An ontology reasoning architecture for data mining knowledge management

In order to realize the intelligent management of data mining （DM） domain knowledge, this paper presents an architecture for DM knowledge management based on ontology. Using ontology database, this architecture can realize intelligent knowledge retrieval and automatic accomplishment of DM tasks by means of ontology services. Its key features include：①Describing DM ontology and meta-data using ontology based on Web ontology language （OWL）.② Ontology reasoning function. Based on the existing concepts and relations, the hidden knowledge in ontology can be obtained using the reasoning engine. This paper mainly focuses on the construction of DM ontology and the reasoning of DM ontology based on OWL DL（s）.     

Analysis of the design methods of word oriented linear feedback shift registers

Based on analysis of the structure characteristics and implementation methods of some representative word oriented linear feedback shift registers （LFSRs） in several modem software oriented stream ciphers, this paper firstly classifies the word oriented LFSRs into two classes： the machine instruction type and the arithmetic type. The similarities and differences between each type are illustrated by concrete examples. Then we give a detailed analysis about the word oriented LFSRs in each category from design structure, cryptographic properties and implementation issue aspects. Finally, some basic design criteria for modem word oriented LFSRs and suitable for software implementation are summarized.     

Instantiate random oracles in OAEP with pseudorandom functions

This paper focuses on the instantiation of random oracles in public key encryption schemes. A misunderstanding in the former instantiations is pointed out and analyzed. A method of using this primitive as a substitution of random oracles is also proposed. The partial and full instantiations of random oracles in optimal asymmetric encryption padding （OAEP） implemented by pseudorandom functions are described and the resulted schemes are proven to be indistinguishable secure against adaptive chosen ciphertext attack （IND-CCA2） secure. Using this method, one can transform a practical public key encryption scheme secure in the random oracle model into a standard-model secure scheme. The security of the scheme is based on computational assumptions, which is weaker than decisional assumptions used in Cramer- Shoup like schemes.     

Novel Schmitt trigger with wide temperature range

A novel Schmitt trigger circuit, implemented by a reset-set (RS) trigger and two simple distinct inverters, is proposed. Its trigger levels are determined by two Complementary Metal-Oxide-Semiconductor (CMOS) inverters. Contrast with traditional six transistors Schmitt trigger, its temperature and supply voltage characteristics have been analyzed. These two triggers are applied into relaxation oscillator and the result shows that the proposed one in this paper has better performance over wide temperature range, whose temperature coefficient from 0 to 85 °C is 1/5 of the traditional one. Biography: ZOU Zhige (1975–), male, Ph.D. candidate, research direction: analog and mix-signal IC design.     

On <Emphasis Type="Italic">k</Emphasis>-error linear complexity of some explicit nonlinear pseudorandom sequences

Combining with the research on the linear complexity of explicit nonlinear generators of pseudorandom sequences, we study the stability on linear complexity of two classes of explicit inversive generators and two classes of explicit nonlinear generators. We present some lower bounds in theory on the k-error linear complexity of these explicit generatol＇s, which further improve the cryptographic properties of the corresponding number generators and provide very useful information when they are applied to cryptography.     

Application of the modified neighborhood interference model to the cultivation of forest and herbaceous ecosystem

This paper is an extension of the application of neighborhood interference model--being modified--to the study of the interference between forest plants and herbaceous plants. The exploration of the neighborhood interference between triploid Populus tomentosa and Lolium multiflorum shows that the interference of Lolium multiflorum on triploid populus tomentosa is positive, with the primary interference factor living weight, and secondary factor cover degree; the growth of an individual tree is affected by the number, height, and coverage of the Lolium multiflorum; the more dense the coverage of the Lolium multiflorum in a certain area, the taller, faster and more trees will grow as a result of a greater positive neighborhood interference. The modified neighborhood interference model well serves as an effective approach to extend the application of neighborhood interference researches.     

Relations between the underground biomass and soil organic carbon and nitrogen of the alpine meadow at the Eastern Margin of the Qinghai-Tibet Plateau

This article, by combining field investigation with laboratorial analysis, studies diverse alpine meadow at the Eastern Margin of the Qinghai-Tibet Plateau for the underground biomass dynamics, vertical distribution of the content of soil carbon and nitrogen, the connection between the biomass and the content of carbon and nitrogen. The studies show that underground biomass in the herb layer of upland meadow is more than that in the terrace meadow, while underground biomass in the upland shrubland is the most. The vertical distribution of underground biomass of each type is obvious as in shape of＂T＂. As to the distribution of the content of soil organic carbon in the three sample grounds, it showed that the deeper the soil the less the content of soil organic carbon. In May, unlike at terrace meadow, the underground biomass and the content of soil organic carbon in positive proportion, such revelation at upland meadow and upland shrubland is not apparent. In July, at upland meadow and terrace meadow the underground biomass and the content of soil total nitrogen in positive proportion, such revelation at upland shrubland is not apparent either.     

A mobile accessible closed multi-part group communication scheme in IPv6 network

To solve the problems of current IP multicast which includes poor inter-domain many-to-many group support, security vulnerabilities and dependency to specific multicast infrastructure, a mobile accessible closed multi-part group （MACMPG） communication protocol in IPv6 network is proposed. By extending the single source multicast protocol, the communication channel for multi-part group communication across domains is established. Based on lPv6 CGA, the secure closed group communication scheme is designed. The access to the multicast traffic only confined to the authorized senders and receivers and only trusted routers are allowed to be the branch points of MACMPG tree. By tunneling mechanism, the MACMPG traffic can be transmitted across non-MACMPG routing area, and the mobile nodes can join the group remotely and roam freely between domains, which eliminates the dependency on specific IP multicast routing.     

A distributed dynamic clustering algorithm for wireless sensor networks

This paper proposes a distributed dynamic k-medoid clustering algorithm for wireless sensor networks (WSNs), DDKCAWSN. Different from node-clustering algorithms and protocols for WSNs, the algorithm focuses on clustering data in the network. By sending the sink clustered data instead of practical ones, the algorithm can greatly reduce the size and the time of data communication, and further save the energy of the nodes in the network and prolong the system lifetime. Moreover, the algorithm improves the accuracy of the clustered data dynamically by updating the clusters periodically such as each day. Simulation results demonstrate the effectiveness of our approach for different metrics. Biography: WANG Leichun (1974–), male, Ph.D. candidate, research direction: wireless communication.     

Evolutionary computation based optimization of image Zernike moments shape feature vector

The image shape feature can be described by the image Zernike moments. In this paper, we points out the problem that the high dimension image Zernike moments shape feature vector can describe more detail of the original image but has too many elements making trouble for the next image analysis phases. Then the low dimension image Zernike moments shape feature vector should be improved and optimized to describe more detail of the original image. So the optimization algorithm based on evolutionary computation is designed and implemented in this paper to solve this problem. The experimental results demonstrate the feasibility of the optimization algorithm. Biography: LIU Maofu (1977–), male, Associate professor, Ph.D., research direction: image mining, natural language processing.