QuickBird and Hyperion data analysis of an invasive plant species in the Galapagos Islands of Ecuador: Implications for control and land use management

In the Galapagos Islands of Ecuador, one of the greatest threats to the terrestrial ecosystem is the increasing number and areal extent of invasive species. Increased human presence on the islands has hastened the introduction of plant and animal species that threaten the native and endemic flora and fauna. Considerable research on invasive species in the Galapagos Islands has been conducted by the Charles Darwin Foundation. We complement that work through a spatially- and spectrally-explicit satellite assessment of an important invasive plant species (Psidium guajava — guava) on Isabela Island that integrates diverse remote sensing systems, data types, spatial and spectral resolutions, and analytical and image processing approaches. QuickBird and Hyperion satellite data are processed to characterize the areal extent and spatial structure of guava through the following approaches: (1) QuickBird data are classified through a traditional pixel-based approach (i.e., an unsupervised classification approach using the ISODATA algorithm), as well as an Object-Based Image Analysis (OBIA) approach; (2) multiple approaches for spectral “unmixing” of the Hyperion hyper-spectral data are assessed to construct spectral end-members from QuickBird data using linear and non-linear mixture modeling approaches; and (3) landscape pattern metrics are calculated and compared for the pixel-based, object-based, and spectral unmixing approaches. The spectral–spatial characteristics of guava are interpreted relative to management strategies for the control of guava and the restoration of natural ecosystems in the Galapagos National Park.     

The impact of misregistration on SRTM and DEM image differences

Image differences between Shuttle Radar Topography Mission (SRTM) data and other Digital Elevation Models (DEMs) are often performed for either accuracy assessment or for estimating vegetation height across the landscape. It has been widely assumed that the effect of sub-pixel misregistration between the two models on resultant image differences is negligible, yet this has not previously been tested in detail. The aim of this study was to determine the impact that various levels of misregistration have on image differences between SRTM and DEMs. First, very accurate image co-registration was performed at two study sites between higher resolution DEMs and SRTM data, and then image differences (SRTM–DEM) were performed after various levels of misregistration were systematically introduced into the SRTM data. It was found that: (1) misregistration caused an erroneous and dominant correlation between elevation difference and aspect across the landscape; (2) the direction of the misregistration defined the direction of this erroneous and systematic elevation difference; (3) for sub-pixel misregistration the error due solely to misregistration was greater than, or equal to the true difference between the two models for substantial proportions of the landscape (e.g., greater than 33% of the area for a half-pixel misregistration); and (4) the strength of the erroneous relationship with aspect was enhanced by steeper terrain. Spatial comparisons of DEMs were found to be sensitive to even sub-pixel misregistration between the two models, which resulted in a strong erroneous correlation with aspect. This misregistration induced correlation with aspect is not likely specific to SRTM data only; we expect it to be a generic relationship present in any DEM image difference analysis.     

Real-time modeling and rendering of raining scenes

Real-time modeling and rendering of a realistic raining scene is a challenging task. This is because the visual effects of raining involve complex physical mechanisms, reflecting the physical, optical and statistical characteristics of raindrops, etc. In this paper, we propose a set of new methods to model the raining scene according to these physical mechanisms. Firstly, by adhering to the physical characteristic of raindrops, we model the shapes, movements and intensity of raindrops in different situations. Then, based on the principle of human vision persistence, we develop a new model to calculate the shapes and appearances of rain streaks. To render the foggy effect in a raining scene, we present a statistically based multi-particles scattering model exploiting the particle distribution coherence along each viewing ray. By decomposing the conventional equations of single scattering of non-isotropic light into two parts with the physical parameter independent part precalculated, we are able to render the respective scattering effect in real time. We also realize diffraction of lamps, wet ground, the ripples on puddles in the raining scene, as well as the beautiful rainbow. By incorporating GPU acceleration, our approach permits real-time walkthrough of various raining scenes with average 20 fps rendering speed and the results are quite satisfactory.     

基于VxWorks的系统故障快速恢复设计

针对CDMA通讯系统基站侧的重要单板——基带信号处理单板的系统故障需要在极短时间内进行自恢复的要求,设计了一种基于VxWorks操作系统的故障快速恢复方法,包括操作系统的任务、消息队列、信号量等操作设计,同时对设计前后系统故障恢复情况进行了对比测试、验证。     

Global dynamics for non-autonomous reaction-diffusion neural networks with time-varying delays

In this paper, a class of non-autonomous reaction-diffusion neural networks with time-varying delays is considered. Novel methods to study the global dynamical behavior of these systems are proposed. Employing the properties of diffusion operator and the method of delayed inequalities analysis, we investigate global exponential stability, positive invariant sets and global attracting sets of the neural networks under consideration. Furthermore, conditions sufficient for the existence and uniqueness of periodic attractors for periodic neural networks are derived and the existence range of the attractors is estimated. Finally two examples are given to demonstrate the effectiveness of these results.     

Investigating university student preferences and beliefs about learning in the web-based context

Psychological studies have shown that personal beliefs about learning and environmental preferences affect learning behaviors. However, these learner characteristics have not been widely discussed in the web-based context. By developing questionnaires, this study attempted to detect learners’ web-based learning environmental preferences (WLEP) and beliefs about web-based learning (BWL). The scope of WLEP focused on the pedagogical dimension of the web-based learning environment, while BWL concerned the attributes and control factors of the web-based learning. There were about five hundreds of Taiwan university students participating in the study. Through factor analysis, the scales discussed in the study revealed a satisfactory validity and reliability in assessing students’ preferences and beliefs. Further analyses showed that university students preferred more of individual and structured instructional configurations while expected the outward mode of interaction. In general, students held a rather contextual belief about web-based learning, which was found to be correlated with their environmental preferences.     

Study of diffusion mobilities of Nb and Zr in bcc Nb–Zr alloys

On the basis of the available thermodynamic parameters, the atomic mobilities of Nb and Zr in bcc Nb–Zr alloys are critically assessed as functions of temperatures and compositions by the CALPHAD method, where self-diffusion coefficients, impurity diffusion coefficients, tracer diffusion coefficients, interdiffusion coefficients and concentration curves are simultaneously optimized. Comparisons between the calculated and experimentally measured diffusion coefficients are made, where good agreement is evident. In addition, the obtained mobility parameters can reproduce a reasonable concentration profile for the Nb/Zr diffusion couple annealed at 1868 K for 5400 s.     

Using simulation and multi-criteria methods to provide robust solutions to dispatching problems in a flow shop with multiple processors

Dispatching rules are important to the performance of a manufacturing system. Selective applications of different priority rules at different processing stages in a multiple workstation manufacturing system have a positive impact on shop performance. This type of problem is a combinatorial dispatching decision. However, no dispatching rule can consistently produce better performance than all other rules under a variety of operating conditions and criteria. It is the purpose of this study to provide a robust solution for a dispatching decision that will have ‘good’ performance under different operating scenarios. In this paper a simulation case of a flow shop with multiple processors is proposed, specifically a multi-layer ceramic capacitor manufacturing system. Two multiple criteria decision-making methods – techniques for order preference by similarity to ideal solution (TOPSIS) and an analytic hierarchy process (AHP) – in combination with Taguchi orthogonal array are used to find the most suitable dispatching rule for every workstation. The results show that for 15 production scenarios and 4 criteria this combinatorial dispatching rule is robust, in the sense that it outperforms other commonly employed strategies.     

Small sample improvements in the threshold cointegration test using residual-based moving block bootstrap

A residual-based moving block bootstrap procedure for testing the null hypothesis of linear cointegration versus cointegration with threshold effects is proposed. When the regressors and errors of the models are serially and contemporaneously correlated, our test compares favourably with the Sup LM test proposed by Gonzalo and Pitarakis. Indeed, shortcomings of the former motivated the development of our test. The small sample performance of the bootstrap test is investigated by Monte Carlo simulations, and the results show that the test performs better than the Sup LM test.     

Analysis and reduction of data spikes in thin client computing

While various optimization techniques have been used in existing thin client systems to reduce network traffic, the screen updates triggered by many user operations will still result in long interactive latencies in many contemporary network environments. Long interactive latencies have an unfavorable effect on users’ perception of graphical interfaces and visual contents. The long latencies arise when data spikes need to be transferred over a network while the available bandwidth is limited. These data spikes are composed of a large amount of screen update data produced in a very short time. In this paper, we propose a model to analyze the packet-level redundancy in screen update streams caused by repainting of graphical objects. Using this model we analyzed the data spikes in screen update streams. Based on the analysis result we designed a hybrid cache-compression scheme. This scheme caches the screen updates in data spikes on both server and client sides, and uses the cached data as history to better compress the recurrent screen updates in possible data spikes. We empirically studied the effectiveness of our cache scheme on some screen updates generated by one of the most bandwidth-efficient thin client system, Microsoft Terminal Service. The experiment results showed that this cache scheme with a cache of 2M bytes can reduce 26.7%–42.2% data spike count and 9.9%–21.2% network traffic for the tested data, and can reduce 25.8%–38.5% noticeable long latencies for different types of applications. This scheme costs only a little additional computation time and the cache size can be negotiated between the client and server.