Atif Mashkoor

Formal Domain Modeling: From Specification to Validation ⋆

The main theme of this research is to study and develop techniques for the modeling of software controlled safety critical systems. In this work, we formally specify different entities, phenomena and their inter-relationships, and specially non functional properties related to land transportation systems with refinement based approach at domain level. We also introduce a stepwise validation process to maintain seamlessness between environment and its captured models. We apply our results on two safety critical case studies.

Introduction

Having good understanding of an application domain is a crucial prerequisite to develop software within that domain. The understanding of a domain is referred to as a domain model. A domain model is a conceptual model of a system which describes various entities, phenomena and their inter-relationships, along with their important static and dynamic properties of the domain. The domain model may be expressed in the form of requirements, specifications, or architectural references.

According to [START_REF] Bjørner | Development of transportation systems[END_REF], if domain models and requirements of software are not formally expressed, software correctness can not be meaningfully achieved. Safety is also one of the major factors which can not be overlooked while designing complex and critical systems. The development of correct and safe systems can be difficult and error prone with traditional software development methods. However, use of formal methods, in order to ensure their correctness and to structure their development from domain modeling to implementation, can significantly help system development.

Formal languages are notoriously difficult to read for the non-initiated. Furthermore, well-written specifications often introduce abstract objects and operations that have no intuitive concrete counterpart. Hence, validation has to wait. This implies that the development of the model requires an uncomfortable level of trust.

The pivotal concept of formal methods such as B [START_REF] Abrial | The B Book[END_REF] is the notion of refinement and its relation to correctness. The assessment of the correctness of a piece of code, its verification, is no more a unique big process step but it is broken down into small pieces along with the whole development process. The proof of correctness is the sum of the proofs of small assertions (invariant preservation, well-formedness, existence of abstraction function, etc.) associated to each refinement. Likewise, the technique of animation could be used with each refinement step to break its validation into smaller assessments.

Introduction of validation into refinement based processes yields two advantages: First, early detection of problems in the models (say, misunderstanding about a certain behavior) should be easier and inexpensive to correct. Second, users can be involved into the development right from the start.

In this work, we focus on animation technique which is the "execution" of a specification as a mean to validate it. Thanks to the development of tools, like Brama [START_REF] Servat | BRAMA: A New Graphic Animation Tool for B Models[END_REF], it is possible to animate specifications in B or Event-B [START_REF] Abrial | Modeling in Event-B: System and Software Engineering[END_REF] before they reach an implementation stage. However, there are restrictions on the kind of specifications that can be animated. Non-constructive definitions, infinite sets, or complex quantified logic expressions are among the list of restrictions.

We devise a technique to animate abstract specifications by systematic transformations. The product of the transformations is a specification which may be non provable, but which is guaranteed to have the same behavior as the formally correct initial specification. This goal is achieved through the design of a set of transformation heuristics whose correction is rigourously asserted and a rigorous process.

The main aim of the research is two fold: first, formal modeling of data, behaviors, protocols, interaction between elements, and non-functional properties of transportation domain and second, to incorporate a stepwise validation technique into the overall modeling process.

The presentation of the paper is organized as follows: Next section presents the language and tool we use: Event-B and Brama. Then we present a stepwise specification and validation process for domain modeling. Two case-studies are described thereafter to show how we have implemented our approaches. Finally, we conclude that what should now be completed to have a technique that could be used as standard practice and our future research endeavors.

Tools

This section introduces the tools which we use for specification and validation.

Event-B

Event-B is a formal method for system-level modeling and analysis of large reactive and distributed systems. Main features of Event-B are the use of set theory and first order logic for modeling systems, the use of refinement to represent systems at different levels of abstraction and the use of mathematical proof to verify consistency between refinement levels. Event-B is provided with tool support in the form of an Eclipse-based IDE called RODIN 1 which is a platform for writing and proving Event-B specifications.

Brama

Brama is an animator for Event-B specifications. It is an Eclipse based plug-in for the RODIN platform which can be used in two complementary modes. Either Brama can be manually controlled from within the RODIN or it can also be connected to a Flash graphical animation through a communication server; it then acts as the engine which controls the graphical effects.

Stepwise specification and validation

In order to verify complex systems against their requirements, the breakdown of overall system into different levels of abstraction is highly recommended. This can be achieved by their stepwise development. To specify our domain models we follow the same principle. We start from abstract requirements, we gradually refine them to achieve concrete and fine grained description of the model, and verify each refinement step against the specification constructed in the previous refinement.

We use two different notions of refinement to specify our models: horizontal refinement and vertical refinement. In horizontal refinement the details are added to the model while remaining at the same level of abstraction. However in vertical refinements we add the description to the model while making a leap to the next abstraction level.

Once a domain model has been specified and verified, an important question arises: does it accurately capture the environment? While proof tools guarantee the consistency of the specification, they are of little help to check if it is the true representation of the environment. Like the verification of the model can be broken down into smaller proofs associated with each refinement step, we use the technique of animation at each refinement step to break its validation into smaller assessments.

Animation of specification is not that straightforward because it heavily depends upon tools. Any limitation of the tool will be a restriction on the class of animatable specifications. To validate a specification which does not belong to this class, we need to "bring it in." We do this by applying transformation rules which are designed to keep the behavior unaltered, possibly at the expense of other properties.

Experimenting with Brama on two Event-B safety critical systems-a formal domain model of land transportation [START_REF] Mashkoor | B événementiel pour la modélisation du domaine: application au transport[END_REF] and a situated multi-agent platooning system [6]-we have dressed up a typology of five general cases:

1 Brama forbids finite clauses in axioms 2 Brama interprets quantifications as iterations 3 Brama cannot compute dynamic functional bindings in substitutions 4 Brama does not compute analytically defined functions 5 Brama has limited communication with its external graphical environment This lead us to design 10 transformation heuristics [START_REF] Mashkoor | Incorporating Animation in Stepwise Development of Formal Specification[END_REF] expressed following the pattern shown by figure 1.

Fig. 1. The heuristic pattern

We designed the heuristics to preserve the behavior of the specification, not its formal properties. In particular, the transformed specification may not be provable. The correctness of the transformation is then a crucial issue.

Since heuristics cannot be "proven" within B formal logic system, we relied on the mathematical tradition of rigorous arguments. For this to work, we need a basic assumption: the initial specification text must have been formally verified. Most of the arguments given in the Justification clause of heuristic rely on this hypothesis.

A verified specification must be the starting point of the validation process. The application of the heuristics will "downgrade" it to a non provable specification. Running the animation may uncover some mistakes. These entail the modification of the initial specification, which then must be verified, and transformed again for proceeding with the validation. This is summed-up in figure 2.

4 Case studies Fig. 2. The validation process This section describes two case studies which were the incentive for this work. Both specifications concern the domain of land transport systems. They are part of cooperative projects. TACOS is an effort to integrate components and non functional properties into formal requirement specifications. In particular, safety critical properties must be assessed and formalized. CRISTAL is a joint project with the industrial goal of designing urban mobility systems based on autonomous vehicles. As these systems interact with humans and operate on public space, the certification issue is a major problem.

TACOS

The specification in this case study is about the modeling of the land-transportation domain. In the model, we want to express properties that any system working within the domain is expected to meet and maintain.

In this specification effort, the focus is on the formal definition of concepts, constraints and properties, rather than on the implementation of a particular system. Refinement is then used to introduce new notions; the proof Fig. 3. Levels of abstraction of transport domain model obligations serve to guarantee the consistency of the model. Our devised stepwise validation technique was used for the validation of the model whose details can be found in [START_REF] Mashkoor | Transformation Heuristics for Formal Requirements Validation by Animation[END_REF].

The current specification consists of 8 refinements (3 horizontal and 5 vertical). It is organized into five abstraction levels which are summarized by figure 3. A detailed description of the model can be found in [START_REF] Mashkoor | B événementiel pour la modélisation du domaine: application au transport[END_REF].

This specification exhibits several properties which call for validation, namely:

complex data which constraint behaviors (following a route), protocols and iterations (travel as sequence of stages, hub crossing protocol), and non deterministic interaction between elements (autonomous vehicles).

several non-functional properties, such as collision avoidance, timing, etc.

CRISTAL

The second case study deals with a specification of platooning. Platooning is a mode of moving where vehicles are synchronized and follow one another closely. A platoon can be seen as a road-train where cars are linked by software instead of hardware. A local Event-B specification of the model has been written [START_REF] Lanoix | Event-B specification of a situated multi-agent system: Study of a platoon of vehicles[END_REF] as an effort to make it amenable to the formal techniques required by certification. The specification consists of five machines (one abstract and four vertical refinements). Contrary to the previous case study, the structure of the development of this case study can be interpreted as a sequence of refinements toward an implementation. Each refinement decomposes some events to make explicit a part of the general computation.

We mainly use this case study to experiment our devised transformation heuristics for its validation. The underlying rationale was to observe the animation of a model based on kinematic laws specified by heavy use of functions and also to compare the results of the validation by animation with the results of validation by simulations that had been previously made.

Conclusion and future work

Using a modeling language which is not conceived particularly for domain engineering was a challenging task. Though we stumbled upon some shortcomings in Event-B (for example, lack of temporal constraints, lack of notion of sequences, etc.) yet, the general philosophy has been well suited to our purpose. The notions of events and non determinism allow us easy modeling of independent vehicles without any assumption other than their common property: they move. The strong safety constraints we have considered are also easily modeled. Modeling of other non functional properties, such as, collision avoidance, timing, etc. also did not pose great difficulties. All was done through standard refinement techniques. We are thus encouraged to proceed further with enrichment of current domain models specially with inclusion of more non functional properties, such as, oscillation, hooking/unhooking, etc.

While arguing about the relationship between refinement based modeling and its stepwise validation, we discovered that not every refinement step is animatable. This is consistent with using animation as a kind of quality-assurance activity during development. We believe that one animation per abstraction level is sufficient. In fact, the first refinement of a level may often have a non-determinism too wide to allow for meaningful animation (concept introduction), but subsequent refinements get the definitions of the new concept precise enough to allow animation.

The list of heuristics is not closed yet. In future this is expected to grow as we model and validate new properties of the domain. Manual application of these heuristics to specification is tedious, cumbersome and may be error prone if not applied carefully. Therefore we are planning to write a plug-in/tool which can apply these transformations automatically to specifications.

⋆ This work has been partially supported by the ANR (National Research Agency) in the context of the TACOS project, whose reference number is ANR-06-SETI-017 (http://tacos.loria.fr), and by the Pôle de Compétitivité Alsace/Franche-Comté in the context of the CRISTAL project (http://www.projet-cristal.org).

http://sourceforge.net/projects/rodin-b-sharp/


Oladejo Bolanle
email: oladejof@loria.fr

David Amos
email: amos.david@loria.fr

Osofisan Adenike
email: nikeosofisan@gmail.com

Representation of Knowledge Resource in the context of Economic Intelligence Systems

Keywords: Knowledge, Knowledge resource, Knowledge representation, Knowledge Capitalization, Economic Intelligence (EI), knowledge exploitation

Knowledge representation is an essential criterion to capitalization of knowledge in organizations. There is need for organizations to employ strategic methods to ensure optimal innovation and effective decision making. Thus, Economic Intelligence proffers strategy to facilitate effective decision making through collection, treatment and use of relevant information for economic actors in decision making process. There are knowledge and information on actors and from required activities respectively that need be capitalized in order to aid resolution of related future decision problems. It is imperative to establish a system of organization, representation, storage and transmission of these knowledge resources. The goal of this study is to provide adaptable framework and user-centered knowledge model for the representation and exploitation of knowledge in the decision making projects of the Economic Intelligence process by acquiring, organizing, integrating and capitalizing such knowledge in order to exploit it for reuse and sharing.

Introduction

The success of any socioeconomic organization concerns the management of its 'knows' and 'know-hows'. These include knowledge, experiences and skills of the organization. Socioeconomic organization structure may include any individual or collective ability to innovate and make strategic decisions. Economic Intelligence (EI) serves as a key for achieving strategic decisions. EI provides the resources that are enacted upon by actors to address decision problems in order to generate relevant information that resolves such problems ( [START_REF] Kislin | A model of information retrieval problem in Economic Intelligence context[END_REF]. The resources, actors, as well as information solution to decision problems constitute essential knowledge in the context of EI. Such knowledge could foster resolution of future problems that are related to the past ones. This benefit could only be feasible if the knowledge is acquired and stored. Thus, its representation with an appropriate formalism is required. It is only then knowledge can serve as a key for innovation in an organization with respect to its decisionmaking needs. The goal of this paper is to develop appropriate methods for capitalizing knowledge of decision-making projects of EI. We propose the use of an adaptable framework for representation and capitalization of such knowledge. The challenges of the research revolve around the required methods for acquisition, harmonization, and representation of knowledge of EI actors and activities. We generate a relational model based on the proposed framework to capture and represent knowledge. The main purpose of this model is to enable possible exploitation of stored knowledge in order to obtain relevant solution to new needs with less efforts and time.

The paper is divided into five sections. The first section introduces the motivation for and goal of the research. The related theoretical concepts are discussed in the second section. Our approach of representing knowledge in the context of EI constitutes the third section. The result observed from the implementation of the proposed framework for knowledge representation and capitalization is discussed in the fourth section. The paper is concluded by a summary of contribution and direction for future work.

2.0

Theoretical Background The concept of knowledge with the success criteria for its representation and exploitation is brought to limelight here. The viewpoint of Economic Intelligence with respect to information and the significance of knowledge required to achieving its goals are addressed in this section.

2.1

Knowledge There are several notions about knowledge from literatures. From philosophical point of view, it is referred to as justified true belief. This indicates that it is a belief. However, belief is a mental attitude or state of mind: a personal conviction or acceptance of a particular fact or idea. Most contemporary philosophers characterize belief as a 'propositional belief'. It cannot be regarded as knowledge due to the fact that it is only a disposition (Stanford Encyclopedia of Philosophy, 2006). Also, [START_REF] Blackburn | Truth: A Guide[END_REF] disputes that whatever the form of belief it cannot be regarded as knowledge. Thus, from epistemology (the study of knowledge), it is referred to as a perception or observation of an object or event as well as skill for or experience in performing an activity. There is another view of knowledge with respect to socio-economic perception.

Knowledge is referred to as a capital which has an economic value, and also serves as a new strategic resource for increasing productivity. [START_REF] Dieng-Kuntz R | Knowledge Management and Organizational Memories[END_REF]. This view is reinforced by [START_REF] Stata R | Organizational learning -the key to management innovation[END_REF] opinion that knowledge is the primary source of wealth in industries and traditional sectors of economy. This description of knowledge fails to pinpoint what it actually depicts or means.

According to Pohl, (2002) knowledge is defined as the addition of context to information where the latter is defined as the existing relationships among data i.e. numbers and words. In [START_REF] Miller | I = 0 (Information has no intrinsic meaning)[END_REF] knowledge is defined in terms of interpretation attributed to given information as claimed by the author that "information is intrinsically meaningless on its own and remains so unlessand until -it is interpreted by human beings, within some context". We take side with this view of knowledge.

From a critical and logical point of view, information could be seen as a message which has its borderline from which knowledge takes its landmark. That is to say, they are related and inseparable but distinct. Knowledge adds value to information when it (the latter) is analyzed with respect to surrounding circumstance or related facts. We conclude with the notion that knowledge refers to facts with its attributed meaning, where meaning is a function of an observation, learning, experience, and understanding of a reality in a particular situation or context at a specific period of time by an individual. Figure 1 summarizes our view. There is need to consider the classification of knowledge for the purpose of its representation.

Figure 1: what is knowledge?

Classification of Knowledge

From philosophical point of view, there are two kinds of knowledge with respect to experience, namely priori and posteriori knowledge (Stanford Encyclopedia of Philosophy, 2006). A priori knowledge is independent of experience, while a posteriori knowledge is dependent on experience. Howbeit, from [START_REF] Prusak | Knowledge-Can It Be Managed?[END_REF]: four kinds of knowledge are identified namely episteme, techne, phronesis and metis. Episteme refers to scientific principles while techne indicates technical know-how and community of practice. Phronesis refers to practical wisdom from social practice and metis is a form of practical knowledge. Nonetheless, there are two major types of knowledge: explicit (objective) and tacit (subjective) Knowledge. [START_REF] Nonaka | The knowledge-Creating Company: How Japanese Companies Create the Dynamics of Innovation[END_REF]. Table 1 Explicit knowledge could be expressed in form of theoretical and practical experience. It could be readily transmitted across individuals formally and systematically. On the other hand, tacit knowledge is in form of skill and it is highly personal and hard to formalize, thus, difficult to share with others. An obvious challenge is the issue of transformation of tacit knowledge into explicit knowledge in order to represent it in a way to aid its exploitation.

Transformation of Knowledge

There is need to explore tacit knowledge resource of an organization in order to represent and share (capitalize) it for optimal economic value. As earlier mentioned, explicit knowledge is already in a form which is easy to capture and formalize, on the other hand, it is not so for tacit knowledge. Thus, it requires a transformation process to convert it to explicit knowledge before it could be capitalized or managed. There are four modes of conversion involved in this process namely, socialization, externalization, internalization and combination [START_REF] Nonaka | The knowledge-Creating Company: How Japanese Companies Create the Dynamics of Innovation[END_REF]. Table 2 describes the transition between tacit and explicit knowledge for each of the modes. Organization can only become innovative and can gain a competitive advantage when it recognizes the significance of knowledge of both individual and group involved in its operation and who contribute to its existence. This realization on its own does not suffice unless there is a conscious effort directed towards acquisition and representation of existing knowledge. Then will it become feasible to exploit the knowledge in addressing new problem. Thus, this necessity requires the method of capitalization of knowledge.

2.2

Knowledge Capitalization Knowledge Capitalization (KC) can be viewed as the task of mapping the existing knowledge of an organization in terms of the stored information which entails the specific states, (what, when and how) of decision taken to a current similar decision-problem in order to re-use the knowledge [START_REF] Dieng-Kuntz R | Knowledge Management and Organizational Memories[END_REF]. In other words, to capitalize knowledge means " to reuse, in a relevant way, the knowledge of a given domain previously stored and modeled, in order to perform new tasks" [START_REF] Simon | Knowledge Acquisition and modeling for corporate memory: lessons learnt from experience[END_REF]. This knowledge is stored in a database called "corporate memory" or organizational memory. Corporate memory refers to a structured set of knowledge related to the firm experience in a given domain. It is also a "repository of knowledge and know-how of a set of individuals working in particular firm" [START_REF] Euzenat | Corporate memory through cooperative creation of knowledge bases and hyper-documents[END_REF]. In a Knowledge Capitalization task, it is essential to identify the crucial expert/domain knowledge in order to determine the required kind of corporate memory (CM) that would "support the integration of resources and know-how in the enterprise and the co-operation by effective communication and active documentation" [START_REF] Durstewiz | Report on workshop on Corporate Memory[END_REF]. Subsequently, the knowledge could be formalized and modeled in a corporate memory for re-use and update by designated users. In this work we aim at representation, integration, sharing and reuse of knowledge in Economic Intelligence projects.

2.3

Economic Intelligence Economic Intelligence (EI) is a set of coordinated actions of search, processing and distribution for exploitation of useful information for economic actors. These actions are carried out legally with all the necessary protection for the safeguard of the company's patrimony, and with the best quality, delay and cost [START_REF] Martre | Intelligence économique et stratégique des entreprises. Travaux du groupe présidé par Henri Martre[END_REF]. Information is needed at various levels of decisionmaking process of a company or community to develop a coherent strategy and tactics necessary to achieve the goals set by the company in order to improve its position in its competitive environment. These actions are to be structured in a continuing cycle in order to track and capitalize the knowledge resource. The EI research develops methods for identifying relevant sources of information, analyzing the collected information and manipulating it to provide what the user needs for decision making. There are four major economic actors involved in the decision-making process who are responsible for playing key roles in performing the required tasks for ensuring the success of the process. Each actor has a designated responsibility as discussed below.

Decision maker who must formulate exact description of the decision-problem. Watcher who must locate, supervise, validate and emphasize the strategic information needed for solving the problem.

Information system analyst/designer who supports the watcher in information retrieval task. Project Coordinator who serves as a link between decision-maker and watcher as well as end-users [START_REF] Knauf | Caractérisation des rôles du coordinateur -animateur : émergence d'un acteur nécessaire à la mise en pratique d'un dispositif régional d'intelligence économique[END_REF]. All the actors work together in collaboration in order to optimize sharing of strategic knowledge amongst one another. Thus, EI is decision-maker-centered as information needs are treated based on the contexts of the decision-maker. There are existing models in EI for representing knowledge. They serve as tools for the various phases of EI process in decision-making activities. They are designed to represent knowledge in the different stages of EI process. They are as follows.

MEDP(Model for Explicit definition of Decision Problem):

This model handles the first step of EI process by clarifying the decision problem. It combines both the context of the problem, the decision-maker and the challenges of the decision-making problem to identify the real needs of the decision maker for information and preparation of the information research project by addressing two major questions: what the need is and its purpose [START_REF] Bouaka | Développement d' un modèle pour l' explicitation d' un problème décisionnel : un outil d' aide à la décision dans un contexte d' intelligence économique[END_REF]. WISP(Watcher's Information Search Problem): It relates to the second phase of EI process. It represents a methodology for translating the decision problem into information retrieval problems [START_REF] Kislin | Modelisation Du Problème Informationnel Du Veilleur[END_REF].

MIRABEL(Model for Information Retrieval query Annotations Based on Expression

Levels): It expresses the equivalence between a given decision problem and the corresponding specification of information retrieval problem [START_REF] Goria | Proposition d'une démarche d'aide à l[END_REF]. MORPRI 2 E(Model for the representation of Information Search Problem in Economic Intelligence): It is meant to represent users with respect to their specific needs and its context and to model an information system which adapts to the changing needs of users [START_REF] Afolabi | La conception et l'adaptation de la structure d'un système d'intelligence économique par l'observation des comportements de l'utilisateur[END_REF]. RUBICUBE(Representation of User's needs at the time of Identification and Interrogation of an Information System): It adapts information system design to users' types of needs in the design of a multidimensional data warehouse of document resources [START_REF] Peguiron | Application de l' Intelligence Economique dans un Système d' Information Stratégique universitaire : les apports de la modélisation des acteurs[END_REF]. This and MORPRI 2 E consider the third and fourth phases of EI process AMIE(Annotation Model for Information Exchange): This relates to the fifth and sixth phases of EI process. It expresses information relevance and reliability by analyzing and annotating collected information and its contexts [START_REF]L' annotation pour la recherche d' informations dans le contexte d' intelligence économique[END_REF]. CADRIE(Specification of the competence of the moderator of Regional Economic Intelligence): This Model specifies the roles and the competences of the coordinator of a regional economic intelligence for managing EI actors and their activities [START_REF] Knauf | Caractérisation des rôles du coordinateur -animateur : émergence d'un acteur nécessaire à la mise en pratique d'un dispositif régional d'intelligence économique[END_REF].

These different models are used to represent the tacit knowledge or skill of actors with respect to the specific phases of EI process. There is a need to integrate all these models in order to realize the following benefits:

• Preservation or storage of valuable knowledge resources in activities of EI projects.

• Provision of platform for integration of models, information research skills, results etc.

• Possibility of solving new problems with existing relevant knowledge resources.

2.4

Success criteria for representation and exploitation of knowledge We consider the essential factors for knowledge representation and capitalization in order to explore maximal benefit of its exploitation.

Principles of Knowledge Representation

According to (Randall et al., 1993[START_REF] Sowa | Knowledge Representation: Logical, Philosophical, and Computational Foundations[END_REF], five factors contribute to adequate representation of knowledge. The following considers each of these principles.

Knowledge representation should serve as a surrogate (substitute/stand-in) for physical objects or events and the relationships amongst them with the aid of symbols and its links to model an external system. It is a set of ontological commitments that determine various categories of objects of a domain. It should describe the behavior and interaction amongst domain objects in order to reason about them. Next is the fact that knowledge representation should be a medium for efficient computation which enables the encoding of represented knowledge in order to facilitate efficient processing with the aid of appropriate computing equipment. Finally, it should be a medium of human expression in such a way to facilitate the understanding and communication of both knowledge engineer and domain experts.

We apply these principles to the development of a knowledge repository (corporate memory) for EI in section 3.

Reasoning Techniques in Knowledge Representation

Knowledge representation is often augmented with reasoning (the process of applying knowledge to arrive at conclusion) techniques: that is, provision of methods to handle the tracking of transition among system's properties or knowledge and underlying reasons for such transitions. There are two approaches to reasoning techniques, namely, declarative and procedural. The latter is similar to step-wise programming or algorithmic approach while the former requires the use of axioms or logical statements to describe specifications and theoremproving technique to reason about knowledge [START_REF] Sowa | Knowledge Representation: Logical, Philosophical, and Computational Foundations[END_REF]. The choice of appropriate techniques for representing and reasoning about domain knowledge actually depends on the nature of requirements for knowledge-based system. Sowa recommends the use of a procedural approach for representing a system which requires a natural sequence of operations of its processes. On the other hand, logic is best suited for modeling a system in which there is no time sequence or linear pattern of relationships amongst its processes. We choose the procedural approach due to the fact that our context of EI represents a process which entails a sequence of stages or phases (as stated in section 2.3).

Representation and Exploitation of Knowledge in Economic Intelligence

The goal of this paper is to capitalize knowledge in EI-based projects by acquiring, organizing, integrating, representing and storing such knowledge in order to exploit it for re-use and distribution. The challenges confronting us relate to the acquisition, harmonization, and representation of knowledge resources from EI activities. Also, there is need for an appropriate reasoning technique to facilitate exploitation of relevant information. Our approach is to identify, design, and represent knowledge resources and to integrate EI models/tools for performing EI tasks. We have identified the knowledge resources in section 2.3. After identification of the knowledge resources of EI projects, the structure and representation of knowledge resources is an important factor just as a foundation is to a building. Thus, we design an adaptable user-oriented framework to serve as the bedrock for the representation of the proposed work.

3.1

Framework for Knowledge capitalization of EI projects Our approach is to design an adaptable framework for capitalization of EI projects such that diverse problem domains requiring resolution of decision problems can be adequately catered for. The framework serves as a base to the modeling and development EI knowledge repository. Figure 2 illustrates the general framework of Knowledge Capitalization in EI. This framework organizes the knowledge resources of EI capitalization system. The actors and the roles they play or their tasks serve as the drivers or determinants of the transition from one phase to the other in a given project of decision problem. The EI process is decomposed into the various phases that depict the tasks to be carried out. On the other hand, the EI models that serve as the tool or methods of problem resolution are applied to respective task of actor(s). The framework harmonizes all the knowledge resources of each EI model into a single pool. Knowledge resources on actors, tasks, tools, time-stamps and information results are integrated and stored into the knowledge repository. These knowledge resources could be exploited for reuse when actors explore available resources to address new problem case. The framework leads to the modeling of relational schema of EI knowledge repository.

Relational Modeling of Knowledge resources

We represent the harmonization of the knowledge resources in EI projects of decision problem with the aid of relational modeling schema. This choice is necessitated by the need for a dynamic structure which permits class object relationships. This supports the definition and classification of knowledge resources based on the context of EI. This approach is different form the use of ontology which is limited to hierarchical representation of objects with respect to its types, parts, properties etc. The Relational model for the capitalization system in the context of EI is depicted in figure 3 We demonstrate the model with a prototype to verify its adequacy to the context of EI in section 4.

• • • ! " # • $ • % " • # & # '

Information Watcher

High percentage of school drop outs.

A bad omen for the state of future leadership. Social menace.

The terms or concepts of the DP are interpreted by the watcher as well. Both actors assess the individual viewpoints and resort to a specific definition of the decision problem.

Acquisition and Representation of EI Knowledge and resource

We simulate the acquisition and representation of knowledge resources of the above scenario based on the proposed relational model. Figure 5 depicts the access page to actor-action based information entry. The identification and definition phase of the EI process is illustrated in figures 6. [START_REF] Thiery | LÀrchitecture Equate 2 te son Application a Lìntelligence Economique[END_REF]. It allows user's query to be formulated in a way that best describes the contexts of user's needs. Figure 7 illustrates one of the methods of the chosen technique in which attributes of knowledge resources that are related to an actor's role could be selected to retrieve specific instances of knowledge resources.

Conclusion

Knowledge is a key for innovation and for gaining competitive advantage. We have taken cognizance of this fact by providing adequate methods to represent and to capitalize knowledge. In this paper, Economic Intelligence has been presented as a strategic tool or method which aims at providing relevant information for resolution of decision problems. This terget of EI can be ameliorated or optimized by the possibility of capitalizing knowledge in order to reuse it to solve related future decision problems. We designed an adaptable framework which serves as a platform for modeling and organizing knowledge resources in the context of EI. The relational knowledge model facilitates the acquisition, representation and harmonization of knowledge in EI projects. We implement a prototype to demonstrate the development of a knowledge repository and its exploration. This consequently aids actors to exploit stored knowldege for reuse in new problem cases. The main benefit of this work is the possibility of exploring the knowledge resources based on the role of actor(s). We propose to extend the framework and consequently the model with feedback strategy such that it will be possible to validate the relevance of exploited knowledge resources. We propose further to integrate the update of knowledge resources into the prototype system.

6.

  The process of EI, according to SITE research team(SITE Report, 2007) entails the phases highlighted below. a) Identification and definition of a decisional problem b) Translation of the decisional problem to an information search problem c) Identification of relevant information sources d) Collection of relevant information e) Analysis of the information collected to extract indicators for decision f) Interpretation of indicators g) Decision-making

Figure 2 :

 2 Figure 2: General framework of Knowledge Capitalization in EI

  . It represents the knowledge resources of the first two phases of the EI process namely: a) Identification and definition of a decisional problem b) Translation of the decisional problem to an information search problem.

Figure 3 :

 3 Figure 3: The Relational Model for the representation of knowledge in EI

Figure

  Figure 4: Scenario of a decision problem

Figure 5 :

 5 Figure 5: Access Verification for Actor-action Forms

Figure 7 :

 7 Figure 7: Exploitation of Knowledge Resources

Table 1 :

 1 gives a summary of this classification. Types of knowledge

	Explicit (episteme)	Tacit (techne)
	Formal and systematic	Insights, intuitions, and hunches
			(Phronesis)
	Knowledge	of rationality	Knowledge of experience (body)
	(mind)		(Metis)
	Can be expressed in words and	Not easily visible and expressible: it
	numbers		resides in people's heads
	Easily communicated and	Highly personal, hard to formalize,
	shared in form of data,	difficult to communicate or share
	formula, graphs, manuals,	with others
	books, documents, or theories
	etc.
	Can be expressed in computer	Rooted in individual's actions and
	code, databases, simulations,	experiences: in form of rules of
	sets of general principles etc.	thumb, ideals, values, or emotions.

4.

Experimentation of the Framework and Model with a Prototype We build "EI Knowledge repertoire" for knowledge resources and its time-stamps in EI activities. We apply the user-based search technique for exploration of the Repository for identical cases of knowledge resources.

Experimentation

The described framework and relational model in section 3 are implemented with a prototype to simulate the acquisition and representation of knowledge resources of a scenario of decision problem. The prototype also demonstrates the exploitation of knowledge for possible reuse.

We consider a sample decision problem. It is 'moral decadence amongst youth'. Figure 4 depicts the knowledge resources of the first phase of EI process.

The knowledge resources are identified with respect to the EI tools or models applied by actors and tracked for storage. The following section indicates the knowledge resources of resolving the decision problem.

Case Study of Decision Problem of Moral Decadence amongst youth

The framework provides a template for the capitalization of knowledge resources in the given case study. That is, knowledge resources are identified and acquired from the actors and activities involving the phases of EI process and respective models. The following scenario exemplifies the knowledge resources in the first phase of EI process.

Scenario Decision maker states the decision problem (DP) as: Moral decadence amongst youth

The Context of Decision Problem is Educational sector in Nigeria. Understanding the Decision problem: What is the meaning of the decision problem? (This helps to acquire the knowledge of DP.) The terms or concepts of the DP are defined by the Decision maker as thus:

Moral refers to principles or rules of right conduct. Decadence is a state of decline in moral.

Moral decadence implies a state of decline or deterioration in conformity to principles or rules of right conduct.

Thus, moral decadence amongst youth implies a state in which teenagers or secondary school aged people decline in conformity to rules of right conduct.

Definition of the Stake of DP:

Object: Moral decadence Signal: truancy, violence, crime, immorality. Hypothesis: If DP is not curbed then there would be:


S Nourizadeh
email: shahram.nourizadeh@loria.fr

C Deroussent
email: claude.deroussent@medetic.com

Y Q Song
email: song@loria.fr

J P Thomesse
email: thomesse@loria.fr

A Distributed Elderly healthcare System

The recent advances of ICT allow developing new generation of telehomecare systems to enable elderly health monitoring and management and ease their daily life. Such a system can reduce the amount of admissions to hospital, facilitate more efficient clinical visits, and may replace a hospital stay by living at home. In this paper we present a patient oriented distributed telehomecare system, by which we created a new concept of building smart home by integrating telemedicine and home automation systems.

INTRODUCTION

As the population grows older, people becomes increasingly dependent as their sensory, motor and cognitive physiological health capacities deteriorate; these agerelated changes, are amplified if they are accompanied by pathological conditions (e.g. osteoporosis, osteoarthritis) that are common in the elderly population. Most European countries are now facing an urgent requirement to provide appropriate retired home environments solutions for these citizens and allow them to play a role in our society. Elderly requiring healthcare services must move to distant medical centers and this is often not feasible due to their state. Elderly tele-healthcare systems can be achieved using advanced communication networks and Internet technologies. These technologies have a key role in the development of a telehealth system and smart homes.

Healthcare integrated smart home allows the tenants and their family members to benefit from a safe home environment with activities and services accompaniment for their daily steps. In order to reach that goal, we aimed at several technologies and implemented them in a demonstration prototype apartment. Several issues on objectives and contributions of technologies were stressed out [START_REF] Boulanger | Preliminary Based Service Evaluation for Elderly People and Healthcare Professionals in Residential Home Care Units[END_REF]:

• Enhance independent living with cognitive assistive systems [START_REF]Funded by the European Commission under the Programme "Quality of Life and Management of Living Resources[END_REF].

• Provide safety and security to inhabitants with the help of medical services supervision; monitor general activities of the occupants [START_REF]Digital services enhancing of the elderly at home[END_REF] and monitor unusual routines or abnormal behaviors that reach dangerous levels [START_REF]Système d'aide aux personnes âgées[END_REF]. • Improve social contact and cultural activities within the elderly surrounding thanks to communication systems and appropriate equipment [START_REF]Mainstreaming on Ambient Intelligence[END_REF].

• Engage medical actors to use computerized systems in order to ease information processing and traceability. For these reasons, elderly tele-homecare, videoconferencing and tele-consultation systems have been attempted by many researchers. Many telemedicine and e-health systems are being developed and many innovations and ICT-based emerging solutions are close to be operational, nevertheless the expected take-up did not occur yet, since proposed systems and their targeted medical benefits are certainly too segmented and disconnected the ones from the others. In addition, most of existing products and services in this field rely on proprietary technologies, which is a substantial obstacle to the development of complementary services or applications, and thus of the market. Consequently, population like elderly, disabled people or chronically ill people, who are often suffering from co-existing troubles, are not encouraged to dare benefiting from ICT and innovations, as available solutions are not complete, not compatible the ones with the others, not scalable, neither end-to-end nor comprehensive, and remain then unaffordable for someone who would try to subscribe to each relevant service covering a more or less significant part of its medical and social needs, without ensuring a global management of the daily problems. The current developments and innovations are limited in terms of commercial and operational perspectives and suffer from certain phenomena:

• The fragmentation of experimentation, projects and products did not yet give birth to any efficient and affordable holistic solution that could fulfill the various targeted beneficiaries and users' expectations. • The development costs and R&D expenses required for a proper adaptation to each community of users and beneficiaries' needs make investment very high, as timeto-market delays are uncertain and no business model has been successfully assessed yet in this domain. • The accompanying measures, at institutional, ethical, legal, financial and organizational levels remain insufficient, which prevent the development and the sustainability of such assistance and at-home monitoring services. • Finally, the population is neither confident nor familiar enough with these innovation-based solutions, especially in such a medical or health-related purpose, although their development requires that they become a natural component of the medical and social environment and infrastructure.

State of the art

A telehealth application is a complex system that requires the integration of various sub-systems and applications. As we said, nowadays, many telehealth and e-Home applications are available; however, it is difficult to find the system that matches exactly the end-user requirements.

In [START_REF] Newman | A High Performance Web-based Teleconsultation System for Island Telemedicine[END_REF] the authors presented a teleconsultation system. This system is based on web technologies and the user accesses the system over the Internet or an intranet. The system therefore is designed to do a teleconsultation, and it is not integrated with the other healthcare modules or an automatic analysis of patient's health situation. TOPCARE [7] is a telehealth system for mobile care and homecare of high risk patients, elderly and care needing people. The system is an open telecare platform solutions for telemedicine services. The overall objective of TOPCARE is to develop technical devices and telecommunication structures and to lay the organizational groundwork for bringing co-operative health care services into the home of patients. System comprises a telematic homecare platform (THP) backbone, the development of telematic home stations (THS) and health professional stations (HPS) and a communication server that will manage the network administration, the health professional registration at the THS, the device communication, and the Internet access. Therefore, in TOPCARE, interaction is limited to only the clients having TeleHealth Client (THC) module.

The Interactive and cooperative tele-monitoring of the dialyzing at home (DIATELIC) is a system of tele-monitoring of dialyzing at home by the technology of DPCA (Dialyze Peritoneal Continue Ambulant) [8]. It was developed by LORIA in cooperation with the doctors of the ALTIR (Lorraine Association of Treatment of Renal Insufficiency) and a doctor advice of the Health insurance. Research works drove to the Diatelic system. This system is only designed specially for the dialyze patients.

The AFIRM team of the laboratory TIMC-IMAG in Grenoble developed a project called System of Information and Communication of the Inteligent Home for Health (SIC -HITCH) [START_REF] Vincent Rialle | Modélisation d'un support de communication pour des personnes âgées à domicile Abir Ghorayeb1[END_REF]. Objective is to monitoring the patient in his home with sensors installed in his home, by triggering off alarms in the appropriate urgent centers, in case of feelings of faintness, in falls or in abnormal situations. This system is an experimentation and simulation platform.

System architecture

The requirements presented in the previous sections and remaining obstacles or brakes make the design of monitoring and assistance tools quite complex, as each pathology or disability generates its own set of requirements and constraints. Such context increases the need for the development of innovative global ICT-based solution allowing to implement personalized and person-centric care process and tools, which can evolve with the users' medical and social and physical evolution, and which can compile the various collection and analysis of data to ensure a reliable and sound diagnosis, medication and evaluation of the medical and social state of the person.

To reach these advantages, we developed a patient oriented tele-homecare system. By a user requirement analysis, we propose a Multi-tiered architecture (see Fig. 1). The elements of this architecture are:

• Medical Sensors (and / or Body Sensor Network (BSN)): This part consists of the medical instrumentation important to patients medical monitoring. As the studies show [START_REF] Boulanger | Preliminary Based Service Evaluation for Elderly People and Healthcare Professionals in Residential Home Care Units[END_REF], for 65% of the elderly, this is not acceptable to attach theme any sensor, for this reason we use a noninvasive medical monitoring, but for the exceptional cases that we need to have a real-time monitoring of their medial state, we use Body Sensor Network. This network consists of very small portable devices equipped with a variety of sensors for medical monitoring, patient localization and identification. • Environmental Sensors and Home automation sensors network: This network must include sensors unfolded in environment (rooms, halls, WC …). These sensors can include those of the temperature, humidity, movement, acoustics, the camera, etc. • Gateway: It may be the mini PC installed in each home, or a mobile system such as a PDA. It connects body sensor network and also environmental sensors like home automation sensors and actuators to the Internet. It also includes intermediate receivers, assuring an efficient data transmission. In this part we have some preprocessing of the data received from medical and home automation sensors, to detect urgency anomalies. • XML data exchange by using web services technology: This system uses web services to interact between the client and the server, as shown in Fig. 2 This system has intention to address the need to standardize the transmission of physiological data, by using the platform independence of web services and the structural independence of XML in the development of a web service for data transmission, processing and storage of physiological data for the service of telemonitoring. By using web services, the system requires minimal additional technological elements and minimal technical requirements of support. • Graphical User Interfaces. We designed a very easy-to-use graphical user interface.

This interface is commendable by using a PDA or TV remote controller. This system interfaces to healthcare providers, doctors, care-givers and the medical call centers (See Fig. 3) and also is integrated with a mobile platform for the occupant to remote control his home and another mobile platform for the doctors and nurses to view the state of their patients. Typically they will receive an alarm in case of a health problem of their patients.This figure shows that the system is integrated with vital sign monitoring devices and sensors. The system has possibility of integrating the system with the wireless devices and sensors with different communication methods such as Bluetooth, ZigBee, USB and the other technologies. The medical data are store in the database aromatically; without any manual action. We aim in this project to integrate ZigBee protocol with home automation protocols, such as KNX, IHC. Among the many wireless technologies, ZigBee is one of the most promising ones for home automation; a wireless home networking system can be configured using ZigBee alone [10].

Functions and features

The main objective of this project is to develop a universal user-oriented healthcare system to allow elderly to be medically monitored and assisted in their home. The benefits and added-values of the proposed system and service are to offer a continuous medical monitoring of the person's health combined with a permanent watch of the immediate dangers in the person's home: the automated alert system will contact a video call center able to evaluate the emergency level of the alert and to contact the most relevant assistance (like relatives, doctors, carers or emergency services). The continuous follow-up of the evolution of the medical state allows detecting automatically the potential deterioration of his/her health, thanks to biomedical sensors adapted to the person's specific pathologies, and thanks to actimetry and situation detection systems. The automated alert system will then send an alarm to the supporting call center in case of deterioration of the health parameters or detected immediate dangers, like fire and flood. The service will also ensure an automated monitoring and alert system for the detection of falls and abnormal behavior according to the localization, activity, condition and habits of the person. This solution's advantage is to propose a global system, accessible from anywhere, displaying an adapted remote sensing service combined with interactive telecommunications and an automated alert system. The innovative feature of the system regard two main axis: the high level technological integration of several innovative modules to be interconnected and correlated, on the hand, and the challenging conception of an adapted and sustainable service from end-to-end, with the overall management of the value chain involving the industrials -who develop, adapt and integrate technical products and services-the service providers and operators -who define and implement new models and structures for the delivery of services from the call center up to the distribution of the offer, and finally, the users and beneficiaries of such services, including the patient, its carers and relatives -who integrate this new habits and tools into their daily life and environment and provide their feedback on each brick of the overall solution and its concrete organization. These two main innovative issues resulted into a real challenge in terms of services, as to whole project's conception involves the users and the involved actors, so as to well define and adapt each element to turn into a success factor in terms of acceptance.

Technological innovation:

The technological innovative activities and technical challenges addressed in the system are as follows:

Distributed patient record

As shown in Fig. 3, the patient record has a distributed architecture, and we have a local database in each client computer. We used a distributed patient record because in distributed database architecture the data is not stored entirely at a single physical location. Instead, it is spread across a network of computers that are geographically dispersed and connected via communications links. We have therefore a large database capacity and incremental growth, and like all distributed databases, we have a reliable, available and flexible database. The most important advantage of a distributed database for our system is that a distributed database allows faster local queries and can reduce network traffic.

In this system, in each client computer we have a pre-processing of patient's data to detect the eventual emergency problems. This distributed database architecture helps to early detection of emergency problems, that means by checking the local database, if the data from healthcare devices are outside the ranges defined in their care plan, or if the data have not been received when expected, the system will trigger an alarm that may result in an automated connection with a medical call centre.

On the other hand, by using the data from home automation sensor and medical devices, the application stored in the web server, will analyse the medical record by using intelligent methods like Fuzzy Logic or other more complex cognitive systems, to find the potential health problem. By detecting a problem, the system will trigger an alarm that may result in an automated data transmission to a doctor.

Activity monitoring by Home automation system and with/without BSN

The system gives not only to the patients a full control of Home automation devices, by using system's simplified interface (Fig. 4) but also generates the alerts by using home automation sensors, which allow an indoor localisation of the beneficiary and can, thus, propose a fall detection service generating alerts. The system allows doctors or healthcare providers to measure the physical activities of elderly. The system uses a more passive method. It senses a person's presence in a room by home automation sensors installed throughout the living areas, such as motion and presence detectors, light, magnetic and temperature sensors. Activity patterns are then analyzed in the local computer for unusual behavior in activities and also to fall detection, which use an intelligent method by using Fuzzy Logic. All the results save in a database and the system in its learning period will use this database to person's behavior modelling to reduce number of false alerts.

Video conferencing and Tele-consulting

Tele-Healthcare is related to offer health care services over Internet or a wide area network, and in this domain, videoconferencing is one of the important solutions, allowing real-time interaction between patients and the Doctors. The offered system is integrated with a simplified and user-friendly videoconference system which is adapted to use in elderly tele-Healthcare. This sub system is used to have a video meeting by the families and also to request an online consulting; in this case the in the first step, the patient requests a medical visit by connecting to videoconferencing system. System sends a message to doctor and loads patient's medical record. Doctor joins the conference and by ending the consultation, fills a form and saves it to medical record and ends the consulting. Finally, the system creates a billing and sends it to patient. Patient can view the billing in his interface and pay it online.

Integration with other home or health systems

Integration of several innovative modules into a global and interoperable network of networks and systems is a grate innovative point in our system. The client side system is a media centre module to facilitate usage of TV and easy access to video and music sources. Figure 5 shows the client side system architecture. In this system, we used a modular architecture to facilitate integrating of the optional module and also to provide an easy procedure of updating and maintenance.

Conclusions and discussion

In this paper, we have presented a distributed system to support remote medical consultations and elderly management and homecare across global wide area networks and heterogeneous platforms.

A flat is entirely equipped to act as demonstrator and as laboratory and our system is under final testing there. We use this flat to evaluate our system and also the different algorithm that we proposed during this project, the algorithms like clustering and indoor localization in sensor networks [START_REF] Nourizadeh | A Location-Unaware Distributed Clustering Algorithm for Mobile Wireless Networks Using Fuzzy Logic[END_REF] and fault management in these networks.

By using this system, MEDeTIC (www.medetic.com) , a non-profit organization, offers a new concept of building smart homes by using telemedicine and home automation, named in French "Maisons Vill'Âge®". The first houses are in building with basic implements of data acquisition and human-machine interface.

In this type of systems, several challenges need to be addressed. The technological challenges regard the generic features of the dynamic database, of the wireless sensor networks, of the different supporting platforms, of the video call centre, and web services, to allow a flexible and smooth interaction among those items and to anticipate further additional functionalities, interacting devices, and so on. In this respect, the methodology of specifications, development and integration of the technological features must be realized with a major concern for some important concepts, like: Interoperability, Scalability, Evolution and customization according to the users' medical and social profiles and needs.

On the other hand the design and integration effort for the technical and R&D activities of the project focus on the design of services and interfaces ensuring a maximum level of natural understanding on the way to use them, that is to say with an enhanced effort on the prerequisite and experimentation feedback's of the users who are suffering from chronic conditions and are not familiar-and sometimes reluctantwith ICT and innovation-based devices and systems. Ergonomic interface, accessibility, scalability and evolutionary solution according to the evolution of the users' needs are the important aspect of development.

Another important point is QoS (Quality of Service) requirements, like availability and response time. As the healthcare industry is turning to information technology to help solve its business issues, specially provide to quality patient care services, it is important to develop QoS specification in distributed health information systems [START_REF] Ray; Weerakkody | Quality of service management in health care organizations: a casestudy" Computer-Based Medical Systems[END_REF]. Unlike traditional systems, many non-end-to-end mission-critical applications envisioned for healthcare systems, which are complex systems, because in these systems, we can find different subsystems, such as, wireless sensor networks, LANs, software platforms, home automation systems, mobile systems, Internet… that require different QoS requirements on the system, and these requirements pose unprecedented challenges in the area of QoS support in healthcare systems.

Our first study shows that all the healthcare professionals have a positive attitude toward dedicated means for ICT practical application (50% "totally agree", 33.3% "strongly agree" and 16.6% "lightly agree"). Majority of interviewed elderly residents, in this study, declare not knowing what would be their family attitude toward ICT use (45.83%); 37.5% think that their family would be favourable to ICT use and 16.67% think that the family would be unfavourable to ICT use, but this study with the projected family attitudes of elderly people shows that the limitations experienced in everyday life do not lead to a favourable or unfavourable category of ICT user [START_REF] Boulanger | Preliminary Based Service Evaluation for Elderly People and Healthcare Professionals in Residential Home Care Units[END_REF].

Any failure or lack of performance on the system which could not be tackled in a reasonable delay may have some damageable consequences on the solutions' acceptance and development potential: the confidence is a basic and elementary factor of acceptance or reject, such incident could also generate a psychological defiance towards ICT's in general and towards such innovative assistance and monitoring services. For these raisons, as our future work, a middleware will be developed to give a dynamic and intelligent QoS to the system.

Due to the results of this first study, definition and revision of planned applications (scenarios improvement), behavioural intention and acceptance of designed implemented solutions and finally actual usage and acceptance evaluation will be our future work.

Fig. 1 .Fig. 2 .Fig. 3 .

 123 Fig. 1. System's general architecture

Fig. 4 .

 4 Fig. 4. Home automation interface

Fig. 5 .

 5 Fig. 5. Client side atchitecture


Maxime Mikikian

Laïfa Boufendi
email: laifa.boufendi@univ-orleans.fr

Experimental investigations of void dynamics in a dusty discharge

Keywords: numbers: 52.25.Vy, 52.27.Lw, 52.35.Ra

We report on first electrical and spectroscopic characterizations of an instability, usually called "heartbeat" instability, occurring in a laboratory dusty plasma. It consists of successive contractions and expansions of the central dust free region observed in a dense cloud of dust particles. This cloud is formed in a radio-frequency plasma by sputtering polymer material deposited on the electrodes. The evolution of the discharge current reveals the relatively complex shape of the instability and allows to measure its evolution as a function of gas pressure and radio-frequency power.

I. INTRODUCTION

The formation of dust particles in low pressure plasmas is actively studied [START_REF] Bouchoule | Dusty Plasmas : Physics, Chemistry and Technological Impacts in Plasma Processing[END_REF] since their discovery in plasma processing reactors [START_REF] Roth | [END_REF]3]. In laboratory experiments, this formation is usually achieved by two different ways: using reactive gases such as silane [4][5][6] or using a target sputtered by the ion bombardment coming from the plasma [7][8][9][10]. In capacitively coupled radio-frequency discharges, these two methods usually lead to the formation of a dense cloud of submicron dust particles filling the whole gap between the electrodes. The dust particles are trapped in the discharge due to the negative charge they acquire in the plasma [11][12][13]. Their position is fixed by the balance of the various forces acting on them and principally due to the ions, the electrical fields, the thermal gradients, the gas flow and gravity. This last force plays an important role and consequently three-dimensional (3D) clouds can be obtained in laboratory only with submicron dust particles. With bigger particles ( 1µm), 3D clouds can be formed under microgravity conditions [14,15] or using an additional force like thermophoresis to counterbalance gravity [16]. When this cloud is obtained, experiments show that the central region of the plasma is free of dust particles [17][18][19][20]. The formation of this egg-shaped region, usually called "void", is still actively studied [21][22][23][24][25][26] and it seems that the dust particles are pushed away from this region by the ion drag forces acting on these negatively charged dust particles. This structure is usually stable but sometimes a self-excited instability occurs, characterized by a low frequency oscillation of the void size known as the "heartbeat" instability. It has been previously observed during microgravity experiments [START_REF] Goree | Proceedings of the 4th Microgravity Fluid Physics and Transport Phenomena Conference[END_REF] with a frequency around 1.5 Hz in a cloud of micron-sized dust particles and theoretical works [19] proposed that this oscillation is related to a modulation of the ionization rate. In this paper we report on the formation of this instability in lab-oratory and on the correlation between the void dynamics and the discharge characteristics such as current transport and optical emission. After describing our major observations concerning the void formation, new experimental results are presented, emphasizing the complex shape of this instability.

II. EXPERIMENTAL SETUP

The work presented here is performed in the PKE-Nefedov (Plasma Kristall Experiment) chamber designed for microgravity experiments [14,15]. The experimental setup consists in a parallel plate (4 cm in diameter separated by 3 cm) rf discharge operating in push-pull excitation mode (0-4 W). Dust particles are grown in an argon plasma (0.2 -2 mbar) from a sputtered polymer layer deposited on the electrodes and coming from previously injected dust particles (3.4µm, melamine formaldehyde). The cloud is illuminated by a thin laser sheet perpendicular to the electrodes and the scattered light is recorded at 90 o with standard charge-coupled device (CCD) cameras with 25 images per second. A detailed description of this experiment and previous results are presented in References [START_REF] Mikikian | Dusty Plasmas in the New Millennium[END_REF][START_REF] Mikikian | Proceedings of the 29th EPS Conference on Plasma Physics and Controlled Fusion[END_REF][START_REF] Mikikian | [END_REF].

III. DUST PARTICLE GROWTH AND VOID FORMATION

Depending on the experimental conditions, the growth process leads to various shapes of the dust cloud (few layers, domelike shape, 3D dense cloud) and is highly sensitive to the gas purity as previously reported [20]. This effect, well observed on successive runs [START_REF] Mikikian | Proceedings of the 30th EPS Conference on Plasma Physics and Controlled Fusion[END_REF], is amplified by the fact that the experiments are performed without gas flow (static pressure). We need to pump down during a sufficiently long time (at least one hour) between each experiment in order to eliminate the species formed during the previous run and coming from the outgassing of the walls and from the sputtered matter. Indeed, a very high dust density has been achieved recently by op- timizing the pumping system leading to a better base pressure (few 10 -6 mbar actually instead of few 10 -5 mbar before). The working pressure is 1.6 mbar and the rf power is around 2.8 W. When a high dust density is reached, the dust particle size is very small (few hundreds of nanometers using scanning electron microscopy) and a cloud without a clear void can be obtained. After this step, we usually see the progressive formation of the void (Figure 1) but sometimes the plasma switches off by itself due to very high concentration of dust particles attaching the free electrons. A mixture of chaotic behaviour and instabilities with well defined frequencies [START_REF] Mikikian | Proceedings of the 30th EPS Conference on Plasma Physics and Controlled Fusion[END_REF] (different from the broadband "filamentary mode" [18,20]) appears sometimes in the discharge current during dust particle growth. However, it seems to be not indispensable for the void formation. At low power, the plasma is more sensitive to any internal modification and if the void is small (few mm), its frontiers become less defined and some dust particles begin to cross this region [START_REF] Thomas | [END_REF]. Then, more and more dust particles cross the void and the plasma switches off by itself. Increasing the power prevents any particles to enter in this region. This observation underlines the role of the forces responsible for the void formation like the ion drag force. When the coupled power to the plasma decreases, the forces pushing away the dust particles from the center cannot maintain a stable size of the void.

IV. VOID INSTABILITY AND ELECTRICAL MEASUREMENTS

Once the cloud is formed, increasing the rf power and decreasing the pressure enable the formation of the void and the generation of the heartbeat instability in a quite repetitive way. In the same manner, the size of the stable void is increased by increasing the power or by lowering the pressure [24]. From our observations it seems that this instability concerns only small voids appearing only when a huge density of small dust particles (few hundreds of nanometers) is produced. In these conditions, the scattering parameter x = 2πrp λ > 1 where λ is the laser wavelength (685 nm) and r p the particle radius. Thus, the scattered light is collected at an angle lying approximately between 20 o and 30 o with respect to the incident laser direction. Therefore, the images seem to be compressed in the horizontal direction and a perspective effect appears. Figure 2 shows four consecutive frames separated by 2 ms during a typical heartbeat instability with a frequency around 14 Hz. We can distinguish the minimum size (≃ 6 mm in (a) and (d)) and maximum size (≃ 12 mm in (b)) of the void. Moreover, the maximum size of the void during the instability seems bigger than the size of the stable void. Due to the standard video speed limitations it is not possible to study more in details the instability and high speed cameras must be used in the future. In consequence we have studied the instability by measuring the amplitude of the fundamental harmonic of the discharge current. These measurements have been performed in various conditions of power and pressure during the same run assuming that the dust cloud remains unchanged in terms of particle density and size. Other runs have proved that the results are qualitatively reproducible even if small variations in the instability frequency or shape are observed.

The evolution of the instability as a function of the pressure at constant injected power (3.3 W) and as a function of the power at constant pressure (0.6 mbar) is presented respectively in Figures 3 and4. The time and amplitude scales are kept constant in order to point out the evolution in frequency and amplitude. The measured frequencies are compiled in Figure 5. Concerning the pressure effect, the first remark is the evolution of

FIG. 4: (Color online)

. Power dependence of the electrode current during the heartbeat instability. The x-axis is time in seconds and the y-axis is the current amplitude in arbitrary units.

the relative amplitude of the oscillation. Indeed, we start from a very small linear fluctuation at high pressure (1.6 mbar) which corresponds to a classical limit cycle in the phase space. Then, a bigger non linear oscillation appears at 1 mbar which slowly decreases when the pressure is lowered. At the same time, the frequency decreases slowly from 21 Hz at 1.6 mbar to the minimum value of 15 Hz at 1 mbar. Then, as the pressure is still lowered, the frequency increases faster and faster to 27 Hz at 0.6 mbar and can attain more than 100 Hz at 0.3 mbar. Due to the low video sampling rate, the frequency cannot be correlated to the void size. The frequency increases slowly by decreasing the rf power and after a maximum value around 35 Hz it decreases certainly due to the fact that we are near the excitation threshold of this instability (Figure 4, 2.05 W). Indeed, below a given power the instability appears in an erratic way with sometimes a single contraction-expansion sequence in the middle of a stable sequence (open void corresponding to the continu- ous part of the signal). The fourier spectrum of the signal shows a clear peak at the oscillation frequency, for example at 3.3 W in Figure 6(a). When the power decreases, the oscillation shape becomes distorted and harmonics appear in the fourier space. Close to the threshold of the instability (2.05 W), the electrode current becomes a succession of Dirac functions and the fourier spectrum shows peaks centered at the harmonic frequencies (Figure 6(b)). The fact that the dust cloud remained nearly unchanged during the measurements is confirmed by the similar signals recorded, with few minutes delay, at 0.6 mbar and 3.3 W (Figures 3,4 and circles in Figure 5).

An other important observation coming from these curves is the complex shape of the instability. Indeed, we can distinguish various regions in the contractionexpansion sequence. When the instability occurs, the current amplitude oscillates around its stable value. If we take as a reference the curve obtained at 3.3 W in Figure 4, we observe first, a slow increase of the current which looks like a small shoulder. To correlate this part to a phase of the contraction-expansion sequence we must analyze an individual sequence or a succession of well separated ones as at 2.05 W. From these observations we can suppose that this stage follows the void contraction and is related to the void opening. Indeed, this part starts below the stable current value (dc value, horizontal line at value 0), converges toward this value and then stay constant (static open void) until the next event. This stage is then followed by a faster increase which can be either the end of the expansion or the beginning of the contraction. The rest of the signal seems to correspond to the void contraction which appears relatively complex especially with the presence of a sharp peak. For example, in Figure 3 at 1 mbar the rising time of this peak is around 2 ms for a peak duration of approximately 6 ms. We can see that this peak is not always clearly visible for example at 1.6 mbar and decreases for low pressures. It has been observed during other runs and seems to behave always in the same way concerning its progressive decrease when the pressure is lowered. It appears always at the right hand side of the main oscillation and its correlation with a specific phase of the contraction-expansion sequence is still not clear. To perform a good analysis of these curves we must also think that when the current is changing very rapidly (as for example in the case of the sharp peak) the dust cloud cannot follow. Then, the evolution of the curves cannot be always correlated to the dust cloud motion and can indicate modifications of the plasma properties preceding the contraction or the expansion of the void.

V. VOID INSTABILITY AND OPTICAL MEASUREMENTS

The complex shape of the discharge current has been correlated to the evolution of the plasma light thanks to optical emission spectroscopy. The intensity of the 750.4 nm argon line has been recorded inside the void region during the instability and its evolution seems similar to the current (Figure 7(a) and (b)). Consequently, the expansion seems to be in good correspondance with an increase of the excitation rate and thus higher ionization leading to an increase of the ion outward force. At this time, the correlation between the two curves near the sharp peak is not clear due to a low signal to noise ratio for the emission signal and the very small time duration of the peak. The curves (c), (d) and (e) correspond to the line intensity outside the void and are recorded by moving the optic fiber horizontally towards the edge of the plasma. These curves show a deformation of the emission signal on the path of the void motion with a last curve (e) symmetric of the signal taken in the center (b). This could underline the modification of the plasma local conditions driving (or due to) the dust cloud motion. Another remark concerning the optical results is a higher intensity of the emission line inside the void than outside. This effect is not appearing in the curves presented here because the continuous component has been suppressed but it can be "guessed" through the high signal to noise ratio in the void center. This effect is also very well seen with the naked eye where a bright ball of plasma is observed inside the void. This enhanced emission can be related to a higher density of argon metastables produced by the elevation of the electron temperature due to the electron attachment on the dust particles [START_REF] Mikikian | Proceedings of the 30th EPS Conference on Plasma Physics and Controlled Fusion[END_REF]33,34].

VI. CONCLUSION

In this paper, we have presented new experimental results of a self-excited instability of the void called "heartbeat" instability. These results have been obtained under gravity condition with submicron dust particles. We have measured the instability frequency as a function of free parameters of the discharge and we have shown that the shape of this instability is not purely sinusoidal but relatively complex. The motion of the dust cloud and its correlation with the discharge current will be investigated in the future using high speed cameras. Optical emission spectroscopy allows to validate the current measurements and add a spatial information necessary to understand the behavior of the void region.

FIG. 1 :

 1 FIG. 1: (Color online). Cloud of submicron particles with a clear void structure in the center of the plasma.

FIG. 2 :

 2 FIG. 2: (Color online). Consecutive frames taken at ≃ 20 o -30 o with respect to the laser direction during the heartbeat instability. The black region at the top is the upper sheath.The black region at the bottom marks the laser sheet limit.

FIG. 6 :

 6 FIG. 6: (Color online). Fourier spectrum and oscillation frequency corresponding to Figure 4, (a) at 3.3 W, (b) at 2.05 W.

FIG. 7 :

 7 FIG. 7: (Color online). Electrode current Ic (a), argon line (750.4 nm) intensity Ie inside the void (b), moving towards the plasma edge (c), (d), (e).

Acknowledgments

The PKE-Nefedov chamber has been made available by the Max-Planck-Institute for Extraterrestrial Physics, Germany, under the funding of DLR/BMBF under grants No.50WM9852. The authors would like to thank M. Dudemaine for his electronic support. This work was supported by CNES under contract No.03/CNES/4800000132.

Author manuscript, published in "Physics of Plasmas 11, 8 (2004) 3733" DOI : 10.1063/1.1761578


A Rodin plugin for quantitative timed models * Joris Rehm joris.rehm@loria.fr -LORIA -Nancy Université

We propose to develop a Rodin 1 plug-in that experiments a systematic use of a refinement pattern. The goal of this pattern is to help in modeling of timed system in Event-B. By timed system we mean system with quantitative temporal constraints and properties.

The user (of the plug-in) will see and modify an Event-B machine augmented with a new operator S. This unary operator over an event name e gives the delay elapsed since the latest triggering of the event e. By using this operator in the invariant, the user will be able to write and prove temporal properties over the events. By using this operator in the guard of an event f , the user will be able to specify temporal constraints over the duration S(e) (which becomes here the delay between the event e and f ). For the possible constraints, we plan to consider lower time bounds (l ≤ S(e) in guard of f ) and upper time bound (S(e) ≤ u in guard of f ). The upper time bound is a bound within the event f must obligatory occurs, it is not just a possibility. In this text, the usages of the operator S is called the annotations, it is an extension of the syntaxe of the B models. The annotations can only appear in invariant or guards.

Our pattern is an Event-B model that encodes the behaviour of the operator S (we call this model the pattern model). The annotations given by the user define how to refine the pattern model and how to obtain the behaviour of S needed for a particular augmented model. The goal of our plug-in is to generate a normal Event-B model that is the studied (augmented) model where the annotations are replaced with the superposition of the refined pattern model.

To explain briefly what is the idea of the pattern, we show below an augmented model (on the left) and the generated result (on the right). This small model define a light that can be on (lo = TRUE) or off (lo = FALSE); the light can be switch on by a button (the event on) and goes automaticaly off (event off) after a delay between cd and c + d. You can see the temporal annotations in the elements named lb of f (Lower Bounds) and up of f (Upper Bounds). The S operator can also appear in the invariant, for example we can write c + d < S(on) ⇒ lo = FALSE. To generate the model the plug-in will have to: declare a new variable s e for all events which appears in the operator S; reset this variable s e to zero in the event e; replace all S(e) by s e for all e; generate a tic event that increments the s e clocks (for all e) and add in the guard of tic the predicate : GUARD(f ) ⇒ s e + s ≤ u for all upper bound S(e) ≤ u in a event f , with GUARD(f ) being the guard of the event e (without temporal annotations).

For the user interface, we plan to specialize the standard "edit" editor of Rodin. The user will be able to add his annotations and when the machine is saved, the plugin will generate a normal machine. The proof will be done over the proof obligations of this generated machine.

For more information about our pattern see [START_REF] Rehm | Pattern Based Integration of Time applied to the 2-Slots Simpson Algorithm[END_REF], another example of pattern for time can be see in [START_REF] Cansell | Time constraint patterns for event B development[END_REF]. Our notion of (refinement) pattern is the same than the Action/Reaction pattern (see the chapter 3 of [START_REF] Abrial | Modeling in Event-B: System and Software Engineering[END_REF]). As related work, we can also cite the works about automatic refinement with tools like Bart2 . There are some common elements between this tool and our work, the major difference is that Bart transforms a B machine to a B machine (more close to an implementation), where our augmented model is not a normal B machine.

  lo := TRUE act2: s on := 0 End * This work was supported by grant No. ANR-06-SETI-015-03 awarded by the Agence Nationale de la Recherche. 1 http://www.event-b.org 1 off b = When grd1: lo = TRUE lb off: cd ≤ S(on) ub off: S(on) ≤ c + d Then act1: lo := FALSE End off b = When grd1: lo = TRUE lb off: cd ≤ s on Then act1: lo := FALSE End tic b = Any s Where grd1: 0 < s ub off: lo = TRUE ⇒s on + s ≤ c + d Then act1: s on := s on + s End

http://www.tools.clearsy.com/index.php5?title=BART_Project