Catálogo de publicaciones - revistas

<jats:p> The analysis of biological sequencing data has been one of the biggest applications of string algorithms. The approaches used in many such applications are based on the analysis of <jats:italic>k</jats:italic> -mers, which are short fixed-length strings present in a dataset. While these approaches are rather diverse, storing and querying a <jats:italic>k</jats:italic> -mer set has emerged as a shared underlying component. A set of <jats:italic>k</jats:italic> -mers has unique features and applications that, over the past 10 years, have resulted in many specialized approaches for its representation. In this survey, we give a unified presentation and comparison of the data structures that have been proposed to store and query a <jats:italic>k</jats:italic> -mer set. We hope this survey will serve as a resource for researchers in the field as well as make the area more accessible to researchers outside the field. </jats:p>

<jats:p>Computing technologies are currently based on the binary logic/number system, which is dependent on the simple on and off switching mechanism of the prevailing transistors. With the exponential increase of data processing and storage needs, there is a strong push to move to a higher radix logic/number system that can eradicate or lessen many limitations of the binary system. Anticipated saturation of Moore’s law and the necessity to increase information density and processing speed in the future micro and nanoelectronic circuits and systems provide a strong background and motivation for the beyond-binary logic system. In this review article, different technologies for Multiple-valued-Logic (MVL) devices and the associated prospects and constraints are discussed. The feasibility of the MVL system in real-world applications rests on resolving two major challenges: (i) development of an efficient mathematical approach to implement the MVL logic using available technologies, and (ii) availability of effective synthesis techniques. This review of different technologies for the MVL system is intended to perform a comprehensive investigation of various MVL technologies and a comparative analysis of the feasible approaches to implement MVL devices, especially ternary logic.</jats:p>

<jats:p> <jats:italic>Nature-inspired computing</jats:italic> is a type of human-designed computing motivated by nature, which is based on the employ of paradigms, mechanisms, and principles underlying natural systems. In this article, a versatile and vigorous bio-inspired branch of natural computing, named <jats:italic>membrane computing</jats:italic> is discussed. This computing paradigm is aroused by the internal membrane function and the structure of biological cells. We first introduce some basic concepts and formalisms of membrane computing, and then some basic types or variants of <jats:italic>P systems</jats:italic> (also named <jats:italic>membrane systems</jats:italic> ) are presented. The state-of-the-art computability theory and a pioneering computational complexity theory are presented with P system frameworks and numerous solutions to hard computational problems (especially <jats:bold>NP</jats:bold> -complete problems) via P systems with membrane division are reported. Finally, a number of applications and open problems of P systems are briefly described. </jats:p>

<jats:p>This survey covers the basic principles and related works addressing the time-triggered scheduling of periodic tasks with deadlines. The wide range of applications and the increasing complexity of modern real-time systems result in the continually growing interest in this topic. However, the articles in this field appear without systematic notation. To address it, we extend the three-field Graham notation to cover periodic scheduling. Moreover, we formally define three example periodic scheduling problems (PSPs) and provide straightforward implementations of these examples in the Satisfiability Modulo Theories formalism with source codes. Then, we present a summary of the complexity results containing existing polynomially solvable PSPs. We also provide an overview of simple state-of-the-art methods and tricks to solve the PSPs efficiently in terms of time. Next, we survey the existing works on PSP according to the resource environment: scheduling on a single resource, on parallel identical resources, and on dedicated resources. In the survey, we indicate which works propose solution methods for more general PSPs. Finally, we present related problems that are not periodic by nature to provide inspiration for the PSP solution.</jats:p>

<jats:p>In the near future, our streets will be populated by myriads of autonomous self-driving vehicles to serve our diverse mobility needs. This will raise the need to coordinate their movements in order to properly handle both access to shared resources (e.g., intersections and parking slots) and the execution of mobility tasks (e.g., platooning and ramp merging). The aim of this article is to provide a global view of the coordination issues and the related solutions in the field of autonomous vehicles. To this end, we firstly introduce the general problems associated with coordination of autonomous vehicles by identifying and framing the key classes of coordination problems. Then, we overview the different approaches that can be adopted to deal with such problems by classifying them in terms of the degree of autonomy in decision making that is left to autonomous vehicles during the coordination process. Finally, we overview some further research challenges to address before autonomous coordinated vehicles can safely hit our streets.</jats:p>

<jats:p>As connectivity between and within vehicles increases, so does concern about safety and security. Various automotive serial protocols are used inside vehicles such as Controller Area Network (CAN), Local Interconnect Network (LIN), and FlexRay. CAN Bus is the most used in-vehicle network protocol to support exchange of vehicle parameters between Electronic Control Units (ECUs). This protocol lacks security mechanisms by design and is therefore vulnerable to various attacks. Furthermore, connectivity of vehicles has made the CAN Bus vulnerable not only from within the vehicle but also from outside. With the rise of connected cars, more entry points and interfaces have been introduced on board vehicles, thereby also leading to a wider potential attack surface. Existing security mechanisms focus on the use of encryption, authentication, and vehicle Intrusion Detection Systems (IDS), which operate under various constraints such as low bandwidth, small frame size (e.g., in the CAN protocol), limited availability of computational resources, and real-time sensitivity. We survey and classify current cryptographic and IDS approaches and compare these approaches based on criteria such as real-time constraints, types of hardware used, changes in CAN Bus behaviour, types of attack mitigation, and software/ hardware used to validate these approaches. We conclude with mitigation strategies limitations and research challenges for the future.</jats:p>

<jats:p>Byzantine fault-tolerant (BFT) state-machine replication makes it possible to design systems that are resilient against arbitrary faults, a requirement considered crucial for an increasing number of use cases such as permissioned blockchains, firewalls, and SCADA systems. Unfortunately, the strong fault-tolerance guarantees provided by BFT replication protocols come at the cost of a high complexity, which is why it is inherently difficult to correctly implement BFT systems in practice. This is all the more true with regard to the plethora of solutions and ideas that have been developed in recent years to improve performance, availability, or resource efficiency. This survey aims at facilitating the task of building BFT systems by presenting an overview of state-of-the-art techniques and analyzing their practical implications, for example, with respect to applicability and composability. In particular, this includes problems that arise in the context of concrete implementations, but which are often times passed over in literature. Starting with an in-depth discussion of the most important architectural building blocks of a BFT system (i.e., clients, agreement protocol, execution stage), the survey then focuses on selected approaches and mechanisms addressing specific tasks such as checkpointing and recovery.</jats:p>

<jats:p>Decentralised learning is attracting more and more interest because it embodies the principles of data minimisation and focused data collection, while favouring the transparency of purpose specification (i.e., the objective for which a model is built). Cloud-centric-only processing and deep learning are no longer strict necessities to train high-fidelity models; edge devices can actively participate in the decentralised learning process by exchanging meta-level information in place of raw data, thus paving the way for better privacy guarantees. In addition, these new possibilities can relieve the network backbone from unnecessary data transfer and allow it to meet strict low-latency requirements by leveraging on-device model inference. This survey provides a detailed and up-to-date overview of the most recent contributions available in the state-of-the-art decentralised learning literature. In particular, it originally provides the reader audience with a clear presentation of the peculiarities of federated settings, with a novel taxonomy of decentralised learning approaches, and with a detailed description of the most relevant and specific system-level contributions of the surveyed solutions for privacy, communication efficiency, non-IIDness, device heterogeneity, and poisoning defense.</jats:p>

<jats:p>Experts from different domains have resorted to machine learning techniques to produce explainable models that support decision-making. Among existing techniques, decision trees have been useful in many application domains for classification. Decision trees can make decisions in a language that is closer to that of the experts. Many researchers have attempted to create better decision tree models by improving the components of the induction algorithm. One of the main components that have been studied and improved is the evaluation measure for candidate splits.</jats:p> <jats:p>In this article, we introduce a tutorial that explains decision tree induction. Then, we present an experimental framework to assess the performance of 21 evaluation measures that produce different C4.5 variants considering 110 databases, two performance measures, and 10× 10-fold cross-validation. Furthermore, we compare and rank the evaluation measures by using a Bayesian statistical analysis. From our experimental results, we present the first two performance rankings in the literature of C4.5 variants. Moreover, we organize the evaluation measures into two groups according to their performance. Finally, we introduce meta-models that automatically determine the group of evaluation measures to produce a C4.5 variant for a new database and some further opportunities for decision tree models.</jats:p>

<jats:p>With the advent of Web 2.0, there exist many online platforms that result in massive textual-data production. With ever-increasing textual data at hand, it is of immense importance to extract information nuggets from this data. One approach towards effective harnessing of this unstructured textual data could be its transformation into structured text. Hence, this study aims to present an overview of approaches that can be applied to extract key insights from textual data in a structured way. For this, Named Entity Recognition and Relation Extraction are being majorly addressed in this review study. The former deals with identification of named entities, and the latter deals with problem of extracting relation between set of entities. This study covers early approaches as well as the developments made up till now using machine learning models. Survey findings conclude that deep-learning-based hybrid and joint models are currently governing the state-of-the-art. It is also observed that annotated benchmark datasets for various textual-data generators such as Twitter and other social forums are not available. This scarcity of dataset has resulted into relatively less progress in these domains. Additionally, the majority of the state-of-the-art techniques are offline and computationally expensive. Last, with increasing focus on deep-learning frameworks, there is need to understand and explain the under-going processes in deep architectures.</jats:p>