Uma abordagem baseada em filtragem colaborativa integrada a mapas de saliência para a recomendação de imagens

Nowadays, the amount of customers using sites for shopping is greatly increasing, mainly due to the easiness and rapidity of this way of consumption. The sites, differently from physical stores, can make anything available to customers. In this context, Recommender Systems (RS) have become indispensable to help consumers to find products that may possibly pleasant or be useful to them. These systems often use techniques of Collaborating Filtering (CF), whose main underlying idea is that products are recommended to a given user based on purchase information and evaluations of past, by a group of users similar to the user who is requesting recommendation. One of the main challenges faced by such a technique is the need of the user to provide some information about her preferences on products in order to get further recommendations from the system. When there are items that do not have ratings or that possess quite few ratings available, the recommender system performs poorly. This problem is known as new item cold-start. In this paper, we propose to investigate in what extent information on visual attention can help to produce more accurate recommendation models. We present a new CF strategy, called IKB-MS, that uses visual attention to characterize images and alleviate the new item cold-start problem. In order to validate this strategy, we created a clothing image database and we use three algorithms well known for the extraction of visual attention these images. An extensive set of experiments shows that our approach is efficient and outperforms state-of-the-art CF RS.

RF MIMO Systems for Wide-Area Indoor Human Motion Monitoring

Human motion monitoring is an important function in numerous applications. In this dissertation, two systems for monitoring motions of multiple human targets in wide-area indoor environments are discussed, both of which use radio frequency (RF) signals to detect, localize, and classify different types of human motion. In the first system, a coherent monostatic multiple-input multiple-output (MIMO) array is used, and a joint spatial-temporal adaptive processing method is developed to resolve micro-Doppler signatures at each location in a wide-area for motion mapping. The downranges are obtained by estimating time-delays from the targets, and the crossranges are obtained by coherently filtering array spatial signals. Motion classification is then applied to each target based on micro-Doppler analysis. In the second system, multiple noncoherent multistatic transmitters (Tx's) and receivers (Rx's) are distributed in a wide-area, and motion mapping is achieved by noncoherently combining bistatic range profiles from multiple Tx-Rx pairs. Also, motion classification is applied to each target by noncoherently combining bistatic micro-Doppler signatures from multiple Tx-Rx pairs. For both systems, simulation and real data results are shown to demonstrate the ability of the proposed methods for monitoring patient repositioning activities for pressure ulcer prevention.

Comparing architectural styles for distributed expert knowledge modules in intelligent tutoring systems

Intelligent Tutoring Systems (ITSs) are computerized systems for learning-by-doing. These systems provide students with immediate and customized feedback on learning tasks. An ITS typically consists of several modules that are connected to each other. This research focuses on the distribution of the ITS module that provides expert knowledge services. For the distribution of such an expert knowledge module we need to use an architectural style because this gives a standard interface, which increases the reusability and operability of the expert knowledge module. To provide expert knowledge modules in a distributed way we need to answer the research question: ‘How can we compare and evaluate REST, Web services and Plug-in architectural styles for the distribution of the expert knowledge module in an intelligent tutoring system?’. We present an assessment method for selecting an architectural style. Using the assessment method on three architectural styles, we selected the REST architectural style as the style that best supports the distribution of expert knowledge modules. With this assessment method we also analyzed the trade-offs that come with selecting REST. We present a prototype and architectural views based on REST to demonstrate that the assessment method correctly scores REST as an appropriate architectural style for the distribution of expert knowledge modules.

EMMA 2--a MAGE-compliant system for the collaborative analysis and integration of microarray data

Background: Understanding transcriptional regulation by genome-wide microarray studies can contribute to unravel complex relationships between genes. Attempts to standardize the annotation of microarray data include the Minimum Information About a Microarray Experiment (MIAME) recommendations, the MAGE-ML format for data interchange, and the use of controlled vocabularies or ontologies. The existing software systems for microarray data analysis implement the mentioned standards only partially and are often hard to use and extend. Integration of genomic annotation data and other sources of external knowledge using open standards is therefore a key requirement for future integrated analysis systems. Results: The EMMA 2 software has been designed to resolve shortcomings with respect to full MAGE-ML and ontology support and makes use of modern data integration techniques. We present a software system that features comprehensive data analysis functions for spotted arrays, and for the most common synthesized oligo arrays such as Agilent, Affymetrix and NimbleGen. The system is based on the full MAGE object model. Analysis functionality is based on R and Bioconductor packages and can make use of a compute cluster for distributed services. Conclusion: Our model-driven approach for automatically implementing a full MAGE object model provides high flexibility and compatibility. Data integration via SOAP-based web-services is advantageous in a distributed client-server environment as the collaborative analysis of microarray data is gaining more and more relevance in international research consortia. The adequacy of the EMMA 2 software design and implementation has been proven by its application in many distributed functional genomics projects. Its scalability makes the current architecture suited for extensions towards future transcriptomics methods based on high-throughput sequencing approaches which have much higher computational requirements than microarrays.

Elastic Computing - a novel paradigm for distributed systems

This talk, which is based on our newest findings and experiences from research and industrial projects, addresses one of the most relevant challenges for a decade to come: How to integrate the Internet of Things with software, people, and processes, considering modern Cloud Computing and Elasticity principles. Elasticity is seen as one of the main characteristics of Cloud Computing today. Is elasticity simply scalability on steroids? This talk addresses the main principles of elasticity, presents a fresh look at this problem, and examines how to integrate people, software services, and things into one composite system, which can be modeled, programmed, and deployed on a large scale in an elastic way. This novel paradigm has major consequences on how we view, build, design, and deploy ultra-large scale distributed systems.

Collaborative Systems for Smart Networked Environments

International audience

Strategic Context, Organizational Features and Network Performances: A Survey on Collaborative Networked Organizations of Italian SMEs

Part 15: Performance Management Frameworks

Collaborative Systems in Crisis Management: A Proposal for a Conceptual Framework

Part 11: Reference and Conceptual Models

Achieving Coherence between Strategies and Value Systems in Collaborative Networks

Part 8: Business Strategies Alignment

Collaborative Networked Organizations as System of Systems: A Model-Based Engineering Approach

Part 6: Engineering and Implementation of Collaborative Networks