Reviewerly/exHarmony huggingface dataset:
ADAPTATION OF EDUCATIONAL MIGRANTS IN RUSSIAN UNIVERSITIES: MODERN SCIENTIFIC APPROACHES AND OPINIONS OF FOREIGN STUDENTS

Objective of the study is the analysis of the main theoretical approaches of modern Russian researchers to the study of the problems of adaptation of foreign students and comparison with the results of a survey of educational migrants. &nbsp; The methodological basis of the research is presented by the results of an applied sociological study implemented by the SRB – FCTAS RAS in the first half of 2021. During the implementation of the study, foreign students of the Southern Federal District universities were interviewed. &nbsp; Research results. This article examines the theoretical works of modern Russian researchers devoted to the study of the problem of adaptation of educational migrants in Russian universities. The main recommendations and examples of implemented measures to facilitate the process of adaptation of foreign students highlighted in these works are described. A comparative analysis of the opinions of educational migrants regarding the necessary improvements in the educational process and the recommendations presented by researchers in scientific papers is carried out. The methods of educational work to assist in the adaptation of foreign students at the university are highlighted, the need for the implementation of which is noted by both representatives of the scientific community and the educational migrants themselves. Also, the directions of work are identified, the importance of which is paid attention to by foreign students, but not sufficiently studied in the works of researchers. &nbsp; &nbsp; Prospects of the study. The results of the study will improve the effectiveness of educational work in higher education institutions aimed at helping students from other countries to adapt.
Etnomathematic Analysis: Implementation Of The Ecentric Digraph In Determining The Ka'ba As Center Of The Earth

The Rajaban tradition is a tradition of religious rituals as an expression of gratitude and moments to commemorate historical events, one of which is the change in the direction of Qibla from Baitul Maqdis to the Kaaba in Mecca. Based on these problems, in this article, it is shown by using the study of Graph Theory, namely the eccentric digraph to determine the center of the earth's region. Data processing is done by making the Kaaba and the seven continents on the earth's surface as a point on graph G and the side connecting the points is the distance (in km) with physical boundaries between them being considered non-existent. The results of the discussion show that the Kaaba in Mecca is the center of the earth's area with ec(v1) = 12,039 = rad(G).
Penerapan Model Discovery Learning Melalui Latihan Soal Terbimbing Sebagai Upaya Meningkatkan Hasil Belajar Matematika Peserta Didik pada Pokok Bahasan FBB dan KPK di Kelas IV SDN 03/X Tanjung Solok Semester Ganjil Tahun Ajaran 2021/2022

This study aims to describe and obtain information on improving Mathematics learning outcomes through Discovery Learning. This research is a classroom action research consisting of two cycles, each cycle consisting of two meetings. Each meeting consists of four stages, namely planning, implementation, observation and reflection. The subjects of this study were the fourth grade students of SDN 03/X Tanjung Solok, totaling 25 people. This research was conducted in the odd semester of the 2021/2022 academic year. Data collection techniques using tests, observations, and documentation. Data were analyzed using percentages. The results of the study indicate that through Discovery Learning, students can improve their Mathematics learning outcomes in class VI SDN 03/X Tanjung Solok by giving rewards.
Hybrid dynamic chunk ensemble model for multi-class data streams

In the analysis more specifically in the classification of continuous data stream using machine learning algorithms joint occurrence of concept drift and imbalanced issue becomes more provocative. Also, imbalance issue is again more challenging when the data stream is multi-class with minority class and that is too with data-difficulty factors. Incremental learning with ensemble models found more promising in handling theses issues. But most of the approaches are for two-class data streams which can’t be utilized for multiclass data streams. In this paper we have designed hybrid dynamic chunk ensemble model (HDCEM) for the classification of multi-class insect-data stream for handling imbalance and concept drift issue. To deal with imbalance issue we have proposed effective split bagging algorithm which has achieved better performance on minority class recall and F-measure on arriving dynamic chunks of data from multi-class data stream. HDCEM model can adapt to abrupt and gradual drift because it has combined features of both online and chunk-based learning together. It has achieved average 78% minority class recall in abrupt insect data stream and 71% in gradual drift insect stream.
A Novel Algorithmic Similarity Measure for Collaborative Filtering: A Recommendation System Based on Rating Distances

Internet sources contain a vast amount of information about items that people desire to purchase. It is impossible to evaluate these resources and come to an informed decision. People need automated systems that evaluate previous information and propose item alternatives. Recommending items using a smart system, which is based on the previous user preferences, has growing importance since the available product data is exponentially growing. Additionally, it is difficult to find new and correct things that a user would like among this massive amount of data. To make accurate recommendations with a smart system, researchers and practitioners use collaborative filtering methods with similarity calculation based on user preferences. The crucial point in collaborative filtering is to find a valuable measure that resembles correct similarity between users. The current similarity metrics in the literature have some disadvantages in conducting accurate recommendations. To improve the recommendation performance, this study proposes a novel similarity measure that assesses the distance between the user’s ratings and the median score. Considering distance from the median score is essential since some users may prefer to rate close to the median rather than the extremes. Experiments were conducted with a famous collaborative filtering dataset. Results showed that proposed similarity measure demonstrated superior performance regarding the recommendation accuracy. Implications of our results for XYZ are discussed.
GREEDY LAYERBYLAYER LEARNING OF CONVOLUTIONAL NEURAL NETWORKS

Layer-by-layer training is an alternative end-to-end backpropagation approach for training deep convolutional neural networks. Layer-by-layer training on specific architectures can yield very competitive results. In the ImageNet database (www.imagenet. org), layer-by-layer trained networks can perform comparable to many modern end-to-end trained networks. This article compares the performance gap between the two training procedures over a wide range of network architectures and further analyzes the potential limitations of layer-by-layer training. The results show that layer-by-layer learning quickly saturates after a certain critical level due to overfitting of early levels in neural networks. Several approaches that have been used to solve this problem are discussed, and a methodology for improving layer-by-layer learning in various neural network architectures is discussed. Fundamentally, this research highlights the need to open up the black box that represents modern deep neural networks and explore the layer-by-layer interactions between intermediate hidden layers within deep networks through the lens of layer-by-layer learning.
Stabilizing a healthy spiritual environment in the family

The article deals with the problem of the formation and stabilization of a healthy spiritual environment in the family. Specific examples of the organization of a holistic pedagogical process in this direction based on the use of innovative approaches are considered. It also reveals the importance of the influence of the family on the emotional state, on the spiritual health of the child, offers advice that can be used not only by parents, but also by teachers.
BAYESIAN NEURON MODEL AND POSSIBILITIES OF ITS USE FOR INTELLIGENT PROCESSING OF MEASUREMENT RESULTS

In the article, the possibilities of using neural networks constructed on neurons with an activation function based on the Bayes' theorem for intelligent processing of measurement results are discussed. In the authoring Bayesian model of a neuron, the weight vector is used as a reference pattern, the input signals of the neuron are interpreted as evidence in favor of two alternative hypotheses: compliance and noncompliance with the condition of the neuron activation. The output signal of the neuron is formed on the basis of the posterior probability distribution of hypotheses calculated using the Bayes' rule. The ability of the Bayesian neuron to recognize fuzzy graphic images covered with a raster grid is shown. An illustrative example of processing the results of measuring the surface temperature of the mechanism in order to detect potential malfunctions in places of overheating is given.
Digital Transformation of Foreign Language Education in Modern Society in Terms of Key Changes and Development Prospects

Within the framework of this article, the authors considered the problems of the transformation of foreign language education due to the spread of digitalisation trends, which influenced the systems of traditional foreign language education, especially the requirements for training and the learning outcomes of future specialists. It is emphasised that digitalisation dictates the need to optimise the professionally-oriented training of students and requires a revision of the basic aspects of teaching foreign languages. The particular emphasis we placed on the specifics of the activities of teachers in the course of foreign language education and the formation of special competence. Attention is drawn to the essence of digitalisation in relation to foreign language education and to such aspects as solving professional problems in a foreign language, developing professional thinking, and mastering a foreign language professional discourse. The authors note that the current foreign language training, even at the university, pays insufficient attention to students’ creative potential activation and development. The paper considers the case study technology as an effective method that can be used in the framework of foreign language education at a university.
PERBANDINGAN MODEL REGRESI BINOMIAL NEGATIF BIVARIAT DENGAN MODEL GEOGRAPHICALLY WEIGHTED NEGATIVE BINOMIAL BIVARIAT REGRESSION (GWNBBR) PADA KASUS ANGKA KEMATIAN BAYI DAN KEMATIAN IBU DI JAWA TENGAH

Infant mortality (0-11 months) and maternal mortality (during pregnancy, childbirth, and postpartum) are significant indicators in determining the level of public health. Central Java Province which has 35 regencies/cities is included in the top five regions with the highest number of infant and maternal mortality in Indonesia. The data characteristics of the number of infants and maternal mortality are count data. Therefore, the Poisson Regression method can be used to analyze the factors that influence the number of infants and maternal mortality. In Poisson regression analysis, there must be a fulfilled assumption, called equidispersion. Frequently, the variance of count data is greater than the mean, which is known as the overdispersion. The research, binomial negative bivariate regression is used as a solutions to overcome the problem of overdispersion in poisson regression. This method produce a global model. In reality, the geographical, socio-cultural, and economic conditions of each region will be different. This illustrates the effect of spatial heterogeneity, so it needs to be developed into Geographically Weighted Negative Binomial Bivariate Regression (GWNBBR). The model of GWNBBR provides weighting based on the position or distance from one observation area to another. Significant variables for modeling infant mortality cases included the percentage of obstetric complications treated (X1), the percentage of infants who were exclusively breastfed (X3), and the percentage of poor people (X5). Significant variable for modeling maternal mortality cases is the percentage of poor people (X5). Based on the AIC value, GWNBBR model is better than binomial negatif bivariat regression model because it has a smaller AIC value.
Optimization of a Wireless Sensor-Based Tennis Motion Pattern Recognition System

With the rapid development of information technology in today’s era, the application of the Internet, big data, and smart bracelet information technology in the field of sports has enhanced the intelligence of sports and plays an important role in promoting sports performance. This paper focuses on the application of wireless sensors in the field of tennis, using research methods such as literature research, video analysis, comparative research, and mathematical statistics, to explore and analyze the application of wireless sensors in the field of tennis big data, tennis robotics, and the implementation of tennis teaching and training, to provide a theoretical basis for promoting the application of wireless sensors in the field of tennis and also for the broader application of wireless sensors in sports to provide a theoretical reference. For the problem of multiple scales of motion targets in action videos, two video action recognition methods based on high- and low-level feature fusion are proposed, which are the video action recognition methods based on top-down feature fusion and the video action recognition methods based on bottom-up feature fusion. The multipowered mobile anchor nodes are allowed to move along a prescribed route and broadcast multiple power signals, and then, the location of the unknown node is estimated using a four-ball intersection weight center-of-mass algorithm. Simulations show experimentally that the algorithm reduces the average localization error and requires fewer anchor nodes.
Modelling and Optimisation in the Design of Pipeline Network Systems Using Ant Colony Optimisation Algorithm (ACO)

Modelling and Optimisation in the Design of Pipeline Network Systems Using Ant Colony Optimisation Algorithm (ACO)
HUBUNGAN PENGGUNAAN SMARTPHONE DAN KESIAPAN BELAJAR DENGAN HASIL BELAJAR MATEMATIKA

Abstrak Masalah dalam penelitian ini adalah rendahnya hasil belajar matematika. Tujuan penelitian ini untuk mengetahui hubungan yang signifikan antara penggunaan smartphone dengan kesiapan belajar, penggunaan smartphone dengan hasil belajar matematika, kesiapan belajar dengan hasil belajar matematika serta penggunaan smartphone dan kesiapan belajar dengan hasil belajar matematika. Jenis penelitian ex-post facto korelasi. Populasi berjumlah 118 peserta didik dan sampel penelitian berjumlah 54 peserta didik. Instrumen pengumpul data berupa angket dengan skala likert, yang sebelumnya diuji validitas dan reliabilitasnya. Analisis data yang digunakan adalah korelasi product moment dan multiple correlation . Hasil penelitian menunjukkan terdapat hubungan yang signifikan antara penggunaan smartphone dan kesiapan belajar dengan hasil belajar matematika dengan koefisien korelasi sebesar 0,515 berada pada taraf “Cukup Kuat”. Kata kunci: hasil belajar matematika, penggunaan smartphone, kesiapan belajar Abstract The problem in this study was the low mathematics learning outcomes. The purpose of this study was to determine the significant relationship between use smartphone using with learning readiness, smartphone using with mathematics learning outcomes, learning readiness with mathematics learning outcomes and smartphone using and learning readiness with mathematics learning outcomes. The type of this research was ex-post facto correlation. The population was 118 students and the research sample was 54 students. The data collection instrument was a questionnaire with a scale l ikert, which had previously been tested for validity and reliability. The data analysis used the product moment and multiple correlation. The results showed that there were a significant relationship between use smartphone and learning readiness with mathematics learning outcomes with a correlation coefficient of 0.515 at the "Strong Enough" level. Keywords: mathematics learning outcomes, smartphone using, learning readiness
Influence of Sector-Specific Components of Growth on Economic Freedom: Evidence from Sub-Saharan Africa

Africa in general and precisely Sub-Saharan Africa (SSA) has been performing dismally in economic freedom determination parameters. This has substantially diminishes the probabilities of keeping up with other regions which have so far flourished in terms of sustainable economic and human development as highlighted through economic freedom index by the Heritage Foundation 2021. It is for this reason that this study purpose to investigate the influence of value added components of GDP on economic freedom. This is explored using a panel of 40 Sub-Saharan African (SSA) countries from 1995 to 2019. Using both conventional unit root and co-integration tests showed that all the series are stationary and co-integrated of order one I(1). Further estimations on the long-run relationship using dynamic panel econometric techniques key in accounting for panel data hiccups. Specifically, fixed effect and general method of moments which is adopted to discourse concerns of endogeneity and serial correlation commonly associated with panel data. Key significant results based on GMM indicate that both value added growth components of industry and service sectors positively and significantly influences economic freedom but the effect is negative regarding value added from agriculture sector. Inward FDI was equally found to positively influence for the overall score of economic freedom for SSA The practical implication is that for an increasing economic freedom, SSA economies or decision makers should gear for policies that improve industrial production by creating an enabling environment, encouraging the service sector through incentives and tax holidays, diversify agriculture and minimize wasteful FDI inflow. All these are critical in a bid to the realization of competitive economic freedom in SSA.
Agile Sof t ware Development of Clinical Healthcare Management Information System for Public Health

Organization should manage information just as like as it manages its other resources correctly to fully maximize the usefulness of information especially in the field of healthcare. The use of software model to create information systems made it possible. To support the healthcare of the community, the appearance of Rural Health Unit is much needed. This study will discuss the problems encountered by the health professionals and health workers of Rural Health Unit in the Province of Alaminos, Laguna on the existing manual processes of storing and retrieving of patients’ data that are mainly used in assessing the public health of the community. With this situation, the researchers developed a Clinical Healthcare Management Information System for public health. This paper will also focus on the development of the system using Agile model and evaluation adapted from ISO 25010 to test its effectiveness.
Quantum annealing learning search implementations

This paper presents the details and testing of two implementations (in C++ and Python) of the hybrid quantum-classical algorithm Quantum Annealing Learning Search (QALS) on a D-Wave quantum annealer. QALS was proposed in 2019 as a novel technique to solve general QUBO problems that cannot be directly represented into the hardware architecture of a D-Wave machine. Repeated calls to the quantum machine within a classical iterative structure and a related convergence proof originate a learning mechanism to find an encoding of a given problem into the quantum architecture. The present work considers the Number Partitioning Problem (NPP) and the Travelling Salesman Problem (TSP) for the testing of QALS. The results turn out to be quite unexpected, with QALS not being able to perform as well as the other considered methods, especially in NPP, where classical methods outperform quantum annealing in general. Nevertheless, looking at the TSP tests, QALS has fulfilled its primary goal, i.e., processing QUBO problems not directly mappable to the QPU topology.
Texture Management for Glossy Objects Using Tone Mapping

In this paper, we proposed a method for matching the color and glossiness of an object between different displays by using tone mapping. Since displays have their own characteristics, such as maximum luminance and gamma characteristics, the color and glossiness of an object when displayed differs from one display to another. The color can be corrected by conventional color matching methods, but the glossiness, which greatly changes the impression of an object, needs to be corrected. Our practical challenge was to use tone mapping to correct the high-luminance part, also referred to as the glossy part, which cannot be fully corrected by color matching. Therefore, we performed color matching and tone mapping using high dynamic range images, which can record a wider range of luminance information as input. In addition, we varied the parameters of the tone-mapping function and the threshold at which the function was applied to study the effect on the object's appearance. We conducted a subjective evaluation experiment using the series category method on glossy-corrected images generated by applying various functions to each display. As a result, we found that the differences in glossiness between displays could be corrected by selecting the optimal function for each display.
Approaches Applied by HR Services in Assessment of Critical Thinking

The article presents the analysis of role-playing by critical thinking as a selection criterion applied by HR services aiming to assess the employees and candidates for vacant positions. The article’s authors show facts proving the growing significance of the ability to think critically as demonstrated in the business and industrial relations system and outline scientific views on the content and attributes of critical thinking. The article undertakes an analysis of different stages and forms of critical thinking applied in a professional context. A thoroughly analysed example of an IT company illustrates the differences in requirements to different categories of employees whose jobs involve various degrees of critical thinking as a soft skill. There identified is a category of workers whose critical thinking ability is crucial to the company’s success. The article gives examples of tasks that can be used during job interviews or qualifying interviews to measure the critical thinking ability of job candidates or employees. Critical thinking is studied concerning the job responsibilities of employees and the suitability of employee performance for the goals and tasks of the organisation or company for which employees work.