2713110
Orthographic case restoration using supervised learning without manual annotation
One challenge in text processing is the treatment of case insensitive documents such as speech recognition results. The traditional approach is to re-train a language model excluding case-related features. This paper presents an alternative two-step approach whereby a preprocessing module (Step 1) is designed to restore case-sensitive form which is subsequently processed by the original system (Step 2). Step 1 is mainly implemented as a Hidden Markov Model trained on a large raw corpus of case sensitive documents. It is demonstrated that this approach (i) outperforms the feature exclusion approach for named entity tagging, (ii) leads to limited degradation for parsing, relationship extraction and case insensitive question answering, (iii) reduces system complexity, and (iv) has wide applicability: the restored text can be used in both statistical model and rule-based systems.
8155707
A Question Answering System Supported by Information Extraction
This paper discusses an information extraction (IE) system, Textract, in natural language (NL) question answering (QA) and examines the role of IE in QA application. It shows: (i) Named Entity tagging is an important component for QA, (ii) an NL shallow parser provides a structural basis for questions, and (iii) high-level domain independent IE can result in a QA breakthrough.
28902667
Performance analysis of a PCS network with state dependent calls arrival processes and impatient calls
This paper studies the behavior of performance evaluation for a personal communication services (PCS) network, in which the calls' arrival process may depend on the number of calls in the target cells. Each cell of the PCS network consists of a finite channel and a buffer (with finite or infinite size) for handoff calls. The handoff calls having to wait in the buffer for further communication may become impatient and leave the system if their waiting time exceeds their own patience. The mobilities of the portables are characterized by the random cell residence times of the portables. For insight into the effect of dependent calls arrival processes and the impatient calls on PCS network performance, we propose an analytical model and obtain the expressions for the following interesting conventional and new performance measures: the new call blocking probability, handoff call failure probability and the forced termination probability of a handoff call; the quasi and actual waiting time of a handoff call in the buffer; the actual call holding time of a new call; and the blocking period of time of the new calls and the handoff calls etc. We also provide an algorithm to compare these blocking probabilities and the arrival rates for handoff calls. Some special cases of our model used in previous traffic models of wireless and/or wireline communications are discussed. The results presented in this paper can provide guidelines for field data processing on updated PCS network design and performance evaluation.
17819380
Feature Selection for Complex Patterns
Feature selection is an important data preprocessing step in data mining and pattern recognition. Many algorithms have been proposed in the past for simple patterns that can be characterised by a single feature vector. Unfortunately, these algorithms are hardly applicable to what are referred as complex patterns that have to be described by a finite set of feature vectors. This paper addresses the problem of feature selection for the complex patterns. First, we formulated the calculation of mutual information for complex patterns based on Gaussian mixture model. A hybrid feature selection algorithm is then proposed based on the formulated mutual information calculation (filter) and Baysian classification (wrapper). Experimental results on XM2VTS speaker recognition database have not only verified the performance of the proposed algorithm, but also demonstrated that traditional feature selection algorithms designed for simple patterns would perform poorly for complex patterns.
26434237
Method to Balance the Communication Among Multi-agents in Real Time Traffic Synchronization
A method to balance the communication among Multi-Agents in real time traffic synchronization is proposed in this research. The paper presents Air Traffic Flow Management (ATFM) problem and its synchronization property. For such a complex problem, combing grid computing with multi-agent coordination techniques to improve ATFM computational efficiency is the main objective of actual research. To demonstrate the developed model – ATFM in Grid Computing (ATFMGC), the grid architecture, the basic components and the relationship among them are described. At the same time, the function of agents (tactical planning agent etc.), their knowledge representation and inference processes are also discussed. As criteria to measure the effective to reduce quantity of the communication among agents and the delay of the flights, Standard of Balancing among Agents (SBA) is used in the analysis. The simulation shows the efficiency of the developed model and successful application in the case study.
33595781
New Optimal Tame Towers of Function Fields over Small Finite Fields
Ihara [11] introduced the quantity A(q) = limsupg→∞ N q (g)/g where N q (g) is the maximum number of rational places of a function field with genus g and with the finite field F q as the full field of constants. Drinfeld and Vladut [2] showed that A(q) ≤ √q - 1. It was also shown by Ihara [11], and Tsfasman, Vladut and Zink [17] in special cases, that A(q)= √ q - 1 when q is a square. When q is not a square, the exact value of A(q) is currently unknown. While the problem of finding A(q) in this case is an interesting problem in its own right, much motivation comes from implications in asymptotic results in coding theory. Essentially there are three approaches to finding lower bounds for A(q): class field towers [15], modular curves [11], [17], [3], [4]and explicit towers (that is, given explicitly in terms of generators and relations) of function fields. For applications to coding theory though, explicit towers are needed. In [6], a tower of function fields over Fq is defined to be a sequence F = (F 1, F 2, F 3,.. ) of function fields F i , having the following properties: 
 
(i) 
 
F1 ⊆F2 ⊆ F3 ⊆.... 
 
 
 
 
(ii) 
 
For each n ≥ 1, the extension F n+1/ F n is separable of degree [F n+1: F n ] > 1. 
 
 
 
 
(iii) 
 
the genus g(F j ) > 1 for some j ≥ 1. 
 
 
 
 
(iv) 
 
F q is the full field of constants of each F n .
2550376
LDV Remote Voice Acquisition and Enhancement
Laser Doppler vibrometers (LDVs) have been widely used in industry inspection. One of the superior characteristics of an LDV is that it can detect and measure extremely tiny vibration of a target at a large distance, with sensitivity on the order of 1 mum/s. On the other hand, we have found that most objects nearby audio sources can be vibrated by the audio waves. These two aspects motivate our research in a new application of the LDVs, namely remote voice detection from surrounding vibrated objects. However, the detected speech signals may be corrupted by many noise sources, such as laser photon noises, target movements, and background acoustic noises (wind, engine sound, etc.). Therefore, speech enhancement algorithms based on Gaussian bandpass and Wiener filters are designed to effectively improve the intelligibility of the noisy voice signals detected by the LDV system. Experimental results show that remote voice detection via an LDV is very promising, when choosing appropriate targets close to human subjects and using the proposed enhancement techniques