Minimum Spanning Tree Research Articles

Online distributed waveform-synchronization for acoustic sensor networks with dynamic topology

Acoustic sensing by multiple devices connected in a wireless acoustic sensor network (WASN) creates new opportunities for multichannel signal processing. However, the autonomy of agents in such a network still necessitates the alignment of sensor signals to a common sampling rate. It has been demonstrated that waveform-based estimation of sampling rate offset (SRO) between any node pair can be retrieved from asynchronous signals already exchanged in the network, but connected online operation for network-wide distributed sampling-time synchronization still presents an open research task. This is especially true if the WASN experiences topology changes due to failure or appearance of nodes or connections. In this work, we rely on an online waveform-based closed-loop SRO estimation and compensation unit for nodes pairs. For WASNs hierarchically organized as a directed minimum spanning tree (MST), it is then shown how local synchronization propagates network-wide from the root node to the leaves. Moreover, we propose a network protocol for sustaining an existing network-wide synchronization in case of local topology changes. In doing so, the dynamic WASN maintains the MST topology after reorganization to support continued operation with minimum node distances. Experimental evaluation in a simulated apartment with several rooms proves the ability of our methods to reach and sustain accurate SRO estimation and compensation in dynamic WASNs.

Using Trust Measures to Optimize Neighbor Selection for Smart Blockchain Networks in IoT

The blockchain paradigm is currently modifying all the major Internet of Things (IoT) application domains, giving the opportunity of constructing decentralized environments in which trustful and anonymous activities can be efficiently performed. Blockchain proposes an approach which assures data saved on a distributed ledger would be continuously synchronized and in such a way the ledger will remain consistent. The distributed ledger has the responsibility to maintain a higher level of consistency. Given a connected network, the Optimum Neighbor Selection (ONS) of paths can be obtained by finding the Minimum Spanning Tree of the network. However, none of past approaches proposed in the literature to construct ONS considered the problem of having nodes with low levels of reliability in the network and even malicious or fraudulent nodes, that is a situation very common in an IoT environment. In this paper, we propose an optimized blockchain ONS algorithm, called Trust-based ONS (TONS), which allows the miners to communicate with a globally-optimized selection of neighbors. The algorithm can also guarantee that these nodes are the most reliable miners. We also describe an experimental simulation campaign we have performed to evaluate the effectiveness and the efficiency of our approach.

How does urban heat island differ across urban functional zones? Insights from 2D/3D urban morphology using geospatial big data

The deteriorating urban thermal environment poses a huge impediment to sustainable urban development, which is closely related to the urban morphology under different urban functional zones (UFZs). By integrating remote sensing and geospatial big data, this work aims to reveal the divergent mechanism behind Urban Heat Island (UHI) across UFZs taking insights from 2D/3D urban morphology. The Minimum Spanning Tree (MST) indicator depicting 3D building distribution was introduced and integrated with the classic indicators. Their impacts on UHI were measured by ensemble learning and SHapley Additive exPlanations (SHAP) model. Taking Wuhan as the study area, the eighteen 2D/3D urban morphology indicators affecting UHI in different locations and UFZs were extensively examined and compared. The results reveal that: 1) The impact of 2D/3D urban morphology indicators on UHI significantly varies across different UFZs, with dominance in transportation zones exhibiting opposite polarity compared to the other types; 2) positive impacts have a decreasing trend from the urban center to the edge, while negative impacts exhibit opposite trend; 3) XGBoost outperforms other classic methods in interpreting the impact of urban morphology on UHI for all UFZ types. The findings improving knowledge of UHI across UFZs will provide a practical guide for urban planning.

Minimum spanning tree analysis for epilepsy magnetoencephalography (MEG) data

Aim: Recently, brain network research is actively conducted through the application of graph theory. However, comparison between brain networks is subject to bias issues due to topological characteristics and heterogeneity across subjects. The minimum spanning tree (MST) is a method that is increasingly applied to overcome the thresholding problem. In this study, the aim is to use the MST analysis in comparing epilepsy patients and controls to find the differences between groups. Methods: The MST combines entities for epileptic magnetoencephalography (MEG) data. The MST was applied and compared to 21 left surgery (LT) and 21 right surgery (RT) patients with epilepsy and good postoperative prognosis and a healthy control (HC) group. MST metrics such as betweenness centrality, eccentricity, diameter, and leaf fraction, are computed and compared to describe the integration and efficiency of the network. The MST analysis is applied to each subject, and then the integrated MST is obtained using the distance concept. This approach can be advantageous when comparing the topological structure of patients to controls with the same number of nodes. Results: The HC group showed less topological change and more network efficiency than the epilepsy LT and RT groups. In addition, the posterior cingulate gyrus was found as a hub node only in the patient group in individual and integrated subject data analysis. Conclusions: This study suggests propose that the hippocampus borrows from the default network when one side fails, compensating for the weakened function.

Linear time manageable edge-aware filtering on complementary tree structures

Typical non-local edge-aware filtering methods build long-range connections by deriving a minimum spanning tree (MST) from the input image. Each pixel on the MST only connects to a sub-set of pixels in the 8-connected neighborhood, resulting in piece-wise constant output with fake edges among sub-trees for the unbalanced information propagation along eight directions. In this paper, we propose two complementary spatial trees to incorporate information from the entire image. The structure of each tree depends on the spatial relationships of neighboring pixels. The distances between any two pixels in both spatial space and intensity space are the shortest distances on each tree. We introduce an efficient algorithm to recursively compute the output and the normalization constant on each tree with linear time complexity. For each pixel, we first calculate the outputs from eight subtrees and then fuse them to obtain the result on each tree structure. The final filtering output of our method is the weighted average of the results from two complementary spatial trees. Moreover, we present a distance mapping scheme to adjust the intensity distance between neighboring pixels, enabling our method to filter out a manageable degree of low-amplitude structures while sharpening major edges. Extensive experiments in graphic applications, such as image denoising, JPEG artifact removal, tone mapping, detail enhancement, and colorization, demonstrate the effectiveness and versatility of our method.

Impact assessment of unsustainable airport development in the Himalayas using remote sensing: A case study of Pakyong Airport, Sikkim, India

Ground deformation is a widespread phenomenon that accelerates due to anthropogenic land development. Thus reclaimed/created land is more vulnerable to deformation and subsidence, especially in mountain areas. Advanced Differential Synthetic Aperture Radar Interferometry (A-DInSAR) can be used to monitor such projects. The Pakyong Airport is an engineering feat, constructed by cutting a mountain and converting it into a tabletop in a landslide-prone zone and seismically active region of the Sikkim Himalayas. The cutting of hill slopes for airport construction and other anthropogenic activities has increased slope instability in the region. This paper studies the slow-moving landslides in the airport neighbourhood using A-DInSAR on Sentinel-1 time series data consisting of 64 images of ascending track and 82 images of the descending track. The time period of monitoring was from October 2014 to April 2018 (43 months). The images have been connected using the Minimum Spanning Tree graph for interferogram generation for estimating deformation. The atmospheric noise was removed, and the results enabled the identification of deformation (in line-of-sight) on the airstrip as well as in the neighbouring area, both the upslope and downslope of the airport. The deformation rates estimated were up to ±90 mm/year in Pakyong from both tracks. We could successfully capture such land movement associated with the Pakyong Airport construction and help assess the impacts of infrastructure construction on the slope stability of the area. The controlling factors such as precipitation, seismicity, geology and others were analysed with respect to the deformation obtained. This study helps in assessing the land deformation after construction (cutting and filling of the slope) in the area. The deformation detected in this study needs to be addressed for the safety of the residents as well as for the infrastructure present in the area.

Innovative method to solve the minimum spanning tree problem: The Dhouib-Matrix-MSTP (DM-MSTP)

The Minimum Spanning Tree problem aims to create a subset of a graph where all the vertices are connected with the minimum edge weights and with no cycle. In this field, an innovative method entitled Dhouib-Matrix-MSTP (DM-MSTP) is designed in this research work with a time complexity independently of the number of edges O(n*log(n)) where n is the number of vertices. DM-MSTP is a constructive algorithm based on a matrix navigation with two new lists (Min-Columns and MST-Path) in order to organize the steering flow. DM-MSTP is composed of four simple steps where the first and the fourth steps are repeated only once, whereas the second and third are reiterated (n-1). For more clarification, a step-by-step application of the proposed method is presented in details. Besides, the performance of DM-MSTP is proved through different examples from the literature including a graph with negative weighted edges and complete graphs from TSP-LIB. Moreover, with a simple modification (Min by Max) the DM-MSTP is tested on the Maximum (Largest) Spanning Tree Problem. Also, DM-MSTP is applied on eight case studies and compared to six methods developed in the literature. All these experimental results in the above different environments show that DM-MSTP can rapidly plan the shortest spanning tree with a stable performance and convivial representation of the optimal tree. Hence, DM-MSTP is developed under Python programming language using Matplotlib and Numpy standard libraries.

THREE-DIMENSIONAL MODELING OF SHRUBS BASED ON LIDAR POINT CLOUDS

Abstract. This paper proposes a method for constructing 3D models of shrubs with high accuracy from 3D point clouds acquired by terrestrial laser scanning (TLS). Since the shrub point cloud obtained by LiDAR scanning contains a large amount of redundant data, the focus of this method is to segment the branches and leaves of the shrub point cloud first, which can remove the noise and make the branch skeleton of the shrub stand out. Secondly, a triangulation network is constructed for the segmented branch points, and a minimum spanning tree (MST) is established from the triangulation network as the initial shrub skeleton of the input point cloud. Then, the redundant branches are removed by merging adjacent points and edges to simplify the initial skeleton. Finally, the 3D model of a shrub is constructed by a cylindrical fitting algorithm based on robust principal component analysis (RPCA). Experiments on different types of shrubs from different data sources demonstrate the effectiveness and robustness of the proposed method. The 3D models of shrubs can be further applied to the accurate estimation of shrub attributes and urban landscape visualization.

Reorganization of functional brain networks in healthy aging and mild cognitive impairment during the visual motion discrimination task

AbstractBackgroundPreviously, we reported that there was significant decrease in spectral power for eyes‐closed resting state EEG (rsEEG) immediately following a visual motion discrimination task as compared to before task engagement in older adults – the so‐called Task Aftereffect (TA). Further, we have also shown that rsEEG TA differentiated between older adults with mild cognitive impairment (MCI) and healthy controls (HC), with the MCI participants showing more integrated topology in post‐ as compared to pre‐cognitive task rsEEG. We now report EEG topological changes during task performance with regards to: changes in functional network organization from the beginning to the end of the task and evidence for significant differences in topology between MCI patients and HC.MethodWe studied a sample of community dwelling African American older participants over age 60 years, with consensus‐based diagnosis for 51 HC and 39 MCI. EEG epochs extracted for analysis were two‐second epochs before the motion onset of each stimulus at the beginning, middle, and end of the full task. Functional connectivity between channels was assessed by the phase lag index. Minimum spanning tree (MST) was used to characterize network topology.ResultTime effect was confirmed, as network organization in all participants significantly improved with task progression. On average, brain topology became more integrated with higher leaf fraction and smaller average eccentricity. Moreover, our results show differences between groups in MST parameters over the whole task. Most differences were observed at the earliest timepoint at lower frequency range (theta and lower alpha) where average eccentricity was significantly decreased. Leaf fraction and maximal betweenness centrality were significantly increased in the MCI group as compared to HC.ConclusionThe change in network organization suggests that MCI require greater network integration across brain areas before repeated motion onset presentations. This could reflect compensatory brain mechanisms, especially as both groups did not show significant differences in task performance. These findings enhance our understanding of the functional brain network organization immediately prior to repeated responses in a visual perceptual task in MCI compared to HC. This emphasizes the potential for using graph‐theoretic measures as a valid tool for the early detection of cognitive impairment.

Monetary Policy and Crisis Contagion to the Stock Market: an Application of Minimum Spanning Tree (MST)

Monetary Policy and Crisis Contagion to the Stock Market: an Application of Minimum Spanning Tree (MST)

Carbapenemase genes distribution in clonal lineages of Acinetobacter baumannii: a comprehensive study on plasmids and chromosomes.

The global spread of plasmids carrying carbapenemase genes within carbapenem resistant Acinetobacter baumannii (CRAB) strains poses a worldwide public health issue. In this study, we conducted a comprehensive genetic analysis of plasmids and chromosomes harboring the major carbapenemase genes (bla NDM, bla KPC, bla VIM, bla IMP, bla GES, bla OXA-58-like, bla OXA-24/40-like, bla OXA-143-like, and bla OXA-23-like) in CRAB strains using bioinformatic tools. We retrieved plasmids and chromosomes carrying the major carbapenemase genes from GenBank. The size, replicon type, and conjugal apparatus of the plasmids were also determined. Furthermore, allele types, co-existence of other antimicrobial resistance genes alongside carbapenemases in plasmids or chromosomes, co-occurrence of carbapenemase genes, gene repetition, and sequence types (ST) of whole genomes were characterized. The database contained 113 plasmids and 38 chromosomes harboring carbapenemase genes. This investigation revealed that bla NDM and bla OXA-58-like were the predominant allele types in both the plasmids and chromosomes. Nine (7.96%) plasmids with bla NDM-1 were potentially conjugative. The most common replicon types of the plasmids were R3-T1, R3-T8, R3-T2, R3-T23, and RP-T1. The analysis revealed that bla NDM-1 and bla OXA-58-like genes possessed the highest variety of co-existence with other antibiotic resistance genes. The co-occurrence of dual carbapenemases was identified in 12 plasmids and 19 chromosomes. Carbapenemase gene repetitions were identified in 10 plasmids and one chromosome. Circular alignment revealed that the plasmids carrying the co-occurrence of bla NDM-1 and bla OXA-58 were more homogeneous. However, there was heterogeneity in certain regions of these plasmids. According to the minimum spanning tree (MST) results, the majority of the plasmids belonged to the genomes of ST2Pas, ST1Pas, ST422Pas, ST622Pas, and ST85Pas. A. baumannii appears to have a strong ability for genome plasticity to incorporate carbapenemase genes on its plasmids and chromosomes to develop resistance against carbapenems. Mobilizable plasmids harboring carbapenemases significantly contribute to the dissemination of these genes. The genetic structure of the plasmids revealed a strong associations of class I integrons, ISAba-like structures, Tn4401 elements, and aac (6')-Ib with carbapenemases. Furthermore, gene repetition may also be associated with carbapenem heteroresistance.

Molecular epidemiology and antimicrobial resistance patterns of carbapenem-resistant Acinetobacter baumannii isolates from patients admitted at ICUs of a teaching hospital in Zunyi, China.

Carbapenem-resistant Acinetobacter baumannii (CRAB) has emerged as a predominant strain of healthcare-associated infections worldwide, particularly in intensive care units (ICUs). Therefore, it is imperative to study the molecular epidemiology of CRAB in the ICUs using multiple molecular typing methods to lay the foundation for the development of infection prevention and control strategies. This study aimed to determine the antimicrobial susceptibility profile, the molecular epidemiology and conduct homology analysis on CRAB strains isolated from ICUs. The sensitivity to various antimicrobials was determined using the minimum inhibitory concentration (MIC) method, Kirby-Bauer disk diffusion (KBDD), and E-test assays. Resistance genes were identified by polymerase chain reaction (PCR). Molecular typing was performed using multilocus sequence typing (MLST) and multiple-locus variable-number tandem repeat analysis (MLVA). Among the 79 isolates collected, they exhibited high resistance tovarious antimicrobials but showed low resistance to levofloxacin, trimethoprim-sulfamethoxazole, and tetracyclines. Notably, all isolates of A. baumannii were identified as multidrug-resistant A. baumannii (MDR-AB). The bla OXA-51-like, adeJ, and adeG genes were all detected, while the detection rates of bla OXA-23-like (97.5%), adeB (93.67%), bla ADC (93.67%), qacEΔ1-sul1 (84.81%) were higher; most of the Ambler class A and class B genes were not detected. MLST analysis on the 79 isolates identified five sequence types (STs), which belonged to group 3 clonal complexes 369. ST1145Ox was the most frequently observed ST with a count of 56 out of 79 isolates (70.89%). MLST analysis for non-sensitive tigecycline isolates, which were revealed ST1145Ox and ST1417Ox as well. By using the MLVA assay, the 79 isolates could be grouped into a total of 64 distinct MTs with eleven clusters identified in them. Minimum spanning tree analysis defined seven different MLVA complexes (MCs) labeled MC1 to MC6 along with twenty singletons. The locus MLVA-AB_2396 demonstrated the highest Simpson's diversity index value at 0.829 among all loci tested in this study while also having one of the highest variety of tandem repeat species. The molecular diversity and clonal affinities within the genomes of the CRAB strains were clearly evident, with the identification of ST1144Ox, ST1658Ox, and ST1646Oxqaq representing novel findings.

Review on greedy algorithm

The greedy algorithm is a commonly used algorithm design idea that can provide efficient solutions to many practical problems. This paper aims to review and summarize the basic ideas, characteristics and application fields of greedy algorithms, and discuss their advantages and limitations. Firstly, the basic concepts of greedy algorithms are introduced, including the greedy selection properties and optimal substructures. Then, some classic greedy algorithms such as the backpack problem, the activity selection problem, and the minimum spanning tree problem are introduced, and the concept of time complexity is introduced. Next, the application of greedy algorithms in practical problems, such as scheduling problems, network routing, and graph generation, will be discussed. Finally, the advantages of the greedy algorithm and the limitation of the inability to obtain the global optimal solution will be evaluated, and the improvement direction combined with other algorithms will be proposed.

On minimum spanning trees for random Euclidean bipartite graphs

AbstractWe consider the minimum spanning tree problem on a weighted complete bipartite graph $K_{n_R, n_B}$ whose $n=n_R+n_B$ vertices are random, i.i.d. uniformly distributed points in the unit cube in $d$ dimensions and edge weights are the $p$ -th power of their Euclidean distance, with $p\gt 0$ . In the large $n$ limit with $n_R/n \to \alpha _R$ and $0\lt \alpha _R\lt 1$ , we show that the maximum vertex degree of the tree grows logarithmically, in contrast with the classical, non-bipartite, case, where a uniform bound holds depending on $d$ only. Despite this difference, for $p\lt d$ , we are able to prove that the total edge costs normalized by the rate $n^{1-p/d}$ converge to a limiting constant that can be represented as a series of integrals, thus extending a classical result of Avram and Bertsimas to the bipartite case and confirming a conjecture of Riva, Caracciolo and Malatesta.

코로나19(COVID-19)를 전후로 한 코스닥(KOSDAQ) 종목들의 수익률 상관관계 변동에 대한 구조적 분석

In this study, the Minimum spanning tree (MST) method was applied to daily price data of KOSDAQ stocks to conduct a structural analysis of changes in each graph and degree based on before and after COVID-19 occurred and at the start of each pandemic. As a result, it was confirmed that the minimum height tree graph and order change were the greatest before and after the outbreak of COVID-19 and at the beginning of the first and second pandemic, and stock market stabilized as of the start of the third pandemic as COVID-19 entered a prolonged period. These results confirmed that the change in the correlation between stocks increased at a time when social turmoil was the biggest, and that the stock market gradually stabilized at some point when the situation caused by social confusion entered a prolonged period.

Minimum spanning tree in analyzing audiovisual integration network: A developmental study

Minimum spanning tree in analyzing audiovisual integration network: A developmental study

Community-based zigzag piloting algorithm for the strong generalized minimum label spanning tree problem

Community-based zigzag piloting algorithm for the strong generalized minimum label spanning tree problem

Decoding the genetic structure of conjugative plasmids in international clones of Klebsiella pneumoniae: A deep dive into blaKPC, blaNDM, blaOXA-48, and blaGES genes

Carbapanem-resistant Klebsiella pneumoniae is a globally healthcare crisis. The distribution of plasmids carrying carbapenemase genes among K. pneumoniae poses a serious threat in clinical settings. Here, we characterized the genetic structure of plasmids harboring major carbapenemases (e.g. blaKPC, blaNDM, blaOXA-48-like, and blaGES) from K. pneumoniae using bioinformatics tools. The plasmids carrying at least one major carbapenemase gene were retrieved from the GenBank database. The DNA length, Inc type, and conjugal apparatus of these plasmids were detected. Additionally, allele types, co-existence, co-occurrence of carbapenemase genes, gene repetition, and sequence types of isolates, were characterized. There were 2254 plasmids harboring carbapenemase genes in the database. This study revealed that blaKPC-2, blaNDM-1, blaOXA-48, and blaGES-5 were the most prevalent allele types. Out of 1140 (50%) plasmids were potentially conjugative. IncFII, IncR, IncX3, and IncL replicon types were predominant. The co-existence analysis revealed that the most prevalent of other resistance genes were blaTEM-1 (related to blaKPC), blaOXA-232 (related to blaOXA-48), bleMBL (related to blaNDM), and aac (6′)-Ib4 (related to blaGES). The co-occurrence of carbapenemases was detected in 42 plasmids while 15 plasmids contained carbapenemase gene repetitions. Sequence alignments highlighted that plasmids carrying blaKPC and blaOXA-48-like were more homogeneous whereas the plasmids carrying blaNDM were divergent. It seems that K. pneumoniae utilizes diversity of genetic flexibility and recombination for resistance against carbapenems. The genetic structure of the plasmids showed that class I and III, Tn3 family, Tn5403 family derivatives, and Tn7-like elements were strongly associated with carbapenemases. The mobilizable plasmids carrying carbapenemases play an important role in the spread of these genes. In addition, gene repetition maybe is related to carbapenem heteroresistance. According to MST (minimum spanning tree) results, the majority of plasmids belonged to sequence type (ST) 11, ST14, and ST12. These international clones have a high capacity to acquire the carbapenemase-containing plasmids.

Introduction and benchmarking of pyMLST: open-source software for assessing bacterial clonality using core genome MLST.

Core genome multilocus sequence typing (cgMLST) has gained in popularity for bacterial typing since whole-genome sequencing (WGS) has become affordable. We introduce here pyMLST, a new complete, stand-alone, free and open source pipeline for cgMLST analysis. pyMLST can create or import a core genome database. For each gene, the first allele is aligned against the bacterial genome of interest using BLAT. Incomplete genes are aligned using MAFT. All data are stored in a SQLite database. pyMLST accepts assembly genomes or raw data (with the option pyMLST-KMA) as input. To evaluate our new tool, we selected three genome collections of major bacterial pathogens (Escherichia coli, Pseudomonas aeruginosa and Staphylococcus aureus) and compared them with pyMLST, pyMLST-KMA, ChewBBACA, SeqSphere and the variant calling approach. We compared the sensitivity, precision and false-positive rate for each method with those of the variant calling approach. Minimal spanning trees were generated with each type of software to evaluate their interest in the context of a bacterial outbreak. We found that pyMLST-KMA is a convenient screening method to avoid assembling large bacterial collections. Our data showed that pyMLST (free, open source, available in Galaxy and pipeline ready) performed similarly to the commercial SeqSphere and performed better than ChewBBACA and pyMLST-KMA.

Minimum spanning tree cycle intersection problem on outerplanar graphs

We study the minimum spanning tree cycle intersection (MSTCI) problem on outerplanar graphs in this paper. Consider a connected simple graph G=(V,E) and any spanning tree T=(V,ET) of G, it is well-known that each non-tree edge e∈E∖ET induces a fundamental cycle in T∪{e}. We say that two distinct fundamental cycles intersect if they share at least one edge. The MSTCI problem seeks a spanning tree such that the number of pairwise cycle intersections is minimized. We provide a linear-time algorithm to solve the problem on outerplanar graphs by exploiting the cycle-cut duality on plane graphs. Besides, we show that the minimum cycle intersection number is bounded by O(n) for outerplanar graphs with n vertices.