Catálogo de publicaciones - revistas

<jats:p>Wireless indoor positioning has been extensively studied for the past 2 decades and continuously attracted growing research efforts in mobile computing context. As the integration of multiple inertial sensors (e.g., accelerometer, gyroscope, and magnetometer) to nowadays smartphones in recent years, human-centric mobility sensing is emerging and coming into vogue. Mobility information, as a new dimension in addition to wireless signals, can benefit localization in a number of ways, since location and mobility are by nature related in the physical world. In this article, we survey this new trend of mobility enhancing smartphone-based indoor localization. Specifically, we first study how to measure human mobility: what types of sensors we can use and what types of mobility information we can acquire. Next, we discuss how mobility assists localization with respect to enhancing location accuracy, decreasing deployment cost, and enriching location context. Moreover, considering the quality and cost of smartphone built-in sensors, handling measurement errors is essential and accordingly investigated. Combining existing work and our own working experiences, we emphasize the principles and conduct comparative study of the mainstream technologies. Finally, we conclude this survey by addressing future research directions and opportunities in this new and largely open area.</jats:p>

<jats:p>The expansion of the Internet over the last decade and the proliferation of online social communities, such as Facebook, Google+, and Twitter, as well as multimedia sharing sites, such as YouTube, Flickr, and Picasa, has led to a vast increase of available information to the user. In the case of multimedia data, such as images and videos, fast querying and processing of the available information requires the annotation of the multimedia data with semantic descriptors, that is, labels. However, only a small proportion of the available data are labeled. The rest should undergo an annotation-labeling process. The necessity for the creation of automatic annotation algorithms gave birth to label propagation and semi-supervised learning. In this study, basic concepts in graph-based label propagation methods are discussed. Methods for proper graph construction based on the structure of the available data and label inference methods for spreading label information from a few labeled data to a larger set of unlabeled data are reviewed. Applications of label propagation algorithms in digital media, as well as evaluation metrics for measuring their performance, are presented.</jats:p>

<jats:p>3D registration or matching is a crucial step in 3D model reconstruction. Registration applications span along a variety of research fields, including computational geometry, computer vision, and geometric modeling. This variety of applications produces many diverse approaches to the problem but at the same time yields divergent notations and a lack of standardized algorithms and guidelines to classify existing methods. In this article, we review the state of the art of the 3D rigid registration topic (focused on Coarse Matching) and offer qualitative comparison between the most relevant approaches. Furthermore, we propose a pipeline to classify the existing methods and define a standard formal notation, offering a global point of view of the literature.</jats:p> <jats:p>Our discussion, based on the results presented in the analyzed papers, shows how, although certain aspects of the registration process still need to be tested further in real application situations, the registration pipeline as a whole has progressed steadily. As a result of this progress in all registration aspects, it is now possible to put together algorithms that are able to tackle new and challenging problems with unprecedented data sizes and meeting strict precision criteria.</jats:p>

<jats:p> Affect detection is an important pattern recognition problem that has inspired researchers from several areas. The field is in need of a systematic review due to the recent influx of Multimodal (MM) affect detection systems that differ in several respects and sometimes yield incompatible results. This article provides such a survey via a quantitative review and meta-analysis of 90 peer-reviewed MM systems. The review indicated that the state of the art mainly consists of person-dependent models (62.2% of systems) that fuse audio and visual (55.6%) information to detect acted (52.2%) expressions of basic emotions and simple dimensions of arousal and valence (64.5%) with feature- (38.9%) and decision-level (35.6%) fusion techniques. However, there were also person-independent systems that considered additional modalities to detect nonbasic emotions and complex dimensions using model-level fusion techniques. The meta-analysis revealed that MM systems were consistently (85% of systems) more accurate than their best unimodal counterparts, with an average improvement of 9.83% (median of 6.60%). However, improvements were three times lower when systems were trained on natural (4.59%) versus acted data (12.7%). Importantly, MM accuracy could be accurately predicted (cross-validated <jats:italic>R</jats:italic> <jats:sup>2</jats:sup> of 0.803) from unimodal accuracies and two system-level factors. Theoretical and applied implications and recommendations are discussed. </jats:p>

<jats:p>This article explains the full reconfigurable multidecree Paxos (or multi-Paxos) protocol. Paxos is by no means a simple protocol, even though it is based on relatively simple invariants. We provide pseudocode and explain it guided by invariants. We initially avoid optimizations that complicate comprehension. Next we discuss liveness, list various optimizations that make the protocol practical, and present variants of the protocol.</jats:p>

<jats:p>Multilabel learning has become a relevant learning paradigm in the past years due to the increasing number of fields where it can be applied and also to the emerging number of techniques that are being developed. This article presents an up-to-date tutorial about multilabel learning that introduces the paradigm and describes the main contributions developed. Evaluation measures, fields of application, trending topics, and resources are also presented.</jats:p>

<jats:p>A MapReduce scheduling algorithm plays a critical role in managing large clusters of hardware nodes and meeting multiple quality requirements by controlling the order and distribution of users, jobs, and tasks execution. A comprehensive and structured survey of the scheduling algorithms proposed so far is presented here using a novel multidimensional classification framework. These dimensions are (i) meeting quality requirements, (ii) scheduling entities, and (iii) adapting to dynamic environments; each dimension has its own taxonomy. An empirical evaluation framework for these algorithms is recommended. This survey identifies various open issues and directions for future research.</jats:p>

<jats:p>Large interactive displays are increasingly placed in public (or semipublic) locations, including museums, shops, various city settings, and offices. This article discusses the evolution of such displays by looking at their use and analyzing how they are changing the concept of human-computer interaction through new modalities. By surveying the literature on systems using these displays, relevant features were identified and used as classification dimensions. The analysis provided may inform the design and development of future installations. A discussion on research challenges concludes the article.</jats:p>

<jats:p>One of the major problems in wireless multihop networks is the scheduling of transmissions in a fair and efficient manner. Time Division Multiple Access (TDMA) seems to be one of the dominant solutions to achieve this goal since it is a simple scheme and can prolong the devices’ lifetime by allowing them to transmit only a portion of the time during conversation. For that reason, several TDMA scheduling algorithms may be found in the literature. The scope of this article is to classify the existing TDMA scheduling algorithms based on several factors, such as the entity that is scheduled, the network topology information that is needed to produce or maintain the schedule, and the entity or entities that perform the computation that produces and maintains the schedules, and to discuss the advantages and disadvantages of each category.</jats:p>

<jats:p>3D meshes are commonly used to represent virtual surface and volumes. However, their raw data representations take a large amount of space. Hence, 3D mesh compression has been an active research topic since the mid 1990s. In 2005, two very good review articles describing the pioneering works were published. Yet, new technologies have emerged since then. In this article, we summarize the early works and put the focus on these novel approaches. We classify and describe the algorithms, evaluate their performance, and provide synthetic comparisons. We also outline the emerging trends for future research.</jats:p>