An intelligent sales assistant for configurable products

Some of the recent proposals of web-based applications are oriented to provide advanced search services through virtual shops. Within this context, this paper proposes an advanced type of software application that simulates how a sales assistant dialogues with a consumer to dynamically configure a product according to particular needs. The paper presents the general knowl- edge model that uses artificial intelligence and knowledge-based techniques to simulate the configuration process. Finally, the paper illustrates the description with an example of an application in the field of photography equipment.

‘State-of-the-art’ of building integrated photovoltaic products

During the last decades, the photovoltaic (PV) modules and their associated architectural materials are increasingly being incorporated into the construction of the building envelope such as façade, roof and skylights in the urban centers. This paper analyzes the-state-of-the-art of the PV elements and construction materials which are advertised as BIPV-products at the most important companies in the world. For this purpose 136 companies and 445 PV elements have been investigated and analyzed from a technical and architectural point of view. Also, the study has been divided into two main groups according to industry which producing the product: BIPV-Modules, which comes from the PV modules manufacturers and consist of standard PV-modules with some variations in its aesthetic features, support or dimensions; and PV-Constructions Elements, which consist of conventional constructive elements with architectural features intentionally manufactured for photovoltaic integration. In advance for conclusions, the solar tile is the most common PV-constructions element, the Si-crystalline is the most widely used PV technology, and the BIPV-urban furniture is the fastest growing market experienced in recent years. However, it is clear the absences of innovative elements which meet at the same time both the constructive purpose as the quality standards of PV technology.

Cross-Products LASSO

Negative co-occurrence is a common phenomenon in many signal processing applications. In some cases the signals involved are sparse, and this information can be exploited to recover them. In this paper, we present a sparse learning approach that explicitly takes into account negative co-occurrence. This is achieved by adding a novel penalty term to the LASSO cost function based on the cross-products between the reconstruction coefficients. Although the resulting optimization problem is non-convex, we develop a new and efficient method for solving it based on successive convex approximations. Results on synthetic data, for both complete and overcomplete dictionaries, are provided to validate the proposed approach.