Dose optimization studies established 6 g L⁻¹ as the optimal adsorbent concentration. The synergistic combination of iron\u27s affinity for heavy metals and titanium\u27s structural stability, coupled with environmentally friendly synthesis, resulted in a promising material for sustainable water treatment applications.
Keywords: Nanoparticles, lead, adsorption, green synthesis, dextrose, heavy metal pollutio
Analysis Of Antioxidant Capacity In Storage Roots From Some F2 Progenies Of A Sweetpotato (Ipomoea Batatas (L.) Lam) Segregating Population
No full textSweetpotato (Ipomoea batatas [L.] Lam) is a globally important crop known for its high yield, adaptability, and rich nutritional profile. Sweetpotatoes are especially high in β-carotene, a provitamin A carotenoid that is vital for vision, immune function, and skin health, making them effective in combating vitamin A deficiency in vulnerable populations. Purple-fleshed sweetpotatoes are particularly recognized for their very rich antioxidant nutrition, which includes significantly high levels of phenolic compounds such as many types of phenolic acids, flavonoids, and anthocyanins. Regular consumption of sweetpotato has been associated with reduced risks of chronic diseases such as cardiovascular disease, type 2 diabetes, and certain cancers. Its low glycemic index also supports better blood sugar regulation, making it a suitable dietary component for individuals with diabetes. This research was focused on determining the dry matter, anthocyanin, and total flavonoid contents, and the total antioxidant capacity in sweetpotatoes of 126 selected progenies of an F2 segregating population using high-throughput colorimetric assays. Statistical analyses of the phenotyping data revealed: 1. The dry matter and anthocyanin contents in sweetpotatoes of the selected F2 progenies
were not tightly correlated; 2. The contributions of anthocyanins or total flavonoids to the total antioxidant capacity in sweetpotatoes were limited. These results suggest: 1. The genetic factors regulating the dry matter and anthocyanin contents in sweetpotatoes may not be tightly linked as previously hypothesized; 2. Biochemical components other than anthocyanins and flavonoids may have a larger contribution to the total antioxidant capacity in sweetpotatoes. The findings are expected to provide useful information to the breeding program, aiding in developing high-antioxidant sweetpotato varieties.
Keywords: anthocyanin, antioxidant, flavonoids, phenolic compound, and sweetpotato
(SI15-010) On Perturbations of Gabor Frames
No full textStability plays a crucial role in frame theory and its applications. The present paper studies the interaction between Gabor frames and perturbations, presenting perturbation results related to small changes of the frame parameters and the window functions both in regular and irregular settings. Examples are provided for illustration. Additionally, the paper briefly discusses algorithms pertinent to Gabor frames under perturbations and highlights challenging areas in the field
(SI15-093) Dynamics of the Generalized Nonlinear Schrödinger Equation with a Source using an Analytical Method
No full textIn the present article, an analytical method is used to obtain hyperbolic, trigonometric, and rational solutions of the generalized nonlinear Schrödinger (GNLS) equation with a source. The ability of solitons to preserve their shapes during propagation makes them suitable for optical fiber communication. Solutions to the generalized nonlinear Schrödinger equation with a source can also describe solitons, and understanding their dynamics helps to design communication systems based on solitons. The analytical method used is compelling and effective for finding exact solutions to various nonlinear evolution equations (NLEEs). To further understand the phenomena, we create 3−D, contour, and 2−D graphs of a few obtained solutions