Reviewerly/exHarmony huggingface dataset:
Self-Education - A Stage Of Professional Growth

The article describes the work of the teacher in the field of education, as well as the organization of pedagogical activity in society on the basis of modern requirements.
An Order-Independent Algorithm for Learning Chain Graphs

LWF chain graphs combine directed acyclic graphs and undirected graphs. We propose a PC-like algorithm, called PC4LWF, that finds the structure of chain graphs under the faithfulness assumption to resolve the problem of scalability of the proposed algorithm by Studeny (1997). We prove that PC4LWF is order dependent, in the sense that the output can depend on the order in which the variables are given. This order dependence can be very pronounced in high-dimensional settings. We propose two modifications of the PC4LWF algorithm that remove part or all of this order dependence. Simulation results with different sample sizes, network sizes, and p-values demonstrate the competitive performance of the PC4LWF algorithms in comparison with the LCD algorithm proposed by Ma et al. (2008) in low-dimensional settings and improved performance (with regard to error measures) in high-dimensional settings.
Backtracking Restarts for Deep Reinforcement Learning

Manipulating the starting states of a Markov Decision Process to accelerate the learning of a deep reinforcement learning agent is an idea that has been proposed in several ways in the literature. Examples include starting from random states to improve exploration, taking random walks from desired goal states, and using performance-based metrics for starting states selection policy. In this paper, we explore the idea of exploiting the RL agent's trajectories generated during training for use as starting states. The main intuition behind this proposal is to focus the training of the RL agent to overcome its current weaknesses by practicing overcoming failure states by resetting the environment to a state in its recent past. We shall call the idea of starting from a fixed (or variable) number of steps back from recent terminal or failure states `backtracking restarts'. Our empirical findings show that this modification yields tangible speedups in the learning process.
INFLECTIONAL ANALYSIS OF MORPHOLOGICAL PROCESS IN TEACHING MORPHOSYNTAX THROUGH ONLINE LEARNING

Inflectional is the smallest part of morphosyntax but it becomes important because it is the basic knowledge that students have to comprehend in learning and producing correct sentence. To understand them, the students have to learn it through virtual learning in COVID-19 pandemic era which has changed the way of teaching and learning process especially in Morphosyntax. This research aimed to explore the types and the students’ difficulties in understanding inflectional process of morphology. This research used descriptive qualitative method to describe and to analyze the data. To collect the data, the researchers used two kinds of instruments namely pre-test, post-test, and interview. The population in this research consist of two classes from English Education Study Program at the fifth semester at IKIP Siliwangi.The result showed that the student mostly found the types of inflectional process namely plural form, 3rd singular person, past tense, progressive, comparative and superlative correctly while participle both in present and past tense form are mostly found incorrectly for they are having the higher function which are having similarity as verb progressive and as adjective at the same time. To understand the difference of the both function, the students are demanded to recognize well the structure of both. Keywords: Inflectional Process, Morphosyntax, Online Learning
IMPLEMENTING BILINGUAL STORY-TELLING PICTURE BOOK TO REINFORCE CHARACTER EDUCATION FOR PRE-SCHOOLERS IN ENGLISH EXTRACURRICULAR ACTIVITY

Reinforcing character education in the early childhood education or preschooler was deemed important nowadays; however, in order to do so it requires creative yet unique method to pique young pupils’ interest. Therefore, this research intends to elaborate the idea of reinforcing character education by implementing Bilingual Story-Telling Picture Book towards the pupils at one of the preschoolers located in Malang, East Java. This Bilingual Story-Telling Picture Book was composed specifically to teach the students about character education by integrating it with one of extracurricular activities in this school, the English language extracurricular activity. Therefore, this Bilingual Story-Telling Picture Book attempted to not only reinforcing the young pupils’ character education in story telling activity, but also improving their literacy and interest towards English language. Thus, the results indicate that the students were keen on learning English on the story-telling activity delivered by the teacher in charge whilst absorbing the value of character education delivered by the book.
Higher order functions and Brouwer’s thesis

Abstract Extending Martín Escardó’s effectful forcing technique, we give a new proof of a well-known result: Brouwer’s monotone bar theorem holds for any bar that can be realized by a functional of type (ℕ→ℕ)→ℕ in Gödel’s System T . Effectful forcing is an elementary alternative to standard sheaf-theoretic forcing arguments, using ideas from programming languages, including computational effects, monads, the algebra interpretation of call-by-name λ-calculus, and logical relations. Our argument proceeds by interpreting System T programs as well-founded dialogue trees whose nodes branch on a query to an oracle of type ℕ→ℕ, lifted to higher type along a call-by-name translation. To connect this interpretation to the bar theorem, we then show that Brouwer’s famous “mental constructions” of barhood constitute an invariant form of these dialogue trees in which queries to the oracle are made maximally and in order.
Attainability and Lower Semi-continuity of the Relative Entropy of Entanglement and Variations on the Theme

Abstract The relative entropy of entanglement $$E_R$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mi>E</mml:mi> <mml:mi>R</mml:mi> </mml:msub> </mml:math> is defined as the distance of a multipartite quantum state from the set of separable states as measured by the quantum relative entropy. We show that this optimisation is always achieved, i.e. any state admits a closest separable state, even in infinite dimensions; also, $$E_R$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mi>E</mml:mi> <mml:mi>R</mml:mi> </mml:msub> </mml:math> is everywhere lower semi-continuous. We use this to derive a dual variational expression for $$E_R$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mi>E</mml:mi> <mml:mi>R</mml:mi> </mml:msub> </mml:math> in terms of an external supremum instead of infimum. These results, which seem to have gone unnoticed so far, hold not only for the relative entropy of entanglement and its multipartite generalisations, but also for many other similar resource quantifiers, such as the relative entropy of non-Gaussianity, of non-classicality, of Wigner negativity—more generally, all relative entropy distances from the sets of states with non-negative $$\lambda $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>λ</mml:mi> </mml:math> -quasi-probability distribution. The crucial hypothesis underpinning all these applications is the weak*-closedness of the cone generated by free states, and for this reason, the techniques we develop involve a bouquet of classical results from functional analysis. We complement our analysis by giving explicit and asymptotically tight continuity estimates for $$E_R$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mi>E</mml:mi> <mml:mi>R</mml:mi> </mml:msub> </mml:math> and closely related quantities in the presence of an energy constraint.
The extent to which private schools in Shafa Badran area, Amman, implement their educational and legal obligations to apply online education in light of Corona pandemic: مدى تنفيذ المدارس الخاصة في منطقة شفا بدران بالعاصمة عمان لالتزاماتها التربوية والقانونية بتنفيذ التعليم عن بُعد في ظل كورونا

This study examines whether or not the outbreak of Corona Virus under the Jordanian Defense Law considers a legal impossibility "force majeure", and it determines the obligations of private schools in the online teaching with taking into account the satisfaction of students and their guardians. For this purpose, the descriptive survey approach has followed in this research by analyzing (34) questionnaires filled by the students' guardians. From the educational side, the survey has reached that (97%) of the guardians prefer the direct/traditional teaching while (3%) prefer the online method; (65%) believe that the online teaching applied by the private schools did not take care of the various needs of students; (70%) think that non-direct communication (face to face) between the teachers and students was one of the main obstacles in the online teaching; and (90%) see that WhatsApp was the only online way for teaching the courses. From the legal side, the study has reached that the obligations of private schools changed from traditional teaching to online teaching because of the legal impossibility (majeure force) and the applied defense law. By other words, Unlike traditional teaching, the obligations of private schools have changed to online teaching and contacting as a new way since the outbreak of coronavirus.
THE USE OF INTERACTIVE TECHNOLOGIES IN PREPARING FUTURE TEACHERS FOR TEACHING MATHEMATICS IN PRIMARY SCHOOL

The importance of the technological approach to the organization of the educational process was substantiated in the article. The authors of the article see its significance in the fact that it will allow the New Ukrainian school to implement the transition from the traditional passive model of educational and cognitive activities of schoolchildren to active. Both teachers and students should be the initiators and leaders of such changes. Therefore, authoritarian pedagogy must be replaced by the pedagogy of partnership. A comfortable educational environment, creative search can be provided in the process of subject-subject interaction. An important tool in its implementation is interactive technologies. The future teacher must be prepared for this type of activity. Revealing the peculiarities of training future teachers to use interactive technologies in the process of teaching mathematics in primary school, were substantiated the methodological approaches and conditions that were provide this process in the article. Conclusions are also were made and prospects for further research were determined.
Visual Analysis of Data Sales Using the Knime Platform Template - A Study at PT. Soho Global Health Alliance Division Cirebon

Industry 4.0 Era data is very important and is the starting point for managers to make decisions on the next step.Sales data generally have been presented and processed using Ms. Excel.This has limitations in visualizing, the purpose of this study is to bridge the limitations of the author by conducting a visual study of sales data analysis using the open-source KINIME Platform template.The results show that using KNIME Data visualization can be done easily and quickly (drag and drop node) using the template provided.The empirical advantage of this study is that it makes it easier for target managers to manage data, and big data is used as a basis for companies to plan everything.Theoretically adding knowledge about big data to marketing theory.Future research in The database can be used for terms of machine learning and artificial intelligence for marketing.
ANALISIS ISI INFOGRAFIS AKUN RESMI LINE KEMENTERIAN KOMUNIKASI DAN INFORMATIKA

This research is conducted to find the contents of information in the form of infographics on the official LINE account of KEMKOMINFO and to find whether the infographics made have fulfilled its function as a means of information repackaging. In general, researchers conduct research on academic implications and the object of the research is academics, but this research is different, the object of this research is official LINE account of KEMKOMINFO which is a government institution. This research uses descriptive qualitative methods with content analysis techniques without using respondents or informants as research objects. Content analysis for infographics on the official LINE KEMKOMINFO account was carried out for 6 months in October 2019 to March 2020. There are 9 information displays on the official LINE account of KEMKOMINFO: (1) latest news on the most popular issues in Indonesia; (2) information on specific themes; (3) information regarding the results of the activity conducted by government institutions; (4) information regarding KEMKOMINFO's clarification of news and issues circulating in public; (5) congratulory message at certain moments; (6) quiz about knowledge related to Indonesia; (7) information regarding procedures in the management of government-related matters; (8) the game of finding words based on clues; (9) word equivalents or translate. To facilitate the dissemination of information to the public, the Ministry of Communication and Information Technology (KEMKOMINFO) chose to use infographics because information in visual form is more attractive and easily understood by the general public, especially by the younger generation as readers.
A General Two-stage Multi-label Ranking Framework

In this paper we develop and study solutions for the multi-label ranking (MLR) problem. Briefly, the goal of multi-label ranking is not only to assign a set of relevant labels to a data instance but also to rank the labels according to their importance. To do so we propose a two-stage model that consists of: (1) a multi-label classification model that first selects an unordered set of labels for a data instance, and, (2) a label ordering model that orders the selected labels post-hoc in order of their importance. The advantage of such a model is that it can represent both the dependencies among labels, as well as, their importance. We evaluate the performance of our framework on both simulated and real-world datasets and show its improved performance compared to the existing multiple-label ranking solutions.
The Implementation of CSR on EFL Students’ Reading Class in Different Group Sizes

&lt;p&gt;&lt;strong&gt;Abstract:&lt;/strong&gt; This study addresses senior high school students’ reading comprehension on expository texts and its relation with the group sizes assigned to the students. It involves 133 eleventh grade students of SMAN Model Terpadu Bojonegoro. Quantive data were analyzed descriptively. The findings show that CSR affect the students’ reading comprehension significantly. Yet, it fails to reveal the effect of group sizes arrangement on the strategies applied towards the students reading comprehension. Consequently, the use of CSR in reading class can not be related to the group sizes assigned to the students. &lt;/p&gt;&lt;strong&gt;Abstrak:&lt;/strong&gt;&lt;em&gt; &lt;/em&gt;Penelitian ini bertujuan untuk mengungkap penguasaan pemahaman bacaan siswa SMA dan hubungannya dengan ukuran kelompok yang ditetapkan pada siswa. Penelitian ini melibatkan 133 siswa kelas XI SMAN Model Terpadu Bojonegoro. Data kuantitatif dianalisis secara deskriptif. Hasil penelitian menunjukkan bahwa penggunaan CSR memberikan pengaruh yang signifikan pada pemahaman bacaan siswa. Namun, penelitian ini gagal menunjukkan pengaruh ukuran pengaturan kelompok dalam strategi yang diterapkan terhadap pemahaman bacaan siswa. Karena itu, penggunaan CSR dalam pembelajaran membaca tidak bisa dihubungkan dengan ukuran kelompok yang ditugaskan kepada siswa.
Exploratory Data Analysis and Offence Prediction

Big data is a part of data science that pinpoint different ways to diagnosis, systematically withdraw facts from informational collections that are excessively enormous or complex to be managed by customary information handling application software. Big Data Analytics(BDA) is a specific tactic for breaking down and recognizing assorted examples, kindred, and patterns inside a massive volume in order. Big data analytics (BDA) is a meticulous approach to data analysing and recognising unique layers, connections, and trends ina gigantic volume of data. We apply BDA to illegitimate information collected in this paper, where preliminary data analysis was conducted for visual analysis and trend prediction. Following statistical analysis and visualisation, some incredibly interesting facts and patterns emerge from illegal data in INDIAN states i.e. (Uttar Pradesh, New Delhi, Goa). The prognostic results demonstrate that Kerasstateful LSTM execute enhanced than neural network models. These capable outcomes will allow police departments and law enforcement agencies to better understand crime problems and gain insights that will allow them to schedule activities, predict the likelihood of incidents, efficiently allocate resources, and optimise decision making.
Expanding the Reach of Structured EHR Data with Clinical Notes

Appropriate treatment decisions and end-of-life planning for patients with serious, life-limiting disease rely on accurate prognosis estimates. Many existing methods rely on structured electronic health record data which may limit generalizability across sites and restrict performance for patients with less documented history. Clinical notes may help to 'level the playing field'. We use History and Physical (H&amp;P) notes written within 16 hours of hospitalization to predict 60-day, all-cause mortality. We test several neural network approaches and observe little improvement over a CNN by adding bi-directional recurrence or convolutional attention. The CNN was prospectively validated against an existing system using structured data. The CNN reports higher discrimination (86.0% vs. 80.6%) and average precision (31.4% vs. 17.9%). The CNN identifies fewer patients at high-risk but 91% were under-estimated by the existing method (high-risk: 80 vs. 131 with overlap of 7). Patients of both groups do die in the following months suggesting the two approaches identify different patient phenotypes which supplement one another. The CNN model better adapts to a new hospital where many patients have little or no structured history incapacitating the existing system (high-risk: 27 vs. 1).
Intelligent Velocity Control of Mobile Robots Using Fuzzy and Supervised Machine Learning

This paper proposes an intelligent technique for velocity control of a wheeled mobile robot by simultaneously using a fuzzy controller and a supervised machine learning (SML) algorithm.The technique is suitable for flexible leader-follower formation control on straight paths where a follower robot maintains a safe but flexible distance from a leader robot.The fuzzy controller determines the ultimate distance of the follower with respect to the leader from the measurements of two ultrasonic sensors.The SML algorithm calculates an appropriate velocity for the follower based on the ultimate distance.Simulations showed the effectiveness of the proposed technique in adjusting the follower robot's velocity in order to maintain a flexible formation with the leader robot.
The Effect of Government Support for Fuel and Wheat on Economic Growth in Jordan: An Application of Dynamic Autoregressive-Distributed Lag

This study aims to investigate the effect of government support for Fuel and Wheat on economic growth in Jordan.This study employs the time series data from 1970-2019.Furthermore, this study applies the powerful unit root to test the stationarity of the variables.The unit root tests are Augmented Dickey-Fuller, Phillips-Perron, Saikonen and Lütkepohl and Zivot-Andrews.Moreover, this study also uses a recent cointegration test developed by Gregory and Hansen to investigate the long-run effect of government support for fuel and Wheat on economic growth.Similarly, this study uses dynamic autoregressive distributive lags.The results of unit root tests show that all the variables are stationary.Also, the results of the cointegration test reveal the long-run effect of government support for fuel and Wheat and trade openness on economic growth in Jordan.Similarly, the long-run and short-run estimates reveal the positive effects of both government support for fuel and Wheat and trade openness on economic growth, respectively.While the 2015 food crisis shows a negative effect on economic growth, conclusively, the policy will be contributed to Jordan to optimize the effects of government support for fuel and Wheat in economic growth.It is also recommended that if government support is utilized in the excess amount, the excessive development support becomes unproductive at the margin.Moreover, fiscal policy can be used as a macroeconomic instrument for economic stability.Intensive government support should be employed as an investment by allocating the funds to productive sectors.In addition, the government needs to make sure that increment in government support does not hurt the economy, particularly the economy of people within the country.
Development Of Professional Identity Of Future Educational Psychologists

The article discusses the problem of developing professional identity among future educational psychologists.Numerous studies of domestic and foreign authors illustrate a variety of theoretical concepts and approaches to the study of the professional identity of educational psychologists.However, there is no single, holistic, consistent concept of professional identity.This has instigated us to study the concept and the problem of professional identity of educational psychologists on the basis of psychological and pedagogical research, to analyze the process of developing the professional identity of educational psychologists in scientific literature.The conducted empirical research was aimed to test the assumptions that, firstly, the professional identity of undergraduates is determined by the specifics of target attitudes, value orientations, interests and motivations, and secondly, the professional identity of 1 st -2 nd year graduates is individual, random and uneven in its development.Thirdly, the components of professional identity differ substantially in first-and second-year graduates.The results of the longitudinal study generally confirm the suggested hypotheses.Professional identity is determined by the specifics of target attitudes, value-motivational orientations and motivations.The leading ones are job stability, service to mankind and management.The data obtained reflect the need of adolescence for social and personal security, a willingness to take responsibility and integrate the efforts of other people.The obtained research findings can be used in the activities of educational psychologists of the faculty in organizing support for professional identity development.