Publications (267)
ARTICLE
FRAGILE BASE-CLASS PROBLEM, PROBLEM?
Aminata Sabané, Yann-Gaël Guéhéneuc, Venera Arnaoudova et Giuliano Antoniol
The fragile base-class problem (FBCP) has been described in the literature as a consequence of “misusing” inheritance and composition in object-oriented programming when (re)using frameworks. Many research works have focused on preventing the FBCP by proposing alternative mechanisms for reuse, but, to the best of our knowledge, there is no pre(...)
Mots clés non renseignés
COMMUNICATION
ICT emerging technologies context and possibilities of applications in GIST
KOURAOGO Pegdwindé Justin
In this work we give some overviews on how emerging technologies can improve the use and design of Geospatial Information Systems and Technologies (GIST). We present the issues in three points of views, namely hardware systems points of view, software systems point of view and data management systems points of view. We present opportunity of i(...)
Emerging Technologies, GIST, hardware, software, data
ARTICLE
Quantifying Ruin Metrics in a Diffusion-Driven Erlang (2) Risk Model with Dependency Modeled using the Spearman Copula.
François Xavier Ouedraogo, Delwendé Abdoul-Kabir Kafando, Frédéric Béré, Pierre Clovis Nitiéma
This paper focuses on the perturbation of an Erlang (2) risk model by a diffusion process, challenging the assumption of independence between claim amounts and inter claim durations. To account for a tail dependency structure, we introduce the Spearman copula, enabling the evaluation of Gerber-Shiu functions and ruin probabilities associated w(...)
gerber-shiu functions, dependence, copula, integro-differential equation, laplace transform, ruin probability.
ARTICLE
Using QoE Metric as a Decision Criterion in Multimedia Heterogeneous Network Optimization: Challenges and Research Perspectives
Hamidou Harouna Omar, Kouraogo Justin P., Kabre Windmi Jonathan, Tapsoba Stanislas David Wendkouni, Sie Oumarou
This article explores the growing importance of the QoE (Quality of Experience) metric as a fundamental criterion in the optimization of heterogeneous multimedia networks. We explore the bene2ts of using QoE, such as improving user experience, efficient resource management, and adaptation to network conditions. However, this paradigm presents(...)
QoS metric, Heterogeneous Network, Multimédia, Optimization
ARTICLE
Convolutional Neural Networks Deep Learning Based for Malaria Detection and Diagnosis
Kabore K. Kisito; Ouédraogo Josué; Guinko T. Ferdinand
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
ARTICLE
Towards a More Generic and Elastic Metadata Management Model in a Data Lake Environment
Safiatou S Sore, T Frederic T Frédric Ouedraogo, Moustapha M Bikienga, Yaya Y Traore
The evolution of the vast amount of heterogeneous data sources is leading to the emergence of several new concepts. One of the best-known concepts that is emerging as a new and trending topic in the big data space is the data lake. This is a central repository that stores heterogeneous data sources in their native format, without any predefine(...)
Mots clés non renseignés
ARTICLE
Characterization of Malicious URLs Using Machine Learning and Feature Engineering
Nana, S.R., Bassolé, D., Dimitri Ouattara, J.S., Sié, O.
In this paper, we use Machine Learning models for malicious URL detection and classification by Feature Engineering techniques. These models were implemented with scikit-learn using Random Forest, Support Vector Machine and XGBoost classifier algorithms. Our models were trained, tested, and then optimized with a dataset of 641,125 URLs (benign(...)
Malicious URL, Characterization, Feature Engineering, Detection, Classification
ARTICLE
Voice Interaction in Moore Language Study on Isolated Word Recognition in Audio Samples
Moumini Kabore, Rodrique Kafando, Aminata Sabane, Abdoul Kader Kabore, Tégawendé F. Bissyande
This paper explores the optimization of telephone functionalities through voice interaction in the
Moore language, prevalent in Burkina Faso. Data gathered from 492 individuals in Ouagadougou,
representing diverse dialects and vocal intensities across age groups, informs the study. Employing
K-Nearest Neighbor (KNN), Random Forest (RF), and(...)
Isolated Word Recognition, RNN
ARTICLE
Fakipedia: Building and exploiting an AI model for detecting online fake news in Burkina Faso
Angelique Sidbewendin Yameogo, Aminata Sabané, Tégawendé F. Bissyandé, Rodrique Kafando, Abdoul-Kader Kabore
Misinformation poses a significant challenge, especially in developing countries with low literacy rates. The rapid spread on social media, coupled with their lack of robust verification mechanisms, makes distinguishing between credible and false information increasingly difficult. This document outlines our efforts to address this challenge i(...)
Fake News, Machine Learning, Text Classification, camemBERT, Artificial Intelligence
ARTICLE
Neural Machine Translation for Mooré, a Low-Resource Language
Hamed Joseph Ouily, Aminata Sabane, Delwende Eliane Birba, Rodrique Kafando, Abdoul Kader Kabore, Tegawende F. Bissyandé
Natural Language Processing (NLP) is a field of artificial intelligence with the goal of enabling machines to understand human language. Neural Machine Translation (NMT) is one of the many applications of NLP and allows for the translation of a source language into a target language. NMT has made significant progress in recent years. However,(...)
Natural Language Processing, Neural Machine Translation, Low-ressource Lan- guage
ARTICLE
Analyzing Bankruptcy Probability under Partial Shareholder Payments and Dependent Claims via Spearman Copula
Kiswendsida Mahamoudou Ouedraogo, Delwendé Abdoul-Kabir Kafando, Lassané Sawadogo, François Xavier Ouedraogo, Pierre Clovis Nitiema
This paper is an extension of the compound poisson risk model with a strategy of partial dividend payment to shareholders, constant threshold b and dependence between claim amounts and inter-claim times via the Spearman copula. We study the probability of ultimate ruin associated with this risk model.
Cet article est une extension du modèle d(...)
Gerber-Shiu Functions, Dependence, Spearman Copula, Dividends, Integro-Differential Equation
ARTICLE
Special Issue of PPAP 2013: Preface
Surafel Lemma Abebe, Venera Arnaoudova, Laleh Mousavi Eshkevari, Aminata Sabané, Wei Wu
On the 5th of March, 2013, the first workshop on Patterns Promotion and Anti-patterns Prevention (PPAP 2013) took place in Genova, Italy. PPAP 2013 was co-located with the 17th European Conference on Software Maintenance and Reengineering (CSMR'2013), the premier European conference on the theory and practice of maintenance, reengineering and(...)
Business process reengineering, Computer science, Promotion (chess), Software engineering, Engineering, Political science, Operations management
ARTICLE
AI-driven Generation of News Summaries Leveraging GPT and Pegasus Summarizer for Efficient Information Extraction
Issiaka Faissal Compaoré, Rodrique Kafando, Aminata Sabané, Abdoul Kader Kaboré, Tegawendé F. Bissyandé
The surge of online information makes it challenging to access relevant news quickly. This necessitates automated methods to effectively extract and summarize information. Our research focuses on designing an online press synthesis tool using advanced AI models. We investigate the feasibility of emp
Computer science, Information extraction, Automatic summarization, Extraction (chemistry), Information retrieval, Natural language generation, Artificial intelligence, Natural language processing, Natural language
ARTICLE
A Comparison of AI Methods for Groundwater Level Prediction in Burkina Faso
Abdoul Aziz Bonkoungou, Souleymane Zio, Aminata Sabané, Rodrique Kafando, Abdoul Kader Kaboré, Tegawendé 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(...)
Groundwater, Environmental science, Water resource management, Geography, Geology, Geotechnical engineering
COMMUNICATION
Cross-lingual Code Clone Detection: When LLMs Fail Short Against Embedding-based Classifier
Micheline Benedicte Moumoula, Abdoul Kader Kabore, Jacques Klein, Tegawende F. Bissyande
Cross-lingual code clone detection has gained attention in softwaredevelopment due to the use of multiple programming languages.Recent advances in machine learning, particularly Large LanguageModels (LLMs), have motivated a reexamination of this problem.This paper evaluates the performance of four LLMs and eightprompts for detecting cross-ling(...)
Cross-Language Pairs, Code Clone Detection, Large LanguageModel, Prompt Engineering, Embedding Mode