Toward exploratory analysis of diversity unified across fields of study: an information visualization approach

The study of the diversity of multivariate objects shares common characteristics and goals across disciplines, including ecology and organizational management. Nevertheless, subject-matter experts have adopted somewhat separate diversity concepts and analysis techniques, limiting the potential for sharing and comparing across disciplines. Moreover, while large and complex diversity data may benefit from exploratory data analysis, most of the existing techniques emphasize confirmatory analysis based on statistical metrics and models. This work aims to bridge these gaps. First, by cross comparing the analyses of species diversity, microbial diversity, and workgroup diversity, we introduce a framework of diversity concerns aligned across the three areas. The alignment framework is validated and refined by feedback from subject-matter experts. Then, guided by the framework and theoretical information visualization and visual analytics principles (as distinguished from scientific visualization), we propose a unified taxonomy of common analytical tasks for exploration of diversity.     

Understanding spatial variations of malaria in Vietnam using remotely sensed data integrated into GIS and machine learning classifiers

Abstract

This study examines the potentials of remotely sensed data, GIS and some machine learning classifiers and ensemble techniques in the investigation of the non-linear relationship between malaria occurrences and socio-physical conditions in the Dak Nong province of Viet Nam. Accuracy assessment was determined with Receiver Operating Characteristic (ROC) curve and pair t-test. The results showed that the area under ROC of Random Subspace ensemble model performed better than the other models based on statistical indicators. Comparing pair t-test with Area Under Curve values showed a slight difference of about 1%. Therefore ensemble techniques had significantly improved the performance of the base classifier. However, the performances might vary according to geographic locations. It is concluded that the machine learning classifiers combined with remotely sensed data and GIS is promising for malaria vulnerability mapping, and the derived maps can be used as a fundamental basis for programmes on spatial disease control.     

Simultaneous hydrological prediction at multiple gauging stations using the NARX network for Kemaman catchment,Terengganu, Malaysia

ABSTRACT

This paper presents a neural network model capable of catchment-wide simultaneous prediction of river stages at multiple gauging stations. Thirteen meteorological parameters are considered in the input, which includes rainfall, temperature, mean relative humidity and evaporation. The NARX model is trained with a representative set of hourly data, with optimal time delay for both the input and output. The network trained using 120-day data is able to produce simulations that are in excellent agreement with field observations. We show that for application with one-step-ahead predictions, the loss in network performance is marginal. Inclusion of additional tidal observations does not improve predictions, suggesting that the river stage stations under consideration are not sensitive to tidal backwater effects despite the claim commonly made.

EDITOR D. Koutsoyiannis ASSOCIATE EDITOR F. Pappenberger     

Correlating mass physical properties with ALOS reflectance spectra for intertidal sediments from the Ba Lat Estuary (northern Vietnam): an exploratory laboratory study

Characterization of the sediment composition of tidal flats and monitoring of their spatiotemporal changes has become an important part of the sustainable management of coastal environments. To accurately classify sediments through remote sensing, a comprehensive understanding of sediment reflectance spectra is indispensable. The present laboratory-based study explores the performance of the high spatial resolution (10?×?10 m) Advanced Land Observing Satellite (ALOS) launched in 2006. Relationships between reflectance spectra (bands 1 to 4) and four typical mass physical properties were investigated under wet and dry experimental conditions for intertidal sediments sampled near the Ba Lat Estuary in northern Vietnam. Reflectance in the near-infrared region corresponding to ALOS band 4 (0.76–0.89 μm) was found (1) to have a strong negative correlation with sand content (dry wt%) under both wet and dry conditions (linear correlation coefficient r?=?–0.7859 and –0.8094, respectively), (2) to increase with decreasing relative water content (%) in a given sediment type (r?=?–0.7748 to –0.9367 for mud, sandy mud, muddy sand, and sand), (3) to have a positive correlation with organic matter content (r?=?0.7610 and 0.6460 under wet and dry conditions for contents >0.20 dry wt%), and (4) to be insignificantly correlated with mineral composition assessed in terms of contents (wt%) of quartz, clay minerals, and mica group minerals. Positive relationships between reflectance and water content for the pooled data of all sediment types (r?=?0.6395) or organic matter content contrast with previous findings, and can be attributed to close interrelationships between these properties and the predominance of sand content as controlling factor of reflectance. This study clarifies that ALOS band 4 provides the most useful imagery for intertidal monitoring because its reflectance, as simulated using the laboratory data, shows the strongest correlation with sand content. In a next step, these experimental findings should be verified by identifying the reflectance relationships at satellite image scales, and also considering the effects of other tidal flat features on reflectance, such as microtopography and biological surface characteristics.     

Experimental evidence of the double-porosity effects in geomaterials

Double-porosity is an important characteristic of microstructure in a large range of geomaterials. It designs porous media with connected fissures/fractures or aggregated soils. The origin of double-porosity can be natural or/and it can result from mechanical, chemical or biological damage. The presence of double-porosity can significantly affect the behaviour of geomaterials. In this paper we provide an experimental evidence of the double-porosity effects by performing laboratory experiments. Series of tracer dispersion experiments (in saturated and unsaturated steady-state water flow conditions) in a physical model of double-porosity geomaterial were carried out. For the comparative purposes, experiments of the same type were also performed in a singleporosity model medium. The results clearly showed that the double-porosity microstructure leads to the non-Fickian behaviour of the tracer (early breakthrough and long tail) in both saturated and unsaturated cases.     

龙门山构造带区域稳定性探讨

根据龙门山构造带的地震地质特征、地震活动规律及新构造活动特征,综合分析认为该地区区域稳定性受控于龙门山断裂带。而断裂带又以韧性切变形为主,蠕滑运动为特征,决定该带在相当长的一段时间内,发生强烈地震的可能性不大。     

辽河坳陷双清地区古近系沙河街组四段孔隙度演化模拟

在综合考虑沉积微相和成岩作用对储集层孔隙度影响的基础上,建立了辽河坳陷双清地区不同沉积微相成岩指数ID与储集层平均孔隙度的相关关系,预测了该地区沙四段储集层在各沉积时期的平均孔隙度,恢复了孔隙演化史,确定了不同沉积时期有效油气储集层的分布范围。孔隙度预测结果表明,有效油、气储集层分布于研究区北部孔隙度大于58％的地区。孔隙演化史的模拟结果表明,储集层孔隙度在埋藏早期主要受沉积相的影响,而在晚期则主要受成岩作用的控制。储集层预测孔隙度与实测孔隙度的绝对误差为2.7％.,而研究区储集层的填隙物含量在1.0％～40.0％之间,平均为21.7％.,由此可见,所建预测模型可用于填隙物含量较高的储集层钻前孔隙度预测和孔隙演化史模拟。     

Numerical Modeling of Wave-Enhanced Turbulence in the Oceanic Upper Layer

A coupled model of air-wave-sea interaction is modified based on a new roughness formulation and the latest data. The model parameters for aerodynamic roughness from below (ARB) and wave-dependent roughness from above (ARA, z _0a ) are assumed equal. The combined roughness is assumed to be a function of friction velocity, gravity, air and seawater densities, and wave age (c _w ). The model is used in a study of wave-enhanced turbulence under breaking waves to predict turbulent dissipation (), ARA, and drag coefficient (C _d ). Both waves and shear production are considered as sources of ocean turbulent energy. The atmospheric part of the model is used only to specify a correct condition at the interface. Numerical experiments are performed to study the -distribution, z _0a and C _d , and to compare with data. The major achievement is model verification using all available data. The first full application of this model is in conjunction with an ocean circulation model in a coupled circulation-wave system. Simulations show that the -distribution is strongly dependent on local wind-forced wave heights. For each wind and wave state there is a particular wave-dependent depth that is verified by data. The comparison shows that the model predicted agrees well with the observed of the z ^–4 law distribution of Gargett (1989). Simulations also show that waves have an important role in causing to differ from the classical wall-layer theory and z _0a , with a value of 0.30 for the empirical constant a _a . The model-predicted , z _0a , C _d and C _gd agree well with data.