Digital Commons Network^™

A Deep Learning Model For Accurate Tomato Leaf Disease Identification, Maheen Shahzad, Muhammad Abdullah Javed, Erum Ashraf, Hafiz Ishfaq Ahmad, Sabeen Masood

Turkish Journal of Electrical Engineering and Computer Sciences

Recent advances in machine learning and deep learning have greatly improved how we detect plant diseases, making diagnoses more accurate, faster, and easier to scale. However, many existing solutions depend on large, pretrained models that need powerful hardware, which limits their use in the field, especially in areas with limited resources. To tackle this, we designed a custom lightweight convolutional neural network (CNN) built from scratch using 20,000 carefully selected images from the PlantVillage tomato dataset. Our model uses Squeeze-and-Excitation (SE) blocks and Swish activation functions to boost performance, reaching an accuracy of 97.7% while using far fewer computing resources …

Influence Of Sinr And Noise Variance On Outage Probability For Mimo-Noma System In 5g And Beyond, Sadiq Ur Rehman, Jawwad Ahmed, Muhammad Zubair, Syed Sajjad Hussain Rizvi

Turkish Journal of Electrical Engineering and Computer Sciences

Nonorthogonal multiple access (NOMA) communication presents a promising solution to the limitations of traditional orthogonal multiple access techniques, offering potential improvements in achievable rates. Multiple-input multiple-output (MIMO), when combined with NOMA (MIMO-NOMA), further enhances these benefits by leveraging the diversity advantages of multiple antennas. Looking ahead, the future of wireless communication hinges on deploying heterogeneous networks (HetNets), facilitating the coexistence of various wireless access networks in a hierarchical fashion. However, the advent of 5G and 6G communications brings shorter channel coherence times, rendering channel reciprocity unreliable. Consequently, conventional channel estimation methods relying on uplink (UL) pilots for downlink (DL) transmission …

A Novel Approach To Maximum Weighted Traffic Flow Method For Effective Signal Control, Zülal Hi̇lal Yildiz Budak, Seyi̇t Alperen Çeltek, Aki̇f Durdu

Turkish Journal of Electrical Engineering and Computer Sciences

Traffic signal management is a critical challenge due to its environmental, economic, and public health impacts. The maximum weighted flow method (MaxWeightedFlow) was developed to optimize traffic flow at isolated and coordinated urban intersections. This study proposes a new method, the novel MaxWeightedFlow, which includes two key strategies to enhance the classical approach. The first strategy reduces computational burden by estimating vehicle approach times based on instantaneous speeds, improving real-time performance. The second employs regression analysis to optimize the alpha parameter, representing the vehicle waiting coefficient. The proposed approach, the novel MaxWeightedFlow, was evaluated using real-world traffic data from Kilis, …

Improving Rail System Signaling Efficiency Through Ai-Based Driving Profile Generation: A Comparative Performance Analysis, Mehmet Taci̇ddi̇n Akçay, Abdurrahi̇m Akgündoğdu

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, a dataset comprising 3600 discrete operational snapshots (rather than continuous time-series data) derived from real-field operations is used to obtain a high-accuracy driving profile equation using a second-degree Polynomial Regression method. This equation demonstrates the model’s interpretability. The performance metrics obtained with the second-degree polynomial regression model’s equation are as follows: a coefficient of determination (R2) of 0.84, a Pearson Correlation Coefficient of 0.91, and an RMSE of 11.13. These results indicate the effectiveness of artificial intelligence-based approaches in improving the efficiency of the railway signaling system. The same dataset is also utilized with other machine learning …

Coastal Conservation And Blue Carbon: Willingness To Pay For Changes To Nearshore Management In Oregon, Arthur Caplan, Marcelo Pignatari, Sarah Klain, Kreg Lindberg

Browse all Datasets

This paper reports results from a discrete choice experiment conducted with Oregon residents regarding possible policy changes in spatial management of nearshore habitat. We evaluate public preferences across several policy scenarios, each characterized by varying levels of marine reserve size (bounded areas where extractive activities are prohibited), coastal jobs generated or lost, and carbon sequestration by seagrass beds, tidal marshes and kelp forests(blue carbon habitat expansion), with models estimated in both utility and willingness to pay (WTP) space. Each of these attributes across all models displays positive, monotonic marginal WTP. Scenario analysis reveals that an “optimistic” policy package (+50 % …

Distribution System Reliability Evaluation Considering Protection Coordination Using Petri Nets, Rani Kumari, Bhukya Krishna Naick

Turkish Journal of Electrical Engineering and Computer Sciences

Maintaining reliable and high-quality power delivery becomes increasingly complex with expanding power grids. The lack of protection coordination poses a significant threat, compromising overall system reliability. This research addresses this challenge by proposing a method for coordinating protective devices within the distribution system, specifically during network faults. The proposed approach utilizes a stochastic timed Petri net (STPN) based methodology to model protective device coordination across various fault scenarios. This technique effectively captures the dynamic behavior and interactions of protective equipment, allowing for the anticipation of potential disturbances. This proactive insight facilitates preventative measures to address prewarning situations, thereby preventing cascading …

Proposed Methodology For Correcting Fourier-Transform Infrared Spectroscopy Field-Of-View Scene-Change Artifacts, Kody A. Wilson, Michael L. Dexter, Benjamin F. Akers, Anthony L. Franz

Faculty Publications

Fourier-transform spectrometers are widely used for spectral measurements. Changes in the field of view during measurement introduce oscillations into the measured spectra known as scene-change artifacts. Field-of-view changes also introduce uncertainty about which target the measured spectrum represents. Though scene-change artifacts are often present in dynamic data, their significance is disputed in the current literature. This work presents a theoretical framework and experimental validation for scene-change artifacts. Field-of-view changes introduce variable interferogram offsets, which standard processing techniques assume are constant. The error between the interferogram offset and its estimate is Fourier-transformed, yielding scene-change artifacts, often confused with noise, in the …

Analysis Of A Few Quantum Algorithms And Circuits Related To Boolean Functions, Suman Dutta

Doctoral Theses

Boolean functions are fundamental to computation and presently play a crucial role in quantum information processing. This thesis presents two facets of Boolean functions in the context of quantum computing: (I) extending and applying the theoretical framework of Forrelation to cryptographic analysis, and (II) designing efficient quantum circuits for multi-controlled Toffoli gates and Boolean circuit implementations. Given two Boolean functions $f$ and $g$, Forrelation, introduced by Aaronson (2010), measures the correlation between the truth table of $f$ and the Walsh-Hadamard transform of $g$ at the corresponding points. Here, we revisit the Forrelation framework to study several cryptographically significant spectra of …

Combinatorial & Algebraic Approaches In Analyzing Mutually Unbiased Bases (Mubs) And Their Approximations, Rakesh Kumar

Doctoral Theses

Mutually Unbiased Bases (MUBs) are an important concept in quantum information theory. Two orthonormal bases in a $d$-dimensional complex Hilbert space $\mathbb{C}^d$ are said to be mutually unbiased if the absolute value of the inner product between any pair of vectors, one from each basis, is $1/\sqrt{d}$. A set of $r$ orthonormal bases is called mutually unbiased if every pair of bases in the set is unbiased. It is known that at most $d + 1$ mutually unbiased bases can exist in $\mathbb{C}^d$, and a set achieving this bound is termed a \emph{complete sets of MUBs} in $\mathbb{C}^d$. We can …

Pythagorean Neutrosophic Mathematical Modelling, M. Kavitha, R. Irene Hepzibah

Neutrosophic Systems with Applications

Survey-based assessments often suffer from ambiguity, inconsistency, and uncertainty, which weaken the reliability of decision-making outcomes. To address these challenges, this study proposes a novel decision-support framework for data fuzzification, ranking, and agility measurement using Pythagorean Neutrosophic Fuzzy Sets (PNFS). The proposed method offers three major advantages: (i) enhanced ability to capture high levels of indeterminacy compared with classical fuzzy and intuitionistic models, (ii) improved ranking accuracy through a newly developed score function and ranking algorithm, and (iii) greater robustness in scenarios involving conflicting, incomplete, or imprecise expert judgments. The framework includes a refined Pythagorean Neutrosophic fuzzification technique, mathematically supported …

Neutrosophic Hankel Transforms And Their Application To Cross-Domain Legislative Integration, Mona Gharib, Mehboob Ali, Ishtiaq Hussain

Neutrosophic Systems with Applications

This paper introduces the Neutrosophic Hankel Transform (NHT) as a novel mathematical framework for modeling systems with radial structure under uncertainty, indeterminacy, and inconsistency. Building upon classical Hankel transforms and neutrosophic logic, we define two complementary realizations: a componentwise transform (NHT–C) that transports uncertainty with the signal, and a kernel-weighted transform (NHT–K) that embeds neutrosophic weights into the integral kernel. We establish linearity, inversion, and Parseval-type relations, and derive operational rules that diagonalize the Bessel radial operator.

To demonstrate utility, we formulate a radial diffusion–reaction model for pollutant concentration in a radialized river cross-section and solve it in closed form …

From Uncertainty To Lucidity: Awareness Neutrosophic Kähler-Einstein Innovative Evaluator Methodological In Era Of Green Artificial Intelligence, Mona Mohamed, Ahmed M. Ali

Neutrosophic Systems with Applications

The rapid development of generative artificial intelligence (Gen AI) is a double-edged sword. On the positive side, Large Language Models (LLMs) of Gen AI as chatbot considered intelligent friend. Due to its potential to stimulate the maturation of ideas and cultivate fundamental general abilities like problem-solving and critical thinking. The advancement of Gen AI continued after that, moving from “chatbots” to “AI agents” that carry out multi-step activities in addition to responding to queries.

Regarding the downside, the terminology of “Red AI” era brought about by generative AI is marked by a performance at any expense that puts pressure on …

Single-Valued Neutrosophic Pessimistic Multi-Granulation Rough Set Model Based On (A,B,C)-Cut Relations And Its Applications, Xu-Xi Wu, Hu Zhao, Qiao-Ling Song, Xiong-Wei Zhang

Neutrosophic Systems with Applications

To address uncertainty in multi-source data, this paper proposes a single-valued neutrosophic pessimistic multi-granulation rough set (P-SVN-MGRS) model based on (a,b,c)-cut relations. In this framework, each neutrosophic relation is characterized by three membership-degree functions: T(x,y), I(x,y), and F(x,y). These functions correspond to truth-membership, indeterminacy, and falsity, respectively. The (α,β,γ)-cut relation employs parameters α,β,γ∈(0,1] as thresholds for the three functions. A pair (x,y) belongs to …

Improving Stem Assessments: Strategies For Increasing The Accessibility And Adoption Of Two-Stage Exams, Kristina Callaghan

LSU Doctoral Dissertations

Over three decades of research have shown that students taught using active learning strategies achieve better learning outcomes compared to those taught using traditional methods. Two-stage exams, which pair a traditional exam with a group component, are an increasingly popular method for incorporating active learning within the assessment component of a course. Previous studies have shown this assessment strategy provides a variety of benefits for students, including increased engagement and collaboration, immediate feedback, and potentially increased content retention. However, the unique circumstances of each instructor can pose a non-trivial barrier to the implementation of two-stage exams. In this thesis, we …

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 …

ℤ3-Graded Cartan Calculus On 𝒪(ℂQ1|1|1), Sultan Çeli̇k, Sali̇h Çeli̇k

Turkish Journal of Mathematics

After a brief introduction of the basic concepts of ℤ₃-grading, the paper continues by introducing ℤ₃-graded differential calculus and ℤ₃-graded Cartan calculus. Then, using a matrix R which is a solution of the Yang-Baxter equation, a new ℤ₃-graded quantum group and a ℤ₃-graded quantum space are introduced. The scheme of the ℤ₃-graded differential calculus developed on the algebra of functions on this quantum space is extended to the ℤ₃-graded Cartan calculus and all the results obtained are formulated using the matrix R.

G-Topological Groupoids, Osman Mucuk

Turkish Journal of Mathematics

In the groupoid theory, it is unclear that a topological groupoid's quotient groupoid with the quotient topology is topological.  In this paper, we approach this problem considering  G-methods and G-convergence. We define  G-topological groupoid, which agrees with the sequential version of a topological groupoid in the particular case G=lim, and give some counterexamples. Then, we extend the usual properties of topological groupoids to the G-topological groupoids. We also prove that a G-topological groupoid's quotient groupoid is  G-topological groupoid when a normal subgroupoid is suitably chosen. This result enables us to obtain examples of topological quotient groupoids in a particular case.

The Variation Of Eigenvalues Of The Two-Dimensional Magnetic Schrödinger Operator With Respect To The Angle Of A Flat Sector, Araz R. Aliev, Elshad H. Eyvazov

Turkish Journal of Mathematics

A two-dimensional Schrödinger operator with a spherically symmetric electric potential and an Aharonov Bohm magnetic field in a circular sector under Neumann boundary conditions is considered. The intervals of the angular variation of the flat region are found, where the eigenvalues of the Neumann problem for the Schrödinger operator with a spherically symmetric electric potential strictly decrease monotonically in the Aharonov-Bohm magnetic field.

Further Geometric Properties Of The Generalized K-Bessel Functions, Merve Görgülü, İbrahi̇m Aktaş

Turkish Journal of Mathematics

This study investigates certain geometric properties of the normalized k-Bessel function, which is a natural generalization of classical and modified Bessel functions of the first kind. These geometric properties include η-starlikeness, η-uniform convexity, starlikeness associated with exponential function and Bernoulli’s lemniscate, and convexity associated with exponential function and Bernoulli’s lemniscate. Moreover, certain corollaries related to classical and modified Bessel functions are presented by specialising parameters. In addition, some examples and their graphical representations are provided to support the findings of this study.

Some Methods For Finding The Number Of Partitions Of N With M−Parts, P(N, M), Yusuf Soyvural, Ali̇ Bülent Eki̇n

Turkish Journal of Mathematics

P(n, m) denotes the number of partitions of n with m parts, while P_m(n) denotes the number of partitions of n with parts at most m. It is a well-known result that the number of partitions of n ≥ 0 into m or fewer parts is equal to P_m(n). In the literature, there are some results for P(n, m) and P_m(n) for some values of m. In this work, we give more compact results for P(n …

On Almost Kenmotsu Manifolds Admitting Nearly Vacuum Static Equations With Applications, Uday Chand De, Krishnendu De, Sudhakar Kumar Chaubey

Turkish Journal of Mathematics

In this article, we study certain characteristics of nearly vacuum static equations on almost Kenmotsu manifolds. It is established that an η-Einstein almost Kenmotsu manifold allowing nearly vacuum static equations is of constant scalar curvature and either the solution is trivial or, the manifold reduces to an Einstein manifold. Next,  nearly vacuum static equations on (κ,μ)-almost Kenmotsu manifolds and generalized (κ,μ)'-nullity distribution are considered and we obtain several interesting results. Moreover, we illustrate that if a 3-dimensional Kenmotsu manifold allows nearly vacuum static equations, then the manifold is locally isometric to the hyperbolic space Η3(-1). After that, we investigate a …

Fubini Collocation Method For Numerical Solutions Of Differential Equations With Quadratic And Cubic Nonlinearities, Kübra Erdem Bi̇çer, Havva Türkhan

Turkish Journal of Mathematics

In this study, the Fubini collocation method is proposed for the approximate solution of nonlinear differential equations. The method utilizes fundamental relations involving Fubini polynomials and their derivatives, employing collocation points to enhance solution accuracy. Within this framework, the given differential equation is transformed into a system of nonlinear algebraic equations involving the unknown coefficients of the approximate solution. This resulting system is then solved using appropriate numerical techniques to obtain the approximate solution. The effectiveness of the proposed method is demonstrated through several test problems, with accuracy evaluated using absolute error functions. Furthermore, illustrative examples and residual-based error analysis …

The Derivative Of Spectral Function Of The Problem With The Boundary Condition Dependent On Spectral Parameter, Eli̇f Başkaya, Haskiz Coşkun

Turkish Journal of Mathematics

In this study, the computation of the derivative of the spectral function for Sturm-Liouville problem with eigenvalue dependent boundary condition at the finite left end is considered.

Representation Of Inverse Ordered Semigroups By Means Of Symmetric Inverse Semigroups On A Set, Michael Tsingelis

Turkish Journal of Mathematics

A partial one-to-one mapping on a set X is a mapping whose domain is a subset of X. The set of partial one-one mappings on a set X is an inverse semigroup (the symmetric inverse semigroup on X). An element x of an ordered semigroup (S, ·, ≤) is called an inverse element of α ∈ S if α ≤ xαx and x ≤ xαx. An inverse ordered semigroup is an ordered semigroup S for which every element of S possesses an inverse element and the inverse elements of any element of S are in …

Cospectrality Results For Signed Graphs With Two Eigenvalues Unequal To ±1, Willem H. Haemers, Hati̇ce Topcu

Turkish Journal of Mathematics

Recently the collection G of all signed graphs for which the adjacency matrix has all but at most two eigenvalues equal to ±1 has been determined. Here we investigate G for cospectral pairs, and for signed graphs determined by their spectrum (up to switching). If the order is at most 20, the outcome is presented in a clear table. If the spectrum is symmetric we find all signed graphs in G determined by their spectrum, and we obtain all signed graphs cospectral with the bipartite double of the complete graph. In addition we determine all signed graphs cospectral with the …

Protocol For The Development Of The Who Gestational Weight Gain Charts, Thais Rangel Bousquet Carrilho, Olufemi Taiwo Oladapo, Jennifer A. Hutcheon, Giovanna Gatica-Domínquez, Kathleen M. Rasmussen, Monica C. Flores-Urrutia, Richard Kumapley, Ӧzge Tunçalp, Dang Bahya-Batinda, Amel A. Fayed, Annick Bogaerts, Aris T. Papageorghiou, Cinthya Muñoz-Manrique, Dayana Rodrigues Farias, Eric Ohuma, Harshpal Sachdev, Hayfaa A. Wahabi, Helena J. Teede, Molin Wang, Nandita Perumal Phd

Faculty Publications

Introduction Gestational weight gain (GWG) is an important indicator of maternal nutrition to be monitored during pregnancy. However, there is no evidence-based tool that can be used to monitor it across all geographic locations and pre-pregnancy body mass index (BMI) categories. The WHO is undertaking a project to develop GWG charts by pre-pregnancy BMI category, and to identify GWG ranges associated with the lowest risks of adverse maternal and infant outcomes. This protocol describes all the steps that will be used to accomplish the development of these GWG charts.

Methods and analysis This project will involve the analysis of individual …

Codazzi Normalized Null Hypersurfaces, Théophile Kemajou Mbiakop, Cyriaque Atindogbe, Ferdinand Ngakeu

Turkish Journal of Mathematics

We introduce a class of null hypersurfaces of Lorentzian manifolds, namely Codazzi normalized null hyper surfaces, whose (screen) shape operator associated with the rigged vector field is a Codazzi tensor. Several examples are given to support our study. Moreover, we investigate conditions implying that the induced Riemannian screen structure on a Codazzi-type normalized null hypersurface of a Lorentzian space is locally a nontrivial warped product.

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 …

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

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Design Of Nanomaterial-Based Sensors For Enhanced Halogen Bonding, Ben H. Edelman, Charles W. Sheppard, Lucas A. Chuidian, Arielle Vinnikov, Felix Bevc, Lillian B. Hughes, Carol A. Parish, Michael C. Leopold

Chemistry Faculty Publications

Halogen bonding is a highly directional, noncovalent, intermolecular interaction which has been harnessed for a variety of applications, including sensor design. A halogen bond (XB) is formed between a region of positive electrostatic potential on a halogen atom (X) and electron rich portions of target molecules. The strength of XB interactions relies on shorter XB bond distances and more linear R–X···B bond angles, which facilitate stronger, more negative binding energies. While prior studies have sought to maximize interactions, few have explored or experimentally demonstrated how geometries and bond angles can enhance XB interactions. Herein, fundamental studies are conducted at self-assembled …