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Accreditation; Quality assurance; Machine learning; Higher education; Early warning; Nigeria

A Machine-Learning Approach To Predictive Quality Assurance And Accreditation Monitoring In Nigerian Universities

Osemengbe Oyaimare Uddin, Susan Konyeha, Glory Nosa Edegbe

Programme accreditation by the National Universities Commission (NUC) is the main external quality assurance mechanism in Nigerian universities, but it is periodic and retrospective: weaknesses are usually discovered during the visit rather than before it. This study aimed to develop and evaluate a machine-learning (ML) framework that predicts accreditation outcomes from routinely collected pre-visit indicators so that institutions can remediate deficiencies early. Because programme-level accreditation records are not publicly available, we built a reproducible synthetic panel of 4,321 accreditation visits to 1,515 programmes in 149 simulated universities (2014–2024), with outcomes (full, interim, denied) generated by NUC-style scoring rules. Fifteen indicators covering staffing, curriculum, facilities, library, funding, research and employer rating, together with ownership, discipline and prior status, were used as predictors. Logistic regression (LR), support vector machine, multilayer perceptron, random forest and extreme gradient boosting (XGBoost) were trained on 2014–2021 visits with university-grouped cross-validation and tested on 2022–2024 visits. LR performed best on the temporal test set (accuracy 0.773; macro-F1 0.708, 95% CI 0.669–0.744; area under the curve [AUC] 0.908), exceeding a prior-status rule (macro-F1 0.537). For the binary task of identifying programmes at risk of not receiving full accreditation, LR achieved an AUC of 0.900 and good calibration; the 20% of programmes with the highest predicted risk included 52 of the 53 denied programmes. Proportion of PhD-holding staff and laboratory provision were the most influential predictors. ML-based risk scoring could support continuous, pre-emptive quality monitoring, but validation on real NUC data is required before operational use.

African Journal of Mathematics, Statistics and Computer Science · 2026
Research publication

A Comparative Imputations Statistics Approaches With Application to Nigerian Rainfall Data

Taiwo Wale Ayanniyi, Efosa Michael Ogbeide

Missing values in rainfall datasets reduce the reliability of statistical inference and undermine decision-making in agriculture, climate studies, and environmental management. This study evaluated the performance of five imputation techniques; Expectation-Maximization (EM), Multiple Imputation (MI), Regression Imputation (RI), Bootstrap Expectation-Maximization (BEM), and Random Forest (RF) using the 2019 Nigerian rainfall dataset obtained from the National Bureau of Statistics. The methods were compared using Raw Bias, Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Variance to assess estimation accuracy, predictive performance, and stability. The results revealed that MI produced the lowest bias (-0.003), making it the most suitable method for minimizing systematic estimation error. In contrast, RF achieved the highest predictive accuracy, recording the lowest MSE (0.9530) and RMSE (0.9762). Although BEM exhibited the lowest variance (0.9844), indicating greater stability, it was associated with relatively high bias, limiting its overall effectiveness. The findings demonstrate that no single method is universally optimal; rather, the choice of imputation technique should be guided by the primary analytical objective. RF is recommended for applications requiring high predictive accuracy, whereas MI is preferable when unbiased parameter estimation is essential. The study provides empirical evidence to support the adoption of robust imputation techniques by agencies such as the Nigerian Meteorological Agency (NiMet), thereby improving the quality of national climate databases and strengthening evidence-based agricultural and environmental decision-making.

Ktrend - International Journal of Mathematics and Statistics (IJMS) · 2026
Rhotrix semigroup; extended Green relations; matrix monoid; finite field; rank pair.

Extended Green Relations and Rank Pair Enumeration in Finite Rhotrix Semigroups

O. G. Udoaka

Let $q$ be a prime power and let $T_m(q)$ be the monoid of order-$(2m-1)$ Rhotrix arrays whose row–column multiplication corresponds to componentwise multiplication in $M_m(\mathbb F_q)\times M_{m-1}(\mathbb F_q)$. The extended Green relations $\mathcal L^*$ and $\mathcal R^*$ are characterized by the row and column spaces of both matrix components. Regularity implies $\mathcal L^*=\mathcal L$ and $\mathcal R^*=\mathcal R$, while $\mathcal D^*=\mathcal D=\mathcal J$ is indexed by the pair of component ranks. For each rank pair, closed formulas are derived for the sizes and numbers of $\mathcal L^*$-, $\mathcal R^*$-, and $\mathcal H^*$-classes, the number of idempotents, and the order of every maximal subgroup. The principal ideal order, all two-sided ideals, and a rank-generating polynomial are determined. An exhaustive computation for $T_2(2)$ confirms the formulas and the translation-kernel definitions. These results provide an explicit finite-field structure theory for the specified row–column Rhotrix monoid.

Ktrend – Nigerian Journal of Mathematical and Computational Sciences · 2026
Research publication

Development of an AI-Powered Ransomware Early Warning System for Hospital Managements

Osifo Nosayaba Blessing, John Temitope Ogbiti

Ransomware poses an escalating threat to healthcare institutions, where attacks disrupt clinical workflows, compromise patient data, and directly endanger patient safety. Existing detection systems are reactive, binary in classification, and lack contextual awareness of hospital-specific risk. This paper presents the design and implementation of Leadeks REWS, an AI-powered, hospital-aware ransomware early warning system that classifies system behaviour into three stages: normal, pre-encryption, and encryption, using a Random Forest ensemble classifier trained on dynamic behavioural features. The system identifies the affected hospital subsystem (Electronic Health Records, Picture Archiving and Communication Systems, or Administrative Systems), assigns a clinical risk level, and surfaces confidence-scored alerts through a real-time Flask and MongoDB dashboard with stage-specific mitigation recommendations. A rule-based Hospital Security Monitor additionally detects brute-force, privilege-escalation, and cross-system attacks within three interactive hospital subsystems. The Random Forest model, trained on an 80/20 stratified split of a 2,000-sample dynamic ransomware dataset, achieved 91% overall classification accuracy and 87% recall for the pre-encryption stage, outperforming Logistic Regression, single Decision Tree, and Support Vector Machine baselines. Twenty-five structured test cases and a formal evaluation against eight non-functional requirements confirm that the system delivers low-latency, reliable, and clinically prioritised ransomware detection suited to resource-constrained hospital environments.

Ktrend - International Journal of Computer Science and Artificial Intelligence (IJCSAI) · 2026
stochastic processes; bank stress testing; geometric Brownian motion; exponential decay; stock prices

Stress Testing Nigerian Banks: An Exponential-Decay Geometric Brownian Motion Model

Innocent Uchenna Amadi, Nkemdinim Kaydee Odu-Ndom, Celestine Nelson

This paper applies an exponential-decay geometric Brownian motion (GBM) model to illustrate how shocks and sustained downward pressure may affect Nigerian bank stock prices. The standard GBM drift is adjusted from $\mu$ to $\mu-k$, where $k>0$ is the decay rate. Brownian-motion paths illustrate the source of uncertainty, while simulated stock-price paths demonstrate how assets with identical initial values can diverge under volatility. Sensitivity analysis shows that the relationship between $k$ and $\mu$ determines the behavior of the expected price: the mean grows when $\mu>k$, remains constant when $\mu=k$, and declines exponentially when $\mu\mu$, the mean-price half-life is $\ln(2)/(k-\mu)$. The model therefore offers a transparent scenario-generation tool for regulators and risk managers. It is an illustrative stress-testing model rather than an empirically calibrated model of any named Nigerian bank.

Ktrend – Nigerian Journal of Mathematical and Computational Sciences · 2026
stochastic fluctuations; bank valuation; geometric Brownian motion; inflation; long-term growth; stock prices.

Solution of a Linear Stochastic Differential Equation for the Impact of Inflation and Long-Term Growth Trends on Bank Valuation

Innocent Uchenna Amadi, Tombari Stephen Ban, Nkemdinim Kaydee Odu-Ndom

This study investigates the dynamics of Nigerian bank stock prices using an exponential-growth geometric Brownian motion framework. The model extends the classical geometric Brownian motion (GBM) by incorporating a growth-adjustment parameter $k$ in the drift term, allowing it to capture both deterministic long-term growth and stochastic fluctuations. Three Brownian-motion paths are first presented to illustrate the underlying randomness, followed by sample price paths demonstrating how the same growth rate can produce both upward and downward trajectories depending on the shock realizations. A sensitivity analysis is then conducted to assess the effect of $k$ on the simulated paths. The results show that higher values of $k$ amplify exponential growth or decay and increase dispersion in absolute valuation. This framework provides insight into how long-term growth expectations interact with short-term volatility in the Nigerian banking sector.

African Journal of Mathematics, Statistics and Computer Science · 2026
leadership dynamics; financial performance; differential transform method; mathematical modelling

Mathematical Modelling of Leadership Dynamics and Financial Performance Using Coupled Ordinary Differential Equations

S.O. Edeki

Leadership is widely known to be the key to organizational effectiveness and firm financial performance, but the situation is complicated by the fact that leadership style, leadership behavior, employee experience, organizational state, and financial performance are not fully mathematically correlated. In this paper, two basic contributions are made. First, a mathematical model based on differential equations is developed to describe the dynamics of leadership and organization, and a rigorous mathematical proof is provided for the existence of a repeatable solution. Secondly, the model is analyzed and interpreted analytically and numerically using numerical solutions obtained from the differential transform method. In this technique, the set of differential equations is converted into a more convenient form. Since the coupled system of differential equations is not analytically tractable, the Differential Transform Method and numerical simulations are used to obtain approximate analytical solutions of the main equations. Lastly, the results are explored in terms of the evolution of leadership and its impact on employee, contextual, and financial outcomes. The results show that adaptive leadership strategies lead to better employee outcomes and make organizations more resilient and improve long-term financial performance compared to a focus on short-term wins. Therefore, the model proposed in this study is designed to be a quantitative tool for tracking the leadership process and a mathematical basis for managing organizations in the era of modernism.

Ktrend – Nigerian Journal of Mathematical and Computational Sciences · 2026
Research publication

Ordinary Differential Equation Models of Chemical Kinetics, HIV-Prevention Pathways, Epidemic Spread, and Growth–Decay Processes

Etim Uduak James

Ordinary differential equations provide a common language for representing rates of change in chemical, biological, epidemiological, and financial systems. This study develops and computationally examines four model families drawn from physical and life-science applications: the dimensionless Lengyel–Epstein model for the chlorine dioxide–iodine–malonic acid reaction; a six-compartment demographic, exposure, infection, and AIDS-progression model motivated by delayed first sexual intercourse; the classical susceptible–infectious–removed epidemic model; and exponential growth and radioactive-decay models. Equilibria and local stability conditions are derived analytically, while numerical solutions are obtained with adaptive Runge–Kutta integration. For the chemical model with illustrative parameters $a=12$ and $b=0.30$, the positive equilibrium is unstable and the numerical trajectory approaches sustained oscillation. The delayed-intercourse model is locally asymptotically stable when the feedback between the sexually active and under-age compartments is weaker than total demographic removal, specifically when $(d_1+m_1)(d_2+m_2+b_2)>b_1m_1$. For the epidemic illustration, the effective transmission rate is $0.8$ per day, the recovery rate is $0.125$ per day, and $R_0=6.4$; the infectious population peaks at approximately $554$ persons near day $13$ in a population of $1,000$. Continuous $5%$ financial growth increases $20,000$ monetary units to $23,236.68$ after three years, whereas an $800,\mathrm{mg}$ bismuth-210 sample with a five-day half-life declines to $12.5,\mathrm{mg}$ after $30$ days. The results demonstrate how a shared differential-equation framework supports model formulation, stability analysis, simulation, and transparent comparison across distinct applications. All numerical outcomes are illustrative and are not fitted to clinical or laboratory observations.

Ktrend - International Journal of Computational Mathematics and Scientific Computing · 2026
Research publication

Teachers' Job Description and Students' Academic Performance in Lagos State Junior Secondary Schools

Abosede Oyebukola Adenipebi, Mohammed Mubashiru Olayiwola Babatunde, Abari Ayodeji Olasunkanmi

The specification and implementation of teachers’ professional responsibilities are increasingly recognised as factors associated with student success. This study examined the relationship between the dimensions of teachers’ job descriptions, specifically planning, organising, lesson delivery, and classroom management, and students’ academic performance in public junior secondary schools in Lagos State, Nigeria. The study adopted a descriptive survey and correlational research design. The target population comprised 8,865 teachers in 327 public junior secondary schools across the state’s six Education Districts. A multi-stage sampling procedure was used. Of 563 questionnaires administered, 551 were valid for analysis, representing a 97.9% response rate. Data were collected using the Teachers’ Job Description Questionnaire (TJDQ), a 20-item instrument on a 4-point Likert scale, while students’ academic performance was measured using Basic Education Certificate Examination (BECE) results obtained through a Record Observation Format. The TJDQ achieved a Cronbach alpha reliability coefficient of 0.85. Data analysis involved descriptive statistics and Pearson Product-Moment Correlation at the .05 level of significance. The findings revealed a strong, positive, and statistically significant relationship between teachers’ job description and students’ academic performance $r=.711$, $N=551$, $p<.001$. Among the four dimensions, planning and lesson delivery had the highest mean scores $M=3.34$, followed closely by classroom management $M=3.33$ and organising $M=3.30$. The study concluded that clearer and more effective execution of prescribed instructional duties was associated with higher student achievement. Recommendations include the formal codification of teachers’ job descriptions by educational authorities and the provision of regular professional development focused on the core instructional dimensions.

Ktrend - International Journal of Education and Educational Research (IJEER) · 2026
conformal mapping; Joukowski transformation; circular domains; airfoil profile; complex analysis; potential flow; aerodynamics.

Joukowski Mapping of Circular Domains to Aerodynamic Profiles

Etim Uduak James

Conformal mapping is one of the central geometric techniques of complex analysis because it permits a complicated planar domain to be represented by a simpler one while preserving local angles. This paper develops the analytic conditions for conformality from the principal linear part of a differentiable complex mapping, relates the Cauchy--Riemann equations to local rotation and dilation, and presents explicit mappings between standard domains. Particular attention is given to the Joukowski transformation and its constructive action on circular boundaries. Actual mappings are worked out for the upper half-plane and unit disk, for a strip and half-plane, and for circles mapped by the Joukowski transformation into a line segment, an ellipse, and an airfoil-like profile. The derivations are accompanied by graphical realizations and a discussion of potential-flow aerodynamics. The results make explicit the connection between the analytic formula, its critical points, transformed geometry, and the distinction between local conformality and global one-to-one behavior.

African Journal of Mathematics, Statistics and Computer Science · 2026
soft set theory; soft algebra; soft group; soft ring; soft semiring; soft lattice; uncertainty; decision making; parameter reduction.

The Study of Soft Set Theory, Its Algebra and Applications

Udoaka, O. G.

Soft set theory is a parameterized framework for the representation of uncertainty in situations where the available information is incomplete, qualitative, or difficult to encode by a probability distribution or membership function. In this paper, I develop a unified treatment of the basic algebra of soft sets and examine how classical algebraic structures can be represented through parameter-dependent approximations. I formulate the principal soft-set operations on compatible parameter domains, establish elementary structural properties, and study soft groups, soft rings, soft semirings, and soft lattices. I further show that, for a fixed parameter set, suitable families of soft subsets inherit commutative idempotent monoid and distributive lattice-type structures under parameterwise union and intersection. To demonstrate the applied value of the framework, I construct a multi-parameter decision model for selecting an alternative from a finite universe. The model combines binary soft information, parameter reduction, and weighted choice values. An illustrative house-selection example shows how the same soft information can be converted into a transparent ranking procedure while preserving the semantic role of each parameter. The analysis emphasizes that the validity of algebraic identities depends on the adopted definitions and parameter domains, and therefore distinguishes fixed-domain operations from extended operations. The paper provides a concise bridge between the foundational theory, algebraic interpretation, and decision-making use of soft sets.

African Journal of Mathematics, Statistics and Computer Science · 2026
Research publication

A Unified Recurrence Framework for Power-Series and Frobenius Solutions of Second-Order Linear ODEs

D. GOODHEAD, I. D. EDEM

This paper presents a unified coefficient-recurrence framework for obtaining series solutions of second-order linear ordinary differential equations with variable coefficients. The standard power-series method, applicable at ordinary points, and the Frobenius method, applicable at regular singular points, are treated as special cases of a common series ansatz $y(x)=(x-x_0)^r\sum_{n=0}^{\infty}a_n(x-x_0)^n$, where $r=0$ recovers the ordinary case and $r$ is determined by an indicial equation in the singular case. General recurrence relations for analytic coefficient functions are derived, conditions under which series terminate to yield polynomial solutions are established, and resonance in the integer-difference root case is characterized. Carefully selected examples illustrate the framework, including polynomial solutions, fractional exponents, resonance with logarithmic terms, and the Bessel equation. The analysis provides a systematic structural comparison of the two methods in terms of recurrence order, termination, resonance, and computational complexity.

Ktrend - International Journal of Mathematics and Statistics (IJMS) · 2026
Research publication

Emerging Loanwords in Nigerian English

Ordu Isaac Chioma, Florence Nne Agwu

Loanwords are an integral part of language development, particularly in multilingual societies where speakers are in constant contact with other languages. As languages evolve, lexical items are borrowed to meet new communicative, cultural, and social needs. This study identifies emerging loanwords in Nigerian English and examines how they enter Nigerian English, with particular attention to indigenous Nigerian languages within the Port Harcourt speech community. The study is anchored in Terence Odlin’s theory of language transfer, especially the concept of substratum transfer, which explains the influence of a source or native language on a recipient language [16]. A qualitative survey design was adopted, with data collected through random sampling from language use on WhatsApp and Facebook. The findings show that many emerging loanwords in Nigerian English originate from Igbo, Hausa, Yoruba, and Nigerian Pidgin. Some retain their meanings in both donor and recipient languages, whereas others undergo semantic change after entering Nigerian English. Of the 108 items examined, 30 exhibit semantic change and 78 retain their donor-language meanings. The study recommends greater scholarly attention to emerging loanwords because they contribute to the continuing lexical expansion and localization of Nigerian English.

Ktrend - International Journal of English, Communication and Applied Linguistics · 2026
wealth; stochastic systems; financial mathematics; periodic events; stocks.

Empirical Estimates of Stochastic Systems to Measure the Wealth of Corporate Investors

Nwagor Peters

Financial-market dynamics are inherently uncertain, and stochastic differential equations provide a natural framework for assessing the evolution of investment wealth under such conditions. This study formulates two stochastic systems for measuring the wealth of corporate investors by incorporating expected stock returns, intrinsic growth rates, interest-rate parameters, volatility, periodic effects, and random market fluctuations. The systems are solved analytically through Itô's lemma after logarithmic transformation of the wealth processes, yielding explicit expressions for the fourth and fifth corporate investors. For the fourth corporate investor, the stochastic wealth process is expressed as $$ V_4(t)=V_{40}\exp\left[\left(\mu\alpha_4-\beta_4-\frac{1}{2}\sigma^2\right)t+\sigma W_t^4\right], $$ while the corresponding wealth process for the fifth corporate investor is $$ V_5(t)=V_{50}\exp\left[\left(K\tanh(\alpha_5)-\beta_5-\frac{1}{2}\sigma^2\right)t+\sigma W_t^5\right]. $$ Numerical evaluations are used to examine the effects of intrinsic growth, interest rates, and stock volatility on portfolio values. The results show that increases in intrinsic growth rates generally increase investor wealth, whereas higher interest-rate parameters reduce wealth. Increased volatility lowers wealth under the non-periodic specification and makes wealth more sensitive to market fluctuations when periodic effects are incorporated. Surface-view representations further illustrate the response of investor wealth to changes in the principal model parameters. The findings provide a quantitative basis for corporate investment decisions under time-varying and uncertain market conditions and suggest that stochastic delay and periodic extensions may offer useful directions for subsequent research.

Ktrend – Nigerian Journal of Mathematical and Computational Sciences · 2026
wealth; stochastic systems; investments; interest rates; stock prices

Stochastic System Estimates to Assess Corporate Investor Portfolio Value in Stock Markets

Nwagor Peters

Uncertainty in stock-market conditions makes the quantitative assessment of corporate investment portfolios an important problem in financial modelling. This study develops a system of stochastic differential equations for estimating the wealth dynamics of three corporate investors under changing market conditions. The model incorporates expected stock returns, intrinsic growth rates, interest-rate effects, stock-price volatility, and random market fluctuations. The stochastic wealth processes are solved analytically using Itô's lemma, leading to explicit solutions of the general form $$ V_i(t)=V_{i0}\exp\left[\left(\mu\alpha_i-\beta_i-\frac{1}{2}\sigma^2\right)t+\sigma W_i(t)\right],\qquad i=1,2,3. $$ Numerical evaluations are performed to determine the effects of the principal model parameters on corporate-investor portfolio values. The results show that increases in the intrinsic growth-rate parameters $\alpha_i$ are associated with higher terminal wealth, whereas increases in the interest-rate parameters $\beta_i$ reduce portfolio wealth. The volatility parameter $\sigma$ affects both the deterministic Itô correction $-\frac{1}{2}\sigma^2$ and the stochastic component $\sigma W_i(t)$, thereby influencing the distribution and sensitivity of terminal wealth. Under the parameter values considered, the second corporate investor records the largest wealth values among the three investors. The stochastic framework provides a useful mathematical approach for assessing corporate-investor portfolio values and evaluating the effects of key financial parameters under uncertain stock-market conditions.

African Journal of Mathematics, Statistics and Computer Science · 2026
Research publication

Acceptance and Utilization of Contraceptive Practices among Women of Childbearing Age in Sapele Community, Delta State, Nigeria: A Cross-Sectional Study

Obataze J. Akpoyovwere, Aruoriwo Grace Okparavero

Contraceptive access and informed use are essential components of reproductive health, enabling women to prevent unintended pregnancies, achieve desired birth spacing, and exercise informed reproductive choices. Despite increasing awareness of family-planning services in Nigeria, contraceptive acceptance and consistent utilization remain uneven across communities. This study assessed knowledge, attitudes, acceptance, utilization, communication patterns, and perceived barriers to contraceptive practices among women of childbearing age in Sapele Community, Delta State, Nigeria. A descriptive cross-sectional survey was conducted among 109 women aged 15–49 years selected through a multistage sampling procedure. Data were collected using a structured, pre-tested questionnaire with good internal consistency (Cronbach’s α = 0.85) and analysed using frequencies and percentages. Although 69 respondents (63.3%) had heard about contraceptive practices, 69 (63.3%) were classified as having poor method-specific knowledge, indicating a considerable gap between general awareness and practical contraceptive literacy. Fifty-one respondents (46.8%) reported ever or current contraceptive use, whereas 58 (53.2%) reported no use, and only 13 (11.9%) reported always using contraception. Condoms were the most frequently reported method (18.3%), followed by intrauterine devices (9.2%), injectables (approximately 8–9%), implants (5.5%), and oral contraceptive pills (4.6%). Attitudes toward contraception were predominantly unfavourable: 55.0% did not consider contraception important for women’s health, 50.5% did not regard its use as morally acceptable, and 64.2% did not believe that contraception was effective in preventing pregnancy. Fear of side effects (31.2%) was the leading reported barrier, followed by inadequate contraceptive knowledge (27.5%), partner opposition (22.9%), and religious or cultural beliefs (18.3%). Furthermore, 62.4% had never discussed contraception with a partner or healthcare provider, while 40.4% reported difficulty accessing contraceptive services. The findings demonstrate that general awareness alone does not necessarily translate into adequate knowledge, favourable attitudes, acceptance, or consistent contraceptive use. Strengthening method-specific education, nurse-led counselling, side-effect management, confidential reproductive-health communication, culturally responsive community engagement, reliable access to a broad range of contraceptive methods, and appropriate partner involvement may improve informed contraceptive decision-making and sustained utilization among women of reproductive age in Sapele.

Ktrend - International Journal of Medical and Health Sciences (IJMHS) · 2026
Research publication

Machine Learning-Assisted Selection of Algebraic Structures for Post-Quantum Cryptographic Systems: A Multi-Objective Computational Optimization Model

Tombotamunoa W. J. LAWSON

The transition to post-quantum cryptography creates a mathematical decision problem in which security strength, algebraic structure, key and ciphertext sizes, execution time, memory demand, implementation complexity, and side-channel resilience must be considered simultaneously. This paper develops a machine learning-assisted multi-objective computational framework for ranking candidate algebraic structures and parameter configurations for post-quantum cryptographic deployment. The framework combines a normalized utility model, feasibility constraints, Pareto dominance, and supervised learning. A reproducible simulation study with 2,400 synthetic candidate configurations representing lattice-, code-, hash-, multivariate-, and group-based families is used to demonstrate the methodology without presenting the simulated values as implementation benchmarks. Random Forest, Gradient Boosting, and Support Vector Machine classifiers are compared using a stratified 70:30 train-test split and five-fold cross-validation. On the held-out test set, Gradient Boosting achieved an accuracy of 0.901, F1-score of 0.869, and ROC-AUC of 0.968, while five-fold cross-validation produced a mean ROC-AUC of 0.960. Security strength was the dominant predictor in permutation analysis, but side-channel resilience, algebraic dimension, key size, memory demand, and decapsulation time also contributed to the selection boundary. A Pareto analysis identified 25 non-dominated feasible configurations in the simulated design space. The proposed model provides a transparent mathematical mechanism for combining cryptographic constraints with data-driven classification and can be adapted to measured benchmark datasets as they become available. The principal contribution is therefore methodological: it gives a reproducible bridge between computational algebra, multi-criteria optimization, and machine learning for cryptographic parameter selection.

Ktrend - International Journal of Mathematics and Statistics (IJMS) · 2026
Research publication

Knowledge, Practice, and Barriers Relating to Prostate Cancer Screening Among Male Undergraduate Students at Edo State University, Iyamho, Nigeria

Obataze J. Akpoyovwere, Gabriella Oghenevwede Igbru

Prostate cancer remains an important cause of cancer-related morbidity and mortality among men, while late presentation continues to undermine early detection and treatment outcomes in many low- and middle-income settings. Although most male university students are younger than the age at which routine prostate cancer screening is generally discussed, knowledge acquired in early adulthood may influence future health-seeking behaviour, risk perception, peer communication, and family health decisions. This study assessed knowledge, reported practice, and perceived barriers relating to prostate examination and prostate cancer screening among male undergraduate students at Edo State University, Iyamho, Nigeria. A descriptive cross-sectional survey was conducted among 200 male undergraduates selected from a target population of 2,169 students using simple random sampling. Data were collected using a researcher-developed structured questionnaire and analysed with SPSS version 25 using frequencies, percentages, and mean scores. The grand mean for knowledge was 2.44, below the predefined criterion mean of 2.50, indicating inadequate knowledge. Only 35% of respondents identified digital rectal examination as being related to prostate examination and 38% recognized the examination position described in the questionnaire. Screening-related practice was also low: 25% reported ever performing what the original questionnaire termed self-prostate examination, 22% reported ever having or performing digital rectal examination, 22.5% reported current practice, 20% routine practice, and 21% previous prostate examination or screening by a nurse or physician. Feeling healthy or having no symptoms was the most frequently reported barrier (37%), followed by discomfort with the examination (24%), discomfort with body exposure (15%), embarrassment (14%), and being too busy (10%). The findings reveal important gaps in prostate cancer literacy and preventive health orientation among the respondents. University-based health promotion should therefore emphasize accurate information on prostate cancer risk, the distinction between symptoms and preventive assessment, evidence-based screening pathways, and the importance of professional clinical evaluation rather than unsupervised self-examination.

Ktrend - Annals of Nursing and Clinical Medicine · 2026
Research publication

Characterization of Stable Regulatory Attractors in Malaria Parasite Gene Networks: Asynchronous Boolean Update Method

Isere Abednego O., Elakhe O. Abraham, Okhuonurie Monday

Plasmodium falciparum</em>, the most virulent human malaria parasite, possesses a highly regulated genome that supports survival, adaptation, virulence, drug resistance, developmental switching, and stress responses within the human host. This study characterizes stable regulatory attractors in a malaria-parasite gene regulatory network using an asynchronous Boolean update method. The network is formulated as a Boolean dynamical system with nine biological components: \(X_1=\mathrm{PfEMP1}\), \(X_2=\mathrm{PfCRT}\), \(X_3=\mathrm{PfMDR1}\), \(X_4=\mathrm{PfDHFR}\), \(X_5=\mathrm{AP2\text{-}G}\), \(X_6=\mathrm{PfSIR2A}\), \(X_7=\mathrm{PfK13}\), \(X_8=\mathrm{HP1}\), and \(X_9=\mathrm{H3K9me3}\), representing regulators associated with virulence, drug resistance, developmental regulation, stress response, and epigenetic control. External pressure is represented by a general stress signal \(\omega\) together with selectors for chloroquine \((\lambda)\), antifolate pressure \((\alpha)\), artemisinin pressure \((\beta)\), and partner-drug pressure \((\rho)\). Fixed points are states satisfying \(F(X)=X\); such states are invariant under either synchronous or asynchronous updating. Under the all-stress-OFF condition, the model yields three fixed points, whereas the all-stress-ON condition yields four fixed points. The attractors show how stress-dependent logical regulation can shift the network between distinct stable expression patterns and provide a mathematical framework for exploring regulatory states associated with parasite adaptation and antimalarial pressure.

Ktrend - International Journal of Computational Mathematics and Scientific Computing · 2026
Research publication

Principals' Communication Practices, Teachers' Job Descriptions, And Students' Academic Performance In Lagos State Junior Secondary Schools, Nigeria

A. O. ADENIPEBI, M.O.B.. MOHAMMED, A. O. ABARI

The quality of school leadership and the precision with which teaching responsibilities are widely acknowledged as determinants of educational success. This research explored the interplay between principals' communication practices, teachers' understanding and execution of their professional roles, and the resulting academic achievement of students in public junior secondary schools across Lagos State, Nigeria. A descriptive survey and correlational research design was adopted for the study. The investigation involved a population of 327 principals and 8,865 teachers distributed among the six Education Districts in Lagos State. A multi-stage sampling procedure produced 563 participants, with 551 usable responses retained for final analysis, representing a 97.9% response rate. Measurement tools included a Principals' Communication Practices Questionnaire, a Teachers' Job Description Questionnaire, and a Record Observation Format capturing Basic Education Certificate Examination outcomes. The instruments demonstrated strong psychometric properties, with Cronbach alpha values of 0.87 and 0.85 respectively. Statistical analysis involved Pearson's correlation and multiple regression, with significance set at the 0.05 level. Findings revealed substantial positive associations between principals' communication practices and students' achievement scores (r = 0.682), between instructional role execution and learning results (r = 0.711), and between leadership communication and role performance (r = 0.624). The regression model was highly significant, with the predictor set accounting for 71.6% of the variability in academic outcomes (R = 0.846, R² = 0.716). It was concluded that when school heads communicate with clarity and consistency, and when teaching staff possess a precise understanding of their duties, student attainment improves markedly. Recommendation include the need for compulsory communication training for school administrators and the formalization of unambiguous job Description for classroom practitioners.

Ktrend - International Journal of Education and Educational Research (IJEER) · 2026
Research publication

PSCAE-SN: Physics-Aware Spiking RFI Detection for Simulated MeerKAT Data.

Furgurson Dawuda Abubakari Awuni, Linus Kweku Labik

This archive contains version 1.0.0 of PSCAE-SN, a physics-aware spiking convolutional autoencoder for detecting radio-frequency interference in simulated MeerKAT data. It includes the executed Jupyter notebook used for model training, evaluation, and figure generation, together with citation metadata, documentation, and the MIT License. The notebook reproduces five stochastic training runs and the reported pixel-level detection metrics using the publicly available TABASCAL SNN-NLN dataset. Trained model weights are not included; users must retrain the model by executing the notebook.

Zenodo (CERN European Organization for Nuclear Research) · 2026
Research publication

PSCAE-SN: Physics-Aware Spiking RFI Detection for Simulated MeerKAT Data.

Furgurson Dawuda Abubakari Awuni, Linus Kweku Labik

This archive contains version 1.0.0 of PSCAE-SN, a physics-aware spiking convolutional autoencoder for detecting radio-frequency interference in simulated MeerKAT data. It includes the executed Jupyter notebook used for model training, evaluation, and figure generation, together with citation metadata, documentation, and the MIT License. The notebook reproduces five stochastic training runs and the reported pixel-level detection metrics using the publicly available TABASCAL SNN-NLN dataset. Trained model weights are not included; users must retrain the model by executing the notebook.

Zenodo (CERN European Organization for Nuclear Research) · 2026
Student Assessment and Feedback, Science Education and Pedagogy, Educational Challenges and Innovations

Formative Assessment Strategies of Senior High School Physics Teachers in Selected Ashanti Region Districts, Ghana

Michael Atibilla Akooba, George Oduro-Okyireh, Isaac Owusu-Mensah

The study examined the formative assessment strategies senior high school physics teachers in selected districts of the Ashanti Region practice in their classrooms. Using a descriptive survey design, the study purposively selected 108 physics teachers from 36 senior high schools across nine districts. Data were collected through a 21-item closed-ended questionnaire and an observation guide. Descriptive statistics such as mean, standard deviation, and percentage were used to analyse the research question, while an independent samples t-test was used to test the hypothesis at a significance level of (α = 0.05). The results revealed that physics teachers in the Ashanti Region employ diverse formative assessment strategies to support students’ learning. These include clarifying learning objectives, providing timely feedback, using varied assessment tasks, and offering suggestions for improvement. However, peer and self-assessment practices were found to be infrequently implemented. Furthermore, the study established a statistically significant difference between more experienced teachers (those with at least five years of service) and less experienced teachers (serving less than five years), with the former employing diverse formative assessment strategies. The findings suggest that teaching experience enhances teachers’ ability to apply varied formative assessment approaches effectively. The recommendation for this study suggests that the Ghana Education Service should organize professional development programmes focused on formative assessment practices for less experienced teachers to strengthen their classroom assessment literacy and improve instructional quality. The study enhances the comprehension of subject-specific formative assessment practices and underscores the need for continuous professional learning to promote effective physics teaching and learning in senior high schools.

Journal of Research in Education and Pedagogy. · 2026
Quantum Electrodynamics and Casimir Effect, Quantum and Classical Electrodynamics, Particle physics theoretical and experimental studies

Dual Architecture: A Continuous Regularization Technique with Applications in Physics

julinho jorge luis Luis

The Gamma function diverges at negative integer and half-integer arguments, posing a fundamental obstacle for both perturbative and non-perturbative theories. Analytic continuation, while guaranteeing uniqueness, does not preserve the Euler integral representation in the left half-plane, as noted by Hardy and Titchmarsh. We present a continuous regularization technique - the Dual Architecture - that addresses this limitation through a complementary function with directional vector opposite to that of the Gamma function. The phase function is uniquely determined by the boundary conditions and , and its periodicity is established by Lemma 2.1. The regularized function for is finite by construction at all points where the classical Gamma function diverges, unifying regulation and subtraction within a single definition. We demonstrate the physical applicability of the technique across six systems: the cosmological constant, the Higgs boson mass, the strong CP problem, the Casimir effect, dimensional regularization in , and a divergent Gaussian integral. In each case, the algebraic development is presented in full, yielding analytical results consistent with experimental values. The technique offers a unified framework for treating Gamma-function divergences across perturbative and non-perturbative regimes. Keywords: Continuous regularization, Gamma function, uniqueness theorem, Casimir effect, Standard Model.

Zenodo (CERN European Organization for Nuclear Research) · 2026