Reviewerly/exHarmony huggingface dataset:
Feature subset selection for kernel SVM classification via mixed-integer optimization

We study the mixed-integer optimization (MIO) approach to feature subset selection in nonlinear kernel support vector machines (SVMs) for binary classification. First proposed for linear regression in the 1970s, this approach has recently moved into the spotlight with advances in optimization algorithms and computer hardware. The goal of this paper is to establish an MIO approach for selecting the best subset of features for kernel SVM classification. To measure the performance of subset selection, we use the kernel-target alignment, which is the distance between the centroids of two response classes in a high-dimensional feature space. We propose a mixed-integer linear optimization (MILO) formulation based on the kernel-target alignment for feature subset selection, and this MILO problem can be solved to optimality using optimization software. We also derive a reduced version of the MILO problem to accelerate our MILO computations. Experimental results show good computational efficiency for our MILO formulation with the reduced problem. Moreover, our method can often outperform the linear-SVM-based MILO formulation and recursive feature elimination in prediction performance, especially when there are relatively few data instances.
Practice of Artificial Intelligence and Virtual Reality Technology in College English Dialogue Scene Simulation

English is regarded as one of the most important business languages in the world. Various technologies have been developed to aid language acquisition in this field. The academic and corporate worlds are both responding favorably to technology intrusion in business communication abilities. The new normal condition is presenting a plethora of options to study a language, particularly English for nonnative speakers, using one of the immersive platforms, virtual reality. Striving people must improve their fluency and proficiency in order to stay competitive in the commercial sector. Learners might benefit from considering business-specific English in this situation. The research examines how virtual reality (VR) allows learners to experience business-related situations in a hands-on manner. It also addresses scenarios in which learners might maximize their professional potential. A mixed methodology study demonstrates how virtual reality technologies may be used to enhance English communication abilities. It discusses how different VR applications may pique learners’ attention and passion, as well as several strategies for improving Business English.
Content Moderator Startle Response: A Qualitative Study

Commercial Content Moderators review user-generated content (UGC) to ensure the posts meet platform policies, guidelines, community standards, and regional laws. While the majority of posted UGC is deemed acceptable, a large amount of content remains, which is classified as non-compliant and may include gore, violence, suicide, child sexual abuse material (CSAM), and pornography, to name a few. Because of this, content moderators have a greater prevalence of their nervous system activating a startle response, which can impact emotional, psychological, and physiological processes. Prior research on content moderators has failed to explore moderators' initial reactions to content from the start of employment through tenure as the subjection to material and habituation increases. This study takes an in-depth look at moderators' experiences from recruiting, through training, and production to better understand the content moderators' startle response and factors that enable startle habituation. The current study sample consisted of a total of 78 respondents - 38 content moderators located in the Philippines employed by TaskUs Inc. and 40 content moderators located in Estonia employed by Sutherland Global Services. Employee tenure ranged from 0-6 months. Succeeding our analysis, transparency, understanding, and preparedness were major themes identified as the critical factors found within both companies when exploring the activation of the startle response and facilitation of habituation following content exposure. These themes were prevalent in the recruiting, training, and production phases of the employment life-cycle.
ESL Teachers’ Attitude and Motivation towards CEFR Implementation

The alignment of English language education according to Common European Framework of Reference (CEFR) is important to ensure that the English education landscape in Malaysia is comparable international standard.English language teacher have to constantly adapt and improve their proficiencies in the language accordingly and be mentally prepared to implement CEFR framework in school.Hence, this study investigates the correlation between English Language teachers' attitude and motivation in regards to Common European Framework of Reference (CEFR) implementation in education policy in Malaysia.A questionnaire which consists of 30 items with five-point Likert scale was administered to 242 primary and secondary school English teachers in two districts of Negeri Sembilan, Malaysia.The relationship between the variables was established using Spearmen-Rho correlation and the finding shows that there was a strong positive relationship between English as Second Language teachers' attitudes and their motivation level towards CEFR implementation.Hence, based on the result, it can be indicated that when teachers possess positive attitudes and acceptance to CEFR implementation will directly improve their motivation level thus, becoming a push factor for them in ensuring the positive outcome of CEFR implementation.
Efektivitas Pembelajaran Daring, SwayVS Form SD Negeri Kedunggubah

The development of education today is influenced by the rapid progress of information and communication technology. One of the information technologies that play a role in the world of education is online learning. Online learning functions as a liaison between educators and students with an internetnet work that can be accessed anytime and anywhere. The online media used by the research subjects were various (Sway,Form). The purpose of this study is to identify online learning activities at the homes of students as an effort to support government programs, namely study from home during the Covid 19 pandemic and to analyze the effectiveness of online learning. The method used in data collection was a question and answer session to sources,namely primary school teachers through interviews. The results showed that online learning that was carried out at home made students more independent and created motivation to learn. Inaddition, online learning is one of the successes in creating social distancing behavior soas to minimize the appearance of crowds which are considered to have the potential to spread Covid19 in the school environment. However, it is still ineffective in its implementation due to various obstacles such as economic capability, mastery of technology, internet quota, and inadequate network.
Investigating Teachers Grading Perceptions, Current Grading Habits and Their Views Towards Classroom Assessment Grading Practice

This study empirically investigated teachers' perceptions, current assessment grading practices, and views towards classroom assessment grading practice. The study randomly sampled 204 teachers and utilized three questionnaires for data collection. Cronbach Alpha Coefficient established the reliability of the various questionnaires. Frequency counts and percentages were used to answer the study research questions, while Pearson correlation was employed to test the study hypotheses. The study found that teachers do not positively perceive assessment grading practice, included non-achievement factors when grading students' assessments and used subjective knowledge when grading assessments. However, teachers viewed the assessment grading practice as an essential tool for quantification of students learning. Subsequently, significance difference was found between teachers' experience and teachers' perception towards assessment grading practice and views on the classroom importance of assessment grading practice. Nonetheless, no significant difference was found between teachers experience and teachers' current classroom grading habits.
DESIGN AND DEVELOPMENT OF AUTHENTIC MATERIAL BY USING LITERATURE IN ENGLISH LANGUAGE TEACHING

The purpose of this paper is to discuss an attempt to incorporate the use of literature in English language teaching. As a result, language teachers must be aware of several key concepts, including the types of literature that can be used for teaching purposes, the approach to using literature in language teaching, the underlying reasons for using literature in language teaching, and the steps to implementing the use of literature in language classrooms. The most fundamental idea of this paper is focused on the steps to use literature in English language teaching, namely, making a decision about needs analysis to know: the types of literary works that the learners want to learn, the difficulty level of the selected literary works in terms of grammar, lexical items, and text patterns, and ensuring that a literary work brings pleasure and enjoyment to the learners, formulating objectives to describe what the learners will be able to do. Language teachers can use the techniques to teach English through literature.
Demystifying Approximate Value-based RL with $ε$-greedy Exploration: A Differential Inclusion View

Q-learning and SARSA with $ε$-greedy exploration are leading reinforcement learning methods. Their tabular forms converge to the optimal Q-function under reasonable conditions. However, with function approximation, these methods exhibit strange behaviors such as policy oscillation, chattering, and convergence to different attractors (possibly even the worst policy) on different runs, apart from the usual instability. A theory to explain these phenomena has been a long-standing open problem, even for basic linear function approximation (Sutton, 1999). Our work uses differential inclusion to provide the first framework for resolving this problem. We also provide numerical examples to illustrate our framework's prowess in explaining these algorithms' behaviors.
Exploring Language Learning Strategies in Enhancing Writing Skills Employed by Secondary School Successful Learners

Language learners require different strategies in language learning including in specific skills that they want to be good at.However, acquiring a language skill could pose some major challenges to some learners.In relation to that, this study aims to identify the most and least popular language learning strategies used in writing by secondary school successful learners.Purposive sampling was used in selecting 40 high English proficient students as the respondents from an urban secondary school in Sarawak.The Young Learners' Language Strategy Use Survey by Cohen and Oxford (1990) was adopted which was further analysed by using a descriptive analysis method.It was found out that 31 participants preferred reading what they wrote to see if it is good enough as the most popular language learning strategy in writing.Meanwhile, the least popular language learning strategy selected by the participants is using words from their own language but adding new endings to those words.With advancement of technology used specifically for education, it is recommended that schools to provide electronic tools or gadgets to help students make their skill learnt all the way into their writing activities.It is hoped that this study will provide some meaningful insights to the language learning strategies used among successful learners to enhance their writing skills especially for the betterment of English language teaching and learning.
Towards a Coq formalization of a quantified modal logic

We present a Coq formalization of the Quantified Reflection Calculus with one modality, or $\mathsf{QRC}_1$. This is a decidable, strictly positive, and quantified modal logic previously studied for its applications in proof theory. The highlights are a deep embedding of $\mathsf{QRC}_1$ in the Coq proof assistant, a mechanization of the notion of Kripke model with varying domains and a formalization of the soundness theorem. We focus on the design decisions inherent to the formalization and the insights that led to new and simplified proofs.
Feature Learning in $L_{2}$-regularized DNNs: Attraction/Repulsion and Sparsity

We study the loss surface of DNNs with $L_{2}$ regularization. We show that the loss in terms of the parameters can be reformulated into a loss in terms of the layerwise activations $Z_{\ell}$ of the training set. This reformulation reveals the dynamics behind feature learning: each hidden representations $Z_{\ell}$ are optimal w.r.t. to an attraction/repulsion problem and interpolate between the input and output representations, keeping as little information from the input as necessary to construct the activation of the next layer. For positively homogeneous non-linearities, the loss can be further reformulated in terms of the covariances of the hidden representations, which takes the form of a partially convex optimization over a convex cone. This second reformulation allows us to prove a sparsity result for homogeneous DNNs: any local minimum of the $L_{2}$-regularized loss can be achieved with at most $N(N+1)$ neurons in each hidden layer (where $N$ is the size of the training set). We show that this bound is tight by giving an example of a local minimum that requires $N^{2}/4$ hidden neurons. But we also observe numerically that in more traditional settings much less than $N^{2}$ neurons are required to reach the minima.
Learning a Restricted Boltzmann Machine using biased Monte Carlo sampling

Restricted Boltzmann Machines are simple and powerful generative models that can encode any complex dataset. Despite all their advantages, in practice the trainings are often unstable and it is difficult to assess their quality because the dynamics are affected by extremely slow time dependencies. This situation becomes critical when dealing with low-dimensional clustered datasets, where the time required to sample ergodically the trained models becomes computationally prohibitive. In this work, we show that this divergence of Monte Carlo mixing times is related to a phenomenon of phase coexistence, similar to that which occurs in physics near a first-order phase transition. We show that sampling the equilibrium distribution using the Markov chain Monte Carlo method can be dramatically accelerated when using biased sampling techniques, in particular the Tethered Monte Carlo (TMC) method. This sampling technique efficiently solves the problem of evaluating the quality of a given trained model and generating new samples in a reasonable amount of time. Moreover, we show that this sampling technique can also be used to improve the computation of the log-likelihood gradient during training, leading to dramatic improvements in training RBMs with artificial clustered datasets. On real low-dimensional datasets, this new training method fits RBM models with significantly faster relaxation dynamics than those obtained with standard PCD recipes. We also show that TMC sampling can be used to recover the free-energy profile of the RBM. This proves to be extremely useful to compute the probability distribution of a given model and to improve the generation of new decorrelated samples in slow PCD-trained models.
Hubungan Antara Keaktifan Warga Belajar Dengan Hasil Belajar Pada Mata Pelajaran Matematika Program Paket B di PKBM

This research is motivated by the low learning outcomes of residents studying the Package B program at PKBM Tuah Sepakat Nagari Tanjung. It is suspected that this is caused by the lack of active learning of the learning community during the process. The aims of this study were to: 1) to describe the learning activities of the residents in PKBM Tuah Sepakat Nagari Tanjung, 2) to describe the learning outcomes of citizens studying mathematics at PKBM Tuah Sepakat Nagari Tanjung, and 3) to determine the relationship between learning residents and learning outcomes at Mathematics subject package B at PKBM Tuah Agreed Nagari Tanjung. This type of research is quantitative with a correlational approach. The population in this study was the Package B learning community program at PKBM Tuah Sepakat Nagari Tanjung which opened 70 people and the respondents in this study opened 30 people. The results of this study indicate that: 1) the learning activities of the residents in PKBM Tuah Sepakat Nagari Tanjung are still low, 2) the learning outcomes of students learning mathematics in PKBM Tuah Sepakat Nagari Tanjung are still low, and 3) there is a significant relationship between the activeness of the citizens studying with the results studying mathematics in the Package B program at PKBM Tuah Sepakat Nagari Tanjung.
A Protocol for Creating and Modifying the Outlier Detection System's General Framework

Abstract Early detection of outliers has major applications in various industrial domains such as machine failure detection, patient monitoring systems and early warning systems of natural disasters. Although many machine learning and deep learning techniques have developed in the last few years, training of these algorithms requires a large amount of labelled dataset. However, generation of hand labelled training dataset is time consuming and has less accuracy. Likewise, the artificial dataset should follow the characteristics of real time data. Hence, generation of a time series dataset following the rules of data generation aids data scientists to develop and evaluate different supervised models. This generated data can help experts to develop a general framework for outlier detection. Hyper parameter optimisation performed in this base model ensures maximum efficiency of the generated model. Once the base model is ready, experts from various domains can utilise the framework for outlier detection in their specific application by applying domain specific heuristics. A case analysis using atmospheric dataset is conducted in this paper that act as a guideline for adding domain specific heuristics into the base model.
Pemanfataan Komputer dan Internet Dalam Pendidikan dan Pembelajaran PAI

The growing era of digitalization requires that every aspect of life always depends on technology. This advanced technology has contributed greatly to the renewal of various aspects such as business, telecommunications, and even the world of education in particular. Departing from the various facts above, this paper is here to examine more deeply about the use of technology in PAI learning. This study aims to describe : 1) What is the urgency of advances in information technology in the world of education?2) How is the use of computers and the internet in education? 3) How is the use of modern technology through internet-assisted computers in PAI learning? The method used in writing this article is a literature study (library research) by exploring various important information related to the use of computer and internet technology in PAI learning, it can be in the form of books, journal articles, research results, news, reports, and various other important documents that are relevant to this study. Furthermore, after the data has been collected, an inductive analysis is then carried out to then find a relevant and comprehensive conclusion.
Libri d'altri, cataloghi di noialtri: le scritture non latine in SBN [Others' Books, Catalogues of our own: non-roman scripts in SBN]

The catalogue of the Italian National Library System (SBN) is a roman-script-only database. Local libraries, on the other hand, are facing requests from an increasing number of users from Asia and Africa, and are filling the gaps of the national system by developing isolated, non-collaborative ways to manage resources in non-Roman scripts.Though a couple of Institutions have recently, but independently each other, developed projects to catalogue resources in native scripts, it is still impossible to predict when this feature will be finally implemented. In the next future, Italian cataloguers will therefore still rely on romanization only. After having briefly reviewed the romanization methods recommended by the Italian cataloguing rules (REICAT), the article suggests to expand its repertoire by establishing a method for identifying the most suitable romanization standards.
Aplikasi Pengajuan Pembuatan KTP Online Berbasis Web di Kelurahan Argasunya Kota Cirebon

Argasunya village is an institution responsible for the management of community data in a government environment. The need for public service will involve the state as a public service provider and individual citizens as recipients. But there is no application about the design of the application for the creation of E-KTP online, for that the author tried to make the Final Task regarding the Application for Submission of E-KTP Online which until now has not existed in Argasunya Village. In the process of collecting data with the aim to solve the problem, the author uses methods with data collection techniques, namely by observation and interview. And to design the application, the author used prototype development methods. In order to solve the problem, an application was made to make E-KTP Online. The final result obtained in this study is an application that can make it easier for people to create E-KTP. With some of the advantages that this application has, the application for the creation of E-KTP Online should be able to further alleviate the tasks given to the village. It is expected that this application will always be well controlled in terms of accuracy and data validation can be accounted for so that the information generated will be even better.
Translation Strategies of News Articles in Universitas Gadjah Mada Official Website

This research examines the translation strategies applied in the translation of Indonesian articles published on the official website of Universitas Gadjah Mada English into English. The data were collected from 15 articles published in Bahasa Indonesia on the website and their English translations. The analysis and categorization were based on the news translation theory proposed by Bielsa and Bassnett (2009). The results show that all the news translation strategies were applied in the translation of the Indonesian news articles into English. Out of 227 data found in the research, 69 (30.40%) were translated using the elimination strategy, 57 (25.11%) the addition strategy, 24 (10.57%) the summarizing information strategy, 37 (16.30%) the change in the order of paragraphs strategy, and 40 (17.62%) the change of title and lead strategy.