Synthetic dry adhesives inspired by the nano-and micro-scale hairs found on the feet of geckos and some spiders have beendeveloped for almost a decade. Elastomeric single level micro-scale mushroom shaped fibres are c...Synthetic dry adhesives inspired by the nano-and micro-scale hairs found on the feet of geckos and some spiders have beendeveloped for almost a decade. Elastomeric single level micro-scale mushroom shaped fibres are currently able to function evenbetter than natural dry adhesives on smooth surfaces under normal loading. However, the adhesion of these single level syntheticdry adhesives on rough surfaces is still not optimal because of the reduced contact surface area. In nature, contact area ismaximized by hierarchically structuring different scales of fibres capable of conforming surface roughness. In this paper, weadapt the nature’s solution arid propose a novel dual-level hierarchical adhesive design using Polydimethylsiloxane (PDMS),which is tested under peel loading at different orientations. A negative macro-scale mold is manufactured by using a laser cutterto define holes in a Poly(methyl methacrylate) (PMMA) plate. After casting PDMS macro-scale fibres by using the obtainedPMMA mold, a previously prepared micro-fibre adhesive is bonded to the macro-scale fibre substrate. Once the bondingpolymer is cured, the micro-fibre adhesive is cut to form macro scale mushroom caps. Each macro-fibre of the resulting hierarchicaladhesive is able to conform to loads applied in different directions. The dual-level structure enhances the peel strengthon smooth surfaces compared to a single-level dry adhesive, but also weakens the shear strength of the adhesive for a given areain contact. The adhesive appears to be very performance sensitive to the specific size of the fibre tips, and experiments indicatethat designing hierarchical structures is not as simple as placing multiple scales of fibres on top of one another, but can requiresignificant design optimization to enhance the contact mechanics and adhesion strength.展开更多
A multilevel secure relation hierarchical data model for multilevel secure database is extended from the relation hierarchical data model in single level environment in this paper. Based on the model, an upper lowe...A multilevel secure relation hierarchical data model for multilevel secure database is extended from the relation hierarchical data model in single level environment in this paper. Based on the model, an upper lower layer relationalintegrity is presented after we analyze and eliminate the covert channels caused by the database integrity.Two SQL statements are extended to process polyinstantiation in the multilevel secure environment.The system based on the multilevel secure relation hierarchical data model is capable of integratively storing and manipulating complicated objects ( e.g. , multilevel spatial data) and conventional data ( e.g. , integer, real number and character string) in multilevel secure database.展开更多
This article is an addendum to the 2001 paper [1] which investigated an approach to hierarchical clustering based on the level sets of a density function induced on data points in a d-dimensional feature space. We ref...This article is an addendum to the 2001 paper [1] which investigated an approach to hierarchical clustering based on the level sets of a density function induced on data points in a d-dimensional feature space. We refer to this as the “level-sets approach” to hierarchical clustering. The density functions considered in [1] were those formed as the sum of identical radial basis functions centered at the data points, each radial basis function assumed to be continuous, monotone decreasing, convex on every ray, and rising to positive infinity at its center point. Such a framework can be investigated with respect to both the Euclidean (L2) and Manhattan (L1) metrics. The addendum here puts forth some observations and questions about the level-sets approach that go beyond those in [1]. In particular, we detail and ask the following questions. How does the level-sets approach compare with other related approaches? How is the resulting hierarchical clustering affected by the choice of radial basis function? What are the structural properties of a function formed as the sum of radial basis functions? Can the levels-sets approach be theoretically validated? Is there an efficient algorithm to implement the level-sets approach?展开更多
基金Finallcial support was provided by the Natural Sciences and Engineering Research Council of Canada(NSERC)the European Space Agency(ESA)
文摘Synthetic dry adhesives inspired by the nano-and micro-scale hairs found on the feet of geckos and some spiders have beendeveloped for almost a decade. Elastomeric single level micro-scale mushroom shaped fibres are currently able to function evenbetter than natural dry adhesives on smooth surfaces under normal loading. However, the adhesion of these single level syntheticdry adhesives on rough surfaces is still not optimal because of the reduced contact surface area. In nature, contact area ismaximized by hierarchically structuring different scales of fibres capable of conforming surface roughness. In this paper, weadapt the nature’s solution arid propose a novel dual-level hierarchical adhesive design using Polydimethylsiloxane (PDMS),which is tested under peel loading at different orientations. A negative macro-scale mold is manufactured by using a laser cutterto define holes in a Poly(methyl methacrylate) (PMMA) plate. After casting PDMS macro-scale fibres by using the obtainedPMMA mold, a previously prepared micro-fibre adhesive is bonded to the macro-scale fibre substrate. Once the bondingpolymer is cured, the micro-fibre adhesive is cut to form macro scale mushroom caps. Each macro-fibre of the resulting hierarchicaladhesive is able to conform to loads applied in different directions. The dual-level structure enhances the peel strengthon smooth surfaces compared to a single-level dry adhesive, but also weakens the shear strength of the adhesive for a given areain contact. The adhesive appears to be very performance sensitive to the specific size of the fibre tips, and experiments indicatethat designing hierarchical structures is not as simple as placing multiple scales of fibres on top of one another, but can requiresignificant design optimization to enhance the contact mechanics and adhesion strength.
文摘A multilevel secure relation hierarchical data model for multilevel secure database is extended from the relation hierarchical data model in single level environment in this paper. Based on the model, an upper lower layer relationalintegrity is presented after we analyze and eliminate the covert channels caused by the database integrity.Two SQL statements are extended to process polyinstantiation in the multilevel secure environment.The system based on the multilevel secure relation hierarchical data model is capable of integratively storing and manipulating complicated objects ( e.g. , multilevel spatial data) and conventional data ( e.g. , integer, real number and character string) in multilevel secure database.
文摘This article is an addendum to the 2001 paper [1] which investigated an approach to hierarchical clustering based on the level sets of a density function induced on data points in a d-dimensional feature space. We refer to this as the “level-sets approach” to hierarchical clustering. The density functions considered in [1] were those formed as the sum of identical radial basis functions centered at the data points, each radial basis function assumed to be continuous, monotone decreasing, convex on every ray, and rising to positive infinity at its center point. Such a framework can be investigated with respect to both the Euclidean (L2) and Manhattan (L1) metrics. The addendum here puts forth some observations and questions about the level-sets approach that go beyond those in [1]. In particular, we detail and ask the following questions. How does the level-sets approach compare with other related approaches? How is the resulting hierarchical clustering affected by the choice of radial basis function? What are the structural properties of a function formed as the sum of radial basis functions? Can the levels-sets approach be theoretically validated? Is there an efficient algorithm to implement the level-sets approach?
