Publications (274)
ARTICLE
LPWAN Localization via RSSI/SNR Fingerprinting and Lightweight Machine Learning
Désiré Guel, Flavien Hervé Somda, P. Justin Kouraogo, Boureima Zerbo and Oumarou Sié
Accurate geolocation for low-power wide-area (LPWAN) devices is desirable when GNSS is unavailable or too energy-expensive, yet RSSI-/TDoA-based approaches are often fragile under channel variability, collisions and cross-device heterogeneity. We address this gap with a reproducible, tabular pipeline that maps LoRa RSSI/SNR/ToA and PHY metadat(...)
LPWAN, LoRA, Localization, Fingerprinting, RSSI, SNR, IoT, Machine Learning
ARTICLE
Innovative and Secure Private Key Synchronization Mechanism Between Devices Using Peer-to-Peer Approach in Passkeys System
Assane ILBOUDO, Didier BASSOLE, Désiré GUEL
Passkeys are a passwordless authentication method that is increasingly being adopted. Based on asymmetric cryptography, they offer a secure and promising alternative to traditional passwords. In this paper, we propose a new secure approach for passkey synchronization based on a Peer-to-Peer mechanism between devices. Our secure services integr(...)
Elliptic Curve Diffie-Hellman, Passkey system, Zero-Knowledge Proofs, Security
COMMUNICATION
Ville intelligente et parking intelligent : enjeux et perspectives
OUATTARA Yacouba
Le stationnement en milieu urbain constitue une problématique majeure, engendrant des pertes de temps significatives (en moyenne 20 minutes par conducteur et par jour), une hausse du trafic d'environ 30 % et une hausse de la pollution de 15 % (source : ADEME). Pour répondre à ces enjeux, les technologies de stationnement intelligentes, combina(...)
parking intelligent , intelligence artificielle, capteurs
ARTICLE
Assessing the clinical reasoning of large language models on complex rheumatology cases: A multidimensional evaluation of four artificial intelligence
Yannick Laurent Tchenadoyo Bayala , Fulgence Kaboré, Charles Sougué , Aboubakar Ouedraogo , Yamyellé Enselme Zongo , Wendlassida Joelle Stéphanie Zabsonré/Tiendrebeogo , and Dieu-Donné Ouedraogo
Background: Large language models (LLMs) have demonstrated promising capabilities in medical diagnostic reasoning, yet
their performance in specialized clinical domains such as rheumatology remains incompletely characterized. While diagnostic
accuracy has been evaluated, critical dimensions including calibration, reasoning quality, and tempo(...)
large language models, artificial intelligence, diagnostic reasoning, rheumatology, clinical decision support, calibration
ARTICLE
Contributing to Speech-to-Speech Translation for African Low-Resource Languages : Study of French-Mooré Pair
Fayçal S. A. Ouedraogo, Maimouna Ouattara, Rodrique Kafando, Abdoul Kader Kaboré, Aminata Sabané, Tegawendé F. Bissyandé
Most of African low-resource languages are primarily spoken rather than written and lack large, standardized textual resources. In many communities, low literacy rates and limited access to formal education mean that text-based translation technologies alone are insufficient for effective communication. As a result, speech-to-speech translatio(...)
Translation (biology), Languages of Africa, Natural language, Context (archaeology)
ARTICLE
Neural Machine Translation for French–Mooré: Adapting Large Language Models to Low-Resource Languages
Walker Stanislas Rocksane COMPAORE, Maimouna Ouattara, Rodrique Kafando, Tegawendé F. Bissyandé, Abdoul Kader Kaboré, Aminata Sabané
This work focuses on neural machine translation between French and Mooré, leveraging the capabilities of Large Language Models (LLMs) in a low-resource language context. Mooré is a local language widely spoken in Burkina Faso but remains underrepresented in digital resources. Alongside Mooré, French, now a working language, remains widely used(...)
Machine translation, Natural language, Translation (biology), Feature (linguistics), Artificial neural network
ARTICLE
A Novel Reference Model for Intelligent and Comfortable Longitudinal Vehicle Control: Theory, Optimization, and Validation
Flavien H. Somda, Désiré Guel, Kisito K. Kaboré, Antoine Schorgen
This paper introduces a novel reference model for intelligent longitudinal vehicle control, designed to enhance both safety and passenger comfort. The proposed model dynamically adjusts the follower vehicle’s acceleration based on its penetration distance relative to the lead vehicle, ensuring smooth speed transitions and adaptive deceleration(...)
Longitudinal Vehicle Control, Nonlinear Control Model, Adaptive Deceleration, Safety Distance Optimization, Intelligent Transportation Systems, Advanced Driver Assistance Systems (ADAS)
ARTICLE
Multi-label Classification of Plant Diseases Using the Binary Relevance Approach: An Application for Tomato
Hamandé Koursangama, Zakaria Cheick Oumar Keita & Yaya Traore
Burkinabe agriculture is a fundamental pillar of the national economy. It plays a crucial role in the economic, social, and food security sectors, contributing to the stability and development of the country. However, this sector faces several challenges, particularly plant diseases, which lead to yield losses, inflated production costs, and f(...)
Agriculture, Agronomy, Pattern Recognition Receptors in Plants, Plant Pathology, Plant Biotechnology, Pomology
COMMUNICATION
5G-NR PRACH Detection Using an AutoEncoder Under Interference
Ahmed Sawadogo, Désiré Guel, Boureima Zerbo
Efficient detection of the Physical Random Access Channel (PRACH) is vital for reliable initial access in 5G New Radio (5G-NR), yet it remains challenged by intra- and inter-cell interference. This paper proposes a deep learning-based solution leveraging an Autoencoder (AE) trained on synthetic PRACH data under noisy conditions. The model dete(...)
5G-NR, PRACH, Autoencoder, Interference, Machine Learning, Deep Learning
COMMUNICATION
Emergency Severity Index Protocol with Machine Learning
Manegaouindé Roland Tougma, Boureima Zerbo, Désiré Guel, Salah Idriss Seif Traore, Salifou Napon
Effective triage in emergency departments is vital for optimizing patient outcomes and resource use, especially in resource-limited contexts like Burkina Faso. This study presents an automated triage system using machine learning (ML) to predict patient priority levels and appropriate medical services based on the Emergency Severity Index (ESI(...)
Emergency triage, Machine learning, Emergency Severity Index (ESI)
COMMUNICATION
A Comparative Study of CDL/TDL Channel Models in 5G-mmWave Networks
Mahamadi Sogoba, Désiré Guel, Boureima Zerbo
Millimeter-wave (mmWave) bands play a key role in 5G New Radio (5G-NR). They provide wider bandwidth and support much higher data rates. However, these bands also bring serious challenges. Signal propagation is more complex and affects system performance. This study fills an important gap. It compares two standard 3GPP channel models: Clustere(...)
5G-NR, NR-PDSCH, CDL/TDL channels, mmWave bands, BLER, SNR
COMMUNICATION
Vehicle Routing Optimization for Medical Product Distribution in Regional Capitals of Burkina Faso: A Linear Programming Approach with Gurobi
Saan-Nonnan Olivier Dabire, Boureima Zerbo, Désiré Guel
This study presents a MILP based approach to the Vehicle Routing Problem (VRP) for optimizing medical product distribution in Burkina Faso. The model accounts for critical real-world constraints including restricted areas and road inaccessibility while ensuring equitable service to priority healthcare centers. Implemented using the Gurobi solv(...)
Vehicle Routing Problem (VRP), Medical product distribution, Mixed-Integer Linear Programming (MILP)
ARTICLE
Comparative study of the performance of ChatGPT-4, Claude, Gemini, Mistral, and perplexity on multiple-choice questions in cardiology
Martin Wendlassida Nacanabo, Yannick Laurent Tchenadoyo Bayala, André Arthur Taryètba Seghda, Anna Tall/Thiam, Aristide Relwendé Yaméogo, Nobila Valentin Yaméogo, André Koudnoaga Samadoulougou & Patrice Zabsonré
Objective
The objective of our study was to assess and compare the performance of five LLMs on multiple-choice questions (MCQs) in cardiology.
Materials and methods
This was a comparative study conducted in the cardiology department of the Bogodogo University Hospital, Ouagadougou, involving 83 MCQs derived from the 2020 French national c(...)
Artificial intelligence, Large language model, Cardiology, Medical education, Multiple-choice question, Ouagadougou, Burkina faso
ARTICLE
SpreadSentinel: A Forward-Chaining Approach to Early and Adaptive DDoS Mitigation
Delwende D. Arthur Sawadogo, Abdoul Rahim Koné, Zakaria Sawadogo, Didier Bassole, Roland Kalmogo, et Gouayon Koala
The early detection of Distributed Denial-of-Service (DDoS) attacks in dynamic and imbalanced network environments remains a critical and unresolved challenge. While temporal deep learning architectures such LSTM, GRU, TCN, and RNN have demonstrated effectiveness in capturing sequential dependencies in network traffic, their real-time utilizat(...)
software security, Deep learning, Forward chaining, Class imbalance handling
ARTICLE
Recommendation Generation Justified for Information Access Assistance Service (IAAS): Study of Architectural Approaches and Post-Hoc Algorithm
Kabore, K. , Kyelem, Y. and Ouedraogo, T.
Recommendation systems only provide more specific recommendations to users. They do not consider giving a justification for the recommendation. However, the justification for the recommendation allows the user to make the decision whether or not to accept the recommendation. It also improves user satisfaction and the relevance of the recommend(...)
IAAS, Justification of Recommendations, Weight of Comments, Relevance of Recommendations, Justification of Recommendation Architecture for IAAS