Branch Nodes Research Articles

Accurate and Efficient Estimation of Short-Circuit Current for MTDC Grids Considering MMC Control

DC short-circuit current calculation for the modular multilevel converter based multi-terminal direct current (MMC-MTDC) grid is critical and fundamental in equipment selection and protection setting. The existing MTDC grid short-circuit current calculation methods suffer from low efficiency, poor adaptability, and inflexibility. To address these issues, this paper proposes an efficient and general companion circuit-based method to estimate the short-circuit currents of asymmetric bipolar MTDC grids. First, an MMC is equivalent to an RLC series circuit in parallel with a time-dependent controlled current source. The equivalent model considers not only the discharge currents of the sub-module capacitors but also the ac in-feed current determined by MMC controllers. Then, the equivalent model for a bipolar MTDC grid with the dedicated metallic return is established by combing the equivalent MMC model with the lumped model of the dc transmission lines. Next, the companion circuit method is employed to efficiently and readily solve the equivalent model of the dc grid to obtain post-fault branch currents and node voltages. Both theoretical analyses and intensive tests on the CIGRE benchmark MTDC grid and Zhangbei bipolar MTDC grid verify the improved accuracy, efficiency, adaptability, and flexibility of the presented method.

Heuristic search via graphical structure in temporal interval-based planning for deep space exploration

Operations of conventional spacecraft used to be planned on ground and are uploaded as telecommands and executed on board at due time. However, because of difficulties in communicating with distant spacecraft, direct human control for the spacecraft is infeasible. Therefore, great hopes are placed on automated planning techniques to enhance the security of the spacecraft. By deciding a coon, as to support opportunistic science, the planner is mplex set of activities or states, an onboard planner is able to effectively arrange the daily tasks on a spacecraft. In additialso required to respond in the shortest possible time. Typically, to better characterize the spacecraft, the timeline-based knowledge representation benefits from its powerful ability to describe time and temporal behaviors, which is essential to effectively address real world problems. Compliant with the representation method, an elegant approach is devised for search guidance and solving problems efficiently in space-like contexts. Specifically, the key technique we build on is the heuristic estimate strategy based on a graphical structure defined in the model. Furthermore, a search algorithm joint with the heuristic function is proposed to avoid redundant work. By evaluating the branching nodes, this approach is able to prune irrelevant search space and make improvements in onboard planning efficiency. Our experiments exhibit an excellent performance on tested instances compared to Europa2.

Bi-objective Branch-and-Cut Algorithms Based on LP Relaxation and Bound Sets

Most real-world optimization problems are multi-objective by nature, with conflicting and incomparable objectives. Solving a multi-objective optimization problem requires a method that can generate all rational compromises between the objectives. This paper proposes two distinct bound set-based branch-and-cut algorithms for general bi-objective combinatorial optimization problems based on implicit and explicit lower-bound sets. The algorithm based on explicit lower-bound sets computes, for each branching node, a lower-bound set and compares it with an upper-bound set. The other fathoms branching nodes by generating a single point on the lower-bound set for each local nadir point. We outline several approaches for fathoming branching nodes, and we propose an updating scheme for the lower-bound sets that prevents us from solving the bi-objective linear programming relaxation of each branching node. To strengthen the lower-bound sets, we propose a bi-objective cutting-plane algorithm that adjusts the weights of the objective functions such that different parts of the feasible set are strengthened by cutting planes. In addition, we suggest an extension of the branching strategy “Pareto branching.” We prove the effectiveness of the algorithms through extensive computational results.

A branch-and-cut algorithm for Mixed-Integer Bilinear Programming

In this paper, we consider the Mixed-Integer Bilinear Programming problem, a widely-used reformulation of the classical mixed-integer quadratic programming problem. For this problem we describe a branch-and-cut algorithm for its exact solution, based on a new family of intersection cuts derived from bilinear-specific disjunctions. We also introduce a new branching rule that is specifically designed for bilinear problems. We computationally analyze the behavior of the proposed algorithm on a large set of mixed-integer quadratic instances from the MINLPlib problem library. Our results show that our method, even without intersection cuts, is competitive with a state-of-the-art mixed-integer nonlinear solver. As to intersection cuts, their extensive use at each branching node tends to slow down the solver for most problems in our test bed, but they are extremely effective for some specific instances.

A QoE-Driven Multicast Strategy With Segment Routing—A Novel Multimedia Traffic Engineering Paradigm

Quality of Experience (QoE) reflects end users' overall experience and feeling with network services, but needs support in terms of end-to-end Quality of Service (QoS). Segment routing (SR) as a new routing paradigm can provide good end-to-end QoS guarantee, making traditional multimedia traffic routing more efficient and scalable. In this paper, we address two problems related to the new SR mechanism: enabling fine-grained end-to-end QoS routing under a complex network environment and constructing the multicast routing tree with branch node load balancing. To solve these problems, an Inaccurate information-based QoE-driven Routing algorithm (IQdR) and a Branch-aware Multicast Tree (BaMT) algorithm were proposed. Simulation test results that have compared the performance of our proposed solution against that of other algorithms show that the previous works were outperformed. Additionally, the results also show that our multicast architecture improves the scalability of the network in terms of the number of flows.

Electrical properties of an arbitrary 2 × n order fan network

This paper deals with the electrical properties (branch current, node voltage, and equivalent resistance) of arbitrary 2 × n order Fan resistor network by means of the recursion-transform method. Taking the branch current as a variable, the matrix equation model and the boundary condition equation model are firstly established by applying Kirchhoff’s laws. Then the general solution and special solution of the matrix difference equation are studied by the matrix transformation. After that, the branch current formula of 2 × n order Fan network, the voltage formula of arbitrary node, and the equivalent resistance formula between any two nodes are all derived. Finally, special cases in the conclusions are analyzed and discussed.

Quantification of macropores of Malan loess and the hydraulic significance on slope stability by X-ray computed tomography

The accurate identification and quantitative characterization of loess structural properties at the pore scale are important in the study of macroscopic permeability. To characterise the macropore structure of Malan loess systematically, a non-destructive detecting method, that is, X-ray computed tomography (CT), was adopted for scanning five undisturbed specimens. A series of processing steps, including image filtering by a novel compositing image filter, image segmentation with the effective combination of threshold and top hat method, and three-dimensional (3D) reconstruction and visualisation by marching cube algorithm and volume-rendering technique were finished in AVIZO® software to acquire the 3D pore network model and to extract the two-dimensional (2D) and 3D structural parameters, such as porosity, equal diameter, aspect ratio, shape factor (SF), node density, number of terminal and branching nodes, coordinate number, dip angle, dip direction angle and tortuosity. Results show that (1) Malan loess is a kind of porous geological material with strong verticality and spatial anisotropy reflected by the 2D parameters including porosity, equal diameters and aspect ratio as well as the 3D dip angle and 3D-visualised loess macropores; (2) Malan loess has higher permeability in the vertical direction than that in the horizontal direction so that prone to induce excessive infiltration and preferential flow, thereby threatening the loess slope stability; (3) SF is an effective parameter for pore classification in both 2D and 3D scales; (4) the macropores with a large diameter have a larger volume fraction, better connectivity (effective porosity) and greater contribution to water permeability; (5) the larger the coordinate number, the greater the hydraulic conductivity, nevertheless other than the aggregates for the water repellency caused by organic matter. In conclusion, the combination of CT and AVIZO® is excellent for quantifying the key macropore structural parameters (e.g., shape factor and tortuosity) and their hydraulic significance on slope stability.

Abstract 1634: A topology based data analysis method to predict survival time

Abstract There are different methods to predict survival time, including traditional statistical regression, and modern neural network. Still, precise prediction of survival time remains as a challenge. In recent years algebraic topology was introduced as a novel method to infer information from high dimensional data set, where a mapper uses an algorithm to obtain geometric or topological features of the data set, and associate the features with the predicted variables. In this study, the data set includes gender, age, AFP, GGT, PPT, TB, ALT, tumor size, tumor number, BCLC stage, number of liver nodules, type of surgical approach etc., total 21 diagnostic variables. We use these variables to predicted OS and DFS, and the data set contains 329 records. In this study, the topology mapper is executed to acquire the topological features of all the data (including training and test sets), since this task is unsupervised, so the target values are not considered. Our method is to infer three new features of each data record, including the location of the record on the main branch of the topology, whether it is a branch node (i.e. has more than 2 branches), and whether it is an endpoint. A simple neural network with one hidden layer is designed and implemented with Tensorflow, and the three features will be added to the data set and provide valuable information for prediction of the target values. Without adding the new features from topology mapper, we have 72% accuracy (in predicting the survival time is greater or less than the mean value) on test set data when predicting OS, and we have 75% accuracy on test set data when predicting the DFS. With the new features from topology mapper, we have 83% accuracy on test set data when predicting OS, and 84% accuracy on test set data when predicting the DFS. The three new features inferred from the topology mapper have a significant effect on the accuracy of prediction and provide better accuracy. The topology based data analysis method in this study could be applied to other classification problems related to clinical trial data, and will need further verification. Citation Format: Cheng Huang, Hui-Chuan Sun, Junda Chen, Lin Shi, Fengqing Li, Yihui Lin, Hanyan Yang. A topology based data analysis method to predict survival time [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1634.

Ramification has little impact on shoot hydraulic efficiency in the sexually dimorphic genus Leucadendron (Proteaceae).

Despite the diversity of branching architectures in plants, the impact of this morphological variation on hydraulic efficiency has been poorly studied. Branch junctions are commonly thought to be points of high hydraulic resistance, but adjustments in leaf area or xylem conduit abundance or dimensions could compensate for the additional hydraulic resistance of nodal junctions at the level of the entire shoot. Here we used the sexually dimorphic genus Leucadendron (Proteaceae) to test whether variation in branch ramification impacts shoot hydraulic efficiency. We found that branch ramification was related to leaf traits via Corner’s rules such that more highly ramified shoots had smaller leaves, but that branch ramification had little consistent impact on shoot hydraulic efficiency, whether measured on a leaf area or stem cross-sectional area basis. These results suggest that the presumed increase in resistance associated with branching nodes can be compensated by other adjustments at the shoot level (e.g. leaf area adjustments, increased ramification to add additional branches in parallel rather than in series) that maintain hydraulic efficiency at the level of the entire shoot. Despite large morphological differences between males and females in the genus Leucadendron, which are due to differences in pollination and reproduction between the sexes, the physiological differences between males and females are minimal.

Form-Finding and Structural Shape Optimization of the Metal 3DPrinted Multi-Branch Node with Complex Geometry

The application of additive manufacturing (AM) technology in architecture and structural engineering has been extended due to recent development of metal 3d printing. In space frame structures, a set of bars is configured in three dimensions, with bars connected by nodes. This article presents two methods to design metal 3d-printed multi-branch nodes to accommodate any number of incident bars at arbitrary angles. Resulting node designs are intended to be smooth and lightweight. A multi-branch node is sketched using the dimensional information of the blank space between the converging bars in a pre-designed space frame and then parameterized by two different approaches to perform structural optimization. The first design method, namely the curve parameter method, which is semi-automated approach, the distances between the control points of the spline curves between node branches and the node branch intersection point are the optimization parameters. For the other method, called fatness parameter method, which is a fast and automated approach, the fatness parameters of the center part of the node and the root radiuses of each branch are chosen as the main parameters of optimization. The optimization procedure is accomplished using a genetic algorithm to minimize the maximum von Mises stress as the objective function subjected to the mass of the node as a constraint function. Finally, functional tests are conducted on 3D printed metal nodes in order to compare the strength and stiffness of the nodes designed by the two form-finding approaches.

Direct and Hierarchical Models for Aggregating Spatially Dependent Catastrophe Risks

We present several fast algorithms for computing the distribution of a sum of spatially dependent, discrete random variables to aggregate catastrophe risk. The algorithms are based on direct and hierarchical copula trees. Computing speed comes from the fact that loss aggregation at branching nodes is based on combination of fast approximation to brute-force convolution, arithmetization (regriding) and linear complexity of the method for computing the distribution of comonotonic sum of risks. We discuss the impact of tree topology on the second-order moments and tail statistics of the resulting distribution of the total risk. We test the performance of the presented models by accumulating ground-up loss for 29,000 risks affected by hurricane peril.

Fast Solving Method Based on Linearized Equations of Branch Power Flow for Coordinated Charging of EVs (EVCC)

Reported researches on smart charging methods have the disadvantages of low calculation efficiency or have not simultaneously taken the three-phase imbalance, voltage, and power flow constraints into account. It is an important topic to improve the computational speed to meet the online rolling optimization requirement for EVCC problems. In this paper, the branch power flow equations of balanced and unbalanced distribution system are derived. The linearization methods for the nonlinear terms of the branch power flow equations are proposed. Two stages linear programming (LP) is introduced for EVCC to minimize the total charging costs of the holders where three-phase imbalance, charging demand, voltage, and power flow constraints have been taken into account. Via ignoring the nonlinear terms of the branch power flow equations, the first stage LP is formulated to calculate the estimated branch power and node voltages as the initial points for linearizing the nonlinear terms of branch power flow equations. The second stage LP is formulated to calculate the optimal charging power using the linearized branch power flow equations. Four case studies show that the proposed method without the compromise of precision is significantly faster than state-of-the-art works with respect to the computational speed.

Unsupervised lip segmentation based on quad-tree MRF framework in wavelet domain

In this paper, we propose a new extended method to implement lip segmentation. Based on a quad-tree structure (QTS) Markov random field (MRF) model under unsupervised situation, the proposed method achieves the lip segmentation in wavelet domain. Firstly, we set up a multi-layer hierarchical model, in which each pixel of every layer corresponds to the four nodes in quad-tree structure. Then the probability of a branch node can be calculated by using the probability of the previous branch node through the tree structure easily. Subsequently, a Markov random field derived from the model is obtained so that the segmentation problem is formulated as a labeling optimization problem in the framework of the maximum a posteriori Markov random field (MAP-MRF). Assuming that the pre-assigned cluster of data segments may overestimate the underlying fact, and leads to over-segmentation, we propose a variable-weight segmentation approach to improve the robustness of the segmentation. The experimental results show that this method has better segmentation accuracy than traditional methods.

Insights into bootstrap percolation: Its equivalence with k-core percolation and the giant component.

K-core and bootstrap percolation are widely studied models that have been used to represent and understand diverse deactivation and activation processes in natural and social systems. Since these models are considerably similar, it has been suggested in recent years that they could be complementary. In this manuscript we provide a rigorous analysis that shows that for any degree and threshold distributions heterogeneous bootstrap percolation can be mapped into heterogeneous k-core percolation and vice versa, if the functionality thresholds in both processes satisfy a complementary relation. Another interesting problem in bootstrap and k-core percolation is the fraction of nodes belonging to their giant connected components P_{∞b} and P_{∞c}, respectively. We solve this problem analytically for arbitrary randomly connected graphs and arbitrary threshold distributions, and we show that P_{∞b} and P_{∞c} are not complementary. Our theoretical results coincide with computer simulations in the limit of very large graphs. In bootstrap percolation, we show that when using the branching theory to compute the size of the giant component, we must consider two different types of links, which are related to distinct spanning branches of active nodes.

Branch and Bound Algorithm for the Single Machine Scheduling Problem with Release and Delivery times

The single machine scheduling problem is one of the classic NP-hard optimization problems, and it is useful in solving flowshop and jobshop scheduling problems. The goal of this paper is to prepare algorithms for the scheduling problem, where set of tasks is performed on a single processor. Each task has a release time when it becomes available for processing, a processing time and a delivery time. At most one job can be processed at a time, but all jobs may be simultaneously delivered. Preemption is not allowed. The objective is to minimize the time, by which all tasks are delivered. We compare the nondelay schedule, in which no processor is kept idle at a time when it could begin processing a task and an inserted idle time schedule, in which a processor is kept idle at this time. In this paper, we propose an approximation algorithm and by combining this algorithm and branch and bound method, we develop branch and bound algorithm, which can find optimal solutions for the single processor scheduling problem. We use a binary branching rule, where at each branch node, a complete schedule is generated. To illustrate the effectiveness of our algorithms we tested them on randomly generated set of tasks.

Calculating Nodal Voltages Using the Admittance Matrix Spectrum of an Electrical Network

Calculating nodal voltages and branch current flows in a meshed network is fundamental to electrical engineering. This work demonstrates how such calculations can be performed using the eigenvalues and eigenvectors of the Laplacian matrix which describes the connectivity of the electrical network. These insights should permit the functioning of electrical networks to be understood in the context of spectral analysis.

Morphological characterization of leaves at different crown positions of tangerine genotypes

The leaf anatomy has been shown as an important tool to understand the interaction between this organ and its microclimate but this topic is still unclear for citrus plants. The objective of this study was to analyze the leaf structure of Ponkan, Fremont and Thomas tangerine and Murcott tangor. Fully expanded leaves were collected collected, from the 2nd and 3rd nodes of plagiotropic branches facing West, at three crown heights (lower, middle and upper). The leaves were fixed in 70% ethanol and embedded in historesin and sectioned in a semi-automatic microtome. The sections were stained with toluidine blue; images were captured under a light microscope coupled and analyzed to measure leaf tissue thickness. The Fremont tangerine leaves had greater epidermis thickness on the adaxial and abaxial surfaces and secretory cavity diameter as well as a shorter distance between secretory cavities, whereas the Murcott leaves had greater palisade and spongy parenchyma thickness. Thus, Fremont and Murcott are potential varieties for xeric conditions, as they are able to reduce transpiration and make optimal use of high incident radiation. The microclimates created by plant architecture may affect the leaf anatomy of the Ponkan, Fremont and Thomas and Murcott trees, allowing anatomical plasticity.

PERTUMBUHAN DAN HASIL DUA VARIETAS TANAMAN KEDELAI (Glycine max (L.) Merril) DIBAWAH KONDISI CEKAMAN KEKERINGAN PADA BERBAGAI STADIA TUMBUH

Soybean is categorized as a plant which sensitive to water deficit or surplus in its life cycle. If water requirement is not sufficient for the growth and development, the soybean will be subjected to stress. Water stress, such deficiency or excess of water in the plant environment is a condition that disrupts the balance of plant growth. Therefore, it is necessary to observe the interaction between drought stress at various growth stages and soybean varieties, and observe which growth stages that would provide the highest yield of soybean know the differences in drought stress in various stadia of plant growth on the growth and yield of two varieties of soybean crops and which currently can give the highest yield in various stadia grow. This research was carried out by using polybag in the greenhouse of Faculty of Agriculture Universitas Lambung Mangkurat Banjarbaru for 4 months from March to June 2017. The experimental design was Randomized Completely Design with Split Plot Design Factorial. The first factor is soybean varieties (V) as main plot, i.e. Grobogan (v1) and Anjasmoro (v2), and the second factor is the growth stages those subjected to drought stress (C) as subplot, i.e. c1 : vegetative stage 3 (29 DAS and 36 DAS), c2 : flowering stage (35 DAS and 46 DAS), c3 pods appearance/emergence (42 DAS and 53 DAS), and c4 : pods filling stage (68 DAS and 76 DAS). The treatment was repeated 3 times and each experiment unit consists of 5 polybags, thus there were 120 plants in total. The crop growth rate, number of main branch nodes, number of effective root nodules, shoot root ratio, the first flowering time, the harvest time, number of pods per plant, number of seed per plant, 100 seed dry weight, and the number of dry seed per plant. The result showed there was no interaction effect between drought stress in various stages and soybean varieties on all variables. Drought stress at vegetative stage 3 (c1) caused the number of main branch nodes, the number of pods per plant, the number of seed per plant, the 100 seed dry weight and the number of dry seed per plant are lower if they are compared to the plants those subjected to drought stress at pod filling stage (c4). Nevertheless, those variables were not different at drought stress at flowering stage (c2), pods appearance (c3) and pod filling stage (4). Soybean varieties observation showed that the Grobogan were faster in flowering time and higher in crop growth (26.49 DAS and 3.08 g d-1 respectively) compared to the Anjasmoro (34.08 DAS and 2.73 g d-1 respectively).

Nucleotide diversity of a nuclear gene ITS region and chloroplast genes (matK, rbcL, rpoC1) of Canarium nigrum in some provinces in Northern Vietnam

In this study, three chloroplast genes (matK, rbcL and rpoC1) and one nuclear gene (ITS) were used to assess the nucleotide diversity for nine individuals of Canarium nigrum species in Bac Giang, Hoa Binh and Phu Tho provinces (three individuals from each province). The nucleotide sequence of the four regions (ITS, matK, rbcL and rpoC1) of C. nigrum were determined with the results showing their size to be 696 bp, 798 bp, 702 bp and 522 bp, respectively. Results of nucleotide sequence comparison for the studied samples exhibited 100% similarity for all the four gene regions. Sequence comparison with other species in the Canarium genus available in the GenBank revealed that the nucleotide diversity level (π) was the highest for the ITS gene (0.02), followed by matK (0.007), and the lowest for rbcL (0.003). The phylogenetic tree of C. nigrum with the species in Canarium genus indicated that the separation of species was the clearest for the rpoC1 gene, followed by rbcL, matK and ITS gene, with the bootrap values obtained from the branching nodes of each species ranging from 98 to 99%, 35 to 67%, 65 to 98% and 98 to 99%, respectively. The species C. nigrum had the closest nucleotide similarity to C. tramdenum (KP093200) and C. album (KP093198) for the ITS gene and to species C. subulatum (KR530509), C. acutifolium (KR530512) for matK gene region. These results suggests the rpoC1 gene region could be used as barcode for the species in genus Canarium.

Fault Incidence Matrix Based Reliability Evaluation Method for Complex Distribution System

A fast reliability calculation method based on the fault incidence matrix (FIM) for the complex distribution system is proposed in this paper. First, the M-segment-N-tie-switch (MSNT) reliability calculation unit for the complex distribution network is established and the power supply path matrix is obtained by inversing the node branch incidence matrix of the MSNT unit. Then, three types of FIMs are constructed considering the influence type of each fault event on the load points. Finally, the system reliability indexes are calculated through the algebraic operation between the FIMs and the fault event parameter vectors. The accuracy and the efficiency of this method are verified using the IEEE RBTS bus-6 system. The reliability evaluation method proposed in this paper avoids complicated fault event enumeration and repetitive fault influence range searching, thus, saves the computation time greatly. And more importantly, the analytical expression of the reliability indexes in the matrix form can clearly show the influence of each fault event on each load interruption. So, it is convenient for the reliability sensitivity analysis and helpful for the operator with the reliability improvement planning.