Abstract
Australia has experienced increasing number of heatwave events (HWEs) in recent decades. This study aims to examine key synoptic features of austral summer HWEs over Australia during ...1950/1951–2019/2020. Based on ERA5‐reanalysis and rotated empirical orthogonal functions, HWEs in Australia are categorized into four types according to where they often occur together: East Australia (EA), North Australia (NA), West Australia (WA) and Southeast Australia (SEA). Our results reveal that while anomalous anticyclones at 500 hPa level are the typical synoptic circulations responsible for HWEs of each subregion, their specific mechanisms differ between subregions. The atmospheric heat budget at 850 hPa level shows that anomalous diabatic heating promotes the onset of HWEs in each subregion. While anomalous vertical advection and adiabatic heating due to the anomalous subsidence play an important role in maintaining HWEs till their demise in NA, they only help trigger HWEs in EA, SEA and WA. Our results also suggest that anomalous advection of climatological mean temperature is important to both the onset and persistence of HWEs in EA and SEA, while it only helps sustain (trigger) HWEs in NA (WA). The advection of anomalous temperature also acts to trigger HWEs in EA, SEA and WA. On the surface, upward long‐wave radiation and sensible heat flux contribute to the development of HWEs, whereas both of them are reduced in SEA due to the enhanced anomalous cyclones near the surface and the decreased land–air temperature difference. These findings help improve understanding of the synoptic characteristics and distinctive mechanisms of HWEs in different subregions of Australia.
Computationally efficient and numerically accurate modelling of heterogeneous materials with complex internal architectures at the macroscale is a current problem. For instance, in engineering ...materials such as 3D woven composites, retaining the description of material architectures is important to obtain an accurate prediction of stiffness. However, computational cost increases in proportion to the level of mesoscale details modelled. To enable efficient and accurate calculations on the structural scale, a multiscale method that can identify repeatable patterns in the mesoscale and represent them efficiently at the macroscale is proposed. This method has two important novelties, (i) a method to identify and store repeatable patterns during offline stage in the form of 3D Voronoi cells using a data compression algorithm, k-means clustering. This improves the identification with a minimum number of data clusters and minimises the effects of mesh sizes, and (ii) a method to select most similar Voronoi cells from the mesoscale database during online stage using image registration and k-d tree data structure. This enables computations being performed without explicitly modelling mesoscale details and reduces the computational cost that are otherwise required. The proposed method is validated against 3D woven unit-cell and three-point bending examples. Furthermore, the ability to find repeatable patterns is tested by analysing a woven architecture previously not stored in the database.
•A multiscale method to identify repeatable patterns observed in the mesoscale.•A Voronoi clustering method is proposed to identify and store repeatable patterns.•Image registration and k-d data tree structure to retrieve the relevant data.•Accurate online macroscale computations using the retrieved data.
The stability and stabilizability concepts for means in two variables have been introduced in (Raïssouli in Appl. Math. E-Notes 11:159-174, 2011). It has been proved that the arithmetic, geometric, ...and harmonic means are stable, while the logarithmic and identric means are stabilizable. In the present paper, we introduce new concepts, the so-called sub-stabilizability and super-stabilizability, and we apply them to some standard means.
MSC:
26E60.
•Overview of agricultural machine vision system using statistical ML algorithms.•Supervised statistical ML algorithms include naïve Bayes, DA, kNN and SVMs.•Unsupervised ones include K-means ...clustering, Fuzzy clustering and GMM.•Highlight the limitations of different statistical ML algorithms in agriculture.•Suggest effective statistical ML algorithms in each specific area in agriculture.
With being rapid increasing population in worldwide, the need for satisfactory level of crop production with decreased amount of agricultural lands. Machine vision would ensure the increase of crop production by using an automated, non-destructive and cost-effective technique. In last few years, remarkable results have been achieved in different sectors of agriculture. These achievements are integrated with machine learning techniques on machine vision approach that cope with colour, shape, texture and spectral analysis from the image of objects. Despite having many applications of different machine learning techniques, this review only described the statistical machine learning technologies with machine vision systems in agriculture due to broad area of machine learning applications. Two types of statistical machine learning techniques such as supervised and unsupervised learning have been utilized for agriculture. This paper comprehensively surveyed current application of statistical machine learning techniques in machine vision systems, analyses each technique potential for specific application and represents an overview of instructive examples in different agricultural areas. Suggestions of specific statistical machine learning technique for specific purpose and limitations of each technique are also given. Future trends of statistical machine learning technology applications are discussed.
SURE-Based Non-Local Means Van De Ville, D.; Kocher, M.
IEEE signal processing letters,
11/2009, Letnik:
16, Številka:
11
Journal Article
Recenzirano
Odprti dostop
Non-local means (NLM) provides a powerful framework for denoising. However, there are a few parameters of the algorithm-most notably, the width of the smoothing kernel-that are data-dependent and ...difficult to tune. Here, we propose to use Stein's unbiased risk estimate (SURE) to monitor the mean square error (MSE) of the NLM algorithm for restoration of an image corrupted by additive white Gaussian noise. The SURE principle allows to assess the MSE without knowledge of the noise-free signal. We derive an explicit analytical expression for SURE in the setting of NLM that can be incorporated in the implementation at low computational cost. Finally, we present experimental results that confirm the optimality of the proposed parameter selection.
Linear Spectral Clustering Superpixel Chen, Jiansheng; Li, Zhengqin; Huang, Bo
IEEE transactions on image processing,
2017-July, 2017-Jul, 2017-7-00, 20170701, Letnik:
26, Številka:
7
Journal Article
Recenzirano
In this paper, we present a superpixel segmentation algorithm called linear spectral clustering (LSC), which is capable of producing superpixels with both high boundary adherence and visual ...compactness for natural images with low computational costs. In LSC, a normalized cuts-based formulation of image segmentation is adopted using a distance metric that measures both the color similarity and the space proximity between image pixels. However, rather than directly using the traditional eigen-based algorithm, we approximate the similarity metric through a deliberately designed kernel function such that pixel values can be explicitly mapped to a high-dimensional feature space. We then apply the conclusion that by appropriately weighting each point in this feature space, the objective functions of the weighted K-means and the normalized cuts share the same optimum points. Consequently, it is possible to optimize the cost function of the normalized cuts by iteratively applying simple K-means clustering in the proposed feature space. LSC possesses linear computational complexity and high memory efficiency, since it avoids both the decomposition of the affinity matrix and the generation of the large kernel matrix. By utilizing the underlying mathematical equivalence between the two types of seemingly different methods, LSC successfully preserves global image structures through efficient local operations. Experimental results show that LSC performs as well as or even better than the state-of-the-art superpixel segmentation algorithms in terms of several commonly used evaluation metrics in image segmentation. The applicability of LSC is further demonstrated in two related computer vision tasks.
Since 2008, the Japanese whiskey business has grown steadily. Overall, the whiskey market (at factory price) is expected to reach $2.95 billion in 2019, accounting for 8.6 percent of the entire ...alcoholic beverage industry. The rise in popularity of Japanese whiskey is associated with the country's growing international reputation. Founded 1985 as an independent bottler, Master of Malt was the first company to service clients who ordered single malt whiskey through the mail-order system. Master of Malt's omnichannel approach encompasses all channels available to the company. Known as their 'omnichannel,' this refers to the organization's capability to provide speed and precision from any place at any time. As their brand has grown over the years, they have used various marketing strategies, including a website redesign and rebuild that involved the creation of all relevant content and designing and constructing landing pages for their website. Following a clustering technique, we discovered that the data is being divided into four distinct groups and that these clusters may serve as a recommender system based on the occurrence of terms in each of the categories. Our summarizing component combined phrases related to the exact subtopics and provided users with a concise summary and sentimental information about the group of phrases.
In this paper, the complementary of arithmetic mean, geometric mean, harmonic mean and contra harmonic mean with respect to Heron mean are defined. Further, by finding the partial derivatives ...developed the Schur convexity and Schur geometric convexity results.
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