User profiles for S. Aridhi

Sabeur Aridhi

Associate Professor (Maître de conférences), University of Lorraine
Verified email at loria.fr
Cited by 1749

Application of artificial intelligence to gastroenterology and hepatology

C Le Berre, WJ Sandborn, S Aridhi, MD Devignes… - Gastroenterology, 2020 - Elsevier
… A neural network that analyzes morphometric images of early-stage biopsies from patients
with Crohn’s disease identified those with disease progression with approximately 83.3% …

[HTML][HTML] The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens

…, M Mesiti, DB Roche, J Reeb, DW Ritchie, S Aridhi… - Genome biology, 2019 - Springer
Background The Critical Assessment of Functional Annotation (CAFA) is an ongoing, global,
community-driven effort to evaluate and improve the computational annotation of protein …

Big graph mining: Frameworks and techniques

S Aridhi, EM Nguifo - Big Data Research, 2016 - Elsevier
… if its support is greater than a minimum support threshold: s u p p o r t ( g ) > m i n S u p p . …
11, Hill et al.'s approach generates the set of frequent subgraphs by performing two …

An experimental survey on big data frameworks

W Inoubli, S Aridhi, H Mezni, M Maddouri… - Future Generation …, 2018 - Elsevier
… per second varies between 375 KB/s and 385 KB/s in the case of Flink, and varies between
387 KB/s and 390 KB/s in the case of Storm and about 400 Mb/s in the case of Samza. This …

Preesm: A dataflow-based rapid prototyping framework for simplifying multicore dsp programming

…, J Heulot, C Guy, JF Nezan, S Aridhi - 2014 6th european …, 2014 - ieeexplore.ieee.org
… link for each core at 16 GB/s while the external DDR3 has a unique link to the processor
at 10.6 GB/s. More advanced features are representable in S-LAM such as the delegation of …

Accuracy and diversity-aware multi-objective approach for random forest construction

…, AA Korba, A Assi, H Seridi, S Aridhi… - Expert Systems with …, 2023 - Elsevier
… First, a training sample T r i will be generated by using L i , I d S i and I d R i as follows: (1)
A set S i of instance indexes is generated by using the Algorithm 1 and Eq. (3) ( E is an array …

Pimm: Parameterized and interfaced dataflow meta-model for mpsocs runtime reconfiguration

…, JF Nezan, SS Bhattacharyya, S Aridhi - 2013 International …, 2013 - ieeexplore.ieee.org
Dataflow models of computation are widely used for the specification, analysis, and optimization
of Digital Signal Processing (DSP) applications. In this paper a new meta-model called …

Improving memory-based user collaborative filtering with evolutionary multi-objective optimization

NEI Karabadji, S Beldjoudi, H Seridi, S Aridhi… - Expert Systems with …, 2018 - Elsevier
… subset of profiles P s index i d P s − p 0 , we generate the appropriate P s . Now, an … s , P s
can be generated as follows: First, we generate P s with only the index of p s 0 (ie., P s = { p s 0 …

[HTML][HTML] The uncertain cloud: State of the art and research challenges

H Mezni, S Aridhi, A Hadjali - International Journal of Approximate …, 2018 - Elsevier
During the last decade, cloud computing became a natural choice to host and provide
various computing resources as on-demand services. The correct characterization and …

Distributed k-core decomposition and maintenance in large dynamic graphs

S Aridhi, M Brugnara, A Montresor… - Proceedings of the 10th …, 2016 - dl.acm.org
Distributed processing of large, dynamic graphs has recently received considerable attention,
especially in domains such as the analytics of social networks, web graphs and spatial …