Abstract
The paper proposes a mixed annotation approach that exploits the advantages of both automatic and manual annotation techniques. Annotated multimedia material is regarded as a source of low- to high-level feature mappings supporting the propagation of annotations to new multimedia material. Video analysis tools do not currently produce effective annotations for retrieval, while manual annotation is expensive. The proposed approach uses low-level feature similarity to guide the retrieval of keyword annotations and aims to preserve the high quality of manual annotations while reducing the time and cost per annotated video unit. The annotation tool assists users, suggesting keywords for an item that come from similar items according to low-level descriptors. The effectiveness of current descriptors has been evaluated in an experimental environment using 5 video collections and a set of MPEG-7 descriptors. The similarity results have been compared to manually evaluated similarity.

Abstract
The widespread use of new technologies for data acquisition and communications is disclosing large amounts of time-varying data that organizations wish to use for monitoring or decision support purposes. The efficient management of such large data sets depends largely on the use of appropriate data structures and access methods. This issue is an important topic of research in the spatiotemporal databases community. This paper presents a novel approach for the representation of large series of time-varying multidimensional data. It is based on a model of approximations that allows creating a hierarchical data structure by using different degrees of precision for each level. The hierarchical data structure allows representing an instance of a single series of discretely or continuously changing data as an abstract data type. The paper also shows how to use this approach to represent the movement of an object within a spatiotemporal database system.

Abstract
In this paper, global descriptors from MPEG7, GIST and Compact Composite Descriptors are evaluated for image retrieval in the IRMA-2007 medical collection. This evaluation tests descriptors using every image from each class instead of a small group of representative images. The evaluation results obtained by Mean-Average Precision (MAP) and precision@N indicate that MPEG7 EH, GIST and Fuzzy BTDH outperform the other global descriptors analyzed by a large margin, even more when combined by late-fusion rank aggregation. A multimedia retrieval evaluation systemwas developed to support the experiment and offers the possibility of textual, visual and combined searches over the medical collection. © 2010 IEEE.

Abstract
Journalists and bloggers need to find useful images to illustrate news stories and blog entries with high quality photos. The dpikt text illustration system uses multimedia information retrieval to assist this content enrichment task. Users query the system with text fragments and get collections of candidate photos. Images in the results can be visually sorted according to a selected photo, or be used as a seed for interactive searches over the entire collection. dpikt incorporates a recent visual descriptor, the Joint Composite Descriptor, and an approximate indexing scheme designed for large-scale image collections, the Permutation-Prefix Index. We have used the SAPO-Labs large-scale news stories photo collection, containing almost two million high quality photos with short descriptions, as the resource for the illustration task. © 2011 IEEE.

Abstract
In this paper, we approach the task of finding suitable images to illustrate text, from specific news stories to more generic blog entries. We have developed an automatic illustration system supported by multimedia information retrieval, that analyzes text and presents a list of candidate images to illustrate it. The system was tested on the SAPO-Labs media collection, containing almost two million images with short descriptions, and the MIRFlickr-25000 collection, with photos and user tags from Flickr. Visual content is described by the Joint Composite Descriptor and indexed by a Permutation-Prefix Index. Illustration is a three-stage process using textual search, score filtering and visual clustering. A preliminary evaluation using exhaustive and approximate visual searches demonstrates the capabilities of the visual descriptor and approximate indexing scheme used. © 2011 IEEE.

Abstract
The integration of computer systems into clinical practice is a consequence of the growing sophistication of medical machinery. The fact that patient management in large institutions is handled by complex information systems brings about the need for integration between applications on both sides. The paper describes a prototype for automatic data collection from intensive care devices developed at Pedro Hispano Hospital in Portugal. The system acts as an application gateway between the network of patient monitoring devices and the general-purpose hospital network. The conformance to medical standards is one of the main concerns. The international standard Health Level 7 (HL7) has been adopted to import vital signs, as well as to prepare data for visualization in departmental applications and to organize archives. The design has followed the administrative and clinical processes in the hospital closely, leading to a successful interaction with the health professionals. Automatic acquisition eliminates transcription errors, improves the quality of records and allows the assembly of large electronic archives of vital sign data. The concern with data archiving in standard formats opens many possibilities for further analysis of the collected data sets. The possibility of communicating via the HL7 standard makes the whole system easily interoperable with applications in related domains.