浙江近海海鳗食性的分析研究

海鳗是我国沿海重要的海产经济鱼类之一。本文根据1988～1990年采集的224尾标本的解剖观察,对海鳗的消化器、饵料生物组成、摄食强度变化、不同海区饵料生物组成进行了分析研究。     

新型造纸原料洋麻的硫酸盐法制浆及ECF漂白

以洋麻为研究对象,分析了洋麻的化学成分,研究了不同H因子下硫酸盐法制浆(KP)的较优工艺,以及KP浆的ECF漂白性能及较优的漂白工艺.结果表明:洋麻的硝酸-乙醇纤维素含量为45.00%,酸不溶木素含量为16.50%,聚戊糖和抽出物含量均较低,是优良的造纸用原料;KP法蒸煮较优的制浆工艺为H因子1000、活性碱用量20%、硫化度22%,该工艺下细浆得率达44.9%、卡伯值为20.4、残碱质量浓度为11.67 g/L;ECF漂白的较优ODED漂白工艺为OD0,2%EpD1,1.5%,该工艺条件下终漂浆白度可达82.3%ISO.     

Structures of magnetic null points in reconnection diffusion region: Cluster observations

Magnetic reconnection is a very important and fundamental plasma process in transferring energy from magnetic field into plasma. Previous theory, numerical simulations and observations mostly concentrate on 2-dimensional （2D） model; however, magnetic reconnection is a 3-dimensional （3D） nonlinear process in nature. The properties of reconnection in 3D and its associated singular structure have not been resolved completely. Here we investigate the structures and charactedstics of null points inside the reconnection diffusion region by introducing the discretized Poincar6 index through Gauss integral and using magnetic field data with high resolution from the four satellites of Cluster mission. We estimate the velocity and trajectory of null points by calculating its position in different times, and compare and discuss the observations with different reconnection models with null points based on characteristics of electric current around null points.     

Exploration of TCM Masters Knowledge Mining

Traditional Chinese medicine （TCM） has a rich knowledge about human health and disease by its special way evolved along a very long history. As modern medicine is achieving much progress, arguments and disputes toward TCM never end. To avoid losing precious knowledge of living TCM masters, endeavors have been engaged to systematic collection of those knowledge of TCM masters, such as their growth experiences, effective practical cases toward diseases and typical therapeutic principles and methods. Knowledge mining methods have been expected to explore some useful or hidden patterns to unveil some mysteries of the TCM system. In the paper, some computerized methods are applied toward those collected materials about some living TCM masters in China mainland to show a different way of exposing essential ideas of those TCM masters by correspondence visualization which aims to help people understand TCM holistic views toward disease and body, and facilitate tacit knowledge transfer and sense-making of the essence of TCM. The work is one kind of qualitative meta-synthesis of TCM masters＇ knowledge.     

Research on the self-defence electronic jamming decision-making based on the discrete dynamic Bayesian network

The manner and conditions of running the decision-making system with self-defense electronic jamming are given.After proposing the scenario of applying discrete dynamic Bayesian network to the decision making with self-defense electronic jamming,a decision-making model with self-defense electronic jamming based on the discrete dynamic Bayesian network is established.Then jamming decision inferences by the aid of the algorithm of discrete dynamic Bayesian network are carried on.The simulating result shows that this method is able to synthesize different targets which are not predominant.In this way,various features at the same time,as well as the same feature appearing at different time complement mutually;in addition,the accuracy and reliability of electronic jamming decision making are enhanced significantly.     

Krylov subspace method based on data preprocessing technology

The performance of adaptive beamforming techniques is limited by the nonhomogeneous clutter scenario. An augmented Krylov subspace method is proposed, which utilizes only a single snapshot of the data for adaptive processing. The novel algorithm puts together a data preprocessor and adaptive Krylov subspace algorithm, where the data preprocessor suppresses discrete interference and the adaptive Krylov subspace algorithm suppresses homogeneous clutter. The novel method uses a single snapshot of the data received by the array antenna to generate a cancellation matrix that does not contain the signal of interest （SOI） component, thus, it mitigates the problem of highly nonstationary clutter environment and it helps to operate in real-time. The benefit of not requiring the training data comes at the cost of a reduced degree of freedom （DOF） of the system. Simulation illustrates the effectiveness in clutter suppression and adaptive beamforming. The numeric results show good agreement with the proposed theorem.     

New model for load-sharing k-out-of-n: G system with different components

On the basis of capacity flow model, a new model is developed for a load-sharing k-out-of-n： G system consisting of different components, to describe the increase of the same component＇s failure rates under different loads. All components have exponential life distributions and are nonrepairable in the system. Reliability of load- sharing 2-out- of-3： G system is calculated and some special cases for the system are discussed. The calculation and discussions show that the model is right and practical.     

The distributed representation for societal risk classification toward BBS posts

The risk classification of BBS posts is important to the evaluation of societal risk level within a period. Using the posts collected from Tianya forum as the data source, the authors adopted the societal risk indicators from socio psychology, and conduct document-level multiple societal risk classification of BBS posts. To effectively capture the semantics and word order of documents, a shallow neural network as Paragraph Vector is applied to realize the distributed vector representations of the posts in the vector space. Based on the document vectors, the authors apply one classification method KNN to identify the societal risk category of the posts. The experimental results reveal that paragraph vector in document-level societal risk classification achieves much faster training speed and at least 10% improvements of F-measures than Bag-of-Words. Furthermore, the performance of paragraph vector is also superior to edit distance and Lucene-based search method. The present work is the first attempt of combining document embedding method with socio psychology research results to public opinions area.     

Margin optimization algorithm for digital subscriber lines based on particle swarm optimization*

The margin maximization problem in digital subscriber line (DSL) systems is investigated. The particle swarm optimization (PSO) theory is applied to the nonconvex margin optimization problem with the target power and rate constraints. PSO is a new evolution algorithm based on the social behavior of swarms, which can solve discontinuous, nonconvex and nonlinear problems efficiently. The proposed algorithm can converge to the global optimal solution, and numerical example demonstrates that the proposed algorithm can guarantee the fast convergence within a few iterations.     

水泥窑协同处置生活垃圾的燃烧特性分析优化

针对传统方法难以分析掺烧生活垃圾后的水泥窑复杂燃烧特性的问题,引入数据挖掘技术,以国内某水泥厂为对象,采集相关参数数据,使用稳定性选择算法分析各参数对煤耗与NO_x排量的影响系数,通过随机森林算法建立煤耗与NO_x排量的数学模型,结合K-means聚类算法得出关键优化参数及其最优值。结果表明,该方法能够建立精确的煤耗与NO_x排量模型,挖掘出节能减排的关键优化参数及其最优目标值。通过改善关键优化参数至最优值,能够大大降低煤耗与NO_x排量,可指导水泥厂优化窑内燃烧特性。