2700489
An efficient algorithm for predictive continuous nearest neighbor query processing and result maintenance
Predictive continuous nearest neighbor queries are concerned with finding the nearest neighbor objects for some future time period according to the current object and query locations and their motion information. Existing continuous query processing algorithms are not efficient enough, requiring multiple dataset lookups to evaluate the query results throughout the duration of a continuous query. More importantly, the complete result for the whole query time interval is only available at the moment when all object motion updates have been examined, based on which adjustment of the query result is made. In this paper, we propose an algorithm which requires only one dataset lookup to deliver a complete predictive result. We then apply a differential update technique to maintain the query results incrementally in the presence of object location and motion updates.
5976830
A semantic broadcast scheme for a mobile environment based on dynamic chunking
Data broadcast is an effective approach to disseminate information from a database server to numerous mobile clients in a mobile environment. Since a broadcast session contains only a subset of the database items, a client might not be able to obtain all its items from the broadcast and is forced to request additional ones from the server on demand. We describe a semantic-based broadcast approach which attaches a semantic description to each broadcast unit, called a chunk, which is a cluster of data items. This allows a client to determine if a query can be answered entirely using a broadcast as well as defining the precise nature of the remaining items in the form of a "supplementary" query. Chunks could be of different sizes and are hierarchically organized. We propose a heuristic to schedule the broadcast order of the chunks to improve the tuning time, access time, and a new metric called a data affinity index. The performances are evaluated via experiments based on a simulation model.
14116288
A Practitioner's Approach to Normalizing XQuery Expressions
XQuery becomes a standard of the XML query language. Just like in SQL, XQuery allows nested expressions. To optimize XQuery processing, a lot of research has been done on normalization, i.e., transforming nested expressions to equivalent unnested ones. Previous normalization rules are classified into two categories – source-level and algebra-level – depending on whether a construct is specified by using a query language or an algebraic expression. In implementation point of view, we contend that the source-level rule is preferable to the algebra-level rule because algebras used for normalization are hard to be directly exploited in a typical DBMS. However, a complete set of source-level rules is yet to be developed. In this paper, we propose source-level rules for normalizing XQuery expressions and present an implementation mechanism. We show that our rules are correct and complete according to the nesting types classified by Kim. Our mechanism is easily implementable since it adapts the well-known Query Graph Model (QGM) representation. We have successfully implemented this mechanism into our XML DBMS named Odysseus/XML.
2439836
Mitigating soft error failures for multimedia applications by selective data protection
With advances in process technology, soft errors(SE)are becoming an increasingly critical design concern. Due to their large area and high density, caches are worst hit by soft errors. Although Error Correction Code based mechanisms protect the data in caches, they have high performance and power overheads. Since multimedia applications are increasingly being used in mission-critical embedded systems where both reliability and energy are a major concern, there is a de?nite need to improve reliability in embedded systems, without too much energy overhead. We observe that while a soft error in multimedia data may only result in a minor loss in QoS, a soft error in avariable that controls the execution ?ow of the program may be fatal. Consequently, we propose to partition the data space into failure critical and failure non-critical data, and provide a high-degree of soft error protection only to the failure critical data in Horizontally Partitioned Caches. Experimental results demonstrate that our selective data protection can achieve the failure rate close to that of a soft error protected cache system, while retaining the performance and energy consumption similar to those of a traditional cache system, with some degradation in QoS. For example, for conventional con?guration as in IntelXScale, our approach achieves the same failure rate, while improving performance by 28% and reducing energy consumption by 29%in comparison with a soft error protected cache.
10984576
Are physically embodied social agents better than disembodied social agents?: The effects of physical embodiment, tactile interaction, and people's loneliness in human-robot interaction
Two experiments were conducted to investigate the effects of physical embodiment in human-agent interaction. Experiment 1 (N=32) shows positive effects of physical embodiment on the feeling of an agent's social presence, the evaluation of the agent, the assessment of public evaluation of the agent, and the evaluation of the interaction with the agent. A path analysis reveals that the feeling of the agent's social presence mediates the participants' evaluation of the social agent. Experiment 2 (N=32) shows that physical embodiment with restricted tactile interaction causes null or even negative effects in human-agent interaction. In addition, Experiment 2 indicates that lonely people feel higher social presence of social agents, and provide more positive social responses to social agents than non-lonely people. The importance of physical embodiment and tactile communication in human-agent interaction and the diverse role of social robots, especially for the lonely population, are discussed.
5737535
A new algorithm for Kohonen layer learning with application to power system stability analysis
In certain classification problems, input patterns are not distributed in a clustering manner but distributed uniformly in an input space and there exist certain critical hyperplanes called decision boundaries. Since learning vector quantization (LVQ) classifies an input vector based on the nearest neighbor, the codebook vectors away from the decision boundaries are redundant. This paper presents an alternative algorithm called boundary search algorithm (BSA) for the purpose of solving this redundancy problem. The BSA finds a fixed number of codebook vectors near decision boundaries by selecting appropriate training vectors. It is found to be more efficient compared with LVQ and its validity is demonstrated with satisfaction in the transient stability analysis of a power system.
34164098
A New EM Algorithm for Resource Allocation Network
Clustering usually assumes that the number of clusters is known or given. No knowledge of such a priori information is needed to find an appropriate number of clusters. This paper introduces an elliptical clustering algorithm with incremental growth of clusters, which is derived from the batch EM algorithm with a decay factor and a novelty criterion. The proposed algorithm can start with no or a small number of clusters. Whenever unusual data is presented, the algorithm adds a new cluster and finally the number of clusters in the data is obtained after clustering. The usefulness of the proposed algorithm is demonstrated for texture image segmentation and skin image segmentation.