Efficient Tate pairing computation using double-base chains

Pairing-based cryptosystems have developed very fast in the last few years. The efficiencies of these cryptosystems depend on the computation of the bilinear pairings, In this paper, a new efficient algorithm based on double-base chains for computing the Tate pairing is proposed for odd characteristic p 〉 3. The inherent sparseness of double-base number system reduces the computational cost for computing the Tate pairing evidently. The new algorithm is 9% faster than the previous fastest method for the embedding degree k = 6.     

触摸传感器QST108与PIC单片机的接口设计

QST108为意法半导体公司生产的电容触摸传感器,具有功能强大且易操作等特点,非常适合应用在能够对用户触摸做出响应的智能控制界面中。本文重点介绍了QST108的工作方式及主要操作命令,给出了QST108与PIC单片机的接口设计以及部分程序代码。     

A Framework for Mining Sequential Patterns from Spatio-Temporal Event Data Sets

Given a large spatio-temporal database of events, where each event consists of the fields event ID, time, location, and event type, mining spatio-temporal sequential patterns identifies significant event-type sequences. Such spatio-temporal sequential patterns are crucial to the investigation of spatial and temporal evolutions of phenomena in many application domains. Recent research literature has explored the sequential patterns on transaction data and trajectory analysis on moving objects. However, these methods cannot be directly applied to mining sequential patterns from a large number of spatio-temporal events. Two major research challenges still remain: 1) the definition of significance measures for spatio-temporal sequential patterns to avoid spurious ones and 2) the algorithmic design under the significance measures, which may not guarantee the downward closure property. In this paper, we propose a sequence index as the significance measure for spatio-temporal sequential patterns, which is meaningful due to its interpretability using spatial statistics. We propose a novel algorithm called Slicing-STS-miner to tackle the algorithmic design challenge using the spatial sequence index, which does not preserve the downward closure property. We compare the proposed algorithm with a simple algorithm called STS-miner that utilizes the weak monotone property of the sequence index. Performance evaluations using both synthetic and real-world data sets show that the slicing-STS-miner is an order of magnitude faster than STS-Miner for large data sets.     

Dynamic visualization of coexpression in systems genetics data

Biologists hope to address grand scientific challenges by exploring the abundance of data made available through modern microarray technology and other high-throughput techniques. The impact of this data, however, is limited unless researchers can effectively assimilate such complex information and integrate it into their daily research; interactive visualization tools are called for to support the effort. Specifically, typical studies of gene co-expression require novel visualization tools that enable the dynamic formulation and fine-tuning of hypotheses to aid the process of evaluating sensitivity of key parameters. These tools should allow biologists to develop an intuitive understanding of the structure of biological networks and discover genes residing in critical positions in networks and pathways. By using a graph as a universal representation of correlation in gene expression, our system employs several techniques that when used in an integrated manner provide innovative analytical capabilities. Our tool for interacting with gene co-expression data integrates techniques such as: graph layout, qualitative subgraph extraction through a novel 2D user interface, quantitative subgraph extraction using graph-theoretic algorithms or by compound queries, dynamic level-of-detail abstraction, and template-based fuzzy classification. We demonstrate our system using a real-world workflow from a large-scale, systems genetics study of mammalian gene co-expression.     

Reconstruction of cellular biological structures from optical microscopy data

Developments in optical microscopy imaging have generated large high-resolution data sets that have spurred medical researchers to conduct investigations into mechanisms of disease, including cancer at cellular and subcellular levels. The work reported here demonstrates that a suitable methodology can be conceived that isolates modality-dependent effects from the larger segmentation task and that 3D reconstructions can be cognizant of shapes as evident in the available 2D planar images. In the current realization, a method based on active geodesic contours is first deployed to counter the ambiguity that exists in separating overlapping cells on the image plane. Later, another segmentation effort based on a variant of Voronoi tessellations improves the delineation of the cell boundaries using a Bayesian formulation. In the next stage, the cells are interpolated across the third dimension thereby mitigating the poor structural correlation that exists in that dimension. We deploy our methods on three separate data sets obtained from light, confocal, and phase-contrast microscopy and validate the results appropriately.     

Structural-symmetry-related sequence patterns of the proteins of beta-propeller family

It is still not very clear to what extent and how does the amino acid sequences of proteins determine their tertiary structures. In this paper, we report our investigations of the sequence-structure relations of the proteins in the beta-propeller fold family, which adopt highly symmetrical tertiary structures while their sequences appear "random". We analyzed the amino acid sequences by using a similarity matrix plus Pearson correlation method and found that the sequences can show the same symmetries as their tertiary structures only if we deduce the conditions of sequence similarity. This suggests that some key residues may play an important role in the formation of the tertiary structures of these proteins.     

Dynamically adjusting MPEG4 video streams based on network bandwidth

In the paper, we try to find a method that can service more users in a video-on-demand (VoD) system, based on MPEG-4 object streams. The characteristics of object segmentation made on MPEG-4 videos can be utilized to reduce re-transmission of the same objects, and then the saved bandwidth can be used to service more users. However, some thresholds must be analyzed first to maintain the acceptable quality of services (QoS) requested by users, when reducing unnecessary object transmission on one side. Thus, according to the defined thresholds, we propose a dynamically adjusting algorithm to coordinate the object streams between the server and clients. The server not only allocates network bandwidth, but also adjusts ever-allocated QoS appropriately using a degrading and upgrading strategy, based on the current network status. Lastly, through the simulation, we found that our method has better performance than the other three methods owing to its flexibility to the network status.

Responding to Security Issues in WiMAX Networks

WiMAX technology, the commercialization of the evolving IEEE 802.16 standard, aims to solve the last-mile problem with broadband wireless access at the scale of metropolitan area networks. WiMAX has attracted significant attention and interest because of its wide transmission range, high transmission rate, and mobility support. However, to make WiMAX networks usable and reliable, several security issues must be addressed in the standard and its protocols. In this article, the authors give an introduction to the security protocols used in WiMAX networks and then discuss why these protocols are deficient in terms of anti-replay, efficiency, scalability, and forward and backward secrecy, as well as how they can be enhanced to address these issues for real applications.     

Batch Nearest Neighbor Search for Video Retrieval

To retrieve similar videos to a query clip from a large database, each video is often represented by a sequence of high- dimensional feature vectors. Typically, given a query video containing m feature vectors, an independent nearest neighbor (NN) search for each feature vector is often first performed. After completing all the NN searches, an overall similarity is then computed, i.e., a single content-based video retrieval usually involves m individual NN searches. Since normally nearby feature vectors in a video are similar, a large number of expensive random disk accesses are expected to repeatedly occur, which crucially affects the overall query performance. Batch nearest neighbor (BNN) search is stated as a batch operation that performs a number of individual NN searches. This paper presents a novel approach towards efficient high-dimensional BNN search called dynamic query ordering (DQO) for advanced optimizations of both I/O and CPU costs. Observing the overlapped candidates (or search space) of a pervious query may help to further reduce the candidate sets of subsequent queries, DQO aims at progressively finding a query order such that the common candidates among queries are fully utilized to maximally reduce the total number of candidates. Modelling the candidate set relationship of queries by a candidate overlapping graph (COG), DQO iteratively selects the next query to be executed based on its estimated pruning power to the rest of queries with the dynamically updated COG. Extensive experiments are conducted on real video datasets and show the significance of our BNN query processing strategy.