Javier Pereira

Flexibility dimensions to control the bullwhip effect in a supply chain

In this paper, we analyse the consequences of two flexibility dimensions proposed in a previous approach—adjustment capability and responsiveness—on the bullwhip effect in a supply-chain model when a stochastic AR(1) demand process is considered. First modelling the managers belief on forecasting in pull, push and hybrid ordering methods, it is revealed that high adjustment capability induces a robust reduction of the bullwhip effect. Secondly, it is found that maximal responsiveness is not always a necessary management strategy. Indeed, we show that these dimensions may be organised in a trade-off, always keeping amplification to acceptable values in the whole supply chain.

Recommender system for contextual advertising in IPTV scenarios

This paper presents a recommender system for contextual targeted advertisement in Video-on-demand scenarios. The proposal arises from a real case of a Japanese company planning to add advertisement to its On-Demand IPTV services. The advertisements consist of icon or text-based links that may be shown before, during or after the playing of the film the customer has selected to watch. The goal of the company is to maximize the number of times customers follow the links to advertised sites because its revenues depends on this. Since only a small portion of the advertising links can be included in a movie, these must be selected carefully. This work proposes a recommender system for selecting the most appropriate advertisement for a certain customer based on the success the advertisement has had in the past among other customers having similar preferences. The paper describes the proposed method, shows the implementation work done so far and describes the remaining work in order to test it in the real scenario.

Robustness analysis in a TODIM-based multicriteria evaluation model of rental properties

AbstractA new robustness analysis framework is proposed where robustness of a solution in a decision aiding process is measured as the distance from that solution to an expected outcome, chosen by the decision-aiding analyst. The framework is explained by the application of the TODIM method of multicriteria decision aiding to the problem of predicting rental ranges for properties in a Chilean city. Therefore, the robustness concern concentrates on changes in criteria weights as well as in trade-off rates, as they are defined in the method. Two main contributions are introduced: a local robustness measure, defined in terms of a distance among rankings; and a global robustness measure, as an adaptation of the minimax-regret rule to select a global robust solution, i.e. a ranking produced by TODIM.

Identifying “interesting” component assemblies for NFRs using imperfect information

Component-based software elaboration becomes unwieldy for some practical situations with large numbers of components for which information is imperfect (incomplete, imprecise and/or uncertain). This article addresses the problem of identifying “interesting” component sets for some given non-functional requirements (NFRs), using imperfect information about large number of components. Rather than providing completely specified solutions, this approach allows architects to identify and compare whole assemblies, and focus eventual information- improvement efforts only on those components that are part of candidate assemblies. The proposed technique builds on the Azimut layered architectural abstractions, adapting an algorithmic approach used to mine association rules, and taking three parameters: a minimal “support score” that candidate assemblies must meet, and two credibility-value thresholds about the catalog themselves. An example illustrates the approach.

Choreography of web services based on natural language storybooks

Universally available services, which communicate in a standardized way, can provide a new generation of middleware. Harnessing the advantages of this promising middleware technology, however, means to be capable to understand and to handle its design language which emerges from standards like SOAP, WSDL, BPEL, etc. These languages are necessary for finding, composing and orchestrating web services. If at all, only IT experts are familiar with these languages.The key actors, the domain experts of business processes, however, are not IT experts, and thus do not become the main designers. WS-Talk is a research project that encourages the co-existence of Natural Language and Web service technology. It reinforces the role of domain experts in designing business processes without having to resort to their IT colleagues. In our approach business process experts write storybooks in their own language. Their instructions are matched with semantics that represent application logic that, in turn, supports the automatic composition of software components. The WS-Talk products currently support organizations in managing their own and individual information, i.e. to set up their own enterprise search engine.

Evaluating alternative COTS assemblies from imperfect component information

Component-based approaches to elaborate software must deal with the fact that in practical settings, components information may be incomplete, imprecise and uncertain, and requirements may be likewise. Architects wanting to evaluate candidate architectures regarding requirements satisfaction need to use whatever information be available about components, however imperfect. Imperfect information can be dealt with using specialized analytical formalisms, such as fuzzy values for imprecision and rough sets for incompleteness; but if used, evaluations need to compare and rank using non-scalar, non-symbolic values. This article presents an approach to systematically describe components’ imperfect information, and to evaluate and rank whole component assemblies, by using credibility values-based “support scores” that aggregate imperfect information about requirements, mechanisms and components. The approach builds on the Azimut framework, which offers progressive refinement of architectural entities via architectural policies, architectural mechanisms, components, and component assemblies. An example of the proposed approach and “what-if” analysis are illustrated.

Governance of Responsible Research and Innovation: An Agent-Based Model Approach

Abstract Responsible research and innovation is a new research field that is still emerging, particularly in connection with recent efforts within the European Commission. Inspired in these recent developments, we put forth the first agent-based model of responsible research and innovation (RRI). The model has been designed as a decision-aiding tool for both policymakers driving innovation policy and innovation managers facing the complex trade-offs posed by the involvement of civil society organizations in innovation agendas. The model allows policymakers and innovation strategists to inform and guide public policies and strategic decisions regarding the governance of responsible research and innovation.

A Context Description Language for Medical Information Systems

Contextualized delivery of information is one of the many strengths of ubiquitous computing. It makes information actionable and helps us to better understand our situations. In the realm of healthcare, contextual information provides a terse but precise picture of the patient’s health situation. The patient context can have many facets, ranging from nutrition context over health heritage context to the context of symptoms, just to name a few. Setting up the correct health condition context of a patient favors better and faster recognition of the patient’s actual health situation.

The role of natural language in social information engineering

In this paper we present work-in-progress - a technology platform for Social Collaboration in the context of Personalized Information Extraction. In particular, we consider elements of user-centered software engineering as it converges on the development of folksonomies. Results from our work-in-progress demonstrate to what extent non-IT users can apply natural language when managing their IT-based processes addressing information integration. We concentrate on the language model that supports the development of process-related folksonomies in the context of retrieving and merging textual information from different sources concerning legal documents. Findings in our work-in-progress underpin the conjecture that the computational nature of natural language overcomes the inherent problem of ambiguity when applied in a collaboration context that the users are aware of.

A practitioner experiment in understanding software process improvement using systems modular analysis

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