Catálogo de publicaciones - revistas

<jats:p>The variety of data is one of the most challenging issues for the research and practice in data management systems. The data are naturally organized in different formats and models, including structured data, semi-structured data, and unstructured data. In this survey, we introduce the area of multi-model DBMSs that build a single database platform to manage multi-model data. Even though multi-model databases are a newly emerging area, in recent years, we have witnessed many database systems to embrace this category. We provide a general classification and multi-dimensional comparisons for the most popular multi-model databases. This comprehensive introduction on existing approaches and open problems, from the technique and application perspective, make this survey useful for motivating new multi-model database approaches, as well as serving as a technical reference for developing multi-model database applications.</jats:p>

<jats:p>Scripts are widely used to design and run scientific experiments. Scripting languages are easy to learn and use, and they allow complex tasks to be specified and executed in fewer steps than with traditional programming languages. However, they also have important limitations for reproducibility and data management. As experiments are iteratively refined, it is challenging to reason about each experiment run (or trial), to keep track of the association between trials and experiment instances as well as the differences across trials, and to connect results to specific input data and parameters. Approaches have been proposed that address these limitations by collecting, managing, and analyzing the provenance of scripts. In this article, we survey the state of the art in provenance for scripts. We have identified the approaches by following an exhaustive protocol of forward and backward literature snowballing. Based on a detailed study, we propose a taxonomy and classify the approaches using this taxonomy.</jats:p>

<jats:p>This survey provides an overview of the scientific literature on timing verification techniques for multi-core real-time systems. It reviews the key results in the field from its origins around 2006 to the latest research published up to the end of 2018. The survey highlights the key issues involved in providing guarantees of timing correctness for multi-core systems. A detailed review is provided covering four main categories: full integration, temporal isolation, integrating interference effects into schedulability analysis, and mapping and allocation. The survey concludes with a discussion of the advantages and disadvantages of these different approaches, identifying open issues, key challenges, and possible directions for future research.</jats:p>

<jats:p>Model comparison has been widely used to support many tasks in model-driven software development. For this reason, many techniques of comparing them have been proposed in the last few decades. However, academia and industry have overlooked a classification of currently available approaches to the comparison of design models. Hence, a thorough understanding of state-of-the-art techniques remains limited and inconclusive. This article, therefore, focuses on providing a classification and a thematic analysis of studies on the comparison of software design models. We carried out a systematic mapping study following well-established guidelines to answer nine research questions. In total, 56 primary studies (out of 4,132) were selected from 10 widely recognized electronic databases after a careful filtering process. The main results are that a majority of the primary studies (1) provide coarse-grained techniques of the comparison of general-purpose diagrams, (2) adopt graphs as principal data structure and compare software design models considering structural properties only, (3) pinpoint commonalities and differences between software design models rather than assess their similarity, and (4) propose new techniques while neglecting the production of empirical knowledge from experimental studies. Finally, this article highlights some challenges and directions that can be explored in upcoming studies.</jats:p>

<jats:p>Register allocation (mapping variables to processor registers or memory) and instruction scheduling (reordering instructions to increase instruction-level parallelism) are essential tasks for generating efficient assembly code in a compiler. In the past three decades, combinatorial optimization has emerged as an alternative to traditional, heuristic algorithms for these two tasks. Combinatorial optimization approaches can deliver optimal solutions according to a model, can precisely capture trade-offs between conflicting decisions, and are more flexible at the expense of increased compilation time.</jats:p> <jats:p>This article provides an exhaustive literature review and a classification of combinatorial optimization approaches to register allocation and instruction scheduling, with a focus on the techniques that are most applied in this context: integer programming, constraint programming, partitioned Boolean quadratic programming, and enumeration. Researchers in compilers and combinatorial optimization can benefit from identifying developments, trends, and challenges in the area; compiler practitioners may discern opportunities and grasp the potential benefit of applying combinatorial optimization.</jats:p>

<jats:p>The skin offers exciting possibilities for human--computer interaction by enabling new types of input and feedback. We survey 42 research papers on interfaces that allow users to give input on their skin. Skin-based interfaces have developed rapidly over the past 8 years but most work consists of individual prototypes, with limited overview of possibilities or identification of research directions. The purpose of this article is to synthesize what skin input is, which technologies can sense input on the skin, and how to give feedback to the user. We discuss challenges for research in each of these areas.</jats:p>

<jats:p>Cyberattacks on both databases and critical infrastructure have threatened public and private sectors. Ubiquitous tracking and wearable computing have infringed upon privacy. Advocates and engineers have recently proposed using defensive deception as a means to leverage the information asymmetry typically enjoyed by attackers as a tool for defenders. The term deception, however, has been employed broadly and with a variety of meanings. In this article, we survey 24 articles from 2008 to 2018 that use game theory to model defensive deception for cybersecurity and privacy. Then, we propose a taxonomy that defines six types of deception: perturbation, moving target defense, obfuscation, mixing, honey-x, and attacker engagement. These types are delineated by their information structures, agents, actions, and duration: precisely concepts captured by game theory. Our aims are to rigorously define types of defensive deception, to capture a snapshot of the state of the literature, to provide a menu of models that can be used for applied research, and to identify promising areas for future work. Our taxonomy provides a systematic foundation for understanding different types of defensive deception commonly encountered in cybersecurity and privacy.</jats:p>

<jats:p>Orthogonal moments provide an efficient mathematical framework for computer vision, image analysis, and pattern recognition. They are derived from the polynomials that are relatively perpendicular to each other. Orthogonal moments are more efficient than non-orthogonal moments for image representation with minimum attribute redundancy, robustness to noise, invariance to rotation, translation, and scaling. Orthogonal moments can be both continuous and discrete. Prominent continuous moments are Zernike, Pseudo-Zernike, Legendre, and Gaussian-Hermite. This article provides a comprehensive and comparative review for continuous orthogonal moments along with their applications.</jats:p>

<jats:p>Adaptive Authentication allows a system to dynamically select the best mechanism(s) for authenticating a user depending on contextual factors, such as location, proximity to devices, and other attributes. Though this technology has the potential to change the current password-dominated authentication landscape, research to date has not led to practical solutions that transcend to our daily lives. Motivated to find out how to improve adaptive authentication design, we provide a structured survey of the existing literature to date and analyze it to identify and discuss current research challenges and future directions.</jats:p>