Authorship Detection and Encoding for eBay Images

This paper describes a framework to detect authorship of eBay images. It contains three modules: editing style summarization, classification and multi-account linking detection. For editing style summarization, three approaches, namely the edge-based approach, the color-based approach, and the color probability approach, are proposed to encode the common patterns inside a group of images with similar editing styles into common edge or color models. Prior to the summarization step, an edge-based clustering algorithm is developed. Corresponding to the three summarization approaches, three classification methods are developed accordingly to predict the authorship of an unlabeled test image. For multi-account linking detection, to detect the hidden owner behind multiple eBay seller accounts, two methods to measure the similarity between seller accounts based on similar models are presented.

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A Novel Unsupervised Classification Method for Sandy Land Using Fully Polarimetric SAR Data

Remote Sensing ◽

10.3390/rs13030355 ◽

2021 ◽

Vol 13 (3) ◽

pp. 355

Author(s):

Weixian Tan ◽

Borong Sun ◽

Chenyu Xiao ◽

Pingping Huang ◽

Wei Xu ◽

...

Keyword(s):

Spectral Clustering ◽

Large Scale ◽

Clustering Algorithm ◽

Feature Vector ◽

Unsupervised Classification ◽

Classification Method ◽

Sandy Land ◽

Classification Methods ◽

The Many ◽

Representative Points

Classification based on polarimetric synthetic aperture radar (PolSAR) images is an emerging technology, and recent years have seen the introduction of various classification methods that have been proven to be effective to identify typical features of many terrain types. Among the many regions of the study, the Hunshandake Sandy Land in Inner Mongolia, China stands out for its vast area of sandy land, variety of ground objects, and intricate structure, with more irregular characteristics than conventional land cover. Accounting for the particular surface features of the Hunshandake Sandy Land, an unsupervised classification method based on new decomposition and large-scale spectral clustering with superpixels (ND-LSC) is proposed in this study. Firstly, the polarization scattering parameters are extracted through a new decomposition, rather than other decomposition approaches, which gives rise to more accurate feature vector estimate. Secondly, a large-scale spectral clustering is applied as appropriate to meet the massive land and complex terrain. More specifically, this involves a beginning sub-step of superpixels generation via the Adaptive Simple Linear Iterative Clustering (ASLIC) algorithm when the feature vector combined with the spatial coordinate information are employed as input, and subsequently a sub-step of representative points selection as well as bipartite graph formation, followed by the spectral clustering algorithm to complete the classification task. Finally, testing and analysis are conducted on the RADARSAT-2 fully PolSAR dataset acquired over the Hunshandake Sandy Land in 2016. Both qualitative and quantitative experiments compared with several classification methods are conducted to show that proposed method can significantly improve performance on classification.

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Fuzzy Set Based Clustering Algorithm of Web Text

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.678.19 ◽

2014 ◽

Vol 678 ◽

pp. 19-22

Author(s):

Hong Xin Wan ◽

Yun Peng

Keyword(s):

Key Words ◽

Fuzzy Set ◽

Clustering Algorithm ◽

Text Clustering ◽

Classification Methods ◽

Comparative Experiment ◽

Fuzzy Algorithm ◽

Pattern Clustering ◽

The Web ◽

Computing Accuracy

Web text exists non-certain and non-structure contents ,and it is difficult to cluster the text by normal classification methods. We propose a web text clustering algorithm based on fuzzy set to increase the computing accuracy with the web text. After abstracting the key words of the text, we can look it as attributes and design the fuzzy algorithm to decide the membership of the words. The algorithm can improve the algorithm complexity of time and space, increase the robustness comparing to the normal algorithm. To test the accuracy and efficiency of the algorithm, we take the comparative experiment between pattern clustering and our algorithm. The experiment shows that our method has a better result.

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N-(3-Chloro-1H-indazol-5-yl)-4-methoxybenzenesulfonamide

Acta Crystallographica Section E Structure Reports Online ◽

10.1107/s160053681302744x ◽

2013 ◽

Vol 69 (11) ◽

pp. o1632-o1632

Author(s):

Hakima Chicha ◽

El Mostapha Rakib ◽

Latifa Bouissane ◽

Mohamed Saadi ◽

Lahcen El Ammari

Keyword(s):

Hydrogen Bonds ◽

Benzene Ring ◽

Dihedral Angle ◽

Title Compound ◽

Two Dimensional ◽

Common Edge ◽

Compound C ◽

Dimensional Network ◽

The Common ◽

The Mean

In the title compound, C14H12ClN3O3S, the fused five- and six-membered rings are folded slightly along the common edge, forming a dihedral angle of 3.2 (1)°. The mean plane through the indazole system makes a dihedral angle of 30.75 (7)° with the distant benzene ring. In the crystal, N—H...O hydrogen bonds link the molecules, forming a two-dimensional network parallel to (001).

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Revealing the Presence of a Symbolic Sequence Representing Multiple Nucleotides Based on K-Means Clustering of Oligonucleotides

Molecules ◽

10.3390/molecules24020348 ◽

2019 ◽

Vol 24 (2) ◽

pp. 348

Author(s):

Byoungsang Lee ◽

So Yeon Ahn ◽

Charles Park ◽

James J. Moon ◽

Jung Heon Lee ◽

...

Keyword(s):

Nucleotide Sequence ◽

Clustering Algorithm ◽

Sequence Information ◽

Symbolic Sequence ◽

Representative Sequence ◽

Combined Application ◽

The Social ◽

The Common ◽

Hybridization Profile ◽

Common Sequence

In biological systems, a few sequence differences diversify the hybridization profile of nucleotides and enable the quantitative control of cellular metabolism in a cooperative manner. In this respect, the information required for a better understanding may not be in each nucleotide sequence, but representative information contained among them. Existing methodologies for nucleotide sequence design have been optimized to track the function of the genetic molecule and predict interaction with others. However, there has been no attempt to extract new sequence information to represent their inheritance function. Here, we tried to conceptually reveal the presence of a representative sequence from groups of nucleotides. The combined application of the K-means clustering algorithm and the social network analysis theorem enabled the effective calculation of the representative sequence. First, a “common sequence” is made that has the highest hybridization property to analog sequences. Next, the sequence complementary to the common sequence is designated as a ‘representative sequence’. Based on this, we obtained a representative sequence from multiple analog sequences that are 8–10-bases long. Their hybridization was empirically tested, which confirmed that the common sequence had the highest hybridization tendency, and the representative sequence better alignment with the analogs compared to a mere complementary.

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Eliminating Vertical Stripe Defects on Silicon Steel Surface byL1/2Regularization

Mathematical Problems in Engineering ◽

10.1155/2011/854674 ◽

2011 ◽

Vol 2011 ◽

pp. 1-13 ◽

Cited By ~ 1

Author(s):

Wenfeng Jing ◽

Deyu Meng ◽

Chen Qiao ◽

Zhiming Peng

Keyword(s):

Steel Surface ◽

Technical Problem ◽

Silicon Steel ◽

Electromagnetic Properties ◽

Gradient Boosting ◽

Vertical Stripe ◽

Classification Methods ◽

Production Environment ◽

Data Set ◽

The Common

The vertical stripe defects on silicon steel surface seriously affect the appearance and electromagnetic properties of silicon steel products. Eliminating such defects is adifficult and urgent technical problem. This paper investigates the relationship between the defects and their influence factors by classification methods. However, when the common classification methods are used in the problem, we cannot obtain a classifier with high accuracy. Byanalysis of the data set, we find that it is imbalanced and inconsistent. Because the common classification methods are based on accuracy-maximization criterion, they are not applicable to imbalanced and inconsistent data set. Thus, we propose asupport-degree-maximization criterion and anovel cost-sensitive loss function and also establish an improvedL1/2regularization approach for solution of the problem. Moreover, by employing reweighted iteration gradient boosting algorithm, we obtain a linear classifier with a high support degree. Through analyzing the classifier, we formulate a rule under which the silicon steel vertical stripe defects do not occur in the existing production environment. By applying the proposed rule to 50TW600 silicon steel production, the vertical stripe defects of the silicon steel products have been greatly decreased.

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Multi-Method Tracking of Monsoon Floods Using Sentinel-1 Imagery

Water ◽

10.3390/w11112289 ◽

2019 ◽

Vol 11 (11) ◽

pp. 2289 ◽

Cited By ~ 3

Author(s):

Ruzza ◽

Guerriero ◽

Grelle ◽

Guadagno ◽

Revellino

Keyword(s):

Synthetic Aperture Radar ◽

Clustering Algorithm ◽

Temporal Evolution ◽

Human Life ◽

Computation Time ◽

Synthetic Aperture ◽

Classification Methods ◽

Flood Monitoring ◽

Sar Imagery ◽

Flooded Area

Floods cause great losses in terms of human life and damages to settlements. Since the exposure is a proxy of the risk, it is essential to track flood evolution. The increasing availability of Synthetic Aperture Radar (SAR) imagery extends flood tracking capabilities because of its all-water and day/night acquisition. In this paper, in order to contribute to a better evaluation of the potential of Sentinel-1 SAR imagery to track floods, we analyzed a multi-pulse flood caused by a typhoon in the Camarines Sur Province of Philippines between the end of 2018 and the beginning of 2019. Multiple simple classification methods were used to track the spatial and temporal evolution of the flooded area. Our analysis indicates that Valley Emphasis based manual threshold identification, Otsu methodology, and K-Means Clustering have the potential to be used for tracking large and long-lasting floods, providing similar results. Because of its simplicity, the K-Means Clustering algorithm has the potential to be used in fully automated operational flood monitoring, also because of its good performance in terms of computation time.

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A dislocation at the common edge of semi-infinite boundaries in anisotropic elasticity

Acta Metallurgica ◽

10.1016/0001-6160(82)90070-0 ◽

1982 ◽

Vol 30 (1) ◽

pp. 311-315 ◽

Cited By ~ 3

Author(s):

R. Bonnet

Keyword(s):

Anisotropic Elasticity ◽

Common Edge ◽

The Common

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Medicinal Plants Segmentation using Thresholding and Edge based Techniques

International Journal of Innovative Technology and Exploring Engineering - Special Issue ◽

10.35940/ijitee.f1014.0486s419 ◽

2019 ◽

Vol 8 (6S4) ◽

pp. 71-76

Keyword(s):

Image Processing ◽

Medicinal Plants ◽

Know How ◽

Medicinal Value ◽

Texture Characteristics ◽

Different Shapes ◽

The Common ◽

Edge Based ◽

Processing Techniques

Medicinal value is the integral essence and active ingredients in plants. Knowledge about medicinal plants is more essential to mankind. Manual identification of medicinal plant requires prior information and needs the assistance of botanist because all the plants have similar color, shape and texture characteristics and it is time consuming process. Due to this reason it is very much essential for Pharmacists, Botanist and Ayurveda Practitioners to know how to identify medicinal plants through computer technologies. Image processing technology is used for identification and classification of medicinal plants. The following three general phases of image processing techniques are applied to all types of images namely pre-processing, segmentation and feature extraction. Among all the stages of image processing, segmentation phase partition an image into number of regions and segment the object from background. It improve the representation of an image into more meaningful and easier to analyze the features. The medicinal plants segmentation is carried out in this proposed work. The common and famous segmentation techniques like edge detection and thresholding methods are applied on different shapes of flowers, leaves and fruits/seeds images. This paper explores the comparisons of above two methods and effects of filtering and enhancement techniques.

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Analysis, Results, and Interpretation for Radiation Between Some Simply-Arranged Gray Surfaces

Journal of Heat Transfer ◽

10.1115/1.3680523 ◽

1961 ◽

Vol 83 (2) ◽

pp. 207-214 ◽

Cited By ~ 39

Author(s):

E. M. Sparrow ◽

J. L. Gregg ◽

J. V. Szel ◽

P. Manos

Keyword(s):

Integral Equations ◽

Incident Radiation ◽

Parallel Plates ◽

Radiation Problem ◽

Common Edge ◽

Common Assumption ◽

Wide Range ◽

Physical Insight ◽

The Common ◽

Detailed Interpretation

A detailed analysis has been made to obtain both physical insight and numerical results for radiation between gray surfaces. In particular, it was desired to examine the common assumption that the incident radiation is uniformly distributed over a surface. To lift this assumption, the radiation problem must be formulated in terms of integral equations. The study was carried out for two simple configurations: Two plates sharing a common edge, and two parallel plates. Solutions of the governing integral equations were found for a wide range of geometric and radiative conditions. A detailed interpretation is made of the results, and comparisons with the predictions from the simplified theory of uniform incident radiation are presented.

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