以尚希庄水库为例探讨GB50487规范中标贯液化复判法的缺陷

以尚希庄水库为例,通过国际通用的Seed简化方法以及现行《水利水电工程地质勘察规范》的标贯复判法对其坝基土分别进行判别,得出不同的结果。由此对规范标贯复判法中的N计算公式提出质疑,建议对其进行完善。

尼日尔国际承包工程招投标程序简介

尼日尔共和国的基础设施相对落后且极不完善,因而现任政府积极扩大对外融资的力度,不断加大各种基础建设工程项目的投资和建设,如国家公路、市政道路、城市建设、住宅建筑、机场建设、给排水以及供水管道、农田整治等项目。随着中国对外开放政策的深入推行及企业自身的发展需要,越来越多的中国企业迈出国门到尼日尔来参与国际承包工程的竞争,事先了解尼日尔共和国的招投标程序和操作流程,将有助于企业知晓该国的承包市场、科学有效地降低投标风险和避免弯路,从而从容进入尼日尔国际工程承包市场。本文简述了尼日尔国际承包工程的管理机构、招投标程序、标书的编制、评标和判标的特点以及应注意的事项,以供同行参考。

Prediction Method for Network Traffic Based on Maximum Correntropy Criterion

This paper proposes a method for improving the precision of Network Traffic Prediction based on the Maximum Correntropy Criterion(NTPMCC),where the nonlinear characteristics of network traffic are considered.This method utilizes the MCC as a new error evaluation criterion or named the cost function(CF)to train neural networks(NN).MCC is based on a new similarity function(Generalized correlation entropy function,Correntropy),which has as its foundation the Parzen window evaluation and Renyi entropy of error probability density function.At the same time,by combining the MCC with the Mean Square Error(MSE),a mixed evaluation criterion with MCC and MSE is proposed as a cost function of NN training.According to the traffic network characteristics including the nonlinear,non-Gaussian,and mutation,the Elman neural network is trained by MCC and MCC-MSE,and then the trained neural network is used as the model for predicting network traffic.The simulation results based on the evaluation by Mean Absolute Error(MAE),MSE,and Sum Squared Error(SSE)show that the accuracy of the prediction based on MCC is superior to the results of the Elman neural network with MSE.The overall performance is improved by about 0.0131.

A novel face recognition method with feature combination

A novel combined personalized feature framework is proposed for face recognition (FR). In the framework, the proposed linear discriminant analysis (LDA) makes use of the null space of the within-class scatter matrix effectively, and Global feature vectors (PCA-transformed) and local feature vectors (Gabor wavelet-transformed) are integrated by complex vectors as input feature of improved LDA. The proposed method is compared to other commonly used FR methods on two face databases (ORL and UMIST). Results demonstrated that the performance of the proposed method is superior to that of traditional FR ap- proaches

The effects of fluid loss on physical performance： A critical review

Purpose： The purpose of this review was to critically analyse the cun;ent evidence investigating the effect of an athlete＇s hydration status on physical performance. Methods： A literature search of multiple databases was used to identify studies that met the inclusion criteria for this review. The included studies were then critically appraised using the Downs and Black protocol. Results： Nine articles were found to meet the inclusion criteria, with an average score of 79% for methodological quality representative of a ＂high＂ standard of research. Conclusion： The evidence suggests that dehydration has a negative impact on physical performance for activities lasting more than 30 s in duration. However dehydration was found to have no significant impact on physical performance for activities lasting less than 15 s in duration.

Water resistant features of high-risk outburst coal seams and standard discriminant model of mining under water-pressure

It is important to emphasize the value of research in safe mining technology of high-risk water outburst coal seams. We describe briefly current conditions abroad and in China. Based on an Ordovician limestone aquifer with high-risk water outburst seams in the Feicheng coal field, we analyzed the water-resistant characteristics of a coal floor aquifuge and the behavior of water head intrusion of a confined aquifer and propose a safe criterion model and relevant technology of mining above aquifers. This has brought satisfactory results in engineering practice.

SURVEILLANCE OF MOVING TARGET BEHIND PARTITIONS USING A UWB-TWDR

This paper firstly analyzes the property of the low frequency electromagnetic wave, which can penetrate many types of non-metallic materials, and the ability of Ultra-Wide Band (UWB) impulse signal which has high range resolution. Then the methods are discussed for conducting surveillance through walls, detecting and locating the moving persons behind the partitions. The schematic diagram of Through-Wall Detecting Radar (TWDR) and the models of moving target are shown and the principle of detecting the moving target is also provided with coherent superimposing technique on a range gate. Finally an algorithm for estimating the location of targets is given. The performance of TWDR is validated by the experiments of penetrating a wood block, a red brick wall and a reinforced concrete wall.

Study on the judgment model of dyeing and weaving corporation's core competence

On the basis of the dyeing and weaving corporations’ characters,this paper put forward the dimensionality and index system to analyze the core competence. This paper divided the core competence into three layers and gave out the Dimensional-Hierarchical structure of core competence through combining the analysis dimensionalities with the competence layers. The model was described to evaluate,analyze and judge the dyeing and weaving corporation’s competence.

ACTIVITY ATTACK ON REDUCED VARIANTS OF RIJNDAEL

The famous Square attacks against the Rijndael algorithm have taken advantage of the change of the balance of some bytes. Further study shows that the change of activity always happens before the change of balance, which builds the foundation for a new activity attack presented in this paper. In the activity attack, the round in which the activity changes is executed in an equivalent form to avoid the obstructive restriction of the subkeys of that round.The existence of the birthday paradox guarantees much fewer plaintexts necessary for activity attacks comparing with that for corresponding Square attacks. But no benefit may result from the new attacks performed independently because the activity attacks guess four instead of one key byte once. Only when both the balance property and the activity property are exploited at the same time can much better performance be obtained. The better performance in the simulation shows that the consuming time and chosen plaintexts necessary are both reduced to one tenth of those of the corresponding Square attacks. So the activity attacks could be viewed as an efficient supplement to the Square attacks.

Evaluation of the propensity for coal spontaneous combustion based on catastrophe theory

Generally, different prevention measures should be taken according to spontaneous combustion propensities. The current methods to evaluate the propensity of coal spontaneous combustion, such as chromatographic method of oxygen adsorption, oxidation kinetics method and activation energy method, are mostly affected by human factors. Their boundaries among different classes of propensities were all established by subjective judgments. A new evaluation method using catastrophe theory is introduced. This method can accurately depict the process of coal spontaneous combustion and the evaluation index, ＂catastrophe temperature＂, be obtained based on the model. In terms of catastrophe temperature, the spontaneous combustion propensity of different coals can be sequenced. Experimental data indicate that this method is appropriate to describe the spontaneous combustion process and to evaluate the propensity of coal svontaneous combustion.

The Characteristics of Earthquake Swarms in and around Jiangsu Province

This paper systematically analyzed 36 earthquake swarms in and around Jiangsu Province, summarized their characteristics and discussed the relationship between earthquske swarms and subsequent strong earthquakes. It also analyzed the judgment criteria for precursory earthquake swarms. Earthquake swarms in Jiangsu Province are concentrated in several areas. Most of them were of magnitude ML2.0～3.9. For most earthquake swarms, the number of earthquakes was less than 30. Time duration for about 55% of earthquake swarms was less than 15 days. The biggest magnitude of one earthquake swarm was not proportional to the number of earthquakes and time duration. There are 78% of earthquake swarms corresponded to the forthcoming earthquakes of M>4.6 in which there're 57% occured in one year, This shows a medium-and short-term criterion. Distance between earthquake swarm and future earthquake was distributed dispersedly. There were no earthquakes occurring in the same location as earthquake swarms. There was no good correlation between the magnitude and the corresponding rate of future earthquakes and the intensity of earthquake swarms. There was also no good correlation between the number of earthquakes in an earthquake swarm and the corresponding rate. The study also shows that it's better to use U-p or whole-combination to determine the type of earthquake swarm.

The ＂Pictorial Turn＂ as Crisis and the Necessity of a Critique of Visual Culture

The ＂Pictorial＂ or ＂Iconic Turn＂ is a central issue in the contemporary theory of images and visual cultural studies. Should the theories concerning the ＂Iconic Turn＂ and formulated in the last 20 years by scholars such as Gottfried Boehm, William Mitchell, Hans Belting be taken as critical theories of crisis？ Is the currently experienced ＂turn towards images＂ （and their progressive rehabilitation after a long standing philosophical and theological rejection） a sign and symptom of some crisis of people＇s relation with images, language and, generally speaking, with the representation forms of reality？ The main hypothesis of this essay envisages two sets of problems： first, the analysis of the relation between the possible idea of turning point and the concept of crisis; secondly, the thorough investigation of the relation connecting the iconic turn to the project of ＂critical iconology＂ or ＂critique of visual culture,＂ as outlined by Hans Belting and William Mitchell. From the interpretation of the ＂Iconic Turn＂ as situation of crisis and aesthetic, anthropological, and epistemological transformation follows the need for the sciences of image to provide a ＂critical iconology＂ in order to be able to theoretically reformulate the ideological and political presuppositions of some dominant contemporary forms of visual representation.

语文课堂日常性评价策略

小学语文课堂评价的宗旨是促进学生的学习和发展,让学习走向深入。课堂评价三大内容是关键能力、学习策略、情感态度。学生必须成为关键的评价主体,“清楚终点在哪”“明白身处何方”“懂得如何抵达”,是学生成为合格评价者的三大条件;提前孕伏、融入过程、对标研判则是课堂评价三大操作要点。

Discriminative Structured Dictionary Learning for Image Classification

In this paper, a discriminative structured dictionary learning algorithm is presented. To enhance the dictionary's discriminative power, the reconstruction error, classification error and inhomogeneous representation error are integrated into the objective function. The proposed approach learns a single structured dictionary and a linear classifier jointly. The learned dictionary encourages the samples from the same class to have similar sparse codes, and the samples from different classes to have dissimilar sparse codes. The solution to the objective function is achieved by employing a feature-sign search algorithm and Lagrange dual method. Experimental results on three public databases demonstrate that the proposed approach outperforms several recently proposed dictionary learning techniques for classification.

Gambling on God： A Qualified Defense of Pascal＇s Wager

The paper critically examines and refutes some of the standard arguments against Pascal＇s Wager, particularly, the ＂Many Gods Objection＂. The paper argues that Pascal＇s philosophical and theological opponents proceed far too quickly in dismissing his argument as implausible. Their determined attempts to tear down Pascal＇s Wager have caused them to miss its power and force. While the Wager may not be sound for today＇s multi culturally sophisticated audience, the Wager is quite cogent relative to Pascal＇s time, when theism and agnosticism were the only genuine possibilities. Thus, the paper concludes that Pascal＇s Wager is less vulnerable than most detractors seem to think.

Statistical Methods for Classification of Medicinal Plants

Statistical classification methods are frequently applied to analyze metabolomics data, especially from medicinal plants. Combined with variable selection techniques, we are able to identify marker candidates, which can be used to discriminate the group to which unknown subjects belong. After preprocessing, such as outlier checking, normalization, missing value imputation and transformation, we then mainly utilized four novel classification methods： RF （random forest）, NSC （nearest shrunken centroid）, PLS-DA （partial least square discriminant analysis） and SAM （significant analysis ofmicroarrays）. Each method has its own device to measure the importance of single metabolite, so that, it is probable to choose highly ranked metabolites, which show the best prediction accuracy. Adapting above strategy, we have successfully analyzed several kinds of metabolomics data including Panax ginseng, Lespedeza species, Anemarrhean asphodeloides and Gastrodia elata.

Multi-label dimensionality reduction based on semi-supervised discriminant analysis

Multi-label data with high dimensionality often occurs,which will produce large time and energy overheads when directly used in classification tasks.To solve this problem,a novel algorithm called multi-label dimensionality reduction via semi-supervised discriminant analysis(MSDA) was proposed.It was expected to derive an objective discriminant function as smooth as possible on the data manifold by multi-label learning and semi-supervised learning.By virtue of the latent imformation,which was provided by the graph weighted matrix of sample attributes and the similarity correlation matrix of partial sample labels,MSDA readily made the separability between different classes achieve maximization and estimated the intrinsic geometric structure in the lower manifold space by employing unlabeled data.Extensive experimental results on several real multi-label datasets show that after dimensionality reduction using MSDA,the average classification accuracy is about 9.71% higher than that of other algorithms,and several evaluation metrices like Hamming-loss are also superior to those of other dimensionality reduction methods.

Face Recognition Using LDA with Wavelet Transform Approach

Linear Discriminant Analysis （LDA） is one of the principal techniques used in face recognition systems. LDA is well-known scheme for feature extraction and dimension reduction. It provides improved performance over the standard Principal Component Analysis （PCA） method of face recognition by introducing the concept of classes and distance between classes. This paper provides an overview of PCA, the various variants of LDA and their basic drawbacks. The paper also has proposed a development over classical LDA, i.e., LDA using wavelets transform approach that enhances performance as regards accuracy and time complexity. Experiments on ORL face database clearly demonstrate this and the graphical comparison of the algorithms clearly showcases the improved recognition rate in case of the proposed algorithm.

Discriminate spatial Ricci scalar dark energy from ΛCDM

We apply two geometrical diagnostics, the statefinder {s, r} and Om（x）, to discriminate the Spatial Ricci scalar dark energy model from the ACDM model. We plot the evolution trajectories of those models in the statefinder plane and Om（x） plane. We show that the Spatial Ricci scalar dark energy model can be distinguished from the ACDM model at 68.3% confidence level for z ≤ 1.