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The security of personal data is crucial for a company or any individual. Phishing is one of the most common and dangerous cybercrime attacks. These attacks aim to steal information used by individuals and organizations using social engineering, which is a key point for the success of the phishing attack. Even though there are several systems and solutions, the amount of personal information stolen continues to increase as cyberattacks become more difficult to detect. This paper consists of a broad review to study the work carried out in the fight against phishing and the identification of vulnerabilities in existing systems to achieve better efficiency. The authors focused on the social medium Twitter to study the phishing attacks passing through this medium, and they present their new design, which is based on new features. The classification of the approach includes 23 features and uses the MLP artificial neural network (ANN MLP) algorithm. Experiments show that the system is effective at detecting phishing sites, with a 96% success rate using recent data.

Social networks are used by terrorist groups and people who support them to propagate their ideas, ideologies, or doctrines and share their views on terrorism. To analyze tweets related to terrorism, several studies have been proposed in the literature. Some works rely on data mining algorithms; others use lexicon-based or machine learning sentiment analysis. Some recent works adopt other methods that combine multi-techniques. This paper proposes an improved approach for sentiment analysis of radical content related to terrorist activity on Twitter. Unlike other solutions, the proposed approach focuses on using a dictionary of weighted terms, the Word2vec method, and trigrams, with a classification based on fuzzy logic. The authors have conducted experiments with 600 manually annotated tweets and 200,000 automatically collected tweets in English and Arabic to evaluate this approach. The experimental results revealed that the new technique provides between 75% to 78% of precision for radicality detection and 61% to 64% to detect radicality degrees.

Nowadays the current market is in evolution, organisations must work together to ensure their survival. The collaboration partners are heterogeneous and incompatible, which makes the interaction and exchange between them complicated, and requires new technologies to support them. This paper presents a knowledge management-based approach for inter-organisational collaborative processes IOCP modelling. Ontologies represent an effective solution to deal with the heterogeneity and incompatibility problems in different domains. Collaboration ontologies provide a way to promote its modelling. In this domain, there are only few ontologies which cover it partially. The developed system is composed of three part: 1) gathering and formalising collaborative network knowledge; 2) storing knowledge in a knowledge-based to infer the collaborative process model; 3) the IOCP modelling. The heart of this knowledge-based system is a modular ontology conceived to cover as maximum as possible the collaboration domain. The proposed system was conceived as a part of a collaborative platform allowing the modelling of the IOCP in a generic way.

Social media are used by hundreds of millions of users worldwide. On these platforms, any user can post and share updates with individuals from his social network. Due to the large amount of data, users are overwhelmed by updates displayed chronologically in their newsfeed. Moreover, most of them are irrelevant. Ranking newsfeed updates in order of relevance is proposed to help users quickly catch up with the relevant updates. In this work, the authors first study approaches proposed in this area according to four main criteria: features that may influence relevance, relevance prediction models, training and evaluation methods, and evaluation platforms. Then the authors propose an approach that leverages another type of feature which is the expertise of the update's author for the corresponding topics. Experimental results on Twitter highlight that judging expertise, which has not been considered in the academic and the industrial communities, is crucial for maximizing the relevance of updates in newsfeeds.

Enterprises are progressively embedded in business to business atmospheres, in order to achieve their common business objectives. Such collaborations lead to Inter-Organizational Business Processes. Therefore, IOBP modeling involves new challenges, mainly the ability to deal with autonomy, privacy, heterogeneity. As a contribution in this area, a IOBP meta-model was designed. This model takes into account the maximum concepts related to the collaboration. Where, the process is complex, and its model in a global way affects its vision and complicates its implementation and hence the idea of its analysis into sub-IOBP to reduce the complexity of the global collaborative process, to streamline information exchange and to facilitate the understanding of the process by partners. A set of Atlas Transformation Language (ATL) transformation rules has been defined to convert Unified Modeling Language (UML) models to Business Process Model and Notation. Finally, the application of our approach has been demonstrated through a framework which can solve the problem of generic IOBP.

The emergence of spatial or geographic data in DW Systems defines new models that support the storage and manipulation of the data. The need to build an SDW and to optimize SOLAP queries continues to attract the interest of researchers in recent years. Several spatial data models have been investigated to extend classical multidimensional data models with spatial concepts. However, most of existing models do not handle a non-strict spatial hierarchy. Moreover, the complexity of the spatial data makes the execution time of spatial queries very considerable. Often, spatial indexation methods are applied to optimizing access to large volumes of data and helps reduce the cost of spatial OLAP queries. Most of existing indexes support predefined spatial hierarchies. The authors show, in this article, that the logical models proposed in the literature and indexing techniques are not suitable to non-strict hierarchies. The authors propose a new logical schema supporting the non-strict hierarchies and a bitmap index to optimize queries defined by spatial dimensions with several non-strict hierarchies.

Business intelligence systems provide an effective solution from large volumes of data for multidimensional online computing and analysis. Usually, in a decision-making process, organisations and enterprises, require several internal and/or external cubes which are often heterogeneous. Most of the time, the structure of these cubes is unknown to the decision-makers. To analyse a phenomenon, the decision-maker seeks among sets of cubes, in a collection, the cube which responds better to his need. In this context, we propose an approach that enables decision-makers to express their needs via a query expressed in a natural language, returns top-K relevant cubes and designs/constructs new cubes when no, or few deployed cubes are relevant. We propose a tool called RD-cubes-query implementing our approach in a ROLAP architecture. We use this tool in some experiments to validate our approach.

The upper member of the Jafnayn Formation in Wadi Rusayl and Al Khoud, Seeb Area in north Oman contains Nemkovella stockariLess & Özcan, 2007, an Early Eocene orthophragminid recorded here for the first time from the Arabian Peninsula. N. stockari, the only orthophragminid identified in Jafnayn Formation, is quite distinct from any other species from Tethys in having spiral and orbitoidiform chambers around the isolepidine embryon developed before the onset of annular chambers. The Oman specimens exhibit equal-sized principal auxiliary chambers and symmetrical spirals and are assigned to N. stockari bejaensisÖzcan, Boukhalfa & Scheibner, 2014, an advanced form of the N. stockarilineage. The associated alveolinids, revised in this study, rotaliids and other age-diagnostic foraminiferal taxa in the transgressive basal part of the upper member have enabled us to revise the age as middle Ilerdian (Early Eocene), assignable to SBZ 7/8 and 8; OZ 3/4. Integrating a new record of this species from Arabian Plate margin in Belen, S Turkey, and previous records from north Africa, N. stockariappears to be a diagnostic marker for the Early Eocene along the southern peri-Tethys platforms, facilitating the Tethyan correlation by orthophragminids. The palaeobiogeographic distribution of N. stockariis discussed.

Geographic Information (GI) is currently available at any time, from anywhere on the surface of the earth, for any person connected to internet. Some applications of design, implementation, generation and dissemination of maps on the web are recognized as “Webmapping” application, geographic web services or more generally on demand-map making tools. All these web applications aims the satisfaction of user needs by providing personalized maps in a fast response time with a good quality. However, the complexity and diversity of aspects taking into account have lead researchers to focus on one aspect at the expense of others. Consequently, few works have addressed all these aspects simultaneously. The authors propose in this paper, a Webmapping approach organized into two main tasks: (1) query analysis driven by domain ontology in analyzing a query launched by a user on a web browser and (2) map generation process. The first step allows extracting and formalizing user needs through two map determinants factors: the Level of Detail (LoD) and Point of View (PoV) and the second, exploit an hybrid approach “Multi Representation and Generalization” in storing and generating geographical data with integrating Multi-Agent technology in all steps of processing. To evaluate the effectiveness of our proposal, a first tool prototype implementing our approach is so developed using a geographic vector dataset provided by national cartographic agency.

The orthophragminids in lower Bartonian Reineche Limestone member, a fossiliferous shallow-marine unit exposed in Cap Bon peninsula in Tunisia, are represented by 17 species assigned to Discocyclinidae Galloway 1928 and Orbitoclypeidae Brönnimann 1946. These taxa, associated with nummulitids and alveolinids, belong to the lineages of DiscocyclinaGümbel 1870, Nemkovella, 1987, OrbitoclypeusSilvestri 1907, and AsterocyclinaGümbel 1870, described for the first time from north Africa lying at the southern margin of Tethyan ocean during Paleogene. We identified Nemkovella evae, previously not recorded in upper Lutetian/lower Bartonian and younger Eocene deposits of northern Tethyan platforms, and erected a new subspecies, N. evae reinechensisn. ssp. A comparison of Reineche orthophraminids, assigned to orthophragmines zone (OZ) 12 and shallow benthic zone (SBZ 17), to the well-described coeval assemblages at northern Tethyan platforms in Italy, Hungary, Turkey, and to those in Kutch Basin in the Indian subcontinent suggests that some species are confined to certain paleogeographic domains. Orbitoclypeus haynesi, the only orbitoclypeid and the most abundant orthophragminid in lower Bartonian deposits in Kutch, appears to be the most common orbitoclypeid in Reineche Limestone. In Europe, this species is not known and is replaced by Orbitoclypeus varians, the most common orbitoclypeid in middle Eocene of central Europe. Both species occur in varying proportions in marine successions in Turkey. Asterocyclina sireli, identified so far only in Turkey, occurs in Reineche Limestone and in lower Bartonian deposits in Kutch. This species is recorded for the first time in the Indian subcontinent. Relying on present study, as well as our recent studies in Kutch Basin, we conclude that the generic and specific diversity of orthophragminids decreases eastward from the peri-Mediterranean region to Indian subcontinent and to the western Pacific.

Horizontal Partitioning has been largely adopted by the database community, where it took a significant part in the physical design process. Actually, it is supported by most commercial database systems (DBMS), where a native Data Definition Language for decomposing tables/materialized views using various modes is proposed. In traditional databases, horizontal partitioning has been largely studied, where several fragmentation algorithms were proposed to partition tables in isolation. In the relational data warehouse environment, horizontal partitioning consists in decomposing the whole warehouse schema into sub schemas, where each schema contains fragments of dimension and fact tables. Dimension tables are fragmented using the primary partitioning mode, whereas the fact table is divided using referential mode. In this article, the authors first focus on the evolution of horizontal partitioning in commercial DBMS motivated by decision support applications. Secondly, they give a formalization of the referential fragmentation schema selection problem in the data warehouse and they study its hardness to select an optimal solution. Due to its high complexity, they develop two algorithms: hill climbing and simulated annealing with several variants to select a near optimal partitioning schema. Finally, extensive experimental studies are conducted using the data set of APB1 benchmark to compare the quality the proposed algorithms using a mathematical cost model. Based on these experiments, some recommendations are given to advise database administrator for well using horizontal partitioning.