基于工程管理的南海地质数据库

从南海地质数据资源、工程实例出发,结合高级语言设计和开发了基于工程管理的南海地质信息数据库系统.该系统设计实现了南海地质信息数据共享、数据融合、数据分析,简单快捷的结合到工程实例中,并应用ADO、DAO、OLE等计算机技术实现的数据资源快速导入、导出便于工程应用的目的.对工程中土的性质做详细的介绍,包括随深度的下降有效重度、抗剪强度、单位表面摩阻力、单位桩端阻力的变化情况.可以按层号、深度、土体性质等不同的条件进行查找.汇总功能可以绘制曲线,比较同一工程土体参数和不同工程之间的参数等,对工程设计和施工进行指导.     

高职计算机应用专业教学改革探索与实践

从构建"六位一体"实践教学体系、建立与实践教学相适应的理论教学体系、探索高职计算机应用技术专业人才培养模式等方面,就高职计算机应用专业教学改革进行了探索、实践和总结。     

高职电子技术课程的兴趣教学法

高职院校学生学习基础相对较差,对于传统的课堂教育难以适应,提出在电子技术教学中实施兴趣教学法,提高学生主动学习的积极性,也有助于提高教学质量。电子技术课实践性强,几乎每堂课都会涉及到实验,这样可以长期在实验室上课或者在教室做演示实验,每次课前教师列一个清单让学生提前到实验室准备好实验器材,学生在准备器材的过程中就会带着疑问：这是做什么用的呢？学生有了疑问就会有学习的好奇心,进而也就激发了对该课程的学习兴趣。     

小型水电站扩容增效技改中同期点和同期方式选择

本文针对目前每个小型水电站扩容增效技改中微机监控设计和改造中必须解决的同期点选择和同期方式确定问题结合相关理论、规范,在总结常规监控方式下同类问题的解决办法基础上结合工程实际提出了切实可行解决问题的方法和依据。     

Experimental study on total dissolved gas supersaturation in water

More and more high dams have been constructed and operated in China. The total dissolved gas (TDG) supersaturation caused by dam discharge leads to gas bubble disease or even death of fish. Through a series of experiments, the conditions and requirements of supersaturated TDG generation were examined in this study. The results show that pressure (water depth), aeration, and bubble dissolution time are required for supersaturated TDG generation, and the air-water contact area and turbulence intensity are the...     

Gibbs2: A new version of the quasiharmonic model code. II. Models for solid-state thermodynamics, features and implementation

In the second article of the series, we present the Gibbs2 code, a Fortran90 reimplementation of the original Gibbs program [Comput. Phys. Commun. 158 (2004) 57] for the calculation of pressure–temperature dependent thermodynamic properties of solids under the quasiharmonic approximation. We have taken advantage of the detailed analysis carried out in the first paper to implement robust fitting techniques. In addition, new models to introduce temperature effects have been incorporated, from the simple Debye model contained in the original article to a full quasiharmonic model that requires the phonon density of states at each calculated volume. Other interesting novel features include the empirical energy corrections, that rectify systematic errors in the calculation of equilibrium volumes caused by the choice of the exchange-correlation functional, the electronic contributions to the free energy and the automatic computation of phase diagrams. Full documentation in the form of a user?s guide and a complete set of tests and sample data are provided along with the source code.

Program summary

Program title:Gibbs2Catalogue identifier: AEJI_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEJI_v1_0.htmlProgram obtainable from: CPC Program Library, Queen?s University, Belfast, N. IrelandLicensing provisions: GNU General Public License, v3No. of lines in distributed program, including test data, etc.: 936 087No. of bytes in distributed program, including test data, etc.: 8 596 671Distribution format: tar.gzProgramming language: Fortran90Computer: Any running Unix/LinuxOperating system: Unix, GNU/LinuxClassification: 7.8External routines: Part of the minpack, pppack and slatec libraries (downloaded from www.netlib.org) are distributed along with the program.Nature of problem: Given the static E(V) curve, and possibly vibrational information such as the phonon density of states, calculate the equilibrium volume and thermodynamic properties of a solid at arbitrary temperatures and pressures in the framework of the quasiharmonic approximation.Additional comments: A detailed analysis concerning the fitting of equations of state has been carried out in the first part of this article, and implemented in the code presented here.Running time: The tests provided only take a few seconds to run.     

Large area forest stem volume mapping in the boreal zone using synergy of ERS-1/2 tandem coherence and MODIS vegetation continuous fields

ERS-1/2 tandem coherence was reported to have high potential for the mapping of boreal forest stem volume (e.g. Santoro et al., 2002, 2007a; Wagner et al., 2003; Askne & Santoro, 2005). Large-scale application of the data for forest stem volume mapping, however, is hindered by the variability of coherence with meteorological and environmental acquisition conditions. The traditional way of stem volume retrieval is based on the training of models, relating coherence to stem volume, with the aid of forest inventory data which is generally available for a few small test sites but not for large areas. In this paper a new approach is presented that allows model training using the MODIS Vegetation Continuous Fields canopy cover product (Hansen et al., 2003) without further need for ground data. A comparison of the new approach with the traditional regression-based and ground-data dependent model training is presented in this paper for a multi-seasonal ERS-1/2 tandem dataset covering several well known Central Siberian forest sites. As a test scenario for large-area application, the approach was applied to a multi-seasonal ERS-1/2 tandem dataset of 223 ERS-1 and ERS-2 image pairs covering Northeast China (~ 1.5 million km²) to map four stem volume classes (0-20, 20-50, 50-80, and > 80 m³/ha).     

Simulating multiple class urban land-use/cover changes by RBFN-based CA model

Land use systems are complex adaptive systems, and they are characterized by emergence, nonlinearity, feedbacks, self organization, path dependence, adaptation, and multiple-scale characteristics. Land use/cover change has been recognized as one of the major drivers of global environmental change. This paper presents a coupled Cellular Automata (CA) and Radial Basis Function Neural (RBFN) Network model, which combines Geographic Information Systems (GIS) to contribute to the understanding of the complex land use/cover change process. In this model, GIS analysis is used to generate spatial drivers of land use/cover changes, and RBFN is trained to extract model parameters. Through the RBFN-CA model, the conversion probabilities of each cell from its initial land use state to the target type can be generated automatically. Future land use/cover scenarios are projected by using generated parameters in the model training process. This RBFN-CA model is tested based on the comparison of model output and the real data. A BPN-CA model is also built and compared with the RBFN-CA model by using a variety of calibration metrics, including confusion matrix, figure of merit, and landscape metrics. Both the location and landscape metrics based assessment for model simulation indicate that the RBFN-CA model performs better than the BPN-CA model for simulating land use changes in the study area. Therefore the RBFN-CA model is capable of simulating multiple classes of land use/cover changes and can be used as a useful communication environment for stakeholders involved in land use decision-making.     

Suitability evaluation of urban construction land based on geo-environmental factors of Hangzhou, China

Suitability evaluation of urban construction land based on geo-environmental factors is the process of determining the fitness of a given tract of land for construction. This process involves a consideration of the geomorphology, geology, engineering geology, geological hazards, and other geological factors and is the basis of urban construction land planning and management. With the support of Geographic Information Systems (GIS), grid analysis, and geo-spatial analysis techniques, four factor groups comprising nine separate subfactors of geo-environmental attributes were selected to be used in the evaluation of the suitability level for construction land in Hangzhou. This was based on K-means clustering and back-propagation (BP) neural network methods due to their advantages in fast computing, unique adaptive capacity, and self-organization. Simultaneously, the evaluation results based on K-means clustering and BP neural network were compared and analyzed, and the accuracy evaluation was set. The results showed that the geo-environmental suitability evaluation results of construction land based on K-means clustering and BP neural network were similar in terms of the distribution and scale of construction land suitability level. At the same time, the results of the two evaluation methods were consistent with the variability in suitability level, engineering geology, and hydrogeology of Hangzhou. The results also showed that the real advantage of the methods proposed in this paper lies in their capacity to streamline the mapping process and to ensure that the results are consistent throughout. The suitability level of the urban construction land based on the geo-environment in Hangzhou was divided into four construction sites: land for building super high-rise and high-rise buildings, land for building multistorey buildings, land for low-rise buildings, and nonbuilding land. The results of the suitability evaluation for each category will provide a scientific basis for decision-making in urban development in Hangzhou.     

Development and application of a simulation model for changes in land-use patterns under drought scenarios

In arid and semiarid areas of northern China, one of the most vulnerable regional environments, water resources are a key constraint on socioeconomic development. We constructed a simulation model for land-use patterns under a drought transition (i.e., the increased frequency and duration of drought since the late 1970s in the Yongding River Basin study area) to account for the complexity of both the driving factors behind land-use change and the micro-level changes in land-use patterns. This model was a combination of the “top-down” system dynamics model, the “bottom-up” cellular automaton model, and the artificial neural network model. In this model, we considered the socioeconomic development and water resource restrictions, as well as the balance between the land-use requirements and the land supply. We then verified the model through a case study. The results demonstrated the value of constructing a simulation model driven by water resource constraints under the influence of drought. The spatial distribution of land uses in future scenarios will help support decision-making for sustainable regional development.