34452017
On using flexure-hinge five-bar linkages to develop novel walking mechanisms and small-scale grippers for microrobots
120592105
Hydrodynamic modelling and CFD simulation of ferrofluids flow in magnetic targeting drug delivery
Magnetic targeting drug delivery is a method of carrying drug-loaded magnetic nanoparticles to a tissue target in the human body under the applied magnetic field. This method increases the drug concentration in the target and reduces the adverse side-effects. In this article, a mathematical model is presented to describe the hydrodynamics of ferrofluids as drug carriers flowing in a blood vessel under the applied magnetic field. Numerical simulations are performed to obtain better insight into the theoretical analysis with computational fluid dynamics. A 3D flow field of magnetic particles in an idealised blood vessel model containing an aneurysm is analysed to further understand clinical application of magnetic targeting drug delivery. Simulation samples demonstrate the important parameters leading to adequate drug delivery to the target site depending on the applied magnetic field in coincidence with reported results from animal experiments. Results of the analysis provide the important information and can suggest strategies for improving delivery in favour of the clinical application.
38041019
Towards an Efficient Self-organizing Reconfiguration Method for Self-reconfigurable Robots
This paper deals with the essential technique for self-organizing metamorphosis of self-reconfigurable robots. A general model describing self-reconfigurable robots is proposed; the model is capable of expressing the topological structure of typical 2-D and 3-D self-reconfigurable robots. Afterwards, a self-organizing metamorphic strategy of self-reconfigurable robots, based on full-discrete local intelligence, is proposed. The modules concurrently process the local interactive information. A reasonable motion sequence for modules can be obtained by means of determining and evolving the rules of modules motion. Consequently, the global self-organizing behavior will be obtained, and the complexity of the algorithm is reduced. Simulation samples are provided to illustrate this approach and demonstrate the effectiveness of the proposed strategy.
8988025
Improving STT MRAM storage density through smaller-than-worst-case transistor sizing
This paper presents a technique to improve the storage density of spin-torque transfer (STT) magnetoresistive random access memory (MRAM) in the presence of significant magnetic tunneling junction (MTJ) write current threshold variability. In conventional design practice, the nMOS transistor within each memory cell is sized to be large enough to carry a current larger than the worst-case MTJ write current threshold, leading to an increasing storage density penalty as the technology scales down. To mitigate such variability-induced storage density penalty, this paper presents a smaller-than-worst-case transistor sizing approach with the underlying theme of jointly considering memory cell transistor sizing and defect tolerance. Its effectiveness is demonstrated using 256Mb STT MRAM design at 45nm node as a test vehicle. Results show that, under a normalized write current threshold deviation of 20%, the overall memory die size can be reduced by more than 20% compared with the conventional worst-case transistor sizing design practice.
5881297
Deep Learning with Kernel Regularization for Visual Recognition
In this paper we aim to train deep neural networks for rapid visual recognition. The task is highly challenging, largely due to the lack of a meaningful regular-izer on the functions realized by the networks. We propose a novel regularization method that takes advantage of kernel methods, where an oracle kernel function represents prior knowledge about the recognition task of interest. We derive an efficient algorithm using stochastic gradient descent, and demonstrate encouraging results on a wide range of recognition tasks, in terms of both accuracy and speed.
120158207
Thermoelastic plastic metals with mass diffusion
Abstract. In this paper we develop new governing equations for contact stresses in metals. They include the coupled effects of thermal elastic-plastic theory, including balance and constitutive laws. While the results are quite general, this work had it origins in describing the metal cutting process. As one example, the resulting equations can be applied to precision and ultraprecision cutting.

42837717
Lossless Subdivision-Based Multiresolution Representation of Arbitrary Triangle Meshes Using Kite Trees
We introduce a new type of subdivision-based multiresolution representation for triangle meshes, kite trees, which has the flexibility to represent arbitrary triangle meshes losslessly. We also develop an algorithm for extracting a balanced kite tree representation of an arbitrary input mesh that preserves mesh topology and regularities in the subdivision structure. Our scheme allows us to combine surface information automatically extracted from input data with algorithmically-generated information in a single multiresolution representation and to represent the results of adaptive refinement of regular subdivision surfaces.
15326279
GCS-MA: A group communication system for mobile agents
Reliable messaging is a key component necessary for mobile agent systems. Current researches focus on reliable one-to-one message delivery to mobile agents. But how to implement a group communication system for mobile agents remains an open issue, which is a powerful block that facilitates the development of fault-tolerant mobile agent systems. In this paper, we propose a group communication system for mobile agents (GCS-MA), which includes totally ordered multicast and membership management functions. We divide a group of mobile agents into several agent clusters, and each agent cluster consists of all mobile agents residing in the same sub-network and is managed by a special module, named coordinator. Then, all coordinators form a ring-based overlay for interchanging messages between clusters. We present a token-based algorithm, an intra-cluster messaging algorithm and an inter-cluster migration algorithm to achieve atomicity and total ordering properties of multicast messages, by building a membership protocol on top of the clustering and failure detection mechanisms. Performance issues of the proposed system have been analysed through simulations. We also describe the application of the proposed system in the context of the service cooperation middleware (SCM) project.