19,959 research outputs found
Network analysis of correlation strength between the most developed countries
A new algorithm of the analysis of correlation among economy time series is
proposed. The algorithm is based on the power law classification scheme (PLCS)
followed by the analysis of the network on the percolation threshold (NPT). The
algorithm was applied to the analysis of correlations among GDP per capita time
series of 19 most developed countries in the periods (1982, 2011), (1992, 2011)
and (2002, 2011). The representative countries with respect to strength of
correlation, convergence of time series and stability of correlation are
distinguished. The results are compared with ultrametric distance matrix
analysed by NPT.Comment: submitted to Acta Physica Polonica
Improved sorting networks with O(log n) depth
The sorting network described by Ajtai, KomlOs and Szemeredi was the first to achieve a depth of O(Iog n). The networks introduced here are simplifications and improvements based strongly on their work. While the constants obtained for the depth bound still prevent the construction being of practical value, the structure of the presentation offers a convenient basis for further development
An Enhanced Multiway Sorting Network Based on n-Sorters
Merging-based sorting networks are an important family of sorting networks.
Most merge sorting networks are based on 2-way or multi-way merging algorithms
using 2-sorters as basic building blocks. An alternative is to use n-sorters,
instead of 2-sorters, as the basic building blocks so as to greatly reduce the
number of sorters as well as the latency. Based on a modified Leighton's
columnsort algorithm, an n-way merging algorithm, referred to as SS-Mk, that
uses n-sorters as basic building blocks was proposed. In this work, we first
propose a new multiway merging algorithm with n-sorters as basic building
blocks that merges n sorted lists of m values each in 1 + ceil(m/2) stages (n
<= m). Based on our merging algorithm, we also propose a sorting algorithm,
which requires O(N log2 N) basic sorters to sort N inputs. While the asymptotic
complexity (in terms of the required number of sorters) of our sorting
algorithm is the same as the SS-Mk, for wide ranges of N, our algorithm
requires fewer sorters than the SS-Mk. Finally, we consider a binary sorting
network, where the basic sorter is implemented in threshold logic and scales
linearly with the number of inputs, and compare the complexity in terms of the
required number of gates. For wide ranges of N, our algorithm requires fewer
gates than the SS-Mk.Comment: 13 pages, 14 figure
Environmental, human health and socio-economic effects of cement powders: The multicriteria analysis as decisional methodology
The attention to sustainability-related issues has grown fast in recent decades. The experience gained with these themes reveals the importance of considering this topic in the construction industry, which represents an important sector throughout the world. This work consists on conducting a multicriteria analysis of four cement powders, with the objective of calculating and analysing the environmental, human health and socio-economic effects of their production processes. The economic, technical, environmental and safety performances of the examined powders result from official, both internal and public, documents prepared by the producers. The Analytic Hierarchy Process permitted to consider several indicators (i.e., environmental, human health related and socio-economic parameters) and to conduct comprehensive and unbiased analyses which gave the best, most sustainable cement powder. As assumed in this study, the contribution of each considered parameter to the overall sustainability has a different incidence, therefore the procedure could be used to support on-going sustainability efforts under different conditions. The results also prove that it is not appropriate to regard only one parameter to identify the ‘best’ cement powder, but several impact categories should be considered and analysed if there is an interest for pursuing different, often conflicting interests
Modeling and Optimal Design of Machining-Induced Residual Stresses in Aluminium Alloys Using a Fast Hierarchical Multiobjective Optimization Algorithm
The residual stresses induced during shaping and machining play an important role in determining the integrity and durability of metal components. An important issue of producing safety critical components is to find the machining parameters that create compressive surface stresses or minimise tensile surface stresses. In this paper, a systematic data-driven fuzzy modelling methodology is proposed, which allows constructing transparent fuzzy models considering both accuracy and interpretability attributes of fuzzy systems. The new method employs a hierarchical optimisation structure to improve the modelling efficiency, where two learning mechanisms cooperate together: NSGA-II is used to improve the model’s structure while the gradient descent method is used to optimise the numerical parameters. This hybrid approach is then successfully applied to the problem that concerns the prediction of machining induced residual stresses in aerospace aluminium alloys. Based on the developed reliable prediction models, NSGA-II is further applied to the multi-objective optimal design of aluminium alloys in a ‘reverse-engineering’ fashion. It is revealed that the optimal machining regimes to minimise the residual stress and the machining cost simultaneously can be successfully located
Renormalization group flows of Hamiltonians using tensor networks
A renormalization group flow of Hamiltonians for two-dimensional classical
partition functions is constructed using tensor networks. Similar to tensor
network renormalization ([G. Evenbly and G. Vidal, Phys. Rev. Lett. 115, 180405
(2015)], [S. Yang, Z.-C. Gu, and X.-G Wen, Phys. Rev. Lett. 118, 110504
(2017)]) we obtain approximate fixed point tensor networks at criticality. Our
formalism however preserves positivity of the tensors at every step and hence
yields an interpretation in terms of Hamiltonian flows. We emphasize that the
key difference between tensor network approaches and Kadanoff's spin blocking
method can be understood in terms of a change of local basis at every
decimation step, a property which is crucial to overcome the area law of mutual
information. We derive algebraic relations for fixed point tensors, calculate
critical exponents, and benchmark our method on the Ising model and the
six-vertex model.Comment: accepted version for Phys. Rev. Lett, main text: 5 pages, 3 figures,
appendices: 9 pages, 1 figur
Sign and amplitude representation of the forex networks
We decompose the exchange rates returns of 41 currencies (incl. gold) into
their sign and amplitude components. Then we group together all exchange rates
with a common base currency, construct Minimal Spanning Trees for each group
independently, and analyze properties of these trees. We show that both the
sign and the amplitude time series have similar correlation properties as far
as the core network structure is concerned. There exist however interesting
peripheral differences that may open a new perspective to view the Forex
dynamics.Comment: Article based on talk by S. Gworek given at FENS'08 Conference,
Rzeszow, Polan
A Decision Making Framework for Reverse Logistics Network Design
The main objective of this research is to answer the following research question “How should a company design their reverse logistics network in a more efficient or responsive way?”
In this research, a conceptual framework has been developed based on several key factors for network design. Through the analysis of each key factor affecting network design decision, we have built a conceptual framework for reverse logistics network for companies to decide on whether to centralize versus decentralize their reverse logistics operations, and whether to outsource or insource some of their operations? Some existing studies are able to fit well in our proposed framework, giving us better insights to decision making in reverse logistics network design.
The proposed conceptual framework is helpful for the companies or organizations to make better decisions when designing their reverse logistics operations to achieve a lean or responsive network
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