Node Insertion Research Articles

Minimal surface-guided higher-order mesh generation for CAD models

This paper presents a novel method for generating higher-order meshes for CAD surfaces by leveraging minimal surface theory to improve element shapes. We explore the concept of higher-order mesh distortion through deformation gradients and introduce an energy function designed to minimize the surface area of these meshes, providing a theoretical justification for its effectiveness in untangling. The process of mesh generation starts with segmenting CAD surfaces into linear elements, followed by the insertion of higher-order nodes within these elements. These nodes are then projected onto the CAD surface to form the initial higher-order elements. By optimizing energy functions related to minimal surfaces and the projection distances, we achieve high-quality, geometrically accurate higher-order surface meshes. Our method has been validated on complex geometries, showcasing its potential in creating effective higher-order meshes for industrial CAD models.

Adaptive convolutional-LSTM neural network with NADAM optimization for intrusion detection in underwater IoT wireless sensor networks

Abstract Underwater IoT networks rely on sensor nodes to continuously monitor and collect real-time data from marine environments. The nodes in the underwater networks face security challenges in terms of intrusions. Intrusions are common in conventional wireless sensor networks as well as in underwater sensor networks. Intrusions like data tampering, node insertion, unauthorized access compromises the security and privacy of the network. The existing Intrusion Detection Systems (IDS) faces limitations while detecting intrusions in Underwater IoT Wireless Sensor Networks (UIoTWSN) due to the dynamic condition of underwater environment. To overcome this, a novel IDS for UIoTWSN is proposed by combining the features of advanced deep learning techniques in an optimized manner. The proposed hybrid model comprises convolutional LSTM network with NADAM optimizer to analyze the spatial and temporal features to detect the intrusions. To handle the dynamic nature of underwater sensor network and to improve the convergence speed of the proposed IDS, NADAM optimizer is integrated in this research work. Experimentations of the proposed model validates the higher accuracy of 96.7%, precision of 94.5% and recall of 95.2% which is better than the conventional techniques.

Combined Sweeping and Jumping Method to Enhance Node Insertion Algorithm for Wi-Fi Sensor Networks

Two dominant driving forces for evolving communication technologies in the current society have been the proliferation of wireless access networks to the Internet and the broadbandization of access and infrastructure networks. Through these evolutions of communication technologies, high-resolution contents are instantly delivered to wireless devices such as mobile phones, wireless tablets, and headsets. Recently, wireless sensor networks, where up to 1000 low-power sensors are wirelessly connected to each other, have been created and connected to the Internet, which presents a new challenge of efficiently coordinating the transmissions of many wireless sensors with minimal transmission overheads. Developing an efficient Medium Access Control (MAC) protocol governing the transmissions of wireless sensor networks is crucial for the success of wireless sensor networks for the realization of the Internet of Things (IoT). In 2023, the node insertion algorithm was proposed to efficiently derive the minimal number of serially connected multipolling sequences of many wireless sensors, by which Access Points (APs) can poll wireless sensors with minimal polling overheads. In this paper, the combined sweeping and jumping method is presented to dramatically enhance the searching performance of the node insertion algorithm. To validate the performance of the combined sweeping and jumping method, simulation results are presented for wireless sensor networks where wireless sensors with varying transmission ranges exist.

Pseudo node insertion method for synchronization in drone–truck combined operations

Drone–truck combined last-mile delivery systems present several advantages, which can be summarized in two folds: (1) enabling faster pick-up/delivery of items and (2) expanding operation areas beyond the range that could be achieved by using only one type of vehicle. Drone–truck combined operation (DTCO) solutions are based on vehicle routes and drone launch and retrieval locations, usually customer nodes. Since a perfect synchronization of both vehicles is very rare, most of the solutions obtained after designing combined delivery routes generally contain time losses, caused by the need for the first vehicle that reaches the meeting point to wait until the arrival of the other. In this paper, a pseudo node insertion method is proposed to make DTCO solutions more efficient by improving the truck–drone synchronization operations. To this end, starting from a given routing solution, pseudo nodes are created at the point where a drone and a truck can meet simultaneously. We present a detailed method to calculate the location of the pseudo nodes and provide a detailed analysis of the conditions that allow us to reduce the travel completion time for different route patterns. Furthermore, we explore a variety of scenarios to illustrate the efficiency of the pseudo node insertion method for different DTCO problem solutions. An algorithm for the pseudo node insertion method is provided, and numerical examples are presented to discuss the efficacy and efficiency of the proposed approach.

A velocity-based moving mesh virtual element method

We present a velocity-based moving mesh virtual element method for the numerical solution of PDEs involving boundaries which are free to move. The virtual element method is used for computing both the mesh velocity and a conservative Arbitrary Lagrangian-Eulerian solution transfer on general polygonal meshes. The approach extends the linear finite element method to polygonal mesh structures, achieving the same degree of accuracy. In the context of moving meshes, a major advantage of the virtual element approach is the ease with which nodes can be inserted on mesh edges. Demonstrations of node insertion techniques are presented to show that moving polygonal meshes can be simply adapted for situations where a boundary encounters a solid object or another moving boundary, without reduction in degree of accuracy.

Node Insertion Algorithm and Ant Colony Optimization: Performance Review on Travelling Salesman Problem Paper for the Optimality of Network Topology

Node Insertion Algorithm and Ant Colony Optimization: Performance Review on Travelling Salesman Problem Paper for the Optimality of Network Topology

Adaptive meshfree method for fourth-order phase-field model of fracture using consistent integration schemes

An adaptive fourth-order phase-field model is proposed using consistent element-free Galerkin method (EFG). Convenient construction of high-order interpolation functions in EFG method is fully utilized. Requirement of C1 continuity of shape functions is satisfied in fourth-order phase-field model. Two different consistent integration schemes with high efficiency and high accuracy, namely quadratically consistent one-point integration scheme and three-point integration scheme, are employed to evaluate the fourth-order phase-field equation and displacement equation, respectively. To reduce computational cost, the adaptive strategy of local background mesh refinement is established on basis of strain energy history and phase field. Background mesh is refined via the insertion of nodes at the midpoints of each side of the integration element. Comparing with EFG method, computational accuracy and efficiency are enhanced by the proposed method. Load-displacement response, the smoothness of the resulting stress and crack paths are predicted well.

Efficient Node Insertion Algorithm for Connectivity-Based Multipolling MAC Protocol in Wi-Fi Sensor Networks

Since low-power Wi-Fi sensors are connected to the Internet, effective radio spectrum use is crucial for developing an efficient Medium Access Control (MAC) protocol for Wi-Fi sensor networks. A connectivity-based multipolling mechanism was employed for Access Points to grant uplink transmission opportunities to Wi-Fi nodes with a reduced number of multipolling frame transmissions. The existing connectivity-based multipolling mechanism in IEEE 802.11 wireless LANs with many nodes may require excessive time to derive the optimal number of serially connected sequences due to the backtracking algorithm based on the Traveling Salesman Problem model. This limitation hinders the real-time implementation of the connectivity-based multipolling mechanism in Wi-Fi sensor networks. In this study, an efficient node insertion algorithm is proposed, by which the number of derived serially connected multipolling sequences that cover nodes in Wi-Fi sensor networks converges to only one as the number of Wi-Fi sensors increases in Wi-Fi sensor networks. As verified by simulation experiments for Wi-Fi sensor networks, the proposed node insertion algorithm produces a near-optimal number of multipolling sequences that cover the nodes in Wi-Fi sensor networks. This study proposes a node insertion algorithm for the real-time implementation of the connectivity-based multipolling mechanism in MAC protocol for Wi-Fi sensor networks.

Crossing edge minimization in radial outerplanar layered graphs using segment paths

Crossing minimization is a natural problem in graph drawing, which consists of drawing it in the plane with a minimum number of crossings on the edges. We present an algorithm to minimize the crossing edges in radial layered graphs. The algorithm determines the optimal location of nodes in their corresponding circle layer and consists of two phases. In the first phase, a counterclockwise rotation of concentric circles is performed; in the next phase, edges are converted into segment paths. Unlike other algorithms with circular drawings, our algorithm does not require the insertion or removal of nodes and edges; only rotation and path construction operations are utilized. Two versions of the algorithm were created; the exhaustive version tests all the possible paths, while the random version tests a few number of paths. The goal is to minimize the crossing edges to obtain a clear visualization using three criteria: rotation, crossing edge detection and segment path construction. The algorithm has been successfully implemented in 30 instances of graphs with 20, 35 and 50 layers, where crossings are minimized in 86–93%, 93–96% and 95–97%, respectively.

Drain-to-Drain Abutment-Aware Detailed Placement Refinement for Power Staple Insertion Optimization

Power staple insertion is an effective means to mitigate IR drop in the advanced technology process. Previous works have shown that detailed placement refinement can greatly enhance the power staple insertion rate. However, with FinFET, it is necessary to consider the drain-to-drain abutment (DDA) constraints. We note that extra source node insertion for resolving DDA violations can interfere with power staple insertion. To handle DDA constraints and optimize power staple insertion at the same time, we formulate and solve a new DDA-aware placement refinement problem in this work. Given an initial nonoverlapping placement optimized for other conventional objectives, we compute a refined placement with cell shifting subject to DDA constraints such that the number of staple insertion slots can be maximized. An effective approach is proposed that supports a nonrestricted cell displacement range during placement refinement. It provides the flexibility to adjust the displacement bound of each cell dynamically in order to resolve all DDA violations. As a result, our algorithm guarantees that a placement solution with no DDA violation can always be computed without using a large displacement range for each cell which would require much longer runtime and larger average cell displacement. In addition to cell shifting, we incorporate concurrent cell flipping to reduce the required cell displacement to satisfy the DDA constraints and to facilitate power staple insertion. The experimental results showed the effectiveness of the proposed approach.

A note on improved results for one round distributed clique listing

In this note, we investigate listing cliques of arbitrary sizes in bandwidth-limited, dynamic networks. The problem of detecting and listing triangles and cliques was originally studied in great detail by Bonne and Censor-Hillel (ICALP 2019). We extend this study to dynamic graphs where more than one update may occur as well as resolve an open question posed by Bonne and Censor-Hillel (2019). Our algorithms and results are based on some simple observations about listing triangles under various settings and we show that we can list larger cliques using such facts. Specifically, we show that our techniques can be used to solve an open problem posed in the original paper: we show that detecting and listing cliques (of any size) can be done using O(1)-bandwidth after one round of communication under node insertions and node/edge deletions. We conclude with an extension of our techniques to obtain a small bandwidth 1-round algorithm for listing cliques when more than one node insertion/deletion and/or edge deletion update occurs at any time.

Efficient tooth gingival margin line reconstruction via adversarial learning

Gingival margin morphology plays an important role in the functional and aesthetic restoration of denture. However, this is a challenging task, mainly because there are great differences in the gingival margin morphology between different individuals and different dental positions. To address this problem, we present a deep adversarial network-driven gingival margin line reconstruction (GMLR) framework to automatically obtain the personalized gingival contour for a partially edentulous patient. Specifically, we first establish the training database by a visual distance-based orthogonal projection method to realize the bidirectional reversible mapping between three-dimensional gingival model and two-dimensional depth representation. Then, the GMLR network consists of a dual generator model and a two-scale discriminator model to avoid the loss of the gingival contour details. The proposed generator uses the global-to-local scheme to reconstruct clear gingival contour images in an end-to-end manner, while two-scale discriminator aims to guide the generator to produce a globally consistent gingival contour result with finer details. In addition, a comprehensive loss function is presented to combine gingival contour details, structure and perceptual features. Finally, we propose to reconstruct the personalized gingival line by the polygon-based node insertion and the feature line reconstruction method via the tangent constraint. Experimental results demonstrate that, under the same conditions, the proposed method outperforms recent advances on the real-world dental database. Importantly, the reconstructed missing GMLs are basically harmonious with the adjacent teeth and have enough anatomical morphology.

Adaptive grids for the estimation of dynamic models

This paper develops a method to flexibly adapt interpolation grids of value function approximations in the estimation of dynamic models using either NFXP (Rust, Econometrica: Journal of the Econometric Society, 55, 999–1033, 1987) or MPEC (Su & Judd, Econometrica: Journal of the Econometric Society, 80, 2213–2230, 2012). Since MPEC requires the grid structure for the value function approximation to be hard-coded into the constraints, one cannot apply iterative node insertion for grid refinement; for NFXP, grid adaption by (iteratively) inserting new grid nodes will generally lead to discontinuous likelihood functions. Therefore, we show how to continuously adapt the grid by moving the nodes, a technique referred to as r-adaption. We demonstrate how to obtain optimal grids based on the balanced error principle, and implement this approach by including additional constraints to the likelihood maximization problem. The method is applied to two models: (i) the bus engine replacement model (Rust, 1987), modified to feature a continuous mileage state, and (ii) to a dynamic model of content consumption using original data from one of the world’s leading user-generated content networks in the domain of music.

A Linear Time Solution to the Labeled Robinson-Foulds Distance Problem.

A large variety of pairwise measures of similarity or dissimilarity have been developed for comparing phylogenetic trees, for example, species trees or gene trees. Due to its intuitive definition in terms of tree clades and bipartitions and its computational efficiency, the Robinson–Foulds (RF) distance is the most widely used for trees with unweighted edges and labels restricted to leaves (representing the genetic elements being compared). However, in the case of gene trees, an important information revealing the nature of the homologous relation between gene pairs (orthologs, paralogs, and xenologs) is the type of event associated to each internal node of the tree, typically speciations or duplications, but other types of events may also be considered, such as horizontal gene transfers. This labeling of internal nodes is usually inferred from a gene tree/species tree reconciliation method. Here, we address the problem of comparing such event-labeled trees. The problem differs from the classical problem of comparing uniformly labeled trees (all labels belonging to the same alphabet) that may be done using the Tree Edit Distance (TED) mainly due to the fact that, in our case, two different alphabets are considered for the leaves and internal nodes of the tree, and leaves are not affected by edit operations. We propose an extension of the RF distance to event-labeled trees, based on edit operations comparable to those considered for TED: node insertion, node deletion, and label substitution. We show that this new Labeled Robinson–Foulds (LRF) distance can be computed in linear time, in addition of maintaining other desirable properties: being a metric, reducing to RF for trees with no labels on internal nodes and maintaining an intuitive interpretation. The algorithm for computing the LRF distance enables novel analyses on event-label trees such as reconciled gene trees. Here, we use it to study the impact of taxon sampling on labeled gene tree inference and conclude that denser taxon sampling yields trees with better topology but worse labeling. [Algorithms; combinatorics; gene trees; phylogenetics; Robinson–Foulds; tree distance.]

Evaluating sources of variability in inflorescence number, flower number and the progression of flowering in Sauvignon blanc using a Bayesian modelling framework

The time of flowering is key to understanding the development of grapevines. Flowering coincides with inflorescence initiation and fruit set, important determinants of yield. This research aimed to determine between and within-vine variability in 4-cane-pruned Sauvignon blanc inflorescence number per shoot, number of flowers per inflorescence and flowering progression using an objective method of assessing flowering via image capture and statistical analysis using a Bayesian modelling framework. The inflorescence number and number of flowers per inflorescence were measured by taking images over the flowering period. Flowering progression was assessed by counting open and closed flowers for each image over two seasons. An ordinal multinomial generalised linear mixed-effects model (GLMM) was fitted for inflorescence number, a Poisson GLMM for flower counts and a binomial GLMM for flowering progression. All the models were fitted and interpreted within a Bayesian modelling framework. Shoots arising from cane node one had lower numbers of inflorescences compared to those at nodes 3, 5 and 7, which were similar. The number of flowers per inflorescence was greater for basal inflorescences on a shoot than apical ones. Flowering was earlier, by two weeks, and faster in 2017/18 when compared to 2018/19 reflecting seasonal temperature differences. The time and duration of flowering varied at each inflorescence position along the cane. While basal inflorescences flowered later and apical earlier at lower insertion points on the shoot, the variability in flowering at each position on the vine dominated the date and duration of flowering.This is the first study using a Bayesian modelling framework to assess variability inflorescence presence and flower number, as well as flowering progression via objective quantification of open and closed flower counts rather than the more subjective method of visual estimation in the field or via cuttings. Although flower number differed for apical and basal bunches, little difference in timing and progression of flowering by these categories was observed. The node insertion point along a shoot was more important. Overall, the results indicate individual inflorescence variation and season are the key factors driving flowering variability and are most likely to impact fruit set and yield.

Virtual elements for sound propagation in complex poroelastic media

We develop a novel Virtual Element Method (VEM) to resolve the mixed Biot displacement-pressure formulation governing wave propagation in porous media. Within this setting, the weak form of the governing equations is discretized using implicitly defined canonical basis functions and the resulting integral forms are computed using appropriate polynomial projections. The projection operator accounting for the solid, fluid, and coupling phases of the problem are presented. Different boundary, interface and excitation conditions are accounted for. The convergence behaviour, accuracy, and efficiency of the method is examined through a set of illustrative examples. A node insertion strategy is proposed to resolve non-conforming interfaces that naturally arise in multilayered systems. Finally the power of the VEM is exploited to examine the acoustic response of composite materials with periodic and non-periodic inclusions of complex geometries.

Redefining the Graph Edit Distance

Graph edit distance has been used since 1983 to compare objects in machine learning when these objects are represented by attributed graphs instead of vectors. In these cases, the graph edit distance is usually applied to deduce a distance between attributed graphs. This distance is defined as the minimum amount of edit operations (deletion, insertion and substitution of nodes and edges) needed to transform a graph into another. Since now, it has been stated that the distance properties have to be applied [(1) non-negativity (2) symmetry (3) identity and (4) triangle inequality] to the involved edit operations in the process of computing the graph edit distance to make the graph edit distance a metric. In this paper, we show that there is no need to impose the triangle inequality in each edit operation. This is an important finding since in pattern recognition applications, the classification ratio usually maximizes in the edit operation combinations (deletion, insertion and substitution of nodes and edges) that the triangle inequality is not fulfilled.

Sublinear update time randomized algorithms for dynamic graph regression

A well-known problem in data science and machine learning is linear regression, which is recently extended to dynamic graphs. Existing exact algorithms for updating the solution of dynamic graph regression require at least a linear time (in terms of n: the size of the graph). However, this time complexity might be intractable in practice.In the current paper, we utilize subsampled randomized Hadamard transformand CountSketchto propose the first sublinear update time randomized algorithms for regression of general dynamic graphs. Suppose that we are given a n×d matrix embedding M of the graph, where d≪n and M has certain properties. Let r be the number of samples required by subsampled randomized Hadamard transform for a 1±ϵ approximation, which is a sublinear of n. Our first algorithm supports edge insertion and edge deletion and updates the approximate solution in O(rd) time. Our second algorithm is based on CountSketchand supports edge insertion, edge deletion, node insertion and node deletion. It updates the approximate solution in O(qd) time, where q=O(d2ϵ2log6(d/ϵ)).

New and improved algorithms for unordered tree inclusion

The tree inclusion problem is, given two node-labeled trees P and T (the “pattern tree” and the “target tree”), to locate every minimal subtree in T (if any) that can be obtained by applying a sequence of node insertion operations to P. Although the ordered tree inclusion problem is solvable in polynomial time, the unordered tree inclusion problem is NP-hard. The currently fastest algorithm for the latter is a classic algorithm by Kilpeläinen and Mannila from 1995 that runs in O(d22dmn) time, where m and n are the sizes of the pattern and target trees, respectively, and d is the degree of the pattern tree. Here, we develop a new algorithm that runs in O(d2dmn2) time, improving the exponential factor from 22d to 2d by considering a particular type of ancestor-descendant relationships that is suitable for dynamic programming. We also study restricted variants of the unordered tree inclusion problem.

Influence of the compensation method of machining errors of Bspline and Cspline

ABSTRACT Contemporary advances in manufacturing are moving towards the diversification of interpolation methods in Computer Aided Manufacturing (CAM) softwares thanks to the growing need of free-forms of high quality. New interpolations such as ‘Bspline’ and ‘Cspline’ provide accurate toolpaths, but they generate significant machining errors. The nodes insertion technique is one of compensation methods of those errors. This paper presents a study of the influence of this compensation method on the manufacturing process: dynamic behavior of machine-tools, errors of controller, and surface quality. To make this study, Bspline and Cspline interpolations, errors generated, and the compensation method are defined. In addition to that, feed rate, cycle time and roughness before and after compensation are measured in order to exanimate the impact of the nodes insertion method. The present work aims to deliver a framework that demonstrates how manufacturing companies with such specific parameters optimization can improve smartness and machining efficiency.