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A Statistic and analysis of Access pattern for Online VoD Multimedia

JOURNAL OF SIGNAL PROCESSING SYSTEMS FOR SIGNAL image AND VIDEO TECHNOLOGY 2019年第10期91卷 1149-1157页

作者： Han, Zhijie Ma, Jiao He, Xin Fan, Weibei Henan Univ Inst Data & Knowledge Engn Kaifeng Henan Peoples R China Jiangsu High Technol Res Key Lab Wireless Sensor Nanjing Jiangsu Peoples R China Henan Univ Sch Software Kaifeng Henan Peoples R China Soochow Univ Sch Comp Sci & Technol Suzhou 215006 Peoples R China

The generally accepted that Zipf-Distribution is a convinced access pattern for text-based Web. However, with the dramatic increasement of VoD media traffic on the Internet such as Flash P2P, the inconsistency between the access patterns of media objects and the Zipf model has been researched by many scholars. In this paper, we have studied a large variety of media work-loads collected from both browser and server sides in Adobe Flash P2P systems which applied in Youku, Youtube, etc. Through extensive analysis and modeling. And found the object reference ranks of all these workloads follow the logistic (LOG) distribution despite their different media systems and delivery methods by extensive analysis and modeling. This mean it does not follow long tail effect;Furthermore, we have constructed mathematical models which can applied in access pattern in FlashP2P traffic. By analyzing the model of media traffic access, it is possible to better describe the user's access mode. Meantime, it is very suitable for the configuration and allocation of network resources which can be used more efficiently.

关键词： Traffic analysis Modeling Access pattern Logistic distribution

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The hyperbolic model for edge and texture detection in the primary visual cortex

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JOURNAL OF mathematical NEUROSCIENCE 2020年第1期10卷 2页

作者： Chossat, Pascal Univ Cote Azur Mathneuro INRIA Valbonne France Univ Cote Azur CNRS Valbonne France

The modeling of neural fields in the visual cortex involves geometrical structures which describe in mathematical formalism the functional architecture of this cortical area. The case of contour detection and orientation tuning has been extensively studied and has become a paradigm for the mathematical analysis of image processing by the brain. Ten years ago an attempt was made to extend these models by replacing orientation (an angle) with a second-order tensor built from the gradient of the image intensity, and it was named the structure tensor. This assumption does not follow from biological observations (experimental evidence is still lacking) but from the idea that the effectiveness of texture processing with the structure tensor in computer vision may well be exploited by the brain itself. The drawback is that in this case the geometry is not Euclidean but hyperbolic instead, which complicates the analysis substantially. The purpose of this review is to present the methodology that was developed in a series of papers to investigate this quite unusual problem, specifically from the point of view of tuning and pattern formation. These methods, which rely on bifurcation theory with symmetry in the hyperbolic context, might be of interest for the modeling of other features such as color vision or other brain functions.

关键词： Primary visual cortex Neural field equations Texture perception Structure tensor pattern formation Hyperbolic geometry

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An active contour model for medical image segmentation using a quaternion framework 18

An active contour model for medical image segmentation using...

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18th image Processing: Algorithms and Systems Conference, IPAS 2020

作者： Voronin, V. Zhdanova, M. Semenishchev, E. Zelensky, A. Agaian, S. Moscow State University of Technology "STANKIN" Moscow Russia Don State Technical University Lab. «Mathematical methods of image processing and computer vision Intelligent Systems» Gagarina 1 Rostov on Don Russia CUNY/ College of Staten Island Dept. of Computer Science New York United States

This paper presents a new method for segmenting medical images is based on Hamiltonian quaternions and the associative algebra, method of the active contour model and LPA-ICI (local polynomial approximation - the intersection of confidence intervals) anisotropic gradient. Since for segmentation tasks, the image is usually converted to grayscale, this leads to the loss of important information about color, saturation, and other important information associated color. To solve this problem, we use the quaternion framework to represent a color image to consider all three channels simultaneously when segmenting the RGB image. As a method of noise reduction, adaptive filtering based on local polynomial estimates using the ICI rule is used. The presented new approach allows obtaining clearer and more detailed boundaries of objects of interest. The experiments performed on real medical images (Z-line detection) show that our segmentation method of more efficient compared with the current state-of-art methods. © 2020, Society for Imaging Science and Technology

关键词： Adaptive filtering

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Reliability analysis Based on Incompletely Specified Data 14th

Reliability Analysis Based on Incompletely Specified Data

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14th International Conference on pattern Recognition and Information Processing (PRIP)

作者： Zaitseva, Elena Levashenko, Vitaly Sedlacek, Peter Univ Zilina Fac Management Sci & Informat Zilina Slovakia

ISBN: (纸本)9783030354305;9783030354299

In this paper new algorithm for the reliability analysis of system is considered. The reliability analysis consists of 2 essential steps - creation of mathematical model and quantitative analysis. The system mathematical model is constructed depending on the specifics of analysis and properties of the investigated system. In this paper the mathematical model in form of the structure function of non-coherent Multi-State System (MSS) is considered. The non-coherent system is specific group of systems in context of reliability analysis for which for system component degradation does not always lead to a degradation or failure of the system. MSS is mathematical model that allows analyzing of some (not only two) states/performance levels of system reliability. The structure function is type of mathematical model, that express dependency between system behavior and behavior of its components. Structure function can be represented in different forms, for example, as minimal cuts/paths, fault tree, reliability bloc diagrams. One of them used in this paper is Multi-Valued Decision Diagram (MDD). MDD is typical used for representation of data of large dimension. Created mathematical model is then used for quantitative analysis. This analysis includes calculus of different system characteristics such as availability/unavailability and other indices and measures. New methods for the creating of structure function in form of MDD and calculation of some indices for quantitative analysis is proposed in the paper. Important advantage of this method is possibility to use for MDD construction based on incompletely specified data and analysis of non-coherent MSS. Usage of the method is demonstrated on biker crashes survival evaluation.

关键词： Reliability analysis Multi-valued decision diagrams Non-coherent systems Incompletely specified data Structure importance

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Computation of Lacunarity from Covariance of Spatial Binary Maps

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JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS 2019年第2期24卷 264-288页

作者： Hingee, Kassel Baddeley, Adrian Caccetta, Peter Nair, Gopalan Univ Western Australia Dept Math & Stat 35 Stirling Highway Perth WA 6009 Australia CSIRO Data61 Leeuwin Ctr 65 Underwood Ave Perth WA 6014 Australia Curtin Univ Dept Math & Stat GPO Box U1987 Perth WA 6845 Australia

We consider a spatial binary coverage map (binary pixel image) which might represent the spatial pattern of the presence and absence of vegetation in a landscape. 'Lacunarity' is a generic term for the nature of gaps in the pattern: a popular choice of summary statistic is the 'gliding-box lacunarity' (GBL) curve. GBL is potentially useful for quantifying changes in vegetation patterns, but its application is hampered by a lack of interpretability and practical difficulties with missing data. In this paper we find a mathematical relationship between GBL and spatial covariance. This leads to new estimators of GBL that tolerate irregular spatial domains and missing data, thus overcoming major weaknesses of the traditional estimator. The relationship gives an explicit formula for GBL of models with known spatial covariance and enables us to predict the effect of changes in the pattern on GBL. Using variance reduction methods for spatial data, we obtain statistically efficient estimators of GBL. The techniques are demonstrated on simulated binary coverage maps and remotely sensed maps of local-scale disturbance and meso-scale fragmentation in Australian forests. Results show in some cases a fourfold reduction in mean integrated squared error and a twentyfold reduction in sensitivity to missing data.

关键词： Forest disturbance Fractal Gliding box image analysis Random set Spatial statistics

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Applying machine learning methods toward classification based on small datasets: Application to shoulder labral tears

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Journal of Engineering and Science in Medical Diagnostics and Therapy 2020年第1期3卷 011004页

作者： Clymer, Daniel R. Long, Jason Latona, Carmen Akhavan, Sam Le Duc, Philip Cagan, Jonathan Department of Mechanical Engineering Carnegie Mellon University 5000 Forbes Avenue PittsburghPA15213 United States Department of Musculoskeletal Radiology Allegheny General Hospital 320 E. North Avenue PittsburghPA15212 United States Department of Orthopedic Surgery Allegheny General Hospital 1308 Federal Street PittsburghPA15212 United States

Machine learning is a powerful tool that can be applied to pattern search and mathematical optimization for making predictions on new data with unknown labels. In the field of medical imaging, one challenge with applying machine learning techniques is the limited size and relative expense of obtaining labeled data. For example, in glenoid labral tears, current imaging diagnosis is best achieved by imaging through magnetic resonance (MR) arthrography, a method of injecting contrast-enhancing material into the joint that can potentially cause discomfort to the patient, and adds expense compared to a standard magnetic resonance image (MRI). This work proposes limiting the use of MR arthrography through a medical diagnostic approach, based on convolutional neural networks (CNNs) and transfer learning from a separate medical imaging dataset to improve the efficiency and effectiveness. The results indicate an effective method applied to a small dataset of unenhanced shoulder MRI in order to diagnose labral tear severity while potentially significantly reducing cost and reducing unnecessary invasive imaging techniques. The proposed method ultimately can reduce physician workload while ensuring that the least number of patients as possible need to be subjected to an additional invasive contrast-enhanced imaging procedure. Copyright © 2020 by ASME

关键词： Medical imaging

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A Framework for Analyzing Stochastic Optimization Algorithms Under Dependence

A Framework for Analyzing Stochastic Optimization Algorithms...

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作者： Zhou, Chaoxu Columbia University

学位级别：Ph.D.

In this dissertation, a theoretical framework based on concentration inequalities for empirical processes is developed to better design iterative optimization algorithms and analyze their convergence properties in the presence of complex dependence between directions and step-sizes. Based on this framework, we proposed a stochastic away-step Frank-Wolfe algorithm and a stochastic pairwise-step Frank-Wolfe algorithm for solving strongly convex problems with polytope constraints and proved that both of those algorithms converge linearly to the optimal solution in expectation and almost surely. Numerical results showed that the proposed algorithms are faster and more stable than most of their competitors. This framework can be applied for designing and analyzing stochastic algorithms with adaptive step-sizes that are based on local curvature for self-concordant optimization problems. Notably, we proposed and analyzed a stochastic BFGS algorithm without line-search, and proved that it converges linearly globally and super-linearly locally using the framework mentioned above. This is the first work that analyzes a fully stochastic BFGS algorithm, which also avoids time consuming or even impossible line-search steps. A third class of problems that the empirical processes framework can be applied to is to study the optimization of compositions of stochastic functions. A multi-level Monte Carlo based unbiased gradient generation method is introduced into stochastic optimization algorithms for minimizing function compositions. Based on this, standard stochastic optimization algorithms can be applied to these problems directly.

关键词： Operations research mathematical optimization--Computer programs Computer algorithms Stochastic processes--Computer programs Monte Carlo method

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基于文生图的纬编移圈提花针织物设计与三维仿真

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现代纺织技术 2025年第5期33卷 126-133页

作者：曹叶蒋高明穆秀萍李炳贤江南大学针织技术教育部工程研究中心

为实现纬编提花移圈织物的快速设计与三维仿真，借助AI生成花型效果图，通过图像输入和解析、数据处理和转换，生成完整的编织工艺。根据织物的成品纵密和成品横密，将花型效果图进行网格化得到花型意匠图，构建花型意匠图模型、组织结... 详细信息

为实现纬编提花移圈织物的快速设计与三维仿真，借助AI生成花型效果图，通过图像输入和解析、数据处理和转换，生成完整的编织工艺。根据织物的成品纵密和成品横密，将花型效果图进行网格化得到花型意匠图，构建花型意匠图模型、组织结构图模型，并通过二者之间的变换关系得到织物的编织矩阵模型，将织物结构进行数字化存储。在深入研究纬编提花移圈织物结构特点的基础上，建立织物理想状态下的线圈结构基本模型，实现了对纬编提花移圈织物的仿真。该模型可提高产品的设计效率，增强产品设计的可视化，弥补纬编双面移圈织物设计方法复杂、设计周期长、生产效率低的不足，拓宽纬编移圈织物的市场应用。

关键词：纬编提花移圈织物 AI绘画三维仿真

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β-Skeleton analysis of the cosmic web

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MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY 2019年第4期485卷 5276-5284页

作者： Fang, Feng Forero-Romero, Jaime Rossi, Graziano Li, Xiao-Dong Feng, Long-Long Sun Yat Sen Univ Sch Phys & Astron Guangzhou 510297 Guangdong Peoples R China Univ Los Andes Dept Fis Cra 1 18A-10 Edificio IpCP 111711 Bogota Colombia Sejong Univ Dept Phys & Astron Seoul 143747 South Korea

The beta-skeleton is a mathematical method to construct graphs from a set of points that has been widely applied in the areas of image analysis, machine learning, visual perception, and pattern recognition. In this work, we apply the beta-skeleton to study the cosmic web. We use this tool on simulated data to identify the filamentary structures and characterize the statistical properties of the skeleton. We find that the beta-skeleton is able to reveal the underlying structures without any parameter fine-tuning. A different degree of sparseness can be obtained by adjusting the value of beta. In addition, the statistical properties of the length and direction of the skeleton connections show a clear dependence on the redshift space distortions, volume effect, Alcock-Paczynski effect, and galaxy bias. Our proof-of-concept study shows that the statistical properties of the beta-skeleton can be used to probe cosmological parameters and galaxy evolution.

关键词： methods: statistical cosmological parameters cosmology: observations large-scale structure of Universe

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AFSI: Adaptive Restart for Fast Semi-Iterative Schemes for Convex Optimisation 40th

AFSI: Adaptive Restart for Fast Semi-Iterative Schemes for C...

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40th German Conference on pattern Recognition, GCPR 2018

作者： Tómasson, Jón Arnar Ochs, Peter Weickert, Joachim Mathematical Image Analysis Group Faculty of Mathematics and Computer Science Campus E1.7 Saarland University Saarbrücken66041 Germany Mathematical Optimization Group Faculty of Mathematics and Computer Science Campus E1.7 Saarland University Saarbrücken66041 Germany

ISBN: (纸本)9783030129385

Smooth optimisation problems arise in many fields including image processing, and having fast methods for solving them has clear benefits. Widely and successfully used strategies to solve them are accelerated gradient methods. They accelerate standard gradient-based schemes by means of extrapolation. Unfortunately, most acceleration strategies are generic, in the sense, that they ignore specific information about the objective function. In this paper, we implement an adaptive restarting into a recently proposed efficient acceleration strategy that was coined Fast Semi-Iterative (FSI) scheme. Our analysis shows clear advantages of the adaptive restarting in terms of a theoretical convergence rate guarantee and state-of-the-art performance on a challenging image processing task. © 2019, Springer Nature Switzerland AG.

关键词： Gradient methods

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