Zohra Bakkoury

Analyzing risks in business process models using a deviational technique

In a business environment, many processes are performing ineffectively due to different risks. Several methods and techniques for the identification and management of risks in business processes have been proposed. Some of them originate from other domains and have been adapted to the business environment such as deviational approaches. Nevertheless, there are few examples for potential applications of those methods in business process redesign. This paper addresses this gap through proposing an approach that adapts HAZOP (HA-Zard OP-erability), a systematic deviational technique, to business process environment. We discuss how this method can contribute to the improvement of business process models.

A New Cluster-Based Paradigm for SIP Routing in MANET

We propose a new paradigm based on a time varying grid to handle SIP routing over MANET. This paradigm takes advantage of the geometric properties of the square grid in order to establish calls using the closest route to the callee in terms of physical distance. Normally, shorter paths and optimized latencies are reached by broadcast based approaches where bindings of the whole network are stored in every single node and where SIP REGISTER messages are flooded. Our approach utilizes a grid based clustering method to arrange MANET nodes in an organized structure during the initialization phase in order to mark the centroid of each cluster. Then, the structure is updated periodically using the initial coordinates of the centroids. We resort also in this work to the use of replication in an astute manner in order to sidestep to the need of flooding based solutions.

Approaches to Access Biological Data Sources

In recent years, technological revolutions in genomics and proteomics have revolutionized the work of researchers in molecular biology. Through various techniques of data generation, they have at their hand in the web a very large amount of information contained in public and heterogeneous data sources. Each source has content organized around a particular data type like sequences in Uniprot (for proteins) and Genbank (for gene and mRNA), protein structure in PDB (Protein Data Bank) and publications in biomedical Medline. Their content is heterogeneous in the sense that a similar data can be represented differently in two data sources (eg different names for the same gene). More data sources have a variety in terms of structure, and there are sources of structured data, such as relational databases or semi-structured sources like XML and unstructured sources such as databases composed of flat files. That is to say that a biologist who wishes to obtain information from these sources have to question these one by one, then copy and analyze the data collected, and manage redundancy, complementarities of the information and inconsistencies. Today, one of the greatest challenges of bioinformatics is to enable biologists to effectively access multiple data sources, each with a different pattern. Various approaches have been adopted to unify access to various data sources given a query. Several systems have been produced from data warehouses, a federation of databases or mediators.