新一代络合态代森锰锌新技术产品的研究开发及应用

采用全新自主研发工艺和设备,对代森锰锌生产工艺进行创新,得到较为纯净的"络合态"化合物。该化合物对作物幼苗、幼叶、幼果的安全性提高了;解决了普通代森锰锌和络合态代森锰锌在合成、干燥、物料输送、含氨废水处理及分析检测等方面的技术难题;生产及分析中的废物处理与利用水平国际领先。实现了废水、尾气全部循环利用,废渣回用,废水趋零排放,对环境无污染;实现了络合态代森锰锌连续化生产,此生产工艺具有节能、节水和生产安全性高等特点。

STRONGER PROVABLE SECURE MODEL FOR KEY EXCHANGE

The key exchange is a fundamental building block in the cryptography. Several provable security models for the key exchange protocol are proposed. To determine the exact properties required by the protocols, a single unified security model is essential, The eCK , eCK and CK models are examined and the result is proved that the eCK＇ model is the strongest provable security model for the key exchange. The relative security strength among these models is analyzed. To support the implication or non-implication relations among these models, the formal proofs and the counter-examples are given.

Improved results on synchronization in arrays of coupled delayed neural networks with hybrid coupling

In order to investigate the influence of hybrid coupling on the synchronization of delayed neural networks, by choosing an improved delay-dependent Lyapunov-Krasovskii functional, one less conservative asymptotical criterion based on linear matrix inequality （LMI） is established. The Kronecker product and convex combination techniques are employed. Also the bounds of time-varying delays and delay derivatives are fully considered. By adjusting the inner coupling matrix parameters and using the Matlab LMI toolbox, the design and applications of addressed coupled networks can be realized. Finally, the efficiency and applicability of the proposed results are illustrated by a numerical example with simulations.

Optimization and coordination model of information system security investment for interdependent risk

The impact of risk correlation on firm＇s investments in information system security is studied by using quantification models combining the ideas of the risk management theory and the game theory. The equilibrium levels of self-protection and insurance coverage under the non- cooperative condition are compared with socially optimal solutions, and the associated coordination mechanisms are proposed. The results show that self-protection investment increases in response to an increase in potential loss when the interdependent risk is small; the interdependent risk of security investments often induce firms to underinvest in security relative to the socially efficient level by ignoring marginal external costs or benefits conferred on others. A subsidy on self-protection investment from the government can help coordinate a firm＇s risk management decision and, thereby, improve individual security level and overall social welfare.

A Novel Multivalued Associative Memory System

Globally coupled map (GCM) model can evolve through chaotic searching into several stable periodic orbits under properly controlled parameters. This can be exploited in information processing such as associative memory and optimization. In this paper, we propose a novel covariance learning rule for multivalue patterns and apply it in memorization of gray scale images based on modified GCM model (S GCM). Analysis of retrieval results are given finally.

Crayfish Shell Waste as Safe Biosorbent for Removal of Cu^(2+)and Pb^(2+)from Synthetic Wastewater

Crayfish shell is an abundant natural waste and is also a potential biosorbent for pollutants,especially,heavy metals.In this study,the safety of the use of crayfish shell as a biosorbent was first assessed by release experiments involving primary heavy metal ions,such as Cu^(2+),Zn^(2+),and Cr^(3+),in aqueous solution under different environmental conditions.The release concentrations of heavy metals were dependent on pH,ionic strength,and humic acid;and the maximum release concentrations of heavy metals were still lower than the national standard.Specifically,Cu^(2+) and Pb^(2+) removal by crayfish shell in synthetic wastewater was investigated.The removal process involved biosorption,precipitation,and complexation,and the results indicate that crayfish shell is an excellent biosorbent for Cu^(2+) and Pb^(2+) removal.The precipitation step is particularly dependent on Ca species,pH,and temperature.The maximum removal capacities of Pb^(2+) and Cu^(2+) were 676.20 and 119.98 mg/g,respectively.The related precipitates and the generated complex products include Cu_(2)CO_(3)(OH)_(2),Ca_(2)CuO_(3),CuCO_(3),Pb_(2)CO_(3)(OH)_(2),CaPb_(3)O_(4),and PbCO_(3).

Research on stateful public key based secure data aggregation model for wireless sensor networks

Data aggregation technology reduces traffic overhead of wireless sensor network and extends effective working time of the network,yet continued operation of wireless sensor networks increases the probability of aggregation nodes being captured and probability of aggregated data being tampered.Thus it will seriously affect the security performance of the network. For network security issues,a stateful public key based SDAM( secure data aggregation model) is proposed for wireless sensor networks( WSNs),which employs a new stateful public key encryption to provide efficient end-to-end security. Moreover,the security aggregation model will not impose any bound on the aggregation function property,so as to realize the low cost and high security level at the same time.

Synchronization and Control of Halo-Chaos in Beam Transport Network with Small World Topology

The synchronous conditions of two kinds of the small-world （SW） network are studied. The small world topology can affect on dynamical behaviors of the beam transport network （BTN） largely, if the BTN is constructed with the SW topology, the global linear coupling and special linear feedback can realize the synchronization control of beam halo-chaos as well as periodic state in the BTN with the SW topology, respectively. This important result can provide an effective way for the experimental study and the engineering design of the BTN in the high-current accelerator driven radioactive clean nuclear power systems, and may have potential use in prospective applications for halo-chaos secure communication.

A scalable model for network situational awareness based on Endsley＇ s situation model

The paper introduces the Endsley＇ s situation model into network security to describe the network security situation, and improves Endsley＇s data processing to suit network alerts. The proposed model contains the information of incident frequency, incident time and incident space. The HoneyNet dataset is selected to evaluate the proposed model in the evaluation. The paper proposes three definitions to depict and predigest the whole situation extraction in detail, and a fusion component to reduce the influence of alert redundancy on the total security situation. The less complex extraction makes the situation analysis more efficient, and the fine-grained model makes the analysis have a better expansibility. Finally, the situational variation curves are simulated, and the evaluation results prove the situation model applicable and efficient.

Secure Data Aggregation Approach Based on Monitoring in Wireless Sensor Networks

In order to avoid internal attacks during data aggregation in wireless sensor networks, a grid-based network architecture fit for monitoring is designed and the algorithms for network division, initialization and grid tree construction are presented. The characteristics of on-off attacks are first studied and monitoring mechanisms are then designed for sensor nodes. A Fast Detection and Slow Recovery (FDSR) algorithm is proposed to prevent on-off attacks by observing the behaviors of the nodes and computing reputations. A recovery mechanism is designed to isolate malicious nodes by identifying the new roles of nodes and updating the grid tree. In the experiments, some situations of on-off attacks are simulated and the results are compared with other approaches. The experimental results indicate that our approach can detect malicious nodes effectively and guarantee secure data aggregation with acceptable energy consumption.

Design and Implementation of Weibo Sentiment Analysis Based on LDA and Dependency Parsing

Information content security is a branch of cyberspace security. How to effectively manage and use Weibo comment information has become a research focus in the field of information content security. Three main tasks involved are emotion sentence identification and classification,emotion tendency classification,and emotion expression extraction. Combining with the latent Dirichlet allocation(LDA) model,a Gibbs sampling implementation for inference of our algorithm is presented,and can be used to categorize emotion tendency automatically with the computer. In accordance with the lower ratio of recall for emotion expression extraction in Weibo,use dependency parsing,divided into two categories with subject and object,summarized six kinds of dependency models from evaluating objects and emotion words,and proposed that a merge algorithm for evaluating objects can be accurately evaluated by participating in a public bakeoff and in the shared tasks among the best methods in the sub-task of emotion expression extraction,indicating the value of our method as not only innovative but practical.