Parallel swarm intelligence strategies for large-scale clustering based on MapReduce with application to epigenetics of aging

Clustering is an important technique for data analysis and knowledge discovery. In the context of big data, it becomes a challenging issue due to the huge amount of data recently collected making conventional clustering algorithms inappropriate. The use of swarm intelligence algorithms has shown promising results when applied to data clustering of moderate size due to their decentralized and self-organized behavior. However, these algorithms exhibit limited capabilities when large data sets are involved. In this paper, we developed a decentralized distributed big data clustering solution using three swarm intelligence algorithms according to MapReduce framework. The developed framework allows cooperation between the three algorithms namely particle swarm optimization, ant colony optimization and artificial bees colony to achieve largely scalable data partitioning through a migration strategy. This latter reaps advantage of the combined exploration and exploitation capabilities of these algorithms to foster diversity. The framework is tested using amazon elastic map-reduce service (EMR) deploying up to 192 computer nodes and 30 gigabytes of data. Parallel metrics such as speed-up, size-up and scale-up are used to measure the elasticity and scalability of the framework. Our results are compared with their counterparts big data clustering results and show a significant improvement in terms of time and convergence to good quality solution. The developed model has been applied to epigenetics data clustering according to methylation features in CpG islands, gene body, and gene promoter in order to study the epigenetics impact on aging. Experimental results reveal that DNA-methylation changes slightly and not aberrantly with aging corroborating previous studies

Algerian Dialect

These datasets have been gathered using the YouTube API. These comments are sorted by relevance from more than 30 Algerian press channels. The dataset consists of 45,000 annotated comments, with five class sentiments, namely very negative (0), negative (1), neutral (2), positive (3), and very positive (4).Here's the columns description:Column 1: commentsColumn 2: label (from 0 to 4)Column 3: collection dateColumn 4: like countColumn 5: video URL from which the comment has been extractedColumn 6: annotation datetimeTHIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV

Algerian Dialect

These datasets have been gathered using the YouTube API. These comments are sorted by relevance from more than 30 Algerian press channels. The dataset consists of 45,000 annotated comments, with five class sentiments, namely very negative (0), negative (1), neutral (2), positive (3), and very positive (4).Here's the columns description:Column 1: commentsColumn 2: label (from 0 to 4)Column 3: collection dateColumn 4: like countColumn 5: video URL from which the comment has been extractedColumn 6: annotation datetimeTHIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV

EVALUATION OF CEMENT THIXOTROPY FOR THE CEMENT OF OIL WELLS IN AREAS WITH LOSSES: EFFECT OF PLASTER AND DAIRY OF HIGH FURNACES

Cementing of oil and gas wells can be a very delicate operation. Among the concerns of service companies, during this operation are the nature and conditions of the formations in well. This is the case of cementing operations in southern Algeria, specifically on the fields of In-Amen, where the formations in lost zones are naturally weak and highly permeable. In these areas, drilling fluids (muds and cements) pumped will be, completely or partially lost, what we call "lost circulation". Thixotropic cements are useful to overcome lost circulation problems. They are characterized by a special rheological behavior, allowing it to plug lost zones when they are pumped. Our work aims to assess the thixotropy of cements perapred with two types of cement (class G Asland cement and CEM I 42.5 portland cement) with the plaster, using a viscometer with coaxial cylinder (couette type). Moreover, the effect of blast furnace slag (LHF) on the properties and thixotropic mixtures prepared was also studied. The results show that portland cement (available locally) can produce mixes with higher and more stable thixotropy than the class G cement (from importation), which is a practical and economical for cementing job operations in wells with loss zones. The results also show that the effect of LHF is positive, since in addition to his contribution to long term performances, especially the durability of hardened concrete, it improves the thixotropy of cement made of plaster