Reviewerly/exHarmony huggingface dataset:
Actual socio-humanitarian problems of strengthening the subjectness of the Russian Federation

In the context of the growing conflict with the “collective West”, it is necessary to create adequate mechanisms for governing the country, focused on consolidating the state, soci­ety and business, on strengthening its subjectness to ensure life and development. Philo­sophical foundations are proposed to justify the increase in the role of subjectness and the basic characteristics of subjectness are considered. The analysis of the current state of Russia’s subjectness allows us to conclude that it has a poorly organized subjectness, which has been formed over the past thirty years of the cult of money and admiration for the “collective West”. The centuries-old history of Russia gives grounds for the asser­tion that it has a civilizational code that saves it in situations that threaten the loss of sovereignty. Conventionally, this code can be called the code of “mobilization subject­ness”. The topical socio-humanitarian problems of strengthening the subjectness of Russia are considered, among which an important place is occupied by the problem of improving the mechanisms of public participation at all levels from local to federal. The expediency of forming a new direction in ensuring the security of social systems – “subjectness secu­rity” is substantiated. The basic philosophical and methodological foundations of this work are related to post-non-classical scientific rationality and post-non-classical cybernetics of self-developing poly-subject (reflexive-active) environments – third-order cybernetics. In the context of the problem of subjectness, this approach allows, when assembling sub­jects, to rely on the harmony of hierarchies, networks and environments, creating condi­tions for their convergence, and not opposition. The basis for these processes is a system of ontologies of self-developing poly-subject (reflexive-active) environments, which al­lows overcoming the limitations of the network approach (non-classical scientific rational­ity) and proceeding to the formation of an integral macrosubject.
Modern Concepts of Documentary and Information Science as an Educational Component of Master's Training

The purpose of the work is to characterise the content, outline methodical and didactic approaches to teaching the educational component "Modern Concepts of Documentary and Information Science". The methodology of the work is based on the use of a systematic approach to the analysis of the didactic phenomenon, which is the educational component "Modern Concepts of Documentary and Information Science", the methods of analysis and synthesis made it possible to carry out a mental reconstruction of the researched object, to study its structure, to highlight the most significant features and properties, connections and relations, methods of generalisation, abstraction, and concretisation were also used. The scientific novelty consists in the formulation of the term "documentary and information science", its characteristics as a component of the educational component of the master's training "Modern Concepts of Documentary and Information Science", the outline of the content and methodological approaches in teaching the educational component, as well as the proposal of the structure of the content of the educational component "Modern Concepts of documentary and Information Science". Conclusions. "Modern Concepts of Documentary and Information Science" is an educational component of the training of those obtaining the "master's" educational and qualification level, which covers the interdisciplinary field of document and information activity, is based on the logical system of scientific knowledge created in the field of research in librarianship, bibliography, document studies, archival studies and bibliography as the sciences of the document and information cycle, their methods and means of knowledge, which are constantly developing. The purpose of the educational component is the formation of future master's students with a holistic view of the development of theories, concepts, provisions that reflect the role and place of documents and information in society, as well as the development of knowledge in the field of modern document and information sciences. In the field of professional competences, future masters develop the ability to monitor trends in the development of the subject area by analysing information flows and arrays and the ability to use knowledge of scientific principles and methods of archival science and library science in their professional activities.&#x0D; Keywords: documentary and information science, documentary and information activity, master's training, educational component.
Epistemological Traditions in Modern Russian Philosophy

“Gnoseology” and “epistemology”, two terms widely used in the theory of cog­nition, have a history of use for about hundred years. During this time, they were interpreted very differently. In world philosophy, the first term is considered obsolete, and understanding of the second has developed in connection with the great interest in scientific knowledge. In Russia, the first term is much more common due to its use in dialectical materialism and official ideology, while the second has become widespread in the last fifty years due to the influence of works and translations in the field of philosophy of science. The paper’s authors take into account the current practice and propose to use the term “gnoseology” to describe the theory of cognition, built on the maximum abstrac­tion of the subject, and to use the term “epistemology” in the theory of cognition with a reduced level of abstraction of the subject, a level that takes into account such social characteristics of the subject as its communicativeness and values. In gnoseology, these components were either not studied, or they were fought with as unscientific and acceptable only in everyday knowledge. Despite the de­velopment of philosophical concepts of the sociality of the subject in the theory of cognition, in real technoscience the model of the most abstract mind is still very widely used, which is reflected, first of all, in the content and rhetoric of scientific papers. The paper provides examples from modern scientific texts published in high-ranking technical journals. It is concluded that the exceptional use the abstract representation of the subject prevents the scientists from formu­lating and realizing the current acute problems of their sciences.
The Effect Of Summarizing Technique On Student’s Writing Ability

The significance of this research are expected to find out whether or not the students’ writing ability of the eight grade students of SMP N 10 Pematangsiantar can be improved through the Summarizing Technique. This research is pre - experimental that using a study group meanwhile collecting data of this research using pre-test and post - test design. There are two variables. Namely independent variable is Summarizing Technique and dependent is students’ writing ability. The population of this research was the students of the eight grade students of SMP N 10 Pematangsiantar which consist the number of students is 256 students. The writer will be doing research in class VIII -1 and VIII - 7 SMP N 10 Pematangsiantar. That students consist of 64 students in it. The instrument used in this research is writing text.The result of the mean score of the students pre-test was 59,43 and after giving the treatment the mean score of the students post - test was 71,59. The comparison between the mean scores in pre - test and post - test showed a difference and increased than before. The result of the t-test value is 15,2 was greater than t - table value 2000 with degree of freedom (df) N-1 (64 - 1). It means the teaching writing can improve the students’ writing ability of the eight grade students of SMP N 10 Pematangsiantar was accepted while null hypothesis (H0) summarizing Technique in teaching writing is able to improve the students’ writing ability of the eight grade students of SMP N 10 Pematangsiantar
Development of Wetland Environment Based Textbooks to Improve Critical Literacy Competencies

Based on rankings carried out by a number of international institutions, the literacy level of Indonesian students is still below the literacy level of other countries. Based on the research results, there are a number of factors that cause this. One of these factors is the need to provide quality textbooks for critical literacy learning. However, until now there have been no good textbooks designed to improve critical literacy competencies. Therefore, research into the development of this textbook was carried out. The development of this book is based on the land environment and critical literacy. In the development process the ASSURE model was used(analyze learners; state objectives; select (methods, media, and materials); utilize materials; require learners' participation; evaluate and revise). The results of the development obtained the following findings: the validation results from material and language experts obtained an average score of 89%, which means it is very feasible; the results of media expert validation obtained an average score92% which also means very feasible; and students' literacy competence before using this book was 59.64 and after using this textbook their competence became 79.47, which means there was an increase in literacy competence by 24.95%. The implication is that the textbooks resulting from this development need to be used in language learning in schools to improve students' critical literacy competencies.
DEVELOPMENT OF A SPEECH SYNTHESIZER FOR PORTUGUESE LANGUAGE WITH HARDWARE IMPLEMENTATION

This article presents a comprehensive analysis of speech synthesizers developed for the Portuguese language, focusing on hardware implementation and consideration of regional linguistic variations. Three synthesizers (A, B, and C) were evaluated in terms of regional variations, hardware implementation, efficiency, portability, ease of use, voice variation, comprehensibility, Braille compatibility, responsiveness, responsiveness, and resource consumption on mobile devices. The Synthesizer A, despite its moderate efficiency and high portability, stood out for its consideration of regional variations, easy initiation of speech synthesis, and high comprehensibility. The Synthesizer B, with hardware implementation, demonstrated efficiency and fast response times, but faced challenges in voice variation. The C Synthesizer offered high efficiency, portability, and Braille compatibility, making it suitable for a variety of devices. The detailed analysis of these synthesizers has provided valuable insights to guide the future development of these technologies.
Circular FC: Fast Fourier Transform Meets Fully Connected Layer for Convolutional Neural Network

The fully connected (FC) layer is generally located behind the global pooling layer in the convolutional neural network (CNN). Its essence is the weighted summation of the features extracted from the previous convolutional layers, that is, feature remapping. However, the FC layer with close internal correlation inevitably brings parameter redundancy. In order to alleviate this problem, in this paper, we propose a novel lightweight FC-like module, dubbed as Circular FC, by constructing weight parameters in a circular manner. Inspired by digital signal processing theories, we implement Circular FC by fast Fourier transform (FFT) based on the circular convolution theorem of discrete signals. Circular FC is designed to be a plug-and-play classification head and can be easily embedded into existing CNNs such as VGG, Xception, DenseNet, and ResNets. Extensive experiments on CIFAR-10, CIFAR-100, and ImageNet datasets illustrate that the above networks equipped with Circular FC reduce the number of parameters while maintaining comparable image classification performance.
Cross-Lingual Knowledge Distillation via Flow-Based Voice Conversion for Robust Polyglot Text-to-Speech

In this work, we introduce a framework for cross-lingual speech synthesis, which involves an upstream Voice Conversion (VC) model and a downstream Text-To-Speech (TTS) model. The proposed framework consists of 4 stages. In the first two stages, we use a VC model to convert utterances in the target locale to the voice of the target speaker. In the third stage, the converted data is combined with the linguistic features and durations from recordings in the target language, which are then used to train a single-speaker acoustic model. Finally, the last stage entails the training of a locale-independent vocoder. Our evaluations show that the proposed paradigm outperforms state-of-the-art approaches which are based on training a large multilingual TTS model. In addition, our experiments demonstrate the robustness of our approach with different model architectures, languages, speakers and amounts of data. Moreover, our solution is especially beneficial in low-resource settings.
Implementation of the Weighted Product Method for Bank Credit Restructuring Applications

The impact of the Covid-19 pandemic is felt by the company, which is a decline in business revenue. The scan also has an impact in terms of the ability to repay bank credit and has a risk of credit clogging. The XYZ Bank as a lender has an obligation to implement the established policy of National Economic Stimulus. Nowadays, credit restructuring services exist, but many of the service processes are still carried out semi-automatically, partly by the system and the other part by humans and using paper-based data. The method used to solve such problems is the Decision Support System using the Weighted Product method. (WP).Research conclusions on the implementation of the Weighted Product (WP) method show good results and can perform criteria calculations (in numerical form) for all criteria. This method can be implemented by combining server-side scripting in PHP and client-sided scripting using Javascript. The overall results can be concluded the application created to meet the needs of the research problem that is making the automation of the priority process of submission of credit restructuring in Bank XYZ. There is a minimum result that is the algorithm used affecting the increase in the load of memory and processor performance.
Fire Drill Simulation Game for Primary School Students

A natural disaster represents a distressing incident that profoundly affects communities, resulting in significant casualties that disrupt their daily routines. Fire, as a facet of such calamities, ensues when flammable substances and gases intermingle, leading to the emission of heat and light. Research conducted in Malaysia reveals an alarming occurrence of over five thousand fire-related incidents within buildings. In response, the country has advised the primary schools to conduct fire drill simulations once or twice a year. However, the infrequent nature of these drills potentially hampers the retention of vital knowledge by the young students. Preliminary investigations have pinpointed the main challenge to conduct the drill simulations more frequently is the school’s struggle to coordinate with the fire departments. Consequently, this study aims to devise a computer-based fire drill simulation game specifically for primary school pupils. Employing the Game Development Life Cycle (GDLC) approach offers the advantage of adaptability during the game's creation. The project will also incorporate the System Usability Scale (SUS) as a model to ensure the game's practicality and playability. Through this initiative, the intention is to enhance fire safety awareness among the students in an engaging and effective manner.
Blink, Pull, Nudge or Tap? The Impact of Secondary Input Modalities on Eye-Typing Performance

Eye trackers (ET) are used in various domains, from assistive technology to virtual reality and gaming. Typing with one’s eyes using on-screen soft keyboards is one activity common to all these domains. Using ET technology is liberating but can also be frustrating due to inherent issues such as Midas-Touch - where unintentional actions are not distinguished from intentional ones. To mitigate this, dwell times are typically introduced to distinguish between intentional selections and scanning, however, this has a negative effect on typing speed as well as the perception of workload. Secondary input modalities, such as switches, introduce an explicit way to make on-screen selections, bypassing the need for dwelling. With this in mind, we sought to investigate the impact of various secondary input modalities within a controlled lab study. We recruited 15 individuals who were asked to perform a series of eye-typing tasks using both the dwell-based approach as the baseline, as well as a series of multi-modal configurations. Along with five different input modalities, two different keyboard layouts were also included as independent variables. Results show that, with some exceptions, secondary input modalities generally have a positive impact on eye-typing performance with lower perceived workload scores.
The Choice of a Persona: An Analysis of Why Stakeholders Choose a Given Persona for a Design Task

Although personas have been applied for two decades, not much is known about why a designer chooses a specific persona for a given design task. This question matters because if designers prefer one persona over another, then the needs and attributes of that persona would be favored in the design process, resulting in possible “blind spots” and bias in regards to other personas. To explore reasons and behaviors associated with the choice of a persona, we conduct an on-site user study with 37 participants in a workplace setting focused on a social media content creation task. Our findings show that factors affecting the choice of persona include age similarity between the persona and the designer, persona’s looks, how many users the persona represents, time spent browsing the persona information, and whether the persona is (a)typical relative to other personas. Under different persona sets, these factors were correlated with the probability of a persona being chosen for a design task, and also supported by a qualitative analysis of the think-aloud records where the participants explained their persona choice. The findings provide implications for developing interaction techniques that support users’ varying information needs and persona selection strategies, including recommenders that would increase the match between the designers’ information needs and the available personas.
Enhancing Art Gallery Visitors' Experiences through Audio Augmented Reality Technology

Audio Augmented Reality (AAR) applications are gaining traction, especially for entertainment purposes. To that extent, the current study explored its use and effectiveness in enhancing art gallery visitors’ experiences. Four paintings were selected and sonified using the Jython algorithm to produce computer generated music (Basic AAR); the audio was then further enhanced with traditional music by a musician (Enhanced AAR). Twenty-six participants experienced each painting in Basic, Enhanced, and No AAR condition. Results show that AAR cues had a significant effect on participants’ subjective feedback towards the paintings. Sentiment Analysis shows that participants mentioned significantly more positive words from Enhanced AAR than the others. Enhanced AAR also made participants express a sense of immersion, whereas Basic AAR made them concentrate more on forlorn aspects of the paintings. Findings from this study suggest ways to improve and customize AAR cues for different painting styles, and indicate the need for multi-modal augmentations.
Unsupervised Monocular Depth Estimation with Semantic Reconstruction Using Dual-Discriminator Generative Adversarial

Monocular depth estimation is a key issue in the field of computer vision. The unsupervised learning framework has the advantage of not requiring data labels, and has become a hot research topic. Currently, most methods use view synthesis as a supervisory signal, resulting in unclear edges and semantic distortion of predicted results in some situations. We proposed a new framework that introduce a semantic reconstruction loss to provide additional constraints for the network and improve the ability of the depth network to understand scenarios. In addition, we proposed a dual-discriminator adversarial training strategy to further strengthen semantic supervision and improve the accuracy of depth estimation. The test results show that our proposed method has achieved competitive performance on the KITTI dataset.
Research on the Training Model of Innovative Talents in Innovation Education Driven by Design Thinking under the Background of Blockchain

Innovation education, design thinking, and blockchain technology have emerged as three interconnected and globally significant phenomena that have the potential to revolutionize the way we solve problems, create value, and build trust in a rapidly changing world. This study investigates the relationship between design thinking-driven innovation education and the training model of inventive talents, with an emphasis on the mediating influence of student involvement and the moderating effect of blockchain technological background. A survey questionnaire was used to collect data from 325 higher education institute students in Hunan, China, and structural equation modeling was used to analyze the results. The findings suggest that design thinking-driven innovation education has a favorable impact on the training model of inventive abilities, and that student involvement mediates this relationship. However, the moderating influence of blockchain technology's backdrop was not supported. These findings show the efficacy of adding design thinking into innovation education as well as the significance of encouraging student engagement. The study's cross-sectional design and small sample size limit it, and future research could use longitudinal designs and larger sample sizes. Overall, this study adds to our understanding of how design thinking-driven innovation education can support the development of innovative skills, and how student engagement is critical in this process.
Impact of ISP Tuning on Object Detection

In advanced driver assistance systems (ADAS) or autonomous vehicle research, acquiring semantic information about the surrounding environment generally relies heavily on camera-based object detection. Image signal processors (ISPs) in cameras are generally tuned for human perception. In most cases, ISP parameters are selected subjectively and the resulting image differs depending on the individual who tuned it. While the installation of cameras on cars started as a means of providing a view of the vehicle’s environment to the driver, cameras are increasingly becoming part of safety-critical object detection systems for ADAS. Deep learning-based object detection has become prominent, but the effect of varying the ISP parameters has an unknown performance impact. In this study, we analyze the performance of 14 popular object detection models in the context of changes in the ISP parameters. We consider eight ISP blocks: demosaicing, gamma, denoising, edge enhancement, local tone mapping, saturation, contrast, and hue angle. We investigate two raw datasets, PASCALRAW and a custom raw dataset collected from an advanced driver assistance system (ADAS) perspective. We found that varying from a default ISP degrades the object detection performance and that the models differ in sensitivity to varying ISP parameters. Finally, we propose a novel methodology that increases object detection model robustness via ISP variation data augmentation.