Rene Richard

National Research Clouncil · Digital Technologies

In scenarios where obtaining real-time labels proves challenging, conventional approaches may result in sub-optimal performance. This paper presents an optimal strategy for streaming contexts with limited labeled data, introducing an adaptive technique for unsupervised regression. The proposed method leverages a sparse set of initial labels and int...

In scenarios where obtaining real-time labels proves challenging, conventional approaches may result in sub-optimal performance. This paper presents an optimal strategy for streaming contexts with limited labeled data, introducing an adaptive technique for unsupervised regression. The proposed method leverages a sparse set of initial labels and int...

Intelligence Everywhere is predicated on the seamless integration of INTERNET of Things (IoT) networks transporting a vast amount of data streams through many computing resources across an edge-to-cloud continuum, relying on the orchestration of distributed machine learning models. The result is an interconnected and collective intelligent ecosyste...

Anomalous behavior detection is an important component in many applications. Anomalies can represent problematic situations where early detection is critical to make situational assessments in the event of unexpected conditions. For many problems, the state of the art in machine learning is batch learning. However, online anomaly detection algorith...

Decoupling vehicles from the immediate consumption of fossil fuels introduces new opportunities in supporting sustainable mobility. Fostering a shift from vehicles with internal combustion engines to Electric Vehicles (EV) often involves using publicly funded subsidies. Given early EV adoption challenges, some charging stations may be under-utilize...

Transport electrification introduces new opportunities in supporting sustainable mobility. Fostering Electric Vehicle (EV) adoption integrates vehicle range and infrastructure deployment concerns. An understanding of EV charging patterns is crucial for optimizing charging infrastructure placement and managing costs. Clustering EV charging events ha...

Identification of rare events is an important component in intrusion and fraud detection, system monitoring and event detection. Anomalies can represent problematic situations where early, accurate and actionable insights are critical to make situational assessments in the event of unexpected conditions. For many problems, the state of the art in m...

Training Deep Learning (DL) models with missing labels is a challenge in diverse engineering applications. Missing value imputation methods have been proposed to try to address this problem, but their performance is affected with Massive Proportion of Missing Labels (MPML). This paper presents a approach for handling MPML in Multivariate Long-Term...

Electric vehicles (EVs) are part of the solution towards cleaner transport and cities. Clustering EV charging events has been useful for ensuring service consistency and increasing EV adoption. However, clustering presents challenges for practitioners when first selecting the appropriate hyperparameter combination for an algorithm and later when as...

Security and Information Event Management (SIEM) systems require significant manual input; SIEM tools with machine learning minimizes this effort but are reactive and only effective if known attack patterns are captured by the configured rules and queries. Cyber threat hunting, a proactive method of detecting cyber threats without necessarily knowi...

The vision for smart cities is to provide a core infrastructure that enables a good quality of life for their citizens and the sustainable management of natural resources. Towards this vision, supporting the adoption of Electric Vehicles (EV) contributes to improved air quality, sustainable mobility, and utility distribution. Fostering EV adoption...

The vision for smart cities is to provide a core infrastructure that enables a good quality of life for their citizens and the sustainable management of natural resources. Towards this vision, supporting the adoption of Electric Vehicles (EV) contributes to improved air quality, sustainable mobility, and utility distribution. Fostering EV adoption...

Background Expression quantitative trait loci (eQTL) mapping is often used to identify genetic loci and candidate genes correlated with traits. Although usually a group of genes affect complex traits, genes in most eQTL mapping methods are considered as independent. Recently, some eQTL mapping methods have accounted for correlated genes, used biolo...

One under-addressed issue in the field of Web Services composition is authentication between disparate services using different authentication methods or protocols. A Single Sign-On (SSO) framework reduces the burden on the end user to provide authentication credentials to these separate services; thus it is a desirable feature for systems and appl...

Objective: To develop a rule-based method for assisting consumers in automatically evaluating the quality of online health information. Methods: Eighteen measurable criteria related to quality of online health information were chosen, and for each criterion measurable indicators with indicator values and expected location in a web page were defined...

To develop and test a web-based Clinical Decision Support System (CDSS) tool, which integrated a new fuzzy multiple criteria classification methodology named PROAFTN in acute leukemia (AL) diagnosis. We have integrated a PROAFTN method and developed a web-based clinical decision support system using standard JSP, servlets, and XML technologies. All...

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