The problem of packing circles into a domain of prescribed topology is considered. The circles need not have equal radii. The Collins-Stephenson algorithm computes such a circle packing. This algorithm is parallelized in two different ways and its performance is reported for a triangular, planar domain test case. The implementation uses the highly parallel graphics processing unit (GPU) on commodity hardware. The speedups so achieved are discussed based on a number of experiments.

Deformation is an important research topic in graphics. There are two key issues in mesh deformation: (1) self-intersection and (2) volume preserving. In this paper, we present a new method to construct a vector field for volume-preserving mesh deformation of free-form objects. Volume-preserving is an inherent feature of a curl vector field. Since the field lines of the curl vector field will never intersect with each other, a mesh deformed under a curl vector field can avoid self-intersection between field lines. Designing the vector field based on curl is useful in preserving graphic features and preventing self-intersection. Our proposed algorithm introduces distance field into vector field construction; as a result, the shape of the curl vector field is closely related to the object shape. We define the construction of the curl vector field for translation and rotation and provide some special effects such as twisting and bending. Taking into account the information of the object, this approach can provide easy and intuitive construction for free-form objects. Experimental results show that the approach works effectively in real-time animation.

We propose a robust digital watermarking algorithm for copyright protection. A stable feature is obtained by utilizing QR factorization and discrete cosine transform (DCT) techniques, and a meaningful watermark image is embedded into an image by modifying the stable feature with a quantization index modulation (QIM) method. The combination of QR factorization, DCT, and QIM techniques guarantees the robustness of the algorithm. Furthermore, an embedding location selection method is exploited to select blocks with small modifications as the embedding locations. This can minimize the embedding distortion and greatly improve the imperceptibility of our scheme. Several standard images were tested and the experimental results were compared with those of other published schemes. The results demonstrate that our proposed scheme can achieve not only better imperceptibility, but also stronger robustness against common signal processing operations and lossy compressions, such as filtering, noise addition, scaling, sharpening, rotation, cropping, and JPEG/JPEG2000 compression.

In the training of feedforward neural networks, it is usually suggested that the initial weights should be small in magnitude in order to prevent premature saturation. The aim of this paper is to point out the other side of the story: In some cases, the gradient of the error functions is zero not only for infinitely large weights but also for zero weights. Slow convergence in the beginning of the training procedure is often the result of sufficiently small initial weights. Therefore, we suggest that, in these cases, the initial values of the weights should be neither too large, nor too small. For instance, a typical range of choices of the initial weights might be something like (?0.4, ?0.1)∪(0.1,0.4), rather than (?0.1, 0.1) as suggested by the usual strategy. Our theory that medium size weights should be used has also been extended to a few commonly used transfer functions and error functions. Numerical experiments are carried out to support our theoretical findings.

We present an iterative linear quadratic regulator (ILQR) method for trajectory tracking control of a wheeled mobile robot system. The proposed scheme involves a kinematic model linearization technique, a global trajectory generation algorithm, and trajectory tracking controller design. A lattice planner, which searches over a 3D (x, y, θ) configuration space, is adopted to generate the global trajectory. The ILQR method is used to design a local trajectory tracking controller. The effectiveness of the proposed method is demonstrated in simulation and experiment with a significantly asymmetric differential drive robot. The performance of the local controller is analyzed and compared with that of the existing linear quadratic regulator (LQR) method. According to the experiments, the new controller improves the control sequences (v, ω) iteratively and produces slightly better results. Specifically, two trajectories, ‘S’ and ‘8’ courses, are followed with sufficient accuracy using the proposed controller.

We develop a multi-objective model in a multi-product inventory system. The proposed model is a joint replenishment problem (JRP) that has two objective functions. The first one is minimization of total ordering and inventory holding costs, which is the same objective function as the classic JRP. To increase the applicability of the proposed model, we suppose that transportation cost is independent of time, is not a part of holding cost, and is calculated based on the maximum of stored inventory, as is the case in many real inventory problems. Thus, the second objective function is minimization of total transportation cost. To solve this problem three efficient algorithms are proposed. First, the RAND algorithm, called the best heuristic algorithm for solving the JRP, is modified to be applicable for the proposed problem. A multi-objective genetic algorithm (MOGA) is developed as the second algorithm to solve the problem. Finally, the model is solved by a new algorithm that is a combination of the RAND algorithm and MOGA. The performances of these algorithms are then compared with those of the previous approaches and with each other, and the findings imply their ability in finding Pareto optimal solutions to 3200 randomly produced problems.

Due to the shortage of suitable research methods for real-time and long-term observation of oceans, an innovative approach that can provide abundant power and wide bandwidth is being developed worldwide for undersea instruments. In this paper, we develop a direct current (DC) power system which is applied to a multi-node cabled ocean observatory system named ZERO (Zhejiang University Experimental and Research Observatory). The system addresses significant issues ranging from terrestrial facility to subsea infrastructure, and focuses on using appropriate methods to deal with several key challenges, including delivery, conversion, distribution, and management of power, and heat dissipation in pressure vessels. A basic laboratory platform consisting of a shore station, a primary node in a water tank, and a secondary node in a deep-sea simulation chamber under 42 MPa pressure was built and fully tested. An improved secondary node was deployed in Monterey Bay in California for a deep-sea trial. An 11-day laboratory test and a half-year sea trial proved that the DC power system based on our proposed methods is viable for the underwater multi-node observatory system.

This paper presents a method to detect the quantization index modulation (QIM) steganography in G.723.1 bit stream. We show that the distribution of each quantization index (codeword) in the quantization index sequence has unbalanced and correlated characteristics. We present the designs of statistical models to extract the quantitative feature vectors of these characteristics. Combining the extracted vectors with the support vector machine, we build the classifier for detecting the QIM steganography in G.723.1 bit stream. The experiment shows that the method has far better performance than the existing blind detection method which extracts the feature vector in an uncompressed domain. The recall and precision of our method are all more than 90% even for a compressed bit stream duration as low as 3.6 s.