Reviewerly/exHarmony huggingface dataset:
PRINCIPLES OF FORMATION OF READYNESS FOR PROFESSIONAL-CREATIVE SELF-REALIZATION OF FUTURE TEACHERS OF FINE ARTS

The article examines the problem of forming readiness for professional and creative self-realization of future teachers of fine arts. In this context, the author highlights the basic principles that underlie this process: professional orientation, scientificity, optimization, emotional pedagogical process. The principle of professional orientation includes both the professional orientation of the individual to work and a specific profession and the professional orientation of general education and vocational training. The author provides not only professionally relevant material that is introduced into the content of education but also activities, which are aimed at mastering such mental operations, the analogues of which will be performed by students in teaching. According to the principle of scientificity, the content of higher education should correspond to scientific achievements in a particular field. Thus, future teachers of artists should receive only scientifically sound and reliable information, including facts, patterns, processes and phenomena, features of the formation and development of scientific discoveries. The principle of optimization presupposes high-quality implementation of the technology of formation of readiness for professional and creative self-realization of future teachers of fine arts, which leads to the achievement of the set goal. The main pedagogical actions to optimize the process of formation of the studied readiness of future teachers-artists are to specify the tasks; generalization; interdisciplinary coordination; selection of options based on their comparative assessment; differentiation and individualization of the educational process; humanization. The principle of emotionality of the pedagogical process will help to intensify the activities of both students and teachers, remove psychological barriers, stimulate cognitive processes, etc., which will significantly increase the efficiency of the process of formation of the studied education and will help future teachers of art to communicate effectively with students.&#x0D; Keywords: principles; readiness, professional and creative self-realization; artistic and pedagogical activity; professional training; future teachers of fine arts; fine arts; institution of higher education.
Design and Construction of Crop Suitability Prediction System Using Fuzzy Logic Classifier Method

The potential of land in Indonesia which is quite large and has not been used optimally is one of the problems. this study focused on developing fuzzy logic models to predict plants that are suitable for planting on agricultural land to enable the land use more optimal. In conducting this study, there were two stages of implementation, namely hardware design, and software design which included system workflow design using the Fuzzy Logic Classifier method where three input variables were used, namely soil pH, soil temperature, and humidity. The findings of this study are in the form of predictions consisting of eight outputs, namely Unfavorable Land, Spinach, Cayenne Pepper, Beans, Long Beans, Cucumber, Eggplant, and Tomatoo. The prediction results generated were directly displayed on the LCD of the instrument that has been designed.
WiDG: An Air Hand Gesture Recognition System Based on CSI and Deep Learning

Hand gesture recognition has become a hot research topic because it plays a crucial role in human-computer interaction applications. Channel State Information (CSI) is attracting more attention since it depicts more accurate communication links and can be leveraged to recognize target action in its coverage area. In this paper, we propose a device-free hand gesture recognition system based on CSI and deep learning models, called WiDG. This system can recognize handwritten digits from 0 to 9 in the air according to CSI changes caused by different hand movements. We build deep learning models to identify hand gestures. We conduct experiments in both non-through-the-wall and through-the-wall scenarios to evaluate system performance. The experimental results show that Convolutional Neural Networks (CNN) achieves 97.2% and 95.7% recognition accuracy in the non-through-the-wall scene and through-the-wall scene, respectively. In addition, we discuss the system parameters affecting recognition accuracy and compare system performance with WiNum. The results show that deep learning models can realize hand gesture recognition with a satisfactory performance using CSI.
Chi-square of Pseudorandom Number Generator of Normal Distribution in C++17

High quality pseudorandom number generators were needed in many software solutions throughout the history of programming. Nowadays, these generators play an even more significant role in software development. Generally, these generators bring a certain level of coincidence in some algorithms which need it. This work focuses on the statistical evaluation of one of the representatives of the generators using Pearson's Chi-square goodness of fit test. The generator of pseudorandom numbers under test is the specific implementation in the modern standard of the programming language of C++ (the standard of C++17). Results presented in this paper inform whether the numbers generated by the selected generator follow the desired probability distribution (normal).
THE INTERNET AS A DETERMINING FACTOR IN ECONOMIC CONVERGENCE ACROSS COUNTRIES

This paper examines whether the Internet is a determining factor in explaining economic growth and convergence across countries when it acts as a channel of information and knowledge diffusion. Literature has identified around 140 possible growth factors, therefore given the contradictory results obtained from previous empirical studies it is crucial we understand the actual role of the Internet. Using the conditional convergence theory and a Bayesian panel data model averaging method from a sample of 100 countries between 1994 and 2017, our results demonstrate that an increase in access to the Internet is a non-determinant factor in economic convergence, being its probability of inclusion in the true growth model conditioned by the regressors included in the estimates and the time span analysed.
IMPLEMENTASI ALGORITMA NAÏVE BAYES CLASSIFIER DAN SUPPORT VECTOR MACHINE PADA KLASIFIKASI SENTIMEN REVIEW LAYANAN TELEMEDICINE HALODOC

Halodoc is a telemedicine-based healthcare application that connects patients with health practitioners such as doctors, pharmacies, and laboratories. There are some comments from halodoc users, both positive and negative comments. This indicates the public's concern for the Halodoc application so it is necessary to analyze the sentiment or comments that appear on the Halodoc application service, especially during the COVID-19 pandemic in order for Halodoc application services to be better. The Naïve Bayes Classifier (NBC) and Support Vector Machine (SVM) algorithms are used to analyze the public sentiment of Halodoc's telemedicine service application users. The negative category sentiment classification result was 12.33%, while the positive category sentiment was 87.67% from 5,687 reviews which means that the positive review sentiment is more than the negative review sentiment. The accuracy performance of the Naive Bayes Classifier Algorithm resulted in an accuracy rate of 87.77% with an AUC value of 57.11% and a G-Mean of 40.08%, while svm algorithm with KERNEL RBF had an accuracy value of 86.1% with an AUC value of 60.149% and a G-Mean value of 49.311%. Based on the accuracy value of the model can be known SVM Kernel RBF model better than NBC on classifying the review of user sentiment of halodoc telemedicine service
Various English Literacy Activities in Bilingual Primary School

The results of Program of International Student Assessment show that the literacy skills of Indonesian students was in the low level. This study aims to investigate English literacy activities in elementary schools. This research is a qualitative research with a case study method. There were three English teachers who teach on the 1st, 2nd, and 3rd grade assigned as the subjects of this study. Data were collected using a questionnaire, interview guide, and checklist. The data collection procedure was carried out by distributing questionnaires, conducting interviews, and conducting classroom observations. Data were analyzed using data analysis methods from Cresswell which consisted of data organization, coding, description and developing themes, reporting findings, interpreting, and validating data. The results of this study indicate that there are eight literacy activities, namely Directed Reading-Thinking Activity, guided reading, reading with multimedia assistance, thinking aloud, reading aloud, dictating, recognizing letters, and writing. This study provides a description about English literacy activities in Primary School conducted by teachers. Therefore, a suggestion is directed to English teachers to teach literacy to students since the early age as literacy is an important basis for students’ future learning.
Understanding the usability issues in contact management of illiterate and semi-literate users

The effective utilization of a communication channel like calling a person involves two steps. The first step is storing the contact information of another user, and the second step is finding contact information to initiate a voice or text communication. However, the current smartphone interfaces for contact management are mainly textual; which leaves many emergent users at a severe disadvantage in using this most basic functionality to the fullest. Previous studies indicated that less-educated users adopt various coping strategies to store and identify contacts. However, all of these studies investigated the contact management issues of these users from a qualitative angle. Although qualitative or subjective investigations are very useful, they generally need to be augmented by a quantitative investigation for a comprehensive problem understanding. This work presents an exploratory study to identify the usability issues and coping strategies in contact management by emergent users; by using a mixture of qualitative and quantitative approaches. We identified coping strategies of the Pakistani population and the effectiveness of these strategies through a semi-structured qualitative study of 15 participants and a usability study of 9 participants, respectively. We then obtained logged data of 30 emergent and 30 traditional users, including contact-books and dual-channel (call and text messages) logs to infer a more detailed understanding; and to analyse the differences in the composition of contact-books of both user groups. The analysis of the log data confirmed problems that affect the emergent users’ communication behaviour due to the various difficulties they face in storing and searching contacts. Our findings revealed serious usability issues in current communication interfaces over smartphones. The emergent users were found to have smaller contact-books and preferred voice communication due to reading/writing difficulties. They also reported taking help from others for contact saving and text reading. The alternative contact management strategies adopted by our participants include: memorizing whole number or last few digits to recall important contacts; adding special character sequence with contact numbers for better recall; writing a contact from scratch rather than searching it in the phone-book; voice search; and use of recent call logs to redial a contact. The identified coping strategies of emergent users could aid the developers and designers to come up with solutions according to emergent users’ mental models and needs.
Putting software requirements under the microscope: automated extraction of their semantic elements

The relationships between software requirements work as the basis for several important software activities, such as change impact and developing cost analysis. Multiple types of relationships are mentioned in the RE literatures including normal (e.g., dependency) and abnormal ones (e.g., conflicts), and most of the existing work usually focus on the identification of one specific relationship. We collect and analyze the relations in the RE literatures, and find some common semantic elements of functional requirements are involved in the definition of multiple types of relations. Thus, to support automatically identifying diverse relationships, we propose our definition of the micro-level semantic constitution of functional requirement (M-FRDL), and one automatic approach for the element extraction, named by Micro-level Semantic elements Analyser of functional requirement (MISA). The experiments with three open requirement datasets show that our MISA can correctly identify about 94.93% elements of requirements on average.
TEACHERS’ STRATEGIES IN TEACHING READING COMPREHENSION

This research aimed to figure out the strategies used by the English teachers in teaching reading and how they applied the strategies. This research was designed as descriptive qualitative research. The research was conducted at Junior High School 09 Bengkulu City. Participants of the research were two English teachers who teach in second grade of that school. Each English teacher had eigh meetings that observed by the researcher. The instruments of the research were strategies checklist and interview. The instruments were used to figure out the strategies used and how the English teachers applied the strategies in teaching reading comprehension. The result of the data were analyzed and broken down into three stages; they were Data Reduction, Data Display, and Drawing Conclusion or Interpretation. The result showed that the teacher one used several strategies in teaching reading comprehension. The strategies were brainstorming, reading aloud, and asking for specific information. While the teacher two used nine strategies. They were encouraging the use of dictionaries, reading aloud, reread for checking comprehension, evaluating comprehension in particular tasks, and asking questions for specific information. Both teachers applied and combined the strategies divided into three stages of teaching reading comprehension. The stages were pre-reading stage, while reading stage, and post reading stage. The strategies applied were very effective in teaching reading comprehension in that school. It was proven by the students’ motivation, students’ attention, and teachers’ ease in teaching and learning process. Keywords: Reading Comprehension and Teachers’ Strategies.
Feature fusion-based collaborative learning for knowledge distillation

Deep neural networks have achieved a great success in a variety of applications, such as self-driving cars and intelligent robotics. Meanwhile, knowledge distillation has received increasing attention as an effective model compression technique for training very efficient deep models. The performance of the student network obtained through knowledge distillation heavily depends on whether the transfer of the teacher’s knowledge can effectively guide the student training. However, most existing knowledge distillation schemes require a large teacher network pre-trained on large-scale data sets, which can increase the difficulty of knowledge distillation in different applications. In this article, we propose a feature fusion-based collaborative learning for knowledge distillation. Specifically, during knowledge distillation, it enables networks to learn from each other using the feature/response-based knowledge in different network layers. We concatenate the features learned by the teacher and the student networks to obtain a more representative feature map for knowledge transfer. In addition, we also introduce a network regularization method to further improve the model performance by providing a positive knowledge during training. Experiments and ablation studies on two widely used data sets demonstrate that the proposed method, feature fusion-based collaborative learning, significantly outperforms recent state-of-the-art knowledge distillation methods.
Qubit decoherence and symmetry restoration through real-time instantons

A parametrically driven quantum oscillator, stabilized by a nonlinear dissipation, exhibits a spontaneous breaking of the parity symmetry. It results in the quantum bistability, corresponding to a Bloch sphere of dark states. This makes such a driven-dissipative system an attractive candidate for a qubit. The parity symmetry breaking is exact both on the classical level and within the quantum mechanical perturbation theory. Here, we show that nonperturbative quantum effects lead to the symmetry restoration and result in an exponentially small but finite qubit decoherence rate. Technically, the symmetry restoration is due to real-time instanton trajectories of the Keldysh path integral, which represents the Lindbladian evolution of the driven-dissipative oscillator.
INTRODUCTION TO THE PROBLEMATICS OF BULLYING, CYBERBULLYING AND CYBER-AGGRESSION - ANALYSIS OF SELECTED METHODS OF PREVENTION AND INTERVENTION

Information about the paper titled "INTRODUCTION TO THE PROBLEMATICS OF BULLYING, CYBERBULLYING AND CYBER-AGGRESSION - ANALYSIS OF SELECTED METHODS OF PREVENTION AND INTERVENTION" at IATED Digital Library
3D Spatial Positioning by Binocular Infrared Cameras

The calibration of binocular infrared camera is a key step to realize the positioning of infrared camera. The existing methods of binocular camera calibration are not suitable for infrared camera, so it is necessary to study the methods of binocular infrared camera calibration and positioning. In this paper, a calibration and positioning method of binocular infrared camera is proposed, and the infrared positioning of two kinds of objects is completed by using this method. Firstly, a special temperature calibration system is used to collect the images for binocular calibration, then the center point detection algorithm and Zhang’s calibration method are used to process the infrared calibration image to obtain the internal and external parameters of the binocular infrared camera. The calibration error is compared with that of binocular visible camera to prove the feasibility of the binocular infrared camera calibration. Secondly, according to the calibrated parameter matrix of the binocular infrared camera, symmetrical circle calibration object detection algorithm and coordinate transformation are carried out for the distortion correction images to achieve infrared positioning of different objects, and the positioning error is obtained. The results show that the calibration method of binocular infrared camera is feasible, and it has more functions than the traditional calibration method.
The Linear Pottery culture face vessel from the site Biskupice 18, southern Poland

This paper presents the stylistic analysis of a unique face vessel fragment, found at a recently excavated settlement of the Linear Pottery culture near Biskupice, located in the Carpathian foothill region in southern Poland. The evaluation is based on a multivariate analysis of the stylistic features of 130 human face vessels from 91 Central European Neolithic sites of the Linear Pottery culture and the Alföld Linear Pottery culture, and is conducted with the help of multiple correspondence analysis (MCA). The main objective of the research is to find the closest analogies of the Biskupice by tracking similarities between the manner of execution of the combination of facial elements and accompanying motifs appearing on the Biskupice vessel and on other depictions of the human face. This investigation also aims to make inferences about the chrono-cultural connections of the first agrarian societies in the area of the Carpathian foothills with other regions of the Linear Pottery world.
Medical Record Encryption Storage System Based on Internet of Things

The Internet of Things takes data as the center, and its core is data storage and management. With the emergence and rapid development of wireless communication technology, with the huge number of terminals in human society, massive data will be generated. Undoubtedly, data storage and management technology will attract much attention. In view of this, this paper proposes a data storage scheme based on the Internet of Things. This paper introduces the Internet of Things technology, designs it from the perspective of the massive data storage system of the Internet of Things, realizes the intelligent processing of data storage, and provides security guarantee for information services. By combing the business process management of doctors, nurses and patients, this paper constructs a medical record encryption management system, makes a comparative analysis before and after the system goes online, and carries out simulation experiments. The simulation results show that (1) the cost of paper is significantly reduced, and the related forms of medical records are more unified and standard, (2) medical record inquiry and reading are more convenient and controllable, and (3) the safety of medical records is well guaranteed. Except that the relevant doctors and nurses of patients can view the relevant medical records, and others have no authority to query and access them. Therefore, the encrypted medical record storage system based on Internet of Things technology can effectively solve the collection, statistics, and integration of patient treatment information, which can be summarized into a unified, shared, and interconnected electronic medical record management system to realize the collection of patient treatment information in the whole process.
Macroeconomic and Institutional Determinants of Capital Flight in Cameroon, Gabon and the Republic of Congo: A Comparative Analysis

Cameroon, Congo and Gabon are characterized by an impressive flight of capital. Meanwhile, the macroeconomic variables of these countries are unstable and there is a degradation of governance indicators. This study examines the relationship between capital flight and the evolution of macroeconomic and institutional indicators in these three countries. The objective of the study is to identify the macroeconomic and institutional determinants of capital flight for the period 1970-2015 in Cameroon, Gabon and the Republic of Congo. Time series technique is used for the analysis. Appropriate tests are performed to verify the robustness of the results. The models are estimated through Autoregressive Distributed Lag approach. For each of the three countries considered in this paper, the results reveal a stable long-run relationship between capital flight and macroeconomic and institutional variables. In addition, some macroeconomic and institutional variables positively and significantly influence capital flight in each of the three countries. Policy implications are country-specific. For Cameroon, entrepreneurs should reinvest the profits from other growth sectors of the economy to ensure its diversification. In addition, natural resource rent management should be more transparent to limit capital flight. Anti-corruption structures should have more extensive powers to pursue the perpetrators of corruption before the competent courts. The application of the provisions of the constitution relating to the declaration of the property of the leaders occupying high positions should come into force to limit any hint of embezzlement of public funds. Concerning the Republic of Congo, the debt must be deeply restructured to make it sustainable. Leaders of anti-corruption structures should have a degree of autonomy in carrying out their mandate. Deadlines for dealing with corruption cases should be defined with a view to speeding up the procedures for sanctions. For Gabon, the main macroeconomic recommendation concerns the restructuring of the capital of multinational companies operating in Gabon. The state and private operators should take stakes in these multinationals to benefit from part of the dividends that can be reinvested locally and limit capital flight. In terms of political governance, efforts must be made to ensure that the country has strong institutions for transparent elections.