18767073
Fitting Ellipses to a Region with Application in Calligraphic Stroke Reconstruction
Given a region, it is a challenge to find a set of primitive shapes such as rectangles, circles or ellipses to cover it. This is in fact a set-covering problem, which is known to be NP-hard. The focus of this paper is on fitting a set of ellipses onto an image region. This problem was first formulated by identifying a number of criteria required for the ellipse fitting. A solution is then proposed for automatically determining the set of ellipses that best fits onto an image region. The proposed ellipse fitting algorithm has also been applied to strokes forming characters of Chinese calligraphic artwork. The results show that our proposed algorithm generates ellipses fitting onto stroke regions and capturing the characteristics of the strokes during turning, tilting and back-trace.
18854339
Brush Writing Style Classification from Individual Chinese Characters
Chinese calligraphic artwork usually contains a few or even a single character. In order to perform automatic brush writing style classification on these kinds of Chinese calligraphic images, existing approaches need to be modified because they assume that many characters of the same style exist in the input image. A novel approach is proposed to address the brush writing style classification problem for single-character Chinese calligraphic images by combining the texture analysis and the structural information through a set of parameterised ellipses
37235208
Model-Based Analysis of Chinese Calligraphy Images
206606389
e-Learning Martial Arts
Traditionally, when people want to learn martial arts, they have to go to training clubs and learn under the coach together with the other students. To reduce the tuition fees, there are usually a lot of students under a single coach and hence, it is difficult for the students to get enough suggestions in the class. It would be far easier if the students could practice themselves at home and ask for suggestions from a virtual coach in the computer. Occasionally, in case they find difficulties going to the next step, they may then approach the real coach for suggestions and training. In this paper, we propose such a training system based on the motion capture system. The system automatically analyzes the motions of the player and gives suggestions. The students can also view the martial art techniques stored in the system or their own techniques captured by the motion capture system from various points of view in order to gain objective ideas of the techniques.
8282971
Protein Subcellular Localization Based on Psi-blast and Machine Learning
Subcellular location is an important functional annotation of proteins. An automatic, reliable and efficient prediction system for protein subcellular localization is necessary for large-scale genome analysis. This paper describes a protein subcellular localization method which extracts features from protein profiles rather than from amino acid sequences. The protein profile represents a protein family, discards part of the sequence information that is not conserved throughout the family and therefore is more sensitive than the amino acid sequence. The amino acid compositions of whole profile and the N-terminus of the profile are extracted, respectively, to train and test the probabilistic neural network classifiers. On two benchmark datasets, the overall accuracies of the proposed method reach 89.1% and 68.9%, respectively. The prediction results show that the proposed method perform better than those methods based on amino acid sequences. The prediction results of the proposed method are also compared with Subloc on two redundance-reduced datasets.
206606372
A Web-Based Chinese Handwriting Education System with Automatic Feedback and Analysis
We propose a web-based Chinese handwriting system that allows students to learn Chinese handwriting at anytime and anywhere. The system combines technologies such as electronic ink, database, Flash animations, and pattern recognition technique to provide students with an intelligent and effective learning environment. In particular, our system contains an Automatic Feedback and Analysis (AFA) tool that can check multiple kinds of handwriting mistakes and provide useful feedback to the user. Survey results show that most users agreed that our proposed system can help them to learn Chinese handwriting more efficiently as well as reducing teachers’ workload. The user evaluation results suggest that it takes less time for users to learn Chinese handwriting with our system than with traditional teaching method.
33568725
A novel M-ary chaotic spread spectrum communication scheme for DSRC system in ITS
In this paper, a novel non-coherent M-ary chaotic spread spectrum communication scheme is proposed for dedicated short range communications (DSRC) in intelligent transportation systems (ITS). The proposed scheme encodes the M-ary information symbols on to the bifurcation parameter of a chaotic system. This new chaotic communication scheme exploits the ergodic properties of chaotic signals for demodulating the received signal. The proposed scheme is basically non-coherent which eliminates the complex synchronization procedure. Furthermore, the proposed scheme utilizes a low complexity multipath mitigation technique to combat fading. Performance analysis shows the superior communication performance of the proposed chaotic spread spectrum scheme over conventional spread spectrum schemes in rapid multipath fading environments. Thus, the developed scheme is attractive in terms of communication performance, multipath mitigation, and system complexity.
17170661
On finite automata with limited nondeterminism
Abstract. We develop a new algorithm for determining if a given nondeterministic finite automaton is limited in nondeterminism. From this, we show that the number of nondeterministic moves of a finite automaton, if limited, is bounded by 
$2^{n} - 2$ where 
$n$ is the number of states. If the finite automaton is over a one-letter alphabet, using Gohon's result the number of nondeterministic moves, if limited, is less than 
$n^{2}$. In both cases, we present families of finite automata demonstrating that the upper bounds obtained are almost tight. We also show that the limitedness problem of the number of nondeterministic moves of finite automata is PSPACE-hard. Since the problem is already known to be in PSPACE, it is therefore PSPACE-complete.

30262171
Improving defect removal effectiveness for software development
The paper first reviews the industry statistics on defects, presents a model of defect removal, then develops the relationships between the defect removal effectiveness of different defect removal phases. The defect removal effectiveness of an average organization is determined based on published data. Combining the industry data with the defect removal model, insights into improvement of the defect removal process can be gained. It is determined that the defect removal effectiveness of individual phases cannot be higher than that of the overall development process. Also, introducing inspection to the software development process will certainly allow an average organization to achieve higher defect removal effectiveness.
38923052
Reconstruction of piecewise chaotic dynamics using a multiple model approach
In this paper we propose using a multiple model (MM) predictor to reconstruct piecewise chaotic dynamic. The motivation relies on the observation that conventional single model is usually incapable of reconstructing the piecewise dynamic properly because a piecewise map is non-differentiable. In our approach, multiple radial basis function (RBF) neural nets are used to model the dynamic in different partition intervals. Switching between different intervals could be estimated by a nonlinear gate model. In particular, an Expectation-Maximization (EM) algorithm is employed to train the MM-RBF. Compared to the conventional approach, the proposed MM is shown to greatly improve the reconstruction performance for piecewise chaotic dynamic. We further apply it to combat channel distortions in an analog chaotic spread spectrum (SS) system. It is found that the proposed method has satisfactory equalization performance even when channel effect is strong.
11779035
Chaotic binary sequences for efficient wireless multipath channel estimation
This paper presents a better binary sequence design for efficient wireless multipath channel estimation. Chaotic binary sequences with better properties than conventional maximal length sequences are obtained through an optimization algorithm based on DNA computation. The proposed method is attractive due to its ability to generate binary sequences for specific design criteria. The generated chaotic binary sequences have superior performance compared to maximal length sequences and have complexity similar to the levels of shift register implementation. The effectiveness of the proposed method was evaluated for sequence design for frequency domain channel estimation. Simulation results clearly show the improved performance of the sequence obtained using the proposed scheme over the maximal length sequence. Further, the proposed scheme is not only limited to channel estimation sequence design but can be applied to various communication system design problems.