Fill Algorithm Research Articles

Design and Implementation of Flood Fill and Pledge Algorithm for Maze Robot

Design and Implementation of Flood Fill and Pledge Algorithm for Maze Robot

A Fast 3D Brain Extraction and Visualization Framework Using Active Contour and Modern OpenGL Pipelines

Brain extraction is a process of removing non-brain tissue in the brain magnetic resonance (MR) images and serves as a first step towards more delicate brain segmentation. Although many brain extraction methods have been proposed in the literature, most of them are either laborious or time consuming, and lack of instant visualization. This leads to a time lag between image acquisition and comprehensive visualization. Especially for intraoperative image based neurosurgery navigation, the time lag from image acquisition to brain visualization should be reduced as much as possible. In this paper, we propose an end-to-end fast brain extraction and visualization framework. The input is a T1-weighted MR volume and the output is comprehensive brain visualization. An improved brain extraction tool (BET) algorithm is proposed to evolve a 3D active mesh model to fit the brain surface in the 3D image. Then the brain mask is generated per slice using a polygon fill algorithm. At last, a ray-casting volume rendering algorithm is used to visualize the brain surface with the help of the generated mask. All the operations are performed using the modern OpenGL pipelines running on a graphics processing unit (GPU). Experiments were performed on two publicly available datasets and one clinical dataset to compare our method with five state-of-the-art methods including the original BET in terms of segmentation accuracy and time cost. Our method achieved mean Dice coefficients of 96.8%, 97.1%, 98.5% and mean time cost of 361 ms, 341 ms, 502 ms on the three datasets, outperforming all the other methods.

ARU-Net: Research and Application for Wrist Reference Bone Segmentation

Due to the influence of the irregular shapes and the adjacent positions of the wrist reference bones, it is difficult for the expert to accurately estimate the mature indication of the wrist reference bones of the minor. How to precisely segment the reference bones of the minor is a challenge. For this problem, the ARU-Net for wrist reference bone segmentation is proposed. First, we extract the reference bone ROI by Faster R-CNN. Then, the pre-processed ROI is fed into ARU-Net for segmentation. On the basis of traditional U-Net, ARU-Net adds residual mapping and attention mechanism, which improves the utilization rate of features and the accuracy of reference bone segmentation. Finally, a post-processing method including the flood fill algorithm and the morphological operation is used to eliminate jagged edges and holes in the segmented result. The hamate is one of the most difficult reference bones to segment in the wrist. This paper takes it as an example to assess the performance of ARU-Net. Experiments show that compared with FCN, U-Net and ResUnet, the accuracy and F1 scores of ARU-Net are higher. The accuracy rate is 96.4%, and the F1 score is 0.953. The post-processing method can further improve the result. Finally, the accuracy rate reaches 96.5%, and the F1 score reaches 0.954. In order to verify the segmentation stability of ARU-Net, it is also applied to the segmentation of the radius and the capitate. RU-Net can precisely segment the reference bone, which facilitates the expert to assess its mature indication, so as to accurately evaluate the bone age.

A Sphere Filling Algorithm for Irregular Aggregate Particle Generation based on Nonlinear Optimization Method

The angularity of particles has important effects on the mechanical properties of asphalt mixture and other granular materials. To simulate these effects, the glue-sphere method was usually used to create an arbitrary polyhedron particle. Unlike other studies, this paper aims to efficiently fill a polyhedron with as few spheres as possible through optimization technology in order to reduce the cost of calculation during mixture simulation. Four contents are mainly discussed here: a) how to produce non-spherical aggregates and control their sizes with the minimal bounding box; b) how to fill convex non-spherical particles with the fewest balls as possible using the constrained nonlinear optimization method; c) how to compute the typical shape factors of these particles; and d) how the control parameters affect the filling effect. The algorithm for this study was programmed by MATLAB software and was proven to have better filling performance and less computational cost compared to other methods.

Optimal distribution of Plug-In-Electric Vehicle’s storage capacity using Water Filling Algorithm for load flattening and vehicle prioritization using ANFIS

Ever increasing Plug-In Electric Vehicles (PEVs) can be considered as mobile storage units and can be exploited for grid ancillary services such as frequency support, voltage regulation and to support to intermittent renewable sources. However, available PEV power is limited by battery State-of-Charge (SoC) and customer flexibility. Smart charging control strategies are required in order to maximize PEV storage utilization. In this article, a new control strategy is developed to achieve flat load profile and to minimize the cost of charging. Both utility and customer benefits are given equal importance while utilizing PEV’s storage for load flattening. Water Filling Algorithm (WFA) is used to distribute available PEV energy which in turn helps in the effective day-ahead scheduling of PEVs. Minimization of the cost of charging and maximization of PEV power usage has been accomplished by Adaptive Neuro-Fuzzy Inference System (ANFIS). ANFIS is trained to prioritize vehicles based on both utility and customer perspectives simultaneously. The impact of ANFIS prioritization on aggregate PEVs power availability and load flattening at a given time is studied. Also, the role of WFA in the prior scheduling of PEVs on load flattening is analyzed. Danish power grid data is used to implement the proposed control strategy in a residential distribution network. Due to the active power transactions between PEV and grid, the bus voltages are maintained within limits without using additional control for voltage regulation.

An efficient algorithm for the calculation of sub-grid distances for higher-order LBM boundary conditions in a GPU simulation environment

This paper presents a new and efficient algorithm for the calculation of sub-grid distances in the context of a lattice Boltzmann method (LBM). LBMs usually operate on equidistant Cartesian grids and represent moving geometries by either using immersed boundary conditions or dynamic fill algorithms in combination with slip or no-slip boundary conditions. In order to obtain sufficiently high geometric accuracy, the sub-grid distances from Eulerian fluid nodes on uniform and structured grids to a tessellated triangular surface mesh have to be calculated. The proposed algorithm extends a previously published grid generation procedure by an efficient calculation of sub-grid distances. The algorithm is optimized for massively parallel execution on graphics processing units (GPUs). Based on a linearized representation of the obstacle surface, surface normal vectors are computed and stored, which then serve to compute the sub-grid distances. This saves GPU memory, re-uses information that is available from the surface voxelization step, and has shown to be very accurate and efficient for the implementation in a state-of-the-art LBM-GPU solver.

An industrial facility layout design method considering energy saving based on surplus rectangle fill algorithm

The facility layout design within a plant is a key step in the process of chemical engineering design. A good layout can save capital cost, energy and natural resource. The aim of this work is to determine the relative location of facilities in a large-scale industrial plant considering multi-floor structure to make the total cost minimum. The objective function consists of piping investment cost, pump power cost, land cost, and floor construction cost. Surplus rectangle fill algorithm is applied in this work, and it is combined with a genetic algorithm to obtain the optimal solution. Constraints of pump area, joint arrangement of heat exchangers, and the cross-floor facilities are also taken into consideration. In the case study, a plant from a real refinery including 217 facilities is designed with different floor number. The comparison of the three different conditions proves the important role of floor number in the trade-off among investment cost, energy consumption, and land resource. The case illustrates that, the proposed method can generate a reasonable layout design for the industrial facilities and save capital and operating cost effectively. A sensitivity analysis is also done to explore the influence of basic data on the optimal construction structure.

CFD study on laminar mixing at a very low Reynolds number by pitching and heaving a square cylinder

In this work, CFD is used to show how the combined motion of heaving and pitching a 2D square cylinder located in the middle of the channel can be used to enhance mixing of two fluids flowing at a very low Reynolds number along a rectangular channel. Both type of motions are applied and enforced with a phase difference at the same time, but at difference frequencies and amplitudes, in order to see if mixing efficiency can be enhance. The characteristics of five governing input parameters and output results are examined. The input parameters consist of two frequencies, one for heaving and one for pitching, and two amplitudes, one for heaving and one for pitching. The output results are mixing efficiency, input power coefficient and mixing energy cost. The Optimal Space Filling algorithm is used to generate 60 different combinations of the input parameters which are used in the numerical studies. Different response surfaces of the output parameters are obtained. It is noted that certain combinations of the input parameters produce the highest mixing efficiency (around 55%), the lowest input power coefficient (around 260 units) or the lowest mixing energy cost (around 13 units) are found. On the other hand a multi-objective optimisation is also carried out in order to find the input parameters that give rise to the highest possible mixing efficiency with lowest possible input power coefficient. A set of optimal solutions leading to Pareto Front is obtained which shows the trade-off between the objectives. Three potential optimal candidates are proposed in this paper.

Segmenting overlapping nano-objects in atomic force microscopy image

Recently, techniques for nanoparticles have rapidly been developed for various fields, such as material science, medical, and biology. In particular, methods of image processing have widely been used to automatically analyze nanoparticles. A technique to automatically segment overlapping nanoparticles with image processing and machine learning is proposed. Here, two tasks are necessary: elimination of image noises and action of the overlapping shapes. For the first task, mean square error and the seed fill algorithm are adopted to remove noises and improve the quality of the original image. For the second task, four steps are needed to segment the overlapping nanoparticles. First, possibility split lines are obtained by connecting the high curvature pixels on the contours. Second, the candidate split lines are classified with a machine learning algorithm. Third, the overlapping regions are detected with the method of density-based spatial clustering of applications with noise (DBSCAN). Finally, the best split lines are selected with a constrained minimum value. We give some experimental examples and compare our technique with two other methods. The results can show the effectiveness of the proposed technique.

QoE‐Aware Scheduling Algorithm for Adaptive HTTP Video Delivery in Wireless Networks

In the last years, the video content consumed by mobile users has increased exponentially. Since mobile network capacity cannot be increased as fast as required, it is crucial to develop intelligent schedulers that allocate radio resources very efficiently and are able to provide a high Quality of Experience (QoE) to most of the users. This paper proposes a new and effective scheduling solution—the Maximum Buffer Filling (MBF) algorithm—which aims to increase the number of satisfied users in video streaming services provided by wireless networks. The MBF algorithm uses the current buffer level at the client side and the radio channel conditions, which are reported to the network by the client, as well as the bitrate of the requested video segment. The proposed scheduling strategy can also fulfill different satisfaction criteria, since it can be tuned to maximize the numbers of users with high QoE levels or to minimize the number of users with low QoE levels. A simulation framework was developed, considering a Long Term Evolution (LTE) scenario, in order to assess the performance of the proposed scheduling scheme and to compare it with other well‐known scheduling solutions. The results show the superior performance achieved by the proposed technique, in terms of the number of satisfied and unsatisfied users.

Efficient image compression and decompression algorithms for OCR systems

This paper presents an efficient new image compression and decompression methods for document images, intended for usage in the pre-processing stage of an OCR system designed for needs of the ?Nikola Tesla Museum? in Belgrade. Proposed image compression methods exploit the Run-Length Encoding (RLE) algorithm and an algorithm based on document character contour extraction, while an iterative scanline fill algorithm is used for image decompression. Image compression and decompression methods are compared with JBIG2 and JPEG2000 image compression standards. Segmentation accuracy results for ground-truth documents are obtained in order to evaluate the proposed methods. Results show that the proposed methods outperform JBIG2 compression regarding the time complexity, providing up to 25 times lower processing time at the expense of worse compression ratio results, as well as JPEG2000 image compression standard, providing up to 4-fold improvement in compression ratio. Finally, time complexity results show that the presented methods are sufficiently fast for a real time character segmentation system.

Design and Implementation of Swam Robotics using Flood Fill Algorithm

<p>Swam Intelligence provides a basis with which it is possible to explore collective (or distributed) problem solving without centralized control or the provision of a global model. This paper presents design and implementation of swam robotics in a multi-agent environment. At the beginning, robot agents are ignorant of the maze. The robots are programmed with Flood fill algorithm to solve maze. The robot scans maze and stores the values in EEPROM. The robot agent shares the information to other robot agents through wireless communication. The proposed flood fill algorithm is found to be effective tool for solving maze of moderate size.</p>

Generalized N-way iterative scanline fill algorithm for real-time applications

A generalized iterative scanline fill algorithm intended for use in real-time applications and its highly optimized machine code implementation are presented in this paper. The algorithm uses the linear image representation in order to achieve the fast memory access to the pixel intensity values. The usage of the linear image representation is crucial for achieving the highly optimized low-level machine code implementation. A few generalization features are also proposed, and discussion about the possible real-time applications is given. The proposed efficient machine code implementation is tested on several PC machines, and a set of numerical results is provided. The machine routine is compared with standard and optimized implementations of the 4-way flood fill algorithm and scanline fill algorithm. The machine code implementation performs approximately 2 times faster than the optimized scanline fill algorithm implementation and 6 times faster than standard iterative scanline fill algorithm implementation on two-dimensional image data structure. Furthermore, the machine routine proved to perform even more than 15 times faster than the optimized flood fill algorithm implementations. Provided results prove the efficiency of the proposed generalized scanline fill algorithm and its advantage over the state-of-the-art algorithms, and clearly show that optimized machine routine is capable of performing the real-time tasks.

Optimization Approach of the Vehicle Routing Problem with Packing Constraints Using Genetic Algorithm

Vehicle Routing Problem is an issue in item delivery from depot to its customers using several vehicles which have limited capacity with a purpose to minimize transportation cost. The packing constraints exist because the vehicles which are usually used in item delivery have rectangular-box shaped container. Also, the items are commonly in shape of rectangular-box. Therefore, packing or loading method is needed so that containers could load all of the items without causing damage and could ease unloading process. The purpose of this final project is to develop a model and algorithm using metaheuristics method, especially genetics algorithm in order to minimize total delivery distance. A hybrid genetics algorithm and bottom-left fill algorithm also take place to solve the packing process. This algorithm delivered average solution 0.08% worse than ant colony optimization, but had 2.93% better solution than tabu search.

In middle-aged and old obese patients, training intervention reduces leptin level: A meta-analysis.

BackgroundLeptin is one of the major adipokines in obesity that indicates the severity of fat accumulation. It is also an important etiological factor of consequent cardiometabolic and autoimmune disorders. Aging has been demonstrated to aggravate obesity and to induce leptin resistance and hyperleptinemia. Hyperleptinemia, on the other hand, may promote the development of age-related abnormalities. While major weight loss has been demonstrated to ameliorate hyperleptinemia, obese people show a poor tendency to achieve lasting success in this field. The question arises whether training intervention per se is able to reduce the level of this adipokine.ObjectivesWe aimed to review the literature on the effects of training intervention on peripheral leptin level in obesity during aging, in order to evaluate the independent efficacy of this method. In the studies that were included in our analysis, changes of adiponectin levels (when present) were also evaluated.Data sources3481 records were identified through searching of PubMed, Embase and Cochrane Library Database. Altogether 19 articles were suitable for analyses.Study eligibility criteriaEmpirical research papers were eligible provided that they reported data of middle-aged or older (above 45 years of age) overweight or obese (body mass index above 25) individuals and included physical training intervention or at least fitness status of groups together with corresponding blood leptin values.Statistical methodsWe used random effect models in each of the meta-analyses calculating with the DerSimonian and Laird weighting methods. I-squared indicator and Q test were performed to assess heterogeneity. To assess publication bias Egger’s test was applied. In case of significant publication bias, the Duval and Tweedie's trim and fill algorithm was used.ResultsTraining intervention leads to a decrease in leptin level of middle-aged or older, overweight or obese male and female groups, even without major weight loss, indicated by unchanged serum adiponectin levels. Resistance training appears to be more efficient in reducing blood leptin level than aerobic training alone.ConclusionsPhysical training, especially resistance training successfully reduces hyperleptinemia even without diet or major weight loss.

Digital Material Representation Model of Porous Microstructure Based on 3D Reconstruction Algorithm

AbstractDevelopment of the Digital Material Representation (DMR) model, based on 3D reconstruction algorithm and serial sectioning, is the main goal of the present paper. Details on the serial sectioning and image processing algorithms are presented first. Serial sectioning is realized on the basis of light microscopy (LM). Then concept of 3D reconstruction and developed algorithms are presented. Two approaches, based on shape coefficients and the flood fill algorithms, are developed to identify corresponding features on subsequent 2D images. Then, the interpolation algorithm to reconstruct 3D volume between 2D images is presented. Finally, obtained 3D model is an input for finite element mesh generation software for subsequent finite element calculations.

A projection matrix design method for MSE reduction in adaptive compressive sensing

In adaptive compressive sensing, measurement matrix is adaptively designed to recover the sparse signal. After the support of the sparse signal is recovered, the projection measurement is designed to reduce the mean squared error of the estimated sparse signal. This paper proposes a projection matrix design method using the support set of the sparse signal estimated via previous measurements. The projection matrix design problem is formulated as an optimization problem, which minimizes the mean squared error of the estimated sparse signal with the energy of the projection matrix being constrained. A water filling like algorithm is proposed to solve the optimization problem. It is proved that the Water Filling algorithm gives the globally optimal solution once the sufficient condition is satisfied. A method is given to check whether the result given by the Water Filling algorithm is globally optimal or not. Numerical experiments demonstrate the effectiveness of the designed algorithm.

Advanced Radio Resource Scheduling Algorithm for Energy Efficient Cellular Base Station

This work is to introduce an advanced calculation to enhance the energy efficiency of the radio base station for MU-MIMO-OFDM framework. Advanced Radio Resource Scheduling (ARRS) is introduced. Power utilization is considered a standout amongst the most imperative parts of the research for the wireless network. In view of the increasing mindfulness for saving the earth, and to give green frameworks. The calculations fundamentally divided into two phases. First, it discovers the resource shares, and the number of dynamic antennas in light of channel state based on essential Resource Allocations as Bandwidth Adaptation (BA) and Discontinuous Transmission (DTX). Secondly, it applies the Amplitude Carving Greedy (ACG) and Inverse Water Filling (IWF) Algorithms for the ARRS. Which finds the ideal number of resource blocks allocated to every client in view of the wanted rates, and the number of dynamic receiving antennas that maximize the utilization of base station power for the time changing frequency selective channel. The results illustrate that the proposed ARRS Algorithm is giving an upgrade in the diminishment of the supply power utilization from 10% in low rates up to 17% in high rates, compared with essential asset designation for RAPS calculations.

RANCANG BANGUN MOBILE ROBOT MICROMOUSE UNTUK PENCARIAN RUTE TERPENDEK MENGGUNAKAN ALGORITMA FLOOD FILL

Mobile robot merupakan salah satu jenis robot yang banyak digunakan dalam membantu pekerjaan manusia. Mobile robot micromouse adalah salah satu jenis robot yang dibuat agar dapat mencari rute terpendek dalam sebuah labirin atau maze. Algoritma flood fill merupakan salah satu cara untuk mencari rute terpendek dengan melakukan maze mapping, dimana robot akan membandingkan nilai dari setiap cell dan bergerak menuju cell terkecil. Dalam penelitian yang dilakukan, mobile robot micromouse dirancang menggunakan Sensor Ultrasonic PING untuk mendeteksi halangan dan Arduino Uno yang akan mengontrol pergerakan dari motor DC. Robot akan mencari rute terpendek berdasarkan maze mapping yang telah dilaluinya. Robot diujikan pada 3 buah labirin atau maze, dimana setiap labirin atau maze dilakukan 10 kali pengujian dan diperoleh keberhasilan sebesar 80% pada maze 1, pada maze 2 sebesar 70% dan pada maze 3 sebesar 70%.

분해모델과 구멍 메움 알고리즘을 이용한 냉장고 내부 용적의 자동 계산

분해모델과 구멍 메움 알고리즘을 이용한 냉장고 내부 용적의 자동 계산