A Fast Distributed Algorithm for Association Rule Mining Based on Binary Coding Mapping Relation

Association rule mining is an important issue in data mining. The paper proposed an binary system based method to generate candidate frequent itemsets and corresponding supporting counts efficiently, which needs only some operations such as ＂and＂, ＂or＂ and ＂xor＂. Applying this idea in the existed distributed association rule mining al gorithm FDM, the improved algorithm BFDM is proposed. The theoretical analysis and experiment testify that BFDM is effective and efficient.     

Agglomerating Growth of One-Dimensional Carbon Nano-Materials Synthesized from Ethanol Flames

One-dimensional carbon nano-materials （ODCNMs） synthesized from ethanol flames exhibit various agglomerated morphologies, such as ＂chrysanthemum-like＂, ＂hairball-like＂ or ＂orange-peel-like＂, ＂vertically aligned＂ and ＂wrinkling-pileup＂. The present work studied the agglomerating process and the growth mechanism by using scanning electron microscopy （SEM） and transmission electron microscopy （TEM）. It is thought that the size and distribution of the catalyst particles produced from pretreatment of the substrates play a key role during the formation of agglomerations. It is expected that the steady growth of ODCNMs in flames will be improved through the preparation of the catalysts.     

RTP-Packets＇ Loss Recovery Scheme Based on Layered Buffer-Routers

This paper introduces an RTP-packets‘ loss recovery scheme in MPEG-4 playback type multicast application model, which is based on retransmission scheme. Through the auxiliary and coordinated buffer playing scheme of layered “buffer-routers”, the RTP-packets‘ loss recovery in limited time is made possible. We consider in the scheme to handle retransmission request with buffer waiting when network congestion occurs. Thus, neither the degree of congestion will be worsened nor the retransmission request will be lost when sending the request to higherlevel buffer router. The RTP-packets‘ loss recovery scheme suggested by us is not only applied to MPEG-4 muhieast application in LAN, but also can be extended to more spacious WAN (wide area network) when user groups comparatively centralize in certain number of local areas.     

An Image Encryption Method Based on Bit Plane Hiding Technology

A novel image hiding method based on the correlation analysis of bit plane is described in this paper. Firstly, based on the correlation analysis, different bit plane of a secret image is hided in different bit plane of several different open images. And then a new hiding image is acquired by a nesting ＂Exclusive-OR＂ operation on those images obtained from the first step. At last, by employing image fusion technique, the final hiding result is achieved. The experimental result shows that the method proposed in this paper is effec rive.     

Building Intrusion Tolerant Software System

In this paper, we describe and analyze the hypothesis about intrusion tolerance software system, so that it can provide an intended server capability and deal with the impacts caused by the intruder exploiting the inherent security vulnerabilities. We present some intrusion tolerance technology by exploiting N-version module threshold method in con-structing multilevel secure software architecture, by detecting with hash value, by placing an ““““““““antigen““““““““ word next to the return address on the stack that is similar to human immune system, and by adding ““““““““Honey code““““““““ nonfunctional code to disturb intruder, so that the security and the availability of the software system are ensured.     

BloomRouter： A Framework for Dissemination of Compressed XML Stream

As our best knowledge, in the Publish/Subscribe application environment, few research work has been done on the dissemination and routing of compressed XML （extended markup language） data. A high-speed compressed XML data routing and dissemination framework BloomRouter is proposed. In BloomRouter, a Bloom Filter based prefilte ring mechanism is used to filter out compressed XML elements that users do not care; after that an interval tree dis seminator forwards target elements to the corresponding end users by matching the incomming compressed XML elements with indexed users＇ query regions. Based on this framework, we can efficiently filter/query the compressed incoming XML data, and then route the query result to the corresponding subseriber.     

Floristic Characteristics of the Rare and Endangered Plants and the Conservation Countermeasures in Tibet, China

The floristic elements and the geographical distribution are analyzed in this paper based on statistics of elements of rare and endangered plants in Tibet. The results have been gained as following:① According to ““““the National Important Wild Conservative Plants List (List 1)““““ and ““““the National Important Wild Conservative Plants List (List 1)““““, there are a total of 54 plant species (48 genera and 33 families); ② The geographical elements are very complicated in Tibet with 12 of 15 distribution patterns of genera classified byacademician Wu; ③ There are obvious temperate genera with 28 genera accounting for 60.40% of the total genera; ④ There are abundant endemic speciesaccounting for 18.52% of total species but poor endemic genera; ⑤ The geographical distribution is uneven and a great of species distribute in the areas be-tween 1 000 m and 3 500 m above sea level; ⑥ To protect the rare and endangered plants efficiently, six conservation measures are proposed, and 35 species are suggested for the conservative plants of the autonomous conservation level.     

Clustering of Web learners based on rough set

The demand for individualized teaching from Elearning websites is rapidly increasing due to the huge differences existed among Web learners. A method for clusteringWeb learners based on rough set is proposed. The basic ideaof the method is to reduce the learning auributes prior to clustering, and therefore the clustering of Web learners iscarried out in a relative low-dimensional space. Using thismethod, the E-learning websites can arrange correspondingleaching content for different clusters of learners so that thelearners‘ individual requirements can be more satisfied.     

A hybrid model for the mid-long term runoff forecasting by evolutionary computation techniques

The mid-long term hydrology forecasting is one of most challenging problems in hydrological studies. This paper proposes an efficient dynamical system prediction model using evolutionary computation techniques. The new model overcomes some disadvantages of conventional hydrology forecasting ones. The observed data is divided into two parts: the slow “smooth and steady” data, and the fast “coarse and fluctuation” data. Under thedivide and conquer strategy, the behavior of smooth data is modeled by ordinary differential equations based on evolutionary modeling, and that of the coarse data is modeled using gray correlative forecasting method. Our model is verified on the test data of the mid-long term hydrology forecast in the northeast region of China. The experimental results show that the model is superior to gray system prediction model (GSPM). Foundation item: Supported by the National Natural Science Foundation of China ( 60133010, 70071042, 60073043) Biography: Zou Xiu-fen(1966-),female,Associate professor, research direction:evolutionary computing, parallel computing.     

ISS： Efficient Search Scheme Based on Immune Method in Modern Unstructured Peer-to-Peer Networks

Flooding is the most famous technique for locating contents in unstructured P2P networks. Recently traditional flooding has been replaced by more efficient dynamic query （DQ） and different variants of such algorithms. Dynamic query is a new flooding technique which could estimate a proper time-to-live （TTL） value for a query flooding by estimating the popularity of the searched files, and retrieve sufficient results under controlled flooding range for reducing network traffic. However, all DQ-like search algorithms are ＂blind＂ so that a large amount of redundant messages are caused. In this paper, we proposed a new search scheme, called Immune Search Scheme （ISS）, to cope with this problem. In ISS, an immune systems inspired concept of similarity-governed clone proliferation and mutation for query message movement is applied. Some assistant strategies, that is, shortcuts creation and peer traveling are incorporated into ISS to develop ＂immune memory＂ for improving search performance, which can make ISS not be blind but heuristic.     

A New Framework for Focused Web Crawling

Focused crawlers are important tools to support applications such as specialized Web portals, online searching, and Web search engines. A topic driven crawler chooses the best URLs and relevant pages to pursue during Web crawling. It is difficult to deal with irrelevant pages. This paper presents a novel focused crawler framework. In our focused crawler, we propose a method to overcome some of the limitations of dealing with the irrelevant pages. We also introduce the implementation of our focused crawler and present some important metrics and an evaluation function for ranking pages relevance. The experimental result shows that our crawler can obtain more ＂important＂ pages and has a high precision and recall value.     

A Lightweight Mobile RSVP for Unicast

This paper presents a lighter protocol, and it removes the multicast burdens from RSVP to adapt to unicast applications. At the same time, when RSVP is used in wireless networks, some issues about mobility raise popular concerns. The proposed protocol a lightweight mobile RSVP protocol, solves the problems by the following mechanisms： changeless flow identifier, a new state management and ＂refresh＂ mechanism.     

Research of Dynamic Competitive Learning in Neural Networks

Introduce a method of generation of new units within a cluster and a algorithm of generating new clusters. The model automatically builds up its dynamically growing in ternal representation structure during the learning process. Comparing model with other typical classification algorithm such as the Kohonen‘s self-organizing map. the model realizes a multilevel classification of the input pattern with an optional accuracy and gives a strong support possibility for the parallel computational main processor. The idea is suitable for the high-level storage of complex datas structures for object recognition.     

Subliminal Channels in the NTRU and the Subliminal-Free Methods

The construetion and destruction of subliminal channel are important problems in the information hiding. The subliminal channel can send secret information without notice. Two subliminal-free methods named weak （strong） subliminal-free on public-key cryptosystem （PKC） are proposed in this paper using the combinatorial method. The first method can only free the subliminal information with any minor probability and the second can free all. Moreover, the ＂traitor problem＂ which is same as the model of the subliminal channel in PKC is given. Two subliminal channels are embedded in N-th degree truncated polynomial ring （NTRU） cryptosystem, and their subliminal-free methods are also be obtained by the action of surveillant.     

Probabilistic Analysis on Connectivity for Sensor Grids with Unreliable Nodes

0 IntroductionWireless sensor networks consist of manynodes , each containing application-specificsensors ,a wirelesstransceiver ,anda si mple proces-sor[1-4]. Sensor networks have extensive applica-tions . A large number of research results can beseenin Refs .[5-7] .This paper mainly concerns with sensor net-works that are inherently unreliable. We consider anetwork with mn nodes ,arranged in a grid over asquare region of areaA. This model was presentedin[8 ,9].Each nodeis a sensor ,and can…     

Polynomial Analysis of DH Secrete Key and Bit Security

In this paper, we lower the upper bound of the number of solutions of oracle transformation polynomial F(x) over GF(q). So one can also recover all the secrete keys with fewer calls. We use our generalized ““““““““even-and-odd test““““““““ method to recover the least significant p-adic ‘bits‘ of representations of the Lucas Cryptosystem secret keys x. Finally, we analyze the Efficient Compact Subgroup Trace Representation (XTR) Diffie-Hellmen secrete keys and point out that if the order of XTR subgroup has a special form then all the bits of the secrete key of XTR can be recovered form any bit of the exponent x.     

Dynamically Computing Approximate Frequency Counts in Sliding Window over Data Stream

This paper presents two one-pass algorithms for dynamically computing frequency counts in sliding window over a data stream-computing frequency counts exceeding user-specified threshold ε. The first algorithm constructs subwindows and deletes expired sub-windows periodically in sliding window, and each sub-window maintains a summary data structure. The first algorithm outputs at most 1/ε ＋ 1 elements for frequency queries over the most recent N elements. The second algorithm adapts multiple levels method to deal with data stream. Once the sketch of the most recent N elements has been constructed, the second algorithm can provides the answers to the frequency queries over the most recent n （ n≤N） elements. The second algorithm outputs at most 1/ε ＋ 2 elements. The analytical and experimental results show that our algorithms are accurate and effective.     

Extracting Result Schema Based on Query Instances in the Deep Web

Deep Web sources contain a large of high-quality and query-related structured date. One of the challenges in the Deep Web is extracting result schemas of Deep Web sources. To address this challenge, this paper describes a novel approach that extracts both result data and the result schema of a Web database. The approach first models the query interface of a Deep Web source and fills in it with a specifically query instance. Then the result pages of the Deep Web sources are formatted in the tree structure to retrieve subtrees that contain elements of the query instance, Next, result schema of the Deep Web source is extracted by matching the subtree＇ nodes with the query instance, in which, a two-phase schema extraction method is adopted for obtaining more accurate result schema. Finally, experiments on real Deep Web sources show the utility of our approach, which provides a high precision and recall.     

Remote intelligent identification system of structural damage

The focus of this paper is to build the damage identify system, which performs “system identification“ to detcct the positions and extents of structural damages. The identification of structural damage can be characterized as a nonlinear process which linear prediction models such as linear regression are not suitable. However. neural network techniques may provide an effective tool for system identification. The method of damage identification using the radial basis function neural network (P, BFNN) is presented in this paper. Using this method, a simple reinforced concrete structure has been tested both in the absence and presence of noise. The resuits show that the RBFNN identification technology can he used with related success for the solution of dynamic damage identification problems, even in the presence of a noisy identify data. Furthermore, a remote identification system based on that is set up with Java Technologies.