Hakim Bendjenna

Using multi‐criteria analysis to prioritize stakeholders

– Many problems in science and engineering fields involve decision making. Usually these decision‐making processes are based on several criteria that represent various experts knowledge. Stakeholder prioritization is useful for assisting in decision‐making situations where various stakeholders have competing interests, resources are limited, and stakeholder requirements must be appropriately balanced. When these conflicts arise it is important to the success of the organization that it has prioritized each stakeholder according to the situation. To date, few researchers tried to resolve this question, mostly are based on intuitive and very simple reasoning methods which are error prone. The purpose of this paper is to propose a multi‐criteria decision analysis process to help decision makers when evaluating and prioritizing stakeholders., – In this process, Mitchell et al.s model is used for identifying criteria on which stakeholders will be evaluated and the fuzzy Choquet integral as an aggregation operator. This research also tested and discussed the proposal using a case study from Toulouse city subway., – The results show the applicability of this process and the effectiveness of using the fuzzy Choquet integral than a traditional multi‐criteria evaluation method for human subjective evaluation, or when criteria are not mutually independent., – The highly subjective nature of criteria weights and rapid elicitation can lead to questions of validity. Also, results are not always widely accepted., – The paper is original in considering the stakeholder prioritization problem as a multi‐criteria decision analysis problem; using a simple and well‐known model to classify stakeholders, i.e Mitchell et al.s model; and in using Choquet integral as an aggregation operator which allows considering interaction between criteria.

Eliciting requirements for an inter‐company cooperative information system

Purpose – The requirements engineering (RE) process constitutes the earliest phase of the information system development life cycle. Requirements elicitation is considered as one of the most critical activities of this phase. Moreover, requirements elicitation is still a challenge, especially in the distributed environment of so‐called inter‐company cooperative information systems (ICISs). The purpose of this paper is to propose a methodology to elicit requirements for an ICIS.Design/methodology/approach – An analytical research approach was conducted. The current RE approaches, which are based either on goal, scenario or viewpoint were evaluated. Then the role of the elicitation technique selection step within the requirements elicitation process was examined. Finally the factors that affect this step in a distributed environment were studied. An example from the textile industry is used to illustrate the applicability of the proposed methodology.Findings – Though existing requirements elicitation approa...

Identifying and Modeling Non-Functional Concerns Relationships

Requirements elicitation step is of paramount importance in the requirements engineering process. In the distributed environment of so-called inter-company cooperative information system, this step is a thorny issue. To elicit require-ments for an inter-company cooperative information system, we early proposed a methodology called MAMIE (from MAcro to MIcro level requirements Elicitation) with an accompanied tool. In MAMIE methodology, requirements are the result of composing functional and non-functional concerns. Before non-functional concerns composition, it’s primary to identify relationships between them. According to the most existing approaches, a non-functional concern may have a negative, positive or null contribution on the other non-functional concerns. In this paper, we argue that using only these three contributions types is not sufficient to express relationships which may exist between non-functional concerns. Thus, we propose a process which aims to identify non-functional concerns’ relationships and model them using a fuzzy cognitive map. The resulting model is composed of non-functional concerns, relationships between them and the weight of these relationships expressed with linguistics fuzzy values. Using fuzzy cognitive maps to model non-functional concerns relationships allows moving from the conventional modelling toward developing a computer based model. An example from the textile industry is used to illustrate the applicability of our process.

Combining palmprint & Finger-Knuckle-Print for user identification

Biometrics is a field of analysis of biological characteristics of an individual. Its purpose is to recognize and automatically verify the identity of a person based on physiological or behavioral characteristics. Multi-modal biometrics which combining several biometric based systems, are increasingly studied. Indeed, they reduce some limitations of unimodal based biometric systems, such as the inability to acquire data of individuals or intentional fraud, while improving the recognition performance. These benefits of multi-modality with unimodal biometric based systems are obtained by fusing multiple biometric traits. In this paper, PaLMprint (PLM) and Finger-Knuckle-Print (FKP) modalities are combined to get the best of both worlds. They are recent and very important biometrics modalities due to there discriminatory power, robustness over time and there acceptability by users. To use, there characteristics must be extracted and enrolled for future comparison. The present proposed method is based on Histogram of Oriented Gradients (HOG) and Random Forest Transform (RFT) in order to improve the performance of the multi-modal biometric system based on PLM and FKP modalities. The results of the different classifiers are combined (fused) at the matching score level. In order to evaluate the proposed systems, a database of 165 persons is used. The obtained experimental results show the effectiveness and reliability of the proposed systems.

Multispectral palmprint identification method using rotation invariant variance measures

Biometric technologies are becoming the foundation of an extensive array of highly secure identification and personal verification solutions. Nowadays, palmprint identification is a novel and one of the most reliable biometrically based technology in applications of personal identification due to its highly stability and uniqueness. In this paper, biometric security system for access control based on multi-spectral palmprint is presented. To represent texture information, rotation invariant variance measures is used. Finally, a hamming distance score is employed to measure the similarity between templates of palmprints during the atching phase. The results show that a rotation invariant variance measure is robust to some extent in rotation of the images. The accuracy and speed of the proposed method can meet the requirements of an online biometric identification.

Incorporating the Negotiation Process in Urban Planning DSS

Cooperation in multi-agent systems is necessary in order to perform complex tasks and lead Multi-agent System MAS towards its objective. Contract-Net Protocol CNP is one of the communication and coordination mechanisms used by multi-agent systems which prefer cooperation through interaction protocols. This paper proposes a new cooperation and negotiation protocol based on the principals of the Contact Net Protocol CNP. The auhtors suggested negotiation protocol is used to solve one of the problems in the context of the city planning which is the problem of election of urban projects. Their proposed protocol is intended to the decision makers in order to help them resolve the problem of the evaluation and the selection of the best urban project without the need to be together in a decision urban room.

Implementing a Cloud-Based Decision Support System in a Private Cloud: The Infrastructure and the Deployment Process

This paper introduces the architecture and the deployment of a Cloud based decision support system DSS. The DSS the authors proposed is deployed on a platform Cloud CloudBees and managed by the OpenStack infrastructure. The DSS is built on the Cloud Computing architecture with three layers and includes the multiple criteria decision making MCDM method PROMETHEE II as well as the procedure of negotiation Hare in order to help the decision makers to select the best urban project. The Cloud based DSS reduces the deployment and processing time, ameliorates the communication and the cooperation between the decision makers, facilitates the accessibility and decrease the cost. The Cloud based multiple criteria DSS the authors designed and implemented has significant advantages. It reduces the deployment and processing time, ameliorates the communication and the cooperation between the decision makers, facilitates the accessibility, and decrease the cost.

Enhancing Elicitation Technique Selection Process in a Cooperative Distributed Environment

Requirements elicitation is a key stage in the successful designing of the computerized information system of a distributed organization. Few works have been focusing on how a requirements analyst selects one of the existing requirements elicitation techniques, notably in a distributed cooperative environment. However, the elicitation technique selection process creates significant communication, coordination, cultural and processes diversity challenges which impact the effectiveness of all the requirements engineering process and, further, product quality. This paper presents a decision making process that allows a requirements analyst to choose an elicitation technique in a cooperative distributed environment based on stakeholders preferences, linguistic knowledge and priorities.

MAMIE: A Methodology to Elicit Requirements in Inter-company Co-operative Information Systems

In this paper, we propose a methodology, namely MAMIE (from MAcro to MIcro level requirements Elictation) in order to elicit requirements for an Inter-company Co-operative Information Systems development. It is based on UML use cases and sequence diagrams: they represent understandable notations by all stakeholders and they are useful for acquiring, analyzing and modeling requirements. The sequence diagram allows also to model interaction between companies and constraints of co-operation. MAMIE methodology is also based on viewpoints which have advocated as a means of partitioning requirements as a set of partial specifications that are helpful for traceability and consistency management. Preliminary results suggest that MAMIE methodology is of valuable help to requirements engineers during elicitation process.

Improving Biometric Identification Performance Using PCANet Deep Learning and Multispectral Palmprint

Biometric technology is an emerging field of information technology that recognizes a person based on a feature vector derived from specific physiological or behavioral characteristic that the person possesses. In the last few years, several works in the field of biometrics got to improve the identification system performance rather than the traditional methods. So far, with the pace of rapid evolution in these works, new biometric modality (palmprint) is appearing to make the process of identification more efficient. There are a number of studies addressing the palmprint modality and the majority of these studies are mainly based on image captured under visible light. However, multispectral imaging technology has been recently used to improve the performance of biometric system. Furthermore, the feature extraction phase plays an important role in the biometric system. For that, several researchers are focused on methods used to extract the majorities of the characteristics that can discriminate each modality, which can decrease the intra-class variability and increase the inter-class variability. In this context and with the growing interest in biometrics applications, the studies in this chapter try to combine the multispectral imaging of palmprint and a new feature extraction method, called PCANet deep learning, in order to improve the system accuracy. To evaluate the performance of the proposed scheme, a database containing palmprint images was required. Thus, experiments were performed using two popularly databases: PolyU and CASIA databases.