Reviewerly/exHarmony huggingface dataset:
Theoretical Musicology in Bukovyna (on the Example of S. Vorobkevych’s Harmony Textbook)

The purpose of the work is to characterise the state of theoretical musicology in Bukovyna in the late nineteenth and early twentieth centuries on the basis of Sydir Vorobkevych’s work “Musical Harmony”. Research methodology. The article is based on the following research methods: historical, biographical, cultural, and theoretical generalisation. The systematic approach of scientific research helped to analyse the work, which became one of the attempts to adapt the theoretical foundations of musical harmony to the needs of the multinational environment of the Bukovyna region. Scientific novelty is that for the first time, the article thoroughly analyses the music-theoretical work that became the basis for theoretical training of music specialists in Bukovyna, and draws conclusions about the peculiarities of musicology in the region. Conclusions. One of the first theoretical works in Bukovyna to appear during the period of Austro-Hungarian rule in the region was a textbook on harmony by Sydir Vorobkevych. Despite the fact that the vast majority of imported books and works of local artists were written in German, S. Vorobkevych’s “Musical Harmony” was written in Romanian, as the majority of the region’s population was Romanian. The need for such a textbook was extremely relevant among the musicians of Bukovyna and Chernivtsi. S. Vorobkevych created one of the first works of theoretical musicology in Bukovyna, which became the basis of musical education in the region. Sydir Vorobkevych’s work is fully in line with the traditions of the second half of the nineteenth century and confirms the idea that the terminology and methodological explanation of the foundations of music theory, in particular musical harmony, were at the stage of development at that time and underwent changes already in the next century. S. Vorobkevych’s “Musical harmony” is a source of information about the basic postulates of theoretical musicology, related to the principles of harmonic thinking, which, according to the author of the textbook, is an indispensable basis for successful composing.&#x0D; Key words: art of Bukovyna, musicology, musical education of Bukovyna, musical harmony, music theory.
Meiningen Theatre of the Second Half of the Nineteenth Century: Creativity of Ludwig Kroneck's Directing Mechanisms

The purpose of the work is to describe and highlight the artistic and creative activities of the Meiningen Theatre and the professional skill and creativity of Ludwig Kroneck's directing mechanisms. The research methodology is to apply the art historical method for a comprehensive study and understanding of all components of the nature of stage creativity and directorial activity of the Meiningen theatre of the corresponding period, its artistic and aesthetic value. The structural method and a systematic approach in combination with the historical method are used for a thorough study of the creative experience of the Meiningen theatre and its directing, analysis of the characteristic differences in artistic activity. The functional method helped to analyse the essentially practical component of the imaginative and creative process, pragmatic characteristics of the theatre ensemble and director's explications of the German Meiningen Theatre of the second half of the nineteenth century. The analytical method was applied for considering the essence of the techniques and means of practical implementation of an artistic work, its transformation into a stage reality with the help of special professional methods and means of ideological and emotional expression. The scientific novelty of the study lies in a comprehensive analysis of Ludwig Kroneck's creative skills, the creativity of his theatre directing mechanisms and the significance of the master's professional experience for the stage professional process of contemporary theatre. Conclusions. The PR experience of L. Kronek, director and manager of the Meiningen Theatre in the second half of the nineteenth century, impresses today with its expediency in the theatrical process of stage creativity, namely: the master’s innovations in solving mass scenes of productions, performing role material by each performer with the help of all means and skills of high artistry The integrity of all methods of building a synthetic artistic and figurative stage canvas was achieved by the artist due to the complex skills of the director's ideas – light, scenery, mise-en-scene and performance of the acting ensemble. Modern theatre directing, as always, is in a constant process of inventing the latest original solutions for creating a stage form, figurative, and associative disclosure of a dramatic work as an artistic form of theatre. In their aspirations, the artists of the Melpomene stage should not forget the fruitful experience of their predecessors, who stood at the origins of the profession of directing as the main creator of visual and entertainment performance.&#x0D; Key words: directing activity, Ludwig Kroneck, Meiningen Theatre, director, actor, theatre.
Entanglement classification via operator size

In this work, multipartite entanglement is classified by polynomials. I show that the operator size is closely related to the entanglement structure. Given a generic quantum state, I define a series of subspaces generated by operators of different sizes acting on it. The information about the entanglement is encoded into these subspaces. With the dimension of these subspaces as coefficients, I define a polynomial which I call the entanglement polynomial. The entanglement polynomial induces a homomorphism from quantum states to polynomials. It implies that we can characterize and find the building blocks of entanglement by polynomial factorization. Two states share the same entanglement polynomial if they are equivalent under the stochastic local operations and classical communication. To calculate the entanglement polynomial practically, I construct a series of states, called renormalized states, whose ranks are related to the coefficients of the entanglement polynomial.
Application of a systematic approach in the development and use of information methods for the study of crime

Combating crime should be based on the principles of criminological science. Therefore, the formation of the theory of criminology remains an urgent need. And the development of information methods for the study of crime is one of the primary tasks of specialists.The task of the article is to substantiate the expediency of applying a systematic approach to the study of information methods for the study of crime in criminological science. The purpose of the article is to form the basis of the criminological theory of crime prevention measures.The following elements are asserted as the subject of criminological science: 1) toolkit of criminological research; 2) crime; 3) determination of criminality; 4) the identity of the criminal; 5) mechanism of individual criminal behavior; 6) crime prevention.The methodological basis of the research is the understanding of the global mega system, where the informational aspect is always manifested in the objectification of material and energy processes. Here, all processes are based on information, and the organization, functionality and interaction of system objects are determined by information.The system approach is a direction of research, and study of the world, which is based on considering objects as a system, focusing on revealing the integrity of the object, identifying the variety of connections in it, and bringing them to a single theoretical picture. It is the systematic approach that is an adequate cognitive tool for the systemic nature of the universe.Science in general, and criminological science in particular, represents a union of scientific activity and its informational result. Regarding the informational result of criminological science, we are talking about criminological information.It is considered reasonable to define criminology as a scientific activity of processing criminological information to obtain new knowledge. This activity is part of the systemic World, so it has a systemic nature and the tools of the systemic approach can be applied to it. First of all, about the research of information methods for the study of crime.It is considered a reasonable possibility of using information methods in criminology. Prospective areas of such work will be:1) detection of crime trends and measures to prevent it;2) modeling of criminogenic processes and law enforcement measures;3) criminological prognosis.Improvement of digital criminological methods in the future will be carried out primarily through the use of «artificial intelligence» technologies.
New report underlines advances in Iranian cyber skills

Headline IRAN: New report underlines advances in cyber skills
Deep Multi-task Convolutional Neural Networks for Efficient Classification of Face Attributes

Facial feature recognition is an important subject in computer vision with numerous applications. The human face plays a significant role in social interaction and personology. Valuable information such as identity, age, gender, and emotions can be revealed via facial features. The purpose of this paper is to present a technique for detecting age, smile, and gender from facial images. A multi-task deep learning (MT-DL) framework was proposed that can simultaneously estimate three important features of the human face with remarkable accuracy. Additionally, the proposed approach aims to reduce the number of trainable network parameters while leveraging the combination of features from different layers to increase the overall accuracy. The conducted tests demonstrate that the proposed method outperforms recent advanced techniques in all three accuracy criteria. Moreover, it was demonstrated that multi-task learning (MTL) is capable of improving the accuracy by 1.55% in the smile task, 2.04% in the gender task, and 3.52% in the age task even with less available data, by utilizing tasks with more available data. Furthermore, the trainable parameters of the network in the MTL mode for estimating three tasks simultaneously increase only by about 40% compared to the single-task mode. The proposed method was evaluated on the IMDB-WIKI and GENKI-4K datasets and produced comparable accuracy to the state-of-the-art methods in terms of smile, age detection, and gender classification.
K-means Algorithm Based on Improved Krill Herd Algorithm and Calinski-Harabasz Index

Aiming at the problems that the Krill Herd (KH) algorithm is easy to fall into the local optimum, the searchability is weak, and the k-means algorithm is easily affected by the selection of the initial clustering centre, a k-means algorithm based on the improved KH algorithm is proposed. The algorithm is initialized by chaos, dynamic clustering, elite leadership and random mutation strategies to improve the KH algorithm and introduce the optimal clustering number adaptive mechanism, which enhances the comprehensive optimization ability of the algorithm. Six benchmark functions test the improved KH algorithm. The effectiveness of the k-means algorithm based on the improved KH algorithm was tested and verified with UCI machine learning and artificial datasets. The verification results showed that the improved KH algorithm improved based on ensuring a faster convergence speed. Compared with other algorithms, the performance of this algorithm has been significantly improved in all aspects.
Bibliometric Analysis of Deep Learning for Social Media Hate Speech Detection

Social media has become an important web technology for creating and sharing information plus enhancing business reputations worldwide. However, the anonymity accorded by social media platforms has been cryptically vituperated to spread horrendous content such as hate speech. Recently, researchers have been progressively gravitating towards the use of deep learning techniques to address the problem of social media hate speech detection. This study provides bibliometric analysis and mapping of the existing literature on hate speech detection using deep learning algorithms. The study used articles published between 2016 and 2022 from the Scopus database, while Vos Viewer, Biblioshiny, and Panda’s software tools were employed for the bibliometric analysis. The research explored the yearly trajectory of recent publications, dominant countries, collaborative institutions, sources of primary studies that have employed deep learning for hate speech detection, and the intellectual and social structures of the research constituents. It has been observed that the literature on hate speech detection is rapidly growing, but research output and collaborations from the developing countries of the world are still limited. The findings of this study provide insights into the intellectual structure and advancements in deep learning applications for hate speech detection while identifying research gaps for future work.
Analysis of User Experience on SPOTA UNTAN Using Heuristic Walkthrough Method

SPOTA UNTAN is an abbreviation for Sistem Pendukung Outline Tugas Akhir for the Informatics study program at Tanjungpura University. SPOTA UNTAN was developed within the Informatics study program at Tanjungpura University in 2008. SPOTA UNTAN is an information system that support students in submitting their final project topics. As for now, SPOTA UNTAN has undergone several updates, including the new features to enhance the information system functionality. As its interface has undergone some changes, such as the addition of content, however, the CSS framework (colors, fonts, shapes, etc.) still retains the original design and not yet updated to align with the user experience. Therefore, several analyses are needed to address these uncertainties from a user interface perspective by usability tests. The study will apply the Heuristic Walkthrough method, which combines Cognitive Walkthrough and Heuristic Evaluation. The analysis will involve 5 expert evaluators in UI/UX. This study result showed a total of 39 recommendations for problem resolution, categorized into functional feature improvements and interface enhancements.
Pengaruh Model Problem Based Learning Berbantuan Media Audio terhadap Keterampilan Menyimak Siswa Kelas V Sekolah Dasar

The purpose of this study was to determine the effect of the problem based learning model on the listening skills of fifth grade students at SDN 37 Pekanbaru in the 2022/2023 academic year. This type of research is a non-equivalent control group design involving two classes, namely the experimental class and the control class. The subjects of this study were the VC class as the control class, totaling 25 people and the VE class as the experimental class, totaling 26 people. Researchers conducted learning using the problem based learning model for the experimental class while in the control class the researchers carried out conventional learning. Students' listening skills are measured through listening skills tests in the form of audio. The results showed that the hypothesis tested using the t-test obtained a significance of 0.000 &lt; 0.05, so that Ha was accepted and Ho was rejected. These findings indicate that there is an influence of the Problem Based Learning model on students' listening skills.
Prevention or Promotion? Predicting Author's Regulatory Focus

People differ fundamentally in what motivates them to pursue a goal and how they approach it. For instance, some people seek growth and show eagerness, whereas others prefer security and are vigilant. The concept of regulatory focus is employed in psychology, to explain and predict this goal-directed behavior of humans underpinned by two unique motivational systems – the promotion and the prevention system. Traditionally, text analysis methods using closed-vocabularies are employed to assess the distinctive linguistic patterns associated with the two systems. From an NLP perspective, automatically detecting the regulatory focus of individuals from text provides valuable insights into the behavioral inclinations of the author, finding its applications in areas like marketing or health communication. However, the concept never made an impactful debut in computational linguistics research. To bridge this gap we introduce the novel task of regulatory focus classification from text and present two complementary German datasets – (1) experimentally generated event descriptions and (2) manually annotated short social media texts used for evaluating the generalizability of models on real-world data. First, we conduct a correlation analysis to verify if the linguistic footprints of regulatory focus reported in psychology studies are observable and to what extent in our datasets. For automatic classification, we compare closed-vocabulary-based analyses with a state-of-the-art BERT-based text classification model and observe that the latter outperforms lexicon-based approaches on experimental data and is notably better on out-of-domain Twitter data.
Analysis of Adjacency Pairs of Cristiano’s Interview

Conversation is a vital tool in communication for communicating meaningful pieces of interactions. Adjacency pairs are often seen as fundamental units in conversational organization. The form and purpose of a specific pair component, as well as the context beside the stage of the conversation, all play essential roles in determining the meaning and function of an utterance. Each pair has special intended meaning, purpose and function which cannot be fully understood without relying on the context at which the adjacency pairs appear. The present study tends to focus on adjacency pairs within sports interviews with the aim of studying these pairs pragmatically since defining the underlying expectations on which the regularities are founded is difficult. The study also aims at examining the adjacency pairs included in the exchanges between the TV interviewers as well as the footballers, finding out the communicative purposes behind the adjacency pairs usage that the player wishes to transmit when being interviewed. The method used for analysis is a mixed one (quantitative and qualitative) to analyze the latest interview for the player. The qualitative analysis examines the content of the utterances descriptively and the quantitative analysis relies on a table, under the interview, that shows the rates of the types of adjacency pairs. So, the selected interview is analyzed in terms of number, types, frequency and distribution of adjacency pairs. The adopted model is an eclectic one which composes Cook's (1989) model of Adjacency Pairs, Van Dijk's (2006) model of Context and Grice's (1975) model of Cooperative Principles.
Build your own closed loop: Graph-based proof of concept in closed loop for autonomous networks

Next Generation Networks (NGNs) are expected to handle heterogeneous technologies, services, verticals and devices of increasing complexity. It is essential to fathom an innovative approach to automatically and efficiently manage NGNs to deliver an adequate end-to-end Quality of Experience (QoE) while reducing operational expenses. An Autonomous Network (AN) using a closed loop can self-monitor, self-evaluate and self-heal, making it a potential solution for managing the NGN dynamically. This study describes the major results of building a closed-loop Proof of Concept (PoC) for various AN use cases organized by the International Telecommunication Union Focus Group on Autonomous Networks (ITU FG-AN). The scope of this PoC includes the representation of closed-loop use cases in a graph format, the development of evolution/exploration mechanisms to create new closed loops based on the graph representations, and the implementation of a reference orchestrator to demonstrate the parsing and validation of the closed loops. The main conclusions and future directions are summarized here, including observations and limitations of the PoC.
Discourse-Based Teaching in English Language Teaching at Islamic Universities in Borneo: A Critical Discourse Analysis Perspective

This critical discourse analysis aims to uncover what ideologies emerge in English language teaching at Islamic universities in Borneo, explain how discourse-based teaching is implemented, and why discourse-based teaching is necessary for English language teaching at Islamic universities in Borneo. This is qualitative phenomenological research using Fairclough's Critical Discourse Analysis model. The primary data sources for this research are English language lecturers and college students at universities in Borneo, namely UIN Sultan Aji Muhammad Idris Samarinda, UIN Antasari Banjarmasin, IAIN Palangkaraya, and IAIN Pontianak. The researcher used several research instruments to collect the data: interviews, questionnaires, observations, and documentation. The data analysis technique used in this research is the interactive model from Miles et al. with the stages of data collection, data condensation, data display, and conclusion. This research concludes that English language education at Islamic universities in Borneo has an ideology of character development, influenced by several factors such as the shift in character values, the spirit of nationalism, and political policies of the Ministry of Religion to maintain national unity with a religious moderation agenda, and the vision to develop graduates who have solid Islamic character. In addition, English language education aims not only to master English language skills but also to compete in the era of information technology with critical thinking skills. Therefore, English language teaching at Islamic universities in Borneo is based on a discourse approach, from lesson planning and teaching implementation to teaching evaluation. This research implies that English language teaching should not only focus on English language skills or TEFL content but also on achieving learning outcomes from the goals of the study program, students’ needs, and the roles of lecturers as educators of Islamic and national character values.
Underwater Object Detection Through Analysis and Data Augmentation of Underwater Datasets

Nowadays, with the rapid development of artificial intelligence (AI) technologies, more and more jobs can be fulfilled by underwater drones. Particularly, object detection with deep learning becomes an important issue which can significantly improve the performance of underwater drones. In this work, we analyzed and augmented an existing underwater dataset and proposed a new object detection dataset for inshore aquaculture. The renewal dataset is used for the training of the network for real-time object detection. The simulation results showed that the existing underwater dataset has a class imbalance problem. In addition, it is shown that although large objects are detected with high accuracy, rocks and small shadows are sometimes mis-detected as targets. It is due to the distance between the target object and the camera lenses, simulation of the background, and the object detection model not learning the difference between background and target. This indicates that object detection accuracy could be improved by the dataset that can accurately learn object features.