Catálogo de publicaciones - revistas

<jats:p>The Semantic Web emerged with the vision of eased integration of heterogeneous, distributed data on the Web. The approach fundamentally relies on the linkage between and reuse of previously published vocabularies to facilitate semantic interoperability. In recent years, the Semantic Web has been perceived as a potential enabling technology to overcome interoperability issues in the Internet of Things (IoT), especially for service discovery and composition. Despite the importance of making vocabulary terms discoverable and selecting the most suitable ones in forthcoming IoT applications, no state-of-the-art survey of tools achieving such recommendation tasks exists to date. This survey covers this gap by specifying an extensive evaluation framework and assessing linked vocabulary recommendation tools. Furthermore, we discuss challenges and opportunities of vocabulary recommendation and related tools in the context of emerging IoT ecosystems. Overall, 40 recommendation tools for linked vocabularies were evaluated, both empirically and experimentally. Some of the key findings include that (i) many tools neglect to thoroughly address both the curation of a vocabulary collection and effective selection mechanisms, (ii) modern information retrieval techniques are underrepresented, and (iii) the reviewed tools that emerged from Semantic Web use cases are not yet sufficiently extended to fit today’s IoT projects.</jats:p>

<jats:p>Numerous challenges present themselves when scaling traditional on-chip electrical networks to large manycore processors. Some of these challenges include high latency, limitations on bandwidth, and power consumption. Researchers have therefore been looking for alternatives. As a result, on-chip nanophotonics has emerged as a strong substitute for traditional electrical NoCs.</jats:p> <jats:p>As of 2017, on-chip optical networks have moved out of textbooks and found commercial applicability in short-haul networks such as links between servers on the same rack or between two components on the motherboard. It is widely acknowledged that in the near future, optical technologies will move beyond research prototypes and find their way into the chip. Optical networks already feature in the roadmaps of major processor manufacturers and most on-chip optical devices are beginning to show signs of maturity.</jats:p> <jats:p>This article is designed to provide a survey of on-chip optical technologies covering the basic physics underlying the operation of optical technologies, optical devices, popular architectures, power reduction techniques, and applications. The aim of this survey article is to start from the fundamental concepts and move on to the latest in the field of on-chip optical interconnects.</jats:p>

<jats:p>Due to decelerating gains in single-core CPU performance, computationally expensive simulations are increasingly executed on highly parallel hardware platforms. Agent-based simulations, where simulated entities act with a certain degree of autonomy, frequently provide ample opportunities for parallelisation. Thus, a vast variety of approaches proposed in the literature demonstrated considerable performance gains using hardware platforms such as many-core CPUs and GPUs, merged CPU-GPU chips as well as Field Programmable Gate Arrays. Typically, a combination of techniques is required to achieve high performance for a given simulation model, putting substantial burden on modellers. To the best of our knowledge, no systematic overview of techniques for agent-based simulations on hardware accelerators has been given in the literature. To close this gap, we provide an overview and categorisation of the literature according to the applied techniques. Since, at the current state of research, challenges such as the partitioning of a model for execution on heterogeneous hardware are still addressed in a largely manual process, we sketch directions for future research towards automating the hardware mapping and execution. This survey targets modellers seeking an overview of suitable hardware platforms and execution techniques for a specific simulation model, as well as methodology researchers interested in potential research gaps requiring further exploration.</jats:p>

<jats:p>The synthesis of facial expressions has applicationsin areas such as interactive games, biometrics systems, and training of people with disorders, among others. Although this is an area relatively well explored in the literature, there are no recent studies proposing to systematize an overview of research in the area. This systematic review analyzes the approaches to the synthesis of facial expressions in photographs, as well as important aspects of the synthesis process, such as preprocessing techniques, databases, and evaluation metrics. Forty-eight studies from three different scientific databases were analyzed. From these studies, we established an overview of the process, including all the stages used to synthesize expressions in facial images. We also analyze important aspects involved in these stages such as methods and techniques of each stage, databases, and evaluation metrics. We observed that machine learning approaches are the most widely used to synthesize expressions. Landmark identification, deformation, mapping, fusion, and training are common tasks considered in the approaches. We also found that few studies used metrics to evaluate the results, and most studies used public databases. Although the studies analyzed generated consistent and realistic results while preserving the identity of the subject, there are still research themes to be exploited.</jats:p>

<jats:p> People who design, use, and are affected by autonomous artificially intelligent agents want to be able to <jats:italic>trust</jats:italic> such agents—that is, to know that these agents will perform correctly, to understand the reasoning behind their actions, and to know how to use them appropriately. Many techniques have been devised to assess and influence human trust in artificially intelligent agents. However, these approaches are typically ad hoc and have not been formally related to each other or to formal trust models. This article presents a survey of <jats:italic>algorithmic assurances</jats:italic> , i.e., programmed components of agent operation that are expressly designed to calibrate user trust in artificially intelligent agents. Algorithmic assurances are first formally defined and classified from the perspective of formally modeled human-artificially intelligent agent trust relationships. Building on these definitions, a synthesis of research across communities such as machine learning, human-computer interaction, robotics, e-commerce, and others reveals that assurance algorithms naturally fall along a spectrum in terms of their impact on an agent’s core functionality, with seven notable classes ranging from integral assurances (which impact an agent’s core functionality) to supplemental assurances (which have no direct effect on agent performance). Common approaches within each of these classes are identified and discussed; benefits and drawbacks of different approaches are also investigated. </jats:p>

<jats:p>The immense amount of data created by digitalization requires parallel computing for machine-learning methods. While there are many parallel implementations for support vector machines (SVMs), there is no clear suggestion for every application scenario. Many factor—including optimization algorithm, problem size and dimension, kernel function, parallel programming stack, and hardware architecture—impact the efficiency of implementations. It is up to the user to balance trade-offs, particularly between computation time and classification accuracy. In this survey, we review the state-of-the-art implementations of SVMs, their pros and cons, and suggest possible avenues for future research.</jats:p>

<jats:p>The advent of quantum computing threatens to break many classical cryptographic schemes, leading to innovations in public key cryptography that focus on post-quantum cryptography primitives and protocols resistant to quantum computing threats. Lattice-based cryptography is a promising post-quantum cryptography family, both in terms of foundational properties as well as in its application to both traditional and emerging security problems such as encryption, digital signature, key exchange, and homomorphic encryption. While such techniques provide guarantees, in theory, their realization on contemporary computing platforms requires careful design choices and tradeoffs to manage both the diversity of computing platforms (e.g., high-performance to resource constrained), as well as the agility for deployment in the face of emerging and changing standards. In this work, we survey trends in lattice-based cryptographic schemes, some recent fundamental proposals for the use of lattices in computer security, challenges for their implementation in software and hardware, and emerging needs for their adoption. The survey means to be informative about the math to allow the reader to focus on the mechanics of the computation ultimately needed for mapping schemes on existing hardware or synthesizing part or all of a scheme on special-purpose har dware.</jats:p>

<jats:p>Graph Drawing Beyond Planarity is a rapidly growing research area that classifies and studies geometric representations of nonplanar graphs in terms of forbidden crossing configurations. The aim of this survey is to describe the main research directions in this area, the most prominent known results, and some of the most challenging open problems.</jats:p>

<jats:p>Mobile Cloud Computing (MCC) has been extensively explored to be applied as a vital tool to enhance the capabilities of mobile devices, increasing computing power, expanding storage capacity, and prolonging battery life. Offloading works as the fundamental feature that enables MCC to relieve task load and extend data storage through an accessible cloud resource pool. Several initiatives have drawn attention to delivering MCC-supported energy-oriented offloading as a method to cope with a lately steep increase in the number of rich mobile applications and the enduring limitations of battery technologies. However, MCC offloading relieves only the burden of energy consumption of mobile devices; performance concerns about Cloud resources, in most cases, are not considered when dynamically allocating them for dealing with mobile tasks. The application context of MCC, encompassing urban computing, aggravates the situation with very large-scale scenarios, posing as a challenge for achieving greener solutions in the scope of Cloud resources. Thus, this article gathers and analyzes recent energy-aware offloading protocols and architectures, as well as scheduling and balancing algorithms employed toward Cloud green computing. This survey provides a comparison among system architectures by identifying their most notable advantages and disadvantages. The existing enabling frameworks are categorized and compared based on the stage of the task offloading process and resource management types, describing current open challenges and future research directions.</jats:p>

<jats:p>Traffic load in any 802.11 infrastructure mode network is typically distributed unevenly between access points (APs), creating hotspots. This is due to the inherent nature of wireless area networks (WLANs), where stations are free to associate to any known AP they desire, and the lack of control by the APs themselves. This imbalance creates a condition where affected APs in the network suffer traffic congestion while others are underutilized, leading to stations experiencing lower throughput, longer latency, and operating below the network potential capacity. To alleviate this problem, some form of load balancing is required to redistribute the work load among other available APs in the wireless network. This article presents a survey of the various works done in performing load balancing in an infrastructure mode wireless network and will cover the common methods including admission control, association management, cell breathing, and association control. Updates to the IEEE standards are also presented that support load-balancing efforts. Finally, software-defined networks are investigated to determine the extent of control integration to support managing and load-balancing WLANs. Trends in load-balancing research are also uncovered that indicate how the introduction of new wireless standards influences the amount of research.</jats:p>