Reviewerly/exHarmony huggingface dataset:
THE CORRELATION BETWEEN PARTS OF SPEECH MASTERY AND WRITING ACHIEVEMENT

This research was done because there were some problems in students’ writing, especially in parts of speech mastery. The parts of speech as a basic of grammar seem to be necessary in the process of language learning. If the students understand this, the students may construct sentence easily and the students may understand the differences between the words. Relate to this condition, the researchers wanted to investigate the correlation between parts of speech mastery and writing achievement at 11th students of MAN 4 AGAM in Academic Years 2020/2021. The design of this research was correlation research. The population of this research was all students at XI Grade of MAN 4 AGAM in academic years 2020/2021 which consist of 4 classes. The sample was 39 students taken by purposive sampling technique. The instruments of this research were test and documentation for collecting writing score of the students. To analyze the data, the researchers used the SPSS version 20 for windows. In analyzing the data, the researchers used Pearson Product Moment Correlation Coefficient to search and to find the correlation between two variables. The researchers found that the coefficient of correlation between students’ mastery in parts of speech and writing achievement at the 11th students of MAN 4 AGAM was 0,376. The correlation was positive and significant. It means that Ho was rejected and Ha was accepted. Thus, there was positive correlation between students’ parts of speech mastery and writing achievement at the 11th grade students of MAN 4 AGAM.
STRATEGIES ON TEACHING READING COMPREHENSION FOR THE JUNIOR HIGH SCHOOL STUDENTS DURING THE COVID-19 PANDEMIC

English teacher applies certain strategies in teaching reading comprehension to achieve the objective of learning. Covid-19 pandemic has changed the ways of teaching from face to face to online learning. This study is intended to investigate strategies the teacher used, to know the problems faced by the teacher in implementing strategies, and to know how the teacher solves the problems in implementing strategies on teaching reading comprehension during the covid19 pandemic at junior high school. This descriptive qualitative research was conducted at SMP 2 Manyaran, Central Java. The subject is an English teacher. Observation and interview were applied to collect the data. Miles and Huberman’s interactive model is used to analyze the data. The results of this research show that the teacher applies five strategies to teach reading comprehension during the pandemic covid-19 namely, strategy of identifying the purpose in reading, skimming the text for main ideas, scanning the text for specific information, analyzing vocabulary, and implementing L-R-D (Listen-Read-Discuss) strategy. The teacher encounters several problems in implementing the strategies because the students fail to identify the purpose of the text, face difficulty to skim the text and analyzing vocabulary. To overcome the problems, the teacher makes several efforts such as giving more exercises and texts and conducting discussions. The online learning during the covid-19 pandemic challenges the English teacher to navigate the students to find the sources of learning using the technologies.
PENERAPAN MODEL PEMBELAJARAN INKUIRI TERHADAP PENINGKATAN MINAT BACA SISWA KELAS VII A DALAM MATA PELAJARAN AKIDAH AKHLAK DI MTS CINA

This study aims to determine the effect of the inquiry learning model on students' reading interest. Reading interest referred to in this study, namely the level of achievement of students in understanding the material as measured through observations made by researchers. This type of research is classroom action research, where the researcher acts as a teacher and observer. This research design is one part of the cooperative learning model. This research was conducted in the odd semester of the 2021/2022 academic year, namely in November at MTs China. The population consists of 30 students and the research sample is 11 students of class VII A MTs China, the object of research is students' reading interest. Data collection techniques using tests, observations, and questionnaires. The data analysis technique used is descriptive data analysis. The results showed a significant increase in students' reading interest, it can be seen from the increase experienced by the three assessment indicators. Namely: the feeling of pleasure of students increased from 5 students to 11 students, interest increased from 4 students to 9 students, and finally the attention of students increased from 9 students to 11 students.Keywords: interest in learning, inquiry learning model
PENGARUH KOMPETENSI PEDAGOGIK GURU TERHADAP PENINGKATAN MOTIVASI BELAJAR SISWA PADA PEMBELAJARAN ONLINE DI MA AS ADIYAH MATTIROWALIE KABUPATEN BONE

This study aims to determine the effect of teacher pedagogic competence on the improvement of students' learning motivation in online learning and the motivation that most influences the online learning process. This research was conducted in Madrasah Aliyah As Adiyah Mattirowalie, Bone Regency. The population in this study were all stakeholders in the MA As Adiyah Mattirowalie educational institution, Bone Regency. The sampling technique used in this study is Nonprobability Sampling by selecting 10 samples needed in the study. Data were collected using questionnaire, observation and documentation instruments. Data were analyzed descriptively. The results showed that there was a positive influence of teacher pedagogic competence (variable X) on increasing students' learning motivation in online learning (variable Y) with a relationship between the two variables of 0.57.Keywords: teacher pedagogic, learning motivation
When Transformer models are more compositional than humans: The case of the depth charge illusion

State-of-the-art Transformer-based language models like GPT-3 are very good at generating syntactically well-formed and semantically plausible text. However, it is unclear to what extent these models encode the compositional rules of human language and to what extent their impressive performance is due to the use of relatively shallow heuristics, which have also been argued to be a factor in human language processing. One example is the so-called depth charge illusion, which occurs when a semantically complex, incongruous sentence like "No head injury is too trivial to be ignored" is assigned a plausible but not compositionally licensed meaning ("Don't ignore head injuries, even if they appear to be trivial"). I present an experiment that investigated how depth charge sentences are processed by Transformer models, which are free of many human performance bottlenecks. The results are mixed: Transformers do show evidence of non-compositionality in depth charge contexts, but also appear to be more compositional than humans in some respects.
Perceived Factors Affecting Academic Performance of Pantawid Pamilyang Pilipino Program (4Ps) Beneficiaries of Apayao State College

The study aimed to determine the perceived factors affecting the academic performance of Pantawid Pamilyang Pilipino Program (4Ps) Beneficiaries of Apayao State College. Significantly, perceived factors such as personal, family, school, teacher, community and multi-media sometimes affect the academic performance of the 4Ps respondents except for peer factors. Furthermore, it has also been a result of this study that there is a significant relationship between the profile variables and the academic performance of the respondents except for age. However, the level of the academic performance of the student is found as satisfactory so it has to be improved to attain higher grades in all the subject areas in school. It is acknowledged further, that the academic performance is a multi-factorial variable; hence other problems that affect their academic performance should be dealt with in order to look into other variables affecting academic performance.
in Chatbot-based Information Service using RASA Open-SourceFrameworkin Prambanan Temple Tourism Object

The pandemic has caused a shift in the tourism industry's drive towards comprehensive digitization. This approach is used to prevent the spread of the Covid-19 virus. The impact of Pemberlakuan Pembatasan Kegiatan Masyarakat (PPKM) limiting the mobility of tourists who will vacation in Indonesia causes losses and foreign exchange earnings of the state in the tourism industry sector of 20.7 billion. So, to survive in the current situation, industry players must be able to adapt and rise by providing more effective innovations. This study aims to develop a Question Answering System or a digital question and answer system using a chatbot (ChatterBot). The chatbot is used as an information service provider that can make it easier for tourists who are looking for information about tourist attractions. Chatbot-based information service systems can work 24 hours or all day, reducing the intensity of direct physical contact with officers and saving operational costs. The chatbot implementation is built on the Machine Learning Framework using RASA Open Source with the Python programming language. The knowledge base of the chatbot system is trained based on the FAQ (Frequently Asking Question) dataset with a case study of the Prambanan Temple tourist attraction as a sample of Indonesian tourism. The results of the evaluation and system performance based on data testing obtained the level of model accuracy is 0.91. Furthermore, the weighted average value in the Confusion Matrix produces a precision of 0.97, a recall of 0.94, and an F1-score of 0.95. The training and testing model processes locally using the Visual Studio Code software.&#x0D;
News Text Learning With Tribunnews Instagram Account for 8th Grade Students

Online learning frequently employs tedious media, including news text learning. This study aims to describe the innovative use of learning media in class VIII B learning of news texts using the Tribunnews Instagram account at SMP 17 Agustus – 1 Muncar. This research is qualitative because the data are presented in the form of words. The method of research employed is descriptive research. The subjects of this study were eighth-grade B SMP 17 Agustus-1 Muncar students. With Instagram Tribunnews, the objective is to learn news text. Documentation is the technique used for data collection. The data processing technique used is a qualitative descriptive technique. The findings of this study indicate that learning with Instagram Tribunnews video media is superior and more engaging for students than learning with news sample text media alone. This can be seen in the improvement of student interactions over time. There were only students who did not have access to a reliable network, and there were students who were late for Zoom. However, the teacher has provided a solution for this.
Roulette: A Diverse Family of Feasible Fault Attacks on Masked Kyber

At Indocrypt 2021, Hermelink, Pessl, and Pöppelmann presented a fault attack against Kyber in which a system of linear inequalities over the private key is generated and solved. The attack requires a laser and is, understandably, demonstrated with simulations—not actual equipment. We facilitate and diversify the attack in four ways, thereby admitting cheaper and more forgiving fault-injection setups. Firstly, the attack surface is enlarged: originally, the two input operands of the ciphertext comparison are covered, and we additionally cover re-encryption modules such as binomial sampling and butterflies in the last layer of the inverse numbertheoretic transform (INTT). This extra surface also allows an attacker to bypass the custom countermeasure that was proposed in the Indocrypt paper. Secondly, the fault model is relaxed: originally, precise bit flips are required, and we additionally support set-to-0 faults, random faults, arbitrary bit flips, and instruction skips. Thirdly, masking and blinding methods that randomize intermediate variables kindly help our attack, whereas the IndoCrypt attack is like most other fault attacks either hindered or unaltered by countermeasures against passive side-channel analysis (SCA). Randomization helps because we randomly fault intermediate prime-field elements until a desired set of values is hit. If these prime-field elements are represented on a circle, which is a common visualization, our attack is analogous to spinning a roulette wheel until the ball lands in a desired set of pockets. Hence, the nickname. Fourthly, we accelerate and improve the error tolerance of solving the system of linear inequalities: run times of roughly 100 minutes are reduced to roughly one minute, and inequality error rates of roughly 1% are relaxed to roughly 25%. Benefiting from the four advances above, we use a reasonably priced ChipWhisperer® board to break a masked implementation of Kyber running on an ARM Cortex-M4 through clock glitching.
BLOCK CHAIN TECHNOLOGY AND ITS APPLICATIONS: A REVIEW

The Bit coin's underlying block chain has recently drawn a lot of attention.Randomized transactions are made possible via block chain, which acts as a digital ledger.Numerous industries, including financial services, reputation management, and the Internet of Things (IoT), are seeing the emergence of block chain-based solutions.But there are still a lot of difficulties with block chain technology to be solved, including scalability and security issues.This essay provides a thorough introduction to block chain technology.Prior to comparing several common consensus methods used in various block chains, we first present an introduction of the architecture of the block chain.Also briefly addressed are technological difficulties and recent advancements.We also outline potential Block Chain tendencies going forward.
Breaking Masked Implementations of the Clyde-Cipher by Means of Side-Channel Analysis

In this paper we present our solution to the CHES Challenge 2020, the task of which it was to break masked hardware respective software implementations of the lightweight cipher Clyde by means of side-channel analysis. We target the secret cipher state after processing of the first S-box layer. Using the provided trace data we obtain a strongly biased posterior distribution for the secret-shared cipher state at the targeted point; this enables us to see exploitable biases even before the secret sharing based masking. These biases on the unshared state can be evaluated one S-box at a time and combined across traces, which enables us to recover likely key hypotheses S-box by S-box.In order to see the shared cipher state, we employ a deep neural network similar to the one used by Gohr, Jacob and Schindler to solve the CHES 2018 AES challenge. We modify their architecture to predict the exact bit sequence of the secret-shared cipher state. We find that convergence of training on this task is unsatisfying with the standard encoding of the shared cipher state and therefore introduce a different encoding of the prediction target, which we call the scattershot encoding. In order to further investigate how exactly the scattershot encoding helps to solve the task at hand, we construct a simple synthetic task where convergence problems very similar to those we observed in our side-channel task appear with the naive target data encoding but disappear with the scattershot encoding.We complete our analysis by showing results that we obtained with a “classical” method (as opposed to an AI-based method), namely the stochastic approach, thatwe generalize for this purpose first to the setting of shared keys. We show that the neural network draws on a much broader set of features, which may partially explain why the neural-network based approach massively outperforms the stochastic approach. On the other hand, the stochastic approach provides insights into properties of the implementation, in particular the observation that the S-boxes behave very different regarding the easiness respective hardness of their prediction.
Toward a transdisciplinary educational method Draft-visualization: a didactic methodology

The predominance of an epistemological paradigm that remains linked to the linear, cumulative, and reductionist form of science highlights the delay with which transdisciplinarity spreads in the educational world.&#x0D; The debate on the need for a global education reform fails to materialize, which, despite its long-term existence, views the same operators/teachers as only partially aware of the need for change; however, they are never sufficiently involved to give force to this change. The system remains paralyzed due to a dead end for which students are paying.&#x0D; Therefore, this study proposes a teaching methodology (Draft-Visualization©®). If adopted as a collegiate tool, it is capable of allowing the students to independently work in a transdisciplinary sense regardless of the initial degree of involvement of teachers. Finally, the general operating scheme of a method is proposed (Vetas-Educando©®) as a result of direct experience, which is inspired by the theory of complexity and organized in the principles of transdisciplinarity. The study believes that each educational reality must be capable of conducting its work without renouncing the rigor of a method that enables it to verify and measure results. In this manner, a classic error of the school world is avoided, that is, its self-referentiality.
THE USE OF CODE-MIXING BY SOUTH JAKARTAN YOUTH IN TWITTER

Abstract&#x0D; Youth and language are two inseparable things. In communication, youth usually have their way of communication. In form of written communication, youth mostly use code-mixing, especially in social media. Based on this phenomenon, this research attempts to analyze 20 posts by South Jakartan Youth on Twitter from September to October 2018 that contained code-mixing. The writer applied qualitative research and the theory of code-mixing by Mckay and Nancy. In those posts on Twitter by South Jakartan youth, the writer found three forms of codemixing; insertions, phrases insertions, and sentence insertions.
SA-UBA: Automatically Privileged User Behavior Auditing for Cloud Platforms with Securely Accounts Management

Cloud platforms allow administrators or management applications with privileged accounts to remotely perform privileged operations for specific tasks, such as deleting virtual hosts. When privileged accounts are leaked and conduct dangerous privileged operations, severe security problems will appear on cloud platforms. To solve these problems, researchers focus on auditing privileged users’ behaviors. However, it is difficult to automatically audit fine-grained privileged behaviors for graphical operating systems. Moreover, it is hard to prevent users from bypassing the audit system or to prevent hackers from attacking audit system. In this paper, we propose a Secure and Automatic Behavior Audit system named SA-UBA. It provides advanced deep learning models to automatically achieve fine-grained user behavior audits for graphical operating systems. Furthermore, it adopts cryptography-based account storage and sharing methods to securely manage privileged accounts. In particular, privileged accounts cannot be leaked even if SA-UBA is compromised by attackers. We built a threat model of a cloud platform to evaluate the security of the SA-UBA and conduct extensive experiments with SA-UBA in real scenarios. The results show SA-UBA introduces a small overhead on securely managing privileged accounts and accurately recognizes fine-grained user behaviors.
Digital media ‘changes the game’: investigating digital affordances impacts on sex crime and policing in the 21st century

With society becoming increasingly digital, new opportunities are afforded to potential offenders to weaponize digital features and affordances to carry out their crimes. As a result, concerns persist over online forms of crime, particularly cybercrime involving sexual exploitation, and what can be done about them. Drawing on interview and focus group data collected from 70 sex crime investigators from police service organizations across Canada, we uncover police perspectives on online sex-based crime. We demonstrate that police perceive online crimes to not necessarily be new forms of crime, but rather altered by digital media in terms of methods and weapons being used. We focus on uncovering the features and affordances police identify as contributing to the increase in crime itself as well as the creation of greater opportunities for crime to occur. In addition, resulting from crime shifting into digital spaces, we uncover the challenges digital media has presented for police in terms of how they handle, respond to, and investigate online crime. We discuss these challenges and their impact on policing and provide solutions for combatting them moving forward. Overall, this article contributes to the current body of literature investigating online crime and policing in the digital age by drawing on the theoretical framework of affordances and offering police perspectives on online sex-based crimes.
Drivers and Barriers for Using Blockchain Technology to Create a Global Fact-Checking Database

A core concept within journalism is the demand for correctness and the ability to double-check news and its sources (Kovach & Rosenstiel, 2014). In this paper, we reflect on the development of a prototype to study the possible use of blockchain technology to create a global secure database of fact-checks that is open to the public. The prototype utilized Hyperledger fabric to create a permissioned blockchain that stores fact-checks created by its users. Through automated processes using smart contracts (chain code applications), we aimed to create a solution that would improve the reliability of fact-checking and keep track of each fact-checking process for digital content, including pictures and videos. Our conclusion is that it is indeed possible to create a blockchain-based system that allows the establishment of a network of fact-checkers that could collectively build and maintain a globally accessible fact-checking database. However, based on technical developments and the evaluation performed by the professional fact-checkers and data journalists in our study, we conclude that the cost, complexity, and rapid technological changes required in this domain indicate that blockchain technology is not yet ready to be directly applied to fact-checking processes in a real-world scenario.