scholarly journals Improving Anticompression Robustness of JPEG Adaptive Steganography Based on Robustness Measurement and DCT Block Selection

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Haocheng Fu ◽  
Xianfeng Zhao ◽  
Xiaolei He
Keyword(s):  
State Of The Art ◽  
Auxiliary Information ◽  
Selection Strategy ◽  
Common Channel ◽  
Adaptive Steganography ◽  
Change Rate ◽  
Jpeg Images ◽  
The Public ◽  
Image Sharing ◽  
Construction Scheme

With the development of the Internet, social network platforms (SNPs) have become the most common channel for image sharing. As a result, transmitting stego images in the public channels gives steganographers the best opportunity to transmit secret messages with behavioral security preserved. However, the SNPs typically compress uploaded images and damage the weak signal of steganography. In this study, a robust JPEG steganographic scheme based on robustness measurement and cover block selection (CBSRS) is proposed. We first design a deep learning-based model to fit the blockwise change rate of coefficients after JPEG recompression. Then, a cover block selection strategy is proposed to improve the robustness by optimizing the joint distortion function of transmission costs and classic costs. Moreover, by embedding indicator of cover block selection in chrominance channels of JPEG images, a shareable cover construction scheme is designed to solve the problem of auxiliary information transmission. The experimental results show that our proposed framework improves robustness while maintaining statistical security. Comparing with state-of-the-art methods, the framework achieves better performance under given recompression channels.

scholarly journals Semi-Supervised PolSAR Image Classification Based on Self-Training and Superpixels

2019 ◽  
Vol 11 (16) ◽  
pp. 1933 ◽  
Author(s):  
Yangyang Li ◽  
Ruoting Xing ◽  
Licheng Jiao ◽  
Yanqiao Chen ◽  
Yingte Chai ◽  
...  
Keyword(s):  
Image Classification ◽  
State Of The Art ◽  
Sample Selection ◽  
Spatial Relations ◽  
Speckle Noise ◽  
Classification Performance ◽  
Selection Strategy ◽  
Training Set ◽  
Polarimetric Synthetic Aperture Radar ◽  
Unlabeled Sample

Polarimetric synthetic aperture radar (PolSAR) image classification is a recent technology with great practical value in the field of remote sensing. However, due to the time-consuming and labor-intensive data collection, there are few labeled datasets available. Furthermore, most available state-of-the-art classification methods heavily suffer from the speckle noise. To solve these problems, in this paper, a novel semi-supervised algorithm based on self-training and superpixels is proposed. First, the Pauli-RGB image is over-segmented into superpixels to obtain a large number of homogeneous areas. Then, features that can mitigate the effects of the speckle noise are obtained using spatial weighting in the same superpixel. Next, the training set is expanded iteratively utilizing a semi-supervised unlabeled sample selection strategy that elaborately makes use of spatial relations provided by superpixels. In addition, a stacked sparse auto-encoder is self-trained using the expanded training set to obtain classification results. Experiments on two typical PolSAR datasets verified its capability of suppressing the speckle noise and showed excellent classification performance with limited labeled data.

Performance measurement and management in the public sector: state of the art and research opportunities

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Patrizia Garengo ◽  
Alberto Sardi
Keyword(s):  
Public Sector ◽  
Performance Measurement ◽  
State Of The Art ◽  
Business Management ◽  
Academic Research ◽  
Conceptual Structure ◽  
Content Type ◽  
Research Opportunities ◽  
The Public ◽  
Public Organisations

PurposeSince the 1980s, performance measurement and management (PMM) has been described as an essential element of new public management (NPM) reforms. The purpose of this paper is to provide an overview of the current state of the art and future research opportunities for PMM in public sector management.Design/methodology/approachThe paper carried out a bibliometric literature review using two main techniques named (1) performance analysis and (2) science mapping techniques. It investigated the academic research area describing the main publications' trend, the conceptual structure and its evolution from 1996 to 2019.FindingsThe results highlighted the growing relevance of PMM research in public organisations and confirmed a great interest of the business, management and accounting literature on PMM in public sector management. Furthermore, the results also described a conceptual structure of the public PMM literature analysed and its evolution being too generic to answer public organisations' needs. The results identified five main research gaps and research opportunities.Originality/valueAlthough the adoption of rigorous bibliometric techniques was recognised as being useful for assessing the academic research study, the paper describes the business, management and accounting literature contributing to new theoretical and practical future opportunities.

scholarly journals State of the art of the public-private relation in k-12 education

2015 ◽  
Vol 5 ◽  
Author(s):  
Luiz Araújo
Keyword(s):  
State Of The Art ◽  
The Public ◽  
K 12

Um dos debates mais antigos nas políticas públicas educacionais é, sem sombra de dúvida, a participação do setor privado no atendimento educacional e a destinação (ou proibição) de recursos públicos para escolas privadas. Aproveitando as brechas abertas com a redação da Constituição Federal de 1988, o setor privado aprofundou sua presença na prestação de serviço na educação básica. Os dados censitários mostram que é forte a presença do setor, com destaque para uma parcela de instituições que sobrevivem às custas de repasse de recursos públicos para a manutenção das vagas por elas oferecidas. Ao contrário do que era esperado, é nas capitais que encontramos as situações que mais contrariam a conquista da educação como direito de todos e dever do Estado. Em que pese salvaguardas presentes no PNE, os programas federais e mudanças legais são fortes sinalizações de que parcelas maiores da oferta educacional poderão ser ocupadas pelo setor privado na próxima década.

scholarly journals The State-of-the-Art Technology of Currency Identification

2017 ◽  
Vol 9 (3) ◽  
pp. 58-72 ◽  
Author(s):  
Guangyu Wang ◽  
Xiaotian Wu ◽  
WeiQi Yan
Keyword(s):  
Feature Extraction ◽  
New Zealand ◽  
Comparative Study ◽  
State Of The Art ◽  
The State ◽  
Classification Algorithms ◽  
Security Issue ◽  
The Public ◽  
Us Dollar ◽  
Chinese Yuan

The security issue of currency has attracted awareness from the public. De-spite the development of applying various anti-counterfeit methods on currency notes, cheaters are able to produce illegal copies and circulate them in market without being detected. By reviewing related work in currency security, the focus of this paper is on conducting a comparative study of feature extraction and classification algorithms of currency notes authentication. We extract various computational features from the dataset consisting of US dollar (USD), Chinese Yuan (CNY) and New Zealand Dollar (NZD) and apply the classification algorithms to currency identification. Our contributions are to find and implement various algorithms from the existing literatures and choose the best approaches for use.

scholarly journals Disentangled Feature Learning Network for Vehicle Re-Identification

2020 ◽  
Author(s):  
Yan Bai ◽  
Yihang Lou ◽  
Yongxing Dai ◽  
Jun Liu ◽  
Ziqian Chen ◽  
...  
Keyword(s):  
State Of The Art ◽  
Feature Learning ◽  
Feature Representation ◽  
Public Security ◽  
The Public ◽  
Common Features ◽  
Learning Network ◽  
Single Feature ◽  
Art Performance

Vehicle Re-Identification (ReID) has attracted lots of research efforts due to its great significance to the public security. In vehicle ReID, we aim to learn features that are powerful in discriminating subtle differences between vehicles which are visually similar, and also robust against different orientations of the same vehicle. However, these two characteristics are hard to be encapsulated into a single feature representation simultaneously with unified supervision. Here we propose a Disentangled Feature Learning Network (DFLNet) to learn orientation specific and common features concurrently, which are discriminative at details and invariant to orientations, respectively. Moreover, to effectively use these two types of features for ReID, we further design a feature metric alignment scheme to ensure the consistency of the metric scales. The experiments show the effectiveness of our method that achieves state-of-the-art performance on three challenging datasets.

scholarly journals Color Image Encryption using AES and RSA

2020 ◽  
Vol 9 (5) ◽  
pp. 547-550
Keyword(s):  
Data Security ◽  
Block Cipher ◽  
Color Image ◽  
Signal To Noise Ratio ◽  
Security Level ◽  
Change Rate ◽  
The Public ◽  
Key Block ◽  
Symmetric Key ◽  
Encryption Algorithms

Information security is an important task on multimedia and communication world. During storing and sharing maintaining a strategic distance from the outsider access of information is the difficult one. There are many encryption algorithms that can provide data security. In this paper two of the encryption algorithms namely AES and RSA are implemented for color images. AES (Advanced Encryption Standard) is a symmetric key block cipher published in December 2001 by NSIT (National Institute of Standards and Technology). RSA (Rivest-Shamir-Adleman) is an asymmetric key block cipher. It uses two separate keys, one for encryption called the public key and other for decryption called the private key. Both the implementation and analysis are done in Matlab. The quality and security level of both the algorithms is analysed based on various criteria such as Histogram analysis, Correlation analysis, Entropy analysis, NPCR (Number of Pixel Change Rate), UACI (Unified Average Changing Intensity), PSNR (Peak Signal-to-Noise Ratio).

What is the stock of the situation? A bibliometric analysis on social and environmental accounting research in public sector

2019 ◽  
Vol 32 (1) ◽  
pp. 21-41 ◽  
Author(s):  
Floriana Fusco ◽  
Paolo Ricci
Keyword(s):  
Public Sector ◽  
State Of The Art ◽  
Environmental Accounting ◽  
Future Research ◽  
Academic Journals ◽  
Environmental Reporting ◽  
Bibliometric Method ◽  
Content Type ◽  
The Public ◽  
Social And Environmental Reporting

PurposeThe purpose of this paper is to provide a picture of the state of the art in social and environmental accounting research applied to the public sector, highlighting different streams and the main gaps in current literature and providing input for future research.Design/methodology/approachA bibliometric method was used to analyse the characteristics, citation patterns and content of 38 papers published in international academic journals.FindingsThe findings show that the research on social and environmental reporting in the public sector is still at an early stage. Current investigations, although slowly on the increase, are still very few and localised. Most papers are about the reasons why public organisations report, what and how they report, but there are so many aspects that need to be investigated more in-depth or require extra validation in order to open new directions for future research, among which the relationship with and the differences between other non-financial type of reporting, namely ICR and IR.Research limitations/implicationsThe study shows some limitations, mainly related to the adoption of the bibliometric method. Indeed, it does not take into account books and chapters but only papers published in international and academic journals. This leads to exclude a significant part of the existing literature and other relevant contributions on the field.Originality/valueSocial and environmental reporting practices are quickly spreading in the public sector. The field is particularly interesting, given the specific connotations of this kind of organisations. However, the literature is clearly not exhaustive and there is not a comprehensive and systematic review of the state of the art on the subject.

Prioritizing Attention over Privacy: Analysis of Face Image Posting Behavior in Online Direct-to-Consumer Genetic Testing Forum (Preprint)

2021 ◽  
Author(s):  
Yongtai Liu ◽  
Zhijun Yin ◽  
Zhiyu Wan ◽  
Chao Yan ◽  
Weiyi Xia ◽  
...  
Keyword(s):  
Genetic Testing ◽  
Language Processing ◽  
Face Image ◽  
Online Forums ◽  
The Public ◽  
Image Sharing ◽  
Direct To Consumer ◽  
Face Images ◽  
Identity Disclosure ◽  
The Face

BACKGROUND As direct-to-consumer genetic testing (DTC-GT) services have grown in popularity, the public has increasingly relied upon online forums to discuss and share their test results. Initially, users did so under a pseudonym, but more recently, they have included face images when discussing DTC-GT results. When these images truthfully represent a user, they reveal the identity of the corresponding individual. Various studies have shown that sharing images in social media tends to elicit more replies. However, users who do this clearly forgo their privacy. OBJECTIVE This study aimed to investigate the face image sharing behavior of DTC-GT users in an online environment and determine if there exists the association between face image sharing and the attention received from others. METHODS This study focused on r/23andme, a subreddit dedicated to discussing DTC-GT results and their implications. We applied natural language processing to infer the themes associated with posts that included a face image. We applied a regression analysis to learn the association between the attention that a post received, in terms of the number of comments and karma scores (defined as the number of upvotes minus the number of downvotes), and whether the post contains a face image. RESULTS We collected over 15,000 posts from the r/23andme subreddit published between 2012 and 2020. Face image posting began in late 2019 and grew rapidly, with over 800 individuals’ revealing their faces by early 2020. The topics in posts including a face were primarily about sharing or discussing ancestry composition, and sharing family reunion photos with relatives discovered via DTC-GT. On average, posts including a face received 60% (5/8) more comments than other posts, and these posts had karma scores 2.4 times higher than other posts. CONCLUSIONS DTC-GT consumers in the r/23andme subreddit are increasingly posting face images and testing reports on social platforms. The association between face image posting and a greater level of attention suggests that people are forgoing their privacy in exchange for attention from others. To mitigate the risk of face image posting, platforms, or at least subreddit organizers, should inform users about the consequence of such behavior for identity disclosure.

Cloud Computing Applications in the Public Sector

2019 ◽  
pp. 1241-1272
Author(s):  
Amir Manzoor
Keyword(s):  
Cloud Computing ◽  
Public Sector ◽  
Data Privacy ◽  
State Of The Art ◽  
Specific Recommendation ◽  
Regulatory Issues ◽  
The Public ◽  
Cloud Adoption ◽  
Digital Services ◽  
Public Sector Organizations

Cloud computing brings key advantages to the governments facing conflicting IT challenges. However, the cloud paradigm is still fragmented and concerns over data privacy and regulatory issues presents significant barriers to its adoption. Cloud computing is expected to provide new ways to run IT in public sector. At the same time, it presents significant challenges for governments, and to make the most of cloud, public sector organizations need to make some important decisions. Governments planning to migrate to the cloud are actively moving to harness digital services but with different focus, reasons, and strategy. However, the degree of cloud adoption by the public sector around the globe varies significantly. Most governments are piloting cloud computing but there are huge differences between each country. This chapter explores the state of the art of cloud computing applications in the public sector; various implications and specific recommendation are also provided.

The State-of-the-Art Technology of Currency Identification

2018 ◽  
pp. 252-269
Author(s):  
Guangyu Wang ◽  
Xiaotian Wu ◽  
WeiQi Yan
Keyword(s):  
Feature Extraction ◽  
New Zealand ◽  
Comparative Study ◽  
State Of The Art ◽  
The State ◽  
Classification Algorithms ◽  
Security Issue ◽  
The Public ◽  
Us Dollar ◽  
Chinese Yuan

The security issue of currency has attracted awareness from the public. De-spite the development of applying various anti-counterfeit methods on currency notes, cheaters are able to produce illegal copies and circulate them in market without being detected. By reviewing related work in currency security, the focus of this paper is on conducting a comparative study of feature extraction and classification algorithms of currency notes authentication. We extract various computational features from the dataset consisting of US dollar (USD), Chinese Yuan (CNY) and New Zealand Dollar (NZD) and apply the classification algorithms to currency identification. Our contributions are to find and implement various algorithms from the existing literatures and choose the best approaches for use.

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