Reviewerly/exHarmony huggingface dataset:
Impact of Desert Aerosols on the Solar Radiation of a Solar Central Photovoltaic (PV): A Modelling Approach

This work focuses on modeling the impact of desert aerosols on a central solar photovoltaic (PV). Our studied physical model is comparable to a multilayer. We have described and discretized the mathematical equations which govern the physical model. Also, we analyzed the influence of the parameters \(\tau\)a and X on the solar radiation received at the surface of solar PV modules. The results of the study taken from Figs. 6(a)-(d) representing the variations of the global solar radiation on the solstices and equinoxes as well as the 21 of the months of the year days understood show that : if \(\tau_{a}\) = 0 and X = 0, IC = 67.87% ; if \(\tau_{a}\) = 0.5 \(\mu\)m and X = 0.5 \(\mu\)m, IC = 21% ; if \(\tau_{a}\) = 1.8 \(\mu\)m and X = 0.8 \(\mu\)m, IC = 12% and if \(\tau_{a}\) = 1.5 \(\mu\)m and X = 1.5 \(\mu\)m then IC = 4%. These results show that desert aerosols significantly influence the global solar radiation received. Unfortunately, this influence lowers the productivity of the central solar PV in general. The present study aims global to investigate the influence of desert aerosols on the production yield of the IRSAT solar central PV and characterize the aerosols impact on the production yield of the solar central PV. The specific objectives of the study are to : (i) evalute the optical depth of desert aerosols in the atmosphere above the solar central PV ; (ii) model the process of a simultaneous impact of the dust suspended in the atmosphere and / or deposited on the solar PV field ; (iii) evaluate the impact of desert aerosols (to different suspension layers and / or disposition) on incident (direct, diffuse, thoughtful and global) solar radiation and production yield of solar PV solar systems.
K-means on Multi-networks

Many methods have trust that there has to have some common clustering in the networks, one of the methods are multi view and multidomain network clustering. These methods were specially proposed for multi-networks resulting in very good and accurate results in fact, it showed way better results than individual networks, there still exists those networks who always bring complex results on such clustering structure. Different-different groups makes better cluster and much better clustering performance is achieved. So, such a method is needed who selects the group of networks on its own so here networks that contains or carries same group should share a common clustering structure. To this problem, we have a best solution to this that we apply this problem with K-means, K-means to group and perform clustering on multi networks.
Continual Learning of Long Topic Sequences in Neural Information Retrieval

In information retrieval (IR) systems, trends and users' interests may change over time, altering either the distribution of requests or contents to be recommended. Since neural ranking approaches heavily depend on the training data, it is crucial to understand the transfer capacity of recent IR approaches to address new domains in the long term. In this paper, we first propose a dataset based upon the MSMarco corpus aiming at modeling a long stream of topics as well as IR property-driven controlled settings. We then in-depth analyze the ability of recent neural IR models while continually learning those streams. Our empirical study highlights in which particular cases catastrophic forgetting occurs (e.g., level of similarity between tasks, peculiarities on text length, and ways of learning models) to provide future directions in terms of model design.
Textbook functions in the development of cognitive independence of future music teachers

The article is devoted to the issues of competence of future music teachers, the composition of the necessary competencies, the features of their formation in the learning process, the specifics of the pedagogical activity of a teacher-musician. The pedagogical conditions necessary for the formation ofprofessional competencies of music teachers are considered. Particular attention is paid to musical performance competence, which forms the basis of the special competences of a music teacher. The paper analyzes the general and special categories of competencies that music teachers need to possess. Since the specificity of the subject “Music” is associated with multifunctionality and an increased emotionally creative component, and require the development of special competencies related to musical performance, conducting and choral activities, as well as the need to organize special emotionally enriched, psychologically comfortable, dialogic relationships with students.
A Web-Based Recommendation Mechanism for Learning Objects Combining Ontologies and Zero-Shot Learning

Content management, selection and reuse is a difficult task especially for educational purposes. Flat metadata aggregations lack semantic interoperability and content is often poorly indexed thus making its discovery and integration troublesome. In this paper we propose a web interface for managing learning objects that leverages ontologies, automated subject classification and scoring to aid users and curators overcome these obstacles. We examine and document requirements and design decisions spanning data handling, storage, display, and user interaction. Through research and comparative evaluation, we choose an appropriate database layer and corresponding web framework for the application’s development. The app is capable of consuming metadata from other repositories but also maintains a local pool of learning object metadata where users can collaboratively contribute on content indexing and recommendation.
Expression for primitive idempotents of length 8pn and corresponding codes

The group algebra FG of the group G of order 8pn over the field F of prime power order q, where p is an odd prime n≥1, q is of the form 8k+1 and q is primitive root modulo pn, have 8(n+1) primitive idempotents. The explicit expressions for these idempotents are obtained. Generating polynomials, minimum distances and dimensions for the corresponding minimal cyclic codes are also obtained.
The Theory of Relational Problem-Solution Dualities, The Unity of Knowing, The Unity of Science and the Diversity in Knowledge

This chapter is used to present the theory of problem-solution dualitiesProblem-solution dualities as the first part of the general theory of opposites where the second part is the theory of problem-solution dualities which will be taken up in the next chapter. It discusses the conditions of the nature of problems relative to solutions in dualistic-polar structures with relational continua, unity and give-and-take-sharing modes in the space of fundamental-applies dualities to provide conditional connectivity to the development of the theory of polarities. The concepts of ontological and epistemological spaces are introduced, defined, explicated and connected to the space of problem-solution dualitiesProblem-solution dualities. and the connectivity of these concepts to the roles they play in the knowing process as intellectual investment flows and the production of information-knowledge system as intellectual capital accumulation stocks is then explained. The space of incentive-disincentive dualities is introduced and linked to the space of cost-benefit dualities in order to establish the concepts of primary-derived spaces and parent-offspring processes relative to the elements in the space of problem-solution dualitiesProblem-solution dualities as transformational elements where problems are transformed into solutions to give rise to new problems over the multiplicity of cost-benefit or destruction-construction enveloping that establishes the space of problem-solution genetic paths of socio-natural variety dynamics. The space of problem-solution dualitiesProblem-solution dualities are established over the space of imagination-reality dualitiesImagination-reality dualities which is shown as a sub-space of actual-potential dualitiesActual-potential dualities that constitutes the space of ontological-epistemological dualities.
Real-time polarization compensation system for wavelength division multiplexing in low noise fiber channel based on single photon counting feedback

The physical effects such as random birefringence of fiber optic channels due to environmental influences make the optical signals transmitted in them have sensitive polarization variations, which seriously affects the performance of polarization biased code quantum key distribution systems. In this paper, a low-noise fiber channel wavelength division multiplexing real-time polarization compensation system is presented, where single photon counting is used as a feedback signal. The system can acquire the fiber channel polarization change information by detecting the photon counting of the conjugate reference light. In the system, the compensation algorithm is designed to control the electric polarization controller to calibrate the polarization state of the quantum signal light under the corresponding polarization base in real time, and the stable fiber channel polarization compensation is successfully achieved. In order to verify the effectiveness of the compensation system, a quantum key distribution test based on BB84 protocol with a transmission distance of 25.2 km is conducted, and stable test results of up to 8 hours are obtained in the laboratory environment and the simulated metropolitan area network buried fiber environment, with the average quantum bit error rate being 0.52% and 1.25%, respectively. The experimental results show that this system can guarantee the stable operation of polarization-encoded quantum key distribution in the buried fiber environment in urban areas.
Off-Line Writer Identification Based on Small Segments of Handwritten Text and Convolutional Neural Networks

This paper proposes a new method for writer identification based on small fragments of handwritten text randomly obtained from a paragraph. The main contribution of this work is to show that small fragments carry enough biometric information for writer identification. A second contribution is the creation of 2 repositories of images of handwritten text from 50 writers. The first one is made up of 4 text paragraphs of 64 words in high resolution per writer. The second one contains more than 700 thousand fragments of text per writer. Experiments were conducted with different Convolutional Neural Networks, considering the VGG-16, VGG19, InceptionV3, ResNet-50 and MobileNetV2m models. 2 classification schemes were implemented. First, the classification of individual fragments and, second, the classification of groups of fragments. The best results were obtained using groups of fragments, achieving accuracy of 96% on the identification of a text with the same semantic content and of 87% on the identification of the writer considering a text with different semantic content.
Cloud Authentication Using FIDO Compliant Java Card Technology Secure Elements

The necessity of using secure elements for accessing different clouds or blockchain exchange websites in a secure manner has increased over years. Most of the websites and cloud platforms offer second-factor authentication as mobile application, OTP token, or even biometric key. The technology evolved and a market requirement appeared regarding the access with first and second factor as a combination between biometry and public-key cryptography, therefore the non-usage of the passwords which often are not strong enough for the authentication. The first section is an introduction in the set of the standards for FIDO authentication and in the second section, the authors present a proof of concept solution for Cloud authentication using Java Card Secure elements. The last section offers a view of a benchmark regarding the speed of performing cryptographic algorithms required by FIDO using different secure elements.
Traditional IPRs and Open Access Initiatives: Achieving a Fine Balance

This paper had critically examined the tension between Open Access Initiatives and Traditional Intellectual Property Rights and the challenges that make a balance unobtainable, which has become a major issue. This work further posits that; IPR and Open Access are diametrical, to the point where accepting one is harmful to the other. Regardless of these differences, this paper examines and suggest the need to have a fine balance by taking into consideration their respective benefits to society. It is crystal clear that IPR registration largely consists of securing one's intellectual work for innovations and creative works, indicating its source, and granting the owner limitless ownership over that specific product for a set period. However, Inventors or authors may think about the ramifications of doing something for the greater good, but they are also likely to think about how profitable their innovation will be, thus obtaining a fine balance between Traditional Intellectual Property Rights and Open Access Initiatives can be challenging and almost look unobtainable. Consideration of all the above formed the gamut of this entire paper.
Enhancement of IoT Security by Integration of Convolutional Neural Network and Image Processing

This research is focusing on enhancement of Internet of Things security by integration of convolutional neural network mechanism to image processing. This research paper has considered various image processing mechanisms such as edge detection and used convolutional neural network for pattern classification. In the IoT environment, simulation has been performed by capturing images by camera, and face mask pattern has been detected by convolutional neural network after applying edge detection mechanism in order to increase the accuracy as well as performance. It has been concluded that the proposed simulation performed to detect the face mask is taking less space as compared to previous research. Moreover, the time consumption in case of proposed work is less than previous research. The edge detection mechanism used in research has increased the performance along with resolving storage issues. After elimination of unnecessary content, it has become convenient for convolutional neural network classifiers to train and test the image dataset rapidly without wasting storage space in order to get more accurate results.
Short Introduction to Decorators

In this appendix, I would like to introduce decorators, another topic that allows us to express solutions to cross-cutting functionalities elegantly. Decorators are useful for parameter checks, for example, and are used primarily in this book for advanced recursion topics.
Landau-type sudden transitions of quantum correlations

Abstract Sudden changes of quantum correlations in the Bell-diagonal states are well-known effects. They occur when the set of optimal parameters that determine the quantum correlation consists of isolated points and optimal parameters during the evolution of the system jump from one such point to another (e.g., the optimal measurement angle of the quantum discord changes discontinuously from zero to π /2 or vice versa). However, when considering more general X quantum states, we found that quantum discord and one-way quantum work deficit can experience sudden changes of other kinds. Namely, the optimal measurement angle may suddenly start to shift continuously from its stationary value 0 or π /2 to an intermediate optimal measurement angle ϑ ∈ (0, π /2). This leads to a new behavior of quantum correlations, which is mathematically described by the Landau phenomenological theory of second-order phase transitions. In addition, for the one-way quantum work deficit, we found cases where the optimal measurement angle jumps from zero to a nonzero step less than π /2, and then continuously changes its value. This behavior of quantum correlation is similar to a first-order phase transition in Landau’s theory. Dependencies of quantum discord and one-way quantum work deficit near the boundaries, which separate regions with state-dependent (variable) and state-independent (stationary, constant) optimal measurement angles, are examined in detail on an example of the XXZ spin model in an external field at thermal equilibrium.
Formation of professional and pedagogical interest of future primary school teachers

The article deals with the issue of developing the professional interest of students of a pedagogical university. This problem is of particular importance in the preparation of primary school teachers, since the foundations of the necessary knowledge, skills and abilities of students are laid precisely in the first years of their schooling. The effectiveness of his professional activity depends on the presence of a genuine, deep professional interest of a primary school teacher. The article traces the connection of professional interest with the concept of “professional and pedagogical orientation of the individual.” In this regard, it is noted that professional interest can be considered as a complex personal formation that is part of the personality orientation. In this paper, an attempt is made to distinguish between the concepts of “professional pedagogical interest” and “interest in the teaching profession”. The article draws attention to the fact that it is necessary to include future teachers in active activities as close as possible to professional ones, during which conditions are created conducive to the formation of a specific idea of a modern school, the functions of a teacher, the educational process, in addition, a positive emotional attitude is strengthened. for future teaching activities.
WebRTcmix - A Cloud-Based API for the Music Programming Language RTcmix

As the technologies continue to grow, traditional standalone music programming languages and their local IDEs have shown the drawbacks that could not meet people’s demands on today’s scenes, especially for cross-platform projects. In this works, we investigate a cloud-based API for the music programming language RTcmix based on Google Cloud Run and named it the WebRTcmix. This API will help the users to deploy the music programming language under almost any web-connected environment such as browser apps, mobile apps, games, even single-board computers in no time.
Finite element tearing and interconnecting-1 method for the solution of the topology optimisation problem

The algebraic system derived from the descritisation of problems arising in physical field and engineering science appears to be challenging to solve due to the strong nonlinearity and the large size of such problems. Parallel processing is shown to be an efficient technique to handle the computational complexity associated with solving large linear systems and this is readily obtained by using one of the most popular methods which is known to be suitable for parallelisation, namely, domain decomposition methods. In this work, we apply finite element tearing and interconnecting method within the framework of topology optimisation, we describe a methodology that brings together existing fast algorithms for topology optimisation and FETI for solving the resulting large-scale linear systems.
Parallel Support Vector Machines: The Balanced Cascade SVM

Cascade SVM (CSVM) can group datasets and train subsets in parallel, which greatly reduces the training time and memory consumption. However, the model accuracy obtained by using this method has more errors than direct training. To reduce these errors, we analyze the causes of error in group training and summarize the grouping characteristics under ideal conditions, without error. A balanced cascade SVM (BCSVM) algorithm is proposed, which balances the sample proportions in the subsets after grouping to ensure that the sample proportions in the subsets are the same as those in the original dataset. At the same time, we demonstrate that the accuracy of the model obtained by the BCSVM algorithm is higher than that of the CSVM. Finally, two common datasets are used for experimental verification, and the results show that the accuracy error obtained by the BCSVM algorithm is reduced from 1\% of CSVM to 0.1\%, which amounts to a reduction by an order of magnitude.
Socio-Cultural Change and Education: Implications for Media Education

The transition from industrialism to informationism, and the creation of a global economy, a new type of society and culture, starts a new phase of development, related to the revolution of information technologies and knowledge-based economy. The world is entering a new era, an information era generated by the information technology revolution and the rapid development of science and education. On our eyes we can see the rising global network society, completely opened to social communication of virtual communities, accepting cultural diversity, creating its own rules of social life, transnational, democratic, pictorial and audiovisual, collecting and processing information, working, paying bills online, investing, absorbing specialists with high digital and communication skills. All this poses new unimaginable challenges to education on a global scale, as it is faced with absolutely new demands and tasks, expressed by the global economy, multinational corporations, virtual culture, national values and the tensions of globalization.
Revealing Chaos-Based Steganographic Transmission by the Recurrence Quantification Analysis

Among modern approaches to cryptography and steganography, a technique based on the use of chaos theory is rapidly developing. Using noise-like chaotic signals and special modulation methods, it is possible to reliably conceal both the message content and the fact of its transmission. To attack this encryption scheme, various techniques such as spectral or envelope analysis can be applied. In this paper, we explore the possibilities of recurrent quantitative analysis to recover the bitstream encrypted with the chaotic parameter modulation. The results show its higher performance compared to the method based on the spectrogram analysis.
Native Bacteria Isolated from Djebel Onk Deposits (Algeria) Reveal Efficient Metal Biosorption Properties

Highlights• Raw phosphate is contaminated with dolomite and heavy metals• Biosorption is an eco-friendly method to purify ore and post-flotation wastes• Bacillus sp. efficiently accumulates Cd and Mg in a wide range of pH• Native bacteria accumulate more metals than a reference Bacillus sp. strain
Modification of the LSB Implementation Method of Digital Watermarks

Steganography methods allow not only to secretly transmit data but also to solve the problem of noise-tolerant authentication and protection of information from unauthorized copying. They can track information spread on communication networks and search for information in multimedia databases. The paper gives a brief comparative description of steganographic methods, requirements for steganographic systems, containers, applications, and limitations in implementing such systems. It is shown that the most effective application of steganography is the introduction of protected files resistant to distortion of digital watermarks. The authors describe the methods of digital steganography realization in sound files and images. Also, they considered a general model of the steganography process, its features concerning the degree of compression, and the size of data that can be hidden in it. It is shown that steganography can be successfully used in the case of containers with graphic, audio, and video information. The software has been developed to study the modified LSB method and change the parameters of the CEV during encryption, which allows you to implement this method in practice to hide the encrypted content of a file of any format or embed a digital watermark in media files.