Predictive Queries Research Articles

Adaptive index management for future location-based queries

Many location-based applications have arisen in various areas including mobile communications, traffic control and military command and control (C2) systems. And one of the important research issue in these areas is tracking and managing moving objects through spatiotemporal indexing for the efficient location-based services. However, managing exact geometric location information is difficult to be achieved due to continual changes of moving objects.Traditionally spatiotemporal index structures focus on optimizing the node accesses during construction and massive updates that do not refer on-line movement updates. In this paper we propose an indexing framework for future location queries based on space partitioning and the dual transformation. Our method provides a constraint database approach for constructing indexes to improve the efficiency of spatiotemporal query answering. In addition, the performance enhancement is achieved by our cost-based dynamic management algorithm that determines the appropriate index reorganization probabilistically induced by various mobility models and query cost functions. This approach can be applied for the predictive range queries on moving object's trajectories specifically in the mobile communication environments. We evaluate our method and compare the performance with the related spatiotemporal index structures in the simulated environments.

Hybrid Model-Based and Memory-Based Traffic Prediction System

Short-term traffic forecasting capabilities on freeways and major arterials have received special attention in the past decade primarily because of their vital role in supporting various traveler trip decisions and traffic management functions. A hybrid model-based and memory-based methodology used to improve freeway traffic prediction performance is presented. The proposed methodology integrates both approaches to strengthen predictions under both recurrent and nonrecurrent conditions. The model-based approach relies on a combination of static and dynamic neural network architectures to achieve optimal prediction performance under various input and traffic condition settings. Concurrently, the memory-based component is derived from the data archival system that encodes the commuters' travel experience in the past. The outcomes of the two approaches are two prediction values for each query case. The two values are subsequently processed by a prediction query manager, which ultimately produces one final prediction value by using an error-based decision algorithm. It was found that the hybrid approach produced speed estimates with smaller errors than those produced when the two approaches were used separately. The proposed prediction approach could be used to derive travel times more reliably for advanced traveler information systems applications.

Genomics. Plant biology in 2010.

The completion of the Arabidopsis sequence will be followed by a new ten-year project that will determine the function of all angiosperm genes. Funding for the U.S. component of this multinational project will originate from a new initiative from the U.S. National Science Foundation called the 2010 Project. Progress toward completion of this ambitious project will necessitate significant changes in how the plant biology community selects and approaches research objectives. The plan envisions that the project will facilitate the development of a computational model of a virtual plant that will allow predictive queries about basic mechanisms underlying plant growth and development.