Jinxiang Dong

A collaborative approach to assembly sequence planning

Distributed product development requires collaborative work among team members. For the sake of supporting assembly planning activities involving geographically dispersed designers, this paper presents an approach of collaborative assembly sequence planning to validate the assemblability of parts and subassemblies rapidly. In order to increase the planning efficiency and support the collaborative planning, role-based model is exploited to compress or simplify the product. In role-based model, the B-rep models are simplified according to the permissions associated with the role, so the surfaces invisible from outside of the model are removed. In collaborative planning, the planning tasks are assigned to different designers that carry out the collaborative planning, respectively. In this paper, a knowledge-based approach is proposed to the assembly sequence planning problem. This research shows that the typical or standard CSBAT (Connection Semantics Based Assembly Tree) can be applied to a given assembly problem. This paper presents the structure of the Co-ASP (Collaborative Assembly Sequence Planning System) and provides an example to illustrate the collaborative planning approach.

Designated-receiver proxy signature scheme for electronic commerce

Proxy signature is the solution to delegation of signing capabilities in electronic world. Proxy signatures are signature schemes that an original signer delegates his signing capability to a proxy signer, and the proxy signer creates signatures on behalf of the original signer. To avoid the misuse of proxy signatures, the original signer hopes that he can restrict the signing capability delegated to the proxy signers. In this paper, a designated-receiver proxy signature scheme is proposed. In this scheme, an original signer nominates a person as signature receiver when he delegates his signing capability to a proxy signer, and the proxy signer can generate valid proxy signature on behalf of the original signer which none but the nominated receiver can verify and accept, thus the misuse of proxy signature is avoided. The security of the proposed signature scheme is analyzed. The scheme will be applied in e/spl I.bar/commerce and other fields.

Droplet: a virtual brush model to simulate Chinese calligraphy and painting

This paper proposes a virtual brush model based on droplet operation to simulate Chinese calligraphy and traditional Chinese painting in real time. Two ways of applying droplet model to virtual calligraphy and painting are discussed in detail. The second droplet model is more elaborated and can produce more vivid results while being slightly more time-consuming. The novel feature of the proposed droplet virtual brush model successfully enables the simulation painting system to overcome the poor expressional ability of virtual brush based on particle system and avoids the complex evaluation of physical brush with solid model. The model, derived from the actual calligraphy and painting experience, due to the simplicity of the droplet operation and its powerful expressive ability, considerably improves the performance of the simulation system and maintains painting effect comparable with real brush by supporting special Chinese brush effect such as dry brush, feng and stroke diffusion.

Orthogonal Neighborhood Preserving Embedding for Face Recognition

In this paper, we propose a new algorithm called Orthogonal Neighborhood Preserving Embedding (ONPE) for face recognition. ONPE can preserve local geometry information and is based on the local linearity assumption that each data point and its k nearest neighbors lie on a linear manifold locally embedded in the image space. ONPE is based on Neighborhood Preserving Embedding (NPE), but overcomes the metric distortion problem of NPE, while metric distortion usually leads to performance degradation. Besides, we propose a classification method (ONPC) based on the ONPE, which use local label propagation method in the reduced space for face recognition. ONPC is based on the natural assumption that the local neighborhood information is also preserved in reduced space, and the label of a data point can be obtained in the reduced space by the labels of its neighbors. Experimental results on two face databases demonstrate the effectiveness of our proposed method.

Incremental manifold learning via tangent space alignment

Several algorithms have been proposed to analysis the structure of high-dimensional data based on the notion of manifold learning. They have been used to extract the intrinsic characteristic of different type of high-dimensional data by performing nonlinear dimensionality reduction. Most of them operate in a “batch” mode and cannot be efficiently applied when data are collected sequentially. In this paper, we proposed an incremental version (ILTSA) of LTSA (Local Tangent Space Alignment), which is one of the key manifold learning algorithms. Besides, a landmark version of LTSA (LLTSA) is proposed, where landmarks are selected based on LASSO regression, which is well known to favor sparse approximations because it uses regularization with l1 norm. Furthermore, an incremental version (ILLTSA) of LLTSA is also proposed. Experimental results on synthetic data and real word data sets demonstrate the effectivity of our algorithms.

Chaos and Graphics: Gradient field based inhomogeneous volumetric mesh deformation for maxillofacial surgery simulation

This paper presents a novel inhomogeneous volumetric mesh deformation approach by gradient field manipulation, and uses it for maxillofacial surgery simulation. The study is inspired by the state-of-the-art surface deformation techniques based on differential representations. Working in the volumetric domain instead of on only the surface can preserve the volumetric details much better, avoid local self-intersections, and achieve better deformation propagation because of the internal mesh connections. By integrating the mesh cell material stiffness parameter into our new discrete volumetric Laplacian operator, it is very convenient to incorporate inhomogeneous materials into the deformation framework. In addition, the system matrix for solving the volumetric harmonic field to handle the local transformation problem is the same used for Poisson reconstruction equation, thus it requires solving essentially only one global linear system. The system is easy to use, and can accept explicit rotational constraints, or only translational constraints to drive the deformation. One typical maxillofacial surgery case was simulated by the new methodology with inhomogeneous material estimated directly from CT data, and compared to the commonly used finite element method (FEM) approach. The results demonstrated that the deformation methodology achieved good accuracy, as well as interactive performance. Therefore, the usage of our volumetric mesh deformation approach is relevant and suitable for daily clinical practice.

Conflicts classification and solving for collaborative feature modeling

Based on the analysis of feature modeling activities in a collaborative environment, a definition and a classification of concurrency conflicts have been presented. A feature adjustment method is proposed to solve the conflicts, an enhanced naming mechanism for the collaborative feature modeling to preserve the design intentions, and a process for the non-locked multi-client collaborative design. The algorithms have been implemented in a prototype system integrating C++, Java3D and VRML, and CORBA technologies. Flexibility and efficiency in collaborative feature modeling environment have been achieved in our system.

A Database Encryption Scheme for Enhanced Security and Easy Sharing

Database encryption is a crucial technique in the security mechanisms of database. It is widely recognized as one of the key issues of data security. Current techniques of sharing the keys and the encrypted data for databases are neither convenient nor flexible in the real applications. Inspired by the PGP technique, we propose a novel database encryption scheme for enhanced data sharing inside a database, while preserving data privacy. It is characterized by both the fast speed of the conventional encryption and the convenience of key distribution of public key encryption. It also provides secured storage for security related data and effective key management, which enables the encrypted data to be shared conveniently. The scheme has been implemented and successfully applied on Oscar, a commercial DBMS developed by us

Bottom-up discovery of frequent rooted unordered subtrees

In the past decade, XML has emerged as the standard language for information exchanging over the Internet. Due to its tree-structure paradigm, XML is superior for its capability of storing, querying, and manipulating complex data. Therefore, discovering frequent tree patterns over tree-structured data has become an interesting topic for XML data management. In this paper, we propose a tree mining algorithm, named BUXMiner, for finding a special class of frequent trees, called rooted unordered trees, from a tree-structured database. BUXMiner employs an efficient bottom-up approach to enumerate all candidate trees over a compact global tree guide and computes the frequent trees based on the tree guide. In addition to BUXMiner, we also propose a mining approach called BUMXMiner to discover the maximal frequent rooted unordered trees. We compare BUXMiner with previous tree-structure mining algorithms, namely XQPMinerTID and FastXMiner, which were also proposed to discover rooted unordered trees. The experimental results show that our algorithm outperforms XQPMinerTID and FastXMiner in terms of efficiency. The performance results from real-world applications also indicate the usefulness of our proposed tree mining algorithms in a variety of web applications, such as analysis of web page access patterns and mining frequent XML query patterns for caching.

Selective image abstraction

We present a novel and convenient method for producing selective stylized simplification of images. The user uses a brush to interactively mark certain areas of the input image which are to be left unaltered. Boundaries of these areas are then automatically optimized to underlying object boundaries in the image. Our method then performs stylized simplification of the unmarked areas, while preserving the marked areas. The method ensures a smooth transition between stylized and unaltered regions to leave a mixed reality image which combines the real and the abstract. Stylized simplification is performed using nonlinear diffusion, which can generate sophisticated results. We modify the classic model of nonlinear diffusion to incorporate bilateral filtering; we apply diffusion speed control of each pixel based on the user’s input. The level of simplification can be controlled intuitively based on the diffusion time; another parameter controls the abstraction style, giving a simple and intuitive user interface. Our contributions include a simple-to-use method to produce a novel NPR style and a modified nonlinear diffusion model suited to this selective stylized simplification task. Experimental results show that the final mixed reality results are harmonious.