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Risk Factor Hypertension Prediction Model

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Journal of Applied Mathematics and Physics 2023年第2期11卷 428-437页

作者： Vercus Ntirandekura jeremie ndikumagenge Center of Research in Infrastructure Environment and Technology (CRIET) University of Burundi Bujumbura Burundi

According to the 2020 Ministry of Health reports, the public health sector is facing an acute shortage of logistical resources and qualified competent human resources, as evidenced by the doctor-to-hospital ratio in relation to population [1]. Aside from these structural and cyclical issues, the above ratios are even lower in rural areas with low incomes. Underdevelopment is a major impediment to establishing a normal public health situation, though the Burundian government is working hard to ensure that it is at an acceptable level. Furthermore, some Burundian traditions, customs, and practices are undermining efforts to build an international-standard public health facility. Indeed, the mental state of a people (tradition, culture, and practices) has a significant impact on the fluctuation of risk factors in public health. It is determined by the socioeconomic development and sociocultural behavior of the population. This demonstrates that hypertension is a public health concern in Burundi. Unfortunately, the vast majority of people are completely unaware of the risks that high blood pressure poses to public health. High blood pressure, on the other hand, has always been a key physiological measure in medical examinations, serving as one of the most important biological markers in clinical evaluation. As a result, cardiovascular diseases caused by high blood pressure have a significant impact on mortality worldwide, particularly in Burundi. Predicting high blood pressure based on risk factors can help to reduce complications associated with this disease, which is known as a silent killer. The digital era provides a variety of tools for studying, analyzing, managing, and monitoring the risk factors that contribute to and degenerate high blood pressure. The primary goal of this work is to create a decision-making tool based on the outcomes of high blood pressure epidemic and/or pandemic predictions from sanitarian districts. The current paper work employs a predicti

关键词： Artificial Intelligence Machine Learning Prediction Gradient Descent Hypertension Cardiovascular Disease

Modeling the Dynamics of the Random Demand Inventory Management System

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Journal of Applied Mathematics and Physics 2023年第2期11卷 438-447页

作者： jeremie ndikumagenge Jean Pierre Ntayagabiri Center of Research in Infrastructure Environment and Technology (CRIET) University of Burundi Bujumbura Burundi

At any given time, a product stock manager is expected to carry out activities to check his or her holdings in general and to monitor the condition of the stock in particular. He should monitor the level or quantity available of a given product, of any item. On the basis of the observation made in relation to the movements of previous periods, he may decide to order or not a certain quantity of products. This paper discusses the applicability of discrete-time Markov chains in making relevant decisions for the management of a stock of COTRA-Honey products. A Markov chain model based on the transition matrix and equilibrium probabilities was developed to help managers predict the likely state of the stock in order to anticipate procurement decisions in the short, medium or long term. The objective of any manager is to ensure efficient management by limiting overstocking, minimising the risk of stock-outs as much as possible and maximising profits. The determined Markov chain model allows the manager to predict whether or not to order for the period following the current period, and if so, how much.

关键词： Ergodic Markov Chain Irreducible Markov Chain Modeling Optimization Stochastic Processes

Management Tools for Random Demand Inventory and Supply

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Journal of Applied Mathematics and Physics 2023年第3期11卷 670-678页

作者： jeremie ndikumagenge Jean Pierre Ntayagabiri Vercus Ntirandekura Center for Research in Infrastructure Environment and Technologies “CRIET” University of Burundi Bujumbura Burundi

A mathematical management model’s added value is obtained only after the design and implementation of a user-friendly operating and usage tool. Fol-lowing work on developing an automated inventory management system and/or supplies, a dynamic model for the rational management of product stocks was established. Its implementation aims to limit or eliminate over-stocking and/or stock depletion. The orderable quantity prediction tool based on a settable and preset time period demonstrates the added value of incorporating probabilistic mathematical principles into supply management processes. In this context, this article discusses aspects of the design and implementation of random demand management algorithms based on Mar-kov chains. The goal is to forecast the state or behavior of goods marketing company’s product stocks and to develop a user supply management inter-face. The latter’s functional application will ultimately demonstrate the ac-curacy of the model. This paper also looks at how to use Markov chains to predict the reliability of any technical device, as well as how to implement an automated system with the desired technical specifications.

关键词： Model Algorithm Markov Chain Transition Matrix Steady State State Space

Comparative Study of Probabilistic and Least-Squares Methods for Developing Predictive Models

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Open Journal of Applied Sciences 2024年第7期14卷 1775-1787页

作者： Boribo Kikunda Philippe Thierry Nsabimana Jules Raymond Kala jeremie ndikumagenge Longin Ndayisaba Centre de Recherche en Infrastructure Environnement et Technologie (CRIET) Faculty of Engineering Sciences Universit du Burundi Bujumbura Burundi Faculty of Sciences Universit Catholique de Bukavu (UCB) Bukavu DR Congo Management Computer Department Institut suprieur Pdagogique de bukavu (ISP/Bukavu) Bukavu DR Congo

This article explores the comparison between the probability method and the least squares method in the design of linear predictive models. It points out that these two approaches have distinct theoretical foundations and can lead to varied or similar results in terms of precision and performance under certain assumptions. The article underlines the importance of comparing these two approaches to choose the one best suited to the context, available data and modeling objectives.

关键词： Predictive Models Least Squares Bayesian Estimation Methods

Comparative Study of the Reliability and Complexity of Symmetrical and Asymmetrical Cryptosystems for the Protection of Academic Data in the Democratic Republic of Congo

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Journal of Information Security 2024年第3期15卷 299-307页

作者： Mugaruka Buduge Gulain jeremie ndikumagenge Buhendwa Nyenyezi Justin Bulonza Masumbuko Alexis Katho Seba Jacques Department of Management Computing for Companies Section of Commercial and Computing Sciences Teachers Training College of Bukavu Bukavu The Democratic Republic of the Congo Center of Research in Infracture Environment and Technology (CRIET) Doctoral School University of Burundi Bujumbura Burundi Department of Maths-Physics Section of Exact Sciences Teachers Training College of Bukavu Bukavu The Democratic Republic of the Congo Higher Institute of Medical Techniques of Bukavu Bukavu The Democratic Republic of the Congo Department of Maths-Physics Section of Exact Sciences Teachers Training College of Bunia Bunia The Democratic Republic of the Congo

In the digital age, the data exchanged within a company is a wealth of knowledge. The survival, growth and influence of a company in the short, medium and long term depend on it. Indeed, it is the lifeblood of any modern company. A companys operational and historical data contains strategic and operational knowledge of ever-increasing added value. The emergence of a new paradigm: big data. Today, the value of the data scattered throughout this mother of knowledge is calculated in billions of dollars, depending on its size, scope and area of intervention. With the rise of computer networks and distributed systems, the threats to these sensitive resources have steadily increased, jeopardizing the existence of the company itself by drying up production and losing the interest of customers and suppliers. These threats range from sabotage to bankruptcy. For several decades now, most companies have been using encryption algorithms to protect and secure their information systems against the threats and dangers posed by the inherent vulnerabilities of their infrastructure and the current economic climate. This vulnerability requires companies to make the right choice of algorithms to implement in their management systems. For this reason, the present work aims to carry out a comparative study of the reliability and effectiveness of symmetrical and asymmetrical cryptosystems, in order to identify one or more suitable for securing academic data in the DRC. The analysis of the robustness of commonly used symmetric and asymmetric cryptosystems will be the subject of simulations in this article.

关键词： Comparative Study Cryptosystems Symmetric Encryption Asymmetric Encryption