Reviewerly/exHarmony huggingface dataset:
Video Tutorial Lessons Using 5W1H Model in Enhancing the Numeracy Skills of Grade 8 Non-Numerate Students

The study aimed to determine the effectiveness of using video tutorial lessons (VTLs) based on the 5W1H model on non-numerate grade 8 students. 44 non-numerate grade 8 students were identified and used as study respondents. The pretest was employed, followed by utilizing the VTLs and posttest administration. The study identified the personal related factors of the respondents in terms of instructional resources, learning environment, and parental support. The level of acceptability of the designed video tutorial lessons was determined in terms of content and technical production. The study also determined whether there is a significant difference in the pretest and posttest scores of Grade 8 students before and after using the VTLs. A significant relationship between variables was also tested using Pearson r. The findings revealed that the personal related factors for instructional resources of the respondents were printed modules, touchscreen cellphone and television. Likewise, learning environment and parental support are good as their personal related factors. In the pretest result, the respondents do not have mastery in measurement, calculating, patterns and relationships, and rational. On the other hand, they ranged from nearing mastery to mastery level in spatial and interpreting. Further, the level of acceptability of the respondents and experts on the quality of VTLs using the 5W1H model in terms of content and technical production. It improves the level of numeracy skills of the Grade 8 students based on the post-assessment results ranging from nearing mastery to mastery in measurement, calculating, patterns and relationships, and rational. Moreover, the respondents' numeracy skills and the personal related factors do not significantly correlate. The respondents' numeracy skills and the level of acceptability of the quality of the video tutorial lessons are not significantly correlated. Last but not least, there is a considerable change in the Grade 8 students' posttest results compared to their pretest scores after using the video tutorial lessons.
Movable Surface Models of Hand Joints Using Visible Korean

The human hand can make precise movements utilizing several joints of various articular types. To understand hand movements more accurately, it is essential to view the actual movements of bones and muscles considering the X, Y, and Z axes in the joints. This study aimed to investigate the joint movements in a hand using movable surface models, including these axes. These movable surface models of the hand will improve medical studentsâ understanding of hand movements around the joints. To achieve this aim, 70 surface models were adopted from a Visible Korean model. Using Maya software, 20 virtual joints with X, Y, and Z axes included nine distal and proximal interphalangeal joints, five metacarpophalangeal joints, five carpometacarpal joints, and one wrist joint were created. Bone surface models were elaborately polished to maintain their original shape during movement. Muscle surface models were also processed to display the deformation of the muscle shape during movement. The surface models of the hand joints were moved by virtual control of the joints. We saved 87 movable surface models of the hand, including bones, muscles, and joint axes in stereolithography format, and compiled a Portable Document Format (PDF) file. Using the PDF file, the joint movements in a hand could be observed considering the X, Y, and Z axes alongside the stereoscopic shapes of the bones and muscles. These movable surface models of the hand will improve medical studentsâ understanding of hand movements around the joints.
Data collection for aggregation of digital repositories: Entities linked to the Special Secretariat of Culture of Brazil

This article aims to clarify the use of data science techniques in information science by reporting data collection from the digital repositories of entities linked to the Special Secretariat of Culture of Brazil. This process is part of a research project promoted by the Foundation of Research Support of the State of São Paulo and carried out at the University of Brasília by the Network Intelligence Laboratory. The quantitative descriptive methodology applied alludes to extracting, transforming, and data load used in the constitution of data warehouses, in which Python scripts were developed to collect the data. The results indicate how many scripts were needed and how many storage files were generated, in addition to the description of the data collected, denoting a greater use of the web scraping technique, making the collection process more difficult. Thus, the article points out how the current reality of the analyzed Brazilian cultural institutions is far from enabling the aggregation of their digital repositories. At the same time, it points out how data science strategies allow information science professionals to overcome existing technical barriers and promote data analysis and reuse.
Research on an Artificial Intelligence-Based Professional Ability Evaluation System from the Perspective of Industry-Education Integration

The rapid development of artificial intelligence technology demands higher requirements for employment and talent training. The integration of industry and education is an important way to solve the mismatch between industrial demand and talent supply. Therefore, this study starts from the perspective of the integration of industry and education. We collect recruitment texts from the perspective of “industry” and mine the specific requirements of the artificial intelligence post system through the LDA topic model and the combination of Word2Vec and K-means. We then conduct expert consultations and adjust the selected indicators from the perspective of “education.” Finally, we construct a four-dimensional vocational ability grade evaluation index system, including basic vocational skills of artificial intelligence, database, network skills, algorithm and design skills, and research and practice skills. The intuitionistic fuzzy analytic hierarchy process, which can eliminate the subjective uncertainty of experts in the scoring process, is applied to calculate the index weights. We find that the weight of algorithm and design skill is the highest, which is an important criterion for artificial intelligence professional ability evaluation. Among the second-level indicators, practical indicators such as team spirit, innovation ability, and communication ability are the focus of investigation from the perspective of industry, while in education, the cultivation of knowledge and skills such as programming ability, applied mathematics ability, data structures, and algorithms are more important.
ORGANIZATION OF THE INCLUSIVE EDUCATIONAL ENVIRONMENT IN THE HIGHER EDUCATIONAL INSTITUTION OF CULTURE

The article considers the peculiarities of organizing and possibilities of the educational environment in the higher learning institution of culture for including inclusion into the educational process. The article gives the data on which the inclusive education is built in accordance with the demands regulat-ing the organization of the educational process and special conditions for the people with disabilities.
Multi-key searchable encryption technique for index-based searching

Multi-key searchable encryption scheme enables keyword search on encrypted data with different keys. The scheme is practical to apply for client server applications to achieve data confidentiality and makes the server to perform the search operation on the encrypted data. So far, this algorithm can be implemented for sequential search. This paper presents an improved version of multi-key searchable encryption algorithm implemented for index-based searching and also shows the experimental results of index-based multi key searchable encryption scheme implemented using C and pbc library. This research uses elliptic curve cryptography (ECC) technique for key improving security. This ECC technique contains the sequence of steps for a secure key generation by the user using hash function. Through the use of the hash function in ECC, performance is enhanced for index-based searching. Experimental results show the execution time of an improved version of multi key searchable scheme for index-based search constructed for different elliptic curves. An application is also designed by using new scheme to perform the search on one lakh encrypted collections with Java as front end and MongoDB as back end.
FACTORS OF CONSERVATION OF THE READERS’ CARD CATALOGUES IN THE MUNICIPAL LIBRARIES IN THE EXPERT ASSESSMENTS

The article gives a comparative analysis of electronic and card library readers’ catalogues, characterizes the functions of the paper catalogue as an important component of the reference search apparatus of the library infor-mation institution and the source of reference library servicing of different cat-egories of information consumers. The views of the prominent theorists of the modern Russian library science (E.R. Sukiasyan, L.B. Zuparova, etc.) concern-ing the usefulness of parallel introduction of traditional catalogues and their digital versions have been analyzed. The key factors that condition the librar-ies’ decision in favor of maintaining paper catalogues in actual condition are considered. In the author’s conclusion, keeping card catalogues in the epoch of digital transformation of information environment is guaranteed by the set of conditions the basic of which is the demand from the library readers.
Simulink Model Based on the Theory of Electric Wheelchairs

Considering an aging society, it is necessary to make the electric wheelchair safer and easy to drive. The one of the important technologies to realize it is the tracking control. The tracking performance is affected by the environmental circumstances and the wheelchair dimensions alike. Therefore, the theoretical SIMULINK Model of wheelchair is developed, which makes it possible to develop efficiently the tracking control considering the effect of the wheelchair dimensions. And through the simulation using this SIMULINK Model, it is clarified that the gravity center of the chair must be considered to develop the algorithm.
Are Irrational Numbers (Like the Square Root of the Number Seven) Applicable to Genetic Sequences?

According to Quantum Perspective Model, this article researches whether there is a link between the square root of seven numbers and the genetic sequences.At first, the square root digits of the number seven after the comma are added respectively.Secondly, the resulting sum corresponds to the nucleotide bases, the results obtained in this way are expressed as nucleotide bases.(A, T, C, G, and U).(A) Adenine, (T) Thymine, (C) Cytosine, (G) Guanine, (U) Uracil.From this point of view, when the first four hundred and fifty digits of the square root of the number seven after the comma are calculated, the gene sequence is obtained as follows:[GATTUAAGUTAATATTAUTAGTTTGATT].Thirdly, after researching this sequence at NCBI (National Biotechnology Information Center), the search result is similar to bony fishes, especially Danio rerio (zebrafish).Fourthly, the genetic codes of zebrafishes were found to be similar to human genetic codes.Lastly, some repetitions were detected exactly like this: as "GAT" and "UTA".In summary, the connection between these results and the square root of the seven in mathematical science and the genetic codes in biochemistry shed light on explaining irrational numbers.
Multi-label Text Categorization using Error-correcting Output Coding with Weighted Probability

In several real-world categorization problems, labeled data is generally hard to acquire when there is a huge number of unlabeled data. Hence, it is very important to devise a novel approaches to solve these problems, thereby choosing the most valuable instances for labeling and creating a superior classifier. Several existing techniques are devised for the binary categorization issues, only a limited number of algorithms are designed for handling the multi-label cases. The multi-label classification problem turns out to be more complex when the sample belongs to multiple labels from the group of accessible classes. In World Wide Web, text data is generally present nowadays, and is an obvious example for such type of tasks. This paper develops a novel technique to perform the multi-label text categorization by modifying the Error-Correcting Output Coding (ECOC) approach. Here, a cluster of binary complimentary classifiers are employed to facilitate the ECOC more effective for the multi-class problems. In addition, a weighted posterior probability is computed to enhance the multi-label text classification performance more effectively. Moreover, the performance of the proposed ECOC with weighted probability is analyzed using the performance metrics, like precision, recall, and f-measure with maximal precision of 0.897, higher recall value of 0.896, and maximum f-measure of 0.895.
Using the Temporal Data and Three-dimensional Convolutions for Sign Language Alphabet Recognition

Research is the development of the communication technology for detection of gestures of Ukraine sign alphabet.Basis of neural network with mobilenet architecture was improved with a new deep learning architecture -mobilenetv3.Another improvement lies in the field of the dataset -additional portion of train dataset was collected, and test dataset became more diverse, also due to improved data augmentation techniques.Deep learning model was improved with three dimensional convolution and data processing technique in a form of temporal frames.A lot of experiments to have a consistent improvement in model performance with better data augmentation, novel mobilenetv3 architecture as a basis and spatio-temporal frame are demonstreted the effectiveness proposed approach.
Monte Carlo Augmented Channel Estimator

We have developed a novel Monte Carlo augmented channel estimator for millimeter-wave orthogonal frequency-division multiplexing systems to better estimate and correct a transmitted orthogonal frequency-division multiplexed signal by incorporating the predefined known responses of system hardware and their errors.We compare our estimator against current channel estimators for different phased-array configurations and propagation channels.By accounting for these known responses of system hardware, our estimator provides an order-of-magnitude reduction of the standard deviation of the error vector magnitude and a reduction of the mean and standard deviation of the bit error ratio.
Corporate Information Security Processes and Services

This chapter addresses all the processes and services in the organization’s information security scope that should be implemented. Processes related to security awareness, training, and simulated attacks are addressed in the next chapter.
Installing Python

Before you can use Python, you need to install it. Some operating systems, such as macOS and some Linux variants, have Python preinstalled. Those versions of Python, colloquially called system Python, often make poor defaults for people who want to develop in Python.
OS Automation

Python was initially built to automate a distributed operating system called Amoeba. Although the Amoeba OS is mostly forgotten, Python has found a home in automating Unix-like operating systems tasks.
Car Race - an Engaging Interdisciplinary Python Based Project Activity

Abstract: Here we present and evaluate a Calculus project using Python and parametrizations: the CarRace. Each student picks an image of a circuit and another of a car online to make the car perform a race in the circuit. Because every student gets a different circuit, they have different lines to parametrize. This is performed using a Python program. Beforehand students get an example of the code for a car performing a circuit and must adapt it to their own project. This project was posed to a total of 346 engineering students over the course of 3 years. To evaluate the effectiveness of the project, we surveyed all participating students and 120 of them answered. The feedback from the students was mostly positive. It was engaging for students to make this project. They liked to see an immediate application of Mathematics. It helped them understand the subject better and they found it interesting to combine Python and Mathematics. At the same time, they also develop their critical thinking and problem-solving skills. Keywords: python, interdisciplinary, engineering students, project, coding, calculus.
Motive of Early Lyric and Philosophical Stories by A. Platonov

The article examines the motivational corpus of early lyric and philosophical stories by A. Platonov. The author himself calls them “poems” in his correspondence with his future wife. It is shown that the source of ontological tragedy for the author and his heroes is the destroyed unity of the universe. This maxim organizes the motivational system of the analyzed works. The main motives are longing, thirst for the impossible, the heroes’ love for distant stars and clouds. The intonational features of the stories put forward the main character’s inner position, the sphere of his experiences, to the main place. This turns him into a lyrical hero. From the point of view of the young author and his auto-characters, overcoming the separation from the sky can be achieved through “rebellion against the universe”. Here there is a clash of two opposites: love for the world and hatred for existing existence. This explains the opposite direction of the motivational system in the entire cycle of stories and within each work. At the genre level, this conflict is expressed through the clash of utopia with dystopia. Involvement in the analysis of letters, journalism, poetry of Platonov strengthens the argumentation of the author`s naming of the analyzed works of poems.
An Introductory Study to Quantum Programming

Computational capabilities are reaching their limits with the current technology. Quantum computing is the answer to this limitation. It has unraveled new possibilities of solving the unsolvable and computationally hard problems within a feasible time frame. In this chapter, the authors have discussed the basics of quantum computing, which include the need for quantum computers and how it internally works without getting into too much mathematics for an introductory understanding. The authors have also discussed different technologies in which the scientific communities and industries are working to make these computers feasibly work and the different programming techniques and tools available to implement the algorithms in these computers and the testbeds available to common people for testing the feasibilities of their programs.
Estimation of the factors affecting lactation milk yield of Holstein cattle by the adaptiveneuro-fuzzy inference system

Materıal and methods 2.1
Rational Analysis of Deep Learning in Mathematics

Under the background of talent training requirements and classroom teaching in mathematics, this article compares the differences between shallow learning and deep learning, and finds the characteristics of mathematical deep learning: unity of shallow processing and deep processing, unity of multiple understanding and overall construction, unity of master knowledge and promotion ability, unity of independent learning and cooperative learning, and unity of active learning and lifelong learning.Accordingly, it puts forward the rational understanding to promote deep learning in mathematics: rational understanding of deep learning, dealing with dialectical relations, and giving full play to the guiding value of teachers.
Densely Convolutional Networks For Breast Cancer Classification With Multi-modal Image Fusion

Breast cancer is the main health burden worldwide. Cancer is located in the breast, starts when the cell grows under control and begins as in-situ carcinoma and when spread into other parts known as invasive carcinoma. Breast cancer mass can early be found by image modality when discovering mass early can easily diagnose and treated. Multimodalities used for the classification of breast cancer Such as mammography, ultrasound, and Magnetic resonance imaging. Two types of fusion are used earlier fusion and later fusion. Early fusion it’s a simple relation between modalities while later fusion gives more interest to fusion strategy to learn the complex relationship between various modalities as a result, can get highly accurate results when using the later fusion. When combining two image modalities (mammography, ultrasound) and using an excel sheet containing the age, view, side, and status attribute associated with each mammographic image using DenseNet 201 with Layer level fusion strategy as later fusion by making connections between the various paths and same path by using Concatenated layer. Fusing at the feature level achieves the best performance in terms of several evaluation metrics (accuracy, recall, precision area under the curve, and F1 score) and performance.
A Methodology and Information System for Computing and Optimization of Impellers and Vanned Diffusers Geometry Parameters

Abstract The study aims to develop an information-computing complex for computer design of a centrifugal compressor with parallel calculation of stages and optimization of the geometric parameters of the impellers and the diffusers. The paper presents a universal methodology and computerized information system of the main geometry parameter determination and optimization of the centrifugal compressor impellers and vanned diffusers. Optimization of cross-sectional areas of the input and output channels of the impeller and diffuser blade channels is held using a gradient descent method by gas flowrate quadratic integral deviation criteria. The information-computing complex is built on the algorithm proposed by the authors and implemented as a computer program with a human-machine interface. Calculation data are written in the form of numerical arrays with the possibility of interpolating data and obtaining graphical dependencies.
SBugLocater: Bug Localization Based on Deep Matching and Information Retrieval

Bug localization is a technology that locates buggy source files using bug reports reported by users. Automatic localization of buggy files can speed up the process of bug fixing to improve the efficiency and productivity of software quality assurance teams. Nowadays, some research studies have investigated the natural language information retrieval technology, but few of them have applied the matching technology in deep learning to bug localization. Therefore, we propose a bug localization model SBugLocater based on deep matching and IR. The model composes of three layers: semantic matching layer, relevance matching layer, and IR layer. In particular, the relevance matching layer captures fine-grained local matching signals, while coarse-grained semantic similarity signals come from the semantic matching layer. Further, based on collaborative filtering in different directions, the IR layer works to find whether bug reports and source files are related, which indirectly transforms the matching task of different grammatical structures between bug reports and source files into the same structure and solves the mismatching problem of the first two matching models when the query is short. In our work, four benchmark data sets are used as experimental data sets and Accuracy@k, MAP, and MRR as evaluation metrics, which are used to compare and analyze the performance of bug localization with the four state-of-the-art methods. Experimental results show that SBugLocater outperforms the four models. For example, compared with the best of the four models, the evaluation metrics of Accuracy@10, MAP, and MRR are improved by 6.9%, 13.9%, and 17%, respectively.