1,720,993 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Segmentation in a Distributed Real-Time Main-Memory Database
No full textTo achieve better scalability, a fully replicated, distributed, main-memory database is divided into subparts, called segments. Segments may have individual degrees of redundancy and other properties that can be used for replication control. Segmentation is examined for the opportunity of decreasing replication effort, lower memory requirements and decrease node recovery times. Typical usage scenarios are distributed databases with many nodes where only a small number of the nodes share information. We present a framework for virtual full replication that implements segments with scheduled replication of updates between sharing nodes. Selective replication control needs information about the application semantics that is specified using segment properties, which includes consistency classes and other properties. We define a syntax for specifying the application semantics and segment properties for the segmented database. In particular, properties of segments that are subject to hard real-time constraints must be specified. We also analyze the potential improvements for such an architecture
Virtual Full Replication for Scalable Distributed Real-Time Databases
No full textA fully replicated distributed real-time database provides high availability and predictable access times, independent of user location, since all the data is available at each node. However, full replication requires that all updates are replicated to every node, resulting in exponential growth of bandwidth and processing demands with the number of nodes and objects added. To eliminate this scalability problem, while retaining the advantages of full replication, this thesis explores Virtual Full Replication (ViFuR); a technique that gives database users a perception of using a fully replicated database while only replicating a subset of the data. We use ViFuR in a distributed main memory real-time database where timely transaction execution is required. ViFuR enables scalability by replicating only data used at the local nodes. Also, ViFuR enables flexibility by adaptively replicating the currently used data, effectively providing logical availability of all data objects. Hence, ViFuR substantially reduces the problem of non-scalable resource usage of full replication, while allowing timely execution and access to arbitrary data objects. In the thesis we pursue ViFuR by exploring the use of database segmentation. We give a scheme (ViFuR-S) for static segmentation of the database prior to execution, where access patterns are known a priori. We also give an adaptive scheme (ViFuR-A) that changes segmentation during execution to meet the evolving needs of database users. Further, we apply an extended approach of adaptive segmentation (ViFuR-ASN) in a wireless sensor network - a typical dynamic large-scale and resource-constrained environment. We use up to several hundreds of nodes and thousands of objects per node, and apply a typical periodic transaction workload with operation modes where the used data set changes dynamically. We show that when replacing full replication with ViFuR, resource usage scales linearly with the required number of concurrent replicas, rather than exponentially with the system size
A Simulation Approach for Evaluating Scalability of a Virtually Fully Replicated Real-time Database
No full textVirtual Full Replication for Scalable Distributed Real-Time Databases [Elektronisk resurs]
No full textDistributed real-time systems increase in size an complexity, and the nodes in such systems become difficult to implement and test. In particular, communication for synchronization of shared information in groups of nodes becomes complex to manage. Several authors have proposed to using a distributed database as a communication subsystem, to off-load database applications from explicit communication. This lets the task for information dissemination be done by the replication mechanisms of the database. With increasingly larger systems, however, there is a need for managing the scalability for such database approach. Furthermore, timeliness for database clients requires predictable resource usage, and scalability requires bounded resource usage in the database system. Thus, predictable resource management is an essential function for realizing timeliness in a large scale setting.We discuss scalability problems and methods for distributed real-time databases in the context of the DeeDS database prototype. Here, all transactions can be executed timely at the local node due to main memory residence, full replication and detached replication of updates. Full replication contributes to timeliness and availability, but has a high cost in excessive usage of bandwidth, storage, and processing, in sending all updates to all nodes regardless of updates will be used there or not. In particular, unbounded resource usage is an obstacle for building large scale distributed databases. For many application scenarios it can be assumed that most of the database is shared by only a limited number of nodes. Under this assumption it is reasonable to believe that the degree of replication can be bounded, so that a bound also can be set on resource usage.The thesis proposal identifies and elaborates research problems for bounding resource usage in large scale distributed real-time databases. One objective is to bound resource usage by taking advantages of pre-specified data needs, but also by detecting unspecified data needs and adapting resource management accordingly. We elaborate and evaluate the concept of virtual full replication, which provides an image of a fully replicated database to database clients. It makes data objects available where needed, while fulfilling timeliness and consistency requirements on the data.In the first part of our work, virtual full replication makes data available where needed by taking advantages of pre-specified data accesses to the distributed database. For hard real-time systems, the required data accesses are usually known since such systems need to be well specified to guarantee timeliness. However, there are many applications where a specification of data accesses can not be done before execution. The second part of our work extends virtual full replication to be used with such applications. By detecting new and changed data accesses during execution and adapt database replication, virtual full replication can continuously provide the image of full replication while preserving scalability.One of the objective of the thesis work is to quantify scalability in the database context, so that actual benefits and achievements can be evaluated. Further, we find out the conditions for setting bounds on resource usage for scalability, under both static and dynamic data requirements.</p
Virtual Full Replication for Scalable Distributed Real-Time Databases
No full textA fully replicated distributed real-time database provides high availability and predictable access times, independent of user location, since all the data is available at each node. However, full replication requires that all updates are replicated to every node, resulting in exponential growth of bandwidth and processing demands with the number of nodes and objects added. To eliminate this scalability problem, while retaining the advantages of full replication, this thesis explores Virtual Full Replication (ViFuR); a technique that gives database users a perception of using a fully replicated database while only replicating a subset of the data. We use ViFuR in a distributed main memory real-time database where timely transaction execution is required. ViFuR enables scalability by replicating only data used at the local nodes. Also, ViFuR enables flexibility by adaptively replicating the currently used data, effectively providing logical availability of all data objects. Hence, ViFuR substantially reduces the problem of non-scalable resource usage of full replication, while allowing timely execution and access to arbitrary data objects. In the thesis we pursue ViFuR by exploring the use of database segmentation. We give a scheme (ViFuR-S) for static segmentation of the database prior to execution, where access patterns are known a priori. We also give an adaptive scheme (ViFuR-A) that changes segmentation during execution to meet the evolving needs of database users. Further, we apply an extended approach of adaptive segmentation (ViFuR-ASN) in a wireless sensor network - a typical dynamic large-scale and resource-constrained environment. We use up to several hundreds of nodes and thousands of objects per node, and apply a typical periodic transaction workload with operation modes where the used data set changes dynamically. We show that when replacing full replication with ViFuR, resource usage scales linearly with the required number of concurrent replicas, rather than exponentially with the system size.</p
Virtual Full Replication for Scalable Distributed Real-Time Databases (Thesis Proposal)
No full textDistributed real-time systems increase in size an complexity, and the nodes in such systems become difficult to implement and test. In particular, communication for synchronization of shared information in groups of nodes becomes complex to manage. Several authors have proposed to using a distributed database as a communication subsystem to offload database applications from explicit communication. This lets the task for information dissemination be done by the replication mechanisms of the database. With increasingly larger systems, however, there is a need for managing the scalability for such database approach. Furthermore, timeliness for database clients requires predictable resource usage, and scalability requires bounded resource usage in the database system. Thus, predictable resource management is an essential function for realizing timeliness in a large scale setting. We discuss scalability problems and methods for distributed real-time databases in the context of the DeeDS database prototype. Here, all transactions can be executed timely at the local node due to main memory residence, full replication and detached replication of updates. Full replication contributes to timeliness and availability, but has a high cost in excessive usage of bandwidth, storage, and processing, in sending all updates to all nodes regardless of updates will be used there or not. In particular, unbounded resource usage is an obstacle for building large scale distributed databases. For many application scenarios it can be assumed that most of the database is shared by only a limited number of nodes. Under this assumption it is reasonable to believe that the degree of replication can be bounded, so that a bound also can be set on resource usage. The thesis proposal identifies and elaborates research problems for bounding resource usage in large scale distributed real-time databases. One objective is to bound resource usage by taking advantages of pre-specified data needs, but also by detecting unspecified data needs and adapting resource management accordingly. We elaborate and evaluate the concept of virtual full replication, which provides an image of a fully replicated database to database clients. It makes data objects available where needed, while fulfilling timeliness and consistency requirements on the data. In the first part of our work, virtual full replication makes data available where needed by taking advantages of pre-specified data accesses to the distributed database. For hard real-time systems, the required data accesses are usually known since such systems need to be well specified to guarantee timeliness. However, there are many applications where a specification of data accesses can not be done before execution. The second part of our work extends virtual full replication to be used with such applications. By detecting new and changed data accesses during execution and adapt database replication, virtual full replication can continuously provide the image of full replication while preserving scalability. One of the objective of the thesis work is to quantify scalability in the database context, so that actual benefits and achievements can be evaluated. Further, we find out the conditions for setting bounds on resource usage for scalability, under both static and dynamic data requirements.</p
- …
