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1.
Chris Hope 《The Journal of the Operational Research Society》2003,54(11):1167-1176
What strategy should a football (soccer, in American parlance) club adopt when deciding whether to sack its manager? This paper introduces a simple model assuming that a club's objective is to maximize the number of league points that it scores per season. The club's strategy consists of three choices: the length of the honeymoon period during which it will not consider sacking a new manager, the level of the performance trapdoor below which the manager get the sack, and the weight that it will give to more recent games compared to earlier ones. Some data from the last six seasons of the English Premiership are used to calibrate the model. At this early stage of the research, the best strategy appears to have only a short honeymoon period of eight games (much less than the actual shortest period of 12 games), to set the trapdoor at 0.74 points per game, and to put 47% of the weight on the last five games. A club adopting this strategy would obtain on average 56.8 points per season, compared to a Premiership average of 51.8 points. 相似文献
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Dave J Adams Eric G Hope Peter J Pogorzelec 《Journal of organometallic chemistry》2004,689(8):1413-1417
The hydroformylation of long chain alkenes under fluorous biphase conditions and in neat perfluorocarbon solvents is reviewed. Special emphasis is placed upon the authors' evaluation of the steric and electronic influence of perfluoroalkylation on catalyst activity, regioselectivity and retention in the fluorocarbon phase. 相似文献
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Soderstrom E McKenna JA Abrams GS Adolphsen CE Averill D Ballam J Barish BC Barklow T Barnett BA Bartelt J Bethke S Blockus D Bonvicini G Boyarski A Brabson B Breakstone A Bulos F Burchat PR Burke DL Cence RJ Chapman J Chmeissani M Cords D Coupal DP Dauncey P DeStaebler HC Dorfan DE Dorfan JM Drewer DC Elia R Feldman GJ Fernandes D Field RC Ford WT Fordham C Frey R Fujino D Gan KK Gero E Gidal G Glanzman T Goldhaber G Gomez Cadenas JJ Gratta G Grindhammer G Grosse-Wiesmann P Hanson G Harr R 《Physical review letters》1990,64(25):2980-2983
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Komamiya S Abrams GS Adolphsen CE Averill D Ballam J Barish BC Barklow T Barnett BA Bartelt J Bethke S Blockus D Bonvicini G Boyarski A Brabson B Breakstone A Bulos F Burchat PR Burke DL Cence RJ Chapman J Chmeissani M Cords D Coupal DP Dauncey P DeStaebler HC Dorfan DE Dorfan JM Drewer DC Elia R Feldman GJ Fernandes D Field RC Ford WT Fordham C Frey R Fujino D Gan KK Gatto C Gero E Gidal G Glanzman T Goldhaber G Gomez Cadenas JJ Gratta G Grindhammer G Grosse-Wiesmann P Hanson G Harr R 《Physical review letters》1990,64(24):2881-2884
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Pierce KM Hope JL Johnson KJ Wright BW Synovec RE 《Journal of chromatography. A》2005,1096(1-2):101-110
A fast and objective chemometric classification method is developed and applied to the analysis of gas chromatography (GC) data from five commercial gasoline samples. The gasoline samples serve as model mixtures, whereas the focus is on the development and demonstration of the classification method. The method is based on objective retention time alignment (referred to as piecewise alignment) coupled with analysis of variance (ANOVA) feature selection prior to classification by principal component analysis (PCA) using optimal parameters. The degree-of-class-separation is used as a metric to objectively optimize the alignment and feature selection parameters using a suitable training set thereby reducing user subjectivity, as well as to indicate the success of the PCA clustering and classification. The degree-of-class-separation is calculated using Euclidean distances between the PCA scores of a subset of the replicate runs from two of the five fuel types, i.e., the training set. The unaligned training set that was directly submitted to PCA had a low degree-of-class-separation (0.4), and the PCA scores plot for the raw training set combined with the raw test set failed to correctly cluster the five sample types. After submitting the training set to piecewise alignment, the degree-of-class-separation increased (1.2), but when the same alignment parameters were applied to the training set combined with the test set, the scores plot clustering still did not yield five distinct groups. Applying feature selection to the unaligned training set increased the degree-of-class-separation (4.8), but chemical variations were still obscured by retention time variation and when the same feature selection conditions were used for the training set combined with the test set, only one of the five fuels was clustered correctly. However, piecewise alignment coupled with feature selection yielded a reasonably optimal degree-of-class-separation for the training set (9.2), and when the same alignment and ANOVA parameters were applied to the training set combined with the test set, the PCA scores plot correctly classified the gasoline fingerprints into five distinct clusters. 相似文献
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