Reviewerly/exHarmony huggingface dataset:
The Effectiveness of Padlet in Enhancing Reading and Writing Skills in English Language Course Among EFL Students at Secondary Stage

The study aimed to investigate the effectiveness of Padlet in enhancing the EFL reading and writing skills, which are considered as basic skills taught in public schools, in Saudi Arabia. The present study followed the quasi-experimental design in the form of two groups - a control group (taught reading and writing skills in a conventional way), and an experimental group (taught reading and writing skills by using Padlet). The study sample consisted of (60) grade 10 students (thirty students in each group) from Al-Shati High School. The sample took a pre-post achievement test as an evaluation tool of student’s performance in reading and Writing. The results, showed that there are statistically significant differences between the mean score of the two groups in the achievement test in favor of the experimental group. The study recommended adopting the use of Padlet in EFL classroom learning environments for learning reading and writing skills.
Forecasting Price of Amazon Spot Instances Using Machine Learning

An auction-based cloud model is followed in the spot pricing mechanism, where the spot instances charge changes with time. The user is bound to pay for the time that is initially initiated. If the user terminates before the sessional hourly completion, then the customer will be billed on the entire hourly session. In case Amazon terminates the instance then the customer would not be billed for the partial hour. When the current spot price reduces to bid price without any notification the cloud provider terminates the spot instance, it is a big disadvantage to the time of the availability factor, which is highly important. Therefore, it is crucial for the bidder to forecast before engaging the bids for spot prices. This paper represents a technique to analyze and predict the spot prices for instances using machine learning. It also discusses implementation, explored factors in detail, and outcomes on numerous instances of Amazon Elastic Compute Cloud (EC2). This technique reduces efforts and errors for forecasting prices.
AUTOMATIC IDENTIFICATION OF MINERALS IN IMAGES OF POLISHED SECTIONS

Abstract. Automatic identification of minerals in images of polished section is highly demanded in exploratory geology as it can provide a significant reduction in time spent in the study of ores and eliminate the factor of misdiagnosis of minerals. The development of algorithms for automatic analysis of images of polished sections makes it possible to create of a universal tool for comparing ores from different deposits, which is also much in demand. The main contribution of this paper can be summed up in three parts: i) creation of LumenStone dataset (https://imaging.cs.msu.ru/en/research/geology/lumenstone) which unites high-quality geological images of different mineral associations and provides pixel-level semantic segmentation masks, ii) development of CNN-based neural network for automatic identification of minerals in images of polished sections, iii) implementation of software tool with graphical user interface that can be used by expert geologists to perform an automatic analysis of polished sections images.
Teaching Speaking and The Teacher`s Role for EFL Learner in Emergency Remote Teaching (A Qualitative Study on Non-English Department Students)

Teaching EFL nowadays confronts a technical problem of having non face to face meeting. Amongst the four skills in teaching EFL, speaking still be the trend in language research especially in emergency remote teaching. This study revealed teaching speaking and the teacher`s role for EFL Learner in non-English department class. The data were taken from online interview, self-written and observation. The research was taken on online class of Speech Therapy students which undergo on the online class group. The results showed that teaching speaking using video and voice note as media for teaching and learning successfully made the process occur effectively and meaningfully. The use of video stimulate students’ interest and motivation in learning the materials. Moreover, voice note be an effective media in practicing speaking, giving feedback and discussing. The result contributed to teachers and other researchers for selecting the suitable media in teaching and practicing speaking amidst the emergency remote teaching.
Problem-based Learning in Pedagogic Tertiary Education: European Context Through Denmark Environment

Nowadays every European knowledge-based society demands a highly qualified, competent workforce being able to adjust to modern innovative production. To educate such specialists is the aim of contemporary teachers. So efficient and innovative pedagogic education becomes an integral part of the European education system. The article deals with the analysis of problem-based technology in the modern system of Danish teacher training in pedagogical higher educational institutions. Analyzing works of European scientists and problem-based model of teacher education in Denmark, working with university and college programs and documents we came to the conclusion that principles of problem-based technology in professional teacher training are similar in the whole European educational environment and in general they may be described as an approach to learning and instruction that has the following characteristics: 1) the use of problems as the starting point for learning, 2) small-group collaboration, 3) flexible guidance of a tutor, 4) student-initiated learning, 5) time availability for self-study. The findings imply that well-designed problem-based learning may lead to better educational results. Multiple sources in Ukrainian, European, and Danish educational environments at various time points from 1990 till 2020 have been used in data collection for this study. Pedagogic education in Ukraine requires a substantial adjustment at the legislative, structural, and technological levels. European experience in this sphere of teacher education modernization can become a valuable asset of the comparative pedagogic science. This practice will lead to effective technological change in teacher professional training in Ukraine.
How is the Awareness of Javanese Language Phonology of Elementary School Teacher Candidates?: Descriptive Qualitative Study

Introduction: language awareness needs to be developed to ensure that children can have it.In this process, each child must have different views in terms of developing language awareness.This research aimed to investigate the phonological awareness of Javanese language in Primary Teacher Education students who are also candidates for Javanese language teachers at the elementary school level.This is important considering that students' language skills are highly dependent on the ability of teachers at the initial level of learning, namely at the elementary school level.Phonological awareness greatly affects students' reading and writing skills.Especially in Javanese language where there are words that are well written and pronounced differently.For this reason, it is necessary to know how far the level of awareness of Javanese phonology in elementary school teacher candidates.Method: This research was a descriptive qualitative.The data were collected through observation and documentation in the form of student assignments regarding the skills of writing Javanese words, syllables, onset, rhythm, and phonemics, then analyzed constructively.Results: The study showed that the level of phonological awareness of Javanese language teacher candidates for elementary school was still low.Lots of mistakes in writing words.Conclusion: Javanese language teacher candidates have low awareness of Javanese language phonology, so it is necessary to increase mastery of other language materials, and it can be ensured that it also has an effect on the learning outcomes of Javanese language learning for elementary school students.
Gamification in education: threats or new opportunities

This article discusses the expediency and efficiency of implementing gamification in education. This study is a meta-analysis of the modern experience of gamification application obtained from numerous international studies, practical cases, and reports of educational entities. The influence of gamification technologies on cognition and learning processes was proved by hardware neurobiological research of students’ brain activity during a game using electroencephalography, functional magnetic resonance tomography, and functional near-infrared spectroscopy. On the basis of an analysis of gamification effects regarding efficiency improvement due to perceptive learning, the conclusions were obtained used in a generalized list of opportunities, problems, and threats of application of gamification elements in education. This study systematizes practical results presented by corporate cases and reference literature, which mention the necessity to use specialized online platforms or automated control systems for systematic implementation of gamification into education. The practical cases in the context of education considered the results of gamification application mainly as positive; however, at the same time, negative results were mentioned, which should be analyzed and which also should be included in the list of threats in this study.
Attacking FPGA-based Dual Complementary AES Implementation Using HD and SD Models

Field-programmable gate arrays (FPGAs) are widely used in many fields because of their low power consumption, easy design and good performance. For applications running on FPGAs, security is very important. A lot of researches have been done on the security issue of FPGA implementations, many attacks and countermeasures have been proposed. The dual complementary strategy is a countermeasure designed to thwart side channel attacks. In this paper, we perform Correlation Power Analysis (CPA) against dual complementary AES implemented on the SAKURA-G FPGA board. For dual complementary AES with constant Hamming Weight (HW) value, which is demonstrated to be robust against CPA based on HW model, we successfully recover the secret key using Hamming Distance (HD) and Switching Distance (SD) models with 2,000 power traces. For dual complementary AES with constant HD, 16,000 resp. 10,000 power traces are required to recover the key with HD resp. SD model.
A Gender Recognition System Using Facial Images with High Dimensional Data

Gender recognition has been seen as an interesting research area that plays important roles in many fields of study. Studies from MIT and Microsoft clearly showed that the female gender was poorly recognized especially among dark-skinned nationals. The focus of this paper is to present a technique that categorise gender among dark-skinned people. The classification was done using SVM on sets of images gathered locally and publicly. Analysis includes; face detection using Viola-Jones algorithm, extraction of Histogram of Oriented Gradient and Rotation Invariant LBP (RILBP) features and trained with SVM classifier. PCA was performed on both the HOG and RILBP descriptors to extract high dimensional features. Various success rates were recorded, however, PCA on RILBP performed best with an accuracy of 99.6% and 99.8% respectively on the public and local datasets. This system will be of immense benefit in application areas like social interaction and targeted advertisement.
Technology use in secondary level of English language teaching: A Literature Review

Technology has been widely used in the education field, especially for teaching language. Many teachers and students believe in the advantages of technology to enhance language learning. There have been many studies investigating the use of technology in secondary language classrooms. Some studies approve that technology can be applied to increase students' language competence. This paper comprehensively analysed the use of technology for English language teaching in the secondary level based on empirical studies. It reviews 57 articles from reputable journals and publishers. The existing literature shows that studying and reviewing the use of technology in ELT leads to a deeper understanding of its potential benefits. Many technology tools have been utilized to support the teaching of English skills. Kinds of learning activities that require technological tools and applications, such as presentation, discussion, assessment are also discussed. Additionally, problems and solutions encountered in the implementation of technology in secondary ELT levels are scrutinized in this study.&#x0D; HIGHLIGTS:&#x0D; &#x0D; Scholars need to set the content and pedagogy first before the technology to obtain meaningful and contextual experiments and discussion in academic circumstances.&#x0D; The finding unveils a fact that technology use in the ELT context contributes more to students' learning strategies, such as learning motivation, engagement, collaborative work, rather than the improvement of students' learning outcomes.&#x0D; This finding can be a rationale to rectify the common logical fallacy encountered among studies that claimed that technology can improve particular language skill.&#x0D; &#x0D;
A conceptual framework for establishing trust in real world intelligent systems

Intelligent information systems that contain emergent elements often encounter trust problems because results do not get sufficiently explained and the procedure itself can not be fully retraced. This is caused by a control flow depending either on stochastic elements or on the structure and relevance of the input data. Trust in such algorithms can be established by letting users interact with the system so that they can explore results and find patterns that can be compared with their expected solution. Reflecting features and patterns of human understanding of a domain against algorithmic results can create awareness of such patterns and may increase the trust that a user has in the solution. If expectations are not met, close inspection can be used to decide whether a solution conforms to the expectations or whether it goes beyond the expected. By either accepting or rejecting a solution, the user’s set of expectations evolves and a learning process for the users is established. In this paper we present a conceptual framework that reflects and supports this process. The framework is the result of an analysis of two exemplary case studies from two different disciplines with information systems that assist experts in their complex tasks.
Multi-Aspect Sentiment Analysis Hotel Review Using RF, SVM, and Naïve Bayes based Hybrid Classifier

In the hotel tourism sector, of course, it cannot be separated from the role of social media because tourists tend to share experiences about services and products offered by a hotel, such as adding pictures, reviews, and ratings which will be helpful as references for other tourists, for example on the media online TripAdvisor. However, tourists' many experiences regarding a hotel make some people feel confused in determining the right hotel to visit. Therefore, in this study, an aspect-based analysis of reviews on hotels is carried out, which will make it easier for tourists to determine the right hotel based on the best category aspects. The dataset used is the TripAdvisor Hotel Reviews dataset which is already on the Kaggle website. And has five aspects, namely Room, Location, Cleanliness, Registration, and Service. A review analysis was carried out into positive and negative categories using the Random Forest, SVM, and Naive Bayes based Hybrid Classifier methods to solve this problem. In this study the Hybrid Classifier method gets better accuracy than the classification using one algorithm on multi-aspect data, namely the Hybrid Classifier got an average accuracy 84%, Naïve Bayes got an average accuracy 82.4%, Random Forest got an average accuracy 82.2%, and use SVM got an average accuracy 81%
Optimasi SVM Berbasis PSO pada Analisis Sentimen Wacana Pindah Ibu Kota Indonesia

President Joko Widodo decided to move the capital city of the country outside Java. The relocation of the capital city is contained in the 2020-2024 National Medium-Term Development Plan. Community response to this has been mixed through national television and social media, especially Twitter. The tendency of Twitter users to respond to the government discourse can be seen with sentiment analysis. Sentiment analysis is one of the areas of Natural Language Processing (NLP) that builds systems for recognizing and extracting opinions. In this study, the Feature Selection PSO algorithm in the classification of the SVM model is proposed to improve the resulting accuracy in the sentiment analysis of moving capital cities. Experiments on the data of 1,319 tweets (457 positive sentiments and 862 negative sentiments) indicate an increase in accuracy by 2.09% from 79.06% to 81.15%, with the classification category is “Good Classification”.
Development of Interactive Ebook Taksi (Fiction Story) As a Media of Literary Appreciation Skills

Literary appreciation is the skill of understanding, living, and giving opinions on a literary work. Observations of literary appreciation learning in 3 elementary schools showed literary appreciation learning by lecture method, and 66% of children had difficulty appreciating stories. The purpose of this research is to develop an media interactive ebook Taksi (Fiction Story) that deserves to be used in the study of literary appreciation. This type of research is Research and Development (RnD) uses Borg and Gall development models that have been adapted using 7 steps (potential and problems, data collection, product design, design validation, design revision, readability test, product revision). Data analysis using descriptive quantitative. The percentage feasibility of interactive ebook Taksi (1) material and language experts is 86% (2) multimedia and learning media experts by 85%. Teacher readability test results by 88%. Student readability test results by 99%. Thus, media interactive ebook Taksi deserves to be used as a learning medium.
Phytoremediation Of Crude Oil Impacted Soil Using Purple Nutsedge

The present study investigated the viability of purple nutsedge in the phytoremediation of a crude oilcontaminated land in the Kom-Kom community, Oyigbo, Rivers state, Nigeria. 150g of soil samples were randomly collected from two (2) different points on the polluted site and a control site and analyzed for Petroleum Aromatic Hydrocarbons (PAHs), Total Petroleum Hydrocarbons (TPH) and Heavy metals ( Pb, Cd, Cr &amp; Ni). in soils and plants before and after phytoremediation. Plants were transplanted into the contaminated and contaminated soil after soil sample collection.After planting,the progress of plant growth was observed and recorded biweekly for 3 months before harvesting. From the results obtained, over 80% and 66% PAHs and TPHs phytodegradation efficiencies were achieved using the plant while Cd, Pb and Cr were removed by 90%, 67% and 39.2% respectively. The Bioaccumulation Factor (B.F) of the heavymetals in study plant were found to be greated than 1 which makes it suitable for phytoextraction of heavy metals. Therefore, the study suggests that purple nutsedge can be useful in the phytoremediation of a crudeoil polluted soil.&#x0D; Keywords: Hydrocarbons, Heavy metals, Phytoremediation, Crude oil, Purple nutsedge
Autonomous Navigation Using Deep Reinforcement Learning in ROS

For an autonomous robot to move safely in an environment where people are around and moving dynamically without knowing their goal position, it is required to set navigation rules and human behaviors. This problem is challenging with the highly stochastic behavior of people. Previous methods believe to provide features of human behavior, but these features vary from person to person. The method focuses on setting social norms that are telling the robot what not to do. With deep reinforcement learning, it has become possible to set a time-efficient navigation scheme that regulates social norms. The solution enables mobile robot full autonomy along with collision avoidance in people rich environment.
Foundations of Ring Sampling

Abstract A ring signature scheme allows the signer to sign on behalf of an ad hoc set of users, called a ring. The verifier can be convinced that a ring member signs, but cannot point to the exact signer. Ring signatures have become increasingly important today with their deployment in anonymous cryptocurrencies. Conventionally, it is implicitly assumed that all ring members are equally likely to be the signer. This assumption is generally false in reality, leading to various practical and devastating deanonymizing attacks in Monero, one of the largest anonymous cryptocurrencies. These attacks highlight the unsatisfactory situation that how a ring should be chosen is poorly understood. We propose an analytical model of ring samplers towards a deeper understanding of them through systematic studies. Our model helps to describe how anonymous a ring sampler is with respect to a given signer distribution as an information-theoretic measure. We show that this measure is robust – it only varies slightly when the signer distribution varies slightly. We then analyze three natural samplers – uniform, mimicking, and partitioning – under our model with respect to a family of signer distributions modeled after empirical Bitcoin data. We hope that our work paves the way towards researching ring samplers from a theoretical point of view.
USING PICTURES AS TEACHING MEDIA IN WRITING DESCRIPTIVE TEXT (A Pre-Experimental Study at one of Junior High School in Garut, West Java, Indonesia)

This research investigated “Using Picture as Teaching Media in Writing Descriptive Text”. It enhanced the ability to write descriptive in one of junior high school in Garut. The purpose of the research was to know the effect of using pictures on students’ writing ability in descriptive text. The research population was the eighth grade students. The researcher used a written test to collect data. The research design was quantitative experimental. Data were collected through pre-test and post-test. The technique used in analyzing the data was t-test formula. It was used to determine whether there was a significance difference between the pre-test and post-test. The result of the test between pre-test and post-test, the mean of pre-test was 59.63 and the mean of post-test was 75.17 The obtained t- test was tobserved = 12.51 and tcritical = 2.0452. The result showed that tobserved greater than tcritical (12.51 &gt; 2.0452). The tobserved was in the area H0 rejected it means H0 was rejected so Ha was accepted. So it can be concluded that using the pictures as teaching media is effective to develop students’ ability in writing descriptive text after being given the treatments. The result of the research was expected to consider teachers to practice the use pictures as teaching media in writing descriptive text. . It would developed students’ writing skill easily.