Tsinghua Science and Technology最新文献

Creating realistic virtual humans has been a challenging objective in computer science research for some time. This paper describes an integrated framework for modeling virtual humans with a high level of autonomy. The framework seeks to reproduce human-like believable behavior and movement in virtual humans in a virtual environment. The framework includes a visual and auditory information perception module, a decision network based behavior decision module, and a hierarchical autonomous motion control module. These cooperate to model realistic autonomous individual behavior for virtual humans in real-time interactive virtual environments. The framework was tested in a simulated virtual environment system to demonstrate the ability of the framework to create autonomous, perceptive and intelligent virtual humans in real-time virtual environments.

This paper describes the effect of channel estimation error (CEE) on the performance of distributed estimations of an unknown parameter in a wireless sensor network. Both the classical and Bayesian estimators are derived to mitigate the adverse effects caused by the CEE. Power scheduling among sensors and the power ratio between the training and data transmission at each individual node are optimized by directly minimizing the final average mean squared error to compensate for the CEE. A closed-form power scheduling policy is given for a homogeneous environment, which shows that more than 50% of the power should be allocated to sensor observation transmissions. For an inhomogeneous environment, a multilevel waterfilling type solution is developed for the power scheduling among sensors for only the sum power constraint with a “cave” waterfilling solution for both the sum and individual power constraints. Simulations show that the proposed power scheduling schemes achieve better performance than the equal power scheduling scheme.

This paper describes a parallel fast convolution back-projection algorithm design for radar image reconstruction. State-of-the-art general purpose graphic processing units (GPGPU) were utilized to accelerate the processing. The implementation achieves much better performance than conventional processing systems, with a speedup of more than 890 times on NVIDIA Tesla C1060 supercomputing cards compared to an Intel P4 2.4 GHz CPU. 256×256 pixel images could be reconstructed within 6.3 s, which makes real-time imaging possible. Six platforms were tested and compared. The results show that the GPGPU super-computing system has great potential for radar image processing.

The number of equivalent keys in multivariate cryptosystem is closely related to the scheme security. This study analyzes the structure of the private key space in some multivariate schemes. The result gives the lower bounds on the number of equivalent keys of some variants of the hidden field equation (HFE) scheme including plus, minus-plus, embedding, and internal perturbation. This method estimates the number of invertible transformations which maintain the form of the central map invariant. Furthermore, a formal proof shows that the two modifications of fixing and embedding are equivalent in security analyses of multivariate schemes. Also this paper corrects previous proofs in Wolf's work on the number of equivalent keys in HFEv, the unbalanced oil and vinegar (UOV) scheme, and the stepwise triangular systems (STS).

Digital mobile telecommunication systems, such as the global system for mobile (GSM) system, want to further improve speech communication quality without changing the channel encoders and decoders. Speech quality is most affected by residual bit errors in received speech frames. Conventional methods use binary decision strategies for error detection and concealment in frames. This paper presents a multi-level error detection and concealment algorithm for GSM full rate speech codec systems. The algorithm uses multi-source knowledge to detect and conceal speech frame errors at the frame, parameter, and even bit levels. Tests show that most corrupted frames can be appropriately concealed by this algorithm, resulting in MOS gains of more than 50% for real-world data tests.

Assembly line balancing involves assigning a series of task elements to uniform sequential stations with certain restrictions. Decision makers often discover that a task assignment which is optimal with respect to a deterministic or stochastic/fuzzy model yields quite poor performance in reality. In real environments, assembly line balancing robustness is a more appropriate decision selection guide. A robust model based on the α worst case scenario is developed to compensate for the drawbacks of traditional robust criteria. A robust genetic algorithm is used to solve the problem. Comprehensive computational experiments to study the effect of the solution procedure show that the model generates more flexible robust solutions. Careful tuning the value of α allows the decision maker to balance robustness and conservativeness of assembly line task element assignments.

This paper considers the distributed estimation of a source parameter using quantized sensor observations in a wireless sensor network with noisy channels. Repetition codes are used to transmit quantization bits of sensor observations and a quasi best linear unbiased estimate is constructed to estimate the source parameter. Simulations show that the estimation scheme achieves a better power and spectral efficiency than the previous scheme.

Coupled map lattices (CML) have been recently used to construct ciphers. However, the complicated operations on real numbers make these CML-based ciphers difficult to analyze. This paper presents a new stream cipher with the discretized CML which operates on binary numbers. When discretizing the CML, the effective network structure is explicitly preserved to improve the confusion and diffusion. The proposed cipher can be easily analyzed using proper cryptographic techniques and has good security. The cipher has a strict lower bound on the period length of 2⁶⁴ and its key setup scheme achieves enough diffusion. The keystreams pass all of the NIST statistical randomness tests and have good randomness properties. In addition the cipher is resistant to the guess-and-determine attack.

Two characteristics of traffic flows make the vehicle departure headways in Beijing, China different from that in Atlanta, USA. Urban traffic flows in China are often hindered by pedestrians at intersections and queuing vehicles often cannot be totally discharged during the green time, so most signalized intersections are over-saturated in the day time. The first characteristic makes the departure headways of the first and second vehicles in Beijing depend heavily on the start-up situations (with or without interference). The departure headways of the 3rd to 5th vehicles in Beijing have similar characteristics to those in Atlanta. The second characteristic makes the departure headways after the 5th vehicle significantly different from those in Atlanta. These comparisons show that the conventional delay estimate methods and signal control algorithms may not fit Chinese scenarios, which makes imported intelligent traffic control systems not work well in China without calibrations.

An immune algorithm-based approach was developed to optimize a feedforward neural network. The network architecture, activation functions, and training method were encoded as individuals with an appropriate method for individual selection. The immune feedforward neural network is then applied to fault detection of water quality monitoring equipment. This gives better performance than a feedforward neural network.