Reviewerly/exHarmony huggingface dataset:
Traffic optimization in wifi networks for the internet of things

One of the main problems of modern IoT networks is the large amount of automated traffic generated by their nodes. This puts a significant strain on modern communications networks, which will only increase over time. One way to overcome this problem is to optimize the data structure and improve the methods of data collection, transmission and processing. The purpose of this study is to optimize traffic in the IoT network at the level of software architecture and data representation. The object of the study is the FireBeetle Covers-24 x 8 LED Matrix ESP32, which is controlled by the HOLTEK HT1632C controller, connected via WiFi - interface with the IoT network, implemented on the basis of the ESP8266 microcontroller. The subject of the research is the process of optimizing program code by choosing the most efficient software architecture. The article considers the three most common software architectures and gives examples of their implementation. The architecture based on REST technology was the first to be considered. This technology is the most popular and widespread due to the simplicity of concept and implementation. But its disadvantage is the significant congestion of the communication line with a large amount of the same type of service information. Reducing the amount of service information by optimizing the HTML page code using JavaScript is demonstrated by the example of the second software architecture. But such optimization does not allow to completely separate the static and dynamic components of the information transmitted by the communication line. This division can easily be done within the software architecture based on Ajax &amp; JSON, an example of which is given in the third. The great advantage of this architecture is that the static component is transmitted by the network only once at the beginning of the communication session. Then only the dynamic component is transmitted. According to the results of testing the developed hardware and software module and comparing the amount of generated data transmitted by WiFi network, it is shown that the software architecture based on Ajax &amp; JSON has the highest network efficiency, significantly reducing network traf6fic compared to others.
TRACE: Early Detection of Chronic Kidney Disease Onset with Transformer-Enhanced Feature Embedding

Chronic kidney disease (CKD) has a poor prognosis due to excessive risk factors and comorbidities associated with it. The early detection of CKD faces challenges of insufficient medical histories of positive patients and complicated risk factors. In this paper, we propose the TRACE (Transformer-RNN Autoencoder-enhanced CKD Detector) framework, an end-to-end prediction model using patients’ medical history data, to deal with these challenges. TRACE presents a comprehensive medical history representation with a novel key component: a Transformer-RNN autoencoder. The autoencoder jointly learns a medical concept embedding via Transformer for each hospital visit, and a latent representation which summarizes a patient’s medical history across all the visits. We compared TRACE with multiple state-of-the-art methods on a dataset derived from real-world medical records. Our model has achieved 0.5708 AUPRC with a 2.31% relative improvement over the best-performing method. We also validated the clinical meaning of the learned embeddings through visualizations and a case study, showing the potential of TRACE to serve as a general disease prediction model.
Challenges of Applying Data-Driven Persona Development

This chapter reviews issues and challenges of data-driven-persona development. We introduce an analytical framework for ethical dimensions to assess if data-driven personas are fair and representative of minority groups while also countering the perpetuation of stereotypes. The complicated intersections of people and technology form the basis of this ethical inquiry of data-driven persona development. By exploring how the individual steps in data-driven persona development correspond with algorithms, we present a model for considering data-driven persona ethics. This is based on procedural justice—that fairness can best be assured when considering every step of an algorithmic process. We also introduce four values of algorithmic transparency. The result is a set of guiding questions that consider the entire life cycle of data-driven persona development from collecting datasets to the interface between personas and end-users. We conclude with three key principles of ethical decision-making in data-driven persona development.
The Professional and Personal Qualities of Music Teacher as a Research Subject

The article’s relevance arises from the tasks of higher education to train a competent competitive specialist in the field of art education, which is characterised by the appropriate professional and personal qualities, as well as the ability to apply them in educating students through music. The goal of this article is to determine the essence and structure of a music teacher’s professional and personal qualities through the analysis of philosophical, psychological-pedagogical, and musical-methodical works. The research methodology is founded on the complex application of methods of analysis (of scientific literature to determine teachers’ productive professional and personal qualities), generalisation (of theoretical provisions for the development of future teachers’ professional and personal qualities), and synthesis (of scientific theory and practice in order to determine the nature and structure of professional and personal qualities of this specialist). It is noted that the essence and structure of a music teacher’professional and personal qualities should be determined by taking into account the specifics of music and pedagogical activities and teachers’ social status, educational values and educational value of music, professional erudition and teaching competency, teachers’ pedagogical talent and creativity. The study’s findings include the author’s definition and the structure of a music teacher’s professional and personal qualities. A music teacher’s professional and personal qualities are defined as a complex of professional and pedagogical, musical and creative, social and personal competency characteristics that are developed during the learning and professional activity process and ensure their effectiveness. Three dominant components represent the structure of a music teacher’s professional and personal qualities: 1) professional and pedagogical qualities (professional motivation, education and value orientation, pedagogical tact, pedagogical style, professional image); 2) musical and creative qualities (musicality and musical talent, musical and methodical ability, creativity, musical and performing mobility, stage adaptability); 3) socio-personal qualities (social activity, emotional stability, character traits, erudition, authority and leadership). It has been ascertained that the professional and personal qualities of a music teacher are competency characteristics, which ensures the effectiveness of music teaching and creative music activities
Formation of Emotional Intelligence of Future Music Teachers: results of pedagogical experiment

The article shows the results of a pedagogical experiment on the formation of emotional intelligence of future teachers of music. The author’s definition of the concept of “emotional intelligence of a music teacher” is given. The essence of the concept of formation of emotional intelligence as a personal and professional quality of a future music teacher is revealed, which consists in understanding this process as one that is carried out in the conditions of multilevel professional education and is provided by a specially organized system of professional training aimed at simultaneous introduction into the educational process of the developed content and selected forms and methods in accordance with sound theoretical-and-methodological and organizational-and-methodological principles of the study. The pedagogical experiment was conducted for five years (2016–2020) and consisted of ascertaining and formative stages. At the main stage of the formative experiment, organisational and methodological principles were introduced as a basis for formation of emotional intelligence of future music teachers by means of content, forms and methods of professional training, enriched with emotional and intellectual component. Quantitative and qualitative analysis of the results of the pedagogical experiment, determining the dynamics of changes in the formation of components of emotional intelligence of future music teachers according to certain criteria, was carried out during the analytical and productive stage of the formative experiment. To measure the formation of emotional intelligence of future teachers of music as a holistic phenomenon, and to form each of the structural components, the selection and modification of special diagnostic methods were made. Based on the results of the pedagogical experiment, the conclusion was made about the effectiveness of the developed organizational and methodological foundations for the formation of emotional intelligence of future music teachers in the process of professional training, which is confirmed by statistical processing using Fisher’s and Pearson’s criteria.
Conclusion: Dispelling Myths and Laying Out the Grand Challenges of Data-Driven Personas

In this concluding chapter, we address three myths concerning data-driven personas. In some respects, these myths are the foundational drivers for the grand challenges in the data-driven persona domain. We then present and discuss the grand challenges that must be addressed, in a multidisciplinary manner, to take data-driven personas to the next level of fully functional persona analytics in order to achieve enhanced user understanding across the many domains that employ personas.
Video Anomaly Detection for Smart Surveillance

In modern intelligent video surveillance systems, automatic anomaly detection through computer vision analytics plays a pivotal role which not only significantly increases monitoring efficiency but also reduces the burden on live monitoring. Anomalies in videos are broadly defined as events or activities that are unusual and signify irregular behavior. The goal of anomaly detection is to temporally or spatially localize the anomaly events in video sequences. Temporal localization (i.e. indicating the start and end frames of the anomaly event in a video) is referred to as frame-level detection. Spatial localization, which is more challenging, means to identify the pixels within each anomaly frame that correspond to the anomaly event. This setting is usually referred to as pixel-level detection. In this paper, we provide a brief overview of the recent research progress on video anomaly detection and highlight a few future research directions.
Content of Teaching a Future Artist/Vocalist Jazz Improvisation

Teaching vocalists jazz improvisation contributes, on one hand, to developing general skills (sociability, memory, attentiveness, coordination of movements), and on the other, to developing musical and creative abilities, as well as it helps to shape the worldview and aesthetic taste that a student acquires when studying at higher artistic education establishments and provides an opportunity to develop one’s abilities further in other areas. Special attention in the content of teaching vocalists jazz improvisation is paid to further development of individual improvisational and interpretive abilities of students, complete mastering of improvisational techniques and principles of their organization, formation of quality professional improvisational and performing levels of instrumentalists in the course of learning, an individual creative method in the art of improvisation and interpretation of jazz standards, study of signature methods and concepts of outstanding improvisers of jazz, rock, pop music and mixed improvisational and folklore directions in the historical and temporal aspect for the purpose of their creative rendering and use in one’s work. A goal, objectives, content and methods are all necessary elements of teaching vocalists jazz improvisation. The study of these issues is of great importance for determining its direction and nature, since a misunderstanding of the teaching goal and objectives often leads to negative results in the development of methods for training an artist/vocalist. Objectives and specifics of the content of teaching vocalists jazz improvisation in higher educational establishments are defined in three main areas: “why teach” (teaching goal), “teach what” (teaching content), “how to teach” (teaching forms and methods).
DeePattern: Layout Pattern Generation With Transforming Convolutional Auto-Encoder

VLSI layout patterns provide critical resources in various design for manufacturability research, from early technology node development to back-end design and sign-off flows. However, a diverse layout pattern library is not always available due to long logic-to-chip design cycle, which slows down the technology node development procedure. To address this issue, in this paper, we explore the capability of generative machine learning models to synthesize layout patterns. A transforming convolutional auto-encoder (TCAE) family is developed to learn vector-based instantiation of squish pattern topologies. We show our TCAE models can capture simple design rules and enlarge the existing squish topology space under certain transformations. With adaptive configurations, the proposed GTCAE framework allows both massive pattern generation and context-specific pattern generation. Geometry information of each squish topology is obtained from an associated linear system derived from design rule constraints. Experiments on 7nm EUV designs show that our framework can more effectively generate diverse pattern libraries with DRC-clean patterns compared to a state-of-the-art industrial layout pattern generator.
Obstacle detection in front of a railway vehicle using a stereo camera

Trams are widely used for clean public transportation, but little research has been performed on the automatic operation of trams. However, it is thought that such automatic operation will be considered in the future. For automatic operation of trams, it will be necessary to detect obstacles in front of the vehicle in real time and to control the braking of the vehicle when obstacles are detected. This paper proposes a method for detecting obstacles using a stereo camera installed in front of the vehicle. The proposed system can be division three steps. First, template matching is performed to estimate the railway track position. Next, the predicted area considering vehicle gauge is calculated based on the railway track position. Finally, obstacle detection is performed inside the predicted area considering vehicle gauge using the distance image obtained from the stereo camera. When the object larger than the certain value, the proposed system controls the braking of the vehicle. The effectiveness of the proposed system is investigated using a 1/10 scale model experimental vehicle, and the verification results show the feasibility of the proposed system.
Action Recognition in Real-World Videos

The goal of human action recognition is to temporally or spatially localize the human action of interest in video sequences. Temporal localization (i.e. indicating the start and end frames of the action in a video) is referred to as frame-level detection. Spatial localization, which is more challenging, means to identify the pixels within each action frame that correspond to the action. This setting is usually referred to as pixel-level detection. In this chapter, we are using action, activity, event interchangeably.
Evaluating Data-Driven Personas

In this chapter, we briefly introduce the critically needed task of data-driven persona evaluation. Although we specifically focus on data-driven, nearly all of the evaluation content applies to other types of personas as well. We highlight the need for evaluation in both persona research and practice, and we introduce techniques for persona evaluation. We discuss what is a good persona and what elements combine to make a good persona. We then introduce the Persona Perception Scale (PPS) that measures user perceptions of personas, moving then to a technical definition of a good persona. We then look at a good persona in terms of use cases, introducing the concept of “personas + x”. We end the chapter using APG for data-driven personas generation and evaluation, chapter takeaways, and discussion questions.
The synchronization of medical systems databases: models and methods

In order to build a system of medical information exchange, it is necessary that different medical systems are compatible with each other. If the systems are incompatible, compatibility must be achieved by achieving semantic and syntactic compatibility of systems. If compatibility is achieved, databases of different systems must be synchronized. To achieve this goal, a study was conducted to examine the most popular models and methods of synchronization of medical data. Thus, there are several different ways to synchronize medical information between two systems. The most common are replication, ETL, and two-way synchronization.
Blockchain Applications in Agriculture: A Scoping Review

Blockchain is a distributed, immutable ledger technology initially developed to secure cryptocurrency transactions. Following its revolutionary use in cryptocurrencies, blockchain solutions are now being proposed to address various problems in different domains and is currently one of the most "disruptive" technologies. This paper presents a scoping review of the scientific literature for exploring the current research area of blockchain applications in the agricultural sector. The aim is to identify the service areas of agriculture where blockchain is used, the blockchain technology used, the data stored in it, its combination with external databases, the reason it is used, for which products, as well as the level of maturity of the respective approaches. The study follows the PRISMA-ScR methodology. The purpose of conducting the scoping review is to identify the evidence of this field and clarify the key concepts. The literature search was conducted in April 2021 using Scopus and Google Scholar, and a systematic selection process identified 104 research articles for detailed study. Our findings show that in the field, although still in the early stages, with the majority of studies in the design phase, several experiments have been made, so a significant percentage of the work is in the implementation or piloting phase. Finally, our research shows that the use of blockchain in this domain mainly concerns the integrity of agricultural production records, the monitoring of production steps, and the monitoring of products. However, other varied and remarkable blockchain applications include incentive mechanisms, circular economy, data privacy, product certification, and reputation systems.
ARCHIVAL DOCUMENTS ABOUT TARAS SHEVCHENKO HOMELAND

Article by Iu. Sokoliuk Archival Documents on the Birthplace of Taras Shevchenko aims to broaden the scientific understanding of locations that are important for the creative development of Taras Shevchenko. An extremely important aspect of the methodological work is the involvement of archival information in the channels of mass and scientific communication, the discussion at seminars and conferences, publication in specialized publications, etc. Archival documents of the 19th century reflect the features of real life of all segments of the population of Russian Impire. In the given intelligence the author directed his efforts to applied research in the archives of Kyiv. The relevance of the intelligence is that the documents are still unknown to the general public. Some archival cases relate to Mr. Paul Engelhardt's estates, whose serfs were the Boyko-Shevchenko families. Of particular interest are cases of abuse of serfs in the village of Kirilovka. This shows that the human tragedies described by Shevchenko have a true historical basis. Summarizing the rich information material collected by renowned Shevchenko scholars, it should be noted that Shevchenko's childhood in a special way influenced the formation of the poet as an artist and as a person. Modern science opens new pages every day. An address to the original sources is an extraordinarily important aspect of modern Shevchenko’s studies. More and more scientists are interested in this topic. Therefore, we conclude that the archival institutions of Ukraine are still an inexhaustible source for studying the historical realities of T. Shevchenko's life and their influence on the writer's work.
Pedagogical Conditions for Professional Burnout Prevention of the Future Teachers of Art Disciplines

The results of scientific research of pedagogical conditions for professional burnout prevention of the future teachers of art disciplines have been presented in the article. The psychological prerequisites for the professional activities of teachers of art disciplines have been established, which determine the emergence of emotional tension, including external and internal stressors. As to external stressors, they are the following: excessive number of concert and stage performances, a significant number of professional commitments, lack of “vital energy”, lack of time for rest, fear of being “thrown out of the stable”, subjective dissatisfaction with the conditions of creative activity, socio-demographic characteristics (age, work experience in a particular artistic group, category, marital status); as to internal stressors, they are motivation, needs, goals and evaluation of one’s own activities. The individual personality traits that determine the professional burnout of future teachers of art disciplines include introversion, a high level of motivation and anxiety, high normativeness or demonstrative behaviour, a high level of concert excitement. The practical significance of the research results is that the obtained results provide an opportunity to improve the professional training system of specialists in the field of art, preventing the negative burnout impact during the performance of their professional functions.
Use Cases for Data-Driven Personas

This chapter explores use cases of data-driven personas. In particular, we discuss 12 specific use cases in 3 general types: (1) analytical, (2) interactive, and (3) team-centered use cases. The use cases are presented from the viewpoint of end-users of the personas. By “end-users”, we refer to the professional stakeholders that make decisions based on the personas or communicate with other stakeholders using the personas. As such, end-users are different from the “users” that the personas represent. The chapter contains action points for both data-driven persona end-users and persona developers.
Shondhi: Connecting Parents and Teachers of Children with Autism in Bangladesh

Communication is important for collaboration between parents and teachers of children with autism (CWA); gap in communication creates lack of trustworthiness. Our work explores the reasons behind the communication challenges and the opportunities to reduce the miscommunication between parents and teachers of CWA. We conducted the study during COVID-19 pandemic when CWA parent-teacher interaction changed due to the adoption of online education. The in-depth qualitative study involves n = 10 participants, including both stakeholders. We found personalized communication as well as maintaining privacy and accountability while communicating using contemporary technologies remains a challenge. This motivated us to develop an Android-based application, ‘Shondhi’. This study enhances the nuances of parent-teacher collaboration by providing them a personalized tool that specifically focuses on the needs of parents and teachers of CWA.