Reviewerly/exHarmony huggingface dataset:
ANALISIS PROSES PERSEDIAAN BARANG PT VARIA SRI CENDANA DEPARTEMEN STORE DENGAN MENGGUNAKAN FUZZY LOGIC MAMDANI

Fuzzy logic is an appropriate way to solve problems that are difficult to define using mathematical models. This study focuses on analyzing the use of goods so that goods are always available when needed. The purpose of this study is to analyze how many items should be provided and how many items will be used. To optimize the inventory of goods, this research method is carried out by direct observation and collecting data on the use of goods in July 2019 to December 2019 and analyzes the use of goods using fuzzy logic with the Mamdani method so as to find out how much goods must be provided for the use of goods in the month January 2020.
The Digital Double of a Teacher as a Tool for Managing the Process of Forming Individual Tasks for Students

The article describes the issue of modeling the digital twin of a teacher in the context of the task of forming individual educational tasks for students. An approach is proposed that analyzes the patterns in the teacher's choice of the most priority topics and areas for each student based on the available data on his previous experience. The article deals with the search for patterns between the digital twins of teachers for the subsequent prediction of their choice of topics and sections of training materials for the individual work of students. As the basis for creating a dataset for the formation of digital twins of teachers, the methodology of decomposition of tasks by tags is used (tags are designation of typical tasks within the framework of tasks by students). The paper describes the relationship between the student's digital trace, the digital trace and the teacher's digital twin as a part of solving the problems of managing the process of forming individual tasks.
Optimized Auxiliary Particle Filters

Auxiliary particle filters (APFs) are a class of sequential Monte Carlo (SMC) methods for Bayesian inference in state-space models. In their original derivation, APFs operate in an extended state space using an auxiliary variable to improve inference. In this work, we propose optimized auxiliary particle filters, a framework where the traditional APF auxiliary variables are interpreted as weights in a importance sampling mixture proposal. Under this interpretation, we devise a mechanism for proposing the mixture weights that is inspired by recent advances in multiple and adaptive importance sampling. In particular, we propose to select the mixture weights by formulating a convex optimization problem, with the aim of approximating the filtering posterior at each timestep. Further, we propose a weighting scheme that generalizes previous results on the APF (Pitt et al. 2012), proving unbiasedness and consistency of our estimators. Our framework demonstrates significantly improved estimates on a range of metrics compared to state-of-the-art particle filters at similar computational complexity in challenging and widely used dynamical models.
Музыкальное мышление: операнды и операторы

It is watched the phenomena “Musical thinking” and analyzed its concept. It is formulated the definition and adjusted the structure of this phenomena.
Extremal steering assemblages

Nonlocal correlations between a fully characterized quantum system and an untrusted black box device are described by an assemblage of conditional quantum states. These assemblages form a convex set, whose extremal points are relevant in many operational contexts. We give necessary and sufficient conditions for an assemblage to be extremal using linear independence conditions and an algorithm to decompose a generic assemblage into extremal points. A matlab implementation of this algorithm is also provided.
An Artificial Neural Network Based Approach of Solar Radiation Estimation Using Location and Meteorological Details

This paper proposes a methodology to estimate monthly average global solar radiation using Artificial Neural Network. Due to abundancy, solar energy is at the cutting edge for a long time among other types of renewable energy. It has several applications in several fields. Solar energy devices completely depend on the amount of solar radiation that is to be received. So, optimization of solar energy is possible only when solar radiation is estimated well in advance. This is challenging since solar radiation is the location and seasonal-dependent. The current study addresses the issue of scarce meteorological stations which in turn limits the radiation measuring devices at the location of interest of the researchers. In this study, an ANN-based solar radiation estimation model is proposed using Levenberg–Marquardt training algorithm here. The study is performed on the six stations of Bihar, India. The Neural Fitting Tool (NF Tool) of MATLAB R2016a is used for simulation purposes. The data set is collected from the FAO, UN. The proposed model shows the R values of 0.9974, 0.97909, 0.90589, 0.9925, slope (m) values of 0.99, 1.0, 0.87 and 0.99, and intercept (c) values 0.0086, 0.021, 0.021 and 0.0066, for ‘training’, ‘validation’, ‘testing’, and ‘all’, respectively. The mean square error (MSE) is found to be 0.07727, 0.08092, and 0.08076 for ‘training’, ‘validation’, and ‘testing’, respectively.
Theorizing the role of technologies in the COVID-19 pandemic times

The COVID-19 pandemic has surfaced the fragility arising from often overlooked risks across a breadth of contexts, including the lack of coordination among public health institutions, disruption in supply-chains, the spread of misinformation, uncertainty in decision making, and the absence of real-time monitoring systems. For these reasons, many organizations and societies turn to digital tools to reduce the magnitude of disruption. The surge in the use of digital technologies in the face of the COVID-19 pandemic may emerge new opportunities and problems. Some view the current pandemic as an opportunity for organizations to thrive by accelerating digital transformation. Others voiced that the reckless use of technologies may make the situation even worse, generating unexpected challenges. The empirical insights from presenters will advance our understanding of whether and how the digital tools can address the challenges in the face of the COVID-19 crisis at various levels of analysis - individual, organizational and societal levels. Building Trust in Simulation Models: Lessons from the Study of Digital Modeling for COVID and Beyond Presenter: Paul Leonardi; UC Santa Barbara What does contact tracing really mean? The contestation process over the meaning of contact tracing Presenter: Semi Min; New York U. Presenter: Natalia Levina; New York U. Presenter: Hila Lifshitz-Assaf; New York U. Reducing the Uncertainty of Treating COVID-19 patients: Application of an AI-based Predictive Model Presenter: Batia Mishan Wiesenfeld; New York U. Presenter: Elisabeth Yang; Yale School of Management The Transformation Myth: Leading Your Organization Through Uncertain Times Presenter: Jerry Kane; Boston College
PENGARUH DISIPLIN BELAJAR SISWA TERHADAP PRESTASI BELAJAR PADA SISWA KELAS III SD NEGERI 040528 SUKADAME T.P. 2020/2021

The research objective was to determine the description of student learning discipline, the description of student learning achievement, and the significant influence of learning discipline on the learning achievement of third grade students SD Negeri 040528 Sukadame in the 2020/2021 learning year. This type of research is a quantitative study with a population of third grade students SD Negeri 040528 Sukadame and the sampling used was total sampling with a total of 17 students. The method used is descriptive analysis, using the t test formula. The average score of students is 78. The description of student learning achievement based on the average score of the semester report cards is 78, including the good category, and there is a significant influence between Student Discipline on Student Learning Achievement in class III SD Negeri 040528 Sukadame.
Implementasi Kurikulum 2013 Mata Pelajaran Bahasa Indonesia pada Teks Surat Pribadi dan Surat Dinas di Kelas VII SMP Negeri Lubuk Tua Kabupaten Musi Rawas

The purpose of this study was to describe the implementation of the 2013 curriculum for Indonesian subjects in the text of personal letters and official letters in class VII SMP Negeri Lubuk Tua, Musi Rawas Regency, especially in preparing learning implementation plans or RPP, implementation of learning, authentic assessment. The method used is descriptive method. The source of the data for this research is the Indonesian language teacher who teaches students in grade VII SMP Negeri Lubuk Tua. The data in this study were in the form of RPP document data, words, behavior, and learning implementation activities in learning the text of personal letters and official letters. Data collection techniques were carried out by interviewing, observing, and documenting. The data analysis technique was carried out in the following steps: 1) data reduction, namely by grouping the data in interviews, documentation, and observations; 2) data presentation is done by classifying and outlining the data of the Learning Implementation Plan, implementation of learning, authentic assessment; (3) data interpretation, evaluation and analysis are carried out according to the problem to draw conclusions. The results showed that teachers had understood the 2013 Curriculum with evidence that they had prepared the lesson plans well, had prepared personal texts and official letters according to the basic competencies achieved, carried out learning activities according to the lesson plans, and and in authentic assessment activities the teacher still focuses on applying attitude and knowledge assessment.
Gender Bias Hidden Behind Chinese Word Embeddings: The Case of Chinese Adjectives

Gender bias in word embeddings gradually becomes a vivid research field in recent years.Most studies in this field aim at measurement and debiasing methods with English as the target language.This paper investigates gender bias in static word embeddings from a unique perspective, Chinese adjectives.By training word representations with different models, the gender bias behind the vectors of adjectives is assessed.Through a comparison between the produced results and a human scored data set, we demonstrate how gender bias encoded in word embeddings differentiates from people's attitudes.
THE AUTOMATIC SYNTHESIS OF PETRI NETS BASED ON THE FUNCTIONING OF ARTIFICIAL NEURAL NETWORK

Context. The important task was solved during the scientific research related to the development of the methods for automatic synthesis of Petri nets while tuning up of the coordinating automatic control systems. The importance of development of these methods is due to the evolution of intelligent systems. These systems provide the automation of labor intensive processes in the particular case this is the tuning of the certain type of complex control systems. Objective. The purpose of the scientific work is to minimize the time and automation of process in tuning of the multilevel coordinating automatic control systems. Method. The principle of automatic synthesis of Petri nets and the implementation of certain algorithms for tuning complex control systems based on the functioning of an artificial neural network are proposed. The mathematical description of the method for changing the coefficients in neural connections of network in the synthesis of Petri nets is presented. Results. The experiments were conducted in the Matlab\Simulink 2012a environment. These experiments were bound to the joint functioning of an artificial neural network and Petri nets. The functioning of Petri nets was presented in the Matlab \ Simulink environment using Statflow diagrams. As a result of the experiments we have obtained the temporal characteristics of the functioning of artificial neural network providing the composition of Petri nets. The fundamental suitability of using artificial neural network to provide the automatic composition of Petri nets was determined on the basis of analysis of temporal characteristics. Conclusion. The problem linked to the development of system for the joint functioning of neural network and Petri nets for the formation of algorithms and sequential calculations was solved in this work. Thus the method of automatic synthesis of Petri nets and the method of developing of the certain algorithms based on the functioning of a neural network were further developed.
Research on College English Teaching Model of “Double Innovation” Education and English Education

Innovation and entrepreneurship have gradually become the most obvious feature of the development of the new era. The integration of innovation and entrepreneurship education and English education is a section that colleges and universities need to explore in English teaching. Innovation and entrepreneurship have changed various fields, and the integration with English education will become an important direction for future education development. Based on the current situation of English teaching, this paper studies the college English teaching model that integrates innovation education and English education, and proposes relevant measures to provide a new model for English teaching to promote better development of English teaching.
Encouraging far-sightedness with automatically generated descriptions of optimal planning strategies: Potentials and Limitations

Author(s): Becker, Frederic; Skirzynski, Julian Mateusz; van Opheusden, Bas; Lieder, Falk | Abstract: People often fall victim to decision-making biases, e.g. short-sightedness, that lead to unfavorable outcomes in their lives. It is possible to overcome these biases by teaching people better decision-making strategies. Finding effective interventions is an open problem, with a key challenge being the lack of transfer to the real world. Here, we tested a new approach to improving human decision-making that leverages Artificial Intelligence to discover procedural descriptions of effective planning strategies. Our benchmark problem regarded improving far-sightedness. We found our intervention elicits transfer to a similar task in a different domain, but its effects in more naturalistic financial decisions were not statistically significant. Even though the tested intervention is on par with conventional approaches, which also struggle in far-transfer, further improvements are required to help people make better decisions in real life. We conclude that future work should focus on training decision-making in more naturalistic scenarios.
Application of Modern Educational Technology in English Situational Teaching in Secondary Vocational Schools

A good mastery of English is particularly important for contemporary secondary vocational students. Establishing a good English learning environment is of great help for students to learn English, especially integrating into modern English situational teaching, which has further promoted the English learning of secondary vocational students. Starting with the characteristics and advantages of modern education, this paper explains in detail the application of modern educational technology in English situational teaching, hoping to provide reference for English teachers to carry out efficient classrooms teaching.
Probing the Mental Representation of Relation-Defined Categories

Author(s): Du, Yuhui; Hummel, John E.; Petrov, Alexander Alexandrov | Abstract: The mental representation of relation-based concepts is different from that of feature-based concepts. In the present experiment, participants learned to categorize two fictional diseases that were defined either by a feature (e.g., short cells) or an ordinal relation (e.g., diseased cells being shorter than healthy cells). After the participants learned the categorization task to criterion, their strategies were probed in transfer task in which features and relations were pitted against one another. Finally, participants engaged in a stimulus reconstruction task. The results supported the prediction that participants who had adopted a feature-based strategy on a stimulus dimension, as identified by transfer data, tended to reconstruct values close to the means presented during training. By contrast, participants who had adopted a relation-based strategy tended to exaggerate that dimension away from the mean of the training examples and in the direction of the category-defining comparative relation. These data add to the growing literature suggesting that, unlike featural categories, relational categories are not represented in terms of the category’s central tendency.
Dynamic Visualization and Analysis of Government Responses - A Support System to Control Pandemic Situations

Covid 19 has focused the world's attention on health care facilities across the globe.Data modeling is a latent contributor for dynamic assessment and reporting/analyzing in distributed research networks.During our research, it was found that without demonstrative data, data sharing among subgroups focusing on various policy-making classifications, discoveries, and predictions become problematic and inefficient.The dearth of illustrative pandemic data (COVID-19) is a holdup for showcase and deliberate potential solutions.The realization of data for pioneering new technology in clinical healthcare systems and designing government decision support systems to help fight novel coronavirus is crucial.Dynamic graphs are a potential tool that aids in the dynamic assessment of country-wise policy data at a given point of time and is extremely significant for estimating public health measures and stringent policies.In the present research, the openly accessible Oxford's COVID-19 Government Response Tracker (OxCGRT) dataset is used.The OxCGRT is counting statistics from more than 180 countries, it enables the investigators and officials to explore the pragmatic outcomes of policy responses on the accelerating spread of COVID-19, in addition to financial and communal welfare.The stringent policy index and Containment and health policy index is observed for the 11 Countries across the world with the highest occurrence of cases.This assortment of the sub-group countries reduces the complexity and upsurges the representativeness of data with respect to the model policy indicators.
The Preparedness of Tunggak Community Dealing with Drought Disaster, Grobogan Regency

Drought disaster is geosphere events that occur in a long period of time that giving impact of society in terms of social, economic and environmental aspects. Drought disaster that often occurs in the Village of Tunggak has made BPBD Grobogan Regency distributing clean water assistance in the last 6 years. Drought conditions require preparedness to respond to a situation of disaster preparedness precisely to minimize the impact of drought. This study goals to detect forecasts in the early months of the drought in station rain area of Toroh Sub-district and to determine the community's preparedness for dealing with drought in Tunggak Village, Grobogan Regency. Detect forecasts in the early months of the drought used data on rainfall monthly index calculated by method of Standardized Precipitation Index (SPI) in accordance with WMO (World Meteorological Organization) guidelines and analysis of preparedness index data referring to LIPI UNESCO/USDR, 2006. The results showed that in the early months of drought forecasts occurring in May with an SPI value of-2.10 which is included in the classification of Extreme Dry, so that when entering May, the community can prepare to face drought. Meanwhile, the preparedness of Tunggak community in facing drought disasters is classified as Less Ready based on knowledge indicators, emergency response plans and resource mobility. While the value of each indicator is 41.4% with the Less Ready classification for the knowledge indicator, 55% is classified as Nearly Ready for the emergency response plan indicator and 46.4% which is included in the Less Ready classification for the resource mobility indicator.
Rol del Perú frente a la educación virtual y nuevos desafíos por la pandemia Covid-19

The Peruvian state assumes that the incorporation of Information and Communication Technologies into education requires thinking in advance about the objectives and challenges of education and subsequently determining in what way and under what conditions the presence of ICT contributes to it, in the context of COVID-19. The objective of this article is to determine the meaning of virtual education and the role of the Peruvian state that allows it to contribute more directly to improve educational quality from the challenges posed by the pandemic. The research is documentary and of an explanatory level that searches for information selectively in the sources available on the web. It is concluded that the Peruvian state must finance the development of significant, pertinent and sufficient digital content, as well as the training of teachers so that they have the necessary skills to use it.
IMAGERY ANALYSIS IN MATSUOKA’S CLOUD OF SPARROWS

The research is entitled Imagery Analysis in Matsuoka’s Cloud of Sparrows. This study aims to reveal how imagery described through the dialogues and narratives of Cloud of Sparrows written by Takashi Matsuoka, by applying Perrine and Thomas’ theory regarding the seven types of imagery in literature. The analysis uses the dialogues of the characters and narrations included in the novel as its main data of study, then finding the contextual similarity to Perrine and Thomas’ imagery in literature. This research uses descriptive qualitative method as the study attempts to identify and describe its types of imagery in accordance Perrine and Thomas’ imagery. The result of the study shows that the narrative within Matsuoka’s Cloud of Sparrows contains all of Perrine and Thomas’ seven types of imagery; starting from visual, auditory, gustatory, olfactory, kinesthetic, and organic imagery. The novel contains all of the seven types of literature imagery found in the narratives within.Keywords: Auditory, cloud of sparrows, gustatory, imagery, kinesthetic, olfactory, organic, tactile, visual
SMLtoCoq: Automated Generation of Coq Specifications and Proof Obligations from SML Programs with Contracts

Formally reasoning about functional programs is supposed to be straightforward and elegant, however, it is not typically done as a matter of course. Reasoning in a proof assistant requires "reimplementing" the code in those tools, which is far from trivial. SMLtoCoq provides an automatic translation of SML programs and function contracts into Coq. Programs are translated into Coq specifications, and function contracts into theorems, which can then be formally proved. Using the Equations plugin and other well established Coq libraries, SMLtoCoq is able to translate SML programs without side-effects containing partial functions, structures, functors, records, among others. Additionally, we provide a Coq version of many parts of SML's basis library, so that calls to these libraries are kept almost as is.
Correlation Between Writing Skills, High Frequency Lexicon Mastery and Students’ Reading Skills at SMP Negeri 1 Rambang, Muara Enim

This study aims to determine the correlation between writing skills, high frequency lexicon mastery, and reading skills at SMP Negeri 1 Rambang.This study used descriptive method and statistical analysis.This study's population was all the eighth-grade students of SMP Negeri 1 Rambang which were contributed into four classes.The total population is 119 students.The sample was taken randomly, 25% of the population.The total number of samples was 40 students.Based on data analysis, there is relationship between writing skills, high-frequency lexicon mastery and reading skill at SMP Negeri 1 Rambang (r table < rxy = 0.220<0.66.It showed that the students who got good marks at reading tests also got good marks at writing tests.It could be concluded that there is writing skills, high frequency lexicon mastery and reading skills of the eighth grade of SMP Negeri 1 Rambang in the academic year of 2020/2021.