44825673
Vision-Based Recognition of Hand Shapes in Taiwanese Sign Language
The pixel-based shape representation has been sensitive to rotation. In this paper, we propose a pixel-based descriptor that is invariant with rotation and scale for the hand shape recognition in Taiwanese Sign Language (TSL). Based on the property that a hand shape is characteristic of a unique pointing direction, angle normalization is used to meet the rotation-invariant requirement. With angle normalization, the traces of class covariance matrices have been reduced almost all over the classes of hand shapes, implying a less overlap between classes. It is confirmed by the experiments that show an increase in recognition accuracy.
15699236
Facial Phoneme Extraction for Taiwanese Sign Language Recognition
We have developed a system that recognizes the facial expressions in Taiwanese Sign Language (TSL) using a phoneme-based strategy. A facial expression is decomposed into three facial phonemes of eyebrow, eye, and mouth. A fast method is proposed for locating facial phonemes. The shapes of the phonemes were then matched by the deformable template method, giving feature points representing the corresponding phonemes. The trajectories of the feature points were tracked along the video image sequence and combined to recognize the type of facial expression. The tracking techniques and the feature points have been tailored for facial features in TSL. For example, the template matching methods have been simplified for tracking eyebrows and eyes. The mouth was tracked using the optical flow method, taking lips as homogeneous patches. The experiment has been conducted on 70 image sequences covering seven facial expressions. The average recognition rate is 83.3%.
8586136
Emotion recognition using acoustic features and textual content
The paper presents an approach to emotion recognition from speech signals and textual content. In the analysis of speech signals, thirty-three acoustic features are extracted from the speech input. After principle component analysis (PCA), 14 principle components are selected for discriminative representation. In this representation, each principle component is the combination of the 33 original acoustic features and forms a feature subspace. Support vector machines (SVMs) are adopted to classify the emotional states. In text analysis, all emotional keywords and emotion modification words are manually defined. The emotion intensity levels of emotional keywords and emotion modification words are estimated from a collected emotion corpus. The final emotional state is determined based on the emotion outputs from the acoustic and textual approaches. The experimental result shows that the emotion recognition accuracy of the integrated system is better than each of the two individual approaches.
47400657
Construction of correlation immune Boolean functions
It is shown in this paper that every correlation immune Boolean function of n variables can be written as f(x) = g(xGT ), where g is an algebraic non-degenerate Boolean function of k (k ≤ n) variables and G is a generating matrix of an [n, k, d] linear code. It is known that the correlation immunity of f (x) is at least d − 1. In this paper we further prove when the correlation immunity exceeds this lower bound. A method which can theoretically search exhaustively all possible correlation immune functions is proposed, while constructions of higher order correlation immune functions as well as algebraic non-degenerate correlation immune functions are discussed in particular. It is also shown that many cryptographic properties of g can be inherited by the correlation immune function f (x) = g(xGT) which is an important property for choosing useful correlation immune functions.
12475257
ProClass Protein Family Database
ProClass is a protein family database that organizes non-redundant sequence entries into families defined collectively by PIR superfamilies and PROSITE patterns. By combining global similarities and functional motifs into a single classification scheme, ProClass helps to reveal domain and family relationships and classify multi-domain proteins. The database currently consists of >155 000 sequence entries retrieved from both PIR-International and SWISS-PROT databases. Approximately 92 000 or 60% of the ProClass entries are classified into approximately 6000 families, including a large number of new members detected by our GeneFIND family identification system. The ProClass motif collection contains approximately 72 000 motif sequences and >1300 multiple alignments for all PROSITE patterns, including >21 000 matches not listed in PROSITE and mostly detected from unique PIR sequences. To maximize family information retrieval, the database provides links to various protein family, domain, alignment and structural class databases. With its high classification rate and comprehensive family relationships, ProClass can be used to support full-scale genomic annotation. The database, now being implemented in an object-relational database management system, is available for online sequence search and record retrieval from our WWW server at http://pir.georgetown.edu/gfserver/proclass.html
27793990
Fail Safe Distributed Fault Diagnosis of Multiprocessor Systems
17356448
Web Directory Integration Using Conditional Random Fields
The purpose of integrating web directories is to transfer instances from a source to a target directory. Unlike conventional text categorization, in directory integration, there is extra information about the source directory that can be used to improve the classification accuracy. Many approaches exploit the measured similarity between two corresponding classes to enhance traditional text classifiers. These methods perform well if the topics of two classes are very similar, but they could lead to misclassification if the topics are dissimilar. We propose a directory integration approach based on the conditional random fields (CRFs) model, and model the integration process using a finite-state model. The advantage of using CRFs is that the transition features naturally include information about the relations between classes. Our results show that CRFs outperform conventional text classifiers. In addition, CRFs allow us to apply complex features to integrate the information about the contents of class and their labels. The performance of our approach can be improved by applying these features, especially for instances whose source and target classes are moderately similar
14149213
Efficient Stack Simulation for Shared Memory Set-Associative Multiprocessor Caches
We propose efficient stack simulation algorithms for shared memory multiprocessor (MP) caches. A stack simulation algorithm for write-updated MP caches is first presented. It produces the number of write-updates as well as misses for all cache configurations in a single run. We then devise a new stack simulation algorithm for writeinvalidate MP caches. Our algorithm takes into account cross-invalidation among processors, and generates the number of invalidations as well as misses for all cache configurations in a single run. A cache simulator based on our algorithms for MP caches is developed and the results on sample traces are reported. Our results show that effi cient stack simulation is a powerful technique for multi processor cache analysis.