Catálogo de publicaciones - revistas

<jats:p>Most common database management systems represent information in a simple record-based format. Semantic modeling provides richer data structuring capabilities for database applications. In particular, research in this area has articulated a number of constructs that provide mechanisms for representing structurally complex interrelations among data typically arising in commercial applications. In general terms, semantic modeling complements work on knowledge representation (in artificial intelligence) and on the new generation of database models based on the object-oriented paradigm of programming languages.</jats:p> <jats:p>This paper presents an in-depth discussion of semantic data modeling. It reviews the philosophical motivations of semantic models, including the need for high-level modeling abstractions and the reduction of semantic overloading of data type constructors. It then provides a tutorial introduction to the primary components of semantic models, which are the explicit representation of objects, attributes of and relationships among objects, type constructors for building complex types, ISA relationships, and derived schema components. Next, a survey of the prominent semantic models in the literature is presented. Further, since a broad area of research has developed around semantic modeling, a number of related topics based on these models are discussed, including data languages, graphical interfaces, theoretical investigations, and physical implementation strategies.</jats:p>

<jats:p>This paper surveys a variety of data compression methods spanning almost 40 years of research, from the work of Shannon, Fano, and Huffman in the late 1940s to a technique developed in 1986. The aim of data compression is to reduce redundancy in stored or communicated data, thus increasing effective data density. Data compression has important application in the areas of file storage and distributed systems. Concepts from information theory as they relate to the goals and evaluation of data compression methods are discussed briefly. A framework for evaluation and comparison of methods is constructed and applied to the algorithms presented. Comparisons of both theoretical and empirical natures are reported, and possibilities for future research are suggested.</jats:p>

<jats:p>The problem of deadlock detection in distributed systems has undergone extensive study. An important application relates to distributed database systems. A uniform model in which published algorithms can be cast is given, and the fundamental principles on which distributed deadlock detection schemes are based are presented. These principles represent mechanisms for developing distributed algorithms in general and deadlock detection schemes in particular. In addition, a hierarchy of deadlock models is presented; each model is characterized by the restrictions that are imposed upon the form resource requests can assume. The hierarchy includes the well-known models of resource and communication deadlock. Algorithms are classified according to both the underlying principles and the generality of resource requests they permit. A number of algorithms are discussed in detail, and their complexity in terms of the number of messages employed is compared. The point is made that correctness proofs for such algorithms using operational arguments are cumbersome and error prone and, therefore, that only completely formal proofs are sufficient for demonstrating correctness.</jats:p>

<jats:p>This paper reviews empirical studies concerning the readability of text from computer screens. The review focuses on the form and physical attributes of complex, realistic displays of text material. Most studies comparing paper and computer screen readability show that screens are less readable than paper. There are many factors that could affect the readability of computer screens. The factors explored in this review are the features of characters, the formatting of the screen, the contrast and color of the characters and background, and dynamic aspects of the screen. Numerous areas for future research are pinpointed.</jats:p>

<jats:p>A polling model is a system of multiple queues accessed by a single server in cyclic order. Polling models provide performance evaluation criteria for a variety of demand-based, multiple-access schemes in computer and communication systems. This paper presents an overview of the state of the art of polling model analysis, as well as an extensive list of references. In particular, single-buffer systems and infinite-buffer systems with exhaustive, gated, and limited service disciplines are treated. There is also some discussion of systems with a noncyclic order of service and systems with priority. Applications to computer networks are illustrated, and future research topics are suggested.</jats:p>

<jats:p>Object-oriented programming is becoming a popular approach to the construction of complex software systems. Benefits of object orientation include support for modular design, code sharing, and extensibility. In order to make the most of these advantages, a type theory for objects and their interactions should be developed to aid checking and controlled derivation of programs and to support early binding of code bodies for efficiency. As a step in this direction, this paper surveys a number of existing type theories and examines the manner and extent to which these theories are able to represent the ideas found in object-oriented programming. Of primary interest are the models provided by type theories for abstract data types and inheritance, and the major portion of this paper is devoted to these topics. Code fragments illustrative of the various approaches are provided and discussed. The introduction provides an overview of object-oriented programming and types in programming languages; the summary provides a comparative evaluation of the reviewed typing systems, along with suggestions for future work.</jats:p>

<jats:p>Application of computer and communications technology to cooperative work and group decision making has grown out of three traditions: computer-based communications, computer:based information service provision, and computer-based decision support. This paper reviews the group decision support systems (GDSSs) that have been configured to meet the needs of groups at work, and evaluates the experience to date with such systems. Progress with GDSSs has proved to be slower than originally anticipated because of shortcomings with available technology, poor integration of the various components of the computing package, and incomplete understanding of the nature of group decision making. Nevertheless, the field shows considerable promise with respect to the creation of tools to aid in group decision making and the development of sophisticated means of studying the dynamics of decision making in groups.</jats:p>

<jats:p> A new type of dynamic file access called <jats:italic>dynamic hashing</jats:italic> has recently emerged. It promises the flexibility of handling dynamic files while preserving the fast access times expected from hashing. Such a fast, dynamic file access scheme is needed to support modern database systems. This paper surveys dynamic file access scheme is needed to support modern database systems. This paper surveys dynamic hashing schemes and examines their critical design issues. </jats:p>

<jats:p>Semantic data models have emerged from a requirement for more expressive conceptual data models. Current generation data models lack direct support for relationships, data abstraction, inheritance, constraints, unstructured objects, and the dynamic properties of an application. Although the need for data models with richer semantics is widely recognized, no single approach has won general acceptance. This paper describes the generic properties of semantic data models and presents a representative selection of models that have been proposed since the mid-1970s. In addition to explaining the features of the individual models, guidelines are offered for the comparison of models. The paper concludes with a discussion of future directions in the area of conceptual data modeling.</jats:p>

<jats:p>A statistical profile summarizes the instances of a database. It describes aspects such as the number of tuples, the number of values, the distribution of values, the correlation between value sets, and the distribution of tuples among secondary storage units. Estimation of database profiles is critical in the problems of query optimization, physical database design, and database performance prediction. This paper describes a model of a database of profile, relates this model to estimating the cost of database operations, and surveys methods of estimating profiles. The operators and objects in the model include build profile, estimate profile, and update profile. The estimate operator is classified by the relational algebra operator (select, project, join), the property to be estimated (cardinality, distribution of values, and other parameters), and the underlying method (parametric, nonparametric, and ad-hoc). The accuracy, overhead, and assumptions of methods are discussed in detail. Relevant research in both the database and the statistics disciplines is incorporated in the detailed discussion.</jats:p>