基于序列格的隐私时序模式挖掘方法

基于差分隐私的时间序列模式挖掘方法中,序列的最大长度以及添加拉普拉斯噪声的多少直接制约着挖掘结果的可用性.针对现有时间序列模式挖掘方法全局敏感度过高、挖掘结果可用性较低的不足问题,提出了一种基于序列格的差分隐私下时间序列模式挖掘方法PrivTSM(Differentially Private Time Series Pattern Mining).该方法首先利用最长路径的策略对原始数据库进行截断处理;在此基础上,采用表连接操作生成满足差分隐私的序列格;结合序列格结构本身的特性,合理分配隐私预算,提高输出模式的可用性.理论分析表明PrivTSM方法满足ε-差分隐私,基于真实数据库上实验结果表明,PrivTSM方法的准确率TPR(True Postive Rate)和平均相对误差ARE(Average Relative Error)明显优于N-gram和Prefix-Hybrid方法.

Banach格上的无界绝对弱收敛的弱~*Dunford-Pettis算子

为进一步研究Banach格上算子的性质,首先,给出无界绝对弱收敛的弱~*Dunford-Pettis算子的定义.其次,通过构造不交序列,探究无界绝对弱收敛的弱~*Dunford-Pettis算子的等价刻画和控制性,并获得了相关推论.最后,研究了该算子与弱~*Dunford-Pettis算子、极限算子和紧算子间的关系.

Partial transmitting sequence method based on trellis factor search

To obtain good trade-offs between complexity and performance onpeak-to-average power ratio (PAPR) reduction in orthogonal frequency division multiplexing (OFDM)using partial transmitting sequence (PTS) schemes, a trellis structure based PTS factor searchmethod is proposed. The trellis search is with a variant constraint length L_C, 1 ≤ L_C ≤ V-1,where V is the number of PTS subblocks. The method is to decide a PTS factor by searching all thepossible paths obtained by varying L_C consecutive factors. The trellis search can be viewed as ageneral PTS factor search model. If L_C = V-1, it is a full search, and if L_C = 1, it is aniterative search. Using different constraint lengths, trellis factor search PTS exhibits differentPAPR reduction performances. A larger L_C results in a better performance and L_C = V-1 results inthe optimum. However, a larger L_C requires more computation. This helps to choose a good trade-offbetween complexity and performance.

基于差分隐私的轨迹模式挖掘算法

针对现有基于差分隐私的频繁轨迹模式挖掘算法全局敏感度过高、挖掘结果可用性较低的问题,提出一种基于前缀序列格和轨迹截断的差分隐私下频繁轨迹模式挖掘算法——LTPM。该算法首先利用自适应的方法获得最优截断长度,然后采用一种动态规划的策略对原始数据库进行截断处理,在此基础上,利用等价关系构建前缀序列格,并挖掘频繁轨迹模式。理论分析表明LTPM算法满足ε-差分隐私;实验结果表明,LTPM算法的准确率(TPR)和平均相对误差(ARE)明显优于N-gram和Prefix算法,能有效提高挖掘结果的可用性。

Sequence Analysis of ITS Region of rDNA of Alternaria Nees. from Some Areas of China

[Objective] The study aimed to identify Alternaria Nees from some areas of China at molecular level by analyzing the rDNA ITS sequence. [ Method ] The DNA sequences coding for the 5.8S rDNA and the flanking internal transcribed spacers （ ITS1 and ITS2） were amplified by PCR with universal primers ITS4 and ITS5 and subsequently sequenced for 34 Alternaria isolates from different areas of China. [Result] Sequences analysis showed that 5.8S rDNA was 159 bp and no variation in tested 34 isolates. There had variables sites in ITS. The isolates that had same sequences as A. tenuissima or A. alternata all put up eurytopicity to area and host. The variables sites of the isolates showed the diver- sity of Alternaria in the hosts of Oleaceae, Rosaceae and Solanaceae. At the same time that ITS could not clearly separated the isolates was indicated. The results indicated that the phylogenetic relationship were not closely related to the geographical origin and hosts of these isolates. [ Conclusion] The sequence analysis of ITS region could provide theory basis for the identification of Alternaria Nees..

度序列在图结构相似研究中的应用

给出一个度序列的所有的度序列分解,研究了度序列的并、分度重合、分度撕裂、分解运算;给出特殊度序列匹配;用图同态运算和图的度序列来判断图同构,以及度序列的图结构的相似性:如果2个图的度序列相等,则它们有非平凡全同构度序列匹配;建立了度序列格(伴随图格)与普通格的一个等价关联。度序列格和图格为图结构的相似与匹配提供了“集合形式的相似与匹配”,使得点-点(图-图)之间的相似与匹配上升到集合-集合之间的相似与匹配,更加适合研究网络社区间的相似与匹配。提出了求解完备度序列、最近度序列、最小度序列、近似最近度序列、最近度序列邻居等几个尚待研究的问题。

Prediction of metal futures price volatility and empirical analysis based on symbolic time series of high-frequency

The metal futures price fluctuation prediction model was constructed based on symbolic high-frequency time series using high-frequency data on the Shanghai Copper Futures Exchange from July 2014 to September 2018,and the sample was divided into 194 histogram time series employing symbolic time series.The next cycle was then predicted using the K-NN algorithm and exponential smoothing,respectively.The results show that the trend of the histogram of the copper futures earnings prediction is gentler than that of the actual histogram,the overall situation of the prediction results is better,and the overall fluctuation of the one-week earnings of the copper futures predicted and the actual volatility are largely the same.This shows that the results predicted by the K-NN algorithm are more accurate than those predicted by the exponential smoothing method.Based on the predicted one-week price fluctuations of copper futures,regulators and investors in China’s copper futures market can timely adjust their regulatory policies and investment strategies to control risks.

Rearrangement Inequality and Chebyshev＇s Sum Inequality on Positive Tensor Products of Orlicz Sequence Space with Banach Lattice

Let φ be an Orlicz function that has a complementary function φ＊ and let lφ be an Orlicz sequence space. We prove a similar version of Rearrangement Inequality and Chebyshev＇s Sum Inequality in lφ FX, the Fremlin projective tensor product of lφ with a Banach lattice X, and in lφ iX, the Wittstock injective tensor product of lφ with a Banach lattice X.

Wind Speed Forecasting Based on ARMA-ARCH Model in Wind Farms

Wind speed forecasting is signif icant for wind farm planning and power grid operation. The research in this paper uses Eviews software to build the ARMA (autoregressive moving average) model of wind speed time series, and employs Lagrange multipliers to test the ARCH (autoregressive conditional heteroscedasticity) effects of the residuals of the ARMA model. Also, the corresponding ARMA-ARCH models are established, and the wind speed series are forecasted by using the ARMA model and ARMA-ARCH model respectively. The comparison of the forecasting accuracy of the above two models shows that the ARMA-ARCH model possesses higher forecasting accuracy than the ARMA model and has certain practical value.

Golay Sequence Based Time-Domain Compensation of Frequency-Dependent I/Q Imbalance

A time-domain frequencydependent I/Q imbalance compensation scheme based on Golay complementary sequence for receiver is presented. By utilizing property of Golay sequence, the signal and its conjugate interference(image interference)in preamble are separated by correlation and used to estimate I/Q imbalance parameters.After that, a Least Square(LS) estimation of compensation filter is obtained and adopted in the compensation structure. Two applications of the presented algorithm are discussed: we could either estimate the channel along with I/Q imbalance or estimate the imbalance parameter only to maintain a lower cost. Both applications are testified by simulation. The results show that the image interference is significantly suppressed even in poor SNR condition, and the computation cost of the algorithms is low.

Modeling Time Series Analysis between Feedstuff and Hog Prices in Taiwan

Pork in Taiwan has played an important role in terms of domestic consumption, production and price fluctuation in several decades. This study attempts to investigate the causal relationship between hog and feedstuff prices in Taiwan by using monthly time series over the period of January 2000 to October 2010. Prices from hog, feedstuff, soybean meal and corn are considered and performed through a multivariate vector autoregressive （VAR） model. As the empirical results, the long-run equilibrium is captured identifying price elasticity among the variables using the Johansen cointegration diagnosis. Then, the Granger causality approach shows that bidirectional relationship is detected running from feedstuff to corn and from soybean meal to hog as well as unidirectional relationship running from corn to hog, from feedstuff to hog and from soybean meal to feedstuff. In the conclusions, we point out to raw material prices of feedstuff, namely corn and soybean meal that have an importance to hog price as the cost of meat production. Pig farmers and policy-makers should understand the behavior of price interactions to manage the risks on hog market and to increase the profitability on suitable price.

Time Series of Random Macro-price and Application

This paper tries to utilize the methods of stochastic analysis and matrix analysis to research the existential problem of price series. By using the means of time series analysis, the input-output, Markov processes and the modern matrix analysis, the limiting problem of price balance and vibration in stochastic economic environment has been researched, and surprising conclusions obtained are as following： the probability that the economic collapse time is equal ∞ is 0.

Exploring Image Culture Through Narrative： A Study on Jennifer Egan＇s Twitter Fiction Black Box

Notable for the completeness with which it surrenders formally and artistically to the textual dictates of Twitter, Jennifer Egan＇s 2012 short science fiction Black Box is one of the most triumphant and fully-fledged fictions written in the form of new media. This paper explores the Twitter narrative employed in Black Box, pointing out that the serialized tweeting format of the story released via computer, mobile phone, or other electronic equipments brings readers immediate reading experience, allowing readers to sense the same feelings as the protagonist does. Through the experimental serialization of＂Twitter＂ narrative, Egan expresses her concerns and worries about the security of the American security as well as the whole world in the post-＂9.11＂ period and at the same time she embraces the virtues and pleasures of traditional storytelling delivered through a wholly new digital format. This paper concludes that Black Box is perhaps one of the boldest experiments of narrative form and is direct exploration into the contemporary image culture.

A Self-synchronizing Stream Encryption Scheme Based on One-Dimensional Coupled Map Lattices

We present a self-synchronizing stream encryption scheme based on one-dimensional coupled map lattices which is introduced as a model with the essential features of spatiotemporal chaos, and of great complexity and diffusion capability of the little disturbance in the initial condition. To evaluate the scheme, a series of statistical tests are employed, and the results show good random-look nature of the ciphertext. Furthermore, we apply our algorithm to encrypt a grey-scale image to show the key sensitivity.

Effect of Topography and Accessibility on Vegetation Dynamic Pattern in Mountain-hill Region

Knowledge of both vegetation distribution pattern and phenology changes is very important.Their complicated relationship with elevation and accessibility were explored through a geographically weighted regression(GWR) framework in Fujian province,China.The 16-day time series of 250 m Moderate Resolution Imaging Spectroradiometer(MODIS) Enhanced Vegetation Index(EVI) dataset from 2000 to 2010 was applied.Wavelet transform method was adopted to decompose the original time series and construct the annual maximum EVI and amplitude of the annual phenological cycle(EVI).Candidate explaining factors included topographic conditions,accessibility variables and proportions of primary vegetation types.Results revealed very strong positive influence from parameters of elevation and accessibility to big rivers and negative effect from accessibility to resident on both maximum EVI and phenological magnitude through ordinary linear least square(OLS) regression analysis.GWR analysis revealed that spatially,the parameters of topography and accessibility had a very complex relationship with both maximum EVI and phenology magnitude,as a result of the various combinations of environmental factors,vegetation composition and also intensive anthropogenic impact.Apart from the continuously increasing trend of phenology magnitude with increasing altitude,the influence of topography and accessibility on maximum EVI and phenological magnitude generally decreased,even from strongly positive to negative,with increasing altitude or distance.Specially,the most rapid change of correlation coefficient between them was observed within a low elevation or close distance;less variation was discovered within a certain range of medium altitude or distance and their relationship might change above this range.Non-stationary approaches are needed to better characterize the complex vegetation dynamic pattern in Mountain-hill Region.

An Empirical Study on the stock Price of Modeling

the model in time series analysis are widely used in the field of economy. We often use the model in time series to analyze data, but without regard to the rationality of the model. In this paper, we introduce and analyze Ping An Of China（601318） shares at the opening price（2013/01/04-2013/07/04）.The model is established by analyzing data. Modeling steps of ARIMA model and GARCH model are presented in this paper. The data whether ARIMA model is suitable by white noise. Or the data whether GARCH model is suitable by since the correlation of variance test. By comparing the analysis, it selects a more reasonable model.

On convergence analysis of a derivative-free trust region algorithm for constrained optimization with separable structure

In this paper,we propose a derivative-free trust region algorithm for constrained minimization problems with separable structure,where derivatives of the objective function are not available and cannot be directly approximated.At each iteration,we construct a quadratic interpolation model of the objective function around the current iterate.The new iterates are generated by minimizing the augmented Lagrangian function of this model over the trust region.The filter technique is used to ensure the feasibility and optimality of the iterative sequence.Global convergence of the proposed algorithm is proved under some suitable assumptions.

SEQUENCE-BASED PROTEIN-PROTEIN INTERACTION PREDICTION VIA SUPPORT VECTOR MACHINE

This paper develops sequence-based methods for identifying novel protein-protein interactions （PPIs） by means of support vector machines （SVMs）. The authors encode proteins ont only in the gene level but also in the amino acid level, and design a procedure to select negative training set for dealing with the training dataset imbalance problem, i.e., the number of interacting protein pairs is scarce relative to large scale non-interacting protein pairs. The proposed methods are validated on PPIs data of Plasmodium falciparum and Escherichia coli, and yields the predictive accuracy of 93.8% and 95.3%, respectively. The functional annotation analysis and database search indicate that our novel predictions are worthy of future experimental validation. The new methods will be useful supplementary tools for the future proteomics studies.

基于时空混沌的CPSK多用户扩频通信

传统的混沌扩频(CDSS)是利用混沌序列量化、编码后产生的0、1序列作为扩频码,来实现频谱展宽。另外,由于混沌序列本身的宽频特性,一些传统的混沌数字调制技术也可被用于扩频通信系统的设计。在单向耦合映像格子(OCML)时空混沌模型同步的基础上,直接利用混沌相位键控(CPSK)调制技术构建了一个多用户扩频通信系统。该模型为每个用户分配一个OCML时空混沌模型,为了更好地利用时空混沌系统的时间与空间混沌特性,其采用"跳格序列"作为扩频调制序列对用户信息进行调制。通过与传统混沌直接序列扩频(CDSS)系统的仿真比较发现,所设计的CPSK调制多用户扩频通信系统拥有比后者更好的误码性能及安全性能。

Proofs of some conjectures on monotonicity of number-theoretic and combinatorial sequences

In 2012,Zhi-Wei Sun posed many conjectures about the monotonicity of sequences of form {n√zn},where {zn} is a familiar number-theoretic or combinatorial sequence. We show that if the sequence {zn+1/zn}is increasing(resp.,decreasing),then the sequence {n√zn} is strictly increasing(resp.,decreasing) subject to a certain initial condition. We also give some sufficient conditions when {zn+1/zn} is increasing,which is equivalent to the log-convexity of {zn}. As consequences,a series of conjectures of Zhi-Wei Sun are verified in a unified approach.