20,620 research outputs found
Fabrication of Embedded Microvalve on PMMA Microfluidic Devices through Surface Functionalization
The integration of a PDMS membrane within orthogonally placed PMMA
microfluidic channels enables the pneumatic actuation of valves within bonded
PMMA-PDMS-PMMA multilayer devices. Here, surface functionalization of PMMA
substrates via acid catalyzed hydrolysis and air plasma corona treatment were
investigated as possible techniques to permanently bond PMMA microfluidic
channels to PDMS surfaces. FTIR and water contact angle analysis of
functionalized PMMA substrates showed that air plasma corona treatment was most
effective in inducing PMMA hydrophilicity. Subsequent fluidic tests showed that
air plasma modified and bonded PMMA multilayer devices could withstand fluid
pressure at an operational flow rate of 9 mircoliters/min. The pneumatic
actuation of the embedded PDMS membrane was observed through optical microscopy
and an electrical resistance based technique. PDMS membrane actuation occurred
at pneumatic pressures of as low as 10kPa and complete valving occurred at
14kPa for 100 micrometers x 100 micrometers channel cross-sections.Comment: Submitted on behalf of EDA Publishing Association
(http://irevues.inist.fr/handle/2042/16838
A fuzzy k-modes algorithm for clustering categorical data
This correspondence describes extensions to the fuzzy k-means algorithm for clustering categorical data. By using a simple matching dissimilarity measure for categorical objects and modes instead of means for clusters, a new approach is developed, which allows the use of the k-means paradigm to efficiently cluster large categorical data sets. A fuzzy k-modes algorithm is presented and the effectiveness of the algorithm is demonstrated with experimental results.published_or_final_versio
Testing Cluster Structure of Graphs
We study the problem of recognizing the cluster structure of a graph in the
framework of property testing in the bounded degree model. Given a parameter
, a -bounded degree graph is defined to be -clusterable, if it can be partitioned into no more than parts, such
that the (inner) conductance of the induced subgraph on each part is at least
and the (outer) conductance of each part is at most
, where depends only on . Our main
result is a sublinear algorithm with the running time
that takes as
input a graph with maximum degree bounded by , parameters , ,
, and with probability at least , accepts the graph if it
is -clusterable and rejects the graph if it is -far from
-clusterable for , where depends only on . By the lower
bound of on the number of queries needed for testing graph
expansion, which corresponds to in our problem, our algorithm is
asymptotically optimal up to polylogarithmic factors.Comment: Full version of STOC 201
Chapter Development of Sustainable High-Strength Self-Consolidating Concrete Utilising Fly Ash, Shale Ash and Microsilica
With high flowability and passing ability, self-consolidating concrete (SCC) does not require compaction during casting and can improve constructability. The favourable properties of SCC have enabled its widespread adoption in many parts of the world. However, there are two major issues associated with the SCC mixes commonly used in practice. First, the cement content is usually at the high side. Since the production of cement involves calcination at high temperature and is an energy-intensive process, the high cement content imparts high embodied energy and carbon footprint to the SCC mixes. Besides, the exothermic reaction of cement hydration would cause high heat generation and early thermal cracking problem that would impair structural integrity and necessitate repair. Second, the strength is usually limited to around grade 60, which is considered as medium strength in nowadays achievable norm. With a view to develop sustainable high-strength self-consolidating concrete (HS-SCC), experimental research utilising fly ash (FA), shale ash (SA), and microsilica (MS) in the production of SCC has been conducted, as reported herein
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