创新是企业持续发展的动力

创新,顾名思义就是推陈出新。企业创新战略理论形成于20世纪初,至今已备受国内外许多企业家的关注和青睐。其实质是根据市场环境和形势要求,开创性地做出战略性调整,包括进行体制创新、机制创新、制度创新、技术创新、组织创新、管理创新等,不断确立新的领先优势。因此有经济学家认为,企业创新战略就是一个将资源从低效率使用转向高效率使用的过程。

黑色棒棒糖——小蝌蚪

春季的一天,我在荷花池里网到了几只活泼可爱、长得黑乎乎的小动物——蝌蚪。小蝌蚪长着椭(tuǒ)圆形的小脑袋,细长的扁扁的尾巴,中间还有条细细的黑线。所以,整体看起来。

An Algorithm to Construct Concurrent Reachability Graph of Petri Nets

Reachability graph is a very important tool to analyze the dynamic properties of Petri nets, but the concurrent relation of transitions in Petri nets cannot be represented by reachability graph. Petri net is a concurrent system, while reachability graph is a serial one. However, concurrency is a kind of property which is not only very significant but also difficult to be analyzed and controlled. This paper presents the concepts of concurrent reachable marking and concurrent reachable graph in order to represent and analyze the concurrent system. The algorithm constructing concurrent reachable marking set and concurrent reachability graph is also shown so that we can study the response problems among services in a network computing environment and analyze the throughput of the system. The Dining Philosophers Problem, which is a classic problem of describing the management of concurrent resources, is given as an example to illustrate the significance of concurrent reachability graph.

An SPN analysis method for parallel scheduling in Ad Hoc networks

In this paper, a new analytic method for modeling and evaluating mobile ad hoc networks (MANET) is proposed. Petri nets technique is introduced into MANET and a packet-flow parallel scheduling scheme is presented using Stochastic Petri Nets (SPN). The flowing of tokens is used in graphics mode to characterize dynamical features of sharing a single wireless channel. Through SPN reachability analysis and isomorphic continuous time Markov process equations, some network parameters, such as channel efficiency, one-hop transmission delay etc., can be obtained. Compared with conventional performance evaluation methods, the above parameters are mathematical expressions instead of test results from a simulator.

ANOMALY INTRUSION DETECTION METHOD USING FOURIER TRANSFORM

A set of discrete points obtained from audit records on a behavior session is processed with Fourier transform. The criterion of selecting Fourier transform coefficients is introduced, and is used to find a unified value from the set of coefficients. This unified value is compared with a threshold to determine whether the session is abnormal. Finally simple test results are reported.

Experimental and Numerical Analysis of Turbulent Flow Heat Transfer Enhancement in a Horizontal Circular Tube Using Mesh Inserts

The present work focuses on experimental and numerical investigations of the augmentation of turbulent flow heat transfer in a horizontal circular tube by means of mesh inserts with air as the working fluid. Sixteen types of mesh inserts with screen diameters of 22 mm, 18 mm, 14 mm and 10 mm for varying distance between the screens of 50 mm, 100 mm, 150 mm and 200 mm in the porosity range of 99.73 to 99.98 were considered for experimentation. The horizontal tube was subjected to constant and uniform heat flux. The Reynolds number varied from 7,000 to 14,000. The results are compared with the clear flow case when no porous material was used. Computational fluid dynamics （CFD） techniques were also employed to perform optimization analysis of the mesh inserts. The horizontal tube along with mesh inserts was modeled in Gambit 2.2.30 with fine meshing and analyzed using FLUENT 6.2.16. CFD analysis was performed initially for plain tube and the results are compared with experimental values for validation.

“网”里乾坤

背景：有一只鸟从远处飞来。捕鸟者张开鸟网等着它，鸟一头扎进了网，捕鸟者轻而易举捕得了鸟。这时捕鸟者发现，鸟只是钻进网上的一个网眼。于是有人便制作了只有一个网眼的捕鸟网，结果再也捕不到鸟了。

Network Biological Modeling:A Novel Approach to Interpret the Traditional Chinese Medicine Theory of Exterior-Interior Correlation Between the Lung and Large Intestine

Objective To study the common pathogenesis of pneumonia and colitis using modern biological network analysis tools,and to explore the theory that the lung and large intestine are exteriorly and interiorly related.Methods The relevant target genes(hereinafter,“targets”)of pneumonia and colitis were separately queried on the GeneCards database.The main targets of the two diseases were then screened out according to their correlation scores and intersected to obtain those common to the two diseases.Metascape was used to analyze the main and common targets identified,and the Database for Annotation,Visualization and Integrated Discovery(DAVID)was used to enrich and analyze the common targets.Cytoscape 3.7.2 software was used to build the network diagram.Results In total,54 targets,such as TNF,IL-10,IL-6,IL-2,IL-4,TLR4,TLR2,CXCL8,IL-17A and IFNG,etc.,are common to pneumonia and colitis,which are mainly enriched in these processes such as cytokine–cytokine receptor interaction,the Tcell receptor signaling pathway,the Toll-like receptor signaling pathway and the Jak-STAT signaling pathway.The Metascape modular analysis identified 11 modules for pneumonia,six modules for colitis,and two modules for the common targets.Conclusions Pneumonia and colitis have the same pathogenic targets and mechanisms of action and finally interact with each other through inflammatory reactions and immune responses.This provides a probable molecular mechanism that explains the theory that the lung and large intestine are exteriorly and interiorly related.

Fourier and wavelet transformations application to fault detection of induction motor with stator current

Fault detection of an induction motor was carried out using the information of the stator current. After synchronizing the actual data, Fourier and wavelet transformations were adopted in order to obtain the sideband or detail value characteristics under healthy and various faulty operating conditions. The most reliable phase current among the three phase currents was selected using an approach that employs the fuzzy entropy measure. Data were trained with a neural network system, and the fault detection algorithm was verified using the unknown data. Results of the proposed approach based on Fourier and wavelet transformations indicate that the faults can be properly classified into six categories. The training error is 5.3×10-7, and the average test error is 0.103.

Comparison of Artificial Neural Networks,Geographically Weighted Regression and Cokriging Methods for Predicting the Spatial Distribution of Soil Macronutrients(N,P,and K)

Soil macronutrients(i.e. nitrogen(N), phosphorus(P), and potassium(K)) are important soils components and knowing the spatial distribution of these parameters are necessary at precision agriculture. The purpose of this study was to evaluate the feasibility of different methods such as artificial neural networks(ANN) and two geostatistical methods(geographically weighted regression(GWR) and cokriging(CK)) to estimate N, P and K contents. For this purpose, soil samples were taken from topsoil(0–30 cm) at 106 points and analyzed for their chemical and physical parameters. These data were divided into calibration(n = 84) and validation(n = 22). Chemical and physical variables including clay, p H and organic carbon(OC) were used as auxiliary soil variables to estimate the N, P and K contents. Results showed that the ANN model(with coefficient of determination R^2 = 0.922 and root mean square error RMSE = 0.0079%) was more accurate compared to the CK model(with R^2 = 0.612 and RMSE = 0.0094%), and the GWR model(with R^2 = 0.872 and RMSE = 0.0089%) to estimate the N variable. The ANN model estimated the P with the RMSE of 3.630 ppm, which was respectively 28.93% and 20.00% less than the RMSE of 4.680 ppm and 4.357 ppm from the CK and GWR models. The estimated K by CK, GWR and ANN models have the RMSE of 76.794 ppm, 75.790 ppm and 52.484 ppm. Results indicated that the performance of the CK model for estimation of macro nutrients(N, P and K) was slightly lower than the GWR model. Also, the accuracy of the ANN model was higher than CK and GWR models, which proved to be more effective and reliable methods for estimating macro nutrients.

Air Pollution Interpolation Analysis Based on Measured and Simulated Sites in Nanjing

Based on the statistical analysis of API （air pollution index）, the study improves the layout of the site in the downtown of Nanjing and the surroundings. Through selecting more relevant factors to establish the API regression equation and making the inversion of API data in simulated sites, the interpolation values of API in both actual sites and simulated sites have been calculated. The methods include IDW （inverse distance weighting） interpolation, Spline interpolation, and Kriging interpolation Spherical model, Exponential model and the Gaussian model. Meanwhile, through the cross-validation to test the results of interpolation in different models or parameters, the study also obtains the best fit of the interpolation model or parameters. In addition, IDW p = 3, fitting coefficient of 0.644; Spline interpolation w = 1, the fitting coefficient of 0.972; Kriging interpolation, Gaussian, fitting coefficient of 0.684. The study indicates that in best fitting model, the parameters after in increasing the simulated site are not in line with the ones previous. The result shows that it is best to test different data separately and select the appropriate interpolation model, but not blindly use the same spatial interpolation. After the increasing of the stimulated site, the API estimated results in three interpolation methods are consistent with the spatial distribution trend. In the aspect of calculating the range, the improvement close the results between 3 interpolation methods and increase of the stimulated sites, and the values of Spline interpolation and Kriging interpolation is closer.

Study on the Method for Obtaining Acceleration Waveform Records from Velocity Type Seismograms of the Digital Seismograph Network

The authors proposed a method for obtaining high-quality acceleration seismograms from velocity type seismograms of digital Seismographic network, and took as an example the analysis and processing of the seismograms of a same earthquake that was simultaneously recorded by velocity seismograph CTS1-EDAS24 and strong motion seismograph EST-Q4128 installed in Jixian Station, Tianjin. The calculation steps and the processing method have been discussed in detail. From the analysis and the comparison of the obtained results, it is concluded that the proposed method is simple and effective, and it broadens the application of digital seismographic network.

An Addressing and Routing Scheme Based on Modified Euclidean Space for Hexagonal Networks

The addressing and routing algorithm on hexagonal networks is still an open problem so far.Although many related works have been done to resolve this problem to some extent,the properties of hexagonal networks are still not explored adequately.In this paper,we first create an oblique coordinate system and redefine the Euclidean space to address the hexagonal nodes.Then an optimal routing algorithm using vectors and angles of the redefined Euclidean space is developed.Compared with the traditional 3-directions scheme and the Cayley graph method,the proposed routing algorithm is more efficient and totally independent of the scale of networks with two-tuples addresses.We also prove that the path(s) obtained by this algorithm is always the shortest one(s).

A Parametric Autoregressive Model for the Extraction of Electric Network Frequency Fluctuations in Audio Forensic Authentication

This paper proposes a new method for extracting ENF （electric network frequency） fluctuations from digital audio recordings for the purpose of forensic authentication. It is shown that the extraction of ENF components from audio recordings is realizable by applying a parametric approach based on an AR （autoregressive） model. The proposed method is compared to the existing STFT （short-time Fourier transform） based ENF extraction method. Experimental results from recorded electrical grid signals and recorded audio signals show that the proposed approach can improve the time resolution in the extracted ENF fluctuations and improve the detection of tampering with short alterations in longer audio recordings.

Bitmap lattice index in road networks

A novel technique called the bitmap lattice index(BLI) is proposed, which combines the advantages of a wireless broadcasting environment with a road network. Existing road networks are based on the on-demand method: a server's workload increases as the query request increases when a server sends a client information. To solve this problem, we propose the BLI. The BLI denotes an object and a node as 0 and 1 in the Hilbert curve(HC) map. The BLI can identify the position of a node and an object through bit information; it can also reduce the broadcasting frequency of a server by reducing the size of the index, thereby decreasing the access latency and query processing times. Moreover, the BLI is highly effective for data filtering, as it can identify the positions of both an object and a node. In a road network, if filtering is done via the Euclidean distance, it may result in an error. To prevent this, we add another validation procedure. The experiment is conducted by applying the BLI to kNN query, and the technique is assessed by a performance evaluation experiment.

Ma Yun’s Internet World

AS the founder and chairman of Alibaba Group,every one of Ma Yun’s business decisions attracts attention.From spending RMB 1.2 billion on stakes in the Guangzhou Evergrande Football Club to wholly acquiring UCWeb,and to making the Initial Public Offering(IPO)in the U.S.,Ma Yun continues to make headlines with many fingers in many pies。

基于小波消噪的EMD模型在GPS振动信号处理中的应用

经验模式分解和小波分解是当前有效处理非平稳信号的两种时频分析方法,它们各具有其优缺点,适用于不同的应用。从对GPS振动信号的预处理、时域和频域处理入手,结果分析表明,对GPS振动信号先进行小波滤波消除随机噪声的干扰,再应用经验模式分解更有利于变形特征信息的分离和提取,提取的信号与振动平台记录数据更加吻合。

第一次吃月饼

1943年8月,我8岁,哥哥11岁,去塘里网鱼。鱼网得不多却捉到一只大甲鱼,拿回家问母亲：是自己吃还是拿去街上卖?母亲想了片刻后说：“自己吃填不饱全家7人的肚子,还是拿去卖吧,换些大米全家人能吃两天。”后来邻村一个姓赵的地主要我卖给他,照街上的价格,两升米一斤。