Software requirements engineering deals with: elicitation, specification, and validation of software requirements. Furthermore there is a need to facilitate collaboration amongst stakeholders and analysts. Fewer efforts were deployed to support them in performing their job on a day to day basis. To solve this problem we use knowledge management for software requirements engineering. This paper proposes a knowledge management framework, based on the SECI model of knowledge creation, aimed at exploiting tacit and explicit knowledge related to software requirements within a given software project. The core part of the proposed framework is a set of four sub systems “Socializer”; “Externalizer”; “Combiner”; and “Internalizer”, attached to a couple of domain ontologies and a set of knowledge assets. Indeed we aim to facilitate a semantic based interpretation of knowledge assets related to software requirements by restricting their interpretation through the application domain and software requirements ontologies. We anticipate that this framework would be very helpful for stakeholders as well as analysts to exchange and manage their knowledge within a given software project. We show in the case study, through a virtual payroll project using the two-step approach: domain level requirements plus design level requirements, how the key elicitation SRE techniques are used during the first phase of domain requirements elicitation through the four subsystems of our framework

The control of supply chains passes often by identification of various constraints and optimization of the different links and parameters associated to the functioning of the supply chain. To attain these goals, it is vital to get the best knowing and understanding of the supply chain diversity and complexity also to anticipate its behavior, which requires, a pertinent modeling that will offer the necessary information to evaluate the supply chain performance. The present paper focuses on modeling and simulation of a case study of a supply chain using SIMAN ARENA ® Rockwell software, mainly transport and different operations in this chain. The purpose is creating the simulation models and how to use in a case study to diagnose and master the operation and functioning of this supply chain. The objective is creating simulation models to determine the performance of the supply chain by calculating the transportation time in each travel, number of travels, number of transported fertilizers and sulfur wagons and unloaded acid talks and finally the waiting times in train station, in order to optimize this performance indicators.

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Grouping learners in cooperative learning can help interaction and discussion among learners.However two main problems must be settled so as to group learners. The first is how to build the learner model, which describes the attributes of learners. The second is which technique would be appropriate for learners grouping according to the selected learner model. This paper aims to propose a novel cooperative learning approach using a multiple-intelligence based learners grouping technique. This contribution is three folds: (1) a conceptual model of learners' intelligence, (2) a pre-learning process that aims at: (a) acquiring knowledge of individual learners' intelligence according to the conceptual model of learners' intelligence; (b) grouping the learners into balanced groups based on this intelligence; and (c) calculating knowledge of collective intelligence, useful for cooperative learning during the learning process, and (3) a framework architecture, in order to support the new cooperative learning approach and demonstrate its feasibility. ß

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Requirements engineering is one of the most important pillars of software engineering. Its success contributes greatly to that of the software as a whole. In fact, the software development process is not devoid from changing requirements, which affects the cost, time, and quality of the final software. The change problem is unavoidable and also swells when the development of the software is made globally. Therefore, there is a need to improve the quality of requirements change management (RCM), especially in global software development (GSD) environments. Our research hypothesis is that the RCM is naturally a knowledge-intensive process that can benefit substantially from ontology. Indeed, we assume that using a multilevel ontology framework will greatly support RCM in GSD environments by ensuring the semantic correctness of the requirement change request and accordingly solving miscommunication and misunderstanding problems. The framework was successfully evaluated using a questionnaire and a case study. The results indicate that using the proposed framework can intensely improve the semantic correctness of requirement change requests. Accordingly, the entire RCM process is then improved by increasing the reliability of the change and reducing the time consumed for dealing with semantically wrong change requests. INDEX TERMS Requirement engineering, global software development, requirement change management, change requests, ontology.

We present a new interactive segmentation framework to segment the prostate from MR prostate imagery. We first explicitly address the segmentation problem based on fast globally Finsler Active Contours (FAC) by incorporating both statistical and geometric shape prior knowledge. In doing so, we are able to exploit the more global aspects of segmentation by incorporating user feedback in segmentation process. In addition, once the prostate shape has been segmented, a cost functional is designed to incorporate both the local image statistics as user feedback and the learned shape prior. We provide experimental results, which include several challenging clinical data sets, to highlight the algorithm's capability of robustly handling supine/prone prostate segmentation task.