Reviewerly/exHarmony huggingface dataset:
School as an educational context for the development of students' social competence

The paper discusses the possibilities of developing the social competence of students at school using the method of theoretical analysis. The school is expected to adapt its way of working with students to new needs, in order to develop certain segments from a number of individual and social abilities as a capacity for social success - social competence. The school, with its educational mission, within which the role of teachers is crucial, encourages social competences through: acquiring and expanding students' social knowledge and understanding of social reality; drawing students' attention to other people's feelings and interests; encouraging alternative interpretations of other people's behaviour; providing students with assistance in active participation in discussions; assisting students in discovering common features; supporting communication between students (fostering verbal and nonverbal communication); encouraging the constructive cooperation among students; strengthening empathy and strengthening altruism).
Improving image deblurring

In this paper, we present a new model to improve image deblurring for the Helsinki Deblur Challenge, promoted by the Finnish Inverse Problems Society in the year of 2021. The challenge consisted in deblurring photographs of random strings of text with varying levels of blur caused by misfocusing the camera. This problem is usually referred to in the literature as out-of-focus deblur. A set of blurred and sharp images was available and also images of dots and other technical targets (horizontal and vertical lines) with the same camera settings. From the observation that the convolution of the sharp images with a uniform disk, which is commonly used as the point spread function (PSF) for the out-of-focus deblur problem, resulted in a image different from the observed blurred images, we observed a pattern that could be modeled as a contrast map. By multiplying this map to the observed images it was possible to significantly improve the image deblurring algorithms, specially for high levels of blur. This map was obtained from the blurred and sharp images that were available. Also, we propose a new deblurring function to be used with the fixed point Regularization by Denoise (RED) algorithm and the results were compared with the Least Absolute Shrinkage and Selection Operator (LASSO) algorithm.
Multimodal approach for fall detection based on support vector machine

Falls commonly occur for elderly citizens, which may lead to severe injuries. Therefore, Fall Detection (FD) for elderly people is one of the most critical health-care applications as it allows timely medical intervention. This paper proposes an intelligent FD system with a low false alarm rate. The FD is done based on depth maps and accelerometer data. The system utilized publicly available datasets University of Rzeszow Fall Detection Dataset (URFD). The URFD includes sequences of 40 ADL and 30 falls. The initial features are extracted from the Kinects camera. These features can be extracted by segmenting the foreground from the background. This operation can be performed by subtracting the current frame from the background frame to detect the difference region. The other features are extracted from the accelerometer by calculating the total acceleration. This work employed a support vector machine (SVM) classifier to distinguish the fall from Activities Daily Living (ADL). The experiment results show that the system achieves accuracy, precision, recall, and time. Where the accuracy is obtained is 99.96 with 0.282 second execution time.
Pengaruh Pembelajaran Berbasis Google Classroom Terhadap Hasil Belajar PJOK

The development of information technology and multimedia is so rapid that we are not ready to make full use of it. Learning models need to be well designed so that the student's learning experience is memorable and can achieve learning. The learning model is also important because it is used by teachers as a guide in planning and implementing teaching and learning activities. The COVID-19 pandemic has made preventive prevention services closed by closing schools that are in the Covid-19 red zone. One way teachers can continue to provide learning to students is online or online. However, the implementation of the online learning process has several obstacles. In addition, problems that are often encountered in learning physical education, sports and health (PJOK) in schools are the low interest and learning activities of students so that student learning outcomes are less than optimal. To overcome learning obstacles during the COVID-19 pandemic, Google Classroom-based bold learning media is used so that student learning outcomes can increase. This study uses an experimental method with an experimental class and a control class, with the results of student learning outcomes using google classroom higher than students who do not use google classroom.
The Nexus between Creative Leadership, Job Satisfaction, Organizational Citizenship Behaviour, and Employee Performance Moderation through Transparency

The aim of this study is to analyze the effect of creative leadership (CL) and job satisfaction (JS) on organizational citizenship behavior (OCB) and employee performance (EP) moderation through transparency.The study was conducted at PT. Pos Indonesia, using a sample of 216 employees, chosen randomly from branches spread across Bali.Data were collected using a questionnaire for all predetermined samples.The data collected were then analyzed using descriptive analysis, and using inferential analysis the hypotheses were used by PLS with smartPLS3.0.The results showed that CL and JS had no significant effect on EP but a significant effect on OCB.Furthermore, OCB had a positive and significant effect on EP.This study also illustrated that OCB fully mediated the effect of CL and JS on EP.Meanwhile, transparency did not significantly moderate the effect of CL on EP.Theoretically, this study confirms the social exchange theory, suggesting that there are always things exchanged between the organization and its employees.The practical implications of this study emphasize the important role of management in making changes when carrying out work in accordance with competitive industry conditions.
Refining Word Embeddings with Sentiment Information for Sentiment Analysis

Natural Language Processing problems generally require the use of pre-trained distributed word representations to be solved with deep learning models. However, distributed representations usually rely on contextual information which prevents them from learning all the important word characteristics. The task of sentiment analysis suffers from such a problem because sentiment information is ignored during the process of learning word embeddings. The performance of sentiment analysis can be affected since two words with similar vectors may have opposite sentiment orientations. The present paper introduces a novel model called Continuous Sentiment Contextualized Vectors (CSCV) to address this problem. The proposed model can learn word sentiment embedding using its surrounding context words. It uses Continuous Bag-of-Words (CBOW) model to deal with the context and sentiment lexicons to identify sentiment. Existing pre-trained vectors are combined then with the obtained sentiment vectors using Principal component analysis (PCA) to enhance their quality. The experiments show that: (1) CSCV vectors can be used to enhance any pre-trained word vectors; (2) The result vectors strongly alleviate the problem of similar words with opposite polarities; (3) The performance of sentiment classification is improved by applying this approach.
EMOTIONAL AND ARTISTIC ENVIRONMENT OF UNIVERSITY EDUCATION - A RESOURCE OF QUALITY TRAINING OF FUTURE TEACHERS

This study was conducted to define and outline the main theoretical characteristics of the concepts of "quality of education", "emotional and artistic environment", "professional training of future teachers for successful professional activities in higher education institutions." The authors defined the emotional and artistic environment as: a system of conditions that determine the purpose and objectives, planning, functioning and development of learning, the mechanism of subject-subject interaction, emotional and aesthetic relations in the system "teacher - students", which has a positive impact on the quality of training of future teachers for professional activities. Emotional and artistic environment of the educational process provides the development of personality of the future teacher, his abilities and abilities, individual style and professional position, means, ways of mastering cultural values and interaction to enter the world of spirituality, music, art, creative experience in teaching. activities. The emotional and artistic environment operates with a set of tools by which students evaluate the mechanism of organization and construction of educational activities on the basis of aesthetics, art and science; provide "transfer" of objectively existing values in the field of significant phenomena for future teachers, deepening and expanding existing professional values, intensification of thought processes and reflective position of students. Identified and justified conditions: updating the content of the humanities; emotional and artistic orientation of their content; modeling of event-role situations when the results of the student's activity coincide with his expectations; creating an emotionally favorable climate in the educational process; inclusion of participants in the educational process in various types of artistic and creative activities ensure the productivity of the educational environment in the formation of emotional and artistic image of the future teacher, his readiness for artistic and creative activities through a system of educational and cognitive tasks. cinema, music, which serve as the basis for the visualization of information and the experience of artistic creativity gained by students.
AI Design Lessons for Social Modeling at Scale

City of Gangsters is a commercial strategy game in which the player is principally challenged by navigating a complex and large-scale social network, in which every action resonates through the network and holds associated risks and rewards. Our procedurally-generated city results in a large social network with randomized and non-prescriptive configurations. Gameplay is oriented around social reciprocity and engaging in the same via an understanding of a concise set of social norms. Addressing these problems in a video game required a close unity between AI design and game design. We present four key AI design and implementation lessons learned in developing and shipping this game: the paramount need to make social actions and their consequences legible, the need for reversible actions, the need for modeled social norms to comprise a succinct set, and the need for individuals to be fungible with one another vis-a-vis social actions. We conclude with a description of the design affordances of this approach.
Validation of a Limit Ellipsis Controller for Rescue Drones

In recent years, more and more robotic systems have been supporting rescue forces in their missions. This paper presents the control algorithm and its application of an unmanned areal vehicle (UAV), which can support emergency personnel in their work. An adaption of the so-called Limit Ellipsis Controller (LEC) for indoor UAV is proposed. This adaptation enables the LEC to be used in semi-structured environments with static and dynamic obstacles. The main benefit of the LEC is that it can prevent deadlocks caused by other methods in complex environments. Furthermore, the LEC function is implemented on an experimental UAV system and tested in various environments. The proposed technical system enables exploration of a building by a semi-autonomous UAV, saving valuable rescue time. The UAV can fly into the building and explore the interior without collision. The results show that the proposed controller can adequately avoid local minima, guide the UAV to the desired target, and provide essential information for the rescue team in real demonstration scenarios.
Development of College Student Analytical Thinking Skills Through Evaluation Learning with Flip Book Assisted E-Books

The purpose of this study was to compare college student analytical thinking skills in evaluation learning with and without flipbook-assisted e-books. The research method used is quasi-experimental with a nonequivalent control group research form. The sample in this study were fourth-semester college students. The result of the research is that the college student analytical thinking ability after being given a mathematics learning evaluation course with and without an e-book assisted by a flipbook is equally good. This study carries out the application of learning mathematics learning evaluation courses with e-books assisted by flipbooks as an effort to develop students' analytical thinking skills which are indispensable in solving problems in these subjects where so far no one has conducted research in this field. The implications of the research are by applying the learning of mathematics learning evaluation courses with e-books with the help of flipbooks to the maximum extent that they can develop college student analytical thinking skills.Tujuan dalam penelitian ini adalah untuk membandingkan kemampuan berpikir analitis mahasiswa dalam pembelajaran evaluasi dengan dan tanpa e-book berbantuan flipbook. Metode penelitian yang digunakan adalah quasi experimental dengan bentuk penelitian nonequivalent control group. Sampel dalam penelitian ini adalah mahasiswa semester IV. Hasil penelitian yaitu kemampuan berpikir analitis mahasiswa sesudah diberikan mata kuliah evaluasi pembelajaran matematika dengan dan tanpa e-book berbantuan flipbook sama baiknya. Penelitian ini mengusung penerapan pembelajaran mata kuliah evaluasi pembelajaran matematika dengan e-book berbantuan flipbook sebagai upaya dalam mengembangkan kemampuan berpikir analitis mahasiswa yang sangat diperlukan dalam menyelesaikan permasalahan di mata kuliah tersebut dimana selama ini belum ada yang melakukan penelitian di bidang tersebut. Adapun implikasi dalam penelitian yaitu dengan melakukan penerapan pembelajaran mata kuliah evaluasi pembelajaran matematika dengan e-book berbantuan flipbook secara maksimal dapat mengembangkan kemampuan berpikir analitis mahasiswa.
Refocus attention span networks for handwriting line recognition

Recurrent neural networks have achieved outstanding recognition performance for handwriting identification despite the enormous variety observed across diverse handwriting structures and poor-quality scanned documents. We initially proposed a BiLSTM baseline model with a sequential architecture well-suited for modeling text lines due to its ability to learn probability distributions over character or word sequences. However, employing such recurrent paradigms prevents parallelization and suffers from vanishing gradients for long sequences during training. To alleviate these limitations, we propose four significant contributions to this work. First, we devised an end-to-end model composed of a split-attention CNN-backbone that serves as a feature extraction method and a self-attention Transformer encoder–decoder that serves as a transcriber method to recognize handwriting manuscripts. The multi-head self-attention layers in an encoder–decoder transformer-based enhance the model’s ability to tackle handwriting recognition and learn the linguistic dependencies of character sequences. Second, we conduct various studies on transfer learning (TL) from large datasets to a small database, determining which model layers require fine-tuning. Third, we attained an efficient paradigm by combining different strategies of TL with data augmentation (DA). Finally, since the robustness of the proposed model is lexicon-free and can recognize sentences not presented in the training phase, the model is only trained on a few labeled examples with no extra cost of generating and training on synthetic datasets. We recorded comparable and outperformed Character and Word Error Rates CER/WER on four benchmark datasets to the most recent (SOTA) models.
Generation of professional competencies of advertisers

Introduction. The advertising and information space is impossible without communication processes, in particular data exchange, the purpose of which is to ensure the understanding of information created, transmitted and received by people.&#x0D; Problem. The formation of communication processes does not take place without specialists capable of working in the media industry in conditions of advanced computerization.&#x0D; The aim of the work is to determine the features of the formation of communication competence; the presentation of approaches and recommendations for improving the methodology of training advertising specialists and the results of its approval.&#x0D; Methods. The classification and analytical method was used; questionnaire surveys, graphic and structural analysis, logical generalization.&#x0D; Results. One of the general competencies of the specialization «Advertising and public relations» is the acquisition of skills in the use of information and communication technologies. The purpose of using software products is to: provide students with tools for professional work; intensify the task performance process; stimulate the development of creative abilities; formation of critical thinking regarding the analysis of media products. In the conditions of a pandemic and martial law, classes take place via Zoom, using the Viber and Telegram applications, e‑mail. Among the problems there are: high cost of licensed programs; selection of software products suitable for use as a learning tool; professional and pedagogical qualification of teachers.&#x0D; Conclusions. Education with the use of the latest technologies acts today as a component of student training in accordance with the social orders of our time. This approach forms a new «computer» intelligence, including in the field of media product creation.
Learning to play an imperfect information card game using reinforcement learning

Artificial intelligence and machine learning are widely popular in many areas.One of the most popular ones is gaming.Games are perfect testbeds for machine learning and artificial intelligence with various scenarios and types.This study aims to develop a self-learning intelligent agent to play the Hearts game.Hearts is one of the most popular trick-taking card games around the world.It is an imperfect information card game.In addition to having a huge state space, Hearts offers many extra challenges due to its nature.In order to ease the development process, the agent developed in the scope of this study was divided into subagents such that each subagent was assigned a part of the game.The experiment results reveal that the developed agent can compete against some rule based Hearts agents and human Hearts players.
Research on the Integration and Innovation of Chinese Traditional Culture and College English Teaching

Language is the most important tool for human communication and communication, as well as the main carrier of culture. It can not only record and preserve the history of human civilization, but also promote the progress and development of social civilization. With the deepening development of economic globalization, my country and The world is becoming more and more connected, and exchanges and cooperation are increasingly strengthened. In this international context, our country pays more attention to foreign exchanges in English. Therefore, the English courses for Chinese college students should not only highlight the content of Western culture, but also show the beauty of traditional Chinese culture, so that students can fully learn and use the local language and spread Chinese culture. speakers and representatives. This paper analyzes the current situation of Chinese traditional culture in college courses in my country and proposes how to better integrate Chinese traditional culture and college English teaching for innovative development.
E-Learning Service Quality During COVID-19 Pandemic from Postgraduate Students’ Perspective in Jordan

The study aimed to define E- Learning Service Quality from Postgraduate Students Perspective in Jordan during COVID-19 pandemic. To achieve the study purpose, the researcher used the descriptive methodology survey. The study instrument was built and it contained three domains and was applied on the study sample which consisted of (214) from Postgraduate Students (male &amp;female). The study results indicated that the E- Learning Service Quality from Postgraduate Students Perspective in Jordan obtained an overall mean of (3.43) with a medium degree. However, on the secondary areas the level of student ranked first with mean of (3.68) which was high; in the second rank came the field of Student Environment with mean of (3.29) which was medium. In the last rank came the domain of educational course with an arithmetic mean of (3.27) which was medium. The results of the study indicated that there are no differences between the means of the E- Learning Service Quality from Postgraduate Students Perspective in Jordan referred to (Gender) for the student and educational course, but there are difference for educational environment refer to males. Also, the study indicated that there are no differences between the means of the E- Learning Service Quality from Postgraduate Students Perspective in Jordan refer to specialization. In the light of the study results, a number of recommendations were proposed.
Low Time-Complexity Chaotic Image Encryption Algorithm Based on Plaintext Information

Based on plaintext information, a dynamic chaotic color image encryption algorithm is proposed as a solution for the security problem in image data transmission, Comparatively, the existing one has the characteristics of high key acquisition complexity and low encryption speed. Firstly, normalize the RGB components of the images so as to obtain the dynamic key associated with the plaintext, which encrypts images with any shape by rearranging and combining pixels from the original image. Secondly, the parameter offset key is introduced as the initial parameter of the logistic map to generate a high-precision chaotic encryption sequence. The chaotic value sequence is stored for disordered pixels according to the image size, and enlarged and rounded to enhance the pixel value diffusion of the original image. Finally, RGB components are fully fused and uniformly distributed to form a completely encrypted image. According to the experimental results and security analysis, the proposed algorithm is effective against differential attacks, with low complexity, high efficiency, and faster encryption speed.
Mechanical engineering design optimization using reptile search algorithm

Optimization algorithms plays a vital role in mechanical engineering. In this paper we have demonstrated how the Reptile Search Algorithm (RSA) algorithm is able to solve classical engineering design problems. In the first part, the biological reference, as well as a detailed overview of the algorithm is given. Afterwards, the RSA algorithm and the potential to solve the machine engineering design class of problems is given. The source code for this algorithm was written using MATLAB R2020a software suite. The Reptile Search Algorithm (RSA) algorithm was used for optimization problems in the field of engineering design, such as: pressure vessel optimization, disk brake optimization and cantilever beam optimization. The statistical results and comparisons show that the RSA algorithm provides comparable results to other state-of-the-art algorithms used for this problem.