Dr. Zakayo Ndiku MORRIS

Publications in Journals:

1.  Mbithi, J. N., Atitwa, E. B., Morris, Z. N., & Anapapa, A. O. Overdispersion and Zero-Inflation in HIV Surveillance Data: Comparative Analysis of Classical Count Models. interpretation, 1(2), 3.
2. Edwin Cherani Sindiga, Zakayo Ndiku Morris, Cornelius Nyakundi, and Edwine Benson Atitwa, "Evaluating the Effects of Dairy Feed Types and Sequences on Milk Yield and Quality Using a 3 x 3 Crossover Design with Random Cow-Level Variability," IAENG International Journal of Applied Mathematics, vol. 56, no. 5, pp1817-1831, 2026
3. Wanyonyi, M., Morris, Z. N., Musyoka, F. M., & Kitavi, D. M. (2025). Enhanced machine learning and hybrid ensemble approaches for Coronary Heart Disease prediction. PLoS One, 20(12), e0328338.
4.  Wanyonyi, M., Morris, Z. N., Musyoka, F. M., & Kitavi, D. M. (2025). Predicting Coronary Heart Disease Using Classical Statistical Models: A Comparative Evaluation of Logistic Regression and Cox Proportional Hazards. IAENG International Journal of Applied Mathematics, 55(12).
5.  Maurice Wanyonyi, Zakayo Ndiku Morris, Faith Mueni Musyoka, and Dominic Makaa Kitavi, "Balancing Interpretability and Accuracy: A Comparative Evaluation of Logistic Regression and Machine Learning Approaches for Coronary Heart Disease Risk Prediction in Low-Resource Settings," IAENG International Journal of Computer Science, vol. 53, no. 3, pp1135-1154, 2026
6. Kandie, A. K., Atitwa, E. B., & Nyaluke, W. (2025). Perspectives on Judicial Efficiency: Case Study of Predictive Modeling in Kenyan High Courts. In IJCA (Vol. 16, p. 1).
7. Ouma, F. O., Atitwa, E. B., Morris, Z. N., & Wanyonyi, M. (2025). Comparative Analysis of Spline-based and Standard Frailty Models: Impact of Model Misspecification on Estimation Accuracy. IAENG International Journal of Applied Mathematics, 55(11).
8. Waweru, P. K., Atitwa, E. B., Morris, Z. N., & Kailemia, P. N. (2025). Semi-Markovian analysis of the prognosis of breast cancer between diagnosis and treatment initiation in Kenya: A case study of two counties. Commun. Math. Biol. Neurosci., 2025, Article-ID.
9. K. T. Wong, Z. N. Morris, & C. J. Nnonyelu, “Rules-of-thumb to design a uniform spherical array for direction finding – its Cramer-Rao bounds’ nonlinear dependence on the number of sensors,” The Journal of the Acoustical Society of America, vol. 145, no. 2, pp. 714-723, February 2019. https://pubs.aip.org/asa/jasa/article/145/2/714/993753
10. K. T. Wong, Z. N. Morris, D. M. Kitavi, & T. C. Lin, “A uniform circular array of isotropic sensors that stochastically dislocate in three dimensions – the hybrid Cramer-Rao bound of direction-of-arrival estimation,” The Journal of the Acoustical Society of America, vol. 146, no. 1, pp. 150-163, July 2019. https://pubs.aip.org/asa/jasa/article/146/1/150/993796
11. Z. N. Morris & K. T. Wong, “Comparing the “rim” versus the “filled” rectangular array grids-their direction-finding Cramer-Rao bounds,” IEEE Transactions on Aerospace and Electronic Systems, vol. 55, no. 4, pp. 1945-1956, August 2019. https://ieeexplore.ieee.org/abstract/document/8528521/
12. C. J. Nnonyelu & Z. N. Morris, “Acoustical direction finding using a Bayesian regularized multilayer perceptron artificial neural networks on a tri-axial velocity sensor”, International Journal of Mechatronics, Electrical and Computer Technology, vol. 10, no. 35, pp. 4493-4501, January 2020. http://repository.embuni.ac.ke/handle/embuni/3971
13. Z. N. Morris, K. T. Wong, & Y.I. Wu, “3D Dislocations in a uniform linear array’s isotropic sensors – direction finding’s hybrid Cramer-Rao bound”, The Journal of the Acoustical Society of America, vol. 147, no. 5, pp. 3209-3220, May 2020.https://pubs.aip.org/asa/jasa/article/147/5/3209/993546
14. C. J. Nnonyelu, Z. N. Morris, & A Madukwe, “On the Performance of L- and V-shaped arrays of cardioid microphones for direction finding”, IEEE Sensors Journal, vol. 21, no. 2, pp. 2211-2218, September 2020.https://ieeexplore.ieee.org/abstract/document/9186059/
15. L. Yang, K. T. Wong, & Z. N. Morris, “A centrosymmetric array comprising a horizontal uniform circular subarray and a vertical uniform linear subarray – its design in reference to its direction-finding Cramer-Rao bound,” IEEE Transactions on Aerospace and Electronic Systems, vol.57, no. 2, pp. 1624-1632, Dec 2021.https://ieeexplore.ieee.org/abstract/document/9300215/

Presentation of Papers at Academic and Professional Conferences
1.    Z. N. Morris, K. T. Wong, & Y. Han, “Hybrid Cramer-Rao Bound for Near-Field Source Localization Using a Spatially Spread Acoustic Vector Sensor,” The Journal of the Acoustical Society of America, vol. 145, p. 1801, May 2019.
2.    C. J. Nnonyelu, C. -C. L. Cheung, & Z. N. Morris, “Acoustical Direction Finding Using a Bayesian Regularized Multilayer Perceptron Artificial Neural Networks on a Tri-Axial velocity Sensor,” IEEE International Conference on Mechatronics, Automation and Cyber-Physical Computer Systems, March 2019.
3.    Z. N. Morris, K. T. Wong, D. M. Kitavi, & T. C. Lin, “The hybrid Cramer-Rao bound of direction finding by a uniform circular array of isotropic sensors that suffer stochastic dislocations,” The Journal of the Acoustical Society of America, vol. 142, no. 4, p. 2554, December 2017.