Enterprise Information Systems VI

Much has been written and many discussions have taken place on the causes and cures of IT projects. This introspection is not a new phenomenon. It has been going on as long as industrial size IT systems became into being. The continuing reliance of businesses, government and society on such systems coupled to the realisation that only a little progress has been made in the last 20–30 years in delivering effective and efficient systems are sufficient motivations for continuing this debate. This paper is the product of such a public debate by the authors during the 2004 International Conference on Enterprise Information System. The paper focuses on four topics: ecological complexity, product complexity, project management and education.

We examine how to improve our understanding in stating and managing successfully requirements for large systems, because the current concept of a system requirement is ill suited to develop true requirements for such systems. It regards requirements as goals to be discovered and solutions as separate technical elements. In consequence, current Requirements Engineering (RE) theory separates these issues and reduces RE to an activity where a technical solution is documented for a given set of goals (problems). In contrast, we advocate a view where a requirement specifies a set of mappings between problem and solution spaces, which both are socially constructed and negotiated. Requirements are emergent and need to be discovered through a contracted process, which likens to a “garbage-can” decision-making. System requirements thereby embrace an emergent functional ecology of requirements. This leads to equate requirements engineering with heterogeneous engineering. The admitted heterogeneity of technological activity avoids a commitment to social (or technological) reductionism. Requirements engineers need to be seen as “heterogeneous engineers” who must associate entities that range from people, through skills, to artifacts and natural phenomena. They are successful only, if built socio-technical networks can remain stable in spite of attempts of other entities to dissociate them.

Agile methods need to include stakeholder metrics in order to ensure that projects focus better on the critical requirements, and that projects are better able to measure their achievements, and to adapt to feedback. This paper presents a short, simple defined process for evolutionary project management (Evo), and discusses its key features.

The

complexity

of modern software is not that much in the size of systems as it is in the “wires” — in the linkages and communication paths between system components. The inter-component linkages create dependencies between distributed components that are difficult to understand and manage. The difficulty is inflated by the fact that components are frequently developed and managed by separate teams and by various component providers.

This paper identifies main issues for successful management of complexity in large software projects. It uses the

holon

hypothesis to explain that all complex systems of a stable but evolvable character display hierarchic organization. The paper makes it clear that a complexity-aware

architectural design

paves the way for developing

supportable systems

. It makes it also clear that unless implementation is design-conformant and complexity-assured, the initial good intents may still result in an unsupportable system. Without rigorous project management, supported by tools able to compute and visualize

complexity metrics

, contemporary large software production risks delivering unsupportable systems.

Most of the software discipline has come to honor the role of architecture to organize software development. The software pattern discipline has taken up the architectural metaphor quite literally, borrowing its key notions from Christopher Alexander, an innovative master builder of houses, neighborhoods, and towns. However, the software industry has missed the obvious: that architecture is a secondary concern that precipitates from the structure of the enterprise that builds it. Getting the architecture right means getting the enterprise structure right: it is certainly a necessary and potentially sufficient condition for achieving most of the goals that software engineering holds out for architectural activity.

Like most metaphors, the architectural metaphor breaks down somewhere. Unlike houses, whose structure tends to reflect the activities of the end users of the product, the structure of software exists more to serve those who build it than those who use it. This parallel has been shifting, but not on the software side: modern buildings, driven more by technology that make it possible to create 100-foot spans on the ground floor of a skyscraper, pay homage to the technology to be used in construction, and to the design techniques used to support that technology. Software, a largely technological field, has had this outlook almost from the beginning. As an industry focused on technology, it is no surprise that our software pattern discipline has taken up a largely technical agenda. Our current direction in patterns avoids the most central foundation of the pattern discipline: to build systems that are beautiful, morally profound, and “habitable” for the people they touch.

Yet there is hope: as a strong parallel to the structural concerns of software that are found in software architecture,

organizational patterns

give a voice to the crucial structural constructs of software development enterprises. It is these structures of human relationships, rather than the technological underpinnings, that drive architecture. That fact has long been known to the industry as Conway’s Law, but most managers view Conway’s Law more as a Dilbertesque joke than as a sober planning principle.

Organizational patterns are a major stride for creating the generative structure of the business—the structure of the enterprise itself—that gives rise to such other important structures as the system architecture and, by inference, the system’s human interface. The first major pattern language of software organizational structure has been completed after a decade of research. There is much more that can be done—not just by organizational specialists, but also by “software people” of every job and description.

We present an assessment of an empirical study aiming at building effort estimation models for corrective maintenance projects. We show results from the application of the prediction models to a new corrective maintenance project within the same enterprise and the same type of software systems used in a previous study. The data available for the new project are finer grained according to the indications devised in the first study. This allowed to improve the confidence in our previous empirical analysis by confirming most of the hypotheses made and to provide other useful indications to better understand the maintenance process of the company in a quantitative way.

This paper analyzes the evolution of organizational and technological critical success factors along the ERP implementation phases. The identification of factors leading to success or failure of ERP systems is an issue of increasing importance, since the number of organizations choosing the ERP path keeps growing. Our findings suggest that while both good organizational and technological perspectives are essential for a successful ERP implementation project, their importance shifts as the project moves through its lifecycle.

An adaptive caching algorithm, known as Adaptive Caching with Multiple Experts (ACME), has recently been presented in the field of web-caching. We explore the migration of ACME to the database caching environment. By integrating recently proposed database replacement policies into ACME’s existing policy pool, an attempt is made to gauge ACME’s ability to utilise newer methods of database caching. The results suggest that ACME is indeed well-suited to the database environment and performs as well as the best currently caching policy within its policy pool at any particular moment in its request stream. Although execution time increases by integrating more policies into ACME, the overall processing time improves drastically with erratic patterns of access, when compared to static policies.

This paper presents a strategy for applying sampling techniques to relational databases, in the context of data quality auditing or decision support processes. Fuzzy cluster sampling is used to survey sets of records for correctness of business rules. Relational algebra estimators are presented as a data quality-auditing tool.

The paper discuss reasons why service-oriented architecture is a new software paradigm and the consequences of this fact for the design of enterprise information systems. It is shown that such systems called confederations need not use web services in the sense of W3C. It is, however, more or less a necessity in e-commerce. Confederations (service-oriented systems with known set of services) are typical for manufacturing systems. As business processes supported by enterprise systems must be supervised by businessmen, the same must hold for communication inside service-oriented systems. It implies that the interfaces of the services must be user-oriented (user-friendly). It can be easier achieved in confederations than in e-commerce systems. User oriented interface has positive consequences for the software engineering properties of the confederation. Confederations should sometimes include parts based on different implementation philosophies (e.g. data orientation). Pros and cons of it are discussed. Open issues of service orientation are presented.

Presently, digital continuous media (CM) are well established as an integral part of many applications. In recent years, a considerable amount of research has focused on the efficient retrieval of such media. Scant attention has been paid to servers that can record such streams in real time. However, more and more devices produce direct digital output streams. Hence, the need arises to capture and store these streams with an efficient data stream recorder that can handle both recording and playback of many streams simultaneously and provide a central repository for all data.

In this report we investigate memory management in the context of large scale data stream recorders. We are especially interested in finding the minimal buffer space needed that still provides adequate resources with varying workloads. We show that computing the minimal memory is an

NP

-complete problem and will require further study to discover efficient heuristics.

One of the key decision activities in financial institutions is to assess the credit-worthiness of an applicant for a loan, and thereupon decide whether or not to grant the loan. Many classification methods have been suggested in the credit-scoring literature to distinguish good payers from bad payers. Especially neural networks have received a lot of attention. However, a major drawback is their lack of transparency. While they can achieve a high predictive accuracy rate, the reasoning behind how they reach their decisions is not readily available, which hinders their acceptance by practitioners. Therefore, we have, in earlier work, proposed a two-step process to open the neural network black box which involves: (1) extracting rules from the network; (2) visualizing this rule set using an intuitive graphical representation. In this paper, we will focus on the second step and further investigate the use of two types of representations: decision tables and diagrams. The former are a well-known representation originally used as a programming technique. The latter are a generalization of decision trees taking on the form of a rooted, acyclic digraph instead of a tree, and have mainly been studied and applied by the hardware design community. We will compare both representations in terms of their ability to compactly represent the decision knowledge extracted from two real-life credit-scoring data sets.

Large product variety in mass customization involves a high internal complexity level inside a company’s operations, as well as a high external complexity level from a customer’s perspective. To cope with both complexity problems, an information system based on agent technology is able to be identified as a suitable solution approach. The mass customized products are assumed to be based on a modular architecture and each module variant is associated with an autonomous rational agent. Agents have to compete with each other in order to join coalitions representing salable product variants which suit real customers’ requirements. The negotiation process is based on a market mechanism supported by the target costing concept and a Dutch auction. Furthermore, in order to integrate the multi-agent system in the existing information system landscape of the mass customizer, a technical architecture is proposed and a scenario depicting the main communication steps is specified.

In the past years, the

Clinical Data Mining

arena has suffered a remarkable development, where

intelligent data analysis

tools, such as

Neural Networks

, have been successfully applied in the design of medical systems. In this work,

Neural Networks

are applied to the prediction of organ dysfunction in

Intensive Care Units

. The novelty of this approach comes from the use of

adverse events

, which are triggered from four bedside alarms, being achieved an overall predictive accuracy of 70%.

Temporal mining is a natural extension of data mining with added capabilities of discovering interesting patterns, inferring relationships of contextual and temporal proximity and may also lead to possible cause-effect associations. Temporal mining covers a wide range of paradigms for knowledge modeling and discovery. A common practice is to discover frequent sequences and patterns of a single variable. In this paper we present a new algorithm which is the combination of many existing ideas consists of the reference event as proposed in (Bettini, Wang et al. 1998), the event detection technique proposed in (Guralnik and Srivastava 1999), the large fraction proposed in (Mannila, Toivonen et al. 1997), the causal inference proposed in (Blum 1982) We use all of these ideas to build up our new algorithm for the discovery of multivariable sequences in the form of the predisposing factor and co-incident factor of the reference event of interest. We define the event as positive direction of data change or negative direction of data change above a threshold value. From these patterns we infer predisposing and co-incident factors with respect to a reference variable. For this purpose we study the Open Source Software data collected from SourceForge website. Out of 240+ attributes we only consider thirteen time dependent attributes such as Page-views, Download, Bugs0, Bugs1, Support0, Support1, Patches0, Patches1, Tracker0, Tracker1, Tasks0, Tasks1 and CVS. These attributes indicate the degree and patterns of activities of projects through the course of their progress. The number of the Download is a good indication of the progress of the projects. So we use the Download as the reference attribute. We also test our algorithm with four synthetic data sets including noise up to 50 %. The results show that our algorithm can work well and tolerate the noise data.

With the development and the availability of large textual corpora, there is a need for enriching and organizing these corpora so as to make easier the research and navigation among the documents. The Semantic Web research focuses on augmenting ordinary Web pages with semantics. Indeed, wealth of information exists today in electronic form, they cannot be easily processed by computers due to lack of external semantics. Furthermore, the semantic addition is an help for user to locate, process information and compare documents contents. For now, Semantic Web research has been focused on the standardization, internal structuring of pages, and sharing of ontologies in a variety of domains. Concerning external structuring, hypertext and information retrieval communities propose to indicate relations between documents via hyperlinks or by organizing documents into concepts hierarchies, both being manually developed. We consider here the problem of automatically structuring and organizing corpora in a way that reflects semantic relations between documents. We propose an algorithm for automatically inferring concepts hierarchies from a corpus. We then show how this method may be used to create specialization/generalization links between documents leading to document hierarchies. As a byproduct, documents are annotated with keywords giving the main concepts present in the documents. We also introduce numerical criteria for measuring the relevance of the automatically generated hierarchies and describe some experiments performed on data from the LookSmart and New Scientist web sites.

The Differential Evolution algorithm goes back to the class of Evolutionary Algorithms and inherits its philosophy and concept. Possessing only three control parameters (size of population, differentiation and recombination constants) Differential Evolution has promising characteristics of robustness and convergence. In this paper we introduce a new principle of Energetic Selection. It consists in both decreasing the population size and the computation efforts according to an energetic barrier function which depends on the number of generation. The value of this function acts as an energetic filter, through which can pass only individuals with lower fitness. Furthermore, this approach allows us to initialize the population of a sufficient (large) size. This method leads us to an improvement of algorithm convergence.

In this work, we start from a database built with soil information from heterogeneous scientific sources (Local Soil Databases, LSDB). We call this an Aggregated Soil Database (ASDB). We are interested in determining if knowledge obtained by means of fuzzy association rules or fuzzy approximate dependencies can represent adequately expert knowledge for a soil scientific, familiarized with the study zone. A master relation between two soil attributes was selected and studied by the expert, in both ASDB and LSDB. Obtained results reveal that knowledge extracted by means of fuzzy data mining tools is significatively better than crisp one. Moreover, it is highly satisfactory from the soil scientific expert’s point of view, since it manages with more flexibility imprecision factors (IFASDB) commonly related to this type of information.

To an increasing extend software systems are integrated across the borders of individual enterprises. The Web service approach provides group of technologies to describe components and their composition, based on well established protocols. Focused on business processes, one Web service implements a local subprocess. A distributed business processes is implemented by the composition a set of communicating Web services.

At the moment, there are various modeling languages under development to describe the internal structure of one Web service and the choreography of a set of Web services. Nevertheless, there is a need for methods for stepwise construction and verification of such components.

This paper abstracts from concrete syntax of any proposed language definition. Instead, we apply Petri nets to model Web services. Thus, we are able to reason about essential properties, e. g.

usability

of a Web service — our notion of a quality criterion. Based on this framework, we present an algorithm to analyze a given Web service and to transfer a complex process model into a appropriate model of a Web service.

COTS (Commercial Off-The-Shelf) components can be incorporated into other systems to help software developers to produce a new system, so that both artefacts — components and the system — form a single functional entity. In that way, developing software becomes a matter of balancing required and offered functionality between the parties. But required functionality is highly dependent on component’s users, i.e. stakeholders of a COTS component selection process. Inputs to this process include discussions with composers, reuse architects, business process coordinators, and so forth. In this paper, we present an approach for balancing stakeholder’s preferences, which can be used in the process of measuring functional suitability of COTS candidates. We describe and illustrate the use of our proposal to weight requirements of components and determine suitable COTS candidates for given software.

Nowadays, there is an increasing need for flexible approaches, adaptable to different kinds of Information System Development (ISD). But customization of ISD processes have mainly be thought of for the person in charge of building processes, i.e. the methodologists, in order to allow him/her to adapt the process to the need of its company or projects. But there is also a need for customizations dedicated to project team members (application engineers), to provide them with customized guidelines (or heuristics) which are to be followed while performing their daily task. The knowledge capitalization framework we propose supports evolvability and customization of ISD processes. Reuse and customization are handled through

process fragments

stored in a dedicated

repository

. Our purpose is not to propose a new way to built processes, as several approaches already exist on this topic, but to ease the use of existing ones by making them less rigid and allowing their adaptation to the need of the company, the project and most of all, the project team member. Therefore, in addition to a

repository

of

process fragments

, we propose a scalable and polymorphic structure allowing methodologists to define a working space through a

context

made of

criterias

. Thanks to this

context

the project team members better qualify their ISD problem in order to find a suitable solution. A solution is made of

process fragments

organized into a

route-map

specially built to answer the project team member need and directly usable by him/her.

The

context-frame

we focus on in this paper is a scalable structure which supports evolution and tailoring by the methodologists for the project team member’s need with regards to project and process features.

There is a growing need to reduce the cycle of business information systems development and make it independent of underlying technologies. Model-driven synthesis of software offers solutions to these problems. This article describes a method for synthesizing business software implementations from technology independent business models. The synthesis of business software implementation performed in two steps, is based on establishing a common feature space for problem and solution domains. In the first step, a solution domain and a software architecture style are selected by matching the explicitly required features of a given software system, and implicitly required features of a given problem domain to the features provided by the solution domain and the architectural style. In the second step, all the elements of a given business analysis model are transformed into elements or configurations in the selected solution domain according to the selected architectural style, by matching their required features to the features provided by the elements and configurations of the selected solution domain. In both steps it is possible to define cost functions for selecting between different alternatives which provide the same features. The differences of our method are the separate step of solution domain analysis during the software process, which produces the feature model of the solution domain, and usage of common feature space to select the solution domain, the architectural style and specific implementations.

The developments in the ICT led companies to strive to make parts of the business transaction electronic and raised again the issue of interoperability. Although interoperability between computer systems has been widely addressed in literature, the concept of interoperability between organizations is still to a large extent unexplored. Standards are claimed to help achieving interoperability. However, experience with the implementation of EDI standards shows that many EDI implementation projects led to technical solutions with unclear business benefits. New standards are currently being developed, however their implementation can also lead again to purely technical solution, if the social context is not taken sufficiently into account. In this paper we address the problem on how to identify interoperability problems on a pragmatic level that can occur between organizations that want to carry out business transactions electronically. We also point out that, in order to identify interoperability problems on a pragmatic level, it is necessary to capture the communication requirements of the business parties and to evaluate to what extent a standard is capable to meet these requirements. To perform that evaluation we develop a meta model for describing communication. The meta model is based on theory of speech-act and communicative actions. The use of the meta model to identify interoperability problems on a pragmatic level is illustrated with an example.

Past few years have witnessed a growing recognition of intelligent techniques for the construction of efficient and reliable intrusion detection systems. Due to increasing incidents of cyber attacks, building effective intrusion detection systems (IDS) are essential for protecting information systems security, and yet it remains an elusive goal and a great challenge. In this paper, we report a performance analysis between Multivariate Adaptive Regression Splines (MARS), neural networks and support vector machines. The MARS procedure builds flexible regression models by fitting separate splines to distinct intervals of the predictor variables. A brief comparison of different neural network learning algorithms is also given.

CASE tools supporting many activities of the software development process embed visual modeling environments. Indeed, visual languages are practical means to allow engineers to define models and different views of software systems. However the effectiveness of visual modeling environments strongly depends from the process and tools used for their development. In this paper we present a user-centered methodology for the development of customized visual environments, and a tool to support it. The use of UML meta-modeling techniques and formal methods characterizes the proposed approach. Moreover, incremental development and rapid prototyping are ensured by the use of an automatic generation tool that allows designers to focus on structural features of the target language disregarding the visual environment creation.

Some consulting projects are carried out in virtual teams, which are networks of people sharing a common purpose and working across organizational and temporal boundaries by using information technologies. Multiple investigations covering these teams focus on coordination, group communication and computer supported collaborative work. However, additional perspectives like the formation of teams are also important. Here one should deal with the question: how to form the best team?

To approach this question, we have defined team formation as the process of finding the right expert for a given task and allocating the set of experts that best fulfills team requirements. This has been further transformed into a problem of constraint based optimal resource allocation.

Our environment for computer supported team formation has been developed by having adopted the brokerage view that consists of mediating experts between peers requesting a team and the ones willing to participate in a team. Computer supported brokerage of experts has been realized as a distributed problem solving that involves entities representing experts, brokers and team initiators.

E-learning is starting to play a major role in the learning and teaching activities at institutions of higher education worldwide. The students perform significant parts of their study activities decentralized and access the necessary information sources via the Internet. Several tools have been developed providing basic infrastructures that enable individual and collaborative work in a location-independent and time-independent fashion. Still, systems that adequately provide personalized and permanent support for using these tools are still to come.

This paper reports on the advances of the Semantic E-learning Agent (SEA) project, whose objective is to develop virtual student advisors, that render support to university students in order to successfully organize und perform their studies. The E-learning agents are developed with novel concepts of the Semantic Web and agents technology. The key concept is the semantic modeling of the E-learning domain by means of XML-based applied ontology languages such as DAML+OIL and OWL. Software agents apply ontological and domain knowledge in order to assist human users in their decision making processes. For this task, the inference engine JESS is applied in conjunction with the agent framework JADE.

Providing mobile workers with mobile devices such as a Compaq iPaq with a CDPD card can support them in retrieving information from centralized information systems. More specifically, mobile devices can enable mobile users to make notifications for schedule changes and add new data into the information system. In addition these devices can facilitate group communication anytime and anywhere. This paper presents different ways of providing non-critical information in a timely fashion for nomadic users of mobile devices using a wireless network. A distributed application prototype to support nomadic users is proposed, and a simulated environment is used to evaluate the prototype. Since solutions for seamless access are highly domain specific, the study involves homecare workers at Saskatoon District Health (SDH). By keeping track of the users’ current context (time, location etc.) and a user task model, it is possible to predict the information needs of mobile users and to provide context dependent adaptation of both the content and the functionality. Moreover, to avoid interrupts in the user’s interaction with the main information sources, methods for mobile transactions management using agent-based smart proxies that buffer, delay or pre-fetch information/data are introduced.

This paper proposes an agent programming language called AgentSpeak(I). This new language allows agent programs (1) to effectively perform while having incomplete knowledge of the environment, (2) to detect no-longer possible goals and re-plan these goals correspondingly, and (3) to behave reactively to changes of environment. Specifically, AgentSpeak(I) uses default theory as agent belief theory, agent always act with preferred default extension at current time point (i.e. preference may changes over time). A belief change operator for default theory is also provided to assist agent program to update its belief theory. Like other BDI agent programming languages, AgentSpeak(I) uses semantics of transitional system. It appears that the language is well suited for intelligent applications and high level control robots, which are required to perform in highly dynamic environment.

The capture, the structuring and the exploitation of the expertise or the capabilities of an “object” (like a business partner, an employee, a software component, a Web site, etc.) are crucial problems in various applications, like cooperative and distributed applications or e-business and e-commerce applications. The work we describe in this paper concerns the advertising of the capabilities or the know-how of an object. The capabilities are structured and organized in order to be used when searching for objects that satisfy a given objective or that meet a given need. One of the originality of our proposal is in the nature of the answers the intended system can return. Indeed, the answers are not Yes/No answers but they may be cooperative answers in that sense that when no single object meets the search criteria, the system attempts to find out what a set of “complementary” objects do satisfy the whole search criteria, every object in the resulting set satisfying part of the criteria. In this approach, Description Logics (DL) is used as a knowledge representation formalism and classification techniques are used as search mechanisms. The determination of the “complementary objects” is founded on the DL complement concept.

In this paper, we present an innovating on-line monitoring system that has been developed by applying new advances in biosensors, mobile devices and wireless technologies. The aim of the system is to monitor people that suffer from heart arrhythmias without having to be hospitalized; and therefore, living a normal life while feeling safe at the same time. On the one hand, the architecture of the system is presented; and, on the other hand, some performance results and implementation details are explained showing how the previous solution can be effectively implemented and deployed into a system that makes use of PDAs, and wireless communications: Bluetooth and GPRS. Moreover, special attention is paid to two aspects: cost of the wireless communications and notification latency for the detected serious heart anomalies.

In order to support the residual communication capabilities of verbal impaired peoples softwares allowing Augmentative and Alternative Communication (AAC) have been developed. AAC communication software aids provide verbal disables with an electronic table of AAC languages (i.e. Bliss, PCS, PIC, etc.) symbols in order to compose messages, exchange them via email, or vocally synthetize them, and so on. A current open issue, in thins kind of software, regards human-computer interaction in verbal impaired people suffering motor disorders. They can adopt only ad-hoc input device, such as buttons or switches, which require an intelligent automatic scansion of the AAC symbols table in order to compose messages. In such perspective we have developed

Caba

2

l

an innovative composition assistant exploiting an user linguistic behavior model adopting a semantic/probabilistic approach for predictive Bliss symbols scansion.

Caba

2

l

is based on an original discrete implementation of auto-regressive hidden Markov model called DAR-HMM and it is able to predict a list of symbols as the most probable ones according to both the previous selected symbol and the semantic categories associated to the symbols. We have implemented the composition assistant as a component of

Bliss

2003 an AAC communication software centered on Bliss language and experimentally validated it with both synthetic and real data.

This paper puts forward a new design method based upon Alexandrian patterns for interface design for particular user groups. The author has created a set of interface design patterns for speech systems for older adults with the aim of supporting the dynamic diversity in this group. The patterns themselves reflect a significant body of research work with this user group uncovering important information about how they interact with speech systems. The design knowledge embedded in these patterns is therefore closely linked to knowledge about the user and enables interface designers to clarify which users are excluded from their software.

Within corporate intranet or on the WWW, a global search engine is the main service used to discover and sort information. Nevertheless, even the most “intelligent” ones have great difficulties to select those targeted to each user specific needs and preferences. We have built a mediated social media named SoMeONe, which helps people to control their information exchanges through trusted relationships. A key component of this system is a contact recommender, which helps people to open their relationship networks by exchanging targeted information with qualified new users. Instead of using only matching between interests of users, this “socially aware” recommender system also takes into account existing relationships in the social network of the system. In this paper, we describe the computations of those recommendations based on a social network analysis.

Man-Machine Interaction (MMI) systems that utilize multimodal information about users’ current emotional state are presently at the forefront of interest of the computer vision and artificial intelligence communities. Interfaces with human faces expressing emotions may help users feel at home when interacting with a computer because they are accepted as the most expressive means for communicating and recognizing emotions. Thus, emotion synthesis can enhance the atmosphere of a virtual environment and communicate messages far more vividly than any textual or speech information. In this paper, we present an abstract means of description of facial expressions, by utilizing concepts included in the MPEG-4 standard to synthesize expressions using a reduced representation, suitable for networked and lightweight applications.

Internet accessibility for the visually impaired community is still an open issue. Guidelines have been issued by the W3C consortium to help web designers to improve web site accessibility. However several studies show that a significant percentage of web page creators are still ignoring the proposed guidelines. Several tools are now available, general purpose, or web specific, to help visually impaired readers. But is reading a web page enough? Regular sighted users are able to scan a web page for a particular piece of information at high speeds. Shouldn’t visually impaired readers have the same chance? This paper discusses some features already implemented to improve accessibility and presents a user feedback report regarding the AudioBrowser, a talking browser. Based on the user feedback the paper also suggests some avenues for future work in order to make talking browsers and screen readers compatible.

The success of the Information Society, with the overabundance of online multimedia information, has become an obstacle for users to discover pertinent resources. For those users, the key is the refinement of resource discovery as the choice and complexity of available online content continues to grow. The work presented in this paper will address this issue by representing complex extensible user and information provider profiles and content metadata using XML and the provision of a middle canonical language to aid in learner-to-content matching, independent of the underlying metadata format. This approach can provide a federated search solution leading to personalise resource discovery based on user requirements and preferences, seamlessly searching over multiple repository types. The novelty of the work includes the complex extensible user profiles, information provider profiles, the canonical language and the federated search strategy. Although, the work presented is focused on E-Learning, the general ideas could be applied to any resource discovery or information retrieval system.