Modal Identification of Offshore Platforms Using Statistical Method Based on ERA

Identification of modal parameters of a linear structure with output-only measurements has received much attention over the past decades. In the paper, the Natural Excitation Technique (NExT) is used for acquisition of the impulse signals from the structural responses. Then Eigensystem Realization Algorithm (ERA) is utilized for modal identification. For disregarding the fictitious ‘computational modes', a procedure, Statistically Averaging Modal Frequency Method (SAMFM), is developed to distinguish the true modes from noise modes, and to improve the precision of the identified modal frequencies of the structure. An offshore platform is modeled with the finite element method. The theoretical modal parameters are obtained for a comparison with the identified values. The dynamic responses of the platform under random wave loading are computed for providing the output signals used for identification with ERA. Results of simulation demonstrate that the proposed method can determine the system modal frequency with high precision.

Efficient Heavy Hitters Identification over Speed Traffic Streams

With the rapid increase of link speed and network throughput in recent years,much more attention has been paid to the work of obtaining statistics over speed traffic streams.It is a challenging problem to identify heavy hitters in high-speed and dynamically changing data streams with less memory and computational overhead with high measurement accuracy.In this paper,we combine Bloom Filter with exponential histogram to query streams in the sliding window so as to identify heavy hitters.This method is called EBF sketches.Our sketch structure allows for effective summarization of streams over time-based sliding windows with guaranteed probabilistic accuracy.It can be employed to address problems such as maintaining frequency statistics and finding heavy hitters.Our experimental results validate our theoretical claims and verifies the effectiveness of our techniques.

Research on the Transmutation of Chinese Loanwords-Based on Modern Chinese Dictionary(7th Edition)

Vocabulary plays an irreplaceable role in a language.As an important carrier to record foreign cultures in vocabulary,loanwords are widely used in all aspects of society.Modern Chinese Dictionary includes loanwords from a variety of languages from the perspective of universal use.This paper takes the loanwords in Modern Chinese Dictionary(7th Edition)as the closed corpus,and analyzes the etymology,structure,word length,and other aspects while making blanket statistics on the loanwords.The representative words are investigated by word frequency and described from multiple perspectives.

THE CHARACTERISTICS OF THUNDERSTORM FREQUENCY VARIATION AND THEIR POSSIBLE RELATION WITH THE ADJUSTMENT OF CROP DISTRIBUTION IN THE LEIZHOU PENINSULA

In order to research possible influences of the adjustment of plant distribution on the development frequency of thunderstorms over the Leizhou Peninsula, mathematic statistic methods, including correlation analyses, 11 kinds of fitting models and all-variable regression methods, were used for analyses and research. The results show that the average trend of the number of annual thunderstorm days is descending obviously, and there are thunderstorms in all seasons, in which warm post-midday thunderstorms have taken up the most part, and high frequency is found from May to September, and the starting and ending dates of thunderstorms have a great annual discrepancy. The vegetation structure has been improved along with the reduction of rice fields and the area increment of sugarcane and fruits planting, which results in the decrease of the number of thunderstorm days; the change in the characteristics of winter spare fields, which is caused by the planting of vegetables, limits the formation of thunderstorms in early winter and late spring. Meanwhile, the area adjustment of peanut planting has little influence on the variation of thunderstorm days. The adjustment of principal crop distribution, such as rice, sugarcane, fruits and vegetables, may have obvious influence on the formation of thunderstorms, and sugarcane has the largest effect, followed in turn by rice, vegetables and fruits, and the adjustment of crop distribution has little influence on the starting and ending dates of thunderstorms.