Catálogo de publicaciones - revistas

<jats:p>Social robots, conversational agents, voice assistants, and other embodied AI are increasingly a feature of everyday life. What connects these various types of intelligent agents is their ability to interact with people through voice. Voice is becoming an essential modality of embodiment, communication, and interaction between computer-based agents and end-users. This survey presents a meta-synthesis on agent voice in the design and experience of agents from a human-centered perspective: voice-based human–agent interaction (vHAI). Findings emphasize the social role of voice in HAI as well as circumscribe a relationship between agent voice and body, corresponding to human models of social psychology and cognition. Additionally, changes in perceptions of and reactions to agent voice over time reveals a generational shift coinciding with the commercial proliferation of mobile voice assistants. The main contributions of this work are a vHAI classification framework for voice across various agent forms, contexts, and user groups, a critical analysis grounded in key theories, and an identification of future directions for the oncoming wave of vocal machines.</jats:p>

<jats:p>Robustness is the degree to which a certain system or component can operate correctly in the presence of invalid inputs or stressful environmental conditions. With the increasing complexity and widespread use of computer systems, obtaining assurances regarding their robustness has become of vital importance. This survey discusses the state of the art on software robustness assessment, with emphasis on key aspects like types of systems being evaluated, assessment techniques used, the target of the techniques, the types of faults used, and how system behavior is classified. The survey concludes with the identification of gaps and open challenges related with robustness assessment.</jats:p>

<jats:p>In a blockchain-based system, the lack of centralized control requires active participation and cooperative behaviors of system entities to ensure system security and sustainability. However, dynamic environments and unpredictable entity behaviors challenge the performances of such systems in practice. Therefore, designing a feasible incentive mechanism to regulate entity behaviors becomes essential to improve blockchain system performance. The prosperous characteristics of blockchain can also contribute to an effective incentive mechanism. Unfortunately, current literature still lacks a thorough survey on incentive mechanisms related to the blockchain to understand how incentive mechanisms and blockchain make each other better. To this end, we propose evaluation requirements in terms of the properties and costs of incentive mechanisms. On one hand, we provide a taxonomy of the incentive mechanisms of blockchain systems according to blockchain versions, incentive forms and incentive goals. On the other hand, we categorize blockchain-based incentive mechanisms according to application scenarios and incentive goals. During the review, we discuss the advantages and disadvantages of state-of-art incentive mechanisms based on the proposed evaluation requirements. Through careful review, we present how incentive mechanisms and blockchain benefit with each other, discover a number of unresolved issues, and point out corresponding potential directions for future research.</jats:p>

<jats:p>Named Data Networking (NDN) is a prominent realization of the vision of Information-Centric Networking. The NDN architecture adopts name-based routing and location-independent data retrieval. Among other important features, NDN integrates security mechanisms and focuses on protecting the content rather than the communications channels. Along with a new architecture come new threats and NDN is no exception. NDN is a potential target for new network attacks such as Interest Flooding Attacks (IFAs). Attackers take advantage of IFA to launch (D)DoS attacks in NDN. Many IFA detection and mitigation solutions have been proposed in the literature. However, there is no comprehensive review study of these solutions that has been proposed so far. Therefore, in this paper, we propose a survey of the various IFAs with a detailed comparative study of all the relevant proposed solutions as counter-measures against IFAs. We also review the requirements for a complete and efficient IFA solution and pinpoint the various issues encountered by IFA detection and mitigation mechanisms through a series of attack scenarios. Finally, in this survey, we offer an analysis of the open issues and future research directions regarding IFAs.</jats:p>

<jats:p> Continuous integration enables the development of microservices-based applications using container virtualization technology. Container orchestration systems such as Kubernetes, which has become the <jats:italic>de facto</jats:italic> standard, simplify the deployment of container-based applications. However, developing efficient and well-defined orchestration systems is a challenge. </jats:p> <jats:p>This paper focuses specifically on the scheduler, a key orchestrator task that assigns physical resources to containers. Scheduling approaches are designed based on different Quality of Service (QoS) parameters to provide limited response time, efficient energy consumption, better resource utilization, and other things. This paper aims to establish insight knowledge into Kubernetes scheduling, find the main gaps, and thus guide future research in the area. Therefore, we conduct a study of empirical research on Kubernetes scheduling techniques and present a new taxonomy for Kubernetes scheduling. The challenges, future direction, and research opportunities are also discussed.</jats:p>

<jats:p>This study presents a literature systematic review of automatic performance assessment in three-dimensional interactive medical and dental simulators with haptic feedback, resulting in 63 included articles. The main contributions regard analysis and discussion of investigated procedures, extracted metrics, experiment types, and assessment techniques. Studies have mostly focused on assessing performance by analyzing metrics using statistical techniques, while machine learning algorithms appear to be underexplored. Metrics related to time were observed in 84% of the studies, and aspects related to force, error and precision were investigated to a lesser degree. Difficulties reported in the articles are discussed, and research opportunities are presented.</jats:p>

<jats:p>The COVID-19 pandemic has resulted in more than 440 million confirmed cases globally and almost 6 million reported deaths as of March 2022. Consequently, the world experienced grave repercussions to citizens’ lives, health, wellness, and the economy. In responding to such a disastrous global event, countermeasures are often implemented to slow down and limit the virus’s rapid spread. Meanwhile, disaster recovery, mitigation, and preparation measures have been taken to manage the impacts and losses of the ongoing and future pandemics. Data-driven techniques have been successfully applied to many domains and critical applications in recent years. Due to the highly interdisciplinary nature of pandemic management, researchers have proposed and developed data-driven techniques across various domains. However, a systematic and comprehensive survey of data-driven techniques for pandemic management is still missing. In this paper, we review existing data analysis and visualization techniques and their applications for COVID-19 and future pandemic management with respect to four phases (namely Response, Recovery, Mitigation, and Preparation) in disaster management. Data sources utilized in these studies and specific data acquisition and integration techniques for COVID-19 are also summarized. Furthermore, open issues and future directions for data-driven pandemic management are discussed.</jats:p>

<jats:p>The design and evaluation of accessibility technology is a core component of the Computer Science landscape, aiming to ensure that digital innovations are accessible to all. One of the most prominent and long-lasting areas of accessibility research focuses on motor impairments, deficiencies that affect the ability to move, manipulate objects, and interact with the physical world. In this survey paper, we present an extensive overview of the last two decades of research into accessibility for people with motor impairments. Following a structured selection process, we analysed the study details as reported in 177 relevant papers. Based on this analysis, we critically assess user representation, measurement instruments, and existing barriers that exist in accessibility research. Finally, we discuss future directions for accessibility research within the Computer Science domain.</jats:p>

<jats:p>ICT platforms for news production, distribution, and consumption must exploit the ever-growing availability of digital data. These data originate from different sources and in different formats; they arrive at different velocities and in different volumes. Semantic knowledge graphs (KGs) is an established technique for integrating such heterogeneous information. It is therefore well-aligned with the needs of news producers and distributors, and it is likely to become increasingly important for the news industry. This paper reviews the research on using semantic knowledge graphs for production, distribution, and consumption of news. The purpose is to present an overview of the field; to investigate what it means; and to suggest opportunities and needs for further research and development.</jats:p>

<jats:p>Constructing energy-efficient database systems to reduce economic costs and environmental impact has been studied for ten years. With the emergence of the big data age, along with the data-centric and -intensive computing trend, the great amount of energy consumed by database systems has become a major concern in a society that pursues green information technology. However, to the best of our knowledge, despite the importance of this matter in Green IT, there have been few comprehensive or systematic studies conducted in this field. Therefore, the objective of this article is to present a literature survey with breadth and depth on existing energy management techniques for database systems. The existing literature are organized hierarchically with two major branches focusing separately on energy consumption models and energy-saving techniques. Under each branch, we first introduce some basic knowledge, and then we classify, discuss, and compare existing research according to their core ideas, basic approaches, and main characteristics. Finally, based on these observations through our study, we identify multiple open issues and challenges, and provide insights for future research. We hope that our outcome of this work will help researchers to develop more energy-efficient database systems.</jats:p>