scholarly journals The Generalized STAR Modelling with Minimum Spanning Tree Approach of Weight Matrix for COVID-19 Case in Java Island

2021 ◽  
Vol 2084 (1) ◽  
pp. 012003
Author(s):  
Utriweni Mukhaiyar ◽  
Bayu Imadul Bilad ◽  
Udjianna Sekteria Pasaribu
Keyword(s):  
Spanning Tree ◽  
Large Scale ◽  
Minimum Spanning Tree ◽  
Weight Matrix ◽  
Average Score ◽  
New Approach ◽  
Central Java ◽  
Good Ability ◽  
The Relationship ◽  
Inverse Distance

Abstract The ongoing global Coronavirus 2019 (COVID-19) pandemic poses a major threat. The spread of the COVID-19 virus is likely to occur from one location to another location due to the mobility of people. Many efforts and policies have been made by each country to reduce the spread of the COVID-19 outbreak. The imposition of lockdown and large-scale social restrictions or social distancing has been widely applied to limit the transmission of this virus among the community and provincial levels. Both policies have proven effective in reducing the spread of the COVID-19 virus. To obtain the overview of this case, many researchers were conducted. Here, the Generalized STAR (GSTAR) model was applied to model the increasing number of COVID-19 positive cases per day in six provinces in Java Island. The data was recorded simultaneously in six locations, namely in the Provinces of Banten, Jakarta, West Java, Central Java, Yogyakarta Special Region, and East Java. This paper proposes a new approach in constructing the weight matrix required to build the GSTAR model, namely Minimum Spanning Tree (MST). The weight matrix represents the relationship among observed locations. By using the MST, a topological (undirected graph) network model could be created to show the correlation, centrality, and relationship on the increase of COVID-19 positive cases among the provinces in Java Island. The GSTAR(1;1) with the inverse distance weight matrix using MST presents a good ability to predict the COVID-19 increasing cases of Java island. This is indicated by the final MAPE average score of 19.55.

scholarly journals Beyond two-point statistics: using the minimum spanning tree as a tool for cosmology

2019 ◽  
Vol 491 (2) ◽  
pp. 1709-1726 ◽  
Author(s):  
Krishna Naidoo ◽  
Lorne Whiteway ◽  
Elena Massara ◽  
Davide Gualdi ◽  
Ofer Lahav ◽  
...  
Keyword(s):  
Spanning Tree ◽  
Large Scale ◽  
Minimum Spanning Tree ◽  
Cosmological Parameters ◽  
Skeletal Structure ◽  
Additional Information ◽  
The Rich ◽  
Unique Graph ◽  
The Individual ◽  
First Time

ABSTRACT Cosmological studies of large-scale structure have relied on two-point statistics, not fully exploiting the rich structure of the cosmic web. In this paper we show how to capture some of this cosmic web information by using the minimum spanning tree (MST), for the first time using it to estimate cosmological parameters in simulations. Discrete tracers of dark matter such as galaxies, N-body particles or haloes are used as nodes to construct a unique graph, the MST, that traces skeletal structure. We study the dependence of the MST on cosmological parameters using haloes from a suite of COmoving Lagrangian Acceleration (COLA) simulations with a box size of $250\ h^{-1}\, {\rm Mpc}$, varying the amplitude of scalar fluctuations (As), matter density (Ωm), and neutrino mass (∑mν). The power spectrum P and bispectrum B are measured for wavenumbers between 0.125 and 0.5 $h\, {\rm Mpc}^{-1}$, while a corresponding lower cut of ∼12.6 $h^{-1}\, {\rm Mpc}$ is applied to the MST. The constraints from the individual methods are fairly similar but when combined we see improved 1σ constraints of $\sim 17{{\ \rm per\ cent}}$ ($\sim 12{{\ \rm per\ cent}}$) on Ωm and $\sim 12{{\ \rm per\ cent}}$ ($\sim 10{{\ \rm per\ cent}}$) on As with respect to P (P + B) thus showing the MST is providing additional information. The MST can be applied to current and future spectroscopic surveys (BOSS, DESI, Euclid, PSF, WFIRST, and 4MOST) in 3D and photometric surveys (DES and LSST) in tomographic shells to constrain parameters and/or test systematics.

New Approach to Portfolio Creation Using the Minimum Spanning Tree Theory and Its Robust Evaluation

2020 ◽  
Vol 24 (2) ◽  
pp. 22
Author(s):  
Jakub Danko ◽  
Vincent Šoltés ◽  
Tomáš Bindzár
Keyword(s):  
Spanning Tree ◽  
Minimum Spanning Tree ◽  
Investment Strategy ◽  
Point Of View ◽  
Equal Weight ◽  
Individual Investor ◽  
New Approach ◽  
Active Approach ◽  
Risky Investment ◽  
One Year

<p><strong>Purpose:</strong> The aim of this paper is to describe another possibility of portfolio creation using the minimum spanning tree method. The research contributes to the existing body of knowledge with using and subsequently developing a new approach based on graph theory, which is suitable for an individual investor who wants to create an investment portfolio.</p><p><strong>Methodology/Approach:</strong> The analyzed data is divided into two (disjoint) sets – a training and a testing set. Portfolio comparisons were carried out during the test period, which always followed immediately after the training period and had a length of one year. For the sake of objectivity of the comparison, all proposed portfolios always consist of ten shares of equal weight.</p><p><strong>Findings:</strong> Based on the results from the analysis, we can see that our proposed method offers (on average) the best appreciation of the invested resources and also the least risky investment in terms of relative variability, what could be considered as very attractive from an individual investor’s point of view.</p><p><strong>Research Limitation/implication:</strong> In our paper, we did not consider any fees related to the purchase and holding of financial instruments in the portfolio. For periods with extreme market returns (sharp increase or decrease), the use of Pearson’s correlation coefficient is not appropriate.</p><strong>Originality/Value of paper:</strong> The main practical benefit of the research is that it presents and offers an interesting and practical investment strategy for an individual investor who wants to take an active approach to investment.

Research on Routing Protocol for Large-Scale Wireless Sensor Networks

2014 ◽  
Vol 511-512 ◽  
pp. 146-149
Author(s):  
Kai Zhang ◽  
Min Jin
Keyword(s):  
Wireless Sensor Networks ◽  
Routing Protocol ◽  
Spanning Tree ◽  
Large Scale ◽  
Minimum Spanning Tree ◽  
Cluster Head ◽  
Wireless Sensor ◽  
Cluster Heads ◽  
Application Characteristics ◽  
The One

Aimed at the application characteristics of the large-scale WSN, a new clustering routing protocol LEACH_CHMST is proposed in this paper. The multi-hop strategy for cluster-heads communication has been introduced instead of the one-hop strategy in LEACH, and a minimum spanning tree of cluster-head is established, in which the routes from all cluster-heads to sink are found.

scholarly journals The Use of Weighted Adjacency Matrix for Searching Optimal Transportation Routes

2018 ◽  
Author(s):  
Karel Antoš
Keyword(s):  
Graph Theory ◽  
Adjacency Matrix ◽  
Spanning Tree ◽  
Minimum Spanning Tree ◽  
Optimal Transportation ◽  
New Approach ◽  
New Variant ◽  
Transportation Routes ◽  
Weighted Adjacency Matrix

This article provides a new approach to searching solutions of the ship transport optimalization problems. It brings a new variant of one algorithm of searching for the Minimum Spanning Tree. The new element in the algorithm is that it uses the Weighted Adjacency Matrix. This Weighted Adjacency Matrix is suitable for searching for the Minimum Spanning Tree (MST) of the graph. It shows how it could be used in cases where weighted edges of the graph are given. This creates a new procedure of searching for the MST of the graph and completes previously known algorithms of searching for the MST. In the field of transportation it could be succesfully used for solutions of optimizing transportation routes where smallest costs are wanted. Proposed Weighted Adjacency Matrix could be used in similar issues in the field of the graph theory, where graphs with weighted edges are given. The procedure is shown on the attached example.

scholarly journals Large-scale star formation in Auriga region

2019 ◽  
Vol 492 (2) ◽  
pp. 2446-2467 ◽  
Author(s):  
A K Pandey ◽  
Saurabh Sharma ◽  
N Kobayashi ◽  
Y Sarugaku ◽  
K Ogura
Keyword(s):  
Star Formation ◽  
Spanning Tree ◽  
Large Scale ◽  
Minimum Spanning Tree ◽  
Young Stellar Objects ◽  
Molecular Gas ◽  
Archival Data ◽  
Stellar Objects ◽  
Tree Analysis ◽  
Formation Efficiency

ABSTRACT New observations in the VI bands along with archival data from the 2MASS and WISE surveys have been used to generate a catalogue of young stellar objects (YSOs) covering an area of about 6° × 6° in the Auriga region centred at l ∼ 173° and b ∼ 1.5°. The nature of the identified YSOs and their spatial distribution are used to study the star formation in the region. The distribution of YSOs along with that of the ionized and molecular gas reveals two ring-like structures stretching over an area of a few degrees each in extent. We name these structures as Auriga Bubbles 1 and 2. The centre of the Bubbles appears to be above the Galactic mid-plane. The majority of Class I YSOs are associated with the Bubbles, whereas the relatively older population, i.e. Class ii objects are rather randomly distributed. Using the minimum spanning tree analysis, we found 26 probable subclusters having five or more members. The subclusters are between ∼0.5 and ∼3 pc in size and are somewhat elongated. The star formation efficiency in most of the subcluster region varies between 5 ${{\ \rm per\ cent}}$ and 20 ${{\ \rm per\ cent}}$ indicating that the subclusters could be bound regions. The radii of these subclusters also support it.

scholarly journals Parallel Regional Segmentation Method of High-Resolution Remote Sensing Image Based on Minimum Spanning Tree

2020 ◽  
Vol 12 (5) ◽  
pp. 783 ◽  
Author(s):  
Wenjie Lin ◽  
Yu Li
Keyword(s):  
Remote Sensing ◽  
Parallel Processing ◽  
High Resolution ◽  
Spanning Tree ◽  
Large Scale ◽  
Minimum Spanning Tree ◽  
Process Efficiency ◽  
Qualitative Assessment ◽  
Segmentation Method ◽  
High Resolution Images

With finer spatial scale, high-resolution images provide complex, spatial, and massive information on the earth’s surface, which brings new challenges to remote sensing segmentation methods. In view of these challenges, finding a more effective segmentation model and parallel processing method is crucial to improve the segmentation accuracy and process efficiency of large-scale high-resolution images. To this end, this study proposed a minimum spanning tree (MST) model integrated into a regional-based parallel segmentation method. First, an image was decomposed into several blocks by regular tessellation. The corresponding homogeneous regions were obtained using the minimum heterogeneity rule (MHR) partitioning technique in a multicore parallel processing mode, and the initial segmentation results were obtained by the parallel block merging method. On this basis, a regionalized fuzzy c-means (FCM) method based on master-slave parallel mode was proposed to achieve fast and optimal segmentation. The proposed segmentation approach was tested on high-resolution images. The results from the qualitative assessment, quantitative evaluation, and parallel analysis verified the feasibility and validity of the proposed method.

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