Reviewerly/exHarmony huggingface dataset:
Super-Exponential Growth in Models of a Binary String World

The Theory of the Adjacent Possible (TAP) equation has been proposed as an appropriate description of super-exponential growth phenomena, where a phase of slow growth is followed by a rapid increase, leading to a “hockey stick” curve. This equation, initially conceived to describe the growth in time of the number of new types of artifacts, has also been applied to several natural phenomena. A possible drawback is that it may overestimate the number of new artifact types, since it does not take into account the fact that interactions, among existing types, may produce types which have already been previously discovered. We introduce here a Binary String World (BSW) where new string types can be generated by interactions among (at most two) already existing types. We introduce a continuous limit of the TAP equation for the BSW; we solve it analytically and show that it leads to divergence in finite time. We also introduce a criterion to distinguish this type of behavior from the familiar exponential growth, which diverges only as t → ∝. In the BSW, it is possible to directly model the generation of new types, and to check whether the newborns are actually novel types, thus discarding the rediscoveries of already existing types. We show that the type of growth is still TAP-like, rather than exponential, although of course in simulations one never can observes true divergence. We also show that this property is robust with respect to some changes in the model, as long as it deals with types (and not with individuals).
A Review of Machine Translation: Implications to Human Translators and Translation Teaching

Machine translation has witnessed great development in the recent decades and we have entered the era of neural machine translation (NMT).A review of MT is necessary for a better understanding of the relationship between MT and human translators and translation teaching in this era when MT has flourished.This paper first briefs the machine translation (MT) development in the past decades, focusing on the features, application, and drawbacks of each main paradigm of rule-based machine translation (RBMT), corpus-based translation (CBMT), and long-short term memory (LSTM), a main paradigm of NMT.It continues with a discussion of what MT means to human translators and translation teaching in universities.It concludes that MT should not and could not replace human translators which will always be vital in some fields and aspects; only a good integration between the two can ensure satisfying output with post-editing by human translators to meet the increasingly demanding market.This signifies that translation teaching in universities should embrace MT knowledge.
THE USE OF MONOPOLY GAME AS A TEACHING MEDIA TO ENHANCE STUDENTS’ ABILITY IN PRESENT CONTINUOUS TENSE (A Classroom Action Research at the Eighth Grade of SMP Katolik Unggulan Santa Maria Timika)

Grammar is the basic knowledge of language to understand English perfectly. Some students who study English face difficulties in understanding grammar, especially in mastering present continuous tense. The teacher must find new techniques to improve the students' mastery in grammar. Monopoly game is one of the techniques used to assist students in mastering present continuous tense. The aim of this research was to find out the implementation of Monopoly Game as teaching media in improving the students’ ability in learning present continuous tense. Method: This research applied classroom action research to collect the data, which was carried out through four steps. They were planning, action, observation, and reflection. The subjects of this study were 31 students at the eighth grade of SMP Katolik Unggulan Santa Maria Timika in the academic year of 2022/2023. The research findings showed that there was a development on the students’ ability in present continuous tense. It was proven by the mean score of pre-test was 28, the mean score of post-test in the cycle I was 50, and the mean score of post-test in the cycle II was 72. The percentage of the students’ score in the pre-test was 3,2%, and the percentage of the students’ score in the post test of the cycle I improved into 32%. It means that there was improvement as much as 28,8%. Then, the percentage of the students’ score in the post test of the cycle II was 77%. It means that the improvement was 73,8%. From the data above, it is indicated that using Monopoly Game as teaching media in learning present continuous tense was effective. It can be concluded that the students’ ability in present continuous tense had been improved by using Monopoly Game as the teaching media
AN ANALYSIS OF SPEAKING ACHIEVEMENT OF EXTROVERT AND INTROVERT STUDENTS AT THE SECOND YEAR STUDENTS OF ISLAMIC EARLY CHILDHOOD EDUCATION STUDENTS OF STITNU SAKINAH DHARMASRAYA

Personality is the part that influences student learning behavior. This behavior is significant in the teaching process. Two types of student personalities affect student learning behavior: open personality and closed personality. Students with available personalities are friendly, have many friends, and love to chat and collaborate with classmates. Meanwhile, students with introverted personalities tend to be quiet, shy, and aloof. This study intends to understand the spoken language scores of students with open and closed personalities. The sample from this study is 36 second-semester students of STITNU Sakinah Dharmasraya in the 2021/2022 academic year consisting of 18 students with open personalities and 18 students with closed personalities taken using stratified random sampling techniques. In collecting data, researchers used two types of research instruments. First is the personality test. The personality test aims to find the student's personality type between open and closed. The second is the speaking test which seeks to find the student's speaking score. The study results found that students with available personalities obtained good speaking scores (71. 66), and students with closed personalities received lower speech scores (49.55)
Toward Culturally and Linguistically Responsive E-Learning in Post-COVID-19 Higher Education: Perspectives from the United Arab Emirates

The COVID-19 pandemic has caused dramatic shifts in education worldwide. In the spring of 2020, universities abruptly moved to emergency remote teaching and learning (ERT&amp;L), with online and hybrid education continuing into the post-pandemic era. In the Gulf, cultural, religious, and sociolinguistic dynamics can present additional challenges for teaching and learning online. Reluctance to use cameras due to modesty, privacy, and E-safety concerns, amongst others, affects interaction and rapport. This article presents empirical data from a qualitative phenomenological case study investigating male and female Emirati university students’ (n = 107) perspectives on access, interaction, and engagement during Zoom classes in the fall of 2020 and spring of 2021. Students’ reflective essays and researcher observations revealed that intersecting factors, such as gender, religion, culture, linguistic challenges in English-medium universities, and fear of judgment, affected participants’ comfort levels and learning effectiveness in online classes. Data are analyzed through interpretive phenomenological analysis and the analytical tool of intersectionality, through which complexities of learner identities are explored. Practical suggestions are made on adapting online and hybrid learning to suit the sociocultural realities of Gulf states better by enhancing interaction and engagement in online classes without compromising comfort, E-safety, and privacy in post-pandemic education
THE DEVELOPMENT OF DIGITAL BOOK BASED ON A METACOGNITIVE APPROACH TO FRACTION OPERATIONS FOR CLASS V ELEMENTARY SCHOOL

This study aims to determine the validity, practicality, and effectiveness of learning books based on metacognitive approaches in arithmetic operations mathematics lessons. This type of research is ADDIE model development research. Data collection techniques in this study were observation, interviews, validation, and tests. This research was conducted in class V. The results showed The product was valid in terms of media by 88%, in terms of material by 93.8%, and in terms of language by 92%; The product gets a positive response from users; and The percentage of classical learning completeness reaches 85% or most of the learning outcomes are as complete as stated.
MDL-LDA Agile Method v1

As a guide in modeling the document labels using Latent Dirichlet allocation for archived documents in an Integrated Quality Assurance System (IQAS), the researchers used the agile method as it promotes flexibility, speed, and, most importantly, continuous improvement in developing, testing, documenting, and even after delivery of the software. Since the phases of this model are light, the teams are not bound by a rigid systematic-based process on pre-set constraints and restrictions as some other models, like the waterfall model, and can adjust changes whenever they are needed. This flexibility on every stage propagates creativity and freedom within processes. Furthermore, development teams can modify and re-prioritize the backlog, allowing for speedy implementation
Implementation of Minatku Application as Alternative Information in the Selection of FurtherStudy for Junior High School Students

This article aims to assess the application of Minatku as alternative information in choosing further studies for junior high school students.The assessment of the Minatkuapplication as a result of the study aims to measure the User Experience of the Minatku application through the User Experience Questionnaire (UEQ).The method used in this research is descriptive quantitative, involving 35 junior high school students to fill out the UEQ questionnaire.The instrument consists of 6 rating scales consisting of attractiveness (DT = 1,476), clarity (KJ = 1,236), efficiency (E = 1,514), accuracy (KT = 1,321), simulation (SM = 1,421) and novelty (KB = 0,693 ). .The UEQ test data shows that the Minatku application has a good efficiency in testing the interest of junior high school students in providing options for further studies.Therefore, junior high school students canuse the Minatku application to study the factors that influence the selection of junior high school students to continue further studies based on student interests.
Application of the Spider Web Integrated Learning Model ( Webbed ) to Student Learning Activities

Learning activity is a fundamental principle in learning interactions.Student learning activities can be seen in the learning process, such as listening, asking questions, reading, writing, and responding, but at SMP Negeri 10 Padang, student learning activities still need to be more visible.Therefore, the purpose of this study was to analyze the application of the webbed learning model to the learning activities of students in social studies class VIII.2 at SMP Negeri 10 Padang.The research results on the webbed learning model were conducted in class VIII.2.We can see student activity in the learning process by applying the webbed learning model.Student learning activities such as listening, asking, reading, writing, and responding increased compared to learning before using the webbed learning model..
The Role of Bunda Literasi in Realizing Women's Social Inclusion in Jembrana Regency, Bali

The literacy rate of women is lower than that of men.For this reason, many programs and activities have been implemented to reduce this gap.In one of the government's efforts to mobilize public literacy, bunda literasi (mother of literacy) was confirmed as a literacy ambassador in various regions in Indonesia.This study aimed to explore bunda literasi programs for women in Jembrana Regency as an effort to increase the community's literacy index in Jembrana regency Bali.This research uses the descriptive qualitative method, where data were collected through in-depth interviews and observations.Data were analyzed using an interactive model following data reduction, presentation, interpretation, and conclusion.The results showed that most bunda literasi programs were integrated with other programs in which the bunda literasi was, at the same time, the bunda PAUD, the team leader of the PKK (Family Empowerment and Welfare), and the wife of the regent of Jembrana Regency.This condition is beneficial in terms of effectiveness but has yet to be able to focus on activities to increase literacy culture.
Hypothetical Model of ICT-Based Learning Media Management in Non-Formal Education

ICT-based learning media is the time to be introduced and mastered by teachers to be then used in the learning process in the class so that the material presented can be absorbed by students optimally.Learning activities that use teaching aids and good learning media have been proven in theory to improve learning outcomes.This condition applies to learning that occurs in formal education, such as at school and NFE.This study focuses on developing a hypothetical model of ICT-based learning media management in NFE by using a qualitative approach with a descriptive case study type at three centers of community learning activities and nonformal education in West Java, Indonesia.The results of this study are just a product that is expected to be a reference model in implementing ICT-based learning media management in NFE, especially in centers of community learning activities.
APLIKASI PEMBELAJARAN HURUF HIJAIYAH BERBASIS ANDROID

Making the Belajar Mengaji application discusses learning hijaiyah letters. This study aims to help parents introduce hijaiyah letters to their children. In addition, it can make it easier for users to understand and learn hijaiyah letter material and its punctuation anywhere and anytime. The Belajar Mengaji application can be used by users to view material in the form of hijaiyah letters and punctuation marks and is equipped with practice questions about hijaiyah letters to hone users' skills, which are also equipped with sound effects.Belajar Mengaji application was created using Android Studio with Java and XML Programming Language. The method used in this study is the SDLC (System Development Life Cycle) method, which consists of planning, analysis, design, manufacture, and implementation, as well as device testing. This application has been successfully created and implemented on an Android smartphone with a minimum layer criterion of 5 inches and the Android 5.1 (Lollipop) operating system, so that it is running as expected.
FullStop: Punctuation and Segmentation Prediction for Dutch with Transformers

Abstract When applying automated speech recognition (ASR) for Belgian Dutch (Van Dyck et al. 2021), the output consists of an unsegmented stream of words, without any punctuation. A next step is to perform segmentation and insert punctuation, making the ASR output more readable and easy to manually correct. As far as we know there is no publicly available punctuation insertion system for Dutch that functions at a usable level. The model we present here is an extension of the models of Guhr et al. (2021) for Dutch and is made publicly available. We trained a sequence classification model, based on the Dutch language model RobBERT (Delobelle et al. 2020). For every word in the input sequence, the models predicts a punctuation marker that follows the word. We have also extended a multilingual model, for cases where the language is unknown or where code switching applies. When performing the task of segmentation, the application of the best models onto out of domain test data, a sliding window of 200 words of the ASR output stream is sent to the classifier, and segmentation is applied when the system predicts a segmenting punctuation sign with a ratio above threshold. Results show to be much better than a machine translation baseline approach.
The Impact of GloVe and Word2Vec Word-Embedding Technologies on Bug Localization with Convolutional Neural Network

In the field of software engineering, software quality assurance faces many challenges, including overcoming the problem of identifying errors in the source code. Finding the location of the error in the source code is a very important process, as is taking advantage of the semantic information available in the bug reports and the source code to find the similarities between them, using modern techniques called word embedding. This study aims to demonstrate how GloVe and Doc2Vec word-embedding technologies affect bug localization accuracy and performance. Therefore, this study proposes to adapt DeepLoc by using GloVe embedding techniques to process the source code instead of Word2vec and using Word2vec embedding techniques to process the bug report instead of Sent2Vec. AspectJ represents the large dataset, which contains many bug reports, while SWT's small dataset contains fewer bug reports. Experimental results show that the improved DeepLoc on SWT achieves 0.60 and 0.72 MAP and MRR, respectively. While the improved DeepLoc on AspectJ achieves 0.17 and 0.27 MAP and MRR, respectively. The results of the improved DeepLoc should be compared using two advanced models from previous studies: DeepLoc, DeepLocator.
Crypto Price Prediction as an Investment Opportunity: An Empirical Study of Three Global Cryptocurrencies

Aims: To determine the investment feasibility of evaluating cryptocurrency opportunities as an investment product under the possibility of crypto price valuation selection. The study analyzes three indicators: asset price returns in unrelated time, selection of cryptocurrency investment price weights, and crypto price forward contract opportunities on ARCH-GARCH probability forecasts in the selection of price valuations by individual cryptocurrency prices.&#x0D; Study Design: Quantitative research.&#x0D; Place and Duration of Study: The period from 10 September 2021 to 4 September 2022 using sample data downloaded from the Yahoo Finance website database with metric data retrieval bound in amount, data quantity, or distance relative to writing opportunities to examine the distribution of the amount of research data.&#x0D; Methodology: This study employed Bitcoin (BTC), Ethereum (ETH), and Tether (USDT) cryptocurrencies as the research objects with used panel and multiple regression analysis methodologies and using forecasting the appropriate ARCH and GARCH methods&#x0D; Results: The results show that the prediction of future crypto price selection in BTC and ETH tokens has a probability of 78.6% and 59.6%, respectively. The study highlights the prediction of future BTC and ETH price selection with 79.21% and 78.64% forecast results as found in the ARCH-GARCH(1, 0, 1) technique. Meanwhile, USDT token has no possibility to be forecasted in the future, leaving a 7.3% possibility of crypto price selection under probability by investors in the form of high (or different) price fluctuation inequalities.&#x0D; Conclusion: Conclusions could state that the partial (combined) selection of crypto coin price assessments and individual crypto assets can reduce the expected return from the selection of the asset price so that this form of investment in crypto assets can reduce the level of observation of return on wealth from crypto assets for investors especially in expecting the chance on that investment.
Application of the SMART Method in Teaching the Module "Scientific Education" in Students

Rapidly developing computer information technology is bringing significant changes in all aspects of our daily lives. It is no secret to all of us that at present society cannot be imagined without Information Communication Technologies. In general, the development of each country can be judged by the introduction of modern information and communication technologies into the industry. The innovative activity of pedagogues is the main factor in the reform of the education system. One of the most important aspects of modern education is the achievement of the innovative character of the pedagogical activity. The more innovation there is in the pedagogical activity, the better understanding of the teacher's own experiment can be achieved. In it, the teacher participates widely in creating, applying and improving innovation as the subject and organizer of the innovation activity. They seek to analyze the content in science and the essence of changes in knowledge and traditions. This article highlights the importance of using the "mental method" in teaching the" scientific education " module in the development of innovative activities of students of higher educational institutions in an informed environment.
Cloud Backup and Restore

Digital devices are prone to failure. An increasing range of cloud backup solutions aim to ensure that no matter what should happen to a user’s device, their files and data can be quickly re-downloaded and reinstalled on a new device with ease. Whereas the failure or breakdown of a digital device may once have resulted in a potentially devastating data loss event, cloud backup and recovery tools now work to reduce the disruptive impact of device failure. This has implications for theories of failure that are based on the premise that breakdown or failure are disruptive events. Drawing on Apple’s cloud-based data backup and restore service, this chapter conceptualises the cloud as an infrastructure designed to anticipate and absorb digital failure. In doing so, it explores how cloud services bolster cultures of routine device upgrading and e-waste production.
Image Classification Using Contrastive Learning

This chapter aims to present recent implementation of contrastive self-supervised learning algorithm SimCLR, a simple framework for contrastive learning of visual representations. Our work explores how to learn these visual representations by consistently studying the most important parts of the framework. We have shown that composition of data augmentation operations plays an important role in predictive tasks, introducing a stable and learnable nonlinear transformation between the illustration and the contrastive loss improves the standard of the learned representations, and SimCLR framework’s contrastive learning produces better predictions on using larger batch sizes and additional training steps compared to supervised learning, but for better results, greater computational power is also required, which we plan to do as a part of our future work. A supervised ResNet-18 classifier showed an accuracy of 76.8 percent, which is 12 percent more than the accuracy of 64.8 percent achieved by a linear classifier trained on 10 percent of the self-supervised image representations learned by SimCLR.
Adapting to game trees in zero-sum imperfect information games

Imperfect information games (IIG) are games in which each player only partially observes the current game state. We study how to learn $\epsilon$-optimal strategies in a zero-sum IIG through self-play with trajectory feedback. We give a problem-independent lower bound $\widetilde{\mathcal{O}}(H(A_{\mathcal{X}}+B_{\mathcal{Y}})/\epsilon^2)$ on the required number of realizations to learn these strategies with high probability, where $H$ is the length of the game, $A_{\mathcal{X}}$ and $B_{\mathcal{Y}}$ are the total number of actions for the two players. We also propose two Follow the Regularized leader (FTRL) algorithms for this setting: Balanced FTRL which matches this lower bound, but requires the knowledge of the information set structure beforehand to define the regularization; and Adaptive FTRL which needs $\widetilde{\mathcal{O}}(H^2(A_{\mathcal{X}}+B_{\mathcal{Y}})/\epsilon^2)$ realizations without this requirement by progressively adapting the regularization to the observations.