Spanning Tree Model Research Articles

Optimal Sensor Deployment in Internet of Things based Wireless Sensor Network for Irrigation Management System

In recent years, several applications are found to be exploiting under Wireless Sensor Networks (WSNs), and more particularly civil and military applications. However, Target Coverage (TCOV) and Network Connectivity (NCON) are found to be the most crucial issues that have to be resolved to attain effective robust data communication and environmental sensing in WSN. This paper has made an attempt to propose a new effective sensor deployment model in the application of the irrigation management system in agriculture sector. The data logger (data collector) IoT devices are typically placed over the field, which does the communication one another. The main point of this design is the IoT device TCOV and NCON, and the real-time issue related to this design is the device mobility that consumes more power thereby minimizes the lifetime of network. The proposed model intends to solve the comprised NCON and TCOV with the aid of Euclidean Spanning Tree Model (ECST). Further, this paper introduces a new Fitness Interrelated Whale Optimization Algorithm (FI-WOA) that insisted in the minimum movement of mobile sensors over the network. This novel characteristic of sensor deployment model would create the effectual impacts in the irrigation management system. Further, the adopted ECST-WOA model is compared with conventional models and the results attained from the execution demonstrate the enhanced performance of the implemented technique.

Models and cutting-plane strategies for the tree-star problem

Let G = (V, E) be a connected graph of set of nodes V and set of edges E. Let T = (VT, ET), with VT = V and ET ⊆ E, be a spanning tree of G. With each edge e ∈ E there is associated a routing cost ceR if e connects two internal nodes of T; or an access cost ceA, otherwise. The problem is to determine a spanning tree (tree-star) considering access and routing edge costs of minimum cost. We present two new formulations and a cutting-plane algorithm. One is based on a classical spanning tree model. The novelty relies on the way we capture access and routing edges depending on the internal nodes of the tree. The second model is completely new and is based on the concept of dicycle to represent routing edges as quadratic variables that are linearized accordingly to obtain a tree-star equivalent structure. Computational experiments performed on benchmark instances for models PFlow and PHR from the literature and for the new ones (PST and PDC) indicate that this problem is very difficult to deal with. Only a very small number of instances was solved to optimality in a given time limit. Models PDC and PHR, improved with cutting-plane strategies, although they do not solve optimally almost instances, performed better for this problem, with the dicycle-based model presenting the smallest gaps for instances for which some feasible solution was found.

Active Spanning Trees with Bending Energy on Planar Maps and SLE-Decorated Liouville Quantum Gravity for $${\kappa > 8}$$

We introduce a two-parameter family of probability measures on spanning trees of a planar map. One of the parameters controls the activity of the spanning tree and the other is a measure of its bending energy. When the bending parameter is 1, we recover the active spanning tree model, which is closely related to the critical Fortuin–Kasteleyn model. A random planar map decorated by a spanning tree sampled from our model can be encoded by means of a generalized version of Sheffield’s hamburger-cheeseburger bijection. Using this encoding, we prove that for a range of parameter values (including the ones corresponding to maps decorated by an active spanning tree), the infinite-volume limit of spanning-tree-decorated planar maps sampled from our model converges in the peanosphere sense, upon rescaling, to an $${{\rm SLE}_\kappa}$$ -decorated γ-Liouville quantum cone with $${\kappa > 8}$$ and $${\gamma = 4/ \sqrt\kappa \in (0,\sqrt 2)}$$ .

Minimizing movement for network connectivity in mobile sensor networks: an adaptive approach

Nowadays the most important key point in the design of wireless sensor networks (WSNs) is the sensor coverage point and network connectivity. The main practical issue in designing the essential WSN is the mobility of mobile sensors which consumes more power thereby reduces the network lifetime significantly. In order to avoid these problems, we have investigated the mobile sensor deployment (MSD) problem comprises of network connectivity and target coverage is resolved using Euclidean spanning tree model (ECST) and ECST-adaptive VABC (ECST-AVABC) method respectively. Besides, we proposed an AVABC optimization algorithm by obtaining minimum movement of mobile sensors over the network. Furthermore, the extensive simulation experiments have offered the optimal promising solutions of NCON, to the MSD problem with minimum movement and providing the extended lifetime of WSN. Finally, the experimental results states that the movement distance shown by the proposed ECST-AVABC become 4.2, 10, and 20% lesser than the standard ECST-VABC method.

Study on the Layout of Intercity Rail Transit Network Based on Traffic Location

The concept of a high-speed passenger traffic location line is proposed by analyzing intercity rail traffic location and network evolution characteristics to improve the effectiveness of intercity rail transit network layout planning. Then, a multilevel intercity rail transit network planning and optimization model is constructed. The model is divided into two levels, namely, the backbone network and the preliminary network. The backbone network optimization model is the minimum spanning tree model, which uses the reciprocal of economical relation intensity as its weight. The preliminary network model is a multi-objective function, which maximizes economical relation intensity and connectivity and minimizes the total length of rail transit lines. The optimization model provides a new method for intercity rail transit network planning. Finally, the rationality and effectiveness of the network layout are verified using the line network within the Wuhan urban agglomeration area as an example.

Finite size and boundary effects in critical two-dimensional free-fermion models

Here we will consider the finite-size scaling, finite-size corrections and boundary effects for the critical two-dimensional free-fermion models. A short review of significant achievements and possibilities is given. However, this review is still far from completeness. We derive the exact finite-size corrections for the set of free models of statistical mechanics, including Ising model, dimer model, resistor network and spanning tree model under different boundary conditions. We have shown that the partition functions of all these models can be written in terms of the only object, namely, the partition function with twisted boundary conditions.

Analysis of Mixing Models for use in Simulations of Turbulent Spray Combustion

The present study concerns the investigation of different mixing models for use in the transported probability density function (PDF) modeling of turbulent (reacting) spray flows. The modeling of the turbulent mixing and other characteristic scalar variables such as gas enthalpy using transported (joint) PDFs has become an important method to describe turbulent (reacting) spray flows since the evaporation process causes the PDF of the mixture fraction to deviate from the widely used β function, which is typically used in models for turbulent gas flows. In the PDF transport equation, the molecular mixing does not appear in closed form so that modeling strategies are required. For gas combustion, the interaction-by-exchange-with-the-mean (IEM) model, the modified Curl (MC) model, and the Euclidean minimum spanning tree (EMST) models are used. More recently, a new mixing model, the PSP model, which is based on parameterized scalar profiles has been developed. The present study focuses on the use and analysis of the IEM, MC and PSP models for turbulent spray flames. For this purpose, the models are reconsidered with respect to the evaporation process that must be included and evaluated if spray combustion is considered. For model evaluation, turbulent ethanol/air spray flames are simulated, and the results are compared to experimental data by A. Masri, University of Sydney, Australia.

Ordered Weighted Average optimization in Multiobjective Spanning Tree Problem

Multiobjective Spanning Tree Problems are studied in this paper. The ordered median objective function is used as an averaging operator to aggregate the vector of objective values of feasible solutions. This leads to the Ordered Weighted Average Spanning Tree Problem, a nonlinear combinatorial optimization problem. Different mixed integer linear programs are proposed, based on the most relevant minimum cost spanning tree models in the literature. These formulations are analyzed and several enhancements presented. Their empirical performance is tested over a set of randomly generated benchmark instances. The results of the computational experiments show that the choice of an appropriate formulation allows to solve larger instances with more objectives than those previously solved in the literature.

Good initialization model with constrained body structure for scene text recognition

Scene text recognition has gained significant attention in the computer vision community. Character detection and recognition are the promise of text recognition and affect the overall performance to a large extent. We proposed a good initialization model for scene character recognition from cropped text regions. We use constrained character’s body structures with deformable part-based models to detect and recognize characters in various backgrounds. The character’s body structures are achieved by an unsupervised discriminative clustering approach followed by a statistical model and a self-build minimum spanning tree model. Our method utilizes part appearance and location information, and combines character detection and recognition in cropped text region together. The evaluation results on the benchmark datasets demonstrate that our proposed scheme outperforms the state-of-the-art methods both on scene character recognition and word recognition aspects.

Performance of transported PDF mixing models in a turbulent premixed flame

Modeling of premixed turbulent flames is challenging due to the effects of strong turbulence-chemistry interaction. In the transported probability density function (TPDF) methods, chemical reactions are treated exactly, while molecular mixing needs to be modeled. In the present study, the performance of three widely used mixing models, namely the Interaction by Exchange with the Mean (IEM), Modified Curl (MC), and Euclidean Minimum Spanning Tree (EMST) models, are assessed using direct numerical simulation (DNS) data of a lean premixed hydrogen–air slot jet flame simulated at Sandia. The DNS provides initial conditions and time varying input quantities, including the mean velocity, turbulent diffusion coefficient, and scalar mixing rate for the TPDF simulations. A number of progress variable definitions are explored, as well as the commonly used constant mechanical-to-scalar mixing timescale model. It is found that the EMST model provides the best prediction of the flame structure and flame propagation speed out of the models tested. The IEM model implies a qualitatively incorrect conditional mean and RMS diffusion rate, while the MC model can qualitatively capture the conditional mean diffusion rate. Only the EMST model can accurately predict the conditional mean diffusion rate for this flame, which can be attributed to its enforcement of mixing that is local in composition space. Finally, a parametric study on the mechanical-to-scalar timescale ratio is performed. It is found that the optimal choice for the timescale ratio varies by a factor of 2 for the two DNS cases study, despite the cases having the same configuration. Therefore, this commonly used approach does not appear to be viable for turbulent premixed flames and further attention to mixing timescale models for reactive scalars is merited.

Farm drainage channel network optimization by improved modified minimal spanning tree

Collection, conveyance and discharge of farm drainage water using open channel network is an important task in an agricultural area. Design of an open channel network is based on the total length and conveying capacity of the channel, topography of the area and specific local conditions. Therefore, designing proper channel paths is an effective factor in the optimum network design. In this study, three optimization models have been considered: the modified minimal spanning tree, the shortest path and the out-of-kilter algorithms. The modified minimal spanning tree model for optimization of a farm drainage channel network (FDCN) has been improved to a better algorithm. The algorithm has been applied to optimize a part of the Sansad irrigation network project. Then, the FDCN system of the Jiroft and Roodbar plain was mathematically modeled considering regional constraints and optimized using the presented models. Results showed that the improved modified minimal spanning tree model, gives the shortest channel network length compared to the other three models.

Exact finite-size corrections for the spanning-tree model under different boundary conditions.

We express the partition functions of the spanning tree on finite square lattices under five different sets of boundary conditions in terms of a principal partition function with twisted-boundary conditions. Based on these expressions, we derive the exact asymptotic expansions of the logarithm of the partition function for each case. We have also established several groups of identities relating spanning-tree partition functions for the different boundary conditions. We also explain an apparent discrepancy between logarithmic correction terms in the free energy for a two-dimensional spanning-tree model with periodic and free-boundary conditions and conformal field theory predictions. We have obtained corner free energy for the spanning tree under free-boundary conditions in full agreement with conformal field theory predictions.

Transfer current and pattern fields in spanning trees

When a simply connected domain $D\subset{\mathbb{R}}^d$ ($d\ge 2$) is approximated in a "good" way by embedded connected weighted graphs, we prove that the transfer current matrix (defined on the edges of the graph viewed as an electrical network) converges, up to a local weight factor, to the differential of Green's function on $D$. This observation implies that properly rescaled correlations of the spanning tree model and correlations of minimal subconfigurations in the abelian sandpile model have a universal and conformally covariant limit. We further show that, on a periodic approximation of the domain, all pattern fields of the spanning tree model, as well as the minimal-pattern (e.g. zero-height) fields of the sandpile, converge weakly in distribution to Gaussian white noise.

A DNS evaluation of mixing models for transported PDF modelling of turbulent nonpremixed flames

Transported probability density function (TPDF) methods are well suited to modelling turbulent, reacting, variable density flows. One of the main challenges to the successful deployment of TPDF methods is accurately modelling the unclosed molecular mixing term. This study examines three of the most widely used mixing models: the Interaction by Exchange with the Mean (IEM), Modified Curl (MC) and Euclidean Minimum Spanning Tree (EMST) models. Direct numerical simulation (DNS) data-sets were used to provide both initial conditions and inputs needed over the course of the runs, including the mean flow velocities, mixing frequency, and the turbulent diffusion coefficient. The same chemical mechanism and thermodynamic properties were used, allowing the study to focus on the mixing model. The simulation scenario was a one-dimensional, nonpremixed, turbulent jet flame burning either a syngas or ethylene fuel stream that featured extinction and reignition. This test scenario was selected because extinction and reignition phenomena are sensitive to the mixing model. Three DNS cases were considered for both the syngas and ethylene cases with a parametric variation of Reynolds and Damköhler numbers, respectively. Extinction events became more prevalent with increasing Reynolds number in the syngas cases and with decreasing Damköhler number in the ethylene cases. The model was first tested with the mixing frequency defined from the dissipation rate and variance of mixture fraction. With this definition, for the syngas cases this study finds that the TPDF method is successful at predicting flame extinction and reignition using all three mixing models for the relatively lower and intermediate Reynolds number cases, but that all models under-predict reignition in the relatively higher Reynolds number case. In the ethylene fuelled cases, only the EMST mixing model correctly predicts the reignition event for the two higher Damköhler number cases, however, in the lowest Damköhler number case the EMST model over-predicts reignition and the IEM and MC models under-predict it. Mixing frequency was then modelled based on the turbulence frequency and a model constant Cϕ, the ratio of scalar to mechanical mixing rates. The DNS cases were reexamined with this definition and the results suggested that the optimal value for Cϕ is mixing model and case dependent. In particular, it was found in the ethylene case considered that reignition could be achieved with the IEM and MC models by adjusting the value of Cϕ.

Models for inverse minimum spanning tree problem with fuzzy edge weights

An inverse minimum spanning tree problem is to make the least modification on the edge weights such that a predetermined spanning tree is a minimum spanning tree with respect to the new edge weights. In this paper, a type of fuzzy inverse minimum spanning tree problem is introduced from a LAN reconstruction problem, where the weights of edges are assumed to be fuzzy variables. The concept of fuzzy α-minimum spanning tree is initialized, and subsequently a fuzzy α-minimum spanning tree model and a credibility maximization model are presented to formulate the problem according to different decision criteria. In order to solve the two fuzzy models, a fuzzy simulation for computing credibility is designed and then embedded into a genetic algorithm to produce some hybrid intelligent algorithms. Finally, some computational examples are given to illustrate the effectiveness of the proposed algorithms.

The Weight and Optimization of the Path Analysis of Waste-Heat Utilization in Larege Hospitals

The value of wasteheat utilization in large general hospitals is a critical problem that can not be ignored with social development. To make use of this source means to establish a system of wasteheat utilization, and two priorities are determining the weigh of different wasteheat utilization point properly and determine the best path for waste heat utilization. In this paper, based on Analytic Hierarchy Process (AHP) and Information Entropy of wasteheat utilization point distribution model, we find the way to determine the weights. At the same time, the Minimum Spanning Tree Model based on Kruskal's algorithm helps to find the new method of optimal path in using wasteheat. Both models will be used in the heat research of a hospital, and we identify both clear wasteheat utilization point weights distribution and minimum cost of the best path which really paves the way for the further system construction of wasteheat utilization in large general hospital with further research and application value.

Transported-PDF (IEM, EMST) micromixing models in a hydrogen-air nonpremixed turbulent flame

The topic of this study is the numerical simulation of a turbulent non-premixed hydrogen flame with different micromixing models in order to investigate their predictive capability. The two micromixing models are compared. The first model is the interaction by exchange with the mean (IEM) model (Dopazo and O’Brien Acta Astronaut 1(9–10):1239, 1974). The second one is the Euclidean minimum spanning tree (EMST) model (Subramaniam and Pope Combust Flame 115(4):487, 1998). The dynamic model for the mixing time-scale is handled, by computing the individual time-scales for the reactive scalars in each cell during the simulation course using the Fluent/MM-INTAS CFD code. The predictions are validated against experimental data provided by Raman and Laser Doppler anemometry measurements for a turbulent jet Hydrogen-air diffusion flame. The interaction of turbulence-chemistry is handled with TPDF method. The chemical model used here consists of 11 chemical species and 23 reactions. Comparisons with experimental data demonstrate that predictions based on the EMST model are slightly better. The EMST improves largely the precision of the results to the detriment of the RAM and the CPU performances. Overall, profile predictions of mixture fraction, flame temperature and major species are in reasonable agreement with experimental data.

A spanning tree model for the Heegaard Floer homology of a branched double-cover

Given a diagram of a link K in S^3, we write down a Heegaard diagram for the branched-double cover Sigma(K). The generators of the associated Heegaard Floer chain complex correspond to Kauffman states of the link diagram. Using this model we make some computations of the homology \hat{HF}(Sigma(K)) as a graded group. We also conjecture the existence of a delta-grading on \hat{HF}(Sigma(K)) analogous to the delta-grading on knot Floer and Khovanov homology.

A return to the traveling salesman model: a network branch and bound approach

This paper presents a network branch and bound approach for solving the traveling salesman problem. The problem is broken into sub-problems, each of which is solved as a minimum spanning tree model. This is easier to solve than either the linear programming-based or assignment models.

An Adaptive One-class Classification Algorithm Based on Multi-resolution Minimum Spanning Tree Model in High-dimensional Space

The coverage radii in the algorithm of MSTCD(Minimum spanning tree class descriptor) are generally fixed without diversification,which makes it diffcult to construct a close coverage for the local structure.This article combines multi-resolution thought and minimum spanning tree(MST) covering model,and proposes an adaptive multi-resolution covering model based MST in high-dimensional space.In this algorithm,multi-resolution of data is determined by the distributed feature of data manifold itself.The resolution of any location is depended on the structure of sample point and edge.The proposed novel algorithm permits that the whole covering model could have different coverage radii or resolutions and the resolution has relationship with location.Experiments show that the algorithm is reasonable.