Development Of An Soi-Based Micro Check Valve
This paper presents a bulk micromachined check valve with very high frequency and extremely low leak rates. The valve is designed to have a hexagonal orifice, a hexagonal membrane flap and three flexible tethers. The three elbow-shaped flexible tethers are used both to secure the membrane flap to the valve seat and to abtain a large flap displacement in the forward flow direction. SOI wafer and DRIE technology are used to implement this micro valve. A very simple farbication process has been developed, and only two photolithographic masks are employed. Preliminary testing on a 1.5 milimeters size check valve shows that a maximum flow rate (DI water) of 35.6ml/min was obtained at pressure drop of 65.5kPa and negligible leakage rate in the reverse flow direction observed at pressure up to 600kPa.

title: A Rotary Micromirror For Fiber-Optic Switching
abstract: We demonstrate a novel rotary micromirror for fiber-optic switching. A very simple fabrication process which uses SOI wafer and DRIE technology has been employed to micromachine this electrotastically actuated vertical mirror. Based on this one-mask process, 2N-switch-architecture crossconnects with all the components, inlcuding optic fiber couplers electrostatic comb drives and reflective vertical mirrors, has been integrally fabricated on a monolithic silicon substrate.

title: Learning from Positive and Unlabeled Examples with Different Data Distributions
abstract: We study the problem of learning from positive and unlabeled examples. Although several techniques exist for dealing with this problem, they all assume that positive examples in the positive set P and the positive examples in the unlabeled set U are generated from the same distribution. This assumption may be violated in practice. For example, one wants to collect all printer pages from the Web. One can use the printer pages from one site as the set P of positive pages and use product pages from another site as U. One wants to classify the pages in U into printer pages and non-printer pages. Although printer pages from the two sites have many similarities, they can also be quite different because different sites often present similar products in different styles and have different focuses. In such cases, existing methods perform poorly. This paper proposes a novel technique A-EM to deal with the problem. Experiment results with product page classification demonstrate the effectiveness of the proposed technique.

title: Designing Neural Networks Using PSO-Based Memetic Algorithm
abstract: This paper proposes an effective particle swarm optimization (PSO) based memetic algorithm (MA) for designing artificial neural network. In the proposed PSO-based MA (PSOMA), not only the evolutionary searching mechanism of PSO characterized by individual improvement plus population cooperation and competition is applied to perform the global search, but also several adaptive high-performance faster training algorithms are employed to enhance the local search, so that the exploration and exploitation abilities of PSOMA can be well balanced. Moreover, an effective adaptive Meta-Lamarckian learning strategy is employed to decide which local search method to be used so as to prevent the premature convergence and concentrate computing effort on promising neighbor solutions. Simulation results and comparisons demonstrate the effectiveness and efficiency of the proposed PSOMA.

title: A Graph-Based Algorithm for Mining Maximal Frequent Itemsets
abstract: Association rule mining is an important research branch of data mining, and computing frequent itemsets is the main problem. The paper is designed to find maximal frequent itemsets only. It presents an algorithm based on a frequent pattern graph, which can find maximal frequent itemsets quickly. A breadth-first-search and a depth-first-search techniques are used to produce all maximal frequent itemsets of a database. The paper also analyzes the complexity of the algorithm, and explains the computation procedure by examples. It has high time efficiency and less space complexity for computing maximal frequent itemsets.

title: ASG Automated Signature Generation for Worm-Like P2P Traffic Patterns
abstract: Many P2P software have the similar communication patterns with computer worms, thus they will bring in false positives for behaviour based worm detection. Up to now, little work is done on the research of the similarities between communication patterns of worm and P2P software as well as how to eliminate the worm-like P2P traffic. Based on the analysis of popular P2P software used nowadays and the host process information, this paper presents ASG, which is a novel host based algorithm to generate signatures for worm-like P2P communication patterns. The contribution of our work lies in three aspects: a) Analyzing communication pattern similarities between P2P traffic and worm traffic through examples. b) Designing one practical and simple signature format for worm-like P2P traffic based on the host process information, c) Presenting automated signature generation (ASG) method to extract the signature of worm-like P2P traffic. Experiments with the popular used P2P software show that ASG can effectively extract the signature and reduce the false positives.

title: Content-based indexing and retrieval method of Chinese document images
abstract: In Chinese information retrieval, it is easy to index a Chinese text document for retrieval. We just need to segment the text document into phrases. When the document is a Chinese document image (non-ASCII file), we may first convert the document image into the text file by using Chinese optical character recognition (OCR) technology and then index the document by using an information retrieval algorithm. However, OCR needs more time, which can influence retrieval efficiency. This paper proposes an index method based on stroke density code. First segment the document image to get all the Chinese character images, then calculate the stroke density of each Chinese character image, and at last attain the stroke density code of the character image. The index method has the advantage of speed and robustness to noise. In addition, this paper also offers a retrieval method for Chinese document images based on the index technology. We discuss the index and retrieval method for duplicate detection. We have proved the validity of the index method through its application to keyword spotting and duplicate detection.