Reviewerly/exHarmony huggingface dataset:
STUDENTSâ€™ PERCEPTION ON THE UTILIZATION OF ZOOM VIDEO CONFERENCING IN IMPROVING SPEAKING ABILITY AMIDST COVID-19 PANDEMIC

This research investigated about studentsâ€™ perception on the utilization of Zoom Video Conferencing in improving speaking ability in the midst of COVID-19 outbreak. These days, the conventional class were converted into distance learning to prevent the contagious outbreak COVID-19. Therefore, this situation influenced the teachers and students to utilize Zoom Video Conferencing as their learning media. Thus, this research applied Mix Methods Approach by using closed-ended questionnaire and open-ended questionnaire which is adopted and modified from Bawantiâ€™s study (2021). These questionnaires were distributed by Google Form through WhatsApp and Twitter to 103 junior high school and high school student in Jabodetabek area. As the result, it discovered that Zoom Video Conferencing can help the students to develop positive attitude and have a great impact for developing speaking skills. Students feel they never feel afraid to volunteer themselves to speaking English in the classroom. Zoom also facilitates students and teachers to have direct communication, discussion, and teaching and learning process with its features as face-to-face classroom owns.
Framework mekanisme tata kelola dan sumber daya manusia untuk efektifitas aliran informasi

This study develops a framework of governance mechanisms and human resource capabilities for the effective flow of information within the organization. This research is an exploratory research based on secondary data using a literature study methodology. The results of the synthesis show that the governance mechanism determines the success of information flow. The results also indicate the need for human resource capabilities to support governance and information sharing mechanisms. There are two types of governance mechanisms: formal and informal governance. Formal governance includes contracts, business processes, performance appraisal and information systems, and cross-functional teams. Meanwhile, informal governance includes trust, commitment, power and social interaction. Human resources with systems thinking, mastery of technology, and interpersonal skills are very valuable for sharing information. This study helps to understand the factors that affect the effectiveness of information flow.
Faktor-faktor yang mempengaruhi minat mahasiswa dalam berorganisasi di kampus STIE Pancasetia

This study aims to determine the partial and simultaneous influence, as well as the dominant influence of internal factors (X1) and external factors (X2) on student interest in organizing on the STIE Pancasetia campus (Y). This research is quantitative which intends to explain the causal relationship between variables through hypothesis testing. The population used in this study are active and less active students who follow the organization on the STIE Pancasetia campus. The number of members for the 2021/2022 period is 110 and the sample is 86 students. sample size using the Slovin formula. The results showed that the Internal Factor Variable (X1) had a significant effect on Organizational Interest (Y) at STIE Pancasetia Banjarmasin partially. External Factor Variables (X2) have a significant effect on Organizational Interest (Y) at STIE Pancasetia Banjarmasin partially, the influence of both Internal Factor variables (X1) and External Factors (X2), simultaneously (together) affect Organizational Interest (Y ) At STIE Pancasetia Banjarmasin. The results of the study stated that the variable that had the dominant influence on Interest in Organization was Internal Factor (X1), which means that Internal Factor (X1) had the strongest influence on Interest in Organization (Y) at STIE Pancasetia Banjarmasin. The variable with the most dominant influence on Interest in Organization (Y) at STIE Pancasetia Banjarmasin, because the partial r value of the Internal Factor variable (X1) is greater than the other variables.
Distance learning: the view of students and teachers

The purpose of the article is to study the technologies of distance learning and the attitude to this form of education of students and teachers (on the example of VP "MF KNUKiM" and VP " Mykolaiv Faculty of Management and Business of the KUC"). The methodological basis of the study. In the course of the research scientific methods of analysis, synthesis, generalization, method of questionnaires of students and teachers of VP "Mykolaiv branch of KNUKiM", VP "Mykolaiv faculty of management and business of KUC" were applied. Quantitative methods were used to process the results of the survey. The scientific novelty of the work is the generalization of knowledge about the possibility of introducing distance learning in the educational process of training in the field of knowledge "Culture and Art", in particular, the specialty "Information, Library and Archival Affairs"; outlining the main features of distance learning through the prism of the views of students and teachers, their readiness for self-study and self-improvement; a vision of prospects for the development of distance learning, etc. Conclusions. It has been proven that distance learning technologies create conditions for fruitful interaction between teachers and students as subjects of the information environment and promote the development of their competencies, including the ability to self-development and analytical thinking. The survey found that more than half of students have a positive attitude towards distance learning and the use of modern information technology to obtain information. The most popular were practical and lecture classes using multimedia technologies. Among the prospects of distance learning by students on the ranked list are selected manufacturability, flexibility, and modularity. The results of the survey proved that distance learning technologies, based on the principles of open learning, create a modern information educational environment that is attractive to student youth. Based on the study, it was determined that distance learning can be actively used in the system of blended learning for students of the information sphere, and in times of crisis - as an independent element of modern education.&#x0D; Key words: information and communication technologies, distance education, distance learning, students, teachers.
Stage design as a directing decision tool

The aim of the article is to identify the features of stage design as a tool for representing the director's vision of the play in historical retrospect and at the present stage. Research methodology. The system method was used (for the study of scenographic design as a holistic and developed system); functional-typological method (to clarify the functions of stage design in the context of the specifics of design and directing); historical and cultural method (to consider this issue in the development of stage design), etc. Scientific novelty. Stage design as a unique tool for representing the director's vision of production is studied; the peculiarities of the conceptual and material sequence of the process of creating a visual image of the play are analyzed (according to D. Payne); the influence of the New Stagecraft movement on the formation of the modern concept of stage design was revealed; the specifics of stage design in traditional and non-traditional space are considered. Conclusions. Over the centuries, the artistic solution of stage production has undergone many different transformations, according to a specific period of historical development of theatrical art, recreating the environment in detail, minimizing to virtually free of scenery and props stage space, representing innovative technologies and others. At the present stage, theatrical art in general and directing in particular, continues the search for a new form of production. Under the influence of intensification of integration processes, which technologically and informationally combine various means of communication and information, as well as in accordance with the development of a specific culture of creating and showing theatrical performances, an important part of stage design of the XXI century. became audiovisual media - television, cinema, video and multimedia. The study found that in the process of historical development of the theater, the focus of the set designer has shifted from the interpretation of the text on a given stage space to the deconstruction of the found space in a critical context. However, stage design remains a powerful expressive force in the work of the playwright and director, strengthening them as a visual imprint, organically integrated into the semantic universe of the play. The stage design of a theatrical performance is the result of logical, figurative thinking and intuitive feeling expressed through an idea or a central theme. The original organization of space, drama, functionality of scenery and costumes, multimedia, lighting solution embody in a plastic solution the idea of ​​the play, staged by the director. Remaining the most important figure in the theater, the director finds visual support in the scenographic rhetoric of forms, volumes and chromatics in the process of creating an ideal sphere, with a single homogeneous content.&#x0D; Key words: stage design, artist, director, performance, visual-symbolic interpretation, scenery.
Turbidity Reduction of Groundwater by Using Nanomagnetic Adsorbent Composite (NMAC): Process Optimization by 3k Factorial Design and Analysis

&lt;p&gt;The widespread use of alternative water sources in Kelantan encourages the development of cost-effective methods for the purification of water. A simple and straightforward adsorption process using a nanomagnetic adsorption composite (NMAC) was introduced in this study as a new adsorbent for the treatment of turbid polluted groundwater. The use of iron oxide nano-coated adsorbents (NMACs) showed a high porosity relative to commercial activated carbons (CACs). Analysis of X-ray diffraction analysis for NMAC is confirmed by a crystal framework for Fe2O3, Fe3O4, and FeO are cubic components. A 3k maximum factor configuration of four factors, i.e., adsorbent dosage (0.02, 0.04, and 0.06 g), agitation time (15, 30, and 60 min), rotation speed (150, 200, and 250 rpm) and adsorbent scale (&amp;lt; 45 μm and &amp;gt; 300 μm) were used. The turbidity removal capability of both NMAC and CAC was compared. The adequacy of the developed empirical model for the elimination of turbidity and maximum turbidity efficiency was determined by regression model analysis. The obtained results revealed regression values of NMAC (R2; 0.9903, R2 adj.; 0.9875, R2 pred; 0.9808) and CAC (R2; 0.9909, R2 adj.; 0.9981, R2 pred.; 0.9817). The analysis of variance and surface response methodology revealed that turbidity removal efficiency of NMAC is affected by the four factors investigated. Among the samples, 0.04 g NMAC (&amp;lt; 45 μm) agitated at 150 rpm for 48 min showed 98.76% maximum adsorption efficiency. The findings showed that NMAC is a strong adsorbent for use in the treatment of raw water.&lt;/p&gt;&#x0D;
Adaptive Motion Planning with Artificial Potential Fields Using a Prior Path

Motion planning in an autonomous agent is responsible for providing smooth, safe and efficient navigation. Many solutions for dealing this problem have been offered, one of which is, Artificial Potential Fields (APF). APF is a simple and computationally low cost method which keeps the robot away from the obstacles in environment. However, this approach suffers from trapping in local minima of potential function and then fails to produce motion plans. Furthermore, Oscillation in presence of obstacles or in narrow passages is another disadvantage of the method which makes it unqualified for many planning problems. In this paper we aim to resolve these deficiencies by a novel approach which employs a prior path between origin and goal configuration of the robot. Therefore, the planner guarantees to lead the robot to goal area while the inherent advantages of potential fields remain. For path planning stage, we intend to use randomized sampling methods such as Rapidly-exploring Random Trees (RRT) or its derivatives, however, any path planning approach can be utilized. We have also designed an optimization procedure for evolving the motion plans towards optimal solution. Then genetic algorithm is applied to find smoother, safer and shorter plans. In our experiments, we apply a simulated vehicle in Webots simulator to test and evaluate the motion planner. Our experiments showed our method to enjoy improving the performance and speed in comparison to basic approaches.
Tool Cutting Force Prediction Model Based on ALO-ELM Algorithm

Aiming at the problems of low learning efficiency, slow convergence speed, and low prediction accuracy of traditional data-driven model applied to tool cutting force prediction, a prediction method of tool cutting force based on ant lion optimizer (ALO) extreme learning machine (ELM) is proposed. ALO was used to improve the weights of input layer and hidden layer of ELM, so as to improve its prediction accuracy. The tool cutting force prediction models were established by using ALO-ELM, ELM, BP (backpropagation) neural network, and support vector machine, respectively. The experimental results show that the mean square error, mean absolute percentage error, and mean absolute error of ALO-ELM prediction model are 0.9911%, 0.0011%, and 1.0863%, respectively, which are far lower than the other three prediction models. ALO-ELM prediction model has stronger prediction accuracy and generalization ability, which can be effectively applied to the prediction of cutting force.
calculus: High Dimensional Numerical and Symbolic Calculus in R

The R package calculus implements C++ optimized functions for numerical and symbolic calculus, such as the Einstein summing convention, fast computation of the Levi-Civita symbol and generalized Kronecker delta, Taylor series expansion, multivariate Hermite polynomials, high-order derivatives, ordinary differential equations, differential operators and numerical integration in arbitrary orthogonal coordinate systems. The library applies numerical methods when working with R functions or symbolic programming when working with characters or expressions. The package handles multivariate numerical calculus in arbitrary dimensions and coordinates and implements the symbolic counterpart of the numerical methods whenever possible, without depending on external computer algebra systems. Except for Rcpp, the package has no strict dependencies in order to provide a stable self-contained toolbox that invites re-use.
Quantum Algorithms based on the Block-Encoding Framework for Matrix Functions by Contour Integrals

The matrix functions can be defined by Cauchy's integral formula and can be approximated by the linear combination of inverses of shifted matrices using a quadrature formula. In this paper, we show a concrete construction of a framework to implement the linear combination of the inverses on quantum computers and propose a quantum algorithm for matrix functions based on the framework. Compared with the previous study [S. Takahira, A. Ohashi, T. Sogabe, and T.S. Usuda, Quant. Inf. Comput., 20, 1&2, 14--36, (Feb. 2020)] that proposed a quantum algorithm to compute a quantum state for the matrix function based on the circular contour centered at the origin, the quantum algorithm in the present paper can be applied to a more general contour. Moreover, the algorithm is described by the block-encoding framework. Similarly to the previous study, the algorithm can be applied even if the input matrix is not a Hermitian or normal matrix.
A Doxastic Characterisation of Autonomous Decisive Systems

A highly autonomous system (HAS) has to assess the situation it is in and derive beliefs, based on which, it decides what to do next. The beliefs are not solely based on the observations the HAS has made so far, but also on general insights about the world, in which the HAS operates. These insights have either been built in the HAS during design or are provided by trusted sources during its mission. Although its beliefs may be imprecise and might bear flaws, the HAS will have to extrapolate the possible futures in order to evaluate the consequences of its actions and then take its decisions autonomously. In this paper, we formalize an autonomous decisive system as a system that always chooses actions that it currently believes are the best. We show that it can be checked whether an autonomous decisive system can be built given an application domain, the dynamically changing knowledge base and a list of LTL mission goals. We moreover can synthesize a belief formation for an autonomous decisive system. For the formal characterization, we use a doxastic framework for safety-critical HASs where the belief formation supports the HAS's extrapolation.
Cold start and Data Sparsity Problems in Recommender System: A Concise Review

An enormous amount of data available on the e-commerce sites are of different forms as ratings, reviews, opinions, remarks, feedback, and comments about any item, and it is difficult for the system to search the user interest and predict the user preference. The recommender system (RS) came into existence and supports both customers and providers in their decision-making process. Nowadays, recommender systems are suffering from various problems such as data sparsity, cold start, scalability, synonymy, gray sheep, and data imbalance. One of the major problems to be considered for better recommendation is data sparsity. Cross-domain recommendation (CDR) is one way to address data sparsity problems, cold start issues, etc. In the most traditional system, cross-domain analysis is used to understand the feedback matrices by transferring hidden information and imposing dependencies across the domains. There is no vast comparison of existing research in CDR. This paper defines the problem, related and existing work on CDR for data sparsity and cold start, comparative survey to classify and analyze the revised work.
Performance Comparison of Machine Learning and Deep Learning Algorithms in Detecting Online Hate Speech

The main objective of this research is to analyze and compare the performance of machine learning (ML) and deep learning (DL) algorithms in detecting online hate speech. Therefore, Support Vector Machine (SVM), Random Forest (RF), Decision Tree (DT), Logistic Regression (LR), Convolution Neural Network (CNN), Recurrent Neural Network_Long Short-Term Memory (RNN_LSTM), BERT (Bidirectional Encoder Representations from Transformers), and Distil BERT algorithms have been explored and analyzed in this research. This research has applied the dataset on hate speech which was developed by Andry Samoshyn which is publicly available in Kaggle. ML algorithms and DL algorithms have got good scores in accuracy. In ML, SVM, RF, and LR have got top accuracy values. In DL algorithms, RNN_LSTM, Distil BERT, and BERT have performed well in accuracy. Based on F-measurement, DL classifiers have outperformed ML algorithms. Distil BERT has obtained the highest F-measurement scores. When we compare the overall performances, DL is performed well rather than ML in detecting hate speech. Especially transformer-based models of DL are more efficient than other DL and ML algorithms.
Vernacular biotechnologies

“Biotechnology” is defined by the reputed journal Nature Biotech as “[the] technology/methodology of relevance to the biological, biomedical, agricultural and environmental sciences”. Most often, what are defined as biotechnologies are based on the utilisation of cellular or molecular mechanisms for industrial applications, i.e., specific to the recent developments of Western science and livelihoods defined in the capitalist context. However, societies have been using their understanding of biological organisms and systems (biotechnology) to meet various hierarchies of needs (livelihoods) long before western scientists have shaped the understanding of molecular mechanisms. This question invites a wide range of research contributions in which we identify, evaluate and speculate on “what are we missing” in the (western) mainstream definition of biotechnology and design? We invite contributions in “vernacular biotechnologies” that challenge the paradigm that biotechnology and design is a modern discipline practiced by engineers in a laboratory. Vernacular biotechnologies can be common objects that are designed to interface with a living component of everyday life or the environment, and can include work shaped by traditional ecological knowledge (TEK), and/or performed by persons who do not identify as engineers, and/or taking place in non-lab locations such as the kitchen or the field. We also invite critiques of colonial practices in biotechnologies such as biomining or synthetic biology, and their applications.
Comprehensive support of professional adaptation of young teachers for a successful career start

Comprehensive support of young teachers to work in educational institutions during the period of professional adaptation involves a practical course of support for young teachers at the first stages of work. Within the framework of this course, teachers receive psychological, professional, methodological and economic assistance.&#x0D; The article discusses these areas in detail, describes the identified difficulties faced by teachers at the initial stage of work, and ways to solve these difficulties and problems.&#x0D; So, due to lack of experience, young teachers need professional and methodological assistance.&#x0D; The article discusses the difference between the terms "Emotional burnout" and "Overwork". Young teachers often face not only emotional burnout, but also other psychological difficulties.&#x0D; Economic assistance as one of the sections of the course of comprehensive support for young teachers during the period of professional adaptation to work in educational institutions could help solve the economic problems of teachers.
Real Time Speech Recognition in 1-Dimensional Using Convolution Neural Network

Abstract: Automatic voice recognition is a hot topic in artificial intelligence and machine learning, with the goal of creating robots that can communicate with humans through speech. Speech is an information-dense communication that includes both linguistic and paralinguistic information. Emotion is a prime example of paralinguistic information that is partially communicated through speech. Developing machines that can grasp non-linguistic information like emotion simplifies humanmachine communication by making it more natural and straightforward. The effectiveness of convolutional neural networks in recognizing speech has been examined in this study.. The input characteristics of the networks were wide-band spectrograms of voice samples. The networks were trained using voice signals produced by actors while acting out a given mood. Our models were trained and evaluated using English-language speech datasets. Two degrees of augmentations were applied to the training data in each database. To regularize the networks, the dropout approach was used. Our findings revealed that the genderagnostic, language-agnostic CNN models attained state-of-the-art accuracy, beat previously published results in the literature, and matched or even surpassed human performance on benchmark databases. Future research should look at the deep learning models' capacity to recognize speech emotion using real-world speech signals.