Publications (213)
ARTICLE
Recommendation of Documentary Units in a Progressively Intelligent City
Kiswendsida Kisito Kaboré, Désiré Guel, Yaya Traoré, Pegdwinde Justin Kouraogo, Didier Bassolé, Yacouba Kyelem, Tonguim Ferdinand Guinko, Oumarou Sié
The large cities and capitals of developing countries are becoming larger and more populated. These cities are modernizing day by day in order to increase the standard of living of their constantly growing population. To do this, they are equipping themselves with the latest generation of intelligent infrastructures that can make a city very a(...)
Smart City, Recommendation, IAAS, Documentary Unit
ARTICLE
Ouagadougou SUMO traffic scenarios for urban mobility.
Emile NANA, Ferdinand Tonguim GUINKO
In our work, we are attempting to predict urban traffic congestion in order to address issues related to urban mobility. We believe that congestion situations have upstream causes that significantly impact urban traffic flow. Thus, to resolve the problem of traffic congestion, there are intermediate steps that allow us to understand the traffi(...)
urban traffic simulation , road traffic prediction , road traffic engineering , SUMO , ontology , road traffic planning
ARTICLE
A Robust Crop Recommendation System Leveraging Soil and Climate Parameters
Desire Guel and Jimna Kongo
We present a benchmarking study of classical machine learning (ML) methods for crop recommendation from soil and climate parameters with an emphasis on methodological transparency, interpretability and deployability in low-resource contexts. We evaluate K-Nearest Neighbors (KNN), Random Forest (RF), Support Vector Classifier (SVC), Gaussian Na(...)
Crop Recommendation, Precision Agriculture, Ensemble Learning, Interpretability
ARTICLE
A Survey on Deep Learning Techniques for Malaria Detection: Datasets Architectures and Future Perspectives
Desire Guel, Kiswendsida Kisito Kabore, Flavien Herve Somda
Malaria remains a significant global health challenge that affects more than 200 million people each year and disproportionately burdens regions with limited resources. Precise and timely diagnosis is critical for effective treatment and control. Traditional diagnostic approaches, including microscopy and rapid diagnostic tests (RDTs), encount(...)
Malaria Detection, Deep Learning (DL), Convolutional Neural Networks (CNNs), Medical Imaging, Automated Diagnostics
COMMUNICATION
Towards An Ecore-Based, Uncertainty-Aware Metamodel for Auditable Geopolitical Decision Support
Somda Flavien Hervé, Guel Désiré , Kangoye Sékou
We present GeoDepend-ML, a temporal, multiplex Ecore metamodel for representing geopolitical interdependence and influence with auditability. The model treats actors (states, blocs, enterprises, organizations), assets (resources, technologies, infrastructures, routes), and artifacts (e.g., treaties, licenses, sanctions) as first-class elements(...)
Multiplexing, Uncertainty, Sensitivity analysis, Semantics, Lithography, Licenses, Security, Risk analysis, Reliability, Sustainable development, Ecore, EMF, international relations, knowledge graphs, multiplex networks, decision support, provenance, uncertainty
ARTICLE
Optimizing the 4G--5G Migration: A Simulation-Driven Roadmap for Emerging Markets
Desire Guel and Justin Pegd-Windé Kouraogo and Kouka Kouakou Nakoulma
Deploying fifth-generation (5G) networks in emerging markets demands a balance between performance targets and constraints in budget, spectrum, and infrastructure. We use MATLAB simulations to quantify how radio and architectural levers - MIMO (beamforming, diversity, spatial multiplexing), carrier aggregation (CA), targeted spectrum refarming(...)
5G migration, emerging markets, MIMO, carrier aggregation, spectrum refarming, mmWave, NSA/SA, D2D, M2M
COMMUNICATION
BF-WeakWeb-2025: A Novel Dataset and LLM Benchmark for Web Vulnerability Detection in Burkina Faso
Nana Sidwendluian Romaric and Bassolé Didier and Guel Désiré and Sié Oumarou
In a context of increasing digitalisation of administrative processes, cybersecurity has become a strategic issue for states, particularly Burkina Faso. Unfortunately, there is a lack of research into cybersecurity in Burkina Faso. In this article, we present an approach for identifying vulnerabilities in applications and websites from Burkina(...)
Knowledge engineering, Analytical models, Large language models, Cyberspace, Benchmark testing, Aging, Software, Data models, Communications technology, Computer security, OWASP Top 10, Web vulnerablity scanners, Fine-tuning, Large Language Model, Web application attacks
COMMUNICATION
Private Key Fragments Secure Recovery Approach in Passkeys System Based on Blockchain Technology and Error-Correcting Codes
Assane Ilboudo Didier Bassole and Desire Guel
In this paper, we propose an innovative approach to enhance the security and resilience of passkeys. this approach combines Shamir’s Secret Sharing Scheme, Reed–Solomon error-correcting codes, AES-GCM encryption, and decentralized storage systems such as blockchain and IPFS. In this approach, the adopted methodology is structured around three(...)
Solid modeling, Scalability, Computational modeling, Resists, Robustness, Error correction codes, Blockchains, Encryption, Secure storage, Resilience, Passkey System, Blockchain, Error-Correcting Codes, Security
ARTICLE
Big data analytics in healthcare: machine learning-based cardiac disease prediction in West Africa
Amédée W. DERA, Ferdinand T. GUINKO
This paper investigates the application of machine learning for cardiac disease prediction in resource constrained healthcare settings. This study conducts an empirical study evaluating four classification algorithms (Support Vector Machine, Random Forest, Logistic Regression, Decision Tree) on a real-world dataset. The results demonstrate tha(...)
Big Data Analytics, Data-driven healthcare, Data analytics in healthcare, Machine Learning in Healthcare, Disease Prediction
ARTICLE
Optimization and comparison of Deep Learning architectures for multi class classification of DDoS attacks in enterprise networks
Yacouba OUATTARA, Yaya TRAORE and Yves SAVADOGO
This article presents an in-depth study aimed at optimizing and comparing several deep learning architectures for multi-class classification of DDoS attacks in enterprise
networks, using the CIC-DDoS2019 dataset. The methodological approach includes rigorous data preprocessing (normalization, encoding, balancing, stratified split) as well as(...)
DDoS, intrusion detection, multi- class classification, Deep Learning, CNN-1D, CNN-LSTM, CNN-BiLSTM, CIC-DDoS2019.
ARTICLE
African digital health strategic plans analysis: key weaknesses in contextualization, intervention focus, and technological foresight
Bry Sylla; Ansiouonèkou Pascal Somda; Jean Noel Nikiema; Leon Gueswende Blaise Savadogo; Gayo Diallo; Nicolas Meda
Digital health strategies are increasingly being adopted in Africa, but their consistency with best practice planning is poorly documented. 54 countries were screened; 48 had a plan in the Global Digital Health Monitor, and 11 recent plans met the inclusion criteria. Using the “Ready, Extract, Analyze, Distill” methodology and a customized gri(...)
Health policy, Public health, Digital health
COMMUNICATION
A Metamodel for Simplifying Infrastructure Deployment Using Vagrant
Flavien Hervé Somda; Arnold Stéphane Kabore; Boureima Zerbo
We propose a metamodel–driven framework that replaces hand-written Ruby Vagrantfiles with validated EMF models capturing core Vagrant concepts (virtual machines, providers, networks, shares, plugins) and provisioners including Shell, Puppet, and Ansible. The framework raises the level of abstraction by allowing users to specify infrastructures(...)
Metamodeling , Infrastructure as Code , Vagrant , Virtualization , Code Generation , DevOps
ARTICLE
Deep learning models for binary ddos attack detection in enterprise environments
Yacouba OUATTARA Yaya TRAORE Yves SAVADOGO
This paper proposes an experimental methodology
based on the comparison of several deep learning models for the
detection of distributed denial of service (DDoS) attacks in
enterprise network environments. The CIC-DDoS2019 dataset,
recognized for the richness and realism of its attack scenarios,
served as a basis for the preparation, trai(...)
Cybersecurity, Deep Learning, Binary Classification, Intrusion Detection System (IDS), DDoS, CIC- DDoS2019 dataset
ARTICLE
A Hybrid Optimization Framework for Emergency Resource Allocation in Low-Resource Settings: Application to Burkina Faso
Tougma Manegaouindé Roland, Zerbo Boureima, Guel Désiré, Traore Salah Idriss Seif, Napon Salifou
The overuse of hospitals in Burkina Faso, especially during emergencies, is largely due to chronic underfunding and weak coordination among health centers. These challenges create critical bottlenecks in emergency care, where resources are limited and demand is often unpredictable. Motivated by the need for improved management of emergency pat(...)
Adaptation Models, Uncertainty, Hospitals, Decision Making, Urban Areas, Artificial Neural Networks, Linear Programming, Mathematical Models, Resource Management, Particle Swarm Optimization, Linear Programming, Particle Swarm Optimization, Artificial Neural Networks, Emergency Resource Allocation, Healthcare Optimization, Burkina Faso
ARTICLE
Network Optimization for Data Flow Control in a Security-Challenged Country: The Case of Burkina Faso
Yamba Dabone, Pengwendé Zongo & Tounwendyam Frédéric Ouedraogo
The Internet plays a crucial role in everything these days—economic development, education, and civic engagement—but it is also exploited by cybercriminals and terrorists, particularly via propaganda on social networks. In Burkina, where the terrorist threat has been present since 2016, cyber-activists sometimes relay unverified information, w(...)
Internet, IXP, Cyber-terrorism, Social network, Architecture.