A novel dynamic survivable routing in WDM optical networks with/without sparse wavelength conversion

In this paper, we study the dynamic survivable routing problem, both in optical networks without wavelength conversion and in optical networks with sparse wavelength conversion, and propose a novel hybrid algorithm for it based on the combination of mobile agents technique and genetic algorithms (GA). By keeping a suitable number of mobile agents in the network to cooperatively explore the network states and continuously report cycles (that are formed by two disjoint-link routes) into the routing tables, our new hybrid algorithm can promptly determine the first population of cycles for a new request based on the routing table of its source node, without the time consuming process associated with current GA-based lightpath protection schemes. We further improve the performance of our algorithm by introducing a more advanced fitness function that is suitable for both the above networks. Extensive simulation studies on the ns-2 network simulator show that our hybrid algorithm achieves a significantly lower blocking probability than the conventional survivable routing algorithms for all the cases we studied.     

Graft polymerization of vinyl acetate onto granular starch: Comparison on the potassium persulfate and ceric ammonium nitrate initiated system

This work was undertaken to discuss in depth the vital differences in the morphological development during synthesis, and properties of starch‐g‐poly‐(vinyl acetate) copolymers using two different initiators, potassium persulfate (KPS) and ceric ammonium nitrate (CAN). KPS‐initiated system gave relatively low values of grafting ratio and grafting efficiency, indicating a great tendency for the formation of poly(vinyl acetate) homopolymer (PVAc). Yet, higher values were seen for the CAN‐initiated system. Transmission electron microscope observations indicated a relatively broad distribution of latex particles for the KPS‐initiated system. The surface potential of latex particles was about ?3.5 mV, which turned out to be insufficient to maintain stability of latex particles. On the other hand, a uniform particle size distribution was found for the CAN‐initiated system, as the surface potential of latex particles was 21.5 mV. Moreover, radicals on starch molecules were generated directly through a redox reaction with positively charged ceric ion. The hydrophobic PVAc chains were thus grafted on starch, resulting in an amphiphilic graft copolymer, which provides a sufficient stabilization degree as a role of surfactant to render a relatively uniform distribution of latex particles. The synthesized starch‐g‐poly(vinyl acetate) copolymers were further converted to starch‐g‐poly(vinyl alcohol) through saponification, which were subjected to evaluations regarding the biodegradation and cell culture capability. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 102: 3017–3027, 2006     

Development of a quadruped walking robot AiDIN-III using biologically inspired kinematic analysis

This paper presents a bio-inspired mechanism design for a quadruped walking robot. The approach is derived from the observation on the behaviors of quadruped locomotion, skeletal structure, and the study on the stability of walking based on morphological analysis. In the first, we define the design parameters such as the dimensions of the body and limbs, the center of mass position, and locomotion mechanisms based on surveys on the literatures from biologists. Then, by using the parameters, we propose an useful framework for determining the design parameters of a quadruped walking robot. For implementations, we manufacture a dog-type self-contained quadruped walking robot, named AiDIN-III (Artificial Digitigrade for Natural Environment version III) and the effectiveness of the proposed idea is validated via experimental works.     

An efficient approach for damage identification based on improved machine learning using PSO-SVM

Engineering with Computers - Structural health monitoring (SHM) and Non-destructive Damage Identification (NDI) using responses of structures under dynamic excitation have an imperative role in the...     

Improving traversability of quadruped walking robots using body movement in 3D rough terrains

This paper presents a study on improving the traversability of a quadruped walking robot in 3D rough terrains. The key idea is to exploit body movement of the robot. The position and orientation of the robot are systematically adjusted and the possibility of finding a valid foothold for the next swing is maximized, which makes the robot have more chances to overcome the rough terrains. In addition, a foothold search algorithm that provides the valid foothold while maintaining a high traversability of the robot, is investigated and a gait selection algorithm is developed to help the robot avoid deadlock situations. To explain the algorithms, new concepts such as reachable area, stable area, potential search direction, and complementary kinematic margin are introduced, and the effectiveness of the algorithms is validated via simulations and experiments.     

A Knowledge Discovery System with Support for Model Selection and Visualization

The process of knowledge discovery in databases consists of several steps that are iterative and interactive. In each application, to go through this process the user has to exploit different algorithms and their settings that usually yield multiple models. Model selection, that is, the selection of appropriate models or algorithms to achieve such models, requires meta-knowledge of algorithm/model and model performance metrics. Therefore, model selection is usually a difficult task for the user. We believe that simplifying the process of model selection for the user is crucial to the success of real-life knowledge discovery activities. As opposed to most related work that aims to automate model selection, in our view model selection is a semiautomatic process, requiring an effective collaboration between the user and the discovery system. For such a collaboration, our solution is to give the user the ability to try various alternatives and to compare competing models quantitatively by performance metrics, and qualitatively by effective visualization. This paper presents our research on model selection and visualization in the development of a knowledge discovery system called D2MS. The paper addresses the motivation of model selection in knowledge discovery and related work, gives an overview of D2MS, and describes its solution to model selection and visualization. It then presents the usefulness of D2MS model selection in two case studies of discovering medical knowledge in hospital data—on meningitis and stomach cancer—using three data mining methods of decision trees, conceptual clustering, and rule induction.     

Morphology and mechanical properties of dual‐curable epoxyacrylate hybrid composites

A dual‐curable epoxyacrylate (EA) oligomer with one epoxide group and one vinyl group at each end was synthesized for the application as adhesive sealant in the liquid crystal display panels. However, after UV and thermal cure, the EA resin was brittle with a poor resistance to crack initiation and propagation. Liquid rubbers with different functional end groups were thus tried as toughening agents for the EA resin. Among all the rubber‐toughened EAs, the EA‐V5A5 added with vinyl‐terminated and amino‐terminated butadiene‐acrylonitrile copolymers (VTBN and ATBN) each at 5 phr had the highest fracture toughness, tensile strength, and elongation at break but a lower initial modulus. To raise the modulus, submicron‐sized silica particles (∼170 nm) with surface vinyl functional groups were further added to the EA‐V5A5 to prepare the hybrid composites. Because of interfacial chemical bonding provided by the surface vinyl functional groups, both modulus and fracture toughness were increased by adding silica particles, without any appreciable decrease in extensibility. For the hybrid composite at 20 phr silica particles, the initial modulus, fracture toughness, and fracture energy were raised by 10.3, 100, and 267%, respectively, when compared to the neat epoxyacrylate. Owing to their strong interfacial bonding, the increase of fracture toughness was mainly due to the crack deflection and bifurcation on silica particles, in addition to the rubber particle bridging and tearing as evidenced by SEM pictures on the fracture surface. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015 , 132, 41820.     

Concentration of cupric and nickel ions by complexation-ultrafiltration. Synergic effect of succinic acid

In ultrafiltration, high rejection of small ion species can be achieved by complexing these species with a suitable macroligand.We have studied the concentration of cupric or/and nickel ions by ultrafiltration, through the DDS GR8 membrane, using polyethylenimine as a basic macroligand. The rejections of the metallic ions increased with the pH and the concentration of the polymeric ligand as expected. The addition of succinic acid (a molecular acidic chelating) to the mixtures allowed an improvement of the retentions of these ions at all pHs studied. This indicates that positive synergic effect was obtained by the formation of a mixed complex base-metal-acid.