Reviewerly/exHarmony huggingface dataset:
Experience of Application of Modern Educational Methods in Teaching of the Course «Laboratory Diagnostics» in National University of Pharmacy

The global process of transition to the information society, as well as the economic, political and social changes that accompany it, are accelerating the reform of the education system. Distance learning is a humanistic personality-oriented form of learning, the basis of which is purposeful, motivated learning and communication between the teacher and students by using of modern information technology. The distance learning system opens wide access to various educational services to a large number of people who, due to objective or subjective reasons, cannot receive education in the traditional way. In addition, the advantage of this form of education is the lack of «age requirements», which is sometimes an objective obstacle to retraining or additional education for those categories of people with professional experience. The purpose of the study was to analyze the features of teaching a distance course in the discipline «Laboratory Diagnostics», developed at the Department of Clinical Laboratory Diagnostics National university of pharmacy. Material and methods. The methodological basis of the study included the following components: system approach; the concept of personality-oriented learning; principles of distance learning; theory of information systems. The article considers the peculiarities of the organization of distance learning in National university of pharmacy, the main methodological regulations on which the introduction of distance learning courses is based. The distance courses of the discipline «Laboratory Diagnostics» for students of specialty 226 «Pharmacy, Industrial Pharmacy» in the information environment Moodle was analyzed and generalized and the basic elements of educational information placement were directly described. The authors determined the place of distance courses in the process of independent training of educational process; the special role of the teacher (tutor) in the organization of independent training of the students according to the offered methodical recommendations and distance courses was shown. Conclusion. Distance learning in a virtual educational environment provides a variety of modern e-learning tools that can be used not only in full-scale distance learning, but also in traditional forms. National university of pharmacy is actively implementing measures to comply with the requirements of current regulations of the Ministry of Education and Science of Ukraine on the implementation of distance learning. The experience of teaching the discipline «Laboratory Diagnostics» using distance learning technology allows future professionals in the field of knowledge «Health» to acquire skills and abilities
The Everyday World and Intersubjectivity

Abstract We have learned through processes of socialization how to name and identify things, which helps us continually reduce complexity and bring order to the contingent world around us in our everyday life. At the same time, we move within many “small” social lifeworlds, or “multiple realities,” that are disconnected from one another and each have a particular cultural grammar in which “things” are loaded with quite a variety of meanings that impact and alter our identities. Design ethnographers also move within these small social lifeworlds. They should neither judge these morally nor overwrite them with their own values, but rather meet them with openness and sensitivity.
Parameterized Families of Correctly Functioning Sigma-Pi Neurons

The \(\Sigma \Pi \)-neuron is a biologically inspired formal model for logical information processing. The \(\Sigma \Pi \)-neuron model adequately reflects information processing processes in the cerebral cortex and in the dendritic trees of neurons. The advantage of the \(\Sigma \Pi \)-neuron model is the ability to accurately represent any Boolean function and the possibility of constructive learning (direct construction) in a single pass of the training sample. Another possibility is the direct construction of an ensemble of \(\Sigma \Pi \)-neurons that function correctly on the training sample. This article discusses a new algorithm for constructing an ensemble of \(\Sigma \Pi \)-neurons in parameterized form. This form can also be easily represented as a single \(\Sigma \Pi \)-neuron with a hidden layer of linear and threshold linear units. In some cases, this makes it easier to retrain on new inputs by setting the appropriate control parameter values.
Exploring augmented reality for mobile learning: a case study with children's readings on environmental sustainability

An increasing number of children are using mobile devices at an early age. Some argue that excessive technology usage could have negative impacts on children. If used appropriately, mobile devices can be effective learning tools for children. The main purpose of this study is to explore the impact of Augmented Reality (AR) for children in mobile learning. The experimental study was conducted with 30 participants divided into two groups: AR (a book accompanied with AR) and Book (the same book with no AR). Children's perceptions regarding conservation, wild animals, and the new ecological paradigm were measured with survey questions before and after reading the same AR or Book content on environmental sustainability. The study results demonstrates that AR was more engaging than books alone and more efficient at improving attitudes toward the environment. AR allowed children to empathise more with environmental issues and develop their own learning environments. The study reveals the potential of AR for improving children's learning experiences on environmental sustainability.
What does the examiner's report say?

This chapter includes information on the language used by Forensic Document Examiners when reporting their conclusions. The use of terminology and SWGDOC requirements for each degree of certainty expressed by the Forensic Document Examiner is discussed. Some of the legal conventions that are used when writing a report and testifying are also included.
Creative considerations for on-screen visuals in electronic pop music performances

The impact of visual cues on auditory perception is also demonstrated by the McGurk effect, where the perception of a syllable can be altered when a video of a different spoken syllable is shown. Overall, added visual information can likely bridge the gap between what is seen and heard in an electronic music performance. One way to achieve this is through the use of on-screen visuals, which this chapter focuses on. The chapter investigates creative considerations for on-screen visuals in popular electronic music performances. The following questions are addressed: How can visuals be created and played back during the live performance? How can a relationship be established between what is seen and heard? What challenges and affordances can arise from working with visuals? Nyokeë's visuals reflect the game aesthetic of the music, consisting almost entirely of pixelated animations and voxel-based scenes. Visual performance cues can outweigh auditory performance cues in terms of audience ratings of expressivity.
Assessment of the use of digital technologies by students of higher education institutions

Abstract The article assesses the use of digital technologies by students of higher educational institutions. As part of the study, we analyzed the indicators on the use of personal computers by students in different places, the use of computers with Internet access and the frequency of use of personal computers. It was found that, basically, students daily use personal computers with Internet access in places of residence, but this indicator in urban areas is higher than in rural areas. To eliminate the digital divide, it was proposed to introduce satellite Internet, which will increase the number of students living in rural areas using the Internet, as well as other areas of activity and industries located in rural areas or in remote areas will be provided with the Internet.
A Data Association Approach for Plot-Sequences Outputted by Multi-Frame Track-Before-Detect

This paper addresses the data association problem with respect to the multi-frame track-before-detect (MF-TBD). Different from the classical target detection and tracking approaches which declare target and update tracks for each single frame, the MF-TBD can achieve superior performance by integrating target energy over several consecutive frames, especially for dim or fluctuating targets. Moreover, with jointly processing consecutive frames of raw data, the outputs of MF-TBD are plot-sequences. However, in the single-target or multi-target scenario, there needs to assign the plot-sequences to the existing trajectories. In other words, MF-TBD is not a complete target detection and tracking system, or rather, the further tracking treatments are needed, such as the association step. In this paper, by referring to the existing works of data association methods, a novel data association approach for the plot-sequences outputted by MF-TBD is developed. Last, the simulation results show that the proposed algorithm can correctly associate target trajectories with the corresponding plot-sequences and significantly enhance the tracking performance compared with the traditional tracking algorithm.
The Concoct of Digital Preservation in Open Access

Research pursuit in Open Access (OA) has become a center of interest in academic institutions. Academic institutions and publishers have been energetically working hard towards achieving strategic and sustained partnerships in providing OA to information resources. While the work of strengthening these endeavours is ongoing, very little have been done on the logistics for digital preservation of OA resources in Institutional Repositories. This chapter explores digital preservation processes in OA using the University of Botswana Research, Innovation, and Scholarship Archive (UBRISA) as a case study. The chapter establishes the implementation activities, the outcomes, and challenges experienced by UBRISA. The findings reveal that the UBRISA commits to strategically capturing and preserving the intellectual output, raw data, and historic values of the institution for posterity. The UBRISA is challenged by limited budgets, logistical challenges, and limited expertise. This chapter recommends that partnerships and advocacy for legislative structures that support OA are critical.
Designing smart to revitalize a multicultural shopping street

Contributing to the broader concept of a sociable smart city enabling a transforming society into a more participative domain where innovation takes place, the chapter addresses the economic revitalization of Middellandstraat, a multicultural shopping street in Rotterdam, The Netherlands. Through a growing influx of immigrants, Middellandstraat has evolved into a unique multicultural neighborhood with a similar mix of shops. This chapter aims to push the current envelope of the smart city debate by adding a culture-sensitive design perspective on placemaking. This elaborates upon learnings from a local contextually grounded design project in the context smart city revitalization challenge and promotes design as a means to improve and revitalize the street. After presenting the rich insights of the contextual study, the chapter describes the findings of the culture-sensitive design approach following its four stages and the resulting concept, called SmaakReis. Next, barriers and enablers of culture-sensitive design are discussed along five themes that are found key in designing for the revitalization of the shopping street and reflect on the value of design and cocreation. Based on the lessons learned, the chapter concludes with ten guidelines for smart urban design and implementation. It can be concluded that SmaakReis was helpful in codesigning futures with the local stakeholders and enabled them to act on the designed smart city vision in aligning their strategic activities. Interestingly the implementation of the SmaakReis concept in one of the local restaurants stresses the importance of capacity building and the relevance of the guidelines for cultural and local embedment.
Application Integration Using Context Model Based on CIM

Many utilities and control centers has adapted CIM standards as their data model in application integration. The CIM profile is a subset of CIM for specific domain. Object-oriented modeling is used to create CIM profile, and mapping process to XML Schema and XML messages is used in many scenario. This method has several weakness, mainly because object-oriented modeling is complicated, and XML is heavy-weight message format, not suitable for IOT and low-bandwidth environment. The context model is characterized as collection of attribute-value pairs, CIM model converting to context model and mapping to JSON is a much more efficient way than profile-XML mapping method. XML sample and context model mapping to JSON sample are illustrated too.
System of technological support for continuous environmental education (by the example of the Altai republic)

This paper presents a concept of continuous environmental education that has a generic nature but was considered in the context of one particular region — the Republic of Altai. The work also presents a structural-functional model of the system of technological support of the continuous environmental education of secondary school students. The model of the system mentioned above is based on the results of theoretical, methodological and practical research as well as on its experimental verification. The system is based on the principle of environmental education with its substantive, regulatory and procedural functions. The study has confirmed the assumption about the necessity of this concept and proved its effectiveness in terms of developing a technology for continuous environmental education in the region. This concept was adopted by the Government of the Altai Republic and became the theoretical and methodological basis of this technology. The concept of environmental education in the Republic of Altai proposed allows observing the entire educational process and taking into account the connections between all functional structures most fully, since all of them are based on systematic, activity, reflexive, synergetic, resource, cultural approaches. The concept creates a theoretical basis for solving an important practical problem — the scientific substantiation of the didactic basis of environmental education. The investigation performed helps explain the essence and predict the development of complex processes in the field of education. The research allows using the experience of theoretical substantiation of the introduction of didactic provisions to the rank of teaching principles and experience in developing their "instrumentality" (the method of application) in the form of content, normative and procedural didactic functions. Also, this research allows building a concept that creates a theoretical basis for solving important practical problems in the education system and using the experience of revealing the deeper content of previously known pedagogical concepts, enabling the identification of their new core features.
DC Bias Phenomenon Recognition Based on Supervised Learning Model

dc bias phenomenon refers to the abnormal operation state of transformers whose vibration and noise signals increase due to the high voltage direct current (HVDC) transmission lines operating in ground return mode or the geomagnetically induced current (GIC). Shanghai Power Grid have built transformers' neutral point dc, vibration and noise monitoring platform since 2015. In this paper, Logistics Regression is firstly selected as a supervised learning model to judge whether the transformer has dc bias phenomenon based on the acquiring data. Two characteristic indexes representing dc bias phenomenon are found to improves the efficiency of model building. Simultaneously, appropriate regularization coefficients are chosen according to the evaluation effect and the physical meaning of model parameters. Considering most of data are unlabeled owing to the enormous effort of tagging data, a semi-supervised learning method is used to utilize the unlabeled data. Finally, an estimation model is established which calculates a probability value to indicate the risk of transformers' de bias phenomenon quantitatively. This model can remind operation and maintenance personnel strengthen devices inspection, and improves the efficiency of equipment management.
Urinary Red Blood Cells Extraction Based on Multiple Instance Learning and Watershed Segmentation

Doctors can diagnose many diseases by urinary red blood cells morphological analysis, and cell extraction is an important step in morphological analysis, which can help the subsequent classification of cells. However, it is time-consuming and inefficient for doctors to observe cells under a microscope, which easily leads to misdiagnosis and missed diagnosis. This paper proposes a method of cell extraction: firstly, the weak supervised multiple instance learning (MIL) is combined with resnet for cell localization, and the probability value of each pixel in urinary red blood cell image can be obtained through neural network, we set threshold value for probability value to obtain mask, finally, a marker-based watershed segmentation method was used to extract single urinary red blood cells. The experiment showed that the model achieved good results, with this method, doctors can directly analyze segmented cells, which can improve the efficiency of analysis and reduce the workload.
Application of Gradient Tree in Credit Evaluation of Chinese Peasant Households

The traditional peasant household credit evaluation is not only subjective, but also complex, time-consuming and inefficient with the help of experts' experience. In this paper, the research data of China family survey and research center are used to establish an evaluation model of China's peasant household credit with the help of the gradient tree model in the machine learning algorithm, and the AUC and F1 score are used to verify the evaluation results of the model. The empirical results show that the gradient tree model has a good prediction ability in peasant household credit evaluation, and it can be used as a new evaluation method in peasant household credit evaluation in China.
Multi Labeled Multi-Expressions to Explore Descriptive Documents

Abstract Expressive Clustering contains ordinarily filtering through information occasions into get-togethers and making a practical plan for each get-together. The depiction should inspire a client to press ahead with no more prominent assessment of the specific occasions regarding the substance regarding each social occasion, enabling a client to channel quickly for suitable classes. Once in a while, the choice of delineations relies on anxious representation of heuristic data. We model and coordinate reasonable assembly that recognises highlights from bundle assignments and from a subset of highlights seeks bundle assignments. For updated extraction of Multi Labeled Multi-Word Phrases, we present a zone free clustering based way of thought (MLMWEs). The framework incorporates true information from Wikipedia articles from an all-around obliging corpus and connexions. We lace alliance checks to package MLMWEs through pieces of server homesteads and then the organising score for each MLMWEs subject to the closest model offered to a social affair after that process. Results of the assessment, A combination of association figures, achieved for two vernaculars, shows that an improvement in the organisation of independent and vital coefficient frequency controls and ultimately undeniable steps for MLMWEs is given.
Improving Query Quality for Transductive Learning in Learning to Rank

In traditional transductive learning, all queries are used in learning to rank in order to generate pseudo-labels when sufficient training data are not available. However, low quality queries may affect retrieval performance in transductive learning. We thus think that it is important to improve the quality of queries in transductive learning to train an effective ranking model. By using a small number of reliable samples and data close to the boundaries of classification, we propose building a query quality estimator by establishing a relationship between the benefits of good retrieval performance and features of the normalized query commitment that influence query quality. In our proposed transduction model, all queries available are filtered by the proposed query quality estimator and only high quality queries that enhance the effectiveness of retrieval such that they yield performance-related benefits, are used to generate pseudo-labels for learning to rank. Queries that can degrade performance benefits are discarded while creating the pseudo-labels. Pseudo-labels aggregated by high quality queries in transductive learning are then leveraged in learning to rank scenarios without sufficient training data. The results of extensive experiments on the standard LETOR 4.0 dataset showed that our proposed method can outperform strong baselines and the average normalized discounted cumulative gain is enhanced up to 7.77% in some case.
Breaking the Circuit: Encountering Media’s Entanglements with Environment and Behavior through an Energy Art Practice

Uncovering and exhibiting digital media’s entanglements with energy, behavior and environment through artistic practice has been a decade-long quest for the author. Through three art projects the author describes his experiments with the energy consumption of media, lithium battery recycling, the Cloud and network connectivity. Arguing for critical artistic approaches, the author examines concerns of ecology and behavior as investigated by installation, by workshop, and by community participation, together forming an energy art practice.
Designing Software for Risk Assessment Using a Neural Network

This article presents the results of the research in terms of using mathematical methods for the risk management process in the implementation of software development projects. Software development projects are not always implemented in a final form that meets the expectations of customers. Both internal and external factors can influence this. In this regard, the problems of risk management, which inevitably arise during the implementation of software development projects, become particularly relevant due to the large uncertainty of the internal and especially external environment of enterprises. The introduction of a comprehensive approach to risk management allows the company to form an objective view of the current and planned activities of the organization, taking into account possible negative events or new opportunities, anticipate risks and make decisions based on information about them, respond to risks in a timely manner and reduce the negative impact of risks in their implementation. Within the framework of this research, the risk assessment software is designed to assess the situation in the project, predict the future effectiveness of the project, and build scenarios to support decision-making. Such software will allow to combine all the actions of the analyst in one tool, where all the information about the project and the external environment will be stored, updated and constantly used for training the Neural Network apparatus on which the software is designed. This work was supported by Russian Foundation for Basic Research (RFBR) grant № 20-010-00708\20.