基于数据流的船舶证书智能化审批研究

当前海事证书审批虽然已经由纸质审批发展为电子审批,但依然是以人为核心的审批方式,大数据等科技元素融合不足,难以适应当下信息时代的要求。文中介绍了以"数据流"为核心,推进"审核条件"向"具备条件"转变,不再强调审批的独立地位,同时融合大数据等技术,实现以数据为核心,打造一款标准化的海事智能化审批系统,并对未来AI智能审批提出展望。

Clustering algorithm for multiple data streams based on spectral component similarity

A new algorithm for clustering multiple data streams is proposed.The algorithm can effectively cluster data streams which show similar behavior with some unknown time delays.The algorithm uses the autoregressive （AR） modeling technique to measure correlations between data streams.It exploits estimated frequencies spectra to extract the essential features of streams.Each stream is represented as the sum of spectral components and the correlation is measured component-wise.Each spectral component is described by four parameters,namely,amplitude,phase,damping rate and frequency.The ε-lag-correlation between two spectral components is calculated.The algorithm uses such information as similarity measures in clustering data streams.Based on a sliding window model,the algorithm can continuously report the most recent clustering results and adjust the number of clusters.Experiments on real and synthetic streams show that the proposed clustering method has a higher speed and clustering quality than other similar methods.

IMPROVED ALGORITHM FOR CFD/CSD COUPLED SYSTEM DESIGN AND CALCULATION

The data information transfer and time marching strategies between computational fluid dynamics （CFD） and computational structural dynamics （CSD） play crucial roles on the aeroelastic analysis in a time domain. An improved CFD/CSD coupled system is designed, including an interpolation method and an improved loosely coupled algorithm. The interpolation method based on boundary element method （BEM） is developed to transfer aerodynamic loads and structural displacements between CFD and CSD grid systems, it can be universally used in fluid structural interaction solution by keeping energy conservation. The improved loosely coupled algo-rithm is designed, thus it improves the computational accuracy and efficiency. The new interface is performed on the two-dimensional （2-D） extrapolation and the aeroelastie response of AGARD445.6 wing. Results show that the improved interface has a superior accuracy.

The Analysis of the Characteristics of the Dishpan Experiment and the Revolving Motion of Atmosphere

In this paper we summarize the characteristics of the dishpan experiment, the principle of substance revolving, and the scientific basis of the “retrograde wave in only one direction” with respect to weather data and S. C. OuYang＇s articles in which the fundamental questions in the meteorological theory were pointed out. Furthermore, we discuss the systematic changes involving the concept, theory, and method that substance evolves.

Data partitioning based on sampling for power load streams

A novel data streams partitioning method is proposed to resolve problems of range-aggregation continuous queries over parallel streams for power industry.The first step of this method is to parallel sample the data,which is implemented as an extended reservoir-sampling algorithm.A skip factor based on the change ratio of data-values is introduced to describe the distribution characteristics of data-values adaptively.The second step of this method is to partition the fluxes of data streams averagely,which is implemented with two alternative equal-depth histogram generating algorithms that fit the different cases：one for incremental maintenance based on heuristics and the other for periodical updates to generate an approximate partition vector.The experimental results on actual data prove that the method is efficient,practical and suitable for time-varying data streams processing.

Min-wise hash function-based sampling over distributed data streams

In order to avoid the redundant and inconsistent information in distributed data streams, a sampling method based on min-wise hash functions is designed and the practical semantics of the union of distributed data streams is defined. First, for each family of min-wise hash functions, the data with the minimum hash value are selected as local samples and the biased effect caused by frequent updates in a single data stream is filtered out. Secondly, for the same hash function, the sample with the minimum hash value is selected as the global sample and the local samples are combined at the center node to filter out the biased effect of duplicated updates. Finally, based on the obtained uniform samples, several aggregations on the defined semantics of the union of data streams are precisely estimated. The results of comparison tests on synthetic and real-life data streams demonstrate the effectiveness of this method.

Identification of Sewage Monitoring Data Based on Mathematical Statistics

In order to reduce the enormous pressure to environmental monitoring work brought by the false sewage monitoring data, Grubbs method, box plot, t test and other methods are used to make depth analysis to the data, providing a set of technological process to identify the sewage monitoring data, which is convenient and simple.

PROCESS DRIVEN ANALYSIS AND DESIGN OF MIS

This paper presents the methodology of process driven analysis to eliminate the redundant information conducted from homogeneous procedures in management system. Process flow is emphasized and events triggered by process based states are described.

Super point detection based on sampling and data streaming algorithms

In order to improve the precision of super point detection and control measurement resource consumption, this paper proposes a super point detection method based on sampling and data streaming algorithms （SDSD）, and proves that only sources or destinations with a lot of flows can be sampled probabilistically using the SDSD algorithm. The SDSD algorithm uses both the IP table and the flow bloom filter （BF） data structures to maintain the IP and flow information. The IP table is used to judge whether an IP address has been recorded. If the IP exists, then all its subsequent flows will be recorded into the flow BF; otherwise, the IP flow is sampled. This paper also analyzes the accuracy and memory requirements of the SDSD algorithm , and tests them using the CERNET trace. The theoretical analysis and experimental tests demonstrate that the most relative errors of the super points estimated by the SDSD algorithm are less than 5%, whereas the results of other algorithms are about 10%. Because of the BF structure, the SDSD algorithm is also better than previous algorithms in terms of memory consumption.

Research of NS dataflow mechanism and its analyzer implementation

This paper analyzes the main elements in NS network simulator, makes adetailed view of dataflow management in a link, a node, and an agent, respectively, and introducesthe information described by its trace file. Based on the analysis of transportation and treatmentof different packets in NS, a dataflow state machine is proposed with its states exchange triggeringevents and a dataflow analyzer is designed and implemented according to it. As the machine statefunctions, the analyzer can make statistic of total transportation flux of a specified dataflow andoffer a general fluctuation diagram. Finally, a concrete example is used to test its performance.

Product Data Management Implementation

On the basis of PDM(product data management) definition and its connotation, the factors to ensure implementation success are analyzed. The definition phase, analysis phase, design phase, build and test phase, and post production phase during PDM implementation are described. The implementation is divided into ten processes, which consist of the above different phases. The relationships between phases and processes are illustrated. Finally, a workflow is proposed to guide the implementing at a fixed price.

Ground data transfer research in AMS-02

To increase the performance of bulk data transfer mission with ultra-long TCP （ transmission control protocol） connection in high-energy physics experiments, a series of experiments were conducted to explore the way to enhance the transmission efficiency. This paper introduces the overall structure of RC@ SEU （ regional center @ Southeast University） in AMS （alpha magnetic spectrometer）-02 ground data transfer system as well as the experiments conducted in CERNET （China Education and Research Network）/CERNET2 and global academic Internet. The effects of the number of parallel streams and TCP buffer size are tested. The test confirms that in the current circumstance of CERNET, to find the fight number of parallel TCP connections is the main method to improve the throughput. TCP buffer size tuning has little effect now, but may have good effects when the available bandwidth becomes higher.

Grid data management based on dataspace

To manipulate the heterogeneous and distributed data better in the data grid,a dataspace management framework for grid data is proposed based on in-depth research on grid technology.Combining technologies in dataspace management,such as data model iDM and query language iTrails,with the grid data access middleware OGSA-DAI,a grid dataspace management prototype system is built,in which tasks like data accessing,Abstraction,indexing,services management and answer-query are implemented by the OGSA-DAI workflows.Experimental results show that it is feasible to apply a dataspace management mechanism to the grid environment.Dataspace meets the grid data management needs in that it hides the heterogeneity and distribution of grid data and can adapt to the dynamic characteristics of the grid.The proposed grid dataspace management provides a new method for grid data management.

Design of the Testing System for Jet Elements

To analyze the errors of processing data, the testing principle for jet elements is introduced and the property of testing system is theoretically and experimentally studied. On the basis of the above, the method of processing data is presented and the error formulae, which are the functions of the testing system property, are derived. Finally, the methods of reducing the errors are provided. The measured results are in correspondence with the theoretical conclusion.

An automatic identification algorithm for freeway bottleneck based on loop detector data

A bottleneck automatic identification algorithm based on loop detector data is proposed. The proposed algorithm selects the critical flow rate as the trigger variable of the algorithm which is calculated by the road conditions the level of service and the proportion of trucks.The process of identification includes two parts. One is to identify the upstream of the bottleneck by comparing the distance between the current occupancy rate and the mean value of the occupancy rate and the variance of the occupancy rate.The other process is to identify the downstream of the bottleneck by calculating the difference of the upstream occupancy rate with that of the downstream.In addition the algorithm evaluation standards which are based on the time interval of the data the detection rate and the false alarm rate are discussed.The proposed algorithm is applied to detect the bottleneck locations in the Shanghai Inner Ring Viaduct Dabaishu-Guangzhong road section.The proposed method has a good performance in improving the accuracy and efficiency of bottleneck identification.

Trends of Extreme Flood Events in the Pearl River Basin during 1951-2010

The study investigated the trend of extreme flood events in the Pearl River basin during 1951-2010. Stream flow data at 23 gauging stations were used for the study. The Pearson type III distribution was selected for the flood frequency analysis. Results indicate that extreme flood events increase significantly in the Pearl River Basin since 1980. At the 23 gauging stations, there are 16 (70%) stations show positive (increasing) trends in 1981-2010. Most of the 16 stations are located along the West River and North River. While 7 (30%) stations show negative (decreasing) trends, and are found in the East River and the southeast region of the West River Basin.

SCMR:a semantic-based coherence micro-cluster recognition algorithm for hybrid web data stream

Data aggregation from various web sources is very significant for web data analysis domain. In ad- dition, the recognition of coherence micro cluster is one of the most interesting issues in the field of data aggregation. Until now, many algorithms have been proposed to work on this issue. However, the deficiency of these solutions is that they cannot recognize the micro-cluster data stream accurately. A semantic-based coherent micro-cluster recognition algorithm for hybrid web data stream is nronosed.Firstly, an objective function is proposed to recognize the coherence micro-cluster and then the coher- ence micro-cluster recognition algorithm for hybrid web data stream based on semantic is raised. Fi-

An Experimental Analysis of Water and Soil Conservation Effected by Micro-landscape Structure

[Objective] This comparative experiment was to explore the soil loss con- trol effects under cultivation combination of different soil and vegetation types, and to provide scientific basis for the upcoming pilot project of ecological recovery. [Method] Both the rudiment of water locomotion functioned by micro-landscape structures and different spatial combinations of various landscape constituents are considered, thus, the combination of multi-soil type, crop species and site conditions is designed in three different experimental sites. [Result] Soil loss estimates in experiments in South Wello significantly depended on various soil type, slope, vegetation and type of con- servation structure; grass cover tremendously reduces soil loss; legume cultivation performed better than cereal cultivation in soil loss control. [Conclusion] By conduct- ing the data analysis of the experiment, a scientific reference is proposed to the agri- culture planting and protective mode for the alleviation of water and soil loss in Amhara Region, Ethiopia.

Assimilation of High Frequency Radar Data into a Shelf Sea Circulation Model

High Frequency(HF) radar current data is assimilated into a shelf sea circulation model based on optimal interpolation(OI) method. The purpose of this work is to develop a real-time computationally highly efficient assimilation method to improve the forecast of shelf current. Since the true state of the ocean is not known, the specification of background error covariance is arduous. Usually, it is assumed or calculated from an ensemble of model states and is kept in constant. In our method, the spatial covariances of model forecast errors are derived from differences between the adjacent model forecast fields, which serve as the forecast tendencies. The assumption behind this is that forecast errors can resemble forecast tendencies, since variances are large when fields change quickly and small when fields change slowly. The implementation of HF radar data assimilation is found to yield good information for analyses. After assimilation, the root-mean-square error of model decreases significantly. Besides, three assimilation runs with variational observation density are implemented. The comparison of them indicates that the pattern described by observations is much more important than the amount of observations. It is more useful to expand the scope of observations than to increase the spatial interval. From our tests, the spatial interval of observation can be 5 times bigger than that of model grid.

Energy-balanced clustering protocol for data gathering in wireless sensor networks with unbalanced traffic load

Energy-efficient data gathering in multi-hop wireless sensor networks was studied,considering that different node produces different amounts of data in realistic environments.A novel dominating set based clustering protocol (DSCP) was proposed to solve the data gathering problem in this scenario.In DSCP,a node evaluates the potential lifetime of the network (from its local point of view) assuming that it acts as the cluster head,and claims to be a tentative cluster head if it maximizes the potential lifetime.When evaluating the potential lifetime of the network,a node considers not only its remaining energy,but also other factors including its traffic load,the number of its neighbors,and the traffic loads of its neighbors.A tentative cluster head becomes a final cluster head with a probability inversely proportional to the number of tentative cluster heads that cover its neighbors.The protocol can terminate in O(n/lg n) steps,and its total message complexity is O(n2/lg n).Simulation results show that DSCP can effectively prolong the lifetime of the network in multi-hop networks with unbalanced traffic load.Compared with EECT,the network lifetime is prolonged by 56.6% in average.