16266615
NeuroQL: A Domain-Specific Query Language for Neuroscience Data
In this paper, we propose a domain-specific query language called NeuroQL for the neuroscience domain. NeuroQL is designed primarily for neuroinformatics database users and aims to enable users to directly interact with neuroscience databases in their professional concepts and terms with the help of a conceptual data model. NeuroQL is DBMS independent and can be translated into traditional query language such as SQL, OQL and XQuery. It integrates some object-oriented features, and supports neuron domain-specific data types and query operators, which can dynamically evolve when the underlying database schema evolves.
15780176
Understanding the design space of referencing in collaborative augmented reality environments
For collaborative environments to be successful, it is critical that participants have the ability to generate effective references. Given the heterogeneity of the objects and the myriad of possible scenarios for collaborative augmented reality environments, generating meaningful references within them can be difficult. Participants in co-located physical spaces benefit from non-verbal communication, such as eye gaze, pointing and body movement; however, when geographically separated, this form of communication must be synthesized using computer-mediated techniques. We have conducted an exploratory study using a collaborative building task of constructing both physical and virtual models to better understand inter-referential awareness -- or the ability for one participant to refer to a set of objects, and for that reference to be understood. Our contributions are not necessarily in presenting novel techniques, but in narrowing the design space for referencing in collaborative augmented reality. This study suggests collaborative reference preferences are heavily dependent on the context of the workspace.
2014328
A 3D reconstruction algorithm based on 3D deformable atlas
Reconstructing 3D models from 2D images is an important problem in visualization, particularly in medical and biological visualization. We present a new algorithm for 3D model reconstruction from 2D-images. In our approach, a 3D atlas is deformed to fit the feature data set in the target images. Compared with existing 3D reconstruction techniques, our approach is more efficient and easier to control. The resultant model has good inherent connectivity and smoothness. The resolution of the final model is determined by the resolution of reference model rather than the dataset. The model generates highly detailed view with a limited number of images. This algorithm has been successfully applied to medical simulation.
17768872
AMMP-Vis: a collaborative virtual environment for molecular modeling
Molecular modeling is an important research area, helping scientists develop new drugs against diseases such as AIDS and cancer. Prior studies have demonstrated that immersive virtual environments have unique advantages over desktop systems in visualizing molecular models. However, exploration and interaction in existing molecular modeling virtual environments is often limited to a single user, lacking strong support for collaboration. In addition, scientists are often reluctant to adopt these systems because of their lack of availability and high cost. We propose an affordable immersive system that allows biologists and chemists to manipulate molecular models via natural gestures, receive and visualize real-time feedback from a molecular dynamics simulator, allow the sharing of customized views, and provide support for both local and remote collaborative research.
6725306
Design and Implementation of a Workflow Rendering Engine
Business visualization is an effective tool for business decision making and problem solving. Despite its obvious benefits, 3D visualization is far less common in practice than it should be due to the lack of software support. To address this problem, we have developed a workflow rendering engine that facilitates the 3D visualization of business process information for organizational process analysis and efficiency studies. The workflow information is represented in XML format to be compatible with the new Web graphics standard X3D. The rendering engine is implemented using C++ and OpenGL in order to take full advantage of modern 3D graphics hardware. The object-oriented design makes this engine highly extensible.
35564489
Accelerated 2D Image Processing on GPUs
Graphics processing units (GPUs) in recent years have evolved to become powerful, programmable vector processing units. Furthermore, the maximum processing power of current generation GPUs is roughly four times that of current generation CPUs (central processing units), and that power is doubling approximately every nine months, about twice the rate of Moore's law. This research examines the GPU's advantage at performing convolutionbased image processing tasks compared to the CPU. Straight-forward 2D convolutions show up to a 130:1 speedup on the GPU over the CPU, with an average speedup in our tests of 59:1. Over convolutions performed with the highly optimized FFTW routines on the CPU, the GPU showed an average speedup of 18:1 for filter kernel sizes from 3x3 to 29x29.
15073241
An Article Language Model for BBS Search
Bulletin Board Systems (BBS), similar to blogs, newsgroups, online forums, etc., are online broadcasting spaces where people can exchange ideas and make announcements. As BBS are becoming valuable repositories of knowledge and information, effective BBS search engines are required to make the information universally accessible and useful. However, the techniques that have been proven successful for web search are not suitable for searching BBS articles due to the nature of BBS. In this paper, we propose a novel article language model (LM) to build an effective BBS search engine. We investigate the differences between BBS articles and web pages, then extend the traditional LM to author LM and category LM. The article LM is powerful in the sense that it can combine the three LMs into a single framework. Experimental results shows that our article LM substantially outperforms both INQUERY algorithm and the traditional LM.
26735928
I/O Response Time in a Fault-Tolerant Parallel Virtual File System
A fault tolerant parallel virtual file system is designed and implemented to provide high I/O performance and high reliability. A queuing model is used to analyze in detail the average response time when multiple clients access the system. The results show that I/O response time is with a function of several operational parameters. It decreases with the increase in I/O buffer hit rate for read requests, write buffer size for write requests and number of server nodes in the parallel file system, while higher I/O requests arrival rate increases I/O response time.
15428033
On Optimal Physical Carrier Sensing: Theoretical Analysis and Protocol Design
Traditional Physical Carrier Sensing (PCS), which aims at eliminating hidden terminals in wireless networks, causes too many exposed terminals and deteriorates the throughput per user seriously. Some existing work has proven that an aggressive PCS can improve the throughput by balancing the tradeoff between hidden terminals and exposed terminals. However, little work has been conducted to optimize the PCS according to the network conditions. In this paper, we develop an analytical model to study the behaviors of a user in the aggressive PCS scenario, with which the optimal PCS threshold can be derived. Then, to avoid the complicated computation, we present a heuristic algorithm, in which the parameters required for PCS tuning are estimated by the carrier sensing mechanism employed in IEEE 802.11. Simulation results show that the proposed heuristic algorithm can make the PCS threshold approach to the theoretical optimal one. Moreover, the proposed heuristic algorithm can obtain significant throughput gain compared to the traditional PCS threshold setting solutions.
27145573
Stochastic semidefinite programming: a new paradigm for stochastic optimization
Semidefinite programs are a class of optimization problems that have been studied extensively during the past 15 years. Semidefinite programs are naturally related to linear programs, and both are defined using deterministic data. Stochastic programs were introduced in the 1950s as a paradigm for dealing with uncertainty in data defining linear programs. In this paper, we introduce stochastic semidefinite programs as a paradigm for dealing with uncertainty in data defining semidefinite programs.
10155852
Nexus: a novel weighted-graph-based prefetching algorithm for metadata servers in petabyte-scale storage systems
An efficient, accurate and distributed metadata-oriented prefetching scheme is critical to the overall performance in large distributed storage systems. In this paper, we present a novel weighted-graph-based prefetching technique, built on successor relationship, to gain performance benefit from prefetching specifically for clustered metadata servers, an arrangement envisioned necessary for petabyte-scale distributed storage systems. Extensive trace-driven simulations show that by adopting our new prefetching algorithm, the hit rate for metadata access on the client site can be increased by up to 13%, while the average response time of metadata operations can be reduced by up to 67%, compared with LRU and an existing state of the art prefetching algorithm.