Publications (184)
COMMUNICATION
A Structured Metamodel for Architecture Debt Management
Flavien Hervé SOMDA, Desire GUEL
Architecture debt in information systems poses significant challenges, leading to increased maintenance costs, reduced performance, and compromised quality. Effective management of architecture debt is crucial for the sustainability and efficiency of software systems. This paper proposes a comprehensive metamodel to support managing architectu(...)
Architecture Debt, Metamodel, Impact Analysis, Traceability, Model-Driven Engineering.
ARTICLE
Integrating the Syracuse Algorithm with K-MEAN: A Comprehensive Approach to Energy Optimization in Wireless Sensor Networks
Yacouba OUATTARA
In deploying a sensor network in a challenging environment, it is crucial to consider energy consumption to ensure an extended network lifespan. Since the inception of sensor networks, researchers have proposed various energy-saving solutions outlined in the introduction. In our study, we introduce a novel approach for cluster formation and po(...)
Energy, K-MEAN, Syracuse, WSN, SHEM.
ARTICLE
The Personalization of Justified Recommendations Using the Users Profile Interest and Reviews
Kyelem Yacouba, Tounwendyam Frederic Ouedraogo, Kiswendsida Kisito Kaboré
This paper is about the adaptive and personalized justification of the recommenders collaborative filtering system using notices. A method to justify recommendations based on item reviews and the user profile interest is suggested. The reviews with a positive sentiment have been first kept through the sentiment analysis expressed on the review(...)
Personalization, Justified Recommendations, Users Profile, Interest, Reviews
ARTICLE
Optimizing Real-time Video Analytics for Resource-Constrained Environments
Rodrique Kafando, Aminata Sabane, Tégawendé F. Bissyandé
Developing countries face a growing demand for video analytics, yet often lack sufficient computational resources. This paper addresses this challenge by proposing and evaluating optimization techniques for efficient video stream processing on resource-constrained devices, including edge systems. We introduce and evaluate several techniques, i(...)
RSTP stream, Real-time Video Analytics, Computational Optimization, Post-Training Optimization
ARTICLE
Enhancing 5G-NR mm Wave: Phase Noise Models Evaluation with MMSE for CPE Compensation
GUEL Desire, SOMDA Flavien Herve, ZERBO Boureima, SIE Oumarou
The rapid development of 5G New Radio (NR) and millimeter-wave (mmWave) communication systems highlights the critical importance of maintaining accurate phase synchronization to ensure reliable and efficient communication. This study focuses on evaluating phase noise models and implementing Minimum Mean Square Error (MMSE) algorithms for Commo(...)
5G New Radio (NR), mmWave, CPE Compensation, Phase Noise Models, Minimum Mean Square Error (MMSE), EVM (Error Vector Magnitude), BLER (BLock Error Rate), SNR (Signal-to-Noise Ratio), NRPDSCH (Physical Downlink Shared Channel), PT-RS (Phase Tracking Reference Signals)
ARTICLE
Enhancing Connectivity and Energy Efficiency in Mobile Wireless Sensor Networks with SHEM
Yacouba Ouattara, Christophe Lang
The wireless sensor network can be useful in many domains such as military field, environmental control, medicine and healthcare. We, specially, focus on networks with mobiles nodes. Such networks require continuous dynamic reconfiguration to maintain effective communication between the nodes. Maintaining communication links and connectivity i(...)
algorithmic, energy, mobility, topology, connectivity, distributed
ARTICLE
5G NR PRACH Detection with Convolutional Neural Networks (CNN): Overcoming Cell Interferences Challenges
Desire Guel, Arsene Kabore, Didier Bassole
In this paper, we present a novel approach to interference detection in 5G New Radio (5G-NR) networks using Convolutional Neural Networks (CNN). Interference in 5G networks challenges high-quality service due to dense user equipment deployment and increased wireless environment complexity. Our CNN-based model is designed to detect Physical Ran(...)
5G-NR, PRACH, CNN, Interference Detection
ARTICLE
5G NR PRACH Detection with Convolutional Neural Networks (CNN): Overcoming Cell Interference Challenges
GUEL Desire, KABORE Arsene, BASSOLE Didier
In this paper, we present a novel approach to interference detection in 5G New Radio (5G-NR) networks using Convolutional Neural Networks (CNN). Interference in 5G networks challenges high-quality service due to dense user equipment deployment and increased wireless environment complexity. Our CNN-based model is designed to detect Physical Ran(...)
5G-NR, PRACH, Réseaux de Neurones Convolutifs (CNN), Interference Detection
ARTICLE
Deep Learning and Web Applications Vulnerabilities Detection: An Approach Based on Large Language Models
Sidwendluian Romaric Nana, Didier Bassole, Desire Guel and Oumarou Sie
Web applications are part of the daily life of Internet users, who find services in all sectors of activity. Web applications have become the target of malicious users. They exploit web application vulnerabilities to gain access to unauthorized resources and sensitive data, with consequences for users and businesses alike. The growing complexi(...)
Deep Learning, Web application, Vulnerability, Detection, Large Language Model
ARTICLE
Deep Learning and Web Applications Vulnerabilities Detection: An Approach Based on Large Language Models
NANA Sidwendluian Romaric, BASSOLE Didier, GUEL Desire, SIE Oumarou
Web applications are part of the daily life of Internet users, who find services in all sectors of activity. Web applications have become the target of malicious users. They exploit web application vulnerabilities to gain access to unauthorized resources and sensitive data, with consequences for users and businesses alike. The growing complexi(...)
Deep learning, Web application, Vulnerability, Detection, Large language model
ARTICLE
A comparison of AI methods for Groundwater Level Prediction in Burkina Faso
Abdoul Aziz Bonkoungou, Souleymane Zio, Aminata Sabane, Rodrique Kafando, Abdoul Kader Kabore, Tégawendé F Bissyandé
Groundwater serves as a valuable resource to supplement surface water, and its extensive utilization underscores the importance of precise groundwater level predictions. Burkina Faso confronts a critical challenge in the domain of sustainable groundwater resource management, underscoring the need for accurate forecasts of groundwater levels to(...)
Mots clés non renseignés
ARTICLE
Detecting Illicit Data Leaks on Android Smartphones Using an Artificial Intelligence Models
Serge Lionel Nikiema, Aminata Sabane, Abdoul-Kader Kabore, Rodrique Kafando & Tégawendé F. Bissyande
In today’s digital landscape, hackers and espionage agents are increasingly targeting Android, the world’s most prevalent mobile operating system. We introduce DeepDetector - a system based on artificial intelligence to recognize data thefts in Android. This model is based upon a large dataset comprising of clean and tainted network traffic tr(...)
Mots clés non renseignés
COMMUNICATION
5G-NR PRACH Detection Performance Optimization in Context of Intra/Inter-Cell Interference
Désiré Guel, Pegdwindé Justin Kouraogo, Boureima Zerbo, Elie Jephte Yaro
The ever-evolving landscape of wireless communication technologies has led to the development of 5G-NR (5G New Radio) networks [1] promising higher data rates and lower latency. However, with these advancements come challenges in managing intra-cell and inter-cell interference, particularly during the random-access procedure. This article aims(...)
5G-NR PRACH, Intra/Inter-Cell Interference, Quality of Service (QoS)
ARTICLE
Convolutional Neural Networks Deep Learning Based for Malaria Detection and Diagnosis
Kabore, Josue, Guinko, Ferdinand T, Kiswendsida Kisito, Ouedraogo
Malaria is a disease that occurs worldwide, especially in tropical regions where a high prevalence is observed. Difficulties are encountered especially in developing countries where resources in terms of equipment and trained personnel are limited. Until today, microscopic analysis is the standard method for diagnosing Plasmodium falciparum, w(...)
Malaria, Deep Learning, Object detection, YOLOv5
COMMUNICATION
A Metamodel for Enhancing Program Increment (PI) Planning: Towards a Framework for Modeling and Impact Analysis
Flavien Hervé SOMDA, Désiré GUEL, Kiswendsida Kisito KABORE
This article introduces a novel approach to addressing challenges in Program Increment (PI) Planning within Agile methodologies and large-scale software development. Our research develops a metamodel and framework to formalize the PI Planning domain, enabling systematic modeling and effective impact analyses. PI Planning is crucial in Agile so(...)
Program Increment (PI) Planning