Reviewerly/exHarmony huggingface dataset:
The effect of speaker reliability on adult cross-situational word learning

Word learning is guided by the statistical co-occurrence between spoken words and potential referents, through which learners gradually map labels to objects across situations. Given that word learning does not occur in a vacuum, rather in a communicative context, it is relevant to evaluate the role that speakers play. Because we do not evaluate the information provided by every person equally, it is reasonable to think that someone who makes lexical errors is not a reliable speaker from whom to learn new words. The current study focuses on speaker reliability in adult cross-situational word learning (CSWL). In two experiments we investigated the extent to&amp;nbsp; which&amp;nbsp; adults&amp;nbsp; attend&amp;nbsp; to&amp;nbsp; the&amp;nbsp; reliability&amp;nbsp; of&amp;nbsp; the&amp;nbsp; speaker&amp;nbsp; and&amp;nbsp; how&amp;nbsp; this&amp;nbsp; affects&amp;nbsp; word&amp;nbsp; learning&amp;nbsp; in&amp;nbsp; a CSWL task. We varied the consistency with which a speaker mapped novel words to familiar objects. We hypothesized (1) that the speakers’ reliability would be judged differently depending on their past object-labeling accuracy, and (2) that new words would be more difficult to learn when&amp;nbsp; presented&amp;nbsp; by&amp;nbsp; an&amp;nbsp; unreliable&amp;nbsp; speaker.&amp;nbsp; Experiment&amp;nbsp; 1&amp;nbsp; shows&amp;nbsp; that&amp;nbsp; the&amp;nbsp; unreliable&amp;nbsp; speaker&amp;nbsp; was&amp;nbsp; assessed&amp;nbsp; as&amp;nbsp; less&amp;nbsp; reliable,&amp;nbsp; compared&amp;nbsp; to&amp;nbsp; the&amp;nbsp; reliable&amp;nbsp; speaker,&amp;nbsp; but&amp;nbsp; this&amp;nbsp; effect&amp;nbsp; disappeared&amp;nbsp; in&amp;nbsp; Experiment&amp;nbsp; 2,&amp;nbsp; when&amp;nbsp; participants&amp;nbsp; were&amp;nbsp; taught&amp;nbsp; new&amp;nbsp; words&amp;nbsp; by&amp;nbsp; two&amp;nbsp; speakers,&amp;nbsp; a&amp;nbsp; reliable&amp;nbsp; and&amp;nbsp; an&amp;nbsp; unreliable&amp;nbsp; one.&amp;nbsp; Furthermore,&amp;nbsp; we&amp;nbsp; found&amp;nbsp; no&amp;nbsp; evidence&amp;nbsp; to&amp;nbsp; support&amp;nbsp; the&amp;nbsp; hypothesis&amp;nbsp; that&amp;nbsp; being&amp;nbsp; exposed&amp;nbsp; to&amp;nbsp; an&amp;nbsp; unreliable&amp;nbsp; speaker&amp;nbsp; impairs&amp;nbsp; CSWL&amp;nbsp; in&amp;nbsp; adults.&amp;nbsp; We&amp;nbsp; discuss&amp;nbsp; the&amp;nbsp; relevance&amp;nbsp; of&amp;nbsp; these&amp;nbsp; findings and the importance of further research on the role of speaker reliability in CSWL.
NONLINEAR ESTIMATION STEAMY ONE-PARAMETER REGRESSION IN TERMS OF LACK OF STATISTICS

Parametric regression is a mathematical model of a phenomenon in the form of functional dependence between the parameters of this phenomenon, one of which is a dependent variable and independent arguments of a function, and the other is its unknown estimated parameters. Since measurements are often burdened with errors, the construction of the model is carried out in the probabilistic scheme of the problem statement, and the estimates of unknown parameters are carried out by statistical methods using evaluation equations. For a nonlinear regression that is not intrinsically linear, the estimated equations with respect to the estimated parameter are not analytically solved. In this case, iteration methods are used, the effectiveness of which depends on the initial approximation. There is an iterative formula for generalized minimal-contrast estimation of non-linear one-parameter pair (one argument) regression. Its components are the implementations of the estimated regression parameter found analytically or numerically by the regression function at measured values of the dependent variable and the independent argument without taking into account the measurement errors. The average of these realizations with a certain approximation accuracy is a consistent estimate, which was previously proved by the numerical characteristics of the realizations found. This estimate can be used as an initial estimate in an iterative parametric regression estimation formula. In this paper, the implementation of the estimated parameter with approximately zero variance is considered not only as an initial approximation, but also as a self-sufficient estimate, if its accuracy is satisfactory. It is an approximation of the estimated parameter of known accuracy proportional to the cube of the standard deviation of the initial data. The results of the simulation experiment for estimating regression parameters by the proposed approximation method and by means of a consistent assessment are consistent with the theoretical descriptions of the methods. Their comparison is in favor of approximation, if the volume of the original data is less than ten. In this case, the deviation from the true value of the estimated parameter is less than the deviation of the compared state estimate by a maximum of two orders of magnitude (188 times) by at least 1.5 times. Conditions of optimality of the method assumes its use in studies of rare phenomena, as well as in expensive experiments in the broad (economic and humanitarian) sense of the word, he effectiveness of the evaluation method can be anticipated by checking to experience the fulfillment of the conditions of evaluation formation, which depend on the range of values of the argument of the regression function.
Students’ Abilities and Difficulties in Comprehending English Reading Texts at Secondary Schools; An Effect of Phonemic Awareness

Reading comprehension in the EFL context requires abilities not only linguistic competences but also reading strategies. The timely acquisition of this competence has a crucial effect for language learners. Unfortunately, most language learners in all level have low skills and high difficulties to acquire reading skills. This study aims to explore students’ abilities and difficulties in comprehending English reading texts as secondary level. This study is categorized as qualitative study consisting of three main data gathering methods: semi-structured interviews, classroom observations, and group discussions. The data collected then are analyzed in stages, namely data condensation, data display, and data conclusion. Based on the result of analysis, this study showed that students have low reading achievement at secondary level. The low achievement is affected by some reading difficulties such as low reading exercises, unwilling to read out loud, low reading skills, low vocabulary, low phonemic awareness, low reading strategies, and low grammatical competence. For further studies, reading exercises and phonemic awareness in reading activities should be paid intention with giving students with various reading texts to train them comprehend EFL texts.
Analysis of Social Media Algorithm Recommendation System

Once, the Internet was considered an important force to promote social public welfare activities and spread social justice. Today, the driving force of the Internet on the spread of negative social information and polarisation also exists. Social media platforms use this kind of method to customise personalised content distribution schemes by mining and analysing individual historical behaviour data based on algorithms. This behaviour of the platform brings about efficient and accurate information matching. At the same time, the content recommended by the algorithm is also controversial due to the risk of privacy violations and other issues. This article will analyse the advantages and disadvantages of social media platform algorithms and recommendation systems for citizens.
Enhancing Vocabulary Mastery through Applying Visual Auditory Kinesthetic (VAK): A Classroom Action

Vocabulary mastery is paramount to support the four language skills and it determines the success of students’ communication after grammatical competences. lexical competence is assumed as the second competence to that of the grammar. One of the alternatives in teaching vocabulary is visual auditory kinesthetic (VAK). This classroom action research (CAR) aimed at applying the VAK due to the students’ difficulties in memorizing new vocabulary especially the abstract noun. The procedure of the CAR comprises planning, acting, observing, and reflecting. Each stage has activities to attain the research goals. The subjects of this study were the Seventh Graders of SMP Islam Al-Badriyah. There were a vocabulary test, questionnaire, and observation sheet as the research instruments. Then, the data was analyzed using both quantitatively and qualitatively. The findings from the vocabulary test showed that 21 out of 25 students passed the settled minimum criteria or the mean score fell on 77. It found out the students were active participation, paid good attention to the material and showed enthusiasm in the English class. It can be concluded that the application of the VAK could increase not only the students’ vocabulary mastery but also classroom participation. In addition, the result of this current study proved that the application of VAK as one of the teaching alternatives could lead the students in memorizing abstracted vocabularies.
Effectiveness of Gamification Tool in Teaching Vocabulary

This research investigates the views of students in a home school centre from Setia Alam towards the effectiveness of using gamification tools in teaching vocabulary.In recent years, numerous game-based technologies have been developed with the aim of providing fun yet meaningful experience to their users.These technologies are also common among students in the ESL classroom since they act as supplements for effective game-based classroom activities.Many studies have proven that game-based learning had motivated students to participate and engage actively in learning as it creates positive feelings among them.This study seeks to explore students' attitudes towards the usage of gamification tool to enhance vocabulary skills, the different attitudes of male and female students toward using gamification tool to learn vocabulary and the differences of vocabulary scores between the traditional method of teaching and when gamification is used when teaching.This study was conducted both quantitatively and qualitatively with the participation of 60 students.The prime data was collected via questionnaires using Google Forms Survey which was later analysed descriptively.Data collected from the interview was used to supplement the findings.The findings report that Kahoot! is proven to be useful and effective for students in the ESL classroom.The study provides insights for better implementation of game-based technologies in the English language classroom curriculum.
Developing an ELT Instructional Model for Vocational High Schools Students at Tourism Zones

Indonesian Economic Development has become a gate to Bali and Lombok for international visitors. Recently, the Lombok tourism development has established a refinement after facing serial earthquakes. In the statistic for the tourism year 2016, there were 3.1 million tourists coming to Lombok. In addition, 3.8 million people were targeted to come to Lombok in the year 2020. In other words, Lombok promotes the highest contribution to the national government economy. Because of these issues, the vocational high schools which have tourism study programs should lead their students in foreign language communication, English. Teaching English for a specific purpose needs a precise instructional model because ELT teachers apply the ELT model for different objectives. Therefore, learners study English for different purposes. For vocational high school students, they learn English to help them to communicate in the workplace. Because of this, they are directed to have communicative competence. In senior or junior high schools, scientific-based instruction has been applied to help students learn English and even other subjects. This instruction is considered as a solution for them to have not only linguistic competencies but also communicative skills. Therefore, this study will be aimed at developing an instructional model for vocational high school students in tourism zones. This study applied the procedural research and development (R&amp;D) design. The R&amp;D design follows the Borg &amp; Gall and David design, which consists of pre-development and development stages. The product of this study was an instructional model, namely the tourism-based instructional (TBI) model for vocational high school students in the tourism zones.
Image Style Conversion using Deep Convolutional Neural Network

At present, research on image style conversion based on deep learning is increasing, different from the conventional style conversion, this paper is based on convolutional neural networks, using the InceptionV3 model trained under ImageNet dataset. By using Deep Dream technology, which gives a dull and ordinary background picture a warm color, makes the picture content richer, the texture is very softer and more exquisite.
An Intelligent Examination Monitoring Tool for Online Student Evaluation

The global reach of online education has increased due to a pandemic or other unique circumstances. As online education got more popular, it became crucial to ensure the quality of evaluation. This study's goal is to find a solution to the issue of monitoring during online exams. We have used behavioural biometrics through students' interaction with an Intelligent Examination Monitoring Tool (IEMT), which was developed, even though many studies concentrate on using video analysis. The test-taking prototype uses mouse, touch, and keyboard interfaces to administer multiple-choice questions with a variety of information and events. Students who used additional sources to answer questions were later discovered during an online interview. We built a prediction model that can determine if a student is answering on his own or using any other sources using the events through input interaction when these students are sorted. The Machine Learning (ML) techniques Decision Tree, Random Forest, K-Nearest Neighbour, and Naive Bayes were used to generate a few models. After evaluating the performance of the models, we find that random forest performs best, with an accuracy of about 91 percent.
Teachers’ Attitude on Implementing the Free Basic Education in Kiteto District Council, Tanzania

This paper sought to highlight teachers’ attitudes on implementing the Free Basic Education Policy in Kiteto District Council, Tanzania. Data were collected from 169 respondents by using questionnaires and interviews. Data analysis was done by descriptive statistics and content analysis. The findings showed that the teachers generally had positive attitudes towards the implementation of the free basic education policy. In their efforts to implement the policy, the teachers treated the students with passion, listening to students’ problems, encouraging students to participate in implementing the policy and motivating students to study hard to attain their goals. Teachers’ practices included their participation in school decision-making, communicating with parents to encourage them to side school in implementing the free education policy, preparing the learning environment for the implementation of the policy, monitoring, supervising, and distributing teaching/learning materials to students equitably, and supervising students’ academic progress. It was concluded that teachers’ attitude is very important in the implementation of any program or policy in the school. It is recommended to the government that all plans, programs, and policies that are related to education need consultation from the teachers so that they can be sustainable and effective.
A Short Review on Fast Ways to Multiply Two Matrices

Matrix multiplication is probably one of the most basic and important operations having a wide range of applications in studying Linear algebra. We will be primarily focused on reviewing different algorithms for the multiplication of two n&amp;times;n matrices. The most Naive method has a complexity of O(n3) but interestingly, algorithms with better complexity have been achieved. We will get to see how the complexity can be improved further, occasionally giving a survey.
USABILITY ANALYSIS USING USER EXPERIENCE QUESTIONNAIRE METHOD ON MEDISOL WEBSITE

The aim of this study is to analyze the usability of the Medisol website using the User Experience Questionnaire (UEQ) method so that it can be further developed according to user needs in the future. This analysis was carried out using four variables from the User Experience Questionnaire method: Usefulness, Ease of Use, Ease of Learn, and User Satisfaction. Usability measurement is obtained from the percentage of feasibility based on a questionnaire distributed to users who access the Medisol website with 30 respondents. In addition, the Likert scale was used to facilitate filling out the questionnaire and processing of the results by researchers. Based on calculations on the aspects covered by the User Experience Questionnaire (UEQ) method, the results obtained are 86% on the Usefulness aspect, 86% on the Ease of Use aspect, 89.67% on the Ease of Learn aspect, and 84.48% on the User Satisfaction aspect. It is said that the Medisol website perfectly fulfills these aspects. And from the usability calculation results obtained, namely 86.13%, it can be concluded that the percentage level of the Medisol website eligibility can be categorized as very feasible.
Learning the lie of the land: How people construct mental representations of distributions.

An unexamined assumption in many studies of learning and decision making is that people learn underlying probability distributions. However, the acquisition of distributional knowledge is rarely the focus of investigations. We report five experiments (N = 580 adults) that provide this focus and highlight the factors that impact people’s ability to accurately learn and reproduce underlying distributions. We find that people accurately reproduced the distribution only when either the environmental signal is strong (i.e., non-noisy discrete bimodal distributions), or sufficient cues are provided to aid construction of mental representations (e.g., items from the modes in a noisy bimodal distribution are presented in different colours). Together the results challenge strong assumptions about the role of probability distribution-knowledge in explanations of learning and decision making.
Algebraic Presentations of Dependent Type Theories

C-systems were defined by Cartmell as models of generalized algebraic theories. B-systems were defined by Voevodsky in his quest to formulate and prove an initiality conjecture for type theories. They play a crucial role in Voevodsky's construction of a syntactic C-system from a term monad. In this work, we construct an equivalence between the category of C-systems and the category of B-systems, thus proving a conjecture by Voevodsky. We construct this equivalence as the restriction of an equivalence between more general structures, called CE-systems and E-systems, respectively. To this end, we identify C-systems and B-systems as "stratified" CE-systems and E-systems, respectively; that is, systems whose contexts are built iteratively via context extension, starting from the empty context.
Universum GANs: Improving GANs through contradictions

Limited availability of labeled-data makes any supervised learning problem challenging. Alternative learning settings like semi-supervised and universum learning alleviate the dependency on labeled data, but still require a large amount of unlabeled data, which may be unavailable or expensive to acquire. GAN-based data generation methods have recently shown promise by generating synthetic samples to improve learning. However, most existing GAN based approaches either provide poor discriminator performance under limited labeled data settings; or results in low quality generated data. In this paper, we propose a Universum GAN game which provides improved discriminator accuracy under limited data settings, while generating high quality realistic data. We further propose an evolving discriminator loss which improves its convergence and generalization performance. We derive the theoretical guarantees and provide empirical results in support of our approach.
Characterizing Uncertainty in the Visual Text Analysis Pipeline

Current visual text analysis approaches rely on sophisticated processing pipelines. Each step of such a pipeline potentially amplifies any uncertainties from the previous step. To ensure the comprehensibility and interoperability of the results, it is of paramount importance to clearly communicate the uncertainty not only of the output but also within the pipeline. In this paper, we characterize the sources of uncertainty along the visual text analysis pipeline. Within its three phases of labeling, modeling, and analysis, we identify six sources, discuss the type of uncertainty they create, and how they propagate. The goal of this paper is to bring the attention of the visualization community to additional types and sources of uncertainty in visual text analysis and to call for careful consideration, highlighting opportunities for future research.
Study on phase demodulation algorithm of fiber optic pressure sensor based on nonlinear differential equation

Fiber optic Fabry–Pérot sensors have been widely developed with unique advantages, such as ease of reuse, resistance to electromagnetic interference, light weight, and their ability to work in extreme environments. There are many demodulation methods that can be applied to fiber optic Fabry–Pérot sensors, including the intensity demodulation method, spectral demodulation, and the phase carrier method, but these demodulation methods cannot meet the requirements that take into account range, speed, and dynamic and static demodulation capabilities. In view of these problems, this paper uses nonlinear differential equations to solve the problem of simultaneous measurement of a large number of ranges and dynamic and static parameters. The measuring interferometer in the demodulation module was built using a polarizing interferometer, which avoids the difficulty in optical wedge processing when using a Fizeau interferometer. Regarding the problems of high and low signal-to-noise ratios of the generated signal, for the problem that the introduction of dispersion in the crystal causes the demodulation result of the traditional demodulation method to be wrong, a nonlinear differential equation is proposed to achieve the correct demodulation of the fiber optic sensor: the slow demodulation speed problem. This paper designs the acquisition, transmission, and processing system based on digital signal processing and a field-programmable gate array, which provide a hardware platform for real-time demodulation. Finally, experiments to test the resolution, linearity, stability, and repeatability of the interferometer were carried out on the designed demodulation system.