Understanding Sen's Idea of a Coherent Goal-Rights System in the Light of Political Liberalism

Being qualified as a right implies being recognized as having a universal value. It describes a political ideal of equality in its highly abstract form. Yet, in the exercise of a right, we must consider differences in personal characteristics or social contexts, since the extent to which individuals can concretely exercise rights might differ greatly according to the differences in personal characteristics or social contexts. To respect every individual impartially, we must set up public rules of the effectiveness of rights, which will direct each individual in concrete terms the doings and beings he/her can actually realize depending on his/her will. A Coherent Goal-Rights System mainly focuses on this problem. It is considered as a pluralistic coherent-value system, in which different kinds of values are appropriately balanced under certain criteria, which intends to overcome certain kinds of dualism such as vs. , or vs. . The purpose of this paper is to explore a way to balance social goals and rights, the right to civil freedom, the right to well-being freedom, and the right to political freedom, understanding Sen's idea of a Coherent Goal-Rights System.

Topic-based mixture language modelling

This paper describes an approach for constructing a mixture of language models based on simple statistical notions of semantics using probabilistic models developed for information retrieval. The approach encapsulates corpus-derived semantic information and is able to model varying styles of text. Using such information, the corpus texts are clustered in an unsupervised manner and a mixture of topic-specific language models is automatically created. The principal contribution of this work is to characterise the document space resulting from information retrieval techniques and to demonstrate the approach for mixture language modelling. A comparison is made between manual and automatic clustering in order to elucidate how the global content information is expressed in the space. We also compare (in terms of association with manual clustering and language modelling accuracy) alternative term-weighting schemes and the effect of singular value decomposition dimension reduction (latent semantic analysis). Test set perplexity results using the British National Corpus indicate that the approach can improve the potential of statistical language modelling. Using an adaptive procedure, the conventional model may be tuned to track text data with a slight increase in computational cost

Nonlinear Realization of Partially Broken N=2 Superconformal Symmetry in Four Dimensions

We investigate the nonlinear realization of spontaneously broken N=2 superconformal symmetry in 4 dimensions. We particularly study Nambu-Goldstone degrees of freedom for the partial breaking of N=2 superconformal symmetry down to N=1 super-Poincar{\'e} symmetry, where we get the chiral NG multiplet of dilaton and the vector NG multiplet of NG fermion of broken Q-supersymmetry. Evaluating the covariant differentials and supervielbeins for the chiral as well as the full superspace, we obtain the nonlinear effective lagrangians.Comment: 14 pages, LaTeX, minor typos correcte

RDF Curator: A Novel Workflow that Generates Semantic Graph from Literature for Curation Using Text Mining

There exist few databases that enable cross-reference among various research fields related to bioenergy. Cross-reference is highly desired among bioinformatics databases related to environment, energy, and agriculture for better mutual cooperation. By uniting Semantic Graph, we can economically construct a distributed database, regardless of the size of research laboratories and research endeavors.

Our purpose is to design and develop a workflow based on RDF (Resource Description Framework) that generates Semantic Graph for a set of technical terms extracted from documents of various formats, such as PDF, HTML, and plain text. Our attempt is to generate Semantics Graph as a result of text mining including morphological analysis and syntax analysis.

We have developed a prototype of workflow program named "RDF Curator". By using this system, various types of documents can be automatically converted into RDF. "RDF Curator" is composed of general tools and libraries so that no special environment is needed. Hence, “RDF Curator” can be used on many platforms, such as MacOSX, Linux, and Windows (Cygwin). We expect that our system can assist human curators in constructing Semantic Graph. Although fast and high throughput, the accuracy of the present version of "RDF Curator" is lower than that of human curators. As a future task, we have to improve the accuracy of the workflow. In addition, we also plan to apply our system to analysis of network similarity

Variable Word Rate N-grams

The rate of occurrence of words is not uniform but varies from document to document. Despite this observation, parameters for conventional n-gram language models are usually derived using the assumption of a constant word rate. In this paper we investigate the use of variable word rate assumption, modelled by a Poisson distribution or a continuous mixture of Poissons. We present an approach to estimating the relative frequencies of words or n-grams taking prior information of their occurrences into account. Discounting and smoothing schemes are also considered. Using the Broadcast News task, the approach demonstrates a reduction of perplexity up to 10%.Comment: 4 pages, 4 figures, ICASSP-200

Efficient training algorithms for HMMs using incremental estimation

Typically, parameter estimation for a hidden Markov model (HMM) is performed using an expectation-maximization (EM) algorithm with the maximum-likelihood (ML) criterion. The EM algorithm is an iterative scheme that is well-defined and numerically stable, but convergence may require a large number of iterations. For speech recognition systems utilizing large amounts of training material, this results in long training times. This paper presents an incremental estimation approach to speed-up the training of HMMs without any loss of recognition performance. The algorithm selects a subset of data from the training set, updates the model parameters based on the subset, and then iterates the process until convergence of the parameters. The advantage of this approach is a substantial increase in the number of iterations of the EM algorithm per training token, which leads to faster training. In order to achieve reliable estimation from a small fraction of the complete data set at each iteration, two training criteria are studied; ML and maximum a posteriori (MAP) estimation. Experimental results show that the training of the incremental algorithms is substantially faster than the conventional (batch) method and suffers no loss of recognition performance. Furthermore, the incremental MAP based training algorithm improves performance over the batch versio

Cl-35 NQR study of lattice dynamic and magnetic property of a crystalline coordination polymer {CuCA(phz)(H2O)2}n

Copper(II) compounds {CuCA(phz)(H2O)2}n (H2CA = chloranilic acid, phz = phenazine) having a layer structure of -CuCA(H2O)2- polymer chains and phenazine was studied by 35Cl nuclear quadrupole resonance (NQR). The single NQR line observed at 35.635 MHz at 261.5 K increased to 35.918 MHz at 4.2 K. The degree of reduction of electric field gradient due to lattice vibrations was similar to that of chloranilic acid crystal. Temperature dependence of spin-lattice relaxation time, T1, of the 35Cl NQR signal below 20 K, between 20 and 210 K, and above 210 K, was explained by 1) a decrease of effective electron-spin density caused by antiferromagnetic interaction, 2) a magnetic interaction between Cl nuclear-spin and electron-spins on paramagnetic Cu(II) ions, and 3) an increasing contribution from reorientation of ligand molecules, respectively. The electron spin-exchange parameter |J| between the neighboring Cu(II) electrons was estimated to be 0.33 cm−1 from the T1 value of the range 20−210 K. Comparing this value with that of J = −1.84 cm−1 estimated from the magnetic susceptibility, it is suggested that the magnetic dipolar 2 coupling with the electron spins on Cu(II) ions must be the principal mechanism for the 35Cl NQR spin-lattice relaxation of {CuCA(phz)(H2O)2}n but a delocalization of electron spin over the chloranilate ligand have to be taken into account.</p