Reviewerly/exHarmony huggingface dataset:
Assisting Struggling Early ESL Readers. What Can English Teachers Do?: A Review Paper

The teaching and learning of reading to struggling readers have become a distinguished area to be researched recently. Past studies discovered the effectiveness of the teaching and learning process involving early struggling readers in foreign countries. However, in Malaysia, the study of intervention in the teaching of reading to ESL readers is scarce. Hence, this paper reviews interventions and the findings of the effectiveness of the interventions in teaching reading to struggling ESL readers to provide the framework for Malaysian researchers and English educators dealing with struggling early ESL readers. This paper addresses issues that will help the struggling reader succeed. Several themes have emerged from research on identifying teaching strategies that support struggling readers in the classroom. Increased student engagement occurs when pairwork, reading with a reading specialist and playing reading games took place during the reading interventions to assist struggling readers. Moreover, explicit instruction in phonological awareness and ample opportunities to practise reading, both at home and at school, improve reading skills.
Rhodes: A Next-Generation OS based on Resource Governance Model

&lt;p&gt;At present, four types of OS kernels are widely available: monolithic kernels, microkernels, hybrid kernels, and exokernels. These kernel architectures are either too tightly-coupled such as monolithic, or too loose such as exokernels, or have no rules such as hybrid kernels. In recent years, to solve these problems, resource management concept frequently appears in industry and academia. Although resource management concept makes resources in OSes orderly, no existing OSes or software systems can modify and extend management rules conveniently and dynamically.&lt;/p&gt; &lt;p&gt;This paper attempts to unify the ServiceMesh architecture and OSes, proposing a resource governance model that places resources such as applications and hardware into the model. Through unified rule governance in the model, the organization of resources is more orderly and scalable. At the same time, by separating rules from resources, rules in the model are also scalable and flexible. Based on the model, we built Rhodes OS that allows users to modify and extend resource management rules by governance center. We implemented Rhodes on x86-64 and evaluated it. Our evaluation results show that applications performance in Rhodes is equivalent to Linux. We believe that OSes based on the resource governance model will pave the way for a brand new direction in the development of operating systems.&lt;/p&gt;
The impact of Spiritual Leadership on Knowledge Hiding Behavior: Professional Commitment as the Underlying Mechanism

Abstract&#x0D; Purpose – The purpose of this study is to investigate the impact of spiritual leadership on knowledge hiding behavior of employees in agriculture research institutes of Khyber Pakhtunkhwa, Pakistan. The study also aims to analyze theoretically and then investigate empirical evidence concerning the mediation pathway (namely, professional commitment) to clarify the significant association amid spiritual leadership and subordinate&amp;#039;s knowledge hiding behavior.&#x0D; Design/methodology- The cross-sectional data using five point lickert scale was used in this survey based study to investigate the given hypotheses. In order to account for the prim effect and any potential for common method bias, data was gathered at two different time points with a gap of four weeks. Smart PLS4 was used to assess a sample of 298 complete and valid responses for hypotheses testing.&#x0D; Findings – The results show that spiritual leadership impacts negatively the employees’ knowledge hiding behavior. Moreover, this relationship is mediated by professional commitment.&#x0D; Originality/value – First, in contrast to the majority of past studies that concentrated on antecedents of knowledge sharing, the present study examined the impact of spiritual leadership on employee’s knowledge hiding behaviors, which are two opposing concepts. Secondly, the study examined empirically, the mediation effect of professional commitment. These three variables have not been studied together previously.
Information System for Determining Student Achievement Using the K-Means Method

Value is an important thing in the world of education and requires a special processing and policy, both in its use, maintenance and recording. Because of the importance of using this value, it is necessary to carry out systematic and effective processing of the values ​​obtained by students. Processing grades consisting of formative grades, assignment grades, and semester grades for each student. To calculate the student's grades, the K-Means method was used to determine students who excel at SMA Swa Bina Karya. The information system for determining outstanding students at Swa Bina Karya High School is still manual. Where the process of recording and calculating student grades is still manual where the recording of each student's grades is recorded in the gradebook owned by each homeroom teacher so that the process of making class ranking reports requires a lot of time and the resulting information is less effective and efficient. To be able to overcome this frequent problem, the authors designed a system for determining student achievement using the K-Means method using Microsoft Visual Basic.Net 2008 and the database used was Sql Server 2008. With the design of this system, the homeroom teacher and school principal can receive more accurate and timely class ranking reports. Besides that, this system also helps admin work much more effectively and efficiently
Descriptive Method in Observation and Its Application

&lt;p&gt;By extending metric space to expression in hash of directed graph, spatiotemporal observation could be described in matrix quantized state. (Working paper, more contents would be added soon)&lt;/p&gt;
Deep Learning-Based Methods for Detecting Generated Fake Faces

&lt;p&gt; Due to the recent rapid development of AI, a variety of techniques and technologies are now employed to alter multimedia. Although we had the technology, it was frequently mishandled or exploited for nefarious or criminal ends rather than for legitimate uses like entertainment and education. Recently, the term "Deep fake" has come to refer to the realistic, high-quality videos and images that have been altered. In a literature review, numerous methods for deep fake detection have been described. It is essential to develop detection techniques that can thwart these kinds of frauds and enhance the study of video and audio forensics. With the use of techniques like Convolutional Neural Networks (CNN), Xception Network, Recurrent Neural Networks (RNN), Long Short Term Memory (LSTM), and others, we demonstrate the numerous Deep fake creation and detection approaches currently being researched. These techniques will act as the cornerstone for the creation of a new deep fake detection system that is more accurate and concise. We also performed a comparison examination of several approaches using a standard methodology. &lt;/p&gt;
Mengembangkan Bahasa Indonesia Anak Usia Dini Melalui Permainan Kotak Ajaib Di Raudhatul Athfal Munzhiroh 3 Kulim Kota Pekanbaru

This research is motivated by the lack of children's Indonesian language development, some children have not been able to recognize simple words and some children are less active in learning. The purpose of this study was to determine the improvement of children's Indonesian language skills by using the magic box game through the CAR research method (Classroom Action Research). This research was conducted in two cycles and each cycle was conducted in two meetings. In order for this classroom action research to be successful without any obstacles that interfere with the smooth running of the research, the researcher arranges the stages that are passed in classroom action research, namely: 1) Action planning/preparation, 2) Action implementation, 3) Observation, and 4) Reflection. The subjects in this study were B1 class students with 16 students, namely in the first semester of the 2022/2023 academic year at RA Munzhiroh 3 Kulim Pekanbaru City. Meanwhile, the object of this research is the use of the magic box game to improve the development of Indonesian in children. The research data were collected through teacher observation techniques and children's activities and documentation. After the data is collected through observation, the data is processed using the percentage formula. The results of this study are an increase in the learning process carried out by the teacher and the children's Indonesian language skills. Observation of children's activities also increased, this can be seen from the initial data to cycle II meeting 2. Initial data 41.27%, Cycle II meeting 2 obtained an average percentage of 85.28%. So that the overall increase in teacher activity obtained an average percentage of 44.01%
Understanding Foundation of Neural Network: Reasoning-based Approach

&lt;p&gt;Background: Currently, neural network model needs understanding on what derives conclusion by execution. Neural network model imitates human intelligence but it has a limitation of cannot explaining what it is to construct the knowledge which it derives.&lt;/p&gt; &lt;p&gt;Object: By inducing universal framework from existing neural network models, common reasoning that regulates the intelligence that derives from the models would be introduced.&lt;/p&gt; &lt;p&gt;Method: Starting from minimizing model's bias, integrative method of understanding how neural network takes place in numerical ordinals and cardinals would be introduced. After that, explanation of intelligence by neural network would be described.&lt;/p&gt; &lt;p&gt;Result: Foundation of artificial neural network intelligence is an optimization with a grid of minimized error from ground truth.&lt;/p&gt;
Face attribute classification with evidential deep learning

We address the problem of uncertainty quantification in the domain of face attribute classification, using Evidential Deep Learning (EDL) framework. The proposed EDL approach leverages the strength of Convolution Neural Networks (CNN), with the objective of representing the uncertainty in the output predictions. Predominantly, the softmax/sigmoid activation functions are applied to map the output logits of the CNN to target class probabilities in multi-class classification problems. By replacing the standard softmax/sigmoid output of a CNN with the parameters of the evidential distribution, EDL learns to represent the uncertainty in its predictions. The proposed approach is evaluated on CelebA and LFWA datasets. The quantitative and qualitative analysis demonstrate the suitability and strength of EDL to estimate the uncertainty in the output predictions without hindering the accuracy of CNN-based models.
bgGLUE: A Bulgarian General Language Understanding Evaluation Benchmark

We present bgGLUE(Bulgarian General Language Understanding Evaluation), a benchmark for evaluating language models on Natural Language Understanding (NLU) tasks in Bulgarian. Our benchmark includes NLU tasks targeting a variety of NLP problems (e.g., natural language inference, fact-checking, named entity recognition, sentiment analysis, question answering, etc.) and machine learning tasks (sequence labeling, document-level classification, and regression). We run the first systematic evaluation of pre-trained language models for Bulgarian, comparing and contrasting results across the nine tasks in the benchmark. The evaluation results show strong performance on sequence labeling tasks, but there is a lot of room for improvement for tasks that require more complex reasoning. We make bgGLUE publicly available together with the fine-tuning and the evaluation code, as well as a public leaderboard at https://bgglue.github.io/, and we hope that it will enable further advancements in developing NLU models for Bulgarian.
5IDER: Unified Query Rewriting for Steering, Intent Carryover, Disfluencies, Entity Carryover and Repair

Providing voice assistants the ability to navigate multi-turn conversations is a challenging problem. Handling multi-turn interactions requires the system to understand various conversational use-cases, such as steering, intent carryover, disfluencies, entity carryover, and repair. The complexity of this problem is compounded by the fact that these use-cases mix with each other, often appearing simultaneously in natural language. This work proposes a non-autoregressive query rewriting architecture that can handle not only the five aforementioned tasks, but also complex compositions of these use-cases. We show that our proposed model has competitive single task performance compared to the baseline approach, and even outperforms a fine-tuned T5 model in use-case compositions, despite being 15 times smaller in parameters and 25 times faster in latency.
Minat Baca Mahasiswa PBSI 2021 Universitas Riau

Reading for students is not only an obligation but also a necessity. Through reading a vast ocean of knowledge can be explored. This study aims to analyze the reading interest of PBSI class 2021 B students, FKIP, Riau University. This study uses a mixed method. The research subjects were 10 PBSI 2021B students who were selected. Data is collected by filling out a questionnaire. Data were analyzed using descriptive statistics. The results showed that students' reading interest was in the moderate category with indicators of high reading intensity and moderate interest in visiting the library or reading corner.
What are the discourses concerning misinformation about vaping on Twitter?: A systematic content analysis (Preprint)

<sec> <title>BACKGROUND</title> While there has been substantial analysis of social media content deemed to spread misinformation about electronic nicotine delivery systems use, the strategic use of misinformation accusations to undermine opposing views has received limited attention. </sec> <sec> <title>OBJECTIVE</title> This study aims to fill this gap by analyzing how social media users discuss the topic of misinformation related to electronic nicotine delivery systems, notably vaping products. Additionally, this study identifies and analyzes the actors commonly blamed for spreading such misinformation and how these claims support both the provaping and antivaping narratives. </sec> <sec> <title>METHODS</title> Using Twitter’s (subsequently rebranded as X) academic application programming interface, we collected tweets referencing #vape and #vaping and keywords associated with fake news and misinformation. This study uses systematic content analysis to analyze the tweets and identify common themes and actors who discuss or possibly spread misinformation. </sec> <sec> <title>RESULTS</title> This study found that provape users dominate the platform regarding discussions about misinformation about vaping, with provaping tweets being more frequent and having higher overall user engagement. The most common narrative for provape tweets surrounds the conversation of vaping being perceived as safe. On the other hand, the most common topic from the antivape narrative is that vaping is indeed harmful. This study also points to a general distrust in authority figures, with news outlets, public health authorities, and political actors regularly accused of spreading misinformation, with both placing blame. However, specific actors differ depending on their positionalities. The vast number of accusations from provaping advocates is found to shape what is considered misinformation and works to silence other narratives. Additionally, allegations against reliable and proven sources, such as public health authorities, work to discredit assessments about the health impacts, which is detrimental to public health overall for both provaping and antivaping advocates. </sec> <sec> <title>CONCLUSIONS</title> We conclude that the spread of misinformation and the accusations of misinformation dissemination using terms such as “fact check,” “misinformation,” “fake news,” and “disinformation” have become weaponized and co-opted by provaping actors to delegitimize criticisms about vaping and to increase confusion about the potential health risks. The study discusses the mixed types of impact of vaping on public health for both smokers and nonsmokers. Additionally, we discuss the implications for effective health education and communication about vaping and how misinformation claims can affect evidence-based discourse on Twitter as well as informed vaping decisions. </sec>
Werner state tomography based on multiple noises and fiber attenuation

Abstract In this paper, we establish a new quantum state tomography model that fits the real environment very well. In our model, the number of photons emitted by the photon source is a random number of Gaussian distribution. The emitted photons are attenuated by a fiber, resulting in a binomial distribution of photons arriving at the detector. In the process of measurement, we impose Poisson noise, which makes the number of photons measured each time assume Poisson distribution. The quantum states are reconstructed from photon counts obtained for symmetric informationally complete positive operator-valued measures, and consider the influence of noise on the measurement operators. We study the quantum tomography efficiency of any two-qubit Werner state in our model. We obtained the relationship between the tomographic efficiency and multiple variables of the model through numerical simulation. PACS numbers: 03.67.Mn, 03.65.Ud, 03.67.-a
PENAMBAHAN DALAM EKRANISASI NOVEL ANTARES KARYA RWEINDA KE WEB SERIES

This study aims to describe the form of ecranization of the additional aspects of the Antares novel to the Antares web series. This research use desciptive qualitative approach. The data in this study is the addition of plot, character, and setting in the Antares web series from the Antares novel. The data sources used are the novel Antares by Rweinda published by Loveable in 2020 and the web series Antares, produced by Manoj Punjabi and directed by Rizal Mantovani. Data collection techniques are through reading, viewing documentation, and taking notes. The data analysis technique used is comparative analysis. The results of this study obtained the form of adding plots, adding characters, and adding backgrounds which were shown through scenes in the Antares web series. There are thirty additional scenes that can be classified into thirteen scenes that show the addition of the plot (events), six scenes that show the addition of characters, and eleven scenes that show the addition of the setting. Additions are needed for the sake of a filmic angle and are still relevant to the overall content of the story.
KEMAMPUAN MENULIS TEKS PERSUASI MELALUI MEDIA GAMBAR

This study aims to describe the ability to write persuasive texts for class VIII junior high school students through the use of image media. The instrument used in this study was a performance test of writing persuasive text. The assessment taken in writing the text is based on the structure and linguistic rules contained in the persuasion text, namely the existence of opinions or arguments, facts, and invitation sentences. Then students write persuasive texts using image media. This research is a type of descriptive research with a quantitative approach. The research data was obtained from the students' ability to write persuasive texts. The research subjects were students of class VIIIF as many as 30 students. Analysis of the data used in this study is the result of student work.The results showed that the ability to write persuasive texts using image media in every aspect got a score above the average. In the aspect of writing arguments, the score is 84, the ability to write facts is 89, and the value of the ability to write invitations is 85. The conclusions of this study indicate that the ability to write persuasive texts for class VIIIF students is in the capable category with an average score of 86. of the overall results of the assessed aspects.
An Investigation of the User-avatar Relationships in VRchat - Evidence from Interview Research

VRchat is a popular virtual social platform that allows users to interact with avatars as social images. Avatars have been widely used, and still has application prospects, such as the metauniverse. While recent games and other special environments may have psychological implications for users, VR chat, as a social platform, enables users to express themselves more freely. The purpose of this study is to examine and sort out how different users relate to their avatars. Using semi-structured interviews, the study aims to investigate and sort out the relationship between the users and their avatars, and what meaning does the act of dressing up an avatar give to both the avatar and the user. According to the research results, avatar dressing is not only a form of self-expression, but also has a significant impact on users' psychology and behavior. This influence will continue to expand and penetrate into real life.
Post-Truth Era: Gender-Related Reversal Events Taking the Case of Ying Liang and Guanjun Luo as an Example

Given the high transmission efficiency and the vast loads of users on social media platforms, Weibo in China is used by victims to reveal immoral or illegal behaviors to the public. In the post-truth era, an individual's subjectivity on the Internet outweighs objective truths in exerting significant impact. Taking the event of 'Ying Liang and Guanjun Luo' as an example, this study analyzes how digital culture constructed and reinforced public opinion direction by citing statistics on https://ef.zhiweidata.com and several representative comments on Weibo. It can be concluded that the priming effect influences how people evaluate this case and the development of public opinions. Furthermore, this reversal event eventually caused a decline in public trust among netizens, created more obstacles for other female victims who genuinely needed help, and induced a discredit towards feminists radically participating in supporting the female victim.
Emoji Culture on the WeChat Platform

Emojis are being used more and more frequently in social media communication, and they are appearing in more and more styles in contemporary society. Emojis transcend other visual and graphic languages and are popular across the boundaries of languages, races, cultures, etc. However, the reason for the increasing use of Emojis has not been given much attention. This study attempts to analyze and investigate the reasons why Emojis are actively used on social media. This study refers to research materials in psychology and communication and focuses on WeChat, the most frequently used social media platform in China. This study argues that Emojis have become a way for people to express their emotions quickly and accurately. Beyond textual expression, Emojis can arouse people's empathy. The use of Emojis makes emotions and feelings visible, which plays a role in indenting social distance.