Reviewerly/exHarmony huggingface dataset:
Peculiarities of Pedagogical Internship Organization for Future Specialists of Foreign Philology in Blended Learning

The competitiveness of the professional training of future philologists depends on the opportunities for professional realization, due to the formation of specific competencies, one of which is the competency of teaching activities. The specified factor encourages the creation of students’ conditions to obtain opportunities for professional realization in the practical activity of a teacher in secondary education.&#x0D; The conditions of a prolonged pandemic require the correction of the implementation of any type of educational activity by transferring it to the mode of distance learning which causes the need for students’ special training for pedagogical activities in the conditions of the mixed and distance mode in work of a secondary education.&#x0D; The purpose of the article is to analyze the features of pedagogical internship organization for students of foreign philology in a mixed form of education.&#x0D; The methodology is the analysis of scientific approaches to the definition the concepts "pedagogical practice of future philologists", "distance learning", "information and communication technologies (ICT)"; results’ presentation in the organization of pedagogical practice for philology students; determination of effective means for implementing the practical activities of an English language teacher in the conditions of distance learning which is based on the results of the pedagogical practice for philology students.&#x0D; Results. The pedagogical practice of philology students is aimed at forming the practical skills necessary for teaching a foreign language, in particular in all types of speech activity: speaking, reading, writing, listening. The formation of students' abilities to take into account the peculiarities of the presentation of educational information and the practice of specific foreign language skills for learners in the conditions of distance learning acquires importance.&#x0D; The analysis of the options of several platforms for the implementation of distance learning of a foreign language revealed the greatest effectiveness of the ZOOM program which was confirmed among other things by its selection as a common platform for training by basic colleges in O.M. Beketov National University of Urban Economy in Kharkiv (Ukraine). &#x0D; According to the results of pedagogical practice in the distance learning mode of the basic colleges, the need to correct the program of practices and the content of psychological and pedagogical disciplines and the methodology of teaching a foreign language, taking into account the characteristics of the teacher's activity in the conditions of the distance mode of work with the study group, was determined. &#x0D; In conclusion it should sum up that it is important to focus students on a clear distribution of time for the implementation of all types of speaking activities in a foreign language for students in the classroom and the reflection of these tools at specific stages of a lesson, taking into account the time of assessment and reflection.
IMPACT OF DIGITALIZATION ON ECONOMY IN UTTAR PRADESH IN INDIA

This evaluation paper affords information concerning the impact of digitalization on the economic system. By gathering and compiling studies articles related to the impact of digitalization and statistics and communiqué technology on the financial system in Uttar Pradesh in India. The digital economy is not in reality about transferring business transactions from head-to-head to online, but its approximately remodeling the various facets of enterprise interactions and transactions and enabling innovations too. From the reviews, the variables are Pricing, Speed, Unemployment, GDP, FDI, Money, Governance, Infrastructure, and many others., have found essential on this. Problem: Uttar Pradesh is a developing nation and dealing with many financial troubles with more or less 70% of the population dwelling in the rural elements of India it is barely difficult to educate them about the Digitalization and its influences of it. India is developing in many aspects like usage of the net and many others however making them use inside the right direction, which could assist them in increasing their productiveness and adds a fee to the money the front and making them financially literate is the main demanding situations in advance.
Incidence &amp; prevalence of leukemia with sub-typing in tertiary care centre: A retrospective &amp; prospective study

Introduction: Leukemia is a heterogeneous group of haematological malignancies that comprises several diverse and biologically distinct subgroups.The exact cause of leukemia is not yet clear.However, several factors, mainly hereditary inheritance, genetic mutations, epigenetic lesion, ionic radiation, chemical and other occupational exposures, therapeutic drugs, smoking, and some viral agents, have been implicated in developing leukemia.It is one of the fatal diseases and their morbidity and mortality rates increase day by day all over the world.Material and Method: 52 patients of leukemia were evaluated during May 2020 to June 2022 retrospectively & prospectively having chief complains of fatigue, weakness, infections, bleeding tendencies & bone pain out of total 81552 presenting to the OPD.Result: It was found that leukemia was equally prevalent in male and female patients, ratio being 1: 1 & most of the patients were over the age of 51 years.It was also observed that chronic leukemia was more prevalent than acute leukemia.Amongst types of leukemia, Acute myelogenous Leukemia (AML) was more prevalent (29%) than Acute lymphocytic Leukemia (ALL) (10%), similarly Chronic lymphocytic leukemia (CLL) was more prevalent (34%) than chronic myeloid leukemia (CML) (27%).Conclusion: Chronic leukemia was more prevalent than acute leukemia in this part of the country and its risk factors & pathogenesis needs to be addressed so that modifiable risk factors can be reduced to a minimum.
The Impact of Blockchain Technology Adoption Announcements on Firm’s Market Value

ABSTRACT Despite the growing interest in blockchain (BC) technology, recent research shows mixed perceptions due to its risks and returns. We utilize event study methodology to examine overall market reactions and to delineate how specific contexts associated with BC technology influence the market reactions. Using 149 BC technology adoptions announced between January 2015 and December 2019, we find positive abnormal returns, reflecting investors’ optimistic perception toward BC technology adoption. Specifically, we find that abnormal returns from BC technology are higher when used in a transformative strategic role and offered by leading vendors, suggesting that investors view this adoption as a value-enhancing activity. Our results are robust to the use of an alternative sample and different methods of measuring variables. Overall, our study provides insights for academics and practitioners to better understand the market value of BC technology adoptions. Data Availability: Data are available from the public sources cited in the text.
HUMAN BLASTOCYST EUPLOID PREDICTION BASED ON 3D MORPHOLOGICAL EVALUATION

To develop quantitative criteria for human blastocyst euploidy prediction based on 3D morphological measurement.
Digital competence frameworks in teacher education-A literature review

The role of the teacher in digital education is unconditional. Using ICT in the classroom is crucial for students' education and teachers' professional development. Qualitative teacher preparation plays an essential role in their further pedagogical practice. However, the lack of a digital competencies framework in initial education can cause problems in the subsequent practice of teachers. This paper analyzes the relevant literature that presents the available ICT competency frameworks to evaluate pre-service teachers' digital competence levels. The findings indicate a lack of pre-service teachers' digital competencies framework that can guide them in their initial preparation and develop digital competencies before actual practice. Generally, this paper provides an overview of digital competencies frameworks for teachers and their components, as well as information and recommendations to those responsible for initial teacher education program development and the integration of technologies into initial teacher education.
ART AS A POTENTIAL FOR THE DEVELOPMENT AND LEARNING OF CHILDREN IN CHILD EDUCATION

The present research consists of approaching the importance of including Art and its different languages in Early Childhood Education, since it guarantees the potentialization of children's development and learning, by establishing internal and external connections, through the sensitive.Art, intertwined with education, is something that has been discussed for years, however, we still see stereotyped and mechanized productions in the classroom.This research comes as an attempt to break with these paradigms and demonstrate an education aimed at childhood, with different interactions, with the self, the other and the world around them, with freedom, curiosity, experiences and games, reaching, more effectively, children's development and meaningful learning.
Technological glitches and creative interactions in Sharing Dance

Co-authored by an Improving Social Inclusion for People with Dementia and Carers through Sharing Dance project researcher and European collaborators involved in the expansion of the Sharing Dance Older Adults program internationally, the aim of this chapter is to explore the effectiveness and challenges of using technology to deliver a remote dance program to rural communities. This chapter situates remote delivery of Sharing Dance Older Adults within gerontological research on the use of technology to enhance older people’s lives. A key feature of the chapter is its emphasis on understanding the role and limitations of technology in facilitating program delivery and the development of new research approaches. The chapter is of particular interest to researchers in the field of technology as well as professionals and organizations delivering technologically mediated programs.
New Teaching Strategy Reusing Multimedia Materials: Different Uses of the Quiz Resource

The pandemic and forced social isolation in 2020 prompted a radical change in teaching strategies. This situation was maintained in the 2021 academic year and there was a rethinking of the methodology used in distance education. In a first statistics course offered by the Faculty of Economics at the National University of Cordoba (UNC), Argentina in 2021, the didactic resources of 2020 were reused but redesigned based mainly on the implementation of quizzes worked on during synchronous virtual classes. The results of the strategy change were very encouraging because they allowed for more active virtual classes with greater student attendance, and also presented students with practice to review content and become familiar with the platform used for virtual evaluations.
Data Visualization and Analysis of COVID-19 Data

Abstract: During the COVID-19 pandemic, many data visualizations were created to alert the public to the rapidly growing threat. Statistics on the spread of COVID-19 have been displayed on data dashboards, a mechanism for sharing information throughout the pandemic, which has aided in this process. When developing the visuals for COVID-19, the majority of time was spent on the technical aspects of designing and evaluating various visualization methods. Little is understood about the inner workings of visualization production processes due to the complex sociotechnical environments in which they are embedded. However, such ecological data is necessary for identifying the particulars and tendencies of visualization design practices in the wild and generating insights into how artists learn to perceive and approach visualization design on their terms and for their contextual aims. We conducted in-depth interviews with dashboard designers from federal and state health departments, major news media outlets, and other firms that created (often widely used) COVID-19 dashboards to gain insight into the following areas. What kind of problems, disagreements, and conflicts arose during making the COVID-19 dashboard because of the participation of visualization creators? The trajectory of design practices—from genesis to expansion, maintenance, and termination—is determined by the complex interconnections between design goals, design tools and technologies, labour, emerging crisis circumstances, and public participation. We zeroed in on these procedures' tensions between designers and the general public. Conflicts frequently arose due to a chasm between public demands and prevailing policies. They typically centred on the types and amounts of information that should be visualized and how public perceptions shape and are shaped by visualization design. The strategies used to deal with (potential) misinterpretations and misuse of visualizations. Our findings and takeaways offer fresh viewpoints on visualization design by highlighting the bundled activities typically linked with human and nonhuman participation along the entire trajectory of design practice
A Comparative Study of Existing Approaches for Modeling the Incident Irradiance on Bifacial Panels

Accurate modeling of bifacial module energy production is conditioned to the correct modeling of the front and rear irradiance. This paper compares the existing approaches used to estimate the incident irradiance on the back side and the front side of a photovoltaic (PV) bifacial module, by studying the performance of each model in terms of accuracy and computation time. In this study, we have selected three software with different approaches. We started with Bifacial_radiance which uses the ray-tracing technique. The second software is Sandia model which is a three-dimensional implementation of view factor method under MATLAB™. We complete our study with pvfactors that employs a two-dimensional configuration factor model. This study aims to propose the most time-efficient way to compute the irradiances received by bifacial panels, which will serve to predict the energy production of power plants. Having a fast model allows to develop efficient real-time management strategies for power supply systems that use bifacial modules. According to this study, pvfactors has the lowest execution time and gives almost the same output results as Bifacial_radiance and Sandia model that use complex algorithms.
Auto-scoring of Student Speech: Proprietary vs. Open-source Solutions

This paper compares the speaking scores generated by two online systems that are designed to automatically grade student speech and provide personalized speaking feedback in an EFL context. The first system, Speech Assessment for Moodle (SAM), is an open-source solution developed by the author that makes use of Google’s speech recognition engine to transcribe speech into text which is then automatically scored using a phoneme-based algorithm. SAM is designed as a custom quiz type for Moodle, a widely adopted open-source course management system. The second auto-scoring system, EnglishCentral, is a popular proprietary language learning solution which utilizes a trained intelligibility model to automatically score speech. Results of this study indicated a positive correlation between the speaking scores generated by both systems, meaning students who scored higher on the SAM speaking tasks also tended to score higher on the EnglishCentral speaking tasks and vice versa. In addition to comparing the scores generated from these two systems against each other, students’ computer-scored speaking scores were compared to human-generated scores from small-group face-to-face speaking tasks. The results indicated that students who received higher scores with the online computer-graded speaking tasks tended to score higher on the human-graded small-group speaking tasks and vice versa.
Optimal detection of the feature matching map in presence of noise and outliers

We consider the problem of finding the matching map between two sets of $d$ dimensional vectors from noisy observations, where the second set contains outliers. The matching map is then an injection, which can be consistently estimated only if the vectors of the second set are well separated. The main result shows that, in the high-dimensional setting, a detection region of unknown injection can be characterized by the sets of vectors for which the inlier-inlier distance is of order at least $d^{1/4}$ and the inlier-outlier distance is of order at least $d^{1/2}$. These rates are achieved using the estimated matching minimizing the sum of logarithms of distances between matched pairs of points. We also prove lower bounds establishing optimality of these rates. Finally, we report results of numerical experiments on both synthetic and real world data that illustrate our theoretical results and provide further insight into the properties of the estimators studied in this work.
Googling Model based on Interactive Multimedia for Elementary School Students

This study aims to develop an interactive multimedia-based Googling learning model for elementary school students in Banjarmasin City. The research method used is Research and Development (R&amp;D). The subject of this study was a Grade IV student at SD Surgi Mufti, Banjarmasin. Data collection techniques through questionnaires, observations, and tests. The data analysis technique used is a descriptive analysis using tables and graphs. The feasibility testing results of this interactive multimedia-based googling learning model product are categorized as feasible because the effects of media validation testing, materials, and individual and small group tests show excellent categories. In terms of practicality, the development of this learning model is categorized as very good because the score category of learning implementation results and learning activities of class students has a range between 3.5–4.0. Googling model can train and develop students' ability to think critically, become more active and passionate in learning, and train student cooperation in discussions. The interactive multimedia-based googling model clarifies the presentation of the material, overcomes the limitations of space, time, and sensory power, and can overcome students' passive attitudes.
4-Band Multispectral Images Demosaicking Combining LMMSE and Adaptive Kernel Regression Methods

In recent years, multispectral imaging systems are considerably expanding with a variety of multispectral demosaicking algorithms. The most crucial task is setting up an optimal multispectral demosaicking algorithm in order to reconstruct the image with less error from the raw image of a single sensor. In this paper, we presented a four-band multispectral filter array (MSFA) with the dominant blue band and a multispectral demosaicking algorithm that combines the linear minimum mean square error (LMMSE) and the adaptive kernel regression methods. To estimate the missing blue bands, we used the LMMSE algorithm and for the other spectral bands, the directional gradient method, which relies on the estimated blue bands. The adaptive kernel regression is then applied to each spectral band for their update without persistent artifacts. The experiment results demonstrate that our proposed method outperforms other existing approaches both visually and quantitatively in terms of peak signal-to-noise-ratio (PSNR), structural similarity index (SSIM) and root mean square error (RMSE).
Novel Cloud-Edge Collaborative Detection Technique for Detecting Defects in PV Components, Based on Transfer Learning

The existing techniques for detecting defects in photovoltaic (PV) components have some drawbacks, such as few samples, low detection accuracy, and poor real-time performance. This paper presents a cloud-edge collaborative technique for detecting the defects in PV components, based on transfer learning. The proposed cloud model is based on the YOLO v3-tiny algorithm. To increase the detection effect of small targets, we produced a third prediction layer by fusing the shallow feature information with the stitching layer in the second detection scale and introducing a residual module to achieve improvement of the YOLO v3-tiny algorithm. In order to further increase the ability of the network model to extract target features, the residual module was introduced in the YOLO v3-tiny backbone network to increase network depth and learning ability. Finally, through the model’s transfer learning and edge collaboration, the adaptability of the defect-detection algorithm to personalized applications and real-time defect detection was enhanced. The experimental results showed that the average accuracy and recall rates of the improved YOLO v3-tiny for detecting defects in PV components were 95.5% and 93.7%, respectively. The time-consumption of single panoramic image detection is 6.3 ms, whereas the consumption of the model’s memory is 64 MB. After cloud-edge learning migration, the training time for a local sample model was improved by 66%, and the accuracy reached 99.78%.
Mobile learning in grades K–12: A literature review

Due to the widespread use of mobile technologies, their use of them in teaching processes has also increased. Within this framework, in this study, in-depth investigation of K-12 grades studies from 2015 to 2021 which were conducted on “mobile learning”, and “learning anywhere” published on “Web of Science” through specific criteria. A total of 4419 studies published only in English were accessed initially. Then, other keywords related to K-12 grades within the scope of the study were also searched, and 452 publications were reached. 336 studies that did not meet the inclusion criteria were excluded, and as a result, 109 studies were identified as primary studies. In this study, apart from the basic criteria used in previous literature review studies, criteria such as "reporting the prerequisite tests of the analyses used in the research", "validity, and reliability studies", "reporting the effect size", and "the existence of ethical, and legal permissions" are also included. The study could be considered important in terms of these additional criteria, and with its purpose of trying to reveal mobile learning tendencies.
Term Frequency Based Approach for Binary Classi?cations on Short Sentences

Abstract: Great strides have been taken in advancing the domain of Natural Language Processing(NLP) over the past few years. The introduction of attention mechanism in neural networks has led to the creation very complex and efficient architectures like the BERT and GPT. These architectures have been well established as the first choice for most problem statements but, there application in certain simpler use cases generally undermines their real potential. The use case I explore in this research paper is the Natural Language Processing with Disaster Tweets. This is a binary classification task for picking out tweets that refer to a disaster. In this research paper I report the performance of Term Frequency based algorithm without leveraging any vector embedding techniques. Since I am making use of an open source dataset from Kaggle, I have received a leaderboard score of 0.78. The scoring metric used for the leaderboard is the F1 metric and the best score stands at 0.85. The approach leverages the ability of a inverse document frequency(IDF) metric to readily eliminate "stop word" from a corpus and uses a modified term frequency metric&lt;put definition reference&gt; to classify the sentences. The said term frequency metric has been designed in a way to eliminate any impact of stop words that might have escaped from the IDF filter. This paper presents the detailed description of all the algorithms and metrics utilized before coming to a final conclusion.