Catálogo de publicaciones - revistas

<jats:p>Craniofacial superimposition is a forensic process in which a photograph of a missing person is compared with a skull found to determine its identity. After one century of development, craniofacial superimposition has become an interdisciplinary research field where computer sciences have acquired a key role as a complement of forensic sciences. Moreover, the availability of new digital equipment (such as computers and 3D scanners) has resulted in a significant advance in the applicability of this forensic identification technique. The purpose of this contribution is twofold. On the one hand, we aim to clearly define the different stages involved in the computer-aided craniofacial superimposition process. Besides, we aim to clarify the role played by computers in the methods considered.</jats:p> <jats:p>In order to accomplish these objectives, an up-to-date review of the recent works is presented along with a discussion of advantages and drawbacks of the existing approaches, with an emphasis on the automatic ones. Future case studies will be easily categorized by identifying which stage is tackled and which kind of computer-aided approach is chosen to face the identification problem. Remaining challenges are indicated and some directions for future research are given.</jats:p>

<jats:p>The architecture of a software-intensive system can be defined as the set of relevant design decisions that affect the qualities of the overall system functionality; therefore, architectural decisions are eventually crucial to the success of a software project. The software engineering literature describes several techniques to choose among architectural alternatives, but it gives no clear guidance on which technique is more suitable than another, and in which circumstances. As such, there is no systematic way for software engineers to choose among decision-making techniques for resolving tradeoffs in architecture design. In this article, we provide a comparison of existing decision-making techniques, aimed to guide architects in their selection. The results show that there is no “best” decision-making technique; however, some techniques are more susceptible to specific difficulties. Hence architects should choose a decision-making technique based on the difficulties that they wish to avoid. This article represents a first attempt to reason on meta-decision-making, that is, the issue of deciding how to decide.</jats:p>

<jats:p>The capabilities of current fault-handling techniques for Field Programmable Gate Arrays (FPGAs) develop a descriptive classification ranging from simple passive techniques to robust dynamic methods. Fault-handling methods not requiring modification of the FPGA device architecture or user intervention to recover from faults are examined and evaluated against overhead-based and sustainability-based performance metrics such as additional resource requirements, throughput reduction, fault capacity, and fault coverage. This classification alongside these performance metrics forms a standard for confident comparisons.</jats:p>

<jats:p>Aspect-orientation provides a new way of modularization by clearly separating crosscutting concerns from noncrosscutting ones. While aspect-orientation originally has emerged at the programming level, it now stretches also over other development phases. There are, for example, already several proposals for Aspect-Oriented Modeling (AOM), most of them pursuing distinguished goals, providing different concepts as well as notations, and showing various levels of maturity. Consequently, there is an urgent need to provide an in-depth survey, clearly identifying commonalities and differences between current AOM approaches. Existing surveys in this area focus more on comprehensibility with respect to development phases or evaluated approaches rather than on comparability on bases of a detailed evaluation framework.</jats:p> <jats:p>This article tries to fill this gap focusing on aspect-oriented design modeling. As a prerequisite for an in-depth evaluation, a conceptual reference model is presented as the article's first contribution, centrally capturing the basic design concepts of AOM and their interrelationships in terms of a UML class diagram. Based on this conceptual reference model, an evaluation framework has been designed, resembling the second contribution, by deriving a detailed and well-defined catalogue of evaluation criteria, thereby operationalizing the conceptual reference model. This criteria catalogue is employed together with a running example in order to evaluate a carefully selected set of eight design-level AOM approaches representing the third contribution of the article. This per approach evaluation is complemented with an extensive report on lessons learned, summarizing the approaches' strengths and shortcomings.</jats:p>

<jats:p>Constraint programming is well suited for the computational modeling of music theories and composition: its declarative and modular approach shares similarities with the way music theory is traditionally expressed, namely by a set of rules which describe the intended result. Various music theory disciplines have been modeled, including counterpoint, harmony, rhythm, form, and instrumentation. Because modeling music theories “from scratch” is a complex task, generic music constraint programming systems have been proposed that predefine the required building blocks for modeling a range of music theories. After introducing the field and its problems in general, this survey compares these generic systems according to a number of criteria such as the range of music theories these systems support.</jats:p>

<jats:p>In the last few years we have observed a proliferation of approaches for clustering XML documents and schemas based on their structure and content. The presence of such a huge amount of approaches is due to the different applications requiring the clustering of XML data. These applications need data in the form of similar contents, tags, paths, structures, and semantics. In this article, we first outline the application contexts in which clustering is useful, then we survey approaches so far proposed relying on the abstract representation of data (instances or schema), on the identified similarity measure, and on the clustering algorithm. In this presentation, we aim to draw a taxonomy in which the current approaches can be classified and compared. We aim at introducing an integrated view that is useful when comparing XML data clustering approaches, when developing a new clustering algorithm, and when implementing an XML clustering component. Finally, the article moves into the description of future trends and research issues that still need to be faced.</jats:p>

<jats:p>Digital images are everywhere—from our cell phones to the pages of our online news sites. How we choose to use digital image processing raises a surprising host of legal and ethical questions that we must address. What are the ramifications of hiding data within an innocent image? Is this an intentional security practice when used legitimately, or intentional deception? Is tampering with an image appropriate in cases where the image might affect public behavior? Does an image represent a crime, or is it simply a representation of a scene that has never existed? Before action can even be taken on the basis of a questionable image, we must detect something about the image itself. Investigators from a diverse set of fields require the best possible tools to tackle the challenges presented by the malicious use of today's digital image processing techniques.</jats:p> <jats:p>In this survey, we introduce the emerging field of digital image forensics, including the main topic areas of source camera identification, forgery detection, and steganalysis. In source camera identification, we seek to identify the particular model of a camera, or the exact camera, that produced an image. Forgery detection's goal is to establish the authenticity of an image, or to expose any potential tampering the image might have undergone. With steganalysis, the detection of hidden data within an image is performed, with a possible attempt to recover any detected data. Each of these components of digital image forensics is described in detail, along with a critical analysis of the state of the art, and recommendations for the direction of future research.</jats:p>

<jats:p>This survey covers hard real-time scheduling algorithms and schedulability analysis techniques for homogeneous multiprocessor systems. It reviews the key results in this field from its origins in the late 1960s to the latest research published in late 2009. The survey outlines fundamental results about multiprocessor real-time scheduling that hold independent of the scheduling algorithms employed. It provides a taxonomy of the different scheduling methods, and considers the various performance metrics that can be used for comparison purposes. A detailed review is provided covering partitioned, global, and hybrid scheduling algorithms, approaches to resource sharing, and the latest results from empirical investigations. The survey identifies open issues, key research challenges, and likely productive research directions.</jats:p>

<jats:p> The task of similarity search is widely used in various areas of computing, including multimedia databases, data mining, bioinformatics, social networks, etc. In fact, retrieval of semantically unstructured data entities requires a form of aggregated qualification that selects entities relevant to a query. A popular type of such a mechanism is similarity querying. For a long time, the database-oriented applications of similarity search employed the definition of similarity restricted to metric distances. Due to its topological properties, metric similarity can be effectively used to index a database which can then be queried efficiently by so-called metric access methods. However, together with the increasing complexity of data entities across various domains, in recent years there appeared many similarities that were <jats:italic>not</jats:italic> metrics—we call them <jats:italic>nonmetric</jats:italic> similarity functions. In this article we survey domains employing nonmetric functions for effective similarity search, and methods for efficient nonmetric similarity search. First, we show that the ongoing research in many of these domains requires complex representations of data entities. Simultaneously, such complex representations allow us to model also complex and computationally expensive similarity functions (often represented by various matching algorithms). However, the more complex similarity function one develops, the more likely it will be a nonmetric. Second, we review state-of-the-art techniques for efficient (fast) nonmetric similarity search, concerning both exact and approximate search. Finally, we discuss some open problems and possible future research trends. </jats:p>

<jats:p>Sensor networks, which consist of sensor nodes each capable of sensing environment and transmitting data, have lots of applications in battlefield surveillance, environmental monitoring, industrial diagnostics, etc. Coverage which is one of the most important performance metrics for sensor networks reflects how well a sensor field is monitored. Individual sensor coverage models are dependent on the sensing functions of different types of sensors, while network-wide sensing coverage is a collective performance measure for geographically distributed sensor nodes. This article surveys research progress made to address various coverage problems in sensor networks. We first provide discussions on sensor coverage models and design issues. The coverage problems in sensor networks can be classified into three categories according to the subject to be covered. We state the basic coverage problems in each category, and review representative solution approaches in the literature. We also provide comments and discussions on some extensions and variants of these basic coverage problems.</jats:p>