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.
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.
15674805
Animating reactive motions for biped locomotion
In this paper, we propose a new method for simulating reactive motions for running or walking human figures. The goal is to generate realistic animations of how humans compensate for large external forces and maintain balance while running or walking. We simulate the reactive motions of adjusting the body configuration and altering footfall locations in response to sudden external disturbance forces on the body. With our proposed method, the user first imports captured motion data of a run or walk cycle to use as the primary motion. While executing the primary motion, an external force is applied to the body. The system automatically calculates a reactive motion for the center of mass and angular momentum around the center of mass using an enhanced version of the linear inverted pendulum model. Finally, the trajectories of the generalized coordinates that realize the precalculated trajectories of the center of mass, zero moment point, and angular momentum are obtained using constrained inverse kinematics. The advantage of our method is that it is possible to calculate reactive motions for bipeds that preserve dynamic balance during locomotion, which was difficult using previous techniques. We demonstrate our results on an application that allows a user to interactively apply external perturbations to a running or walking virtual human model. We expect this technique to be useful for human animations in interactive 3D systems such as games, virtual reality, and potentially even the control of actual biped robots.
6040271
Web-Based Handwriting Education with Animated Virtual Teacher
Traditionally, in teaching handwriting, the teacher writes a character on the blackboard, and then students try to follow the teacher in order to write the same character. The teacher can check whether a student’s handwriting is spatially correct by looking at its shape but he/she is not able to verify if the student is writing in the correct stroke order with the correct number of strokes. As a result, we design a web-based handwriting education system. With our proposed system, students can stay at home to do the exercises for learning the handwriting of characters. A student’s handwriting can be captured in digital format with the information in both temporal and spatial domain and the results can be sent to the teacher for evaluation. In addition, we propose to animate a virtual teacher on the student’s terminal for demonstrating the handwriting of the characters to give students a sense of presence.
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.
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.
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.
38019992
A comparative study of different chaos based spread spectrum communication systems
Using different properties of chaotic systems, different chaos based communication schemes have been proposed in the literature. However, their performances are seldom compared. In this paper, we implement several major chaos based communication methods including chaotic spreading codes, chaotic carrier, chaos shift keying, chaotic masking and chaotic parameter modulation in a common digital communication background. Their performance in terms of bit error rate and robustness are then evaluated.
16283263
Robust classification of blurred imagery
In this paper, we present two novel approaches for the classification of blurry images. It is assumed that the blur is linear and space invariant, but that the exact blurring function is unknown. The proposed fusion-based approaches attempt to perform the simultaneous tasks of blind image restoration and classification. We call such a problem blind image fusion. The techniques are implemented using the nonnegativity and support constraints recursive inverse filtering (NAS-RIF) algorithm for blind image restoration and the Markov random field (RIRF)-based fusion method for classification by Schistad-Solberg et al. Simulation results on synthetic and real photographic data demonstrate the potential of the approaches. The algorithms are compared with one another and to situations in which blind blur removal is not attempted.