59762733
The application of artificial neural networks in editing noisy seismic data
59116191
A High Accuracy Printed Traditional and Simplified Chinese Character Document Recognition System
206756450
Nonlinear Dimensionality Reduction by Locally Linear Inlaying
High-dimensional data is involved in many fields of information processing. However, sometimes, the intrinsic structures of these data can be described by a few degrees of freedom. To discover these degrees of freedom or the low-dimensional nonlinear manifold underlying a high-dimensional space, many manifold learning algorithms have been proposed. Here we describe a novel algorithm, locally linear inlaying (LLI), which combines simple geometric intuitions and rigorously established optimality to compute the global embedding of a nonlinear manifold. Using a divide-and-conquer strategy, LLI gains some advantages in itself. First, its time complexity is linear in the number of data points, and hence LLI can be implemented efficiently. Second, LLI overcomes problems caused by the nonuniform sample distribution. Third, unlike existing algorithms such as isometric feature mapping (Isomap), local tangent space alignment (LTSA), and locally linear coordination (LLC), LLI is robust to noise. In addition, to evaluate the embedding results quantitatively, two criteria based on information theory and Kolmogorov complexity theory, respectively, are proposed. Furthermore, we demonstrated the efficiency and effectiveness of our proposal by synthetic and real-world data sets.
2980184
Supporting Scalable and Distributed Data Subsetting and Aggregation in Large-Scale Seismic Data Analysis
The ability to query and process very large, terabyte-scale datasets has become a key step in many scientific and engineering applications. In this paper, we describe the application of two middleware frameworks in an integrated fashion to provide a scalable and efficient system for execution of seismic data analysis on large datasets in a distributed environment. We investigate different strategies for efficient querying of large datasets and parallel implementations of a seismic image reconstruction algorithm. Our results on a state-of-the-art mass storage system coupled with a high-end compute cluster show that our implementation is scalable and can achieve about 2.9 Gigabytes per second data processing rate – about 70% of the maximum 4.2GB/s application-level raw I/O bandwidth of the storage platform.
117948556
Some Intersection Theorems and Minimax Inequalities
This paper proves some intersection theorems. The proofs are new in the sense that they do not require the finite intersection property. As an application, some of the Fan minimax inequalities are proved.
119805904
Distorted-wave born approximation for the ionisation of hydrogen by electrons
Matrix elements for ionisation play an important part in electron-atom scattering calculations. Two methods for describing ionisation that can be incorporated into a scattering calculation are tested here against coplanar asymmetric experimental differential cross sections at 150 and 250 eV. They are the distorted-wave Born approximation and the coupled pseudostates methods. A method that incorporates the exact boundary conditions for three charged bodies describes the data significantly better and shows an important direction for improvement of scattering calculations
15202321
FREEDOM-7: A High Fidelity Seven Axis Haptic Device with Application to Surgical Training
A seven axis haptic device, called the Freedom-7, is described in relation to its application to surgical training. The generality of its concept makes it also relevant to most other haptic applications. The design ratio- nale is driven by a long list of requirements since such a device is meant to interact with the human hand: uniform response, balanced inertial proper- ties, static balancing, low inertia, high frequency response, high resolution, low friction, arbitrary reorientation, and low visual intrusion. Some basic performance gures are also reported.
16687476
PULMONARY CT IMAGE ANALYSIS AND COMPUTER AIDED DETECTION
This short article summarizes the use of current CT image data for a comprehensive assessment of pulmonary structure and function. It identifies the need for the development of highly automated methods and techniques allowing quantitative analysis of lungs, lung lobes, airway trees, and pulmonary parenchyma. Such analyses serve as the stepping stones for more sophisticated computer-aided detection approaches capable of parenchymal tissue characterization and identification of pulmonary nodules, some of which are discussed