Reviewerly/exHarmony huggingface dataset:
Ways to form students' creative abilities in the school mathematics course

The article discusses the theoretical foundations and pedagogical features of the organization of students' creative abilities during the development of «creative abilities of students». The factors and conditions that contribute to the skills of students' creative abilities are revealed, didactic units and functions worthy of organizing students' research activities are considered in the mathematical learning process, the structure of which is indicated. In teaching mathematics, the definition of «creativity» is clarified. A pedagogical analysis of textbooks of the natural and mathematical direction is carried out and the advantages in textbooks are indicated. The concept of «creative abilities of students» is considered and problems are given. Scientific research was carried out in the general secondary school «Shokai No. 24». When conducting research work, methods of analysis of pedagogical and psychological literature, pedagogical analysis of creative abilities, observation, survey, pedagogical experiment are used. As a result of the research, search and research, creative tasks aimed at the development of search and research, creative activities of students were compiled. Students were interviewed anonymously. The study involved 57 students, 25 percent of whom were able to complete the tasks in full. Discussing the results of the survey; students who work with additional literature, who are interested in independent search, creative work, were able to complete the tasks. The result of scientific research can be used as an auxiliary tool for specialists in the field of mathematics, who teach algebra courses in the school curriculum, search and Research tasks for the development of search and research activities of students.
Exploring the Arctic deep-sea by color filters

&#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; Focus:&#x0D; To get to know some of the creatures in the deep-sea that use color and the lack of light to camouflage themselves.&#x0D; Learning objectives:&#x0D; With these TWO activities, we use vision to explore life forms in the deep sea which have adapted to extreme conditions. Through the activities, the pupils will also become familiar with some organisms well-hidden at the bottom of the ocean.&#x0D; Key words:&#x0D; Camouflage strategies, Deep sea ocean, Physical effects of light, Characteristics of sea lifeforms&#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D;
Manifesting creativity in the learning activity process of early school-age students

In this article, we analyze the specifics of the manifestation of creativity in the process of the learning activity of students of small school age. In general, at early school age, the educational process fully requires the activation of the student's creative forces. Stepping on the threshold of school, children are trained in assiduous and continuous intellectual work, largely unknown to them. In such a situation, life experience and previously accumulated knowledge prove to be insufficient for obtaining a positive result. And then, children activate their creative potential. That is, it appeals to intuition, manifests intellectual initiative, attributes elements of fantasy to the element of knowledge: unexpected comparisons and associations, unusual hypotheses.
Ad astra or astray: Exploring linguistic knowledge of multilingual BERT through NLI task – CORRIGENDUM

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IOT BASED TRANSFORMER PARAMETER MONITORING

Transformers are the primary component of a power system.Transformer damage has a negative impact on the stability of a power system.Damages primarily result from overloading and ineffective cooling.The major goal of employing IOT technology to monitor the transformer parameters in real time.The transformer's properties, including temperature, voltage, current, and oil level, are tracked, processed, and recorded on servers.We use sensors that are connected to microcontrollers for this purpose.The recorded data can be sent using a GSM/Wi-Fi module and accessed using IOT technology from any location in the world.This aids in identification without reliance on people.This assists in spotting and fixing issues before they become failures without human supervision.
Network Analysis of Academic Medical Center Websites in the United States

Healthcare resources are published annually in repositories such as the AHA Annual Survey DatabaseTM. However, these data repositories are created via manual surveying techniques which are cumbersome in collection and not updated as frequently as website information of the respective hospital systems represented. Also, this resource is not widely available to patients in an easy-to-use format. Network analysis techniques have the potential to create topological maps which serve to aid in pathfinding for patients in their search for healthcare services. This study explores the topological structure of forty United States academic health center websites. Network analysis is utilized to analyze and visualize 48,686 webpages. Several elements of network structure are examined including basic network properties, and centrality measures distributions. The Louvain community detection algorithm is used to examine the extent to which these techniques allow identification of healthcare resources within networks. The results indicate that websites with related healthcare services tend to form observable clusters useful in mapping key resources within a hospital system.
Chatbot Automation for Student Educational Purpose

Abstract: Chat bots are gradually becoming more sophisticated as they are now adapting to new AI features with ease. We can also expect them for recognizing user intent efficiently, decode mood of end users instantly, and then drive flow of conversations in tune with end user’s emotions. Also, sentiment analysis is one of such features that make bots even powerful in terms of understanding emotions in end user messages. In fact, 65% of businesses believe that the chat bots could help them providing more customized support experiences for their users. We can always leverage chat bot sentiment analysis feature for easily knowing if users are having a good experience with chat bots
Development of a High Min-Entropy Quantum Random Number Generator Based on Amplified Spontaneous Emission

We present the theory, architecture, and performance characteristics of a quantum random number generator (QRNG) which operates in a PCI express form factor-compatible plug-and-play design. The QRNG relies on a thermal light source (in this case, amplified spontaneous emission), which exhibits photon bunching according to the Bose-Einstein (BE) statistics. We demonstrate that 98.7% of the unprocessed random bit stream min-entropy is traceable to the BE (quantum) signal. The classical component is then removed using a non-reuse shift-XOR protocol, and the final random numbers are generated at a 200 Mbps rate and shown to pass the statistical randomness test suites FIPS 140-2, Alphabit, SmallCrush, DIEHARD, and Rabbit of the TestU01 library.
Light RAT-SQL: A RAT-SQL with More Abstraction and Less Embedding of Pre-existing Relations

RAT-SQL is among the popular framework used in the Text-To-SQL challenges for jointly encoding the database relations and questions in a way to improve the semantic parser. In this work, we propose a light version of the RAT-SQL where we dramatically reduced the number of the preexisting relations from 55 to 7 (Light RAT-SQL-7) while preserving the same parsing accuracy. To ensure the effectiveness of our approach, we trained a Light RAT-SQL-2, (with 2 embeddings) to show that there is a statistically significant difference between RAT-SQL and Light RAT-SQL-2 while Light RAT-SQL-7 can compete with RAT-SQL. Keywords: Deep learning, Natural Language Processing, Neural Semantic Parsing, Relation Aware Transformer, RAT-SQL, Text-To-SQL, Transformer.
The Effects of Flipped Learning Teaching Methods Using Application of the Action Research Models

This study was attempted to find out the effectiveness of the flipped learning teaching methods using application of the action research model.The participation were 94 nursing students from J college and the study was conducted from August 31, 2020 to December 18, 2020.The action research model is a spiral self-reflective circulation model that repeats the three stages of planning, execution and observation, and reflection.The flipped learning teaching method, which applied the action research model, was conducted for two hours every week, and data collection was conducted in advance in the first week of the lecture, and in the last week of the semester.The collected data analysis was analyzed using SPSS 22.0 for window.As a result of the study, self-efficacy(t=24.70,p<.001), learning satisfaction(t=-11.05,p<.05), learning attitude(t=6.85,p<.05), willingness to participate in continuing learning(t=-7.52,p<.001).All increased statistically significantly.Based on the results of this study, it is expected to be actively used through the teaching and learning method of flip learning using a spiral self-reflective circulation model.
Exploration of Technological Collaboration Trends in Ulsan through Patent Network Analysis

The purpose of this study is to explore the technological cooperation structure of Ulsan through the analysis of the technological cooperation network.This study analyzed the network of patent applicants filed in Ulsan for 10 years from 2012 to 2021.The study conducted frequency analysis of patent networks to identify major applicants and key technology in Ulsan.The result showed patent applications have been rapidly expanding to universities and individuals, which increases the diversity of industries and technologies in the region.Especially, the study investigated co-occurrence patterns of patent applicants over time to examine collaboration trends in Ulsan.The result showed Collaborative Activities of Industry-University-Research have not yet been extensively expanded.Moreover, there is a tendency to collaborate with applicants outside the region rather than within the region.However, the local environment for technical cooperation has improved, and small-scale cooperation has recently been on the rise.In particular, local universities are not only the core of knowledge production and distribution, but also central to cooperative activities for the effective production and distribution of knowledge.
Exploring Spiritual Concepts for Spirituality Education in Secondary School

While research on spiritual education is increasing, spirituality is still recognized to be an abstract, difficult, and ambiguous concept.The purpose of this study is to define the concept of spirituality clearly by considering the concept and exploring the direction of spiritual education in secondary education.Spirituality can be defined according to vertical and horizontal dimensions.First, the vertical dimension implies metaphysical and religious meaning concerning a relationship with a higher and transcendental being in a specific individual context that goes beyond the existing understanding of individualistic, inner-centered, and afterlife-centered spirituality.Second, the horizontal dimension includes existential meaning in social and environmental relationships, meaning relationships with self, others, and nature.Thus, spirituality is "expansion of consciousness about transcendent existence."This emphasizes spirituality linked to temporal life, exemplifying the need to fulfil social responsibility and the possibility of practicing it.Moreover, it serves as a basis for escaping from the narrow perception of interpreting spirituality only from an excessively mystical or rationalistic perspective in the past.Spiritual education in schools needs to teach both horizontal and vertical dimensions harmoniously.
Effects of the Background Variables and Level of Communication on Collaborative Self-regulation and Collaborative Self-efficacy of University Students in Learning Community Program

This study was conducted to investigate the variables which effected on effectiveness of the learning community program operated by the Center for Teaching and Learning as part of a noncurricular program at a university.This study was conducted to explore the effects of the learning community program on collaborative self-regulation and collaborative self-efficacy according to the background variables of gender, grade, and communication level of undergraduate students who voluntarily participated in the learning community program.The results were analyzed based on the survey responses of 151 people who faithfully responded to the pre-and post-test among a total of 240 people who participated in the learning community program held in the first semester of 2021 at A University located in the metropolitan area.The research method was a single experimental group without a control group.Collaborative self-regulation and collaborative self-efficacy before and after participation in the learning community program as a group were compared with a paired sample t-test, and gender, grade, and communication level were used as intergroup variables, and before and after participation in the learning community program were compared.Repeated measures ANOVA was conducted on collaborative self-regulation and collaborative self-efficacy as within-group variables.First, as a result of verifying the difference between pre-post collaborative self-regulation and collaborative self-efficacy, both were statistically significantly improved.Second, as a result of analyzing the differences in the pre-and post-collaborative self-regulation changes according to gender, grade, and communication level, a significant interaction effect was derived between the communication level and the time point.There was a difference in the pattern of regulatory changes.Third, as a result of analyzing the difference according to gender, grade, and communication level in the changing patterns of pre-post collaborative self-efficacy, a significant interaction effect was derived between gender and communication level and time.There was a difference in the aspect of collaborative self-regulation change according to the results.Based on these results, the implications for operating learning community programs were discussed.
Reading Habits and Educational Achievement of Secondary Schools Learners in Bishan, Singapore

Reading habits have been singled out as having a significant impact on learners' intellectual output. Good reading habits allow learners to develop their critical thinking skills and eventually improve their academic performance also reading non-academic novels helps learners improve their linguistic skills. Learners with weak reading habits have made noticeable improvements after taking part in lengthy reading assignments. Learners nurture skills such as thinking, valuing, flexibility and creativity are helped by extensive reading habits. The study found that learners who read both academic and non-academic literature regularly improve their conceptual understanding, critical thinking abilities and language fluency which leads to improved academic achievements. The study noted that reading habit at home is hampered by the lack of a comfortable environment. Several factors such as home environment, family income, access to books, and parental involvement can influence students' reading habits. Students from homes with a reading culture, those with access to a wide range of reading materials, and those whose parents encourage and model reading are more likely to develop good reading habits. The study concluded that reading is a fundamental skill that should be encouraged continually throughout childhood to help people become lifelong learners. The lack of reading resources, poverty and conventional ideas all have a detrimental impact on how readers develop their habits. The study recommends that teachers should create strategies for encouraging learners to read more. This involves making sure that reading materials are available in the libraries and resource areas. In order for books to become an integral part of learners’ life, let them be easily accessible both in schools and in homes. Schools should create a schedule for library hours to enable learners to visit the library for reading. Parents should encourage their children to read in a calm environment at home. Keywords: Reading Habits, Educational Achievement, Learners, Singapore
Study of Heavy Metal Contamination in Industrial Soils of Aurangabad Using GIS Techniques

The main objective of the present study is to assess the level of contamination, source identification, and health risk assessment of heavy metals in the industrial soils of Aurangabad. A total of 15 Soil samples were collected with a sampling density of 3–5 composite soil samples from 0–10 cm surface soil, analyzed heavy metals (Ni, Pb, Cd, Zn, Cr, Mn, Fe, and Cu) using atomic absorption spectroscopy. The geographical information system (GIS) technology like Kriging and inverse distance weighted interpolation (IDW) was used for the preparation of spatial distribution maps. A significant spatial relationship was found for Ni, Cd, Zn, Pb, and Cu in the soils using a GIS-based analysis, suggesting that these metal contaminants in the industrial area had common sources. Assess the risks of contamination for heavy metals in the soil were assessed based on a geo-accumulation index (Igeo) and contamination factor (CF). According to the Igeo and CF, most of the samples vary between 0 to 1, unpolluted to moderately polluted except Cd values. Most of the measured heavy metals showed the highest availability in top soils collected from around the steel and metal industries of the Waluj MIDC area. Also, based on the outcomes of the health risk assessment, particular attention should be paid to Ni, Pb, Cd, Zn, Cr and Cu in the industrial soils of Aurangabad. This study is socially beneficial for prevailing human health hazards in such industrially populated regions.
Temporal status and change detection of stone quarrying and crushing activities using multi-temporal google earth images

Stone quarrying and crushing (SQC) activities under mining operations normally produce a destructive landscaping impression during the period from start to end. Spatio-temporal data, downloaded from Google Earth Pro s/w, coupled with remote sensing, GIS, and GPS has been used to evaluate time series (2003, 2008, 2015 and 2021) analysis of stone quarrying and crushing activities in a part of Jhansi Tehsil. Results shows that the variability and pressure on land resources due to stone quarry and crushing activities were found linear increments during the time. There was annual heavy exploitation record during 2003-2008 (30.83%) of stone from quarry sites and total increments of SQC activities were found 277.64% since last 18 years. This study exhibited the prospective advantage of annual monitoring over period and support to make the possible preparations/ management for destructive mining operations. This study exhibited the prospective advantage of annual monitoring over period and support to make the possible preparations/ management for destructive mining operations.
Multimodal Deep Learning Methods to Predict Radiotherapy Structure Names using Image and Textual Data from DICOM Files

Physicians often label anatomical structure sets in Digital Imaging and Communications in Medicine (DICOM) images with nonstandard names. As these names vary widely, the standardization of the nonstandard names in the Organs at Risk (OARs), Planning Target Volumes (PTVs), and &amp;#039;Other&amp;#039; organs inside the area of interest is a vital problem. Prior works considered traditional machine learning approaches on structure sets with moderate success. This paper presents integrated deep learning methods applied to structure sets by integrating the multimodal data compiled from the radiotherapy centers administered by the US Veterans Health Administration (VHA) and the Department of Radiation Oncology at Virginia Commonwealth University (VCU). The de-identified radiation oncology data collected from VHA and VCU radiotherapy centers have 16,290 prostate structures. Our method integrates the heterogeneous (textual and imaging) multimodal data with Convolutional Neural Network (CNN)-based deep learning approaches like CNN, Visual Geometry Group (VGG) network, and Residual Network (ResNet). Our model presents improved results in prostate (RT) structure name standardization. Evaluation of our methods with macro-averaged F1 Score shows that our deep learning model with single-modal textual data usually performs better than the previous studies. We also experimented with various combinations of multimodal data (masked images, masked dose) besides textual data. The models perform well on the textual data alone, while the addition of imaging data shows that deep neural networks can achieve improved performance using information present in the other modalities. Additionally, using masked images and masked doses along with text leads to an overall performance improvement with the various CNN-based architectures than using all the modalities together. Undersampling the majority class leads to further performance enhancement. The VGG network on the masked image-dose data combined with CNNs on the text data performs the best and establishes the state-of-the-art in this domain.
Ordinal Logistic Regression as a Tool To Estimate the Risk of Escalating Outcomes. An Application to Vehicle Crash Data

The use of logistic regression models in data analysis and machine learning has expanded in recent years and has become the primary preference of researchers in risk assessment studies across a wide range of scientific fields. From the assessment of credit risk in financial institutions to the estimation of risk factors for traffic accidents or the identification of etiological factors for chronic diseases. All logistic models are natural extensions of the simple binary model, and their interpretation is based on it. Using the data of a cross-sectional study on the risk factors of traffic collisions, the two main extended models of logistic techniques, multinomial and ordinal logistic regression, are presented in the article in detail. Emphasis is placed on the use of ordinal regression since the outcome variable of the collision data is defined as ordinal measurement reflecting a latent continuous scale.