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Comparative analysis of proficiencies of various textures and geometric features in breast mass classification using k-nearest neighbor

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Visual Computing for Industry,Biomedicine,and Art 2022年第1期5卷 25-43页

作者： Harmandeep Singh vipul sharma Damanpreet Singh Department of Computer Science and Engineering IKG Punjab Technical UniversityJalandharPunjab 144603India Department of Computer Science and Engineering Sant Longowal Institute of Engineering and TechnologySangrurPunjab 148106India

This paper introduces a comparative analysis of the proficiencies of various textures and geometric features in the diagnosis of breast masses on *** improved machine learning-based framework was developed for this *** proposed system was tested using 106 full field digital mammography images from the INbreast dataset,containing a total of 115 breast mass *** proficiencies of individual and various combinations of computed textures and geometric features were investigated by evaluating their contributions towards attaining higher classification *** state-of-the-art filter-based feature selection algorithms(Relief-F,Pearson correlation coefficient,neighborhood component analysis,and term variance)were employed to select the top 20 most discriminative *** Relief-F algorithm outperformed other feature selection algorithms in terms of classification results by reporting 85.2%accuracy,82.0%sensitivity,and 88.0%specificity.A set of nine most discriminative features were then selected,out of the earlier mentioned 20 features obtained using Relief-F,as a result of further *** classification performances of six state-of-the-art machine learning classifiers,namely k-nearest neighbor(k-NN),support vector machine,decision tree,Naive Bayes,random forest,and ensemble tree,were investigated,and the obtained results revealed that the best classification results(accuracy=90.4%,sensitivity=92.0%,specificity=88.0%)were obtained for the k-NN classifier with the number of neighbors having k=5 and squared inverse distance *** key findings include the identification of the nine most discriminative features,that is,FD26(Fourier Descriptor),Euler number,solidity,mean,FD14,FD13,periodicity,skewness,and contrast out of a pool of 125 texture and geometric *** proposed results revealed that the selected nine features can be used for the classification of breast masses in mammograms.

关键词： Mammography Breast cancer Machine learning Classification

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Flexible biodegradable transparent heaters based on fractal-like leaf skeletons

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npj Flexible Electronics 2020年第1期4卷 235-242页

作者： vipul sharma Anastasia Koivikko Kyriacos Yiannacou Kimmo Lahtonen Veikko Sariola Faculty of Medicine and Health Technology Tampere UniversityFinland Korkeakoulunkatu 333720TampereFinland Faculty of Engineering and Natural Sciences Tampere UniversityP.O.Box 69233014TampereFinland

We present a facile method to prepare flexible,transparent,biodegradable,and fast resistive heaters by applying silver(Ag)nanowires onto fractal-like leaf *** fractal-like structure of the leaf skeleton maximizes its surface area,improving the transfer of heat to its surroundings and thus making the heater fast,without compromising *** ion layer on the leaf skeleton helps to conformally cover the surface with Ag *** sheet resistance of the heater can be controlled by the loading of Ag nanowires,without sacrificing the optical transmittance(~80%at 8Ωsq^(−1)).The heating is uniform and the surface temperature of a 60 mm×60 mm heater(8Ωsq^(−1))can quickly(5-10 s)raise to 125℃ with a low voltage(6 V).The heater displays excellent mechanical flexibility,showing no significant change in resistance and heating temperature when bent up to curvature of 800 m^(−1).Finally,we demonstrate the potential of the bioinspired heater as a thermotherapy patch by encapsulating it in a biodegradable tape and mounting it on the human wrist and *** study shows that fractal-like structures from nature can be repurposed as fractal designs for flexible electronics.

关键词： nanowires fractal transparent

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Effects of particle size on the triboelectrification phenomenon in pharmaceutical excipients:Experiments and multi-scale modeling

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Asian Journal of Pharmaceutical Sciences 2016年第5期11卷 603-617页

作者： Raj Mukherjee vipul Gupta Shivangi Naik Saurabh Sarkar Vinit sharma Prasad Peri Bodhisattwa Chaudhuri Department of Pharmaceutical Sciences University of ConnecticutStorrsCT 06269USA Institute of Material Sciences University of ConnecticutStorrsCT 06269USA Merck Sharp and Dohme West PointPA 19486USA

Particle sizes play a major role to mediate charge transfer, both between identical and different material surfaces. The study probes into the probable mechanism that actuates opposite polarities between two different size fractions of the same material by analyzing the charge transfer patterns of two different sizes of microcrystalline cellulose(MCC). Quantum scale calculations confirmed alteration of charge transfer capacities due to variation of moisture content predicted by multiple surface and bulk analytical techniques. Discrete Element Method(DEM) based multi-scale computational models pertinent to predict charge transfer capacities were further implemented, and the results were in accordance to the experimental charge profiles.

关键词： Tribocharging Work function Excipient Discrete Element Modeling

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