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1.
企鹅珍珠贝人工苗生长的初步观察 总被引:3,自引:0,他引:3
为了解企鹅珍珠贝生长规律,观察了壳高2.5~5.0mm的出池幼苗,按月测量其生长参数和成活率,以及环境因子。结果表明,企鹅珍珠贝生长最快的月份为7~11月和次年4~6月,壳长,壳高和壳宽月均增加量分别为3.8~13.0mm、4.7~11.2mm、2.3~3.8mm,月成活率97.8%~98.6%。企鹅珍珠贝生长最慢月份是11月至次年3月。 相似文献
2.
Linux 防火墙的研究与设计 总被引:4,自引:0,他引:4
阐述了Linux2.4内核的防火墙Linux的原理,并分析了netfilter的设计与实现,叙述了Linux的动态地址转换,介绍了在Linux下基于netfilter架构如何开发自己的防火墙并给出具体实例。 相似文献
3.
M. Irfan Yesilnacar Erkan Sahinkaya Muhsin Naz Bestamin Ozkaya 《Environmental Geology》2008,56(1):19-25
Monitoring groundwater quality by cost-effective techniques is important as the aquifers are vulnerable to contamination from
the uncontrolled discharge of sewage, agricultural and industrial activities. Faulty planning and mismanagement of irrigation
schemes are the principle reasons of groundwater quality deterioration. This study presents an artificial neural network (ANN)
model predicting concentration of nitrate, the most common pollutant in shallow aquifers, in groundwater of Harran Plain.
The samples from 24 observation wells were monthly analysed for 1 year. Nitrate was found in almost all groundwater samples
to be significantly above the maximum allowable concentration of 50 mg/L, probably due to the excessive use of artificial
fertilizers in intensive agricultural activities. Easily measurable parameters such as temperature, electrical conductivity,
groundwater level and pH were used as input parameters in the ANN-based nitrate prediction. The best back-propagation (BP)
algorithm and neuron numbers were determined for optimization of the model architecture. The Levenberg–Marquardt algorithm
was selected as the best of 12 BP algorithms and optimal neuron number was determined as 25. The model tracked the experimental
data very closely (R = 0.93). Hence, it is possible to manage groundwater resources in a more cost-effective and easier way with the proposed
model application. 相似文献
4.
Until recently the traditional spatial configuration of the European geography was based upon the core-periphery model. The
‘pentagon’, broadly defined as lying between London, Paris, Milan, Munich and Hamburg, was seen as the core area characterised
by having the highest concentration of economic development in the European Union (EU), with the remainder of the European
territory viewed as peripheral, albeit to varying degrees. In a number of cases such peripheral areas equated with clear regional
disparities. The elaboration of the European Spatial Development Perspective (ESDP) (CEC, European spatial development perspective, towards balanced and sustainable development in the territory of the
European Union, 1999) challenged this core-periphery model. European spatial planning policies, aimed at encouraging social
and economic, and with ever increasing importance, territorial cohesion, seek amongst other aspects to encourage the development
of a balanced and polycentric urban system. This paper adopts a network analysis approach to the analysis of air passenger
flows between some 28 principal European metropolitan urban regions. The evaluation of these flows contributes to an enhanced
comprehension of the spatial dynamics of the European metropolitan territory which goes beyond that deriving from the more
standard analyses of the individual components of the urban system. Several indicators are used, deriving from gravitational
modelling techniques, to analyse the complexity of the air passenger flows. A multidimensional scaling (MDS) technique is
introduced in order to interpret and visualise the resulting spatial configuration and positioning of the different metropolitan
centres within the conceptual European ‘space of air passenger flows’, thereby contrasting with the more traditional map-based
geographical image of Europe, based upon Cartesian coordinates.
相似文献
Malcolm C. BurnsEmail: |
5.
T. G. Sitharam Pijush Samui P. Anbazhagan 《Geotechnical and Geological Engineering》2008,26(5):503-517
Geospatial technology is increasing in demand for many applications in geosciences. Spatial variability of the bed/hard rock
is vital for many applications in geotechnical and earthquake engineering problems such as design of deep foundations, site
amplification, ground response studies, liquefaction, microzonation etc. In this paper, reduced level of rock at Bangalore,
India is arrived from the 652 boreholes data in the area covering 220 km2. In the context of prediction of reduced level of rock in the subsurface of Bangalore and to study the spatial variability
of the rock depth, Geostatistical model based on Ordinary Kriging technique, Artificial Neural Network (ANN) and Support Vector
Machine (SVM) models have been developed. In Ordinary Kriging, the knowledge of the semi-variogram of the reduced level of
rock from 652 points in Bangalore is used to predict the reduced level of rock at any point in the subsurface of the Bangalore,
where field measurements are not available. A new type of cross-validation analysis developed proves the robustness of the
Ordinary Kriging model. ANN model based on multi layer perceptrons (MLPs) that are trained with Levenberg–Marquardt backpropagation
algorithm has been adopted to train the model with 90% of the data available. The SVM is a novel type of learning machine
based on statistical learning theory, uses regression technique by introducing loss function has been used to predict the
reduced level of rock from a large set of data. In this study, a comparative study of three numerical models to predict reduced
level of rock has been presented and discussed. 相似文献
6.
Nonlinear interactions between large waves and freely floating bodies are investigated by a 2D fully nonlinear numerical wave tank (NWT). The fully nonlinear 2D NWT is developed based on the potential theory, MEL/material-node time-marching approach, and boundary element method (BEM). A robust and stable 4th-order Runge–Kutta fully updated time-integration scheme is used with regriding (every time step) and smoothing (every five steps). A special φn-η type numerical beach on the free surface is developed to minimize wave reflection from end-wall and wave maker. The acceleration-potential formulation and direct mode-decomposition method are used for calculating the time derivative of velocity potential. The indirect mode-decomposition method is also independently developed for cross-checking. The present fully nonlinear simulations for a 2D freely floating barge are compared with the corresponding linear results, Nojiri and Murayama’s (Trans. West-Jpn. Soc. Nav. Archit. 51 (1975)) experimental results, and Tanizawa and Minami’s (Abstract for the 6th Symposium on Nonlinear and Free-surface Flow, 1998) fully nonlinear simulation results. It is shown that the fully nonlinear results converge to the corresponding linear results as incident wave heights decrease. A noticeable discrepancy between linear and fully nonlinear simulations is observed near the resonance area, where the second and third harmonic sway forces are even bigger than the first harmonic component causing highly nonlinear features in sway time series. The surprisingly large second harmonic heave forces in short waves are also successfully reproduced. The fully updated time-marching scheme is found to be much more robust than the frozen-coefficient method in fully nonlinear simulations with floating bodies. To compare the role of free-surface and body-surface nonlinearities, the body-nonlinear-only case with linearized free-surface condition was separately developed and simulated. 相似文献
7.
8.
本研究初步评价CHIMEHERB人工皮的治疗效果.74例,105个创面应用人工皮:供皮区47个创面,愈合时间平均为9±1.94d(天),油纱布对照为11.7±1.93d(P<0.01);14个浅Ⅱ°新鲜创面,70%在3~5d内逐渐干燥与创面紧密粘附,平均愈合时间为9.8±3.09d;11个存留上皮组织的削痂深Ⅱ°创面,平均5.7±1.7d干燥,平均愈合时间为10.55±3.09d,不需植自体皮;8个削痂刨面至脂肪组织或切痂创面4~9d更植自体皮,其存活率近乎100%,2个创面因残留坏死组织而失败;人工皮应用于16个自体皮间隙创面,除三个网状植皮和一个条状植皮创面失败外,所植自体皮都在人工皮下扩展融合,未观察到占位现象;对后期残余小创面有良好的效果.本研究结果提示人工皮对创面愈合具有有利影响.主要适用于供皮区、浅Ⅱ°新鲜创面、深Ⅱ°脱痂和削痂后存留上皮组织较多的创面、自体皮间隙创面和后期残余小创面,不适宜于深Ⅲ°新鲜创面. 相似文献
9.
将现代人工神经网络方法应用于地质学的判别分析,通过实例计算表明,无论是对于两组判别分析还是多组判别分析,人工神经网络方法都是切实可行的。 相似文献
10.
Unlike in the open sea, the use of wind information for forecasting waves may encounter more ambiguous uncertainties in the coastal or harbor area due to the influence of complicated geometric configurations. Thus this paper attempts to forecast the waves based on learning the characteristics of observed waves, rather than the use of the wind information. This is reported in this paper by the application of the artificial neural network (ANN), in which the back-propagation algorithm is employed in the learning process for obtaining the desired results. This model evaluated the interconnection weights among multi-stations based on the previous short-term data, from which a time series of waves at a station can be generated for forecasting or data supplement based on using the neighbor stations data. Field data are used for testing the applicability of the ANN model. The results show that the ANN model performs well for both wave forecasting and data supplement when using a short-term observed wave data. 相似文献