Multiple statistical models for soft decision in noisy speech enhancement

Most speech enhancement algorithms are based on the assumption that speech and noise are both Gaussian in the discrete cosine transform (DCT) domain. For further enhancement of noisy speech in the DCT domain, we consider multiple statistical distributions (i.e., Gaussian, Laplacian and Gamma) as a set of candidates to model the noise and speech. We first use the goodness-of-fit (GOF) test in order to measure how far the assumed model deviate from the actual distribution for each DCT component of noisy speech. Our evaluations illustrate that the best candidate is assigned to each frequency bin depending on the Signal-to-Noise-Ratio (SNR) and the Power Spectral Flatness Measure (PSFM). In particular, since the PSFM exhibits a strong relation with the best statistical fit we employ a simple recursive estimation of the PSFM in the model selection. The proposed speech enhancement algorithm employs a soft estimate of the speech absence probability (SAP) separately for each frequency bin according to the selected distribution. Both objective and subjective tests are performed for the evaluation of the proposed algorithms on a large speech database, for various SNR values and types of background noise. Our evaluations show that the proposed soft decision scheme based on multiple statistical modeling or the PSFM provides further speech quality enhancement compared with recent methods through a number of subjective and objective tests.     

Face recognition under arbitrary illumination using illuminated exemplars

Recently, the importance of face recognition has been increasingly emphasized since popular CCD cameras are distributed to various applications. However, facial images are dramatically changed by lighting variations, so that facial appearance changes caused serious performance degradation in face recognition. Many researchers have tried to overcome these illumination problems using diverse approaches, which have required a multiple registered images per person or the prior knowledge of lighting conditions. In this paper, we propose a new method for face recognition under arbitrary lighting conditions, given only a single registered image and training data under unknown illuminations. Our proposed method is based on the illuminated exemplars which are synthesized from photometric stereo images of training data. The linear combination of illuminated exemplars can represent the new face and the weighted coefficients of those illuminated exemplars are used as identity signature. We make experiments for verifying our approach and compare it with two traditional approaches. As a result, higher recognition rates are reported in these experiments using the illumination subset of Max-Planck Institute face database and Korean face database.     

The BYY annealing learning algorithm for Gaussian mixture with automated model selection

Bayesian Ying-Yang (BYY) learning has provided a new mechanism that makes parameter learning with automated model selection via maximizing a harmony function on a backward architecture of the BYY system for the Gaussian mixture. However, since there are a large number of local maxima for the harmony function, any local searching algorithm, such as the hard-cut EM algorithm, does not work well. In order to overcome this difficulty, we propose a simulated annealing learning algorithm to search the global maximum of the harmony function, being expressed as a kind of deterministic annealing EM procedure. It is demonstrated by the simulation experiments that this BYY annealing learning algorithm can efficiently and automatically determine the number of clusters or Gaussians during the learning process. Moreover, the BYY annealing learning algorithm is successfully applied to two real-life data sets, including Iris data classification and unsupervised color image segmentation.     

A discriminant analysis using composite features for classification problems

In this paper, we propose a new discriminant analysis using composite features for pattern classification. A composite feature consists of a number of primitive features, each of which corresponds to an input variable. The covariance of composite features is obtained from the inner product of composite features and can be considered as a generalized form of the covariance of primitive features. It contains information on statistical dependency among multiple primitive features. A discriminant analysis (C-LDA) using the covariance of composite features is a generalization of the linear discriminant analysis (LDA). Unlike LDA, the number of extracted features can be larger than the number of classes in C-LDA, which is a desirable property especially for binary classification problems. Experimental results on several data sets indicate that C-LDA provides better classification results than other methods based on primitive features.     

Improvement of jitter transfer characteristics of a 9.95328 Gb/s data recovery DLL using saw filter

This paper presents a design of a high-speed data recovery circuit for non return zero (NRZ) data transmission using delay-locked loop (DLL) with SAW filter. The jitter generation of the circuit is decreased by adjusting the loop gain in DLL whereas surface acoustic wave (SAW) filter with low centered frequency (f_c) improves the jitter transfer function of DLL. It is seen that the circuit using SAW filter of f_c = 1.24416 GHz and Q = 1000 provides the cut off frequency of about 600 kHz which is ∼10 times lower than that of conventional DLL circuit.     

Insider attacks on multi-proxy multi-signature schemes

In 2004, Hwang and Chen demonstrated new multi-proxy multi-signature schemes that allow a group of authorized proxy signers to sign messages on behalf of a group of original signers. Later, Lyuu and Wu pointed out Hwang et al.’s schemes were not secure and then proposed a modified scheme. They claimed that their modified schemes were secure. But in this paper we show a new attack on the Lyuu-Wu et al.’s schemes. Moreover, the original Hwang-Chen’s schemes are also vulnerable to this insider attack. Furthermore, we point out some improvements for the Lyuu-Wu scheme and Hwang-Chen schemes according to Wang et al.’s methods [Wang GL, Han XX, Zhu B. On the security of two threshold signature schemes with traceable signers. In: Applied Cryptography and Network Security (ACNS 2003). Lect Notes Comput Sci (LNCS), vol. 2846, Springer-Verlag; 2003. p. 111-222]. These improvements can resist our insider attack.     

Fraternities and ITexts: Composing in the post-industrial turn

Web sites are a ubiquitous Internet genre employed by student organizations. This article investigates the role of a web site in an Interfraternity Council at a large midwestern university in the United States. The web site is examined through the work of Anthony Giddens, specifically his structuration theory, and the recent research on ITexts. In turn, the composing process required for such IText creation and maintenance is considered in light of the complicated network of forces and restraints surrounding the Interfraternity Council and the web site. By positioning the web site as an IText, the article revisits the field's understanding of genre as well as the knowledge creation surrounding such genres. Ultimately, the article contends that it may be in everyday (I)texts, such as organization web sites, where the intertwined shifts to post-industrialism and an emphasis on multiliteracies are most recognizable and accessible for teachers of writing.     

Weathering wikis: Net-based learning meets political science in a South African university

Wikis represent flexible tools functioning as open-ended environments for collaboration while also offering process and group writing support. Here we focus on a project to innovate the use of wikis for collaborative writing within student groups in a final-year undergraduate political science course. The primary questions guiding our research were in what ways could wikis assist collaborative learning in an undergraduate course in political science and how we could support educators’ in the effective use of wikis? Curiously, wikis may serve as a mediating artifact for collaborative writing even among students who are reluctant to post online drafts. The paper raises questions concerning the nature and limits of lecturer and tutor power to deliver transformative educational innovations in relation to the capacity of students to embrace, comply with, or resist such innovation. In analysing the negotiation of the use of wikis in the course by and among the lecturer, tutors, and students, we draw on two principles in activity theory, which Yrjö Engeström argued are central to his model of expansive learning: multi-voicedness and contradictions [Engeström, Yrjö. (1987). Learning by expanding: An activity-theoretical approach to developmental research. Helsinki: Orienta-Konsultit; Engeström, Yrjö. (2001). Expansive learning at work: Toward an activity theoretical reconceptualization. Journal of Education and Work14(1), 133-156.]. We add a third principle, transparency, to more fully capture what we observed.     

Applying rough set theory in the function group analysis for phenolic amide compounds

This research synthesized and assayed 15 phenolic amide compounds for antioxidant activity. The principle approach was based on the antioxidant activity (IC₅₀) values of various R₁-R₅ in the phenolic amide compound backbones for investigating the impact in functional groups. Through the analysis and calculation by rough set mathematics, it was determined that R₅ was responsible for the most significant impact on antioxidant activity. This finding indicated that the functional group at the para-position in the phenethylamine backbone was the most influential, followed by R₂ and R₄, indicating the critical role of the functional group at the meta-position. This result was consistent with the actual circumstance. In the future, functional groups at different positions should be synthesized to increase the number of compounds followed by integrating the mathematics model and computer toolbox to validate the accuracy and rationality.