Geometric Cluster Algorithm for Interacting Fluids

We discuss a new Monte Carlo algorithm for the simulation of complex fluids. This algorithm employs geometric operations to identify clusters of particles that can be moved in a rejection-free way. It is demonstrated that this geometric cluster algorithm (GCA) constitutes the continuum generalization of the Swendsen-Wang and Wolff cluster algorithms for spin systems. Because of its nonlocal nature, it is particularly well suited for the simulation of fluid systems containing particles of widely varying sizes. The efficiency improvement with respect to conventional simulation algorithms is a rapidly growing function of the size asymmetry between the constituents of the system. We study the cluster-size distribution for a Lennard-Jones fluid as a function of density and temperature and provide a comparison between the generalized GCA and the hard-core GCA for a size-asymmetric mixture with Yukawa-type couplings.Comment: To appear in "Computer Simulation Studies in Condensed-Matter Physics XVII". Edited by D.P. Landau, S.P. Lewis and H.B. Schuettler. Springer, Heidelberg, 200

Multi-task CNN Model for Attribute Prediction

This paper proposes a joint multi-task learning algorithm to better predict attributes in images using deep convolutional neural networks (CNN). We consider learning binary semantic attributes through a multi-task CNN model, where each CNN will predict one binary attribute. The multi-task learning allows CNN models to simultaneously share visual knowledge among different attribute categories. Each CNN will generate attribute-specific feature representations, and then we apply multi-task learning on the features to predict their attributes. In our multi-task framework, we propose a method to decompose the overall model's parameters into a latent task matrix and combination matrix. Furthermore, under-sampled classifiers can leverage shared statistics from other classifiers to improve their performance. Natural grouping of attributes is applied such that attributes in the same group are encouraged to share more knowledge. Meanwhile, attributes in different groups will generally compete with each other, and consequently share less knowledge. We show the effectiveness of our method on two popular attribute datasets.Comment: 11 pages, 3 figures, ieee transaction pape

Microfluidic Technology and Application in Urinal Analysis

Microfluidic technology offers numerous advantages in minimizing and integrating the traditional assays. However, the lack of efficient control components of the microfluidic systems has been hindering the widely commercialization of the technology. The research work in this dissertation focused on the development of effective control components for microfluidic applications. A linear peristaltic pump was firstly designed, fabricated, and tested for conventional microfluidics by synchronously compressing the microfluidic channel with a miniature cam-follower system in Chapter 2. The miniature cam-follower system and microfluidic chip was prototyped using three-dimensional (3D) printing technology and soft lithography technology. Results from experimental test showed that the pump is self-priming and tolerant of bubbles. The pumping flowrate and back pressure could be controlled by changing the driving speed of the motor. Then a novel pinch-type valving system that can be used to realize both normally closed and normally open valves for centrifugal microfluidics was demonstrated in Chapter 3. A sliding wedge was actuated by centrifugal force to drive the valves. Experimental test and theoretical predication showed that the burst frequency of the valves could be tuned by changing the physical parameters of the valving system. In Chapter 4, the pinch type valving system was then further improved for better integration of multiple valves in limited space to realize sequential control of microfluidics. A valve chip with grooves on the surface was used to drive multiple valves. A flow switch which is capable of working at low rotation frequency and constant rotation direction is realized. Finally, the microfluidic platform was utilized for automatic urinalysis for the application at point of care (POC) to eliminate the difficulties in control of sample distribution and read-out time in manually conducted colorimetric urinalysis. 3D printed prototype of the microfluidic chip was used to test the proposed system. Commercial urinalysis strips was integrated with the microfluidic system for detecting glucose, specific gravity, PH, and protein from simulated urine sample. The color change of the pads was recorded using smartphone camera and analyzed to quantify the interested parameters