A hybrid clustering algorithm based on improved GWO and KHM clustering

To solve the problem that the K-means algorithm is sensitive to the initial clustering centers and easily falls into local optima, we propose a new hybrid clustering algorithm called the IGWOKHM algorithm. In this paper, we first propose an improved strategy based on a nonlinear convergence factor, an inertial step size, and a dynamic weight to improve the search ability of the traditional grey wolf optimization (GWO) algorithm. Then, the improved GWO (IGWO) algorithm and the K-harmonic means (KHM) algorithm are fused to solve the clustering problem. This fusion clustering algorithm is called IGWOKHM, and it combines the global search ability of IGWO with the local fast optimization ability of KHM to both solve the problem of the K-means algorithm’s sensitivity to the initial clustering centers and address the shortcomings of KHM. The experimental results on 8 test functions and 4 University of California Irvine (UCI) datasets show that the IGWO algorithm greatly improves the efficiency of the model while ensuring the stability of the algorithm. The fusion clustering algorithm can effectively overcome the inadequacies of the K-means algorithm and has a good global optimization ability.

Mixed modeling for fiber yield genetic selection in sugarcane

The current demand for clean and renewable energy has provoked considerable changes in the production system of agroindustrial companies. The generation of bioelectricity through the burning of sugarcane bagasse has considerably risen in the recent years. This work aimed to focus on the sugarcane genotypes selection for fiber productivity. The experiment was outlined in randomized blocks with four repetitions, and sixteen genotypes were evaluated. The evaluated traits were: cane tons per hectare, sucrose tons per hectare, fiber tons per hectare, fiber content and apparent sucrose content. To the selection, the mixed linear models methodology was used. The heritability coefficients suggest a significant genetic gain and the harmonic means of relative performances of predicted genotypic values allowed the identification of stable genotypes related to the traits evaluated in four harvest cycles. Considering the current average demand of sugarcane agroindustry for varieties with fiber content between 12% and 17% and sucrose content near 13%, for energy generation and sugar production, the genotypes EECAC 06, EECAC 03, EECAC 04 and EECAC 07 are presented as commercial cultivation options. Highlights - Mixed models constitute an efficient tool for sugarcane selection focused onto fiber and sucrose production. - This methodology provides significant genetic gains based on predicted genetic values free from interaction with harvest cycles. - The evaluated genotypes present high fiber and sucrose productivity, genotypic adaptability and stability throughout harvest cycles, indicating longevity in the sugarcane crop.

Global Bounds for the Generalized Jensen Functional with Applications

In this article we give sharp global bounds for the generalized Jensen functional Jn(g,h;p,x). In particular, exact bounds are determined for the generalized power mean in terms from the class of Stolarsky means. As a consequence, we obtain the best possible global converses of quotients and differences of the generalized arithmetic, geometric and harmonic means.

Considerations for Performance Metrics of Metagenomic Next Generation Sequencing Analyses

Background: Evaluating the performance of metagenomics analyses has proven a challenge, due in part to limited ground-truth standards, broad application space, and numerous evaluation methods and metrics. Application of traditional clinical performance metrics (i.e. sensitivity, specificity, etc.) using taxonomic classifiers do not fit the “one-bug-one-test” paradigm. Ultimately, users need methods that evaluate fitness-for-purpose and identify their analyses’ strengths and weaknesses. Within a defined cohort, reporting performance metrics by taxon, rather than by sample, will clarify this evaluation.Results: For a complete assessment, estimated limits of detection, positive and negative control samples, and true positive and negative true results are necessary criteria for all investigated taxa. Use of summary metrics should be restricted to comparing results of similar, or ideally the same, cohorts and data, and should employ harmonic means and continuous products for each performance metric rather than arithmetic mean. Conclusions: Organism-centric analysis and reporting will enable clear performance assessment and meaningful comparisons between methods in evaluating fitness for purpose of metagenomic analyses with their intended applications.

Cyclic abundance fluctuations in a completely isolated population of Euphydryas maturna

A highly isolated and the last autochthonous Czech Republic population of the endangered Euphydryas maturna (Lepidoptera: Nymphalidae) is monitored since 2001 by larval nests counts. The 20 years` time series displays remarkable abundance fluctuations with peak-to-peak period 11 years, peak numbers >150 and bust numbers <15 larval nests (arithmetic and harmonic means: 92.6 and 36.3). Establishment of more favourable management of the site probably heightened and prolonged the boom phase but did not alter the overall pattern. We attribute the cycling to pressures of natural enemies. Climatically unfavourable years appear deepening the bust phase. Species displaying such fluctuations cannot be conserved within a single site, which is being addressed by ex-situ breeding of the Czech stock and recent reestablishment of two additional populations, with the aim to achieve asynchronous dynamics of the local populations and eventually stabilise the regional metapopulation.

Mean value estimates of gcd and lcm-sums

We study the distribution of the generalized gcd and lcm functions on average. The generalized gcd function, denoted by [Formula: see text], is the greatest [Formula: see text]th power divisor common to [Formula: see text] and [Formula: see text]. Likewise, the generalized lcm function, denoted by [Formula: see text], is the smallest [Formula: see text]th power multiple common to [Formula: see text] and [Formula: see text]. We derive asymptotic formulas for the average order of the arithmetic, geometric, and harmonic means of [Formula: see text]. Additionally, we also deduce asymptotic formulas with error terms for the means of [Formula: see text], and [Formula: see text] over a set of lattice points, thereby generalizing some of the previous work on gcd and lcm-sum estimates.

Factors of uneven progress of the European Union countries towards a circular economy

The increased final consumption exacerbates the problem of the scarcity of natural resources and leads to environmental pollution. The concept of circular economy, which implies the formation of closed-loop chains of production and consumption with maximum regeneration and recycling of materials, is considered as an alternative to the firmly established “linear economy” (take-make-dispose). As a part of sustainable development strategy, the European Union adopted a general policy on the transition to a circular economy. However, for objective reasons, such transition is quite uneven at the level of member countries, which adversely affects the total progress. Therefore, the need arises to assess the positions of individual countries and identify major reasons for the uneven transition to support the countries that are lagging.The goal of the study is to identify the factors of uneven progress of the EU countries towards a circular economy. For that reason, a set of empirical data (20 indicators) has been compiled; cluster, classification, and parametric analyses have been conducted. As a result, three clusters of the EU countries have been obtained and six indicators, included into combinations that make all clusters different, have been identified. These indicators can be interpreted as the key factors contributing to the uneven progress of the EU countries towards a circular economy. The difference in harmonic means by clusters allowed quantitatively estimating a “circular gap”. It is of practical value for the EU policy aimed at bridging the gaps between member countries during the transition to a circular economy.

Geometric and harmonic means based priority dispatching rules for single machine scheduling problems

<span lang="ES">This work proposes two new prority dispatching rules (PDRs) for solving single machine scheduling problems. These rules are based on the geometric mean (GM) and harmonic mean (HM) of the processing time (PT) and the due date (DD) and they are referred to as GMPD and HMPD respectively. Performance of the proposed PDRs is evaluated on the basis of five measures/criteria i.e. Total Flow Time (TFT), Total Lateness (TL), Number of Late Jobs (TNL), Total Earliness (TE) and Number of Early Parts (TNE). It is found that GMPD performs better than other PDRs in achieving optimal values of multiple performance measures. Further, effect of variation in the weight assigned to PT and DD on the combined performance of TFT and TL is also examined which reveals that for deriving optimal values of TFT and TL, weighted harmonic mean (WHMPD) rule with a weight of 0.105 outperforms other PDRs. The weighted geometric mean (WGMPD) rule with a weight of 0.37 is found to be the next after WHMPD followed by the weighted PDT i.e. WPDT rule with a weight of 0.76.</span>