scholarly journals Topic-aware Neural Linguistic Steganography Based on Knowledge Graphs

2021 ◽  
Vol 2 (2) ◽  
pp. 1-13
Author(s):  
Yamin Li ◽  
Jun Zhang ◽  
Zhongliang Yang ◽  
Ru Zhang
Keyword(s):  
Privacy Protection ◽  
Covert Communication ◽  
Text Generation ◽  
Specific Topic ◽  
The Core ◽  
Proposed Model ◽  
Linguistic Steganography ◽  
Knowledge Graphs ◽  
Communication Privacy

The core challenge of steganography is always how to improve the hidden capacity and the concealment. Most current generation-based linguistic steganography methods only consider the probability distribution between text characters, and the emotion and topic of the generated steganographic text are uncontrollable. Especially for long texts, generating several sentences related to a topic and displaying overall coherence and discourse-relatedness can ensure better concealment. In this article, we address the problem of generating coherent multi-sentence texts for better concealment, and a topic-aware neural linguistic steganography method that can generate a steganographic paragraph with a specific topic is present. We achieve a topic-controllable steganographic long text generation by encoding the related entities and their relationships from Knowledge Graphs. Experimental results illustrate that the proposed method can guarantee both the quality of the generated steganographic text and its relevance to a specific topic. The proposed model can be widely used in covert communication, privacy protection, and many other areas of information security.

Propp Revisited: A Structural Analysis of Vuk Karadžić’s Collection Serbian Folk Fairy Tales

2020 ◽  
Vol 65 (3) ◽  
pp. 335-367
Author(s):  
Dijana Vučković ◽  
Vesna Bratić
Keyword(s):  
Fairy Tales ◽  
Fairy Tale ◽  
Folk Tales ◽  
The Core ◽  
Proposed Model ◽  
Core Feature ◽  
Vuk Stefanovic Karadzic ◽  
Plot Structure ◽  
Vladimir Propp

SummaryIn the mid-19th century Vuk Stefanović Karadžić collected folk tales in the broader South-Slavic region and published them in a collection titled Serbian Folk Tales. Folk fairy tales make the major part of the collection. In this paper, the authors determine the folk fairy tale structure according to the methodology proposed by Vladimir Propp in the Morphology of the Folktale. The aim of the paper is to investigate, whether these fairy tales can be fully described using Propp’s Morphology. Propp’s model of the meta-folk fairy tale was developed inductively based on a rich, comprehensive, yet limited, corpus of Russian folk fairy tales, which opens up space for further testing of the proposed model.The hypothesis was set that the analyzed folk fairy tales completely conform to the plot structure of the meta-folk fairy tale with a maximum of 31 functions as proposed by Propp. The hypothesis is grounded in: 1. the time when the folktales were collected (mid-19th century, the same time as the Russian collection analyzed by Propp) and 2. the similarity of the South Slavic peoples with the peoples of the Slavic East.However, after categorial and structural analyses of the corpus were performed, it was clear that the hypothesis could not be accepted in its entirety. In the analyzed folk fairy tales, no new functions were found as compared to the 31 functions identified by Propp, but some of these functions were altered as compared to those to be expected in folk tales. This alteration occurred not only regarding the changed order of functions, assimilation and cases of dual morphological meanings of functions, but also in terms of the fantastic category of the marvelous, which is the core feature of the fairy tale genre, whose nature was changed. The study identified the rationalization of some magical motifs, which partially mitigates the quality of the miraculous in the fairy tale and found out that, in some cases, the marvelous was mitigated and “shifted” towards the (merely) fantastic. This was achieved by introducing oniric elements. One of the important conclusions of our study of the fairy tale is that these fairy tales, although labeled as folk tales, feature significant authorial intervention.

scholarly journals Novel Linguistic Steganography Based on Character-Level Text Generation

Mathematics ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1558 ◽  
Author(s):  
Lingyun Xiang ◽  
Shuanghui Yang ◽  
Yuhang Liu ◽  
Qian Li ◽  
Chengzhang Zhu
Keyword(s):  
Large Scale ◽  
Experimental Results ◽  
Selection Strategy ◽  
Generation Model ◽  
Text Generation ◽  
Embedding Capacity ◽  
Secret Information ◽  
Prediction Probability ◽  
Linguistic Steganography

With the development of natural language processing, linguistic steganography has become a research hotspot in the field of information security. However, most existing linguistic steganographic methods may suffer from the low embedding capacity problem. Therefore, this paper proposes a character-level linguistic steganographic method (CLLS) to embed the secret information into characters instead of words by employing a long short-term memory (LSTM) based language model. First, the proposed method utilizes the LSTM model and large-scale corpus to construct and train a character-level text generation model. Through training, the best evaluated model is obtained as the prediction model of generating stego text. Then, we use the secret information as the control information to select the right character from predictions of the trained character-level text generation model. Thus, the secret information is hidden in the generated text as the predicted characters having different prediction probability values can be encoded into different secret bit values. For the same secret information, the generated stego texts vary with the starting strings of the text generation model, so we design a selection strategy to find the highest quality stego text from a number of candidate stego texts as the final stego text by changing the starting strings. The experimental results demonstrate that compared with other similar methods, the proposed method has the fastest running speed and highest embedding capacity. Moreover, extensive experiments are conducted to verify the effect of the number of candidate stego texts on the quality of the final stego text. The experimental results show that the quality of the final stego text increases with the number of candidate stego texts increasing, but the growth rate of the quality will slow down.

Model and Method for Contributor’s Quality Assessment in Community Image Tagging Systems

2018 ◽  
pp. 45-51
Author(s):  
A. V. Ponomarev
Keyword(s):  
Large Scale ◽  
Wide Spectrum ◽  
Preference Relation ◽  
Pairwise Comparison ◽  
Ground Truth ◽  
Comparison Method ◽  
Characteristic Matrix ◽  
Image Tagging ◽  
Proposed Model

Introduction: Large-scale human-computer systems involving people of various skills and motivation into the information processing process are currently used in a wide spectrum of applications. An acute problem in such systems is assessing the expected quality of each contributor; for example, in order to penalize incompetent or inaccurate ones and to promote diligent ones.Purpose: To develop a method of assessing the expected contributor’s quality in community tagging systems. This method should only use generally unreliable and incomplete information provided by contributors (with ground truth tags unknown).Results:A mathematical model is proposed for community image tagging (including the model of a contributor), along with a method of assessing the expected contributor’s quality. The method is based on comparing tag sets provided by different contributors for the same images, being a modification of pairwise comparison method with preference relation replaced by a special domination characteristic. Expected contributors’ quality is evaluated as a positive eigenvector of a pairwise domination characteristic matrix. Community tagging simulation has confirmed that the proposed method allows you to adequately estimate the expected quality of community tagging system contributors (provided that the contributors' behavior fits the proposed model).Practical relevance: The obtained results can be used in the development of systems based on coordinated efforts of community (primarily, community tagging systems). 

Assessment of multimorbidity of diseases in geriatric practice

2020 ◽  
pp. 17-21
Author(s):  
Mark Oprenko
Keyword(s):  
Quality Of Life ◽  
The Core ◽  
Definition Of

The definition of the multimorbidity concept reveals insufficient specificity of the comorbidity and multimorbidity definitions and, as a result, confusion in the use of these terms. Most authors are unanimous that the “core” of multimorbidity is presence of more than one disease in a patient. These coexisting diseases can be pathogenetically interconnected and non-interconnected. Regardless, the degree of multimorbidity always affects prognosis and quality of life.

STUDI ANALISIS DAMPAK PADEMI COVID-19 TERHADAP EKSISTENSI PEMBELAJARAN PENDIDIKAN AGAMA ISLAM DI INDONESIA

Edupedia ◽  
2020 ◽  
Vol 5 (1) ◽  
pp. 45-53
Author(s):  
Ilzam Dhaifi
Keyword(s):  
Online Education ◽  
Religious Education ◽  
Virtual Classroom ◽  
Education Services ◽  
Religious Consciousness ◽  
The Core ◽  
Equal Education ◽  
The World ◽  
The Government

The world has been surprised by the emergence of a COVID 19 pandemic, was born in China, and widespread to various countries in the world. In Indonesia, the government issued several policies to break the COVID 19 pandemic chain, which also triggered some pro-cons in the midst of society. One of the policies government takes is the closure of learning access directly at school and moving the learning process from physical class to a virtual classroom or known as online learning. In the economic sector also affects the parents’ financial ability to provide sufficient funds to support the implementation of distance learning applied by the government. The implications of the distance education policy are of course the quality of learning, including the subjects of Islamic religious education, which is essentially aimed at planting knowledge, skills, and religious consciousness to form the character of the students. Online education must certainly be precise, in order to provide equal education services to all students, prepare teachers to master the technology, and seek the core learning of Islamic religious education can still be done well.

Estudio del proceso de lavado de contenedores para eliminar tiempos y movimientos innecesarios, caso: Wash Containers S.A de C.V.

2020 ◽  
pp. 25-36
Author(s):  
Juan Alfredo Lino-Gamiño ◽  
Carlos Méndez-González ◽  
Eduardo José Salazar-Araujo ◽  
Pablo Adrián Magaña-Sánchez
Keyword(s):  
Business Process ◽  
Value Chain ◽  
Process Management ◽  
Core Business ◽  
The Core ◽  
Washing Process ◽  
Overall Performance ◽  
The Times

In the value chain it is important to keep in mind the core business of the company, since it depends largely on the competitiveness of the company and its overall performance, bearing in mind that all business indicators depend on it. In this work we will study the washing process within the company WASH CONTAINERS SA DE CV, to improve the washing processes and in this way reduce times and movements in the process leading the company to reduce costs considerably within the operations company daily, having a more competitive operation and with greater profit margin in its business process. Goals: It Improve the logistics of the movement of containers for washing and with it the core business of the company. Methodology: The action research will be applied applying Business Process Management for the improvement of processes in situ, it will be developed in a certain period of time and with that it will establish an improvement projection. Contribution: The improvement of the times for the disposal of the containers and their subsequent use, allows a better competitiveness and with it the income of the company, on the other hand, the transport companies improve in performance in quantity, quality of disposition and with it their income.

Citizen Deliberation Online

2019 ◽  
pp. 689-712
Author(s):  
Patrícia Rossini ◽  
Jennifer Stromer-Galley
Keyword(s):  
Political Engagement ◽  
Future Research ◽  
The Internet ◽  
Digital Platforms ◽  
The Core ◽  
Political Conversation ◽  
Political Talk ◽  
Citizen Deliberation ◽  
The Impact

Political conversation is at the heart of democratic societies, and it is an important precursor of political engagement. As society has become intertwined with the communication infrastructure of the Internet, we need to understand its uses and the implications of those uses for democracy. This chapter provides an overview of the core topics of scholarly concern around online citizen deliberation, focusing on three key areas of research: the standards of quality of communication and the normative stance on citizen deliberation online; the impact and importance of digital platforms in structuring political talk; and the differences between formal and informal political talk spaces. After providing a critical review of these three major areas of research, we outline directions for future research on online citizen deliberation.

scholarly journals Research on Blockchain-Based E-Bidding System

2021 ◽  
Vol 11 (9) ◽  
pp. 4011
Author(s):  
Dan Wang ◽  
Jindong Zhao ◽  
Chunxiao Mu
Keyword(s):  
Data Transmission ◽  
Privacy Protection ◽  
Graph Isomorphism ◽  
Third Party ◽  
Business Logic ◽  
Core Concept ◽  
The Core ◽  
Blockchain Technology ◽  
Smart Contract ◽  
Bidding Process

In the field of modern bidding, electronic bidding leads a new trend of development, convenience and efficiency and other significant advantages effectively promote the reform and innovation of China’s bidding field. Nowadays, most systems require a strong and trusted third party to guarantee the integrity and security of the system. However, with the development of blockchain technology and the rise of privacy protection, researchers has begun to emphasize the core concept of decentralization. This paper introduces a decentralized electronic bidding system based on blockchain and smart contract. The system uses blockchain to replace the traditional database and uses chaincode to process business logic. In data interaction, encryption techniques such as zero-knowledge proof based on graph isomorphism are used to improve privacy protection, which improves the anonymity of participants, the privacy of data transmission, and the traceability and verifiable of data. Compared with other electronic bidding systems, this system is more secure and efficient, and has the nature of anonymous operation, which fully protects the privacy information in the bidding process.

scholarly journals Nodule Detection with Convolutional Neural Network Using Apache Spark and GPU Frameworks

2021 ◽  
Vol 11 (6) ◽  
pp. 2838
Author(s):  
Nikitha Johnsirani Venkatesan ◽  
Dong Ryeol Shin ◽  
Choon Sung Nam
Keyword(s):  
Neural Network ◽  
Radiation Dose ◽  
Convolutional Neural Network ◽  
Model Performance ◽  
Performance Comparison ◽  
Apache Spark ◽  
Training Time ◽  
Learning Framework ◽  
Proposed Model

In the pharmaceutical field, early detection of lung nodules is indispensable for increasing patient survival. We can enhance the quality of the medical images by intensifying the radiation dose. High radiation dose provokes cancer, which forces experts to use limited radiation. Using abrupt radiation generates noise in CT scans. We propose an optimal Convolutional Neural Network model in which Gaussian noise is removed for better classification and increased training accuracy. Experimental demonstration on the LUNA16 dataset of size 160 GB shows that our proposed method exhibit superior results. Classification accuracy, specificity, sensitivity, Precision, Recall, F1 measurement, and area under the ROC curve (AUC) of the model performance are taken as evaluation metrics. We conducted a performance comparison of our proposed model on numerous platforms, like Apache Spark, GPU, and CPU, to depreciate the training time without compromising the accuracy percentage. Our results show that Apache Spark, integrated with a deep learning framework, is suitable for parallel training computation with high accuracy.

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