3096595
Analysis of a novel cylindrical 3-DoF parallel robot
Abstract In this paper, a novel three degrees of freedom (DoFs), that are two degrees of translational freedom and one degree of rotational freedom, parallel robot is proposed. The parallel robot consists of a base plate, a movable platform, and three connecting legs. Because the locus of any point on the moving platform is the subset of a cylinder if z is specified, the robot is called a cylindrical parallel robot. The inverse and forward kinematics problems are described in closed forms. And the velocity equation of the new parallel robot is given. Three kinds of singularities are presented. The workspace for the robot is analyzed systematically, especially, a new index to evaluate the mobility (In this paper, mobility means rotational capability.) of the moving platform of the robot is defined and discussed in detail. The parallel robot has wide application in the fields of industrial robots, simulators, microrobots and parallel machine tools.
7114960
On the optimum design of planar 3-DOF parallel manipulators with respect to the workspace
The design of the robotic mechanisms is one of the most important activities, because these mechanisms determine the performance characteristics of the robots. The paper concerns the issue of computer-aided design (CAD) for planar 3-DOF parallel robotic mechanisms by means of the physical model of the solution space, which can be used systematically to express the relationships between the performance criteria and all link lengths of one type of the robotic mechanism. The performance atlases of the workspace volume for the manipulators are plotted in the physical model of the solution space. The characteristics of the distribution of the workspace shapes in the physical model of the solution space are presented. The results are useful for the optimum design of the robotic mechanisms. The paper proposes a new way for the robotic CAD.
10565448
Singularity analysis of the HALF parallel manipulator with revolute actuators
This paper concerns the singularity of the half parallel manipulator, a novel three degrees of freedom (DOFs) mechanism, with revolute actuators. The parallel manipulator, proposed previously, consists of a base plate, a movable platform, and three connecting legs. It has the advantages in terms of only single-DOF joints and high rotational capability. The parallel manipulator has wide application in the fields of industrial robots, simulators, parallel machine tools and any other manipulating devices that high rotational capability is required. The inverse kinematics problem and Jacobian matrices are recalled firstly. And then all possible singularities of the manipulator are analyzed in detail. The results of the paper are very useful for the apprehension and the application of the manipulator.
14510898
Evolutionary learning of dynamic probabilistic models with large time lags
In this paper, we explore the automatic explanation of multivariate time series (MTS) through learning dynamic Bayesian networks (DBNs). We have developed an evolutionary algorithm which exploits certain characteristics of MTS in order to generate good networks as quickly as possible. We compare this algorithm to other standard learning algorithms that have traditionally been used for static Bayesian networks but are adapted for DBNs in this paper. These are extensively tested on both synthetic and real-world MTS for various aspects of efficiency and accuracy. By proposing a simple representation scheme, an efficient learning methodology, and several useful heuristics, we have found that the proposed method is more efficient for learning DBNs from MTS with large time lags, especially in time-demanding situations. © 2001 John Wiley & Sons, Inc.
6032766
A Novel Volume Constrained Smoothing Method for Meshes
In general, mesh smoothing is performed by minimizing the discrete energy function for the surface. One of the major problems in mesh smoothing is to prevent the mesh from shrinking. In this paper, we propose a novel volume constraint to address the shrinking problem in mesh smoothing. Our key observation is that the mesh can be efficiently smoothed patch by patch in a signal processing manner, and then a local volume preserving constraint can be easily imposed to the energy minimization problem associated with the small patch, called the smoothing stencil, so as to effectively avoid the mesh shrinkage. In our implementation, the smoothing stencil is the 1-ring neighboring region of an edge or a triangle. And the constrained minimization problem is solved by a 2-step approximation method for efficiency. A series of examples demonstrate that the proposed smoothing method can be applied to remove noise from a mesh or remove rough detail from an original mesh to generate a smooth model in object reconstruction and geometry modeling.
15430727
Towards Service Discovery and Subscription based on Community-of-Interest
Current service discovery and subscription are "provider-centric " indeed, which costs the consumers too many efforts and makes the wide spectrum of QoS hard to use. In this position paper, we propose a "consumer-centric" service discovery and subscription approach. The core idea is derived from the "community-of-interest (CoI)" concept, which means the services with same or similar functionalities can form a community of the consumer's interest. This approach facilitates the consumers in three ways. Firstly, it simplifies the service discovery for the consumers who can "purely" care about the functionality and qualities instead of the providers. Secondly, it optimizes the service subscription for the consumers who just subscribe the CoI instead of a single and monolithic service provider while the COI takes charge of matching and scheduling the "best-of-breed" service automatically. Thirdly, it incarnates the wide spectrum of QoS to the consumers who will face with all possible QoS supported by the services in the CoI. The supporting framework is discussed and some key technical issues are demonstrated
8835059
Computing the maximum similarity bi-clusters of gene expression data
MOTIVATIONS
Bi-clustering is an important approach in microarray data analysis. The underlying bases for using bi-clustering in the analysis of gene expression data are (1) similar genes may exhibit similar behaviors only under a subset of conditions, not all conditions, (2) genes may participate in more than one function, resulting in one regulation pattern in one context and a different pattern in another. Using bi-clustering algorithms, one can obtain sets of genes that are co-regulated under subsets of conditions.


RESULTS
We develop a polynomial time algorithm to find an optimal bi-cluster with the maximum similarity score. To our knowledge, this is the first formulation for bi-cluster problems that admits a polynomial time algorithm for optimal solutions. The algorithm works for a special case, where the bi-clusters are approximately squares. We then extend the algorithm to handle various kinds of other cases. Experiments on simulation data and real data show that the new algorithms outperform most of the existing methods in many cases. Our new algorithms have the following advantages: (1) no discretization procedure is required, (2) performs well for overlapping bi-clusters and (3) works well for additive bi-clusters.


AVAILABILITY
The software is available at http://www.cs.cityu.edu.hk/~liuxw/msbe/help.html.
21789348
Evolutionary algorithms for grouping high dimensional Email data
Grouping problems arise in many industrial and medical applications; examples include bin packing, workshop layout design, and graph colouring. This type of problem has been successfully handled using Grouping Genetic Algorithms. However in problems where there are perhaps thousands of objects to be grouped, we have found that Genetic Algorithm approaches can run into problems. This paper continues our research into a method we have developed for decomposing a large number of objects into mutually exclusive subsets where within-group dependencies are high and between-group dependencies are low. The method uses an Evolutionary Algorithm approach but where the whole population is a solution to the grouping problem rather than considering many candidate solutions. This reduces the resource overheads during computer implementation and the results are promising when compared with standard statistical methods and a Hill Climbing algorithm, all applied to email log file data.