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41.
Cordero-Dávila A Luna-Aguilar E Vázquez-Montiel S Zárate-Vázquez S Percino-Zacarias ME 《Applied optics》1998,37(4):672-675
We use a square grid in the Ronchi test. This grid allows processing of both the X and the Y directions when calculating optical path difference. We use trapezoidal integration to analyze the new patterns, since it does not have the smoothing drawback at the edges of the wave front. 相似文献
42.
The current scanning near-field optical microscopy has been developed with optical-fiber probes obtained by use of either laser-heated pulling or chemical etching. For high-resolution near-field imaging, the detected signal is rapidly attenuated as the aperture size of the probe decreases. It is thus important to fabricate probes optimized for both spot size and optical transmission. We present a two-step fabrication that allowed us to achieve an improved performance of the optical-fiber probes. Initially, a CO(2) laser-heated pulling was used to produce a parabolic transitional taper ending with a top thin filament. Then, a rapid chemical etching with 50% buffered hydrofluoric acid was used to remove the thin filament and to result in a final conical tip on the top of the parabolic transitional taper. Systematically, we obtained optical-fiber nanoprobes with the apex size as small as 10 nm and the final cone angle varying from 15 degrees to 80 degrees . It was found that the optical transmission efficiency increases rapidly as the taper angle increases from 15 degrees to 50 degrees , but a further increase in the taper angle gives rise to important broadening of the spot size. Finally, the fabricated nanoprobes were used in photon-scanning tunneling microscopy, which allowed observation of etched double lines and grating structures with periods as small as 200 nm. 相似文献
43.
Periodically poled flux-grown KTiOPO(4) was used for efficient extracavity 1064-nm Nd:YAG laser frequency doubling. A conversion efficiency exceeding 65% was obtained in Q-switched operation, and 1.34 W of average frequency-doubled power was generated with 2.2 W of mode-locked laser output. The conversion efficiency is approximately two times higher for periodically poled KTP than for conventional type II phase-matched KTP. The measurements indicate that periodically poled KTP is less susceptible to optical damage than type II KTP. 相似文献
44.
The characterization of a simple, dual-fiber quartz capillary/fiber optical sensor (C/FOS) for remote excitation and collection of Raman signals is presented. The Raman signals acquired with the C/FOS exhibit a 70-fold sensitivity enhancement and a 50-fold improvement in detectability relative to those obtained with the corresponding conventional dual-fiber sensor without the capillary. A background spectral feature at 790 cm(-)(1) is related to the optical fiber background and is not due to the capillary tube. With no focusing lenses or filters needed at the sample site, the remote Raman C/FOS is easy to assemble and use, and it is relatively inexpensive compared to other designs. 相似文献
45.
The possibilities of stabilization of the interference pattern by filtration of a random-phase noise caused by vibrations, turbulence, and other local changes in the wave front in interferometric measurements are investigated. Dynamic holographic recording in photorefractive Bi(12)TiO(20) crystals is used. The parameters of the holographic recording are presented for determination of the dynamic range for filtering. Noise filtering takes place in real time and contributes to the enhancement of the contrast and the signal-to-noise ratio of the interference pattern. This results in a considerable increase in the sensitivity and the accuracy of the interferometric measurements. 相似文献
46.
Wang B Summa B Pascucci V Vejdemo-Johansson M 《IEEE transactions on visualization and computer graphics》2011,17(12):1902-1911
Large observations and simulations in scientific research give rise to high-dimensional data sets that present many challenges and opportunities in data analysis and visualization. Researchers in application domains such as engineering, computational biology, climate study, imaging and motion capture are faced with the problem of how to discover compact representations of high-dimensional data while preserving their intrinsic structure. In many applications, the original data is projected onto low-dimensional space via dimensionality reduction techniques prior to modeling. One problem with this approach is that the projection step in the process can fail to preserve structure in the data that is only apparent in high dimensions. Conversely, such techniques may create structural illusions in the projection, implying structure not present in the original high-dimensional data. Our solution is to utilize topological techniques to recover important structures in high-dimensional data that contains non-trivial topology. Specifically, we are interested in high-dimensional branching structures. We construct local circle-valued coordinate functions to represent such features. Subsequently, we perform dimensionality reduction on the data while ensuring such structures are visually preserved. Additionally, we study the effects of global circular structures on visualizations. Our results reveal never-before-seen structures on real-world data sets from a variety of applications. 相似文献
47.
Bennett JC Krishnamoorthy V Liu S Grout RW Hawkes ER Chen JH Shepherd J Pascucci V Bremer PT 《IEEE transactions on visualization and computer graphics》2011,17(12):1822-1831
We present a new framework for feature-based statistical analysis of large-scale scientific data and demonstrate its effectiveness by analyzing features from Direct Numerical Simulations (DNS) of turbulent combustion. Turbulent flows are ubiquitous and account for transport and mixing processes in combustion, astrophysics, fusion, and climate modeling among other disciplines. They are also characterized by coherent structure or organized motion, i.e. nonlocal entities whose geometrical features can directly impact molecular mixing and reactive processes. While traditional multi-point statistics provide correlative information, they lack nonlocal structural information, and hence, fail to provide mechanistic causality information between organized fluid motion and mixing and reactive processes. Hence, it is of great interest to capture and track flow features and their statistics together with their correlation with relevant scalar quantities, e.g. temperature or species concentrations. In our approach we encode the set of all possible flow features by pre-computing merge trees augmented with attributes, such as statistical moments of various scalar fields, e.g. temperature, as well as length-scales computed via spectral analysis. The computation is performed in an efficient streaming manner in a pre-processing step and results in a collection of meta-data that is orders of magnitude smaller than the original simulation data. This meta-data is sufficient to support a fully flexible and interactive analysis of the features, allowing for arbitrary thresholds, providing per-feature statistics, and creating various global diagnostics such as Cumulative Density Functions (CDFs), histograms, or time-series. We combine the analysis with a rendering of the features in a linked-view browser that enables scientists to interactively explore, visualize, and analyze the equivalent of one terabyte of simulation data. We highlight the utility of this new framework for combustion science; however, it is applicable to many other science domains. 相似文献
48.
Thomas DM Natarajan V 《IEEE transactions on visualization and computer graphics》2011,17(12):2035-2044
Study of symmetric or repeating patterns in scalar fields is important in scientific data analysis because it gives deep insights into the properties of the underlying phenomenon. Though geometric symmetry has been well studied within areas like shape processing, identifying symmetry in scalar fields has remained largely unexplored due to the high computational cost of the associated algorithms. We propose a computationally efficient algorithm for detecting symmetric patterns in a scalar field distribution by analysing the topology of level sets of the scalar field. Our algorithm computes the contour tree of a given scalar field and identifies subtrees that are similar. We define a robust similarity measure for comparing subtrees of the contour tree and use it to group similar subtrees together. Regions of the domain corresponding to subtrees that belong to a common group are extracted and reported to be symmetric. Identifying symmetry in scalar fields finds applications in visualization, data exploration, and feature detection. We describe two applications in detail: symmetry-aware transfer function design and symmetry-aware isosurface extraction. 相似文献
49.
The massive computational resources available in the framework of a grid paradigm approach represent an emerging tool in the bioinformatics field. In this paper, we used the above approach in the rapid determination of the interactions between the ring-hydroxylating dioxygenase, comprised six enzymatic subunits, and polycyclic aromatic hydrocarbons (PAHs) in their optimal positions. The results were obtained by simulating enzyme dynamics at 300 K through molecular dynamics calculations. For the first time, the equilibrated structure of the dioxygenase revealed a network of channels throughout the enzyme that were sufficiently large to allow a flow of small ions or molecules from the inner core of the complex to its exterior surface. The ring-hydroxylating dioxygenase was able to interact with some of the studied PAHs. Additionally, not only the number of aromatic rings but also the PAH shape were critical in predicting the ability of the dioxygenase to interact with these types of molecules. Docking calculations shed light on a new possible binding site that is far from the enzymatic one, which is potentially interesting in considering the stability of the enzyme itself. 相似文献
50.
The problem of multimodal clustering arises whenever the data are gathered with several physically different sensors. Observations from different modalities are not necessarily aligned in the sense there there is no obvious way to associate or compare them in some common space. A solution may consist in considering multiple clustering tasks independently for each modality. The main difficulty with such an approach is to guarantee that the unimodal clusterings are mutually consistent. In this letter, we show that multimodal clustering can be addressed within a novel framework: conjugate mixture models. These models exploit the explicit transformations that are often available between an unobserved parameter space (objects) and each of the observation spaces (sensors). We formulate the problem as a likelihood maximization task and derive the associated conjugate expectation-maximization algorithm. The convergence properties of the proposed algorithm are thoroughly investigated. Several local and global optimization techniques are proposed in order to increase its convergence speed. Two initialization strategies are proposed and compared. A consistent model selection criterion is proposed. The algorithm and its variants are tested and evaluated within the task of 3D localization of several speakers using both auditory and visual data. 相似文献