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51.
Geoffrey M. Rowe Jay N. Meegoda Andris Jumikis Mark J. Sharrock Nishantha Bandara Chamil H. Hettiarachchi 《Canadian Metallurgical Quarterly》2004,130(6):924-934
Abstract: This paper describes the research funded by the New Jersey Department of Transportation to develop an automated technology to monitor segregation during construction of hot-mix asphalt concrete pavements. A Laser-based system was used to measure surface texture and to detect segregation. Two segregated test sections and a control test section were tested to evaluate the applicability of Laser texture method to detect and quantify segregation. Laser texture data were gathered from all three sections. Ratios of texture in segregated areas to that in nonsegregated areas were set as the basis for detection of different levels of segregation. By combining the level of segregation and extent of segregation, an AREA index was developed to determine the acceptability of a pavement section. Based on AREA index, pay adjustment factors were proposed to reduce the payment to account for loss of pavement life due to segregation. Further remedial actions were proposed to correct segregated pavement sections with acceptable AREA index. Based on the above concepts, Windows-based computer program NJTxtr was developed to detect and quantify segregation. This computer program uses the Laser-equipment-collected pavement texture data and determines whether the pavement section is acceptable or unacceptable based on the level of segregation within a pavement section, and provides bonus or penalties to the contractor. The paper describes a novel technology using laser and associated software for construction quality control of asphalt concrete pavements. The proposed methodology was applied to detect segregation in an interstate highway section in New Jersey, and this section was repaved based on visual observation and recommendation from this study. 相似文献
52.
David J. Munk Timoleon Kipouros Gareth A. Vio Geoffrey T. Parks Grant P. Steven 《Structural and Multidisciplinary Optimization》2018,57(2):665-688
To date the design of structures using topology optimization methods has mainly focused on single-objective problems. Since real-world design problems typically involve several different objectives, most of which counteract each other, it is desirable to present the designer with a set of Pareto optimal solutions that capture the trade-off between these objectives, known as a smart Pareto set. Thus far only the weighted sums and global criterion methods have been incorporated into topology optimization problems. Such methods are unable to produce evenly distributed smart Pareto sets. However, recently the smart normal constraint method has been shown to be capable of directly generating smart Pareto sets. Therefore, in the present work, an updated smart Normal Constraint Method is combined with a Bi-directional Evolutionary Structural Optimization (SNC-BESO) algorithm to produce smart Pareto sets for multiobjective topology optimization problems. Two examples are presented, showing that the Pareto solutions found by the SNC-BESO method make up a smart Pareto set. The first example, taken from the literature, shows the benefits of the SNC-BESO method. The second example is an industrial design problem for a micro fluidic mixer. Thus, the problem is multi-physics as well as multiobjective, highlighting the applicability of such methods to real-world problems. The results indicate that the method is capable of producing smart Pareto sets to industrial problems in an effective and efficient manner. 相似文献
53.
54.
Circulating hormones and estrous stage predict cellular and stromal remodeling in murine uterus 总被引:2,自引:0,他引:2
The understanding of how estrogen and progesterone (P(4)) drive uterine remodeling in rodents has largely been based on studies involving administration of exogenous hormones, using steroid receptor-deficient mice, or relying on vaginal smears. In all these cases, the actual serum levels of 17beta-estradiol (E(2)) and P(4) are not directly measured, and the relationship between physiological levels of female sex hormones and uterine remodeling in cycling mice has not been fully explored. Here, we measured the circulating levels of E(2) and P(4) in cycling mice and performed correlation analysis between hormone levels and epithelial and stromal uterine parameters, irrespective of the estrous stage. In parallel, these parameters were analyzed in relation to the more conventional method of vaginal smear classification of estrous stage. We found that circulating P(4) inversely correlated with uterine width, luminal epithelial proliferation, stromal apoptosis, and degradation of luminal epithelial basement membrane collagen type-IV. Circulating E(2) positively correlated with uterine width, stromal cell proliferation, and collagen type-I content, while it negatively correlated with glandular epithelial proliferation, loss of collagen type-IV surrounding glandular epithelium, and apoptosis in luminal, glandular, and stromal compartments. Our findings indicate that measuring P(4) or E(2) levels can predict many concurrent cellular and stromal events in the mouse uterus, suggesting that in naturally cycling mice cellular responses to hormone changes are not delayed, but occur very rapidly. 相似文献
55.
Mary F. Barbe Mamta Amin Michele Y. Harris Siva Tejaa Panibatla Soroush Assari Steven N. Popoff Geoffrey M. Bove 《International journal of molecular sciences》2022,23(12)
The effectiveness of manual therapy in reducing the catabolic effects of performing repetitive intensive force tasks on bones has not been reported. We examined if manual therapy could reduce radial bone microstructural declines in adult female Sprague–Dawley rats performing a 12-week high-repetition and high-force task, with or without simultaneous manual therapy to forelimbs. Additional rats were provided 6 weeks of rest after task cessation, with or without manual therapy. The control rats were untreated or received manual therapy for 12 weeks. The untreated TASK rats showed increased catabolic indices in the radius (decreased trabecular bone volume and numbers, increased osteoclasts in these trabeculae, and mid-diaphyseal cortical bone thinning) and increased serum CTX-1, TNF-α, and muscle macrophages. In contrast, the TASK rats receiving manual therapy showed increased radial bone anabolism (increased trabecular bone volume and osteoblast numbers, decreased osteoclast numbers, and increased mid-diaphyseal total area and periosteal perimeter) and increased serum TNF-α and muscle macrophages. Rest, with or without manual therapy, improved the trabecular thickness and mid-diaphyseal cortical bone attributes but not the mineral density. Thus, preventive manual therapy reduced the net radial bone catabolism by increasing osteogenesis, while rest, with or without manual therapy, was less effective. 相似文献
56.
Julie K. Furmick Dr. Ichiro Kaneko Angela N. Walsh Joanna Yang Jaskaran S. Bhogal Geoffrey M. Gray Juan C. Baso Drew O. Browder Jessica L. S. Prentice Luis A. Montano Chanh C. Huynh Lisa M. Marcus Dorian G. Tsosie Jungeun S. Kwon Alexis Quezada Nicole M. Reyes Brittney Lemming Puneet Saini Dr. Arjan van der Vaart Dr. Thomas L. Groy Dr. Pamela A. Marshall Dr. Peter W. Jurutka Dr. Carl E. Wagner 《ChemMedChem》2012,7(9):1551-1566
57.
58.
Athanasios Kotsiopoulos Geoffrey S. Hansford Randhir Rawatlal 《American Institute of Chemical Engineers》2012,58(8):2428-2440
A dynamic analysis of chalcopyrite bioleaching was performed in continuous flow systems. In contrast to a previous batch analysis1 in which the influence of particle surface area on reaction rate was not accounted for, the unsteady‐state change in particle surface area was integrated into the dynamic analysis by application of the modified PBM.2 The current study extends the analysis to include the influence of convective flow on the system. It is demonstrated that the analysis can be used to determine feasible control strategies for operating near the steady‐state maximum rate that is stable. Two strategies were evaluated for the purpose of increasing the leaching rates, showing that an increased rate of 56% is feasible. Analysis on experimental data showed that increased rates can be achieved by controlling the biomass concentration and ferric:ferrous ion ratio at an optimum by increasing the solids loading [m/v] in the reactor. © 2011 American Institute of Chemical Engineers AIChE J, 58: 2428–2440, 2012 相似文献
59.
60.
Geoffrey I. Webb Janice R. Boughton Fei Zheng Kai Ming Ting Houssam Salem 《Machine Learning》2012,86(2):233-272
Averaged n-Dependence Estimators (AnDE) is an approach to probabilistic classification learning that learns by extrapolation from marginal to full-multivariate
probability distributions. It utilizes a single parameter that transforms the approach between a low-variance high-bias learner
(Naive Bayes) and a high-variance low-bias learner with Bayes optimal asymptotic error. It extends the underlying strategy
of Averaged One-Dependence Estimators (AODE), which relaxes the Naive Bayes independence assumption while retaining many of
Naive Bayes’ desirable computational and theoretical properties. AnDE further relaxes the independence assumption by generalizing AODE to higher-levels of dependence. Extensive experimental
evaluation shows that the bias-variance trade-off for Averaged 2-Dependence Estimators results in strong predictive accuracy
over a wide range of data sets. It has training time linear with respect to the number of examples, learns in a single pass
through the training data, supports incremental learning, handles directly missing values, and is robust in the face of noise.
Beyond the practical utility of its lower-dimensional variants, AnDE is of interest in that it demonstrates that it is possible to create low-bias high-variance generative learners and suggests
strategies for developing even more powerful classifiers. 相似文献