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Research Article
Modelling the Dependence Between Drought and Heatwave Extremes in Kenya Using an Integrated EVT-Copula-XGBoost Framework
Charity Mueni Mulwa*
,
Herbert Imboga,
Susan Mwelu
Issue:
Volume 11, Issue 1, March 2026
Pages:
1-12
Received:
26 October 2025
Accepted:
8 November 2025
Published:
15 January 2026
Abstract: Compound drought-heatwave events pose serious threats to agriculture, ecosystems, and livelihoods in Kenya, where increasing climate variability amplifies their frequency and intensity. This study developed a hybrid Extreme Value Theory (EVT)-Copula-XGBoost framework to characterize and predict concurrent drought and heatwave extremes using ERA5 reanalysis data (2005-2024).The EVT component modeled the marginal tails of temperature and precipitation, revealing that temperature extremes follow a bounded Weibull-type tail, while rainfall deficits exhibit heavy tails, indicating a high potential for severe droughts. Copula modeling captured the dependence structure between drought and heatwave indices, showing weak but significant negative dependence (Kendall’s τ = −0.189 to 0.034), strongest during the short rains season (SON), implying that hot and dry conditions often co-occur. Joint risk analysis estimated return periods of 2.5-4.7 years, with five-year joint thresholds of 2.3-2.7 mm rainfall and 25.1-25.3◦C temperature, suggesting that compound drought-heatwave events recur roughly every three years. The XGBoost model achieved high predictive skill (AUC = 0.989), with EVT and Copula derived features contributing most to performance. This hybrid framework provides a robust, data driven foundation for early detection, risk mapping, and climate adaptation planning, supporting proactive management of compound climate extremes in Kenya.
Abstract: Compound drought-heatwave events pose serious threats to agriculture, ecosystems, and livelihoods in Kenya, where increasing climate variability amplifies their frequency and intensity. This study developed a hybrid Extreme Value Theory (EVT)-Copula-XGBoost framework to characterize and predict concurrent drought and heatwave extremes using ERA5 re...
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Research Article
Hiemenz Steady Hydromagnetic Flow and Heat and Mass Transfer Through a Porous Medium onto a Stretching Surface
Issue:
Volume 11, Issue 1, March 2026
Pages:
13-29
Received:
20 October 2025
Accepted:
6 November 2025
Published:
20 January 2026
Abstract: In the present paper, steady stagnation flow of conducting fluid through a porous medium over a flat stretching surface with heat absorption/generation and chemical reaction in the presence of magnetic field has been studied under Soret and Dufour effects. The governing partial differential equation involved in this analysis viz conservation of mass, momentum, energy and concentration are transformed into self similar steady equations using similarity transformations and are solved numerically by using the Runge-Kutta fourth order scheme along with shooting technique for the whole domain for different existing flow parameters in this investigation. A representative set of graphical results for the flow field, temperature and concentration are presented for the different existing non dimensional flow parameters. The dimensionless velocity profiles are seen to decrease with increasing the magnetic, Lewis, porosity, viscosity, radiation, chemical reaction parameters and increases with Soret, Dufour, Stretching, thermal and concentration buoyancy parameters. An enhancement of temperature and concentration profiles are observed with increasing magnetic, and porosity parameter and the both temperature and concentration fall down with increment of surface stretching parameter, Prandtl number, thermal and concentration buoyancy parameters. On the other hands, the concentration is seen to become more thicker with enhancement of Soret, radiation, viscosity parameters while the reversed effects is observed in the case of temperature distribution. The reduction in concentration is observed with the increasing Lewis, Dufour, heat absorption, chemical reaction parameter and enhancement in temperature is noted for these parameters. Furthermore, the shear stress parameters, the rate of heat transfer and mass transfer are derived for existing non-dimensional flow parameters. A special case of our results obtained during investigation is an excellent agreement with an earlier published work.
Abstract: In the present paper, steady stagnation flow of conducting fluid through a porous medium over a flat stretching surface with heat absorption/generation and chemical reaction in the presence of magnetic field has been studied under Soret and Dufour effects. The governing partial differential equation involved in this analysis viz conservation of mas...
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Research Article
Classification of Prostate Tumors for Effective Diagnosis and Treatment
Issue:
Volume 11, Issue 1, March 2026
Pages:
30-38
Received:
26 October 2025
Accepted:
8 November 2025
Published:
4 February 2026
DOI:
10.11648/j.ajmcm.20261101.13
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Abstract: Prostate tumors are tumors that grow in or around the prostate gland of the male reproductive system. these tumors are classified into two, that is: benign and malignant. Malignant tissues are cancerous and more dangerous as they can easily spread to other soft tissues that are easily attacked by cancer cells, such as the lungs and liver. In contrast, benign tumors are not as dangerous and can be surgically removed and never regrow. The cancerous tumors has a high mortality rate, according to GLOBOCAN 2020, there were estimated 19.3 million cases with 10 million registered deaths over the same year. Current diagnosis of prostate tumor still lacks maximum precision, with the PSA and invasive biopsy methods suffering from most false positives and negatives. The study suggested a ML algorithm blending technique from three base models, SVM, RF, and XGBoost. For maximum accuracy and overfitting, the study performed SMOTE for class balancing and correlation elimination techniques. The blended model outperformed the base model with an accuracy of 0.981 at 0.05 confidence level, followed by RF and XGboost at 0.971. In other performance metrics, blended model had the highest sensitivity and specificity of 0.979 and 0.981, respectively. XGBoost and RF shared almost the same sensitivity of 0.97 and a higher specificity of 0.98. SVM had an overall low performance and was not recommended for such a task as a standalone model. The study recommends the incorporation of a blended model over each performance, although Random Forest and XGBoost are still viable for application.
Abstract: Prostate tumors are tumors that grow in or around the prostate gland of the male reproductive system. these tumors are classified into two, that is: benign and malignant. Malignant tissues are cancerous and more dangerous as they can easily spread to other soft tissues that are easily attacked by cancer cells, such as the lungs and liver. In contra...
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