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EUROPHYSICS LETTERS 2003年第2期62卷 189-195页

作者： Fukuda, K Amaral, LAN Stanley, HE Boston Univ Ctr Polymer Studies Boston MA 02215 USA Boston Univ Dept Phys Boston MA 02215 USA NTT Corp Network Innovat Labs Tokyo 1808585 Japan Northwestern Univ Dept Chem Engn Evanston IL 60208 USA

The Internet is a world-wide communication network, whose optimization depends on the knowledge of the statistical characterization of the aggregated traffic flow. Internet traffic is dependent on a number off actors, including communication protocols, network topology, and human behavior. Using a recently proposed segmentation algorithm, we find a surprising analogy between the nonstationarity and the correlations in the communication dynamics in the Internet and in another communication network of great interest: the autonomic nervous system (ANS). The ANS controls involuntary muscle motion, secreting glands, and the heart, hence, we surmise that the time interval between successive heartbeats-an easily measured physiological signal-provides a probe of the communication dynamics for the ANS. We find quantitative similarities between the statistical properties of i) healthy heart rate variability and non-congested Internet traffic, and ii) diseased heart rate variability and congested Internet traffic. Our findings suggest that the understanding of the mechanisms underlying the "human-made" Internet could help to understand the "natural" network that controls the heart.

关键词： .interval ndings communication network time series segmentation algorithm EUROPHYSICS Similarities communication dynamics Internet traffic ANS healthy heart congested

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Heuristic segmentation of a nonstationary time series

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Physical Review E 2004年第2期69卷 021108-021108页

作者： Kensuke Fukuda H. Eugene Stanley Luís A. Nunes Amaral NTT Network Innovation Laboratories Tokyo 180-8585 Japan Center for Polymer Studies and Department of Physics Boston University Boston Massachusetts 02215 USA Department of Chemical and Biological Engineering Northwestern University Evanston Illinois 60208 USA

Many phenomena, both natural and human influenced, give rise to signals whose statistical properties change under time translation, i.e., are nonstationary. For some practical purposes, a nonstationary time series can be seen as a concatenation of stationary segments. However, the exact segmentation of a nonstationary time series is a hard computational problem which cannot be solved exactly by existing methods. For this reason, heuristic methods have been proposed. Using one such method, it has been reported that for several cases of interest—e.g., heart beat data and Internet traffic fluctuations—the distribution of durations of these stationary segments decays with a power-law tail. A potential technical difficulty that has not been thoroughly investigated is that a nonstationary time series with a (scalefree) power-law distribution of stationary segments is harder to segment than other nonstationary time series because of the wider range of possible segment lengths. Here, we investigate the validity of a heuristic segmentation algorithm recently proposed by Bernaola-Galván et al. [Phys. Rev. Lett. 87, 168105 (2001)] by systematically analyzing surrogate time series with different statistical properties. We find that if a given nonstationary time series has stationary periods whose length is distributed as a power law, the algorithm can split the time series into a set of stationary segments with the correct statistical properties. We also find that the estimated power-law exponent of the distribution of stationary-segment lengths is affected by (i) the minimum segment length and (ii) the ratio R≡σε/σx¯, where σx¯ is the standard deviation of the mean values of the segments and σε is the standard deviation of the fluctuations within a segment. Furthermore, we determine that the performance of the algorithm is generally not affected by uncorrelated noise spikes or by weak long-range temporal correlations of the fluctuations within segments.

关键词： .tail heuristic investigate durations reason time series statistical properties stationary segments decays power-law segment lengths segmentation algorithm surrogate

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A mean shift segmentation scheme using several pixel characteristics

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COMPUTERS & ELECTRICAL ENGINEERING 2021年 90卷 107022-107022页

作者： Cuevas, Erik Galvez, Jorge Avalos, Omar Chavarin, Angel Univ Guadalajara Dept Elect CUCEI Av Revolucion 1500 Guadalajara 44430 Jalisco Mexico

In this paper, a new segmentation method based on the mean shift (MS) algorithm is presented. The proposed approach divides the image into two sets of pixels: operative elements and inactive elements. In its first phase, the MS scheme considers only the operative elements. In its second stage, the results obtained by the MS method with the operative data are used to include the inactive data. During this stage, each inactive pixel is assigned to the cluster corresponding to the nearest operative pixel. As a final operation, clusters that maintain the minimal number of elements are blended with other nearby clusters. Our method has been tested against other current segmentation methods using test images extracted from the Berkley dataset. Numerical experiments demonstrate that our approach exhibits better performance in terms of consistency, quality, velocity and accuracy.

关键词： segmentation algorithm Mean shift method Non-local mean Kernel density estimator (KDE) Clustering methods

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Automated Tracing of Horizontal Neuron Processes During Retinal Development

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NEUROCHEMICAL RESEARCH 2011年第4期36卷 583-593页

作者： Kerekes, Ryan A. Martins, Rodrigo A. P. Davis, Denise Karakaya, Mahmut Gleason, Shaun Dyer, Michael A. Oak Ridge Natl Lab Measurement Sci & Syst Engn Div Oak Ridge TN 37831 USA Univ Fed Rio de Janeiro Inst Biofis Carlos Chagas Filho CCS BR-21941900 Rio De Janeiro Brazil St Jude Childrens Hosp Dept Dev Neurobiol Memphis TN 38105 USA Univ Tennessee Dept Comp Sci & Elect Engn Knoxville TN 37996 USA Univ Tennessee Hlth Sci Ctr Dept Ophthalmol Memphis TN 38105 USA Johns Hopkins Univ Sch Med Howard Hughes Med Inst Baltimore MD 21205 USA

In the developing mammalian retina, horizontal neurons undergo a dramatic reorganization of their processes shortly after they migrate to their appropriate laminar position. This is an important process because it is now understood that the apical processes are important for establishing the regular mosaic of horizontal cells in the retina and proper reorganization during lamination is required for synaptogenesis with photoreceptors and bipolar neurons. However, this process is difficult to study because the analysis of horizontal neuron anatomy is labor intensive and time-consuming. In this paper, we present a computational method for automatically tracing the three-dimensional (3-D) dendritic structure of horizontal retinal neurons in two-photon laser scanning microscope (TPLSM) imagery. Our method is based on 3-D skeletonization and is thus able to preserve the complex structure of the dendritic arbor of these cells. We demonstrate the effectiveness of our approach by comparing our tracing results against two sets of semi-automated traces over a set of 10 horizontal neurons ranging in age from P1 to P5. We observe an average agreement level of 81% between our automated trace and the manual traces. This automated method will serve as an important starting point for further refinement and optimization.

关键词： Horizontal retinal neuron Retinal development Automated tracing segmentation algorithm

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EXAMPLE COMPUTER LOGIC GRAPH AND ITS PARTITIONS AND MAPPINGS

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IEEE TRANSACTIONS ON COMPUTERS 1974年第11期C 23卷 1198-1204页

作者： MENNONE, A RUSSO, RL IBM THOMAS J WATSON RES CTRYORKTOWN HEIGHTSNY 10598

The purpose of this correspondence is to provide an example computer logic graph and data concerning various partitions and mappings of this graph. This information should be of particular interest to those workers who are developing partitioning and mapping algorithms, since it provides a means to test and compare alternative methods. It should also be of use to those interested in other algorithms (e.g., placement, diagramming, grouping, etc.) for logic graphs.

关键词： Computer Aided Design Computer Based Design Computer Logic Graph Design Automation Heuristic algorithm Logic Mapping Logic Partitioning Logic segmentation Mapping algorithm Partitioning algorithm segmentation algorithm

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An in-depth automated approach for fish disease recognition

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JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES 2022年第9期34卷 7174-7183页

作者： Mia, Md. Jueal Bin Mahmud, Rafat Sadad, Md. Safein Al Asad, Hafiz Hossain, Rafat Daffodil Int Univ Dept Comp Sci & Engn Dhaka Bangladesh Hajee Mohammad Danesh Sci & Technol Univ Fac Fisheries Rangpur Bangladesh

Fish plays a significant role in food and nutritional security in our country as well as the whole world. Owing to this reason, it becomes essential to increase the production of fish. But it is diminishing due to numerous diseases which can deteriorate the national economy. It is a fact that there is no single effec-tive research work that has been done in regards to fish disease due to a lack of data and a high level of expertise. Consequently, our aim is to recognize the fish disease effectively that can help the remote farmers who need proper support for fish farming. Recognition of disease-attacked fish at an early stage can help us take necessary steps to prevent from spreading of the disease. In this work, we have per-formed an in-depth analysis of expert systems that can continue with an image captured with the help of smartphones and identifies the disease. Two set of features is selected then a segmentation algorithm is employed to detect the disease attacked portion from the disease-free portion. Furthermore, eight prominent classification algorithms are implemented accordingly to measure the performance using per-formance evaluation matrices. The achieved accuracy of Random forest 88.87% which is promising enough.(c) 2022 The Authors. Published by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).

关键词： Fish disease Recognition Expert system segmentation algorithm Classification Evaluation matrices

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Lung segmentation on standard and mobile chest radiographs using oriented Gaussian derivatives filter

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BIOMEDICAL ENGINEERING ONLINE 2015年第1期14卷 1-26页

作者： Ahmad, Wan Siti Halimatul Munirah Wan Zaki, W. Mimi Diyana W. Fauzi, Mohammad Faizal Ahmad Multimedia Univ Fac Engn Persiaran Multimedia Cyberjaya Selangor Malaysia Univ Kebangsaan Malaysia Fac Engn & Built Environm Dept Elect Elect & Syst Engn Bangi 43600 Selangor Malaysia

Background: Unsupervised lung segmentation method is one of the mandatory processes in order to develop a Content Based Medical Image Retrieval System (CBMIRS) of CXR. The purpose of the study is to present a robust solution for lung segmentation of standard and mobile chest radiographs using fully automated unsupervised method. Methods: The novel method is based on oriented Gaussian derivatives filter with seven orientations, combined with Fuzzy C-Means (FCM) clustering and thresholding to refine the lung region. In addition, a new algorithm to automatically generate a threshold value for each Gaussian response is also proposed. The algorithms are applied to both PA and AP chest radiographs from both public JSRT dataset and our private datasets from collaborative hospital. Two pre-processing blocks are introduced to standardize the images from different machines. Comparisons with the previous works found in the literature on JSRT dataset shows that our method gives a reasonably good result. We also compare our algorithm with other unsupervised methods to provide fairly comparative measures on the performances for all datasets. Results: Performance measures (accuracy, F-score, precision, sensitivity and specificity) for the segmentation of lung in public JSRT dataset are above 0.90 except for the overlap measure is 0.87. The standard deviations for all measures are very low, from 0.01 to 0.06. The overlap measure for the private image database is 0.81 (images from standard machine) and 0.69 (images from two mobile machines). The algorithm is fully automated and fast, with the average execution time of 12.5 s for 512 by 512 pixels resolution. Conclusions: Our proposed method is fully automated, unsupervised, with no training or learning stage is necessary to segment the lungs taken using both a standard machine and two different mobile machines. The proposed pre-processing blocks are significantly useful to standardize the radiographs from mobile machines. The algori

关键词： Chest radiograph Unsupervised lung segmentation Fuzzy C-means Thresholding Gaussian derivatives Medical image processing segmentation algorithm

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A Laser Scanner Point Cloud Registration Method Using Difference of Normals (DoN) Based segmentation

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LASERS IN ENGINEERING 2022年第1-2期53卷 87-103页

作者： Lyu, J-H Wang, Z-W Zhou, Y. Meng, J. Wang, S-F Changchun Univ Sci & Technol Natl Demonstrat Ctr Expt Optoelect Engn Educ Sch Optoelect Engn 7089 Weixing Rd Changchun 130022 Jilin Peoples R China Changchun Univ Sci & Technol Key Lab Optoelect Measurement & Opt Informat Tran Minist Educ Sch Optoelect Engn 7089 Weixing Rd Changchun 130022 Jilin Peoples R China

The coarse registration is required before fine registration to obtain a better initial pose;however, it is difficult for coarse registration to obtain a better initial pose when the overlapping coefficient of source and target point cloud is low. To overcome this we propose a registration method using difference of normals (DoN) based segmentation algorithm and sample consensus initial alignment algorithm. First, the DoN based segmentation algorithm is employed to segment areas where obvious normal differences from source and target point cloud. Afterwards, Gaussian models for these subsets are established to find a pair of point cloud subsets with the most similar distribution. Then the sample consensus initial alignment algorithm (SAC-IA) is employed to register the matched subsets to obtain transformations between them, applied to source point cloud to find a better initial pose. Eventually, the iterative closest point (ICP) algorithm is involved to complete the registration. The experiments show the root mean square error (RMSE) of the registered point cloud using proposed method has been improved by 0.435 m compared with that of previous algorithm when the overlapping coefficient is 5%. The analysis shows the segmented region has clearer normal features;consequently, the SAC-IA algorithm to extract a more effective feature histogram to obtain a more accurate transformation.

关键词： Laser scanner point cloud registration iterative closest point (ICP) algorithm difference of normals (DoN) segmentation algorithm sample consensus initial alignment algorithm (SAC-IA)

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Segmentor3IsBack: an R package for the fast and exact segmentation of Seq-data

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algorithmS FOR MOLECULAR BIOLOGY 2014年第1期9卷 6-6页

作者： Cleynen, Alice Koskas, Michel Lebarbier, Emilie Rigaill, Guillem Robin, Stephane AgroParisTech UMR 518 F-75231 Paris 05 France INRA UMR 518 F-75231 Paris 05 France Univ Evry Val dEssonne CNRS INRA URGV F-91057 Evry France

Background: Change point problems arise in many genomic analyses such as the detection of copy number variations or the detection of transcribed regions. The expanding Next Generation Sequencing technologies now allow to locate change points at the nucleotide resolution. Results: Because of its complexity which is almost linear in the sequence length when the maximal number of segments is constant, and as its performance had been acknowledged for microarrays, we propose to use the Pruned Dynamic Programming algorithm for Seq-experiment outputs. This requires the adaptation of the algorithm to the negative binomial distribution with which we model the data. We show that if the dispersion in the signal is known, the PDP algorithm can be used, and we provide an estimator for this dispersion. We describe a compression framework which reduces the time complexity without modifying the accuracy of the segmentation. We propose to estimate the number of segments via a penalized likelihood criterion. We illustrate the performance of the proposed methodology on RNA-Seq data. Conclusions: We illustrate the results of our approach on a real dataset and show its good performance. Our algorithm is available as an R package on the CRAN repository.

关键词： segmentation algorithm Exact algorithm Fast algorithm RNA-Seq data Genome annotation Count data Data compression

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Reconstruction of porous electrodes by FIB/SEM for detailed microstructure modeling

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JOURNAL OF POWER SOURCES 2011年第17期196卷 7302-7307页

作者： Joos, Jochen Carraro, Thomas Weber, Andre Ivers-Tiffee, Ellen Karlsruher Inst Technol Inst Werkstoffe Elektrotech D-76131 Karlsruhe Germany Karlsruher Inst Technol Ctr Funct Nanostruct D-76131 Karlsruhe Germany Univ Heidelberg Inst Angew Math D-62120 Heidelberg Germany

Polarization losses within electrodes of solid oxide fuel cells (SOFCs) are determined both by material composition and microstructure. Improvement in performance can be supported by a detailed characterization and modeling of the electrode microstructure. Focused ion beam (FIB) and scanning electron microscopy (SEM) combined with image processing have already proven potential for the reconstruction of porous electrodes. In this contribution the serialized reconstruction procedure of a high-performance, mixed ionic-electronic conducting La0.58Sr0.4Co0.2Fe0.8O3-delta (LSCF)-cathode will be illustrated in detail. Based on corrected reconstruction data sets and by the evaluation of qualified algorithms discriminating between porosity and electrode material, a sensitivity analysis of the grayscale threshold value on the essential parameters (i) surface area, (ii) volume/porosity fraction and (iii) tortuosity is performed. (C) 2010 Elsevier B.V. All rights reserved.

关键词： SOFC LSCF Focused ion beam (FIB) Microstructure modeling segmentation algorithm

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