Coastal plant communities are being transformed or lost because of sea level rise (SLR) and land-use change. In conjunction with SLR, the Florida Everglades ecosystem has undergone large-scale ...drainage and restoration, altering coastal vegetation throughout south Florida. To understand how coastal plant communities are changing over time, accurate mapping techniques are needed that can define plant communities at a fine-enough resolution to detect fine-scale changes. We explored using bi-seasonal versus single-season WorldView-2 satellite data to map three mangrove and four adjacent plant communities, including the buttonwood/glycophyte community that harbors the federally-endangered plant
. Bi-seasonal data were more effective than single-season to differentiate all communities of interest. Bi-seasonal data combined with Light Detection and Ranging (LiDAR) elevation data were used to map coastal plant communities of a coastal stretch within Everglades National Park (ENP). Overall map accuracy was 86%. Black and red mangroves were the dominant communities and covered 50% of the study site. All the remaining communities had ≤10% cover, including the buttonwood/glycophyte community. ENP harbors 21 rare coastal species threatened by SLR. The spatially explicit, quantitative data provided by our map provides a fine-scale baseline for monitoring future change in these species' habitats. Our results also offer a method to monitor vegetation change in other threatened habitats.
This study tests the assumption of weak separability between demand for dairy and nondairy milk products by using food scanner data from 2012 to 2017 and estimating linear-approximate EASI demand ...systems. Our results show that the weak separability structures can be rejected. First, this finding shows that nondairy milk products compete with dairy milk for consumers' budget allocated to milk. Second, although milk demand studies often do not include nondairy milk, or assume weak separability, the exclusion of these products-or the separability assumptions-may lead to biased estimates.
Electronic noses (E-Nose) are devices used to substitute human or canine olfactory systems in detecting gases or chemical substances. The success of an E-Nose in detecting a set of target gases ...depends on how optimal is the choice of the gas sensors. This paper proposes a novel algorithm for selection of an optimal set of surface acoustic wave (SAW) sensors for an E-Nose from a given set of available gas sensors. The sensor performance is quantified in terms of separability of data obtained from them. A similarity measure specifying how similar the responses of sensors are when exposed to a set of gases, is also defined. The sensor selection algorithm is then specified as an optimization problem in terms of separability of target gases and similarity of sensor responses. The advantage of the proposed method lies in its performance being independent of the choice of the pattern recognition engine.
In this paper, we propose a novel bilinear projections model for unsupervised learning, which can be directly applied to dimension reduction and feature extraction for image analysis. Compared to ...previous 2-dimensional (2D) methods, our method seeks multiple rank-k bilinear projections (MRBP), which makes a balance between two opposite problems of enhancing the degree of freedom and avoiding the problem of over-fitting by adjusting k . Besides, each renewed feature in our method is extracted independently, rather than dimensions reduced by row or column like before, and thus our reduced dimension is not restricted by the size of a sample. In addition, we demonstrate that our model could be optimized via two equivalent optimization problems based on the criteria of maximum separability and nearest reconstruction respectively. Motivated by this, the corresponding robust version (RMRBP) achieving a better performance to occluded data is introduced as well. Extensive experiments on several datasets have been done to verify the effectiveness and superiority of our methods.
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► Reduction of cement paste content on fine recycled aggregates. ► Density and magnetic separation to remove particles with cement paste attached.► Advanced characterization to define ...liberation of natural aggregates. ► A low-cement paste content recycled sand may be achieved with high mass recovery. ► The change in recycling approach encourages the use of recycled sand.
The quality of recycled aggregates from construction and demolition waste (CDW) is strictly related to the content of porous and low strength phases, and specifically to the patches of cement that remain attached to the surface of natural aggregates. This phase increases water absorption and compromises the consistency and strength of concrete made from recycled aggregates. Mineral processing has been applied to CDW recycling to remove the patches of adhered cement paste on coarse recycled aggregates. The recycled fine fraction is usually disregarded due to its high content of porous phases despite representing around 50% of the total waste.
This paper focus on laboratory mineral separability studies for removing particles with a high content of cement paste from natural fine aggregate particles (quartz/feldspars). The procedure achieved processing of CDW by tertiary impact crushing to produce sand, followed by sieving and density and magnetic separability studies. The attained results confirmed that both methods were effective in reducing cement paste content and producing significant mass recovery (80% for density concentration and 60% for magnetic separation). The production of recycled sand contributes to the sustainability of the construction environment by reducing both the consumption of raw materials and disposal of CDW, particularly in large Brazilian centers with a low quantity of sand and increasing costs of this material due to long transportation distances.
Fire is one of the natural agents with the greatest impact on the terrestrial ecosystem and plays an important ecological role in a large part of the terrestrial surface. Remote sensing is an ...important technique applied in mapping and monitoring changes in forest landscapes affected by fires. This study presents a spectral separability analysis for the detection of burned areas using Landsat-8 OLI/TIRS images in the context of fires that occurred in different biomes of Brazil (dry ecosystem) and Portugal (temperate forest). The research is based on a fusion of spectral indices and automatic classification algorithms scientifically proven to be effective with as little human interaction as possible. The separability index (M) and the Reed–Xiaoli automatic anomaly detection classifier (RXD) allowed the evaluation of the spectral separability and the thematic accuracy of the burned areas for the different spectral indices tested (Burn Area Index (BAI), Normalized Burn Ratio (NBR), Mid-Infrared Burn Index (MIRBI), Normalized Burn Ratio 2 (NBR2), Normalized Burned Index (NBI), and Normalized Burn Ratio Thermal (NBRT)). The analysis parameters were based on spatial dispersion with validation data, commission error (CE), omission error (OE), and the Sørensen–Dice coefficient (DC). The results indicated that the indices based exclusively on the SWIR1 and SWIR2 bands showed a high degree of separability and were more suitable for detecting burned areas, although it was observed that the characteristics of the soil affected the performance of the indices. The classification method based on bitemporal anomalous changes using the RXD anomaly proved to be effective in increasing the burned area in terms of temporal alteration and performing unsupervised detection without relying on the ground truth. On the other hand, the main limitations of RXD were observed in non-abrupt changes, which is very common in fires with low spectral signal, especially in the context of using Landsat-8 images with a 16-day revisit period. The results obtained in this work were able to provide critical information for fire mapping algorithms and for an accurate post-fire spatial estimation in dry ecosystems and temperate forests. The study presents a new comparative approach to classify burned areas in dry ecosystems and temperate forests with the least possible human interference, thus helping investigations when there is little available data on fires in addition to favoring a reduction in fieldwork and gross errors in the classification of burned areas.
Linear separability and classification complexity Elizondo, David A.; Birkenhead, Ralph; Gamez, Matias ...
Expert systems with applications,
July 2012, 2012-7-00, 20120701, Letnik:
39, Številka:
9
Journal Article
Recenzirano
► Relationship between linear separability degree and complexity level of a data set. ► Quantification of the complexity of a classification problem. ► Transformation of non linearly separable ...problems into linearly separable ones.
We study the relationship between linear separability and the level of complexity of classification data sets. Linearly separable classification problems are generally easier to solve than non linearly separable ones. This suggests a strong correlation between linear separability and classification complexity. We propose a novel and simple method for quantifying the complexity of the classification problem. The method, which is shown below, reduces any two class classification problem to a sequence of linearly separable steps. The number of such reduction steps could be viewed as measuring the degree of non-separability and hence the complexity of the problem. This quantification in turn can be used as a measure for the complexity of classification data sets. Results obtained using several benchmarks are provided.
Firms develop products by manipulating the attributes of offerings, and consumers derive utility from the benefits that the attributes afford. While the field of marketing has long been aware of the ...distinction between attributes and benefits, it has not developed methods for understanding how attributes and benefits are related. This paper develops a benefit-based model for conjoint analysis that assumes consumers satiate on attributes that are perceived to provide the same benefit. A latent-variable model is proposed that estimates the map between attributes and benefits, and is applied to data from two conjoint studies involving a durable product and a household consumable. The model is shown to fit the data better, provide improved predictions, and lead to different product design implications than the standard conjoint model.
Data, as supplemental material, are available at
http://dx.doi.org/10.1287/mksc.2016.1003
.
The separability and the entanglement (that is, inseparability) of the composite quantum states play important roles in quantum information theory. Mathematically, a quantum state is a trace-class ...positive operator with trace one acting on a complex separable Hilbert space. In this paper, in more general frame, the notion of separability for quantum states is generalized to bounded positive operators acting on tensor product of Hilbert spaces. However, not like the quantum state case, there are different kinds of separability for positive operators with different operator topologies. Four types of such separability are discussed; several criteria such as the finite rank entanglement witness criterion, the positive elementary operator criterion and PPT criterion to detect the separability of the positive operators are established; some methods to construct separable positive operators by operator matrices are provided. These may also make us to understand the separability and entanglement of quantum states better, and may be applied to find new separable quantum states.
In this paper, we study a differential operator of parabolic type with a variable and unbounded coefficient, defined on an infinite strip. Sufficient conditions for the existence and compactness of ...the resolvent are established, and an estimate for the maximum regularity of solutions of the equation Lu=f∈L2(Ω) is obtained. Two-sided estimates for the distribution function of approximation numbers are obtained. As is known, estimates of approximation numbers show the rate of best approximation of the resolvent of an operator by finite-dimensional operators. The paper proves the assertion about the existence of positive eigenvalues among the eigenvalues of the given operator and finds two-sided estimates for them.
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