Reviewerly/exHarmony huggingface dataset:
Communications network security using quantum physics

Applications of quantum technologies are rapidly progressing in communications systems implementations. In particular, quantum key distribution (QKD) and quantum random number generation have become key applications for cryptography and physical layer security. Unlike classical cryptography and network security, in QKD, security is ensured by the laws of physics and is, in principle, unbreachable by an interceptor. In particular, peculiar properties and postulates of quantum physics, such as superposition, entanglement, and quantum measurement uncertainty, are exploited to achieve system security. Quantum random number generator (QRNG) is also an important component in the implementation of QKD protocols. Likewise, in QRNG, true randomness (unpredictability using past data and uniformity of statistical distribution) is guaranteed by the laws of quantum physics. In this study, we review prominent aspects of QKD and QRNG, related standards, protocols, and hardware components. Moreover, a comprehensive review of the current QKD protocols and quantum random number generation methods is also presented.
Orientation to the Pentatonic Scale

Abstract This unit introduces the m-r-d subset of the pentatonic scale. This unit is written to help students develop knowledge of both musical notation and performance. German solfège syllables are introduced, and exercises and assessment forms are provided.
Visualization for Emotion Detection in Mobile-Based Land Monitoring Using User-Centred Design

Many colleges employ online learning as media learning where each piece of multimedia, be it sound, film, or text, can receive feedback from students. The lecture wants to know about the emotions that students experienced when they accessed the media, such as happiness, disappointment, or unhappiness, and instructors want to know how joyful they felt. This study built a tool cell for online media to use in identifying emotions in column comments. This paper focuses on user experience (UX) design, which is based on the Human-Centred Design method that prioritizes empathy for users and focuses on user demands to meet the discovery of user wants and develop high-fidelity prototypes. The results of the testing show that the average accuracy is 1.68%, the average recall is 1.55, the average precision is 1.45, and the average accuracy for the use of this phone website is 80% for emotion recognition based only on a column of comment in the internet media.
Histopathological image-based breast cancer detection employing 3D-convolutional neural network feature extraction and Stochastic Diffusion Kernel Recursive Neural Networks classification

Among the various cancer categories, breast cancer diagnoses are commonly found in many women, and automatic classification of breast cancer images is a crucial task using computer-aided analysis. This paper proposed a method for the detection of histopathological image-based breast cancer and the main motive of the technique is to employ feature extraction and classification based on DL techniques. The input image is filtered using edge smoothening for noise removal and image resizing on the pre-processing method and used 3D-Convolutional Neural network (3D_CNN) for extracting the features of the image process. Extracted deep features have been given as input for the classification process using Stochastic Diffusion Kernel Recursive Neural Networks (SDKRNN). The suggested model combines the sturdiness of convolutional and kernel blocks and demonstrates performance stability when compared to existing techniques. The experimental results are assessed using a variety of performance metrics and compared to current breast cancer detection methodologies. The result demonstrated the experimental evaluation analyzed for various datasets in terms of accuracy, precision, F-1 score, specificity, and AUC of 98%, 93.8%, 89%, 80%, and 70% and it determined the outperforms in the detection of breast cancer.
Demonstrating Multi-modal Human Instruction Comprehension with AR Smart Glass

We present a multi-modal human instruction comprehension prototype for object acquisition tasks that involve verbal, visual and pointing gesture cues. Our prototype includes an AR smart-glass for issuing the instructions and a Jetson TX2 pervasive device for executing comprehension algorithms. With this setup, we enable on-device, computationally efficient object acquisition task comprehension with an average latency in the range of 150-330msec.
Analysis of Cryptography before Steganography Operation by ROC Curves and Confusion Matrices Criteria

The steganography algorithms based on media type, format and capacity are used for different applications. The use of cryptographic algorithms also depends on the type of application. The challenge that can be investigated is the use of cryptographic algorithms in the steganography process, which must be properly scrutinized due to the special sensitivities of these two technologies. The use of cryptographic algorithms in steganographic systems increases the security of hidden data, but this security level should not make the entropy more visible and did not consider other metric. For this reason, in this paper, two steganographic algorithms for JPEG image and two steganographic algorithms for audio in WAV format are investigated, so that before the steganographic operation, a cryptography algorithm is used to encrypt the message. In the following, after reviewing the steganographic algorithms using several valid steganalysis, the advantages of using and not using these cryptographic algorithms against their disadvantages are reviewed and suggestions about their use in steganography algorithms and systems are presented.
Dictionary Learning

This extraordinary three-volume work, written in an engaging and rigorous style by a world authority in the field, provides an accessible, comprehensive introduction to the full spectrum of mathematical and statistical techniques underpinning contemporary methods in data-driven learning and inference. This final volume, Learning, builds on the foundational topics established in volume I to provide a thorough introduction to learning methods, addressing techniques such as least-squares methods, regularization, online learning, kernel methods, feedforward and recurrent neural networks, meta-learning, and adversarial attacks. A consistent structure and pedagogy is employed throughout this volume to reinforce student understanding, with over 350 end-of-chapter problems (including complete solutions for instructors), 280 figures, 100 solved examples, datasets and downloadable Matlab code. Supported by sister volumes Foundations and Inference, and unique in its scale and depth, this textbook sequence is ideal for early-career researchers and graduate students across many courses in signal processing, machine learning, data and inference.
Variation of Playfair Cipher

Transmission of information plays a vital role in the world. Now-a-days, at a given point of time, two people are transmitting messages from one place to another irrespective of the distance between them. But the main concern is that how does it guarantee that the message which is received by the receiver is not tampered or is hundred percent confidential. Therefore, this transmission process always faces some problems such as complex working, integrity issues and attacks, which make us doubt whether the data source is correct or incorrect. For this reason, many authors have come up with different variations of encrypting the data. This paper illustrates a Playfair cipher algorithm integrated with MD5 hashing and seed-based algorithm. It is a variation of Playfair cipher which tries to overcome some of the issues which can be seen in other variations of Playfair cipher. It not only provides great range of characters to work with but also provides integrity and prevents our message from man-in-the-middle and brute-force attacks.
The Dynamics of a Bug Bounty Platform

A security vulnerability in software, often referred as a bug, is a weakness in software code that arises as a result of unforeseen design decisions or model mathematical inadequacies. It is a security problem that could be used in cyberattacks to gain entry to digitally stored data unless the defect is fixed with a software patch. We found that a growing community of developers can shift the production from inside the company to its ecosystem partners (eg. bug bounty hunters) using a comprehensive framework for code exposure. That is, instead of closed vertical integration, enterprises can opt to innovate utilizing open external contracts. It's preferable if the center of value creation shifts from within the company to outside. Digital commodities, unlike physical items, allow businesses to maximize spillovers. Bug Bounty Programs use crowdsourcing to find bugs. Bug Bounty Programs (BBPs) are becoming standard security practices within enterprises, thanks to the benefits of crowdsourcing flaw and vulnerability management. Bug bounty programs help businesses by enlisting the help of hackers who can find flaws in their software. Because these programs have access to a larger number of hackers or testers, the chances of detecting problems before malicious hackers try to exploit them are higher. It can be a good public relations option for businesses. These programs can also act as a signal to the public and regulators that a company's security program is well-developed. The relevance of these types of programs is expected to grow, as they have become an industry standard that should attract investment from all companies. We evaluate the existing competitors in the market and learn from the case studies accessible while designing our own bug bounty platform. We also look at the Vulnerability Market Mechanism as well as five key aspects of BBP practice: Scoping of BBPs, Timing of Crowd Engagement, Quality of Submission, Researcher-Firm Communication, and Hackers Motivation Management. We examine difficulties in each area and aim to put strategies in place to improve the effectiveness of BBP. This study contributes to research and practice by identifying difficulties and best practices in crowdsourcing information security for rapid vulnerability detection and mitigation.
An Improvised Approach for Website Domain Classification

In today's world, all search engine portals use suggestions to provide users with various options while searching for websites of a genre. The search engine needs to understand the genre of these websites to give the user relevant suggestions for websites. According to a survey, as of June 2021, about 1.86 billion websites are available on the Web. After looking at these statistics, a manual classification seems rather impractical and tedious. Owing to technological advancements, the authors have used machine learning to categorize websites into a group of preset genres provided in a curated dataset prepared in this particular work. The websites are classified into eleven domains according to popularity and user convenience. It was then made accessible through a dynamic web application that used the machine learning model to predict the type of website after taking the user's input. The authors have explored various classification models for this categorization and implemented the most suitable model with the highest accuracy as the final website domain classifier. The proposed model is also verified using the “web genre corpus 2004 (Genre-KI-04)” open dataset created for website genre classification.
Data Collection System based on PWA (Progressive Web App) as SaaS

The Data Collection System (Track Money)is a system for small and medium-sized businesses, which are looking for a reliable and cost-effective solution for data collection. This system will help save time and effort in tracking the business on various devices. This PWA system will collect bills and keep track of money. It will allow users to store their data of sales, purchases, profit, loss, and expenses for their business. Progressive Web Application (PWA) is a piece of software for applications provided online. Several apps need to be downloaded from Google Play or Apple store and installed on the system that occupies storage. PWA does not require any installation or publication in any store. Developers can simply publish it online as a website-like app that users can add to their home screen and use as an app. It works on any platform, such as desktops and smartphones. This app is created using the ReactJS framework as the user interface and the MongoDB API server based on Software as a Service (SaaS).
CITATIONS ANALYSIS OF PUBLICATIONS ON THE PAGES OF EDITIONS IN THE LIBRARY AND INFORMATION SPHERE

The editions of the library and information sector of the Republic of Belarus are reviewed: the scientific collection «Library Herald» devoted to the formation of modern library and information space and the prospects of library development; and the journal «Library World» which publishes articles on state policy in the area of libraries, the situation and prospects for the development of libraries in various systems and departments, and foreign experience. The authors of these publications have been monitored, and a detailed analysis of the references to the &#x0D; collection articles from 2010-2020 and the journal articles from 1997-2016 has been carried out.
THE FIRST SCIENTIFIC JOURNALS: THE HISTORY OF CREATION AND DEVELOPMENT

The article is devoted to the history of origin and development of the first scientific journals in the modern era in Western Europe in the second half of the XVII century. It is shown that the main task of journals at that time was to inform about the news of the world of science.
MAIN ACTIVITIES OF THE REPUBLICAN LIBRARY FOR SCIENCE AND TECHNOLOGY OF BELARUS AS A METHODOLOGICAL CENTER FOR SCIENTIFIC AND TECHNICAL LIBRARIES OF ENTERPRISES AND ORGANIZATIONS OF THE REPUBLIC OF BELARUS

The article describes the main activities of the Republican Library for Science and Technology (RLST) in the field of scientific and methodological support of scientific and technical libraries, standardization services, information and patent services of enterprises and organizations of the Republic of Belarus. The aim, objectives and working methods of the RLST in carrying out these activities are listed. Also, the professional development activities for scientific and technical libraries, organized by the RLST, are outlined.
PROFESSIONAL COMMUNICATION OF LIBRARY PROFESSIONALS: FROM TRADITIONAL TO DIGITAL FORMATS

The article presents the statements that reveal the essence of professional communication in librarianship. The objectivity of the accelerating transition from traditional forms of library communication to digital ones, their simultaneous development and application in the library and information environment is noted. The digital tools Anchor and OBS Studio that facilitate communication between library specialists and remote users in the global network space are characterized.
Human-guided deep learning with ante-hoc explainability by convolutional network from non-image data for pregnancy prognostication

Deep learning is applied in medicine mostly due to its state-of-the-art performance for diagnostic imaging. Supervisory authorities also require the model to be explainable, but most explain the model after development (post hoc) instead of incorporating explanation into the design (ante hoc). This study aimed to demonstrate a human-guided deep learning with ante-hoc explainability by convolutional network from non-image data to develop, validate, and deploy a prognostic prediction model for PROM and an estimator of time of delivery using a nationwide health insurance database. To guide modeling, we constructed and verified association diagrams respectively from literatures and electronic health records. Non-image data were transformed into meaningful images utilizing predictor-to-predictor similarities, harnessing the power of convolutional neural network mostly used for diagnostic imaging. The network architecture was also inferred from the similarities. This resulted the best model for prelabor rupture of membranes (n=883, 376) with the area under curves 0.73 (95% CI 0.72 to 0.75) and 0.70 (95% CI 0.69 to 0.71) respectively by internal and external validations, and outperformed previous models found by systematic review. It was explainable by knowledge-based diagrams and model representation. This allows prognostication with actionable insights for preventive medicine.
Multi-photon-addition amplified coherent state

State [Formula: see text] and state [Formula: see text] are same to state [Formula: see text], which is called as multi-photon-addition amplified coherent state (MPAACS) by us. Here, [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text] are photon number operator, creation operator, coherent state, gain factor, and an integer, respectively. We study mathematical and physical properties for these MPAACSs, including normalization, photon component analysis, Wigner function, effective gain, quadrature squeezing, and equivalent input noise. Actually, the MPAACS, which contains more nonclassicality, is an amplified version of photon-added coherent state (PACS) introduced by Agarwal and Tara [Phys. Rev. A 43, 492 (1991)]. Our work provides theoretical references for implementing amplifiers for light fields.
THE BIOGRAPHY OF THE WRITER AS AN ELEMENT OF THE CULTURAL AND PHILOSOPHICAL MODEL OF A LITERARY AND ARTISTIC WORK

In modern humanities, there is a search for optimal and more effective (compared to existing) research methods and strategies. The author of this article, as a research method, develops the general theoretical foundations of the cultural-philosophical model of a literary and artistic work, which can be used in the study of the creative heritage of various writers. The structural elements of the cultural-philosophical model of a literary and artistic work, along with the biography of the writer, include: the sum of humanitarian studies of a literary and artistic work, its concept sphere, main idea and genre. The description of the writer's biography as an element of the cultural-philosophical model of a literary and artistic work is the purpose of this article. The basis of the research is formed by general scientific methods and interdisciplinary methods of scientific knowledge. While working on the article, the author turned to cultural-philosophical analysis, content analysis of scientific literature, as well as to the biographical method. Based on the results of the study, the author comes to the conclusion that the biography of the writer, presented as an element of the model under consideration, has a significant cognitive potential, since it allows not only to present the creative and life path of the writer, but also to represent the features of his creative laboratory. The results of the study can be used not only in philosophical and cultural studies, but also in works of a wide humanitarian profile, as well as in the educational process.
Dense Residual Fusion and Spatial Local Filtering Low Light Dehazing Algorithm Based on Attention Mechanism

Image dehazing under low-light condition is easy to produce color distortion, patches and artifacts. To adapt to low-light condition, a dense residual fusion and spatial local filtering dehazing algorithm based on attention mechanism is proposed. Firstly, dense residual block is proposed to increase the depth of the neural network, so that the network can learn more advanced feature information. Then, the spatial and channel attention mechanism is introduced to filter and screen the features, so that the network can distinguish the uneven illumination areas and solve the problems of color distortion. The model adopts the method of spatial local filter enhancement to improve the contrast, clarity and visibility of dehazing results. Finally, a learning of joint loss function constraint network is designed to avoid error amplification and learning hybrid degradation of series structure. In the PyTorch environment, the night urban synthetic haze dataset (NHR) is used for testing and compared with the existing dehazing algorithms such as FFANet and GridDehaze. The experimental results show that compared with other dehazing algorithms, proposed method improves PSNR by 8.01‒14.16 dB and increases SSIM by 0.10‒0.36. In addition, proposed method solves the problems of color distortion, plaque and artifact.
Realistic 3D Face Reconstruction Method for Single Image

To solve the problem that the 3DMM parameter fitting methods cannot generate realistic 3D face, a single-image realistic 3D face reconstruction method based on deep learning is proposed. Firstly, the RP-Net regression network is constructed, and a dataset containing 50 000 face images is constructed at the same time. The parameters are learned from the input images, and the face model is fitted to generate the 3D face geometry. Secondly, weakly supervised learning is performed by constructing a multi-level loss function, which includes low-level pixel loss, landmark loss, and high-level identity loss. Thirdly, a realistic face texture is generated by means of texture mapping. Finally, two real face data and one generated data are used to compare experiments with recent 3D face reconstruction methods. The factors affecting the reconstruction such as lighting, expression, and steering are used to test proposed method, and quantitatively evaluate the reconstruction by SSIM and PSNR. These results show that proposed method can generate accurate face shapes and realistic face textures. Compared with the recent 3D face reconstruction method, the training time and number of iterations of the proposed method are reduced by 6% and 13%, respectively, the SSIM value is increased by 0.005‒0.010, and the PSNR value is increased by 0.03‒0.08 dB on average.
3D MODELING FOR LEATHERGOODS

Leather good products are intended to complete the outfit having an important aesthetic but also functional attributes. A distinct category of leather goods is represented by those products that are attached to the body. The positioning of these products in relation to the body involves a lot of design restrictions. One of the most significant restrictions is the ability not to affect the freedom of movement of the wearer. 3D modelling can be used for a good visualization of the model, on one hand, and adjusted it on different parts of the human body, on the other hand. Any product can be 3D modeled using specialized software and modeling techniques for video games. This paper presents the 3D modeling stages of a bum bag using modeling techniques for video games. The steps presented for creating the product in 3D represents a general "workflow". In order to complete the object, in working mode, multiple transition will be made from one program to another following specific steps for completion. They are used in different areas such as movies, games or 3D printers for toys. The program used are Zbrush &gt; RizomUV &gt; AutodeskMaya &gt; SubstancePainter &gt; Marmoset ToolBag3. In order to transform from 3D to 2D and pattern making was used MarvelousDesigner9 program. Using these programs can lead to student attractiveness and a better understanding of the steps of creating a leather good product. The objective of the paper was to present a creative and attractive way for students to improve their learning experience.