细金工艺及其物化研究——向本

细金工艺是一门传统的金属手工技法,是值得当代艺术家和设计师不断修炼并传承,而现代细金工艺传承过程中,造型、图样等趋于单一、守旧,值得工艺师思考、创新。通过史料收集,对细金工艺及其历史演化进行了概述,从造型的角度出发,利用现代制造工艺和理念创作了多件当代作品,表现了大自然的本心本源之美,并从中感悟到细金工艺要求制作者静心于一物、一事,抛弃杂念,具有匠人情怀和精神。达·芬奇是伟大的画家、发明家、艺术家,从小对大自然充满了好奇,在不同的领域执着追求,取得举世瞩目的成就,但其一直不忘初心。作者以"向本"为创作主题,以"祥鸟"为形制,研究并完成了细金工艺表达下的飞翔的鸟的创作《向本——致敬达·芬奇》。

《世本》成书年代问题考论

《世本》一书的成书年代问题,在战国史学史与历史文献学研究上十分重要。据司马迁未见及此书和对刘向整编图书工作的考析,盖为西汉季年刘向汇编战国时诸多零散文献而成书,先秦时期并无此书存在。但学界多将其定位先秦史籍,谬说流播已久,乃至误以为《史记》仿其体例,误指《世本》为第一部分类编纂的通史著述云云,造成极大学术混乱,应当予以纠正。误判《世本》为先秦史籍的学术教训,表明在中国史学史的研究中,必须尽力重新审视具体的史籍和史学现象,不能现成地借用旧有成说。

Prediction of Hot Deformation Behavior of 7Mo Super Austenitic Stainless Steel Based on Back Propagation Neural Network

The hot compression tests of 7Mo super austenitic stainless(SASS)were conducted to obtain flow curves at the temperature of 1000-1200℃and strain rate of 0.001 s^(-1)to 1 s^(-1).To predict the non-linear hot deformation behaviors of the steel,back propagation-artificial neural network(BP-ANN)with 16×8×8 hidden layer neurons was proposed.The predictability of the ANN model is evaluated according to the distribution of mean absolute error(MAE)and relative error.The relative error of 85%data for the BP-ANN model is among±5%while only 42.5%data predicted by the Arrhenius constitutive equation is in this range.Especially,at high strain rate and low temperature,the MAE of the ANN model is 2.49%,which has decreases for 18.78%,compared with conventional Arrhenius constitutive equation.

The Minimum Norm of Solutions of the Boolean Matrix-Equation A^k=J

Let A be an n×n primitive Boolean matrix. γ(A) is the least number k such that A k=J. σ(A) is the number of 1 entry in A . In this paper, we consider the parameter M ′(k,n)= min {σ(A)|A k=J, trace (A)=0} and obtain the values of M ′(2,n) and M ′(k,n) for k≥2n-6 . Furthermore, the characterization of solution of A 2=J with trace (A) =0 and σ(A)=3n-3 is completely determined.

Rapid vision-based system for secondary copper content estimation

A vision-based color analysis system was developed for rapid estimation of copper content in the secondary copper smelting process. Firstly, cross section images of secondary copper samples were captured by the designed vision system. After the preprocessing and segmenting procedures, the images were selected according to their grayscale standard deviations of pixels and percentages of edge pixels in the luminance component. The selected images were then used to extract the information of the improved color vector angles, from which the copper content estimation model was developed based on the least squares support vector regression (LSSVR) method. For comparison, three additional LSSVR models, namely, only with sample selection, only with improved color vector angle, without sample selection or improved color vector angle, were developed. In addition, two exponential models, namely, with sample selection, without sample selection, were developed. Experimental results indicate that the proposed method is more effective for improving the copper content estimation accuracy, particularly when the sample size is small.

D pouillement en faveur de l'Essence——Lecture tao ste d'Henri Michaux

本文以老子哲学为参照 ,释读了米修的诗作 ,努力揭示米修与道家的深层关系 ,突出文本分析。

NEW HYBRID AI-SVM ALGORITHM: COMBINATION OF SUPPORT VECTOR MACHINES AND ARTIFICIAL IMMUNE NETWORKS

Support vector machines （SVMs） are combined with the artificial immune network （aiNet）, thus forming a new hybrid ai-SVM algorithm. The algorithm is used to reduce the number of samples and the training time of SVM on large datasets, aiNet is an artificial immune system （AIS） inspired method to perform the automatic data compression, extract the relevant information and retain the topology of the original sample distribution. The output of aiNet is a set of antibodies for representing the input dataset in a simplified way. Then the SVM model is built in the compressed antibody network instead of the original input data. Experimental results show that the ai-SVM algorithm is effective to reduce the computing time and simplify the SVM model, and the accuracy is not decreased.

THE COUPLED MODE BETWEEN THE KUROSHIO REGION MARINE HEATING ANOMALY AND THE NORTH PACIFIC ATMOSPHERIC CIRCULATION IN WINTERTIME

Using monthly reanalysis data of the National Center for Environmental Research/National Center for Atmospheric Research(NCEP/NCAR) and Objectively Analyzed Air-Sea Heat Flux(OAFlux) gathered during the winter,singular vector decomposition(SVD) analysis was conducted to reveal the coupled mode between the Kuroshio marine heating anomaly and the geopotential height at 500 hPa(Z500) over the North Pacific.The first SVD mode showed that when the northern Kuroshio marine heating anomaly was positive,the Z500 in the central and western sections of the North Pacific was anomalously low.By composing the meteorological field anomalies in the positive(or negative) years,it has been revealed that while the Aleutian Low deepens(or shallows),the northwesterly wind overlying the Kuroshio strengthens(or weakens) and induces the near-surface air to be cool(or warm).Furthermore,this increases(or decreases) the upward heat flux anomaly and cools(or warms) the sea surface temperature(SST) accordingly.In the vicinity of Kuroshio and its downstream region,the vertical structure of the air temperature along the latitude is baroclinic;however,the geopotential height is equivalently barotropic,which presents a cool trough(or warm ridge) spatial structure.The divergent wind and vertical velocities are introduced to show the anomalous zonal circulation cell.These are characterized by the rising(or descending) air in the central North Pacific,which flows westward and eastward toward the upper troposphere,descends(or rises) in the Kuroshio and in the western section of North America,and then strengthens(or weakens) the mid-latitude zonal cell(MZC).

A-BQ,a classification system for anisotropic rock mass based on China National Standard

The rock mass in nature is in most cases anisotropic,while the existing classifications are mostly developed with the assumption of isotropic conditions that not always meet the engineering requirements.In this study,an anisotropic system based on China National Standard of BQ,named as A-BQ,is developed to address the classification of anisotropic rock mass incorporating the anisotropy degree as well as the quality of rock mass.Two series of basic rating factors are incorporated including inherent anisotropy and structure anisotropy.The anisotropy degree of rock mass is characterized by the ratio of maximum to minimum quality score and adjusted by the confining stress.The quality score of rock mass is determined by the key factors of anisotropic structure occurrence and the correction factors of stress state and groundwater condition.The quality of rock mass is characterized by a quality score and classified in five grades.The assessment of stability status and probable failure modes are also suggested for tunnel and slope engineering for different quality grades.Finally,two cases of tunnel and slope are presented to illustrate the application of the developed classification system into the rock masses under varied stress state.

Chinese Fuzzy Ontology Mapping Based on Support Vector Machine

Taking into account that fuzzy ontology mapping has wide application and cannot be dealt with in many fields at present,a Chinese fuzzy ontology model and a method for Chinese fuzzy ontology mapping are proposed.The mapping discovery between two ontologies is achieved by computing the similarity between the concepts of two ontologies.Every concept consists of four features of concept name,property,instance and structure.First,the algorithms of calculating four individual similarities corresponding to the four features are given.Secondly,the similarity vectors consisting of four weighted individual similarities are built,and the weights are the linear function of harmony and reliability.The similarity vector is used to represent the similarity relation between two concepts which belong to different fuzzy ontolgoies.Lastly,Support Vector Machine(SVM) is used to get the mapping concept pairs by the similarity vectors.Experiment results are satisfactory.

Shrek:a dynamic object-oriented programming language

From a perspective of theoretical study, there are some faults in the models of the existing object-oriented programming languages. For example, C# does not support metaclasses, the primitive types of Java and C# are not objects, etc. So, this paper designs a programming language, Shrek, which integrates many language features and constructions in a compact and consistent model. The Shrek language is a class-based purely object-oriented language. It has a dynamical strong type system, and adopts a single-inheritance mechanism with Mixin as its complement. It has a consistent class instantiation and inheritance structure, and the ability of intercessive structural computational reflection, which enables it to support safe metaclass programming. It also supports multi-thread programming and automatic garbage collection, and enforces its expressive power by adopting a native method mechanism. The prototype system of the Shrek language is implemented and anticipated design goals are achieved.

A SVM Based Text Steganalysis Algorithm for Spacing Coding

Group distance coding is suitable for secret communication covered by printed documents. However there is no effective method against it. The study found that the hiding method will make group distances of text lines coverage on specified values, and make variances of group distances among N-Window text lines become small. Inspired by the discovery, the research brings out a Support Vector Machine （SVM） based steganalysis algorithm. To avoid the disturbance of large difference among words length from same line, the research only reserves samples whose occurrence-frequencies are ± 10dB of the maximum frequency. The results show that the correct rate of the SVM classifier is higher than 90%.

Unfaithfulness or Expressiveness？ On KU Hung-ming＇s Translation of Chinese Classics From the Perspective of Translation Norms

As a beak with the traditional ＂prescriptive＂ approach and an important complement to translation theories, translation norms thus open up a descriptive and target-oriented perspective for the translation practice and study. For the successful access of the translation text into the target culture, the translator has to make choices between two languages, texts and cultures, etc.. Thus the translation norms are revealed. This paper shows the operation of translation norms as seen from the English version of Chinese classics by KU Hung-ming and analyzes why KU Hung-ming＇s translation of Confucian classics such as Lun Yu and Zhong Yong enjoyed greater popularity among Western readers than the translation of Western missionaries. The paper also holds that the unfaithful translations regarded by a source text-oriented approach were actually where KU was most successful in implementing his translation strategies to achieve expressiveness.

NUMERICAL EXPERIMENT ON IMPACT OF ANOMALOUS SST WARMING IN KUROSHIO EXTENSION IN PREVIOUS WINTER ON EAST ASIAN SUMMER MONSOON

The impact of anomalous sea surface temperature (SST) warming in the Kuroshio Extension in the previous winter on the East Asian summer monsoon (EASM) was investigated by performing simulation tests using NCAR CAM3.The results show that anomalous SST warming in the Kuroshio Extension in winter causes the enhancement and northward movement of the EASM.The monsoon indexes for East Asian summer monsoon and land-sea thermal difference,which characterize the intensity of the EASM,show an obvious increase during the onset period of the EASM.Moreover,the land-sea thermal difference is more sensitive to warmer SST.Low-level southwesterly monsoon is clearly strengthened meanwhile westerly flows north (south) of the subtropical westerly jet axis are strengthened (weakened) in northern China,South China Sea,and the Western Pacific Ocean to the east of the Philippines.While there is an obvious decrease in precipitation over the Japanese archipelago and adjacent oceans and over the area from the south of the Yangtze River in eastern China to the Qinling Mountains in southern China,precipitation increases notably in northern China,the South China Sea,the East China Sea,the Yellow Sea,and the Western Pacific to the east of the Philippines.North China is the key area where the response of the EASM to the SST anomalous warming in the Kuroshio Extension is prominent.The surface air temperature shows a warming trend.The warming in the entire troposphere between 30oN and 50oN increases the land-sea thermal contrast,which plays an important role in the enhancement of the EASM.Atmospheric circulation and precipitation anomalies in China and its adjacent regions have a close relationship with the enhancement of the Western Pacific subtropical high and its northward extension.

Comparison of flow behaviors of near beta Ti-55511 alloy during hot compression based on SCA and BPANN models

The flow behavior of Ti-55511 alloy was studied by hot compression tests at temperatures of 973−1123 K and strain rates of 0.01−10 s^(−1).Strain-compensated Arrhenius(SCA)and back-propagation artificial neural network(BPANN)methods were selected to model the constitutive relationship,and the models were further evaluated by statistical analysis and cross-validation.The stress−strain data extended by two models were implanted into finite element to simulate hot compression test.The results indicate that the flow stress is sensitive to deformation temperature and strain rate,and increases with increasing strain rate and decreasing temperature.Both the SCA model fitted by quintic polynomial and the BPANN model with 12 neurons can describe the flow behaviors,but the fitting accuracy of BPANN is higher than that of SCA.Sixteen cross-validation tests also confirm that the BPANN model has high prediction accuracy.Both models are effective and feasible in simulation,but BPANN model is superior in accuracy.

Optimal Structural Design of the Midship of a VLCC Based on the Strategy Integrating SVM and GA

In this paper a hybrid process of modeling and optimization, which integrates a support vector machine （SVM） and genetic algorithm （GA）, was introduced to reduce the high time cost in structural optimization of ships. SVM, which is rooted in statistical learning theory and an approximate implementation of the method of structural risk minimization, can provide a good generalization performance in metamodeling the input-output relationship of real problems and consequently cuts down on high time cost in the analysis of real problems, such as FEM analysis. The GA, as a powerful optimization technique, possesses remarkable advantages for the problems that can hardly be optimized with common gradient-based optimization methods, which makes it suitable for optimizing models built by SVM. Based on the SVM-GA strategy, optimization of structural scantlings in the midship of a very large crude carrier （VLCC） ship was carried out according to the direct strength assessment method in common structural rules （CSR）, which eventually demonstrates the high efficiency of SVM-GA in optimizing the ship structural scantlings under heavy computational complexity. The time cost of this optimization with SVM-GA has been sharply reduced, many more loops have been processed within a small amount of time and the design has been improved remarkably.

Artificial intelligence model of complicated flow behaviors for Ti-13Nb-13Zr alloy and relevant applications

The comprehensive nonlinear flow behaviors of a ductile alloy play a significant role in the numerical analysis of its forming process. The accurate characterization of as-forged Ti-13 Nb-13 Zr alloy was conducted by an improved intelligent algorithm, GA-SVR, the combination of genetic algorithm(GA) and support vector regression(SVR). The GA-SVR model learns from a training dataset and then is verified by a test dataset. As for the generalization ability of the solved GA-SVR model, no matter in β phase temperature range or(α+β) phase temperature range, the correlation coefficient R-values are always larger than 0.9999, and the AARE-values are always lower than 0.18%. The solved GA-SVR model accurately tracks the highly-nonlinear flow behaviors of Ti-13 Nb-13 Zr alloy. The stress-strain data expanded by this model are input into finite element solver, and the computation accuracy is improved.

RS-SVM forecasting model and power supply-demand forecast

A support vector machine (SVM) forecasting model based on rough set (RS) data preprocess was proposed by combining the rough set attribute reduction and the support vector machine regression algorithm, because there are strong complementarities between two models. Firstly, the rough set was used to reduce the condition attributes, then to eliminate the attributes that were redundant for the forecast, Secondly, it adopted the minimum condition attributes obtained by reduction and the corresponding original data to re-form a new training sample, which only kept the important attributes affecting the forecast accuracy. Finally, it studied and trained the SVM with the training samples after reduction, inputted the test samples re-formed by the minimum condition attributes and the corresponding original data, and then got the mapping relationship model between condition attributes and forecast variables after testing it. This model was used to forecast the power supply and demand. The results show that the average absolute error rate of power consumption of the whole society and yearly maximum load are 14.21% and 13.23%, respectively, which indicates that the RS-SVM forecast model has a higher degree of accuracy.

Large Number,Dark Matter,Dark Energy,and Superstructures in the Universe

Since there may exist dark matter particles ν and δ with mass - 10^-1 e V in the universe, the superstructures with a scale of 10^19 solar masses （large number A - 10^19） appeared during the era near and before the hydrogen recombination. Since there are superstructures in the universe, there may be no necessity for the existence of dark energy. For checking the superstructure in the universe by CMB anisotropy, we need to measure CMB angular power spectrum especially around ten degrees across the sky- in more details, While neutrino u is related to electroweak unification, the fourth stable elementary particle 6 may be related to strong-gravity unification, which suggests p ＋ p^- → n ＋ δ^- and that some new baryons appeared in the TeV region.

Generalized plasticity model considering grain crushing and anisotropy for rockfill materials

Rockfill materials have been widely used in the construction of rockfill dam,railway and highway subgrade due to its high filling density,good compaction performance,strong water permeability,small settlement deformation and high bearing capacity.A reasonable constitutive model for rockfill materials is very important for engineering computation and analysis,and has a great development space.Based on the crushing stress and spatial mobilized plane(SMP),a state parameter that can comprehensively reflect the anisotropy and grain crushing is proposed.This state parameter is used to improve the MPZ model(a modifed ZienkiewiczⅢmodel),so that a generalized plastic model is constructed to describe the stress and deformation characteristics of rockfill materials in engineering.The validity of the developed model is verified by a series of conventional triaxial tests with different inclination angles of the compaction plane.The variation trend of the constructed anisotropy indexωcan reflect the non monotonic variation of the deformation and strength of rockfill with the direction angle of large principal stress,so the model can reflect the obvious difference caused by the initial anisotropy of rockfill on the mechanical properties.