Reviewerly/exHarmony huggingface dataset:
Using Whatsapp in Teaching Vocabulary: A Case Study from Palestine

essaging applications have become well-known among 21st-century students worldwide and in Palestine in particular. These applications are useful in teaching and learning all disciplines and English in particular. This study has sought to find out the effect of using the WhatsApp application in enriching primary school students’ vocabulary. To this end, a 20 sixth-grade students (10 males and 10 females) from Al-Omariya Private Schools, Nablus were selected as a study sample. Since the research adopted one-group design method, a pre-test was administered to assess the student's level in vocabulary knowledge and to ensure their homogeneity. After that, the students in the experimental group received vocabulary instructions and a teacher's pedagogy through WhatsApp messages, which included pictures, texts and videos, three days a week for two months. A post-test was administered to the experimental group to measure the effect of using WhatsApp instructions on their vocabulary knowledge and gender as well. The results revealed that using WhatsApp had a significant effect on the improvement of the student's vocabulary knowledge. They also showed that there were differences in the effect of using WhatsApp in teaching vocabulary between males and females in favor of males. In light of these findings, the researchers suggest using WhatsApp messaging in other private and government schools.&#x0D; This study contributed to raising the awareness of students, teachers and curriculum designers of the importance of utilizing WhatsApp in teaching and learning. It also contributed to introducing students to new strategies and techniques for learning English vocabulary in a new environment that promotes students’ motivation and enhances autonomous learning whenever and wherever they want according to their pace. The study may also participate in introducing foreign researchers to the reality and capacities of the Palestinian educational context that may lead to mutual collaboration in future.
(Digital Presentation) Application of Plasma Cleaning in the Preservation and Restoration of Cultural Heritage

The chemical reactivity of metals at inappropriate climate conditions can be a threat to metallic cultural heritage. It is known that oxygen plays an important role in the corrosion and decay of metallic objects. Oxide formation is among the most prevalent destructive phenomena in this field. The metallic archaeological objects lose their original shape due to the oxide layer that develops on their surface. Among physical-mechanical and chemical techniques used in the past to remove the oxide layer from these antiques, Cold plasma technology has been proposed as a novel safe method to successfully achieve this goal. In a plasma medium, which can be formed by an electrical discharge, chemically reactive species exhibit a unique behavior in response to the injected gas type, electrical and chemical parameters, etc. This special behavior aids in achieving the user's goal through physicochemical phenomena. In this study, Hydrogen gas, with its reductive character, in the plasma phase provides free radicals of Hydrogen reacting to the copper oxide layer on ancient coins. As a result of this plasma reduction reaction, separation of the oxide layer from the copper surface is achievable. This phenomenon which is called Plasma cleaning, is a type of etching. Plasma cleaning does not destroy surface structure and information contained within metallic heritage artifacts. The feasibility of this non-destructive cleaning method has been investigated for the preservation and restoration of ancient copper coins dating back roughly 300 years ago. These ancient copper coins were exposed to a cold hydrogen plasma for 120 minutes. Results show that Tenorite and Spertiniite formed on the surface of coins have been successfully removed. The black color of Tenorite, a type of copper oxide, gives a dark appearance to copper coins' surface, and Spertitnite, as a copper hydroxide, exhibits a blue-green color on copper coins. According to the results, after 2 hours of hydrogen plasma treatment, not only these green spots have been removed, but also the dark appearance of the entire surface of the coin has been reduced. This amount of clearance is a good result considering the untreated area. Moreover, Figure 1 illustrates the coin's surface using SEM (A) before and (B) after Hydrogen plasma treatment. These images were obtained at a 200x magnification from the surface. In contrast to Figure 1(A), which had heavily polluted surfaces, case B's dark pollution has been removed, reducing the amount of darkness on the coin's surface. This study shows the efficacy of Plasma cleaning for the preservation and restoration of ancient copper coins. Figure 1
Travel recommendation system using graph neural networks

There are many applications and uses of recommendation systems. For any recommendation system, the user-to-item interactions are important which can also be seen as graphs. We are focusing on travel or place recommendations. There are very few works on travel or trip recommendation systems using Graph Neural Networks (GNN) leveraging user-to- item interactions. In this work, we have implemented travel or place recommendations using the LightGCN model and compared it with the implementation of the traditional non-graph-based collaborative filtering Matrix Factorization (MF) approach. We have then shown that the LightGCN model performs better for travel or place recommendations than the Matrix Factorization approach. We achieved very good results [203% increase in precision, a 167% increase in recall, and a 98.6% NDCG increase in metrics] using a graph based LightGCN model for travel or place recommendations compared to the Matrix Factorization approach.
Multi-View Deep Gaussian Processes for Supervised Learning

Multi-view learning is a widely studied topic in machine learning, which considers learning with multiple views of samples to improve the prediction performance. Even though some approaches have sprung up recently, it is still challenging to jointly explore information contained in different views. Multi-view deep Gaussian processes have shown strong advantages in unsupervised representation learning. However, they are limited when dealing with labeled multi-view data for supervised learning, and ignore the application potential of uncertainty estimation. In this paper, we propose a supervised multi-view deep Gaussian process model (named SupMvDGP), which uses the label of the views to further improve the performance, and takes the quantitative uncertainty estimation as a supplement to assist humans to make better use of prediction. According to the diversity of views, the SupMvDGP can establish asymmetric depth structure to better model different views, so as to make full use of the property of each view. We provide a variational inference method to effectively solve the complex model. Finally, we conduct comprehensive comparative experiments on multiple real world datasets to evaluate the performance of SupMvDGP. The experimental results show that the SupMvDGP achieves the state-of-the-art results in multiple tasks, which verifies the effectiveness and superiority of the proposed approach. Meanwhile, we provide a case study to show that the SupMvDGP has the ability to provide uncertainty estimation than alternative deep models, which can alert people to better treat the prediction results in high-risk applications.
The students’ error analysis in writing descriptive texts

This study aimed to find out and analyze students’ error analysis at three student’s categories in writing descriptive text on paragraph-based writing subject. The analysis involved students’ writing ability in developing the ideas, organizing the ideas, vocabulary, grammar, punctuation, and the elements of descriptive text include generic structure and language features. The design of this study was case study under qualitative approach. There were 9 students from three categories as the subject of this study. The categories were high, medium, and low-level students at the fourth-semester of English Education Department at one of private university in Cirebon, West Java in the academic years of 2019/2020. The data were taken from student’s descriptive writing text and interview. The findings showed that the most errors from three students’ categories were grammatical errors, and how they arrange the elements of descriptive text. The total numbers of errors committed by students were 50 items, which include grammatical error with 40 items and the percentage 80%, generic structure error with 3 items and the percentage 6%, language features error with 7 items and percentage 14%. The most error made by the students are grammatical error with 40 items and the percentage 80%. It can be concluded that the students made grammatical errors, it is because they lack of vocabulary mastery and lack of grammar rules.&#x0D; Keywords: students’ error analysis; writing; descriptive text
Designing System Information DAMRI (SIRI) in an Effort to Improve Damri Transportation Services User in Bandung

The DAMRI bus or Djawatan Angkoetan Motor Republic Indonesia is one of the mainstays of public transportation for residents in the Bandung area with relatively low costs for the facilities with varied travel routes. The existence of this DAMRI bus is able to help increase the productivity of the community to fulfil needs. However, any of these advantages can be difficult for users of the bus service to obtain due to waiting for a bus for a long time. This is because the number of routes is not as many as other public transportation and there is a lack of information about the bus schedule for each route, so that service users can only guess the arrival time of the bus. This design is carried out by the observation method of collecting data on the experience of DAMRI bus service users through questionnaires, website-based software development methods, and literature reviews. The purpose of this design is to provide convenience to customers in accessing information on DAMRI Bus transportation through their smartphones or computers. The result of this design is a media route schedule information, routes, and costs of each route for users with a minimalist design and easy to understand is also used.
The Students’ Preference on Using Screen Text towards their Reading Comprehension

The objectives of this study was conducted to know the students’ preference on using screen text toward thier reading comprehension. In this case, finding out the information that can be used in teaching learning process toward improving the students’ reading comprehension is the focus of the educators. Moreover, the students’ familiarity reading the text by their mobile technology was as the source of information. The population of this study was students at English Education Study Program of Baturaja Univesity in academic year 2018/2019 and 36 students as sample. The research method was survey design, which to investigate the students’ response on the use of screen text relate to their reading comprehension. Questionaire was used in collecting the data, which was classified into four aspects: reading comprehension skills, retention and recall memory, motivation and psychology aspect. The data was analyzed the dominant percentage of each item. Based on the result, students were found to have higher positive preference of the reading by using screen text on the aspect of motivation. It could be concluded that reading a text on screen can give motivation for their reading skill and comprehension.&#x0D; Keywords : preference; screen text; reading comprehension
An Overview and Concerns Related to Quantum Cryptanalysis: Past, Present, and Future

We outline the important quantum algorithms that are instrumental toward cryptanalysis of classical ciphers. Here we attempt to touch on the relevant security issues and explain certain (some low-level) technical points on the cryptographic primitives.
Record Management Practices and the Performance of Produce Dealers in Lira City

Purpose: The study aimed to determine the effect of record management practices on the performance of produce dealers in lira city, Uganda. Specifically, the examined record filling, record retention and record retrieval on performance of produce dealers.&#x0D; Methodology: The study adopted a cross-sectional study design, which employed a mixed methods approach of both quantitative and qualitative methods. The study population consisted of 195 respondents, which comprised of produce dealers in Lira City. Both the Simple random sampling technique and purposive sampling technique were used to select a sample of 103 participants. The researcher adopted Self-Administered Questionnaires to collect quantitative data and an interview guide to collect qualitative data. Both descriptive statistics (mean, and standard deviation), and inferential statistics (correlation and regression) were used to analyse numerical data. Content analysis was used to analyse qualitative data.&#x0D; Findings: The findings revealed a statistically significant positive relationship between record filling, record retrieval and performance while insignificant relationship was realised between record retention and performance. Further, it was revealed that record filling and record retrieval yields a significant effect on performance while record retention yields insignificant effect on performance.&#x0D; Unique contribution to theory, policy and practice: The study concluded that record management significantly affects performance of produce dealers in Lira City. It is encouraged that, for good performance of produce dealers, the authorities of Lira City should enhance that capacity of business people in record management by training them in record management. This study is very instrumental in unveiling the pertaining issues in the field of produce dealers, which has become a very lucrative business in Uganda in terms of how record keeping is a central aspect in their day-to-day operations.
The Correlation Between Students’ Interest and Students’ Achievement in Learning English

The article aims to investigate whether there is significant correlation between students’ interest and students’ achievement in learning English at SMA Swasta Pertiwi Medan. The techniques used to collect the data are observation and questionnaire. The researcher selected 30 students as a sampling from Grade X IA2. The Finding of the study is the students’ interest could influence the in achievement. Students who have high interest try to pursue knowledge more than who have the low one. They tend to be more attentive in learning the lesson and motivation to enrich their vocabulary, to practice their English and do a lot of exercises to make them more skillful in using English. Based on the research finding, the conclusion is that there is a correlation between students’ interest and their achievement. it is suggested to (1) to teacher who teaches English in the classroom need to ensure that student realize that both high and low interest gets attention, (2) the teacher has to manage the classroom to help the students think creatively
Discovery and Inference of a Causal Network with Hidden Confounding

This article proposes a novel causal discovery and inference method called GrIVET for a Gaussian directed acyclic graph with unmeasured confounders. GrIVET consists of an order-based causal discovery method and a likelihood-based inferential procedure. For causal discovery, we generalize the existing peeling algorithm to estimate the ancestral relations and candidate instruments in the presence of hidden confounders. Based on this, we propose a new procedure for instrumental variable estimation of each direct effect by separating it from any mediation effects. For inference, we develop a new likelihood ratio test of multiple causal effects that is able to account for the unmeasured confounders. Theoretically, we prove that the proposed method has desirable guarantees, including robustness to invalid instruments and uncertain interventions, estimation consistency, low-order polynomial time complexity, and validity of asymptotic inference. Numerically, GrIVET performs well and compares favorably against state-of-the-art competitors. Furthermore, we demonstrate the utility and effectiveness of the proposed method through an application inferring regulatory pathways from Alzheimer's disease gene expression data. Supplementary materials for this article are available online.
Use of Instagram as learning media in senior high school

This study examines using Instagram as an innovative learning tool for high school students. The indicators assessed are the easiness, frequency, and experience that Instagram provides as a learning tool. This study used a qualitative approach and collected data using a questionnaire completed by SMA/SMK/MA/MAK students. The study used a Likert scale by giving weight to each available answer. The weights in each category will be summed and converted into qualitative data. The data will be drawn by counting how many categories of answers from all respondents. The results showed that forty-four point four percent of students who were respondents agreed with Instagram as a learning tool. The results showed that respondents considered Instagram an easy-to-use learning tool. Instagram's position is ideal as a learning tool because students are comfortable using it. Teachers are expected to use Instagram social media more often as a learning tool so that the benefits of using Instagram can be more optimized in supporting student learning achievements.
Use of gamification to increasing motivation in learning

The industrial revolution 4.0 became a driver of progress for all fields of life. In the field of education, era 4.0 made the old way of learning must be improved along with technological developments. One of them is gamification, a learning approach that uses several elements in games that aim to motivate students in the learning process so that they feel comfortable and have fun. This study uses a survey method, with the aim of knowing the responses, motivations, and interests of respondents related to this gamification. The survey was conducted using a google form, and distributed online to respondents through various communication media. The data is generated from research in the form of a bar chart. Then, this data is processed and the difference value is obtained from each question. Description of the research developed based on the questions in the questionnaire. The results of the study show that students like the learning process by gamification because students with a ranking game system have an award. Results Based on the research, students like learning by gamification. It should be explained that gamification is not just making a game. However, using the game system in real life. So, it is necessary to conduct further research on ways to develop gamification to increase students learning motivation.
Impact of using podcasts on students learning motivation

A podcast is a media file or digital audio to be specific, which can be published regularly through the internet in a particular format, such as mp3 formats. Podcast is also widely used, and the education field is not an exception. During the pandemic state that is happening right now, the education process is required to continue, so a Distance Learning policy is issued, which requires all people, including students, to stay at home as a way to prevent transmission of the virus through a circular by the Minister of Education and Culture that stated in law number 3 of 2020 regarding the prevention of Covid-19. This distance learning policy requires educators to be able to choose suitable learning media. In this research, the researcher uses an interview method with the Mahad Abu Aziz elementary school teacher. The results showed that podcasts as a learning media received a good response from the students. Podcasts can be effectively used in the learning process only if the educators have good speaking ability, including good intonation, and can create a pleasant situation in their audio presentation. In conclusion, podcast as a learning media receives excellent feedback from students because it is considered easy to use and works better, especially in Language lesson.
Variational quantum algorithms for Poisson equations based on the decomposition of sparse Hamiltonians

Solving a Poisson equation is generally reduced to solving a linear system with a coefficient matrix $A$ of entries ${a}_{ij}, i,j=1,2,...,n$, from the discretized Poisson equation. Although the variational quantum algorithms are promising algorithms to solve the discretized Poisson equation, they generally require that $A$ be decomposed into a sum of $O[\text{poly}({\text{log}}_{2}n)]$ simple operators in order to evaluate efficiently the loss function. A tensor product decomposition of $A$ with $2{\text{log}}_{2}n+1$ terms has been explored in previous works. In this paper, based on the decomposition of sparse Hamiltonians we greatly reduce the number of terms. We first write the loss function in terms of the operator ${\ensuremath{\sigma}}_{x}\ensuremath{\bigotimes}A$ with ${\ensuremath{\sigma}}_{x}$ denoting the standard Pauli operator. Then for the one-dimensional Poisson equations with different boundary conditions and for the $d$-dimensional Poisson equations with Dirichlet boundary conditions, we decompose ${\ensuremath{\sigma}}_{x}\ensuremath{\bigotimes}A$ into a sum of at most 7 and $(4d+1)$ Hermitian, one-sparse, and self-inverse operators, respectively. We design explicitly the quantum circuits to evaluate efficiently the loss function. The decomposition method and the design of quantum circuits can also be easily extended to linear systems with Hermitian and sparse coefficient matrices satisfying ${a}_{i,i+c}={a}_{c}$ for $c=0,1,...,n\ensuremath{-}1$ and $i=0,\ensuremath{\cdots},n\ensuremath{-}1\ensuremath{-}c$.
The treedata.table Package

The data.table package enables high-performance extended functionality for data tables in R. treedata.table is a wrapperfor data.table for phylogenetic analyses that matches a phylogeny to the data.table, and preserves matching during data.table operations.Using the data.table package greatly increases analysis reproducibility and the efficiency of data manipulation operations over other ways of performing similar tasks inbase R, enabling proces
Recognition of the speech signal of the Mongolian language by syllables

In this paper, we considered the possibility of Mongolian speech recognition using a neural network. At the same time, we applied a method with highlighting the syllable of a recognizable word, since in the Mongolian language words are formed by adding a suffix to its root. And the method of extracting the syllable of a word allows you to reduce the size of the database, since there is no need to save the features of each word. The neural network was trained using the Levenberg–Marquardt algorithm, which is more stable and faster when working with a small database. The experiment used 4 words of the Mongolian language with one or two syllables. The words were written directly into the computer using the Matlab software. The speakers who voiced these words are 11 people, men and women of different ages. Of these, 1 person aged 20–30 years, 7 people aged 30–40 years and 3 people aged 60–70 years. In addition, the neural network recognizes the area in speech where the noise occurs in order to distinguish and separate the speech area from the noise. The trained network recognizes the words of the Mongolian language by syllables from the database with a probability of 96.5 %.