124 research outputs found
An Artificial Stream Network and Its Application on Exploring the Effect of DEM Resolution on Hydrological Parameters
No full textDigital elevation models (DEM) are widely used in various distributed hydrological models. The stream network can be extracted from it so that runoff routing can be calculated. With the advent of remote sensing and computing technologies, the computation based on DEM with high resolution becomes possible. However, there still exist regions with poor resolution, particularly in developing countries. Previous work only conducted comparisons between results by implementing hydrological models for specific basins in the real world and resolutions were only assigned to several fixed values, such as 30 and 90 m. So, the results derived were thus not in a general sense. To roughly understand how DEM resolution influences the hydrologic response, in this paper, first an artificial stream network of which the principle is originated from fractal theory is constructed. Then by implementing calculation on such artificial networks in an iterative way and performing aggregation, the influence of DEM resolution on several hydrological parameters, namely, the number of basins, drainage density of all basins, total stream length, average stream slope and average topographic index used to assess the spatial distribution of soil saturation of the largest basin can thus be acquired. It is found that DEMs of low resolution would reduce drainage density, total stream length and average stream slope, but would increase topographic index. But the effect is insignificant regarding the number of basins. In the end, the results of the simulation as well as the quality of the fractal terrain are validated by referencing field data.Accepted Author ManuscriptOLD Department of GIS Technolog
A Buckling-Based Method for Measuring the Strain-Photonic Coupling Effect of GaAs Nanoribbons
No full textInfluence of Fines on Evaluating Liquefaction of Sand by CPT
No full textA method of evaluating liquefaction potential of sand by Static Cone Penetration Test (CPT) was firstly developed basing on the field tests over Tangshan earthquake area and then confirmed by the test result in Haicheng earthquake. However, it showed considerable deviations when the method was used over Lutai area. The author holds that this outcome is mainly due to the difference between the soil characteristics of Lutai and Tangshan, i.e.. the former contains much more fine particles than the latter. Thus the method should be modified according to the fine particles content of the soil. A preliminary method of modification is herein presented
nD-PointCloud Data Management: continuous levels, adaptive histograms, and diverse query geometries
No full textIn the Geomatics domain, a point cloud refers to a data set which records the coordinates and other attributes of a huge number of points. Conceptually, each of these attributes can be regarded as a dimension, representing a specific type of information. Apart from routinely concerned spatio-temporal dimensions for coordinates, other dimensions such as intensity and classification are also widely used in spatial applications. In fact, more dimensions can be involved. For instance, a point in the hydraulic modelling grid also records the flow direction, speed, sediment concentration, and other related attributes. As these point cloud data can be directly collected, computed, stored and analyzed, this thesis proposes the term – nD-PointCloud, as a general spatial data representation to cover them. At present, drastically increasing production of nD-PointCloud data raises essential demand for smart and highly efficient data management and querying solutions. However, we lack effective tools. Prevalent software for nD-PointCloud processing, analyzing and rendering are built on file-based systems, requiring substantial development of data structures and algorithms. To make things worse, when other data types are involved, multiple formats, libraries and systems need enormous effort to be integrated. Aimed at generic support for diverse applications, DataBase Management Systems (DBMSs) on the other hand avoid these issues to a large extent. However, since they are initially developed to resolve 2D or 3D issues, they do not provide native support for nD data indexing and operations. Yet the 2D and 3D operators cannot be easily extended to nD.This thesis aims at developing a generic yet efficient solution for managing and querying nD-PointCloud data. The work is based on an existing solution called PlainSFC, which maps nD data into 1D space. PlainSFC is implemented in the DBMS, adopting space filling curve based clustering and B+-tree indexing strategies. Besides, PlainSFC applies an advanced querying mechanism which recursively refines hypercubic nD spaces to 1D ranges to approach the query geometry for primary filtering. This achieves high querying efficiency. However, the solution still has drawbacks, and this research focuses on resolving them by developing and using novel methods:• A continuous Level of Importance (cLoI) method for data organization to eliminate visual artifacts of density shocks in points' rendering, which is introduced by conventional tree structures such as Quadtree or Octree. The cLoI method computes an importance value for every point according to an ideal distribution generalized from the discrete distributions of those tree structures. This forms an additional cLoI dimension, and each point actually represents a level. By integrating the cLoI dimension into PlainSFC, smooth and efficient rendering is realized. • An nD-histogram approach to improve querying efficiency on non-uniformly distributed data. PlainSFC decomposes the nD space into sub-spaces recursively to approach the query geometry without considering point distribution. This is not optimal when the distribution of points is severely skewed. To improve this, an nD-histogram which records the number of points inside each nD sub-space is established as a representation of data distribution. The developed solution called HistSFC decomposes and refines the nD space more smartly, which improves the accuracy and efficiency of primary filtering.• A convex polytope querying function. Besides orthogonal window queries, the polytope query, which is the extension of the widely adopted polygonal query in 2D, also plays a critical role in many nD spatial applications. To address this type of query, an easy-to-use polytope formulation for querying is firstly proposed. Then, based on PlainSFC and HistSFC, efficient intersection algorithms are developed for convex polytope querying on nD point clouds. These algorithms are tested through experiments with up to 10D point data. Using this newly developed function, applications including perspective view selections and flood risk queries are resolved more efficiently, achieving sub-second performance. Additionally, other optimization techniques such as parallelization are developed and experimented with, which also bring performance gain. To verify the whole framework, several benchmark tests devised by considering real applications are conducted, and comparisons with different state-of-the-art solutions are performed. The result shows that the newly developed solution outperforms the others, overall. In certain cases, the solution can be applied without further optimizations. However, this will not be the end. Rapidly arising high tech such as cloud computing platforms can boost the solution further to incorporate more data and users. Potential nD-PointCloud based applications still need to be explored, prototyped and tested to serve the society in practice.A+BE | Architecture and the Built Environment No 12 (2022)GIS Technologi
Parameter optimization of EPON physical layer and the performance analysis for burst mode receiver
No full textLarge Magnetocaloric Effect and Magnetoresistance in Fe and Co Co-Doped Ni-Mn-Al Heusler Alloys
No full textThe Ni40Co10-xFexMn33Al17 (x = 4, 6, 8) alloys are prepared by arc-melting method. The crystallographic structure, magnetic and magnetoresistance properties are systematically studied. The large magnetic change is obtained across the martensitic transformation from the ferromagnetic austenite phase to weak-magnetic martensite phase. With the increase in Fe/Co ratio, the martensite transformation temperature shifts to the lower temperature. The large values of magnetoresistance of 33.3, 25.7, and 13.1% are achieved at the field of 3T for x = 4, x = 6, and x = 8 alloys around the martensitic transformation, respectively. These results indicate that Ni-Fe-Co-Mn-Al alloy provides the motive power for further research in practical applications
The orthographic sensitivity to written Chinese in the occipital-temporal cortex
No full textPrevious studies have identified an area in the left lateral fusiform cortex that is highly responsive to written words and has been named the visual word form area (VWFA). However, there is disagreement on the specific functional role of this area in word recognition. Chinese characters, which are dramatically different from Roman alphabets in the visual form and in the form to phonological mapping, provide a unique opportunity to investigate the properties of the VWFA. Specifically, to clarify the orthographic sensitivity in the mid-fusiform cortex, we compared fMRI response amplitudes (Exp. 1) as well as the spatial patterns of response across multiple voxels (Exp. 2) between Chinese characters and stimuli derived from Chinese characters with different orthographic properties. The fMRI response amplitude results suggest the existence of orthographic sensitivity in the VWFA. The results from multi-voxel pattern analysis indicate that spatial distribution of the responses across voxels in the occipitotemporal cortex contained discriminative information between the different types of character-related stimuli. These results together suggest that the orthographic rules are likely represented in a distributed neural network with the VWFA containing the most specific information regarding a stimulus' orthographic regularity
Managing Large Multidimensional Array Hydrologic Datasets: A Case Study Comparing NetCDF and SciDB
No full textAbstractManagement of large hydrologic datasets including storage, structuring, indexing and query is one of the crucial challenges in the era of big data. This research originates from a specific data query problem: time series extraction at specific locations takes a long time when a large multidimensional dataset is stored in non-chunked NetCDF classic or 64-bit offset format. The essence of this issue lies in the contiguous storage structure adopted by NetCDF. In this research, NetCDF file based solutions and a multidimensional (MD) array database management system (DBMS) applying chunked storage structure are benchmarked to determine the best solution for storing and querying large hydrologic datasets. To achieve this, expert consultancy was conducted to establish benchmark sets. To guarantee a fair benchmark test environment, HydroNET-4 system was utilized and adapters for NetCDF files and SciDB were developed to manage and query data. In final benchmark tests, effect of data storage configurations such as chunk size and compression on query performance is also explored. Results indicate that SciDB arrays utilizing small chunk sizes show favorable performance. However with current implementation of SciDB, large numbers of small chunks cause huge overload of main memory which constraints SciDB's scalability. Compression of SciDB can either have negative or no effect on query performance, while it causes significant query degradation to NetCDF-4 solution. The research illustrates that for big hydrologic array data management, the properly chunked NetCDF-4 solution without compression is in general more efficient than the SciDB DBMS. So under current big data environment, traditionally adopted file-based hydroinformatic solutions can still be applicable after proper updating
Author response: Quantitative proteomics reveal proteins enriched in tubular endoplasmic reticulum of Saccharomyces cerevisiae
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