scholarly journals Color Zero-Watermarking Algorithm for Medical Images Based on BEMD-Schur Decomposition and Color Visual Cryptography

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Deyang Wu ◽  
Miaomiao Wang ◽  
Jing Zhao ◽  
Jiayan Wang ◽  
Meiyu Zhong ◽  
...  
Keyword(s):  
Information Structure ◽  
Large Scale ◽  
Medical Images ◽  
Personal Information ◽  
Binary Sequence ◽  
Visual Cryptography ◽  
Schur Decomposition ◽  
Copyright Information ◽  
Mode Decomposition ◽  
Zero Watermarking

With the widespread use of medical images in telemedicine, personal information may be leaked. The traditional zero-watermarking technology has poor robustness under large-scale attacks. At the same time, most of the zero-watermarking information generated is a binary sequence with a single information structure. In order to effectively solve the poor robustness problem of traditional zero-watermarking under large-scale attacks, a color zero-watermarking algorithm for medical images based on bidimensional empirical mode decomposition (BEMD)-Schur decomposition and color visual cryptography is proposed. Firstly, the color carrier image and the color copyright logo are decomposed into R, G, and B three color components, respectively, and the feature value of each sub-block are extracted by wavelet transform, BEMD decomposition, block operation, and Schur decomposition. Then, the R, G, and B components of the copyright logo are scrambled by Arnold scramble and converted into binary watermark information. Finally, a color visual cryptography scheme is proposed to generate two color shared images based on the carrier characteristics and copyright information. One shared image is used to generate a color zero-watermark, and the other is used for copyright authentication phase. Experimental results show that this algorithm has strong robustness and stability in resisting large-scale noise attacks, filtering attacks, JPEG compression, cropping attacks, and translation attacks at different positions. Compared with similar zero-watermarking algorithms, the robust performance is improved by about 10%, and it can adapt to more complex network environments.

A novel robust zero-watermarking algorithm for medical images

2021 ◽  
Author(s):  
Kun Hu ◽  
Xiaochao Wang ◽  
Jianping Hu ◽  
Hongfei Wang ◽  
Hong Qin
Keyword(s):  
Medical Images ◽  
Zero Watermarking

scholarly journals TransMed: Transformers Advance Multi-Modal Medical Image Classification

Diagnostics ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 1384
Author(s):  
Yin Dai ◽  
Yifan Gao ◽  
Fayu Liu
Keyword(s):  
Image Analysis ◽  
Image Classification ◽  
Long Range ◽  
Medical Image ◽  
Large Scale ◽  
Medical Images ◽  
Medical Image Analysis ◽  
Lesion Detection ◽  
Tumor Segmentation ◽  
Medical Image Classification

Over the past decade, convolutional neural networks (CNN) have shown very competitive performance in medical image analysis tasks, such as disease classification, tumor segmentation, and lesion detection. CNN has great advantages in extracting local features of images. However, due to the locality of convolution operation, it cannot deal with long-range relationships well. Recently, transformers have been applied to computer vision and achieved remarkable success in large-scale datasets. Compared with natural images, multi-modal medical images have explicit and important long-range dependencies, and effective multi-modal fusion strategies can greatly improve the performance of deep models. This prompts us to study transformer-based structures and apply them to multi-modal medical images. Existing transformer-based network architectures require large-scale datasets to achieve better performance. However, medical imaging datasets are relatively small, which makes it difficult to apply pure transformers to medical image analysis. Therefore, we propose TransMed for multi-modal medical image classification. TransMed combines the advantages of CNN and transformer to efficiently extract low-level features of images and establish long-range dependencies between modalities. We evaluated our model on two datasets, parotid gland tumors classification and knee injury classification. Combining our contributions, we achieve an improvement of 10.1% and 1.9% in average accuracy, respectively, outperforming other state-of-the-art CNN-based models. The results of the proposed method are promising and have tremendous potential to be applied to a large number of medical image analysis tasks. To our best knowledge, this is the first work to apply transformers to multi-modal medical image classification.

scholarly journals Analysis of V-Gutter Reacting Flow Dynamics Using Proper Orthogonal and Dynamic Mode Decompositions

Energies ◽  
2020 ◽  
Vol 13 (18) ◽  
pp. 4886 ◽  
Author(s):  
Yang Yang ◽  
Xiao Liu ◽  
Zhihao Zhang
Keyword(s):  
Shear Layer ◽  
Large Scale ◽  
Dynamic Mode Decomposition ◽  
Dynamic Mode ◽  
Reacting Flow ◽  
Eddy Simulation ◽  
Mode Decomposition ◽  
Wake Instability ◽  
Shedding Frequency ◽  
Proper Orthogonal

The current work is focused on investigating the potential of data-driven post-processing techniques, including proper orthogonal decomposition (POD) and dynamic mode decomposition (DMD) for flame dynamics. Large-eddy simulation (LES) of a V-gutter premixed flame was performed with two Reynolds numbers. The flame transfer function (FTF) was calculated. The POD and DMD were used for the analysis of the flame structures, wake shedding frequency, etc. The results acquired by different methods were also compared. The FTF results indicate that the flames have proportional, inertial, and delay components. The POD method could capture the shedding wake motion and shear layer motion. The excited DMD modes corresponded to the shear layer flames’ swing and convect motions in certain directions. Both POD and DMD could help to identify the wake shedding frequency. However, this large-scale flame oscillation is not presented in the FTF results. The negative growth rates of the decomposed mode confirm that the shear layer stabilized flame was more stable than the flame possessing a wake instability. The corresponding combustor design could be guided by the above results.

scholarly journals Ethnic Discrimination in the Dutch Labor Market: Differences Between Ethnic Minority Groups and the Role of Personal Information About Job Applicants—Evidence from a Field Experiment

2020 ◽  
Author(s):  
Lex Thijssen ◽  
Marcel Coenders ◽  
Bram Lancee
Keyword(s):  
Labor Market ◽  
Field Experiment ◽  
Ethnic Minority ◽  
Large Scale ◽  
Minority Groups ◽  
Personal Information ◽  
Empirical Support ◽  
Ethnic Discrimination ◽  
Ethnic Minority Groups ◽  
Large Scale Field

AbstractIn this study, we present the results of a large-scale field experiment on ethnic discrimination in the Dutch labor market. We sent fictitious job applications (N = 4211) to vacancies for jobs in ten different occupations in the Netherlands. By examining 35 different ethnic minority groups, we detect considerable differences in discrimination rates, predominantly between Western and non-Western minorities. Furthermore, we find little systematic variation in discrimination patterns with regard to gender, regions, and occupations, pointing to the existence of an ethnic hierarchy that is widely shared among employers. Finally, we do not find empirical support for the hypothesis that adding personal information in job applications reduces discrimination.

Unravelling the large-scale circulation modes in turbulent Rayleigh–Bénard convection

2021 ◽  
Author(s):  
Susanne Horn ◽  
Peter J. Schmid ◽  
Jonathan M. Aurnou
Keyword(s):  
Large Scale ◽  
Three Dimensional ◽  
Dynamic Mode Decomposition ◽  
Dynamic Mode ◽  
Mean Flow ◽  
Large Scale Circulation ◽  
Convective Systems ◽  
Aspect Ratios ◽  
Mode Decomposition ◽  
Coherent Flow Structure

Abstract The large-scale circulation (LSC) is the most fundamental turbulent coherent flow structure in Rayleigh-B\'enard convection. Further, LSCs provide the foundation upon which superstructures, the largest observable features in convective systems, are formed. In confined cylindrical geometries with diameter-to-height aspect ratios of Γ ≅ 1, LSC dynamics are known to be governed by a quasi-two-dimensional, coupled horizontal sloshing and torsional (ST) oscillatory mode. In contrast, in Γ ≥ √2 cylinders, a three-dimensional jump rope vortex (JRV) motion dominates the LSC dynamics. Here, we use dynamic mode decomposition (DMD) on direct numerical simulation data of liquid metal to show that both types of modes co-exist in Γ = 1 and Γ = 2 cylinders but with opposite dynamical importance. Furthermore, with this analysis, we demonstrate that ST oscillations originate from a tilted elliptical mean flow superposed with a symmetric higher order mode, which is connected to the four rolls in the plane perpendicular to the LSC in Γ = 1 tanks.

The complication of cyber manhunt: How cyber manhunt further complicated the ethical conflict between breaching the confidentiality and endangering the society in face of the COVID-19 pandemic (Preprint)

2021 ◽  
Author(s):  
Yen-Chang Chen ◽  
Yen-Yuan Chen
Keyword(s):  
Public Health ◽  
Large Scale ◽  
Health Workers ◽  
Early Stage ◽  
Personal Information ◽  
Public Health Intervention ◽  
Contact Tracing ◽  
Online Activity ◽  
Contact Investigation ◽  
The Impact

UNSTRUCTURED While health care and public health workers are working on measures to mitigate the COVID-19 pandemic, there is an unprecedentedly large number of people spending much more time indoors, and relying heavily on the Internet as their lifeline. What has been overlooked is the influence of the increasing online activities on public health issues. In this article, we pointed out how a large-scale online activity called cyber manhunt may threaten to offset the efficacy of contact tracing investigation, a public health intervention considered highly effective in limiting further transmission in the early stage of a highly contagious disease outbreak such as the COVID-19 pandemic. In the first section, we presented a case to show how personal information obtained from contact investigation and disclosed in part on the media provoked a vehement cyber manhunt. We then discussed the possible reasons why netizens collaborate to reveal anonymized personal information about contact investigation, and specify, from the perspective of public health and public health ethics, four problems of cyber manhunt, including the lack of legitimate public health goals, the concerns about privacy breach, the impact of misinformation, and social inequality. Based on our analysis, we concluded that more moral weight may be given to protecting one's confidentiality, especially in an era with the rapid advance of digital and information technologies.

scholarly journals Public attitudes towards algorithmic personalization and use of personal data online: evidence from Germany, Great Britain, and the United States

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Anastasia Kozyreva ◽  
Philipp Lorenz-Spreen ◽  
Ralph Hertwig ◽  
Stephan Lewandowsky ◽  
Stefan M. Herzog
Keyword(s):  
United States ◽  
Great Britain ◽  
Data Privacy ◽  
Large Scale ◽  
Personal Information ◽  
Public Attitudes ◽  
Personal Data ◽  
The United States ◽  
Individual Level ◽  
Personalized Services

AbstractPeople rely on data-driven AI technologies nearly every time they go online, whether they are shopping, scrolling through news feeds, or looking for entertainment. Yet despite their ubiquity, personalization algorithms and the associated large-scale collection of personal data have largely escaped public scrutiny. Policy makers who wish to introduce regulations that respect people’s attitudes towards privacy and algorithmic personalization on the Internet would greatly benefit from knowing how people perceive personalization and personal data collection. To contribute to an empirical foundation for this knowledge, we surveyed public attitudes towards key aspects of algorithmic personalization and people’s data privacy concerns and behavior using representative online samples in Germany (N = 1065), Great Britain (N = 1092), and the United States (N = 1059). Our findings show that people object to the collection and use of sensitive personal information and to the personalization of political campaigning and, in Germany and Great Britain, to the personalization of news sources. Encouragingly, attitudes are independent of political preferences: People across the political spectrum share the same concerns about their data privacy and show similar levels of acceptance regarding personalized digital services and the use of private data for personalization. We also found an acceptability gap: People are more accepting of personalized services than of the collection of personal data and information required for these services. A large majority of respondents rated, on average, personalized services as more acceptable than the collection of personal information or data. The acceptability gap can be observed at both the aggregate and the individual level. Across countries, between 64% and 75% of respondents showed an acceptability gap. Our findings suggest a need for transparent algorithmic personalization that minimizes use of personal data, respects people’s preferences on personalization, is easy to adjust, and does not extend to political advertising.

Hearing Aid Use and Mild Hearing Impairment: Learnings from Big Data

2017 ◽  
Vol 28 (08) ◽  
pp. 731-741 ◽  
Author(s):  
Barbra H. B. Timmer ◽  
Louise Hickson ◽  
Stefan Launer
Keyword(s):  
Hearing Impairment ◽  
Large Scale ◽  
Personal Information ◽  
Hearing Aid ◽  
Total Sample ◽  
British Society ◽  
Hearing Aid Use ◽  
Listening Environments ◽  
And Gender ◽  
The Right

AbstractPrevious research, mostly reliant on self-reports, has indicated that hearing aid (HA) use is related to the degree of hearing impairment (HI). No large-scale investigation of the relationship between data-logged HA use and HI has been conducted to date.This study aimed to investigate if objective measures of overall daily HA use and HA use in various listening environments are different for adults with mild HI compared to adults with moderate HI.This retrospective study used data extracted from a database of fitting appointments from an international group of HA providers. Only data from the participants’ most recent fitting appointment were included in the final dataset.A total of 8,489 bilateral HA fittings of adults over the age of 18 yr, conducted between January 2013 and June 2014, were included. Participants were subsequently allocated to HI groups, based on British Society of Audiology and American Speech-Language-Hearing Association audiometric descriptors.Fitting data from participating HA providers were regularly transferred to a central server. The data, with all personal information except age and gender removed, contained participants’ four-frequency average (at 500, 1000, 2000, and 4000 Hz) as well as information on HA characteristics and usage. Following data cleaning, bivariate and post hoc statistical analyses were conducted.The total sample of adults’ average daily HA use was 8.52 hr (interquartile range [IQR] = 5.49–11.77) in the left ear and 8.51 hr (IQR = 5.49–11.72) in the right ear. With a few exceptions, there were no statistical differences between hours of HA use for participants with mild HI compared to those with moderate impairment. Across all mild and moderate HI groups, the most common overall HA usage was between 8 and 12 hr per day. Other factors such as age, gender, and HA style also showed no relationship to hours of use. HAs were used, on average, for 7 hr (IQR = 4.27–9.96) per day in quiet and 1 hr (IQR = 0.33–1.41) per day in noisy listening situations.Clinical populations with mild HI use HAs as frequently as those with a moderate HI. These findings support the recommendation of HAs for adults with milder degrees of HI.

Color image zero-watermarking based on SVD and visual cryptography in DWT domain

2017 ◽  
Author(s):  
Xilin Liu ◽  
Beijing Chen ◽  
Gouenou Coatrieux ◽  
Huazhong Shu
Keyword(s):  
Color Image ◽  
Visual Cryptography ◽  
Zero Watermarking
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