Neural network prediction of nitrate in groundwater of Harran Plain, Turkey

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.     

GMOs and their contexts: A comparison of potential and actual performance of GM crops in a local agricultural setting

In this paper, I argue that genetically modified organisms (GMOs) have inherent potential to contribute to socially and environmentally sustainable agriculture by virtue of their ‘biological embeddedness’. Their actual ‘performance’ and how this contributes to sustainability depends on the ‘mutual shaping’ of technology and context. While much attention has been given to the design context of GMOs, this paper considers the influence of the application context and of users. A case study investigating the use of insect-resistant and herbicide-tolerant GM cotton in the cotton-growing region of New South Wales in Australia is presented. The study was based on focus groups with farmers and other stakeholders in a cotton-growing community. It demonstrated a range of direct and indirect effects of GM cotton use, both positive and negative for sustainability, and the ways in which these effects were influenced by the local social context. The influences of the biotechnology industry context, in limiting the contributions that gene technologies can make to sustainability, were also considered, and remedies suggested. I argue that the polarity of the GM debate is hindering progress on these issues, and that a more balanced approach to our analysis of GMOs is necessary in order to fully understand, and to influence, their role in the future of rural spaces.     

Contribution of the SISCam Web-based GIS to the seismotectonic study of Campania (Southern Apennines): an example of application to the Sannio-area

In this article the implementation and potential of the Seismotectonic Information System of the Campania Region (SISCam) are described, in particular an application of this Web-based GIS system to the seismotectonic analysis of the Sannio area (Southern Apennines) is performed. WEB-GIS technologies greatly contribute to both the environmental monitoring and the disaster management of areas affected by high natural risks. Specifically the SISCam system has been developed with the aim of providing easy access and fast diffusion, through Internet technology, of the most significant geological, geophysical, and territorial data relative to the Campania Region. The Sannio area has been selected as our application example because it is among the most active seismic regions in Italy. This portion of the Southern Apennines which was hit by the June 5, 1688 strong earthquake (M _W = 6.7, CPTI 1999) and by some low- and moderate-energy seismic sequences (1990–1992, 1997), is characterized by a complex inherited tectonic setting and low-tectonic deformation rates that hide the seismogenic sources position. Since this case study turned out to be complicated, the use of the SIScam WEB-GIS has become indispensable because it allowed us to visualize, integrate and analyze all the data available, in order to obtain an accurate and direct picture of the seismotectonic setting of the area. Moreover, a different approach of data analysis was necessary, due to the lack of up-to-date neotectonic and structural data; therefore, the operation of this GIS system enabled us to process and generate some original informative layers, through image analysis, such as new structural lineaments represented on a map of the potential active faults of the area, which has been the final result of our application, as a contribution to new knowledge about the local seismic risk parameters.     

Numerical estimation of REV and permeability tensor for fractured rock masses by composite element method

The Monte Carlo method is used to generate parent stochastic discrete fracture network, from which a series of fractured rock samples of different sizes and orientations are extracted. The fracture network combined with a regular grid forms composite element mesh of the fractured rock sample, in which each composite element is composed of sub‐elements incised by fracture segments. The composite element method (CEM) for the seepage is implemented to obtain the nodal hydraulic potential as well as the seepage flow rates through the fractured rock samples. The application of CEM enables a large quantity of stochastic tests for the fractured rock samples because the pre‐process is facilitated greatly. By changing the sizes and orientations of the samples, the analysis of the seepage characteristics is realized to evaluate the variation of the permeability components, the existence of the permeability tensor and the representative element volume. The feasibility and effectiveness are illustrated in a numerical example. Copyright © 2008 John Wiley & Sons, Ltd.     

基于Mindlin理论Winkler地基参数的Kalman滤波识别

提出了Winkler地基参数的Kalman滤波识别方法。引入Mindlin理论后,推导了Winkler地基上板的控制微分方程。利用Fourier变换,推求了Winkler地基上简支板的Fourier闭式解。推导了Winkler地基参数的Kalman滤波方程,研究了Winkler地基参数的Kalman滤波识别的具体计算步骤。研究表明,运用Kalman滤波理论进行Winkler地基参数的识别,能有效地估计Winkler地基参数;Winkler地基参数的滤波收敛速度和精度受地基参数初始值选取和位移实测资料的影响,且Kalman滤波理论也可用于其他地基模型地基参数的识别。     

矿物数字博物馆的建设构想与实现

在基于互联网的应用、信息数字化、多种技术发展较为成熟及适应公众需求的基础上,对矿物数字博物馆的建设做了简要的分析,将矿物按矿物一结晶学分类方案将馆藏矿物进行合理的分类,设计了七大功能结构和相应的子结构,并对矿物所要展示的内容设定了标准.建设矿物数字博物馆旨在利用三维技术、多媒体技术、文字信息等,将矿物从宏观的外形到抽象的晶体形态和微观的晶体结构及其最小单位结构通过网络的形式具体展现给观众.矿物数字博物馆的建设可以为人们认知整个矿物世界搭建一个良好的平台,在科研教学、推动国民科学普及教育、培养创新人才方面发挥重要作用.     

钢筋混凝土梁结构断裂损伤诊断方法

提出一种基于BP神经网络的结构破损诊断方法,该方法以结构破损前后柔度的变化作为破损诊断网络输入,为了解决由于系统响应样本数据空间分布不均匀对网络收敛速度及网络诊断影响问题,对网络训练样本采用广义空间格点进行了交换,模拟算例及应用实例均表明,本文方法能准确诊断结构破损位置与破坏程度,是一种有效的结构破损诊断方法.     

Modeling of Multi-Freedom Ship Motions in Irregular Waves with Fuzzy Neural Networks

1 .IntroductionAshiptravelingatseaundergoesundesirablewave inducedmotions ,namely ,surge ,sway ,heav ing ,rolling ,pitchingandyaw .Thesemotionsoftencauseproblemstothecrew ,theonboardequip mentand ,intheworstcase ,thesafetyofthevessel.Tominimizethewave inducedshipmotions ,controlsystemsmaybeapplied .Theaccuratemodelingofshipmotionsisthereforeveryimportantforshipdesignanddesignofmotioncontrolsystems .Manyresearchershavedevelopedshipmotionpredictionmethodsbasedonthepotentialflowtheo ries (Dong ,…     

Neural Network-Based Active Control for Offshore Platforms

1 .IntroductionWiththedevelopmentofoceantechnology ,moreandmoreextremelylargeandlongflexibleoff shoreplatformsusedforoilexplorationanddrillingoperationarebuiltinhostileoceanenvironments .Ingeneral,thiskindofplatformsisanonlineardistributedparametersystemanditsnaturalfrequencyfallsclosertothedominantwavefrequencieswiththeincreaseofwaterdepth .Besides ,itsstructureisverycomplexandtheexternalwaveforceontheplatformisuncertain .Thus ,theseplatformsarepronetoexcessivewave inducedoscillationsunderbot…     

嵌入式Linux技术在海洋自动观测系统中的应用研究

随着Linux技术逐步走向成熟，嵌入式Linux技术在海洋自动观测系统中的应用将全面提高海洋观测系统整体性能，降低系统开发成本，进一步推进我国海洋自动观测系统产权自主化的建设。文章就如何研制适用于海洋自动观测系统的嵌入式Linux系统进行了论述。